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Applications hosted in commercial clouds are typically multi-tier and comprise multiple tightly coupled virtual machines (VMs). Service providers (SPs) cater to the users using VM instances with different configurations and pricing depending on the location of the data center (DC) hosting the VMs. However, selecting VMs to host multi-tier applications is challenging due to the trade-off between cost and quality of service (QoS) depending on the placement of VMs. This paper proposes a multi-cloud broker model called CoMCLOUD to select a sub-optimal VM coalition for multi-tier applications from an SP with minimum coalition pricing and maximum QoS. To strike a trade-off between the cost and QoS, we use an ant-colony-based optimization technique. The overall service selection game is modeled as a first-price sealed-bid auction aimed at maximizing the overall revenue of SPs. Further, as the hosted VMs often face demand spikes, we present a parallel migration strategy to migrate VMs with minimum disruption time. Detailed experiments show that our approach can improve the federation profit up to 23% at the expense of increased latency of approximately 15%, compared to the baselines.

The concept of sustainable livelihood security has wider generic meaning pertaining to sustainable development to ensure ecologically secure, economically efficient, socially equitable and sufficiency in infrastructure in the society. Dairying provides sufficient income to the farming community of West Bengal. Therefore, sustainability of dairy-based livelihood in the districts of West Bengal was assessed to find out necessary interventions to be required to ensure sustainable livelihood security of dairy farmers. An exclusively district level Dairy-based Sustainable Livelihood Security Index was developed underline the principle of Human Development Index of United Nations Development Programme by using 17 indicators divided into four sub-indices i.e. Ecological Security index, Economic Efficiency Index, Infrastructural Sufficiency Index and Social Equity Index. The overall mean value of Dairy-based Sustainable Livelihood Security Index was found to be 0.38 with a range from 0.12 (Purulia district) to 0.59 (Darjeeling district), indicated the sustainability status was low. In case of sub indices, Infrastructural Sufficiency Index (0.49) and Ecological Security Index (0.45) were stronger indices than other two indices, Economic Efficiency Index (0.32) and Social Equity Index (0.29) which signified the very lower level sustainability. Districts were categorized for better interpretation into four based on overall Sustainable Livelihood Security Index score as very low (less than 0.3), low (0.3–0.54), medium (0.55–0.70) and high (greater than 0.70). Districts namely Maldah, Uttar Dinajpur, Purulia were having very lower level sustainability in dairy-based livelihood. But, it was moderately sustainable in the districts of Darjeeling, Nadia and Hooghly. Hence, Dairy-based Sustainable Livelihood Security Index (SLSI) is not only highlighting the state of sustainability of dairy-based livelihood but also emphasized the area where necessary policy matters to be intervened for improvement of livelihood of dairy farmers.

Strain engineering as one of the most powerful techniques for tuning optical and electronic properties of Ill-nitrides requires reliable methods for strain investigation. In this work, we reveal, that the linear model based on the experimental data limited to within a small range of biaxial strains (0.2%), which is widely used for the non-destructive Raman study of strain with nanometer-scale spatial resolution is not valid for the binary wurtzite-structure group-III nitrides GaN and AlN. Importantly, we found that the discrepancy between the experimental values of strain and those calculated via Raman spectroscopy increases as the strain in both GaN and AlN increases. Herein, a new model has been developed to describe the strain-induced Raman frequency shift in GaN and AlN for a wide range of biaxial strains (up to 2.5%). Finally, we proposed a new approach to correlate the Raman frequency shift and strain, which is based on the lattice coherency in the epitaxial layers of superlattice structures and can be used for a wide range of materials.Supplementary material (Table S1: Values of bulk phonon deformation potentials and elastic constants for GaN and AlN from each reference used in Table 1, Fig. S1: Lattice parameters of SL layers using Eq. (8), and Fig. S2: Raman mapping using Eq. (7)) is available in the online version of this article at 10.1007/s12274-021-3855-4.

Images with visual and scene text content are ubiquitous in everyday life. However, current image interpretation systems are mostly limited to using only the visual features, neglecting to leverage the scene text content. In this paper, we propose to jointly use scene text and visual channels for robust semantic interpretation of images. We do not only extract and encode visual and scene text cues, but also model their interplay to generate a contextual joint embedding with richer semantics. The contextual embedding thus generated is applied to retrieval and classification tasks on multimedia images, with scene text content, to demonstrate its effectiveness. In the retrieval framework, we augment our learned text-visual semantic representation with scene text cues, to mitigate vocabulary misses that may have occurred during the semantic embedding. To deal with irrelevant or erroneous recognition of scene text, we also apply query-based attention to our text channel. We show how the multi-channel approach, involving visual semantics and scene text, improves upon state of the art., Comment: The paper is under consideration at Pattern Recognition Letters

Purpose:The comparative cardiovascular risk profiles of available hormone therapies for the treatment of prostate cancer is not known.Materials and Methods:We queried the U.S. Food and Drug Adminis...

India faces the burden of under-nutrition, especially among children under five years of age. The gap in nutritional needs and intake, point to the inadequacies in the food and nutrition security of India. This study examines data at the district level to identify vulnerable populations across the geographical expanse of the country. In order to identify districts appropriate for improving the food and nutrition security, a statistical approach was developed to prioritize areas for public health interventions. We used ranking based on two indices: Vulnerability Index of agriculture to climate change (VI), as a relative measure of risk to agriculture due to climate change severity, and a Child Health Index (CHI), based on key health parameters such as stunting, wasting, underweight, anaemia, and diarrhoea in the most vulnerable age group (

Bayesian network has gained increasing popularity among the data scientists and research communities, because of its inherent capability of capturing probabilistic information and reasoning with uncertain knowledge. However, the discrete Bayesian learning, with continuous and categorical variables, often shows poor performance because of parameter value uncertainty , arising due to strict boundary value of the discretized data and lack of knowledge on domain semantics . In this work, we propose semFBnet , a variant of Bayesian network with incorporated fuzziness and semantic knowledge , to reduce the uncertainty during parameter learning. The performance of semFBnet has been validated with prediction of daily meteorological conditions in two states of India, namely West Bengal and Delhi, for the years 2015 and 2016, respectively. The study of Dawid-Sebastiani score and the confidence interval analysis , in comparison with the state-of-the-art and benchmark prediction techniques, demonstrate the effectiveness of the proposed semFBnet in reducing parameter value uncertainty.

In online social networks (OSNs), detection of malicious social bots is an important research challenge to provide legitimacy of user profiles and trustworthy service ratings. Further, spam-influential users must be minimal to control the fake information-spread in OSNs. Learning from example patterns using supervised learning may not provide accurate results in cases where existing data items are biased and bot behavior dynamically changes over a period of time. Moreover, deep reinforcement learning provides improved learning by repeated interactions with the environment. However, a typical deep reinforcement leaning algorithm converges slower to find an optimal sequence of actions to reach out a goal state. In this article, we design a particle swarm optimization (PSO) based deep Q-learning algorithm for detecting social spam bots by integrating PSO with Q -value function. In addition, spam-influential users are identified using the proposed spam influence minimization model and it helps in restricting the flow of illegitimate tweets in Twitter network. Further, an influential community detection algorithm has been proposed to reduce the spreading of spam content through influential communities in Twitter network. Experimental results illustrate the efficacy of our proposed algorithms by considering two Twitter datasets and performance metrics such as precision, recall, and modularity.

Left atrial (LA) strain mechanics refer to the measurement of LA myocardial deformation expressed as a percentage, and have been gathering interest over the last decade with expanding research supporting their utility in multiple cardiovascular disorders. Measured through advanced dynamic imaging techniques which include tissue Doppler imaging (TDI) and two-dimensional (2D) speckle tracking echocardiography (STE), LA strain mechanics are affected by left ventricular diastolic dysfunction prior to the onset of functional and structural changes in the left ventricle (LV). There is a need for practising cardiologists to become more familiar with the clinical utility of LA strain mechanics. In this article, we begin by reviewing the physiologic function of the LA, using this as a basis for understanding LA strain mechanics. The focus of this review article is to provide a contemporary update on the utility of LA strain mechanics in a range of cardiovascular disorders, including atrial fibrillation (AF), hypertrophic cardiomyopathy (HCM), valvular pathologies, coronary artery disease (CAD) as well as systemic diseases, such as hypertension (HTN), obesity and diabetes mellitus (DM). This article also highlights the current limitations in more widespread clinical applications of LA strain mechanics, as well as outlining the future perspectives on the clinical applications of LA strain mechanics.

Soil organic carbon (SOC) is highly sensitive to land use change and helps in maintaining soil quality. Changes in soil fertility status, SOC dynamics, and carbon indices were studied in a four-yea...

Recurrent pericarditis affects 15-30% of patients after acute pericarditis. A large number of the patients with recurrent pericarditis can become corticosteroid dependent, leading to disease chronicity and drug dependence, with additional morbidity from long-term steroid use. Recent randomized trials indicate the efficacy of the interleukin-1 inhibitors anakinra and rilonacept in recurrent pericarditis, including colchicine-resistant and corticosteroid-dependent cases. In particular, rilonacept was assessed in the RHAPSODY clinical trial and found to be a potential treatment option that would decrease recurrent episodes, enabling patients to be weaned off steroids. Additionally, new data indicate that rilonacept should be considered as an option for patients with recurrent pericarditis, as add-on therapy to colchicine and nonsteroidal anti-inflammatory drugs, in place of steroids. We review the current management options for recurrent pericarditis as well as rilonacept as a prospective new addition to our armamentarium.

The present study is a “first-of-its-kind” work on an integrated process consisting of a hydrodynamic cavitation (HC)-assisted advanced oxidation process and vacuum membrane distillation (VMD) for ...

Optical computing is a significant improvement over conventional electronic circuits due to much higher computing speeds and better data handling capabilities. A multivalued logic (MVL) system incorporates more than two logical states to enable higher data density, reduce or eliminate ripple-through carries in arithmetic operations. Optical multivalued logic may be one of the best solutions in modern computational system to resolve the recent problems associated with the existing one. The singed-bit states in a multivalued logic system also permits simplified carry or borrow free operations. In this paper an optical multivalued logic system with signed-bit is introduced, called Modified Septenary System (MSS). The seven logical states of the system are introduced and different arithmetic and logical operations are also implemented accordingly. The different logic gates of this system are designed and realized with SLM and savart plate using Optical Tree Architectures (OTA).

Introduction:On September 20, 2017, Hurricane Maria, a Category 4 hurricane, swept across Puerto Rico (PR), wreaking devastation to PR’s power, water, and health care infrastructure. To address the imminent humanitarian crisis, the US government mobilized Federal Medical Shelters (FMS) to serve the needs of hurricane victims. This study’s objective was to provide a description of the patients seeking emergency care at FMS and the changes in their needs over time.Methods:This retrospective, cross-sectional study included all patients presenting to the FMS Manatí from October 6, two weeks after Hurricane Maria’s landfall, to November 2, 2017. Categories were created to catalogue the nature of new acute medical issues by patients presenting to the Shelter. Descriptive, graphical analyses were performed to assess changes to presenting complaints over time, and by age groups defined as infant (age ≤1 years), child (1 year < age ≤10 years), adolescent (10 years < age ≤ 25 years), and adult (age > 25 years).Results:Over the 30-day period, 5,268 patients were seen in the FMS seeking medical care (average 188.1 patients per day), spending less than five hours in the facility. The distribution of patients’ age was bimodal: the first peak at one year and the second at age 50. The most common patient complaint was infection (38.8%), then musculoskeletal (MSK) complaints (11.8%) and management of chronic medical conditions (11.8%). The proportion of patients presenting with chronic disease complaints declined over the course of the period of observation (21.4% on Day 4 to 8.0% on Day 30) while the proportion of patients presenting with infection increased (31.0% on Day 4 to 48.6% on Day 30). Infection complaints were highest in all age groups, but most in infxants (80.2%), while MSK and chronic disease complaints were highest in adults (14.9% and 14.9%, respectively).Conclusion:Infection treatment and chronic disease management were important medical needs facing patients seeking care at FMS Manatí after Hurricane Maria. These findings suggest that basic needs related to sanitation and shelter remained important weeks after the hurricane, and a focus on access to medications, infection control, and injury prevention/management after a disaster needs to be prioritized during disaster response.

Multiple myeloma (MM) is the third most common haematological malignancy, with increasing prevalence over recent years. Advances in therapy have improved survival, changing the clinical course of MM into a chronic condition and meaning that management of comorbidities is fundamental to improve clinical outcomes. Cardiovascular (CV) events affect up to 7.5% of individuals with MM, due to a combination of patient, disease and treatment-related factors and adversely impact survival. MM typically affects older people, many with pre-existing CV risk factors or established CV disease, and the disease itself can cause renal impairment, anaemia and hyperviscosity, which exacerabate these further. Up to 15% of patients with MM develop systemic amyloidosis, with prognosis determined by the extent of cardiac involvement. Management of MM generally involves administration of multiple treatment lines over several years as disease progresses, with many drug classes associated with adverse CV effects including high rates of venous and arterial thrombosis alongside heart failure. Recommendations for holistic management of patients with MM now include routine baseline risk stratification including ECG and echocardiography and administration of thromboprophylaxis drugs for patients treated with immunomodulatory drugs. Close surveillance of high-risk patients with collaboration between haematology and cardiology is required, with prompt investigation in the event of CV symptoms, in order to identify and treat complications early. Decisions regarding discontinuation of cardiotoxic therapies should be made in a multidisciplinary setting, taking into account the severity of the complication, prognosis, expected benefits and the availability of effective alternatives.

Background Viruses cause many life threatening human diseases. Recently, COVID-19 pandemic has challenged the health care systems worldwide. As a disease preventive approach and to bring relief to the severity of the symptoms, a infusion termed as Bhabha Anti-Viral Infusion-23 (‘BhAVI-23’) was conceptualized and formulated which comprised of 23 selected spices and herbals. Objective The present study was conducted to assess the in vitro antiviral potential of the formulation, BhaAVI-23. Material and methods The in-vitro anti-viral potential of BhAVI-23 was assessed through inhibition of HIV1 reverse transcriptase (RT) as well as through a novel P1 (virulent) bacteriphage based screening assay system. Anti-diabetic potential was assessed by non-enzymatic glycosylation of haemoglobin and the bioactive volatile components were detected through headspace gas chromatography followed by molecular docking analysis. Results The infusion displayed prominent anti-viral activity as evident from significant (57%) inhibition of the HIV1-RT as well as through reduction in the infectivity of P1 (virulent) bacteriophage. The infusion also exerted profound protection (∼64%) to non-enzymatic glycosylation of haemoglobin. Headspace gas chromatography and mass spectrometric analysis confirmed the presence of at least 47 major compounds. Docking analysis indicated possible interaction of α-pinene and eugenol with SARS-CoV spike protein. Conclusion This ‘BhAVI-23’ infusion displayed prominent in-vitro anti-viral and anti-diabetic potential in different model systems. These attributes have relevance as diabetic patients are more prone to COVID-19 morbidity. ‘BhAVI-23’ opens the avenue for its potential inclusion as a supportive health care system upon due regulatory approval during the current pandemic.

Amputees are prone to experiencing discomfort when wearing their prosthetic devices. As the amputee population grows this becomes a more prevalent and pressing concern. There is a need for new prosthetic technologies to construct more comfortable and well-fitted liners and sockets. One of the well-recognized impediments to the development of new prosthetic technology is the lack of practical inner socket sensors to monitor the inner socket environment (ISE), or the region between the residual limb and the socket. Here we present a capacitive pressure sensor fabricated through a simple, and scalable sewing process using commercially available conductive yarns and textile materials. This fully-textile sensor provides a soft, flexible, and comfortable sensing system for monitoring the ISE. We provide details of our low-power sensor system capable of high-speed data collection from up to four sensor arrays. Additionally, we demonstrate two custom set-ups to test and validate the textile-based sensors in a simulated prosthetic environment. Finally, we utilize the textile-based sensors to study the ISE of a bilateral transtibial amputee. Results indicate that the textile-based sensors provide a promising potential for seamlessly monitoring the ISE.

Background: Stylomastoid foramen is the terminal part of facial canal and is the exit gateway for facial nerve from skull base. We hypothesized that anatomical variations of this foramen could be a risk factor for the injury of facial nerve resulting in unilateral facial nerve paralysis or Bell’s palsy. Hence the present study was conducted to study the variations in size and shape of stylomastoid foramen in dry adult human skulls. Materials and methods: The study was conducted on 37 dry adult human skulls of unknown age and sex. High resolution images of the skulls under study were processed by ImageJ software and observations were undertaken. Results: Total eight variations of stylomastoid foramen were observed in terms of shape. The common variants were round, oval and square (present in 83.79% skulls on right side and 81.07% skulls on left side), whereas the rare variants were triangular, rectangular, serrated, bean-shaped and irregular. It was noted that stylomastoid foramen were associated with extensions (45.95% skulls) and also adjacent foramen (18.92% skulls). Exclusively unilateral observations included bifurcation of foramen (16.22% skulls), foramen situated deep inside skull groove (5.41% skulls) and foramen interrupted by bony spur (2.7% skulls). No significant differences were observed between the mean diameters (antero-posterior and transverse) of the stylomastoid foramen. Conclusions: The unilateral variations along with rare variations in terms of shape such as serrated, bean-shaped and irregular foramen (which were also unilateral findings) could be potential risk factors towards injury of facial nerve at the point of exit from skull base leading to Bell’s palsy.

The subspecialty of cardio-oncology aims to reduce cardiovascular morbidity and mortality in patients with cancer or following cancer treatment. Cancer therapy can lead to a variety of cardiovascular complications, including left ventricular systolic dysfunction, pericardial disease, and valvular heart disease. Echocardiography is a key diagnostic imaging tool in the diagnosis and surveillance for many of these complications. The baseline assessment and subsequent surveillance of patients undergoing treatment with anthracyclines and/or human epidermal growth factor (EGF) receptor (HER) 2-positive targeted treatment (e.g. trastuzumab and pertuzumab) form a significant proportion of cardio-oncology patients undergoing echocardiography. This guideline from the British Society of Echocardiography and British Cardio-Oncology Society outlines a protocol for baseline and surveillance echocardiography of patients undergoing treatment with anthracyclines and/or trastuzumab. The methodology for acquisition of images and the advantages and disadvantages of techniques are discussed. Echocardiographic definitions for considering cancer therapeutics-related cardiac dysfunction are also presented.

Inducement of high charge carrier density in organic field-effect transistors (OFETs) is a subject of immense interest due to its fundamental and applied impact on device operation. Here, the high ...

Background Patients with pre-existing vascular disease are known to have worse outcomes after acute myocardial infarction (AMI). However, there is limited data for outcomes stratified by type and number of vascular territories involved. Methods Using the Nationwide Inpatient Sample (2015–2017), we examined outcomes of AMI in patients with pre-existent vascular disease stratified by number as well as types of diseased beds including all five major vascular sites: cardiac, cerebrovascular, renal, aortic and peripheral vascular disease (PVD). Multivariable logistic regression was used to determine the adjusted odds ratios (aOR) of adverse outcomes and invasive procedure utilization. Results Out of 2,184,614 AMI admissions, 49.7% had pre-existent vascular disease. The odds of major adverse cardiovascular and cerebrovascular events (MACCE), mortality, ischemic stroke and major bleeding incrementally increased and was highest in those with ≥3 vascular sites involved (aOR for MACCE 1.16, CI 1.13–1.19; mortality 1.3, CI 1.26–1.34; stroke 1.15, CI 1.1–1.2; major bleeding 1.21, CI 1.16–1.25). Amongst those with a single pre-existent diseased vascular bed, the adjusted odds of MACCE appeared to be higher in those with PVD (1.28, CI 1.26–1.31), aortic disease (1.24, CI 1.19–1.29), and cerebrovascular disease (1.22, CI 1.2–1.25). Patients with pre-existent vascular disease had a lower overall likelihood of undergoing invasive revascularization procedures. Conclusions Approximately half of the population presenting with AMI have pre-existent vascular disease. There is an incremental increase in adverse outcomes with increasing number of diseased vascular beds, with further differences in outcomes and utilization of invasive procedures based on sub-types of sites involved.

Cancer patients face a higher risk of future myocardial infarction (MI), even after completion of anticancer therapies. MI is a critical source of physical and financial stress in non-cancer patients, but its impacts associated with cancer patients also saddled with the worry (stress) of potential reoccurrence is unknown. Therefore, we aimed to quantify MI’s stress and financial burden after surviving cancer and compare to those never diagnosed with cancer. Utilizing cross-sectional national survey data from 2013–2018 derived from publicly available U.S. datasets, the National Health Interview Survey (NHIS), and economic data from the National Inpatient Sample (NIS), we compared the socio-economic outcomes among those with MI by cancer-status. We adjusted for social, demographic, and clinical factors. Overall, 19,504 (10.2%) of the 189,836 NHIS survey responders reported having cancer for more than 1 year. There was an increased prevalence of MI among cancer survivors compared to non-cancer patients (8.8% vs. 3.2%, P0.05). There was no difference in annual residual family income by cancer status; however, 3 lowest deciles of residual income representing 21.1% cancer-survivor with MI had a residual income of

Colloidal quantum dots (QDs) are promising materials for optoelectronic devices. In this paper, monodispersed and environment stable cobalt (Co)-doped CdS QDs have been synthesized and characterize...

This paper discusses the response of ecosystem service values to land use/land cover (LULC) changes and examines spatial contributions of individual transformations to the ecosystem service functions in the Barasat Sadar subdivision (West Bengal, India) over the period from 1977 to 2016 on the basis of a modified coefficient. Spatiotemporal LULC patterns were identified on the basis of Landsat series satellite images taken at intervals of 10 years. To identify the LULC parameters, a supervised classification was performed on the basis of the maximum likelihood (MXL) classifier. Ecosystem service values have been computed per ha of the terrestrial ecosystem based on coefficients determined for each land cover parameter in earlier studies. In 2016, the highest ecosystem service value was attributed to surface waters ($477.06 million); while the lowest value corresponded to fallow lands ($0.98 million). The results obtained using the assumed coefficient indicate a continuous loss of the total ecosystem service value of $238.92 million over 1977–2016 due to the deterioration of agricultural fallow lands, areas occupied by dense vegetation, and shrubby lands, as well as rapid expansion of arable lands and development of an artificial infrastructure for surface-water bodies. The results of this study can be used as a reference and basis for decision making in the field of wise land resource management. In addition, the obtained data can be used to strike a compromise between urban growth and the decline of ecosystem services.

The industrial advancement has promoted the development of deep learning (DL)-based intelligent fault diagnosis methods for condition-based maintenance (CBM). Though these methods rely on large dataset for training, the collection of large number of fault samples is not practically feasible. For this purpose, generative adversarial networks (GANs) are capable to generate high-quality synthetic samples. However, the problem still persists with the training of GAN using limited fault samples that are present in practical conditions. This article proposes a novel conditional auxiliary classifier GAN framework coupled with model agnostic meta learning (MAML) to resolve this problem. The objective is to initialize and update the network parameters using MAML instead of regular stochastic gradient learning. This modification enables GAN to learn the task of synthetic sample generation using the limited training dataset. The effectiveness of the proposed framework has been compared with several famous state-of-the-art intelligent fault diagnosis methods existing in the literature. The comparative performance has been validated on benchmarked datasets, i.e., air compressor and bearing datasets collected from a single-stage reciprocating air compressor. The proposed framework is able to achieve the classification accuracy of 99.26% and 98.55% for bearing and air compressor datasets, respectively, with only ten samples per class. Moreover, a real-time case study is performed to validate the proposed method in real time.

The uncertainties of solar photovoltaics generation, electric vehicle charging demand, and home appliances load are the major challenge of energy management planning in the residential areas. Optimal allocation of battery energy storage systems for distribution networks based on probabilistic power flow (PPF) is an effective solution to deal with these uncertainties. However, the high computational burden is the main obstacle of this method. Therefore, this paper proposes a surrogate-assisted multi-objective probabilistic optimal power flow (POPF) to reduce the expensive computational time. The surrogate model is developed by using a machine learning method namely deep learning which is used for bypassing the deterministic load flow calculation. Zhao's point estimation method combined with Nataf transformation is selected to handle the PPF analysis considering correlated uncertain input variables. The multi-objective POPF problem is solved using the multi-objective differential evolution. The historical data including solar irradiation, ambient temperature, residential load, and electric vehicle (EV) travel distance is calculated in the low voltage distribution system to demonstrate the potential advantages of the proposed method. Numerical results show that the proposed surrogate assisted multi-objective POPF method provides the optimal solution for operating cost, helps to prolong transformer life and reducing environmental impact. Moreover, the results show that the proposed surrogate-assisted optimization framework gives a better solution when comparing with the conventional surrogate-assisted method.

Skin fibrosis caused by excessive collagen synthesis and deposition in the dermis affects the quality of daily life of hundreds of thousands of people around the world. The skin quality, including its smoothness in young age and wrinkly during the aging process, depends largely on the levels of extracellular matrix proteins such as collagen in skin. As physiological levels of collagen are desirable for skin homeostasis, beauty, and its flexibility, too much collagen deposition in the skin is associated with tight hard skin, loss of adipose layer, and flexibility, the pathological manifestations of skin fibrosis in fibrotic diseases such as scleroderma. To understand the molecular basis of skin fibrosis and in search of its therapy, different cellular, molecular, epigenetic, and preclinical studies have been undertaken to control abnormal excessive synthesis and accumulation of matrix protein collagen. Over the last two decades, numerous phase 1 through 3 clinical trials have been conducted to test the safety and efficacy of a wide variety of compounds in amelioration of skin fibrosis and other pathologies in scleroderma, yet, no effective therapy for skin fibrosis is available. This article solely focuses on the role of a nuclear receptor and transcription factor, peroxisome proliferator-activated receptor-gamma (PPAR-γ), as an anti-skin fibrotic driving force and the potential therapeutic efficacies of PPAR-γ-specific ligands/agonists including antidiabetic drugs and other natural or semi-synthetic compounds derived from cannabis in amelioration of skin fibrosis in scleroderma. The underlying molecular basis of agonist-activated PPAR-γ-mediated suppression of profibrogenic signaling and skin fibrogenesis is also highlighted.

Segmentation of retinal blood vessels is a very important diagnostic procedure in ophthalmology. Segmenting blood vessels in the presence of pathological lesions is a major challenge. In this paper, an innovative approach to segment the retinal blood vessel in the presence of pathology is proposed. The method combines both supervised and unsupervised approaches in the retinal imaging context. Two innovative descriptors named local Haar pattern and modified speeded up robust features are also proposed. Experiments are conducted on three publicly available datasets named: DRIVE, STARE and CHASE DB1, and the proposed method has been compared against the state‐of‐the‐art methods. The proposed method is found about 1% more accurate than the best performing supervised method and 2% more accurate than the state‐of‐the‐art Nguyen et al.’s method.

Large-scale graph processing is one of the recently developed significant research areas relevant to big data analytics. Distributed graph analytics is useful to see the intuitive insights of node interactions from large-scale network data. Distributed graph computing is an upcoming area in graph data mining that explores crucial node relationships for a given graph dataset. In this paper, we propose a new method to discover top-k user–user communities for a weighted bipartite network by defining a weighted similarity measure. We extend the structural similarity metric, namely Otsuka–Ochiai coefficient, by adding weights of nodes and quantifies the similarity between distinct items of a user–item network. We propose a new method to mine top-k user–user communities based on the similarity of items using a weighted similarity measure. Further, two algorithms, namely TUCSGF, TUCFlink, are presented to mine top-k user–user communities in a distributed approach based on the strength of the item-to-item similarities. Moreover, we execute the TUCSGF algorithm using Apache Spark by utilizing the advantage of Spark GraphFrames to mine top-k user–user communities. Also, we implement the TUCFlink algorithm to mine top-k communities using Apache Flink by utilizing the functionalities of Flink Gelly. Further, we explore two real-world network applications online learning network, chain of hospitals network with various graph methods that are to be applied for both the applications. Furthermore, we systematically perform various experiments concerning execution time, memory consumption, and CPU usage of both TUCSGF, TUCFlink on three distinct datasets. The performance of TUCFLINK is far better than TUCSGF concerning computing time. Applying distributed graph analytics for various complex networks using distributed graph processing tools GraphX, GraphFrames and Gelly provides more intuitive insights about distinct types of node interactions in graph data mining.

Understanding the pathophysiology of the coronavirus disease 2019 (COVID-19) infection remains a significant challenge of our times. The gingival crevicular fluid being representative of systemic status and having a proven track record of detecting viruses and biomarkers forms a logical basis for evaluating the presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The study aimed to assess gingival crevicular fluid (GCF) for evidence of SARS-CoV-2 in 33 patients who were deemed to be COVID-19 positive upon nasopharyngeal sampling. An attempt was also made to comparatively evaluate it with saliva in terms of its sensitivity, as a diagnostic fluid for SARS-CoV-2. GCF and saliva samples were collected from 33 COVID-19–confirmed patients. Total RNA was extracted using NucliSENS easyMAG (bioMérieux) and eluted in the elution buffer. Envelope gene ( E gene) of SARS-CoV-2 and human RNase P gene as internal control were detected in GCF samples by using the TRUPCR SARS-CoV-2 RT qPCR kit V-2.0 (I) in an Applied Biosystems 7500 real-time machine. A significant majority of both asymptomatic and mildly symptomatic patients exhibited the presence of the novel coronavirus in their GCF samples. Considering the presence of SARS-CoV-2 RNA in the nasopharyngeal swab sampling as gold standard, the sensitivity of GCF and saliva, respectively, was 63.64% (confidence interval [CI], 45.1% to 79.60%) and 64.52% (CI, 45.37% to 80.77%). GCF was found to be comparable to saliva in terms of its sensitivity to detect SARS-CoV-2. Saliva samples tested positive in 3 of the 12 patients whose GCF tested negative, and likewise GCF tested positive for 2 of the 11 patients whose saliva tested negative on real-time reverse transcription polymerase chain reaction. The results establish GCF as a possible mode of transmission of SARS-CoV-2, which is the first such report in the literature, and also provide the first quantifiable evidence pointing toward a link between the COVID-19 infection and oral health.

Allogeneic hematopoietic cell transplantation (alloHCT) for multiple myeloma (MM), with its underlying graft-versus-tumor capacity, is a potentially curative approach for high-risk patients. Relapse is the main cause of treatment failure, but predictors for postrelapse survival are not well characterized. We conducted a retrospective analysis to evaluate predictors for postrelapse overall survival (OS) in 60 MM patients who progressed after myeloablative T cell-depleted alloHCT. The median patient age was 56 years, and 82% had high-risk cytogenetics. Patients received a median of 4 lines of therapy pre-HCT, and 88% achieved at least a partial response (PR) before alloHCT. Of the 38% who received preemptive post-HCT therapy, 13 received donor lymphocyte infusions (DLIs) and 10 received other interventions. Relapse was defined as very early ( 24 months; 22%). At relapse, 27% presented with extramedullary disease (EMD). The median postrelapse overall survival (OS) by time to relapse was 4 months for the very early relapse group, 17 months for the early relapse group, and 72 months for the late relapse group (P = .002). Older age, relapse with EMD

BackgroundRe-allocation of resources during the COVID-19 pandemic has resulted in delays in care delivery to patients with cardiovascular disease and cancer. The ability of health care providers to provide optimal care in this setting has not been formally evaluated.ObjectivesTo assess the impact of COVID-19 resource re-allocation on scheduling, testing, elective procedures, telemedicine access, use of new COVID-19 therapies, and providers’ opinions on healthcare policies among oncology and cardiology practitioners.MethodsAn electronic survey was conducted by a cardio-oncology collaborative network through regional and state chapters of the American College of Cardiology, American Society of Clinical Oncology, and the International Cardio-Oncology Society. Descriptive statistics were reported by frequency and proportion for analyses, and stratified categorically by geographic region and specialty.ResultsOne thousand four hundred fifteen providers (43 countries) participated: 986 cardiologists, 306 oncologists, and 118 trainees/internal medicine. 63% (195/306) of oncologists vs 92% (896/976) of cardiologists reported cancellations of treatments/elective procedures (p = 0.01). 46% (442/970) of cardiologists and 25% (76/303) of oncologists modified the scope of their practice (p = p = 0.018). Telemedicine was less common in Europe 81% (74/91), and Latin America 64% (101/158), than the United States, 88% (950/1097) (p = ConclusionsThese results support initiatives to promote expanded coverage for telemedicine, increased access to PPE, better testing availability and involvement of medical professional societies to help with preparedness for future health care crisis.

Merozoite surface protein-1 (MSP-1) of malaria parasites has been extensively studied as a malaria vaccine candidate and the antibody response to this protein is an important indicator of protective immunity to malaria. Mangaluru city and its surrounding areas in southwestern India are endemic to malaria with Plasmodium vivax being the most widespread and prevalent species although P. falciparum also frequently infects. However, no information is available on the level of protective immunity in this population. In this regard, a prospective hospital-based study was performed in malarial patients to assess antibody responses against the 19-kDa C-terminal portion of P. vivax and P. falciparum MSP-1 (MSP-119). Serum samples from 51 healthy endemic controls and 267 infected individuals were collected and anti-MSP-119 antibody levels were analyzed by ELISA. The possible association between the antibody responses and morbidity parameters such as malarial anemia and thrombocytopenia was investigated. Among the 267 infected cases, 144 had P. vivax and 123 had P. falciparum infections. Significant levels of anti-MSP-119 antibody were observed both in P. vivax (123/144; 85.4%) and P. falciparum (108/123; 87.9%) infected individuals. In both type of infections, the major antibody isotypes were IgG1 and IgG3. The IgG levels were found to be increased in patients with severe anemia and thrombocytopenia. The antibody levels were also higher in infected individuals who had several previous infections, although antibodies produced during previous infections were short lived. The predominance of cytophilic anti-MSP-119 IgG1 and IgG3 antibodies suggests the possibility of a dual role of Pv MSP-119 and Pf MSP-119 during malarial immunity and pathogenesis.

Breast cancer is the most common site-specific cancer in women and is the leading cause of death from cancer for women aged 20-59 years. It accounts for 26% of all newly diagnosed cancers in females and is responsible for 15% of the cancer-related deaths in women. Presently, 75,000 new cases occur in Indian women every year. Locally advanced breast cancer (LABC) constitutes more than 50 to 70% of the patients presenting for treatment.

Burnout is a syndrome of emotional exhaustion, loss of meaning at work, feeling of ineffectiveness, and a tendency to view people as objects rather than as a human being. Physician burnout leads to dissatisfaction at work and suboptimal patient care. Various causes of burnout at the individual, work environment, and health system levels have been identified. In this review, we initially focus on the burden of burnout. Subsequently, we describe the determinants of this problem in India and the West, while drawing on relevant literature. Finally, we provide evidence based practical suggestions to deal with physician burnout. Strategies suggested to deal with burnout need to be implemented based on locally available resources. Repeated assessment of burnout constructs using validated questionnaires can evaluate the effectiveness of an intervention. Hospitals, educational institutions, and physician societies need to collaborate with practicing physicians to address burnout and invest in physician well-being to continue providing high-quality medical care in the future.

Purpose The paper aims to develop a comprehensive framework for adopting an information and communication technology (ICT)-enabled customer relationship management (CRM) system, toward strengthening and expanding the customer basis of the organization. Design/methodology/approach Advanced ICT-enabled CRM includes mobile CRM, AI integrated CRM and social CRM and several business organizations have already started exploring their advanced utilization for direct financial gain and indirect “soft” benefits. Most of them, however, are challenged in the process, due to lower-than-demanded adoption of such CRM systems. To deal with the issue, the paper methodologically applies a dual qualitative case study approach that ultimately develops an advanced comprehensive CRM adoption framework. Findings The key findings pertaining to the evaluation of organizations’ readiness to adopt advanced ICT-enabled CRM systems in terms of infrastructure and resources, the identification of the critical functional areas of the organization’s focus and the differences in the requisite approaches across industries and organization types. Practical implications In the context of the internet and social media, the analysis and management of customer big data and their transcription into useable information is crucial. Traditional and conventional CRM was deemed unable to address this need, thus necessitating the use of advanced ICT-enabled CRM. The proposed corresponding framework tangibly and practically, thus, directs businesses toward the successful deployment of ICT-based CRM systems. Originality/value This study constitutes a novel attempt to identify the issues of deployment of ICT-based CRM systems in an organization and proposes a comprehensive framework, which will enable organizations to overcome the barriers when adopting a new system.

The design of mobility-aware framework for edge/fog computing for IoT systems with back-end cloud is gaining research interest. In this paper, a mobility-driven cloud-fog-edge collaborative real-time framework, Mobi-IoST, has been proposed, which has IoT, Edge, Fog and Cloud layers and exploits the mobility dynamics of the moving agent. The IoT and edge devices are considered to be the moving agents in a 2-D space, typically over the road-network. The framework analyses the spatio-temporal mobility data (GPS logs) along with the other contextual information and employs machine learning algorithm to predict the location of the moving agents (IoT and Edge devices) in real-time. The accumulated spatio-temporal traces from the moving agents are modelled using probabilistic graphical model. The major features of the proposed framework are: (i) hierarchical processing of the information using IoT-Edge-Fog-Cloud architecture to provide better QoS in real-time applications, (ii) uses mobility information for predicting next location of the agents to deliver processed information, and (iii) efficiently handles delay and power consumption. The performance evaluations yield that the proposed Mobi-IoST framework has approximately 93% accuracy and reduced the delay and power by approximately 23–26% and 37–41% respectively than the existing mobility-aware task delegation system.

Fungal Endophthalmitis is a potentially blinding condition, and difficult to treat. It is more often reported from Asia, including India. The mainstays of treatment are vitrectomy and intravitreal ...

Background India introduced rotavirus vaccines (RVV, monovalent, Rotavac™ and pentavalent, Rotasiil™) in April 2016 with 6, 10 and 14 weeks schedule and expanded countrywide in phases. We describe the epidemiology of intussusception among children aged 2–23 months in India. Methods The prospective surveillance at 19 nationally representative sentinel hospitals from four regions recruited children with intussusception from April 2016 to September 2017. Data on sociodemography, immunization, clinical, treatment and outcome were collected. Along with descriptive analysis, key parameters between four regions were compared using Chi-Square/Fisher’s exact/Mann–Whitney U/Kruskal-Wallis tests. The pre- and post-RVV periods were compared to estimate the risk ratios. Results Six hundred twenty-one children with intussusception from South (n = 262), East (n = 190), North (n = 136) and West (n = 33) regions were recruited. Majority (n = 465, 74.8%) were infants (40.0% aged 4–7 months) with median age 8 months (IQR 5, 13 months), predominantly males (n = 408, 65.7%) and half (n = 311, 50.0%) occurred during March–June months. A shorter interval between weaning and intussusception was observed for ragi based food (median 1 month, IQR 0–4.2 months) compared to rice (median 4 months, IQR 1–9 months) and wheat (median 3 months, IQR 1–7 months) based food (p Conclusions Intussusception cases were observed across all sites, although there were variations in cases, presentation and mode of management. The high case load age coincided with age of the RVV third dose. The association with ragi based weaning food in intussusception needs further evaluation.

Background Acute coronary syndrome (ACS) is a highly thrombotic state, and a sustained antiplatelet effect is vital to the prevention of thrombotic complications. Clopidogrel, the most widely used oral P2Y12 receptor antagonist in ACS, has attracted considerable attention because of significant variability in antiplatelet effect depending on the presence of CYP2C19 allele. Other P2Y12 receptor antagonists offer sustained and more predictable antiplatelet effects than clopidogrel albeit at an increased cost. Several studies have demonstrated the promising application of pharmacogenetics in choosing personalized antiplatelet therapy using the point-of-care genotype assays. Areas of uncertainty Guidelines regarding the genotype-guided approach to the selection of antiplatelet therapy have been conflicting, and studies evaluating the effect of pharmacogenetic-guided selection of antiplatelet therapy on the outcomes have demonstrated mixed results. Data sources A literature search was conducted using MEDLINE and EMBASE for studies reporting the association of pharmacogenetic-guided selection of antiplatelet therapy and the outcomes in patients with ACS until December 2018. Results Presence of specific CYP2C19 allele significantly influences clopidogrel metabolism and associated outcomes in patients with ACS. Thrombotic and bleeding complications are more common in patients with loss-of-function (LOF) and gain-of-function (GOF) alleles, respectively. Although the pharmacogenetic-guided approach to the selection of antiplatelet therapy appears promising in ACS, studies have shown conflicting results, and direct randomized evidence linking this approach with the better outcomes is lacking. Conclusions Genotype-guided selection of antiplatelet therapy is expected to be useful in patients undergoing percutaneous coronary intervention (PCI) with a high risk of adverse outcomes. The patient-physician discussion should be an essential part of this decision-making process. Large-scale multicenter randomized controlled trials using the point-of-care genotype assay are needed to investigate this approach further before its use can be recommended in all comers.

Depression is a recognized predictor of adverse outcomes in patients with heart failure (HF) and is associated with poor quality of life, functional limitation, increased morbidity and mortality, decreased adherence to treatment, and increased rehospitalization. To understand the impact of depression on HF readmission, we conducted a retrospective cohort study using the Nationwide Readmission Database (NRD) 2010-2014.We identified all patients with the primary discharge diagnosis of HF by ICD-9-CM codes. The primary outcome of the study was to identify 30-day all-cause readmission and causes of readmission in patients with and without depression. Multivariate Cox regression analysis was used to estimate the adjusted hazard ratio for the primary and secondary outcomes.Among, 3,500,570 patients admitted with HF, 9.7% had concomitant depression. Patients with depression were more likely to be readmitted within 30 days (19.7% vs. 18.5%; P 0.001). Concomitant depression was associated with higher risk of all-cause readmissions within 30 days and 90 days [P 0.001] but was not associated with increased readmissions due to cardiovascular (CV) cause at 30 days and 90 days. The hazard of psychiatric causes of readmission was higher in patients with depression, both at 30 days [P 0.001], and 90 days [P 0.001]. Most of the readmissions were due to CV causes, with HF being the most common cause.Among patients hospitalized with HF, the presence of depression is associated with increased all-cause readmission driven mainly by psychiatric causes but not CV-related readmission. Standard interventions targeted toward HF are unlikely to modify this portion of all-cause readmission.

The 2019 COVID-19 pandemic has thrown the global health-care system into a chaotic flux. Consolidating and reviewing all available knowledge will be crucial to combating the spread of this novel coronavirus. Prevention is paramount, but health care workers are at increased risk, and protective supplies are being limited and being rationed. Common symptoms include fever, cough, and shortness of breath. Hospitalizations are estimated to occur in about 20% of cases and are mostly due to pneumonia.[1] While multiple promising treatments are being reported in the medical literature; there is limited, reliable clinical data are available. To minimize exposure of medical staff to contagious patients and to provide rapid escalation of care to these patients, a telehealth strategy could be leveraged. Such a strategy would entail the use of both telemedicine visits for communication and digital health platforms for monitoring.

Purpose The purpose of this study is to make an attempt to identify the factors responsible for the adoption of an artificial intelligence (AI)-integrated customer relationship management (CRM) system in Indian organizations with a special focus on security and privacy issues. Design/methodology/approach This study was conducted for the identification of factors responsible for the adoption of the AI-integrated CRM system in Indian organizations focusing attention on security and privacy perspective. For this, the adoption theories and models have been studied. The literature available in this context has also been studied with a focus on security and privacy issues. After the initial study, few hypotheses have been formulated and a conceptual model has been developed. These hypotheses were validated with the help of statistical tools by conducting sample survey with 324 usable responses against 36 questionnaires. Findings The results of this study highlight that of the eight hypotheses conceptually formulated, one hypothesis was not supported as is evident from the application of statistical analysis. This is the influence of perceived ease of use on attitude of the stakeholders intending to use the AI-integrated CRM system in Indian organizations. The results also transpire that the model so provided has achieved 87% explanative power. Research limitations/implications The model so provided has taken the help of the technological acceptance model. It has also used the issues circumscribing menace of security and privacy vulnerabilities. Consideration of the technological acceptance model and aspects of issues of security and privacy has enriched the model rendering its explanative power to 87%. Practical implications The model is simple. Practitioners can execute this model without having any complexity. The policymakers could also get inputs from the model, as it has focused specially on security and privacy issues that could help to enhance the trust of the potential users. Originality/value Not many studies are found covering the adoption of the AI-integrated CRM system by Indian organizations with a special focus on security and privacy aspects. In this light, this study is a novel attempt.

Purpose of review Cancer patients often have cardiovascular risk factors at the time of cancer diagnosis, which are known to increase the risk of cardiotoxicity. Cancer survivors have significantly higher cardiovascular risk. Current cardiovascular disease prevention guidelines are based on studies that largely excluded these patients. We reviewed recent data regarding cardiovascular disease prevention in this population. Recent findings Nonpharmacologic therapies aiming to reduce 'lifestyle toxicity' produced by cancer treatments have demonstrated potential to decrease the incidence of adverse outcomes. Exercise before, during and after cancer treatment not only promotes higher quality of life and cardiorespiratory fitness but also reduces adverse cardiovascular outcomes. Lipid and cardiometabolic disease management is paramount but predominantly based on data that excludes these populations of cancer patients and survivors. Summary A comprehensive approach including medical evaluation, prescriptive exercise, cardiac risk factor modification, education, counseling, pharmacologic and behavioral interventions are needed in cancer patients. These interventions constitute the core of cardio-oncology rehabilitation programs, which if implemented appropriately may help reduce cardiovascular events in this population. Knowledge gaps in these areas are starting to be addressed by ongoing clinical trials.

Uterine torsion is considered an obstetrical emergency and should be corrected as soon as it is diagnosed. It occurs frequently in buffaloes as compared to other species of animals, mainly due to their peculiar anatomy and physiology. This case report describes the occurrence of uterine torsion in a pregnant pluriparous buffalo. The buffalo was presented with history of persistent straining for over 6 hours. The cervix was fully dilated and obstetrical examination revealed dystocia due to a left sided uterine torsion. Haematological results revealed a normal PCV but with an accompanying macrocytosis. There was also neutrophilia, eosinophilia as well as lymphopenia as well as hypocalcium and hypomagnesemia. The dystocia was corrected using the Schafer’s technique. This involved the placing of the free end of a wooden plank on the left flank while the other free end, having an assistant standing on it rested on the ground. Rolling the buffalo twice with this arrangement corrected the anomaly.

Soft materials with high power factors (PFs) and low thermal conductivity (κ) are critically important for integration of thermoelectric (TE) modules into flexible form factors for energy harvestin...