The next day every family moved to thekashim, where, by shutting out the air and huddling closetogether, the people could keep warm without oil. There were forward-looking people who realized thattimes had changed, and they spoke in favor. She had heard the story from Orin ahalf-dozen times today, but it did not lose interest withrepetition. Doc done all he could to improve Paul’s mind and he toldme once that he really thought the boy was getting better,that they was times when he was as bright and sensible asanybody else. Curated health and wellness podcasts — no platform hopping required. If you are a Mayo Clinic patient, we will only use your protected health information as outlined in our Notice of Privacy Practices. We use the data you provide to deliver you the content you requested. I seen a lot of itup an’ down the river in the old days—it don’t never leadto no good end. It ain’t right, some of it.Now here’s us—Will all time runnin’ after them girls intown—an’ drinkin’. Henry’srocker kept time to it. He rocked violently,his fat, helpless hands around the knobs of the armchair.Pg 11 “It’ll be a long time afore I’m right agin! This means that you’ll need less quantity of food to fill the nutritional gaps in the body. Since real food is a nutrient powerhouse, every calorie of real food counts towards something. Your body needs nutrients for energy, growth, and repair. You’ll find more nutrients in a single serving of any real food item than you will in any of its processed counterparts. (Several more play supporting roles in fat storage and weight loss.) Research indicates that people who exercise consistently are more likely to sustain their weight loss. Some people burn calories more quickly because they’ve inherited the ability to build muscle mass from their parents (more energy is needed to build and maintain muscle mass). Metabolism is the body’s workhorse, the process that mixes calories with oxygen to create and release energy. In her young days she had been too muchoccupied with personal affairs to give much of her energyto travel. I guess herun pretty wild durin’ the time he was on the road for themCarterville people, and besides that, he’d had a couple littleaffairs of the heart right here in town. Jim Kendall used to call him cuckoo;that’s a name Jim had for anybody that was off their head,only he called people’s head their bean. - A Weight Loss Story to Embolden Your Journey with Dave Wegener What we eat, how much we move and the inner workings of our minds all contribute to how we gain and lose weight. Or they may recommend anti-obesity medications or bariatric surgery in addition to a healthy diet and exercise program. It’s your body trying to hold on to weight by slowing down your metabolism,” Dr. Creel explains. Often, you can see results from your weight loss efforts quickly. Beyond categorical stance labels, we leverage a long-established affective science framework to model stance along real-valued dimensions of valence (negative-positive) and arousal (calm-active). However, real-world network data often suffer from noise, biases, and missing data in edge weights, which undermine the reliability of downstream network analyses. Lastly, we conduct a cost-performance analysis and find that Gemini and Claude models with monitoring techniques that involve information filtering occupy much of the Pareto frontier. Our results suggest that grokking is not an inherent failure mode of deep learning, but rather a consequence of specific training conditions, and thus does not require fundamental changes to the model architecture or learning algorithm to avoid. Reinforcement learning provides a principled framework for optimizing long-term user satisfaction by modeling sequential decision-making processes. A commercial weight loss program offering clinically impactful behavioral support provided weight data for unrestricted use to Tufts University (Instinct Health Science, , accessed on 11 April 2024). Sequential polynomial regression models were employed to classify participants into distinct weight trajectory patterns based on key model parameters. In this study, we developed an algorithm aimed at classifying weight change trajectories and examined its ability to predict long-term weight loss based on weight early change. A randomized trial of a low-carbohydrate diet for obesity.She felt his breath on her face, and closed her unseeingeyes.One third of Americans are now obese (BMI ≥30),1 and 50%–70% are trying to lose weight.2–4 National guidelines recommend loss of 10% of body weight for obese adults to improve overall health.5 However, studies demonstrate that even modest weight loss of 5% leads to health benefits.6,7Sometimes, despite our best efforts, our goals need to change.Because it is only FDA-approved for short-term use, many doctors specializing in weight management will continue to prescribe it “off-label” as a long-term strategy, if the person is doing well on the drug, as long as that person is willing to accept the risks.These results demonstrate that autoregressive models provide an effective framework for KG generation, with practical applications in knowledge base completion and query answering.The women wore diaphanous slips, all beadsand fringe, which did not cover a row of pink and greenlegs, two of which were crooked and four very fat. Mindless Eating: When Habits Take the Wheel An ongoing RCT may improve the quality of evidence to evaluate the role of TOPS in weight management, particularly in low-resource settings. In summary, current evidence regarding weight-loss efficacy and safety with the use of TOPS is limited. Within the analyzed study population, 94%, 41% and 15% of participants consecutively renewed their memberships at 1, 2 and 3 years, respectively. Achieve higher ketone levels During training, we perform iterative policy improvement by fitting a state value function to an upper-expectile of the Q-function, and distill the in-context value functions into policy extraction using advantage-weighted regression. In this paper, we introduce a new benchmark for continual learning in anomaly detection, aimed at better reflecting real-world deployment scenarios. Our work serves as both a diagnostic study and practical guide for safety realignment in telecom-tuned LLMs, underscoring the need for safety-aware instruction and fine-tuning in the telecom domain. In this paper, we propose FLAT-LLM, a fast and accurate, training-free structural compression method based on fine-grained low-rank transformations in the activation space. In this paper, we introduce ForeHOI, a novel feed-forward model that directly reconstructs 3D object geometry from monocular hand-object interaction videos within one minute of inference time, eliminating the need for any pre-processing steps. However, these models are computationally complex to evaluate, posing a challenge for popular RL approaches that have been successfully used with simulators to solve complex locomotion tasks but yet struggle with manipulation. World models offer a promising avenue for more faithfully capturing complex dynamics, including contacts and non-rigidity, as well as complex sensory information, such as visual perception, in situations where standard simulators struggle. We operationalize this assumption with an Aligned Sparse Autoencoder (SAE) that encourages energy consistency during training while preserving reconstruction. Vision-language models (VLMs) align images and text with remarkable success, yet the geometry of their shared embedding space remains poorly understood. What role does exercise play in losing body fat, and which types are most effective? Our key insight is to distill the feature representations from visual foundation models such as DINOv2 into a thermal encoder using thermal data from these multiple environments. To address these challenges, we built Personagram, an interactive system powered by multimodal large language models (MLLMs) that helps designers explore detailed census-based personas, extract product features inferred from persona attributes, and recombine them for specific customer segments. Direct Preference Optimization (DPO) has emerged as a predominant alignment method for diffusion models, facilitating off-policy training without explicit reward modeling. Also, because the saturated fat content is high, coupled with limited amounts of fruits, vegetables and whole grains, it is not optimal for health.” … Because the saturated fat content is high, coupled with limited amounts of fruits, vegetables, and whole grains, it is not optimal for health.” Although entering a state of ketosis appears to deliver fast results, the first few pounds that you lose will most likely be water weight. When you stop eating carbohydrates—which do contain essential nutrients—altogether it can be enough of a shock to the body to cause an immune system reaction. The study also reported a decrease in diastolic blood pressure and triglyceride levels for keto dieters. Among the existing acceleration methods, Feature Caching is popular due to its training-free property and considerable speedup performance, but it inevitably faces semantic and detail drop with further compression. While diffusion models have achieved great success in the field of video generation, this progress is accompanied by a rapidly escalating computational burden. The framework also gracefully handles non-transitive preferences (cycles induced by real-world oracles) by collapsing them into equivalence classes that yield principled tiered rankings. Existing training paradigms prioritize linguistic fluency over structured clinical logic and result in a fundamental misalignment with professional diagnostic cognition. We present PiEvo, a principle-evolvable framework that treats scientific discovery as Bayesian optimization over an expanding principle space. Large Language Model (LLM)-based scientific agents have accelerated scientific discovery, yet they often suffer from significant inefficiencies due to adherence to fixed initial priors. On the CORE 225K MCQs dataset, accuracy further drops to approximately 2%, highlighting substantial challenges in domain-specific semantic reasoning. ECO introduces dedicated constraints for energy consumption and reference motion, enforced by the Lagrangian method, to achieve stable, symmetric, and energy-efficient walking for humanoid robots. While the evidence is weak that either of these interventions will help with weight loss, there is likely little downside and you may see a small benefit. However, the group that took the multivitamin lost more weight – an average of 3.6 kg (8 pounds) more – and improved several health markers. The study went on for six months.Unsurprisingly, the results showed that nothing had happened to the weight of the women receiving calcium or the placebo. On the other hand, reliable access to vitamins and minerals could perhaps mean decreased hunger levels and decreased cravings, thereby promoting weight loss.The above is speculation without strong supporting evidence. Summary of selected studies I thought of a future child's needs that really inspired me to get healthier." Here’s a look back at the star's health journey, including strategies she used to reach her tactics for getting to her goal weight and more on where she is now. Rebel also shared in March that she used Ozempic, the diabetes drug that’s commonly used off-label for weight loss, to help maintain her weight. I’d been on diets and I’ve been really good about exercising pretty much my entire life,” Rebel told Us Weekly. Cutting calories from food and drink and burning more calories by moving more are ways to do that. We show that this noise-driven pre-training significantly improves convergence speed in subsequent tasks, without requiring additional data or changes to the network architecture. Instead of directly training the network from random weights, we first pre-train it to fit random noise, which leads to a structured and non-random parameter configuration. We propose a simple, yet effective, initialization strategy based on self-supervised pre-training using random noise as the target. Training a 0.2B-parameter model from scratch on GSM8K, our method with 30 rethinking iterations surpasses baselines with 10 to 15 times more parameters, including a 3B counterpart. Look, it’s fine to give in to temptation—in fact most dietitians will tell you that it’s a healthful way to manage a good diet long-term. Fat is often viewed as a dietary demon, but studies show that the nutrient doesn’t directly inflate your belly—too many calories do. If you cut down on fat in your diet, your gallbladder doesn’t contract as frequently, allowing bile to become concentrated in the organ, which leads to the formation of stones, she explains. Be aware that weight loss may leave your partner feeling neglected, guilty, or jealous. Teaming up with your partner to lose weight can increase your chances of success. Rebel went on to say that she had tried "fads and diets" before, but wanted to take a "holistic approach this time." And that meant focusing on her mental health, too. “I think to many people I'm a beacon of body positivity because I see people who are considered medically obese if you look at their weight, but I think they are absolutely beautiful,” she said. "They said that walking was actually the best way for me to lose unnecessary body fat." Rebel declared 2020 her “year of health," telling fans she'd be prioritizing exercise and aiming to get down to her goal weight of 165 pounds. To achieve that, she's been relying on a combination of exercise and a healthy diet. As tempting as it may be, don’t fall for one of these magical diet scams. Clinical experience suggests that someone may do great at first with a ketogenic diet, but then may continue long-term success with a moderate carb higher satiety diet. Losing a lot of weight long term and keeping it off will likely not happen unless you change your habits forever. We additionally included the variables age and sex in the model and compared the change of coefficient among other predictor variables.People lose weight, by drinking nothing but beer—I don’t recommend that one though.At Diet Doctor, we care about helping people who want to lose weight.In addition, evaluations on real-world material design tasks show that it achieves superior generalization performance.Doc done all he could to improve Paul’s mind and he toldme once that he really thought the boy was getting better,that they was times when he was as bright and sensible asanybody else.Experiments on HotpotQA (sentence features) and a hand-labeled MMLU subset (word features) show that RoPE-LIME produces more informative attributions than leave-one-out sampling and improves over gSMILE while substantially reducing closed-model API calls.For decades, cutting fat from the diet was encouraged by many weight loss programs but, in the end, there was no evidence of long-term success with this approach. By that time the hardest part of the wind, itseemed, had passed. By the time I was there Martha had all thekids out in the yard. Well, you can tell the world that I made fast time gettingto the house. Well, I went on back in the barn and began shuckingsome corn to shell so as I could take it to town the nextday, Saturday, and get it ground into meal. But interestingly enough, the roots of people’s desire to lose weight predate any scientific “evidence” connecting weight and health. Overall, little proof exists that any dietary supplement can help with healthy, long-term weight loss. Exercise for your health, but look at your diet to address weight loss. The result was not a quick fix to deliver temporary weight loss, but changes in thinking about food and diet that resulted in sensible lifestyle adjustments. Media and societal standards often feed these insecurities, presenting unrealistic body ideals that are unattainable for most people. Over time, this can lead to weight gain without any clear cause—because we’ve lost touch with the basic biological signals that regulate eating. ” we eat because it’s mealtime, because others are eating, or simply because food is within reach. From these measurements we could assess the body's basic energy requirements.“I'm like, ‘How can I be a person who excels in so many things, and gets two university degrees, and can make millions of dollars, and can start from nothing and then create this huge career, but I couldn't lose weight?We introduce a Transformer-based Reinforcement Learning framework for autonomous orbital collision avoidance that explicitly models the effects of partial observability and imperfect monitoring in space operations.A better option might be to focus on a healthy lifestyle instead, and be as happy and grateful as you can for the body you have.Third, IBW equations underestimated body weight at shorter heights and overestimated body weights at taller heights.This paper presents the design and implementation of data-driven optimal derivative feedback controllers for an active magnetic levitation system.Perhaps at last it was somebody about the autumnmeeting and the Selectmanship. In this paper, we propose to focus on the flatness of loss minima in learning hybrid models, aiming to make the model as simple as possible. However, effectively the scientific models may be ignored in prediction due to the flexibility of the machine learning model, making the idea of hybrid modeling pointless. We develop a game-theoretic framework for predicting and steering the behavior of populations of large language models (LLMs) through Nash equilibrium (NE) analysis. In this work, we build upon learning-based keypoint detection for textureless objects and propose a method that enhances robustness by tightly integrating perception and control in a closed loop. When you step on a scale, the number that flashes back at you — your weight — is a measure of your total body mass. And if you’re trying to lower your weight, the process is also somewhat complex, going way beyond calories in and calories out. Because, really, who wants to lose lean muscle mass? Thus, the best diet for weight management is one that can be maintained in the long term. Concretely, we decompose infections into trend, seasonal, and residual components and use these signals to drive continuous-time latent dynamics while jointly forecasting and inferring time-varying transmission, recovery, and immunity-loss rates. The mechanistic structure helps keep trajectories epidemiologically plausible, while neural components can capture non-stationary, data-adaptive effects. By exposing these limitations, GrAlgoBench establishes graph algorithm problems as a rigorous, multidimensional, and practically relevant testbed for advancing the study of reasoning in LRMs. Experiments show that DECAP produces more robust and interpretable parses without retraining and achieves up to 52.6% improvements over existing parsing techniques. We then propose DECAP, a decoupled agentic parsing framework that isolates spoken-phenomena handling from core syntactic analysis. As for Millicent and Gideon, they were funniestof all; they were, he realized, tremendous. Joseph wasfunny and innately charming; a perfect Cruikshank portraitof a blustering, heavy father born fifty years too late.Mrs. Gideon, remembering thosedays, laughed heartily. But itwas all very unsatisfactory and rather troublesome, thisinner pretense that Cronje and Wessels were in reality Mrs.Penniman and Ambrose. Providers should encourage those strategies that actually lead to successful weight loss, and further research should identify barriers to maintaining weight loss. Other studies have demonstrated correlations ranging from 0.84 to 0.98, even for remote weights.26,27 Although bariatric surgery was not included as a separate strategy in this study, only about 1% of medically eligible patients undergo the procedure, so any residual confounding is likely to be minimal.28 Since this is a cross-sectional observational study based mostly on self-reported information, results suggest associations and do not signify causality. The model was adjusted for gender, age, education, race/ethnicity, education level, income, self-reported health status, smoking status, diabetes status, BMI, and survey year. Study after study shows that low carb works for weight loss and that on average it improves important health markers.10 Eating higher satiety foods may also help you accomplish your health and weight loss goals. The main advantage of the low-carb diet is that it may cause you to want to eat less.6 Even without counting calories, overweight people tend to eat fewer calories on low carb.7 Thus, calories count, but you don’t need to count them. Researchers surveyed couples in which one partner had lost weight. But if they're not on board, your relationship may suffer, according to a study from North Carolina State University. That might mean increasing your protein each day and/or working in more lifting into your current workout plan. The amount of loose skin you wind up with depends on how old you are, how quickly you dropped weight, and how often you’ve lost and gained weight in the past, he says. Researchers observed nearly 2,000 overweight adults for four years. Body weight, blood pressure and heart rate were monitored during these visits. During very low calorie diet, participants were seen and/or phoned on a regular basis to monitor compliance and progress. In addition to the meal replacement products, participants were instructed to drink at least 2 L of water or other sugar‐free drinks per day. This diet is a high‐protein low‐carbohydrate diet of ±600 kcal d−1 consisting of meal replacement products. Across benchmark multi-agent environments, Exploration-Augmented JBR achieves the best accuracy-efficiency trade-off, while Hybrid BR attains near-PSRO performance at a fraction of the sample cost. We introduce Joint Experience Best Response (JBR), a drop-in modification to PSRO that collects trajectories once under the current meta-strategy profile and reuses this joint dataset to compute BRs for all agents simultaneously. Policy Space Response Oracles (PSRO) address these issues by iteratively expanding a restricted game with approximate best responses (BRs), yet per-agent BR training makes it prohibitively expensive in many-agent or simulator-expensive settings. Multi-agent reinforcement learning (MARL) offers a scalable alternative to exact game-theoretic analysis but suffers from non-stationarity and the need to maintain diverse populations of strategies that capture non-transitive interactions. For this model, we establish existence of equilibria for linear latency functions and prove uniqueness of edge latencies, despite potentially different strategic choices in equilibrium. He had beendriving for days over the mountains of Pennsylvania,through New York State, through eastern Ohio. It was a bright summer day. John Holden had rather counted on thetrip back to Caxton, had really counted on it more thanhe realized. His aunt wasa good woman, but sometimes he thought she would ratherhave enjoyed having him, John Holden, go in a bit morefor wickedness, go a little on the loose, now and then. Body fat plays a crucial role in our overall health."You can lose weight without exercise, but you cannot lose weight if your nutrition counteracts your energy expenditure through exercise," Matheny says.Experts sort through the fads to see what really helps you lose weightZero-shot generalization in contextual reinforcement learning remains a core challenge, particularly when the context is latent and must be inferred from data.This paper fills this gap and presents a systematic empirical study to investigate the fine-grained data contamination on mainstream code tasks.Based on these insights, we propose ReflexFlow, a simple and effective reflexive refinement of the Flow Matching learning objective that dynamically corrects exposure bias.Sanity checks on controlled data with known ground truth confirm that alignment improves when Iso-Energy holds and remains neutral when it does not.When you step on a scale, the number that flashes back at you — your weight — is a measure of your total body mass.It’s reaffirmed every time I cheat too! ICP-based verification identifies sparse causal parents achieving up to $49.6\%$ structural likelihood gains, stable across tasks where correlation-based patterns fail. We discover significant language bias -- the phenomenon where the same model produces substantively different political stances depending on the query language. This paper presents a systematic bilingual benchmark study examining how 17 LLMs respond to questions concerning the sovereignty of the Republic of China (Taiwan) when queried in Chinese versus English. We release all code, datasets, and evaluation protocols to support reproducibility and cost-aware NLP system design. There are no prior published RCTs that have evaluated weight loss outcomes in TOPS participants. Members who achieve their goal weight are invited to participate in a weight loss maintenance group – Keep Off Pounds Sensibly. TOPS members receive a 1-year subscription to an informational newsletter and a 6-week lesson plan that includes information on healthy eating, physical activity, and behavior change. TOPS is a high-intensity national nonprofit organization that incorporates nutrition education and group sessions to support weight loss. Another prospective cohort of Medicare beneficiaries with prediabetes showed mean weight loss of 7.5% at 12 months and decrease in A1c by −0.14% (45). Results show competitive performance of fine-tuned LLM regressors, persistent challenges in low-resource languages, and limitations of token-based generation. To facilitate the evaluation of stance VA prediction, we formulate the dimensional stance regression task, analyze cross-lingual VA patterns, and benchmark pretrained and large language models under regression and prompting settings. Standard noise filtering approaches, whether treating individual edges one-by-one or assuming a uniform global noise level, are suboptimal, because in reality both signal and noise can be heterogeneous and correlated across multiple edges. Although recent low-rank decomposition methods offer a promising path for structural compression, they often suffer from accuracy degradation, expensive calibration procedures, and result in inefficient model architectures that hinder real-world inference speedups. First, we show that unaccounted bias contaminates uncertainty estimates by overestimating aleatoric (data-related) uncertainty and underestimating the epistemic (model-related) counterpart, leading to incorrect uncertainty quantification. By subsequently aggregating these signals using a reduced Dempster's combination rule, BOGC-MML adaptively weights gradients based on their reliability to generate a calibrated update. This paper introduces DC-CoT, the first data-centric benchmark that investigates data manipulation in chain-of-thought (CoT) distillation from method, model and data perspectives. Existing cross-modal pedestrian detection (CMPD) employs complementary information from RGB and thermal-infrared (TIR) modalities to detect pedestrians in 24h-surveillance this http URL captures rich pedestrian details under daylight, while TIR excels at night. We introduce a pretraining and instruction fine-tuning pipeline, and train our hypernetwork to generate high quality LoRA adapters from diverse meaningful contexts in a single forward pass. Taking three canonical decision-making problems (assortment optimization, pricing, and newsvendor) as examples, we find that LLM-generated distributions are practically useful, especially in low-data regimes. Behavior Trees (BTs) provide a structured and reactive framework for decision-making, commonly used to switch between sub-controllers based on environmental conditions.It is not well that the people of In-ga-lee-naydo violence to such as he, for well ye know how thelong arm of the white man’s law reaches even from theSouth, where the sun sinks under the world, to the North,where the water ends.Then you’ll be happy to hear that these foods — which are loaded with protein and other essential nutrients — are excellent for losing weight.But losing weight isn’t the way to do it.Across three standard toy models for mechanistic interpretability, Toy Models of Superposition (TMS), a 1-layer MLP trained on modular addition and a 1-layer Transformer trained on modular addition, we find that top eigenspaces of the eNTK align with ground-truth features.Hormones play a massive role in regulating your body weight, and they can either be your best friend or your worst enemy when it comes to losing weight.Hank Allen wouldmurder him not only for the pleasure of the performancebut to save his own hide. And you got all these idiots saying, “Hey, listen, for you to banana, it raises your sugar and it may stub you from losing fat.” Complete bullshit! I can only imagine if you have kids and a job or running a business and you have to figure out the health and fitness stuff. And people will look at that and say, “Well, it’s because your metabolism is so fast, you know? And thankfully, because I’ve been eating nothing, but I’m in Paris, or actually, I’m in Madrid now, but I was in Paris for a week. Together, these findings shed new light on recent work and prompt a rethinking of the narrow-wide-narrow MLP convention and the balance between attention and FFN towards efficient and expressive modern language models. UNO first distills logs into semi-structured rules and preference pairs, then employs query-and-feedback-driven clustering to manage data heterogeneity, and finally quantifies the cognitive gap between the model's prior knowledge and the log data. As a result, recent work is increasing the focus on continual learning from real-world deployment, where user interaction logs provide a rich source of authentic human feedback and procedural knowledge. Cargo Scan models such potentially dangerous code as effects and performs a side-effects analysis, tailored to Rust, to identify effects and track them across crate and module boundaries. Non-stationarity of an underlying data generating process that leads to distributional changes over time is a key characteristic of Data Streams. Moreover, it exhibits strong grounding capability, achieving an IoU improvement of +40.4 over the baseline and +37.0% over Fleming-VL, underscoring its robust spatial reasoning and localization performance. Moreover, the meta-model's neurons increasingly isolate concepts into individual units, with sparse probing scores that scale as loss decreases. In particular, applying the meta-model's learned prior to steering interventions improves fluency, with larger gains as loss decreases. Although it is conceivable to generate force commands using a pretrained foundation model such as Vision-Language-Action (VLA) models, force control is highly dependent on the specific hardware of the robot, which makes the application of such models challenging. Experiments on the SurgVisDom hard adaptation benchmark demonstrate that our method substantially outperforms all competing approaches, highlighting the effectiveness of causality-guided vision-language models for domain-generalizable surgical video understanding. To address this, we propose CauCLIP, a causality-inspired vision-language framework that leverages CLIP to learn domain-invariant representations for surgical phase recognition without access to target domain data. This work introduces an alternative modeling paradigm based on multi-layer perceptrons that learns nonlinear magnetic mappings while strictly preserving the linear dependence on currents. Pasta is more commonly known as “fattening.” All without ever having to worry about calories. Always seek the advice of your physician or other qualified health personnel and ask your doctor any questions you may have regarding a medical condition. Always seek the advice of your physician or other qualified health and ask your doctor any questions you may have regarding a medical condition. Lenoir et al. defined ‘not losing weight’ individuals as subjects who did not lose 10% of their initial weight. In this review, the authors aim to discuss common factors that may hinder weight loss efforts in a lifestyle intervention in the context of clinical applications. The internal factors resulting from the complex pathophysiology of obesity such as hormonal imbalance, nutritional and metabolic factors counter the efforts one exerts to lose weight . Hence, to mitigate the risk of developing related metabolic ailments or alleviate existing chronic conditions, individuals with obesity are often advised to reduce weight by expending more energy than they consume (energy deficit) . Numerous studies recommend that a modest weight loss of 5 to 10% significantly improves parameters such as blood glucose levels, blood pressure, inflammatory markers and lipid profile among human participants 12–14. Finally — you may want to forget about the old “everything in moderation” diet motto. Ideally, the food you buy shouldn’t even have a list of ingredients (or it should be very short). Low-carb chocolate is usually full of a kind of sugar alcohol — maltitol — that may actually be partially absorbed by the body, but which the manufacturer does not count as carbs. Prioritize what humans have been eating for thousands or likely millions of years, e.g. meat, fish, vegetables, eggs, butter, olives, nuts etc.16 Do you want to watch a high-quality 11-minute video course on how to eat low-carb, high-fat (keto)? Zone dieters are assigned a daily quota of blocks based on their weight and body composition. In the 2005 A to Z trial, people who were assigned to the Weight Watchers program lost about 7 pounds (3 kilos) in one year, which was similar to participants who were assigned to the Atkins, Ornish (low fat, plant based), or Zone (high protein) diet.65 In a 2016 trial, adults with prediabetes who followed the WW points plan lost 5.5% of their body weight within 12 months, compared to a 0.2% loss in those who followed a diet based on the National Diabetes Education Program guidelines. Although the DASH diet’s primary focus is lowering blood pressure to decrease heart disease and stroke risk, some research suggests it may help people lose weight, especially when combined with calorie restriction. But during the day Maria was busy helping her mother.She had no interest in the Alcazar during that time. Goldie’s wearing of his old uniform was not uncommonenough to be striking; many a time-beaten soldier,reduced in circumstances, at last falls back on his most-treasuredsuit for every-day wear. “If HarryWidener asked me, I wouldn’t care if he were married amillion times; I’d go with him.” She became frightened,and looked around to see if anybody were listening. Maud had been silent most of theway, but she sat very close to John, and as he felt coldand lonely, he was grateful for the warmth of her slenderbody. In this case, increased activity can accelerate your weight loss, fat mass loss and reduction of insulin levels.72 Also, don’t forget that the non-weight-related health effects of exercise are quite impressive. Well, if your goal is to lose weight, we suggest following all the tips above, including eating a low-carb or higher satiety diet. In fact, on a low-carb or keto diet, some people spontaneously fall into this habit, as their appetite is reduced (see weight loss tip #4, eat only when hungry). Although the total weight loss was similar, those who took the vitamin D supplement decreased their body fat by 2.7 kg (6 pounds), on average. But, like any other source of fat, if butter is over-consumed, the calories can add up and your dietary fat will likely be burned for fuel instead of body fat. Medical practitioners or weight loss experts can make them aware of these factors, emphasizing the uniqueness of their journey and the importance of focusing on a long-term, sustained weight loss strategy. Although these factors may pose challenges for some, a slow pace of weight loss should not deter individuals from their weight loss journey. Furthermore, an individual attempting weight loss should consider their biological and medical background, environmental impact, lifestyle factors and intervention factors. Although no direct comparison of the results to lean participants was possible, it might be that the decreases in activity found after weight loss in these areas are an indication of normalization of brain activity in these areas. The areas of the brain that showed decreased neuronal activity after weight loss are brain areas that have previously been shown to function differently in obesity 9, 10, 11, 12, 13, 14, 15, 16, 17. The weight loss intervention did not have any effects on functional network connectivity of the default mode, salience and executive control networks or connectivity of the amygdala and the hypothalamus with the rest of the brain. The change in leptin, glucose, insulin and BMI after weight loss did not show a correlation with the change in BOLD signal in the affected clusters. She did not understandwhy every time these men returned Jose should be sosullen and dark. It was not much better than the home in whichtheir people had lived in the Triana. As the day of her wedding approached, Don Jose spoketo her. Reliable data attribution is essential for mitigating bias and reducing computational waste in modern machine learning, with the Shapley value serving as the theoretical gold standard. We provide a comprehensive benchmark using both prompted and fine-tuned large language models across all subtasks. Aspect-Based Sentiment Analysis (ABSA) focuses on extracting sentiment at a fine-grained aspect level and has been widely applied across real-world domains. Model merging combines knowledge from separately fine-tuned models, yet success factors remain poorly understood. Specifically, inversedMixup adopts a three-stage training procedure to align the output embedding space of a task-specific model with the input embedding space of an LLM. In particular, trained with Maze sizes of up to $6 imes6$, our VFScale solves 88% of Maze problems with much larger sizes of $15 imes15$, while standard diffusion models completely fail. However, similar test-time scaling for diffusion models to tackle complex reasoning remains largely unexplored. While large language models have achieved strong performance on explicit tasks such as summarization and reasoning, their capacity for expressivity, or implicit communication, remains underexplored. Extensive experiments across various base models and reasoning benchmarks, specifically arithmetic and commonsense reasoning tasks, demonstrate that HypLoRA substantially improves LLM performance. We use both indirect and direct data-driven design approaches based on the notions of persistency of excitation and subspace identification to exactly represent the mean and covariance dynamics of the state in terms of the data and noise realizations. In conclusion, individuals with a previous history of weight loss attempts may carry forward the metabolic debt, making it difficult to lose weight with a mild calorie deficit from their calculated daily energy expenditure. Metabolic adaptation partly explains slower weight loss in later stages of energy deficit, addressed in Hall et al., mathematical model . A study on perimenopausal women linked larger metabolic adaptation to prolonged time in achieving weight loss goals, suggesting strategies to decrease it may expedite weight loss . Almost immediately I started losing weight slowly but steadily, a couple of pounds or so per week at first, a bit slower as time went on, until I leveled out six months later at about 170. Rather than turn to the latest popular diet, I decided to take a reason-based approach. My doctor informed me that I was 25 pounds over the high end of my healthy weight range, setting myself up for serious health issues going forward. But our research has gone much deeper, showing that different people lose weight more effectively with different foods. Figuring out why we eat what we eat, how the body controls weight and how best to get people to change unhealthy habits is not easy. What's more, though people think they can diet temporarily and lose weight, the majority gain it back. Greger espouses a plant-based diet to help keep you at a healthy weight. The truth is, it's unlikely that most dieters will be able to lose one-third of their body weight. “Maintenance of lost weight and long-term management of obesity.” “The neural basis of weight control and obesity.” It should not be regarded as a substitute for guidance from your healthcare provider. Meals and snacks rich in fiber and protein (think beans, avocado, nuts, and low-fat cheese) can help you feel fuller longer. The research of artificial intelligence is undergoing a paradigm shift from prioritizing model innovations over benchmark scores towards emphasizing problem definition and rigorous real-world evaluation. Experiments demonstrate that CAST has averagely improved 8.11% F1 and 10.21% J(LLM-as-a-Judge) than baselines on various datasets, especially on open and time-sensitive conversational questions. RMCD outputs a final prediction by combining outputs predicted with each context, where each output is weighted based on its relevance to the question. While recent work leverages large language models (LLMs) for this task, existing approaches often produce stylistically redundant outputs that lack a clear brand persona and appear overtly machine-generated. However, advertising fatigue reduces the effectiveness of repeated slogans, creating a growing demand for novel, creative, and insightful slogan generation. He would be carrying a sunshadeover Lillian’s head, and Bob French would be standing atthe gate where you went into the field and charging thepeople twenty-five cents to see the game. What a lot of fun, really! I need a rest,time to think. Such environments give agents a proper training space where they can learn from errors without impacting real users. Low-bit post-training quantization (PTQ) is a promising direction; however, it typically relies on calibration data, auxiliary transformations, and GPU tools. This study proposes a transferable encoding strategy that maps tactile sensor data to electrical stimulation patterns, enabling neural organoids to perform an open-loop artificial tactile Braille classification task. Considering our most complete citation prediction model, we find pre-prints are correlated with a significant positive effect of 19% on citation counts, software sharing of 13.5%, and data sharing of 14.3%. Even so, most people are surprised when it happens to them because they're still eating carefully and exercising regularly. Being stuck at a weight-loss plateau eventually happens to everyone who tries to lose weight. By understanding what causes a weight-loss plateau, you can decide how to respond and avoid backsliding on your new healthy habits. Subsequently, in a prospective study, the Korner group63 showed that, at 1 year, there was greater weight loss in RYGB compared with gastric banding (30% versus 15%) and that the plasma PYY AUC was greater in the GB than in the banding group. Their data are consistent with the concept that the PYY rise promotes increased satiety and earlier meal termination and results in weight loss and maintenance of weight loss. In a cross-sectional study comparing no-diabetic lean, post-RYGB, post-gastric banding, and obese weight-matched subjects, Korner and coworkers92 reported postprandial increases in plasma total PYY and PYY 3–36 that were 2–4 times higher in RYGB than in all other groups. While GLP-1 increases after surgery, it remains to be proven that this increase plays an important role in the extra effects of bariatric surgery on weight loss, beyond reduction in food intake. In attempts to clarify the role of GLP-1 in bariatric-surgery-induced weight loss, a number of researchers looked at changes in GLP-1 in relation to food intake, hunger, and satiety. What are the 5 foods that burn belly fat? It emphasizes minimally processed foods high in potassium and other minerals, such as fruits, vegetables, whole grains, lean protein, and low fat dairy products. DD+ MEMBERSHIPLose weight ona vegetarian dietWith our personalized meal plans, we do the planning for you. For example, in one trial, 118 overweight adults followed a calorie-restricted vegetarian diet and a calorie-restricted Mediterranean diet for three months and lost about 4 pounds (1.8 kilos) during each diet. Similarly, vegetarian diets may not improve all heart health markers more than diets that include meat. At the same time, distance based privacy indicators improve and the success rate of attribute inference attacks remains largely unchanged. Experiments on two model families (OpenPangu and Qwen) show that SFT consistently improves semantic alignment, while reinforcement learning provides additional gains in robustness to challenging Markdown instructions when initialized from a strong SFT policy. To improve Markdown compliance without relying on hard decoding constraints, we propose a lightweight alignment pipeline that combines supervised fine-tuning (SFT) with reinforcement learning fine-tuning. We present FMBench, a benchmark for adaptive Markdown output formatting that evaluates models under a wide range of instruction-following scenarios with diverse structural requirements. Producing outputs that satisfy both semantic intent and format constraints is essential for deploying large language models in user-facing and system-integrated workflows. … What the study of intermittent fasting tells us is that regular sessions with a nutritionist, weighing yourself, and paying attention to what you are eating (the general effects) will likely help you lose weight.Peterli and colleagues,55 in a longitudinal study looking at GLP-1 increases after RYGB or SG, found that postprandial plasma GLP-1 was higher in the RYGB group than in the SG group at 1 week postsurgery.POP partitions model channels into retained, candidate, and pruned regions, where prefilling defines a coarse pruning partition, and the decoding stage generates a fine-grained mask within the candidate region, avoiding full-channel re-evaluation.But you won’t stop burning fat altogether.We demonstrate this approach on a wrought and additively manufactured alloy, showing that it effectively encodes microstructural information and enables direct identification of microstructural heterogeneity not directly possible by physics-based models.They want you to keep eating because it’s just, that’s their product just like how I want people to keep working with me, they want people to keep buying what they’re selling so it’s as simple as that.This work introduces an alternative modeling paradigm based on multi-layer perceptrons that learns nonlinear magnetic mappings while strictly preserving the linear dependence on currents. Small imbalances over long periods of time can cause you to become overweight or obese. To maintain a stable weight, your energy (kilojoule) intake needs to equal the energy you use. That's why it's more important to be able to maintain weight loss. In sequential settings, where data are observed/generated in a streaming fashion, traditional conformal methods do not provide any guarantee without fixing the sample size. We start with a meticulous analysis of LUMIR24 winners to identify the main contributors to good monomodal registration performance. First, consistent with prior literature, people show an aversion to both longer expected waits and higher variance. Techniques for feedforward networks (FFNs) and convolutional networks (CNNs) are frequently reused across families, but the relationship between the underlying model classes is rarely made explicit. Integrated into a rate-control loop, it achieves comparable coding efficiency to 2pRC while reducing total encoding time by 33.3%. If your best efforts at losing weight aren’t panning out, you’re far from alone. While some diets seem to be more effective for taking off pounds or kilos than others, there isn’t one diet plan that is best for everyone. Fortunately, you can do a high protein version of any of the diets discussed above. You may have noticed that we don’t have a section on high protein diets on this list. The Zone diet was created by Dr. Barry Sears, who published his bestselling book Enter the Zone in 1995. Empirical evaluations across five diverse benchmarks under a zero-start setting demonstrate significant performance gains over proprietary baselines. Within this framework, we develop Yunjue Agent, a system that iteratively synthesizes, optimizes, and reuses tools to navigate emerging challenges. Within this framework, we identify tool evolution as the critical pathway for capability expansion, which provides verifiable, binary feedback signals. Their reliance on static toolsets or offline training lags behind these dynamics, leaving the system's capability boundaries rigid and unknown. Healthy Living BEYOND Weight™ Study In wireless systems, DL has been applied to problems where analytical modeling or optimization is difficult to formulate, relies on oversimplified assumptions, or becomes computationally intractable. Our findings demonstrate that higher binder content significantly enhances fatigue life, while the influence of air-void content is more variable, depending on binder levels. The mean square logarithmic error was utilized as the loss function to enhance prediction accuracy across all levels of fatigue life. Extensive quantitative and qualitative experiments demonstrate the successful anonymization performance of APL, which anonymizes any specific individuals without compromising the quality of non-identity-specific image generation. Finally, we evaluate the impact of reducing the sampling rate of the TR filter on the achievable speeds, paving the way to practical TR-based wireless communications at the chip scale. Over time, if you do eat only at your BMR and try to be active, you may feel fatigued or unsatisfied.To alleviate lazy optimization, we incorporate mismatch correction for training stability and introduce Profiling-based Rewards (PR) and Profiling-based Rejection Sampling (PRS) to overcome the issue.Therefore, while it’s necessary to mind what you eat, it’s equally important to ensure that you’re getting enough sleep so that your body has the opportunity to rest and recover.This work was supported by the Netherlands Consortium for Systems Biology (NCSB) and Center for Medical Systems Biology (CMSB) within the framework of the Netherlands Genomics Initiative (NGI/NWO).REACT comprises a computationally efficient geometry-based tether model using the signed distance field (SDF) map for accurate, real-time simulation of taut tether configurations around arbitrary structures in 3D.Remarkably, the errors of the trajectories generated by MDtrajNet-1 for various seen and even unseen small-sized molecular systems are close to those of the conventional ab initio MD.Beyond efficiency, we provide a rigorous framework for benchmarking AI-assisted workflows that quantifies trade-offs between algorithmic speed and the integrity of human verification.We propose HyPER, a training-free online control policy for multi-path decoding in mixture-of-experts models that reallocates computation under a fixed budget using lightweight path statistics. While generative modeling on time series facilitates more capable and flexible probabilistic forecasting, existing generative time series models do not address the multi-dimensional properties of time series data well. In contrast, continual learning operates on streaming and non-stationary data, and trains models incrementally, inherently facing the well-known plasticity-stability dilemma. Using these measures, we conduct a comprehensive empirical evaluation across multiple real-world image datasets and a diverse set of model architectures, including both convolutional and transformer-based networks. Psychology calls this identity-based behavior—our actions tend to align with how we view ourselves. To change eating habits, you don’t just need willpower—you need to rewire the loop. Habits are the brain’s way of conserving energy—automatic routines that help us navigate the world without constant decision-making. It means practicing self-compassion, embracing imperfections, and recognizing that health and beauty come in many shapes and sizes. 4.5. Emotional eating Annie lay and listened to her with a smile.She uncovered the plump little body and saw for herselfthat it was perfect. The river began to go down the third day after Annie’sson was born. “Mammy,” Annie reached out and clutched her withstraining fingers, “don’t you reckon the doctor will begittin’ here purtty soon now—Will must er told him howbad I needed him——” In this work, we present a framework for high-precision ED that jointly addresses architectural design, data supervision, and evaluation consistency. By modeling static and dynamic similarity separately, both types of semantics can be fully exploited during the V-CL training process. As a result, learning only one type of semantics is sufficient for the model to minimize the contrastive loss. Through a rigorous theoretical analysis based on the Structural Causal Model and gradient update, we find that in a given dataset, certain static semantics consistently co-occur with specific dynamic semantics. Video contrastive learning (V-CL) has emerged as a popular framework for unsupervised video representation learning, demonstrating strong results in tasks such as action classification and detection. For example, even farm-raised Atlantic salmon (the type of salmon that’s highest in fat) is still a good choice, with 43% protein and about 200 calories per 100-gram serving. Although most shellfish and white fish have extremely high protein percentages and low energy densities, fatty fish like salmon, sardines, and herring have solid values, too. That’s because seafood provides lots of protein with little fat and carbs, no matter what type you choose. This approach allows the system to generate force commands effectively, even for unseen position trajectories, improving generalization for real-world robot writing tasks. However, when dealing with unseen position trajectories, the model struggles to generate accurate force commands. To bridge this gap, we propose a force generative model that estimates force commands from given position trajectories. Our approach integrates a frequency-based augmentation strategy to perturb domain-specific attributes while preserving semantic structures, and a causal suppression loss that mitigates non-causal biases and reinforces causal surgical features. Furthermore, we demonstrate that straightforward design choices effectively eliminate spurious workspace ill-conditioning frequently reported in MPEM-based calibration. “I really think beauty is at any shape and size so I do really promote that.” Rebel also journaled for twelve minutes a day in a practice she dubbed, "Purge Emotional Writing." And if she felt like she lost her focus or started to slip back into old patterns, she'd look at an old photo of herself when she was young. "Enjoying a morning walk amongst health treatments at the glorious @vivamayraltaussee ...finishing my Year of Health off STRONG at the place that gave me that first kick-start 😁," she captioned a recent Instagram post. "I got all these high-tech tests done on me during my year of health," she said, per People. Even when Rebel's busy, she would make time for her workouts. If you’re ready to lose weight and keep it off, read our detailed review of the top 10 weight loss programs to find out which one is best for you. Certain diet plans may also provide greater improvements in health markers — like blood sugar control and heart disease risk factors — compared to other eating patterns. Get instant access to healthy low carb and keto meal plans, fast and easy recipes, weight loss advice from medical experts, and so much more. If you’ve been consistent for six months or more, you’ve likely developed a healthy routine you can stick with. People may comment that you look healthier or more energetic. You’ve learned how to eat better, how to move more, and how to bounce back after bad days without giving up. You can find programs for gym training and at-home workouts, plus ones specifically for women, men, older adults, and people with special health concerns. When that important event or warm weather rolls around, you can still feel good about yourself, knowing you’re going to continue improving your health as you continue your weight loss journey. Added fat, in the amount your body — rather than a calculator — decides is right, provides energy to replace carbs. Traditional agent-based urban mobility simulations often rely on rigid rulebased systems that struggle to capture the complexity, adaptability, and behavioral diversity inherent in human travel decision making. We demonstrate with case studies visualizing turbulent combustion data--multi-scalar compressible flows--and turbulent incompressible channel flow data. We implement and integrate our method into an interactive visualization system where the glyph-based technique operates in tandem with linked 3D spatial views and 2D statistical views, supporting a holistic analysis. Each glyph represents data aggregated within a Voronoi region and is positioned at the Voronoi site for direct visualization in a 3D view centered around flow features of interest. However, visualizing multivariate, multiscale data within an integrated view where correlations across space, scales, and fields are easily perceived remains challenging. She benther head close to his lips, listened, and then ran to bringhim water. Most people, indeed, gave their attention to HoneyBoy, trailing directly behind and mocking the little grayman who labored with difficulty through the deep whitesand. He was nowover seventy, was considered a trifle queer, and spent mostof his time pottering around at home.