bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Impact of Emotional Responses on Female Reproduction: Fibrinolysis in the Spotlight
Authors: Hoirisch-Clapauch Silvia 
Published: July 2024

AbstractFibrinolytic enzymes modify various substrates required for tissue remodeling, playing a crucial role in mechanisms underlying resilience, reward processing, ovulation, embryo implantation, and placentation. Individuals with low resilience and reduced reward responsiveness, when exposed to chronic stress, are at increased risk of experiencing a range of negative emotions. Chronic anxiety and melancholia are examples of negative emotions associated with hypercortisolism, while fear and atypical depression are characterized by systemic inflammation. Both cortisol and inflammatory cytokines stimulate the production of plasminogen activator inhibitor-1 (PAI-1), a potent fibrinolysis inhibitor. Chronic anxiety, fear, and depression are among the many hypofibrinolytic conditions increasing the risk of oligo-anovulation, miscarriage, fetal growth restriction, and preeclampsia. Although significant, the impact of negative emotions on implantation is not as obvious as on ovulation or placentation. Other hypofibrinolytic conditions that may affect female reproduction through mechanisms dependent or independent of PAI-1 include metabolic disturbances (e.g., due to consumption of highly palatable foods, often used to alleviate negative affect), inflammation, hyperhomocysteinemia, hypothyroidism, hypercortisolism, antiphospholipid antibodies, and the 4G allele of the PAI-1 gene. Benzodiazepines and antidepressants should be used with caution in the first trimester as this combination may cause malformations. Also, selective serotonin reuptake inhibitors have fibrinolytic properties that increase the risk of bleeding after surgical procedures. Psychological interventions, especially group therapy, are effective in the prevention of reproductive disorders. Controlled trials are needed to test the hypothesis that female reproductive health depends on psychological well-being, a balanced diet and physical activity, suppression of inflammation and autoantibodies, and homocysteine and hormonal homeostasis.
Determinants of the profitability of Sheltered Workshops: efficiency and effects of the COVID-19 crisis
Authors: Maside-Sanfiz José Manuel , López-Penabad María-Celia , Iglesias-Casal Ana , Torrelles Manent Juan 
Published: July 2024

AbstractThe socio-labor inclusion of people with disabilities represents a substantial social challenge in European countries, particularly in Spain. Sheltered Workshops (SWs), a type of Work Integration Social Enterprise, are companies specifically designed to provide employment opportunities for individuals with disabilities, offering ongoing support throughout the integration process. SWs need to be profitable to sustain their social contributions. This study investigates the determinants of profitability for SWs in Spain, analyzing a sample of 1133 entities from 2010 to 2020. Using a static panel data model (random effects) and a dynamic panel data model (Generalized Method of Moments, GMM system), we estimate, among other factors, the impact of efficiency on profitability, with efficiency scores calculated via data envelopment analysis (DEA). Our findings reveal that the positive effect of operational efficiency outweighs the negative effect of social efficiency, resulting in a net positive impact of overall efficiency on profitability. The SWs were able to operate effectively to meet the needs of people with disabilities while achieving financial viability by combining social and economic goals. The study shows no significant differences in these effects when considering the legal status of the SWs (for-profit vs. non-profit). Additional factors influencing SW performance include size, low risk, and leverage, which have a positive impact, while age, liquidity, and tangibility generally have a negative and significant effect. During both the financial and COVID-19 crises, SWs experienced lower profitability; however, a positive and significant relationship between efficiency and profitability was observed during the COVID-19 crisis. The robustness of our results was confirmed through alternative measures of efficiency and performance and by addressing potential endogeneity issues. Understanding how financial and social factors influence profitability helps policymakers develop growth and sustainability policies for SWs and enables practitioners to identify strengths and weaknesses, facilitating better decision-making.
Real time prediction algorithm for SOC of lithium ion power battery under high pulse rate
Authors: Zhang Zhi , Bai Shuhua , He Baiqing 
Published: July 2024

The battery needs to provide a large amount of power in a short time under the condition of a high pulse rate. Real time and accurate State of Charge (SOC) prediction can help the battery management system understand the current status of the battery better, optimize the battery charging and discharging strategy, and improve the efficiency of the battery. In order to prolong battery life and enhance battery safety, a real-time prediction algorithm for SOC of the power battery under a high pulse rate was proposed. The second order RC equivalent circuit is used to establish the model of the battery. The equivalent circuit model of the battery is designed online using the recursive least squares algorithm, and the time-varying parameter model of the battery is established. Its output value is used as the input to the gating recurrent cell neural network, and the neural network is used to output the predicted SOC value. The SOC prediction result is used as the observation vector of the adaptive extended Kalman filter algorithm to obtain the final real-time prediction result of lithium ion power battery SOC. The experimental results show that the parameters identified by the research algorithm for lithium-ion power batteries are as follows: the fluctuation range of ohmic internal resistance is 0.05–0.40 Ω, and the fluctuation range of electrochemical polarization is 0–4.5 F. The terminal voltage values collected by the research algorithm have higher accuracy, with the error being always less than 0.03 V. Moreover, the algorithm can effectively predict the SOC of lithium-ion power batteries in real time, with a maximum average absolute error of about 2%.
Sheep producers report docking tails shorter than recommended, knowledge–practice gap, and inconsistent length descriptions: an Australian survey
Authors: Woodruff Madeleine E. , Munoz Carolina A. , Coleman Grahame J. , Doyle Rebecca E. , Barber Stuart R. 
Published: July 2024

Context In Australia, it is a common practice to dock sheep tails, to reduce breech soiling and flystrike. According to research, for docking to provide the optimal benefit, tails should be left at a length that covers the vulva in ewes and to an equivalent length in males. Docking tails shorter than recommended increases the risk of perineal cancers, arthritis and prolapse. Research indicates that some producers dock tails shorter than recommended, up to 57% in surveys and up to 86% in on-farm data. Aims This study aimed to ascertain the current tail docking length, practices, knowledge and attitudes of Australian sheep producers. Methods A national survey was conducted using online, hardcopy and computer-assisted telephone interview (CATI) modes of delivery (n = 547). Key results Fifty-seven percent (205/360) of online and hardcopy survey participants chose short tail images to represent their practice, where the vulva was exposed. Although 88% (135/154) of CATI participants described their sheep tail lengths to be covering the vulva, participants equated the length to leaving two tail joints (40%, 54/134) and/or 50 mm (29%, 39/134), both of which have been previously found to be too short to cover the vulva. There was a high awareness of the recommended length (75.7%, 408/539) and 60% (234/390) of participants described it accurately. Significant associations were identified between choosing the short tail image and (1) describing the recommended length to be shorter than it is (P < 0.01), (2) being a producer in South Australia (P < 0.05), and (3) practicing mulesing (P < 0.01). Tail docking is important for producers to reduce flystrike, but docking at their chosen length held more importance than following the recommendation. Participants tended to agree that shearers preferred short tails. Docking tails with a hot knife or rubber rings were the most common methods used. Conclusions These results indicated that short tail docking remains a sheep-welfare issue for Australian sheep, and that a knowledge–practice gap exists for some producers. Implications Future research in the space of tail length could address the identified knowledge–practice gap, attitudes, and individual barriers to benefit sheep welfare and the industry.
“I want children to see that their languages are respected”
Authors: Timpe-Laughlin Veronika , Sova Lorraine , Kim Michelle 
Published: July 2024

Abstract
Demand for an understanding and appreciation of linguistic and cultural diversity in educational contexts has
intensified, given increasing levels of globalization. Moreover, guidelines from educational agencies (e.g., United Nations, 2015b; U.S. Department of Education, 2017) as
well as state-level preschool teaching standards call for raising awareness of languages, cultures, and diversity beginning in
early childhood. However, limited research in that area suggests most U.S. pre-primary teachers are monolingual English speakers
(Espinosa & Crandell, 2021). Additionally, professional development and
instructional programs on language and cultural awareness in pre-primary classrooms are rare (Kearney & Barbour, 2015). These observations raise the question as to how pre-primary educators promote linguistic
and cultural diversity in their classrooms.
This study explores world language learning practices in state-licensed, Northeastern U.S. pre-primary schools. We
administered an online survey about world language learning resources, pedagogical approaches, and classroom practices to 138
pre-primary educators and conducted individual, semi-structured interviews with 15 of the teachers. We calculated frequency
distributions for survey items to determine consensus or discrepancy among teachers and applied the procedure of initial, axial,
and selective coding (Friedman, 2012) to open-ended survey responses and interview
transcripts to identify trends and refine themes. Findings show that teachers recognized the benefits of building language and
cultural awareness. Despite limited time, training, and resources to implement such pedagogy, they included different
languages and cultures in instruction. We present their practices, focusing in particular on three distinct approaches, and
discuss implications for promoting pre-primary plurilingual and (inter)cultural education.
Observation of a phase transition from a continuous to a discrete time crystal
Authors: Kongkhambut Phatthamon , Cosme Jayson G , Skulte Jim , Moreno Armijos Michelle A , Mathey Ludwig , Hemmerich Andreas , Keßler Hans 
Published: July 2024

AbstractDiscrete (DTCs) and continuous time crystals (CTCs) are novel dynamical many-body states, that are characterized by robust self-sustained oscillations, emerging via spontaneous breaking of discrete or continuous time translation symmetry. DTCs are periodically driven systems that oscillate with a subharmonic of the external drive, while CTCs are continuously driven and oscillate with a frequency intrinsic to the system. Here, we explore a phase transition from a continuous time crystal to a discrete time crystal. A CTC with a characteristic oscillation frequencyωCTCis prepared in a continuously pumped atom-cavity system. Modulating the pump intensity of the CTC with a frequencyωdrclose to2ωCTCleads to robust locking ofωCTCtoωdr/2, and hence a DTC arises. This phase transition in a quantum many-body system is related to subharmonic injection locking of non-linear mechanical and electronic oscillators or lasers.
Holographic Einstein ring of a charged Rastall AdS black hole with bulk electromagnetic field*
Authors: Aslam M. Israr , Zeng 曾 Xiao-Xiong 晓雄 , Saleem Rabia , Hu 胡 Xin-Yun 馨匀 
Published: July 2024

Abstract
We study the Einstein images of a charged Rastall AdS black hole (BH) within the fabric of AdS/CFT correspondence. Considering the holographic setup, we analyze the amplitude of the total response function for various values of model parameters. With an increase in parameter λ and temperature T, the amplitude of the response function decreases, while it increases with an increase in electric charge e and chemical potential μ. The influence of frequency ω also plays an important role in the bulk field, as it is found that decreasing ω leads to an increase in the periods of the waves, which means that the amplitude of the response function also depends on the wave source. The relation between T and the inverse of the horizon

for various values of parameter λ is interpreted under fixed values of other involved parameters. These, in turn, affect the behavior of the response function and the Einstein ring, which may be used to differentiate the present study from previous ones. We construct the holographic images of the BH in bulk via a special optical system. The results show that the Einstein ring always appears with concentric stripes at the position of the north pole, and this ring transforms into a luminosity-deformed ring or bright light spot when the distant observer lies away from the north pole. Finally, we discuss the influence of the associated parameters on the Einstein ring radius, which is consistent with wave optics.
UV hybrid photon detector based on GaN photocathodes and Si low gain avalanche diode
Authors: Boukhicha Mohamed , Tsang Thomas Y. , Giacomini Gabriele , Dabiran Amir M. , Cultrera Luca 
Published: July 2024

Abstract
Photon detectors featuring single-photon sensitivity play a
crucial role in various scientific domains, including high-energy
physics, astronomy, and quantum optics. Fast response time, high
quantum efficiency, and minimal dark counts are the characteristics
that render them ideal candidates for detecting individual photons
with exceptional signal-to-noise ratios, at frequencies in the range
of hundreds of MHz. Here, we report on our first design and
operational results on a Hybrid Photon Detector (HPD) that combines
the high quantum efficiency of a Gallium Nitride (GaN) photocathode
and the low noise characteristics of a Si-based Low-Gain Avalanche
Diode (LGAD). This hybrid detection scheme has the potential to
reach single-photon detection sensitivity with high quantum
efficiency, low noise levels and capable of operating at hundreds of
MHz repetition rates.
Artificial Neural Network MPPT method of Solar PV System for Electric Vehicles using Mat Lab Simulink
Authors: Bharathi G , Rishitha B D S N , Lakshmi D B D M N , Likhitha Valli A , Durga B 
Published: July 2024

Abstract
Artificial Intelligence (AI) techniques are increasingly used in various areas due to their capability of handling complex systems specifies. Among the techniques of AI, Artificial Neural Networks (ANN) technique plays an important role. The Power Quality (PQ) of average to short-voltage control transmission power flow continues to be an increasingly significant issue in electric vehicles. In the previous method, charging management, large duration, and low performance are drawbacks of renewable electric vehicles. So in this method, Photovoltaic based on the available irradiance and temperatures with Battery operate charging Condition. The DC-DC converter is a bidirectional flow in order to charge the battery and supply electricity to the demand when the irradiance is high enough to generate the necessary voltage. The battery will provide power to the load using an identical bidirectional DC-DC converter whenever the PV array’s irradiance is insufficient to create a suitable voltage, at which point the battery will drain across the load. A bidirectional power flow is created by connecting buck and boost converters antiparallel to one another. Neural network controllers are designed to produce a particular duty cycle for MOSFET/IGBT. Maximum power point tracking (MPPT) using Artificial Neural Network technique for PWM. Condition to evaluate output power quality by applying convert DC to DC for the Duty cycle. The output result gains a better-charging state and analyses the outcomes of simulations in Mat lab/Simulink is used for improved output results.
Fuzzy Based Solar MPPT for Electric Vehicle Application
Authors: Bharathi G , Sai Mahitha P , Baby Sree K , Satya Sai Sri K , Usha Rani U 
Published: July 2024

Abstract
The power quality of electrical equipment relates to how well the electricity specified meets the required parameters such as harmonics, higher frequency electrical signals, low power factor, and power quality problems. To overcome this drawback, the maximum output and stable operation of solar-based power generation systems depend on the control and management of home load and electrical vehicle applications. A non-isolated buck–boost converter design with switches and inductors operating in buck-boost mode. Compared to buck-boost conversion device, the step-up/step-down voltage ratio of the isolated converter has a better gain, and the output voltage improves the power quality. A fuzzy logic-based maximum power point tracking (MPPT) technique monitors voltage (V) and current (I) under environmental conditions such as high insolation variations and partial shade. The maximum power point of a photovoltaic (PV) module remains constant despite fluctuations in solar radiation and cell temperature. Fuzzy logic for high-frequency power conversion is performed in two stages using a bridge-type converter with a DC link in the base and a chain connection of DC–DC step-up conversion devices. The output result shows the harmonic distortion from the single-phase output with power analysis through simulation.
Parameter Estimation of Solar PV Module Employing Electric EEL Foraging Optimization Algorithm
Authors: Kumari Pinki , Rahman Mukhlesur , Mani Sankar Matta 
Published: July 2024

Abstract
The extraction of unknown parameters from photovoltaic (PV) modules is critical for evaluating PV system performance amidst unpredictable conditions. This paper introduces a pioneering metaheuristic algorithm, the electric eel foraging optimization (EEFO) algorithm, tailored for resolving non-linear PV parameter estimation challenges. Inspired by the predatory behaviour of electric eels, EEFO represents a novel swarm optimization approach. The proposed methodology combines the EEFO algorithm with the Newton-Raphson method to bolster solution accuracy. Comparative assessments against established optimization algorithms validate the superior efficacy of the EEFO algorithm, substantiating its potential as a leading solution in this domain.
Numerical Analysis of Tilted Cavities Placement Effects on the Airfoils in Wind Turbine Systems
Authors: Bucur I O , Crunteanu D E , Dombrovschi M C 
Published: July 2024

Abstract
The objective of this study is to contribute to the research and development of vertical axis wind turbines (VAWTs). This will be achieved through a comprehensive analysis of modified airfoils featuring inclined cavities, specifically tailored for applications in wind systems but not limited to this. The investigation conducted in this manuscript utilizes computational fluid dynamics (CFD) to perform a numerical assessment of different airfoil configurations that have undergone modifications consisting of the incorporation of tilted cavities along distinct lengths of their upper surfaces. The aim is to ascertain an optimal airfoil geometry for VAWT applications, with a focus on concurrently achieving a high lift coefficient while minimizing the impact on the drag coefficient, therefore enhancing the overall aerodynamic performance of VAWTs. The airfoil employed in this study is the NACA0012, serving as a benchmark for comparison with airfoils subjected to modifications involving the incorporation of tilted cavities. The results of this investigation reveal that, in terms of aerodynamic traits, one of the altered airfoil configurations exhibits superior performance relative to the NACA0012 airfoil.
Energy Efficient Data Transfer in Internet of Things Sensor Network using Message Queuing Telemetry Transport
Authors: Dhanabalan G , Sudhakar P , Ashok R 
Published: July 2024

Abstract
Sensors and actuators play a vital role in realizing the Internet of Things (IoT) applications. The data transmission capability from edge devices to servers and vice-versa enables IoT applications to be more realistic and effective. However, one of the major challenges to IoT applications is power management at the edge devices. The power consumption of the edge devices depends on the amount of data transferred through the network in a defined interval. Data size and its applicability to the receiving device are controllable parameters, and consequently, energy efficiency can be improved. This work aims to establish an IoT architecture using a message queuing telemetry transport (MQTT) protocol that effectively handles the data transmission in the network. It also provides a solution for the elimination of data redundancy; hence, the network was effectively utilized, and the energy consumption was reduced in the edge devices. The proposed architecture was demonstrated with a potentiometer as a data generator and MQTT as a message broker. Further, the transmitted data was received at the edge devices and its performance was analyzed. Based on the results, it was verified that the client was able to receive the data without any loss in terms of precision. Data redundancy was avoided by disabling the data transmission whenever the nodeMCU identifies the constant sensor value. This retains the power at the edge devices and data transmission devices.