Miracle-dz/UniFAR-FTUs huggingface dataset:
Research on Sandy Desertification in Inner Mongolia by Remote Sensing and GIS

Using two images data in late 1980s and in 2000 as information sources through synthesis,enhancement,correction,mosaic , and man-computer interactive ,on the basis of getting two data of sandy desertification,wedeeply analyzed the present condition of sandy desertification in 2000 of the whole autonomous region ,and at the same time , set up transfer matrix and dynamic rate of sandy desertification landsin late 1980s and in 2000 through count change of area in various degrees sandy desertification lands in ten years in the middle part of Inner Mongolia byadoptingtransfer matrix method and mathematical modeling method . The conclusions are as follows: ①67. 72 %of the whole autonomous region is sandy desertificated seriously. (include potentialsandydesertification lands ) ; ②It is obvious that there is latitudinalzonallaw for the distribution of sandydesertification. According to remote sensing image feature and image interpretation, it canbe divided into three latitude zones, whichareHulunbiarsandydesertificationzone (48-52 N) , the north side of the YinshanHunshandake--Keerqinsandy desertification zone ( 42-44 N), and Alax-Mowusu sandydesertification zone (38-40 N); ③The middle part of Inner Mongolia is the region with serioussandydesertification and spreading quickly wheresandy desertification landsover mid-degree isabove22 %; ④From the late 1980sto 2000, the net increaseofsandy desertification landsis about0.1 million hm 2 ,with the annual average dynamic rate is 0.75 %. 0.087 million hm 2non-sandy desertification lands in ten years changed into sandy desertification lands , meanwhile , 0.012 million hm 2 varioussandy desertification lands turned intonon-sandy desertification . ⑤Low-degree sandy desertification lands increased 121011.45 hm 2, mid-degree sandy desertification sandy desertification lands increased 327831.59 hm 2 ,strong sandy desertification lands increased 402497.13 hm 2 ,and serious sandy desertification lands increased 143998.67 hm 2 , meantime , 302758.83 hm 2 mid-degree sandy desertification lands and 281038.26 hm 2 strong sandy desertificationlands changed into strong and serious sandy desertification lands . ⑥The quick spreadingof sandy desertification seriously restricts the stability and sustainable development of social economy of Inner Mongolia autonomous region, and also threatens the safety of eco-environment of contiguous zone.
The Changing Coastline of the Cedros Peninsula, Trinidad

The extreme tip of south-western Trinidad at Icacos has been the site of aggressive shoreline erosion and accretion over the past several decades. The effects of erosion are particularly noticeable at Coral Point, Constance Estate and accretion at Punta del Arenal. Anecdotal evidence suggests that the rate of erosion at Coral Point has accelerated over the past three decades. There are few readily identified landmarks of known age making it difficult to measure recession or progradation of the shoreline. The most prominent are the estate buildings at Constance Estate and the base of the navigational beacon beside the beach road leading to Punta del Arenal. Nevertheless, using details of the earliest comprehensive coastal survey map of 1797, the Mallet Map, the Cazabon painting of Columbus Bay dated 1857 showing the Los Gallos rocks, and aerial photography of Icacos Point in 1957 and 1994, it has been possible to estimate rates of erosion and accretion. At Coral Point the rate of recession is approximately 4.3m per year while that of progradation at Punta del Arenal is about 3m per year. Evidence from the Mallet Map, the Cazabon painting and aerial photography indicates extreme change in the Los Gallos rocks over the past 200 years. It is suggested that the apparent acceleration at Constance Estate may be caused by continued natural erosion of the Los Gallos rocks permitting more violent longshore currents in Columbus Bay.
L2 stress discrimination by non-musicians and musicians playing wind or percussion instruments

The present study explores the influence of music expertise on French-speaking listeners' ability to process L2 Spanish stress. Musicians playing wind or percussion instruments and non-musicians completed an Odd-One-Out task, where they heard three Spanish words presented in babble noise and were asked to detect the word with a different stress pattern. Results first showed that musicians (playing either wind or percussion instruments) outperformed non-musicians, confirming the advantage of music expertise in 'speech in noise' perception. Secondly, they revealed that percussionists – who, as rhythm experts, relied more on stress-related timing cues – performed better than musicians playing wind instruments – who, as pitch experts, were more sensitive to stress-related pitch cues – in detecting stress in Spanish words presented in babble noise. Finally, there was no evidence of the larger advantage of being a musician when processing L2 stress under perceptually challenging conditions. Taken together, our findings not only highlighted the benefits of music expertise in L2 stress perception, but also revealed that the type of music instruments played by the musicians also influences L2 stress discrimination performance.
TOURISM ONTOLOGY AND SEMANTIC MANAGEMENT SYSTEM: STATE-OF-THE-ARTS ANALYSIS

ABSTRACT The global importance of tourism is steadily rising,creating new job opportunities in many countries. Today’s information management solutions for the complex tasks of tourism intermediaries are still at an early stage from a semantic point of view. This paper presents some preliminary results of OnTourism Project. OnTourism is aimed at (1) applying, concretizing and evaluating Semantic Web technologies such as ontologies, semantic annotation of content, and semantic search to the information-rich and economically important tourism domain, (2) identifying, developing and integrating reference ontologies for the tourism industry, and (3) showing the proof-of-concept in a real-world scenario of the Austrian tourism industry. First results presented in this paper identify publicly available tourism ontologies and existing freely available ontology management tools for the tourism domain. We identify seven tourism ontologies which are suitable as a basis for creating problem-specific ontologies. Furthermore we review and evaluate five freely available ontology management tools that are suited for application in the tourism domain.
Using teacher-supported peer feedback to develop student feedback literacy in L2 writing: An instructional model

To realize the potential of feedback, students need to possess feedback literacy. Frequently implemented in writing classrooms, peer feedback activities carry unique potential for developing student feedback literacy. This paper proposes an instructional model of teacher-supported peer feedback in relation to the enhancement of student feedback literacy from a self-regulatory perspective. The paper conceptualizes student feedback literacy as learners’ capabilities to carry out core activities in feedback processes, including seeking, generating, processing, and using feedback during self-regulation. It outlines pertinent teacher support before, during, and after peer feedback activities to facilitate student writers’ seeking, generating, processing, and using of feedback during their behavioral self-regulation of writing encompassing self-observation, self-judgement, and self-reaction. The instructional model highlights teacher support to foster an active learner role in feedback processes by giving students opportunities to conduct several rounds of feedback calibration by themselves before seeking teacher feedback. Future studies may investigate the implementation and effectiveness of the instructional model.
Unraveling behavioral biases in decision making: A study of Nepalese investors

The Nepalese stock market has experienced substantial transformations in recent years. Research on investors’ herding behavior is of paramount importance since it explores the influence of collective choices made by investors, which could result in intensified market price fluctuations. This study examined the influence of behavioral biases on investment decisions among Nepalese investors – general individuals who actively participate in the country’s stock market, considering overconfidence, representative, anchoring, regret aversion, and herding biases as explanatory variables, with investment decisions as the response variable. The study employed a linear regression model, establishing relationships using a structured questionnaire with 379 observations. The study revealed the significant influence of overconfidence, anchoring, and regret aversion biases on investment decisions among Nepalese investors. Conversely, the influence of representative bias had a little impact on investment choices, and herding behavior showed no significant relationship with investment decisions. Hence, it suggests that behavioral biases have a greater impact on individual investment choices in the Nepalese financial market. It is essential for investors, advisers, and policymakers to be aware of and address these biases to make well-informed decisions, maintain financial stability, and foster market development.
Experimental warming alters the relative survival and emigration of two dung beetle species from an Australian dung pat community

To preserve insect‐mediated ecosystem services under ongoing climate change, it is necessary to first understand the impact that warming will have on the insects that provide or mediate these services. Furthermore, because responses of a species may be modified by interactions with competitors, it is informative to examine warming effects on organisms and service provision under competition. Dung beetles provide numerous services to agriculture by burying the manure of other animals. To understand the potential impacts of climate warming on ecosystem service provision, we exposed two dung beetle species (Sisyphus rubrus and Euoniticellus fulvus (Coleoptera: Scarabaeidae)), occurring together in the same experimental pats, to warming and measured reproduction (dung ball production and burial, brood production, and egg laying), pat departure behaviour and survival of both species. These two species are likely competitors in pastures in northern New South Wales. To simulate climate warming, we used custom‐built chambers to add offsets (+0, +2 or +4°C) to field recorded, diurnally fluctuating baseline temperatures. There was no direct effect of increased temperature on any measured trait in either species. We did find however that the relative survival of the two species depended on temperature; S. rubrus had a higher probability (resulting in greater odds) of surviving than E. fulvus in the +0 and +4°C offset chambers, but not in the +2°C offset chambers. Likewise, the relative likelihood of the different species leaving a dung pat was temperature dependent; in the +2°C offset chambers, E. fulvus were more likely to leave than S. rubrus, but not in the +0 and +4°C offsets chambers. Our results highlight that it may be important for future studies to consider warming effects on relative survival and emigration because such effects could potentially lead to changes in dung beetle species composition.
Ecosystem Stability in Integrated Catchment Management

Freshwater is vital for human civilization. Growing population and societal development demand for more water resources. Freshwater is not considered globally scarce, but its distribution across the planet is not even and many countries suffer from water shortage. Human activities constantly produce an impact upon natural waters causing their destruction, degradation and pollution. Freshwater is a multi-purpose resource and this circumstance dictates a need to coordinate the interests of various water users. Integrated catchment management is a framework with the explicit objective to improve natural resources management on a catchment basis. Water resources are an integral part of ecosystems and their sustainable management is only possible within an ecosystem-based approach. It is important to predict ecosystem stability properties in response to exogenous stress. The paper discusses ecosystem stability from mathematical and ecological perspectives and demonstrates invariant patterns in ecosystem stress reactions. Using the typology of the stress reactions, the tasks of integrated catchment management can be viewed as a prediction of a particular type of ecosystem behaviour in response to the expected effects of planned activities.
A Detailed Study of SOT-MRAM as an Alternative to DRAM Primary Memory in Multi-Core Environment

As the current primary memory technology is reaching its limits, it is essential to explore alternative memory technologies to accommodate modern applications and use cases. However, using new memory technology poses the challenge of deriving accurately estimated parameters for integrating new memory technology and doing reliable simulations. This study proposes a new approach incorporating Spin-Orbit-Torque-Magnetic-RAM (SOT-MRAM) into hybrid and full main memory architectures within a multi-core system, encompassing various memory configurations and capacities. The study addresses the challenge of evaluating SOT-MRAM-based memory systems when specific SOT-MRAM memory parameters are not publicly available. The research methodology includes micro-architectural (circuit-level) design space exploration and comprehensive full system simulations, which evaluate benchmark programs representing diverse application domains. The evaluation includes three memory structures with varying memory organizations and capacities. The results show that SOT-MRAM is a robust replacement for DRAM or hybrid memory, offering compelling advantages such as a remarkable 74.05% reduction in power consumption, a noteworthy 40.10% increase in bandwidth utilization, and a significant 72.85% reduction in Energy-Delay Product (EDP). The maximum latency penalties are also minimal, with a 3.71% increase for hybrid structures and a mere 0.07% for standalone SOT-MRAM memory structures.
Measurement of Student Engagement in a Generic and Online Learning Management System-Based Environment

Use of technology on campuses of higher education has changed how students are engaged in the process of learning. It also has brought lot of asynchrony to the definition of class room teaching, active learning, student-staff interactions, and dealing with various academic challenges. The paper presents a study conducted to measure student engagement in a generic and online learning management system-based teaching learning environment. The paper presents threefold results. The first one is on identification of student engagement styles. The styles identified can further be used to design, develop, and implement most student engaging policies on campus which are beneficial to all the stakeholders. Second, the central point of the study is the student and her/his engagement with the learning process. The paper presents a student engagement report card to individual students for their analysis. Informing and involving students to know about their engagement report card would be beneficial. The third is feedback on a trail left by students' logs on the learning management system that can help the teachers to plan the teaching methodology. The methodology used was based on the data collected by the students of the institute/university. A student engagement questionnaire was used to measure student engagement in both generic and online learning environments. A cluster analysis was conducted on the data collected to identify the student engagement styles. A subcategory analysis was reported as a student engagement report card. The student-logged data on the institute learning management system was used to present the third analysis.
3D SH-wave Velocity Structure of East Asia using Love-Wave Tomography and Implication on Radial Anisotropy

We present a 3D SH-wave velocity model of the crust and uppermost mantle and seismic radial anisotropy beneath East Asia. The SH-wave velocity structure model was built using Love-wave group-velocity dispersion data from earthquake data recorded at broadband seismic networks of Korea, Japan, and China. Love-wave group-velocity dispersion curves were obtained by using the multiple filtering technique in the period range of 3 to 150 s for 3,369 event-station pairs. The inverted model using these data sets provides a crust and upper mantle SH-wave velocity structure down to 100 km depth. At 10 ~ 40 km depths SH-wave velocity beneath the East Sea is higher than beneath the Japanese island region. We estimated the Moho beneath the East Sea to be between 10 ~ 20 km depth, while Moho beneath the Korean Peninsula at around 35 km based on the depth where high-velocity anomalies are detected. We estimated the lithosphereasthenosphere boundary beneath the East Sea to be at around 50 km based on the depth where strong low-velocity anomalies are observed. Widespread low-velocity anomalies are found between 50 ~ 100 km depth in the study region. Positive radial anisotropy (VSV > VSH) is observed down to 35 km depth, while negative radial anisotropy (VSV > VSH) is observed for deeper depth.
Thermal performance estimation of a v-corrugated solar air heater using ann techniques

A solar air heater (SAH) is a unique form of solar thermal collector that utilizes solar energy emitted from the sun to produce heated air. Various experimental and theoretical investigations have been undertaken to improve the poor thermal performance of SAHs. The difficulties related to these studies drew attention toward a reliable soft computing technique exemplified by the Artificial Neural Network (ANN) technique. The current work applied actual meteorological data from Miskolc City, Hungary, to an ANN model with the structure of a Multi-layer Perceptron (MLP) to forecast the energy performance of a V-corrugated solar-powered air heater. Seven input parameters and one output parameter make up the ANN structure, with a single hidden layer. For the purpose of selecting the most effective network for predicting output parameters, ten neurons have been assessed. The suggested ANN model was trained with 336 data sets using the Levenberg-Marquardt (LM) learning technique. The comparison of anticipated and real thermal performance values shows a very good agreement. The statistical error analysis showed that the optimal ANN model structure of 7-8-1 can reliably and accurately predict SAH’s thermal performance and thus it can save both time and cost.
Prediction of anticancer drug resistance using a 3D microfluidic bladder cancer model combined with convolutional neural network-based image analysis

Bladder cancer is the most common urological malignancy worldwide, and its high recurrence rate leads to poor survival outcomes. The effect of anticancer drug treatment varies significantly depending on individual patients and the extent of drug resistance. In this study, we developed a validation system based on an organ-on-a-chip integrated with artificial intelligence technologies to predict resistance to anticancer drugs in bladder cancer. As a proof-of-concept, we utilized the gemcitabine-resistant bladder cancer cell line T24 with four distinct levels of drug resistance (parental, early, intermediate, and late). These cells were co-cultured with endothelial cells in a 3D microfluidic chip. A dataset comprising 2,674 cell images from the chips was analyzed using a convolutional neural network (CNN) to distinguish the extent of drug resistance among the four cell groups. The CNN achieved 95.2% accuracy upon employing data augmentation and a step decay learning rate with an initial value of 0.001. The average diagnostic sensitivity and specificity were 90.5% and 96.8%, respectively, and all area under the curve (AUC) values were over 0.988. Our proposed method demonstrated excellent performance in accurately identifying the extent of drug resistance, which can assist in the prediction of drug responses and in determining the appropriate treatment for bladder cancer patients.
Antecedents of E-wallet Usage Intention: An Empirical Study

Nowadays, the importance of cashless transactions is increasing due to the advancement of technology, especially in the post-pandemic era. An e-wallet is an application that helps users make payments through a mobile device instead of cash. With the advent of e-wallets, people are shifting from using cash to cashless in the era of smartphone technology. This study aims to explore the antecedent factors affecting the intention to use e-wallets as a payment mechanism among young adults in Kerala, India. The study was conducted by following an extended Technology Acceptance Model (TAM) and a Unified Theory of Acceptance and Use of Technology (UTAUT). Data were collected from 380 users of e-wallets, and the data were analyzed using partial least squares structural equation modelling (PLS-SEM) following a two-step approach. The results of the path analysis showed that perceived usefulness and perceived ease of use are the most significant predictors of usage intention for e-wallets, followed by perceived trust and perceived risk. It is also revealed that perceived security does not affect the usage intention of e-wallets. The results will help policymakers make strategic decisions considering customer perceptions of usage intentions.
Effect of drying temperature on proximate components of turmeric rhizome in tray dryer

Freshly harvested turmeric rhizomes of Salem variety were procured from a farmer’s field. Turmeric rhizomes were cleaned, peeled, and dried in a tray dryer at 60, 70 and 80 oC temperature. Effect of drying temperature on proximate content viz. moisture content, carbohydrate, protein, oil, crude fiber and ash were evaluated. Completely Randomized Design was used for statistically analysis. Drying of turmeric rhizome at 60 oC temperature in tray dryer resulted with moisture content 10.81 %, carbohydrate 46.54 %, protein 9.58 %, oil 6.70 %, crude fibre 4.51 % and ash content 6.94 % in the dried turmeric powder.
Anomalous Dispersion in Reflection and Emission of Dye Molecules Strongly Coupled to Surface Plasmon Polaritons

We have studied dispersion of surface plasmon polaritons (SPPs) in the Kretschmann geometry (prism/Ag/dye-doped polymer) in weak, intermediate, and ultra-strong exciton–plasmon coupling regimes. The dispersion curves obtained in the reflection experiment were in good agreement with the simple model predictions at small concentrations of dye (Rhodamine 590, Rh590) in the polymer (Poly(methyl methacrylate), PMMA). At the same time, highly unusual multi-segment “staircase-like” dispersion curves were observed at extra-large dye concentrations, also in agreement with the simple theoretical model predicting large, small, and negative group velocities featured by different polariton branches. In a separate experiment, we measured angular dependent emission of Rh590 dye and obtained the dispersion curves consisting of two branches, one nearly resembling the SPP dispersion found in reflection and the second one almost horizontal. The results of our study pave the road to unparalleled fundamental science and future applications of weak and strong light—matter interactions.