Miracle-dz/UniFAR-FTUs huggingface dataset:
Nonlinear dynamics of large-scale coherent structures in turbulent free shear layers

Fully developed turbulent free shear layers exhibit a high degree of order, characterized by large-scale coherent structures in the form of spanwise vortex rollers. Extensive experimental investigations show that such organized motions bear remarkable resemblance to instability waves, and their main characteristics, including the length scales, propagation speeds and transverse structures, are reasonably well predicted by linear stability analysis of the mean flow. In this paper, we present a mathematical theory to describe the nonlinear dynamics of coherent structures. The formulation is based on the triple decomposition of the instantaneous flow into a mean field, coherent fluctuations and small-scale turbulence but with the mean-flow distortion induced by nonlinear interactions of coherent fluctuations being treated as part of the organized motion. The system is closed by employing a gradient type of model for the time- and phase-averaged Reynolds stresses of fine-scale turbulence. In the high-Reynolds-number limit, the nonlinear non-equilibrium critical-layer theory for laminar-flow instabilities is adapted to turbulent shear layers by accounting for (1) the enhanced non-parallelism associated with fast spreading of the mean flow, and (2) the influence of small-scale turbulence on coherent structures. The combination of these factors with nonlinearity leads to an interesting evolution system, consisting of coupled amplitude and vorticity equations, in which non-parallelism contributes the so-called translating critical-layer effect. Numerical solutions of the evolution system capture vortex roll-up, which is the hallmark of a turbulent mixing layer, and the predicted amplitude development mimics the qualitative feature of oscillatory saturation that has been observed in a number of experiments. A fair degree of quantitative agreement is obtained with one set of experimental data.
An Extensive Literature Review on Risk Assessment Models (Techniques and Methodology) for Construction Industry

This study looks into the many methods that are used in the risk assessment procedure that is used in the construction industry nowadays. As a result of the slow adoption of novel assessment methods, professionals frequently resort to strategies that have previously been validated as being successful. When it comes to risk assessment, having a precise analytical tool that uses the cost of risk as a measurement and draws on the knowledge of professionals could potentially assist bridge the gap between theory and practice. This step will examine relevant literature, sort articles according to their published year, and identify domains and qualities. Consequently, the most significant findings have been presented in a manner that is consistent with logic and is predicated on the temporal evolution between 1990 and 2015.
Solving hyperbolic conservation laws by using Lagrangian-Eulerian approach

We discuss a procedure for numerically solving nonlinear hyperbolic conserva- tion law problems by means of a Lagrangian-Eulerian framework. The underlying hyperbolic conservation law is written in a space-time divergence form, so that inherent conservation properties of the problem are reflected in the numerical scheme. In order to enhance resolution and accuracy of the approximations, we make use of polynomial reconstruction ideas into the Lagrangian-Eulerian novel approach. Finally, numerical results are given to verify the formal construction as well as to demonstrate its accuracy, efficiency, and versatility. These results for the considered sample problems compare very well to analytical results.
Essential Surgical Techniques During Fully Endoscopic Spine Surgery: A Historical Review and Future Perspectives

Full-endoscopic spine surgery (FESS) offers minimally invasive techniques for treating spinal lesions with smaller incisions, leading to reduced tissue damage and consequently more rapid patient recovery. The essential techniques in FESS —namely, the transforaminal and interlaminar approaches—have evolved with technological advances in endoscopic systems and surgeon expertise. The transforaminal approach consists of “inside-out” and “outside-in” techniques that have distinct applications depending on the patient’s condition. The interlaminar approach, similar to traditional spinal surgery techniques, is gaining wider acceptance due to its efficacy in addressing unique anatomical challenges. Advanced procedures, such as endoscopic laminectomy and interbody fusion surgery, coupled with navigation systems, have broadened the scope of endoscopic spine surgery, making it an increasingly vital tool in modern spinal surgery.
Unravelling the Role of Uncommon Hydrogen Bonds in Cyclodextrin Ferrociphenol Supramolecular Complexes: A Computational Modelling and Experimental Study

We sought to determine the cyclodextrins (CDs) best suited to solubilize a patented succinimido-ferrocidiphenol (SuccFerr), a compound from the ferrociphenol family having powerful anticancer activity but low water solubility. Phase solubility experiments and computational modelling were carried out on various CDs. For the latter, several CD-SuccFerr complexes were built starting from combinations of one or two CD(s) where the methylation of CD oxygen atoms was systematically changed to end up with a database of ca. 13 k models. Modelling and phase solubility experiments seem to indicate the predominance of supramolecular assemblies of SuccFerr with two CDs and the superiority of randomly methylated β-cyclodextrins (RAMEβCDs). In addition, modelling shows that there are several competing combinations of inserted moieties of SuccFerr. Furthermore, the models show that ferrocene can contribute to high stabilization by making atypical hydrogen bonds between Fe and the hydroxyl groups of CDs (single bond with one OH or clamp with two OH of the same glucose unit).
The Influence of Work-Life Balance on Employee Performance

This study aims to examine the influence of work-life balance on employee performance, an empirical study of the hybrid working system for Telkomsel Regional Sumbagsel office employees. The data that used on this study are primary data, with 64 employees as a sample, using a simple random sampling technique. The analytical method used is quantitative analysis with a simple regression analysis. The result of this study is work-life balance has a positive and significant influence on employee performance. It is recommended for the company to provide support from both superiors and colleagues to employees in order to achieve a balance of work and personal life while doing hybrid working.
Crystal Structure of the ORP8 Lipid Transport ORD Domain: Model of Lipid Transport

ORPs are lipid-transport proteins belonging to the oxysterol-binding protein family. They facilitate the transfer of lipids between different intracellular membranes, such as the ER and plasma membrane. We have solved the crystal structure of the ORP8 lipid transport domain (ORD8). The ORD8 exhibited a β-barrel fold composed of anti-parallel β-strands, with three α-helices replacing β-strands on one side. This mixed alpha–beta structure was consistent with previously solved structures of ORP2 and ORP3. A large cavity (≈1860 Å3) within the barrel was identified as the lipid-binding site. Although we were not able to obtain a lipid-bound structure, we used computer simulations based on our crystal structure to dock PS and PI4P molecules into the putative lipid-binding site of the ORD8. Comparative experiments between the short ORD8ΔLid (used for crystallography) and the full-length ORD8 (lid containing) revealed the lid’s importance for stable lipid binding. Fluorescence assays revealed different transport efficiencies for PS and PI4P, with the lid slowing down transport and stabilizing cargo. Coarse-grained simulations highlighted surface-exposed regions and hydrophobic interactions facilitating lipid bilayer insertion. These findings enhance our comprehension of ORD8, its structure, and lipid transport mechanisms, as well as provide a structural basis for the design of potential inhibitors.
Rock fissure pattern characterization by combining 1-D fractal dimension and statistical analysis

How to characterize rock fissures/fractures is significant for the measurement and analysis in a lot rock engineering applications. A new method for characterizing rock fissure patterns is studied in this paper. It is constructed by combining 1-D fractal dimension and statistical analysis for the whole rock surface in an image. In a binary fissure image, to characterize fissures accurately, all the possible fissures are skeletonized, and then the short lines or curves are removed and the gaps on the main fissure segments are linking up. After that, 1-D fractal dimension is applied for analyzing fissure patterns, in which, the fissure network complexity and the fissure quantity is characterized by statistical analysis. The testing fissure images were taken from a Swedish laboratory and a Chinese Mine, and the testing results prove that the fissure pattern characterization by the new method is promising.
Type of Student’s Interaction in Learning Research Methodology Course

This paper aim to investigate on type of student’s interaction in learning Research Methodology course through a mobile learning environment. A qualitative research design was used in this study and data was collected from ten postgraduate students (purposive sampling) who have enrolled in a social science research course for one semester. Face-to-face interviews were conducted to collect the qualitative data to gather comprehensive information for this study. The findings and discussions in this study relate to five types of student interactions which are learner-learner, learner-instructor, learner-content, learner-self and learner-interface in the development of a mobile learning environment for a social science research course. The study concludes that student roles, instructor roles, learning tools, learning activities, and learning materials are important criteria to consider when developing student interactions, especially for social science researchers, in a mobile learning environment. In conclusion, this paper discusses four limitations and makes recommendations for future studies.
A Safety-Performance Metric Enabling Computational Awareness in Autonomous Robots

This letter takes a first step towards the analysis of safety and performance critical computational tasks for autonomous robots. Our contribution is a safety-performance (SP) metric that ensures safety first and then rewards improved performance of real-time computational tasks, building on the notion of “nominal safety” which defines timely computation as critical to safety. To fully utilize the computing capacity of heterogeneous processing units (e.g., CPU + GPU), a computational task graph model called the Stochastic Heterogeneous Parallel Directed Acyclic Graph (SHP-DAG) is adopted to capture the uncertain nature of robotic applications and their required computation. Compared to state-of-the-art task models, SHP-DAG avoids the pessimism of deterministic worst-case execution time (WCET), instead modeling the execution times of tasks by probability distributions. Our SP metric is defined upon this task model, which allows us to apply the FIFO and CFS schedulers of the Linux kernel on complex robotic computational tasks and compare the SP metric with baseline metrics, average and worst-case makespan. Extensive experimental results on NVIDIA Jetson AGX Xavier hardware demonstrate that the proposed SP metric is appropriate for managing computational tasks in a manner that balances safety and performance in robotic systems.
Acyl Homoserine Lactone-Based Quorum Sensing and its Role in Regulation of Extracellular Hydrolytic Enzymes in Marine Snow Associated Bacteria

The discovery of quorum sensing (QS) amongst bacterial cells substantiates the coordinated activities in these microscopic organisms. QS is a system of cell-to-cell communication through which bacteria express certain genes to achieve various physiological and biological functions. Presently, several kinds of autoinducers have been reported in microbial cells, however N -acyl homoserine lactones (AHLs) are known as the most significant QS autoinducers, frequently produced by large numbers of Gram-negative bacteria. QS system in marine snow associated bacteria has a great concern with respect to regulate extracellular enzymatic activities. Substantially, marine aggregates are large sinking particles composed of both organic and inorganic detritus and living organisms including phytoplankton, zooplankton and bacteria, and perform a critical role in moving materials from upper levels to deep Ocean. Intriguingly, findings of AHL signaling molecules in marine snow aggregates and associated microbial cells have been attributed to play a crucial role in dissociation of these large carbon rich particles with a profound impact on marine food webs along with biogeochemical cycles in marine environment. This mini review highlights the role of AHL based QS system in marine snow with respect to enhanced enzymatic activities (EEA) of marine snow associated bacterial populations and hydrolysis of these carbon rich aggregates.
Hybrid Microcalcification Detection In Mammograms

This paper presents a combined system for detecting microcalcifications in mammographic images. The proposed approach analyses the mammograms using the parallel combination of two methods. One of the methods is a heuristic approach that is based on features used by humans to descript microcalcifications. Second approach applies a hierarchical neural structure trained on images already interpreted by human experts. The results of the two methods are binary masks of the microcalcifications. These results are integrated on pixel level, currently the 'AND' relation of the binary masks are used. Tests show that the combined system could decrease false positive ratio significantly with a modest increase of false negative cases.
Defect and field-enhancement characterization through electron-beam-induced current analysis

To investigate the effects of defects and field enhancement in diamond power devices, a biased Schottky barrier diode was characterized by electron-beam-induced current (EBIC) analysis. The nonuniform distribution of the electrical field was revealed by bright spots on the laterally expanded depletion layer of the EBIC intensity map when the applied electrical field exceeded 0.95 MV/cm. The nonuniformity is partly due to a structural effect: the roughness at the edge of the Schottky electrode, induced by lithography and lift-off processes. A second family of spots was shown to increase the leakage current of the device. The time constant associated with this second spot family was 0.98 ms, which is three orders of magnitude shorter than that for defects previously characterized by deep-level transient spectroscopy.
Zircon Structure as a Prototype Host for Fast Monovalent and Divalent Ionic Conduction

: “Beyond Li-ion” energy storage solutions based on ions such as Na, Mg, Ca, and Zn have attracted increasing attention due to growing concerns about the cost, resource availability, and safety of the currently dominant Li-ion batteries. One of the greatest challenges for beyond-Li systems, especially multivalent ones, is the lack of materials with high ionic mobility. In this study, we find that zircon-type YPO 4 presents a unique structural environment that enables superior conduction of multiple species including Na + , Ca 2+ , Mg 2+ , and Zn 2+ , even in the dilute carrier concentration regime. This highly unusual capability originates from one-dimensional (1D) percolating channels of adjacent, distorted octahedral sites, which results in a smoothly varying coordination environment and correspondingly low activation barriers. Low decomposition energy of multiple compositions of doped YPO 4 , where the carrier ions are introduced into the system along with subvalent doping into P sites, confirmed good stability and synthesizability. Among these compositions, we found Na 0.0625 YSi 0.0625 P 0.9375 O 4 exhibiting good Na + conductivity of 0.99 mS/cm at 300 K with an activation energy of 220 meV. Zircon-structured Na 0.05 YSi 0.05 P 0.95 O 4 was successfully synthesized; however, the highest density achieved (78%) was insufficient to conclusively establish its conductivity. Finally, we identify dopant − carrier association in doped YPO 4 as a key challenge for long-range diffusion in this structure family.
A Quality-of-Experience Database for Adaptive Omnidirectional Video Streaming

Recent advances in virtual reality (VR) technologies and devices have enabled new forms of media content, such as omnidirectional video (ODV) that attracts increasing attention of both academic and industrial communities. Omnidirectional video, which is also called $360^\circ$ video, represents panoramic spherical video that can give users an immersive viewing experience. Compared with traditional 2D video, the complex characteristic (high resolution, bandwidth intensive, etc.) of ODVs brings up new challenges to stream them under volatile network conditions and model the quality-of-experience (QoE) of end-users. To meet the requirements of practical VR applications, it is desired to design effective methods for adaptive bitrate streaming (ABR) and QoE evaluation of ODVs. In this article, we establish a large omnidirectional video streaming QoE database (VRQoE-JUFE), containing 1,440 adaptive streaming ODVs generated with diverse content. A comprehensive subjective experiment is conducted, where viewing behaviors and human opinions of total 180 subjects are collected. We provide a thorough statistical data analysis and carry out performance evaluation of the-state-of-art objective QoE models on the proposed database. The results suggest that QoE modeling for ODV streaming is an extremely challenging problem and there is a large space for improvement. Many interesting observations are made that may shed light on the improvement in both omnidirectional video QoE modeling and ABR strategies in the future. The annotated dataset from the tests is made publicly available for the research community.
A New Species of Megastigmus and First Record of the Genus and Megastigmidae Family from the Paradise of the Maldives Archipelago

Simple Summary Pemphis acidula is a relative common plant on the seashores of the Maldives islands but it can be found in the coastline and mangroves zones from East Africa to Southeast Asia, Australia, Micronesia, and French Polynesia. We describe a new, very tiny species measuring around 1.6 mm in length, which develops as a larva inside the seeds of P. acidula, with one larva per seed. We photographed the live female and male specimens and used advanced microscopy techniques, such as scanning electron microscopy, to provide a detailed description of this new species. This research sheds some light on the Megastigmidae family and Megastigmus genus by discovering a surprising new species that provides interesting data on morphology and biology. It was conducted in the paradise of the Maldives Archipelago, offering insights into islands biodiversity and biogeography, climate change, and habitat destruction. Abstract Megastigmidae comprises more than 200 species in 12 genera. Megastigmus has a worldwide distribution with more than 150 species. Over 80% of these species are recorded from the Australian and Palearctic region, with a few from Afrotropical and Oriental regions, but none from the Neotropical region. We describe a new species of Megastigmus obtained from the seeds of Pemphis acidula in the Maldives Archipelago. This is the first mention of Megastigmidae having as a host plant a species from Lythraceae. It is also the first recorded association of Chalcidoidea with the genus Pemphis and the first mention of Megastigmidae and Megastigmus in the Maldives Archipelago. We provide a detailed description of the species, focusing on its morphology, using both light microscopy and scanning electron microscopy (SEM). Megastigmus irinae Popescu n. sp. is a strictly phytophagous species, with each larva consuming a single seed. Currently, M. irinae is an endemic species found only in the Maldives Archipelago. However, considering the distribution of its host plant, P. acidula, which ranges from East Africa to Southeast Asia, Australia, Micronesia, and French Polynesia, we anticipate that future research could significantly expand the known range of this interesting new species.
Evaluation of Antiphytoviral and Antibacterial Activity of Essential Oil and Hydrosol Extracts from Five Veronica Species

Agricultural production without pollution is possible using bioactive plant compounds, which include essential oils as important substances of plant origin. The aim of this study was to evaluate the antiphytoviral and antibacterial potentials of lipid (essential oil, EO) and water (hydrosol, HY) extracts from five Veronica species (Plantaginaceae) obtained by Clevenger hydrodistillation (HD) and microwave-assisted extraction (MAE), with analysis by gas chromatography coupled with mass spectrometry. The antiphytoviral activities of both extracts were tested on local host plants infected with tobacco mosaic virus (TMV). The antibacterial potential was tested against ten strains of opportunistic pathogens using the broth microdilution test. Species V. chamaedrys EO-MAE extract, V. arvensis EO from both extractions and V. montana, V. serpyllifolia, and V. persica EO-HD extracts were more effective in inhibiting TMV infection. Furthermore, HY- HD extracts of V. arvensis, V. chamaedrys and V. persica showed significant antiphytoviral activity. HY fractions had no effect on bacterial growth, regardless of the Veronica species tested, likely due to the fact that the maximum concentrations of the HY fractions tested in this study were low (1.83 and 2.91 mg/mL). EOs showed significant antibacterial activity independent of the extraction method. Notably, V. chamaedrys EO-MAE fraction, showed significantly better activity against Listeria monocytogenes and Enterococcus faecalis. Also, the EO-HD fraction of V. arvensis showed slightly better antibacterial activity. By combining extracts and using different extraction methods, valuable bioproducts can be obtained from the investigated Veronica species for safe use in agricultural production and food conservation.
Multitask Transfer Deep Reinforcement Learning for Timely Data Collection in Rechargeable-UAV-Aided IoT Networks

Thanks to their high-flexibility and low-operational cost, unmanned aerial vehicles (UAVs) can be used to support mission-critical applications in the Internet of Things (IoT). However, due to the limited onboard energy, it is difficult for UAVs to provide continuous data collection. In this article, we study the problem of rechargeable-UAV-aided timely data collection in IoT networks, where the UAV collects status updates from multiple sensors and gets recharged from the charging stations (CSs) to keep its energy level above a threshold. To tradeoff the information freshness and energy consumption, we formulate a Markov decision process (MDP) with the objective of minimizing the weighted sum of the average total Age of Information and average recharging price. Under the dynamics and uncertainty of the environment, we propose a multitask transfer deep reinforcement learning method to jointly optimize the UAV ’ s flight trajectory, transmission scheduling, and battery recharging. To enable the application of the learned policy to new environments with similar settings and avoid starting from scratch, we develop a multitask network made up of common knowledge layers and task-specific knowledge layers. It specifically makes it possible for the transfer of common knowledge between environments with different network scales (e.g., different numbers of sensors/CSs) and/or topologies (e.g., different locations of sensors/CSs). Simulation results demonstrate that the proposed algorithm can adapt to new environments and achieve superior performance compared to the baseline algorithms.