Combating unemployment through skill development

In this paper, we propose and analyze a nonlinear mathematical model to study the effect of skill development on unemployment. We assume that government promulgates different levels of skill development programs for unemployed persons through which two different categories of skilled persons, namely, the low-skilled and the highly-skilled persons, are coming out and the highly-skilled persons are able to create vacancies. The model is studied using stability theory of nonlinear differential equations. We find analytically that there exists a unique positive equilibrium point of the proposed model system under some conditions. Also, the resulting equilibrium is locally as well as globally stable under certain conditions. The effective use of implemented policies to control unemployment by providing skills to unemployed persons and the new vacancies created by highly-skilled persons are identified by using optimal control analysis. Finally, numerical simulation is carried out to support analytical findings

Effect of Ceramic/Graphite Reinforcement on Dry Sliding Wear Behavior of Copper Metal Matrix Hybrid Composites

In the present investigation, effect of ceramic/graphite addition on the dry sliding wear behavior of copper-based hybrid composites have been assessed at three different normal loads of 9.81, 19.62 and 29.43 N. Wear test is performed by using pin-on-disc test rig at sliding speeds of 1.30 and 1.84 m/s under ambient conditions. The copper-based hybrid composites are successfully synthesized by using stir casting route. The samples are characterized by various techniques such as X-rays diffraction (XRD), high resolution-scanning electron microscopy (HR-SEM), scanning electron microscope (SEM) equipped with energy dispersive analysis of X-ray spectroscopy (EDAX). Microstructural investigations reveal the presence of the WC, TiC and graphite particles in the hybrid composites. It is observed that graphite reinforced hybrid composite shows better wear resistance than hybrid composite without graphite addition. In all the cases cast copper specimen shows highest wear rate. The observed friction and wear behavior have been explained on the basis of the presence tribofilm on the worn surface. Microstructural characterization of the worn surface and wear debris show that the mechanism of wear is primarily adhesive and oxidative in case of cast copper, where as it is a mix of adhesive and abrasive wear in case of hybrid composites. Wear debris analysis also helps to understand the wear mechanism involved during dry sliding

Development and Evaluation of Active Case Detection Methods to Support Visceral Leishmaniasis Elimination in India.

As India moves toward the elimination of visceral leishmaniasis (VL) as a public health problem, comprehensive timely case detection has become increasingly important, in order to reduce the period of infectivity and control outbreaks. During the 2000s, localized research studies suggested that a large percentage of VL cases were never reported in government data. However, assessments conducted from 2013 to 2015 indicated that 85% or more of confirmed cases were eventually captured and reported in surveillance data, albeit with significant delays before diagnosis. Based on methods developed during these assessments, the CARE India team evolved new strategies for active case detection (ACD), applicable at large scale while being sufficiently effective in reducing time to diagnosis. Active case searches are triggered by the report of a confirmed VL case, and comprise two major search mechanisms: 1) case identification based on the index case's knowledge of other known VL cases and searches in nearby houses (snowballing); and 2) sustained contact over time with a range of private providers, both formal and informal. Simultaneously, house-to-house searches were conducted in 142 villages of 47 blocks during this period. We analyzed data from 5030 VL patients reported in Bihar from January 2018 through July 2019. Of these 3033 were detected passively and 1997 via ACD (15 (0.8%) via house-to-house and 1982 (99.2%) by light touch ACD methods). We constructed multinomial logistic regression models comparing time intervals to diagnosis (30-59, 60-89 and ≥90 days with =90 days compared to the referent of <30 days for ACD vs PCD were 0.88, 0.56 and 0.42 respectively. These ACD strategies not only reduce time to diagnosis, and thus risk of transmission, but also ensure that there is a double check on the proportion of cases actually getting captured. Such a process can supplement passive case detection efforts that must go on, possibly perpetually, even after elimination as a public health problem is achieved

Regulation of Plasmodium falciparum Glideosome Associated Protein 45 (PfGAP45) Phosphorylation

The actomyosin motor complex of the glideosome provides the force needed by apicomplexan parasites such as Toxoplasma gondii (Tg) and Plasmodium falciparum (Pf) to invade their host cells and for gliding motility of their motile forms. Glideosome Associated Protein 45 (PfGAP45) is an essential component of the glideosome complex as it facilitates anchoring and effective functioning of the motor. Dissection of events that regulate PfGAP45 may provide insights into how the motor and the glideosome operate. We found that PfGAP45 is phosphorylated in response to Phospholipase C (PLC) and calcium signaling. It is phosphorylated by P. falciparum kinases Protein Kinase B (PfPKB) and Calcium Dependent Protein Kinase 1 (PfCDPK1), which are calcium dependent enzymes, at S89, S103 and S149. The Phospholipase C pathway influenced the phosphorylation of S103 and S149. The phosphorylation of PfGAP45 at these sites is differentially regulated during parasite development. The localization of PfGAP45 and its association may be independent of the phosphorylation of these sites. PfGAP45 regulation in response to calcium fits in well with the previously described role of calcium in host cell invasion by malaria parasite

Adsorption-Desorption Surface Bindings, Kinetics, and Mass Transfer Behavior of Thermally and Chemically Treated Great Millet Husk towards Cr(VI) Removal from Synthetic Wastewater

This study reports the efficacy of adsorbents synthesized by thermal (TT-GMH) and chemical (CT-GMH) modification of great millet husk (GMH) for the treatment of synthetic wastewater containing Cr(VI). The chemical modification of raw GMH was done by concentrated H2SO4 to increase the porosity and heterogeneity on the surface. The comparative investigations of physicochemical properties of synthesized adsorbents were examined by point of zero charge (pHpzc), BET surface area, SEM-EDX, FTIR, and XRD analyses. The results revealed that CT-GMH had around three times higher surface area and more porous structure as compared to TT-GMH. The adsorption experiments were executed in batch mode to examine the impact of parameters governing the adsorption process. For Cr(VI) solution of 25 mg/L, adsorbent dose of 4 g/L, temperature of 25°C, and shaking speed of 150 RPM, the maximum removal for TT-GMH was attained at pH 1 and contact time 150 min, while for CT-GMH, maximum removal was attained at pH 2 and contact time 120 min. The experimental results fitted to the rate kinetic equations showed that for both TT-GMH and CT-GMH, adsorbents followed the quasi-second-order kinetic model during the adsorption process. Further, results revealed that the adsorption process was endothermic and Sips isotherm model was followed for both TT-GMH and CT-GMH. Based on the Sips isotherm, maximum uptake capacity for TT-GMH and CT-GMH was noted to be 16 and 22.21 mg/g, respectively. Among the tested mass transfer models, liquid film diffusion model was followed during the adsorption process of both the adsorbents. The desorption study revealed that TT-GMH and CT-GMH give 69.45% and 74.48% removal, respectively, up to six cycles

Towards post-disaster damage assessment using deep transfer learning and GAN-based data augmentation

Cyber-physical disaster systems (CPDS) are a new cyber-physical application that collects physical realm measurements from IoT devices and sends them to the edge for damage severity analysis of impacted sites in the aftermath of a large-scale disaster. However, the lack of effective machine learning paradigms and the data and device heterogeneity of edge devices pose significant challenges in disaster damage assessment (DDA). To address these issues, we propose a generative adversarial network (GAN) and a lightweight, deep transfer learning-enabled, fine-tuned machine learning pipeline to reduce overall sensing error and improve the model's performance. In this paper, we applied several combinations of GANs (i.e., DCGAN, DiscoGAN, ProGAN, and Cycle-GAN) to generate fake images of the disaster. After that, three pre-trained models: VGG19, ResNet18, and DenseNet121, with deep transfer learning, are applied to classify the images of the disaster. We observed that the ResNet18 is the most pertinent model to achieve a test accuracy of 88.81%. With the experiments on real-world DDA applications, we have visualized the damage severity of disaster-impacted sites using different types of Class Activation Mapping (CAM) techniques, namely Grad-CAM++, Guided Grad-Cam, &amp; Score-CAM. Finally, using k-means clustering, we have obtained the scatter plots to measure the damage severity into no damage, mild damage, and severe damage categories in the generated heat maps

Implementation of infection prevention and control practices in an upcoming COVID-19 hospital in India: An opportunity not missed.

Infection prevention and control (IPC) program is obligatory for delivering quality services in any healthcare setup. Lack of administrative support and resource-constraints (under-staffing, inadequate funds) were primary barriers to successful implementation of IPC practices in majority of the hospitals in the developing countries. The Coronavirus Disease 2019 (COVID-19) brought a unique opportunity to improve the IPC program in these hospitals. A PDSA (Plan-Do-Study- Act) model was adopted for this study in a tertiary care hospital which was converted into a dedicated COVID-19 treatment facility in Varanasi, India. The initial focus was to identify the deficiencies in existing IPC practices and perceive the opportunities for improvement. Repeated IPC training (induction and reinforce) was conducted for the healthcare personnel (HCP) and practices were monitored by direct observation and closed-circuit television. Cleaning audits were performed by visual inspection, review of the checklists and qualitative assessment of the viewpoints of the HCP was carried out by the feedbacks received at the end of the training sessions. A total of 2552 HCP and 548 medical students were trained in IPC through multiple offline/onsite sessions over a period of 15 months during the ongoing pandemic. Although the overall compliance to surface disinfection and cleaning increased from 50% to >80% with repeated training, compliance decreased whenever newly recruited HCP were posted. Fear psychosis in the pandemic was the greatest facilitator for adopting the IPC practices. Continuous wearing of personal protective equipment for long duration, dissatisfaction with the duty rosters as well as continuous posting in high-risk areas were the major obstacles to the implementation of IPC norms. Recognising the role of an infection control team, repeated training, monitoring and improvisation of the existing resources are keys for successful implementation of IPC practices in hospitals during the COVID-19 pandemic

Ligand-free Pd-catalyzed C-N cross-coupling/cyclization strategy: an unprecedented access to 1-thienyl pyrroloquinoxalines for the new approach towards apoptosis

The link between PDE4 and apoptosis prompted us to design and synthesize for the first time a series of novel 1-thienyl pyrroloquinoxalines as potential PDE4 inhibitors/apoptotic agents. A ligand-free Pd-catalyzed C–N cross-coupling/cyclization strategy has been developed for the rapid and milder access to this class of compounds some of which showed interesting pharmacological properties when tested in vitro and in zebrafish embryos

Protein kinase TgCDPK7 regulates vesicular trafficking and phospholipid synthesis in Toxoplasma gondii.

Apicomplexan parasites are causative agents of major human diseases. Calcium Dependent Protein Kinases (CDPKs) are crucial components for the intracellular development of apicomplexan parasites and are thus considered attractive drug targets. CDPK7 is an atypical member of this family, which initial characterization suggested to be critical for intracellular development of both Apicomplexa Plasmodium falciparum and Toxoplasma gondii. However, the mechanisms via which it regulates parasite replication have remained unknown. We performed quantitative phosphoproteomics of T. gondii lacking TgCDPK7 to identify its parasitic targets. Our analysis lead to the identification of several putative TgCDPK7 substrates implicated in critical processes like phospholipid (PL) synthesis and vesicular trafficking. Strikingly, phosphorylation of TgRab11a via TgCDPK7 was critical for parasite intracellular development and protein trafficking. Lipidomic analysis combined with biochemical and cellular studies confirmed that TgCDPK7 regulates phosphatidylethanolamine (PE) levels in T. gondii. These studies provide novel insights into the regulation of these processes that are critical for parasite development by TgCDPK7