Miracle-dz/UniFAR-FTUs huggingface dataset:
Neurophysiological effects of mobile phone electromagnetic fields on humans: A comprehensive review

In recent years a growing number of people have begun to use mobile phone technology. This phenomenon has raised questions and doubts about possible effects on users' brains. This literature review focuses on the human electrophysiological and neuro‐metabolic effects of mobile phone (MP)‐related electromagnetic fields (EMFs) published in the last 10 years. To this end, all relevant papers have been reported and, subsequently, a literature selection has been carried out by taking several criteria into account, such as: blind techniques, randomization or counter‐balancing of conditions and subjects, detail of exposure characteristics and the statistical analyses used. As a result, only the studies meeting the selection criteria have been described, evaluated and discussed further. The main goal of this review is to provide a clear scenario of the most reliable experiments carried out over the last decade and to offer a critical point of view in their evaluation. It is concluded that MP‐EMFs may influence normal physiology through changes in cortical excitability and that in future research particular care should be dedicated to both methodological and statistical control, the most relevant criteria in this research field. Bioelectromagnetics 28:415–432, 2007. © 2007 Wiley‐Liss, Inc.
The Routledge companion to accounting, reporting and regulation

Financial accounting, reporting and regulation is a vast subject area of huge global importance, with interest rising significantly in the light of the ongoing global financial crisis. The authors begin with a broad overview of the subject of accounting, setting the stage for a discussion on the theoretical and practical issues and debates regarding financial reporting, which are expanded on in the second part of the book. This includes how to define the reporting entity, recognition and measurement of the elements of financial statements, fair values in financial reporting and the costs and benefits of disclosure. The third part assesses the interest, need and theories behind the accounting, reporting and regulation industry, while parts four and five look at the institutional, social and economic aspects; with issues such as accounting for environmental management and, accounting regulation and financial reporting in Islamic countries, both issues of ever increasing importance. This authoritative Companion presents a broad overview of the state of these disciplines today, and will provide a comprehensive reference source for students and academics involved in accounting, regulation and reporting.
The Malleability of Intellectual Styles

Intellectual styles are individuals’ preferred ways of using the abilities that they possess. The extent to which one can change his or her intellectual style is a question of interest to both researchers and the general public. This book presents the first comprehensive and systematic review of existing research on the malleability of intellectual styles. By critically analyzing research findings derived from both cross-sectional and longitudinal investigations performed over the past seven decades, Li-fang Zhang demonstrates that intellectual styles can be modified through both socialization and purposeful training. Professor Zhang elucidates the heuristic value of these findings for the development of adaptive intellectual styles in both academic and nonacademic settings. She proposes further avenues of research that might advance scholarly understanding of the nature of and the potential for modifying intellectual styles.
Above‐ and Belowground Competition Intensity in Two Contrasting Wetland Plant Communities

A fundamental question in plant ecology is if and how the intensity of competition changes with productivity. This question has been the source of considerable discussion during the last two decades, yet few experiments have tested whether competition intensity changes with productivity in nature. Even fewer studies have separated competition into its above- and belowground components in the field. We used a field experiment to measure total competition intensity and its above- and belowground components in two wetlands that represent extremes in habitat productivity: an infertile sandy shoreline and a fertile bay. Transplants of Lythrum salicaria and Carex crinita were grown with no neighbors, with roots of neighbors only, and with roots and shoots of neighbors; their growth rates were used to measure competition intensity (CI). The experiment was carried out to answer the following main questions: (1) Is there a difference in total, above- and belowground competition intensity in two wetlands that differ in standing crop? and (2) Is there an effect of standing crop on total, above- and belowground competition intensity when the data from the two wetlands are combined? Results based on the average of both species show that total and aboveground com- petition intensity were greater in the high standing crop wetland, but belowground com- petition did not differ between wetlands (CITOTAL: P < 0.00001, CIABOVE: P = 0.0013, CIBELOW. P = 0.58). Total and aboveground competition intensity were significantly affected by standing crop in the wetlands studied but belowground competition intensity was not (CITOTAL: P = 0.0001, CIABOVE: P = 0.0001, CIBELOW: P = 0.89). Results based on the two species separately show that species vary in their sensitivity to competition in wetland communities.
The Return of the King or Bringing Snails to the Garden? The Human Dimensions of a Proposed Restoration of European Bison (Bison bonasus) in Germany

Human dimensions research can help resource and wildlife managers make informed decisions, target information efforts, and gain a greater understanding of the factors that comprise attitudes toward wildlife management efforts. Despite these often‐stated merits, studies addressing the human dimensions of resource and wildlife management efforts are rare in Europe. A proposed restoration of free‐ranging European bison (Bison bonasus) in North Rhine‐Westphalia, Germany, has presented an opportunity to help address this research gap. During May to July 2006, we used a randomly distributed, self‐administered questionnaire (n = 398) to assess local residents’ attitudes, beliefs, and levels of support or opposition toward the proposed restoration. These factors were compared across two administrative regions spanned by the proposed restoration area. We found that respondents from the Siegen‐Wittgenstein region held significantly more positive attitudes and significantly higher knowledge levels than respondents from the Hochsauerlandkreis region. Principal components analysis revealed that attitudes comprised a general attitude factor pertaining to issues such as the importance of conserving bison for future generations and a lifestyle impact factor, which included items pertaining to bison‐caused damages to trees and crops. Logistic regression was used to show the influence of fear of bison on attitudes. We discuss the likely causes and management implications of our findings and provide suggestions to managers wishing to target information efforts and address the concerns of those affected by the proposed restoration.
Microhabitat to landscape impacts: crested porcupine digs in the Negev Desert highlands

Abstract Indian crested porcupines ( Hystrix indica ) are adaptable, generalist herbivores with wide environmental tolerances and a large geographic range. In the arid Negev Desert highlands of southern Israel, porcupines excavate and consume subterranean organs of 18 species of geophytes and hemicryptophytes in a variety of habitats. Their foraging generates a network of direct and indirect impacts on ecological processes. Porcupine digs varied in size according to depth of forage and substrate, and new digs averaged about 8 cm in depth, and 400 cm 2 and 940 cm 3 in surface area and volume, respectively. Digging rates also differed among habitats. In hilly watersheds, highest digging rates were in soil belts supporting the greatest cover of shrubs and geophytes. Dig densities peaked at > -031 dig m −2 , impacting up to 4% of soil surfaces. Digs are temporary soil pockets (longevities of -0310 years) that trap soil, water, organic matter, and seeds. As highly productive microhabitats compared to surrounding soil matrix, they promote the germination and growth of annual plants including some porcupine forage species. Loose soil excavated by porcupines enhances soil erosion and transport, and may substantially enhance ecosystem flows of water, soil, and nutrients. Porcupine digging may help to maintain bare rock outcrops in Negev watersheds, thereby promoting large runoff flows that produce mesic patches and plant habitats. Runoff dynamics have greatly influenced past and present human exploitation of Negev landscapes. Recent experiments indicate that porcupine digs have important properties as small-scale landscape disturbances, and as sources and sinks of critical environmental resources. Additional research is needed to better define and predict porcupine digging impacts at several ecological levels, and as a basis for realistic management of Negev habitats and landscapes.
Clinical characteristics and outcomes for 7,995 patients with SARS-CoV-2 infection

Objective: Severe acute respiratory syndrome virus (SARS-CoV-2) has infected millions of people worldwide. Our goal was to identify risk factors associated with admission and disease severity in patients with SARS-CoV-2. Design: This was an observational, retrospective study based on real-world data for 7,995 patients with SARS-CoV-2 from a clinical data repository. Setting: Yale New Haven Health (YNHH) is a five-hospital academic health system serving a diverse patient population with community and teaching facilities in both urban and suburban areas. Populations: The study included adult patients who had SARS-CoV-2 testing at YNHH between March 1 and April 30, 2020. Main outcome and performance measures: Primary outcomes were admission and in-hospital mortality for patients with SARS-CoV-2 infection as determined by RT-PCR testing. We also assessed features associated with the need for respiratory support. Results: Of the 28605 patients tested for SARS-CoV-2, 7995 patients (27.9%) had an infection (median age 52.3 years) and 2154 (26.9%) of these had an associated admission (median age 66.2 years). Of admitted patients, 1633 (75.8%) had a discharge disposition at the end of the study period. Of these, 192 (11.8%) required invasive mechanical ventilation and 227 (13.5%) expired. Increased age and male sex were positively associated with admission and in-hospital mortality (median age 81.9 years), while comorbidities had a much weaker association with the risk of admission or mortality. Black race (OR 1.43, 95%CI 1.14-1.78) and Hispanic ethnicity (OR 1.81, 95%CI 1.50-2.18) were identified as risk factors for admission, but, among discharged patients, age-adjusted in-hospital mortality was not significantly different among racial and ethnic groups. Conclusions: This observational study identified, among people testing positive for SARS-CoV-2 infection, older age and male sex as the most strongly associated risks for admission and in-hospital mortality in patients with SARS-CoV-2 infection. While minority racial and ethnic groups had increased burden of disease and risk of admission, age-adjusted in-hospital mortality for discharged patients was not significantly different among racial and ethnic groups. Ongoing studies will be needed to continue to evaluate these risks, particularly in the setting of evolving treatment guidelines.
Neutralizing and binding antibody kinetics of COVID-19 patients during hospital and convalescent phases

Knowledge of the host immune response after natural SARS-CoV-2 infection is essential for informing directions of vaccination and epidemiological control strategies against COVID-19. In this study, thirty-four COVID-19 patients were enrolled with 244 serial blood specimens (38.1% after hospital discharge) collected to explore the chronological evolution of neutralizing (NAb), total (TAb), IgM, IgG and IgA antibody in parallel. IgG titers reached a peak later (approximately 35 days postonset) than those of Nab, Ab, IgM and IgA (20~25 days postonset). After peaking, IgM levels declined with an estimated average half-life of 10.36 days, which was more rapid than those of IgA (51.25 days) and IgG (177.39 days). Based on these half-life data, we estimate that the median times for IgM, IgA and IgG to become seronegative are 4.59 (IQR 4.12-5.03), 7.78 (IQR 6.71-9.16) and 42.72 (IQR 33.75-47.96) months post disease onset. The relative contribution of IgM to NAb was higher than that of IgG (standardized {beta} regression coefficient: 0.53 vs 0.48), so the rapid decline in NAb may be attributed to the rapid decay of IgM in acute phase. However, the relative contribution of IgG to NAb increased and that of IgM further decreased after 6 weeks postonset. It's assumed that the decline rate of NAb might slow down to the same level as that of IgG over time. This study suggests that SARS-CoV-2 infection induces robust neutralizing and binding antibody responses in patients and that humoral immunity against SARS-CoV-2 acquired by infection may persist for a relatively long time.
A Deep Learning Approach for IP Hijack Detection Based on ASN Embedding

IP hijack detection is an important security challenge. In this paper we introduce a novel approach for BGP hijack detection using deep learning. Similar to natural language processing (NLP) models, we show that by using BGP route announcements as sentences, we can embed each AS number (ASN) to a vector that represents its latent characteristics. In order to solve this supervised learning problem, we use these vectors as an input to a recurrent neural network and achieve an excellent result: an accuracy of 99.99% for BGP hijack detection with 0.00% false alarm. We test our method on 48 past hijack events between the years 2008 and 2018 and detect 32 of them, and in particular, all the events within two years from our training data.
Enhanced Learning : A framework for investigating assets and needs

Despite the fact that teaching is increasingly referred to as a design science, teacher education programs devote relatively little time to developing expertise in the design of instruction, beyond lesson planning. Yet today’s teachers not only plan lessons that incorporate existing classroom activities and instructional resources, they also design new learning activities and create their own (technology enhanced) learning materials. Different approaches have been tried to support preand in-service teacher design learning. Past efforts to develop teacher skills in design had limited success, probably due to poor alignment of traditional instructional design models with teachers’ knowledge, needs and natural ways of engaging with design tasks. More recently, researchers have begun to investigate and develop ways to build on teacher expertise to support them in their design efforts. Yet to date, little has been done to capitalize on what is already understood about teachers as designers nor to draw on the wealth of literature on designers and designing outside the field of education. With the ultimate aim of supporting the work of teachers as designers of technology enhanced learning, this contribution synthesizes research on design from classical design fields, instructional design, and teachers’ designing. These perspectives are brought together in an ecological framework that can be used by researchers to study teacher design knowledge and work across projects. This synthesis could also provide an articulated framework for developers and facilitators of teacher professional development programs for identifying key areas for support to teacher-designers in specific settings.
SAM: Self-Attention based Deep Learning Method for Online Traffic Classification

Network traffic classification categorizes traffic classes based on protocols (e.g., HTTP or DNS) or applications (e.g., Facebook or Gmail). Its accuracy is a key foundation of some network management tasks like Quality-of-Service (QoS) control, anomaly detection, etc. To further improve the accuracy of traffic classification, recent researches have introduced deep learning based methods. However, most of them utilize the privacy-concerned payload (user data). Besides, they generally do not consider the dependency of bytes in a packet, which we believe can be exploited for the more accurate classification. In this work, we treat the initial bytes of a network packet as a language and propose a novel Self-Attention based Method (SAM) for traffic classification. The average F1-scores of SAM on protocol and application classification are 98.62% and 98.93%. With the higher accuracy of SAM, better QoS and anomaly detection can be met.
Temporal patterns of vampire bat rabies and host connectivity in Belize

In the Neotropics, vampire bats (Desmodus rotundus) are the main reservoir host for rabies, a highly fatal encephalitis caused by viruses in the genus Lyssavirus. Although patterns of rabies virus exposure and infection have been well-studied for vampire bats in South America and Mexico, exploring the ecology of vampire bat rabies in other regions is crucial for predicting risks to livestock and humans. In Belize, rabies outbreaks in livestock have increased in recent years, underscoring the need for systematic data on viral dynamics in vampire bats. In this study, we examine the first three years of a longitudinal study on the ecology of vampire bat rabies in northern Belize. Rabies seroprevalence in bats was high across years (29–80%), suggesting active and endemic virus circulation. Across two locations, the seroprevalence time series per site were inversely related and out of phase by at least a year. Microsatellite data demonstrated historic panmixia of vampire bats, and mark–recapture detected rare but contemporary inter-site dispersal. This degree of movement could facilitate spatial spread of rabies virus but is likely insufficient to synchronize infection dynamics, which offers one explanation for the observed phase lag in seroprevalence. More broadly, our analyses suggest frequent transmission of rabies virus within and among vampire bat roosts in northern Belize and highlight the need for future spatiotemporal, phylogenetic, and ecological studies of vampire bat rabies in Central America.
COVID-19 Detection on Chest X-Ray and CT Scan Images Using Multi-image Augmented Deep Learning Model

COVID-19 is posed as very infectious and deadly pneumonia type disease until recent time. Despite having lengthy testing time, RT-PCR is a proven testing methodology to detect coronavirus infection. Sometimes, it might give more false positive and false negative results than the desired rates. Therefore, to assist the traditional RT-PCR methodology for accurate clinical diagnosis, COVID-19 screening can be adopted with X-Ray and CT scan images of lung of an individual. This image based diagnosis will bring radical change in detecting coronavirus infection in human body with ease and having zero or near to zero false positives and false negatives rates. This paper reports a convolutional neural network (CNN) based multi-image augmentation technique for detecting COVID-19 in chest X-Ray and chest CT scan images of coronavirus suspected individuals. Multi-image augmentation makes use of discontinuity information obtained in the filtered images for increasing the number of effective examples for training the CNN model. With this approach, the proposed model exhibits higher classification accuracy around 95.38% and 98.97% for CT scan and X-Ray images respectively. CT scan images with multi-image augmentation achieves sensitivity of 94.78% and specificity of 95.98%, whereas X-Ray images with multi-image augmentation achieves sensitivity of 99.07% and specificity of 98.88%. Evaluation has been done on publicly available databases containing both chest X-Ray and CT scan images and the experimental results are also compared with ResNet-50 and VGG-16 models.
The Aging Brain and Executive Functions Revisited: Implications from Meta-Analytic and Functional-Connectivity Evidence

Healthy aging is associated with changes in cognitive performance including executive functions (EFs) and their associated brain activation patterns. However, it has remained unclear which EF-related brain regions are affected consistently, because the results of pertinent neuroimaging studies and earlier meta-analyses vary considerably. We, therefore, conducted new rigorous meta-analyses of published age differences in EF-related brain activity. Out of a larger set of regions associated with EFs, only left inferior frontal junction (IFJ) and left anterior cuneus/precuneus (aC/PrC) were found to show consistent age differences. To further characterize these two age-sensitive regions, we performed seed-based resting-state functional connectivity (RS-FC) analyses using fMRI data from a large adult sample with a wide age range. We also assessed associations of the two regions’ whole-brain RS-FC patterns with age and EF performance. Although functional profiling and RS-FC analyses point towards a domain-general role of left IFJ in EFs, the pattern of individual study contributions to the meta-analytic results suggests process-specific modulations by age. Our analyses further indicate that left aC/PrC is recruited differently by older (compared to younger) adults during EF tasks, potentially reflecting inefficiencies in switching the attentional focus. Overall, our findings question earlier meta-analytic results and suggest a larger heterogeneity of age-related differences in brain activity associated with EFs. Hence, they encourage future research that pays greater attention to replicability, investigates age-related differences in deactivation, and focuses on more narrowly defined EF subprocesses, combining multiple behavioral assessments with multi-modal imaging. Highlights - Healthy aging is linked to deterioration in executive functions (EFs) - ALE meta-analyses examined consistent age differences in brain activity linked to EFs - In a larger set of EF regions, only left IFJ and (pre)cuneus were sensitive to age - Advanced age was linked to weaker functional coupling within EF-related networks - Our findings question earlier meta-analytic findings
Sex-biased gene expression in rhesus macaque and human brains

Sexually dimorphic traits (i.e. phenotypic differences between males and females) are largely produced by sex-biased gene expression (i.e. differential expression of genes present in both sexes). These expression differences may be the result of sexual selection, although other factors (e.g., relaxed purifying selection, pleiotropy, dosage compensation) also contribute. Given that humans and other primates exhibit sex differences in cognition and neuroanatomy, this implicates sex differences in brain gene expression. Here, we compare sex-biased gene expression in humans and rhesus macaques across 16 brain regions using published RNA-Seq datasets. Our results demonstrate that most sex-biased genes are differentially expressed between species, and that overlap across species is limited. Human brains are relatively more sexually dimorphic and exhibit more male-than female-biased genes. Across species, gene expression is biased in opposite directions in some regions and in the same direction in others, suggesting that the latter may be more relevant in nonhuman primate models of neurological disorders. Finally, the brains of both species exhibit positive correlations between sex effects across regions, higher tissue specificity among sex-biased genes, enrichment of extracellular matrix among male-biased genes, and regulation of sex-biased genes by sex hormones. Taken together, our results demonstrate some conserved mechanisms underlying sex-biased brain gene expression, while also suggesting that increased neurodevelopmental plasticity and/or strong sexual selection on cognitive abilities may have played a role in shaping sex-biased brain gene expression in the human lineage.