Deep Learning-aided TR-UWB MIMO System

This paper presents a novel deep learning-aided scheme dubbed PRρ-net for improving the bit error rate (BER) of the Time Reversal (TR) Ultra-Wideband (UWB) Multiple Input Multiple Output (MIMO) system with imperfect Channel State Information (CSI). The designed system employs Frequency Division Duplexing (FDD) with explicit feedback in a scenario where the CSI is subject to estimation and quantization errors. Imperfect CSI causes a drastic increase in BER of the FDD-based TR-UWB MIMO system, and we tackle this problem by proposing a novel neural network-aided design for the conventional precoder at the transmitter and equalizer at the receiver. A closed-form expression for the initial estimation of the channel correlation is derived by utilizing transmitted data in time-varying channel conditions modeled as a Markov process. Subsequently, a neural network-aided design is proposed to improve the initial estimate of channel correlation. An adaptive pilot transmission strategy for a more efficient data transmission is proposed that uses channel correlation information. The theoretical analysis of the model under the Gaussian assumptions is presented, and the results agree with the Monte-Carlo simulations. The simulation results indicate high performance gains when the suggested neural networks are used to combat the effect of channel imperfections

Evaluation of Cold Spray Process for Solid-State Welding

Welding is an important manufacturing process used in various industries, from automotive to aerospace. However, existing welding techniques have certain drawbacks that affect weld integrity and limit their use in joining some temperature-sensitive materials. A significant concern is the heat-affected zone (HAZ), which often becomes softer than its surrounding areas. To address this problem, the expansion of cold spray process—a solid-state layer-by-layer high speed particle deposition process—as an alternative solid-state welding technique is proposed, developed, and evaluated, a process referred to as cold spray welding (CSW). As a starting point, the origin of softening in a Tungsten inert gas (TIG)-welded AA 6061-T651 plates is first comprehensively investigated using experimental, analytical, and thermodynamic modelling approaches; this is further compared with the CSWed samples to assess its (CSW) potential and current limitations for future optimization. The outcome of this study reveals that the softening effect or HAZ in the TIG-welded sample could extend up to ~40 mm from the weld center. The HAZ further partitions into four regions: HAZ1, HAZ2, HAZ3, and HAZ4, based on peak temperature, hardness, and stable precipitate phases in those regions. While the CSWed samples show several benefits: negligible microstructural alterations, inhibition of phase transformations, and suppression of deleterious HAZ, they exhibit lower tensile strength and impact toughness than TIG-welded counterpart due to the presence of ubiquitous microvoids resulting from inadequate metallurgical bonding in CSWed area. These microvoids act as initiation sites for microcracks. To guide future optimization efforts, a failure mechanism in the CSWed parts is established. This research underscores the importance of addressing softening effects in welded materials, while also charting a new path to establishing a new unexplored solid-state welding technique that has the potential to minimize the drawbacks in conventional welding methods. By understanding and overcoming the poor particle-particle/particle-substrate metallurgical bonding, CSW is poised to be an alternative greener solid-state welding technique for applications in various industries

Efficient PPA-SiO2-catalyzed synthesis of β-enaminones under solvent-free conditions

An efficient method has been developed for the synthesis of β-enaminones under solvent-free reaction conditions using PPA-SiO2 as catalyst. The reaction yields were good to excellent (up to 90%). This methodology affords high selectivity and good tolerance of a variety of different functional groups present on both aromatic and aliphatic amines. In addition, the methodology is environmentally benign and cost-effective due to absence of solvent and easy work-up

Comparison Of Prophylactic Injection Of Corticosteroid With Placebo, In Management Of Wrist Pain On Ulnar Aspect In Patients Of Fractures Of Distal Radius

INTRODUCTION: Distal radius fractures are one of the commonest fractures experienced by the Orthopaedic surgeons. Pain on the ulnar aspect of the wrist is the most usual complication of such fractures.  Corticosteroid injection is a simple and effective method for elevating pain of such nature.  OBJECTIVE: To compare the mean pain score with prophylactic corticosteroid injection versus placebo in management of wrist pain on ulnar aspect in patients presenting with fracture of distal radius. MATERIAL AND METHODS: Study Design: Randomized controlled trial Setting: Orthopedic Surgery Department, Benazir Bhutto Hospital, Rawalpindi Duration: Six months (March 5, 2018 to Sept 5, 2018) Data Collection Procedure: 80 patients were included by using non-probability consecutive sampling after fulfilling the selection criteria. Demographic profile (patient name, age, gender, anatomical side and contact details) was obtained. Patients were splitted in two random groups by simple lottery method. Patients of group A were given one shot of 80mg corticosteroid in the area of ulnar styloid process near TFCC and group B patients were given a shot of distilled water (2 cc). Both group of patients were followed in OPD for 3 months in their postoperative visits. Visual analogue scale (VAS) score was recorded. Data was analyzed using SPSS version 21. Results: The mean age of the patients was 41.05 ± 11.05 years and age range of 40 years. The mean age in the corticosteroid and placebo groups was 39.68±10.67 years and 42.42 ± 11.39 years respectively. There were 42 (52.50%) male and 38 (47.50%) female patients with a higher male ratio i.e., 1.10:1. In corticosteroid and placebo groups there were 21 (52.50%) male and 19 (47.50%) female cases. The mean pain at baseline was 7.72 ± 1.66 while in the corticosteroid and placebo group, the mean pain was 7.60 ± 1.67 and 7.85 ± 1.65 respectively with statistically equal mean pain p-value = 0.504. After 3 months of treatment, mean pain in the corticosteroid group was 1.30 ± 0.66 and was 2.60 ± 1.58 in the placebo group, p-value < 0.001. Conclusion: Our findings suggested that prophylactic corticosteroid injection is more effective in reducing pain in patients with distal radial fracture than placebo. By using prophylactic corticosteroid injections in the future, we can reduce pain to achieve more satisfaction of patients.

Frequency limited impulse response gramians based model reduction

In order to simplify the analysis of complex electronic systems, they needsto be modeled accurately. Model reduction is further required to streamline the procedural and computational complexities. Further the instability caused by the model reduction techniques worstly effects the accuracy of a system. Therefore, we have proposed some improvements in the frequency limited impulse response Gramians based model order reduction techniques for discrete time systems. The propsed techniques assures the stability of the model after it get reduced. The proposed techniques provided better results than the stability preserving techniques

Machine learning and blockchain technologies for cybersecurity in connected vehicles

Future connected and autonomous vehicles (CAVs) must be secured againstcyberattacks for their everyday functions on the road so that safety of passengersand vehicles can be ensured. This article presents a holistic review of cybersecurityattacks on sensors and threats regardingmulti-modal sensor fusion. A compre-hensive review of cyberattacks on intra-vehicle and inter-vehicle communicationsis presented afterward. Besides the analysis of conventional cybersecurity threatsand countermeasures for CAV systems,a detailed review of modern machinelearning, federated learning, and blockchain approach is also conducted to safe-guard CAVs. Machine learning and data mining-aided intrusion detection systemsand other countermeasures dealing with these challenges are elaborated at theend of the related section. In the last section, research challenges and future direc-tions are identified

Performance Assessment and Working Fluid Selection for Novel Integrated Vapor Compression Cycle and Organic Rankine Cycle for Ultra Low Grade Waste Heat Recovery

This paper presents the performance assessment and working fluid selection for a novel integrated vapor compression cycle-organic Rankine cycle system (i-VCC-ORC), which recovers ultra-low-temperature waste heat rejected (50 °C) by the condenser of a vapor compression cycle (VCC). The analyses are carried out for a vapor compression cycle of a refrigeration capacity (heat input) of 35kW along with the component sizing of the organic Rankine cycle (ORC). The effects of the operational parameters on integrated system performance were investigated. The integrated system performance is estimated in terms of net COP, cycle thermal efficiency and exergy efficiency by completely utilizing and recovering the heat rejected by the condenser of the VCC system. R600a-R141b with COPnet (3.54) and ORC thermal efficiency (3.05%) is found to be the most suitable VCC-ORC working fluid pair. The integration of the vapor compression refrigeration cycle with the organic Rankine cycle increases the COP of the system by 12.5% as compared to the standalone COP of the vapor compression system. Moreover, the sensitivity analysis results show that there exists an optimum operating condition that maximizes the thermal performance of the integrated system

Genetic diversity and multiplicity of infection in Fasciola gigantica isolates of Pakistani livestock

Fasciola spp. are responsible for over 3 billion US dollars of production loss annually in livestock and cause widespread zoonotic disease. Nevertheless, understating of the emergence and spread of the trematode species is poor. The multiplicity of F. gigantica infection and its spread is potentially influenced by multiple factors, including the abundance of suitable intermediate hosts, climatic conditions favouring the completion of the parasite's lifecycle, and translocation of infected animals, or free-living parasite stages between regions. Here we describe the development of a ‘tremabiome’ metabarcoding sequencing method to explore the numbers of F. gigantica genotypes per infection and patterns of parasite spread, based on genetic characteristics of the mitochondrial NADH dehydrogenase 1 (mt-ND-1) locus. We collected F. gigantica from three abattoirs in the Punjab and Balochistan provinces of Pakistan, and our results show a high level of genetic diversity in 20 F. gigantica populations derived from small and large ruminants consigned to slaughter in both provinces. This implies that F. gigantica can reproduce in its definitive hosts through meiosis involving cross- and self-breeding, as described in the closely related species, Fasciola hepatica. The genetic diversity between the 20 populations derived from different locations also illustrates the impact of animal movements on gene flow. Our results demonstrate the predominance of single haplotypes, consistent with a single introduction of F. gigantica infection in 85% of the hosts from which the parasite populations were derived. This is consistent with clonal reproduction in the intermediate snail hosts.[Display omitted]•To confirm the species identity of recovered Fasciola spp.•To identify the presence of single or multiple genotypes per infection (multiplicity of infection)•Demonstrate the spread of F. gigantica mt-ND-1 haplotype

Point prevalence survey of antimicrobial use during the COVID-19 pandemic among different hospitals in Pakistan : findings and implications

The COVID-19 pandemic has significantly influenced antimicrobial use in hospitals raising concerns regarding increased antimicrobial resistance (AMR) through their overuse. The objective of this study was to assess patterns of antimicrobial prescribing during the current COVID-19 pandemic among hospitals in Pakistan, including the prevalence of COVID-19. A point prevalence survey (PPS) was performed among 11 different hospitals from November 2020 to January 2021. The study included all hospitalized patients receiving an antibiotic on the day of the PPS. The Global-PPS web-based application was used for data entry and analysis. Out of 1024 hospitalized patients, 662 (64.64%) received antimicrobials. The top three most common indications for antimicrobial use were pneumonia (13.3%), central nervous system infections (10.4%) and gastrointestinal indications (10.4%). Ceftriaxone (26.6%), metronidazole (9.7%) and vancomycin (7.9%) were the top three most commonly prescribed antimicrobials among surveyed patients, with the majority of antibiotics administered empirically (97.9%). Most antimicrobials for surgical prophylaxis were given for more than one day, which is a concern. Overall, a high percentage of antimicrobial use, including broad-spectrums, was seen among the different hospitals in Pakistan during the current COVID-19 pandemic. Multifaceted interventions are needed to enhance rational antimicrobial prescribing including limiting their prescribing post-operatively for surgical prophylaxis