Miracle-dz/UniFAR-FTUs huggingface dataset:
Too Late or Too Soon for School? The Impact of School Entry Age

Abstract The education laws of each country establish starting cutoff dates for compulsory education which could, potentially, affect students’ academic achievement. Specifically, they could be detrimental for those students whose birthday is just before the school entry cutoff, as they will be the youngest in their classroom, while it could boost the academic performance of those whose birthday is just after (the eldest ones). The present research paper analyses this issue in respect to students’ academic achievement using census and longitudinal data for the most populated region of Spain (Andalusia) with a regression discontinuity methodology. Our results show that those students who are the youngest in the classroom due to this school entry cutoff present lower academic achievement compared to the eldest students, an effect which is reduced while students advance in their education. This motivates policy recommendations aimed at checking students’ cognitive skills prior to their access to compulsory education and at letting parents choose whether or not to delay their children’s access to school in case they are not yet ready.
Nutritional Global Status and Its Impact in Crohn’s Disease

Abstract Background Malnutrition among inflammatory bowel disease (IBD) subjects is well documented in literature and may emerge from factors including inadequate dietary intake, malabsorption and disease activity. The aim of this study was to complete a comprehensive nutrition assessment and explore what possibilities may help bring a better quality of life for IBD subjects. Methods Nutritional status based on biochemical tests, body composition and body mass index (BMI). Food intake was assessed by an alternate 3-day food record and the adequacy of intake was evaluated according to national and international references. Clinical disease activity was evaluated by the Harvey-Bradshaw index and CRP levels. Results The study included 217 patients and 65 controls, where 54.4% of these patients were classified as normal weight with a mean BMI lower than controls (23.8 ± 4.9 versus 26.9 ± 4.8 kg/m2, P = 0.02). Patients with disease activity showed more overweight and obesity than patients with controlled disease. Vitamin B12 deficiency was present in 19% of Crohn’s disease (CD), mainly in patients with ileal commitment and small bowel resections. Anemia was present in 21.7% of patients, being more common in patients with active disease (25%) and bowel resection (23%). Regarding calorie intake (EI), CD group ingested more than controls (1986.3 ± 595.9 kcal versus 1701.8 ± 478.9 kcal; P = 0.003). Conclusions CD patients presented micronutrient deficiency when compared with controls, explained for other reasons than intake restrictions. Also, fat excess might have contributed to disease burden as continuously reported in the literature.
Decision Factors behind Cisco Networking Hardware Acceptance in Business Environments

Networking hardware might be considered a relatively unexposed enabler of the enormous success of the modern digital economy, and information technology of a global reach. The COVID-19 traffic spike across e-commerce portals puts further pressure on computer network component vendors and raises the bar regarding both performance and reliability. Therefore, the authors undertake a challenge of identifying factors influencing the level of Cisco switches acceptance among network administrators in business environments. To achieve that, Structural Equation Modelling is introduced. The feedback gathered from 205 study contributors enabled the authors to evaluate the significance of two domain-specific factors—Technological Innovation (TI) and Availability of Professional Training (APT). The APT was confirmed to have a significant impact on networking hardware acceptance. The study contributes to extending the decision-making rationale regarding the procurement of networking switches and shows the added value of technology-oriented professional training for job satisfaction and working efficiency.
X-ray-based Imaging for Characterizing Heterogeneous Gas Diffusion Layers for Polymer Electrolyte Membrane Fuel Cells

Characterization of gas diffusion layers (GDLs) for polymer electrolyte membrane (PEM) fuel cells informs modeling studies and the manufacturers of next generation fuel cell materials. Identifying the physical properties related to the primary functions of the modern GDL (thermal, electrical, and mass transport) is necessary for understanding the impact of GDL design choices. X-ray micro-computed tomographic reconstructions of GDLs were studied to isolate GDL surface morphologies. Surface roughness was measured for a wide variety of samples and a sensitivity study highlighted the scale-dependence of surface roughness measurements. Furthermore, a spatially resolved distribution map of polytetrafluoroethylene (PTFE) in the microporous layer (MPL), critical for water management and mass transport, was identified and the existence of PTFE agglomerations was highlighted. Finally, the impact of accelerated degradation on GDL wettability and water transport increases in liquid water accumulation and oxygen mass transport resistance were quantified as a result of accelerated GDL degradation.
Engaging leadership: Enhancing work engagement through intrinsic values and need satisfaction

Should leaders pay more attention to values? The present study aims to examine and explain the associations of engaging leadership (EL) with employees' perceptions of the organization's values, need fulfillment, and employee engagement. EL is a recent leadership concept drawing on self-determination theory, specifically on the fulfillment of the basic psychological needs of autonomy, competence, and relatedness. We expected EL to associate with employees perceiving the values of their organization as more intrinsic (e.g., care for others, contributing to making the world a better place, stimulating personal growth), which would satisfy employees' basic psychological needs and fuel work engagement, rather than as extrinsic (financial success, power, status). Study 1 detailed the model using a cross-sectional study design ( N = 436), and, as expected, structural equation modeling identified a positive path from leadership to work engagement via perceived intrinsic organizational values and subsequent satisfaction of the need for autonomy. EL associated negatively with extrinsic organizational values. Study 2 corroborated outcomes of study 1 through a longitudinal study across three time-points ( N = 69) in a cross-lagged panel model and found specific directionality from leadership to perceived intrinsic values. Implications for leadership and motivation are discussed.
Reinforcement Learning for Electric Vehicle Charging using Dueling Neural Networks

We consider the problem of coordinating the charging of an entire fleet of electric vehi1 cles (EV), using a model-free approach, i.e., purely data-driven reinforcement learning (RL). The 2 objective of the RL-based control is to optimize charging actions, while fulfilling all EV charging 3 constraints (e.g., timely completion of the charging). In particular, we focus on batch-mode learn4 ing and adopt fitted Q-iteration (FQI). A core component in FQI is approximating the Q-function 5 using a regression technique, from which the policy is derived. Recently, a dueling neural net6 works architecture was proposed and shown to lead to better policy evaluation in the presence of 7 many similar-valued actions, as applied in a computer game context. The main research contribu8 tions of the current paper are that (i) we develop a dueling neural networks approach for the set9 ting of joint coordination of an entire EV fleet, and (ii) we evaluate its performance and compare 10 it to an all-knowing benchmark and an FQI approach using EXTRA trees regression technique, 11 a popular approach currently discussed in EV related works. We present a case study where 12 RL agents are trained with an ǫ–greedy approach for different objectives, i.e., (a) cost minimiza13 tion, and (b) maximization of self-consumption of local renewable energy sources. Our results 14 indicate that RL agents achieve significant cost reductions (70–80 %) compared to a business-as15 usual scenario without smart charging. Comparing the dueling neural networks regression to 16 EXTRA trees indicates that for our case study’s EV fleet parameters and training scenario, the 17 EXTRA trees-based agents achieve higher performance in terms of both lower costs (or higher 18 self-consumption) and stronger robustness, i.e., less variation among trained agents. This sug19 gests that adopting dueling neural networks in this EV setting is not particularly beneficial as 20 opposed to the Atari game context from where this idea originated. 21
Deep Learning Use for Differentiation of Low-grade vs High-Grade Glioma in Intraoperative Squash Smears

ObjectiveAutomated diagnosis using Artificial Intelligence (AI) techniques would be a useful addition to the intraoperative squash smear diagnosis. A robust diagnostic tool would enhance capabilities in centres where there is limited expertise for the diagnosis of intracranial lesions. The study aims to explore possibilities of deep learning technique-based models to classify squash smear images of glioma into high- and low-grade tumors.Methods500 Scanned images of squash smear were obtained intraoperatively and dataset was built. Image dataset was then pre-processed and fed into a CNN (Convolutional Neural Network) model for training and validation. The dataset consisted of 10,000 images of high (6000) and low (4000) grade gliomas, divided into three sets of training, validation and testing. ResultsCNN model based on deep learning algorithm was built and trained on training dataset to get accuracy of 96.2%. On a testing dataset which contains images previously unseen by trained model, it could achieve accuracies of 91% for diagnosing high grade glioma and 77% for low grade glioma. A positive predictive value of 86.6% and F1-score of 0.887 was achieved. Feature visualization technique was applied at the end to visualize regions of interest.ConclusionDeep Learning techniques can be applied as diagnostic tool if proper standardized images are obtained for reporting of squash smears of gliomas. The diagnostic accuracies of such tools can reach up to current standard diagnostic accuracies by conventional ways of reporting. Feature visualization techniques applied which can be used for rapid screening of slides or section of slide to assist in rapid diagnosis.
Too many immigrants: How does local diversity contribute to attitudes toward immigration?

This paper investigates the link between residential context, perceptions and attitudes toward immigrants by linking data from the British Election Study with Census statistics on composition of electoral constituencies in 2001 and 2011. I consider which type of local diversity is most salient for natives’ attitudes by combining information on ethnicity, religion and skills. Second, I look at whether base levels of and changes in local diversity affect anti-immigration attitudes in the same way. I find that immigration is more salient when defined by ethnic criteria, rather than criteria that combine ethnicity and religion or skills. Anti-immigrant attitudes are more likely to be expressed by natives who live in constituencies where there has been a large change in diversity between 2001 and 2011, but these responses depend on initial diversity levels. For non-whites and skilled ethnic minorities higher residential segregation is associated with more negative attitudes toward immigrants among natives.
Persistence in Croatian tourism: The impact of COVID-19

This research note examines the change in the degree of persistence in the Croatian tourism indicators, foreign arrivals, and overnight stays, due to the COVID-19 pandemic using recursive estimation of a fractional integration model. The results indicate that the shock from the COVID-19 pandemic can be viewed as permanent in nature. The policy response to restore tourism to its original trend should consider whether such policies proceed as in the past with the promotion of the traditional tourism growth model or support the transformation toward a more sustainable tourism model.
Home Bias and Local Outperformance of Limited Partner Investments: Evidence from Private Equity Fund Manager Selection

Based on a sample of 114,098 investments committed by 12,258 limited partners into 20,473 private equity funds, we study an international home bias in fund manager selection in private equity. We find that limited partners overweigh their investments with fund managers domiciled in the same geographical region by 45% on average. The home bias in local fund manager selection holds across investor types, fund characteristics as well as market regions. Investments committed with locally domiciled fund managers are not only being overweighed, but also perform better than investments with fund managers domiciled in foreign market regions. We argue that limited partners benefit from information advantages and better fund access when selecting private equity funds within their home market region.
Comparison of Attitudes towards Roadside Vegetation Management across an Exurban Landscape

Exurban development is the fastest growing land use across the United States (US). Its prevalence on the East Coast is susceptible to natural disaster events such as hurricanes and nor’easters. However, the socio-ecological processes related to disaster mitigation within exurban areas remain understudied. Our objective was to integrate social and landscape data to compare resident attitudes towards utility roadside vegetation management across four areas in the state of Connecticut, US. We collected data from residents using two mail surveys completed in 2017 and 2019 (n = 1962). From the survey questions, three attitude variables measured perceptions of the utility vegetation management process, and tradeoffs between protecting trees and maintaining reliable power. Across all locations, respondents with more favorable attitudes toward vegetation management were more likely to have greater knowledge about trees, and beliefs that trees should be used for human benefit; land cover characteristics and sociodemographic variables were less strongly associated with attitudes scores. Respondents differed among study areas in their preferences for aesthetics of roadside trees and their basic beliefs regarding the importance of trees. The results suggested that social processes within the exurban landscapes are spatially heterogeneous. Therefore, local variation in residential preferences for vegetation management may influence support for natural disaster management policy.
A Review of Numerical Simulations of Secondary Flows in River Bends

River bends are one of the common elements in most natural rivers, and secondary flow is one of the most important flow features in the bends. The secondary flow is perpendicular to the main flow and has a helical path moving towards the outer bank at the upper part of the river cross-section, and towards the inner bank at the lower part of the river cross-section. The secondary flow causes a redistribution in the main flow. Accordingly, this redistribution and sediment transport by the secondary flow may lead to the formation of a typical pattern of river bend profile. It is important to study and understand the flow pattern in order to predict the profile and the position of the bend in the river. However, there are a lack of comprehensive reviews on the advances in numerical modeling of bend secondary flow in the literature. Therefore, this study comprehensively reviews the fundamentals of secondary flow, the governing equations and boundary conditions for numerical simulations, and previous numerical studies on river bend flows. Most importantly, it reviews various numerical simulation strategies and performance of various turbulence models in simulating the flow in river bends and concludes that the main problem is finding the appropriate model for each case of turbulent flow. The present review summarizes the recent advances in numerical modeling of secondary flow and points out the key challenges, which can provide useful information for future studies.
Specific Magnetic Resonance Imaging Findings as Predictors of Osteomyelitis in Routine Clinical Practice

Background: The gold standard for the diagnosis of osteomyelitis is histopathology combined with positive bone cultures. Magnetic Resonance Imaging (MRI) is often used to aide diagnosis and guide treatment decisions. The purpose of the study was to examine the association of MRI findings with, and their sensitivity and specificity in identifying osteomyelitis as proven by bone histopathology and bone culture in routine clinical practice. Materials and Methods: A retrospective analysis of patients with bone specimens obtained by biopsy or at resection for suspected osteomyelitis during 2010-2014 at an academic medical center in New York City. We used bivariate analysis to compare findings of patients who did or did not have osteomyelitis confirmed on histopathology (Analysis 1) and those who had either bone histopathology demonstrating osteomyelitis, positive bone cultures or both or who had neither (Analysis 2). Results: We identified 103 patients with an MRI in the week prior to bone biopsy or bone resection. In Analysis 1, 52 (50.5%) of 103 patients had osteomyelitis confirmed on histopathology. In Analysis 2, 72 (70%) patients had proven osteomyelitis. These groups with and without osteomyelitis did not differ significantly with respect to the frequency of marrow edema, cortical erosions, decreased T1 signal or increased T2 signal in either analysis and the sensitivity and specificity of MRI findings for detecting osteomyelitis was lower than reported in prior studies. Conclusions: Based on the above results, clinicians should be aware that the sensitivity and specificity of MRI findings for histologic and microbiologic osteomyelitis may be less in real world practice than is reported in formal studies.
Key gaps in soil monitoring during forest restoration in Colombia

The knowledge of soil indicators during forest restoration is essential for understanding the recovery of ecosystem functions such as biomass production and water regulation. Despite this importance, in most restoration programs over the world, the soil remains under‐investigated. Here, we conducted a systematic literature review in order to determine: (1) the extent to which soil indicators are monitored during forest restoration in Colombia; (2) the type of soil indicators (e.g. physical, chemical, or biological) that are used for the monitoring; and (3) the regions where soil indicators are measured. We found 34 studies that report soil indicators. The most frequently studied restoration sites were 0–5 years old (36%). The majority (71%) of the studies only measured the soil characteristics at the topsoil. Soil sodium (Na) and phosphorus (P) concentrations were the most common chemical soil indicators reported by the studies. Soil biological indicators were the least frequently reported indicators. The studies rarely reported soil indicators that affect water movement directly. Of the retrieved studies, most included information about old‐growth forests (63%) or degraded sites (56%) for comparisons with forests undergoing restoration. Based on these results we provide recommendations for monitoring soil characteristics to assess the effectiveness of forest restoration projects in Colombia, and other tropical countries.
4-PYRROLIDINO/MORPHOLINO-1-(4-SUBSTITUTED PHENYLMETHYL/2-ETHOXY-2- OXOETHYL)PYRIDINIUM BROMIDE: SYNTHESIS, ANTIMICROBIAL EVALUATION AND ANTI- MRSA STUDIES

Methods: A series of 1-(4-substituted phenylmethyl/2-ethoxy-2-oxoethyl)-4-pyrrolidino/morpholinopyridinium bromides ( 1-12 ) were synthesized by stirring 4-substituted phenylmethyl/2-ethoxy-2-oxoethyl bromide and pyrrolidino/morpholinopyridine in dry acetone. The physical and spectral (IR, 1H & 13 C NMR and MS) data were collected to confirm their structures. The compounds 1-12 were screened for antimicrobial activity by twofold serial dilution technique. The anti-MRSA studies were performed by agar-well diffusion method and the data were analyzed using One Way Analysis of Variance (ANOVA). Results: The results of the invitro antimicrobial screening studies revealed that compounds 2, 8 against Staphylococcus aureus, Klebesilla pneumonia, Escherichia coli, Aspergillus niger and 6 against Streptococcus mutants , Rhizopus arrhizus were found better activity than the standard drugs. The compound 8 has exhibited the highest inhibitory effect against methicillin-resistant Staphylococcus aureus. The ANOVA of anti-MRSA data showed significant differences at P<0.01. Conclusion: The compound 8 has shown promising antibacterial activity against methicillin-resistant Staphylococcus aureus.
Tolerance niche expansion and potential distribution prediction during Asian openbill bird range expansion

Abstract It is prevalent to use ecological niche models in the analysis of species expansion and niche changes. However, it is difficult to estimate the niche when alien species fail to establish in exotic areas. Here, we applied the tolerance niche concept, which means that niche of species can live and grow but preclude a species from establishing self‐sustaining populations, in such fail‐to‐establish events. Taking the rapidly expanded bird, Asian openbill (Anastomus oscitans), as a model species, we investigated niche dynamics and its potential effects on the population by Niche A and ecospat, predicted potential distribution by biomod2. Results showed that niche expansion has occurred in two non‐native populations caused by the tolerance of colder and wetter environments, and potential distribution mainly concentrated on equatorial islands. Our study suggested that the expanded niche belongs to tolerance niche concept according to the populations' dynamics and GPS tracking evidence. It is essential to consider source populations when we analyze the alien species. We recommended more consideration to the application of tolerance niche in alien species research, and there is still a need for standard measurement frameworks for analyzing the tolerance niche.
Sponsor message processing in live broadcasts—A pilot study on the role of game outcome uncertainty and emotions

Live sport broadcasts can evoke emotions in consumers and allow companies to reach their audience in environments that allow for automatic processing of brand messages. However, only few studies have applied psychophysiological methodologies to assess how the live nature of a competition and viewers' emotions affect the processing of sponsor messages, and prior research has mostly relied on ex ‐ post data. Therefore, to identify the interplay of game outcome uncertainty, viewers' emotions and attention to sponsor messages, this exploratory lab study tracks continuous viewer data during live sport broadcasts. Soccer fans' ( n = 11) arousal, emotional valence, and visual attention to sponsors while watching live soccer broadcasts were measured using galvanic skin response, video ‐ based facial expressions, and infrared eye ‐ tracking. In ‐ play betting odds served as an indicator of outcome uncertainty. Multi ‐ level modeling reveals that greater outcome uncertainty increases arousal and the magnitude of emotional response. Further, the data reveal that low ‐ to ‐ moderate arousal and valence ‐ neutral emotional states increase viewer attention to sponsor messages. This study is the first to consider the dynamics of live sports experiences in the explanation of sponsorship effectiveness. It contributes to the literature by using continuous measurements involving psychophysiological data to investigate emotions and attention to sponsors.