Miracle-dz/UniFAR-FTUs huggingface dataset:
Automated classification of piano-guitar notes

In this paper, a new decisively important factor in both the perceptual and the automated piano-guitar identification process is introduced. This factor is determined by the nontonal spectral content of a note, while it is, in practice, totally independent of the note spectrum tonal part. This conclusion and all related results are based on a number of extended acoustical experiments, performed over the full pitch range of each instrument. The notes have been recorded from six different performers each of whom played a different instrument. Next, a number of powerful criteria for the classification between guitar and piano is proposed. Using these criteria, automated classification between 754 piano and guitar test notes has been achieved with a 100% success rate.
Fast failover of multicast sessions in software-defined networks

With the rapid growth of services that stream to groups of users comes an increased importance of and demand for reliable multicast. In this paper, we turn to software-defined networking and develop a novel general-purpose multi-failure protection algorithm to provide quick failure recovery, via Fast Failover (FF) groups, for dynamic multicast groups. This extends previous research, which either could not realize fast failover, worked only for single link failures, or was only applicable to static multicast groups. However, while FF is know to be fast, it requires pre-installing back-up rules. These additional memory requirements, which in a multicast setting are even more pronounced than for unicast, are often mentioned as a big disadvantage of using FF. We develop an OpenFlow application for resilient multicast, with which we study FF resource usage, in an attempt to better understand the trade-off between recovery time and resource usage. Our tests on a realistic network suggest that using FF groups can reduce the recovery time of the network significantly compared to other methods, especially when the latency between the controller and the switches is relatively large.
Adaptive coordinated motion control of two manipulator arms

An adaptive controller is presented for the coordinated motion control of two manipulators handling an object of unknown mass. Global convergence in tracking of both position and internal force trajectories of the object is proved, assuming perfect models for both manipulators. The computational algorithm is similar to the Newton-Euler inverse dynamics algorithm with complexity linear in the number of links in the manipulators. A significant feature of the control method is that both manipulators use the identical computational algorithm. Thus, the concept of master/slave relationship between the two manipulators is avoided. Two simulations are presented. The first assumes an ideal model for each manipulator. As expected, the controller is stable and provides excellent tracking ability of the manipulator. The second simulation investigates the effects of modeling errors in the mass properties of each arm. The position trajectories track very close to their desired values; however, they never completely converge. <<ETX>>
Estimate Markups with a Flexible Supply Model

This paper provides a theoretically founded empirical model to simultaneously investigate firm competition and estimate markups. The model nests the standard oligopoly model, but also allows for firm collusion. Different from conduct parameter models, our model is consistent with a series of theoretical models. We show that a nonparametric marginal cost function can be identified, which gives an estimate of markups. Through Monte Carlo simulations, we show that our approach works better in estimating markups than a standard oligopoly model or a conduct parameter model.
Expression of muscarinic receptors in human and mouse sclera and their role in the regulation of scleral fibroblasts proliferation

Purpose To determine the expression of muscarinic receptor subtypes (mAChRs) in human and mouse scleral fibroblasts (SFs), to investigate the mechanism that mediate the role mAChRs play in cell proliferation, and to explore the underlying intracellular signaling pathways involved in mouse SFs with treatment of muscarinic agents. Methods Reverse transcription polymerase chain reaction (RT-PCR) was used to detect mRNA expression of mAChRs in the human and mouse sclera. Western blot analysis and immunocytochemistry were used to detect proteins of mAChRs in the cultured SFs. An immunohistochemical study was used to further detect the presence of mAChR proteins in frozen scleral sections. BrdU (5-bromo-2-deoxyuridine ) cell proliferation assay was performed to measure DNA synthesis. Enzyme linked immunosorbent assay (ELISA) was used to measure in vitro kinase activity for epidermal growth factor receptor (EGF-R), fibroblast growth factor (FGF-2), transforming growth factor (TGF)-β1, and extracellular signal-regulated kinase (ERK)1/2. Expressions of epidermal growth factor-receptor (EGF-R); protein kinase C (PKC); Proline-rich tyrosine kinase 2 (Pyk-2), v-raf murine sarcoma viral oncogene homolog B1 (B-Raf), Rat Sarcoma (Ras), c-Jun N-terminal kinases (JNK1/2), and ERK1/2 were detected by immunoblot. Results mAChR for subtypes M1-M5 were detected in both mouse and human SFs by protein, cellular, and mRNA analysis. EGF-R, PKC, Pyk-2, B-Raf, Ras, JNK1/2, and ERK1/2 were activated after treatment by agonists and antagonists, indicated by changes in phosphorylation of these proteins. Atropine abolished the carbachol-induced activation of SF cell proliferation in a concentration-dependent manner. Carbachol also activated p42/44 mitogen-activated protein kinase (MAPK) and Ras in a time-dependent manner. Muscarinic agents also modulated fibroblast growth factor expression in these cells. Conclusions This study confirms the presence and functional role of all five mAChRs in human and mouse SFs. These results show that proliferative responses of SFs to muscarinic receptor stimulation are mediated via the activation of the classical MEK-ERK-MAPK cascade.
Combined effect of albuminuria and estimated glomerular filtration rate on cardiovascular events and all-cause mortality in uncomplicated hypertensive patients

Objectives Decreased glomerular filtration rate (GFR) and microalbuminuria predict cardiovascular events and mortality in the general population and in high-risk patients. Their combined prognostic power in low-risk patients has never been reported. We assessed the prognostic role of GFR and albuminuria for cardiovascular disease and all-cause mortality in nondiabetic patients with primary hypertension. Methods We conducted an 11.2-year follow-up of 837 uncomplicated hypertensive patients enrolled in the Microalbuminuria: A Genoa Investigation on Complications (MAGIC) cohort between 1993 and 1997. Urinary albumin-to-creatinine ratio (ACR) and estimated GFR (eGFR) were assessed in untreated patients at baseline. Renal dysfunction was defined as the inclusion in the most unfavorable sex-specific decile of eGFR or of ACR. The primary endpoints were the occurrence of fatal and nonfatal cerebrovascular and cardiac events (CVEs), composite of nonfatal cerebrovascular and cardiac events (CVD) and all-cause death (CEP), and composite of CVD and chronic renal insufficiency (CRE). Results During 9374 person-years of follow-up, the incidence rate for CVE, CRE, and all-cause mortality was 6.3, 7.8, and 3.1 /1000 person-years, respectively. Renal dysfunction was associated with increased risk for CVE [relative risk (RR) 2.13, 95% confidence interval (CI) 1.15–3.93, P = 0.011], CEP (RR 1.78, 95% CI 1.02–3.08, P = 0.027), and CRE (RR 2.47, 95% CI 1.45–4.29, P < 0.001), even after adjusting for several baseline covariates such as sex, duration and severity of blood pressure, and total cholesterol. Conclusion Renal dysfunction is a risk factor for cardiorenal events and all-cause mortality, regardless of traditional confounders, in uncomplicated patients with primary hypertension.
Deep Spatial–Spectral Representation Learning for Hyperspectral Image Denoising

Deep learning has found successful applications in restoration of two-dimensional (2-D) images including denoising, dehazing, and superresolution. However, existing deep convolutional neural network (DCNN) architecture cannot fully exploit spatial–spectral correlations in three-dimensional (3-D) hyperspectral images (HSIs) (directly extending 2-D DCNN into 3-D will significantly increase computational complexity); meantime, unlike 2-D images, there is an obstacle caused by the shortage of training data for HSIs. To meet those challenges, we present a novel, deep-learning framework for 3-D HSI denoising with the following contributions. First, inspired by the success of U-net in low-dose current-transformer denoising, we propose a novel approach of encoding rich multi-scale information of HSIs by a modified 3-D U-net. Second, we present a computationally efficient implementation of 3-D U-net based on the strategy of separable filtering. By decomposing 3-D filtering into 2-D spatial filtering and 1-D spectral filtering, we can achieve substantial savings on the number of network parameters to keep the computational complexity low. Third, we have developed a transfer learning approach of synthetically generating HSIs from RGB images as supplementary training data. The synthesized HSIs are used for the initial training of the modified 3-D U-net denoising network, which will be fine-tuned on real HSI images. Experimental results have shown that the proposed 3-D U-net denoising method significantly outperforms existing model-based HSI denoising methods.
A comparative, randomized clinical study of haemodynamic response to laryngoscopy and tracheal intubation using vecuronium with and without neuromuscular monitoring by peripheral nerve stimulator

Introduction: Laryngoscopy and endotracheal intubation during induction of general anaesthesia are extremely strong nociceptive stimuli, which often lead to unintended stimulating of the sympathetic nervous system manifested by increased arterial pressure and tachycardia. The present study aimed to assess usefulness of neuromuscular monitoring with peripheral nerve stimulator in reducing the haemodynamic response to laryngoscopy and tracheal intubation using vecuronium. Material and Methods: This study included 100 cases classified randomly into two group (Each n= 50). Group I (C) (n=50): control group: Laryngoscopy and tracheal intubation done at the end of 3 minutes after administration of 0.1mg/kg body weight of intravenous iv vecuronium. Group II (N) n=50: Neuromuscular monitoring done after giving 0.1mg/kg body weight of intravenous vecuronium using TOF with supramaximal stimuli of current intensity 50 mA at right ulnar nerve, and the response of the thumb is monitored every 10 seconds, once all the responses for TOF are lost, the time noted and laryngoscopy and endotracheal intubation were performed. Statistical Analysis: IndependentSamples t test, Cross tabs and Repeated Measure ANOVA were used. SPSS for windows (version 17.0) was employed for data analysis. p<0.05 was considered as significant and p<0.01 was considered as highly significant. Results: Group-N (study group) showed statistically significant decreased haemodynamic response to laryngoscopy and intubation after iv Vecuronium, when compared to Group-C (control group). Conclusion: Neuromuscular monitoring by using PNS at AP is useful to have good intubation condition and to reduce the haemodynamic response to laryngoscopy and intubation.
Therapeutic approaches in adults with congenital heart disease-associated pulmonary arterial hypertension

Pulmonary arterial hypertension is a major contributor to reduced functional capacity in patients with congenital heart disease. Expert care is essential. Whilst careful supportive management has traditionally been the mainstay for these patients, in recent times significant improvements in exercise capacity and even survival have been observed with the use of disease-targeted therapy, including endothelin receptor antagonists, phosphodiesterase inhibitors and prostanoids. In this review we will discuss current therapeutic options and summarise the recent literature on disease-targeted therapy.
Towards Application Portability on Blockchains

We discuss the issue of what we call incentive mismatch, a fundamental problem with public blockchains supported by economic incentives. This is an open problem, but one potential solution is to make application portable. Portability is desirable for applications on private blockchains. Then, we present examples of middleware designs that enable application portability and, in particular, support migration between blockchains.
Analyzing and Tuning the Distributed Coordination Function in the IEEE 802.11 DFWMAC Draft Standard

The upcoming standard for wireless LANs DFWMAC1 developed by the IEEE2 802.11 working group consists of two parts the distributed coordination function DCF that is based on a contention scheme and the point coordination function PCF based on a contention free scheme. The DCF is CSMA/CA like access protocol with several extensions. In this paper, following a short presentation of the elements in DFWMAC in general and DCF in particular we will present the results of our simulative analysis of the DCF part in DFWMAC focussing on two key mechanisms in it the RTS/CTS message exchange and the backoff algorithm.
Fresh Osteochondral Total Ankle Allograft Transplantation for the Treatment of Ankle Arthritis

Background: Fresh osteochondral total ankle allograft transplantation has been reported in the literature with survival rates between 50% and 92% at 1- to 12-years followup. The goal of this study was to present the results of total ankle allografts from another institution. Materials and Methods: Twenty-nine patients underwent osteochondral total ankle transplant at our institution between July 2003 and July 2005. The mean patient age was 41 years old and the mean followup duration was 2 years. Results: At followup, 14 of the 29 transplants had been revised to a repeat ankle transplant, prosthetic total ankle arthroplasty, or bone block arthrodesis. In addition, 6 of the remaining 15 transplants were deemed to be radiographic failures due to allograft fracture, allograft collapse, or progressive loss of joint space. The remaining 9 allografts (31%) were considered successes. In comparing the success versus the failure group, patients who were older, who had a lower body-mass index, and who had minimal preoperative angular deformity did significantly better. Conclusion: This is the largest series of osteochondral total ankle allograft transplants reported in the literature to date. There is an extremely high rate of failure associated with this procedure, and we currently consider it only rarely in patients who are too young for ankle replacement, have excellent range of motion, low body mass index, normal radiographic alignment, and who refuse arthrodesis.
The need for new models of staff development

Staff development is widely recognised as being crucial in the successful introduction of technological innovations in teaching. However, even where this is accepted, development costs still have a tendency to usurp large portions of the funding. This falsely suggests that given the appropriate hardware and software, academics will quickly and easily change their teaching methods and course materials to take advantage of it. It is likely that many projects have failed to reach wide acceptance because adequate post adoption support was not provided (Hansen, Deshpande, & Murugesan, 1999; Surry & Farquhar, 1997). Apart from the ‘early-adopters’, many academics are understandably reluctant to move to technologically based teaching innovations which they perceive as complex, untried and lacking in support (Sawyers & Alexander, 1998).
A Novel Approach for Image Steganography in Spatial Domain

This paper presents a new approach for hiding information in digital image in spatial domain. In this approach three bits of message is embedded in a pixel using Lucas number system but only one bit plane is allowed for alternation. The experimental results show that the proposed method has the larger capacity of embedding data, high peak signal to noise ratio compared to existing methods and is hardly detectable for steganolysis algorithm.
Source Localization and Tracking Using Distributed Asynchronous Sensors

This paper presents a source localization algorithm based on the source signal's time-of-arrival (TOA) at sensors that are not synchronized with one another or the source. The proposed algorithm estimates source positions using a window of TOA measurements which, in effect, creates a virtual sensor array. Based on a Gaussian noise model, maximum likelihood estimates (MLE) for the source position and displacement are obtained. Performance issues are addressed by evaluating the Cramer-Rao lower bound and considering the virtual sensor array's geometric properties. To track the source trajectory from the TOA measurement, which is a nonlinear function of source position and displacement, this localization algorithm is combined with the extended Kalman filter (EKF) and the unscented Kalman filter, resulting in good tracking performance
A game theoretical approach for energy trading in wireless networks powered by green energy

Green energy sources, such as solar and wind, provide an alternative solution for powering wireless networks. To maximize the utilization of green energy charged from different sources, it is desirable to allow energy trade among neighbor cells. In this paper, the local energy trade issues in a wireless mesh network powered by green energy are studied such that energy can be purchased either from neighbor cells or from electricity grid, based on the energy charging and discharging characteristics in each cell. Our objective is to determine the optimal price and quantity of energy purchase and sale for each cell such that the profits of all cells can be maximized and their energy demands can be fulfilled. To this end, the energy trading problem is formulated as a Stackelberg game. Based on the utility function, the closed-form expressions of the optimal energy quantity and price for trading are derived. Finally, an optimal scheme, namely, Optimal Profits Energy Trading (OPET), is proposed to maximize the profits of all cells. The proposed OPET can achieve the optimal solution with polynomial time complexity. Extensive simulations are conducted to verify the performance of the proposed scheme.
Cluster Overlap Distribution Map: Visualization for Gene Expression Analysis Using Immersive Projection Technology

In this paper, we discuss possible applications of virtual reality technologies, such as immersive projection technology (IPT), in the field of genome science, and propose cluster-oriented visualization that attaches importance to data separation of large gene data sets with multiple variables. Based on these strategies, we developed the cluster overlap distribution map (CDCM), which is a visualization methodology using IPT for pairwise comparison between cluster sets generated from different gene expression data sets. This methodology effectively provides the user with indications of gene clusters that are worth a close examination. In addition, by using the plate window manager system, which enables the user to manipulate existing 2D GUI applications in the virtual 3D space, we developed the virtual environment for the comprehensive analysis from providing the indications to further examination by referring to the database on Web sites. Our system was applied in the comparison between the gene expression data sets of hepatocellular carcinomas and hepatoblastomas, and the effectiveness of the system was confirmed.
Material for “ Adversarial Inverse Graphics Networks : Learning 2 Dto-3 D Lifting and Image-to-Image Translation from Unpaired Supervision ”

Here we discuss the benefits of using non-parametric and domain-specific renderers, over learned decoders. Both the proposed model and CycleGAN [5] can be viewed as autoencoders: the input is first transformed into a target domain, and then transformed back to its original space. A parametric decoder could be more desirable, for the reason that we do not need to hand-engineer a mapping function from the target domain back to the inputs. However, simply using reconstruction loss and adversarial loss does not guarantee that the predictions look spatially similar to the inputs. In tasks such as image-to-image translation, spatial precision can be of critical importance. With a parametric decoder, the transformed input can be viewed as a information bottleneck, and as long as the decoder can correctly “guess” the final output from the transformed input (i.e., the code), the code is valid and the solution is optimal. To support this point, we conduct an experiment on image inpainting using the MNIST dataset. Similar to the parametric encoder-decoder described in the main text, the network has two main parts: (1) an encoder that transforms the input (a partially obscured image of a digit) into prediction (a hallucinated digit), and (2) a decoder that transforms the prediction back into the input. Instead of using convolutional layers, which have an architectural bias on preserving spatial relationships, we use fully-connected layers in both the encoder and the decoder. This is important, because such architectural conveniences are unavailable in less-structured tasks, such as 3D pose prediction and SfM. We train the model with a reconstruction loss on the decoder, and adversarial loss on the encoder. The results are shown in Figure 1. While inpainting, the encoder (incorrectly) transforms many of the digits into other digits. For instance, several obscured “1” images are inpainted as “4”. In the parametric decoding process, however, these errors are undone, and the original input is re-
α-Synuclein in filamentous inclusions of Lewy bodies from Parkinson’s disease and dementia with Lewy bodies

Lewy bodies and Lewy neurites are the defining neuropathological characteristics of Parkinson’s disease and dementia with Lewy bodies. They are made of abnormal filamentous assemblies of unknown composition. We show here that Lewy bodies and Lewy neurites from Parkinson’s disease and dementia with Lewy bodies are stained strongly by antibodies directed against amino-terminal and carboxyl-terminal sequences of α-synuclein, showing the presence of full-length or close to full-length α-synuclein. The number of α-synuclein-stained structures exceeded that immunoreactive for ubiquitin, which is currently the most sensitive marker of Lewy bodies and Lewy neurites. Staining for α-synuclein thus will replace staining for ubiquitin as the preferred method for detecting Lewy bodies and Lewy neurites. We have isolated Lewy body filaments by a method used for the extraction of paired helical filaments from Alzheimer’s disease brain. By immunoelectron microscopy, extracted filaments were labeled strongly by anti-α-synuclein antibodies. The morphologies of the 5- to 10-nm filaments and their staining characteristics suggest that extended α-synuclein molecules run parallel to the filament axis and that the filaments are polar structures. These findings indicate that α-synuclein forms the major filamentous component of Lewy bodies and Lewy neurites.