Evaluating the investment performance of Japanese households: A comparison between professional financial advice and free financial advice.

Technological advancements have given rise to various sources of financial advice, prompting an investigation into how professional and free financial advice influence investment performance. Research lacks clarity on the impact of professional services on investment performance and overlooks the potential of free financial advice. This study, analyzing data from Rakuten Securities, a leading online-based security company in Japan, finds that investors prefer free financial advice from sources such as social media, mass media, personal networks, and individual decision-making.

Characteristics and outcomes of out-of-hospital-cardiac-arrest in rural and suburban areas of Sindh, Pakistan: A cross-sectional study.

Background: Despite extensive research on OHCA in urban centres worldwide, there is a significant gap in knowledge regarding these events in less urbanized regions, especially in Low-Middle-Income Countries (LMICs).

Aim: To determine the characteristics and outcomes of adult out-of-hospital cardiac arrest (OHCA) in rural and suburban districts of Sindh, Pakistan.

Methods: Data of OHCA patients (>18 years) was collected retrospectively from January 2020 to December 2022, from the medical records of district and tehsil hospitals of the province of Sindh Data analysis was performed using the Statistical Package Software for the Social Sciences (SPSS) Statistics 29.

A modified adaptive Kalman filter algorithm for the distributed underwater multi-target passive tracking system.

A modified adaptive Kalman filter (AKF) algorithm is proposed to make underwater multi-target tracking with uncertain measurement noise reliable. By utilizing the proposed AKF algorithm with three core points, including an adaptive fading factor, measurement noise covariance adjustment, and an adaptive weighting factor, the unknown measurement noise and state vector can be estimated with good accuracy and robustness. The practical trial data verify this algorithm, and it has proven superior to all traditional algorithms in this Letter based on the results that it reduces the estimated position RMSEs by at least 10.

Advanced federated ensemble internet of learning approach for cloud based medical healthcare monitoring system.

Medical image machines serve as a valuable tool to monitor and diagnose a variety of diseases. However, manual and centralized interpretation are both error-prone and time-consuming due to malicious attacks. Numerous diagnostic algorithms have been developed to improve precision and prevent poisoning attacks by integrating symptoms, test methods, and imaging data.

GroupFormer for hyperspectral image classification through group attention.

Hyperspectral image (HSI) data has a wide range of valuable spectral information for numerous tasks. HSI data encounters challenges such as small training samples, scarcity, and redundant information. Researchers have introduced various research works to address these challenges.

Epidemiology and outcomes of out of hospital cardiac arrest in Karachi, Pakistan - A longitudinal study.

Background: Out-of-hospital cardiac arrest (OHCA) is a major cause of morbidity and mortality globally, with survival outcomes remaining poor particularly in many low- and middle-income countries. We aimed to establish a pilot OHCA registry in Karachi, Pakistan to provide insights into OHCA patient demographics, pre-hospital and in-hospital care, and outcomes.

Methods: A multicenter longitudinal study was conducted from August 2015-October 2019 across 11 Karachi hospitals, using a standardized Utstein-based survey form.

Mycotoxins in food: Occurrence, health implications, and control strategies-A comprehensive review.

Mycotoxins are secondary metabolites produced by various filamentous fungi, including Aspergillus, Fusarium, Penicillium, Alternaria, Claviceps, Mucor, Trichoderma, Trichothecium, Myrothecium, Pyrenophora, and Stachybotrys. They can contaminate various plants or animal foods, resulting in a significant loss of nutritional and commercial value. Several factors contribute to mycotoxin production, such as humidity, temperature, oxygen levels, fungal species, and substrate.

Does Behavior Evolve First? Correlated Responses to Selection for Voluntary Wheel-Running Behavior in House Mice.

AbstractHow traits at multiple levels of biological organization evolve in a correlated fashion in response to directional selection is poorly understood, but two popular models are the very general "behavior evolves first" (BEF) hypothesis and the more specific "morphology-performance-behavior-fitness" (MPBF) paradigm. Both acknowledge that selection often acts relatively directly on behavior and that when behavior evolves, other traits will as well but most with some lag. However, this proposition is exceedingly difficult to test in nature.

Exploring the Biochemical and Nutra-Pharmaceutical Prospects of Some Thymus Species - A Review.

The Thymus genus includes various medicinal and aromatic species, cultivated worldwide for their unique medicinal and economic value. Besides, their conventional use as a culinary flavoring agent, Thymus species are well-known for their diverse biological effects, such as antioxidant, anti-fungal, anti-bacterial, anti-viral, anti-tumor, anti-inflammatory, anti-cancer, and anti-hypertensive properties. Hence, they are used in the treatment of fever, colds, and digestive and cardiovascular diseases.

A comprehensive review of mycotoxins: Toxicology, detection, and effective mitigation approaches.

Mycotoxins, harmful compounds produced by fungal pathogens, pose a severe threat to food safety and consumer health. Some commonly produced mycotoxins such as aflatoxins, ochratoxin A, fumonisins, trichothecenes, zearalenone, and patulin have serious health implications in humans and animals. Mycotoxin contamination is particularly concerning in regions heavily reliant on staple foods like grains, cereals, and nuts.

Cervical Pott's Disease Presenting As Quadriplegia in a Young Patient: A Case Report.

Cervical Pott's disease, a form of spinal tuberculosis (TB), is a significant concern in low- and middle-income countries (LMICs). Early detection and treatment are critical to preventing complications like vertebral collapse. Clinical and radiological features of cervical Pott's disease can resemble other spinal conditions, posing diagnostic challenges.

Development and Evaluation of Essential Oil-Based Nanoemulgel Formulation for the Treatment of Oral Bacterial Infections.

Prevalence of oral infections in diabetic patients is a health challenge due to persistent hyperglycemia. However, despite great concerns, limited treatment options are available. We therefore aimed to develop nanoemulsion gel (NEG) for oral bacterial infections based on essential oils.

A Neighborhood and Machine Learning-Enabled Information Fusion Approach for the WSNs and Internet of Medical Things.

Data redundancy or fusion is one of the common issues associated with the resource-constrained networks such as Wireless Sensor Networks (WSNs) and Internet of Things (IoTs). To resolve this issue, numerous data aggregation or fusion schemes have been presented in the literature. Generally, it is used to decrease the size of the collected data and, thus, improve the performance of the underlined IoTs in terms of congestion control, data accuracy, and lifetime.

An Industrial IoT-Based Blockchain-Enabled Secure Searchable Encryption Approach for Healthcare Systems Using Neural Network.

The IoT refers to the interconnection of things to the physical network that is embedded with software, sensors, and other devices to exchange information from one device to the other. The interconnection of devices means there is the possibility of challenges such as security, trustworthiness, reliability, confidentiality, and so on. To address these issues, we have proposed a novel group theory (GT)-based binary spring search (BSS) algorithm which consists of a hybrid deep neural network approach.

Deep Learning in Cancer Diagnosis and Prognosis Prediction: A Minireview on Challenges, Recent Trends, and Future Directions.

Deep learning (DL) is a branch of machine learning and artificial intelligence that has been applied to many areas in different domains such as health care and drug design. Cancer prognosis estimates the ultimate fate of a cancer subject and provides survival estimation of the subjects. An accurate and timely diagnostic and prognostic decision will greatly benefit cancer subjects.

3D convolutional neural networks-based multiclass classification of Alzheimer's and Parkinson's diseases using PET and SPECT neuroimaging modalities.

Background: Alzheimer's disease (AD) is a neurodegenerative brain pathology formed due to piling up of amyloid proteins, development of plaques and disappearance of neurons. Another common subtype of dementia like AD, Parkinson's disease (PD) is determined by the disappearance of dopaminergic neurons in the region known as substantia nigra pars compacta located in the midbrain. Both AD and PD target aged population worldwide forming a major chunk of healthcare costs.

Aflatoxin Biosynthesis, Genetic Regulation, Toxicity, and Control Strategies: A Review.

Aflatoxins (AFs) are highly toxic and cancer-causing compounds, predominantly synthesized by the species. AFs biosynthesis is a lengthy process that requires as minimum as 30 genes grouped inside 75 kilobytes (kB) of gene clusters, which are regulated by specific transcription factors, including , , and some general transcription factors. This paper summarizes the status of research on characterizing structural and regulatory genes associated with AF production and their roles in aflatoxigenic fungi, particularly and , and enhances the current understanding of AFs that adversely affect humans and animals with a great emphasis on toxicity and preventive methods.

A Lightweight Mutual Authentication and Privacy-preservation Scheme for Intelligent Wearable Devices in Industrial-CPS.

Industry 5.0 is the digitalization, automation and data exchange of industrial processes that involve artificial intelligence, Industrial Internet of Things (IIoT), and Industrial Cyber-Physical Systems (I-CPS). In healthcare, I-CPS enables the intelligent wearable devices to gather data from the real-world and transmit to the virtual world for decision-making.

Real-World Clinical Experience of Semaglutide in Secondary Care Diabetes: A Retrospective Observational Study.

Introduction: The glucagon-like peptide-1 receptor analogue (GLP-1RA) semaglutide is associated with improvements in glycaemia and cardiovascular risk factors in clinical trials. The aim of this study was to examine the real-world impact of semaglutide administered by injection in people with type 2 diabetes (T2D) across three secondary care sites in Wales.

Methods: A retrospective evaluation of 189 patients with T2D initiated on semaglutide between January 2019 and June 2020 with at least one follow-up visit was undertaken.

The Impact of Observation Versus Parathyroidectomy on Bone Mineral Density and Fracture Risk Determined by FRAX Tool in Patients With Primary Hyperparathyroidism.

To study impact of observation (OBV) vs parathyroidectomy (PTX) on biochemistry, bone mineral density (BMD) and fracture risk calculated by Fracture Risk Assessment (FRAX) tool in primary hyperparathyroidism (PHPT). Retrospective study of 60 patients (OBV - 26; PTX - 34 patients). Mean adjusted calcium improved in both groups [OBV - 2.

Coeliac disease presenting with chorea.

Chorea can be genetic or acquired, and often leads to a challenging diagnostic conundrum. In a significant proportion, there is no specific identifiable cause. Chorea is a rare but potentially reversible neurological manifestation of coeliac disease, usually presenting insidiously and often presumed to be associated with typical gastrointestinal symptoms.