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Feedforward backpropagation, Genetic Algorithm approaches for predicting reference evapotranspiration

Shafika Sultan Abdullah, M.A. Malek, Namiq Sultan Abdullah, A. Mustapha

Sains Malaysiana, 2015;44:1053-1059.

Water scarcity is a global concern, as the demand for water is increasing tremendously and poor management of water resources will accelerates dramatically the depletion of available water. The precise prediction of evapotranspiration (ET), that consumes almost 100% of the supplied irrigation water, is one of the goals that should be adopted in order to avoid more squandering of water especially in arid and semiarid regions. The capabilities of feedforward backpropagation neural networks (FFBP) in predicting reference evapotranspiration (ET0) are evaluated in this paper in comparison with the empirical FAO Penman-Monteith (P-M) equation, later a model of FFBP+Genetic Algorithm (GA) is implemented for the same evaluation purpose. The study location is the main station in Iraq, namely Baghdad Station. Records of weather variables from the related meteorological station, including monthly mean records of maximum air temperature (Tmax), minimum air temperature (Tmin), sunshine hours (Rn), relative humidity (Rh) and wind speed (U2), from the related meteorological station are used in the prediction of ET0 values. The performance of both simulation models were evaluated using statistical coefficients such as the root of mean squared error (RMSE), mean absolute error (MAE) and coefficient of determination (R2). The results of both models are promising, however the hybrid model shows higher efficiency in predicting ET0 and could be recommended for modeling of ET0 in arid and semiarid regions.

Matched MeSH terms: Goals
Fulltext The de novo transcriptome of workers head of the higher group termite Globitermes sulphureus Haviland (Blattodea: Termitidae)

Hussin NA, Najimudin N, Ab Majid AH

Heliyon, 2019 Dec;5(12):e02969.
PMID: 31872129 DOI: 10.1016/j.heliyon.2019.e02969

The subterranean termite Globitermus sulphureus is an important Southeast Asian pest with limited genomic resources that causes damages to agriculture crops and building structures. Therefore, the main goal of this study was to survey the G. sulphureus transcriptome composition. Here, we performed de novo transcriptome for G. sulphureus workers' heads using Illumina HiSeq paired-end sequencing technology. A total of 88, 639, 408 clean reads were collected and assembled into 243, 057 transcripts and 193, 344 putative genes. The transcripts were annotated with the Trinotate pipeline. In total, 27, 061 transcripts were successfully annotated using BLASTX against the SwissProt database and 17, 816 genes were assigned to 47, 598 GO terms. We classified 14, 223 transcripts into COG classification, resulting in 25 groups of functional annotations. Next, a total of 12, 194 genes were matched in the KEGG pathway and 392 metabolic pathways were predicted based on the annotation. Moreover, we detected two endogenous cellulases in the sequences. The RT-qPCR analysis showed that there were significant differences in the expression levels of two genes β-glucosidase and endo-β-1,4-glucanase between worker and soldier heads of G. sulphureus. This is the first study to characterize the complete head transcriptome of a higher termite G. sulphureus using a high-throughput sequencing. Our study may provide an overview and comprehensive molecular resource for comparative studies of the transcriptomics and genomics of termites.

Matched MeSH terms: Goals
Fulltext Big Brain Data Initiative in Universiti Sains Malaysia: Challenges in Brain Mapping for Malaysia

Shekh Ibrahim SA, Hamzah N, Abdul Wahab AR, Abdullah JM, Nurul Hashimah Ahamed Hassain Malim, Sumari P, et al.

Malays J Med Sci, 2020 Jul;27(4):1-8.
PMID: 32863741 DOI: 10.21315/mjms2020.27.4.1

Universiti Sains Malaysia has started the Big Brain Data Initiative project since the last two years as brain mapping techniques have proven to be important in understanding the molecular, cellular and functional mechanisms of the brain. This Big Brain Data Initiative can be a platform for neurophysicians and neurosurgeons, psychiatrists, psychologists, cognitive neuroscientists, neurotechnologists and other researchers to improve brain mapping techniques. Data collection from a cohort of multiracial population in Malaysia is important for present and future research and finding cure for neurological and mental illness. Malaysia is one of the participant of the Global Brain Consortium (GBC) supported by the World Health Organization. This project is a part of its contribution via the third GBC goal which is influencing the policy process within and between high-income countries and low- and middle-income countries, such as pathways for fair data-sharing of multi-modal imaging data, starting with electroencephalographic data.

Matched MeSH terms: Goals
Fulltext Working Memory From the Psychological and Neurosciences Perspectives: A Review

Chai WJ, Abd Hamid AI, Abdullah JM

Front Psychol, 2018;9:401.
PMID: 29636715 DOI: 10.3389/fpsyg.2018.00401

Since the concept of working memory was introduced over 50 years ago, different schools of thought have offered different definitions for working memory based on the various cognitive domains that it encompasses. The general consensus regarding working memory supports the idea that working memory is extensively involved in goal-directed behaviors in which information must be retained and manipulated to ensure successful task execution. Before the emergence of other competing models, the concept of working memory was described by the multicomponent working memory model proposed by Baddeley and Hitch. In the present article, the authors provide an overview of several working memory-relevant studies in order to harmonize the findings of working memory from the neurosciences and psychological standpoints, especially after citing evidence from past studies of healthy, aging, diseased, and/or lesioned brains. In particular, the theoretical framework behind working memory, in which the related domains that are considered to play a part in different frameworks (such as memory's capacity limit and temporary storage) are presented and discussed. From the neuroscience perspective, it has been established that working memory activates the fronto-parietal brain regions, including the prefrontal, cingulate, and parietal cortices. Recent studies have subsequently implicated the roles of subcortical regions (such as the midbrain and cerebellum) in working memory. Aging also appears to have modulatory effects on working memory; age interactions with emotion, caffeine and hormones appear to affect working memory performances at the neurobiological level. Moreover, working memory deficits are apparent in older individuals, who are susceptible to cognitive deterioration. Another younger population with working memory impairment consists of those with mental, developmental, and/or neurological disorders such as major depressive disorder and others. A less coherent and organized neural pattern has been consistently reported in these disadvantaged groups. Working memory of patients with traumatic brain injury was similarly affected and shown to have unusual neural activity (hyper- or hypoactivation) as a general observation. Decoding the underlying neural mechanisms of working memory helps support the current theoretical understandings concerning working memory, and at the same time provides insights into rehabilitation programs that target working memory impairments from neurophysiological or psychological aspects.

Matched MeSH terms: Goals
Fulltext Monthly distribution map of carbon monoxide (CO) from AIRS over Peninsular Malaysia, Sabah and Sarawak for the year 2003

Jasim M. Rajab, Mat Jafri, M.Z, Lim, H.S., Abdullah, K.

Pertanika Journal of Science & Technology, 2011;19(3):89-96.
MyJurnal

Carbon monoxide (CO) is a ubiquitous, an indoor and outdoor air pollutant. It is not a significant greenhouse gas as it absorbs little infrared radiation from the Earth. It is produced by the incomplete combustion of fossil fuels, and biomass burning. The CO data are obtained from Atmospheric Infrared Sounder (AIRS) onboard NASA’s Aqua satellite. The AIRS provides information for several greenhouse gases, CO2, CH4, CO, and O3 as a one goal of the AIRS instrument (included on the EOS Aqua satellite launched, May 4, 2002) as well as to improve weather prediction of the water and energy cycle. The results of the analysis of the retrieved CO total column amount (CO_total_column_A) as well as effective of the CO volume mixing ratio (CO_VMR_eff_A), Level-3 monthly (AIR*3STM) 1º*1º spatial resolution, ascending are used to study the CO distribution over the East and West Malaysia for the year 2003. The CO maps over the study area were generated by using Kriging Interpolation technique and analyzed by using Photoshop CS. Variations in the biomass burning and the CO emissions where noted, while the highest CO occurred at late dry season in the region which has experienced extensive biomass burning and greater draw down of CO occurred in the pristine continental environment (East Malaysia). In all cases, the CO concentration at West Malaysia is higher than East Malaysia. The southeastern Sarawak (lat. 3.5˚ - long. 115.5˚) is less polluted regions and less the CO in most of times in the year. Examining satellite measurements revealed that the enhanced CO emission correlates with occasions of less rainfall during the dry season.

Matched MeSH terms: Goals
Fulltext Intestinal obstruction: predictor of poor prognosis in colorectal carcinoma?

Mohd Suan MA, Tan WL, Soelar SA, Ismail I, Abu Hassan MR

Epidemiol Health, 2015;37:e2015017.
PMID: 25868638 DOI: 10.4178/epih/e2015017

OBJECTIVES: The goal of this study was to assess the relationship between intestinal obstruction and the prognosis of colorectal carcinoma.
METHODS: Data pertaining to 4,501 colorectal carcinoma patients were extracted from the national colorectal registry and analysed. Survival analysis was performed using the Kaplan-Meier method. The log-rank test was used to compare the survival rate between patients with intestinal obstruction and those without intestinal obstruction. The p-values<0.05 were considered to indicate statistical significance. Simple Cox proportional hazards regression analysis was used to estimate the crude hazard ratio of mortality from colorectal cancer.
RESULTS: Intestinal obstruction was reported in more than 13% of patients. The 3-year survival rate after treatment was 48.3% (95% confidence interval [CI], 43.9 to 52.8) for patients with intestinal obstruction (n=593) and 54.9% (95% CI, 53.1 to 56.6) for patients without intestinal obstruction (n=3,908). The 5-year survival rate for patients with intestinal obstruction was 37.3% (95% CI, 31.9 to 42.8), which was lower than that of patients without intestinal obstruction (45.6%; 95% CI, 43.5 to 47.7). After adjusting the hazard ratio for other prognostic variables, intestinal obstruction had a statistically significant negative correlation with the survival rate of colorectal cancer patients, with an adjusted hazard ratio of 1.22 (p=0.008).
CONCLUSIONS: The presence of intestinal obstruction is associated with a lower survival rate among colorectal cancer patients.

Matched MeSH terms: Goals
Fulltext A Statistical Study on the Development of Metronidazole-Chitosan-Alginate Nanocomposite Formulation Using the Full Factorial Design

Sabbagh HAK, Hussein-Al-Ali SH, Hussein MZ, Abudayeh Z, Ayoub R, Abudoleh SM

Polymers (Basel), 2020 Apr 01;12(4).
PMID: 32244671 DOI: 10.3390/polym12040772

The goal of this study was to develop and statistically optimize the metronidazole (MET), chitosan (CS) and alginate (Alg) nanoparticles (NP) nanocomposites (MET-CS-AlgNPs) using a (21 × 31 × 21) × 3 = 36 full factorial design (FFD) to investigate the effect of chitosan and alginate polymer concentrations and calcium chloride (CaCl2) concentration ondrug loading efficiency(LE), particle size and zeta potential. The concentration of CS, Alg and CaCl2 were taken as independent variables, while drug loading, particle size and zeta potential were taken as dependent variables. The study showed that the loading efficiency and particle size depend on the CS, Alg and CaCl2 concentrations, whereas zeta potential depends only on the Alg and CaCl2 concentrations. The MET-CS-AlgNPs nanocomposites were characterized by X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), thermal gravimetric analysis (TGA), scanning electron microscopy (SEM) and in vitro drug release studies. XRD datashowed that the crystalline properties of MET changed to an amorphous-like pattern when the nanocomposites were formed.The XRD pattern of MET-CS-AlgNPs showed reflections at 2θ = 14.2° and 22.1°, indicating that the formation of the nanocompositesprepared at the optimum conditions havea mean diameter of (165±20) nm, with a MET loading of (46.0 ± 2.1)% and a zeta potential of (-9.2 ± 0.5) mV.The FTIR data of MET-CS-AlgNPs showed some bands of MET, such as 3283, 1585 and 1413 cm-1, confirming the presence of the drug in the MET-CS-AlgNPs nanocomposites. The TGA for the optimized sample of MET-CS-AlgNPs showed a 70.2% weight loss compared to 55.3% for CS-AlgNPs, and the difference is due to the incorporation of MET in the CS-AlgNPs for the formation of MET-CS-AlgNPs nanocomposites. The release of MET from the nanocomposite showed sustained-release properties, indicating the presence of an interaction between MET and the polymer. The nanocomposite shows a smooth surface and spherical shape. The release profile of MET from its MET-CS-AlgNPs nanocomposites was found to be governed by the second kinetic model (R2 between 0.956-0.990) with more than 90% release during the first 50 h, which suggests that the release of the MET drug can be extended or prolonged via the nanocomposite formulation.

Matched MeSH terms: Goals
Arrhythmia detection using deep convolutional neural network with long duration ECG signals

Yıldırım Ö, Pławiak P, Tan RS, Acharya UR

Comput Biol Med, 2018 11 01;102:411-420.
PMID: 30245122 DOI: 10.1016/j.compbiomed.2018.09.009

This article presents a new deep learning approach for cardiac arrhythmia (17 classes) detection based on long-duration electrocardiography (ECG) signal analysis. Cardiovascular disease prevention is one of the most important tasks of any health care system as about 50 million people are at risk of heart disease in the world. Although automatic analysis of ECG signal is very popular, current methods are not satisfactory. The goal of our research was to design a new method based on deep learning to efficiently and quickly classify cardiac arrhythmias. Described research are based on 1000 ECG signal fragments from the MIT - BIH Arrhythmia database for one lead (MLII) from 45 persons. Approach based on the analysis of 10-s ECG signal fragments (not a single QRS complex) is applied (on average, 13 times less classifications/analysis). A complete end-to-end structure was designed instead of the hand-crafted feature extraction and selection used in traditional methods. Our main contribution is to design a new 1D-Convolutional Neural Network model (1D-CNN). The proposed method is 1) efficient, 2) fast (real-time classification) 3) non-complex and 4) simple to use (combined feature extraction and selection, and classification in one stage). Deep 1D-CNN achieved a recognition overall accuracy of 17 cardiac arrhythmia disorders (classes) at a level of 91.33% and classification time per single sample of 0.015 s. Compared to the current research, our results are one of the best results to date, and our solution can be implemented in mobile devices and cloud computing.

Matched MeSH terms: Goals
Fulltext Impact of intrapersonal and interpersonal emotional intelligence and self-directed learning on academic performance among pre-university science students

Okwuduba EN, Nwosu KC, Okigbo EC, Samuel NN, Achugbu C

Heliyon, 2021 Mar;7(3):e06611.
PMID: 33869848 DOI: 10.1016/j.heliyon.2021.e06611

Provision of equitable access to university education is the primary goal of pre-university education. Academically weak students stand to benefit more from pre-university program. However, available literature on effectiveness of the program revealed that high percentage of students still fail pre-university courses. Although the role of psycho-emotional factors on student academic performance has been highlighted, mechanism through which psycho-emotional factors impact on academic performance of pre-university science students is still not clear to offer adequate insights for proper intervention program. Therefore, we examined the pre-university students' academic performance in sciences in relation to Emotional Intelligence (EI) (Interpersonal EI and Intrapersonal EI) and Self-directed Learning (SDL). Specifically, a correlational study design was conducted to measure and gauge the level of relationships amongst Interpersonal EI, Intrapersonal EI, SDL and academic performance of pre-university students. The participants were 443 Nigerian students enrolled in pre-university science program. Students' self-report on EI and SDL were gathered and analyzed using SPSS 26 and AMOS 24. Exploratory and confirmatory factor analysis were performed to determine cross-cultural validity of the instruments in the Nigerian context. After controlling for gender and age, the hierarchical regression analysis reveals that student academic performance was positively predicted by perceived Interpersonal and Intrapersonal EI, whereas self-directed learning has an inconsistent predictive impact at different steps in the model. Overall, the predictor variables were able to explain substantial proportion of students' academic performance in pre-university program. Insightful suggestions were made.

Matched MeSH terms: Goals
Fulltext Fracture resistance tests validation: a survey of literature review

Ahmad Mahmood, Aws H. Ali Al-Kadhim, Zaripah Wan Bakar, Adam Husein

Malaysian Dental Journal, 2011;32(1):12-16.
MyJurnal

Evaluation of the mechanical behaviour of restoration dental materials is essential to understand their performance under different load conditions and to estimate their durability under clinical oral function. Restorative materials and dental tissues like other materials by having specific mechanical properties, such as static strength (i.e. compressive strength, tensile strength, flexural strength) and dynamic strength (i.e. fatigue strength). The selection of proper mechanical test type depends on the goals that the study claims to define. On such basis, the mechanical test can be chosen correctly. Laboratory studies should be designed as replications of the clinical oral circumstances to measure the mechanical and physical properties of a material and any arbitrary choices in the design of the study may result in large variations of data.

Matched MeSH terms: Goals
Parkinson's disease: Cause factors, measurable indicators, and early diagnosis

Bhat S, Acharya UR, Hagiwara Y, Dadmehr N, Adeli H

Comput Biol Med, 2018 11 01;102:234-241.
PMID: 30253869 DOI: 10.1016/j.compbiomed.2018.09.008

Parkinson's disease (PD) is a neurodegenerative disease of the central nervous system caused due to the loss of dopaminergic neurons. It is classified under movement disorder as patients with PD present with tremor, rigidity, postural changes, and a decrease in spontaneous movements. Comorbidities including anxiety, depression, fatigue, and sleep disorders are observed prior to the diagnosis of PD. Gene mutations, exposure to toxic substances, and aging are considered as the causative factors of PD even though its genesis is unknown. This paper reviews PD etiologies, progression, and in particular measurable indicators of PD such as neuroimaging and electrophysiology modalities. In addition to gene therapy, neuroprotective, pharmacological, and neural transplantation treatments, researchers are actively aiming at identifying biological markers of PD with the goal of early diagnosis. Neuroimaging modalities used together with advanced machine learning techniques offer a promising path for the early detection and intervention in PD patients.

Matched MeSH terms: Goals
Fulltext Smart and Climate-Smart Agricultural Trends as Core Aspects of Smart Village Functions

Adesipo A, Fadeyi O, Kuca K, Krejcar O, Maresova P, Selamat A, et al.

Sensors (Basel), 2020 Oct 22;20(21).
PMID: 33105622 DOI: 10.3390/s20215977

Attention has shifted to the development of villages in Europe and other parts of the world with the goal of combating rural-urban migration, and moving toward self-sufficiency in rural areas. This situation has birthed the smart village idea. Smart village initiatives such as those of the European Union is motivating global efforts aimed at improving the live and livelihood of rural dwellers. These initiatives are focused on improving agricultural productivity, among other things, since most of the food we eat are grown in rural areas around the world. Nevertheless, a major challenge faced by proponents of the smart village concept is how to provide a framework for the development of the term, so that this development is tailored towards sustainability. The current work examines the level of progress of climate smart agriculture, and tries to borrow from its ideals, to develop a framework for smart village development. Given the advances in technology, agricultural development that encompasses reduction of farming losses, optimization of agricultural processes for increased yield, as well as prevention, monitoring, and early detection of plant and animal diseases, has now embraced varieties of smart sensor technologies. The implication is that the studies and results generated around the concept of climate smart agriculture can be adopted in planning of villages, and transforming them into smart villages. Hence, we argue that for effective development of the smart village framework, smart agricultural techniques must be prioritized, viz-a-viz other developmental practicalities.

Matched MeSH terms: Goals
Fulltext Insights into an Award-Winning Summer Internship Program: The First Six Years

Kashou A, Durairajanayagam D, Agarwal A

World J Mens Health, 2016 Apr;34(1):9-19.
PMID: 27169124 DOI: 10.5534/wjmh.2016.34.1.9

Since its inception in 2008, the American Center for Reproductive Medicine's summer internship program in reproductive research and writing has trained 114 students from 23 states within the United States and 10 countries worldwide. Its fundamental goal is to inspire pre-medical and medical students to embrace a career as a physician-scientist. During this intensive course, established scientists and clinicians train interns in the essential principles and fundamental concepts of bench research and scientific writing. Over the first six years (2008~2013), interns have collectively published 98 research articles and performed 12 bench research projects on current and emerging topics in reproductive medicine. Interns have also developed and honed valuable soft skills including time management, communication and presentation skills, as well as life values, which all enhance personal and professional satisfaction. Program graduates are able to recognize the value of medical research and its potential to impact patient care and gain insight into their own career pathway. Between 2011 and 2014, the internship program was thrice awarded a Scholarship in Teaching Award by Case Western Reserve School of Medicine for its innovative teaching approach and positive impact on medical education and student careers. This report highlights the demographics, logistics, implementation, feedback, and results of the first six years of the American Center for Reproductive Medicine's summer internship program at Cleveland Clinic (Cleveland, OH, USA). This may be helpful to other research and academic institutions considering implementing a similar program. In addition, it creates awareness among potential physician-scientists of what the world of research has to offer in both scientific writing and bench research. Finally, it may stimulate further discussion regarding narrowing the gap between physicians and scientists and refinement of the current program.

Matched MeSH terms: Goals
Fulltext Development of spark program in 11 years old children : a pilot study

Nurul Diyana Sanuddin, Ahmad Bin Hashim

Jurnal Sains Sukan & Pendidikan Jasmani, 2018;7(1):46-52.
MyJurnal

The development of SPARK (Sport Play Active and Recreation for Kids) program is an effort to improve physical fitness activities among school children. In addition, the development of this program is planned and systematic activity that will help children express ideas freely, especially in the Physical Education or during Co-curriculum activities. In this study, the validity of the SPARK program is based on the Sidek & Jamaludin (2005) module. The SPARK (Sports Play Active and Recreation for Kids) content creation process begins with the goal and concludes with a draft union. In the initial stages of the content development, researchers determine the purpose and objective of this program. Besides that, Researchers determine the appropriate types of activities are applied to enhance the physical fitness activities for the students. Therefore, the development of the SPARK program is through two phases, namely program construction and validity of content. Therefore, the results of the expert assessment on SPARK (Sport Play Active and Recreation for Kids) program content have a high content legality value of .78. This value can be explained that the SPARK program (Sport Play Active and Recreation for Kids) is highly relevant to the learning and teaching process for Physical Education subjects, co-curricular activities and it is ideal use in this research. In conclusion, the program is expected to provide opportunities for children to undergo natural learning through cognitive social theories that contribute to the learning and teaching process for Physical and Health Education subjects to see the impact on the involvement of children's physical activity.

Matched MeSH terms: Goals
Fulltext A Secure, Intelligent, and Smart-Sensing Approach for Industrial System Automation and Transmission over Unsecured Wireless Networks

Shahzad A, Lee M, Xiong NN, Jeong G, Lee YK, Choi JY, et al.

Sensors (Basel), 2016;16(3).
PMID: 26950129 DOI: 10.3390/s16030322

In Industrial systems, Supervisory control and data acquisition (SCADA) system, the pseudo-transport layer of the distributed network protocol (DNP3) performs the functions of the transport layer and network layer of the open systems interconnection (OSI) model. This study used a simulation design of water pumping system, in-which the network nodes are directly and wirelessly connected with sensors, and are monitored by the main controller, as part of the wireless SCADA system. This study also intends to focus on the security issues inherent in the pseudo-transport layer of the DNP3 protocol. During disassembly and reassembling processes, the pseudo-transport layer keeps track of the bytes sequence. However, no mechanism is available that can verify the message or maintain the integrity of the bytes in the bytes received/transmitted from/to the data link layer or in the send/respond from the main controller/sensors. To properly and sequentially keep track of the bytes, a mechanism is required that can perform verification while bytes are received/transmitted from/to the lower layer of the DNP3 protocol or the send/respond to/from field sensors. For security and byte verification purposes, a mechanism needs to be proposed for the pseudo-transport layer, by employing cryptography algorithm. A dynamic choice security buffer (SB) is designed and employed during the security development. To achieve the desired goals of the proposed study, a pseudo-transport layer stack model is designed using the DNP3 protocol open library and the security is deployed and tested, without changing the original design.

Matched MeSH terms: Goals
Fulltext Complex Chemical Data Classification and Discrimination Using Locality Preserving Partial Least Squares Discriminant Analysis

Aminu M, Ahmad NA

ACS Omega, 2020 Oct 20;5(41):26601-26610.
PMID: 33110988 DOI: 10.1021/acsomega.0c03362

Partial least squares discriminant analysis (PLS-DA) is a well-known technique for feature extraction and discriminant analysis in chemometrics. Despite its popularity, it has been observed that PLS-DA does not automatically lead to extraction of relevant features. Feature learning and extraction depends on how well the discriminant subspace is captured. In this paper, discriminant subspace learning of chemical data is discussed from the perspective of PLS-DA and a recent extension of PLS-DA, which is known as the locality preserving partial least squares discriminant analysis (LPPLS-DA). The objective is twofold: (a) to introduce the LPPLS-DA algorithm to the chemometrics community and (b) to demonstrate the superior discrimination capabilities of LPPLS-DA and how it can be a powerful alternative to PLS-DA. Four chemical data sets are used: three spectroscopic data sets and one that contains compositional data. Comparative performances are measured based on discrimination and classification of these data sets. To compare the classification performances, the data samples are projected onto the PLS-DA and LPPLS-DA subspaces, and classification of the projected samples into one of the different groups (classes) is done using the nearest-neighbor classifier. We also compare the two techniques in data visualization (discrimination) task. The ability of LPPLS-DA to group samples from the same class while at the same time maximizing the between-class separation is clearly shown in our results. In comparison with PLS-DA, separation of data in the projected LPPLS-DA subspace is more well defined.

Matched MeSH terms: Goals
Fulltext Factors influencing functional outcome of Philos Plate fixation for proximal humerus fractures

Hazwan Ab. Wahid, Khairul Nizam bin Siron, Ahmad Zakiran

International Medical Journal Malaysia, 2017;16(11):42-42.
MyJurnal

Displaced and unstable proximal humerus fractures are difficult to treat
and they have high morbidity. The main goal is to achieve painless shoulder with full
recovery of the shoulder joint motion. Impingement syndrome is one of the commonest
postoperative complication. This study aim is to appreciate the functional outcomes of
Philos-plate fixation for proximal humerus fractures and to establish association with
high plate positioning with impingement syndrome of the shoulder after Philos-plate
fixation. (Copied from article).

Matched MeSH terms: Goals
Fulltext The applicability of social cognitive career theory in predicting life satisfaction of university students: A meta-analytic path analysis

Mohd Rasdi R, Ahrari S

PLoS One, 2020;15(8):e0237838.
PMID: 32822400 DOI: 10.1371/journal.pone.0237838

Derived from the social cognitive career theory (SCCT), the present study developed a model for the empirical examination of factors affecting the life satisfaction of university students. A random-effects meta-analysis of zero-order correlations observed the results of 16 studies (20 samples, n = 7,967), and associations among the SCCT variables were examined by using a meta-analytic structural equation modeling (MASEM) according to a pooled correlation matrix. An alternative model was offered and then assessed. The findings showed a satisfactory fit of the new model as compared to the original SCCT. The results demonstrated support for the alternative model of SCCT in predicting life satisfaction. The present study suggested that researchers should embrace this alternative model when synthesizing SCCT factors. Limitations and avenues for future research were put forward for further consideration.

Matched MeSH terms: Goals
Fulltext Development and implementation of a potential coronavirus disease 2019 (COVID-19) vaccine: A systematic review and meta-analysis of vaccine clinical trials

Sathian B, Asim M, Banerjee I, Roy B, Pizarro AB, Mancha MA, et al.

Nepal J Epidemiol, 2021 Mar;11(1):959-982.
PMID: 33868742 DOI: 10.3126/nje.v11i1.36163

Background: To date, there is no comprehensive systematic review and meta-analysis to assess the suitability of COVID-19 vaccines for mass immunization. The current systematic review and meta-analysis was conducted to evaluate the safety and immunogenicity of novel COVID-19 vaccine candidates under clinical trial evaluation and present a contemporary update on the development and implementation of a potential vaccines.
Methods: For this study PubMed, MEDLINE, and Embase electronic databases were used to search for eligible studies on the interface between novel coronavirus and vaccine design until December 31, 2020.
Results: We have included fourteen non-randomized and randomized controlled phase I-III trials. Implementation of a universal vaccination program with proven safety and efficacy through robust clinical evaluation is the long-term goal for preventing COVID-19. The immunization program must be cost-effective for mass production and accessibility. Despite pioneering techniques for the fast-track development of the vaccine in the current global emergency, mass production and availability of an effective COVID-19 vaccine could take some more time.
Conclusion: Our findings suggest a revisiting of the reported solicited and unsolicited systemic adverse events for COVID-19 candidate vaccines. Hence, it is alarming to judiciously expose thousands of participants to COVID-19 candidate vaccines at Phase-3 trials that have adverse events and insufficient evidence on safety and effectiveness that necessitates further justification.

Matched MeSH terms: Goals
Fulltext Properties and Applications of Polyvinyl Alcohol, Halloysite Nanotubes and Their Nanocomposites

Gaaz TS, Sulong AB, Akhtar MN, Kadhum AA, Mohamad AB, Al-Amiery AA

Molecules, 2015;20(12):22833-47.
PMID: 26703542 DOI: 10.3390/molecules201219884

The aim of this review was to analyze/investigate the synthesis, properties, and applications of polyvinyl alcohol-halloysite nanotubes (PVA-HNT), and their nanocomposites. Different polymers with versatile properties are attractive because of their introduction and potential uses in many fields. Synthetic polymers, such as PVA, natural polymers like alginate, starch, chitosan, or any material with these components have prominent status as important and degradable materials with biocompatibility properties. These materials have been developed in the 1980s and are remarkable because of their recyclability and consideration of the natural continuation of their physical and chemical properties. The fabrication of PVA-HNT nanocomposites can be a potential way to address some of PVA's limitations. Such nanocomposites have excellent mechanical properties and thermal stability. PVA-HNT nanocomposites have been reported earlier, but without proper HNT individualization and PVA modifications. The properties of PVA-HNT for medicinal and biomedical use are attracting an increasing amount of attention for medical applications, such as wound dressings, drug delivery, targeted-tissue transportation systems, and soft biomaterial implants. The demand for alternative polymeric medical devices has also increased substantially around the world. This paper reviews individualized HNT addition along with crosslinking of PVA for various biomedical applications that have been previously reported in literature, thereby showing the attainability, modification of characteristics, and goals underlying the blending process with PVA.

Matched MeSH terms: Goals

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