تأسيس الشركات بين الجامعات السودانية و مؤسسات المجتمع خاصة الشركات الخاصة

تأسيس الشركات بين الجامعات السودانية و مؤسسات المجتمع خاصة الشركات الخاصة This research tackles the way in which Sudanese universities establish partnerships with community institutions especially private sector companies in order to spare universities needs materially and physically which helps in achieving the economical job of the universities by benefiting from Peculiarities Of knowledge economics. The research also handles how Sudanese universities translates their developing efforts in academic process and scientific research through encouraging and adopting innovations and Excellent Research Ideas. In addition, The research aimed at identifying the important role of Innovations and Excellent Research Ideas Centers in universities in transforming Excellent Research Ideas into successful projects which enables universities in developing their Learning Inputs in order to obtain developed outputs, then accordingly, universities will find the way paved to Establish successful partnerships with community institutions especially private sector companies, in doing so, universities will spare the needed finance for scientific programmes, training, academic, and research programmes. The research confirms that transforming Excellent Research Ideas into successful projects attains good beneficial income for universities in especial* and thereafter for the economy of the country in general

Sex, Gender, and Diversity Analysis in Research Policies of Major Public Granting Agencies: A Global Review

National research agencies are funded by taxpayer monies and, as such, are responsible for promoting excellent research that benefits all of society. Integrating sex, gender and diversity analysis (SG&DA) into the design of research, where relevant, can improve research methodology and provide new insights. To realize this potential, funding agencies have developed policies for integrating this type of analysis into the grant proposal process. This study reviews those policies for 23 agencies across six continents. Overall, one agency achieved superior performance, six agencies scored excellent performance, five showed average performance, two need some improvement and nine require improvement. Our study developed a five-part SG&DA policy roadmap for agencies and collected best practices across that guide. Standard practices, tailored as appropriate to country-specific cultures and regulatory landscapes, will enhance collaboration potential, global equity, research excellence and reproducibility.

ForkDec: Accurate Detection for Selfish Mining Attacks

Incentive mechanism is the key to the success of the Bitcoin system as a permissionless blockchain. It encourages participants to contribute their computing resources to ensure the correctness and consistency of user transaction records. Selfish mining attacks, however, prove that Bitcoin’s incentive mechanism is not incentive-compatible, which is contrary to traditional views. Selfish mining attacks may cause the loss of mining power, especially those of honest participants, which brings great security challenges to the Bitcoin system. Although there are a series of studies against selfish mining behaviors, these works have certain limitations: either the existing protocol needs to be modified or the detection effect for attacks is not satisfactory. We propose the ForkDec, a high-accuracy system for selfish mining detection based on the fully connected neural network, for the purpose of effectively deterring selfish attackers. The neural network contains a total of 100 neurons (10 hidden layers and 10 neurons per layer), learned on a training set containing about 200,000 fork samples. The data set, used to train the model, is generated by a Bitcoin mining simulator that we preconstructed. We also applied ForkDec to the test set to evaluate the attack detection and achieved a detection accuracy of 99.03%. The evaluation experiment demonstrates that ForkDec has certain application value and excellent research prospects.

Applying the FAIR4Health Solution to Identify Multimorbidity Patterns and their Association with Mortality through a Frequent Pattern Growth Association Algorithm. (Preprint)

BACKGROUND Chronic diseases are responsible for most health problems in older people. We know that chronic conditions tend to cluster in the form of patterns, also known as multimorbidity patterns. However, health systems and professionals are generally organized and trained to respond to specific diseases independently, negatively impacting patients and health systems. Different initiatives are trying to respond to these problems. In this context, the current availability of electronic health records and other types of health research data represents an excellent research opportunity. However, there are also some relevant limitations and challenges related to a current lack of tools that allow us to access, harmonize, integrate and reuse datasets technically, legally, ethically, and respectfully to patients and society. In this sense, the FAIR (Findability, Accessibility, Interoperability, and Reusability) principles can help us to guide scientific data management and stewardship and drive scientific discovery to a new paradigm. FAIR4Health is a European Commission supported project that applies FAIR principles on publicly-funded research datasets. OBJECTIVE To present the FAIR4Health pathfinder case study designed to validate and evaluate the FAIR4Health solution with the aim of identifying multimorbidity patterns and their association with mortality in older adults from different health organizations databases of four European countries. METHODS To apply the FAIR principles in five European cohorts from different healthcare settings (i.e., primary care, hospitals, and nursing homes) and institutions (i.e., University of Geneva from Switzerland, Università Cattolica del Sacro Cuore from Italy, University of Porto from Portugal, Instituto Aragonés de Ciencias de la Salud from Spain, and Andalusian Health Service also from Spain), a multicentric retrospective observational study (N = 11,034) was performed. In FAIR4Health, a workflow was designed to implement the FAIR principles on health datasets, and two tools were developed, a Data Curation Tool to transform the raw datasets into FAIR datasets and a Data Privacy Tool to preserve data privacy. On top of these, the FAIR4Health Platform was implemented to provide an interface for researchers, and enable the usage of federated machine learning algorithms on FAIR datasets. In this study, we applied a federated frequent pattern growth association algorithm to identify the most frequent disease patterns among a set of variables. RESULTS We applied the FAIR principles in the health research datasets from different organizations, and we were able to reuse and integrate heterogeneous datasets, increasing the variability of data compared to the studies not applying those principles. We identified and described high-frequent multimorbidity patterns consistent with the literature and observed a strong association with polypharmacy and mortality. CONCLUSIONS Our results highlight the importance of implementing the FAIR data policy to overcome the difficulties in data management and accelerate responsible health research with patients and society.

Research on multi-sensor information fusion and intelligent optimization algorithm and related topics of mobile robots

Research on mobile robots began in the late 1960s. Mobile robots are a typical autonomous intelligent system and a hot spot in the high-tech field. They are the intersection of multiple technical disciplines such as computer artificial intelligence, robotics, control theory and electronic technology. The product not only has potentially very attractive application value and commercial value, but the research on it is also a challenge to intelligent technology. The development of mobile robots provides excellent research for various intelligent technologies and solutions. This dissertation aims to study the research of multi-sensor information fusion and intelligent optimization methods and the methods of applying them to mobile robot related technologies, and in-depth study of the construction of mobile robot maps from the perspective of multi-sensor information fusion. And, in order to achieve this function, combined with autonomous exploration and other related theories and algorithms, combined with the Robot Operating System (ROS). This paper proposes the area equalization method, equalization method, fuzzy neural network and other methods to promote the realization of related technologies. At the same time, this paper conducts simulation research based on the SLAM comprehensive experiment of the JNPF-4WD square mobile robot. On this basis, the high precision and high reliability of robot positioning are further realized. The experimental results in this paper show that the maximum error of the X-axis and Y-axis, FastSLAM algorithm is smaller than EKF algorithm, and the improved FASTSALM algorithm error is further reduced compared with the original FastSLAM algorithm, the value is less than 0.1.

Push-Out Test and FEM Analysis of Continuous Shear Connector

Composite steel concrete bridges with embedded continuous shear connectors are one of the newer popular options for short span (up to 20 m) bridges. They can be used for both road and railway bridges and due to their low structural height, nowadays, they are also a welcome alternative for bridge reconstructions – the concrete part serves as the bridge deck as well as the main structure. Unfortunately, In the Slovak Republic, no such bridges have been built as of yet (2020). At Technical University of Kosice, Department of Steel and Timber Structures, an extensive research regarding the steel shear connectors have been launched. Its goals are to bring new, easier for construction (due to prefabrication process), more resistant with even lower structural height, and more economical (due to lesser usage of materials and quick construction) geometrical solutions for composite steel concrete bridges as well as to open and popularize this solution for developers in the Slovak Republic. In this article, one of the new types is presented. It has a cross-section in a shape of a trapezoid, with holes in all its sides, except the bottom flange. Their purpose is to create concrete studs and secure full shear transmission with higher shear resistance, but they also serve to create space for transverse reinforcing bars. Its geometrical and material characteristics are closely specified. Results and process of push-out tests performed in Laboratory of Excellent Research onto three specimens are described and compared to results of finite element analysis simulation performed in Abaqus software.

Zeolites as Scaffolds for Metal Nanoclusters

This chapter critically reviews the studies related to structural and photophysical properties of metal clusters within zeolites matrices and summarizes the progress made in understanding the host-guest interactions. The goal is to provide useful insight into the nature of such interactions and experiments used in identifying the excited state dynamics and the reaction mechanisms leading to the emitting species. Especially interesting are the combined experimental and computational approaches used to elucidate the structures and electronic transition of clusters inside the cavity. Although a number of excellent research articles have been published in the last years they only cover rather specific areas like organic photochemistry, confinement, charge transfer, theoretical modeling or photostimulated luminescence.

Revitalization of Residential Buildings Dating Back to the Late 19th and Early 20th Century on the Example of “Willa Halina” in Sopot (Poland)

Residential buildings dating back to the late 19th and early 20th century constitute an important element of the urban composition of many European cities, often determining their overall spatial expression. These buildings often require revitalization and sometimes also reconstruction or extension. Such activities make it possible to restore historical buildings to their former glory, but also to create new architecture, inscribed in the context of the place, yet bearing witness to modern times. Revitalization of historically and architecturally valuable but technically degraded residential buildings is one of the important elements of maintaining and sometimes rebuilding the image of modern cities and their sustainable development. However, revitalization activities require solving many problems of conservational nature, especially issues related to preserving the authenticity of the existing tissue, ways of reconstructing lost elements, and connecting historical architecture with contemporary architecture. Historic residential buildings of Sopot, a city located in Poland on the shores of the Baltic Sea, dating back to the late 19th and early 20th century, provide excellent research material for such considerations. In the article, the historical center of Sopot was examined, with particular emphasis on the historic Willa Halina from 1896 located there, which was revitalized (according to the design of the author of the article). Using such research methods as analysis of historical source material (iconography), observation (operationalization of preserved historical objects), comparative analysis of contemporary investments, and analysis of the revitalization design of “Willa Halina”, an attempt was made to present spatial and technical solutions leading to the desired effects in the revitalization process. This work aims to show (on the example of Willa Halina in Sopot) the author’s method of revitalizing valuable, historical residential buildings, complying with international conservation standards, including the Venice Charter, adopted in 1964 by the Second International Congress of Architects and Technicians of Historical Monuments. The paper also aims to present spatial and technical solutions leading to desired effects in the revitalization process, consistent with the idea of sustainable development.

Zebrafish as a Model for the Study of Lipid-Lowering Drug-Induced Myopathies

Drug-induced myopathies are classified as acquired myopathies caused by exogenous factors. These pathological conditions develop in patients without muscle disease and are triggered by a variety of medicaments, including lipid-lowering drugs (LLDs) such as statins, fibrates, and ezetimibe. Here we summarise the current knowledge gained via studies conducted using various models, such as cell lines and mammalian models, and compare them with the results obtained in zebrafish (Danio rerio) studies. Zebrafish have proven to be an excellent research tool for studying dyslipidaemias as a model of these pathological conditions. This system enables in-vivo characterization of drug and gene candidates to further the understanding of disease aetiology and develop new therapeutic strategies. Our review also considers important environmental issues arising from the indiscriminate use of LLDs worldwide. The widespread use and importance of drugs such as statins and fibrates justify the need for the meticulous study of their mechanism of action and the side effects they cause.