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The study of complex networks is a significant development in modern science, and has enriched the social sciences, biology, physics, and computer science. Models and algorithms for such networks are pervasive in our society, and impact human behavior via social networks, search engines, and recommender systems, to name a few. A widely used algorithmic technique for modeling such complex networks is to construct a low-dimensional Euclidean embedding of the vertices of the network, where proximity of vertices is interpreted as the likelihood of an edge. Contrary to the common view, we argue that such graph embeddings do not capture salient properties of complex networks. The two properties we focus on are low degree and large clustering coefficients, which have been widely established to be empirically true for real-world networks. We mathematically prove that any embedding (that uses dot products to measure similarity) that can successfully create these two properties must have a rank that is nearly linear in the number of vertices. Among other implications, this establishes that popular embedding techniques such as singular value decomposition and node2vec fail to capture significant structural aspects of real-world complex networks. Furthermore, we empirically study a number of different embedding techniques based on dot product, and show that they all fail to capture the triangle structure.

We study the issue of polarization in society through a model of opinion formation. We say an opinion formation process is polarizing if it results in increased divergence of opinions. Empirical studies have shown that homophily, i.e., greater interaction between like-minded individuals, results in polarization. However, we show that DeGroot’s well-known model of opinion formation based on repeated averaging can never be polarizing, even if individuals are arbitrarily homophilous. We generalize DeGroot’s model to account for a phenomenon well known in social psychology as biased assimilation: When presented with mixed or inconclusive evidence on a complex issue, individuals draw undue support for their initial position, thereby arriving at a more extreme opinion. We show that in a simple model of homophilous networks, our biased opinion formation process results in polarization if individuals are sufficiently biased. In other words, homophily alone, without biased assimilation, is not sufficient to polarize society. Quite interestingly, biased assimilation also provides a framework to analyze the polarizing effect of Internet-based recommender systems that show us personalized content.

Sleep is a critical component of healthy development, particularly during the formative years from infancy through adolescence. Sleep undergoes continuous change throughout life characterized by frequent awakenings and a high proportion of rapid eye movement (REM) sleep during infancy, changes in sleep architecture, an increase in non-rapid eye movement (NREM) sleep during adolescence, and an eventual decrease in REM sleep in old age. Adequate sleep is therefore essential for cognitive development, especially between ages 10 and 16. Sleep deprivation may negatively affect academic performance, attention regulation, and emotional well-being. Biological factors, such as hormonal changes during puberty, significantly influence sleep patterns, leading to later bedtimes and a tendency for chronic sleep deprivation in adolescents. Environmental factors, including light exposure and screen time, also play a critical role in regulating sleep. This paper examines the evolution of sleep patterns across infancy and adolescence, describing changes in sleep architecture, timing, and regulation. The influence of biological, environmental, and socio-cultural factors on sleep is explored, highlighting how these factors collectively shape sleep behaviors and health outcomes. It also addresses the profound role sleep plays in cognitive development, brain maturation, and emotional well-being. The importance of understanding sleep patterns and their developmental trajectories to address sleep-related issues is emphasized. Promoting healthy sleep from an early age can enhance cognitive and emotional outcomes, contributing to better academic performance and overall well-being in children and adolescents. The findings advocate for further standardized sleep intervention programs globally to prioritize sleep health and support optimal development.

PurposeThe purpose of this paper is to examine various uncertainties underlying the concept of sustainability in construction and built environment (SCBE) and determine if SCBE is a “wicked problem” (WP).Design/methodology/approachQualitative text analysis and inductive reasoning are used as research methods in this paper. Text analysis of extant literature is performed to categorise the uncertainties underlying the concept of SCBE. Inductive reasoning, based on these categories of uncertainties and the characteristics of WPs provided in the seminal work of Rittel and Webber (1973), is used to assess SCBE as a probable WP.FindingsSix distinct categories of uncertainties underlying the concept of SCBE are developed: temporal uncertainty, spatial uncertainty, stakeholder uncertainty, societal uncertainty, dimensional uncertainty and assessment uncertainty. The inductive reasoning provides a prima facie evidence that SCBE, underpinned by these uncertainties, is a WP.Originality/valueTo the best of author’s knowledge, this is first of its kind analysis that assesses SCBE from a WP perspective by a systematic categorisation of underlying uncertainties. The findings necessitate a new approach for the context-specific conception of sustainability to commensurate with local values. They also provide a sound academic base to challenge the positivist notions generally associated with SCBE, reflected in sustainability assessment and rating systems currently pursued globally as a means of promoting SCBE.

Childhood obesity is a complex public health challenge with profound implications for both physical and psychological well-being. A significant portion of the global population struggles with obesity. Sedentary lifestyles, increased consumption of ultra-processed foods, and socioeconomic disparities are major contributors. The COVID-19 pandemic has further exacerbated these issues, leading to a surge in obesity rates among children. The consequences of childhood obesity extend beyond immediate health issues like type 2 diabetes and cardiovascular diseases; obese children are at higher risk for psychological problems such as depression, anxiety, and low self-esteem, which can persist into adulthood. These health challenges also impose substantial economic burdens due to increased healthcare costs and reduced productivity. This paper synthesizes findings from various articles to provide an overview of the causes, consequences, and preventive strategies related to childhood obesity. It highlights the varied nature of obesity, including genetic, environmental, and lifestyle factors, and discusses the profound impact on physical health, socioemotional skills, and mental health. Additionally, it examines the global challenge of childhood obesity, particularly in developing nations, and emphasizes the importance of preventive measures, family and parental behaviors, and effective policy interventions.

The global impact of COVID-19 pandemic has led to a rapid development and utilization of mobile health applications. These are addressing the unmet needs of healthcare and public health system including contact tracing, health information dissemination, symptom checking and providing tools for training healthcare providers. Here we provide an overview of mobile applications being currently utilized for COVID-19 and their assessment using the Mobile Application Rating Scale. We performed a systematic review of the literature and mobile platforms to assess mobile applications currently utilized for COVID-19, and a quality assessment of these applications using the Mobile Application Rating Scale (MARS) for overall quality, Engagement, Functionality, Aesthetics, and Information. Finally, we provide an overview of the key salient features that should be included in mobile applications being developed for future use. Our search identified 63 apps that are currently being used for COVID-19. Of these, 25 were selected from the Google play store and Apple App store in India, and 19 each from the UK and US. 18 apps were developed for sharing up to date information on COVID-19, and 8 were used for contact tracing while 9 apps showed features of both. On MARS Scale, overall scores ranged from 2.4 to 4.8 with apps scoring high in areas of functionality and lower in Engagement. Future steps should involve developing and testing of mobile applications using assessment tools like the MARS scale and the study of their impact on health behaviours and outcomes.

Background In light of escalating rates of childhood obesity, understanding the gender-specific correlation between body mass index (BMI) and hypertension has become crucial for effective public health interventions. This study investigates the interplay between BMI and hypertension among school-aged children, with a particular emphasis on gender stratification to identify distinct trends. Methodology A cross-sectional study was conducted with a diverse sample of 702 schoolchildren aged 5-16 years from a lower-middle-income school in urban Mumbai. This cohort consisted of 491 boys and 211 girls within the gender subset. BMI was calculated using height and weight measurements, while blood pressure readings determined hypertension prevalence. The children were categorized based on the Indian Academy of Pediatrics (IAP) growth chart BMI calculations and blood pressure percentiles. SPSS Statistics version 23 (IBM Corp., Armonk, NY, USA) was used for data analysis. Data were analyzed using the chi-square test, with p-values <0.05 deemed significant. Results The overall prevalence of overweight was 16.52%, with 15.89% in boys and 18.10% in girls, revealing no significant gender difference (p = 0.487). In terms of obesity, the overall prevalence was 10.83%, with 10.99% in boys and 10.34% in girls, revealing no significant gender difference (p = 0.823). The prevalence of pre-hypertension was 7%, exhibiting a significantly higher prevalence in high BMI males (overweight and obese) versus non-high BMI males (normal and underweight) (p < 0.001); however, no such difference was observed in females (p = 0.289). The prevalence of hypertension was 15.95% with a significantly higher prevalence in high BMI males (overweight and obese) versus non-high BMI males (normal and underweight) (p < 0.001) and high BMI females (overweight and obese) versus non-high BMI females (normal and underweight) (p < 0.001). Hypertension was significantly higher in children with high BMI (overweight and obese) compared to their non-high BMI (normal and underweight) counterparts. Conclusions In lower-middle socioeconomic strata schoolchildren in urban Mumbai, the prevalence of obesity and hypertension was alarmingly high, attributed to shifting lifestyles and unhealthy dietary habits. Hypertension rates were notably elevated among overweight and obese individuals compared to normal and underweight individuals. More than a third of both boys and girls with obesity were diagnosed with hypertension, emphasizing a concerning surge in hypertension cases among children. Prioritizing age-specific blood pressure assessments can facilitate early identification and timely interventions.

Background Metabolic syndrome (MetS) represents a critical public health challenge globally, characterized by a cluster of metabolic abnormalities that heighten the risk of cardiovascular diseases and type 2 diabetes. In India, the prevalence of MetS, particularly in urban areas, is rising rapidly. This study investigates the prevalence of MetS and its association with waist circumference in middle-aged individuals from urban Mumbai. Methods A cross-sectional study was conducted among 1,851 participants (814 men and 1,037 women, with a mean age of 56.8 years) in a public health camp in urban Mumbai. Data were collected on anthropometric measures, blood pressure, and blood markers, including fasting glucose and lipid profiles. MetS was diagnosed based on the National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III) criteria. This included the presence of three or more of the following five criteria: waist circumference of ≥102 cm for men and ≥88 cm for women, fasting triglycerides of ≥150 mg/dL, fasting high-density lipoprotein (HDL) cholesterol of <40 mg/dL for men and <50 mg/dL for women, blood pressure of ≥130/85 mm Hg, and fasting glucose of ≥100 mg/dL. Data were analyzed using SPSS Statistics version 23 (IBM SPSS Statistics, Armonk, NY). Statistical analyses were performed using the chi-square test, with statistical significance set at p<0.05. Results The overall prevalence of metabolic syndrome (MetS) in the cohort was 32.6% (605 out of 1,851 participants), with women exhibiting a significantly higher prevalence at 38% (394 out of 1,037 women) compared to men at 26% (211 out of 814 men) (p<0.001). High waist circumference (≥102 cm for men and ≥88 cm for women) was strongly correlated with MetS, as 73.8% of individuals (314 out of 425 participants) in the high waist circumference group met the criteria for MetS, compared to 20.4% of individuals (291 out of 1,426 participants) in the non-high waist circumference group (<102 cm for men and <88 cm for women) (p<0.001). Furthermore, elevated blood pressure, elevated fasting glucose, and elevated fasting triglycerides were significantly more common in the high waist circumference group, than in the non-high waist circumference group (p<0.001). Conclusion The study highlights the significant association between central obesity and MetS in an urban Indian population, with notably higher prevalence in women. Waist circumference is a critical determinant of MetS and should routinely be measured, with significant application especially in resource-limited settings for early detection and intervention.

In motor learning, augmented feedback (AF) is the information provided by sources outside the body and encompasses visual feedback, auditory feedback, and multimodal augmented feedback. This review aims to examine the most recent evidence on these different modality types in healthy and diseased populations and athletes. The reporting of this review was guided by the standards of the \"Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA)\" statement with the aim to examine the most recent evidence on these feedback types in healthy and diseased populations and athletes. The literature search for this review has been limited to electronic journals with the search engines ISI Web of Knowledge, OvidSP EMBASE, and PubMed databases. This review considers visual feedback as the cornerstone of all augmented feedback types by citing its superiority in learning complex skills by medical students and balance maintenance by older adults. The review also deciphers the role of auditory augmented feedback in encumbering already burdened visual connections in the rehabilitation of patients with Parkinson's disease (PD) and prosthetic limbs and further argues why the multimodal feedback model seems to be the most efficient way to offer feedback in learning motor tasks by alluding to multifaceted \"skill training communication model\" in the prevention of sports injuries such as anterior cruciate ligament tears. Multimodal augmented feedback seems to be the most effective and appropriate way to give feedback during motor learning in healthy and diseased populations and athletes as its stimuli are perceived faster and tend to be retained longer compared with the unimodal stimuli of auditory and visual feedback mechanisms.