Miracle-dz/UniFAR-FTUs huggingface dataset:
An Adaptive Level Set Evolution for the Analysis of Ventricle Variations in Alzheimer MR Images

: Alzheimer’s disease (AD) is a common form of dementia and it is fatal neurogenerative disorder resulting in atrophy of brain regions.MR imaging is a very important tool in diagnosing AD. The enlargement of ventricles due to neuronal loss is a significant characteristic of AD. In this work, ventricular expansion in Axial, Saggital and Coronal views of MR images is analyzed by segmenting the ventricles. Due to intensity inhomogeneties segmentation techniques are to be more sensitive to capture variations in the structural boundaries. Intensity inhomogeneties may cause considerable difficulties in image segmentation. In order to overcome this difficulty we propose a region based active contour model that draws upon intensity information in local regions at a controllable scale. A data fitting energy is defined in terms of a contour and this energy is incorporated into level set formulation. Due to kernel function intensity information in local regions is extracted to guide the motion of the contour. The size and shape of the ventricles in AD subjects are apparently enlarged in the axial view than in the sagittal and coronal views. Segmentation of dilated ventricle is a key step in the diagnosis of AD .
Prevalence of C282Y and H63D mutations in the HFE gene in patients from São Paulo and Southern Brazil

Hereditary hemochromatosis (HH) is an autosomal recessive disorder caused by mutations in the HFE gene; it is characterized by the risk of iron overload. C282Y and H63D are the most associated mutations in HH. This study aimed to determine the frequency of mutations in the south of Brazil and Sao Paulo. It used the real-time polymerase chain reaction (PCR) technique and the results collected from Genolab data. In 90 individuals, 46.67% had at least one of the mutations for HH. There is a high prevalence of these mutations in both populations, therefore searching for patients under clinical suspicion is recommended.
Cloud computing: cloud adoption in professional practice

Cloud computing creates new opportunities in the era of technological advancement specifically to Malaysia. This paper will present and discuss an overview of cloud computing and how the implementation of cloud computing impact an organization and an industries. There are many sectors can get the benefits when adopting the cloud computing services, including education, healthcare, agriculture, tourism, banking, and the automotive industry. In the paper, we briefly highlight certain industry which cloud adoption can significantly enhance system efficiency, effectiveness, and reliability.
Functional DTI in Voluntarily Contracted Human Calf Muscles Using an MR Compatible Ergometer

Introduction Knowledge about the 3D architecture of muscles is important, first, for deeper understanding of contraction dynamics and muscle deformation, and second, as a prerequisite for the development of realistic finite-element muscle models. Diffusion tensor imaging (DTI) provides valuable information about muscle architecture in both normal and diseased states [1]. So far, most DT acquisitions in skeletal muscles relied on SE-EPI sequences, which are used to determine DTI changes in passively moved muscles [1,2]. Recent studies including measurements in voluntarily contracted calf muscles did not use ergometers that provide force or movement monitoring during the exercise and, thus, may be limited by varying muscle performance [3,4]. Therefore, in the present work we introduce an MR compatible ergometer with monitoring and visual feedback options to perform DTI measurements during voluntary muscle contractions at different joint angles. In addition, we employed a pulse sequence for DTI, which is based on a stimulated echo acquisition mode (STEAM) preparation in combination with a FLASH readout [5].
Program Synthesis Through Reinforcement Learning Guided Tree Search

Program Synthesis is the task of generating a program from a provided specification. Traditionally, this has been treated as a search problem by the programming languages (PL) community and more recently as a supervised learning problem by the machine learning community. Here, we propose a third approach, representing the task of synthesizing a given program as a Markov decision process solvable via reinforcement learning(RL). From observations about the states of partial programs, we attempt to find a program that is optimal over a provided reward metric on pairs of programs and states. We instantiate this approach on a subset of the RISC-V assembly language operating on floating point numbers, and as an optimization inspired by search-based techniques from the PL community, we combine RL with a priority search tree. We evaluate this instantiation and demonstrate the effectiveness of our combined method compared to a variety of baselines, including a pure RL ablation and a state of the art Markov chain Monte Carlo search method on this task.
Green Synthesis of Zinc Oxide (ZnO) Nanoparticles Using Ocimum Tenuiflorum Leaves

In this research paper, we discussed on the synthesis and characterization of ZnO nanoparticles by green synthesis method. Here we utilized the leaves of Ocimum Tenuiflorum plant as reducing agent in the synthesis of ZnO nanoparticles. Green synthesis method avoids inert gases, high pressure, laser radiation, high temperature, toxic chemicals etc. as compared to conventional method like sol-gel technique method, laser ablation method, solvothermal method, inert gas condensation method, chemical reduction method etc. Prepared ZnO nanoparticles were characterized by X-Ray diffraction (XRD), scanning electron microscope (SEM) technique, Fourier Transform Infrared Spectroscopy (FTIR). The average particle are calculated as 13.86 nm by using Scherrer’s formula.
Impaired Glutamatergic and GABAergic function at Early Age in APPswe-PS 1 dE 9 Mice : Implications for Preclinical Diagnosis of Alzheimer ’ s Disease

INTRODUCTION: Alzheimer’s disease (AD) is one of the very common neurodegenerative disorders, characterized by neuritic plaques and neurofibrillary tangles marked with loss of cognitive functions and memory impairment. As there is no effective treatment available for AD, a paradigm shift in AD research is towards the early diagnosis and interventions for delay of the disease. APP-PS1 mice exhibit increase in amyloid plaques with age and more closely match the neurochemical profile and pathology of human AD. Moreover, these mice show occasional deposits of amyloid plaques at the age of 5-6 months without significant memory impairment and neuronal losscharacteristics typical of AD pathology at an early stage of the disease. The objective of the present study is to investigate neuronal metabolism in APP-PS1 mice at 6 month to find out biomarker for the early diagnosis of AD.
Protein Expression and Codon 72 Polymorphism of TP53 Gene in Triple Negative Breast Cancer

A subgroup of tumor that has received attention is triple-negative breast cancer (TNBC), which presents phenotype of negative estrogen receptor, negative progesterone receptor and has no overexpression of HER2. TP53 acts as a tumor suppressor limiting the proliferation of damaged cells. A polymorphic site (rs1042522) of TP53 encodes either an arginine or a proline amino acid, but its biological significance remains unclear. This study aimed to investigate this variant and its expression in search for a possible involvement in TNBC susceptibility and clinical outcome. Genetic polymorphism was evaluated in 50 patients and 115 controls by PCR based methodology and immunohistochemistry was done with monoclonal antibody. Case-control study showed no positive or negative association (OR= 0.95; CI95%= 0.48-1.89). Comparison of genotypes and clinical outcome showed no significant results. Despite most of patients presented p53 positive staining by immunohistochemistry, there was no significant association in relation to prognostic parameters. Results demonstrated a lack of association between codon 72 polymorphism, susceptibility and prognosis of TNBC. Immunohistochemistry analysis should be done more carefully, since most of the patients had the somatic mutation of p53, which could be an indicator of prognostic value in TNBC.
Carbon limitation, stem growth rate and the biomechanical cause of Corner’s rules

Background and aims Corner's rules describe a global spectrum from large-leaved plants with thick, sparingly branched twigs with low-density stem tissues and thick piths to plants with thin, highly branched stems with high-density stem tissues and thin piths. The hypothesis was tested that, if similar crown areas fix similar amounts of carbon regardless of leaf size, then large-leaved species, with their distantly spaced leaves, require higher stem growth rates, lower stem tissue densities and stiffnesses, and therefore thicker twigs. Methods Structural equation models were used to test the compatibility of this hypothesis with a dataset on leaf size, shoot tip spacing, stem growth rate and dimensions, and tissue density and mechanics, sampling 55 species drawn from across the angiosperm phylogeny from a morphologically diverse dry tropical community. Key results Very good fit of structural equation models showed that the causal model is highly congruent with the data. Conclusions Given similar amounts of carbon to allocate to stem growth, larger-leaved species require greater leaf spacing and therefore greater stem extension rates and longer stems, in turn requiring lower-density, more flexible, stem tissues than small-leaved species. A given stem can have high resistance to bending because it is thick (has high second moment of area I) or because its tissues are stiff (high Young's modulus E), the so-called E-I trade-off. Because of the E-I trade-off, large-leaved species have fast stem growth rates, low stem tissue density and tissue stiffness, and thick twigs with wide piths and thick bark. The agreement between hypothesis and data in structural equation analyses strongly suggests that Corner's rules emerge as the result of selection favouring the avoidance of self-shading in the context of broadly similar rates of carbon fixation per unit crown area across species.
Demographics and the correlation between irrational parenthood cognitions and marital relationship quality in infertile women in Zanjan province in 2016.

PURPOSE The study determined the correlation between Irrational Parenthood Cognitions (IPC) and marital quality by demographic variables in infertile women. METHODS A correlational study with a census method was conducted on all primary infertile women, who had a file in Zanjan, Iran. FINDINGS A 47% significant positive correlation was showed between IPC and marital quality (p < 0.001). The highest correlation was observed in the subsets of women aged 31-40 years, with high level of education, those at third socioeconomic classes, those with less than 10 years of married life, and women whose husband had no children from their previous marriage (all ps < 0.05). PRACTICE IMPLICATIONS Providing counseling services to women with primary infertility, especially high-risk women may help to reduce IPC and to improve marital quality.
A Review of Childhood Obesity Prevention Efforts among Evidence-Based Home Visiting Programs

Childhood obesity is a major health concern. A high body mass index (BMI) is associated with the onset of several chronic diseases and can impact physical, mental, and emotional health. Several lifestyle factors have played a role in the rising prevalence of obesity over recent decades, including poor diet and lack of physical activity. Previous obesity intervention efforts have focused on reversing obesity rather than addressing risk factors prior to weight gain. The evidence-base of best practices for childhood obesity prevention is weak, and few interventions have indicated long-term success on weight reduction and maintenance. Parents play a major role in influencing behaviors related to eating and exercise, thus home visiting programs may present an opportunity for addressing risk factors for obesity. Many of these programs aim to prevent adverse experiences in early childhood by working with parents and caregivers and have been successful in improving child outcomes. This setting has recently been explored in the context of childhood obesity prevention and research has indicated that such efforts may be effective. This project examines the extent to which childhood obesity is addressed among 8 evidence-based home visiting programs. These programs’ efforts are compared to expert recommendations for childhood obesity prevention and opportunities for future consideration are discussed. Finally, recommendations from the literature are made for integrating best practices for maintaining a healthy weight into home visiting programs. A Review of Childhood Obesity Prevention Efforts among Evidence-Based Home Visiting Programs by Olga Costa B.A., The University of Georgia A Capstone Submitted to the Graduate Faculty of Georgia State University in Partial Fulfillment of the Requirements for the Degree MASTER OF PUBLIC HEALTH ATLANTA, GEORGIA 30303
Multiscale Decomposition of Global Edge-Preserving for the High Dynamic Range Image Deepika

High Dynamic Range (HDR) imaging is an extent of increasing significance of display equipment still has Limited Dynamic Range (LDR). Multi-scale Decomposition image processing approaches have a fame of causing halo artifacts when passed down for range compression. The synthesized Standard Dynamic Range (SDR) image contains much more background analysis than any of the captured SDR image. The edge-preserving image decompositions accept analyzed image to be low contrast aberration. This paper suggests a new method of equalized analysis-mixture filters assign with bounded gain control to the sub-bands systems for disintegrating and regenerating images. The Gradient-domain based method on the resources of HVS for high dynamic range compression. Experimental outcomes on real images indicate that our method is exclusively emphatic at preserving and improving each details.
Patient Portal Use in Diabetes Management: Literature Review

Background Health information technology tools (eg, patient portals) have the potential to promote engagement, improve patient-provider communication, and enhance clinical outcomes in the management of chronic disorders such as diabetes mellitus (DM). Objectives The aim of this study was to report the findings of a literature review of studies reporting patient portal use by individuals with type 1 or type 2 DM. We examined the association of the patient portal use with DM-related outcomes and identified opportunities for further improvement in DM management. Methods Electronic literature search was conducted through PubMed and PsycINFO databases. The keywords used were “patient portal*,” “web portal,” “personal health record,” and “diabetes. ” Inclusion criteria included (1) published in the past 10 years, (2) used English language, (3) restricted to age ≥18 years, and (4) available in full text. Results This review included 6 randomized controlled trials, 16 observational, 4 qualitative, and 4 mixed-methods studies. The results of these studies revealed that 29% to 46% of patients with DM have registered for a portal account, with 27% to 76% of these patients actually using the portal at least once during the study period. Portal use was associated with the following factors: personal traits (eg, sociodemographics, clinical characteristics, health literacy), technology (eg, functionality, usability), and provider engagement. Inconsistent findings were observed regarding the association of patient portal use with DM-related clinical and psychological outcomes. Conclusions Barriers to use of the patient portal were identified among patients and providers. Future investigations into strategies that engage both physicians and patients in use of a patient portal to improve patient outcomes are needed.
Adaptation and Frontend Features to Improve Naturalness in Found-Data Synthesis

We compare two approaches for training statistical parametric voices that make use of acoustic and prosodic features at the utterance level with the aim of improving naturalness of the resultant voices – subset adaptation, and adding new acoustic and prosodic features at the frontend. We have found that the approach of labeling high, middle, or low values for a given feature at the frontend and then choosing which setting to use at synthesis time can produce voices rated as signiﬁcantly more natural than a baseline voice that uses only the standard contextual frontend features, for both HMM-based and neural network-based synthesis.
Risk Distribution and Validation of Data in Passport Data Analysis Using Cluster Analysis

: This paper presents a comprehensive statistical experiment to identify the sensitive office from the passport database. Data mining is the process of finding the meaningful patterns, correlations among dozens of fields that lie hidden within very large databases. The presented work focus on implementing different data mining approaches on passport database which is the primary data taken from passport offices. This paper combines two major approaches to provide profiling via clustering and validation of data using classification. According to defined approach, clustering is implemented to profile offices according to their risk identified. The design of experiments software named Weka Tool is used for making clusters using attributes place of issue and risk type dataset by using simple k means algorithm. With the simulation and analysis results, identify the sensitive centre which contribute to high risk score
Risk-Informed Mean Recurrence Intervals for Updated Wind Maps in ASCE 7-16.

ASCE 7 is moving toward adopting load requirements that are consistent with risk-informed design goals characteristic of performance-based engineering (PBE). ASCE 7-10 provided wind maps that correspond to return periods of 300, 700, and 1,700 years for Risk Categories I, II, and combined III/IV, respectively. The risk targets for Risk Categories III and IV buildings and other structures (designated as essential facilities) are different in PBE. The reliability analyses reported in this paper were conducted using updated wind load data to (1) confirm that the return periods already in ASCE 7-10 were also appropriate for risk-informed PBE, and (2) to determine a new risk-based return period for Risk Category IV. The use of data for wind directionality factor, Kd , which has become available from recent wind tunnel tests, revealed that reliabilities associated with wind load combinations for Risk Category II structures are, in fact, consistent with the reliabilities associated with the ASCE 7 gravity load combinations. This paper shows that the new wind maps in ASCE 7-16, which are based on return periods of 300, 700, 1,700, and 3,000 years for Risk Categories I, II, III, and IV, respectively), achieve the reliability targets in Section 1.3. 1.3 of ASCE 7-16 for nonhurricane wind loads.
Responses of Honey Bees to Lethal and Sublethal Doses of Formulated Clothianidin Alone and Mixtures

Abstract The widespread use of neonicotinoid insecticides has sparked concern over the toxicity risk to honey bees (Apis mellifera L. (Hymenoptera: Apidae)). In this study, feeding treatments with the clothianidin formulation at 2.6 ppb (residue concentration) or its binary mixtures with five representative pesticides (classes) did not influence on adult survivorship, but all treatments caused significantly lower body weight than controls. Most binary mixtures at residue levels showed minor or no interaction on body weight loss, and synergistic interaction was detected only from the mixture of clothianidin + λ-cyhalothrin. Chlorpyrifos alone and the mixture of clothianidin + chlorpyrifos significantly suppressed esterase (EST) activity, while most treatments of individual pesticides and mixtures had no effect on EST and glutathione S-transferase (GST) activities. However, ingestion of clothianidin at 2.6 ppb significantly enhanced P450 oxidase activity by 19%. The LC50 of formulated clothianidin was estimated at 0.53 ppm active ingredient, which is equivalent to 25.4 ng clothianidin per bee (LD50) based on the average sugar consumption of 24 μl per bee per day. In addition to mortality, ingestion of clothianidin at LC50 significantly reduced bee body weight by 12%. P450 activities were also significantly induced at 24 and 48 h in clothianidin-treated bees, while no significant difference was found in GST and EST activities. Further examinations revealed that the expression of an important CYP9q1 detoxification gene was significantly induced by clothianidin. Thus, data consistently indicated that P450s were involved in clothianidin detoxification in honey bees. Although the honey bee population in Stoneville (MS, United States) had sixfold lower susceptibility than other reported populations, clothianidin had very high oral toxicity to bees.
IgG Antibody 3D Structures and Dynamics

Antibodies are vital for human health because of their ability to function as nature’s drugs by protecting the body from infection. In recent decades, antibodies have been used as pharmaceutics for targeted therapy in patients with cancer, autoimmune diseases, and cardiovascular diseases. Capturing the dynamic structure of antibodies and characterizing antibody fluctuation is critical for gaining a deeper understanding of their structural characteristics and for improving drug development. Current techniques for studying three-dimensional (3D) structural heterogeneity and variability of proteins have limitations in ascertaining the dynamic structural behavior of antibodies and antibody-antigen complexes. Here, we review current techniques used to study antibody structures with a focus on the recently developed individual-particle electron tomography (IPET) technique. IPET, as a particle-by-particle methodology for 3D structural characterization, has shown advantages in studying structural variety and conformational changes of antibodies, providing direct imaging data for biomolecular engineering to improve development and clinical application of synthetic antibodies.
Image Embedding in QR Code

Quick Response (QR) code is a two dimensional barcode widely used in many applications such as manufacturing, advertising, retailing etc. QR code looks like a noisy structure. The appearance of QR code can be improved by embedding an image into the code. This work proposed a method where the appearance of QR code is composed of visually meaningful patterns selected by users. This work makes QR code from machine read only to a personalized form with human visual pleasing appearance. The image embedding in the QR code is not an easy task because embedded result should be decodable by standard decoding applications and can be applied to any color image with full area coverage. In this work QR code pixels are selected by genetic algorithm, then the selected pixels are encoded with the luminance values of the image.