Dimensionality reduction plays a pivotal role in preparing high-dimensional data for classification and discrimination tasks by eliminating redundant features and enhancing the efficiency of classifiers. The effectiveness of a dimensionality reduction algorithm hinges on its numerical stability. When data projections are numerically stable, they lead to enhanced class separability in the lower-dimensional embedding, consequently yielding higher classification accuracy. This paper investigates the numerical attributes of dimensionality reduction and discriminant subspace learning, with a specific focus on Locality-Preserving Partial Least Squares Discriminant Analysis (LPPLS-DA). High-dimensional data frequently introduce singularity in the scatter matrices, posing a significant challenge. To tackle this issue, the paper explores two robust implementations of LPPLS-DA. These approaches not only optimize data projections but also capture more discriminative features, resulting in a marked improvement in classification accuracy. Empirical evidence supports these findings through numerical experiments conducted on synthetic and spectral datasets. The results demonstrate the superior performance of the proposed methods when compared to several state-of-the-art dimensionality reduction techniques in terms of both classification accuracy and dimension reduction.
An efficient and computationally linear algorithm is derived for total least squares solution of adaptive filtering problem, when both input and output signals are contaminated by noise. The proposed total least mean squares (TLMS) algorithm is designed by recursively computing an optimal solution of adaptive TLS problem by minimizing instantaneous value of weighted cost function. Convergence analysis of the algorithm is given to show the global convergence of the proposed algorithm, provided that the stepsize parameter is appropriately chosen. The TLMS algorithm is computationally simpler than the other TLS algorithms and demonstrates a better performance as compared with the least mean square (LMS) and normalized least mean square (NLMS) algorithms. It provides minimum mean square deviation by exhibiting better convergence in misalignment for unknown system identification under noisy inputs.
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.
Wireless local area networks (WLAN)-fingerprinting has been highlighted as the preferred technology for indoor positioning due to its accurate positioning and minimal infrastructure cost. However, its accuracy is highly influenced by obstacles that cause fluctuation in the signal strength. Many researchers have modeled static obstacles such as walls and ceilings, but few studies have modeled the people's presence effect (PPE), although the human body has a great impact on signal strength. Therefore, PPE must be addressed to obtain accurate positioning results. Previous research has proposed a model to address this issue, but these studies only considered the direct path signal between the transmitter and the receiver whereas multipath effects such as reflection also have a significant influence on indoor signal propagation. This research proposes an accurate indoor-positioning model by considering people's presence and multipath using ray-tracing, we call it (AIRY). This study proposed two solutions to construct AIRY: an automatic radio map using ray tracing and a constant of people's effect for the received signal strength indicator (RSSI) adaptation. The proposed model was simulated using MATLAB software and tested at Level 3, Menara Razak, Universiti Teknologi Malaysia. A K-nearest-neighbor (KNN) algorithm was used to define a position. The initial accuracy was 2.04 m, which then reduced to 0.57 m after people's presence and multipath effects were considered.
The study examines the psychometric properties of the adapted Schutte Emotional Intelligence Scale (A-SEIS) with 200 undergraduate students at the Universiti Putra Malaysia (UPM). Upon the permission, the researchers adapted the original instrument, SEIS by incorporating a new construct which is understanding of emotions and some ability-based items into the perceived emotions construct. The A-SEIS is a mixed (trait and ability) measure EI instrument that aims at assessing four important dimensions of EI, including perception of emotions, utilization of emotions, understanding of emotions, and management of emotions. The study investigated the content validity of the A-SEIS by using the content validity indexing (CVI). Three expert panels translated and back-translated the A-SEIS and rated the degree of relevance of every item based on the four-point scale provided in the content validation form. The exploratory factor analysis (EFA) methods were used to explore the underlying structure of the A-SEIS. The general validity testing of the adapted instrument was carried out in the framework of the structural equation modeling (SEM) approach by applying two iterations of confirmatory factor analysis (CFA), the first approach is the covariance-based SEM (CB-SEM) approach, followed by the partial least squares based SEM (PLS-SEM) using two different software: AMOS and smartPLS. Research findings concluded that the instrument is reliable and valid to be applied in tertiary education settings and future research.
Stimuli responsive hydrogels have shown enormous potential as a carrier for targeted drug delivery. In this study we have developed novel pH responsive hydrogels for the delivery of 5-fluorouracil (5-FU) in order to alleviate its antitumor activity while reducing its toxicity. We used 2-(methacryloyloxyethyl) trimetylammonium chloride a positively charged monomer and methacrylic acid for fabricating the pH responsive hydrogels. The released 5-FU from all except hydrogel (GEL-5) remained biologically active against human colon cancer cell lines [HT29 (IC50 = 110-190 μg ml(-1)) and HCT116 (IC50 = 210-390 μg ml(-1))] but not human skin fibroblast cells [BJ (CRL2522); IC50 ≥ 1000 μg ml(-1)]. This implies that the copolymer hydrogels (1-4) were able to release 5-FU effectively to colon cancer cells but not normal human skin fibroblast cells. This is probably due to the shorter doubling time that results in reduced pH in colon cancer cells when compared to fibroblast cells. These pH sensitive hydrogels showed well defined cell apoptosis in HCT116 cells through series of events such as chromatin condensation, membrane blebbing, and formation of apoptotic bodies. No cell killing was observed in the case of blank hydrogels. The results showed the potential of these stimuli responsive polymer hydrogels as a carrier for colon cancer delivery.
Although non-sporulating molds (NSM) are frequently isolated from patients and have been recognized as agents of pulmonary disease, their clinical significance in cutaneous specimens is relatively unknown. Therefore, this study aimed to identify NSM and to determine the keratinolytic activity of isolates from cutaneous sites. NSM isolates from clinical specimens such as skin, nail, and body fluids were identified based on their ribosomal DNA sequences. Of 17 NSM isolates (7 Ascomycota, 10 Basidiomycota), eleven were identified to species level while five were identified to the genus level. These include Schizophyllum commune, a known human pathogen, Phoma multirostrata, a plant pathogen, and Perenniporia tephropora, a saprophyte. To determine fungal pathogenicity, keratinolytic activity, a major virulence factor, was evaluated ex vivo using human nail samples by measuring dye release from keratin azure, for NSM along with pathogens (Trichophyton mentagrophytes, Trichophyton rubrum, Microsporum canis and Fusarium spp.) and nonpathogenic (endophyte) fungi for comparison. This study showed that pathogenic fungi had the highest keratinolytic activity (7.13 ± 0.552 keratinase units) while the nonpathogenic endophytes had the lowest activity (2.37 ± 0.262 keratinase units). Keratinolytic activity of two Ascomycota NSM (Guignardia mangiferae and Hypoxylon sp.) and one Basidiomycota NSM (Fomitopsis cf. meliae) was equivalent to that of pathogenic fungi, while Xylaria feejeensis showed significantly higher activity (p
Aptamers are short oligonucleotides that possess high specificity and affinity against their target. Generated via Systematic Evolution of Ligands by Exponential Enrichment, (SELEX) in vitro, they were screened and enriched. This review covering the study utilizing bioinformatics tools to analyze primary sequence, secondary and tertiary structure prediction, as well as docking simulation for various aptamers and their ligand interaction. Literature was pooled from Web of Science (WoS) and Scopus databases until December 18, 2020 using specific search string related to DNA aptamers, in silico, structure prediction, and docking simulation. Out of 330 published articles, 38 articles were assessed in the analysis based on the predefined inclusion and exclusion criteria. It was found that Mfold and RNA Composer web server is the most popular tool in secondary and tertiary structure prediction of DNA aptamers, respectively. Meanwhile, in docking simulation, ZDOCK and AutoDock are preferred to analyze binding interaction in the aptamer-ligand complex. This review reports a brief framework of recent developments of in silico approaches that provide predictive structural information of ssDNA aptamer.
BACKGROUND Trichoblastoma is a rare, benign, cutaneous adnexal neoplasm arising from rudimentary hair follicles. The incidence and prevalence in the general population is unknown. However, most cases occur in adults aged 40 years and older. CASE REPORT A 62-year-old woman presented to our primary care clinic for a hypertension and diabetes followup visit. The doctor, who had never seen the patient before, noticed several small lumps over the patient's eyebrows. After she removed her headscarf and face mask for a thorough examination, numerous skin-colored papules and nodules were seen on her nose, nasal bridge, forehead, and around her eyebrows. She was referred to a dermatologist, and a skin biopsy showed well-circumscribed dermal nests of basaloid cells, with peripheral palisading, and keratin horn cysts surrounded by dense fibrous stroma. These features were consistent with trichoblastoma. She was then referred to a plastic surgeon to discuss further management options. The patient finally chose laser ablation as she was fearful of the other more invasive surgical options. CONCLUSIONS This is a very rare case of extensive facial trichoblastoma. It highlights the need for clinicians to ensure optimal exposure when examining patients. It also highlights the role of biopsies for skin lesions of uncertain etiology. In this case, it helped to rule out basal cell carcinoma, which can be a more locally destructive condition than trichoblastoma. This case also serves as a reminder about the need for ongoing review and referral for further management for conditions for which previous treatment was unsuccessful.
The Global Positioning System demonstrates the significance of Location Based Services but it cannot be used indoors due to the lack of line of sight between satellites and receivers. Indoor Positioning Systems are needed to provide indoor Location Based Services. Wireless LAN fingerprints are one of the best choices for Indoor Positioning Systems because of their low cost, and high accuracy, however they have many drawbacks: creating radio maps is time consuming, the radio maps will become outdated with any environmental change, different mobile devices read the received signal strength (RSS) differently, and peoples' presence in LOS between access points and mobile device affects the RSS. This research proposes a new Adaptive Indoor Positioning System model (called DIPS) based on: a dynamic radio map generator, RSS certainty technique and peoples' presence effect integration for dynamic and multi-floor environments. Dynamic in our context refers to the effects of people and device heterogeneity. DIPS can achieve 98% and 92% positioning accuracy for floor and room positioning, and it achieves 1.2 m for point positioning error. RSS certainty enhanced the positioning accuracy for floor and room for different mobile devices by 11% and 9%. Then by considering the peoples' presence effect, the error is reduced by 0.2 m. In comparison with other works, DIPS achieves better positioning without extra devices.
Although industrialisation is a crucial aspect of economic growth across developing nations, through the release of air contaminants, industrial activities may also create adverse environmental health consequences. Noting that continuous production and other economic activities are crucial for continued survival, this study explores this issue by including the role of governance that is deemed essential but the literature is relatively sparse particularly in the context of developing countries. This research empirically analyses the relationship between air pollution and adult mortality rates from 72 developing countries from the period of 2010 until 2017. Particulate matter (PM2.5) and carbon dioxide (CO2) are used as indicators of air pollution. From the generalized method of moments (GMM) estimations, the results reveal that air pollution negatively affects adult mortality rate. The result reveals that a 10% increase in the PM2.5 level induces the adult mortality rates to increase between 0.04% and 0.06%. In addition, the government significantly moderates the negative effect of air pollution on adult mortality, whereby a one-unit enhancement in governance quality index reduces mortality among the adults in the developing countries by 0.01%. On the other hand, CO2 emission also appears to be positive, but not statistically significant. The results suggest that governance and public health interplay in the sense of a transition towards economic development for improved living and health states can be achievable with improved governance quality.
While studies have demonstrated that air pollution can be catastrophic to the population's health, few empirical studies are found in the economic literature because a considerable proportion of the evidence comes from epidemiological studies. Because of the crucial role of governance in the health community, good governance has been a contentious issue in public sector management in recent years. Therefore, the aim of this study is to examine the effects of air pollution and the role of governance on health outcomes. This study employed the generalized method of moment (GMM) estimation techniques to analyse panel data for 72 developing countries from 2010 to 2017. The empirical results confirm that higher PM2.5 and CO2 levels have a detrimental influence on life expectancy and healthy life expectancy, whereas the role of governance has a positive impact on life expectancy and healthy life expectancy. Furthermore, the findings show governance quality plays a role in moderating the negative effect of PM2.5 on health outcomes. The ongoing rise in air pollution has had a significant impact on the health of developing countries. It appears that governance quality has improved health outcomes. The findings have important policy implications, such that strengthening governance can reduce air pollution emissions in developing countries. However, to reduce the health effects of air pollution, developing countries must implement effective environmental development policies and track the implementation and enforcement of such policies.
The complex nature of coaching challenges instructional coaches (ICs) professionally as it requires them to deal with not only teachers' resistance, acceptance and expectation but also adhere to the complex and multifaceted roles that they are bearing. Psychological capital (PsyCap) has been upheld as an effective construct for defending against stress, negative emotions and burnout among educators. This phenomenological study explores ways in which PsyCap was experienced by Malaysian instructional coaches (ICs). Data were gathered from face-to-face interviews with seven instructional coaches purposefully selected from six different District Education Offices (DEOs) throughout Malaysia. Extracted from participants' own words and through the exploration performed, PsyCap was experienced by the participants through a sense of responsibility, positive resources and work commitment. This study highlights the importance of PsyCap as inner positive psychological resources that aided instructional coaches in their practice of coaching. In addition, this study suggests future research recommendations towards implementing PsyCap developmental training with another group of instructional coaches.
The effectiveness of the autopsy as an educational tool in forensic medicine courses has been widely acknowledged, and medical students were expected to attend regularly. Nevertheless, the use of autopsies for teaching has dramatically declined in recent years and worldwide despite their high-value benefits. This study aims to understand the importance and relevance of attending autopsies during forensic teaching sessions and identify any challenges that may impede attendance. A self-administered online questionnaire that assesses the knowledge, attitudes, and practices related to autopsies attendance was distributed to fourth-year medical students at the National Defence University of Malaysia and Universiti Sains Islam Malaysia. A total of 99 respondents were involved in this study. Our findings indicate that most respondents (over 85%) demonstrated good knowledge of forensic medicine. Pearson's statistical test revealed a significant correlation between the knowledge and students' attitudes toward autopsy. This study demonstrates the need to strategically integrate autopsy attendance into medical curricula to encourage constructive attitudes and practices among medical students. Students gain the most benefits from frequently attending autopsies. Passionate educators can conduct preparatory sessions to set expectations and address concerns, encourage students to process their experiences, and reinforce learning outcomes in the mortuary setting. Mandatory autopsy teaching should be integrated into the curriculum to ensure medical students have the necessary skills and knowledge to become competent doctors.
The National School-Based Health Survey 2012 was a nationwide school health survey of students in Standard 4 to Form 5 (10-17 years of age), who were schooling in government schools in Malaysia during the period of data collection. The survey comprised 3 subsurveys: the Global School Health Survey (GSHS), the Mental Health Survey, and the National School-Based Nutrition Survey. The aim of the survey was to provide data on the health status of adolescents in Malaysia toward strengthening the adolescent health program in the country. The design of the survey was created to fulfill the requirements of the 3 subsurveys. A 2-stage stratified sampling method was adopted in the sampling. The methods for data collection were via questionnaire and physical examination. The National School-Based Health Survey 2012 adopted an appropriate methodology for a school-based survey to ensure valid and reliable findings.
Study name: Global School-Based Student Health Survey (GSHS)
Three specific orthodontic tooth movement genes, that is, FCRL1, HSPG2, and LAMB2 were detected at upper first premolar (with appliance) dental pulp tissue by using GeneFishing technique as compared to lower first premolar (without appliance). These three differentially expressed genes have the potential as molecular markers during orthodontic tooth movement by looking at molecular changes of pulp tissue.
An 11-year-old girl presented with multiple blisters on her the right foot complicated with cellulitis. The conventional and molecular identification were performed on the culture. The internal transcribed spacer (ITS) region in rRNA gene of the isolate was amplified by PCR. The sequence of the amplified ITS region matched 99 % with that of Chaetomium globosum in the GenBank. This is the first report describing C. globosum causing cutaneous infection in Malaysia.
Coronavirus 2019 (COVID-19) has globally affected the human mortality rate and economic history of the modern world. According to the World Health Organization, COVID-19 has caused a severe threat to the health of the vulnerable groups, notably the elderly. There is still some disagreements regarding the source of the virus and its intermediate host. However, the spread of this disease has caused most countries to enforce strict curfew laws and close most industrial and recreational centres. This study aims to show the potential positive effects of COVID-19 on the environment and the increase of renewable energy generation in Malaysia. To prevent the spread of this disease, Malaysia enacted the Movement Control Order (MCO) law in March 2020. Implementation of this law led to a reduction in environmental pollution, especially air pollution, in this country. The greenhouse gases (GHG) emission , which was 8 Mt CO2 eq. from January 2020 to March 2020, reduced to <1 Mt CO2 eq. for April and May. The reduction of GHG emission and pollutant gases allowed more sunlight to reach photovoltaic panels, hence increasing the renewable energy generation.
The antiradical efficiency (AE) and kinetic behavior of a new ferulate-based protic ionic liquids (PILs) were described using 2,2-diphenyl-1-picrylhydrazyl (DPPH) free radical assay. The reduction of the DPPH free radical (DPPH•) was investigated by measuring the decrease in absorbance at 517 nm. The time to reach steady state for the reaction of parent acid (ferulic acid) and synthesized PILs with DPPH• was continuously recorded for 1 h. Results revealed that the AE of 2-butylaminoethanol ferulate (2BAEF), 3-dimethylaminopropanol ferulate (3DMAPF) and 3-diethylaminopropanol ferulate (3DEAPF) PILs have improved compared to ferulic acid (FA) as the reaction class changes from low to medium. This attributed to the strong hydrogen abstraction occurred in the PILs. Furthermore, these PILs were found to have a good kinetic behavior compared to FA due to the high rate constant (k₂) (164.17, 242.84 and 244.73 M-1 s-1, respectively). The alkyl chain length and more alkyl substituents on the nitrogen atom of cation were believed to reduce the cation-anion interaction and speed up the hydrogen atom transfer (HAT) and electron transfer (ET) mechanisms; hence, increased rate constant was observed leading to a strong antioxidant activity of the synthesized PILs.