Publication1

The structural transformation path in most developing economies follows an employment shift towards service activities, skipping an industrialisation phase. In this paper, we explore how this premature deindustrialisation trend affects the inclusive growth trajectory of middle-income economies. Considering the trends in manufacturing employment and value-added share, we identify premature deindustrialisation phases in economies. We apply panel fixed-effects and bootstrap-corrected dynamic fixed-effects models to empirically examine the relationship between premature deindustrialisation and income inequality. Our findings suggest that income inequality rises with premature deindustrialisation if the displaced workers are absorbed into market services (especially with employment movement towards non-business market services such as trade, transport, hotels, and accommodation). In contrast, if non-market services (such as education and health) or business services (such as banking and financial services) are the dominant employment provider, it helps to reduce income inequality even in the presence of premature deindustrialisation.

This work aims to analyze the complexity of surface electromyography (sEMG) signals under muscle fatigue conditions using Hjorth parameters and bubble entropy (BE). Signals are recorded from the biceps brachii muscle of 25 healthy males during dynamic and isometric contraction exercises. These signals are filtered and segmented into 10 equal parts. The first and tenth segments are considered as nonfatigue and fatigue conditions, respectively. Activity, mobility, complexity, and BE features are extracted from both segments and classified using support vector machine (SVM), Naïve bayes (NB), k-nearest neighbor (kNN), and random forest (RF). The results indicate a reduction in signal complexity during fatigue. The parameter activity is found to increase under fatigue for both dynamic and isometric contractions with mean values of 0.35 and 0.22, respectively. It is observed that mobility, complexity, and BE are lowest during fatigue for both contractions. Maximum accuracy of 95.00% is achieved with the kNN and Hjorth parameters for dynamic signals. It is also found that the reduction of signal complexity during fatigue is more significant in dynamic contractions. This study confirms that the extracted features are suitable for analyzing the complex nature of sEMG signals. Hence, the proposed approach can be used for analyzing the complex characteristics of sEMG signals under various myoneural conditions.

A tracked vehicle employs a special transmission to generate a speed difference between the inner and outer tracks for steering. In this paper, the dynamic model of one of the most widely used steering transmissions called double differential steering has been derived and integrated with a multi-body tracked vehicle model. A simplified multi-body model for tracks has been proposed to reduce the computational and numerical difficulties arising from a detailed three-dimensional multi-body model. The accuracy of the proposed model is demonstrated by extensive comparison with a detailed multi-body model developed using the Tracked Vehicle module of the commercial software ADAMS. Simulations are carried out using the integrated tracked vehicle model to demonstrate the effects of changes in three-dimensional vehicle dynamic performance with design changes in powertrain systems.

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant of concern (VoC) Omicron (B.1.1.529) has rapidly spread around the world, presenting a new threat to global public human health. Due to the large number of mutations accumulated by SARS-CoV-2 Omicron, concerns have emerged over potentially reduced diagnostic accuracy of reverse-transcription polymerase chain reaction (RT-qPCR), the gold standard diagnostic test for diagnosing coronavirus disease 2019 (COVID-19). Thus, we aimed to assess the impact of the currently endemic Omicron sublineages BA.4 and BA.5 on the integrity and sensitivity of RT-qPCR assays used for coronavirus disease 2019 (COVID-19) diagnosis via in silico analysis. We employed whole genome sequencing data and evaluated the potential for false negatives or test failure due to mismatches between primers/probes and the Omicron VoC viral genome. Methods: In silico sensitivity of 12 RT-qPCR tests (containing 30 primers and probe sets) developed for detection of SARS-CoV-2 reported by the World Health Organization (WHO) or available in the literature, was assessed for specifically detecting SARS-CoV-2 Omicron BA.4 and BA.5 sublineages, obtained after removing redundancy from publicly available genomes from National Center for Biotechnology Information (NCBI) and Global Initiative on Sharing Avian Influenza Data (GISAID) databases. Mismatches between amplicon regions of SARS-CoV-2 Omicron VoC and primers and probe sets were evaluated, and clustering analysis of corresponding amplicon sequences was carried out. Results: From the 1164 representative SARS-CoV-2 Omicron VoC BA.4 sublineage genomes analyzed, a substitution in the first five nucleotides (C to T) of the amplicon's 3′-end was observed in all samples resulting in 0% sensitivity for assays HKUnivRdRp/Hel (mismatch in reverse primer) and CoremCharite N (mismatch in both forward and reverse primers). Due to a mismatch in the forward primer's 5′-end (3-nucleotide substitution, GGG to AAC), the sensitivity of the ChinaCDC N assay was at 0.69%. The 10 nucleotide mismatches in the reverse primer resulted in 0.09% sensitivity for Omicron sublineage BA.4 for Thai N assay. Of the 1926 BA.5 sublineage genomes, HKUnivRdRp/Hel assay also had 0% sensitivity. A sensitivity of 3.06% was observed for the ChinaCDC N assay because of a mismatch in the forward primer's 5′-end (3-nucleotide substitution, GGG to AAC). Similarly, due to the 10 nucleotide mismatches in the reverse primer, the Thai N assay's sensitivity was low at 0.21% for sublineage BA.5. Further, eight assays for BA.4 sublineage retained high sensitivity (more than 97%) and 9 assays for BA.5 sublineage retained more than 99% sensitivity. Conclusion: We observed four assays (HKUnivRdRp/Hel, ChinaCDC N, Thai N, CoremCharite N) that could potentially result in false negative results for SARS-CoV-2 Omicron VoCs BA.4 and BA.5 sublineages. Interestingly, CoremCharite N had 0% sensitivity for Omicron Voc BA.4 but 99.53% sensitivity for BA.5. In addition, 66.67% of the assays for BA.4 sublineage and 75% of the assays for BA.5 sublineage retained high sensitivity. Further, amplicon clustering and additional substitution analysis along with sensitivity analysis could be used for the modification and development of RT-qPCR assays for detecting SARS-CoV-2 Omicron VoC sublineages.

The Direct Analysis Method (DAM) of ANSI/AISC 360-16 enables the prediction of design strength in columns without the use of effective length factors. While adopting DAM, a designer must ensure that the software used to calculate the design demands, can capture the second-order effects accurately. For two-dimensional (2D) second-order analysis of steel framed structures, there are several benchmark problems published in the literature, and in contrast very few for 3D frames. This paper presents 3D benchmark problems that accurately capture coupled flexural, and torsional behavior. A geometrically exact total Lagrangian formulation is used where Euler angles define the rigid body dynamics of the system in space. The governing equations in space coordinates are formed using fully nonlinear, objective Jaumann strains and stresses before using principle of virtual work to obtain a 16-degree-of-freedom space beam element. Two benchmark problems are presented - (i) a right angle bent which has no restraint to out-of-plane displacements, and (ii) the bent frame with adequate restraints against out-of-plane displacements at the joints. In the former, the lateral-torsional deformations of the beam cause significant biaxial bending moments in the column. In the second benchmark problem, the behavior of the frame with adequate lateral restraint is brought out. The notional loads have been applied to cause a coupled biaxial bending and twist deformations. It was shown that the exclusion of twist from the deformation response of the frame leads to the underestimation of design demands which is evident from the interactive surface. The paper also suggests a few combinations of notional loads to bring out the true buckling behavior of the frame.

Convolutional Neural Networks, CNNs are known for their unparalleled accuracy in the classification of benign images. It is observed that neural networks are prone to having lesser accuracy in the classification of images with noise perturbation. The following study resulted in inferences to establish that CNNs are extremely vulnerable at predicting noisy images while Feed-forward Neural Networks, FNNs are least affected due to noise perturbation, maintaining their accuracy almost undisturbed. FNNs showcase better classification accuracy when tested with noise-intensive, single-channelled images that are just sheer noise to human vision. The hand-written digit images from the MNIST dataset t are classified using the architectures of FNNs with 1 and 2 hidden layers and CNNs with 3, 4, 6, and 8 convolutions, which provide the stated experimental inferences. Deviations in the performances of these architectures analyzed systematically propose that FNNs stand out to show a classification accuracy of more than 85%, irrespective of the intensity of noise and CNNs witness a trend in the reduction in speed of classification accuracy against increasing noise intensities. Correlation analysis and mathematical modelling of the accuracy trends act as roadmaps to picture that the change in the speed of classification accuracy against increasing noise intensities for CNN with 8 convolutions is half of that of the rest of the CNNs. This experimental study is a step to quantify the performance of deep learning image classification models in the context of adversarial images.

This paper reports the critical reviews on the gassing tendency of different insulating fluids along with the precautionary measures to be considered during their fault diagnosis in transformer insulation. The experimental techniques and procedures for identifying the gassing due to electrical and thermal stress along with the stray gassing phenomenon has been elucidated. The different interpretation schemes used for determining the faults in transformers results in unexpected errors when the historical data relating to mineral oil is used for the other alternative fluids. Mineral oil and natural ester show a positive gassing tendency compared to synthetic ester which exhibit a negative gassing tendency. The stray gases are mostly due to breakage of C-C bonds under normal operating temperature of transformer. Among the different hydrocarbons, hydrogen and ethylene are more predominantly formed under lower temperatures. The silicone oil and ester fluids are more stable even under localised hot spots simulated observing a lesser gassing compared to the mineral oil. The impact of additives along with the oxygen and water content in the insulating fluids can lead to the stray gas’s causing confusion towards the identification of actual faults occurring in transformers. Furthermore, the regeneration of insulating fluids using different adsorbents reduces the gassing tendency depending on the number of cycles used for its reclamation.

The paper presents a model-based demand-responsive traffic control system for mixed traffic conditions using sample travel time data. The model incorporates mixed traffic characteristics such as heterogeneity, limited lane discipline of varied vehicle types, and spatio-temporal traffic dynamics across the width of the road. The methodology includes optimization of intersection performance by accommodating the varying traffic demand through signal timing variables. On validation, the model yielded reliable queue estimates within a close proximity of the actual, ranging from 20 to 40 meters. Upon optimization, the proposed model reduced total intersection delay by 15.42% on an average across 14 cycles, for near-saturated traffic conditions. The optimal green splits are found to be responsive to the varying traffic demand. The proposed system is simple and can be easily implemented in the mixed traffic conditions.

The vital role of structurally and functionally stable vasculature in engineered tissues is well-established in regenerative medicine. Large-volume, natural, and synthetic tissue constructs require a high degree of perfusion and nutrient diffusion to meet the physiological demands of the encapsulated cells. Additionally, cancer tissue models fabricated using various scaffolds and matrices also need to incorporate tumor-mimetic abnormal vasculature to study the influence of angiogenesis on tumor growth, progression, and anti-cancer drug delivery. In this chapter, prominent hydrogel-based matrices that have been developed for vascular tissue engineering as well as modeling of the tumor vasculature and angiogenesis are discussed. Various microenvironmental considerations (including biophysical and biochemical characteristics of the matrix) required for emulating vascular regeneration as well as tumor angiogenesis are described. A wide range of hydrogel-based models (including natural, synthetic and hybrid materials) and associated biofabrication strategies (spanning molecular design to macroscale materials processing) for creating vascularized scaffolds are elaborated. Overall, this chapter provides an overview to the reader on creation of engineered scaffolds for implementation in tissue vascularization and repair and in disease models for future applications in drug testing.

We introduce the notion of public key encryption with secure key leasing (PKE-SKL). Our notion supports the leasing of decryption keys so that a leased key achieves the decryption functionality but comes with the guarantee that if the quantum decryption key returned by a user passes a validity test, then the user has lost the ability to decrypt. Our notion is similar in spirit to the notion of secure software leasing (SSL) introduced by Ananth and La Placa (Eurocrypt 2021) but captures significantly more general adversarial strategies. (In more detail, our adversary is not restricted to use an honest evaluation algorithm to run pirated software.) Our results can be summarized as follows: 1.Definitions: We introduce the definition of PKE with secure key leasing and formalize a security notion that we call indistinguishability against key leasing attacks (IND-KLA security). We also define a one-wayness notion for PKE-SKL that we call OW-KLA security and show that an OW-KLA secure PKE-SKL scheme can be lifted to an IND-KLA secure one by using the (quantum) Goldreich-Levin lemma.2.Constructing IND-KLA PKE with Secure Key Leasing: We provide a construction of OW-KLA secure PKE-SKL (which implies IND-KLA secure PKE-SKL as discussed above) by leveraging a PKE scheme that satisfies a new security notion that we call consistent or inconsistent security against key leasing attacks (CoIC-KLA security). We then construct a CoIC-KLA secure PKE scheme using 1-key Ciphertext-Policy Functional Encryption (CPFE) that in turn can be based on any IND-CPA secure PKE scheme.3.Identity Based Encryption, Attribute Based Encryption and Functional Encryption with Secure Key Leasing: We provide definitions of secure key leasing in the context of advanced encryption schemes such as identity based encryption (IBE), attribute-based encryption (ABE) and functional encryption (FE). Then we provide constructions by combining the above PKE-SKL with standard IBE, ABE and FE schemes. Notably, our definitions allow the adversary to request distinguishing keys in the security game, namely, keys that distinguish the challenge bit by simply decrypting the challenge ciphertext, as long as it returns them (and they pass the validity test) before it sees the challenge ciphertext. All our constructions satisfy this stronger definition, albeit with the restriction that only a bounded number of such keys is allowed to the adversary in the IBE and ABE (but not FE) security games. Prior to our work, the notion of single decryptor encryption (SDE) has been studied in the context of PKE (Georgiou and Zhandry, Eprint 2020) and FE (Kitigawa and Nishimaki, Asiacrypt 2022) but all their constructions rely on strong assumptions including indistinguishability obfuscation. In contrast, our constructions do not require any additional assumptions, showing that PKE/IBE/ABE/FE can be upgraded to support secure key leasing for free.

Laser surface melting (LSM) is the most helpful technique to improve the surface properties of the high-entropy alloy (HEA). LSM reduces the pores, voids, cracks, and other surface defects at the sample's surface. LSM utilized high-power fiber laser to partially or fully melt the surface to enhance the various properties such as wear, corrosion, and fatigue resistance without impacting the bulk material properties. LSM of HEA enhances the microhardness and wear properties by reducing the pores and surface defects. It facilitates flexibility such as control over laser spot diameter, penetration depth, mode of operation, and higher cooling rate, which increase its applicability in various applications such as automobile, medical, and aerospace. The relevance of LSM in wear-resistant applications is increasing among multiple sectors. The application domain of LSM ranges from cladding to repairing components. The LSM gained popularity over time due to its ability to improve the surface properties of specimens in a lower lead time. The HEA is a novel class of material used for wear and high-temperature applications due to its high configurational entropy and superior wear, oxidation, and corrosion resistance. Many researchers are working on the LSM of various HEAs to be applied in wear resistance applications. This chapter introduces the different types of laser-based surface modification techniques and their application in detail. This chapter also describes the effect of LSM on the microstructure and microhardness of atmospheric plasma sprayed HEA and compares it with the as-deposited alloy. This chapter will serve as a quick start for researchers to appreciate the improvement with laser-based surface modification techniques.

Numerical investigations are carried out in flow past spring mounted heated circular cylinder undergoing vortex-induced vibrations. The computations are performed using Open Source Field Operations and Manipulation (OpenFoam). The existing solver has been modified to include thermal effects of the circular cylinder. Two degrees of freedom, i.e., the transverse and streamwise oscillations of the cylinder, are considered in the present study. The computations are carried out assuming a negligible damping ratio at Re values of 150 and 200. Wake characteristics are examined for different values of reduced velocity (Ur) varying from 3 to 8. The effect of Ur on cylinder displacement, lock-in behaviour, and frequency ratio is disclosed for the heated cylinder. Unsteady flow and thermal characteristics of the wake are illustrated using vorticity and temperature contours. The variation in the average value of Nusselt number around the cylinder has been plotted for different values of reduced velocity. Force coefficients on the cylinder surface are also reported for varying Ur.

In addition to serving high-value-to-weight goods, the air cargo market is expanding substantially mainly because of globalisation and the need for increased responsiveness in supply chains. At the same time, the theory of air cargo revenue management is far from the contemporary practices because of cargo-specific complexities like uncertain, multidimensional capacities, variable tendering, and forwarder’s market power. This paper surveys the scientific contributions relevant to air cargo revenue management. We provide a comprehensive review of the developments in both quantity and pricing revenue management decisions. Additionally, we substantiate each decision with the appropriate dynamic programming formulation, which helps in highlighting the extensions to the current literature. We conclude our discussion by enumerating the potential prospects that are great revenue-yielding opportunities. This review links theoretical contributions and practical problems and serves as the signpost for the 30-year-old air cargo revenue management.

This chapter describes a coastal and marine data information system that can be used for Maritime Spatial Planning. The system takes advantage of Internet mapping and web services technology to publish data as maps. These maps are created dynamically and enable the visualization of a diverse and growing collection of environmental data. Capabilities of the system include (i) visualization of environmental parameters on 2D maps; (ii) visualization of location-specific depth profiles of selected parameters; (iii) time animation of grids of environmental parameters and (iv) preparation of digital elevation and cultural object data sets for 3D terrain visualization (Durairaju et al., 2003, 2010). The function and interaction between key components of the system are described to illustrate the working of the system. The use of a mature map publishing engine greatly eased the development of these capabilities into a web-based system.

This work reports a novel “divide and conquer” approach to estimate the principal thermal conductivities of an orthotropic material, specifically engineered with a view to demonstrate the potency of the inverse heat transfer method with unsteady temperature data. The sample is placed in a vacuum chamber maintained at a pressure of 8.6 (Formula presented.) mbar. The heat capacity of the engineered orthotropic material was determined via estimating the heat capacity of a solid SS304 in a sequential fashion. First steady-state experiments followed by a Bayesian estimation with the Metropolis Hastings-Markov Chain Monte Carlo method were done to obtain the thermal conductivity of a solid SS304 block. Using this as a prior, the heat capacity of solid SS304 was obtained through unsteady experiments followed by Bayesian estimation. The heat capacity of SS304 thus obtained is multiplied by the solidity of the engineered orthotropic material, and using this information, the three components of the orthotropic conductivity are estimated again using the Bayesian route. To expedite the estimation, a surrogate for the forward model was developed using artificial neural network. Finally, the retrieved parameters are used to determine the simulated temperatures through the forward model for the orthotropic material. These, when compared with the measured temperatures, gave excellent agreement.

This paper relates to the design of a novel reflectance pulse oximeter, which can measure not only the arterial oxygen saturation, but also that of carbon monoxide, in a non-contact manner. Such an instrument is especially relevant in the monitoring of patients who have a history of smoking, or those who have been exposed to carbon monoxide poisoning, such as from fires. The remote manner of measurement ensures that the risk of contact contamination is eliminated, and that the instrument can be used on infants as well, especially those born prematurely and having sensitive skin. A novel algorithm was devised which uses light sources of three different wavelengths to calculate the above mentioned saturations. A thorough sensitivity analysis was performed to determine the most suitable wavelengths for the purpose, which were determined to be 660 nm, 640 nm, and 940 nm. A system was designed to leverage the above mentioned algorithm, and the same was simulated using Simulink. The simulation gave satisfactory results, with maximum errors in calculation of oxygen and carbon monoxide saturations being 0.36% and 0.66%, respectively. These results are discussed along with measures that can be used to improve accuracy.

The transition of the conventional power grid into the smart grid requires continuous monitoring of integrated grids speared over wide-area through Phasor Measurement Units (PMU). These PMUs additionally perform protection and state estimation functions in the smart grid. This paper discusses implementation of a new phasor estimation method to eliminate the effects of Decaying DC (DDC) component and off-nominal frequencies during the extraction of the phasors from a relaying signal. The practical implementation of the proposed method in a low-cost microcontroller (ESP32-WROOM-32 development board) in compliance with the requirements of IEEE C37.118.1a-2011 standard is also demonstrated. The analysis of various existing algorithms estimating the phasors is carried out. The microcontroller is programmed with the best among the analysed algorithm and its feasibility to function as a proper Phasor Measurement Unit is tested. The newly designed PMU is rigorously tested with different estimation methods compliant with IEEE C37.118a-2011 standard. The comparison of the proposed method with different phasor estimation algorithms is also discussed.

Nonlinear controllers are useful if the equations governing the system dynamics are nonlinear. The fuel cell (FC)-fed boost converter is a nonlinear system as the VI characteristics of the fuel cell and the output voltage to duty cycle transfer function of the boost converter are nonlinear. The choice of a nonlinear controller depends on the dynamic performance of the FC-fed boost converter for wide load variations. This paper compares the performance of the system using conventional sliding mode control (CSMC) and super twisting sliding mode control (STSMC) strategies for tight voltage regulation for the load disturbance and reference voltage tracking. Simulation and experimental results of the fuel cell-fed 600 W boost converter prove the supremacy of STSMC strategy over CSMC strategy in terms of overshoot, undershoot, settling time and chattering reduction.