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Background With recent advancements in bronchoscopic procedures, data on the best modality to sample peripheral pulmonary lesions (PPLs) is lacking, especially comparing bronchoscopy with computed tomography-guided transthoracic biopsy or needle aspiration (CT-TBNA). Methods We performed a meta-analysis, pairwise meta-analysis and network meta-analysis on studies reporting diagnostic yield and complications with the use of CT-TBNA, radial endobronchial ultrasound (rEBUS), virtual bronchoscopy (VB), electromagnetic navigation (EMN) or robot-assisted bronchoscopy (RAB) to sample PPLs. The primary outcome was diagnostic yield and the secondary outcome was complications. We estimated the relative risk ratios using a random-effects model and used the frequentist approach for the network meta-analysis. We performed extensive analysis to assess the heterogeneity including reporting bias, publication bias, subgroup and meta-regressional analysis. We assessed the quality of the studies using Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) and QUADAS-Comparative (QUADAS-C). Results We included 363 studies. The overall pooled diagnostic yield was 78.1%, the highest with CT-TBNA (88.9%), followed by RAB (84.8%) and the least with rEBUS (72%). In the pairwise meta-analysis, only rEBUS showed inferiority to CT-TBNA. The network meta-analysis ranked CT-TBNA as likely the most effective approach followed by VB, EMN and RAB, while rEBUS was the least effective, with a low-GRADE certainty. CT-TBNA had the highest rate of complications. Conclusion Although CT-TBNA is the most effective approach to sample PPLs, RAB has a comparable diagnostic yield with a lesser complication rate. Further prospective studies are needed comparing CT-TBNA and RAB.

Abstract Lung cancer is the deadliest cancer worldwide, therefore, early and prompt diagnosis is essential for better patient outcomes. It is known to have a high predilection for metastasis to the adrenal glands; however, two‐thirds of adrenal masses in patients with lung cancer will turn out to be benign, so timely detection is crucial. We present a case of a lung squamous cell carcinoma diagnosed by shape‐sensing robotic‐assisted bronchoscopy (ssRAB), negative mediastinal and hilar staging with endobronchial ultrasound (EBUS) and transbronchial needle aspiration (TBNA), and a pheochromocytoma diagnosed through endoscopic ultrasound with bronchoscope (EUS‐B) fine needle aspiration (FNA) all in the same endoscopic procedure.

Mobile Ad hoc Network (MANET) regarded to be a group of mobile nodes that can communicate with others in the absence of network infrastructure. MANET is at high risk due to its basic features, such as peer-to-peer (P2P) architecture; wireless shared medium, strictly constrained resources, extremely powerful network topology and open nodes for physical capture. Security is an essential service in all types of network communication. MANET must present security that raises human’s belief in MANET. This paper proposed the Four Stage Security Algorithm (FSSA) improve MANET security. First, secret keybased encryption and decryption provided in Stage 1. Then, public keybased encryption and private key based decryption provided in Stage 2. Followed by, signature generation and verification provided in Stage 3, at last, token-based access control provided in Stage 4. The experimental result shows the proposed FSSA algorithm provides robust security compared with other existing algorithms in MANET.

After an initial traumatic brain injury, it was hypothesized that systemic inflammation contributes to secondary brain injury. Our study aims to observe the effect of splenectomy on mortality in patients with concomitant splenic injury and head injury. A retrospective study which involved 243 cases, out of which 119 patients had splenectomy for grade 4,5 splenic injury or hemodynamic instability. We observed that the mortality was 67% in moderate head injury patients and 72.7% in severe head injury patients who underwent splenectomy. We conclude that the mortality in patients with concomitant splenic injury and head injury patients increases with increase in severity of head injury. [ABSTRACT FROM AUTHOR]

Mobile Ad hoc Network (MANET) regarded to be a group of mobile nodes that can communicate with others in the absence of network infrastructure. MANET is at high risk due to its basic features, such as peer-to-peer (P2P) architecture; wireless shared medium, strictly constrained resources, extremely powerful network topology and open nodes for physical capture. Security is an essential service in all types of network communication. MANET must present security that raises human's belief in MANET. This paper proposed the Four Stage Security Algorithm (FSSA) improve MANET security. First, secret keybased encryption and decryption provided in Stage 1. Then, public keybased encryption and private key based decryption provided in Stage 2. Followed by, signature generation and verification provided in Stage 3, at last, token-based access control provided in Stage 4. The experimental result shows the proposed FSSA algorithm provides robust security compared with other existing algorithms in MANET. [ABSTRACT FROM AUTHOR]

Abstract Background The Covid-19 pandemic necessitated the delivery of online higher education. Online learning is a novel experience for medical education in Sri Lanka. A novel approach to undergraduate surgical learning was taken up in an attempt to improve the interest amongst the students in clinical practice while maximizing the limited contact time. Method Online learning activity was designed involving medical students from all stages and multi consultant panel discussions. The discussions were designed to cover each topic from basic sciences to high-level clinical management in an attempt to stimulate the student interest in clinical medicine. Online meeting platform with free to use basic plan and a social media platform were used in combination to communicate with the students. The student feedback was periodically assessed for individual topics as well as for general outcome. Lickert scales and numeric scales were used to acquire student agreement on the desired learning outcomes. Results A total of 1047 student responses for 7 questionnaires were analysed. During a 6-week period, 24 surgical topics were discussed with 51 contact hours. Eighty-seven per cent definitely agreed (highest agreement) with the statement ‘students benefitted from the discussions’. Over 95% have either participated for all or most sessions. A majority of the respondents (83.4%) ‘definitely agreed’ that the discussions helped to improve their clinical sense. Of the total respondents, 79.3% definitely agreed that the discussions helped to build an interest in clinical medicine. Around 90% agreed that both exam-oriented and clinical practice-oriented topics were highly important and relevant. Most widely raised concerns were the poor Internet connectivity and limitation of access to the meeting platform. Conclusion Online teaching with a novel structure is feasible and effective in a resource-limited setting. Students agree that it could improve clinical interest while meeting the expected learning outcomes.

In this work, we propose a Semantically Contextual Generative Adversarial Network (SC-GAN) for video captioning. The semantic features extracted from a video are used in the discriminator to weigh the word embedding vectors. The weighted word embedding vectors along with the visual features are used to discriminate the ground truth descriptions from the descriptions generated by the generator. The manager in the generator uses the features from the discriminator to generate a goal vector for the worker. The worker is trained using: a goal based reward and a semantics based reward in generating the description. The semantics based reward ensures that the worker generates descriptions that incorporate the semantic features. The goal based reward calculated from discriminator features ensures the generation of descriptions similar to the ground truth descriptions. We have used MSVD and MSR-VTT datasets to demonstrate the effectiveness of the proposed approach to video captioning. [Display omitted] • Use of semantic context along with the word embedding vector in the discriminator. • Training the discriminator using both visual and semantic features for classification. • Training the manager to generate a goal based on discriminator features. • Training the generator using both the goal based reward and the semantics based reward. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we propose the large margin autoregressive (LMAR) model for classification of time series patterns. The parameters of the generative AR models for different classes are estimated using the margin of the boundaries of AR models as the optimization criterion. Models that use a mixture of AR (MAR) models are considered for representing the data that cannot be adequately represented using a single AR model for a class. Based on a mixture model representing each class, we propose the large margin mixture of AR (LMMAR) models. The proposed methods are applied on the simulated time series data, electrocardiogram data, speech data for E-set in English alphabet and electroencephalogram time series data. Performance of the proposed methods is compared with that of support vector machine (SVM) based classifier that uses AR coefficients based features. The proposed methods give a better classification performance compared to the SVM based classifier. Being generative models, the LMAR and LMMAR models provide a generative interpretation that enables utilization of the rejection option in the high risk classification tasks. The proposed methods can also be used for detection of novel time series data. [Copyright &y& Elsevier]

There are two paradigms for modelling the varying length temporal data namely, modelling the sequences of feature vectors as in the hidden Markov model-based approaches for speech recognition and modelling the sets of feature vectors as in the Gaussian mixture model (GMM)-based approaches for speech emotion recognition. In this paper, the methods using discrete hidden Markov models (DHMMs) in the kernel feature space and string kernel-based SVM classifier for classification of discretised representation of sequence of feature vectors obtained by clustering and vector quantisation in the kernel feature space are presented. The authors then present continuous density hidden Markov models (CDHMMs) in the explicit kernel feature space that use the continuous valued representation of features extracted from the temporal data. The methods for temporal pattern classification by mapping a varying length sequential pattern to a fixed-length sequential pattern and then using an SVM-based classifier for classification are also presented. The task of recognition of spoken letters in E-set, it is possible to build models that use a discretised representation and string kernel SVM based classification and obtain a classification performance better than that of models using the continuous valued representation is demonstrated. For modelling sets of vectors-based representation of temporal data, two approaches in a hybrid framework namely, the score vector-based approach and the segment modelling based approach are presented. In both approaches, a generative model-based method is used to obtain a fixed length pattern representation for a varying length temporal data and then a discriminative model is used for classification. These two approaches are studied for speech emotion recognition task. The segment modelling based approach gives a better performance than the score vector-based approach and the GMM-based classifiers for speech emotion recognition. [ABSTRACT FROM AUTHOR]

Abstract Objective Colorectal cancer (CRC) burden is increasing in the south Asian region due to the changing socio-economic landscape and population demographics. There is a lack of robust high quality data from this region in order to evaluate the disease pattern and comparison. Using generalized linear models assuming Poisson distribution and model fitting, authors describe the variation in the landscape of CRC burden along time since 1997 at a regional tertiary care center in Sri Lanka. Results Analyzing 679 patients, it is observed that both colon and rectal cancers have significantly increased over time (pre 2000—61, 2000 to 2004—178, 2005 to 2009—190, 2010 to 2014–250; P

Aim: The aim was to assess the seroprevalence of B. abortus and Leptospira hardjo in the cattle population of Bihar, this work was carried out. Materials and Methods: Randomly selected 450 cattle from nine districts of Bihar were serologically screened for antibodies against L. hardjo and B. abortus. DAS-ELISA for leptospira and AB-ELISA for brucella were carried out. Based on the results prevalence in each district and the state are reported herewith. Results: In this study, it was found that the seroprevalence of L. hardjo was 9.11% and that of B. abortus was 12.2% in Bihar. Indigenous cattle were found to be less susceptible to leptospirosis and brucellosis even though they accounted for 83.11% of the study population. Conclusion: Although there was no acute disease, antibodies detected against L. hardjo and B. abortus in the cattle population indicated the presence of chronic and subclinical infection, which could challenge the fertility of the animals.

Aim: The present study was carried out on cattle and buffalo farm of Indian Veterinary Research Institute, Izatnagar (Uttar Pradesh) to determine the effect of different shade materials on physiological performance in Vrindavani crossbred calves during the summer. Materials and Methods: Twenty-eight crossbred calves were divided into four groups viz. Thatch shading roof (T1), agro-net shading roof - 60 % light diffusion (T2), asbestos with canvas shading roof (T3) and well-grown tree (T4). The recording of macro and micro climate as well as the physiological parameters viz. rectal temperature and respiration rate were recorded at 9:00 AM and 2:00 PM for 2 consecutive days at every fortnight interval. Result: The microclimate viz. maximum and minimum, relative humidity, temperature humidity index and surface temperature of the roof was lower in T2 group in the summer season. The physiological responses viz. rectal temperature and respiration rate was significantly higher in T4. Conclusion: During the summer season both thatch and agro-net shade material helped in better relieving the summer stress.