Template Database Research Articles

RT-EQcorrscan: Near-Real-Time Matched-Filtering for Rapid Development of Dense Earthquake Catalogs

Abstract Matched-filtering (template-matching) is an effective method for detecting clustered seismicity such as aftershocks, low-frequency earthquakes, repeating earthquakes, and tectonic and volcanic swarms. Several groups have developed efficient codes implementing matched-filter methods and demonstrated that earthquake catalogs can be substantially expanded using these methods. Here, we present a near-real-time implementation of the matched-filter method, designed to be used in response to ongoing seismicity. Its near-real-time capabilities enable dense catalogs of seismicity to be constructed rapidly, providing input into real-time seismic hazard and forecasting and thus informing the earthquake response and scientific understanding. Such rapid development of detailed earthquake catalogs has similar application in volcano monitoring, monitoring of induced seismicity, and for online construction of slow-earthquake catalogs. Our software package, RT-EQcorrscan, is an open-source extension of the EQcorrscan Python package. The package can either be deployed to apply near-real-time matched-filters to a specific geographic region or sequence on a continuous basis, or configured to respond to large earthquakes or high-rate sequences by automatically starting a matched-filter run in response to these events. The system relies on, and maintains, a constantly updated template database of waveforms and event metadata, which is then queried for the specific target region. This template database can be updated while the matched-filter is running to enable the set of templates to expand in response to previous results. Multiple region-specific matched-filters can be run in parallel, allowing the system to respond to distinct trigger events.

Boosting the accuracy of protein secondary structure prediction through nearest neighbor search and method hybridization

Motivation Protein secondary structure prediction is a fundamental precursor to many bioinformatics tasks. Nearly all state-of-the-art tools when computing their secondary structure prediction do not explicitly leverage the vast number of proteins whose structure is known. Leveraging this additional information in a so-called template-based method has the potential to significantly boost prediction accuracy. Method We present a new hybrid approach to secondary structure prediction that gains the advantages of both template- and non-template-based methods. Our core template-based method is an algorithmic approach that uses metric-space nearest neighbor search over a template database of fixed-length amino acid words to determine estimated class-membership probabilities for each residue in the protein. These probabilities are then input to a dynamic programming algorithm that finds a physically valid maximum-likelihood prediction for the entire protein. Our hybrid approach exploits a novel accuracy estimator for our core method, which estimates the unknown true accuracy of its prediction, to discern when to switch between template- and non-template-based methods. Results On challenging CASP benchmarks, the resulting hybrid approach boosts the state-of-the-art Q8 accuracy by more than 2-10%, and Q3 accuracy by more than 1-3%, yielding the most accurate method currently available for both 3- and 8-state secondary structure prediction. Availability and implementation A preliminary implementation in a new tool we call Nnessy is available free for non-commercial use at http://nnessy.cs.arizona.edu.

Boosting the accuracy of protein secondary structure prediction through nearest neighbor search and method hybridization.

MotivationProtein secondary structure prediction is a fundamental precursor to many bioinformatics tasks. Nearly all state-of-the-art tools when computing their secondary structure prediction do not explicitly leverage the vast number of proteins whose structure is known. Leveraging this additional information in a so-called template-based method has the potential to significantly boost prediction accuracy.MethodWe present a new hybrid approach to secondary structure prediction that gains the advantages of both template- and non-template-based methods. Our core template-based method is an algorithmic approach that uses metric-space nearest neighbor search over a template database of fixed-length amino acid words to determine estimated class-membership probabilities for each residue in the protein. These probabilities are then input to a dynamic programming algorithm that finds a physically valid maximum-likelihood prediction for the entire protein. Our hybrid approach exploits a novel accuracy estimator for our core method, which estimates the unknown true accuracy of its prediction, to discern when to switch between template- and non-template-based methods.ResultsOn challenging CASP benchmarks, the resulting hybrid approach boosts the state-of-the-art Q8 accuracy by more than 2–10%, and Q3 accuracy by more than 1–3%, yielding the most accurate method currently available for both 3- and 8-state secondary structure prediction.Availability and implementationA preliminary implementation in a new tool we call Nnessy is available free for non-commercial use at http://nnessy.cs.arizona.edu.

Minor surgery in general practice in Ireland- a report of workload and safety

BackgroundThe provision of minor surgical services is an established part of the task profile of general practitioners (GPs) in many countries in Europe and elsewhere. This study aimed to collect data on the clinical process and outcomes for specified minor surgical procedures undertaken in Irish general practice by GPs experienced in minor surgery in order to document the scope and safety of minor surgery being undertaken.MethodsOver a six-month period, 24 GPs in 20 practices recorded data on a pre-determined list of procedures undertaken in adults (aged 18 and older); procedures for ingrown toenails were also recorded for those aged 12–18 years. Clinical data were rendered fully anonymous by the participating GPs, entered onto the Excel database template and returned to the project team monthly.ResultsOn average, each practice undertook 212 procedures in a six-month period. The four most frequent procedures include two relatively non-invasive procedures (cryosurgical ablation of skin lesions and aspiration and/or injection of joints) and two more invasive procedures (full thickness excision of skin lesion and shave, punch or incisional biopsy). Overall, 83.8% of relevant specimens were submitted for histology. Combining benign and malignant cases, there was an overall 87% clinical and histological concordance; 85% of malignancies were suspected clinically. A complication was recorded in 0.9% after 1 month.ConclusionsIrish GPs with experience in minor surgery can provide a range of surgical services in the community safely.

Camrelizumab in the treatment of patients with advanced lung cancer: A multicenter, prospective, cohort study.

e21650 Background: Camrelizumab is a humanized PD-1 monoclonal antibody. The efficacy of camrelizumab monotherapy or combined with chemotherapy in the treatment of advanced NSCLC had been demonstrated with promising anti-tumor activity in previous studies. However, in the real-world clinical practice, the activity of camrelizumab in patients with advanced lung cancer is poorly characterised. We sought to analyse the antitumour activity and toxicity of camrelizumab in advanced lung cancer to explore benefit subgroups and optimal treatments. Methods: This is a multicentre, prospective cohort study of advanced lung cancer in Jiangsu province, China. Eligibility required patients with histologically confirmed advanced lung cancer who couldreceive treatment regimen based on camrelizumab. No other restrictive inclusion criteria were applied. Data were captured with electronic uniform database templates to ensure consistent data collection. Primary endpoint is progression-free survival (PFS), Secondary endpoints are adverse events (AE), objective response rate (ORR), disease control rate (DCR), and overall survival (OS). Results: 97 pts with advanced lung cancer were enrolled from August 7, 2019 to December 20, 2019. Median age was 64, male 82.5%, adenocarcinoma 50.5%, squamous carcinoma 29.9%, SCLC 14.4%. 30.9% were treated as first-line therapy, 24.7% were second-line treatment, 44.4% were third-line and above treatment. Treatment regimens included camrelizumab monotherapy 13.4%, combination chemotherapy 52.6%, combination anti-angiogenic therapy 24.7%. 52 pts were accessable for efficacy analysis. 11 (21%), 37(71%), and 6(8%) patients showed partial response (PR), stable disease (SD), and progression disease (PD), respectively. The ORR, DCR was 21.2%, 92.3%. 72 pts had experienced the safety assessment. This was an early stage of data analysis, PFS has not yet reached. Major AE was reactive cutaneous capillary hyperplasia (RCCEP) (20/72), no Grade≥3 RCCEP occurred. Other common AEs were eutrophil count decreased (14/72), nausea (12/72), fatigue (11/72), white blood cell decreased (10/72). No treatment-related deaths occurred. Conclusions: This Real-world research showed current treatment status of advanced lung cancer and provides preliminary evidence for camrelizumab treating with advanced lung cancer, and we expect follow-up data to provide more clues. Clinical trial information: ChiCTR1900026089.

CRiSP: accurate structure prediction of disulfide-rich peptides with cystine-specific sequence alignment and machine learning.

High-throughput sequencing discovers many naturally occurring disulfide-rich peptides or cystine-rich peptides (CRPs) with diversified bioactivities. However, their structure information, which is very important to peptide drug discovery, is still very limited. We have developed a CRP-specific structure prediction method called Cystine-Rich peptide Structure Prediction (CRiSP), based on a customized template database with cystine-specific sequence alignment and three machine-learning predictors. The modeling accuracy is significantly better than several popular general-purpose structure modeling methods, and our CRiSP can provide useful model quality estimations. The CRiSP server is freely available on the website at http://wulab.com.cn/CRISP. wuyd@pkusz.edu.cn or jiangfan@pku.edu.cn. Supplementary data are available at Bioinformatics online.

Attendance Monitoring Using Face Recognition with Message Alert

Face recognition technology is the least intrusive and fastest bio-metric technology invented so for. The accurate recognition of a person is the sole aim of a face recognition system and this identification may be used for further processing. The methods to exploit this physical feature have seen a great change since the advent of image processing techniques. Here, the camera detects and recognizes the persons while them entering the door and then sends their personal information to the host to generate a 3D Facial Model. The proposed system will update the attendance once the students face is match with the template database. This paper describes the working of the face recognition system that will be deployed as an Automated Attendance System in a classroom environment.

Iot Based End to End Solutions for Industrial Surveillance using Raspberry Pi

The proposed system introduces an industrial surveillance system providing a secure data flow with privacy & authenticity in the domain of Automation. This system makes use of Raspberry Pi to provide automation in a workplace environment, utilizing the benefits of IoT. It is used in an industrial scenario for authenticating and monitoring entry and exit of employees, automatic turning ON/OFF of lights and temperature control. All operations are controlled by Raspberry Pi which also acts as the server. Programming languages used are Python & C. Entry and exit of employees are authenticated using Finger Print Scanner. All the information of an employee along with finger print template is already enrolled in database. So every time, the input from fingerprint sensor is authenticated with templates in database to provide access and store time logs. Similarly inputs from temperature sensor and LDR are accessed and sent to server for uninterrupted monitoring and safety services. MQTT protocol is used as the communication protocol for transferring data to IOT server.

Template Based Pose and Illumination Invariant Face Recognition

This article presents a method “Template based pose and illumination invariant face recognition”. We know that pose and Illumination are important variants where we cannot find proper face images for a given query image. As per the literature, previous methods are also not accurately calculating the pose and Illumination variants of a person face image. So we concentrated on pose and Illumination. Our System firstly calculates the face inclination or the pose of the head of a person with various mathematical methods. Then Our System removes the Illumination from the image using a Gabor phase based illumination invariant extraction strategy. In this strategy, the system normalizes changing light on face images, which can decrease the impact of fluctuating Illumination somewhat. Furthermore, a lot of 2D genuine Gabor wavelet with various orientations is utilized for image change, and numerous Gabor coefficients are consolidated into one entire in thinking about spectrum and phase. Finally, the light invariant is acquired by separating the phase feature from the consolidated coefficients. Then after that, the obtained Pose and illumination invariant images are convolved with Gabor filters to obtain Gabor images. Then templates will be extracted from these Gabor images and one template average is generated. Then similarity measure will be performed between query image template average and database images template averages. Finally the most similar images will be displayed to the user. Exploratory results on PubFig database, Yale B and CMU PIE face databases show that our technique got a critical improvement over other related strategies for face recognition under enormous pose and light variation conditions.

A Novel Image Compression Based Method for Multispectral Fingerprint Biometric System

Abstract A biometric system is a pattern recognition tool for efficient human recognition based upon biological and behavioral traits. The fingerprint is one of the most promising and widely used biometric with almost 48% market share. The images for fingerprint systems may be captured in multispectral bands which needs special techniques for efficient working of the overall system. Multispectral Fingerprint biometric system has recently become quite popular as it provides high security and recognition. Multispectral images are of high dimensions, the high dimensionality of multispectral data requires robust compression technique. In this Paper a novel approach using Huffman coding and wavelet decomposition for multispectral fingerprint biometric system has been presented. The technique promises high security to templates in database as well as compressed templates. The compressed templates results in faster matching during authentication phase of the fingerprint biometric system. Moreover, the presented technique results in low revocability but high security to mitigate the effect of masquerade attacks.

Principles of Automated Data Processing of Mandelstam – Brillouin Backscatter Characteristics for Evaluating the State of Optical Fibers

For early diagnostics of the state of optical fibers (OFs) located in the laid optical cables (OCs), it is necessary to identify potentially unreliable sections of the S in advance, which over time can lead to the destruction of fibers and disrupt the normal operation of fiber-optic communication lines (FOCLs). For diagnosis and forecasting of the state of the OFs that are in the laid OCs, Brillouin optical pulse reflectometers (BOTDR) are used, in which the back-reflected signal of the spontaneous Mandelstam – Brillouin scattering (MBS) is analyzed. In the process of obtaining a trace of the distribution of the Mandelshtam – Brillouin backscatter spectrum (MBBS) along the OF, the Brillouin frequency shift (BFS) is determined. After this, a graphs of the distribution of strain along the light-guide is constructed. A classification of varieties of single-mode optical fibers based on analysis of the MBS characteristics is discussed in this paper. It is shown how by the characteristics of the frequency profiles of the MBBS, one can determine the type of fiber and also evaluate the change in the strain and BFS. The MBBS profile come under influence by the functional dependence of the distribution of acoustic modes in the OF, their longitudinal direction. Both of them depend on the structure of the OF layers, as well as on the types and concentration of various alloying additives of the core OF. For single-mode OFs, when describing the MBS process, it is necessary to take into account the spatial distribution and interaction of the main optical and several acoustic modes. After uploading the data file from the BOTDR, it is necessary to process the information in order to determine the BFS and the strain along the light-guide. This process can be automatized, if a database has been formed. When a new Brillouin reflectogram appears, the MBBS profile from it must be compared with templates from the generated database. To classify the fiber types, it is necessary to evaluate the degree of matching of the explored MBBS profile with all the database templates. To assess the degree of coincidence of the considered MBBS profiles, needs to be defined the overall part of the frequency band for analysis. The programs for the automated processing of the Brillouin reflectograms data are presented. Based on the analysis of Brillouin reflectograms, it is possible to identify a factor that had a predominant influence on the characteristics of the MBS signal in the explored sections of single-mode optical fibers. As a result of the program's work, a template is output that, according to the program's estimates according to the algorithm described above, has the best match with the downloaded image. To increase the accuracy of assessing the similarity of the explored profiles, it is also recommended to carry out calculations according to the above-described algorithm when aligning not only the maximum levels, but also combine the graphs along the frequency axis. It is clear that during the overlay the frequencies of the "peaks" (BFS), there will be a very strong coincidence of the patterns, and the type of the OFs will be determined correctly, while at some temperatures a good degree of similarity with another pattern could be obtained. The obtained estimate of the BFS allows one to determine the degree of the OF strain. The identification of the MBBS profile and other characteristics of the MBS allows you to create a database various types of the OFs and different manufacturers, which can be used to classify the type of the OFs. The results presented in this exploratory development show how based on the analysis of BOTDR reflectograms, it is possible to automatically determine the type of the OF in OC, to identify a factor that has a predominant effect on the frequency response and strain in the explored sections of the OFs in FOCL, which can improve the efficiency of predicting the operational parameters of the physical channels of optical telecommunication systems.

Development of a Geographic Information Systems Baseline Spatial Geodatabase Template for Evaluating Potential and Predicted Environmental Impacts for Sustainable Environmental Impact Assessment of Mining in Sierra Leone

Baseline Environmental Impact Assessment (EIA) of mining projects in Sierra Leone creates a challenging environment for data collection and impact prediction. Application of geographic information systems provides suitable spatial analysis data collection methods to reduce the challenges created by mining environments. This research develops a baseline spatial geodatabase template for evaluating potential and predicted environmental impacts assessment of mining projects in Sierra Leone. It is observed that spatial analysis of impacts of mining projects on the environmental attributes, especially air, noise, water, land, and socio-economy in mining areas is largely unexplored in Sierra Leone. The literature review revealed that no complete GIS spatial data geodatabase collection template appears to have been developed to date to provide an integrated sustainable spatial analysis and modelling tool for EIA and environmental management of mining in Sierra Leone. Therefore developing a Geographic Information Systems baseline geodatabase template for the evaluation of potential and predicted environmental impact for sustainable environmental impact assessment of mining in Sierra Leone will: 1) provide support to the data acquisition process of environmental impact assessment, 2) offer a concept for developing analysis methods for environmental management of mining, 3) minimize the undesired environmental impacts of mining, and 4) give an optimal proposal for data collection and analysis of mining industry in attaining sustainable development in Sierra Leone. Due to the limited available data, a conceptual GIS database template has been developed rather than a database case study of a mining site. No site investigation and data collection were undertaken. The geospatial database template was designed using ArcCatalog, ArcGIS 10.7.1. software, through the following steps: exploration of the general data requirement of environmental impact assessment studies of mining, the definition of the general baseline datasets requirement of environmental impact assessment in mining, structuring of the environmental impact assessment baseline spatial geodatabase, creating the geographic geodatabase dictionary, selecting, matching geographic data with geodatabase structure, designing the feature class and attributes, creating the baseline GIS geodatabase template. The GIS spatial geodatabase template has several advantages for environmental impact assessment of mining including avoiding data redundancy, integrating data into a single database, creating uniformity in data collection, easy to find and track data, integrated spatial and non-spatial data, and reducing the volume of data.

Fingerprint verification using the traveling salesman problem solution and decomposition of the vicinity of the minutiae

The article presents an example of verification of the fingerprint database by the method of solving the problem of a salesman using the decomposition of the neighborhood of the nearest minutes. The solution of this problem is resistant to linear, angular deformations, mixing of points. This method provides the correct solution for a small number of points, for a large number of points there is a cross section of the contours, the solution is not optimal. Therefore, to reduce the processing time and calculate the metric, a modified algorithm for solving the problem by the method of branches and boundaries, namely the alignment and exclusion of arcs on each cycle of the optimal route. Verification is based on the creation of local structures for each minute of the imprint, because it is the local structures that are resistant to deformation. Building global structures very often does not lead to good quality indicators, as there is a problem with the centering of the entire sample. A complete list of tests of fingerprint database templates during their verification by this method has been carried out. The use of decomposition of characteristic features provides greater stability when adding false and erasing true minutes. The results of the article show the values of pairwise comparisons of two templates for true and false tests. The indicators of false rejection rate (FRR), false access rate (FAR), single equivalent error rate (EER) were studied.

Non-Invertible cancellable fingerprint template for fingerprint biometric

Fingerprint biometric has emerged as a highly successful biometric recognition system and find its application in the diverse domain. The fingerprint template database needs to be protected from unauthorized access. If an adversary has acquired the unprotected fingerprint template, then he/she may reconstruct original fingerprint which can be used for unauthorized access of all the systems where the same fingerprint has been used. Hence, securing the fingerprint template is required. In this paper, a non-invertible cancellable fingerprint template based on information extracted from the Delaunay triangulation of minutiae points is proposed. For making the template cancellable a user-specific key of a random binary string is used. The proposed template is revocable, diverse, secure and also gives a good recognition accuracy. The proposed template is tested with a standard FVC2002 database and gives good results as compared with the latest methods.

Development of Output Correction Methodology for Long Short Term Memory-Based Speech Recognition

This paper presents a correction methodology for Long Short Term Memory (LSTM) based speech recognition. A strategy that validates with a reference database was developed for LSTM. It is conceptually simple but requires a large keyword database to match test templates. The correction method is based on the “most matching method” that is finding the word in which the system output is closest among the “Referenced Template Database”. Each LSTM model recognition output was corrected with the proposed new concept. Thus, system recognition performance was improved by correcting faulty outputs. The effectiveness, efficiency, and contribution of this approach to system performance were demonstrated by experiments. Tests carried out using different speech-text datasets and LSTM models yielded an average performance increase of 2.25%. With some advanced models, this ratio rises to 3.84%.

572-P: Lower Insulin Secretion Is Associated with Parahippocampal Gyrus Atrophy in Elderly Patients with Type 2 Diabetes Mellitus

Objectives: Alzheimer's disease (AD) is increasingly recognized as an important comorbidity of diabetes mellitus and is often accompanied by parahippocampal gyrus atrophy (PGA). But the associations between diabetes-related parameters and PGA are not well known. Voxel-based morphometry (VBM) recently became a popular tool for the early diagnosis of AD. One of the clinically useful tools using magnetic resonance imaging (MRI) is the Voxel-based Specific Regional Analysis system for AD (VSRAD) that evaluates the degree of volume loss of parahippocampal gyrus by comparing grey matter with the original normal database template. We examined the risk factors for PGA by using VSRAD in patients with type 2 diabetes mellitus (T2DM). Methods: A total of 137 patients aged ≥ 50 years with T2DM (mean age 67.8 ± 9.8 years) underwent brain MRI scans and comprehensive health examinations. Volume of interest (VOI) was measured using VSRAD for each patient. We examined associations between the severity of VOI atrophy and diabetes-related parameters such as HbA1c, fasting plasma glucose (FPG), C-peptide (CPR) index (plasma CPR/FPG x 100) and Hasegawa Dementia Scale-Revised (HDS-R) score, consisting of 9 simple questions with a maximum score of 30. PGA was defined as the VOI atrophy more than 1.0. Results: Mean HbA1c was 9.3 ± 2.2%. HDS-R (median (range)) score was 28 (12 - 30). CPR index (median (range)) was 1.29 (0.03 - 8.88). The severity of VOI atrophy was more than 1.0 in 36 patients. The VOI atrophy was negatively correlated with HDS-R score (R = - 0.261, p < 0.02). By a using multivariate logistic regression analysis, age (OR 1.08, 95% CI 1.03 - 1.14) and CPR index (OR 0.477, 95% CI 0.233 - 0.977) were significantly associated with PGA. Conclusions: The HDS-R score was significantly correlated with the VOI atrophy. Older age and lower insulin secretion were significantly associated with PGA in patients with T2DM. Disclosure Y. Adachi: None. K. Ota: None. R. Ishii: None. K. Cho: None. Y. Hiramatsu: None. S. Masuda: None. S. Koseki: None. T. Hayashi: None. N. Komatsu: None. E. Ueda: None. Y. Mizuguchi: None. I. Minami: None. T. Yamada: None. T. Watanabe: None.

Partial DCT-based cancelable biometric authentication with security and privacy preservation for IoT applications

Biometric authentication is being vastly used in identity verification for several IoT applications, nowadays. The security and privacy of the biometrics templates used in the authentication process becomes mandatory as it contains rich personal information of the user. Cancelable Biometric System (CBS) is a template securing approach using repeated distortions/transformations at feature/signal level. It is an effective template securing approach which provides non-invertibility, revocability and diversity to the users enrolled with the cancelable template database. The cancelable template database containing cancelable biometric templates of the users is typically stored in a trusted standalone server. To meet the growing demand of IoT applications, cloud computing with provision to store and process even large database, is being largely deployed. However, the security and privacy of the data stored in the cloud is uncertain. In this paper, we have proposed a novel partial DCT-based CBS with privacy and security preservation for providing authentication services in various IoT applications. We have also devised techniques for session key agreement, data encryption and data integrity in the proposed framework to solve the issues of confidentiality, integrity, and availability (CIA) during cancelable template enrolment and authentication. The experimental results and analysis prove that proposed approach performs user authentication with high accuracy and minimal overhead while preserving security and privacy of sensitive cancelable biometric templates.

Securing one-time password generation using elliptic-curve cryptography with self-portrait photograph for mobile commerce application

Over the decades, the security in mobile commerce application via One Time Password (OTP) plays a vital role. With new developments in mobile wallets, the volume of transactions increase globally and the need for securing transactions is still a challenging aspect. A strong user authentication mechanism is required since many of the attacks take minimum effort to break the security. User Authentication is a critical requirement since many of the attacks take minimum effort to break the security. Hence a novel cryptographic scheme is proposed to bridge the gap between security and authentication mechanisms. Initially, the scheme captures the user image to analyze the face for its structure, texture and feature identification. Once the image components are matched from the available template database user authentication is successful. To avoid conflict during template matching the face components are further subjected to segment location, radius and center of eyeballs at subpixellic accuracy. Iris matching is done via spatial histogram. If the iris information is similar, the Transaction Server (TS) generates OTP and sends it to the user mobile in order to complete the transaction. The proposed model is proven to be highly efficient against False Acceptance Rate (FAR) and False Rejection Rate (FRR) measures and is validated over Q- Fire dataset.

Bio-Key Based AES for Personalized Image Cryptography

Abstract In the era of multimedia technologies and rapidly growing multimedia contents, secured information transfer needs to be ensured through robust cryptography techniques. This paper presents a bio-key-generation scheme in the local environment to transfer multimedia content over vulnerable networks. To encrypt the images, one user has to ensure his/her authentication and further needs to provide a secret key for bio-key generation. Secret key aids to fetch biometric features for key formation and key expansion. Thus, the user receives an expanded key from the template database to perform encryption of a plain image. Once the cipher image is delivered to the network, the user has to repeat the same steps for decryption. This paper experiments the proposed bio-key-generation scheme with advanced encryption standard algorithm. This encryption strategy can also be used to encrypt confidential or personal images in various digital systems such as mobile phones, personal digital gadgets and so on. Various analyses ensure the robustness and the performance of the bio-key-based AES encryption scheme. Entropy, correlation coefficient, number of pixel change rate and unified average changing intensity are evaluated to ensure the effectiveness of the proposed method over other key-based encryption techniques.

Cabozantinib in advanced non-clear-cell renal cell carcinoma: a multicentre, retrospective, cohort study.

Cabozantinib is approved for patients with metastatic renal cell carcinoma on the basis of studies done in clear-cell histology. The activity of cabozantinib in patients with non-clear-cell renal cell carcinoma is poorly characterised. We sought to analyse the antitumour activity and toxicity of cabozantinib in advanced non-clear-cell renal cell carcinoma. We did a multicentre, international, retrospective cohort study of patients with metastatic non-clear-cell renal cell carcinoma treated with oral cabozantinib during any treatment line at 22 centres: 21 in the USA and one in Belgium. Eligibility required patients with histologically confirmed non-clear-cell renal cell carcinoma who received cabozantinib for metastatic disease during any treatment line roughly between 2015 and 2018. Mixed tumours with a clear-cell histology component were excluded. No other restrictive inclusion criteria were applied. Data were obtained from retrospective chart review by investigators at each institution. Demographic, surgical, pathological, and systemic therapy data were captured with uniform database templates to ensure consistent data collection. The main objectives were to estimate the proportion of patients who achieved an objective response, time to treatment failure, and overall survival after treatment. Of 112 identified patients with non-clear-cell renal cell carcinoma treated at the participating centres, 66 (59%) had papillary histology, 17 (15%) had Xp11.2 translocation histology, 15 (13%) had unclassified histology, ten (9%) had chromophobe histology, and four (4%) had collecting duct histology. The proportion of patients who achieved an objective response across all histologies was 30 (27%, 95% CI 19-36) of 112 patients. At a median follow-up of 11 months (IQR 6-18), median time to treatment failure was 6·7 months (95% CI 5·5-8·6), median progression-free survival was 7·0 months (5·7-9·0), and median overall survival was 12·0 months (9·2-17·0). The most common adverse events of any grade were fatigue (58 [52%]), and diarrhoea (38 [34%]). The most common grade 3 events were skin toxicity (rash and palmar-plantar erythrodysesthesia; five [4%]) and hypertension (four [4%]). No treatment-related deaths were observed. Across 54 patients with available next-generation sequencing data, the most frequently altered somatic genes were CDKN2A (12 [22%]) and MET (11 [20%]) with responses seen irrespective of mutational status. While we await results from prospective studies, this real-world study provides evidence supporting the antitumour activity and safety of cabozantinib across non-clear-cell renal cell carcinomas. Continued support of international collaborations and prospective ongoing studies targeting non-clear-cell renal cell carcinoma subtypes and specific molecular alterations are warranted to improve outcomes across these rare diseases with few evidence-based treatment options. None.