Miracle-dz/UniFAR-FTUs huggingface dataset:
Part-Load Energy Performance Assessment of a Pumped Thermal Energy Storage System for an Energy Community

Research on pumped thermal energy storage (PTES) has gained considerable attention from the scientific community. Its better suitability for specific applications and the increasing need for the development of innovative energy storage technologies are among the main reasons for that interest. The name Carnot Battery (CB) has been used in the literature to refer to PTES systems. The present paper aims to develop an energy analysis of a CB comprising a high-temperature two-stage heat pump (2sHP), an intermediate thermal storage (latent heat), and an organic Rankine cycle (ORC). From a broad perspective, the CB is modeled considering two types of heat inputs for the HP: a cold reservoir in the ground (at a constant temperature of 12 °C throughout the entire year) and a heat storage at 80 °C (thermally-integrated PTES—TI-PTES). The first part defines simple models for the HP and ORC, where only the cycles’ efficiencies are considered. On this basis, the storage temperature and the kind of fluids are identified. Then, the expected power-to-power (round-trip) efficiency is calculated, considering a more realistic model, the constant size of the heat exchangers, and the off-design operation of expanders and compressors. The model is simulated using Engineering Equation Solver (EES) software (Academic Professional V10.998-3D) for several working fluids and different temperature levels for the intermediate CB heat storage. The results demonstrate that the scenario based on TI-PTES operation mode (toluene as the HP working fluid) achieved the highest round-trip efficiency of 80.2% at full load and 50.6% round-trip efficiency with the CB operating at part-load (25% of its full load). Furthermore, when the HP working fluid was changed (under the same scenario) to R1336mzz(Z), the round-trip full-load and part-load efficiencies dropped to 72.4% and 46.2%, respectively. The findings of this study provide the HP and ORC characteristic curves that could be linearized and used in a thermo-economic optimization model based on a Mixed-Integer Linear Programming (MILP) algorithm.
Structure and Properties of Water in a New Model of the 10-Å Phase: Classical and Ab Initio Atomistic Computational Modeling

The 10-Å phase is an important member of the family of dense hydrous magnesium silicates (DHMSs) that play a major role in the water budget in the Earth’s upper mantle. Its nominal composition is usually written as Mg3Si4O10(OH)2·xH2O, and its structure is often described as layers of talc with some amount of water present in the interlayer space. However, its actual structure and composition and the detailed mechanisms of retaining H2O molecules within the mineral are not yet sufficiently known. In particular, more recent spectroscopic and diffraction data indicate the presence of Si vacancies in the tetrahedral silicate sheets of the 10-Å phase leading to the formation of Q2-type Si sites terminated by silanol groups. These silanols are, in turn, hydrogen bonded to interlayer H2O molecules. Here, we use classical and ab initio molecular dynamics (MD) simulations to compare the structures and properties of ideal and defect models of the 10-Å phase under ambient conditions. For classical MD simulations, the most recent modification of the ClayFF force field is used, which can accurately account for the bending of Mg–O–H and Si–O–H angles in the mineral layers, including the structural defects. The crystal lattice parameters, elastic constants, structure, and dynamics of the interlayer hydrogen bonding network for the model 10-Å phase are calculated and compared with available experimental data. The results demonstrate that the inclusion of Si vacancies leads to better agreement with crystallographic data, elastic constants, and bulk and shear moduli compared to a simpler model based on the idealized talc structure. The results also clearly illustrate the importance of the explicit inclusion of Mg–O–H and Si–O–H angular bending terms for accurate modeling of the 10-Å phase. In particular, the properly constrained orientation of the silanol groups promotes the formation of strong hydrogen bonds with the interlayer H2O molecules.
The Role of Cytokines in Neutrophil Development, Tissue Homing, Function and Plasticity in Health and Disease

Neutrophils are crucial innate immune cells and comprise 50–70% of the white blood cell population under homeostatic conditions. Upon infection and in cancer, blood neutrophil numbers significantly increase because of the secretion of various chemo- and cytokines by, e.g., leukocytes, pericytes, fibroblasts and endothelial cells present in the inflamed tissue or in the tumor microenvironment (TME). The function of neutrophils in cancer has recently gained considerable attention, as they can exert both pro- and anti-tumorigenic functions, dependent on the cytokine milieu present in the TME. Here, we review the effect of cytokines on neutrophil development, tissue homing, function and plasticity in cancer and autoimmune diseases as well as under physiological conditions in the bone marrow, bloodstream and various organs like the spleen, kidney, liver, lung and lymph nodes. In addition, we address several promising therapeutic options, such as cytokine therapy, immunocytokines and immunotherapy, which aim to exploit the anti-tumorigenic potential of neutrophils in cancer treatment or block excessive neutrophil-mediated inflammation in autoimmune diseases.
School management information systems: Challenges to educational decision-making in the big data era

Despite the benefits of school management information systems (SMIS), the concept of data-driven school culture failed to materialize for many educational institutions. Challenges posed by the quality of data in the big data era have prevented many schools from realizing the real potential of the SMIS. The paper analyses the uses, features, and inhibiting factors of SMIS. The paper proposes a five-phase conceptual model that assist administrators with making timely, quality decisions. The paper enriches the theoretical landscape of SMIS usage in the era of big data and lays a foundation for the future by establishing an educational decision-making model.
Facial Expression Recognition Model Based on CNN and Data Augmentation Method

Face expressions are essential in expressing human emotions, and it is accomplished by separating features and categorizing them. Facial expression recognition technology has been widely employed in human-computer interaction, telemedicine, mental health, and criminal investigation detection. In recent years, significant advances in deep learning have facilitated the development of facial expression recognition, making it increasingly accessible. Convolutional neural networks (CNN) are the foundation of the face expression recognition model presented in this article. In order to maximize the final accuracy, an abundance of sample photographs are required for training and optimization. As a result, the 35,886 facial expression photos from the FER2013 dataset, which contains all seven emotions, were used for both training and testing. The photos were scaled down to 4848 pixels during data preparation, and data augmentation was carried out. To get accurate face expression recognition results, various optimizers and parameters were chosen for the training network, which was a bespoke structure based on the VGG network design. The model constructed in this study achieved an accuracy of 73.16% during prediction.
Optimization of freeze drying parameters for moringa (Moringa oleifera) flower powder by using response surface methodology and principal component analysis

Moringa oleifera Lam. is an incredible plant because of vital nutrients such as minerals, vitamins and phytochemicals. The present work is focused on studying the optimization and quality attributes retention in moringa flowers in a freeze dryer (FD). Because the conventional drying process takes more time and energy which will affect the product quality and safety. Response surface methodology (RSM) was employed to optimize the effect of drying temperature (- 65 to - 45°C), vacuum pressure (0.5 to 2.5 mmHg) and drying time (18 to 24 h.) on the vitamin C, total antioxidant activity(TAA) and hygroscopicity (HS) of moringa flower. The developed model response R2 values of vitamin C 0.96, total antioxidant activity 0.97 and hygroscopicity0.95. Based on response surface and desirability (0.74) functions, moringa flower was freeze sdried at - 63.75°C for18 hr under 0.55 vacuum pressure had an optimum level of vitamin C 285.84 mg/100g, TAA 453.20 mg/100g and HS 1.57 percent. Freeze dried moringa flower powder at -55°C had maximum drying characteristics with special reference to high powder recovery (98.75%) and excellent flowability.The first principal component, accounting for 52.15 per cent and two 23.02 per cent of the total variance resolved the different drying temperatures.
Trade openness, financial development, and urbanization in the renewable energy-growth-environment nexus

ABSTRACT The renewable energy-economic growth-environment nexus has been generally considered an important puzzle that needs to be addressed for the following phrases of sustainable economic growth and development globally. The existing literature confirms the potential role of trade openness, financial development, and urbanization in this nexus. However, these roles have largely been ignored in empirical studies. This study uses the second-generation macro econometrics regarding panel unit root tests, cointegration tests, long-run estimations, and Granger homogeneous non-causality tests to investigate these impacts on the important nexus. First, the findings reveal that economic growth increases CO2 emissions, whereas renewable energy usage supports economic growth and mitigates CO2 emissions. There appears to be a bidirectional causality relationship between renewable energy and economic growth, which Granger-cause CO2 emissions unidirectionally. Second, trade openness increases CO2 emissions and renewable energy usage. We also find that financial development positively contributes to economic growth, whereas urbanization has no impact on the nexus in the long run. Third, trade openness Granger causes economic growth bidirectionally, and unidirectional causality from financial development to economic growth and CO2 emissions is found. Our results confirm a bidirectional causality relationship between urbanization, economic growth, and CO2 emissions and a unidirectional causality relationship from renewable energy to urbanization. Policy implications have emerged for countries globally, including emerging markets, which are the main emitters. Increased renewable energy supply and usage in total energy and extended financial systerms will sustain economic development and limit CO2 emissions.
Taking Prime, Maximal and Two--class Congruences Through Morphisms

In this paper we study prime, maximal and two--class congruences from the point of view of the relationships between them in various kinds of universal algebras, as well as their direct and inverse images through morphisms. This research has also produced a set of interesting results concerning the prime and the maximal congruences of several kinds of lattices.
Perceptions of fatherhood and confidence regarding neonatal care among fathers of high-risk neonates in South Korea: a descriptive study

Purpose The purpose of this study was to investigate perceptions of fatherhood among fathers of high-risk neonates and their confidence regarding neonatal care. Methods A study was conducted of 100 fathers whose neonates had been admitted to a neonatal intensive care unit (NICU) for at least 48 hours. Perceptions of fatherhood, neonatal characteristics, and fathers' confidence regarding neonatal care were measured using a self-reported questionnaire. The survey took approximately 10 minutes to complete and was completed anonymously. The factors that affected fathers' confidence regarding neonatal care were analyzed using multiple regression. Results The scores for positive and negative perceptions of fatherhood were relatively high at 4.27 and 3.42 out of 5 points, respectively. A positive perception of fatherhood was found to influence fathers' confidence regarding neonatal care. Conclusion NICU nurses should encourage fathers to effectively perform their parenting roles by implementing educational programs and interventions to promote positive perceptions of fatherhood and fathers' confidence regarding neonatal care after discharge.
Bibliometric and Visual Analysis of Global Research on Taurine, Creatine, Carnosine, and Anserine with Metabolic Syndrome: From 1992 to 2022

Red meat and animal-sourced protein are often disparaged as risk factors for developing metabolic syndrome, while emerging research has shown the beneficial effects of dietary taurine, creatine, carnosine, and anserine which are all exclusively abundant in red meat. Thus, it is imperative to highlight the available evidence to help promote red meat as part of a well-balanced diet to optimize human health. In this study, a bibliometric analysis was conducted to investigate the current research status of dietary taurine, creatine, carnosine, and anserine with metabolic syndrome, identify research hotspots, and delineate developmental trends by utilizing the visualization software CiteSpace. A total of 1094 publications were retrieved via the Web of Science Core Collection from 1992 to 2022. There exists a gradual increase in the number of publications on this topic, but there is still much room for research papers to rise. The United States has participated in the most studies, followed by China and Japan. The University of Sao Paulo was the research institute contributing the most; Kyung Ja Chang and Sanya Roysommuti have been identified as the most prolific authors. The analysis of keywords reveals that obesity, lipid profiles, blood pressure, and glucose metabolism, as well as ergogenic aid and growth promoter have been the research hotspots. Inflammation and diabetic nephropathy will likely be frontiers of future research related to dietary taurine, creatine, carnosine, and anserine. Overall, this paper may provide insights for researchers to further delve into this field and enlist the greater community to re-evaluate the health effects of red meat.
EFFECTIVITY OF DOLOMITE ADSORBENT IN PURIFICATION OF Mn AND Cu FROM ACID MINE DRAINAGE

The mining industry raises many environmental problems in the ecosystem, one of which is the emergence of acid mine drainage. Because of this issue, this study was conducted to see the performance of dolomite adsorbents in purifying acid mine drainage at iron ore mining in Aceh Besar, Indonesia. The adsorption of Cu2+ metal ions using dolomite adsorbents has the best equilibrium result at a contact time of 15 minutes, the efficiency at equilibrium reaches 92.97%, and the absorption capacity reaches 9.07 mg/g at an initial measured concentration of 19.5 mg/L with an adsorbent weight of 0.2 gr. On the other hand, Mn2+ has the best equilibrium in 30 minutes with an efficiency of 95.17% and an adsorption capacity of 0.92 mg/g at a measured concentration of 5.8 mg/L and an adsorbent weight of 0.6 gr. The obtained kinetic model is a pseudo second order.
Redox Regulation in Age-Related Cataracts: Roles for Glutathione, Vitamin C, and the NRF2 Signaling Pathway

Age is the biggest risk factor for cataracts, and aberrant oxidative modifications are correlated with age-related cataracts, suggesting that proper redox regulation is important for lens clarity. The lens has very high levels of antioxidants, including ascorbate and glutathione that aid in keeping the lens clear, at least in young animals and humans. We summarize current functional and genetic data supporting the hypothesis that impaired regulation of oxidative stress leads to redox dysregulation and cataract. We will focus on the essential endogenous antioxidant glutathione and the exogenous antioxidant vitamin C/ascorbate. Additionally, gene expression in response to oxidative stress is regulated in part by the transcription factor NRF2 (nuclear factor erythroid 2-related factor 2 [NFE2L2]), thus we will summarize our data regarding cataracts in Nrf2-/- mice. In this work, we discuss the function and integration of these capacities with the objective of maintaining lens clarity.
Clinical Value of Hospital-Community-Family Integrated Nursing Model in the Treatment of Patients with Hyperlipidemia Pancreatitis

Objective This study aimed to observe the impact of the hospital-community-family integrated nursing paradigm on the compliance, psychological state, and blood lipid levels in patients with hyperlipidemia pancreatitis (HLP). Methods Totally 66 HLP patients treated in our institution between June 2018 and June 2021 were randomized to Exp group and Con group. The Exp group received the hospital-community-family integrated nursing mode, whereas Con group adopted conventional nursing. Outcome measures included patient compliance, mental state, and blood cholesterol levels. Results Patients with integrated nursing exhibited markedly higher compliance than those with conventional nursing, as evinced by higher scores of compliance behavior, compliance awareness, medication attitude, and treatment attitude (P < 0.05). Integrated nursing offered more potent mitigation of negative emotions of patients than conventional nursing (P < 0.05). Integrated nursing resulted in better enhanced quality of life of patients versus conventional nursing (P < 0.05). Superior blood lipid amelioration was observed in patients after integration nursing versus those after conventional nursing, demonstrated by a higher serum high-density lipoprotein (HDL) level, and lower levels of triglycerides (TG), cholesterol (TC), and low-density lipoprotein (LDL) (P < 0.05). Patients were more satisfied with integrated nursing (96.97%) than conventional nursing (72.73%), suggesting a high patient acceptance of the nursing mode (P < 0.05). Conclusion The hospital-community-family integrated nursing model provides a viable alternative to enhance HLP patients’ compliance and optimize their psychological state and blood lipid levels, demonstrating good potential for clinical promotion.
Preparing the assimilation of the future MTG‐IRS sounder into the mesoscale numerical weather prediction AROME model

The infrared sounder (IRS) instrument is an infrared Fourier‐transform spectrometer that will be on board the Meteosat Third Generation series of the future European Organization for the Exploitation of Meteorological Satellite's geostationary satellites. It will measure the radiance emitted by the Earth at the top of the atmosphere using 1,960 channels. The IRS will provide high spatial‐ and temporal‐frequency four‐dimensional information on atmospheric temperature and humidity, winds, clouds, and surfaces, as well as on the chemical composition of the atmosphere. The assimilation of these new observations represents a great challenge and opportunity for the improvement of numerical weather prediction (NWP) forecast skill, especially for mesoscale models such as the Applications de la Recherche à l'Opérationnel à Méso‐Echelle (AROME) at Météo‐France. The objectives of this study are to prepare for the assimilation of the IRS in this system and to evaluate its impact on the forecasts when added to the currently assimilated observations. By using an observing system simulation experiment constructed for a mesoscale NWP model. This observing system simulation experiment framework makes use of synthetic observations of both IRS and the currently assimilated observing systems in AROME, constructed from a known and realistic state of the atmosphere. The latter, called the “nature run”, is derived from a long and uninterrupted forecast of the mesoscale model. These observations were assimilated and evaluated using a 1 hr update cycle three‐dimensional variational data assimilation system over 2‐month periods, one in the summer and one in the winter. This study demonstrates the benefits that can be expected from the assimilation of IRS observations into the AROME NWP system. The assimilation of only 75 channels over oceans increases the total amount of observations used in the AROME three‐dimensional variational data assimilation system by about 50%. The IRS impact in terms of forecast scores was evaluated and compared for the summer and winter periods. The main findings are as follows: (a) over both periods the assimilation of these observations leads to statistically improved forecasts over the whole atmospheric column; (b) for the summer‐season experiment, the forecast ranges up to >$$ > $$ 48 hr are improved; (c) for the winter‐season experiment, the impact on the forecasts is globally positive but is smaller than the summer period and extends only to 24 hr. Based on these results, it is foreseen that the addition of future IRS observations in the AROME NWP systems will significantly improve mesoscale weather forecasts.
End-to-End Multiview Fuzzy Clustering With Double Representation Learning and Visible-Hidden View Cooperation

Multiview clustering has received great attention in recent years for the potential in clustering performance improvement by using cooperative learning of different views. Despite the considerable progress, a few issues remain: 1) real multiview data contains redundant features and noises that lead to unsatisfactory clustering performance; 2) most existing multiview clustering methods only mine the shared information between views and ignore the specific information within views; and 3) most multiview clustering methods are based on a two-step framework that learn the hidden view representation and then perform clustering, overlooking the correlation between the two processes. Although some approaches have been proposed to deal with these issues, they cannot them simultaneously. To this end, we propose an end-to-end multiview fuzzy clustering. First, we construct a multiview fuzzy clustering framework to mine the specific information of the visible views. Second, to reduce the impact of redundant features and noises on clustering performance, we introduce the orthogonal projection matrix into the clustering framework to learn the low-dimensional representation of the visible views. Meanwhile, this procedure is integrated into the clustering framework. Third, we explore the shared hidden view representation between the visible views by multiview non-negative matrix factorization and integrate it into the clustering framework to realize visible-hidden view cooperation learning. Finally, the shared hidden view representation learning between visible views, the low-dimensional representation learning of visible views, and the clustering partition of multiview data negotiate with each other in the end-to-end learning framework. Extensive experiments on benchmark multiview datasets indicate the superiority of the proposed method over state-of-the-art methods.
Macroeconomic uncertainty and monetary policy transmission in Brazil: a TVAR approach

ABSTRACT This article assesses the impact of uncertainties on the effectiveness of monetary policy in Brazil after the adoption of the inflation-targeting regime. We employ the methodology of autoregressive vectors with an endogenous threshold (TVAR) with a general uncertainty indicator (IGI), proposed as a linear combination of four existing proxies for the Brazilian context. The sample covers 2003 to June 2022 at a monthly frequency. The results show the IGI variable has the highest degree of correlation with economic recessions in the country among all the analysed indicators. Moreover, in regimes of high uncertainty, the responses of the output gap, inflation, and inflationary expectations to interest rate shocks are severely reduced. Therefore, we conclude that an increase in macroeconomic uncertainties can reduce the effectiveness of monetary policy in Brazil.