bluuebunny/crossref_metadata_2025 huggingface dataset:
A Formal Representation for Intelligent Decision-Making in Games
Authors: Liu Chanjuan , Zhang Ruining , Zhang Yu , Zhu Enqiang
Published: November 2023

The study of intelligent game-playing has gained tremendous attention in the past few decades. The recent development of artificial intelligence (AI) players (e.g., the Go player AlphaGo) has made intelligent game-playing even more prominent in both academia and industry. The performance of state-of-the-art AI players benefits greatly from machine learning techniques, based on which, players can make estimations and decisions even without understanding the games. Although AI machines show great superiority over humans in terms of data processing and complex computation, there remains a vast distance between artificial intelligence and human intelligence with respect to the abilities of context understanding and reasoning. In this paper, we explore the theoretical foundation of intelligent game-playing from a logical perspective. The proposed logic, by considering the computational limits in practical game-playing, drops the ideal assumptions in existing logics for the classical game model. We show that under logical framework, the basis of decision-making for agents in game scenarios can be formally represented and analyzed. Moreover, by characterizing the solutions of games, this logic is able to formalize players’ rational decision-making during practical game-playing.
Very High Cycle Fatigue of Welds: A Review
Authors: England Andrew , Toumpis Athanasios , Gorash Yevgen
Published: November 2023

The design life of welded structures and components extends into the very high cycle fatigue (VHCF) regime across various applications. However, the availability of data on the fatigue behaviour of welded joints in the VHCF regime is limited, particularly when compared to the low and high cycle fatigue regimes. The development of ultrasonic fatigue testing equipment has accelerated fatigue testing and allowed for the VHCF properties of welds to be investigated in a feasible timeframe. In the present review, the emerging research concerning the VHCF behaviour of welds of various steels and non-ferrous alloys are individually explored. Overall, it is observed that welded joints have significantly lower fatigue strength than the base metal in the VHCF regime and that welding defects have a considerable influence on fatigue strength. Through the discussion of the relevant literature, important findings concerning the effects of specimen geometry and fatigue improvement methods are underlined. Furthermore, the guidance provided within design standards is compared, and some examples of VHCF failures of in-service components are highlighted. Finally, perspectives on future directions of investigation are put forward with the aim of encouraging further research in the field of VHCF of welds.
Reconstruction of the Steroid 1(2)-Dehydrogenation System from Nocardioides simplex VKM Ac-2033D in Mycolicibacterium Hosts
Authors: Fufaeva Svetlana R. , Dovbnya Dmitry V. , Ivashina Tanya V. , Shutov Andrei A. , Donova Marina V.
Published: November 2023

Microbial 1(2)-dehydrogenation of 3-ketosteroids is an important basis for the production of many steroid pharmaceuticals and synthons. When using the wild-type strains for whole cell catalysis, the undesirable reduction of the 20-carbonyl group, or 1(2)-hydrogenation, was observed. In this work, the recombinant strains of Mycolicibacterium neoaurum and Mycolicibacterium smegmatis were constructed with blocked endogenous activity of 3-ketosteroid-9α-hydroxylase, 3-ketosteroid-1(2)-dehydrogenase (3-KSD), and expressing 3-KSD encoded by the gene KR76_27125 (kstD2NS) from Nocardioides simplex VKM Ac-2033D. The in vivo activity of the obtained recombinant strains against phytosterol, 6α-methyl-hydrocortisone, and hydrocortisone was studied. When using M. smegmatis as the host strain, the 1(2)-dehydrogenation activity of the constructed recombinant cells towards hydrocortisone was noticeably higher compared to those on the platform of M. neoaurum. A comparison of the strengths of inducible acetamidase and constitutive hsp60 promoters in M. smegmatis provided comparable results. Hydrocortisone biotransformation by M. smegmatis BD/pMhsp_k expressing kstD2NS resulted in 95.4% prednisolone yield, and the selectivity preferred that for N. simplex. Mycolicibacteria showed increased hydrocortisone degradation at 35 °C compared to 30 °C. The presence of endogenous steroid catabolism in Mycolicibacterium hosts does not seem to confer an advantage for the functioning of KstD2NS. The results allow for the evaluation of the prospects for the development of simple technological methods for the selective 1(2)-dehydrogenation of 3-ketosteroids by growing bacterial cells.
Get to Know Your Neighbors: Characterization of Close Bacillus anthracis Isolates and Toxin Profile Diversity in the Bacillus cereus Group
Authors: Abdelli Mehdi , Falaise Charlotte , Morineaux-Hilaire Valérie , Cumont Amélie , Taysse Laurent , Raynaud Françoise , Ramisse Vincent
Published: November 2023

Unexpected atypical isolates of Bacillus cereus s.l. occasionally challenge conventional microbiology and even the most advanced techniques for anthrax detection. For anticipating and gaining trust, 65 isolates of Bacillus cereus s.l. of diverse origin were sequenced and characterized. The BTyper3 tool was used for assignation to genomospecies B. mosaicus (34), B. cereus s.s (29) and B. toyonensis (2), as well as virulence factors and toxin profiling. None of them carried any capsule or anthrax-toxin genes. All harbored the non-hemolytic toxin nheABC and sphygomyelinase spH genes, whereas 41 (63%), 30 (46%), 11 (17%) and 6 (9%) isolates harbored cytK-2, hblABCD, cesABCD and at least one insecticidal toxin gene, respectively. Matrix-assisted laser desorption ionization-time of flight mass spectrometry confirmed the production of cereulide (ces genes). Phylogeny inferred from single-nucleotide polymorphisms positioned isolates relative to the B. anthracis lineage. One isolate (BC38B) was of particular interest as it appeared to be the closest B. anthracis neighbor described so far. It harbored a large plasmid similar to other previously described B. cereus s.l. megaplasmids and at a lower extent to pXO1. Whereas bacterial collection is enriched, these high-quality public genetic data offer additional knowledge for better risk assessment using future NGS-based technologies of detection.
Arginine and Lysine Supplementation Potentiates the Beneficial β-Hydroxy ß-Methyl Butyrate (HMB) Effects on Skeletal Muscle in a Rat Model of Diabetes
Authors: Manzano Manuel , Girón María D. , Salto Rafael , Burgio Chiara , Reinoso Antonio , Cabrera Elena , Rueda Ricardo , López-Pedrosa Jose M.
Published: November 2023

Skeletal muscle is the key tissue for maintaining protein and glucose homeostasis, having a profound impact on the development of diabetes. Diabetes causes deleterious changes in terms of loss of muscle mass, which will contribute to reduced glucose uptake and therefore progression of the disease. Nutritional approaches in diabetes have been directed to increase muscle glucose uptake, and improving protein turnover has been at least partially an oversight. In muscle, β-hydroxy β-methyl butyrate (HMB) promotes net protein synthesis, while arginine and lysine increase glucose uptake, albeit their effects on promoting protein synthesis are limited. This study evaluates if the combination of HMB, lysine, and arginine could prevent the loss of muscle mass and function, reducing the progression of diabetes. Therefore, the combination of these ingredients was tested in vitro and in vivo. In muscle cell cultures, the supplementation enhances glucose uptake and net protein synthesis due to an increase in the amount of GLUT4 transporter and stimulation of the insulin-dependent signaling pathway involving IRS-1 and Akt. In vivo, using a rat model of diabetes, the supplementation increases lean body mass and insulin sensitivity and decreases blood glucose and serum glycosylated hemoglobin. In treated animals, an increase in GLUT4, creatine kinase, and Akt phosphorylation was detected, demonstrating the synergic effects of the three ingredients. Our findings showed that nutritional formulations based on the combination of HMB, lysine, and arginine are effective, not only to control blood glucose levels but also to prevent skeletal muscle atrophy associated with the progression of diabetes.
Comment on Kaufman et al. Popular Dietary Trends’ Impact on Athletic Performance: A Critical Analysis Review. Nutrients 2023, 15, 3511
Authors: Wakolbinger-Habel Robert , Muschitz Christian
Published: November 2023

The authors [...]
Vegan Diets for Children: A Narrative Review of Position Papers Published by Relevant Associations
Authors: Jakše Boštjan , Fras Zlatko , Fidler Mis Nataša
Published: November 2023

The scientific discourse on vegan diets for children and adolescents primarily involves referencing position statement papers from different scientific and professional organizations, including paediatric associations. Over the past two decades, specialized associations have issued official statements and published position papers about adopting well-designed vegan diets during crucial life stages, including pregnancy and lactation, infancy, and childhood. A subset of these associations firmly supports the notion that a well-designed vegan diet can indeed be healthy and support normal growth and development during particularly delicate life stages, emphasizing careful planning, vitamin B12 supplementation, and regular supervised medical and dietetics oversight. In contrast, specific paediatric associations caution against vegan diets for children and adolescents, citing potential harm and the lack of adequate substantiation. These criticisms in position papers frequently point to lower-quality studies and/or outdated studies. Additionally, concerns extend to comparing vegan and omnivorous diets, considering public health issues such as obesity and early stages of cardiovascular disease as well as the risk of prediabetes and type 2 diabetes. Notably, some scepticism stems from studies where children’s adherence to a well-designed vegan diet is incomplete. Scientific rigor suggests performing a comparable assessment of omnivorous and vegan diets. This narrative review highlights the need for a comprehensive, up-to-date literature review to inform balanced perspectives on vegan diets for children and adolescents. Researchers and decision-makers should aim to actively improve the design and consistent implementation of both diet types.
Characterization of Equine Rhinitis B Virus Infection in Clinically Ill Horses in the United States during the Period 2012–2023
Authors: Schneider Chrissie , James Kaitlyn , Craig Bryant W. , Chappell Duane E. , Vaala Wendy , van Harreveld Philip D. , Wright Cara A. , Barnum Samantha , Pusterla Nicola
Published: November 2023

Equine rhinitis B virus is a lesser-known equine respiratory pathogen that is being detected with increasing frequency via a voluntary upper respiratory biosurveillance program in the United States. This program received 8684 nasal swab submissions during the years 2012–2023. The nasal swabs were submitted for qPCR testing for six common upper respiratory pathogens: Streptococcus equi subspecies equi (S. equi), equine influenza virus (EIV), equine herpesvirus type 1 (EHV-1), equine herpesvirus type 4 (EHV-4), equine rhinitis A virus (ERAV), and equine rhinitis B virus (ERBV). The overall ERBV qPCR-positivity rate was 5.08% (441/8684). ERBV was detected as a single pathogen in 291 cases (65.99% of positives, 291/441) and was detected as a coinfection with at least one other respiratory pathogen in 150 cases (34.01%, 150/441). Young horses, less than a year of age, with acute onset of fever and respiratory signs and horses used for competition are more likely to test qPCR-positive for ERBV. Horses with ERBV may present with fever, nasal discharge, ocular discharge, and/or cough. Coinfection is a common feature of ERBV infection and S. equi, EHV-4 and EIV were the most common pathogens coinfected with ERBV. This report provides important information regarding the clinical relevance of ERBV in the horse and begins investigating the impact of coinfection on clinical disease.
Comparative Analysis of Cd Uptake and Tolerance in Two Mangrove Species (Avicennia marina and Rhizophora stylosa) with Distinct Apoplast Barriers
Authors: Chang Li-Fang , Fei Jiao , Wang You-Shao , Ma Xiao-Yu , Zhao Yan , Cheng Hao
Published: November 2023

Mangrove plants demonstrate an impressive ability to tolerate environmental pollutants, but excessive levels of cadmium (Cd) can impede their growth. Few studies have focused on the effects of apoplast barriers on heavy metal tolerance in mangrove plants. To investigate the uptake and tolerance of Cd in mangrove plants, two distinct mangrove species, Avicennia marina and Rhizophora stylosa, are characterized by unique apoplast barriers. The results showed that both mangrove plants exhibited the highest concentration of Cd2+ in roots, followed by stems and leaves. The Cd2+ concentrations in all organs of R. stylosa consistently exhibited lower levels than those of A. marina. In addition, R. stylosa displayed a reduced concentration of apparent PTS and a smaller percentage of bypass flow when compared to A. marina. The root anatomical characteristics indicated that Cd treatment significantly enhanced endodermal suberization in both A. marina and R. stylosa roots, and R. stylosa exhibited a higher degree of suberization. The transcriptomic analysis of R. stylosa and A. marina roots under Cd stress revealed 23 candidate genes involved in suberin biosynthesis and 8 candidate genes associated with suberin regulation. This study has confirmed that suberized apoplastic barriers play a crucial role in preventing Cd from entering mangrove roots.
Asymbiotic Seed Germination and In Vitro Seedling Development of the Endangered Orchid Species Cypripedium guttatum
Authors: Park Hyeong Bin , An Jiae , Bae Kee-Hwa , Hong Seung Hyo , Park Hwan Joon , Kim Seongjun , Lee Chang Woo , Lee Byoung-Doo , Baek Ju Hyoung , Kim Nam Young , Hwang Jung Eun
Published: November 2023

Cypripedium guttatum is a highly restricted terrestrial orchid that faces increasing endangerment owing to its habitat destruction and illegal collection. Compared to epiphytic orchids, terrestrial orchids such as C. guttatum have harder seed coats and more demanding in vitro germination conditions. This study aimed to develop an effective in vitro propagation system for C. guttatum to aid in its conservation. Seeds from mature capsules were subjected to various conditions, including sterilization using 1% sodium hypochlorite (NaOCl) and different light conditions, culture media, hormones, and organic supplements, to assess germination and early seedling development in vitro. Sterilization with 1% NaOCl significantly improved the germination rate, especially under dark conditions. Germination initiation occurred at 2 and 3 months in orchid seed sowing medium (OSM) and Murashige and Skoog (MS) medium, respectively. The addition of 1 mg/L naphthaleneacetic acid (NAA) further enhanced germination. However, the inclusion of organic supplements, such as apple and banana homogenates, in the culture medium led to substantial growth inhibition after 12 months. Notably, orchid maintenance medium (OMM) without organic additives proved to be the most suitable for seedling growth. The results of this study show that sterilization, appropriate light, and optimal NAA concentrations are beneficial for seed germination.
The Effects of Partial Substitution of Fertilizer Using Different Organic Materials on Soil Nutrient Condition, Aggregate Stability and Enzyme Activity in a Tea Plantation
Authors: Huang Chengyi , Zhang Kairui , Guo Wentao , Huang Huijuan , Gou Zhangyong , Yang Liu , Chen Yian , Oh Kokyo , Fang Conggang , Luo Ling
Published: November 2023

Fertilization plays a crucial role in enhancing tea production. However, it has been demonstrated that the long-term single application of chemical fertilizer will reduce soil nutrient content and the formation of soil aggregates, which is not conducive to the sustainable development of soil and agriculture. Many studies have shown that partial substitution of chemical fertilizer with organic fertilizer can improve soil physicochemical properties and soil nutrient content. This study compared the effects of different organic materials as substitutes for chemical fertilizer. We partially replaced chemical fertilizer with rabbit manure, wine lees and rapeseed cake, amounting to 30% of the total annual nitrogen application in the field experiment, and we set nine different fertilization methods to assess and analyze the soil nutrient condition, aggregate stability and enzyme activity. The results showed that the experimental soil aggregate mean weight diameter (MWD) and geometric mean diameter (GMD) were significantly increased compared with control (p < 0.05); the aforementioned fertilization methods also decreased the soil aggregate fractal dimension (D), disruption rate (PAD), average weight-specific surface area (MWSSA) and soil erodibility factor (K). The application of the fertilizer containing organic materials and microbial agent increased soil organic carbon (SOC) by 20.7% to 22.6% and total nitrogen (TN) by 34.6% to 38.1%; it also significantly promoted sucrase, urease and protease activities in all aggregate sizes (p < 0.05) and increased the 2–5 mm aggregate content. The correlation coefficients between the SOC and the enzyme activities were 0.18–0.95, and most of them showed an extremely significant positive correlation (p < 0.01). In conclusion, the application of fertilizers containing organic materials and microbial agents can improve soil aggregate stability, aggregate enzyme activity and soil structural stability.
Employing a Plant Probiotic Actinomycete for Growth Promotion of Lettuce (Lactuca sativa L. var. longifolia) Cultivated in a Hydroponic System under Nutrient Limitation
Authors: Kitwetch Benyapa , Rangseekaew Pharada , Chromkaew Yupa , Pathom-Aree Wasu , Srinuanpan Sirasit
Published: November 2023

The consumption of lettuce is associated with an increased risk of ingesting nitrate, a naturally occurring and potentially harmful compound that can have adverse effects on human health. Hydroponic cultivation systems serve as effective tools for regulating nutrient solutions and nitrogen availability, which are essential for controlling nitrate levels. However, the techniques for reducing nutrient levels need to be appropriately calibrated based on lettuce growth responses and their interactions with the environment and growing conditions. Previous studies have demonstrated that plant probiotic actinomycetes can alleviate nutritional stress in various crops. However, there is a noticeable gap in research concerning the effects of actinomycetes on hydroponically grown lettuce, particularly under nutrient-limiting conditions. This study aimed to evaluate the effectiveness of the actinomycete Streptomyces thermocarboxydus S3 in enhancing lettuce growth in a nutrient-restricted hydroponic system. The results indicated that the detrimental effects of nutrient stress on lettuce were mitigated by the inoculation of lettuce with S. thermocarboxydus S3. This mitigation was evident in various growth parameters, including leaf count, shoot length, and the fresh and dry weights of both shoots and roots. In the presence of nutritional stress, S. thermocarboxydus S3 likely mitigated the negative effects on lettuce by reducing hydrogen peroxide levels, presumably through the synthesis of H2O2-scavenging enzymes. Furthermore, S. thermocarboxydus S3 successfully survived and colonized lettuce roots. Therefore, the inoculation of lettuce with S. thermocarboxydus S3 offers significant advantages for promoting lettuce growth in nutrient-limited hydroponic systems.
A Review on Intelligent Control Theory and Applications in Process Optimization and Smart Manufacturing
Authors: Lee Min-Fan Ricky
Published: November 2023

In the evolving landscape of manufacturing, the integration of intelligent control theory stands as a pivotal advancement, driving both process optimization and the paradigm of smart manufacturing. This review delves into the multifaceted applications of intelligent control theory, emphasizing its role in equipment, operations, and controls optimization. With a focus on three primary methodologies—fuzzy logic, neural networks, and genetic algorithms—the paper elucidates their biological parallels and their significance in simulation, modeling, and optimization. The transformative potential of smart manufacturing, synonymous with Industry 4.0, is also explored, highlighting its foundation in data, automation, and artificial intelligence. Drawing from a comprehensive analysis of recent literature, the review underscores the growing interest in this domain, as evidenced by the surge in publications and citations over the past decade. The overarching aim is to provide contemporary discourse on the applications and implications of intelligent control theory in the realms of process optimization and smart manufacturing.
Industrial Investigation of the Combined Action of Vacuum Residue Hydrocracking and Vacuum Gas Oil Catalytic Cracking While Processing Different Feeds and Operating under Distinct Conditions
Authors: Stratiev Dicho , Toteva Vesislava , Shishkova Ivelina , Nenov Svetoslav , Pilev Dimitar , Atanassov Krassimir , Bureva Vesselina , Vasilev Svetlin , Stratiev Danail Dichev
Published: November 2023

Ebullated bed vacuum residue hydrocracking and fluid catalytic cracking (FCC) are among the most profitable processes in modern refining. Their optimal performance is vital for petroleum refining profitability. That is why a better understanding of their combined action and the interrelations between these two heavy oil conversion processes in a real-world refinery could provide valuable information for further performance optimization. Nine distinct petroleum crudes belonging to the extra light, light, and medium petroleum crude types were processed in the LUKOIL Neftohim Burgas refinery to study the combined performance of two processes: FCC of vacuum gas oil and ebullated bed vacuum residue H-Oil hydrocracking. The operating conditions along with the characterization data of the feeds and products of both processes were evaluated through the employment of intercriteria analysis to define the variables with statistically significant relationships. Maple 2023 Academic Edition mathematics software was used to develop models to predict the vacuum residue conversion level under different operating conditions. The plug flow reactor model with an activation energy of 215 kJ/mol and a reaction order of 1.59 was found to provide the highest accuracy of vacuum residue conversion, with an average absolute deviation of 2.2%. H-Oil yields were found to correlate with the vacuum residue conversion level and the content of FCC slurry oil (SLO), the recycling of partially blended fuel oil, a material boiling point below 360 °C, and the vacuum gas oil (VGO) in the H-Oil feed. FCC conversion was found to depend on the H-Oil VGO content in the FCC feed and the content of FCC SLO in the H-Oil feed.
Assessment of Zn, Pb and Cd in Soil around an MSW Incineration Plant: Using Risk Assessment and Multivariate Statistical Techniques
Authors: Wei Chunmei , Zhang Yanfei , Zuo Xinxin , Wan Chunyan , Wang Zijian
Published: November 2023

To investigate and evaluate the spatial distribution of Zn, Pb and Cd in the soil around a municipal solid waste incineration plant and its ecological risks, Zn, Pb and Cd were analyzed in soil samples around a municipal solid waste incineration plant in Chengdu, Sichuan Province, China. The results revealed that the average content of Zn and Pb did not exceed the soil environmental quality value for the risk control standard for soil contamination of agricultural land (GB15618-2018), but the average content of Cd in the soil was higher than this standard. Multivariate statistical analysis indicated that Cd was the predominant pollutant and had strong correlations with Zn and Pb. The Cd content was most impacted by human activities, which also explained that this municipal solid waste incineration plant has little effect on Zn, Pb and Cd in the surrounding soil. The geo-accumulation index decreased in the order of Cd > Zn > Pb, and the geo-accumulation index of Cd was greater than 5, indicating that the pollution level for Cd was extremely heavy. The comprehensive potential ecological risk index (RI) of various heavy metals was greater than 1200, And the potential ecological risk level of the study area was high. The contribution rate of Cd to RI was relatively large, and Cd pollution should be paid more attention to.
Diffusion Behavior of Carbon and Silicon in the Process of Preparing Silicon Steel Using Solid-State Decarburization
Authors: Wen Li , Ai Liqun , Hong Lukuo , Zhou Yuqing , Zhu Guangpeng , Sun Caijiao
Published: November 2023

In this study, we investigated the relationship between the decarburization effect of the solid-state decarburization method for preparing silicon steel and the atomic diffusion behavior in the matrix, focusing on 1 mm thick Fe-0.18 wt% C-Si (1.5, 3.5 wt%) alloy strips as the research object. Solid-state decarburization experiments were carried out in an Ar-H2O-H2 atmosphere, and the self-diffusion behavior of C and Si in Fe-C-Si alloy system was simulated by molecular dynamics. The results show that the molecular dynamics simulation results are consistent with the decarburization experimental results. When the temperature is lower than 800 °C, the atoms maintain a compact bcc structure, so the migration rate of carbon is low. When the temperature rises, the atoms move violently, resulting in the destruction of the crystal structure. Because the atomic arrangement tends towards a disordered structure, the migration rate of C is high and the diffusion coefficient increases. The experimental results showed that the decarburization rate was accelerated. At the same temperature, the diffusion activation energy Q = 48.7 kJ·mol−1 of carbon in an Fe-3.5 wt% Si-C alloy matrix can be calculated. The diffusion activation energy of carbon Q = 47.3 kJ·mol−1 was calculated using a molecular dynamics simulation. When the content of Si is 3.5 wt% and 1.5 wt%, the diffusion series of Si can be expressed as D3.5Si, Si = 8.54 × 10−10 exp(−33,089.7/RT) m2/s and D1.5Si, Si = 2.06 × 10−9 exp(−46,641.5/RT) m2/s, respectively. When the Si content is 3.5 wt%, the diffusion coefficient of Si is larger. After diffusion to the near surface, it combines with the remaining O to form a continuous strip of SiO2. When the Si content is 1.5 wt%, the diffusion coefficient of Si is small. The remaining O diffuses in the matrix and will oxidize when encountering Si; it cannot aggregate in a highly-dispersed distribution. The lattice transition from face centered cubic lattice austenite to body centered cubic lattice ferrite occurred in the matrix of the thin strip. The diffusion coefficient of C in ferrite is much larger than that in austenite. Therefore, the decarburization rate suddenly increases before decarburization stagnation. With the increase in Si content, the diffusion activation energy of C decreases, which promotes the decarburization effect.
Use of Methylphenidate for Hypoactive Delirium: A Comprehensive Systematic Review
Authors: Bachu Anil , Kotapati Padma , Kainth Tejasvi , Yadav Garima , Ashraf Sahar , Papudesi Bhavani Nagendra , Kennedy Kristina , Prasad Sakshi , Youssef Nagy A.
Published: November 2023

Background: Delirium is a complex neuropsychiatric syndrome common in all medical settings. An acute change in cognition characterizes a disturbance of consciousness, usually resulting from an underlying medical condition or withdrawal from medications or drugs. Three different subtypes of delirium have been identified based on the motor symptoms exhibited by the patient: hyperactive, hypoactive, and mixed. This study aims to review the use of methylphenidate for treating hypoactive delirium. Methods: The review was conducted in accordance with the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. We performed a literature search of PubMed, MEDLINE, Cochrane, and clinical trial registries from 1990 to 15 March 2023. Results: A total of 115 articles were identified. After removing duplicates, 68 abstracts were reviewed by all the authors. Then, 13 full-text articles were assessed for eligibility. Three articles were deemed eligible for the systematic review. These included one prospective clinical study, one case series, and one case report. The total number of participants was 17, with multiple comorbidities. Most studies reported using methylphenidate for hypoactive delirium in terminally ill patients. All reviewed studies reported symptomatic benefits in individuals with hypoactive delirium. Conclusions: Methylphenidate may be beneficial in treating hypoactive delirium in terminally ill patients. Clinical trials are needed to assess the safety and efficacy of methylphenidate in Hypoactive delirium.
Dynamic Plant–Herbivore Interactions between Bison Space Use and Vegetation Heterogeneity in a Tallgrass Prairie
Authors: Ling Bohua , Raynor Edward J. , Joern Anthony , Goodin Douglas G.
Published: November 2023

Investigations into plant–herbivore interactions are of importance for understanding grassland ecosystem dynamics. Our research quantified the effects of vegetation heterogeneity at a patch scale of 30 m on bison space use in a tallgrass prairie through the analyses of the resource utilization function. In addition, we assessed the vegetation heterogeneity associated with bison locations by comparing the patch-scale vegetation characteristics between areas with high and low bison space use through Mann–Whitney U tests. Furthermore, we simulated the interactions between bison and vegetation patches (2 × 2 m) during the early growing season for the lowland topographic positions using agent-based modeling (ABM) as a preliminary study of linking bison foraging site selection with vegetation responses to bison grazing dynamically. The bison grazing strategy in the ABM of the grassland system was adjusted to ensure consistency in the vegetation pattern variations related to bison space use between the simulation and the empirical on-the-ground observations. The results indicated the following: (1) The effects of the patch-scale vegetation heterogeneity on the bison foraging site selection varied across the seasons, which were most evident in the middle of the growing season. (2) A relatively high level of bison space use generally resulted in diverse grassland canopies with high variability and interspersion. (3) From the ABM of the grassland system, it can be implied that bison select patches with high quality and quantity at the beginning of the growing season; as the vegetation quality and quantity improve overall, the bison graze randomly. This pattern was confirmed by observations of the bison foraging site selection in our study site. The ABM proved to be valuable in exploring and elucidating the underlying mechanisms of the grassland dynamics with a native North American grazer.
Unsupervised Methodology for Large-Scale Tree Seedling Mapping in Diverse Forestry Settings Using UAV-Based RGB Imagery
Authors: Jayathunga Sadeepa , Pearse Grant D. , Watt Michael S.
Published: November 2023

Mapping and monitoring tree seedlings is essential for reforestation and restoration efforts. However, achieving this on a large scale, especially during the initial stages of growth, when seedlings are small and lack distinct morphological features, can be challenging. An accurate, reliable, and efficient method that detects seedlings using unmanned aerial vehicles (UAVs) could significantly reduce survey costs. In this study, we used an unsupervised approach to map young conifer seedlings utilising spatial, spectral, and structural information from UAV digital aerial photogrammetric (UAV-DAP) point clouds. We tested our method across eight trial stands of radiata pine with a wide height range (0.4–6 m) that comprised a total of ca. 100 ha and spanned diverse site conditions. Using this method, seedling detection was excellent, with an overall precision, sensitivity, and F1 score of 95.2%, 98.0%, and 96.6%, respectively. Our findings demonstrated the importance of combining spatial, spectral, and structural metrics for seedling detection. While spectral and structural metrics efficiently filtered out non-vegetation objects and weeds, they struggled to differentiate planted seedlings from regenerating ones due to their similar characteristics, resulting in a large number of false positives. The inclusion of a row segment detection algorithm overcame this limitation and successfully identified most regenerating seedlings, leading to a significant reduction in false positives and an improvement in overall detection accuracy. Our method generated vector files containing seedling positions and key structural characteristics (seedling height, crown dimensions), offering valuable outputs for precision management. This automated pipeline requires fewer resources and user inputs compared to manual annotations or supervised techniques, making it a rapid, cost-effective, and scalable solution which is applicable without extensive training data. While serving as primarily a standalone tool for assessing forestry projects, the proposed method can also complement supervised seedling detection methods like machine learning, i.e., by supplementing training datasets.
Multi-Stage Semantic Segmentation Quantifies Fragmentation of Small Habitats at a Landscape Scale
Authors: van der Plas Thijs L. , Geikie Simon T. , Alexander David G. , Simms Daniel M.
Published: November 2023

Land cover (LC) maps are used extensively for nature conservation and landscape planning, but low spatial resolution and coarse LC schemas typically limit their applicability to large, broadly defined habitats. In order to target smaller and more-specific habitats, LC maps must be developed at high resolution and fine class detail using automated methods that can efficiently scale to large areas of interest. In this work, we present a Machine Learning approach that addresses this challenge. First, we developed a multi-stage semantic segmentation approach that uses Convolutional Neural Networks (CNNs) to classify LC across the Peak District National Park (PDNP, 1439 km2) in the UK using a detailed, hierarchical LC schema. High-level classes were predicted with 95% accuracy and were subsequently used as masks to predict low-level classes with 72% to 92% accuracy. Next, we used these predictions to analyse the degree and distribution of fragmentation of one specific habitat—wet grassland and rush pasture—at the landscape scale in the PDNP. We found that fragmentation varied across areas designated as primary habitat, highlighting the importance of high-resolution LC maps provided by CNN-powered analysis for nature conservation.
First Assessment of Bistatic Geometric Calibration and Geolocation Accuracy of Innovative Spaceborne Synthetic Aperture Radar LuTan-1
Authors: Mou Jingwen , Wang Yu , Hong Jun , Wang Yachao , Wang Aichun , Sun Shiyu , Liu Guikun
Published: November 2023

LuTan-1 (LT-1) is a bistatic synthetic aperture radar (BiSAR) system consisting of two identical L-band SAR satellites. The bistatic mode of LT-1 plays a critical role in generating high-precision digital elevation models (DEMs), which requires precise geometric calibration of initial range and azimuth times for both SARs to ensure the reliability and quality of geolocation. However, existing geometric calibration methods predominantly focus on monostatic SAR systems, with limited literature on slave SAR calibration in bistatic systems. This research addresses this gap by establishing geometric calibration models for both SARs based on signal echo history and the range–Doppler model. The geometric errors are effectively resolved using corner reflector data from Xinjiang, China. Through statistical analysis of LT-1 SAR images acquired between July and November in bistatic mode, this paper has demonstrated range delay accuracy of better than 5 ns and azimuth time accuracy of better than 0.1 ms. This level of precision translates into a positional accuracy better than 0.8 m. The proposed models have been successfully applied to geometric calibration, providing precise geolocation for LT-1, thus enhancing its utility for a wide range of Earth observation applications. This paper is the first endeavor to present the assessment of the geometric calibration and geolocation accuracy of LT-1 and discuss the results of the bistatic geometric calibration of the master and slave SARs in a BiSAR formation.
Dual-Signal Feature Spaces Map Protein Subcellular Locations Based on Immunohistochemistry Image and Protein Sequence
Authors: Zou Kai , Wang Simeng , Wang Ziqian , Zou Hongliang , Yang Fan
Published: November 2023

Protein is one of the primary biochemical macromolecular regulators in the compartmental cellular structure, and the subcellular locations of proteins can therefore provide information on the function of subcellular structures and physiological environments. Recently, data-driven systems have been developed to predict the subcellular location of proteins based on protein sequence, immunohistochemistry (IHC) images, or immunofluorescence (IF) images. However, the research on the fusion of multiple protein signals has received little attention. In this study, we developed a dual-signal computational protocol by incorporating IHC images into protein sequences to learn protein subcellular localization. Three major steps can be summarized as follows in this protocol: first, a benchmark database that includes 281 proteins sorted out from 4722 proteins of the Human Protein Atlas (HPA) and Swiss-Prot database, which is involved in the endoplasmic reticulum (ER), Golgi apparatus, cytosol, and nucleoplasm; second, discriminative feature operators were first employed to quantitate protein image-sequence samples that include IHC images and protein sequence; finally, the feature subspace of different protein signals is absorbed to construct multiple sub-classifiers via dimensionality reduction and binary relevance (BR), and multiple confidence derived from multiple sub-classifiers is adopted to decide subcellular location by the centralized voting mechanism at the decision layer. The experimental results indicated that the dual-signal model embedded IHC images and protein sequences outperformed the single-signal models with accuracy, precision, and recall of 75.41%, 80.38%, and 74.38%, respectively. It is enlightening for further research on protein subcellular location prediction under multi-signal fusion of protein.
A Pipeline Defect Instance Segmentation System Based on SparseInst
Authors: Wang Niannian , Zhang Jingzheng , Song Xiaotian
Published: November 2023

Deep learning algorithms have achieved encouraging results for pipeline defect segmentation. However, existing defect segmentation methods may encounter challenges in accurately segmenting the complex features of pipeline defects and suffer from low processing speeds. Therefore, in this study, we propose Pipe-Sparse-Net, a pipeline defect segmentation system that combines StyleGAN3 to segment the complex forms of underground drainage pipe defects. First, we introduce a data augmentation algorithm based on StyleGAN3 to enlarge the dataset. Next, we propose Pipe-Sparse-Net, a pipeline segmentation model based on SparseInst, to accurately predict the defect regions in drainage pipes. Experimental results demonstrate that the segmentation accuracy of this model can reach 91.4% with a processing speed of 56.7 frames per second (FPS). To validate the superiority of this method, comparative experiments were conducted against Yolact, Condinst, and Mask R-CNN, and the model achieved a speed improvement of 45% while increasing the accuracy by more than 4%.
Governance of a Blockchain-Enabled IoT Ecosystem: A Variable Geometry Approach
Authors: Ullah Ikram , Havinga Paul J. M.
Published: November 2023

The proliferation of Internet of Things (IoT) applications is rapidly expanding, generating increased interest in the incorporation of blockchain technology within the IoT ecosystem. IoT applications enhance the efficiency of our daily lives, and when blockchain is integrated into the IoT ecosystem (commonly referred to as a blockchain-IoT system), it introduces crucial elements, like security, transparency, trust, and privacy, into IoT applications. Notably, potential domains where blockchain can empower IoT applications include smart logistics, smart health, and smart cities. However, a significant obstacle hindering the widespread adoption of blockchain-IoT systems in mainstream applications is the absence of a dedicated governance framework. In the absence of proper regulations and due to the inherently cryptic nature of blockchain technology, it can be exploited for nefarious purposes, such as ransomware, money laundering, fraud, and more. Furthermore, both blockchain and the IoT are relatively new technologies, and the absence of well-defined governance structures can erode confidence in their use. Consequently, to fully harness the potential of integrating blockchain-IoT systems and ensure responsible utilization, governance plays a pivotal role. The implementation of appropriate regulations and standardization is imperative to leverage the innovative features of blockchain-IoT systems and prevent misuse for malicious activities. This research focuses on elucidating the significance of blockchain within governance mechanisms, explores governance tailored to blockchain, and proposes a robust governance framework for the blockchain-enabled IoT ecosystem. Additionally, the practical application of our governance framework is showcased through a case study in the realm of smart logistics. We anticipate that our proposed governance framework will not only facilitate but also promote the integration of blockchain and the IoT in various application domains, fostering a more secure and trustworthy IoT landscape.
Explanatory Journalism within European Fact Checking Platforms: An Ally against Disinformation in the Post-COVID-19 Era
Authors: Moreno-Gil Victoria , Ramon-Vegas Xavier , Rodríguez-Martínez Ruth , Mauri-Ríos Marcel
Published: November 2023

In the post-COVID era, explanatory journalism is undergoing a resurgence that can be attributed to the proliferation of false content disseminated via social networks and the maturation of fact checking initiatives. Fact checkers are beginning to delve into those topics that are recurrent targets of disinformation to make complex issues accessible to the public. This study investigates the characteristics and methodologies of contemporary explanatory journalism by analysing four European verification platforms (Newtral in Spain, Les Décodeurs in France, FACTA.news in Italy and The Journal FactCheck unit in Ireland). We employed content analysis of a corpus of explainers and semi-structured interviews with the managers of these outlets. Our findings reveal that explainers encompass a wide range of topics, typically revolving around current affairs. These pieces are usually authored by fact checkers and published, with bylines, within dedicated sections that encourage audience participation. Explainers do not adhere to a fixed periodicity or length and adopt a format similar to feature articles, displaying a degree of flexibility. They leverage data provided by experts and official sources and employ visual elements to convey information clearly. The interviewed managers concur that explanatory journalism represents an invaluable tool in combatting disinformation and has a promising future ahead.
Impact of Social Media on Adolescence: Mapping Emerging Needs to Build Resilient Skills
Authors: Falcón-Linares Carolina , González-Yubero Sara , Mauri-Medrano Marta , Cardoso-Moreno María Jesús
Published: November 2023

It is important to study the impact of social media on mental health and well-being, as most young people use social media. Research has provided evidence of the link between social media and mental health, identifying vulnerability variables, risk factors, comorbidity, and predictors of deterioration or improvement. However, there is still very little qualitative insight into young people’s experiences and perceptions of social media and its impact on their subjective well-being. This study consists of a systematic review of the literature and a narrative synthesis of scientific articles published between 2013 and 2023 and indexed in the most important scientific databases in our field of knowledge. The SALSA protocol for systematic reviews of scientific literature was followed. We worked on a final sample of 25 articles, all of which were qualitative in methodology. From the content analysis, we extracted five thematic categories that describe and explore in depth the complex impact of social networks on adolescents’ well-being. The interactions between positive and negative effects, as well as the links with protective or vulnerability factors, are presented with the aim of constructing as complete a knowledge framework as possible. The paper concludes with useful implications for educational interventions.
Blockchain-Powered Incentive System for JIT Arrival Operations and Decarbonization in Maritime Shipping
Authors: Nguyen Son , Leman Aengus , Xiao Zhe , Fu Xiuju , Zhang Xiaocai , Wei Xiaoyang , Zhang Wanbing , Li Ning , Zhang Wei , Qin Zheng
Published: November 2023

Efficiency and sustainability are undisputedly the most critical objectives for modern ports. Current exercises for port services still lack performance profiling for arriving vessels regarding their arrival punctuality and compliance with port resource schedule for Just-in-time (JIT) service, as well as their efforts contributing towards less emission through reduced turnaround time within port. As a result, a performance-based incentive is missing. Bringing in the incentive component may facilitate the objectives of achieving both port efficiency and sustainability. Blockchain technology, owning to its intrinsic features like immutability, traceability, governance and provenance, and in-built tokens (for most public chain platforms), allow for the establishment of system solutions to record key performance indicators (KPIs) and distribute incentives to good performers. This paper is the first to propose a blockchain-based system to incentivize JIT and green operations in ports. The platform system design and operating mechanisms are elaborated in detail, and a prototype system has been implemented based on the Solana blockchain to demonstrate the core features. The current system’s potential is substantial, considering the industry’s increasing awareness about its environmental footprint. Continuous developments can be facilitated by connecting to market-based measures such as carbon pricing and emission trading in the maritime sector.