Miracle-dz/UniFAR-FTUs huggingface dataset:
A Column Generation Mathematical Model for a Teaching Assistant Workload Assignment Problem

Abstract. This paper presents a column generation-based modelling and solution approach for a teaching assistant workload scheduling problem that arises at academic institutions. A typical weekly workload schedule involves teaching deficiency classes, instructing problem-solving tutorial sessions, and allocating help-hours for students. For this purpose, a mixed-integer programming model that selects valid combinations of weekly schedules from the set of all feasible schedules is formulated. Due to the overwhelming number of variables in this model, an effective column generation procedure is developed. To illustrate the proof-of-concept along with modelling and algorithmic constructs, a case study related to the Department of Mathematics at Kuwait University is addressed. Computational results based on real data indicate that the generated schedules using the proposed model and solution procedure yield improved weekly workloads for teaching assistants in terms of fairness, and achieve enhanced satisfaction levels among assistants, as compared to schedules obtained using ad-hoc manual approaches.
Assessing short-term social media marketing outreach of a healthcare organization using machine learning

Social networking portals serve as an ideal platform for a person or an organization, to accomplish self-presentation and self-enhancement goals there by to understand their social relevance and hence, there have been many studies attempting to identify the relationship between different aspects of social media articles. Machine learning methods play a critical role in social media data analytics. This study evaluates the efficiency of predictive analytics with social media data of a private healthcare institution using classification and clustering algorithms. In this study, we also investigated the influence of system specific feature set and user generated features of social media articles to identify relevant data mining algorithms that are suitable for identifying knowledge-related patterns in dataset. Among the classification methods it is found that Bayesian algorithm performs better compared to other classification techniques. K-Means and Filtered cluster among the clustering techniques have better predictive analytics efficiency compared to other algorithms. Identifying the predictive analytics efficacy of these algorithms helps healthcare institution to build a model with most appropriate characteristics of social media articles.
Development and validation of the educational psychological capital scale

Since the introduction of psychological capital to the field of education, it has drawn a lot of interest from researchers. This is due to the numerous studies that have demonstrated the positive effects of psychological capital on academic performance. Nevertheless, the psychological capital scale was initially developed to measure the psychological capital of employees, not students. There is a dearth of studies that examine the psychological capital scale’s psychometric properties in educational contexts, particularly in Southeast Asia. Therefore, the present study aims to develop and test the validity of an educational psychological capital scale. The study was carried out with the participation of a total of 2,494 undergraduates. The tests of indicator reliability, construct reliability convergent, validity, and discriminant validity were executed. The result revealed that the scale demonstrated satisfactory psychometric properties. The study also found psychological capital can serve as a positive predictor of student academic performance. It signified that the scale can be used to measure student psychological capital precisely. This has resolved the flaw of the original psychological capital scale, which measured students’ psychological capital in the workplace rather than in educational settings. However, since the study was conducted in Malaysia, the psychometric properties of the scale can be further verified in other countries.
ZRTP: Media Path Key Agreement for Unicast Secure RTP

This document defines ZRTP, a protocol for media path Diffie-Hellman exchange to agree on a session key and parameters for establishing unicast Secure Real-time Transport Protocol (SRTP) sessions for VoIP applications. The ZRTP protocol is media path keying because it is multiplexed on the same port as RTP and does not require support in the signaling protocol. ZRTP does not assume a Public Key Infrastructure (PKI) or require the complexity of certificates in end devices. For the media session, ZRTP provides confidentiality, protection against man-in-the-middle (MiTM) attacks, and, in cases where the signaling protocol provides end-to-end integrity protection, authentication. ZRTP can utilize a Session Description Protocol (SDP) attribute to provide discovery and authentication through the signaling channel. To provide best effort SRTP, ZRTP utilizes normal RTP/AVP profiles. ZRTP secures media sessions which include a voice media stream, and can also secure media sessions which do not include voice by using an optional digital signature.
Fusion of Topic Modeling and RoBERTa for Detecting Signs of Depression from Social Media

Depression, or Major Depressive Disorder, is a serious and common medical condition that affects people worldwide. It negatively affects the person's feelings, thoughts, and actions. Depression causes a loss of interest in activities he enjoyed in the past. It can lead to physical and emotional problems that hamper the daily activities at work and home. In recent years, much research has been done to identify Depression through various modalities of image, speech, and text through artificial intelligence. Social media is an important medium where many discussions and mentions happen about Depression. The current study proposes a novel approach to understand how the depressed and non-depressed communicate differently with the help of Topic Modeling with latent-Dirichlet allocation (LDA) and also detect depression with the help of Robustly Optimized BERT Pretraining Approach (RoBERTa). The current study achieved an accuracy of 66.4% for the depression detection model, which outperformed the previous approaches with similar methodology. The current study is helpful for self-diagnosis of signs of Depression at very early stages.
Exploring the Impact of Partial Occlusion on Emotion Classification From Facial Expressions: A Comparative Study of XR Headsets and Face Masks

This study provides of a comparative analysis of emotion estimation from facial expressions under partial occlusion caused by face masks and extended reality (XR) headsets. Unlike previous studies that have independently explored these two scenarios, this research compares and analyzes the statistical differences between them. In order to achieve this, the RAF-DB dataset has been used as a non-occluded baseline to construct two new datasets: i) a dataset formed by faces partially occluded by face masks, and ii) a dataset formed by faces partially occluded by XR headsets. To evaluate the impact of occlusion in emotion estimation, three deep learning models have been fine-tuned using transfer learning, and results from a random classifier have been used as a baseline. Seven different metrics were obtained per dataset, and a 2-way ANOVA test was performed on each metric. As expected, significant statistical differences are observed between the non-occluded faces (acc. 0.8780) and the faces partially occluded by face masks (acc. 0.7520) and XR headsets (acc. 0.7400) on all metrics. Notably, the comparison between the two partially occluded datasets revealed significant statistical differences in the metrics f1-score (macro), precision (macro) and recall (macro), which we attribute to different types of occlusion affecting different parts of the face that are key to some emotions. This research contributes to advancing emotion recognition systems by highlighting their robustness and effectiveness even in partial occlusion settings, and showing a full comparative analysis between two common types of occlusion.
A generalization of "image lossy data compression" recommendation

This paper deals with the encoding of high resolution images for remote sensing and geographic information systems applications. We are currently investigating the suitability of several still image coding techniques for this kind of applications. We present results for an adapted and modified version of the CCSDS-ILDC technique. In addition to evaluate its compression factor and quality of recovery with respect to the latest still image coding standard JPEG2000, we also consider whether this technique may fulfill the particular functionalities requested by remote sensing users
An Improved Protocol for Quantification of Freshwater Actinobacteria by Fluorescence In Situ Hybridization

ABSTRACT We tested a previously described protocol for fluorescence in situ hybridization of marine bacterioplankton with horseradish peroxidase-labeled rRNA-targeted oligonucleotide probes and catalyzed reporter deposition (CARD-FISH) in plankton samples from different lakes. The fraction of Bacteria detected by CARD-FISH was significantly lower than after FISH with fluorescently monolabeled probes. In particular, the abundances of aquatic Actinobacteria were significantly underestimated. We thus developed a combined fixation and permeabilization protocol for CARD-FISH of freshwater samples. Enzymatic pretreatment of fixed cells was optimized for the controlled digestion of gram-positive cell walls without causing overall cell loss. Incubations with high concentrations of lysozyme (10 mg ml−1) followed by achromopeptidase (60 U ml−1) successfully permeabilized cell walls of Actinobacteria for subsequent CARD-FISH both in enrichment cultures and environmental samples. Between 72 and >99% (mean, 86%) of all Bacteria could be visualized with the improved assay in surface waters of four lakes. For freshwater samples, our method is thus superior to the CARD-FISH protocol for marine Bacteria (mean, 55%) and to FISH with directly fluorochrome labeled probes (mean, 67%). Actinobacterial abundances in the studied systems, as detected by the optimized protocol, ranged from 32 to >55% (mean, 45%). Our findings confirm that members of this lineage are among the numerically most important Bacteria of freshwater picoplankton.
Seismic Performance of One-storey Thatched Roof Wooden Structure Against a Strong Earthquake Ground Motion

In order to investigate the seismic behaviour of an old one-storey thatched roof wooden structure, 3-D non-linear collapsing process analysis of this wooden structure was conducted against a strong earthquake ground motion with the Japan Meteorological Agency seismic intensity of “6 upper” level. A non-linear behaviour of timber elements in the wooden structure during a strong earthquake ground motion can be simulated by this 3-D non-linear collapsing process analysis based on the Distinct Element Method. The effect of the post fixing condition under wooden structure floor on seismic response of this wooden structure was numerically investigated in this paper.
Morphogenetic Evolvable Hardware Controllers for Robot Walking

We propose to develop reactive robot leg controllers in hardware using a morphogenetic approach that incorporates both evolutionary and developmental processes. Evolvable hardware has been crippled by issues of scalability and viability of evolved designs that arise when evolving complex circuits on modern mainstream field programmable gate arrays (FPGAs). To overcome these limitations requires a shift away from direct encodings of the FPGA configuration to encoding a growth process, morphogenesis, thus moving the complexity from the genotype to the genotype-phenotype mapping. Although a few researchers have attempted this, how to successfully apply morphogenesis to evolvable hardware still remains an open question.
Low-value Laplacian pyramid coefficient prediction for faster radiography image processing

We propose a method for predicting low-value Laplacian pyramid details that can be used for radiographic image processing time reduction via reorganization of the Laplacian pyramid calculation process. High resolution low-value detail prediction is based on the value of coarser details. Low-value details are then omitted in Laplacian pyramid calculation as well as in the image enhancement process. Proposed algorithm was evaluated on a database consisting of real medical images. Image degradation introduced by the proposed method was measured using structural similarity index (SSIM). It was shown that average processing time reduction of 4.62 % can be achieved without noticeable processed image degradation. The average SSIM obtained on the database was 0.995.
Comparison Of Financial Performance Based On The Implementation Of PSAK 30 And PSAK 73 On Leases In Energy Industry Companies

A finance operation that takes the form of supplying capital goods is called leasing. PSAK 30 will be replaced with PSAK 73, which was accepted from IFRS 16, on January 1, 2020. The purpose of this study is to compare the financial performance of the organization using leases for PSAK 30 and PSAK 73. A quantitative descriptive strategy is employed in this investigation. 67 firm samples were obtained using the purposive sampling approach from the population of 74 enterprises that made up the research. The firms in the energy industry sector that are listed on the Indonesia Stock Exchange during the 2019–2020 research period are the focus of this study. Ratio analysis, descriptive statistical analysis, regression analysis (which includes the normality test and the Wilcoxon signed rank test), and hypothesis testing are the data analysis techniques used in this work. According to the study's findings, which were derived from the use of descriptive statistics, hypothesis testing, and ratio analysis test, there is a difference in the financial performance of transportation firms listed on the Indonesia Stock Exchange when PSAK 30 and PSAK 73 are implemented.
Regulation of human thioltransferase (hTTase) gene by AP-1 transcription factor under oxidative stress.

PURPOSE To study the mechanism of activation of the human thioltransferase (hTTase) gene under oxidative stress. METHODS Human lens epithelial cells (HLE-B3) were exposed to 0.1 mM H2O2 for 0, 5, 10, 15, 30, or 60 minutes; lysed; and used for gel mobility shift assay (GMSA) and supershift assay for activating protein (AP)-1 transcription factor. The search for transcriptional coactivators was performed with Western blot analysis. The ability of different parts and a mutated fragment of the hTTase gene promoter region to activate the gene expression under the oxidative stress conditions was examined by reporter gene assay. RESULTS The AP-1-binding element was identified in the 5' region of the hTTase gene, and evidence was obtained that binding of AP-1 with this element in vivo was redox sensitive. In addition, the pattern of AP-1 binding under the oxidative stress was similar to the pattern of TTase activity and mRNA synthesis modulation. In contrast, direct exposure of the cell lysate to oxidants, reductants, or redox-regulating enzymes in vitro had no influence on AP-1 binding. AP-1 transcriptional coactivator redox factor (Ref)-1 was present in the lens epithelium and was association with the AP-1-binding complex during oxidative stress. In the reporter gene assay, only the fragments of the hTTase 5' region, which contained the AP-1-binding site, could activate the CAT reporter gene's expression in an oxidative stress-dependent manner. The mutant with a replaced AP-1-binding site failed to stimulate CAT expression in an oxidation-sensitive manner. The results showed that the c-Jun component in the AP-1-binding complex was transiently phosphorylated during H2O2 treatment. The c-Jun N-terminal kinase or SAPK/JNK, which responds to stress signaling and is the upstream protein kinase of c-Jun, was activated and translocated from cytosol to nucleus under the same conditions. CONCLUSIONS The data demonstrate that the activation of the hTTase gene under oxidative stress depends on the AP-1 transcription factor. The event was initiated only through an intact cell, possibly mediated through signal transduction by a phosphorylation-dephosphorylation mechanism. As far as the authors know, this is the first evidence of the association of AP-1 with the regulation of hTTase gene expression.
Effects of Drying Methods on the Physicochemical and Functional Properties of Cinnamomum camphora Seed Kernel Protein Isolate

Cinnamomum camphora seed kernel protein isolate (CPI) has attracted increasing attention due to its sustainability and potential applications. This study aimed to investigate the effects of freeze-drying (FD), vacuum-drying (VD), and spray-drying (SD) on the physicochemical and functional properties of CPI. The morphology observation results showed that the SD-CPI, SD-CPI, and VD-CPI were spherical, lamellar, and massive, respectively. Compared to FD and SD, VD had more impact on the color, surface hydrophobicity, intermolecular disulfide bonds, intrinsic fluorescence, and thermal stability of CPI. Fourier transform infrared spectroscopy (FTIR) analyses showed that among three CPI samples, VD-CPI had the highest content of β-sheet but the lowest contents of α-helix and β-turn. At different pH values, the solubility, emulsification, and foaming properties of VD-CPI were inferior to those of FD-CPI and SD-CPI. These results provide useful information on the changes in the physicochemical and functional properties of CPI subjected to different drying methods, and offer theoretical guidance for the production and use of CPI in the food industry.
Neutralino annihilation processes in the minimal supergravity model

We study all tree-level neutralino annihilation processes concerning energy-dependence at the mSUGRA benchmark point SPS1a using tree-level calculators MadGraph and CompHEP as well as FormCalc. We further investigate the total tree-level neutralino annihilation cross section by scanning over the mSUGRA parameters and identifying the dominant channels in every region. The results for the cross sections are presented in the m1/2-m0 planes for different values of tan(beta) and A0. We identify as well the resonances due to the exchange of the heavy Higgs bosons A and H in the s-channel of many neutralino annihilation processes, where the total cross section increases significantly if these Higgs bosons can be produced close to on-shell. Finally, we provide a few comments on the neutralino annihilation processes at loop-level.
Evaluating Recent Updated Black Carbon Emissions and Revisiting the Direct Radiative Forcing in Arctic

There is significant uncertainty in the global inventory of black carbon (BC). Several recent studies have reported BC emission updates, including the Fire Emission Inventory‐northern Eurasia, anthropogenic emission in Russia, and global natural gas flaring. Compared with the inventory used by Intergovernmental Panel on Climate Change, these updates are only 10% higher on a global scale but are 3 times greater than previous estimations in Arctic (60–90°N). We applied GEOS‐Chem to examine these emission updates and evaluate their impacts on direct forcing. We found that Fire Emission Inventory‐northern Eurasia may be substantially overestimated, Russia shows no prominent influence on simulation, and natural gas flaring noticeably improves simulation performance in the Arctic. Model estimated direct forcing of BC is increased by 30% on the global scale and is 2 times higher in the Arctic through application of these emission updates. This study reveals the urgent need to improve the reliability of emission inventories in the high latitudes, especially over Eurasia.
Vascular filters of functional MRI: Spatial localization using BOLD and CBV contrast

The spatial distributions of functional activation of rat somatosensory cortex by forepaw stimulation were quantitatively compared using blood oxygen level dependent (BOLD) signal and signal weighted by cerebral blood volume (CBV). The BOLD contrast to noise (CNR) distribution showed a significant dorsal shift with respect to the CBV method at fields strengths of 2 T (0.69 ± 0.09 mm) and 4.7 T (0.44 ± 0.15 mm). These shifts were attributed to the gradient of resting state blood volume across somatosensory cortex and the different CNR characteristics of the two image methods. The underlying principles suggest that the CBV method has a more uniform sensitivity to percent changes in functional indicators (blood volume or deoxygenated hemoglobin) across regions of variable resting state CBV. Magn Reson Med 42:591–598, 1999. © 1999 Wiley‐Liss, Inc.
Comparing Differences in Jogging Support across Various Land Use Types in Urban Built-Up Areas Using User-Recommended Routes

Land use types other than specialized athletic fields provide a variety of jogging environments, addressing the shortage of urban fitness facilities and promoting urban health as well as sustainability. Currently, there is limited research comparing the differences in jogging support among various land use types, which can assist decision-makers in setting priorities and targeted strategies for urban renewal, especially in urban built-up areas with limited land resources. Initially, spatial information, statistical data, and recommendation reason text were extracted from recommended routes in mobile fitness apps and categorized into six land use types. Subsequently, spatial potential was measured through descriptive statistics, buffer area analysis, spatial autocorrelation analysis, and line density analysis. Environmental preferences were gauged by text analysis using jieba word segmentation and grouped word frequency calculation. Finally, the measurement results of different land uses were compared, including scale differences, spatial differentiation, environmental perception, and environmental elements. The research found that streets, residential areas, campuses, parks, and greenways possess significant potential to support jogging, particularly streets. These types of land use exhibit varying spatial potentials and attractions in environmental preferences. Targeted recommendations have been proposed to support the renewal of urban built-up areas and research in related fields.
APP based iterations stopping criteria for MNBTC

A study of the iterations stopping criteria adapted to multi-non-binary turbo-decoders, based on the evolution of a posteriori probability density (APP) is presented. The performaces bit / frame error rate (B/FER) versus signal to noise ratio (SNR) of multi-non-binary turbo codes (MNBTC) equipped with the iterations stopping mechanism proposed in this study are compared with those obtained using the genie iterations stopping criterion. Details about the redundancy in the number of processed iterations as compared to the ideal criterion are also presented.