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The increasing use of multimedia applications often makes the information prone to leakage and makes the user's privacy at risk. The information hiding technique is mainly used to secure multimedia communication/information by modifying the secret information in a way that makes it useless for an unintended user. In this way, the secret information is secured from unauthorized access. To create a mosaic image, initially, a style transfer is applied using the Convolutional Neural Network (CNN) architecture. The style transfer alters the style of an image using another image still preserving the original content. The CNN’S optimization problem is to optimize the content loss, style loss, and total variation loss done using an Archimedes Optimization Algorithm (AOA). The AOA algorithm also alters the block in the target image by selecting an appropriate tile in the secret image. The tile fitting information is randomly inserted into the selected pixels using an improved dual image-based LSB matching (DILSBM) scheme. The DILSBM scheme can retrieve both the secret and target images from the mosaic image by offering a high PSNR value. The proposed DILSBM and CNN optimized AOA architecture is primarily intended to provide high capacity, improved visual quality, and solve the source image selection problem. The feasibility of the proposed technique can be observed from the experimental analysis where it is analyzed using different performance metrics such as Embedding Rate, Structural Similarity Method (SSIM), and peak signal-to-noise ratio (PSNR).

Kidney transplantation is the therapy of choice for patients with end-stage renal disease. Preexisting diabetes is highly prevalent in kidney transplant recipients (KTR), and the development of posttransplant diabetes is common because of a number of transplant-specific risk factors such as the use of diabetogenic immunosuppressive medications and posttransplant weight gain. The presence of pretransplant and posttransplant diabetes in KTR significantly and variably affect the risk of graft failure, cardiovascular disease (CVD), and death. Among the many available therapies for diabetes, there are little data to determine the glucose-lowering agent(s) of choice in KTR. Furthermore, despite the high burden of graft loss and CVD among KTR with diabetes, evidence for strategies offering cardiovascular and kidney protection is lacking. Recent accumulating evidence convincingly shows glucose-independent cardiorenal protective effects in non-KTR with glucose-lowering agents, such as sodium-glucose cotransporter-2 inhibitors and glucagon-like peptide-1 receptor agonists. Therefore, our aim was to review cardiorenal protective strategies, including the evidence, mechanisms, and rationale for the use of these glucose-lowering agents in KTR with diabetes. ispartof: TRANSPLANTATION vol:106 issue:4 pages:734-748 ispartof: location:United States status: published

BACKGROUND COVID-19 is a novel disease caused by Coronavirus. It was declared a pandemic by WHO in March 2020. To reduce the impact of the disease lockdown was imposed by various governments. This has a psychological impact on various groups of people. Schoolteachers are no less affected. There is scarcity in our understanding of the psychological impact among schoolteachers. This study is an attempt to understand the psychological impact among schoolteachers. We wanted to study the psychological impact of the COVID-19 pandemic on schoolteachers. METHODS The study was a cross-sectional one and conducted using online Google forms. A total of seventy-nine schoolteachers were included in the study analysis. The data were analysed using R language; nonparametric tests like Mann Whitney U and Kruskal Wallis test were used. The data obtained were tabulated and discussed. RESULTS Nearly half the sample belongs to 46 to 55 years, males constitute 57 %, majority of the participants were married, there was an equal distribution from a rural and urban background and teachers working in Government setup were 86 %. Females had significantly higher levels of depression and stress. Married had significantly higher levels of depression. Moderate to severe levels of depression, anxiety and stress were seen in 2.6 %, 10 %, and 2.5 % of the participants. CONCLUSIONS The study has found an increase in psychological impact among the schoolteachers. But the reported increase is less than that observed during the peak of the pandemic. Females have more depression and stress compared to males. KEYWORDS COVID-19, Mental Disorders, Pandemic, Schoolteachers

Tropical cyclones as natural disturbances, influence ecosystem structure, function and dynamics at the global scale. This study assesses the inundation due to the super cyclone Amphan in coastal districts of eastern India by leveraging the computational power of Google Earth Engine (GEE) and the availability of high resolution Sentinel-1 Synthetic Aperture Radar (SAR) data. A cloud-based image processing framework was developed and implemented in GEE for classification using Random Forest algorithm. The inundation areas due to storm surge owing to cyclone Amphan, were mapped and further categorised to different land use and land cover classes based on an existing land cover map. Sentinel-1 images were useful in post-cyclone studies for the change detection analysis due to its higher temporal resolution and cloud penetration ability. The study found that the majority of agricultural and agricultural fallow lands were inundated in the coastal districts. The availability of open-source cloud-based data processing platforms provides cost effective way to rapidly gather accurate geospatial information. Such information could be useful for emergency response planning and post-event disaster management including relief, rescue and rehabilitation measures; and crop yield loss assessment. Cyclone and Land Use and Land Cover (LULC) change can have significant impacts on the human population and if both coexist, the consequences for people and the surrounding environment may be severe.

Alcoholic fatty liver disease (AFLD) is characterized by lipid accumulation and inflammation and can progress to cirrhosis and cancer in the liver. AFLD diagnosis currently relies on histological analysis of liver biopsies. Early detection permits interventions that would prevent progression to cirrhosis or later stages of the disease. Herein, we have conducted the first comprehensive time-course study of lipids using novel state-of-the art lipidomics methods in plasma and liver in the early stages of a mouse model of AFLD, i.e., Lieber-DeCarli diet model. In ethanol-treated mice, changes in liver tissue included up-regulation of triglycerides (TGs) and oxidized TGs and down-regulation of phosphatidylcholine, lysophosphatidylcholine, and 20-22-carbon-containing lipid-mediator precursors. An increase in oxidized TGs preceded histological signs of early AFLD, i.e., steatosis, with these changes observed in both the liver and plasma. The major lipid classes dysregulated by ethanol play important roles in hepatic inflammation, steatosis, and oxidative damage. Conclusion: Alcohol consumption alters the liver lipidome before overt histological markers of early AFLD. This introduces the exciting possibility that specific lipids may serve as earlier biomarkers of AFLD than those currently being used.

The energy consumption of the buildings for cooling, especially during the days of high solar exposure is large due to the increased indoor temperature. The roof of the building contributes more for this cause by allowing a large quantity of heat during day hours. Further, the single storey buildings with the metal roof would help to penetrate a greater quantity of heat and increase the total heat gain of the building. In this way, they could increase the cooling load to attain the human comfort. In this current work, an experimental investigation was carried-out to reduce the indoor temperature of the metal roof single storey industrial building with the help of paraffin based phase changing material (PCM). In this fashion, an attempt was made to reduce the total cooling load of the building which can diminish a greater quantity of conventional power requirement. A scale model of the proposed building was fabricated and tested for the analysis. The experiments conducted in two modes such as the first case without any PCM in the roof (Plain Roof) and next case with encapsulated paraffin as PCM within the roof (PCM Roof). The test results proved that the encapsulation of PCM within the metal roof of the single storey building reduced the temperature of the outer roof, inner roof and consequently the indoor temperature of the building space to a vast extent. Quantitatively, the daily average indoor temperature was dropped by 5 °C and peak indoor temperature was reduced by 9.5 °C with the help of PCM.

Targeted therapy aiming at the metastatic signal pathway, such as that triggered by receptor tyrosine kinase (RTK), for the prevention of tumor progression is promising. However, RTK-based targeted therapy frequently suffered from drug resistance due to the co-expression of multiple growth factor receptors that may raise compensatory secondary signaling and acquired mutations after treatment. One alternative strategy is to manipulate the common negative regulators of the RTK signaling. Among them, Raf kinase inhibitory protein (RKIP) is highlighted and focused on this review. RKIP can associate with Raf-1, thus suppressing the downstream mitogen-activated protein kinase (MAPK) cascade. RKIP also negatively regulates other metastatic signal molecules including NF-κB, STAT3, and NOTCH1. In general, RKIP achieves this task via associating and blocking the activity of the critical molecules on upstream of the aforementioned pathways. One novel RKIP-related signaling involves reactive oxygen species (ROS). In our recent report, we found that PKCδ-mediated ROS generation may interfere with the association of RKIP with heat shock protein 60 (HSP60)/MAPK complex via oxidation of HSP60 triggered by the tumor promoter 12-O-tetradecanoyl-phorbol-13-acetate. The departure of RKIP may impact the downstream MAPK in two aspects. One is to trigger the Mt→cytosol translocation of HSP60 coupled with MAPKs. The other is to change the conformation of HSP60, favoring more efficient activation of the associated MAPK by upstream kinases in cytosol. It is worthy of investigating whether various RTKs capable of generating ROS can drive metastatic signaling via affecting RKIP in the same manner.

Additive Manufacturing of ahuman mandible physical model is developedfrom thepatient having missing teeth at first molar position usingFDM (Fused Deposition Modelling) technique. These physical models are helpful for the surgeons to perform pre-operative procedure to improve the success rates of the surgery. Genesis AKTIV implant is Modelled using CATIA V5 software by considering DICOM Datain NNT viewer software. Finite element analysis is performed on implant with occlusal force and torque. For this initially DICOM data of mandible is extracted from CT Scan and converted to STL format using InVesalius medical modelling software. Modelling of fixture, abutment and screw are developed with IMPLANT GENESIS AKTIV implant standards using CAD software. Depending on the NNT Viewer results suitable parameters are chosen to develop fixture. STL file attained from medical modelling software is further processed and converted to STEP format for performing analysis. Analysis is performed to check deformation and vonmises stress using ANSYS software. Finite element analysis results shown that the von mises stresses does not surpass the yield strength and all the stresses generated are permissible to the mandible.

Electrocardiogram (ECG) is a non-invasive technique used to detect various cardiac disorders. One of the major causes of cardiac arrest is an arrhythmia. Furthermore, ECG beat classification is essential to detect life-threatening cardiac arrhythmias. The major limitations of the traditional ECG beat classification systems are the requirement of an extensive training dataset to train the model and inconsistent performance for the detection of ventricular and supraventricular ectopic (V and S) beats. To overcome these limitations, a system denoted as SpEC is proposed in this work based on Stockwell transform (ST) and two-dimensional residual network (2D-ResNet) for improvement of ECG beat classification technique with a limited amount of training data. ST, which is used to represent the ECG signal into a time-frequency domain, provides frequency invariant amplitude response and dynamic resolution. The resultant ST images are applied as input to the proposed 2D-ResNet to classify five different types of ECG beats in a patient-specific way as recommended by the Association for the Advancement of Medical Instrumentation (AAMI). The proposed SpEC system achieved an overall accuracy (Acc) of 99.73%, sensitivity (Sen) = 98.84%, Specificity (Spe) = 99.50%, Positive predictivity (Ppr) = 98.20% on MIT-BIH arrhythmia database, and shows an overall Acc of 89.87% on real-time acquired ECG dataset with classification time of single ECG beat image = 0.2365 (s) in detecting of five arrhythmia classes. The proposed method shows better performance on both the database compared to the earlier reported state-of-art techniques.

Despite all its potential for paddy farming, productivity in Sunsari is still below the productivity of nearby districts like Jhapa, Morang, and Udayapur having similar climatic conditions as Sunsari. So, this research was carried out in the month of May- June in 2020 to identify the factors affecting paddy production and problems of paddy production in Sunsari district. Sunsari district was purposively selected due to the high potential of paddy production in the region. Total one hundred of farmer’s households were selected by simple random sampling and primary data was collected with the help of a pre-tested semi-structured questionnaire by interview schedule and secondary data were collected from relevant journals. A multiple regression model was applied to identify the factors of paddy production. This study identified that paddy cultivated land with irrigation facility, the experience of farmers in the field of paddy farming (years), and use of modern rice varieties had a significant positive impact on paddy production in the study area. About 85% variation in paddy production was explained by the independent variable considered under the study. Indexing was applied to identify major problems of paddy production. This study revealed that lack of fertilizer in peak plantation time, lack of sufficient measure and knowledge for disease and pest management, lack of training about improved paddy farming practices, lack of government support in agricultural inputs, etc. were major constraints of paddy production in the study area. The irrigation facility should be further improved to bolster paddy production.

Purpose Many investigations are going on in monitoring, contact tracing, predicting and diagnosing the COVID-19 disease and many virologists are urgently seeking to create a vaccine as early as possible. Even though there is no specific treatment for the pandemic disease, the world is now struggling to control the spread by implementing the lockdown worldwide and giving awareness to the people to wear masks and use sanitizers. The new technologies, including the Internet of things (IoT), are gaining global attention towards the increasing technical support in health-care systems, particularly in predicting, detecting, preventing and monitoring of most of the infectious diseases. Similarly, it also helps in fighting against COVID-19 by monitoring, contract tracing and detecting the COVID-19 pandemic by connection with the IoT-based smart solutions. IoT is the interconnected Web of smart devices, sensors, actuators and data, which are collected in the raw form and transmitted through the internet. The purpose of this paper is to propose the concept to detect and monitor the asymptotic patients using IoT-based sensors. Design/methodology/approach In recent days, the surge of the COVID-19 contagion has infected all over the world and it has ruined our day-to-day life. The extraordinary eruption of this pandemic virus placed the World Health Organization (WHO) in a hazardous position. The impact of this contagious virus and scarcity among the people has forced the world to get into complete lockdown, as the number of laboratory-confirmed cases is increasing in millions all over the world as per the records of the government. Findings COVID-19 patients are either symptomatic or asymptotic. Symptomatic patients have symptoms such as fever, cough and difficulty in breathing. But patients are also asymptotic, which is very difficult to detect and monitor by isolating them. Originality/value Asymptotic patients are very hazardous because without knowing that they are infected, they might spread the infection to others, also asymptotic patients might be having very serious lung damage. So, earlier prediction and monitoring of asymptotic patients are mandatory to save their life and prevent them from spreading.

Rheumatoid arthritis (RA) is a heterogeneous autoimmune disease, characterized by chronic inflammation, hyperplasia (swelling), tenderness, erosion of cartilage and bones in synovial joints. Transforming growth factor-β1 (TGF-β1) is an important regulator of inflammation, and its polymorphism is implicated in several diseases. Therefore, the study was done to determine whether TGF-β1 C/T gene polymorphism was associated with RA in North Indian population.Eighty-seven (male/female: 29/58) healthy controls and 76 (male/female: 17/59) RA patients were recruited for association study between TGF-β1 +869C/T polymorphism. TGF-β1 +869C/T polymorphism was genotyped by allele specific amplification refractory mutation system polymerase chain reaction (ARMS-PCR) to test susceptibility to clinical presentation of RA patients in North Indian population by comparing RA genotypes with control groups.The genotypic association studies and dominant, recessive, and allelic models revealed that TGF-β1 +869C/T gene polymorphism is involved in the onset of RA. TGF-β1 +869 T (either TT or CT) allele and TT v/s CC (OR = 36.18, 95% CI = 11.98-109.31, P = 0.001); TT + CT v/s CC (OR = 0.16, 95% CI = 0.08-0.33, P = 0.001); TT v/s CC + CT (OR = 0.04, 95% CI = 0.1-0.09, P = 0.001); and T v/s C (OR = 0.12, 95% CI = 0.07-0.2, P = 0.001) show significant association with RA as compared with CC genotype or C alleles (P = 0.001). The patient carrying T alleles showed significant associations with increased ESR, uric acid, CRP, DAS28-ESR, and number of tender joints as compared to other genotypes. In the presence of RF, DAS-28-ESR was high in CT genotype. ESR, CRP, and swollen joint count were highest in TT genotype of RF negative patients.TGF-β1 polymorphism is associated with disease activity of RA. Disease activity is strongly modulated in the presence of serum RF and TGF-β1 polymorphism. Key Points •TGF-β1 +869C/T polymorphism was found to be associated with RA in the patients. •The polymorphism showed significant association with all inflammatory parameters as ESR, CRP, and DAS-28 in RA subjects. •RF negative patients showed high ESR, CRP, and swollen joint count with TT genotype. •TGF-β1 polymorphism and serum RF are modulating disease activity in RA.

In this article, we investigate the transient behavior of a sequence of packets/bits traversing a multi-hop wireless network under static routing. Our work is motivated by novel applications from the domain of process automation, Machine-Type Communication (MTC) and cyber-physical systems, where short messages are communicated and statistical guarantees need to be provided on a per-message level. In order to optimize such a network, apart from understanding the stationary system dynamics, an understanding of the short-term dynamics (i.e. transient behavior) is also required. To this end, we derive novel Wireless Transient Bounds (WTB) for end-to-end delay and backlog in a multi-hop wireless network using stochastic network calculus approach. We start by analyzing a single end-to-end path, i.e. a line topology, and then we show how the obtained results can be applied to a mesh network with static routing using a concept called ’ leftover service ’. WTB depends on the initial backlog at each node as well as the instantaneous channel states. We numerically compare WTB with Kernel-Based-Transient Bound (KBTB), which can be obtained by adapting existing stationary bound, as well as simulated end-to-end delay of the investigated network. While KBTB and stationary bounds are not able to capture the short-term system dynamics well, WTB provides relatively tight upper bound and has a decay rate that closely matches the simulation. This is achieved by WTB only with a slight increase in the computational complexity, by a factor of $O(T+N)$ , where $T$ is the duration of the arriving sequence and $N$ is the number of hops in the network. We believe that the presented analysis and the bounds are necessary tools for future work on transient network optimization for many important emerging applications, e.g., massive MTC, critical MTC, edge computing and autonomous vehicle.

In machine learning, an efficient classifier model design is mostly based on effective feature extraction and appropriate feature selection. This work mainly focused on different optimized feature ...

Highlights • Prelicensure trials of ROTAVAC® not powered to assess risk of intussusception. • During ROTAVAC® rollout we assessed risk of intussusception in infants in 3 states. • No increased risk of intussusception within 21 days of 1st and 2nd dose. • No increased risk of intussusception within 21 days of any single dose or all 3 doses., Background Pre-licensure trials of ROTAVAC® were not adequately powered to assess risk of intussusception, a rare adverse event associated with other rotavirus vaccines in some settings. We examined the risk of intussusception after ROTAVAC® vaccination among Indian infants during pilot rollout of the vaccine in the public health system in three states - Himachal Pradesh, Maharashtra and Tamil Nadu. Methods Passive surveillance for intussusception was set up in 35 sentinel health facilities covering 26.3 million population in the three states under monitoring of an Interministerial-Interagency Steering Committee. Clinical and immunization data were collected by independent teams. An expert committee blinded to vaccination status, classified intussusception cases using Brighton criteria. The self-controlled case-series method was used to estimate risk of intussusception (Brighton Level 1) after ROTAVAC® vaccination. Results 151 intussusception cases were included in the analysis. The relative incidence (incidence during the risk period compared to the control period) 1–21 days after doses 1 and 2 combined was 1.56 (95% CI, 0.0–5.28) and that for three doses combined was 1.88 (95% CI, 0.76–4.30). Attributable risk 1–21 days after doses 1 and 2 combined was 0.11 (95% CI, 0.0–0.25) and that for 3 doses combined was 0.42 (95% CI, 0.0–0.70) per 100,000 doses. Conclusions No increased risk of intussusception within 21 days of receipt of the first two doses combined or all 3 doses combined of ROTAVAC® was detected.

Coronavirus disease of 2019 (COVID-19) is a highly contagious infectious disease which lead to a global pandemic. This virus attacks the small blood vessels, endothelial linings and lead to impaired blood flow and vessel malfunctioning's in various organs. This explains the reason why the high vulnerability patient population is those with comorbidities like hypertension, diabetes, COPD, obesity and cardiovascular diseases. The objective of the study was to compare the rates of recovery in the comorbid Covid-19 patient population when compared to those without comorbidities by evaluating their CT Chest - Score, RT- PCR, duration of hospitalization and thereby assess if the quality of life was compromised. A Prospective Observational Study was conducted for a period of 4 months with over 400 laboratory-confirmed Covid-19 patients. Out of the 400 patients, considering the exclusion and inclusion criteria 191 moderately ill covid-19 patients with or without comorbidities were included in the study. The severity of the patients was assessed based on the CT- Chest Score and COVID-19 RT-PCR reports. Various other complications faced by comorbid patients when compared to patients with nil comorbidities were also investigated. In our study among the underlying comorbidities, the most common were DM (40.11%), HTN (35.32 %), CAD (7.78 %), COPD (6.58 %), CKD (5.38 %) and then hypothyroidism (4.79 %). Our study also concluded that the percentage of patients with a comorbid condition was higher (59.68%) than those without a comorbid condition (40.31%). The mean reduction in CT-Score in the comorbid and nil-comorbid was found to be 9.38 ± 2.85 and 7.08 ± 2.89. The mean reduction in hospital stay in the comorbid and nil comorbid group was found to be 9.50 ± 2.34 and 8.08 ± 1.71. The mean reduction in RT-PCR was 10.04 ± 2.95 and 7.44 ± 2.33 in the comorbid and nil comorbid group respectively. Therefore, the RT-PCT, duration of hospital stay and CTChest Score showed a statistical si

This research study has applied facial recognition techniques using the angle detection algorithm. Also, a fast angle detection algorithm has been used here, but modified it by applying a shielding technique to create a technique related to loud noise. This article describes twelve facial signs that include the corner of the left eye, the corner of the right eye, the left eyebrow, the right eyebrow, the corner of the lip, and the nostril. It consists of two parts; first, a private browsing technique has been performed to filter the image from noise. The proposed method is based on the assumption that an image is available from the front (fully front). Skin areas were first detected using a color-based learning algorithm and six sigma techniques on RGB, HSV, and NTSC scales. Other analyzes involve morphological processing using the detection of the borderline and the detection of the reflection from the light source of the eye commonly referred to as the eye point. In the second step, a fast angle detection algorithm has been used to detect the placeholders on the face. The Fast Angle Finder works on the Angular Response Function (CRF) which is calculated as the minimum change in intensity in all possible directions. Finally, a comparison has been made with other filtering techniques based on the proposed protection techniques. This article has performed different experiments by using the IRIS Face Database, BioID, and the Cohn Canada Database. The recognition rate obtained by the proposed method is appreciable.

Electro Encephalo Gram (EEG) is a monitoring method used in biomedical and computer science to understand brain activity. Therefore, the analysis and classification of these signals play a prominent role in estimating a person’s behavior to certain events. Manually analyzing these signals is very tedious and time-consuming, so an automated scientific tool is required to analyze the brain signals. In this work, the authors are explored various pre-processing segmentation techniques that are helpful in an automatic machine and deep learning-based classification methods available for EEG signal processing. Most of the machine and deep learning methods are followed pre-processing as a common step in classification. Extraction of the basic sub-band components from EEG signals such as delta (δ), theta (θ), alpha (α), beta (β), and gamma (γ) is very important in the pre-processing stage. These sub bands of EEG signal have extraordinary evidence related to multiple neurophysiological processes, which are useful for further prediction & diagnosis of diseases and other emotion-based applications. This review paper elaborates various elementary ideas of extracting EEG sub-bands and the role of EEG in Brain-Computer Interface (BCI) in the classification. (Submitted To IEEE reviews in Biomedical Engineering)

At present, people spend most of their time in passive rather than active mode. Sitting with computers for a long time may lead to unhealthy conditions like shoulder pain, numbness, headache, etc. To overcome this problem, human posture should be changed for particular intervals of time. This paper deals with using an inertial sensor built in the smartphone and can be used to overcome the unhealthy human sitting behaviors (HSBs) of the office worker. To monitor, six volunteers are considered within the age band of 26 ± 3 years, out of which four were male and two were female. Here, the inertial sensor is attached to the rear upper trunk of the body, and a dataset is generated for five different activities performed by the subjects while sitting in the chair in the office. Correlation-based feature selection (CFS) technique and particle swarm optimization (PSO) methods are jointly used to select feature vectors. The optimized features are fed to machine learning supervised classifiers such as naive Bayes, SVM, and KNN for recognition. Finally, the SVM classifier achieved 99.90% overall accuracy for different human sitting behaviors using an accelerometer, gyroscope, and magnetometer sensors.

MXenes are a new type of two-dimensional (2D) material which are rapidly gaining traction for a range of environmental, chemical and medical applications. MXenes and MXene-composites exhibit high surface area, superlative chemical stability, thermal conductivity, hydrophilicity and are environmentally compatible. Consequently, MXenes have been successfully employed for hydrogen storage, semiconductor manufacture and lithium ion batteries. In recent years, MXenes have been utilized in numerous environmental applications for treating contaminated surface waters, ground and industrial/ municipal wastewaters and for desalination, often outperforming conventional materials in each field. MXene-composites can adsorb multiple organic and inorganic contaminants, and undergo Faradaic capacitive deionization (CDI) when utilized for electrochemical applications. This approach allows for a significant decrease in the energy demand by overcoming the concentration polarization limitation of conventional CDI electrodes, offering a solution for low-energy desalination of brackish waters. This article presents a state-of-the-art review on water treatment and desalination applications of MXenes and MXene-composites. An investigation into the kinetics and isotherms is presented, as well as the impact of water constituents and operating conditions are also discussed. The applications of MXenes for CDI, pervaporation desalination and solar thermal desalination are also examined based on the reviewed literature. The effects of the water composition and operational protocols on the regeneration efficacy and long-term usage are also highlighted.

Background COVID-19 is associated with both venous and arterial thrombotic complications. While prophylactic anticoagulation is now widely recommended for hospitalized patients with COVID-19, the effectiveness and safety of thromboprophylaxis in outpatients with COVID-19 has not been established. Study Design PREVENT-HD is a double-blind, placebo-controlled, pragmatic, event-driven phase 3 trial to evaluate the efficacy and safety of rivaroxaban in symptomatic outpatients with laboratory-confirmed COVID-19 at risk for thrombotic events, hospitalization, and death. Several challenges posed by the pandemic have necessitated innovative approaches to clinical trial design, start-up, and conduct. Participants are randomized in a 1:1 ratio, stratified by time from COVID-19 confirmation, to either rivaroxaban 10 mg once daily or placebo for 35 days. The primary efficacy end point is a composite of symptomatic venous thromboembolism, myocardial infarction, ischemic stroke, acute limb ischemia, non-central nervous system systemic embolization, all-cause hospitalization, and all-cause mortality. The primary safety end point is fatal and critical site bleeding according to the International Society on Thrombosis and Haemostasis definition. Enrollment began in August 2020 and is expected to enroll approximately 4,000 participants to yield the required number of end point events. Conclusions PREVENT-HD is a pragmatic trial evaluating the efficacy and safety of the direct oral anticoagulant rivaroxaban in the outpatient setting to reduce major venous and arterial thrombotic events, hospitalization, and mortality associated with COVID-19.

Objective Understanding cardiorenal pathophysiology in heart failure (HF) is of clinical importance. We sought to characterize the renal hemodynamic function and the transrenal gradient of the renin-angiotensin-aldosterone system (RAAS) markers in patients with HF and in controls without HF. Methods In this post hoc analysis, the glomerular filtration rate (GFRinulin), effective renal plasma flow (ERPFPAH) and transrenal gradients (arterial-renal vein) of angiotensin converting enzyme (ACE), aldosterone, and plasma renin activity (PRA) were measured in 47 patients with HF and in 24 controls. Gomez equations were used to derive afferent (RA) and efferent (RE) arteriolar resistances. Transrenal RAAS gradients were also collected in patients treated with intravenous dobutamine (HF, n = 11; non-HF, n = 11) or nitroprusside (HF, n = 18; non-HF, n = 5). Results The concentrations of PRA, aldosterone and ACE were higher in the renal vein vs the artery in patients with HF vs patients without HF (P Conclusions A larger transrenal RAAS marker gradient in patients with HF suggests a renal origin for neurohormonal activation associated with a vasoconstrictive renal profile.

The world population is increasing day by day, so demands for the resources like water and food also increases because these are the basic need for the people. People need the water for their daily uses. Even though your earth is covered mostly of water but it is not useful for humans to use. There is less amount of water that is useful. To save the water without wasting it. To reduce the water from wasting this is designed an automated switch that can automatically on and off the device when the tank is full of water, These reduce the overflow of water, it uses IOT (sensors)to make these processes automated. When the water level touches the sensor it turns off the water supplying pump. Since the electricity demand is very high, automatic water controllers save energy. To prevent over the labor of pumping machine and prevent it from getting worse. This water pump can be used for many purposes in the companies like it can be used as Liquid level detector and fuel detect the device, It also helps us to indicate the sudden increase of water during floods. A fully automated that is low cost and low maintenance with good compact and design which saves water and energy. This device is cost efficient.

Chest computed tomography (CT) imaging has become indispensable for staging and managing coronavirus disease 2019 (COVID-19), and current evaluation of anomalies/abnormalities associated with COVID-19 has been performed majorly by the visual score. The development of automated methods for quantifying COVID-19 abnormalities in these CT images is invaluable to clinicians. The hallmark of COVID-19 in chest CT images is the presence of ground-glass opacities in the lung region, which are tedious to segment manually. We propose anamorphic depth embedding-based lightweight CNN, called Anam-Net, to segment anomalies in COVID-19 chest CT images. The proposed Anam-Net has 7.8 times fewer parameters compared to the state-of-the-art UNet (or its variants), making it lightweight capable of providing inferences in mobile or resource constraint (point-of-care) platforms. The results from chest CT images (test cases) across different experiments showed that the proposed method could provide good Dice similarity scores for abnormal and normal regions in the lung. We have benchmarked Anam-Net with other state-of-the-art architectures, such as ENet, LEDNet, UNet++, SegNet, Attention UNet, and DeepLabV3+. The proposed Anam-Net was also deployed on embedded systems, such as Raspberry Pi 4, NVIDIA Jetson Xavier, and mobile-based Android application (CovSeg) embedded with Anam-Net to demonstrate its suitability for point-of-care platforms. The generated codes, models, and the mobile application are available for enthusiastic users at https://github.com/NaveenPaluru/Segmentation-COVID-19 .

We report the impact of SMS reminder on follow-up visit compliance among patients who are on treatment for diabetic macular edema. The randomization based on intervention did not show any difference between the two study groups.

Photoacoustic/Optoacoustic tomography aims to reconstruct maps of the initial pressure rise induced by the absorption of light pulses in tissue. This reconstruction is an ill-conditioned and under-determined problem, when the data acquisition protocol involves limited detection positions. The aim of the work is to develop an inversion method which integrates denoising procedure within the iterative model-based reconstruction to improve quantitative performance of optoacoustic imaging. Among the model-based schemes, total-variation (TV) constrained reconstruction scheme is a popular approach. In this work, a two-step approach was proposed for improving the TV constrained optoacoustic inversion by adding a non-local means based filtering step within each TV iteration. Compared to TV-based reconstruction, inclusion of this non-local means step resulted in signal-to-noise ratio improvement of 2.5 dB in the reconstructed optoacoustic images. Accepted version Phaneendra K. Yalavarthy acknowledges the DST-ICPS cluster funding (T-851) for the data science program. Part of the work is supported through IFTAS-CDS Collaborative Laboratory of Data Science and Engineering. Jaya Prakash acknowledges the IISc Startup Grant as well as DBT-IYBA Program.

Photoacoustic tomography (PAT) is an imaging technique that enables us to visualize vasculature networks at high resolution at depths much greater than optical microscopy.1,2 PAT can also resolve tissue chromophores such as oxyhemoglobin and deoxyhemoglobin, which allows estimation of tissue oxygentation levels.1,3 Accurate estimation of tissue oxygentation is very important in the fields of neuroimaging, cancer diagnostics, and critical care medicine.4,5 PAT involves collection of broadband acoustic waves generated by thermoelastic expansion of tissue upon absorption of light (illuminated at near-infrared wavelengths).6,7 PAT image reconstruction involves recovery of the acoustic source distribution from the detected broadband acoustic waves, which can be performed using analytical or model-based methods.8 Analytical methods are computationally less expensive compared to model-based image reconstruction.8,9 In contrary, model-based schemes are known to generate accurate images compared to analytical schemes, specifically in scenarios where irregular acquisition geometry is involved or limited data is acquired.9,10 Even with the model-based schemes, PAT inversion becomes difficult when the number of ultrasound detector positions is limited, and the situation gets aggravated due to the presence of noise in the data. More recently deep learning-based image postprocessing schemes have been developed for artifact removal and for limited data situations in PAT/microscopy;11–13 however, these schemes were trained on simulated data and generating large experimental data is very difficult. Segmentation approaches were proposed to delineate skin lining in mesoscopic photoacoustic images.14 Active contours-based image segmentation was used to obtain the PAT region of interest (ROI), the obtained ROI was then used to perform fluence correction to make PAT more quantitative.15,16 Different computational techniques have been reported in the literature to obtain vascular network in photoacoustic imaging. Vesselness filter has been proposed to enable accurate recovery of vasculature in PAT;17–19 however, questions have been raised on the accuracy of using the vesselness filter (due to generation of artificial vasculature).20 Probabilistic approach involving different steps such as smoothing and filtering the data, clustering, vessel-segmentation using clusters, and morphological filling was developed for segmenting vessels in photoacoustic images.21 More recently convolution neural network-based approaches were also developed for jointly performing the image reconstruction and segmentation.22 Further, deep learning-based approach was proposed for segmenting animal boundary using multi-modal photoacoustic and ultrasound data.23 Further, deep learning-based method has also been developed for animal brain imaging.24 Notably segmenting vasculature is very important in the context of diagnosis and surgical guidance, specifically for cardiovascular diseases.25,26 In this work, we developed a binary tomography approach wherein we assume the reconstruction distribution contains only two unknowns namely the background and the absorbers. The major contributions of this work include: (a) application of binary tomographic methods for photoacoustic tomographic imaging involving spherical wave propagation as opposed to straight line approximation applied in x-ray computed tomography; (b) showing the utility of binary tomographic methods for improving photoacoustic tomographic imaging of vasculature; and (c) establishing the binary tomographic method superiority in photoacoustic tomographic imaging for providing approximate priors to improve model-based image reconstruction. Binary tomography problem is solved based on a dual optimization approach with an auxiliary variable posed as a constrained optimization problem. We compared the binary tomography algorithm against standard backprojection approach and model-based reconstruction schemes such as Tikhonov regularization and sparsity-based regularization.27 The performance of these different algorithms was validated with in-silico data, physical phantom, and in-vivo brain vasculature imaging data.

Bacteria-mediated cancer-targeted therapy is a novel experimental strategy for the treatment of cancers. Bacteria can be engineered to overcome a major challenge of existing therapeutics by differentiating between malignant and healthy tissue. A prerequisite for further development and study of engineered bacteria is a suitable imaging concept which allows bacterial visualization in tissue and monitoring bacterial targeting and proliferation. Optoacoustics (OA) is an evolving technology allowing whole-tumor imaging and thereby direct observation of bacterial colonization in tumor regions. However, bacterial detection using OA is currently hampered by the lack of endogenous contrast or suitable transgene fluorescent labels. Here, we demonstrate improved visualization of cancer-targeting bacteria using OA imaging and E. coli engineered to express tyrosinase, which uses L-tyrosine as the substrate to produce the strong optoacoustic probe melanin in the tumor microenvironment. Tumors of animals injected with tyrosinase-expressing E. coli showed strong melanin signals, allowing to resolve bacterial growth in the tumor over time using multispectral OA tomography (MSOT). MSOT imaging of melanin accumulation in tumors was confirmed by melanin and E. coli staining. Our results demonstrate that using tyrosinase-expressing E. coli enables non-invasive, longitudinal monitoring of bacterial targeting and proliferation in cancer using MSOT.

Many organisms achieve locomotion through undulatory traveling-wave motions, both on land (e.g., snakes, caterpillars, and worms) and underwater (e.g., eels and flagellar single-celled organisms). Recently, caterpillar locomotion has been modeled using the theory of planar discrete elastic rods (PDER) and open-loop control. This work considers a planar discrete elastic rod model with closed-loop control over the intrinsic material parameters of length and curvature distributed along its length. We introduce local curvature feedback control laws to drive the shape of the robot to a desired traveling-wave reference trajectory, where the phase of the wave is determined via a central pattern generator or via distributed control with a circulant communication topology. Through numerical simulations utilizing simple models of fluid–body interaction forces we examine undulatory eel-like swimming gaits that give rise to net forward motion. These results show promise for the design of distributed feedback control laws in modular soft robotic systems.

The renin angiotensin aldosterone system (RAAS) is associated with renal disease and inflammation in a diabetes setting, however, little is known about the implicated mechanisms in individuals with long standing diabetes. Accordingly, our aim was to perform an observational study to quantify urinary excretion of inflammatory biomarkers in participants with long standing type 1 diabetes (T1D) (with and without diabetic kidney disease [DKD]) and controls, at baseline and in response to RAAS activation. GFRINULIN, ERPFPAH, and 42 urine inflammatory biomarkers were measured in 74 participants with T1D for ≥50 years (21 with DKD and 44 without DKD [DKD resistors]) and 73 healthy controls. Additionally, inflammatory biomarkers were measured before and after an angiotensin II infusion (ANGII, 1 ng∙kg−1∙min−1). Significantly lower urinary excretion of cytokines (IL-18, IL-1RA, IL-8), chemokines (MCP1, RANTES) and growth factors (TGF-α, PDGFAA, PDGFBB, VEGF-A) was observed in participants with T1D at baseline compared to controls. Urinary IL-6 was higher in DKD than in DKD resistors in an exploratory analysis unadjusted for multiple comparisons. In T1D only, lower GFRINULIN correlated with greater excretion of proinflammatory biomarkers (IL-18, IP-10, & RANTES), growth factors (PDGF-AA & VEGFAA), and chemokines (eotaxin & MCP-1). ANGII increased 31 of 42 inflammatory biomarkers in T1D vs controls (p

Introduction: Deviated nasal septum is one of the most common causes for the nasal obstruction. The objective of this study is to compare the surgical outcomes in patients undergoing conventional septoplasty and endoscopic septoplasty in the management of deviated nasal septum. Methods: Prospective comparative study was conducted on 60 patients who presented to the Department of ENT, College of Medical sciences, during a period of one year. The severity of the symptoms was subjectively assessed using NOSE score and objectively assessed using modified Gertner plate. Results: There was significant improvement in functional outcome like NOSE Score and area over the Gertner plate among patients who underwent endoscopic septoplasty. Significant difference in incidence of post-operative nasal synechae and haemorrhage was seen in conventional group compared to endoscopic group. Conclusions: Endoscopic surgery is an evolutionary step towards solving the problems related to deviated nasal septum. It is safe, effective and conservative, alternative to conventional septal surgery.

Processing of fish in aquaculture generates considerable amounts of by-products that remain underused and/or unexploited. We evaluated the nutritive content of fish by-products (head, gills, intestines, trimmings, bones, and skin) from meagre and gilthead sea bream fish species reared in Greece in order to estimate their nutritional value for future development of high added-value products. The proximate composition of the fish samples (total protein, total lipid, ash, moisture, and macro-element content) was determined using the Association of Official Analytical Chemists (AOAC) and International Organization for Standardization (ISO) official methods. The content of fatty acids was determined using capillary gas chromatography, and the protein profile was estimated employing scientific orbitrap mass spectrophotometer methodology. The nutrient composition of fish by-products presented fluctuations among the different by-products. Skin was the most significant protein source, trimmings and bones were high in calcium, and the head, intestines, and bones were a good source of lipids. The most abundant lipid acids found in by-products were oleic, palmitic, linoleic, and eicosenoic acids, whereas the most abundant proteins were adenosine triphosphate (ATP) synthase subunit epsilon, mitochondrial nicotinamide adenine dinucleotide (NADH) dehydrogenase, and mitochondrial cytochrome b-c1 complex subunit 8. These data suggest that by-products constitute valuable sources of nutrients and could therefore be exploited in accordance with the principles of a circular economy.

Background: Laryngopharyngeal reflux is retrograde flow of contents of the stomach to the larynx and the pharynx. The study aims to compare two regimens (proton pump inhibitor monotherapy versus triple therapy) on the outcome of Helicobactor pylori positive laryngopharyngeal reflux disease. Methods: The presence of laryngopharyngeal reflux was determined by reflux symptom index and reflux finding score. The presence of Helicobactor pylori in the tissue was confirmed by rapid urease test. All urease test negative laryngopharyngeal reflux patients were given a course of proton pump inhibitors and results were evaluated. All urease test positive patients were divided into two groups. One group was given a course of proton pump inhibitors and another group was given a course of triple therapy and the results were compared. Results: A total number of 704 laryngopharyngeal reflux patients were screened for urease test. Among them 138 patients (19.6 %) were urease test negative and were given proton pump inhibitor therapy. Improvement in both reflux finding score (average score 11.75) and reflux symptom index (average score 5.25) score was observed after 3 months with p-value

Using the same ultrasound detector, hybrid optoacoustic-ultrasound (OPUS) imaging provides concurrent scans of tissue slices or volumes and visualizes complementary sound- and light-based contrast at similar resolutions. In addition to the benefit of hybrid contrast, spatial co-registration enables images from one modality to be employed as prior information for improving an aspect of the performance of the other modality. We consider herein a handheld OPUS system and utilize structural information from ultrasound images to guide regional Laplacian regularization-based reconstruction of optoacoustic images. Using phantoms and data from OPUS scans of human radial and carotid arteries, we show that ultrasound-driven optoacoustic inversion reduces limited-view artefacts and improves image contrast. In phantoms, prior-integrated reconstruction leads to a 50 % higher contrast-to-noise ratio (CNR) of the image than standard reconstruction, and a 17 % higher structural similarity (SSIM) index. In clinical data, prior-integrated reconstruction detects deep-seated radial arteries with higher CNR than the standard method at three different depths. In this way, the prior-integrated method offers unique insights into atherosclerotic carotid plaques in humans (with p < 0.01 between patients and healthy volunteers), potentially paving the way for new abilities in vascular imaging and more generally in optoacoustic imaging.

In future industrial scenarios, Wireless Sensor Networks (WSN) are envisioned to support the traffic of Networked Control Systems (NCS). WirelessHART is a prevalent WSN protocol that uses the Time Slotted Channel Hopping (TSCH) medium access to cope with the delay and reliability requirements of NCS in the harsh industrial environment. In TSCH, time slots and frequencies can be scheduled by a network coordinator to provide Quality of Service (QoS). In contrast to previous works that consider the end-to-end delay requirement of a flow of packets, we focus on a finite sequence of time-critical packets. These packets may belong to a time-critical message whose latency could significantly impact the NCS. Given an end-to-end delay deadline, our objective is to minimize the Delay Violation Probability (DVP) for a finite sequence of packets by dynamically scheduling the time slots in each frame. This is a challenging task as DVP depends on the instantaneous state of the network and requires its transient analysis. In this work, we model the wireless NCS as a two-queue lossy wireless network and propose the first transient analysis of DVP for a finite sequence of time-critical packets. Noting that DVP cannot be directly used for dynamic resource allocation, we propose a heuristic algorithm by relating DVP with the network's throughput. The proposed heuristic maximizes the expected throughput, is computed by solving a finite-horizon Markov Decision Process (MDP), and can be implemented at the network coordinator. Using simulation we demonstrate that the MDP-based heuristic achieves lower DVP compared to the classical MaxWeight and Weighted-Fair Queuing.

Significance Shortly after its appearance on the drug market, it was found out that thalidomide was highly teratogenic. Although thalidomide passed the safety check in pregnant mice, it was not safe among humans due to different actions of thalidomide among various species. Due to inactivity of immunomodulatory drugs (IMiDs) in mice, preclinical safety checks and clinical investigation of IMiDs is impossible in murine models. Here, we developed a murine model to study IMiDs in vivo and began to unravel the complex IMiD mechanism of action. This model may also permit investigation of the main safety concerns. We further investigated IMiD activity toward different substrates targeted by small molecules. Overall, our study provides an important insight into the study of IMiDs., Immunomodulatory drugs (IMiDs), including thalidomide derivatives such as lenalidomide and pomalidomide, offer therapeutic benefit in several hematopoietic malignancies and autoimmune/inflammatory diseases. However, it is difficult to study the IMiD mechanism of action in murine disease models because murine cereblon (CRBN), the substrate receptor for IMiD action, is resistant to some of IMiDs therapeutic effects. To overcome this difficulty, we generated humanized cereblon (CRBNI391V) mice thereby providing an animal model to unravel complex mechanisms of action in a murine physiological setup. In our current study, we investigated the degradative effect toward IKZF1 and CK-1α, a target substrate of IMiDs. Unlike WT mice which were resistant to lenalidomide and pomalidomide, T lymphocytes from CRBNI391V mice responded with a higher degree of IKZF1 and CK-1α protein degradation. Furthermore, IMiDs resulted in an increase in IL-2 among CRBNI391V mice but not in the WT group. We have also tested a thalidomide derivative, FPFT-2216, which showed an inhibitory effect toward IKZF1 protein level. As opposed to pomalidomide, FPFT-2216 and lenalidomide degrades CK-1α. Additionally, we assessed the potential therapeutic effects of IMiDs in dextran sodium sulfate (DSS)-induced colitis. In both WT and humanized mice, lenalidomide showed a significant therapeutic effect in the DSS model of colitis, while the effect of pomalidomide was less pronounced. Thus, while IMiDs’ degradative effect on IKZF1 and CK-1α, and up-regulation of IL-2, is dependent on CRBN, the therapeutic benefit of IMiDs in a mouse model of inflammatory bowel disease occurs through a CRBN–IMiD binding region independent pathway.

This study demonstrates the development of vision based static hand gesture recognition system using web camera in real-time applications. The vision based static hand gesture recognition system is developed using the following steps: preprocessing, feature extraction and classification. The preprocessing stage consists of illumination compensation, segmentation, filtering, hand region detection and image resize. This study proposes a discrete wavelet transform (DWT) and Fisher ratio ( F -ratio) based feature extraction technique to classify the hand gestures in an uncontrolled environment. This method is not only robust towards distortion and gesture vocabulary, but also invariant to translation and rotation of hand gestures. A linear support vector machine is used as a classifier to recognise the hand gestures. The performance of the proposed method is evaluated on two standard public datasets and one indigenously developed complex background dataset for recognition of hand gestures. All above three datasets are developed based on American Sign Language (ASL) hand alphabets. The experimental result is evaluated in terms of mean accuracy. Two possible real-time applications are conducted, one is for interpretation of ASL sign alphabets and another is for image browsing.

Objective: Monitoring emerging vascular-targeted photodynamic therapy (VTP) and understanding the time-dynamics of treatment effects remains challenging. We interrogated whether handheld multispectral optoacoustic tomography (MSOT) could noninvasively monitor the effect of VTP using WST11, a vascular-acting photosensitizer, on tumor tissues over time using a renal cell cancer mouse model. We also investigated whether MSOT illumination can induce VTP, to implement a single-modality theranostic approach. Materials and Methods: Eight BalB/c mice were subcutaneously implanted with murine renal adenocarcinoma cells (RENCA) on the flank. Three weeks later VTP was performed (10 min continuous illumination at 753 nm following intravenous infusion) using WST11 or saline as control. Handheld MSOT images were collected prior to VTP administration and subsequently thereafter over the course of the first hour, at 24 and 48 h. Data collected were unmixed for blood oxygen saturation in tissue (SO 2 ) based on the spectral signatures of deoxy- and oxygenated hemoglobin. Changes in oxygen saturation over time, relative to baseline, were examined by paired t-test for statistical significance (p < 0.05). In-vivo findings were corroborated by histological analyses of the tumor tissue. Results: MSOT is shown to prominently resolve changes in oxygen saturation in tumors within the first 20 min post WST11-VTP treatment. Within the first hour post-treatment, SO 2 decreased by more than 60% over baseline (p < 0.05), whereas it remained unchanged (p > 0.1) in the sham-treated group. Moreover, unlike in the control group, SO 2 in treated tumors further decreased over the course of 24 to 48 h post-treatment, concomitant with the propagation of profound central tumor necrosis present in histological analysis. We further show that pulsed MSOT illumination can activate WST11 as efficiently as the continuous wave irradiation employed for treatment. Conclusion: Handheld MSOT non-invasively monitored WST11-VTP effects based on the SO 2 signal and detected blood saturation changes within the first 20 min post-treatment. MSOT may potentially serve as a means for both VTP induction and real-time VTP monitoring in a theranostic approach.

Simple Summary Alcohol consumption is a leading cause of lifestyle-induced morbidity and mortality worldwide. It is well-established that there is an association between alcohol consumption and an increased risk of colorectal cancer. Long-term alcohol consumption causes a spectrum of liver diseases, including steatosis, hepatitis, and liver cancer, and is detrimental to many other organs. In the body, alcohol can be metabolized to chemicals that exhibit biological activity, such as acetaldehyde. The intracellular accumulation of these compounds can result in suppression of antioxidant defense systems, and alterations in DNA. In addition, they can elicit changes at the tissue level, leading to reductions in nutrient absorption, inflammation, and impairment of the immune system. Together, these effects may increase the risk of cancer in a variety of organs. This review discusses the mechanisms by which alcohol may promote colorectal cancer. It is anticipated that a clearer understanding of the mechanisms by which alcohol induces cancer will facilitate the development of more effective therapeutic interventions. Abstract The etiology of colorectal cancer (CRC) is complex. Approximately, 10% of individuals with CRC have predisposing germline mutations that lead to familial cancer syndromes, whereas most CRC patients have sporadic cancer resulting from a combination of environmental and genetic risk factors. It has become increasingly clear that chronic alcohol consumption is associated with the development of sporadic CRC; however, the exact mechanisms by which alcohol contributes to colorectal carcinogenesis are largely unknown. Several proposed mechanisms from studies in CRC models suggest that alcohol metabolites and/or enzymes associated with alcohol metabolism alter cellular redox balance, cause DNA damage, and epigenetic dysregulation. In addition, alcohol metabolites can cause a dysbiotic colorectal microbiome and intestinal permeability, resulting in bacterial translocation, inflammation, and immunosuppression. All of these effects can increase the risk of developing CRC. This review aims to outline some of the most significant and recent findings on the mechanisms of alcohol in colorectal carcinogenesis. We examine the effect of alcohol on the generation of reactive oxygen species, the development of genotoxic stress, modulation of one-carbon metabolism, disruption of the microbiome, and immunosuppression.

This paper reviews the recent developments of Indian outward foreign direct investment (OFDI), which has been expanding rapidly, against the backdrop of liberalization and openness policies that have been instituted since the 1990s. The Indian OFDI landscape is changing with the participation of increasing numbers of Indian firms from a wide range of industries, the proactive role of State-owned enterprises in seeking overseas energy resources, and the growing distribution of investments, which are now geographically well spread across developed and developing regions. Indian firms are turning into global players with a global market focus and are undertaking overseas investments for international production, acquisition of foreign-created assets and foreign R&D activities.