Miracle-dz/UniFAR-FTUs huggingface dataset:
A New Approach to Achieve Maximum Power Point Tracking for PV System With a Variable Inductor

Maximum power transfer in solar microgrid applications is achieved by impedance matching with a dc-dc converter with maximum power point tracking by the incremental conductance method. Regulation and dynamic control is achieved by operating with continuous conduction. It can be shown that under stable operation, the required output inductor has an inductance versus current characteristic, whereby the inductance falls off with increasing current, corresponding to increasing incident solar radiation. This paper describes how a variable inductor whereby the inductor core progressively saturates with increasing current meets this requirement and has the advantage of reducing the overall size of the inductor by up to 75% and increases the operating range of the tracker to recover solar energy at low solar levels.
Frequency-domain equalization for continuous phase modulation

Frequency-domain equalization for continuous phase modulation (CPM) is investigated. A discrete representation of the CPM signal is obtained by using the Gram-Schmidt orthonormalization procedure. The CPM discrete signal representation admits frequency-domain equalization for the purpose of mitigating intersymbol interference. General full- and partial-response CPM waveforms, and specific examples of MSK and GMSK with BT=0.3 are considered. Frequency-domain equalization is shown to be effective for CPM on severe frequency-selective fading channels.
There are No Bit Parts for Sign Bits in Black-Box Attacks

We present a black-box adversarial attack algorithm which sets new state-of-the-art model evasion rates for query efficiency in the $\ell_\infty$ and $\ell_2$ metrics, where only loss-oracle access to the model is available. On two public black-box attack challenges, the algorithm achieves the highest evasion rate, surpassing all of the submitted attacks. Similar performance is observed on a model that is secure against substitute-model attacks. For standard models trained on the MNIST, CIFAR10, and IMAGENET datasets, averaged over the datasets and metrics, the algorithm is 3.8x less failure-prone, and spends in total 2.5x fewer queries than the current state-of-the-art attacks combined given a budget of 10, 000 queries per attack attempt. Notably, it requires no hyperparameter tuning or any data/time-dependent prior. The algorithm exploits a new approach, namely sign-based rather than magnitude-based gradient estimation. This shifts the estimation from continuous to binary black-box optimization. With three properties of the directional derivative, we examine three approaches to adversarial attacks. This yields a superior algorithm breaking a standard MNIST model using just 12 queries on average!
Ropivacaine at different concentrations on intrapartum fever, IL-6 and TNF-α in parturient with epidural labor analgesia

Effects of ropivacaine at different concentrations on intrapartum fever, interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) in parturient with epidural labor analgesia were compared to provide reference for the rational selection of anesthetics in clinic. Medical records of 198 cases of primi-paras admitted to the Obstetrics and Gynecology Department, Shanghai First Maternity and Infant Hospital, Tongji University School of Medicine, from January 2017 to January 2018 were analyzed retrospectively and divided into 2 groups. A total of 105 patients were treated with 0.075% ropivacaine injection 10 ml and 0.5 µg/ml sulfentanyl injection 100 ml in parturition as the experimental group, and 93 patients were treated with 0.1% ropivacaine injection 10 ml and 0.5 µg/ml sulfentanyl injection 100 ml in parturition as the control group. After patient-controlled epidural analgesia, the pain visual analogue score (VAS), labor duration, administration time and febrile rate of parturient after administration were compared between the two groups at different time-points. Venous blood 2 ml was taken at T1 (cervix open to 2 cm), T2 (cervix fully open) and T3 (24 h postpartum), and the concentration of IL-6 TNF-α was detected by enzyme-linked immunosorbent assay. The time of the second stage of labor and analgesia were shorter in the experimental group than that in the control group after administration (P<0.05). The febrile rate of parturient in the experimental group was lower than that in the control group (P<0.05). The concentration of IL-6 and TNF-α in the experimental group was lower than that in the control group at T2 (P<0.05; P<0.01). The effect of patient-controlled epidural administration with 0.075% ropivacaine injection combined with 0.5 mg/ml sulfentanyl injection on labor analgesia is shorter than that with 0.1% ropivacaine combined with sulfentanyl. It could also shorten the duration of the second stage of labor, reduce the intrapartum febrile rate, and alleviate inflammation.
Prevalence and Characterization of Food-Related Methicillin-Resistant Staphylococcus aureus (MRSA) in China

Methicillin-resistant Staphylococcus aureus (MRSA) is an emerging pathogen that is difficult to treat due to the multiresistance of the bacteria upon infection. From 2011 to 2016, 1581 S. aureus strains were isolated from 4300 samples from retail foods covering most provincial capitals in China. To determine the prevalence of food-related MRSA and its genetic background in China, antibiotic resistance, staphylococcal toxin genes, staphylococcal cassette chromosome mec (SCCmec) typing, spa-typing and MLST were carried out in this study. In total, 108 (7.4%) isolates were confirmed for MRSA by phenotyping (cefoxitin) and genotyping (mecA/mecC gene). A total of 52.8% (57/108) of the MRSA isolates belonged to clonal complex 59 (CC59) (ST59, ST338, and ST3355), which was the predominant clone in this study. These CC59 isolates carried SCCmec elements of type IV, V, or III and exhibited spa type t437, t441, t543, t163, t1785, or t3485, and half of them carried major virulence genes, such as the Panton-Valentine leucocidin (PVL) gene. The secondary clones belonged to ST9 (15.7%, 17/108) with a type of t899-SCCmec III and showed a broader range of antimicrobial resistance. The remaining MRSA isolates (31.5%, 34/108) were distributed in 12 different STs and 18 different spa types. All isolates harbored at least one of the enterotoxin genes, whereas only 4 isolates (3.70%) were positive for the toxic shock syndrome toxin tsst alleles. For antibiotic susceptibility testing, all isolates were resistant to more than three antibiotics, and 79.6% of the isolates were resistant to more than 10 antibiotics. Amoxycillin/clavulanic acid, ampicillin, cefoxitin, penicillin, ceftazidime, kanamycin, streptomycin, clindamycin, and telithromycin was the most common antibiotic resistance profile (55.6%, 60/108) in the study. In summary, the results of this study implied that the major food-related MRSA isolate in China was closer to community-associated MRSA, and some of the remaining isolates (ST9-t899-SCCmec III) were supposed to livestock-associated MRSA. In addition, most MRSA isolates showed resistance to multiple drugs and harbored staphylococcal toxin genes. Thus, the pathogenic potential of these isolates cannot be ignored. In addition, further studies are needed to elucidate the transmission routes of MRSA in relation to retail foods and to determine how to prevent the spread of MRSA.
Behavioral plasticity in larval reef fish: orientation is influenced by recent acoustic experiences

Animals use many different cues to orient in their environment, solve directional movement challenges, and select suitable habitat. Recent work has highlighted the importance of the ambient soundscape in providing orientation cues for larvae of coral reef fishes at the key life-history phase when they recruit from open ocean to coral reef environments. In this study, we combined acoustic conditioning with binary choice chambers and used 442 settlement-stage larvae from 4 Pomacentridae (damselfish) species (Pomacentrus amboinensis, P. brachialis, P. moluccensis, and P. nagasakiensis) to test whether responses to acoustic cues are fixed or whether behavior is influenced by recent acoustic experience. Over 8 trials, groups of wild-caught larvae that experienced noise (natural reef noise or artificial tone noise) during a 12-h conditioning period showed a positive directional response to reef noise in the chambers. Groups conditioned with reef noise responded adversely to the tone noise, whereas groups conditioned to the artificial tones were subsequently attracted by them. This plasticity in behavior suggests that settlement-stage larval reef fish (∼20 days old) are influenced by, and can retain information from, recent acoustic experiences. Behavioral plasticity may enable greater control by larvae over their selection of settlement sites but could also mean that anthropogenic sounds have more than masking effects on the orientation behavior of fishes. Copyright 2010, Oxford University Press.
Silencing of lncRNA PKIA-AS1 Attenuates Spinal Nerve Ligation-Induced Neuropathic Pain Through Epigenetic Downregulation of CDK6 Expression

Neuropathic pain (NP) is among the most intractable comorbidities of spinal cord injury. Dysregulation of non-coding RNAs has also been implicated in the development of neuropathic pain. Here, we identified a novel lncRNA, PKIA-AS1, by using lncRNA array analysis in spinal cord tissue of spinal nerve ligation (SNL) model rats, and investigated the role of PKIA-AS1 in SNL-mediated neuropathic pain. We observed that PKIA-AS1 was significantly upregulated in SNL model rats and that PKIA-AS1 knockdown attenuated neuropathic pain progression. Alternatively, overexpression of PKIA-AS1 was sufficient to induce neuropathic pain-like symptoms in uninjured rats. We also found that PKIA-AS1 mediated SNL-induced neuropathic pain by directly regulating the expression and function of CDK6, which is essential for the initiation and maintenance of neuroinflammation and neuropathic pain. Therefore, our study identifies PKIA-AS1 as a novel therapeutic target for neuroinflammation related neuropathic pain.
Explaining a black-box using Deep Variational Information Bottleneck Approach

Briefness and comprehensiveness are necessary in order to give a lot of information concisely in explaining a black-box decision system. However, existing interpretable machine learning methods fail to consider briefness and comprehensiveness simultaneously, which may lead to redundant explanations. We propose a system-agnostic interpretable method that provides a brief but comprehensive explanation by adopting the inspiring information theoretic principle, information bottleneck principle. Using an information theoretic objective, VIBI selects instance-wise key features that are maximally compressed about an input (briefness), and informative about a decision made by a black-box on that input (comprehensive). The selected key features act as an information bottleneck that serves as a concise explanation for each black-box decision. We show that VIBI outperforms other interpretable machine learning methods in terms of both interpretability and fidelity evaluated by human and quantitative metrics.
Downlink NOMA in Multi-UAV Networks over Bivariate Rician Shadowed Fading Channels

Unmanned aerial vehicles (UAVs) are set to feature heavily in upcoming fifth generation (5G) networks. Yet, the adoption of multi-UAV networks means that spectrum scarcity in UAV communications is an issue in need of urgent solutions. Towards this end, downlink non-orthogonal multiple access (NOMA) is investigated in this paper for multi-UAV networks to improve spectrum utilization. Using the bivariate Rician shadowed fading model, closed-form expressions for the joint probability density function (PDF), marginal cumulative distribution functions (CDFs), and outage probability expressions are derived. Under a stochastic geometry framework for downlink NOMA at the UAVs, an outage probability analysis of the multi-UAV network is conducted, where it is shown that downlink NOMA attains lower outage probability than orthogonal multiple access (OMA). Furthermore, it is shown that NOMA is less susceptible to shadowing than OMA.
Reproducibility of ultrasound attenuation imaging for the noninvasive evaluation of hepatic steatosis

Purpose The purpose of this study was to evaluate the intra-observer reproducibility of ultrasound attenuation imaging (ATI) for the noninvasive assessment of hepatic steatosis in patients with suspected hepatic steatosis and the inter-observer reproducibility in asymptomatic volunteers. Methods This prospective study was approved by our institutional review board and informed consent was obtained from all patients. In group 1, composed of patients with suspected hepatic steatosis (n=143), one abdominal radiologist performed gray-scale ultrasonography and two sessions of ATI. In group 2, composed of healthy volunteers (n=18), three independent sessions of ATI were performed by three abdominal radiologists. The visual degree of hepatic steatosis in all study subjects was graded on a 4-point scale by two independent reviewers using gray-scale ultrasonography. Thereafter, the attenuation coefficient (AC) was correlated with the degree of hepatic steatosis using Spearman rank correlation analysis. Intra-class correlation coefficients (ICCs) were used to assess the intra-observer (group 1) and inter-observer reproducibility (group 2) of ATI measurements. Results For the intra-observer reproducibility of ATI, the ICC was 0.929 (95% confidence interval [CI], 0.901 to 0.949), and the coefficient of variation was 7.1%. Inter-observer reproducibility of ATI measurements showed an ICC of 0.792 (95% CI, 0.549 to 0.916). The AC showed a significant correlation with the visual grade of hepatic steatosis for both reviewers (rho, 0.780 and 0.695; P<0.001, respectively). Conclusion ATI showed high intra- and inter-observer reproducibility in the assessment of hepatic steatosis.
Gilbert damping constant of ultrathin perpendicularly magnetized CoFeB/Pt-structures

For the development of new spintronic devices there is currently a great interest in influencing the magnetic state of a system by means of an electric current. An good example of such a device is the ’racetrack memory’ as introduced by S. Parkin [Science, vol. 320, pp 19
Accelerating web application loading with snapshot of event and DOM handling

Reducing the loading time of a web app is important for a better user experience. The loading time includes a large amount of JavaScript execution, often composed of the execution of the global code in the script tags followed by the execution of event handlers. One approach to accelerate the app loading is saving the already-loaded execution state of JavaScript objects in a file called the snapshot in advance. Then, we start an app by copying the objects in the snapshot to the JavaScript heap directly, instead of executing JavaScript code to create them. Unfortunately, existing works save only the execution state of the global code in the snapshot, not that of the event handlers. Also, JavaScript code whose execution may change the DOM (Document Object Model) tree is not saved in the snapshot, limiting the coverage of the snapshot. In this paper, we introduce snapshot+, an extended version of the snapshot where we save the execution state of the event handlers as well as that of the global code. Unlike the global code whose execution order is statically determined, the event handlers have a more dynamic execution order, depending on the triggering order of the events and the registration order of the event handlers. This makes it somewhat complicated to decide when to create and restore the snapshot. Snapshot+ provides a new API for the app developer to specify and register the event handlers eligible for snapshot, so the browser can create and restore the snapshot at the right place automatically. Also, snapshot+ can save a changed DOM tree in a serialized HTML string and restore it during app loading, allowing the DOM-changing JavaScript executions to be saved in the snapshot. Our experimental results show that snapshot+ can improve the app loading time by 52% (AngularJS apps), 42% (Ext JS apps), 48% (jQuery apps), and 18% (MooTools apps), compared to the original snapshot.
The Intensity of Early Attentional Processing, but Not Conflict Monitoring, Determines the Size of Subliminal Response Conflicts

Response conflicts hamper goal-directed behavior and may be evoked by both consciously and subliminally (unconsciously) processed information. Yet, not much is known about the mechanisms and brain regions driving the size of subliminally induced conflicts. We hence combined a response conflict paradigm featuring subliminal primes and conscious flankers with in-depth neurophysiological (EEG) analyses, including source localization in a sample of N = 243 healthy subjects. Intra-individual differences in the size of subliminal conflicts were reflected both during early attentional stimulus processing (prime-associated N1 and target-associated P1 and N1 amplitudes) and conflict monitoring (N2 amplitudes). On the neuroanatomical level, this was reflected by activity modulations in the TPJ (BA39, BA40) and V2 (BA18), which are known to be involved in attentional stimulus processing and task set maintenance. In addition to a “standard” analysis of event-related potentials, we also conducted a purely data-driven machine learning approach using support vector machines (SVM) in order to identify neurophysiological features which do not only reflect the size of subliminal conflict, but actually allow to classify/predict it. This showed that only extremely early information processing (about 65 ms after the onset of the prime) was predictive of subliminal conflict size. Importantly, this predictive feature occurred before target information could even be processed and was reflected by activity in the left middle frontal gyrus (BA6) and insula (BA13). We conclude that differences in task set maintenance and potentially also in subliminal attentional processing of task-relevant features, but not conflict monitoring, determine the size of subliminally induced response conflicts.
Protein signatures linking history of miscarriages and metabolic syndrome: a proteomic study among North Indian women

Background Metabolic syndrome (MeS), a constellation of metabolic adversities, and history of miscarriage make women at a higher risk for cardiovascular diseases (CVDs). However, molecular evidence indicating a link between the two phenotypes (history of miscarriage and MeS) among women would offer an opportunity to predict the risk factor for CVDs at an early stage. Thus, the present retrospective study attempts to identify the proteins signatures (if any) to understand the connection between the history of miscarriage and MeS. Methods Age-matched 80 pre-menopausal women who were not on any medical intervention or drugs were recruited from a Mendelian population of the same gene pool. Recruited women were classified into four groups—(a) Group A—absolute cases with history of miscarriage and MeS, (b) Group B—absolute controls without any history of miscarriage and MeS, (c) Group C—cases with MeS but lack any history of miscarriage, (d) Group D—cases with history of miscarriage but lack MeS. Differentially expressed proteins in plasma samples of women from four groups were identified using 2-D gel electrophoresis and mass spectrometry. Results Three case groups (A, C, and D) showed 18 differentially expressed proteins. Nearly 60% of proteins (11/18) were commonly dysregulated in Group C (only with MeS) and Group D (only with miscarriage history). Nearly 40% of proteins (7/18) were commonly dysregulated in the three case groups (Groups A, C, and D), indicating a shared pathophysiology. Four proteins were exclusive but shared by case groups C and D indicating the independent routes for CVDs through MeS or miscarriages. In absolute cases, transthyretin (TTR) showed exclusive upregulation, which was further validated by Western blotting and ELISA. Networking analyses showed the strong association of TTR with haptoglobin, transferrin and ApoA1 hinting toward a cross-talk among these proteins which could be a cause or an effect of TTR upregulation. Conclusion The study provides evidence for molecular link between the history of miscarriage and MeS through a putative role of TTR. However, longitudinal follow-up studies with larger sample size would further help to demonstrate the significance of TTR and other targeted proteins in risk stratification and the onset of CVDs.
GPU-accelerated fixpoint algorithms for faster compiler analyses

Inter-procedural data-flow analyses are slow. We parallelize these predicate propagation fixpoint algorithms efficiently on a GPU. Our approach is (mostly) synchronization free even though the processed graphs in general are cyclic and have nodes with fan-in and fan-out degrees above 1. We detect and fix any data races that occur while propagating predicates in a SIMD fashion. Additionally, we solve the parallel termination problem by means of heuristics. The GPU-codes of five data-flow analyses are up to 89.8 times faster than their sequential LLVM variants. Offloading the analyses to the GPU saves up to 26.5% of the total compilation time.
Recovery of a mixture of Gaussians by sum-of-norms clustering

Sum-of-norms clustering is a method for assigning $n$ points in $\mathbb{R}^d$ to $K$ clusters, $1\le K\le n$, using convex optimization. Recently, Panahi et al.\ proved that sum-of-norms clustering is guaranteed to recover a mixture of Gaussians under the restriction that the number of samples is not too large. The purpose of this note is to lift this restriction, i.e., show that sum-of-norms clustering with equal weights can recover a mixture of Gaussians even as the number of samples tends to infinity. Our proof relies on an interesting characterization of clusters computed by sum-of-norms clustering that was developed inside a proof of the agglomeration conjecture by Chiquet et al. Because we believe this theorem has independent interest, we restate and reprove the Chiquet et al.\ result herein.
Genome-Wide Transcriptional Responses of Mycobacterium to Antibiotics

Antibiotics can stimulate or depress gene expression in bacteria. The analysis of transcriptional responses of Mycobacterium to antimycobacterial compounds has improved our understanding of the mode of action of various drug classes and the efficacy and effect of such compounds on the global metabolism of Mycobacterium. This approach can provide new insights for known antibiotics, for example those currently used for tuberculosis treatment, as well as help to identify the mode of action and predict the targets of new compounds identified by whole-cell screening assays. In addition, changes in gene expression profiles after antimycobacterial treatment can provide information about the adaptive ability of bacteria to escape the effects of antibiotics and allow monitoring of the physiology of the bacteria during treatment. Genome-wide expression profiling also makes it possible to pinpoint genes differentially expressed between drug sensitive Mycobacterium and multidrug-resistant clinical isolates. Finally, genes involved in adaptive responses and drug tolerance could become new targets for improving the efficacy of existing antibiotics.