Academic literature on the topic 'Er Network Systems In Uganda'

One of the most important tasks of a living organism is to maintain its genetic integrity with respect to stress. Endoplasmic reticulum (ER) has a crucial role in sensing cellular homeostasis by controlling metabolism, proteostasis, and several signaling processes. ER stressors can induce autophagy-dependent survival; however excessive level of stress results in apoptotic cell death. Although many molecular components of these networks have already been discovered, the analysis of the dynamical features of the regulatory network of life-or-death decision is still lacking. Our goal was to incorporate both theoretical and molecular biological techniques to explore the autophagy-apoptosis crosstalk under ER stress. Using various levels of different ER stressors we confirmed that the control network always generated an evidently detectable autophagy-dependent threshold for apoptosis activation. We explored the features of this threshold by introducing both autophagy activators and inhibitors, and transient treatment with excessive level of ER stressor was also performed. Our experimental data were also supported by a stochastic approach. Our analysis suggests that even if the switch-like characteristic of apoptosis activation is hardly seen on population level the double negative feedback loop between autophagy and apoptosis inducers introduces bistability in the control network.

Summary The Systems Biological Graphical Notation (SBGN) is an international community effort for standardized graphical representations of biological pathways and networks. The goal of SBGN is to provide unambiguous pathway and network maps for readers with different scientific backgrounds as well as to support efficient and accurate exchange of biological knowledge between different research communities, industry, and other players in systems biology. Three SBGN languages, Process Description (PD), Entity Relationship (ER) and Activity Flow (AF), allow for the representation of different aspects of biological and biochemical systems at different levels of detail.The SBGN Entity Relationship language (ER) represents biological entities and their interactions and relationships within a network. SBGN ER focuses on all potential relationships between entities without considering temporal aspects. The nodes (elements) describe biological entities, such as proteins and complexes. The edges (connections) provide descriptions of interactions and relationships (or influences), e.g., complex formation, stimulation and inhibition. Among all three languages of SBGN, ER is the closest to protein interaction networks in biological literature and textbooks, but its well-defined semantics offer a superior precision in expressing biological knowledge.

As the Internet of Things technology develops rapidly, cyber-physical systems (CPSs) have provided critical technologies in the industrial field. A smart grid is a typical application of the CPS, which is formed by the coupling of the power network and communication network. In general, the two networks are heterogeneous. Considering the characteristics of the power network, the ordinary percolation network model is not suitable for the network carrying physical flow. Therefore, we propose an interdependent network model with a load. That is, nodes in the physical network have loaded. Then, we research the security of CPS under the multi-load mode. The rule for node failure is different from the percolation model. When a node’s load exceeds its capacity, the node fails. Through the theoretical analysis, we obtained the iterative equation of the percolation threshold and analyzed it through simulation experiments. We adopt both linear and nonlinear capacity models. It is found that appropriately increasing the average degree of ER network can improve its ability to resist attacks. In contrast, the power exponent of the SF network has less influence on the critical value of network percolation. In addition, we found that increasing the capacity parameter in the linear capacity model can improve the robustness of the network, where the variation of the ER-ER network is more evident than that of the SF-SF network. Increasing the capacity parameter in the nonlinear capacity model can significantly increase the network’s ability to resist attacks. However, due to the increase in economical cost, we can improve the network’s reliability by increasing the node capacity while controlling the cost.

Hybrid power generation system (HPGS) is an active research area, which is in need of a continuous improvement. It represents the best solution for the most complex problems facing the world in the last decades. These problems are known as the shortage of energy, or lack of electricity, which logically are the results of the continuous increasing demand. Therefore, the researchers do their best to overcome all expected roadblocks facing the development, where the most applicable solutions to solve these problems are introduced. In this paper, the HPGS includes; wind turbine (WT), photovoltaic (PV), storage battery (SB), gas turbine (GT), and utility grid (UG). The GT of this system is fueled directly from the natural gas distribution network considering all operational conditions of it, which may be affected by fueling the natural gas for the GT. So, the natural gas distribution network is becoming an important component of the HPGS, and it is included in the HPGS for the first time. Multi meta-heuristic optimization techniques are applied to obtain the components sizing of this system, where cuckoo search algorithm (CSA), firefly algorithm (FA), and flower pollination algorithm (FPA) have been applied. Therefore, this paper introduces a new contribution not only to the new configuration of the HPGS, but also in applying the new optimization techniques as solving tools. The output results are compared to show the effectiveness and the superiority of the applied techniques as well as extract a recommendation for the best solving technique.

The successful development of a new generation of technology incorporating an electro-rheological (ER) fluid requires three principal ingredients; advanced ER fluid, reliable mechanical mechanism and efficacious control scheme. This paper discusses the third one. After describing general, but stringent requirements for semiactive or active control systems featuring the ER fluid, feedback control characteristics of some specific ER devices are presented; a frequency-dependent feedback control of mode shape in a smart flexible structure containing the ER fluid, an optimal control of vibration in a semi-active suspension installed with ER shock absorbers, and a neural network control of position in a hydraulic ER valve-cylinder system.

Abstract The recent Ebola virus outbreak in West Africa clearly demonstrated the critical role of laboratory systems and networks in responding to epidemics. Because of the huge challenges in establishing functional laboratories at all tiers of health systems in developing countries, strengthening specimen referral networks is critical. In this review article, we propose a platform strategy for developing specimen referral networks based on 2 models: centralized and decentralized laboratory specimen referral networks. These models have been shown to be effective in patient management in programs in resource-limited settings. Both models lead to reduced turnaround time and retain flexibility for integrating different specimen types. In Haiti, decentralized specimen referral systems resulted in a 182% increase in patients enrolling in human immunodeficiency virus treatment programs within 6 months. In Uganda, cost savings of up to 62% were observed with a centralized model. A platform strategy will create a network effect that will benefit multiple disease programs.

In this paper, the reliability of data transmission in social networks is thoroughly studied and analyzed using wireless sensor network topology technology. This paper, based on the introduction of sensor network reliability analysis-related technology, combined with the characteristics, and needs of the sensor network itself, focuses on the study of the reliability analysis of the sensor network under the state of perturbation scheme. Based on the idea of making full use of data changes to respond to the sensor state, this paper takes the actual monitoring data of the wireless sensor network as the research object, selects the temporal correlation and spatial correlation of the measured environmental data as the reliability index by extracting the features of the wireless sensor network data, and proposes the Evidential reasoning rule- (ER-) based wireless sensor network data reliability assessment model based on Evidential reasoning rule (ER) is proposed. The data are mined, analyzed, and quantified from the perspective of content popularity, and the interest indicators of nodes on data under content popularity are analyzed to derive stable interest quantification values. Combined with the network properties, i.e., node autoassembly community, we analyze the data dissemination characteristics of social networks in wireless sensor network topology environment and derive the upper and lower bounds of data transmission capacity under node interest-driven and its variation on network performance. Social relationships among nodes affected by social attributes are considered; in turn, the data forwarding behavior of nodes is modeled using data transmission probability and data reception probability; finally, the data forwarding process is analyzed and a closed expression for the average end-to-end transmission capacity is derived in turn.

Extracellular/intracellular stimuli can influence eukaryotic cell function through organelles that regulate critical signaling pathways. The endoplasmic reticulum (ER), for example, impacts cellular processes including protein synthesis, folding and secretion; amino acid transport; apoptosis; cell proliferation; lipid synthesis across major cell types in response to stimuli such as accumulation of misfolded proteins and glucose deprivation. Dysregulated signaling pathways underlying the ER-mediated processes mentioned above have been linked to disease conditions such as diabetes, obesity, and Alzheimer's disease. Our current understanding, however, lacks a detailed network view that integrates organelle-mediated pathway dysregulation with cellular processes and disease pathogenesis. In this report, we introduce an integrative network biology approach that combines ER-stress response pathways with basic cellular processes using data from peer-reviewed literature. As an example, we apply our systems biology approach to study the role of ER stress in pancreatic β cells under obese diabetic conditions, generate testable hypotheses, and provide novel insights into β-cell pathogenesis.

Summary The Systems Biological Graphical Notation (SBGN) is an international community effort for standardized graphical representations of biological pathways and networks. The goal of SBGN is to provide unambiguous pathway and network maps for readers with different scientific backgrounds as well as to support efficient and accurate exchange of biological knowledge between different research communities, industry, and other players in systems biology. Three SBGN languages, Process Description (PD), Entity Relationship (ER) and Activity Flow (AF), allow for the representation of different aspects of biological and biochemical systems at different levels of detail.The SBGN Activity Flow language represents the influences of activities among various entities within a network. Unlike SBGN PD and ER that focus on the entities and their relationships with others, SBGN AF puts the emphasis on the functions (or activities) performed by the entities, and their effects to the functions of the same or other entities. The nodes (elements) describe the biological activities of the entities, such as protein kinase activity, binding activity or receptor activity, which can be easily mapped to Gene Ontology molecular function terms. The edges (connections) provide descriptions of relationships (or influences) between the activities, e.g., positive influence and negative influence. Among all three languages of SBGN, AF is the closest to signaling pathways in biological literature and textbooks, but its well-defined semantics offer a superior precision in expressing biological knowledge.

The main purpose of this thesis is to test a communications solution for the second to largest refugee settlement in the world, Bidi Bidi. A solution where it is possible to inform the refugees with necessary information, for example that the water at a specific location is currently contaminated or that food is provided at another location. The idea is to use nRF24L01+ modules which operate in the 2.4 GHz frequency band and send information through various ways. This includes turning LEDs' on and off, sending text Strings and streaming audio. The results showed that the modules are too unreliable for a refugee settlement. They also showed that it is not possible to send other types' of data while streaming audio, but there could be workarounds. It is clear that more knowledge and further investigations are needed.

The multidimensional open epistemological active network MOGAN is the basis for the transition to a qualitatively new level of creating logical artificial intelligence. Mivar databases and rules became the foundation for the creation of MOGAN. The results of the analysis and generalization of data representation structures of various data models are presented: from relational to "Entity — Relationship" (ER-model). On the basis of this generalization, a new model of data and rules is created: the mivar information space "Thing-Property-Relation". The logic-computational processing of data in this new model of data and rules is shown, which has linear computational complexity relative to the number of rules. MOGAN is a development of Rule - Based Systems and allows you to quickly and easily design algorithms and work with logical reasoning in the "If..., Then..." format. An example of creating a mivar expert system for solving problems in the model area "Geometry"is given. Mivar databases and rules can be used to model cause-and-effect relationships in different subject areas and to create knowledge bases of new-generation applied artificial intelligence systems and real-time mivar expert systems with the transition to"Big Knowledge". The textbook in the field of training "Computer Science and Computer Engineering" is intended for students, bachelors, undergraduates, postgraduates studying artificial intelligence methods used in information processing and management systems, as well as for users and specialists who create mivar knowledge models, expert systems, automated control systems and decision support systems. Keywords: cybernetics, artificial intelligence, mivar, mivar networks, databases, data models, expert system, intelligent systems, multidimensional open epistemological active network, MOGAN, MIPRA, KESMI, Wi!Mi, Razumator, knowledge bases, knowledge graphs, knowledge networks, Big knowledge, products, logical inference, decision support systems, decision-making systems, autonomous robots, recommendation systems, universal knowledge tools, expert system designers, logical artificial intelligence.

The artifacts developed over several ages, such as libraries, encyclopedias, and databases, show the cultural evolution of information systems. Compiling, organizing and visualizing information is a task carried out by mankind for thousands of years. The added difficulty in effectively communicating information in various sectors and services of our society reveals that an efficient communication of information is of the utmost importance in the current network society. The glut of information is directly related to the fact that the information that we are exposed, is not subject to a filtering and organization process. This reveals an urgency to develop strategies that not only prioritize the organization and searching, but also increase the efficiency of the communication process, in order to promote an efficient framework in the user’s cognitive and perceptual field. Therefore the task of designing complex information systems in an accessible manner, currently represents an important goal and an imperative task of the Design/er (Wurman, 2001), (Bonsiepe, 1997; 2000) (Rheingold, 2005), (Thackara, 2006), (Wright, 2008), (Castells, 2010), (Gleick, 2011), (Lima, 2011; 2014), (Meirelles, 2013), (Börner, 2010; 2014; 2015). The publication and the querying of articles, papers, journals, books, are an integral part of the research process. However, the querying and information visualization process in a scientific academic repository often proves to be a hard and inefficient task, because the wide range of results hardly fits in the user’s specific subject. However, if we equate that the knowledge objects are accessed by a significant number of users with a specific interest in a topic, and in the course of their research, each user handles a significant amount of results. It is then possible to consider the existence of a hierarchical and relational structure of evidences that emerges from the relationship established between the users, their specific interests and knowledge in a topic and the querying performed. Therefore, it is fundamental to consider the user’s experience and the leading role that it represents in the information filtering process.This paper aims to present key insights on the information glut problematic and proposes a new approach/system applied to the academic scientific repositories. A collaboration system is designed, in order to filter and visualize the rating flows based in the user’s experience, instead of the usual citation "object" centered approach. The focus of this work is to describe one part of the system, that is the experimental implementation of an interactive hierarchical structure.DOI: http://dx.doi.org/10.4995/IFDP.2016.3308

Emergency Relief (ER) is a Department of Social Services (DSS) funded program, delivered by 197 community organisations (ER Providers) across Australia, to assist people facing a financial crisis with financial/material aid and referrals to other support programs. ER has been playing this important role in Australian communities since 1979. Without ER, more people living in Australia who experience a financial crisis might face further harm such as crippling debt or homelessness. The Emergency Relief National Coordination Group (NCG) was established in April 2020 at the start of the COVID-19 pandemic to advise the Minister for Families and Social Services on the implementation of ER. To inform its advice to the Minister, the NCG partnered with the Institute for Governance at the University of Canberra to conduct research to understand the issues and challenges faced by ER Providers and Service Users in local contexts across Australia. The research involved a desktop review of the existing literature on ER service provision, a large survey which all Commonwealth ER Providers were invited to participate in (and 122 responses were received), interviews with a purposive sample of 18 ER Providers, and the development of a program logic and theory of change for the Commonwealth ER program to assess progress. The surveys and interviews focussed on ER Provider perceptions of the strengths, weaknesses, future challenges, and areas of improvement for current ER provision. The trend of increasing case complexity, the effectiveness of ER service delivery models in achieving outcomes for Service Users, and the significance of volunteering in the sector were investigated. Separately, an evaluation of the performance of the NCG was conducted and a summary of the evaluation is provided as an appendix to this report. Several themes emerged from the review of the existing literature such as service delivery shortcomings in dealing with case complexity, the effectiveness of case management, and repeat requests for service. Interviews with ER workers and Service Users found that an uplift in workforce capability was required to deal with increasing case complexity, leading to recommendations for more training and service standards. Several service evaluations found that ER delivered with case management led to high Service User satisfaction, played an integral role in transforming the lives of people with complex needs, and lowered repeat requests for service. A large longitudinal quantitative study revealed that more time spent with participants substantially decreased the number of repeat requests for service; and, given that repeat requests for service can be an indicator of entrenched poverty, not accessing further services is likely to suggest improvement. The interviews identified the main strengths of ER to be the rapid response and flexible use of funds to stabilise crisis situations and connect people to other supports through strong local networks. Service Users trusted the system because of these strengths, and ER was often an access point to holistic support. There were three main weaknesses identified. First, funding contracts were too short and did not cover the full costs of the program—in particular, case management for complex cases. Second, many Service Users were dependent on ER which was inconsistent with the definition and intent of the program. Third, there was inconsistency in the level of service received by Service Users in different geographic locations. These weaknesses can be improved upon with a joined-up approach featuring co-design and collaborative governance, leading to the successful commissioning of social services. The survey confirmed that volunteers were significant for ER, making up 92% of all workers and 51% of all hours worked in respondent ER programs. Of the 122 respondents, volunteers amounted to 554 full-time equivalents, a contribution valued at $39.4 million. In total there were 8,316 volunteers working in the 122 respondent ER programs. The sector can support and upskill these volunteers (and employees in addition) by developing scalable training solutions such as online training modules, updating ER service standards, and engaging in collaborative learning arrangements where large and small ER Providers share resources. More engagement with peak bodies such as Volunteering Australia might also assist the sector to improve the focus on volunteer engagement. Integrated services achieve better outcomes for complex ER cases—97% of survey respondents either agreed or strongly agreed this was the case. The research identified the dimensions of service integration most relevant to ER Providers to be case management, referrals, the breadth of services offered internally, co-location with interrelated service providers, an established network of support, workforce capability, and Service User engagement. Providers can individually focus on increasing the level of service integration for their ER program to improve their ability to deal with complex cases, which are clearly on the rise. At the system level, a more joined-up approach can also improve service integration across Australia. The key dimensions of this finding are discussed next in more detail. Case management is key for achieving Service User outcomes for complex cases—89% of survey respondents either agreed or strongly agreed this was the case. Interviewees most frequently said they would provide more case management if they could change their service model. Case management allows for more time spent with the Service User, follow up with referral partners, and a higher level of expertise in service delivery to support complex cases. Of course, it is a costly model and not currently funded for all Service Users through ER. Where case management is not available as part of ER, it might be available through a related service that is part of a network of support. Where possible, ER Providers should facilitate access to case management for Service Users who would benefit. At a system level, ER models with a greater component of case management could be implemented as test cases. Referral systems are also key for achieving Service User outcomes, which is reflected in the ER Program Logic presented on page 31. The survey and interview data show that referrals within an integrated service (internal) or in a service hub (co-located) are most effective. Where this is not possible, warm referrals within a trusted network of support are more effective than cold referrals leading to higher take-up and beneficial Service User outcomes. However, cold referrals are most common, pointing to a weakness in ER referral systems. This is because ER Providers do not operate or co-locate with interrelated services in many cases, nor do they have the case management capacity to provide warm referrals in many other cases. For mental illness support, which interviewees identified as one of the most difficult issues to deal with, ER Providers offer an integrated service only 23% of the time, warm referrals 34% of the time, and cold referrals 43% of the time. A focus on referral systems at the individual ER Provider level, and system level through a joined-up approach, might lead to better outcomes for Service Users. The program logic and theory of change for ER have been documented with input from the research findings and included in Section 4.3 on page 31. These show that ER helps people facing a financial crisis to meet their immediate needs, avoid further harm, and access a path to recovery. The research demonstrates that ER is fundamental to supporting vulnerable people in Australia and should therefore continue to be funded by government.