bluuebunny/crossref_metadata_2025_split huggingface dataset:
Water, energy, and food nexus in a solar-powered brackish water desalination plant in Jordan
Authors: Bdour Ahmed , Al-Sadeq Noor , Gharaibeh Muna , Mendoza-Sammet Angeles , Salinas-Rodriguez Sergio G 
Published: September 2024

Abstract
The growing demand for water in domestic, agricultural, and energy production applications poses a significant challenge for Jordan. This work assesses the role of brackish water desalination as an alternative to alleviate water scarcity in semi-arid regions. Desalination is still limited in its application in Jordan due to high electricity tariffs. Shifting to renewable sources such as solar energy, abundant in the country, is a feasible way to power technologies with a high energy demand. In this work, we study the brackish water desalination plant at the Hashemite University in Jordan that is powered by a photovoltaic (PV) solar system (the HU PV-BWRO). The plant’s performance was evaluated in the context of the water-energy nexus as a hybrid water supply solution. While this work integrates essential elements, such as water availability, technical options, economic viability, and agricultural management, the analysis primarily focuses on the technical and economic aspects related to water, energy, and food. Water assessment results indicate that the groundwater wells near the HU campus are at risk of quality degradation over time, as they have shown a slight increasing trend in salinization from 2015 to 2023. Energy assessment results show a promising performance from the HU PV-BWRO desalination plant, with a specific energy consumption (SEC) value of 1.2 kWh m−3 (140% to 400% less energy consumption compared with other Jordanian desalination plants of similar capacity). Unit price comparisons indicate that the energy cost of PV (0.042 USD/m3) is 5 times less than the cost of grid electricity (0.24 USD/m3). The operational cost of the solar desalination plant at full capacity, is USD 0.23/m3. This is about 260% less than the operation cost for local, grid-powered desalination plants. Finally, it is estimated that by operating the plant at 50% of its total capacity, the produced water could be sufficient to irrigate up to 80% of the HU campus to increase agricultural production. This study highlights the importance of decreasing reliance on energy for water and food production, and it shows that the use of solar powered desalination could be used as an example in semi-arid regions, particularly in terms of integrating renewable energy and energy efficiency.
Microstructural analysis on the compatibility of various dilution oils on magnetorheological grease performance
Authors: Pang Zheng Bin , Mazlan Saiful Amri , Ubaidillah Ubaidillah , Nordin Nur Azmah , Mohamad Norzilawati , Johari Mohd Aidy Faizal , Mohd Yusuf Shahir Yasin , Ahmad Khairi Muntaz Hana , Abdul Aziz Siti Aishah 
Published: September 2024

Abstract
This research explores the effects of dilution oils on the storage stability of magnetorheological grease (MRG) by studying the effect of dilution oil viscosity on the microstructure of carrier fluids medium for MRG, which can help address practical challenges encountered in the development and deployment of MRG. Three samples of MRG with 70 wt% CIP are prepared; a control, and 2 samples diluted until 10 wt% hydraulic fluid and kerosene respectively. The resulting samples were analysed using a modular compact rheometer (MCR) for oscillatory strain sweep and rotational current sweep. Rheological analyses were repeated after one year in storage. Fourier-Transform Infrared (FTIR) spectroscopy and Atomic Force Microscopy (AFM) results show significant microstructural and performance deterioration of grease thickener in the sample with kerosene, which concludes that kerosene had a very significant effect on the degradation of the grease thickener. From this study, it was revealed that low viscosity oils disrupt the reconstruction of the thickener of lithium grease, which in turn causes deteriorating shear rheological performance of MRG at off-state conditions. This comprehensive analysis explains the relationships between MRG composition, microstructural characteristics, and performance parameters, offering a foundational framework for further exploration and advancement in this scientific field.
Multi response optimization of process parameters in titanium alloy minimum quantity lubrication drilling operation
Authors: Dalke Piyush A , Karanjkar Atul V , Wankhede Pankaj 
Published: September 2024

Abstract
This work investigates the application of minimal quantity lubrication (MQL) in the drilling process, where a combination of liquid and air creates an aerosol in the form of a fine mist. This protective layer decreases friction and tool wear, hence improving overall efficiency. The study examines the conventional Gulfcut oil blend drilling technique to enhance drilling performance on the titanium alloy Ti-6Al-4V under MQL circumstances. The key drilling parameters, namely spindle speed (N), feed rate (F), and point angle (D), were analyzed using a Taguchi L16 orthogonal array. The experimental inquiry aimed to identify the most favorable conditions that lead to the least amount of torque (TQ), thrust force (TF), and surface roughness (SR). An Analysis of Variance (ANOVA) was used to examine the impact of control factors on drilling performance. The optimized drilling parameters led to a reduction in torque, thrust force, and surface roughness by 12.88%, 21.29%, and 25.76%, respectively. Furthermore, microstructure analysis demonstrated that the Gulfcut lubricant plays a pivotal role in reducing grain size during drilling. This research provides valuable insights into optimizing drilling conditions for titanium alloy using a conventional Gulfcut oil blend with MQL, aiming to reduce torque, thrust force, and surface roughness.
Analysis of disturbance factors of magnetorheological damper in continuous impact buffer system
Authors: Wang Xin , Hou Minjie , Ouyang Qing , Xu Xiao , Yu Zhen , Cheng Yuzhu , Li Zhaochun 
Published: September 2024

Abstract
Magnetorheological (MR) impact buffering systems are widely used in vehicle suspensions, bridge damping, and aircraft landing gear due to their excellent buffering performance and rapid response time. However, under the condition of high-speed continuous impact, magnetorheological damper (MRD) operate in complex environments where various internal and external uncertainties can negatively affect control performance. This paper analyzes the impact of disturbance signals on MR buffering systems and explores control strategies to mitigate these effects. First, we established a hysteresis model based on experimental data and identified parameters using a genetic algorithm to determine the influence of hysteresis disturbances. Next, we developed a temperature model based on the thermal characteristics of SG-MRF2035 magnetorheological fluid, fitting the relationship between temperature and dynamic viscosity to identify temperature disturbances. The results showed that when disturbances were considered, the system exhibited higher peak damping forces and a deviation from the desired ‘platform effect’ in the damping force-displacement relationship. Finally, we applied an Active Disturbance Rejection Control(ADRC) strategy, which effectively compensated for the hysteresis and temperature disturbances, enhancing the system’s robustness. Compared to PID control, the ADRC-controlled system demonstrated lower peak damping forces and a damping force-displacement relationship closer to the desired platform effect.
Influential mechanism of operational parameters on internal resonance of drill strings by numerical simulations
Authors: Li Xinye , Li Mingming , Guo Xiaoqiang , Agila Wassef , Zhang Huabiao , Yang Jie 
Published: September 2024

Abstract
Drill string vibration is highly conductive to drill string fatigue and component failure. In this study, a finite element model of a drill string with bottom hole assembly (BHA) is constructed to investigate the effect of different operational parameters, such as different string length, density, pressure, and velocity of drilling fluid on drill string natural frequencies, and thus internal resonance by considering fluid-structure interaction (FSI) in ANSYS. Numerical simulations demonstrate that the natural frequencies decrease as the length of the drill string increases, which is especially true for the axial mode. The condition of 1:1 internal resonance between the axial and torsional modes only occurs when the length of drill string is sufficiently high. Nevertheless, this resonance fades away in the presence of fluid. The increment of fluid density slightly increases the natural frequency in lateral mode, whereas decreases that in axial mode. On the other hand, this effect of density is negligible in the torsional mode. The natural frequencies for axial, torsional and lateral modes decrease as the fluid velocity increases, and the impact of fluid pressure on natural frequency is almost not observable. The numerical results for the case without drill fluid are in qualitative agreement with analytical solutions. when considing the effect of drill length on natural frequency.
Distance preserving machine learning for uncertainty aware accelerator capacitance predictions
Authors: Goldenberg Steven , Schram Malachi , Rajput Kishansingh , Britton Thomas , Pappas Chris , Lu Dan , Walden Jared , Radaideh Majdi I , Cousineau Sarah , Harave Sudarshan 
Published: September 2024

Abstract
Accurate uncertainty estimations are essential for producing reliable machine learning models, especially in safety-critical applications such as accelerator systems. Gaussian process models are generally regarded as the gold standard for this task; however, they can struggle with large, high-dimensional datasets. Combining deep neural networks with Gaussian process approximation techniques has shown promising results, but dimensionality reduction through standard deep neural network layers is not guaranteed to maintain the distance information necessary for Gaussian process models. We build on previous work by comparing the use of the singular value decomposition against a spectral-normalized dense layer as a feature extractor for a deep neural Gaussian process approximation model and apply it to a capacitance prediction problem for the High Voltage Converter Modulators in the Oak Ridge Spallation Neutron Source. Our model shows improved distance preservation and predicts in-distribution capacitance values with less than 1% error.
A comparison of deep learning models for proton background rejection with the AMS electromagnetic calorimeter
Authors: Hashmani R K , Akbas E , Demirköz M B 
Published: September 2024

Abstract
The alpha magnetic spectrometer (AMS) is a high-precision particle detector onboard the International Space Station containing six different subdetectors. The transition radiation detector and electromagnetic calorimeter (ECAL) are used to separate electrons/positrons from the abundant cosmic-ray proton background. The positron flux measured in space by AMS falls with a power law which unexpectedly softens above 25 GeV and then hardens above 280 GeV. Several theoretical models try to explain these phenomena, and a more accurate measurement of positrons at higher energies is needed to help test them. The currently used methods to reject the proton background at high energies involve extrapolating shower features from the ECAL to use as inputs for boosted decision tree and likelihood classifiers. We present a new approach for particle identification with the AMS ECAL using deep learning (DL). By taking the energy deposition within all the ECAL cells as an input and treating them as pixels in an image-like format, we train an MLP, a CNN, and multiple ResNets and convolutional vision transformers (CvTs) as shower classifiers. Proton rejection performance is evaluated using Monte Carlo (MC) events and ISS data separately. For MC, using events with a reconstructed energy between 0.2–2 TeV, at 90% electron accuracy, the proton rejection power of our CvT model is more than five times that of the other DL models. Similarly, for ISS data with a reconstructed energy between 50–70 GeV, the proton rejection power of our CvT model is more than 2.5 times that of the other DL models.
Local accommodation energy efficiency in Lisbon: a red flag for tourism, indoor thermal comfort, and energy renovation targets
Authors: Valente Inês , Fernandes Bárbara , César André , Menezes Laura , Gouveia João Pedro 
Published: September 2024

Abstract
Climate change affects all sectors of society, and tourism is no exception. Adaptation in this sector is challenging because of its vulnerability to rapid change and uncertainties of an environmental and political nature. Local accommodation (LA) (short-term rentals) plays a key role in the Portuguese economy and is, thus, potentially a key driver of increased energy efficiency and promoting buildings decarbonization, thereby contributing both to climate change adaptation and mitigation of this sector. However, there is limited research on energy efficiency and climate change resilience in the LA sector. To address this research gap, this study focuses on four civil parishes situated in the historic center of Lisbon, Portugal. Using a multidimensional approach and cross-sectoral datasets, we assessed the energy efficiency of LA in Lisbon and explored the cost of renovation measures. This analysis exposed poor energy performance in LA buildings and a low frequency of buildings with thermal insulation or double-glazed windows. Despite this, energy performance in the LA sector was comparatively better than in the residential sector. Additionally, LA s are equipped with more heating and cooling systems than the broader residential sector. This knowledge is relevant for researchers and policymakers, contributing to developing sustainable tourism approaches and reaching the objectives outlined in energy renovation policies.
Advances in forest restoration management and technology
Authors: Stanturf John A , Dumroese R Kasten , Elliott Stephen , Ivetic Vladan , Khokthong Watit , Kleine Michael , Lang Mait , Löf Magnus , Madsen Palle , Prescott Cindy , Young Timothy 
Published: September 2024

Abstract
Forest landscape restoration is a participatory process for setting objectives that should be explicitly stated and recognize the needs of local communities. Restoration technology should be appropriate to site and landscape conditions as well as socioeconomic and cultural contexts. This chapter focuses on establishing forests where they are currently lacking. The techniques discussed can also establish trees outside of forests or restore degraded forests. Topics include understanding and documenting initial conditions and monitoring outcomes. Passive regeneration techniques include natural regeneration, sometimes with assistance. Active techniques addressed cover direct seeding by hand or drones and planting. Quality plant material is critical to achieve adequate seedling survival; we survey advanced methods of genomics, molecular genetics, genetic engineering, and genome editing. Other topics include seed collection and seed orchards, nursery practices, seed zones, assisted migration, and planting designs. Site modification techniques considered are conventional mechanical site preparation, micro-catchments, mulching, water-absorbing gels, and biostimulants.
Impact of Vietnam-era G.I. Bill eligibility on later-life blood pressure distribution: evidence from the Vietnam draft lottery natural experiment
Authors: Khadka Aayush , Pacca Lucia , Glymour M Maria , Bibbins-Domingo Kirsten , White Justin S , Basu Sanjay , Jiang Fei , Vable Anusha M 
Published: September 2024

Abstract
We quantified the impact of Vietnam-era G.I Bill eligibility, which subsidized college education for eligible Veterans, on the later-life blood pressure distribution by exploiting the Vietnam draft lottery natural experiment. We restricted Health and Retirement Study data (2006-2018) to men born between 1947-1953 (N=1,970). We estimated intention-to-treat effects at the mean and 1st-99th quantiles of blood pressure using linear and quantile regressions. Our outcomes were systolic blood pressure (SBP), diastolic blood pressure (DBP), hypertension, and self-reported stroke. We proxied G.I. Bill eligibility using lottery-defined draft eligibility. We also conducted analyses stratified by childhood socioeconomic status (cSES) defined based on a previously validated measure. Draft eligibility reduced mean blood pressure outcomes (e.g., effect on SBP: -1.33 [95% confidence interval (CI) -2.85, 0.19]). Draft eligibility also had larger protective effects at higher quantiles of the SBP and DBP distributions relative to lower quantiles (effects on SBP at the 10th and 90th quantiles: -0.33mmHg [95% CI -2.35,1.68]; -3.00mmHg [95% CI -5.68,-0.32]). Draft eligibility had protective effects on blood pressure among low and medium cSES men but opposite effects among high cSES men. G.I. Bill eligibility reshaped the blood pressure distribution to one of lower morbidity risk, particularly among low and medium cSES men.
Estimating community-wide indirect effects of influenza vaccination: triangulation using mathematical models and bias analysis
Authors: Arinaminpathy Nimalan , Reed Carrie , Biggerstaff Matthew , Nguyen Anna T , Athni Tejas S , Arnold Benjamin F , Hubbard Alan , Reingold Art , Benjamin-Chung Jade 
Published: September 2024

Abstract
Understanding whether influenza vaccine promotion strategies produce community-wide indirect effects is important for establishing vaccine coverage targets and optimizing vaccine delivery. Empirical epidemiologic studies and mathematical models have been used to estimate indirect effects of vaccines but rarely for the same estimand in the same dataset. Using these approaches together could be a powerful tool for triangulation in infectious disease epidemiology because each approach is subject to distinct sources of bias. We triangulated evidence about indirect effects from a school-located influenza vaccination program using two approaches: a difference-in-difference (DID) analysis, and an age-structured, deterministic, compartmental model. The estimated indirect effect was substantially lower in the mathematical model than in the DID analysis (2.1% (95% Bayesian credible intervals 0.4 – 4.4%) vs. 22.3% (95% CI 7.6% – 37.1%)). To explore reasons for differing estimates, we used sensitivity analyses and probabilistic bias analyses. When we constrained model parameters such that projections matched the DID analysis, results only aligned with the DID analysis with substantially lower pre-existing immunity among school-age children and older adults. Conversely, DID estimates corrected for potential bias only aligned with mathematical model estimates under differential outcome misclassification. We discuss how triangulation using empirical and mathematical modelling approaches could strengthen future studies.
A new method for quantifying glyoxalase II activity in biological samples
Authors: Kadhum Mohammed Alaa , Hadwan Mahmoud Hussein 
Published: September 2024

Abstract
Glyoxalase II (Glo II) is a crucial enzyme in the glyoxalase system, and plays a vital role in detoxifying harmful metabolites and maintaining cellular redox balance. Dysregulation of Glo II has been linked to various health conditions, including cancer and diabetes. This study introduces a novel method using 2,4-dinitrophenylhydrazine (2,4-DNPH) to measure Glo II activity. The principle behind this approach is the formation of a colored hydrazone complex between 2,4-DNPH and pyruvate produced by the Glo II-catalyzed reaction. Glo II catalyzes the hydrolysis of S-D-lactoylglutathione (SLG), generating D-lactate and reduced glutathione (GSH). The D-lactate is then converted to pyruvate by lactate dehydrogenase, then reacting with 2,4-DNPH to form a brown-colored hydrazone product. The absorbance of this complex, measured at 430 nm, allows for the quantification of Glo II activity. The study rigorously validates the 2,4-DNPH method, demonstrating its stability, sensitivity, linearity, and resistance to interference from various biochemical substances. Compared to the existing UV method, this 2,4-DNPH-Glo II assay shows a strong correlation. The new protocol for measuring Glo II activity using 2,4-DNPH is simple, cost-effective, and accurate, making it a valuable tool for researchers and medical professionals. Its potential for widespread use in various laboratory settings, from academic research to clinical diagnostics, offers significant opportunities for future research and medical applications.
Persistent delirium is associated with cerebrospinal fluid markers of neuronal injury
Authors: Tsui Alex , Johnstone Benjamin , Heslegrave Amanda , Zetterberg Henrik , Watne Leiv Otto , Neerland Bjørn Erik , Krogseth Maria , Cunningham Colm , MacLullich Alasdair , Muniz Terrera Graciela , Davis Daniel , Caplan Gideon 
Published: September 2024

Abstract
Delirium is associated with the risk of future long-term cognitive impairment, but the degree to which markers of neuronal injury may be distinct or shared with dementia has yet to be comprehensively described. We investigated CSF biomarkers of dementia, astrocytosis and neuronal damage in a clinical cohort with persistent delirium, comparing them with an outpatient memory clinic sample. Our aim was to determine if different patterns of biomarker changes could implicate specific mechanisms for delirium-related neuronal injury over and above that attributable to comorbid dementia. We recruited 35 participants from the Prince of Wales Hospital, Sydney, Australia. We included inpatients with delirium persisting for at least 5 days (n = 15, 10 with underlying dementia) and participants from outpatient memory clinics (n = 20, 17 with dementia). CSF assays were as follows: amyloid-β42, amyloid-β40, phosphorylated tau181, neurofilament light chain and glial fibrillary acidic protein. We used propensity score matching to estimate effect sizes for each standardized CSF biomarker separately for persistent delirium (irrespective of underlying dementia) and dementia (irrespective of superimposed delirium). Compared with individuals without delirium, persistent delirium was associated with elevated glial fibrillary acidic protein (normalized coefficient per transformed standard deviation, β = 0.85; 95% confidence interval: 0.03–1.68) and neurofilament light chain (β = 1.1; 95% confidence interval: 0.5–1.6), but not phosphorylated tau181. Compared with individuals without dementia, glial fibrillary acidic protein, neurofilament light chain and phosphorylated tau181 were all increased to expected levels in dementia cases, with the former two biomarkers at levels comparable to those seen in persistent delirium [glial fibrillary acidic protein (β = 1.54; 95% confidence interval: 1.05–2.0) and neurofilament light chain (β = 0.65; 95% confidence interval: 0.24–1.1)]. Persistent delirium was linked with changes in CSF biomarkers not necessarily attributable to dementia. These findings support the potential that delirium is associated with direct neuronal injury independent of dementia pathophysiology. Whether this neuronal injury involves astrocyte dysfunction or direct axonal damage are both possibilities. Future work examining acute brain injury in delirium is needed.