Mastering Everyday Life in Ordinary Housing for People with Psychiatric Disabilities by Rosita Brolin, David Brunt, Mikael Rask, Susanne Syrén, Anna Sandgren

“…Mastering everyday life can be seen as a process, which involves identifying, organizing, tackling, challenging and boosting. …”
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CHALLENGES OF THE LAND REFORM IN THE FORMER COMMUNIST STATES OF CENTRAL AND EASTERN EUROPE by ANDREEA DRAGOI, CRISTINA BALGAR

“…One of the most important was the large-scale abandonment of state ownership in the agricultural sector, a transformation that was essential for boosting economic development. Our article aims to present the land property privatization process in the former communist countries of Central and Eastern Europe, pointing out the obstacles which hindered this action and represented barriers of the reform process. …”
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Ultralow-threshold upconversion infrared vision via a microsphere-mediated directional photofield by Dong Wang, Qikuan Cheng, Weibang Xia, Yongyao Tan, Kexuan Yu, Lu Zhang, Guigang Li, Rong Liu, Wei Wang, Linjuan Xu, Suli Wu, Yang Liu, Yunming Wang, Huamin Zhou

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ATP6AP1 drives pyroptosis-mediated immune evasion in hepatocellular carcinoma: a machine learning-guided therapeutic target by Lei Tang, Xiyue Wang, Zhengzheng Xia, Jiayu Yan, Shanshan Lin

“…Multiple machine learning techniques, including GBM (gradient boosting machine), XGBoost (extreme gradient boosting machine), SVM (support vector machine), LASSO (least absolute shrinkage and selection operator) and random forest, as well as functional analysis, were used to systematically investigate the role of ATP6AP1 in HCC. …”
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Optimizing High-Al₂O₃ Limonite Pellet Performance: The Critical Role of Basicity in Consolidation and Reduction by Yufeng Guo, Yixi Zhang, Feng Chen, Shuai Wang, Lingzhi Yang, Yanqin Xie, Xinyao Xia

“…During the reduction process, pellets with high basicity exhibited superior reduction performance.…”
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Assistance in Obtaining Halal Certification (Self-Declaration) for Sweet Hony Canteen at Mulawarman University by Lalu Aditya Sumadi, Panggulu Ahmad Ramadhani Utoro, Agustu Sholeh Pujokaroni, Yulian Andriyani, Maghfirotin Marta Banin, Hadi Suprapto, Miftakhur Rohmah

“…The effort led to the issuance of a Business Identification Number (BIN) and an ongoing halal certification process.…”
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Dual-omics strategy for selecting optimal fermentation strains in traditional koumiss production by Xiaoyan Wang, Zhixin Zhao, Feiyan Zhao, Yu Li, Yinsuo Liang, Runzhi Zhou, Shijia Shen, Jie Yu, Wenjun Liu, Bilige Menghe

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Significance of α-Al cellular matrix in tensile behavior and work-hardening of additive manufactured AlSi10Mg alloy by Shuoqing Shi, Yufan Zhao, Xin Lin, Haoyuan Deng, Lv Zhao, Guangyao He, Weidong Huang

“…The significance revealed in this work is expected to be also applicable to other alloys that commonly have cellular structures in AM process.…”
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Diffusion-Improved Recrystallization of Ammonia Doping to Enhancing the Optoelectronic and Thermoelectric Effects of Multi-Junction Carbon Nanotube Paper Diodes by Jih-Hsin Liu, Cheng-Jhe Yen

“…N-type CNTs are synthesized through ammonia doping and combined with intrinsic P-type CNTs to create PN multi-junction “buckypaper”. Post-diffusion processes improve junction crystallinity and doping gradients, significantly boosting the rectification ratio and optoelectronic and thermoelectric response. …”
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Fault detection and diagnosis method for heterogeneous wireless network based on GAN by Xiaorong ZHU, Peipei ZHANG

“…Aiming at the problem that in the process of network fault detection and diagnosis,how to train the precise fault diagnosis and detection model based on small data volume,a fault diagnosis and detection algorithm based on generative adversarial networks (GAN) for heterogeneous wireless networks was proposed.Firstly,the common network fault sources in heterogeneous wireless network environment was analyzed,and a large number of reliable data sets was obtained based on a small amount of network fault samples through GAN algorithm.Then,the extreme gradient boosting (XGBoost) algorithm was used to select the optimal feature combination of input parameters in the fault detection stage and completed fault diagnosis and detection based on these data.Simulation results show that the algorithm can achieve more accurate and efficient fault detection and diagnosis for heterogeneous wireless networks,with an accuracy of 98.18%.…”
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Structural biology meets typography: using protein structures to inspire creative expression and connect diverse audiences by Leonora Martínez-Núñez

“…Using ChimeraX, Blender and Molecular Nodes, 3D molecular models were processed, stylized, and shared on social media under the #36daysoftype hashtag, which led to engagement across a diverse audience. …”
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METHODS OF ENRICHING KNOWLEDGE. HOW DO THEY INFLUENCE THE EMPLOYEES’ ACTIVITY? by Teodora PÎRȘOI (NEBUNU-PÎRȘOI)

“…In order to emphasize this particular resource's importance and contribution to the process of boosting organizational activity, our scientific effort aims to establish and analyze the employees' perceptions of some proposed knowledge developing methods, as well as regarding some internal/external aspects that could influence the managerial model implementation within military institutions. …”

Optimizing XGBoost Hyperparameters for Credit Scoring Classification Using Weighted Cognitive Avoidance Particle Swarm by Atul Vikas Lakra, Sudarson Jena, Kaushik Mishra

“…Manually setting these hyperparameters can be a time-consuming process. Therefore, to automate this process, weighted cognitive avoidance particle swarm optimization (WCAPSO) is employed for hyperparameter optimization. …”
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Machine learning-based radiomics for differentiating lung cancer subtypes in brain metastases using CE-T1WI by Xueming Xia, Wei Du, Qiheng Gou

“…Ten machine learning models, including Light Gradient Boosting Machine (LightGBM), RandomForest, and eXtreme Gradient Boosting (XGBoost), were built using selected features. …”
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Improving SMART learning: Course completion via AI-driven hybrid system integration in big data by Abdellah Bakhouyi, Amine Dehbi, Lahcen Amhaimar, Said Broumi, Mohamed Talea, Abderrahim Khalidi

“…Integrating artificial intelligence in hybrid systems for big data management and processing is highly pertinent within smart-learning. …”
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Prediction of Pyrolysis Kinetics of Biomass: New Insights from Artificial Intelligence-Based Modeling by Lei Dong, RanRan Wang, PeiDe Liu, Saeed Sarvazizi

“…The present work introduces a quantitative structure-property relationship (QSPR)-based stochastic gradient boosting (SGB) decision tree framework for simulating and capturing of the thermal decomposition kinetics of biomass considering effective parameters of the ultimate analysis (such as carbon, hydrogen, oxygen, nitrogen, and sulfur content) and process heating rate. …”
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FOREIGN TRADE OF THE REPUBLIC OF MOLDOVA: DEVELOPMENTS, TRENDS, PROSPECTS by Diana BRAGOI

“…European integration has positively influenced Moldova's trade, redirecting it towards the EU markets and boosting part of the economy towards modernization. …”
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Static power model for CMOS and FPGA circuits by Anas Razzaq, Andy Ye

“…Abstract In Ultra‐Low‐Power (ULP) applications, power consumption is a key parameter for process independent architectural level design decisions. …”
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Transformational Leadership, Organizational Resilience, and Team Innovation Performance: A Model for Testing Moderation and Mediation Effects by Jiayu Yu, Kaibiao Xiang

“…This relationship is more significant when environmental uncertainty is considered as a moderator in the mediation process. Ultimately, based on the findings illustrated above, this study provides suggestions to improve team innovation performance by developing transformational leadership capabilities and awareness, enhancing the business environment, boosting organizational resilience, and increasing the resilience of enterprises in the context of environmental uncertainty. …”
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Machine learning assisted design and preparation of Fe85Si2B8.5P3.5C1 amorphous/nanocrystalline alloy with high Bs and low Hc by Shengdong Tang, Rui Sun, Yifan He, Guichang Liu, Ruixuan Wang, Yuqin Liu, Chengying Tang

“…Four machine learning (ML) models including eXtreme Gradient boosting (XGBT), k-Nearest Neighbor (kNN), Gradient Boosting Decision Tree (GBDT) and Artificial Neural Network (ANN) were employed to predict saturation flux density (Bs), coercivity (Hc), grain size, magnetostriction (λ), and Curie temperature (Tc) of Fe-based amorphous/nanocrystalline alloys. …”
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