bluuebunny/crossref_metadata_2025 huggingface dataset:
An Analysis of dolly red-light district closure impact: 10-year post-transformation study on the psychological and economic vulnerability of susceptible women groups
Authors: Setyawan Jefri , Wibowo Joshi Maharani , Indrawardani Ken Fitria
Published: November 2024

The Dolly area, known as a former red-light district in Surabaya City, is closed, as instructed by local government policy in 2014. This transformation negatively impacted the psychological and economic of vulnerable community groups in the surrounding area, especially women. This research is conducted to revisit the impact of Dolly area closure instruction and policy after ten years. The research is done qualitatively in the Former Dolly red-light district, Surabaya City, by obtaining the primary data through focus group discussions (FGD) in 2023. The analysis method used is TNA (thematic network approach), which is processed and visualized using NVIVO 12 pro. Feminist Standpoint Theory (FST) is used as a theoretical framework to ensure that the knowledge produced involves the participation of individuals who experience it directly. The results show the majority of former sex workers' lives, mainly women, rarely experience a decent life of living after 10 years of Former Dolly red-light district closure. There are three main obstacles (theme) causing this, which is: social, economic and administrative. The poor welfare of this community group leads to discrimination and stigmatization of former Dolly sex workers, and they become more psychologically vulnerable, marginalized and rarely considered as strategic development subjects. Apart from that, excessive social problems such as discrimination and stigmatization affect their economic activity. They lost the freedom to enter a legal sector as labour. Instead, they were forced to enter the shadow economy sectors, such as returning as sexual workers illegally.
Early warning system modeling for rice supply using backpropagation artificial neural network to manage imported rice
Authors: Novianti Trisita , Agustina Fitri , Indriartiningtias Retno
Published: November 2024

Rice is a staple food in Indonesia. Although Indonesia produces a large amount of rice, it cannot meet domestic rice needs. The unpredictable domestic rice supply prompted the government to import rice. Moreover, rice imports are one of the efforts to provide rice stock. On the other hand, importing rice can decrease domestic rice prices because it creates a market competitor. This study uses backpropagation artificial neural networks to develop a prediction system for rice supply crises in Indonesia based on models similar to currency crisis prediction systems. The study identified key variables and indicators for predicting rice supply crises, including rice production, consumption, prices, land area, and population. Data from January 2012 to December 2022 was analyzed. The optimal neural network architecture achieved a Mean Squared Error (MSE) of 0.209192. The analysis revealed that rice consumption, land area, and total population are the most strongly correlated indicators of a rice commodity crisis
Relevance of the Retrieval of Hadith Information (RoHI) using Bidirectional Encoder Representations from Transformers (BERT) in religious education media
Authors: Ni’mah Ana Tsalitsatun , Yunitarini Rika
Published: November 2024

This research explores the impact of integrating Bidirectional Encoder Representations from Transformers (BERT) into the Retrieval of Hadith Information (RoHI) application within the realm of religious education media. Hadith, the sayings and actions of Prophet Muhammad, play a pivotal role in Islamic teachings, requiring accurate and contextually relevant retrieval for educational purposes. RoHI, designed to enhance access and comprehension of Hadith literature, employs BERT's advanced natural language processing capabilities. The study assesses how BERT-enhanced RoHI facilitates efficient retrieval and interpretation of Hadith texts. By leveraging BERT's ability to capture intricate language patterns and semantics, the study aims to enhance the precision and contextual appropriateness of retrieved Hadith information. The study also discusses implications for digital learning platforms, emphasizing the potential of NLP technologies to foster broader access to religious knowledge and promote inclusive educational practices. This research contributes to the field by proposing a framework that integrates advanced AI techniques with religious education, ensuring that learners receive accurate and meaningful Hadith information tailored to their educational needs. The findings highlight the potential of BERT in revolutionizing information retrieval processes in religious studies, paving the way for more effective educational tools and resources in Islamic learning environments.
Reduction of waste in biodiesel production with Value Stream Mapping (VSM)
Authors: Sianturi Ruth Indah , Singgih Moses Laksono
Published: November 2024

Currently, the biodiesel industry in Indonesia presents significant opportunities within the broader industrial sector. However, competition within this field has intensified, leading to higher price offers. This situation may be caused by inefficiencies in the production floor. The application of Lean Manufacturing is implemented to map all activities involved in biodiesel production. A questionnaire method is employed to identify the inefficiencies. After assessing the current state, the root causes are analyzed using the 5W method, followed by a production gemba walk. This research is then carried out through process activity mapping to evaluate time utilization on the production floor. The steps undertaken include creating a future state map plan, which provides a design for improvements and the implementation of continuous improvement in biodiesel production, ultimately leading to cost savings. The results of this study indicate a production savings margin of IDR 1,870,726,000 per year, and the application of continuous improvement at the Biodiesel Plant successfully reduced the total time required by 3,920 hours.
Model of brand image jamu Madura through product knowledge, brand communication and packaging attractiveness
Authors: Herawati Netty , Rohmah Nailur , Hutagalung Fonny D. , Bulut Sefa
Published: November 2024

The fame of Madura’s jamu is motivated by a thick culture. Madura’s jamu is made from processed spices that are used as an alternative treatment to maintain body health, both preventively and curatively. The tradition of drink Madura’s jamu is applied from an early age at home. But currently the development of jamu Madura is very slow, not increased and showed very poor development significant from year to year compared to chemical drugs in circulation in Indonesia. Therefore, this study wants to find out what can increase the use of Madura’s jamu again to maintain health. The researcher looks at the influence of brand communication factors, product knowledge and the attractiveness of packaging in building the brand image of Madura’s jamu. This study uses a quantitative method with a total of 1.315 respondents. Result shows simultaneously the brand image model of Madura’s jamu requires the role of product knowledge, brand communication and packaging attractiveness. Therefore, marketers must always design a brand image development program in marketing activities and carry out activities that support marketing to strengthen the brand.
Using ensemble neural network based on sampling for multiclass classification
Authors: Khotimah Bain Khusnul , Setiawan Eko , Anamisa Devie Rosa , Puspitarini Oktavia Rahayu
Published: November 2024

Multiclass data classification with class imbalance causes classification performance to decrease, especially in the Neural network method. Research shows that the model proposed by eNN can improve model performance for imbalanced data in the selection of superior quality in beef and cattle data. The results of the Ensemble ANN study with adaboost are able to understand complex relationships by measuring the level of correlation with the target class produced. This study aims to overcome the problem of data imbalance in the ensemble neural network method by comparing the oversampling method with undersampling, so that more representative synthetic data is obtained. Performance evaluation is processed using precision, recall and accuracy calculations. Research on superior local Madura cattle data The RUS-eNN method produces the highest average accuracy value compared to others, reaching 98.00% with a recall value of 100%. While the ROS-eNN method produces a difference in accuracy value that is not so far away, namely 97.69%. The research on the sampling-based eNN approach has better accuracy than without using data replication in improving its performance.
Dimensional stability of brake pads reinforced with calcined eggshell particles under exposed to engine lubricating oil
Authors: Sunardi Sunardi , Ariawan Dody , Surojo Eko , Prabowo Aditya Rio , Wibowo Cahyo Hadi , Akbar Hammar Ilham , Sudrajad Agung , Seputro Harjo
Published: November 2024

Exposure to a humid environment can affect the behavior of brake lining composites. Considering the vital function of brake linings in controlling vehicle speed, environmental influences must receive serious attention. Exposure to lubricating oil that sticks to the brake lining can cause changes in performance during work. This study will investigate the dimensional stability of brake pad composites when exposed to engine oil and understand the physical behavior of material to facilitate appropriate handling. The brake pads in this study comprised 35% phenolic resin, 10% graphite, 10% bamboo fiber, 10% alumina powder, 5% zinc powder, 5% bamboo particles, and 25% eggshell particles. The manufacturing of brake linings involves three process stages: cold compaction, hot compaction, and post-curing. The samples were soaked in Federal Ultratec API SJ JASO MA engine lubricating oil for 12, 24, 36, and 48 hours. The results showed that the immersion time of the composite in lubricating oil did not significantly affect the dimensional stability of the composite. This result shows that the addition of calcined eggshell particles can improve the material's resistance to engine lubricating oil.
Tourism SDGs action plan from a regulatory perspective
Authors: Nugroho Lucky Dafira , Melati Santi Rima , Ganindha Ranitya , Wahyuliana Ida , Kurniawan Lexy Fatharany , Amilia Ditta , Bariroh Nur Afifatul
Published: November 2024

Sustainable tourism is one that fully considers current and future economic, social, and environmental impacts and meets the needs of visitors, industry, the environment, and local communities. Sustainable tourism is part of the Sustainable Development Goals (SDGs). Indonesia has adopted the SDGs. These SDGs and the sustainable tourism criteria set by the Global Sustainable Tourism Council (GSTC) are then translated into a sustainable tourism development program in Indonesia called Sustainable Tourism for Development (STDev). STDev has been stipulated in the Minister of Tourism Regulation (Permenpar) No. 14 of 2016 concerning Guidelines for Sustainable Tourism Destinations. The United Nations World Tourism Organization (UNWTO) has recognized these programs and criteria as amended by Permenparekraf 9/2021.1. Permenpar 9/2021 discusses sustainable destination management, abbreviated as 3P + 1M, namely people, planet, prosperity, added with management. As for the research method used to answer problems regarding government compliance in implementing regulations, research will be carried out using socio-legal methods which elaborate legal phenomena with applicable laws. Thus, it can be seen that Permenpar 9/2021 has provided guidelines in an effort to realize sustainable tourist destinations through criteria and indicators that are easy for local governments to realize.
Assessing Tourism Competitiveness in Pamekasan Regency: A Tourist Perspective
Authors: Wispandono Mochamad , Purnomo Hadi
Published: November 2024

Pamekasan district has several interesting tourist attractions, such as Jumiang Beach and Kehi Hill, but these spots have not yet become the main choice for tourists. The problem identified is the low competitiveness of these tourist spots compared to others in the region. The solution proposed involves analyzing tourism competitiveness in Pamekasan Regency from the perspective of tourists. The research contribution is to provide insights for improving tourism policies in Pamekasan. This research employs a quantitative descriptive method using purposive sampling techniques and the Slovin formula to obtain a sample of 80 tourists. Samples were drawn from frequent visitors to both Pamekasan and other areas. The method combines commonly used dimensions and indicators, including attractions, facilities, accessibility, infrastructure, and sacrifices (time, energy, and money), along with tourist satisfaction. The results reveal that satisfaction and preferences significantly influence tourist visits, supporting the findings of Miragaia, Conde, and Soares (2016). Pamekasan's tourist competitiveness is found to be lower than tourist attractions outside Madura but competitive within Madura. The study concludes that Pamekasan’s tourism competitiveness could improve with stronger governmental and community collaboration in managing tourism sites. This research contributes to policy development aimed at boosting tourism competitiveness in Pamekasan through multi-stakeholder collaboration..
SWOT analysis of educational facilities and infrastructure for enhancing language literacy at State Islamic Elementary School 1 Malang: Challenges and opportunities
Authors: Nurharini Firdausi , Mas Ulliyah Hasan Laili , Nadiyah Salma Kunti , Adhimah Syifaul , Shidqiyyah Nabila
Published: November 2024

This study aims to analyze the strengths, weaknesses, opportunities, and threats (SWOT) related to the educational facilities and infrastructure at SD Islam Negeri 1 Malang and their contribution to improving language literacy. The research employs a descriptive qualitative approach, utilizing SWOT analysis to evaluate the current state of facilities and their impact on Arabic and English literacy. Data collection techniques include observation, interviews, documentation, and questionnaires, targeting the school principal, teachers, students, and committee members. The results indicate that SD Islam Negeri 1 Malang generally meets the standards set by national regulations, with well-maintained facilities such as Wi-Fi, electricity, sound systems, and digital learning technologies that enhance the learning environment. However, issues such as inadequate water supply during the dry season and suboptimal toilet conditions need to be addressed. The analysis highlights that while the existing infrastructure supports effective language learning, improvements and collaboration with external partners are needed to address the identified weaknesses and threats. Implementing digital resources, interactive materials, and enhancing security measures are recommended strategies to further improve language literacy.
Farmers’ entrepreneurial behavior in long pepper (Piper retrofractum Vahl) cultivation in Bluto District, Sumenep Regency
Authors: Hasan Fuad , Ihsannudin  , Kurniyanto Ifan Rizky , Destiarni Resti Prastika , Musyafak
Published: November 2024

The cultivation of long pepper presents promising economic and agroclimatic potential. Sumenep Regency—characterized by its suitability for long pepper cultivation—remains underutilized due to limited intensive management by local farmers. This phenomenon hinges significantly on farmers’ entrepreneurial behavior. This study seeks to evaluate and understand the entrepreneurial behavior of long pepper farmers in Sumenep Regency and identify the factors that influence this behavior using six indicators as follows future orientation, risk-taking propensity, task and result orientation, confidence, innovation and persistence. Primary data was gathered through questionnaires administered to a sample of 50 farmers selected using purposive sampling, ensuring that respondents were selected based on their relevance to the research objectives. Descriptive statistics and multiple linear regression were employed for data analysis. The descriptive findings indicate that most farmers exhibit satisfactory entrepreneurial behavior across four defining indicators: future orientation, risk-taking propensity, task and results orientation, and innovation. Moreover, farmers demonstrate commendable entrepreneurial traits in terms of self-efficacy and persistence. Regression analysis reveals that farmers’ experience and membership in agricultural groups positively correlate with entrepreneurial behavior, whereas educational attainment shows no significant impact. These findings could inform targeted interventions to improve entrepreneurial behavior among farmers and potentially improve cultivation and economic sustainability.
Analysis of the influence of farmers' knowledge skills and attitudes towards extension in understanding the capacity of Madurese cattle farmers in West Waru Village, Pamekasan Regency
Authors: Triyasari Sri Ratna , Kamilah Istifadatul
Published: November 2024

Livestock businesses in West Waru Village tend to apply traditional treatment techniques rather than using scientifically measured rules. Even scientifically sound methods may be inefficient economically and nutritionally, leading to high costs, particularly in feed procurement. The purpose of this study is to identify the characteristics of breeders that influence the performance of feed supply management in the beef cattle business and to examines factors such as knowledge transfer, skill, and attitude of extension methods within the beef cattle industry. The sampling technique using Roscoe theory and snowball sampling obtained as many as 50 respondents. The analysis method used to answer the first goal is multiple linear regression analysis and then the second goal uses qualitative descriptive. The results showed that knowledge and attitude has a significant impact to breeder welfare. Breeders who participated in extension activities demonstrated an improved understanding of livestock management, including the importance of proper feeding, record-keeping, and maintaining cleanliness in livestock and their surroundings. This improved knowledge and positive attitude towards livestock management were found to be crucial factors in enhancing the welfare of the breeders.
Family attitude and responsibility: A Quranic-based theoretical framework in the globalization challenges
Authors: Qomaro Galuh Widitya , Supaat Dina Imam , Nasrulloh Nasrulloh
Published: November 2024

This study addresses the urgent need for a theoretical framework on family attitudes and responsibilities in Islam, particularly in response to the challenges posed by globalization that threaten traditional Muslim family values. The research contribution is the development of a new theoretical model that integrates emotional well-being, spiritual leadership, and the balance of rights and responsibilities, based on Quranic teachings. The methodology involved a textual analysis of Quranic verses to formulate variables and indicators related to family attitudes and responsibilities, followed by a survey to evaluate the instrument's validity and reliability. The results demonstrate a strong correlation between spiritual leadership and family harmony, highlighting emotional well-being as a key factor in maintaining a sakinah (peaceful) family. The study finds that the balance of rights and responsibilities rooted in Islamic principles significantly contributes to family stability. This framework serves as a foundational tool for future research on Muslim family development. Future studies should test the model empirically across different cultural contexts to ensure its applicability.
Photo-Aging of Biodegradable Polylactic Acid Microplastics
Authors: Wang Chu , Yan Zhiyong , Liu Muhan , Liu Lu
Published: November 2024

Microplastic (MPs) pollution has became a serious issue. Photoaging is one of the main ways to produce MPs. Polylactic acid (PLA) is the most commonly used biodegradable plastic in industry, however, the current reports on the quantitative data of biodegradable PLA MPs produced by photoaging were little known. Therefore, this study selected PLA MPs as representative MPs to explore photoaging of biodegradable MPs. The results showed that PLA MPs were broken by photoaging, resulting in an increase in the total particle numbers and a decrease in average particle size. The numbers of particle in PLA MPs increased from 4.39×106 particles/L to 6.74×106 particles/L, and the average particle size decreased from 22 μm to 17 μm. C=O and C-O on PLA MPs surface were broken, which further confirmed that PLA MPs were degraded and broken after photoaging. This work is helpful to better understand the impact of light on the aging of biodegradable MPs and to assess the environmental risk of biodegradable MPs.
Synthesis and Properties of Amphoteric Etherified Starch Flocculant CMSG
Authors: Li Haihua , Gao Yuhua , Zhang Yaze , Li Na
Published: November 2024

Etherified starch has the advantages of cheap raw materials and simple preparation process. In the field of wastewater treatment, it can be used as a flocculant and adsorbent. Amphoteric etherified starch CMGS was synthesized in a one-step method using cornstarch (St) as raw material, 2,3-epoxypropyl trimethyl ammonium chloride (GTA) and chloroacetic acid (CAA) as cationic and anionic etherification agents, respectively, and the flocculation performance on kaolin suspension was studied. The results showed that compared with cationic etherified starch, the optimal dose of the amphoteric etherified starch CMGS increased and the flocculation window length increased. The optimal dose of CMGS2 was 14 mg/L, and the flocculation window length was 24 mg/L, which has certain practical value.
Study on Wind Effect of Train Piston in Railway Tunnel with High Altitude and High Rock Temperature
Authors: Feng Guohui , Zhang Xiao , Sun Jialin , Huang Kailiang
Published: November 2024

The piston wind effect in the tunnel of the Sichuan-Tibet railway under high rock temperature and low-pressure environment was studied and analyzed to provide theoretical support for the tunnel’s thermal environment analysis and ventilation design. The calculation model of piston wind for trains running under low pressure is established, and the influence of atmospheric pressure and tunnel wall temperature on the piston wind effect in the tunnel is increased. By comparing the impact of different factors on the piston wind effect in the tunnel, the fitting rule function between train speed and piston wind speed is obtained. The results show that atmospheric pressure and tunnel wall temperature have little influence on the piston wind effect in the tunnel and can be ignored. Natural ventilation and train speed significantly influence the piston wind effect in the tunnel. Reasonable use of natural ventilation and train speed control can effectively reduce the piston wind effect, reduce the heat accumulation in the tunnel, and ensure the safety and comfort of the tunnel.
Study of Condenser Spatial State Model Based on Dynamic Thresholding of Environmentally Adaptive Multi-Dimension Eigenvalues
Authors: Qian Hong , Sun Shuyin , Wang Xuehua , Li Zhenpeng
Published: November 2024

This study proposes an approach that takes into account the impact of marine environmental impacts on the multi-dimension eigenvalues and analyzes the condenser status based on multi-dimension eigenvalues dynamic threshold. Firstly, we get the multi-dimensional eigenvalues of the condenser Based on thermodynamic theory analysis. Then, utilizing seawater-temperature and seawater-level as environmental parameters, the partitioning of the condenser marine environmental region is optimized based on the CalinskiHarabasz index. Subsequently, the multi-dimension eigenvalues are used to calculate to get the multidimension eigenvalues dynamic thresholds and mean corresponding to the marine environmental regions by improved Gaussian mixture algorithm (GMM). Then, the multi-dimension eigenvalues of the condenser are used to construct the spatial state analysis model of the condenser by improving Euclidean distance and cosine distance. Real time multi-dimension eigenvalues and normal means corresponding to the marine environment region are utilized for spatial quantification analysis of the condenser running status, the running status’s average during the sliding time window is used as the standard to determine whether the condenser running status is abnormal. Dynamic threshold and spatial state model calculations are performed using real data under different marine environment regions, its demonstrated that the proposed method accurately identifies the condenser running status.
Study on Carbon Footprint of Cold Chain Logistics of Agricultural Products in Sichuan Province Based on LCA Method
Authors: Yang Chunxia , Liu Chenghua , Yang Ningning
Published: November 2024

Under the “dual carbon” goal, the contradiction between the growth of agricultural product cold chain logistics demand and the low-carbon economy goal is becoming increasingly prominent. As a key link connecting production and consumption, the energy consumption and carbon emission issues of agricultural product cold chain logistics cannot be ignored. This study established a life cycle analysis framework for agricultural product cold chain logistics. Based on the circulation data of agricultural product cold chain in Sichuan Province, the carbon footprint of agricultural product cold chain logistics was calculated from five stages: processing, packaging, transportation, sales and disposal. A comparative analysis was conducted from the two perspectives of agricultural product types and cold chain logistics links, and relevant low-carbon development suggestions were put forward accordingly.
Why Median Severity and Ordinal Scale Severity Values should not be used for Injury Burden Results: A Critical Review
Authors: Fuller Colin W.
Published: November 2024

Injury burden is a composite measure of injury incidence and mean severity; this parameter has been reported as an output measure from injury surveillance studies in rugby for over 20 years. The benefits of reporting injury burden results have, more recently, been recognised in other sports. This wider use of injury burden as an output measure from injury surveillance studies has, however, highlighted misunderstandings about how to calculate, present and interpret injury burden data. The aim of this critical review is to explain why median severity and ordinal severity scales should not be used to calculate and report injury burden results in injury surveillance studies. Equations are presented to show how injury burden results should be calculated, and graphs and tables are presented to explain the errors that are introduced when median severity and ordinal scales of severity are used instead of mean severity. This critical review is intended to highlight the correct procedures for calculating, reporting and interpreting injury burden results in order to avoid incorrect results, conclusions and injury prevention recommendations being published.
Das muskelinvasive und metastasierte Urothelkarzinom aus Sicht der Pathologie
Authors: Klümper Niklas , Kalogirou Charis , Eckstein Markus
Published: November 2024

Das muskelinvasive und metastasierte Urothelkarzinom ist eine heterogene Erkrankung mit breitem morphologischem und molekularem Spektrum. Mit der Novelle der WHO-Klassifikation haben sich einige Veränderungen in der Nomenklatur und Einteilung muskelinvasiver und metastasierter Urothelkarzinome ergeben. Aufgrund zunehmender Individualisierung therapeutischer Optionen gewinnt die korrekte Diagnose morphologischer Varianten des Urothelkarzinoms, die mit spezifischen molekularen Alterationen assoziiert sind, zunehmend an Bedeutung. Die morphologischen Varianten korrelieren zudem mit molekularen Subtypen des Urothelkarzinoms. Darüber hinaus sind sowohl morphologische als auch molekulare Subtypen mit immunologischen und anderen molekularen Eigenschaften assoziiert, die z.B. in Form des PD-L1- und des NECTIN-4-Status relevant für moderne Immuntherapien oder Antikörper-Drugkonjugate sein könnten. Mit der anstehenden Zulassung von Erdafitinib (FGFR3-Inhibitor) werden in Zukunft auch molekulare Tumorboards für Patienten mit metastasiertem Urothelkarzinom an Bedeutung gewinnen.
Daily versus Twice Daily Nifedipine for Blood Pressure Control in Pregnancy and Postpartum
Authors: Peterson Jessica A. , Band Isabelle C. , Wang Kelly , Bianco Angela
Published: November 2024

Objective The objective of this study was to compare 60 mg daily (QD) extended released (XR) nifedipine to 30 mg twice daily (BID) for blood pressure (BP) control antepartum and postpartum.

Study Design This is a retrospective chart review conducted at the Mount Sinai Health System. Patients admitted from January 1, 2015, to April 30, 2021, diagnosed with a hypertensive disorder of pregnancy, who received nifedipine XR 30 mg BID or 60 mg QD for intrapartum or postpartum BP control were included. The primary outcome was the need for up-titration (i.e., the need for an increase in nifedipine dose or addition of another antihypertensive) after reaching one of the study doses (30 mg BID or 60 mg QD). Patients were excluded if they had preexisting renal disease or were already on oral antihypertensives. In a 1:1 ratio between single- and twice-daily dosing groups, the sample size needed to detect a 20% difference in up-titration rate to achieve 0.80 power is 97 patients per group, for a total of 194 patients. This is based on a Pearson chi-square test with a significance level of 0.05.

Results A total of 237 patients were included, 139 (59%) received 30 mg BID and 98 (41%) 60 mg QD. There was no statistically significant difference in the need for an increase in nifedipine dose or addition of another oral antihypertensive agent between those receiving 30 mg BID versus 60 mg QD (33.8 vs. 35.7%; adjusted odds ratio [aOR], 95% confidence interval [CI]: 0.90 [0.50–1.60]; p = 0.71). There was no difference in the need for emergency hypertensive treatment after reaching the study dose (p = 0.19) or readmission for BP control between groups (p > 0.99).

Conclusion These findings suggest that BID dosing does not confer better BP control in the antepartum or postpartum periods. Thus, daily dosing is reasonable and may be preferable for patient convenience and compliance.

Key Points
Nonlinear effects in a system comprising a large number of Josephson junctions
Authors: Khlus V. A. , Rozhavskii A. S. , Kulik I. O.
Published: November 2024

The behavior of a large number of Josephson junctions placed at the antinode of the electromagnetic field in a cavity resonator is investigated. It is shown that at sufficiently large currents through the junctions, a “coherent” state is formed in which the phases change synchronously and the total ac voltage equals the sum of the voltage amplitudes at all the junctions.
Electron structure of paramagnetic chromium and its change under pressure
Authors: Kulikov N. I.
Published: November 2024

Using an approximate method for the solution of the secular Korringa–Kohn–Rostoker equation (model Hamiltonian), a self-consistent calculation of the band structure and Fermi surface of paramagnetic chromium is performed for normal conditions and for a pressure of 270 kbar. Results of this calculation, based on “fundamental first principles,” agree well with experimental data on the de Haas-van Alphen effect and with x-ray emission spectra under normal pressure. The calculation predicts a tendency to change in electron structure under pressure. In particular, the value of the calculated logarithmic derivative of the spin density wave vector agrees satisfactorily with a recent measurement of this quantity.
Effect of inhomogeneities and measuring current on the current-voltage characteristics of superconducting nonsymmetric tunnel junctions
Authors: Chubov P. N.
Published: November 2024

It is shown experimentally that the shape of the current-voltage characteristics of superconducting nonsymmetric thin-film junctions depends on both the inhomogeneity of the films and the tunnel resistivity which determines the measurement current. Reproducible results consistent with the BCS theory were obtained only for low-resistance junctions in which the shape of the I-V curve is close to the theoretical shape. In the case of slight deviations from the theoretical I-V curve the smearing of the current jump at V≃ (Δ1 + Δ2)/e can be attributed to the superconductor with the higher Tc. Comparison of experiment with theory for highly inhomogeneous Al and Zn thin films revealed that the criteria for reckoning both the energy gap and Tc are important. Measurements on low-resistance aluminum-insulator-thallium and zinc-insulator-aluminum junctions yielded the following values for 2Δ (0)/kTc: 3.55±0.04 and 3.53±0.04 for Al films, 3.54±0.04 for thallium films, and 3.53±0.06 for zinc films.
Sparse Gaussian process based machine learning first principles potentials for materials simulations: Application to batteries, solar cells, catalysts, and macromolecular systems
Authors: Willow Soohaeng Yoo , Hajibabaei Amir , Ha Miran , Yang David ChangMo , Myung Chang Woo , Min Seung Kyu , Lee Geunsik , Kim Kwang S.
Published: November 2024

To design new materials and understand their novel phenomena, it is imperative to predict the structure and properties of materials that often rely on first-principles theory. However, such methods are computationally demanding and limited to small systems. This topical review investigates machine learning (ML) approaches, specifically non-parametric sparse Gaussian process regression (SGPR), to model the potential energy surface (PES) of materials, while starting from the basics of ML methods for a comprehensive review. SGPR can efficiently represent PES with minimal ab initio data, significantly reducing the computational costs by bypassing the need for inverting massive covariance matrices. SGPR rank reduction accelerates density functional theory calculations by orders of magnitude, enabling accelerated simulations. An optimal adaptive sampling algorithm is utilized for on-the-fly regression with molecular dynamics, extending to interatomic potentials through scalable SGPR formalism. Through merging quantum mechanics with ML methods, the universal first-principles SGPR-based ML potential can create a digital-twin capable of predicting phenomena arising from static and dynamic changes as well as inherent and collective characteristics of materials. These techniques have been applied successfully to materials such as solid electrolytes, lithium-ion batteries, electrocatalysts, solar cells, and macromolecular systems, reproducing their structures, energetics, dynamics, properties, phase-changes, materials performance, and device efficiency. This review discusses the built-in library universal first-principles SGPR-based ML potential, showcasing its applications and successes, offering insights into the development of future ML potentials and their applications in advanced materials, catering to both educational and expert readers.
A reaction network model of microscale liquid–liquid phase separation reveals effects of spatial dimension
Authors: Kim Jinyoung , Lawley Sean D. , Kim Jinsu
Published: November 2024

Proteins can form droplets via liquid–liquid phase separation (LLPS) in cells. Recent experiments demonstrate that LLPS is qualitatively different on two-dimensional (2D) surfaces compared to three-dimensional (3D) solutions. In this paper, we use mathematical modeling to investigate the causes of the discrepancies between LLPS in 2D and 3D. We model the number of proteins and droplets inducing LLPS by continuous-time Markov chains and use chemical reaction network theory to analyze the model. To reflect the influence of space dimension, droplet formation and dissociation rates are determined using the first hitting times of diffusing proteins. We first show that our stochastic model reproduces the appropriate phase diagram and is consistent with the relevant thermodynamic constraints. After further analyzing the model, we find that it predicts that the space dimension induces qualitatively different features of LLPS, which are consistent with recent experiments. While it has been claimed that the differences between 2D and 3D LLPS stem mainly from different diffusion coefficients, our analysis is independent of the diffusion coefficients of the proteins since we use the stationary model behavior. Our results thus give new hypotheses about how space dimension affects LLPS.
Rigidity transition of a highly compressible granular medium
Authors: Poincloux Samuel , Takeuchi Kazumasa A.
Published: November 2024

A wide range of disordered materials, from biological to geological assemblies, feature discrete elements undergoing large shape changes. How significant geometrical variations at the microscopic scale affect the response of the assembly, in particular rigidity transitions, is an ongoing challenge in soft matter physics. However, the lack of a model granular-like experimental system featuring large and versatile particle deformability impedes advances. Here, we explore the oscillatory shear response of a sponge-like granular assembly composed of highly compressible elastic rings. We highlight a progressive rigidity transition, switching from a yielded phase to a solid one by increasing density or decreasing shear amplitude. The rearranging yielded state consists of crystal clusters separated by melted regions; in contrast, the solid state remains amorphous and absorbs all imposed shear elastically. We rationalize this transition by uncovering an effective, attractive shear force between rings that emerges from a friction-geometry interplay. If friction is sufficiently high, the extent of the contacts between rings, captured analytically by elementary geometry, controls the rigidity transition.
BCL2 regulates antibacterial autophagy in the intestinal epithelium
Authors: Li Yun , Bel Shai , Benjamin Jamaal L. , Ruhn Kelly A. , Hassell Brian , Behrendt Cassie L. , Kuang Zheng , Hooper Lora V.
Published: November 2024

Autophagy is a key innate immune defense mechanism in intestinal epithelial cells. Bacterial invasion of epithelial cells activates antibacterial autophagy through a process that requires the innate immune adaptor protein MYD88, yet how MYD88 signaling connects to the autophagy machinery is unknown. Here, we show that the mouse intestinal pathogen
Salmonella
enterica Serovar Typhimurium (
Salmonella
Typhimurium) triggers MYD88 signaling that regulates binding of the anti-autophagy factor B cell lymphoma 2 (BCL2) to the essential autophagy protein Beclin1 (BECN1) in small intestinal enterocytes, a key epithelial cell lineage.
Salmonella
infection activated the kinase c-Jun N-terminal protein kinase 1 (JNK1) downstream of MYD88. JNK1 induced enterocyte BCL2 phosphorylation, promoting dissociation of the inhibitory BCL2–BECN1 complex and releasing BECN1 to initiate autophagy. Mice with BCL2 phosphorylation site mutations that prevent BCL2–BECN1 dissociation showed increased
Salmonella
invasion of enterocytes and dissemination to extraintestinal sites. These findings reveal that BCL2 links MYD88 signaling to enterocyte autophagy initiation, providing mechanistic insight into how invading bacteria trigger autophagy in the intestinal epithelium.
Methodological approaches to integrate gender analysis in One Health perspective at human-animal-ecosystem interface
Authors: Cataldo Claudia
Published: November 2024

The One Health approach considers the interdependence between environmental aspects, human and animal health, and promotes a multi-sectoral collaboration of policies, systems and processes that should be taken into account to prevent and mitigate emerging risks at human-animal-ecosystem interface. Gender is defined as the sum of roles and behaviors determined by the social context learned and adopted by men and women which lead to different identities and roles considered suitable for each of them. Men and women are systematically exposed to several factors that can affect their well-being; this exposure is influenced by gender, social rules and behaviors. It follows that gender analysis is an essential element to maximize the potential of One Health, and it is a lens to analyze, prevent and mitigate risks at the human-animal-ecosystem interface, more effectively, identifying in detail the target groups involved in specific contexts in a socio-ecological perspective.

One Health impact statement

The One Health approach to public health is a holistic approach that considers environmental sustainability, animal health, and human health together. Several factors including gender, age groups, cultures and social conditions may affect significantly the risk of diseases and their clinical evolution. Supplementing the One Health perspective with a gender analysis to study the Influence of social norms, activities, and risk behavior on exposure to infections, chemical pollution, and the consequences of climate change, could help to formulate targeted interventions and maximize the effectiveness of intersectoral approach at the human-animal-ecosystem interface. However, it is often ignored, but this inclusion is critical to the ongoing development of the One Health approach in prevention and preparedness to global threats in line with the recent socio-ecological principles.
Nap1 and Kap114 co-chaperone H2A-H2B and facilitate targeted histone release in the nucleus
Authors: Fung Ho Yee Joyce , Jiou Jenny , Niesman Ashley B. , Bernardes Natalia E. , Chook Yuh Min
Published: November 2024

Core histones, synthesized and processed in the cytoplasm, must be chaperoned as they are transported into the nucleus for nucleosome assembly. The importin Kap114 transports H2A-H2B into the yeast nucleus, where RanGTP facilitates histone release. Kap114 and H2A-H2B also bind the histone chaperone Nap1, but how Nap1 and Kap114 cooperate in transport and nucleosome assembly remains unclear. Here, biochemical and structural analyses show that Kap114, H2A-H2B, and a Nap1 dimer (Nap12) associate in the absence and presence of RanGTP to form equimolar complexes. A previous study had shown that RanGTP reduces Kap114’s ability to chaperone H2A-H2B, but a new cryo-EM structure of the Nap12•H2A-H2B•Kap114•RanGTP complex explains how both Kap114 and Nap12 interact with H2A-H2B, restoring its chaperoning within the assembly while effectively depositing it into nucleosomes. Together, our results suggest that Kap114 and Nap12 provide a sheltered path that facilitates the transfer of H2A-H2B from Kap114 to Nap12, ultimately directing its specific deposition into nucleosomes.
Gravitational reheating in Starobinsky inflation
Authors: Dorsch Gláuber C. , Miranda Luiz , Yokomizo Nelson
Published: November 2024

We investigate the possibility of achieving post-inflationary reheating exclusively through the gravitational interaction in Starobinsky inflation, which itself assumes nothing but gravity. We consider the possibility that the reheating sector couples to gravity via a non-minimal coupling. Our analysis is performed both in a perturbative and in a non-perturbative approach, where particle production is computed from Bogoliubov coefficients.
Our findings indicate that, for a minimal coupling, a reheating temperature T
reh ∼ 108 GeV is obtained, with a reheating duration of approximately 21 e-folds. We also show that non perturbative gravitational production during preheating can lead to maximum temperatures of the order of 1012 GeV. This shows that the gravitational interaction could be the sole responsible for reheating the Universe after inflation, without the need to assume other ad hoc inflaton interactions.
K-mouflage at high k: extending the reach of Hi-COLA
Authors: Gupta Ashim Sen , Fiorini Bartolomeo , Baker Tessa
Published: November 2024

The Hi-COLA (https://github.com/Hi-COLACode/Hi-COLA) code is an efficient dark matter simulation suite that flexibly handles the Horndeski family of modified gravity models. In this work we extend the scope of Hi-COLA to accommodate Horndeski theories with K-mouflage screening, allowing for the computation of matter power spectra in the non-linear regime in these models. We explore the boost of the dark matter power spectrum relative to GR-ΛCDM in K-mouflage gravity, and also discuss how large-scale structure computations change between the Einstein and Jordan frames. A dissection of the relative contributions of the modified background, linear growth, fifth force, and the conformal factor (a new inclusion to Hi-COLA) to the boost factor is presented. The ability of Hi-COLA to run with general Horndeski models and multiple screening mechanisms makes it an ideal tool for testing gravity with upcoming galaxy survey data.
CNN based approach for root zone soil moisture prediction by ground penetrating radar
Authors: Liu Kexin , Lu Qi , Guo Shilong , Liang Wenjing
Published: November 2024

Traditional soil moisture prediction methods often face challenges in providing spatially and temporally comprehensive root zone soil moisture (RZSM) with complex soil environment. In this paper, a novel method is proposed for predicting RZSM using images obtained from ground penetrating radar (GPR) data and processed with the convolutional neural network (CNN). The CNN encompasses two major stages: classification and regression. Initially, a CNN is tailored to classify tree root images obtained by GPR into distinct water content categories. Subsequently, through transfer learning, the pre-trained classification network is adapted for regression to predict continuous soil moisture levels. Then, the field experimental results demonstrate the efficacy and robustness of our approach, offering promising avenues for enhancing root zone water management and sustainability.
Deep learning-based cross-hole GPR travel time tomography
Authors: Cheng H , Hu S F , Zhao Y H
Published: November 2024

As a non-destructive geophysical detection method that is not limited by the target depth, cross-hole radar can accurately identify the positions and properties of underground cavities. Traditional cross-hole radar methods face significant challenges in stability, accuracy, and computational efficiency. In recent years, with the rapid development of deep learning and its remarkable achievements in the field of imaging, it has been applied in various fields. As a deep learning network structure for image segmentation, the Unet model can realize “end-to-end” image output. Therefore, the Unet model of convolutional neural network is introduced into cross-hole radar travel time tomography in this paper. A deep-learning trave time tomography method based on the nonlinear relationship between travel time data and models is proposed. Firstly, the models with cavities of different permittivities are constructed. The 2D traveltime images of transmitting and receiving pairs are calculated based on the GPR travel time fast-picking algorithm. Then, a Unet model is built to learn the nonlinear mapping relationship between the 2D travel time images and models with cavities. Finally, the intelligent travel time tomography method based on the Unet model of underground cavities is realized. Experiment results of models demonstrate the effectiveness of the proposed method.