bluuebunny/crossref_metadata_2025 huggingface dataset:
Impacts of Environmental Targets on the Livestock Sector: An Assessment Tool Applied to Italy
Authors: Dell’Unto Davide , Dono Gabriele , Cortignani Raffaele
Published: March 2023

Environmental and climate targets are becoming very relevant policy objectives for European agriculture. The introduction of environmental targets could have important impacts on production, land use and economic dimensions of the EU agricultural sector. The livestock sector is influenced doubly, considering crop cultivation and livestock-rearing activities and their interactions. This study assesses the impacts on Italian livestock farms from the implementation of some environmental targets set by the Farm to Fork strategy, i.e., reducing the use of chemical inputs for forage crops and antimicrobials for livestock. An agroeconomic supply model based on microdata from the Farm Accountancy Data Network is used to evaluate the impacts on production, land use and socio-economic outcomes. Results show an increase of feed purchases to maintain livestock numbers in all farm types, while limiting the use of chemical inputs for forage crops. Adding limitations on the use of antimicrobials, livestock number decreases in all farm types, but especially in those rearing granivores. Negative economic impacts are particularly observed in farms of small and medium economic size. The highest reduction of labor employment occurs in farms of large economic size. Results could support policymakers’ decisions in setting measures that aid transition towards more sustainable farming systems.
Automated Quantification of the Behaviour of Beef Cattle Exposed to Heat Load Conditions
Authors: Idris Musadiq , Gay Caitlin C. , Woods Ian G. , Sullivan Megan , Gaughan John B. , Phillips Clive J. C.
Published: March 2023

Cattle change their behaviour in response to hot temperatures, including by engaging in stepping that indicates agitation. The automated recording of these responses would be helpful in the timely diagnosis of animals experiencing heat loading. Behavioural responses of beef cattle to hot environmental conditions were studied to investigate whether it was possible to assess behavioural responses by video-digitised image analysis. Open-source automated behavioural quantification software was used to record pixel changes in 13 beef cattle videorecorded in a climate-controlled chamber during exposure to a simulated typical heat event in Queensland, Australia. Increased digitised movement was observed during the heat event, which was related to stepping and grooming/scratching activities in standing animals. The 13 cattle were exposed in two cohorts, in which the first group of cattle (n = 6) was fed a standard finisher diet based on a high percentage of cereal grains, and the second group of cattle (n = 7) received a substituted diet in which 8% of the grains were replaced by lucerne hay. The second group displayed a smaller increase in digitised movements on exposure to heat than the first, suggesting less discomfort under hot conditions. The results suggest that cattle exposed to heat display increased movement that can be detected automatically by video digitisation software, and that replacing some cereal grain with forage in the diet of feedlot cattle may reduce the measured activity responses to the heat.
Potential Impact of Environmental Pollution by Human Antivirals on Avian Influenza Virus Evolution
Authors: Ala Ugo , Bajardi Paolo , Giacobini Mario , Bertolotti Luigi
Published: March 2023

Antiviral (AV) drugs are the main line of defense against pandemic influenza. However, different administration policies are applied in countries with different stocks of AV drugs. These policies lead to different occurrences of drug metabolites in the aquatic environment, altering animal behavior with evolutionary consequences on viruses. The aim of this study was to investigate the potential impact of environmental pollution by human antivirals, such as oseltamivir carboxylate (OC), on the evolutionary rate of avian influenza. We used NA, HA, NP, and MP viral segments from two groups of neighboring countries sharing migratory routes of wild birds and characterized by different AV stockpiles. BEAST analyses were performed using the uncorrelated lognormal clock evolutionary model and the Bayesian skyline tree prior model. The ratios between the rate of evolution of the NA gene and the HA, NP, and MP segments were considered. The two groups of countries were compared by analyzing the differences in the ratio distributions. Our analyses highlighted a possible different behavior in the evolution of H5N1 2.3 clade viral strains when OC environmental pollution is present. In conclusion, the widespread consumption of antivirals and their presence in wastewater could influence the selective pressure on viruses.
Artificial Neural Network Prediction of Antiadhesion and Antibiofilm-Forming Effects of Antimicrobial Active Mushroom Extracts on Food-Borne Pathogens
Authors: Vunduk Jovana , Klaus Anita , Lazić Vesna , Kozarski Maja , Radić Danka , Šovljanski Olja , Pezo Lato
Published: March 2023

The problem of microbial biofilms has come to the fore alongside food, pharmaceutical, and healthcare industrialization. The development of new antibiofilm products has become urgent, but it includes bioprospecting and is time and money-consuming. Contemporary efforts are directed at the pursuit of effective compounds of natural origin, also known as “green” agents. Mushrooms appear to be a possible new source of antibiofilm compounds, as has been demonstrated recently. The existing modeling methods are directed toward predicting bacterial biofilm formation, not in the presence of antibiofilm materials. Moreover, the modeling is almost exclusively targeted at biofilms in healthcare, while modeling related to the food industry remains under-researched. The present study applied an Artificial Neural Network (ANN) model to analyze the anti-adhesion and anti-biofilm-forming effects of 40 extracts from 20 mushroom species against two very important food-borne bacterial species for food and food-related industries—Listeria monocytogenes and Salmonella enteritidis. The models developed in this study exhibited high prediction quality, as indicated by high r2 values during the training cycle. The best fit between the modeled and measured values was observed for the inhibition of adhesion. This study provides a valuable contribution to the field, supporting industrial settings during the initial stage of biofilm formation, when these communities are the most vulnerable, and promoting innovative and improved safety management.
Screening for Tuberculosis Infection among Migrants: A Cost-Effectiveness Analysis in the Italian Context
Authors: Russo Giulia , Marchese Valentina , Formenti Beatrice , Cimaglia Claudia , Di Rosario Gianluca , Cristini Irene , Magro Paola , El-Hamad Issa , Cirillo Daniela Maria , Girardi Enrico , Matteelli Alberto
Published: March 2023

Background: Screening of tuberculosis infection (TBI) among migrants from high-incidence countries is a cornerstone of tuberculosis control in low-incidence countries. However, the optimal screening strategy has not been defined yet. Methods: A quasi-experimental study involving migrants residing in the province of Brescia was carried out that aimed at assessing the completion rate, time to completion, preventive treatment initiation rate, and cost-effectiveness of two strategies for TBI screening. They underwent TBI screening with the IGRA-only strategy (arm 1) or with the sequential strategy (tuberculin skin test, TST, followed by IGRA in case of a positive result—arm 2). The two strategies were compared in terms of screening completion, time to complete the screening process, therapy initiation, and cost-effectiveness. Results: Between May 2019 and May 2022, 657 migrants were evaluated, and 599 subjects were included in the study, with 358 assigned to arm 1 and 237 to arm 2. Screening strategy was the only factor associated with screening completion in a multivariable analysis, with the subjects assigned to the IGRA-only strategy more likely to complete the screening cascade (n = 328, 91.6% vs. n = 202, 85.2%, IRR 1.08, 95% CI (1.01–1.14), p = 0.019). The time to complete the screening process was significantly longer for patients assigned to the sequential strategy arm (74 days vs. 46 days, p = 0.002). Therapy initiation did not significantly differ between the two arms, and cost-effectiveness was higher for the sequential strategy. Conclusion: Sequential strategy implementation for TBI screening among migrants may be justified by its higher cost-effectiveness in spite of the lower completion of the screening cascade.
Active Optics and Aberration Correction Technology for Sparse Aperture Segmented Mirrors
Authors: Zhang Benlei , Yang Fei , Wang Fuguo , Lu Baowei
Published: March 2023

Active optics and aberration correction techniques for sparse aperture segmented mirrors are studied. A finite element model of the sparse aperture segmented mirror was established, and a multi-aperture aberration polynomial was derived. According to the hard spot theorem, a co-phase maintenance method based on the change of the edge sensor position in the conventional mode is derived. And a co-phase maintenance method based on the change of the aberration of the segmented mirror surface without the participation of the edge sensor is proposed. The method can correct aberrations of the segmented mirror surface, which are caused by the rigid body displacement along the horizontal direction of the segments. This method can reduce the RMS of the segmented mirror surface to 2.2 nm. The correction principle of the Warping Harness (WH) technique is derived. For the problems of tedious steps and a small number of target aberrations, the correction method is proposed to directly target the aberrations of the segmented mirrors, which is simple and has a wider range of target aberrations. Using this method, the amplitude of each aberration of the stitched mirror is corrected to below 10−4nm. It is also verified that combining the generalized ridge estimation method and the differential evolution algorithm can effectively solve the correction quantity. Finally, it is verified that the SiC material can effectively improve the adaptability of the segmented mirror to gravity load by reducing the mirror’s weight.
Research on Fault Diagnosis Algorithm of Ship Electric Propulsion Motor
Authors: Ma Fengxin , Qi Liang , Ye Shuxia , Chen Yuting , Xiao Han , Li Shankai
Published: March 2023

The permanent magnet synchronous motor (PMSM) has been used in electric propulsion and other fields. However, it is prone to the stator winding inter-turn short-circuit, and if no effective measures are taken, the ship’s power system will be paralyzed. To realize intelligent diagnosis of inter-turn short circuits, this paper proposes an intelligent fault diagnosis method based on improved variational mode decomposition (VMD), multi-scale principal component analysis (PCA) feature extraction, and improved Bi-LSTM. Firstly, the stator current simulation dataset is obtained by using the mathematic model of the inter-turn short-circuit of PMSM, and the parameters of VMD are optimized by the grey wolf algorithm. Then, the data is coarse-grained to obtain multi-scale features, and the main features are selected as the sample data for fault classification by PCA. Subsequently, the Bi-LSTM neural network is used for training and analyzing the data of the sample set and the test set. Finally, the learning rate and the number of hidden-layer nodes of the Bi-LSTM are optimized by the whale algorithm to increase the diagnosis accuracy. Experimental results show that the accuracy of the proposed method for inter-turn short-circuited fault diagnosis is as high as 100%, which confirms the effectiveness of the method.
Research on Truck Lane Management Strategies for Platooning Speed Optimization and Control on Multi-Lane Highways
Authors: Rui Yikang , Wang Shu , Wu Renfei , Shen Zhe
Published: March 2023

Automated truck platooning has become an increasingly popular research subject, and its applicability to highways is considered one of the earliest possible landing scenarios for automated driving. However, there is a lack of research regarding the combination of truck platooning technology and truck lane management strategy on multilane highways in the environment of a cooperative vehicle–infrastructure system (CVIS). For highway weaving sections under the CVIS environment, this paper proposes a truck platooning optimal speed control model based on multi-objective optimization. Through a combination of model predictive control and the cell transmission model, this approach considers the bottleneck cell traffic flow, overall vehicle travel time, and truck platooning fuel consumption as objectives. By conducting experiments on a mixed traffic flow simulation platform, the multi-lane management strategies and optimal speed control effect were evaluated through different scenarios. This study also determined the appropriate proportion of truck platooning for an exclusive lane and to increase truck lanes, thus providing effective lane management decision support for highway managers.
Small-Scale Zero-Shot Collision Localization for Robots Using RL-CNN
Authors: Lin Haoyu , Lou Ya’nan , Quan Pengkun , Liang Zhuo , Wei Dongbo , Di Shichun
Published: March 2023

For safety reasons, in order to ensure that a robot can make a reasonable response after a collision, it is often necessary to localize the collision. The traditional model-based collision localization methods, which are highly dependent on the designed observer, are often only useful for rough localization due to the bias between simulation and real-world application. In contrast, for fine collision localization of small-scale regions, data-driven methods can achieve better results. In order to obtain high localization accuracy, the data required by data-driven methods need to be as comprehensive as possible, and this will greatly increase the cost of data collection. To address this problem, this article is dedicated to developing a data-driven method for zero-shot collision localization based on local region data. In previous work, global region data were used to construct the collision localization model without considering the similarity of the data used for analysis caused by the assembly method of the contact parts. However, when using local region data to build collision localization models, the process is easily affected by similarity, resulting in a decrease in the accuracy of collision localization. To alleviate this situation, a two-stage scheme is implemented in our method to simultaneously isolate the similarity and realize collision localization. Compared with the classical methods, the proposed method achieves significantly improved collision localization accuracy.
Edge Currents Induced by AC Electric Field in Two-Dimensional Dirac Structures
Authors: Durnev Mikhail V. , Tarasenko Sergey A.
Published: March 2023

Edges in two-dimensional structures are the source of nonlinear transport and optical phenomena which are particularly important in small-size flakes. We present a microscopic theory of the edge photogalvanic effect, i.e., the formation of DC electric current flowing along the sample edges in response to AC electric field of the incident terahertz radiation, for two-dimensional Dirac materials including the systems with massive and massless charge carriers. The edge current direction is controlled by the AC field polarization. The spectral dependence of the current is determined by the carrier dispersion and the mechanism of carrier scattering, as shown for single-layer and bilayer graphene as examples.
All-Digital Computing-in-Memory Macro Supporting FP64-Based Fused Multiply-Add Operation
Authors: Li Dejian , Mo Kefan , Liu Liang , Pan Biao , Li Weili , Kang Wang , Li Lei
Published: March 2023

Recently, frequent data movement between computing units and memory during floating-point arithmetic has become a major problem for scientific computing. Computing-in-memory (CIM) is a novel computing paradigm that merges computing logic into memory, which can address the data movement problem with excellent power efficiency. However, the previous CIM paradigm failed to support double-precision floating-point format (FP64) due to its computing complexity. This paper presents a novel all-digital CIM macro-DCIM-FF to complete FP64 based fused multiply-add (FMA) operation for the first time. With 16 sub-CIM cells integrating digital multipliers to complete mantissa multiplication, DCIM-FF is able to provide correct rounded implementations for normalized/denormalized inputs in round-to-nearest-even mode and round-to-zero mode, respectively. To evaluate our design, we synthesized and tested the DCIM-FF macro in 55-nm CMOS technology. With a minimum power efficiency of 0.12 mW and a maximum computing efficiency of 26.9 TOPS/W, we successfully demonstrated that DCIM-FF can run the FP64-based FMA operation without error. Compared to related works, the proposed DCIM-FF macro shows significant power efficiency improvement and less area overhead based on CIM technology. This work paves a novel pathway for high-performance implementation of an FP64-based matrix-vector multiplication (MVM) operation, which is essential for hyperscale scientific computing.
The Politics and Aesthetic Choices of Feminist Art Criticism
Authors: Deepwell Katy
Published: March 2023

This article explores feminist art criticism from the point of view of aesthetics/politics in global contemporary art. It is based on the author’s experience as an art critic and founding editor of n.paradoxa: international feminist art journal (1998–2017). Reading articles published in the previous two decades both for the journal and outside it, it became possible to identify how subjects produce specific objects in art criticism that demonstrate different locations and standpoints in thought and how these align with criticism from broader feminist political theories. This is an exploration of the aesthetics/politics both in, about and beyond feminist art criticism. The methodology presented analyses feminist art criticism using a model of clusters of concepts that draws on Anne Ring Petersen’s examination of identity politics, race and multiculturalism from 2012. Feminist analyses in which this approach has been attempted are discussed: Sue Rosser’s 2005 analysis of cyberfeminism and Tuzyline Jita Allan’s 1995 discussion of black/womanist/African feminisms. The article identifies four types of feminist art criticism: liberal feminism, materialist feminism, feminist cosmopolitan multi-culturalism, and queer post-colonial feminism. The aims, methods and approaches of these tendencies are outlined to demonstrate the differences between them. The article concludes with a discussion about the futures of feminist art criticism.
Coefficient Bounds for a Family of s-Fold Symmetric Bi-Univalent Functions
Authors: Al-shbeil Isra , Khan Nazar , Tchier Fairouz , Xin Qin , Malik Sarfraz Nawaz , Khan Shahid
Published: March 2023

We present a new family of s-fold symmetrical bi-univalent functions in the open unit disc in this work. We provide estimates for the first two Taylor–Maclaurin series coefficients for these functions. Furthermore, we define the Salagean differential operator and discuss various applications of our main findings using it. A few new and well-known corollaries are studied in order to show the connection between recent and earlier work.
Dynamic Regulation Genes at Microtubule Plus Ends: A Novel Class of Glioma Biomarkers
Authors: Wang Wenwen , Li Weilong , Pan Lifang , Li Lingjie , Xu Yasi , Wang Yuqing , Zhang Xiaochen , Zhang Shirong
Published: March 2023

Glioma is the most prevalent and aggressive primary nervous system tumor with an unfavorable prognosis. Microtubule plus-end-related genes (MPERGs) play critical biological roles in the cell cycle, cell movement, ciliogenesis, and neuronal development by coordinating microtubule assembly and dynamics. This research seeks to systematically explore the oncological characteristics of these genes in microtubule-enriched glioma, focusing on developing a novel MPERG-based prognostic signature to improve the prognosis and provide more treatment options for glioma patients. First, we thoroughly analyzed and identified 45 differentially expressed MPERGs in glioma. Based on these genes, glioma patients were well distinguished into two subgroups with survival and tumor microenvironment infiltration differences. Next, we further screened the independent prognostic genes (CTTNBP2, KIF18A, NAV1, SLAIN2, SRCIN1, TRIO, and TTBK2) using 36 prognostic-related differentially expressed MPERGs to construct a signature with risk stratification and prognostic prediction ability. An increased risk score was related to the malignant progression of glioma. Therefore, we also designed a nomogram model containing clinical factors to facilitate the clinical use of the risk signature. The prediction accuracy of the signature and nomogram model was verified using The Cancer Genome Atlas and Chinese Glioma Genome Atlas datasets. Finally, we examined the connection between the signature and tumor microenvironment. The signature positively correlated with tumor microenvironment infiltration, especially immunoinhibitors and the tumor mutation load, and negatively correlated with microsatellite instability and cancer stemness. More importantly, immune checkpoint blockade treatment and drug sensitivity analyses confirmed that this prognostic signature was helpful in anticipating the effect of immunotherapy and chemotherapy. In conclusion, this research is the first study to define and validate an MPERG-based signature closely associated with the tumor microenvironment as a reliable and independent prognostic biomarker to guide personalized choices of immunotherapy and chemotherapy for glioma patients.
Current State of Rare and Endangered Barbels of the Genus Luciobarbus Heckel, 1843 in the Aral–Syrdarya Basin (Kazakhstan) and Prospects for Their Conservation (A Review)
Authors: Adyrbekova Kamila , Isbekov Kuanysh B. , Barakbayev Tynysbek T. , Iskhakhov Galymzhan Zh.
Published: March 2023

The current status of the barbels inhabiting the Kazakhstan section of the Syrdarya River needs special study, as has been noted since the second half of the 20th century. Stocks of commercial fish valuable in the past as barbels in the Aral–Syrdarya basin are now catastrophically reduced as a result of anthropogenic impact on the ichthyofauna and natural environment of the Aral Sea region. The study of the condition; abundance and distribution range is necessary to determine measures for their restoration in natural habitats and their breeding in fish farms. Research on the biotechnology of barbel breeding with subsequent acclimatization and reacclimatization of these fish species will not only improve the composition of the ichthyofauna of the Aral–Syrdarya basin, but also preserve the genetic potential of natural populations. At present, the only way to restore the population of the Aral barbel is stocking hatchery reared juveniles in natural environments. Under the current situation, a way forward is seen in the creation of domesticated replacement-broodstocks of barbels. As a result of the influence of anthropogenic factors, the populations of this species have come to almost complete degradation and depletion and require the development and adoption of urgent measures for their conservation and restoration through reintroduction, which is a priority and urgent task for the fisheries of the republic.
A Study on South Korean College Students’ Perceptions of Gratitude
Authors: Lee Namki , Kim Yucheon
Published: March 2023

Humans feel happy when they experience positive emotions; gratitude is a significant inducer of positive emotions. This study investigates perceptions of gratitude among South Korean college students using the Q methodology, which enables the examination of individuals’ subjectivity. We collected 227 statements from a Q population through literature reviews, paper reviews, interviews, and questionnaire surveys; from them statements, we selected 40 Q samples. The P samples included 46 college students at Dongguk University in Seoul, South Korea, and we performed data analysis with Principal Component Factor Analysis using the Quanl program. Using the results of this study, we classified gratitude into five types: Type 1 active gratitude through expression; Type 2 passive gratitude depending on conditions; Type 3 gratitude through relationships; Type 4 gratitude through internal satisfaction, and; Type 5 gratitude through materials. The results point to differences in experiences of gratitude that depend on conditions and environments, and by type. Researchers and administrators can use the results of this study to understand South Korean college students’ perspectives and perceptions when planning and implementing gratitude programs that prioritize their happiness.
Regret Theory and Fuzzy-DEMATEL-Based Model for Construction Program Manager Selection in China
Authors: Yan Hongyan , Yang Yuxuan , Lei Xi , Ye Qing , Huang Wenzhen , Gao Ce
Published: March 2023

During the drastic changing process of the construction industry in China, construction program management has been given significant attention. Due to the complexity of construction programs, selecting competent managers is crucially important to its success. Therefore, based on a comprehensive literature review, this paper combines regret theory and the Fuzzy-DEMATEL method to develop a multi-attribute model for construction program manager selection. Firstly, six competence elements are extracted, then the manager selection and evaluation index system are constructed. Secondly, the regret theory is used to simulate the psychological characteristics of the decision makers, combined with Fuzzy-DEMATEL, the comprehensive weights for each element are calculated. Lastly, all alternatives for the selection are sorted and the competent ones are selected. A case study is provided to exam the effectiveness of the developed model. Results shows that the proposed model adopted multi-attribute evaluation and group decision making and took into account the psychological behavior of decision makers as well as influences from the relationships between different attributes. Such results indicate that the proposed model is able to provide more comprehensive and scientific construction program manager selections, which can further improve the management of construction programs.
Green Synthesis of Magnesium Oxide Nanoparticles and Nanocomposites for Photocatalytic Antimicrobial, Antibiofilm and Antifungal Applications
Authors: Ramezani Farani Marzieh , Farsadrooh Majid , Zare Iman , Gholami Amir , Akhavan Omid
Published: March 2023

Magnesium oxide nanoparticles (MgO NPs) have emerged as potential materials for various biomedical applications due to their unique physicochemical properties, including biodegradability, biocompatibility, cationic capacity, high stability and redox properties. MgO NPs have become an attractive platform to combat microbes and may be a promising alternative to overcome challenges associated with eliminating microbial biofilms and antibiotic resistance. Hence, due to the increasing use of MgO NPs in biomedicine, new synthetic strategies for MgO NPs are necessary. MgO NPs synthesised using green methods are non-toxic, eco-friendly and have high stability for a wide range of biological, medical and catalytic applications. This review presents the recent advances in biosynthesis strategies of MgO NPs by diverse bio-templates, such as plant, bacterial, fungal and algal extracts. Its photocatalytic properties show a suitable inhibitory function against pathogenic agents, such as microbial proliferation, biofilm formation and fungal growth. Furthermore, MgO NPs and relevant nanocomposites are comprehensively discussed regarding the mechanisms of their effect on microbes, biofilms and fungal strains, as well as challenges and future perspectives.
Computational and Functional Analysis of Structural Features in the ZAKα Kinase
Authors: Johansen Valdemar Brimnes Ingemann , Snieckute Goda , Vind Anna Constance , Blasius Melanie , Bekker-Jensen Simon
Published: March 2023

The kinase ZAKα acts as the proximal sensor of translational impairment and ribotoxic stress, which results in the activation of the MAP kinases p38 and JNK. Despite recent insights into the functions and binding partners of individual protein domains in ZAKα, the mechanisms by which ZAKα binds ribosomes and becomes activated have remained elusive. Here, we highlight a short, thrice-repeated, and positively charged peptide motif as critical for the ribotoxic stress-sensing function of the Sensor (S) domain of ZAKα. We use this insight to demonstrate that the mutation of the SAM domain uncouples ZAKα activity from ribosome binding. Finally, we use 3D structural comparison to identify and functionally characterize an additional folded domain in ZAKα with structural homology to YEATS domains. These insights allow us to formulate a model for ribosome-templated ZAKα activation based on the re-organization of interactions between modular protein domains. In sum, our work both advances our understanding of the protein domains and 3D architecture of the ZAKα kinase and furthers our understanding of how the ribotoxic stress response is activated.
Induced Pluripotent Stem Cells and Their Applications in Amyotrophic Lateral Sclerosis
Authors: Du Hongmei , Huo Zijun , Chen Yanchun , Zhao Zhenhan , Meng Fandi , Wang Xuemei , Liu Shiyue , Zhang Haoyun , Zhou Fenghua , Liu Jinmeng , Zhang Lingyun , Zhou Shuanhu , Guan Yingjun , Wang Xin
Published: March 2023

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease that results in the loss of motor function in the central nervous system (CNS) and ultimately death. The mechanisms underlying ALS pathogenesis have not yet been fully elucidated, and ALS cannot be treated effectively. Most studies have applied animal or single-gene intervention cell lines as ALS disease models, but they cannot accurately reflect the pathological characteristics of ALS. Induced pluripotent stem cells (iPSCs) can be reprogrammed from somatic cells, possessing the ability to self-renew and differentiate into a variety of cells. iPSCs can be obtained from ALS patients with different genotypes and phenotypes, and the genetic background of the donor cells remains unchanged during reprogramming. iPSCs can differentiate into neurons and glial cells related to ALS. Therefore, iPSCs provide an excellent method to evaluate the impact of diseases on ALS patients. Moreover, patient-derived iPSCs are obtained from their own somatic cells, avoiding ethical concerns and posing only a low risk of immune rejection. The iPSC technology creates new hope for ALS treatment. Here, we review recent studies on iPSCs and their applications in disease modeling, drug screening and cell therapy in ALS, with a particular focus on the potential for ALS treatment.
Characterization of Non-Cholesterol Sterols in Microglia Cell Membranes Using Targeted Mass Spectrometry
Authors: Begcevic Brkovic Ilijana , Reinicke Madlen , Chey Soroth , Bechmann Ingo , Ceglarek Uta
Published: March 2023

Background: Non-cholesterol sterols, as well as plant sterols, cross the blood–brain barrier and, thus, can be incorporated into cell membranes, affecting the cell’s inflammatory response. The aim of our work was to develop an analytical protocol for a quantitative assessment of the sterol composition within the membrane microdomains of microglia. Methods: A protocol for cell membrane isolation using OptiPrepTM gradient ultracentrifugation, in combination with a targeted mass spectrometry (LC-MS/MS)-based assay, was developed and validated for the quantitative analysis of free sterols in microglia cell membranes. Results: Utilizing an established LC-MS/MS assay, cholesterol and seven non-cholesterol sterols were analyzed with a limit of detection from 0.001 to 0.05 mg/L. Applying the detergent-free isolation of SIM-A9 microglia cell membranes, cholesterol (CH), desmosterol (DE), lanosterol (LA) stigmasterol (ST), beta-sitosterol (SI) and campesterol (CA) were quantified with coefficients of variations between 6 and 29% (fractions 4–6, n = 5). The highest concentrations of non-CH sterols within the microglia plasma membranes were found in the microdomain region (DE>LA>SI>ST>CA), with ratios to CH ranging from 2.3 to 435 lower abundancies. Conclusion: By applying our newly developed and validated analytical protocol, we show that the non-CH sterol concentration is about 38% of the total sterol content in microglia membrane microdomains. Further investigations must clarify how changes in the non-sterol composition influence membrane fluidity and cell signaling.
Influence of Milling Conditions on AlxCoCrFeNiMoy Multi-Principal-Element Alloys
Authors: Delgado Arroyo Diego , Richter Tim , Schroepfer Dirk , Boerner Andreas , Rhode Michael , Lindner Thomas , Preuß Bianca , Lampke Thomas
Published: March 2023

Multi-Principal-Element or High-Entropy Alloys (MPEAs/HEAs) have gained increasing interest in the past two decades largely due to their outstanding properties such as superior mechanical strength and corrosion resistance. However, research studies on their processability are still scarce. This work assesses the effect of different machining conditions on the machinability of these novel alloys, with the objective of advancing the introduction of MPEA systems into industrial applications. The present study focuses on the experimental analysis of finish-milling conditions and their effects on the milling process and resulting surface finish of CoCrFeNi, Al0.3CoCrFeNi and Al0.3CoCrFeNiMo0.2 alloys fabricated via Spark Plasma Sintering. Ball-nose-end milling experiments have been carried out various milling parameters such as cutting speed, feed per cutting edge, and ultrasonic assistance. In situ measurements of cutting forces and temperature on the tool edge were performed during the experiments, and surface finish and tool wear were analyzed afterwards. The results exhibited decreasing cutting forces by means of low feed per cutting edge and reduced process temperatures at low cutting speed, with the use of ultrasonic-assisted milling. It was shown that the machinability of these modern alloys through conventional, as well as modern machining methods such as ultrasonic-assisted milling, is viable, and common theories in machining can be transferred to these novel MPEAs.
Effect of ZrH2 Doping on Electron Emission Performance of Rare Earth Tungsten Electrode
Authors: Zhou Shaoxin , Zhang Yingchao , Liang Shangshang , Yang Jiancan , Nie Zuoren
Published: March 2023

In order to explore the effect of ZrH2 on the electron emission performance of rare earth tungsten electrodes (W-La-Y), different proportions of ZrH2 were added to rare earth tungsten in this study, and samples of three proportions were obtained by ball milling and vacuum hot-pressing sintering. The electron emission performance, phase evolution and surface valence state of the samples were analyzed, respectively. The test results of electrode emission performance show that increasing the mass fraction of ZrH2 in the range of 0% to 0.1% can continuously improve the electrode emission performance. At 1600 °C, 0.1% ZrH2 can increase the zero-field current emission density from 0.36 to 0.90 A/cm2. X-ray diffraction (XRD), the comprehensive thermalgravimetric and differential thermal analysis (TG-DTA) and X-ray photoelectron spectroscopy (XPS) results showed that the ZH2 added to rare earth tungsten electrodes would react with impurity oxygen in the electrode and consume impurity oxygen, thus reducing the inhibitory effect of impurity oxygen on the electron emission of the electrode and improving its electron emission performance.
Global Instability of Rod Eutectic Growth in Directional Solidification
Authors: Gan Yanlin , Li Xiangming
Published: March 2023

In our previous work, we obtained the uniformly valid asymptotic solution of a cylindrical rod eutectic. In order to further study the critical point of the stable growth of a rod eutectic, we have considered the unsteady growth of a rod eutectic on the basis of the steady solution of the rod eutectic. Based on the experimental system of rod eutectic growth, combined with solidification thermodynamics and kinetics, the unsteady mathematical model of the rod eutectic was established. We used the asymptotic analysis method to seek the analytical solution of the mathematical model and used the nonlinear stability analysis theory to analyze the analytical solution and establish the corresponding disturbance model. We obtained the analytic form of the global mode solution and the corresponding quantization conditions and find that there is a stable growth mode, namely the mode (ST-mode), for rod eutectic growth; when ε<εST0, the rod eutectic growth is stable, when ε>εST0, the rod eutectic growth is unstable and when ε=εST0, the rod eutectic growth is of a neutral stability. The critical eutectic spacing of succinonitrile(D)camphor (SCN-DC) predicted by us is smaller than that predicted by Jackson–Hunt, which is consistent with the corresponding experimental data. Finally, we found that the critical eutectic spacing and stable region of rod eutectic growth changed little with the temperature gradient.
Current Concepts of Precancerous Lesions of Hepatocellular Carcinoma: Recent Progress in Diagnosis
Authors: Liao Ziyue , Tang Cuiping , Luo Rui , Gu Xiling , Zhou Jun , Gao Jian
Published: March 2023

The most common cause of hepatocellular carcinoma (HCC) is chronic hepatitis and cirrhosis. It is proposed that precancerous lesions of HCC include all stages of the disease, from dysplastic foci (DF), and dysplastic nodule (DN), to early HCC (eHCC) and progressed HCC (pHCC), which is a complex multi-step process. Accurately identifying precancerous hepatocellular lesions can significantly impact the early detection and treatment of HCC. The changes in high-grade dysplastic nodules (HGDN) were similar to those seen in HCC, and the risk of malignant transformation significantly increased. Nevertheless, it is challenging to diagnose precancerous lesions of HCC. We integrated the literature and combined imaging, pathology, laboratory, and other relevant examinations to improve the accuracy of the diagnosis of precancerous lesions.
Performance Comparison of Procalcitonin, Delta Neutrophil Index, C-Reactive Protein, and Serum Amyloid A Levels in Patients with Hematologic Diseases
Authors: Cho Jooyoung , Lee Jong-Han , Lee Dong Hyun , Kim Juwon , Uh Young
Published: March 2023

(1) Background: We compared the diagnostic and prognostic performance of serum amyloid A (SAA), procalcitonin (PCT), delta neutrophil index (DNI), and C-reactive protein (CRP) in patients with hematologic diseases; (2) Methods: We retrospectively collected the remaining serum samples from patients with hematologic diseases, analyzed their clinical data, and measured the levels of PCT, DNI, CRP, and SAA. Performances for infection diagnosis were evaluated using a receiver operating characteristic curve analysis, and 90-day mortality was analyzed using Kaplan–Meier estimation; (3) Results: The levels of all markers were significantly higher in the infected group (N = 27) than those in the uninfected group (N = 100) (p < 0.0001 for all markers). The areas under the curve for diagnosing infection for PCT, DNI, CRP, and SAA were 0.770, 0.817, 0.870, and 0.904, respectively. Increased PCT levels were associated with higher mortality (p = 0.0250); this association was not observed with other examined markers; (4) Conclusions: CRP and SAA exhibited greater discriminative power for infection than PCT. However, only PCT levels were positively associated with 90-day mortality. Herein, we evaluated the diagnostic performance of the four markers. Additional studies are needed to confirm the findings of the present study and validate the potential of these markers in clinical practice.
Presence of KIR2DL2/S2, KIR2DL5, and KIR3DL1 Molecules in Liver Transplant Recipients with Alcoholic Cirrhosis Could Be Implicated in Death by Graft Failure
Authors: Morales Raquel , Bolarín José Miguel , Muro Manuel , Legaz Isabel
Published: March 2023

Background: The second-most frequent diagnosis among patients receiving liver transplants (LTs) is alcoholic liver disease. The multifactorial pathophysiology of alcoholic liver disease depends on the innate immune system and the inflammatory cascade. According to recent studies on these receptors, killer-cell immunoglobulin-like receptors (KIRs) may be involved in sepsis, liver rejection, and virus relapse. We aimed to investigate the impact of preclinical issues like ascites and encephalopathy and KIR genetic traits on death from sepsis, multiorgan failure (MF), and graft failure (GF) in AC patients undergoing LTs. Methods: We retrospectively reviewed 164 consecutive and deceased Caucasian AC patients who underwent LTs. Pre-transplant complications, cause of death, and patient survival were analyzed. Genomic DNA was taken from peripheral blood, and PCR-SSO was used for genotyping KIR. Results: Compared to GF patients, there was a statistically significant increase in the frequency of KIR2DL2+ (75.8% vs. 51.2%; p = 0.047). Another increase in frequency was also observed in KIR2DS2+ in sepsis compared to the GF group (51.2% vs. 43.7%; p = 0.018). In patients who passed away from MF, a decrease in KIR2DL5+ was observed in AC patients with and without encephalopathy (p = 0.018). The frequency of KIR3DL1+ in the AC patients significantly increased the mortality from sepsis (p = 0.045), which was confirmed by multivariate logistic regression. The frequency of KIR3DL1+ in the AC patients significantly increased the mortality from sepsis (p = 0.012) and was confirmed by multivariate logistic regression. KIR2DS1+ and KIR2DS4+ showed increased mortality due to GF compared to patients without these genes (p = 0.011 and 0.012, respectively). However, this fact was confirmed only for KIR2DS1+ by multivariate logistic Cox regression. Conclusions: The presence of the KIR2DL2/S2+, KIR2DL5+, and KIR3DL1+ genes increases the frequency of death from multiple organ failure or graft failure. Our findings highlight the AC patient’s vulnerability to a LT during hospitalization. Following the transplant and outside of it, we adopt essential preventive measures to create a routine healthcare screening to enhance and modify treatments to increase survival.
Advantages and Disadvantages of Online and Face-to-Face Peer Learning in Higher Education: A Review
Authors: Topping Keith James
Published: March 2023

During the pandemic, many institutions shifted to online teaching, and in some cases, this included existing peer learning programs. As the pandemic receded, some of these peer learning programs returned to face-to-face operation and others adopted a blended format, while others remained online. Interestingly, the literature suggests that online peer learning is somewhat more effective than face-to-face peer learning. This might be because online peer learning enables responses at any time (which might be more thoughtful), anonymity, and a wider nexus of relationships, although it can create issues regarding the initial development of trust. There are a great many studies of both face-to-face and online peer learning, but relatively few that directly compare both. By way of addressing this gap, this paper aims to systematically review 17 papers that directly compare both, informed by and updating the only previous review in this area. Online performs better than offline learning in terms of cognitive outcomes, with a small to moderate effect size. However, the associated socio-emotional issues are more complex. Online learning offers flexibility regarding response time, but sacrifices the immediate dialogue of offline learning. Some cultures found accepting peer learning more difficult. Few studies undertook longer-term follow-up, although with more practice motivation, this might well improve. The results have implications for the type of peer learning chosen by pedagogical designers as appropriate to their own learning context.
Agency and Affordances in Study Abroad
Authors: Tweed Andrew D. , Reinders Hayo
Published: March 2023

Research in study abroad (SA) has developed over the past several decades, with an increasing focus on individual learners and their experiences. Despite this trend, it remains unclear what affordances beyond the classroom are available to students and whether and how learners enact their agency to make use of the available opportunities. The present study adopts an ecological framework to examine how four Japanese learners enacted their agency to capitalize on affordances for language learning beyond the classroom during study abroad. Agency is understood as a multidimensional construct, with both internal and external dimensions. Learners utilized a smartphone application to regularly report their language use and associated reflections. Further details about their experiences were elicited by post-study abroad questionnaires and interviews. The findings reveal the various kinds of language episodes reported by the students and how these learners exercised their agency in relation to their learning experiences. A discussion of what factors likely contributed to these learners’ enacting their agency is included. The study concludes with implications for supporting students’ out-of-class learning during study abroad.
Deep Crowd Anomaly Detection by Fusing Reconstruction and Prediction Networks
Authors: Sharif Md. Haidar , Jiao Lei , Omlin Christian W.
Published: March 2023

Abnormal event detection is one of the most challenging tasks in computer vision. Many existing deep anomaly detection models are based on reconstruction errors, where the training phase is performed using only videos of normal events and the model is then capable to estimate frame-level scores for an unknown input. It is assumed that the reconstruction error gap between frames of normal and abnormal scores is high for abnormal events during the testing phase. Yet, this assumption may not always hold due to superior capacity and generalization of deep neural networks. In this paper, we design a generalized framework (rpNet) for proposing a series of deep models by fusing several options of a reconstruction network (rNet) and a prediction network (pNet) to detect anomaly in videos efficiently. In the rNet, either a convolutional autoencoder (ConvAE) or a skip connected ConvAE (AEc) can be used, whereas in the pNet, either a traditional U-Net, a non-local block U-Net, or an attention block U-Net (aUnet) can be applied. The fusion of both rNet and pNet increases the error gap. Our deep models have distinct degree of feature extraction capabilities. One of our models (AEcaUnet) consists of an AEc with our proposed aUnet has capability to confirm better error gap and to extract high quality of features needed for video anomaly detection. Experimental results on UCSD-Ped1, UCSD-Ped2, CUHK-Avenue, ShanghaiTech-Campus, and UMN datasets with rigorous statistical analysis show the effectiveness of our models.