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COVID-19 is a global crisis where India is going to be one of the most heavily affected countries. The variability in the distribution of COVID-19-related health outcomes might be related to many underlying variables, including demographic, socioeconomic, or environmental pollution related factors. The global and local models can be utilized to explore such relations. In this study, ordinary least square (global) and geographically weighted regression (local) methods are employed to explore the geographical relationships between COVID-19 deaths and different driving factors. It is also investigated whether geographical heterogeneity exists in the relationships. More specifically, in this paper, the geographical pattern of COVID-19 deaths and its relationships with different potential driving factors in India are investigated and analysed. Here, better knowledge and insights into geographical targeting of intervention against the COVID-19 pandemic can be generated by investigating the heterogeneity of spatial relationships. The results show that the local method (geographically weighted regression) generates better performance ( R 2 = 0.97 ) with smaller Akaike Information Criterion (AICc = - 66.42 ) as compared to the global method (ordinary least square). The GWR method also comes up with lower spatial autocorrelation (Moran’s I = - 0.0395 and p < 0.01 ) in the residuals. It is found that more than 86% of local R 2 values are larger than 0.60 and almost 68% of R 2 values are within the range 0.80–0.97. Moreover, some interesting local variations in the relationships are also found.

Macrophages function as sentinel cells, which constantly monitor the host environment for infection or injury. Macrophages have been shown to exhibit a spectrum of activated phenotypes, which can often be categorised under the M1/M2 paradigm. M1 macrophages secrete proinflammatory cytokines and chemokines, such as TNF-α, IL-6, IL-12, CCL4, and CXCL10, and induce phagocytosis and oxidative dependent killing mechanisms. In contrast, M2 macrophages support wound healing and resolution of inflammation. In the past decade, interest has grown in understanding the mechanisms involved in regulating macrophage activation. In particular, epigenetic control of M1 or M2 activation states has been shown to rely on posttranslational modifications of histone proteins adjacent to inflammatory-related genes. Changes in methylation and acetylation of histones by methyltransferases, demethylases, acetyltransferases, and deacetylases can all impact how macrophage phenotypes are generated. In this review, we summarise the latest advances in the field of epigenetic regulation of macrophage polarisation to M1 or M2 states, with particular focus on the cytokine and chemokine profiles associated with these phenotypes.

In every household, women play a crucial role in shaping the foundation of food and nutrition. They are primarily responsible for ensuring nutritional security for all members. However, women often find themselves in vulnerable positions within this context. With this in mind, the study aimed to evaluate the nutritional security status of women and explore its determinants. Data were extracted from the Bangladesh Integrated Households Survey-2018. A total of 5604 women were considered, and their nutritional security status was measured based on their minimum dietary diversity intake and sufficient calorie consumption in a 24-hour period. The data were divided into two subsets: households with livestock and households without livestock, to examine the impact of livestock ownership on women’s nutritional security status. The findings revealed that within the overall population, approximately 9% of women have achieved nutritional security. Interestingly, a higher proportion of women, around 11%, from households with livestock were found to be nutritionally secure compared to those without livestock, where only about 7% of women achieved nutritional security. A binary logit regression model was utilized to explore significant predictors and found that livestock ownership, women’s education level, household income, farm size, household size, ownership of a mobile phone by women, and women`s nutritional knowledge were significantly positively associated with their nutritional security status. When examining the subset of women from households without livestock, it was found that their monthly income, farm size, and women’s nutritional knowledge had insignificant impacts compared to women from households with livestock. Addressing the role of livestock, the study concludes that the predictors of women’s nutritional status are not equally significant based on livestock ownership. The study’s findings will assist in designing and formulating future policies and development programs addressing this newly acquired knowledge.

Food insecurity and agriculture in South Asia, including Bangladesh, pose significant threats to the well-being and livelihoods of its people. Building adaptive capacities and resilient food systems is crucial for sustainable livelihoods. This study employs the Resilience Index Measurement and Analysis II framework to construct a Resilience Capacity Index (RCI) and analyze its relationship with food security using data from the Bangladesh Integrated Household Survey 2018. The study applies Exploratory Factor Analysis and Structural Equation Modeling to examine the impact of key resilience components such as Access to Basic Services, Adaptive Capacity, and Assets on household resilience. The findings reveal that access to basic services, land assets, and farm equipment positively influences households’ resilience capacity. However, the presence of livestock assets has a negative impact, potentially due to market volatility, climate vulnerability, and disease outbreaks. Additionally, adaptive capacity has a positive but insignificant influence on RCI, suggesting that without enhancing economic opportunities, institutional support, and inclusive development strategies, adaptive capacity could not be enough to foster resilience. However, resilient capacity enhances food security metrics such as the Food Consumption Score and Expenditure. These findings underscore the importance of policies that focus on increasing and maintaining access to basic services, promoting sustainable land management practices, and strengthening social safety nets. This study emphasizes the importance of focusing on livestock assets to ensure their sustainability by stabilizing the livestock market, improving veterinary services, and providing subsidies to reduce maintenance costs.

Owing to poor thermal conductivity, heat dissipation, and high chemical reactivity toward most of the tool materials, temperature elevation in the machining of titanium alloy leads to poor surface quality. Based on analyzing the variation laws of the milling forces under cryogenic cooling, the present investigation concerns the surface integrity (surface roughness, micro-hardness, microstructures, and residual stresses) in cryogenic milling of Ti-6Al-4 V alloy under the application of liquid nitrogen (LN 2 ) as a cooling mode. Findings have indicated a dramatic increase in milling forces, and decreasing surface roughness was observed under variation of jet temperature (20~−196 °C). Besides an increase in cutting speed from 60 to 120 m/min, a linear increase in cutting forces, surface roughness, micro-hardness, and residual compressive stress was observed. The minimum micro-hardness decreased at cutting speed of 90 m/min and up to 30 μm in depth. A holistic comparison between obtained results under cryogenic milling and previously studied results under dry milling at same cutting conditions depicted higher micro-hardness and higher compressive residual stress under cryogenic LN 2 on the machined surface. However, the residual stress under LN 2 cooling conditions tends to decrease relatively slower compared to dry milling. Also, there are no significant differences in grain refinement and twisting under dry and cryogenic LN 2 machining. The research work proves the effectiveness of cryogenic milling in improving the surface integrity of the Ti-6Al-4 V alloy.

Proper maintenance of roads is an extremely complex task and also an important issue all over the world. One of the most critical road monitoring and maintenance activities is the detection of road anomalies such as potholes. Identification of potholes is necessary to avoid road accidents, prevent damage of vehicles, enhance travelling comforts, etc. Although maintenance of roads is considered to be a serious issue by the authorities over the years, lack of proper detection and mapping of road potholes makes the issue more severe. To overcome this problem, an end-to-end system called PotSpot is built for real-time detection, monitoring, and spatial mapping of potholes across the city A Convolutional Neural Network (CNN) model is proposed and evaluated on real-world dataset for pothole detection. Additionally, real-time pothole-marked maps are generated with the help of Google Maps API (Application Programming Interface). To provide an end-to-end service through this system, both the pothole detection and pothole mapping are integrated through an android application. The proposed model is also compared with six baselines namely Artificial Neural Network (ANN), Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and three pre-trained CNN models InceptionV3, VGG19 and VGG16 in terms of performance metrics to verify its effectiveness. The proposed model achieves better accuracy (≈ 97.6 %) as compared to the above-mentioned baseline methods. It is also observed that the Area Under the Curve (AUC) value for the proposed pothole detection model (AUC= 0.97) is higher than the baseline methods.

Purpose This study aims to examine whether counterfeit luxury buyers’ tendency to impress others overrides their anticipation of embarrassment or whether the anticipation of embarrassment delimits their self-presentational goals. Design/methodology/approach This paper is based on three studies – a survey and two experiments that test the predictions. This study adopts a mix of moderation and mediation analyses to test the proposed hypotheses. Findings The findings reveal a greater counterfeit purchase likelihood and embarrassment aversion among publicly (vs privately) self-conscious consumers. Furthermore, a higher (vs a lower) audience class and a conspicuous (vs an inconspicuous) brand lead to lower counterfeit purchase intention, and anticipated embarrassment mediates both these effects. To mitigate the threat of embarrassment, publicly self-conscious consumers are more likely to buy counterfeits among a higher-class audience when the brand is inconspicuous (vs conspicuous). They, however, are indifferent to brand conspicuousness among a lower-class audience. Practical implications To deter counterfeit consumption, anti-counterfeiting campaigns must invoke consumers’ tendency to overestimate the degree of public attention. Ad appeals must accentuate the anticipation of embarrassment by enhancing self-consciousness through a higher-class audience involving a conspicuous brand. Originality/value This paper makes a novel contribution to counterfeiting literature by demonstrating that counterfeit luxury consumption is driven by countervailing motives of gaining approval and avoiding disapproval. The paper departs from mainstream theorizing by demonstrating that counterfeit luxury buyers engage in a protective self-presentation style by choosing inconspicuous counterfeits.

Purpose This paper aims to theorize that millennials' counterfeit buying behavior is partly driven by perceived peer counterfeit consumption – the perception that counterfeit luxury consumption is a norm within members of their own generation. Design/methodology/approach The research is based on two survey-based studies: Study 1 investigates the phenomenon on young millennials (n = 438) and Gen X (n = 374) using moderation analyses in PROCESS Macro; and Study 2 is based on young millennials (n = 643) and runs a partial least squares structural equation modeling model. Findings The findings reveal that perceived counterfeit consumption within own (vs other) generation leads to greater counterfeit purchase intention and this effect is stronger for young millennials (vs Gen X). Counterfeiting values (materialism, counterconformity and morality) strengthen the impact of perceived peer counterfeit consumption on the counterfeit purchase intention of young millennials, thereby establishing counterfeit luxury consumption as a salient norm. Practical implications To modify perceptions about peer counterfeiting norms, normative messages must communicate counterfeit avoidance among millennials through social media influencers. Luxury brand managers must focus on the experiential value of luxury and pursue unconventional luxury inspired by a sense of rebelliousness and independence. Originality/value This work demonstrates that millennials engage in counterfeit luxury consumption when they perceive it as a salient consumption norm among members of their own generation. It adds a novel construct of perceived counterfeit consumption and demonstrates the role of generation as a normative referent. The article provides a values-based motivational account of conformity to peer counterfeiting norms.

The investigation of the interrelationships among different oceanic and atmospheric circulation patterns is crucial for future climate projections in the current century. This paper presents the transition matrix approach of the stochastic Markov chain process to investigate the state/event based relationship between the new index of the Interdecadal Pacific Oscillation (IPO) named as the IPO Tripole index (TPI) and different sea surface temperature anomalies (SSTA) based El Nino-Southern Oscillation (ENSO) indices such as Niño 1.2, Niño 3, Niño 3.4, Niño 4 and the Multivariate ENSO Index (MEI) for the period of 120 years (1900–2019) respectively. Several Markovian descriptors like state dependency, temporal stationarity, expected number of state visits and entropy are derived from the estimated transition matrix. These descriptors are helpful in establishing the validity of Markov chain method and useful to characterize the dynamical properties of a time series like persistence, randomness and behaviour of cycles. Through the Markov chain analysis and by derived descriptors, this study finds similar self-communication (periodic) pattern between the transition states, resemblance in expected number of visits from one transition state to another, asymmetric and truncated cyclic nature of the data sequence and the existence of randomness in the transition states. Finally, a strong 2-dimensional correlation values endorses the existence of strong relations between selected indices datasets. This analysis approach may be helpful in understanding the role of the IPO and ENSO in modulating future climate variability and to formulate effective predictive models at the climatic state.

Microbial-induced calcite precipitation (MICP) is a promising new technology in the area of Civil Engineering with potential to become a cost-effective, environmentally friendly and sustainable solution to many problems such as ground improvement, liquefaction remediation, enhancing properties of concrete and so forth. This paper reviews the research and developments over the past 25 years since the first reported application of MICP in 1995. Historical developments in the area, the biological processes involved, the behaviour of improved soils, developments in modelling the behaviour of treated soil and the challenges associated are discussed with a focus on the geotechnical aspects of the problem. The paper also presents an assessment of cost and environmental benefits tied with three application scenarios in pavement construction. It is understood for some applications that at this stage, MICP may not be a cost-effective or even environmentally friendly solution; however, following the latest developments, MICP has the potential to become one.