Miracle-dz/UniFAR-FTUs huggingface dataset:
Structural abnormalities in volume, thickness, and surface area in 22q11.2 microdeletion syndrome: Relationship with psychotic symptoms.

Results: Relative to controls, 22q11DS participants showed bilateral volumetric reductions in the inferior temporal cortex, fusiform gyrus, anterior cingulate, superior parietal cortex, and cuneus, which were driven by decreased SA in these regions. 22q11DS participants also had increased volumes, driven by increased CT, in bilateral insula regions. 22q11DS youth had increased CT in frontal regions, particularly middle frontal and medial orbitofrontal cortices. A pattern of age-associated cortical thinning was observed in typically developing controlsinbrain regionsassociatedwithvisualandsensory information-processing (i.e.,leftpericalcarinecortex and fusiform gyrus, right lingual and postcentral cortices). However, this relationship was disrupted in 22q11DS participants. Finally, correlational analyses revealed that increased CT in right medial orbitofrontal cortex was associated with increased positive symptom severity in 22q11DS. Conclusion: Differential disruptions of CT and SA in distinct cortical regions in 22q11DS may indicate abnormalities in distinct developmental neural processes. Further, neuroanatomic abnormalities in medial frontal brain structures disproportionately affected in idiopathic schizophrenia were associated with psychotic symptom severity in 22q11DS youth, suggesting that disrupted biological processes in these cortical regions may underlie development of psychotic symptoms, both in 22q11DS and in the broader population.
Isolated Digit Recogntion using Mathematical Tool based on Hidden Markov Model

-The work presented here describes the use of Mathematical tool like HTK (Hidden Markov Model Toolkit) for recognition of English isolated digits. Two different databases are used here which comprise of audio recordings for the English language isolated digits. Digits used are ZERO to NINE. First database is a standard CUAVE database (36 speakers, each spoken 10 words) and other database is self-recorded sample files of students of Engineering. The system has been implemented for speaker dependent and independent way, corresponding comparison has been made. For every individual digit, separate HMM has been created. It has been trained many times and tested against every other digit to check the every possibility of recognition/ duplication. Further this system can be used for continuous digit recognition also and one can go for sentence recognition using database like TIMIT.
Therapeutic Bene ﬁ t of Selective Inhibition of p110 a PI3-Kinase in Pancreatic Neuroendocrine Tumors

Purpose: Mutations in the PI3K pathway occur in 16% of patientswithpancreaticneuroendocrinetumors(PanNETs),whichsuggeststhatthesetumorsareanexcitingsettingforPI3K/AKT/ mTOR pharmacologic intervention. Everolimus, an mTOR inhibitor, is being used to treat patients with advanced PanNETs. However,resistancetomTOR-targetedtherapyisemergingpartiallyduetothelossofmTOR-dependentfeedbackinhibitionofAKT.In contrast, the response to PI3K inhibitors in PanNETs is unknown. Experimental Design: In the current study, we assessed the frequency of PI3K pathway activation in human PanNETs and in RIP1-Tag2 mice, a preclinical tumor model of PanNETs, and we investigated the therapeutic ef ﬁ cacy of inhibiting PI3K in RIP1-Tag2 mice using a combination of pan (GDC-0941) and p110 a selective (GDC-0326) inhibitors and isoform-speci ﬁ c PI3K kinase-dead – mutant mice. Results: Human and mouse PanNETs showed enhanced pAKT, pPRAS40, and pS6 positivity compared with normal tissue. Although treatment of RIP1-Tag2 mice with GDC-0941 led to reduced tumor growth with no impact on tumor vessels, the selective inactivation of the p110 a PI3K isoform, either genetically or pharmacologically, reduced tumor growth as well as vascular area. Furthermore, GDC-0326 reduced the incidence of liver and lymph node metastasis compared with vehicle-treated mice. We also demonstrated that tumor and stromal cells are implicated in the antitumor activity of GDC-0326 in RIP1-Tag2 tumors. Conclusion: Our data provide a rationale for p110 a -selective interventioninPanNETsandunravelanewfunctionofthiskinase in cancer biology through its role in promoting metastasis. Clin Cancer Res; 1 – 13. (cid:2) 2016 AACR. PanNETsareheterogeneoustumors,whichhascomplicated the design of targeted therapies. By using a preclinical mouse modelofPanNET,wereport hereonanewtherapytotreat this malignancy, namely selective inhibition of the class I p110 a PI3K isoform, and demonstrate that targeting this isoform inhibits tumor progression and metastasis. This is particularly relevant, given that isoform-selective PI3K inhibitors are likely to exhibit lower toxicity compared with pan-PI3K inhibitors, and therefore higher drug doses that achieve complete inhibition of the pathway are expected to be tolerated. We also observe that p110 a signaling regulates tumor cell dissemination, which provides a signi ﬁ cant advance in understanding the role of PI3K signaling in cancer and opens new therapeutic opportunities for agents targeting this pathway.
The 2MASS Large Galaxy Atlas

We present the largest galaxies as seen in the near-infrared (1–2 μm), imaged with the Two Micron All Sky Survey (2MASS), ranging in angular size from 1′ to 1. °5. We highlight the 100 largest in the sample. The galaxies span all Hubble morphological types, including elliptical galaxies, normal and barred spirals, and dwarf and peculiar classes. The 2MASS Large Galaxy Atlas provides the necessary sensitivity and angular resolution to examine in detail morphologies in the near-infrared, which may be radically different from those in the optical. Internal structures such as spirals, bulges, warps, rings, bars, and star formation regions are resolved by 2MASS. In addition to large mosaic images, the atlas includes astrometric, photometric, and shape global measurements for each galaxy. A comparison of fundamental measures (e.g., surface brightness, Hubble type) is carried out for the sample and compared with the Third Reference Catalogue. We further showcase NGC 253 and M51 (NGC 5194/5195) to demonstrate the quality and depth of the data. The atlas represents the first uniform, all-sky, dust-penetrated view of galaxies of every type, as seen in the near-infrared wavelength window that is most sensitive to the dominant mass component of galaxies. The images and catalogs are available through the NASA/IPAC Extragalactic Database and Infrared Science Archive and are part of the 2MASS Extended Source Catalog.
This is a repository copy of Case-mix analysis and variation in rates of non-surgical treatment of older women with operable breast cancer

Title: mix does not fully explain variation in rates of non-surgical treatment of older women with operable breast cancer. Abstract: Introduction: Non-surgical management of older women with ER positive, operable breast cancer is common in the UK with up to 40% of over 70s receiving primary endocrine therapy. Whilst this may be appropriate for frailer patients, for some it may result in treatment failure, contributing to the poor outcomes seen in this age group. Wide variation in the rates of non-operative management of breast cancer in older women exists across the UK. Case mix may explain some of this variation in practice. Methods : Data from two UK regional cancer registries were analysed to identify whether variation in treatment observed between 2002 and 2010 at hospital and clinician level persisted following adjustment for case mix. Expected case-mix adjusted surgery rates were derived by logistic regression using the variables age, proxy Charlson Co-morbidity Score, deprivation quintile, method of cancer detection, tumour size, stage, grade and nodal status. Results : Data on 17154 women over 70 with ER+ operable breast cancer were analysed. There was considerable variation in rates of surgery at both hospital and clinician level. Despite adjusting for case mix, this variation persisted at hospital level , although not at clinician level. Conclusion : This study demonstrates variation in selection criteria for older women for operative treatment for early breast cancer, meaning that some older women may be under or over treated and may partly explain the inferior disease outcomes associated with this age group. It emphasises the urgent need for evidence based guidelines for treatment selection criteria in older women with breast cancer. The present study aimed to analyse UK practice in older women with operable, ER-positive breast cancer to establish whether the variation observed at hospital and clinician level persists following adjustment for the patient and tumour characteristics of the cases managed.
Fruits and Vegetables Consumption and Risk of Stroke A Meta-Analysis of Prospective Cohort Studies Clinical

to quantitatively assess the effect of fruits and vegetables consumption on the risk of stroke. conducted a meta-analysis to summarize evidence from prospective cohort studies about the association of fruits and vegetables consumption with the risk of stroke. Methods studies were identified a search of and PubMed databases to January 2014. Study-specific relative risks with 95% confidence intervals were pooled using a random-effects model. Dose–response relationship was assessed by restricted cubic spline. Results —Twenty prospective cohort studies were included, involving 16 981 stroke events among 760 629 participants. The multivariable relative risk (95% confidence intervals) of stroke for the highest versus lowest category of total fruits and vegetables consumption was 0.79 (0.75–0.84), and the effect was 0.77 (0.71–0.84) for fruits consumption and 0.86 (0.79–0.93) for vegetables consumption. Subgroup and meta-regression showed that the inverse association of total fruits and vegetables consumption with the risk of stroke was consistent in subgroup analysis. Citrus fruits, apples/pears, and leafy vegetables might contribute to the protection. The linear dose–response relationship showed that the risk of stroke decreased by 32% (0.68 [0.56–0.82]) and 11% (0.89 [0.81–0.98]) for every 200 g per day increment in fruits consumption ( P for nonlinearity=0.77) and vegetables consumption ( P for nonlinearity=0.62), respectively. Conclusions —Fruits and vegetables consumption are inversely associated with the risk of stroke. ( Stroke . 2014;45:1613-1619.) from meta-regression was calculated with a permutation test of 1000 to control the spurious findings. Study quality was assessed using the 9-star Newcastle–Ottawa scale (http:// www.ohri.ca/programs/clinical_epidemiology/oxford.asp). The results for both sexes were included as 2 separate results if the total result was not reported within a cohort. A 2-stage random-effects dose–response meta-analysis was per- formed to examine a potential nonlinear relationship. 23 Briefly, a restricted cubic spline model with 3 knots at percentiles 25%, 50%, and 75% of the distribution of fruits and vegetables consumption was estimated, and then the 2 regression coefficients (3 knots minus 1) and the variance/covariance matrix within each study were combined in a multivariate random-effects meta-analysis. The average serving was calculated as 77 g for vegetables and 80 g for fruits. 24 A P value for nonlinearity was calculated by testing the null hypothesis that the coefficient of the second spline is equal to 0. Stata 12.0 was used, and P <0.05 was considered statistically significant.
A Deep Learning based Advanced Gait Detection

A gait is a biometric sign that people use to provide visual verification of viewing. Distinctive highlights need more than one movement cycle. In Gait Energy Image (GEI), for example, typical images of a frame with more than one cycle motion are analyzed. The unique stride highlights the required movement of an individual strolling more than one complete walking cycle. For instance, in Gait Energy Image (GEI), normal outline pictures of more than one entire walk cycle are processed. Be that as it may, there may be an incomplete step cycle in which information is accessible due to impediments. This research work has designed and developed a model for implementing stride arrangement and profound learning strategies. A separate walk dataset is used in our trial. The walk marks are removed from the Gait Energy Image (GEI) using the Convolution Neural Network (CNN). The classifier proposed here for grouping human gait postures is Mobile Net. Finally, the proposed methodology is evaluated on the OULP step dataset, affirming that the proposed design effectively reproduces total GEI even from the outrageously deficient walk cycles.
Design and implementation of power efficient clock gated dual-port SRAM

Synchronous clock gated Dual-port RAM has been designed in this paper. To increase the design’s power, a negative latch-based clock gating approach was used. On Xilinx Vivado ML Edition, the design was implemented on an XC7Z010ICLG225-1L device with a - 1-speed grade and the Zynq-7000 FPGA family. The Verilog HDL was used to create the design. A 2-bit AND gate is used to realize clock gating which takes the clock and enable signal as input thus clock become only high when enable is high which reduces the switching frequency and thus power consumption by the clock is reduced as power is directly proportional to (frequency)2. Apart from clock gating, the SRAM is Dual-Port based, allowing multiple reads or writes to occur simultaneously, or at approximately the same time, unlike single-port RAM, which permits only one access at a given time. The power consumption value of the clock signal with clock gating at 100 GHz is 627.61 mW as compared to power consumption without clock gating which is 1405 mW, at a clock frequency of 100 GHz, a 55 percent reduction in total clock power was achieved. Xilinx Vivado ML Edition’s XPower Analyzer tool was used to calculate the device’s power.
Friend Recommendation System using Image Encryption and Deep learning

The recommendation system functions similarly to a content filtering system, providing information depending on the preferences and behavior of the user. People use image sharing platforms such as Facebook, LinkedIn, and Instagram to share photographs of various elements to convey their sentiments with linked peers. As image sharing has been increasingly popular among individuals in recent years, it plays an important part in our daily lives. However, because of photo leaks and misuse, people are becoming increasingly concerned about their privacy. Encrypting photographs before publishing to social media is a better approach but decrypting the images and then searching for comparable images is computationally costly. The prior model advocated encrypting pictures using AES encryption and classifying them with deep autoencoders which is only a 2-step compression technique and takes quite more time for classifying. We provide a feasible privacy-protected friend recommendation system in proposed model by encrypting images using the Gaussian blur technique and a deep learning strategy for feature extraction and image classification for user recommendation. For training the dataset, the deep learning system utilizes the Keras model with CNN method, and a new model is generated from the features extracted from the blurred images. After that, the test dataset is compared to the model developed for similar image prediction. The accuracy measurements used to plot the graph are val acc and val loss. The accuracy result for the original image is 91.8%, while the accuracy result for the blurred image is 86.2% percent, demonstrating that our model is highly efficient and results in lower data loss.
Machine Learning approach for Software Effort Estimation using Combination of Principal Component Regression and Neural Network

For software projects that deploy vital tasks, it is difficult to estimate the effort of a project. In order to anticipate a few hours of labour effort (either time or personal) to deploy or maintain the software programme, software measurement points must be used. It is difficult to predict the behavior of an application that is engaged in software development during the initial phases of the effort. The hybrid model technique is used in this paper. It is necessary to apply Supervised Learning techniques in the Machine Learning algorithm. It is further subdivided into different types, such as linear regression, logistic regression, SVM (Support Vector Machine) algorithm, Naive Bayes algorithm, PCR(Principal Component Regression) algorithm, (Neural Network)NNET algorithm, KNN (K-Nearest Neighbour) algorithm, K-means, Random Forest algorithm, Dimensionality reduction algorithms, Gradient boosting algorithm, and Ada Boosting algorithm, to name a few examples. PCR algorithm and the nnet algorithm have been utilised for hybrid method, as shown above. Predictions from JM1/Software have been used to create this data collection. With 10886 unique instances and 18 unique traits, this is a very large amount. Metrics for evaluating this system include Mean Absolute Error (MAE), Mean Relative Error (MRE), Mean Magnitude of Relative Error (MMRE), Percentage of Predictive Accuracy (PRED), and R-squared. Compared to single model approaches based on machine learning algorithms techniques, the proposed hybrid using principal component regression and neural networks produced the best results, as demonstrated by the results.
Optimized 6x6 Optical Router for Three Dimensional Optical Networks-on-Chip

The interconnection network is very influential in Multiprocessor system-on-chip (MPSoC) performance. Due to low power efficiency and high latency, conventional interconnects are replaced by electrical networks on-chip (ENoC). However, ENoCs cannot gratify the bandwidth, latency and loss requirements within the available power budget of optical integrated circuits. The reasons being restricted bandwidth, extended delay, and reasonably high power consumption. So, ENoC are being replaced by optical networks-on-chip (ONoC). ONoC has emerged as a promising substitute to provide greater bandwidth, low latency and low power ingestion in MPSoCs. Number of cores required on-chip is increasing which leads to demand of multilayer multi-core processors. Three dimensional (3D) ONoC has become essential for such multilayer multi-core processors. For 3D ONoC, in this paper we have proposed 6x6 non-blocking optical router using micro-ring resonator (MRR) with less number of waveguide crossings and waveguide bendings. Phoenix software is used to simulate proposed optical router. Insertion loss of proposed optical router is lowest among existing non-blocking optical routers of 3D ONoC.
Deﬁning Domestic Environmental Experience for Occupants’ Mental Health and Wellbeing

: This study was stipulated by today’s limited living conditions of middle income households in Bangladesh who have economic constraints that contribute to hindering improvement of their existing domestic settings that may a ﬀ ect occupants’ mental health and wellbeing. The design of domestic living environments tend to inﬂuence occupants’ emotions, feelings and moods. Thus, domestic environmental experiences need to be examined and incorporated into architectural design decisions. To understand the notion of such experiences, this study reviewed literatures concerning the related domains extensively. This study found the signiﬁcant impact of domestic environments on human perceptions. Each design of domestic settings a ﬀ ects occupants’ emotional responses positively or negatively. Through this study, the term domestic environmental experience was deﬁned as users’ experiences of cognitive perceptions and physical responses to their domestic built environment. In addition, it led to proposing the composition of domestic environmental experiences that need to be correlated with architectural design solutions. Nonetheless, this study did not examine the correlation where the emerging notion of Environmental Experience Design (EXD) may serve as the mediator. Accordingly, this new horizon of EXD research needs to be explored further with the aim to improve domestic built environments in Bangladesh which were the original driver of this research.
The location and kinematics of the emission line regions in active galactic nuclei

This thesis contains the results from a study of the optical emission lines of various samples of active galactic nuclei (AGN). We have used three separate techniques to determine the precise kinematics and the relative location of the emission line regions of AGN: a detailed study of a small sample (10) of AGN, a study of the general emission line properties of two larger samples, and the interpretation of the results from observations using numeric photoionisation models. Although we present results on both the broad line and narrow line regions of AGN the main drive behind this work is the study of the poorly defined intermediate line region using emission from highly ionised species (high ionisation emission lines). Our results derived from observations indicate that a significant proportion of the emission from these species is produced within the central void of the putative dusty torus and that emission from more highly ionised species increases at radii closer to the central engine of the AGN. Furthermore, we find strong evidence that the intermediate region traced by these high ionisation emission lines is generally outflowing from the central engine but there is little evidence of any significant acceleration or deceleration of this material between the inner and outer regions traced by the higher and lower ionisation lines, respectively. Our results derived from numerical photoionisation codes support a model in which this outflowing material responsible for the high ionisation line emission is launched from the inner edge of the the dusty torus.
Reconﬁgurable Distributed Power Electronics Technique for Solar PV Systems

: A reconﬁguration technique using a switched-capacitor (SC)-based voltage equalizer differential power processing (DPP) concept is proposed in this paper for photovoltaic (PV) systems at a cell/subpanel/panel-level. The proposed active diffusion charge redistribution (ADCR) architecture increases the energy yield during mismatch and adds a voltage boosting capability to the PV system under no mismatch by connected the available PV cells/panels in series. The technique performs a reconﬁguration by measuring the PV cell/panel voltages and their irradiances. The power balancing is achieved by charge redistribution through SC under mismatch conditions, e.g., partial shading. Moreover, PV cells/panels remain in series under no mismatch. Overall, this paper analyzes, simulates, and evaluates the effectiveness of the proposed DPP architecture through a simulation-based model prepared in PSIM. Additionally, the effectiveness is also demonstrated by comparing it with existing conventional DPP and traditional bypass diode architecture.
A regularity theory for multiple-valued Dirichlet minimizing maps

This paper discusses the regularity of multiple-valued Dirichlet minimizing maps into the sphere. It shows that even at branched point, as long as the normalized energy is small enough, we have the energy decay estimate. Combined with the previous work by Chun-Chi Lin, we get our first estimate that m-2 dimensional Hausdorff measure of singular set is zero. Furthermore, by looking at the tangent map and using dimension reduction argument, we show that the singular set is at least of codimension 3.