Miracle-dz/UniFAR-FTUs huggingface dataset:
Implementation of Learning Leadership, School Principal Supervisor, and Teacher Performance on Students’ Learning Outcomes

This study aims to analyze empirically (1) the influence of the principal’s learning leadership on MAN student learning outcomes in Jombang, (2) the influence of the principal’s supervisor on MAN student learning outcomes in Jombang, (3) the influence of the teaching effectiveness MAN results of student learning in Jombang (4) the impact of the head’s, supervisor’s, and teachers’ learning leadership on the learning outcomes of MAN students in Jombang. This research approach is quantitative, with a population of MAN teachers in Jombang and 310 teachers in Madrasah Aliyah (MAN) as respondents. The results of the study showed that (1) Principal learning leadership had no significant effect on MAN student learning outcomes in Jombang, (2) Principal supervisors had no significant effect on MAN student learning outcomes in Jombang, (3) Teacher performance in learning had a significant effect on student learning outcomes MAN in Jombang (4) Principal learning leadership, principal supervisor and teacher performance in learning simultaneously influence student learning outcomes of MAN in Jombang.
An exploratory study on how workplace bullying is conceptualised in the Australasian media

Workplace bullying continues to be a prominent issue in both New Zealand and Australian workplaces. Victims of workplace bullying suffer a multitude of grievances on a personal and working level, reducing their job satisfaction and job performance, whilst increasing levels of absenteeism and likelihood of quitting the organisation. An organisation which enables workplace bullying to remain unresolved is breaching legal statutes in Australasia, which require that employers provide a safe environment for their workers. This paper reports on an analysis of some 200 media articles from Australasia regarding the issue of workplace bullying, with a view to understanding how bullying is represented in the media. From a work-environment hypothesis view, the analysis sought to determine whether bullying was portrayed as predominantly a product of the work environment, or as a largely interpersonal concern. The findings of this paper suggest that although reports of the words “culture” and “environment” are present, particularly in New Zealand articles, there is little evidence from media accounts to indicate that Australasian sources perceive the issue of workplace bullying as one that is derivative from an organisation’s workplace environment. The implications of this finding indicate that Australasian media sources are placing the blame of bullying behaviours on the actions of employees, rather than holding organisations responsible for creating an environment that enables workplace bullying behaviours to occur.
Stepwise exhumation of the Triassic Lanling high‐pressure metamorphic belt in Central Qiangtang, Tibet: Insights from a coupled study of metamorphism, deformation, and geochronology

The E‐W trending Central Qiangtang metamorphic belt (CQMB) is correlated to the Triassic orogeny of the Paleo‐Tethys Ocean prior to Cenozoic growth of the Tibetan Plateau. The well‐exposed Lanling high‐pressure, low‐temperature (HP‐LT) metamorphic complex was chosen to decipher the process by which it was exhumed, which thereby provides insights into the origin of the CQMB and Qiangtang terrane. After a detailed petrological and structural mapping, three distinct N‐S‐trending metamorphic domains were distinguished. Microscopic observations show that core domain garnet (Grt)‐bearing blueschist was exhumed in a heating plus depressurization trajectory after peak eclogitic conditions, which is more evident in syntectonic vein form porphyroblastic garnets with zoning typical of a prograde path. Grt‐free blueschist of the mantle domain probably underwent an exhumation path of temperature increasing and dehydration, as evidenced by pervasive epidote veins. The compilation of radiometric results of high‐pressure mineral separates in Lanling and Central Qiantang, and reassessments on the published phengite data sets of Lanling using Arrhenius plots allow a two‐step exhumation model to be formulated. It is suggested that core domain eclogitic rocks were brought onto mantle domain blueschist facies level starting at 244–230 Ma, with exhumation continuing to 227–223.4 Ma, and subsequently were exhumed together starting at 223–220 Ma, reaching lower greenschist facies conditions generally after 222–217 Ma. These new observations indicate that the CQMB formed as a Triassic autochthonous accretionary complex resulting from the northward subdcution of the Paleo‐Tethys Ocean and that HP‐LT rocks therein were very probably exhumed in an extensional regime.
Prediction of the Tribological Properties of Polytetrafluoroethylene Composites Based on Experiments and Machine Learning

Because of the complex nonlinear relationship between working conditions, the prediction of tribological properties has become a difficult problem in the field of tribology. In this study, we employed three distinct machine learning (ML) models, namely random forest regression (RFR), gradient boosting regression (GBR), and extreme gradient boosting (XGBoost), to predict the tribological properties of polytetrafluoroethylene (PTFE) composites under high-speed and high-temperature conditions. Firstly, PTFE composites were successfully prepared, and tribological properties under different temperature, speed, and load conditions were studied in order to explore wear mechanisms. Then, the investigation focused on establishing correlations between the friction and wear of PTFE composites by testing these parameters through the prediction of the friction coefficient and wear rate. Importantly, the correlation results illustrated that the friction coefficient and wear rate gradually decreased with the increase in speed, which was also proven by the correlation coefficient. In addition, the GBR model could effectively predict the tribological properties of the PTFE composites. Furthermore, an analysis of relative importance revealed that both load and speed exerted a greater influence on the prediction of the friction coefficient and wear rate.
Utility of rapid on-site evaluation (ROSE) using toluidine blue stain in respiratory cytology

Introduction and Aim: Cytology has gained importance as a diagnostic test in pulmonary lesions, especially in patients presenting with advanced malignancy which are surgically non-resectable. Although cytopathological diagnosis may be limited, its role cannot be underestimated considering the minimal invasive nature of the technique. Single slide (SS) Rapid on-site evaluation (ROSE) will aid in adequacy assessment and diagnosis of pulmonary lesions on cytopathology. Materials and Methods: We conducted a prospective study. SS ROSE was done on transbronchial fine needle aspiration and bronchial brushing specimens using toluidine blue staining. The slides were microscopically evaluated for adequacy and for diagnosis. In case of inadequate smears, a repeat was suggested. The diagnosis was compared with the diagnosis rendered on remaining slides which were processed using conventional cytology. Results: The study includes 82 cases for ROSE. A correlation of 100% was found between ROSE diagnosis and final cytology diagnosis. Out of 82 cases, 24 cases were malignancies and 3 were granulomatous lesions on ROSE. The remaining were negative for atypical/malignant cells. 2nd pass was advised in 21 cases due to the inadequacy of the diagnostic material in 1st pass. Out of 21 cases advised for 2nd pass, 11 were found to be malignant. A statistically significant p value of 0.05 was obtained. Conclusion: In our study, we found that ROSE using toluidine blue stain is simple, yet a very useful procedure to reduce the number of passes, the need for repeat bronchoscopy procedure and helpful in suggesting more samples for ancillary tests and rapid cytopathological diagnosis.
Unsupervised Real Time and Early Anomalies Detection Method for Sewer Networks Systems

Sewer networks (SNs) are susceptible to various factors that can lead to failures, resulting in economic losses and environmental pollution. Data-driven approaches based on sewage flow monitoring enhance the awareness and maintenance capabilities of SNs. However, the current research lacks early warning systems for flow anomalies. This presents a challenge for the application of supervised methods, primarily due to the scarcity of anomalous flow datasets. Even with the availability of such datasets, the effectiveness of these methods may vary due to environmental differences, since SNs are situated in diverse environments. Therefore, effectively achieving early warnings for anomalies in unlabeled flow data is a challenge that must be addressed in the field of flow monitoring. To address this challenge, we propose a detection method for effectively warning of anomalies in flow data. Since anomalies typically result in significant deviations from normal data, early warnings can be achieved by comparing the differences between current and historical data. The key to this early warning lies in establishing an adaptive threshold for detecting abnormal data changes. Our detection method employs an unsupervised bagging-based multi-anomaly detection algorithm to detect such abnormal data changes. Experiments conducted on Erhai Lake SNs flow data demonstrate that our method can predict anomalies 5-15 minutes in advance with a precision of 80.00%, a recall of 66.67%, and an F1 score of 0.73. Our approach not only achieves cost-effective and timely anomalies detection but also overcomes the challenges associated with limited dataset availability, making it applicable to various other industries.
Predictive Resource Allocation Strategies for Cloud Computing Environments Using Machine Learning

Cloud computing revolutionizes fast-changing technology. Companies' computational resource use is changing. Businesses can quickly adapt to changing market conditions and operational needs with cloud-based solutions' adaptability, scalability, and cost-efficiency. IT operations and service delivery have changed due to widespread computational resource access. Cloud computing efficiently allocates resources in cloud environments, making it crucial to this transformation. Resource allocation impacts efficiency, cost, performance, and SLAs. Users and providers can allocate cloud resources based on workloads using elasticity, scalability, and on-demand provisioning. IT economics and operational effectiveness have changed due to rapid and flexible resource allocation. Proactive versus reactive resource allocation is key to understanding cloud resource management challenges and opportunities. Reactive strategies allocate resources only when shortages or surpluses occur at demand. This responsive strategy often leads to inefficiencies like over- or under-allocation, which raises costs and lowers performance. Predictive analysis and workload forecasting predict resource needs in proactive resource allocation. Optimize resource use to avoid shortages and over-provisioning. Attention has been drawn to proactive predictive resource allocation. These methods predict resource needs using historical data, machine learning, and predictive analytics. Predictive strategies optimize resource allocation by considering future decisions. Reduced bottlenecks boost user satisfaction and lower operational costs. Matching resource distribution to workloads optimizes cloud resource management. Resource allocation prediction improves with deep learning. CNN, LSTM, and Transformer cloud resource forecasting algorithms are promising. New tools for accurate and flexible workload predictions have come from their ability to spot intricate patterns in historical data. This paper compares CNN, LSTM, and Transformer deep learning algorithms for cloud computing resource allocation forecasting. This study determines the best predictive accuracy and workload ada[1]ptability algorithm using Google Cluster Data (GCD). The study evaluates upgrading cloud computing resource allocation with the Transformer model. This study advances predictive resource allocation strategies, which can help cloud service providers and organizations improve resource utilization, cost-effectiveness, and performance in the face of rapid technological change.
Hydrogeochemistry of a wetland area of southwestern Sicily (Italy)

The “Preola” and “Gorghi tondi” lakes are the most noticeable wetlands in the Mazara del Vallo territory (south-west Sicily). There are four karst origin lakes located in a natural depression formed by gypsum dissolution and subsequent collapse of the “Calcarenite di Marsala”, a few meters above sea level. Erosion of the depression sides and human activity has caused visible colluvial deposits, which have contributed to a natural filling process of the lakes. A hydrogeological map of the area and the reconstruction of a water circulation model supplying the lakes have been drafted from geochemical and hydrogeological data. It is apparent from δ18O values that the well waters are mainly fed by local meteoric water circulating within the calcarenitic aquifer. However, the lake waters chemical composition are very likely controlled by evaporation processes and a complex mixing between seawater and groundwater, depending on seasonal variation in the hydrodynamic equilibrium. SOMMARIO I laghi “Preola e Gorghi tondi” sono le aree umide più importanti del territorio di Mazara del Vallo (Sicilia sud-occidentale). Si tratta di quattro laghi di origine carsica situati in una depressione originata dalla dissoluzione di gessi e conseguente crollo della sovrastante “Calcarenite di Marsala”, ad una quota prossima al livello del mare. L’erosione e le attività umane sono la causa della formazione di depositi colluviali che hanno contribuito al naturale processo di interramento dei laghi. Con l’acquisizione di dati idrogeologici e geochimici è stato possibile disegnare una carta idrogeologica, linee di deflusso sotterraneo un modello di circolazione delle acque. I dati isotopici del δ18O dell’acqua di falda confermano che l’alimentazione dell’acquifero calcarenitico è dovuta ad acque meteoriche locali. Tuttavia la composizione chimica dei laghi e controllata da processi di evaporazione e di miscela tra acqua di mare e di falda, sensibilmente dipendenti dalle variazioni dell’equilibrio idrodinamico.
Nonisolated Integrated Boost Featured (NIIBF) Multi-Input Ultrahigh Gain DC–DC Converter

The nonisolated multi-input topologies are restricted to low voltage gain relative to single-input topologies. To achieve high voltage gain, coupled inductor, and various voltage-boosting techniques (such as switched inductors/capacitors) are used in the literature. The voltage-boosting structures increase the total component count, size, and cost of the converter. The operational limitations are observed in coupled-inductor-based converters due to peak current at a source side. This work proposes a nonisolated integrated boost featured converter without using a coupled inductor and voltage-boosting techniques. It achieves ultrahigh voltage gain with three basic boost cells, over other reported converters in a two-input category, with less component count and low average normalized voltage stress. It also facilitates flexible operating possibilities such as single-input, multi-input, and energy transfer capability among input ports. Furthermore, with equal duty cycle control ($D_{1}=D_{2}=D_{3}$), the power management between the energy storage systems is inherently provided by the proposed topological structure. The control complexity is minimized in a modified control algorithm. Hence, the integration of various energy storage systems is simplified. A hardware prototype is developed to validate the functional capability of the proposed converter.
Metagenomics study of tea rhizosphere soil in elevated carbon dioxide and temperature

One of the most pressing environmental issue of our time is climate change. Additionally, the atmospheric carbon dioxide concentrations and the global temperature are also increasing. North East India is widely known for tea. Tea cultivation is largely dependent on its distinct soil fertility and its associated microorganisms. However, little is known about how high elevated CO2 and temperature affect the rhizosphere of tea plants. This study was conducted in order to comprehend the general microbial diversity of the tea soil rhizosphere in response to rising temperatures and CO2 . The study was performed using two Open top chambers where four different tea cultivars were exposed to elevated CO2 and temperature, and only elevated temperature where microbial dynamics was studied using metagenomics of 16s rRNA analysis. The results indicated that in the treatments highest abundance was found in the phylum Proteobacteria, 32.11%, which was followed by Acidobacteria, 14.32% and Actinobacteria, 9.13%. Significant variations were observed in both treatments when compared to the control. The results of this study would thus help in understanding the culturable as well as unculturable bacteria associated with tea plant rhizosphere, which may be beneficial in planning future adaptation and mitigation strategies under climate change scenarios.
The Status Quo Analysis of Dam Removal in the World

The history of constructing water conservancy project has been several thousands of years.After industrialization,especially electricity being discovered in nature,making use of waterpower has been become the symbol of human civilization.Up to 20th century,dams constructing became prosperous and fashionable.Many dams and waterpower plants were built all over the world.As a result,the boom of constructing dams in 20th century greatly impelled the global economic development and social advancement.However,with continually constructing dams,some side effects brought by dams have been increasingly emerged and the disputes about dams have appeared.Based on above-mentioned reasons,in some countries dam removal was chosen as a means of river ecological restoration.Through collection foreign countries dam removal experiences,let more and more people understand that hydropower development should abide by scientific regulations.Otherwise,dam construction will bring us much more side effects.
K-Ar-Ages of Eocene to Oligocene Glauconitic Sands from Helmstedt and Lehrte (Northwestern Germany)

Glauconitic sand at Helmstedt and Lehrte is covered by sediments yielding Lower Oligocene nannoplankton (zone NP 21). The sand is subdivided at both localities by phosphoritic pebble beds and at Helmstedt is underlain by Middle Eocene zone NP 16 strata. Thus the glauconitic sands may include the whole Upper Eocene. The KlAr-dates from the sections below the pebble beds at Helmstedt and Lehrte (38.9 ± 0.6 and 38 ± 0.6 m.y.) indicate latest Late Eocene age. The dates from the upper part of the glauconite sand of the Gehlberg Formation (36.9 ± 0.7 and 36.5 ± 0.7 m.y.) and the dates from 1 Gefordert im Schwerpunktprogramm der Deutschen Forschungsgemeinschaft: . Geologische Kor­ relationsforschung" • 2 Author's addresses: Dr. FRANZ GRAMANN, Dr. ERNST-RuDIGER LOOK, Dr. BERNHARD MATTIAT, Niedersachsisches Landesamt fiir Bodenforschung, D 3000 Hannover 51, Postfach 510153. Dr. WILHELM HARRE, HANS KREUZER, BUlldesanstalt fiir Geowissenschaften und Rohstoffe, D 3000 Hannover 51, Postfach 51 01 53. 5 Newsletters 4 (2) (c) 2015 www.schweizerbart. com DOI:10.1127/nos/4/1975/71
Small Sample Target Recognition Based on Radar HRRP and SDAE-WACGAN

The high resolution range profile (HRRP) of radar targets is commonly used for target recognition, and the recognition of non-cooperative targets is one of the urgent problems to be solved in radar target recognition. In order to address the noise impact and small sample issues in non-cooperative target recognition, this paper proposes a radar target HRRP recognition method based on SDAE-WACGAN. This method combines Stacked Denoising Auto-encoders (SDAE) and Weighted Auxiliary Classifier Generative Adversarial Networks (WACGAN). In this networks, the decoder of SDAE is used as the generator of WACGAN and the weight coefficients is introduced on the basis of ACGAN, so that the network can generate high-quality data that is more consistent with the real sample distribution, and can be more robust to noise. Experimental results show that compared with other commonly used models, the proposed method achieves higher recognition accuracy in scenarios with small samples and high noise, and demonstrates certain advantages in different SNRs and different number of sample sets.
Transferability in the Automatic Off-Line Design of Robot Swarms: From Sim-to-Real to Embodiment and Design-Method Transfer Across Different Platforms

Automatic off-line design is an attractive approach to implementing robot swarms. In this approach, a designer specifies a mission to be accomplished by the swarm, and an optimization process generates suitable control software for the individual robots through computer-based simulations. Most relevant literature has focused on effectively transferring control software from simulation to physical robots. Here, we investigate <list list-type="ordered"><list-item><label>1)</label><p>whether the design methods that generate control software are transferable across robot platforms and</p></list-item> <list-item><label>2)</label><p>whether control software generated via such methods is itself transferable. </p></list-item> </list> We experiment with two ground mobile platforms with equivalent functional capabilities. Our measure of transferability is based on the performance drop observed when control software and/or design methods are ported from one platform to another. Results indicate that, while the control software generated via automatic design is possibly transferable, better performance can be achieved when a transferable method is directly applied to the new platform.
Synthesis, in silico and in vitro antimicrobial activity of N-(benzyl)-5-methyl-4-oxo-3,4-dihydrothieno[2,3-d]pyrimidine-6-carboxamides

According to the recent studies bezylcarboxamide fragment attached to the thiophene ring of thieno[2,3-d]pyrimidine is beneficial for antimicrobial activity of the compounds. Therefore we focused our efforts on constructing of the simple molecules such as N-(benzyl)-5-methyl-4-oxo-3,4-dihydrothieno[2,3-d]pyrimidine-6-carboxamides to get deeper insight into their antimicrobial activity. As the optimal procedure for preparation of target compounds we choose 1,1’-carbonyldiimidazole promoted interaction of 5-methyl-4-oxo-3,4-dihydrothieno[2,3-d]pyrimidine-6-carboxylic acid with the series of substituted benzyl amines. The obtained amides showed good activity against the strains of S. aureus and B. subtilis, which was higher for the derivative without substituents in benzene ring or the compounds with small substituents like methyl or methoxyl groups in the para-position of the benzene ring. Docking studies showed that despite the good values of the scoring functions, the conformational analysis of the ligands’ poses in the active site revealed their ability for only partial inhibition of TrmD of P. aeruginosa.