Correlation of udder thermogram and somatic cell counts as a tool for detection of subclinical mastitis in buffaloes.

This study aimed to monitor the mammary health of 37 multiparous Murrah buffaloes through infrared thermography (IRT). Based on the California Mastitis Test (CMT) and milk somatic cell counts (SCC), buffaloes were grouped into healthy (H, n = 16), subclinical mastitis (SCM, n = 10), and clinical mastitis (CM, n = 11). Buffaloes were milked twice daily in the morning (5:00-6:00 AM) and evening (5:00-6:00 PM). Rectal temperature and respiratory rates were recorded, CMT was performed and thermal images of the mammary gland of all the buffaloes were taken before and after each milking. Milk samples were analysed after each milking for SCC, fat, Solids-Not-Fat (SNF), density, protein, lactose, salts, conductivity, and pH immediately in the laboratory from fresh milk samples. The surface temperature of the periocular region of both the eyes, muzzle, flank, and vagina were also taken. Thermal images were used to assess the surface temperature of the udder (USST), teat apex (TAT), teat barrel (TB1T), teat base (TB2T), and teat skin surface (TSST). Eye and USST showed significantly higher temperatures (p < 0.05), whereas skin surface temperatures (SST) of different body parts were non-significant in both SCM and CM animals than buffaloes in the H group. Milk SCC showed a positive correlation with conductivity (r > 0.7), salts, and pH (r < 0.6) and a negative correlation with fat, SNF, density, protein, and lactose. TAT, TB1T, TB2T, TSST, and USST were positively correlated with milk SCC. Receiver Operating Characteristic (ROC) analysis of H and SCM groups showed that USST before milking had optimum sensitivity (Se = 0.80) and specificity (Sp = 0.906) among the various skin temperatures recorded. Thermal images captured during the morning showed higher sensitivity compared to images taken in the evening. Results indicate IRT can be used to monitor the mammary health of buffaloes but using IRT in conjunction with milk SCC can help in the accurate prediction of SCM in dairy buffaloes.

Optimizing coal mine planning and design for sustainable development in the context of mass exploitation of coal deposits.

Sustainable mining practices is a concept that embeds the principles of sustainable development into the whole mine life-cycle, from exploration, extraction and processing through to mine closure. The optimization of coal mine planning and the developing a standardized design for its sustainable development is very challenging and requires more effort. The present research attempts to address the conditions of sustainability and necessary measures for sustainable development, thereby providing appropriate solutions for each stage of mining operation besides expressing the necessity of sustainable development integration at different stages of mining life cycle (MLC). The approach of systems engineering is essential to assist the sustainability goals which are integrated with the expected results. Hence a method depending more on systems engineering principles and optimization can be incorporated to attain better results. Several socio-environmental factors associated with sustainability depends on the geographic condition and few mining engineering considerations such as mine location, topography, coal seam characteristics and so on. These systems engineering approach can be further enhanced by incorporating tools like Geographic Information System (GIS), which provides more accuracy and precision of the geographic conditions of the site identified for the coal mining plan. In order to begin this way of approach towards the sustainability development and mining planning, the appropriate optimization parameters should be identified. The outcome of these optimization parameters can be also achieved by optimizing coal mining system models.

A Randomized Comparative Study of the Use of Individual Modality and Combination of Endoscopic Retrograde Cholangiopancreatography (ERCP) and Digital Single-Operator Cholangioscopy (DSOC) for Diagnosis of Indeterminate Biliary Strictures.

Background: To determine the superiority of the combination of endoscopic retrograde cholangiopancreatography (ERCP) and digital single-operator cholangioscopy (DSOC) in the same sitting over the individual modality alone in patients with indeterminate biliary strictures. Materials and Methods: A randomized study enrolled 60 adult patients with biliary strictures who were randomized into two groups: ERCP + DSOC and ERCP/DSOC. Histopathologic or cytologic assessment was performed in terms of benign, indeterminate, or malignant nature of the strictures. Procedural adverse events were documented. Accuracy in terms of sensitivity (Sn), specificity (Sp), and predictive value [positive (PPV) and negative (NPV)] were noted. Results: As per final diagnosis, in ERCP/DSOC group, there were 12 (40%) benign cases and 18 (60%) malignant cases, and in group ERCP + DSOC, there were 8 (26.67%) benign cases and 22 (73.33%) malignant cases. ERCP/DSOC labeled 16 (53.33%) patients as benign, 8 (26.67%) as malignant, and 6 (20%) as indeterminate, while ERCP + DSOC labeled 8 (26.67%) as benign, 17 (56.67%) as malignant, and 5 (16.67%) as indeterminate. The Sn, Sp, PPV, and NPV of ERCP/DSOC were 44.4%, 75%, 100%, and 56.25%, and for ERCP + DSOC was 77.27%, 62.50%, 100%, and 62.5%, respectively (P = 0.033). Side effects were statistically similar in both the groups (P > 0.05). Conclusion: To conclude, the combination of ERCP with DSOC is safe and effective with higher diagnostic sensitivity (77.27%) in comparison to standard ERCP or DSOC alone (44.4%) for the diagnosis of biliary strictures.

Pushing the Limit of Oxygen Balance on a Benzofuroxan Framework: K2DNDP as an Extremely Dense and Thermally Stable Material as a Substitute for Lead Azide.

Because of environmental and health impacts, there is an ongoing necessity to develop sustainable primary explosives to replace existing lead-based analogues. Now we describe a potential primary explosive, dipotassium 4,6-dinitro-5,7-dioxidobenzo[c][1,2,5]oxadiazole 1-oxide (K2DNDP), which exhibits an excellent thermal stability (Tdec = 281 °C), positive oxygen balance (+4.79%), and a calculated crystal density of ρ = 2.274 g cm-3 at 100 K. Its physicochemical properties concomitantly with its straightforward synthesis make it a potential replacement for lead-based initiators.

Experimental Analysis for the Performance Assessment and Characteristics of Enhanced Magnesium Composites Reinforced with Nano-Sized Silicon Carbide Developed Using Powder Metallurgy.

Magnesium, which is lightweight and abundant by nature, was widely used in the 19th century to make parts for automobiles and airplanes. Due to their superior strength-to-weight ratios, magnesium alloys were favored for engineering applications over unadulterated magnesium. These alloys result from the combination of magnesium with various metals, including aluminum (Al), titanium (Ti), zinc (Zn), manganese (Mn), calcium (Ca), lithium (Li), and zirconium (Zr). In this study, an alloy of magnesium was created using the powder metallurgy (PM) technique, and its optimal performance was determined through the Taguchi-Gray (TG) analysis method. To enhance the alloy's mechanical properties, diverse weight fractions of silicon carbide (SiC) were introduced. The study primarily focused on the Mg-Zn-Cu-Mn alloy, achieving the optimal composition of Mg-3Zn-1Cu-0.7Mn (ZC-31). Subsequently, composites of ZC-31/SiC were produced via PM and the hot extrusion (HE) process, followed by the assessment of the mechanical properties under various strain rates. The use of silicon carbide (SiC) resulted in enhanced composite densities as a consequence of the increased density exhibited by SiC particles. In addition, the high-energy postsintering approach resulted in a decrease in porosity levels. By integrating silicon carbide (SiC) to boost the microhardness, as well as the ultimate compressive and tensile strength of the composite material, we can observe significant improvements in these mechanical properties. The experimental findings also demonstrated that an augmentation in the weight fraction of SiC and the strain rate led to enhanced ductility and a shift toward a more transcrystalline fracture behavior inside the composite material.

Bis(dinitropyrazolyl)methanes spruced up with hydroxyl groups: high performance energetic salts with reduced sensitivity.

With an aim to improve the overall physical stability of high-performing 3,5-dinitro-functionalised bispyrazolymethanes, a hydroxyl functionality was introduced at the fourth position to obtain 1,1'-methylenebis(3,5-dinitro-1H-pyrazol-4-ol) and its energetic salts. Superior oxygen balance and energy in comparison to the amino substituent at the 4th position and enhanced sensitivity with respect to the nitro and azido substituents helped in unlocking the potential of less explored N-alkylated-4-hydroxy-3,5-dinitropyrazoles. Fine-tuning of properties via dicationic salt formation, which is not feasible in any other reported symmetrically connected pyrazole-based energetic materials, resulted in improved physical and thermal stabilities, as well as energetic performance. Hirshfeld surface analysis, electrostatic potential analysis, the study of aromaticity and weakest Mayer-bond order analysis helped further in studying the structure-property relationship of the synthesized compounds with respect to different reported methylene-bridged symmetrical compounds.

Controlling the Energetic Properties of N-Methylene-C-Linked 4-Hydroxy-3,5-dinitropyrazole- and Tetrazole-Based Compounds via a Selective Mono- and Dicationic Salt Formation Strategy.

In the quest to synthesize high-performing insensitive high-energy density materials (HEDMs), the main challenge is establishing an equilibrium between energy and stability. For this purpose, we explored 4-hydroxy-3,5-dinitropyrazole- and tetrazole-based energetic scaffolds connected via a N-methylene-C bridge. The hydroxy functionality between nitro groups on the pyrazole ring promotes physical stability via inter- and intramolecular hydrogen bonding and contributes to oxygen balance, supporting better energetic performance. Due to two acidic sites (OH and NH) with different reactivities, a series of monocationic and dicationic salts were synthesized, and their overall performance was compared. All compounds synthesized in this study have high physical stability with impact sensitivity >40 J and friction sensitivity >360 N. Monocationic salts were generally found to have better thermal stability with respect to their corresponding dicationic energetic salts, which showed better energetic performance. The salt formation strategy effectively improved the thermal stability of 2 (Td = 168 °C), where most energetic salts have decomposition temperatures higher than 220 °C. All of the compounds were characterized through IR, multinuclear NMR spectroscopy, high-resolution mass spectrometry (HRMS), and elemental analysis. The structure-property relationship was studied using Hirshfeld surface analysis, noncovalent interaction (NCI) analysis, and electrostatic potential studies.

Empowering elderly care with intelligent IoT-Driven smart toilets for home-based infectious health monitoring.

The COVID-19 pandemic highlights the need for effective and non-intrusive methods to monitor the well-being of elderly individuals in their homes, especially for early detection of potential viral infections. Conspicuously, the present paper develops a Multi-scaled Long Short Term Memory (Ms-LSTM) model for the routine health monitoring of elderly patients to detect COVID-19. The proposed method offers home-based health diagnostics through urine analysis by leveraging the IoT-Fog-Cloud paradigm. Mainly, the proposed model constitutes a four-layered architecture: data acquisition, fog layer, cloud layer, and interface layer. Each layer serves distinct functionalities and provides specific services, thereby collectively enhancing the overall effectiveness of the model. The statistical results of the study demonstrate the superior performance of the proposed Ms-LSTM model in comparison to state-of-the-art methods, including Artificial Neural Networks (ANN), K-Nearest Neighbors (K-NN), Support Vector Machine (SVM), Random Forest, and LSTM. Further, the proposed model attains a mean temporal efficiency of 39.23 seconds. It exhibits high reliability (92.97%), stability (70.06%), and predictive accuracy (93.25%).

Analytical performance verification of a high throughput system for Hepatitis B and Hepatitis C viral load quantifications.

Objective: To verify the analytical performance of cobas® HBV PCR and cobas® HCV PCR assays with Abbott m2000 RealTime System as the reference method. Design: De-identified residual, archived patient specimens, and College of American Pathologists (CAP) proficiency testing samples were used. Analytical parameters verified were accuracy, precision, limit of detection (LOD), linear range, and cross-contamination. Experiments were designed in accordance with Clinical Laboratories Standards Institute (CLSI) guidelines and CAP standards. Analysis of accuracy was done through regression plots and Bland Altman analyses. Precision was analyzed through coefficient of variation and ANOVA; LOD through probit analysis; and linear range through polynomial fit analysis. Results: The regression plots for accuracy showed a slope nearing 1, with a y-intercept close to zero, while Bland Altman analyses also showed no systematic evidence of bias, though concordance of results was not perfect near the lower limit of quantification. Coefficients of variation were all below 15%, while ANOVA returned p-values above 0.99, indicating no statistically significant imprecision. The LOD verified were an order of magnitude higher than the manufacturer reported ones for both assays, while the linear range verified was more limited. Within the verified range, polynomial fit analysis showed line to be the best fit for the data. Conclusions: cobas® HBV PCR and cobas® HCV PCR assays showed acceptable accuracy, acceptable precision, as well as no evidence of cross-contamination. The LOD verified were higher, and linear ranges more limited than those reported by the manufacturer. Verifications of these may be limited by availability of appropriate testing specimens.

Energy, economics and environmental (3E's) analysis of a solar-assisted HRES through demand side management.

The limitation of renewable energy is its fluctuation with time, season, and peak load demand. Hence, most of the research was carried using demand side management to reduce the actual consumption load to lower the peak load. This will also hamper the basic energy need of the facility. Therefore, the objective of the present study is to model a hybrid renewable energy system (HRES) to attain the specific consumption of a community health centre (CHC) in Yomcha, Arunachal Pradesh, with load shedding. The optimization of HRES is performed on HOMER® Pro software along with the demand side management algorithm and a maximum annual capacity shortage of 5%. Three different cases were compared based on feasibility, economics, and environmental basis to estimate the performance of the HRES. The results show that the proposed model is appropriate for the CHC over the previously proposed system. Moreover, HRES with (design-side management) DSM will reduce the overall cost and increase efficiency and reliability with an net present value of Rs. 3013482 and a cost of energy of Rs. 5.42/kW, renewable fraction 78%, internal rate of return 70%, return of investment 66%, and payback period of 1.4 years. Moreover, it reduces emissions, controls overloading during peak hours, and decreases load shifting. The study also supports the sustainable development goal (SDG)-7 set by the United Nation SDG Committee.

Polynitro-functionalized 4-phenyl-1H-pyrazoles as heat-resistant explosives.

A new class of heat-resistant explosives was synthesized by coupling N-methyl-3,5-dinitropyrazole with polynitrobenzene moieties through carbon-carbon bonds. Simple Pd(0)-based Suzuki cross-coupling reactions between N-methyl-4-bromo-3,5-dinitropyrazole and 4-chloro/3-hydroxy-phenylboronic acid followed by nitration, amination and oxidation lead to the formation of C-C connected penta-nitro energetic derivatives 6 and 10. Various other energetic derivatives, such as amino (5), azido (7), nitramino (8) and energetic salts (11-14), were also explored to fine-tune their properties. All the compounds were thoroughly characterized using IR, NMR [1H, 13C{1H}], differential scanning calorimetry (DSC), elemental analysis, and HRMS studies. Compounds 5, 10 and 13 were further characterized through 15N NMR, and the crystal structures of 6 and 14 were confirmed through single-crystal X-ray diffraction studies. The physicochemical and energetic properties of all the energetic compounds were explored. Most of the synthesized compounds demonstrated high thermal stability (decomposition temperature Tdec > 250 °C), among which compounds 5 and 6 showed excellent thermal stability, having decomposition temperatures above 300 °C. The excellent thermal stability, acceptable sensitivity and good energetic properties of compounds 5, 6, 10 and 13 make them promising heat-resistant explosives. Furthermore, these compounds were found to be more thermally stable than the known N-methyl-3,5-dinitropyrazole-based and C-N coupled 3,4,5-trinitrobenzene-azole-based energetic compounds.

Enhancement of thermal efficiency and development of Nusselt number correlation for the solar air heater collector roughened with artificial ribs for thermal applications.

The thermal efficiency of conventional solar air heater is very low. This research article concentrates on incorporating V-shaped staggered twisted ribs over absorber surface of solar air heater. Various roughness parameters were tested to determine their effect on the Nusselt number, friction factor, thermo-hydraulic performance index, and thermal efficiency. During experiment, the Reynolds number is varied from 3000 to 21,000; while relative roughness length varied for 4.39 to 10.26 and relative staggered distance for 2 to 6. However, relative roughness pitch, twist length, and angle of attack were kept constant. The Nusselt number and friction factor of the roughened collector enhances to 3.41 and 2.56 times that of the smooth collector, respectively. The thermal efficiency of the roughened solar air heater increases to 73.64% of the roughened plate as it was noticed 42.63% for smooth surface due to breakage of the laminar sublayer. The correlations for Nusselt number and friction factor as function of Reynolds number and roughness parameters are also developed. The maximum thermohydraulic performance gained at the optimum parameters of d/e of 4 and S/e of 6.15 is 2.69. The percentage deviation between the developed correlations and the experimental findings shows very satisfactory outcomes. Therefore, it can be concluded that inclusion of twisted V staggered ribs enhances the thermal performance of solar air heater with the lowest frictional penalty.

Influence of sustainable environmental exercises in the green restaurant industry.

The restaurant business is gaining popularity for its capacity to alleviate numerous adverse environmental influences to achieve a competitive edge. Green restaurants can employ a distinctive brand strategy. Nevertheless, additional research is necessary to better understand customer behavior in this subject. This study explores the relationship between brand awareness and brand image, and brand performance from the consumer's perspective. However, it is unknown how this connection is affected by the attitude of green restaurant brands. This research aims to address the research gaps by determining the structure and function of brand attitudes. This study handles the quantitative data analysis to fit the study problem. The data was collected through a questionnaire form, and the questionnaire was collected from the customers from twelve restaurants in Karachi city of Pakistan by utilizing random sampling. In sum, 290 samples were obtained and interpreted with SPSS (Statistical Package for the Social Sciences) and PLS (Partial Least Squares) to come up with the results of the study. According to the findings, restaurant customers' observed brand awareness and brand image positively impact brand attitude. The results of the structural equation analysis revealed that brand awareness and brand image have a substantial impact on brand performance, whereas brand attitude has a profound effect on meditation. The adaptation of brand attitude to brand management has sparked a lot of interest in the incredibly competitive restaurant business. There is a good likelihood that green restaurants will ultimately find value in using the measuring tools and suggestions offered in this research to analyze and lead their marketing efforts. In practice, it is recommended that green restaurant management cultivate familiar brand awareness and preserve the brand image to create brand attitude and performance.

Valorised polypropylene waste based reversible sensor for copper ion detection in blood and water.

Heavy metals and plastic pollutants are the two most disastrous challenges to the environment requiring immediate actions. In this work, a techno-commercially feasible approach to address both challenges is presented, where a waste polypropylene (PP) based reversible sensor is produced to selectively detect copper ions (Cu2+) in blood and water from different sources. The waste PP-based sensor was fabricated in the form of an emulsion-templated porous scaffold decorated with benzothiazolinium spiropyran (BTS), which produced a reddish colour upon exposure to Cu2+. The presence of Cu2+ was checked by naked eye, UV-Vis spectroscopy, and DC (Direct Current) probe station by measuring the current where the sensor's performance remained unaffected while analysing blood, water from different sources, and acidic or basic environment. The sensor exhibited 1.3 ppm as the limit of detection value in agreement with the WHO recommendations. The reversible nature of the sensor was determined by cyclic exposure of the sensor towards visible light turning it from coloured to colourless within 5 min and regenerated the sensor for the subsequent analysis. The reversibility of the sensor through exchange between Cu2+- Cu+ was confirmed by XPS analysis. A resettable and multi-readout INHIBIT logic gate was proposed for the sensor using Cu2+ and visible light as the inputs and colour change, reflectance band and current as the output. The cost-effective sensor enabled rapid detection of the presence of Cu2+ in both water and complex biological samples such as blood. While the approach developed in this study provides a unique opportunity to address the environmental burden of plastic waste management, it also allows for the possible valorization of plastics for use in enormous value-added applications.

Design, characterization and evaluation of a new 99mTc-labeled folate derivative with affinity towards folate receptor.

Folate receptors (FRs) are known to be over-expressed in several human malignancies and therefore serve as an important target for small radiolabeled folate derivatives for non-invasive imaging of tumor, which is an important tool for future treatment recourse. In the present article, we report the synthesis of a new 99mTc-labeled radiotracer for the aforementioned application following the well-established 99mTc-'4+1' chemistry. Formation of the desired [99mTc]Tc-complex with >95% radiochemical purity was confirmed by radio-HPLC and its structure was ascertained by characterizing a natural rhenium analogue of the said complex. Although the ligand exhibited a weaker affinity towards FRs compared to native folic acid (IC50 8.09 µM vs 29.46 nM), the 99mTc-labeled complex was found to bind folate receptor-positive KB cells with high specificity (∼90%). Similar studies in a folate receptor negative cell line viz. A549 further corroborated the receptor-specificity of the synthesized complex. In vivo studies in KB tumor xenograft showed moderate uptake of ∼2.6% upto 3 h post-injection with high specificity (∼80%). The favorable features observed warrant further screening of the current design towards achieving an improved molecular probe for the said application.

Partial Cricotracheal Resection - Our Experience.

Introduction: The incidence of acquired laryngotracheal stenosis is on rise, being caused usually due to prolonged intubation or trauma. Its management has thus become a common clinical challenge for Otolaryngologists and Head and Neck surgeons. Further, with advances in Critical care medicine, Cardiopulmonary surgery and Neurosurgery, the number of intubation-related laryngotracheal injuries is increasing. Objectives: To assess the outcome of patients who underwent Partial Cricotracheal Resection (PCTR) for subglottic stenosis on basis of pre-defined parameters. Design of Study: This is a prospective study. Materials and Methods: Four patients who came to Ear Nose Throat (ENT) department, All India Institute of Medical Sciences (AIIMS) Patna with complaints of either difficult decannulation or stridor, for which PCTR was planned, were included in the study. Surgical resection was done and all patients were followed up for a minimum of 6 months. Postoperatively certain parameters, such as respiration, voice, difficulty in swallowing, feeding and personal satisfaction, were used to evaluate the patients and analyse the efficacy of the surgery. Results: Three out of four cases came up with complete cure with no dyspnoea, dysphagia, hoarseness of voice. Only one patient could not be extubated and was continued on Ryle's tube for longer duration compared to other patients. Conclusion: PCTR is an effective and reliable procedure for management of laryngotracheal stenosis caused due to trauma.

Detection of Epileptic Seizure Using Accelerometer Time Series Data and Hidden Markov Model.

Epilepsy is one of the most prevalent neurological diseases globally, which causes seizures in the patient. As per a survey done worldwide, it is found that approximately 70 million people are living with epilepsy (~1% of the total population of the world). Effective detection of these seizures requires specialized approaches such as video and electroencephalography monitoring, which are expensive and are mainly available at specialized hospitals and institutes. Hence, there is a need to develop simpler and affordable systems that can be made available to health care centers and patients for accurate detection of epileptic seizures. A wireless remote monitoring system based on a wrist-worn accelerometer is an optimum choice for the same. Sophisticated algorithms need to be developed for effectively detecting seizure events from this accelerometer data with minimal false alarms. This paper presents a Hidden Markov Model (HMM) based probabilistic approach applied to the reduced-dimension feature vector representation of time-series accelerometer data to detect epileptic seizures. The results obtained from the HMM were compared with three commonly used machine learning models viz. support vector machine (SVM), logistic regression, and random forest. The proposed approach was able to detect 95.7% of seizures with a low false alarm rate of 14.8% with a run time of just under 24 seconds.

Vegetation health conditions assessment and mapping using AVIRIS-NG hyperspectral and field spectroscopy data for -environmental impact assessment in coal mining sites.

This paper focuses on vegetation health conditions (VHC) assessment and mapping using high resolution airborne hyperspectral AVIRIS-NG imagery and validated with field spectroscopy-based vegetation spectral data. It also quantified the effect of mining on vegetation health for geo-environmental impact assessment at a fine level scale. In this study, we have developed and modified vegetation indices (VIs) based model for VHC assessment and mapping in coal mining sites. We have used thirty narrow banded VIs based on the statistical measurement for suitable VIs identification. The highest Pearson's r, R2, lowest RMSE, and P values indices have been used for VIs combined pixels analysis. The highest different (Healthy vs. unhealthy) vegetation combination index (VCI) has been selected for VHC assessment and mapping. We have also compared VIs model-based VHC results to ENVI (software) forest health tool and Spectral-based SAM classification results. The 1st VCI result showed the highest difference (72.07%) from other VCI. The AUC values of the ROC curve have shown a better fit for the VIs model (0.79) than Spectral classification (0.74), and ENVI FHT (0.68) based on VHC results. The VHC results showed that unhealthy vegetation classes are located at low distances from mine sites, and healthy vegetation classes are situated at high distances. It is also seen that there is a highly significant positive relationship (R2 =0.70) between VHC classes and distance from mines. These results will provide a guideline for geo-environmental impact assessment in coal mining sites.

A visual review of artificial intelligence and Industry 4.0 in healthcare.

The COVID-19 outbreak has led to a substantial loss of human life throughout the world and has a tremendous impact on healthcare services. Industry 4.0 technologies have established effective supply chain management towards the fulfillment of customized demands in the healthcare field. In addition, the internet of things, artificial intelligence, big data analytics, and 3D printing have been extensively used to combat the COVID-19 pandemic and assist in providing value-added services in the healthcare sector. Henceforth, this paper presents a scientometric analysis on the literature of aforementioned Industry 4.0 technologies in the context of COVID-19. It provides extensive insights into co-citation and co-occurrence analysis of high cited publications, participating countries, influential authors, prolific journals, and keywords using the CiteSpace tool. The analyses reveal that China has produced the highest research outputs, although India is the most collaborative country in this field. The current research hotspots include supply chain, 4D printing, and social distancing technologies. Furthermore, it explores emerging trends, intellectual structure of publications, research frontiers, and potential research directions for further work in the Industry 4.0 assisted healthcare domain.

Iron-Based Shape Memory Alloys in Construction: Research, Applications and Opportunities.

As a promising candidate in the construction industry, iron-based shape memory alloy (Fe-SMA) has attracted lots of attention in the engineering and metallography communities because of its foreseeable benefits including corrosion resistance, shape recovery capability, excellent plastic deformability, and outstanding fatigue resistance. Pilot applications have proved the feasibility of Fe-SMA as a highly efficient functional material in the construction sector. This paper provides a review of recent developments in research and design practice related to Fe-SMA. The basic mechanical properties are presented and compared with conventional structural steel, and some necessary explanations are given on the metallographic transformation mechanism. Newly emerged applications, such as Fe-SMA-based prestressing/strengthening techniques and seismic-resistant components/devices, are discussed. It is believed that Fe-SMA offers a wide range of applications in the construction industry but there still remains problems to be addressed and areas to be further explored. Some research needs at material-level, component-level, and system-level are highlighted in this paper. With the systematic information provided, this paper not only benefits professionals and researchers who have been working in this area for a long time and wanting to gain an in-depth understanding of the state-of-the-art, but also helps enlighten a wider audience intending to get acquainted with this exciting topic.