Miracle-dz/UniFAR-FTUs huggingface dataset:
Interventions During Pregnancy Reduce Excessive Gestational Weight Gain but Yield Unexpected Effects on Neonatal Body Composition

This issue of Obesity includes articles about two randomized trials that were part of the Lifestyle Interventions for Expectant Moms (LIFEMoms) consortium of seven independent trials (1). The consortium was formed to determine whether various behavioral and lifestyle interventions could reduce excessive gestational weight gain (GWG), adverse maternal and neonatal outcomes, and obesity among the offspring of pregnant women with overweight and obesity (1). Both trials partnered with or used an existing evidence-based program or curriculum as the basis of the lifestyle intervention that was tested, increasing the likelihood of the translation of their interventions into practice. Cahill et al. (2) partnered with an existing community-based organization to deliver the Parents as Techers (PAT) program (3) to the control group and the PAT program plus a lifestyle intervention to the intervention group. Both treatments were delivered by trained parent educators through home visits to socioeconomically disadvantaged African American women in St. Louis, Missouri. Gallagher et al. (4) adapted and integrated the Diabetes Prevention Program (5) and the Look AHEAD: Action for Health in Diabetes curricula (6) for pregnant women, using a 20-module program that was delivered by a professional nutritionist at individual clinical visits in a racially diverse, highly educated sample in New York City. Control arm women received usual care that included a single visit with a nutritionist, and both treatment groups had an opportunity to attend different group sessions held every 8 weeks during pregnancy. Both programs reached participants on a biweekly basis and achieved excellent adherence, including a median of nine out of ten visits for an average of 53 minutes each in the intervention group in the Cahill et al. (2) trial and 72% of clinic visits attended in the intervention group in the Gallagher et al. (4) trial. What is not stated in the articles (and is important because of the relevance to translation into real-world settings) is whether incentives were given to women to attend visits.
Distributed leader-following consensus of a class of nonlinear multi-agent systems

This paper addresses the leader-following consensus issue for a type of nonlinear multi-agent systems with affine nonlinear term. A distributed control algorithm is constructed for each follower, and sufficient condition is obtained. The proposed control algorithm guarantees the state consensus of the multi-agent systems when the communication network among followers is an undirected and connected graph, and the leader sends its information to at least one follower. The effectiveness and usefulness of the theoretical results are illustrated by numerical simulation finally.
TrmL and TusA Are Necessary for rpoS and MiaA Is Required for hfq Expression in Escherichia coli

Previous work demonstrated that efficient RNA Polymerase sigma S-subunit (RpoS) translation requires the N6-isopentenyladenosine i6A37 transfer RNA (tRNA) modification for UUX-Leu decoding. Here we investigate the effect of two additional tRNA modification systems on RpoS translation; the analysis was also extended to another High UUX-leucine codon (HULC) protein, Host Factor for phage Qβ (Hfq). One tRNA modification, the addition of the 2’-O-methylcytidine/uridine 34 (C/U34m) tRNA modification by tRNA (cytidine/uridine-2’O)-ribose methyltransferase L (TrmL), requires the presence of the N6-isopentenyladenosine 37 (i6A37) and therefore it seemed possible that the defect in RpoS translation in the absence of i6A37 prenyl transferase (MiaA) was in fact due to the inability to add the C/U34m modification to UUX-Leu tRNAs. The second modification, addition of 2-thiouridine (s2U), part of (mnm5s2U34), is dependent on tRNA 2-thiouridine synthesizing protein A (TusA), previously shown to affect RpoS levels. We compared expression of PBAD-rpoS990-lacZ translational fusions carrying wild-type UUX leucine codons with derivatives in which UUX codons were changed to CUX codons, in the presence and absence of TrmL or TusA. The absence of these proteins, and therefore presumably the modifications they catalyze, both abolished PBAD-rpoS990-lacZ translation activity. UUX-Leu to CUX-Leu codon mutations in rpoS suppressed the trmL requirement for PBAD-rpoS990-lacZ expression. Thus, it is likely that the C/U34m and s2U34 tRNA modifications are necessary for full rpoS translation. We also measured PBAD-hfq306-lacZ translational fusion activity in the absence of C/U34m (trmL) or i6A37 (miaA). The absence of i6A37 resulted in decreased PBAD-hfq306-lacZ expression, consistent with a role for i6A37 tRNA modification for hfq translation.
Radon-Fourier Transform for Radar Target Detection (II): Blind Speed Sidelobe Suppression

This paper gives a detailed performance analysis for the novel radar long-time coherent integration method, i.e., Radon-Fourier transforms (RFT). Some important properties of RFT, e.g., two-dimensional (2D) impulse response, 2D translational invariance, multitarget linear additivity, linear signal-to-noise ratio gain in additive white Gaussian noise (AWGN), as well as the 2D correlation function of transformed AWGN, are derived for continuous and discrete RFT, respectively. However, because of discrete pulse sampling, finite range resolution, and limited integration time, the "blind-speed sidelobes (BSSL)" of discrete RFT may inevitably appear in real applications. Although the BSSL are reduced with the increase of the blind-speed integer, they may still lead to false alarms or loss detections in a real multitarget scenario. Based on the analytic expression derived for BSSL, the causes of BSSL are analyzed and the effective BSSL suppression methods are proposed. Finally, numerical experiments are also provided to demonstrate the effectiveness of the proposed methods.
Checking for k-Anonymity Violation by Views

When a private relational table is published using views, secrecy or privacy may be violated. This paper uses a formally-defined notion of k-anonymity to measure disclosure by views, where k >1 is a positive integer. Intuitively, violation of k-anonymity occurs when a particular attribute value of an entity can be determined to be among less than k possibilities by using the views together with the schema information of the private table. The paper shows that, in general, whether a set of views violates k-anonymity is a computationally hard problem. Subcases are identified and their computational complexities discussed. Especially interesting are those subcases that yield polynomial checking algorithms (in the number of tuples in the views). The paper also provides an efficient conservative algorithm that checks for necessary conditions for k-anonymity violation.
Design and Analysis of a Miniaturization Nanoindentation and Scratch Device

In this paper, a miniaturization nanoindentation and scratch device was developed. Finite element analysis was carried out to study static and modal characteristics of x/y flexure hinge and z axis driving hinge as well as effect of geometric parameters on output performances of z axis driving hinge. Results indicated that x/y flexure hinge and z axis driving hinge had enough strength and high natural frequencies. Geometric parameters of z axis driving hinge affected output performances significantly. The model of developed device was established. Indentation experiments of Si and amorphous alloy showed that the developed miniaturization nanoindentation and scratch device worked well and can carry out indentation experiments with certain accuracy.
Fast gender recognition in videos using a novel descriptor based on the gradient magnitudes of facial landmarks

The growing interest in recent years for gender recognition from face images is mainly attributable to the wide range of possible applications that can be used for commercial and marketing purposes. It is desirable that such algorithms process high resolution video frames acquired by using surveillance cameras in real-time. To the best of our knowledge, however, there are no studies which analyze the computational impact of the methods and the difficulties related to the processing of faces extracted from videos captured in the wild. We propose a novel face descriptor based on the gradient magnitudes of facial landmarks, which are points automatically extracted from the face contour, eyes, eyebrows, nose, mouth and chin. We evaluate the effectiveness and efficiency of the proposed approach on two new datasets, which we made available online and that consist of color face images and color video sequences acquired in real scenarios. The proposed approach is more efficient and effective than three commercial libraries.
Blind Nonlinearity Equalization by Machine-Learning-Based Clustering for Single- and Multichannel Coherent Optical OFDM

Fiber-induced intra- and interchannel nonlinearities are experimentally tackled using blind nonlinear equalization (NLE) by unsupervised machine-learning-based clustering (MLC) in ∼46-Gb/s single-channel and ∼20-Gb/s (middle-channel) multichannel coherent multicarrier signals (orthogonal frequency-division multiplexing (OFDM) based). To that end, we introduce, for the first time, hierarchical and fuzzy-logic C-means (FLC)-based clustering in optical communications. It is shown that among the two proposed MLC algorithms, FLC reveals the highest performance at optimum launched optical powers (LOPs), while at very high LOPs, hierarchical can compensate more effectively nonlinearities only for low-level modulation formats. When employing binary phase-shift keying and quaternary phase-shift keying, FLC outperforms K-means, fast-Newton support vector machines, supervised artificial neural networks, and NLE with deterministic Volterra analysis. In particular, for the middle channel of a QPSK wavelength-division multiplexing coherent optical OFDM system at optimum −5 dBm of LOP and 3200 km of transmission, FLC outperforms Volterra-NLE by 2.5 dB in Q-factor. However, for a 16-QAM single-channel system at 2000 km, the performance benefit of FLC over inverse Volterra-series transfer function reduces to ∼0.4 dB at a LOP of 2 dBm (optimum). Even when using novel sophisticated clustering designs in 16 clusters, no more than additional ∼0.3-dB Q-factor enhancement is observed. Finally, in contrast to the deterministic Volterra-NLE, MLC algorithms can partially tackle the stochastic parametric noise amplification .
Real-time gait phase detection using wearable sensors

Intelligent assistive devices using powered actuators are used to restore the gait patterns of amputees or patients with lower limb pathologies. These devices use feedback systems to drive actuators accurately at the right instances during gait. As such, information about gait phases in real-time is necessary to diagnose and/or to provide feedback to assistive devices. This paper presents a method to detect the gait phases in real-time using minimal hardware. A flex sensor that was mounted on a leather shoe was used to accurately measure the ankle angles as well as for the detection of the initial contact and toe-off events during a gait cycle. The data was sent to the software via serial interface and plotted to validate the results-which shows that the technique is feasible to be employed as an integral part of a feedback control system for a powered assistive device.
An Empirical Study on Display Ad Impression Viewability Measurements

Display advertising normally charges advertisers for every single ad impression. Specifically, if an ad in a webpage has been loaded in the browser, an ad impression is counted. However, due to the position and size of the ad slot, lots of ads are actually not viewed but still measured as impressions and charged. These fraud ad impressions indeed undermine the efficacy of display advertising. A perfect ad impression viewability measurement should match what the user has really viewed with a short memory. In this paper, we conduct extensive investigations on display ad impression viewability measurements on dimensions of ad creative displayed pixel percentage and exposure time to find which measurement provides the most accurate ad impression counting. The empirical results show that the most accurate measurement counts one ad impression if more than 75% of the ad creative pixels have been exposed for at least 2 continuous seconds.
The Nile Rat (Arvicanthis niloticus) as a Superior Carbohydrate-Sensitive Model for Type 2 Diabetes Mellitus (T2DM)

Type II diabetes mellitus (T2DM) is a multifactorial disease involving complex genetic and environmental interactions. No single animal model has so far mirrored all the characteristics or complications of diabetes in humans. Since this disease represents a chronic nutritional insult based on a diet bearing a high glycemic load, the ideal model should recapitulate the underlying dietary issues. Most rodent models have three shortcomings: (1) they are genetically or chemically modified to produce diabetes; (2) unlike humans, most require high-fat feeding; (3) and they take too long to develop diabetes. By contrast, Nile rats develop diabetes rapidly (8–10 weeks) with high-carbohydrate (hiCHO) diets, similar to humans, and are protected by high fat (with low glycemic load) intake. This review describes diabetes progression in the Nile rat, including various aspects of breeding, feeding, and handling for best experimental outcomes. The diabetes is characterized by a striking genetic permissiveness influencing hyperphagia and hyperinsulinemia; random blood glucose is the best index of disease progression; and kidney failure with chronic morbidity and death are outcomes, all of which mimic uncontrolled T2DM in humans. Non-alcoholic fatty liver disease (NAFLD), also described in diabetic humans, results from hepatic triglyceride and cholesterol accumulation associated with rising blood glucose. Protection is afforded by low glycemic load diets rich in certain fibers or polyphenols. Accordingly, the Nile rat provides a unique opportunity to identify the nutritional factors and underlying genetic and molecular mechanisms that characterize human T2DM.
Preparation of Bionic TiO2 Structure Using Aquatic Plants as Template

The bionic structure nanoporous TiO2 materials were prepared using aquatic plants as biological templates. The X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), high resolution transmission electron microscopy (HRTEM), nitrogen adsorption method and ultraviolet-visible light spectrometer were employed to characterize the structure of samples and the degradation performance of methylene blue solution under the visible light. The results showed that TiO2 sample inherited the porous structure of original template. Such bionic material was composed of ultra-thin piece layers which were full of TiO2 nanoparticles with size of about 10 nm. The product was studded with piled pores which had a few to dozens of nanoaperture. The material was doped with a small number of bionic legacy elements which can enhance the absorption of 400-800 nm range of the visible light, thus the bionic nanoporous TiO2 materials had better photocatalytic degradation effects of methylene blue solution in the sun.
A comparative analysis of WAN emulators

Testing network applications and protocols in a real WAN environment can be difficult and complex due to costs and distances. Therefore, many researchers and developers use network simulation or controlled testbeds where the WAN is emulated over cheap and widely spread LAN technologies such as Ethernet. In this paper, we present an up-to-date survey of WAN emulation tools. We discuss their main characteristics and the network parameters they allow to setup and modify. We also present the results of some experiments we conducted with the tools, using both IPv4 and IPv6 traffic, in order to verify their accuracy and analyze the results obtained.
Reducing Network Congestion and Synchronization Overhead During Aggregation of Hierarchical Data

Hierarchical data representations have been shown to be effective tools for coping with large-scale scientific data. Writing hierarchical data on supercomputers, however, is challenging as it often involves all-to-one communication during aggregation of low-resolution data which tends to span the entire network domain, resulting in several bottlenecks. We introduce the concept of indexing templates, which succinctly describe data organization and can be used to alter movement of data in beneficial ways. We present two techniques, domain partitioning and localized aggregation, that leverage indexing templates to alleviate congestion and synchronization overheads during data aggregation. We report experimental results that show significant I/O speedup using our proposed schemes on two of today's fastest supercomputers, Mira and Shaheen II, using the Uintah and S3D simulation frameworks.
A spline-based technique for optimal set point regulation through pseudo-inversion of nonminimum phase linear systems

This paper considers the optimal output set-point regulation for MIMO, non minimum phase sampled data systems. The usually proposed methods are based on stable model inversion whose exact solution is approximated through preview based implementation schemes. The new approach proposed here considers the meaningful practical situation of plants with a given, possibly uncertain, initial state, that can not be modified through pre-actuation. The structure of the optimal control input is ”a priori” assumed to be given by a smoothing spline function. In this way a twofold objective is achieved: a smooth behavior of the control input and its derivatives can be imposed, a very accurate tracking performance can be obtained by reducing the mesh size of spline [1]. Given the desired transient output response between two fixed set points, the spline coefficients are determined as the least-squares solution of the over determined system of linear equations obtained imposing that the spline function assumed as control input yields the specified output. In this way an optimal least square approximation of the desired output trajectory is obtained avoiding the stable explicit model inversion. Rather, this operation is implicitly approximately performed solving for the spline coefficients, the over-determined system of linear equations carrying the information on the model to be inverted and on the desired output. An interesting feature of this new method is that it also works for linear systems which are not required to be either square or right invertible.
An intelligent system for infant cry detection and information in real time

Acoustic analysis of infant cry signal can indicate the physical-emotional state of a baby and the cry-cause. Knowing it remotely is a challenge for working parents. This paper proposes an ‘Intelligent Cry Detection Information System (ICDIS)’, to automatically detect an infant's cry and alert the parents. Parents can verify whether baby is in-fact crying, by informing a care taker who can send a web/app-controlled smart robot to fetch live video-streaming. It also sends text/image message to the parent, with urgency-level. The proposed system consists of sensors, Signal Processing Unit (SPU) and Information Transmission Unit (ITU). The audio-visual signals are processed in SPU. Acoustic features extracted from cry signal are analyzed. If a cry is detected then ITU automatically sends SMS to the parents. Performance of the prototype ICDIS is evaluated using a ‘Infant Cry Signals Database’. The proposed system has potential applications in child care centers, schools and hospitals etc.
HIV testing and the care continuum among transgender women: population estimates from Rio de Janeiro, Brazil

Introduction: Evidence suggests that, of all affected populations, transgender women (transwomen) may have the heaviest HIV burden worldwide. Little is known about HIV linkage and care outcomes for transwomen. We aimed to estimate population‐level indicators of the HIV cascade of care continuum, and to evaluate factors associated with viral suppression among transwomen in Rio de Janeiro, Brazil.
The effects of prescribing varenicline on two‐year health outcomes: an observational cohort study using electronic medical records

Abstract Aims To investigate whether smokers prescribed varenicline had lower risks of serious ill‐health during the 4 years following treatment compared with those prescribed nicotine replacement therapy (NRT). Design Observational cohort study of electronic medical records. Setting A total of 370 UK general practices sampled from the Clinical Practice Research Datalink. Participants A total of 126 718 patients aged 18 and over who were issued smoking cessation prescriptions between 1 September 2006 and 31 March 2014. Measurements Our primary outcome was all‐cause mortality within 2 years of first prescription as indicated by linked Office of National Statistics data. Our secondary outcomes were cause‐specific mortality, all‐cause, cause‐specific hospitalization, primary care diagnosis of myocardial infarction or chronic obstructive pulmonary disease (COPD), body mass index and attendance rate to primary care within 2 years of first prescription. Risk differences and 95% confidence intervals were estimated by multivariable adjusted regression and propensity score matched regression. We used instrumental variable analysis to overcome residual confounding. Findings People prescribed varenicline were healthier at baseline than those prescribed NRT in almost all characteristics, highlighting the potential for residual confounding. Our instrumental variable analysis results found that people prescribed varenicline had a similar risk of mortality at 2 years [risk difference per 100 patients treated = 0.67, 95% confidence interval (CI) = ‐0.11 to 1.46)] to those prescribed NRT, and there were similar rates of all‐cause hospitalization, incident primary‐care diagnoses of myocardial infarction and COPD. People prescribed varenicline subsequently attended primary care less frequently. Conclusions Smokers prescribed varenicline in primary care in the United Kingdom do not appear to be less likely to die, be hospitalized or experience a myocardial infarction or chronic obstructive pulmonary disease during the following 2 years compared with smokers prescribed nicotine replacement therapy, but they gain more weight and attend primary care less frequently.
Separating Subjective Norms, University Descriptive and Injunctive Norms, and U.S. Descriptive and Injunctive Norms for Drinking Behavior Intentions

The theory of planned behavior and the social norms approach both stress the important influence that normative perceptions have on behavioral intentions and behavior. These 2 approaches were used to examine the behavioral intention to limit drinking to 0 to 4 drinks. Further, this study examined whether perception of subjective norms, university- and U.S.-level descriptive norms, and university- and U.S.-level injunctive norms represented separate dimensions for this behavioral intention. A representative sample of 1,100 undergraduate students completed a Web-based survey. The results confirmed that the 5 types of norms were all unique constructs and showed that individuals' intentions to limit their alcohol consumption to 0 to 4 drinks were predicted by positive attitudes, perceived behavioral control, subjective norms, U.S. descriptive norms, and U.S. injunctive norms. Subjective norms also moderated the relationship between perceived behavioral control and behavioral intention. University descriptive norms served as a moderator between attitudes and behavioral intentions and between perceived behavioral control and behavioral intentions. This study has important implications for norms-based theories and campaigns.