Population Growth Research Articles

Effective Patient Engagement in Private Healthcare Institutions in Riyadh: An Analysis of Management Strategies

The healthcare sector in Saudi Arabia is undergoing a remarkable transformation driven by factors such as population growth and rising disposable income. This has led to a significant surge in demand for private healthcare services, particularly in major cities like Riyadh. While catering to the needs of a growing patient base, there is an urgent need to ensure patient-centered care to enhance service quality and satisfaction. Multiple research studies have affirmed the positive impact of patient engagement. Studies consistently demonstrate that patients actively involved in their healthcare decisions experience improved quality of life, better adherence to treatment, and reduced hospital readmission rates. This ultimately leads to improved health outcomes and reduced overall healthcare costs. Despite these well-established benefits, many private healthcare institutions in Riyadh struggle to effectively integrate patient engagement strategies into their practices. This implementation gap necessitates a deeper understanding of the factors influencing these efforts. This study aims to address this pressing need by investigating the factors affecting patient engagement initiatives within private healthcare institutions in Riyadh. The study will explore the influence of three key domains: Digital Technology: The increasing reliance on digital tools in healthcare holds the potential to revolutionize patient engagement. This study will explore how technology platforms, telemedicine applications, and patient portals can facilitate patient engagement. Organizational Leadership: Leadership plays a pivotal role in fostering a patient-centered care culture. This research will examine how leadership styles, commitment to patient engagement, and resource allocation impact patient engagement initiatives. Organizational Culture: The overall culture of a healthcare institution significantly influences patient interactions. This study will explore how factors such as communication practices, staff training, and patient empowerment within the organizational culture shape patient engagement. By examining these three domains, the study aims to provide valuable insights into the factors that influence patient engagement in private healthcare settings in Riyadh. The findings will contribute to the development of effective strategies for enhancing patient engagement and improving overall healthcare quality.

Assessing performance of Amblyseius swirskii as a predatory mite of Tetranychus urticae and Frankliniella occidentalis: life table and foraging behaviour studies

ABSTRACT Life table parameters of Amblyseius swirskii when Frankliniella occidentalis and Tetranychus urticae were offered solely as diet were investigated. The switching behaviour of this predator was studied on F. occidentalis in the presence of spider mites. The data showed that feeding on the spider mite resulted in significantly longer developmental time compared to thrips. We found a significant effect of prey on the total life span, adult pre-oviposition period (APOP), and total pre-oviposition period (TPOP) of the predatory mite. The length of the oviposition period and the number of laid eggs per female were not affected by the kind of the offered prey. None of population growth parameters was affected by the type of diet except for mean generation time (T). Predators fed on spider mite had a longer T than those reared on thrips. Furthermore, our data illustrated a negative switching in the behaviour of A. swirskii when T. urticae and F. occidentalis were present. In other words, the predator switched from the abundant prey to the rarer prey. The results of this study are needed to understand and forecast the performance of A. swirskii in greenhouse environments where both T. urticae and F. occidentalis can be present.

Central Tendency Data Real-Time Acid Rain Measurement to Evaluate Tool’s Performance Using Statistical Analysis

Increased population growth has implications for increased industrial and transportation activities. This activity increased gas emissions in the form of Sulfur Dioxide (SO2) and Nitrogen Dioxide (NO2), resulting in acid rain. The measuring instrument, a rain gauge, is used to measure acid rain in Greater Bandung at Telkom University, Indonesia, but it is currently unable to measure in real-time. Therefore, this study aims to measure acid rain in real-time by measuring parameters such as pH, temperature, conductivity, and precipitation to test the acidity contained in rainwater and evaluate the tool's performance with data for March 2022. The analysis uses various statistical methods: anomaly detection, outlier detection, central tendency, person correlation analysis, Mean Absolute Percentage Error, T-test, and Analysis of Variance (ANOVA). Each parameter can be worked out in real-time based on the central tendency and rain dispersion results. If there is only daily rain, then the correlation for each parameter is the highest, namely pH if there is acid rain. The real-time average pH is 6.45; in the laboratory, it is 6.56, so the MAPE value is 5.37 (good category). Even though this tool can work well, it needs to improve the quality of the temperature control in it. Since temperature significantly affects pH, the results show a negative correlation of -0.80 between pH and temperature. In the ANOVA test, the resulting p-value, when compared with data in the laboratory, is >0.05, meaning that the average daily pH does not have a significant difference from the average laboratory test.

CPM Analysis on Boarding House Construction Projects in Samarinda City

Population growth increases the need for practical and affordable housing, so boarding houses become the main choice. Boarding house construction projects need to be managed through good project management. This research discusses the use of the Critical Path Method (CPM) in the boarding house project on Jl. Mangkupalas Gg. Padai in Samarinda City. The CPM method is used to determine project duration and optimize costs, with information on work, costs and time for each stage. The results show the critical activity path A – B – C – E – F – G – H – I – K, reducing the project duration from 210 days to 173 days, 37 days faster. Using the CPM method saves IDR 19,050,000 from the initial project cost of IDR 298,939,000 to IDR 279,889,000. This research supports the CPM method for cost and time efficiency in development projects and the results of this research are in accordance with previous studies which also discusses the CPM method of project management.

Solar performance-driven urban development: the case of western Sydney, Australia

ABSTRACT Urban densification, a response to population growth, poses adverse impacts on built environments. Limited access to sunlight is one of these consequences. Solar radiation and daylight affect urban canyons in different ways, including thermal comfort and illuminance levels. A balance between summer and solar heat gain can alleviate solar thermal considerations. This becomes even more important in an urban context like Western Sydney with an air temperature of around 6 to 10 degrees hotter than Inner Sydney (during extreme heat events). Additionally, Western Sydney is predicted to absorb two-thirds of the population growth of the Sydney region. Nevertheless, the urban development trend in this region doesn’t seem to meet the requirements of an environmentally sustainable scheme covering solar geometry-based design principles. Therefore, this study aims to develop a general urban model based on the spatial analysis of the western Sydney suburbs and propose a novel integrated methodology to provide the optimal solar-based urban design solution. This process uses an evolutionary algorithm as a computational tool to optimize solar radiation and daylight levels in extreme weather conditions. Results offer the optimum value for a wide range of design parameters regarding solar geometry.

Changes in urban green space configuration and connectivity using spatial graph-based metrics in Ardabil developing city, Iran.

Urban planning is essential for managing the diverse impacts of urban green spaces, such as public access, stormwater control, urban life quality, and landscape aesthetics, promoting sustainable urban development and urban residents' well-being by integrating green space considerations into city planning. The aim of this study is to use graph-based metrics to calculate the connectivity of UGS across the main municipal zones of Ardabil city over consecutive periods under different population growth rates. Another objective of this study is to compare the connectivity values of UGS in the four municipal zones and to evaluate changes in the connectivity indices at various distance thresholds of UGS patches. After identifying UGS in different periods, the changes in graph-based connectivity indices at various distance thresholds of UGS patches were analyzed. Additionally, the changes in connectivity indices over different periods and across various municipal zones were compared and analyzed. The findings reveal that UGS areas were larger in the past but have recently had smaller patch sizes. Connectivity between UGS nodes (dNL) decreased at various distances over the study years, showing a declining trend in different connectivity indices. UGS connectivity decreased in municipal zones 1, 2, and 3 but increased in recent years after a decline until 2012 across all four zones of Ardabil city. Zone 4 had the highest UGS connectivity due to newly developed urban areas and well-allocated UGSs. Integrating the ecological impacts of UGS connectivity in urban development and design will enhance trade-offs between conservation, public health, and social equity. New urban areas should allocate sufficient land for UGS and parks, ensuring accessibility to support health and leisure through municipal planning. The study highlights the need for sustainable urban development policies that prioritize the allocation and maintenance of UGSs.

Exploring the user experience, quality, and provision of urban greenspace: A mixed-method approach

Urban greenspace plays a crucial role in city design, offering residents various benefits for their health and wellbeing. With increasing urbanisation and human population growth, urban greenspace is becoming an even more significant resource. By implementing a mixed-method approach, we conducted a comprehensive assessment of urban greenspace based on public usage and perceptions, and quality, availability and accessibility in Derby, UK. Our methodology included an online questionnaire to investigate greenspace usage and perceptions, an in-situ assessment to assess greenspace quality, and Geographical Information Systems analysis to quantify greenspace provision based on Natural England’s (2023) Accessible Greenspace Standards (AGS). We found that greenspace usage and perception vary according to demographic and socioeconomic aspects, with younger people and students showing lower engagement with greenspace. Positive engagement correlates with factors such as proximity, car access, employment, and education. We also found that moderately high levels of greenspace quality (69.47/100) are available in the city, with the most notable insufficiencies related to quietness/peacefulness, aesthetics, and naturalness. Finally, none of the AGS criteria are met at a city-wide scale given the lack of large greenspace sites (particularly over 100 ha) and inequalities in spatial distribution. Our study highlights the value of the use of different methodologies to assess greenspace-related factors and emphasises the significance of public engagement in evaluating greenspace quality. Additionally, we identified factors adversely affecting greenspace use, including parking fees and issues with facilities, amenities, and safety. We therefore recommend interventions to address these challenges and enhance greenspace experience and accessibility in the city.

Developing a machine learning prediction model for honey production

Türkiye, with its rich flora diversity, holds a significant share in global honey production. However, honey bee populations, essential for agricultural ecosystems, face multifaceted threats such as climate change, habitat degradation, diseases, parasites, and exposure to pesticides. Alongside the increasing global food demand driven by population growth, there is a pressing need for a substantial increase in honey production. In this context, advances in machine learning algorithms offer tools to predict future food needs and production levels. The objective of this work is to develop a predictive model using machine learning techniques to predict Türkiye's honey output in the next years. To achieve this goal, a range of machine learning algorithms including K-Nearest Neighbor, Random Forest, Linear Regression, and Gaussian Naive Bayes were employed. Following investigations, Linear Regression emerged as the most effective method for predicting honey production levels (R2= 0.97).

Tracking China's methane emissions from wastewater: Inventories, driving forces, and mitigation potential

China's rapid urbanization and burgeoning economy drove significant growth in sewage discharge, necessitating an examination of factors influencing wastewater methane emissions and mitigation measures. This study presented a comprehensive inventory of methane emissions in 31 provinces of China over a significant period. We developed a logarithmic mean divisor index (LMDI) model to reveal the driving forces behind emission changes. Methane emissions surged from approximately 1.4 Tg in 2000 to about 2.7 Tg in 2020, with treated domestic sewage being the fastest-growing source (49 Gg to 810 Gg). In 2020, the eastern, central, and southern regions contributed 61.7 % to total emissions. The increase in emissions was primarily driven by economic output, urbanization and population growth. This study forecasted future emission reduction potential, highlighting that reducing emission intensity (52.7 %) offered the most significant mitigation opportunities, followed by enhancing methane recovery (35.2 %). We recommended strengthening sewage discharge supervision and promoting biogas production.

Development of a Risk Breakdown Structure in Mega Projects based on Different Case Studies

Rapid urbanization, globalization, and population growth have led to an increase in megaprojects in recent decades. Consequently, as construction projects move forward, a wider range of risks arise. By looking into and managing risk factors in advance of their occurrence, it is vital to reduce their negative effects. In construction projects, risk management is seen as a critical procedure that helps meet project objectives in relation to schedule, budget, quality, safety, and sustainability concerns. This study aims to examine and gain a deeper understanding of project-related risks in mega projects. This study also develops a risk breakdown structure in mega projects based on a literature review. This will help project participants manage these risks in their projects properly. Another objective of this study is to examine the methodologies used in data collection for determining and categorizing risks in mega projects. Finally, it is concluded that the risk factors in mega projects can be divided into two categories: internal and external risks whereas the main risk factors in mega projects are categorized as execution, construction, technical, economic and financial, environmental, social, political, and other.

Observed declines in body size have differential effects on survival and recruitment, but no effect on population growth in tropical birds.

Declines in body size can be an advantageous physiological response to warming temperatures, or a result of physiological and nutritional stress. Either way, studies often assume that these climate-induced trait changes have important implications for fitness and demography. We leveraged almost three decades of capture-mark-recapture data of 51 bird species in Panama to examine if body size has changed through time, how sensitive body size is to changes in weather, and if body size impacts population demography. We evaluated two metrics of body size, structural size (wing length), and body condition (residual body mass). Over the study, wing length changed in varying directions for 88% of species (23 decrease, 22 increase), but the effects were weak, and change was only significant for two species. Conversely, body condition declined for 88% of species (45), effects were stronger, and that change was significant for 22% of species (11). This suggests that nutritional stress is likely the cause of changes in body size, not an adaptive response to warming. Precipitation metrics impacted body condition across three of our four feeding guilds, while wing length was only impacted by weather metrics for two guilds. This suggests that body condition is more sensitive to change in weather metrics compared to wing length. Lastly, we found that the impact of changes in body size on survival and recruitment was variable across species, but these relationships were in the opposite direction, ultimately resulting in no change in population growth for all but one species. Thus, while different stages (adult survival and recruitment) of populations may be impacted by body size, populations appear to be buffered from changes. The lack of an effect on population growth rate suggests that populations may be more resilient to changes in body size, with implications for population persistence under expected climate change.

Climate change and food security causality in ECOWAS region: Do countries interdependence matter?

Studies abound on the causal relationship between climate change and food security; however, the ECOWAS sub-region, despite its unique climatic, agricultural, and socioeconomic characteristics, remains insufficiently explored. Utilizing data from 14 ECOWAS countries spanning 1986 to 2022, this study departs from earlier studies by incorporating the Dumitrescu–Hurlin Panel Causality test, the Pooled Mean Group (PMG), Common Correlated Effect Mean Group (CCEMG), Augmented Mean Group (AMG) and the Cross-Sectional Augmented Autoregressive Distributed Lag (CS-ARDL) technique to analyze the complex relationship between climate change and food security in the ECOWAS sub-region. Unlike the prior empirical studies, the findings reveal a robust mutual influence of climate change and food security in the ECOWAS sub-region. Furthermore, the findings reported a positive impact of climate change on food security, aided by increased cropland area and population growth. At the same time, drought incidence and erratic rainfall between July and September annually remained a severe concern in the region. However, while the conversion of forests and natural habitats into cropland in the sub-region can lead to heightened carbon emissions and reduced ecosystem services, policy recommendations advocate the need for ECOWAS sub-regional policymakers to carefully balance the benefits of food security through sustainable practices and environmental considerations to ensure long-term food security benefits.

Application of the ARIMA model in house price index in Malaysia

The factors that affecting the escalating price of houses in Malaysia are driven by factors such as population growth, income dynamics, interest rates, and GDP. This phenomenon has notably outpaced the growth of household incomes, thus majorly impacting Malaysians. The study’s primary goal is to forecast the housing price index in Malaysia from the best model obtained using Box-Jenkins method. aligning with the 2018-2025 National Housing Policy objectives, utilizing advanced machine learning and time series modeling. The objectives guide the research: to find the best model for predicting house price index in Malaysia using Box-Jenkins Method. Utilizing secondary data from the National Property Information Centre (NAPIC) spanning from 1988 to 2023, the study employed the analytical method of ARIMA. The results favored the ARIMA (1,1,1) model as the best model in predicting housing price indexes. This offers an excellent forecasting model for residential properties towards gaining better understanding of their pricing dynamics and offers potential solutions to the issue of housing affordability for Malaysians.

Landscape Design of ”Tjikoepa Inn” Agrotourism in Sukanagara District, Cianjur Regency

Abstract The population growth rate of Cianjur Regency, Indonesia, continues to increase with an annual growth rate of 1.26%. This population growth has consequences to the need of land requirement for settlements, so that the conversion of agricultural land is inevitable. To reduce the rate of the conversion, it can be pursued through the utilization of less productive land into multifunctional productive land, for example by building agro-tourism. One of the lands that has not been optimally utilized is a 3 hectare agricultural land owned by Tjikoepa Inn in Sukanagara, Cianjur Regency. The purpose of this research is to design the less productive of agricultural land into an agrotourism landscape that can meet the lodging and tourism needs of Cianjur Regency. The method used in this research is the description method through an approach of program-based landscape design. Agricultural activities and commodities are determined by the land owner. The design concept adopted is modern integrated agricultural tourism by considering low external input and sustainable agriculture (LEISA) that can maximize the potential of integrated farming that is educative and provides a more inspiring and fun experience for visitors ranging from children to adults. The space formed includes service area, culinary tourism area, agricultural tourism area (horticulture, plantations, livestock, and fisheries), outbound area, glamping area, conservation area, and place of view point. Visitors are pampered with all their senses along the way starting from the parking lot upto the highest level at the place of view point.

Design framework to renewal abandoned areas in historic districts

ABSTRACT Urbanization and population growth have profoundly impacted the environment of historic and cultural blocks, resulting in a lack of public buildings and spaces for internal adjustment, fostering pronounced homogeneity. This study focuses on completely abandoned areas within historical streets, integrating space syntax analysis with semantic analysis to explore reshaping regional public buildings. Unlike previous studies centered around restoring old objects, the abandoned disconnected areas require a novel regional public architecture design framework through the semantic transformation of archival photographs, historical plans, and local culture. Taking Huishan Ancient Town in Wuxi as a case study, this research comprehends the abandoned disconnection area through a literature review and examination of archival data. By using spatial syntax analysis to combine the overall pedestrian flow space with the depth of ancient historical plans, entrances are set according to the pedestrian flow, preserving unique spatial characteristics and transforming the abandoned land into new public building spaces with distinct regional and contiguous features. Through semantic translation rooted in local culture, classical elements were extracted from intangible cultural heritage and applied to the ancient town’s architectural facades, navigation systems, and structures, thereby mitigating homogenization tendencies in both spatial and cultural elements.

Solution analysis of Solow Growth Model for financial practices and applications

Solow Growth Model (SGM) is an economic model that is exogenous in nature and examines the relationship between the output and input levels in an economy over a period of time. It projects long-term economic growth in relation to labour (population growth), savings rate, and technological development. However, traditional approaches to solving the Solow growth model may rely on complex mathematical techniques that might not give an accurate representation of real-world economic dynamics. Thus, this paper applies the Natural Decomposition Method (NDM) to the Solow growth financial model. The NDM is a numerical technique that combines the Natural Transform (NT) and the ADM-Adomian decomposition method. The NDM simplifies problem-solving by converting the original differential equations into algebraic equations as regards limitations associated with nonlinear models. From the results obtained by applying the NDM to the Solow growth financial model, researchers and policymakers can better understand the interplay between financial variables, such as savings rates, investment, and capital allocation, and their impact on economic growth dynamics, as a systematic approach to capturing the complex relationship between finance and economic development within the Solow framework is ensured. Further research and application of the NDM can contribute to advancing the knowledge of economic dynamics and support evidence-based decision-making in economic policy.

Research on the Factors Contributing to Low Fertility in South Korea

In 2023, South Korea had a fertility rate of 0.8831, the lowest in the world. Compared to most other east Asian countries, Korea recovered from the Second World War relatively earlier and is home to some of the most influential companies in the world today. Therefore, while other east Asian countries are in the industrial stage characterized by moderate to high rates of population growth, Korea is already a post-industrial society, marked by low population growth. This paper aims to identify the contributing factors to South Koreas low fertility rate by examining previous surveys completed by Koreans, interviews done with Koreans, and statistics about the Korean economy and society. These surveys, interviews, and statistics show the current economic, social, and cultural characteristics of the country and the flaws in them that lead to low fertility rate. The first significant factor related to the low fertility rate in South Korea is the high economic uncertainty due to rising living costs. Many Koreans struggle to achieve financial independence and move out of their parents homes, which is a barrier to starting a family. The second factor is the rising number of women obtaining higher levels of education and subsequently entering the workforce. The last factor is the practice of neo-Confucianism beliefs that are patriarchal in nature. Therefore, the proposed solution is that the Korean government should focus on changing current social and cultural beliefs to minimize the conflict between family and work for Korean women.

Evaluasi Kebijakan Pengelolaan Sampah di Desa Bandar Khalipah

Until now, waste management is still a major problem, almost every region experiences this problem. Along with population growth and community activity levels. The research method used is qualitative research with several interview techniques. From the results of observations that have been carried out directly in the field by researchers and the results of interviews with the Village Head and several residents of Bandar Khalipah village, information can be produced that in Bandar Khalipah Village, Percut Sei Tuan District, Deli Serdang Regency, North Sumatra, even though the village government has tried to implement the policy the public to encourage citizens to care about the environment by managing waste properly and correctly is still not implemented well. The public policy implemented by the village government in providing waste management infrastructure in Bandar Khalipah Village was attempted several years ago but has not been implemented well due to several existing factors. The unavailability of TPA (Final Disposal Site) is one of the triggers for many village communities continuing to throw rubbish carelessly, such as in rivers, roadsides near ditches and on empty, uninhabited land.

Finding Common Ground a comparison between coastal nature-based solutions in the Netherlands and British Columbia, Canada

Many coastal communities worldwide are facing challenges caused by increasing sea levels. However, urban development, population growth and industrialisation in low-lying delta regions persists. This includes the Netherlands and British Columbia, Canada. Both regions explore new and innovative flood risk and adaptation strategies by initiating nature-based solutions (NBS) pilot projects and integrating research and community initiatives. The aim of this paper is to learn from the experiences with these NBS pilots and support practitioners with insights and knowledge about the prospectives and implementation process of NBS. Our study takes a bird's eye view by diving into four NBS case study projects that try to enhance flood defence and quality of life while considering ecosystems and community values simultaneously. To better understand current initiatives on NBS, we first describe the historical trajectories of flood risk management and climate adaptation policy in both countries. Then we analyse two urban and two suburban case studies to identify and compare enablers and barriers that surround the implementation of NBS. We use the Pilot Paradox as a framework to reflect on the enablers and barriers, and to formulate recommendations for barriers that are common ground. We found that upscaling of the pilots forms an important challenge in both countries. We also found that Canada is interested in exchanging technical knowledge, experiences, and insights with other countries through the involvement of international researchers, consultants, and students in projects. Such collaboration between countries, communities, practitioners, and academics could accelerate the development of innovative climate adaptation strategies worldwide.

Assessment of Chinese urban land-use efficiency (SDG11.3.1) utilizing high-precision urban built-up area data

Assessment of SDG11.3.1 indicator of the United Nations Sustainable Development Goals (SDGs) is a valuable tool for policymakers in urban planning. This study aims to enhance the accuracy of the SDG11.3.1 evaluation and explore the impact of varying precision levels in urban built-up area on the indicator's assessment outcomes. We developed an algorithm to generate accurate urban built-up area data products based on China's Geographical Condition Monitoring data with a 2 m resolution. The study evaluates urban land-use efficiency in China from 2015 to 2020 across different geographical units using both the research product and data derived from other studies utilizing medium and low-resolution imagery. The results indicate: (1) A significant improvement in the accuracy of our urban built-up area data, with the SDG11.3.1 evaluation results demonstrating a more precise reflection of spatiotemporal characteristics. The indicator shows a positive correlation with the accuracy level of the built-up area data; (2) From 2015 to 2020, Chinese prefecture-level cities have undergone faster urbanization in terms of land expansion relative to population growth, leading to less optimal land resource utilization. Only in extra-large cities does urban population growth show a relatively balanced pattern. However, urban population growth in other regions and cities of various sizes lags behind land urbanization. Notably, Northeast China and small to medium cities encounter significant challenges in urban population growth. Our comprehensive framework for evaluating SDG11.3.1 with high-precision urban built-up area data can be adapted to different national regions, yielding more accurate SDG11.3.1 outcomes. Our urban area and built-up area data products provide crucial inputs for calculating at least four indicators related to SDG11.