Sovren.Media: Premium Video + Social Media

09/03/2024

No statistically significant difference in extension range of the knee was noted in either groups as it was normal at base line.This study aims to observe the spectrum of Prenatal Diagnosis of Rare Genetic conditions at a Tertiary care hospital in Karachi. This is a retrospective review conducted at the Aga Khan University Hospital, Karachi from January 2016 to July 2018. All cases undergoing invasive testing by Chorionic villus sampling for indications other than Thalassemia were included. Forty percent of patients in our cohort underwent invasive testing for muscular dystrophies particularly survival motor neuron (SMN) gene deletion and 32% for Cystic Fibrosis. Other rare disorders like JAM 3 mutation, PEX 1 gene, Barters Syndrome, Wardenberg, Bardet-Beidl Syndrome and Lissencephaly accounted for 28%. Sophistication in laboratory technology and DNA banking has improved the prenatal diagnosis of rare genetic disorders particularly SMN gene deletion. Integrated care involving foetal medicine specialist, Paediatric geneticist, and dedicated Laboratory personnel improves Counseling and Diagnosis of rare genetic conditions. Provision of dedicated nursing staff along with strengthening of welfare facility for non-affording patients would improve the uptake of invasive testing.The current study was planned to assess how the integration of brief cognitive behaviour therapy (CBT) with hypnotherapy can be productive for a client's quick progress in treatment. It illustrates the effectiveness of two methods of treatment integrated to make better prognosis in the treatment of a depressed Pakistani housewife aged 25 years, who had been suffering for a year. The sessions included hypnotic induction, teaching self-hypnosis with positive suggestions, mood monitoring, use of imagery and relaxation techniques along with specific strategies of brief CBT. Predominant feature of her clinical presentation was the belief of being unloved, and the negative thoughts of being devalued by the husband. Hypnotherapy contributed to achieving remarkable therapeutic progress in a relatively short time. At initial presentation, the depressive symptoms were extremely high as demonstrated by psychological assessment tests and Beck Depression Inventory (BDI). Subsequent test results indicated that she had returned to normal level of functioning (81-90) as assessed through the Global Assessment of Functioning Scale (GAFS). At the time of reporting the case, she was in the follow-up phase. The case highlights the value of hypnosis as a tool of empowerment especially important to diminish depression when used as an adjunct with cognitive behaviour therapy.Frontal sinuses have unique anatomical features that are distinct to every individual. https://www.selleckchem.com/PARP.html Radiographic measurement of the frontal sinus is becoming popular in identifying deceased persons in cases where soft tissue remains are not found such as in cases of mass explosions and natural disasters. The aim of this review article is to highlight the significance of employing the method of radiography of frontal sinuses in the process of identification of human bodies. With the use of Pubmed, Medline and Embase, articles on frontal sinus anthropological significance were analyzed from 2015 till 2018. Sexual dimorphism was evident between the two genders. The dimensions are bigger for the males as compared to the females. The left sinus has bigger dimensions as compared to the right frontal air sinus. The reliable use of the radiographic technique is a simple and cost effective method of knowing identity even when the body is severely decomposed.The 2015 heat wave resulted in an estimated over 1200 deaths during the month of June. However, there were no records on the spatial distribution of the effects of this heat wave. An analysis of Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) daily data was conducted to identify regions that experienced above normal temperatures in 2015. An analysis of the monthly averages showed that in general April and May were the warmer months in Karachi, unlike the case in 2015. In addition, the general warm trends were common in the highly industrialised Sindh Industrial Trading Estate (SITE) and Liaquatabad towns, while Gadap, with its mostly barren land, and New Karachi also experience higher temperatures. Coastal towns were naturally cooler and more habitable in the given scenario. A count of the spatial presence of health facilities for the city was also extracted where Gadap and Korangi were poorly served while the more affluent towns of Defence Housing Authority (DHA) and Gulshan-e-Iqbal appeared to be better served.OBJECTIVE To determine the effect of a multi-component exercise programme on elderly adults' risk of falling in nursing homes. METHODS A computerised search of published randomised controlled trials in the English language was performed using PubMed, Cochrane Library, the Cumulative Index of Nursing and Allied Health Literature, Physiotherapy Evidence Database (PEDro), and the Institute for Scientific Information up to December 2017. We included highquality articles that reported a score of ≥5 on the Physiotherapy Evidence Databasescale which compared multicomponent exercise with a single exercise programme in nursing homes, with the risk of falling as an outcome, among participants aged ≥65 years. RESULTS A total of 8 articles, comprising 382 participants, were included. All these articles scored 6-8 points out of 10 on the PEDro scale, with an average of 6.7 points. The mean age of participants in the included articles was ranged from 76±8.0 to 92±2.0 years, and286 (75%) participants were females. A multi-component exercise programme in the experimental group, which had 204 (53.4%) subjects significantly reduced the risk of falling in nursing homes compared to a single-exercise programme, which was used in the control group that had 178(46.6%) subjects. CONCLUSIONS A multi-component exercise programme was found to be useful for reducing elderly adults' risk of falling in nursing homes.OBJECTIVE To assess the compliance of healthcare personnel with regard to sending completely filled transfusion requisition forms. METHODS The audit was conducted at Aga Khan University Hospital, Karachi, and comprised requisition slips received at the hospital blood bank from September 2014 to February 2015. The British Committee for Standards in Haematology guidelines was used as the standard. Percentage of each variable on the proforma was analsyed. Rating less then 50% for each form was defined as "needs improvement", 51-99% as "good compliance" and 100% as "excellent compliance". After implementing strategies to increase awareness and the launching of an online transfusion requisition form, a re-audit of physician compliance was done from February to April 2016 and the results were compared with the initial audit.. Data was analysed using SPSS 21. RESULTS The audit and the re-audit both comprised 1000 transfusion requisition forms each. In the audit, The sum of total scores of all the transfusion requisition forms was 4911, indicating a compliance rate of 46.9%, while the corresponding numbers in the re-audit were 10000 and 100%. CONCLUSIONS The implementation of online blood transfusion requisition system had a positive impact on compliance rate.OBJECTIVE To evaluate pre-microscopic errors in anatomical pathology. METHODS The cross-sectional descriptive study was conducted at the Department of Pathology of a tertiary care hospital in Lahore, Pakistan, from September, 2016, to January, 2017, and comprised surgical pathology specimens. Errors were noted across the pre-microscopic process. Defects per million opportunities were calculated to determine sigma metric value in every step, from requisition to slide preparation. Root cause analysis was applied to the process of histology preparation to identify the root cause of each previously identified problem using Eindhoven classification. All errors were recorded on a pre-designed proforma. RESULTS There were 2420 specimens. While errors were encountered in all phases of the pre-microscopic process, but the (G6 n=1085, 44.83%), followed by requisition (R3 n=893, 36.9%) and cover slipping (C1 n=776, 32.06%). CONCLUSIONS Development of standard procedures and protocols with staff training is likely to help in controlling the errors.OBJECTIVE To determine the frequency of factors related to hypertension in a peri-urban community. METHODS It was a cross-sectional survey conducted from January to August, 2016, in Nain Sukh, Sheikhupura, near Lahore comprised household individuals of either gender aged 15-69 years. Data was collected through interviews by using a structured questionnaire focussing on socio-demography, history and factors associated with hypertension, like body mass index and lifestyle modifications. Hypertensive patients were identified by using clinical and medication history. SPSS 21 was used to analyse data. RESULTS Of the 1080 subjects, 871(80.6%) were females and 209(19.4%) were males. The overall mean age was 33.5±14 years. Hypertension was found in 307(28.4%) subjects. Hypertension was significantly associated with lifestyle modification factors, like weight reduction, reduction in salt intake and smoking cessation (p less then 0.05), and with body mass index categories (p less then 0.05). CONCLUSIONS Hypertension was found to be significantly high among overweight and obese participants, especially females.OBJECTIVE To translate and adapt the children's Perception of Parents Scale in Urdu language, and to determine its psychometric properties. METHODS The study was conducted in schools from different areas of Karachi (such as Happy Palace Grammar School, Beacon Askari School, The Educators, and Clifton Grammar School) from October, 2017 to March, 2018. The first phase of the study was conducted from January, 2017 to September, 2017. In the first phase, Perception of Parents Scale children version was forward and backward translated in consultation with experts and a final version was prepared and its reliability was assessed through Cronbach's alpha and test-retest reliability. Construct validity was evaluated by using the Urdu versions of standardised scales. In the second phase, the Urdu version of the scale was administered on secondary school students aged 12-16 from October, 2017, to March, 2018, in different areas of the city. Data was analysed using SPSS 20. RESULTS Of the758 subjects, 383(50.5%) were boys and 375(49.5%) were girls. The overall mean age was 13.57±1.24 years. Cronbach's alpha values for the four subscales were mother involvement 0.592, mother autonomy support 0.777, father involvement 0.653, and father autonomy support 0.717. Test-retest values were 0.803, 0.791, 0.874, and 0.845 respectively. CONCLUSIONS The Urdu version of Perception of Parents Scale children version was found to be a reliable and valid instrument.Objective To determine the effects of education on knowledge, attitude and practice status regarding cervical cancer, its prevention and screening among registered nurses working at tertiary care hospitals. METHODS The quasi-experimental study was conducted in 2016(15th June-15th July) at Civil Hospital, Karachi, and Dow University of Health Sciences, Karachi, and comprised registered nurses enrolled through non-probability convenience sampling. Baseline demographic characteristics and knowledge, attitude and practice levels of the nurses was gathered using a self-structured pretested and validated questionnaire. An education session on, "prevention and screening of cervical cancer" was conducted and its effectiveness was determined using the same questionnaire post-intervention. The difference in pre- and post-intervention values were determined. P0.05). The difference in knowledge scores were significant in all age groups, marital status, work experience and education (p less then 0.05 each). CONCLUSIONS There was a highly significant impact of education on the knowledge level of the subjects.

Quietdesert8

08/30/2024

Our vectorization approach reduces memory consumption by orders of magnitude, enabling real-time visualization performance. https://www.selleckchem.com/products/Amprenavir-(Agenerase).html Different types of interactive visualizations are demonstrated to show the effectiveness of our technique, which could help further research on quantum turbulence.Human-in-the-loop topic modeling allows users to explore and steer the process to produce better quality topics that align with their needs. When integrated into visual analytic systems, many existing automated topic modeling algorithms are given interactive parameters to allow users to tune or adjust them. However, this has limitations when the algorithms cannot be easily adapted to changes, and it is difficult to realize interactivity closely supported by underlying algorithms. Instead, we emphasize the concept of tight integration, which advocates for the need to co-develop interactive algorithms and interactive visual analytic systems in parallel to allow flexibility and scalability. In this paper, we describe design goals for efficiently and effectively executing the concept of tight integration among computation, visualization, and interaction for hierarchical topic modeling of text data. We propose computational base operations for interactive tasks to achieve the design goals. To instantiate our concept, we present ArchiText, a prototype system for interactive hierarchical topic modeling, which offers fast, flexible, and algorithmically valid analysis via tight integration. Utilizing interactive hierarchical topic modeling, our technique lets users generate, explore, and flexibly steer hierarchical topics to discover more informed topics and their document memberships.In this paper, we investigate the importance of phase for texture discrimination and similarity estimation tasks. We first use two psychophysical experiments to investigate the relative importance of phase and magnitude spectra for human texture discrimination and similarity estimation. The results show that phase is more important to humans for both tasks. We further examine the ability of 51 computational feature sets to perform these two tasks. In contrast with the psychophysical experiments, it is observed that the magnitude data are more important to these computational feature sets than the phase data. We hypothesise that this inconsistency is due to the difference between the abilities of humans and the computational feature sets to utilise phase data. This motivates us to investigate the application of the 51 feature sets to phase-only images in addition to their use on the original data set. This investigation is extended to exploit Convolutional Neural Network (CNN) features. The results show that our feature fusion scheme improves the average performance of those feature sets for estimating humans' perceptual texture similarity. The superior performance should be attributed to the importance of phase to texture similarity.Edge detection is one of the most fundamental operations in the field of image analysis and computer vision as a critical preprocessing step for high-level tasks. It is difficult to give a generic threshold that works well on all images as the image contents are totally different. This paper presents an adaptive, robust and effective edge detector for real-time applications. According to the two-dimensional entropy, the images can be clarified into three groups, each attached with a reference percentage value based on the edge proportion statistics. Compared with the attached points along the gradient direction, anchor points were extracted with high probability to be edge pixels. Taking the segment direction into account, these points were then jointed into different edge segments, each of which was a clean, contiguous, 1-pixel wide chain of pixels. Experimental results indicate that the proposed edge detector outperforms the traditional edge following methods in terms of detection accuracy. Besides, the detection results can be used as the input information for post-processing applications in real-time.Obtained by wide band radar system, high resolution range profile (HRRP) is the projection of scatterers of target to the radar line-of-sight (LOS). HRRP reconstruction is unavoidable for inverse synthetic aperture radar (ISAR) imaging, and of particular usage for target recognition, especially in cases that the ISAR image of target is not able to be achieved. For the high-speed moving target, however, its HRRP is stretched by the high order phase error. To obtain well-focused HRRP, the phase error induced by target velocity should be compensated, utilizing either measured or estimated target velocity. Noting in case of under-sampled data, the traditional velocity estimation and HRRP reconstruction algorithms become invalid, a novel HRRP reconstruction of high-speed target for under-sampled data is proposed. link2 The Laplacian scale mixture (LSM) is used as the sparse prior of HRRP, and the variational Bayesian inference is utilized to derive its posterior, so as to reconstruct it with high resolution from the under-sampled data. Additionally, during the reconstruction of HRRP, the target velocity is estimated via joint constraint of entropy minimization and sparseness of HRRP to compensate the high order phase error brought by the target velocity to concentrate HRRP. Experimental results based on both simulated and measured data validate the effectiveness of the proposed Bayesian HRRP reconstruction algorithm.Semantic segmentation is a key step in scene understanding for autonomous driving. Although deep learning has significantly improved the segmentation accuracy, current highquality models such as PSPNet and DeepLabV3 are inefficient given their complex architectures and reliance on multi-scale inputs. Thus, it is difficult to apply them to real-time or practical applications. On the other hand, existing real-time methods cannot yet produce satisfactory results on small objects such as traffic lights, which are imperative to safe autonomous driving. In this paper, we improve the performance of real-time semantic segmentation from two perspectives, methodology and data. Specifically, we propose a real-time segmentation model coined Narrow Deep Network (NDNet) and build a synthetic dataset by inserting additional small objects into the training images. The proposed method achieves 65.7% mean intersection over union (mIoU) on the Cityscapes test set with only 8.4G floatingpoint operations (FLOPs) on 1024×2048 inputs. Furthermore, by re-training the existing PSPNet and DeepLabV3 models on our synthetic dataset, we obtained an average 2% mIoU improvement on small objects.In recent years, hashing methods have been proved to be effective and efficient for large-scale Web media search. However, the existing general hashing methods have limited discriminative power for describing fine-grained objects that share similar overall appearance but have a subtle difference. To solve this problem, we for the first time introduce the attention mechanism to the learning of fine-grained hashing codes. Specifically, we propose a novel deep hashing model, named deep saliency hashing (DSaH), which automatically mines salient regions and learns semantic-preserving hashing codes simultaneously. DSaH is a two-step end-to-end model consisting of an attention network and a hashing network. Our loss function contains three basic components, including the semantic loss, the saliency loss, and the quantization loss. As the core of DSaH, the saliency loss guides the attention network to mine discriminative regions from pairs of images.We conduct extensive experiments on both fine-grained and general retrieval datasets for performance evaluation. Experimental results on fine-grained datasets, including Oxford Flowers, Stanford Dogs, and CUB Birds demonstrate that our DSaH performs the best for the fine-grained retrieval task and beats the strongest competitor (DTQ) by approximately 10% on both Stanford Dogs and CUB Birds. DSaH is also comparable to several state-of-the-art hashing methods on CIFAR-10 and NUS-WIDE.Mode coupled vibrations in a UHF ZnO thin film bulk acoustic resonator (FBAR) operating at thickness-extensional (TE) mode are studied by employing weak boundary conditions (WBCs), constructed based on Saint -Venant's principle and mixed variational principle in the piezoelectric theory. The frequency spectra, describing the lateral size-dependence of mode couplings between the main mode (TE) and undesirable eigen-modes, for clamped lateral edges are compared with the existing frequency spectra for free lateral edges to illustrate the boundary influence. The displacement and stress variations in FBAR volume are also presented to intuitionally understand and distinguish the difference of frequency spectra between these two different lateral edges, and then we discuss how to select outstanding lateral sizes to weaken the mounting effect. The frequency spectra predicted from our approximate weak boundary conditions are also compared with and agree well with those predicted by finite element method (FEM) using COMSOL, which proves the correctness and accuracy of our theoretical method. link3 These results indicate that the WBCs could have potentials in the valid predictions of lateral size-dependence of mode couplings in piezoelectric acoustic wave devices.Iterative model-based algorithms are known to enable more accurate and quantitative optoacoustic (photoacoustic) tomographic reconstructions than standard back-projection methods. However, three-dimensional (3D) model-based inversion is often hampered by high computational complexity and memory overhead. Parallel implementations on a graphics processing unit (GPU) have been shown to efficiently reduce the memory requirements by on-the-fly calculation of the actions of the optoacoustic model matrix, but the high complexity still makes these approaches impractical for large 3D optoacoustic datasets. Herein, we show that the computational complexity of 3D model-based iterative inversion can be significantly reduced by splitting the model matrix into two parts one maximally sparse matrix containing only one entry per voxel-transducer pair and a second matrix corresponding to cyclic convolution. We further suggest reconstructing the images by multiplying the transpose of the model matrix calculated in this manner with the acquired signals, which is equivalent to using a very large regularization parameter in the iterative inversion method. The performance of these two approaches is compared to that of standard back-projection and a recently introduced GPU-based model-based method using datasets from in vivo experiments. The reconstruction time was accelerated by approximately an order of magnitude with the new iterative method, while multiplication with the transpose of the matrix is shown to be as fast as standard back-projection.In this paper, we present a comprehensive review of the imbalance problems in object detection. To analyze the problems in a systematic manner, we introduce a problem-based taxonomy. Following this taxonomy, we discuss each problem in depth and present a unifying yet critical perspective on the solutions in the literature. In addition, we identify major open issues regarding the existing imbalance problems as well as imbalance problems that have not been discussed before. Moreover, in order to keep our review up to date, we provide an accompanying webpage which catalogs papers addressing imbalance problems, according to our problem-based taxonomy. Researchers can track newer studies on this webpage available at https//github.com/kemaloksuz/ObjectDetectionImbalance.