ethicalabs/Research-Intent-Collab huggingface dataset:
Parallel Genetic Algorithm and High Performance Computing to Solve the Intercity Railway Alignment Optimization Problem

Despite the advances in solving the Railway Alignment Optimization (RAO) problem, the computational burden of the current algorithms to estimate new intercity connections of minimum cost is still an issue. This paper proposes a parallel Genetic Algorithm framework running on a high performance computing environment to solve the RAO problem while minimizing the costs of new railway alignments constrained by the geometric parameters required to run trains with different average speeds. The framework was applied to new connections between Brazilian cities and the results show that it is capable of providing accurate estimations compared to the international experience. From the computational aspect, the parallel computing approach drastically reduces the running times in the cases studied. However, scaling the computing infrastructure to more than 5 machines running in parallel may not be advantageous since the running times do not decrease significantly when more virtual machines are available.
What is an interoperability bus for health information exchange?

Interoperability in healthcare is a requirement for effective communication between entities, to ensure timely access to up-to-date medical information and knowledge about patients and therefore facilitate consistent patient care. An interoperability bus for healthcare (BIS) is a software and hardware architecture model that facilitates the exchange of health information between different information systems, such as electronic health records (EHR), laboratory information systems (LIS), medication management systems, electronic prescription, among other health care applications. This is commonly based on the Enterprise Service Bus (ESB) middleware software architecture as a solution for three of the four levels of interoperability for health information systems: foundational, structural and semantic.  This type of technological infrastructure is designed to allow communication and data exchange with a principle of technological neutrality, ensuring that healthcare providers have access to the information they need to provide effective patient care, empowering the citizen on the value of your health data to improve traceability and healthcare.  This document contains a practical guide to have a greater understanding of what a Health Interoperability Bus (BIS) is, what its characteristics are and why it is necessary to consider this type of solutions to have a greater impact on the health of populations. of the countries of Latin America and the Caribbean. Likewise, it aims to guide those governments and entities that are developing acquisition processes for this type of solutions, those who are in charge of auditing, transparency of investments for financing and accountability, as well as the end user of health services who directly or indirectly finance health care.
The power spectrum of the cosmic microwave background Kolmogorov maps: possible clue to correlation of voids

A &amp; A (Lett.) (accepted), 4 pages, 3 figs
Photorealistic Video Generation with Diffusion Models

Project website https://walt-video-diffusion.github.io/
Social media diet in adolescence: effects on mental health and eating behaviour

In the digital age, adolescents are constantly exposed to viral content promoting unrealistic beauty standards and unhealthy eating habits. This article examines the concept of the "social media diet" defined as the selective or excessive consumption of nutrition-related content, body image trends, and dietary fads on digital platforms [e.g., "What I Eat in a Day" videos, ”detox challenges”] and its bidirectional impact on teens’ mental and physical health. Through a systematic literature review of studies from psychology, nutrition, and digital media, we identify key mechanisms by which social media influences body perception, eating behaviours [e.g., orthorexia, binge eating], and self-esteem. The findings underscore the need for a multidisciplinary approach to foster healthier social media consumption among adolescents. The analysis reveals that adolescents, due to their developmental vulnerability and heightened sensitivity to peer comparison, are particularly susceptible to internalizing distorted ideals portrayed online. Exposure to idealized body types and restrictive eating patterns may lead to increased anxiety, body dissatisfaction, and the normalization of disordered eating behaviours. Simultaneously, the pursuit of social validation through likes and comments often reinforces harmful behaviours and perpetuates a cycle of comparison and self-criticism. Findings underscore the need for a multidisciplinary approach combining mental health support, media education, and nutritional consulting to foster healthier social media consumption among adolescents.
Resilience at the Core: Critical Infrastructure Protection Challenges, Priorities and Cybersecurity Assessment Strategies

The importance of a nation’s infrastructure is a vital core for economic growth, development, and innovation. Health, wealth, access to education, public safety, and helping prepare for global crises like pandemics are all dependent on functioning and reliable infrastructures. In decades, the substantial threats affecting infrastructures globally whether in the form of extreme weather, Covid-19 pandemic, or the threats of state and non-state actors’ hackers, demanded urgency in building resilience infrastructures both during crises and in more stable conditions. At the same time, the adoption of emerging and innovative technologies boosts the development of the infrastructures using information, communication, and technology (ICT) platform. This shift accelerated its evolution toward digitization where interdependent and interconnected cyberspace demands collaborative and holistic strategies in protecting critical and high risks infrastructure assets from a growing number of disruptive cyberattacks. These ever-evolving cyber threats are creating increasingly dangerous and targeted cyberattacks to damage or disrupt the critical infrastructures delivering vital services to government, energy, healthcare, transportation, telecommunication, and other critical sectors. The infrastructure’s high risks assets present serious challenges and are crucial to safety, efficiency, and reliability. Any nation must recognize and determine how to cope with any type of threats to their critical infrastructure as well as the strategies to remain resilient. This article first describes the challenges and the need for critical infrastructure protection including the related global risks challenges. It then reviews the United Nations, the European Union, and the United States’ strategies, priorities, and urgencies of critical infrastructure protection. Subsequently, it surveys the critical infrastructure protection resilience strategies including ISO, IEC, ISA, NIST, CAF and CMM frameworks.
Failure Analysis towards Reliable Performance of Aero-Engines

Aero-engines are critical components whose reliable performance decides the primary safety of an aircrafthelicopter. This is met by rigorous maintenance schedule with periodic inspection/nondestructive testing of various engine components. In spite of these measures, failure of areo-engines do occur rather frequently in comparison to failure of other components. Systematic failure analysis helps one to identify root cause of the failure, thus enabling remedial measures to prevent recurrence of such failures. Turbine blades made of nickel or cobalt-based alloys are used in aero-engines. These blades are subjected to complex loading conditions at elevated temperatures. The main causes of failure of blades are attributed to creep, thermal fatigue and hot corrosion. Premature failure of blades in the combustion zone was reported in one of the aero-engines. The engine had both the compressor and the free-turbine in a common shaft. Detailed failure analysis revealed the presence of creep voids in the blades that failed. Failure of turbine blades was also detected in another aero-engine operating in a coastal environment. In this failure, the protective coating on the blades was cracked at many locations. Grain boundary spikes were observed on these locations. The primary cause of this failure was the hot corrosion followed by creep damage.
For principled model fitting in mathematical biology

The mathematical models used to capture features of complex, biological systems are typically non-linear, meaning that there are no generally valid simple relationships between their outputs and the data that might be used to validate them. This invalidates the assumptions behind standard statistical methods such as linear regression, and often the methods used to parameterise biological models from data are ad hoc. In this perspective, I will argue for an approach to model fitting in mathematical biology that incorporates modern statistical methodology without losing the insights gained through non-linear dynamic models, and will call such an approach principled model fitting. Principled model fitting therefore involves defining likelihoods of observing real data on the basis of models that capture key biological mechanisms.
One Health best practices for addressing health threats at the human–animal–environment interface, with focus on the Eastern Mediterranean Region

Abstract                   One Health threats at the human–animal–environment interface involve zoonotic diseases that spread from animals to humans and may directly impact humans through their intake of food and water or from the environment. The function of One Health is to enhance collaboration, coordination, communication and capacity building among the human health, animal health and environmental sectors, to provide effective disease prevention and control programs and to identify recommendations and practical action plans. Information in this study was compiled from Google Scholar and PubMed to assess the success of the implementation of the One Health approach worldwide. This comprehensive literature review included only peer-reviewed articles published in English within the past 10 y that addressed One Health practices relevant to the Eastern Mediterranean Region. The latest data show that 75% of newly emerging infectious diseases have animal origins, that domestic animals or wildlife are the source of 60% of these pathogens and that animals are the source of 80% of pathogens that pose a bioterrorism threat. Thus the significance of the One Health approach remains ever more urgent to address and mitigate these threats. Country studies from India, Kenya, Pakistan, Qatar, Saudi Arabia, Uganda and Zambia showcased multisectoral coordination and collaboration through technical activities in epidemiological surveillance, emergency preparedness and response, joint leadership and risk assessment in response to an outbreak. The World Health Organization Regional Office of the Eastern Mediterranean has rolled out the One Health framework, with some degree of success in certain countries, in response to epidemics, disease prioritization or as a road map for collaboration. However, other countries in the region have yet to adopt the One Health approach. Overall, One Health has demonstrated its value in protecting animals, humans and the environment by pooling expertise from different fields to prevent and control future pandemics.
Estimating acoustic peak positions in the cosmic microwave background anisotropy power spectrum

Abstract                                        We present a simple formula for estimating the positions of acoustic peaks in the temperature power spectrum of the cosmic microwave background anisotropies:                     l                      = (                     n                      − 1/4)                     π                     /                     θ                     ∗                     , where                     l                     is the multipole moment in spherical harmonics,                     n                     is a positive integer, and                     θ                     ∗                     is the angular acoustic scale. Using published cosmological parameters, we calculate                     θ                     ∗                      = 1/96.35. Our estimates for the first seven acoustic peaks positions agree with the 2018 results of ESA’s Planck mission within a 3% of relative error.
Privacy, Personalization, and Price Discrimination

Abstract                We study a bilateral trade setting in which a buyer has private valuations over a multi-product seller’s inventory. We introduce the notion of an incentive-compatible market segmentation (IC-MS)—a market segmentation compatible with the buyer’s incentives to voluntarily reveal their preferences. Our main result is a characterization of the buyer-optimal IC-MS. It is partially revealing, comprised primarily of pooling segments wide enough to keep prices low but narrow enough to ensure trade over relevant products. We use our results to study a novel design problem in which a retail platform seeks to attract consumers by calibrating the coarseness of its search interface. Our analysis speaks directly to consumer privacy and the debate regarding product steering versus price discrimination in online retail.
Gene family amplification facilitates adaptation in freshwater Unionid bivalve Megalonaias nervosa

As organisms are faced with intense rapidly changing selective pressures, new genetic material is required to facilitate adaptation. Among sources of genetic novelty, gene duplications and transposable elements (TEs) offer new genes or new regulatory patterns that can facilitate evolutionary change. With advances in genome sequencing it is possible to gain a broader view of how gene family proliferation and TE content evolve in non-model species when populations become threatened. Freshwater bivalves (Unionidae) currently face severe anthropogenic challenges. Over 70% of species in the United States are threatened, endangered or extinct due to pollution, damming of waterways, and overfishing. We have created a reference genome for M. nervosa to determine how genome content has evolved in the face of these widespread environmental challenges. We observe a burst of recent transposable element proliferation causing a 382 Mb expansion in genome content. Gene family expansion is common, with a duplication rate of 1.16 x 10^-8 per gene per generation. Cytochrome P450, ABC transporters, Hsp70 genes, von Willebrand proteins, chitin metabolism genes, mitochondria eating proteins, and opsin gene families have experienced significantly greater amplification and show signatures of selection. We use evolutionary theory to assess the relative contribution of SNPs and duplications in evolutionary change. Estimates suggest that gene family evolution may offer an exceptional substrate of genetic variation in M. nervosa, with Psgv=0.185 compared with Psgv=0.067 for single nucleotide changes. Hence, we suggest that gene family evolution is a source of "hopeful monsters" within the genome that facilitate adaptation.
Phase transitions of some discrete models in statistical mechanics

We studied in this thesis the critical behaviours of percolation and directed percolation models using Monte Carlo simulations, including estimating percolation thresholds, critical exponents, and various universal amplitudes. In addition, we examined the geometric structure of percolation clusters, and verified the critical behaviours of a leaf-excluded percolation model belong to the standard percolation universality class. Finally, we rigorously studied an n-component face-cubic model on the complete graph, by a large deviations analysis. We proved limit theorems for the standard face-cubic model, and studied phase diagrams for the general face-cubic model.
Using mHealth Tools to Improve Access and Coverage of People With Public Health Insurance and High Cardiovascular Disease Risk in Argentina: A Pragmatic Cluster Randomized Trial

Background                            Control of cardiovascular disease (               CVD               ) risk factors is suboptimal in Argentina, despite the government's provision of free blood pressure and cholesterol‐lowering medications for people without private insurance. We assessed whether community health workers’ use of an integrated               mH               ealth tool encourages patients to attend visits at primary care clinics to improve               CVD               risk management in 2 provinces of Argentina.                                                Methods and Results                            We conducted a pragmatic cluster randomized trial, with primary care clinics randomly assigned to intervention or control. Eligible people were aged 40 to 79 years, lived in the catchment area of primary care clinics, possessed a mobile phone for personal use, had public health coverage, and a 10‐year               CVD               risk ≥10%. In the control arm, community health workers screened for               CVD               risk using a paper‐based tool and encouraged high‐risk people to present to the primary care clinics for care. In the intervention arm, community health workers used the               mH               ealth tool to calculate               CVD               risk and confirm a scheduled physician appointment. Primary outcomes were the proportion of participants who attended a baseline visit and completed at least 1 follow‐up, respectively. We enrolled 755 people (376 interventions; 379 controls). Intervention participants were significantly more likely to complete baseline visits (49.4% versus 13.5%,               P               value 0.0008) and follow‐up visits (31.9% versus 7.7%;               P               value 0.0041). The use of chronic medication and current smoking were significant predictors of primary outcomes.                                                Conclusions                            Use of               mH               ealth tools identifies patients at high               CVD               risk in their home, increases the likelihood of participating in chronic               CVD               risk factor management, and strengthens referrals.                                                Clinical Trial Registration                            URL               :               http://www.clinicaltrials.gov               . Unique identifier:               NCT               02913339.
Development and Testing of LoRaWAN Sensor Network for Internet of Things Applications

There are several wireless technologies that can be used for Internet of Things. Among these are Bluetooth, Cellular and Low Power Wide Access Network (LPWAN). Devices connected to LPWAN may work longer and be placed in remote areas. One of the implementations of LPWAN is LoRaWAN. In the current work, an infrastructure managed by Altibox AS has been applied for connecting sensors in one network using LoRaWAN protocol. A monitoring and logging application combining services provided by Altibox and open-source tool Node-RED has been setup to present measurements from sensors. Comparison of applications has shown that application from a network provider suits best for the devices under its management. However, it may be more convenient to use other solutions if data from unrelated providers are to be collected and presented in one place.
Technologies and Educational Resources of the Future: Generative AI and Learning Analytics in the Classroom and Beyond

Learning analytics has become an increasingly prominent aspect of 21st century educational research and practice. In this article, I will discuss some of the key applications of learning analytics, as well as emerging opportunities to use learning analytics to understand and support learning, engagement, and long-term life success. I will also discuss how recent developments in generative artificial intelligence are impacting learning analytics methods and uses. At the same time, I will discuss the new challenges brought by the growing use of generative AI and the new opportunities to influence both research and practice.                   Учебная аналитика становится всё более важным аспектом образовательных исследований и практики XXI века. В данной статье рассматриваются ключевые области применения учебной аналитики, а также новые возможности её использования для понимания и поддержки процессов обучения, вовлечённости учащихся и их долгосрочного жизненного успеха. Особое внимание уделяется тому, как последние достижения в области генеративного искусственного интеллекта влияют на методы и применение аналитики обучения. Наряду с этим анализируются вызовы, возникающие в связи с распространением генеративного ИИ, и обсуждаются перспективы, открывающиеся как для научных исследований, так и для практики в образовании.                   Оқытудағы аналитика – XXI ғасырда білім берудегі зерттеулер мен тәжірибенің аса маңызды аспектілерінің бірі болып табылады. Мақалада оқудағы аналитика қолданылатын негізгі салалар, оқыту процесін, оқушылардың белсенді қатысуын, олардың өмірде табысты болуын қолдауға бағытталған жаңа мүмкіндіктер қарастырылады. Сонымен қатар генеративті жасанды интеллект саласындағы соңғы жетістіктердің оқытудағы аналитика әдістеріне және оның қолданылуына қалай әсер ететініне тоқталамыз. Генеративті ЖИ-дің кеңінен таралуы білім беру саласына жаңа мүмкіндіктермен қатар бірқатар сын-талаптарды да алып келуде. Мақалада осы жаңа сын-талаптар және оларды еңсеру жолдары, сондай-ақ зерттеу және білім беру тәжірибесін жетілдірудегі әлеуеті талқыланады.
Analysis of non-Markovian repairable fault trees through rare event simulation

AbstractDynamic fault trees (DFTs) are widely adopted in industry to assess the dependability of safety-critical equipment. Since many systems are too large to be studied numerically, DFTs dependability is often analysed using Monte Carlo simulation. A bottleneck here is that many simulation samples are required in the case of rare events, e.g. in highly reliable systems where components seldom fail. Rare event simulation (RES) provides techniques to reduce the number of samples in the case of rare events. In this article, we present a RES technique based on importance splitting to study failures in highly reliable DFTs, more precisely, on a variant of repairable fault trees (RFT). Whereas RES usually requires meta-information from an expert, our method is fully automatic. For this, we propose two different methods to derive the so-called importance function. On the one hand, we propose to cleverly exploit the RFT structure to compositionally construct such function. On the other hand, we explore different importance functions derived in different ways from the minimal cut sets of the tree, i.e., the minimal units that determine its failure. We handle RFTs with Markovian and non-Markovian failure and repair distributions—for which no numerical methods exist—and implement the techniques on a toolchain that includes the RES engine FIG, for which we also present improvements. We finally show the efficiency of our approach in several case studies.