In this work, we show that a late fusion approach to multi-modality in sign language recognition improves the overall ability of the model in comparison to the singular approaches of Computer Vision (88.14%) and Leap Motion data classification (72.73%). With a large synchronous dataset of 18 BSL gestures collected from multiple subjects, two deep neural networks are benchmarked and compared to derive a best topology for each. The Vision model is implemented by a CNN and optimised MLP and the Leap Motion model is implemented by an evolutionary optimised deep MLP topology search. Next, the two best networks are fused for synchronised processing which results in a better overall result (94.44%) since complementary features are learnt in addition to the original task. The hypothesis is further supported by application of the three models to a set of completely unseen data where a multi-modality approach achieves the best results relative to the single sensor method. When transfer learning with the weights trained via BSL, all three models outperform standard random weight distribution when classifying ASL, and the best model overall for ASL classification was the transfer learning multi-modality approach which scored 82.55% accuracy.

Abstract— Flight Control System is an integrated avionics system equipped with the minimum required components for an autonomous flight. This paper focuses on the Hardware Design of the Flight Control System and presents specific details of the components and its interface. The system architecture is based on Field Programmable Gate Array and Digital Signal Processor. Employing these two processors in the flight control system would improve the Flight Control System performance in terms of fast sequential processing of high-level control algorithms. In addition to Field Programmable Gate Array and Digital Signal Processor, the flight control computer system will also make use of Global Positioning System and Micro Electro Mechanical System sensors. The project will be implemented using Altera’s System On Programmable Chip builder, currently known as Qsys – Platform Designer implemented in Quartus-II. The system employs Nios-II processor which is 32-bit soft-core embedded-processor architecture designed especially for the Altera’s family of Field Programmable Gate Array. From conceptualization to final design, this paper presents the functionality of the different modulus and complex interfaces employed in this Flight Control System.

Mpox, formerly known as Monkeypox, is a rare viral disease initially discovered in Africa in 1958. Since its first identification, several outbreaks have occurred in various African nations. Recently, the global community has witnessed a resurgence in the number of Mpox cases reported worldwide, prompting the World Health Organization (WHO) to declare the ongoing multi-country outbreak a public health emergency in July 2022. This study reports on the first cases of Mpox detected in Khartoum State, Sudan, outlining the epidemiology, preparedness, and public health response to this new challenge. A total of 55 suspected cases were identified, with two confirmed cases. The clinical manifestations observed in these cases align with the classic skin rash typical of Mpox, presenting alongside symptoms like fever, headache, and joint pain. The findings underscore the need for heightened surveillance, early detection, and timely intervention to prevent the domestic spread of Mpox and its potential impact on public health. Continued global efforts are needed to support effective screening, diagnostic, and control measures, ultimately enhancing preparedness and response in the face of this emerging disease.

The objective of this work was to investigate the deacidification of bio-oils (BOs) from triglyceride-based biomass through the application of liquid-liquid extraction (LLE) in a simple stage, using methanol and water as a binary solvent and feed/solvent ratio of 1/1. For this, the effects of process parameters such as the water content present in the solvent, the content of carboxylic acids present in the bio-oil, and the extraction temperature on the deacidification process through the efficiency and distribution coefficient were evaluated, as well as the effects of such parameters on the quality of deacidified bio-oils through physical-chemical analyzes and GC-MS analysis. The results show that such process parameters significantly affect the quality of deacidified bio-oils. The ideal condition to have the highest acid removal, i.e., the highest deacidification efficiency (72.65%), is the one in which the deacidification process is performed with aqueous methanol (5% water) at 35 °C and for BOs that have a total acid number (TAN) equal to 24.38 mg KOH/g. Therefore, the process of deacidification by LLE using aqueous methanol is a promising alternative for removing carboxylic acids and other oxygenated compounds, contributing significantly to the upgrading or improving biofuels produced by catalytic thermal cracking.

Total-body PET/CT scanners provide increased sensitivity, enabling the adjustment of imaging parameters by reducing injected activity or shortening acquisition time. This study aimed to evaluate the limitations of reduced [18F]FDG activity doses on image quality, lesion detectabil-ity, and quantification of lesion uptake in the Biograph Vision Quadra, as well as to assess the benefits of the recently introduced ultra-high sensitivity mode in a clinical setting. A number of 26 patients who underwent [18F]FDG-PET/CT (3.0 MBq/kg, 5 min. scan time) were included in this analysis. PET raw data was rebinned for shorter frame durations to simulate 5 min. scans with lower activities in high sensitivity (HS) and ultra-high sensitivity (UHS) modes. Image quality, noise, and lesion detectability (n=82) were assessed using a 5-point Likert scale. The co-efficient of variation (CoV), signal-to-noise ratio (SNR), tumor-to-background ratio (TBR), and standardized uptake values (SUV) including SUVmean, SUVmax, and SUVpeak were evaluated. Sub-jective image ratings were generally superior in UHS compared to HS mode. At 0.5 MBq/kg, le-sion detectability decreased to 95% (HS) and 98% (UHS). SNR was comparable at 1.0 MBq/kg in HS (5.7±0.6) and 0.5 MBq/kg in UHS (5.5±0.5). With lower doses, there were negligible reductions in SUVmean and SUVpeak, whereas SUVmax increased steadily. Reducing [18F]FDG activity to 1.0 MBq/kg (HS/UHS) in a total-body PET/CT provides diagnostic image quality without statistical-ly significant changes in uptake parameters. UHS mode improves image quality, noise, and le-sion detectability compared to HS mode.

Cybersecurity is a crucial concern for local governments, as they serve as the primary interface between public and government services, managing sensitive data and critical infrastructure. While technical safeguards are integral to cybersecurity, the role of well-structured policy is equally important, as it provides structured guidance to translate technical requirements into actionable protocols. This study reviews local governments’ cybersecurity policies to provide a comprehensive assessment of how these policies align with NIST CSF, which is a widely adopted and commonly used cybersecurity assessment framework. The review offers local governments a mirror to reflect on their cybersecurity stance, identifying potential vulnerabilities and areas needing urgent attention. The study further extends to developing a cybersecurity policy framework, which local governments can use as a strategic tool. It provides valuable information on crucial cybersecurity elements that local governments must incorporate into their policies to protect confidential data and critical infrastructure.

This study analyzes the relevance of governance structure for efficiency in revenue collection by Brazilian Water Utilities (WUs). Data was collected from the National Information System on Sanitation (SNIS) for 127 Brazilian WUs, covering a balanced longitudinal panel from 2018 to 2022. Governance structures evaluated included Ownership (public or private) and Corporatization (publicly traded or not). In scientific databases, we did not find studies on the efficiency of specific WUs in collecting customer bills for services rendered and its relationships with this type of governance; thus, this would be the main innovative contribution of the study to the previous literature. In the first stage, the study utilized the Dynamic Slack Based Model (DSBM) to assess revenue collection efficiency. In the second stage, an econometric model with Generalized Estimating Equations (GEE) to explain the efficiency. The findings revealed a global average inefficiency of 50.47% in revenue collection. Corporatization was linked to higher collection efficiencies, while ownership type was significant, but with lower collection efficiency. Factors such as tariff accessibility, urbanization, and the COVID-19 pandemic also influenced efficiency. The study suggests regulatory bodies should consider these insights to implement policies that prevent inefficiencies from affecting the tariff system for services.

Upon declaration of poliovirus (PV) type 2 eradication in 2015, the World Health Organization (WHO) published PV containment requirements in the Global Action Plan III (GAPIII) for mitigating risks of a facility-associated release post-eradication. In 2018, the 71st World Health Assembly resolution urged Member States retaining PV to appoint a National Authority for Containment (NAC), reduce the number of PV facilities, and submit applications for containment certification. The United States (US) NAC was established in 2018 for containment oversight, and two paths to WHO GAPIII containment certification were developed. Facilities retaining PV were identified through national poliovirus containment surveys. US NAC conducted 27 site visits at 18 facilities (20 laboratories: A/BSL-2 (65%), A/BSL-3 (20%), and storage-only (15%)) to verify implementation of US NAC’s preliminary containment measures. NAC identified areas for improvement in seven categories: primary containment, decontamination, hand hygiene, security, emergency response, training, and immunization practices. Sixteen facility applications were endorsed to pursue poliovirus-essential facility (PEF) certification whereas four facilities opted to withdraw during the containment certification process. The US made noteworthy progress in PV containment to enhance biosafety and biosecurity practices at US PV facilities to safeguard the polio eradication effort.

With the changing relationship between urban and rural areas in China, the rural areas are experiencing rapid social transformation. To ensure successful implementation of the rural revitalization strategy, land consolidation has become a major measure of rural economic reform. Existing research focuses on quantitative studies exploring the relationship between land consolidation and rural economic development, but there is a lack of studies on the relationship between land consolidation and social change. In this study, Jin’an Village is selected as the research area, using semi-structured interviews and semi-participatory observation to obtain original materials, aiming to make a detailed description of the specific practice of land consolidation, and to analyze the impact of land consolidation on the transformation of rural social consciousness. The study found that rural land consolidation involves villagers in the land consolidation process, which can effectively stimulate villagers’ participation in public affairs. Concurrently, the interaction between villagers and outside investors disrupts the conventional socialization model in rural areas and motivates villagers to act in accordance with contractual agreements. The conclusion is that land consolidation in rural areas can enhance the political democracy and legal consciousness of local villagers, which can lead to a change in local social consciousness. Our findings also emphasize the crucial necessity to grant rural villagers with improved accessibility to professional services and information, coupled with the continued promotion of land consolidation to advance modernization in these areas.

This study, which was supported by a quantitative research paradigm with two experiment and two control groups of 4x4 quasi-experimental design, aimed to find out the impact of a sustainable progressive STEAM (SP-STEAM Model) application model on 5th grade primary school students critical thinking dispositions and mathematic achievements in Northern Cyprus. The treatment model was applied to experimental groups for 14 weeks of time. Split-plot multiple group analysis of variance (Split-plot ANOVA) statistical technique was used to calculate between and within group significances regarding exogenous variable. SPSS24 software package was used for the analysis. Pre-test and post-test results derived from experiment and control groups revealed significant effect of SP-STEAM Model on 5th grade primary school students’ critical thinking dispositions as measured with CCTDI and mathematic achievements as measured with a dedicated ex-am. The results were discussed in detail under the light of related literature and suggestions for further studies were proposed.

Bullying makes learning difficult for nursing students, and using real-life scenarios during training can improve the understanding of workplace bullying. Thus, to mitigate bullying experienced by nurses, this study developed and evaluated a cognitive rehearsal education program that constituted of training nursing students through role-play simulations. A mixed-method research design was used to evaluate 39 nursing students from two universities. A quasi-experimental research design was applied to assess symptoms, knowledge, and perceptions of bullying, and a focus group interview was conducted with six participants. Quantitative analyses revealed that the program improved participants’ knowledge and perceptions, but not their symptoms. The focus group interview revealed that the program improved participants’ coping skills and desire for education. This program could be effective in raising awareness of workplace bullying and increasing relevant coping skills. It can be further developed as part of an overall strategy to manage workplace bullying and its consequences in hospital settings.

This retrospective study evaluates the effect of a telemedicine program developed in the central Catalan region in lowering the environmental footprint by reducing the emission of atmospheric pollutants thanks to a reduction in the number of hospital visits involving journeys by road. Between January 2018 and June 2019 a total of 12,322 referrals were made to telemedicine services in the primary care centers, avoiding a total of 9,034 face-to-face visits. In total, the distance saved was 192,682 km, with a total travel time savings of 3,779 hours and a total fuel reduction of 11,754 liters with an associated cost of €15,664. This represents an average reduction of 3,248.3 g of carbon dioxide, 4.05 g of carbon monoxide, 4.86 g of nitric oxide and 3.2 g of sulphur dioxide. This study confirms that telemedicine reduces the environmental impact of atmospheric pollutants emitted by vehicles, reducing the number of journeys made for face-to-face visits and can contribute to environmental sustainability.

Freshwater fish represent half of all fish species and are the most threatened vertebrate group. Given their considerable passion and knowledge, aquarium hobbyists can play a vital role in their conservation. CARES is made up of many hobbyist organizations, whose purpose is to encourage aquarium hobbyists to the most endangered or extinct-in-the-wild freshwater fish to help ensure their survival. We found the CARES priority list contains nearly six hundred species from twenty families and two dozen species extinct-in-the-wild. The major families were typically the ones with largest hobbyist affiliations such as killifish, livebearers, and cichlids; which alone were half of CARES species. CARES contained every IUCN threatened species of Pseudomugilidae and Valenciidae, but only one percent of threatened Characidae, Cobitidae, and Gobiidae species. No Loricariidae in CARES were in the IUCN red list as they were not scientifically described. Tanzania and Mexico contained the largest amount of species, with the latter containing the most endemics. A large percent of species were classified differently than the IUCN, including a third of extinct-in-the-wild species classified as least concern by the IUCN. The vast disconnect exemplifies the importance of collaboration and information exchange required between hobbyists, the scientific community, and conservation organizations.

This research assess the effects of training program based on the usage of the digital learning objects in teaching practice at the Northern Borders University staff. E Assessment through the tablets and smart phones and the teachers’ attitudes towards such way of evaluation is the major objective of this study as the researcher expects that the assessment mechanism in the university through utilization of tablets and smart phones and its application will inevitably bring in a systematic improvement in the assessment and evaluation process of the curricula. Moreover, making use of the e learning objects in training will make a significant change in e training program of the university. Hence, the researcher has chosen voluntary random samples from the university teaching staff (men\women) from various different faculties (medicine, medical sciences, science, education and arts, business administration, home economics, and science and literature). These samples included 300 members of the teaching staff. In a group of 20 to 25 members, a personal training was conducted regarding the usage of tablets and smart phones and its applications in the assessment process. Each group participated by producing a complete e-assessment for their students in the Northern Borders University and by the e learning system i.e. Blackboard and Question Mark. The research also depends on the semi-experimental design of multiple groups and on testing the groups’ pre and post achievement tests. In addition, the research identifies the level of the university teaching staff in using the tablets and the smartphones and its applications in the assessment process by the note card that the individuals have during the test.

At-home rapid antigen test (RAT) kits for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are valuable public health tools during the present coronavirus disease (COVID-19) pandemic. They provide fast identification of coronavirus infection, which can help to reduce the transmission rates and burden on the healthcare system. However, they have lower sensitivity when compared with the reverse transcription polymerase chain reaction (RT-PCR) tests. One of the reasons for the lower sensitivity is due to the RAT color indicators being indistinct or invisible to the naked eye after the measurements. For this reason, we propose a systematic approach, through which we investigated anonymously provided at-home RAT kit results by using our in-house open source image processing scripts developed for affordable Raspberry Pi computer and Raspberry Pi HQ camera systems (available at https://github.com/kmiikki/ratcv). Therefore, we aimed at minimizing the human-related analysis errors for such kits. We believe that our framework can contribute to reduced the delayed quarantines of infected individuals and spreading of the current infectious disease.

The rapid growth in scientific article publications allows us to access articles as soon as possible. Therefore, automatic summarization systems (ATSs) are widely preferred. In most studies, the en-tire source document is expected to be summarized, just as it would be summarized by a human. Summarizing long articles, such as scientific articles, is quite difficult due to token restraint and extraction of scientific words. To address this problem, a novel Graph-Based Abstractive Summa-rization (GBAS) model is proposed, which is a novel scientific text summarization model based on SciBERT and the graph transformer network (GTN). The document's integrity is maintained since the SciIE system uses the graph structure to create a terminology-based document structure. Therefore, long documents are also summarized. The proposed model is compared with baseline models and human evaluation. Human evaluation results show that the results of the proposed model are informative, fluent, and consistent with the ground-truth summary. The experimental results indicate that the proposed model outperforms baseline models with a 37.10 and 34.96 ROUGE-L score.

Artificial intelligence (AI) is transforming many healthcare fields including pediatric urology. This in-depth review explores recent advances in AI tools for pediatric urology, emphasizing how state-of-the-art technologies can be used to enhance patient treatment. An initial overview of pediatric urology is given to provide context for this interdisciplinary field and the wide spectrum of problems this entails, before discussing potential uses of AI to improve diagnostic accuracy, treatment planning, and surgical results. AI-powered predictive models are already changing pediatric clinical practice by guiding interpretation of medical images and supporting decision making. In addition to outlining the aims, methods, and conclusions of previous studies on AI applications in pediatric urology, this review also highlights knowledge gaps and priority areas for future study. Particular focus is given to specialized surgeries such pyeloplasty, where AI-guided treatment may help overcome specific technical challenges of this complex procedure. Also highlighted are practical, ethical, and legal aspects of integrating AI into pediatric urology, which will be crucial for responsible innovation in patient-centered treatment. Overall, this article aims to enlighten and inspire clinicians, researchers, and other healthcare stakeholders by offering insight into the future of AI in pediatric urology.

This work investigates into the enhancement of iris recognition systems through a two-module approach focusing on low level image preprocessing techniques and advanced feature extraction. The first module is dedicated to the preprocessing of iris images, leveraging the Canny algorithm for edge detection followed by the circle-based Hough transform for precise iris extraction. This process, integral to our methodology, ensures the quality and consistency necessary for the subsequent Binary Statistical Image Features (BSIF) analysis. The second module employs the BSIF technique, incorporating domain-specific filters trained on iris-specific data, for robust biometric identification. By combining these advanced image preprocessing techniques, the proposed method addresses key challenges in iris recognition, such as occlusions, varying pigmentation, and textural diversity. Experimental results on the Human-inspired Domain-specific Binarized Image Features (HDBIF) Dataset composed of 1892 iris images demonstrate the effectiveness of the developped approach, with potential future improvements including adaptive algorithms and machine learning integrations for enhanced performance in diverse and unpredictable real-world applications. The novel contributions of this paper lie in the provision of a reproducible research framework, making the iris-domain-specific BSIF filters, training patches, testing database, and source codes publicly available for further application and study.

The agronomic characteristics of Cenchrus purpureus were assessed through a randomized block experimental design with seven accessions (Taiwan grass, King grass, Elephant grass, Merkeron, CT-115, Purpule grass and Maralfalfa) as treatments and four replications research was carried out at the Instituto Tecnológico Superior de Tantoyuca, in 2019 and 2020, under rainfed conditions. Sowing density was established at 36 tillers in 25 m2. Green and dry matter yield, daily rates of dry matter accumulation in leaves, leaf/stem ratio, height, leaf area index and cutting frequency were assessed. Rainfall amount, temperature, relative humidity and global radiation levels were recorded to assess their effect on the evaluated variables. One-way ANOVA and multivariate analysis techniques, such as multiple linear regression (MLR), Clustering, and Principal component analysis (PCA) with the Statistica V7 software, were used. The leaf area index was greatest (p < 0.05) on the dry season. Green and dry matter yield were greatest in Maralfalfa (p < 0.05). Variation in the results is attributed to weather phenomena; nonetheless, Elephant grass and Maralfalfa showed the highest yields. Quality parameters must be evaluated to identify those grasses with the best attributes.

This cross-sectional, analytical, and observational study aimed to investigate the relationship between Visceral Adiposity Index (VAI) and anthropometric, biochemical, and insulin resistance (IR) parameters in Brazilians at risk of CVD. Biochemical parameters and anthropometric measurements were evaluated. The Pearson test was used to assess the correlation between VAI and anthropometric, biochemical, and IR parameters, with a predefined significance level of 5%. The analyzed sample consisted of 88 men and 72 women, with an average age of 58.78±13.48. VAI revealed noteworthy and positive correlations with all anthropometric parameters assessed (p<0.0001). Furthermore, significant positive associations were noted between VAI and total cholesterol in women (p=0.0064), glycemia in men (p=0.0105), and LDL-c (p<0.01) and triglycerides in both genders (p˂0.0001). A significant negative association was observed between VAI and HDL-c in both genders (p<0.0001). Notably, the correlation between VAI and total cholesterol in men, glycemia in women, and CRP in both genders was not found to be significant. However, a significant relationship between VAI and IR parameters was observed in both sexes (p<0.05). The results obtained from our study suggest that VAI functions as a simple and non-intrusive instrument, demonstrating significant effectiveness in identifying metabolic changes primarily associated with adipose tissue dysfunction, particularly dyslipidemia.

Probiotics are living microbes that provide benefits to the host. The increasing data on health promotion following probiotics administration triggered growing interest among researchers and pharmaceutical companies looking for novel therapeutic or preventive tools. Infections of the lower genital tract in females are caused by a wide range of pathogens, they are widespread, and represent one of the main areas for the use of probiotics and postbiotics. Vulvovaginal candidiasis (VVC) affects 75% of women in their reproductive age at least once during their lifetime. Of these women 5-8% develop the recurrent form (RVVC). The disease onset is triggered by the overgrowth of Candida species on the vaginal mucosa. Here, we evaluated the beneficial properties of the Bacillus coagulans spore-producing LMG S-24828 against C. albicans and C. parapsilosis. Our results show that both alive B. coagulans and its Cell-Free-Supernatant (CFS) exerted antifungal activity against both fungi. Moreover, alive B. coagulans reduced hyphal formation, inhibited C. albicans adhesion to vaginal epithelial cells and showed co-aggregation capacity. Overall, B. coagulans LMG S-24828 exerted a protective effect on vaginal epithelial cells infected with C. albicans. These data suggest that B. coagulans LMG S-24828 may provide benefits in the context of Candida vaginal infections.

With the development of educational technology, machine learning and deep learning provide technical support for traditional classroom observation assessment. However, in real classroom scenarios, the technique faces challenges such as lack of clarity of raw images, complexity of datasets, multi-target detection errors and complexity of character interactions.Based on the above problems, a student classroom behavior recognition network incorporating super-resolution and target detection is proposed. To cope with the problem of unclear original images in the classroom scenario, SRGAN (Super Resolution Generative Adversarial Network for Images) is used to improve the image resolution and thus the recognition accuracy.To address the dataset complexity and multi-targeting problems, feature extraction is optimized and multi-scale feature recognition is enhanced by introducing AKConv and LASK attention mechanisms into the Backbone module of YOLOv8s algorithm. To improve the character interaction complexity problem, the CBAM attention mechanism is integrated to enhance the recognition of important feature channels and spatial regions. Experiments show that it can detect six behaviors of students raising their hands, reading, writing, playing cell phones, looking down, and lying on the table in high-definition images. And the accuracy and robustness of this network are verified.Compared with small target detection algorithms such as Faster R-CNN, YOLOv5, and YOLOv8s, this network has better detection performance and can efficiently deal with the behavior recognition of multiple students.

Background: Falls in hospitalized older patients lead to increased length of stay and poorer discharge outcomes. The Comprehensive Unit-based Safety Program (CUSP) represents a quality improvement intervention for patient safety. Objective: To evaluate CUSP implementation for the prevention of falls at a teaching hospital. Method: An interdisciplinary CUSP team, received a four-hour online module and one-day face-to-face training. The intervention was developed using the WHO implementation science plan-do-study-act framework. Process evaluation was conducted using the UK Medical Research Council framework. The primary outcome measure of patient safety culture was determined using the Safety Attitude Questionnaire (SAQ), while annual fall rates were considered the secondary outcome measure. Results: Safety rounds were conducted during the two-year intervention period, each attended by five to eight HCPs, with nine to 29 patients reviewed each month. Risk factors, plans and actions were administered to individual patients, while local issues were identified and resolved through engagement of senior executives. SAQ domains increased from before (n=39) to after (n=30) the intervention of CUSP. Fall rates reduced from 11.18 per 1,000 bed days pre-implementation to zero falls post-implementation. Conclusion: Improvements in patient safety culture were observed after the implementation of CUSP alongside a reduction in fall rates.

Spinal muscular atrophy 5q (SMA) is the most common neuromuscular inherited disease in neonates which is associated with homozygous deletion of exon 7 in the SMN1 gene. Recently established drugs can improve the motor functions of SMA infants when treated in the pre-symptomatic stage. With aim of providing an early diagnosis, newborn screening (NBS) for SMA using real-time PCR assay with dried blood spots (DBS) was performed in Saint-Petersburg from January 2022 through November 2022. Here, 36,140 newborns were screened by GenomeX real-time PCR-based screening test, and three genotypes were determined. Homozygous deletion carriers (4 newborns), heterozygous carriers (772 newborns) and wild-type individuals (35,364 newborns) were identified. All four newborns screened positive for homozygous SMN1 deletion were confirmed by alternate methods. Two of the newborns had two copies of SMN2, and two of the newborns had three copies. We determined Saint-Petersburg spinal muscular atrophy incidence of 1 in 9,035 and SMA carrier frequency of 1 in 47. In conclusion, it can be summarized that providing both timely SMN1 information and confirmation along with SMN2 copy number as part of SMA newborn screening algorithm can significantly improve clinical follow-up, family members testing, and SMA patients' treatment.

ackground: This study aimed to examine the effects of a woodworking program on psychosocial health in older adults who had mild cognitive impairment (MCI) or mild dementia (MD) in Korea. Setting: The study was carried out in a dementia center in Seoul in Korea. Population: A total of 61 participants who had MCI or MD were allocated into two groups: the experimental group (EG, n = 35) and the control group (CG, n = 26). Methods: This study was carried out using a nonequivalent control group pre-test–post-test design. The EG participated in the woodworking program a total of 10 times for 120 min per session twice a week for 5 weeks, and the CG did not participate in the woodworking program. Both groups completed the same survey before and after the intervention. In the survey, demographic characteristics, psychological health (life satisfaction, depression, self-efficacy, and resilience), and social health (social isolation and social support) were measured. Results: In the within-group comparison, there was no significant difference between any factors of the CG before and after the intervention. In contrast, the EG had a significant improvement before and after the woodworking program. Participants in the EG with MCI and MD significantly improved their social support (p < 0.05). Psychological factors (life satisfaction, depression, and self-efficacy) were positively changed, although not significantly. Conclusions: The woodworking program promoted psychosocial health, such as life satisfaction, resilience, and social support, among older adults with mild cognitive impairment and mild dementia.

After a long waited span, the whole world could see the ray of covid-19 vaccine to resist the planet to watch the death procession. But some country people especially the people of Bangladesh keep them aside to take the vaccination. This study aims to understand the perception towards the COVID-19 vaccination program in Bangladesh and the targeted subject is the university student as they are suffering highly depression nowadays. Higher education has been affected globally as a result of the COVID-19 pandemic in 223 countries. Moreover, for this pandemic situation, the university students can not complete their graduation which binds them to enter their professional career. Alike all of the developed countries, as well as developing countries, Bangladesh, also considered vaccination as an effective measure to protect the peoples from the Covid-19 virus. This study targeted three psychological factors of the university students and surveyed 322 students from the different universities in Bangladesh to understand their perception regarding vaccines. Moreover, it is seen that most of the students doubt the effectiveness of the vaccine which interrupts them from taking the vaccine willingly.

Background: Physical activity is recommended to mitigate the incidence of obesity, but delivery of community wide initiatives is cumbersome. The challenges met by such programs are magnified when implementation transpires in the remote villages of Alaska. To overcome the difficulty of this challenge in the Arctic, the Skiku/AK Nordic cross-country skiing program was developed. The objective of this study was to evaluate whether access to Skiku/AK Nordic program would promote physical activity levels that met the daily recommendations for physical activity in Alaska Native children. Methods: Eight children (4 females and 4 males; 10±2 years/age) were recruited from Kaktovik, Alaska for participation in this study. Expert coaches and staff provided one week of cross-country ski instruction and access to ski equipment. Physical activity was monitored using ActiGraph GT3X+ accelerometers. Data collected from the devices was then downloaded and analyzed using ActiLife software. Results: The participants expended ~586 calories/day devoted to physical activity. Light and moderate physical activity was 68±38 minutes/day and 447±248 minutes/day, respectively. Conclusions: Delivery of the Skiku/AK Nordic program promoted favorable levels of physical activity in Alaska Native children. Further research is needed to assess the longitudinal and seasonal effectiveness of the Skiku/AK Nordic program.

Kinesio tape is considered one of the most common techniques which using recently, where it is used as a therapeutic technique for pain relief, correction of joint position, prevention of oedema and injuries, improve range of motion and muscular activity for the individual. This study is a descriptive research design and aims to identify the effect of using Kinesio tape on the neuromuscular activity of quadriceps muscle after the rehabilitation program of the knee joint. The study sample consists of (10) players from different sports (football, basketball …etc.) and suffering from knee joint injuries. This sample was taken from Kafr-El sheikh and Kaleen club. Results showed that Kinesio tape doesn’t have any explicit effect on the neuromuscular activity of muscle but acts as a catalyst for muscle and promote a person’s feeling of psychological wellbeing and reassurance.When comparing results of using Kinesio tape during performing leg squatting and balance test with not using tape, founded that when performing leg squatting and balance test with using Kinesio tape, there were significant effects on muscle activity compared to not using it.

Preparing high school students for engineering disciplines is crucial for sustainable scientific and technological developments in the USA. This paper discusses a pre-college program, which not only exposes students to various engineering disciplines but also enables them to consider engineering as the profession. The four-week long “Engineering Innovation (EI)” course is offered every year to high school students by the center of outreach, Johns Hopkins University. EI program is designed to develop problem-solving skills through extensive hands-on engineering experiments. A team consisting of an instructor, generally a PhD in Engineering, and a teaching fellow, generally a high school science teacher, closely work with students to pedagogically inculcate basics of core engineering disciplines such as civil, mechanical, electrical, materials, and chemical engineering. EI values independent problem-solving skills and simultaneously promote the team spirit among students. A number of crucial engineering aspects such as professional ethics, communications, technical writing, and understanding of common engineering principles are inculcated among high school students via well-designed individual and group activities. This paper discusses the model of EI program and its impact on students learning and their preparation for the engineering career.

Breast cancer is an important disease that threatens the lives of women. The majority of breast screening health education is printed promotional material, which is ineffective in enhancing women’s knowledge on breast screening in Taiwan, and showed low breast cancer screening rate in women. This provided the impetus for us to carry out this study to understand the major barrier of women on breast cancer and screening procedures. This study used quasi-experimental design and purposive sampling. The study participants were 45–69 year-old women. Data collection was carried out before and after intervention. The health belief model was used as a research framework to examine changes in the study participants after multimedia health education intervention for detecting which factors most affect women's breast cancer screening behavior. Then we could make the policy for enhancing women's breast cancer screening in the future. Our study showed that after multimedia health education intervention, the scores of perceived susceptibility, perceived seriousness, perceived benefits, perceived barriers, cues to action, and self-efficacy in the experimental group were all significantly higher than the control group. We believe that the effectiveness of multimedia health education is better than traditional health education methods, and can enhance women to receive breast cancer screening.

The results of this study offer a potential to gain a better understanding of the mechanisms underlying the falls in the elderly. The results were recorded for a group of 27 women in a control group (CON) and 16 women in an experimental group (EXP), aged 60-70. Participants took part in the six-weeks Elderly Recreation Movement Program (ERMP) with the difference, that the EXP group practiced twice as often as the CON group. The measurement of variations in the index called limits of stability (LOS) was performed by application of Kistler force plate and the coactivation index (CI) was registered by means of sEMG. The results demonstrate the existence of statistically significant differences in terms of the principal outcome of the exercise time in the measurements of LOS (F (1.42) = 10.0, p = 0.003), and CI (F (1.42) = 10.5, p = 0.002). The effect of the program was associated with an increase the level of the maximum LOS, and a decrease of the CI level, especially in the experimental group. Hence, the implementation of an innovative ERMP exercise program results in the improvement of the physical capabilities of senior subjects and a reduction of the risk of falls.

Credit card payment platforms are increasingly used for e-commerce activities. Credit cards are payment cards issued to individuals so they can purchase products and services based on their accumulated debt. Since credit cards are becoming very popular and widely used, the number of related fraud cases is likewise increasing. Whereas, there are large numbers of credit card transactions daily; thus, it becomes complex to differentiate between fraudulent and non-fraudulent transactions. Accordingly, different machine learning (ML) tools have been deployed in the literature to filter credit card transactions to prevent cardholders and financial institutions from losing money. In this article, the ensemble hidden Markov model (EHMM) approach is deployed to predict credit card fraud. EHMM is a popular and flexible ML tool that can easily model randomly changing datasets. Yet, the performance of the EHMM solely depends on the adopted feature extraction technique. The more reliable the feature extraction technique, the better the performance of the EHMM. In this vein, this article analyses two feature extraction techniques that can be combined with the EHMM for the prediction of credit card fraud. First, the principal component analysis (PCA) feature extraction techniques are combined with the EHMM to effectively predict credit card fraud. Yet, the PCA increases the computational time complexity of the EHMM. Therefore, this article adapts some statistical features to reduce the computational time complexity imposed on the EHMM. These robust but simple statistical features termed MRE; Mean, Relative Amplitude, and Entropy, are merged to form a feature vector that can be combined with the EHMM to effectively predict credit card frauds. The performance of the PCA-EHMM and MRE-EHMM are evaluated using the credit card transactions dataset of European cardholders gathered within two days in September 2013. The results were documented using different performance metrics such as recall/sensitivity, specificity, precision, and F1-score. The findings of this article will offer solutions to the loss experienced by cardholders and financial institutions as a result of online banking which requires credit card details.

Early and accurate mapping of winter canola planting areas provides critical support for sustainable cropland management. Although some methods have been proposed to map the winter canola at the flowering or later stage, mapping winter canola planting areas at the early stage is still challenging, due to the insufficient understanding of the multi-source remote sensing features sensitive for winter canola mapping. This study proposed an early-stage winter canola area mapping method by using the combination of optical and synthetic aperture radar (SAR) data. We analyzed the spectral features, backscatter coefficients, and textural features of winter canola based on Sentinel-2 and Sentinel-1 images. Random forest (RF) and Support Vector Machine (SVM) classification models were built to map winter canola based on early-stage images and field samples in 2017 and then apply the best model to corresponding satellite data in 2018-2022. Results showed that: (1) The red edge and near-infrared-related spectral features were most important for the mapping of early-stage winter canola, followed by VV, DVI and GOSAVI, which also showed greater differences than the other features; (2) Based on Sentinel-1 and Sentinel-2 data, winter canola could be earliest mapped around 130 days prior to ripening (i.e., early overwinter stage) with the F-score over 0.85 and the OA over 81%; (3) Adding Sentinel-1 could improve the OA by about 2%-4% and the F-score by about 1% -2% in winter canola mapping. (4) The F-score of winter canola mapping based on the classifier transfer approach in 2018-2022 varied between 0.75 and 0.97, and the OA ranged from 79% to 86%. This study demonstrates the potential of early-stage winter canola mapping using the combination of Sentinel-2 and Sentinel-1 images, which could provide valuable and timely information for stakeholders and decision makers.

Identification and measurement of pain are critical aspects of designing effective pain management interventions aimed at alleviating suffering and preventing a functional decline in the health medical domain. Traditional methods of pain identification rely on verbal patient reports or observable signs. However, these approaches may be imprecise or subjective due to the variability in patient self-assessments. Therefore, there is a pressing need for automated methods that can standardize pain measurement procedures. In this paper, we propose a novel facial expression-based automated pain assessment system as a behavioral indicator for pain evaluation. Our system integrates a fusion structure comprising Convolutional Neural Networks (CNNs) and Tensor-based extended Quantitative Expression Descriptors Analysis (TXQEDA). This innovative approach allows for the joint learning of robust pain-related facial expression features from raw facial images, combining RGB appearance with shape-based latent representation. We extensively evaluated our proposed model using the UNBC-McMaster dataset for pain classification and intensity estimation. Our results demonstrate the efficacy of the proposed technique, achieving an impressive accuracy of 98.80% for pain level classification. Furthermore, our system excels in pain intensity estimation, showcasing its potential to provide precise and reliable assessments of pain severity. Overall, our research underscores the importance of automated pain assessment systems in improving patient care and clinical outcomes. By leveraging advanced deep learning techniques and fusion strategies, our proposed model offers a promising approach for standardizing pain measurement procedures and enhancing the quality of pain management interventions.

Stueckelberg-Horwitz-Piron (SHP) electrodynamics formalizes the distinction between coordinate time (measured by laboratory clocks) and chronology (temporal ordering) by defining 4D spacetime events x^μ as functions of an external evolution parameter τ. Classical spacetime events x^μ (τ) evolve as τ grows monotonically, tracing out particle worldlines dynamically and inducing the five U(1) gauge potentials through which events interact. Since Lorentz invariance imposes time reversal symmetry on x⁰ but not τ, the formalism resolves grandfather paradoxes and related problems of irreversibility. The action involves standard first order field derivatives but includes a higher order τ derivative that while preserving gauge and Lorentz invariance removes certain singularities and makes the related QFT super-renormalizable. The resulting field equations are Maxwell-like but τ-dependent and sourced by a current that represents a statistical ensemble of instantaneous events distributed along the worldline. The width λ of this distribution defines a correlation time for the interactions and a mass spectrum for the photons that carry the interaction. As λ becomes very large, the photon mass goes to zero and the field equations become τ-independent Maxwell’s equations. Maxwell theory thus emerges as an equilibrium limit of SHP, in which λ is larger than any other relevant time scale. Particles and fields are not constrained to mass shells in SHP theory, and by exchanging mass may produce pair creation/annihilation processes at the classical level. On-shell evolution with fixed particle masses is restored through a self-interaction associated with the 5D wave equation.

Rosavin, a phenylpropanoid in Rhodiola rosea's rhizome, an adaptogen, is known for enhancing the body's response to environmental stress. It significantly affects cellular metabolism in health and many diseases, particularly influencing bone tissue metabolism. In vitro, rosavin inhibits osteoclastogenesis, disrupts F-actin rings formation, and lowers osteoclastogenesis-related gene expression (cathepsin K, CTR, TRAF6, TRAP, MMP-9). It also impedes NFATc1, c-Fos, NF-κB, and MAPK signaling pathways, and blocks phosphorylation processes crucial for bone resorption. Moreover, rosavin promotes osteogenesis, osteoblast differentiation and increases Runx2 and OCN expression. In vivo studies show its effectiveness in enhancing BMD in PMOP mice, re-straining osteoclast maturation, and increasing active osteoblast percentage in bone tissue. It modulates mRNA expressions (increasing EEF2 and decreasing HDAC1, thereby activating os-teoprotective epigenetic mechanisms) and alters various serum markers, including decrease of CTX-1, TRAcp5b, RANKL, M-CSF, TRAP, and increase of ALP and OCN. Additionally, when combined with zinc and probiotics, it reduces pro-osteoporotic MMP-3, IL-6, TNF-α, and en-hances anti-osteoporotic IL-10 and TIMP3 expressions. This paper aims to systematically review rosavin's impact on bone tissue metabolism, exploring its potential in osteoporosis prevention and treatment, and suggesting future research directions.

This review explores the transformative impact of sensor technologies in early disease detection. It highlights recent advancements in nanotechnology-based sensors, particularly focusing on their applications in identifying disease biomarkers at early stages. The integration of these sensors with artificial intelligence for predictive analytics in healthcare is also discussed. Applications in cancer, infectious diseases, and chronic disease management underscore their diverse utility. Challenges in sensor technology adoption and future directions, including multiplexed sensors and wearable devices, are examined. This review underscores sensors' potential in enhancing disease management and patient outcomes.

Herpesvirus is a prevalent pathogen that primarily infects human epithelial cells and has the ability to reside in neurons. In the field of otolaryngology, herpesvirus infection primarily leads to hearing loss and vestibular neuritis, and is considered the primary hypothesis regarding the pathogenesis of vestibular neuritis. In this review, we provide a summary of the effects of herpes virus on cellular processes in both host cells and immune cells, with a focus on HSV-1 as illus-trative examples.

Energy demand has exponentially increased with the increase in the world population and ur-banization. Renewable energy is clean, renewable, and environmentally friendly. Hydrogen production through Proton Exchange Membrane (PEM) electrolyzer is an efficient way to produce renewable energy. The efficiency and energy consumption of the PEM electrolyzer depends on the feed water quality. In this report, we study the effect of pH, TDS, and conductivity on hydrogen production as well as energy consumption during the process. pH values (3, 7, 9), TDS values (300ppm, 600ppm, 900ppm), and conductivity values (30mS/cm, 70mS/cm, 100mS/cm) were studied to understand and optimize the hydrogen production using PEM electrolyzer. The in-vestigations showed that hydrogen production is significantly affected by pH, total dissolved solids, and conductivity, and the best levels of each variable were identified by extensive testing. The findings show both the scientific significance of proton exchange electrolysis in meeting the growing energy demands of society as well as the importance of knowing the influence that di-verse conditions have on the creation of hydrogen. Our research, in general, contributes to the expanding body of scientific knowledge on the topic of the effective production of hydrogen and offers useful insights for the continuation of investigation in this field.

The article is aimed at a brief comparison and analysis of the results of queries to IEEE Xplore and the leading abstract databases Scopus and Web of Science to identify research trends. Some errors in the Author Keywords in Web of Science have been revealed. Therefore, a more detailed analysis was conducted by comparing different types of key terms for IEEE Xplore and Scopus platforms only. I used IEEE Access journal metadata as indexed on both platforms. The sample match for IEEE Xplore and Scopus was achieved by comparing DOI. The IEEE Xplore metadata contains more types of key terms, which provides an advantage in analyzing research trends. Using NSPEC Controlled Terms from expert-compiled vocabulary provides a more stable data, which gives an advantage when considering the change of terms over time. Apriori, an algorithm for finding association rules, has been used to compare co-occurrence of terms for a more detailed description of sample subjects on both platforms. VOSviewer was used to analyze trends in scientific research based on IEEE Xplore data. The 2011-2021 ten-year period was divided into two sub-intervals for comparing the occurrence of Author Keywords, IEEE Terms, and NSPEC Controlled Terms. Using the IEEE conference proceedings bibliometric data, I illustrated the importance of context in estimating the rate of growth of publishing activity on a topic of interest.

Intravitreal injection is the gold standard therapeutic option for posterior segment pathologies, and long-lasting release is necessary to avoid reinjections. There is no effective intravitreal treatment for glaucoma or other optic neuropathies in daily practice, nor is there a non-invasive method to monitor drug levels in the vitreous. Here we show that a glaucoma treatment combining a hypotensive and neuroprotective intravitreal formulation (IF) of brimonidine-Laponite (BRI/LAP) can be monitored non-invasively using vitreous imaging captured with optical coherence tomography (OCT) over 24 weeks of follow-up. Qualitative and quantitative characterization was achieved by analysing the changes in vitreous (VIT) signal intensity, expressed as a ratio of retinal pigment epithelium (RPE) intensity. Vitreous hyperreflective aggregates mixed in the vitreous and tended to settle on the retinal surface. Relative intensity and aggregate size progressively decreased over 24 weeks in treated rat eyes as the BRI/LAP IF degraded. VIT/RPE relative intensity and total aggregate area correlated with brimonidine levels measured in the eye. The OCT-derived VIT/RPE relative intensity may be a useful and objective marker for non-invasive monitoring of BRI/LAP IF.

Traceability has been applied in the fisheries, for example in tuna, as a means of verification and validation of the quality of fish meat and its origin. Traceability as a platform in the fisheries remains elusive in many parts of the country due to slow adoption. This study reviewed the existing literature in relation to, “agri-fishery traceability system,” “fishery traceability,” and “food safety” from year 2000-2023. It aimed to elucidate the common drivers and barriers to the adoption of fisheries traceability system. The authors used PRISMA to analyse articles obtained from SCOPUS and WOS (Web of Science), DOAJ (Directory of Open Access Journal), Academia, and PubMed central databases. The results showed that 125 articles were included after the inclusion and exclusion process. There were nine articles included in the year 2000 to 2005, followed by 19 in 2006 to 2010, and 26 from the year 2011 to 2015. A total of 40 articles were recorded from the year 2016 to 2020 and 31 from the year 2021 to 2023. In terms of text data from the authors, “fish”, “supply chain”, “traceability system”, and “food safety” have the highest total link strength. Moreover, food safety, market compliance, consumer protection, product origin, quality, and seafood fraud are driving factors in the implementation of traceability system. Costs, inadequate practices, lack of support from the government, infrastructure, information, and laws and regulations are foreseen barriers to the adoption of a traceability system. Leading countries in fisheries traceability studies include, China, USA, Italy, Indonesia, UK, and Taiwan where the first and corresponding authors originated. While this review endeavored to find fish traceability studies in the Philippines, the lack of comprehensive and relevant literature published in this topic shifted our focus to finding barriers and drivers to adopting a traceability system. We recommend that government agencies that oversee various commodities, should link up with academics and non-government organizations in the implementation and monitoring of their traceability systems.

In the context of restorative dentistry and the use of different techniques and dental adhesive systems, this study was to designed to assess the degree of adhesive absorption and wetting for each dental micro applicator; and also quantify the amount of lost fiber flocks after three applications of dental adhesive on the inside surface of a plastic veneer tooth in order to reveal a potential contaminating factor at the adhesive interface. Initially, one drop of dental adhesive was dispensed into a glass dental mixing well. The dental adhesive was then applied onto the inside surface of the veneer restoration for 30s using a dental micro applicator which was weighed afterwards. For each dental micro applicator, this sequence was repeated three times and measured again by the same operator. Each adhesive application was analyzed separately, to show the values independently and compare them to the initial weight. The samples of Fiber-Free Elastomer Bristle Micro Applicators (FEBM) demonstrated the best performance with a good degree of absorption and wetting of the dental adhesive without the loss fiber flocks and release-induced weight loss. The samples of Conventional Fiber Flocked Micro Applicators (CFFM) demonstrated good initial absorption and wetting of the dental adhesive, but visually shed several fiber flocks which resulted in significant weight loss and can also be considered a contaminating factor at the adhesive interface.

Cocoa is an important commodity crop not only to produce one of the most complex products such as chocolate from the sensory perspective, but one that commonly grows in developing countries close to the tropics. This paper presents novel techniques applied using cover photography and a novel computer application (VitiCanopy) to assess the canopy architecture of cocoa trees in a commercial plantation in Queensland, Australia. From the cocoa trees monitored, pod samples were collected, fermented, dried and grinded to obtain the aroma profile per tree using gas chromatography. The canopy architecture data were used as inputs in an artificial neural network (ANN) algorithm and the aroma profile considering six main aromas as targets. The ANN model rendered high accuracy (R = 0.82; MSE = 0.09) with no overfitting. The model was then applied to a satellite image from the whole cocoa field studied to produce canopy vigor and aroma profile maps up to the tree-by-tree scale. The tool developed could aid significantly the canopy management practices in cocoa trees that have a direct effect on cocoa quality.

Alcoholic liver disease (ALD) is a major cause of chronic liver disease. This term covers a broad spectrum of liver lesions, from simple steatosis to alcoholic hepatitis and cirrhosis. The patho-genesis of ALD is multifactorial and not fully elucidated due to complex mechanisms related to direct ethanol toxicity with subsequent hepatic and systemic inflammation. The accumulation of pro-inflammatory cytokines and the reduction of anti-inflammatory cytokines promote the development and progression of ALD. To date, there are no targeted therapies to counteract disease progression and prevent acute liver failure. Corticosteroids reduce mortality by acting on the hepatic-systemic inflammation. On the other hand, several studies analyzed the effect of the inhibition of pro-inflammatory cytokines and the stimulation of anti-inflammatory cytokines as potential therapeutic targets in ALD. This narrative review aims to clarify the role of the cy-tokines in the pathogenesis and treatment of ALD.

Monte Carlo simulations were conducted to investigate the interaction between nucleation and the rates of chemical reduction in Au/Ag, Au/Pt and Au/Pd nanoparticles prepared in microemulsions using a one-pot method. The impact of nucleation on final nanostructure depends on the critical nucleus size value: at a high critical nucleus size, nucleation becomes the main factor in determining the final nanostructure, even with very large difference in reduction rates, as seen in the Au/Pd pair. However, when the critical nucleus size is small, the difference in reduction rates of the two metals becomes the key parameter determining the final nanostructure. Furthermore, the relevance of heteroatomic nucleation on the mechanism of nanoparticle formation depends on the difference between the reduction rates of the two metals. Smaller differences, such as in the Au/Ag or Au/Pt pairs, result in a greater impact of heteroatomic nucleation on the final nanostructure. In contrast, in the Au/Pd pair, heteroatomic nucleation becomes less important due to the low availability of Pd until late stages of synthesis. This study provides deeper insight into the complex mechanisms that govern reactions in microemulsions.

This research addresses the respiratory distress syndrome (RDS) in preterm newborns, caused by insufficient surfactant synthesis, which can lead to serious complications, including pneumothorax, pulmonary hypertension, and pulmonary hemorrhage, increasing the risk of a fatal outcome. By analyzing chest radiographs and blood gases, we specifically focus on the significant contributions of these parameters to the diagnosis and analysis of the recovery of patients with RDS. The study involved 32 preterm newborns, and the analysis of gas parameters before and after the administration of surfactants and inhalation corticosteroid therapy revealed statistically significant changes in values of parameters such as FiO2, pH, pCO2, HCO3 and BE (Sig.&lt;0.05), ehile the pO2 parameter showed a potential change (Sig.=0.061). Parallel to this, the research emphasizes the development of a lung segmentation algorithm implemented in the MATLAB programming environment. The key steps of the algorithm include preprocessing, segmentation, and visualization for a more detailed understanding of the recovery dynamics after RDS. These algorithms have achieved promising results, with a global accuracy of 0.93±0.06, precision 0.81±0.16 and an F-score of 0.82±0.14. These results highlight the potential application of algorithms in the analysis and monitoring of recovery in newborns with RDS, also underscoring the need for further development of software solutions in medicine, particularly in neonatology, to enhance the diagnosis and treatment of preterm newborns with respiratory distress syndrome.

This paper proposes several LabVIEW applications to accomplish the data acquisition, processing, features extraction and real-time classification of the electroencephalographic (EEG) signal detected by the embedded sensor of the NeuroSky Mindwave Mobile headset. The LabVIEW applications are aimed at the implementation of a Brain-Computer Interface system, which is necessary to people with neuromotor disabilities. It is analyzed a novel approach regarding the preparation and automatic generation of the EEG dataset by identifying the most relevant multiple mixtures between selected EEG rhythms (both time and frequency domains of raw signal, delta, theta, alpha, beta, gamma) and extracted statistical features (mean, median, standard deviation, route mean square, Kurtosis coefficient and others). The acquired raw EEG signal is processed and segmented into temporal sequences corresponding to the detection of the multiple voluntary eye-blinks EEG patterns. The main LabVIEW application accomplished the optimal real-time artificial neural networks techniques for the classification of the EEG temporal sequences corresponding to the four states: 0 - No Eye-Blink Detected; 1 - One Eye-Blink Detected; 2 – Two Eye-Blinks Detected and 3 – Three Eye-Blinks Detected. Nevertheless, the application can be used to classify other EEG patterns corresponding to different cognitive tasks, since the whole functionality and working principle could estimate the labels associated with various classes.

Besides the increase in global energy demand, access to clean energy, reduction in greenhouse gas emissions caused by conventional power generation sources, energy security, and availability of electricity in remote villages in emerging nations are some of the factors that foster the use of renewable energy sources (RESs) in generating electricity. One of the aims of initiating microgrids (MGs) is to maximize the benefits of RES and alleviate the associated grid integration issues. Microgrids are made up of RES connected to electrical loads within clearly delineated electrical limits that operate as individual controllable units on the electrical network. It can operate in-dependently as well as in connection with the grid. The paper presents an overview of microgrids and investigates the system's performance when connected to and disconnected from the grid. Furthermore, in both modes of operation, the functioning and behavior of system components such as the bidirectional DC-DC converter and energy storage system (ESS) were evaluated. The architecture of the proposed microgrid consists of a small hydropower plant, a wind farm, and a battery energy storage system (BESS). The microgrid under investigation is modeled and simu-lated using MATLAB and Simulink.

In this paper, a completely different metaheuristic algorithm called the Orangutan Optimization Algorithm (OOA) is introduced, which replicates the complex and adaptive behaviors of Orangutans in their natural habitat. The main inspiration for OOA lies in the strategic foraging techniques of Orangutans, alongside their highly developed nesting abilities. More words are used to provide a detailed theoretical explanation of OOA, followed by a comprehensive modeling of the algorithm’s implementation in two key phases: exploration and exploitation. These phases are mathematically structured to ensure the balance required for optimal search processes. The performance of OOA is rigorously evaluated using twenty-nine benchmark functions from the CEC 2017 test suite, with problem dimensions of 10, 30, 50, and 100. More sentences are included to elaborate on the optimization outcomes, which reveal that OOA effectively balances the exploration and exploitation stages, yielding suitable and competitive solutions across the benchmark functions. Additionally, to further validate its quality, the results from OOA are compared against twelve other well-established metaheuristic algorithms. The analysis of these simulation results demonstrates that OOA consistently outperforms competing algorithms by achieving superior results across most benchmark functions. Furthermore, to assess its real-world applicability, OOA is implemented on a set of twenty-two constrained optimization problems drawn from the CEC 2011 test suite. The extended simulation results clearly indicate that OOA is highly efficient in solving real-world optimization challenges, consistently delivering a superior performance when compared to other competitor algorithms.

This paper provides a comparative analysis of AES (Advanced Encryption Standard) and Salsa20 algorithm implementations, focusing on power consumption efficiency in passive RFID (Radio Frequency Identification) tags and ultra-low-power devices. The main objective of this work is to determine which of these algorithms is more suitable to operate in these types of devices. For this purpose, ASIC (Application-Specific Integrated Circuit) implementations of AES and Salsa20 based on low-power approaches were developed and their power consumption was evaluated. Results demonstrate that Salsa20 power consumption is lower than AES (2.82μW and 4.01μW, respectively - both in 0.18μm), indicating that Salsa20 is a better choice than AES for passive RFID tags.

We aimed to determine if infection-associated urine biomarkers can differentiate true urinary tract infection (UTI) from non-UTI controls. Midstream clean-catch urine samples were collected from asymptomatic volunteers and symptomatic subjects > 60 years old diagnosed with presumptive UTI in a specialty setting. Microbial identification and density were assessed using multiplex PCR/pooled antibiotic susceptibility test (M-PCR/P-AST) and standard urine culture (SUC). Three biomarkers (NGAL, IL-8, and IL-1β) were measured in the same urine specimens. Definitive UTI cases were symptomatic and had positive microorganism detection by SUC and M-PCR, while definitive non-UTI cases were asymptomatic volunteers regardless of microbial detection. We observed a strong positive correlation (R2 ≈ 1) between microbial density and the biomarkers NGAL, IL-8, and IL-1β. Biomarker consensus criteria of two or more positive biomarkers had sensitivity 90.2%, specificity 91.2%, positive predictive value (PPV) 91.7%, negative predictive value (NPV) 89.7%, accuracy 90.7%, positive likelihood ratio of 10.28, and negative likelihood ratio of 0.11 in differentiating definitive UTI from non-UTI cases, regardless of microbial density. NGAL, IL-8, and IL-1β showed a significant elevation in symptomatic cases with positive microbe identification compared to asymptomatic cases with or without microbe identification. Biomarker consensus exhibited high accuracy in distinguishing UTI from non-UTI cases.

The global meat industry has grown substantially, producing 357.39 million tons in 2021, with poultry and pork comprising nearly 73% of this total. However, contamination by mycotoxins, such as zearalenone (ZEA) and fumonisin B1 (FB1), presents a major issue, as these toxins resist common preservation methods. This study explores the potential of bioprotective microorganisms in mycotoxin degradation and fungal control within the animal food production chain, a sector facing significant challenges due to fungal contamination. In this study, 23 bacterial and yeast strains were tested for their ability to degrade ZEA and FB1, and to inhibit mycotoxigenic fungi. Four bacterial strains were highly effective in degrading ZEA: Bacillus amyloliquefaciens MLB3, Bacillus subtilis MLB2, Bacillus velezensis CL197, and Streptomyces griseus CECT 3276. However, no strain achieved satisfactory FB1 degradation. The strains also displayed antifungal activity, inhibiting up to 100% of fungi growth in solid media co-culture tests. Simulated swine and poultry digestion demonstrated complete ZEA degradation after 2 hours of incubation. Metabolite analysis revealed that low-toxicity conjugates were formed. These findings suggest that these bacteria hold significant promise for biotechnological applications in animal production, helping to reduce mycotoxin contamination, improve food safety, and protect both animal and human health.

The paper presents the design and the implementation of different advanced control strategies that are applied to a nonlinear model of a thermal unit. A data–driven grey–box identification approach provided the physically meaningful nonlinear continuous–time model, which represents the benchmark exploited in this work. The control problem of this thermal unit is important since it constitutes the key element of passive air conditioning systems. The advanced control schemes analysed in this paper are used to regulate the outflow air temperature of the thermal unit by exploiting the inflow air speed, whilst the inflow air temperature is considered as an external disturbance. The reliability and robustness issues of the suggested control methodologies are verified with a Monte–Carlo analysis for simulating modelling uncertainty, disturbance and measurement errors. The achieved results serve to demonstrate the effectiveness and the viable application the suggested control solutions to air conditioning systems. The benchmark model represents one of the key issues of this study, which is exploited for benchmarking different model–based and data–driven advanced control methodologies through extensive simulations. Moreover, this work highlights the main features of the proposed control schemes, while providing practitioners and heating, ventilating and air conditioning engineers with tools to design robust control strategies for air conditioning systems.

Optical coherence tomography (OCT) is a non-invasive imaging technique widely used in ophthalmology for visualizing retinal layers, aiding in early detection and monitoring of retinal diseases. OCT is useful for detecting diseases such as age-related macular degeneration (AMD) and diabetic macular edema (DME), which affect millions of people globally. Over the past decade, the area of application of Artificial Intelligence (AI), particularly Deep Learning (DL), has significantly increased. The number of medical applications is also rising, with solutions from other domains being increasingly applied to OCT. The segmentation of biomarkers is an essential problem that can enhance the quality of retinal disease diagnostics. For 3D OCT scans, AI is beneficial since manual segmentation is very labor-intensive. In this paper, we employ the new SAM 2 and MedSAM 2 for the segmentation of OCT volumes for two open-source datasets, comparing their performance with the traditional U-Net. The model achieved an overall Dice score of 0.913 and 0.902 for macular holes (MH) and intraretinal cysts (IRC) on OIMHS and 0.888 and 0.909 for intraretinal fluid (IRF) and pigment epithelial detachment (PED) on the AROI dataset, respectively.

Digital skills are essential in today’s digital age, which means that students must gain technology-enhanced skills from higher education for their future careers. Studies in Art & Design (A&D) programs in this university surveyed three faculties’ perspectives and nineteen students’ experiences. During the COVID-19 pandemic, this university changed its teaching and learning strategies by offering courses online during autumn 2020 and spring 2021 during mandatory quarantine. However, the A&D program was not entirely based online. As a result, it is important to take a closer look at the A&D programs offered in order to assess the faculties’ perspectives and students’ experiences during the two online semesters. The study included online surveys from instructors’ perspectives and with regard to students’ experiences about the quality of studio learning, traditional studio learning opportunities, and online studio learning opportunities via either live (on-campus) or online studios. Using relationship-based research design, posttest data surveys were collected to ascertain the differences in the mean scores, standard deviations, and percentages of some forms of agreement between the faculties’ perspectives and students’ experiences of the quality of studio learning, traditional studio learning opportunities, and online studio learning opportunities in these Art & Design (A&D) programs. This quantitative research aimed to develop formative assessments and suggestions while establishing whether it would be possible to hold all A&D courses online in a higher education setting.

Background: This study aimed to develop and evaluate a dietary self-care promotion program for hemodialysis patients based on Hurley's self-efficacy model. Methods: The needs of hemodialysis patients were identified, and an online community-based dietary self-care promotion program was developed with expert evaluations. 44 hemodialysis patients were randomly assigned to an experimental group (n=22) and a control group (n=22). The program was applied to the experimental group for four weeks. Before and after the intervention, as well as four weeks after the intervention, dietary self-efficacy, dietary self-care behavior, interdialytic weight gain, serum phosphorus, and serum potassium were assessed in both groups. Results: Significant differences over time and between groups were observed in dietary self-efficacy, interdialytic weight gain, serum phosphorus, and serum potassium. The interaction between time and group was also significant. While no significant differences were found over time in dietary self-care behavior, significant group differences and interaction effects between time and group were identified. Conclusions: The results indicate that the dietary self-care promotion program using an online community for hemodialysis patients is more effective in enhancing dietary self-efficacy and dietary self-care behavior compared to conventional treatment. This suggests the clinical applicability of the proposed dietary self-care promotion program.

Abstract: Objective: The aim of this study is to evaluate the effectiveness of an affective-sexual education programme among 14-15 year-old adolescents and its impact on their perception of their health. Design: This is a quantitative, descriptive and prospective quasi-experimental study, employing various cross-sections throughout the school year. It constitutes an educational promotion intervention where a health blog serves as a supplementary component to the "Health and School" programme. This phase is assessed using specific tools designed to evaluate scales. The study aims to assess the programme's effectiveness in the areas of knowledge and attitudes related to sexuality, sexually transmitted diseases, and affectivity. Additionally, it aims to evaluate the intervention's impact on 292 secondary school students, divided into a control group (N=144) and an intervention group (N=148). Both groups belong to the same population and have undergone affective-sexual education interventions focusing on gender and sexual diversity perspectives. The assessment considers perceptions and behaviours related to knowledge about HIV and other STDs/STIs, attitudes towards HIV, health anxiety, and AIDS phobia. Cross-sectional comparisons between the control and intervention groups are conducted at three points during the school year: longitudinal study, baseline, at month 4, and at month 9 post-intervention. Methods: Median and interquartile range, Wilcoxon test for numerical variables and Fisher's test for categorical variables were calculated according to intervention group. Results: 53% of the students reported a very good perception of health, compared to 45% with a good perception. Boys reported a good perception of health (85%) and had perceptions of their physical appearance and health (p=0.023) and (p<0.001) in the intervention group. Differences were found between perceptions of physical appearance in the control group, which was close to normal (p=0.429). In terms of level of knowledge about HIV and other STDs/STIs, the most significant difference was found in knowledge about HIV transmission, which varied between groups. Conclusions: Early affective-sex education sessions have an impact on health perception and behaviours related to knowledge about HIV and other STDs/STIs, leading to reduced anxiety in adolescents. School nurses should focus on health promotion, prevention of sex-related diseases, healthy attitudes from a gender perspective and integrated affective relationships in all their dimensions.

The opioid crisis in the United States has had devastating effects on communities across the country, leading many states to pass legislation that limits the prescription of opioid medications in an effort to reduce the number of overdose deaths. This study evaluates the impact of two categories of PDMP and Pill Mill regulations on the supply of opioid prescriptions at the level of dispensers and distributors (excluding manufacturers) using ARCOS data. The study uses a difference-in-difference method with a two-way fixed design to analyze the data. The study finds that both of the regulations are associated with reductions in the volume of opioid distribution. However, the study reveals that these regulations may have unintended consequences, such as shifting the distribution of controlled substances to neighboring states. For example, in Tennessee, the implementation of Operational PDMP regulations reduces in-state distribution of opioid drugs by 3.36% (95% CI, 2.37 to 4.3), while the out-of-state distribution to Georgia, which did not have effective PDMP regulations in place, increases by 16.93% (95% CI, 16.42 to 17.44). Our studies emphasize that policymakers should consider the potential for unintended distribution shifts of opioid drugs to neighboring states with laxer regulations as well as varying impacts on different dispenser types.

Mindfulness-based interventions (MBIs) have been shown to improve health and well-being in adolescents with chronic illnesses. Because they are most often delivered in person in a group setting, there are several barriers that limit access to MBIs for youth with limited mobility or who cannot access in-person MBIs in their communities. The objective of this study was to determine if eHealth is a viable platform to increase accessibility to MBIs for teens with chronic illnesses. This study reports the qualitative results of a mixed method randomized trial describing the experience of the Mindful Awareness and Resilience Skills for Adolescents (MARS-A) program, an 8-week MBI, delivered either in person or via eHealth. Participants were adolescents between the ages of 13 and 18 with a chronic illness recruited at a tertiary pediatric hospital in Toronto, Canada. Individual semi-structured post-participation audio-video interviews were conducted by a research assistant. A multiple-pass inductive process was used to review interview transcripts and interpret emergent themes from the participants’ lived experiences. Fifteen participants completed post-participation interviews. Four distinct themes emerged from participants in both the in-person and eHealth groups: creation of a safe space, fostering peer support and connection, integration of mindfulness skills into daily life and improved well-being through the application of mindfulness. Results from this study suggest that eHealth may be an acceptable and feasible mode of delivery for MBIs in adolescents with chronic illnesses. EHealth should be considered in future studies as a promising avenue to increase access to MBIs in this population.

The Tumor Microenviroment (TME) is a complex milieu that is increasingly recognized as a key factor in multiple stages of disease progression and responses to therapy as well as escape from immune surveillance. However, the precise contribution of specific immune effector and immune suppressor components of the TME in Burkitt lymphoma (BL) remains poorly understood. In this paper, we applied the computational algorithm CIBERSORT to Gene Expression Profile (GEP) datasets of 40 BL samples to draw a map of immune and stromal components of TME. Furthermore, by VECTRA multispectral immunofluorescence (IF) and multiple immunohistochemistry (IHC), we investigated the TME of an additional series of 40 BL cases and evaluated the possible role of the PD-1/PD-L1 immune checkpoint axis. Our results indicated that M2 polarized macrophages are the most prominent TME component in BL. In addition, we investigated the correlation between PD-L1 and latent membrane protein-2A (LMP2A) expression on tumour cells, highlighting a subgroup of BL cases characterized by a non- canonical latency program of EBV with an activated PD-L1 pathway. In conclusion, our study analysed the TME in BL and identified a tolerogenic immune signature highlighting new potential therapeutic targets.

Exposure to adverse childhood experiences (ACE) has been found to have a profound negative impact on multiple child outcomes, including academic achievement, social cognition patterns, and behavioral adjustment. However, these links have yet to be examined in preschool children that are already experiencing behavior or social-emotional problems. Thus, the present study examined the links between the caregiver's and the child's exposure to ACE and multiple child and caregiver's outcomes in a sample of 30 preschool children enrolled in a Therapeutic Nursery Program (TNP). Children are typically referred to this TNP due to significant delays in their social emotional development that often result in difficulty functioning in typical childcare, home, and community settings. Analyses revealed some contradictory patterns that may be specific to this clinical sample. Children with higher exposure to ACE showed more biased social information processing patterns and their caregivers reported lower child social skills than caregivers of children with less exposure, however their inhibitory control levels were higher (better control) and staff reported that these children exhibited better social skills as well as better approaches to learning than children with less exposure. No such contradictions were found in relation to the caregiver's exposure to ACE, as it was positively associated with a number of negative child and caregiver outcomes.

Copper-containing materials are attracting attention as self-desinfecting surfaces, suitable for helping healthcare settings in reducing healthcare associated infections. However, the impact of repeated exposure to disinfectants frequently used in biocleaning protocols on their antibacterial activity remains insufficiently characterized. This study aimed at evaluating the antibacterial effi-ciency of copper (positive control), a brass alloy (AB+®) and stainless steel (negative control) after repeated exposure to a quaternary ammonium compound and/or a mix of peracetic acid/hydrogen peroxide routinely used in healthcare settings. A panel of 6 antibiotic-resistant strains (clinical isolates) was selected for this assessment. After a short (5 min) exposure time, the copper and brass materials retained significantly better antibacterial efficiencies than stainless steel, whatever the bacterial strain or disinfectant treatment considered. Moreover, post-treatment with both disinfectant products, copper-containing materials still reached similar levels of antibacterial efficiency as those obtained before treatment. Antibiotic resistance mechanisms such as efflux pump overexpression did not impair the antibacterial efficiency of copper-containing materials, neither did the presence of one or several genes related to copper homeostasis/resistance. In light of those results, surfaces made out of copper and brass remain interesting tools in the fight against dissemination of antibiotic-resistant strains that might cause healthcare associated infections.

With recent focus on deep neural network architectures for development of algorithms for computer-aided diagnosis (CAD), we provide a review of studies within the last 3 years (2015-2017) reported in selected top journals and conferences. 29 studies that met our inclusion criteria were reviewed to identify trends in this field and to inform future development. Studies have focused mostly on cancer-related diseases within internal medicine while diseases within gender-/age-focused fields like gynaecology/pediatrics have not received much focus. All reviewed studies employed image datasets, mostly sourced from publicly available databases (55.2%) and few based on data from human subjects (31%) and non-medical datasets (13.8%), while CNN architecture was employed in most (70%) of the studies. Confirmation of the effect of data manipulation on quality of output and adoption of multi-class rather than binary classification also require more focus. Future studies should leverage collaborations with medical experts to aid future with actual clinical testing with reporting based on some generally applicable index to enable comparison. Our next steps on plans for CAD development for osteoarthritis (OA), with plans to consider multi-class classification and comparison across deep learning approaches and unsupervised architectures were also highlighted.

Suicide dynamics form a complex system deeply influenced by interrelated factors, necessitating advanced methodologies for comprehensive analysis. This study pioneers the application of Particle Markov Chain Monte Carlo (PMCMC) methods in suicide research, recognized for their enhanced sampling efficiency over traditional techniques in complex, high-dimensional models. PMCMC is particularly adept at handling non-Gaussian distributions and navigating parameter spaces efficiently, preventing the entrapment in local optima. Utilizing PMCMC, our research simulated a broad spectrum of potential outcomes, clarifying the probable scenarios and their likelihoods, thus enriching the predictive accuracy and understanding of suicide dynamics. These methods facilitated the exploration of dynamic interactions among key risk factors such as mental health issues, trauma, substance use, social isolation, and access to harmful means, whose complex interplays challenge predictive modeling. The study extends previous applications of PMCMC in complex systems like H1N1, opioid crises, and COVID-19 to the domain of suicide, suggesting its potential in enhancing decision-making and intervention strategies. However, limitations due to the model's simplified assumptions and the specificity of the data to certain populations underscore the necessity for broader application to validate findings across varied demographics. In summary, while PMCMC offers robust capabilities for the dynamic modeling of suicide, it requires careful parameter selection and consideration of computational demands. Future research should continue to leverage this approach in more complex settings, enhancing our ability to predict and mitigate suicide risks effectively.

California has experienced a surge in wildfires, prompting research into contributing factors, including weather and climate conditions. This study investigates the complex, multiscale interactions between large-scale climate patterns, such as the Boreal Summer Intraseasonal Oscillation (BSISO), El Niño Southern Oscillation (ENSO), and the Pacific Decadal Oscillation (PDO), and their influence on moisture and temperature fluctuations, and wildfire dynamics in California. The combined impacts of PDO and BSISO on intraseasonal fire weather changes, the interplay between Fire Weather Index (FWI), relative humidity, vapor pressure deficit (VPD), and temperature in assessing wildfire risks, and geographical variations in the relationship between FWI and climatic factors within California are examined. The study employs a multi-pronged approach, analyzing wildfire frequency and burned areas alongside climate patterns and atmospheric conditions. Findings reveal significant variability in wildfire activity across different climate conditions, with heightened risks during specific BSISO phases, La-Niña, and cool PDO. The influence of BSISO varies depending on its interaction with PDO. Temperature, relative humidity, and VPD show strong predictive significance for wildfire risks, with significant relationships between FWI and temperature in elevated regions (correlation, r &gt; 0.7, p ≤ 0.05) and FWI and relative humidity along the Sierra Nevada Mountains (r ≤ -0.7, p ≤ 0.05).

Catalytic studies for hydrogen production via steam reforming of ethanol (SRE) are essential for process optimization. Likewise, selecting the ideal support for the active phase can be critical to achieve high conversion rates during the catalytic steam reforming. In this work, copper-based catalysts were synthesized using two different supports, NaY zeolite and Nb2O5/Al2O3 mixed oxides. The materials were prepared using wet impregnation and characterized for their physicochemical properties using different analytical techniques. Differences in catalyst morphologies were readily attributed to the characteristics of the support. The Cu/NaY catalyst showed better textural properties than Cu/Nb2O5/Al2O3, resulting in a homogeneous metal dispersion over the support surface. Both catalytic systems were active in SRE, but Cu/NaY resulted in higher ethanol conversions compared to Cu/Nb2O5/Al2O3. Hence, the performance of copper-based catalysts was influenced significantly by the textural properties of the support.

The influence of climate conditions and stable design on horses housed in single stalls can have significant effects, especially in regions with tropical savannah climates. A recent study observed variations in autonomic responses in horses housed in different stable designs during the summer, but there is limited information about their conditions during the monsoon. This study investigated the stable microenvironment and autonomic regulation of horses housed in different stable archi-tectures during the monsoon in a tropical savannah environment. Twenty-two horses were allo-cated to one of three stable architectures, each with varying stable microenvironments. The findings reveal that the heart rate variability (HRV) was lower in horses in a stable with a solid external wall and lower volume-to-horse ratio compared to those in a stable with a solid external wall but a higher volume-to-horse ratio or one without a solid external wall. Additionally, the study found that stable microenvironments and HRV modulation were correlated with stable architecture. Autonomic responses differed among horses in different stable architectures, indicating that stable microen-vironments and, to some extent, volume-to-horse ratio play a role in horses’ autonomic regulation. The findings have implications for improvements in housing and welfare in tropical savannah environments.

Aim: The aim of the study is to analyze quantitatively the scientific literature covering nursing studies on patient safety. Method: The Web of Science database is queried in this retrospective bibliometric analysis to identify relevant publications. The study themes, contributing journals, countries, institutions, and authors were evaluated quantitatively. Thus, a total of 5470 publications concerning patient safety in nursing were included and analyzed. Findings: The number of studies conducted increased every year from 1992 to 2023. While the country whose articles receive the most citations (31072) is the United States of America (USA), Turkey is ranked as last with the lowest number of citations (581). Journal of Clinical Nursing, with 338 articles, appeared to have the highest number of publications, Chaboyer W. appeared to have the highest number of citations with a total of 1426 and 45 publications. The countries that have the strongest international cooperation for research in this field are the USA, England, Australia and China. Results: After examining the literature in the field of patient safety in nursing through bibliometric analysis, it is seen that themes such as patient safety, medication errors, nursing care, nursing, education, systematic review, quality care and leadership were emphasized as important considerations.

Abstract Introduction: In the last thirty years, brain neuromodulation techniques have been used as an alternative to pharmacological treatment of neurological disorders. Parkinson's disease (PD) is a neurodegenerative disorder leading to bradykinesia, rest tremor, postural changes, and non-motor symptoms such as depression, anxiety, sleep disorders, pain, and cognitive decline that compromises executive functions (EFs), responsible for the orderly execution of behaviors and tasks of daily life and intentional and directed actions. To this date, a few studies with transcranial direct current stimulation (tDCS) have shown beneficial effects in PD patients concerning specific motor and non-motor symptoms, targeting the motor cortex and/or prefrontal regions. Objective: The main objective of this study was to evaluate the effects of left prefrontal tDCS across a broad spectrum of motor and non-motor symptoms of PD using established validated scales. Method: Single-blind randomized clinical trial with 18 volunteers with PD, aged between 45 and 80 years (66.1 ± 9.65), who met inclusion and exclusion criteria. Participants were submitted to assessments of motor and non-motor functions employing psychometric scales and tests to evaluate EFs and were randomly divided into two groups: control (sham stimulation) and experimental (active stimulation). All participants were involved in three separate tDCS sessions. The anode was positioned over the left dorsolateral prefrontal cortex and the cathode over the right supraorbital region, with a direct current intensity of 2mA, lasting 20 minutes. At the end of the three sessions, all participants were reassessed. Results: Significant effects of tDCS on non-motor functions were observed for cognition (verbal fluency of actions, clock copy test, appointment by visual confrontation, and verbal memory with immediate free recall) and subjective assessment of sleep quality (overall restlessness and discomfort in the arms and legs at night, leg and arm cramps at night and distressing dreams). There was also an improvement in the rate of errors and successes for congruent and incongruent stimuli of the Stroop Test. The beneficial effects on motor function were decreased rigidity, improved gait, and greater agility in the finger-tapping test. Conclusion: Three tDCS sessions showed positive results for participants with PD, producing significant improvements in various motor and non-motor functions, including sleep quality, cognition, and EFs. Additionally, the present results indicate that tDCS neuromodulation of the left dorsolateral prefrontal cortex region is feasible, safe, and provides significant objective benefits for PD patients.

Alkaloid-based urea derivatives were produced with high yield through the reaction of anabasine and cytisine with isoxazolylphenylcarbamates in boiling benzene. Their antitumor ac-tivity in combination with the commonly used six anticancer drugs namely cyclophosphane, fluorouracil, etoposide, cysplatine, ribomustine with different mechanisms of action was investi-gated. Based on the quantum chemical calculations data and molecular docking, hypotheses have been put forward to explain their mutual influence when affecting on the С6 rat glioma model cells.

The goal of newborn screening is to improve health outcomes by identifying and treating affected newborns. This manuscript provides an overview of a data tool to facilitate the longitudinal collection of health information on newborns diagnosed with a condition through NBS. The Newborn Screening Translational Research Network (NBSTRN) developed the Longitudinal Pediatric Data Resource (LPDR) to capture, store, analyze, visualize, and share genomic and phenotypic data over the lifespan of NBS identified newborns to facilitate understanding of genetic disease, and to assess the impact of early identification and treatment. NBSTRN developed a consensus-based process using clinical care experts to create, maintain, and evolve question and answer sets organized into common data elements (CDEs). The LPDR contains 24,172 core and disease-specific CDEs for 118 rare genetic diseases, and the CDEs are being made available through the NIH CDE Repository. The number of CDEs for each condition average of 2,200 with a range from 69 to 7,944. The LPDR is used by state NBS programs, clinical researchers, and community-based organizations. Case level, de-identified data sets are available for secondary research and data mining. The development of the LPDR for longitudinal data gathering, sharing, and analysis supports research and facilitates the translation of new discoveries into clinical practice.

This article explores the application of machine learning techniques, specifically focusing on ensemble methods like Random Forests, for detecting fraudulent activities in digital financial transactions. Highlighting the evolution from traditional statistical approaches to modern machine learning models, it underscores the effectiveness of Random Forests in handling the inherent challenges of imbalanced datasets typical in fraud detection scenarios. Using a Kaggle dataset of credit card transactions, the study optimizes Random Forest parameters through rigorous parameter tuning, achieving significant improvements in model performance metrics such as Area Under the Curve (AUC). The findings underscore the critical role of machine learning in enhancing fraud detection capabilities, emphasizing the ongoing evolution and future potential of these methodologies in financial risk management.

Energy generation now heavily relies on the field of photocatalysis. Many conventional research topics have been superseded by the conversion of solar energy into chemical or thermal energy for a variety of energy-related applications. The urgent necessity of moving away from non-renewable energy sources is a result of the problem of global warming. In an effort to create the best photocatalysts for effective solar conversion, scientists are investigating a variety of material systems and material combinations. By examining the influence of morphology changes on the photoelectrochemical activity of zinc oxide nanostructures, here electrodeposition was used to create the nanostructures. By using the proper capping agents, it is possible to control the growth rates of different ZnO facets and get well-defined nanostructures and orientation. In order to generate distinct ZnO morphologies, we report here the electrodeposition of ZnO nanostructured thin films in the presence of different capping agents. A zinc nitrate (Zn (NO₃)₂) bath was used to electrodeposit ZnO nanostructures on indium tin oxide glass (ITO) substrate at 70 °C with an applied potential of -1.0 V. Capping agents such as ethylenediamine (EDA) or ammonium fluoride (NH₄F) were added to this zinc nitrate bath. The photoelectrochemical capabilities of the morphology-controlled zinc oxide nanostructures were extensively evaluated and characterised. Thus various ZnO morphologies had an impact on the PEC properties.

In order to improve contrast and restore color for underwater image captured by camera sensors without suffering from insufficient details and color cast, a fusion algorithm for image enhancement in different color spaces based on contrast limited adaptive histogram equalization (CLAHE) is proposed in this article. The original color image is first converted from RGB color space to two different special color spaces: YIQ and HSI. The color space conversion from RGB to YIQ is a linear transformation, while the RGB to HSI conversion is nonlinear. Then, the algorithm separately operates CLAHE in YIQ and HSI color spaces to obtain two different enhancement images. The luminance component (Y) in the YIQ color space and the intensity component (I) in the HSI color space are enhanced with CLAHE algorithm. The CLAHE has two key parameters: Block Size and Clip Limit, which mainly control the quality of CLAHE enhancement image. After that, the YIQ and HSI enhancement images are respectively converted backward to RGB color. When the three components of red, green, and blue are not coherent in the YIQ-RGB or HSI-RGB images, the three components will have to be harmonized with the CLAHE algorithm in RGB space. Finally, with 4 direction Sobel edge detector in the bounded general logarithm ratio operation, a self-adaptive weight selection nonlinear image enhancement is carried out to fuse YIQ-RGB and HSI-RGB images together to achieve the final fused image. The enhancement fusion algorithm has two key factors: average of Sobel edge detector and fusion coefficient, and these two factors determine the effects of enhancement fusion algorithm. A series of evaluate metrics such as mean, contrast, entropy, colorfulness metric (CM), mean square error (MSE) and peak signal to noise ratio (PSNR) are used to assess the proposed enhancement algorithm. The experiments results showed that the proposed algorithm provides more detail enhancement and higher values of colorfulness restoration as compared to other existing image enhancement algorithms. The proposed algorithm can suppress effectively noise interference, improve the image quality for underwater image availably.

Our investigations show that electrochemical corrosion of copper is faster than electrochemical corrosion of aluminium at temperatures below 100oC. Literature data analysis shows that the Al atoms diffuse faster than the Cu atoms at temperatures higher than 475oC, Al rich intermetallic compounds (IMCs) are formed faster in the Cu-Al system, and the Kirkendall plane shifts toward Al side. Electrochemical corrosion occurs due to electric current and due to diffusion. An electronic devise working time, for example, depends on initial copper cover thickness on aluminium wire, connected to the electronic devise, temperature, and volume and dislocation pipe diffusion coefficients, so copper, iron, and aluminium electrochemical corrosion rates are investigated experimentally at room temperature and at temperature 100oC. Intrinsic diffusivities ratios of copper and aluminium at different temperatures and diffusion activation energies in the Cu-Al system are calculated by proposed here methods using literature experimental data. Dislocation pipe and volume diffusion activation energies of pure iron are calculated separately by earlier proposed method using literature experimental data. Aluminium dissolved into NaCl solution as the Al3+ ions at room temperature and at temperature 100oC, iron dissolved into NaCl solution as the Fe2+ (not Fe3+) ions at room temperature and at temperature 100oC, copper dissolved into NaCl solution as the Cu+ ions at room temperature and as the Cu+ and the Cu2+ ions at temperature 100oC. It is founded experimentally that copper corrosion is higher than aluminium corrosion, and ratio of electrochemical corrosion rates, kCu/kAl>1, decreases with temperature increasing, although iron electrochemical corrosion rate doesn’t depend on temperature below 100oC. It is obvious, because melting point of iron is more higher then melting point of copper or aluminium. It is calculated that copper electrochemical corrosion rate is approximately equal to aluminium electrochemical corrosion at temperature about 300oC, so copper can dissolve into NaCl solution mostly as the Cu2+ ions at temperature about 300oC. Ratio of intrinsic diffusivities, DCu/DAl <1, increases with temperature increasing, and intrinsic diffusivity of aluminium could be approximately equal to intrinsic diffusivity of copper at temperature about 460oC.

Byers Peninsula (62°34’-62°40’S-60°54’61°13’W), 60 km2 in size, is considered one of the largest ice-free areas in Antarctica. Since 2006, the Spanish Polar Program has taken part in a large number of environmental studies involving effects of climate changes, limnology and microbiology, live cycles, but not albedo. Surface albedo is one of the key physical parameters in the surface energy budget of polar regions. Most of Antarctica is covered by ice sheets; only about 0.44% of the area is permanently ice-free. However, in maritime Antarctica, the ice-free areas, corresponding to small islands, peninsulas, and coastal beaches, account for about 3% of the territory. To incorporate the contribution of these areas into global albedo models, it is necessary to relate the soil properties of the ice-free areas to the surface albedo response. Also, mapping soil properties and albedo have and special interest in these ice-free areas. Image classification using machine learning methods trained with georeferenced soil data could be useful for mapping soil properties and albedo in multispectral optical satellite images. A shallow neural network implemented using the Keras Python module was used to define and train models of soil properties using 15 explanatory variables corresponding to bands and spectral indices of a Sentinel image and a population of 49 soil samples taken from the top 5 centimeters of the soil profile. The soil samples were analyzed in the laboratory and a spectral library in the Vis-Nir range (350-2500 nm) was created. The albedo of the samples was integrated from the ADS spectra. At the same time, a linear regression model of albedo using the soil properties as explanatory variables was performed. The R2 fit of this new model was about 0.82 and the error of estimation was 4.1. The model was extended to the entire Byers Peninsula using the ML soil property models as explanatory variables. The RMSE of the extended models increased up to 8.2. We think that the main cause of this increase (2.6 points) is related to the error propagation, phenomenon due to the use of models as explanatory variables. However, another important part of the error increase could be due, among other reasons, to the use of an image that, although corrected, is not completely free of clouds.

Reducing visceral fat is an important issue for obesity prevention. We previously reported a novel dietary intervention program using “Optimized Nutri-Dense Meals” based on the nutrients described in Dietary Reference Intakes in Japan. This open-label randomized controlled trial evaluated the visceral fat reducing effect of the program. In total, 100 Japanese obese/overweight male patients were recruited and divided into a control group that continued their usual diets and a test group that consumed test meals twice per weekday for four weeks. Visceral fat area, set as the primary outcome, was significantly decreased in the test group compared with the control group. Regarding other outcomes, the occupancy levels of some gut floras and presenteeism scores were significantly increased in the test group compared with the control group. These results indicate that dietary intervention based on the Dietary Reference Intakes can prevent visceral fat accumulation and contribute to the improvement of health, without the need for completely replacing the everyday diet.

In the context of the Korean building structure standard KDS2022, wind loads can be readily calculated in terms of the along-wind, across-wind, and torsional components, based on a single wind direction. However, this approach falls short in accurately and safely evaluating the impact of winds from various directions. Therefore, in this study, we developed a Wind Load Calculation Program (WCP) capable of predicting wind loads with relative precision during the preliminary design phase. First, wind tunnel tests were conducted to identify the essential factors necessary for calculating wind loads and the variables influencing these factors. The building shape considered was a square, and the wind force coefficients and power spectral density were measured by combining 4 ground roughness values, 11 side ratios (), 4 aspect ratios (), and wind directions ranging from 0° to 90°. Subsequently, a generalized formulation was devised to facilitate wind load calculations across diverse conditions and a method for calculating load combination coefficients, considering response correlation and load simultaneity, was presented. Finally, the wind loads obtained from the wind tunnel tests were compared with those predicted by the WCP using an actual project model.

Background: Identity diffusion plays a central role in the onset of borderline personality and disorders. The Dialectical Behavioral Therapy for Adolescents (DBT-A) is a treatment program for adolescents with emotional instability and dysregulation. The interest of this study is to examine the influence of a standardized and certified DBT-A therapy program on identity development of adolescents with emotion dysregulation in an inpatient setting. Methods: 138 adolescents aged 13 to 18 years with symptoms of emotional instability were assessed before and after a curricular 12-weeks in-patient DBT-A program with standardized instruments for the assessment of identity (AIDA), emotion regulation (FEEL-KJ, SEE) and general psychopathology (SCL-90-R, DIKJ). Results: The results indicate a significant change in identity development, emotion regulation and general symptoms of psychopathology after treatment with DBT-A. A connection between identity scales and psychopathological symptoms of adolescents with diagnosed borderline disorders and impaired emotion regulation could be established. Conclusion: In this large sample of adolescents, DBT-A significantly improved identity and reduced identity diffusion. As identiy disturbance is a core symptom of borderline personality disorder, our results may become clinically relevant for the prevention of personality disorders in emotionally unstable adolescents

Fish tissue samples from 203 adult individuals were collected in the main ports and markets of the Pacific coast of Panama. Molecular identification based on cytochrome oxidase I gene segment of all species was verified GENBANK reference sequences. 34 species from 14 families (Ariidae, Lutjanidae, Caranjidae, Scianidae, Centropomidae, Serranidae, Scombridae, Sphyraenidae, Haemulidae, Gerreidae, Stromotidae, Lobotidae, Malacanthidae, Mugilidae) were identified at species molecular level from 164 sequences. Also, three Caribbean species were molecularly identified among the analyzed samples (Mycteroperca xenarcha, Paralonchurus brasilensis and Lobotes surinamensis). Species diversity was slightly higher in the Gulf of Panama than in the Gulf of Chiriquí. For species with 5 or more individual sequences, genetic diversity and genetic connectivity parameters such as: total number of haplotypes (H), haplotype diversity (Hd), and nucleotide diversity (π) were calculated. Overall, pelagic-migratory species showed higher values of genetic diversity than coastal and estuarine species with some exceptions. Connectivity between Gulf areas was compared using values of genetic distances and genetic differentiation (Fst). High level of connectivity observed between Gulf of Chiriqui and Gulf of Montijo indicates the existence of a single stock in that area for the following species: Scomberomorus sierra, Caranx caninus and Lutjanus guttatus. Demographic history of the most common species was examined using Tajima’s D values suggesting population expansion for two snapper species, L. peru and L. argentiventris, having significant and higher values. Another important contribution from this research was the production of primers and dual labeled probes for environmental DNA detection using qPCR for the five most abundant species (spotted rose snapper, yellow snapper, green jack, Pacific crevalle jack and the Pacific sierra fish). These markers represent a new set of tools for environmental DNA (eDNA) detection and molecular traceability of three commercially important fish species along the supply chain including landing sites and markets of the main fishery areas.

In various countries of the global south, school feeding programs are implemented in order to alleviate short-time hunger in children, improved their nutrition and provide employment for food vendors. The impact of these programs is important not only in terms of pupils’ nutrition but also in improving farmers’ livelihoods. This study analyzes the impact of the school feeding program on smallholders' food security based on data collected in 2021 from 240 farmers surveyed in northeast Nigeria. Differently from other studies, several econometric methods are used to analyze the data, namely, binary probit regression, propensity score matching, inverse probability weighted adjusted regression and endogenous switching regression. The results show that about 40% of the beneficial smallholder farmers are food secure compared to 20% of the non-beneficiary households. Findings revealed that the Homegrown school feeding program (HGSF) positively improved smallholder farmers improve household food security status. Results provide evidence for the need to expand school feeding programs vis-a-vis interventions in facilitating farmers’ access to capital and capacity building for better integration in the supply chain.

The affected upper limb in children with Unilateral Spastic Cerebral Palsy (US CP) has motor and somatosensory impairments, that contribute negatively to children’s bimanual performance and quality of life. Mirror Therapy (MT) is being studied to become an approachable intensive and home-based therapy, suitable for children with US CP. The aim of this study is to examine the feasibility of a 5-week home-based program of MT for children with US CP. Six children aged 8-12 years old performed the therapy, five days per week, 30 minutes per day. A minimum of an 80% of compliance was required. The evaluations included the feasibility of the therapy (compliance, total dosage, perceived difficulty of the exercises, and losses of follow-ups and evaluations), the bimanual performance, the somatosensory function and the quality of life at baseline, at the end of the intervention, and at 1-month follow-up. All children completed the therapy and were included in the analysis. The total accomplishment was 86.47 ± 7.67. The perceived difficulty of the exercises ranged from 2,37 to 4,51. As a conclusion, a home-based program of Mirror Therapy is suitable and feasible for children with US CP.

Cempo Ireng (Oryza sativa L. var. Cempo Ireng) is one of the black rice variety in Indonesia that consumed as functional food, not as a staple food because of the black rice contains anthocyanin pigment which has beneficial to human health. High concentration of anthocyanin reaching 393.93 ppm cause black color in the pericarp layer of Cempo Ireng which make this variety as an antioxidant source, low glycemic index, and free of gluten, leading to have higher price in the rice market. However, most of the farmers are not cultivate Cempo Ireng due to the longer vegetative phase up to 150 days compared to the white rice varieties which only takes 90 days, the taller phenotype of Cempo Ireng cause problems in cultivation, and also the purple color of Cempo Ireng attract birds and earhead bug (Leptocorisa oratorius) to feed on black rice caryopsis that cause severe yield loss. Transgenic methods, mutation technique, intensification systems, and physical treatment have been applied in Cempo Ireng to overcome those lack characteristics. In the future, Cempo Ireng also has a big potential to become a parent in cross breeding program because of the positive characters. The aim of this review is to describe the potential of Cempo Ireng in rice breeding program for improving food sustainability.

Background: Physical activity has been considered as a promising approach to slow down the disease process in Multiple Sclerosis (MS) patients. While the functional impairments of MS have been studied in detail, but there is limited evidence of the efficacy of exercise interventions on the Multiple Sclerosis functional composite (MSFC) score in these patients. The study aim was to in-vestigate the improvement in MSFC score by multi-function swing suspension training (MFSST) in the women with MS. Methods: The patients were divided into the intervention and control groups. A total of 47 MS patients completed the MSFC components at baseline and after the intervention. Z scores were created for each test based on control means. Results: The MSFC components showed a significant increment in comparison with the baseline levels in the four, six, and eight weeks following the first exercise session (all p<0.05). These dif-ferences in the control group were not significant. The improvement in the MSFC score and the component Z-scores in the intervention groups was found from the fourth week onwards. Conclusions: The study findings highlight that MFSST can be used as an effective treatment method in MS patients due to its positive effects on physical parameters, such as muscles strength, functional impairments, and cognitive problems.

Zika virus (ZIKV) is an emerging mosquito-borne flavivirus considered as a threat to human health due to large epidemics and serious clinical outcomes such as microcephaly in newborns. Like all flaviviruses, ZIKV relies on the cellular machinery to complete its viral cycle, with the endoplasmic reticulum (ER) being the critical site of viral replication factories. The sudden high protein load in the ER induces an ER stress to which the cell responds with an appropriate unfolded protein response (UPR) in an attempt to restore its disturbed homeostasis. When the restoration fails, the cell signaling leads to a programmed cell death by apoptosis with the upregulation of the UPR-induced C/EBP homologous protein (CHOP) which acts as the main trigger for this fatal outcome. Our previous studies have shown the ability of ZIKV to manipulate various cellular responses in order to optimize virus production. ZIKV is able to delay apoptosis to its benefit and although ER stress is induced, the UPR is not complete. Here we discovered that ZIKV impairs the expression of CHOP/DDIT3, the main factor responsible of ER-stress driven apoptosis. Surprisingly, the mechanism does not take place at the transcriptional level but at the translational level.

(1) Background: Chronic musculoskeletal pain (CMP) in adolescents can negatively affect physical, psychological and social functioning, resulting in functional disability. This study aims to evaluate the effectiveness of an outpatient rehabilitation program based on graded exposure in vivo (EP) compared with care as usual (CAU) in a RCT. The aim of the interventions (EP and CAU) is to improve functional ability in adolescents with CMP, CAU is interdisciplinary outpatient rehabilitation care, based on graded activity. (2) Methods: A pragmatic multicenter randomized clinical trial with a 12-month follow-up was used. Adolescents (12-21 years) with musculoskeletal pain were invited to participate. Primary outcome was functional disability (Functional Disability Inventory). Most important secondary measures: perceived harmfulness, pain catastrophizing and intensity. Data analysis was performed by intention-to-treat linear mixed model analysis. (3) Results: Sixty adolescents were randomized to EP or CAU and data of 53 adolescents (93% female) could be analyzed (25 EP, 28 CAU). Mean age was 16.0 years (SD=1.87). Adolescents in EP showed a clinically relevant and statistically significant decrease in functional disability (estimated mean difference at least -8.81,p-values≤0.01) compared with CAU at all time points. Significant differences in favor of EP were found for perceived harmfulness at all time points (p-values≤0.002), for pain catastrophizing (PCS) at 2 months follow-up (p-value=0.039) and for pain intensity at 4 and 10 months follow-up (p-values≤0.028). (4) Conclusion: The effectiveness of the trial is in favor of the EP and leads to a significant and clinically relevant decrease in functional disability compared to usual care.

The National Breast and Cervical Cancer Early Detection Program (NBCCEDP) of Minnesota, “Sage”, provides breast cancer screening to uninsured women. We introduce a novel mapping technique, spatially adaptive filters (SAFs), to estimate utilization of Sage screening in Minnesota. Sage screenings (N = 74,712) were geocoded. The eligible population was modeled with the RTI synthetic population dataset. Between 2011 and 2015, 36,979 women a year were Sage eligible. Utilization was highly variable across Minnesota (M = 37.2%, range 0% - 131%, SD = 18.7%). This replicable approach modeled utilization rates to the neighborhood-level, allowing Sage to prioritize locations and engage communities.

As most of the videos are destined for human perception, many techniques have been designed to improve video coding based on how the human visual system perceives video quality. In this paper, we propose the use of two perceptual coding techniques, namely contrast masking and texture masking, jointly operating under the High Efficiency Video Coding (HEVC) standard. These techniques aim to improve the subjective quality of the reconstructed video at the same bit rate. For contrast masking, we propose the use of a specific weighting matrix for each block size (from 4×4 up to 32×32). We achieve average Bjøntegaard Delta-Rate (BD-rate) gains of between 2.5% and 4.48%, depending on the perceptual metric and coding mode used. The texture masking scheme is based on the classification of each coding unit, using its mean directional variance features as input to a support vector machine model. According to this classification, the block’s energy, the type of coding unit, and its size, an over-quantization is computed to provide a QP offset (DQP) for this coding unit. By applying both techniques in the HEVC Reference Software, an overall average of 5.79% BD-rate gain is achieved.

The goal of this study is to synthesize, determine the structure, and examine the antimicrobial properties of novel metal complexes of 2,4-dithiouracil and its derivatives. These complexes were obtained by mixing aqueous solutions of the corresponding metal salts with the ligand dissolved in DMSO and aqueous NaOH, using a metal-to-ligand ratio of 1:4:2. The structures of the new compounds were analyzed by melting point determination, microwave plasma atomic emission spectrometry (MP-AES) for Cu and Au, inductively coupled plasma optical emission spectrometry (ICP-OES) for S, ATR, solution and solid-state NMR and Raman spectroscopy. The interpretation of the complex spectra was aided by data for 2,4-dithiouracil obtained from 1H-1H COSY, DEPT-135, HMBC, and HMQC spectra. Additionally, the antimicrobial activity of these complex-es and the free ligands was evaluated against Gram-positive and Gram-negative bacteria, as well as yeasts.

Ultrasound, as mechanical waves with frequencies exceeding 20 thousand hertz, has found wide applications in medicine, physiotherapy, and more recently in agriculture. This study aimed to investigate the impact of ultrasound on potato yield and its parameters, particularly on seed potato yield, quantity, mass, and multiplication coefficient of potato tubers. The research was based on a three-year field experiment, utilizing the randomized block design in a split-split-plot arrangement, in the central-eastern region of Poland. The primary factor were technologies: a) technology with employing ultrasonic pre-planting treatment, b) traditional cultivation without this treatment. The secondary factors were potato varieties. Sonication of tubers was conducted using a bath-type ultrasonic device equipped with piezoe-lectric transducers. Results revealed a significant influence of cultivation technology, cultivar, and weather conditions on seed tubers yield, quantity, and multiplication coefficient of potato tubers. However, genetic traits of the examined varieties and random factors significantly affected the individual seed tuber mass and the number of shoots emerging from a single tuber. Future Outlook: Future research could focus on further optimizing ultrasound application techniques in potato cultivation, considering diverse varieties and environmental conditions. Additionally, it would be worthwhile to analyze the long-term effects of ultrasound on tuber seed potato quality and their ability to adapt to changing climatic and soil conditions. Furthermore, studies investi-gating the impact of ultrasound on other plant species could broaden our understanding of po-tential benefits in agriculture.

This study focuses on the design, development, and evaluation of an educational mobile robot, named Robot-T2, to be used in educational activities within a technical school. The primary objective was to create a versatile platform that allows students to explore programming, engineering, and science concepts in a practical and collaborative manner. The methodology included an iterative design and testing approach, incorporating feedback from students and teachers to continuously improve the robot's functionality. The tests covered autonomous navigation, line following, and object manipulation, using the OnBotJava programming software and the Control Hub as the main interface. The results demonstrated that Robot-T2 is highly efficient and adaptable in various educational contexts, showing remarkable precision in navigation and object manipulation. The design iterations significantly improved the robot's performance, enriching the educational experience and promoting active learning. In conclusion, educational robotics, represented by Robot-T2, has great potential to enhance the teaching and learning process in technical schools, fostering teamwork, problem-solving, and the integration of technology in the classroom. This project is expected to inspire future developments in educational robotics.

Smart electronic devices and telemedicine are widely used in humans' daily lives. This provides remote treatment of patients using information and communications technology. New telemedicine technologies, such as the Internet of Medical Things (IoMT), make it easier for medical and computing devices to communicate regularly and effectively. Critical motivations for adapting the IoMT are reduced cost, increased quality of life, and timely medical intervention. IoMT is significant because it enables continuous, real-time patient monitoring during routine everyday activities using a variety of wearables and sensors. With big data, the IoMT technology makes excellent use of Artificial Intelligence (AI) to support disease detection and health condition prediction, alerting patients and healthcare providers. Many research studies have been conducted to explore various aspects of IoMT and its applications in the real world. However, it is challenging to comprehend all the techniques and solutions proposed by the research community. Therefore, this survey sheds light on some crucial aspects of IoMT technologies and explores the potential research gaps and directions the research community could tackle. The survey examines and discusses the characteristics of IoMT standards, protocols, and types. It then delves into the layers of IoMT and distinguishes them into Fog and edge. The studies published under each type were explored, and the limitations of these works were highlighted. The research gaps and directions on IoMT approaches and technologies were also highlighted. With such findings and research directions, further research endeavors could be carried out to address the issues and existing limitations in the IoMT.

In the digital age, Artificial Intelligence (AI) is emerging as a transformative force in various sectors, in-cluding medicine. This article explores the potential of AI, akin to the magical genie of Aladdin's lamp, particularly within thoracic surgery and lung cancer management. It examines AI applications like ma-chine learning and deep learning in achieving more precise diagnoses, preoperative risk assessment, and improved surgical outcomes. The challenges and advancements in AI integration, especially in computer vision and multi-modal models, are discussed alongside their impact on robotic surgery and operating room management. Despite its transformative potential, implementing AI in medicine faces challenges regarding data scarcity, interpretability issues, and ethical concerns. Collaboration between AI and medi-cal communities is essential to address these challenges and unlock the full potential of AI in revolution-izing clinical practice. This article underscores the importance of further research and interdisciplinary collaboration to ensure the safe and effective deployment of AI in real-world clinical settings.

Historic expeditions are events that are flavored by exploratory, scientific, military or geographic characteristics. Such events are often documented in literature, journey notes or personal diaries. A typical historic expedition involves multiple site visits and their descriptions contain spatiotemporal and attributive contexts. Expeditions involve movements in space that can be represented by triplet features (location, time and description). However, such features are implicit and innate parts of textual documents. Extracting the geospatial information from these documents requires understanding the contextualized entities in the text. To this end, we developed a semi-automated framework that has multiple Information Retrieval and Natural Language Processing components to extract the spatiotemporal information from a two-volumes historic expedition gazetteer. Our framework has three basic components, namely, the Text Preprocessor, the Gazetteer Processing Machine and the JAPE (Java Annotation Pattern Engine) Transducer. We used the Brazilian Ornithological Gazetteer as an experimental dataset and extracted the spatial and temporal entities from entries that refer to three expeditioners’ site visits and mapped the trajectory of each expedition using the extracted information. Finally, one of the mapped trajectories was manually compared with a historical reference map of that expedition to assess the reliability of our framework. The reference map was manually prepared in previous research work by others.

KLHL genes and the related KBTBD genes encode components of the Cullin-E3 ubiquitin ligase complex and typically target tissue-specific proteins for degradation, thereby affecting differentiation, homeostasis, metabolism, cell signaling, and the oxidative stress response. Despite their importance in normal cell function and in disease (KLHL40, KLHL41, KBTBD13, KEAP1, and ENC1), previous studies that examined epigenetic factors affecting transcription were predominantly limited to promoter DNA methylation. Using diverse tissue and cell culture whole-genome profiles, we examined 17 KLHL or KBTBD genes preferentially expressed in skeletal muscle or brain to identify tissue-specific enhancer and promoter chromatin, open chromatin (DNaseI hypersensitivity), and DNA hypomethylation. Sixteen of the 17 genes displayed muscle- or brain-specific enhancer chromatin in their gene bodies, and most exhibited specific intergenic enhancer chromatin as well. Seven genes were embedded in a super-enhancer. The enhancer chromatin regions typically displayed foci of DNA hypomethylation at peaks of open chromatin. In addition, we found evidence that gene neighbors (HHATL and FBXO32) of KLHL40 and KLHL38 harbor enhancer chromatin that likely upregulates the adjacent KLHL gene. Many KLHL/KBTBD genes had tissue-specific promoter chromatin at their 5’ ends, but surprisingly, two (KBTBD11 and KLHL31) had constitutively unmethylated promoter chromatin in their 3’ exons that overlaps a retrotransposed KLHL gene. Our findings demonstrate the importance of expanding epigenetic analyses beyond the 5’ ends of genes in studies of normal and abnormal gene regulation.

The text examines the assessment of learning in science and the use of technologies like Scratch to enhance this process. Assessment is crucial for measuring progress and guiding teaching, especially in science where it fosters scientific skills and understanding. The study focuses on third-year secondary education students, evaluating the impact of Scratch on their learning compared to a gamification approach. Scratch, developed by MIT, is effective in interactive teaching and improves academic performance and student motivation. The research used an experimental design with a control group (gamification) and an experimental group (Scratch), measuring acquired knowledge through pretests and posttests. Results show that both groups significantly improved their knowledge, although the control group had a higher baseline initially. Students valued collaboration and playful learning. However, they faced technical challenges and highlighted the importance of teamwork. The study concludes that Scratch has great educational potential, suggesting improvements such as redesigning activities and increasing work sessions to maximize its effectiveness in learning and student motivation.

Problem:Palestinian demographic landscape is undergoing an increase in the elderly population like many regions across the world. The elderly Palestinians face a unique challenges and problems of limited access to traditional care due to restricted movement, checkpoints, and also for limited healthcare resources. Therefore, the need arose to develop a sensitive and adaptable smart health monitoring system for Palestinian elderly to provide accurate and timely health data to improve well-being and prevent complications. Method: The proposed system (SHMS) leverages the Internet of Things (IoT) with appropriate sensors to track vital signs like heart rate, blood oximeter, body temperature and signal from a patient heart. Advanced algorithms analyze the data, generating alerts for potential health risks, triggering timely interventions, and enabling remote consultations. Results: This system has the potential to contributes to SDG 3 to significantly improve the health and well-being of elderly Palestinians by providing an accurate, low-power, and low-cost system for remote health monitoring. The system, being wearable, reads vital signs in real-time, overcoming geographical barriers and facilitating remote monitoring, especially in areas with limited healthcare centers and suffered from barriers along the way. The Doctor can suggest the patient’s prescription needed based on the momentary condition of the elderly and on previous readings of the sensors, if necessary. Which will also be notified via messages. Moreover, the doctor can take immediate intervention in case of an emergency. By implementing the system, it will be unnecessary for more than 50\% of the elderly to visit health care, thus reducing the cost to 50\%.}

Background and objectives: Unrestricted kinematic alignment total knee arthroplasty (KA-TKA) with a soft tissue respecting technique (STRT) is a soft tissue-dependent tibial resection entailing restoration of the original soft tissue tension using ligamentotaxis after resurfacing the femur, based on the concept of restoring the native or pre-osteoarthritis alignment in each patient. However, there is no consensus on the indications of unrestricted KA-TKA with STRT. We modified the STRT, followed by investigation of the effects of surgery on the postoperative hip-knee-ankle angle (HKAA). Materials and Methods: We retrospectively analyzed the clinical background data, including the preoperative and postoperative HKAA, of 87 patients who underwent unrestricted KA-TKA with the modified STRT. Univariate and multivariate analyses were performed to determine the factors affecting the postoperative HKAA. A receiver operating characteristic (ROC) curve was plot-ted to investigate the change in the cut-off values of preoperative HKAA with respect to the safe zone of the postoperative HKAA. We generated two regression models, the linear regression model and generalized additive model (GAM) using machine learning, to predict the postopera-tive HKAA. Results: Univariate and multivariate analyses revealed the preoperative HKAA as the factor most relevant to the postoperative HKAA. ROC analysis revealed that the preoperative HKAA exhibited high predictive utility, with a cut-off value of -10°, when the safe range of postoperative HKAA was set at ± 5°. The GAM was the superior machine learning model, indicating a non-linear association between the preoperative and postoperative HKAA. Patients with preoperative HKAAs ranging from -18° to 4° were more likely to fall within the ± 5° safe range of the postoperative HKAA. Conclusions: The preoperative HKAA influences the postoperative HKAA in unrestricted KA-TKA with the modified STRT. Machine learning using the GAM may contribute to the selection of patients eligible for the surgical approach.

One of the important research directions in the field of photovoltaics is integration with construction. The integration of solar cell systems with a building can reduce installation costs and help optimize the used space. One of the interesting types of cells is dye-sensitized solar cells. In addition to their interesting properties, they also have aesthetic value. In the classic arrangement, they are constructed using glass with a transparent conductive layer (TCL). This article describes replacing a classic glass counter electrode with an electrode based on a ceramic tile and nickel foil. This solution makes it possible to expand their construction applications. The advantage of this solution is full integration with construction while simultaneously generating electricity. A dye-sensitized solar cell was built layer-by-layer on ceramic tile and nickel foil. An atomization method was used to deposit fluorine-doped tin oxide, and then a screen printing method was used to deposit a platinum layer. The electrical parameters of the manufactured DSSCs with and without a counter electrode tile were characterized by measuring their current-voltage characteristics under standard AM 1.5 radiation. A dye-sensitized solar cell integrated with ceramic tiles and nickel foil was produced and displayed an efficiency of over 4%.