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Narrow band imaging (NBI) is an emerging modality that enhances the accuracy of detection of head and neck malignancies by visualisation of aberrant neoangiogenesis in malignant tissue using narrow bandwidth light in blue and green spectrum. The purpose of this study was to assess the role of NBI in detecting recurrence in patients with Squamous cell carcinoma larynx and hypopharynx who have undergone Radiotherapy/Chemoradiotherapy (RT/CTRT). The aim of the study was to (a) determine the role of NBI in follow-up of patients with carcinoma of larynx and hypopharynx previously treated with radiotherapy or chemotherapy, (b) determine the role of NBI as the initial investigatory tool of choice in detecting local recurrence and compare with other modalities like fibreoptic laryngoscopy (FOL), Magnetic Resonance Imaging (MRI) and Positron Emission Tomography- Computed Tomography (PETCT). Prospective multicentric study at ENT departments of tertiary care centres in Delhi, Bangalore and Pune in India was conducted from Jan 2019 to Sep 2022. Thirty-four consecutive patients diagnosed as squamous cell carcinoma (SCC) larynx/hypopharynx who underwent chemo/radiotherapy were scheduled for NBI 12 weeks after completion of therapy with FOL and PETCT/MRI and followed up 03 monthly for 02 years. NBI/FOL/PETCT or MRI and Histopathological Examination (HPE) were compared. NBI was found to be 100% sensitive and 96% specific with a positive predictive value of 85% and negative predictive value of 100% respectively with a diagnostic accuracy of 97%. NBI along with FOL increases the sensitivity of detection of recurrence in patients of laryngeal/hypopharyngeal cancer post-chemo/radiotherapy. [ABSTRACT FROM AUTHOR]

Axial, flexure, and shear loads are the most common loads that could impact any structure. For instance, wall panels and columns majorly carry axial loads from the beam and slabs; they are also susceptible to flexure and shear loads from the wind or earthquake loads. Insulated concrete form (ICF) is a portable component of interconnected expanded polystyrene (EPS) panels filled with concrete. EPS remains in place and becomes part of the wall to enhance thermal resistance and structural performance. This paper focuses on an experiment that investigated the performance of ICF wall panels under axial compression and flexure. EPS with a higher density of 20 and 40 kg/m3 and a higher thickness of 50 and 100 mm was selected to prepare ICF wall panels for this experimental investigation. In addition, the plain concrete panel was cast for reference. Axial, flexure, and shear load-carrying capacity, load displacement, load–deflection profiles, crack propagation patterns, failure nature, and strain energy are analyzed and reported in this paper. It was observed that ICF panels were superior to plain concrete panels in terms of axial, flexure, and shear load-carrying capacity, failure nature, and absorbed strain energy. [ABSTRACT FROM AUTHOR]

Next generation firewall is taking major part to secure network environment in the industry. This device will monitor all the traffic which is coming inside the network or going outside of the network. With all these security devices attackers can still perform various kind of attacks on the network. DDoS attack is one of the hardest attack to identify which will send packets to the network and which will look like normal traffic but it will act as a DDoS traffic. In this paper we used binary decision tree, XGBoost and support vector machine to identify DDoS attack traffic pattern from the different features in the packet header. Data will be fetched from the packet header and among them standard deviation of the packet bytes and packet flows are the features considered. We have applied this data on the trained dataset. Algorithm will predict whether the traffic coming inside the network is trusted or not. Out of the three algorithms Binary Decision tree algorithm is giving 99 percentage of accuracy and will predict the data as fast as possible. Here priority is to filter DDos attacks of any security level in the line speed of the NIDS or any other appliances. This method of DDoS attack detection will add extra layer of security in the next generation firewall which will make firewall more robust. [ABSTRACT FROM AUTHOR]

To investigate the effects of combining bone marrow stimulation (BMS) with oral losartan to block transforming growth factor β1 (TGF-β1) on biomechanical repair strength in a rabbit chronic injury model. Forty rabbits were randomly allocated into 4 groups (10 in each group). The supraspinatus tendon was detached and left alone for 6 weeks to establish a rabbit chronic injury model and was then repaired in a surgical procedure using a transosseous, linked, crossing repair construct. The animals were divided into the following groups: control group (group C), surgical repair only; BMS group (group B), surgical repair with BMS of the tuberosity; losartan group (group L), surgical repair plus oral losartan (TGF-β1 blocker) for 8 weeks; and BMS-plus-losartan group (group BL), surgical repair plus BMS plus oral losartan for 8 weeks. At 8 weeks after repair, biomechanical and histologic evaluations were performed. The biomechanical testing results showed significantly higher ultimate load to failure in group BL than in group B (P =.029) but not compared with group C or group L. A 2 × 2 analysis-of-variance model found that the effect of losartan on ultimate load significantly depended on whether BMS was performed (interaction term F 1,28 = 5.78, P =.018). No difference was found between the other groups. No difference in stiffness was found between any groups. On histologic assessment, groups B, L, and BL showed improved tendon morphology and an organized type I collagen matrix with less type III collagen compared with group C. Group BL showed the most highly organized tendon matrix with more type I collagen and less type III collagen, which indicates less fibrosis. Similar results were found at the bone-tendon interface. Rotator cuff repair combined with oral losartan and BMS of the greater tuberosity showed improved pullout strength and a highly organized tendon matrix in this rabbit chronic injury model. Tendon healing or scarring is accompanied by the formation of fibrosis, which has been shown to result in compromised biomechanical properties, and is therefore a potential limiting factor in healing after rotator cuff repair. TGF-β1 expression has been shown to play an important role in the formation of fibrosis. Recent studies focusing on muscle healing and cartilage repair have found that the downregulation of TGF-β1 by losartan intake can reduce fibrosis and improve tissue regeneration in animal models. [ABSTRACT FROM AUTHOR]

The conventional PI-based speed controllers are susceptible to speed tracking error and limited load rejection capability. This paper presents the high-performance fractional-order PI speed controller (FOPI) for field oriented control of induction motor (FOC-IM) drives with enhanced disturbance rejection capability. The design of FOPI involves third-order voltage source inverter fed induction motor (VSI-IM) model identification, fitting it into the required phase margin and gain margin constraints and Oustaloups fractional element approximation. The identification algorithm using the hardware-in-loop system is provided. The non-linear integer order VSI-IM model improves the tracking and dynamic performance of the drive. The designed FOPI speed controller performance is compared with the literature's existing FOPI controller design methods. The experimental analysis found that, in terms of speed tracking, parameter variations, inertia variations, and disturbance rejection capabilities, the suggested controller is more effective and resilient than existing tuning approaches. • A novel identification method based on a chirp signal is proposed to obtain an accurate integer order plant model for VSI-fed IM. Compared to existing identification techniques, the proposed method is more practical and yields comparable accuracy. • A robust FOPI controller is developed to address various operating conditions such as load disturbances, inertia changes, and parameter variations. The proposed controller's speed control performance is evaluated in realistic field situations and found to be more robust than existing PI [ZN-method], FOPI (John et al., 2020), and FOPI (Sudheer and Aware, 2022) controllers. • The classical Oustaloup's approximation method suitable for practical hardware implementation. A design procedure is presented to implement the FOPI controller for the identified nonlinear VSI-fed IM IO plant model. This makes the proposed controller more feasible for real-world induction motor applications. • A comparative study has been carried out on the Hardware-In-Loop (HIL) system with existing tuning rules of the FOPI controller and Ziegler and Nicholas (ZN) PI controller tuning method to evaluate the proposed design method advantages. The proposed controller's error and control signals performance analysis, load disturbance rejection analysis, robustness against parameter and inertia variations are also demonstrated on the laboratory HIL prototype. [ABSTRACT FROM AUTHOR]

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Task Scheduling is an enormous challenge in cloud computing model as to map diverse tasks arises from various sources there should be an efficient scheduling mechanism which provision resources dynamically to users based on their corresponding requests. Ineffective scheduling leads to increase in makespan, energy consumption and violates SLA made between cloud user and service provider thereby quality of service will be degraded and trust on the cloud service provider will be degraded. Trust typically based on quality-of-service parameters such as Availability of virtual resources, Success rate of tasks, Turnaround efficiency of tasks which are included in SLA. In this paper, we designed a Multi objective trust aware scheduler which takes priority of tasks, VMs and schedule tasks to appropriate virtual resources while minimizing makespan, energy consumption. Whale Optimization algorithm used to model our task scheduler. Entire simulation carried out on Cloudsim. Workload used in this simulation is of both fabricated and real-time worklogs captured from HPC2N and NASA. Our proposed approach compared against existing metaheuristic approaches i.e., ACO, GA, PSO approaches. From Simulation results, we observed that there is a significant improvement in makespan, Energy consumption, total running time and trust parameters i.e., Availability, Success rate, Turnaround efficiency. [ABSTRACT FROM AUTHOR]

Task Scheduling is a tremendous challenge in cloud computing as tasks are varied in terms of their processing capacity and interdependent on each other i.e. workflows. Therefore, it is difficult to map workflows to suitable virtual resources in cloud environment. Many authors developed various schedulers, which addresses makespan and Quality of service metrics. Authors have not addressed parameters makespan in combination with migration time, which also affects performance of cloud computing environment. In this manuscript, a new workflow-scheduling mechanism is proposed, which takes priorities of tasks and schedules tasks effectively on to corresponding virtual resources. Whale optimization algorithm as the methodology to model this algorithm. Extensive simulations carried out on workflowsim simulator. It was evaluated aganist existing PSO, CS, ACO, GA algorithms. Finally, from simulation results, it was identified that makespan, migration time and energy consumption were minimized to a good extent. [ABSTRACT FROM AUTHOR]

VM packing is one of prodigious challenge in cloud computing as it depends on the incoming workload onto virtual resources. Workload in the cloud is highly dynamic and it is difficult to predict the upcoming tasks and place them properly onto an appropriate VM is a challenging task. While scheduling workload onto VMs it is important to pack them in an appropriate physical machine because there is a chance of wastage of virtual resources and which leads to high energy consumption. Therefore, it is necessary to pack VMs into an appropriate Physical machines based on utilization of CPU. Many of authors proposed various consolidation techniques to assess parameters makespan, energy consumption, Througput but still there is a research gap and we can minimize energy consumption based on utilization of CPU in proposed approach i.e. EVMPCSA. Consolidation of VMs and chososing of VM for migration onto a Physical host is based on utilization of CPU. Chaotic Social Spider algorithm is used as a methodology for VM packing mechanism. EVMPCSA uses cpu utilization as constraint and used Chaotic Social Spider algorithm as methodology in this work to solve VM packing problem. It is simulated on Cloudsim and evaluated aganist existing algorithms named as PSO, CS and ACO. When it is compared with PSO, CS and ACO makespan is greatly minimizes by 30.25, 23.5% and 17.31% respectively and energy consumption is minimized for PSO, CS and ACO by 27.6%, 24.78% and 10.09% respectively. [ABSTRACT FROM AUTHOR]

Advancements in data availability, including high frequency, near real-time multiparameter sensors, laboratory analysis, and in-situ and remote observations, have driven the development of machine learning (ML) models for applications such as toxic Harmful Algal Bloom (HABs) monitoring. However, the performance of ML predictions is influenced by both model uncertainties due to inherent model structures and errors associated with input dataset measurements. For example, measurement uncertainty arises from sample collection, sensor drift and laboratory analysis and sample handling errors. While impacts of model uncertainty are commonly addressed using probabilistic approaches, the effect of measurement uncertainty is less studied due to the limited availability of detailed measurement information. This study focuses on assessing the impact of measurement uncertainty on the ML prediction of chlorophyll-a concentration as an index of HABs in a mesotrophic lake. Using randomized subsets of input measured datasets that mimic possible chlorophyll-a concentration distributions, the study built 1000 Random Forest (RF) and Support Vector Regression (SVR) models. An independent measured dataset was used to validate the ensemble models, allowing for model performance evaluation and the creation of prediction intervals to measure the propagated uncertainty. Our findings showed that the model predictions have MAE that ranged between 0.16 μg/l and 5.19 μg/l, and RMSE ranging between 0.20 μg/l and 7.39 μg/l. The highest uncertainty coverage of 0.71 was observed in the RF model without chlorophyll-a sensor values as a predictor. The study found that the training dataset sizes due to the high frequency and manually sampled nature influence how much measurement uncertainty is covered. The results of this study demonstrate how well ML models can capture various HABs patterns when given diverse measurement variables. Our findings will give researchers insightful information on how to lessen the impact of measurement uncertainty when using ML models as decision-support tools for HABs management. [Display omitted] • ML prediction of HABs is affected by errors in measured water quality datasets. • Chlorophyll-a prediction as index of HABs was assessed using subsets of measured data. • Ensemble RF and SVR models were used to generate chlorophyll-a prediction intervals. • Variation in datasets influences the ability of HABs ML models to reduce measurement uncertainty effect. [ABSTRACT FROM AUTHOR]

As health care continues to evolve toward information transparency, an increasing number of patients have access to their medical records, including result reports that were not originally designed to be patient-facing. Previous studies have demonstrated that patients have poor understanding of medical terminology. However, patient comprehension of terminology specific to breast pathology reports has not been well studied. We assessed patient understanding of common medical terms found in breast pathology reports. A survey was administered electronically to patients scheduled for a screening mammogram within a multisite health care system. Participants were asked to objectively define and interpret 8 medical terms common to breast biopsy pathology reports. Patient perception of the utility of various educational tools was also assessed. Demographic information including health literacy, education level, previous cancer diagnosis, and primary language was collected. In total, 527 patients completed the survey. Terms including "malignant" and "benign" were the most correctly defined at 80% and 73%, respectively, whereas only 1% correctly defined "high grade." Factors including race/ethnicity and education level were correlated with more correct scores. Patients preferred educational tools that were specific to their diagnosis and available at the time they were reviewing their results. Patient comprehension of common medical terminology is poor. Potential assumptions of understanding based on patient factors including education, past medical history, and occupation are misinformed. With the newly mandated immediate release of information to patients, there is a pressing need to develop and integrate educational tools to support patients through all aspects of their care. [ABSTRACT FROM AUTHOR]

LULC maps are important thematic maps that provide a baseline for monitoring, assessing, and planning activities. This study incorporates spatio-temporal land use/ land cover (LULC) monitoring (1991–2021) and urban growth modeling (2021–2041) of Islamabad, Pakistan to deduce the changes in various LULC classes in the past and the future by incorporating realistic influential thematic layers and Artificial Neural Network-Cellular Automata (ANN-CA) machine learning algorithms. Three decades of Landsat satellite imagery were used to classify LULC maps using a random forest algorithm with high Kappa indexes ranging from 0.93 to 0.97. Simulations for 2011 and 2021 were done for well-calibration of the model with Kappa (>0.85) and spatial similarity (>75%) using the MOLUSCE plugin in QGIS software. Future predictions were done for the years 2031 and 2041 to analyze and study the future urban growth patterns. The satellite-based LULC maps during 1991–2021 exhibited a 142.4 km2 increase in net urban growth. This had detrimental effects on other classes: net decrease of forests by 38.4 km2 and waterbodies by 2.9 km2. The projected increase of urban areas in 2021–2041 will be 58.2 km2. Visual urban sprawl assessment on LULC maps was done to highlight the type of sprawls. Overall, it was sensed that the city's urbanization has been unplanned and erratic; leading to dire consequences on the environmental and urban systems. Therefore, the study necessitates better monitoring and better planning of urbanization by enforcing policies and necessary measures. [ABSTRACT FROM AUTHOR]

The Indian oil sardine (Sardinella longiceps, hereafter IOS) has a unique position in terms of its economic value. In the last decade, IOS has contributed about 15–20% to India's total marine fish landings. However, recently, a sharp decline has been observed in the annual landing of the resource, and it is on the verge of collapsing due to climatic and anthropogenic perturbations. Various researchers have observed a cyclic pattern of wide annual fluctuation for IOS. This review revealed a long history of IOS research dating back to 1924. To mine the information regarding past research on IOS, bibliometric analysis has been carried out to understand the growth of literature, research area focuses, and research requirements. This study highlights a noticeable shift in research focus regarding IOS. While earlier investigations centered primarily on the physiology and biochemical properties of sardine and sardine oil, contemporary research emphasizes oceanographic parameters in relation to the IOS life cycle. The evolution of research efforts now extends beyond taxonomic classification, encompassing ecological, fisheries, and environmental aspects. The study underscores an increasing awareness of the multifaceted challenges posed by climate change and anthropogenic activities, which have prompted a transition toward interdisciplinary research approaches aimed at IOS conservation. A notable gap identified in this study is the lack of comprehensive analyses on IOS habitat suitability, particularly under dynamic oceanographic conditions and environmental indicators critical for predicting IOS availability. Additionally, the study points to the potential application of advanced predictive modeling techniques, including regression-based models such as Generalized Linear Models (GLM) and Generalized Additive Models (GAM), as well as machine learning approaches like Boosted Regression Trees (BRT) and Random Forest (RF), to predict IOS abundance and distribution effectively. • Comprehensive assessment of the evolution and recent developments in Indian oil sardine (IOS) research • Highlights the dynamic nature of scientific inquiries surrounding IOS within the Indian context. • Progressive research efforts beyond fundamental taxonomic investigations expand to broader areas. • A growing recognition of the complex challenges posed by climate change and anthropogenic activities. • Need for IOS-specific fishing ground advisories to benefit fishermen and enhance the country's blue economy. • Proposes a habitat suitability-based predictive approach with a comprehensive framework. [ABSTRACT FROM AUTHOR]

Antimicrobial resistance is a major threat worldwide especially when it comes to nosocomial infections caused by ESKAPE bacteria. These pathogens exhibit a remarkable capacity to develop resistance to antimicrobial treatments. Probiotics are receiving considerable attention as potential antimicrobial therapies that are safe, and very effective. The objective of this study is to identify a possible treatment using antimicrobial peptides (AMPs) derived from probiotics. The primary objective is to comprehend the interplay between AMPs and the virulence proteins produced by ESKAPE pathogens that are linked with biofilms. We subjected the 12 peptides found in our earlier investigation to a comprehensive screening approach targeting the virulence proteins of ESKAPE infections by applying shape complementarity concepts and chose the docked complexes with the lowest energy score. The screening process involved assessing binding affinity and interactions with active residues using sophisticated computational tools such as HPEPDOCK, ClusPro 2.0, and AutoDock Vina. The AMP designated as plsa_07 was selected for subsequent examination and validated using molecular dynamic simulations. The in vitro assay demonstrated the antibacterial and antibiofilm properties of AMP plsa_07, with a minimal inhibitory concentration ranging from 1 to 4 μg/ml. The AMP plsa_07 demonstrated biofilm inhibition and eradication action against various bacteria, including E. faecium , S.aureus , K. pneumoniae , A. baumannii , and P. aeruginosa , with a range of effectiveness between 17% and 70%. This study establishes a fundamental foundation for clinical research on the possible application of therapeutic peptides produced from probiotics to address the increasing problem of drug-resistant infections. [ABSTRACT FROM AUTHOR]

Coconut water (CW) is anti-inflammatory, can manipulate the gut microbiome, and is a rich source of potassium. Gut microbiome modulation improves outcomes in ulcerative colitis (UC), and potassium possesses in vitro anti-inflammatory property. We evaluated the effect of CW as an adjunct therapy for patients with mild-moderate UC. This single-center, double-blind, placebo-controlled trial randomized patients with mild to moderate (Simple Clinical Colitis Activity Index [SCCAI]: 3–9) endoscopically active UC (Ulcerative Colitis Endoscopic Index of Severity [UCEIS] >1) in 1:1 ratio to CW + standard medical therapy (SMT) vs placebo + SMT. Four hundred mL of CW was administered for 8 weeks. Primary outcome measure was clinical remission (SCCAI ≤2), and secondary outcome measures were clinical response (SCCAI decline ≥3) and adverse events at 8 weeks. Microbiome was analyzed at baseline and 8 weeks. Of 121 patients screened, 95 were included for modified intention to treat analysis (CW, n = 49; placebo, n = 46) (mean age, 37.2 ± 11.2 years; males, 54.1%; disease duration, 48 months [interquartile range (IQR), 24–90 months]; pancolitis, 26.1%; SCCAI, 5 [IQR, 4–6]; UCEIS, 4 [IQR, 3–5]). Clinical response (57.1% vs 28.3%; odds ratio [OR], 3.4; 95% confidence interval [CI], 1.4–7.9; P =.01), remission (53.1% vs 28.3%; OR, 2.9; 95% CI, 1.2–6.7; P =.02), and proportion of patients with fecal calprotectin (FCP) <150 μg/g (30.6% vs 6.5%; OR, 6.3; 95% CI, 1.7–23.6; P =.003) were significantly higher in CW. The relative abundance of bacterial taxa that had a significant or trend towards negative correlation with SCCAI, UCEIS, or FCP increased at 8 weeks in CW, and this effect was independent of disease activity and dietary fiber. Adverse events were comparable, and no patient developed hyperkalemia. CW was more effective than placebo for induction of clinical remission in patients with mild to moderate UC. The trial was prospectively registered on Clinical Trials Registry of India (ctri.nic.in, Number: CTRI/2019/03/01827). [Display omitted] [ABSTRACT FROM AUTHOR]

We conducted a network meta-analysis to compare the efficacy of advanced therapies for achieving endoscopic outcomes in patients with moderate-to-severely active Crohn's disease. MEDLINE, Embase, and Cochrane CENTRAL databases were searched from inception to August 2, 2023 to identify phase II and III randomized controlled trials (RCTs) in adults (≥18 years) with moderate-to-severe Crohn's disease treated with tumor necrosis factor (TNF) antagonists, etrolizumab, vedolizumab, anti-interleukin (IL)12/23p40, anti-IL23p19, or Janus kinase-1 (JAK1) inhibitors, compared with placebo/active comparator, for induction and/or maintenance of remission and reported endoscopic outcomes. Primary outcome was endoscopic response after induction therapy, and endoscopic remission after maintenance therapy. We performed a random-effects network meta-analysis using a frequentist approach, and estimated relative risk (RRs), 95% confidence interval (CI) values, and P score for ranking agents. We used GRADE to ascertain certainty of evidence. A total of 20 RCTs (19 placebo-controlled and 1 head-to-head trial; 5592 patients) were included out of which 12 RCTs reported endoscopic outcomes for the induction phase, 5 reported for the maintenance phase, and 3 reported for both induction and maintenance phases. JAK1 inhibitors (RR, 3·49 [95% CI, 1·48–8·26]) and anti-IL23p19 (RR, 2·30 [95% CI, 1·02–5·18]) agents were more efficacious than etrolizumab (moderate certainty of evidence), and JAK1 inhibitors (RR, 2·34 [95% CI, 1·14–4·80]) were more efficacious than anti-IL12/23p40 agents for inducing endoscopic response (moderate certainty of evidence). JAK1 inhibitors and anti-IL23p19 ranked highest for induction of endoscopic response. There was paucity of RCTs of TNF antagonists reporting endoscopic outcomes with induction therapy. On network meta-analysis of 6 RCTs, all agents except vedolizumab (RR, 1.89 [95% CI, 0.61–5.92]) were effective in maintaining endoscopic remission compared with placebo. TNF antagonists, IL12/23p40, and JAK1 inhibitors were ranked highest. On network meta-analysis, JAK1 inhibitors and anti-IL23p19 agents may be the most effective among non-TNF-targeting advanced therapies for inducing endoscopic response. Future head-to-head trials will further inform positioning of different therapies for the management of Crohn's disease. [ABSTRACT FROM AUTHOR]

With increasing use of antibiotics, the development of antibiotic-resistant pathogens poses a serious threat to human health and the environment. Photocatalytic inactivation of these harmful pathogens is one of the novel and non-antibiotic treatments. The study fabricated Ag NPs decorated CdZnS QDs via a facile and biological co-precipitation method using L. camara plant extract as a green alternative to treat the toxic chemicals. The fabricated Ag/CdZnS QDs (NCs) were prepared for the efficient treatment of antibiotic-resistant pathogens as they raise a major global concern. The fabricated NCs were characterized with various characterization techniques to verify its physicochemical properties. The fabricated NCs have shown excellent photo-sterilization performance of 97 % against S. aureus. The excellent activity was attributed to the decoration of Ag NPs on CdZnS QDs as it helped in shortening band gap, improved visible light absorption ability, increased active sites, and boosted photogenerated electron/hole pairs stability. Radical trapping experiment and ESR analysis indicated the involvement of •OH and h+ in the photoinactivation of bacteria. The photo sterilization reaction of NCs was carried out under different environmental conditions, including light and dark conditions and different pH conditions. The experiment was carried out in sewage-treated water in order to test the real-time application, and the fabricated NCs achieved excellent 95.9 % photo-inactivation of S. aureus cells in sewage treated water and the Chemical Oxygen Demand (COD) of the system was increased after photo inactivation treatment. The fabricated NCs have also shown excellent reusable efficiency of 95% after six runs and the photostability and anti-corrosive nature of NCs were confirmed. The study provides an insight for the employment of photocatalysis for the sterilization of pathogens in real time aquatic environment across the globe. [Display omitted] [ABSTRACT FROM AUTHOR]

Background: Tracheobronchial (TB) tumors follow same pathological classification as lung neoplasms; however, some entities are known to favor airways. Distinction of pathological types is necessary for suggesting appropriate management strategy.Purpose: To evaluate utility of multidetector CT (MDCT) in differentiation of primary TB tumors; and assess validity of a scoring system based on imaging biomarkers to differentiate tumor types.Methods: MDCT features of 45 patients were analyzed for location, shape, calcification, attenuation, parenchymal changes, bronchoceles, extraluminal extension, lymphadenopathy, metastases. The two largest groups were compared with each other and remaining entities using Chi square tests. Six-point scoring system combining the differentiating features was devised and receiver operating characteristic curve analysis performed.Results: The most frequent type was neuroendocrine tumors (NET) (51.1%), followed by salivary gland tumors (SGT) (20%); including adenoid cystic carcinoma (ACC) (13.3%) and mucoepidermoid carcinoma (MEC) (6.7%). Comparing NETs with other entities as a whole, and independently with SGTs, significant difference was found among location (p = 0.05 and 0.001 respectively), shape (p < 0.001), calcification (p = 0.038 and 0.041 respectively), attenuation (p = 0.001 and 0.019 respectively), bronchoceles (p = 0.013 and 0.010 respectively). Significant difference was found among ACC and MEC in location (p = 0.01) and morphology (p < 0.001). On receiver operating characteristic (ROC) curve analysis of the score, areas under curve for NET, SGT and ACC were 0.913, 0.872 and 0.962 respectively. Suggested cut-off values were >3.5 for carcinoid (sensitivity 70%, specificity 91%), <2.5 for SGT (sensitivity 78%, specificity 75%), <1.5 for ACC (sensitivity 83%, specificity 92%).Conclusion: Use of a scoring system enables maximum diagnostic accuracy in MDCT differentiation of TB tumors. [ABSTRACT FROM AUTHOR]

Kimura disease is a rare chronic inflammatory disorder mostly reported in males in second to third decades from south-east Asia. Head and neck is the most commonly involved region. The usual presentation is painless facial swelling with salivary gland involvement and regional lymphadenopathy. The diagnosis can be suspected on imaging but needs to be proven on histopathology. We describe three histopathology proven cases of Kimura disease and emphasize the specific clinic-radiological findings which can help in early identification of the condition and its differentiation from other diseases with similar presentation. Gray scale Ultrasound, contrast-enhanced ultrasound, and contrast-enhanced Magnetic Resonance Imaging (CE-MRI) were done in all patients and Computed Tomography (CT) was done in one. The salient imaging features were ill-defined solid mass in the subcutaneous location of the facial region which was heteroechoic on Gray scale Ultrasound, heterogeneously hyperintense on T2W MRI and without much diffusion restriction. There was involvement of salivary glands with ipsilateral cervical adenopathy. The lesion showed avid contrast enhancement on contrast-enhanced ultrasound and CE-MRI. We also present a systematic literature review of clinico-radiological features in Kimura disease in the head and neck. The articles with histopathologically proven cases and satisfactory description of imaging findings were included and we have compared the findings in our cases with published literature. In addition, we have included examples of radiological mimics of this disease. Certain imaging findings are highly suggestive and can aid in early diagnosis of Kimura disease which helps in early initiation of treatment with better patient prognosis. [ABSTRACT FROM AUTHOR]

To analyze the epidemiology of hospitalized ocular injuries occurring in counter insurgency and proxy war environment in a forward area of northern India over a period of 13 years. Retrospective observational study of medical records was performed of 458 patients with ocular injuries primarily treated at zonal referral hospital of Indian Army between January 1992 and December 2004. A total of 559 eyes with ocular injuries were studied. The average age of the victims was 30 years. In 77% cases, injuries were sustained by army personnel and remaining by paramilitary forces. Of all cases, 86.5% cases were due to combat-related (militant action), of which 93.9% cases were caused by splinters from munitions. Among the eyes injured due to militant action, 60.36% were open globe injuries, 31.19% were closed globe injuries and 8.45% were isolated adnexal injuries. Among the eyes injured, 76.33% of the eyes with open globe injuries owing to militant action had perforating injuries, whereas in closed globe injuries, 47.74% eyes had corneal foreign body. Among eyes with open globe injuries, Corneo-scleral, scleral and corneal lacerations were seen in 45%, 28% and 27% eyes respectively. 15.75% of eyes with ocular injuries underwent eviscerations. The study reveals that splinter eye injuries from munitions were the most common cause of ocular morbidity in counter insurgency and proxy war. Implementation of use of protective glasses by the personnel deployed in such hostile environment and strict compliance of preventive measures would be effective in saving eyes and also medical and economic resources. [ABSTRACT FROM AUTHOR]

Clostridioides difficile infection is reported to occur after 2.2% of colorectal operations and is associated with longer length of hospital stay, greater overall healthcare cost, and significant morbidity and mortality. The incidence of Clostridioides difficile infection is greatest after elective stoma reversal. The purpose of this study was to evaluate the effect of prior Clostridioides difficile infection on patients undergoing stoma reversal. We hypothesized that patients with a history of Clostridioides difficile infection who underwent stoma reversal will be at an increased risk of postoperative Clostridioides difficile infection compared with patients without a history of Clostridioides difficile infection. This was an observational cohort study of patients undergoing elective stoma reversal surgery by colorectal surgeons at a single academic institution during a 10-year period. A prospectively maintained institutional database was queried to identify 454 patients who underwent stoma reversal surgery between January 1, 2007 and December 31, 2017. The primary outcomes were Clostridioides difficile infection after stoma reversal and time to Clostridioides difficile infection after bowel refunctionalization. Secondary outcomes included postoperative complications, length of hospital stay, discharge destination, and 30-day readmission rate. Univariate and multivariable logistic regression analyses were conducted to identify factors associated with Clostridioides difficile infection after stoma reversal. A total of 445 patients were identified who underwent elective stoma reversal, 42 of whom had a history of Clostridioides difficile infection before the stoma reversal. There were no significant differences in patient age, number of days diverted, or use of perioperative antibiotics between patients with and without a history of Clostridioides difficile infection. The incidence of postreversal Clostridioides difficile infection was 23.4% in patients with a history of Clostridioides difficile infection compared with 9.6% in patients with no Clostridioides difficile infection history (P =.004); however, time to Clostridioides difficile infection after reversal did not differ. History of Clostridioides difficile infection was also associated with greater risk of postoperative complications (26.2% vs 9.4%, P <.01), increased length of stay (3 vs 5 days postoperatively, P <.01), increased likelihood of discharge to a skilled-care facility (11.9% vs 6.2%, P <.01), and readmission (13.7 vs 31.0%, P <.01) within 30 days. In a multivariable logistic regression model, history of Clostridioides difficile infection, increased length of hospital stay, and discharge to a skilled facility were associated with increased risk of Clostridioides difficile infection after reversal, while proton pump inhibitors use was associated with decreased risk of Clostridioides difficile infection. Patients with a prior history of Clostridioides difficile infection who underwent stoma reversal exhibited higher rates of postoperative Clostridioides difficile infection and were at greater risk of postoperative complications, discharge to a skilled facility, and 30-day readmission. Furthermore, research into interventions aimed at improving outcomes in this unique, high-risk population is needed. [ABSTRACT FROM AUTHOR]

In this study, we focused on fabrication of porous ultra-thin ZnO nanosheet (PUNs)/CuCo 2 S 4 quantum dots (CCS QDs) for visible light-driven photodegradation of rifampicin (RIF) and Cr(VI) reduction. The morphology, structural, optical and textural properties of fabricated photocatalyst were critically analyzed with different analytical and spectroscopic techniques. An exceptionally high RIF degradation (99.97%) and maximum hexavalent Cr(VI) reduction (96.17%) under visible light was achieved at 10 wt% CCS QDs loaded ZnO, which is 213% and 517% greater than bare ZnO PUNs. This enhancement attributed to the improved visible light absorption, interfacial synergistic effect, and high surface-rich active sites. Extremely high generation of ●OH attributed to the spin-orbit coupling in ZnO PUNs@CCS QDs and the existence of oxygen vacancies. Besides, the ZnOPUNs@CCS QDs, forming Z-scheme heterojunctions, enhanced the separation of photogenerated charge carriers. We investigated the influencing factors such as pH, inorganic ions, catalyst dosage and drug dosage on the degradation process. More impressively, a stable performance of ZnO PUNs@CCS QDs obtained even after six consecutive degradation (85.9%) and Cr(VI) reduction (67.7%) cycles. Furthermore, the toxicity of intermediates produced during the photodegradation process were assessed using ECOSAR program. This work provides a new strategy for ZnO-based photocatalysis as a promising candidate for the treatment of various contaminants present in water bodies. [Display omitted] • ZnO nanosheet coupled CuCo 2 S 4 QDs fabricated via low-temperature reflux method. • Singly ionized oxygen vacancies in ZnO were induced with CuCo 2 S 4 QDs deposition. • Achieved high RIF degradation (99.97%) and Cr(VI) reduction (96.17%). • RIF photodegradation mechanism over CCS QDs@ZnO was proposed. • Reusability and structural stability of the CCS QDs@ZnO were investigated. [ABSTRACT FROM AUTHOR]

The present work is centred around the development of La 2 O 3 /(BiO) 2 CO 3 /Ag 3 PO 4 (LBA), a p-n-p nano-heterojunction to photodegrade doxycycline under visible light irradiation. Here, ultrasonication assisted co-precipitation method was employed to synthesize the photocatalyst. The photocatalyst was characterized using different analysis such as SEM, TEM, elemental mapping, XRD, XPS, FTIR, Raman, BET, DRS, PL and EIS which confirmed the successful fabrication of LBA and their excellent ability to refrain the e−/h+ recombination owing to the construction of the heterojunction. LBA was found to degrade DOX by 91.75 % with the high mineralization of 87.23%. The impact of the reaction parameters influencing the photodegradation process including the concentration of the NCs and DOX, pH and the influence of the commonly present anions were studied. The stability and reusability of the LBA was assessed through subjecting it to four cycles of photodegradation of DOX. In addition, the recovered LBA was characterized through XPS and XRD analysis to confirm the particles stability and reusability. The active participation of the photogenerated charges and the reactive oxygen species were identified through the scavenging assay and ESR analysis. Further, GC-MS/MS analysis was performed to put forward a plausible photodegradation pathway. The toxicity of the end products as well as the intermediates was predicted through ECOSAR software. [Display omitted] • LBA nano-hetrojunctionwas prepared via ultrasonication assisted co-precipitation method. • The photodegradation of doxycycline was found to be 91.75 %. • •OH and h+ were primarily involved in photocatalytic reactions. • The LBA nano-hetrojunction exhibited excellent photostability and reusability. • The degradation pathway was elucidated by GC-MS/MS analysis. [ABSTRACT FROM AUTHOR]

Most bacterial disinfectants contain high levels of extremely toxic and environmental hazardous chemicals, which pose a significant threat to the ecosystem. Semiconductor photocatalysis exhibits attractive prospects as an emerging greener technology for waste water disinfection. However, the fast recombination of charge carriers limits its practical application. Herein, self-assembled polymeric feather-like g-C 3 N 4 (GCN) nanosheets modified with ferromagnetic CuFe 2 O 4 (CFO) nanospheres were successfully applied as a reusable visible light photocatalytic disinfectant. As expected, the g-C 3 N 4 /CuFe 2 O 4 (GCF) nanohybrid displayed superior photocatalytic inactivation efficiency of 0.157log within 120 min towards Escherichia coli DH5α (E. coli) compared with pristine GCN and CFO. The characterization results revealed the synergistic heterostructure interfaces, high surface area, and the transformative self-assembly of GCN to feather-like structure providing a rich active site for improved charge separation efficiency, and wide spectral response, therefore the superior performance of GCF. The radical trapping assay proclaimed that both O 2 •- and •OH radical played major role in the photocatalytic inactivation among the other reactive oxygen species (ROS). Furthermore, the chemical oxygen demand (COD), protein estimation, and DNA estimation assay results validated the cell damage caused by the photocatalyst. Besides that, GCN showed applicability in real-time wastewater samples with improved efficiency than in the saline solution. The excellent magnetic characteristics facilitated the recycling of the catalyst with insignificant leaching, magnetic induction, and distinguished separation. The results of this work signify the well-designed GCF as a high-performance and reusable photocatalyst for real-world pathogenic bacterial disinfection operations. [Display omitted] • Self-assembled g-C 3 N 4 nanosheets on CuFe 2 O 4 nanospheres was fabricated via reflux assisted method. • GCN/CF exhibits superior photocatalytic inactivation of E. coli. • Disinfection study in wastewater sample verified the potential environmental application. • Both.●OH and O 2 •- radicals played the major role in the photocatalytic inactivation of E. coli. • The cell wall damage of E. coli was verified by SEM imaging. [ABSTRACT FROM AUTHOR]

On March 11, 2020, the World Health Organization declared a coronavirus disease 2019 (COVID-19) pandemic. Health care systems worldwide should be prepared for an unusually high volume of patients in the next few weeks to months. Even the most efficient radiology department will undergo tremendous stress when victims of a mass casualty flood the emergency department and in turn the radiology department. A significant increase is expected in the number of imaging studies ordered for the initial diagnosis and treatment follow-up of cases of COVID-19. Here, we highlight recommendations for developing and implementing a mass casualty incident (MCI) plan for a viral outbreak, such as the current COVID-19 infection. The MCI plan consists of several steps, including preparation, mobilization of resources, imaging chain, adjusting imaging protocols, and education, such as MCI plan simulation and in-service training. Having an MCI plan in place for a viral outbreak will protect patients and staff and ultimately decrease virus transmission. The use of simulations will help identify throughput and logistical issues. [ABSTRACT FROM AUTHOR]

Adrenocortical carcinoma is an aggressive malignancy with a low but variable overall survival rate. The role of in adrenocortical carcinoma is poorly understood. Thus, in this study we performed long noncoding RNA expression profiling in adrenocortical carcinomas, adrenocortical adenomas, and normal adrenal cortex. Long noncoding RNA expression profile using Human LncRNA/mRNA Expression Microarray V3.0 (Arraystar, Inc, Rockville, MD) was analyzed in samples from 11 adrenocortical adenomas, 9 adrenocortical carcinomas, and 5 normal adrenal cortex. Differentially expressed long noncoding RNAs were validated using TaqMan, real-time quantitative polymerase chain reaction with additional samples. The dataset from the adrenocortical carcinoma Cancer Genome Atlas Programproject was used to evaluate the prognostic utility of long noncoding RNAs. Unsupervised hierarchical clustering showed distinct clustering of adrenocortical carcinoma samples compared with normal adrenal cortex and adrenocortical adenoma samples by long noncoding RNA expression profiles. A total of 874 long noncoding RNAs were differentially expressed between adrenocortical carcinoma and normal adrenal cortex. LINC00271 expression level was associated with prognosis, patients with low LINC00271 expression survived a shorter time than patients with high LINC00271 expression. Low LINC00271 expression was positively associated with WNT signaling, cell cycle, and chromosome segregation pathways. Adrenocortical carcinoma has a distinct long noncoding RNA expression profile. LINC00271 is downregulated in adrenocortical carcinoma and appears to be involved in biologic pathways commonly dysregulated in adrenocortical carcinoma. [ABSTRACT FROM AUTHOR]

• Over 90 % of carpets are landfilled or incinerated at the end of their lives, comprising 3.5 % of the United States landfill waste. • Compression molding of whole carpets with small amounts of recycled resin will help solve the carpet waste problem. • Composites' design of experiments (DOE) results exhibited remarkable mechanical properties suitable for structural applications. • These composites can recover embodied energy, reduce the waste going into the environment, and reduce carpet landfilling. • Effects of minimal amounts of low-cost additives, compatibilizers and carpet soil need to be studied. Carpets significantly contribute to landfills, forming 3.5 % of the U.S. landfill waste, with less than 10 % being recycled. This study uses intact carpets to create functional composites as a potential solution to this problem. This research introduces a feasible method for manufacturing recycled composites through compression molding of post-consumer polypropylene (PP) carpet and recycled high-density polyethylene (HDPE) resin. Optimal molding temperature and composition ranges were identified using a comprehensive three-level full factorial design of experiments (3D-DOE), resulting in impressive flexural strength (>40 MPa) and flexural modulus (>2000 MPa). Reproducibility tests of 10 specimens yielded 41.8 ± 2.0 MPa flexural strength and 2200 ± 150 MPa flexural modulus. These composites, containing up to 70 % potentially-landfilled carpet and 30 % recycled resin, surpassed the performance for the strength of commercialized thermoplastics, making them suitable for structural applications. The findings present a promising approach to address carpet landfilling while reducing reliance on additives. [Display omitted] [ABSTRACT FROM AUTHOR]

• A new census data-based approach is proposed to estimate industrial water demand. • The model estimates the State-level industrial water demand at the monthly time scale. • The principal components are used as effective predictors to reduce input variables. Rising population and industrialisation aided by technological advancements have resulted in increased industrial water demand in India. Industrial water demand accounts for about 8–10 % of the total water demand in the country. Although some national and international organisations report industrial water demand, there is a wide variation in data due to the scarcity of the reliable data and inconsistencies in the methods adopted for quantification. Rather than using these estimates, the census-based statistical data could provide better figures. Therefore, the present study aims to quantify industrial water demand by compiling census-based statistical data collected from various Governmental agencies in India. Based on census datasets collected at National and State Governmental institutions, this study develops a new model to estimate industrial water demand. Industrial water demand is estimated in this study at State and monthly scale from 1991 to 2010. The study models industrial water demand as a function of industrial production data, industrial survey components, and economic/technological development indicators. Principal component analysis is employed to reduce these large number of input variables to a smaller number of latent variables, which account for the variance in the input variables. The model results are cross-validated with industrial water demand data obtained from National Commission on Integrated Water Resources Development (NCIWRD). Country-level estimates are disaggregated to State-level water demand estimates based on number of industrial units in each State. These State-level results are verified against an independent census dataset on industrial water demand collected from State Governmental organisations. It is found that industrial water demand increased at a rate of 2% per annum during the period of analysis, which exceeds the increase rate of agricultural and domestic water demands during the same period. [ABSTRACT FROM AUTHOR]