bluuebunny/crossref_metadata_2025 huggingface dataset:
Data Protection Issues in Automated Decision-Making Systems Based on Machine Learning: Research Challenges
Authors: Christodoulou Paraskevi , Limniotis Konstantinos
Published: March 2024

Data protection issues stemming from the use of machine learning algorithms that are used in automated decision-making systems are discussed in this paper. More precisely, the main challenges in this area are presented, putting emphasis on how important it is to simultaneously ensure the accuracy of the algorithms as well as privacy and personal data protection for the individuals whose data are used for training the corresponding models. In this respect, we also discuss how specific well-known data protection attacks that can be mounted in processes based on such algorithms are associated with a lack of specific legal safeguards; to this end, the General Data Protection Regulation (GDPR) is used as the basis for our evaluation. In relation to these attacks, some important privacy-enhancing techniques in this field are also surveyed. Moreover, focusing explicitly on deep learning algorithms as a type of machine learning algorithm, we further elaborate on one such privacy-enhancing technique, namely, the application of differential privacy to the training dataset. In this respect, we present, through an extensive set of experiments, the main difficulties that occur if one needs to demonstrate that such a privacy-enhancing technique is, indeed, sufficient to mitigate all the risks for the fundamental rights of individuals. More precisely, although we manage—by the proper configuration of several algorithms’ parameters—to achieve accuracy at about 90% for specific privacy thresholds, it becomes evident that even these values for accuracy and privacy may be unacceptable if a deep learning algorithm is to be used for making decisions concerning individuals. The paper concludes with a discussion of the current challenges and future steps, both from a legal as well as from a technical perspective.
Food Insecurity Is High in a Multi-Site Cohort of Transgender Women Vulnerable to or Living with HIV in the Eastern and Southern United States: Baseline Findings from the LITE Cohort
Authors: Zubizarreta Dougie , Wirtz Andrea L. , Humes Elizabeth , Cooney Erin E. , Stevenson Meg , Althoff Keri N. , Radix Asa E. , Poteat Tonia , Beyrer Chris , Wawrzyniak Andrew J. , Mayer Kenneth H. , Reisner Sari L.
Published: March 2024

The prevalence and correlates of food insecurity—the unavailability of food and limited access to it—have not been adequately considered among transgender women (TW), particularly alongside other health-related conditions burdening this population, such as HIV infection. This study examined the prevalence and correlates of food insecurity among TW. Between 2018 and 2020, 1590 TW in the Eastern and Southern U.S. completed a multi-site baseline assessment (socio-behavioral survey and HIV testing). Descriptive statistics were calculated and multivariable Poisson models with robust error variance were used to estimate prevalence ratios and 95% confidence intervals for correlates of food insecurity (dichotomized as sometimes-to-always vs. seldom-to-never running out of food). Eighteen percent of TW were living with HIV and nearly half of participants (44%) reported food insecurity. Correlates of food insecurity included being Black, multiracial, or another race/ethnicity; having < college education, low income, unstable housing, and high anticipated discrimination; and a history of sex work and sexual violence (all p < 0.05). Food insecurity was highly prevalent among TW. Current programs to provide food support do not adequately meet the needs of TW. HIV pr evention and care programs may benefit from addressing food insecurity.
Toxicity Screening of Fungal Extracts and Metabolites, Xenobiotic Chemicals, and Indoor Dusts with In Vitro and Ex Vivo Bioassay Methods
Authors: Hintikka Tuomas , Andersson Maria A. , Lundell Taina , Marik Tamás , Kredics László , Mikkola Raimo , Andersson Magnus C. , Kurnitski Jarek , Salonen Heidi
Published: March 2024

It is controversial how useful bioassays are for identifying the in vivo toxicity of hazardous environmental exposures. In this study, fruiting bodies of forest mushrooms (n = 46), indoor mold colonies (n = 412), fungal secondary metabolites (n = 18), xenobiotic chemicals such as biocides and detergents (n = 6), and methanol extracts of indoor dusts from urban buildings (n = 26) were screened with two different bioactivity assays: boar sperm motility inhibition (BSMI) and inhibition of cell proliferation (ICP) tests. For the forest mushrooms, the toxicity testing result was positive for 100% of poisonous-classified species, 69% of non-edible-classified species, and 18% of edible-classified species. Colonies of 21 isolates of Ascomycota mold fungal species previously isolated from water-damaged buildings proved to be toxic in the tests. Out of the fungal metabolites and xenobiotic chemicals, 94% and 100% were toxic, respectively. Out of the indoor dusts from moldy-classified houses (n = 12) and from dry, mold-free houses (n = 14), 50% and 57% were toxic, respectively. The bioassay tests, however, could not differentiate the samples from indoor dusts of moldy-classified buildings from those from the mold-free buildings. Xenobiotic chemicals and indoor dusts were more toxic in the BSMI assay than in the ICP assay, whereas the opposite results were obtained with the Ascomycota mold colonies and fungal secondary metabolites. The tests recognized unknown methanol-soluble thermoresistant substances in indoor settled dusts. Toxic indoor dusts may indicate a harmful exposure, regardless of whether the toxicity is due to xenobiotic chemicals or microbial metabolites.
Ovine Herpesvirus 2 Glycoprotein B Complementation Restores Infectivity to a Bovine Herpesvirus 4 gB-Null Mutant
Authors: Moré Daniela D. , Baker Katherine N. , Shringi Smriti , Bastos Reginaldo G. , O’Toole Donal , Donofrio Gaetano , Cunha Cristina W.
Published: March 2024

Ovine herpesvirus 2 (OvHV-2) and bovine herpesvirus 4 (BoHV-4) are gamma herpesviruses that belong to the genera Macavirus and Rhadinovirus, respectively. As with all herpesviruses, both OvHV-2 and BoHV-4 express glycoprotein B (gB), which plays an essential role in the infection of host cells. In that context, it has been demonstrated that a BoHV-4 gB-null mutant is unable to infect host cells. In this study, we used homologous recombination to insert OvHV-2 ORF 8, encoding gB, into the BoHV-4 gB-null mutant genome, creating a chimeric BoHV-4 virus carrying and expressing OvHV-2 gB (BoHV-4∆gB/OvHV-2-gB) that was infectious and able to replicate in vitro. We then evaluated BoHV-4∆gB/OvHV-2-gB as a potential vaccine candidate for sheep-associated malignant catarrhal fever (SA-MCF), a fatal disease of ungulates caused by OvHV-2. Using rabbits as a laboratory model for MCF, we assessed the safety, immunogenicity, and efficacy of BoHV-4∆gB/OvHV-2-gB in an immunization/challenge trial. The results showed that while BoHV-4∆gB/OvHV-2-gB was safe and induced OvHV-2 gB-specific humoral immune responses, immunization conferred only 28.5% protection upon challenge with OvHV-2. Therefore, future studies should focus on alternative strategies to express OvHV-2 proteins to develop an effective vaccine against SA-MCF.
Treatment Patterns, Effectiveness, and Safety of Originator Insulin Glargine versus Insulin Glargine-yfgn within the Veterans Health Administration
Authors: Walczuk Samantha , Cunningham Francesca E. , Zhao Xinhua , Dong Diane , Glassman Peter A. , Miller Donald R. , Khachikian Deborah , Au Anthony , Salone Cedric , Bryan Kelly , Her Qoua , Aspinall Sherrie L.
Published: March 2024

We described insulin glargine (originator) and insulin glargine-yfgn (biosimilar) treatment patterns, assessed effectiveness and safety outcomes, and identified reasons for switching back to the originator product from the biosimilar. This retrospective study included 328,463 Veterans 18 years of age and older who received one or more outpatient prescriptions for insulin glargine and/or insulin glargine-yfgn between 1 June 2021 and 31 December 2022. Patients were assigned to subgroups based on the initial prescription during the study period, prevalent versus incident use for originator insulin glargine, and prior versus no prior use of the originator before the biosimilar (i.e., prevalent originator non-switcher (n = 189,734), originator switch to biosimilar (n = 81,010), incident originator non-switcher (n = 49,401), and incident biosimilar (n = 8318)). There were no differences in the outcome of mean HbA1c (7.9% for all subgroups). There were also no differences in the unadjusted rates of hospitalization and/or emergency room visits for hyper- and hypoglycemia between the prevalent originator non-switcher and originator switched to biosimilar subgroups (p = 0.09 and 0.38, respectively) or the incident originator non-switcher and incident biosimilar subgroups (p = 0.054 and 0.61, respectively). Finally, none of the HbA1c or hyperglycemia outcomes adjusted for baseline characteristics were statistically different. Adjusted analyses for rates of hospitalization and/or emergency room visits for hypoglycemia could not be performed due to the low number of events. Overall, patients who received insulin glargine-yfgn had similar effectiveness and safety outcomes as patients who received the originator.
Integrated QSAR Models for Prediction of Serotonergic Activity: Machine Learning Unveiling Activity and Selectivity Patterns of Molecular Descriptors
Authors: Łapińska Natalia , Pacławski Adam , Szlęk Jakub , Mendyk Aleksander
Published: March 2024

Understanding the features of compounds that determine their high serotonergic activity and selectivity for specific receptor subtypes represents a pivotal challenge in drug discovery, directly impacting the ability to minimize adverse events while maximizing therapeutic efficacy. Up to now, this process has been a puzzle and limited to a few serotonergic targets. One approach represented in the literature focuses on receptor structure whereas in this study, we followed another strategy by creating AI-based models capable of predicting serotonergic activity and selectivity based on ligands’ representation by molecular descriptors. Predictive models were developed using Automated Machine Learning provided by Mljar and later analyzed through the SHAP importance analysis, which allowed us to clarify the relationship between descriptors and the effect on activity and what features determine selective affinity for serotonin receptors. Through the experiments, it was possible to highlight the most important features of ligands based on highly efficient models. These features are discussed in this manuscript. The models are available in the additional modules of the SerotoninAI application called “Serotonergic activity” and “Selectivity”.
The Impact of Water Potential and Temperature on Native Species’ Capability for Seed Germination in the Loess Plateau Region, China
Authors: Hu Guifang , He Xinyue , Wang Ning , Liu Jun’e , Zhou Zhengchao
Published: March 2024

Global warming is increasing the frequency and intensity of heat waves and droughts. One important phase in the life cycle of plants is seed germination. To date, the association of the temperature and water potential thresholds of germination with seed traits has not been explored in much detail. Therefore, we set up different temperature gradients (5–35 °C), water potential gradients (−1.2–0 MPa), and temperature × water potential combinations for nine native plants in the Loess Plateau region to clarify the temperature and water combinations suitable for their germination. Meanwhile, we elucidated the temperature and water potential thresholds of the plants and their correlations with the mean seed mass and flatness index by using the thermal time and hydrotime models. According to our findings, the germination rate was positively correlated with the germination percentage and water potential, with the former rising and the latter decreasing as the temperature increased. Using the thermal time and hydrotime models, the seed germination thresholds could be predicted accurately, and the germination thresholds of the studied species varied with an increase in germination percentage. Moreover, temperature altered the impact of water potential on the germination rate. Overall, the base water potential for germination, but not the temperature threshold, was negatively correlated with mean seed mass and was lower for rounder seeds than for longer seeds. This study contributes to improving our understanding of the seed germination characteristics of typical plants and has important implications for the management and vegetation restoration of degraded grasslands.
Differential Water Conservation Capacity in Broadleaved and Mixed Forest Restoration in Latosol Soil-Eroded Region, Hainan Province, China
Authors: Chen Suyi , Huang Yanping , Yan Mei , Han Yujie , Wang Kang , Chen Zexian , Ruan Dongshuo , Yu Yan , Tu Zhihua
Published: March 2024

The water conservation capacity of the litter and soil layers of forest ecosystems improves the function of forest ecosystems in conserving soil and water. Plantation restoration plays a key role in preventing soil erosion. In order to evaluate the water conservation capacity of plantation restoration in Latosol soil-eroded region, we analyzed the litter thickness and mass, water absorption process, water holding recovery process, and soil water holding capacity of five restoration types (Hevea brasiliensis, Acacia mangium, Eucalyptus robusta, Acacia–Eucalyptus, and Acacia–Hevea) in the Mahuangling Watershed, Hainan province. The results showed that the thickness of the litter ranged from approximately 3.42 ± 0.24 to 4.73 ± 0.81 cm, and the litter mass ranged from 5.04 ± 1.52 t·ha−1 to 13.16 ± 1.76 t·ha−1, with higher litter mass in the SL layer than in the UL layer. The litter mass of A. mangium was higher than that of H. brasiliensis, E. robusta, Acacia–Eucalyptus, and Acacia–Hevea, which was 3.16 ± 1.76 t·ha−1. A. mangium forest was significantly higher than other plantation restoration types in terms of the maximum water retention capacity (Qmax) and the effective water retention capacity (Qeff). The soil bulk weight ranged from approximately 1.52 ± 0.09 to 1.59 ± 0.08 g·cm−3, and porosity ranged from 31.77 ± 4.72 to 35.62 ± 3.02%, both of which increased with the depth of the soil layer. The water holding capacity of 0–60 cm soil varied from approximately 12.94 ± 7.91 to 45.02 ± 31.79 t·ha−1, with A. mangium having the best soil permeability and the strongest soil water holding capacity. The entropy weight method was used to conduct a comprehensive evaluation, and the results showed that the water conservation capacity of the soil layer was 1.26 times higher than that of the litter layer, in which the water conservation capacity of A. mangium was the strongest, with a comprehensive evaluation value of 0.2854, which effectively intercepted rainfall and reduced surface runoff. Hence, we suggest that the planting of A. mangium should be considered in future ecological restoration projects of the erosion area of Mahuangling in order to improve the function of conserving soil and water in a restoration forest ecosystem.
Physiological and Transcriptomic Analyses Reveal the Mechanisms Underlying Methyl Jasmonate-Induced Mannitol Stress Resistance in Banana
Authors: Yu Jiaxuan , Tang Lu , Qiao Fei , Liu Juhua , Li Xinguo
Published: March 2024

Exogenous methyl jasmonate (MeJA) application has shown promising effects on plant defense under diverse abiotic stresses. However, the mechanisms underlying MeJA-induced stress resistance in bananas are unclear. Therefore, in this study, we treated banana plants with 100 μM MeJA before inducing osmotic stress using mannitol. Plant phenotype and antioxidant enzyme activity results demonstrated that MeJA improved osmotic stress resistance in banana plants. Thereafter, to explore the molecular mechanisms underlying MeJA-induced osmotic stress resistance in banana seedlings, we conducted high-throughput RNA sequencing (RNA-seq) using leaf and root samples of “Brazilian” banana seedlings treated with MeJA for 0 h and 8 h. RNA-seq analysis showed that MeJA treatment upregulated 1506 (leaf) and 3341 (root) genes and downregulated 1768 (leaf) and 4625 (root) genes. Then, we performed gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses on the differentially expressed genes. We noted that linoleic acid metabolism was enriched in both root and leaf samples, and the genes of this pathway exhibited different expression patterns; 9S-LOX genes were highly induced by MeJA in the leaves, whereas 13S-LOX genes were highly induced in the roots. We also identified the promoters of these genes, as the differences in response elements may contribute to tissue-specific gene expression in response to MeJA application in banana seedlings. Overall, the findings of this study provide insights into the mechanisms underlying abiotic stress resistance in banana that may aid in the improvement of banana varieties relying on molecular breeding.
Optimized Design of Irrigation Water-Heating System and Its Effect on Lettuce Cultivation in a Chinese Solar Greenhouse
Authors: Guo Liangjie , Chen Xinyi , Yang Shiye , Zhou Ruimin , Liu Shenyan , Cao Yanfei
Published: March 2024

In cold regions, the low irrigation water temperature is an important factor of low-temperature stress for greenhouse crops. In this paper, an irrigation water-heating system (IWHS) is proposed to increase the water temperature by utilizing the excess heat in the solar greenhouse. The heat-collection capacity of the system was analyzed by screening the IWHS process parameters in a Chinese solar greenhouse, and a warm-water irrigation experiment for lettuce was conducted. The results demonstrated that the water temperature increased with the increase in wind speed, and the increase in daily average water temperature reached the maximum value of 8.6 °C at 4.5 m/s wind speed. When the heat exchanger was installed at a height of 3.0 m, the collector capacity increased by 17.8% and 6.0% compared with the heating capacity at 0 m and 1.5 m, respectively, and the operation termination water temperature was 22.0–32.2 °C and its coefficient of performance (COP) was optimal. Surface darkening of the heat exchanger did not affect the heat-collection capacity of the system. Using the IWHS effectively improved the temperature of lettuce irrigation water in the Chinese solar greenhouse. The increased frequency of warm-water irrigation significantly promoted lettuce growth and increased the average yield per plant by 15.9%. Therefore, IWHS effectively increased the irrigation water temperature in a Chinese solar greenhouse in winter. Improving the system would enhance its economic and application value.
The Impact of Phenological Gaps on Leaf Characteristics and Foliage Dynamics of an Understory Dwarf Bamboo, Sasa kurilensis
Authors: Wu Chongyang , Tanaka Ryota , Fujiyoshi Kyohei , Akaji Yasuaki , Hirobe Muneto , Miki Naoko , Li Juan , Sakamoto Keiji , Gao Jian
Published: March 2024

Phenological gaps exert a significant influence on the growth of dwarf bamboos. However, how dwarf bamboos respond to and exploit these phenological gaps remain enigmatic. The light environment, soil nutrients, leaf morphology, maximum photosynthetic rate, foliage dynamics, and branching characteristics of Sasa kurilensis were examined under the canopies of Fagus crenata and Magnolia obovata. The goal was to elucidate the adaptive responses of S. kurilensis to phenological gaps in the forest understory. The findings suggest that phenological gaps under an M. obovata canopy augment the available biomass of S. kurilensis, enhancing leaf area, leaf thickness, and carbon content per unit area. However, these gaps do not appreciably influence the maximum photosynthetic rate, total leaf number, leaf lifespan, branch number, and average branch length. These findings underscore the significant impact of annually recurring phenological gaps on various aspects of S. kurilensis growth, such as its aboveground biomass, leaf morphology, and leaf biochemical characteristics. It appears that leaf morphology is a pivotal trait in the response of S. kurilensis to phenological gaps. Given the potential ubiquity of the influence of phenological gaps on dwarf bamboos across most deciduous broadleaf forests, this canopy phenomenon should not be overlooked.
Unleashed Treasures of Solanaceae: Mechanistic Insights into Phytochemicals with Therapeutic Potential for Combatting Human Diseases
Authors: Jan Saima , Iram Sana , Bashir Ommer , Shah Sheezma Nazir , Kamal Mohammad Azhar , Rahman Safikur , Kim Jihoe , Jan Arif Tasleem
Published: March 2024

Plants that possess a diverse range of bioactive compounds are essential for maintaining human health and survival. The diversity of bioactive compounds with distinct therapeutic potential contributes to their role in health systems, in addition to their function as a source of nutrients. Studies on the genetic makeup and composition of bioactive compounds have revealed them to be rich in steroidal alkaloids, saponins, terpenes, flavonoids, and phenolics. The Solanaceae family, having a rich abundance of bioactive compounds with varying degrees of pharmacological activities, holds significant promise in the management of different diseases. Investigation into Solanum species has revealed them to exhibit a wide range of pharmacological properties, including antioxidant, hepatoprotective, cardioprotective, nephroprotective, anti-inflammatory, and anti-ulcerogenic effects. Phytochemical analysis of isolated compounds such as diosgenin, solamargine, solanine, apigenin, and lupeol has shown them to be cytotoxic in different cancer cell lines, including liver cancer (HepG2, Hep3B, SMMC-772), lung cancer (A549, H441, H520), human breast cancer (HBL-100), and prostate cancer (PC3). Since analysis of their phytochemical constituents has shown them to have a notable effect on several signaling pathways, a great deal of attention has been paid to identifying the biological targets and cellular mechanisms involved therein. Considering the promising aspects of bioactive constituents of different Solanum members, the main emphasis was on finding and reporting notable cultivars, their phytochemical contents, and their pharmacological properties. This review offers mechanistic insights into the bioactive ingredients intended to treat different ailments with the least harmful effects for potential applications in the advancement of medical research.
Development of S Haplotype-Specific Markers to Identify Genotypes of Self-Incompatibility in Radish (Raphanus sativus L.)
Authors: Heo Seong-Ho , Kim Su-Yeon , Mo Suk-Yeon , Park Han-Yong
Published: March 2024

Radish (Raphanus sativus L.), a root vegetable belonging to the Brassicaceae family, is considered one of the representative crops displaying sporophytic self-incompatibility (SSI). The utilization of a self-incompatibility system in F1 breeding can improve the efficiency of cross-combinations, leading to a reduction in breeding time and aiding in the development of novel F1 varieties. The successful implementation of this system necessitates the rapid and accurate identification of S haplotypes in parental lines. In this study, we identified a total of nine S haplotypes among 22 elite radish lines through Sanger sequencing. Subsequently, we obtained sequences for showing a 95% similarity to nine S haplotypes, along with sequences identified by other researchers using BLAST. Following this, multiple sequence alignment (MSA) was conducted to identify SRK and SLG sequence similarities, as well as polymorphisms within the class I and II groups. Subsequently, S haplotype-specific marker sets were developed, targeting polymorphic regions of SRK and SLG alleles. These markers successfully amplified each of the nine S haplotypes. These markers will play a crucial role in the rapid and precise identification of parental S haplotypes in the radish F1 breeding process, proving instrumental in the radish F1 purity test.
Nematicidal Activity of Phytochemicals against the Root-Lesion Nematode Pratylenchus penetrans
Authors: Barbosa Pedro , Faria Jorge M. S. , Cavaco Tomás , Figueiredo Ana Cristina , Mota Manuel , Vicente Cláudia S. L.
Published: March 2024

Plant-parasitic nematodes (PPNs) are highly damaging pests responsible for heavy losses in worldwide productivity in a significant number of important plant crops. Common pest management strategies rely on the use of synthetic chemical nematicides, which have led to serious concerns regarding their impacts on human health and the environment. Plant natural products, or phytochemicals, can provide a good source of agents for sustainable control of PPNs, due to their intrinsic characteristics such as higher biodegradability, generally low toxicity for mammals, and lower bioaccumulation in the environment. In this work, the nematicidal activity of 39 phytochemicals was determined against the root-lesion nematode (RLN) Pratylenchus penetrans using standard direct and indirect contact methodologies. Overall, the RLN was tolerant to the tested phytochemicals at the highest concentration, 2 mg/mL, seldom reaching full mortality. However, high activities were obtained for benzaldehyde, carvacrol, 3-octanol, and thymol, in comparison to other phytochemicals or the synthetic nematicide oxamyl. These phytochemicals were seen to damage nematode internal tissues but not its cuticle shape. Also, the environmental and (eco)toxicological parameters reported for these compounds suggest lower toxicity and higher safety of use than oxamyl. These compounds appear to be good candidates for the development of biopesticides for a more sustainable pest management strategy.
Identification and Genetic Diversity Analysis of the Pathogen of Anthracnose of Pepper in Guizhou
Authors: Zhang Aimin , Li Lei , Xie Xuewen , Chai Ali , Shi Yanxia , Xing Dan , Yu Zhiguo , Li Baoju
Published: March 2024

Anthracnose of pepper is a significant disease caused by Colletotrichum spp. In 2017 and 2021, 296 isolates were obtained from 69 disease samples. Through morphological analysis, pathogenicity detection, and polygenic phylogenetic analysis, the above strains were attributed to 10 species: C. scovillei, C. fructicola, C. karstii, C. truncatum, C. gloeosporioides, C. kahawae, C. boninense, C. nymphaeae, C. plurivorum, and C. nigrum. C. scovillei had the most strains (150), accounting for 51.02% of the total isolates; C. fructicola came in second (72 isolates), accounting for 24.49%. Regarding regional distribution, Zunyi City has the highest concentration of strains—92 strains total, or 34.18%—across seven species. Notably, this investigation showed that C. nymphaeae infected pepper fruit for the first time in China. Genetic diversity analysis showed that C. fructicola could be divided into seven haplotypes, and the population in each region had apparent genetic differentiation. However, the genetic distance between each population was not significantly related to geographical distance. Neutral detection and nucleotide mismatch analysis showed that C. fructicola might have undergone population expansion.
Carbon Material-Reinforced Polymer Composites for Bipolar Plates in Polymer Electrolyte Membrane Fuel Cells
Authors: Gomez-Sanchez Alejandro , Franco-Luján Víctor A. , Alfaro-López Hilda M. , Hernández-Sánchez Laura , Cruz-Martínez Heriberto , Medina Dora I.
Published: March 2024

Bipolar plates (BPs) are one of the most important components of polymer electrolyte membrane fuel cells (PEMFCs) because of their important role in gas and water management, electrical performance, and mechanical stability. Therefore, promising materials for use as BPs should meet several technical targets established by the United States Department of Energy (DOE). Thus far, in the literature, many materials have been reported for possible applications in BPs. Of these, polymer composites reinforced with carbon allotropes are one of the most prominent. Therefore, in this review article, we present the progress and critical analysis on the use of carbon material-reinforced polymer composites as BPs materials in PEMFCs. Based on this review, it is observed that numerous polymer composites reinforced with carbon allotropes have been produced in the literature, and most of the composites synthesized and characterized for their possible application in BPs meet the DOE requirements. However, these composites can still be improved before their use for BPs in PEMFCs.
Cryostructuring of Polymeric Systems: 67 Properties and Microstructure of Poly(Vinyl Alcohol) Cryogels Formed in the Presence of Phenol or Bis-Phenols Introduced into the Aqueous Polymeric Solutions Prior to Their Freeze–Thaw Processing
Authors: Kolosova Olga Yu. , Vasil’ev Viktor G. , Novikov Ivan A. , Sorokina Elena V. , Lozinsky Vladimir I.
Published: March 2024

Poly(vinyl alcohol) (PVA) physical cryogels that contained the additives of o-, m-, and p-bis-phenols or phenol were prepared, and their physico-chemical characteristics and macroporous morphology and the solute release dynamics were evaluated. These phenolic additives caused changes in the viscosity of initial PVA solutions before their freeze–thaw processing and facilitated the growth in the rigidity of the resultant cryogels, while their heat endurance decreased. The magnitude of the effects depended on the interposition of phenolic hydroxyls in the molecules of the used additives and was stipulated by their H-bonding with PVA OH-groups. Subsequent rinsing of such “primary” cryogels with pure water led to the lowering of their rigidity. The average size of macropores inside these heterophase gels also depended on the additive type. It was found also that the release of phenolic substances from the additive-containing cryogels occurred via virtually a free diffusion mechanism; therefore, drug delivery systems such as PVA cryogels loaded with either pyrocatechol, resorcinol, hydroquinone, or phenol, upon the in vitro agar diffusion tests, exhibited antibacterial activity typical of these phenols. The promising biomedical potential of the studied nanocomposite gel materials is supposed.
Attention-Based Two-Dimensional Dynamic-Scale Graph Autoencoder for Batch Process Monitoring
Authors: Zhu Jinlin , Gao Xingke , Zhang Zheng
Published: March 2024

Traditional two-dimensional dynamic fault detection methods describe nonlinear dynamics by constructing a two-dimensional sliding window in the batch and time directions. However, determining the shape of a two-dimensional sliding window for different phases can be challenging. Samples in the two-dimensional sliding windows are assigned equal importance before being utilized for feature engineering and statistical control. This will inevitably lead to redundancy in the input, complicating fault detection. This paper proposes a novel method named attention-based two-dimensional dynamic-scale graph autoencoder (2D-ADSGAE). Firstly, a new approach is introduced to construct a graph based on a predefined sliding window, taking into account the differences in importance and redundancy. Secondly, to address the training difficulties and adapt to the inherent heterogeneity typically present in the dynamics of a batch across both its time and batch directions, we devise a method to determine the shape of the sliding window using the Pearson correlation coefficient and a high-density gridding policy. The method is advantageous in determining the shape of the sliding windows at different phases, extracting nonlinear dynamics from batch process data, and reducing redundant information in the sliding windows. Two case studies demonstrate the superiority of 2D-ADSGAE.
Experimental Study on Pressure Oscillations of Direct-Contact Condensation between Saturated Steam and Droplets at Sub-Atmospheric Pressure
Authors: Jing Yuanlin , Wang Chenhao , Huang Qunwu , Wang Yiping , Yu Yangyang
Published: March 2024

In this paper, under the background of low-temperature steam waste heat recovery technology, the pressure oscillation characteristics of direct-contact condensation between continuously falling droplets and saturated steam at sub-atmosphere pressure were studied. An experimental device of pressure oscillation based on an acceleration oscillation sensor was established to investigate the influence of vapor pressure and fluid velocity on the oscillation characteristics of direct-contact condensation. The results showed that as the absolute pressure increases, the peak value of oscillation decreases gradually and the time-domain periodic waveform becomes fluctuating. When the liquid flow rate is low, the condensation oscillation shows a single-peak waveform and the dominant frequency moves towards a higher frequency. When the liquid velocity increases gradually, the RMS (root mean square) of pressure oscillation remains unchanged at first and then decreases obviously. The dominant frequency of oscillation decreases from 23.68 Hz to 7.16 Hz continuously, and the amplitude of oscillation decreases in a parabolic pattern. The auto power spectrum showed that the frequencies with higher energy become unconcentrated and show fluctuation characteristics. The amplitude of the dominant frequency is about 0.0004 (m/s2)2, while that of the other peak frequencies is about 0.00010–0.00015 (m/s2)2. In practical applications, excessive flow velocity and reduced vacuum degree should be avoided to prevent low-frequency vibration, which may lead to fatigue damage or even failure of the equipment due to resonance. In addition, the direct-contact condensation state can be inferred from the vibration signal to reduce environmental noise.
Anthropological Terms in Chinese Biblical Translations: The Interplay between Catholic and Protestant Versions in Response to Chinese Traditional Cultures
Authors: Hong Xiaochun
Published: March 2024

Notwithstanding the considerable attention that Chinese Bible translations have attracted, some important theological issues have been ignored for a long time, one of which is anthropology. The present article focuses on the Chinese rendering of terms in this category. From the attempts in the first three Catholic versions, the Western theory of soul introduced by Matteo Ricci began to influence the connotation of ling 靈 in Chinese biblical texts, though anima and spiritus had not been distinguished or the translations were still obscure in these renditions. Robert Morrison’s version, though heavily dependent on Jean Basset’s translation, was also indebted to Emmanuel Diaz and Louis A. de Poirot in its dichotomous anthropology, developing a ling–rou 靈–肉 (lit. spirit–flesh) dichotomous discourse with his conceptualization of ling 靈. Initiated by the “second generation” of Protestant Bible translators, the renderings of pneuma/ruach and sarx/basar took the indigenized approach that culminated in the Delegates’ Version of the Bible. With the assistance of some Chinese scholars in completing this version, Medhurst launched a dialogue between Christian anthropology and Chinese traditional outlooks of human beings by emphasizing the concepts of shen 身 and xin 心, which had long-lasting popularity in later versions of the Chinese Bible.
Unsung Heroes of Mission Bible Translation in Colonial West Africa: Ludwig Adzaklo of the Bremen Mission in German Togoland
Authors: Wandusim Michael F.
Published: March 2024

The Africanisation of Christianity in Africa is closely linked to the availability of the Bible in African mother tongues. However, mission-led Bible translation in Africa in the nineteenth and early twentieth centuries was not solely the work of European missionary linguists. Africans, such as Ludwig Adzaklo of the Bremen Mission, played essential roles in this process. Nevertheless, African translators like him were considered as mere Sprachgehilfe (language assistants) to the missionaries and not as co-translators. After a postcolonial analysis of archival data on the translation of the Old Testament into Ewe by Ludwig Adzaklo and Jakob Spieth, this study argues that Adzaklo was not just Spieth’s Sprachgehilfe but a co-translator on the project. Being referred to as Spieth’s Sprachgehilfe was a colonial-missionary label that denied Adzaklo’s agency in mission-led Bible translation in Africa. Therefore, the study suggests that Adzaklo should be viewed as an early Ewe mother-tongue Bible translator in the history of West African Christianity.
Towards Industrial Robots’ Maturity: An Italian Case Study
Authors: Aggogeri Francesco , Pellegrini Nicola , Taesi Claudio
Published: March 2024

This paper aims to investigate the impact of industrial robotics, examining the process integration in a sample of +600 companies located in the Province of Brescia, an intensive industrial area in the North of Italy. Through a detailed economic investigation, this study analyses the adoption of robotic solutions in companies of varying sizes, using a survey and financial databases to investigate the most used types of robots, their applications, the impacts at the operational and personnel level, and the companies’ growth (sales, employees, other). The results highlight a significant presence of robotic solutions, particularly articulated robots, in the large companies involved. Robotics diffusion positively correlates with significant improvements in terms of productivity and quality. The introduction of robots is associated with increased corporate growth indicators, including staff expansion. Large companies demonstrate a superior ability to adapt to these technologies, supported by more significant financial resources and a wide range of internal competencies for managing robots. Furthermore, large companies proactively hire qualified personnel or initiate internal training courses. Small and medium-sized enterprises (SMEs), although currently less equipped with robotic technologies, exhibit a significant interest in future adoption, highlighting the opportunity for growth and innovation. The results suggest that integrating robotics in the manufacturing sector not only constitutes an effective means to enhance operational performance but also acts as a catalyst for developing human capital and strengthening the local economy.
Deep-Learning-Based Automatic Extraction of Aquatic Vegetation from Sentinel-2 Images—A Case Study of Lake Honghu
Authors: Gao Hangyu , Li Ruren , Shen Qian , Yao Yue , Shao Yifan , Zhou Yuting , Li Wenxin , Li Jinzhi , Zhang Yuting , Liu Mingxia
Published: March 2024

Aquatic vegetation is an important component of aquatic ecosystems; therefore, the classification and mapping of aquatic vegetation is an important aspect of lake management. Currently, the decision tree (DT) classification method based on spectral indices has been widely used in the extraction of aquatic vegetation data, but the disadvantage of this method is that it is difficult to fix the threshold value, which, in turn, affects the automatic classification effect. In this study, Sentinel-2 MSI data were used to produce a sample set (about 930 samples) of aquatic vegetation in four inland lakes (Lake Taihu, Lake Caohai, Lake Honghu, and Lake Dongtinghu) using the visual interpretation method, including emergent, floating-leaved, and submerged vegetation. Based on this sample set, a DL model (Res-U-Net) was used to train an automatic aquatic vegetation extraction model. The DL model achieved a higher overall accuracy, relevant error, and kappa coefficient (90%, 8.18%, and 0.86, respectively) compared to the DT method (79%, 23.07%, and 0.77) and random forest (78%,10.62% and 0.77) when utilizing visual interpretation results as the ground truth. When utilizing measured point data as the ground truth, the DL model exhibited accuracies of 59%, 78%, and 91% for submerged, floating-leaved, and emergent vegetation, respectively. In addition, the model still maintains good recognition in the presence of clouds with the influence of water bloom. When applying the model to Lake Honghu from January 2017 to October 2023, the obtained temporal variation patterns in the aquatic vegetation were consistent with other studies. The study in this paper shows that the proposed DL model has good application potential for extracting aquatic vegetation data.
Automated Built-Up Infrastructure Land Cover Extraction Using Index Ensembles with Machine Learning, Automated Training Data, and Red Band Texture Layers
Authors: Maloney Megan C. , Becker Sarah J. , Griffin Andrew W. H. , Lyon Susan L. , Lasko Kristofer
Published: March 2024

Automated built-up infrastructure classification is a global need for planning. However, individual indices have weaknesses, including spectral confusion with bare ground, and computational requirements for deep learning are intensive. We present a computationally lightweight method to classify built-up infrastructure. We use an ensemble of spectral indices and a novel red-band texture layer with global thresholds determined from 12 diverse sites (two seasonally varied images per site). Multiple spectral indexes were evaluated using Sentinel-2 imagery. Our texture metric uses the red band to separate built-up infrastructure from spectrally similar bare ground. Our evaluation produced global thresholds by evaluating ground truth points against a range of site-specific optimal index thresholds across the 24 images. These were used to classify an ensemble, and then spectral indexes, texture, and stratified random sampling guided training data selection. The training data fit a random forest classifier to create final binary maps. Validation found an average overall accuracy of 79.95% (±4%) and an F1 score of 0.5304 (±0.07). The inclusion of the texture metric improved overall accuracy by 14–21%. A comparison to site-specific thresholds and a deep learning-derived layer is provided. This automated built-up infrastructure mapping framework requires only public imagery to support time-sensitive land management workflows.
Applicability of Precipitation Products in the Endorheic Basin of the Yellow River under Multi-Scale in Time and Modality
Authors: Zhu Weiru , Liang Kang
Published: March 2024

Continuous and accurate precipitation data are critical to water resource management and eco-logical protection in water-scarce and ecologically fragile endorheic or inland basins. However, in typical data-scarce endorheic basins such as the endorheic basin of the Yellow River Basin (EBYRB) in China, multi-source precipitation products provide an opportunity to accurately capture the spatial distribution of precipitation, but the applicability evaluation of multi-source precipitation products under multi-time scales and multi-modes is currently lacking. In this context, our study evaluates the regional applicability of seven diverse gridded precipitation products (APHRODITE, GPCC, PERSIANN-CDR, CHIRPS, ERA5, JRA55, and MSWEP) within the EBYRB considering multiple temporal scales and two modes (annual/monthly/seasonal/daily precipitation in the mean state and monthly/daily precipitation in the extreme state). Furthermore, we explore the selection of suitable precipitation products for the needs of different hydrological application scenarios. Our research results indicate that each product has its strengths and weaknesses at different time scales and modes of coupling. GPCC excels in capturing annual, seasonal, and monthly average precipitation as well as monthly and daily extreme precipitation, essentially meeting the requirements for inter-annual or intra-annual water resource management in the EBYRB. CHIRPS and PERSIANN-CDR have higher accuracy in extreme precipitation assessment and can provide near real-time data, which can be applied as dynamic input precipitation variables in extreme precipitation warnings. APHRODITE and MSWEP exhibit superior performance in daily average precipitation that can provide data for meteorological or hydrological studies at the daily scale in the EBYRB. At the same time, our research also exposes typical problems with several precipitation products, such as MSWEP’s abnormal assessment of summer precipitation in certain years and ERA5 and JRA55’s overall overestimation of precipitation assessment in the study area.
Restoration of UAV-Based Backlit Images for Geological Mapping of a High-Steep Slope
Authors: Li Tengyue
Published: March 2024

Unmanned aerial vehicle (UAV)-based geological mapping is significant for understanding the geological structure in the high-steep slopes, but the images obtained in these areas are inevitably influenced by the backlit effect because of the undulating terrain and the viewpoint change of the camera mounted on the UAV. To handle this concern, a novel backlit image restoration method is proposed that takes the real-world application into account and addresses the color distortion issue existing in backlit images captured in high-steep slope scenes. Specifically, there are two main steps in the proposed method, which consist of the backlit removal and the color and detail enhancement. The backlit removal first eliminates the backlit effect using the Retinex strategy, and then the color and detail enhancement step improves the image color and sharpness. The author designs extensive comparison experiments from multiple angles and applies the proposed method to different engineering applications. The experimental results show that the proposed method has potential compared to other main-stream methods both in qualitative visual effects and universal quantitative evaluation metrics. The backlit images processed by the proposed method are significantly improved by the process of feature key point matching, which is very conducive to the fine construction of 3D geological models of the high-steep slope.
Automated Mapping of Land Cover Type within International Heterogenous Landscapes Using Sentinel-2 Imagery with Ancillary Geospatial Data
Authors: Lasko Kristofer , O’Neill Francis D. , Sava Elena
Published: March 2024

A near-global framework for automated training data generation and land cover classification using shallow machine learning with low-density time series imagery does not exist. This study presents a methodology to map nine-class, six-class, and five-class land cover using two dates (winter and non-winter) of a Sentinel-2 granule across seven international sites. The approach uses a series of spectral, textural, and distance decision functions combined with modified ancillary layers (such as global impervious surface and global tree cover) to create binary masks from which to generate a balanced set of training data applied to a random forest classifier. For the land cover masks, stepwise threshold adjustments were applied to reflectance, spectral index values, and Euclidean distance layers, with 62 combinations evaluated. Global (all seven scenes) and regional (arid, tropics, and temperate) adaptive thresholds were computed. An annual 95th and 5th percentile NDVI composite was used to provide temporal corrections to the decision functions, and these corrections were compared against the original model. The accuracy assessment found that the regional adaptive thresholds for both the two-date land cover and the temporally corrected land cover could accurately map land cover type within nine-class (68.4% vs. 73.1%), six-class (79.8% vs. 82.8%), and five-class (80.1% vs. 85.1%) schemes. Lastly, the five-class and six-class models were compared with a manually labeled deep learning model (Esri), where they performed with similar accuracies (five classes: Esri 80.0 ± 3.4%, region corrected 85.1 ± 2.9%). The results highlight not only performance in line with an intensive deep learning approach, but also that reasonably accurate models can be created without a full annual time series of imagery.