Miracle-dz/UniFAR-FTUs huggingface dataset:
Speech enhancement by low-rank and convolutive dictionary spectrogram decomposition

A successful speech enhancement system requires strong models for both speech and noise to decompose a mixture into the most likely combination. However, if the noise encountered differs significantly from the system’s assumptions, performance will suffer. In previous work, we proposed a speech enhancement framework based on decomposing the noisy spectrogram into low rank background noise and a sparse activation of prelearned templates, which requires few assumptions about the noise and showed promising results. However, when the noise is highly non-stationary or has large amplitude, the local SNR of the noisy speech can change drastically, resulting in less accurate decompositions between foreground speech and background noise. In this work, we extend the previous model by changing the modeling of the speech part to be the convolution of a sparse activation and pre-learned template patches, which enforces continuous structure within the speech and leads to better results in highly corrupted noisy mixtures.
A Model Classification Technique for Linear Discriminant Analysis for Two Groups

Linear discriminant analysis introduced by Fisher is a known dimension reduction and classification approach that has received much attention in the statistical literature. Most researchers have focused attention on its deficiencies. As such different versions of classification procedures have been introduced for various applications. In this paper, we attempt not to robustify the Fisher linear discriminant analysis but to propose a comparable model for dimension reduction and classification. The proposed model is investigated and compared with Nearest mean classifier and Fisher classification rule using unscaled normal and scaled normal generated data. Numerical simulations reveal that the proposed model performed exactly as Fisher’s approach and outperformed nearest
Performance optimization of applications based on non-relational databases

This paper is focused on performance optimization of applications based on non-relational databases. Firstly there will be explained differences between relational and non-relational databases and also compared the types of non-relational databases. Then the advantages and disadvantages between MongoDB and ElasticSearch (SQL) database systems will be described and compared. After both database systems were implemented on the web server, their speed is compared in order to determine which system is better to use in different conditions and tasks.
An Adaptive and Compressive Data Gathering Scheme in Vehicular Sensor Networks

In vehicular sensor networks, probe vehicles can act as mobile sensors to monitor physical world and report to an urban sensing center. However, the distribution of probe vehicles is uneven over space and time. Data redundancy and vacancy are common phenomena for different spatiotemporal positions, which seriously degrade sensing efficiency and accuracy. To address this issue, we propose an adaptive and compressive data gathering scheme (AC-Sense) based on matrix completion theory. The scheme adaptively determines the locations where to obtain samples from so that the principal features of physical world can be captured with a reduced number of probe vehicles. The spatio-temporal correlation between sensor data is exploited to estimate the un-sampled data. Furthermore, we introduce a feedback mechanism to stabilize sensing performance according to the evaluation of data error. We perform extensive experiments based on real taxicab mobility traces and air quality data in Beijing. The experimental results show that the proposed scheme largely improves sensing efficiency while ensuring required data quality.
Curved, extended classical solutions: The undulating kink

The energy of extended classical objects, such as vortices, depends on their shape. In particular, we show that the curvature energy of a kink in two spatial dimensions, as a prototype of extended classical solutions, is always negative. We obtain a closed form for the curvature energy, assuming small deviations from the straight line.
Polyamines stimulate the formation of mutagenic 1,N2-propanodeoxyguanosine adducts from acetaldehyde

Alcoholic beverage consumption is associated with an increased risk of upper gastrointestinal cancer. Acetaldehyde (AA), the first metabolite of ethanol, is a suspected human carcinogen, but the molecular mechanisms underlying AA carcinogenicity are unclear. In this work, we tested the hypothesis that polyamines could facilitate the formation of mutagenic α-methyl-γ-hydroxy-1,N2-propano-2′-deoxyguanosine (Cr-PdG) adducts from biologically relevant AA concentrations. We found that Cr-PdG adducts could be formed by reacting deoxyguanosine with μM concentrations of AA in the presence of spermidine, but not with either AA or spermidine alone. The identities of the Cr-PdG adducts were confirmed by both liquid and gas chromatography-mass spectrometry. Using a novel isotope-dilution liquid chromatography-mass spectrometry assay, we found that in the presence of 5 mM spermidine, AA concentrations of 100 μM and above resulted in the formation of Cr-PdG in genomic DNA. These AA levels are within the range that occurs in human saliva after alcoholic beverage consumption. We also showed that spermidine directly reacts with AA to generate crotonaldehyde (CrA), most likely via an enamine aldol condensation mechanism. We propose that AA derived from ethanol metabolism is converted to CrA by polyamines in dividing cells, forming Cr-PdG adducts, which may be responsible for the carcinogenicity of alcoholic beverage consumption.
Global Chaos Synchronization for WINDMI and Coullet Chaotic Systems Using Active Control

In this paper, global chaos synchronization problem is investigated for WINDMI (J.C. Sportt, 2003) and Coullet (P. Coullet, et al., 1979) chaotic systems using active feedback control. Our theorems on synchronization for WINDMI and Coullet chaotic systems are established using Lyapunov stability theory. The controller design can be divided into two steps: the first one needs the derivation of control Lyapunov function and the second step involves using existing control Lyapunov function to synchronize the chaotic system. The active control method is effective and convenient to synchronize the chaotic systems. Mainly this technique gives the flexibility to construct a control law. Numerical simulations are also given to illustrate and validate the synchronization results derived in this paper.
Occlusion handling frame rate up-conversion

Motion-compensated frame interpolation (MCFI) is a technique used extensively to enhance the temporal resolution of video sequences. In order to obtain a high quality interpolation, the motion vector field (MVF) between frames must be well-estimated. However, many current techniques for determining the MVF are prone to errors in occlusion regions. In this work, we propose an improved algorithm for improving the quality of MCFI by restoring the unreliable MVF and pixels in occlusion regions. We first utilize a dual motion estimation (DME) scheme which performs better in occlusion regions. Occlusion regions are determined by the ratio of two directional matching errors. Then, MVs in occlusion regions are refined using an orientation-based refinement (OBR) method, which promotes occluded MVs with its orthogonal neighboring MVF. Finally, regional blending (RB) is proposed to restore the unreliable pixels in occlusion regions for further error concealment. Experimental results demonstrate that the proposed algorithm provides a better quality than previous benchmark frame rate up-conversion (FRUC) methods both objectively and subjectively.
Automatic code locations identification for replacing temporary variable with query method

Automatic application of refactoring techniques can help developer save effort for removing bad smells from their code which improves software maintainability. To remove automatically long method bad smell, which is one of the most serious bad smells, we need an automatic application of six refactoring techniques. However, only one refactoring technique “Extract Method” can be automated. In this research, we propose an algorithm to identify code locations which will be extracted for creating a query method. We performed an experiment to conclude the workability and correctness of our algorithm. This is the most important step towards an automatic application of refactoring technique “replace temp with query”.
LRRK2 Modulates Vulnerability to Mitochondrial Dysfunction in Caenorhabditis elegans

Mutations in leucine-rich repeat kinase 2 (LRRK2) cause autosomal-dominant familial Parkinson's disease. We generated lines of Caenorhabditis elegans expressing neuronally directed human LRRK2. Expressing human LRRK2 increased nematode survival in response to rotenone or paraquat, which are agents that cause mitochondrial dysfunction. Protection by G2019S, R1441C, or kinase-dead LRRK2 was less than protection by wild-type LRRK2. Knockdown of lrk-1, the endogenous ortholog of LRRK2 in C. elegans, reduced survival associated with mitochondrial dysfunction. C. elegans expressing LRRK2 showed rapid loss of dopaminergic markers (DAT::GFP fluorescence and dopamine levels) beginning in early adulthood. Loss of dopaminergic markers was greater for the G2019S LRRK2 line than for the wild-type line. Rotenone treatment induced a larger loss of dopamine markers in C. elegans expressing G2019S LRRK2 than in C. elegans expressing wild-type LRRK2; however, loss of dopaminergic markers in the G2019S LRRK2 nematode lines was not statistically different from that in the control line. These data suggest that LRRK2 plays an important role in modulating the response to mitochondrial inhibition and raises the possibility that mutations in LRRK2 selectively enhance the vulnerability of dopaminergic neurons to a stressor associated with Parkinson's disease.
Extraction Optic Disc of the Digital Image Eye Fundus using Deformable Model

In the medical world a proper diagnosis of the disease will help in the treatment of the disease itself. For example, the separation of optic disc features the eye fundus digital images, it has the objective to distinguish it from other features. Detection of the optic disc is required to distinguish the bright lesion (exudates), which have similar visual characteristics of the optic disc. To do that, we need a detector that features one eye to detect features of Optic Disc. In this study the detection features of Optic Disc using methods previously done Deformable Model preprocessing beforehand to eliminate noise features, vascular, image smoothing and edge detection. Research results are compared with the results extracted manually by humans. The proposed extraction method successfully detected Optic Disc with accuracy 99.63%, sensitivity 85.54% and specificity 99.66%.
The GAL monitoring concept for distributed aal platforms

In most of today's healthcare and AAL scenarios a multitude of data is recorded by different sensors for various purposes. By definition, this data is mostly personal and can be assigned to certain persons, which again makes it interesting for shady data miners, hackers, or even health insurance companies. Thus, this data needs special care regarding privacy and security. On the other hand, if the systems are spread over a larger area, a remote access to such systems is essential for the operator. At least a basic system monitoring should be possible and backups to a distant location are beneficial if the distributed systems fail. In this paper we provide concepts and solutions how in distributed installations of personal AAL platforms privacy and security can be preserved, while remote backup and restore functionality and remote system monitoring can be provided.
Internet of Things based framework for trajectory tracking control

Controlling physical devices from remote places have become necessity in today's practice. These kind of operations require a proper infrastructure which ties all kinds of devices (sensors, actuators, plant etc.) along with the controllers at remote places (either centralized or decentralized) using a communication medium. The heterogeneity of platforms is a challenge to integration of all these aspects. The use of Internet of Things (IoT) provides connectivity across several devices and platforms. The paper presents IoT based real time trajectory tracking by a vehicle. The controller at a far off place devises control actions relying on the information obtained from sensors. The control actions are then sent to actuators through the communication channel so that vehicle tracks the reference trajectory efficiently. The sliding mode controller is used which decides the control actions on the basis of objective function. The framework works on a non uniformly sized control interval consisting of variable number of sampling instants of fixed length. The objective function considers the system states, time interval and also the control and communication constraints (delays and packet losses). The developed algorithm based on IoT shows a proper convergence to the reference trajectory.
Berry Fruit Consumption and Metabolic Syndrome

Metabolic Syndrome is a cluster of risk factors which often includes central obesity, dyslipidemia, insulin resistance, glucose intolerance, hypertension, endothelial dysfunction, as well as a pro-inflammatory, pro-oxidant, and pro-thrombotic environment. This leads to a dramatically increased risk of developing type II diabetes mellitus and cardiovascular disease, which is the leading cause of death both in the United States and worldwide. Increasing evidence suggests that berry fruit consumption has a significant potential in the prevention and treatment of most risk factors associated with Metabolic Syndrome and its cardiovascular complications in the human population. This is likely due to the presence of polyphenols with known antioxidant and anti-inflammatory effects, such as anthocyanins and/or phenolic acids. The present review summarizes the findings of recent dietary interventions with berry fruits on human subjects with or at risk of Metabolic Syndrome. It also discusses the potential role of berries as part of a dietary strategy which could greatly reduce the need for pharmacotherapy, associated with potentially deleterious side effects and constituting a considerable financial burden.
Age at Diagnosis and C-Peptide Level Are Associated with Diabetic Retinopathy in Chinese

Objective To find the associations between diabetic retinopathy and age at diagnosis, C-peptide level and thyroid-stimulating hormone (TSH) level in Chinese type 2 diabetes mellitus. Methods 3100 hospitalized type 2 diabetic patients in Peking University People's Hospital were included in this retrospective study. Their medical history and the laboratory data were collected. All the patients received examination of diabetic retinopathy (DR) by professional ophthalmologist. Results Comparisons among patients with NDR, NPDR and PDR showed that with the progression of diabetic retinopathy, patients turned to have older age but younger age at diagnosis of diabetes, and have higher SBP, longer duration of diabetes, higher mean HbA1c but lower fasting and 2 hours postprandial C-peptide level. Moreover, with the progression of diabetic retinopathy, patients turned to have higher prevalence of primary hypertension, higher prevalence of peripheral vascular sclerosis, higher proportion with insulin treatment. TSH level was comparable among the three groups of patients. Association analysis showed that after adjusting for age, sex, duration of diabetes, body mass index, HbA1c, blood pressure and albuminurea creatinine ratio and insulin treatment, age at diagnosis (OR 0.888, 95%CI 0.870–0.907, p = 0.00) and postprandial C-peptide (OR 0.920, 95%CI 0.859–0.937, p = 0.00) are the independent associated factors of DR in Chinese type 2 diabetes. Conclusions According to the results, postprandial C-peptide level and age at diabetes may be two independent associated factors with DR in Chinese type 2 diabetes. The lower level of postprandial C-peptide, the younger age at diagnosis, may indicate the higher prevalence of DR.
Solvability of forward-backward SDEs and the nodal set of Hamilton-Jacobi-Bellman Equations

The solvability of a class of forward-backward stochastic differential differential equations(SDEs for short)over an arbitrarily prescribed time duration is studied. The authors design a stochastic relaxed control problem, with both drift and diffusion all being controlled, so that the solvability problem is converted to a problem of finding the nodal set of the viscosity solution to a certain Hamilton-Jacobi-Bellman equation.This method overcomes the fatal difficulty encountered in the traditional contraction mapping approach to the existence theorem of such SDEs.
Regression analysis model applied to age-group swimmers: 50m race component times analysis

This investigation aimed to develop a regression model of the Race Component evolution in a large sample of regional age-group Spanish swimmers in 50 m freestyle. Subjects were 280 regional swimmers selected of different club (with an age range of 9 to 22 year) and the swimmers were divided into a five competitive categories. The time spent starting (ST), the time spent stroking (STT1 - STT2), the time spent turning (TT) and the time spent finishing (FT) were used for analysis. Inverse function approximation of the partials times by aging and was carried out. Furthermore, the analysis regression of partials times and event time for age and genders were calculated respectively. It seems that the times of swimmer studied have a tendency to resemble of internationals swimmer´s times. The estimation formula applied was different time according to gender. The crossing age in the swimming partials times were about 12-14 years old. At this age begin to differentiate the performed and swim times between boys and girls.
Intégrer des ressources lexicales et grammaticales externes dans des analyseurs partiels probabilistes

Cet article traite de segmentation lexicale et de segmentation syntaxique. Nous montrons comment combiner des modeles probabilistes comme les champs markoviens aleatoires avec des ressources lexicales et grammaticales externes a l'aide d'une approche a etats finis.
Development Rights: Regulating Vertical Urbanism in Taiwan

ABSTRACT This article examines the contested interaction between planning and private property by focusing on development rights: an important, yet under-studied, aspect of private ownership. Three regulatory approaches – a road-based rule, a FAR (floor area ratio)-based rule, and a TDR (transfer of development rights) mechanism – have influenced how planning in Taiwan has governed vertical development since the early twentieth century. We link them to three planning ideologies, the city pathological, the city rational, and the city neoliberal. We argue that regulation-ideology dynamics have led to greater power for the real estate sector in appropriating density rent in Taiwan.
Network Visualization by Meaningful Substrates

ABSTRACT Networks have remained a challenge for information visualization designers because of the complex issues of node and link layout coupled with the rich set of tasks that users present. This paper offers a five-layer hierarchy of network visualization situations with associated tasks: from simple node and link situations to more elaborate situations involving node labels, directed links, node attributes, and link attributes. Then, it offers a strategy based on tying node placement to node attributes within non-overlapping regions. These user-defined meaningful substrates enable users to easily see which links remain within a region or cross to other regions. Link visibility is controlled by check boxes so that selected subsets of links can be displayed. To further limit display clutter, users can set sliders to control which nodes within a region have their edges visible. We illustrate our meaningful substrate approach in a modest example with legal precedents for 49 cases with 368 precedents, and show these in our implementation of NVMS 1.0.
Adaptive threshold determination method for the dynamic filtering in wireless sensor networks using fuzzy logic

Nodes in sensor networks can be easily compromised by an adversary because of hostile environments. An adversary may use compromised nodes to inject false reports into the network. The dynamic en-route scheme can detect and drop such false reports during the forwarding phase. In this scheme, choosing a threshold value is important, as it trades off between security power and energy consumption. Thus, we should choose a threshold value such that it provides sufficient resilience, yet is small enough to conserve energy. This paper presents a fuzzy-based threshold determination method for the dynamic en-route scheme to filter false reports in wireless sensor networks. The base station periodically determines the threshold value using a fuzzy rule-based system. The resilience and energy efficiency of the proposed method against false data injection attacks are shown by simulation.
Increased circulating antiganglioside antibodies in primary and secondary progressive multiple sclerosis

Plasma samples from 70 patients with multiple sclerosis (MS), 41 patients with other neurological diseases (OND), and 38 healthy subjects were examined for antibodies against gangliosides GM1, GM3, GD1a, GD1b, and GD3 using enzyme‐linked immunosorbent assays. The percentages of subjects with increased anti‐GM3 responses were significantly higher in the primary progressive MS (56.3%) and secondary progressive MS (42.9%) groups than in the relapsing‐remitting MS (2.9%), healthy subject (2.6%), and OND (14.6%) groups. Elevated antiganglioside antibodies may be secondary to axonal damage or may be a cause of axonal damage and accumulating disability in progressive MS. In either case, they may serve as a marker of axonal damage in MS.
Crystal structure of a novel two domain GH78 family α-rhamnosidase from Klebsiella oxytoca with rhamnose bound

The crystal structure of the GH78 family α‐rhamnosidase from Klebsiella oxytoca (KoRha) has been determined at 2.7 Å resolution with rhamnose bound in the active site of the catalytic domain. Curiously, the putative catalytic acid, Asp 222, is preceded by an unusual non‐proline cis‐peptide bond which helps to project the carboxyl group into the active centre. This KoRha homodimeric structure is significantly smaller than those of the other previously determined GH78 structures. Nevertheless, the enzyme displays α‐rhamnosidase activity when assayed in vitro, suggesting that the additional structural domains found in the related enzymes are dispensible for function. Proteins 2015; 83:1742–1749. © 2015 The Authors. Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc.
A control performance of linear model and the MacPherson model for active suspension system using composite nonlinear feedback

The purposes or functions of the commercial car suspension system are to take care on the car body weight, to isolate the car body from road profiles disturbance and to maintain the grip force between the wheel and road profiles. The Composite Nonlinear Feedback (CNF) control law is proposed in this comparative study between conventional linear model and Macpherson model. The control performance consists of velocity of car body, suspension deflection, wheel deflection and velocity of a car wheel. The main measurement in this study is the acceleration of the car body. The Linear Quadratic Regulator (LQR) and passive model are involved in this control performance is for comparison purposes. The mathematical model of linear model and MacPherson model are focused on the quarter car model active suspension system. The simulation work is done by using MATLAB and SIMULINK to see the control performance on the quarter car active suspension model. In this paper we can conclude that the CNF achieved the main objective of active suspension which is the ride comfort and road handling.