Miracle-dz/UniFAR-FTUs huggingface dataset:
Image recognition with deep neural networks in presence of noise - Dealing with and taking advantage of distortions

Data classification in presence of noise can lead to much worse results than expected for pure patterns. In this paper we investigate this problem in the case of deep convolutional neural networks in order to propose solutions that can mitigate influence of noise. The main contributions presented in this paper are experimental examination of influence of different types of noise on the convolutional neural network, proposition of a deep neural network operating as a denoiser, investigation of a deep network training with noise contaminated patterns, and finally an analysis of noise addition during the training process of a deep network as a form of regularization. Our main findings are construction of the deep network based denoising filter which outperforms state-of-the-art solutions, as well as proposition of a practical method of deep neural network training with noisy patterns for improvement against the noisy test patterns. All results are underpinned by experiments which show high efficacy and possibly broad applications of the proposed solutions.
Physical Demand Profiles of Hatha Yoga Postures Performed by Older Adults

Understanding the physical demands placed upon the musculoskeletal system by individual postures may allow experienced instructors and therapists to develop safe and effective yoga programs which reduce undesirable side effects. Thus, we used biomechanical methods to quantify the lower extremity joint angles, joint moments of force, and muscle activities of 21 Hatha yoga postures, commonly used in senior yoga programs. Twenty older adults, 70.7 years ± 3.8 years, participated in a 32-wk yoga class (2 d/wk) where they learned introductory and intermediate postures (asanas). They then performed the asanas in a motion analysis laboratory. Kinematic, kinetic, and electromyographic data was collected over three seconds while the participants held the poses statically. Profiles illustrating the postures and including the biomechanical data were then generated for each asana. Our findings demonstrated that Hatha yoga postures engendered a range of appreciable joint angles, JMOFs, and muscle activities about the ankle, knee, and hip, and that demands associated with some postures and posture modifications were not always intuitive. They also demonstrated that all of the postures elicited appreciable rectus abdominis activity, which was up to 70% of that induced during walking.
Outcomes of hip arthroscopy. A prospective analysis and comparison between patients under 25 and over 25 years of age

Objective To compare the results of hip arthroscopy in patients under the age of 25 with those over 25 years. Design From March 2006 until May 2010, data were collected on all patients who underwent hip arthroscopy for symptomatic intra-articular hip pathology. The patients were divided into two groups based on age (less than 25 years and over 25 years). Patients completed the modified Harris hip score (MHHS), non-arthritic hip score (NAHS) and hip dysfunction and osteoarthritis outcome score (HOOS) questionnaires at baseline then at 6 weeks, 6 months, 12 months and at latest follow-up. Participants 88 patients who underwent 94 hip arthroscopies by the senior author. Mean age was 24.3 (range 11–57 years). Results The mean NAHS and HOOS subscales for pain and activities of daily living were worse at baseline in over 25 groups. Follow-up ranged from 9 to 68 months. 45 hips had greater than 3 year follow-up. The MHHS improved in both groups with a mean difference in the under-25 group of 16.22, and 20.88 in the over 25s. Improvements in the NAHS and HOOS subscales were also of a similar magnitude. There was no statistically significant difference between outcome scores of the two groups at the latest follow-up visit. Conclusions We found a comparable improvement in outcome between those patients under 25 years and those over 25 years. We propose that hip arthroscopy is of potential benefit to patients with symptoms of femoroacetabular impingement regardless of age.
The Well-Founded Semantics of Cyclic Probabilistic Logic Programs : Meaning and Complexity

This paper investigates the properties of cyclic probabilistic normal logic programs, consisting of rules and a set of independent probabilistic facts, under the well-founded semantics. That is, we assume that for each fixed truth assignment for the probabilistic facts, the resulting normal logic program is interpreted through the well-founded semantics. We derive results concerning the complexity of inference, and discuss the challenging interplay between threevalued assignments and probabilities.
Limited Preemption EDF Scheduling of Sporadic Task Systems

The optimality of the Earliest Deadline First scheduler for uniprocessor systems is one of the main reasons behind the popularity of this algorithm among real-time systems. The ability of fully utilizing the computational power of a processing unit however requires the possibility of preempting a task before its completion. When preemptions are disabled, the schedulability overhead could be significant, leading to deadline misses even at system utilizations close to zero. On the other hand, each preemption causes an increase in the runtime overhead due to the operations executed during a context switch and the negative cache effects resulting from interleaving tasks' executions. These factors have been often neglected in previous theoretical works, ignoring the cost of preemption in real applications. A hybrid limited-preemption real-time scheduling algorithm is derived here, that aims to have low runtime overhead while scheduling all systems that can be scheduled by fully preemptive algorithms. This hybrid algorithm permits preemption where necessary for maintaining feasibility, but attempts to avoid unnecessary preemptions during runtime. The positive effects of this approach are not limited to a reduced runtime overhead, but will be extended as well to a simplified handling of shared resources.
English as a second language learner differences in anaphoric resolution: Reading to learn in the academic context

To succeed at a university, students need to read expository texts effectively and meaningfully to access and understand information, and internalize it for study purposes. An important component of the comprehension process is the reader's ability to integrate current information with information mentioned earlier in a text. One aspect of this integration process involves anaphoric resolution. This paper reports on findings from a study that investigated anaphoric resolution by first-year English as a second language students during the reading of expository texts. The relationship between skill in anaphoric resolution, academic performance, and language proficiency was examined. Linguistic and textual factors such as type and inference strength of anaphoric tie were also taken into account to examine differential resolution effects. The findings showed that students who were not performing well academically were not skilled at resolving anaphors. Anaphoric resolution was also affected by linguistic and textual differences. Differences in anaphoric resolution diminished as proficiency in English increased. Anaphoric resolution was also affected by the strength of the anaphoric tie; successful anaphoric resolution dropped when the anaphoric tie required greater inferential processing. This was particularly evident among the academically weaker students. The findings suggest that anaphoric resolution in expository texts plays an important role in reading to learn. The implications of these findings are briefly discussed for English as a second language students.
Test Generation for Open Defects in CMOS Circuits

Open defects in CMOS circuits require two-pattern tests for detection. Traditionally, the only two-pattern tests included in manufacturing test are those targeting transition delay faults. Such tests, however, do not provide complete coverage of all the open defects. In this paper we propose the use of a unified test set that detects all inline resistance faults which model interconnect open defects and all transistor stuck-open faults which model intra-gate open defects in order to obtain a comprehensive coverage of open defects. We also describe a method of generating the proposed test set using an ATPG program for transition delay faults whose sizes are comparable to transition delay fault based test set
Route-aware MAC protocols for Sensor Networks

Fundamental tradeoffs between energy consumption and sustainable quality of services such as throughput and response time are critical in sensor networks because of limited and often irreplaceable battery power. This paper presents a novel energy saving approach, namely route-awareness. This approach provides a wide spectrum of design alternatives even under an extremely low energy budget. Route-awareness is a form of cross-layer optimization techniques that allows sensor nodes to save energy by “sleeping” opportunistically when they are not part of a routing path. This can drastically save energy in large scale sensor network applications that monitor and track infrequently occurring events. Routeawareness meshes well with existing MAC schemes including both contention and schedule based MAC (TDMA) ones to form a class of route-aware sensor MAC protocols. We explore tradeoffs between energy consumption and performance such as throughput and delay which are enabled by route-awareness for sensor networks employing directed diffusion. We found that MAC protocols employing routeawareness provide a far richer set of design choices, especially over a low energy budget, than when they are used alone. In particular, the simulation results show that routeaware TDMA provides better energy-delay tradeoffs than route-aware contention-based MAC schemes.
Automatic Classification of Verbs in Biomedical Texts

Lexical classes, when tailored to the application and domain in question, can provide an effective means to deal with a number of natural language processing (NLP) tasks. While manual construction of such classes is difficult, recent research shows that it is possible to automatically induce verb classes from cross-domain corpora with promising accuracy. We report a novel experiment where similar technology is applied to the important, challenging domain of biomedicine. We show that the resulting classification, acquired from a corpus of biomedical journal articles, is highly accurate and strongly domain-specific. It can be used to aid BIO-NLP directly or as useful material for investigating the syntax and semantics of verbs in biomedical texts.
Modulation of voltage-dependent Ca channel current by arachidonic acid and other long-chain fatty acids in rabbit intestinal smooth muscle

The effects of arachidonic acid (AA) and other long-chain fatty acids on voltage-dependent Ca channel current (ICa) were investigated, with the whole cell patch clamp method, in longitudinal smooth muscle cells of rabbit ileum. 10-30 microM AA caused a gradual depression of ICa. The inhibitory effect of AA was not prevented by indomethacin (10 microM) (an inhibitor of cyclooxygenase) or nordihydroguaiaretic acid (10 microM) (an inhibitor of lipoxygenase). 1-(5-Isoquinolinesulfonyl)- 2-methylpiperazine (H7; 25-50 microM) or staurosporine (2 microM) (inhibitors of protein kinase C) did not block the AA-induced inhibition of ICa, and application of phorbol ester (a protein kinase C activator) (phorbol-12,13-dibutyrate, 0.2 microM) did not mimic the AA action. Some other cis-unsaturated fatty acids (palmitoleic, linoleic, and oleic acids) were also found to depress ICa, while a trans- unsaturated fatty acid (linolelaidic acid) and saturated fatty acids (capric, lauric, myristic, and palmitic acids) had no inhibitory effects on ICa. Myristic acid consistently increased the amplitude of ICa at negative membrane potentials. The present results suggest the possible role of AA, and perhaps other fatty acids, in the physiological and/or pathological modulation of ICa in smooth muscle.
MassJoin: A mapreduce-based method for scalable string similarity joins

String similarity join is an essential operation in data integration. The era of big data calls for scalable algorithms to support large-scale string similarity joins. In this paper, we study scalable string similarity joins using MapReduce. We propose a MapReduce-based framework, called MASSJOIN, which supports both set-based similarity functions and character-based similarity functions. We extend the existing partition-based signature scheme to support set-based similarity functions. We utilize the signatures to generate key-value pairs. To reduce the transmission cost, we merge key-value pairs to significantly reduce the number of key-value pairs, from cubic to linear complexity, while not sacrificing the pruning power. To improve the performance, we incorporate “light-weight” filter units into the key-value pairs which can be utilized to prune large number of dissimilar pairs without significantly increasing the transmission cost. Experimental results on real-world datasets show that our method significantly outperformed state-of-the-art approaches.
Clinical Manifestation of Depression after Stroke: Is It Different from Depression in Other Patient Populations?

Background Despite ample research on depression after stroke, the debate continues regarding whether symptoms such as sleep disturbances, loss of energy, changes in appetite and diminished concentration should be considered to be consequences of stroke or general symptoms of depression. By comparing symptoms in depressed and non-depressed stroke patients with patients in general practice and patients with symptomatic atherosclerotic diseases, we aim to further clarify similarities and distinctions of depression after stroke and depression in other patient populations. Based on this, it is possible to determine if somatic symptoms should be evaluated in stroke patients in diagnosing depression after stroke. Methods An observational multicenter study is conducted in three hospitals and seven general practices including 382 stroke patients admitted to hospital with a clinical diagnosis of intracerebral hemorrhage or ischemic infarction, 1160 patients in general practice (PREDICT-NL), and 530 patients with symptomatic atherosclerotic diseases (SMART-Medea). Results The prevalence of major depressive disorder according to DSM-IV criteria was 14.1% (95% CI 11.0%-18.0%) in the stroke cohort, 5.4% (95% CI 3.8%-7.9%) in the symptomatic atherosclerotic diseases cohort and 12.9% (95% CI 11.1%-15.0%) in the general practice cohorts. Comparing depressed patients of the three cohorts demonstrated broadly similar symptom profiles, as well as comparable levels of individual symptom prevalence. However, the stroke patients suffered more severely from these symptoms than patients in the other populations. Conclusions The findings suggest that depression after stroke is not a different type of depression. This finding indicates that all depressive symptoms should be evaluated in stroke patients, including somatic symptoms.
Application of Power System Frequency for Digital Audio Authentication

Frequency is an important parameter for the operation and control of power systems. One novel application of frequency measurements involves using this information to authenticate a digital audio/video recording presented as forensic evidence in legal proceedings. To apply this technique, called the electrical network frequency (ENF) criterion, both a reference frequency database and an accurate frequency estimation method are required. This paper briefly introduces a wide-area frequency monitoring network (FNET) as the reference frequency database and analyzes statistical features of frequency of the four North American interconnections in terms of different time scales. Combined with digital filtering and a three-sample interpolation, the short-time Fourier transform (STFT) is adjusted to estimate the ENF embedded in digital audio recordings. A procedure of using the ENF criterion, ranging from signal preprocessing to ENF estimation and reference frequency database matching, is then proposed. Further, oscillator error of the digital recording device is considered and an iterative error correction method is given to assist with the frequency database matching. Factors which influence the accuracy of frequency estimation, such as parameter selections of the STFT and signal-to-noise ratio, are also discussed. Test results show that the procedure is capable of performing digital audio authentication.
Inhibition of Interleukin 1 Receptor/Toll-like Receptor Signaling through the Alternatively Spliced, Short Form of MyD88 Is Due to Its Failure to Recruit IRAK-4

Toll-like receptors (TLRs) and members of the proinflammatory interleukin 1 receptor (IL-1R) family are dependent on the presence of MyD88 for efficient signal transduction. The bipartite nature of MyD88 (N-terminal death domain [DD] and COOH-terminal Toll/IL-1 receptor [TIR] domain) allows it to link the TIR domain of IL-1R/TLR with the DD of the Ser/Thr kinase termed IL-1R–associated kinase (IRAK)-1. This triggers IRAK-1 phosphorylation and in turn the activation of multiple signaling cascades such as activation of the transcription factor nuclear factor (NF)-κB. In contrast, expression of MyD88 short (MyD88s), an alternatively spliced form of MyD88 that lacks only the short intermediate domain separating the DD and TIR domains, leads to a shutdown of IL-1/lipopolysaccharide-induced NF-κB activation. Here, we provide the molecular explanation for this difference. MyD88 but not MyD88s strongly interacts with IRAK-4, a newly identified kinase essential for IL-1R/TLR signaling. In the presence of MyD88s, IRAK-1 is not phosphorylated and neither activates NF-κB nor is ubiquitinated. Thus, MyD88s acts as a negative regulator of IL-1R/TLR/MyD88-triggered signals, leading to a transcriptionally controlled negative regulation of innate immune responses.
Comparison of six electromyography acquisition setups on hand movement classification tasks

Hand prostheses controlled by surface electromyography are promising due to the non-invasive approach and the control capabilities offered by machine learning. Nevertheless, dexterous prostheses are still scarcely spread due to control difficulties, low robustness and often prohibitive costs. Several sEMG acquisition setups are now available, ranging in terms of costs between a few hundred and several thousand dollars. The objective of this paper is the relative comparison of six acquisition setups on an identical hand movement classification task, in order to help the researchers to choose the proper acquisition setup for their requirements. The acquisition setups are based on four different sEMG electrodes (including Otto Bock, Delsys Trigno, Cometa Wave + Dormo ECG and two Thalmic Myo armbands) and they were used to record more than 50 hand movements from intact subjects with a standardized acquisition protocol. The relative performance of the six sEMG acquisition setups is compared on 41 identical hand movements with a standardized feature extraction and data analysis pipeline aimed at performing hand movement classification. Comparable classification results are obtained with three acquisition setups including the Delsys Trigno, the Cometa Wave and the affordable setup composed of two Myo armbands. The results suggest that practical sEMG tests can be performed even when costs are relevant (e.g. in small laboratories, developing countries or use by children). All the presented datasets can be used for offline tests and their quality can easily be compared as the data sets are publicly available.
Characterization of a DNA binding site that mediates the stimulatory effect of cyclosporin-A on type III collagen expression in renal cells.

BACKGROUND Previous work from our laboratory demonstrated upregulation of type III collagen by cyclosporin A (CsA) in a cellular model of renal fibroblasts 'in vitro', suggesting that a mechanism of gene transcriptional activation might be responsible for collagen accumulation in renal fibrosis resulting from chronic CsA treatment. METHODS We analysed in the same cellular model: (i) COL3A1 mRNA expression by RT-PCR; (ii) COL3A1 promoter activity by transfection of renal fibroblasts with constructs containing promoter fragments of different length fused to a reporter gene; (iii) expression of transcription factors by western blot analysis; (iv) DNA-protein binding by gel retardation assays with nuclear extracts from CsA-treated and untreated cells; and (v) site-directed mutagenesis of COL3A1 promoter to verify the role of a short DNA segment as CsA responsive element. RESULTS CsA induced a 3-5-fold increase in COL3A1 mRNA that was paralleled by a stimulation of the COL3A1 promoter. Degradation of COL3A1 mRNA was comparable in CsA-treated and -untreated cells. The target region was first limited to a 178 bp fragment from -117 to +61 (pFV1). By gel retardation, utilizing several oligonucleotides that covered the whole length of pFV1, we detected a factor able to bind the promoter DNA (oligo 31) in nuclear extracts after 3 h treatment with CsA. The binding was absent in untreated cells and it was not detected when a 10-base mutation was introduced in oligonucleotide 31. Finally, the same substitution mutation at the site of binding of this factor abolished the stimulatory effect of CsA on COL3A1 promoter. Some transcription factors, whose potential binding sites are included in the above promoter fragment, were induced by CsA treatment either soon (3 h) or late (24-72 h) after treatment and were detected by western blot analysis. CONCLUSIONS CsA induces the synthesis of type III collagen by stimulating a pathway leading to activation of COL3A1 promoter and upregulation of COL3A1 mRNA. A short promoter fragment, proximal to the transcription start site, is the target of CsA stimulation.
Improving the SSD Performance by Exploiting Request Characteristics and Internal Parallelism

With the explosive growth in the data volume, the I/O bottleneck has become an increasingly daunting challenge for big data analytics. It is urgent and important to introduce high-performance flash-based solid state drives (SSDs) into the storage systems. However, since the existing systems are primarily designed for conventional magnetic hard disk drives, directly incorporating SSDs in the existing systems cannot fully exploit SSDs’ performance advantages. In this paper, we propose a new I/O scheduler for SSDs, namely Amphibian, that exploits the high-level request characteristics and low-level parallelism of flash chips to improve the performance of SSD-based storage systems. Amphibian includes two performance enhancement schemes: 1) size-based request ordering, which prioritizes requests with small sizes in processing and 2) garbage collection (GC)-aware request dispatching that delays issuing requests to flash chips that are in the GC state. These two schemes employed in Amphibian significantly reduce the average waiting times of the requests from the host. Our extensive evaluation results derived from three types of SSDs show that, compared with the existing I/O schedulers, Amphibian greatly improves both throughput and average response times for SSD-based storage systems, thus improving the I/O performance of the systems.