The Effective Pollination Period of European Plum (Prunus domestica L.) Cultivars in Western Norway

This study evaluated the effective pollination period (EPP) in four European plum (Prunus domestica L.) cultivars (‘Mallard’, ‘Edda’, ‘Jubileum’, and ‘Reeves’) during two years (2018–2019) under the environmental conditions in western Norway. The pollination of plum cultivars was carried out one, three, five, seven, and nine days after anthesis (DAA) with a pollen mix of two compatible cultivars (‘Victoria’ and ‘Opal’). Initial, middle-season, and final fruit set was recorded after one month and two months after pollination and just before the harvest, respectively. On average from both years cultivar ‘Jubileum’ had the highest fruit set when pollinated one, three, five, seven, and nine DAA (33.23%, 30.83%, 8.47%, 3.08%, and 1.15%, respectively), which was more than two folds higher fruit set than in the other studied cultivars. Cultivar ‘Jubileum’ showed significantly reduced fruit set between pollination on five and nine DAA, while cultivars ‘Mallard’, ‘Edda’, and ‘Reeves’ had markedly reduced fruit set if pollinated three to five DAA, implying that the EPP in ‘Jubileum’ was five days while in the rest it was three days. Variation of weather conditions during the flowering period in both years did not have a major effect on the receptivity of stigmas in the studied plum cultivars, which means that the existing differences in the length of EPP is maternal-genotype dependent.

The impact of spatial and social structure on an SIR epidemic on a weighted multilayer network

A key factor in the transmission of infectious diseases is the structure of disease transmitting contacts. In the context of the current COVID-19 pandemic and with some data based on the Hungarian population we develop a theoretical epidemic model (susceptible-infected-removed, SIR) on a multilayer network. The layers include the Hungarian household structure, with population divided into children, adults and elderly, as well as schools and workplaces, some spatial embedding and community transmission due to sharing communal spaces, service and public spaces. We investigate the sensitivity of the model (via the time evolution and final size of the epidemic) to the different contact layers and we map out the relation between peak prevalence and final epidemic size. When compared to the classic compartmental model and for the same final epidemic size, we find that epidemics on multilayer network lead to higher peak prevalence meaning that the risk of overwhelming the health care system is higher. Based on our model we found that keeping cliques/bubbles in school as isolated as possible has a major effect while closing workplaces had a mild effect as long as workplaces are of relatively small size.

Necrotic debris and STING exert therapeutically relevant effects on tumor cholesterol homeostasis

Malignant tumors commonly display necrosis, which invariably triggers an inflammatory response that supports tumor growth. However, the effect on tumor cells of necrotic debris, or damage-associated molecular patterns (DAMPs) released by dying cells is unknown. Here, we addressed the effect of DAMPs on primary Ewing sarcoma (EwS) cells and cell lines grown in 3D (spheroids) and 2D culture. We show that DAMPs promote the growth of EwS spheroids but not 2D cultures and that the underlying mechanism implicates an increase in cholesterol load in spheroids. In contrast, stimulation of the nucleic acid sensor signaling platform STING by its ligand cyclic GMP-AMP decreases the tumor cell cholesterol load and reduces their tumor initiating ability. Overexpression of STING or stimulation with cyclic GMP-AMP opposes the growth stimulatory effect of DAMPs and synergizes with the cholesterol synthesis inhibitor simvastatin to inhibit tumor growth. Our observations show that modulation of cholesterol homeostasis is a major effect of necrotic cell debris and STING and suggest that combining STING agonists with statins may help control tumor growth.

Issues with Romance in the Workplace Environment

Due to the increased interaction between coworkers on a daily basis, studies show there is a direct correlation with romance that stems from the workplace. While there can be benefits, this paper will show how romances in the workplace can result in negative effects on the workplace environments through a multitude of ways. Workplace Romances deal with issues originating from hierarchal relationships, including sexual harassment and favouritism, which further impacts job productivity and morale. The existence of these forms of relationships may be unavoidable, yet they can also be damaging to a company when relationships become unsuccessful. Workplace Romances can have a major effect on coworkers, including tension and conflict. Workplace policies are a divided subject, as they could perhaps prevent issues, while at the same time, they may create further issues.

Importance of ICT Advancement and Culture of Adaptation in the Tourism and Hospitality Industry for Developing Countries

The influence of ICT on tourism and hospitality is related to the facilitation of contact with stakeholders, acting as an effective distribution channel, and providing an effective forum for marketing, among other things. Tourism and hospitality are heavily reliant on information and communication technology in developing countries as well as in the developed nations. ICT has had a major effect on this market. The primary goal of this research is to identify the difference in ICT advancement and adaptation between developed and developing countries, as well as to determine how developing countries can benefit from it and make recommendations. This research was conducted using a qualitative approach. Using various types of literature such as research papers, articles, and books, this study highlights and scrutinizes the significance of ICT and how these actions contribute to the tourism and hospitality sector to raise awareness among academicians, researchers, tourism businesses, and government officials about the effectiveness of ICT applications in tourism and hospitality.

Dynamic analysis of a malaria reaction-diffusion model with periodic delays and vector bias

<abstract><p>One of the most important vector-borne disease in humans is malaria, caused by <italic>Plasmodium</italic> parasite. Seasonal temperature elements have a major effect on the life development of mosquitoes and the development of parasites. In this paper, we establish and analyze a reaction-diffusion model, which includes seasonality, vector-bias, temperature-dependent extrinsic incubation period (EIP) and maturation delay in mosquitoes. In order to get the model threshold dynamics, a threshold parameter, the basic reproduction number $ R_{0} $ is introduced, which is the spectral radius of the next generation operator. Quantitative analysis indicates that when $ R_{0} &lt; 1 $, there is a globally attractive disease-free $ \omega $-periodic solution; disease is uniformly persistent in humans and mosquitoes if $ R_{0} &gt; 1 $. Numerical simulations verify the results of the theoretical analysis and discuss the effects of diffusion and seasonality. We study the relationship between the parameters in the model and $ R_{0} $. More importantly, how to allocate medical resources to reduce the spread of disease is explored through numerical simulations. Last but not least, we discover that when studying malaria transmission, ignoring vector-bias or assuming that the maturity period is not affected by temperature, the risk of disease transmission will be underestimate.</p></abstract>

Geospatial Evaluation of Land Use and Land Cover Changes in Ashulia Industrial Hub in Dhaka, Bangladesh

Spatial and temporal evaluation of the land use and land cover (LULC) changes, its dynamism and overall consequences are considered the fundamental variables in global climate change. These immense changes influence ecosystem, life, and livelihoods. Over the last few decades, industrial expansion in Bangladesh has a major effect on LULC across the suburban areas of the capital city Dhaka, especially the surrounding areas of Ashulia industrial hub. While providing new approaches to improve the frontiers of antecedent revolutions, particularly those of LULC changes monitoring and mapping, this study tried to evaluate further land development and planning in the study area between 2014 and 2020. Remote sensing imageries and relevant multiple secondary information were consecutively used as datasets. The interactive supervised classification tool using a maximum likelihood process was applied in LULC changes evaluations, detections, and as well providing fruitful explanations. Therefore, evaluated LULC maps’ overall accuracies were between 84% and96%, and kappa coefficient between 0.83 and 0.92. The results revealed that the urbanization and built-up area were the prime LULC type (77.36% in 2020) in the study area and were exceedingly increasing land cover type over water bodies, bare land and vegetation. Overall, in between 2014 and 2020, the LULC types as of water bodies, barelands, and vegetation have decreased by 212 hectares, 435 hectares, and 470 hectares, respectively. Moreover, overall downward trends of LULC changes were identified in all the land use types except built-up area. Hence, imbalanced land conversions and lack of proper planning together were creating the region highly vulnerable to several disasters as well as imbalanced ecosystem. Th study findings can help the decision makers and planners apart from future research.

Prediction of Soil Particle Size Fraction using Geographically Weighted Regression and Random Forest

The development of spatial modeling for soil properties has progressed in recent decades. This responds to the growing demand for land spatial data and exact soil property prediction for agronomical reasons, particularly in precision farming, in order to speed up precision agricultural activities. In this regards a comparison of the GWR and RF models was carried out in order to determine which model is the best at forecasting surface soil texture and how dependable each model is at doing so. The purpose of this research is to get the best model in predicting particle soil fraction (PSF). 50 topsoil samples were collected from several locations in the Kalikonto Watershed, Indonesia, and the soil PSF (sand, silt, and clay) in the upper 10 cm varied. The LMV, slope, and elevation were calculated using DEM data and utilized as predictor variables. As a result, the weighting of the GWR model has a considerable impact on the final model, and all other factors have a major effect on the PSF determination. The RF, on the other hand, looks to be superior than the GWR variants. The RF model outperformed the other models in every PSF variable. This study reveals that topsoil quality and terrain attributes are linked, which may be assessed using field measurements and model projections. More research is needed to generate more efficient input parameters that will help with soil variability precision and accuracy of soil map products.