nils-herrmann/clean_scirepeval huggingface dataset:
Hyperimmune bovine colostrum as a low-cost, large-scale source of antibodies with broad neutralizing activity for HIV-1 envelope with potential use in microbicides.

Bovine colostrum (first milk) contains very high concentrations of IgG, and on average 1 kg (500 g/liter) of IgG can be harvested from each immunized cow immediately after calving. We used a modified vaccination strategy together with established production systems from the dairy food industry for the large-scale manufacture of broadly neutralizing HIV-1 IgG. This approach provides a low-cost mucosal HIV preventive agent potentially suitable for a topical microbicide. Four cows were vaccinated pre- and/or postconception with recombinant HIV-1 gp140 envelope (Env) oligomers of clade B or A, B, and C. Colostrum and purified colostrum IgG were assessed for cross-clade binding and neutralization against a panel of 27 Env-pseudotyped reporter viruses. Vaccination elicited high anti-gp140 IgG titers in serum and colostrum with reciprocal endpoint titers of up to 1 × 10(5). While nonimmune colostrum showed some intrinsic neutralizing activity, colostrum from 2 cows receiving a longer-duration vaccination regimen demonstrated broad HIV-1-neutralizing activity. Colostrum-purified polyclonal IgG retained gp140 reactivity and neutralization activity and blocked the binding of the b12 monoclonal antibody to gp140, showing specificity for the CD4 binding site. Colostrum-derived anti-HIV antibodies offer a cost-effective option for preparing the substantial quantities of broadly neutralizing antibodies that would be needed in a low-cost topical combination HIV-1 microbicide.
Randomized, double-blind, placebo-controlled clinical trial for evaluating the efficacy of fractional CO2 laser compared with topical estriol in the treatment of vaginal atrophy in postmenopausal women.

The aim of the study was to evaluate efficacy of fractional CO2 vaginal laser treatment (Laser, L) and compare it to local estrogen therapy (Estriol, E) and the combination of both treatments (Laser + Estriol, LE) in the treatment of vulvovaginal atrophy (VVA).



A total of 45 postmenopausal women meeting inclusion criteria were randomized in L, E, or LE groups. Assessments at baseline, 8 and 20 weeks, were conducted using Vaginal Health Index (VHI), Visual Analog Scale for VVA symptoms (dyspareunia, dryness, and burning), Female Sexual Function Index, and maturation value (MV) of Meisels.



Forty-five women were included and 3 women were lost to follow-up. VHI average score was significantly higher at weeks 8 and 20 in all study arms. At week 20, the LE arm also showed incremental improvement of VHI score (P = 0.01). L and LE groups showed a significant improvement of dyspareunia, burning, and dryness, and the E arm only of dryness (P < 0.001). LE group presented significant improvement of total Female Sex Function Index (FSFI) score (P = 0.02) and individual domains of pain, desire, and lubrication. In contrast, the L group showed significant worsening of pain domain in FSFI (P = 0.04), but FSFI total scores were comparable in all treatment arms at week 20.



CO2 vaginal laser alone or in combination with topical estriol is a good treatment option for VVA symptoms. Sexual-related pain with vaginal laser treatment might be of concern.
Identification of genic SSRs and construction of a SSR-based linkage map in Brassica juncea

Search for genic SSRs from transcriptome sequence data of Brassica juncea and B. nigra and from unigene databank of B. rapa resulted in identification of 20,529 SSRs from 330,827 gene sequences. Identified SSRs (named as unigene microsatellite; UGM) were characterized based on their number of repeats, type of motif and base composition. Primers were designed for 2118 UGMs after in silico polymorphism survey and were tested across 11 different genotypes of B. juncea and B. rapa for PCR amplification and polymorphism. It resulted in clear-cut amplification from 1993 UGMs of which 1319 UGMs showed polymorphism. It was observed that a priori in silico polymorphism survey helped in increasing the polymorphism percentage (6.1–13.2) by PCR amplification. We also report here the development of first SSR-based linkage map of Brassica juncea using a DH mapping population derived from F1 of the cross between the lines EH-2 and Pusajaikisan. The map consisted of 860 markers comprising 462 UGMs, 157 BAC-derived SSRs and 241 intron polymorphic markers and covered a total genetic length of 2073.6 cM. The study also reports an interesting observation of appearance of novel non-parental bands in the mapping population from 18 SSRs and 13 IP markers. Search of Arabidopsis genes orthologous to their primer sequences showed that 11 of such Arabidopsis genes code for proteins involved in various abiotic stresses. The highly transferable genic SSRs developed in the study would serve as valuable resources for comparative genome mapping, mapping of qualitative and quantitative traits, gene cloning and marker-assisted breeding in Brassica species.
Big Data Analysis in Smart Manufacturing: A Review

The technological evolution emerges a unified (Industrial) Internet of Things network, where loosely coupled smart manufacturing devices build smart manufacturing systems and enable comprehensive collaboration possibilities that increase the dynamic and volatility of their ecosystems. On the one hand, this evolution generates a huge field for exploitation, but on the other hand also increases complexity including new challenges and requirements demanding for new approaches in several issues. One challenge is the analysis of such systems that generate huge amounts of (continuously generated) data, potentially containing valuable information useful for several use cases, such as knowledge generation, key performance indicator (KPI) optimization, diagnosis, predication, feedback to design or decision support. This work presents a review of Big Data analysis in smart manufacturing systems. It includes the status quo in research, innovation and development, next challenges, and a comprehensive list of potential use cases and exploitation possibilities.
Going back in Time: An Investigation of Social Media Re-finding

Social Media (SM) has become a valuable information source to many in diverse situations. In IR, research has focused on real-time aspects and as such little is known about how long SM content is of value to users, if and how often it is re-accessed, the strategies people employ to re-access and if difficulties are experienced while doing so. We present results from a 5 month-long naturalistic, log-based study of user interaction with Twitter, which suggest re-finding to be a regular activity and that Tweets can offer utility for longer than one might think. We shed light on re-finding strategies revealing that remembered people are used as a stepping stone to Tweets rather than searching for content directly. Bookmarking strategies reported in the literature are used infrequently as a means to re-access. Finally, we show that by using statistical modelling it is possible to predict if a Tweet has future utility and is likely to be re-found. Our findings have implications for the design of social media search systems and interfaces, in particular for Twitter, to better support users re-find previously seen content.
Detecting Impersonation Attack in WiFi Networks Using Deep Learning Approach

WiFi network traffics will be expected to increase sharply in the coming years, since WiFi network is commonly used for local area connectivity. Unfortunately, there are difficulties in WiFi network research beforehand, since there is no common dataset between researchers on this area. Recently, AWID dataset was published as a comprehensive WiFi network dataset, which derived from real WiFi traces. The previous work on this AWID dataset was unable to classify Impersonation Attack sufficiently. Hence, we focus on optimizing the Impersonation Attack detection. Feature selection can overcome this problem by selecting the most important features for detecting an arbitrary class. We leverage Artificial Neural Network (ANN) for the feature selection and apply Stacked Auto Encoder (SAE), a deep learning algorithm as a classifier for AWID Dataset. Our experiments show that the reduced input features have significantly improved to detect the Impersonation Attack.
Anesthetic efficacy of metomidate and comparison of plasma cortisol responses to tricaine methanesulfonate, quinaldine and clove oil anesthetized channel catfish Ictalurus punctatus

The present experiments were designed to determine the efficacy of metomidate hydrochloride as an alternative anesthetic with potential cortisol blocking properties for channel catfish Ictalurus punctatus. Channel catfish (75 g) were exposed to concentrations of metomidate ranging from 0.5 to 16 ppm for a period of 60 min. At 16-ppm metomidate, mortality occurred in 65% of the catfish. No mortalities were observed at concentrations of 8 ppm or less. The minimum concentration of metomidate producing desirable anesthetic properties was 6 ppm. At this concentration, acceptable induction and recovery times were observed in catfish ranging from 3 to 810 g average body weight. Plasma cortisol levels during metomidate anesthesia (6 ppm) were compared to fish anesthetized with tricaine methanesulfonate (100 ppm), quinaldine (30 ppm) and clove oil (100 ppm). Cortisol levels of catfish treated with metomidate and clove oil remained at baseline levels during 30 min of anesthesia (P>0.05). Plasma cortisol levels of tricaine methanesulfonate and quinaldine anesthetized catfish peaked approximately eightand fourfold higher (P< 0.05), respectively, than fish treated with metomidate. These results suggest that the physiological disturbance of channel catfish during routine-handling procedures and stress-related research could be reduced through the use of metomidate as an anesthetic. D 2003 Elsevier Science B.V. All rights reserved.
A Reversible Data Hiding Scheme Based on Code Division Multiplexing

In this paper, a novel code division multiplexing (CDM) algorithm-based reversible data hiding (RDH) scheme is presented. The covert data are denoted by different orthogonal spreading sequences and embedded into the cover image. The original image can be completely recovered after the data have been extracted exactly. The Walsh Hadamard matrix is employed to generate orthogonal spreading sequences, by which the data can be overlappingly embedded without interfering each other, and multilevel data embedding can be utilized to enlarge the embedding capacity. Furthermore, most elements of different spreading sequences are mutually cancelled when they are overlappingly embedded, which maintains the image in good quality even with a high embedding payload. A location-map free method is presented in this paper to save more space for data embedding, and the overflow/underflow problem is solved by shrinking the distribution of the image histogram on both the ends. This would further improve the embedding performance. Experimental results have demonstrated that the CDM-based RDH scheme can achieve the best performance at the moderate-to-high embedding capacity compared with other state-of-the-art schemes.
The Function of Naringin in Inducing Secretion of Osteoprotegerin and Inhibiting Formation of Osteoclasts

Osteoporosis has become one of the most prevalent and costly diseases in the world. It is a metabolic disease characterized by reduction in bone mass due to an imbalance between bone formation and resorption. Osteoporosis causes fractures, prolongs bone healing, and impedes osseointegration of dental implants. Its pathological features include osteopenia, degradation of bone tissue microstructure, and increase of bone fragility. In traditional Chinese medicine, the herb Rhizoma Drynariae has been commonly used to treat osteoporosis and bone nonunion. However, the precise underlying mechanism is as yet unclear. Osteoprotegerin is a cytokine receptor shown to play an important role in osteoblast differentiation and bone formation. Hence, activators and ligands of osteoprotegerin are promising drug targets and have been the focus of studies on the development of therapeutics against osteoporosis. In the current study, we found that naringin could synergistically enhance the action of 1α,25-dihydroxyvitamin D3 in promoting the secretion of osteoprotegerin by osteoblasts in vitro. In addition, naringin can also influence the generation of osteoclasts and subsequently bone loss during organ culture. In conclusion, this study provides evidence that natural compounds such as naringin have the potential to be used as alternative medicines for the prevention and treatment of osteolysis.
Proceedings of the Frontiers in Retrovirology Conference 2018

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creat iveco mmons .org/licen ses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creat iveco mmons .org/ publi cdoma in/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Oral presentations
Generalized Overlap Measures for Evaluation and Validation in Medical Image Analysis

Measures of overlap of labelled regions of images, such as the Dice and Tanimoto coefficients, have been extensively used to evaluate image registration and segmentation algorithms. Modern studies can include multiple labels defined on multiple images yet most evaluation schemes report one overlap per labelled region, simply averaged over multiple images. In this paper, common overlap measures are generalized to measure the total overlap of ensembles of labels defined on multiple test images and account for fractional labels using fuzzy set theory. This framework allows a single "figure-of-merit" to be reported which summarises the results of a complex experiment by image pair, by label or overall. A complementary measure of error, the overlap distance, is defined which captures the spatial extent of the nonoverlapping part and is related to the Hausdorff distance computed on grey level images. The generalized overlap measures are validated on synthetic images for which the overlap can be computed analytically and used as similarity measures in nonrigid registration of three-dimensional magnetic resonance imaging (MRI) brain images. Finally, a pragmatic segmentation ground truth is constructed by registering a magnetic resonance atlas brain to 20 individual scans, and used with the overlap measures to evaluate publicly available brain segmentation algorithms
Designing vehicle tracking system - an open source approach

Vehicle tracking system has been extensively used for fleet management, asset tracking, surveillance, stolen vehicle recovery and many more. Advances in modern technologies like ubiquitous computing, Internet of Things (IoT) coupled with the availability of the economical hardware building blocks is creating a new wave of vehicular tracking systems. In this work we present VERTIGUO (VEhiculaR TrackInG Using Opensource approach), a GPS,GSM and GPRS technology based vehicular tracking system, that is accurate, robust, flexible, economical and feature rich. Unlike the traditional COTS (Commercial Of The Shelf) vehicular tracking system, that are closed and confined to smartphone and PC's, our vehicular tracking system infrastructure is open sourced and is available for the research fraternity to test, experiment and add more features. The hardware (HW) is developed by leveraging our expertize on open source HW platform. The software (SW) infrastructure can track the vehicles through a web interface on smartphones and PC or through an SMS on normal GSM based feature phones. This application will work for all mobile phones provided they are on a GSM network. In this paper we describe our system architecture, prototype and results obtained in our field trials.
Robust realtime physics-based motion control for human grasping

This paper presents a robust physics-based motion control system for realtime synthesis of human grasping. Given an object to be grasped, our system automatically computes physics-based motion control that advances the simulation to achieve realistic manipulation with the object. Our solution leverages prerecorded motion data and physics-based simulation for human grasping. We first introduce a data-driven synthesis algorithm that utilizes large sets of prerecorded motion data to generate realistic motions for human grasping. Next, we present an online physics-based motion control algorithm to transform the synthesized kinematic motion into a physically realistic one. In addition, we develop a performance interface for human grasping that allows the user to act out the desired grasping motion in front of a single Kinect camera. We demonstrate the power of our approach by generating physics-based motion control for grasping objects with different properties such as shapes, weights, spatial orientations, and frictions. We show our physics-based motion control for human grasping is robust to external perturbations and changes in physical quantities.
Current advances and future perspectives in extrusion-based bioprinting.

Extrusion-based bioprinting (EBB) is a rapidly growing technology that has made substantial progress during the last decade. It has great versatility in printing various biologics, including cells, tissues, tissue constructs, organ modules and microfluidic devices, in applications from basic research and pharmaceutics to clinics. Despite the great benefits and flexibility in printing a wide range of bioinks, including tissue spheroids, tissue strands, cell pellets, decellularized matrix components, micro-carriers and cell-laden hydrogels, the technology currently faces several limitations and challenges. These include impediments to organ fabrication, the limited resolution of printed features, the need for advanced bioprinting solutions to transition the technology bench to bedside, the necessity of new bioink development for rapid, safe and sustainable delivery of cells in a biomimetically organized microenvironment, and regulatory concerns to transform the technology into a product. This paper, presenting a first-time comprehensive review of EBB, discusses the current advancements in EBB technology and highlights future directions to transform the technology to generate viable end products for tissue engineering and regenerative medicine.
Fifty shades of HDR

From relatively unknown, just 5 years ago, High Dynamic Range (HDR) video is now having a major impact on most aspects of imaging. Although one of the five components of the specification for UHDTV, ITU-R Recommendation BT.2020 in 2012, it is only when it became apparent that HDR could help accelerate the slow penetration of 4K into the TV and home-cinema market, that HDR suddenly started to gain significant attention. But what exactly is HDR? Dynamic range is defined as the difference between the largest and smallest useable signal. In photography this has meant the luminance range of the scene being photographed. However, as HDR grows as a “marketing tool” this definition is becoming less “black & white”. This paper considers the different ways in which the term HDR is now being exploited; the challenges of achieving a complete efficient HDR pipeline from capture to display for a variety of applications; and, what could be done to help ensure HDR algorithms are future proof as HDR technology rapidly improves.
A novel liquid antenna for wearable bio-monitoring applications

The performance of the most commonly used metal antennas close to the human body is one of the limiting factors of the performance of bio-sensors and wireless body area networks (WBAN). Due to the high dielectric and conductivity contrast with respect to most parts of the human body (blood, skin, …), the range of most of the wireless sensors operating in RF and microwave frequencies is limited to 1–2 cm when attached to the body. In this paper, we introduce the very novel idea of liquid antennas, that is based on engineering the properties of liquids. This approach allows for the improvement of the range by a factor of 5–10 in a very easy-to-realize way, just modifying the salinity of the aqueous solution of the antenna. A similar methodology can be extended to the development of liquid RF electronics for implantable devices and wearable real-time bio-signal monitoring, since it can potentially lead to very flexible antenna and electronic configurations.
Super-resolution MIMO radar

A multiple input, multiple output (MIMO) radar emits probings signals with multiple transmit antennas and records the reflections from targets with multiple receive antennas. Estimating the relative angles, delays, and Doppler shifts from the received signals allows to determine the locations and velocities of the targets. Standard approaches to MIMO radar based on digital matched filtering or compressed sensing only resolve the angle-delay-Doppler triplets on a (1/(NTNR), 1/B, 1/T ) grid, where NT and NR are the number of transmit and receive antennas, B is the bandwidth of the probing signals, and T is the length of the time interval over which the reflections are observed. In this work, we show that the continuous angle-delay-Doppler triplets and the corresponding attenuation factors can be recovered perfectly by solving a convex optimization problem. This result holds provided that the angle-delay-Doppler triplets are separated either by 10/(NTNR - 1) in angle, 10.01/B in delay, or 10.01/T in Doppler direction. Furthermore, this result is optimal (up to log factors) in the number of angle-delay-Doppler triplets that can be recovered.
Defending against Adversarial Images using Basis Functions Transformations

We study the effectiveness of various approaches that defend against adversarial attacks on deep networks via manipulations based on basis function representations of images. Specifically, we experiment with low-pass filtering, PCA, JPEG compression, low resolution wavelet approximation, and soft-thresholding. We evaluate these defense techniques using three types of popular attacks in black, gray and white-box settings. Our results show JPEG compression tends to outperform the other tested defenses in most of the settings considered, in addition to soft-thresholding, which performs well in specific cases, and yields a more mild decrease in accuracy on benign examples. In addition, we also mathematically derive a novel white-box attack in which the adversarial perturbation is composed only of terms corresponding a to predetermined subset of the basis functions, of which a “low frequency attack” is a special case.
Ultra-Low Power VLSI Circuit Design Demystified and Explained: A Tutorial

In this paper, the state of the art in ultra-low power (ULP) VLSI design is presented within a unitary framework for the first time. A few general principles are first introduced to gain an insight into the design issues and the approaches that are specific to ULP systems, as well as to better understand the challenges that have to be faced in the foreseeable future. Intuitive understanding is accompanied by rigorous analysis for each key concept. The analysis ranges from the circuit to the micro-architectural level, and reference is given to process, physical and system levels when necessary. Among the main goals of this paper, it is shown that many paradigms and approaches borrowed from traditional above-threshold low-power VLSI design are actually incorrect. Accordingly, common misconceptions in the ULP domain are debunked and replaced with technically sound explanations.