Autonomous Detection of Mineral Phases in a Rock Sample Using a Space-prototype LIMS Instrument and Unsupervised Machine Learning by Salome Gruchola, Peter Keresztes Schmidt, Marek Tulej, Andreas Riedo, Klaus Mezger, Peter Wurz

“…In situ mineralogical and chemical analyses of rock samples using a space-prototype laser ablation ionization mass spectrometer along with unsupervised machine learning are powerful tools for the study of surface samples on planetary bodies. …”
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The role of Tei index as an early predictor for evaluating experimental uremic cardiomyopathy model by Shi Cheng, Wei Lu, Jiarui Xu, Yong Yu, Yi Fang, Xiao Tan, Ruizhen Chen, Bo Shen, Xiaoqiang Ding, Yeqing Xie

“…Experimental animal models serve as essential tools for elucidating the potential mechanism underlying UCM. …”
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Experimental comparison of the effectiveness of programs for minimizing systems of Boolean functions in the class of disjunctive normal forms by P. N. Bibilo, I. P. Loginova

“…Algorithms and programs for parallelization of calculations when separate functions of minimizing have been developed. Software tools for the application of joint minimization programs with separate minimization of functions are proposed.Results. …”
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Hip axis length and non-hip cortical fragility fractures in young postmenopausal nonobese Caucasian women by Irina Manuela Nistor, Simona Fica, Sorina Carmen Martin, Marius Lucian Mitrache, Theodor Eugen Oprea, Anca Elena Sirbu, Carmen Gabriela Barbu

“…Recently, clinical risk tools included hip axis length (HAL), a geometric parameter derived from the hip DXA scan, as a predictor of hip fractures in older postmenopausal women. …”
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The Effect of Kinesiology Taping on Posture, Balance, and Gait in Patients Suffering from Low Back Pain by Józef Alphons Opara, Tomasz Fiałkowski

“…Results: The effects of Kinesio taping on pain, gait, coordination, postural control, and balance are statistically significant. The main parameter influencing the effects of Kinesio taping was age (below 55 years); this relationship was also observed in the control group. …”
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A Multiscale Approach to the Design and Manipulation of Oil-in-Water Emulsion-Based Products by Javier D. Gomez, Diego Pradilla, Oscar Alvarez

“…Industrial emulsion-based products, ubiquitous to everyday life, are complex systems driven by interfacial phenomena that require quick property-prediction tools for their commercialization. In this work, by means of a multiscale approach, mathematical relationships to model oil-in-water emulsions and that can be applied to any commercial emulsion-based product are proposed. …”
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Assessing ML classification algorithms and NLP techniques for depression detection: An experimental case study. by Giuliano Lorenzoni, Cristina Tavares, Nathalia Nascimento, Paulo Alencar, Donald Cowan

“…Recent research has evidenced that machine learning (ML) and natural language processing (NLP) tools and techniques have significantly benefited the diagnosis of depression. …”
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The Development of Small-Scale Language Models for Low-Resource Languages, with a Focus on Kazakh and Direct Preference Optimization by Nurgali Kadyrbek, Zhanseit Tuimebayev, Madina Mansurova, Vítor Viegas

“…Low-resource languages remain underserved by contemporary large language models (LLMs) because they lack sizable corpora, bespoke preprocessing tools, and the computing budgets assumed by mainstream alignment pipelines. …”
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Towards Nonlinear Magnetic Rotating Pendula for Low-Frequency Weak Vibration Energy Harvesting by Mihai Ionut Trandafir, Panagiotis Alevras

“…Numerical integration of the nondimensional equation of motion is performed in the system’s parameter space to identify the impact on the regions triggering rotational response to parametric excitation. …”
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An Integrated Building Energy Model in MATLAB by Marco Simonazzi, Nicola Delmonte, Paolo Cova, Roberto Menozzi

“…The IBEM seamlessly integrates thermal and electrical aspects into a complete physical description of the energy performance of a smart building, thus distinguishing itself from co-simulation approaches in which different specialized tools are applied to the two aspects and connected at the level of data exchange. …”
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Comparative analysis of two artificial intelligence models for the diagnosis and treatment guidelines of primary osteoporosis and the interpretation of clinical bone mineral densit... by HU Chaofeng, ZHENG Songtao, CHEN Ruiqiang, LI Shangfu

“…The accuracy score of DeepSeek was significantly higher than that of ChatGPT，and DeepSeek was more accurate in drug management and parameter analysis，which conformed to the key points of guideline update. …”
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The effect of public saving on agricultural and fishing investments for the government and private sectors in Iraq for the period 2005-2021 by Saad A. Hammad, A.D.k Al-Hiyali, Mustafa Fadel Hhamad

“… The target of the manuscript is to quantify and examine the effects of public saving on agricultural and fishing investments for the government and private sectors and economic growth in Iraq for the period 2005-2021. Econometric tools were used to clarify the impact (autoregressive model with distributed lag periods). …”
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Interactive Multimedia Environment Intervention with Learning Anxiety and Metacognition as Achievement Predictors by Aristea Mavrogianni, Eleni Vasilaki, Michalis Linardakis, Aikaterini Vasiou, Konstantinos Mastrothanasis

“…Background: Interactive learning environments have emerged as transformative tools in education, enhancing engagement, academic performance, and addressing challenges like learning anxiety. …”
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Chaotic and quasi-periodic dynamics in fractional-order nonlinear wave systems within dispersive-dissipative media by Wael W Mohammed, Fakhr Gassem, Rabeb Sidaoui, Aleksander Vokhmintsev, Mostafa M. A. Khater

“…Additionally, we conduct an exhaustive examination of the $$\mathcal {FBKP}$$ system, clarifying its evolutionary dynamics through bifurcation analysis, characterization of chaotic/quasi-periodic regimes, and assessment of parameter sensitivity. The primary objective is to illuminate the governing mechanisms of the system’s temporal evolution using advanced mathematical tools rooted in nonlinear dynamical theory.…”
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Using machine learning for the assessment of ecological status of unmonitored waters in Poland by Andrzej Martyszunis, Małgorzata Loga, Karol Przeździecki

“…Abstract Advancements in Artificial Intelligence (AI) technology allow for development of new tools for analytics and management which present new opportunities in field of environmental protection. …”
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The Pharmacological Mydriatic Pupil-to-Limbal Diameter Ratio as an Intuitive Predictor for the Risk of Intraoperative Floppy Iris Syndrome by Yurika Terauchi, Hiroshi Horiguchi, Takuya Shiba

“…The PL ratio is a simple and useful parameter for compensated prediction of IFIS development. …”
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Penetration Testing pada Kerentanan Keamanan Sistem PELAKAT Menggunakan SQL Injection by Khairul, Asrul Abdullah, Sucipto Sucipto

“…Berdasarkan hasil pengujian, salah satu parameter pada form login sistem PELAKAT diketahui rentan terhadap SQL Injection. …”
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Pest Detection in Citrus Orchards Using Sentinel-2: A Case Study on Mealybug (<i>Delottococcus aberiae</i>) in Eastern Spain by Fàtima Della Bellver, Belen Franch Gras, Italo Moletto-Lobos, César José Guerrero Benavent, Alberto San Bautista Primo, Constanza Rubio, Eric Vermote, Sebastien Saunier

“…This work contributes to the development of new monitoring tools for efficient and sustainable action in pest control.…”
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A Novel Alpha-Power X Family: A Flexible Framework for Distribution Generation with Focus on the Half-Logistic Model by A. A. Bhat , Aadil Ahmad Mir , S. P. Ahmad , Badr S. Alnssyan , Abdelaziz Alsubie , Yashpal Singh Raghav

“…In both cases, the proposed model provides a better fit than the traditional half-logistic and related distributions, as shown by lower values of standard model selection criteria. Graphical tools such as fitted density curves, Q–Q and P–P plots, survival functions and box plots further support the suitability of the model for real-world data analysis.…”
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Implementation of a Neural Network for Adaptive PID Tuning in a High-Temperature Thermal System by Juan Carlos Almachi, Ramiro Vicente, Edwin Bone, Jessica Montenegro, Edgar Cando, Salvatore Reina

“…Precise temperature control in high-temperature furnaces is challenged by nonlinearities, parameter drift, and high thermal inertia. This study proposes an adaptive control strategy combining a classical PID loop with real-time gain updates from a feed-forward artificial neural network (ANN). …”
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