Articles

<b>Background: </b>The sensory-motor network is essential for integrating sensory input with motor function and higher-order cognition. Resting-state functional connectivity (rsFC) within this network undergoes significant developmental changes, and disruptions in these connections have been linked to behavioral and psychiatric outcomes. However, the relationship between sensory-motor connectivity, early-life adversity, and later health behaviors remains understudied. <b>Objective: </b>This study examines the associations between rsFC within the sensory-motor network (mouth and hand regions) and key social, psychological, and behavioral factors, including baseline and past socioeconomic status (SES), trauma exposure, family conflict, impulsivity, major depressive disorder (MDD), and future substance use. <b>Methods: </b>Data were drawn from the Adolescent Brain Cognitive Development (ABCD) Study, a national sample of U.S. children. Resting-state fMRI data were used to assess functional connectivity within the sensory-motor network. Bivariate analyses examined associations between rsFC in the sensory-motor mouth and hand regions and baseline SES, past SES, childhood trauma exposure, family conflict, impulsivity, and MDD. Longitudinal analyses assessed whether baseline rsFC predicted future substance use. <b>Results: </b>Greater rsFC between the sensory-motor mouth and hand regions was significantly associated with lower SES, higher trauma exposure, and greater family conflict. Increased connectivity was also correlated with older age and more advanced puberty status. Higher rsFC between the sensory-motor mouth and hand regions was linked to greater impulsivity, lower cognitive function, an increased likelihood of MDD, and future marijuana use. <b>Conclusion: </b>These findings suggest that sensory-motor connectivity is sensitive to socioeconomic and psychosocial stressors, with potential long-term implications for mental health and substance use risk. The results highlight the importance of early-life environmental factors in shaping neurodevelopmental trajectories and emphasize the need for targeted interventions to mitigate the effects of adversity on brain function and behavior. Future research should further explore the role of sensory-motor network alterations in behavioral health outcomes as a function of environmental stressors.

This study aimed to assess the proximate composition, microbial quality, and sensory acceptability of canned Bambara beans in Ghana to determine their nutritional value and consumer perceptions. The research was conducted in Tamale in the northern region of Ghana, focusing on sensory evaluation, nutritional analysis, and consumer preferences for canned Bambara beans. The study utilized canned Bambara bean varieties sourced from local markets in Ghana. It involved sensory panels, proximate analysis, and microbial testing to evaluate the quality and safety of the canned products. Data analysis included sensory scoring, proximate composition determination, and microbial count assessments. The findings indicated positive consumer attitudes towards canned Bambara beans, emphasising their convenience, nutritional richness, and sensory appeal. Nutritional analysis revealed the nutrient content of the canned beans, highlighting their potential as a nutritious food source. Conclusions emphasised the importance of sensory attributes in consumer acceptance and women's role in producing and promoting Bambara beans. It is recommended that Increase awareness among consumers, especially women and homemakers, about the nutritional benefits and culinary versatility of canned Bambara beans. Educational campaigns highlighting canned Bambara beans' health advantages and convenience can encourage their inclusion in household diets. It is also recommended that women involved in the production and processing of Bambara beans should be supported and empowered through training, capacity building, and access to resources. Recognising the pivotal role of women in the Bambara bean value chain is essential for sustainable production practices and economic empowerment.

The banana (<i>Musa spp.</i>) is a tropical fruit with excellent sensory characteristics in terms of aroma, flavor and texture, consumed worldwide and exploited in most tropical countries. Green banana flour is rich in flavonoids, which protect the gastric mucosa, has a high content of resistant starch, which acts in the body as a dietary fiber and thus has health benefits, and is an alternative option for bakery products, reducing waste of both the peel and the pulp. The aim of this study was to develop bread formulations with partial substitution of wheat flour with green banana flour (FBV), thus increasing the nutritional, technological and sensory value. 4 formulations, (A), standard sample; (B), bread with 10% FBV; (C), bread with 15% FBV and (D), bread with 20% FBV. Physico-chemical quality was assessed in terms of moisture content by drying at 105ºC, ash by incineration, fat by the Soxhlet method, protein by the biuret method, carbohydrates by difference calculation and calorific value by sum calculation and sensory analysis by affective methods. The data was evaluated using the RStudio 4.2.1 DCC statistical package. There were no significant differences in moisture content, lipids and calorific value. Differences were evident in the ash and protein content. Sensory acceptance of the standard formulation was 82.22%. The results obtained show that green banana flour can be used as a partial substitute for wheat flour to produce breads with functional properties.

Effective Inclusive education experiences can be built through structured interventions. The purpose of the study was to assess the impact of inclusive education experiences on teacher-trainees with sensory impairment in the Ghana Colleges of Educations of Ghana. The study was based on pragmatist philosophy. The study adopted convergent parallel mixed-methods approach. The population involved all 66 students with sensory (visual and hearing) impaired in the three (3) CoEs (PCE, Akropong Akwapim, WESCO, Kumasi and NJA, Wa) that practice inclusive education (IE) during the 2018/19 academic year. Purposive and census sampling techniques were used to select the three (3) colleges of education and sixty-six students for the study. The main instruments for data collection were questionnaire and focus group discussion. The quantitative data items were coded for input into the Statistical Product and Service Solutions (SPSS) version 23 software and analysed using means and standard deviations. The qualitative extracts collected into themes that were coded, analysed and interpreted. The study revealed that teacher-trainees had varied experiences on campus, while they felt welcomed into the inclusive institution; they also felt the Colleges were not well prepared to meet their needs. The physical environment was not conducive for the VI on campus. It is recommended that, College authorities should work with the MoE and agencies concerned with disability issues in the society to provide comfortable environment on College campuses for TTSI. It is also recommended that, providing a comfortable environment should include facilities and resources needed for the TTSI to learn effectively. It also involves physical arrangement of the campus environment. The TTSI, regardless of their disabilities, should be provided with an environment where their movement, their studies, their interactions with their peers and tutors are made easier to help them graduate successfully.

A hydrographic survey vessel shows three -dimensional movements (Roll, Pitch and Heave) misalignment with respect to the vessel reference unit (VRU) due to environmental effects, such as wind, current, other vessel wakes, etc. These motions if ignored, cause errors in measured depth and in the positioning of the sounding. Hence the need of a motion sensor and gyroscope. However, the alignment of the multi-beam sonar head to the motion sensor and gyro (Octant) is critical to the accuracy of the determined depths. It is not possible to install the sonar head in perfect alignment with the motion sensor and gyroscope to the accuracy required. The synchronization of the GPS time with the Motion sensor and gyro, the latency of the position, as reported by the GPS as well as the velocity of sound in water are important parameters to account for the misalignment of the motion senor and the multi beam sonar head; this is called the Patch Test. In view of this, a patch test was done to ascertain the mounting angles of EMB 2058 Multi-beam sonar with Octan V installed onboard a survey vessel (Bitam). The result of the Patch test gives a row, pitch and heading value of -1.242˚, -4.92˚, and -0.48˚respectively. The speed of sound in water as measured ranges from; 1531.47m/s to 1531.60m/s within a minimum cast depth of 0.49m and maximum cast depth of 16.00m. The statistical analysis gives and average error of 2.642cm/m2 which was within acceptable standard as define by the International Hydrographic Organization (IHO).

The major automated plants have produced large volumes of high-quality products at low cost by introducing various technologies, including robotics and artificial intelligence. The code of many defects on the surface of products is embedded with economic loss and sometimes functionality loss because products are rarely found with defects. Therefore, most items’ production is done based on prediction and has an invisible fluctuation in production. The detection process for hidden defect images requires a lot of costs and needs to be supported for better progress and quality enhancement. Paint shop defects should be analyzed from color changes to detect defects effectively by preventing the variability of product demand over time. It is not easy to take visible light images without noise because the paint surfaces are glossy. A few parts of illumination and shadows remain in images, even in larger size and high-resolution images. The various painted surfaces are also needed to reflect both color and texture information in computer vision models to classify defects precisely. Several automated detection systems have been applied to paint shop inspections using lasers, infrared, x-ray, electrical, magnetic, and acoustic sensors. The chance of paint shop defects can be low, unnecessarily low, compared to clouds in the sky, but those chances impact defect functionalities. Thus, they are called as “lessons learned.” Lately, artificial intelligence has been introduced to the field of factory automation, and many defect detection feeds have found footsteps in machine learning and deep learning. Recent attempts at deep learning-based defect detection are proposing simple techniques using specific neural network architectures with big data. However, big data is still in its early stages, and significant challenges exist in normalizing and annotating such data. To get cost-efficient and timely solutions tailored to automotive paint shops, it might be a better consideration to combine deep learning solutions with traditional computer vision and more elaborate machine learning methods.

Waste collection system has become a challenging task, occasioned by the overflowing garbage bins littered all over the environment, causing environmental hazard and further leading to incurable diseases which endanger life. The present-day waste collection system has proven to be inefficient, taking into consideration the advancement in the technologies on the rise in recent years as well as the continuous increase in population growth. As a result of this inefficiency observed, this work developed a model for electronic waste collection system in a telecommunication driven environment. In the system's implementation, PIC18F4620 based instrumentation, integrated with proximity sensor for external monitoring and level sensors for internal monitoring was adopted, while the controlling of the opening and closing of the cabins was implemented using a smart switching board. A remote reporting to the waste management authority so as to systematically plan route-map for garbage collection when the waste cabin is fully filled was done by deploying a 900MHz transmitter interfaced with the system’s controller. The result shows that with this model the waste cabin opens only on account of a user approaching the sensing distance of the system and the cabin is not filled. But when the cabin gets filled and a user approaches the sensing distance of the system, it directs the user to use the nearest waste cabin by displaying a message on the LCD (Liquid Crystal Display), while communicating with relevant authority for the evacuation of the cabin via SMS. It was obviously seen that the automation incorporated into the system had zero impact on the success rate of the system or system availability while introducing a latency of 5.6seconds, which is just 28.0% of the maximum allowable latency of this kind of system, while protecting the environment from environmental pollution and spread of diseases. This work highlights the potentials of (EWCS) Electronic Waste Collection System in monitoring and controlling waste disposal for healthy and clean environment.