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This study introduces a novel approach for integrating a compact mechanism into the Marine Predator Algorithm (MPA), subsequently proposing innovative parallel and communication strategies. The synergistic combination of these methodologies substantially augments the global search efficiency and accelerates the convergence rate of the original MPA. The paper culminates in presenting an enhanced version of the Marine Predator Algorithm, termed PCMPA, which leverages compact parallel technology. The performance of PCMPA, alongside a range of comparative algorithms, is rigorously evaluated using the CEC2013 benchmark test functions. These comparative algorithms encompass recent variants of MPA, PSO, DE, and other newly developed algorithms. Evaluation results reveal that PCMPA outperforms its counterparts in a more extensive array of test functions. To corroborate PCMPA's efficacy in real-world scenarios, the algorithm is applied to parameter optimization in Backpropagation neural network (BNN) and targeted engineering optimization challenges. This application demonstrates that PCMPA consistently achieves enhanced performance in practical implementations. • The study presents a novel variant of the Marine Predators Algorithm, dubbed PCMPA. • The paper benchmarks PCMPA against other Marine Predators Algorithm variants and other Algorithms. • The research applies PCMPA to optimize parameters of BNNs and to tackle engineering optimization challenges. [ABSTRACT FROM AUTHOR]

A recent engineering study conducted at Pohang University of Science and Technology (POSTECH) in South Korea has developed an automated needle insertion system for eye surgery that enhances precision. The system utilizes a vacuum applanation pad to fixate and flatten the corneal tissue, minimizing tissue deformation and improving needle positioning accuracy. The study achieved precise needle positioning within the corneal tissue without relying on real-time optical coherence tomography feedback. This research has potential implications for deep anterior lamellar keratoplasty (DALK) procedures. [Extracted from the article]

Researchers from the Kyushu Institute of Technology have conducted a study on the friction between intravascular devices and vascular biomodels. The study aims to improve the safety and optimization of medical devices used in endovascular treatments. The researchers emphasize the need for a deeper understanding of vascular biotribology and the development of standardized methods for evaluating friction. The study provides an overview of experimental conditions such as sample shape, sliding speed, contact pressure, lubricant, materials, and temperature. The full research article can be accessed for free through the provided link. [Extracted from the article]

Researchers from Jawaharlal Nehru University in New Delhi, India have developed a new biosensor called the Gate All Around Engineered Gallium Nitride Field Effect Transistor (GAAE-GANFET) for label-free biosensing applications. The biosensor incorporates various device engineering techniques, such as channel engineering, gate engineering, and oxide engineering, to enhance its performance. The researchers evaluated the biosensor's viability using an antigen and an antibody from the Avian Influenza virus and DNA as target biomolecules, and found that the biosensor demonstrated significantly improved biosensing capabilities. This research has been peer-reviewed and published in the ECS Journal of Solid State Science and Technology. [Extracted from the article]

Researchers at Central South University of Forestry and Technology in Changsha, People's Republic of China, have developed a method to improve the photocatalytic activity of carbon nitride for the degradation of tetracycline, a common antibiotic pollutant in Dongting Lake. By using formic acid to create nitrogen defective carbon nitride, the researchers were able to achieve a degradation rate of 95.1% in 60 minutes, compared to conventional carbon nitride. The study also confirmed the ecological safety of the repaired water samples and the alleviation of antibiotic toxicity to legume growth. This research provides a basis for the development of defective carbon nitride for water body restoration in Dongting Lake. [Extracted from the article]

A report from researchers at Chaudhary Charan Singh University in Meerut, India discusses the use of engineered materials, such as composites, polymers, and copolymers, in achieving a sustainable environment. The unique properties of carbon and silver nanoparticles, including antimicrobial and conducting abilities, make them suitable for a wide range of applications in various industries. The researchers highlight the potential for creating novel composite materials with enhanced electrical, thermal, antimicrobial, antistatic, and antibiotic effects. The paper emphasizes the global applications of these nanomaterials. The research has been peer-reviewed and can be accessed through a DOI link provided. [Extracted from the article]

A recent study led by researchers at Washington University in St. Louis analyzed global ambient particulate matter (PM) to understand the health impacts of trace elements like lead and arsenic. The study found that elevated levels of trace elements in the air, particularly arsenic, pose significant health risks, especially in South and Southeast Asia. The researchers identified potential contributors to elevated trace element concentrations, such as informal lead-acid battery recycling and coal-fired brick kilns. The study also highlighted the need for consistent monitoring of PM elemental composition in urban areas worldwide to inform targeted interventions and safeguard public health. [Extracted from the article]

A recent study conducted by researchers at Changchun University of Science and Technology in China has proposed a new type of absolute photoelectric encoder based on a position-sensitive detector (PSD). This encoder design breaks from traditional methods by utilizing a continuous and transparent code track, resulting in a smaller size, high angle measurement accuracy, and ease of engineering. The experimental results demonstrate that the encoder achieves miniaturization, simple installation and adjustment, and high resolution and accuracy. This research provides valuable insights into the development of electronics and engineering in the field of encoders. [Extracted from the article]

Researchers at Ningbo University in China have developed a model called SAM-Att for the automatic segmentation of the left ventricle in echocardiography. The SAM-Att model utilizes deep learning techniques and an attention module to achieve accurate segmentation of the left ventricle. The model achieved a dice similarity coefficient of 94.49% and a hausdorff distance of 3.505 mm on the test set, outperforming other SAM-related models. This research provides valuable insights into the application of deep learning in medical imaging for diagnosing heart diseases. [Extracted from the article]

Researchers at Penn State University have developed an online curriculum and hands-on simulation training program to reduce complications associated with placing central line catheters. The training, which was implemented in 2022, significantly decreased the rates of mechanical issues, infections, and blood clots compared to previous years. The researchers are also applying the training framework to other procedures with high complication rates. The study, published in the Journal of Surgical Education, provides evidence that this approach can improve clinical education and practice. [Extracted from the article]

A recent study conducted by researchers from the Icahn School of Medicine at Mount Sinai in New York City explores the use of advanced deep learning algorithms for magnetic resonance imaging (MRI) segmentation. Accurate MRI segmentation is crucial for diagnosing abnormalities and planning treatments, but traditional supervised learning techniques require a large amount of annotated data. The study reviews state-of-the-art algorithms that utilize a limited number of annotated samples, including self-supervised learning, generative models, few-shot learning, and semi-supervised learning. The researchers also discuss future directions in the field, such as contrastive language-image pretraining, to further improve image segmentation with limited labels. [Extracted from the article]

A recent study conducted by researchers at Manipal Academy of Higher Education in India has developed a new approach to enhance precision in medical imaging. The study focuses on the detection of fiducial markers in neuroimaging, which are crucial reference points for accurate spatial alignment during image registration. The researchers propose a model that addresses challenges in marker placement and variability during MRI scanning, ensuring reliable localization for subsequent analysis. The model utilizes a 3D Convolutional Neural Network (CNN) and achieved exceptional accuracy and sensitivity in detecting fiducial points. The study concludes that this algorithm has the potential to improve accuracy and efficiency in neuroimaging studies. [Extracted from the article]

A recent report discusses research findings on circuits and systems from the 2022 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS). The conference, which focused on the theme of "Building a Fully-connected AIoT World," was held in Shenzhen, China, as a hybrid event due to COVID-19 and travel restrictions. The special issue of the IEEE Open Journal of Circuits and Systems features selected papers from the conference. The research aims to find multidisciplinary solutions to societal and industrial challenges. For more information, readers can access the article through the provided link. [Extracted from the article]

The global food crisis caused by population growth and declining food productivity due to climate change has led to the need for sustainable and nutritious food options. The Korea Advanced Institute of Science and Technology (KAIST) has proposed microbial food production as a solution. Microbial food, produced using microorganisms, contains a high amount of protein and emits less carbon dioxide compared to traditional livestock and crops. The researchers discuss various strategies and raw materials for producing microbial food in a sustainable way, highlighting the potential for a future where microbial foods are commonly consumed for their nutritional value and taste. [Extracted from the article]

The article focuses on a job opening at the Federal Communications Commission (FCC) suitable for recent engineering graduates, particularly those with knowledge of spectrum and RF, located in Washington, DC. Topics include job responsibilities such as propagation analysis, emission characteristics evaluation, and on-the-job training, with applications being accepted until July 2, 2024.

A recent study conducted by researchers at Chongqing University in China explores the use of artificial intelligence technology to improve the monitoring of anesthesia depth during surgery. The researchers developed a model that classified four levels of anesthesia states and extracted feature values from EEG signals. The model, which combined multiple machine learning algorithms and neural networks, outperformed existing algorithms in terms of accuracy and specificity. This research has the potential to enhance the accuracy and effectiveness of anesthesia monitoring, leading to improved patient outcomes. [Extracted from the article]

Researchers from the University of Catania in Italy have conducted a study on the performance analysis of Bluetooth Low Energy (BLE) 5.1 angle of arrival estimation using embedded radiation patterns on a 3 x 3 uniform rectangular array. The study aimed to address the hardware design requirements for locators in BLE 5.1, which include accurate and fast direction-finding algorithms while maintaining compactness. The researchers compared the conventional steering vector approach with a new embedded radiation pattern approach and found that the embedded radiation pattern approach outperformed the conventional approach in terms of accuracy. The study also highlighted that for a signal-to-noise ratio (SNR) greater than 20 dB, the accuracy did not depend on the number of snapshots used. This research was supported by the European Union through the Italian National Recovery and Resilience Plan. [Extracted from the article]

A recent study conducted by researchers from Yanshan University in China focuses on the risk assessment and countermeasures of logistics terminal distribution under public health emergencies. The study evaluates the risk of logistics terminal distribution and proposes corresponding countermeasures. It constructs a risk index system and uses the grey fuzzy comprehensive evaluation method to assess the risk index. The research aims to prevent logistics terminal distribution from being affected during public health emergencies and contributes to existing research in this field. For more information, readers can refer to the journal article published in Systems. [Extracted from the article]

Researchers from the University of Southern California have published a report on biomedical engineering, specifically focusing on the intersection of computational modeling and neurorehabilitation. The report discusses the findings from the Conference on Transformative Opportunities for Modeling in Neurorehabilitation, which brought together experts and trainees from around the world. The conference identified four key focus areas for modeling: Adaptation & Plasticity, Personalization, Human-Device Interactions, and Modeling 'In-the-Wild'. The researchers also emphasized the importance of capturing and curating appropriate data, creating multi-scale models, developing algorithms that extract information efficiently, and leveraging available sensors and data systems for model-driven treatments. The report concludes by mentioning three perspective papers prepared by attendees of the conference. [Extracted from the article]

A new report from the Faculty of Engineering in Baku, Azerbaijan explores the effect of conductivity changes in ischemic heart tissue on electrocardiography (ECG) readings. The study finds that current simulation models of ischemia, which only consider unhealthy transmembrane potential, may not accurately reflect the impact of conductivity changes on ECG results. By incorporating unhealthy conductivities in numerical studies, a more accurate simulation of ischemic heart tissue can be achieved. The research suggests that this approach should be considered in future studies to improve the accuracy of ECG diagnoses for ischemia. [Extracted from the article]

A report from Queen's University Belfast discusses the experience of delivering an online learning module for part-time software engineering students during the Covid-19 pandemic. The study compares on-campus learning with the shift to online learning and evaluates the impact of this shift on the students' perception and performance. The research concludes that the adaptation to online learning was successful and provides valuable insights into effective teaching practices in software engineering education. The findings aim to improve the preparation of future software professionals in the IT industry. [Extracted from the article]

A study conducted by researchers at Polytechnic University Cartagena in Spain explores the use of a digital model of tutoring, known as e-tutoring, to support small and medium enterprises (SMEs) in reducing their risks of failure. The model draws on the concept of relational administration (RA) and aims to enhance collaboration between public administrations and private professionals. The study found that SMEs in Spain are open to receiving selected forms of tutoring and highlights the importance of public administrations improving their capabilities for joint information provision and decision making through the use of information and communication technologies (ICTs). The findings have implications for the restructuring of public administrations and the co-design and implementation of e-government services. [Extracted from the article]

Researchers from Western Norway University of Applied Sciences have published a report on computational modeling and simulation of scaffolds for bone tissue engineering. The study focuses on the use of three-dimensional porous scaffolds as substitutes for traditional bone grafts in bone tissue engineering applications. The researchers highlight the importance of computational modeling in predicting the parameters involved in tissue healing and cell seeding procedures. They emphasize the need for appropriate finite element models and computational fluid dynamics models to create efficient designs of scaffolds for tissue engineering applications. The study provides insights for researchers in selecting the right models for different materials and flow regimes. [Extracted from the article]

A recent study conducted by researchers from the Romanian Academy explores the concept of zootechnical sciences in the context of sustainable development. The study highlights the historical development of zootechnical sciences and their relevance in the 21st century knowledge society. The authors discuss the integration of zootechnical sciences within the broader fields of biosciences and life sciences, providing concrete examples and evidence. The research also presents a new paradigm of integrated eco-bio-economic engineering, which aims to increase bio-food resources and address global food crises. For more information, readers can refer to the article "The Sustainable Development of Zootechnical Sciences in the Context of Life Sciences and the Perspectives of Zootechnical Engineers in the Innovative Concept of Eco-Bio-Economic Engineering" published in Scientific Papers Animal Science and Biotechnologies. [Extracted from the article]

This article explores the role of digital technologies in healthcare and the need for ongoing professional development among medical professionals. It acknowledges the low digital literacy among doctors and the challenges it presents to digital transformation in developed countries. The article emphasizes that a doctor's digital competence extends beyond technical skills and includes psychological and emotional aspects such as trust and culture. It highlights the importance of emotional intelligence in navigating the challenges of digitalization in healthcare, including increased workload and a shift in focus. The article also discusses specific digital skills that doctors can acquire, such as working with medical information systems and artificial intelligence, with the ultimate goal of developing doctors who are both digitally literate and emotionally stable. [Extracted from the article]

A report from the University of Wurzburg in Germany discusses research findings on engineering related to cyberbullying prevention. The study focuses on the need for prevention programs for younger school students who are increasingly becoming victims of cyberbullying. The researchers developed a virtual reality (VR) program that creates a personal space invasion experience to make the intrusion of cyberbullying tangible for victims. The program was tested in a laboratory study and a school workshop, showing promising results in triggering cognitive dissonance and empathy. The research provides empirical evidence and discusses implications for future developments in cyberbullying prevention. [Extracted from the article]

A study conducted by researchers at Bournemouth University in the United Kingdom explores the relationship between online streaming behaviors, cyber security practices, and the risk of IPTV infringement. The study found that security behaviors play a significant role in mediating the relationship between problematic internet use and IPTV risk-taking. The researchers suggest that interventions targeting cyber hygiene and promoting security behaviors may be more effective in combating audiovisual piracy. The study was funded by the European Commission Joint Research Centre, IDEAL CITIES, and the European Union. [Extracted from the article]

A recent study conducted in Roorkee, India, focused on the development of a hybrid framework for recognizing isolated sign language words from video. The researchers proposed a combination of a convolutional neural network (CNN) and an attention-based long-short-term memory (LSTM) neural network. Their methodology achieved an average accuracy of 84.65% and demonstrated computational efficiency compared to other methods. This research contributes to bridging the communication gap between individuals who are hard of hearing and those with good hearing. [Extracted from the article]

A study conducted by researchers at Sichuan University of Science and Engineering in China explores the design of smart senior care (SSC) product app interfaces for the elderly. The researchers use deep learning (DL) technology to optimize the app interface design, taking into consideration the cognitive characteristics and habits of the elderly. The study finds that the proposed model based on the deep-Q-network (DQN) algorithm significantly improves the user experience and satisfaction of the elderly, enhancing their ability to utilize smart products and improve their quality of life. The research provides valuable insights for further research and practice in related fields. [Extracted from the article]

A new study from Wuhan University of Science and Technology explores the co-evolution of epidemics and public opinion on social networks. The researchers propose a networked SIRS epidemic model with opinion dynamics to analyze the impact of community opinion on the spread of epidemics. By introducing stubborn communities, they identify conditions that ensure epidemics converge to a healthy state. The study also examines the influence of vaccination on epidemic spreading, finding that vaccination can delay the peak of infections and reduce the overall infection rate in communities. [Extracted from the article]

Researchers at Zhongkai University of Agriculture and Engineering in Guangzhou, China have developed a high-barrier coating for food packaging materials using oxidized cellulose nanofibrils (OCNFs) and chitosan. The coating solution, when applied to paper, significantly reduces the oxygen and water vapor transmission rates, making it an effective barrier against external elements. The study suggests that this OCNF/CTS-coated paper has great potential for use in food packaging materials, aligning with the growing demand for biodegradable and environmentally friendly packaging options. [Extracted from the article]

A recent study conducted by researchers at Southeast University in Nanjing, China, has developed a semi-supervised convolutional neural network for the automatic classification of white blood cells. Accurate classification of white blood cell subtypes is crucial for diagnosing blood diseases. The researchers found that their model achieved a high accuracy of 94.4% with only 500 labeled samples, demonstrating promising prospects for clinically useful solutions in detecting white blood cells based on blood cell images. This research provides valuable insights into the application of machine learning and emerging technologies in the field of hematology. [Extracted from the article]

A recent report from the Department of Electrical and Computer Engineering discusses the design and simulation of an edge compute architecture for an IoT-based clinical decision support system (CDSS). CDSS has transformed healthcare by utilizing technologies such as IoT, AI, and predictive analysis. The report highlights the drawbacks of cloud-based monitoring systems in healthcare and proposes the use of edge computing to overcome latency issues. The research demonstrates that edge computing reduces decision latency by approximately 87 times and network utilization by 1.5 times, showing its efficacy in implementing IoT-based CDSS. [Extracted from the article]

A new report from Guilin University of Electronic Technology in China presents research on mental workload and its impact on mental health. The study proposes a signal processing method that combines continuous wavelet transform (CWT) and cardiopulmonary coupling mapping (CPC) to classify mental load. The method, which uses a convolutional neural network, shows promising results in accurately assessing mental workload levels. The research suggests that this method has potential for mental workload classification and provides new ideas for monitoring mental health. [Extracted from the article]

A report from Wroclaw Medical University in Poland discusses research on tissue engineering and the use of biomimetic scaffolds. These scaffolds imitate native tissue and can provide a microenvironment for surrounding cells. The research highlights the potential of biomimetic scaffolds in tissue engineering and personalized medicine, particularly in the regeneration of skin and musculoskeletal systems. The report also emphasizes the need for extensive research to ensure the safety of biomimetic tissues and organs. [Extracted from the article]

A recent study conducted by researchers at Instituto Politecnico do Porto in Porto, Portugal, has developed an electrochemical genosensor for detecting a specific gene polymorphism associated with antidepressant treatment variability. The genosensor, based on gold electrodes, utilizes synthetic enzymatically labeled DNA probes to detect the polymorphism in the BDNF gene. The researchers found promising results with the sensor and are currently testing its applicability to real samples. This research provides valuable insights into the potential for personalized antidepressant treatments based on genetic information. [Extracted from the article]

A researcher from Universite Libre de Bruxelles has published new studies and findings in the area of electronics, specifically addressing the issue of plastic waste in the biopharmaceutical production sector. The research proposes a unique approach to standardize and optimize single-use assembly (SUA) drawings through digitization and structured representation. By utilizing graph convolutional networks (GCNs) to capture complex structural relationships, the research demonstrates a promising solution to reduce plastic waste in pharmaceutical assembly processes. The full research article can be accessed for free through the provided link. [Extracted from the article]

Researchers at Al al-Bayt University in Jordan have proposed a new two-parameter model called the unit Mirra distribution (UMD) for probability and statistics. The UMD is a modification of the Mirra distribution (MD) and has various statistical properties, such as moments, variance, and skewness. The researchers also provided reliability functions, distribution parameters estimation methods, and applications of the UMD to real-world data sets. The study concludes that the UMD can be a good alternative for modeling data sets related to infection times of kidney dialysis patients and trade share data. [Extracted from the article]

A study conducted by researchers at Huazhong University of Science and Technology in Wuhan, China, has developed a new method and apparatus for measuring magnetic induction intensity. The study focuses on the non-steady state nuclear magnetic resonance (NSS-NMR) phenomenon and its application in longitudinal time-varying magnetic fields (TVMF). The researchers have developed an experimental scheme and signal processing algorithms to accurately measure magnetic fields in a TVMF environment. The study concludes that the experimental results have verified the effectiveness of the proposed scheme and algorithms. [Extracted from the article]

Researchers at Saarland University are developing smart orthopedic implants that can monitor and promote bone healing. The implants are equipped with "artificial muscles" made from shape memory wires, which can alter the rigidity of the implant and provide micro-massaging to the fracture site. These smart implants can continuously monitor the healing process and send information to a smartphone, allowing doctors to assess the progress of bone repair. The team will be showcasing a prototype of the implant at the Hannover Messe exhibition. [Extracted from the article]

A study conducted by researchers at the University of Catania in Italy explores the engineering requirements for locators in Bluetooth Low Energy (BLE) 5.1. The study focuses on the performance analysis of Direction of Arrival (DoA) estimation in BLE, comparing the Conventional Steering Vector (CSV) approach with a new Embedded Radiation Pattern (ERP) approach. The research concludes that the ERP approach offers higher accuracy in DoA detection, particularly in scenarios with no loss and multipath. The study also highlights that for a signal-to-noise ratio (SNR) greater than 20 dB, the accuracy does not depend on the number of snapshots used, and faster computation is achieved with a single snapshot. [Extracted from the article]

A recent study conducted by researchers from the National Institute of Technology in Telangana, India, focuses on the challenge of extracting essential features from Electroencephalography (EEG) signals in the field of neuroscience. The researchers propose a Spatial Spiking Neural Network (SNN) as a supervised approach for classifying EEG data collected during concealed information tests. The SNN model achieves a peak accuracy of 90.15%, outperforming traditional classification algorithms. This research provides valuable insights into the potential applications of SNNs in EEG analysis and highlights their advantages in terms of temporal precision, event-driven processing, and low power consumption. [Extracted from the article]

A recent research paper from the Indian Institute of Engineering Science & Technology in West Bengal, India, explores various physicochemical methods for disinfecting contaminated surfaces to control the spread of infectious diseases. The paper discusses methods such as applying chemicals, UV-based processes, ionization radiation, self-disinfecting surfaces, no-touch room disinfection, and robotic disinfection. The use of UVC light combined with hydrogen peroxide has shown to be efficient and faster than other methods. The research concludes that surface disinfection using chemicals and UV radiation methods has been widely reported in the literature. [Extracted from the article]

A new study conducted by researchers at the Department of Management explores the consumption patterns and viewer experience of Over-The-Top (OTT) streaming services in Ernakulam City, India. OTT platforms, which distribute online audio-visual content, have become increasingly popular, especially during the COVID-19 epidemic. The study analyzes the OTT platforms used, the time spent on them, and the viewers' experience in terms of pricing, usability, and quality. This research provides valuable insights into the evolving digital entertainment landscape and its impact on consumer behavior. For more information, the full study can be accessed through the provided link. [Extracted from the article]

A report from the U.S. Food and Drug Administration (FDA) highlights the research on engineering in the field of medical extended reality (MXR) applications. MXR applications are rapidly evolving and have various uses in medical training and surgical planning. The report focuses on the connectivity and traffic models of MXR applications, emphasizing the importance of seamless connectivity, such as that promised by 5G, for users to interact with virtual content and collaborate. The proposed models correlate network traffic with specific MXR deployments and events, allowing for an application-specific evaluation of MXR connectivity risks. The research provides practical implementation approaches and considerations for modeling traffic patterns in diverse MXR applications. [Extracted from the article]

A recent report from Northeast Petroleum University in Heilongjiang, China discusses the use of ceramic nanoparticles in 3D printed scaffolds for tissue engineering. The study highlights the benefits of incorporating materials like hydroxyapatite, tricalcium phosphate, and bioactive glass in enhancing the functionality of engineered tissues. These nanoparticles have shown to increase mechanical strength and enable precise control over porosity and mechanical properties. The research concludes that these advancements in regenerative medicine offer promising avenues for future research in personalized and responsive tissue engineering solutions. [Extracted from the article]