Detecting Treatment Interference under the K-Nearest-Neighbors Interference Model

We propose a model of treatment interference where the response of a unit depends only on its treatment status and the statuses of units within its K-neighborhood. Current methods for detecting interference include carefully designed randomized experiments and conditional randomization tests on a set of focal units. We give guidance on how to choose focal units under this model of interference. We then conduct a simulation study to evaluate the efficacy of existing methods for detecting network interference. We show that this choice of focal units leads to powerful tests of treatment interference which outperform current experimental methods

The what and where of adding channel noise to the Hodgkin-Huxley equations

One of the most celebrated successes in computational biology is the Hodgkin-Huxley framework for modeling electrically active cells. This framework, expressed through a set of differential equations, synthesizes the impact of ionic currents on a cell's voltage -- and the highly nonlinear impact of that voltage back on the currents themselves -- into the rapid push and pull of the action potential. Latter studies confirmed that these cellular dynamics are orchestrated by individual ion channels, whose conformational changes regulate the conductance of each ionic current. Thus, kinetic equations familiar from physical chemistry are the natural setting for describing conductances; for small-to-moderate numbers of channels, these will predict fluctuations in conductances and stochasticity in the resulting action potentials. At first glance, the kinetic equations provide a far more complex (and higher-dimensional) description than the original Hodgkin-Huxley equations. This has prompted more than a decade of efforts to capture channel fluctuations with noise terms added to the Hodgkin-Huxley equations. Many of these approaches, while intuitively appealing, produce quantitative errors when compared to kinetic equations; others, as only very recently demonstrated, are both accurate and relatively simple. We review what works, what doesn't, and why, seeking to build a bridge to well-established results for the deterministic Hodgkin-Huxley equations. As such, we hope that this review will speed emerging studies of how channel noise modulates electrophysiological dynamics and function. We supply user-friendly Matlab simulation code of these stochastic versions of the Hodgkin-Huxley equations on the ModelDB website (accession number 138950) and http://www.amath.washington.edu/~etsb/tutorials.html.Comment: 14 pages, 3 figures, review articl

Time to question diabetes self-management support for Arabic-speaking migrants: exploring a new model of care

AIM: The objective of this study was to explore a new model for diabetes self-management support in Arabic-speaking migrants. METHODS: Two qualitative methods were used: face-to-face semi-structured individual interviews and focus groups. Interviews were audio-taped, transcribed verbatim and coded thematically. Arabic-speaking migrants with Type 2 diabetes were recruited from several primary, secondary and tertiary healthcare settings in metropolitan Melbourne, Australia. These settings were purposefully selected to obtain a diverse group of participants. Data collection continued until saturation was reached. This is the first study that involved members of Arabic-speaking communities in Australia in a formal process of consumer and public involvement to inform research design and recruitment in order to provide evidence for a new model of diabetes self-management for Arabic-speaking migrants. RESULTS: No self-management support was offered to Arabic-speaking migrants beyond the initial diagnosis period. Significant knowledge gaps and skills deficits in all self-management domains were evident. The provision of tailored self-management support was considered crucial. When asked about preferred structure and delivery modalities, a strong preference was reported for face-to-face storytelling interactions over telephone- or internet-based interventions. Gender-specific group education and self-management support sessions delivered by Arabic-speaking diabetes health professionals, lay peers or social workers trained in diabetes self-management were highly regarded. CONCLUSIONS: A patient and public involvement approach allows genuine engagement with Arabic-speaking migrants with diabetes. There is urgent need for a new model for self-management support among Arabic-speaking migrants. Findings yielded new recommendations for diabetes health professionals working with these migrant communities to support behaviour change

Bioinformatics: Computational Approaches for Genomics and Proteomics

Bioinformatics is a fast evolving field that combines biology, computer science, and statistics to analyze and comprehend enormous volumes of biological data. As a result of the introduction of high-throughput technologies like next-generation sequencing and mass spectrometry, genomic and proteomics research has generated enormous volumes of data, necessitating the development of computational tools to process and extract useful insights from these datasets. This presentation presents a survey of computational approaches in bioinformatics with a particular emphasis on their application to genomics and proteomics. The study of the entire genome is a topic covered in the discipline of genomics, which also includes genome annotation, assembly, and comparative genomics. Proteomics focuses on the investigation of proteins, including their identification, quantification, structural analysis, and functional characterization. Consequently, the importance of the area of bioinformatics has increased

STRATIFIED WATER-OIL-GAS FLOW THROUGH HORIZONTAL PIPES

Stratified three-phase flow through horizontal pipe has been studied experimentally. The fluids used in the system are water, kerosene, and air. A closed loop flow system, which composed of 0.051 m inside diameter and 4 m length test pipe, is designed with facilities for measuring flow rate, pressure drop and thickness of each phase. The effects of gas, liquid flow rates and water liquid ratio (WLR) have been experimentally observed. It was found that liquid (water, and oil) thickness decreased when the gas flow rate is increased with constant liquid flow rate, and increased when the liquid flow rate is increased at constant gas flow rate. Pressure drop increased when the gas and/or liquid flow rate is increased. Three equations have been formulated, using the experimental data of the present work, to predict liquid, water thickness and system pressure drop in stratified three-phase flow in horizontal pipe. High correlation coefficients are obtained for these equations. The experimental results are compared with the results obtained from three-phase model of Taital, Barnea, & Brill (1995). The comparison showed that the predicted data which obtained from three-phase flow model Taital et al. (1995) is in good agreement with experimental data

Computational Intelligence for Solving Complex Optimization Problems

Complex optimization issues may now be solved using computational intelligence (CI), which has shown to be a powerful and diverse discipline. Traditional optimization approaches frequently struggle to offer efficient and effective solutions because real-world situations are becoming more complicated. Evolutionary algorithms, neural networks, fuzzy systems, and swarm intelligence are just a few examples of the many methods that fall under the umbrella of computational intelligence and are inspired by both natural and artificial intelligence. This abstract examines how computational intelligence techniques are used to solve complicated optimization issues, highlighting their benefits, drawbacks, and most recent developments. In this, computational intelligence techniques provide a potent and adaptable solution for resolving challenging optimization issues. They are highly adapted for dealing with the non-linear connections, uncertainties, and multi-objective situations that arise in real-world problems. The limits of computational intelligence have recently been pushed by recent developments in hybrid techniques and metaheuristics, even if obstacles in algorithm design and parameter tuning still exist. Computational intelligence is anticipated to play an increasingly significant role in tackling complicated optimization issues and fostering innovation across a variety of disciplines as technology continues to advance

Novel Materials for High-Performance Energy Storage Devices

The realm of energy storage devices is witnessing a paradigm shift, driven by the exploration of novel materials. This review delves into the transformative potential of unconventional materials in enhancing the performance and versatility of energy storage systems. We discuss the potential of a hierarchical carbon material derived from E. coli cells, graphene oxide, and iron ion, underscoring its green credentials and promising attributes. Further, we highlight the transformative impact of paper as a material platform, tracing its evolution from a historical medium to a contemporary game-changer in microfluidic devices and microelectronics. The integration of electronics on paper reveals the potential of paper-based devices in diagnostics, MEMS, and energy storage. Collectively, these innovations illuminate the vast potential of avant-garde materials in revolutionising energy storage solutions, bridging the gap between cost-effectiveness and high performance. This review aims to provide a comprehensive overview of these groundbreaking innovations, fostering a deeper understanding of the future trajectory of energy storage research

Quantum Computing: Algorithms,Architectures, and Applications

Cryptography, optimization, simulation, and machine learning are just a few of the industries that might be completely transformed by quantum computing. This abstract gives a thorough introduction to quantum computing with an emphasis on its algorithms, architectures, and applications. In conclusion, this abstract offers an in-depth analysis of quantum computing, including its algorithms, structures, and applications. It highlights the revolutionary potential of quantum computing in tackling difficult issues that are beyond the scope of conventional computers, laying the groundwork for further research and understanding of this quickly developing topic

Data Privacy and Security in Cloud Computing Environments

The globe has adopted the cloud computing environment, which organizes data and manages space for data storage, processing, and access. This technical development has brought up questions regarding data security and privacy in cloud computing environments, though. The purpose of this abstract is to offer a thorough review of the issues, solutions, and future developments related to data privacy and security in cloud computing. Keeping data private and secure while it is being processed and stored in outside data centres is the main difficulty in cloud computing systems. The abstract discusses the dangers of insider threats, data breaches, and illegal access to sensitive information. It digs further into the legal and compliance criteria that businesses must follow in order to protect user data in the cloud. In result, data privacy and security in cloud computing environments remain critical concerns for organizations and individuals alike. In the survey the overview of how to use cloud storage globally and its challenges, solution and future innovation is well explained. It underscores the importance of robust encryption, access controls, user awareness, and emerging technologies in safeguarding data in the cloud. By addressing these concerns, organizations can leverage the power of cloud computing while maintaining the confidentiality, integrity, and availability of their data