Miracle-dz/UniFAR-FTUs huggingface dataset:
Combining Reduced-Order Model With Data-Driven Model for Parameter Estimation of Lithium-Ion Battery

The parameters of a lithium-ion battery are important to construct an effective battery management system. Parameter estimation assisted by the pseudo-two-dimensional (P2D) model is much more cost-effective than direct measurement methods. However, this is a nontrivial task, because the simulation of the P2D model is time-consuming. Alternatively, surrogate models such as reduced-order/data-driven models are often used to accelerate the parameter estimation process. Each category of surrogate models has its own strengths and weaknesses. Traditionally, reduced-order models run faster than data-driven models, while data-driven models are more accurate than reduced-order models. To leverage the complementary advantages of these two kinds of surrogate models, we make an interesting attempt to combine them compactly, thus proposing a two-phase surrogate model-assisted parameter estimation algorithm (TPSMA-PEAL). In the first phase, a fast reduced-order model is designed for parameter prescreening. In the second phase, a high-fidelity data-driven model is developed for fine estimation. In TPSMA-PEAL, except the time-consuming simulation, the other two challenges (i.e., the overfitting problem and the low observability of some parameters) are also considered from the perspective of optimization. Note that TPSMA-PEAL takes advantage of differential evolution and parameter sensitivity analysis to address them. Simulations and experiments verify that TPSMA-PEAL is efficient and accurate.
Influence of exogenous abscisic acid on morpho-physiological and yield of maize (Zea mays L.) under drought stress

Abscisic acid (ABA) is naturally occurring plant hormone, its also known stress hormone, that act the plant responses to abiotic stresses, especially drought. Maize production losses due to drought prominently affect economics and livelihoods of millions of peoples. The current investigation the role of ABA in drought stress tolerance of maize. The influence of drought stress and foliar spray of abscisic acid diffent concentration (25, 50 ,75 and 100 µM) were analysed on morphological, physiological, and biochemical parameters. The present results revealed a most effective to increased after drought stress imposed with 75 µM ABA treated plants. Exogenous abscisic acid acts as a scavenger of ROS for mitigating the injury on cell membranes under drought were observed in the opening of stomata. Histochemical detection of more accumulation ROS (H2O2 and O2• –) was detected in drought stress shoot compared to other ABA treated and respective control. Fourier Infrared Spectroscopic (IR) study, ABA treated leaves indicated the presence of different functional groups. This study shows that can provide vital insights into maize leaves drought responses and could be beneficial in identifying novel drought tolerance characters. Drought and exogenous abscisic acid treatment increased the endogenous abscisic acid level, specifically at 75 µM concentration. The exogenous abscisic acid application effectively ameliorates the adverse effect of drought stress to improve the drought resistance. In concluded, the level of 75 µM concentration ABA was better growth charaterstics, biochmeical alterations and yiled under drought stress.
The Consumption of a Synbiotic Does Not Affect the Immune, Inflammatory, and Sympathovagal Parameters in Athletes and Sedentary Individuals: A Triple-Blinded, Randomized, Place-bo-Controlled Pilot Study

This investigation aimed to identify the effect of a synbiotic in athletes and sedentary people, and their potential varying responses regarding the immune system, autonomic regulation and body composition. Twenty-seven participants were involved in the protocol: 14 sedentary and 13 semi-professional soccer players. Both groups were randomly divided into an experimental and control group. A synbiotic (Gasteel Plus®, Heel España S.A.U.) comprising a blend of probiotic strains, including Bifidobacterium lactis CBP-001010, Lactobacillus rhamnosus CNCM I-4036, and Bifidobacterium longum ES1, was administered to the experimental group, and a placebo was given to the control group for 30 days. Heart rate variability, body composition, and immune/inflammatory cytokines were determined. Statistically significant differences were observed between sedentary individuals and athletes in heart rate variability but not between the experimental and control groups. A difference between the athletic and sedentary group is observed with the influence of training on the effects of the synbiotic on the levels of fat mass and body-fold sum. No significant differences were shown in cytokines after the protocol study. No changes occur with the synbiotic treatment between the athlete and sedentary groups, while no negative effect was produced. Further research will be necessary to see chronic effects in the analyzed biomarkers.
Activity and Stress Estimation Based on OpenPose and Electrocardiogram for User-Focused Level-4-Vehicles

Increasing vehicle automation changes the role of humans in the car, which imposes new requirements on the design of in-vehicle software and hardware for flexible interior concepts. An option to meet these requirements is the development of user-focused automation based on combined user and context monitoring in real time. The system behavior may be dynamically adapted by adjusting the driving style or the interior lighting. Here, we present a hierarchical approach on the basis of semantically motivated low-level features for activity and stress recognition based on OpenPose and electrocardiogram data. A driving simulator study with 29 participants was conducted to determine the potential of the approach. Participants had to accomplish different tasks: manual driving (MD); mobile office work with varying task load levels (high task load: MO-HT, low task load: MO-LT); and relaxing (REL) during automated driving. The validation revealed that our model is able to correctly distinguish between different activities using only a set of primitive features (average precision: driving: 76% and mobile office work: 93%, relaxing: 86%). Furthermore, we evaluated a person-independent and a person-specific approach for stress detection and found that both strategies show similar trends in accordance with our predictions (person-independent: stress detected in MO-HT: 22%, MO-LT: 18%, MD: 18%, REL: 15%; person-specific: stress detected in MO-HT: 79%, MO-LT: 72%, MD: 65%, and REL: 50%). These results demonstrate the efficacy of using a lightweight semantic approach for activity recognition and stress detection as basis for user-focused vehicle automation.
Exploring the attitude of youth towards adventure tourism as a driver for post-pandemic era tourism experiences

ABSTRACT The return to normal conditions after the pandemic requires social readjustment through recreational activities in a controllable environment. Adventure tourism is one of the feasible options. This study develops a model that will allow young people to regain their internal balance by exploring cumulative positive experiences adapted to their needs. A set of indicators are used in the model to measure people’s attitudes towards tourist destinations. The factors that describe adventure tourism have been identified by Hofstede’s theory of the cultural dimension from interviews with people belonging to the millennial generation. Quantitative research was conducted among this generation from 12 counties of Romania. Following the modelling, they were identified as the main factors of the practice of AT: stress decreasing, self-awareness, search for new experiences and social interaction. The use of the model based on structural equations allows the identification of personalized tourist destinations to be used in the industry in order to revitalize tourism activity and rebalance the socio-economic perspective. Examining the interrelationship of factors contributes to a better understanding of the concept of adventure tourism and provides a relevant choice for post-pandemic tourism experiences.
Model Penerjemah Bahasa Isyarat Indonesia (BISINDO) Menggunakan Pendekatan Transfer Learning

Sistem Bahasa Isyarat Indonesia (SIBI) yang berasal dari bahasa isyarat Amerika (American Sign Language) dan lebih banyak dipakai pada situasi formal tidak terlalu familiar bagi insan tuli atau difabel rungu di Indonesia karena mereka umumnya menggunakan Bahasa Isyarat Indonesia (Bisindo). Sejak 1975 perwakilan Tuli melalui organisasi kemasyarakatan Gerakan untuk Kesejahteraan Tunarungu Indonesia (Gerkatin) telah meminta pemerintah untuk mengakui Bisindo sebagai bahasa pengantar resmi di Sekolah Luar Biasa namun upaya ini hingga kini belum berhasil. Untuk membantu meningkatkan aksesibilitas Tuli dengan menambah jumlah penerjemah serta memperluas pemahaman Bisindo di masyarakat luas, penelitian ini berupaya membangun mesin penerjemah bahasa isyarat menggunakan teknik machine learning dengan algoritma Convolutional Neural Network (CNN). Karena bukan merupakan bahasa isyarat format, ketersediaan dataset Bisindo di Internet terbatas. Metode transfer learning, yaitu dengan memanfaatkan model yang dilatih dengan dataset ASL kemudian disesuaikan untuk melakukan pekerjaan yang sama pada menggunakan dataset Bisindo digunakan dalam penelitian ini untuk mengatasi masalah keterbatasan dataset. Karena perbedaan karakteristik bahasa isyarat dan gestur dari masing-masing bahasa isyarat, pemindahan knowledge khususnya learning parameter dari Model ASL tidak dapat meningkatkan performa Model Bisindo dalam memprediksi seluruh huruf pada alfabet Bisindo sehingga model hasil transfer learning hanya mampu memprediksi huruf-huruf Bisindo yang memiliki kemiripan dengan ASL.
Optimization of Cladding Diameter for Refractive Index Sensing in Tilted Fiber Bragg Gratings

This work presents an experimental investigation of the effect of chemical etching on the refractive index (RI) sensitivity of tilted fiber Bragg gratings (TFBGs). Hydrofluoric acid (HF) was used stepwise in order to reduce the optical fiber diameter from 125 µm to 13 µm. After each etching step, TFBGs were calibrated using two ranges of RI solutions: the first one with high RI variation (from 1.33679 RIU to 1.37078 RIU) and the second with low RI variation (from 1.34722 RIU to 1.34873 RIU). RI sensitivity was analyzed in terms of wavelength shift and intensity change of the grating resonances. The highest amplitude sensitivities obtained are 1008 dB/RIU for the high RI range and 8160 dB/RIU for the low RI range, corresponding to the unetched TFBG. The highest wavelength sensitivities are 38.8 nm/RIU for a fiber diameter of 100 µm for the high RI range, and 156 nm/RIU for a diameter of 40 µm for the small RI range. In addition, the effect of the etching process on the spectral intensity of the cladding modes, their wavelength separation and sensor linearity (R2) were studied as well. As a result, an optimization of the etching process is provided, so that the best trade-off between sensitivity, intensity level, and fiber thickness can be obtained.
Knowledge Sharing Enabled Multirobot Collaboration for Preventive Maintenance in Mixed Model Assembly

Intelligent equipment and flexible production lines are at the cores of smart manufacturing. Meanwhile, Internet of Things and Artificial Intelligence have provided new solutions for the intelligent equipment management and maintenance in mixed model assembly (MMA). This article focuses on knowledge-driven techniques, and it proposes a knowledge sharing-enabled multirobot collaboration (KS-enabled MRC) strategy for preventive maintenance of robots in MMA. First, a formal semantic environment for MMA is constructed by way of ontology-enabled semantic modeling. Then,task-related action primitives and ontology-based robot skill bases are established according to robot capability and task environment. Finally, the Wu-Palmer similarity metric and first-order logic are leveraged to match and reason new tasks according to the semantic rules, and a knowledge sharing and update mechanism are developed for this application. Experimental results demonstrate that the proposed KS-enabled MRC can reduce unscheduled downtime and assist in achieving a load balance for robots in MMA. The studied MRC can potentially avoid severe equipment degradation, thus acting as a preventive maintenance paradigm of complex equipment. Furthermore, it is applicable across different platforms and exhibits high deployment efficiency without intense programming requirements.
An Energy-Efficient Domain-Specific Architecture for Regular Expressions

Regular Expressions (REs) are a computational kernel widely used for finding patterns in data in compute-intensive tasks such as genomic markers research, signature-based detection, and database query. Although flexible on the set of searched REs, software-based solutions cannot fulfill latency or throughput requirements to analyze massive data volumes at a given power budget. For this reason, many approaches exploit hardware accelerators as an offloading engine for REs matching. Indeed, various solutions rely on FPGA reconfigurability to embed automata into the reconfigurable fabric. However, this approach leads to time-consuming updates of the REs to search. This work exploits REs as sequences of basic instructions and builds a Domain-Specific Architecture (DSA), called TiReX, for RE matching on FPGAs. Our approach enables the user to change the desired RE at run-time, providing software programmability, flexibility, and specialized hardware mechanisms. Our DSA delivers performance in line with other state-of-the-art hardware approaches, while providing remarkable flexibility and we underline the importance of energy efficiency for these computations. We compared with multiple state-of-the-art software obtaining remarkable performance while achieving noticeable results with a better energy efficiency that ranges from 3× to 490× with our multi-core.
Relationship among production traits, somatic cell score and temperature–humidity index in the Italian Mediterranean Buffalo

Abstract The temperature–humidity index (THI) has been commonly used to analyse heat stress in dairy cattle, but little is known about its effects on buffaloes. In this study, daily milk yield (MY), fat percentage (FP), protein percentage (PP) and somatic cell count (SCC) data from 808 buffalo cows plus environmental temperature and relative humidity were used to investigate the consequence of heat stress. Two mixed models were used to evaluate the impact of THI on MY, FP, PP and log transformed SCC (SCS). The effect of THI was significant for PP, FP and SCS, whereas its interaction with parity was statistically significant for PP and SCS. The relationship between PP and FP and THI was positive but of different magnitude according to the parity. When THI was below 62, an unfavourable effect was observed, especially in primiparous buffalo cows. A significant interaction between SCS and THI across parities was also observed. The effect of THI on MY across parities was not definite but overall a favourable relationship was observed. Our findings depict a susceptibility of buffaloes to low values of THI, suggesting an optimal THI range for water buffaloes between 59 and 63, although some deleterious effects were observed in primiparous buffaloes at THI values lower than 62. Additional investigations are needed to better elucidate the influence of THI on buffalo species. HIGHLIGHTS The overall effect of THI on buffalo diverges from what commonly observed in dairy cattle Cold stress affects milk and udder health in buffaloes The effect of THI on buffaloes’ performance depends on parity, with a larger susceptibility in primiparous than pluriparous buffalo cows Udder health in buffaloes, evaluated using somatic cell count, is also affected by THI
Climate Change Impacts on Irrigated Crops in Cambodia

Increasing heat-stress conditions, rising evaporative demand and shifting rainfall patterns may have multifaceted impacts on Cambodia ’ s agricultural systems, including vegetable production. Concurrently, domestic vegetable supply is highly seasonal and inadequate to meet the domestic food demand, which consequently poses risks to food security locally, particularly in rural areas. This study assesses the impact of climate change on the yields and crop water productivity (CWP) of tomato, pak choi and yard-long bean cultivated year-round under different irrigated conditions (drip, furrow and net irrigation) in Siem Reap, Cambodia. The findings of this study show a similar annual precipitation decline (-23%) when comparing the 2017 – 2040 and 2070 – 2099 periods for both Representative Concentration Pathways (RCPs 4.5 and 8.5), though with significant seasonal differences between the two climate scenarios. Increasing water and heat-stress conditions are expected to have adverse impacts on tomato plants compared to pak choi and yard-long bean, which have a much higher heat tolerance. Differing yield trends are expected depending on the transplanting/sowing date, irrigation method and RCP. In tomato, for example, a -55% yield loss is projected by the end-century (2070 – 2099) when transplanting in January, whereas a + 37% yield increase is expected between November and December over the same period. In addition, pak choi yield enhancements of up to + 30% are projected if sowing in May under RCP 8.5 for both drip and net irrigation conditions. Similarly, higher yard-long bean yields are simulated under RCP 8.5 ( + 29%) compared to RCP 4.5 ( + 11%) for the average of all sowing dates (January to December) and irrigation methods (drip, furrow and net irrigation). In sum, the findings of this work are relevant for evidence-based decision-making and the development of projects, policies and programmes increasingly informed by simulation results from bundling climate-crop approaches to transform agriculture in response to climate change.
A Hybrid MPI/OpenMP Parallelization Scheme Based on Nested FDTD for Parametric Decay Instability

Parametric decay instability (PDI) generated in milliseconds is an important physical phenomenon in ionospheric heating. Usually, numerical simulations are used to study PDI mechanisms. They can intuitively investigate the generation and development process of PDI, which is necessary in experimental studies. When simulating the PDI phenomenon through the explicit finite-difference time-domain (FDTD), the spatial scale spans from kilometers to centimeters, and the time scale needs to meet the Courant–Friedrichs–Lewy condition. Simulating the PDI phenomenon is time-consuming and difficult due to the high spatial resolution and strict restriction on the discrete time step. Although a nested mesh technique can boost the computational efficiency, the application of a parallel strategy is imperative to further improve it. In this study, we present a hybrid Message Passing Interface (MPI)/OpenMP parallelization scheme to solve the above-mentioned problems. This scheme can achieve an adaptive calculation and automatic allocation of MPI tasks and OpenMP threads, proving its flexibility and portability. Under the EISCAT background parameters, the PDI phenomenon was simulated. The results of the wave mode conversion and intense localized turbulence were identical to those of the serial program. Furthermore, a new simulation example and the effect of the cavity depth on electrostatic waves and negative ion density cavity were investigated. By utilizing the proposed parallelization scheme, the simulation time can be reduced from 70 h for the serial program to 3.6 h.
Leadership in the eye of the beholder: stakeholder’s perspectives on principals as leaders improving schools in challenging contexts in South Africa

ABSTRACT The article explored the characteristics of principals as leaders in schools in deprived socio-economic contexts in South Africa. The qualitative research was conducted in four provinces; four schools per province were purposefully sampled, and in each school, individual interviews were conducted with the principal, one member of the school management team, one senior teacher and a focus group with grade 12 learners. The research concluded that leadership characteristics such as motivation and creating a vision are important. Many principals were described as strict but they were taking care of specifically the learners in very difficult situations and that makes the difference that the schools in difficult socio-economic contexts are also able to perform. Principals are able to lead schools to improve the academic results by focusing on a people-orientated leadership approach with strong relationships between leaders and followers and intrinsic motivation as the key factors.
A STOCHASTIC OIL PRICE MODEL FOR OPTIMAL HEDGING AND RISK MANAGEMENT

In this paper, we develop a stochastic model for future monthly spot prices of the most important crude oils and refined products. The model is easy to calibrate to both historical data and views of a user even in the presence of negative prices which have been observed recently. This makes it particularly useful for risk management and design of optimal hedging strategies in incomplete market situations where perfect hedging may be impossible or prohibitively expensive to implement. We illustrate the model with optimization of hedging strategies for refinery margins in illiquid markets using a portfolio of 12 most liquid derivative contracts with 12 maturities traded on New York Mercantile Exchange (NYMEX) and Intercontinental Exchange (ICE).
Lietuvos policijos pareigūnų motyvacinių veiksnių analizė

Straipsnyje nagrinėjamas policijos pareigūnų motyvacijos dirbti skatinimo sistemos efektyvumas. Remiantis mokslinės literatūros, teisės aktų ir atlikto sociologinio tyrimo analize, analizuojamos pareigūnų veiklą motyvacinių veiksnių – darbo organizavimo, darbo sąlygų, darbo užmokescio, paskatinimo ir vertinimų sistemų – grupės. Tyrime daroma isvada, jog policijos sistemoje taikomos pavienės ir epizodinės motyvacinės priemonės, todėl nepavyksta sukurti vieningos sistemos, jungiancios visus pagrindinius personalo motyvavimo aspektus. Efektyviai taikyti motyvacines priemones trukdo netobula įstatyminė bazė, neracionalus lėsų paskirstymas, individualizuotų skatinimo priemonių nebuvimas ir kt.
Enfermedad del desgaste en praderas de Thalassia testudinum (Hydrocharitaceae) y su relación con el perfil metabólico

Introducción: Los protistas del género Labyrinthula causan la denominada “Enfermedad del desgaste” en el pasto marino, Thalassia testudinum. Desde el 2008 los monitoreos en el Caribe colombiano han mostrado variación espacial y temporal en la incidencia de la enfermedad, pero sin la alta mortalidad observada en otras regiones del mundo. Objetivo: Analizar algunos parámetros epidemiológicos en T. testudinum y comparar metabolitos entre plantas sanas e infectadas. Métodos: Registramos la severidad, incidencia y prevalencia de esta enfermedad en el Parque Nacional Natural Tayrona e Isla de Providencia, y analizamos muestras de agua y sedimentos. Además, aplicamos cromatografía líquida y de gases, junto con espectrometría de masas, a extractos metanólicos de muestras de hojas y rizomas de brotes sanos e infectados. Resultados: Las praderas se encontraban en buen estado, a pesar de la escasez de brotes de fanerógamas marinas en Tayrona y una alta incidencia (15 %) y severidad (355 %) de la enfermedad en Providencia. Las plantas infectadas tenían niveles más bajos de fenoles, flavonoides y azúcares. Las flavonas sulfatadas con aglicona luteolina y diosmetina, los esteroles (sitosterol y estigmasterol) y las oxilipinas volátiles se acumularon en las hojas (3-hidroxi-2-isopentanona) y los ácidos isopentanoico y octadecatrienoico en los rizomas. Conclusiones: Estos pastos marinos colombianos tienen producción diferencial de metabolitos. Probablemente como una defensa exitosa, aún a niveles bajos de severidad (0.1 %) e incidencia (1 %) de la enfermedad.