Search results for: Statistical%20package%20IBM%20SPSS%2020

Authors: David C. Boettiger, Tracy Kuo Lin, Maram Almansour, Mariam M. Hamza, Reem Alsukait, Christopher H. Herbst, Nada Altheyab, Ayman Afghani, Faisal Kattan

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Background The number of people aged greater than 65 years per 100 people aged 20–64 years is expected to almost double in The Kingdom of Saudi Arabia (KSA) between 2020 and 2030. We therefore aimed to quantify the growing non-communicable disease (NCD) burden in KSA between 2020 and 2030, and the impact this will have on the national health budget. Methods Ten priority NCDs were selected: ischemic heart disease, stroke, type 2 diabetes, chronic obstructive pulmonary disease, chronic kidney disease, dementia, depression, osteoarthritis, colorectal cancer, and breast cancer. Age- and sex-specific prevalence was projected for each priority NCD between 2020 and 2030. Treatment coverage rates were applied to the projected prevalence estimates to calculate the number of patients incurring treatment costs for each condition. For each priority NCD, the average cost-of-illness was estimated based on published literature. The impact of changes to our base-case model in terms of assumed disease prevalence, treatment coverage, and costs of care, coming into effect from 2023 onwards, were explored. Results The prevalence estimates for colorectal cancer and stroke were estimated to almost double between 2020 and 2030 (97% and 88% increase, respectively). The only priority NCD prevalence projected to increase by less than 60% between 2020 and 2030 was for depression (22% increase). It is estimated that the total cost of managing priority NCDs in KSA will increase from USD 19.8 billion in 2020 to USD 32.4 billion in 2030 (an increase of USD 12.6 billion or 63%). The largest USD value increases were projected for osteoarthritis (USD 4.3 billion), diabetes (USD 2.4 billion), and dementia (USD 1.9 billion). In scenario analyses, our 2030 projection for the total cost of managing priority NCDs varied between USD 29.2 billion - USD 35.7 billion. Conclusions Managing the growing NCD burden in KSA’s aging population will require substantial healthcare spending increases over the coming years.

Keywords: aging, non communicable disease, costs, Saudi Arabia

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Authors: Puntarikorn Rungrattanakasin

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Objectives: To develop the trigger tool to warn about the risk of bleeding as an adverse event from warfarin drug usage during admission in Medical Wards of Chumphae Hospital. Methods: A retrospective study was performed by reviewing the medical records for the patients admitted between June 1st,2020- May 31st, 2021. ADEs were evaluated by Naranjo’s algorithm. The international normalized ratio (INR) and events of bleeding during admissions were collected. Statistical analyses, including Chi-square test and Reciever Operating Characteristic (ROC) curve for optimal INR threshold, were used for the study. Results: Among the 139 admissions, the INR range was found to vary between 0.86-14.91, there was a total of 15 bleeding events, out of which 9 were mild, and 6 were severe. The occurrence of bleeding started whenever the INR was greater than 2.5 and reached the statistical significance (p <0.05), which was in concordance with the ROC curve and yielded 100 % sensitivity and 60% specificity in the detection of a bleeding event. In this regard, the INR greater than 2.5 was considered to be an optimal threshold to alert promptly for bleeding tendency. Conclusions: The INR value of greater than 2.5 (>2.5) would be an appropriate trigger tool to warn of the risk of bleeding for patients taking warfarin in Chumphae Hospital.

Keywords: trigger tool, warfarin, risk of bleeding, medical wards

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Authors: Dimitra Alexiou

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During the last 10 years, in spite of the economic crisis, the number of tourists arriving in Greece has increased, particularly during the tourist season from April to October. In this paper, the number of annual tourist arrivals is studied to explore their preferences with regard to the month of travel, the selected destinations, as well the amount of money spent. The collected data are processed with statistical methods, yielding numerical and graphical results. From the computation of statistical parameters and the forecasting with exponential smoothing, useful conclusions are arrived at that can be used by the Greek tourism authorities, as well as by tourist organizations, for planning purposes for the coming years. The results of this paper and the computed forecast can also be used for decision making by private tourist enterprises that are investing in Greece. With regard to the statistical methods, the method of Simple Exponential Smoothing of time series of data is employed. The search for a best forecast for 2017 and 2018 provides the value of the smoothing coefficient. For all statistical computations and graphics Microsoft Excel is used.

Keywords: tourism, statistical methods, exponential smoothing, land spatial planning, economy

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Authors: Akhigbe Mark, Abang Roger, Mwoltu Nanaribet, Edet Blessing

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Introduction.: The introduction of pre- exposure prophylaxis (PrEP) as a biomedical prevention method for HIV/AIDS has been around for more than a decade since the first confirmed evidence of its effectiveness when used daily as an oral pill. It is now a very valuable addition for people who are at higher risk of contracting HIV. Although globalacceptanceof PrEP hasincreased, PrEP is still highly concentrated in a small number of countries and within a small sub-population, with Kenya and South Africa accounting for only 19% of people who have received PrEP in Africa region, there is still a significant regionGap in PrEP availability and use, with only 28% of the target of 3 million in low-and middle countries currently using PrEP. Description: The purpose of this study is to find out if serum creatinine could be used as an incentive to improve PrEP uptake among Key population.Numerous approaches to increasing the uptake ofPrEP as a prevention mechanism for HIV in KPs has beenemployed, and one of them is serum creatinine. This approach is a biomarker of renal function, which was used in study as an incentive to increase PrEP uptake among key population groups (female sex workers, men who have sex with men, persons who inject drugs, transgender) in 3 states from South-South Nigeria. Whole blood samples are collected from clients, analysis of the samples is done using the clinical chemistry analyzer before they are initiated onto PrEP. Lessons learned and Recommendations: Secondary data was extracted from 3 states of HALG Implementing facilities in Southern part of Nigeria, PrEP uptake before and afterthe introduction of serum creatinine between March 2020 and August 2020 among key populationsin Nigeria. A total of 5664 patients were initiated on PrEP before, and after the introduction of serum creatinine, the PrEP uptake rate before (March 2020 to May 2020) introduction of serum creatinine accounted for only 5% of the total onset, and after (June 2020 to August 2020) introduction of serum creatinine, the uptake rate accounted for 95% of the total onset. These finding shows that increased uptake of PrEP before/after serum creatineindicates that serum creatine may be an effective stimulus for promoting PrEP in key populations.

Keywords: serum creatinine, incentives, PrEP, key populations, Nigeria

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Authors: Baqir Khawari

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This study has been undertaken to investigate the impact of remittances on household poverty and inequality using OLS and Logit Models with a strictly multi-random sampling method. The result of the OLS model reveals that if the per capita international remittances increase by 1%, then it is estimated that the per capita income will increase by 0.071% and 0.059% during 2019/20 and 2020/21, respectively. In addition, a 1% increase in external remittances results in a 0.0272% and 0.025% reduction in per capita depth of poverty and a 0.0149% and 0.0145% decrease in severity of poverty during 2019/20 and 2020/21, respectively. It is also shown that the effect of external remittances on poverty is greater than internal remittances. In terms of inequality, the result represents that remittances reduced the Gini coefficient by 2% and 7% during 2019/20 and 2020/21, respectively. Further, it is bold that COVID-19 negatively impacts the amount of received remittances by households, thus resulting in a reduction in the size of the effect of remittances. Therefore, a concerted effort of effective policies and governance and international assistance is imperative to address this prolonged problem.

Keywords: migration, remittances, poverty, inequality, COVID-19, Afghanistan

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Authors: Vinko Viducic, Jelena Žanic Mikulicic, Maja Racic, Kristina Sladojevic

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The research presented in this paper has been focused on analyzing the impact of traffic on the sustainable development of tourism in Croatia's Dubrovacko-Neretvanska County by the year 2020, based on the figures and trends reported in 2014 and using the relevant variables that characterise the synergy of traffic and tourism in, speaking from the geographic viewpoint, the most problematic county in the Republic of Croatia. The basic hypothesis has been confirmed through scientifically obtained research results, through the quantification of the model's variables and the direct growth rates of the designed model. On the basis of scientific insights into the sustainable development of traffic and tourism in Dubrovacko-Neretvanska County, it is possible to propose a new information model for traffic at the service of the sustainable development of tourism in the County for the period 2014-2020.

Keywords: environment protection, hotel industry, private sector, quantification

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Authors: Jie Ji, Jing Xu, Yuehong Zhuang, Xiangqing Kang, Ying Qian, Ping Zhou, Di Xue

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Background: In 2014, there were 28,341 health professionals in Pudong new area of Shanghai and the number per 1000 population was 5.199, 55.55% higher than that in 2006. But it was always less than the average number of health professionals per 1000 population in Shanghai from 2006 to 2014. Therefore, allocation planning for the health professionals in Pudong new area has become a high priority task in order to meet the future demands of health care. In this study, we constructed an objective-based system dynamics model to forecast the number of health professionals in Pudong new area of Shanghai in 2020. Methods: We collected the data from health statistics reports and previous survey of human resources in Pudong new area of Shanghai. Nine experts, who were from health administrative departments, public hospitals and community health service centers, were consulted to estimate the current and future status of nine variables used in the system dynamics model. Based on the objective of the number of health professionals per 1000 population (8.0) in Shanghai for 2020, the system dynamics model for health professionals in Pudong new area of Shanghai was constructed to forecast the number of health professionals needed in Pudong new area in 2020. Results: The system dynamics model for health professionals in Pudong new area of Shanghai was constructed. The model forecasted that there will be 37,330 health professionals (6.433 per 1000 population) in 2020. If the success rate of health professional recruitment changed from 20% to 70%, the number of health professionals per 1000 population would be changed from 5.269 to 6.919. If this rate changed from 20% to 70% and the success rate of building new beds changed from 5% to 30% at the same time, the number of health professionals per 1000 population would be changed from 5.269 to 6.923. Conclusions: The system dynamics model could be used to simulate and forecast the health professionals. But, if there were no significant changes in health policies and management system, the number of health professionals per 1000 population would not reach the objectives in Pudong new area in 2020.

Keywords: allocation planning, forecast, health professional, system dynamics

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Authors: N. Pegahfar, P. Ghafarian

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In this research, the synoptic weather conditions during the heavy flood of 10-12 January 2020 in the Sistan-va-Balouchestan Province of Iran will be analyzed. To this aim, reanalysis data from the National Centers for Environmental Prediction (NCEP) and National Center for Atmospheric Research (NCAR), NCEP Global Forecasting System (GFS) analysis data, measured data from a surface station together with satellite images from the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) have been used from 9 to 12 January 2020. Atmospheric parameters both at the lower troposphere and also at the upper part of that have been used, including absolute vorticity, wind velocity, temperature, geopotential height, relative humidity, and precipitation. Results indicated that both lower-level and upper-level currents were strong. In addition, the transport of a large amount of humidity from the Oman Sea and the Red Sea to the south and southeast of Iran (Sistan-va-Balouchestan Province) led to the vast and unexpected precipitation and then a heavy flood.

Keywords: Sistan-va-Balouchestn Province, heavy flood, synoptic, analysis data

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Authors: Encarnación Álvarez-Verdejo, Raúl Amor-Pulido, Pablo J. Moya-Fernández, Juan F. Muñoz-Rosas, Francisco J. Blanco-Encomienda

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Many companies use the statistical tool named as statistical quality control, and which can have a high cost for the companies interested on these statistical tools. The evaluation of the quality of products and services is an important topic, but the reduction of the cost of the implantation of the statistical quality control also has important benefits for the companies. For this reason, it is important to implement a economic design for the various steps included into the statistical quality control. In this paper, we describe some relevant aspects related to the economic design of a quality control chart for the proportion of defective items. They are very important because the suggested issues can reduce the cost of implementing a quality control chart for the proportion of defective items. Note that the main purpose of this chart is to evaluate and control the proportion of defective items of a production process.

Keywords: proportion, type I error, economic plan, distribution function

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Authors: Elisabete Alberdi, Irantzu Álvarez, Nerea Astigarraga, Heber Hernández

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The purpose of this research work is to study the emissions of certain substances that contribute to air pollution and, as far as possible, to try to eliminate or reduce them, to avoid damage to both health and the environment. This work focuses on analyzing and comparing air quality in 2019 and 2020 in the Autonomous Community of the Basque Country, especially near the UPV/EHU campuses. We use Geostatistics to develop a spatial model and to analyse the levels of pollutants in those areas where the scope of the monitoring stations is limited. Finally, different more sustainable transport alternatives for users have been proposed.

Keywords: air quality, pollutants, monitoring stations, environment, geostatistics

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Authors: Javed Mallick

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In metropolitan areas, rapid changes in land use and land cover (LULC) have ecological and environmental consequences. Saudi Arabia's cities have experienced tremendous urban growth since the 1990s, resulting in urban heat islands, groundwater depletion, air pollution, loss of ecosystem services, and so on. From 1990 to 2020, this study examines the variance and heterogeneity in land surface temperature (LST) caused by LULC changes in Abha-Khamis Mushyet, Saudi Arabia. LULC was mapped using the support vector machine (SVM). The mono-window algorithm was used to calculate the land surface temperature (LST). To identify LST clusters, the local indicator of spatial associations (LISA) model was applied to spatiotemporal LST maps. In addition, the parallel coordinate (PCP) method was used to investigate the relationship between LST clusters and urban biophysical variables as a proxy for LULC. According to LULC maps, urban areas increased by more than 330% between 1990 and 2018. Between 1990 and 2018, built-up areas had an 83.6% transitional probability. Furthermore, between 1990 and 2020, vegetation and agricultural land were converted into built-up areas at a rate of 17.9% and 21.8%, respectively. Uneven LULC changes in built-up areas result in more LST hotspots. LST hotspots were associated with high NDBI but not NDWI or NDVI. This study could assist policymakers in developing mitigation strategies for urban heat islands

Keywords: land use land cover mapping, land surface temperature, support vector machine, LISA model, parallel coordinate plot

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Authors: Gurcharan Singh Buttar

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It has been discovered that although these two areas, statistics, and information theory, are independent in their nature, they can be combined to create applications in multidisciplinary mathematics. This is due to the fact that where in the field of statistics, statistical parameters (measures) play an essential role in reference to the population (distribution) under investigation. Information measure is crucial in the study of ambiguity, assortment, and unpredictability present in an array of phenomena. The following communication is a link between the two, and it has been demonstrated that the well-known conventional statistical measures can be used as a measure of information.

Keywords: probability distribution, entropy, concavity, symmetry, variance, central tendency

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Authors: A. Maghari, V. M. Maleki

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In this paper, we present a quantum statistical mechanical formulation from our recently analytical expressions for partial-wave transition matrix of a three-particle system. We report the quantum reactive cross sections for three-body scattering processes 1 + (2,3)-> 1 + (2,3) as well as recombination 1 + (2,3) -> 2 + (3,1) between one atom and a weakly-bound dimer. The analytical expressions of three-particle transition matrices and their corresponding cross-sections were obtained from the three-dimensional Faddeev equations subjected to the rank-two non-local separable potentials of the generalized Yamaguchi form. The equilibrium quantum statistical mechanical properties such partition function and equation of state as well as non-equilibrium quantum statistical properties such as transport cross-sections and their corresponding transport collision integrals were formulated analytically. This leads to obtain the transport properties, such as viscosity and diffusion coefficient of a moderate dense gas.

Keywords: statistical mechanics, nonlocal separable potential, three-body interaction, faddeev equations

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Authors: Maitri Dave

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Coronaviruses (CoV) is such infectious virus which has impacted globally in a more dangerous manner causing severe lung problems and leaving behind more serious diseases among the people. This pandemic has affected globally and created severe respiratory problems, and damaged the lungs. India has reported the first case of COVID-19 in January 2020. The first wave of COVID-19 took place from April to September of 2020. Soon after, a second peak is also noticed in the month of March 2021, which in turn becomes more dangerous due to a lack of supply of medical equipment. It created resource deficiency globally, specifically in India, where some necessary life-saving equipment like ventilators and oxygenators were not sufficient to cater to the demand-supply ratio effectively. Through carefully examining such a situation, India began to execute the process of vaccination in the month of January 2021 and successfully administered 25,46,71,259 doses of vaccines till now, which is only 15.5% of the total population while only 3.6% of the total population is fully vaccinated. India has authorized the British Oxford–AstraZeneca vaccine (Covishield), the Indian BBV152 (Covaxin) vaccine, and the Russian Sputnik V vaccine for emergency use. In the present study, we have collected all the data state wisely of both first and second wave and analyzed them using MS Excel Version 2019 and SPSS Statistics Version 26. Following the trends, we have predicted the characteristics of the upcoming third wave of COVID-19 and recommended some strategies, early actions, and measures that can be taken by the public health system in India to combat the third wave more effectively.

Keywords: COVID-19, vaccination, Covishiled, Coronavirus

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Authors: Muhammet Şahal, Oğuz Köklü

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As statistical thinking and problem-solving processes have become increasingly important, teachers need to be more rigorously prepared with statistical knowledge to teach their students effectively. This study examined preservice mathematics teachers' development of statistical investigation projects using data and exploratory data analysis tools, following a design-based research perspective and statistical investigation cycle. A total of 26 pre-service senior mathematics teachers from a public university in Turkiye participated in the study. They formed groups of 3-4 members voluntarily and worked on their statistical investigation projects for six weeks. The data sources were audio recordings of pre-service teachers' group discussions while working on their projects in class, whole-class video recordings, and each group’s weekly and final reports. As part of the study, we reviewed weekly reports, provided timely feedback specific to each group, and revised the following week's class work based on the groups’ needs and development in their project. We used content analysis to analyze groups’ audio and classroom video recordings. The participants encountered several difficulties, which included formulating a meaningful statistical question in the early phase of the investigation, securing the most suitable data collection strategy, and deciding on the data analysis method appropriate for their statistical questions. The data collection and organization processes were challenging for some groups and revealed the importance of comprehensive planning. Overall, preservice senior mathematics teachers were able to work on a statistical project that contained the formulation of a statistical question, planning, data collection, analysis, and reaching a conclusion holistically, even though they faced challenges because of their lack of experience. The study suggests that preservice senior mathematics teachers have the potential to apply statistical knowledge and techniques in a real-world context, and they could proceed with the project with the support of the researchers. We provided implications for the statistical education of teachers and future research.

Keywords: design-based study, pre-service mathematics teachers, statistical investigation projects, statistical model

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Authors: Somruay Apichatibutarapong, Chookiat Pudprommart

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The purpose of this study was to develop of statistical analysis by using R programming via internet applied for agriculture experimental design. Data were collected from 65 items in completely randomized design, randomized block design, Latin square design, split plot design, factorial design and nested design. The quantitative approach was used to investigate the quality of learning media on statistical analysis by using R programming via Internet by six experts and the opinions of 100 students who interested in experimental design and applied statistics. It was revealed that the experts’ opinions were good in all contents except a usage of web board and the students’ opinions were good in overall and all items.

Keywords: experimental design, r programming, applied statistics, statistical analysis

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Authors: Olga Sukhoveeva

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Carbon dioxide (CO2) is the main component of carbon biogeochemical cycle and one of the most important greenhouse gases (GHG). Agriculture, particularly arable soils, are one the largest sources of GHG emission for the atmosphere including CO2.Models may be used for estimation of GHG emission from agriculture if they can be adapted for different countries conditions. The only model used in officially at national level in United Kingdom and China for this purpose is DNDC (DeNitrification-DeComposition). In our research, the model DNDC is offered for estimation of GHG emission from arable soils in Russia. The aim of our research was to create the method of DNDC using for evaluation of CO2 emission in Russia based on official statistical information. The target territory was European part of Russia where many field experiments are located. At the first step of research the database on climate, soil and cropping characteristics for the target region from governmental, statistical, and literature sources were created. All-Russia Research Institute of Hydrometeorological Information – World Data Centre provides open daily data about average meteorological and climatic conditions. It must be calculated spatial average values of maximum and minimum air temperature and precipitation over the region. Spatial average values of soil characteristics (soil texture, bulk density, pH, soil organic carbon content) can be determined on the base of Union state register of soil recourses of Russia. Cropping technologies are published by agricultural research institutes and departments. We offer to define cropping system parameters (annual information about crop yields, amount and types of fertilizers and manure) on the base of the Federal State Statistics Service data. Content of carbon in plant biomass may be calculated via formulas developed and published by Ministry of Natural Resources and Environment of the Russian Federation. At the second step CO2 emission from soil in this region were calculated by DNDC. Modelling data were compared with empirical and literature data and good results were obtained, modelled values were equivalent to the measured ones. It was revealed that the DNDC model may be used to evaluate and forecast the CO2 emission from arable soils in Russia based on the official statistical information. Also, it can be used for creation of the program for decreasing GHG emission from arable soils to the atmosphere. Financial Support: fundamental scientific researching theme 0148-2014-0005 No 01201352499 ‘Solution of fundamental problems of analysis and forecast of Earth climatic system condition’ for 2014-2020; fundamental research program of Presidium of RAS No 51 ‘Climate change: causes, risks, consequences, problems of adaptation and regulation’ for 2018-2020.

Keywords: arable soils, carbon dioxide emission, DNDC model, European Russia

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Authors: Caroline Correia, Stefani Perna, John Gaughan, Elizabeth Cerceo

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Introduction: The COVID-19 pandemic has brought unprecedented changes to how hospitals function on a daily basis. Increased personal protective equipment (PPE) usage and measures to pre-package, separate, and decontaminate have the potential to increase the waste load. However, limiting non-essential surgeries drastically reduces operating room (OR) waste, and restricting visitation policies to contain outbreaks may help conserve resources. The impact of these policy changes with increased disposable PPE usage on hospital production of waste is unknown. Methods: Waste produced in pounds (lbs) was measured for January through June during both 2019 and 2020 through Stericycle in Cooper University Hospital in Camden, NJ. This timeframe was selected since the pandemic began in January 2020 in the US. The total waste produced during this time was 328,623 lbs in 2019 and 306,454 lbs in 2020. Using Poisson counts (α=.05), less waste was produced in 2020 (p < 0.001). The amount of sharps and regulated medical waste (grossly bloody items) were both significantly decreased as well (p < 0.0001, p=0.0002), and these account for 10-15% of the total waste produced. Discussion: Despite the increased usage of disposable PPE, overall hospital waste was decreased during the pandemic as compared to prior. As surgeries are estimated to be responsible for up to one-half of waste produced by hospitals, it is possible that constraint on elective procedures contributed to the decreased waste in all three categories; estimates of a 35% decrease in surgical volume would be expected to impact waste production. The effects of the pandemic on waste production should continue to be monitored to understand the environmental impact as health systems resume backlogged surgeries at a higher volume.

Keywords: COVID-19, hospital, surgery, waste

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Authors: Marco Camilli

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This article examines the impact of the pandemic outbreak of COVID-19 in the tourism sector in Italy, analyzing the current scenario, the government decisions and the private company reaction for the summer season 2020. The framework of the data analyzed shows how massive it’s the impact of the pandemic outbreak in the tourism revenue, and the weaknesses of the measures proposed. Keywords Travel &Tourism, Transportation, Sustainability, COVID-19, Businesses Introduction The current COVID-19 scenario shows a shocking situation for the tourism and transportation sectors: it could be the most affected by the Coronavirus in Italy. According to forecasts, depending on the duration of the epidemic outbreak and the lockdown strategy applied by the Government, businesses in the supply chain could lose between 24 and 66 billion in turnover in the period of 2020-21, with huge diversified impacts at the national and regional level. Many tourist companies are on the verge of survival and if there are no massive measures by the government they risk closure. Data analysis The tourism and transport sector could be among the sectors most damaged by Covid-19 in Italy. Considering the two-year period 2020-21, companies operating in the travel & tourism sector (Tour operator, Travel Agencies, Hotel, Guides, Bus Company, etc..) could in suffer losses in revenues of 24 to 64 billion euros, especially in the sectors such as the travel agencies, hotel and rental. According to Statista Research Department, from April 2020 estimated that the coronavirus (COVID-19) pandemic will have a significant impact on revenues of the tourism industry in Italy. Revenues are expected to decrease by over 40 billion euros in the first semester of 2020, compared to the same period of the previous year. According to the study, hotel and non-hotel accommodations will experience the highest loss. Revenues of this sector are expected to decrease by 13 billion euros compared to the first semester of 2019 when accommodations registered revenues for about 17 billion euros. According to Statista.com, in 2020, Italy is expected to register a decrease of roughly 28.5 million tourist arrivals due to the impact of coronavirus (COVID-19) on the country's tourist sector. According to the estimate, the region of Veneto will record the highest drop with a decrease of roughly 4.61 million arrivals. Similarly, Lombardy is expected to register a decrease of about 3.87 million arrivals in 2020.

Keywords: travel and tourism, sustainability, COVID-19, businesses, transportation

Procedia PDF Downloads 162

Authors: Mary Moner Botros Fanawel

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Many companies use the statistical tool named as statistical quality control, and which can have a high cost for the companies interested on these statistical tools. The evaluation of the quality of products and services is an important topic, but the reduction of the cost of the implantation of the statistical quality control also has important benefits for the companies. For this reason, it is important to implement a economic design for the various steps included into the statistical quality control. In this paper, we describe some relevant aspects related to the economic design of a quality control chart for the proportion of defective items. They are very important because the suggested issues can reduce the cost of implementing a quality control chart for the proportion of defective items. Note that the main purpose of this chart is to evaluate and control the proportion of defective items of a production process.

Keywords: model predictive control, hierarchical control structure, genetic algorithm, water quality with DBPs objectives proportion, type I error, economic plan, distribution function bootstrap control limit, p-value method, out-of-control signals, p-value, quality characteristics

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Authors: Joana PaScoa Pinheiro, David Goncalves Ferreira, Filipe Ramos, Joaquim Soares Do Brito, Samuel Martins, Marco Sarmento

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Introduction: The SARS-CoV-2 (COVID-19) pandemic was identified in January 2020 in China, in the city of Wuhan. The increase in the number of cases over the following months was responsible for the restructuring of hospitals and departments in order to accommodate admissions related to COVID-19. Essential services, such as trauma, had to readapt to maintain their functionality and thus guarantee quick and safe access in case of an emergency. Objectives: This study describes the impact of COVID-19 on a Level III Trauma Center and particularly on the clinical management of hospitalized patients with spine injuries. Study Design & Methods: This is a retrospective cohort study whose results were obtained through the medical records of patients with spine injuries who underwent surgical intervention in the years 2019 and 2020 (period from March 1st to December 31st). A comparison between the two groups was made. In the study patients with injuries in the context of trauma were included who underwent surgery in the periods previously described. Patients hospitalized with a spine injury in a non-traumatic context and/or were not surgically treated were excluded. Results: In total, 137 patients underwent trauma spine surgery of which 71 in 2019 (51.8%) were without significant differences in intergroup comparisons. The most frequent injury mechanism in 2019 was motor vehicle crash (47.9%) compared to 2020 which was of a person falling from a height between 2-4 meters (37.9%). Cervical trauma was reported to be the most frequent spine injury in both years. There was a significant decrease in the need for intensive care in 2020, 51.4% vs 30.3%, p = .015 and the number of complications was also lower in 2020 (1.35% vs 0.98%), including the number of deaths, being the difference marginally significant. There were no significant differences regarding time for presentation to surgery or in the total days of hospitalization. Conclusions: The restructuring made in the trauma unit at a Level III Trauma Center in the context of the current COVID-19 pandemic was effective, with no significant differences between the years of 2019 vs 2020 when compared with the time for presentation to surgery or the number of days of hospitalization. It was also found that lockdown rules in 2020 were probably responsible for the decrease in the number of road traffic accidents, which justifies a significant decrease in the need for intensive care as well as in the number of complications in patients hospitalized in the context of spine trauma.

Keywords: trauma, spine, impact, covid-19

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Authors: Yunus Doğan, Ahmet Durap

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Coastal regions are the one of the most commonly used places by the natural balance and the growing population. In coastal engineering, the most valuable data is wave behaviors. The amount of this data becomes very big because of observations that take place for periods of hours, days and months. In this study, some statistical methods such as the wave spectrum analysis methods and the standard statistical methods have been used. The goal of this study is the discovery profiles of the different coast areas by using these statistical methods, and thus, obtaining an instance based data set from the big data to analysis by using data mining algorithms. In the experimental studies, the six sample data sets about the wave behaviors obtained by 20 minutes of observations from Mersin Bay in Turkey and converted to an instance based form, while different clustering techniques in data mining algorithms were used to discover similar coastal places. Moreover, this study discusses that this summarization approach can be used in other branches collecting big data such as medicine.

Keywords: clustering algorithms, coastal engineering, data mining, data summarization, statistical methods

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Authors: Nino Damenia

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E-commerce opens a new horizon for business development, which is why the presence of e-commerce is a necessary condition for the formation, growth, and development of the country's economy. Worldwide, e-commerce turnover is growing at a high rate every year, as the electronic environment provides great opportunities for product promotion. E-commerce in Georgia is developing at a fast pace, but it is still a relatively young direction in the country's economy. Movement restrictions and other public health measures caused by the COVID-19 pandemic have reduced economic activity in most economic sectors and countries, significantly affecting production, distribution, and consumption. The pandemic has accelerated digital transformation. Digital solutions enable people and businesses to continue part of their economic and social activities remotely. This has also led to the growth of e-commerce. According to the data of the National Statistics Service of Georgia, the share of online trade is higher in cities (27.4%) than in rural areas (9.1%). The COVID-19 pandemic has forced local businesses to expand their digital offerings. The size of the local market increased 3.2 times in 2020 to 138 million GEL. And in 2018-2020, the share of local e-commerce increased from 11% to 23%. In Georgia, the state is actively engaged in the promotion of activities based on information technologies. Many measures have been taken for this purpose, but compared to other countries, this process is slow in Georgia. The purpose of the study is to determine development prospects for the economy of Georgia based on the analysis of electronic commerce. Research was conducted around the issues using Georgian and foreign scientists' articles, works, reports of international organizations, collections of scientific conferences, and scientific electronic databases. The empirical base of the research is the data and annual reports of the National Statistical Service of Georgia, internet resources of world statistical materials, and others. While working on the article, a questionnaire was developed, based on which an electronic survey of certain types of respondents was conducted. The conducted research was related to determining how intensively Georgian citizens use online shopping, including which age category uses electronic commerce, for what purposes, and how satisfied they are. Various theoretical and methodological research tools, as well as analysis, synthesis, comparison, and other types of methods, are used to achieve the set goal in the research process. The research results and recommendations will contribute to the development of e-commerce in Georgia and economic growth based on it.

Keywords: e-commerce, information technology, pandemic, digital transformation

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Authors: El Asnaoui Khalid, Aksasse Brahim, Ouanan Mohammed

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In this paper, we are interested in the problem of finding similar images in a large database. For this purpose we propose a new algorithm based on a combination of the 2-D histogram intersection in the HSV space and statistical moments. The proposed histogram is based on a 3x3 window and not only on the intensity of the pixel. This approach can overcome the drawback of the conventional 1-D histogram which is ignoring the spatial distribution of pixels in the image, while the statistical moments are used to escape the effects of the discretisation of the color space which is intrinsic to the use of histograms. We compare the performance of our new algorithm to various methods of the state of the art and we show that it has several advantages. It is fast, consumes little memory and requires no learning. To validate our results, we apply this algorithm to search for similar images in different image databases.

Keywords: 2-D histogram, statistical moments, indexing, similarity distance, histograms intersection

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Authors: Sarah K. Basudan, Ragad I. Al Jazzar, Zeinah Sulaihim, Hanan M. Al-Kadri

Abstract:

Background: Cesarean section has been increasing in recent years, with a wide range of etiologies contributing to this rise. This study aimed to assess the indications, outcomes, and complications in Riyadh, Saudi Arabia. Methods: A Retrospective Cohort study was conducted at King Abdulaziz medical city. The study includes two cohorts: G1 (2009) and G2 (2020) groups who met the inclusion criteria. The data was transferred to the SPSS (statistical package for social sciences) version 24 for analysis. The initial descriptive statistics were run for all variables, including numerical and categorical data. The numerical data were reported as median, and standard deviation and categorical data were reported as frequencies and percentages. Results: The data were collected from 399 women who were divided into two groups, G1(199) and G2(200). The mean age of all participants is 32+-6​; G1 and G2 had significant differences in age means with 30+-6 and 34+-5, respectively, with a p-value of <0.001, which indicates delayed fertility by four years. Moreover, a breech presentation was less likely to occur in G2 (OR 0.64, CI: 0.21-0.62. P<0.001). Nonetheless, maternal causes such as repeated C-sections and maternal medical conditions were more likely to happen in G2 (OR 1.5, CI: 1.04-2.38, p=0.03) and (OR 5.4, CI: 1.12-23.9, P=0.01), respectively. Furthermore, postpartum hemorrhage showed an increase of 12% in G2 (OR 5.4, CI: 2.2-13.4, p<0.001). G2 was more likely to be admitted to the neonatal intensive care unit (NICU) (OR 16, CI: 7.4-38.7) and to special care baby (SCB) (OR 7.2, CI: 3.9-13.1), both with a p-value<0.001 compared to regular nursery admission. Conclusion: There are multiple factors that are contributing to the increase in c section rate in a Saudi tertiary hospitals. The factors were suggested to be previous c-sections, abnormal fetal heart rate, malpresentation, and maternal or fetal medical conditions.

Keywords: cesarean sections, maternal indications, maternal complications, neonatal condition

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Authors: D. Mokatsanyane, J. Jansen Van Rensburg

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This paper analyses the influence and impact of COVID-19 on major agricultural commodity prices in South Africa. According to a World Bank report, the agricultural sector in South Africa has been unable to reduce the domestic food crisis that has been occurring over the past years, hence the increased rate of poverty, which is currently at 55.5 percent as of April 2020. Despite the significance of this sector, empirical findings concluded that the agricultural sector now accounts for 1.88 percent of South Africa's gross domestic product (GDP). Suggesting that the agricultural sector's contribution to the economy has diminished. Despite the low contribution to GDP, this primary sector continues to play an essential role in the economy. Over the past years, multiple factors have contributed to the soaring commodities prices, namely, climate shocks, biofuel demand, demand and supply shocks, the exchange rate, speculation in commodity derivative markets, trade restrictions, and economic growth. The COVID-19 outbursts have currently disturbed the supply and demand of staple crops. To address the disruption, the government has exempted the agricultural sector from closure and restrictions on movement. The spread of COVID-19 has caused turmoil all around the world, but mostly in developing countries. According to Statistic South Africa, South Africa's economy decreased by seven percent in 2020. Consequently, this has arguably made the agricultural sector the most affected sector since slumped economic growth negatively impacts food security, trade, farm livelihood, and greenhouse gas emissions. South Africa is sensitive to the fruitfulness of global food chains. Restrictions in trade, reinforced sanitary control systems, and border controls have influenced food availability and prices internationally. The main objective of this study is to evaluate the behavior of agricultural commodity prices pre-and during-COVID to determine the impact of volatility drivers on these crops. Historical secondary data of spot prices for the top five major commodities, namely white maize, yellow maize, wheat, soybeans, and sunflower seeds, are analysed from 01 January 2017 to 1 September 2021. The timeframe was chosen to capture price fluctuations between pre-COVID-19 (01 January 2017 to 23 March 2020) and during-COVID-19 (24 March 2020 to 01 September 2021). The Generalised Autoregressive Conditional Heteroscedasticity (GARCH) statistical model will be used to measure the influence of price fluctuations. The results reveal that the commodity market has been experiencing volatility at different points. Extremely high volatility is represented during the first quarter of 2020. During this period, there was high uncertainty, and grain prices were very volatile. Despite the influence of COVID-19 on agricultural prices, the demand for these commodities is still existing and decent. During COVID-19, analysis indicates that prices were low and less volatile during the pandemic. The prices and returns of these commodities were low during COVID-19 because of the government's actions to respond to the virus's spread, which collapsed the market demand for food commodities.

Keywords: commodities market, commodity prices, generalised autoregressive conditional heteroscedasticity (GARCH), Price volatility, SAFEX

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Authors: Ali Akber Khan

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In the 21st century, freshwater resources, especially ice cover, would have grave significance as ice carries most of the total freshwater resources in the world. The Himalayas in Pakistan is one of the biggest sources of fresh water for Pakistan. These regions of the Himalayas and neighboring mountains include Swat, Chitral, Upper Dir, Lower Dir, Mardan, Swabi, Haripur, Abbottabad, Muzaffarabad, Neelum, and Mansehra in Pakistan. The study examines ice resources in the years 1990 to 2020 and shows a decrease in snow-shrouded regions, reducing from 72,187.54 sq. km in 1990 to 66,061.17 sq. km in 2020. This indicates a total ice cover loss of 6,126.37 sq. km area in 40 years due to environmental variabilities and climatic changes. From 2010 to 2020 loss of ice-covered area was 3479.24 sq. km. The mean maximum temperature from 2000 to 2010 in December, January and February is 7.4 °C, 4.2 °Cand 7.8 °C respectively, while from 2011 to 2022 mean maximum temperature registered in December, January and February is 6.9°C, 4.1°C and 6.6 °C respectively. Investigation of anthropogenic elements in the region shows population rise. From investigation, 22 cities and towns of the Himalayas region and neighboring mountains showed the highest rise in population, 329.46%, and a minimum rise of 14.39%, while 12 towns have risen in population by more than 100% from 1990 to 2023. This examination adds to a point-by-point comprehension of the connections among normal variables, population dynamics, snow cover variation, evidence strategies, and multipurpose measures for maintained and strong improvement in the districts.

Keywords: snow, ice, Himalayas, Pakistan, climate change, population

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Authors: Belaynesh Tsegay Beyene, Teklay Gebrecherkos, Atsebaha Gebrekidan Kahsay, Mahmud Abdulkader

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Background: Hepatitis B and C viruses are of important health and socioeconomic problem of the globe with remarkable diseases and deaths in Sub-Saharan African countries. The burden of hepatitis is unknown in the prison settings of Tigrai. Therefore, we aimed to describe the seroprevalence and associated factors of hepatitis B and C viruses among prisoners of Tigrai, Ethiopia. Methods: A cross-sectional study was carried out from February 2020 to May 2020 at the prison facilities of Tigrai. Demographics and associated factors were collected from 315 prisoners prospectively. Five milliliter of blood was collected and tested using rapid tests kits of HBsAg (Zhejiang orient Gene Biotech Co., Ltd., China) and HCV antibodies (Volkan Kozmetik Sanayi Ve Ticaret Ltd. STI, Turkey). Positive samples were confirmed using enzyme-linked immunosorbent assay (ELISA) (Beijing Wantai Biological Pharmacy Enterprise Co. Ltd). Data were analyzed using Statistical Package for Social Sciences (SPSS) version 20 and p < 0.05 was considered statistically significant. Results: The overall seroprevalence of HBV and HCV were 25 (7.9%) and 1(0.3%), respectively. The majority of hepatitis B viral infections were identified from the age groups of 18-25 years (10.7%) and unmarried prisoners (11.8%). Prisoners greater than 100 per cell [AOR =3.95, 95% CI= (1.15, 13.6, p =0.029)] and having history of alcohol consumption [AOR =3.01, 95% CI= (1.17, 7.74, p =0.022)] were significantly associated with HBV infections. Conclusions: The seroprevalence of HBV among prisoners was nearly high or borderline (7.9%) with a very low HCV prevalence (0.3%). HBV was most prevalent among young adults, large number of prisoners per cell and those who had history of alcohol consumption. This study recommends that there should be prison-focused intervention including regular health education by emphasis on the mode of transmission and introducing HBV screening policy for prisoners especially when they enter to the prison.

Keywords: seroprevalence, HBV, HCV, prisoners, Tigrai

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Authors: Weihao Wang, Zhulin Zong

Abstract:

Two-dimensional ordered statistical constant false alarm detection is a widely used method for detecting weak target signals in radar signal processing applications. The method is based on analyzing the statistical characteristics of the noise and clutter present in the radar signal and then using this information to set an appropriate detection threshold. In this approach, the reference cell of the unit to be detected is divided into several reference subunits. These subunits are used to estimate the noise level and adjust the detection threshold, with the aim of minimizing the false alarm rate. By using an ordered statistical approach, the method is able to effectively suppress the influence of clutter and noise, resulting in a low false alarm rate. The detection process involves a number of steps, including filtering the input radar signal to remove any noise or clutter, estimating the noise level based on the statistical characteristics of the reference subunits, and finally, setting the detection threshold based on the estimated noise level. One of the main advantages of two-dimensional ordered statistical constant false alarm detection is its ability to detect weak target signals in the presence of strong clutter and noise. This is achieved by carefully analyzing the statistical properties of the signal and using an ordered statistical approach to estimate the noise level and adjust the detection threshold. In conclusion, two-dimensional ordered statistical constant false alarm detection is a powerful technique for detecting weak target signals in radar signal processing applications. By dividing the reference cell into several subunits and using an ordered statistical approach to estimate the noise level and adjust the detection threshold, this method is able to effectively suppress the influence of clutter and noise and maintain a low false alarm rate.

Keywords: two-dimensional, ordered statistical, constant false alarm, detection, weak target signals

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Authors: Seyed Saeid Nabavi

Abstract:

Background: Many infants with intrauterine growth disorder are screened for TORCH infections. This action has no economic justification in terms of the imposed costs. In this regard, due to the research gap in this field, this study aimed to investigate the relationship between intrauterine growth disorder and TORCH infection in neonates referred to Milad hospital in 2019 and 2020. Materials and Methods: In this cross-sectional study, 41IUGR newborns were selected and evaluated based on diagnostic and clinical studies in Milad Hospital in 2019 and 2020. TORCH results found in IgG and IgM antibody titer assay were tested in mother and infant. Antibody titers of toxoplasmosis, rubella, cytomegalovirus, herpes, and syphilis were determined in cases, and other variables were compared. The collected data were entered in SPSS software 25 and analyzed at a significant level of 0.05 using the statistical tests of Kolmogorov–Smirnov, Shapiro–Wilk, chi-square, and Mann–Whitney. Results: Most of the IUGR infants studied were girls (68.3%), Gravida and Parity were reported to be 68.3% and 80%, respectively, in the study. Mean weight, APGAR score, and neonatal gestational age are reported as 1710.62±334.43 g, 7.71±1.47, and 35.7+ 1.98 weeks, respectively. Most of the newborns were born by cesarean section (92.7%). TORCH infection was reported in three patients, 7.3%. The mean gestational age of IUGR infants with TORCH infection was reported to be less than other babies with IUGR. Therefore, the mean gestational age of subjects with TORCH infection was 33±1.4 weeks and in others 35.94±1.91 weeks (p-value = 0.038). No significant relationship between TORCH infection and gender, gravidity, and parity of newborns was found (p-value > 0.05). Conclusion: TORCH infection was reported in 3 patients( 7.3%). No significant relationship between TORCH infection and gender, gravidity, and parity of newborns was found. p-value > 0.05

Keywords: congenital infection, intrauterine growth restriction, TORCH infections, neonates

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