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Objectives Knowledge about cochlear duct length (CDL) may assist electrode choice in cochlear implantation (CI). However, no gold standard for clinical applicable estimation of CDL exists. The aim of this study is (1) to determine the most reliable radiological imaging method and imaging processing software for measuring CDL from clinical routine imaging and (2) to accurately predict the insertion depth of the CI electrode. Methods Twenty human temporal bones were examined using different sectional imaging techniques (high-resolution computed tomography [HRCT] and cone beam computed tomography [CBCT]). CDL was measured using three methods: length estimation using (1) a dedicated preclinical 3D reconstruction software, (2) the established A-value method, and (3) a clinically approved otosurgical planning software. Temporal bones were implanted with a 31.5-mm CI electrode and measurements were compared to a reference based on the CI electrode insertion angle measured by radiographs in Stenvers projection (CDLreference). Results A mean cochlear coverage of 74% (SD 7.4%) was found. The CDLreference showed significant differences to each other method (p < 0.001). The strongest correlation to the CDLreference was found for the otosurgical planning software-based method obtained from HRCT (CDLSW-HRCT; r = 0.87, p < 0.001) and from CBCT (CDLSW-CBCT; r = 0.76, p < 0.001). Overall, CDL was underestimated by each applied method. The inter-rater reliability was fair for the CDL estimation based on 3D reconstruction from CBCT (CDL3D-CBCT; intra-class correlation coefficient [ICC] = 0.43), good for CDL estimation based on 3D reconstruction from HRCT (CDL3D-HRCT; ICC = 0.71), poor for CDL estimation based on the A-value method from HRCT (CDLA-HRCT; ICC = 0.29), and excellent for CDL estimation based on the A-value method from CBCT (CDLA-CBCT; ICC = 0.87) as well as for the CDLSW-HRCT (ICC = 0.94), CDLSW-CBCT (ICC = 0.94) and CDLreference (ICC = 0.87). Conclusions All approaches would have led to an electrode choice of rather too short electrodes. Concerning treatment decisions based on CDL measurements, the otosurgical planning software-based method has to be recommended. The best inter-rater reliability was found for CDLA-CBCT, for CDLSW-HRCT, for CDLSW-CBCT, and for CDLreference. Key Points • Clinically applicable calculations using high-resolution CT and cone beam CT underestimate the cochlear size. • Ten percent of cochlear duct length need to be added to current calculations in order to predict the postoperative CI electrode position. • The clinically approved otosurgical planning software-based method software is the most suitable to estimate the cochlear duct length and shows an excellent inter-rater reliability.

Immune checkpoint therapy (ICT) can provide durable clinical responses and improve overall survival. However, only subsets of patients with specific tumor types respond to ICT. Thus, significant challenges remain, including understanding pathways of resistance, optimizing patient selection, improving management of immune-related adverse events, and identifying rational therapeutic combinations. These challenges will need a focused approach encompassing both clinical and basic research, with the integration of reverse translational studies. This integrated approach will lead to identification of potential targets for subsequent clinical trials, which will guide decisions as we develop novel combination strategies to maximize efficacy and minimize toxicities for patients.Significance:ICTs induce durable antitumor responses for subsets of patients with cancer. Recent evidence suggests that rational combinatorial strategies can improve response by overcoming primary and adaptive resistance mechanisms, although these may carry an increased risk of immune-mediated toxicities. This review surveys the current understanding of mechanisms of response and resistance to ICTs and active areas of investigation, and proposes a path forward to improving efficacy and minimizing toxicities through better patient selection and rational combinations.

Signal processing algorithms are the hidden components in the audio processor that converts the received acoustic signal into electrical impulses while maintaining as much relevant information as possible. Signal processing algorithms should be smart enough to mimic the functionality of external, middle and the inner-ear to provide the cochlear implant (CI) user with a hearing experience as natural as possible. Modern sound processing strategies are based on the continuous interleaved sampling (CIS) strategy proposed by B. Wilson in 1991, which provided envelope information over several intracochlear electrodes. The CIS strategy brought significant gains in speech perception. Translational research activities of MED-EL resulted in further improvements in speech understanding in noisy environments as well as enjoyment of music by not only coding CIS-based envelope information, but by also representing temporal fine structure information in the stimulation patterns of the apical channels. Further developments include "complete cochlear coverage" made possible by deep insertion of the intracochlear electrode, elaborate front end processing, anatomy based fitting (ABF), triphasic pulse stimulation instrumental in the suppression of facial nerve stimulation, and bimodal delay compensation allowing unilateral CI users to experience hearing with hearing aids on the contralateral ear. The large number of hardware developments might be exemplified by the RONDO, the world's first single unit audio processor in 2013. This article covers the milestones of translational research around the signal processing and audio processor topic that took place in association with MED-EL.

The cochlear implant (CI) as a treatment option for single-sided deafness (SSD) started with a clinical study looking in to the influence of cochlear implantation with a MED-EL device on incapacitating unilateral tinnitus in SSD. The study began in 2003 and was conducted by P. Van de Heyning and his team in Antwerp, Belgium. The first CI in SSD without tinnitus in Germany was implanted by J. Mueller and R. Jacob in Koblenz in 2005. Translational research activities took place since then to evaluate the CI as a treatment option for SSD not only in adults but also in children. They assessed the hearing performance of SSD patients implanted with CI, importance of long electrode arrays in SSD patients, degree of acceptance of CI by SSD children, importance of early CI implantation in SSD children in developing language skills, music enjoyment by hearing with two ears and evidence on spiral ganglion cell body distribution. In 2013, MED-EL was the first CI manufacturer to receive the CE mark for the indication of SSD and asymmetric hearing loss (AHL) in adults and children. In 2019, MED-EL was the first CI manufacturer to get its CI device approved for patients over the age of five with SSD and AHL, by the FDA in the USA. This article covers the milestones of translational research from the first concept to the widespread clinical use of CI in SSD.

Plantar fasciitis is one of the most common cause of heel pain. Injury to the plantar fascia results in loss of normally resilient in fascia. Fascia becomes stiffened and prone to re-injury, which resulting in a vicious cycle of persistent pain and inflammation. Though many therapies would produce better results, there was less exploration on fascial release therapy and k- tape. The purpose of the study is to identify the effect of MFR in addition to K-tape on chronic plantar fasciitis. This is a Quasi- experimental study with 48 participants. The ethical approval was obtained and the study was conducted in multiple physiotherapy centers in Namakkal district, Tamil Nadu. All the participants were selected based on selection criteria mainly those who fulfil any of the three from below, 1) Heel pain increases in the morning with first few steps following prolonged bed rest 2) Pain localized to the inferior heel 3) Pain decreases with activity such as walking or moving 4) Pain score is between 3—7 cms in 10 cm VAS. 24 participants in the experimental group receive myofascial release therapy along with k-tape for 6 weeks, 24 participants in the control group receive stretching along with k-tape for 6 weeks. The outcome measures used in this study are pain and foot function by numerical pain scale and foot function index respectively. Results were analyzed using SPSS 20.0, the results show that there were significant differences obtained between the myofascial release therapy with the k-tape group when compared to k- tape only group. There was a pain score of 10.82 ± 0.196 (p < 0.001) and foot function index score of 10.6 ± 3.85 (p < 0.001). This study concluded that the use of Myofascial release therapy with K-tape reduces pain scores and improves foot function in plantar fasciitis.

Background and objective The size of the cochlea varies a lot among the human population bringing the necessity for electrode arrays to be available in various lengths irrespective of the cochlear implant (CI) brand. This research software helps in the estimation of the patient's cochlear duct length (CDL) which is then used for the simulation of the correct length electrode array matching the patient's cochlear size and as well in getting the patient specific cochlear frequency map. Methods Visual Studio Express 2012 for Windows Desktop is used in the architecture of this research software. The basal turn diameter of the cochlea (“A” value) needs to be measured from the pre-operative computed tomography (CT) image of the patient's temporal bone. This “A” will be taken as the input for the CDL equations proposed by Alexiades et al for estimating the CDL along the basilar membrane for various insertion depths. Greenwood's equation is then used in combination with the CDL for the full length of the cochlea in getting the patient specific frequency map. Results The research software with the help of the “A” value as input, with few button clicks, gives the patient specific CDL for various insertion depths and the Greenwood's frequency map. The users have the choice to select any electrode array of their choice and place it under the frequency map to see how good it fits to that particular patient's cochlea. Also, given the possibility to drag and move the electrode array picture to mimic the post-operative actual electrode insertion depth. Conclusions This research software simplifies the overall process of CDL estimation and in getting the patient specific cochlear frequency map. The clinicians get the chance to simulate placing the various electrode array lengths in patient cochlea in identifying the best fit electrode. This could help in pushing the CI field into the concept of individualized CI electrode array solution that ultimately benefits the patients.

Social media communication serves as an integral part of the crisis response following a mass emergency (disaster) event. Regardless of the kind of disaster event, whether it is a hurricane, a flood, an earthquake or a man-made disaster event like a riot or a terrorist attack, social media platforms like Facebook, Twitter etc. have proven to be a powerful facilitator of communication and coordination between disaster victims and other communities. Consequently, several research articles have been published on social media utilization for disaster response. Many of those recent research articles discuss automated machine learning approaches to extract disaster indicating posts, useful for coordination from various social media posts. Despite this, there is a scarcity of comprehensive review of all the major research works pertaining to the utilization of machine learning approaches for disaster response using social media posts. Thus, this study reviews academic research articles in the domain and classifies them across three disaster phase dimensions – early warning and event detection, post-disaster coordination and response, damage assessment. This review would help researchers in choosing further research topics pertaining to automated approaches for actionable information classification and disaster coordination and would help the emergency teams to make well-informed decisions in disaster situations.

This is a review article on brake pads produced using natural fiber. The various International attempts to address environmental issues and the necessity to safeguard the environment have given light to research emphasizing natural fibers usage in various applications, including automotive brake pads. The usage of asbestos in the brake pads is to be avoided because of the high risk in health it possesses, such as being carcinogenic and unsafe to the environment. Thus researchers are interested in natural fiber due to its excellent properties, very cheap, readily available, non-toxic, etc. In this investigation, the mechanical and tribological property of a non-asbestos brake pad is compared with the asbestos brake pad. These cases illustrate non-asbestos brake pads' ability to achieve substantial improvements in wear rate, Coefficient of friction, Hardness, and moisture absorption compared to conventional brake pads overbroad, and Several factors contribute to these improvements.

Deep learning plays a major task in classification of unsupervised data, which utilises network enhanced learning. This technique proves to be powerful in remote sensing (RS) field for spatial data classification. In the existing environment, huge amounts of data from the earth observation satellites known as satellite images time series (SITS) are gathered, which can be utilised for observing the areas related to geography over through time. In this proposed model the time series model utilised is based on geography. There exists a challenge on how these types of information can be analysed in the field of remote sensing. Notable, techniques related to deep learning substantiated in dealing with remote sensing usually for classification of scene . In this paper, we propose an enhanced classification method involving Recurrent Neural Network (RNN) along with Random forest (RF) for land classification using satellite images, which are publicly available for various research purposes. We utilised spatial data gathered from the satellite images (i.e. time series). Our experimental classification is based on pixel and object-based classification. The attained analysis illustrates that the proposed model outperforms the other present day remote sensing classification techniques by producing 87% target accuracy of classification scene from satellite images.

Objectives This paper attempts to create a new classification type of cochlear hypoplasia (CH)-type malformation taking into consideration of vestibular section and internal auditory canal (IAC). Materials and methods Preoperative computed-tomography (CT) scans of cochlear implant (CI) candidates (N=31) from various clinics across the world with CH type malformation were taken for analysis. CT dataset were loaded into 3D-slicer freeware for three-dimensional (3D) segmentation of the inner-ear by capturing complete inner-ear structures from the entire dataset. Cochlear size in terms of diameter of available cochlear basal turn and length of cochlear lumen was measured from the dataset. In addition, structural connection between IAC and cochlear portions was scrutinized, which is highly relevant to the proposed CH classification in this study. Results CH group-I has the normal presence of IAC leading to cochlear and vestibular portions, whereas CH group-II is like CH group-I but with some degree of disruption in vestibular portion. In CH group-III, a disconnection between IAC and the cochlear portion irrespective of other features. Within all these three CH groups, the basal turn diameter varied between 3.1 mm and 9.6 mm, and the corresponding cochlear lumen length varied between 3 mm and 21 mm for the CI electrode array placement. Conclusion A new classification of CH mainly based on the IAC connecting the cochlear and vestibular portions is presented in this study. CI electrode array length could be selected based on the length of the cochlear lumen, which can be observed from the 3D image.

In recent years, the remote sensing data plays an increasingly significant role in Land use prediction modeling. The effects of land conversion and agricultural bio production are evaluated using remote sensing and economic analysis. It is impossible to over-emphasize the advantages of the vibrant, efficient hybrid mortgage market in Guangdong as it is inseparably linked to economic development. This paper explores specifically the main variables affecting residential mortgage demand and other restrictions on households’ use of a mortgage using the Fuzzy Systematic Evaluation System (FSES). Furthermore, this objective has been accomplished by examining and analyzing the available mortgage products in Guandong through questionnaire survey responses. In addition, the high-interest rates, low income, and house prices result in high and unreasonable repayment-to-earnings mortgages ratios. Moreover, the cumulative effect of this is to make households on low and mid-income prices to the mortgage market. While higher house prices are found in this study to increase mortgage demand, they trigger banks to offer fewer and charge higher rates, particularly after the boom, and especially for highly leveraged households.

The manufacturing industry undergoes a new age with major changes taking place on several fronts. Companies devoted to digital transformation take their future plants inspired by the Internet of Things (IoT). The IoT is a worldwide network of interrelated physical devices,which is an essential component of the internet, including sensors, actuators, smart apps, computers, mechanical machines, and people. The effective allocation of the computing resources and the carrier is critical in the industrial internet of Things (IIoT) for smart production systems. Indeed, the existing assignment method in the smart production system cannot guarantee that resources meet the inherently complex and volatile requirements of the user are timely. Many research results on resource allocations in auction formats which have been implemented to consider the demand and real-time supply for smart development resources, but safety privacy and trust estimation issues related to these outcomes are not actively discussed. The paper proposes a Hierarchical Trustful Resource Assignment (HTRA) and Trust Computing algorithm (TCA) based on Vickrey–Clarke–Groves (VGCs) in the computer carriers necessary resources to communicate wirelessly among IIoT devices and gateways, and the allocation of CPU resources for processing information at the CPC. Finally, experimental findings demonstrate that when the IIoT equipment and gateways are effective, the utilities of each participant are improved.

Thermoplastic polyurethane (TPU) reinforced with natural or renewable fillers gained significant attention in the scientific community and industries. The properties of TPU can be tailored using di...

With cochlear implantation (CI) being the standard of care for profoundly deaf cases, more and more patients with low frequency residual hearing are currently being treated with CI. In view of preserving the residual hearing, the ultimate aim of both the surgeons and the CI companies is to achieve zero-degree of electrode insertion trauma. Variations in the size and shape of cochlea, cross-sectional dimensions of ST, electrode insertion techniques with and without metal stylet rod and the experience level of the operating surgeons, all play a role in the electrode array related insertion trauma. An effective electrode design must include flexible array to accommodate the cochlear shape variation, electrode with variety of array lengths to support the concept of cochlear size specific electrode array and finally smaller cross-sectional dimensions of electrode array in matching the cross-sectional dimensions of ST. As per published reports, FLEX electrode array design offers minimal degree of electrode insertion trauma along with the possibility of patient specific electrode array length matching their cochlear size. Looking at the cross-sectional dimensions of FLEX electrode array along with its volume, it appear to be highly safe to the cochlea by not taking too much volume inside the ST. To offer additional support, otological pre-planning software tool like OTOPLAN is now clinically available in measuring the cochlear size in finding the best electrode array match along with the possibilities of anatomy based post-operative speech processor fitting.

Objective: The objective of this study was to determine the shape of cochlear basal turn through basic cochlear parameters measurement. The secondary aim was to overlay an image of the precurved electrode array on top of the three-dimensional (3D) image of the cochlea to determine which shape of the cochlear basal turn gives optimal electrode-to-modiolus proximity. Materials and Methods: Computed tomography (CT) preoperative image-data sets of 117 ears were made available for the measurements of cochlear parameters retrospectively. Three-dimensional slicer was used in the visualization and measurement of cochlear parameters from both 3D and 2D (2-dimensional) images of the inner ear. Cochlear parameters including basal turn diameter ( A), width of the basal turn ( B), and cochlear height (H) were measured from the appropriate planes. B/ A ratio was made to investigate which ratios correspond to round and elliptical shape of the cochlear basal turn. Results: The cochlear size as measured by A value ranged between 7.4 mm and 10 mm. The B value and the cochlear height ( H) showed a weak positive linear relation with A value. The ratio between the B and A values anything above or below 0.75 could be an indicator for a more round- or elliptical shaped cochlear basal turn, respectively. One sized/shaped commercially available precurved electrode array would not offer a tight electrode-to-modiolus in the cochlea that has an elliptical shaped basal turn as identified by the B/A ratio of Conclusion: Accurate measurement of cochlear parameters adds value to the overall understanding of the cochlear geometry before a cochlear implantation procedure. The shape of cochlear basal turn could have clinical implications when comes to electrode-to-modiolus proximity.

Rabies is a major health issue in the urban areas where there are many free roaming dogs. The absence of knowledge among people regarding the management of dog bites results in increased death due to rabies. Myths and indigenous methods have a greater influence on people than the available vaccines with proven efficacy. Rabies is a 100% fatal disease that can be prevented by timely intervention. Knowledge, attitude and practice among the people play an important role in reducing death due to rabies.So this study aims to assess and evaluate the knowledge, attitude and behaviour on dog bites and its management in the prevention of rabies among general population. A Pretested questionnaire regarding the knowledge, attitude and behaviour on dog bites and it management, containing 34 questions, was used. A cross sectional descriptive study was performed on 205 residents of an urban area (Thirumazhisai) in Tamil Nadu. The data obtained was analysed using SPSS10. A total of 205 subjects were studied. 52 subjects had heard of rabies and knew that it could be spread by animal bite. Regarding the animals that could spread rabies, 52 subjects reported dogs to be the most common source, the second commonest response being cats (24 subjects). Knowledge, attitude and behaviour study suggests that there is need to create awareness amongst the masses regarding epidemiology of the disease and merits of prompt and appropriate post exposure treatment.

This study aims to obtain a better understanding of the number and distribution of spiral ganglion cell bodies (SGCBs) in the central modiolar trunk of the human cochlea with normal hearing as well as with hearing loss due to various pathological conditions. A detailed PubMed search was performed using the key words"human spiral ganglion cell population,""analysis of spiral ganglion cell population,""survival of human spiral ganglion cells,"human Rosenthal's canal,"human ganglion cell counts" and "distribution of human spiral ganglion cells" to identify articles published between 1931 and 2019. The articles were included if the number of SGCBs in the four segments of the human cochlea and angular depth distribution of the SGCBs were mentioned. Out of the 237 articles that were initially identified, 20 articles met the inclusion criteria.The presence of SGCBs inside the Rosenthal's canal (RC) in the modiolar trunk extended to an angular depth of 630 degrees-680 degrees, which is close to the end of the second turn of the cochlea. SGCBs in Segment-IV of the cochlea account for approximately 25-30% of the entire SGCB population, regardless of the cochlear condition (normal vs. pathologic). In normal-hearing subjects, the total number of SGCB cases ranged between 23,910 and 33,702; in patients with hearing loss, the same was between 5,733 and 28,220. This literature review elaborates on the current state of knowledge regarding the number and distribution of SGCBs in the human cochlea.

Identification of the inner ear malformation types from radiographs is a complex process. We hypothesize that each inner ear anatomical type has a uniqueness in its appearance in radiographs. The outer contour of the inner ear was captured from the mid-modiolar section, perpendicular to the oblique-coronal plane, from which the A-value was determined from CT scans with different inner ear anatomical types. The mean A-value of normal anatomy (NA) and enlarged vestibular aqueduct syndrome (EVAS) anatomical types was greater than for Incomplete Partition (IP) type I, II, III and cochlear hypoplasia. The outer contour of the cochlear portion within the mid-modiolar section of NA and EVAS resembles the side view of Aladdin’s lamp; IP type I resembles the side-view of the Sphinx pyramid and type II a Pomeranian dog’s face. The steep spiraling cochlear turns of IP type III resemble an Auger screw tip. Drawing a line parallel to the posterior margin of internal auditory canal (IAC) in axial-view, bisecting the cavity into cochlear and vestibular portions, identifies common-cavity; whereas a cavity that falls under the straight-line leaving no cochlear portion identifies cochlear aplasia. An atlas of the outer contour of seventy-eight inner ears was created for the identification of the inner malformation types precisely.

Objectives: The primary aim was to measure the volume of the scala tympani (ST) and the length of the straight portion of the cochlear basal turn from micro-computed tomography (μCT) images. The secondary aim was to estimate the electrode insertion force based on cochlear size and insertion speed. Both of these objectives have a direct clinical relevance in robotic assisted cochlear implant (CI) surgery.Methods: The ST was segmented in thirty μCT datasets to create a three-dimensional (3D) model and calculate the ST volume. The diameter (A-value), the width (B-value), and the straight portion of the cochlear basal turn (S-value) were measured from the oblique coronal plane. Electrode insertion force was measured in ST models of two different sizes, by inserting FLEX24 (24 mm) and FLEX28 (28 mm) electrode arrays at five different speeds (0.1, 0.5, 1, 2, and 4 mm/s).Results: The mean A-, B-, and S-values measured from the 30 μCT datasets were 9.0 ± 0.5, 6.7 ± 0.4, and 6.9 mm ± 0.5, respectively. The mean ST volume was 34.2 μl ± 7 (range 23–50 μl). The ST volume increased linearly with an increase in A- and B-values (Pearson's coefficient r = 0.55 and 0.56, respectively). The A-value exhibited linear positive correlation with the B-value and S-value (Pearson's coefficient r = 0.64 and r = 0.66, respectively). In the smaller of the two ST models, insertion forces were higher across the range of insertion speeds during both array insertions, when compared to the upscaled model. Before the maximum electrode insertion depths, a trend toward lower insertion force for lower insertion speed and vice-versa was observed.Conclusion: It is important to determine pre-operative cochlear size as this seems to have an effect upon electrode insertion forces. Higher insertion forces were seen in a smaller sized ST model across two electrode array lengths, as compared to an upscaled larger model. The ST volume, which cannot be visualized on clinical CT, correlates with clinical cochlear parameters. This enabled the creation of an equation capable of predicting ST volume utilizing A- and B-values, thus enabling pre-operative prediction of ST volume.

Agriculture is a backbone of our Indian country economy. One of the basic needs is food for every human in the world. An Indian farmer's generally plan the whole cultivation process based upon a traditional method or own experience. The advanced technology will lead to help the farmers in order to take proper guidance of whole cultivation process and achieve better yield. Nowadays in the digital world generates a various large amount of useful information, it is a really difficult task to store and process on a meaningful way. Another trending research area such as different intelligent machine learning techniques are used to help the farmer in order to learn from machine learning model. The pesticide paradox testing will help the plant growth properly. There are many paddy leaf diseases attack the plant at early stage, due to that yield will get reduced. In our research paper, we analyze various rice disease classifications, segmentation and provide an accuracy level using different machine learning techniques (ML), deep Learning (DL) models.

In today's world, with rise in number of people following a sedentary lifestyle, heart disease has become the top reason of death. It is tough for healthcare personnel to forecast such an ailment in advance because it is a complex undertaking that demands competence and a greater knowledge for prediction. We aimed this study towards looking into the topic of predicting cardiovascular disease in advance with use of different ML models, and comparing the accuracies of different older as well newer techniques, on the Framingham heart study dataset from Kaggle. We have investigated the cardiovascular disease prediction using several techniques, namely, Decision Tree, KNN, Naϊve Bayes, SVM, XGBoost, and Random Forest. The prediction accuracy, ROC curve, and AUC value are all used to evaluate the performance of these machine learning techniques. Based on accuracy scores, KNN, SVM, and RFC perform equally well while scoring an accuracy of 85.33%. However, an analysis of the ROC curve and AUC value provides us with a different picture of how despite slightly lesser accuracy percentages, Naϊve Bayes, the modern method XGBoost, and Random Forest actually perform better than the techniques anticipated earlier based on accuracy alone.

Aim: The aim of the study is to study the utility of various inflammatory markers in predicting outcomes of hospitalized patients with coronavirus disease 2019 (COVID-19) pneumonia. Primary Objective: The primary objective of the study is to analyze the correlation between various inflammatory markers and in-hospital mortality. Secondary Objectives: The secondary objective of the study is to assess the correlation between the inflammatory markers and clinical category of patients, and other outcomes such as length of hospital stay and need for invasive ventilation. Methods: A retrospective cross-sectional observational study was done in 221 hospitalized patients who were diagnosed with COVID-19 pneumonia in a tertiary care hospital in South India from May 2020 to July 2020. Clinical and laboratory data of patients diagnosed with COVID-19 pneumonia were collected. This included epidemiological data, clinical data, laboratory parameter (neutrophil: lymphocyte [N: L] ratio, C-reactive protein [CRP], ferritin, interleukin-6 [IL-6], lactate dehydrogenase, D-dimer, and procalcitonin), treatment details, and outcomes. Results: IL-6 levels >60.5 pg/mL and D-dimer levels >0.5 mcg/mL predicted in-hospital mortality with sensitivities of 80% and 76.7%, respectively. N: L ratio and CRP levels had good correlation with the need for oxygen supplementation and/or invasive ventilation. Conclusions: Judicious use of COVID-19 biomarkers could help in disease prognostication and thereby provide guidance to devise appropriate management strategies.

Objectives To understand the growth rate of mastoid thickness and skull width associated with the age for both normal and malformed inner-ear anatomy groups. Also, to determine if there is any mathematical relation between cochlear size as measured by the "A" value against the age, mastoid thickness, and skull width. Methods Ninety-two computed tomography image datasets of human temporal bone were made available that contained normal (n = 44) and malformed inner-ear (n = 48) anatomies. The age of the subjects ranged from 6 months to 79 years. CE marked OTOPLAN preplanning otology software was used to load the patient's preoperative images for making all the measurements including mastoid thickness, skull width, and the cochlear size as measured by the "A" value. Mastoid thickness was measured both in axial and coronal planes starting from the cochlear entrance to the skull surface, with the line in plane with the basal turn of the cochlea. Skull width was measured from side to side in both axial and coronal planes from the image slice that gave the highest width. The cochlear size in terms of basal turn diameter "A" was measured from "Cochlear View" in the oblique coronal plane. Results Mastoid thickness and skull width increased with age in a logarithmic manner. The mastoid thickness increased from a minimum of 17 mm to around 34 mm and the skull width increased from 105 mm to around 146 mm as the age increased from 6 months to 20 years. At the age of around 20, both the mastoid thickness and skull width reached the plateau and thereafter with a very little growth. The skull width was linearly correlated with the mastoid thickness conveying the fact that bigger the head size is, thicker will be the mastoid. The size of the cochlea as measured by the "A" value did not have any meaningful correlation with the age, mastoid thickness, and skull width. This conveys the message that the cochlear size is independent of the overall size of head and the age of patient. Conclusions Mastoid thickness and skull width increased with age, while the cochlear size was independent of age, mastoid thickness, and the size of the skull.

Objective: To understand the anatomical and dimensional variations of the human inner ear using 3-dimensional (3D) segmentation within the Middle East population. Design: Retrospective study. Setting: King Abdullah Ear Specialist Center (KAESC) Riyadh, Saudi Arabia. Participant: Forty computed tomography (CT) images of patients with sensorineural hearing loss who underwent cochlear implant (CI) were taken for analysis. Main outcome Measures: Three-dimensional images showing the anatomical variations of the inner ear including various pathological conditions, cochlear parameters including basal turn diameter (“A” value), “B” value which is perpendicular to “A” value, cochlear height, length, and width of the internal auditory canal (IAC), intercochlear spacing, and electrode angular insertion depth (AID). Results: Out of 40 CT image data sets, 12 had normal inner-ear anatomy (NA), 4 with enlarged vestibular aqueduct syndrome (EVAS), 8 with only 2 turns of the cochlea (2TL), 7 with incomplete partition (IP) type II, 5 with cochlear hypoplasia, 1 with common cavity, and 3 with abnormal IAC. Taking the NA, EVAS, 2TL, and the IP type II cases altogether, age of the patient had no correlation with the “A” value; however, the “A” value had a linear correlation with the “B” value. The age of the patient had an increasing logarithmic correlation with the IAC length and the intercochlear spacing. The “A” value did not have any meaningful correlation with the cochlear height. Three data sets showed asymmetric inner-ear malformation types on either side of the ears. All these 40 cases were implanted with various CI electrode array variants and the corresponding postoperative plain film X-ray images showing the electrode AID are given separately in figures. Conclusions: Three-dimensional segmentation of the inner ear from the temporal bone CT is a valuable clinical and training tool for surgeons and radiologists especially in difficult cases which will certainly help to understand the overall anatomical and dimensional variations.

Objectives Capture the human inner-ear malformation types in 3D by segmenting the inner-ear structures from clinical CT (computed tomography) and MR (magnetic resonance) image datasets. Volumetric analysis was done to find the variations in the volume of cochlear part alone from complete inner-ear followed by 3D printing from the 3D segmented models. Materials and methods Using 3D slicer freeware, the complete inner-ear structures were segmented from anonymized CT and MR image by setting a tight grey-scale threshold to avoid capturing unwanted structures followed by volumetric analysis of the cochlear part alone. 3D printing was done using Form labs desktop 3D printer. Results We identified 2x normal anatomy (NA) cochlea, 1x enlarged vestibular aqueduct syndrome (EVAS), 3x incomplete partition (IP) type-I, 4x IP type-II, 3x IP type-III, 5x common cavity (CC) and 5x cochlear hypoplasia (CH). 3D segmented models along with the 3D printed models showed huge variation in size, shape and the anatomy among the image data-sets analyzed. Volumetric analysis showed that on average, volume of CC was above 150mm3, volume of CH fell below 80mm3, Volume of NA, EVAS and IP-I were all around 85-105mm3 whereas the volume of IP-II was around 50mm3. Conclusion Visualizing human inner-ear malformation types in 3D both as computer models and as 3D printed models is a whole-new experience as demonstrated in this study. The volumetric analysis showed a huge variation among the volume of cochlear part alone among the malformation types.

The objective of this study is to determine the variations in size and shape of the most widely recognized cochlear malformation types using three‐dimensional (3D) visualization. Using 3D slicer freeware, the complete inner‐ear structures were segmented from 46 anonymized high‐resolution computed tomography (HRCT) image datasets. Cochlear height, internal auditory canal height, and width were measured from the axial plane. Cochlear basal turn diameter was measured from the oblique coronal plane. Number of cochlear turns was measured from the 3D images and the corresponding cochlear duct length (CDL) was estimated using the CDL equations given in Alexiades et al. [Otol Neurotol 36 (2015) 904–907]. Out of 46 preoperative HRCT image datasets of human temporal bone, cochlear anatomy types including normal anatomy (4), enlarged vestibular aqueduct syndrome (3), cochlear aplasia (2), incomplete partition Types I (8), II (Mondini's deformity) (3), and III (X‐linked) (4), cochlear hypoplasia (CH) (17), and common cavity (CC) (5) were identified. Majority of CH cases had cochlear height shorter than 4 mm whereas the CC cases measured cochlear height above 6 mm. For all the other malformation types, cochlear height was between 4 and 6 mm. In terms of “A” value, majority of CH cases showed shorter “A” value of

Introduction: Among the oral mucosal infections such as Periodontal Diseases, (PD) there is a strong correlation between systemic metabolic conditions such as type 2 diabetes (T2D). Moreover, there is growing evidence that Diabetic Neuropathy (DN) is associated with increased risk for foot ulceration. However, little is known how DN would correlate with the PD status. Aim: The aim of this study was to determine how the diabetes status as exemplified by the state of HbA1c levels and DN would correlate with the status of PD. Materials and Methods: T2D patients with and without PD, who visited the dental department of a diabetes hospital were included in the study. Patients without PD (n = 494) and with PD (n = 493) were recruited based on probing depth of >4mm/clinical attachment loss of >3mm (mild to moderate PD) according to the diagnostic criteria of the American Academy of Periodontology. Body mass index, fasting blood glucose, postprandial blood glucose and HbA1c were measured. Neuropathy was assessed by biothesiometry. Results: There was a significant difference in the age, duration of diabetes, glycemic levels and presence of neuropathy between the 2 groups (Table). In the regression analysis, neuropathy was highly significant (p Conclusion: The study shows a strong association between PD and DN among T2D patients. Disclosure R. Vinitha: None. A. Ramachandran: None. M. Muthukuru: None. K. Satheesh: None. R. Yogalakshmi: None. A. Rajeswari: None. L. Sundar: None. A. Nanditha: None. A. Raghavan: None. C. Snehalatha: None. Funding India Diabetes Research Foundation

(2021). Thirty Years of Translational Research Behind MED-EL. Acta Oto-Laryngologica: Vol. 141, Thirty Years of Translational Research Behind MED-EL, pp. (i)-(cxcvi).

The Auditory Brainstem Implant (ABI) is based on the classic cochlear implant (CI) but uses a different stimulation electrode. At MED-EL, the early development activities on ABI started in the year 1994, with the suggestion coming from J. Helms and J. Müller from Würzburg, Germany in collaboration with the Univ. of Innsbruck Austria. The first ABI surgery in a neuro-fibromatosis (NF2) patient with the MED-EL device took place in the year 1997. Later, the indication of ABI was expanded to non-NF2 patients with severe inner-ear malformation, for whom a regular CI will not be beneficial. Key translational research activities at MED-EL in collaboration with numerous clinics investigating the factors that affect the hearing performance amongst ABI patients, importance of early ABI implantation in children, tools in pre-operative assessment of ABI candidates and new concepts that were pursued with the MED-EL ABI device. The CE-mark for the MED-EL ABI to be used in adults and children down to the age of 12 months without NF-2 was granted in 2017 mainly based on two long-term clinical studies in the pediatric population. This article covers the milestones of translational research from the first concept to the widespread clinical use of ABI in association with MED-EL.

Electric-acoustic stimulation (EAS) is a special treatment modality for those patients who are profoundly deaf in the high-frequency (HF) region and retain usable hearing in the low-frequency (LF) region. Combining the electric stimulation with cochlear implant (CI) in the HF and acoustic amplification of residual hearing using a conventional hearing aid (HA) in the LF region defines EAS. The EAS concept was first proposed by C. von Ilberg from Frankfurt, Germany in the year 1997. In association with MED-EL, all the necessary safety studies were performed in non-human subjects before the first patient received it in 1997. In association with MED-EL, all the necessary safety studies were performed in non-human subjects before the first patient received it in 1999. For the patient to successfully use the EAS concept, the residual hearing needs to be preserved to a high extent and for several years. This requires a highly flexible electrode array in safeguarding the intra-cochlear structures during and after the CI electrode array insertion. Combining the HA unit with the audio processor unit of the CI was necessary for the convenient wearing of the unified audio processor. Fitting of the unified audio processor is another important factor that contributes to the overall success of the EAS treatment. The key translational research efforts at MED-EL were on the development of flexible electrodes, a unified audio processor, innovations in the fitting process, intra-operative monitoring of cochlear health during electrode insertion, pre-operative soft-ware tool to evaluate the cochlear size and electrode selection and some new innovations tried within EAS topic. This article covers the milestones of translational research from the first concept to the widespread clinical use of EAS.

The A-value used in cochlear duct length (CDL) estimation does not take malformed cochleae into consideration. The objective was to determine the A-value reported in the literature, to assess the accuracy of the A-value measurement and to evaluate a novel cochlear measurement in distinguishing malformed cochlea. High resolution Computer Tomography images in the oblique coronal plane/cochlear view of 74 human temporal bones were analyzed. The A-value and novel C-value measurement were evaluated as predictors of inner ear malformation type. The proximity of the facial nerve to the basal turn was evaluated subjectively. 26 publications report on the A-value; but they do not distinguish normal vs. malformed cochleae. The A-values of the normal cochleae compared to the cochleae with cochlear hypoplasia, incomplete partition (IP) type I, -type II, and -type III were significantly different. The A-value does not predict the C-value. The C-values of the normal cochleae compared to the cochleae with IP type I and IP type III were significantly different. The proximity of the facial nerve to the basal turn did not relate to the type of malformation. The A-value is different in normal vs. malformed cochleae. The novel C-value could be used to predict malformed anatomy, although it does not distinguish all malformation types.

AI and cloud is the future of Scientific research, in our proposed idea will help us solving a various issues using Artificial Intelligence(AI) and Cloud Computing(CC). We identified and discuss about the various problems, which can be solved by collaboration of cloud computing and artificial intelligence. Like, including artificial intelligence programs that will run in the cloud to enhance efficiency is one of the strongest exploration methods. It is important for the drive to develop applications, made in the cloud, past the essential automation pro foresee circumstances and settle on continuous choices by means of the Internet. Intelligent computing language programs is introduced, that machines can make decisions independently and in real-time.

Physical education these days no longer applies to today's younger generations (Gen Y). Internet reading and reading grades that are popularly known as online education play a vital role in the country's education system. There is no denying that online education offers many benefits to younger students. In our proposed idea is to build a website that will use HTML, CSS and JS frontend and Php and MySQL backend. It contains a registration page where you will request user verification. In this case the user can create on his / her id containing username and password. On the home page four tap menu in the navigation bar namely home, services, by us, Contact Us. In each menu will have features, for example, a contact button that will allow the user to contact us with feedback. Our proposed system introduces an interactive method for the user to read blogs delivered by various technologies or teachers related to those subjects and will allow the user to ask his or her questions. In this way it will provide a smart and automated web education app for the academic advisory program. The application is used to promote learning and promote student development by automatically identifying and achieving their educational need and goals.

Nowadays the grain food demand is increasing due to population increase. Rice is one of the essential foods for half of the world’s population. In India most of the farmer struggled to identify paddy leaf disease at a premature stage. The deep learning models were used to detect a rice blast disease such as Brown spot, Sheath blight, Blast and Leaf streak disease at early stage, so we can control disease spread over all plant to increase the rice production. The proposed system is applied to identify a various rice plant leaf images disease detection using mask R-CNN, Faster R-CNN algorithms. We have studied five different paddy diseases and applied in southern region (India) to improve the paddy quantity. We collected a paddy leaf images through a Sony Camera & Mobile device (Vivo V9) and conducted experiments to train the model using 1500 images. Our experimental results analysis mask R-CNN is best suitable for to detect and identify the various rice blast disease such as Blast-96%, Brown spot-95%, and Sheath blight-94.5%. The results implies capable of disease identification from real-time capture leaf images and improve the accuracy applying different areas to control the spread rice blast disease.

The expansion of fake news in online world starts with a trendy topic around us whether it is related to environment, politics, healthcare or any pandemic like Coronavirus. Flashy & altered headlines attract the users to help media enhance their business. Fake news & hoaxes related to pandemic like Coronavirus can lead to much harm than coronavirus itself. This extensive spread of fake news comes with negative impact on all the citizens. Therefore it’s very important to detect, intervene & analyze any pretend news. The main purpose of writing this research article is to come out with the best approach to monitor the misleading information of various diseases around the internet by investigating the principles, methodologies & algorithms. The false news comes with the big, unstructured, irrelevant, incomplete & noisy data and for its detection some evaluation metrics, representative datasets, network analysis approach & algorithm like Naive Bayes Classifier will be on the role leading to the most effective & accurate way to detect fake news related to fake disease news all around the globe. We achieved fake disease news detection accuracy of approximately 82.49%.

Face area is a front vision of every things that remembers finding a face for the photo. Two of the primary perspectives inside the arrangement of the general examination of face affirmation by PCs that are discussed here: the face and features face ID and face affirmation or rather face assessment. Our ideas describe investigation progress towards a substitute method to manage face affirmation. Finally, we report, robotized face affirmation system. Face area is a notable subject in biostatistics. We have perception photographic camera transparently puts for video get similarly as security purposes. The guideline piece of elbowroom of this computation is altogether more the uniqueness and underwriting. Nonetheless, face acknowledgment actually a movement of a couple of related issues: Initially, look at the images and find all the appearances. Second, based on individually face and appreciate that whether or not the face is moved in the direction of a way that is particular or awful lighting, it is up till now a comparative person. Finally select features that can be used to uncommonly perceive every face as the size and shape of the eyes, face, etc at last, taking a gander at these structures of data we need to find the person's identified. Face acknowledgment improvement is generally determined by the advancement of employments, for instance, mastercard check, picture video perception, affirmation for banking and access security structures. Likewise, is separated into areas: Detection and checking a photograph with OpenCV and Deep Learning.

Telecommunication is the transmission of information over electromagnetic systems using technologies such as radio, wire, etc. Mobile phones are the most popular form of telecommunication. As a result, the usage of smartphones has drastically increased each year. And even during this current pandemic COVID-19, the usage of smartphones and internet has tremendously increased. Some significant applications include banking applications, education sectors (online classes), virtual meetings, e-commerce, travel, recreation etc. As the usage increases, there arises a frequent charge and discharge cycle. Enormous amount of energy is generated every day while carrying our daily activities by means of which, a significant amount of pressure is developed. Using this energy, an efficient model is proposed which uses piezoelectric and thermoelectric sensors to generate energy to suffice the daily needs of a common man. As aligning with the SDG goal number 7 - affordable and clean energy, the proposed idea is a step towards attaining a sustainable future.

The education system passed multiple mile stones: from the traditional education, digital education and the introduction of smart education in the cloud, which provides easy access and promotes green IT. Nowadays the form of learning changes dramatically, such as conventional learning to smart learning to offer an all-encompassing understanding of how to use today’s innovation to fully set them up for a rapidly changing world where versatility is important. Students are given various tools and techniques for acquiring knowledge from anywhere and at any time. One of these possible tools are the three blended flavours of significant technologies, namely the Mobile Green-Cloud Computing. Through cloud computing, the operating system focuses mainly on less carbon emissions and sustainable development not just for fostering the green IT advancement but also to reduce the energy consumption and the green house gas emissions. The migration from the conventional learning approach to the Mobile Green-Cloud Computing Learning system therefore allows, among other things, efficient use of resources, reduction of physical books and hardware components (i.e. reduction in energy consumption).

Immune checkpoint therapy (ICT) can produce durable antitumor responses in metastatic urothelial carcinoma (mUCC); however, the responses are not universal. Despite multiple approvals of ICT in mUCC, we lack predictive biomarkers to guide patient selection. The identification of biomarkers may require interrogation of both the tumor mutational status and the immune microenvironment. Through multi-platform immuno-genomic analyses of baseline tumor tissues, we identified the mutation of AT-rich interactive domain-containing protein 1A (ARID1A) in tumor cells and expression of immune cytokine CXCL13 in the baseline tumor tissues as two predictors of clinical responses in a discovery cohort (n = 31). Further, reverse translational studies revealed that CXCL13-/- tumor-bearing mice were resistant to ICT, whereas ARID1A knockdown enhanced sensitivity to ICT in a murine model of bladder cancer. Next, we tested the clinical relevance of ARID1A mutation and baseline CXCL13 expression in two independent confirmatory cohorts (CheckMate275 and IMvigor210). We found that ARID1A mutation and expression of CXCL13 in the baseline tumor tissues correlated with improved overall survival (OS) in both confirmatory cohorts (CheckMate275, CXCL13 data, n = 217; ARID1A data, n = 139, and IMvigor210, CXCL13 data, n = 348; ARID1A data, n = 275). We then interrogated CXCL13 expression plus ARID1A mutation as a combination biomarker in predicting response to ICT in CheckMate275 and IMvigor210. Combination of the two biomarkers in baseline tumor tissues suggested improved OS compared to either single biomarker. Cumulatively, this study revealed that the combination of CXCL13 plus ARID1A may improve prediction capability for patients receiving ICT.

The question of why pre-curved modiolar hugging (MH) electrodes only cover the basal turn of the cochlea and not beyond that is unanswered yet in the CI field. Therefore the aim of this article is to show what the practical limitations are with the pre-curved MH electrode design in not being able to fabricate beyond one full turn. Every CI electrode design needs a metal mold with grooves for placing the platinum wires and for injecting with the silicone elastomer. Limitations in making a mold with groove that goes beyond one full turn of curvature along with the mechanical deformation of the curved silicone elastomer, prevents making a pre-curved MH electrode beyond one full turn. Electrode tip fold-over, electrode scalar deviation and the inconsistent electrode to modiolus wall proximity are the reported issues with this electrode type which does not help by any means to the operating surgeon and the pediatric candidates especially. If intra-operative imaging is recommended to confirm the proper placement of the electrode for one particular electrode design, then how many clinics in the world may have this facility and is it ethical to put the patient under more radiation risk are the natural questions that needs to be answered in the interest of the patient. Every CI brand should come out of their marketing philosophy and innovate what is essential in bringing the full benefit of the device to the patients.

In recent years, different types of review systems have been developed with the recommender system (RS). RSs are developed based on user textual reviews, ratings, and comparative opinions. RSs for social media resources, such as blogs, forums, social network websites, social bookmarking websites, video portals, and chat portals help users to collaborate effectively. Social media resources are used in the RS for recommending contents, articles, news, e-commerce products, and users. Although research on social media in RSs has increased annually, comprehensive literature review and classification of these RS studies are limited and must, therefore, be improved. This paper aims to provide a comprehensive review of the social media RS on research articles published from 2011 to 2015 by exploiting a methodological decision analysis in six aspects, including recommendation approaches, research domains, and data sets used in each domain, data mining techniques, recommendation type, and the use of performance measures. A total of 61 articles are reviewed among the initial 434 articles on RS research published in Web of Science and Scopus between 2011 and 2015. To accomplish the aim of this paper, a comprehensive review and analysis was performed on extracted articles to explore various recommendation approaches which are used in the RS. In addition, various social media domains are identified, where RSs have been employed. In each identified domain, publicly available data sets are also reported. Furthermore, various data mining techniques, recommendation types, and performance measures are also analyzed and reviewed in technical aspects. Finally, potential open research directions are also presented for future researchers intended to work in social media RS domain.

In the present work, we studied the effect of light scattering layer on the performance of DSSCs. TiO2-ZnO thin films were coated onto FTO glass substrate by spin coating technique as a photoanode for DSSCs. ZnO nanorods with flower structures were potentiostatically grown on TiO2-ZnO films at various potentials from −1.1 to 1–1.3 V as a light scattering layer. XRD patterns reveal that as the deposition potentials increase the growth of ZnO nanorods increases along with (101) plane orientation. FE-SEM images display agglomerated grains and nanorods with flower structures for TiO2-ZnO film, and ZnO has grown on TiO2-ZnO film at a deposition potential of −1.3 V. UV–vis spectra confirm the TiO2-ZnO with ZnO nanorods having a higher light scattering effect, absorbance and dye loading than that of another film. The efficiency of the DSSCs consisting of without and with scattering layer is estimated to be 0.79 and 1.81%, respectively.

Microblogging is used to broadcast short messages in form of text, pictures, links, and videos to the followers or subscribers on the Internet. The hashtag is the keyword or metadata that is used to mark messages, which allow users to classify or find the related posts easily. However, posts in microblogging environment are not properly tagged due to data sparsity and finding the popularly used relevant hashtag for the tweets. In this paper, hash tag recommender (HTR) is the proposed method using matrix factorization with tweet’s tags for user input text. To eliminate data sparsity, hashtag recommendations are generated from similar tweets. Hashtags based on the current trends, time, and location are recommended for the short messages of input by the user. To achieve this, the proposed method calculates the score for each tags, which are identified for similar tweets, and recommendations are generated. Results of this study show that hashtag recommendation outperforms the previous methods. The significance of the proposed HTR for twitter data set is more accurate on considering various metadata such as time and location.

OBJECTIVES The aim of this study is to compare the common cavity (CC) with the normal anatomy inner ear in order to evaluate whether the cavity is representing both the cochlear and the vestibular parts of the inner ear and to revisit CC deformity from a three-dimensional (3D) perspective. METHODS High-resolution computed tomography image datasets of 17 temporal bones initially identified as CC were evaluated with 3D reconstruction and multiplanar image analysis using a free available software for 3D segmentation of the inner ear. All 3D images of CC were compared to a normal inner ear. Maximum and minimum diameter of the CC were correlated with the circumference of the CC in an axial plane. RESULTS In 13 cases (76%), CC represented only the vestibular part of the inner ear and did not represent CC as defined here and by Sennaroglu, Kontorinis, and Khan. True CC was correctly diagnosed in only one case (6%). In three cases (18%), a rudimentary part of the cochlear portion could be identified. The axes' length of the elliptical cavity showed a strong positive linear relation to the circumference of the cavity (long axis: r = 0.94; P

A systematic study of changes on optoelectronic properties of (Z)-3-(4-(4,5-diphenyl-1H-imidazole-2-yl)phenyl)-2-phenylacrylonitrile (DPimdPPA) based films owing to treatments with acid or temperature, is reported. The DPimdPPA films treated with vapors of HNO3, HCl, or CH3COOH exhibited a hypsochromic shift up to 70 nm as well as an enhancement in the fluorescence quantum yield. Interestingly, a similar behavior was observed when films were thermally treated at temperatures between 100 °C and 240 °C. XRD studies showed that DPimdPPA in powder form is a polycrystalline material, while the as-deposited films were amorphous. However, the treatments with temperature or acid, induced crystallinity in the films. Studies by atomic force microscopy showed that the induced crystallinity modified the film morphology leading to the formation of agglomerates with needle like shape. These changes in fluorescence were used to tune the emission in OLEDs. Notably, devices with pristine DPimdPPA film as well as treated with HNO3 vapor or heated at 240 °C were prepared. The emission with pristine films was warm white with CIE coordinates (0.45, 0.43); with HNO3 treatment it was green with CIE coordinates (0.28, 0.40) and, when treated at 240 °C the emission was greenish-blue with CIE coordinates (0.35, 0.48). Besides, with the treatments the turn-on voltage decreased, and luminous parameters were enhanced; the maximum luminance was about 5400 cd/m2 while the highest luminance efficiency 5.2 lm/W.

In this present investigation, zinc oxide-titanium oxide (ZnO-TiO 2 ) thin films were prepared by sol-gel spin coating technique and used as a blocking as well as seed layer, and followed by, ZnO nanowire arrays (NWAs) and nanoneedle arrays (NNAs) were synthesized on ZnO-TiO 2 seed layer by facile hydrothermal technique by varying some parameters such as solution concentration, growth time and growth temperature. They are used as a photoanode for dye sensitized solar cell (DSSC) and characterized by spectroscopic and microscopic technique to investigate about the crystal structure, morphology and optical properties. The presence of hexagonal wurtzite structure of the prepared nanostructures grown along with (002) plane was confirmed by using X-ray diffraction (XRD), Raman spectra and transmittance electron microscope (TEM). NWAs and NNAs were observed with flower like structure consisting of nanowires and nanoneedles, respectively by field emission scanning electron microscope (FE-SEM). UV–Vis spectra imply that NNAs have a better light absorbance with more dye loading than NWAs. It could be found from current density-voltage (J-V) curve that the photovoltaic conversion efficiency of the NWAs and NNAs based DSSC is 0.91% and 1.47%, respectively. Electrochemical impedance spectroscopy (EIS) shows that DSSC based on NNAs photoanode has a better electron lifetime with less electron recombination than DSSC based on NWAs photoanode.

488 Background: Immune checkpoint therapy can produce durable anti-tumor responses in metastatic urothelial carcinoma (mUCC); however, the responses are not universal. Despite multiple approvals of immune checkpoint therapy in mUCC, we lack predictive biomarkers to guide patient selection. Therefore, there is a critical need to develop clinically useful biomarkers to refine patient selection. The single biomarker studies either focused on tumor mutations or immune response biomarkers, which may limit predictive power due to lack of integration between cancer cell biology and immune cell responses. The identification of biomarkers may require interrogation of both the tumor mutational status and the immune microenvironment. Methods: We performed retrospective multi-platform immuno-genomic analyses of pre-treatment tumor tissues in a discovery cohort (n = 31). Next, we tested the clinical relevance of ARID1A mutation and pre-treatment CXCL13 expression in two independent confirmatory cohorts (CheckMate275 and IMvigor210). Additionally, we performed reverse translational studies using murine model of bladder cancer to demonstrate direct association of the biomarkers in anti-PD-(L)-1 mediated anti-tumor immunity. Results: We identified genomic mutation of AT-rich interactive domain-containing protein 1A ( ARID1A) in tumor cells and expression of immune cytokine CXCL13 in the pre-treatment tumor tissues as two predictors of clinical responses. We found that ARID1A mutation and expression of CXCL13 in the baseline tumor tissues correlated with improved overall survival (OS) in both confirmatory cohorts (CheckMate275, CXCL13 data, n = 217; ARID1A data, n = 139, and IMvigor210, CXCL13 data, n = 348; ARID1A data, n = 275). Further, reverse translational studies revealed that CXCL13−/− tumor-bearing mice were resistant to immune checkpoint therapy whereas ARID1A knockdown enhanced sensitivity to immune checkpoint therapy in a murine model of bladder cancer. We then interrogated CXCL13 expression plus ARID1A mutation as a combination biomarker in predicting response to immune checkpoint therapy in CheckMate275 and IMvigor210. Combination of the 2 biomarkers in baseline tumor tissues showed improved OS compared to either single biomarker. Conclusions: Cumulatively, this study revealed that the combination of CXCL13 plus ARID1A mutation may improve patient selection in mUCC for immune checkpoint therapy.

Machine learning strategies to automate data processing are urgently needed with the increasing accumulation of biological datasets. In recent years, software development has received considerable ...