Miracle-dz/UniFAR-FTUs huggingface dataset:
A Machine Learning Approach to Classifying Self-Reported Health Status in a Cohort of Patients With Heart Disease Using Activity Tracker Data

Constructing statistical models using personal sensor data could allow for tracking health status over time, thereby enabling the possibility of early intervention. The goal of this study was to use machine learning algorithms to classify patient-reported outcomes (PROs) using activity tracker data in a cohort of patients with stable ischemic heart disease (SIHD). A population of 182 patients with SIHD were monitored over a period of 12 weeks. Each subject received a Fitbit Charge 2 device to record daily activity data, and each subject completed eight Patient-Reported Outcomes Measurement Information Systems short form at the end of each week as a self-assessment of their health status. Two models were built to classify PRO scores using activity tracker data. The first model treated each week independently, whereas the second used a hidden Markov model (HMM) to take advantage of correlations between successive weeks. Retrospective analysis compared the classification accuracy of the two models and the importance of each feature. In the independent model, a random forest classifier achieved a mean area under curve (AUC) of 0.76 for classifying the physical function PRO. The HMM model achieved significantly better AUCs for all PROs (p < 0.05) other than Fatigue and Sleep Disturbance, with a highest mean AUC of 0.79 for the physical function-short form 10a. Our study demonstrates the ability of activity tracker data to classify health status over time. These results suggest that patient outcomes can be monitored in real time using activity trackers.
SGLT1 is required for the survival of triple‐negative breast cancer cells via potentiation of EGFR activity

Sodium/glucose cotransporter 1 (SGLT1), an essential active glucose transport protein that helps maintain high intracellular glucose levels, was previously shown to interact with epidermal growth factor receptor (EGFR); the SGLT1–EGFR interaction maintains intracellular glucose levels to promote survival of cancer cells. Here, we explore the role of SGLT1 in triple‐negative breast cancer (TNBC), which is the most aggressive type of breast cancer. We performed TCGA analysis coupled to in vitro experiments in TNBC cell lines as well as in vivo xenografts established in the mammary fat pad of female nude mice. Tissue microarrays of TNBC patients with information of clinical–pathological parameters were also used to investigate the expression and function of SGLT1 in TNBC. We show that high levels of SGLT1 are associated with greater tumour size in TNBC. Knockdown of SGLT1 compromises cell growth in vitro and in vivo. We further demonstrate that SGLT1 depletion results in decreased levels of phospho‐EGFR, and as a result, the activity of downstream signalling pathways (such as AKT and ERK) is inhibited. Hence, targeting SGLT1 itself or the EGFR–SGLT1 interaction may provide novel therapeutics against TNBC.
Regulation of dendrite morphology and excitatory synapse formation by zDHHC15

ABSTRACT Protein palmitoylation is the most common post-translational lipid modification in the brain and is mediated by a family of 24 zDHHC enzymes. There has been growing interest in zDHHCs due to mounting evidence that these enzymes play key roles in the development and function of neuronal connections, and the fact that a number of zDHHCs have been associated with neurodevelopmental and neurodegenerative diseases. Loss-of-function variants in several zDHHCs, including zDHHC15, have been identified in patients with intellectual disabilities; however, the function of zDHHC15 in the brain has not been well studied. Here, we demonstrate that knocking down zDHHC15 in primary rat hippocampal cultures reduces dendritic outgrowth and arborization, as well as spine maturation. Moreover, knockdown of zDHHC15 reduces palmitoylation of PSD-95 and its trafficking into dendrites, resulting in an overall decrease in the density of excitatory synapses being formed onto mutant cells. Summary: Disruption of zDHHC15 function in primary hippocampal cultures reduces dendritic outgrowth, spine maturation, excitatory synapse density and trafficking of PSD-95 into dendrites.
Female family members lack understanding of indeterminate negative BRCA1/2 test results shared by probands

Genetic test results have important implications for close family members. Indeterminate negative results are the most common outcome of BRCA1/2 mutation testing. Little is known about family members' understanding of indeterminate negative BRCA1/2 test results. The purpose of this mixed‐methods study was to investigate how daughters and sisters received and understood genetic test results as shared by their mothers or sisters. Participants included 81 women aged 40–74 with mothers or sisters previously diagnosed with breast cancer and who received indeterminate negative BRCA1/2 test results. Participants had never been diagnosed with breast cancer nor received their own genetic testing or counseling. This Institutional Review Board‐approved study utilized semi‐structured interviews and surveys. Descriptive coding with theme development was used during qualitative analysis. Participants reported low amounts of information shared with them. Most women described test results as negative and incorrectly interpreted the test to mean there was no genetic component to the pattern of cancer in their families. Only seven of 81 women accurately described test results consistent with the meaning of an indeterminate negative. Our findings demonstrate that indeterminate negative genetic test results are not well understood by family members. Lack of understanding may lead to an inability to effectively communicate results to primary care providers and missed opportunities for prevention, screening, and further genetic testing. Future research should evaluate acceptability and feasibility of providing family members letters they can share with their own primary care providers.
Characterisation of slip and twinning in high rate deformed zirconium with electron backscatter diffraction

Zirconium alloys are used in the nuclear industry as structural materials, and can be subject to high strain rate loading conditions during forming and in the case of a reactor accident. In this context, the relationship between strain rate dependent mechanical properties, crystallographic texture and deformation modes, such as slip and deformation twinning, are explored in this work. Commercially pure zirconium is deformed to 10 % engineering strain under quasi-static and high strain rate loading, and post-mortem analysis of the samples is performed using electron backscatter diffraction (EBSD) to observe different twin and slip systems activated. Twin types are identified from local intergranular misorientation maps, and active slip systems are identified from long range intragranular misorientation maps. We link characterisation of the mechanical responses, twin types and morphologies, and relative slip system activation as a function of loading mode. We find that variations in strength and hardening can be related to the relative propensity of twinning and the number of active slip systems.
Exploiting Existing Replicas of Stack Pointer in theRegister File for Error Detection

Hardware errors, i.e. Soft and Permanent Errors, became a tremendously important problem in the microarchitecture design as technology scales deeply and the number of transistors placed in computer systems increases exponentially. Moreover, single particle strikes may flip the values of several adjacent bits which causes multi-bit upsets. The register file is one of the most vulnerable structure in microprocessors since it is the major data holding component and referenced by most of the other components. Nevertheless, any access latency of register file will affect the rest of the pipeline which makes register file a timecritical component. Thus, it is essential to provide effective and fast reliability solutions to protect register files against hardware errors. In this study we present a fast error detection scheme in order to reduce the vulnerability of register file. We build our scheme on the observation that stack pointer is renamed repeatedly which causes keeping several copies of the same data in different registers. Thus, we leveraged these existing replicas for error detection. We show that our scheme can provide 59% reliability for the calculation of the Stack Pointer on average with a modest hardware overhead and with a negligible performance degradation.
To Interpret or Not to Interpret PCA? This Is Our Question

Principal Component Analysis (PCA) is a central tool for analyzing data and social media data in particular. Typically, the data is projected on the first two PCs to obtain a twodimensional view, and trends and patterns are being examined. A key to making sense of the projected data is the semantic interpretation of the new axes (the PCs). To label the PCs, one usually looks at the top k vector entries in absolute value and assigns meaning according to them. The choice of k is done by “eyeballing” the vector. In this work we provide a computational framework to support this process and suggest an interpretability score, which measures how sensitive the interpretation step could be to the choice of k. Furthermore we give a visual method to choose the optimal k. We study our methodology in four social media platforms and discover that in two of them, Twitter and Instagram, interpretation can be done in a carefree manner, but in Steam and LinkedIn there is no natural labeling of the axes. This separation is clearly reflected in the interpretability score that each dataset received.
High Numbers of Circulating CD57+ NK Cells Associate with Resistance to HER2-Specific Therapeutic Antibodies in HER2+ Primary Breast Cancer

CD57+ NK-cell numbers may be a biomarker to identify breast cancer patients with primary resistance to HER2-specific therapeutic antibodies. NK-cell aging may influence NK-cell antitumor function. Natural killer (NK) cells can orchestrate effective antitumor immunity. The presence of tumor-infiltrating NK cells in diagnostic biopsies predicts pathologic complete response (pCR) to HER2-specific therapeutic antibodies in patients with primary breast cancer. Here, we analyzed whether diversity in circulating NK cells might influence tumor infiltration and HER2-specific therapeutic antibody efficacy. We found that numbers of circulating CD57+ NK cells inversely correlated with pCR to HER2-specific antibody treatment in patients with primary breast cancer independently of age, traditional clinicopathologic factors, and CD16A 158F/V genotype. This association was uncoupled from the expression of other NK-cell receptors, the presence of adaptive NK cells, or changes in major T-cell subsets, reminiscent of cytomegalovirus-induced immunomodulation. NK-cell activation against trastuzumab-coated HER2+ breast cancer cells was comparable in patients with high and low proportions of CD57+ NK cells. However, circulating CD57+ NK cells displayed decreased CXCR3 expression and CD16A-induced IL2-dependent proliferation in vitro. Presence of CD57+ NK cells was reduced in breast tumor–associated infiltrates as compared with paired peripheral blood samples, suggesting deficient homing, proliferation, and/or survival of NK cells in the tumor niche. Indeed, numbers of circulating CD57+ were inversely related to tumor-infiltrating NK-cell numbers. Our data reveal that NK-cell differentiation influences their antitumor potential and that CD57+ NK cells may be a biomarker useful for tailoring HER2 antibody–based therapeutic strategies in breast cancer.
Video e-commerce: Large Scale Online Video Advertising based on user Preference

An advertisement is a notice or announcement in a public medium promoting a product. Advertising plays significant role in the introduction of a new product in the market. It stimulates the people to purchase the product. In this paper, we propose a novel personalized Online Video Advertising System which is presented to recommend product ads from ecommerce sites to users of online video hosting. First we have to find a user preference, so we have to analyze each user’s behavior of ecommerce sites. If the user wants to buy a product, user will spend more time to view the specification at the same time, user clicks that product more number of times to view the specification, price etc. These techniques are used to find the user preference. After collecting each user preference, we have to identify the semantic association between videos and products and construct the association between the key frames and products. A multi view deep learning approach is brought to view item features in different domains. When the User plays the video the user preferred advertisements are shown in the video in proper timestamps. Thus the advertisements are displayed only based on the user’s preference and the user’s will to purchase the desired product. This has been the key feature of our project. Maintaining privacy is one of the major problems for sharing personal information through social sites. Sharing video in social media may lead to unwanted problem and less privacy. As a result we need some tools for secured transmission. For satisfying this need, we propose a system called Adaptive Privacy Policy Prediction (A3P) to enhance privacy settings for user’s data. This system provides a two-level framework for securing the data based on users browsing history on shopping site. It determines the best available privacy policy for users. Our solution relies on image classification which is associated with policies to upload images and also to user's social features. Hence by using this adaptive privacy policy our sharing of shopping and recommended videos can be secured to only desire people.
MAGNETIC MATERIALS FOR ACCELERATOR ELECTROMAGNETS

Accelerator electromagnets are used in synchrotrons for the guidance of particles. For the successful operation of such synchrotrons, high field homogeneity is required to be provided by the electromagnets. Furthermore, the magnetic field characteristics of all electromagnets of one type installed have to be identical. A high field homogeneity and equal performance from electromagnet to electromagnet can only be achieved if great care is taken when the selection of magnetic materials is done, and if a rigorous quality assurance plan is implemented during manufacturing. In this paper a procedure is presented for selecting the magnetic material and mandatory steps during manufacturing are outlined.
Effect of p 21 Waf 1 and p 27 Kip 1 on centrosome replication and proliferation of breast cancer cell

Aberrant centrosome numbers are detected in virtually all cancers increasing the risk for cell division errors and chromosomal instability. N at ur e P re ce di ng s : h dl :1 01 01 /n pr e. 20 10 . 4 42 6. 1 : P os te d 8 M ay 2 01 0 Deregulation of the centrosome duplication cycle is considered as the major contributing factor for abnormal ampli cation of centrosomes. p21 fi Waf1 and p27Kip1, general CDK inhibitors by inhibiting cyclin-dependent kinase 2 (CDK2)/cyclin E and cyclin A complexes, controlled the initiation and progress of centrosome duplication . We transfected p21 Waf1, p27 Kip1 or p21 Waf1p27 Kip1 genes into MCF-7 cells by lipofection to explore the effect of the genes on centrosome duplication and proliferation of breast cancer cell. The result shows that the cell growth was obviously inhibited after being transfected, resulting in an accumulation of cells in G1 and the proportion of cells which contained abnormal centrosomes was obviously decreased. Comparing with p21 Waf1or p27 Kip1, the effects of p21Waf1p27 Kip1 genes are more significative. These results suggest that p21Waf1 and p27Kip1 genes could inhibit the growth of human breast cancer N at ur e P re ce di ng s : h dl :1 01 01 /n pr e. 20 10 . 4 42 6. 1 : P os te d 8 M ay 2 01 0 cells and reverse abnormal duplication of centrosomes. p21Waf1and p27Kip1 cooperate to regulate centrosome duplication and cell cycle progress, indicating p21 Waf1p27 Kip1 combined gene might be potential therapeutic agents of breast cancer which reveals suppressed p21Waf1 and p27Kip1 expression.
Filtered Food and Nofilter Landscapes in Online Photography: The Role of Content and Visual Effects in Photo Engagement

Millions of images are shared through social media every day. Yet, we know little about how the activities and preferences of users are dependent on the content of these images. In this paper, we seek to understand viewers engagement with photos. We design a quantitative study to expand previous research on in-app visual effects (also known as filters) through the examination of visual content identified through computer vision. This study is based on analysis of 4.9M Flickr images and is organized around three important engagement factors: likes, comments and favorites. We find that filtered photos are not equally engaging across different categories of content. Photos of food and people attract more engagement when filters are used, while photos of natural scenes and photos taken at night are more engaging when left unfiltered. In addition to contributing to the research around social media engagement and photography practices, our findings offer several design implications for mobile photo sharing platforms.
The Effects of Learning Styles on Learning Performance of Blockly Programming with Webduino Online Editor

Computational Thinking is a significant educational theme in recent years; using programming to develop students’ computational thinking is one of crucial training methods so plenty of colleges and universities have set up related curriculum recently to develop their abilities. In light of technological innovations, IoT is nowadays the major concept and technique for promoting intelligent life and the essential knowledge for college and university students. Consequently, the researcher used the online editorWebduino Blockly, in which users could use graphical programming methods to control IoT components allowing them to learn IoT knowledge. Moreover, the researcher utilized UTAUT to investigate their technology acceptance of using this tool and used learning style instrument to evaluate their learning performances of different learning styles. The results showed that performance expectancy had significantly affected behavioral intention; behavioral intention and facilitating conditions had significantly affected use behavior. For learning performance, kinesthetic users’ score was significantly higher than auditory users’ score; this indicated that using this tool and instructional method could significantly enhance kinesthetic users’ learning performance. This study was merely a pilot study; in the future, the researcher expects to investigate learners of all age groups using Blockly programming tool in order to provide more references for instructors.
Novel Superhydrophobic Cement-based Materials Achieved by Construction of Hierarchical Surface Structure with FAS/SiO2 Hybrid Nanocomposites

Shandong Provincial Key Lab for the Preparation and Measurement of Building Materials, Jinan, Shandong, 250022, China Lyles School of Civil Engineering, Purdue University, West Lafayette, Indiana, 47906, USA Department of Civil, Construction and Environmental Engineering, Iowa State University, Ames, IA 50011, USA Shenzhen Gangchuang Building Material Co., Ltd, Shenzhen, Guangdong, 518000, China Department of Civil and Environmental Engineering, Northwestern University, Evanston, IL, 60201, USA *E-mail: pkhou@163.com; chengxin@ujn.edu. cn Pengkun Hou, Ran Li, Qinfei Li, Na Lu, Kejin Wang, Mingle Liu, Xin Cheng, and Surendra Shah View Article Online
Simplified models of stellar wind anatomy for interpreting high-resolution data - Analytical approach to embedded spiral geometries

Context. Recent high-resolution observations have shown that stellar winds harbour complexities that strongly deviate from spherical symmetry, which generally is assumed as standard wind model. One such morphology is the Archimedean spiral, which is generally believed to be formed by binary interactions, as has been directly observed in multiple sources. Aims. We seek to investigate the manifestation in the observables of spiral structures embedded in the spherical outflows of cool stars. We aim to provide an intuitive bedrock with which upcoming ALMA data can be compared and interpreted. Methods. By means of an extended parameter study, we modelled rotational CO emission from the stellar outflow of asymptotic giant branch stars. To this end, we developed a simplified analytical parametrised description of a 3D spiral structure. This model is embedded into a spherical wind and fed into the 3D radiative transfer code LIME, which produces 3D intensity maps throughout velocity space. Subsequently, we investigated the spectral signature of rotational transitions of CO in the models, as well as the spatial aspect of this emission by means of wide-slit position-velocity (PV) diagrams. Additionally, we quantified the potential for misinterpreting the 3D data in a 1D context. Finally, we simulated ALMA observations to explore the effect of interferometric noise and artefacts on the emission signatures. Results. The spectral signatures of the CO rotational transition v = 0 J = 3-2 are very efficient at concealing the dual nature of the outflow. Only a select few parameter combinations allow for the spectral lines to disclose the presence of the spiral structure. If the spiral cannot be distinguished from the spherical signal, this might result in an incorrect interpretation in a 1D context. Consequently, erroneous mass-loss rates would be calculated. The magnitude of these errors is mainly confined to a factor of a few, but in extreme cases can exceed an order of magnitude. CO transitions of different rotationally excited levels show a characteristical evolution in their line shape that can be brought about by an embedded spiral structure. However, if spatial information on the source is also available, the use of wide-slit PV diagrams systematically expose the embedded spiral. The PV diagrams also readily provide most of the geometrical and physical properties of the spiral-harbouring wind. Simulations of ALMA observations prove that the choice of antenna configuration is strongly dependent on the geometrical properties of the spiral. We conclude that exploratory endeavours should observe the object of interest with a range of different maximum-baseline configurations.
Designing Vertical Processors in Monolithic 3D

A processor laid out vertically in stacked layers can benefit from reduced wire delays, low energy consumption, and a small footprint. Such a design can be enabled by Monolithic 3D (M3D), a technology that provides short wire lengths, good thermal properties, and high integration. In current M3D technology, due to manufacturing constraints, the layers in the stack are asymmetric: the bottom-most one has a relatively higher performance. In this paper, we examine how to partition a processor for M3D. We partition logic and storage structures into two layers, taking into account that the top layer has lower-performance transistors. In logic structures, we place the critical paths in the bottom layer. In storage structures, we partition the hardware unequally, assigning to the top layer fewer ports with larger access transistors, or a shorter bitcell subarray with larger bitcells. We find that, with conservative assumptions on M3D technology, an M3D core executes applications on average 25% faster than a 2D core, while consuming 39% less energy. With aggressive technology assumptions, the M3D core performs even better: it is on average 38% faster than a 2D core and consumes 41% less energy. Further, under a similar power budget, an M3D multicore can use twice as many cores as a 2D multicore, executing applications on average 92% faster with 39% less energy. Finally, an M3D core is thermally efficient.