Background: Frozen shoulder, also known as Adhesive capsulitis, is a common musculoskeletal disorder that causes discomfort, stiffness, and limited shoulder joint range of motion. This illness is managed using various Physiotherapy techniques such as electrotherapy modalities, manual therapy techniques, exercises, etc. Muscle Energy Technique (MET) is one of the manual therapy technique that have drawn attention as a possible treatment for enhancing shoulder mobility and lowering pain. The objective of this narrative review is to analyze the efficacy of MET in managing frozen shoulder by examining current evidence and discussing how it affects functional outcomes, range of motion, and pain relief. Methods: A thorough analysis of pertinent research and clinical trials on the effectiveness of MET in managing frozen shoulder was carried out. We looked through databases like PubMed, Scopus, and Google Scholar to find papers that had been published during the last 20 years. Reduction of discomfort, enhancement of shoulder mobility, and general functional recovery are among the important outcomes evaluated. Results: According to the research, MET helps people with frozen shoulder move their shoulders more freely, feel less discomfort, and perform better in their daily activities. The method increases flexibility and decreases stiffness by stretching the restricted tissues and facilitating joint movement through voluntary muscle contractions. MET seems to be more beneficial in encouraging active movement and neuromuscular control than passive stretching methods. Conclusion: MET is a potentially effective treatment strategy for frozen shoulder that enhances functional ability, range of motion, and pain alleviation. To create uniform procedures and ascertain its long-term efficacy, more excellent randomized controlled studies are necessary. For patients with frozen shoulder, combining MET with other physiotherapy treatments may result in the best results.
WSNs are extensively explored for their ability to collect and monitor data across a wide range of applications. However, the sensor nodes’ limited energy resources pose a substantial hurdle to prolonging the network’s longevity. To address this, we propose a Deep Learning-based Clustering Model Approach for optimizing energy utilization in WSNs. The DL-Clustering method uses sophisticated deep learning techniques, specifically RNN, to improve energy efficiency through effective cluster formation, CH selection, and CH maintenance. Our approach increases WSN lifespan and data transmission efficiency by using deep learning and intelligent grouping strategies. When compared to existing approaches such as LEACH, TCEER, TASRP, CARA, and SACC, DL-CM outperforms them in terms of energy efficiency. The results demonstrate the effectiveness of advanced deep-learning approaches in optimizing energy consumption and tackling the constraints faced by constrained energy supplies. This study highlights the ability of DL-Clustering to greatly increase energy optimization for WSNs, maximizing network potential and improving data transmission efficiency.
In this work, alkali metals of rubidium and~cesium are studied~through doping in lithium, sodium or potassium ion batteries. A vast study on H-capture by “LiRb (GeO–SiO), LiCs(GeO–SiO), NaRb(GeO–SiO), NaCs(GeO–SiO), KRb(GeO–SiO), KCs(GeO–SiO) “, was carried out including using “DFT” computations at the “CAM–B3LYP–D3/6–311+G (d,p)” level of theory. The hypothesis of the hydrogen adsorption phenomenon was figured out by density distributions of “CDD, TDOS, LOL” for nanoclusters of “LiRb(GeO–SiO)–2H 2 , LiCs(GeO–SiO)–2H 2 , NaRb(GeO–SiO)–2H 2 , NaCs(GeO–SiO)–2H 2 , KRb(GeO–SiO)–2H 2 , KCs(GeO–SiO)–2H 2 ”. The oscillation in charge density amounts displays that the electronic densities were mainly placed in the edge of “adsorbate/adsorbent” atoms during the adsorption status. As the benefits of “lithium, sodium or potassium” over “Ge/Si” possess its higher electron and “hole motion”, permitting “lithium, sodium or potassium” devices to operate at higher frequencies than “Ge/Si” devices. A small portion of “Rb or Cs” entered the “Ge–Si” layer to replace the Li, Na or K sites might improve the structural stability of the electrode material at high multiplicity, thereby improving the capacity retention rate. Among these, potassium-ion batteries seem to show the most promise in terms of “Rb or Cs” doping.
The necessity of green construction technologies is currently a fundamental requirement in India. Although not a novel technology, an examination of Indian statistics reveals a limited number of green-rated projects or buildings. A fundamental benefit of any green building is the reduction in electricity usage, reliance on underground water resources, and the need for air conditioning. The occupants of green buildings experience a noticeable disparity in comfort and energy conservation compared to conventional structures. Within this academic study, the analysis of a residential projects in Bhopal named Sagar Green Hills (SGH), Sage Golden Spring (SGS), Sage Milestone, Sage Suncity and Prime Square, Indore is presented, assessed against the 34 criteria of Green Rating for Integrated Habitat Assessment (GRIHA), emphasizing key findings on achieving a minimum 1-star evaluation. This investigation aims to inspire developers in Tier II cities like Bhopal and Indore to undertake green residential projects and encourage potential residents, or clients, to choose environmentally-friendly initiatives. The evaluation of the project follows the GRIHA guidelines, outlining essential actions required to fulfill mandatory criteria.
Chemical graph theory is prominent research area in mathematical chemistry, due to its extensive applications especially in quantitative structure-activity relationships (QSARs) where eccentricity based topological invariants are used for the mathematical modeling of biological activities of molecules, identifying structurally similar molecules and used to study the structure and properties of materials, such as polymers and ceramics. Carbon nanotubes (CNTs) are cylindrical structures made up of carbon atoms that are arranged in a unique hexagonal pattern. In this research, we examine the \(NA^{n}_{m}\) nanotube after considering it in the form of chemical graph and compute eccentricity based topological invariants like eccentric-connectivity index with total-eccentricity index with some versions of the zagreb indices.
Topological Indices are one of the best molecular descriptors which are widely used in the study of structural properties of various chemicals. Also, they are very much useful in QSPR/QSAR studies. Among several topological indices, distance-based indices are emerging and attracted researchers across the world. In this article, we study the recently introduced sixteen different distance-based topological indices for eleven anti-cancer drugs and also performed QSPR analysis to identify the best predictors for the physico-chemical properties namely, Molar Refractivity, Complexity, Molar Volume, Heavy Atom Count, Monoisotopic Mass and Topological Polar Surface Area with the help of those computed values of the indices.
Gait parameter evaluation is crucial while ascertaining the health status of participants and formulating therapeutic interventions. The design and application of the smartphone technique for evaluating and investigating participants’ gait parameters are presented in this paper. New methodology to investigate the spatiotemporal parameters of healthy individuals: step time, stride time, cadence and walking speed, through insole sensors and smartphones is introduced in this work. The aim of this research is firstly to examine the performance of a couple of Android smartphones (one per leg) two Android smartphone compared to an insole sensor in estimating spatiotemporal gait parameters. Secondly, the research tests the validity of a tri-axial accelerometer of a smartphone to quantify gait features. Spatiotemporal gait parameters of twenty healthy subjects (10 male, 10 female, age >18) were measured using insole sensors and smartphones. Five trials of walking were requested from each subject. The data were obtained from the insole sensors and smartphones. Six statistic measures: Pearson correlation coefficient, linear regression, mean, standard deviation (SD), p-value, and Bland-Altman, were employed to compare the validity of the smartphones. The coefficient of correlation according to the developed approach was 0.79-0.92 for left and right legs, respectively. On the basis of the results obtained by the study using four parameters: step time, stride time, cadence, and walking speed, it was noted that there was consensus between smartphones and insole sensors in gait parameter measurement. In addition, these findings illustrated that the smartphone sensor is effective in measuring healthy adult participants’ spatiotemporal gait parameters. Accordingly, it is capable of generating trustworthy data without having to invest in costly equipment. Lastly, the established technique could assist an expert in objectively and effectively assessing gait.
A comprehension of the structure and function of biologic molecules involves conformational analysis. Conformational alterations are especially important in the influenza virus since they regulate the virus’s ability to proliferate and infect host cell proteins are made up mostly of torsional angles that determine their overall shape and side chains. New information about these structures and functions has been opened up by recent technological breakthroughs. The major uses of the omega angle are in conformational analysis and protein structure studies. The omega angle is still an important parameter when one studies the structures of different proteins and peptides. The study of the protein content of influenza viruses is essential; for vaccine and antiviral drug development. This article reviews the importance of conformational analysis and the use of the omega angle in predicting the behavior of the influenza virus that can be applied in drug-designing.
The scientific article is devoted to the study of criminal offenses against peace, human security and international order, committed under martial law. It was emphasized that such illegal acts, in particular genocide and ecocide, occupy the highest level among illegal acts for which international criminal responsibility is provided. It is noted that the increase in the number of crimes against peace, human security and international order in conditions of sustainable development can lead to negative consequences and a threat to the biological foundations of life on Earth. Arguments are given that counteraction to such criminal manifestations should have appropriate legal regulation, which would correspond to the degree of social danger of illegal actions and the degree of severity of consequences. A conclusion was made on the importance of developing a methodology for documenting and investigating crimes of this category and proper technical forensic and tactical provision of separate procedural procedures for the purpose of identifying, recording, removing and investigating traces of illegal actions. The importance of using the form of data collection through open sources and their processing – Open-Source Intelligence – is indicated.
Globalization is one of the main drivers of economic development in the modern world. However, along with the increase in trade volumes due to the opening of markets, the growth of competitiveness of national economies via the development of communications, the use of the latest technologies, and the attraction of foreign investment, globalization poses numerous challenges for states. This article aims to analyze the positive and negative aspects of globalization impact (the research object) on the processes of countries’ economic development. The system approach serves as the methodological background of this study. The main methods employed include document and correlation analysis, comparative method, abstraction, systematization, induction, and deduction methods. It has been found that there is a direct correlation between the level of countries’ globalization (KOF Globalization Index) and the level of their economic development, as demonstrated by GDP (PPP) per capita. At the same time, other macroeconomic indicators (i.e., unemployment, inflation, and public debt) have a weak correlation with the globalization level of countries. However, the global financial crisis of 2008 had the most severe consequences for countries with high levels of public debt and countries with high rates of economic development. The authors found that globalization promotes the economic inclusion of Asian countries in the world economic processes. These countries successfully compete with developed countries (the USA and the EU) and are already outperforming them in certain areas (China ranks first in the world in terms of exports and in the GDP (PPP) ranking). These facts refute the thesis that globalization benefits only developed countries (the global North). At the same time, globalization processes stimulate the growth of social inequality in the world. Such inequality is typical for both Northern and Southern countries. Therefore, it requires a competent public policy to maximize the benefits of globalization and minimize its negative impact, which will help further the economic development of countries.
The article is devoted to defining the features of the meaningful evolution of the human right to peace, as well as the prospects for its provision in the context of today’s crisis raealities. It is emphasized that modern international legal institutions have demonstrated their inability to adequately guarantee interstate peace and security, and the existing sanctions policy has not justified itself, because, as the example of the Russian-Ukrainian war shows, the aggressor has found ways to circumvent it. In this regard, attention is focused on the importance of developing the International Sanctions Code in order to establish such “rules of the game” that the aggressor will not have the opportunity to use military means to resolve relevant international and other conflicts. The opinion is substantiated that one of the most important prerequisites for ensuring the effective practical implementation of the right to peace is a “healthy” moral environment of human life and society, which can be achieved under the condition of appropriate “normotactics” or an appropriate level of coherence and interconnection between social regulators, primarily law, morality and religion. It is concluded that ensuring and protecting the human right to peace requires the creation of appropriate conditions in society aimed at establishing a state of harmony, coherence, accord, unity, and consensus among legal entities at all levels.
Based on the viscoelastic theory, this paper establishes a variety of finite element model structures for asphalt pavements in combination with finite element software, and defines a variety of asphalt pavement damping forms using the ABAQUS program, and designs experimental loading conditions for asphalt pavements. On the basis of the viscoelastic behavior of the material, the viscoelastic intrinsic model of the asphalt pavement is given, and the viscoelastic mechanics inverse problem of the asphalt pavement is designed, and the finite element model is also used to compare the inverse problem with the inverse calculation. The results of the inverse computational comparison of the inverse problem were explored for the viscoelastic mechanical behavior of asphalt pavements, and the changes in the mechanical properties of asphalt pavement structures were analyzed for different braking coefficients, temperature fields, and loading loading frequencies. It is found that the maximum difference error between the inverse calculation results obtained for different asphalt pavement structures is less than 6\%, and the relative maximum error between the inverse calculation and the measured bending settlement value at a distance of 0.3m under 20t load is 12.65\%. Under different braking coefficients and temperature fields, the shear stress and transverse stress of asphalt pavement have obvious trends, and when the loading frequency is 20Hz, the dynamic modulus difference between different temperatures is large. The viscoelastic change of asphalt pavement can be obtained through backcalculation, and its mechanical change can also be analyzed to provide reference for improving the performance of asphalt pavement.
The article focuses on the syntactic structures inherent in secondary academic (in other words, scientific) texts (e.g., review, abstract, thesis, and summary) in English and Ukrainian. The study of the syntax of secondary academic and scientific texts in various fields of scientific knowledge is essential for several reasons, namely for understanding and communication, academic progress, interdisciplinary research, automatic text processing, and professional training. Moreover, the study of the syntax of scientific texts has a practical significance for teaching students and young scholars. The study aims to compare the syntax of secondary academic texts in different fields of knowledge based on the comparative aspect of English and Ukrainian. The research methodology involved corpus-based research, cognitive-linguistic analysis, comparative and qualitative analysis, and experimental research. The authors analyzed the peculiarities of academic writing of secondary scientific texts: reviews, abstracts, summaries, and theses. In addition, the authors have carried out a comparative analysis of the syntactic structures of secondary scientific texts in Ukrainian and English. The article also focuses on the differences in the syntax of secondary academic and scientific texts in the natural sciences, humanities, engineering, and social sciences. The authors have compared the acceptance rate of secondary academic texts for publication in English and Ukrainian to identify challenges related to their writing. Furthermore, the paper provides recommendations for improving the quality of writing secondary academic and scientific texts. The improvement of the syntax in secondary academic texts can significantly increase their clarity and persuasiveness.
The integration of AI and education makes the education field more “intelligent” and “flexible”. The new era calls for AI to boost the construction of teachers. Under the influence of traditional educational concepts in the past, there are still many problems in college education management in many aspects. This paper first analyzes the evaluation projects, indicator systems, documents, policies, and development context of domestic and foreign college education informatization, and constructs the maturity model and evaluation informatization. The experimental results prove that the optimized structural equation model, combined with the innovative education concept, and optimizes the practical of various education management work in the school under the innovative education concept. And through the analysis and research of these problems, the specific corresponding methods and countermeasures are proposed. It provides a theoretical basis to a certain extent for university administrators to better apply innovative ideas to educational management.
The accuracy of piano music classification based on high-dimensional data collaborative filtering recommendation algorithm is automatically evaluated by computer technology, and the K-means model algorithm is used to conduct a comparison test. By comparing the classification results of high-dimensional data collaborative filtering recommendation algorithm with the piano music classification results of K-means algorithm, the piano learning burden can be reduced and the piano learning effect can be improved. The results of this paper show that the automatic piano performance evaluation system based on the high-dimensional data collaborative filtering recommendation algorithm has an accuracy rate of 95% and has a good rating effect.
NM-polynomial is commendably effective for computations of neighborhood degree sum based topological indices. This work comprises of computations of topological invariants which are first, second, third, fourth and fifth N D e indices, third version of Zagreb index, neighborhood second Zagreb index, neighborhood second modified Zagreb index, neighborhood forgotten topological index, neighborhood general Randi\’c index, neighborhood harmonic index, neighborhood inverse sum index, fourth atom bond connective index, fifth geometric arithmetic index, fifth arithmetic geometric index, fifth hyper first and second Zagreb index and Sunskurti index. In the end graphs are added for better understanding of these invariants.
This paper firstly presents the hierarchical conceptual model and implementation model of the overall framework of the relationship between enterprise management and market economic decision-making based on absorption of different conditions and driven by big data. The overall framework is divided into interaction layer, service composition layer, service layer, business component layer and resource layer. In particular, the service layer includes the basic software components distributed in the enterprise computing environment that can be reused and reorganized and follow standardized interface protocols. Different combinations such as looping, selection, and parallel are used to compile practical solutions. The service component architecture is used to realize the service modeling, the service data object is used as the data and message model, the business process execution language is used to arrange the service, and the enterprise service bus technology based on the system is used to complete the system composition. The experimental results show that the protocol-based hierarchical multi-dimensional data analysis framework in the environment adopts both the aggregation pool object replacement strategy and the real view technology based on the object soft reference technology to improve the query performance of massive multi-dimensional data, to achieve enterprise management and market economy.
As the information era advances, robotic intelligent sorting is being applied more and more in the logistics sector. As such, studying vision-based autonomous identification, localization, grasping, and sorting mobile sorting robot systems is crucial. In order to accomplish the function of motion ranging and positioning, this paper uses a camera mounted at the end of an industrial robot to continuously shoot single-point images of various locations within the world coordinate system. The parameters obtained are similar to those of binocular vision ranging. The vision library (OpenCV for Python) is used to process the image data for an automatic sorting operation of cylindrical workpieces that is currently in place. The point-by-point sampling calculation is carried out within the robot’s running trajectory. According to the experimental results, the monocular motion vision ranging and localization system performs well, with an average localization error of less than 4%. The ranging method can also meet accuracy requirements under some conditions, which is useful in lowering the automatic sorting system’s upgrade costs.
The builders and practitioners of the next thirty years, the creators of the completion of the Chinese dream, and the achievers of the hundred-year change. As the talent reserve and the future pillar, the health condition of college students is related to the future and destiny of the Party and the country. An important foundation of talent quality, and the improvement of mental health literacy is more the improvement of talent quality in the new era. It is a critical period for college students to improve their ideological and moral quality as well as to shape and set their behavioral habits. During this period, it is not only a meaningful but also an urgent matter to emphasize the formation of behavioral habits and the formation of qualities. As we all know, the outward behavioral habits are an important symbol of whether a person has developed good ideology and morality, and also an important symbol of the success of educational activities. Therefore, college students’ mental health and behavioral habit formation education become the central theme of this paper. Behavior activation has the characteristics of simplicity, efficiency and easy dissemination, and there are a few applications in China, but there is a lack of theoretical research on behavior activation therapy. The purpose of this study was to (1) revise the Chinese version of the short version of the Behavior Activation Scale for depression, an important assessment tool in the study of behavior activation treatment, and examine its reliability; (2) examine the effect of behavior activation in improving depression through intervention studies and explore the mechanism of the role of reinforcement sensitivity and coping style in behavior activation intervention. The experimental results show that the best algorithm can study depression, anxiety, stress, analyze depression, anxiety, stress and its influencing factors, and help students explore mental health. Objectively, to accurately identify the risk factors that cause depression, anxiety and stress of college students, and take preventive measures.
This study introduces a hybrid recommendation framework leveraging convolutional neural networks (CNNs) for music recommendation, enhancing accuracy and feature analysis. By integrating music tag features into the CNN architecture, personalized recommendations are facilitated, surpassing traditional methods. Additionally, mobility patterns of educational elites in the Yangtze River Delta are explored, illuminating academic cooperation networks. Experimental results demonstrate the effectiveness of the proposed model in predicting user preferences and outperforming existing methods.
