Miracle-dz/UniFAR-FTUs huggingface dataset:
Barriers and enablers of kangaroo mother care implementation from a health systems perspective: a systematic review

&NA; Kangaroo Mother Care (KMC) is an evidence‐based intervention that reduces neonatal morbidity and mortality. However, adoption among health systems has varied. Understanding the interaction between health system functions—leadership, financing, healthcare workers (HCWs), technologies, information and research, and service delivery—and KMC is essential to understanding KMC adoption. We present a systematic review of the barriers and enablers of KMC implementation from the perspective of health systems, with a focus on HCWs and health facilities. Using the search terms ‘kangaroo mother care’, ‘skin to skin (STS) care’ and ‘kangaroo care’, we searched Embase, Scopus, Web of Science, Pubmed, and World Health Organization Regional Databases. Reports and hand searched references from publications were also included. Screening and data abstraction were conducted by two independent reviewers using standardized forms. A conceptual model to assess KMC adoption themes was developed using NVivo software. Our search strategy yielded 2875 studies. We included 86 studies with qualitative data on KMC implementation from the perspective of HCWs and/or facilities. Six themes emerged on barriers and enablers to KMC adoption: buy‐in and bonding; social support; time; medical concerns; training; and cultural norms. Analysis of interactions between HCWs and facilities yielded further barriers and enablers in the areas of training, communication, and support. HCWs and health facilities serve as two important adopters of Kangaroo Mother Care within a health system. The complex components of KMC lead to multifaceted barriers and enablers to integration, which inform facility, regional, and country‐level recommendations for increasing adoption. Further research of methods to promote context‐specific adoption of KMC at the health systems level is needed.
Efficient Heart Disease Prediction System using K-Nearest Neighbor Classification Technique

The healthcare industry gathers gigantic volumes of healthcare data, which can be turned into useful information by using different Data mining techniques. This knowledge can then be useful in many different decision making environments like Finance, Marketing, Healthcare sector. In health care industry, cardiovascular disease is one of the most significant but difficult task that needs to be done very swiftly, efficiently and the correct automation is desirable. In this regard, different Heart Disease Prediction systems have been reviewed and the work done previously have applied different numbers of medical parameters and risk factors with different data mining techniques. Accuracy claimed in each of those papers depends upon the number of parameters and data mining techniques applied. However, the number of the parameters and datasets to perform experiments was very small to claim high accuracy. We employed K-nearest neighbor classifier to achieve an accuracy of approximately 80% by using 14 attributes. Moreover, a number of predominant classifiers have been evaluated to highlight the supremacy of k-NN classifier based heart disease prediction system.
Single‐cell profiling screen identifies microtubule‐dependent reduction of variability in signaling

Populations of isogenic cells often respond coherently to signals, despite differences in protein abundance and cell state. Previously, we uncovered processes in the Saccharomyces cerevisiae pheromone response system (PRS) that reduced cell‐to‐cell variability in signal strength and cellular response. Here, we screened 1,141 non‐essential genes to identify 50 “variability genes”. Most had distinct, separable effects on strength and variability of the PRS, defining these quantities as genetically distinct “axes” of system behavior. Three genes affected cytoplasmic microtubule function: BIM1, GIM2, and GIM4. We used genetic and chemical perturbations to show that, without microtubules, PRS output is reduced but variability is unaffected, while, when microtubules are present but their function is perturbed, output is sometimes lowered, but its variability is always high. The increased variability caused by microtubule perturbations required the PRS MAP kinase Fus3 and a process at or upstream of Ste5, the membrane‐localized scaffold to which Fus3 must bind to be activated. Visualization of Ste5 localization dynamics demonstrated that perturbing microtubules destabilized Ste5 at the membrane signaling site. The fact that such microtubule perturbations cause aberrant fate and polarity decisions in mammals suggests that microtubule‐dependent signal stabilization might also operate throughout metazoans.
mTOR signaling in VIP neurons regulates circadian clock synchrony and olfaction

Significance The mammalian/mechanistic target of rapamycin (mTOR) kinase resides at the crux of an intracellular signaling network that controls fundamental biological processes. Dysregulation of mTOR signaling is linked to neurological and psychiatric diseases. However, the physiological functions of mTOR signaling in the adult brain are not fully understood. In the current study, we discovered that mTOR in vasoactive intestinal peptide (VIP) neurons plays a key role in regulating neurophysiology in the brain circadian clock and the olfactory system. The conditional mTOR knockout mouse will be a useful model for future investigations of mTOR and/or VIP. Mammalian/mechanistic target of rapamycin (mTOR) signaling controls cell growth, proliferation, and metabolism in dividing cells. Less is known regarding its function in postmitotic neurons in the adult brain. Here we created a conditional mTOR knockout mouse model to address this question. Using the Cre-LoxP system, the mTOR gene was specifically knocked out in cells expressing Vip (vasoactive intestinal peptide), which represent a major population of interneurons widely distributed in the neocortex, suprachiasmatic nucleus (SCN), olfactory bulb (OB), and other brain regions. Using a combination of biochemical, behavioral, and imaging approaches, we found that mice lacking mTOR in VIP neurons displayed erratic circadian behavior and weakened synchronization among cells in the SCN, the master circadian pacemaker in mammals. Furthermore, we have discovered a critical role for mTOR signaling in mediating olfaction. Odor stimulated mTOR activation in the OB, anterior olfactory nucleus, as well as piriform cortex. Odor-evoked c-Fos responses along the olfactory pathway were abolished in mice lacking mTOR in VIP neurons, which is consistent with reduced olfactory sensitivity in these animals. Together, these results demonstrate that mTOR is a key regulator of SCN circadian clock synchrony and olfaction.
Architecting cars as constituents of a system of systems

Future transportation systems will be a heterogeneous mix of items with varying connectivity and interoperability. A mix of new technologies and legacy systems will co-exist to realize a variety of scenarios involving not only connected cars but also road infrastructures, pedestrians, cyclists, etc. Future transportation systems can be seen as a System of Systems (SoS), where each constituent system - one of the units that compose an SoS - can act as a standalone system, but the cooperation among the constituent systems enables new emerging and promising scenarios. In this paper we investigate how to architect cars so that they can be constituents of future transportation systems. This work is realized in the context of two Swedish projects coordinated by Volvo Cars and involving some universities and research centers in Sweden and many suppliers of the OEM, including Autoliv, Arccore, Combitech, Cybercom, Knowit, Prevas, ÅF-Technology, Semcom, and Qamcom.
Note on ‘‘Generalizability of Study Results‘‘

186 | www.epidem. com Epidemiology • Volume 30, Number 2, March 2019 From the Computer Science Department, University of California Los Angeles, Los Angeles, CA; and Computer Science Department, Purdue University, West Lafayette, IN. This research was supported in parts by grants from Defense Advanced Research Projects Agency No. W911NF-16-057, National Science Foundation No. IIS-1302448, No. IIS-1527490, and No. IIS-1704932, and Office of Naval Research No. N00014-17-S-B001 (to J.P.). This research was supported in parts by grants from National Science Foundation No. 1704352 and No. IIS-1750807 (CAREER; to E.B.). The authors report no conflicts of interest. Correspondence: Judea Pearl, Computer Science Department, University of California Los Angeles, 3531 Boelter Hall, Los Angeles, CA 90056. E-mail: judea@ cs.ucla. edu.
Evaluation of a 3 D-aided Pose Invariant 2 D Face Recognition System

A few well-developed face recognition pipelines have been reported in recent years. Most of the face-related work focuses on a specific module or demonstrates a research idea. In this paper, we present a pose-invariant 3D-aided 2D face recognition system (3D2D-PIFR) that is robust to pose variations as large as 90◦ by leveraging deep learning technology. We describe the architecture and the interface of 3D2D-PIFR, and introduce each module in detail (Code for module algorithms are kindly provided for the authors and their institution). Experiments are conducted on the UHDB31 and IJB-A, demonstrating that 3D2D-PIFR outperforms existing 2D face recognition systems such as VGG-Face, FaceNet, and a commercial off-the-shelf software (COTS) by at least 9% on UHDB31 and 3% on IJB-A dataset in average. It fills a gap by providing a 3D-aided 2D face recognition system that has compatible results with 2D face recognition systems using deep learning techniques. A video demo of 3D2D-PIFR is available at http://cbl. uh.edu/index.php/pages/research/demos.
Sensorimotor rhythm-based brain–computer interface (BCI): model order selection for autoregressive spectral analysis

People can learn to control EEG features consisting of sensorimotor rhythm amplitudes and can use this control to move a cursor in one or two dimensions to a target on a screen. Cursor movement depends on the estimate of the amplitudes of sensorimotor rhythms. Autoregressive models are often used to provide these estimates. The order of the autoregressive model has varied widely among studies. Through analyses of both simulated and actual EEG data, the present study examines the effects of model order on sensorimotor rhythm measurements and BCI performance. The results show that resolution of lower frequency signals requires higher model orders and that this requirement reflects the temporal span of the model coefficients. This is true for both simulated EEG data and actual EEG data during brain–computer interface (BCI) operation. Increasing model order, and decimating the signal were similarly effective in increasing spectral resolution. Furthermore, for BCI control of two-dimensional cursor movement, higher model orders produced better performance in each dimension and greater independence between horizontal and vertical movements. In sum, these results show that autoregressive model order selection is an important determinant of BCI performance and should be based on criteria that reflect system performance.
A Whittle's Index Based Approach for QoE Optimization in Wireless Networks

The design of schedulers to optimize heterogeneous users' Quality of Experience (QoE) remains a challenging and important problem for wireless systems. This paper explores three inter-related aspects of this problem: 1) non-linear relationships between a user's QoE and flow delays; 2) managing load dependent QoE trade-offs among heterogeneous application classes; and 3), striking a good balance between opportunistic scheduling and greedy QoE optimization. To that end we study downlink schedulers which minimize the expected cost modeled by convex functions of flow delays for users with heterogeneous channel rate variations. The essential features of this challenging problem are modeled as a Markov Decision Process to which we apply Whittle's relaxation, which in turn is shown to be indexable. Based on the Whittle's relaxation we develop a new scheduling policy, Opportunistic Delay Based Index Policy (ODIP). We then prove various structural properties for ODIP which result in closed form expressions for Whittle's indices under different scheduler scenarios. Using extensive simulations we show that ODIP scheduler provides a robust means to realize complex QoE trade-offs for a range of system loads.
Methodology for the Analysis of the Process Behaviour of Advanced High Strength Steels in Bending and Shearing Operations

In the automotive sector the application of advanced high strength steels (AHSS) for structural and safety relevant components plays an important role. Typical manufacturing processes concerning these parts are bending and cutting operations. However, the forming and cutting potential of these steel grades is different compared to conventional steels, as the process behaviour is changing. For an improved workpiece quality the fundamental knowledge of the damage and failure mechanisms is essential. This study presents a methodology for the analysis of AHSS in bending and out-of-plane shearing operations. Two micro alloyed high strength steels are investigated within this work. First results are presented concerning material characterisation by tensile tests, the material performance in air bending tests and the development of a modular punching tool. The study is closed by summarizing the damage behaviour along the process chain considering both bending and cutting. This shows the applicability of the presented methodology for analysing the process behaviour with respect to occurring failure.
ICDAR2017 Competition on Reading Chinese Text in the Wild (RCTW-17)

Chinese is the most widely used language in the world. Algorithms that read Chinese text in natural images facilitate applications of various kinds. Despite the large potential value, datasets and competitions in the past primarily focus on English, which bares very different characteristics than Chinese. This report introduces RCTW, a new competition that focuses on Chinese text reading. The competition features a large-scale dataset with over 12,000 annotated images. Two tasks, namely text localization and end-to-end recognition, are set up. The competition took place from January 20 to May 31, 2017. 23 valid submissions were received from 19 teams. This report includes dataset description, task definitions, evaluation protocols, and results summaries and analysis. Through this competition, we call for more future research on the Chinese text reading problem.
A Data Trustworthiness Enhanced Reputation Mechanism for Mobile Crowd Sensing

Mobile Crowd Sensing (MCS) arises as an emerging technology to assist smart city applications through crowd sensing services where data is gathered and stored from intelligent devices interacting continuously with citizens. For the success of the burgeoning MCS technology in smart city applications, it is vital to address the key challenge of data trustworthiness in MCS. Therefore, this paper proposes a Data Trustworthiness enhanced Reputation Mechanism (DTRM) to defend against internal attacks and enhance data trustworthiness for MCS. In the DTRM, the sensitivity-level based data category, metagraph theory based user group division and reputation transferring are integrated into the reputation query and evaluation process. Simulation results demonstrate the superior performance of the DTRM compared to existing reputation mechanisms under internal mobile attacks and bad mouthing attacks.
ApoE ε4 Allele Related Alterations in Hippocampal Connectivity in Early Alzheimer's Disease Support Memory Performance.

BACKGROUND Whether the presence of the Apolipoprotein E ε4 allele modulates hippocampal connectivity networks in abnormal ageing has yet to be fully clarified. OBJECTIVE Allele-dependent differences in this pattern of functional connectivity were investigated in patients with very mild neurodegeneration of the Alzheimer's type, carriers and non-carriers of the ε4 allele. METHOD A seed-based connectivity approach was used. The two groups were similar in demographics, volumetric measures of brain structure, and cognitive profiles. RESULTS ε4-carriers had increased connectivity between the seed area in the left hippocampus and 1) a left insular/lateral prefrontal region and 2) the contralateral right parietal cortex. Moreover, hippocampus- to-parietal connectivity in the group of ε4 carriers was positively associated with memory performance, indicating that the between-group difference reflects compensatory processes. Retrospective analyses of functional connectivity based on patients from the ADNI initiative confirmed this pattern. CONCLUSION We suggest that increased connectivity with areas external to the Default Mode Network (DMN) reflects both compensatory recruitment of additional areas, and pathological interwining between the DMN and the salience network as part of a global ε4-dependent circuital disruption. These differences indicate that the ε4 allele is associated with a more profound degree of DMN network breakdown even in the prodromal stage of neurodegeneration.
A Novel Opamp and Capacitor Sharing 10 Bit 20 MS/s Low Power Pipelined ADC in 0.18µm CMOS Technology

In this paper, a novel 10 bit 20 MS/s, low power, pipelined ADC using both capacitor and opamp sharing techniques is proposed. In the proposed ADC, feedback capacitors in the first four stages are shared between adjacent stages in order to decrease the power dissipation of the opamps used in these stages. The opamps in the six pipeline stages are also shared between adjacent stages in pairs for further power reduction. The proposed ADC is designed in UMC 0.18um CMOS technology with a supply voltage of 1.8V and simulated in Cadence Spectre Simulator. The ADC achieves 9.5 bit accuracy with 59.44dB SNR and 70.92dB SFDR and dissipates 4.36mW power. The proposed ADC has better FOM compared to that reported in the literature.
Toxicant mixtures in sediment alter gene expression in the cysteine metabolism of Chironomus tepperi

Sediment contamination can pose risks to the environment, and sediment toxicity tests have been developed to isolate the impact of sediment from other factors. Mixtures of contaminants often occur in sediments, and traditional endpoints used in toxicity testing, such as growth, reproduction, and survival, cannot discern the cause of toxicity from chemical mixtures because of complex interactions. In urban waterways, the synthetic pyrethroid bifenthrin and the metal copper are commonly found in mixtures, so the present study was designed to investigate how these contaminants cause toxicity in mixtures. To investigate this, Chironomus tepperi was exposed to environmentally relevant concentrations of copper and bifenthrin‐spiked sediments in a 2‐way factorial mixture for 5 d. Growth and expression profiles of cysteine metabolism genes were measured after exposure. Growth increased at low copper concentrations, decreased at high copper concentrations, and was unaffected by bifenthrin exposures. Copper exposures induced possible cellular repair by upregulating S‐adenosylmethionine synthetase expression and downregulating expression of S‐adenosylhomocysteine hydrolase and cystathionine‐β‐synthase. Metallothionein upregulation was also observed. Bifenthrin exposure altered cysteine metabolism to a lesser extent, downregulating cystathionine‐β‐synthase and γ‐glutamylcysteine synthase. Synergistic, antagonistic, and dose‐dependent interactions were observed, and there was evidence of conflicting modes of action and limited substrate production. These findings demonstrate how contextual gene expression changes can be sensitive and specific identifiers of toxicant exposure in mixtures. Environ Toxicol Chem 2017;36:691–698. © 2016 SETAC
Transient Liquid Phase Bonding of Al/Mg2Si Composite Using a Cu-Ni Mixed Powder

Transient liquid phase bonding of Al/Mg2Si metal matrix composite (MMC) was investigated using a Cu-Ni mixed powder interlayer (1:1 proportion by weight) in an argon environment at various temperatures and holding time. The composite (MMC), containing 15% Mg2Si particles, was produced by in situ technique. The use of pure copper interlayer in Al/Mg2Si metal matrix composite causes reinforcement particles segregation at the bond interface. The region of weakness produced by the particles segregation at the bond region has been found to promote preferential failure during tensile testing. Using a mixture of Ni and Cu powder as filler material have shown less segregation of particles reinforcement along central bond zone. The composition and microstructure of the joined area were examined by X-ray diffraction (XRD) and scanning electron microscopy equipped with an energy dispersive X-ray spectroscopy (EDS). Shear tests were conducted to the samples to evaluate the effect of bonding duration on weldabillity. As the bonding time increases, with continual diffusion, the structural heterogeneity is diminished, and the microporosities are eliminated at the central bond zone. The shear strength of joints increased with increasing bonding duration.
IIIT-H System for MediaEval 2014 QUESST

This paper describes the experiments and observations for Query-by-Example Search on Speech Task (QUESST) at MediaEval 2014. In this paper, we describe two dierent representations of speech that were explored for the task. We also show the capabilities and limitations of non-segmental dynamic time warping (NS-DTW) technique for searching various types of queries. This paper mainly focuses on the experiments and analysis of the existing NS-DTW algorithm for various types of queries. The observations show that for a specic representation of speech, the algorithm is capable of detecting partial matches.
Intelligent Virtual Environments - A State-of-the-art Report

The impetus for this field comes from a number of directions. Firstly, as the amount of processing power available for rendering has increased, it has now become feasible to devote a little of it to aspects of a VE beyond visual realism. However visually appealing a VE is, if it is static and empty of change and behaviour, the immersive experience is of limited interest. Cities without people cannot make the user feel a real sense of presence. While animation can create dynamic interest, its pre-scripted nature runs against the interactional freedom a VE gives users and can only hold their interest for a limited time.
Measurements of serum procollagen-III peptide and M30 do not improve the diagnostic accuracy of transient elastography for the detection of hepatic fibrosis in patients with nonalcoholic fatty liver disease

Background Transient elastography (TE) has recently emerged as an accurate noninvasive imaging method for the diagnosis of liver fibrosis in nonalcoholic fatty liver disease (NAFLD). Here, we tested whether adding serum measures of serum procollagen-III peptide (PIIIP) and caspase-cleaved cytokeratin 18 fragment (M30) to TE could improve its diagnostic accuracy in patients with biopsy-proven NAFLD. Patients and methods TE was performed in 87 patients with NAFLD. Serum PIIIP and M30 levels were determined by enzyme-linked immunosorbent assay. Liver histology was considered the gold standard. The diagnostic accuracies were assessed by measuring the area under the receiver operating curve. Results At histopathological examination, 34 patients (39.1%) had significant fibrosis (F2–F4) and 19 patients (21.8%) had advanced fibrosis (F3–F4). Both TE and serum M30 levels were independent predictors of fibrosis, whereas no association was found with PIIIP. No significant differences in terms of sensitivity and specificity for both significant and advanced fibrosis were evident for TE, serum M30, or their combination. Moreover, the area under the receiver operating curves of serum M30 combined with TE did not differ significantly from those of either test alone. Conclusion Both TE and serum M30 levels are accurate for the noninvasive diagnosis of fibrosis in NAFLD. However, their combination did not improve the overall diagnostic accuracy.