bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tune optimization for alleviating space charge effects and suppressing beam instability at the RCS of CSNS
Authors: Xu Shouyan , Huang Mingyang , Huang Liangsheng , Li Yong , Rao Li , Wang Sheng 
Published: April 2024

Abstract
The design betatron tune of the Rapid Cycling Synchrotron
(RCS) of China Spallation Neutron Source (CSNS) is (4.86, 4.80),
which allows for incoherent tune shifts to avoid serious systematic
betatron resonances. When the operational bare tune was set at the
design value, serious beam instability in the horizontal plane and
beam loss induced by half-integer resonance in the vertical plane
under space charge detuning were observed. Simulations and
experiments have shown that space charge-induced beam loss reduces
as the tunes move up and away from half-integer resonance
lines. However, experimental observations have shown that
instability growth rates increase rapidly as the tune approaches
integer from below. The tune requirements for reducing the beam loss
caused by space charge effects and suppressing beam instability are
different at the RCS of CSNS. The tunes over the whole acceleration
process are optimized based on space charge effects and beam
instability. The optimized tune pattern was able to well control the
beam loss induced by space charge and beam instability. The beam
power of CSNS achieved the design value of 100 kW with small beam
loss.
Points, cells, or polygons? On the choice of spatial units in forest conservation policy impact evaluation
Authors: Blackman Allen , Leguízamo Emilio , Villalobos Laura 
Published: April 2024

Abstract
A fast-growing literature uses remotely sensed land-cover data along with quasi-experimental statistical methods to assess the efficacy of forest conservation interventions. A critical modeling choice is the spatial unit of analysis—points, grid cells, and polygons are all commonly used. Yet little is known about the implications of this choice for treatment effect estimates and for their interpretation. We demonstrate that point-level data can generate treatment effect estimates substantially different from those based on polygon-level data when (i) a disproportionate share of sample points is drawn from relatively large, treated polygons as a result of random or quasi-random spatial sampling, and (ii) the intervention analyzed has heterogeneous effects that depend on treatment polygon size. Our paper has four parts. First, using real-world data (on the award of timber extraction permits to forest management units in Mexico) that meet the two aforementioned criteria, we demonstrate that point- and polygon-level data generate qualitatively different results, and we propose a simple method for weighting the point-level data to recover the polygon-level results. Second, we conduct a Monte Carlo simulation to clarify the mechanism that causes this phenomenon and to provide reassurance that it is not driven by unobserved confounding factors. Third, we present new evidence (on Mesoamerican and Dominican protected areas) suggesting this phenomenon is not uncommon. Finally, we discuss the implications of our findings for the design and interpretation of spatial evaluations of forest conservation interventions. Although our analysis focuses on point- versus polygon-level data, the mechanism we describe also applies to grid cell- versus polygon-level data.
Asymmetrical individual both left and right otoliths of Tuna Scombrini collected from the Java Sea
Authors: Wiadnya D G R , Khamidah N , Paricahya A F , Anam M C , Kusuma W E 
Published: April 2024

Abstract
Otolith can be used as a natural marker of fish stock or anomalies between individuals within fish stock. This research aims to study the relationships between fish length and otolith length and confirm differences in otolith shape between species in the Scombrini tribe and Carangidae family (Decapterus ruselli). Sample used in our analysis were collected around July - September 2023 from three different location, Rastrelliger brachysoma (Lekok waters, Pasuruan), Scomber australasicus (Bali Strait waters) and Decapterus ruselli (Sendang Biru, South Malang). Total 96 specimens were identified based on morphological character as Rastrelliger brachysoma, Scomber australasicus and Decapterus ruselli. Each of following samples were cut horizontally at the frontal head to open the skull and remove sagitta otolith below the hindbrain using dissecting set, then cleaned and stored dry in microtube 1,5 ml separately for left and right to further documented using Celestron Digital Microscope Pro Gray USB 44308. Otolith morphometric data collected includes maximum length using TpsDig and weight using analytical balance. The relationship between Forked Length (FL) and otolith length, length-weight relationship of otolith was determined using simple linear regression on software Statistical Product and Service Solutions (SPSS). Paired sample t-test was applied to determine asymmetrical size of left and right otoliths. In this study, it was found that the shape of the otoliths between species has differences in the rostrum, antirostrum, ventral and dorsal parts. FL-otolith length relationship of S. australasicus, R. brachysoma and D. ruselli are Y=0,725+0,164X, r2= 0,519; Y=0,191+0,230X, r2= 0,911; Y=3,156+0,075X, r2=0,071 respectively. The LW sagitta relationship shows that there is a very strong relationship (P<0,05) between L and W of otoliths. The results of the Paired Sample T-test showed that there was no significant difference in the size of the left and right otoliths (Sig>0.05). Otolith shape is influenced by fish behaviour, diet and environment and it may be used as additional information to distinguish between tribe or even species. Otherwise, its asymmetric relationship and LW relationship may be potential new methods for stock discrimination and have other implications such as stock assessment, understanding natural asymmetry, and its potential applications in fisheries management and conservation.
Ocean Wave Energy Potential in Southern Waters of Malang
Authors: Setyawan F O , Sartimbul A , Fuad M A Z , Ussania Q , Hidayatullah F , Haq N A , Satrio D 
Published: April 2024

Abstract
Ocean or marine energy has immense renewable energy capability, able to provide more than double the world’s current electricity consumption. Ocean energy is considered a non-polluting, renewable source of energy. The research was conducted in the waters of South Malang, East Java Province. This research utilizes wave modeling data that has been picture confirmed and processed within one year, in 2022. This procedure will yield the monthly height, period, and direction of wave arrival. The data used to create a map of the location of wave energy in South Malang comes from previously created wave energy maps. This location map is the result of an overlay of multiple prior maps in order to create a site that can be developed for the usage of wave energy. According to the results, the southern locations of Donomulyo, Bantur, and Sumbermanjing have the most potential for using wave energy for buoy planting. Point 29 is the closest point following point 30 to point 34. However, point 29 is the area covered by the turtle migratory route. Point 34 is the farthest away from the other two places if the distance from the coastline to the potential point is calculated perpendicularly. Despite its distance from the coast, this site experiences the least disturbance when compared to others.
Liquid Organic Fertilizer Produced from Innards Waste of Catfish (Pangasius djambal) by Using Fermentative Microbes (EM4) and Molasses
Authors: Leksono T , Banjarnahor R , Irasari N , Sidauruk S W 
Published: April 2024

Abstract
Liquid organic fertilizer is a liquid fertilizer yielded from the decomposition of organic materials derived from varied wastes which contain more than one nutrient element. The study was aimed to determine the quality of liquid organic fertilizer made from catfish innards waste by adding fermentative microbes (EM4) and molasses. The research method used was experimental with different formulation consisting of 0% EM4 + 30% molasses (K1), 30% EM4 + 0% molasses (K2), 20% EM4 + 20% molasses (P1), 30% EM4 + 30% molasses (P2), and 40% EM4 + 40% molasses (P3). The percentage is calculated from the total weight of all raw materials used. Parameters measured include yield, pH, total lactic acid bacteria (LAB), Nitrogen, Phosphorus, and Potassium. The results showed that the best value for yield was shown in K2 at 34.73%, the pH value in P3 at 5.10, total amount of LAB in P3 at 2.104 cfu/g, the value of Nitrogen (N) in P3 at 4.30%, the value of Phosphorus (P2O5) in P3 at 0.41%, and the value of Potassium (K2O) in P3 at 3.11 ppm. It is possible to increase the content of phosphorus and potassium by adding with EM4 and molasses more than 40% each.
Boosting photocatalytic activity of β-PbO nanoparticles through metal doping
Authors: Geldasa Fikadu Takele , Kebede Mesfin Abayneh , Shura Megersa Wodajo , Feyisa Gebisa Bekele , Tegegne Newayemedhin A , Hone Fekadu Gashaw 
Published: April 2024

Abstract
The current work focuses on the fabrication of pristine and metals (Co, Cu, Ni, Li, and Sn) doped β-PbO phase nanoparticles by cost-effective precipitation method. The properties of the produced nanoparticles were investigated using a variety of characterization techniques. The produced compound was a highly pure β-PbO phase, according to the XRD data. From the UV–vis DRS the obtained bandgap of pristine β-PbO, Co, Cu, Ni, Li, and Sn doped β-PbO was 2.68 eV, 1.88 eV, 2.01 eV, 2.65 eV, 2.64 eV, and 2.70 eV, respectively. The doped samples with the lowest photoluminescence (PL) intensities show the reduced photogenerated electron–hole pair recombination, which increased the photocatalytic activity of β-PbO nanoparticles. The study of the surface morphology by SEM reveals the irregular distribution of the particles. In both pristine and doped nanoparticles, EDX verifies the existence of the expected elements. In comparison to pristine β-PbO, all doped β-PbO nanoparticles have enhanced photocatalytic activity for the degradation of methylene blue (MB) dye under the irradiation of visible light. Among the doped nanoparticles, Cu and Co-doped β-PbO demonstrated particularly high performance. After 80 min of irradiation, Cu and Co-doped β-PbO showed 99.45% and 99.39% degradation rates of MB dye, compared to only 75.13% for pure β-PbO. Hence, the photocatalytic activity of pure β-PbO is boosted through metals doping due to bandgap narrowing, generation of impurity states, increased specific surface area, higher carrier concentration, reduced carriers recombination, the action of dopant ions, and microstructural changes.
Graph representation of multi-dimensional materials
Authors: Cai Carina T , Parker Amanda J , Barnard Amanda S 
Published: April 2024

Abstract
The integration of graph-based representations with machine learning methodologies is transforming the landscape of material discovery, offering a flexible approach for modelling a variety of materials, from molecules and nanomaterials to expansive three-dimensional bulk materials. Nonetheless, the literature often lacks a systematic exploration from the perspective of material dimensionality. While it is important to design representations and algorithms that are universally applicable across species, it is intuitive for material scientists to align the underlying patterns between dimensionality and the characteristics of the employed graph descriptors. In this review, we provide an overview of the graph representations as inputs to machine learning models and navigate the recent applications, spanning the diverse range of material dimensions. This review highlights both persistent gaps and innovative solutions to these challenges, emphasising the pressing need for larger benchmark datasets and leveraging graphical patterns. As graph-based machine learning techniques evolve, they present a promising frontier for accurate, scalable, and interpretable material applications.
Reasonableness as Responsiveness in Administrative Law in the United States, United Kingdom, and Canada: Kant and Arendt on the Role of the Community in Deferential Judicial Review
Authors: Mayeda Graham 
Published: April 2024

Abstract
When conducting judicial review of administrative decisions using a deferential standard of review, courts should give a greater role to the decision maker’s responsiveness to the interests of the community of judgment—those directly affected by the decision. This Article uses a theory of judgment developed by Immanuel Kant in the Critique of Judgment, and elaborated by Hannah Arendt, to justify why consideration for the community is essential to deciding reasonably. It also reviews the approach to deferential review in the case law of the United States, the United Kingdom, and Canada to determine what the effect would be of this new approach to assessing the reasonableness of a decision. While reviewing courts usually consider the rationality of the decision for achieving the decision maker’s statutory policy goals and the appropriateness of the decision maker’s appreciation of the relevant facts, they do not generally probe the responsiveness of their reasons to the concerns of those affected by it. This Article suggests that courts should do so. The result is that administrative law will in future require better quality reasons from decision makers. Probing the responsiveness of reasons to the concerns of the community of judgment will require courts to compare the weight that the decision maker has placed on facts and arguments to the weight given to them by community members. This will be a significant change in how courts conduct judicial review, but it should enhance the legitimacy of deferential judicial review.
Mediating Effect of the NLR on the Relationship Between HbA1c and Left Atrial Stiffness in Overweight Patients With Hypertension
Authors: Zhang Ri , Pan Yu , Ren Yong K , Sun Qiao B , Fu Ting T , Zhao Xu , Liu Yan , Jiang Yi Nong 
Published: April 2024

AbstractBACKGROUNDWe aimed to investigate the association between hemoglobin A1c (HbA1c) and left atrial (LA) stiffness in patients with hypertension and to explore the mediating effect of the neutrophil/lymphocyte ratio (NLR) on this association.METHODSEssential hypertensive patients (n = 292) aged 18–83 years were enrolled and divided into two groups based on the LA stiffness index (LASI): Group I (LASI ≤ 0.32, n = 146) and Group II (LASI &gt; 0.32, n = 146). The LASI was defined as the ratio of early diastolic transmitral flow velocity/lateral mitral annulus myocardial velocity (E/eʹ) to LA reservoir strain. Multivariate linear regression analysis was performed to determine the independent predictors of the LASI.RESULTSAge, BMI, SBP, HbA1c, CRP, and NLR were significantly greater in Group II than in Group I (P &lt; 0.05). Additionally, Group II had a greater LA volume index (LAVI), left ventricular mass index (LVMI), and early diastolic transmitral flow velocity/lateral mitral annulus myocardial velocity (E/eʹ) and lower LA reservoir, conduit, and booster pump strains than Group I (P &lt; 0.001). Univariate and multivariate linear regression models revealed that age, SBP, HbA1c, and the NLR were independently associated with the LASI. Further mediation analysis was performed to determine the mediating effect of the NLR on the association between HbA1c and the LASI and revealed that the NLR had a mediating role only in overweight hypertensive patients, and the proportion of the mediating effect was 21.9%.CONCLUSIONSThe NLR was independently correlated with the LASI and played a mediating role in the relationship between HbA1c and the LASI in overweight hypertensive patients.
A comprehensive review of machine learning techniques for multi-omics data integration: challenges and applications in precision oncology
Authors: Acharya Debabrata , Mukhopadhyay Anirban 
Published: April 2024

Abstract
Multi-omics data play a crucial role in precision medicine, mainly to understand the diverse biological interaction between different omics. Machine learning approaches have been extensively employed in this context over the years. This review aims to comprehensively summarize and categorize these advancements, focusing on the integration of multi-omics data, which includes genomics, transcriptomics, proteomics and metabolomics, alongside clinical data. We discuss various machine learning techniques and computational methodologies used for integrating distinct omics datasets and provide valuable insights into their application. The review emphasizes both the challenges and opportunities present in multi-omics data integration, precision medicine and patient stratification, offering practical recommendations for method selection in various scenarios. Recent advances in deep learning and network-based approaches are also explored, highlighting their potential to harmonize diverse biological information layers. Additionally, we present a roadmap for the integration of multi-omics data in precision oncology, outlining the advantages, challenges and implementation difficulties. Hence this review offers a thorough overview of current literature, providing researchers with insights into machine learning techniques for patient stratification, particularly in precision oncology. Contact: anirban@klyuniv.ac.in
DSNetax: a deep learning species annotation method based on a deep-shallow parallel framework
Authors: Zhao Hongyuan , Zhang Suyi , Qin Hui , Liu Xiaogang , Ma Dongna , Han Xiao , Mao Jian , Liu Shuangping 
Published: April 2024

Abstract
Microbial community analysis is an important field to study the composition and function of microbial communities. Microbial species annotation is crucial to revealing microorganisms’ complex ecological functions in environmental, ecological and host interactions. Currently, widely used methods can suffer from issues such as inaccurate species-level annotations and time and memory constraints, and as sequencing technology advances and sequencing costs decline, microbial species annotation methods with higher quality classification effectiveness become critical. Therefore, we processed 16S rRNA gene sequences into k-mers sets and then used a trained DNABERT model to generate word vectors. We also design a parallel network structure consisting of deep and shallow modules to extract the semantic and detailed features of 16S rRNA gene sequences. Our method can accurately and rapidly classify bacterial sequences at the SILVA database’s genus and species level. The database is characterized by long sequence length (1500 base pairs), multiple sequences (428,748 reads) and high similarity. The results show that our method has better performance. The technique is nearly 20% more accurate at the species level than the currently popular naive Bayes-dominated QIIME 2 annotation method, and the top-5 results at the species level differ from BLAST methods by &lt;2%. In summary, our approach combines a multi-module deep learning approach that overcomes the limitations of existing methods, providing an efficient and accurate solution for microbial species labeling and more reliable data support for microbiology research and application.
STRIDE-DB: a comprehensive database for exploration of instability and phenotypic relevance of short tandem repeats in the human genome
Authors: Uppili Bharathram , Faruq Mohammed 
Published: April 2024

Abstract
Short Tandem Repeats (STRs) are genetic markers made up of repeating DNA sequences. The variations of the STRs are widely studied in forensic analysis, population studies and genetic testing for a variety of neuromuscular disorders. Understanding polymorphic STR variation and its cause is crucial for deciphering genetic information and finding links to various disorders. In this paper, we present STRIDE-DB, a novel and unique platform to explore STR Instability and its Phenotypic Relevance, and a comprehensive database of STRs in the human genome. We utilized RepeatMasker to identify all the STRs in the human genome (hg19) and combined it with frequency data from the 1000 Genomes Project. STRIDE-DB, a user-friendly resource, plays a pivotal role in investigating the relationship between STR variation, instability and phenotype. By harnessing data from genome-wide association studies (GWAS), ClinVar database, Alu loci, Haploblocks in genome and Conservation of the STRs, it serves as an important tool for researchers exploring the variability of STRs in the human genome and its direct impact on phenotypes. STRIDE-DB has its broad applicability and significance in various research domains like forensic sciences and other repeat expansion disorders.
Database URL: https://stridedb.igib.res.in.
Bacterial diversity in agricultural drainage ditches shifts with increasing urea-N concentrations
Authors: Klick Sabrina A , Pitula Joseph S , Collick Amy S , May Eric B , Pisani Oliva 
Published: April 2024

Abstract
Urea-based fertilizers applied to crop fields can enter the surface waters of adjacent agricultural drainage ditches and contribute to the nitrogen (N) loading in nearby watersheds. Management practices applied in drainage ditches promote N removal by the bacterial communities, but little is known about the impacts of excess urea fertilizer from crop fields on the bacterial diversity in these ditches. In 2017, sediments from drainage ditches next to corn and soybean fields were sampled to determine if fertilizer application and high urea-N concentrations alters bacterial diversity and urease gene abundances. A mesocosm experiment was paired with a field study to determine which bacterial groups respond to high urea-N concentrations. The bacterial diversity in the ditch next to corn fields was significantly different from the other site. The bacterial orders of Rhizobiales, Bacteroidales, Acidobacteriales, Burkholderiales, and Anaerolineales were most abundant in the ditch next to corn and increased after the addition of urea-N (0.5 mg N L−1) during the mesocosm experiment. The results of our study suggests that urea-N concentrations &gt;0.07 mg N L−1, which are higher than concentrations associated with downstream harmful algal blooms, can lead to shifts in the bacterial communities of agricultural drainage ditches.
High-Quality, Chromosome-Level Reference Genomes of the Viviparous Caribbean Skinks Spondylurus nitidus and S. culebrae
Authors: Rivera Danielle , Henderson James B , Lam Athena W , Hostetter Nathan J , Collazo Jaime A , Bell Rayna C 
Published: April 2024

Abstract
New World mabuyine skinks are a diverse radiation of morphologically cryptic lizards with unique reproductive biologies. Recent studies examining population-level data (morphological, ecological, and genomic) have uncovered novel biodiversity and phenotypes, including the description of dozens of new species and insights into the evolution of their highly complex placental structures. Beyond the potential for this diverse group to serve as a model for the evolution of viviparity in lizards, much of the taxonomic diversity is concentrated in regions experiencing increasing environmental instability from climate and anthropogenic change. Consequently, a better understanding of genome structure and diversity will be an important tool in the adaptive management and conservation of this group. Skinks endemic to Caribbean islands are particularly vulnerable to global change with several species already considered likely extinct and several remaining species either endangered or threatened. Combining PacBio long-read sequencing, Hi-C, and RNAseq data, here we present the first genomic resources for this group by describing new chromosome-level reference genomes for the Puerto Rican Skink Spondylurus nitidus and the Culebra Skink S. culebrae. Results indicate two high quality genomes, both ∼1.4 Gb, assembled nearly telomere to telomere with complete mitochondrion assembly and annotation.