Miracle-dz/UniFAR-FTUs huggingface dataset:
POST-SECONDARY PAW PATROL: Effects of Animal-Assisted Activities on Students’ Stress, Happiness and Well-being

Two hundred forty-two students, including 76 college students and 166 university students from Canadian post-secondary schools, participated in a pre-post study of the effects of animal-assisted activities on their stress, happiness, and wellbeing. Findings showed that those students who had recently experienced a negative event showed significantly greater positive effects of the animal-assisted activities on all three dependent variables when compared with other students, although all students benefitted from participating in terms of desired effects on their stress, happiness, and well-being. In keeping with Keyes’ model of mental wellness, these school-based, animal-assisted activities are supported as lowcost, low-stigma, universal approaches to mental health promotion.
Investigations on electrical parameters degradation and recovery of E-mode GaN high-electron mobility transistors under repetitive unclamped inductive switching stresses based on low-frequency noise

During no or minimal avalanche capability, the surge ruggedness of the E-mode AlGaN/GaN high-electron mobility transistors (HEMTs) with p-GaN gate has not been fully understood. This work unveils the comprehensive results from repetitive unclamped inductive switching (UIS) measurements on commercial p-gate GaN HEMTs. The Electrical parameters degradation and recovery characteristics have been investigated. Firstly, a careful study has been made about the degradation of output, transfer, gate leakage, and gate capacitance parameters of GaN HEMT devices before and after repetitive UIS pulses, which acting on the device channel. With the help of the low-frequency noises (LFNs), the test results show that the device characteristics have gradual degradation with an increase in UIS pules, including increased threshold voltage (V th), and decreased gate leakage current (I gss). Subsequently, the LFN testing is carried out with the increase of UIS pulses. Finally, the recovery characteristics of the devices are studied and the physics associated are discussed after putting the device at room temperature in the air for 1–15 d, which includes DC characteristics and trap density. These results physically confirm that the mechanism of the degradation and recovery of device characteristics, that is the charge trapping effects of electrons. After repetitive UIS stresses, the electrons are trapping and de-trapping on interfaces and in the bulk layer of devices, which can change electric field distribution below the grids. These have a strong impact on the electrical performance of devices.
Quantifying the Location Error of Precipitation Nowcasts

In precipitation nowcasting, it is common to track the motion of precipitation in a sequence of weather radar images and to extrapolate this motion into the future. The total error of such a prediction consists of an error in the predicted location of a precipitation feature and an error in the change of precipitation intensity over lead time. So far, verification measures did not allow isolating the extent of location errors, making it difficult to specifically improve nowcast models with regard to location prediction. In this paper, we introduce a framework to directly quantify the location error. To that end, we detect and track scale-invariant precipitation features (corners) in radar images. We then consider these observed tracks as the true reference in order to evaluate the performance (or, inversely, the error) of any model that aims to predict the future location of a precipitation feature. Hence, the location error of a forecast at any lead time Δt ahead of the forecast time t corresponds to the Euclidean distance between the observed and the predicted feature locations at t + Δt. Based on this framework, we carried out a benchmarking case study using one year worth of weather radar composites of the German Weather Service. We evaluated the performance of four extrapolation models, two of which are based on the linear extrapolation of corner motion from t − 1 to t (LK-Lin1) and t − 4 to t (LK-Lin4) and the other two are based on the Dense Inverse Search (DIS) method: motion vectors obtained from DIS are used to predict feature locations by linear (DIS-Lin1) and Semi-Lagrangian extrapolation (DIS-Rot1). Of those four models, DIS-Lin1 and LK-Lin4 turned out to be the most skillful with regard to the prediction of feature location, while we also found that the model skill dramatically depends on the sinuosity of the observed tracks. The dataset of 376,125 detected feature tracks in 2016 is openly available to foster the improvement of location prediction in extrapolation-based nowcasting models.
Radiotracer zur Diagnose des Prostatakarzinoms: Etablierte und neue Verfahren

Zusammenfassung Die nuklearmedizinische Diagnose von Tumoren basierend auf der Radiotracer-vermittelten Bildgebung hat sich in den letzten Jahrzehnten als zentrale Schlüsseltechnologie in der modernen Onkologie etabliert. Die bildgestützte Diagnostik ermöglicht nicht nur die frühe Identifikation und Klassifikation von Tumoren, sondern auch die therapiebegleitende, nicht-invasive Evaluierung des Therapieansprechens sowie der Detektion von Rezidiven, Remissionen und progressiven Erkrankungen nach Abschluss der Therapie. Dies macht die nuklearmedizinische Bildgebung einzigartig im Bereich der personalisierten und Präzisions-Medizin. Daher ist es nur einleuchtend, dass das Feld dynamisch wächst und eine Vielzahl neuer Radiotracer entwickelt werden, die in präklinischen und klinischen Studien validiert werden. In diesem Übersichtsartikel werden die verfügbaren Daten zu den bereits klinisch etablierten metabolischen und zielgerichteten, spezifischen Radiotracern zusammengefasst. Zusätzlich wird ein Ausblick auf neue Entwicklungen gegeben, in dem neue, vielversprechende Radiotracer für die Diagnostik eines Prostatakarzinoms diskutiert werden.
COVID-19 in Ghana: Consequences for Poverty, and Fiscal Implications

This paper estimates the poverty consequences of the COVID-19 pandemic and its fiscal implications in Ghana using a micro-simulation analytical approach applied to household level data collected in 2016/2017 by the Ghana Statistical Service. The results show that the poverty consequences are massive as poverty increased from a base of 20.5% to 34.0% and drove over 4 million pre-COVID non-poor into poverty. The poverty consequences are triggered by income losses of up to US$ 330 million and equalling 5.4% of monthly GDP. The pandemic has also worsened inequality as inequality rose from a base of 42.1% to 47.5%. The fiscal cost of a universal cash transfer potent enough to restore poverty to pre-COVID level is a monthly expenditure of US$ 186 million, which represents 3.1% of monthly GDP. COVID-induced interventions on water and electricity rebates for three months are less effective in reducing poverty. Disaggregated findings based on locality show varying depths of impact. The policy implications of these findings are important for appropriate interventions to tackle the consequences of the pandemic. COVID-19 In Ghana: COnsequenCes fOr POVerty, anD fIsCal ImPlICatIOns 1
Assessment of National Performance Trials of Potatoes in Mid-Altitude Regions of Kenya

Potato is the second most important food crop in Kenya after maize. It is a valuable cash and food crop mainly grown by small-scale farmers. Potato is cultivated mainly under rainfed production conditions at altitudes between 1500 and 3000 metre above sea level (masl). Consequently, National Performance Trials (NPTs) test sites are located in these highlands. Recently, potato production has spread to the mid-highlands (1200-1500masl) mostly due to high food demand occasioned by population increase, and migration of small scale farmers from the densely populated highlands to the more spacious midlands. Consequently, there is increased need to breed potato varieties that can grow profitably in the warmer mid-altitudes. This development called for identification of new conventional NPT test sites located in the midaltitudes. Six mid-altitude sites were identified and client-managed conventional NPTs carried out. Twenty six potato genotypes were evaluated for two seasons. First season crop was planted in 2016 while the second season crop was planted in 2017. There was a significant (p≤ 0.001) effect of genotypes, environments and genotype x environment interaction in the first season. Trans-Nzoia was the highest yielding site. All genotypes yielded between 10 and 25 ton/ha. In the second season, only environments showed significant (p≤ 0.001) effects. Again, Trans-Nzoia was the highest yielding site. Across the two seasons, Trans-Nzoia gave an average yield of 26.96 ton/ha followed by Kabete at 18. 21ton/ha. All the other four sites yielded less than 10 ton/ha. The high yields at Trans-Nzoia and Kabete could be due to higher altitudes in these two sites compared to the others. In order to develop potato varieties that can produce profitably in the warm mid-altitudes, breeding and early generation selections activities should be based in these areas.
A Reinvestigation of the Preparation, Properties, and Applications of Aminomethyl and 4-Methylbenzhydrylamine Polystyrene Resins1

Mild, efficient conditions have been developed for the preparation of 4-methylbenzhydrylamine polystyrene (MBHA) and aminomethyl polystyrene (AMPS) resins by a two-step procedure with synthons 1a and 1c. The products possess excellent swelling characteristics and acylate readily with linkers yielding useful derivatives, which retain good swelling and reactivity. Comparative studies with these resins, and their poly(ethylene glycol) (PEG) derivatives, yield insights into the role of spacer arm and environment effects in synthesis facilitation.
The commensurate (10/4) cluster model in quenched wüstite P''. New simulation of HREM direct images

La structure des defauts de Fe 1−2 O (z≃0,096) serait constituee d'agregats composes de 10 lacunes et de 4 ions Fe III interstitiels. Cette structure s'accorderait avec un ordre a longue distance (2,5X, 2,5X, 5X), comportant un certain desordre local. Les images directes de la phase P sont reinterpretees en utilisant d'apres ce modele d'agregat en utilisant une simulation par ordinateur
Suspicious Activity Detection of Twitter and Facebook using Sentimental Analysis

The purpose of this study is to evaluate the criminal behavior on the social media platforms and to classify the gathered data effectively as negative, positive, or neutral in order to identify a suspect. In this study, data was collected from two platforms, Twitter and Facebook, resulting in the creation of two datasets. The following findings have been pointed out from this study: Initially, VADER twitter sentimental analysis showed that out of 5000 tweets 50.8% people shared a neutral opinion, 39.2% shared negative opinion and only 9.9% showed positive opinion. Secondly, on Facebook, the majority of people showed a neutral response which is 55.6%, 38.9% shared positive response and only 5.6% shared negative opinion. Thirdly, the score of sentiments and engagement in every post affects the intensities of sentiments.
A Novel Method for Power Quality Disturbance Detection Based on LSTM Network Model Residuals

In order to accurately detect the time when the disturbance of power quality (PQ) occurs and the variation of voltage amplitude, a novel method of power quality disturbance detection that is based on the residual of the long short-term memory (LSTM) network model is proposed. Firstly, an offline model is developed based on historical voltage signals from a power grid under the normal condition by using the LSTM theory. Then, in order to detect PQ events online, the grid voltage signal is taken as the input of the model to obtain the residual component between the input signal and the normal signal. Finally, the amplitude change of the residual component reflects the amplitude change of the voltage. The starting and ending time and duration of the disturbance are located by detecting the mutation points of the residual component. Experiments on simulation data and engineering data show that the proposed method can well reflect the amplitude change when the voltage is disturbed, and the disturbance positioning accuracy is high.
An integrative study of the implications of the rise of coworking spaces in smart cities

Coworking practices have proliferated around the world being embraced not only by remote workers, start-up employees and freelancers but also by larger organizations. Coworking spaces in public libraries, business districts and other urban spaces, herald profound changes for the way workspaces are used in cities. The study takes an integrative approach to investigate the economic and socio-cultural implications of coworking trend for smart cities, their ecosystems and the use of urban public spaces. The study examines these issues by studying motivations and challenges of providers and users of coworking spaces. Thirty coworking spaces in urban areas across Australia were studied and thirty-four semi-structured interviews were conducted with both providers and users of the coworking spaces. The findings suggest that coworking spaces play an important role in building communities and developing social and cultural ties. From urban space and environmental perspectives, coworking spaces are likely to contribute to urban mobility and sustainability. From an urban economic perspective, coworking spaces provide a collaborative environment and often a breeding ground for entrepreneurship. Entrepreneurship is one of the most salient themes in the coworking spaces as found in this study. These findings will inform urban policy makers and help them better understand and tap into the source of civic entrepreneurship derived from coworking spaces.
Toward a head movement‐based system for multilayer digital content exploration

In this article, we propose a novel technique based on Head Movement tracking to explore multilayer digital content. We extend an existing method by Kazemi et al. dealing with the extraction of facial landmarks to define the “head‐gaze” of the user. We use the “head‐gaze” to calculate the users' on‐screen coordinates. Hovering the cursor over an interactive area for a given time threshold allows users to explore the next layer contents. Our experimental sessions allowed us to measure the technique's level of control and usability. Our results were promising, and users were able to interact with considerably small regions. Furthermore, our lightweight method can be used with a low‐cost camera or webcam and a wide range of screen sizes and distances.
A Data-Centric Directive-Based Framework to Accelerate Out-of-Core Stencil Computation on a GPU

SUMMARY Graphics processing units (GPUs) are highly e ﬃ cient architectures for parallel stencil code; however, the small device (i.e., GPU) memory capacity (several tens of GBs) necessitates the use of out-of-core computation to process excess data. Great programming e ﬀ ort is needed to manually implement e ﬃ cient out-of-core stencil code. To relieve such programming burdens, directive-based frameworks emerged, such as the pipelined accelerator (PACC); however, they usually lack speciﬁc optimizations to reduce data transfer. In this paper, we extend PACC with two data-centric optimizations to address data transfer problems. The ﬁrst is a direct-mapping scheme that eliminates host (i.e., CPU) bu ﬀ ers, which intermediate between the original data and device bu ﬀ ers. The second is a region-sharing scheme that signiﬁcantly reduces host-to-device data transfer. The extended PACC was applied to an acoustic wave propagator, automatically extending the length of original serial code 2.3-fold to obtain the out-of-core code. Experimental results revealed that on a Tesla V100 GPU, the generated code ran 41.0, 22.1, and 3.6 times as fast as implementations based on Open Multi-Processing (OpenMP), Uniﬁed Memory, and the previous PACC, respectively. The generated code also demonstrated usefulness with small datasets that ﬁt in the device capacity, running 1.3 times as fast as an in-core implementation.
Variation of the Internal Fields and Isomer Shifts at the Fe Sites in the FeAl Series

The Mossbauer technique was used to measure the internal magnetic fields and isomer shifts of Fe57 atoms residing at the various sites in the FeAl series. Alloys of Al content varying from 0 to 50 at. % were studied. In the disordered region (<21 at. % Al) five different type sites were observed, corresponding to Fe atoms having 8 through 4 nearest‐neighbor (nn) Fe atoms. The internal field decreased by about 0.07 HFe for each nn Al atom. In the ordered region sites having 8 through 2 nn Fe atoms were observed. For A type sites (4 nn Fe atoms and 4 nn Al atoms at 25 at. % Al) the internal field decreased by 0.11–0.12 HFe for each nn Al atom. In the region above about 30 at. % Al the alloys are not ferromagnetic but information on the type ordering could be obtained from the isomer shifts. Over the whole series the isomer shift indicated that there is progressively less electronic charge at the nucleus as the number of nn Al atoms increased.
PyDA: A Hands-On Introduction to Dynamical Data Assimilation with Python

Dynamic data assimilation offers a suite of algorithms that merge measurement data with numerical simulations to predict accurate state trajectories. Meteorological centers rely heavily on data assimilation to achieve trustworthy weather forecast. With the advance in measurement systems, as well as the reduction in sensor prices, data assimilation (DA) techniques are applicable to various fields, other than meteorology. However, beginners usually face hardships digesting the core ideas from the available sophisticated resources requiring a steep learning curve. In this tutorial, we lay out the mathematical principles behind DA with easy-to-follow Python module implementations so that this group of newcomers can quickly feel the essence of DA algorithms. We explore a series of common variational, and sequential techniques, and highlight major differences and potential extensions. We demonstrate the presented approaches using an array of fluid flow applications with varying levels of complexity.
Consumer Perceptions and Intentions Toward Buying Green Food Products: A Case of Tanzania

Abstract Research on green products has been extensively developed recently but there is less that is known with respect to consumer perception toward those products especially in emerging markets. The cross-cultural studies have indicated a significant degree of differences between and within these markets, a fact that is expected to provide unique insights for other established theories. This study therefore aimed at examining the consumer perceptions and intentions in buying green food products, with a case of Tanzania (one of the fastest emerging markets of Africa). Quantitative data were collected in a cross-sectional manner, using a well-structured questionnaire with a sample of 399 respondents. Study findings reveal that consumers’ intention to buy is highly influenced by their health benefit perceptions on green food products. Food quality and its safety were also found to be good predictors of consumers’ buying intention that affect it positively contrary to price which influenced the same negatively.
Association between Neospora caninum seropositivity and reproductive disorders in girolando cows

ABSTRACT The aim of this study was to investigate the presence of anti-Neospora caninum antibodies in Girolando cows, in order to evaluate the association between seropositivity and reproductive disorders. Blood samples were collected from 40 dairy cows in their reproductive phase from the cranial superficial epigastric vein. The blood samples were tested using the Indirect Fluorescence Antibody Test (IFAT) to detect anti-N.caninum antibodies. The serological results were used to verify whether there was any association with the manifestation of reproductive disorders based on data from the records of reproductive history from 2017 to 2018 as well as the clinical observations of the herd throughout this study. The Fisher exact test was used to verify the existence of an association between the serology and reproductive disorders, adopting a 95% confidence level. The serological results showed a 27.5% seroprevalence in the herd for N. caninum, however, after statistical analysis, no association between seropositivity and reproductive disorders was found in the evaluated herd. Although the studied population is infected with Neospora caninum, we can infer that anti-Neospora caninum antibodies present in Girolando dairy cows at the UFRRJ Dairy Cattle Facility are not associated with the occurrence of reproductive disorders.
The Role of Hydrological Signatures in Calibration of Conceptual Hydrological Model

Determining an optimal calibration strategy for hydrological models is essential for a robust and accurate water balance assessment, in particular, for catchments with limited observed data. In the present study, the hydrological model Bilan was used to simulate hydrological balance for 20 catchments throughout the Czech Republic during the period 1981–2016. Calibration strategies utilizing observed runoff and estimated soil moisture time series were compared with those using only long-term statistics (signatures) of runoff and soil moisture as well as a combination of signatures and time series. Calibration strategies were evaluated considering the goodness-of-fit, the bias in flow duration curve and runoff signatures and uncertainty of the Bilan model. Results indicate that the expert calibration and calibration with observed runoff time series are, in general, preferred. On the other hand, we show that, in many cases, the extension of the calibration criteria to also include runoff or soil moisture signatures is beneficial, particularly for decreasing the uncertainty in parameters of the hydrological model. Moreover, in many cases, fitting the model with hydrological signatures only provides a comparable fit to that of the calibration strategies employing runoff time series.
PersonalisedComfort: a personalised thermal comfort model to predict thermal sensation votes for smart building residents

ABSTRACT Internet of Things (IoT) empowered Heating, Ventilation, and Air Conditioning (HVAC) buildings are considered to monitor and control the regulation of thermostats, sensors, actuators, and control devices smartly. In this article, we propose a novel model named PersonalisedComfort to predict the thermal sensation votes of individuals living in a building. We use publicly available standard dataset ASHRAE RP-884 for experimentation and analysis. We apply conventional machine learning algorithms and deep learning algorithms to predict the thermal sensation vote. PersonalisedComfort achieves an accuracy of 85% to predict thermal sensation votes which 8% higher than state-of-the-art studies.