The integration of LiDAR and Artificial Intelligence (AI) has revolutionized feature detection in urban environments. LiDAR systems, which utilize pulsed laser emissions and reflection measurements, produce detailed 3D maps of urban landscapes. When combined with AI, this data enables accurate identification of urban features such as buildings, green spaces, and infrastructure. This synergy is crucial for enhancing urban development, environmental monitoring, and advancing smart city governance. LiDAR, known for its high-resolution 3D data capture capabilities, paired with AI, particularly deep learning algorithms, facilitates advanced analysis and interpretation of urban areas. This combination supports precise mapping, real-time monitoring, and predictive modeling of urban growth and infrastructure. For instance, AI can process LiDAR data to identify patterns and anomalies, aiding in traffic management, environmental oversight, and infrastructure maintenance. These advancements not only improve urban living conditions but also contribute to sustainable development by optimizing resource use and reducing environmental impacts. Furthermore, AI-enhanced LiDAR is pivotal in advancing autonomous navigation and sophisticated spatial analysis, marking a significant step forward in urban management and evaluation. The reviewed paper highlights the geometric properties of LiDAR data, derived from spatial point positioning, and underscores the effectiveness of machine learning algorithms in object extraction from point clouds. The study also covers concepts related to LiDAR imaging, feature selection methods, and the identification of outliers in LiDAR point clouds. Findings demonstrate that AI algorithms, especially deep learning models, excel in analyzing high-resolution 3D LiDAR data for accurate urban feature identification and classification. These models leverage extensive datasets to detect patterns and anomalies, improving the detection of buildings, roads, vegetation, and other elements. Automating feature extraction with AI minimizes the need for manual analysis, thereby enhancing urban planning and management efficiency. Additionally, AI methods continually improve with more data, leading to increasingly precise feature detection. The results indicate that the pulse emitted by continuous wave LiDAR sensors changes when encountering obstacles, causing discrepancies in measured physical parameters.

Considering the current climate conjuncture, it is a consensus that green spaces in large contemporary urban areas should be increasingly more numerous and simultaneously more sustainable, being adapted to the edaphoclimatic conditions of the site, and with reduced maintenance costs. In the case of Algarve, where this research is focused, the current and future water availability, assumes a preponderant role in the design of green spaces, where the demands mentioned above can only be achieved if we deviate from conventional landscape practices and develop holistic strategies of management and design of green spaces that integrate different areas of knowledge and not merely aesthetic issues. In this context, this work aims to develop more adapted and resilient landscaping practices to the current and future climatic conditions of the Algarve, thus reinventing the concept of landscaping in the south of Portugal. Thus, it will be of paramount importance to develop more sustainable, resilient and tolerant projects to worsening ecological conditions, particularly limitations associated with water availability. The xeromorphic succulents are a group of plants with mechanisms of tolerance to water stress and with very specific characteristics, being succulence one of the most relevant. Studies on these mechanisms are increasingly frequent, which may prove to be very advantageous in our adaptation to future climatic challenges. In addition, their ornamental potential is enormous, since their bold forms and colours are a veritable sensory explosion, which, combined with their morphological and physiological characteristics, make them the species of choice in the reconversion or creation of xerophytic gardens.

The banana (Musa spp.) 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.

This paper is a general summary of Neuralink, a revolutionary technology set to elevate human life and neurology. Neuralink itself is a key testimonial to the evolution of neuroscience and even brain-computer interfaces, otherwise known as BCI. The original few BCI experiments were conducted on monkeys in the 1960s and 70s, in which the experiment itself narrowed down and understood brain function as a general concept [3]. More specifically, "Work on these technologies began in the early 1970s, led by computer science professor J.J. Vidal at UCLA" [12]. Science itself progresses day by day, growing rapidly in recent years, especially in neuroscience, something highlighted as a focal point in the previous statement. Moreover, recently we have seen technology go on a rampant rise in terms of popularity, inventions, and changes to the human lifestyle. The interactions humans had with technology initially developed with wearables or wearable technology, such as Apple Watches, AirPods, and Fitbits, and now they have even prompted advancements in brain-computer interfaces. Technology has had the power to advance science, but now it’s capable of changing the human mind. Going back to Neuralink, it’s a startup that began its initiative in 2016 and was approved by the FDA for clinical trials in May of 2023, ready to create a wave of change in the field of neuroscience [6]. The foremost baffling thing is how this chip plans on being placed in the somatosensory system. The somatosensory system is a part of the brain that deals with motor actions, recognition, and perception, and applying Neuralink in this area should supposedly allow for cures and treatment of amyotrophic lateral sclerosis, Parkinson’s disease, spinal cord injuries, epilepsy, autism, depression, schizophrenia, and possibly blindness [9]. Neuralink is deemed to lead to a life-changing future, and with co-founders and investors like Elon Musk, there is a lot to know about this piece of technology.

Background: 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. Objective: 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. Methods: 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. Results: 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. Conclusion: 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.

Background: The hippocampus plays a critical role in memory and decision-making processes, with its resting-state functional connectivity (rsFC) linked to various behavioral outcomes. This study investigates whether baseline brain-wide rsFC of the hippocampus mediates the relationship between impulsivity and subsequent substance use, specifically tobacco and marijuana use, in adolescents. Methods: Data were drawn from the baseline wave of the Adolescent Brain Cognitive Development (ABCD) study. Resting-state fMRI data were used to evaluate the functional connectivity of the hippocampus with key brain networks, including the cingulo-parietal network, visual network, sensory-motor network, and default mode network (DMN). Impulsivity was assessed using validated self-report measures, and substance use (tobacco and marijuana) was evaluated at follow-up. Mediation models were conducted to examine the extent to which hippocampal rsFC explains the association between impulsivity and substance use. Results: Baseline hippocampal rsFC with the cingulo-parietal network, visual network, sensory-motor network, and DMN showed marginal associations with future tobacco and marijuana use. Additionally, hippocampal rsFC was significantly associated with impulsivity, which, in turn, predicted higher substance use at follow-up. These findings suggest that hippocampal rsFC partially mediates the relationship between impulsivity and substance use behaviors. Conclusions: Hippocampal functional connectivity with brain networks may influence the pathway from impulsivity to future substance use in adolescence. These findings emphasize the importance of hippocampal connectivity in understanding the neural mechanisms underlying risk behaviors and may inform the development of targeted interventions to reduce substance use in this vulnerable population.

Background: As a central component of the brain's reward system, nucleus accumbens (NAcc) plays a crucial role in reward salience and substance use behaviors. Changes in the NAcc are also relevant to higher rates of substance use of youth and adults from low-income backgrounds. Although resting-state functional connectivity (rsFC) of the NAcc provides valuable insights into the neural mechanisms underlying reward processing and the propensity for self-reported reward salience and substance use, research exploring the association between NAcc rsFC and brain networks beyond the default mode network (DMN) and prefrontal cortex (PFC) is limited. Objective: To investigate the role of the resting-state functional connectivity of the NAcc with the cingulo-opercular network, sensorimotor mouth network, and sensorimotor hand network in the association between socioeconomic status, self-reported reward salience, and future substance use. Methods: Data were obtained from the Adolescent Brain Cognitive Development (ABCD) study. NAcc rsFC with the cingulo-opercular network, sensorimotor mouth network, and sensorimotor hand network was assessed at baseline. Socioeconomic status was measured using family income. Self-reported reward salience was assessed using validated psychometric scales. Substance use outcomes were tracked longitudinally over the study period. Structural Equation Modeling was employed to examine the covariances between family income, NAcc rsFC, reward salience, and subsequent substance use. Results: Higher baseline family income was positively associated with baseline NAcc rsFC (B = 0.092, p < 0.001) and negatively associated with baseline reward salience (B = -0.040, p = 0.036) and future substance use (B = -0.081, p < 0.001). Baseline NAcc rsFC was strongly and positively associated with reward salience (B = 0.734, p < 0.001) and future substance use up to age 13 (B = 0.124, p < 0.001). Additionally, baseline reward salience was positively associated with future substance use (Covariance = 0.176, p < 0.001). Conclusion: The findings suggest that NAcc rsFC with brain networks beyond the DMN or PFC may contribute to the links between low parental socioeconomic status, reward salience, and substance use risk. Expanding the understanding of NAcc rsFC provides new insights into the neural mechanisms underlying these associations. These results have important implications for developing targeted interventions aimed at preventing substance use, particularly among low-income youth with heightened reward salience. Further research is needed to explore causal pathways and moderating factors influencing these relationships.

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.

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.