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Catalytic additives able to accelerate the lithium–sulfur redox reaction are a key component of sulfur cathodes in lithium–sulfur batteries (LSBs). Their design focuses on optimizing the charge distribution within the energy spectra, which involves refinement of the distribution and occupancy of the electronic density of states. Herein, beyond charge distribution, we explore the role of the electronic spin configuration on the polysulfide adsorption properties and catalytic activity of the additive. We showcase the importance of this electronic parameter by generating spin polarization through a defect engineering approach based on the introduction of Co vacancies on the surface of CoSe nanosheets. We show vacancies change the electron spin state distribution, increasing the number of unpaired electrons with aligned spins. This local electronic rearrangement enhances the polysulfide adsorption, reducing the activation energy of the Li–S redox reactions. As a result, more uniform nucleation and growth of Li2S and an accelerated liquid–solid conversion in LSB cathodes are obtained. These translate into LSB cathodes exhibiting capacities up to 1089 mA h g–1at 1 C with 0.017% average capacity loss after 1500 cycles, and up to 5.2 mA h cm–2, with 0.16% decay per cycle after 200 cycles in high sulfur loading cells.

Sleep apnea (SA) is a noncommunicable medical condition associated with sleep, characterized by recurrent interruptions in breathing during sleep. Electrocardiogram (ECG) sensor data are commonly employed in medical diagnosis to capture the minute electrical impulses of the heart and effectively diagnose SA complications. Analyzing raw ECG data to extract the underlying subtle features poses challenges due to its nonlinear and nonstationary nature. This article introduces a novel approach to diagnosing SA patients using a multiresolution assessment of raw ECG data. The tunable ${Q}$ -factor wavelet transform (TQWT) is used to decompose the raw signal into multiple sub-bands (SBs). Selecting the optimal basis parameters for accurate decomposition using TQWT is a complex task. To address this, an artificial gorilla troop optimization algorithm is integrated with the TQWT method to determine the best tuning parameters, resulting in more representative SBs. To differentiate between apnea and normal ECG segments, an array of statistical features is evaluated from all SBs. Selected features are then used as input for five different neural network configurations and four other machine learning modules. The wide neural network (WNN) configuration achieves the highest accuracy of 96.60%, with a sensitivity of 96.50%, and specificity of 96.41%. This research proposes a nonparameterized technique for the efficient decomposition of nonstationary data. The presented strategy, in conjunction with the neural network configurations, can also be applied to detect other health complications.

Many classification problems in the real world are inherently multi-class. However, most of the classifiers are binary. Solving K-class classification problems with “1-versus-1” approach requires KC2binary classifiers. Furthermore, it suffers from information loss as other classes are not considered. But, if the solutions of “1-versus-rest” approach-based binary classifiers are combined, then the number of classifiers drops to K. Still, it comes with the cost of making the binary class problems imbalanced and nonlinear. K-SVCR is a technique that solves class imbalance problems by giving the “1-versus-1-versus-rest” approach, a ternary classifier. But instead of giving any respite on the number of classifiers, researchers again suggest KC2classifiers. This article attempts to reduce the number of classifiers for three class problems, K=3. First, it identifies the reason behind the use of so many classifiers with the help of artificially generated datasets. Then, it proposes two methods to identify the correct labelling of classes that bring the best performance of the classifier as a second step. Finally, it verifies if the proposals are effective on the artificial and real-world datasets. Experimental results show that class labelling with proposed methods improved the average accuracy of K-SVCR by 75.3%on artificial datasets and 9.97%on real-world datasets. In addition to that, the requirement of time and computational resources is reduced to one-third of the original implementation of K-SVCR.

Highly complex cognitive works require more brain power. The productivity of a person suffers due to this strain, which is sometimes referred to as a mental burden or psychological load. A person’s mental health and safety in high-stress working conditions can be improved with the help of mental workload assessment. A photoplethysmogram (PPG) signal is a non-invasive and easily acquired physiological signal that contains information related to blood volume changes in the micro-vascular bed of tissues and can indicate psychologically relevant information to assess a person’s mental workload (MW). An individual under a high MW possesses an increase in sympathetic nervous system activity, which results in morphological changes in the PPG waveform. In this work, a time-frequency analysis framework is developed to capture these distinguishing PPG features for the automatic assessment of MW. In particular, a cross-wavelet coherence (WTC) approach is proposed to extract simultaneous time-frequency information of the PPG during MW relative to the resting PPG. The suggested technique is validated on a publicly available data set of 22 healthy individuals who took part in an N-back task with PPG recording. Under three different fixed window lengths, images are obtained using WTC between PPG records during N-back task activity and rest. The images are used further to obtain PPG classification in two broad classes of low and high MW using a customized pre-trained Inception-V3 model. The best validation and test accuracy of 93.86% and 93.07%, respectively obtained in the window setting of 1200 samples used for WTC image creation.

ABSTRACTWith increasing urbanization, wastewater and industrial effluents are being discharged into watercourses. Due to high-density development, it is difficult to construct conventional flow measurement structures like weirs. Hence, to measure the flow, dye tracing studies are an appropriate method for urban drainage channels. Dye tracing studies along with water quality monitoring can be analyzed to understand the behavior of pollutants in specific sections of the study area. This paper presents a state-of-the-art review for employing dye tracing studies to ascertain the pathways of pollutants and a case study. A dye tracing study was carried out at the Kolshet drain, Thane, India, to conceptualize contaminant transport using rhodamine WT (water tracer) dye. The study was carried out jointly by the Indian Institute of Technology Bombay, India and the University of Warwick, UK. Rhodamine WT dye was injected at the injection point and the distribution of dye concentration with time was logged with four portable fluorometers installed at measurement points. The data were analyzed and the longitudinal dispersion coefficient (‘DL’) for solute transport in the drain was computed.

ABSTRACTIt is evident from the volumes of recently published research articles that ‘maritime sustainability’ is getting much attention nowadays. However, there has been a bias when it comes to the selection of maritime ports. The majority of studies have been done for European and North American ports, but very few have been done for Asian ports, especially when it comes to South-Asian ports. This research evaluated South Asia’s eleven major maritime ports to identify significant environmental sustainability issues they are currently facing through extensive literature review and then sorting these issues based on the Importance-Performance Analysis (IPA) technique. Later, these eleven Major South-Asian ports were ranked based on these sorted issues using the Segmented String Relative Ranking algorithm, thereby analysing environmental sustainable practises at the selected South-Asian ports on a long term basis. The top three ranked Ports are Port of Malé (Maldives), Jawaharlal Nehru Port, Mumbai (India) and Port of Colombo (Srilanka).

In this study an attempt has been made to examine the aftermarket performance of IPOs in the banking, financial services and insurance (BFSI) sector and its relationship with management quality certifications in India. From a sample period of 11 years, mean listing day market adjusted excess returns are observed at 27.86%. Furthermore, it is observed that long-run underperformance of IPOs using buy-and-hold returns is present during the holding period of 36 months. In addition to this, regression analysis depicts professional association of board members significantly influencing IPO performance, whereas, education level of board members, presence of foreign directors and director's diversity moderately influence the long-run performance of sample public issues.

Measurement of abnormal heartbeat rhythm of a fetus to detect arrhythmia using fetal-electrocardiogram (f-ECG) signals is one of the most convenient methods, used to quickly assess the health status of the fetus. However, instruments used to record the clean f-ECG under free-living conditions have several operational difficulties. Therefore, this study presents a new integrated Stockwell transform (S-transform)-based learning system to evacuate the clean f-ECG signals from the mother’s abdomen and automatically detect the arrhythmic fetuses. In this work, an empirical mode decomposition (EMD) algorithm is employed to decompose the raw signals into various intrinsic mode functions (IMFs) and a correlation criterion is set to eliminate noisy IMFs. The remaining noise-free IMFs are utilized to reconstruct the denoised f-ECG signals. The S-transform is used to convert the clean f-ECG signals into time–frequency (T–F) images. The obtained images are given to two prebuilt Alex-Net and Squeeze-Net along with a newly developed lightweight deep convolutional model (DCM). The presented system has yielded an average detection accuracy of 95.31%, an area under the curve of 99.57, and a specificity of 96.29%. The comparison results depict that the developed system provides higher detection performance compared to the state-of-the-art techniques. The proposed learning system efficiently detected the arrhythmic fetus, which may enhance medical measurement performance by reducing operational cost/difficulties of various f-ECG recording instruments and can assist obstetricians in deciding on delivery. Our presented system is suitable to design abdominal wearables for continuous monitoring of the fetus.

In the present study, feasibility of micro-plasma transferred arc (M-PTA) for flank surface treatment of gears has been explored. 20MnCr5 spur gears manufactured by sustainable technique minimum quantity lubrication assisted hobbing (MQLAH) were subjected to M-PTA-based heat treatment for further improving the surface properties of flank surface and comparisons were made with respect to M-PTA treated gears machined by conventional flood lubrication assisted hobbing (FLAH). The results revealed that M-PTA enhanced flank surface hardness of all the gears without deteriorating the gear accuracy. However, flank hardness increment was observed to be almost 18% in case of MQLAH gears as compared to 15% for FLAH gears. This study proves that M-PTA based heat treatment after MQLAH can result in superior surface hardness along with better gear accuracy and can improve the sustainability of overall process chain involved in machining-based gear manufacturing.

Maritime clusters play a crucial role in the economic development of countries, encompassing seaports, maritime businesses, universities, and government agencies. South Asia, although lacking established maritime clusters, exhibits potential for the emergence of such clusters in its seaports. Evaluating the competitiveness of these emerging maritime port clusters is vital as it directly impacts their performance and future potential as world-class maritime clusters. However, no previous attempts have been made to measure the competitiveness of these emerging port clusters. This pioneering study addresses this gap by assessing the level of competitiveness in the emerging South Asian maritime port clusters. The research develops a competitive index using the Multi-Attribute Utility Theory (MAUT) approach, identifying key factors that enhance cluster competitiveness and evaluating the competence of each port cluster across these factors. The findings indicate that Jawaharlal Nehru Port Trust (JNPT) near Mumbai ranks as the top-indexed port cluster, followed by the cluster of Colombo and Male. This study provides a comprehensive assessment tool, identifies strengths and weaknesses, and provides actionable policy implications to enhance the competitiveness of maritime port clusters in South Asia and serves as a foundation for future research and policymaking in this field.

Objective: Diffusion-weighted MRI is a technique that can infer microstructural and microcirculatory features from biological tissue, with particular application to renal tissue. There is extensive literature on diffusion tensor imaging (DTI) of anisotropy in the renal medulla, intravoxel incoherent motion (IVIM) measurements separating microstructural from microcirculation effects, and combinations of the two. However, interpretation of these features and adaptation of more specific models remains an ongoing challenge. One input to this process is a whole organ distillation of corticomedullary contrast of diffusion metrics, as has been explored for other renal biomarkers. Materials and methods: In this work, we probe the spatial dependence of diffusion MRI metrics with concentrically layered segmentation in 11 healthy kidneys at 3 T. The metrics include those from DTI, IVIM, a combined approach titled “REnal flow and microstructure anisotroPy (REFMAP)”, and a multiply encoded model titled “FC-IVIM” providing estimates of fluid velocity and branching length. Results: Fractional anisotropy decreased from the inner kidney to the outer kidney with the strongest layer correlation in both parenchyma (including cortex and medulla) and medulla with Spearman correlation coefficients and p-values (r, p) of (0.42, <0.001) and (0.37, <0.001), respectively. Also, dynamic parameters derived from the three models significantly decreased with a high correlation from the inner to the outer parenchyma or medulla with (r, p) ranges of (0.46–0.55, <0.001). Conclusions: These spatial trends might find implications for indirect assessments of kidney physiology and microstructure using diffusion MRI.

The requirements of gears are increasing rapidly in the global market for applications from micro electro mechanical systems (MEMS) to aerospace. Gears of various profiles and types including spiral-conical are used for motion as well as torque transfer in microsystems. The development of such gears is a challenging task because no compromise in their quality is acceptable. It necessitates highly accurate gear manufacturing process. This article presents such a process i.e. wire-assisted electrical discharge machining (WEDM) and development of stainless-steel made spiral-conical gears of miniature size. All minute aspects of spiral-conical gear development by WEDM are reported in this paper. In order to investigate the impact of process parameters and gear quality, an experimental study has been conducted based on Taguchi’s robust design of experiment technique. The developed gears are found with good manufacturing quality characteristics.

Stainless steel 304 is one of the most promising materials for many industrial applications. Its machinability is poor whether machined in any environment. Conventional machining causes environmental degradation as well. In this paper, sustainable machining of SS304 using green lubricant is presented. Experiments have been conducted on Taguchi’s robust design of experiment technique. For machinability enhancement, a hybrid optimization technique VIKOR-Regression-PSO is employed. Machinability indicators that have been considered are tool wear, surface roughness, and chip reduction coefficient. Cutting speed, depth of cut, and feed rate have been considered as the variable machining parameters in this work. The hybrid optimization has been found very effective and provided a set of optimum machining parameters i.e. cutting speed-70m/min; feed rate-0.1mm/rev; depth of cut-0.5mm for the best values of machinability indicators i.e. tool wear-249.22 μm, roughness-11.08 μm, chip reduction coefficient-2.26.

Squeeze casting is a well-established and reliable process for fabricating high-integrity metallic alloys, bimetals, and composites. The quality and high performance of squeeze cast components are dependent on optimum casting conditions. Inappropriate selection of parameter values may adversely affect the quality of the casting. The squeeze cast components are generally subjected to secondary processing such as heat treatment, extrusion, and other bulk deformation processes to improve the microstructural features and mechanical properties. Heat treatment further refines the grains and reduces porosity, consequently improving tensile strength, and hardness; however, ductility decreases. This paper provides a comprehensive review on studies concerning the influence of processing parameters on porosity, density, percentage elongation, strength, hardness, wear, and fracture of squeeze casting alloys, aiming to provide sufficient information on the squeeze casting process and the effects of processing parameters on product quality.

Highlights: This work demonstrates 98% improvement in the photocurrent density of photoelectrochemical water splitting of ZnO nanorods by p-type Sb doping and 28% more improvement by piezotronic effect through tensile strain, leading to an overall 154% enhancement through the synergistic effects. Abstract: An efficient separation and transport of charges is essential in order to enhance photoelectrochemical (PEC) water splitting efficiency. Herein, we report that PEC water splitting output performance of undoped ZnO nanorods (NRs) is firstly enhanced by p-type Sb doping on oxygen evolution reaction (OER), grown by a facile chemical bath deposition. The specimen with 2 at% Sb-doped ZnO NRs (2 at% Sb-ZnO NRs) yields the highest photocurrent density of 1.07 mA/cm2under a Xe lamp with a power of 100 mW/cm2, two times that of the undoped ZnO NRs (0.54 mA/cm2). Additionally, piezotronic effect is applied to further enhance PEC output performance using an in-house fabricated device. When the sample of 2 at% Sb-ZnO NRs is subject to a strain varying from a compressive strain of ε=  − 0.15% to a tensile strain of ε= 0.15%, the photocurrent density varies from 0.71 mA/cm2to 1.37 mA/cm2accordingly caused by the change of the piezopotential-induced Schottky barrier height. Therefore, compared to the strain-free condition of the undoped ZnO NRs, the PEC photocurrent density gained an enhancement of 98% by p-type Sb doping and a further enhancement of 28% by piezotronic effect through tensile strain, leading to 154% overall enhancement. In this work, we propose a feasible scheme to develop high-performance ZnO-based photoelectrodes for PEC water splitting. Graphical abstract:

In hard turning, the cutting forces are large, which leads to tool wear and tensile nature of residual stresses. Vibration-assisted machining (VAM), where the tool is provided with a low amplitude vibration at significantly high frequency, might improve the process performance of hard turning in terms of cutting forces, residual stress, etc., as VAM helps in reduction of cutting forces and tool wear significantly. To improve the machining operation, a comparative study of VAM with conventional machining is undertaken to study and improve the hard turning performance. A two-dimensional (2D) finite element (FE) model is developed to understand the effect of process parameters better and to study the effect on machining performance by applying one-dimensional ultrasonic vibration to the tool. The model developed is validated with results from a previous work for continuous hard turning conditions. The effect of vibrations induced in cutting velocity direction is studied on the cutting forces and residual stresses induced on the machined workpiece. The ratio of cutting velocity to critical vibrating velocity is an important process parameter that affects the average cutting forces during hard turning using VAM. The nature of cutting force and temperature for a complete cycle of vibration is also studied. The simulation results establish that hard turning using VAM yields lower average cutting forces and more compressive residual stresses in comparison to conventional hard turning.

This article systematically analyzes the effect of scan pattern on the geometry and material properties of wall structures built using laser-directed energy deposition (LDED)-based additive manufacturing. Hastelloy-X (Hast-X), a nickel superalloy, is deposited using an indigenously developed 2-kW fiber laser–based LDED system. The wall structures are built using unidirectional and bidirectional scan patterns with the same LDED process parameters and effect of scan pattern on the geometry, microstructural and mechanical characteristics of Hast-X wall structures built using LDED. The wall width is higher for samples deposited with the bidirectional pattern at the starting and ending points as compared to walls built with the unidirectional pattern. Further, the range of width value is higher for walls built with bidirectional strategy as compared to walls built with unidirectional strategy. Wall height is more uniform with unidirectional deposition at the central region, with the range and standard deviation for walls built using bidirectional deposition at 3 and 2.5 times more than unidirectional deposition, respectively. The deposition rate for bidirectional deposition is two times that of unidirectional deposition. The microstructure of the built walls is cellular/dendritic, with bidirectional deposition showing a finer grain structure. Elemental mapping shows the presence of elemental segregation of Mo, C and Si, confirming the formation of Mo-rich carbides. Micro-hardness and ball indentation studies reveal higher mechanical strength for samples built using the bidirectional pattern, with unidirectional samples showing strength lower than the conventional wrought Hast-X samples (197 HV). This study paves a way to understand the effect of scan pattern on LDED built wall structures for building intricate thin-walled components.

The present work discusses micro-texturing on flat and cylindrical surfaces using the electric-discharge micromachining (EDMM) process. The arrays of micro-dimples are generated on flat Ti-6Al-4V surfaces using a block–electric discharge grinding (block-EDG)–fabricated microtools of an average diameter of 148 µmand 105 µm. Large-area surface texturing on flat Ti-6Al-4V and aluminium surfaces are performed to analyse the variation in water contact angle with varying depths of dimples. Adopting the electric discharge–milling (ED-milling) strategy, micro-pillars of dimensions 242 µm ×166 µm ×50 µm are machined onflat Ti-6Al-4V surfaces. The EDMM process for non-flat surfaces, such as curved (internal and external), spherical and freeform surfaces, is receiving attention in various applications. Machining of the aforementioned surfaces using the EDMM process appears to be problematic, due to the continuous change in curvature, which results in the subsequent spark gap variation. In the present work, processing of cylindrical surfaces for micro-features generation, such as micro-dimple arrays, has been attempted. Arrays of micro-dimples are machined on copper and Ti-6Al-4V cylindrical surfaces. A precise indexing setup is fabricated to hold and index the workpiece at the desired angular positions. Unlike machining on flat surfaces, the relative dimensions of the tool and the workpiece’s curvature result in non-uniform wear at the tool’s end cross-section. Owing to this non-uniform wear of tool electrode caused by the curvature effect of the workpiece, the formation of a microscopic bump/spike is observed on the dimple’s bottom. The depth of the dimple up to which the entire bottom surface of the tool is not exposed to the sparks is defined as its critical depth. For a combination of a tool and a workpiece of diameters 500 µmand 5 mm, respectively, the critical depth of the dimple is found to be 12.53 µm. However, the critical depth increases with a decrease in workpiece diameter, provided the diameter of the tool is constant.

Pulsed laser-based material removal is a preferred technique for microscribing of copper (Cu) film coated on polymers, as the pulse width limits the heat diffusion. However, experimental studies have shown that microscribing of Cu in air results in recast/redeposit formation and oxidation. Although the water medium can reduce these effects to a certain extent, the material removal rate is lesser for Cu. This article reports the influence of laser pulse duration on a hybrid method to enhance the pulsed laser-assisted microscribing of a copper thin film in the presence of an environmentally friendly sodium chloride salt solution (NaCl). The focused laser beam irradiation of Cu film results in ablation with a temperature of the zone well above the boiling point of Cu, which in turn, can assist in accelerating the chemical reaction. In this hybrid scribing technique, along with laser-based material removal, laser-activated chemical etching also helps in removing the material selectively. A sub-nanosecond laser with a pulse width of 500 ps (picosecond [ps] laser) and a nanosecond laser with a pulse width of 6 ns (nanosecond [ns] laser), with a wavelength of 532 nm, are used to understand the influence of laser pulse duration on this hybrid material removal mechanism. Hybrid microscribing with the ps- and ns lasers in salt solution resulted in an increase in the channel depth by ≈5 µm and ≈9 µm, respectively, compared to the channel depth obtained in deionized water. The theoretical model shows that during the ns laser ablation, the cooling rate is slower, resulting in a high temperature in the ablation zone for a longer duration and improved material removal.

Sapphire is an important ceramic material which finds applications in fields such as temperature sensing, optics, electronics, and ceramic bearings. Polishing of sapphire has always been a difficult task for industries and research communities. Hydrodynamic polishing (HDP) is one of the prominent methods used for polishing of hard and profiled surfaces, whereas rigid tool-based methods such as diamond turning, grinding, and honing have many limitations. The HDP process involves deterministic flow of abrasive particles in the slurry between the workpiece surface and a rotating soft tool to obtain the desired surface finish. A novel experimental setup has been fabricated to realize the conformal hydrodynamic nanopolishing on single crystal sapphire cavity. In this study, the experiments were conducted to understand the effect of abrasive particle size, basicity of slurry, and change in temperature of slurry on the polishing of machined sapphire cavity. The effect of the initial surface roughness of the machined cavity on conformal hydrodynamic nanopolishing has also been investigated. A microcrack/pit-free surface has been found after the final polishing of the sapphire cavity. An improvement of 21% is found in surface finish after the final polishing using abrasive particle size of 0.06 µm. Abrasive slurry with higher basicity (pH 13) does not improve the surface finish. By heating the abrasive slurry to a temperature of 70°C–75°C, surface finish improves by ∼26% as compared to improvement of ∼ 21% at room temperature polishing.

This article reports on influence of extrusion pressure, abrasive particle size and volumetric concentration on simultaneous reduction of surface roughness and microgeometry errors of spur and straight bevel gear by abrasive flow finishing (AFF) process. A vertical configured experimental apparatus was developed for two-way AFF and developed fixtures for finishing gears. Experimental investigations were conducted to identify optimum parametric combination, using response surface methodology, based on Box–Behnken design approach. Results revealed that higher values of abrasive particle size and volumetric concentration yield more percentage decrease in surface roughness and microgeometry error. Roughness profile, bearing area curve, microhardness, surface morphology, and wear resistance of the gear having best quality finishing were studied. Surface morphology analysis of the flank regions of the best finished spur and straight bevel gears found them to be smooth and free from cracks and burrs. Reciprocating wear test results revealed higher wear resistance of the AFF finished gears as compared to the unfinished gears. AFF also enhanced microhardness of the finished gears, which would enhance their operating performance and service life. This study shows that AFF is a flexible, economical, productive, easy to operate, and sustainable nontraditional process for precision finishing of gear that can simultaneously improve microgeometry, surface finish, microhardness, surface morphology, wear resistance, and residual stresses of the finished gears. Gear manufacturers and users will be benefited by the outcome of this study.JEL codes:C00, C20

Modern technology requires producing of a sustainable product with a high surface accuracy. In applications where the surface quality is highly considerable in various internal cylindrical components requires technology to manufacture an ultrafine surface finish. There is, in general, a probability of inducing errors into products by the traditional finishing processes (such as grinding/honing), which lead to failure. Preferably with some evidence in the main text. Further, the advanced finishing processes are developed, where the finishing forces can be controlled by varying the power output. Instead of a solid abrasive tool, the smart polishing fluid is used, which gets activated under the magnetic fields. In this manuscript, the material removal under different internal surface finishing processes is elaborated, which helps in improving the surface quality of various industrial components. Also, the surface quality produced on various industrial components after traditional as well as advanced finishing processes are discussed.

The present article deals with the generation of micro-grooves on 316L stainless steel (SS) by a nanosecond pulsed fiber laser system. Fabrication of micro-grooves on 316L SS has immensely contributed to the biomedical and automotive industries through improving the mechanical, lubrication, and corrosion resistance properties. In the present work, the considered process parameters are the preheating temperature (100°C and 200°C), along with the room temperature (24°C), cutting speed, sawing angle, pulse frequency, and laser power. The ranges of cutting speed and sawing angle are 0.1–1.1 mm s−1and 0.1°–1°, respectively. Besides, pulse frequency and laser power vary from 55 kHz to 85 kHz and from 15 W to 45 W, respectively. The constant parameters are the pulse width of 99% and assist air pressure of 6 kgf cm−2. The variable parameters for the analysis are cut width and heat-affected zone (HAZ) width. The article aims to showcase a comprehensive study of fiber laser process parameters at different temperatures (preheated condition and room temperature) with variable sawing angles to produce better process control and bring about each considered process parameter’s critical value. The experimental results show that higher dimensions of cut width and HAZ width are observed at 200°C with the increment of sawing angle and laser power, compared to other temperatures. With the increment of cutting speed and laser power, the HAZ width tends to rise sharply. A significant drop in cut width and HAZ width dimensions is observed with the increment in pulse frequency for any temperature.

Natural fibre composites have received worldwide attention due to their good mechanical properties, lightweight and low density. Due to these advantages, the natural fibre composites have been used in various engineering applications. Drilling is one of the most frequent machining operations performed on hybrid sisal–jute polymer composites, to assemble the numerous structural components by using mechanical joining process. Furthermore, the machining of fibre reinforced composite material has attracted several researchers because of its non-homogeneous and anisotropic structure. The present research work concerns with the experimental studies on the drilling process of hybrid sisal–jute epoxy composite, using three different types of drill geometry (twist drill, step drill and core drill). The significance of the current work aims to reveal the effect of drill geometry configuration and drilling parameters in terms of drilling-induced force and damages (delamination and surface roughness) for the drilling of hybrid natural fibre composites. Drilling forces, drilling-induced damages and hole quality attributes were experimentally investigated for different drill geometries. The delamination and surface roughness type damages are revealed by microscopic analysis with the help of scanning electron microscope (SEM). The results show that twist drill is best suited for the hole- and force-induced damages.

Laser Powder Bed Fusion (LPBF) is one of the revolutionary technologies that can fabricate complex-shaped components by selective melting of the pre-placed powder layer, using high-power laser as directed by the input digital files. Generally, research on the LPBF process is called out for layer thickness (LT) up to 50 µm and smaller beam diameter (≤100 µm), but it has lower productivity. In LPBF, higher productivity can be achieved with higher LT (>50 µm), but it consists of various process instabilities. In the present work, parametric studies are performed by laying Ni-Cr-Fe-Nb-Mo single tracks, using LPBF at higher LT. The process parameters such as laser power (P), scan speed (v), and LT are varied among 150–450 W, 0.04–0.1 m s−1, and 80–160 µm, respectively, at three levels each. For the range of parameters under investigation, the maximum track width of 610 µm and aspect ratio of 7.63 are achieved at a Pof 450 W and vof 0.04 m s−1at 80 µm LT. It is observed that an increase in the energy density and layer thickness resulted in the reduction of track width and aspect ratio due to material vaporization occurring from poor heat conductivity due to unconventionally high powder layer thickness. It is also observed that the build rate increases with an increase in P, v, and LT. As single tracks are basic building blocks, the obtained results can provide an insight into the effect of process parameters on LPBF-built single tracks at higher LT for building engineering components of required width with higher build rate. Furthermore, the track dilution is also found to increase with the increase in Pand decrease in v.

The advanced machining of components used in miniature unmanned aircraft vehicles is the focus of this study. The finite element method (FEM) is used to predict forces and temperatures using cutting tool inserts with a thin nanostructured film of high integrity. Similarity models are used to validate the finite element results and to understand the influence of micromachining parameters on cutting temperatures generated when machining Al 380-0 alloy. The predicted results are compared to experimental forces and temperatures using a three-dimensional piezoelectric function dynamometer and a short-range infra-red wavelength thermal camera. Nanostructured thin layer coatings lower machining forces and temperatures, which are validated through FEM predictions and experimental observations. The experimental results suggest that increasing the cutting tool’s rake angle at higher depths of cut will reduce cutting temperatures, which are predicted using the similarity models for micromachining.

Fused deposition modeling (FDM) or 3D printing is one of the promising techniques widely preferred to fabricate complex and customized 3D objects or prototypes for various engineering and non-engineering applications. With the growing demands of customized prototypes, researchers are facing a major challenge for maintaining effective part quality with adequate surface finish and strength; and minimizing the cost, defects, and waste in 3D printing. Condition monitoring is one of the strategies to achieve the aforementioned. It has a huge potential to minimize defects and print failures in 3D printing. The main objective of this research work is to perform online condition monitoring of the nozzle status with the help of vibration signals in fused deposition modelling process. The effect of nozzle clogging on the consistency of material deposition and its effect on surface finish has experimentally investigated in this work. The set of experiments were performed by artificially creating the condition of nozzle clogging to investigate the effect of nozzle clogging on print quality (surface finish). Nozzle clogging condition was created by increasing the feed rate of polylactic acid (PLA) filament at a low heat supply rate to the nozzle by modifying the commands of 3D printer. The layer thickness was varied throughout the experiments to observe the nozzle clogging. The vibrations signals were acquired by using an accelerometer that was mounted near the nozzle. The data acquisition frequency of the accelerometer was 12500Hz. Further, the acquired vibration signals were analyzed using the Fast Fourier transformation (FFT) signal processing technique. Results revealed that nozzle clogging severely affects surface quality and geometrical accuracy of the fabricated 3D part due to nozzle vibration and non-uniform material deposition. Moreover, nozzle clogging and its relevant consequences like non uniform material deposition can be monitored using vibration signal-based condition monitoring during part fabrication and based upon that appropriate measures can be taken for defects and waste elimination.

Combinatorial and high-throughput experimentation (HTE) is achieving more relevance in material design, representing a turning point in the process of accelerated discovery, development, and optimization of materials based on data-driven approaches. The versatility of drop-on-demand inkjet printing (IJP) allows performing combinatorial studies through fabrication of compositionally graded materials with high spatial precision, here by mixing superconducting REBCO precursor solutions with different rare earth (RE) elements. The homogeneity of combinatorial Y1–xGdxBa2Cu3O7samples was designed with computational methods and confirmed by energy-dispersive X-ray spectroscopy (EDX) and high-resolution X-ray diffraction (XRD). We reveal the advantages of this strategy in the optimization of the epitaxial growth of high-temperature REBCO superconducting films using the novel transient liquid-assisted growth method (TLAG). Advanced characterization methods, such as in situ synchrotron growth experiments, are tailored to suit the combinatorial approach and demonstrated to be essential for HTE schemes. The experimental strategy presented is key for the attainment of large datasets for the implementation of machine learning backed material design frameworks.

World-wide use of wireless sensor networks (WSNs) has urged the need for energy-efficient, distributed routing algorithms. The interest of researchers from the past decade is in energy-efficient routing. In this paper, sequential quadratic programming (SQP) based multi-path routing formulation focusing on improving lifetime and delay is represented, namely EBDA-DEFL. This SQP based formulation is solved using the optimisation tool after that same formulation is solved using particle swarm optimisation (PSO). Also, a quota strategy for traffic load distribution is also introduced to mitigate the negative effects of multi-path routing. The proposed work is experimented and compared with existing algorithms to analyse its quality over previous work. Comparison has been done in terms of first node death, half node death, last node death, delay, and time consumed by Fminimax and PSO. Simulation results confirm the supremacy of proposed work over the existing ones.

Conventional cutting fluids used in gear hobbing have negative impacts on the environment and health of the machine operators thereby adversely affecting the sustainability of the gear hobbing process. This paper reports on MQL assisted hobbing (MQLAH) using environment friendly fatty alcohol-based lubricant to manufacture superior quality spur gears. Experimental investigation was conducted to study of influence of six parameters of MQLAH namely hob cutter speed, axial feed, depth of cut, lube flow rate, air pressure, and nozzle angle on microgeometry deviations, avg. and max. values of flank surface roughness, and material removal rate to identify their optimum ranges to manufacture better quality spur gears with maximum productivity. Deviations in total profile, lead, cumulative pitch and radial runout were used to evaluate microgeometry of the spur gears. It revealed that depth of cut has no considerable effect on the spur gear quality. It identified that higher value of hob cutter speed, lower value of axial feed, optimum values of lube flow rate as 100 ml/h, nozzle angle as 30°, and air pressure in a range from 3 to 5 bar yield superior quality of spur gears by MQLAH.

Persistent sensing requires sensor nodes to keep functioning for a longer duration. Different amounts of incoming packets on some sensor nodes after deployment lead them to deplete their energy faster compared to other nodes without sending the information about their death to the sink node. It results in the formation of energy holes in the network and hence packet loss problem starts. In this study, this problem is overcome by prior notification to the sink about scarcity of resources by setting a dynamic threshold and also, packet delivery is sustained by using a fault tolerance strategy. Simulation analysis shows that proposed work is doing better in terms of packet delivery ratio and number of dead nodes. Also, network lifetime of the proposed work is found to be 73% of the total time duration while its competitor approach has network lifetime 64%.

In this study, a nickel-based superalloy Inconel 718 material was developed through direct metal laser sintering process. To enhance the mechanical properties, printed material was heat-treated at two different conditions in the combination of solution and ageing. The transformations of microstructure from original anisotropic phase were studied using optical microscope. The changes in mechanical properties were evaluated. The hardness of the heat-treated samples obtained is 35HRC and 39HRC for the heat treatment plan at 1100 °C + 845 °C and 980 °C + 720 °C (solution + ageing), respectively. Further, micro-holes were machined on these two material samples using spark erosion micro-machining or micro-electric discharge machining (µEDM) process. Applied voltage, capacitance and material hardness were three major variable parameters. Experiments were performed with hollow tungsten carbide rod of 300 µm in diameter as a drill tool rotating at a speed of 1500 rpm for a constant machining time of 30 min. Optical and scanning electron micrographs were used to analyse the hole quality and therefore the performance of µEDM. Perfect concentric drill hole was produced with 35HRC sample than the other. Weld spatters and metal drops were found around the surface of 39HRC sample. The range of drill hole varied to a maximum of ϕ385 µm in low-hardness and ϕ400 µm in high-hardness samples. The depth of drill hole was maximum with high hard sample at 100 V and 100 nF process condition. Light spectroscope-based roughness characterization revealed that the minimum surface roughness measured was 6.946 µm in low hard and 9.829 µm in high hard material.

In this paper, surface morphology investigation of miniature spur gears manufactured by abrasive water jet machining is discussed. Water jet pressure, abrasive flow rate and stand-off-distance are the varying input parameters to study the surface morphology (surface roughness and topography) of the machined gears. From the investigation, the water jet pressure has highly influenced (with 47% contribution) the surface quality and found as a predominant process parameter. SEM micrograph study found that wear scars and clinging effects are the major surface defects found over the machined surfaces of the gear teeth. Maximum and minimum peaks of the wear tracks are observed with white light spectroscope. The best surface morphology with average surface roughness value 1.08 μm was achieved at 350 MPa water jet pressure, 225 g/min abrasive mass flow rate, and 1mm stand-off distance. The present work identifies the potential of AWJM process for manufacturing of high quality miniature gears.

Sustainable manufacturing is the creation of products using technologies capable of decoupling the factors that may adversely affect the environment. One such technology is thin film coating, extensively used for various commercial applications. Achieving energy and resource efficiency, cost reduction, short process chain of manufacturing and long life for tools and products are some of the benefits of using thin film coatings. This technology significantly contributes to strengthening all three pillars, that is, environment, economy and society of sustainability. This special issue aims to highlight some of the critical application areas of thin film coatings under sustainable manufacturing, focusing on machining.

The cost-effective synthesis of a series of metal propionate powders (copper, yttrium, barium, samarium, gadolinium, and ytterbium) is developed through single chemical reactions resulting in five novel crystalline forms. These complexes are valuable precursors for the preparation of epitaxial REBa2Cu3O7-δ(REBCO) superconducting films (here, RE = Y, Sm, Gd, and Yb) through the innovative transient liquid-assisted growth (TLAG) process based on chemical solution deposition (CSD). TLAG-CSD shows impressive results with YBa2Cu3O7-δ(YBCO), obtaining critical current densities of 2.6 MA/cm2(77 K) on 500 nm films at unprecedented growth rates (50–2000 nm/s), boosting unprecedented high-throughput industrial production. With a cardinal concern on designing the pyrolysis toward optimal nanocrystalline films for TLAG, an analysis of the thermal behavior of the synthesized precursors is essential. Decomposition pathways for each metal propionate are established, and compatibility with TLAG-CSD is corroborated. Metal–organic solutions for these REBCO systems are successfully prepared, and their rheological properties and thermal behavior are analyzed. This work demonstrates homogeneous nanocrystalline films through propionate-based REBCO precursor solutions, including several rare-earth ions, which display exemplary chemical and microstructural characteristics crucial for TLAG, and provides a base for a wide variety of CSD-based functional oxides.

The present study examines herd behaviour in the Indian equity market using daily prices of 11 broad market indices, 12 sectoral indices, 16 strategic indices and 11 thematic indices from 1 January 2016 to 31 March 2022. For examining herd behaviour, daily returns, overnight returns, intraday spread, absolute market return and squared market return are calculated. Nifty 500 is used as a proxy index for the whole market. The regression models suggested by Christie and Huang (1995) and Chang et al. (2000) are used to calculate Cross-Sectional Standard Deviation (CSSD) and Cross-Sectional Absolute Deviation (CSAD) respectively, which measure the equity return dispersions. It is observed that herding exists in the Indian equity market when we calculate return dispersions using intraday spread. However, no herd presence is found when return dispersions are calculated through daily return, overnight return, absolute market return and squared market return. These results may be useful for investors, policy makers and regulatory bodies. Investors might design their investment strategy while making investment decision. Regulators might be able to formulate their policies to ensure market efficiency in the Indian equity market.

Hyperglycemia, obesity, insulin resistance, dyslipidemia and hypertension are interrelated cardiometabolic risk factors for the development of type-2 diabetes and metabolic syndrome. Prevalence of type-2 diabetes is growing at an alarming rate. Treatment target for type-2 diabetes is to keep daily glucose profile as close as possible to that of a non-diabetic person. Sulfonylureas, thiazolidinediones, meglitinides, biguanides and acarbose inhibitors are already being used in controlling glucose levels in type-2 diabetes. This review discusses the new drugs with novel mechanism of actions; which are in pipeline and were marketed recently or will be in market in near future. Keywords: Type-2 diabetes | Pharmacotherapy | Receptor agonists | Bromocriptine | Exenatide | Incretins, Introduction Type-2 diabetes is the most common metabolic disorder worldwide, and its prevalence is growing at an alarming rate in both developed and developing countries. This growth has been related [...]

Baculovirus expression is a time-tested technique to produce proteins in insect cells, in high quality and quantity for a range of applications. MultiBac is a baculovirus expression system we developed originally for producing multiprotein complexes comprising many subunits, for structural and mechanistic studies. First introduced in 2004, MultiBac is now in use in many laboratories worldwide, accelerating research programmes in academia and industry. We have continuously optimized our MultiBac system, providing customized reagents and standard operating protocols to facilitate its use also by non-specialists. More recently, we have generated MultiBac genomes tailored for specific purposes, for example, to produce humanized glycoproteins, high-value pharmaceutical targets including kinases, viral polymerases, and virus-like particles (VLPs) as promising vaccine candidates. By altering the host tropism of the baculovirion, we created MultiBacMam, a heterologous DNA delivery toolkit to target mammalian cells, tissues and organisms. Introducing CRISPR/Cas modalities, we set the stage for large-scale genomic engineering applications utilizing this high-capacity DNA delivery tool. Exploiting synthetic biology approaches and bottom-up design, we engage in optimizing the properties of our baculoviral genome, also to improve manufacturing at scale. Here we provide a perspective of our MultiBac system and its developments, past, present and future.

In the present work, an attempt is made to partially replace high cost silica sand with sustainable eco-friendly cow-dung. The practical utility of cow dung as an additive material that facilitates binding in sand moulds has been tested. The Taguchi method is used to plan and conduct nine experiments with three replicates each. Pareto analysis of variance study is performed to understand the practical significance of moulding sand variables, that is, percentage of cow dung, clay, water, and degree of ramming on sand mould properties. The conflicting multiple objective functions (maximize mould hardness, and minimize collapsibility and gas evolution) are optimized by utilizing the Data Envelopment Analysis Ranking (DEAR) method. The optimal parameters i.e. 6% of clay, 4% of water, 5% of cow-dung and 4 numbers of ramming strokes are obtained by applying a hybrid Taguchi-DEAR method. These parameters show the best moulding properties are: mould hardness 55, gas evolution 5.9 ml·g−1, and collapsibility 470 g·cm−2. Thereafter, a Lovejoy coupling made of aluminium is cast in the sand mould prepared with cow dung and without cow dung, with the optimum set of parameters. The mechanical properties, surface finish, and microstructure of the casting cast with cow-dung are better than that without cow-dung.

In the past decade, research community has paid a good attention towards energy-efficient data routing in wireless sensor networks (WSNs). WSNs have left an imprint in various areas, but sensor nodes are battery powered having limited lifetime. So, while designing the routing protocols, the prime concern is reducing the energy consumption and elongating the lifetime of the network. In this review, we have done comprehensive review on routing protocols focusing on prolonging the network lifetime. We have proposed different classifications of routing protocols to have the in-depth knowledge about the literature. These are operation based, environment based, objectives based and a combined form of these along with discussed papers. Thereafter, strength and weakness of the papers are found by doing a comparative analysis and further, a feature-based analysis is done as well to get a quick insight about the network models. Subsequently, future directions are discussed. This review article is written with a clear objective, which is to enable the beginners who want to do research on energy efficiency of the WSNs, by equipping them with understanding of different methods of achieving the same objective and grouping them with the similarity of their utility.

Nonconventional or advanced machining processes such as electric discharge machining, electrochemical machining, abrasive water jet machining, and laser beam machining have been widely used as a viable alternate to the conventional processes to manufacture high-quality engineered parts having certain typical features. In spite of their special features, wider acceptance, and use, they suffer from certain inherent limitations with regard to sustainability such as high consumption of energy and resources; generation of toxic liquid, gases, and solid wastes; risk for health and safety; air pollution; generation of waste and its disposal problems; and workpiece contamination and thermal damage to the parts being produced. It is found that these factors all adversely affect the environment to a certain extent. Innovative sustainable techniques such as dry, near-dry, and green electric discharge machining; green and hybrid electrochemical machining; ice-jet machining; and eco- and underwater laser beam machining, etc. have been developed to address sustainability challenges and greatly benefited with improvements in quality, productivity, and sustainability. This review article first introduces four major nonconventional machining processes, discusses their inherent sustainability issues and challenges, and presents state-of-the-art review of the work conducted using sustainable innovative techniques and strategies with an aim to encourage academics, researchers, and engineers for research and developments in order to establish the field further. The literature review offered in this article is based on over 80 articles published from 1975 to 2017. Finally, the article ends up with concluding remarks and recommending possible avenues to stimulate future research.

Ni55.8Ti shape memory alloys (SMAs) find applications in different fields of medical and engineering. In every field, surface integrity greatly affects the functional performance of shape memory alloy parts. In the present work, wire spark erosion machining of Ni55.8Ti shape memory alloys has been conducted and surface integrity parameters of the machined specimens have been evaluated. Experiments are designed using Taguchi L16robust design of experiment technique. Effect of important process parameters, i.e. voltage, pulse-on time and pulse-off time on maximum surface roughness has been studied. Deterioration in surface integrity at various combinations of pulse-on and pulse-of time which produced high discharge energy has been observed. Scanned electron microscopic investigation, energy dispersive spectroscopy and XRD analyses, roughness measurement, and micro-hardness testing results are presented, analyzed and discussed. Optimization of process parameters resulted in surface integrity enhancement with low roughness (Rt– 7.78μm and Ra– 1.45μm) and very thin recast layer (4–6μm) along with minimum subsurface defects.

Cross-linking mass spectrometry has become an important approach for studying protein structures and protein–protein interactions. The amino acid compositions of some protein regions impede the detection of cross-linked residues, although it would yield invaluable information for protein modeling. Here, we report on a sequential-digestion strategy with trypsin and elastase to penetrate regions with a low density of trypsin-cleavage sites. We exploited intrinsic substrate-recognition properties of elastase to specifically target larger tryptic peptides. Our application of this protocol to the TAF4–12 complex allowed us to identify cross-links in previously inaccessible regions.

This paper explains and demonstrates how miniature gears of excellent surface quality can be manufactured by modern machining methods. Necessity of gear finishing by post processes such as grinding, lapping, honing etc. is the major limitation of all conventional methods of miniature gear manufacturing. To overcome this limitation, modern machining methods such as wire-EDM, abrasive waterjet machining, and laser beam machining etc. have been explored. It resulted in significant achievements in geometric accuracy, surface finish, and integrity of miniature gears. Using modern machining methods, it is possible to manufacture gears equipped with precision finish (average roughness 1 μm), high geometric accuracy (DIN quality 5), and defect-free tooth surfaces at significantly low cost. This paper aims to facilitate researchers by providing information on important aspects as regards to the manufacturing of miniature gears by modern machining methods and hopes research and development in this area to establish the field further.