Miracle-dz/UniFAR-FTUs huggingface dataset:
The Relationships between Emotional Intelligence and Leadership Effectiveness in Selected Malaysian Public Sectors

Emotional intelligence (EI) refers to an individual's capacity to effectively manage and regulate their emotions, enabling them to recognize and understand the potentially beneficial influence their emotions can have on others. The present study was conducted based on the assumption that emotional intelligence plays an important part in determining the effectiveness of administrative leaders within an organizational context. This is because leadership serves as the important driving force within an organization, guiding employees in their tasks and ensuring the overall success and prosperity of the organization. The main objective of the study was to find out the relationship between emotional intelligence and leadership effectiveness. 50 questionnaires were distributed to all administrative leaders who have a minimum of five years of working experience in any position, and a total of 50 questionnaires were returned. Hence, the data collected was analyzed using Statistical Package for Social Science (SPSS). The result indicated that there is a significant correlation between emotional intelligence and leadership effectiveness among administrative leaders, and strongly supports the previous research finding. It is anticipated that leaders are going to demonstrate an impressive level of emotional intelligence to effectively guide and influence people. Consequently, emotional intelligence empowers leaders to exert a positive influence on the work environment within which they function, since it enhances their self-awareness and their ability to perceive and understand the emotions of others.
Elastic metamaterials for guided waves: from fundamentals to applications

Guided waves, elastic waves propagating through bounded structures, play a pivotal role in various applications, including ultrasonic non-destructive testing and structural health monitoring. Recently, elastic metamaterials artificially engineered to exhibit physical properties not typically seen in nature have emerged as a ground-breaking approach, heralding a new era in guided wave-based technologies. These metamaterials offer innovative solutions to overcome the inherent constraints of traditional guided wave-based technology. This paper comprehensively reviews elastic metamaterials from their fundamental principles to diverse applications, focusing on their transformative impact in guided wave manipulation.
The centralization index: A measure of local spatial segregation

Segregated areas may occur around an attractive park or a waste incinerator, but the magnitude and group membership of the people in closest proximity will likely be difierent. We therefore introduce a local segregation measure that can be applied to any location within a metropolitan area, and that can identify the group that is relatively more concentrated around that reference location. We further introduce an inference approach to identify the statistical significance of a particular segregation value. In an exploratory setting the index can be used to generate a map of hot spots, and seed the question: “why is this group significantly concentrated around that location? ”
Mountain reference technique: Use of mountain returns to calibrate weather radars operating at attenuating wavelengths

The Mountain Reference Technique (MRT) was proposed as a means to perform a self-calibration of a weather radar system operating at an attenuating wavelength in a mountainous environment. Two convective rain events observed during the Grenoble 97-98 Experiment are selected here for an illustration and a further verification of the method at X band: the June 16, 1997, event is a medium event with maximum path-integrated attenuations (PIAs) of about 15 dB over a 9-km path, while the July 3, 1998, event is quite extraordinary with (1) a maximum PIA of 50 dB over the same distance and (2) the temporary presence of hail. An improved scheme is proposed for the MRT parameter estimation procedure with a more satisfactory treatment of such high-attenuation effects. It is shown that the optimal calibration factors obtained for the two rain events are almost equal to each other, a comforting result with respect to the radar equipment stability during the corresponding 1-year period. Although the MRT is based on reflectivity and attenuation measurements only, validation of the rain rate retrieval algorithms with respect to rain gage data for the June 16, 1997, rain event showed that this technique is relevant in terms of rain rate estimation. In particular, the MRT-calibrated Hitschfeld-Bordan algorithm provides satisfactory results for this medium-attenuation event. However, the July 3 case clearly demonstrates that this algorithm cannot correct for such high-attenuation effects because of its inherent instability. For both rain events the Marzoug-Amayenc algorithm, originally proposed for spaceborne configurations, is found to be stable and efficient in terms of rain rate estimation. These interesting features are counterbalanced by the fact that the algorithm implementation is limited to directions for which PIA measurements are actually available.
Enhanced AI-Based CSI Prediction Solutions for Massive MIMO in 5G and 6G Systems

Accurate Channel State Information (CSI) is critical for maximizing the throughput of massive Multi-Input Multi-Output (mMIMO) systems. Due to the environment dynamics and user mobility, CSI aging is a major challenge to achieving the large throughput of mMIMO promised by theory. CSI prediction can be used to overcome this without increasing the signaling overhead. Motivated by the anticipated native support for Artificial Intelligence (AI) in the fifth generation and beyond cellular standards, we propose deep learning CSI prediction solutions based on 3-Dimensional (3D) Complex Convolutional Neural Networks (CCNN). These solutions provide improved capabilities for capturing temporal and spatial correlations, enhancing CSI prediction performance. In particular, they utilize the angle delay decomposition of previously observed CSI to predict the future one. In one architecture, the network, dubbed CSI Prediction Network (CSI-PNet), uses small kernels with circular padding to efficiently capture the correlation between propagation paths in the angle domain. This architecture can be further improved by the use of an attention-like model to vary the weights and enhance prediction performance adaptively. We also propose methods to enhance robustness to noise and time and frequency offsets. We tested these solutions using 3GPP-compatible simulations and field measurements in a commercial network. Our solutions demonstrate stable performance and significantly outperform several benchmarks, especially at low and medium speeds. They strike a balance between performance and architecture complexity, indicating suitability for actual implementation.
To the Origin of Fungi: Analysis of MFS Transporters of First Assembled Aphelidium Genome Highlights Dissimilarity of Osmotrophic Abilities between Aphelida and Fungi

Aphelids are a holomycotan group, represented exclusively by parasitoids infecting algae. They form a sister lineage to Fungi in the phylogenetic tree and represent a key group for reconstruction of the evolution of Holomycota and for analysis of the origin of Fungi. The newly assembled genome of Aphelidium insullamus (Holomycota, Aphelida) with a total length of 18.9 Mb, 7820 protein-coding genes and a GC percentage of 52.05% was obtained by a hybrid assembly based on Oxford Nanopore long reads and Illumina paired reads. In order to trace the origin and the evolution of fungal osmotrophy and its presence or absence in Aphelida, we analyzed the set of main fungal transmembrane transporters, which are proteins of the Major Facilitator superfamily (MFS), in the predicted aphelid proteomes. This search has shown an absence of a specific fungal protein family Drug:H+ antiporters-2 (DAH-2) and specific fungal orthologs of the sugar porters (SP) family, and the presence of common opisthokont’s orthologs of the SP family in four aphelid genomes. The repertoire of SP orthologs in aphelids turned out to be less diverse than in free-living opisthokonts, and one of the most limited among opisthokonts. We argue that aphelids do not show signs of similarity with fungi in terms of their osmotrophic abilities, despite the sister relationships of these groups. Moreover, the osmotrophic abilities of aphelids appear to be reduced in comparison with free-living unicellular opisthokonts. Therefore, we assume that the evolution of fungi-specific traits began after the separation of fungal and aphelid lineages, and there are no essential reasons to consider aphelids as a prototype of the fungal ancestor.
Phenomenological Study of Online Thematic Learning at the Integrated Islamic Elementary School Al-Akhyar Muara Bungo

This study seeks to interpret the teacher's online planning, implementation, and assessment of thematic learning outcomes at Al-Akhyar Muara Bungo Integrated Islamic Elementary School. This study employs an interpretive phenomenological methodology for qualitative research. The interpretive phenomenological strategy seeks to comprehend the significance of the teacher's experience in planning, implementing, and assessing online thematic learning. There were five participants in the study: two fourth-grade teachers, two fifth-grade teachers, and one sixth-grade teacher. The procedure for identifying participants utilized a technique of purposive sampling. Instrument for data collection based on interviews and document analysis The findings of the study indicate that (1) teachers face obstacles when planning lessons because they must adapt the learning format to an online learning format. This difficulty is caused by insufficient accessibility, connectivity, and capabilities. Accessibility, connectivity, and skill constraints make it difficult for instructors to design adaptable learning activity formats for online learning. (2) Al-Akhyar Islamic Elementary School instructors implement online thematic learning by delivering instructional material via video and sending it to the Student Wa group. Sending videos via Wa has limitations. These restrictions include the limited video memory capacity, which restricts the video lengths that can be sent via Wa. (3) The teacher at Al-Akhyar Islamic Elementary School administers an online learning assessment by assigning homework through Wa and grading students based on the results of their homework. Due to limitations in planning, implementing, and evaluating learning, Al-Akhyar Muara Bungo Integrated Islamic Elementary School's online thematic learning does not present meaningful learning. The implementation of thematic learning has failed to motivate students to be more active, investigate, discover, and construct their own knowledge through exploration and reflection on the studied topics. The learning process must have the appropriate infrastructure and technology, schedule and activity arrangements, use of digital resources, and parental participation. Adequate access to learning will improve the efficiency of the implementation of online learning.
Concurrent conservation and development : lessons learned from a community-based case in Thailand

concept from a NGO or development agency, communities seem to be more willing to try their own conservation or development projects when they can see the experiences and results from another community. Communities may also be more willing to work with individuals from other communities than with government representatives, especially if there is any existing conflict or mistrust. Additionally, when new projects partner with successful projects, such as Pred Nai, it can be seen as adding some credibility to their own project and increasing their chances of obtaining outside funding.
Eolian Dune Degradation and Generation of Massive Sandstone Bodies in the Paleoproterozoic Makgabeng Formation, Waterberg Group, South Africa

ABSTRACT Massive sandstone bodies in the 1.85 Ga Makgabeng Formation, South Africa, are located within the middle and upper part of the formation and are associated with the oldest reported deposits of barchan and barchanoid-ridge dunes. Bases of massive sandstone bodies are channelized or planar. Channel-based bodies typically overlie low-angle or up to 26° inclined wind-ripple strata. Channel margins vary from low angle to vertical. Rarely, massive sandstones at channel margins display vague horizontal stratification and/or contain ripped-up fragments of wind-ripple strata. Planar-based massive sandstone bodies are lenticular and characteristically are interbedded with low-angle to horizontal dune toesets. These lobate massive sandstone bodies vary from 5 cm to 6 m in thickness and from 3 m to possibly over 50 m in width; some of the sandstone bodies onlap dune reactivation surfaces. Rare dewatering structures, parting lineations, and adhesion structures occur at tops of the massive sandstone bodies. Lower boundaries of massive sandstone bodies change from channelized to planar-based down the dune foresets. Massive sandstones were generated by two different mechanisms, which are inferred to have been triggered by significant precipitation events. The presence of steep margins, channeling, rip-up fragments, and dewatering features, and a lack of tractional structures, indicate that most massive sandstones were deposited from hyperconcentrated flows down the dune lee face. Flows were initially turbulent, analogous to hyperconcentrated flows, resulting in scouring of wind-ripple strata. As hyperconcentrated flows migrated onto the dune plinth, rapid deposition produced lobate massive sandstone deposits with planar bases. This sedimentation is linked to development of a hydraulic jump at the slipface-plinth intersection, which increased flow depth and reduced flow velocity. Some flows maintained their turbulence onto the dune plinth, resulting in erosion of the plinth and scouring into the underlying preserved dune deposits. Massive sandstone bodies linked to reactivation surfaces are more likely a result of partial lee-face collapse, which generated translational slides.
Towards Grouping in Large Scenes with Occlusion-aware Spatio-temporal Transformers

—Group detection, especially for large-scale scenes, has many potential applications for public safety and smart cities. Existing methods fail to cope with frequent occlusions in large-scale scenes with multiple people, and are difficult to effectively utilize spatio-temporal information. In this paper, we propose an end-to-end framework, GroupTransformer , for group detection in large-scale scenes. To deal with the frequent occlusions caused by multiple people, we design an occlusion encoder to detect and suppress severely occluded person crops. To explore the potential spatio-temporal relationship, we propose spatio-temporal transformers to simultaneously extract trajectory information and fuse inter-person features in a hierarchical manner. Experimental results on both large-scale and small-scale scenes demonstrate that our method achieves better performance compared with state-of-the-art methods. On large-scale scenes, our method significantly boosts the performance in terms of precision and F1 score by more than 10% . On small-scale scenes, our method still improves the performance of F1 score by more than 5% . The project page with code can be found at http://cic.tju. edu.cn/faculty/likun/projects/GroupTrans.
Last Glacial Maximum Human Occupation of the Transbaikal, Siberia

Abstract We analyze the late Pleistocene radiocarbon chronology of the Transbaikal region of Siberia and conclude that humans inhabited the area during parts of the Last Glacial Maximum, but completely abandoned it between 24,800 and 22,800 cal yr BP. Moreover, the distinct contrast between non-microblade producing sites and those with microblades on either side of the radiocarbon gap suggests that the new technology arrived with recolonization.
Intrauterine growth restriction in piglets modulates postnatal immune function and hepatic transcriptional responses independently of energy intake

Introduction: Insufficient prenatal nutrition can affect fetal development and lead to intrauterine growth restriction (IUGR). The aim of this study was to investigate hepatic transcriptional responses and innate immune function in piglets suffering from IUGR compared to normal-sized piglets at 3 days of age and explore whether the provision of an energy-rich supplement at birth could modulate these parameters. Methods: A total of 68 piglets were included in the study. Peripheral blood mononuclear cells were harvested for LPS stimulation, and organs were harvested post-mortem to quantify relative weights. Liver tissue was utilized for RNA sequencing coupled with gene-set enrichment analysis. Results: IUGR resulted in increased expression of genes such as PDK4 and substantial alterations in transcriptional pathways related to metabolic activity (e.g., citric acid and Krebs cycles), but these changes were equivalent in piglets given an energy-rich supplement or not. Transcriptomic analysis and serum biochemistry suggested altered glucose metabolism and a shift toward oxidation of fatty acids. IUGR piglets also exhibited suppression of genes related to innate immune function (e.g., CXCL12) and pathways related to cell proliferation (e.g., WNT and PDGF signaling). Moreover, they produced less IL-1β in response to LPS stimulation and had lower levels of blood eosinophils than normal-sized piglets. Discussion: Taken together, our results indicate that IUGR results in early-life alterations in metabolism and immunity that may not be easily restored by the provision of exogenous energy supplementation.
Predicting Player’s Healthiness Using Machine Learning

- This research paper introduces the PHD (Player Health Detection) system as a solution to address the issue of inadequate health checking of players prior to sports events. The PHD system, utilize real-time image and video processing technology, to detect players' health conditions and prioritize their safety and well-being. The system incorporates analysis of body balance, injury detection, exercise video analysis, and heart rate measurement to evaluate player eligibility for sports events. For this specific purpose, we have created a mobile application by integrating computer vision technology and employing specialized image processing software. The anticipated outcomes of this solution include injury prevention, enhanced player safety, and informed decision-making for coaches regarding player participation. The implementation of the PHD system contributes to the advancement of the sports industry by creating a safer environment and actively supporting the health and well-being of players.
Video-Based Depth Estimation Autoencoder With Weighted Temporal Feature and Spatial Edge Guided Modules

Convolutional neural networks with encoder and decoder structures, generally referred to as autoencoders, are used in many pixelwise transformation, detection, segmentation, and estimation applications, for example, which can be applied for face swapping, lane detection, semantic segmentation, and depth estimation, respectively. However, traditional autoencoders, which are based on single-frame inputs, ignore the temporal consistency between consecutive frames, and may, hence, produce unsatisfactory results. Accordingly, in this article, a video-based depth estimation (VDE) autoencoder is proposed to improve the quality of depth estimation through the inclusion of two weighted temporal feature (WTF) modules in the encoder and a single spatial edge guided (SEG) module in the decoder. The WTF modules designed with channel weighted block submodule effectively extract the temporal similarities in consecutive frames, whereas the SEG module provides spatial edge guidance of the object contours. Through the collaboration of the proposed modules, the accuracy of the depth estimation is greatly improved. The experimental results confirm that the proposed VDE autoencoder achieves a better monocular depth estimation performance than the existing autoencoders with only a slight increase in the computational cost.
Enhancing System Stability with FACTS Devices Using Least Mean Square Based Neural Network Algorithm

The main difficulty with the distribution and transmission network is the power quality (PQ) problems. These problems with PQ are categorised as voltage and current-based problems. Numerous compensation approaches are now required in grid-tied PV systems due to the reduction of PQ concerns. Because of its fixed-parameter architecture, power system stabilisers are ineffective. When equipped with a suitable additional damping control, like a Flexible AC Transmission System (FACTS) Controller effectively dampens low frequency oscillations. Under non-linear and linear loads, the soft computing algorithms have eliminated harmonics in the load currents. The complexity of the stability challenges has risen recently as a result of the rising penetration of various renewable energy sources (RESs) into power systems. This paper's main contribution is a thorough examination of microgrid research and voltage stability concepts. On the basis of an unpredictable load, a capacity restriction for power generation, and the characteristics of the slow feedback seen in a few microgrid systems, the small-signal stability has been studied. Widrof-Hof Least Mean Square Based Neural Network Algorithm for enhancing system stability with FACTS Devices is implemented in the suggested study for RES systems.
PAYMENTS FOR WATERSHED SERVICES REGIONAL SYNTHESES

Summary and conclusions. Asian countries are at different stages in exploring the potential of PES programs to provide environmental services. Indonesia and the Philippines have the largest number of documented PES activities, but all of these are still in the testing/pilot program stage. Consequently, only preliminary lessons learned and best practices are available. Key questions in Asia include whether the definition of PES can be broadened to include both environmental service and poverty alleviation goals, and whether PES can exist where governments exercise tight control over land use, as in much of China and Vietnam. While broader contextual factors, e.g., forms of governance and high population densities, affect the design and implementation of PES schemes in Asia, their feasibility is highly specific to local context. Preliminary evidence indicates that where feasible, PES schemes have the potential to be designed from the start to ensure a higher likelihood of success in Asia.
Steroidal Alkaloids from the Roots of Veratrum mengtzeanum Loes. with Their Anti-Inflammatory Activities

The phytochemical investigation of Veratrum mengtzeanum Loes. roots resulted in the isolation and characterization of two novel, namely Mengtzeanines A (1), Mengtzeanines B (2), and eight known steroidal alkaloids (3–10). Their structural properties were assessed though extensive spectroscopic techniques. All constituents 1–10 were analyzed for suppression of NO formation in LPS-induced RAW264.7 macrophages. Among them, constituent 6 (Verazine) showed inhibition against LPS-induced NO production (IC50 = 20.41 μM). Additionally, compound 6 could inhibit the secretion of IL1β, IL6, and TNFα, and downregulate the productions of iNOS and COX2 in LPS-induced RAW264.7 macrophages. Further experiments revealed that 6 exhibited a potent anti-inflammatory level in LPS-stimulated RAW264.7 macrophages via inhibiting NF-κB, and triggering of Keap1/Nrf2/HO-1 axis, implying that compound 6 may be a promising candidate for treating inflammatory disorders.