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With the confluence of information technology era and the progressively aging society, the internet usage rate by older adults in Malaysia is growing at a substantial rate. Therefore, older adults are becoming an increasingly significant potential target market for electronic commerce. However, previous researchers have focused mainly on the youth market and paid less attention to the online behaviours of older adults. To bridge the gap, the objective of this research is to increase a better understanding of how the factors affecting the perception, acceptance and willingness of older adults in Malaysia towards online shopping. To this end, this study is developed by integrating the unified theory of acceptance and use of technology (UTAUT) and innovation resistance theory (IRT). They are applied to an original dataset of 200 responses from respondents that were collected through a survey.

In children, SARS-CoV-2 infection is usually asymptomatic or causes a mild illness of short duration. Persistent illness has been reported; however, its prevalence and characteristics are unclear. We aimed to determine illness duration and characteristics in symptomatic UK school-aged children tested for SARS-CoV-2 using data from the COVID Symptom Study, one of the largest UK citizen participatory epidemiological studies to date.

BackgroundMental health issues have been reported after SARS-CoV-2 infection. However, comparison to prevalence in uninfected individuals and contribution from common risk factors (eg, obesity and comorbidities) have not been examined. We identified how COVID-19 relates to mental health in the large community-based COVID Symptom Study.MethodsWe assessed anxiety and depression symptoms using two validated questionnaires in 413148 individuals between February and April 2021; 26998 had tested positive for SARS-CoV-2. We adjusted for physical and mental prepandemic comorbidities, body mass index (BMI), age and sex.FindingsOverall, 26.4% of participants met screening criteria for general anxiety and depression. Anxiety and depression were slightly more prevalent in previously SARS-CoV-2-positive (30.4%) vs SARS-CoV-2-negative (26.1%) individuals. This association was small compared with the effect of an unhealthy BMI and the presence of other comorbidities, and not evident in younger participants (≤40 years). Findings were robust to multiple sensitivity analyses. Association between SARS-CoV-2 infection and anxiety and depression was stronger in individuals with recent (<30 days) versus more distant (>120 days) infection, suggesting a short-term effect.InterpretationA small association was identified between SARS-CoV-2 infection and anxiety and depression symptoms. The proportion meeting criteria for self-reported anxiety and depression disorders is only slightly higher than prepandemic.

ObjectivePoor metabolic health and unhealthy lifestyle factors have been associated with risk and severity of COVID-19, but data for diet are lacking. We aimed to investigate the association of diet quality with risk and severity of COVID-19 and its interaction with socioeconomic deprivation.DesignWe used data from 592 571 participants of the smartphone-based COVID-19 Symptom Study. Diet information was collected for the prepandemic period using a short food frequency questionnaire, and diet quality was assessed using a healthful Plant-Based Diet Score, which emphasises healthy plant foods such as fruits or vegetables. Multivariable Cox models were fitted to calculate HRs and 95% CIs for COVID-19 risk and severity defined using a validated symptom-based algorithm or hospitalisation with oxygen support, respectively.ResultsOver 3 886 274 person-months of follow-up, 31 815 COVID-19 cases were documented. Compared with individuals in the lowest quartile of the diet score, high diet quality was associated with lower risk of COVID-19 (HR 0.91; 95% CI 0.88 to 0.94) and severe COVID-19 (HR 0.59; 95% CI 0.47 to 0.74). The joint association of low diet quality and increased deprivation on COVID-19 risk was higher than the sum of the risk associated with each factor alone (Pinteraction=0.005). The corresponding absolute excess rate per 10 000 person/months for lowest vs highest quartile of diet score was 22.5 (95% CI 18.8 to 26.3) among persons living in areas with low deprivation and 40.8 (95% CI 31.7 to 49.8) among persons living in areas with high deprivation.ConclusionsA diet characterised by healthy plant-based foods was associated with lower risk and severity of COVID-19. This association may be particularly evident among individuals living in areas with higher socioeconomic deprivation.

Healthcare institutions are progressively integrating artificial intelligence (AI) into their operations. The extraordinary potential of AI is restricted by insufficient medical data for AI model training and adversarial attacks wherein attackers perturb the dataset by adding some noise to it, which leads to the malfunctioning of the AI models, and a lack of trust caused by the opaque operational approach it employs. This Systematic Literature Review (SLR) is a state‐of‐the‐art survey of the research on blockchain technology for securing AI‐integrated healthcare applications. The most relevant articles from the Scopus and Web of Science (WoS) databases were identified using the PRISMA model. Most of the existing literature is about protecting the healthcare data used by AI‐based healthcare systems using blockchain technology, but the modality of data (text, images, audio, and sound) was not specifically mentioned. Information on protecting the training phase and model deployment for AI‐based healthcare systems considering the variations in feature extraction based on the modality of data was also not clearly specified. Hence, the three subfields of AI, namely, natural language processing (NLP), computer vision, and acoustic AI are further studied to identify security loopholes in its implementation pipeline. The three phases, namely the dataset, the training phase, and the trained models need to be protected from adversaries to avoid malfunctioning of the deployed AI models. The nature of the data processed by NLP, computer vision, and acoustic AI, underlying deep neural network (DNN) architectures, the complexity of attacks, and the perceivability of attacks by humans are analyzed to identify the need for security. A blockchain solution for AI‐based healthcare systems is synthesized based on the findings that have demonstrated the distinctive technological features of blockchains. It offers a solution for the privacy and security issues encountered by NLP, computer vision, and acoustic AI to boost the widespread adoption of AI applications in healthcare. The applicability of blockchain properties from protecting and validating datasets, protecting classifiers/algorithms protecting the post‐training environment in AI is detailed in this image.

ABSTRACTThe expression of viral antigens in chronic hepatitis B virus (HBV) infection drives continuous liver inflammation, one of the main risk factors to develop liver cancer. HBV developed immune-suppressive functions to escape from the host immune system, but their link to liver tumor development is not well understood. Here, we analyzed if and how HBV surface antigen (HBs) expression in combined hepatocellular-cholangiocarcinoma (cHCC/iCCA) cells influences their antigenicity for CD8 T cells. We randomly isolated liver tumor tissues from AlfpCre+-Trp53fl/fl/Alb-HBs+tg mice and established primary carcinoma cell lines (pCCL) that showed a bilineal (CK7+/HNF4α+) cHCC/iCCA phenotype. These pCCL uniformly expressed HBs (HBshi), and low levels of MHC-I (MHC-Ilo), and were transiently convertible to a high antigenicity (MHC-Ihi) phenotype by IFN-γ treatment. HBshi/pCCL induced HBs/(Kb/S190–197)-specific CD8 T cells and developed slow-growing tumors in subcutaneously transplanted C57Bl/6J (B6) mice. Interestingly, pCCL-ex cells, established from HBshi/pCCL-induced and re-explanted tumors in B6 but not those in immune-deficient Rag1−/−mice showed major alterations, like an MHC-Ihiphenotype, a prominent growth-biased gene expression signature, a significantly decreased HBs expression (HBslo) and a switch to fast-growing tumors in re-transplanted B6 or PD-1−/−hosts with an unlocked PD-1/PD-L1 control system. CD8 T cell-mediated elimination of HBshi/pCCL, together with the attenuation of the negative restraints of HBs in the tumor cells, like ER-stress, reveals a novel mechanism to unleash highly aggressive HBslo/pCCL-ex immune-escape variants. Under certain conditions, HBs-specific CD8 T-cell responses thus potentiate tumor growth, an aspect that should be considered for therapeutic vaccination strategies against chronic HBV infection and liver tumors.

AbstractIn this paper, inspired by the concept of generalized single-valued neutrosophic graphs(GSVNG) of the first type, we define yet another generalization of neutrosophic graph called the generalized interval-valued neutrosophic graph of 1 type (GIVNG1) in addition to our previous work on complex neutrosophic graph (CNG1) in [47]. We will also show a matrix representation for this new generalization. Many of the fundamental properties and characteristics of this new concept is also studied. Like the concept CNG1 in [47], the concept of GIVNG1 is another extension of generalized fuzzy graphs 1 (GFG1) and GSVNG1.

In this paper, the authors propose the concept of expert complex fuzzy soft sets as an extension to the classical complex fuzzy set model. Instead of being concerned with the study of the basic set theoretic operations for this model, which are essentially generalizations of the corresponding operations of the complex fuzzy set model, we extend the study of this model through the establishment of the mappings on classes of expert complex fuzzy soft sets. Through these mappings, we introduce the image and inverse image of an expert complex fuzzy soft set, which have immense applications in real-life applications. In addition to presenting the properties of the images and inverse images of this model, we present two numerical examples to demonstrate the utility of these concepts.

The precise representation and analysis of complex data sets have become an increasingly important concern in areas such as medical diagnosis, economics, stock market analysis and pattern recognition. The advent of digital technology has resulted in the ubiquity of digitalized images and patterns. Unlike analog images and patterns, digital images and patterns are defined multi-dimensional data that consists of information pertaining to the physical and non-physical attributes of the images. This calls for a suitable complex fuzzy-based model that has the ability to represent multi-dimensional data in a succinct and concise manner. This paper achieves this goal using the complex vague soft set (CVSS) model to represent the multi-dimensional information for digital images. The information measures of CVSSs pertaining to the measures of distance and similarity are then established with the aim of solving pattern recognition problems involving digital images. The axiomatic definition of the distance-based similarity measure of CVSSs is introduced and the relations between this similarity measure and the distance measure of CVSSs are proposed and verified. The utility of this measure is demonstrated by applying it in a pattern recognition problem involving digitalized images that are defined by multi-dimensional data pertaining to the physical features and non-physical features such as the geographical data and timestamp of the images.

Compounds of the type [(S2C2R2)M(μ-tpbz)M(S2C2R2)] (R = CN, Me, Ph, p-anisyl; M = Ni, Pd, Pt; tpbz = 1,2,4,5-tetrakis(diphenylphosphino)benzene) have been prepared by transmetalation with [(S2C2R2)SnR′2] reagents, by direct displacement of dithiolene ligand from [M(S2C2R2)2] with 0.5 equiv of tpbz, or by salt metathesis using Na2[S2C2(CN)2] in conjunction with X2M(μ-tpbz)MX2(X = halide). X-ray crystallography reveals a range of topologies (undulating, chair, bowed) for the (S2C2)M(P2C6P2)M(S2C2) core. The [(S2C2R2)M(μ-tpbz)M(S2C2R2)] (R = Me, Ph, p-anisyl) compounds support reversible or quasireversible oxidations corresponding to concurrent oxidation of the dithiolene terminal ligands from ene-1,2-dithiolates to radical monoanions, forming [(−S•SC2R2)M(μ-tpbz)M(−S•SC2R2)]2+. The R = Ph and p-anisyl compounds support a second, reversible oxidation of the dithiolene ligands to their α-dithione form. In contrast, [(S2C2(CN)2)Ni(tpbz)Ni(S2C2(CN)2)] sustains only reversible, metal-centered reductions. Spectroscopic examination of [(−S•SC2(p-anisyl)2)Ni(μ-tpbz)Ni(−S•SC2(p-anisyl)2)]2+by EPR reveals a near degenerate singlet–triplet ground state, with spectral simulation revealing a remarkably small dipolar coupling constant of 18 × 10–4cm–1that is representative of an interspin distance of 11.3 Å. This weak interaction is mediated by the rigid tpbz ligand, whose capacity to electronically insulate is an essential quality in the development of molecular-based spintronic devices.

In this article, the authors introduce two new operations for the interval-valued complex fuzzy set model, and study the fundamental algebraic properties of these new operations. The utility and applicability of the relations of this model is then demonstrated by applying it to an economics problem. The interpretation of this example is provided and supported by real-life incidences that took place in the Malaysian economy in recent years. Lastly, a brief comparative analysis of the IV-CFS model and other similar models are presented.

In this paper, the authors aim to extend the notion of interval-valued vague soft sets to establish the concept of possibility interval-valued vague soft expert sets. The set theoretic operations of this concept and other related concepts are introduced. The algebraic properties of this notion such as the laws of commutativity, associativity and De Morgan are established and verified. Lastly, the similarity measure between this set is introduced and illustrated using a hypothetical example related to texture synthesis.

AbstractNumerical model analysis was carried out to study the deflection behaviour of FRP-based prestressed concrete (PSC) beam, because it does not resemble the existing deflection model of steel tendon-based PSC beam due to its non-ductile property. Deflection model by various researchers for the FRP-based PSC beams are underestimating as compared to experimental results which lead to unsafe design. There were 51 numbers of experimental results which were collected from various research articles for the numerical model analysis. Lagrange dual function convex optimisation used to predict the effective moment of inertia and shift of neutral axis distance. It reveals that the deflection of FRP tendon beam depends on deformability of material, degree of prestressing and bond strength. Design chart suggested for calculation of effective moment of inertia and effective neutral axis distance with respect to deformability index. The maximum deflection error by the proposed method is less than 5% as compared to experimental results.

Fiber-reinforced polymer (FRP) composites are preferred as prestressing tendons in concrete structures due to its high-strength, lightweight and non-corrosive property. FRP based prestressed concrete member exhibits different crack behavior than steel based prestressed concrete member due to its less stiffness and non-ductile property. An experimental investigation was carried out to study the cracking behaviour of concrete member using Carbon fiber reinforced polymer (CFRP) bars as prestressing material. Experimental works includes four numbers of prestressed concrete specimens by varying degree of prestressing of 35 to 70%. The characteristics of crack spacing, crack propagation and crack widths of member were presented. Experimental results were compared with various researchers’ recommendation and proposed a new crack width model by modifying the Frosch crack width model.

Pentapartitioned neutrosophic sets are a generalization of the single-valued and quadri-partitioned single-valued neutrosophic sets, and utilizes five symbol-valued neutrosophic logic. In this paper, we introduce some novel concepts regarding pentapartitioned neutrosophic graphs (PPNGs), and emphasize the effectiveness at interpreting extremely heterogeneous data that are prevalent in our daily life, particularly data gathered from various different sources which are becoming increasingly common place in the current times. The applicability of the proposed PPNG is demonstrated by applying the PPNGs on a potential real-life scenario on responding to the spread of COVID-19, where PPNGs are used to determine the safest path of travel and the safest place to stay to minimize the chances of getting infected. Both of this information have proven to be vital aspects in the efforts to combat the spread of the COVID-19 pandemic while providing the necessary support to the domestic economies, most of which are currently in recession due to the adverse effects brought upon by the pandemic. Hence, the PPNGs are applicable to all countries around the world and can be used under any circumstances such as pandemics or even in regular situations to optimize the travelling time and distance.

This study pertains to the usage and effectiveness of the fuzzy time series (FTS) models and machine learning methods in forecasting movements of financial data. The datasets used in this study are the actual closing prices and transaction volumes of 9 different cryptocurrencies, from the earliest time obtainable in Yahoo! Finance, all the way to 31 Oct 2021. Firstly, this paper presents a study of the severe drawbacks of all existing literature on FTS. In particular, this article outlines severe shortcomings of all existing FTS based algorithms that caused inaccuracies among all existing FTS-based algorithms in yielding meaningful prediction. Then, a novel structure of our improvised FTS, denoted as QFTS, is presented in this paper, which aims to rectify all flaws exist in all conventional FTS based models in literature. A further hybrid of QFTS with ANN is also presented. Later, a comparative analysis of all the aforementioned FTS models is presented in terms of overall forecasting accuracy and forecasting accuracy under specific conditions. The results are being compared in terms of MAPE. The newly invented QFTS model and the QFTS-ANN hybrid is found to profoundly outperform all the existing FTS models in literature, which includes Singh's FTS model. Such innovation profoundly rectifies severe shortcomings in financial forecasting that have persisted for many years in the past literature.

Metallodithiolene complexes of the type [(R2C2S2)M(η2-tpbz)] [R = CN, Ph, or p-anisyl; M = Ni2+, Pd2+, or Pt2+; tpbz = 1,2,4,5-tetrakis(diphenylphosphino)benzene] chelate transition metals ions to form trimetallic arrays [[(R2C2S2)M(tpbz)]2M′]n+, where M′ is square planar Pt2+, tetrahedral Cu+, Ag+, or Au+, or octahedral {ReBr(CO)}/{Re(CO)2}+. Forcing conditions (190 °C reflux in decalin, 72 h) are demanded for the Re+compounds. With third-row metals at the nexus, the compounds are stable to air. Twelve members of the set have been characterized by X-ray diffraction and reveal dithiolene centroid–centroid distances ranging from 22.4 to 24.0 Å. Folding around each tpbz intrachelate P···P axis such that the MP2/M′P2planes meet the tpbz P2C6P2mean plane at non-zero values gives rise to core topologies that appear “S-like” or herringbone-like for M′ = Pt2+or {ReBr(CO)}/{Re(CO)2}+. Calculations reveal that departure from idealized D2h/D2d/C2vsymmetries is induced by steric crowding between Ph groups and that dynamic, fluxional behavior is pertinent to the solution phase because multiple, lower-symmetry minima of comparable energy exist. Spectroscopically, the formation of the trimetallic arrays is marked by a shift of the open end 31P nuclear magnetic resonance signal from approximately −14.5 ppm to approximately +41, approximately +20.5, and approximately +28.5 ppm for M′ = Pt2+, Au+, and {ReBr(CO)}/{Re(CO)2}+, respectively. Electrochemically, dithiolene-based oxidations are observed for the R = Ph and M′ = Pt2+or Au+compounds but at potentials that are anodically shifted relative to charge-neutral [[(R2C2S2)M]2(μ-tpbz)]. The compounds reported clarify the possibilities for the synthesis of assemblies in which weakly coupled spins may be created in their modular (R2C2S2)M and M′ parts.

Open-ended, singly metalated dithiolene complexes with 1,2,4,5-tetrakis(diphenylphosphino)benzene (tpbz) are prepared either by ligand transfer to [Cl2M(tpbz)] from (R2C2S2)SnR′2(R = CN, R′ = Me; R = Me, R′ = nBu) or by a direct reaction between tpbz and [M(S2C2R2)2] (M = Ni, Pd, Pt; R = Ph, p-anisyl) in a 1:1 ratio. The formation of dimetallic [(R2C2S2)M(tpbz)M(S2C2R2)] attends these syntheses in modest amounts, but the open-ended compounds are readily separated by silica chromatography. As affirmed by X-ray crystallographic characterization of numerous members of the set, the [(R2C2S2)M(tpbz)] compounds show dithiolene ligands in their fully reduced ene-1,2-dithiolate form conjoined with divalent Group 10 ions. Minor amounts of octahedral [(Ph2C2S2)2PtIV(tpbz)], a presumed intermediate, are isolated from the preparation of [(Ph2C2S2)PtII(tpbz)]. Heterodimetallic [(Ph2C2S2)Pt(tpbz)Ni(S2C2Me2)] is prepared from [(Ph2C2S2)PtII(tpbz)]; its cyclic voltammogram, upon anodic scanning, shows two pairs of closely spaced, but resolved, 1e–oxidations corresponding first to [R2C2S22–] – 1e–→ [R2C2S•S–] and then to [R2C2S•S–] – 1e–→ [R2(C═S)2]. The open diphosphine of [(R2C2S2)M(tpbz)] can be oxidized to afford open-ended [(R2C2S2)M(tpbzE2)] (E = O, S). Synthesis of the octahedral [(dppbO2)3Ni][I3]2[dppbO2= 1,2-bis(diphenylphosphoryl)benzene] suggests that the steric profile of [(R2C2S2)M(tpbzE2)] is moderated enough that three could be accommodated as ligands around a metal ion.

Cases of human dirofilariasis have been reported in several countries around the world, including a large number in the Atlantic and Gulf Coast regions of the United States. Most commonly, these cases have subcutaneous or pulmonary involvement; however, there have been few reports of dirofilariasis involving structures such as large vessels, mesentery, the spermatic cord, and liver. We present a case of an unusual presentation of human dirofilariasis presenting as a shoulder abscess and what is presumed to be pulmonary and splenic involvement in a 55-year-old female.

Synchronous colonic tumours of dual pathology are extremely rare. A review of the literature revealed that few cases have been reported to date. Because of their rarity and lack of specific symptoms, preoperative diagnosis is not easy and there is no protocol as yet for the ideal management of these cases. We present such a case which was treated by a combination of surgery and chemotherapy.