Miracle-dz/UniFAR-FTUs huggingface dataset:
Measurement invariance within and between subjects: A distinct problem in testing the equivalence of intra- and inter-individual model structures

19 We address the question of equivalence between modeling results obtained on intra20 individual and inter-individual levels of psychometric analysis. Our focus is on the concept of 21 measurement invariance and the role it may play in this context. We discuss this in general 22 against the background of the latent variable paradigm, complemented by an operational 23 demonstration in terms of a linear state-space model, i.e., a time series model with latent var24 iables. Implemented in a multiple-occasion and multiple-subject setting, the model simulta25 neously accounts for intra-individual and inter-individual differences. We consider the condi26 tions – in terms of invariance constraints – under which modeling results are generalizable (a) 27 over time within subjects, (b) over subjects within occasions, and (c) over time and subjects 28 simultaneously thus implying an equivalence-relationship between both dimensions. Since 29 we distinguish the measurement model from the structural model governing relations be30 tween the latent variables of interest, we decompose the invariance constraints into those that 31 involve structural parameters and those that involve measurement parameters and relate to 32 measurement invariance. Within the resulting taxonomy of models, we show that, under the 33 condition of measurement invariance over time and subjects, there exists a form of structural 34 equivalence between levels of analysis that is distinct from full structural equivalence, i.e., 35 ergodicity. We demonstrate how measurement invariance between and within subjects can be 36 tested in the context of high-frequency repeated measures in personality research. Finally, we 37 discuss problems of measurement variance in relation to problems of non-ergodicity as cur38 rently discussed and approached in the literature. 39
Ultrafast Low-Loss 40-70 GHz SiGe SPST Switch

The design and characterization of an ultrafast 4070GHz single-pole single-throw absorptive (SPST) differential switch are presented. The switch exhibits low insertion loss, less than 1 dB, and dynamic isolation better than 20 dB over a 30GHz frequency span from 40 GHz to 70 GHz. Sub-nanosecond switching time is achieved by adopting a differential currentsteering technique. The switch’s measured envelope rise time and fall time of less than 50ps suggest that switching rates of up to 5 Gbps are achievable. To our best knowledge this is the fastest SPST switch yet reported that can operate at 60GHz.
Using Digital Stories to Address Sustainability Literacy : Designing a University Hybrid Course to Inspire and Engage Millennial Learners

Instructional design, at its core, is a systematic approach to developing educational materials with specific intended learning outcomes, teaching strategies, and evaluative mechanisms for gathering feedback (Gagne, Wagner, Golas, Keller, & Russell, 2005). It is this process that has enabled Arizona State University (ASU) to create an innovative hybrid course designed to address one of the major challenges facing the 21st century: the idea of creating a more sustainable future. This notion of sustainability is widely defined as, “. a concern for intergenerational equity” and the ability to meet a generation’s needs while not putting the ability for a future generation to meet its needs in danger (Nolet, 2009, p. 413). Considering the increase in the number of people across the globe without access to life’s basic necessities, issues of sustainability are more central than ever before.
Maintenance of the Photovolatic PlantsUsing UAV Equipped with Low-costGNSS RTK Receiver

Global Navigation Satellite System (GNSS) Real Time Kinematic (RTK) employs high-end dual-frequency receivers and antennas to deliver precise positioning that, in some way, restricts the use of GNSSRTKto a subset of user market due to very high cost. The emerging mass-market user applications, however, require centimeter-positioning accuracy considering a cost-effective solution. This calls for low-cost GNSS RTK solutions to create new possibilities for mass-market user applications to make use of GNSS high accuracy positioning in a variety of ways. One of the applications, which makes use of low-cost GNSS RTK receiver, is the maintenance of photovoltaic (PV) plants using Unmanned Aerial Vehicle (UAV). This paper proposes a solution that aims at automating the maintenance of PV plant with enhanced reliability in a time and cost effective manner, which otherwise requires intermediate human intervention. The paper presents the architectural concept, system design, and end-to-end algorithm that plays a pivotal role in enabling the automatic report generation of PV plant status. Preliminary results of the proof-of-concept shows the feasibility of the proposed solution.
Running title: Affordances after spinal cord injury

a Psychology School of Social Sciences – Heriot Watt University, Edinburgh, UK b Department of Neuroscience, University of Padua, Padua, Italy c Faculty of Psychology and Educational Sciences (FAPSE), University of Geneva, Switzerland d School of Psychology, University of East Anglia, Norwich, UK e Unipolar Spinal Unit, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy f Centre for Brain Science, Department of Psychology, University of Essex, UK g Cognitive Neuropsychology Centre, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy h Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy e NeuroMi, Milan Center for Neuroscience, Milano, Italy
Presence of ascites in bullfrog breeders reared and kept on a frog farm

Ascites is a pathology characterized by the extravasation of fluid from blood vessels and its accumulation in the abdominal cavity, caused by several associated factors. In this paper, we report the occurrence of this syndrome in breeding male and female Bullfrogs fed a commercial fish feed with 40% crude protein. Liver malformation was already observed due to lack of protein deposition in adult animals from the same spawning. The culture of ascitic fluid showed absence of bacterial growth. Kidney histopathology showed, in both sexes, a large number of tubular structures with strongly eosinophilic hyaline material suggesting colloid growth in both the cortical region and spinal cord. The analysis also revealed granulomas in various stages of development, many showing central necrotic material. The kidneys, glomerular, were mostly hypoplastic, with enlarged Bowman space, and many were hyalinized or hemorrhagic; the parenchyma showed dystrophic calcification, and many tubules containing fibrinoid material. The liver displayed a large amount of melanomacrophages in the parenchyma and foci of mono-lymphocytic hepatitis and marked cytoplasmic rarefaction, as well as several hepatocytes with pyknotic nuclei and necrotic cells and dissociation of the hepatic trabeculae. Ascites may be caused by the lesions observed in these organs.
Density-dependent changes in alewife growth following their introduction, expansion, and collapse in Otsego Lake, NY

Alewife (Alosa pseudoharengus) is an anadromous planktivore native to Atlantic coastal rivers of North America. When this species becomes landlocked in freshwater lakes, it can quickly become established as the dominant prey species. These introductions can result in unintended or undesirable consequences for water quality and fishery productivity (Rudstam et al. 2011). In the Laurentian Great Lakes, stocked salmonids are dependent upon landlocked alewife as prey, which can destabilize food-web interactions based on the “boom and bust” nature of herring population dynamics (Jones et al. 1993). In smaller, inland water bodies, alewife have altered water quality and plankton communities through grazing, which has resulted in increased hypolimnetic oxygen depletion in lakes (Harman et al. 2002). The species can have effects on forage fish communities through competition (Harman et al. 2002), and they affect a variety of fish species as efficient predators of fish larvae (Crowder 1980). Furthermore, alewife can affect reproductive success of coldwater fishes such as lake trout by causing thiamine deficiencies in the eggs of those species resulting from consumption of alewife (Brown et al. 2005). Efforts to eradicate alewife from freshwater lakes following introduction have had variable effects, but often fall short of management targets (e.g., Rudstam et al. 2011).
Telescope Matching: Reducing Model Dependence in the Estimation of Controlled Direct Effects

Matching methods are widely used to reduce the dependence of causal inferences on modeling assumptions, but their application has been mostly limited to the overall effect of a single treatment. The controlled direct effect, which is the effect of a treatment fixing some mediator, has become an increasingly popular estimand in the social and biomedical sciences. Standard matching analyses, however, are not directly applicable to the estimation of this quantity because of their tendency to induce post-treatment bias, and so almost all applications that estimate these effects are dependent on the correct specification of several models. In this paper, we propose a novel two-step matching approach to estimating direct effects, telescope matching, that reduces model dependence without inducing post-treatment bias. This method uses matching with replacement to impute missing counterfactual outcomes and then employs flexible regression models to correct for bias induced by imperfect matches. We derive the asymptotic properties of this estimator and provide a consistent estimator for its variance. We apply this approach to estimate the effectiveness of a job training program on health fixing the value of post-training employment. *Thanks toAlberto Abadie, Paul Kellstedt, Gary King, Jamie Robins, Jann Spiess, and Yiqing Xu for valuable feedback and discussions. Any remaining errors are our own. Software to implement the methods in this paper will be found in the DirectEffects R package on CRAN. †Department of Government and Institute for Quantitative Social Science, Harvard University, 1737 Cambridge St, ma 02138. web: http://www.mattblackwell. org email: mblackwell@gov.harvard. edu ‡New York University, 60 5th Ave, New York, NY 10011, web: https://www.antonstrezhnev. com/ email: as6672@nyu.edu
A Novel Framework to Classify Malware in MIPS Architecture-Based IoT Devices

Malware on devices connected to the Internet via the Internet of Things (IoT) is evolving and is a core component of the fourth industrial revolution. IoT devices use the MIPS architecture with a large proportion running on embedded Linux operating systems, but the automatic analysis of IoT malware has not been resolved. We proposed a framework to classify malware in IoT devices by using MIPS-based system behavior (system call—syscall) obtained from our F-Sandbox passive process and machine learning techniques. The F-Sandbox is a new type for IoT sandbox, automatically created from the real firmware of the specialized IoT devices, inheriting the specialized environment in the real firmware, therefore creating a diverse environment for sandboxing as an important characteristic of IoT sandbox. This framework classifies five families of IoT malware with F1-Weight = 97.44%.
Optimal dividend problem with a terminal value for spectrally positive Lvy processes

In this paperwe consider amodified version of the classical optimal dividend problem taking into account both expected dividends and the time value of ruin. We assume that the risk process is modeled by a general spectrally positive Lévy process before dividends are deducted. Using the fluctuation theory of spectrally positive Lévy processeswe give an explicit expression of the value function of a barrier strategy. Subsequently we show that a barrier strategy is the optimal strategy among all admissible ones. Our work is motivated by the recent work of Bayraktar, Kyprianou and Yamazaki (2013a). © 2013 The Authors. Published by Elsevier B.V. Open access under CC BY-NC-ND license. C
Diabetes Mellitus Abnormality Detection using AHMM ( Auto Regressive Hidden Markov Model )

Diabetes is a life-threatening issue in modern health care domain. With the use of data mining techniques, diabetesfactors and co morbid risk conditions associated with diabetes has found. In order to stifle the evolution of diabetes mellitus, applies distributed association rule mining and summarization techniques to electronic medical records. This helps to discover set of risk factors and co morbid conditions in distributed medical dataset using frequent itemset mining. In general, association rule mining (ARM) generates bulky volume of data sets which need to summarize certain rules over medical record. This encompasses a novel approach to find the common factors which lead to high risks of diabetes and co morbid conditions associated with diabetes. This performs both association rule mining and association rule summarization techniques with improved classification algorithms.
Diclofenac-Induced Kidney Damage in Wistar Rats: Involvement of Antioxidant Mechanism

Kidney damage has been associated with administration diclofenac, a phenylacetic acid derivative belonging to the nonsteroidal anti-inflammatory drugs (NSAIDs), which is commonly used for the treatment of various diseases such as rheumatoid arthritis, ankylosing spondylitis, acute muscle pain conditions and osteoarthritis. This study investigated the exact mechanism of diclofenac in renal toxicity by determining the involvement of oxidative stress in rats. Adult male Wistar rats were divided into two groups of eight rats in each group and orogastrically treated for three days. Group 1 served as the normal control and received normal saline (0.9% w/v) and group 2 received 40 mg/kg body weight of diclofenac for three days. Administration of diclofenac caused degeneration of the kidney of rats as evidenced by significant elevation in the serum levels of creatinine, urea, albumin, uric acid, protein and electrolytes and the activities of renal-5’-nucleotidase and glucose-6-phosphate-dehydrogenase (G6PDH) compared with control. Furthermore, administration of diclofenac decreased the activities of superoxide dismutase (SOD), catalase, glutathione peroxidase (GPx), and glutathione-S-transferase (GST) and the level of glutathione with concomitant increase in hydrogen peroxide (H2O2) and malondialdehyde (MDA) levels in the kidney of the diclofenac treated groups compared with control. These findings reveal that administration of diclofenac may impair kidney functions through induction of oxidative stress.
Analysis of Rainfall Dynamics in Conakry, Republic of Guinea

Observed rainfall data of the National Meteorological Service of Guinea (NMS) exhibit that synoptic station usually records the largest rainfall amount in Guinea. Only few studies have been done on this rainfall peak observed in Conakry. This work better analyses the atmospheric dynamics leading to rainfall particularity. Using NMS data from 1981 to 2010, the monthly contribution and mean seasonal cycle of each station has been done. These findings of the study show that between July and August (rainfall season peak), the coastline particularly Conakry records the largest amount of rainfall. Using Era Interim data for the common period (1981-2010), we also investigate the rainfall dynamics in the lower level (1000 hPa - 850 hPa) from precipitable water, divergence, and moisture flow transport. There is a west and southwest moisture flow transport explained by a strong moisture convergence in the coastal region (Lower-Guinea). Furthermore, values of precipitable water in the same region are found, in agreement with the high moisture flow transport gradient. These incoming flow (west and south-west) undergo a return by blocking’s Kakoulima range (foehn effect) and Fouta Djallon massif to initiate convection clouds on the Guinean coast. These processes enhance a convergence of moisture associated with orographic origin convection. This has an important effect by increasing the rainfall amount in Conakry.
A (Simplified) Supreme Being Necessarily Exists - Says the Computer!

An approach to universal (meta-)logical reasoning in classical higher-order logic is employed to explore and study simplifications of Kurt Gödel's modal ontological argument. Some argument premises are modified, others are dropped, modal collapse is avoided and validity is shown already in weak modal logics K and T. Key to the gained simplifications of Gödel's original theory is the exploitation of a link to the notions of filter and ultrafilter in topology. The paper illustrates how modern knowledge representation and reasoning technology for quantified non-classical logics can contribute new knowledge to other disciplines. The contributed material is also well suited to support teaching of non-trivial logic formalisms in classroom.
Late Cambrian trilobites from the Mariner Group, northern Victoria Land, Antarctica

This paper describes the youngest Late Cambrian trilobite assemblage so far discovered in the Mariner Group (Bowers Supergroup) northern Victoria Land, Antarctica. It occurs near the base of the Limestone Unit in the middle of the Eureka Formation, at Eureka Spurs, at the head of Mariner Glacier. The assemblage contains seven determined trilobite taxa: Homagnostus cf. ultraobesus Lermontova, 1940, Pseudagnostus (R) ex gr. communis (Hall & Whitfield, 1877), Olente//a cf. shidertensis Ivshin, 1956, Notoaphelaspis sp. undet. , Apheloides? depressa sp. nov" Elviraspis? sp. undet. , and Proceratopyge (R) cf.
Performance comparison of the AS and GTS algorithms for weighted maximum leaf spanning tree problem

In the paper the combinatorial model of the weighted maximum leaf spanning tree problem of simple graph is presented. We give a detailed description of three procedures of the neighbour trees generation to the basis one which are exploited during the course of tree improving process realized by the classical simulated annealing and genetic local search algorithm. Numerical results of improving processes for randomly generated graphs are included.
Bus Corridor Operational Improvement with Intelligent Transportation System based on Autonomous Guidance and Precision Docking

Intelligent Transportation Systems (ITS), Magnetic Sensing. Abstract— It is important to bring to Urban Transportation, in specific of medium capacity, solutions that allow it to increase efficiency. This article shows functionalities associated to Intelligent Transportation Systems that can contribute to the increase in efficiency of Urban Collective Transportation. In particularly, the automation of a conventional bus by way of Autonomous Guidance Technology, which consists of magnetic sensing, computational intelligence and electro-mechanical actuator. The automation of the lateral guidance provides for docking maneuvers with better precision at the stops, in addition to allowing the vehicle to travel on narrow routes quickly and safely. One application of this technology is presented in Expresso Tiradentes bus corridor in São Paulo, where the achieved results demonstrate improvements in the efficiency of bus operations.
1 Revisiting the Levin-Roberts Patient Dropout Model 1

We review an early system dynamics model of mental health care delivery designed to investigate the premature dropout of patients from therapy (Roberts & Levin, 1976). The purpose of our paper is to a large extent pedagogical: First, using the model as a case, we wish to demonstrate the application of current standards and methods of critical model analysis as an illustration of the development of our field. Second, we propose a series of revisions to the model that illustrate techniques for promoting consistency and stringency in modeling “soft” variables related to human emotions, perceptions and attribution of cause, while remaining as true as possible to the purpose and conceptual framework of the original model. Finally, we consider the implications of the revised model for the questions raised by original authors. Many of the conclusions of the original work remain intact, but we find that the revised model provides a more consistent explanation of the dropout phenomenon using concepts that are closer to those used in psychotherapy.
Optimization of Interplanetary Trajectories Using the Colliding Bodies Optimization Algorithm

In this paper, a recent physics-based metaheuristic algorithm, the Colliding Bodies Optimization (CBO), already employed to solve problems in civil and mechanical engineering, is proposed for the optimization of interplanetary trajectories by using both indirect and direct approaches. The CBO has an extremely simple formulation and does not depend on any initial conditions. To test the performances of the algorithm, missions with remarkably different orbital transfer energies are considered: from the simple planar case, as the Earth-Mars orbital transfer, to more energetic ones, like a rendezvous with the asteroid Pallas.
A Real-time Ultrasound Rendering with Model-based Tissue Deformation for Needle Insertion

In the course of developing a training simulator for puncture, a novel approach is proposed to render in real-time the ultrasound (US) image of any 3D model. It is combined with the deformation of the soft tissues (due to their interactions with a needle and a probe) according to their physical properties. Our solution reproduces the usual US artifacts at a low cost. It combines the use of textures and ray-tracing with a new way to efficiently render fibrous tissues. Deformations are handled in real-time on the GPU using displacement functions. Our approach goes beyond the usual bottleneck of real-time deformations of 3D models in interactive US simulation. The display of tissues deformation and the possibilities to tune the 3D morphotypes, tissue properties, needle shape, or even specific probe characteristics, is clearly an advantage in such a training environment.
Chinese and Japanese Word Learning System by Estimation of Word Difficulty

Many foreign students are also enrolling universities in Japan. When foreign students undertake lectures in Japanese, there is an assumption that they understand a good deal of Japanese. However, they do not understand all of the vocabulary needed for lectures. We believe that a Japanese word preparation learning system for providing the vocabulary required for a lecture is required. In addition, there is a change toward using mobile devices for learning, such as iPhone, iPad, Android Tablets, and son. As such, we need to provide a simple method for learning. This research is developing a system for practicing Japanese and Chinese vocabulary using terms taken from a text for beginners, as well as technical term taken from VOD lectures on a database server that have open access to documents such as lecture videos and slides. We are also utilizing the difficulty level of Chinese and Japanese terms to determine the order of appearance and to extract incorrect terms in multiple choice vocabulary problems. To determine the difficulty level of each word, we used support vector machine (SVM) to estimate the difficulty of words with no preexisting difficulty level based on words whose level is already established, and then used a bootstrap method which made use of the estimated difficulty levels of these words.