Cocoa is important for the economy and rural development of Ghana. However, small-scale cocoa production is the leading agricultural product driver of deforestation in Ghana. Uncertain tree tenure disincentivizes farmers to retain and nurture trees on their farms. There is therefore the call for structures that promote tree retention and management within cocoa farming. We examined tenure barriers and governance for tree resources on cocoa farms. Data was collected from 200 cocoa farmers from two regions using multistage sampling technique. Information was gathered on tree ownership and fate of tree resources on cocoa farms, tree felling permit acquisition and associated challenges and illegal logging and compensation payments on cocoa farms. Results suggest 62.2% of farmers own trees on their farms. However, these farmers may or may not have ownership rights over the trees depending on the ownership of their farmlands. More than half of the farmers indicated they require felling permits to harvest trees on their farms, indicative of the awareness of established tree harvesting procedures. Seventy percent of the farmers have never experienced illegal logging on their farms. There is however the need to educate the remaining 30% on their rights and build their compensation negotiation powers for destructions to their cocoa crops. This study has highlighted ownership and governance issues with cocoa farming and it is important for the sustainability of on-farm tree resources and Ghana’s forest at large.

In the era of rapid information technology development, artificial intelligence (AI) and virtual reality (VR) technologies have gradually infiltrated the field of university English teaching, brought significant applications and impacted to English language learning in listening, speaking, writing, translation, and personalized learning. AI plays a vital role as an auxiliary teaching method in university English instruction, and the integration of VR technology further enhances teaching efficiency. This research will propose relevant recommendations to provide theoretical references for university English education in the age of AI, while also offering insights and guidance to educators in the education industry during the informatization reform of education.

Cancer is the 3rd leading cause of death globally, and the countries with low-to-middle income account for most cancer cases. The current diagnostic tools, including imaging, molecular detection, and immune histochemistry (IHC), have intrinsic limitations, such as poor accuracy. However, researchers have been working to improve anti-cancer treatment using different drug delivery systems (DDS) to target tumor cells more precisely. Current advances, however, are enough to meet the growing call for more efficient drug delivery systems, but the adverse effects of these systems are a major problem. Nanorobots are typically controlled devices made up of nanometric component assemblies that can interact with and even diffuse the cellular membrane due to their small size, offering a direct channel to the cellular level. The nanorobots improve treatment efficiency by performing advanced biomedical therapies using minimally invasive operations. Chemotherapy’s harsh side effects and untargeted drug distribution necessitate new cancer treatment trials. The nanorobots are currently designed to recognize 12 different types of cancer cells. Nanorobots are an emerging field of nanotechnology with nanoscale dimensions and are predictable to work at an atomic, molecular, and cellular level. Nanorobots to date are under the line of investigation, but some primary molecular models of these medically programmable machines have been tested. This review on nanorobots presents the various aspects allied, i.e., introduction, history, ideal characteristics, approaches in nanorobots, basis for the development, tool kit recognition and retrieval from the body, and application considering diagnosis and treatment.

During the early spring in the woodlands of eastern North America, Phlox drummondii emerges as a perennial plant adorned with a profusion of blooms in shades of blue, purple, pink, or white. Its evergreen nature adds to its charm. To manage the growth of plants or specific plant parts, plant growth regulators (PGRs) are synthesized and employed, serving as valuable tools for controlling and directing the development of various plant species. A diverse range of ornamental plants, such as Phlox drummondii, have been documented to receive exogenous applications of plant growth regulators (PGRs). Among these regulators, gibberellins (GA) play a vital role by delaying senescence in flowers and promoting the breaking of dormancy in seeds, bulbs, and corms of ornamental plants. The experiment aimed to assess the performance and determine the optimal growth medium for Phlox. Five distinct growth media were employed as treatments during the study, which took place in the Horticulture Department of Gomal University. Collected data underwent analysis through ANOVA and Tuckey HSD tests. The study’s findings revealed that the highest plant height (16 cm) was observed in the control treatment with PGR 1, closely followed by PGR 2 (11.5 cm). The treatment labeled as T5, composed of a mixture of 1/3 sand, 1/3 poultry manure, and 1/3 soil, demonstrated the most favorable results across multiple parameters such as bud initiation (BI), first flower emergence (FFE), flowers per plant (FPP), branches per plant (BPP), leaves per plant (LPP), number of roots (NR), field life of flowers (FLF), and flower diameter (FD). T4, T3, T2, and T1 treatments also exhibited similar positive outcomes, aligning with the promising performance of T5.

The purpose of this study is to investigate customer satisfaction with quality of service known as SERVQUAL improvement or service quality competitiveness in emerging markets. Using Indonesian government medical care as an example the author examines the satisfaction of patients. Information and data were collected through a survey of 399 BPJS users in Indonesia. All data were analyzed using Smart PLS. This study demonstrates that there is a negative value associated with the five-dimensional gap. As a result, the care provided to BPJS patients is below par. Specifically, the sensitivity dimension has the largest disparity at 0.15, while the physical evidence dimension has the smallest at 0.49. In order to raise the level of service provided, it may be necessary to take direct measures or examine tangible evidence. This study develops the relationship between different quality service models. There appears to be a substantial increase in the body of literature in the area of service quality, allowing for constant updates and the incorporation of the lessons learned from the experiences of the departed. These revised guidelines are intended to aid SERVQUAL study participants. The study gives practical support to academics and practitioners in directing service quality improvement through the use of data collected from large-scale surveys of patients and medical professionals as doctors in Indonesia.

To gain a deep understanding of maintenance and repair planning, investigate the weak points of the distribution network, and discover unusual events, it is necessary to trace the shutdowns that occurred in the network. Many incidents happened due to the failure of thermal equipment in schools. On the other hand, the most important task of electricity distribution companies is to provide reliable and stable electricity, which minimal blackouts and standard voltage should accompany. This research uses seasonal time series and artificial neural network approaches to provide models to predict the failure rate of one of the equipment used in two areas covered by the greater Tehran electricity distribution company. These data were extracted weekly from April 2019 to March 2021 from the ENOX incident registration software. For this purpose, after pre-processing the data, the appropriate final model was presented with the help of Minitab and MATLAB software. Also, average air temperature, rainfall, and wind speed were selected as input variables for the neural network. The mean square error has been used to evaluate the proposed models’ error rate. The results show that the time series models performed better than the multi-layer perceptron neural network in predicting the failure rate of the target equipment and can be used to predict future periods.