Miracle-dz/UniFAR-FTUs huggingface dataset:
Thermal niche partitioning and phenology of Nearctic and Palearctic flea (Siphonaptera) communities on rodents (Mammalia: Rodentia) from five ecoregions

ABSTRACT: Seasonality of fleas (Siphonaptera) may be due to species competition, prompting the idea that flea species partition temperature, along with correlated variables such as moisture (thermal-niche partitioning hypothesis). I compared the fleas of five rodent-flea communities described from the literature for thermal-niche optima by fitting non-linear LRF (Lobry–Rosso–Flandrois) curves to examine whether flea species in a community show distinct, partitioned thermal niches. LRF curves estimate physiological parameters of temperature minimum, optimum, maximum, and maximum abundance, and facilitate comparison between species by summarizing seasonal data. Flea-communities were on Nearctic Southern flying squirrel (Glaucomys volans volans), Richardson's ground-squirrel (Urocitellus richardsonii), North American deer-mouse (Peromyscus maniculatus), and Palearctic Midday jird (Meriones meridianus), and Wagner's gerbil (Dipodillus dasyurus). Flea communities appeared to show seasonality consistent with thermal-niche partitioning. Several flea families and genera had characteristic thermal niches: Ceratophyllidae had broad tolerance to extreme temperature, Leptopsyllidae (one species in this study) to cold, and Pulicidae to hot. In contrast, at the local, species level, climatic speciation could be significant in flea diversification. Non-competition hypotheses (environmental filtering, neutrality) require testing, too. Thermal-niche partitioning may increase flea species richness on hosts and could occur in other insect and plant communities. Implications for biodiversity conservation and disease ecology under global warming are wide-ranging.
Design recommendations for chatbots to support people with depression

Depression has been one of the leading causes of disability worldwide. In addition to conventional drugs and clinical treatments, other forms of treatment are also available. For example, computational solutions have been developed to prevent, screen for, and assist the treatment of depression. More specifically, chatbots are computer systems that have been used to provide therapeutic support for individuals diagnosed with depression. Although these systems are commercially available, their design rationale and evaluation are still not fully validated, and further research is needed. Therefore, in this study we (1) select and compare chatbots for depression; (2) present the results of the analysis to healthcare specialists for assessment; (3) formalize the design recommendations for chatbots for people with depression; and (4) check the recommendations with mental healthcare and HCI professionals. We carried out a benchmark of chatbots for people with depression and conducted three discussion sessions involving five experts in mental healthcare and one expert in HCI. As a result, we provide a list of 24 design recommendations encompassing user interface elements, conversation styles, personalization features, among others. Finally, two healthcare and another HCI professionals read the recommendations to check adequacy to both areas.
A Survey on Seismic Sensor based Target Detection, Localization, Identification, and Activity Recognition

Current sensor technologies facilitate device-free and non-invasive monitoring of target activities and infrastructures to ensure a safe and inhabitable environment. Device-free techniques for sensing the surrounding environment are an emerging area of research where a target does not need to carry or attach any device to provide information about its motion or the surrounding environment. Consequently, there has been an increasing interest in device-free sensing. Seismic sensors are extremely effective tools for gathering target motion information. In this paper, we provide a comprehensive overview of the seismic sensor-based device-free sensing process and highlight the key techniques within the research field. We classify the existing literature into three categories, viz., (i) target detection, (ii) target localization, and (iii) target identification, and activity recognition. The techniques in each category are divided into multiple subcategories in a structured manner to comprehensively discuss the details. We also discuss the challenges associated with contemporary cutting-edge research and suggest potential solutions.
Poisoning GNN-based Recommender Systems with Generative Surrogate-based Attacks

With recent advancements in graph neural networks (GNN), GNN-based recommender systems (gRS) have achieved remarkable success in the past few years. Despite this success, existing research reveals that gRSs are still vulnerable to poison attacks, in which the attackers inject fake data to manipulate recommendation results as they desire. This might be due to the fact that existing poison attacks (and countermeasures) are either model-agnostic or specifically designed for traditional recommender algorithms (e.g., neighborhood-based, matrix-factorization-based, or deep-learning-based RSs) that are not gRS. As gRSs are widely adopted in the industry, the problem of how to design poison attacks for gRSs has become a need for robust user experience. Herein, we focus on the use of poison attacks to manipulate item promotion in gRSs. Compared to standard GNNs, attacking gRSs is more challenging due to the heterogeneity of network structure and the entanglement between users and items. To overcome such challenges, we propose GSPAttack—a generative surrogate-based poison attack framework for gRSs. GSPAttack tailors a learning process to surrogate a recommendation model as well as generate fake users and user-item interactions while preserving the data correlation between users and items for recommendation accuracy. Although maintaining high accuracy for other items rather than the target item seems counterintuitive, it is equally crucial to the success of a poison attack. Extensive evaluations on four real-world datasets revealed that GSPAttack outperforms all baselines with competent recommendation performance and is resistant to various countermeasures.
Prototype of deployment of Federated Learning with IoT devices

In the age of technology, data is an increasingly important resource. This importance is growing in the field of Artificial Intelligence (AI), where sub fields such as Machine Learning (ML) need more and more data to achieve better results. Internet of Things (IoT) is the connection of sensors and smart objects to collect and exchange data, in addition to achieving many other tasks. A huge amount of the resource desired, data, is stored in mobile devices, sensors and other Internet of Things (IoT) devices, but remains there due to data protection restrictions. At the same time these devices do not have enough data or computational capacity to train good models. Moreover, transmitting, storing and processing all this data on a centralised server is problematic. Federated Learning (FL) provides an innovative solution that allows devices to learn in a collaborative way. More importantly, it accomplishes this without violating data protection laws. FL is currently growing, and there are several solutions that implement it. This article presents a prototype of a FL solution where the IoT devices used were raspberry pi boards. The results compare the performance of a solution of this type with those obtained in traditional approaches. In addition, the FL solution performance was tested in a hostile environment. A convolutional neural network (CNN) and a image data set were used. The results show the feasibility and usability of these techniques, although in many cases they do not reach the performance of traditional approaches.
UX research in the software industry: an investigation of long-term UX practices

Software industry has sought to apply practices that provide a more meaningful User eXperience (UX) and help maintain a sustainable business. UX Research practices allows conducting research and evaluations with users from the application of methods and techniques. Some UX Research practices reveal longitudinal UX research actions (i.e., Long-Term UX) when they track products' use by users over time. The literature is scarce about studies that discuss the UX Research practices adopted by the software industry and their relationship with the different moments of product use (i.e., before, during, or after). Therefore, we surveyed the UX Research practices which are applied in software development in industry following the systematic literature review process. We selected 45 papers and conducted a qualitative analysis by applying coding techniques. As a result, we identify 38 practices which are classified into six categories, i.e. research planning, data collection with users, data analysis, design with research, organization and communication, and training for the research. Our findings show that 15 of 38 practices are related to Long-Term UX. We also identified the attitudes and needs of Long-Term UX experienced by the software industry.
SELF-SIMILAR ULTRARELATIVISTIC JETTED BLAST WAVE

Following a suggestion that a directed relativistic explosion may have a universal intermediate asymptotic, we derive a self-similar solution for an ultrarelativistic jetted blast wave. The solution involves three distinct regions: an approximately paraboloid head where the Lorentz factor γ exceeds ∼ 1 / 2 ? > of its maximal, nose value; a geometrically self-similar, expanding envelope slightly narrower than a paraboloid; and an axial core in which the (cylindrically, henceforth) radial flow u ? > converges inward toward the axis. Most (∼80%) of the energy lies well beyond the leading, head region. Here, a radial cross section shows a maximal γ (separating the core and the envelope), a sign reversal in u ? > , and a minimal γ, at respectively ∼1/6, ∼1/4, and ∼3/4 of the shock radius. The solution is apparently unique, and approximately agrees with previous simulations, of different initial conditions, that resolved the head. This suggests that unlike a spherical relativistic blast wave, our solution is an attractor, and may thus describe directed blast waves such as in the external shock phase of a γ-ray burst.
Knowledge Graphs for Multidisciplinary Co-Design: Introducing RDF to BHoM

Architecture, engineering, and construction (AEC) projects require multidisciplinary solutions; therefore, one physical asset results in several disciplinary representations. Interoperability problems between different software often hinder disciplinary data integration, which prevents the recognition of violated design constraints until it is too late. The open-source platform Building Habitat object Model (BHoM) integrates many AEC concepts across existing languages and platforms, allowing multiple discrete disciplinary representations of buildings. The Linked Building Data Community Group of the World Wide Web Consortium uses Semantic Web standards to store and share data. This paper explores and presents methods to recast BHoM's object model as a knowledge graph using Semantic Web standards. It analyzes BHoM in an ontological context by elaborating on its approach to object-oriented programming and comparing it to the Semantic Web standards. Furthermore, it presents BHoM RDF prototypes as a potential solution to the interoperability problem of multidisciplinary design in AEC. It exemplifies BHoM RDF prototypes on a small demonstrator project. When combined with Semantic Web standards, the BHoM framework can increase the use of knowledge graphs in the AEC industry, improving data interoperability and assisting design decisions through reasoning. method a mapping approach Web ontologies The RDF prototype results refinement ontology properties and data work focus on refining BHoM’s terminological translation that RDF_Toolkit generates, e.g. refining relations, developing alignment modules between domain-specific ontologies, modularising concept-specific ontologies based on building systems, etc.
HST/STIS ULTRAVIOLET SPECTROSCOPY OF THE COMPONENTS OF THE MASSIVE TRIPLE STAR δ ORI A

The multiple star system of δ Orionis is one of the closest examples of a system containing a luminous O-type, bright giant star (component Aa1). It is often used as a spectral-type standard and has the highest observed X-ray flux of any hot-star binary. The main component Aa1 is orbited by two lower mass stars, faint Aa2 in a 5.7 day eclipsing binary, and Ab, an astrometric companion with an estimated period of 346 years. Generally the flux from all three stars is recorded in ground-based spectroscopy, and the spectral decomposition of the components has proved difficult. Here we present Hubble Space Telescope/Space Telescope Imaging Spectrograph ultraviolet spectroscopy of δ Ori A that provides us with spatially separated spectra of Aa and Ab for the first time. We measured radial velocities for Aa1 and Ab in two observations made near the velocity extrema of Aa1. We show tentative evidence for the detection of the Aa2 component in cross-correlation functions of the observed and model spectra. We discuss the appearance of the UV spectra of Aa1 and Ab with reference to model spectra. Both stars have similar effective temperatures, but Ab is fainter and is a rapid rotator. The results will help in the interpretation of ground-based spectroscopy and in understanding the physical and evolutionary parameters of these massive stars.
Long distance two-party quantum cryptography made simple

Any two-party cryptographic primitive can be implemented using quantum communication under the assumption that it is difficult to store a large number of quantum states perfectly. However, achieving reliable quantum communication over long distances remains a difficult problem. Here, we consider a large network of nodes with only neighboring quantum links. We exploit properties of this cloud of nodes to enable any two nodes to achieve security even if they are not directly connected. Our results are based on techniques from classical cryptography and do not resort to technologically difficult procedures like entanglement swapping. More precisely, we show that oblivious transfer can be achieved in such a network if and only if there exists a path in the network between the sender and the receiver along which all nodes are honest. Finally, we show that useful notions of security can still be achieved when we relax the assumption of an honest path. For example, we show that we can combine our protocol for oblivious transfer with computational assumptions such that we obtain security if either there exists an honest path, or, as a backup, at least the adversary cannot solve a computational problem.
ACHIEVE3000 , 2015-2016

Based on the Lexile ® Framework, a scientific approach to reading and text measurement backed by more than two decades of ongoing research, Achieve3000 ® , a web-based differentiated reading program used by HISD, is designed to improve student reading ability and comprehension of increasingly complex texts by initially meeting students where they are academically. The present study focuses on cohorts of 9 th and 10 th graders and assesses the impact deriving from the use of Achieve3000’s reading solutions on students’ scale score performance on the State of Texas Assessments of Academic Readiness End-Of-Course (STAAR EOC) for the English I and English II exams. Utilizing the inverse-probability-weighted regression adjusted (IPWRA) estimation method to account for the non-randomness of student self-selection into Achieve3000 usage, the results of this evaluation may be viewed as causal. Findings suggest that students’ use of Achieve3000’s web-based software leads to higher performance on the STAAR EOC exams than non-use of Achieve3000. Controlling for student- and school-level factors, the treatment effect among 9 th -grade Achieve3000 students was 50 scale score points higher than the potential outcome mean among their non-Achieve3000 peers on the English I assessment. The corresponding gain for 10 th -grade Achieve3000 students over their non-Achieve3000 peers was 69 scale score points on the English II assessment. Based on these findings, it is recommended that teachers in schools that have Achieve3000 licenses actively encourage the completion of Achieve3000 exercises.
Thermodynamics, by H.J. Kreuzer and Isaac Tamblyn

that we ourselves apply to nature, but at the same time he affirms that nature is ‘orderly’. What does this exactly mean – what is the difference between order and law? There is a chapter on the subject of theories, which he regards as our way of formulating explanations within science; theories can in particular explain laws. I would have liked much firmer statements on all of this. Rosen’s attempts to define what he seeks to say come over too often as vague and intuitive, even though he tries very hard to get his meaning across and there are helpful summaries at the ends of the chapters. The final tantalising conclusion is that quantum mechanics involves the observer too strongly in its account of nature for science to provide a completely objective description, even though objectivity is the business of science. There must therefore be some kind of objective reality transcending physical nature and science and ‘most likely surpassing human understanding’. This is extremely interesting, but the interpretation of quantum physics is a notoriously controversial and subtle area, and it needs a much more thorough treatment than Rosen gives it. He does not want to be technical, but in my view he errs far too much towards informality. Even for a general readership, this very significant conclusion needs to be argued in a clearer, more precise and more informative way. As things stand, then, this book is an interesting read but a rather frustrating one, and I do not see it as making a big impact. A pity.
A multiloop generalization of the circle stability criterion

Abstract : A frequency-domain stability criterion is presented, generalizing the well-known circle stability criterion to multiloop feedback systems having bounded nonlinearity, parameter variations, and/or frequency-dependent ignorance of component dynamics. Unlike previous generalizations, the theory is not restricted to weakly-coupled, diagonally dominant or nearly normal systems. Potential applications include the analysis of feedback system integrity and multiloop feedback system stability margins. (Author)
Longitudinal aerodynamic characteristics of a subsonic, energy-efficient transport configuration in the National Transonic Facility

The Reynolds number, aeroelasticity, boundary layer transition, and nonadiabatic wall temperature effects, and data repeatability was determined in the National Transonic Facility (NTF) for a subsonic, energy efficient transport model. The model was tested over a Mach number range of 0.50 to 0.86 and a Reynolds number range of 1.9 million to approximately 23.0 million (based on mean geometric chord). The majority of the data was taken using cryogenic nitrogen (data at 1.9 million Reynolds number was taken in air). Force and moment, wing pressure, and wing thermocouple data are presented. The data indicate that increasing Reynolds number resulted in greater effective camber of the supercritical wing and horizontal tail, resulting in greater lift and pitching moment coefficients at nearly all angles of attack for M = 0.82. As Reynolds number was increased, untrimmed L/D increased, the angle of attack for maximum L/D decreased, drag creep was reduced significantly, and drag divergence Mach number increased slightly. Data repeatability for both modes of operation of the NTF (air and cryogenic nitrogen) was generally very good, and nonadiabatic wall effects were estimated to be small. Transition-free and transition-fixed configurations had significantly different force and moment data at M = 0.82 for low Reynolds number, and very small differences were noted at high Reynolds numbers.
Reducing Compressor Vibrations by Load Torque Compensation from Acoustic Perspective

As heat pumps helpmeeting the CO2 reduction goals for residential heating, a fast and steady increase of residential heat pump sales is predicted. To enable the installation of heat pumps in densely populated areas, very low noise targets have to be met, especially in the European markets. One major noise source of heat pumps is the compressor. Many authors have identified load torque compensation (LTC) as promisingmethod to reduce noise and vibrations of compressors. So far, this topic has been approached from a control-perspective with focus on developing suitable controller strategies. This paper, in contrast, analyses LTC from an acoustic point of view. It identifies which compressor excitations and hence vibrations can be reduced by LTC and which cannot. With this knowledge the noise reduction potential of LTC can be predicted. Therefore we performed vibration measurements on the compressor surface with and without LTC. To investigate the effects of LTC inside the compressor and consequentially evaluate the potenial of LTC we performed multibody simulations. These simulations cover the path from the load torque source via the applied driving torque to the compressor vibrations. As input for the multibody simulation, the load torque to be compensated is calculated from thermodynamic and geometrical relationships. With our investigations we deliver the following findings: First, we derive how much certain vibration orders can be reduced by LTC. For the investigated twin rotary compressor, we were able to reduce even orders but not odd orders. Second, we estimate the reduction potential of LTC at different operational points. The reduction potential is increasingwith higher pressure differences and decreasingwith increasing rotational speed. Third we identify which vibration directions can be reduced by LTC. Based on these results, LTC can be combined more efficiently with other noise reduction measures, leading to quieter heat pumps.
Integrating Paraphrasing into the FRANK QA System

We present a study into the ability of paraphrase generation to increase the variety of natural language queries that the Frank Query Answering system can answer. We choose an English-French backtransla-tion model to generate paraphrases, which we test using a small challenge dataset. We conclude that this method is not useful for improving the variety of natural language queries that Frank can answer . Based on our observations, we recommend future work in the following directions: (1) allowing the ability to specify a form to paraphrase an input into; (2) constrained paraphrasing to avoid loss of information about query intent; and (3) the need for an automatic evaluation metric which captures semantic similarity, allows syntactic variation, and rewards preservation of query intent.