Some inherent limitations of the alloy process for superconducting Nb3Sn

The Alloy Process for making multifilamentary superconducting Nb₃Sn is critically examined. It is shown the process itself has certain inherent limitations to realize a reasonably high overall J_c. Further, the microstructure of the material produced by this process is unfavourable for high J_c and it is shown that at low currents avalanche like process may occur driving all superconducting filaments suddenly normal. Attention is drawn to other processes which seem free from the limitations discussed.     

Industrial fluorosis in cattle and buffalo around Udaipur, India

Signs of dental discolouration, difficulty in mastication, bony lesions, lameness, debility and mortality in domesticated animals, reared around superphosphate fertiliser plants located approximately 15 km north of Udaipur, Rajasthan prompted us to investigate for the occurrence of fluorosis. Out of 166 animals clinically examined, the prevalence rate was 17.4% (4/23) in calves below 1 year of age, 37.2% (16/43) in cattle between 1 and 3 years, 61.3% (46/75) in cattle above 3 years and 72% (18/25) in buffalo above 1 year. Dental fluorosis was common in buffalo compared to cattle of all the age groups. Fluoride levels in fodder and water, consumed by the animals were much higher than the recommended permissible limit. Mean fluoride concentrations in serum and urine were 1.53 +/- 1.27 and 26.4 +/- 6.17 mg l(-1) in calves below 1 year of age, 0.56 +/- 0.17 and 26.2 +/- 3.86 mg l(-1) in cattle of 1-3 years, 0.49 +/- 1.13 and 27.5 +/- 4.63 mg l(-1) in cattle above 3 years and 0.60 +/- 0.07 and 28.6 +/- 4.73 mg l(-1) in buffalo over 1 year, respectively. The values were significantly (P < 0.01) higher than those of control animals kept over a 15-km distance from the factories. Fluoride concentrations in the environmental sample collected from the affected locality were 534.4 +/- 74.9 mg kg(-1) in fodder, 1.19 +/- 0.29 mg l(-1) in pond water and 0.479 +/- 0.351 mg l(-1) in tube well water. It was concluded that the consumption of fodder and water contaminated by the fumes and dusts emitting from superphosphate fertiliser plants resulted in the development of chronic fluorotic lesions in cattle and buffalo.     

Multiagent based differential evolution approach to optimal power flow

This paper proposes a new differential evolution approach named as multiagent based differential evolution (MADE) based on multiagent systems, for solving optimal power flow problem with non-smooth and non-convex generator fuel cost curves. This method integrates multiagent systems (MAS) and differential evolution (DE) algorithm. An agent in MADE represents an individual to DE and a candidate solution to the optimization problem. All agents live in a lattice like environment, with each agent fixed on a lattice point. In order to obtain optimal solution quickly, each agent competes and cooperates with its neighbors and it can also use knowledge. Making use of these agent-agent interaction and DE mechanism, MADE realizes the purpose of minimizing the value of objective function. MADE applied to optimal power flow is evaluated on 6 bus system and IEEE 30 bus system with different generator characteristics. Simulation results show that the proposed method converges to better solutions much faster than earlier reported approaches.     

An attention-based deep learning model for credibility assessment of online health information

With the surge of searching and reading online health-based articles, maintaining the quality and credibility of online health-based articles has become crucial. The circulation of deceptive health information on numerous social media sites can mislead people and can potentially cause adverse effects on people's health. To address these problems, this work uses deep learning approaches to automate the assessment and scoring of online health-related articles' credibility. The paper proposed an Attention-based Recurrent Multichannel Convolutional Neural Network (ARMCNN) model. The proposed model incorporates a BiLSTM layer, a multichannel CNN layer, and an attention layer and predicts the credibility of online health information. To perform a reliable evaluation of the presented model, we utilize the health articles reviewed by the experts, compiled in a labeled dataset termed “Pubhealth,” which consists of thousands of health articles. The results are evaluated using five performance measures, accuracy, precision, recall, f1-score, and area under the ROC curve (AUC). Furthermore, we extensively compared the proposed model with different deep learning and machine learning models such as Long short-term memory (LSTM), Bidirectional LSTM, CNN (Convolutional neural network), and RNN-CNN. The experimental results showed that the proposed model produced state-of-the-art performance on the used dataset by achieving an accuracy of 0.88, precision of 0.92, recall of 0.87, f1-score of 0.90, and AUC of 0.94. Further, the proposed model yielded better performance than other benchmarked techniques for the credibility assessment of online health articles.     

Internet of Things in Healthcare: Architecture,Applications, Challenges,and Solutions

Healthcare, the largest global industry, is undergoing significant transformations with the genesis of a new technology known as the Internet of Things (IoT). Many healthcare leaders are investing more money for transforming their services to harness the benefits provided by IoT, thereby paving the way for the Internet of Medical Things (IoMT), an extensive collection of medical sensors and associated infrastructure. IoMT has many benefits like providing remote healthcare by monitoring health vitals of patients at a distant place, providing healthcare services to elderly people, and monitoring a large group of people in a region or country for detection and prevention of epidemics. This paper provides a review of IoT in the healthcare domain by first describing the enabling technologies for delivering smart healthcare, followed by some of the key applications of IoT in healthcare. Next, a fog-based architecture consisting of three layers for IoT-based healthcare applications is proposed. Finally, we focus on some of the open challenges of IoT in healthcare, like fault tolerance, interoperability, latency, energy efficiency, and availability. Existing solutions for these challenges are also discussed.     

Particle swarm optimization based K-means clustering approach for security assessment in power systems

Security assessment is a major concern in planning and operation studies of a power system. Conventional method of security evaluation performed by simulation involves long computer time and generates voluminous results. This paper presents a K-means clustering approach for classifying power system states as secure/insecure under a given operating condition and contingency. This paper demonstrates how the traditional K-means clustering algorithm can be profitably modified to be used as a classifier algorithm. The proposed algorithm combines particle swarm optimization (PSO) with the traditional K-means algorithm to satisfy the requirements of a classifier. The proposed PSO based K-means clustering technique is implemented in IEEE 30 Bus, 57 Bus, 118 Bus and 300 Bus standard test systems for static security and transient security evaluation. The simulation results of the proposed algorithm are compared with unsupervised K-means clustering, which uses different methods for cluster center initialization.     

Golden-Free Hardware Trojan Detection with High Sensitivity Under Process Noise

Malicious modification of integrated circuits in untrusted design house or foundry has emerged as a major security threat. Such modifications, popularly referred to as Hardware Trojans, are difficult to detect during manufacturing test. Sequential hardware Trojans, usually triggered by a sequence of rare events, represent a common and deadly form of Trojans that can be extremely hard to detect using logic testing approaches. Side-channel analysis has emerged as an effective approach for detection of hardware Trojans. However, existing side-channel approaches suffer from increasing process variations, which largely reduce the detection sensitivity and sets a lower limit of the sizes of Trojans detectable. In this paper, we present TeSR, a Temporal Self-Referencing approach that compares the current signature of a chip at two different time windows to isolate the Trojan effect. Since it uses a chip as a reference to itself, the method completely eliminates the effect of process noise and other design marginalities (e.g. capacitive coupling), thus providing high detection sensitivity for Trojans of varying size. Furthermore, unlike most of the existing approaches, TeSR does not require a golden reference chip instance, which may impose a major limitation. Associated test generation, test application, and signature comparison approaches aimed at maximizing Trojan detection sensitivity are also presented. Simulation results for three complex sequential designs and three representative sequential Trojan circuits demonstrate the effectiveness of the approach under large inter- and intra-die process variations. The approach is also validated with current measurement results from several Xilinx Virtex-II FPGA chips.     

Effect of fertilizers,irrigation and plant density on groundnut (Arachis hypogaea L)

Experiments were conducted on sandy clay loam soils of Tirupati Campus of Andhra Pradesh Agricultural University for two summer seasons of 1979 and 1980 to study the effect of fertilizers, irrigation and plant density on Spanish groundnut. Three fertilizer schedules (30 kg N, 20 kg P, 50 kg K; 60 kg N, 40 kg P, 10 kg K and 90 kg N, 60 kg P, 150 kg K ha^?1), three schedules of irrigation (irrigation at 25, 50 and 75% depletion of available soil moisture) and three plant densitites (1,000,000; 666,000; and 444,000 plants per ha) were tested in 3³ factorial confounded design with two replications. Groundnut responded to 60 kg N, 40 kg P and 10 kg K ha^?1 due to delayed sowings in 1979. However, response to fertilisers was marginal in 1980, when the sowings were done in optimum time. Pod yield tended to be maximum when irrigations were scheduled at 25% depletion of available soil moisture (DASM) in 1979 and at 50% DASM in 1980. Plant density of 444,000 plants per ha was optimum in both the years. Interaction of fertilizers and plant density, fertilizers and irrigation and plant density and irrigation increased the pod yield of groundnut, only when the sowings were delayed.     

Structural and Thermal Validations of Y<Subscript>3</Subscript>Ba<Subscript>5</Subscript>Cu<Subscript>8</Subscript>O<Subscript>18</Subscript> Composites Synthesized via Citrate Sol-Gel Spontaneous Combustion Method

The fabrication of single-phase superconductors enabled promising advancements in a wide range of technological applications. Numerous parameters including processing temperature, thermal cycle, chemical composition, doping, and atmosphere will be carefully addressed and optimized. This paper investigates phase stability and compound formation of Y₃Ba₅Cu₈O_y (Y-358) preform powders which were sintered at different temperatures. The precursor powder synthesized via chemical route and employing spontaneous combustion technique, respectively. The presence of Y-358 and YBa₂Cu₃O_7-δ (Y-123) phases in composites sintered at different temperatures with varied phase fractions were further confirmed through Rietveld refinement. The formation of Y-123 phase is dominant in all samples and composite was sintered at 900 °C, which was exhibited higher as compared to Y-358 phase content. The decomposition of different phases present in the composites and reaction temperatures were investigated with simultaneous differential thermal and thermogravimetry analysis.     

Milk trace elements in lactating cows environmentally exposed to higher level of lead and cadmium around different industrial units

The present investigation was carried out to assess the trace mineral profile of milk from lactating cows reared around different industrial units and to examine the effect of blood and milk concentration of lead and cadmium on copper, cobalt, zinc and iron levels in milk. Respective blood and milk samples were collected from a total of 201 apparently healthy lactating cows above 3 years of age including 52 cows reared in areas supposed to be free from pollution. The highest milk lead (0.85 ± 0.11 µg/ml) and cadmium (0.23 ± 0.02 µg/ml) levels were recorded in lactating cows reared around lead–zinc smelter and steel manufacturing plant, respectively. Significantly (P < 0.05) higher concentration of milk copper, cobalt, zinc and iron compared to control animals was recorded in cows around closed lead cum operational zinc smelter. Analysis of correlation between lead and other trace elements in milk from lactating cows with the blood lead level > 0.20 µg/ml (n = 79) revealed a significant negative correlations between milk iron and milk lead (r = − 0.273, P = 0.015). However, such trend was not recorded with blood lead level < 0.20 µg/ml (n = 122). The milk cobalt concentration was significantly correlated (r = 0.365, P < 0.001) with cadmium level in milk and the highest milk cadmium (> 0.10 to 0.39 µg/ml) group had significantly (P < 0.05) increased milk cobalt. It is concluded that increased blood and milk lead or cadmium level as a result of natural exposure of lactating cows to these environmental toxicants significantly influences trace minerals composition of milk and such alterations affect the milk quality and nutritional values.