This research explores the relationship between the independent variables (need for achievement, risk-taking, family support, economic factors, and the dependent variable of women’s enterprises’ success) and examines the moderating influence of socio-cultural factors. A survey-based methodology was adopted. One hundred sixty-nine small and medium-sized enterprises (SMEs) in the Palestinian West Bank were surveyed using structured questionnaires. Structural equation modeling (SEM) was conducted by using the Smart-PLS program. The results indicate that women entrepreneurs’ success in SMEs is positively and significantly impacted by the need for achievement as an internal factor and economic factors and family support as external factors. Furthermore, sociocultural factors did not show any significant moderating influence. By gaining knowledge about the relationship between internal and external factors and the success of women-owned SMEs, this study adds to the body of literature already in existence. These factors can be considered in the success of these enterprises, particularly in an environment full of political and economic fluctuations. Furthermore, the research is said to be the first of its type in Palestine, particularly concerning SMEs run by women. It also supports entrepreneurs by providing them with resources that might aid in the growth and success of their businesses.

This research underscores the importance of enhancing the early detection of diabetic retinopathy and glaucoma, two prominent culprits behind vision loss. Typically, retinal diseases lurk without symptoms until they inflict severe vision impairment, underscoring the critical need for early identification. The research is centered on the potential of leveraging fundus images, which offer invaluable insights by analyzing various attributes of retinal blood vessels, such as their length, width, tortuosity, and branching patterns. The conventional practice of manually segmenting retinal vessels by medical professionals is both intricate and time-consuming, demanding specialized expertise. This approach, reliant on pathologists, grapples with limitations related to scalability and accessibility. To surmount these challenges, the research introduces an automated solution employing computer vision. It conducts an evaluation of diverse retinal vessel segmentation and classification methods, including machine learning, filtering-based, and model-based techniques. Robust performance assessments, involving metrics like the true positive rate, true negative rate, and accuracy, facilitate a comprehensive comparison of these methodologies. The ultimate goal of this research is to create more efficient and accessible diagnostic tools, consequently enhancing the early detection of eye diseases through automated retinal vessel segmentation and classification. This endeavor combines the capabilities of computer vision and deep learning to pioneer new benchmarks in the realm of biomedical imaging, thereby addressing the pressing issues surrounding eye disease diagnosis.

We have studied the effect of the series resistance on the heating of the cathode, which is based on carbon nanotubes and serves to realize the field emission of electrons into the vacuum. The experiment was performed with the single multi-walled carbon nanotube (MCNT) that was separated from the array grown by CVD method with thin-film Ni-Ti catalyst (nickel 4 nm/Ti 10 nm). The heating of the cathode leads to the appearance of a current of the thermionic emission. The experimental voltage current characteristic exhibited the negative resistance region caused by thermal field emission. This current increases strongly with increasing voltage and contributes to the degradation of the cold emitter. The calculation of the temperature of the end of the cathode is made taking into account the effect of the phenomenon that warms up and cools the cathode. We have developed a method for processing of the emission volt-ampere characteristics of a cathode, which relies on a numerical calculation of the field emission current and the comparison of these calculations with experiments. The model of the volt-ampere characteristic takes into account the CNT’s geometry, properties, its contact with the catalyst, heating and simultaneous implementation of the thermionic and field emission. The calculation made it possible to determine a number of important parameters, including the voltage and current of the beginning of thermionic emission, the temperature distribution along the cathode and the resistance of the nanotube. The phenomenon of thermionic emission from CNTs was investigated experimentally and theoretically. The conditions of this type emission occurrence were defined. The results of the study could form the basis of theory of CNT emitter’s degradation.

Sport has become a fundamental socio-economic area. Currently, technological progress plays one of the most important roles in the development of sport. In the twenty-first century, innovation, and technology are significantly shaping the world of law enforcement and sports policing, and huge changes are taking place that need to be responded to. The development, spread and completion of info communication, information technology, digital technologies, and digitalization itself at an ever-faster pace than ever before are fundamentally changing all areas of the economy and society. Today there is no question that digitalization is the engine of the economy, which has an impact in all sectors, including sports and law enforcement. In the study, the authors examine the possibility of technical development in the field of sports safety. Among other things, drones, facial recognition systems and predictive analytics will be examined. The methodology used is mainly based on the analysis and examination of previous methods. The authors propose to adapt the innovative tools used at previous sports and mass events in the field of sports safety.

Colorectal cancer is the fourth leading cause of death worldwide and the fifth leading cause of cancer death in Colombia. Magnetic resonance imaging is the ideal modality for the evaluation of colorectal cancer, since it allows staging by determining invasion beyond the muscularis propria, extension towards adjacent organs, identification of patients who are candidates for chemotherapy or pre-surgical radiotherapy and planning of the surgical procedure. The key point is based on the differentiation between T2 and T3 stages through the use of sequences with high-resolution T2 information. In addition to this, it allows the assessment of the size and morphology of the lymph nodes, and considerably increases the specificity for the detection of lymph node involvement. MRI is a technique with high specificity and high reproducibility.

This study aims to determine the effects of monosodium glutamate (MSG) dosage on the yield of long beans (Vigna sinensis L.) of the Peleton variety. The use of MSG as a food ingredient has been a topic of debate, but research on its impact on plant growth is still limited, especially regarding long beans. Therefore, this research is important for providing further understanding of the influence of MSG on long beans plants. The study was conducted from July to October 2023 in Mata Air Village, Central Kupang District, Kupang Regency, East Nusa Tenggara Province. The research method used was a Randomized Complete Block Design (RCBD) with 9 treatments and 3 replications. The treatments included: No MSG, MSG at doses of 2.5 g/plant, 5 g/plant, 7.5 g/plant, 10 g/plant, 12.5 g/plant, 15 g/plant, 17.5 g/plant, and 20 g/plant. Parameters observed included flowering age (days), number of pods (pieces), pod length (cm), and pod weight (g). Based on the results and discussion, it can be concluded that MSG application had a significant effect on the number, length, and weight of pods, but had a non-significant effect on flowering age. The treatment of 15 g/plant was identified as the optimal MSG dosage for the plants, resulting in the highest number of pods (16.2), longest pod length (60.4 cm), and highest pod weight (256.4 g/plant). This research is innovative in exploring the potential use of monosodium glutamate (MSG) on long beans plants, particularly the Peleton variety. The focus on MSG application as a growth stimulant is an innovative step that has been less studied previously. The discovery of the optimal MSG dosage (15 g/plant) for achieving the best results provides valuable information for farmers to enhance productivity efficiently, sustainably, and environmentally friendly. Information about MSG’s potential as a plant stimulant can serve as a starting point for more sustainable agricultural strategies aimed at optimizing available resources.