Miracle-dz/UniFAR-FTUs huggingface dataset:
Observations of the Tasman Sea Internal Tide Beam

Low-mode internal tides, a dominant part of the internal wave spectrum, carry energy over large distances, yet the ultimate fate of this energy is unknown. Internal tides in the Tasman Sea are generated at Macquarie Ridge, south of New Zealand, and propagate northwest as a focused beam before impinging on the Tasmanian continental slope. In situ observations from the Tasman Sea capture synoptic measurements of the incident semidiurnal mode-1 internal-tide, which has an observed wavelength of 183 km and surface displacement of approximately 1 cm. Plane-wave fits to in situ and altimetric estimates of surface displacement agree to within a measurement uncertainty of 0.3 cm, which is the same order of magnitude as the nonstationary (not phase locked) mode-1 tide observed over a 40-day mooring deployment. Stationary energy flux, estimated from a plane-wave fit to the in situ observations, is directed toward Tasmania with a magnitude of 3.4 ± 1.4 kW m−1, consistent with a satellite estimate of 3.9 ± 2.2 kW m−1. Approximately 90% of the time-mean energy flux is due to the stationary tide. However, nonstationary velocity and pressure, which are typically 1/4 the amplitude of the stationary components, sometimes lead to instantaneous energy fluxes that are double or half of the stationary energy flux, overwhelming any spring–neap variability. Despite strong winds and intermittent near-inertial currents, the parameterized turbulent-kinetic-energy dissipation rate is small (i.e., 10−10 W kg−1) below the near surface and observations of mode-1 internal tide energy-flux convergence are indistinguishable from zero (i.e., the confidence intervals include zero), indicating little decay of the mode-1 internal tide within the Tasman Sea.
Spatial Distribution of Microbial Communities in the Alluvial Aquifer along the Oyodo River, Miyakonojo Basin, Japan

The hydrogeological properties of groundwater and behavior of nitrate attenuation in the nitrate-polluted alluvial aquifer, Miyakonojo Basin have been investigated in previous studies, but little knowledge is known about the spatially microbial communities especially associated with nitrate depletion. The objectives of the present study are to reveal the profile of microbial communities in the alluvial aquifer, Miyakonojo Basin, and the association with environmental variations based on cloning-library approach together with hydrogeochemical variables. The results showed that high bacterial diversity was characteristic of a large number of operational taxonomic units unique to the samples. The presence of some human-/livestock related bacteria was consistent with the distribution of high nitrate concentrations, which indicated an influence of hydrogeochemical variables on microbial composition. Methane-producing archaea and ammonia-oxidizing archaea were primar-ily found in the anoxic and oxic environments, respectively, reflected by the distribution of welded tuff. Additionally, heterotrophic and mixo-/autotrophic denitrifiers were ubiquitously distributed, but denitrification process only occurred under the anoxic environment. Microorganisms involved in the various metabolic processes were found to coexist in the same samples. Together, this study suggested that the description of microbial communities profile and associated putative metabolic processes could reflect the hydrogeochemical conditions of the alluvial aquifer, Miyakonojo Basin.
Pyrokinetics - A Python library to standardise
gyrokinetic analysis

Fusion energy offers the potential for a near limitless source of low-carbon energy and is often regarded as a solution for the world’s long-term energy needs. To realise such a scenario requires the design of high-performance fusion reactors capable of maintaining the extreme conditions necessary to enable fusion. Turbulence is typically the dominant source of transport in magnetically-confined fusion plasmas, accounting for the majority of the particle and heat losses. Gyrokinetic modelling aims to quantify the level of turbulent transport encountered in fusion reactors and can be used to understand the major drivers of turbulence. The realisation of fusion critically depends on understanding how to mitigate turbulent transport, and thus requires high levels of confidence in the predictive tools being employed. Many different gyrokinetic modelling codes are available and Pyrokinetics aims to standardise the analysis of such computationally demanding simulations
Navigating Innovation Highways: Unraveling the Entrepreneurial Culture's Role with Knowledge Management as the Mediator in Automotive Technology Innovations

The electric vehicle (e-vehicle) automotive sector in India has been undergoing substantial expansion and metamorphosis, propelled by reasons like governmental regulations, ecological considerations, and technological progress. The objective of this study is to determine the impact of entrepreneurial Culture on technical innovation in the e-vehicle automobile business, while also examining the role of knowledge management as a mediator. Employing a cross-sectional design, data for analysis were gathered using a questionnaire technique from managers and employees of six e-vehicle automobile industries in India. Despite distributing 500 questionnaires, the study received responses from 53 managers and 332 employees. Utilizing the PLS-SEM approach, the research reveals the positive influence of an entrepreneurial culture on technological innovation. Moreover, it highlights the partial mediation effect of knowledge management in the relationship between entrepreneurial culture and technology innovation. These findings carry substantial implications for businesses in the e-vehicle sector aiming to enhance their innovation capabilities by fostering an entrepreneurial culture and implementing effective knowledge management techniques.
Intra-annual Characteristics of the Relationship between the Surface Temperature–Based Urban Heat Island Intensity and the Local Climatic Zones

The population of the world is increasing. The artificial surface modifies the urban climate. One of the main environmental effects of the urban climate is the urban heat island (UHI). The UHI intensity is the difference between the urban and rural temperature (Oke, 1973). To determine the UHI intensity either air temperature and surface temperature can be used. The traditional UHI intensity is based on in-situ air temperature measurements (e.g. Klysik and Fortuniak, 1999; Unger et al., 2000; Pongrácz et al., 2016). To calculate the surface temperature based UHI (SUHI) radiation measurements of satellites can be used (e.g., Price, 1979; Dezső et al., 2005). The Department of Meteorology, Eötvös Loránd University, Budapest, Hungary has investigated urban climate for decades, especially the UHI and SUHI phenomenon (Pongrácz et al., 2010; Bartholy et al., 2016). To analyze the SUHI intensity the radiation and temperature data of NASA satellites were used. The structure of the city is a determining factor in the urban climate research. Stewart and Oke (2012) defined the Local Climate Zones (LCZs) system. The built-up density and the vegetation-cover areas affect the development of SUHI intensity. LCZ classes were used for the analyses of several European (e.g. Brousse et al., 2016) and Asian cities (e.g. Cai et el., 2016). In this paper, the SUHI intensity is analyzed using satellite data for Budapest, the capital city of Hungary, in the Eastern/Central Europe (Fig. 1). The most important objective is to evaluate the relationship between SUHI intensity and the LCZ map of Budapest. The relationship is studied on annual, seasonal, monthly and daily scales. We analyze the SUHI intensity differences between the different LCZ classes, compare selected grid cells from the same LCZ class, and evaluate a case study for the evolution of the spatial structure of SUHI intensity.
Translation surfaces generating with some partner curve

In this article, generating curves of translation surfaces are paired with some special curve pairs. With the results obtained from these pairings, the developable and minimal translation surfaces are characterized. In addition, the surface curvatures of the translation surface are obtained. For a better understanding of the results, examples are given and their drawings are made with the help of Mathematica.
Overlapping Community Detection Based on Weak Equiconcept

Community discovery refers to the process of searching for clusters in a network that are sparsely connected to other nodes and formed dense connections internally. In many real networks, some communities often overlap with each other, meaning that a node may belong to multiple communities simultaneously. Revealing these (overlapping) community structures is an important issue in complex network analysis, as it helps to better analyze the characteristics and organizational structure of the network. Community expansion methods are very important in the study of community detection problems. However, one of the key issues in developing effective community expansion methods is that the position of seed nodes greatly affects the performance of these algorithms, resulting in low robustness of these algorithms. Meanwhile, it is also difficult for them to provide high-quality results for community detection task. To solve the above problem, this paper proposes a seed selection method based on the weak equiconcepts in a network formal context, which integrates the attribute information of nodes during random walk to detect overlapping communities. Specifically, the weak equiconcepts are constructed by establishing a network formal context to obtain seed sets, and an improved PageRank clustering algorithm is used to expand these seed sets to better reveal the overlapping community structure in the network. Experiments show that seed selection is helpful to improving the performance of overlapping community detection algorithms.
Bidirectional Risk Spillovers between Chinese and Asian Stock Markets: A Dynamic Copula-EVT-CoVaR Approach

This study aims to investigate bidirectional risk spillovers between the Chinese and other Asian stock markets. To achieve this, we construct a dynamic Copula-EVT-CoVaR model based on 11 Asian stock indexes from 1 January 2007 to 31 December 2021. The findings show that, firstly, synchronicity exists between the Chinese stock market and other Asian stock markets, creating conditions for risk contagion. Secondly, the Chinese stock market exhibits a strong risk spillover to other Asian stock markets with time-varying and heterogeneous characteristics. Additionally, the risk spillover displays an asymmetry, indicating that the intensity of risk spillover from other Asian stock markets to the Chinese is weaker than that from the Chinese to other Asian stock markets. Finally, the Chinese stock market generated significant extreme risk spillovers to other Asian stock markets during the 2007–2009 global financial crisis, the European debt crisis, the 2015–2016 Chinese stock market crash, and the China–US trade war. However, during the COVID-19 pandemic, the risk spillover intensity of the Chinese stock market was weaker, and it acted as the recipient of risk from other Asian stock markets. The originality of this study is reflected in proposing a novel dynamic copula-EVT-CoVaR model and incorporating multiple crises into an analytical framework to examine bidirectional risk spillover effects. These findings can help Asian countries (regions) adopt effective supervision to deal with cross-border risk spillovers and assist Asian stock market investors in optimizing portfolio strategies.
Quality of Student Administration Services at SMK Negeri 8 Makassar

Student satisfaction is an important component of a formal service assessment plan. Thus, schools are required to always improve the quality of all components in the school. This study aims to determine the quality of student administration services and the factors that support and hinder student administration services at SMK Negeri 8 Makassar. The type of research used is descriptive qualitative. The informants in this study were the Head of Administration, Administration Staff, Teachers, Student Council Chairman, and Students. Data collection techniques are carried out through observation, interviews, and documentation. The data analysis techniques used in this study are data collection, data condensation, data presentation, and conclusions. The results showed that student administration services at SMK Negeri 8 Makassar were in the "quality" category, this can be seen from the results of research on each dimension, namely Direct evidence (Tangible) is complete. Reliability is already reliable. Responsiveness is responsive. Assurance is quite guaranteed, and Empathy is good.
Changement climatique au Mali : impact de la secheresse sur l'agriculture et stratégies d'adaptation

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Changement climatique au Mali : impact de la secheresse sur l’agriculture et stratégies d’adaptation Christelle Flore Tchoupé Makougoum
Prediction of Human Pharmacokinetics of E0703, a Novel Radioprotective Agent, Using Physiologically Based Pharmacokinetic Modeling and an Interspecies Extrapolation Approach

E0703, a new steroidal compound optimized from estradiol, significantly increased cell proliferation and the survival rate of KM mice and beagles after ionizing radiation. In this study, we characterize its preclinical pharmacokinetics (PK) and predict its human PK using a physiologically based pharmacokinetic (PBPK) model. The preclinical PK of E0703 was studied in mice and Rhesus monkeys. Asian human clearance (CL) values for E0703 were predicted from various allometric methods. The human PK profiles of E0703 (30 mg) were predicted by the PBPK model in Gastro Plus software 9.8 (SimulationsPlus, Lancaster, CA, USA). Furthermore, tissue distribution and the human PK profiles of different administration dosages and forms were predicted. The 0.002 L/h of CL and 0.005 L of Vss in mice were calculated and optimized from observed PK data. The plasma exposure of E0703 was availably predicted by the CL using the simple allometry (SA) method. The plasma concentration–time profiles of other dosages (20 and 40 mg) and two oral administrations (30 mg) were well-fitted to the observed values. In addition, the PK profile of target organs for E0703 exhibited a higher peak concentration (Cmax) and AUC than plasma. The developed E0703-PBPK model, which is precisely applicable to multiple species, benefits from further clinical development to predict PK in humans.
Pricing scheme design for vehicle-to-grid considering customers risk-aversive behaviors

The increasing penetration of plug-in electric vehicles (PEVs) brings both opportunities and challenges to the power grid. Vehicle-to-grid (V2G) proposes a promising solution that enhances grid resilience, reduces carbon emissions and saves facility investment. However, the actual motivation of drivers to participate in such programs is questionable: they may have to unexpectedly depart earlier than anticipated, thus risking that their vehicles are not adequately charged. As a consequence, they may refuse to accept the flexible charging plan even though it is attractive in the explicit cost. In this work, we formulate a bi-level model where EV charging station (EVCS) and drivers are considered as distinct entities, both having their own utility functions to maximize. We make extensive discussion on the stochasticity in actual cost of a session, including the energy cost and potential dissatisfaction, of choosing different charging modes. We challenging the widely-adopted assumption that all customers are risk-neutral, and characterize the behavioral differences among different customers with varying time value ν and risk preference factor ρ . Ac-cordingly, we propose a novel pricing/service scheme, denoted as double commitment (DC) to alleviate customers’ concerns on energy short when engaging V2G. The name of the scheme suggests that besides the single commitment (SC) on full charge by stated departure, it also allows users to specify a safety window within which EV charge for basic mobility is ensured. We demonstrate that by introducing double commitment, 15% more customers change their charging modes from ASAP to FLEX/V2G. As a consequence, EVCS gains flexibility to save energy costs, which is mainly realized from a reduction of demand charge. Hence, it also helps enhance grid reliablity and stability.
Archetypal kimberlite from the Maniitsoq region, southern West Greenland and analogy to South Africa

tle nodules have been known for decades from the northern part of the Archaean block and adjacent Proterozoic terranes in southern West Greenland (Fig. 1; Escher & Watterson 1973; Goff 1973; Scott 1981; Larsen & Rex 1992; Mitchell et al. 1999). Some of the dykes have proved to be diamondiferous (see Jensen et al. 2004a, b, for exploration results, diamond contents, and references). The c. 600 Ma old dykes were called ‘kimberlitic’ by Larsen & Rex (1992), but Mitchell et al. (1999) concluded that they were best referred to a ‘carbonatiteultramafic lamprophyre’ suite (aillikites or melnoites). Mitchell et al. (1999) further suggested that the West Greenland province represents “one of the few bona fide examples of ultramafic lamprophyre which contain diamonds”. Reports on indicator mineral assemblages (Jensen et al. 2004b) and diamond contents (e.g. Hudson Resources Inc. 2005) have re-opened the discussion on the classification of the dykes. The results of an investigation of the Majuagaa dyke (Nielsen & Jensen 2005) are summarised below, together with the preliminary results of a regional investigation of the groundmass minerals of the dykes. It is concluded that dykes in the Maniitsoq region are similar to archetypal, South African, on-craton, Type 1 kimberlites, and that all regions of the West Greenland province of ultramafic magmatism are favourable for diamond exploration.
Dynamic planning of edge sensing terminals in distribution network supporting distributed resources observable and controllable

With the advancement of low-carbon distribution networks, the heightened stochasticity introduced by a multitude of renewable energy sources in the power grid has significantly augmented the regulatory challenges faced by the power grid. Dispatching distributed resources emerges as an effective solution to this issue. However, these resources often lack observability and controllability, hindering their participation in power regulation services. To establish a reliable interaction between distributed resources and power grids, the deployment of numerous edge sensing terminals becomes essential, albeit incurring high costs. In light of this, our paper proposes a dynamic network planning method for edge sensing terminals based on node differentiation and resource observability criteria, aiming to facilitate real-time and dependable observation of distributed resources. Initially, the node weight, a metric to gauge the disparity among nodes, is computed, considering communication quality deviation, resource development synergy, and the distribution of distributed resources. Subsequently, an optimal configuration method is introduced, accounting for the terminal’s reliability under faults. Lastly, a method for dynamic terminal networking planning is presented, gradually reducing the depth of unobservable resources. An enhanced genetic algorithm is employed to address this challenge. This method was validated using an IEEE 33 node system and a 91 node actual system, demonstrating significant effectiveness in reducing terminal configuration costs.
Integrating Soil Spectral Library and PRISMA Data to Estimate Soil Organic Carbon in Crop Lands

The increasing demand for precise soil organic carbon (SOC) monitoring in croplands is crucial for food security (SDG 2), and has led to the exploration of fusing soil spectral libraries (SSLs) with hyperspectral sensing data for SOC estimation. However, the widespread adoption of SSL for SOC estimation faces challenges, particularly in developing nations, due to inconsistent calibration libraries and reliable estimation models. Furthermore, SSL rely on regular soil sample collection and spectral data recording using spectroradiometers, which is impractical in agricultural-predominant countries, such as India, with limited time for sample collection between crop rotations. To address this challenge, we developed synthesized SSL in laboratory conditions and integrated it with hyperspectral data using machine learning (ML) algorithms to bridge the gap between synthesized SSL and hyperspectral data for local-scale SOC mapping. This approach was tested by mapping SOC in Mysore, India, using spectroradiometer hyperspectral measurements and PRISMA sensor data. The proposed approach and synthesized SSL exhibited better performance prediction accuracies, ${R}^{{2}}$ of 0.92 and 0.79, and the RMSE values of 2.31 and 9.91 g/kg, respectively, for PRISMA and laboratory spectroscopy data. These results highlight the potential of synthesized SSL for SOC prediction in alluvial soils, leveraging local datasets, and hyperspectral data. Our future work will expand the synthesis approach to other study areas, particularly those with alluvial soil origins, further enhancing the applicability of this methodology for SOC estimation and aiding food security efforts.
Remaining Useful Life Prediction for Two-Phase Hybrid Deteriorating Lithium-Ion Batteries Using Wiener Process

Owing to operating condition switching and internal degradation mechanisms, the degradation processes of some lithium-ion batteries (LIBs) exhibit non-monotone and two-phase patterns, which are composed of a linear first phase and a nonlinear second phase. The existing Gamma process and Inverse Gaussian process methods are limited to modeling the monotone degradation data. Besides, traditional single-phase nonlinear models and two-phase linear models are insufficient to describe such a degradation process effectively. Therefore, degradation modeling and remaining useful life (RUL) prediction of the hybrid deteriorating LIBs is still a compelling practical issue. In this paper, a two-phase hybrid degradation model with a linear first phase and a nonlinear second phase is formulated based on the widely used Wiener process-based model. Taking into account the random effects caused by the unit heterogeneity and the uncertainty of the degradation state at the changing point, we obtain the analytical solutions of the lifetime estimation and RUL prediction under the concept of the first passage time (FPT). In addition, to conduct model parameter identification, the expectation maximization (EM) algorithm in conjunction with a profile log-likelihood function method are utilized for offline parameter estimation. Subsequently, the Bayesian rule is adopted to conduct the online parameter updating. Finally, the numerical and practical experiments are provided for verification and show that the proposed method could achieve high estimation accuracy for the RUL prediction of the two-phase hybrid deteriorating LIBs.