Enhancing Access to Mental Health Services for Antepartum and Postpartum Women Through Telemental Health Services at Wellbeing Centers in Selected Health Facilities in Bangladesh: Implementation Research.

Background: Globally, 10% of pregnant women and 13% of postpartum women experience mental disorders. In Bangladesh, nearly 50% of mothers face common mental disorders, but mental health services and trained professionals to serve their needs are scarce. To address this, the government of Bangladesh's Non-Communicable Disease Control program initiated "Wellbeing Centers," telemental health services in selected public hospitals.

Automated Pipeline for Robust Cat Activity Detection Based on Deep Learning and Wearable Sensor Data.

The health, safety, and well-being of household pets such as cats has become a challenging task in previous years. To estimate a cat's behavior, objective observations of both the frequency and variability of specific behavior traits are required, which might be difficult to come by in a cat's ordinary life. There is very little research on cat activity and cat disease analysis based on real-time data.

Deep learning-based anomaly detection using one-dimensional convolutional neural networks (1D CNN) in machine centers (MCT) and computer numerical control (CNC) machines.

Computer numerical control (CNC) and machine center (MCT) machines are mechanical devices that manipulate different tools using computer programming as inputs. Predicting failures in CNC and MCT machines before their actual failure time is crucial to reduce maintenance costs and increase productivity. This study is centered around a novel deep learning-based model using a 1D convolutional neural network (CNN) for early fault detection in MCT machines.

Nanocarrier-Based, ocular drug delivery: Challenges, prospects, and the therapeutic landscape in the United Arab Emirates.

Human eyes have the most complex and advanced physiological defense barriers. Due to these barriers, efficient delivery of ocular drugs is a major challenge in the treatment of eye diseases and disorders. Posterior eye diseases such as retinopathy are the leading causes of impaired vision and blindness globally.

Stochastic Gauss-Newton method for estimating absorption and scattering in optical tomography with the Monte Carlo method for light transport.

Image reconstruction in optical tomography in the so-called transport regime, where the diffusion approximation is not valid, requires modeling of light transport using the radiative transfer equation. In this work, we approach this problem by utilizing the Monte Carlo method for light transport. In this work, we propose a methodology for absolute imaging of absorption and scattering in this regime utilizing a Monte Carlo method for light transport.

Diffuse optical tomography of the brain: effects of inaccurate baseline optical parameters and refinements using learned post-processing.

Diffuse optical tomography (DOT) uses near-infrared light to image spatially varying optical parameters in biological tissues. In functional brain imaging, DOT uses a perturbation model to estimate the changes in optical parameters, corresponding to changes in measured data due to brain activity. The perturbation model typically uses approximate baseline optical parameters of the different brain compartments, since the actual baseline optical parameters are unknown.

BFLIDS: Blockchain-Driven Federated Learning for Intrusion Detection in IoMT Networks.

The Internet of Medical Things (IoMT) has significantly advanced healthcare, but it has also brought about critical security challenges. Traditional security solutions struggle to keep pace with the dynamic and interconnected nature of IoMT systems. Machine learning (ML)-based Intrusion Detection Systems (IDS) have been increasingly adopted to counter cyberattacks, but centralized ML approaches pose privacy risks due to the single points of failure (SPoFs).

Integrated drying model of lychee as a function of temperature and relative humidity.

Drying is a universal method applied for food preservation. To date, several models have been developed to evaluate drying kinetics. In this study, lychee was dried employing a hot air dryer, and the drying kinetics was evaluated by comparing the Newtonian model, Henderson and Pabis model, Page model, and Logarithmic model.

Testing the effectiveness and acceptability of online supportive supervision for mental health practitioners in humanitarian settings: a study protocol for the caring for carers project.

Background: Local humanitarian workers in low and middle-income countries must often contend with potentially morally injurious situations, often with limited resources. This creates barriers to providing sustainable mental health and psychosocial support (MHPSS) to displaced individuals. Clinical supervision is an often neglected part of ensuring high-quality, sustainable care.

ZIF-8 as support for enhanced stability of immobilized lipase used with a thermoresponsive switchable solvent to simplify the microalgae-to-biodiesel process.

The zeolitic imidazole framework (ZIF)- 8 was tested as a support to enhance the stability of immobilized lipase. The lipase immobilized on ZIF-8, through surface attachment and encapsulation, was used for the simultaneous cell disruption and oil extraction from untreated, wet microalgal paste. The successful attachment of the enzyme to ZIF-8 was confirmed via Fourier-transform infrared spectroscopy.

Photovoltaic performance of MOF-derived transition metal doped titania-based photoanodes for DSSCs.

The enduring effort toward stabilizing and improving the efficiency of dye-sensitized solar cells (DSSCs) has stirred the solar research community to follow innovative approaches. Current research centered on electrode materials design, which improves photoanodes' light-harvesting efficiency (LHE). Metal-Organic Frameworks (MOFs) are a new family of materials that can be used as competent materials due to their desirable qualities, including high porosity, flexible synthesis methodology, high thermal and chemical stability, and good light-harvesting capabilities.

Sulfate reduction accelerates groundwater arsenic contamination even in aquifers with abundant iron oxides.

Groundwater contamination by geogenic arsenic is a global problem affecting nearly 200 million people. In South and Southeast Asia, a cost-effective mitigation strategy is to use oxidized low-arsenic aquifers rather than reduced high-arsenic aquifers. Aquifers with abundant oxidized iron minerals are presumably safeguarded against immediate arsenic contamination, due to strong sorption of arsenic onto iron minerals.

Developing a Low-Cost IoT-Based Remote Cardiovascular Patient Monitoring System in Cameroon.

(1) Background: Cameroonians are exposed to poor health services, more so citizens with cardiovascular-related diseases. The global high cost of acquiring healthcare-related technologies has prompted the government and individuals to promote the need for local research and the development of the health system. (2) Objectives: The main goal of this study is to design and develop a low-cost cardiovascular patient monitoring system (RPM) with wireless capabilities that could be used in any region of Cameroon, accessible, and very inexpensive, that are able to capture important factors, well reflecting the patient's condition and provide alerting mechanisms.

Reliability and validity of the Perceived Stress Scale in Bangladesh.

With validation studies conducted all over the world, the 10-item Perceived Stress Scale (PSS-10) has become a robust and widely used instrument for assessing the appraisal of stress. The present study was aimed at validation and testing for psychometric properties of the PSS-10 on the Bangladeshi population. Three hundred and fifteen adult (aged 18-64 years) from eight divisional districts of Bangladesh participated in this study.

Accelerated Discovery of the Polymer Blends for Cartilage Repair through Data-Mining Tools and Machine-Learning Algorithm.

In designing successful cartilage substitutes, the selection of scaffold materials plays a central role, among several other important factors. In an empirical approach, the selection of the most appropriate polymer(s) for cartilage repair is an expensive and time-consuming affair, as traditionally it requires numerous trials. Moreover, it is humanly impossible to go through the huge library of literature available on the potential polymer(s) and to correlate the physical, mechanical, and biological properties that might be suitable for cartilage tissue engineering.

Does Fish Farming Improve Household Nutritional Status? Evidence from Bangladesh.

In the present study, nutritional status was assessed using dietary diversity of fish and non-fish farming households in Mymensingh district of Bangladesh. It has determined the incidence of poverty in fish and non-fish farm households through a comparative analysis of family profile, food consumption, calories, and protein intake. A total of 420 farms were selected for data collection using structured questionnaires with 210 fish and 210 non-fish farm families.

Well-Switching to Reduce Arsenic Exposure in Bangladesh: Making the Most of Inaccurate Field Kit Measurements.

Well-switching programs in Bangladesh have successfully lowered arsenic exposure. In these programs, households switch from wells that are labeled "unsafe" to nearby wells labeled "safe," but these designations are usually based on inherently inaccurate field kit measurements. Here, we (a) compare the efficacy of field-kit measurements to accurate laboratory measurements for well switching, (b) investigate the potential impact on well switching of the chosen "safe" threshold, and (c) consider the possible benefits of providing more detailed concentration information than just "safe" and "unsafe.

A Model-Based Iterative Learning Approach for Diffuse Optical Tomography.

Diffuse optical tomography (DOT) utilises near-infrared light for imaging spatially distributed optical parameters, typically the absorption and scattering coefficients. The image reconstruction problem of DOT is an ill-posed inverse problem, due to the non-linear light propagation in tissues and limited boundary measurements. The ill-posedness means that the image reconstruction is sensitive to measurement and modelling errors.

Statistical and Machine Learning-Driven Optimization of Mechanical Properties in Designing Durable HDPE Nanobiocomposites.

The selection of nanofillers and compatibilizing agents, and their size and concentration, are always considered to be crucial in the design of durable nanobiocomposites with maximized mechanical properties (i.e., fracture strength (FS), yield strength (YS), Young's modulus (YM), etc).

MOF-derived Co-doped TiO nanoparticles as photoanodes for dye-sensitized solar cells.

Facile synthesis and application of nano-sized semiconductor metal oxides for optoelectronic devices have always affected fabrication challenges since it involves multi-step synthesis processes. In this regard, semiconductor oxides derived directly from metal-organic frameworks (MOFs) routes have gained a great deal of scientific interest owing to their high specific surface area, regular and tunable pore structures. Exploring the application potential of these MOF-derived semiconductor oxides systems for clean energy conversion and storage devices is currently a hot topic of research.

Socio-Economic Context and Community Resilience among the People Involved in Fish Drying Practices in the South-East Coast of Bangladesh.

The south-east coast, specifically the Cox's Bazar region, of Bangladesh has achieved a tremendous impetus for producing a large volume of dried fish by involving thousands of marginalized coastal people. This study aimed to assess the socio-economic profile, livelihood strategies, and resilience of the communities engaged in fish drying on the south-east coast using a mixed-methods approach and an Analytic Hierarchy Process (AHP). The study's findings revealed that communities involved in drying were socio-economically undeveloped due to their lower literacy, unstable incomes, and labor-intensive occupations.