Miracle-dz/UniFAR-FTUs huggingface dataset:
Storm Surge Mapping for Montego Bay, Jamaica

The General Secretariat of the Organization of American States (OAS), in collaboration with the USAID, has sponsored the Caribbean Disaster Mitigation Project (CDMP). As part of this CDMP, a storm hazard pilot project was developed for Montego Bay. The intention of this project was to fine-tune the surge computation and analysis procedures, so that these could be used with confidence in other countries of the Caribbean. In addition, present regulatory and risk assessment practices were evaluated in the light of the predicted storm surge findings.
Encoded sewing soft textile robots

Incorporating soft actuation with soft yet durable textiles could effectively endow the latter with active and flexible shape morphing and motion like mollusks and plants. However, creating highly programmable and customizable soft robots based on textiles faces a longstanding design and manufacturing challenge. Here, we report a methodology of encoded sewing constraints for efficiently constructing three-dimensional (3D) soft textile robots through a simple 2D sewing process. By encoding heterogeneous stretching properties into three spatial seams of the sewed 3D textile shells, nonlinear inflation of the inner bladder can be guided to follow the predefined spatial shape and actuation sequence, for example, tendril-like shape morphing, tentacle-like sequential manipulation, and bioinspired locomotion only controlled by single pressure source. Such flexible, efficient, scalable, and low-cost design and formation methodology will accelerate the development and iteration of soft robots and also open up more opportunities for safe human-robot interactions, tailored wearable devices, and health care.
Post-reflux swallow-induced peristaltic wave index: a new parameter for the identification of non-acid gastroesophageal reflux-related chronic cough

Background: The current available diagnostic criteria for gastroesophageal reflux-related chronic cough (GERC) dominated by non-acid reflux is imperfect. The post-reflux swallow-induced peristaltic wave index (PSPWI) is a parameter reflecting esophageal clearance function. Objectives: This study aims to investigate its diagnostic value for non-acid GERC. Design: This study sought to compare the diagnostic value of PSPWI in different types of GERC, particularly non-acid GERC, and explore the clinical significance of PSPWI in the diagnosis of non-acid GERC through diagnostic experiments. Methods: A retrospective analysis was performed based on 223 patients with suspected GERC who underwent multichannel intraluminal impedance-pH monitoring (MII-pH) in the outpatient clinic of our department from August 2016 to June 2021. Their clinical information, laboratory test results, and treatment responses were assessed and the underlying etiologies of chronic cough were categorized. The predictive value of the PSPWI in diagnosing different types of GERC, especially non-acid GERC, was analyzed and compared. Results: A total of 195 patients with chronic cough who met the inclusion criteria underwent MII-pH monitoring. 143 patients had a definitive diagnosis of GERC, including 98 with acid GERC and 45 with non-acid GERC. The diagnostic value of PSPWI alone was moderate for GERC with an area under the working curve (AUC) 0.760, but poor for non-acid GERC with an AUC of 0.569. However, PSPWI < 39.8% combining with acid exposure time (AET) ⩽ 6.2% demonstrated a moderate diagnostic value for non-acid GERC, with an AUC of 0.722. When PSPWI < 39.8% combined with a non-acid reflux ratio >68.75%, the diagnostic value for non-acid GERC was improved (AUCROC = 0.80 versus AUCROC = 0.722, p < 0.05), which was significantly superior to non-acid symptom index (AUCROC = 0.804 versus AUCROC = 0.550, p < 0.05) and non-acid symptom association probability (AUCROC = 0.804 versus AUCROC = 0.571, p < 0.05). Conclusion: PSPWI < 39.8% and AET ⩽ 6.2% have demonstrated good diagnostic value for non-acid GERC. The diagnostic value was further improved when combined with non-acid reflux ratio >68.75%.
Ciliary neurotrophic factor mediated growth of retinal ganglion cell axons on PGS/PCL scaffolds

Ciliary neurotrophic factor (CNTF) promotes survival and/or differentiation of a variety of neuronal cells including retinal ganglion cells (RGCs). Delivery of CNTF requires a suitable medium capable of mediating diffusion and premature release of CNTF within the target tissue. Polymeric tissue-engineered scaffolds have been readily used as substrates for cell transplantation, expansion, and differentiation and, as carriers of cell growth factors. Their functions to CNTF release for RGC proliferation have remained so far unexplored, especially to CNTF affinity to the scaffold and subsequent RGC fate. Electrospun poly(glycerol sebacate)/poly(ϵ-caprolactone) (PGS/PCL) biopolymer scaffolds have recently shown promising results in terms of supporting regeneration of RGC neurites. This work explores covalent immobilization of CNTF on PGS/PCL scaffold and the way immobilised CNTF mediates growth of RGC axons on the scaffold. An ex-vivo three-dimensional model of rodent optic nerve on PGS/PCL revealed that RGC explants cultured in CNTF mediated environment increased their neurite extensions after 20 d of cell culture employing neurite outgrowth measurements. The CNTF secretion on PGS/PCL scaffold was found bio-mimicking natural extracellular matrix of the cell target tissue and, consequently, has shown a potential to improve the overall efficacy of the RGC regeneration process.
ANÁLISE DE REDES DE COLABORAÇÃO CIENTÍFICA DOS DOCENTES DO PROGRAMA DE PÓS-GRADUAÇÃO EM EDUCAÇÃO MATEMÁTICA E TECNOLÓGICA DA UNIVERSIDADE FEDERAL DE PERNAMBUCO Scientific Collaboration Network Analysis of Pos-Graduation Program in Mathematics and Technology at Federal University of Pernambuco

O trabalho apresenta os resultados de uma pesquisa sobre a producao cientifica do Programa de Pos-Graduacao em Educacao Matematica da UFPE. Foram analisados artigos em uma perspectiva longitudinal em trienios entre 2007 e 2015. O objetivo foi identificar o padrao emergente de coautoria em artigos completos publicados nos estratos Qualis, e, indexados no Google Academico. As metodologias utilizadas foram a Analise de Redes Sociais (ARS) e os indicadores bibliometricos. Foi realizada uma revisao bibliografica sobre ARS, as aplicacoes em Educacao e o uso de metricas de bibliometria. A rede total tem uma estrutura radial. Em todos os trienios encontramos membros mais influentes, grau de centralidade e reciprocidade altos, configurando hubs. Os resultados indicam correlacao entre colaboracao e qualidade da producao por meio de citacoes. O programa desenvolveu intercâmbio entre as areas de pesquisa e presenca de autores externos, mostrando o caminho para novas pesquisas e adensamento da rede. Abstract This work presents results of coauthoship network analysis research of scientific production from professors from graduate program in mathematics and technology at Federal University of Pernambuco. We analyze bibliographic and technical work from coauthors available at Curriculo Lattes from National Council for Scientific and Technological Development (CNPq) with Longitudinal network data from triennial datasets from 2007 through 2015. The main purpose of this research was find emerging patterns between articles published at estrato Qualis and Google Academic, using social network analysis and bibliometrics methodologies. We analyze the datasets and the whole network is radial with low density. All triennials we find hubs and influential nodes with high level of degree centrality and reciprocity. The overall results suggest correlations between collaboration and the quality of articles, also indicates better citations at scientific databases. The graduate program developed internal projects and international partnerships, showing the route for new research endeavors and network growth.
Costs and cost-effectiveness of influenza illness and vaccination in low- and middle-income countries: A systematic review from 2012 to 2022

Background Historically, lack of data on cost-effectiveness of influenza vaccination has been identified as a barrier to vaccine use in low- and middle-income countries. We conducted a systematic review of economic evaluations describing (1) costs of influenza illness; (2) costs of influenza vaccination programs; and (3) vaccination cost-effectiveness from low- and middle-income countries to assess if gaps persist that could hinder global implementation of influenza vaccination programs. Methods and findings We performed a systematic search in Medline, Embase, Cochrane Library, CINAHL, and Scopus in January 2022 and October 2023 using a combination of the following key words: “influenza” AND “cost” OR “economic. ” The search included studies with publication years 2012 through 2022. Studies were eligible if they (1) presented original, peer-reviewed findings on cost of illness, cost of vaccination program, or cost-effectiveness of vaccination for seasonal influenza; and (2) included data for at least 1 low- or middle-income country. We abstracted general study characteristics and data specific to each of the 3 study types. Of 54 included studies, 26 presented data on cost-effectiveness, 24 on cost-of-illness, and 5 on program costs. Represented countries were classified as upper-middle income (UMIC; n = 12), lower-middle income (LMIC; n = 7), and low-income (LIC; n = 3). The most evaluated target groups were children (n = 26 studies), older adults (n = 17), and persons with chronic medical conditions (n = 12); fewer studies evaluated pregnant persons (n = 9), healthcare workers (n = 5), and persons in congregate living settings (n = 1). Costs-of-illness were generally higher in UMICs than in LMICs/LICs; however, the highest national economic burden, as a percent of gross domestic product and national health expenditure, was reported from an LIC. Among studies that evaluated the cost-effectiveness of influenza vaccine introduction, most (88%) interpreted at least 1 scenario per target group as either cost-effective or cost-saving, based on thresholds designated in the study. Key limitations of this work included (1) heterogeneity across included studies; (2) restrictiveness of the inclusion criteria used; and (3) potential for missed influenza burden from use of sentinel surveillance systems. Conclusions The 54 studies identified in this review suggest an increased momentum to generate economic evidence about influenza illness and vaccination from low- and middle-income countries during 2012 to 2022. However, given that we observed substantial heterogeneity, continued evaluation of the economic burden of influenza illness and costs/cost-effectiveness of influenza vaccination, particularly in LICs and among underrepresented target groups (e.g., healthcare workers and pregnant persons), is needed. Use of standardized methodology could facilitate pooling across settings and knowledge sharing to strengthen global influenza vaccination programs.
Reliability Mechanisms for Controllers in Real-Time Cyber-Physical Systems

Cyber-physical systems (CPSs) are real-world processes that are controlled by computer algorithms. We consider CPSs where a centralized, software-based controller maintains the process in a desired state by exchanging measurements and setpoints with process agents (PAs). As CPSs control processes with low-inertia, e.g., electric grids and autonomous cars, the controller needs to satisfy stringent real-time constraints. However, the controllers are susceptible to delay and crash faults, and the communication network might drop, delay or reorder messages. This degrades the quality of control of the physical process, failure of which can result in damage to life or property. Existing reliability solutions are either not well-suited for real-time CPSs or impose serious restrictions on the controllers. In this thesis, we design, implement and evaluate reliability mechanisms for real-time CPS controllers that require minimal modifications to the controller itself. We begin by abstracting the execution of a CPS using events in the CPS, and the two inherent relations among those events, namely network and computation relations. We use these relations to introduce the intentionality relation that uses these events to capture the state of the physical process. Based on the intentionality relation, we define three correctness properties namely, state safety, optimal selection and consistency, that together provide linearizability (one-copy equivalence) for CPS controllers. We propose a labeling mechanism called intentionality clocks that can be used by controllers and PAs to express the intentionality relation. Intentionality clocks are robust to delays and can be used with replicated controllers to establish a total order between the events. We use intentionality clocks to design a CPS controller and PAs that guarantee the state safety and optimal selection properties. Then, we design Quarts, an agreement algorithm that guarantees the consistency property among replicated controllers. Inconsistent controllers can issue setpoints that result in incorrect control of the process. So, agreement is typically achieved using consensus between the replicated controllers. This can add an unbounded-latency overhead. Quarts leverages the properties specific to CPSs to perform agreement using pre-computed priorities among sets of received measurements, resulting in a boundedlatency overhead with high availability. Using simulation, we show that availability of Quarts, with two replicas, is more than an order of magnitude higher than consensus. Intentionality clocks and Quarts together provide linearizability that enables active replication of the central controller. Using this result, we design Axo, a fault-tolerance
Podemos formar líderes responsables? : ¿podemos aprender algo de China y Singapur?

The author proposes that the development of "globally responsible leaders" is a categorical imperative and develops what are the challenges faced by business schools to develop such leaders. Then, he explores whether some learning could possibly be drawn from China and from Singapore, and in the last part, he proposes alternative actions to develop responsible leaders.
LAND SUBSIDENCE INDUCED BY RECENT ALLUVIA DEPOSITS IN YANGTZE RIVER DELTA AREA——A CASE STUDY OF SHANGHAI LINGANG NEW CITY

There are vast non-consolidated alluvia deposits freshly formed in estuary area of Yangtze River and nearby coastal area.The deposits contribute to land subsidence.Based on their distribution,two subsidence volumes of different kinds of deposits are respectively calculated due to their consolidation and underlayer soil consolidation.It is found that the subsidence induced by the deposits has a larger ratio of the total surface subsidence.And also the suggestions for the in-depth study on deposits are discussed in this paper.
A Virtual Class Tool for Facial Expressions Telemonitoring through Embedded Systems

In recent years, there has been a transition from face-to-face class meetings to videoconferences, which has been further expanded during the COVID-19 pandemic. In the area of education, remote classes entailed new advantages and some challenges – in one hand, allowing for an extended time and location flexibility – while, in the other hand, operating in a inexpressive, distanced, manner. Aiming to increase non-verbal communication in virtual class meetings, this research explores the technical feasibility and potential implementation challenges of developing a virtual class tool for facial expressions telemonitoring through embedded systems. As a suggested solution, a system which allows for a teacher to remotely follow the facial expressions of students through real-time rendered graphical data was developed. Technical experimental results include: an average recognition accuracy of 57%, for all facial expressions, peaking at 80% for happiness, in a median processing time of 2.85 seconds with a Raspberry Pi 4B, and of 0.572 seconds with a commodity computer. These findings highlight the technical viability of the implemented system, possibly allowing to decrease the lack of non-verbal communication in distanced learning.
Maritime Anomaly Detection within Coastal Waters Based on Vessel Trajectory Clustering and Naïve Bayes Classifier

Maritime anomaly detection is a key technique in intelligent vessel traffic surveillance systems and implementation of maritime situational awareness. In this paper, we propose a method which combines vessel trajectory clustering and Naïve Bayes classifier to detect anomalous vessel behaviour in the maritime surveillance system. A similarity measurement between vessel trajectories is designed based on the spatial and directional characteristics of Automatic Identification System (AIS) data, then the method of hierarchical and k-medoids clustering are applied to model and learn the typical vessel sailing pattern within harbour waters. The Naïve Bayes classifier of vessel behaviour is built to classify and detect anomalous vessel behaviour. The proposed method has been tested and validated on the vessel trajectories from AIS data within the waters of Xiamen Bay and Chengsanjiao, China. The results indicate that the proposed method is effective and helpful, thus enhancing maritime situational awareness in coastal waters.
Planning and Conducting Heuristic Evaluations with DUXAIT-NG

This workshop will offer participants the opportunity to engage in a face-to-face learning experience. The main objective of this workshop is to equip participants with the essential skills and knowledge necessary to plan and conduct heuristic evaluations using the DUXAIT-NG platform. The proposed workshop will have two main axes: the theoretical part, where the most relevant concepts on heuristic evaluations will be developed, and the method proposed by Granollers will be detailed. Also, how to carry out a heuristic evaluation under a defined process. In the second part, the practical one, participants will be introduced to the DUXAIT-NG platform, and its main features will be detailed in a practical way, as well as how this platform supports the evaluation process detailed in the theoretical part. In this section, participants will interact with the platform, and the planning, conduction, and analysis of a case study will be presented, with the active participation of the attendants.
Precipitation trends and teleconnections identified using quantile regressions over Xinjiang, China

Precipitation in Xinjiang, China, was modelled with covariates, such as time and climate indices, using quantile regressions. Compared to a frequentist quantile regression, a Bayesian quantile regression tended to generate smoother and narrower band confidence intervals of quantile regression coefficients, especially at extremely high and low quantile levels. A full picture of temporal trends at quantile levels from 0.01 to 0.99 indicates that the wet season (May to August) precipitation in Northern Xinjiang and the western regions of Southern Xinjiang showed statistically significant increases with different magnitudes over all quantile levels. However, the wet season precipitation in South‐eastern Xinjiang decreased at some quantile levels. The Eastern Atlantic/Western Russia (EAWR) pattern was the most significant large‐scale climate pattern that influenced wet season precipitation when compared to other studied patterns, i.e. the El Niño–Southern Oscillation (ENSO), the Atlantic Multidecadal Oscillation (AMO), the Pacific Decadal Oscillation (PDO), the Northern Oscillation (NO), the Arctic Oscillation (AO) and the North Atlantic Oscillation (NAO). The quantile regression coefficients associated with the EAWR index positively increased from low to high quantile levels. The ENSO significantly affected the extremely high wet season precipitation in Xinjiang. El Niño increased and La Niña decreased wet season precipitation in Northern Xinjiang, with different magnitudes at different quantile levels. Other climate patterns, i.e. the AMO, PDO, NO, NAO and AO, did not evidently affect the wet season precipitation conditional on the ENSO and EAWR. These findings suggest that the predictability of seasonal precipitation over Xinjiang can be improved by incorporating indices associated with the ENSO and EAWR as model predictors.
Selected TLR7/8 agonist and type I interferon (IFN‐α) cooperatively redefine the microglia transcriptome

Background Microglia, the primary immune cells of the central nervous system, exerts multiple functions to mediate many neurological diseases. Upon any detection of invading pathogen products (e.g., TLR agonists) or host-released signaling factors (e.g., interferon/IFN), these cells undergo an activation process to release large numbers of inflammatory substances that participate in inflammation and homeostasis. The profound effects of inflammation associated with TLR7/8 agonist Resiquimod (R848) and type 1 interferon (e.g., IFN-α)-induced macrophage and dendritic cell activation on biological outcomes have long been recognized. However, the underlying mechanisms are not well defined in microglial cells. Methods The present study investigated the molecular signatures of microglia and identified genes that are uniquely or synergistically expressed in R848-, IFN-αor R848 with IFN-α-treated primary microglial (PM) cells. We used RNA-sequencing, quantitative real-time PCR, and bioinformatics approaches to derive regulatory networks that control the transcriptional response of PM to R848, IFN-α and R848 with IFN-α. Results Our approach revealed that the inflammatory response in R848 with IFN-α-treated PM is faster and more intense than that in R848 or IFN-α-treated PM in terms of the number of differentially expressed genes and the magnitude of induction/repression. In particular, our integrative analysis enabled us to suggest the regulatory functions of TFs, which allowed the construction of a network model that explains how TLR7/8 and IFN-α-sensing pathways achieve specificity. Conclusion In conclusion, the systematic approach presented herein could be important to the understanding microglial activation-mediated molecular signatures induced by inflammatory stimuli related to TLR7/8, IFN-α or co-signaling, and associated transcriptional machinery of microglial functions and neuroinflammatory mechanisms.