Miracle-dz/UniFAR-FTUs huggingface dataset:
Lies in the Air: Characterizing Fake-base-station Spam Ecosystem in China

Fake base station (FBS) has been exploited by criminals to attack mobile users by spamming fraudulent messages for over a decade. Despite that prior work has proposed several techniques to mitigate this issue, FBS spam is still a long-standing challenging issue in some countries, such as China, and causes billions of dollars of financial loss every year. Therefore, understanding and exploring the thematic strategies in the FBS spam ecosystem at a large scale would improve the defense mechanisms. In this paper, we present the first large-scale characterization of FBS spam ecosystem by collecting three-month real-world FBS detection results. First, at "macro-level'', we uncover the characteristics of FBS spammers, including their business categories, temporal patterns and spatial patterns. Second, at "micro-level'', we investigate how FBS ecosystem is organized and how fraudulent messages are constructed by campaigns to trap users and evade detection. Collectively, the results expand our understanding of the FBS spam ecosystem and provide new insights into improved mitigation mechanisms for the security community.
Accuracy of immunoglobulin M immunoassay for diagnosis of chlamydial infections in infants and adults

An improved solid-phase enzyme immunoassay (EIA) with Chlamydia trachomatis L2 434/Bu elementary bodies was developed for the measurement of immunoglobulin M (IgM) antibody to C. trachomatis in serum. Comparison of EIA and microimmunofluorescence IgM antibody titers of 156 serum samples revealed an EIA sensitivity and specificity of 100% for infants, but reduced sensitivity (85%) and specificity (76%) for sera from adults. Sera containing IgM class rheumatoid factor produced false-positive IgM results which could easily be eliminated by pretreatment of the sera with anti-human IgG. Analysis of sera from infants with chlamydial infections revealed that 17 of 17 infants with C. trachomatis pneumonia had high IgM antibody titers (geometric mean titer, 1:64,812), whereas two infants with conjunctivitis only lacked detectable IgM antibody. EIA detected IgM antibody to several serovar groups in serum, including serovars B, BDE, FG, and J. IgM antibody to C. trachomatis in serum was detected as early as 5 days after the infection that was acquired at delivery and persisted for 3 months. The availability of an EIA possessing good sensitivity and specificity for the detection of IgM antibody to C. trachomatis may permit more laboratories to diagnose perinatal chlamydial infections.
Radiologic hand and wrist changes in systemic sclerosis: Associations with the disease duration, skin score and capillaroscopy

Objectives Patients with systemic sclerosis (SSc) have some musculoskeletal manifestations. The radiologic manifestations can be articular or non-articular. There is inconsistency in the correlation between clinical manifestations and radiologic changes; there are few reports on the correlation between them and capillaroscopy. Material and Methods We evaluated 81 patients with SSc, using a cross- sectional single center study, referred to scleroderma clinic affiliated to Shiraz University of Medical Sciences, Iran. Skin score and capillaroscopy were performed and an expert radiologist did the radiologic evaluation of the posterior-anterior views of both hands and wrists. For data analysis, SPSS version 19 was used.Results The participants consisted of 73 women and eight men aged 42±2.6 years old. There were 60.5% limited scleroderma (lcSSc) and 39.5% diffuse scleroderma (dcSSc) patients. After 5 years, 91% of them had some radiologic changes mostly asymptomatic.The most common radiologic changes were non-articular (70.1%), including acro-osteolysis, subcutaneous and peri-articular calcinosis and avascular necrosis. Flexion deformities and DIP joint space narrowing were more seen in patients with dcSSc. Resorption of the distal ulna and avascular necrosis was observed more in lcSSc. There was a correlation between radiologic changes and duration, but not with the skin score. The most common capillaroscopic pattern in patients with radiologic change was late scleroderma pattern.Conclusions Radiologic changes which were mostly asymptomatic were common in patients with SSc. The changes were different in patients with dcSSc and lcSSc and there were associations with duration and capillaroscopic patterns, but not with the skin score.
Effect of native actinobacteria on root knot nematode, Meloidogyne incognita in brinjal

Root knot nematode, Meloidogyne incognita is one of the major nematodes infesting brinjal. It is wide spread in India. An attempt was made to exploit rhizosphere bioagents for the management of root knot nematode. Rhizosphere soil samples were collected from healthy brinjal plants of nematode infested sick field at Virinchipuram village, Tamil Nadu. Around six Bacillus sp. isolates and one actinobacteria isolate were obtained from soil. Preliminary screening was done with culture filtrates of these isolates on egg hatching and nematode penetration. The observations showed that actinobacteria (V5) cultural filtrate @ 75% concentration showed 51.7 % inhibition in egg hatching compared to control. A significant reduction in juvenile penetration (tc > tt) and number of galls per plant as well as number of egg masses were observed in actinobacteria treated brinjal (variety VRM1) plants. A pot culture experiment was carried out to test the effect actinobacteria (V5) in brinjal against M. incognita. Results revealed that the egg mass production was reduced to an extent of 55 % compared to untreated control by the application of actinobacteria culture filtrate.
Characterization of metallo-β-lactamases produced by carbapenem-resistant Pseudomonas aeruginosa in pediatric patients

Objective To characterize metallo-β-lactamases (MBL) produced by carbapenem resistant Pseudomonas aeruginosa. Methods Fifty-nine strains of resistance to imipenem or meropenem were collected. Isolates were further evaluated for MBL production. MBL E test strips were used to screen the phenotype of MBL production. Molecular screening for blaVIM, blaIMP, blaSPM and blaGIM was carried out using primers targeting the conserved regions of the MBL genes. Results Of the 59 carbapenem resistant Pseudomonas. aeruginosa, 29(49.2%)were MBL positive, and 39(66.1%) that were positive for MBL genes by PCR. 35(89.7%)were also positive for blaIMP genes and 4(10.3%) were positive for blaVIM genes. All isolates were negative for blaSPM and blaGIM genes. Resistance of MBL-producing strains to piperacilin and piperacil-tazobactam were higher than non-MBL-producing of carbapenem resistant strains (P0.05) . MIC50 of producing MBLs to cefo-taxime, cefoperazone, ceftazidime, cefepime and cefoperazone-sulbactam was 256μg/ml. MIC90 of MBL-producing strains to them 256μg/ml. Conclusion MBL-producing strains are more common in pediatric patients. The production of MBL is one of the important mechanisms of carbapenem resistant Pseudomonas aeruginosa. It was demonstrated that MBL-producing strains were associated with higher rates ofβ-lactamases resistance than the non-MBL producing of carbapenem resistant strains.
NARMAX Identification Based Closed-Loop Control of Flow Separation over NACA 0015 Airfoil

A closed-loop control algorithm for the reduction of turbulent flow separation over NACA 0015 airfoil equipped with leading-edge synthetic jet actuators (SJAs) is presented. A system identification approach based on Nonlinear Auto-Regressive Moving Average with eXogenous inputs (NARMAX) technique was used to predict nonlinear dynamics of the fluid flow and for the design of the controller system. Numerical simulations based on URANS equations are performed at Reynolds number of 106 for various airfoil incidences with and without closed-loop control. The NARMAX model for flow over an airfoil is based on the static pressure data, and the synthetic jet actuator is developed using an incompressible flow model. The corresponding NARMAX identification model developed for the pressure data is nonlinear; therefore, the describing function technique is used to linearize the system within its frequency range. Low-pass filtering is used to obtain quasi-linear state values, which assist in the application of linear control techniques. The reference signal signifies the condition of a fully re-attached flow, and it is determined based on the linearization of the original signal during open-loop control. The controller design follows the standard proportional-integral (PI) technique for the single-input single-output system. The resulting closed-loop response tracks the reference value and leads to significant improvements in the transient response over the open-loop system. The NARMAX controller enhances the lift coefficient from 0.787 for the uncontrolled case to 1.315 for the controlled case with an increase of 67.1%.
Herpetofauna of the Environmental Protection Area Delta do Parnaíba, Northeastern Brazil

Recent studies on Brazilian coastal zones and restinga environments revealed a high richness ofamphibian and reptile species. However, there is still a lack of information about herpetofaunadiversity in coastal zones of Northeastern Brazil. This study provides a checklist of amphibiansand reptiles inhabiting the Environmental Protection Area (EPA) Delta do Parnaiba, NortheasternBrazil, suggesting conservation actions. To elaborate the checklist, we searched in sevenelectronic databases and check the following scientific collections: Zoological collection ofUniversidade Federal do Piaui (UFPI) and Herpetological collection of Universidade Regionaldo Cariri (URCA). In addition, we sampled 16 areas along the EPA Delta do Parnaiba close tothe river branches and temporary ponds that compose the Parnaiba River Delta (December 2015to April 2017) to fill gaps of information about herpetofauna in some regions from the EPA. Werecorded 86 species (34 amphibians and 52 reptiles), including four anurans, one crocodilian,14 snakes, 12 lizards and two amphisbaenians reported for the first time for the EPA Delta doParnaiba. In addition, we added the first record of the snake Oxybelis fulgidus in Piaui state. TheEPA Delta do Parnaiba shows high herpetofaunal richness; thus, we suggest that conservationactions should be taken to preserve the restingas environments in the Parnaiba River Delta andits high diversity of amphibians and reptiles.
REAL OBSERVATIONS AND SIMULATION OF FREEWAY MERGING TRAFFIC AT BAGHDAD CITY

ABSTRACT Freeway merging sections represent the sources of vehicles entering along freeways and the sources of some of the complicated interactions between merging and the freeway traffic. Therefore such merging sections are considered as an important part of the freeways. This paper abstracts some traffic characteristics at merging locations using video recordings and a speed gun device at Baghdad city. The selected parameters include estimating of lane distribution of the freeway traffic at merging location, types of merging (normal, forced and cooperative) and merging distance. The observed data have been used to develop a simulation model for such locations using PARAMICS micro-simulator. The model has been calibrated and validated based on the available data. The results suggested the ability of the developed model to represents real traffic conditions and therefore the model has been used to examine some traffic management controls. The observed data suggested that the force merging is the dominated type in the case of small available gaps.
Incidence of Salmonella typhi in fruit juices sold in Allahabad city and their antibiotic susceptibility pattern

Continuous rise in the number of outbreaks of food borne multi drug resistant (MDR) typhoid in India is an escalating problem and is linked to fresh fruit juices. MDR isolates of Salmonella typhi are on rise and are becoming a challenge for timely and appropriate treatment. In present work eighty fruit juice samples (40 each of pomegranate and orange) were collected from different locations of Allahabad City. The samples were analyzed for the presence of Salmonella typhi. The isolated Salmonella typhi were subjected to ten commercial antibiotic employing disc diffusion assay. Total 22 isolates of Salmonella typhi were collected from juice samples and incidence of Salmonella typhi from these samples was found to be 25% (16.9x104cfu/ml) in case of orange and 30% (6.08x104cfu/ml) in pomegranate juice. Among the ten commercial antibiotics tested, ofloxacin and chloramphenicol showed 100% sensitivity against Salmonella typhi isolates followed by co-trimoxazole, gatifloxacin and ciprofloxacin with a sensitivity of 95.45%. The least sensitivity (18.18%) shown by ampicillin and intermediate sensitivity was observed in cefixime (36.36%), nalidixic acid (68.18%), ceftriaxone (72.73%) and norfloxacin (90.91%). It was observed that out of total 22 isolates only one was found to be multi drug resistant. Appropriate administration of hygienic measures such as checking the quality of water used for the dilution as well as prevailing unhygienic condition related to washing of utensils and maintenance of the premises may reduce risk.
Effect of different concentrations of roselle on physico-chemical changes in pomegranate wine

Pomegranate (Punica granatum L.) fruits which were unmarketable were used for the preparation of wine. The effect of different concentrations of roselle on various physico-chemical properties of pomegranate wine was investigated. The wine prepared from pomegranate arils with 32oB sugar syrup, 2.5 per cent rind powder and 0.4 % roselle was found best as compared to other treatments with higher TSS (11.45 oB), ascorbic acid (81.55 mg/100 ml), antioxidants (342.43 mg AAE/100 ml), phenols (384.07 mg GAE/100ml), alcohol (10.69) during primary fermentation and at storage of 30, 60 and 90 days were found desirable with physico-chemical properties.
How Can Self-Attention Networks Recognize Dyck-n Languages?

We focus on the recognition of Dyck-n (Dn) languages with self-attention (SA) networks, which has been deemed to be a difficult task for these networks. We compare the performance of two variants of SA, one with a starting symbol (SA+) and one without (SA-). Our results show that SA+ is able to generalize to longer sequences and deeper dependencies. For D2, we find that SA- completely breaks down on long sequences whereas the accuracy of SA+ is 58.82%. We find attention maps learned by SA+ to be amenable to interpretation and compatible with a stack-based language recognizer. Surprisingly, the performance of SA networks is at par with LSTMs, which provides evidence on the ability of SA to learn hierarchies without recursion.
Deep RL With Information Constrained Policies: Generalization in Continuous Control

Biological agents learn and act intelligently in spite of a highly limited capacity to process and store information. Many real-world problems involve continuous control, which represents a difficult task for artificial intelligence agents. In this paper we explore the potential learning advantages a natural constraint on information flow might confer onto artificial agents in continuous control tasks. We focus on the model-free reinforcement learning (RL) setting and formalize our approach in terms of an information-theoretic constraint on the complexity of learned policies. We show that our approach emerges in a principled fashion from the application of rate-distortion theory. We implement a novel Capacity-Limited Actor-Critic (CLAC) algorithm and situate it within a broader family of RL algorithms such as the Soft Actor Critic (SAC) and Mutual Information Reinforcement Learning (MIRL) algorithm. Our experiments using continuous control tasks show that compared to alternative approaches, CLAC offers improvements in generalization between training and modified test environments. This is achieved in the CLAC model while displaying the high sample efficiency of similar methods.
Evaluating galaxy dynamical masses from kinematics and jeans equilibrium in simulations

We provide prescriptions to evaluate the dynamical mass ($M_{\rm dyn}$) of galaxies from kinematic measurements of stars or gas using analytic considerations and the VELA suite of cosmological zoom-in simulations at $z=1-5$. We find that Jeans or hydrostatic equilibrium is approximately valid for galaxies of stellar masses above $M_\star \! \sim\! 10^{9.5}M_\odot$ out to $5$ effective radii ($R_e$). When both measurements of the rotation velocity $v_\phi$ and of the radial velocity dispersion $\sigma_r$ are available, the dynamical mass $M_{\rm dyn} \! \simeq\! G^{-1} V_c^2 r$ can be evaluated from the Jeans equation $V_c^2= v_\phi^2 + \alpha \sigma_r^2$ assuming cylindrical symmetry and a constant, isotropic $\sigma_r$. For spheroids, $\alpha$ is inversely proportional to the S\'ersic index $n$ and $\alpha \simeq 2.5$ within $R_e$ for the simulated galaxies. The prediction for a self-gravitating exponential disc, $\alpha = 3.36(r/R_e)$, is invalid in the simulations, where the dominant spheroid causes a weaker gradient from $\alpha \! \simeq\! 1$ at $R_e$ to 4 at $5R_e$. The correction in $\alpha$ for the stars due to the gradient in $\sigma_r(r)$ is roughly balanced by the effect of the aspherical potential, while the effect of anisotropy is negligible. When only the effective projected velocity dispersion $\sigma_l$ is available, the dynamical mass can be evaluated as $M_{\rm dyn} = K G^{-1} R_e \sigma_l^2$, where the virial factor $K$ is derived from $\alpha$ given the inclination and $v_\phi/\sigma_r$. We find that the standard value $K=5$ is approximately valid only when averaged over inclinations and for compact and thick discs, as it ranges from 4.5 to above 10 between edge-on and face-on projections.
Nonstationary Reinforcement Learning with Linear Function Approximation

We consider reinforcement learning (RL) in episodic Markov decision processes (MDPs) with linear function approximation under drifting environment. Specifically, both the reward and state transition functions can evolve over time, as long as their respective total variations, quantified by suitable metrics, do not exceed certain \textit{variation budgets}. We first develop the $\texttt{LSVI-UCB-Restart}$ algorithm, an optimistic modification of least-squares value iteration combined with periodic restart, and establish its dynamic regret bound when variation budgets are known. We then propose a parameter-free algorithm, $\texttt{Ada-LSVI-UCB-Restart}$, that works without knowing the variation budgets, but with a slightly worse dynamic regret bound. We also derive the first minimax dynamic regret lower bound for nonstationary MDPs to show that our proposed algorithms are near-optimal. As a byproduct, we establish a minimax regret lower bound for linear MDPs, which is unsolved by \cite{jin2020provably}. In addition, we provide numerical experiments to demonstrate the effectiveness of our proposed algorithms. As far as we know, this is the first dynamic regret analysis in nonstationary reinforcement learning with function approximation.
Token-level Adaptive Training for Neural Machine Translation

There exists a token imbalance phenomenon in natural language as different tokens appear with different frequencies, which leads to different learning difficulties for tokens in Neural Machine Translation (NMT). The vanilla NMT model usually adopts trivial equal-weighted objectives for target tokens with different frequencies and tends to generate more high-frequency tokens and less low-frequency tokens compared with the golden token distribution. However, low-frequency tokens may carry critical semantic information that will affect the translation quality once they are neglected. In this paper, we explored target token-level adaptive objectives based on token frequencies to assign appropriate weights for each target token during training. We aimed that those meaningful but relatively low-frequency words could be assigned with larger weights in objectives to encourage the model to pay more attention to these tokens. Our method yields consistent improvements in translation quality on ZH-EN, EN-RO, and EN-DE translation tasks, especially on sentences that contain more low-frequency tokens where we can get 1.68, 1.02, and 0.52 BLEU increases compared with baseline, respectively. Further analyses show that our method can also improve the lexical diversity of translation.
On the Absence of Spurious Local Minima in Nonlinear Low-Rank Matrix Recovery Problems

The restricted isometry property (RIP) is a well-known condition that guarantees the absence of spurious local minima in low-rank matrix recovery problems with linear measurements. In this paper, for general low-rank matrix recovery problems with nonlinear measurements, a novel property named bound difference property (BDP) is introduced. Using RIP and BDP jointly, we propose a new criterion to certify the nonexistence of spurious local minima in the rank-1 case, and prove that it leads to a much stronger theoretical guarantee than the existing bounds on RIP.
Addressing the Real-world Class Imbalance Problem in Dermatology

Class imbalance is a common problem in medical diagnosis, causing a standard classifier to be biased towards the common classes and perform poorly on the rare classes. This is especially true for dermatology, a specialty with thousands of skin conditions but many of which have low prevalence in the real world. Motivated by recent advances, we explore few-shot learning methods as well as conventional class imbalance techniques for the skin condition recognition problem and propose an evaluation setup to fairly assess the real-world utility of such approaches. We find the performance of few-show learning methods does not reach that of conventional class imbalance techniques, but combining the two approaches using a novel ensemble improves model performance, especially for rare classes. We conclude that ensembling can be useful to address the class imbalance problem, yet progress can further be accelerated by real-world evaluation setups for benchmarking new methods.
Dirichlet Graph Variational Autoencoder

Graph Neural Networks (GNNs) and Variational Autoencoders (VAEs) have been widely used in modeling and generating graphs with latent factors. However, there is no clear explanation of what these latent factors are and why they perform well. In this work, we present Dirichlet Graph Variational Autoencoder (DGVAE) with graph cluster memberships as latent factors. Our study connects VAEs based graph generation and balanced graph cut, and provides a new way to understand and improve the internal mechanism of VAEs based graph generation. Specifically, we first interpret the reconstruction term of DGVAE as balanced graph cut in a principled way. Furthermore, motivated by the low pass characteristics in balanced graph cut, we propose a new variant of GNN named Heatts to encode the input graph into cluster memberships. Heatts utilizes the Taylor series for fast computation of heat kernels and has better low pass characteristics than Graph Convolutional Networks (GCN). Through experiments on graph generation and graph clustering, we demonstrate the effectiveness of our proposed framework.
Mark-Evaluate: Assessing Language Generation using Population Estimation Methods

We propose a family of metrics to assess language generation derived from population estimation methods widely used in ecology. More specifically, we use mark-recapture and maximum-likelihood methods that have been applied over the past several decades to estimate the size of closed populations in the wild. We propose three novel metrics: ME_\text{Petersen} and ME_\text{CAPTURE}, which retrieve a single-valued assessment, and ME_\text{Schnabel} which returns a double-valued metric to assess the evaluation set in terms of quality and diversity, separately. In synthetic experiments, our family of methods is sensitive to drops in quality and diversity. Moreover, our methods show a higher correlation to human evaluation than existing metrics on several challenging tasks, namely unconditional language generation, machine translation, and text summarization.