Miracle-dz/UniFAR-FTUs huggingface dataset:
B-Cell Activating Factor Secreted by Neutrophils Is a Critical Player in Lung Inflammation to Cigarette Smoke Exposure

Cigarette smoke (CS) is the major cause of chronic lung injuries, such as chronic obstructive pulmonary disease (COPD). In patients with severe COPD, tertiary lymphoid follicles containing B lymphocytes and B cell-activating factor (BAFF) overexpression are associated with disease severity. In addition, BAFF promotes adaptive immunity in smokers and mice chronically exposed to CS. However, the role of BAFF in the early phase of innate immunity has never been investigated. We acutely exposed C57BL/6J mice to CS and show early BAFF expression in the bronchoalveolar space and lung tissue that correlates to airway neutrophil and macrophage influx. Immunostaining analysis revealed that neutrophils are the major source of BAFF. We confirmed in vitro that neutrophils secrete BAFF in response to cigarette smoke extract (CSE) stimulation. Antibody-mediated neutrophil depletion significantly dampens lung inflammation to CS exposure but only partially decreases BAFF expression in lung tissue and bronchoalveolar space suggesting additional sources of BAFF. Importantly, BAFF deficient mice displayed decreased airway neutrophil recruiting chemokines and neutrophil influx while the addition of exogenous BAFF significantly enhanced this CS-induced neutrophilic inflammation. This demonstrates that BAFF is a key proinflammatory cytokine and that innate immune cells in particular neutrophils, are an unconsidered source of BAFF in early stages of CS-induced innate immunity.
Defender-centric Conceptual Cyber Exposure Ontology for Adaptive Cyber Risk Assessment

: A major gap in cybersecurity studies, especially as it relates to cyber risk, is the lack of comprehensive formal knowledge representation, and often a limited view, mainly based on abstract security concepts with limited context. Additionally, much of the focus is on the attack and the attacker, and a more complete view of risk assessment has been inhibited by the lack of knowledge from the defender landscape, especially in the matter of the impact and performance of compensating controls. In this study, we will start by deﬁning a conceptual ontology that integrates concepts that model all of cybersecurity entities. We will then present an adaptive risk reasoning approach with a particular focus on defender activities. The main purpose is to provide a more complete view, from the defender perspective, that bridges the gap between risk assessment theories and practical cybersecurity operations in real-world deployments.
Unemployment insurance and food insecurity among people who lost employment in the wake of COVID-19

Forty million U.S. residents lost their jobs in the first two months of the coronavirus disease 2019 (COVID-19) pandemic. In response, the Federal Government expanded unemployment insurance benefits in both size ($600 supplement) and scope (to include caregivers and self-employed workers). We assessed the role of unemployment insurance in mitigating the impact of job loss on food insecurity during COVID-19 in low-income households. We analyzed data from the Understanding Coronavirus in America (UAC) cohort, a longitudinal survey collected by the University of Southern California Center for Economic and Social Research (CESR) every two weeks between April 1 and July 8, 2020. We limited the sample to individuals living in households earning less than $75,000 in February 2020 who lost their jobs during COVID-19. Using difference-in-differences and event study regression models, we evaluated the association between receipt of unemployment insurance and self-reported food insecurity and eating less due to financial constraints. We found that 40.5% of those living in households earning less than $75,000 and employed in February 2020 experienced unemployment during the COVID-19 pandemic. Of those who lost their jobs, 31% reported food insecurity and 33% reported eating less due to financial constraints. Food insecurity peaked in April 2020 and declined over time, but began to increase again among people receiving unemployment insurance during the final wave of the survey ahead of the federal supplement to unemployment insurance ending. Food insecurity and eating less were more common among people who were non-White, lived in lower-income households, younger, and who were sexual or gender minorities. Receipt of unemployment insurance was associated with a 4.4 percentage point (95% CI: -7.8 to -0.9 percentage points) decline in food insecurity (a 30.3% relative decline compared to the average level of food insecurity during the study period). Receipt of unemployment insurance was also associated with a 6.1 percentage point (95% CI: -9.6 to -2.7 percentage point) decline in eating less due to financial constraints (a 42% relative decline). Estimates from event study specifications revealed that reductions in food insecurity and eating less were greatest in the four-week period immediately following receipt of unemployment insurance, with no evidence of differential pre-existing trends in either outcome. We conclude that UI benefits during the period when the $600/week federal supplement was in place was associated with large reductions in food insecurity.
Elderly Parents of Adults with Severe Mental Illness

SUMMARY Seriously mentally ill adults frequently require assistance from their parents over many years. As parents age, they confront the dual challenge of caregiver demands and the need to cope with their own aging. Support groups for aging parents are a key component of social support for families that care for a mentally ill family member. This paper presents evidence of the value of support groups for elderly care-givers, through both current literature and a case example that provides a window into the strength of group work to help this vulnerable population of caregivers.
Firsts records of abnormalities and gynandromorphism in hard ticks (Ixodida: Ixodidae) from Panama

Abstract During a review of the Tick Collection of the Gorgas Memorial Institute of Panama, of 6,624 Ixodidae analyzed, 255 presented abnormalities. We detail morphological abnormalities and gynandomorphism in adults of 16 species: Amblyomma auricularium, A. calcaratum, A. dissimile, A. mixtum, A. naponense, A. cf. oblongoguttatum, A. ovale, A. sabanerae, A. tapirellum, A. varium, Dermacentor nitens, Haemaphysalis juxtakochi, Ixodes auritulus, I. tapirus, Rhipicephalus microplus, and R. sanguineus s.l. No abnormalities were found in A. coelebs, A. geayi, A. longirostre, Amblyomma nodosum, A. pacae, A. cf. parvum, A. pecarium, A. rotundatum, Dermacentor imitans, D. latus, D. panamensis, Haemaphysalis leporispalustris, I. affinis, I. bequearti, I. bocatorensis, I. boliviensis, and I. luciae. This represents the first findings of these phenomena in A. auricularium, A. calcaratum, A. naponense, A. ovale, A. sabanerae, A. tapirellum, A. varium, D. nitens, H. juxtakochi, I. auritulus, and I. tapirus. Local abnormalities were more frequent than general malformations. Amblyomma dissimile had the highest percentage of individuals with malformations, including specimens with two or more local abnormalities and gynandromorphism. It is possible that these malformations may go unnoticed or confused with loss appendages or mechanical damage.
Chatbots at Digital Workplaces - A Grounded-Theory Approach for Surveying Application Areas and Objectives

Abstract Background: Chatbots are currently on the rise as more and more researchers tackle this topic from different perspectives. Simultaneously, workplaces and ways of working are increasingly changing in the context of digitalization. However, despite the promised benefits, the changes still show problems that should be tackled more purposefully by chatbots. Application areas and underlying objectives of a chatbot application at digital workplaces especially have not been researched yet. Method: To solve the existing problems and close the research gap, we did a qualitative empirical study based on the grounded-theory process. Therefore, we interviewed 29 experts in a cross-section of different industry sectors and sizes. The experts work in the information systems domain or have profound knowledge of (future) workplace design, especially regarding chatbots. Results: We identified three fundamental usage scenarios of chatbots in seven possible application areas. As a result of this, we found both divisional and cross-divisional application areas at workplaces. Furthermore, we detected fifteen underlying objectives of a chatbot operation, which can be categorized from direct over mid-level to indirect ones. We show dependencies between them, as well. Conclusions: Our results prove the applicability of chatbots in workplace settings. The chatbot operation seems especially fruitful in the support or the self-service domain, where it provides information, carries out processes, or captures process-related data. Additionally, automation, workload reduction, and cost reduction are the fundamental objectives of chatbots in workplace scenarios. With this study, we contribute to the scientific knowledge base by providing knowledge from practice for future research approaches and closing the outlined research gap. Available at: https://aisel.aisnet. org/pajais/vol12/iss2/3/ Recommended Citation Meyer von Wolff, Raphael; Hobert, Sebastian; Masuch, Kristin; and Schumann, Matthias (2020) "Chatbots at Digital Workplaces – A Grounded-Theory Approach for Surveying Application Areas and Objectives," Pacific Asia Journal of the Association for Information Systems: Vol. 12: Iss. 2, Article 3. DOI: 10.17705/1pais.12203 Available at: https://aisel.aisnet. org/pajais/vol12/iss2/3
Wind dispersal of Puccinia psidii urediniospores and progress of eucalypt rust

Summary To identify and implement Puccinia psidii control strategies, it is essential to understand the role of environmental factors on rust-disease development and spread among eucalypt (Eucalyptus spp.) plantations. In this study, we evaluated the wind dispersal of P. psidii urediniospores and the progress of eucalypt rust in a field trial in Brazil. Urediniospores of P. psidii were trapped in a Burkard® spore trap from July 2004 to June 2005. To evaluate the progress of eucalypt rust, plots were established in March 2002 using a clonal hedge scheme. The incidence of both branches and leaves with rust was assessed weekly from February 2003 to October 2005. Disease progress was studied using time-series analysis. Urediniospores were trapped on 77% of the days sampled. The highest average urediniospore concentration was detected from July to November, and most of the urediniospores (58%) were trapped at night. Urediniospore concentration was negatively correlated with rainfall, light intensity, minimum, average and maximum temperatures and wind speed, whereas urediniospore concentration was positively correlated with leaf-wetness duration and relative humidity. From December 2004 to June 2005, average urediniospore concentration was 0.22 spores m−3 air h−1 and had no correlation with meteorological data. The highest average urediniospore concentration was associated with a combination of low average temperature, low light intensity, low wind speed, high relative humidity and high leaf wetness, which reflect conditions observed at night. The disease incidence was positively correlated with the urediniospores trapped at 12 days prior to disease assessment. According to the models obtained by the time series, a seasonal yearly effect was found on rust progress. Using our models, we were also able to forecast disease incidence up to 3 months after the last field assessment.
Towards Secure Edge-assisted Image Sharing for Timely Disaster Situation Awareness

To save human lives and reduce injury and property loss in disasters, it is important to collect real-time situation awareness information such as the surroundings, road conditions, resource information, and more. Among others, images carry rich information and can easily provide a comprehensive view of the disaster situations. This is nowadays greatly facilitated with the prevalence of camera-embedded smartphones. However, high redundancy typically exists among the images gathered from different users during disasters. Given that bandwidth is dearer in disaster situations, it would be valuable to detect the image redundancy during transmission so that bandwidth allocation can be prioritized for unique images, enabling the timely delivery of useful information. In light of the above, in this position paper, we propose the design of an image sharing system architecture for timely disaster situation awareness. Our system architecture takes advantage of the emerging edge computing paradigm to perform image redundancy detection and prioritize the transmission of unique images, optimizing the amount of useful information delivered within a certain period of time. Meanwhile, to prevent images from being exposed to the intermediate edge infrastructure, our protocol is devised in a manner that the edge infrastructure can perform image redundancy detection without seeing the images in the clear.
Holocene East Asian Summer Monsoon Rainfall Variability in Taiwan

Characterizing the spatiotemporal variability of the East Asian summer monsoon (EASM) advances our understanding of its rhythm, dynamics, and future impacts. East Asian summer monsoon variations during the Holocene have been reconstructed from a variety of geological archives and proxies. However, the spatiotemporal heterogeneity of EASM rainfall during the Holocene remains controversial. Taiwan is geographically suitable for studying the EASM history, through its geological archives. Herein, we synthesize the reported lake and peat sedimentary records of the entire Holocene, in addition to the records of mass-wasting and on-land deposition from cores collected from Taiwan to illustrate the EASM induced hydroclimate changes in Taiwan throughout the Holocene. Records from Taiwan indicate that the EASM rainfall maximum occurred during the early Holocene, concurring with other EASM records from monsoon regions in southern China. We suggest that the early Holocene EASM rainfall maximum in southern China was mainly forced by the higher Northern Hemisphere summer insolation and sea surface temperatures (SSTs) in the Western Pacific Warm Pool (WPWP). A synthesis of EASM rainfall records from across China shows that the timing of the Holocene EASM rainfall maximum occurred progressively later than that from southern to northern China. This time-transgressive EASM rainfall maximum may be due to the latitudinal shift of the westerlies and Western Pacific subtropical high (WPSH) that was induced by changes of interhemispheric temperature gradients (ΔTN–S) and the northern high latitude ice volume. Moreover, records from Taiwan suggest a significant collapse of the EASM in Taiwan at ∼4–2 ka BP. Based on the records from Taiwan, coastal East Asia, and the Tropical Pacific, we propose that the SSTs of the WPWP and/or El Niño-Southern Oscillation activity may have exerted a strong influence on the EASM rainfall changes during the late Holocene. Moreover, increased EASM rainfall in southern China during the last 2 ka was likely caused by a southward shift of WPSH, which is associated with gradual decreases in ΔTN–S during the late Holocene.
Generation of Human Images with Clothing using Advanced Conditional Generative Adversarial Networks

One of the main challenges of human-image generation is generating a person along with pose and clothing details. However, it is still a difficult task due to challenging backgrounds and appearance variance. Recently, various deep learning models like Stacked Hourglass networks, Variational Auto Encoders (VAE), and Generative Adversarial Networks (GANs) have been used to solve this problem. However, still, they do not generalize well to the real-world human-image generation task qualitatively. The main goal is to use the Spectral Normalization (SN) technique for training GAN to synthesize the human-image along with the perfect pose and appearance details of the person. In this paper, we have investigated how Conditional GANs, along with Spectral Normalization (SN), could synthesize the new image of the target person given the image of the person and the target (novel) pose desired. The model uses 2D keypoints to represent human poses. We also use adversarial hinge loss and present an ablation study. The proposed model variants have generated promising results on both the Market-1501 and DeepFashion Datasets. We supported our claims by benchmarking the proposed model with recent state-of-the-art models. Finally, we show how the Spectral Normalization (SN) technique influences the process of human-image synthesis.
Catalog Integration of Low-quality Product Data by Attribute Label Ranking

The integration of product data from heterogeneous sources and manufacturers into a single catalog is often still a laborious, manual task. Especially smalland medium-sized enterprises face the challenge of timely integrating the data their business relies on to have an up-to-date product catalog, due to format specifications, low quality of data and the requirement of expert knowledge. Additionally, modern approaches to simplify catalog integration demand experience in machine learning, word vectorization, or semantic similarity that such enterprises do not have. Furthermore, most approaches struggle with low-quality data. We propose Attribute Label Ranking (ALR), an easy to understand and simple to adapt learning approach. ALR leverages a model trained on real-world integration data to identify the best possible schema mapping of previously unknown, proprietary, tabular format into a standardized catalog schema. Our approach predicts multiple labels for every attribute of an input column. The whole column is taken into consideration to rank among these labels. We evaluate ALR regarding the correctness of predictions and compare the results on real-world data to state-of-the-art approaches. Additionally, we report findings during experiments and limitations of our
Systematic Evaluation of the Diagnostic and Prognostic Significance of Competitive Endogenous RNA Networks in Prostate Cancer

Long non-coding RNA (lncRNA)-mediated competitive endogenous RNA (ceRNA) networks act as essential mechanisms in tumor initiation and progression, but their diagnostic and prognostic significance in prostate cancer (PCa) remains poorly understood. Presently, using the RNA expression data derived from multiple independent PCa-related studies, we constructed a high confidence and PCa-specific core ceRNA network by employing three lncRNA-gene inference approaches and key node filter strategies and then established a logistic model and risk score formula to evaluate its diagnostic and prognostic values, respectively. The core ceRNA network consists of 10 nodes, all of which are significantly associated with clinical outcomes. Combination of expression of the 10 ceRNAs with a logistic model achieved AUC of ROC and PR curve up to ∼96 and 99% in excluding normal prostate samples, respectively. Additionally, a risk score formula constructed with the ceRNAs exhibited significant association with disease-free survival. More importantly, utilizing the expression of RNAs in the core ceRNA network as a molecular signature, the TCGA-PRAD cohort was divided into four novel clinically relevant subgroups with distinct expression patterns, highlighting a feasible way for improving patient stratification in the future. Overall, we constructed a PCa-specific core ceRNA network, which provides diagnostic and prognostic value.
Abundance of CD163-Positive Tumor-Associated Macrophages in the Early Gastric Cancer Predicts the Recurrence after Curative Resection

Background: We aimed to investigate the prognostic value of M2 macrophages to predict the recurrence of early gastric cancer (EGC). Methods: A retrospective analysis was carried out among EGC patients (95 non-recurrence and 78 recurrence) who underwent surgery at Luhe People’s Hospital of Nanjing. A 5-year recurrence status was utilized to classify the patients into the recurrence group and non-recurrence group. CD163 and proliferating cell nuclear antigen were utilized as markers to detect M2 macrophages and proliferation. Cumulative tumor recurrence curve was adopted to analyze the association between the number of tumor-associated macrophages (TAMs) and the recurrence of EGC. Colony formation and invasion abilities of MKN45 (JCRB0254, human gastric epithelial cell line) with or without M2 macrophage coculture were detected in vitro, and the xenograft model was utilized to detect in vivo effect of M2 macrophages on tumor growth. Results: The number of CD163+ macrophages and expression of transforming growth factor-β1, matrix metallopeptidase 9, and vascular endothelial growth factor A were significantly different between the EGC recurrence and non-recurrence group. The cumulative tumor recurrence rate was found to be dependent on the infiltration number of TAMs. M2 macrophages promoted the proliferation and invasion of human MKN45 cells in vitro, as well as tumor growth in the xenograft model. Conclusion: The abundance of CD163+-positive TAMs in EGC predicts the recurrence after curative resection.
Climate Change and Childhood Respiratory Health: A Call to Action for Paediatricians

Climate change (CC) is one of the main contributors to health emergencies worldwide. CC appears to be closely interrelated with air pollution, as some pollutants like carbon dioxide (CO2), nitrogen oxides (NOx) and black carbon are naturally occurring greenhouse gases. Air pollution may enhance the allergenicity of some plants and, also, has an adverse effect on respiratory health. Children are a uniquely vulnerable group that suffers disproportionately from CC burden. The increasing global warming related to CC has a big impact on plants’ lifecycles, with earlier and longer pollen seasons, as well as higher pollen production, putting children affected by asthma and allergic rhinitis at risk for exacerbations. Extreme weather events may play a role too, not only in the exacerbations of allergic respiratory diseases but, also, in favouring respiratory infections. Even though paediatricians are already seeing the impacts of CC on their patients, their knowledge about CC-related health outcomes with specific regards to children’s respiratory health is incomplete. This advocates for paediatricians’ increased awareness and a better understanding of the CC impact on children’s respiratory health. Having a special responsibility for children, paediatricians should actively be involved in policies aimed to protect the next generation from CC-related adverse health effects. Hence, there is an urgent need for them to take action and successfully educate families about CC issues. This paper aims at reviewing the evidence of CC-related environmental factors such as temperature, humidity, rainfall and extreme events on respiratory allergic diseases and respiratory infections in children and proposing specific actionable items for paediatricians to deal with CC-related health issues in their clinical practice.