Polygenic diseases by Sergey Dolomatov, Walery Zukow, Anna Zhukova, Svetlana Smirnova

“…For type 2 diabetes, over 600 candidate genes have been identified. In preeclampsia, multiple genes influence maternal-fetal interactions and vascular function. …”
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Soil Respiration Variations in Temperate Rhododendron (Rhododendron arboreum) Forest of Annapurna Conservation Area (ACA) in Nepal by Deepa Dhital, Purushottam Manandhar, Bikash Gosain, Jaishree Sijapati

“…We evaluated the consequences of multiple ecological parameters mainly climatic and biotic factors on SR variations during the month of October in 2016 and 2017. …”
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Factores de entorno determinantes del emprendimiento en México by Miguel Angel García-Macias, Mariana Zerón-Félix, Yesenia Sánchez-Tovar

“…Posteriormente usando un análisis de regresión múltiple se observó que el acceso al financiamiento y el marco regulatorio son los factores que impactan de forma significativa en la apertura de empresas en México. …”
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Ditched and walled enclosures in Prehistoric Iberia (4th-3rd millennia cal. BCE): Like oil and water by Víctor Jiménez-Jáimez, Marcos García-García, Adara López-López, David W. Wheatley

“…This paper will address this problem from a Pan-Iberian perspective, as we will compare type-sites across multiple Iberian regions. We shall formulate and test seven relevant hypotheses by undertaking multiple comparative analyses at various scales on top of a purpose-built database including 345 sites. …”
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Triple-drug antibiotic therapy for disseminated nocardial abscess in the mediastinum and brain of an immunocompetent patient: a case report by Yue Zhang, Zhongchun Qi, Hua Li, Hui Gao

“…A chest-enhanced computed tomography (CT) revealed multiple enhanced nodulars in the bilateral hilum and mediastinum. …”
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New hash function based on C-MD structure and chaotic neural network by Liquan CHEN, Yuhang ZHU, Yu WANG, Zhongyuan QIN, Yang MA

“…In recent years, widely used hash algorithms such as MD5 and SHA-1 have been found to have varying degrees of security risks.The iterative structure of the SHA-2 algorithm is similar to that of SHA-1, making it vulnerable to attacks as well.Meanwhile, SHA-3 has a complex internal structure and low implementation efficiency.To address these issues, a keyed hash function was designed and implemented based on chaotic neural network and C-MD structure.The approach involved improving the Merkle-Damgard structure by proposing the chaotic neural network Merkle-Damgard (C-MD) structure.This structure can be used to design a hash function that can withstand attacks such as the middle attack, multiple collision attack, and second pre-image attack for long information.Besides, the chaotic neural network was used as the compression function to increase the complexity of the hash function and improve its collision resistance, while also enabling it to output multiple lengths.Moreover, a plaintext preprocessor was designed, which used the coupled image lattice to generate chaos sequence related to the length of the plaintext to fill the plaintext, thus enhancing the ability of the hash function to resist length expansion attacks.Simulation results demonstrate that the proposed hash function performs faster than SHA-2, SHA-3 and the same type of chaotic hash function proposed by Teh et al.It can resist second pre-image attack, multi-collision attack and differential attack, while also exhibiting better collision resistance and mapping uniformity.In addition, the proposed Hash function can output Hash values of different lengths, making it suitable for use in digital signature, key generation, Hash-based message authentication code, deterministic random bit generator, and other application fields.…”
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Scenario-aware access control model by Dibin SHAN, Xuehui DU, Wenjuan WANG, Na WANG, Aodi LIU

“…Dynamic access control model is the theoretical basis for constructing a dynamic access control system for big data.However, most existing access control models can only fulfill dynamic access control in a single scenario and are unable to adapt to access control in multiple types of dynamic scenarios.These scenarios include changes in the contextual environment of big data, changes in entity relationships, and changes in the state of objects.To address these issues, an analysis was conducted based on the research of existing access control models and the dynamic factors of big data.Subsequently, scenario-aware access control (SAAC) model was proposed, which was based on dynamic factor conversion and scenario unified modeling.All types of dynamic factors were converted into basic elements such as attributes and relationships.Then, scene information was incorporated to model the various types of constituent elements in a unified manner.A big data dynamic access control model was constructed based on scene information to support multi-type dynamic factors and extended dynamic factors.The working framework of the SAAC model was designed, and the SAAC rule learning algorithm and SAAC rule execution algorithm were proposed corresponding to the workflow of the framework.This enabled the automatic learning of access control rules and dynamic access control decision-making.The security of the proposed model was analyzed and verified by introducing the non-transitive non-interference theory.To validate the effectiveness of the access control policy mining method of the proposed model, experimental comparisons were conducted between the SAAC model and baseline models such as ABAC-L, PBAC-X, DTRM, and FB-CAAC using four datasets.The experimental results demonstrate that the SAAC model and its strategy mining method outperforms the baseline models in terms of metrics such as area under the curve AUC, monotonicity, and steepness of the ROC curve.This verification confirms that the proposed model can support multiple types of dynamic factors and dynamic factor extensions, and that the combined effect of the access control rules obtained from its mining algorithm is relatively high.…”
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Plasma C1q/TNF-Related Protein-3 (CTRP-3) and High-Mobility Group Box-1 (HMGB-1) Concentrations in Subjects with Prediabetes and Type 2 Diabetes by Huili Wei, Hua Qu, Hang Wang, Huacong Deng

“…Further multiple logistical regression analyses revealed that both plasma CTRP-3 and HMGB-1 levels were significantly associated with pre-DM and nT2DM after adjusting for several confounders (P<0.001 for all). …”
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Improving The Performance of Big Data Databases by Nzar Abdulqadir Ali, Dashne Raouf Arif

“…In SQL (Structured Query Language) databases different algorithms are used for inserting and updating data, such as indexing, bulk insert and multiple updating. However, in NoSQL different algorithms are used for inserting and updating operations such as default-indexing, batch insert, multiple updating and pipeline aggregation. …”
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Biosecurity Practices for Reducing Antimicrobial Use in Commercial Broiler Farms in Korea by Min Beom Kim, Young Ju Lee

“…However, its relationship with antimicrobial usage can be difficult to assess because of multiple factors. This study evaluated the impact of biosecurity practices on productivity, frequency of antimicrobial use, and development of antimicrobial resistance. …”
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Desmoplastic Small Round Cell Tumor of the Abdomen and Pelvis: Clinicopathological Characters of 12 Cases by Guangzhao Zhang, Guangjun Liu, Dahua Zhao, Xijun Cui, Gang Li

“…The other 6 cases were diagnosed by fine needle aspiration or exploratory laparotomy biopsy (group 2, 6/12, 50%); all cases received four to six courses of multiple agents chemotherapy, respectively. Results. …”
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A Comprehensive Investigation of Anomaly Detection Methods in Deep Learning and Machine Learning: 2019–2023 by Shalini Kumari, Chander Prabha, Asif Karim, Md. Mehedi Hassan, Sami Azam

“…Many researchers have proposed numerous methods and worked in the area of AD. Multiple anomalies and considerable intraclass variation make industrial datasets tough. …”
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A Case of Neuromyelitis Optica: Puerto Rican Woman with an Increased Time Lag to Diagnosis and a High Response to Eculizumab Therapy by Ramón Vega, Benjamín González, Kiara Ortiz, Viviana Martínez, David Carmona, Ivonne Vicente, Javier Chapa, Ángel Chinea

“…This case illustrates the efficacy of eculizumab therapy and the importance of differentiating the clinical, histopathological, and neuroimaging characteristics that separate demyelinating autoimmune inflammatory disorders, such as NMOSD and multiple sclerosis (MS).…”
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Balancing Progress and Preservation: The Complex Interplay of Economic Growth and Forest Conservation in Nepal’s Carbon Dioxide Emissions by Omkar Poudel, Pradeep Acharya, Sarad Chandra Kafle, Basanta Prasad Adhikari

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Network Graph Analysis of Gene-Gene Interactions in Genome-Wide Association Study Data by Sungyoung Lee, Min-Seok Kwon, Taesung Park

“…Most common complex traits, such as obesity, hypertension, diabetes, and cancers, are known to be associated with multiple genes, environmental factors, and their epistasis. …”
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Short-term Optimal Scheduling Model for Hydropower Stations Considering Peak Shaving of Local and HVDC Receiving Power Grids by ZHOU Binbin, ZHANG Congtong, LIU Benxi, CHENG Chuntian, CHEN Kai, WANG Youxiang

“…In the face of the increasingly severe peak shaving pressure on both sending and receiving power grids of the high voltage direct current (HVDC) of large-scale hydropower stations,a short-term optimal scheduling model that takes into account peak shaving of local and HVDC receiving power grids of the cascade hydropower stations has been established.The model aims to minimize the maximum value of residual load in multiple power grids,not only considering the conventional hydraulic and power constraints of the cascade hydropower stations and the complex operation constraints of the HVDC transmission lines but also introducing coupled operation constraints between the HVDC transmission line and the hydropower stations.In the model-solving phase,the original model is transformed into a mixed-integer linear programming model by introducing auxiliary variables to linearize the objective function,hydraulic operation constraints,and HVDC operation constraints and using the big M method to linearize the bi-directional interval coupled constraints between the HVDC transmission line and the hydropower stations.Typical winter and summer days in a large-scale hydropower system in southwestern China are taken as examples,and the results show that the peak-valley difference of the sending power grid has decreased by up to 100%,while the decrease in the peak-valley difference in the receiving end power grid is 28.1% and 31.6%,respectively.It shows that the proposed model can share the flexibility of hydropower through HVDC transmission lines,achieve peak shaving in multiple power grids,and ensure safe operation of the HVDC transmission lines,which can provide a reference for short-term multi-grid peak shaving of large-scale cascade hydropower stations.…”
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ProNDN: MCDM-Based Interest Forwarding and Cooperative Data Caching for Named Data Networking by Cong Pu

“…However, the conventional stateful forwarding approach is not adaptive and responsive to diverse network conditions because it fails to consider multiple network metrics to make Interest forwarding decision. …”
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Fault localization for automatic train operation based on the adaptive error locating array algorithm by Yanpeng Zhang, Yuxiang Cao

“…Compared to four mainstream adaptive algorithms of fault localization, the proposed algorithm is less affected by the masking effects caused by multiple faults and requires the fewest number of test cases. …”
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Zero-TCE: Zero Reference Tri-Curve Enhancement for Low-Light Images by Chengkang Yu, Guangliang Han, Mengyang Pan, Xiaotian Wu, Anping Deng

“…We compare our proposed method against ten other advanced algorithms based on multiple datasets, including LOL, DICM, MEF, NPE, and ExDark, that encompass complex illumination variations. …”
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Stability Analysis of Batch Offline Action-Dependent Heuristic Dynamic Programming Using Deep Neural Networks by Timotei Lala

“…We present a practical implementation involving a twin rotor aerodynamical system to emphasize the impact difference between the usage of single-hidden-layer and multiple-hidden-layer NN architectures in BOADHDP learning settings. …”
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