Miracle-dz/UniFAR-FTUs huggingface dataset:
Conservation status,ex situpriorities and emerging threats to small carnivores

Madagascar contains the highest concentration of threatened carnivore species anywhere in the world. The country ’ s deteriorating protected-area network makes it a priority for small carnivore conservation, and several species may need some form of ex situ action. Small carnivores in South East Asia are under signi ﬁ cant pressure from hunting to supply the illegal wildlife trade, as well as habitat loss, and the interactions between these two factors. Owston ’ s civet Chrotogale owstoni is the conservation priority from this region. The rapidly declining status of Large- spotted civet Viverra megaspila needs careful monitoring, as it may warrant intervention soon. Otters (Lutrinae) in Asia are in decline and there may exist as yet undescribed conservation units that are extre- mely threatened. Hairy-nosed otter Lutra sumatrana is not yet a priority for ex situ conservation because of low feasibility; efforts should focus on managing the populations of Smooth-coated otter Lutrogale per- spicillata and Asian small-clawed otter Aonyx cinereus already in human care. The future of European mink Mustela lutreola and Black-footed ferret Mustela nigripes will depend on ongoing support to con- servation-breeding efforts, as well as threat reduction. Ailurus fulgens conser- vation is dependent to its integrated conservation plan. There are no obvious candidate species for ex situ conservation of small carnivores from Africa, though the bushmeat trade, large-scale infrastructure and a growing transnational wildlife trade to change this assessment in the near future. It is unclear ex situ conservation would have for Pygmy raccoon Procyon pygmaeus : the main threat to this species is hurricanes. A speculative assessment of emerging threats to small carnivores includes: infrastructural development in the tropics, illegal wildlife trade networks that include Latin American, African and Asian markets, and the growing Viet- namese and Chinese diasporas that operate in other Asian countries, Africa and Latin America, and the interactions between all of these factors.
Data Science based Secure Healthcare Framework for COVID-19

 Abstract — this paper presents a brief introduction to data science role in healthcare applications especially for COVID-19. The corona virus or Covid-19 is a communicable disease a large family of viruses that causes illnesses ranging from the common cold to acute respiratory syndromes, but the current virus is a novel strain not seen before. Common symptoms of the novel corona virus strain include respiratory symptoms such as fever, cough, and shortness of breath, according to the WHO. The WHO has declared the corona virus epidemic as a global health emergency. When clinical and community sectors work synergistically, they can improve care and support patients better than either of these sectors could do alone. It is observed that the use of data science techniques is continuously assisting in managing world is Fighting Corona Virus. The proposed research is more effective disease diagnosis using big data analysis, artificial intelligent, machine learning and virtual reality.
VACCINE INFORMATION SEEKING AND SHARING: HOW PRIVATE FACEBOOK GROUPS CONTRIBUTED TO THE ANTI-VACCINE MOVEMENT ONLINE

Although vaccines are supported by decades of research demonstrating their efficacy and safety, many parents still decide not to vaccinate their children due to the perceived risks. One major factor in vaccine dissent is the proliferation of vaccine opposed content online. Online content has become an integral part of how people make health and science-related decisions. This study explores how members of anti-vaccine Facebook groups use the platform to seek and share vaccine information. Using interviews and Facebook posts shared in vaccine opposed groups, this study was able to identify the information seeking and sharing behaviors on Facebook and how Facebook’s platform changes are affecting the vaccine opposed movement. Findings from this study will provide further insights into the relationships among social media use, values, and trust in the vaccine debate. In addition, results may be applicable to other scientific controversies, online misinformation, and the development of public health interventions.
Between loneliness and belonging: narratives of social isolation among immigrant older adults in Canada

Abstract Research points to a higher risk for social isolation and loneliness among new immigrant and refugee older adults. Our article draws from a research project that explored the everyday stories of ageing among 19 diverse immigrant older adults in Canada. To capture their experiences of loneliness and social isolation, we use four illustrative cases derived from a structural approach to life-story narrative. To these we apply the intersectional lifecourse analytical lens to examine how life events, timing and structural forces shape our participants’ experiences of social isolation and loneliness. We further explore the global and linked lives of our participants as well as the categories of difference that influence their experiences along the continua of loneliness to belonging, isolation to connection. Finally, we discuss how an understanding of sources of domination and expressions of agency and resistance to these forces might lead us to solutions.
Design of measurement and control system for dual incidence polarization high-speed Jones matrix optical coherence tomography

In order to analyze the polarization properties of biological tissues, we constructed a high-speed three-dimensional swept -source polarization sensitive optical coherence tomography (PS-OCT) imaging system with the axial scanning rate up to 200KHz. For automatically detecting and analyzing the polarization properties of peristaltic living tissues in real-time, an advanced measurement and control system is designed using laboratory virtual instrument technology. Based on the producer-consumer pattern, the system mainly includes the sample arm scanning galvanometer module, the interference data acquisition module, the interference data real-time processing and display module, the interference data storage module. Each module not only independently completes specific sub-functions but also interacts with others. In-vivo human finger and in-vitro pork tissue were imaged using the system. The experimental results show that the home-made system obtains 78 cross sectional B-scans per second, and can display two-dimensional OCT images and acquire threedimensional OCT data all in real-time. This robust measurement and control system has the characteristics of short design cycle, high flexibility and real-time monitoring, will significantly promote the development of PS-OCT in clinical applications.
A meta-analysis of linguistic markers of extraversion: Positive emotion and social process words

Past literature has shown that extraversion is related to the use of positive emotion and social process words. However, the strength of the relationships varies substantially across studies. In this research, we conducted a meta-analysis (k = 37, N = 82,132) to estimate the overall effect size of the two linguistic correlates of extraversion. In addition, we tested potential moderators including demographic variables (e.g., age and gender) and communication contexts (e.g., synchronous vs. asynchronous, public vs. private). Our random effects models revealed a small correlation between extraversion and positive emotion words (r = .069, 95% CI = [.041, .096]), and a small correlation between extraversion and social process words (r = .077, 95% CI = [.044, .109]). In addition, the strength of the relationship between extraversion and positive emotion words varies across communication contexts, while the relationship between extraversion and social process words remains consistent across contexts. Our results suggest that positive emotion words and social process words are linguistic correlates of extraversion, but they are small in magnitude.
The Laboratory at Hand: Plastic Sorting Made Easy

Sorting plastics according to their chemical composition is a crucial step in the recycling process, turning mixed plastics waste into a high‐value resource. Near‐infrared spectroscopy (NIRS) is an established method for plastics classification. Evolutionary progress in miniaturization of optical components has enabled the development of hand‐held spectrometers. Cloud‐based computing and centralized databases provide practically unlimited computing power for classification algorithms and enormous spectral databases. Here we discuss the basics of hand‐held NIRS and the essentials of the corresponding data analysis with a focus on plastics sorting.
Développement d'une stratégie thérapeutique pour la dystrophie facio-scapulo-humérale.

La dystrophie facio-scapulo-humerale (FSHD) est une maladie musculaire autosomique dominante rare. Cette pathologie est causee par la perte des marques epigenetiques repressives au macrosatellite D4Z4 en region subtelomerique du chromosome 4, ce qui conduit a la relaxation de la chromatine, l’expression aberrante du facteur de transcription DUX4 et la deregulation de centaines de genes. A ce jour, aucun traitement therapeutique n’existe pour la FSHD. Le but de ce projet etait de determiner si cibler ou non par des oligonucleotides antisens (AOs) les sequences cles impliquees dans la polyadenylation des ARNm peut-etre une strategie therapeutique pour inhiber l’expression de DUX4 chez les patients FSHD. En effet, le clivage et la polyadenylation en 3’ des ARNm sont des mecanismes fondamentaux de la maturation des ARNm necessaires a leur export nucleaire, leur stabilite ou leur traduction efficace. Ces mecanismes representent donc des cibles interessantes pour une suppression de l’expression d’un gene dans des maladies a gain de fonction. Pour la premiere fois, nous avons pu montrer in vitro que l’utilisation d’AOs ciblant les sequences cles impliquees dans l’ajout d’une queue poly(A), notamment le signal de polyadenylation ou le site de clivage, conduit a une sous-expression de l’ARNm gene cible, et en particulier DUX4. Les AOs presentant in vivo une faible capacite a penetrer les cellules et une forte clairance, les sequences des AOs les plus prometteurs ont ete inserees dans un vecteur AAV sous promoteur U7. Les premiers resultats obtenus avec ces vecteurs sur un modele murin sont prometteurs. Cette strategie innovante apparait comme une option therapeutique pour la FSHD.
The Water-Saving Strategies Assessment (WSSA) Framework: An Application for the Urmia Lake Restoration Program

Increases in water demand often result in unsustainable water use, leaving insufficient amounts of water for the environment. Therefore, water-saving strategies have been introduced to the environmental policy agenda in many (semi)-arid regions. As many such interventions failed to reach their objectives, a comprehensive tool is needed to assess them. We introduced a constructive framework to assess the proposed strategies by estimating five key components of the water balance in an area: (1) Demand; (2) Availability; (3) Withdrawal; (4) Depletion and (5) Outflow. The framework was applied to assess the Urmia Lake Restoration Program (ULRP) which aimed to increase the basin outflow to the lake to reach 3.1 × 109 m3 yr−1. Results suggested that ULRP could help to increase the Outflow by up to 57%. However, successful implementation of the ULRP was foreseen to be impeded because of three main reasons: (i) decreasing return flows; (ii) increased Depletion; (iii) the impact of climate change. Decreasing return flows and increasing Depletion were expected due to the introduction of technologies that increase irrigation efficiency, while climate change could decrease future water availability by an estimated 3–15%. We suggest that to reach the intervention target, strategies need to focus on reducing water depletion rather than water withdrawals. The framework can be used to comprehensively assess water-saving strategies, particularly in water-stressed basins.
Prevalence and Trends in Gestational Diabetes Mellitus among Women in the United States, 2006–2016

Gestational diabetes mellitus (GDM) is a common medical complication in pregnancy, carries adverse health outcomes for both mothers and offspring. However, national data on the prevalence and secular trends of GDM during the past 10 years in the U.S. is lacking. This study included 26,340 ever-pregnant women aged ≥ 18 years from the National Health Interview Survey in 20and 2016. We examined GDM prevalence in 20and 2016. The prevalence of GDM increased from 4.6% in 20to 8.2% in 2016 (P In conclusion, the prevalence of GDM increased by 3.6% from 20to 2016; and the rise was more marked among non-white, overweight, low income, age 45-64 years, and insufficient activity groups. Disclosure T. Zhou: None. D. Sun: None. X. Li: None. Y. Heianza: None. H. Nisa: None. G. Hu: None. X. Pei: None. X. Shang: None. L. Qi: None.
Systems Thinking Approach to Implementing Kanban: A case study

Against the backdrop of the growing adoption of Kanban in a variety of software development domains, this paper reports on how a Systems Thinking approach was used to implement Kanban within a business unit of a government organization. Based on an in‐depth case study in the development organization, we describe how Kanban practices such as visualization, manage flow, classes of service, and board design were implemented. Stages in the double diamond design thinking process of exploring an issue more widely (divergent thinking) and then taking focused action (convergent thinking) were incorporated to adapt Kanban practices such as board design. Positive experiences included improved visibility, improved collaboration, and improvements in lead time. Challenges included lack of team buy‐in, setting work‐in‐progress limits, and short‐term Kanban coach. We present the key lessons learned and offer practical recommendations on how teams can better produce knowledge work in today's fast‐paced dynamic business environment.
Communication Disorder of The Autistic Character in The “Fly Away” Movie

This study aims to identify the type of communication disorder in comprehending the speech of an autistic character in the “Fly Away” movie. In addition, it aims to describe the occurrence of communication disorders. In this study, the researchers used the theory on the type of communication disorder (Paul, 2008). As the findings, there are forty-three data of the five types of communication disorders namely, repetition of words, minimal response, limitation of communication function, use of unusual words, and low frequency. The result stated that word repetition is a type of disorder that often occurs in autistic characters in “Fly Away”. The occurrence of communication disturbance is also sown by several incidents such as, jumping, excessive laughs, rebellion, repeating posture, eyes up, just see the interlocutor and bite the fingers. These things are an expression that happened to the autistic character when experiencing communication disorders. This finding can be used as a guideline for those interacting with autistic individuals applying both verbal and nonverbal communication.
Cross Section Analysis of the KBW Nasdaq Financial Technology Index

Financial Technology (FinTech) has emerged as a potentially transformative force in the various financial segments. To track this new sector garnering investor attention, Keefe, Bruyette & Woods and Nasdaq, came up with KBW Nasdaq Financial Technology Index (KFTX) on July 18, 2016 comprising of 49 constituents. The objective of this paper is to compare KFTX performance with the leading market indices, including S&P 500 and Dow Jones Industrial Average index. The data is collected for a period of 12 months, 24 months and 34 months starting from July 18, 2016. The findings of the analysis suggest that the returns for KFTX are consistently higher for 12 months, 24 months and 34 months over S&P 500 and Dow Jones Industrial Average. The cross section analysis of the 48 KFTX index constituents sub-classified into eight categories representing several different financial industry groups and businesses indicate that for the 34 months period networks and payments gave returns of 82.1% and 71.6% whereas asset management business gave an average negative return of – 51.0% and the specialty marketplace lenders gave a return of 26.6%. This indicates a significant non-uniform growth within the FinTech industry. The findings motivate for an in-depth analysis of the various industry groups and businesses within the FinTech industry and to explore further the reasons and attributes which differentiate these sectors. The study has implications for policy makers, asset management companies and investors in terms of understanding and framing policies for FinTech investments.
Integrating Anticipative Replenishment Allocation with Reactive Fulfillment for Online Retailing Using Robust Optimization

Problem definition: In each period of a planning horizon, an online retailer decides how much to replenish each product and how to allocate its inventory to fulfillment centers (FCs) before demand is known. After the demand in the period is realized, the retailer decides on which FCs to fulfill it. It is crucial to optimize the replenishment, allocation, and fulfillment decisions jointly such that the expected total operating cost is minimized. The problem is challenging because the replenishment allocation is done in an anticipative manner under a push strategy, but the fulfillment is executed in a reactive way under a pull strategy. We propose a multiperiod stochastic optimization model to delicately integrate the anticipative replenishment allocation decisions with the reactive fulfillment decisions such that they are determined seamlessly as the demands are realized over time. Academic/practical relevance: The aggressive expansion in e-commerce sales significantly escalates online retailers’ operating costs. Our methodology helps boost their competency in this cutthroat industry. Methodology: We develop a two-phase approach based on robust optimization to solve the problem. The first phase decides whether the products should be replenished in each period (binary decisions). We fix these binary decisions in the second phase, in which we determine the replenishment, allocation, and fulfillment quantities. Results: Numerical experiments suggest that our approach outperforms existing methods from the literature in solution quality and computational time and performs within 7% of a benchmark with perfect information. A study using real data from a major fashion online retailer in Asia suggests that the two-phase approach can potentially reduce the retailer’s cumulative cost significantly. Managerial implications: By decoupling the binary decisions from the continuous decisions, our methodology can solve large problem instances (up to 1,200 products). The integration, robustness, and adaptability of the decisions under our approach create significant value.
DOES ANYONE TALK ABOUT THE ISSUES ANYMORE? THE 2016 U.S. PRESIDENTIAL CANDIDATES' MESSAGING ON FACEBOOK AND TWITTER

Suggested Citation (APA): Stromer-Galley, J., Hemsley, J., Rossini, P., Smith, A. , Bolden, S. (2020, October 28-31). Does Anyone Talk About the Issues Anymore? The 2016 U.S. Presidential Candidates’ Messaging on Facebook and Twitter. Paper submitted to AoIR 2020: The 21th Annual Conference of the Association of Internet Researchers. Virtual Event: AoIR. Retrieved from http://spir.aoir. org. DOES ANYONE TALK ABOUT THE ISSUES ANYMORE? THE 2016 U.S. PRESIDENTIAL CANDIDATES’ MESSAGING ON FACEBOOK AND TWITTER
Hierarchical Instance Recognition of Individual Roadside Trees in Environmentally Complex Urban Areas from UAV Laser Scanning Point Clouds

Individual tree segmentation is essential for many applications in city management and urban ecology. Light Detection and Ranging (LiDAR) system acquires accurate point clouds in a fast and environmentally-friendly manner, which enables single tree detection. However, the large number of object categories and occlusion from nearby objects in complex environment pose great challenges in urban tree inventory, resulting in omission or commission errors. Therefore, this paper addresses these challenges and increases the accuracy of individual tree segmentation by proposing an automated method for instance recognition urban roadside trees. The proposed algorithm was implemented of unmanned aerial vehicles laser scanning (UAV-LS) data. First, an improved filtering algorithm was developed to identify ground and non-ground points. Second, we extracted tree-like objects via labeling on non-ground points using a deep learning model with a few smaller modifications. Unlike only concentrating on the global features in previous method, the proposed method revises a pointwise semantic learning network to capture both the global and local information at multiple scales, significantly avoiding the information loss in local neighborhoods and reducing useless convolutional computations. Afterwards, the semantic representation is fed into a graph-structured optimization model, which obtains globally optimal classification results by constructing a weighted indirect graph and solving the optimization problem with graph-cuts. The segmented tree points were extracted and consolidated through a series of operations, and they were finally recognized by combining graph embedding learning with a structure-aware loss function and a supervoxel-based normalized cut segmentation method. Experimental results on two public datasets demonstrated that our framework achieved better performance in terms of classification accuracy and recognition ratio of tree.
Lactides and Lactones Yielding Eco-Friendly and Biocompatible Polymers by Metal-Catalyzed Ring-Opening Polymerization

Currently, there is a growing interest in the development of suitable methods for the preparation of eco-friendly and biocompatible materials in order to increase the environmental protection and reduce human health risk. Therefore, this mini-review summarizes several studies involving lactides and lactones as monomers for the synthesis of biodegradable and biocompatible polymers via metal-catalyzed ring-opening polymerization (ROP). Hence, synthetic approaches involving mono, bi and trinuclear metallic catalysts, with different catalytic activity, were reviewed. Complexes mostly based on metals such as Na, Mg, Al, Ti, Zn are considered. Generally, from ROP reactions, it has been found that conversion, stereoselectivity, number-average molar mass (Mn) and dispersity of the molar mass (Ð) of polymers are influenced by the type of monomer, the characteristics of the catalyst, the nature of the solvent, temperature and reaction time. Additionally, the polymer properties can also be controlled by varying the molar ratios between the monomer and the initiating system. Thus, this review may result relevant for the scientific community and students immersed in different areas of chemistry such as organic chemistry, inorganic chemistry, polymers chemistry, and materials science. The survey covers selected data published between 2017 and 2020; however, previous relevant reports were also studied.