bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predictive control of permanent magnet synchronous motor based on Super‐Twisting sliding mode
Authors: Hu Jun , Lu Huacai , Zheng Bowen , Zhang Yan 
Published: June 2023

AbstractTo improve the anti‐interference ability and response speed of the permanent magnet synchronous motor control system and the problem of excessive chattering when the speed loop of the system is controlled by fast second‐order Super‐Twisting sliding mode control, an improved second‐order Super‐Twisting sliding mode controller is designed to replace the previous speed loop controller. The current loop uses model prediction to control current, which can effectively suppress chattering and improve the robustness of the whole system. The simulation results show that the response time of the system using this algorithm is not only 0.141 s faster than that of the traditional proportional integral control but also the overshoot is reduced by 10%. Then, under different working conditions, the strategy in this paper is compared with the traditional control method, and good characteristics are obtained. Finally, the whole system is used for experimental analysis. The experimental results show that this strategy has good rapidity and robustness.
Image transmission performance analysis through free space optical communication link using coherent QPSK modulation under various environmental conditions
Authors: Djir Amina , Meskine Fatiha , Tayebi Mohamed Larbi 
Published: June 2023

AbstractFree space optics (FSO) technology has been used recently in many applications due to its various advantages such as high bandwidth, easy deployment, high security, free installation license and immunity to electromagnetic interference. However, this type of communication is vulnerable to meteorological conditions such as rain, haze and fog which significantly degrade the system's efficiency. To enhance the effectiveness of the FSO systems, Quadrature Phase Shift Keying (QPSK) modulation based on coherent detection constitutes a promising technique for achieving high spectral efficiency and long‐distance FSO links with the characteristics of low‐cost implementation and simple design. This work aims to investigate the performance of FSO communication links on image transmission under the presence of atmospheric attenuations. A comparative study has been made using QPSK modulation scheme and on–off‐keying (OOK) modulation scheme to estimate the maximum range that was used to recover an RGB transmitted image over an FSO link under different meteorological weathers. The obtained results clearly show that the quality of the received image has degraded significantly during transmission through free space yielding to limit the propagation range. Moreover, the proposed FSO communication system performs well when using QPSK modulation rather than OOK modulation in different environmental conditions. Thus, to improve the quality of the received image under adverse fog weather condition, high power and small beam divergence angle have been suggested to increase system's performance. The proposed solution increases the communication range of the FSO link by 230 m and 100 m for moderate and heavy fog, respectively.
Integrative physiological, transcriptome, and metabolome analyses reveal the associated genes and metabolites involved in cold stress response in common vetch (Vicia sativa L.)
Authors: Zhou Qiang , Cui Yue , Dong Shuwei , Luo Dong , Fang Longfa , Shi Zunji , Liu Wenxian , Wang Zengyu , Nan Zhibiao , Liu Zhipeng 
Published: June 2023

AbstractAs an economically important legume, Vicia sativa is commonly used as fodder for livestock and in health‐promoting foods for human consumption; however, cold stress is one of the most important limitations to its utilization at high altitudes. The shoot tissues of three cold‐resistant (Lan1, Lan2, and Lan3) and three cold‐sensitive (368, 521, and 538) accessions were collected after cold (4°C) treatment for 0, 6, and 48 h to assess their molecular regulatory mechanisms during cold stress via integrative analyses of their transcriptomes and metabolomes. Our Kyoto Encyclopedia of Genes and Genomes enrichment analysis showed that the biosynthesis of phenylpropanoids was the most enriched pathway in the cold stress response of V. sativa. A total of 18 differential metabolites were obtained in the biosynthesis of the phenylpropanoid pathway, and 722 differentially expressed genes (DEGs) showed a significant positive correlation with naringenin and p‐coumaric acid following a weighted gene co‐expression network analysis, while 84 DEGs showed significant negative associations. Moreover, four DEGs were overexpressed in yeast, and it was indicated that their biological function is to confer cold tolerance. These results provide a valuable resource for understanding the underlying molecular mechanism of V. sativa's response to cold stress and furthering the development of breeding research.
Preclinical study of pachyman inducing ferroptosis against ovarian cancer: Biological targets and underlying mechanisms
Authors: Li Bihui , Deng Yanyan , Lin Xuqiang , Wan Xiaowei , Liu Jiaqi 
Published: June 2023

AbstractFerroptosis has gained extreme purpose in targeting cancer treatment. Poria cocos Wolf, a traditional Chinese herb, has potential anticancer properties, but the action and mechanism against ovarian cancer remain undetailed. Pachyman (Poria cocos polysaccharides) refers to the pharmacologically bioactive ingredients rich in Poria cocos. This study aimed to identify the potent actions and the network mechanisms of pachyman against ovarian cancer through preclinical analysis. Online‐accessible database or platform was employed to predict candidate genes and core targets associated with ferroptosis in pachyman against ovarian cancer. Enrichment analyses were used to characterize the functional action and signaling mechanism in pachyman to treat ovarian cancer. Molecular docking imitation was conducted for verification of core target proteins. Network analysis uncovered that there were 30 mutual and 13 core genes targeting ferroptosis in pachyman and/against ovarian cancer, and additional enrichment analysis characterized that these core genes may act synergistically through multiple biological processes and molecular pathways associated with ferroptosis, including anti‐inflammatory action, immunoregulation, and microenvironment modulation. The strongest affinities in core target proteins between pachyman and sarcoma (SRC), signal transducer, and activator of transcription 3 (STAT3) were further validated using molecular docking method. In conclusion, pachyman may induce antiovarian cancer potentials via regulating ferroptosis‐associated biological functions and pharmacological mechanisms based on current bioinformatics findings. We reason that pachyman, the beneficial nutraceuticals, may be used clinically for future application in ovarian cancer treatment.
Central nervous system lymphomas—Assessment and treatment and prevention of central nervous system relapse
Authors: Ghione Paola , Lewis Katharine L. , Bobillo Sabela , Nayak Laksmi , Schorb Elisabeth , Nichelli Lucia , Ng Andrea , Savage Kerry J. , McKay Pam , Nastoupil Loretta , Soussain Carole , Cwynarski Kate 
Published: June 2023

AbstractIn this review focused on lymphoma and the central nervous system (CNS), we summarize recent developments in the management of primary (PCNSL) and secondary CNS lymphoma (SCNSL), treatment of CNS lymphoma in the older population, the neuroradiological assessment of CNS lymphoma and finally highlight the ongoing debate on optimal CNS prophylaxis. The section on PCNSL focuses on the different approaches available for frontline treatment in Europe and the United States and discusses consolidation strategies. We then highlight available strategies to treat PCNSL in the elderly population, an area of unmet need. New therapies aiming at minimizing toxicity and prioritizing quality of life are emerging for these patients. Secondary CNS lymphoma, especially in the relapsed/refractory setting is another area of unmet need, and the efficacy of CAR‐T cell therapy is being explored. We provide an overview of the imaging challenges in the neuroradiological assessment of CNS lymphoma. Finally, the section on CNS prophylaxis summarizes recent findings from large retrospective studies challenging the efficacy of present approaches to prophylaxis in higher‐risk patients with lymphoma.
Cellular therapy in lymphoma
Authors: Sureda Anna , Lugtenburg Pieternella J. , Kersten Marie José , Subklewe Marion , Spanjaart Anne , Shah Nirali N , Kerbauy Lucila N , Roddie Clarie , Pennings Elise R. A. , Mahuad Carolina , Poon Michelle , Hendricks Candice L , Kamdar Manali , Jacobson Caron 
Published: June 2023

AbstractCD19‐directed chimeric antigen receptor (CAR) T‐cell therapy has had a dramatic impact on the natural history and survival of patients with high‐risk B‐cell non‐Hodgkin lymphoma. Accompanying this success has been the development of new fields of medicine and investigation into toxicity risks and mitigation therapies, mechanisms of resistance and the development of novel and next generation products and strategies in order to address relapse, and issues related to global access and health care economics. This article is a survey of each of these areas as it pertains to the rapidly evolving field of CAR T‐cell therapy, written by an International community of lymphoma experts, who also happen to be women.
Experimental Investigation of an Oxidative C−C Coupling Reaction Catalyzed by HAuCl4
Authors: Krause Melanie T. S. , Schuppener Kim , Wegner Hermann A. , Engeser Marianne 
Published: June 2023

AbstractReaction monitoring by electrospray (ESI) mass spectrometry (MS) is a valuable technique to investigate reaction mechanisms. It allows a glimpse into the reacting solution and the characterization of transient intermediates by tandem mass spectrometry. Herein we studied an intriguing gold(III)‐catalyzed synthesis of dicoumarins which includes a combination of hydroarylation and homocoupling steps. Reactants and products could be detected in positive mode. In negative mode, some species corroborating proposed transient intermediates could be detected by direct infusion ESI of reacting solutions. The ions were characterized by accurate mass determinations and gas‐phase fragmentation. Thus, indications for the nature and ligand sphere of reaction intermediates in the catalytic cycle could be collected.
Lesion‐aware network for diabetic retinopathy diagnosis
Authors: Xia Xue , Zhan Kun , Fang Yuming , Jiang Wenhui , Shen Fei 
Published: June 2023

AbstractDeep learning brought boosts to auto diabetic retinopathy (DR) diagnosis, thus, greatly helping ophthalmologists for early disease detection, which contributes to preventing disease deterioration that may eventually lead to blindness. It has been proved that convolutional neural network (CNN)‐aided lesion identifying or segmentation benefits auto DR screening. The key to fine‐grained lesion tasks mainly lies in: (1) extracting features being both sensitive to tiny lesions and robust against DR‐irrelevant interference, and (2) exploiting and re‐using encoded information to restore lesion locations under extremely imbalanced data distribution. To this end, we propose a CNN‐based DR diagnosis network with attention mechanism involved, termed lesion‐aware network, to better capture lesion information from imbalanced data. Specifically, we design the lesion‐aware module (LAM) to capture noise‐like lesion areas across deeper layers, and the feature‐preserve module (FPM) to assist shallow‐to‐deep feature fusion. Afterward, the proposed lesion‐aware network (LANet) is constructed by embedding the LAM and FPM into the CNN decoders for DR‐related information utilization. The proposed LANet is then further extended to a DR screening network by adding a classification layer. Through experiments on three public fundus datasets with pixel‐level annotations, our method outperforms the mainstream methods with an area under curve of 0.967 in DR screening, and increases the overall average precision by 7.6%, 2.1%, and 1.2% in lesion segmentation on three datasets. Besides, the ablation study validates the effectiveness of the proposed sub‐modules.
Accurate and fast extraction of adhesive cells based on concave points detection and matching
Authors: Liang Dan , Pi Yang‐Jun , Hu Kai , Cui Yu‐Guo , Huang Ye , Liang Dong‐Tai , Feng Shi‐Liang 
Published: June 2023

AbstractPrecise image segmentation of adhesive cells is a challenge during the cell detection process for biomedical image analyses. In this article, a new segmentation and extraction method for adhesive cells based on concave points detection and matching is proposed. First, image preprocessing is used to reduce interference information, which mainly includes sequential gray scale transformation, binarization, hole filling, adhesive cells recognition, and median filtering process. Second, an improved concave detection algorithm is presented which can reduce the interfering feature points and detect the concave points on the adhesive cells accurately. Third, precise extraction of adhesive cell contour is realized by concave matching based on ellipse fitting. Experiments of blood cell sample detection show that the average accuracy is 97.18% with a costing time of 3.36 s. The proposed method can effectively reduce the interference of multiple concave points and extract the cell contour from adhesive regions with higher accuracy and less time, which shows great application potential in the field of biological image detection and analyses.
Sports health information prediction system based on deep learning network
Authors: Liu Juan , Wang Shan 
Published: June 2023

AbstractThis paper adopts the deep network model constructed the results of the training are used to explore the detection of sports, and to verify the deep learning network model from the perspective of reliability and feasibility. The experimental results in this paper show that the comprehensive performance evaluation index FM increased by 2.6%, Pr increased by 0.7%, and Re increased by 4.4%. Therefore, the deep residual network structure used in the DRNTL method proposed in this paper can effectively improve the generalization ability of the network. Through the learning of a large amount of labeled data, the model can be applied to the detection of other untrained complex scenes. The engineering of the moving target detection method is of great significance.
Recurrent and convolutional neural networks for sequential multispectral optoacoustic tomography (MSOT) imaging
Authors: Juhong Aniwat , Li Bo , Liu Yifan , Yao Cheng‐You , Yang Chia‐Wei , Agnew Dalen W. , Lei Yu Leo , Luker Gary D. , Bumpers Harvey , Huang Xuefei , Piyawattanametha Wibool , Qiu Zhen 
Published: June 2023

AbstractMultispectral optoacoustic tomography (MSOT) is a beneficial technique for diagnosing and analyzing biological samples since it provides meticulous details in anatomy and physiology. However, acquiring high through‐plane resolution volumetric MSOT is time‐consuming. Here, we propose a deep learning model based on hybrid recurrent and convolutional neural networks to generate sequential cross‐sectional images for an MSOT system. This system provides three modalities (MSOT, ultrasound, and optoacoustic imaging of a specific exogenous contrast agent) in a single scan. This study used ICG‐conjugated nanoworms particles (NWs‐ICG) as the contrast agent. Instead of acquiring seven images with a step size of 0.1 mm, we can receive two images with a step size of 0.6 mm as input for the proposed deep learning model. The deep learning model can generate five other images with a step size of 0.1 mm between these two input images meaning we can reduce acquisition time by approximately 71%.
Substituent effect on photophysical properties and proton transfer process of HBQ derivatives
Authors: Song Yao‐Dong , Wang Qian‐Ting , Pan Jia 
Published: June 2023

AbstractBackgroundIn view of the potential applications of 10‐hydroxybenzo [h] quinoline (HBQ) in biological probes and organic light‐emission devices, the excited state intramolecular proton transfer (ESIPT) mechanism of HBQ was investigated theoretically in the work.AimsIn order to give a detailed reaction mechanism, the ESIPT of molecular system with hydrogen bond is systematically studied using density functional theory and density functional theoryMethodsUsing density functional theory (DFT) and time‐dependent density functional theory (TDDFT), we investigate the photophysical properties and excited state proton transfer of 10‐hydroxybenzo [h] quinoline (HBQ)derivatives.ResultsThe optimized structure shows that HBQ1 and HBQ2 have no stable structure in S1 state. The analysis of bond length parameters and infrared vibration spectroscopy proved that the substituent groups regulated the hydrogen bond strength in the S0 state.ConclusionTherefore, substitution position will affect the excited state intramolecular proton transfer and the photophysical properties of the molecule.
Physical training promotes remodeling of the skeletal muscle extracellular matrix: An ultrastructural study in a murine model of Down syndrome
Authors: Cisterna Barbara , Boschi Federico , Lacavalla Maria Assunta , Vattemi Gaetano Nicola Alfio , Zancanaro Carlo , Malatesta Manuela 
Published: June 2023

AbstractDown syndrome (DS) is a genetically based disease caused by triplication of chromosome 21. DS is characterized by multi‐systemic premature aging associated with deficit in motor coordination, balance, and postural control. Using a morphological, morphometrical, and immunocytochemical ultrastructural approach, this study investigated in vastus lateralis muscle of Ts65Dn mouse, a murine model of DS, the effect of an adapted physical training on the extracellular matrix (ECM) characteristics and whether the forecasted exercise‐induced ECM remodeling impacts on sarcomere organization. Morphometry demonstrated thicker basement membrane and larger collagen bundles with larger interfibrillar spacing as well as irregularly arrayed myofibrils and lower telethonin density on Z‐lines in trisomic versus euploid sedentary mice. In agreement with the multi‐systemic premature aging described in DS, these ECM alterations were similar to those previously observed in skeletal muscle of aged mice. Adapted physical training induced remodeling of ECM in both trisomic and euploid mice, that is, enlargement of the collagen bundles associated with hypertrophy of collagen fibrils and reduction of the interfibrillar spacing. A re‐alignment of the myofibrils and a higher telethonin density on Z‐line was found in trisomic mice. Altogether, our findings suggest that physical training is an effective tool in limiting/counteracting the trisomy‐associated musculoskeletal structural anomalies. The current findings constitute a solid experimental background for further study investigating the possible positive effect of physical training on skeletal muscle performance.Research Highlights
Vastus lateralis muscle of trisomic mice shows aging‐like alterations of extracellular matrix.
Training promotes extracellular matrix remodeling.
Training may be an effective tool to counteract trisomy‐associated alterations of skeletal muscle.
Evaluation of type 1 diabetes mellitus as a risk factor of Parkinson's disease in a Drosophila model
Authors: Sanz Francisco José , Martínez‐Carrión Guillermo , Solana‐Manrique Cristina , Paricio Nuria 
Published: June 2023

AbstractDiabetes mellitus (DM) is a chronic metabolic disease characterized by high blood glucose levels, resulting from insulin dysregulation. Parkinson's disease (PD) is the most common neurodegenerative motor disorder caused by the selective loss of dopaminergic (DA) neurons in the substantia nigra pars compacta. DM and PD are both age‐associated diseases that are turning into epidemics worldwide. Previous studies have indicated that type 2 DM might be a risk factor of developing PD. However, scarce information about the link between type 1 DM (T1DM) and PD does exist. In this work, we have generated a Drosophila model of T1DM based on insulin deficiency to evaluate if T1DM could be a risk factor to trigger PD onset. As expected, model flies exhibited T1DM‐related phenotypes such as insulin deficiency, increased content of carbohydrates and glycogen, and reduced activity of insulin signaling. Interestingly, our results also demonstrated that T1DM model flies presented locomotor defects as well as reduced levels of tyrosine hydroxylase (a marker of DA neurons) in brains, which are typical PD‐related phenotypes. In addition, T1DM model flies showed elevated oxidative stress levels, which could be causative of DA neurodegeneration. Therefore, our results indicate that T1DM might be a risk factor of developing PD, and encourage further studies to shed light into the exact link between both diseases.
Transmitting affective job insecurity (AJI) within teams: Layoff effects of AJI convergence on intrateam power struggles and team outcomes
Authors: Lam Wing , Chen Ziguang , Wu Wen , Lee Cynthia 
Published: June 2023

SummaryExtant research on job insecurity (JI) largely focuses on the individual level, rather than considering the process of JI at collective, team levels. But employees' worries and anxiety about potential job losses create affective job insecurity (AJI), which can converge over time in teams, especially following dramatic changes such as layoffs. Drawing on a multilevel theory of emergence in teams and uncertainty reduction theory, this study offers theoretical predictions of AJI convergence, as well as its potential influences on team functioning and outcomes. A four‐wave, post‐layoff survey of 468 employees and 91 supervisors confirms two major predictions. First, AJI convergence exists within teams over time, as established by a consensus emergence model. Second, teams with members who converge at a high level of AJI experience intrateam power struggles that impair both team performance and team proactivity. By theorizing about the phenomenon of AJI convergence, this study not only expands the notion of JI from the individual to the team level, noting its harmful effects on teams, but also highlights the need for both team members and team leaders to pay close attention to such convergence and its potentially detrimental effects following layoffs.