Hasil untuk "Home economics"

Jing Lan, Yongzhao Xiong, Kuo Dang et al.

Small peptides, particularly tripeptides, play a crucial role in food umami taste. To dig for more umami tripeptides, the novel tripeptides pharmacophore model was established to rapidly screen umami peptides from natural tripeptide database. Twenty peptides with potential umami characteristics from 8000 tripeptides were further screened by molecular docking. The electronic tongue analysis and sensory evaluation suggested that the 20 tripeptides exhibited umami taste characteristics. The thresholds of the 20 tripeptides spanned from 0.137 to 2.237 mmol/L. Molecular dynamics simulations were used on T1R1 and four tripeptides with high umami intensity to reveal their taste mechanisms. In this study, a new screening strategy was established and 20 new umami tripeptides were identified and validated, providing a theoretical reference for rapid screening of umami tripeptides.

Xiulan Xie, Jiasui Zhan, Maozhi Ren

ABSTRACT Human civilization is threatened by food insecurity and habitat loss owing to the cumulative effects of anthropogenic and natural factors. Thus, increasing food production while using fewer resources and exploring the potential of interstellar migration is essential. Particularly, microalgae can fulfil the biological, nutritional, and efficiency requirements of industrial food production on Earth and other potential planets. Herein, we discuss the industrial production of microalgae on Earth and in outer space, along with the technological advances that will help reshape the genetic and chemical properties of microalgae for better production, nutrition, and adaptation. We propose the concept of “multiplanetary farming” to address future requirements for agricultural development. This perspective review is intended to stimulate a broad debate and research on this paramount issue for the future of mankind.

Zikun Chen, Xuequan Hou, Binyu Chen et al.

Abstract The skeletal system is vital to human health and is influenced by factors such as age and nutritional intake. Although existing studies have identified certain associations between dietary factors and orthopedic diseases, systematic analyses and theoretical perspectives remain insufficient. To address this, we present ONMR, the largest platform using Mendelian Randomization to investigate the impact of dietary intake on orthopedic disorders. By systematically integrating Genome-Wide Association Study (GWAS) data to provide over 100,000 analyses between 210 nutritional items and 503 bone-related phenotypes, ONMR provides a comprehensive framework for understanding the complex interactions between diet and skeletal health. This extensive analysis has elucidated the dual effects of dietary intake on bone health and their age-dependent characteristics. As a pivotal resource for interdisciplinary research spanning nutritional science and orthopedics, this platform could significantly contribute to the advancement of precision medicine in health management. The ONMR supports data querying, downloading, and personalized analysis, which can be accessed via a user-friendly website at https://onmr.ai-bio.net .

Victor Augias, Lina Uhe

We introduce convex function intervals (CFIs): families of convex functions satisfying given level and slope constraints. CFIs naturally arise as constraint sets in economic design, including problems with type-dependent participation constraints and two-sided (weak) majorization constraints. Our main results include: (i) a geometric characterization of the extreme points of CFIs; (ii) sufficient optimality conditions for linear programs over CFIs; and (iii) methods for nested optimization on their lower level boundary that can be applied, e.g., to the optimal design of outside options. We apply these results to four settings: screening and delegation problems with type-dependent outside options, contest design with limited disposal, and mean-based persuasion with informativeness constraints. We draw several novel economic implications using our tools. For instance, we show that better outside options lead to larger delegation sets, and that posted price mechanisms can be suboptimal in the canonical monopolistic screening problem with nontrivial, type-dependent participation constraints.

Craig S Wright

This paper presents a praxeological analysis of artificial intelligence and algorithmic governance, challenging assumptions about the capacity of machine systems to sustain economic and epistemic order. Drawing on Misesian a priori reasoning and Austrian theories of entrepreneurship, we argue that AI systems are incapable of performing the core functions of economic coordination: interpreting ends, discovering means, and communicating subjective value through prices. Where neoclassical and behavioural models treat decisions as optimisation under constraint, we frame them as purposive actions under uncertainty. We critique dominant ethical AI frameworks such as Fairness, Accountability, and Transparency (FAT) as extensions of constructivist rationalism, which conflict with a liberal order grounded in voluntary action and property rights. Attempts to encode moral reasoning in algorithms reflect a misunderstanding of ethics and economics. However complex, AI systems cannot originate norms, interpret institutions, or bear responsibility. They remain opaque, misaligned, and inert. Using the concept of epistemic scarcity, we explore how information abundance degrades truth discernment, enabling both entrepreneurial insight and soft totalitarianism. Our analysis ends with a civilisational claim: the debate over AI concerns the future of human autonomy, institutional evolution, and reasoned choice. The Austrian tradition, focused on action, subjectivity, and spontaneous order, offers the only coherent alternative to rising computational social control.

Qirui Mi, Qipeng Yang, Zijun Fan et al.

Artificial intelligence (AI) has become a powerful tool for economic research, enabling large-scale simulation and policy optimization. However, applying AI effectively requires simulation platforms for scalable training and evaluation-yet existing environments remain limited to simplified, narrowly scoped tasks, falling short of capturing complex economic challenges such as demographic shifts, multi-government coordination, and large-scale agent interactions. To address this gap, we introduce EconGym, a scalable and modular testbed that connects diverse economic tasks with AI algorithms. Grounded in rigorous economic modeling, EconGym implements 11 heterogeneous role types (e.g., households, firms, banks, governments), their interaction mechanisms, and agent models with well-defined observations, actions, and rewards. Users can flexibly compose economic roles with diverse agent algorithms to simulate rich multi-agent trajectories across 25+ economic tasks for AI-driven policy learning and analysis. Experiments show that EconGym supports diverse and cross-domain tasks-such as coordinating fiscal, pension, and monetary policies-and enables benchmarking across AI, economic methods, and hybrids. Results indicate that richer task composition and algorithm diversity expand the policy space, while AI agents guided by classical economic methods perform best in complex settings. EconGym also scales to 10k agents with high realism and efficiency.

Elliot Beck, Franziska Eckert, Linus Kühne et al.

We develop a resource-efficient methodology for measuring economic outlook in news text that combines document embeddings with synthetic training data generated by large language models. Applied to 27 million news articles, the resulting indicator significantly improves GDP growth forecast accuracy and captures sentiment shifts weeks before official releases, proving particularly valuable during crises. The indicator outperforms both survey-based benchmarks and traditional dictionary methods and is interpretable, allowing identification of specific drivers of economic sentiment. Our approach addresses key institutional constraints: it performs sentiment classification locally, enabling analyses of proprietary news content without transmission to external services while requiring minimal computational resources compared to direct large language model classification.

LI Yuling, HUANG Ruoqi, YANG En

Deoxynivalenol （DON） is a toxic secondary metabolite produced by Fusarium， which mainly infects wheat， corn and other grains. It not only causes huge economic losses to the agricultural industry， but also has a potential threat to human and animal health. Therefore， how to efficiently remove DON from grains has always been an urgent problem. Currently， there is good development space in terms of cost and large-scale promotion of the use of microorganisms and their metabolites for biological detoxification of DON. This article makes a detailed description of the harm and detection technology of DON， as well as the research and application of the detoxification mechanism of DON by lactic acid bacteria in recent years， which provides a reference for the biological pest control of DON in grains and feedstuffs by lactic acid bacteria and its large-scale industrial application.

Clement E. Bohr, Marti Mestieri, Frederic Robert-Nicoud

As countries develop, the relative importance of agriculture declines and economic activity becomes spatially concentrated. We develop a model integrating structural change and regional disparities to jointly capture these phenomena. A key modeling innovation ensuring analytical tractability is the introduction of non-homothetic Cobb-Douglas preferences, which are characterized by constant unitary elasticity of substitution and non-constant income elasticity. As labor productivity increases over time, economic well-being rises, leading to a declining expenditure share on agricultural goods. Labor reallocates away from agriculture, and industry concentrates spatially, further increasing aggregate productivity: structural change and regional disparities are two mutually reinforcing outcomes and propagators of the growth process.

Habtamu Hawaz, Mestawet Taye, Diriba Muleta

Food safety remains the main health concern in the developing countries. Thus, the major purpose of the present study was to characterize and determine antibiotic susceptibility patterns of Listeria monocytogenes from raw milk samples collected from southern Ethiopia. Two hundred and forty raw cow milk samples were collected from dairy farms and smallholder dairy producers using a simple random sampling technique and analyzed by cultural and multiplex PCR methods. The antimicrobial susceptibility profile of L. monocytogenes was evaluated using the standard disk diffusion method. Over 28% of the samples were found positive for Listeria spp., of which 17 (7.08%) isolates were identified as L. monocytogenes after morphological and biochemical confirmation. The prevalence of L. monocytogenes was 6.02% in Hawassa city, 5.56% in Dale district, and 9.41% in Arsi Negele district. L. monocytogenes was higher in the wet season (9.32%) than in the dry season (4.92%). The gene for Listeria specific 16S rRNA was detected in all the 17 examined isolates, while hlyA and iapA were only found in 11 of them. Furthermore, no isolate was identified to have the prfA, actA, or plcA genes. Antimicrobial resistance profiling revealed that all the L. monocytogenes isolates were resistant to nalidixic acid (100%), followed by erythromycin (88.24%). However, all the L. monocytogenes isolates were sensitive to vancomycin, gentamicin, and sulfamethoxazole. Raw cow milk is a potential source of L. monocytogenes and it poses a threat to human and animal health. Therefore, it is crucial that dairy producers and vendors of raw milk in the study areas should take considerable precautions to prevent Listeria species from contaminating raw fresh milk.

Atieh Mirzababaei, Faezeh Abaj, Darya Khosravinia et al.

BackgroundObesity affects body composition and anthropometric measurements. A Body Shape Index (ABSI) and Body Roundness Index (BRI) are reportedly associated with an increased risk of cardiovascular disease. However, the relationship between ABSI, BRI, cardiometabolic factors, and inflammatory elements is not well-elucidated. Therefore, this study sought to examine the mediatory effect of inflammatory markers on the association between ABSI and BRI with cardiometabolic risk factors in overweight and obese women.MethodsThis cross-sectional study was performed on 394 obese and overweight women. The typical food intake of individuals was assessed using a 147-item semi-quantitative Food Frequency Questionnaire (FFQ). Body composition was measured by bioelectrical impedance analysis (BIA). Biochemical parameters, such as inflammatory markers and anthropometric components, were also assessed. For each participant, all measurements were carried out on the same day.ResultThere was a significant positive association between ABSI and AC and CRI.I in subjects with higher ABSI scores before and after adjustment (P < 0.05). In addition, there was a significant positive association between BRI and FBS, TC, TG, AIP, AC, CRI.I, CRI.II, and TyG in participants with higher BRI scores before and after adjustment (P < 0.05). We found that hs-CRP, PAI-1, MCP-1, TGF-β, and Galectin-3 were mediators of these relationships (P < 0.05).ConclusionInflammation can play an important role in the relationship between body shape indices and cardiometabolic risk factors among overweight and obese women.

Clyde S. Manuel, Greg Robbins, Jason Slater et al.

Hand hygiene product usage characteristics by food employees when hand sanitizers are made available are not well understood. To investigate hand hygiene product usage in casual dining and quick-service restaurants, we placed automated monitoring soap and sanitizer dispensers side-by-side at handwash sinks used by food employees in seven restaurants. Dispenses were monitored, and multiple dispenses that occurred within 60 s of each other were considered a single hand hygiene event. This resulted in 186,998 events during the study (149,779 soap only, 21 985 sanitizer only, and 15,234 regimen [defined as soap followed by sanitizer at the same sink within 60 s]) over 15,447 days of use. Soap was the most frequently used hand hygiene method by food employees in both restaurant types. Regimen use, despite being the preferred hand hygiene method by both restaurant chains, was the least used hand hygiene method. When pooled over restaurant types, the median daily usage for soap was statistically significantly highest of all methods at 23.5 dispenses per sink per day (p < 0.0001), the sanitizer median daily usage was 4.27 dispenses per sink per day, and regimen use was statistically significantly lowest of all methods at 4.02 dispenses per sink per day (p < 0.0001). When hand hygiene event types were pooled, casual dining restaurants had similar median hand hygiene event rates (11.4 dispenses per sink per day) compared to quick-service restaurants (11.9 dispenses per sink per day; p = 0.890). The number of events by sink location varied, with sinks located at a warewash station having the highest number of events (19.3 dispenses per sink per day; p < 0.0001), while sinks located by a ready-to-eat food preparation area had the lowest number of events (6.8 dispenses per sink per day; p < 0.0001). These data provide robust baseline benchmarks for future hand hygiene intervention studies in these settings.

Rodolphe N’Dedji Sodokin, Chika Oliver Ujah, Daramy Vandi Von Kallon et al.

In recent decades, the use of electrochemistry has increased exponentially. Electrochemistry has demonstrated their effectiveness in the cleaning of manufactured effluents and the decomposition of complex hydrological compounds for water treatment. Looking at the efficiency of the technology in the decomposition of organic matter, one wonders if it is not capable of doing more than just the de-pollution and treatment of water. Of course, there are other uses of electrochemistry, but in the literature, it is understood that it is used more for water treatment and de-pollution. This work is a review of the literature to identify the major works in electrochemical decomposition of organic matter to see to what extent this technology can be used for methane production (cooking gas) using pasty organic matter. The list of works appearing in this review is not exhaustive, but it is sufficient to give a clear idea of the technology, its progress and, above all, the challenges it faces. This review opens the way to other applications of electrochemical decomposition to meet today's energy challenges.

Saniya Ramzan, Maryam Saeed, Zain Ali et al.

The COVID-19 pandemic has sparked a paradigm change in pandemic preparedness measures, motivating an investigation of non-pharmaceutical therapies. This research dives into the lessons learned from COVID-19 to strengthen our strategy to prevent future pandemics. The study aimed to extract valuable insights from the COVID-19 experience, extrapolating lessons learned to develop strong strategies that include diet, lifestyle, risk factors and non-pharmaceutical treatments. Nutrition and lifestyle influences on illness susceptibility were studied using a comprehensive examination of scholarly literature, reports and epidemiological studies. Role of essential risk variables was investigated in magnifying pandemic outcomes and the efficiency of non-pharmaceutical treatments in reducing infectious agent transmission. The analysis demonstrates the long-term utility of COVID-19 findings. This review emphasizes the importance of nutrition and lifestyle variables in determining susceptibility to infectious illnesses. Furthermore, a detailed examination of risk variables shows critical predictors of pandemic severity. Most significantly, the findings highlight the effectiveness of non-pharmaceutical measures, emphasizing their vital role in pandemic containment. This study has far-reaching ramifications that advocate for a paradigm change towards comprehensive pandemic preparation using the lessons learned during COVID-19. Research findings highlight the need for a multifaceted strategy, including diet, lifestyle changes, targeted risk reduction and non-pharmaceutical therapies. This study provides a road map for improving global resilience to potential future pandemics, calling for preventative strategies beyond pharmacological remedies.

Gennady Shkliarevsky

The subject of this study is inflation, a problem that has plagued America and the world over the last several decades. Despite a rich trove of scholarly studies and a wide range of tools developed to deal with inflation, we are nowhere near a solution of this problem. We are now in the middle of the inflation that threatens to become a stagflation or even a full recession; and we have no idea what to prevent this outcome. This investigation explores the real source of inflation. Tracing the problem of inflation to production, it finds that inflation is not a phenomenon intrinsic to economy; rather, it is a result of inefficiencies and waste in our economy. The investigation leads to a conclusion that the solution of the problem of inflation is in achieving full efficiency in production. Our economic production is a result of the evolution that is propelled by the process of creation. In order to end economic inefficiencies, we should model our economic practice on the process that preceded production and has led to its emergence. In addition, the study will outline ways in which our economic theory and practice must be changed to achieve full efficiency of our production. Finally, the study provides a critical overview of the current theories of inflation and remedies that are proposed to deal with it.

Jozef Barunik, Lukas Vacha

We propose a novel framework for modeling time-varying persistence in economic time series, allowing for smoothly evolving heterogeneity in shock dynamics. We leverage localized regression techniques to flexibly identify changes in persistence over time, offering a data-driven alternative to traditional parametric models. We applied this methodology to U.S. inflation and stock market volatility data and found substantial persistence variations that align with key macroeconomic events and market conditions. The results reveal previously undetected pockets of predictability and provide significant increases in out-of-sample forecast accuracy. These findings have important implications for economic modeling, forecasting, and policy analysis.

Mert Nakıp, Onur Çopur, Emrah Biyik et al.

Smart home energy management systems help the distribution grid operate more efficiently and reliably, and enable effective penetration of distributed renewable energy sources. These systems rely on robust forecasting, optimization, and control/scheduling algorithms that can handle the uncertain nature of demand and renewable generation. This paper proposes an advanced ML algorithm, called Recurrent Trend Predictive Neural Network based Forecast Embedded Scheduling (rTPNN-FES), to provide efficient residential demand control. rTPNN-FES is a novel neural network architecture that simultaneously forecasts renewable energy generation and schedules household appliances. By its embedded structure, rTPNN-FES eliminates the utilization of separate algorithms for forecasting and scheduling and generates a schedule that is robust against forecasting errors. This paper also evaluates the performance of the proposed algorithm for an IoT-enabled smart home. The evaluation results reveal that rTPNN-FES provides near-optimal scheduling $37.5$ times faster than the optimization while outperforming state-of-the-art forecasting techniques.

A. Henke, L. Hsu

Recent studies estimate that the COVID-19 pandemic significantly increases reports of domestic violence in several countries. Using mobile device tracking data, city-level unemployment data, and new data on labor market conditions caused by the coronavirus pandemic, we isolate the effects of unemployment and staying at home on incidents of domestic violence. We find that unemployment decreases domestic violence after controlling for the degree to which people stay at home. We also provide evidence that staying at home increases domestic violence. However, we find that the effects of unemployment and staying at home are concentrated right after an initial shock from mid-March to mid-June 2020. Finally, we find that some labor market conditions linked to COVID-19, such as being prevented from looking for work due to the pandemic, decrease domestic violence, and these labor market effects are often gendered.

Anthony Bald, J. Doyle, Max Gross et al.

Foster care provides substitute living arrangements to protect maltreated children. The practice is remarkably common: it is estimated that 5 percent of children in the United States are placed in foster care at some point during childhood. This paper describes the main tradeoffs in child welfare policy and provides background on policy and practice most in need of rigorous evidence. Trends include efforts to prevent foster care on the demand side and to improve foster home recruitment on the supply side. With increasing data availability and a growing interest in evidence-based practices, there are opportunities for economic research to inform policies that protect vulnerable children.

Wanida Tewaruth Chitisankul, Kazuko Shimada, Chigen Tsukamoto

Soyfood isoflavones and soyasaponins are effective compounds in terms of their health-promoting properties. Their chemical structure plays an important role in their antioxidative activity. Thus, six isoflavones and four soyasaponins that are targeted in soyfood were evaluated for their peroxyl radical scavenging capacities by the hydrophilic-oxygen radical absorbance capacity (H-ORAC) method. The antioxidant capacity of non-fermented and fermented soyfoods was also determined by the same method. The results revealed that isoflavones showed higher peroxyl radical scavenging capacities than soyasaponin, with their activities found to depend on their chemical structure. The aglycone isoflavones promoted higher H-ORAC values than glycoside and malonyl glycoside isoflavones, respectively. On the other hand, DDMP saponin promoted a higher H-ORAC value than its derived compound, group B saponin, and the aglycone soyasaponin. In the case of soyfoods, fermented soyfoods had higher antioxidative capacity that the non-fermented ones, especially the long-term fermented products. Soybean-koji miso presented the highest H-ORAC value, followed by natto, soy sauce, and tempeh. Moreover, lightness ( L* ) of miso and soy sauce showed a negative correlation with H-ORAC value probably due to browning substances which might derive from the amino-carbonyl reaction. Considering the high antioxidant capacity of fermented soyfoods, it might relate to aglycone isoflavones which promote strong radical scavenging capacity. Thus, fermented soyfoods, especially miso and natto, could be considered as health-promoting foods.