scholarly journals The effect of sugar on the processing behaviour of palm oil: from confectionery fundamentals to predictive regression models

2021 ◽  
Author(s):  
Ryan West
Keyword(s):  
Palm Oil ◽  
Regression Models ◽  
Crystal Morphology ◽  
Milk Powder ◽  
Bulk Oil ◽  
Process Maps ◽  
Predictive Regression ◽  
Dispersion Effects ◽  
Increased Sensitivity ◽  
The Impact

This dissertation explores the impact of confectioner’s sugar and processing on key physical characteristics of palm oil. Though bulk oils such as palm oil have been well-studied, fat-continuous dispersions that include other ingredients such as sugar, cocoa solids, or milk powder are much more complex due to ingredient interactions and the resulting changes in properties such as fat crystal morphology and crystallization pathway. These implications restrict the ability to extrapolate responses from bulk oils towards multi-ingredient systems. This is particularly important given that palm oil in foods rarely exists in bulk but is usually mixed with multiple ingredients. The effects of processing on both bulk oil and oil-sugar blends were explored over four weeks of storage and clearly demonstrated that the existence of a dispersion resulted in large differences in rheology and texture compared to the bulk. Adding sugar significantly increased storage modulus and firmness of the oils while exhibiting increased sensitivity towards processing conditions. Predictive models were generated through multiple regression analysis that overcame limitations derived from extrapolation and corrected for these behavioural differences using a single binary variable accounting for the presence of confectioner’s sugar. As a result, the contributions of sugar to the rheology and texture of oil-sugar blends were modelled, a first in such systems. The results contained within this dissertation are of great industrial relevance as they: i) limit the dependence on anecdote and empiricism to explain results, ii) generate detailed process maps, iii) identify optimal process values to attain desirable rheological and textural responses, and iv) open the door for further investigation into dispersion effects.

scholarly journals The effect of sugar on the processing behaviour of palm oil: from confectionery fundamentals to predictive regression models

2021 ◽  
Author(s):  
Ryan West
Keyword(s):  
Palm Oil ◽  
Regression Models ◽  
Crystal Morphology ◽  
Milk Powder ◽  
Bulk Oil ◽  
Process Maps ◽  
Predictive Regression ◽  
Dispersion Effects ◽  
Increased Sensitivity ◽  
The Impact

This dissertation explores the impact of confectioner’s sugar and processing on key physical characteristics of palm oil. Though bulk oils such as palm oil have been well-studied, fat-continuous dispersions that include other ingredients such as sugar, cocoa solids, or milk powder are much more complex due to ingredient interactions and the resulting changes in properties such as fat crystal morphology and crystallization pathway. These implications restrict the ability to extrapolate responses from bulk oils towards multi-ingredient systems. This is particularly important given that palm oil in foods rarely exists in bulk but is usually mixed with multiple ingredients. The effects of processing on both bulk oil and oil-sugar blends were explored over four weeks of storage and clearly demonstrated that the existence of a dispersion resulted in large differences in rheology and texture compared to the bulk. Adding sugar significantly increased storage modulus and firmness of the oils while exhibiting increased sensitivity towards processing conditions. Predictive models were generated through multiple regression analysis that overcame limitations derived from extrapolation and corrected for these behavioural differences using a single binary variable accounting for the presence of confectioner’s sugar. As a result, the contributions of sugar to the rheology and texture of oil-sugar blends were modelled, a first in such systems. The results contained within this dissertation are of great industrial relevance as they: i) limit the dependence on anecdote and empiricism to explain results, ii) generate detailed process maps, iii) identify optimal process values to attain desirable rheological and textural responses, and iv) open the door for further investigation into dispersion effects.

FAKTOR DETERMINAN PENYALURAN KREDIT BANK PERSERO

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.

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

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.

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

Foods ◽  
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.

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

Sensors ◽  
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.

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

Mathematics ◽  
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.

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

Buildings ◽  
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.

scholarly journals Traumatic events and psychotic experiences: a nationally representative study in Thailand

2021 ◽  
Vol 30 ◽  
Author(s):  
C. Kilian ◽  
S. Supanya ◽  
C. Probst ◽  
C. Morgan ◽  
T. Bärnighausen ◽  
...  
Keyword(s):  
Regression Models ◽  
Traumatic Event ◽  
Traumatic Events ◽  
Psychotic Experiences ◽  
Representative Study ◽  
Lifetime Experience ◽  
Prevention Programmes ◽  
Nationally Representative ◽  
National Mental Health ◽  
The Impact

Abstract Aims Most research exploring the link between traumatic events and psychotic experiences has focused on either Australia, Europe or North America. In this study, we expand the existing knowledge to Thailand and investigate the impact of the type and the number of traumatic events on psychotic experiences in Thailand. Methods We used data from the nationally representative 2013 Thai National Mental Health Survey (TNMHS), including questions on traumatic events and psychotic experiences. We regressed the lifetime experience of hallucinations or delusions against the following independent variables: the experience of any traumatic event during lifetime (dichotomous; hypothesis 1); the experience of either no traumatic event, one interpersonal, one unintentional or both interpersonal and unintentional traumatic events (categorical; hypothesis 2) and the number of traumatic events experienced during lifetime (categorical; hypothesis 3). We adjusted the regression models for sociodemographic indicators and psychiatric disorders, and considered survey weights. Results About 6% (95% confidence interval: 4.9–7.0) of the respondents stated that they had either hallucinatory or delusional experiences during their lifetime. The risk of reporting such experiences was more than doubled as high among respondents who had experienced at least one traumatic event during their lifetime than among those who had not yet experienced one, with higher risks for interpersonal or multiple traumatic events. Our results further indicated an increase in the risk of psychotic experiences as the number of traumatic events increased, with up to an eight-fold higher risk for people exposed to five or more traumatic events in their lifetime, compared to those with no traumatic events. Conclusions Individuals reporting interpersonal or multiple traumatic events face much higher risk of psychotic experiences. Effective and widely accessible secondary prevention programmes for people having experienced interpersonal or multiple traumatic events constitute a key intervention option.

The Impact of Nontariff Trade Policy of European Union Crude Palm Oil Import on Indonesia, Malaysia, and the Rest of the World Economy: An Analysis in GTAP Framework

2020 ◽  
Vol 9 (1) ◽  
pp. 39-52
Author(s):  
Rozy A. Pratama ◽  
Tri Widodo
Keyword(s):  
European Union ◽  
Palm Oil ◽  
Computable General Equilibrium ◽  
Negative Impact ◽  
Trade Policies ◽  
The European Union ◽  
The World ◽  
Trade Analysis ◽  
Global Trade Analysis Project ◽  
The Impact

Indonesia and Malaysia are the largest producers and exporters of palm oil in the world vegetable oil market. Palm oil and its derivative products are the highest contributors to foreign exchange in 2018. This study aims to analyze the impact of the European Union import non-tariff trade policies on the Indonesian and Malaysian economies The analysis uses the Computable General Equilibrium (CGE) model of world trade on the Global Trade Analysis Project (GTAP) program. The results of this study found that the non-tariff import policy by the European Union had a negative impact on the economies of Indonesia and Malaysia. Moreover, the policy also has a negative impact on countries in Southeast Asia and the European Union. This shows that the enactment of non-tariff import trade policies for Indonesian and Malaysian palm oil products has a global impact.

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