bluuebunny/crossref_metadata_2025_split huggingface dataset:
Carbon negativity of black locust and poplar plantation in different management systems in Hungary
Authors: Mulyana Budi , Polgár András , Vityi Andrea 
Published: February 2025

Abstract
Carbon negativity is one of the promising strategies to uptake carbon emissions from the atmosphere and reduce carbon emissions to the atmosphere. Forests have been proven to sequester atmospheric carbon emissions through photosynthesis and store them as tree biomass. However, forest operations also emit carbon into the atmosphere via fertilizer, pesticides, and fuel consumption. This study aims to compare the carbon negativity of black locusts and poplar plantations in different management systems. Carbon dynamics in short and long-rotation systems was analysed using CO2FIX software. Meanwhile, the carbon emission in forest operations was estimated through the life cycle assessment method. In the simulation period of 45 years, black locust and poplar plantations in short and long-term management systems have shown carbon negativity. The amount of carbon sequestration was higher than carbon emission. Furthermore, carbon negativity in long-rotation management systems was better than in short-rotation coppice management systems.
Swelling kinetics of CNC-g-poly (acrylamide-co-graphene oxide) hydrogels at various GO mass
Authors: Sitorus Andika Steven , Sarah Maya , Harahap Hamidah 
Published: February 2025

Abstract
Cellulose nanocrystal (CNC) is a cellulose derivative in the form of crystalline rods with high biodegradability, mechanical strength, flexibility, ease of modification, and biocompatibility. The performance of CNC as an adsorbent can be elevated by grafting copolymerization using graphene oxide (GO). This study assesses the capacity and swelling kinetics of CNC-g-poly(acrylamide-co-graphene oxide) hydrogels at various GO masses. CNC-g-poly(acrylamide-co-graphene oxide) hydrogels were synthesized using CNC derived from sugarcane bagasse, then functionalized with acrylic acid (AA), acrylamide (AM), and GO, with potassium persulfate initiator and the addition of MBA (N, N-methylene bisacrylamide) as a cross-linking agent. Hydrogel synthesis was performed with varying GO mass of 0 mg, 20 mg, 40 mg, 60 mg, and 80 mg (coded as P0, P20, P40, P60, and P80). Hydrogel swelling capacity and kinetics studies were carried out in pH 2-7. The swelling capacity of all hydrogels increased along with increasing pH, where the largest swelling capacity was obtained at pH 7. P-40 is the best hydrogel, with a diffusion coefficient value of 0.0356 cm2/s, swelling constant of 0.2850, a swelling rate of 0.0484 g water/g hydrogel.min, and a swelling rate constant of 3.9302 g hydrogel/g water.min.
Study of the distribution of domestic wastewater from septic tank in silt-type soil
Authors: Herlina Netti , Faisal Muhammad , Husin Amir , Ardiansyah Edi Yasa , Gulo Emmanuel , Rezki Muhammad 
Published: February 2025

Abstract
The current increase in population continues to encourage intensive development, especially residential development. Continuous development has an impact on people’s lives, especially in the management of domestic wastewater. People generally use septic tanks to manage household domestic wastewater, but this often does not comply with the provisions stipulated in Standar Nasional Indonesia (SNI), so it has the potential to pollute shallow groundwater. This simulation was carried out in a 100 cm x 100 cm x 40 cm glass box. The research aims to determine the distribution distance, travel time, and flow rate of septic tank wastewater spreading inside the glass box. The distribution simulation is carried out at scale testing between laboratory and existing conditions of 1:10. The results showed that contaminants concentration decreased through the soil, with a removal efficiency of 75.6% for E. coli and 65.9% for Ammonia. The simulation results showed that horizontal spread in the glass box at a distance of 80 cm required a travel time of 565 minutes (9 hours and 25 minutes) with wastewater spread speed/flow rate of 7,2 x 10−3 litres per minute. This test concluded that the concentration of Escherichia coli and ammonia at a distance of 8 m from the source of wastewater spread does not meet the quality standard as a clean water resource.
Analysis of energy output variations in a 4.5 kWp residential solar system in Surabaya, Indonesia
Authors: Tarigan Elieser 
Published: February 2025

Abstract
This study evaluates the performance of a residential photovoltaic (PV) system located in Surabaya, Indonesia. The system, with a capacity of 4500 Wp and connected to the grid via an On-Grid inverter. Utilizing real-time data collection through EyeM4 Wi-Fi and the iSolarcloud application, the power and energy output were analyzed over daily, monthly, and annual periods. The monthly energy output showed significant seasonal variations, with the highest production recorded in December at 654.30 kWh and the lowest in February at 420.00 kWh. Daily energy outputs also varied, peaking at 25.50 kWh in March and dropping to as low as 7.20 kWh in February. The daily average energy output ranged from 14.00 kWh in February to 21.81 kWh in December. Detailed analyses of power output on typical sunny and rainy days further highlighted the impact of weather conditions on system performance. On sunny days, the system reached a daily energy output of 23.2 kWh, while on rainy days, it was significantly lower at 7 kWh. This study provides a comprehensive understanding of the PV system’s operational characteristics and highlights the influence of seasonal and daily weather patterns on energy production.
Disruption prediction and mitigation strategies in the EHL-2 spherical torus
Authors: CAI 蔡 Jianqing 剑青 , LIANG 梁 Yunfeng 云峰 , CHEN 陈 Zhongyong 忠勇 , ZHENG 郑 Wei 玮 , HU 胡 Di 地 , XUE 薛 Lei 雷 , LIN 林 Zhifang 志芳 , GU 顾 Xiang 翔 , Team the EHL-2 
Published: February 2025

Abstract
EHL-2 is a compact, high-field spherical tokamak designed to explore the potential of an advanced p-11B nuclear fusion reactor. Due to its high plasma current and thermal energy, it is crucial to mitigate the impact associated with disruptions to ensure the safe operation of EHL-2. This paper evaluates the performance requirements of the disruption prediction system on EHL-2, with a particular focus on applying generalizable knowledge transfer from existing devices to future ones. Furthermore, the key characteristics of disruption mitigation strategies are analyzed, and their overall mitigation performance on EHL-2 is assessed. This insight provides valuable guidance for optimizing the engineering design of EHL-2 and identifying its optimal operational regime.
Soil properties and fenugreek (Trigonella foenum-graecum L) growth, yield and quality as affected by tillage systems, crop rotation and nitrogen fertilization under semi-arid climatic conditions
Authors: Mechri Mouna , Othmani Afef , Raza Taqi , Patil SB , Bouajila Khedija , Ziadi Noura , Beltayef Hayet , Gharbi Azaiez , Hashem Abeer , Alfagham Alanoud , Abd_Allah Elsayed Fathi , Jedidi Naceur 
Published: February 2025

Abstract
Adopting sustainable agricultural practices is considered as an effective strategy to mitigate climate change and to improve soil health and crop production.This study aims to assess the impact of tillage systems (no-tillage (NT) and conventional tillage (CT)), crop rotation (faba beans - oat and faba beans - durum wheat) and nitrogen fertilization rates (0, 20 and 40 kg N.ha−1) on soil properties and growth and yield of fenugreek. Soil samples were collected at two stages: at the 50% blossoming stage and after harvest and fenugreek quality and yield and its components were measured.The results showed that tillage systems and crop rotation treatments had great influence on soil properties. In general, the highest soil organic carbon (SOC) (13.4 and 14.2 g.kg−1), total nitrogen (1.0 and 1.1 g.kg−1), nitric nitrogen (75.73 and 62.42 mg.kg−1), ammonium-nitrogen (14.90 and 19.08 mg.kg−1). were recorded in no tillage practice with durum as a previous crop at 50% blossoming and harvest stage respectively. Exception for SOC, the highest nitrogen fertilization rate improved most of soil variables at both growth stages. Greater biomass and grain protein content were obtained under NT system and 40 kg N.ha−1. Previous crops had no effect on grain protein content. Also, there was a significant synergy among soil fertility and fenugreek production. Conservation tillage, durum wheat previous crop and highest nitrogen fertilization rate gave the best aboveground biomass, yield and yield attributes performances. Overall, NT associated with durum wheat as a previous crop and nitrogen fertilization (40 kg N.ha−1) are the suitable combination to improve both soil quality, and fenugreek yield.
Machine learning-driven prediction and digital twins implementation for VOC emissions in VAT photopolymerization additive manufacturing
Authors: Matoc Dhal A , Kanabar Bhavesh K , Sata Amit 
Published: February 2025

Abstract
With the growing adoption of additive manufacturing (AM) technology across various industries, concerns regarding the possible release of hazardous volatile organic compound (VOC) emissions have surfaced, particularly in VAT photopolymerization (VPP) processes. This study investigates VOC emissions in VPP AM by implementing machine learning (ML) and advanced digital twins to monitor, predict, and mitigate VOC release. An Industrial Internet of Things (IIoT) sensor network, integrated with an Anycubic Mono X 6 K 3D printer, captured data on critical parameters, including layer thickness, exposure time, and light intensity. Subsequent ML model analysis identified exposure time as a principal factor influencing VOC emissions. A Unity-based digital twin was developed to support proactive process optimization, offering real-time visualization and predictive analytics of emission trends. The system aligns with Industry 4.0 objectives, showing considerable potential to enhance operational efficiency and environmental sustainability in VPP AM. This integrated approach significantly advances environmentally responsible AM practices in industrial settings.
A deep learning framework for intrusion detection system in smart grids using graph convolutional network
Authors: Basheer Liloja , P Ranjana 
Published: February 2025

Abstract
Smart grids are an emergent concept that has evolved from combining renewable energy source integration, digital communication advances, and increasing demands for dependable electricity supply. However, although these modernized grids make the process very efficient and reliable, at the same time, the increased vulnerability to cyberattacks makes the need for Intrusion Detection Systems robust, as these infrastructures are critical ones. Traditional intrusion detection systems frequently tend to be inadequate in managing the intricacy and continually evolving nature of threats associated with smart grids. This paper presents a streamlined deep-learning approach for developing an IDS. The process involves the following: a) Data Collection: DNP3 is widely used in most CIs across the United States for industrial communication protocol. It permits remote access between ICS and SCADA systems. b) Preprocessing using Encoding and Normalisation techniques to avoid anomalies and noises from the raw dataset, c) Feature Extraction for extracting features of the smart grid using Autoencoder, and d) Detection using Graphical Convolutional Network (GCN). GCN-based IDS demonstrates superior potential in identifying sophisticated cyber threats, ensuring real-time detection, and maintaining the integrity and reliability of smart grids. The experimental analysis’s findings show that the recommended approach outperforms current cutting-edge models, displaying exceptional sensitivity (0.98), specificity (0.98), accuracy (0.95), and F1 score (91).
Inferring Interpretable Models of Fragmentation Functions using Symbolic Regression
Authors: Makke Nour , Chawla Sanjay 
Published: February 2025

Abstract
Machine learning is rapidly making its path into sciences, including high-energy physics. We present the first study that infers, directly from data, a functional form of fragmentation functions involved in the description of hadron production in high-energy physics processes. Fragmentation functions can not be calculated in theory and have to be determined from data. This is achieved by applying symbolic regression on experimentally measured charged hadron multiplicities. Traditional approaches rely on global fits of experimental data by pre-assuming a functional form to learn its parameters. These functions are a key element in the description of physical observables measured at LHC and the future EIC. The function learned by symbolic regression resembles the Lund string function and describes the data well.
Figuring Death in Classical Athens
Authors: Clifford Emily 
Published: February 2025

Abstract
Figuring Death in Classical Athens puts art and literature in conversation to explore how ancient Athenians grappled with the uncertainties of death. How did objects and texts generate thinking about what death is and might be like? Were Athenians aware of the imaginative frameworks that underpinned their thinking? Did they worry not just about death, but whether they could figure it out? The book takes a fresh approach to the study of ancient death, cutting across sub-disciplines (art, text, philosophy) to build a picture of how ancient art and literature got their audiences thinking—thinking not just about death but about its knowability. Whether in the theatre, at the symposium, or on the Acropolis, representations of death challenged Athenians by presenting problems of exteriority (how can the living know what dying might be like?) and particularity (can one person’s experience hold for another? is death truly a ‘leveller’?). Chapters offer close readings of Plato’s Phaedo, Sophocles’ Oedipus at Colonus, and Thucydides’ account of the plague and detailed analyses of drinking cups, funerary jugs, and the west frieze of the temple of Athena Nike on the Acropolis. The book also includes discursive intermediary chapters looking at Archaic material and at visual and literary representations of the deaths of Alcestis and Niobe.
Death Comes as the End
Authors: Clifford Emily 
Published: February 2025

Abstract
This chapter examines how Plato deals with the literary challenge of getting close to the moment of Socrates’ death as an outsider and how this ecphrastic problem contributes to the dialogue’s explicit philosophical enquiry into death. It begins by considering how Plato employs his mediated literary medium to reflect upon the difficulty of encountering someone else’s death. Then, turning to the internal viewpoints of those that attended Socrates’ final moments, it shows how Plato harnesses narrative to reflect upon death as a significant but asymptotic moment, a climax anticipated by the forward-facing viewpoints of the living. Finally, it explores one passage in which Plato takes an imaginative vault into the mind of the dying Socrates as he, in turn, struggles to grasp the unfathomable abyss of death.
getENRICH: a tool for the gene and pathway enrichment analysis of non-model organisms
Authors: Bhatia Ajay , Pruthi Pranjal , Chakraborty Isha , Shukla Nityendra , Narayan Jitendra 
Published: February 2025

Abstract

Motivation
The Gene Ontology system facilitates the functional annotation of genes by categorizing them into specific biological processes, cellular components, and molecular functions. Despite numerous tools like DAVID and Enrichr, analysing non-model organisms remains challenging due to a lack of genetic information and available tools.

Results
To address this, we present getENRICH, a comprehensive tool for gene enrichment analysis tailored for non-model organisms. Available in both command-line and web-based graphical user interface (GUI) formats, getENRICH facilitates user-friendly interaction for gene dataset uploads, parameter configuration, and visualization. getENRICH employs hypergeometric distribution for P-value calculation and Benjamini–Hochberg correction for multiple testing.

Availability and implementation
getENRICH is freely available under the MIT license, with the source code, documentation, and example datasets available on GitHub (https://github.com/jnarayan81/getENRICH) and the GUI version available at https://getenrich.igib.res.in/.
Putaminal-cortical circuits predict response of bilateral deep brain stimulation of the subthalamic nucleus in the primary Meige syndrome after 5 years
Authors: Wang Ning , Wu Yifeng , Yao Chen , Meng Dawei , Zhang Haoran , Cheng Qinxiu , Zhang Xiaodong , Shen Hailiang , Lu Yingqi , Wang Lin , Xu Jinping 
Published: February 2025

Abstract
The deep brain stimulation (DBS) in the subthalamic nucleus (STN) has attracted more attention for primary Meige syndrome due to easier target location and lower power consumption. However, potential and reliable preoperative predictors of longitudinal outcomes of STN-DBS to guide therapeutic decisions remain largely unexplored. Herein, we used preoperative structural MRI and Burke–Fahn–Marsden Dystonia Rating Scale (BFMDRS) from 55 patients with primary Meige syndrome who finished STN-DBS after 5 years. They were further classified into response (n = 23) and super-response (n = 32) based on the improvement rates of BFMDRS. Voxel-based morphology, partial correlation analyses, receiver operating characteristic (ROC) analyses and support vector machine were performed. We identified that improved rates of BFMDRS were 63, 71.97, 76.64, 79.51, 81.02, 81.36, 81.16, 80.80 and 80.93% at 1, 3, 6, 12, 18, 24, 36, 48 and 60 months after STN-DBS, respectively, and remained steady across 1–5 years. Further voxel-based morphology analyses revealed significantly lower grey-matter volume in the right hippocampus, left putamen, right supramarginal gyrus and left superior frontal gyrus in response when compared with super-response. The grey-matter volumes in the left putamen, right supramarginal gyrus and left superior frontal gyrus were not only positively correlated with improvement rates of BFMDRS after STN-DBS for 5 years in the primary Meige syndrome, but also presented a reliable classification ability in distinguishing response and super-response (area under curve = 0.855). These results suggested that STN-DBS is an effective treatment for primary Meige syndrome, and preoperative grey-matter volume of putaminal-cortical circuits could be used as potential biomarkers to predict longitudinal outcomes.
Dysregulation of G6PD by HPV E6 exacerbates cervical cancer by activating the STAT3/PLOD2 pathway
Authors: Zhang Jie , Dong Wei , Yang Qin , Liu Li-Na , Cai Xi-Lun , Wang Dan , Yan Guo-Ji , Xiyang Yan-Bin , Hu Tao , Zhang Jie 
Published: February 2025

Abstract
High-risk human papillomavirus (HPV) infection is strongly linked to the initiation and progression of cervical cancer, yet the precise molecular mechanisms involved remain partially understood. This investigation examined differential protein expression profiles in various cohorts, including healthy controls and HPV-positive cervical cancer patients with different expression levels of glucose-6-phosphate dehydrogenase (G6PD), shedding light on the dysregulation of oncogenic proteins by HPV. Proteomic analysis of cervical tissues revealed specific protein signatures, indicating significant upregulation of HPV E6, G6PD, STAT3, phosphorylated STAT3, and procollagen-lysine 2-oxoglutarate 5-dioxygenase 2 (PLOD2) in HPV-infected cervical cancer tissues and cell lines. Functional experiments, involving the manipulation of G6PD and STAT3 activities in cervical cancer cells with HPV E6 modulation, demonstrated that dysregulated G6PD enhanced cell proliferation, migration, and invasion while suppressing apoptosis, primarily through the STAT3/PLOD2 pathway. Integrating these findings with the existing literature underscores the role of G6PD as an oncogene, potentially under STAT3 regulation, and highlights the role of PLOD2 as a pivotal factor in cervical cancer progression. This study also proposed a mechanism in which HPV E6-induced dysregulation of G6PD activates the STAT3-PLOD2 axis to promote cervical cancer progression. Understanding the intricate interplay between HPV E6, G6PD, STAT3, and PLOD2 offers valuable insights into the molecular landscape of cervical cancer. These findings may pave the way for targeted therapeutic approaches aimed at disrupting this axis to mitigate the progression of cervical cancer.
Ammonium chloride mitigates the amplification of fish virus by blocking autophagy-dependent replication
Authors: Chen Dan-Dan , Zhang Jia-Xin , Li Zhuo-Cong , Zhang  Can , Xu Xiao , Cui Bao-Jie , Xu Na , Wang Yang-Yang , Zhou Chu-Jing , Zhou Li , Lu Long-Feng , Li Shun 
Published: February 2025

Abstract
Ammonia fertilizer, primarily composed of ammonium chloride, is widely used in pond fish farming throughout Asia. Despite the belief that it possesses antiviral properties, the underlying mechanisms remain unclear. Ammonium chloride (NH4Cl) has been demonstrated to act as a potent inhibitor of autophagy, which is used by many fish viruses to promote their proliferation during infection. It was therefore hypothesized that the antiviral effect of ammonia fertilizers was likely due to the inhibition of autophagy in viruses. The present study sought to evaluate the antiviral effect of NH4Cl in a model of several fish cells and zebrafish. The findings demonstrated that the administration of NH4Cl after viral infection inhibited the proliferation of a variety of fish viruses, encompassing both DNA and RNA viruses. Further studies have indicated that NH4Cl obstructed autophagy-dependent virus proliferation of spring viremia of carp virus (SVCV) by inhibiting autophagic flux. The molecular mechanism revealed that SVCV contributed to the polyubiquitination of interferon regulatory factor 3 (IRF3) and promoted the degradation of IRF3 through cargo receptor sequestosome 1 (SQSTM1/p62)–mediated selective autophagy. However, NH4Cl was observed to inhibit SVCV-mediated selective autophagy of IRF3, thereby facilitating the production of interferon. Furthermore, the SVCV N protein was of critical importance in this process. Nevertheless, NH4Cl impeded this degradation process by inhibiting the autophagy pathway. The study found that NH4Cl was highly efficacious in controlling fish virus infection both in vivo and in vitro. It can therefore be concluded that the antiviral effect of ammonia fertilizers was, at least in part, due to the inhibition of viral autophagy.
A Case Report of Severe Bradycardia Associated With Nirmatrelvir-ritonavir Drug-drug Interactions
Authors: Fu Zhiqing , Guo Yan , Li Shuai , Shi Yang 
Published: February 2025

Abstract
With the increasing use of nirmatrelvir-ritonavir in older COVID-19 patients, adverse drug reactions due to drug-drug interactions have become more frequent. This report describes a patient who experienced severe bradycardia and hypotension following the concurrent use of heart rate-control medications and nirmatrelvir-ritonavir during an active COVID-19 infection. This suggests that clinicians should be cautious when dealing with nirmatrelvir-ritonavir and try their best to avoid serious adverse reactions.