Nutrition for Health and Fitness: Fiber in Your Diet by Linda B. Bobroff

“…Fiber has many names, such as dietary fiber, total fiber, or just plain fiber. …”
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Hyophorbe lagenicaulis, Bottle Palm by Melissa H. Friedman, Michael G. Andreu, Heather V. Quintana, Mary McKenzie

“…Quintana, and Mary McKenzie, describes this palm with a bottle shaped trunk that is endemic to the Mascarene Islands east of Madagascar, and can grow in south Florida — scientific and common names, description, and applications. Includes references. …”
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Unfair Terms and Unpredictability in the Insurance Contract by Ioana Nely MILITARU

“…Thus, in order to prevent abusive practices in the insurance sector, namely of insurers (insurance companies), states have set up administrative authorities to control them, supervise their activity, and sanction their illegal actions.…”
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Integrable 2D Time-Irreversible Systems with a Cubic Second Integral by H. M. Yehia, A. A. Elmandouh

“…Special cases are given interpretation as a motion of a particle on a sphere endowed with a Riemannian metric, a particle in the Euclidean plane, and new generalizations of two cases of motion of a rigid body with a cubic integral, known by names of Goriachev-Chaplygin and Goriachev.…”
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Two-channel electric liquid helium level meter by K. K. Kim, A. A. Tkachuk, A. A. Kuznetsov

“…The need to develop such a meter is dictated by the specifics of the functioning of cryomodules that are part of transport systems, namely, functioning in the strong magnetic fields. …”
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MOBILE LEARNING IN CONDITIONS OF INFORMATION INEQUALITY by Danila N. Monakhov

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RETRACTED: Experiential learning as principle of environmental education by Shutaleva Anna

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RETRACTED: Dynamics of indicators of the acid-base state of the blood in different seasons by Borisova Natalia

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NETWORK EFFECT IN THE REGIONAL ECONOMY PROVIDED BY EDUCATION CLUSTERS by Darya-Anna A. Kaybiyaynen

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A walk around Bukhara by Марина Ткачева

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RETRACTED: Psycholinguistic characteristics of the jargons of the national language representing the learning process by Ahmedova Muyassar

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RETRACTED: Mathematical prediction of the Aldan river freezing based on prehistory in 2000-2022 by Iovleva Elizaveta, Boyarshinov Anatoly

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GENDER PROJECT OF THE FUTURE by V. V. Khmil

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A STUDY ON THE REGISTER OF POLITY by Radityo Tri Nugroho, Afifah Linda Sari

“…Having analyzed the data, the writer finds two forms of polity register namely: word and phrase. The words are in the form of simple word (26, 7%), compound word (26, 7%), and complex word (24, 4%), abbreviation and blended, each has 2,2%. …”
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THREE VIEWS ON THE PROBLEM OF A PRIORI: I. KANT, D. VON HILDEBRAND AND M. SCHELER by Aivaras Stepukonis

“…Hildebrand uses a priori in yet another sense, namely, in the sense of 'independent of blunt observation', but, he does not take the pain of explaining the meaning of the latter phrase. …”
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PROSPECTS FOR THE HEREDITARY FUND IN MODERN RUSSIAN LAW by Tatyana Y. Naumova, Valentina M. Bolshakova, Petr Y. Naumov

“…However, the blind copying of trust legislation, together with the use of an inappropriate form of a Russian legal entity, namely a «fund» became a determining factor for turning a promising civil law institution into a non-working mechanism. …”
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Features of Carbon Regulation in the Republic of Belarus and the Russian Federation: Comparative Analysis and Trends by V. A. Liubchyk, V. E. Pinaev, V. N. Ukhova

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Privacy leakage risk assessment for reversible neural network by Yifan HE, Jie ZHANG, Weiming ZHANG, Nenghai YU

“…In recent years, deep learning has emerged as a crucial technology in various fields.However, the training process of deep learning models often requires a substantial amount of data, which may contain private and sensitive information such as personal identities and financial or medical details.Consequently, research on the privacy risk associated with artificial intelligence models has garnered significant attention in academia.However, privacy research in deep learning models has mainly focused on traditional neural networks, with limited exploration of emerging networks like reversible networks.Reversible neural networks have a distinct structure where the upper information input can be directly obtained from the lower output.Intuitively, this structure retains more information about the training data, potentially resulting in a higher risk of privacy leakage compared to traditional networks.Therefore, the privacy of reversible networks was discussed from two aspects: data privacy leakage and model function privacy leakage.The risk assessment strategy was applied to reversible networks.Two classical reversible networks were selected, namely RevNet and i-RevNet.And four attack methods were used accordingly, namely membership inference attack, model inversion attack, attribute inference attack, and model extraction attack, to analyze privacy leakage.The experimental results demonstrate that reversible networks exhibit more serious privacy risks than traditional neural networks when subjected to membership inference attacks, model inversion attacks, and attribute inference attacks.And reversible networks have similar privacy risks to traditional neural networks when subjected to model extraction attack.Considering the increasing popularity of reversible neural networks in various tasks, including those involving sensitive data, it becomes imperative to address these privacy risks.Based on the analysis of the experimental results, potential solutions were proposed which can be applied to the development of reversible networks in the future.…”
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Edge-centric optimization: a novel strategy for minimizing information loss in graph-to-text generation by Zheng Yao, Jingyuan Li, Jianhe Cen, Shiqi Sun, Dahu Yin, Yuanzhuo Wang

“…We propose a framework named Edge-Optimized Multi-Level Information refinement (EMLR), which aims to maximize the retention of the graph’s structural information from an edge perspective. …”
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Measurement of JMSK PSMZA Lecturer Achievement Based on P & P Monitoring by Pazlina Binti Mat ali, Hasliza Binti Hashim

“…This study was conducted to determine the effect of monitoring the teaching and learning of lecturers based on five domains assessed namely the planning of teaching and instructional, instructional, competence and professionalism of lecturers, management teaching and learning process. …”
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