Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive gamification in collaborative location collecting systems: a case of traveling behavior detection

Collaborative location collecting systems (CLCS) is a particular case of collaborative systems where a community of users collaboratively collects data associated with a geo-referenced location. Gamification is a strategy to convene participants to CLCS. However, it cannot be generalized because of the different users’ profiles, and so it must be tailored to the users and playing contexts. A strategy for adapting gamification in CLCS is to build game challenges tailored to the player’s spatio-temporal behavior. This type of adaptation requires having a user traveling behavior profile. Particularly, this work is focused on the first steps to detect users’ behavioral profiles related to spatial-temporal activities in the context of CLCS. Specifically, this article introduces: (1) a strategy to detect patterns of spatial-temporal activities, (2) a model to describe the spatial-temporal behavior of users based on (1), and a strategy to detect users’ behavioral patterns based on unsupervised clustering. The approach is evaluated over a Foursquare dataset. The results showed two types of behavioral atoms and two types of users’ behavioral patterns.
Phylogeography using mitogenomes: A rare Dipodidae, Sicista betulina, in North‐western Europe

Abstract Repeated climatic and vegetation changes during the Pleistocene have shaped biodiversity in Northern Europe including Denmark. The Northern Birch Mouse (Sicista betulina) was one of the first small rodent species to colonize Denmark after the Late Glacial Maximum. This study analyses complete mitochondrial genomes and two nuclear genes of the Northern Birch Mouse to investigate the phylogeographical pattern in North‐western Europe and test whether the species colonized Denmark through several colonization events. The latter was prompt by (i) the present‐day distinct northern and southern Danish distribution and (ii) the subfossil record of Northern Birch Mouse, supporting early Weichselian colonization. Samples from Denmark, Norway, Sweden, Russia, Latvia, Estonia, and Slovakia were included. Mitogenomes were obtained from 54 individuals, all representing unique mitogenomes supporting high genetic variation. Bayesian phylogenetic analysis identified two distinct evolutionary linages in Northern Europe diverging within the Elster glaciation period. The results of the two nuclear genomes showed lower genetic differentiation but supported the same evolutionary history. This suggests an allopatric origin of the clades followed by secondary contact. Individuals from southern Denmark were only found in one clade, while individuals from other areas, including northern Denmark, were represented in both clades. Nevertheless, we found no evidence for repeated colonization's explaining the observed fragmented distribution of the species today. The results indicated that the mitogenome pattern of the Northern Birch Mouse population in southern Denmark was either (i) due to the population being founded from northern Denmark, (ii) a result of climatic and anthropogenic effects reducing population size increasing genetic drift or (iii) caused by sampling bias.
Seleksi Peserta Didik Baru Dengan Metode Additive Ratio Assessment (ARAS)

Penerimaan peserta didik baru merupakan kegiatan penerimaan calon siswa baru di sekolah pada awal semester yang sering disingkat dengan PPDB. PPDB pada sekolah tingkat pratama dimana kriteria masuk SMP Negeri menyesuaikan kriteria yang ada di dinas pendidikan. Kriteria yang digunakan yaitu nilai matematika, bahasa indonesia, IPA, sertifikat akademik maupun non akademik mulai dari sertifikat tingkat Kabupaten/kota, sertifikat Provinsi, sertifikat Regional, sertifikat Nasional dan Juara Umum pada sekolah dasar. Penyeleksian menggunakan metode additive ratio assessment (ARAS) untuk menghindari kecurangan dalam PPDB. Hasil uji coba pada penelitian ini menggunakan 10 data dengan perankingan tertinggi yaitu A1 dengan nilai tertinggi 0,790 bernama Sandri Pratama.
The energy release rate for non-penetrating crack in poroelastic body by fluid-driven fracture

A new class of constrained variational problems, which describe fluid-driven cracks (that are pressurized fractures created by pumping fracturing fluids), is considered within the nonlinear theory of coupled poroelastic models stated in the incremental form. The two-phase medium is constituted by solid particles and fluid-saturated pores; it contains a crack subjected to non-penetration condition between the opposite crack faces. The inequality-constrained optimization is expressed as a saddle-point problem with respect to the unknown solid phase displacement, pore pressure, and contact force. Applying the Lagrange multiplier approach and the Delfour–Zolésio theorem, the shape derivative for the corresponding Lagrangian function is derived using rigorous asymptotic methods. The resulting formula describes the energy release rate under irreversible crack perturbations, which is useful for application of the Griffith criterion of quasi-static fracture.
Data-Intensive Engineering

Part I of this book discussed the evolving landscape of data-intensive computing and the challenges that organizations and individuals face in extracting knowledge and, eventually, value from data. Part II delved deeper into the analysis processes needed to perform data-oriented computations. These processes included not just analysis techniques, patterns, and approaches to deal with widely distributed and unstructured data, but also strategies for adapting the higher level development processes to deal with dynamic and changing data sources. Part III, this part, is targeted at technical experts, mostly data-analysis experts and data-intensive engineers, expecting to develop components or complex applications in DISPEL and those considering developing platforms supporting the data-intensive architecture outlined here. There may be some domain experts, who will find this discussion interesting, but like the automobile it is not necessary to understand the engine to drive the car; this part is for those that want to understand and work on the data-intensive platform. While most of the focus so far has been on knowledge discovery, the architecture outlined is of a general nature and should be considered by practitioners across a wide range of (data-centric) specialities, for example the programming paradigms such as Hadoop [1], mapreduce [2], and related technologies. We expect data-analysts from many disciplines to make effective use of the data-intensive platform and to contribute its expanding capabilities, including general technologies of data-intensive distributed computing, such
Tracking Changes in the Spring Barley Gene Pool in Poland during 120 Years of Breeding

This study was undertaken to investigate the diversity and population structure of 83 spring barley (Hordeum vulgare L.) cultivars, which corresponded to 120 years of this crop’s breeding in Poland. The analysis was based on 11,655 DArTseq-derived SNPs evenly distributed across seven barley chromosomes. Five groups were assigned in the studied cultivars according to the period of their breeding. A decrease in observed heterozygosity within the groups was noted along with the progress in breeding, with a simultaneous increase in the inbreeding coefficient value. As a result of breeding, some of the unique allelic variation present in old cultivars was lost, but crosses with foreign materials also provided new alleles to the barley gene pool. It is important to mention that the above changes affected different chromosomes to varying degrees. The internal variability of the cultivars ranged from 0.011 to 0.236. Internal uniformity was lowest among the oldest cultivars, although some highly homogeneous ones were found among them. This is probably an effect of genetic drift or selection during their multiplications and regenerations in the period from breeding to the time of analysis. The population genetic structure of the studied group of cultivars appears to be quite complex. It was shown that their genetic makeup consists of as many as eleven distinct gene pools. The analysis also showed traces of directed selection on chromosomes 3H and 5H. Detailed data analysis confirmed the presence of duplicates for 11 cultivars. The performed research will allow both improvement of the management of barley genetic resources in the gene bank and the reuse of this rich and forgotten variability in breeding programs and research.
Ice‐Nucleating Particles That Impact Clouds and Climate: Observational and Modeling Research Needs

Atmospheric ice‐nucleating particles (INPs) play a critical role in cloud freezing processes, with important implications for precipitation formation and cloud radiative properties, and thus for weather and climate. Additionally, INP emissions respond to changes in the Earth System and climate, for example, desertification, agricultural practices, and fires, and therefore may introduce climate feedbacks that are still poorly understood. As knowledge of the nature and origins of INPs has advanced, regional and global weather, climate, and Earth system models have increasingly begun to link cloud ice processes to model‐simulated aerosol abundance and types. While these recent advances are exciting, coupling cloud processes to simulated aerosol also makes cloud physics simulations increasingly susceptible to uncertainties in simulation of INPs, which are still poorly constrained by observations. Advancing the predictability of INP abundance with reasonable spatiotemporal resolution will require an increased focus on research that bridges the measurement and modeling communities. This review summarizes the current state of knowledge and identifies critical knowledge gaps from both observational and modeling perspectives. In particular, we emphasize needs in two key areas: (a) observational closure between aerosol and INP quantities and (b) skillful simulation of INPs within existing weather and climate models. We discuss the state of knowledge on various INP particle types and briefly discuss the challenges faced in understanding the cloud impacts of INPs with present‐day models. Finally, we identify priority research directions for both observations and models to improve understanding of INPs and their interactions with the Earth System.
Navigating the Importance of Selected Educational Technology Tools in Enhancing and Transforming the Task-Based Learning Method: Reflective Insights from Teaching Graduate Educational Psychology Students at one Ugandan University

The study aimed at navigating how edtech tools enhance and transform task-based learning method among university students pursuing graduate studies in Educational Psychology. Basing on Blooms Taxonomy especially the Higher Order Thinking Skills (HOTS), Laurillard's Conversational Framework, TPCK model, SAMR design and the Teaching Change Framework, the researcher motivated the graduate students to utilise Mindmups, Google Slides, WhatsApp texts and Turnitin educational technology (EdTech) tools to navigate if these tools, due to their respective affordances, enhance and transform task-based learning. The study was a visual ethnographic one by design with visual narratives for analysis purposes. It was established that the mentioned tools enhanced learner motivation, interest, participation and ultimately, academic performance. It was concluded that edtech tools, if selected due to their respective affordances, based on the right models, can improve learning and cause changes in the methods in place to transform low-technology-lecturer-centred learning to high-technology-learner-centred learning.
Comparing Flaxseed and Perindopril in the Prevention of Doxorubicin and Trastuzumab-Induced Cardiotoxicity in C57Bl/6 Mice

Background: Two anti-cancer agents, doxorubicin (DOX) and trastuzumab (TRZ), are commonly used in the management of breast cancer in women. Despite their efficacy in reducing the morbidity and mortality of individuals with breast cancer, the use of these agents is limited by adverse cardiotoxic side effects. Both the nutraceutical agent flaxseed (FLX) and the pharmaceutical drug perindopril (PER) have been studied individually in the prevention of chemotherapy-mediated cardiac dysfunction. The objective of this study was to determine whether the prophylactic administration of FLX is comparable and/or synergistic with PER in preventing DOX + TRZ-induced cardiotoxicity. Methods: Over a six-week period, 81 wild-type C57Bl/6 female mice (8–12 weeks old) were randomized to receive regular chow (RC) or 10% FLX-supplemented diets with or without PER (3 mg/kg/week; oral gavage). Starting at week 4, mice were randomized to receive a weekly injection of saline or DOX (8 mg/kg) + TRZ (3 mg/kg). Serial echocardiography was conducted weekly and histological and biochemical analyses were performed at the end of the study. Results: In mice treated with RC + DOX + TRZ, left ventricular ejection (LVEF) decreased from 75 ± 2% at baseline to 37 ± 3% at week 6. However, prophylactic treatment with either FLX, PER, or FLX + PER partially preserved left ventricular systolic function with LVEF values of 61 ± 2%, 62 ± 2%, and 64 ± 2%, respectively. The administration of FLX, PER, or FLX + PER was also partially cardioprotective in preserving cardiomyocyte integrity and attenuating the expression of the inflammatory biomarker NF-κB due to DOX + TRZ administration. Conclusion: FLX was equivalent to PER at preventing DOX + TRZ-induced cardiotoxicity in a chronic in vivo murine model.
Efficient Computer-Generated Holography Based on Mixed Linear Convolutional Neural Networks

Imaging based on computer-generated holography using traditional methods has the problems of poor quality and long calculation cycles. However, recently, the development of deep learning has provided new ideas for this problem. Here, an efficient computer-generated holography (ECGH) method is proposed for computational holographic imaging. This method can be used for computational holographic imaging based on mixed linear convolutional neural networks (MLCNN). By introducing fully connected layers in the network, the suggested design is more powerful and efficient at information mining and information exchange. Using the ECGH, the pure phase image required can be obtained after calculating the custom light field. Compared with traditional computed holography based on deep learning, the method used here can reduce the number of network parameters needed for network training by about two-thirds while obtaining a high-quality image in the reconstruction, and the network structure has the potential to solve various image-reconstruction problems.
Childhood Maltreatment and Psychosocial Flourishing among Emerging Adults: Roles of Psychological Suzhi and Self-Esteem

Studies have shown that childhood maltreatment can negatively predict psychosocial flourishing among emerging adults. However, few studies have revealed the factors that can protect the psychosocial flourishing of emerging adults who experienced maltreatment during childhood. Based on theoretical and empirical considerations, this study investigated whether and how psychological suzhi (a positive quality that can facilitate individuals’ adaptation to environment) plays a protective role in the relationship between childhood maltreatment and psychosocial flourishing among emerging adults. A total of 2863 Chinese emerging adults (Mage = 19.96 years) completed the self-report measures of the Childhood Trauma Questionnaire, Psychological Suzhi Questionnaire, Rosenberg Self-esteem Scale, and Flourishing Scale. The moderated analyses showed that childhood maltreatment had a less negative impact on psychological flourishing in high psychological suzhi emerging adults than in low psychological suzhi emerging adults. Part of the moderating effect of psychological suzhi is mediated through self-esteem. These results demonstrated that psychological suzhi plays a buffering effect between childhood maltreatment and psychosocial flourishing, and part of the effect is achieved by mediated variable self-esteem. These findings are discussed, and practical implications are presented.
On the Minimum Time Tracking Control of the Active Front End Converters

This article introduces the minimum time tracking control of an active front-end (AFE) converter with excellent transient performance. Since the dynamical model of the AFE converter is a bilinear system, switching control is provided for minimum time tracking with final time-varying trajectories in this system. Due to the complexity of implementing this controller, a suboptimal closed-loop controller is proposed whose dynamic performance is very close to the minimum time tracking control. Simulation and experimental results show that the suboptimal proposed controller has excellent dynamic performance against load disturbances compared with the conventional control methods.
Design and Control Method for Sub-module DC Voltage Ripple of HVDC-MMC

This paper proposes a design and control method for a high-voltage direction current modular multilevel converter (HVDC-MMC) considering the capacitor voltage ripple of the sub- module (SM). The capacitor voltage ripple consists of the line frequency and double-line-frequency components. The double line- frequency component does not fluctuate according to the active power, whereas the line-frequency component is highly influenced by the grid-side voltage and current. If the grid voltage drops, a conventional converter increases the current to maintain the active power. A grid voltage drops, current increment, or both occur with a capacitor voltage ripple higher than the limit value. In order to reliably control an MMC within a limit value, the SM capacitor should be designed on the basis of the capacitor voltage ripple. In this paper, the capacitor voltage ripple according to the grid voltage and current are analyzed, and the proposed control method includes a current limitation method considering the capacitor voltage ripple. The proposed design and control method are verified through simulation using PSCAD/EMTDC.
Variant Analysis and Strategic Clustering to Sub-Lineage of Double Mutant Strain B.1.617 of SARS-CoV-2

SARS-CoV-2 is an RNA coronavirus responsible for Acute Respiratory Syndrome (COVID-19). In January 2021, the re-occurrence of COVID-19 infection was at its peak, considered the second wave of epidemics. In the initial stage, it was considered a double mutant strain due to two significant mutations observed in their Spike protein (E484Q and L452R). Although it was first detected in India later on, it was spread to several countries worldwide, causing high fatality due to this strain. In the present study, we investigated the spreading of B.1. 617 strain worldwide through 822 genome sequences submitted in GISAID on 21 April 2021. All genome sequences were analyzed for variations in genome sequences based on their effects due to changes in nucleotides. At Allele frequency 0.05, there were a total of 47 variations in ORF1ab, 22 in Spike protein gene, 6 variations in N gene, 5 in ORF8 and M gene, four mutations in Orf7a, and one nucleotide substitution observed for ORF3a, ORF6 and ORF7b gene. The clustering for similar mutations mentioned B.1. 617 sub-lineages. The outcome of this study established relative occurrence and spread worldwide. The study’s finding represented that “double mutant” strain is not only spread through traveling but it is also observed to evolve naturally with different mutations observed in B.1. 617 lineage. The information extracted from the study helps to understand viral evolution and genome variations of B.1. 617 lineage. The results support the need of separating B.1. 617 into sub-lineages.
Test and mechanism analysis for crack propagation by blasting in rock under the condition of unidirectional load

In deep rock blasting, there are different constraint conditions such as unidirectional loading, bidirectional loading and tridirectional loading due to in-situ stress. The similar model test of rock blasting under unidirectional load was carry out to study the law of crack propagation in rock by blasting in this study. A transparent material which conformed to the mechanical properties of hard rock is used to make specimens. A high-speed camera was used in some model blasts. After blasting the surface cracks on the specimen were measured, including the near zone and middle zone of blasting. The results showed that: (1) the radial main cracks in the specimens under initial static load propagated along the principal stress direction, which is different from that without initial stress, and there is almost no radial main crack in the direction perpendicular to the principal stress. (2) The average length of radial crack and diameter of circumferential fracture circle gradually decrease with the increase of unidirectional initial stress, but the diameter of compression crushing circle increase. (3) The maximum and average initial velocity of radial crack growth decrease with the increase of
Numerical Simulation of the Dispersion of Pollutant in a Canal

This work proposes a numerical approach to model 2D pollutant dispersion in a canal using the famous advection-reaction diffusion equations. The advection-dispersion equation model describes transport and diffusion problems as seen in mixing conservative, nonbuoyant pollutants deposited into a stream or canal. The canal consisted of a narrow channel that allows water inflow through an entry opening and outflow through an exit opening. We obtain stability conditions for finite difference schemes and show the existence and uniqueness of solutions for the finite element method. The simulations show that the concentration of pollutants in the canal is controlled by the divergence term and increases in the direction of ﬂuid ﬂow.
Development of Apremilast Nanoemulsion-Loaded Chitosan Gels: In Vitro Evaluations and Anti-Inflammatory and Wound Healing Studies on a Rat Model

Apremilast (APL) has profound anti-inflammatory and wound healing activity, alongside other dermal care. This study aims to develop APL-loaded NEs (ANE1-ANE5) using eucalyptus oil (EO) as the oil and Tween-80 and transcutol-HP (THP) as a surfactant and co-surfactant, respectively. The prepared NEs were then evaluated based on mean droplet size (12.63 ± 1.2 nm), PDI (0.269 ± 0.012), ZP (−23.00 ± 5.86), RI (1.315 ± 0.02), and %T (99.89 ± 0.38) and ANE4 was optimized. Further, optimized NEs (ANE4) were incorporated into chitosan gel (2%, w/v). The developed ANE4-loaded chitosan gel was then evaluated for pH, spreadability, in vitro diffusion, and wound healing and anti-inflammatory studies. Moreover, in vivo studies denoted improved anti-inflammatory and wound healing activity and represented a decrease in wound size percentage (99.68 ± 0.345%) for the APNE2 gel test compared to a negative control (86.48 ± 0.87%) and standard control (92.82 ± 0.34%). Thus, the formulation of ANE4-loaded chitosan gels is an efficient topical treatment strategy for inflammatory and wound healing conditions.