Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving Met Office seasonal forecasts of Arctic sea ice using assimilation of CryoSat-2 thickness

Interest in seasonal predictions of Arctic sea ice has been increasing in recent years owing, primarily, to the sharp reduction in Arctic sea ice cover observed over the last few decades, which is projected to continue. The prospect of increased human industrial activity in the region, as well as scientific interest in the predictability of sea ice, provides important motivation for understanding, and improving, the skill of Arctic predictions. Several operational forecasting centres now routinely produce seasonal predictions of sea ice cover using coupled atmosphere-ocean-sea ice models. 10 Although assimilation of sea ice concentration into these systems is commonplace, sea ice thickness observations, being much less mature, are typically not assimilated. However many studies suggest that initialisation of winter sea ice thickness could lead to improved prediction of Arctic summer sea ice. Here, for the first time, we directly assess the impact of winter sea ice thickness initialisation on the skill of seasonal summer forecasts by assimilating CryoSat-2 thickness data into the Met Office’s coupled seasonal forecasting system (GloSea). We show a significant improvement in predictive skill of Arctic 15 sea ice extent and ice-edge location for forecasts of September Arctic sea ice made from the beginning of the melt season. The improvements in sea ice cover lead to further improvement of near-surface air temperature and pressure fields across the region. A clear relationship between modelled winter thickness biases and summer extent errors is identified which supports the theory that Arctic winter thickness provides some predictive capability for summer ice extent, and further highlights the importance that modelled winter thickness biases can have on the evolution of forecast errors through the melt season. 20
Ovarian Control of juvenile hormone-III biosynthesis in the cricket species Gryllus bimaculatus (Ensifera: Gryllidae)

Mature ovaries of Gryllus bimaculatus (De Geer 1773) exhibit various humoral factors which either stimulate or inhibit juvenile hormone-III biosynthesis in the corpora allata. Implantation of vitellogenic ovaries into adult MM of various age stimulates juvenile hormone biosynthesis within 24 h. Methanolic extracts inhibit juvenile hormone biosynthesis in active corpora allata in a short-term in vitro radiochemical assay. This inhibitory action is rapid, dose-dependent, and reversible.
Will Self-Monitoring Enhance the Relational Dimension of Workplace Spirituality?

Review Article Workplace Spirituality is a concept that has gained traction in the recent years. It has been proved to be a very beneficial construct for individuals and organizations. Out of the dimensions of workplace spirituality, relational dimension (connection) is considered by many researchers to be the most vital. This dimension is about building and maintaining relationship with co-workers and community. But, this depends on the personality of an individual. Some are able to make relationships much faster than others as they have the ability to understand others‘ emotions and modify their behaviour accordingly to suit the setting. Such people are called high self-monitors. Low self-monitors, on the other hand, always try to portray their true inner self. The relational dimension of workplace spirituality is about creating genuine relationships with the co-workers. In such a context, the question that rises is whether high selfmonitors or low self-monitors are the best suited.
LECTURE NOTES: INTRODUCTION TO MICROLOCAL ANALYSIS WITH APPLICATIONS

Course Summary 2 Notation 4 1. Recap: LCS topologies, distributions, Fourier transforms 5 1.1. Topological vector spaces 5 1.2. Space of distributions 6 1.3. Schwartz kernel theorem 8 1.4. Fourier transform 9 2. Symbol classes, oscillatory integrals and Fourier Integral Operators 10 2.1. Symbol classes 10 2.2. Oscillatory integrals 13 3. Method of stationary phase 16 4. Algebra of pseudodifferential operators 18 4.1. Changes of variables (Kuranishi trick) 22 5. Elliptic operators and L-continuity 23 5.1. L-continuity 25 5.2. Sobolev spaces and PDOs 26 6. The wavefront set of a distribution 29 6.1. Operations with distributions: pullbacks and products 33 7. Manifolds 36 8. Quantum ergodicity 38 8.1. Ergodic theory 39 8.2. Statement and ingredients 41 8.3. Main proof of Quantum Ergodicity 44 9. Semiclassical calculus and Weyl’s law 46 9.1. Proof of Weyl’s law 48 References 50
Effect of soy protein isolate on the functional, pasting, and sensory acceptability of cassava starchbased custard

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2017 The Authors. Food Science & Nutrition published by Wiley Periodicals, Inc. 1Department of Food Technology, Federal Institute of Industrial Research, Oshodi, Lagos, Lagos, Nigeria 2Department of Food Science and Technology, Federal University of Agriculture, Abeokuta, Ogun State, Nigeria 3Department of Chemical Sciences, Federal University of Agriculture, Abeokuta, Ogun State, Nigeria 4International Institutes of Tropical Agriculture, Eastern African Hub, Dar es Salaam, Tanzania
Hi, Can I Help? Exploring How to Design a Mental Health Chatbot for Youths

Chatbots represent new opportunities for low-threshold preventive mental health support to youths. To provide needed knowledge regarding how to design chatbots for this purpose, we present an exploratory design study where we designed and evaluated a prototype chatbot to complement the work of school nurses in the school health service. The prototype was designed with particular regard for preventive mental health support. The design process involved school nurses, digital health workers, and youths. Through user insight activities, we identified four types of support to be provided through the chatbot: informational, relational, processual, and referral. We explored these four types of support through concept development and prototyping. These results are discussed as a potential basis for a framework for understanding youths’ needs regarding chatbots for preventive mental health support. When discussing the study findings, we point out how the study contributes to theory and practice and suggest avenues for future research.
A Review on HOG Feature Extraction based LDA Classification on Medical Image Processing

– In this study, I have referred few papers on Histogram of Oriented Gradients ( HOG) feature extraction and Linear Discriminant Analysis( LDA) classification. HOG is basically used for object detection where as LDA is one of the supervised classification. They have used these algorithms for different identification based on required part of the human body. So, here we would be seeing both these algorithms used individually or in combination with other algorithms to obtain required results. But here I will be surveying these papers by focusing on HOG & LDA, so that combining HOG with LDA after considering the strengths of both the algorithms, where in it would increase the accuracy of detection.
University of Birmingham Synthesis of Coupling Matrix for Diplexers Based on a Self-Adaptive Differential Evolution Algorithm

Diplexer coupling matrix synthesis often involves both analytical methods and optimization techniques. At present, general purpose optimization algorithms are used, but they need strong supporting information (e.g., high-quality starting points and very narrow search ranges) from analytical methods, which is not available or too complex to be obtained in many cases. Aiming to obtain the desired coupling matrix with highly reduced supporting information to relieve the pressure of analytical methods, a new optimization algorithm, called self-adaptive differential evolution for coupling matrix synthesis (SADEC), is proposed. Considering the landscape characteristics of diplexer coupling matrix synthesis problems, a new self-adaptive multipopulation search framework and a self-adaptive algorithm parameter control strategy are proposed and organized in a particular way. The performance of SADEC is demonstrated by two all-resonator-based narrowband diplexers using large search ranges only with the requirement of matching the diplexer topology and no ad hoc analysis is included. Experiments and comparisons show the high performance of SADEC and clear advantages compared with the state-of-the-art global optimization methods. SADEC is also applicable to filter coupling matrix synthesis and is downloadable.
Are Loneliness and Emotional Intelligence Important Factors for Adolescents? Understanding the Influence of Bullying and Cyberbullying Victimisation on Suicidal Ideation

The aims of the present study were to examine whether (1) loneliness mediated the association between two types of peer victimisation and suicidal ideation and (2) emotional intelligence (EI) played a moderating role in the indirect and/or direct effect of a mediation model in a large sample of adolescents. Cross-sectional data on 1,929 students (Mage = 14.65, SD = 1.79) were analysed. A self-report questionnaire was used to measure demographic variables (course grade, sex, and age), peer victimisation types (traditional and cybervictimisation), loneliness, EI, and suicidal ideation. The results indicated that loneliness only partially mediated the relationship between traditional victimisation and suicidal ideation. By contrast, loneliness was not a significant mediator between cybervictimisation and suicidal ideation. Furthermore, the indirect effects of the mediation model for traditional victimisation were moderated by EI. The greater the level of EI, the weaker the indirect effects of traditional victimisation on suicidal ideation. The findings suggest that interventions targeted at improving EI abilities may help break the links among peer victimisation, loneliness, and suicidal ideation in adolescent victims of bullying.
Modia3D: Modeling and Simulation of 3D-Systems in Julia

Modia3D is an experimental Julia package to model and simulate 3D mechanical systems. Ideas from modern game engines are used to achieve a highly ﬂexible setup and features of multi-body algorithms are used to get a rigid mathematical formulation and support, for example, of closed kinematic loops. Collision handling is performed on convex geometries with elastic response calculation. A Modia3D model is solved with a variable-step solver. This is important to combine Modia3D with the equation-based modeling system Modia in the future.
Snakebite Classification Using Active Contour Model and K Nearest Neighbor

Indonesia is categorized as one of tropical countries that have a high risk of snakebites. This surely may endanger rural citizens’ lives for there are still many snakes found in rural areas. The main cause of death from snakebite cases is by reason of the venom squirted from snake’s canine teeth. Others causes are errors in identifying the bite marks visually. There are anatomical differences between puncture wounds from venomous and non-venomous snakes. This study established a snakebite identification system using Active Contour Model and K Nearest Neighbor (KNN) methods. By performing some tests related to the parameters used in the method, the highest accuracy value on K Nearest Neighbor method was obtained by using the correlation distance rule, the K value = 3, without using distance weight in the classification system.
Comparative Study of AI-Based Methods—Application of Analyzing Inflow and Infiltration in Sanitary Sewer Subcatchments

Inflow and infiltration (I/I) is a common problem in sanitary sewer systems. The I/I rate is also considered to be an important indicator of the operational and structural condition of the sewer system. Situation awareness in sanitary sewer systems requires accurate wastewater-flow information at a fine spatiotemporal scale. This study aims to develop artificial intelligence (AI)-based models (adaptive neurofuzzy inference system (ANFIS) and multilayer perceptron neural network (MLPNN)) and to compare their performance for identifying the potential inflow and infiltration of the sanitary sewer subcatchment of two pumping stations. We tested the performance of these AI models by using data gathered from two pumping stations through a supervisory control and data acquisition (SCADA) system. As a result, these two AI models produced similar inflow and infiltration patterns—both subcatchments experienced inflow and infiltration. On the other hand, the ANFIS had overall higher performance than that of the MLPNN model for modelling the I/I situation for the catchments. The results of the research can be used to support spatial decision making in sewer system maintenance.
Engineering a Model to Study Viral Infections: Bioprinting, Microfluidics, and Organoids to Defeat Coronavirus Disease 2019 (COVID-19)

While the number of studies related to severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) is constantly growing, it is essential to provide a framework of modeling viral infections. Therefore, this review aims to describe the background presented by earlier used models for viral studies and an approach to design an “ideal” tissue model for SARS-CoV-2 infection. Due to the previous successful achievements in antiviral research and tissue engineering, combining the emerging techniques such as bioprinting, microfluidics, and organoid formation are considered to be one of the best approaches to form in vitro tissue models. The fabrication of an integrated multi-tissue bioprinted platform tailored for SARS-CoV-2 infection can be a great breakthrough that can help defeat coronavirus disease in 2019.
A Finite Element Formulation of Baraff‐Witkin Cloth

The Baraff‐Witkin [BW98] model has been a popular formulation for cloth for 20 years. However, its relationship to the finite element method (FEM) has always been unclear, because the model resists being written as an isotropic, hyperelastic strain energy. In this paper, we show that this is because the Baraff‐Witkin model is actually a coupled anisotropic strain energy. We show that its stretching term approximates the isotropic As‐Rigid‐As‐Possible (ARAP) energy, and its shearing term is a cross‐fiber coupling energy common in biomechanics. While it has been known empirically for some time that the model can produce indefinite force Jacobians, the conditions under which they occur has never been clear. Our formulation enables a complete eigenanalysis that precisely characterizes exactly when indefiniteness occurs, and leads to fast, analytic, semi‐positive‐definite projection methods. Finally, our analysis suggests a generalized Baraff‐Witkin energy with non‐orthogonal warp and weft directions.
JokeR: A Recurrent Joker

Generating jokes is a challenging and understud-ied task of Natural Language Processing. A computer that intends and succeeds to generate jokes could be deemed artiﬁcially intelligent. We present a couple of novel approaches to joke generation, such as using SeqGAN and a language model. We implement a variety of word-level models to tackle parts of the joke-generation problem, namely text generation and joke clas-siﬁcation. Ideally, merging these steps will allow for a model to write joke candidates, that are then pruned by a well-trained classiﬁer. We train these models from a corpus of 231,657 user-written jokes scraped from reddit.com 1 .
3D Marine Sedimentary Reservoir Stochastic Simulation Accounting for High Resolution Sequence Stratigraphy and Sedimentological Rules

Quantifying the proportions and distribution of rock types is a key step in modeling sedimentary formations, since it greatly determines the quality of petrophysical and dynamic ﬂow models. While forward stratigraphic models well reproduce deposition processes, they rely on inversion for data conditioning, which critically raises the empty space problem. Therefore, several stochastic methods have been suggested to simulate proportions and distribution of rock types in reservoirs respecting the observation data while reproducing realistic spatial patterns. However, these methods are always limited by the stationarity decision. We propose a method to generate 3D facies probability cubes which account for well and seismic data, stratigraphic interpretation, sedimentological rules describing the spatial distribution of rock types, and sequence stratigraphy principles. Different probability cubes are computed by integrating various information controlling the lithofacies occurrence, for instance the stratigraphic control of the shoreline migration, by deﬁning linear or inequality constraints at the spatial estimation stage. The generated P-ﬁeld cubes can then be combined considering the redundancy of the data they express such as the tau model. This methodology is demonstrated on typical synthetic data sets and on a North Sea reservoir.
VALUING BARRIER OPTIONS USING THE ADAPTIVE DISCONTINUOUS GALERKIN METHOD

This paper is devoted to barrier options and the main objective is to develop a sufficiently robust, accurate and efficient method for computation of their values driven according to the well-known Black-Scholes equation. The main idea is based on the discontinuous Galerkin method together with a spatial adaptive approach. This combination seems to be a promising technique for the solving of such problems with discontinuous solutions as well as for consequent optimization of the number of degrees of freedom and computational cost. The appended numerical experiment illustrates the potency of the proposed numerical scheme.
Atypical manifestations in children with Guillain–Barré syndrome

Introduction: Guillain–Barré syndrome (GBS) is an acute single-phase inflammatory demyelinating polyneuropathy that occurs after an infection, characterized by a clinical pattern of acral paresthesias, ascending generalized weakness, and areflexia. Its worldwide incidence ranges from 0.5 to 1.5/100,000 children/year, predominantly males. In children, the predominant symptoms are vague paresthesias, significant, poorly localized pain, weakness manifesting as disturbance of gait, and cranial nerve abnormalities, with facial nerves most commonly affected. Case Report: A 13-month-old female patient, crying for five days, presented with low fever, progressive, asymmetric loss of strength in lower limbs, regular general condition, tachypnea, tachycardia, hypotonia of right upper limb and left lower limb, positive Babinski sign to the right, Achilles and patellar tendon areflexia, discreet neck stiffness, hypoesthesia, and pain from the lower limbs to the xiphoid process, leading to the diagnosis of GBS. The cerebrospinal fluid did not indicate any alterations and Julia Brasileiro de Faria Cavalcante1, Pedro Nogarotto Cembraneli1, Renata Brasileiro de Faria Cavalcante2, Volmer Fernandes Valente Junior2, José Edison da Silva Cavalcante3 Affiliations: 1Medical Sciences Course, Health Sciences School, Faculdade Ceres (FACERES), São José do Rio Preto, SP, Brazil; 2Neurosurgeon, Member of the Brazilian Society of Neurosurgery, Santa Mônica Hospital, Goiânia, GO, Brazil; 3Neurosurgeon, PhD in Neurosurgery, Member of the Brazilian Society of Neurosurgery, Professor at Santa Mônica Hospital, Goiânia, GO, Brazil. Corresponding Author: Julia Brasileiro de Faria Cavalcante, Rua T38, 1097, Setor Bueno, apt 601, Goiânia, GO, Brazil; Email: jubf.cavalcante@outlook.com Received: 23 January 2020 Accepted: 01 April 2020 Published: 06 May 2020 PEER REVIEWED | OPEN A CE S the electroneuromyography showed reduced motor unit action potentials and normal motor conduction velocity, revealing acute motor axonal neuropathy. The patient developed respiratory arrest, requiring intensive care therapy, and orotracheal intubation. Immunoglobulin therapy was initiated and the patient gradually recovered the movements and reflexes. Conclusion: It is very important to point out that when GBS is suspected, even if it is atypical, the patient should be admitted to the pediatric intensive care unit. This allows intensive nursing care and continuous monitoring to reduce the frequency and severity of complications.
Statistical Anomaly Detection and Mitigation of Cyber Attacks for Statistical Anomaly Detection and Mitigation of Cyber Attacks for Intelligent Transportation Systems Intelligent Transportation Systems

Secure vehicular communication is a critical factor for secure traffic management. Perfect security in intelligent transportation systems (ITS) has solid and efficient intrusion detection systems (IDS). In this paper, we consider false data injection attacks and distributed denial-of-service attacks (DDoS), especially the stealth low-rate DDoS attacks, targeting the integrity and availability, respectively, in vehicular ad-hoc networks (VANET). Novel statistical intrusion detection and mitigation techniques are proposed for the considered attacks. The performance of the proposed methods are evaluated using a traffic simulator and a real traffic dataset. Comparisons with the state-of-the-art solutions clearly demonstrate the superior performance of the proposed methods in terms of quick and accurate detection and localization of cyber-attacks.
Relationship between Coyote Group Size and Diet in Southeastern Colorado

We investigated the diet of coyotes (Canis latrans) on the Pifion Canyon Maneuver Site (PCMS) in southeastern Colorado from February 1983 to June 1986. Based on regression analysis, 71% of the variation in the volume of large prey (e.g., adult ungulates) in coyote scats could be explained by coyote group size; 77% of this variation could be explained by coyote group size and snow depth. Snow depth alone explained 28% of the variation in the volume of large prey in the scats. Coyote group size explained 19% of the variation in the volume of medium size prey (e.g., lagomorphs and ungulate fawns) and 38% of the variation in the volume of small prey (e.g., rodents). Coyote groups were largest in winter and smallest in summer. Most juveniles dispersed before the largest group sizes were observed. Group foraging and snow depth may influence prey selection by coyotes in southeastern Colorado. J. WILDL. MANAGE. 52(4):647-653 Diets of coyotes have been examined (Fichter et al. 1955, Gipson 1974, MacCracken 1981) but few studies have examined the relationship of prey selection and coyote social organization. In Jasper National Park, Alberta, during summer, when rodents were the major food, mean coyote group size was 1.4 (Bowen 1978, 1981). In winter, when ungulates were the major food, group size averaged 2.0. Mean group size in Wyoming was 1.3 coyotes in summer, when rodents were the major resource consumed; in winter, when ungulate carrion dominated the diet, coyote group size was 1.8 (Bekoff and Wells 1980). Bekoff and Wells (1980) noted that during 3 successive winters in Rocky Mountain National Park, Colorado, when no ungulate carrion was available, coyotes preyed on small mammals throughout the year. Mean group size for coyotes was 1.1 in summer and winter. Bowen (1978, 1981) and Bekoff and Wells (1980) concluded that when coyotes were feeding on large prey, group sizes were correspondingly larger, which increased foraging efficiency. They further observed that delayed dispersal of pups resulted in the formation of larger packs; however, seasonal variation in the diet still accounted for much of the variation in the number of pack members observed together. Messier and Barrette (1982) found no relationship between prey size and coyote group size in Quebec; they concluded that larger coyote groups could be explained by delayed dispersal of juveniles. The obj ctive of our study was to document the diet of coyotes in southeastern Colorado and examine the relationship between prey size, pack sociality, time of juvenile dispersal, and group