bluuebunny/crossref_metadata_2025 huggingface dataset:
The Cycle 46 Configuration of the HARMONIE-AROME Forecast Model
Authors: Gleeson Emily , Kurzeneva Ekaterina , de Rooy Wim , Rontu Laura , Martín Pérez Daniel , Clancy Colm , Ivarsson Karl-Ivar , Engdahl Bjørg Jenny , Tijm Sander , Nielsen Kristian Pagh , Shapkalijevski Metodija , Maalampi Panu , Ukkonen Peter , Batrak Yurii , Kähnert Marvin , Kettler Tosca , van den Brekel Sophie Marie Elies , Adriaens Michael Robin , Theeuwes Natalie , Pálmason Bolli , Rieutord Thomas , Fannon James , Whelan Eoin , Viana Samuel , Homleid Mariken , Bessardon Geoffrey , Onvlee Jeanette , Samuelsson Patrick , Santos-Muñoz Daniel , Vignes Ole Nikolai , Stappers Roel
Published: November 2024

The aim of this technical note is to describe the Cycle 46 reference configuration of the HARMONIE-AROME convection-permitting numerical weather prediction model. HARMONIE-AROME is one of the canonical system configurations that is developed, maintained, and validated in the ACCORD consortium, a collaboration of 26 countries in Europe and northern Africa on short-range mesoscale numerical weather prediction. This technical note describes updates to the physical parametrizations, both upper-air and surface, configuration choices such as lateral boundary conditions, model levels, horizontal resolution, model time step, and databases associated with the model, such as for physiography and aerosols. Much of the physics developments are related to improving the representation of clouds in the model, including developments in the turbulence, shallow convection, and statistical cloud scheme, as well as changes in radiation and cloud microphysics concerning cloud droplet number concentration and longwave cloud liquid optical properties. Near real-time aerosols and the ICE-T microphysics scheme, which improves the representation of supercooled liquid, and a wind farm parametrization have been added as options. Surface-wise, one of the main advances is the implementation of the lake model FLake. An outlook on upcoming developments is also included.
Analysis of Microplastics in Industrial Processes—Systematic Analysis of Digestion Efficiency of Samples from Forestry, Wastewater Treatment Plants and Biogas Industries
Authors: Hrovat Blaž , Uurasjärvi Emilia , Koistinen Arto
Published: November 2024

Microplastics (MPs) are persistent, globally relevant pollutants that have thus far been rigorously studied in natural waters but have not been as extensively studied in industrial wastewaters. Samples were collected from the forestry industry, wastewater treatment plants and the biogas industry. An enzymatic treatment protocol for MPs’ detection was applied to an assortment of industrial samples ranging from wastewaters, effluents and condensates to sludges and digestates. The effects of selected enzymes were studied systematically to develop a basis for digestion protocols on industrial samples. Further, different methods of detection (micro FTIR and Raman) were compared to each other, and the samples were visually examined using SEM. The developed protocols in this study were then compared with blank samples, contamination controls and samples spiked with artificial microplastics. This research aimed to fill some of the gap in the knowledge regarding the analysis methods and especially in the type of samples screened for microplastics thus far and presents a systematic approach to MPs’ detection in industrial wastewaters. It highlights the issues with the used analytical methods (such as misidentification) and validates the analysis results with milled, random shape and wide-size-range reference MPs that represent real samples better than standardized, ideal round beads. This study provides the first-ever suggestion for an enzymatic digestion protocol for industrial sample analysis.
Influence of Drugs and Toxins on Decomposition Dynamics: Forensic Implications
Authors: Li Shuyue , Hu Zhonghao , Shao Yuming , Zhang Guoan , Wang Zheng , Guo Yadong , Wang Yu , Cui Wen , Wang Yequan , Ren Lipin
Published: November 2024

Drug and toxin-related deaths are common worldwide, making it essential to detect the postmortem concentration of various toxic substances at different stages of decomposition in a corpse. Indeed, determining the postmortem interval (PMI) and cause of death in an advanced stage of decomposed corpses has been a significant challenge in forensic investigations. Notably, the presence of drugs or toxins can have a significant impact on the microbial profile, potentially altering the succession of microbial communities and subsequent production of volatile organic compounds (VOCs), which, in turn, affect insect colonization patterns. This review aims to highlight the importance of investigating the interactions between drugs or toxins, microbial succession, VOC profiles, and insect behavior, which can provide valuable insights into forensic investigations as well as the ecological consequences of toxins occurring in decomposition. Overall, the detection of drugs and other toxins at different stages of decomposition can yield more precise forensic evidence, thereby enhancing the accuracy of PMI estimation and determination of the cause of death in decomposed remains.
Analyzing the Total Attractive Force and Hydrogen Storage on Two-Dimensional MoP2 at Different Temperatures Using a First-Principles Molecular Dynamics Approach
Authors: Viquez Alma Lorena Marcos , Torres Osiris Salas , Solís Luis Fernando Magaña
Published: November 2024

We performed first-principle molecular dynamics (FPMD) calculations to test the total attraction force on a physisorbed molecule at a given temperature and ambient pressure and applied it to the hydrogen storage on the 2D material MoP2. We considered a pristine material and one with 12.5% of Mo vacancies. By optimization, we calculated a gravimetric capacity for pristine MoP2 of 5.72%, with an adsorption energy of −0.13 eV/molecule. We found 6.02% and −0.14 eV/molecule for the defective surface. Next, we applied our approach to determine if the molecular hydrogen physisorption obtained by simple energy optimization exists for a given temperature and ambient pressure. We used this approach to determine the number of molecules adsorbed on the surface at a given temperature. Thus, we conducted a FPMD calculation at temperature T1, using optimization as the initial system configuration. Subsequently, we performed a second FPMD calculation at a temperature T2 (with T2 << T1), using the steady configuration of the first FPMD calculation as the initial configuration. We identified as adsorbed molecules at temperature T1, only those forced back toward the surface at temperature T2 due to kinetic energy loss at the lower temperature. The defective surface gave the best gravimetric capacity, ranging from 5.27% at 300 K to 6.02% at 77 K. The latter met the requirement from the US-DOE, indicating the potential practical application of our research in hydrogen storage.
Exploring the Metabolome and Antimicrobial Properties of Capsicum annuum L. (Baklouti and Paprika) Dried Powders from Tunisia
Authors: Serio Annalisa , Maggio Francesca , Ben Hsouna Anis , Ben Saad Rania , Taiti Cosimo , Garzoli Stefania
Published: November 2024

In this study, for the first time, the volatile fraction from two domesticated Capsicum annuum accessions (“Paprika” and “Baklouti”) collected in Tunisia was investigated by two complementary analytical techniques, such as Solid-Phase Microextraction–Gas Chromatography/Mass Spectrometry (SPME-GC/MS) and Proton Transfer Reaction–Time-of-Flight–Mass Spectrometry (PTR-ToF-MS). The obtained results highlighted the presence of a high number of Volatile Organic Compounds (VOCs), including monoterpene and sesquiterpene compounds with α-curcumene, I-zingiberene, β-bisabolene and β-sesquiphellandrene as the major components. In addition, GC/MS was used to investigate the non-volatile chemical composition of the dried powders and their extracts, which were found to be rich in sulfur compounds, fatty acids and sugars. Eleven bacterial strains were chosen to assess the antimicrobial effectiveness of the extracts. The results showed that the extracts exhibited strain-dependent behavior, and the type strains displayed a greater susceptibility to the treatments, if compared to the wild strains, and, in particular, showed the best antimicrobial activity against Gram-positive bacteria, such as Listeria monocytogenes and Staphylococcus aureus.
Near-Infrared Spectroscopy for Growth Estimation of Spirulina platensis Cultures
Authors: Malletzidou Lamprini , Kyratzopoulou Eleni , Kyzaki Nikoletta , Nerantzis Evangelos , Kazakis Nikolaos A.
Published: November 2024

The present study proposes the use of Near-Infrared (NIR) spectroscopy as a rapid method for estimating the growth of Spirulina platensis cultures, avoiding any sample manipulation or pretreatment. NIR spectroscopy in diffuse reflectance mode was used on culture volumes as received, with Principal Component Analysis (PCA) and Partial Least Squares (PLS) linear regression, for developing the calibration model in the wavelength range of 1000–2500 nm, in order to choose the appropriate wavelength to estimate the growth of the microalga. The local reflectance maximum at 1062.6 nm, connected with reduced water absorption and scattering effects by the microalga, was identified from PCA as the positive peak in the first loading plot, correlating diffuse reflectance with dilution levels. The calibration curve of diffuse reflectance at 1062.6 nm in response to dilution presented strong linearity, supported by a coefficient of determination (R2) of 0.995. Cross-validation of NIR spectra with a S. platensis culture confirmed the method’s reliability, showing that the growth follows an exponential pattern. The study shows that diffuse reflectance NIR spectroscopy can be used for the rapid monitoring of Spirulina platensis growth.
Nitrogen Assimilation, Biomass, and Yield in Response to Application of Algal Extracts, Rhizobium sp., and Trichoderma asperellum as Biofertilizers in Hybrid Maize
Authors: Pérez-Álvarez Sandra , Ochoa-Chaparro Erick H. , Anchondo-Páez Julio César , Escobedo-Bonilla César M. , Rascón-Solano Joel , Magallanes-Tapia Marco A. , Uranga-Valencia Luisa Patricia , Hernández-Campos Reinier , Sánchez Esteban
Published: November 2024

Nitrogen is essential for plants’ growth, yield, and crop quality, and its deficiency limits food production worldwide. In addition, excessive fertilization and inefficient use of N can increase production costs and cause environmental problems. A possible solution to this problem is the application of biofertilizers, which improve N assimilation and increase biomass and yield. Therefore, the objective of this research was to evaluate the impact of the application of a combination of green and red algae (Ulva lactuca and Solieria spp.), Rhizobium sp., Trichoderma asperellum, and the combination of the above three biofertilizers on N assimilation. A completely randomized design was performed, with 10 plants per treatment and five treatments: T1 = control; T2 = algal extracts; T3 = Rhizobium sp.; T4 = T. asperellum; T5 = T2 + T3 + T4. Our analyses showed that the biofertilizers’ application was better than the control. The application of Rhizobium sp. had the best performance amongst all of the biofertilizers, with the highest nitrate reductase activity in maize leaves, which enhanced photosynthesis, increasing biomass and yield. The use of Rhizobium sp. showed increases in biomass (13.4%) and yield (11.82%) compared to the control. This research shows that biofertilizers can be a key component for sustainable agricultural practices.
Diet-Wide Association Study for the Incidence of Type 2 Diabetes in Three Population-Based Cohorts
Authors: Woo Hye Won , Hoang Manh Thang , Shin Min-Ho , Koh Sang Baek , Kim Hyeon Chang , Kim Yu-Mi , Kim Mi Kyung
Published: November 2024

Background: Dietary factors are well-known modifiable risk factors for type 2 diabetes (T2D), but many studies overlook the interrelationships between these factors, even though foods are often consumed together and contain a variety of nutrients. Objectives: In this study, we employed a diet-wide association study approach to investigate the links between various dietary factors and T2D onset, taking into account complex dietary patterns. Methods: We analyzed 16,666 participants without T2D from three Korean population-based cohorts: the Multi-Rural Communities Cohort (n = 8302), the Atherosclerosis Risk of a Rural Area Korean General Population cohort (n = 4990), and the Kanghwa cohort (n = 3374). A two-step approach was employed. In the first step, robust Poisson regression analysis was used for the initial screening (false discovery rate-adjusted p-values < 0.05). In the second step, a hierarchical cluster analysis was conducted of all dietary factors, followed by mutual adjustment of the screened factors within each cluster to account for interrelationships. Results: The 11 food clusters screened were cooked rice with beans, rice cakes, breads/spreads, bread products, cheese and pizza/hamburger, grain powder, snack/confections, nuts and roasted beans, soy milk, traditional beverages, and non-native fruit. These factors were similarly distributed across three of the seven clusters in each cohort. After mutual adjustment, cooked rice with beans (p-value ≤ 2.00 × 10−7 in all three cohorts) and non-native fruits (p-value ≤ 5.91 × 10−3 in two cohorts) remained significantly associated with lower T2D risk in more than one cohort. Conclusions: The inverse association of cooked rice with beans, not observed with other types of cooked rice, and that of non-native fruits, suggest that incorporating beans into rice and eating various fruits may be an effective strategy for preventing diabetes.
Physiological, Performance and Perceptual Effects of Acute Intake of an L-Arginine and L-Citrulline Beverage Prior to a Repeated Bout of Intensive Running Among University Soccer Players
Authors: Nyawose Siphamandla , Naidoo Rowena , Naumovski Nenad , McKune Andrew J.
Published: November 2024

The purpose of this study was to determine whether a combined L-arginine and L-citrulline beverage can enhance total nitric oxide (NOx), as well as physiological (cardiopulmonary metrics) and perceptual (rate of perceived exertion) responses to a repeated bout of high-intensity exercise among university soccer players. Thirty male soccer players were included in a randomized double-blind, placebo-controlled, parallel design. Participants performed two bouts of high-intensity running, spaced two hours apart. Forty minutes before the second bout only, participants consumed a 500 mL beverage containing 6 g L-arginine and 6 g L-citrulline (n = 15) or placebo (n = 15). Blood NOx concentration was measured immediately before and after both bouts. There was no significant increase in NOx or significant interaction effects for physiological, performance, or perceptual variables between the L-arginine/L-citrulline and placebo groups. The peak volume of oxygen uptake of the L-arginine/L-citrulline group was significantly higher in the second compared with the first exercise bout (54.92 ± 4.81 vs. 50.54 ± 9.22 mL/kg/min; p = 0.01). In the second bout of exercise, time to exhaustion in the L-arginine/L-citrulline group increased by 8.5% (~60 s) compared to the first. In conclusion, these results suggest that a single dose of L-arginine/L-citrulline beverage did not increase NOx yet seemed to impact aerobic metabolism in university soccer players.
A Comprehensive Review on the Total Synthesis of Antibacterial Furanomycin and Its Analogs
Authors: Rohokale Rajendra , Mane Rajendra
Published: November 2024

l-(+)-Furanomycin 1 is a miniature antibacterial natural product that contains an α-amino acid core. This non-proteinogenic α-amino acid was first isolated in 1967 by Katagiri and co-workers from the fermentation broth of Streptomyces threomyceticus L-803 (ATCC 15795). It is a substrate of isoleucyl aminoacyl-tRNA synthetase that replaces isoleucine in the protein translation process and exhibits antibacterial properties in vitro. It effectively acts as an antibacterial agent against M. tuberculosis, E. coli, B. subtilis, and some Shigella and Salmonella bacterial species at concentrations as low as the micromolar range. Consequently, synthetic chemists have garnered considerable interest from their specific structure–activity profile, distinctive chemical compositions, and distinct biological profile. This review comprehensively describes cutting-edge synthetic methodologies for synthesizing furanomycin and its analogs reported to date. Therefore, this review will offer an initial perspective on synthesizing furanomycin and its customized compounds.
Therapeutic Potential of Psychedelic Compounds for Substance Use Disorders
Authors: Valdez Tamara , Patel Valbhi , Senesombath Nattaphone , Hatahet-Donovan Zayd , Hornick Mary
Published: November 2024

Psychedelics have recently (re)emerged as therapeutics of high potential for multiple mental health conditions, including substance use disorders (SUDs). Despite early mid-20th century anecdotal reports and pilot studies demonstrating the possibility of these substances in efficaciously treating conditions such as alcohol and opioid use disorders, legal restrictions and social stigma have historically hindered further research into this area. Nevertheless, concurrent with the rise in SUDs and other mental health conditions, researchers have again turned their attention to these compounds, searching for differing pharmacological targets as well as more holistic treatments that might increase patient adherence and efficacy. The aim of this review is to examine the emerging evidence-based data with regards to the therapeutic treatment of SUDs with the psychedelic compounds psilocybin, ketamine, lysergic acid diethylamide (LSD), 3,4-methylenedioxymethamphetamine (MDMA), ayahuasca, ibogaine and peyote.
An Assessment of the Catalytic and Adsorptive Performances of Cellulose Acetate-Based Composite Membranes for Oil/Water Emulsion Separation
Authors: Gurusamy Mahendran , Thangavel Sangeetha , Čespiva Jakub , Ryšavý Jiří , Yan Wei-Mon , Jadlovec Marek , Arthanareeswaran Gangasalam
Published: November 2024

Cellulose acetate (CA) mixed-matrix membranes incorporating polyvinylpyrrolidone (PVP), bentonite (B or Ben), graphene oxide (GO), and titanium dioxide (TiO2) were prepared by the phase inversion separation technique for oil/water separation. An investigation was performed where the mixed-matrix membrane was tested for the separation performance of hydrophilic and hydrophobic surface properties. An ultrafiltration experiment at the laboratory scale was used to test dead-end ultrafiltration models developed for the treatment performances of oily wastewater under dynamic full-scale operating conditions. Artificial oily wastewater solutions were prepared from hexane, toluene, and engine oil with Tween80 emulsions for oil removal treatment using composite membranes. The impacts of material hydrophilicity, weight loss, permeability, and pore size were investigated, and it was found that the oil retention of membranes with larger pore sizes enabled much more sophisticated water flux. The CA-GO-, CA-B-, and CA-TiO2-incorporated membranes achieved pure water flux (PWF) values of 45.19, 53.41, and 100.25 L/m2h, respectively. The performance of CA-TiO2 in oil/water emulsion rejection was assessed, and the rejection of engine oil/water, toluene/water, and hexane/water mixtures was determined to be 95.21%, 90.33%, and 92.4%, respectively. The CA-based mixed-matrix membrane portrayed better antifouling properties due to enhanced hydrophilicity and water molecules. The CA-TiO2-incorporated membrane possessed the potential to provide high separation efficiency for oily wastewater treatment. This study demonstrates the potential of fine-tuning membrane performances through material hybridization to achieve efficient wastewater treatment.
Predicting Performance of Call Center Staff: The Role of Cognitive Ability and Emotional Intelligence
Authors: Treglown Luke , Furnham Adrian
Published: November 2024

This study examined the relationship between cognitive ability (IQ) and emotional intelligence (EQ) in predicting a range of different performance metrics from a call centre environment. In all, 303 call centre staff completed multi-dimensional measures of both EQ and IQ. We also had recorded nine performance data measures for each individual over a 12-month period. There were a few significant correlations with IQ (4/35) and a few more with EQ (4/28), though all EQ measures were related to “Errors Made over the year”. The performance metric that had most correlates was Average Handling Time (AHT) relating to speed of working. The number of errors an employee made was significantly positively correlated with all four EQ factors. Correlational and Structural Equation Model (SEM) analysis highlighted the importance of analysing performance metrics as distinct variables, finding contradictory evidence in the sense that some individual difference factors correlated positively with some and negatively with other outcome measures. The results are discussed in relation to the theoretical implications for researchers interested in analysing call centre performance, and also practical implications for organisations with call centres.
Contribution to the Statistical Mechanics of Static Triplet Correlations and Structures in Fluids with Quantum Spinless Behavior
Authors: Sesé Luis M.
Published: November 2024

The current developments in the theory of quantum static triplet correlations and their associated structures (real r-space and Fourier k-space) in monatomic fluids are reviewed. The main framework utilized is Feynman’s path integral formalism (PI), and the issues addressed cover quantum diffraction effects and zero-spin bosonic exchange. The structures are associated with the external weak fields that reveal their nature, and due attention is paid to the underlying pair-level structures. Without the pair, level one cannot fully grasp the triplet extensions in the hierarchical ladder of structures, as both the pair and the triplet structures are essential ingredients in the triplet response functions. Three general classes of PI structures do arise: centroid, total continuous linear response, and instantaneous. Use of functional differentiation techniques is widely made, and, as a bonus, this leads to the identification of an exact extension of the “classical isomorphism” when the centroid structures are considered. In this connection, the direct correlation functions, as borrowed from classical statistical mechanics, play a key role (either exact or approximate) in the corresponding quantum applications. Additionally, as an auxiliary framework, the traditional closure schemes for triplets are also discussed, owing to their potential usefulness for rationalizing PI triplet results. To illustrate some basic concepts, new numerical calculations (path integral Monte Carlo PIMC and closures) are reported. They are focused on the purely diffraction regime and deal with supercritical helium-3 and the quantum hard-sphere fluid.
The Effects of Proton and Photon Radiation Therapy on the Development of Pediatric Dermatitis
Authors: Kumar Sandra , Gonzalez Angelica , Farbo David , Albritton Karen , Ray Anish
Published: November 2024

Although radiation therapy is the leading option for effective cancer treatment, a prevalent side effect associated with it is dermatitis. Despite some available literature on this topic, there remain many gaps that need to be addressed. The goal of this study is to determine the incidence of radiation-induced dermatitis (RID) among children receiving proton and photon therapies; a retrospective chart review, at a single institution, was conducted on oncology patients who underwent proton or photon therapy radiation between 2018 and 2023. Significant differences were found between the Radiation Therapy Oncology Group (RTOG) score and the total radiation dose (p = 0.04). The median total dose of radiation received by those with an RTOG score of l was 5040.0 mGy and increased to 7600 mGy for those with a score of 3. A significant association was found between those who received chemotherapy and dermatitis (p = 0.04). No significance was found between the incidence of dermatitis in photon and proton therapy (p = 1.00). The study showed that multiple factors, including total radiation dose and chemotherapy, can affect RID. These relationships can be used to determine the modality, dose, and additional treatment options best suited to treat cancer patients in the pediatric population.
Continuous Flow Optimisation of the Pudovik Reaction and Phospha-Brook Rearrangement Using DBN
Authors: Dean Joseph , Buckler Reinoso Natalia , Spiedo Francesco , Romero Fernández Carola , Patel Bhaven
Published: November 2024

Flow chemistry has shown significant versatility over the last two decades, offering advantages in efficiency, scalability, and sustainability. In this study, the continuous stirred tank reactor (CSTR) was used to optimise the synthesis of α-hydroxyphosphonates via the Pudovik reaction and their subsequent conversion to phosphates through the phospha-Brook rearrangement. The study highlights that using CSTRs allows for better control over reaction parameters, leading to reduced reaction times and improved yields compared to traditional batch methods. The optimised conditions successfully facilitated a range of organophosphates, including electron-rich and electron-poor derivatives, with high efficiency. Additionally, a one-pot tandem process combining the Pudovik reaction and the phospha-Brook rearrangement was developed, reducing reaction times to two hours while maintaining comparable yields. This work demonstrates the potential of CSTRs in flow chemistry for synthesising complex organophosphorus compounds, achieving higher reaction yields and shorter reaction times, highlighting the effectiveness of continuous flow methodologies.
Efficient Production of Platform Chemicals from Lignocellulosic Biomass by Using Nanocatalysts: A Review
Authors: Jain Sapna , Kassaye Samuel
Published: November 2024

This paper discusses significant advancements in using lignocellulosic biomass for the sustainable production of biofuels and chemicals. As fossil-based resources decline and environmental concerns rise, the paper emphasizes the role of integrated biorefineries in producing renewable liquid fuels and high-value chemicals from biomass. It highlights exploring various green pathways for biomass conversion, with a particular focus on nanocatalysis. Due to their large surface area-to-volume ratio, nanocatalysts provide enhanced catalytic activity and efficiency in biomass transformation processes. The review delves into the synthesis of value-added and furfural platform chemicals alongside the hydrogenolysis of 5-hydroxymethylfurfural (5-HMF) into biofuels like 2,5-dimethylfuran (DMF) and 2,5-dimethyltetrahydrofuran (DMTHF). The paper ultimately underscores the importance of nanotechnology in achieving high yield and selectivity in the biomass conversion process, positioning it as a promising approach for future sustainable energy and chemical production.
Airborne Multi-Channel Forward-Looking Radar Super-Resolution Imaging Using Improved Fast Iterative Interpolated Beamforming Algorithm
Authors: Liu Ke , Li Yueli , Xu Zhou , Zhou Zhuojie , Jin Tian
Published: November 2024

Radar forward-looking imaging is critical in many civil and military fields, such as aircraft landing, autonomous driving, and geological exploration. Although the super-resolution forward-looking imaging algorithm based on spectral estimation has the potential to discriminate multiple targets within the same beam, the estimation of the angle and magnitude of the targets are not accurate due to the influence of sidelobe leakage. This paper proposes a multi-channel super-resolution forward-looking imaging algorithm based on the improved Fast Iterative Interpolated Beamforming (FIIB) algorithm to solve the problem. First, the number of targets and the coarse estimates of angle and magnitude are obtained from the iterative adaptive approach (IAA). Then, the accurate estimates of angle and magnitude are achieved by the strategy of iterative interpolation and leakage subtraction in FIIB. Finally, a high-resolution forward-looking image is obtained through non-coherent accumulation. The simulation results of point targets and scenes show that the proposed algorithm can distinguish multiple targets in the same beam, effectively improve the azimuthal resolution of forward-looking imaging, and attain the accurate reconstruction of point targets and the contour reconstruction of extended targets.
Sea Surface Temperature Prediction Using ConvLSTM-Based Model with Deformable Attention
Authors: Shi Benyun , Ge Conghui , Lin Hongwang , Xu Yanpeng , Tan Qi , Peng Yue , He Hailun
Published: November 2024

Sea surface temperature (SST) prediction has received increasing attention in recent years due to its paramount importance in the various fields of oceanography. Existing studies have shown that neural networks are particularly effective in making accurate SST predictions by efficiently capturing spatiotemporal dependencies in SST data. Among various models, the ConvLSTM framework is notably prominent. This model skillfully combines convolutional neural networks (CNNs) with recurrent neural networks (RNNs), enabling it to simultaneously capture spatiotemporal dependencies within a single computational framework. To overcome the limitation that CNNs primarily capture local spatial information, in this paper we propose a novel model named DatLSTM that integrates a deformable attention transformer (DAT) module into the ConvLSTM framework, thereby enhancing its ability to process more complex spatial relationships effectively. Specifically, the DAT module adaptively focuses on salient features in space, while ConvLSTM further captures the temporal dependencies of spatial correlations in the SST data. In this way, DatLSTM can adaptively capture complex spatiotemporal dependencies between the preceding and current states within ConvLSTM. To evaluate the performance of the DatLSTM model, we conducted short-term SST forecasts in the Bohai Sea region with forecast lead times ranging from 1 to 10 days and compared its efficacy against several benchmark models, including ConvLSTM, PredRNN, TCTN, and SwinLSTM. Our experimental results show that the proposed model outperforms all of these models in terms of multiple evaluation metrics short-term SST prediction. The proposed model offers a new predictive learning method for improving the accuracy of spatiotemporal predictions in various domains, including meteorology, oceanography, and climate science.
Metallic Artifacts’ Reduction in Microtomography Using the Bone- and Soft-Tissue Decomposition Method
Authors: Juszczyk Jan , Pałachniak Jakub , Piętka Ewa
Published: November 2024

Artifacts in computed tomography and X-ray microtomography are image distortions caused by various factors. Some can be reduced before or during the examination, while others are removed algorithmically after image acquisition. The latter group includes metallic artifacts caused by metal objects in the sample. This paper proposes a new method for eliminating metallic artifacts, applying a bone- and soft-tissue decomposition (BSTD) algorithm to microtomography raw data before the reconstruction process. We show that the decomposition algorithm can effectively remove metallic artifacts in microCT images, which increases the image contrast and allows for better visualization of regions near the metallic elements. For quantity analysis, we computed SSIM and PSNR factors, and we observed values increasing from 0.97 to 0.99 and from 40 dB to 43 dB, respectively.
Structural Damage Detection Using PZT Transmission Line Circuit Model
Authors: Vieira Filho Jozue , Cortez Nicolás E. , De Oliveira Mario , Lima Luis Paulo M. , Park Gyuhae
Published: November 2024

Arrangements of piezoelectric transducers, such as PZT (lead zirconate titanate), have been widely used in numerous structural health monitoring (SHM) applications. Usually, when two or more PZT transducers are placed close together, significant interference, namely crosstalk, appears. Such an effect is usually neglected in most SHM applications. However, it can potentially be used as a sensitive parameter to identify structural faults. Accordingly, this work proposes using the crosstalk effect in an arrangement of PZT transducers modeled as a multiconductor transmission line to detect structural damage. This effect is exploited by computing an impedance matrix representing a host structure with PZTs attached to it. The proposed method was assessed in an aluminum beam structure with two PZTs attached to it using finite element modeling in OnScale® software to simulate both healthy and damaged conditions. Similarly, experimental tests were also carried out. The results, when compared to those obtained using a traditional electromechanical impedance (EMI) method, prove that the new approach significantly improved the sensitivity of EMI-based technique in SHM applications.
Secure and Lightweight Cluster-Based User Authentication Protocol for IoMT Deployment
Authors: Su Xinzhong , Xu Youyun
Published: November 2024

Authentication is considered one of the most critical technologies for the next generation of the Internet of Medical Things (IoMT) due to its ability to significantly improve the security of sensors. However, higher frequency cyber-attacks and more intrusion methods significantly increase the security risks of IoMT sensor devices, resulting in more and more patients’ privacy being threatened. Different from traditional IoT devices, sensors are generally considered to be based on low-cost hardware designs with limited storage resources; thus, authentication techniques for IoMT scenarios might not be applicable anymore. In this paper, we propose an efficient three-factor cluster-based user authentication protocol (3ECAP). Specifically, we establish the security association between the user and the sensor cluster through fine-grained access control based on Merkle, which perfectly achieves the segmentation of permission. We then demonstrate that 3ECAP can address the privilege escalation attack caused by permission segmentation. Moreover, we further analyze the security performance and communication cost using formal and non-formal security analysis, Proverif, and NS3. Simulation results demonstrated the robustness of 3ECAP against various cyber-attacks and its applicability in an IoMT environment with limited storage resources.
High-Precision Measurement Method for Small Angles Based on the Defect Spot Mode of the Position-Sensitive Detector
Authors: Zhai Yusheng , Wang Guorong , Zhao Yiheng , Wu Rongxin , Zhang Lin , Su Zhan , Zhang Zhifeng , Yang Peng , Zhang Ruiliang
Published: November 2024

The paper proposes and verifies a small-angle measurement method based on the defect spot mode of the position-sensitive detector (PSD). With the output characteristics of the PSD in the defect spot mode and the size transformation properties of a focused beam, the measurement sensitivity can be significantly improved. Calibration experiments with the piezoelectric transducer (PZT) indicate that compared with the current PSD-based autocollimation method, the proposed method can improve the sensitivity of small-angle measurement by 57 times, and the measurement sensitivity of the proposed method can be further improved by optimizing the system parameters, while the proposed method has the advantages of a simple system and high real-time performance. Therefore, the proposed method is expected to be used in high-precision motion error detection, as well as in shape and position measurement.
In Their Own Words: Muslim Women Reconstruct the Sexual Script
Authors: Fagen Jennifer Lara
Published: November 2024

Using semi-structured, qualitative interviews of 25 heterosexual Muslim women residing in the US, the author examines the extent to which respondents simultaneously constructed and deconstructed the gender dichotomy when explaining sexuality, countering reductionist accounts of Muslim women’s sexuality. Integrating concepts of religiosity and gender norms, respondents reconfigured the dominant discourse of power and sexuality in innovative ways. One of the main themes that emerged from this research is that male sex drive discourse, typically associated with power and “machismo” within the traditional sexual script, was reimagined by Muslim women as an indicator of women’s greater strength in the eyes of God.
Female Offenders in Human Trafficking: Analyzing Roles in a Spanish Sample
Authors: Giménez-Salinas Andrea
Published: November 2024

Offenders convicted of trafficking human beings for sexual exploitation involve a high percentage of women compared to other similar offenses. Previous studies have searched for explanations for the dynamics of the illegal sex market and the coercion experienced by victims during the process of exploitation and exit. This article analyses the content of 58 judicial decisions involving a sample of 148 women convicted in Spain of trafficking in human beings between 2017 and 2024. Two main dimensions are explored: the criminal organizations performing the sexual exploitation phase in Spain and the characteristics, positions, and roles of women traffickers within the criminal organizations. Half of the sample occupies leadership roles, while the other half consists of supporters, especially in larger trafficking networks. Regarding the positions and roles of women offenders, supporters and partners in crime are at higher risk of being coerced due to the nature of their roles or partnerships.
Sustainability and Social Farming in the Czech Republic: The Impact of Selected Factors on the Employment of Disadvantaged Persons in Agriculture
Authors: Chovanec Tomáš , Eze Festus Onyebuchi , Muhammad Atif , Moudrý Jan , Bartoš Petr , Mukosha Chisenga Emmanuel , Eke Okechukwu George
Published: November 2024

In the agricultural sector, where factors like the type of agriculture, management techniques, and access to funding are critical, disadvantaged people face significant barriers to employment. This study investigated the effects of these factors, especially with regard to sustainability and social farming, on the employment of disadvantaged persons in the Czech Republic. We sent questionnaires to 2036 agricultural businesses within the Czech Republic, and the data we received were sorted and analyzed. There was a favorable relationship between farm size and employment chances. Disadvantaged people were more likely to be hired by large farms, especially those larger than 250 hectares. Furthermore, mixed-production farms were more capable of employing disadvantaged persons, unlike conventional farms, which reached their maximum employment levels at one, three, or six workers. Organic farming had a more even distribution, while biodynamic farming showed limited capacity to employ disadvantaged persons. Farms involved in fundraising had fewer farms but employed more disadvantaged persons (number of employees peaked at two, four, and six), while farms that did not engage in fundraising hired more disadvantaged individuals (peaked at one and three employees). The motivations for employing disadvantaged persons were primarily social concerns, as well as labor shortages and economic and innovative factors. These findings show the importance of agricultural enterprises using these factors to improve the social and economic well-being of disadvantaged persons.
Correction: Sharma et al. Carbon Farming: Prospects and Challenges. Sustainability 2021, 13, 11122
Authors: Sharma Meenakshi , Kaushal Rajesh , Kaushik Prashant , Ramakrishna Seeram
Published: November 2024

Affiliation Update [...]
Small Farmer’s Perceptions of Climate Change and Adoption of Climate-Smart Practices: Evidence from Missouri, USA
Authors: Chen Rui , Su Ye , Tran Lan
Published: November 2024

Using survey data of Missouri small producers in 2022, this paper explores their perceptions of climate change and factors affecting their adoption of climate-smart practices. A synthesized climate change perception (CCP) index is developed to assess the effects of cognition and social demographics of producers on climate-smart practices (CSPs) adoption. The results show that 86.0% of participants have relatively high perceptions of climate change, and 82.0% have adopted at least one climate-smart practice; the higher the climate change perception index, the more likely the producers will adopt climate-smart practices. The findings encourage education on knowledge related to climate change, the relationship between climate change and agriculture, and how CSPs can reduce climate change. Specifically, we find specialty crop producers are more likely to adopt CSPs than other producers; and a one-unit increase in the CCP index can increase the CSP adoption rate by 4.61% for livestock producers and 2.61% for organic producers, suggesting relevant education programs can be tailored to the needs of livestock and organic farmers to improve their adoption rates of CPSs. Further, more resources are needed to support the farmers who reside in severely climate change – impacted areas for their sustainable production and climate sustainability.
Research Driven by User Demand for the Design of a Cross-Border Travel Credential Bag
Authors: Li Shuyun , Zhang Xizhi , Wen Kuohsun , Jiang Jiawei
Published: November 2024

Cross-border travel often presents challenges in document storage, which can burden travelers. This study addresses the issue by designing a credential bag that enhances safety, convenience, and environmental sustainability. Utilizing design research, we applied the KANO model to categorize user needs, employed analytic hierarchy process to prioritize these needs, and used quality functional deployment to translate them into specific design elements. The KANO model has identified a total of 18 demand indicators, including “must-be”, one-dimensional, and attractive. An analytic hierarchy process analysis of the secondary indicators found that demands for the security of anti-theft, partition storage of documents, a variety of carrying methods and green sustainability have relatively high weight. The innovative solutions derived from the KANO-AHP-QFD model improve design practices and user experience in document storage. This approach offers a scientific and practical reference for the sustainable development of travel supplies and the luggage industry.
The Landscapes of Sustainability in Library and Information Science: Diachronous Citation Perspective
Authors: Kamińska Anna Małgorzata , Opaliński Łukasz , Wyciślik Łukasz
Published: November 2024

Sustainability issues constitute a distinct subdiscipline of librarianship and information science, with its own areas of study, methods, and areas of application. Despite being nearly 30 years old, there are still divergent opinions on its current phase of development and its links to other scientific disciplines. The authors aim to clarify and summarize the ongoing discussion through citation analysis, shedding light on the lifecycle of research papers in sustainability-oriented library and information science, the current research subjects of focus, the influence of subdomains within the discipline on other scientific areas, and the overall quantitative and qualitative landscape of the discipline. A detailed elucidation of the inquiry’s results is intended to outline the discipline’s cognitive structure and its impact on sustainability science. The lifecycle of disciplinary papers indicates the dynamic development of the field. Sustainability-oriented library and information science is well-established, and its research focus has already been consolidated. The optimal citation window for measuring the impact strength in this discipline is a period of 3 to 4 years. “Culture” and “Education” have been identified as the most forward-looking subdisciplines, whereas “Buildings” and “Collections” exhibit less dynamic growth. The social sustainability pillar is the dominant one, while the environmental pillar is slightly less prominent. The economic pillar is the least represented. Although the majority of information exchange occurs within the discipline, it maintains strong and numerous links with several other fields, including both technical and social sciences, as well as the humanities.
Intermittent Drip Irrigation Soil Wet Front Prediction Model and Effective Water Storage Analysis
Authors: Zhu Zhu , Rasheed Muhammad Waseem , Safdar Muhammad , Yao Baolin , Tumaerbai Hudan , Sarwar Abid , Zhu Lianyong
Published: November 2024

The depth and width of drip infiltration play a critical role in designing effective irrigation strategies. However, existing models primarily focus on continuous irrigation and fail to predict wetting patterns under intermittent drip irrigation. This study developed an infiltration model to estimate soil moisture depth and width under intermittent drip irrigation and identified strategies that enhance effective water storage. Indoor soil box simulations were conducted, with continuous drip irrigation as the control. Results showed that intermittent irrigation increased infiltration width and reduced depth, maximizing water storage efficiency. We recommend adopting an intermittent irrigation system with 1.5 h of irrigation followed by a 0.5 h interval, repeated four times. This system increased effective water storage by up to 16.23% compared to continuous irrigation. The proposed method is suitable for sandy loam farmland in southern Xinjiang and can significantly improve water use efficiency in arid regions.
Recent Advancements in Applying Machine Learning in Power-to-X Processes: A Literature Review
Authors: Shojaei Seyed Mohammad , Aghamolaei Reihaneh , Ghaani Mohammad Reza
Published: November 2024

For decades, fossil fuels have been the backbone of reliable energy systems, offering unmatched energy density and flexibility. However, as the world shifts toward renewable energy, overcoming the limitations of intermittent power sources requires a bold reimagining of energy storage and integration. Power-to-X (PtX) technologies, which convert excess renewable electricity into storable energy carriers, offer a promising solution for long-term energy storage and sector coupling. Recent advancements in machine learning (ML) have revolutionized PtX systems by enhancing efficiency, scalability, and sustainability. This review provides a detailed analysis of how ML techniques, such as deep reinforcement learning, data-driven optimization, and predictive diagnostics, are driving innovation in Power-to-Gas (PtG), Power-to-Liquid (PtL), and Power-to-Heat (PtH) systems. For example, deep reinforcement learning has improved real-time decision-making in PtG systems, reducing operational costs and improving grid stability. Additionally, predictive diagnostics powered by ML have increased system reliability by identifying early failures in critical components such as proton exchange membrane fuel cells (PEMFCs). Despite these advancements, challenges such as data quality, real-time processing, and scalability remain, presenting future research opportunities. These advancements are critical to decarbonizing hard-to-electrify sectors, such as heavy industry, transportation, and aviation, aligning with global sustainability goals.