Regression Models Analysis in Predicting the Impact of Population Growth on Flood Intensity in Jakarta

Purpose This paper aims to document the impact of Ramadan on the optimism of analysts’ recommendations taking as a sample the countries of the MENA region during the period between 2004 and 2015. The choice of these countries can be explained by the fact that their population is predominantly of a Muslim faith (The Future of World Religions: Population Growth Projections, 2010-2050, 2015). Design/methodology/approach The authors used univariate and multivariate regression models to highlight the existence of the Ramadan effect on the optimism of analysts. They have found that pre-holiday optimism is significantly lower than post-holiday optimism. Findings This paper also documented the effect of analysts’ experience and information uncertainty on the analysts’ optimism level that allowed us to infer that low experience enhances optimism, while environment with low information uncertainty tends to decrease the level of optimism. Originality/value Previous research on this topic has investigated the effect of months of the year, turns of the month and days-of-the-week on the behavior of stock exchanges. Another strand of the literature also analyzed the effect of holidays on the latter. However, this is the first attempt to investigate this effect on analysts’ recommendations optimism when the holiday period is related to Islam.

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The Impact Of Population Growth On Health And Educational Services Distribution In Al-Salt City (1994 - 2015)

10.33976/1442-027-003-017 ◽

2019 ◽

pp. 15

Author(s):

Mohammad Weshah ◽

Mousa A. Samha

Keyword(s):

Population Growth ◽

Educational Services ◽

The Impact

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FAKTOR DETERMINAN PENYALURAN KREDIT BANK PERSERO

Journal of Business Economics ◽

10.35760/eb.2018.v23i1.1812 ◽

2018 ◽

Vol 23 (1) ◽

pp. 60-71

Author(s):

Wigiyanti Masodah

Keyword(s):

Interest Rate ◽

Linear Regression ◽

Interest Rates ◽

Regression Models ◽

Linear Regression Models ◽

Negative Impacts ◽

Main Activity ◽

The Impact ◽

The Given ◽

Multiple Linear Regression Models

Offering credit is the main activity of a Bank. There are some considerations when a bank offers credit, that includes Interest Rates, Inflation, and NPL. This study aims to find out the impact of Variable Interest Rates, Inflation variables and NPL variables on credit disbursed. The object in this study is state-owned banks. The method of analysis in this study uses multiple linear regression models. The results of the study have shown that Interest Rates and NPL gave some negative impacts on the given credit. Meanwhile, Inflation variable does not have a significant effect on credit given. Keywords: Interest Rate, Inflation, NPL, offered Credit.

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The impact of SPY angiography on intraoperative decision making and outcomes for post-mastectomy reconstruction

Journal of Cancer Science and Therapeutics ◽

10.36879/jcst.19.000109 ◽

2019 ◽

pp. 1-5

Keyword(s):

Decision Making ◽

Logistic Regression ◽

Skin Necrosis ◽

Regression Models ◽

Multivariable Analysis ◽

P Value ◽

Flap Necrosis ◽

Single Institution ◽

Logistic Regression Models ◽

The Impact

Objective: While the use of intraoperative laser angiography (SPY) is increasing in mastectomy patients, its impact in the operating room to change the type of reconstruction performed has not been well described. The purpose of this study is to investigate whether SPY angiography influences post-mastectomy reconstruction decisions and outcomes. Methods and materials: A retrospective analysis of mastectomy patients with reconstruction at a single institution was performed from 2015-2017.All patients underwent intraoperative SPY after mastectomy but prior to reconstruction. SPY results were defined as ‘good’, ‘questionable’, ‘bad’, or ‘had skin excised’. Complications within 60 days of surgery were compared between those whose SPY results did not change the type of reconstruction done versus those who did. Preoperative and intraoperative variables were entered into multivariable logistic regression models if significant at the univariate level. A p-value <0.05 was considered significant. Results: 267 mastectomies were identified, 42 underwent a change in the type of planned reconstruction due to intraoperative SPY results. Of the 42 breasts that underwent a change in reconstruction, 6 had a ‘good’ SPY result, 10 ‘questionable’, 25 ‘bad’, and 2 ‘had areas excised’ (p<0.01). After multivariable analysis, predictors of skin necrosis included patients with ‘questionable’ SPY results (p<0.01, OR: 8.1, 95%CI: 2.06 – 32.2) and smokers (p<0.01, OR:5.7, 95%CI: 1.5 – 21.2). Predictors of any complication included a change in reconstruction (p<0.05, OR:4.5, 95%CI: 1.4-14.9) and ‘questionable’ SPY result (p<0.01, OR: 4.4, 95%CI: 1.6-14.9). Conclusion: SPY angiography results strongly influence intraoperative surgical decisions regarding the type of reconstruction performed. Patients most at risk for flap necrosis and complication post-mastectomy are those with questionable SPY results.

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Impact of Preharvest and Postharvest on Color Changes during Convective Drying of Mangoes

Foods ◽

10.3390/foods10030490 ◽

2021 ◽

Vol 10 (3) ◽

pp. 490

Author(s):

Alioune Diop ◽

Jean–Michel Méot ◽

Mathieu Léchaudel ◽

Frédéric Chiroleu ◽

Nafissatou Diop Ndiaye ◽

...

Keyword(s):

Regression Models ◽

Convective Drying ◽

Color Changes ◽

Ripening Time ◽

Physico Chemical ◽

C 30 ◽

The Impact

The purpose of this study was to evaluate the impact of the harvest stage, ripening conditions and maturity on color changes of cv. ‘Cogshall’ and cv. ‘Kent’ variety mangoes during drying. A total of four harvests were undertaken, and the fruits were ripened at 20 and 35 °C for five different ripening times at each temperature. At each ripening time, mangoes were dried at 60 °C/30% RH/1.5 m/s for 5 h. A wide physico-chemical and color variability of fresh and dry pulp was created. The relationships according to the L*, H* and C* coordinates were established using mixed covariance regression models in relation to the above pre- and postharvest (preprocess) parameters. According to the L* coordinate results, browning during drying was not affected by the preprocess parameters. However, dried slices from mangoes ripened at 35 °C exhibited better retention of the initial chroma, and had a greater decrease in hue than dried slices from mangoes ripened at 20 °C. However, fresh mango color, successfully managed by the pre- and postharvest conditions, had more impact on dried mango color than the studied parameters. The preprocess parameters were effective levers for improving fresh mango color, and consequently dried mango color.

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The Impact of Weather and Seasons on Falls and Physical Activity among Older Adults with Glaucoma: A Longitudinal Prospective Cohort Study

Sensors ◽

10.3390/s21103415 ◽

2021 ◽

Vol 21 (10) ◽

pp. 3415

Author(s):

Hursuong Vongsachang ◽

Aleksandra Mihailovic ◽

Jian-Yu E ◽

David S. Friedman ◽

Sheila K. West ◽

...

Keyword(s):

Physical Activity ◽

Older Adults ◽

Fall Prevention ◽

Regression Models ◽

Activity Promotion ◽

Injurious Fall ◽

Multivariable Regression ◽

Multivariable Regression Models ◽

The Impact ◽

The Relationship

Understanding periods of the year associated with higher risk for falling and less physical activity may guide fall prevention and activity promotion for older adults. We examined the relationship between weather and seasons on falls and physical activity in a three-year cohort of older adults with glaucoma. Participants recorded falls information via monthly calendars and participated in four one-week accelerometer trials (baseline and per study year). Across 240 participants, there were 406 falls recorded over 7569 person-months, of which 163 were injurious (40%). In separate multivariable regression models incorporating generalized estimating equations, temperature, precipitation, and seasons were not significantly associated with the odds of falling, average daily steps, or average daily active minutes. However, every 10 °C increase in average daily temperature was associated with 24% higher odds of a fall being injurious, as opposed to non-injurious (p = 0.04). The odds of an injurious fall occurring outdoors, as opposed to indoors, were greater with higher average temperatures (OR per 10 °C = 1.46, p = 0.03) and with the summer season (OR = 2.69 vs. winter, p = 0.03). Falls and physical activity should be understood as year-round issues for older adults, although the likelihood of injury and the location of fall-related injuries may change with warmer season and temperatures.

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Non-Parametric Generalized Additive Models as a Tool for Evaluating Policy Interventions

Mathematics ◽

10.3390/math9040299 ◽

2021 ◽

Vol 9 (4) ◽

pp. 299

Author(s):

Jaime Pinilla ◽

Miguel Negrín

Keyword(s):

Linear Regression ◽

Regression Models ◽

Linear Trend ◽

Generalized Additive Models ◽

Additive Models ◽

Linear Regression Models ◽

Non Linear ◽

Nonlinear Trends ◽

The Impact ◽

Non Parametric

The interrupted time series analysis is a quasi-experimental design used to evaluate the effectiveness of an intervention. Segmented linear regression models have been the most used models to carry out this analysis. However, they assume a linear trend that may not be appropriate in many situations. In this paper, we show how generalized additive models (GAMs), a non-parametric regression-based method, can be useful to accommodate nonlinear trends. An analysis with simulated data is carried out to assess the performance of both models. Data were simulated from linear and non-linear (quadratic and cubic) functions. The results of this analysis show how GAMs improve on segmented linear regression models when the trend is non-linear, but they also show a good performance when the trend is linear. A real-life application where the impact of the 2012 Spanish cost-sharing reforms on pharmaceutical prescription is also analyzed. Seasonality and an indicator variable for the stockpiling effect are included as explanatory variables. The segmented linear regression model shows good fit of the data. However, the GAM concludes that the hypothesis of linear trend is rejected. The estimated level shift is similar for both models but the cumulative absolute effect on the number of prescriptions is lower in GAM.

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Changes in ecosystem service values strongly influenced by human activities in contrasting agro-ecological environments

Ecological Processes ◽

10.1186/s13717-021-00325-1 ◽

2021 ◽

Vol 10 (1) ◽

Author(s):

Mulatu Liyew Berihun ◽

Atsushi Tsunekawa ◽

Nigussie Haregeweyn ◽

Mitsuru Tsubo ◽

Ayele Almaw Fenta

Keyword(s):

Population Growth ◽

Ecosystem Service ◽

Cultivated Land ◽

Nile Basin ◽

Grazing Land ◽

Blue Nile ◽

Lulc Changes ◽

Blue Nile Basin ◽

The Impact ◽

Upper Blue Nile Basin

Abstract Background Evaluating the impacts of land-use/land-cover (LULC) changes on ecosystem service values (ESVs) is essential for sustainable use and management of ecosystems. In this study, we evaluated the impact of human activity driven LULC changes on ESVs over the period 1982–2016/17 in contrasting agro-ecological environments: Guder (highland), Aba Gerima (midland), and Debatie (lowland) watersheds of the Upper Blue Nile basin, Ethiopia. Results During the study period, the continuous expansion of cultivated land at the expense of natural vegetation (bushland, forest, and grazing land) severely reduced the total ESV by about US$ 58 thousand (35%) in Aba Gerima and US$ 31 thousand (29%) in Debatie watersheds. In contrast, the unprecedented expansion of plantations, mainly through the planting of Acacia decurrens, led, from 2006, to a ESV rebound by about US$ 71 thousand (54%) in Guder watershed, after it had decreased by about US$ 61 thousand (32%) between 1982 and 2006. The reduction in natural forest area was the major contributor to the loss of total ESV in the study watersheds, ranging from US$ 31 thousand (63%) in Debatie to US$ 96.9 thousand (70%) in Guder between 1982 and 2016/17. On an area-specific basis, LULC changes reduced the average ESV from US$ 560 ha−1 year−1 (1982) in Guder to US$ 306 ha−1 year−1 (2017) in Debatie watersheds. Specific ESVs such as provisioning (mainly as food production) and regulating services (mainly as erosion control and climate regulation) accounted for most of the total ESVs estimated for the study watersheds. Conclusions In most cases, the total and specific ESVs of the watersheds were negatively associated with the population growth, which in turn was positively associated with the expansion of cultivated land over the study period. In Guder, however, ESVs were positively associated with population growth, especially after 2012. This is mainly due to the expansion of Acacia decurrens plantations. Our results suggest, therefore, that future policy measures and directions should focus on improving vegetation cover through planting multipurpose trees such as Acacia decurrens to prevent future loss of ESV in the midland and lowland regions of the Upper Blue Nile basin and beyond. However, caution must be taken during plantation of invasive species as they may have undesirable consequences.

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Indicators of Land, Water, Energy and Food (LWEF) Nexus Resource Drivers: A Perspective on Environmental Degradation in the Gidabo Watershed, Southern Ethiopia

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18105181 ◽

2021 ◽

Vol 18 (10) ◽

pp. 5181

Author(s):

Zinabu Wolde ◽

Wu Wei ◽

Haile Ketema ◽

Eshetu Yirsaw ◽

Habtamu Temesegn

Keyword(s):

Population Growth ◽

Path Analysis ◽

Driving Factors ◽

Consumption Patterns ◽

Southern Ethiopia ◽

Driving Factor ◽

Path Coefficients ◽

Resource Degradation ◽

The Impact ◽

Land Water

In Ethiopia, land, water, energy and food (LWEF) nexus resources are under pressure due to population growth, urbanization and unplanned consumption. The effect of this pressure has been a widely discussed topic in nexus resource literature. The evidence shows the predominantly negative impact of this; however, the impact of these factors is less explored from a local scale. As a result, securing nexus resources is becoming a serious challenge for the country. This necessitates the identification of the driving factors for the sustainable utilization of scarce LWEF nexus resources. Our study provides a systemic look at the driving factor indicators that induce nexus resource degradation. We use the Analytical Hierarchical Process (AHP) to develop the indicators’ weights, and use a Path Analysis Model (PAM) to quantitatively estimate the effect of the driving factor indicators on the LWEF nexus resources. The results indicate that social (48%), economic (19%), and policy and institutional changes (14%) are the major nexus resource driving factor indicators. The path analysis results indicate that among the social driving factor indicators, population growth and consumption patterns have a significant direct effect on the LWEF nexus, with path coefficients of 0.15 and 0.089, respectively. Similarly, the potential of LWEF nexus resources is also influenced by the institutional and policy change drivers, such as outdated legislation and poor institutional structure, with path coefficients of 0.46 and 0.39, respectively. This implies that population growth and consumption patterns are the leading social drivers, while outdated legislation and poor institutional structures are the institutional and policies change drivers which have a potential impact on LWEF nexus resource degradation. Similarly, other driving factors such as environmental, economic and technological factors also affect nexus resources to varying degrees. The findings of our study show the benefits of managing the identified driving factors for the protection of LWEF nexus resources, which have close links with human health and the environment. In order to alleviate the adverse effects of driving factors, all stakeholders need to show permanent individual and collective commitment. Furthermore, we underline the necessity of applying LWEF nexus approaches to the management of these drivers, and to optimize the environmental and social outcomes.

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Assessing the Energy Resilience of Office Buildings: Development and Testing of a Simplified Metric for Real Estate Stakeholders

Buildings ◽

10.3390/buildings11030096 ◽

2021 ◽

Vol 11 (3) ◽

pp. 96

Author(s):

Paul Mathew ◽

Lino Sanchez ◽

Sang Hoon Lee ◽

Travis Walter

Keyword(s):

Regression Models ◽

Health And Safety ◽

Office Buildings ◽

Extreme Weather Events ◽

Economic Losses ◽

Power Outage ◽

Continuity Of Operations ◽

Quasi Monte Carlo ◽

Building Characteristics ◽

The Impact

Increasing concern over higher frequency extreme weather events is driving a push towards a more resilient built environment. In recent years there has been growing interest in understanding how to evaluate, measure, and improve building energy resilience, i.e., the ability of a building to provide energy-related services in the event of a local or regional power outage. In addition to human health and safety, many stakeholders are keenly interested in the ability of a building to allow continuity of operations and minimize business disruption. Office buildings are subject to significant economic losses when building operations are disrupted due to a power outage. We propose “occupant hours lost” (OHL) as a means to measure the business productivity lost as the result of a power outage in office buildings. OHL is determined based on indoor conditions in each space for each hour during a power outage, and then aggregated spatially and temporally to determine the whole building OHL. We used quasi-Monte Carlo parametric energy simulations to demonstrate how the OHL metric varies due to different building characteristics across different climate zones and seasons. The simulation dataset was then used to develop simple regression models for assessing the impact of ten key building characteristics on OHL. The most impactful were window-to-wall ratio and window characteristics. The regression models show promise as a simple means to assess and screen for resilience using basic building characteristics, especially for non-critical facilities where it may not be viable to conduct detailed engineering analysis.

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