Miracle-dz/UniFAR-FTUs huggingface dataset:
An imperative role of studying existing battery datasets and algorithms for battery management system

Numerous portable technologies, including electric vehicles, cell phones, and laptops, are powered by batteries. The use of batteries is increasing due to the widespread usage of battery energy storage in the generation of renewable energy. This has also resulted in an increase in the number of negative incidents related to batteries and had a significant negative economic impact on industries. The shortcomings in the traditional monitoring of lithium-ion batteries have been overcome through the implementation of advanced technologies. However, few studies have discussed the use of distinct datasets in the implementation of an intelligent battery management system (BMS). This paper presents a discussion on the choice of dataset variables and applied algorithms for the implementation of effective BMS with artificial intelligence (AI) and machine learning (ML). The study analyzed the use of different datasets, including the National Aeronautics and Space Administration (NASA) battery dataset, to improve BMS. It found that the dataset variables must include the terminal voltage, terminal current, charge current, charge voltage, internal resistance, temperature, and cycle to calculate the state of health (SoH). In future, BMS hardware will be developed to obtain more precise results using AI and ML-based prediction models, utilizing the selected dataset characteristics and variables to achieve longer battery life.
In-Store Communications: Understanding the Mundane, the Bright Sides, and the Unexpected

This research examines how retailers convey messages to target customers and facilitate purchase decisions in physical settings. To establish a clear organizing framework for communications in physical settings, the current article examines both how and why retailers communicate with customers. Specifically, the authors address “how” questions from the perspective of whether messages are static or dynamic and “why” questions according to whether the communication is inspirational or informative.
Climatic controls on diffuse groundwater recharge in semiarid environments of the southwestern United States

Although there is no diffuse groundwater recharge at many semiarid sites, evidence for diffuse recharge exists at some locations where mean annual precipitation is much less than mean annual potential evapotranspiration , particularly where soils are coarse and rainfall variable is substantial. We investigate the climatic controls on diffuse recharge using a one‐dimensional, variably saturated flow model. The model is driven by a stochastic parameterization of climate that includes storm size distribution and seasonality of precipitation (P) and potential evapotranspiration (PET), constrained by data from 536 weather stations in the southwestern United States. Storm size distribution and seasonality determine the frequency and duration of intervals when P exceeds PET, which controls the flux of water past the root zone. For coarse soils, climates with large, infrequent storms yield recharge when / exceeds 0.4, compared with 0.7 for a typical climate. Recharge through fine soils is insensitive to storm size and occurs at / > 0.8. Seasonality has a stronger influence on recharge than storm size distribution, and the effects are similar for coarse and fine soils. Recharge is relatively insensitive to rainfall seasonality. In contrast, the typical PET annual cycle lowers / of the recharge threshold by 0.3. The relative timing of P and PET maxima is critical: Recharge occurs at / values that are lower by 0.2 when the rainy season occurs during winter instead of summer. Over the range of climate and soils examined, / values at the recharge threshold varied from 0.2 to 0.7. Therefore and alone are insufficient to predict where recharge will occur.
Modèle hybride pour simuler l’écoulement à travers un birotor éolien caréné et sa validation expérimentale

La these resume la recherche sur le fonctionnement et l’ecoulement autour d’une eolienne carene a deux rotors. Le placement d’une turbine a l’entree d’un canal divergent permet d’augmenter le debit massique a travers le rotor. Afin de mieux tirer parti de l’augmentation de la vitesse du vent a l’entree du diffuseur, il a ete decide d’examiner la possibilite de placer un deuxieme rotor, tournant dans le sens oppose, dans cette zone.L'etude menee combinait plusieurs voies de recherche differentes, y compris les methodes de la mecanique des fluides numerique (CFD) et des etudes experimentales. Cela a permis de mieux comprendre la nature de l'ecoulement et du fonctionnement d'une eolienne a deux rotors. Des recherches experimentales ont ete menees dans la soufflerie de l’Institut de Turbomachinerie de l’Ecole Polytechnique de Lodz (Pologne). Une serie de mesures de systemes d'eoliennes divers, avec et sans carenage, a un et deux rotors, a ete realisee. Les resultats recueillis ont permis de confirmer que le carenage pouvait augmenter considerablement (meme deux fois) l'efficacite du rotor. Cependant, les forces aerodynamiques et la vitesse de rotation augmentent egalement. Cet inconvenient peut etre partiellement resolu en utilisant un deuxieme rotor et en repartissant les charges aerodynamiques sur deux etages de turbine.Une partie importante de l'etude etait les simulations numeriques. Ils ont permis de preciser la nature et les parametres de l'ecoulement et d'estimer leur impact sur les performances de l'eolienne. Deux modeles numeriques differents ont ete developpes:•Modele rotor complet (anglais : Fully-resolved Rotor Model, FRM): modele URANS dans ANSYS CFX, base sur la discretisation de la geometrie complete du rotor; ce modele a ete utilise pour l'analyse de l’ecoulement,•Modele hybride CFD-BET (theorie de l’element de pâle): modele RANS dans ANSYS Fluent, dans lequel le rotor est represente par les termes source dans les equations de Navier-Stokes, determines par un code interne; ce modele a ete utilise pour evaluer les performances de differentes configurations d'eoliennes.Au cours de la recherche, une correction empirique interne de la perte d’extremite de la pâle (anglais : tip loss correction) a ete proposee, en tenant compte de l’influence du diffuseur. L’etude realisee a permis d’observer, entre autres, que le deplacement du rotor en aval vers la sortie du diffuseur pouvait entrainer une reduction de la vitesse du vent a travers le rotor en amont, place a l’entree du diffuseur, et une diminution de la puissance globale du systeme.
Statistical equivalence in gene expression studies.

The goal of this thesis is to develop methods that enable researchers to identify genes with a pre-specified profile in gene expression studies. The motivation for these methods is a gene expression study performed at the University of Adelaide to identify the genes associated with pluripotency in mouse embryonic stem cells. The method developed, gene profiling, utilises intersection-union tests that combine tests both for equivalent and differential expression. The theoretical basis of gene profiling and its application to the stem cell data are discussed in the thesis, as well as a comparison of gene profiling to alternative methods described in the literature for identifying genes corresponding to a pre-specified profile. In the second part of this thesis, ‘strength of evidence’ measures for equivalence and gene profiling are developed. A P -value for equivalence is shown to have undesirable properties and a posterior probability of equivalence is proposed. The calculation of the posterior probabilities for equivalence using a hierarchical model is described and extended to gene profiling. A method to calculate q-values from the posterior probabilities is described. The resultant q-values are compared to the posterior probabilities.
Space time adaptive processing based on sparse recovery and clutter reconstructing

For an airborne-phased array radar system, space-time adaptive processing (STAP) is supposed to be a crucial technique for improving its target detection performance in a strong clutter background. Here, the authors consider the extreme heterogeneous case, i.e. the number of available training samples is limited to one. With only one training sample, the sparse recovery (SR) technique is utilized to estimate the clutter patches in the angular-Doppler plane, i.e. the pair of Doppler frequency and spatial frequency corresponding to the grid in angular-Doppler plane is determined. Based on the observation that some clutter components may be missed for one secondary data sample, the clutter covariance matrix (CCM) is estimated through reconstructing some missed clutter components by utilising the symmetric property of clutter return. From the simulation results, the proposed approach can achieve great performance of clutter suppression with only one training sample compared with conventional SR-based STAP algorithms.
Infestation of spontaneous species in monocrop coffee or intercropped, under agroecological system.

This study aimed to compare weed infestation in coffee crops under two different crop management: traditional and mixed cropping with banana. It was evaluated the composition, level of occurrence, diversity of species and similarity of areas in terms of infestation by spontaneous species. The experiment was installed under field conditions at the Escola Municipal Rural Benedita de Oliveira Feijó, at Ivinhema city in Mato Grosso do Sul state, Brazil. The experiment was installed in 2009 and it was evaluated the occurrence of spontaneous species three years after on both management systems. The occurrence and composition of the flora was evaluated in both systems in the summer 2012, being quantified the abundance, frequency, dominance and the importance index for each plant species. Plant diversity inside each system was estimated by Simpson and Shannon-Weiner index. It was also used the binary assimetric similarity coefficient of Jaccard. Absolute infestation and spontaneous species differed between cropping managements. The incidence of spontaneous species in the mixed cropping coffee/bananas corresponded to 17% and 6.5% to traditional cropping, respectively for the number of plants and weed dry matter. Mixed cropping showed be a good strategy to weed control in coffee crop.
Family structure and entrepreneurship: Evidence from Swedish siblings

ABSTRACT Family background matters for entrepreneurship, but why do siblings differ in their propensity to become entrepreneurs and the type of ventures they pursue? I draw on family socialization and resource allocation theories to develop hypotheses about the differential effects of family structure – comprising birth order, family size, and sibling gender – on (growth-oriented) entrepreneurship. Using firm incorporation as a marker of growth orientation, I test these hypotheses in a sample of Swedish siblings. Relative to older siblings, later born children are more likely to become unincorporated entrepreneurs, partly because they occupy family niches corresponding to lower educational attainment and higher labour market frictions. Moreover, children in very large families are less likely to pursue incorporation, with stronger effects for men and earlier born children, in line with their limited ability to develop self-efficacy due to resource dilution. Growing up with an opposite-gender sibling does not influence entrepreneurship, indicating that sibling sex composition may not foster stronger gender norms or sex-typing in this domain in Sweden. This study integrates existing findings and offers novel insights, broadening our understanding of family background in entrepreneurship.
Quantitative imaging biomarkers of coronary plaque morphology: insights from EVAPORATE

Aims Residual cardiovascular risk persists despite statin therapy. In REDUCE-IT, icosapent ethyl (IPE) reduced total events, but the mechanisms of benefit are not fully understood. EVAPORATE evaluated the effects of IPE on plaque characteristics by coronary computed tomography angiography (CCTA). Given the conclusion that the IPE-treated patients demonstrate that plaque burden decreases has already been published in the primary study analysis, we aimed to demonstrate whether the use of an analytic technique defined and validated in histological terms could extend the primary study in terms of whether such changes could be reliably seen in less time on drug, at the individual (rather than only at the cohort) level, or both, as neither of these were established by the primary study result. Methods and Results EVAPORATE randomized the patients to IPE 4 g/day or placebo. Plaque morphology, including lipid-rich necrotic core (LRNC), fibrous cap thickness, and intraplaque hemorrhage (IPH), was assessed using the ElucidVivo® (Elucid Bioimaging Inc.) on CCTA. The changes in plaque morphology between the treatment groups were analyzed. A neural network to predict treatment assignment was used to infer patient representation that encodes significant morphological changes. Fifty-five patients completed the 18-month visit in EVAPORATE with interpretable images at each of the three time points. The decrease of LRNC between the patients on IPE vs. placebo at 9 months (reduction of 2 mm3 vs. an increase of 41 mm3, p = 0.008), widening at 18 months (6 mm3 vs. 58 mm3 increase, p = 0.015) were observed. While not statistically significant on a univariable basis, reductions in wall thickness and increases in cap thickness motivated multivariable modeling on an individual patient basis. The per-patient response assessment was possible using a multivariable model of lipid-rich phenotype at the 9-month follow-up, p < 0.01 (sustained at 18 months), generalizing well to a validation cohort. Conclusion Plaques in the IPE-treated patients acquired more characteristics of stability. Reliable assessment using histologically validated analysis of individual response is possible at 9 months, with sustained stabilization at 18 months, providing a quantitative basis to elucidate drug mechanism and assess individual patient response.
REVIVE: Regional Visual Representation Matters in Knowledge-Based Visual Question Answering (Supplementary Materials)

Multiple Candidates. We retrieve multiple implicit knowledge candidates for each sample during training and inference stages to improve the robustness of answer generation. Specifically, we follow PICa [6], which proposes to use multi-query ensemble, i.e., they prompt the GPT-3 [1] for k1 times and choose the one with the highest probability as final answer prediction. Compared with PICa’s multi-query ensemble approach, we take all these k1 predictions from GPT-3 [1] as implicit knowledge candidates. Note that for each candidate, we also prompt the GPT-3 model to obtain its corresponding explanation. In our experiments, we just retrieve 5 (i.e., k1 = 5) implicit knowledge candidates and corresponding explanations.
Older Adults and the Health Transition in Agincourt, Rural South Africa: New Understanding, Growing Complexity

The population living in less developed regions of the world is growing rapidly, with the fastest growth projected for Africa. With declining mortality and fertility, the age structures of developing countries have aged. Subject to the same mortality and fertility declines, the percentage of people over age 50 will continue to rise, with large increases in the numbers of older people (Heligman, Chen, and Babkol, 1993). United Nations projections for South Africa indicate that the percentage of the population over age 60 will more than double from 6 percent in 1999 to 14 percent in 2050, estimates that are lower than those computed for less developed regions as a whole (United Nations, 1999). While mortality levels are projected to decrease, the absolute number of deaths in the less developed regions will increase, with a shift to an older age distribution. As the population structure ages, so the age structure of deaths changes to one in which the greatest proportion of deaths is at the oldest ages. This is due to the fact that a greater proportion of the population has reached older ages as well as the lower probability of dying at younger ages. Such change in population age structure shifts the mortality profile from one dominated by the infectious diseases more common in children, toward one dominated by the noncommunicable diseases that affect older adults and the elderly. Despite the relatively young distribution of African mortality compared with other less developed regions, the number of deaths in Africa has increased more at the older ages; this reflects both
Development and validation of a QuEChERS-LC-MS/MS method for determination of multiple mycotoxins in maize and sorghum from Botswana

Climatic conditions such as drought, high temperatures, and pre-harvest rainfalls promote the occurrence of mycotoxins in grains. Contamination of staple food sources such as maize and sorghum means that many populations are at risk of being poisoned by mycotoxins. Hence the need for sensitive methods for their simultaneous analysis. Herein, a quick, easy, cheap, effective, rugged, and safe liquid chromatography tandem mass spectrometry (QuEChERS-LC-MS/MS) method for the simultaneous determination of ten mycotoxins in maize and sorghum is presented. The QuEChERS extraction procedure was optimized to maximize extraction recovery and minimize matrix effects while using relatively small quantities of organic solvents and acids. This method was validated according to Commission Implementing Regulation (EU) 2021/808, Commission Regulation (EC) No 1881/2006, and Regulation (EC) no. 401/2006. The developed method met the specified requirements. Recoveries of 80.77% to 109.83% and CVs below 15% were obtained. The correlation coefficient values (R2) were all above 0.98, and low limits of quantification ranging from 0.53 to 89.28 µg/Kg were recorded. The method was applied to 10 maize and 10 sorghum samples collected from markets in Botswana. Half of the samples had detectable mycotoxins, Aflatoxins, Fumonisins, T2-toxin, HT2-toxin, and Zearalenone. Two maize samples had levels of aflatoxin B1 above the maximum permitted level (2.55, 4.07 µg/Kg). These findings point to the necessity of more stringent monitoring of mycotoxins, particularly AFB1 in maize, as well as the value of regular assessment using LC-MS/MS.
CODER: An efficient framework for improving retrieval through COntextualized Document Embedding Reranking

We present a framework for improving the performance of a wide class of retrieval models at minimal computational cost. It utilizes pre-computed document representations extracted by a base dense retrieval method and involves training a model to jointly score a large set of retrieved candidate documents for each query, while potentially transforming on the ﬂy the representation of each document in the context of the other candidates as well as the query itself. When scoring a document representation based on its similarity to a query, the model is thus aware of the representation of its “peer” documents. We show that our approach leads to substantial improvement in retrieval performance over scoring candidate documents in isolation from one another, as in a pair-wise training setting. Crucially, unlike term-interaction rerankers based on BERT-like encoders, it incurs a negligible computational overhead on top of any ﬁrst-stage method at run time, allowing it to be easily combined with any state-of-the-art dense retrieval method. Finally, concurrently considering a set of candidate documents for a given query enables additional valuable capabilities in retrieval, such as score calibration and mitigating societal biases in ranking.
Predictive Control of Common-Ground Five-Level PV Inverter Without Weighting Factors and Reduced Computational Burden

Mitigation of the leakage current components represents a critical issue in transformerless photovoltaic (PV) inverters. Recently, PV inverters with inherent common-ground (CG) connection are becoming promising proposals for nearly total elimination of leakage current components. However, developing multilevel output while injecting grid currents with high quality is a challenging task for classical control schemes. This article presents a reduced computational burden weighting factorless finite-control-set model-predictive control (WFL-FCSMPC) for the CG five-level single-phase switched capacitor cells inverter-based PV systems. The proposed reduced computational burden WFL-FCSMPC avoids the cascaded control loops of classical controllers. Thence, the problems related to adjusting weighting factors of standard finite control-set model-predictive control (FCSMPC) are eliminated by dividing the control objectives into the desired cost functions. Moreover, high computational burdens in classical FCSMPC methods are considerably reduced using the proposed WFL-FCSMPC, especially at a high number of levels. Therefore, robust and simplified design and implementation are obtained by applying the proposed WFL-FCSMPC while long tuning procedures of weighting factors are avoided. Simulation and experimental results are provided for verifying the superior performance of the proposed WFL-FCSMPC over standard FCSMPC and linear controllers.
An In-Situ Dynamic Quantization With 3D Stacking Synaptic Memory for Power-Aware Neuromorphic Architecture

Spiking Neural Networks (SNNs) show their potential for lightweight low-power inferences because they mimic the functionality of the biological brain. However, one of the major challenges of SNNs like other neural networks is memory-wall and power-wall when accessing data (synaptic weights) from memory. It limits the potential of spiking neural networks implemented on edge devices. In this paper, we present a novel spiking computing hardware architecture named NASH-3DM using 3D-IC-based stacking memory with power supply awareness to effectively decrease power consumption for AI-enabled edge devices. Instead of storing one or multiple weights in a single memory word, we split them into small subsets and allocate each subset into a separate memory in every stacking layer. With the natural separation of stack layers, our system can activate and deactivate each layer separately. Therefore, it can offer in-situ (online, post-manufacture, and without interruption) dynamic quantization with multiple operating modes. With the CMOS 45nm technology, our energy per synaptic operation for MNIST classification can reduce by 36.67% while having 0.93%-1.14% accuracy loss at 5-bit quantization. The energy per synaptic operation reduction for the CIFAR10 dataset is 36.68% when switching from the 16-bit active operation to the in-situ 10-bit one with an accuracy loss of 5.69%.