Title: In vitro Photodynamic Therapy in the Treatment of Endometrial Cancer

Abstract:Background Endometrial cancer is the fourth most common type of cancer in the world. Due to the prevalence and high morbidity, it is of key importance to make a quick and accurate diagnosis and effective therapy. The use of photodynamic therapy (PDT) in the treatment of endometrial cancer is a significant challenge in conducting clinical trials. PDT is non-invasive, with few side effects, damaging only neoplastic tissue, leaving healthy adjacent structures intact. Thanks to numerous experiments (also in vitro), PDT is gaining more and more recognition as a potential tool in endometrium cancer treatment.Objective The aim of the study was to analyze the effectiveness of photodynamic therapy on endometrial cancer tissue samplesMethods In the in vitro experiment of PDT, sections of endometrial cancer tissue taken from female patients were subjected to. Rose Bengal was used as a photosensitizer in order to assess the usefulness of the applied PDT and to introduce these solutions into the in vivo test procedure.Results Changes on the cellular substrate, such as: chromatin condensation, disturbed structure and shape of cell nuclei were observed in all tissues subjected to PDT.Conclusions The PDT experiment in vitro offers opportunities and hopes for using the chosen procedure also in vivo.


Abstract:Vitamin D3 is a steroid hormone produced in the skin under the influence of UV radiation. It is a vitamin discovered in the 20th century and constantly rediscovered. Over the last few decades, numerous scientists conducting research on vitamin D3 have shown its increasing impact on the proper functioning of the human body.\nThis work will present the process of synthesis, metabolism, mechanism of action of vitamin D3, as well as its pleiotropic effect. In preparation for this review\nmostly publications from the last 20 years were selected, but older, highly valued publications were not excluded.

Title: AIWLO-WMO Model Based an Artificial Intelligence to Smart Waste Management for Smart Cities Environment

Abstract:Smart waste management is one of the world\'s massive challenges, either in the advanced or started economies. Regularly, the technologies of artificial intelligence obtained recognition in presenting different computer techniques to solving smart waste challenge. The smart waste management of specified problems, events and doubts and partial statistics were capable for AI. Although this task did operate lots of findings, very few assessments proved the impact of AI to determine numerous difficulties of intelligent organization of waste. Perfect assessment of waste amount and condition is explained to Smart waste management technique development and model.\nCurrently, heavy quantity of waste resources has become substantial enhanced with increasing population. Appropriate management of waste resources becomes necessary to decrease environmental degradation and recover value of life in smart cities. Smart Waste management supports to gather and heal waste resources from society. Suitable arrangement of waste objects needs the model of automated waste category models based on artificial intelligence and image processing-based methods. The aim of this paper, an automated artificial intelligence with world larva optimization supports waste management and organization (AIWLO-WMO) model is proposed for smart cities environment. The proposed model mainly develops a RetinaNet built object finding segment to recognize the presence of smart waste objects in the views. To better the category operation, Adagrad optimizer has used. To confirming the invented outcome of the AIWLO-WMO method, complete testing is performed on normal dataset and the found rates implied the authority of AIWLO-WMO model throughout other methods with expanded accuracy of 99.62%.

Title: Unraveling the Multifaceted Nature of Breast Cancer: Harnessing the Power of Machine Learning and Statistical Models for In-depth Investigation, Prognosis, and Treatment Optimization

Abstract:The most prevalent form of cancer in all of human history. Women typically have a shorter lifespan than men. The death toll from breast cancer is higher than that of any other type of cancer. After \nreaching puberty, women all around the world are at risk for developing breast cancer, however, the disease is more prevalent in elderly individuals. The death rate from breast cancer did not \nsignificantly change from the 1930s through the 1970s. In the 1980s, countries that were healthcare conscious and had early detection systems, as well as a variety of treatment modalities \nto eliminate invasive diseases, began to see an increase in their overall survival rates. This article employed decision tree models and time series models to anticipate breast cancer using time series data from 1930 to 2019. The breast cancer cases that occurred in the United States of America served as the basis for this study. The most precise prediction models will be produced as a result of this data analysis. In order to evaluate how well the predictions were made, we determined how accurate they were by calculating the symmetric mean absolute percentage errors (sMAPE), measured mean absolute percentage errors (MASE), and mean absolute percentage errors (MAPE).

Title: An Efficient Metaheuristic algorithm for optimization for Location of Optimum Connectivity Services with Drones in Healthcare

Abstract:Drones are being extensively used for a variety of practical purposes, including providing \nmedical care. For instance, giving vaccinations, healthcare equipment, and samples of blood to \nindividuals in isolated locations as well as during calamities. This study examined an efficient \nmetaheuristic algorithm called MAP-LOCS, which optimizes the location of optimal \nconnectivity amenities using drones. The use of drones in relation to facility placement and \nnavigation is the issue. Within certain drone range limits, it entails choosing drone launch spots \nto optimize patient care availability. This work develops a heuristic called Location of Optimal \nConnection Services. The algorithm\'s basic premise is to start by randomly selecting a few \nservices to open from among those that are most capable of meeting patient requests. Following \nthat, patients are matched with the nearest open facility that can accommodate them. In the end, \npatients get allocated a drone according to which one uses the smallest quantity of battery life \nwhen traveling between the patient and the facility. In a short amount of time, it was capable \nof handling a large number of patients (above 90% on average).

Title: Using Drone Technology Smart Waste Management in Reducing Municipal Solid Waste and Enhancing Society Recycling Rate

Abstract:Fast industrial development and expansion in several portions of the earth have controlled to a rush in waste production. Presently, over 50 percent of the world’s population has established into smart cities. Near 2030, an expected 60 percent of the population will move from rural to urban zones, on behalf of up to 1.5 billion populations. The town population is established to rise considerably by 2045 to 6 billion; by 2050, it is predictable that seven out of 10 populations will be living within town zones.\nLast 30 years, the Kingdom of Saudi Arabia has verified financial growth and expansion rates corresponding by consistent directs of intake. It has indicated to an exponential raise in the capacity of municipal solid waste. Constant if the mass segment of this waste is recyclable, the inclination of residential to retain in the recycling of waste has so far constructed a minor influence.\n\nThe objective of paper, smart waste management is a new frontier for local authorities assisting in reducing municipal solid waste and improving community recycling rate. We must solve this problem by driving Drone Technology, manufacturing and their established approaches are redefined. Unmanned Aerial Vehicles (UAVs) have released their capacity in the Smart Waste Management industry still again and have confirmed to be the most efficient, virtual tool. \nWe have driven a drone program smart waste management to provide exact and real-time data of your smart waste’s progression and throughput. Drones are not only seeking your waste management, but also save the environment. The objective of zero waste is to decrease and finally destroy smart waste and smart waste management.


Abstract:Micro, small and medium enterprises did not witness the required growth in India despite their importance in generating job opportunities, alleviating poverty, and contributing to economic growth, given the different types of traditional financing (commercial banks, private financing institutions) have not provided adequate financing led to their growth. The relationship between sustainable financing and the growth of (MSMEs), and GDP growth, has not been well studied. The focus of this study is to see the nexus between sustainable financing and the growth of micro, small and medium enterprises, and economic growth in India. In line with the design study, a sample of 72 MSMEs was selected who have access to sustainable financing in Bangalore. The data has been analyzed to measure the relationships between financing, MSMEs growth, and economic growth using the correlation test and (OLS) method. The results from the analysis of the current study show that sustainable finance is essential for the growth of micro, small, and medium enterprises and economic growth.

Title: A Review of Climate Change Adaptation in the Arctic

Abstract:The Arctic is experiencing rapid climate change impacts necessitating adaptation. This systematic literature review provides an overview of the recent climate change indicators necessitating adaptation and the actions implemented in response. Articles included focus on communities across the Arctic and were published between the years 2000 and 2020. Through qualitative analysis of the literature, four indicators of climate change were presented through a social-ecological lens: (1) the degradation of ice, (2) changes in ecosystems, (3) changes in weather patterns, and (4) changes in hydrogeological risk. Further, three main types of adaptation were presented: (1) behavioral changes, (2) regulatory initiatives, and (3) changes to livelihoods or economics. Critically, most of these adaptation actions were implemented at an individual level.

Title: By the Population of Waste Materials Detection of Images in Smart Cities using Internet Drone

Abstract:Internet drone, in modest things, is a kind of rapid automaton that is remotely organized by human beings. It is in machinery relations also known as Unmanned Floating Automobile (UFA). By numerous innovative developments in drone equipment, it has predictable that drones grow additional to contain analytical skills, specifically in the waste materials detection of images in smart cities. The drone offered in this article will be applied for the distribution of waste materials detection of images. Through a security system executed on the vessel involved, it confirms the protection of the waste materials detection of images till they get the correct place. The planned structure is an internet-based drone consuming the values of Internet of Things.\nStill, the procedure of drones’ desires trained control and appropriate setup. Waste materials detection of images by internet drone are misguidedly measured as security drones, therefore has been criticized by prepared services. \n\nWithout the use of internet drones, operators are accountable for conveying things at a high cost. The goal of this internet drone is to monitor waste materials detection of images in smart cities. It is to detect waste material images and send them to administrator (Municipality). The internet drone is accomplished of finding these services and detected images statistics in a 360-degree cycle inside the smart cities. When broadcast is problematic, the self-maintaining internet drone are the ready for rapidly moving one location to another detect waste material images.

Title: A Systematic Review of emerging Trends on Quality of care in the health care

Abstract:High-quality of health care systems are more crucial than service quality in the other sectors because they have a major impact on the health and well-being. In reality, there has been a lot of interest in healthcare quality since raising the standard of treatment has a favourable effect on a nation\'s population\'s health, which in turn helps the economy and culture as a whole. Increasing the calibre of hospital treatment is a top goal for all nations, particularly developing ones where hospitals serve as the primary healthcare facilities. The current research study was inspired by a number of studies on the costs and issues associated with malnutrition. Relevant papers were included after a search of the internet databases of Pubmed, EMBASE, the Web of Science was done with English as the only permitted language. After that, databases got accessed to perform a more thorough literature search using key words or Boolean operators to produce papers relevant to the problem. Using inclusion/exclusion criteria, these papers were vetted to create a manageable eight pieces. These eight articles were evaluated, and the results showed that now the healthcare delivery and standard of care in the health sector suffer from considerable gaps. The study revealed the disparities in key service & quality of care parameters that depend on one another.Doctors & paramedical staff availability, patient discharge procedures, hospital documentation policies, staff awareness of social responsibility, management standards, and medicine availability are some of the important hospital administration elements that have an impact on staff-patient interactions. The Research study came to the conclusion that Healthcare managers as service providers should think about improving the healthcare quality and other dimensions in addition to concentrating on those with the biggest gaps. On these less explored characteristics, future scholars can base their work. The average stay duration, patient cooperation, patient quality/illness, and patient socio-demographic parameters are the final elements influencing the level of service in terms of patient characteristics.