Restoration and rehabilitation of degraded land in arid and semiarid environments: Editorial

info:eu-repo/semantics/publishedVersio

Augmenting Control over Exploration Space in Molecular Dynamics Simulators to Streamline De Novo Analysis through Generative Control Policies

This study introduces the P5 model - a foundational method that utilizes reinforcement learning (RL) to augment control, effectiveness, and scalability in molecular dynamics simulations (MD). Our innovative strategy optimizes the sampling of target polymer chain conformations, marking an efficiency improvement of over 37.1%. The RL-induced control policies function as an inductive bias, modulating Brownian forces to steer the system towards the preferred state, thereby expanding the exploration of the configuration space beyond what traditional MD allows. This broadened exploration generates a more varied set of conformations and targets specific properties, a feature pivotal for progress in polymer development, drug discovery, and material design. Our technique offers significant advantages when investigating new systems with limited prior knowledge, opening up new methodologies for tackling complex simulation problems with generative techniques.Comment: ICML 2023 Workshop on Structured Probabilistic Inference (SPIGM) and Generative Modeling, of the International Conference of Machine Learning (ICML

Pedestrian level of service: the impact of social groups on pedestrian flow characteristics

A comprehensive measure of the level of pedestrian comfort can lead to an improved design of public spaces, to the appropriate dimensioning of urban infrastructure (such as airports, stations and commercial centers), and, most importantly, to a design that is more responsive to people and to that very fundamental human activity: walking. The planning and design of the pedestrian environment is based on pedestrian Levels of Service (LOS). These levels currently classify the level of comfort based on space available for movement and speed (and delay, in case of crosswalks). Guidance is provided for different area types and times of day. Although many methods of assessing pedestrian LOS have been developed, all these do not consider spontaneous pedestrian groups. However, social groups, such as friends, couples, colleagues and families, represent an important component of urban crowds. The paper presents first, an overview of the current methods for assessing pedestrian environment LOS. Then the paper presents the application of the HCM method for the evaluation of a selected site LOS. The calculation is based on collected measurements of pedestrian flow. Some critical issues and inconsistencies result. These have been reviewed and read taking into account the presence of groups in pedestrian flows

Burden and challenges of heart failure in patients with chronic kidney disease. A call to action

Patients with the dual burden of chronic kidney disease (CKD) and chronic congestive heart failure (HF) experience unacceptably high rates of symptom load, hospitalization, and mortality. Currently, concerted efforts to identify, prevent and treat HF in CKD patients are lacking at the institutional level, with emphasis still being placed on individual specialty views on this topic. The authors of this review paper endorse the need for a dedicated cardiorenal interdisciplinary team that includes nephrologists and renal nurses and jointly manages appropriate clinical interventions across the inpatient and outpatient settings. There is a critical need for guidelines and best clinical practice models from major cardiology and nephrology professional societies, as well as for research funding in both specialties to focus on the needs of future therapies for HF in CKD patients. The implementation of crossspecialty educational programs across all levels in cardiology and nephrology will help train future specialists and nurses who have the ability to diagnose, treat, and prevent HF in CKD patients in a precise, clinically effective, and cost-favorable manner.Los pacientes con enfermedad renal crónica (ERC) que desarrollan insuficiencia cardíaca (IC) congestiva crónica presentan cifras inaceptablemente altas de síntomas, hospitalización y mortalidad. Actualmente, se echan en falta iniciativas institucionales dirigidas a identificar, prevenir y tratar la IC en los pacientes con ERC de manera multidisciplinar, prevaleciendo las actuaciones de las especialidades individuales. Los autores de este artículo de revisión respaldan la necesidad de crear equipos multidisciplinares cardiorrenales, en los que participen nefrólogos y enfermeras renales, que gestionen colaborativamente las intervenciones clínicas apropiadas en los entornos de pacientes con ERC e IC hospitalizados y ambulatorios. Es necesario y urgente que se elaboren guías y modelos de práctica clínica sobre la ERC con IC por parte de las sociedades profesionales de cardiología y nefrología, así como financiación para la investigación concertada entre ambas especialidades sobre la necesidad de futuros tratamientos para la IC en pacientes con ERC. La implementación de programas educativos cardiorrenales a todos los niveles en cardiología y nefrología ayudará a formar a los futuros especialistas y enfermeras para que tengan la capacidad de diagnosticar, tratar y prevenir la IC en pacientes con ERC de manera precisa, clínicamente efectiva y económicamente favorabl

Wage inequality, segregation by skill and the price of capital in an assignment model

Some pieces of empirical evidence suggest that in the U.S., over the last few decades, (i) wage inequality between-plants has risen much more than wage inequality within-plants and (ii) there has been an increase in the segregation of workers by skill into separate plants. This paper presents a frictionless assignment model in which these two features can be explained simultaneously as the result of the decline in the relative price of capital. Additional implications of the model regarding the skill premium and the dispersion in labor productivity across plants are also consistent with the empirical evidence. [resumen de autor

Mortality from gastrointestinal congenital anomalies at 264 hospitals in 74 low-income, middle-income, and high-income countries: a multicentre, international, prospective cohort study

Summary Background Congenital anomalies are the fifth leading cause of mortality in children younger than 5 years globally. Many gastrointestinal congenital anomalies are fatal without timely access to neonatal surgical care, but few studies have been done on these conditions in low-income and middle-income countries (LMICs). We compared outcomes of the seven most common gastrointestinal congenital anomalies in low-income, middle-income, and high-income countries globally, and identified factors associated with mortality. Methods We did a multicentre, international prospective cohort study of patients younger than 16 years, presenting to hospital for the first time with oesophageal atresia, congenital diaphragmatic hernia, intestinal atresia, gastroschisis, exomphalos, anorectal malformation, and Hirschsprung’s disease. Recruitment was of consecutive patients for a minimum of 1 month between October, 2018, and April, 2019. We collected data on patient demographics, clinical status, interventions, and outcomes using the REDCap platform. Patients were followed up for 30 days after primary intervention, or 30 days after admission if they did not receive an intervention. The primary outcome was all-cause, in-hospital mortality for all conditions combined and each condition individually, stratified by country income status. We did a complete case analysis. Findings We included 3849 patients with 3975 study conditions (560 with oesophageal atresia, 448 with congenital diaphragmatic hernia, 681 with intestinal atresia, 453 with gastroschisis, 325 with exomphalos, 991 with anorectal malformation, and 517 with Hirschsprung’s disease) from 264 hospitals (89 in high-income countries, 166 in middleincome countries, and nine in low-income countries) in 74 countries. Of the 3849 patients, 2231 (58·0%) were male. Median gestational age at birth was 38 weeks (IQR 36–39) and median bodyweight at presentation was 2·8 kg (2·3–3·3). Mortality among all patients was 37 (39·8%) of 93 in low-income countries, 583 (20·4%) of 2860 in middle-income countries, and 50 (5·6%) of 896 in high-income countries (p<0·0001 between all country income groups). Gastroschisis had the greatest difference in mortality between country income strata (nine [90·0%] of ten in lowincome countries, 97 [31·9%] of 304 in middle-income countries, and two [1·4%] of 139 in high-income countries; p≤0·0001 between all country income groups). Factors significantly associated with higher mortality for all patients combined included country income status (low-income vs high-income countries, risk ratio 2·78 [95% CI 1·88–4·11], p<0·0001; middle-income vs high-income countries, 2·11 [1·59–2·79], p<0·0001), sepsis at presentation (1·20 [1·04–1·40], p=0·016), higher American Society of Anesthesiologists (ASA) score at primary intervention (ASA 4–5 vs ASA 1–2, 1·82 [1·40–2·35], p<0·0001; ASA 3 vs ASA 1–2, 1·58, [1·30–1·92], p<0·0001]), surgical safety checklist not used (1·39 [1·02–1·90], p=0·035), and ventilation or parenteral nutrition unavailable when needed (ventilation 1·96, [1·41–2·71], p=0·0001; parenteral nutrition 1·35, [1·05–1·74], p=0·018). Administration of parenteral nutrition (0·61, [0·47–0·79], p=0·0002) and use of a peripherally inserted central catheter (0·65 [0·50–0·86], p=0·0024) or percutaneous central line (0·69 [0·48–1·00], p=0·049) were associated with lower mortality. Interpretation Unacceptable differences in mortality exist for gastrointestinal congenital anomalies between lowincome, middle-income, and high-income countries. Improving access to quality neonatal surgical care in LMICs will be vital to achieve Sustainable Development Goal 3.2 of ending preventable deaths in neonates and children younger than 5 years by 2030

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Data based rules of public space pedestrian motion

Thesis: S.M., Massachusetts Institute of Technology, Department of Architecture, 2015.Title as it appears in MIT Commencement Exercises program, June 5, 2015: Space and motion : the case of pedestrian in public spaces. Cataloged from PDF version of thesis.Includes bibliographical references (pages 106-107).The understanding of space relies on motion, as we experience space by crossing it. While in motion we sense the environment in time, interacting with space. The vision of this thesis is to incorporate people's motion into architecture design process, enabled by technology. Simulation tools that introduce human motion into the design process in early stages are rare to nonexistent. Available tools are typically used for deterministically visualizing figures and simulating pedestrians with the goal of analyzing emergency exits or egress. Such simulations are built without consideration for non-goal oriented interaction with space; this presents a gap for design. Additionally, simulations are generally governed by assumptions regarding people's motion behavior or by analogous models such as collision avoidance methods. However, the use of data from people can elucidate spatial behavior. Advancements in depth camera sensors and computer vision algorithms have eased the task of tracking human movements to millimetric precision. This thesis proposes two main ideas: creating statistics from people's motion data for grounding simulations and measuring such motion in relation to space, developing a Space- Motion Metric. This metric takes pedestrian motion and spatial features as input, seeks actions composed by speed, time, gestures, direction, shape and scale. The actions are elaborated as Space-Motion Rules through substantial data analysis. The non-prescriptive combination of the rules generates a non-deterministic behavior focused on design. This research maps, quantifies, and formulates pedestrian motion correlation with space and questions the role of data for projecting what space could be.by Paloma Gonzalez Rojas.S.M

Machine Learning Simulation of Pedestrians Exploring the Built Environment

This dissertation explores a new method to model human navigational behavior when engaging with the built environment, with the intent of informing architectural design. A computational process is proposed to produce a generalizable Agent that navigates and explores novel complex environments while interacting with its surroundings. Current modeling software can effectively simulate pedestrian movement. However, it does not provide other simulations that are critical to the design of architecture such as exploration. Exploratory behavior is especially relevant for architects who seek to predict, to a feasible degree, the interaction between people and newly designed spaces; humans investigating new environments and paths to compelling architectural features. This dissertation demonstrates how machine learning methods identify human exploratory trajectories and map such data to Agent navigational behavior. Several Machine Learning techniques were applied, including Computer Vision, Bayesian Probability Programming, Density-Based Clustering, and Reinforcement and Imitation Learning. This data-driven method included human trajectory data and three-dimensional site data, collected through fieldwork in Machu Picchu, located in Cusco, Peru. The method had two sections Data Production and Model Development, which resulted in a trained Navigational Agent. Finally, validation tests were proposed and conducted to evaluate the Agent's behavior. The proposed navigational Agent initially demonstrated generalizable behavior, as when exploring unseen complex environments that it was not trained in. Then, by applying machine learning and analysis of the site-specific data, the human trajectory data was assigned with exploratory intentions of the visitors when approaching compelling architectural features. After the Agent accommodated general behaviors, it demonstrated that site-specific data expanded its behaviors towards simulating human behaviors on the site. The contributions of this dissertation consist of a pedestrian simulation method, a trained navigational Agent, human trajectory data classification method, human trajectory datasets, three-dimensional site models, and finally, theoretical analysis of a tool that simulate pedestrians’ behavior for architectural design. This dissertation uniquely combined these existing machine learning methods and constitutes an important step in developing computational tools to predict human behavior in architectural space.Ph.D

Pedestrian modelling: autonomy and communication needs

A better understanding of pedestrian movement can lead to an improved design of public spaces, to the appropriate dimensioning of urban infrastructure (such as airports, stations and commercial centers), and, most importantly, to a design that is more responsive to people and to that very fundamental human activity: walking. Walking is a highly communicative and social activity: we walk with other people and meet strangers, friends and neighbors. The potential for such communication is in itself a measure of the quality of the space. However social integrations among pedestrians have been largely neglected in the analysis and in the planning process. The research aims at modeling pedestrian needs, taking into account a more inclusive spatial behavior which includes both autonomy needs of pedestrian walking alone towards a target and communication needs of people walking in groups towards a target