AITeQ: a machine learning framework for Alzheimer's prediction using a distinctive five-gene signature.

Neurodegenerative diseases, such as Alzheimer's disease, pose a significant global health challenge with their complex etiology and elusive biomarkers. In this study, we developed the Alzheimer's Identification Tool (AITeQ) using ribonucleic acid-sequencing (RNA-seq), a machine learning (ML) model based on an optimized ensemble algorithm for the identification of Alzheimer's from RNA-seq data. Analysis of RNA-seq data from several studies identified 87 differentially expressed genes. This was followed by a ML protocol involving feature selection, model training, performance evaluation, and hyperparameter tuning. The feature selection process undertaken in this study, employing a combination of four different methodologies, culminated in the identification of a compact yet impactful set of five genes. Twelve diverse ML models were trained and tested using these five genes (CNKSR1, EPHA2, CLSPN, OLFML3, and TARBP1). Performance metrics, including precision, recall, F1 score, accuracy, Matthew's correlation coefficient, and receiver operating characteristic area under the curve were assessed for the finally selected model. Overall, the ensemble model consisting of logistic regression, naive Bayes classifier, and support vector machine with optimized hyperparameters was identified as the best and was used to develop AITeQ. AITeQ is available at: https://github.com/ishtiaque-ahammad/AITeQ.

A Topical Review on Enabling Technologies for the Internet of Medical Things: Sensors, Devices, Platforms, and Applications.

The Internet of Things (IoT) is still a relatively new field of research, and its potential to be used in the healthcare and medical sectors is enormous. In the last five years, IoT has been a go-to option for various applications such as using sensors for different features, machine-to-machine communication, etc., but precisely in the medical sector, it is still lagging far behind compared to other sectors. Hence, this study emphasises IoT applications in medical fields, Medical IoT sensors and devices, IoT platforms for data visualisation, and artificial intelligence in medical applications. A systematic review considering PRISMA guidelines on research articles as well as the websites on IoMT sensors and devices has been carried out. After the year 2001, an integrated outcome of 986 articles was initially selected, and by applying the inclusion-exclusion criterion, a total of 597 articles were identified. 23 new studies have been finally found, including records from websites and citations. This review then analyses different sensor monitoring circuits in detail, considering an Intensive Care Unit (ICU) scenario, device applications, and the data management system, including IoT platforms for the patients. Lastly, detailed discussion and challenges have been outlined, and possible prospects have been presented.

Green consumers' behavioral intention and loyalty to use mobile organic food delivery applications: the role of social supports, sustainability perceptions, and religious consciousness.

Consumer behavior in the food industry has undergone significant changes in recent years, largely driven by growing consumer awareness of environmental, technological, religious, and social concerns. As a result, organic food has emerged as a popular alternative to conventionally produced food. Many emerging nations, including Bangladesh, promote its consumption due to its perceived health and safety benefits. Despite this growing trend, there remains a need for more understanding of consumer behavior, particularly concerning their motivations for continuous purchases toward mobile organic food delivery applications. In order to fill this knowledge gap, this study looks at how six indirect predictors (emotional support, informational support, environmental consciousness, religious consciousness, trust, and technological consciousness) affect customer loyalty through the intention to use organic food. This study employed a purposive sampling technique (i.e., judgmental sampling) and collected data from 386 respondents across three cities in Bangladesh. Data analysis was conducted using SmartPLS 3 software. The study found that all predictors, except for technological consciousness, significantly influenced behavioral intention, which, in turn, significantly influenced loyalty. Additionally, the study revealed that the five predictors, excluding technological consciousness, indirectly influenced loyalty through behavioral intention. The results of this study add to the existing literature on organic food by extending social support theory to include consumers' primary motivations, such as environmental, religious, technological, and social consciousness, as predictors of loyalty to use mobile organic food delivery applications. The study highlights the importance of sustainable food consumption in promoting environmental protection, ensuring social justice, creating economic success, and providing valuable insights for implementers looking to expand the organic food market.

Employer safety obligations, safety climate, and safety behaviors in the ready-made garment context in Bangladesh.

PURPOSE: The impact of employer safety obligations on safety climate and safety outcomes has become an important area of research in organizational and safety sciences. Evidence shows that employer safety obligations positively impact safety outcomes, including safety climate and safety behaviors. However, these relationships have not been thoroughly explored within the garment settings. This study is one of the first known studies to examine the relationships between employer safety obligations, safety climate, and safety behavior outcomes in a sample of garment employees. METHODS: Two-wave time-lagged data were collected from 347 garment employees and their supervisors in Bangladesh. Hierarchical regression analysis was applied to examine hypothesized relationships using AMOS a SPSS. RESULTS: Employer safety obligations positively influenced safety climate perceptions among garment employees. Safety climate perceptions are positively and significantly associated with safety behaviors, including safety compliance behaviors, prosocial safety behaviors, and proactive safety behaviors. Moreover, the safety climate mediates the influence of employer safety obligations on safety behaviors. CONCLUSIONS: These findings provide important evidence of the relationships between employer safety obligations, safety climate, and safety behaviors in the garment industry of Bangladesh. PRACTICAL APPLICATIONS: Ultimately, these findings guide the government, garment manufacturers, and managers to bolster garment employees' safety outcomes.

Hemodynamic and structural effects on bypass graft for different levels of stenosis using fluid structure interaction: A prospective analysis.

Although the flow dynamics have been investigated using fluid-structure interaction scheme for the internal thoracic artery-left anterior descending coronary artery (ITA-LAD) bypass graft in different cases, a detailed analysis associating different degrees of LAD stenosis and its effects on hemodynamics and structural displacement are not comprehensively studied. Therefore, the primary focus of this work is to examine and determine the correlation between the hemodynamic effects and structural variations inside the bypass graft with different degrees of LAD stenosis (0%, 30%, 50%, and 75%). Navier-Stokes equation, arbitrary Lagrangian-Eulerian, and elasticity in the solid region are implemented by coupling incompressible viscous fluid, nonlinear viscous fluid, and the stress tensor equations, respectively. Using fluid-structure interaction, variations in the hemodynamic property and changes in wall shear stress (WSS) including the spatial WSS distribution and the changes in the displacement of different degree of LAD stenosis are determined.Maximum WSS is found to be around 1.58E1 Pa near the anastomosis region and maximum magnitude for the structural displacement is found to be approximately 1.25E-5 m close to the heel. The results demonstrate that the disturbance in the flow pattern is evident mainly in the anastomosis region. Consequently, higher WSS is observed near the toe and on the artery wall, near the anastomosis region.

An Automatic Navigation and Pressure Monitoring for Guided Insertion Procedure.

Navigation is an important feature needed for medical insertion procedures. It is required to guide the medical device in the right direction at the right time. Navigation techniques used in the Wireless Capsule Endoscopy and conventional endoscopy fields are based on image-guided systems that require a large amount of data to be transferred and processed computationally. These issues increase system complexity as well as the overall system and procedure costs. Moreover, these systems cannot provide the required information in dark or liquid areas. To improve the medical internal inspections capabilities, we present a pressure direction measurement system that can be implemented for a capsule endoscope; ordinary endoscopy; and any other insertion procedure where navigation and safety are required. The system can operate in dark and liquid areas because no visualization is required. The system consists of a pressure sensor placed on a semi-hemisphere on top of the steering device to detect azimuth and polar angle variation according to the direction at any differentiable path.

Integration of Low-Power ASIC and MEMS Sensors for Monitoring Gastrointestinal Tract Using a Wireless Capsule System.

This paper presents a wireless capsule microsystem to detect and monitor the pH, pressure, and temperature of the gastrointestinal tract in real time. This research contributes to the integration of sensors (microfabricated capacitive pH, capacitive pressure, and resistive temperature sensors), frequency modulation and pulse width modulation based interface IC circuits, microcontroller, and transceiver with meandered conformal antenna for the development of a capsule system. The challenges associated with the system miniaturization, higher sensitivity and resolution of sensors, and lower power consumption of interface circuits are addressed. The layout, PCB design, and packaging of a miniaturized wireless capsule, having diameter of 13 mm and length of 28 mm, have successfully been implemented. A data receiver and recorder system is also designed to receive physiological data from the wireless capsule and to send it to a computer for real-time display and recording. Experiments are performed in vitro using a stomach model and minced pork as tissue simulating material. The real-time measurements also validate the suitability of sensors, interface circuits, and meandered antenna for wireless capsule applications.

Flexible wearable sensor nodes with solar energy harvesting.

Wearable sensor nodes have gained a lot of attention during the past few years as they can monitor and record people's physical parameters in real time. Wearable sensor nodes can promote healthy lifestyles and prevent the occurrence of potential illness or injuries. This paper presents a flexible wearable sensor system powered by an efficient solar energy harvesting technique. It can measure the subject's heartbeats using a photoplethysmography (PPG) sensor and perform activity monitoring using an accelerometer. The solar energy harvester adopts an output current based maximum power point tracking (MPPT) algorithm, which controls the solar panel to operate within its high output power range. The power consumption of the flexible sensor nodes has been investigated under different operation conditions. Experimental results demonstrate that wearable sensor nodes can work for more than 12 hours when they are powered by the solar energy harvester for 3 hours in the bright sunlight.

An investigation on the effects of the angles between the mitral and aortic orifice during diastolic period using FSI.

BACKGROUND: It was well documented that the changes in the physiological structure of the heart can alter the hemodynamic behaviour of the human left ventricle. Although there were various imaging tools that can stipulate the blood flow characteristics inside the ventricle, but the effect of the variation in the angles between the mitral and aortic orifices were yet to be determined. Hence the primary focus of this paper was to use Fluid-Structure Interaction scheme throughout the diastolic phase to examine and determine the hemodynamic behaviour inside the cavity under various angles between the mitral and aortic orifices (50°, 55° and 60°). METHODS: The incompressible Newtonian liquid (time dependent), linear viscous liquid and stress tensor equations were combined together with the Navier-Stoke's equations and Arbitrary Lagrangian Eulerian and for the elasticity of the structure. RESULTS: During diastasis, the position of the vortex was seen to be slightly upwards (55°) compared to 50° and 60°. Also, the influence of the wall shear stress was primarily observed to be much higher with the rise in the inlet velocity but the effect was seen reduced when the inlet velocity was minimal. Moreover, at the end of the filling phase maximum intraventricular pressure was obtained to be at the tip of LV for 50° compared to 55° and 60°. CONCLUSION: These findings provide significant insights on hemodynamic conditions and structural displacement, which from a clinical point of view would be useful in determining different conditions of cardiac diseases.

Detecting Subtle Vibrations Using Graphene-Based Cellular Elastomers.

Ultralight graphene elastomer-based flexible sensors are developed to detect subtle vibrations within a broad frequency range. The same device can be employed as an accelerometer, tested within the experimental bandwidth of 20-300 Hz as well as a microphone, monitoring sound pressures from 300 to 20 000 Hz. The sensing element does not contain any metal parts, making them undetectable by external sources and can provide an acceleration sensitivity of 2.6 mV/g, which is higher than or comparable to those of rigid Si-based piezoresistive microelectromechanical systems (MEMS).

A MEMS Interface IC With Low-Power and Wide-Range Frequency-to-Voltage Converter for Biomedical Applications.

This paper presents an interface circuit for capacitive and inductive MEMS biosensors using an oscillator and a charge pump based frequency-to-voltage converter. Frequency modulation using a differential crossed coupled oscillator is adopted to sense capacitive and inductive changes. The frequency-to-voltage converter is designed with a negative feedback system and external controlling parameters to adjust the sensitivity, dynamic range, and nominal point for the measurement. The sensitivity of the frequency-to-voltage converter is from 13.28 to 35.96 mV/MHz depending on external voltage and charging current. The sensitivity ranges of the capacitive and inductive interface circuit are 17.08 to 54.4 mV/pF and 32.11 to 82.88 mV/mH, respectively. A capacitive MEMS based pH sensor is also connected with the interface circuit to measure the high acidic gastric acid throughout the digestive tract. The sensitivity for pH from 1 to 3 is 191.4 mV/pH with 550 µV(pp) noise. The readout circuit is designed and fabricated using the UMC 0.18 µm CMOS technology. It occupies an area of 0.18 mm (2) and consumes 11.8 mW.

Meandered conformal antenna for ISM-band ingestible capsule communication systems.

The wireless capsule has been used to measure physiological parameters in the gastrointestinal tract where communication from in-body to external receiver is necessary using a miniaturized antenna with high gain and onmidirectional radiation pattern. This paper presents a meandered conformal antenna with center frequency of 433 MHz for a wireless link between an in-body capsule system and an ex-body receiver system. The antenna is wrapped around the wireless capsule, which provides extra space for other circuits and sensors inside the capsule as well as allows it having larger dimensions compared to inner antennas. This paper analyses return loss, radiation pattern, antenna gain, and propagation loss using pork as the gastrointestinal tissue simulating medium. From the radiation pattern and return loss results, the antenna shows an omni-directional radiation pattern and an ultrawide bandwidth of 124.4 MHz (371.6 to 496 MHz) for VSWR <; 2. Experimental results shows that the path loss is 17.24 dB for an in-body propagation distance of 140 mm.

Graft-artery junctions: design optimization and CAD development.

Designing and manufacturing of vascular prosthesis for arterial bypass grafts is a very complex problem. The process involves the selection of suitable geometry, materials of appropriate characteristics, and manufacturing technique capable of constructing prosthesis in a cost-effective manner. In this chapter, all engineering aspects related to the design and optimization of an artificial graft are presented and discussed. These aspects include CAD design of the graft, in vitro hemodynamic analysis to ensure good mechanical integrity and functionality, and optimization of the manufacturing techniques. Brief discussion is also given on the endothelization and vascularization of the artificial vessels and the future directions of the development of synthetic vessels for human implementation.

Empirical Equation Based Chirality (n, m) Assignment of Semiconducting Single Wall Carbon Nanotubes from Resonant Raman Scattering Data.

This work presents a technique for the chirality (n, m) assignment of semiconducting single wall carbon nanotubes by solving a set of empirical equations of the tight binding model parameters. The empirical equations of the nearest neighbor hopping parameters, relating the term (2n, m) with the first and second optical transition energies of the semiconducting single wall carbon nanotubes, are also proposed. They provide almost the same level of accuracy for lower and higher diameter nanotubes. An algorithm is presented to determine the chiral index (n, m) of any unknown semiconducting tube by solving these empirical equations using values of radial breathing mode frequency and the first or second optical transition energy from resonant Raman spectroscopy. In this paper, the chirality of 55 semiconducting nanotubes is assigned using the first and second optical transition energies. Unlike the existing methods of chirality assignment, this technique does not require graphical comparison or pattern recognition between existing experimental and theoretical Kataura plot.