bluuebunny/crossref_metadata_2025_split huggingface dataset:
Benefits of customizing dust hazard controls to meet your needs
Authors: Gaither Edward 
Published: July 2024

AbstractThe OSHA Combustible Dust National Emphasis Program (NEP), recent studies commissioned by the National Fire Protection Association (NFPA) Research Foundation and U.S. Chemical Safety and Hazard Investigation Board (CSB), as well as emphasis by insurance companies have brought more urgency to combustible dust safety. NFPA standards are being revised for consistency and clarity of standards for combustible dust safety. While that is a significant improvement from conditions of past decades, the situation can be improved even more by implementing risk‐based methods to help develop application‐specific explosion protection. Many facilities that handle combustible particulate solids follow prescriptive requirements of applicable NFPA standards, especially for new installations. Decisions are often driven primarily by meeting codes and standards with minimum capital cost. Legacy installations that do not meet current standards typically claim “grandfather” status as the reason for not implementing the current standard requirement or good engineering practice. The goal of this paper is to present a method of adapting the familiar process safety risk matrix to assess likelihood of a deflagration event rather than the overall the risk of a consequence. This method provides an objective basis to assist staff of a legacy facility to make decisions to prioritize capital improvement projects, to follow current good engineering practice, and to stop relying on “grandfather” status. This paper makes the broad, practical assumption that any deflagration event has serious consequences. The magnitude of those consequences may vary based on facility siting, deflagration area of effect, population of personnel in the affected area, or business criticality of affected equipment and structures. Decisions based solely on the likelihood matrix may inadvertently prioritize a more likely, but less consequential, concern over an event that may put multiple people at risk, or have serious commercial implications. Methods such as Hazard and Operability Study (HAZOP), Failure Modes and Effects Analysis (FMEA), Fault Tree Analysis (FTA) and Layer of Protection Analysis (LOPA) are useful to more comprehensively understand risks. Flexible, outside‐the‐box thinking in applying safeguards, Independent Protection Layers (IPLs), administrative controls, and facility siting may provide a better solution than merely following prescriptive code without making the effort to fully understand the hazard.
University teaching of mass spectrometry as a key practical technique within the context of a fully integrated, spiral curriculum
Authors: Worrall Andrew F. , Campbell Craig D. , Midson Megan O. , Stewart Malcolm I. 
Published: July 2024

RationaleMass spectrometry (MS) is introduced to high school students in the UK in many pre‐university course syllabi. As such, we have identified the use of MS as a key technique that should be taught practically to undergraduates from the outset of their studies. This mini‐review describes how we introduce and develop students' use of MS throughout our three‐year undergraduate spiral curriculum practical programme, using atmospheric pressure chemical ionization MS (APCI‐MS).MethodsWe have used an Advion ExpressionL spectrometer, fitted with an atmospheric solids analysis probe or a Plate Express TLC sampler for sample introduction.ResultsWe have successfully demonstrated the use of APCI‐MS in a range of practicals and experiments covering organic and organometallic chemistries, with large cohorts of students gaining hands‐on instrumental experience in authentic research settings.ConclusionsAPCI‐MS has proven to be an easy‐to‐use and valuable addition to our undergraduate practical course. The robustness of the spectrometer enables routine use by large cohorts of students with minimal supervision, and routine maintenance can be carried out by non‐specialist technicians. Students can readily process and interpret results for a series of routine analyses, as well as demonstrate uses in problem‐solving exercises.
Autonomous navigation method based on RGB‐D camera for a crop phenotyping robot
Authors: Yang Meng , Huang Chenglong , Li Zhengda , Shao Yang , Yuan Jinzhan , Yang Wanneng , Song Peng 
Published: July 2024

AbstractPhenotyping robots have the potential to obtain crop phenotypic traits on a large scale with high throughput. Autonomous navigation technology for phenotyping robots can significantly improve the efficiency of phenotypic traits collection. This study developed an autonomous navigation method utilizing an RGB‐D camera, specifically designed for phenotyping robots in field environments. The PP‐LiteSeg semantic segmentation model was employed due to its real‐time and accurate segmentation capabilities, enabling the distinction of crop areas in images captured by the RGB‐D camera. Navigation feature points were extracted from these segmented areas, with their three‐dimensional coordinates determined from pixel and depth information, facilitating the computation of angle deviation (α) and lateral deviation (d). Fuzzy controllers were designed with α and d as inputs for real‐time deviation correction during the walking of phenotyping robot. Additionally, the method includes end‐of‐row recognition and row spacing calculation, based on both visible and depth data, enabling automatic turning and row transition. The experimental results showed that the adopted PP‐LiteSeg semantic segmentation model had a testing accuracy of 95.379% and a mean intersection over union of 90.615%. The robot's navigation demonstrated an average walking deviation of 1.33 cm, with a maximum of 3.82 cm. Additionally, the average error in row spacing measurement was 2.71 cm, while the success rate of row transition at the end of the row was 100%. These findings indicate that the proposed method provides effective support for the autonomous operation of phenotyping robots.
The role of private sector investment in agriculture: A catalyst for sustainable development in Asia
Authors: Pickson Robert Becker , Gui Peng , Jian Lirong , Boateng Elliot 
Published: July 2024

AbstractThe agricultural sector is a crucial driver for sustainable development in many countries, as it directly or indirectly contributes to various United Nations Sustainable Development Goals. However, this sector requires increasing financial investment to rejuvenate and modernise production processes. This study investigates the impact of private sector investment on agricultural production across selected Asian countries from 2001Q1 to 2020Q4. The results of the Driscoll‐Kraay regression and the method of moments quantile regression reveal that private agricultural investment positively affects agricultural production. The findings indicate positive contributions from agricultural aid, domestic credit, and rural population, whereas remittances negatively affect agricultural production. The Dumitrescu‐Hurlin panel causality test results establish bidirectional causality between farm production and its determinants (private agricultural investment, agricultural aid, domestic credit, remittances, and the rural population). Based on these findings, we recommend that policymakers and governments incentivise and facilitate private agricultural investment to drive sustainable development. This strategy could boost agricultural productivity and enhance a more resilient agricultural system capable of withstanding environmental challenges while improving farmers' incomes and livelihoods.
Recent Breakthroughs and Future Potential of Inorganic Nanocomposites in Hydrogen Generation
Authors: Virender  , Priyanka  , Neeraj  , Kumar Krishan , Prakash Ajay , Kumar Gupta Rakesh , Modi Krunal , Pombeiro Armando J. L. , Singh Gurjaspreet , Mohan Brij 
Published: July 2024

AbstractGreen hydrogen synthesis has attracted researchers due to energy resource applications. Non‐renewable energy sources have been found to be incapable of meeting energy demands. Therefore, the need of the hour is to introduce an alternative to produce an efficient amount of H2. This review has summarized and investigated hetero‐catalysts and their hydrogen production potential under different light illuminations. Here, the syntheses of various nanoparticles (NPs) and composite semiconductors have been reviewed, and insights into the enhanced ability of noble‐free metal electrocatalysts have been provided. Specific nanomaterials, such as nickel, ruthenium, silver, boron‐doped SnO2, AgVO3, cobalt‐ferrite, and cobalt, dominate in synthesizing durable electrocatalysts. These exhibit Schottky junctions and enhance catalytic behaviour for hydrogen production. Finally, the challenges of the nanoparticle‘s structural and conductive properties and critical solutions are discussed. This review discusses mechanistic insights, interactions, and kinetics that involve a higher H2 synthesis rate.
Gelatin Nanoparticles can Improve Pesticide Delivery Performance to Plants
Authors: Park Sunho , Safdar Mahpara , Kim Woochan , Seol Jaehwi , Kim Dream , Lee Kyeong‐Hwan , Son Hyoung Il , Kim Jangho 
Published: July 2024

AbstractNanomaterials associated with plant growth and crop cultivation revolutionize traditional concepts of agriculture. However, the poor reiterability of these materials in agricultural applications necessitates the development of environmentally‐friendly approaches. To address this, biocompatible gelatin nanoparticles (GNPs) as nanofertilizers with a small size (≈150 nm) and a positively charged surface (≈30 mV) that serve as a versatile tool in agricultural practices is designed. GNPs load agrochemical agents to improve maintenance and delivery. The biocompatible nature and small size of GNPs ensure unrestricted nutrient absorption on root surfaces. Furthermore, when combined with pesticides, GNPs demonstrate remarkable enhancements in insecticidal (≈15%) and weed‐killing effects (≈20%) while preserving the efficacy of the pesticide. That GNPs have great potential for use in sustainable agriculture, particularly in inducing plant growth, specifically plant root growth, without fertilization and in enhancing the functions of agrochemical agents is proposed. It is suggested conceptual applications of GNPs in real‐world agricultural practices.
Attojoule Hexagonal Boron Nitride‐Based Memristor for High‐Performance Neuromorphic Computing
Authors: Kim Jiye , Song Jaesub , Kwak Hyunjoung , Choi Chang‐Won , Noh Kyungmi , Moon Seokho , Hwang Hyeonwoong , Hwang Inyong , Jeong Hokyeong , Choi Si‐Young , Kim Seyoung , Kim Jong Kyu 
Published: July 2024

AbstractIn next‐generation neuromorphic computing applications, the primary challenge lies in achieving energy‐efficient and reliable memristors while minimizing their energy consumption to a level comparable to that of biological synapses. In this work, hexagonal boron nitride (h‐BN)‐based metal‐insulator‐semiconductor (MIS) memristors operating is presented at the attojoule‐level tailored for high‐performance artificial neural networks. The memristors benefit from a wafer‐scale uniform h‐BN resistive switching medium grown directly on a highly doped Si wafer using metal–organic chemical vapor deposition (MOCVD), resulting in outstanding reliability and low variability. Notably, the h‐BN‐based memristors exhibit exceptionally low energy consumption of attojoule levels, coupled with fast switching speed. The switching mechanisms are systematically substantiated by electrical and nano‐structural analysis, confirming that the h‐BN layer facilitates the resistive switching with extremely low high resistance states (HRS) and the native SiOx on Si contributes to suppressing excessive current, enabling attojoule‐level energy consumption. Furthermore, the formation of atomic‐scale conductive filaments leads to remarkably fast response times within the nanosecond range, and allows for the attainment of multi‐resistance states, making these memristors well‐suited for next‐generation neuromorphic applications. The h‐BN‐based MIS memristors hold the potential to revolutionize energy consumption limitations in neuromorphic devices, bridging the gap between artificial and biological synapses.
Biosorption of Cadmium by Living and Non‐living Cells of Pseudomonas aeruginosa DR7
Authors: Zhang Jianhui , Noor Zainura Zainon , Baharuddin Nurul Huda , Setu Siti Aminah , Hamzah Mohd Amir Asyraf Mohd , Zakaria Zainul Akmar 
Published: July 2024

ABSTRACTThe global concern over health issues related to heavy metal pollution has driven the adoption of various treatment technologies. The investigation into optimal conditions for cadmium biosorption and bioaccumulation was conducted using a resilient bacterial strain, Pseudomonas aeruginosa DR7, which was isolated from ponds. The equilibrium time of the adsorption process of living cells was much longer than that of non‐living cells, which was about 240 min, which indicates that living cells have intracellular accumulation and delay the adsorption process. Living cells favored a pH of 6.0, while non‐living cells showed higher efficiency at pH 7.0, demonstrating the pH‐dependent nature of metal biosorption. In this context, the maximum biosorption capacities for cadmium using non‐living cells and living cells were 103.8 mg/g and 70.94 mg/g, under cell mass of 1.0 g/L, pH 7.0, initial metal concentration of 200 mg/L, and contact time of 240 min, respectively. Cadmium biosorption by living cells was more accurately described by the Freundlich isothermal model, whereas the Langmuir model was used for non‐living cells. Living cells tend to show pseudo‐second‐order kinetic adsorption behavior, while non‐living cells tend to show pseudo‐first‐order kinetic adsorption behavior. Fourier‐transform infrared spectroscopy (FTIR) analysis suggested that the hydroxyl, amino, and carboxyl groups all play a role in biosorption. Scanning electron microscopy (SEM)–energy dispersive x‐ray spectroscopy (EDS) showed that the high‐temperature treatment destroys the integrity of the cell wall, which enhances the permeability of the cell wall, thus increasing the biosorption of Cd (II) by the non‐living cells. The study found that P. aeruginosa DR7 with high temperature inactivation has a higher Cd(II) adsorption capacity than living cells, making it a green and environmentally friendly biological adsorbent for wastewater treatment with heavy metals.
Real-time dynamics of the Schwinger model as an open quantum system with Neural Density Operators
Authors: Lin Joshua , Luo Di , Yao Xiaojun , Shanahan Phiala E. 
Published: July 2024

Abstract
Ab-initio simulations of multiple heavy quarks propagating in a Quark-Gluon Plasma are computationally difficult to perform due to the large dimension of the space of density matrices. This work develops machine learning algorithms to overcome this difficulty by approximating exact quantum states with neural network parametrisations, specifically Neural Density Operators. As a proof of principle demonstration in a QCD-like theory, the approach is applied to solve the Lindblad master equation in the 1 + 1d lattice Schwinger Model as an open quantum system. Neural Density Operators enable the study of in-medium dynamics on large lattice volumes, where multiple-string interactions and their effects on string-breaking and recombination phenomena can be studied. Thermal properties of the system at equilibrium can also be probed with these methods by variationally constructing the steady state of the Lindblad master equation. Scaling of this approach with system size is studied, and numerical demonstrations on up to 32 spatial lattice sites and with up to 3 interacting strings are performed.
Minijet quenching in non-equilibrium quark-gluon plasma
Authors: Zhou Fabian , Brewer Jasmine , Mazeliauskas Aleksas 
Published: July 2024

Abstract
We study the energy deposition and thermalisation of high-momentum on-shell partons (minijets) travelling through a non-equilibrium Quark-Gluon Plasma using QCD kinetic theory. For thermal backgrounds, we show that the parton energy first flows to the soft sector by collinear cascade and then isotropises via elastic scatterings. In contrast, the momentum deposition from a minijet reaches the equilibrium distribution directly. For expanding non-equilibrium QGP, we study the time for a minijet perturbation to lose memory of its initial conditions, namely, the hydrodynamisation time. We show that the minijet evolution scales well with the relaxation time τR ∝ η/s/T(τ), where T(τ) is the effective temperature and η/s is the viscosity over entropy ratio.
Time Functions on Lorentzian Length Spaces
Authors: Burtscher Annegret , García-Heveling Leonardo 
Published: July 2024

AbstractIn general relativity, time functions are crucial objects whose existence and properties are intimately tied to the causal structure of a spacetime and also to the initial value formulation of the Einstein equations. In this work we establish all fundamental classical existence results on time functions in the setting of Lorentzian (pre-)length spaces (including causally plain continuous spacetimes, closed cone fields and even more singular spaces). More precisely, we characterize the existence of time functions by K-causality, show that a modified notion of Geroch’s volume functions are time functions if and only if the space is causally continuous, and lastly, characterize global hyperbolicity by the existence of Cauchy time functions, and Cauchy sets. Our results thus inevitably show that no manifold structure is needed in order to obtain suitable time functions.
Rats exposed to Alternaria toxins in vivo exhibit altered liver activity highlighted by disruptions in riboflavin and acylcarnitine metabolism
Authors: Peach Jesse T. , Puntscher Hannes , Höger Harald , Marko Doris , Warth Benedikt 
Published: July 2024

AbstractNatural toxins produced by Alternaria fungi include the mycotoxins alternariol, tenuazonic acid and altertoxins I and II. Several of these toxins have shown high toxicity even at low levels including genotoxic, mutagenic, and estrogenic effects. However, the metabolic effects of toxin exposure from Alternaria are understudied, especially in the liver as a key target. To gain insight into the impact of Alternaria toxin exposure on the liver metabolome, rats (n = 21) were exposed to either (1) a complex culture extract with defined toxin profiles from Alternaria alternata (50 mg/kg body weight), (2) the isolated, highly genotoxic altertoxin-II (ATX-II) (0.7 mg/kg of body weight) or (3) a solvent control. The complex mixture contained a spectrum of Alternaria toxins including a controlled dose of ATX-II, matching the concentration of the isolated ATX-II. Liver samples were collected after 24 h and analyzed via liquid chromatography–high-resolution mass spectrometry (LC-HRMS). Authentic reference standards (> 100) were used to identify endogenous metabolites and exogenous compounds from the administered exposures in tandem with SWATH-acquired MS/MS data which was used for non-targeted analysis/screening. Screening for metabolites produced by Alternaria revealed several compounds solely isolated in the liver of rats exposed to the complex culture, confirming results from a previously performed targeted biomonitoring study. This included the altersetin and altercrasin A that were tentatively identified. An untargeted metabolomics analysis found upregulation of acylcarnitines in rats receiving the complex Alternaria extract as well as downregulation of riboflavin in rats exposed to both ATX-II and the complex mixture. Taken together, this work provides a mechanistic view of Alternari toxin exposure and new suspect screening insights into hardly characterized Alternaria toxins.
Stable Recovery of Coefficients in an Inverse Fault Friction Problem
Authors: de Hoop Maarten V. , Lassas Matti , Lu Jinpeng , Oksanen Lauri 
Published: July 2024

AbstractWe consider the inverse fault friction problem of determining the friction coefficient in the Tresca friction model, which can be formulated as an inverse problem for differential inequalities. We show that the measurements of elastic waves during a rupture uniquely determine the friction coefficient at the rupture surface with explicit stability estimates.
Prediction of delayed graft function by early salivary microbiota following kidney transplantation
Authors: Xiang Xuyu , Peng Bo , Liu Kai , Wang Tianyin , Ding Peng , Zhu Yi , Cheng Ke , Ming Yingzi 
Published: July 2024

Abstract
Delayed graft function (DGF) is a frequently observed complication following kidney transplantation (KT). Our prior research revealed dynamic shifts in salivary microbiota post-KT with immediate graft function (IGF), yet its behavior during DGF remains unexplored. Five recipients with DGF and 35 recipients with IGF were enrolled. Saliva samples were collected during the perioperative period, and 16S rRNA gene sequencing was performed. The salivary microbiota of IGFs changed significantly and gradually stabilized with the recovery of renal function. The salivary microbiota composition of DGFs was significantly different from that of IGFs, although the trend of variation appeared to be similar to that of IGFs. Salivary microbiota that differed significantly between patients with DGF and IGF at 1 day after transplantation were able to accurately distinguish the two groups in the randomForest algorithm (accuracy = 0.8333, sensitivity = 0.7778, specificity = 1, and area under curve = 0.85), with Selenomonas playing an important role. Bacteroidales (Spearman’s r =  − 0.4872 and p = 0.0293) and Veillonella (Spearmen’s r =  − 0.5474 and p = 0.0125) were significantly associated with the serum creatinine in DGF patients. Moreover, the significant differences in overall salivary microbiota structure between DGF and IGF patients disappeared upon long-term follow-up. This is the first study to investigate the dynamic changes in salivary microbiota in DGFs. Our findings suggested that salivary microbiota was able to predict DGF in the early stages after kidney transplantation, which might help the perioperative clinical management and early-stage intervention of kidney transplant recipients.

Key points
• Salivary microbiota on the first day after KT could predict DGF.
• Alterations in salivary taxa after KT are related to recovery of renal function.
In-vivo confocal microscopy predicts cytomegalovirus as the cause of chronic or recurrent anterior uveitis among Chinese
Authors: Kwok Stephanie Hiu-wai , Kam Ka Wai , Mok Eugenie , Young Alvin L. 
Published: July 2024

Abstract
Purpose
To evaluate and compare endothelial features by in-vivo confocal microscopy (IVCM) in Chinese eyes with chronic or recurrent anterior uveitis (AU) with and without cytomegalovirus (CMV).

Methods
A double-masked, cross-sectional case-control study at a tertiary eye clinic.

Results
Thirty eyes of 30 subjects were analyzed. Fifteen eyes (50%) were CMV positive, while fifteen eyes were negative for herpes simplex virus, varicella zoster virus and CMV. Absence of pseudoguttata was the strongest, independent risk factor for CMV (OR 34.53, 95% CI: 1.84-648.02, p = 0.018), followed by severe iris depigmentation (OR 31.45, 1.02-965.81, p = 0.048) and low corneal endothelial cell density (ECD) (OR 14.79, 1.14–191.30, p = 0.039) on univariable regression. All three remained statistically significant after adjustment. The combination of absence of pseudoguttata and low ECD on IVCM achieved a similar predictive value as iris depigmentation examination.

Conclusion
Absence of pseudoguttata on IVCM was an independent predictor of positive CMV detection after adjusting for iris depigmentation and corneal endothelial cell density. The addition of this feature to severe iris depigmentation and low corneal ECD can increase the positive predictive value of detecting CMV. IVCM was a useful non-invasive tool to predict CMV in patients with chronic or recurrent AU.