Voice Synthesis Improvement by Machine Learning of Natural Prosody.

Since the advent of modern computing, researchers have striven to make the human-computer interface (HCI) as seamless as possible. Progress has been made on various fronts, e.g.

Examination of Traditional Botnet Detection on IoT-Based Bots.

A botnet is a collection of Internet-connected computers that have been suborned and are controlled externally for malicious purposes. Concomitant with the growth of the Internet of Things (IoT), botnets have been expanding to use IoT devices as their attack vectors. IoT devices utilise specific protocols and network topologies distinct from conventional computers that may render detection techniques ineffective on compromised IoT devices.

Impact of Grinding and Sorting Particle Size on Phytochemical Yield in Leaf Extract.

The main objective of this study was to investigate the impact of grinding (pretreatment) with a pin mill on the crude extract yields of (Yang-Na) leaves. A factorial design in a completely randomized design was conducted to study the combinational effects of sieve sizes (1.0, 1.

Urban flooding resilience evaluation with coupled rainfall and flooding models: a small area in Kunming City, China as an example.

Climate change and increasing urbanization have contributed greatly to urban flooding, making it a global problem. The resilient city approach provides new ideas for urban flood prevention research, and currently, enhancing urban flood resilience is an effective means for alleviating urban flooding pressure. This study proposes a method to quantify the resilience value of urban flooding based on the `4R' theory of resilience, by coupling the urban rainfall and flooding model to simulate urban flooding, and the simulation results are used for calculating index weights and assessing the spatial distribution of urban flood resilience in the study area.

CovTiNet: Covid text identification network using attention-based positional embedding feature fusion.

Covid text identification (CTI) is a crucial research concern in natural language processing (NLP). Social and electronic media are simultaneously adding a large volume of Covid-affiliated text on the World Wide Web due to the effortless access to the Internet, electronic gadgets and the Covid outbreak. Most of these texts are uninformative and contain misinformation, disinformation and malinformation that create an infodemic.

Using the Cardiff model to reduce late-night alcohol-related presentations in regional Australia.

Introduction: The Cardiff model is a data sharing approach that aims to reduce the volume of intoxicated patients in emergency departments (EDs). This approach has not been tested in a rural setting.

Objective: This study assessed whether this approach would reduce the number of alcohol-associated presentations during high-alcohol hours (HAH) in a regional ED.

Physical Activity and Its Association With Body Mass Index: A Cross-Sectional Analysis in Middle-Aged Adults From 4 Sub-Saharan African Countries.

Background: This study aimed to explore association of self-reported physical activity domains of work, leisure, and transport-related physical activity and body mass index (BMI) in 9388 adult men and women from the Africa-Wits-INDEPTH partnership for Genomic (AWI-Gen) study in Africa. Africa-Wits-INDEPTH partnership for Genomic is a large, population-based cross-sectional cohort with participants from 6 sites from rural and urban areas in 4 sub-Saharan African countries.

Methods: A sex-stratified meta-analysis of cross-sectional data from men and women aged 29-82 years was used to assess the association of physical activity with BMI.

An integrated of fuzzy-WASPAS and E-FMEA methods for environmental risk assessment: a case study of petrochemical industry, Iran.

Due to the scope and volume of activities, the petrochemical industry has a high potential for risk to humans and the environment. This study aimed to evaluate the environmental risks caused by the ammonia and urea production process. To screen the risks identified in the follow-up phase, the process hazard analysis (PHA) was used.

Most common principal diagnoses assigned to Australian emergency department presentations involving alcohol use: a multi-centre study.

Objectives: Alcohol is the most widely consumed psychoactive substance in Australia and the consequences of alcohol consumption have enormous personal and social impacts. This study aimed to describe the principal diagnoses of emergency department (ED) presentations involving alcohol use in the previous 12 hours at eight hospitals in Victoria and the Australian Capital Territory, Australia.

Methods: Twelve months' data (1 July 2018 - 30 June 2019) were collected from eight EDs, including demographics, ICD-10 codes, hospital location and self-reported drinking in the preceding 12 hours.

Research on water resources environmental carrying capacity (WRECC) based on support-pressure coupling theory: A case study of the Guangdong-Hong Kong-Macao Greater Bay Area.

Water scarcity and water pollution problems are becoming increasingly serious in many regions of the world due to rapid socioeconomic development. Water resources environmental carrying capacity (WRECC), which embodies the attributes of social, economic, resource and environmental aspects, is usually considered as a significant metric to guide regional sustainable development. Most existing studies on WRECC mainly focus on conceptual discussions and evaluation methods, lacking a systematic insight into the theoretical connotations of WRECC and neglecting the interaction mechanisms within the WRECC system.

Assault-related injuries reported to police and treated by healthcare providers in the United States.

Research suggests that assault-related injuries known by the police significantly differ from those known by healthcare providers, but the magnitude and nature of these differences are poorly understood. To address this gap, our study examined the empirical differences between assault-related injuries reported to police and treated by healthcare providers. In June of 2021, we analyzed the National Crime Victimization Survey (1993-2019) to estimate the prevalence of police reporting and healthcare use among 5093 nonfatal victimizations that caused injury and were either reported to the police or treated by healthcare in the United States.

Out-of-pocket payments for treatment of COVID-19 in Iran.

Introduction: Out-of-pocket (OOP) is among the payment methods in Iran's health system. The present study aimed to examine the OOP treatment costs for patients with COVID-19 in Iran.

Methods: A descriptive-analytical, cross-sectional study was conducted in 2021.

A New Setup for the Measurement of Total Organic Carbon in Ultrapure Water Systems.

With the increasing demand for ultrapure water in the pharmaceutical and semiconductor industry, the need for precise measuring instruments for those applications is also growing. One critical parameter of water quality is the amount of total organic carbon (TOC). This work presents a system that uses the advantage of the increased oxidation power achieved with UV/O advanced oxidation process (AOP) for TOC measurement in combination with a significant miniaturization compared to the state of the art.

Developing Framework and Strategies for Capacity Building to Apply Evidence-Informed Health Policy-Making in Iran: Mixed Methods Study of SAHSHA Project.

Background: SASHA, which stands for "evidence-informed health policy-making (EIHP)" in Persian, is a national project to draw a roadmap for strengthening EIHP in Iran. As a part of SASHA, this research aimed to develop evidence-based and context-aware policy options for increasing the capacity of decision-makers to apply EIHP in Iran.

Methods: This was a qualitative study, which was informed by a literature review of pull efforts' capacity building programs.

Biometrics for Internet-of-Things Security: A Review.

The large number of Internet-of-Things (IoT) devices that need interaction between smart devices and consumers makes security critical to an IoT environment. Biometrics offers an interesting window of opportunity to improve the usability and security of IoT and can play a significant role in securing a wide range of emerging IoT devices to address security challenges. The purpose of this review is to provide a comprehensive survey on the current biometrics research in IoT security, especially focusing on two important aspects, authentication and encryption.

A novel D2D-MEC method for enhanced computation capability in cellular networks.

Device-to-device (D2D) communications and mobile edge computing (MEC) used to resolve traffic overload problems is a trend in the cellular network. By jointly considering the computation capability and the maximum delay, resource-constrained terminals offload parts of their computation-intensive tasks to one nearby device via a D2D connection or an edge server deployed at a base station via a cellular connection. In this paper, a novel method of cellular D2D-MEC system is proposed, which enables task offloading and resource allocation meanwhile improving the execution efficiency of each device with a low latency.

An improved NFC device authentication protocol.

Aimed at the security authentication problem between Near Field Communication (NFC) devices, this paper uses the technology of asymmetric encryption algorithm, symmetric encryption algorithm, hash function, timestamp and survival period to improve the confidentiality, performance and security of the protocol. The symmetric encryption algorithm encrypts the transmission content, while the asymmetric encryption algorithm encrypts the shared key. The whole authentication process is secure, and the key distribution is secure.

The evolution of strongly-held group identities through agent-based cooperation.

Identity fusion represents a strongly-held personal identity that significantly overlaps with that of a group, and is the current best explanation as to why individuals become empowered to act with extreme self-sacrifice for a group of non-kin. This is widely seen and documented, yet how identity fusion is promoted by evolution is not well-understood, being seemingly counter to the selfish pursuit of survival. In this paper we extend agent-based modelling to explore how and why identity fusion can establish itself in an unrelated population with no previous shared experiences.

The effect of microorganisms on the biomodification of montan resin from lignite.

Montan resin (MR) is an industrial by-product or solid waste generated during the production of refined montan wax and is not typically reused. In this paper, a bio-modification method using three strains of microorganisms, (AV), (PA), and (PC), was studied to promote the performance and bio-function of MR so that MR could be recycled. MR can be degraded by these three microorganisms, and their weight loss rates were similar over the treatment period of 15 days.

Visualisation and optimisation of alcohol-related hospital admissions ICD-10 codes in Welsh e-cohort data.

Introduction: The excessive consumption of alcohol is detrimental to long term health and increases the likelihood of hospital admission. However, definitions of alcohol-related hospital admission vary, giving rise to uncertainty in the effect of alcohol on alcohol-related health care utilization.

Objectives: To compare diagnostic codes on hospital admission and discharge and to determine the ideal combination of codes necessary for an accurate determination of alcohol-related hospital admission.

Alcohol affordability: implications for alcohol price policies. A cross-sectional analysis in middle and older adults from UK Biobank.

Background: Increasing the price of alcohol reduces alcohol consumption and harm. The role of food complementarity, transaction costs and inflation on alcohol demand are determined and discussed in relation to alcohol price policies.

Methods: UK Biobank (N = 502,628) was linked by region to retail price quotes for the years 2007 to 2010.

How to construct low-altitude aerial image datasets for deep learning.

The combination of Unmanned Aerial Vehicle (UAV) technologies and computer vision makes UAV applications more and more popular. Computer vision tasks based on deep learning usually require a large amount of task-related data to train algorithms for specific tasks. Since the commonly used datasets are not designed for specific scenarios, in order to give UAVs stronger computer vision capabilities, large enough aerial image datasets are needed to be collected to meet the training requirements.

Association Between COVID-19 Lockdown Measures and Emergency Department Visits for Violence-Related Injuries in Cardiff, Wales.

This study investigates emergency department visits for violence-related injuries occurring at home and outside the home in Cardiff, Wales, before and after COVID-19 lockdown measures were instituted in March 2020.

Dual residual convolutional neural network (DRCNN) for low-dose CT imaging.

The excessive radiation doses in the application of computed tomography (CT) technology pose a threat to the health of patients. However, applying a low radiation dose in CT can result in severe artifacts and noise in the captured images, thus affecting the diagnosis. Therefore, in this study, we investigate a dual residual convolution neural network (DRCNN) for low-dose CT (LDCT) imaging, whereby the CT images are reconstructed directly from the sinogram by integrating analytical domain transformations, thus reducing the loss of projection information.