Monash University Malaysia

As a fascinating conjugated polymer, graphitic carbon nitride (g-C3N4) has become a new research hotspot and drawn broad interdisciplinary attention as a metal-free and visible-light-responsive photocatalyst in the arena of solar energy conversion and environmental remediation. This is due to its appealing electronic band structure, high physicochemical stability, and "earth-abundant" nature. This critical review summarizes a panorama of the latest progress related to the design and construction of pristine g-C3N4 and g-C3N4-based nanocomposites, including (1) nanoarchitecture design of bare g-C3N4, such as hard and soft templating approaches, supramolecular preorganization assembly, exfoliation, and template-free synthesis routes, (2) functionalization of g-C3N4 at an atomic level (elemental doping) and molecular level (copolymerization), and (3) modification of g-C3N4 with well-matched energy levels of another semiconductor or a metal as a cocatalyst to form heterojunction nanostructures. The construction and characteristics of each classification of the heterojunction system will be critically reviewed, namely metal-g-C3N4, semiconductor-g-C3N4, isotype g-C3N4/g-C3N4, graphitic carbon-g-C3N4, conducting polymer-g-C3N4, sensitizer-g-C3N4, and multicomponent heterojunctions. The band structures, electronic properties, optical absorption, and interfacial charge transfer of g-C3N4-based heterostructured nanohybrids will also be theoretically discussed based on the first-principles density functional theory (DFT) calculations to provide insightful outlooks on the charge carrier dynamics. Apart from that, the advancement of the versatile photoredox applications toward artificial photosynthesis (water splitting and photofixation of CO2), environmental decontamination, and bacteria disinfection will be presented in detail. Last but not least, this comprehensive review will conclude with a summary and some invigorating perspectives on the challenges and future directions at the forefront of this research platform. It is anticipated that this review can stimulate a new research doorway to facilitate the next generation of g-C3N4-based photocatalysts with ameliorated performances by harnessing the outstanding structural, electronic, and optical properties for the development of a sustainable future without environmental detriment.

Purpose Partial least squares (PLS) has been introduced as a “causal-predictive” approach to structural equation modeling (SEM), designed to overcome the apparent dichotomy between explanation and prediction. However, while researchers using PLS-SEM routinely stress the predictive nature of their analyses, model evaluation assessment relies exclusively on metrics designed to assess the path model’s explanatory power. Recent research has proposed PLSpredict, a holdout sample-based procedure that generates case-level predictions on an item or a construct level. This paper offers guidelines for applying PLSpredict and explains the key choices researchers need to make using the procedure. Design/methodology/approach The authors discuss the need for prediction-oriented model evaluations in PLS-SEM and conceptually explain and further advance the PLSpredict method. In addition, they illustrate the PLSpredict procedure’s use with a tourism marketing model and provide recommendations on how the results should be interpreted. While the focus of the paper is on the PLSpredict procedure, the overarching aim is to encourage the routine prediction-oriented assessment in PLS-SEM analyses. Findings The paper advances PLSpredict and offers guidance on how to use this prediction-oriented model evaluation approach. Researchers should routinely consider the assessment of the predictive power of their PLS path models. PLSpredict is a useful and straightforward approach to evaluate the out-of-sample predictive capabilities of PLS path models that researchers can apply in their studies. Research limitations/implications Future research should seek to extend PLSpredict’s capabilities, for example, by developing more benchmarks for comparing PLS-SEM results and empirically contrasting the earliest antecedent and the direct antecedent approaches to predictive power assessment. Practical implications This paper offers clear guidelines for using PLSpredict, which researchers and practitioners should routinely apply as part of their PLS-SEM analyses. Originality/value This research substantiates the use of PLSpredict. It provides marketing researchers and practitioners with the knowledge they need to properly assess, report and interpret PLS-SEM results. Thereby, this research contributes to safeguarding the rigor of marketing studies using PLS-SEM.

Abstract High-quality and complete reference genome assemblies are fundamental for the application of genomics to biology, disease, and biodiversity conservation. However, such assemblies are available for only a few non-microbial species 1–4 . To address this issue, the international Genome 10K (G10K) consortium 5,6 has worked over a five-year period to evaluate and develop cost-effective methods for assembling highly accurate and nearly complete reference genomes. Here we present lessons learned from generating assemblies for 16 species that represent six major vertebrate lineages. We confirm that long-read sequencing technologies are essential for maximizing genome quality, and that unresolved complex repeats and haplotype heterozygosity are major sources of assembly error when not handled correctly. Our assemblies correct substantial errors, add missing sequence in some of the best historical reference genomes, and reveal biological discoveries. These include the identification of many false gene duplications, increases in gene sizes, chromosome rearrangements that are specific to lineages, a repeated independent chromosome breakpoint in bat genomes, and a canonical GC-rich pattern in protein-coding genes and their regulatory regions. Adopting these lessons, we have embarked on the Vertebrate Genomes Project (VGP), an international effort to generate high-quality, complete reference genomes for all of the roughly 70,000 extant vertebrate species and to help to enable a new era of discovery across the life sciences.

Higher-order constructs, which facilitate modeling a construct on a more abstract higher-level dimension and its more concrete lower-order subdimensions, have become an increasingly visible trend in applications of partial least squares structural equation modeling (PLS-SEM). Unfortunately, researchers frequently confuse the specification, estimation, and validation of higher-order constructs, for example, when it comes to assessing their reliability and validity. Addressing this concern, this paper explains how to evaluate the results of higher-order constructs in PLS-SEM using the repeated indicators and the two-stage approaches, which feature prominently in applied social sciences research. Focusing on the reflective-reflective and reflective-formative types of higher-order constructs, we use the well-known corporate reputation model example to illustrate their specification, estimation, and validation. Thereby, we provide the guidance that scholars, marketing researchers, and practitioners need when using higher-order constructs in their studies.

The notion of dynamic capabilities complements the premise of the resource‐based view of the firm, and has injected new vigour into empirical research in the last decade. Nonetheless, several issues surrounding its conceptualization remain ambivalent. In light of empirical advancement, this paper aims to clarify the concept of dynamic capabilities, and then identify three component factors which reflect the common features of dynamic capabilities across firms and which may be adopted and further developed into a measurement construct in future research. Further, a research model is developed encompassing antecedents and consequences of dynamic capabilities in an integrated framework. Suggestions for future research and managerial implications are also discussed.

This paper reviews the empirical evidence of the effect of credibility of the message source on persuasion over a span of 5 decades, primarily to come up with recommendations for practitioners as to when to use a high‐ or a low‐credibility source and secondarily to identify areas for future research. The main effect studies of source credibility on persuasion seem to indicate the superiority of a high‐credibility source over a low‐credibility one. Interaction effect studies, however, show source credibility to be a liability under certain conditions. The variables found to interact with source credibility are categorized into 5 categories: source, message, channel, receiver, and destination variables. The most heavily researched variables have been the message and receiver variables. Implications for marketers/advertisers and suggestions for future research are discussed.

IMPORTANCE: The Global Burden of Diseases, Injuries, and Risk Factors Study 2019 (GBD 2019) provided systematic estimates of incidence, morbidity, and mortality to inform local and international efforts toward reducing cancer burden. OBJECTIVE: To estimate cancer burden and trends globally for 204 countries and territories and by Sociodemographic Index (SDI) quintiles from 2010 to 2019. EVIDENCE REVIEW: The GBD 2019 estimation methods were used to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life years (DALYs) in 2019 and over the past decade. Estimates are also provided by quintiles of the SDI, a composite measure of educational attainment, income per capita, and total fertility rate for those younger than 25 years. Estimates include 95% uncertainty intervals (UIs). FINDINGS: In 2019, there were an estimated 23.6 million (95% UI, 22.2-24.9 million) new cancer cases (17.2 million when excluding nonmelanoma skin cancer) and 10.0 million (95% UI, 9.36-10.6 million) cancer deaths globally, with an estimated 250 million (235-264 million) DALYs due to cancer. Since 2010, these represented a 26.3% (95% UI, 20.3%-32.3%) increase in new cases, a 20.9% (95% UI, 14.2%-27.6%) increase in deaths, and a 16.0% (95% UI, 9.3%-22.8%) increase in DALYs. Among 22 groups of diseases and injuries in the GBD 2019 study, cancer was second only to cardiovascular diseases for the number of deaths, years of life lost, and DALYs globally in 2019. Cancer burden differed across SDI quintiles. The proportion of years lived with disability that contributed to DALYs increased with SDI, ranging from 1.4% (1.1%-1.8%) in the low SDI quintile to 5.7% (4.2%-7.1%) in the high SDI quintile. While the high SDI quintile had the highest number of new cases in 2019, the middle SDI quintile had the highest number of cancer deaths and DALYs. From 2010 to 2019, the largest percentage increase in the numbers of cases and deaths occurred in the low and low-middle SDI quintiles. CONCLUSIONS AND RELEVANCE: The results of this systematic analysis suggest that the global burden of cancer is substantial and growing, with burden differing by SDI. These results provide comprehensive and comparable estimates that can potentially inform efforts toward equitable cancer control around the world.

The incidence of foodborne diseases has increased over the years and resulted in major public health problem globally. Foodborne pathogens can be found in various foods and it is important to detect foodborne pathogens to provide safe food supply and to prevent foodborne diseases. The conventional methods used to detect foodborne pathogen are time consuming and laborious. Hence, a variety of methods have been developed for rapid detection of foodborne pathogens as it is required in many food analyses. Rapid detection methods can be categorized into nucleic acid-based, biosensor-based and immunological-based methods. This review emphasizes on the principles and application of recent rapid methods for the detection of foodborne bacterial pathogens. Detection methods included are simple polymerase chain reaction (PCR), multiplex PCR, real-time PCR, nucleic acid sequence-based amplification (NASBA), loop-mediated isothermal amplification (LAMP) and oligonucleotide DNA microarray which classified as nucleic acid-based methods; optical, electrochemical and mass-based biosensors which classified as biosensor-based methods; enzyme-linked immunosorbent assay (ELISA) and lateral flow immunoassay which classified as immunological-based methods. In general, rapid detection methods are generally time-efficient, sensitive, specific and labor-saving. The developments of rapid detection methods are vital in prevention and treatment of foodborne diseases.

Partial least squares structural equation modeling (PLS-SEM) has become a standard tool for analyzing complex inter-relationships between observed and latent variables in tourism and numerous other fields of scientific inquiry. Along with the recent surge in the method’s use, research has contributed several complementary methods for assessing the robustness of PLS-SEM results. Although these improvements are documented in extant literature, research on tourism has been slow to adopt the relevant complementary methods. This article illustrates the use of recent advances in PLS-SEM, designed to ensure structural model results’ robustness in terms of nonlinear effects, endogeneity, and unobserved heterogeneity in a PLS-SEM framework. Our overarching aim is to encourage the routine use of these complementary methods to increase methodological rigor in the field.

Increasing environmental awareness coupled with more stringent regulation standards has triggered various industries to challenge themselves in seeking appropriate wastewater treatment technologies. Coagulation–flocculation process is regarded as one of the most important and widely used treatment processes of industrial wastewaters due to its simplicity and effectiveness. This paper provides a critical review on recent studies of coagulation–flocculation treatment processes of various industrial wastewaters. The limitations and challenges for the coagulation–flocculation process such as the toxicity and health hazard posed by inorganic coagulants, production of large amount of toxic sludge, ineffectiveness in removing heavy metals and emerging contaminants, increase in effluent color, inefficient pollutant removal using natural coagulants, and complexity of scaling up procedure are presented. In addition, an overview on the influence of process parameters on treatment efficiency is included in this review. Finally, this review concludes with recommendations for improvements and new directions for this long-established process.

Partial least squares structural equation modeling (PLS-SEM) has become a key method in international marketing research. Users of PLS-SEM have, however, largely overlooked the issue of endogeneity, which has become an integral component of regression analysis applications. This lack of attention is surprising because the PLS-SEM method is grounded in regression analysis, for which numerous approaches for handling endogeneity have been proposed. To identify and treat endogeneity, and create awareness of how to deal with this issue, this study introduces a systematic procedure that translates control variables, instrumental variables, and Gaussian copulas into a PLS-SEM framework. We illustrate the procedure's efficacy by means of empirical data and offer recommendations to guide international marketing researchers on how to effectively address endogeneity concerns in their PLS-SEM analyses.

Interest toward the human microbiome, particularly gut microbiome has flourished in recent decades owing to the rapidly advancing sequence-based screening and humanized gnotobiotic model in interrogating the dynamic operations of commensal microbiota. Although this field is still at a very preliminary stage, whereby the functional properties of the complex gut microbiome remain less understood, several promising findings have been documented and exhibit great potential toward revolutionizing disease etiology and medical treatments. In this review, the interactions between gut microbiota and the host have been focused on, to provide an overview of the role of gut microbiota and their unique metabolites in conferring host protection against invading pathogen, regulation of diverse host physiological functions including metabolism, development and homeostasis of immunity and the nervous system. We elaborate on how gut microbial imbalance (dysbiosis) may lead to dysfunction of host machineries, thereby contributing to pathogenesis and/or progression toward a broad spectrum of diseases. Some of the most notable diseases namely Clostridium difficile infection (infectious disease), inflammatory bowel disease (intestinal immune-mediated disease), celiac disease (multisystemic autoimmune disorder), obesity (metabolic disease), colorectal cancer, and autism spectrum disorder (neuropsychiatric disorder) have been discussed and delineated along with recent findings. Novel therapies derived from microbiome studies such as fecal microbiota transplantation, probiotic and prebiotics to target associated diseases have been reviewed to introduce the idea of how certain disease symptoms can be ameliorated through dysbiosis correction, thus revealing a new scientific approach toward disease treatment. Toward the end of this review, several research gaps and limitations have been described along with suggested future studies to overcome the current research lacunae. Despite the ongoing debate on whether gut microbiome plays a role in the above-mentioned diseases, we have in this review, gathered evidence showing a potentially far more complex link beyond the unidirectional cause-and-effect relationship between them.

Genome sequences from diverse human groups are needed to understand the structure of genetic variation in our species and the history of, and relationships between, different populations. We present 929 high-coverage genome sequences from 54 diverse human populations, 26 of which are physically phased using linked-read sequencing. Analyses of these genomes reveal an excess of previously undocumented common genetic variation private to southern Africa, central Africa, Oceania, and the Americas, but an absence of such variants fixed between major geographical regions. We also find deep and gradual population separations within Africa, contrasting population size histories between hunter-gatherer and agriculturalist groups in the past 10,000 years, and a contrast between single Neanderthal but multiple Denisovan source populations contributing to present-day human populations.

Visible Light Communication (VLC) is an emerging field in Optical Wireless Communication (OWC) which utilizes the superior modulation bandwidth of Light Emitting Diodes (LEDs) to transmit data. In modern day communication systems, the most popular frequency band is Radio Frequency (RF) mainly due to little interference and good coverage. However, the rapidly dwindling RF spectrum along with increasing wireless network traffic has substantiated the need for greater bandwidth and spectral relief. By combining illumination and communication, VLC provides ubiquitous communication while addressing the shortfalls and limitations of RF communication. This paper provides a comprehensive survey on VLC with an emphasis on challenges faced in indoor applications over the period 1979-2014. VLC is compared with infrared (IR) and RF systems and the necessity for using this beneficial technology in communication systems is justified. The advantages of LEDs compared to traditional lighting technologies are discussed and comparison is done between different types of LEDs currently available. Modulation schemes and dimming techniques for indoor VLC are discussed in detail. Methods needed to improve VLC system performance such as filtering, equalization, compensation, and beamforming are also presented. The recent progress made by various research groups in this field is discussed along with the possible applications of this technology. Finally, the limitations of VLC as well as the probable future directions are presented.

The human gastrointestinal tract is populated with a diverse microbial community. The vast genetic and metabolic potential of the gut microbiome underpins its ubiquity in nearly every aspect of human biology, including health maintenance, development, aging, and disease. The advent of new sequencing technologies and culture-independent methods has allowed researchers to move beyond correlative studies toward mechanistic explorations to shed light on microbiome-host interactions. Evidence has unveiled the bidirectional communication between the gut microbiome and the central nervous system, referred to as the "microbiota-gut-brain axis". The microbiota-gut-brain axis represents an important regulator of glial functions, making it an actionable target to ameliorate the development and progression of neurodegenerative diseases. In this review, we discuss the mechanisms of the microbiota-gut-brain axis in neurodegenerative diseases. As the gut microbiome provides essential cues to microglia, astrocytes, and oligodendrocytes, we examine the communications between gut microbiota and these glial cells during healthy states and neurodegenerative diseases. Subsequently, we discuss the mechanisms of the microbiota-gut-brain axis in neurodegenerative diseases using a metabolite-centric approach, while also examining the role of gut microbiota-related neurotransmitters and gut hormones. Next, we examine the potential of targeting the intestinal barrier, blood-brain barrier, meninges, and peripheral immune system to counteract glial dysfunction in neurodegeneration. Finally, we conclude by assessing the pre-clinical and clinical evidence of probiotics, prebiotics, and fecal microbiota transplantation in neurodegenerative diseases. A thorough comprehension of the microbiota-gut-brain axis will foster the development of effective therapeutic interventions for the management of neurodegenerative diseases.

New technologies rely on the development of new materials, and these may simply be the innovative combination of known components. The structural combination of a polymer hydrogel network with a nanoparticle (metals, non-metals, metal oxides, and polymeric moieties) holds the promise of providing superior functionality to the composite material with applications in diverse fields, including catalysis, electronics, bio-sensing, drug delivery, nano-medicine, and environmental remediation. This mixing may result in a synergistic property enhancement of each component: for example, the mechanical strength of the hydrogel and concomitantly decrease aggregation of the nanoparticles. These mutual benefits and the associated potential applications have seen a surge of interest in the past decade from multi-disciplinary research groups. Recent advances in nanoparticle-hydrogel composites are herein reviewed with a focus on their synthesis, design, potential applications, and the inherent challenges accompanying these exciting materials.

Salmonella is one of the most frequently isolated foodborne pathogens. It is a major worldwide public health concern, accounting for 93.8 million foodborne illnesses and 155,000 deaths per year. To date, over 2500 Salmonella serotypes have been identified and more than half of them belong to Salmonella enterica subsp. enterica, which accounts for the majority of Salmonella infections in humans. Salmonella infections that involve invasive serotypes are often life threatening, necessitating appropriate and effective antibiotic therapy. The emergence of multi-drug-resistant (MDR) Salmonella serotypes is having a great impact on the efficacy of antibiotic treatment, and an increasing prevalence of MDR strains may lead to an increase in mortality rates of Salmonella infections. Epidemiological studies indicate that MDR Salmonella serotypes are more virulent than susceptible strains, as reflected by increased severity and more prolonged disease in patients infected by MDR strains. Preventive measures have been proposed to eliminate the spread of Salmonella infection. While the maintenance of effective food hygiene and water sanitation remain the cornerstones, additional measures such as restriction of indiscriminate use of antibiotics in food animals are important. This review provides an overview of Salmonella infection, and discusses the nomenclature, pathogenesis, clinical manifestations, epidemiology and antibiotic resistance of Salmonella.

Traumatic brain injury (TBI) remains one of the leading causes of morbidity and mortality amongst civilians and military personnel globally. Despite advances in our knowledge of the complex pathophysiology of TBI, the underlying mechanisms are yet to be fully elucidated. While initial brain insult involves acute and irreversible primary damage to the parenchyma, the ensuing secondary brain injuries often progress slowly over months to years, hence providing a window for therapeutic interventions. To date, hallmark events during delayed secondary CNS damage include Wallerian degeneration of axons, mitochondrial dysfunction, excitotoxicity, oxidative stress and apoptotic cell death of neurons and glia. Extensive research has been directed to the identification of druggable targets associated with these processes. Furthermore, tremendous effort has been put forth to improve the bioavailability of therapeutics to CNS by devising strategies for efficient, specific and controlled delivery of bioactive agents to cellular targets. Here, we give an overview of the pathophysiology of TBI and the underlying molecular mechanisms, followed by an update on novel therapeutic targets and agents. Recent development of various approaches of drug delivery to the CNS is also discussed.

Periodontal disease represents a group of oral inflammatory infections initiated by oral pathogens which exist as a complex biofilms on the tooth surface and cause destruction to tooth supporting tissues. The severity of this disease ranges from mild and reversible inflammation of the gingiva (gingivitis) to chronic destruction of connective tissues, the formation of periodontal pocket and ultimately result in loss of teeth. While human subgingival plaque harbors more than 500 bacterial species, considerable research has shown that Porphyromonas gingivalis, a Gram-negative anaerobic bacterium, is the major etiologic agent which contributes to chronic periodontitis. This black-pigmented bacterium produces a myriad of virulence factors that cause destruction to periodontal tissues either directly or indirectly by modulating the host inflammatory response. Here, this review provides an overview of P. gingivalis and how its virulence factors contribute to the pathogenesis with other microbiome consortium in oral cavity.

Mediation and conditional process analyses have become popular approaches for examining the mechanisms by which effects operate and the factors that influence them. To estimate mediation models, researchers often augment their structural equation modeling (SEM) analyses with additional regression analyses using the PROCESS macro. This duality is surprising considering that research has long acknowledged the limitations of regression analyses when estimating models with latent variables. In this article, we argue that much of the confusion regarding SEM’s efficacy for mediation analyses results from a singular focus on factor-based methods, and there is no need for a tandem use of SEM and PROCESS. Specifically, we highlight that composite-based SEM methods overcome the limitations of both regression and factor-based SEM analyses when estimating even highly complex mediation models. We further conclude that composite-based SEM methods such as partial least squares (PLS-SEM) are the preferred and superior approach when estimating mediation and conditional process models, and that the PROCESS approach is not needed when mediation is examined with PLS-SEM.