Miracle-dz/UniFAR-FTUs huggingface dataset:
Multiobjective Optimization in 5G Hybrid Networks

The increasing adoption of the Internet of Things has led to the need for systems with higher spectral and energy efficiency (EE) in order to enable communication. Larger data rate demands had led researchers to look at millimeter wave (mmWave) bands to boost network rates. This paper investigates the downlink performance of a three-tier heterogeneous network that consists of sub-6 GHz macrocells overlaid with small cells operating on both the mmWave and sub-6 GHz bands. A model is developed using tools from stochastic geometry to analyze the coverage, rate, area spectral efficiency, and EE of such a network. Various deployment strategies and their impacts on the considered metrics are studied. Simulation results are used to verify the validity of the proposed model.
Alveolar ridge augmentation with maxillary sinus elevation and split crest

Abstract The purpose of this study was to evaluate the clinical and radiological outcomes of 2 piezosurgical split techniques performed in conjunction with the sinus lift. The present retrospective study included 20 patients with edentulism of the posterior maxilla who had undergone the sinus lift and alveolar ridge split treatment separately or the sinus lift combined with the monoblock alveolar ridge split. Differences between these 2 techniques were analyzed. All the surrounding areas successfully produced an adequate bone volume for the insertion of implants. A clinical evaluation showed a mean vertical augmentation of 3.6 ± 0.4 mm in Group A and 3.2 ± 0.7 mm in Group B. With regards to the lateral augmentation, the clinical evaluation gives a mean gain of 5.2 ± 0.3 mm in Group A and 4.9 ± 0.5 mm in Group B. The mean vertical and horizontal bone augmentation recorded for both types of surgical procedures were comparable. The proposed surgical procedures enabled the tridimensional volume of the alveolar ridge to be recreated. This resulted in the creation of a natural contour of hard and soft tissues which enabled a functional and aesthetic rehabilitation of the edentulous posterior maxilla to be obtained.
Comparison of Collaborative Versus Single-Site Quality Improvement to Reduce NICU Length of Stay

In this study, we describe a multihospital QI collaborative project to reduce LOS for preterm neonates during NICU hospitalization. BACKGROUND: There is unexplained variation in length of stay (LOS) across NICUs, suggesting that there may be practices that can optimize LOS. METHODS: Three groups of NICUs in the California Perinatal Quality Care Collaborative were followed: (1) collaborative centers participating in an 18-month collaborative quality improvement project to optimize LOS for preterm infants; (2) individual centers aiming to optimize LOS; and (3) nonparticipants. Our aim in the collaborative project was to decrease postmenstrual age (PMA) at discharge for infants born between 27 + 0 and <32 weeks’ gestational age by 3 days. A secondary outcome was “early discharge,” the proportion of infants discharged from the hospital before 36 + 5 weeks’ PMA. The balancing measure of readmissions within 72 hours was tracked for the collaborative group. RESULTS: From 2013 to 2015, 8917 infants were cared for in 20 collaborative NICUs, 19 individual project NICUs, and 71 nonparticipants. In the collaborative group, the PMA at discharge decreased from 37.8 to 37.5 weeks (P = .02), and early discharge increased from 31.6% to 41.9% (P = .006). The individual project group had no significant change. Nonparticipants had a decrease in PMA from 37.5 to 37.3 weeks (P = .01) but no significant change in early discharge (39.8% to 43.6%; P = .24). There was no significant change in readmissions over time in the collaborative group. CONCLUSIONS: A structured collaborative project that was focused on optimizing LOS led to a 3-day decrease in LOS and was more effective than individualized quality improvement efforts.
Triple negative breast cancer subtypes and pathologic complete response rate to neoadjuvant chemotherapy

Triple negative breast cancer (TNBC) is a heterogeneous disease with distinct molecular subtypes that differentially respond to chemotherapy and targeted agents. The purpose of this study is to explore the clinical relevance of Lehmann TNBC subtypes by identifying any differences in response to neoadjuvant chemotherapy among them. We determined Lehmann subtypes by gene expression profiling in paraffined pre-treatment tumor biopsies from 125 TNBC patients treated with neoadjuvant anthracyclines and/or taxanes +/- carboplatin. We explored the clinicopathological characteristics of Lehmann subtypes and their association with the pathologic complete response (pCR) to different treatments. The global pCR rate was 37%, and it was unevenly distributed within Lehmann’s subtypes. Basal-like 1 (BL1) tumors exhibited the highest pCR to carboplatin containing regimens (80% vs 23%, p=0.027) and were the most proliferative (Ki-67>50% of 88.2% vs. 63.7%, p=0.02). Luminal-androgen receptor (LAR) patients achieved the lowest pCR to all treatments (14.3% vs 42.7%, p=0.045 when excluding mesenchymal stem-like (MSL) samples) and were the group with the lowest proliferation (Ki-67≤50% of 71% vs 27%, p=0.002). In our cohort, only tumors with LAR phenotype presented non-basal-like intrinsic subtypes (HER2-enriched and luminal A). TNBC patients present tumors with a high genetic diversity ranging from highly proliferative tumors, likely responsive to platinum-based therapies, to a subset of chemoresistant tumors with low proliferation and luminal characteristics.
Multivariate Sexual Selection on Ejaculate Traits under Sperm Competition

The widespread prevalence of sperm competition means that ejaculates face intense sexual selection. However, prior investigations of sexual selection on gametes have been hampered by two difficulties: (1) deriving estimates of relative fitness from sperm competition trials that are comparable across rival male and female genotypes and (2) obtaining measures of competitive fertilization success that are not confounded by postzygotic effects. Here, we exploit the experimental tractability of a broadcast spawning marine invertebrate to overcome these challenges and characterize multivariate sexual selection on sperm traits when multiple ejaculates compete. In multimale spawning events, we tracked real-time success of sperm using fluorescent tags that are visible inside fertilized eggs. We then used multivariate selection analyses to identify patterns of linear and nonlinear sexual selection on multiple sperm morphology and motility traits. Specifically, we found nonlinear selection against divergent combinations of sperm length, velocity, and swimming path linearity. These patterns likely reflect the way different swimming strategies allow sperm to locate and track eggs. Our results demonstrate that there are overall patterns of selection on ejaculates across a biologically realistic range of ejaculate-ejaculate and ejaculate-female interactions; therefore, there is the potential for adaptive evolution of ejaculate traits under sperm competition.
Diffusion of CH4 and CO2 from subarctic lakes in Stordalen, Abisko

Extensive amounts of carbon are stored in the Arctic region, and high latitudes lakes play a large role in the dynamics of methane (CH4) and carbon dioxide (CO2). CH4 is a very important greenhouse gas and one of the major emission pathways is via diffusion. During the ice-free seasons in 2016 and 2017, diffusive sedimentary CH4 and CO2 fluxes were measured in three subarctic lakes in northern Sweden. 21 equilibration samplers were deployed in the lakes and 1050 measurements were taken, with 19 respectively 18 calculations of diffusive sedimentary CH4 and CO2 fluxes. The diffusive sedimentary CH4 and CO2 fluxes ranged between 2.57-14.41 respectively 3.82-61.64 mg m 2 d . Almost all flux and concentration ratios of CO2:CH4 exceeded the 1:1 ratio, which is important in regards to estimations of global warming potential of northern lakes. With lake chambers were diffusive turbulencedriven water surface CH4 fluxes estimated and 298 measurements were taken. During 2016 (June to October) the fluxes ranged between 0.77-14.01 mg m 2 d 1 and during 2017 (June to September) the fluxes ranged between 1.62-10.19 mg m 2 d . In general was the diffusive sedimentary CH4 fluxes higher than the diffusive turbulence-driven water surface CH4 fluxes, when compared during the same temporal period and spatial condition. A systematic temporal variability was presented for the diffusive turbulence-driven water surface CH4 fluxes, with high fluxes during the warmest months July and August. Due to limited data of the diffusive sedimentary CH4 and CO2 fluxes, no clear temporal pattern was presented. Distinct spatial trends could be distinguished in one out of the three lakes, with higher fluxes by the shore border which could be related to easily accessible labile carbon from mire deposits. How atmospheric pressure, air temperature, lake temperature and wind speed control the variability of the diffusive turbulence-driven water surface CH4 fluxes were analyzed. Increasing diffusive turbulence-driven water surface CH4 fluxes was presented with higher airand water temperatures, as well as decreasing atmospheric pressure. The environmental parameters, including depth, was as well analyzed in relation to the diffusive sedimentary CH4 and CO2 fluxes, were no significant correlations were shown. With amplifying temperature rises in the Arctic region, it is of great importance to understand the controlling mechanisms of diffusive sedimentary and turbulence-driven water surface fluxes. Quantification of sedimentary diffusive fluxes from northern lakes are limited, and measurements are critical in order to further assess the global warming potential of high latitude lakes.
Cooperative broadcast performance prediction using inter-node distance distributions

In this paper we propose a novel approach for the performance prediction of multistage cooperative broadcast. It is based on inter-node distance distributions, considers each stage independently and employs the expected values of the coverage area and the number of nodes reached. The required distance distributions are derived and a simple but accurate approximation of their expected values is discussed. The proposed approach is then evaluated for a large range of node densities and compared to Monte Carlo simulations. We thereby show that it leads to very accurate performance predictions for the coverage area and the number of nodes reached in each stage, even for low node densities.
A Hormone-Driven Epigenetic Mechanism for Adaptation in Autonomous Robots

Different epigenetic mechanisms provide biological organisms with the ability to adjust their physiology and/or morphology and adapt to a wide range of challenges posed by their environments. In particular, one type of epigenetic process, in which hormone concentrations are linked to the regulation of hormone receptors, has been shown to have implications for behavioral development. In this paper, taking inspiration from these biological processes, we investigate whether an epigenetic model based on the concept of hormonal regulation of receptors can provide a similarly robust and general adaptive mechanism for autonomous robots. We have implemented our model using a Koala robot, and tested it in a series of experiments in six different environments with varying challenges to negotiate. Our results, including the emergence of varied behaviors that permit the robot to exploit its current environment, demonstrate the potential of our epigenetic model as a general mechanism for adaptation in autonomous robots.
Radar classification of human gait abnormality based on sum-of-harmonics analysis

Radar technology for monitoring of human gait has recently gained interest in the fields of home security, medical diagnosis, assisted living and rehabilitation. Due to its remote, reliable and privacy-preserving sensing, radar is promising to become an effective tool for medical gait analysis. We show the influences of gait abnormalities and assistive walking devices on the joint-variable representations of the back-scattered radar signals. Using both, parametric and non-parametric techniques, we extract gait features to classify normal, abnormal and cane-assisted gait. In particular, the fundamental frequency of the time-frequency behavior is estimated using sum-of-harmonics modeling in order to characterize different gaits. Results obtained using experimental K-band radar data are presented for the person-specific and person-generic case.
The central role of the propensity score in observational studies for causal effects

Abstract : The results of observational studies are often disputed because of nonrandom treatment assignment. For example, patients at greater risk may be overrepresented in some treatment group. This paper discusses the central role of propensity scores and balancing scores in the analysis of observational studies. The propensity score is the (estimated) conditional probability of assignment to a particular treatment given a vector of observed covariates. Both large and small sample theory show that adjustment for the scalar propensity score is sufficient to remove bias due to all observed covariates. Applications include: matched sampling on the univariate propensity score which is equal percent bias reducing under more general conditions than required for discriminant matching, multivariate adjustment by subclassification on balancing scores where the same subclasses are used to estimate treatment effects for all outcome variables and in all subpopulations, and visual representation of multivariate adjustment by a two-dimensional plot. (Author)
Vertical Distribution of Total Mercury and Mercury Methylation in a Landfill Site in Japan

Mercury is a neurotoxin, with certain organic forms of the element being particularly harmful to humans. The Minamata Convention was adopted to reduce the intentional use and emission of mercury. Because mercury is an element, it cannot be decomposed. Mercury-containing products and mercury used for various processes will eventually enter the waste stream, and landfill sites will become a mercury sink. While landfill sites can be a source of mercury pollution, the behavior of mercury in solid waste within a landfill site is still not fully understood. The purpose of this study was to determine the depth profile of mercury, the levels of methyl mercury (MeHg), and the factors controlling methylation in an old landfill site that received waste for over 30 years. Three sampling cores were selected, and boring sampling was conducted to a maximum depth of 18 m, which reached the bottom layer of the landfill. Total mercury (THg) and MeHg were measured in the samples to determine the characteristics of mercury at different depths. Bacterial species were identified by 16S rRNA amplification and sequencing, because the methylation process is promoted by a series of genes. It was found that the THg concentration was 19–975 ng/g, with a geometric mean of 298 ng/g, which was slightly less than the 400 ng/g concentration recorded 30 years previously. In some samples, MeHg accounted for up to 15–20% of THg, which is far greater than the general level in soils and sediments, although the source of MeHg was unclear. The genetic data indicated that hgcA was present mostly in the upper and lower layers of the three cores, merA was almost as much as hgcA, while the level of merB was hundreds of times less than those of the other two genes. A significant correlation was found between THg and MeHg, as well as between MeHg and MeHg/THg. In addition, a negative correlation was found between THg and merA. The coexistence of the three genes indicated that both methylation and demethylation processes could occur, but the lack of merB was a barrier for demethylation.
Do Download Reports Reliably Measure Journal Usage? Trusting the Fox to Count Your Hens?

Download rates of academic journals have joined citation counts as commonly used indicators of the value of journal subscriptions. While citations reflect worldwide influence, the value of a journal subscription to a single library is more reliably measured by the rate at which it is downloaded by local users. If reported download rates accurately measure local usage, there is a strong case for using them to compare the cost-effectiveness of journal subscriptions. We examine data for nearly 8,000 journals downloaded at the ten universities in the University of California system during a period of six years. We find that controlling for number of articles, publisher, and year of download, the ratio of downloads to citations differs substantially among academic disciplines. After adding academic disciplines to the control variables, there remain substantial “publisher effects”, with some publishers reporting significantly more downloads than would be predicted by the characteristics of their journals. These cross-publisher differences suggest that the currently available download statistics, which are supplied by publishers, are not sufficiently reliable to allow libraries to make subscription decisions based on price and reported downloads, at least without making an adjustment for publisher effects in download reports.
A Decentralized Replica Placement Algorithm for Edge Computing

As the devices that make up the Internet become more powerful, algorithms that orchestrate cloud systems are on the verge of putting more responsibility for computation and storage on these devices. In our current age of Big Data, dissemination and storage of data across end cloud devices is becoming a prominent problem subject to this expansion. In this paper, we propose a distributed data dissemination approach that relies on dynamic creation/replacement/removal of replicas guided by continuous monitoring of data requests coming from edge nodes of the underlying network. Our algorithm exploits geographical locality of data during the dissemination process due to the plenitude of common data requests that stem from the clients within a close proximity. Our results using both real-world and synthetic data demonstrate that a decentralized replica placement approach provides significant cost benefits compared to client side caching that is widely used in traditional distributed systems.
Adversarial Learning with Local Coordinate Coding

Generative adversarial networks (GANs) aim to generate realistic data from some prior distribution (e.g., Gaussian noises). However, such prior distribution is often independent of real data and thus may lose semantic information (e.g., geometric structure or content in images) of data. In practice, the semantic information might be represented by some latent distribution learned from data, which, however, is hard to be used for sampling in GANs. In this paper, rather than sampling from the pre-defined prior distribution, we propose a Local Coordinate Coding (LCC) based sampling method to improve GANs. We derive a generalization bound for LCC based GANs and prove that a small dimensional input is sufficient to achieve good generalization. Extensive experiments on various real-world datasets demonstrate the effectiveness of the proposed method.
Using URL shorteners to compare phishing and malware attacks

In this work we use URL shortener click analytics to compare the life cycle of phishing and malware attacks. We have collected over 7,000 malicious short URLs categorized as phishing or malware for the 2 year period covering 2016 and 2017, along with their reported date. We analyze the short URLs and find that phishing attacks are most active 4 hours before the reported date, while malware attacks are most active 4 days before the reported date. We find that phishing attacks have higher click through rate with shorter timespan. Conversely malware attacks have lower click through rate with longer timespan. We also show the comparisons of referrers and countries from which short URLs are accessed, showing in particular an increased use of social media to spread both kinds of attacks. We also find phishing clicks mainly come from USA and Brazil, while malware clicks mainly come from USA and Russia. Overall based on the observation that 50% of malware attacks are active for several years, while less than 50% of phishing attacks are active past 3 months, we conclude that the efforts against phishing attacks are stronger than the efforts against malware attacks.
Defects and Low-Frequency Noise in Irradiated Black Phosphorus MOSFETs With HfO2 Gate Dielectrics

We have evaluated radiation-induced charge trapping and low-frequency noise in passivated black phosphorus (BP) MOSFETs with HfO2 gate dielectrics. Thinning the gate dielectric reduces total ionizing dose-induced threshold voltage shifts. The defect-energy distribution estimated from low-frequency noise measurements performed as a function of temperature decreases with increasing energy in as-processed devices. Local maxima in noise magnitude are observed in irradiated devices at activation energies of ~0.2 and ~0.5 eV. Larger defect-related peaks in noise magnitude in the range of 0.35–0.5 eV are observed after biased post-irradiation annealing, and/or vacuum storage of the devices after irradiation and annealing. Density functional theory calculations strongly support significant roles for O vacancies in HfO2 and H+ transport and reactions near the BP/HfO2 interface in the observed radiation response and low-frequency noise.
SGM: Sequence Generation Model for Multi-label Classification

Multi-label classification is an important yet challenging task in natural language processing. It is more complex than single-label classification in that the labels tend to be correlated. Existing methods tend to ignore the correlations between labels. Besides, different parts of the text can contribute differently for predicting different labels, which is not considered by existing models. In this paper, we propose to view the multi-label classification task as a sequence generation problem, and apply a sequence generation model with a novel decoder structure to solve it. Extensive experimental results show that our proposed methods outperform previous work by a substantial margin. Further analysis of experimental results demonstrates that the proposed methods not only capture the correlations between labels, but also select the most informative words automatically when predicting different labels.
Comparison of different channel modeling techniques used in NB-PLC systems

Using Power Line communication (PLC) is suitable for several Smart Grid applications. Due to the absence of applicable channel model, PLC systems have been slowed down. This paper compares different channel models of Narrowband Power-Line Communication (NB-PLC) which are voltage ratio approach (VRA), ABCD approach, multipath and finite impulse response filter (FIR). Simulation results show that ABCD and VRA methods have not the same behavior despite the same condition of network. It is seen that when the number of branches is increased the channel becomes very frequency selective and the attenuation is dependent also from the length of the cable, frequency and the nature of loads connected to the network. It is therefore suggested that NB-PLC channel modeling will not be based on a mathematical equation of the method but the variation of its transfer function in real time depending on several parameters such as network topology, branches number, charges, and branch length.