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Displaying publications 41 - 60 of 735 in total

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Mathematical modeling and analysis of anemia during pregnancy and postpartum

Mat Daud AA, Toh CQ, Saidun S

Theory Biosci, 2021 Feb;140(1):87-95.
PMID: 33590451 DOI: 10.1007/s12064-020-00334-2

Anemia is a significant public health problem worldwide especially among pregnant women in low- and middle-income countries. In this study, a mathematical model of the population dynamics of anemia during pregnancy and postpartum is constructed. In the modeling process, four independent variables have been considered: (1) the numbers of nonpregnant nonanemic women, (2) anemic nonpregnant women, (3) anemic pregnant or postpartum women and (4) anemic pregnant or postpartum women with complications. The mathematical model is governed by a system of first-order ordinary differential equations. The stability analysis of the model is conducted using Routh-Hurwitz criteria. There is one nonnegative equilibrium point which is asymptotically stable. The equilibrium point obtained indicates the influential parameters that can be controlled to minimize the number of patients at each stage. The proposed model can be employed to forecast the future incidence and prevalence of the disease and appraise intervention programs.

Matched MeSH terms: Models, Theoretical
Fulltext Controlled Release Fertilizers: A Review on Coating Materials and Mechanism of Release

Lawrencia D, Wong SK, Low DYS, Goh BH, Goh JK, Ruktanonchai UR, et al.

Plants (Basel), 2021 Jan 26;10(2).
PMID: 33530608 DOI: 10.3390/plants10020238

Rising world population is expected to increase the demand for nitrogen fertilizers to improve crop yield and ensure food security. With existing challenges on low nutrient use efficiency (NUE) of urea and its environmental concerns, controlled release fertilizers (CRFs) have become a potential solution by formulating them to synchronize nutrient release according to the requirement of plants. However, the most significant challenge that persists is the "tailing" effect, which reduces the economic benefits in terms of maximum fertilizer utilization. High materials cost is also a significant obstacle restraining the widespread application of CRF in agriculture. The first part of this review covers issues related to the application of conventional fertilizer and CRFs in general. In the subsequent sections, different raw materials utilized to form CRFs, focusing on inorganic and organic materials and synthetic and natural polymers alongside their physical and chemical preparation methods, are compared. Important factors affecting rate of release, mechanism of release and mathematical modelling approaches to predict nutrient release are also discussed. This review aims to provide a better overview of the developments regarding CRFs in the past ten years, and trends are identified and analyzed to provide an insight for future works in the field of agriculture.

Matched MeSH terms: Models, Theoretical
Fulltext Linear-Nonlinear Stiffness Responses of Carbon Fiber-Reinforced Polymer Composite Materials and Structures: A Numerical Study

R Koloor SS, Karimzadeh A, Abdullah MR, Petrů M, Yidris N, Sapuan SM, et al.

Polymers (Basel), 2021 Jan 22;13(3).
PMID: 33498984 DOI: 10.3390/polym13030344

The stiffness response or load-deformation/displacement behavior is the most important mechanical behavior that frequently being utilized for validation of the mathematical-physical models representing the mechanical behavior of solid objects in numerical method, compared to actual experimental data. This numerical study aims to investigate the linear-nonlinear stiffness behavior of carbon fiber-reinforced polymer (CFRP) composites at material and structural levels, and its dependency to the sets of individual/group elastic and damage model parameters. In this regard, a validated constitutive damage model, elastic-damage properties as reference data, and simulation process, that account for elastic, yielding, and damage evolution, are considered in the finite element model development process. The linear-nonlinear stiffness responses of four cases are examined, including a unidirectional CFRP composite laminate (material level) under tensile load, and also three multidirectional composite structures under flexural loads. The result indicated a direct dependency of the stiffness response at the material level to the elastic properties. However, the stiffness behavior of the composite structures depends both on the structural configuration, geometry, lay-ups as well as the mechanical properties of the CFRP composite. The value of maximum reaction force and displacement of the composite structures, as well as the nonlinear response of the structures are highly dependent not only to the mechanical properties, but also to the geometry and the configuration of the structures.

Matched MeSH terms: Models, Theoretical
Fulltext Global patterns and climatic controls of forest structural complexity

Ehbrecht M, Seidel D, Annighöfer P, Kreft H, Köhler M, Zemp DC, et al.

Nat Commun, 2021 01 22;12(1):519.
PMID: 33483481 DOI: 10.1038/s41467-020-20767-z

The complexity of forest structures plays a crucial role in regulating forest ecosystem functions and strongly influences biodiversity. Yet, knowledge of the global patterns and determinants of forest structural complexity remains scarce. Using a stand structural complexity index based on terrestrial laser scanning, we quantify the structural complexity of boreal, temperate, subtropical and tropical primary forests. We find that the global variation of forest structural complexity is largely explained by annual precipitation and precipitation seasonality (R² = 0.89). Using the structural complexity of primary forests as benchmark, we model the potential structural complexity across biomes and present a global map of the potential structural complexity of the earth´s forest ecoregions. Our analyses reveal distinct latitudinal patterns of forest structure and show that hotspots of high structural complexity coincide with hotspots of plant diversity. Considering the mechanistic underpinnings of forest structural complexity, our results suggest spatially contrasting changes of forest structure with climate change within and across biomes.

Matched MeSH terms: Models, Theoretical
Oil spill trajectory modelling and environmental vulnerability mapping using GNOME model and GIS

Balogun AL, Yekeen ST, Pradhan B, Wan Yusof KB

Environ Pollut, 2021 Jan 01;268(Pt A):115812.
PMID: 33143984 DOI: 10.1016/j.envpol.2020.115812

This study develops an oil spill environmental vulnerability model for predicting and mapping the oil slick trajectory pattern in Kota Tinggi, Malaysia. The impact of seasonal variations on the vulnerability of the coastal resources to oil spill was modelled by estimating the quantity of coastal resources affected across three climatic seasons (northeast monsoon, southwest monsoon and pre-monsoon). Twelve 100 m3 (10,000 splots) medium oil spill scenarios were simulated using General National Oceanic and Atmospheric Administration Operational Oil Modeling Environment (GNOME) model. The output was integrated with coastal resources, comprising biological, socio-economic and physical shoreline features. Results revealed that the speed of an oil slick (40.8 m per minute) is higher during the pre-monsoon period in a southwestern direction and lower during the northeast monsoon (36.9 m per minute). Evaporation, floating and spreading are the major weathering processes identified in this study, with approximately 70% of the slick reaching the shoreline or remaining in the water column during the first 24 h (h) of the spill. Oil spill impacts were most severe during the southwest monsoon, and physical shoreline resources are the most vulnerable to oil spill in the study area. The study concluded that variation in climatic seasons significantly influence the vulnerability of coastal resources to marine oil spill.

Matched MeSH terms: Models, Theoretical
Security robot for the prevention of workplace violence using the Non-linear Adaptive Heuristic Mathematical Model

Tao H, Rahman MA, Al-Saffar A, Zhang R, Salih SQ, Zain JM, et al.

Work, 2021;68(3):853-861.
PMID: 33612528 DOI: 10.3233/WOR-203419

BACKGROUND: Nowadays, workplace violence is found to be a mental health hazard and considered a crucial topic. The collaboration between robots and humans is increasing with the growth of Industry 4.0. Therefore, the first problem that must be solved is human-machine security. Ensuring the safety of human beings is one of the main aspects of human-robotic interaction. This is not just about preventing collisions within a shared space among human beings and robots; it includes all possible means of harm for an individual, from physical contact to unpleasant or dangerous psychological effects.
OBJECTIVE: In this paper, Non-linear Adaptive Heuristic Mathematical Model (NAHMM) has been proposed for the prevention of workplace violence using security Human-Robot Collaboration (HRC). Human-Robot Collaboration (HRC) is an area of research with a wide range of up-demands, future scenarios, and potential economic influence. HRC is an interdisciplinary field of research that encompasses cognitive sciences, classical robotics, and psychology.
RESULTS: The robot can thus make the optimal decision between actions that expose its capabilities to the human being and take the best steps given the knowledge that is currently available to the human being. Further, the ideal policy can be measured carefully under certain observability assumptions.
CONCLUSION: The system is shown on a collaborative robot and is compared to a state of the art security system. The device is experimentally demonstrated. The new system is being evaluated qualitatively and quantitatively.

Matched MeSH terms: Models, Theoretical
Fulltext A robust fuzzy logic-based model for predicting the critical total drawdown in sand production in oil and gas wells

Alakbari FS, Mohyaldinn ME, Ayoub MA, Muhsan AS, Hussein IA

PLoS One, 2021;16(4):e0250466.
PMID: 33901240 DOI: 10.1371/journal.pone.0250466

Sand management is essential for enhancing the production in oil and gas reservoirs. The critical total drawdown (CTD) is used as a reliable indicator of the onset of sand production; hence, its accurate prediction is very important. There are many published CTD prediction correlations in literature. However, the accuracy of most of these models is questionable. Therefore, further improvement in CTD prediction is needed for more effective and successful sand control. This article presents a robust and accurate fuzzy logic (FL) model for predicting the CTD. Literature on 23 wells of the North Adriatic Sea was used to develop the model. The used data were split into 70% training sets and 30% testing sets. Trend analysis was conducted to verify that the developed model follows the correct physical behavior trends of the input parameters. Some statistical analyses were performed to check the model's reliability and accuracy as compared to the published correlations. The results demonstrated that the proposed FL model substantially outperforms the current published correlations and shows higher prediction accuracy. These results were verified using the highest correlation coefficient, the lowest average absolute percent relative error (AAPRE), the lowest maximum error (max. AAPRE), the lowest standard deviation (SD), and the lowest root mean square error (RMSE). Results showed that the lowest AAPRE is 8.6%, whereas the highest correlation coefficient is 0.9947. These values of AAPRE (<10%) indicate that the FL model could predicts the CTD more accurately than other published models (>20% AAPRE). Moreover, further analysis indicated the robustness of the FL model, because it follows the trends of all physical parameters affecting the CTD.

Matched MeSH terms: Models, Theoretical*
Fulltext Modelling knowledge, health beliefs, and health-promoting behaviours related to cardiovascular disease prevention among Malaysian university students

Lim BC, Kueh YC, Arifin WN, Ng KH

PLoS One, 2021;16(4):e0250627.
PMID: 33909664 DOI: 10.1371/journal.pone.0250627

BACKGROUND: Healthy lifestyle habits formed during young adulthood may have a sustaining impact on health across later life. The current study aimed to test the theoretical model of factors (selected demographic variables, knowledge of heart disease, health belief related to cardiovascular disease (CVD), self-efficacy, cues to action, and screening intention) influencing health-promoting behaviours among Malaysian university students.
METHODS: In a cross-sectional survey, the undergraduate students in Universiti Sains Malaysia were invited to complete the self-administered questionnaires. Participants were selected using a purposive sampling method. The proposed hypothesised model was analysed using a structural equation modelling with Mplus 7.3 program. A total of 788 (70.7% female) undergraduate students with a mean age of 20.2 (SD = 1.02) participated in the study. The primary outcome of knowledge, health beliefs, and health-promoting behaviours related to CVD were measured by questionnaires namely: Knowledge of Heart Disease, Health Beliefs Related to CVD, and Health Promoting Lifestyle Profiles-II.
RESULTS: The final hypothetical structural model showed a good fit to the data based on several fit indices: with comparative fit index (CFI) at .921, standardised root mean square residual (SRMR) at .037, and root mean square error of approximation (RMSEA) at .044 (90% CI: .032, .054). The final structural model supported 13 significant path estimates. These variables explained 12% of the total variance in health-promoting behaviours. Through perceived benefits, total knowledge had an indirect effect on health-promoting behaviours.
CONCLUSION: The results suggest that perceived barriers, perceived benefits, family history of CVD, and screening intention enable young adults to engage in health-promoting behaviours.

Matched MeSH terms: Models, Theoretical
Fulltext Modelling monthly influenza cases in Malaysia

Norrulashikin MA, Yusof F, Hanafiah NHM, Norrulashikin SM

PLoS One, 2021;16(7):e0254137.
PMID: 34288925 DOI: 10.1371/journal.pone.0254137

The increasing trend in the number new cases of influenza every year as reported by WHO is concerning, especially in Malaysia. To date, there is no local research under healthcare sector that implements the time series forecasting methods to predict future disease outbreak in Malaysia, specifically influenza. Addressing the problem could increase awareness of the disease and could help healthcare workers to be more prepared in preventing the widespread of the disease. This paper intends to perform a hybrid ARIMA-SVR approach in forecasting monthly influenza cases in Malaysia. Autoregressive Integrated Moving Average (ARIMA) model (using Box-Jenkins method) and Support Vector Regression (SVR) model were used to capture the linear and nonlinear components in the monthly influenza cases, respectively. It was forecasted that the performance of the hybrid model would improve. The data from World Health Organization (WHO) websites consisting of weekly Influenza Serology A cases in Malaysia from the year 2006 until 2019 have been used for this study. The data were recategorized into monthly data. The findings of the study showed that the monthly influenza cases could be efficiently forecasted using three comparator models as all models outperformed the benchmark model (Naïve model). However, SVR with linear kernel produced the lowest values of RMSE and MAE for the test dataset suggesting the best performance out of the other comparators. This suggested that SVR has the potential to produce more consistent results in forecasting future values when compared with ARIMA and the ARIMA-SVR hybrid model.

Matched MeSH terms: Models, Theoretical
Fulltext The link between climate change, food security and fertility: The case of Bangladesh

Chen M, Atiqul Haq SM, Ahmed KJ, Hussain AHMB, Ahmed MNQ

PLoS One, 2021;16(10):e0258196.
PMID: 34673797 DOI: 10.1371/journal.pone.0258196

Climate change is likely to worsen the food security situation through its impact on food production, which may indirectly affect fertility behaviour. This study examines the direct and indirect effects of climate change (e.g., temperature and precipitation) via the production of major crops, as well as their short- and long-term effects on the total fertility rate (TFR) in Bangladesh. We used structural equation modelling (SEM) to perform path analysis and distinguish the direct influence of climate change on fertility and its indirect influence on fertility through food security. We also applied the error correction model (ECM) to analyze the time-series data on temperature and precipitation, crop production and fertility rate of Bangladesh from 1966 to 2015. The results show that maximum temperature has a direct effect and indirect negative effect-via crop production-on TFR, while crop production has a direct positive effect and indirect negative effect-via infant mortality-on TFR. In the short term, TFR responds negatively to the maximum temperature but positively in the long term. The effect of rainfall on TFR is found to be direct, positive, but mainly short-term. Although indicators of economic development play an important part in the fertility decline in Bangladesh, some climate change parameters and crop production are non-negligible factors.

Matched MeSH terms: Models, Theoretical
Fulltext Multimode HMSIW-Based Bandpass Filter with Improved Selectivity for Fifth-Generation (5G) RF Front-Ends

Iqbal A, Jiat Tiang J, Kin Wong S, Alibakhshikenari M, Falcone F, Limiti E

Sensors (Basel), 2020 Dec 19;20(24).
PMID: 33352800 DOI: 10.3390/s20247320

This article presents the detailed theoretical, simulation, and experimental analysis of a half-mode substrate integrated waveguide (HMSIW)-based multimode wideband filter. A third-order, semicircular HMSIW filter is developed in this paper. A semicircular HMSIW cavity resonator is adopted to achieve wide band characteristics. A U-shaped slot (acts as a λ/4 stub) in the center of a semicircular HMSIW cavity resonator and L-shaped open-circuited stubs are used to improve the out-of-band response by generating multiple transmission zeros (TZs) in the stop-band region of the filter. The TZs on either side of the passband can be controlled by adjusting dimensions of a U-shaped slot and L-shaped open-circuited stubs. The proposed filter covers a wide fractional bandwidth, has a lower insertion loss value, and has multiple TZs (which improves the selectivity). The simulated response of filter agrees well with the measured data. The proposed HMSIW bandpass filter can be integrated with any planar wideband communication system circuit, thanks to its planar structure.

Matched MeSH terms: Models, Theoretical
Fulltext Mathematical Model for Estimating Parameters of Swelling Drug Delivery Devices in a Two-Phase Release

Setapa A, Ahmad N, Mohd Mahali S, Mohd Amin MCI

Polymers (Basel), 2020 Dec 05;12(12).
PMID: 33291495 DOI: 10.3390/polym12122921

Various swelling drug delivery devices are promising materials for control drug delivery because of their ability to swell and release entrapped therapeutics, in response to physiological stimuli. Previously, many mathematical models have been developed to predict the mechanism of drug release from a swelling device. However, some of these models do not consider the changes in diffusion behaviour as the device swells. Therefore, we used a two-phase approach to simplify the mathematical model considering the effect of swelling on the diffusion coefficient. We began by defining a moving boundary problem to consider the swelling process. Landau transformation was used for mitigating the moving boundary problem. The transformed problem was analytically solved using the separation of variables method. Further, the analytical solution was extended to include the drug release in two phases where each phase has distinct diffusion coefficient and continuity condition was applied. The newly developed model was validated by the experimental data of bacterial cellulose hydrogels using the LSQCURVEFIT function in MATLAB. The numerical test showed that the new model exhibited notable improvement in curve fitting, and it was observed that the initial effective diffusion coefficient of the swelling device was lower than the later effective diffusion coefficient.

Matched MeSH terms: Models, Theoretical
Fulltext Fractal-Fractional Mathematical Model Addressing the Situation of Corona Virus in Pakistan

Shah K, Arfan M, Mahariq I, Ahmadian A, Salahshour S, Ferrara M

Results Phys, 2020 Dec;19:103560.
PMID: 33200064 DOI: 10.1016/j.rinp.2020.103560

This work is the consideration of a fractal fractional mathematical model on the transmission and control of corona virus (COVID-19), in which the total population of an infected area is divided into susceptible, infected and recovered classes. We consider a fractal-fractional order

SIR

type model for investigation of Covid-19. To realize the transmission and control of corona virus in a much better way, first we study the stability of the corresponding deterministic model using next generation matrix along with basic reproduction number. After this, we study the qualitative analysis using "fixed point theory" approach. Next, we use fractional Adams-Bashforth approach for investigation of approximate solution to the considered model. At the end numerical simulation are been given by matlab to provide the validity of mathematical system having the arbitrary order and fractal dimension.

Matched MeSH terms: Models, Theoretical
Adsorption and desorption of malachite green by using chitosan-deep eutectic solvents beads

Sadiq AC, Rahim NY, Suah FBM

Int J Biol Macromol, 2020 Dec 01;164:3965-3973.
PMID: 32910963 DOI: 10.1016/j.ijbiomac.2020.09.029

Chitosan-deep eutectic solvent (DES) beads were prepared from chitosan and DESs. The DESs used were choline chloride-urea (DES A) and choline chloride-glycerol (DES B). Both chitosan-DES beads were used to remove malachite green (MG) dye from an aqueous solution. The optimum pH for chitosan-DES A was recorded at pH 8.0 while optimum pH for chitosan-DES B was pH 9.0. The maximum adsorption capacity obtained for chitosan-DES A and chitosan-DES B were 6.54 mg/g and 8.64 mg/g, respectively. The optimum conditions for both chitosan-DES beads to remove MG were 0.08 g of adsorbent and 20 min of agitation time. Five kinetic models were applied to analyse the data and the results showed that the pseudo-second-order and intraparticle diffusion model fitted best with R2 > 0.999. For the adsorption capacity, results show that the Freundlich and Langmuir adsorption isotherms fitted well with chitosan-DES A and chitosan-DES B, respectively. The maximum adsorption capacities (qmax) obtained from chitosan-DES A and chitosan-DES B were 1.43 mg/g and 17.86 mg/g, respectively. Desorption indicated good performance in practical applications.

Matched MeSH terms: Models, Theoretical
Enrichment of surface oxygen functionalities on activated carbon for adsorptive removal of sevoflurane

Ang TN, Young BR, Taylor M, Burrell R, Aroua MK, Chen WH, et al.

Chemosphere, 2020 Dec;260:127496.
PMID: 32659541 DOI: 10.1016/j.chemosphere.2020.127496

Activated carbons have been reported to be useful for adsorptive removal of the volatile anaesthetic sevoflurane from a vapour stream. The surface functionalities on activated carbons could be modified through aqueous oxidation using oxidising solutions to enhance the sevoflurane adsorption. In this study, an attempt to oxidise the surface of a commercial activated carbon to improve its adsorption capacity for sevoflurane was conducted using 6 mol/L nitric acid, 2 mol/L ammonium persulfate, and 30 wt per cent (wt%) of hydrogen peroxide (H2O2). The adsorption tests at fixed conditions (bed depth: 10 cm, inlet concentration: 528 mg/L, and flow rate: 3 L/min) revealed that H2O2 oxidation gave desirable sevoflurane adsorption (0.510 ± 0.005 mg/m2). A parametric study was conducted with H2O2 to investigate the effect of oxidation conditions to the changes in surface oxygen functionalities by varying the concentration, oxidation duration, and temperature, and the Conductor-like Screening Model for Real Solvents (COSMO-RS) was applied to predict the interactions between oxygen functionalities and sevoflurane. The H2O2 oxidation incorporated varying degrees of both surface oxygen functionalities with hydrogen bond (HB) acceptor and HB donor characters under the studied conditions. Oxidised samples with enriched oxygen functionalities with HB acceptor character and fewer HB donor character exhibited better adsorption capacity for sevoflurane. The presence of a high amount of oxygen functional groups with HB donor character adversely affected the sevoflurane adsorption despite the enrichment of oxygen functional groups with HB acceptor character that have a higher tendency to adsorb sevoflurane.

Matched MeSH terms: Models, Theoretical
Fulltext COVID-19 as a viral functional ACE2 deficiency disorder with ACE2 related multi-organ disease

Gan R, Rosoman NP, Henshaw DJE, Noble EP, Georgius P, Sommerfeld N

Med Hypotheses, 2020 Nov;144:110024.
PMID: 32758871 DOI: 10.1016/j.mehy.2020.110024

SARS-CoV-2, the agent of COVID-19, shares a lineage with SARS-CoV-1, and a common fatal pulmonary profile but with striking differences in presentation, clinical course, and response to treatment. In contrast to SARS-CoV-1 (SARS), COVID-19 has presented as an often bi-phasic, multi-organ pathology, with a proclivity for severe disease in the elderly and those with hypertension, diabetes and cardiovascular disease. Whilst death is usually related to respiratory collapse, autopsy reveals multi-organ pathology. Chronic pulmonary disease is underrepresented in the group with severe COVID-19. A commonality of aberrant renin angiotensin system (RAS) is suggested in the at-risk group. The identification of angiotensin-converting-enzyme 2 (ACE2) as the receptor allowing viral entry to cells precipitated our interest in the role of ACE2 in COVID-19 pathogenesis. We propose that COVID-19 is a viral multisystem disease, with dominant vascular pathology, mediated by global reduction in ACE2 function, pronounced in disease conditions with RAS bias toward angiotensin-converting-enzyme (ACE) over ACE2. It is further complicated by organ specific pathology related to loss of ACE2 expressing cells particularly affecting the endothelium, alveolus, glomerulus and cardiac microvasculature. The possible upregulation in ACE2 receptor expression may predispose individuals with aberrant RAS status to higher viral load on infection and relatively more cell loss. Relative ACE2 deficiency leads to enhanced and protracted tissue, and vessel exposure to angiotensin II, characterised by vasoconstriction, enhanced thrombosis, cell proliferation and recruitment, increased tissue permeability, and cytokine production (including IL-6) resulting in inflammation. Additionally, there is a profound loss of the "protective" angiotensin (1-7), a vasodilator with anti-inflammatory, anti-thrombotic, antiproliferative, antifibrotic, anti-arrhythmic, and antioxidant activity. Our model predicts global vascular insult related to direct endothelial cell damage, vasoconstriction and thrombosis with a disease specific cytokine profile related to angiotensin II rather than "cytokine storm". Our proposed mechanism of lung injury provides an explanation for early hypoxia without reduction in lung compliance and suggests a need for revision of treatment protocols to address vasoconstriction, thromboprophylaxis, and to minimize additional small airways and alveolar trauma via ventilation choice. Our model predicts long term sequelae of scarring/fibrosis in vessels, lungs, renal and cardiac tissue with protracted illness in at-risk individuals. It is hoped that our model stimulates review of current diagnostic and therapeutic intervention protocols, particularly with respect to early anticoagulation, vasodilatation and revision of ventilatory support choices.

Matched MeSH terms: Models, Theoretical
Fulltext Price perception and price appearance on repurchase intention of Gen Y: do brand experience and brand preference mediate?

Yasri Y, Susanto P, Hoque ME, Gusti MA

Heliyon, 2020 Nov;6(11):e05532.
PMID: 33294680 DOI: 10.1016/j.heliyon.2020.e05532

The study examines the effect of price perception and price appearance on Gen Y's repurchase intention towards snack products of small and medium-sized enterprises (SMEs), along with the mediating roles of consumers' brand experience and preference. A survey method for data collection in the study used with a structured questionnaire, in which the respondents were requested to give their responses to the experiment conducted on local specialty snack products produced by SMEs. Covariance-based structural equation modeling (CB-SEM) was used to analyze the hypothesized relationships in the research model. The findings show that all the direct effects in the proposed model have a significant effect, except for the relationship between price perception and brand preference that there is no significant effect. Similarly, the mediating roles of consumer brand experience and consumer-based brand preference proved to have a significant effect. Finally, the implications of this study will be discussed further.

Matched MeSH terms: Models, Theoretical
Fulltext Advanced drug delivery systems can assist in targeting coronavirus disease (COVID-19): A hypothesis

Mehta M, Prasher P, Sharma M, Shastri MD, Khurana N, Vyas M, et al.

Med Hypotheses, 2020 Nov;144:110254.
PMID: 33254559 DOI: 10.1016/j.mehy.2020.110254

The highly contagious coronavirus, which had already affected more than 2 million people in 210 countries, triggered a colossal economic crisis consequently resulting from measures adopted by various goverments to limit transmission. This has placed the lives of many people infected worldwide at great risk. Currently there are no established or validated treatments for COVID-19, that is approved worldwide. Nanocarriers may offer a wide range of applications that could be developed into risk-free approaches for successful therapeutic strategies that may lead to immunisation against the severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) which is the primary causative organism that had led to the current COVID-19 pandemic. We address existing as well as emerging therapeutic and prophylactic approaches that may enable us to effectively combat this pandemic, and also may help to identify the key areas where nano-scientists can step in.

Matched MeSH terms: Models, Theoretical
Fulltext Augmenting CO2 Absorption Flux through a Gas-Liquid Membrane Module by Inserting Carbon-Fiber Spacers

Chen L, Ho CD, Jen LY, Lim JW, Chen YH

Membranes (Basel), 2020 Oct 22;10(11).
PMID: 33105658 DOI: 10.3390/membranes10110302

We investigated the insertion of eddy promoters into a parallel-plate gas-liquid polytetrafluoroethylene (PTFE) membrane contactor to effectively enhance carbon dioxide absorption through aqueous amine solutions (monoethanolamide-MEA). In this study, a theoretical model was established and experimental work was performed to predict and to compare carbon dioxide absorption efficiency under concurrent- and countercurrent-flow operations for various MEA feed flow rates, inlet CO2 concentrations, and channel design conditions. A Sherwood number's correlated expression was formulated, incorporating experimental data to estimate the mass transfer coefficient of the CO2 absorption in MEA flowing through a PTFE membrane. Theoretical predictions were calculated and validated through experimental data for the augmented CO2 absorption efficiency by inserting carbon-fiber spacers as an eddy promoter to reduce the concentration polarization effect. The study determined that a higher MEA feed rate, a lower feed CO2 concentration, and wider carbon-fiber spacers resulted in a higher CO2 absorption rate for concurrent- and countercurrent-flow operations. A maximum of 80% CO2 absorption efficiency enhancement was found in the device by inserting carbon-fiber spacers, as compared to that in the empty channel device. The overall CO2 absorption rate was higher for countercurrent operation than that for concurrent operation. We evaluated the effectiveness of power utilization in augmenting the CO2 absorption rate by inserting carbon-fiber spacers in the MEA feed channel and concluded that the higher the flow rate, the lower the power utilization's effectiveness. Therefore, to increase the CO2 absorption flux, widening carbon-fiber spacers was determined to be more effective than increasing the MEA feed flow rate.

Matched MeSH terms: Models, Theoretical
Fulltext Maximizing the value of forest restoration for tropical mammals by detecting three-dimensional habitat associations

Deere NJ, Guillera-Arroita G, Swinfield T, Milodowski DT, Coomes DA, Bernard H, et al.

Proc Natl Acad Sci U S A, 2020 10 20;117(42):26254-26262.
PMID: 32989143 DOI: 10.1073/pnas.2001823117

Tropical forest ecosystems are facing unprecedented levels of degradation, severely compromising habitat suitability for wildlife. Despite the fundamental role biodiversity plays in forest regeneration, identifying and prioritizing degraded forests for restoration or conservation, based on their wildlife value, remains a significant challenge. Efforts to characterize habitat selection are also weakened by simple classifications of human-modified tropical forests as intact vs. degraded, which ignore the influence that three-dimensional (3D) forest structure may have on species distributions. Here, we develop a framework to identify conservation and restoration opportunities across logged forests in Borneo. We couple high-resolution airborne light detection and ranging (LiDAR) and camera trap data to characterize the response of a tropical mammal community to changes in 3D forest structure across a degradation gradient. Mammals were most responsive to covariates that accounted explicitly for the vertical and horizontal characteristics of the forest and actively selected structurally complex environments comprising tall canopies, increased plant area index throughout the vertical column, and the availability of a greater diversity of niches. We show that mammals are sensitive to structural simplification through disturbance, emphasizing the importance of maintaining and enhancing structurally intact forests. By calculating occurrence thresholds of species in response to forest structural change, we identify areas of degraded forest that would provide maximum benefit for multiple high-conservation value species if restored. The study demonstrates the advantages of using LiDAR to map forest structure, rather than relying on overly simplistic classifications of human-modified tropical forests, for prioritizing regions for restoration.

Matched MeSH terms: Models, Theoretical

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