Miracle-dz/UniFAR-FTUs huggingface dataset:
Environmental Concern, Attitude and Intention in Understanding Student’s Anti-Littering Behavior Using Structural Equation Modeling

Concerns about the environment began to rise as various issues such as littering increased. Littering is one of the problems involving the environment, and higher education campuses are also actively practising anti-littering to show their efforts. The aim of this study is to test the relationship between environmental concern, attitude and intention on anti-littering using Theory of Planned Behavior Extended Model. A total of 303 students of the Polytechnic Malaysia campus were respondents in this study and the data were analyzed by Structural Equation Modeling using SPSS Amos 24.0 Statistical Packages. Findings show that there is a direct and indirect effect between environmental concern and student’s anti-littering intention. The indirect result shows that attitude towards anti-littering behavior partially mediates the relationship between environmental concern and anti-littering intention. The implications of the research findings and suggestions for the future study are also included in the study.
The population of donkeys and mules in Brazil according to agricultural censuses from 1960 to 2017

To better understand and manage the population of donkeys and mules, it is essential to know information about its size. In developing countries, these animals are often used as working animals, mainly by poor populations in agricultural and livestock labor, but their use is decreasing in Brazil. Brazilian official data regarding donkeys and mules started to be measured at the agricultural census of 1960 and, from that time, eight agricultural censuses were published. But until the writing of this paper, no scientific paper was dedicated to the analysis of the results of the official agricultural censuses on the population of donkeys and mules in Brazil. Thus, we aim to compile and analyze the official Brazilian data from 1960 until 2017 to enhance the actions of stakeholders, researchers, and decision-makers concerned with Brazilian donkeys and mules.
Integration of Sorensen and Cosine Similarity Measure for Solving Fuzzy Decision Making Problems

Similarity measure has been used in many fields of study to measure common features between objects. The fuzzy similarity measure is popularized when elements of vagueness and subjectivity are incorporated in the comparison process. It is a preferred approach to some distance methods since in obtaining the distances, the defuzzification process will be involved that may cause loss of some vital information due to simplification process to a single value. Several fuzzy similarities have been proposed to cater different setting and for better discrimination. Nevertheless, in many cases, an extreme degree of similarity may occur due to the characteristic of the similarity measure itself. In particular, the Cosine similarity measure gives a too low degree of similarity while the Sorensen similarity measure gives a too high degree of similarity where in return the utilization of these similarities may not give the acceptable measurement of similarity. An integration of two or more similarity measures may assist to eradicate this problem. In this paper, the Sorensen and Cosine similarity measure were integrated based on the variation coefficient representation under fuzzy environment. A procedure of ranking alternatives is proposed using the new integrated similarity measure and is used to solve the grading problem of oil palm fruit bunch. The proposed integrated fuzzy similarity measure of Cosine and Sorensen has an advantage of being able to compromise the extreme values produced by the two similarity measures and has the potential to be applied to solving various fuzzy decision making problems.
To play or not to play: teachers’ and headteachers’ perspectives on play-based approaches in transition from the Early Years Foundation Stage to Key Stage 1 in England

ABSTRACT This study explores the place of play in KS1 classrooms and the perspectives of teachers and headteachers in adopting play-based practices at the start of primary schooling. Data were collected from a survey of KS1 teachers asking for their views of play as an integral part of KS1 pedagogy. This was followed by interviews with eleven headteachers of schools where a play-based approach is embedded. Findings revealed that whilst teachers were in favour of play in KS1, policy constraints and, in particular, the beliefs of their own headteachers, very often acted as a barrier to the implementation of play in their school. The interviews with the headteachers of schools where a play-based approach is encouraged, reveal the influences on their thinking and beliefs, which include the advocacy of their own teachers.
Effets des changements climatiques sur la dynamique de décomposition microbienne du carbone organique du sol en prairie subalpine calcaire

Les sols de montagne constituent un reservoir majeur de carbone stocke sous forme de matiere organique (carbone organique du sol, COS), potentiellement hautement vulnerable aux changements des conditions climatiques. Afin de comprendre les repercussions des changements des conditions climatiques sur la dynamique du COS des sols de montagne, cette these s'appuie sur une experimentation de transplantation altitudinale de monolithes de sol de prairie subalpine calcaire, mise en place dans le Jura Suisse en 2009. Cette experimentation permet de simuler deux scenarios realistes de changements climatiques attendus au cours du 21eme siecle, visant a rechauffer et assecher le climat (+2°C et +4°C ; -20% et -40% de precipitations). La demarche conceptuelle de cette these a ete d'etudier les effets des changements des conditions climatiques (variations saisonnieres et manipulation climatique) au bout de quatre annees d'experimentation sur (i) la dynamique des communautes microbiennes et de leur activite enzymatique de decomposition du COS, (ii) la dynamique de differents pools de COS qui constituent la ressource energetique des micro-organismes decomposeurs, (iii) les interactions s'etablissant entre les communautes microbiennes et leurs ressources energetiques et (iv) les stocks de COS du sol.Nos resultats montrent une tres forte dynamique saisonniere du processus de decomposition microbienne se traduisant par de fortes activites enzymatiques de decomposition, une biomasse microbienne plus importante et une structure des communautes microbienne differente lors de la saison hivernale par rapport a la saison estivale. Ces resultats sont en lien avec la dynamique observee des pools les plus labiles du COS (C organique extractible a l'eau et C organique particulaire libre), et des modeles d'equations structurelles montrent que les conditions climatiques (variations saisonnieres et manipulation climatique) modifient les interactions s'etablissant entre les communautes microbiennes et leurs ressources pour controler la decomposition enzymatique du COS.Enfin, ce travail de these montre une forte diminution des concentrations en COS sous l'effet de la manipulation climatique, qui ne peut etre expliquee par une decomposition microbienne accrue du COS. Au contraire, nos resultats suggerent que la diminution de la concentration en COS pourrait etre due a l'acceleration des processus pedologiques naturels sous les scenarios de changement climatique au sein de ces sols calcaires de prairies subalpines, avec une decarbonatation accrue favorisant la lixiviation du carbone organique dissous et le lessivage du pool de COS associe aux argiles. Ces resultats inedits offrent de nouvelles perspectives de recherche sur les effets des changements climatiques sur l'evolution des stocks de COS.
Information Modelling Method of As-built Process Data

The digital twin concept plays a significant role in the Industry 4.0 era since it was proposed. One key enabling technology for digital twin creation is the information modelling of physical products. Therefore, the modelling approach to modelling as-built process data of physical products, which faithfully reflects the real machining status, emerges to be pivotal. This paper addresses the problem of modelling as-built process data in machining process, which is difficult to accomplish by relevant methods, and hinders data reuse and the long-term archiving. Furthermore, an ontology-based information modelling method of as-built process data is proposed as the recommendation to represent and record the data in the cyberspace. It provides a standardized process for companies to model as-built process data by specifying the contents to be modeled, and the modelling method. To validate the effectiveness, a case study is undertaken in an aviation manufacturing plant at last. The result shows that the proposed information modelling methodology is readily to the virtualization of as-built machining process data.
Monitoring and Evaluating Nature-Based Solutions Implementation in Urban Areas by Means of Earth Observation

Climate change influences the vulnerability of urban populations worldwide. To improve their adaptive capacity, the implementation of nature-based solutions (NBS) in urban areas has been identified as an appropriate action, giving urban planning and development an important role towards climate change adaptation/mitigation and risk management and resilience. However, the importance of extensively applying NBS is still underestimated, especially regarding its potential to induce significantly positive environmental and socioeconomic impacts across cities. Concerning environmental impacts, monitoring and evaluation is an important step of NBS management, where earth observation (EO) can contribute. EO is known for providing valuable disaggregated data to assess the modifications caused by NBS implementation in terms of land cover, whereas the potential of EO to uncover the role of NBS in urban metabolism modifications (e.g., energy, water, and carbon fluxes and balances) still remains underexplored. This study reviews the EO potential in the monitoring and evaluation of NBS implementation in cities, indicating that satellite observations combined with data from complementary sources may provide an evidence-based approach in terms of NBS adaptive management. EO-based tools can be applied to assess NBS’ impacts on urban energy, water, and carbon balances, further improving our understanding of urban systems dynamics and supporting sustainable urbanization.
Scaling Inhibitor Impact to Corrosion Resistance of J55 mild Steel in CO2 saturated brine

The corrosion behavior of the J55 mild steel alloy in CO2 saturated brine have been studied by weight loss technique, potentiodynamic polarization technique and characterization of the corroded surface techniques. The results demonstrate that the corrosion solution is easy to penetrate into the matrix and activate corrosion without scale inhibitor. When the scale inhibitor content was as high as 30 mg/L, the effect of scaling products on corrosion gradually decreased. Adding the corresponding scale inhibitor in the solution was beneficial to slow down the corrosion rate and the possibility of pitting corrosion. The corrosion product film is mainly FeCO3, and with the increase of scale inhibitor contents, the density of FeCO3 was stronger and compact, which could greatly prevent the contact between the medium and the matrix.
Maize Seedling Establishment, Grain Yield and Crop Water Productivity Response to Seed Priming and Irrigation Management in a Mediterranean Arid Environment

Water shortage is a major environmental stress that destructively impacts maize production, particularly in arid regions. Therefore, improving irrigation management and increasing productivity per unit of water applied are needed, especially under the rising temperature and precipitation fluctuations induced by climate change. Laboratory and field trials were carried out in the present study, which were aimed at assessing the possibility of promoting maize germination, growth, grain yield and crop water productivity (CWP) using seed priming under different irrigation regimes. Two seed priming treatments, i.e., hydro-priming and hardening versus unprimed seeds, were applied under four irrigation regimes, i.e., 120, 100, 80 and 60% of estimated crop evapotranspiration (ETc). The obtained results indicated that increasing irrigation water from 100% up to 120% ETc did not significantly increase grain yield or contributing traits, while it decreased CWP. Deficit irrigation of 80 and 60% ETc gradually decreased grain yield and all attributed traits. Seed priming significantly ameliorated seedlings’ vigor as indicated by earlier germination, higher germination percentage, longer roots and shoots, and heavier fresh and dry weight than unprimed seeds with the superiority of hardening treatment. Additionally, under field conditions, seed priming significantly increased grain yield, yield contributing traits and CWP compared with unprimed treatment. Interestingly, the results reflect the role of seed priming, particularly hardening, in mitigating negative impacts of drought stress and enhancing maize growth, grain yield and attributed traits as well as CWP under deficit irrigation conditions. This was demonstrated by a significant increase in grain yield and CWP under moderate drought and severe drought conditions compared with unprimed treatment. These results highlight that efficient irrigation management and seed priming can increase maize yield and water productivity in arid environments.
Enet Semantic Segmentation Combined with Attention Mechanism

Image semantic segmentation is one of the core tasks of computer vision. It is widely used in fields such as unmanned driving, medical image processing, geographic information systems and intelligent robots. Aiming at the problem that the existing semantic segmentation algorithm ignores the different channel and location features of the feature map and the simple method when the feature map is fused, this paper designs a semantic segmentation algorithm that combines the attention mechanism. Firstly, dilated convolution is used, and a smaller downsampling factor is used to maintain the resolution of the image and obtain the detailed information of the image. Secondly, the attention mechanism module is introduced to assign weights to different parts of the feature map, which reduces the accuracy loss. The design feature fusion module assigns weights to the feature maps of different receptive fields obtained by the two paths, and merges them together to obtain the final segmentation result. Finally, through experiments, it was verified on the Camvid, Cityscapes and PASCAL VOC2012 datasets. Mean intersection over union (MIoU) and mean pixel accuracy (MPA) are used as metrics. The method in this paper can make up for the loss of accuracy caused by downsampling while ensuring the receptive field and improving the resolution, which can better guide the model learning. And the proposed feature fusion module can better integrate the features of different receptive fields. Therefore, the proposed method can significantly improve the segmentation performance compared to the traditional method.
Transforming the Fan Experience through Livestreaming: A Conceptual Model

Abstract The purpose of this case study research was to explore how Queensland Rugby League (QRL) used a Facebook brand page, for the Queensland Maroons, and incorporated livestreaming throughout the 2017–2018 State of Origin seasons. Specifically, this study sought to understand managerial perspectives regarding interactive advertising within digital sports marketing strategy encompassing livestreaming and the extent to which it may impact fan engagement. This research utilized a multimethod case study approach involving a content analysis of Facebook, complemented by two semistructured interviews with the organization’s digital staff. The findings revealed livestreaming can be an engaging proposition when it provides exclusive content that allows fans to experience authentic insights into the rituals and traditions of their favorite sports team and athletes in real time. Furthermore, three unique management livestreaming experiences were identified: planning, organization, and delivery (POD). As a response, a conceptual POD model has been created that reevaluates the opportunities for fan engagement adapted from previous research findings (Haimson and Tang 2017; Naraine and Karg 2019). This model is important for sports organizations when considering livestreaming, as there may be unique opportunities to focus on interactive advertising and, thus, to develop awareness and the fan-to-fan and fan-to-athlete/sports organization/team relationship.
The Mechanism Of Action Of Polyphenol On Changes In The Dynamics Of Calcium In The Synaptosomes Of The Rat Brain Against The Background Of Glutamate

The manuscript shows a short data used using fluorescent probes to study the effect of polyphenol PС-7 on changes in the dynamics of intracellular Ca2+ content in rat brain synaptosomes, depending on the site of glutamate binding on calcium channels by a specific mediator with glutamate. To measure the amount of cytosolic Ca2+ synaptosomes, we calculated using the Grinkevich equation. It has been shown that polyphenol PС-7 binds to the β1-subunit of the voltage-gated calcium channel and allosterically changes its conformation so that the conductivity for Ca2+ ions increases through the channel, the blocking effect of polyphenol PС-7 can be explained by its binding to voltage-gated calcium channels and activating them.
Structure–sequence features based prediction of phosphosites of serine/threonine protein kinases of Mycobacterium tuberculosis

Elucidation of signaling events in a pathogen is potentially important to tackle the infection caused by it. Such events mediated by protein phosphorylation play important roles in infection, and therefore, to predict the phosphosites and substrates of the serine/threonine protein kinases, we have developed a Machine learning‐based approach for Mycobacterium tuberculosis serine/threonine protein kinases using kinase‐peptide structure–sequence data. This approach utilizes features derived from kinase three‐dimensional‐structure environment and known phosphosite sequences to generate support vector machine (SVM)‐based kinase‐specific predictions of phosphosites of serine/threonine protein kinases (STPKs) with no or scarce data of their substrates. SVM outperformed the four machine learning algorithms we tried (random forest, logistic regression, SVM, and k‐nearest neighbors) with an area under the curve receiver‐operating characteristic value of 0.88 on the independent testing dataset and a 10‐fold cross‐validation accuracy of ~81.6% for the final model. Our predicted phosphosites of M. tuberculosis STPKs form a useful resource for experimental biologists enabling elucidation of STPK mediated posttranslational regulation of important cellular processes.
Determination Of Cefpodoxime Proxetil Using 1,10-phenanthroline

A simple and sensitive spectrophotometric method for the determination of cefpodoxime proxetil is described. The method is based on the formation of blood red coloured complex (I»max 520 nm) by reaction of the drug with ferric chloride and 1, 10-phenanthroline. The Beer-Lambert's law range observed is 0.8-4.0 I¼g/ml.
A miniaturized reconfigurable unlicensed ultra‐wideband antenna with multiple band‐notch performance

This paper presents a compact reconfigurable ultra‐wideband antenna with multiple band‐notch characteristic. The truncated corners in the rectangular patch are employed to realize the desired ultra‐wideband (UWB) operation. The band‐notch property in the 3.5 GHz WiMAX and 5.2 GHz WLAN bands are obtained by the conventional C‐shaped slots in the radiating patch, and the band‐notch performance in the 7.5 GHz X‐band is especially realized by introducing a parasitic meandering strip beneath the ground. The reconfigurable band‐notch function is achieved by controlling the states of the PIN diodes inserted in the band‐notch structures. The overall dimension of the antenna is 19.5 mm × 14 mm. The simulation and experiment results confirm that the antenna can switch between a UWB state, three single band‐notch states, three dual band‐notch states and a triple band‐notch state. Moreover, stable radiation patterns are exhibited.
Physicochemical and Microbiological Changes during Salt Fermentation of Pangasius Steaks

ABSTRACT Suitability of Pangasius as a source for salt fermentation and its physicochemical and microbiological changes during fermentation were evaluated for a period of 150 days. Biochemical and microbiological parameters such as proximate composition, pH, non-protein nitrogen, total volatile base nitrogen, free α-amino nitrogen, free fatty acid, peroxide value, thiobarbutric acid reactive substances, salt content, total titratable acidity, total viable count, and Escherichia coli were analyzed during the fermentation. Peroxide value and thiobarbutric acid reactive substances indicated that maturation started on the 90th day of fermentation. The highest non-protein nitrogen (NPN)/total nitrogen (TN) ratio was observed on the 120th day and the highest sensory scores were observed on the 150th day of fermentation. NPN/TN ratio and sensory scores showed that salt fermentation accelerate from the 90th day and attains maturation on the 120th day. The study revealed that Pangasius can be an ideal fish for salt fermentation, and this technique can be adopted by small-scale farmers.
Physical therapy scheduling of inpatients based on improved Genetic Algorithm

In recent years, the physical therapy has become more and more extensive. How to schedule corresponding treatments efficiently in rehabilitation hospitals has attracted the attention of many scholars. A typical physical therapy treatment can be divided into three stages, i.e., the beginning, the treating and the ending. Moreover, only the beginning and the ending stages require a therapist. The treating stage does not. In addition, a physical therapy treatment requires to occupy a bed and an instrument related simultaneously. In order to solve challenging scheduling problems, a genetic algorithm based on Waiting Time Priority Algorithm (WTPA) is designed. Finally, an instance from the rehabilitation department in a hospital is tested. By comparing with the classical simulated annealing algorithm (SA), it verifies the effectiveness and efficiency of the genetic algorithm designed.
Simultaneous Calibration of Hydrologic Model Structure and Parameters Using a Blended Model

The advent of hydrological modeling frameworks that support multiple model structures using the same software enables both model structure and model parameters to be calibrated and assessed. To date, the identification of optimal model structure has typically been performed manually. Here, a continuous (rather than discrete) treatment of model structure is used, which enables simultaneous automatic calibration of model structure and parameters using a conventional real‐valued decision variable optimization algorithm (the dynamically dimensioned search algorithm, DDS). The method, referred to herein as blended model structure calibration (BMSC), relies upon the calculation of each hydrologic flux (e.g., for infiltration) as a weighted average of fluxes generated from multiple process algorithm options. This method is applied to 12 lumped MOPEX catchment models and compared to the calibration of 108 fixed model structures, representing all possible permutations of fixed model structures with the given process options in this study. The BMSC method consistently identified near‐optimal model structure (as evaluated using average model rank performance) at significantly lower computational cost than calibrating the collective of fixed structure models. The BMSC method also provides a useful tool in identifying dominant processes and model structures in catchments.