Economic convergence of Balkan regions towards EU by María A. González-Álvarez, Antonio Montañés, Esther Ruiz, Skender Uku

“…We also categorize groups of economies sharing similar divergence patterns. Additionally, among the regions that converge, convergence rates vary, with some regions progressing faster (Bulgaria, Montenegro and North Macedonia). …”
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Smart Cities and Affective-Symbolic Urbanism: A Dual Tourist/Resident Perspective by Nikolaos Iason Koufodontis, Eleni Gaki, Stella Zounta

“…A quantitative analysis of 194 respondents reveals that while adoption rates are similar across roles, residents and tourists differ in usage routines, usability experiences, and sensitivity to symbolic cues. …”
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Anhedonia: Current and future treatments by Alessandro Serretti

“…Abstract Anhedonia is a transdiagnostic domain that leads to poor disorder outcome and low remission rates. This narrative review describes a broad range of interventions targeting anhedonia, including pharmacological, neuromodulatory, behavioral, and lifestyle‐based approaches. …”
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The Demographic Challenge Analyzed Through Ageing Indices in Extremadura and Andalusia (Spain) with Cluster Mapping Tools by José-Manuel Sánchez-Martín, José-Luis Gurría-Gascón, Juan-Ignacio Rengifo-Gallego

“…Based on the observation of growing demographic pressure associated with low birth rates and emigration to more economically dynamic areas, a methodological approach based on spatial analysis techniques is proposed. …”
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Detecting network intrusions in cyber-physical systems using deep autoencoder-based dimensionality reduction approach anddeep neural networks by A. E. Ibor, D. O. Egete, A. O. Otiko, D. U. Ashishie

“…The model is trained and tested on CICIDS2017 and UNSW-NB15 datasets with a rich collection of attack patterns such as DoS, DDoS, Shellcode, and Worm attacks. …”
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Advanced cloud intrusion detection framework using graph based features transformers and contrastive learning by Vijay Govindarajan, Junaid Hussain Muzamal

“…The model achieves low false-positive rates and demonstrates real-time inference performance with modest resource requirements. …”
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Adaptation to sustainable energy use: A case study on agricultural cooperatives by Mustafa Yıldırım, Bengü Everest

“… Energy use rates are continuously increasing with increasing populations. …”
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Quantitative Assessment of Regional Carbon Neutrality Policy Synergies Based on Deep Learning by Daiyang Zhang, Enmiao Feng

“…The deep learning model achieves robust prediction accuracy across diverse scenarios, with sensitivity analysis revealing technology learning rates as the most significant parameter influencing predictions (±24.3%). …”
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An exploration of modeling approaches for capturing seasonal transmission in stochastic epidemic models by Mahmudul Bari Hridoy

“…Seasonal variations in the incidence of infectious diseases are a well-established phenomenon, driven by factors such as climate changes, social behaviors, and ecological interactions that influence host susceptibility and transmission rates. While seasonality plays a significant role in shaping epidemiological dynamics, it is often overlooked in both empirical and theoretical studies. …”
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The influence of crosslink characteristics on key properties of dynamically cured NR/PP blends by Charoen Nakason, Chanida Manleh, Natinee Lopattananon, Azizon Kaesaman

“…Curing systems caused crosslinking rates, reversion, and crosslink density and distribution variations. …”
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Integrating Reinforcement Learning into M/M/1/K Retry Queueing Models for 6G Applications by Djamila Talbi, Zoltan Gal

“…The system’s performance is examined under extensive simulations, taking into account multiple arrival rates, queue sizes, and reward scaling factors. The results show that the integration of RL in the 6G-RQS model successfully enhances queue management while maintaining the high performance of the system, and this is by increasing the number of mobile terminals served, even under different and higher traffic demands. …”
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Space–Time Dynamics of Mortality and Recruitment of Stems and Trees in a Seasonally Dry Tropical Forest: Effect of the 2012–2021 Droughts by Maria Beatriz Ferreira, Rinaldo Luiz Caraciolo Ferreira, Jose Antonio Aleixo da Silva, Robson Borges de Lima, Alex Nascimento de Sousa, Marcos Vinícius da Silva

“…An accumulative effect of droughts on increasing mortality rates and reducing recruitment during the study period was observed. …”
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Impact of plant-based diets and associations with health, lifestyle and healthcare utilisation: a population-based survey study by Natalia Echiburu, Maria Antonieta Also-Fontanet, Antoni Sisó-Almirall, Luis González-de Paz

“…Design: We estimated vegetarian and vegan individuals’ national and regional prevalence and analysed their socio-demographic characteristics and weekly dietary intake patterns. Individuals with a plant-based dietary pattern were matched to a control group (1:4) with similar socio-demographic characteristics. …”
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Radiologic Predictors of Disease Recurrence in Nasopharyngeal Carcinoma: A Retrospective Evaluation of MRI and ¹⁸F-FDG-PET/CT Parameters by Banu Karaalioğlu, Tansel Çakır, Ömer Yazıcı, Mustafa S. Tekin, Ebru Karcı

“…<b>Background/Objectives:</b> NPC is a radiosensitive malignancy with high recurrence rates despite therapeutic advances. This study aimed to identify radiologic and metabolic predictors of recurrence in newly diagnosed NPC by integrating MRI and ¹⁸F-FDG PET/CT parameters. …”
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The Use of AI-Powered Thermography to Detect Early Plantar Thermal Abnormalities in Patients With Diabetes: Cross-Sectional Observational Study by Meshari F Alwashmi, Mustafa Alghali, AlAnoud AlMogbel, Abdullah Abdulaziz Alwabel, Abdulaziz S Alhomod, Ibrahim Almaghlouth, Mohamad-Hani Temsah, Amr Jamal

“…Traditional DFU detection methods face scalability issues due to inefficiencies in time and practical application, leading to high recurrence and amputation rates alongside substantial health care costs. Human medical thermography could significantly enhance disease monitoring and detection, including DFUs. …”
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Non-temperature environmental drivers modulate warming-induced 21st-century permafrost degradation on the Tibetan Plateau by Fu Ziteng, Wu Qingbai, Chen Anping, Wang Luyang, Jiang Guanli, Gao Siru, Yun Hanbo, Chen ji

“…By compiling a 20-year (2001–2020) dataset from 55 in situ monitoring sites, we find permafrost thawing rates increased from 45 ± 15 cm·10a− 1 (2001–2010) to 86 ± 30 cm·10a−1 (2011-2020), while the temperature increasing rates at the top of permafrost rose from 0.15 ± 0.16 oC·10a−1 to 0.38 ± 0.22 oC·10a−1. …”
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Diffusion and Risks of House Prices in the Netherlands by Alfred Larm Teye

“… The rate of home-ownership has increased significantly in many countries over the past decades. …”
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Impact of COVID-19 on Ureteroscopy Management of Urolithiasis: Retrospective Comparative Study Before and After Pandemic by Shota Iijima, Takanobu Utsumi, Naoki Ishitsuka, Takahide Noro, Yuta Suzuki, Yuka Sugizaki, Takatoshi Somoto, Ryo Oka, Takumi Endo, Naoto Kamiya, Hiroyoshi Suzuki

“…Referral sources shifted (<i>p</i> = 0.045), with fewer primary care referrals and more from emergency or higher-level hospitals. Stone-free rates (65.6% vs. 58.7%, <i>p</i> = 0.128) and postoperative complication rates were comparable. …”
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Missed opportunities in early psychosis care: retrospective chart review of cardiovascular disease monitoring, disengagement and weight changes in a Ghanaian psychiatric hospital by Joel Agorinya, Emelda Edem Adzo Asem-Ahiablee, Emefa Adzo Dzordzorme, Jude Nazir Ayambila, Elsie Agyeman Amaning, Chukwuebuka Ohakpougwu, Abdulai Rafiq Arhin, Kwadwo Marfo Obeng, Belinda Lennox

“…Outcomes included antipsychotic prescription patterns, dropout rates, cardiovascular disease monitoring and weight changes. …”
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Potential suitable area prediction of invasive weeds Tithonia diversifolia A. Gray and Synedrella nodiflora L. Gaertn. in China based on the optimized MaxEnt model by Jing XIE, Nishan DUAN, Lijie KONG, Ruiyi XU, Ruoyu AN, Lijuan ZHOU

“…ResultThe standard deviation of temperature seasonal change and the average temperature in the coldest quarter were the main environmental variables affecting the distribution of T. diversifolia, and the sum of their contribution rates reached 70.8%. The range of annual average temperature change, annual average precipitation and precipitation in the wettest month were the main environmental variables affecting the distribution of S. nodiflora, with the sum of their contribution rates reaching 76.7%. …”
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