bluuebunny/crossref_metadata_2025_split huggingface dataset:
Recommendation of excavation method and support system based on rock mass classification of the Matenggeng Dam Tunnel, Cilacap, Central Java
Authors: Firdausi A A , Setianto A , Indrawan I G B 
Published: March 2024

Abstract
The Matenggeng Dam is situated in Matenggeng village, Dayeuhluhur, Cilacap district, Central Java. It features a diversion channel equipped with a tunnel that has a diameter of five meters and is formed like a horseshoe. Therefore required engineering geological analysis for tunnel planning. The purpose of this study is to ascertain the tunneling technique and the corresponding support systems. This study will provide suggestions and input before and during the construction. This research uses rock mass classification and the Point Load Test for several samples. Tunneling method and support systems using empirical method Rock Mass Rating (RMR) and Geological Strength Index (GSI). The study location is composed of sandstone, conglomerate, andesite, and siltstone with alluvium deposits in Cijolang River area. Classification of rock masses is fair to good rock. The GSI and RMR analyses suggest that the excavation technique uses hammer and blasting methodologies and a max stand-up time without support of 20 to 144 hours. The tunneling method uses top heading and bench and support systems using rock bolts, wire mesh, shotcrete, and steel sets.
Indigenous community governance in marine conservation: A bibliometric analysis
Authors: Sejati A A , Sudarmo  , Haryanti R H 
Published: March 2024

Abstract
Maintaining marine sustainability and biodiversity requires support and cooperation from the government, stakeholders, and community. Indigenous communities have the right to restoration and protection of the environment and productive capacity of land, territory, sea, and all their natural resources. Research on community governance has been carried out by many researchers with increasingly developing topics. Including topics about indigenous peoples and natural resource conservation. This research aims is to determine the development of research trends regarding community governance of indigenous communities in marine conservation. The data source is literature in the Scopus database and the data analysis uses bibliometric analysis of indigenous community governance in marine conservation publications. The results are the research of indigenous communities governance in marine conservation from the first publication in 2006 has tended to increase. Although in certain years it has decreased or there have been no publications at all. The research become an interesting topic because it related with environmental science and indigenous communities have a big role in implementing marine conservation. This conservation has been going for a long time and passed down from generation to generation. The recommendation of this research is legal recognition for indigenous peoples to protect their rights.
Vis/NIR reflectance spectroscopy for non-destructive diagnosis of Fusarium spp. infection in postharvest potato tubers (Solanum tuberosum)
Authors: Prasetyo E W , Amanah H Z , Farras I , Pahlawan M F R , Masithoh R E 
Published: March 2024

Abstract
Conventional methods of detecting Fusarium spp. infection, which causes significant economic losses in potato production, are time-consuming and expensive. This study explored rapid and non-destructive detection techniques using visible/near-infrared (Vis/NIR) spectroscopy. Potato seeds of the Granola L variety were intentionally infected with Fusarium spp. by fungal inoculation, then stored at 12°C, 25°C, and a combination of both. Healthy potatoes were stored under the same conditions in containers for 30 days and monitored every five days. Principal component analysis-linear discriminate analysis (PCA-LDA) was used to classify potato tubers based on their infection status. PCA-LDA analysis revealed significant spectral differences between healthy and infected potato seeds across all storage temperatures. Calibration reliability values were 95.87% (for samples stored at 12°C), 97.52% (stored at 25°C), and 98.35% (for the combination of 12°C and 25°C). Similar trends were observed for accuracy: 91.96% (12°C), 98.29% (25°C), and the highest accuracy of 98.65% for the combined temperature. These techniques facilitate rapid identification of infections, aiding farmers and producers in implementing more efficient preventive actions, resulting in decreased crop losses and waste products and enhanced productivity in the agricultural sector.
Household food waste in Surakarta City, Indonesia: Quantity, global warming potential (GWP), and management
Authors: Rohmah M N , Setyono P , Utami T 
Published: March 2024

Abstract
Households represent one of the main contributors to food waste in urban areas. Surakarta is one of the cities in Indonesia where a significant portion of household food waste is disposed of in landfill sites. The piles of food waste can become an environmental issue if left unmanaged, as they generate greenhouse gas emissions that contribute to global warming. The aim of this research is to determine the quantity, emission estimations, and management of household food waste in Surakarta City. A total of 151 household samples had their food waste collected over a period of 7 days. The method for measuring the quantity of food waste involved direct measurements using a scale, calculating food waste emissions using the GWP formula, and collecting management data through a questionnaire. The research results indicate that, on average, households dispose of 0.499 kg/week of food waste and estimate food waste emissions to be 0.789 kg CO2e/week. In addition to being discarded, some food waste is managed as animal feed and fertilizer. Implementing proper and sustainable management can lead to a reduction in the quantity of food waste sent to landfills.
Bioremediation to Overcome Microplastic Contamination in The Water Environment
Authors: Khoiriyah Siti , Dian Syaputra Mei 
Published: March 2024

Abstract
Microplastics are a global environmental issue that is receiving increasing attention. Microplastic particles, which are plastic fragments measuring less than 5 mm, are widely distributed worldwide and have negative impacts on the environment, living organisms, and human health. Bioremediation is one method to address this problem, using living organisms to remove microplastics from the environment. Bioremediation involves the use of living organisms, such as bacteria, algae, worms, and other organisms, to clean up or degrade microplastics that are widely dispersed in the environment. This article explains the concept and role of bioremediation in addressing microplastic contamination, the factors influencing its effectiveness, and the advantages and challenges of using bioremediation. This article is a systematic literature review. The data used in this research consist of 23 scientific articles, with 21 indexed in Scopus and 2 indexed in Google Scholar. Through this article, it is hoped to obtain comprehensive insights into the future potential of sustainable bioremediation technology in addressing the issue of microplastic contamination in aquatic environments.
Substantiating the rational parameters for a complicated non-transport system when mining low-thickness fireclay deposits
Authors: Chebanov Maksym , Sobko Borys , Petlovanyi Mykhailo 
Published: March 2024

Abstract
The paper examines a complicated non-transport system for mining a gently sloping fireclay deposit using ESH-10/70 dragline excavators. The research purpose is to substantiate the technological scheme of stripping operations and determine their parameters to reduce the strip-mining costs. Theoretical research is performed using the following methods: methods of scientific analysis of theoretical research, as well as practices of project and production organizations; mining-geometric calculations; variant method for comparing and selecting a mining system. As a result, the dependence of the excavator block mining velocity on the entry way width has been determined, which makes it possible to study the relationship between mining and stripping equipment in time. The change in the re-excavation coefficient depending on the width of the dragline excavator entry way has been studied and its rational value has been determined. The practical value of the research results is in the substantiation of an effective system for mining a gently sloping fireclay deposit.
Germanium resource provision from mineral deposits in Ukraine
Authors: Lozhnikov Oleksii , Pavlychenko Artem , Shustov Oleksandr , Dereviahina Nataliia 
Published: March 2024

Abstract
The article is devoted to determining the resource potential of Ukraine in supplying industry with germanium. Statistical information on the potential content of germanium in various types of mineral raw materials located on the territory of Ukraine is summarized. The trends of the world market of germanium consumption in industry have been established. The value of the average content of germanium in coal deposits of the Lviv-Volynsky and Donetsky basins is given. It has been established that the greatest potential for germanium extraction is found in lignite deposits, the content of the valuable mineral in which can be ten times higher than that of hard coal. According to the results of research, germanium is found in the condition standards in ferruginous quartzites of the Annivske deposit of Kryvbas, Horishno-Plavnenske, Lavrykivske and Bilanivske deposits of the Kremenchuk district. The average content of germanium in ore deposits formed from magnetite, hematite, ribeckite, etc. was also determined. The approximate resource availability of germanium contained in deposits of coal, ore and non-ore raw materials of Ukraine was determined.
Research of land-saving schemes of mining the horizontal sedimentary mineral deposits
Authors: Adamchuk Andrii , Pavlychenko Artem , Shustov Oleksandr , Bondarenko Andrii 
Published: March 2024

Abstract
Technological mining transport schemes of open development of horizontal sedimentary deposits are considered. Various land-saving technological schemes for transportation of minerals in the absence of a capital trench have been developed. The dependence of the mineral transportation cost on the production capacity of the mine for the developed schemes was established. The research has been carried out for conditions of surface mining manganese deposits of Nikopol Basin. Transport schemes using mobile steeply inclined conveyor are offered. The developed technological solutions for the conditions of surface mining of deposits of the Nikopol manganese ore basin allow not only to reduce the amount of disturbed land, but also to reduce the cost of minerals by reducing its transportation distance by 2 km. The proposed transport schemes will make it possible to obtain an economic effect in the amount of 1–3 million UAH.
GATE Monte Carlo approach to heterogeneity dose distribution in small fields used in radiation therapy
Authors: Elcadi Z A , El Moussaoui M , Aouadi S , Sukumaran R , Hammoud R , Al-Hammadi N , Toufique Y , Bouhali O 
Published: March 2024

Abstract
The Accurate dosage prediction in Radiation Therapy is challenging, prompting a need for precision beyond conventional clinical Treatment Planning Systems (TPS). Monte Carlo-based methods are sought for their superior accuracy. The aim of this study is to compare dose distributions between the ACUROS algorithm and the GATE platform in various tissue densities and field sizes, focusing on smaller fields. This study was initiated with a homogeneous validation of the TrueBeam STX system, using measurements obtained from the Centre Hospitalier Interregional Edith Cavell (CHIREC) in Brussels. The validation compared dosimetric functions (Percentage Depth Dose (PDD), Dose profile (DP) and Collimator scatter fraction (CSF)) employing the GAMMA index with a 2% / 2 mm criterion tolerance. Following this, heterogeneous studies examined dose distributions between the ACUROS algorithm and the GATE platform in various tissue densities and field sizes, with a specific focus on smaller fields. Simulations were conducted using both platforms on chest phantoms with heterogeneous slabs representing bone, lung, and heart, each housing a central tumor. The impact of electronic equilibrium on tumors for different small field sizes was evaluated. Results showed a remarkable 99% agreement between measurements and GATE calculations in the homogeneous validation of the TrueBeam STX system. However, in heterogeneous studies, ACUROS consistently overestimated lung doses by up to 8% compared to GATE simulation, especially evident with a flattening filter and smaller beam sizes at density interfaces. This highlights significant dose estimation discrepancies between ACUROS and GATE, emphasizing the need for precise calculations. The findings support exploring Monte Carlo-based methods for enhanced accuracy in Radiation Therapy treatment planning.
Rotor fault characterization study by considering normalization analysis, feature extraction, and a multi-class classifier
Authors: Barstuğan Mücahid , Arabacı Hayri 
Published: March 2024

Abstract

Background. Rotor faults are the most common malfunctions encountered, especially during the manufacturing stage, in asynchronous motors. These faults cause vibration in the motor torque and a decrease in efficiency. In recent years, the detection of rotor faults has been done using motor current. The reflection of rotor faults on motor current depends on slip, and therefore, the effect increases as the current grows. Good results are achieved in fault detection at nominal loads. However, especially when motor manufacturers are considered, testing the motor by loading it requires expensive testing equipment and long-term test procedures. Therefore, the detection of faults in the motor at no load is emphasized. However, since the effect of the fault decreases when the motor is at no load, fault detection becomes difficult. Generally, small-level faults cannot be detected. Objective. This study focuses on fault detection from the motor current at no load. The development current at no load was used to eliminate the negative effects of slip. However, since the slip is not constant, the change in frequency and amplitude values to be used as a feature makes the diagnosis difficult. Method. In this study, the spectrogram was used to evaluate the change during the start-up time. Thus, a standard dataset was determined for comparison. The texture properties of the spectrogram image were extracted using various methods. The extracted features were subjected to normalization analysis and classified using the k-NN algorithm. Results. In the classification phase, a classification accuracy of 98.66% was achieved using the k-NN method, and it was seen that the proposed method could be used for the detection of rotor faults. Conclusions. The study has successfully demonstrated that broken rotor bar faults in asynchronous motors can be diagnosed using the motor start-up data.
Measurement properties of the usual and fast gait speed tests in community-dwelling older adults: a COSMIN-based systematic review
Authors: Mehdipour Ava , Malouka Selina , Beauchamp Marla , Richardson Julie , Kuspinar Ayse 
Published: March 2024

Abstract

Objective
The gait speed test is one of the most widely used mobility assessments for older adults. We conducted a systematic review to evaluate and compare the measurement properties of the usual and fast gait speed tests in community-dwelling older adults.

Methods
Three databases were searched: MEDLINE, EMBASE and CINAHL. Peer-reviewed articles evaluating the gait speed test’s measurement properties or interpretability in community-dwelling older adults were included. The Consensus-based Standards for the selection of health Measurement Instruments guidelines were followed for data synthesis and quality assessment.

Results
Ninety-five articles met our inclusion criteria, with 79 evaluating a measurement property and 16 reporting on interpretability. There was sufficient reliability for both tests, with intraclass correlation coefficients (ICC) generally ranging from 0.72 to 0.98, but overall quality of evidence was low. For convergent/discriminant validity, an overall sufficient rating with moderate quality of evidence was found for both tests. Concurrent validity of the usual gait speed test was sufficient (ICCs = 0.79–0.93 with longer distances) with moderate quality of evidence; however, there were insufficient results for the fast gait speed test (e.g. low agreement with longer distances) supported by high-quality studies. Responsiveness was only evaluated in three articles, with low quality of evidence.

Conclusion
Findings from this review demonstrated evidence in support of the reliability and validity of the usual and fast gait speed tests in community-dwelling older adults. However, future validation studies should employ rigorous methodology and evaluate the tests’ responsiveness.
polyGBLUP: a modified genomic best linear unbiased prediction improved the genomic prediction efficiency for autopolyploid species
Authors: Song Hailiang , Zhang Qin , Hu Hongxia 
Published: March 2024

Abstract
Given the universality of autopolyploid species in nature, it is crucial to develop genomic selection methods that consider different allele dosages for autopolyploid breeding. However, no method has been developed to deal with autopolyploid data regardless of the ploidy level. In this study, we developed a modified genomic best linear unbiased prediction (GBLUP) model (polyGBLUP) through constructing additive and dominant genomic relationship matrices based on different allele dosages. polyGBLUP could carry out genomic prediction for autopolyploid species regardless of the ploidy level. Through comprehensive simulations and analysis of real data of autotetraploid blueberry and guinea grass and autohexaploid sweet potato, the results showed that polyGBLUP achieved higher prediction accuracy than GBLUP and its superiority was more obvious when the ploidy level of autopolyploids is high. Furthermore, when the dominant effect was added to polyGBLUP (polyGDBLUP), the greater the dominance degree, the more obvious the advantages of polyGDBLUP over the diploid models in terms of prediction accuracy, bias, mean squared error and mean absolute error. For real data, the superiority of polyGBLUP over GBLUP appeared in blueberry and sweet potato populations and a part of the traits in guinea grass population due to the high correlation coefficients between diploid and polyploidy genomic relationship matrices. In addition, polyGDBLUP did not produce higher prediction accuracy than polyGBLUP for most traits of real data as dominant genetic variance was not captured for these traits. Our study will be a significant promising method for genomic prediction of autopolyploid species.
BioNexusSentinel: a visual tool for bioregulatory network and cytohistological RNA-seq genetic expression profiling within the context of multicellular simulation research using ChatGPT-augmented software engineering
Authors: Matzko Richard Oliver , Konur Savas 
Published: March 2024

Abstract

Summary
Motivated by the need to parameterize ongoing multicellular simulation research, this paper documents the culmination of a ChatGPT augmented software engineering cycle resulting in an integrated visual platform for efficient cytohistological RNA-seq and bioregulatory network exploration. As contrasted to other systems and synthetic biology tools, BioNexusSentinel was developed de novo to uniquely combine these features. Reactome served as the primary source of remotely accessible biological models, accessible using BioNexusSentinel’s novel search engine and REST API requests. The innovative, feature-rich gene expression profiler component was developed to enhance the exploratory experience for the researcher, culminating in the cytohistological RNA-seq explorer based on Human Protein Atlas data. A novel cytohistological classifier would be integrated via pre-processed analysis of the RNA-seq data via R statistical language, providing for useful analytical functionality and good performance for the end-user. Implications of the work span prospects for model orthogonality evaluations, gap identification in network modelling, prototyped automatic kinetics parameterization, and downstream simulation and cellular biological state analysis. This unique computational biology software engineering collaboration with generative natural language processing artificial intelligence was shown to enhance worker productivity, with evident benefits in terms of accelerating coding and machine-human intelligence transfer.

Availability and implementation
BioNexusSentinel project releases, with corresponding data and installation instructions, are available at https://github.com/RichardMatzko/BioNexusSentinel.
Advancing entity recognition in biomedicine via instruction tuning of large language models
Authors: Keloth Vipina K , Hu Yan , Xie Qianqian , Peng Xueqing , Wang Yan , Zheng Andrew , Selek Melih , Raja Kalpana , Wei Chih Hsuan , Jin Qiao , Lu Zhiyong , Chen Qingyu , Xu Hua 
Published: March 2024

AbstractMotivationLarge Language Models (LLMs) have the potential to revolutionize the field of Natural Language Processing, excelling not only in text generation and reasoning tasks but also in their ability for zero/few-shot learning, swiftly adapting to new tasks with minimal fine-tuning. LLMs have also demonstrated great promise in biomedical and healthcare applications. However, when it comes to Named Entity Recognition (NER), particularly within the biomedical domain, LLMs fall short of the effectiveness exhibited by fine-tuned domain-specific models. One key reason is that NER is typically conceptualized as a sequence labeling task, whereas LLMs are optimized for text generation and reasoning tasks.ResultsWe developed an instruction-based learning paradigm that transforms biomedical NER from a sequence labeling task into a generation task. This paradigm is end-to-end and streamlines the training and evaluation process by automatically repurposing pre-existing biomedical NER datasets. We further developed BioNER-LLaMA using the proposed paradigm with LLaMA-7B as the foundational LLM. We conducted extensive testing on BioNER-LLaMA across three widely recognized biomedical NER datasets, consisting of entities related to diseases, chemicals, and genes. The results revealed that BioNER-LLaMA consistently achieved higher F1-scores ranging from 5% to 30% compared to the few-shot learning capabilities of GPT-4 on datasets with different biomedical entities. We show that a general-domain LLM can match the performance of rigorously fine-tuned PubMedBERT models and PMC-LLaMA, biomedical-specific language model. Our findings underscore the potential of our proposed paradigm in developing general-domain LLMs that can rival SOTA performances in multi-task, multi-domain scenarios in biomedical and health applications.Availability and implementationDatasets and other resources are available at https://github.com/BIDS-Xu-Lab/BioNER-LLaMA.