Miracle-dz/UniFAR-FTUs huggingface dataset:
An Improved Melody Contour Feature Extraction for Query by Humming

this paper, we propose a new melody contour extraction technique and new normalization methods to improve Query-by-Humming. A critical issue of humming sound is noise interference from both environment and acquisition instruments. Furthermore, most users are not professional singers therefore they cause the other query problems about variation of pitch and timing. Advantage of the proposed technique can reduce noise whereas makes pitch smoothing. Our technique consists of four steps as follows: Firstly, the melody contour is extracted from humming sound by Subharmonic-to-Harmonic Ratio (SHR). Subsequently, the melody contour is filtered and smoothed by median filter and our propose technique. Afterwards, we used various normalization methods, including our new techniques, for scaling and noise robust. Finally, humming sound and melody sequences are different alignment methods such as Dynamic Time Warping (DTW), linear interpolations and nonlinear interpolations, before classification. Our technique offers several advantages: higher accuracy, lower complexity, faster query process and lower memory. In addition, the experimental results show that our proposed technique can perform more effective than other methods. I. INTRODUCTION At present, the music is became part of our lives of most people both listening and singing for entertain and relax. They favor a new kind of entertainment in music which is called Karaoke. The prevalent of problem is users forget the name of the song, but they want to find a song for singing. However, users can retrieve song by only one way, which the user must type keywords (titles, singers, etc.). This search tool is not nsufficient and inconvenient for the user to retrieve the song. Nowadays, this system is known as a Query-by-Humming (QbH) system, which allows users to retrieve a song via simply humming a part of the song. QbH is especially active area of research in the MIR system. Normally, the user always remembers the melody or rhythm and can hum a part of the melody of the song into a microphone and let a QBH system to retrieve the song. Then QbH system will show the result by different names of songs, which users will find it easy and convenient. Outcome presented a list of song ordered by the similarity between humming sound and song in database. This can be used to
Tamoxifen-loaded novel liposomal formulations: evaluation of anticancer activity on DMBA-TPA induced mouse skin carcinogenesis

Purpose: Tamoxifen (TAM) is a non-steroidal estrogen receptor modulator known for its anticancer activity. Apart from marked breast cancer activity, this drug has also shown potential in treating other types of cancers including skin cancers. TAM is reported to be associated with serious side effects primarily due to its systemic distribution. The localized delivery of this drug in this regard would be highly beneficial with respect to safety as well as efficacy. Methods: In the current studies, an endeavor has been made to investigate the efficacy of topically applied liposome-encapsulated TAM on skin cancer model. The drug was encapsulated in phospholipid-based vesicular systems viz. conventional liposomes and elastic liposomes. Incidence of papillomas and histopathological examination were employed to determine the efficacy of the tested formulations. Results: The results demonstrated carrier-dependent strong inhibition of skin carcinogenesis with encapsulated drug vis-à-vis drug in the solution form. The encouraging findings from the current work construe immense potential of the TAM-loaded liposomal systems in the management of skin cancer.
Design Studio 2.0: Augmenting Reflective Architectural Design Learning

Web 2.0 is beyond a jargon describing technological transformation: it refers to new strategies, tools and techniques that encourage and augment informed, creative and social inter(actions). When considered in an educational context, Web 2.0 provides various opportunities for enhanced integration and for improving the learning processes in information-rich collaborative disciplines such as urban planning and architectural design. The dialogue between the design students and studio teachers can be mediated in various ways by creating novel learning spaces using Web 2.0-based social software and information aggregation services, and brought to a level where the Web 2.0 environment supports, augments and enriches the reflective learning processes. We propose to call this new setting Design Studio 2.0. We suggest that Design Studio 2.0 can provide numerous opportunities which are not fully or easily available in a conventional design studio setting. In this context, we will introduce a web-based geographic virtual environment model (GEO-VEM) and discuss how we reconfigured and rescaled this model with the objective of supporting an international urban design studio by encouraging students to make a collaborative and location-based analysis of a project site (the Brussels-Charleroi Canal). Pursuing the discussion further, we will present our experiences and observations of this design studio including web use statistics, and the results of student attitude surveys. In conclusion, we will reflect the difficulties and challenges of using the GEO-VEM in the Design Studio in a blended learning context and develop future prospects. As a result, we will introduce a set of key criteria for the development and implementation of an effective e-learning environment as a sustainable platform for supporting the Design Studio 2.0.
Bax and Bak are required for apogossypolone, a BH3-mimetic, induced apoptosis in chronic lymphocytic leukemia cells

Chronic lymphocytic leukemia (CLL) is a B-cell disease representing the most common leukemia in the Western world. Unlike other cancers which are commonly driven by uncontrolled proliferation, CLL cells are explicitly accumulated through defective apoptosis. High levels of Bcl-2 family anti-apoptotic proteins are primarily responsible for resistance to apoptosis and are major targets for therapy development. Sustained levels of Mcl-1 and Bcl-2 appear to be protective mechanisms in response to cytotoxic agents and are found to be associated with poor prognosis in CLL [1]. Levels of Mcl-1 inversely correlated with in vitro and in vivo responsiveness to chemotherapy in CLL [2, 3]. In contrast, strategies lowering the levels of Mcl-1 in leukemia and lymphoma cells triggered apoptosis. Overexpression of anti-apoptotic proteins observed in relapsed leukemias has been associated with failure to achieve complete responses to initial therapy with fludarabine. Collectively, these reports endorse anti-apoptotic proteins as pro-survival factors and reveal the requisite to fine-tune the pro-survival and pro-death proteins in restoring normal apoptosis in CLL.
Mobile base station antenna composed of a cylindrical dielectric lens radome

This paperproposes a novel mobile base station antenna with a dielectric lens radome. The dielectric lens has a function to shape the radiation pattern which is useful to achieve low side lobe characteristics. In designing the dielectric lens, a ray tracing method has been developed in the MATLAB software. In order to achieve a slender lens shape, adequate radiation patterns for the feed radiator are studied. The bifurcated radiation pattern is shown to be effective.
SPARSE RECOVERY VIA THE ` 0 ( ` 2 ) PENALTY : THEORY AND ALGORITHM

In this work we propose and analyze a novel approach for recovering group sparse signals, which arise naturally in a number of practical applications. It is based on regularized least squares with an 0 (2) penalty. One distinct feature of the new approach is that it has the built-in decorrelation mechanism within each group, and thus can handle the challenging strong inner-group correlation. We provide a complete analysis of the regularized model, e.g., the existence of global minimizers, invariance property, support recovery, and characterization and properties of block coordinatewise minimizers. Further, the regularized functional can be minimized efficiently and accurately by a primal dual active set algorithm with provable global convergence. In particular, at each iteration, it involves solving least squares problems on the active set only, and merits fast local convergence, which makes the method extremely efficient for recovering group sparse signals. Extensive numerical experiments are presented to illustrate salient features of the model and the efficiency and accuracy of the algorithm. A comparative experimental study indicates that it is competitive with existing approaches.
A Truthful Incentive Mechanism for Emergency Demand Response in Geo-Distributed Colocation Data Centers

Data centers are key participants in demand response programs, including emergency demand response (EDR), in which the grid coordinates consumers of large amounts of electricity for demand reduction in emergency situations to prevent major economic losses. While existing literature concentrates on owner-operated data centers, this work studies EDR in geo-distributed multitenant colocation data centers in which servers are owned and managed by individual tenants. EDR in colocation data centers is significantly more challenging due to lack of incentives to reduce energy consumption by tenants who control their servers and are typically on fixed power contracts with the colocation operator. Consequently, to achieve demand reduction goals set by the EDR program, the operator has to rely on the highly expensive and/or environmentally unfriendly on-site energy backup/generation. To reduce cost and environmental impact, an efficient incentive mechanism is therefore needed, motivating tenants’ voluntary energy reduction in the case of EDR. This work proposes a novel incentive mechanism, Truth-DR, which leverages a reverse auction to provide monetary remuneration to tenants according to their agreed energy reduction. Truth-DR is computationally efficient, truthful, and achieves 2-approximation in colocation-wide social cost. Trace-driven simulations verify the efficacy of the proposed auction mechanism.
Robust TRISO-fueled Pebble Identification by Digit Recognition

Nuclear power plays a vital role in providing reliable and clean energy to fulfill increasing demands in electricity worldwide. It continues to be an essential source of national power supply as growing concerns about fossil fuel depletion, global warming, and emissions require utilizing sustainable energy sources. One area contributing to the growth of nuclear power is the development of reactors that have enhanced protection and security, thermal efficiency, and design. Reactor efficiency can be studied by the bur-nup that occurs when a TRISO-fueled pebble is inserted into the nuclear core and subsequently removed. The levels of burnup are measured based on the length of time the pebble spends within the core. In our design, each peb-ble is numbered by multiple digits printed in six locations using Ultra-High Temperature Ceramic paint. Naturally, computer vision techniques can be used to identify and time each pebble based on its digits as it enters and exits the core. We present a deep learning approach that successfully tags each pebble by identifying its digits from a video stream of the entrance and exit of the core. In a multi-step method, we extract only the clearest and most useful views of the pebble’s digits to classify as it rolls by. This algorithm is robust against issues that occur for objects in movement such as motion blur, rotations, and glare. We outperform other state-of-the-art optical character recognition (OCR) models that fail to identify digits that are in motion. Our approach creates a safer and more efficient way to measure burnup within a core while contributing to the improvement of nuclear power produced by reactors. 1
Parent Reports of the Psychosocial Functioning of Children with Cleft Lip and/or Palate

Objectives: (1) to determine the opinion of parents regarding the psychosocial functioning of their child with cleft lip and/or palate (CLP); (2) to identify predictors of psychosocial functioning; and (3) to determine the level of agreement between children with CLP and their parents. Participants: One hundred twenty-nine parents of children with CLP and 96 parents of children without CLP participated in this cross-sectional study. Outcome measures: Parental opinion of the child's self-esteem, anxiety, happiness, and problems caused by facial appearance were assessed using visual analogue scales. Parents completed the Child Behavior Checklist and were interviewed. Results: Children with CLP were more anxious (p < 0.05), less happy with their appearance (p < 0.001), and in general (p < 0.05) had lower self-esteem (p < 0.05) and greater behavioral problems (p < 0.001) compared with non-CLP children. Parents reported that their child with CLP was teased more often (p < 0.001) and was less satisfied with his/her speech (p < 0.01) compared with reports of parents in the control group. A number of factors affected parents’ ratings of their child's psychosocial functioning (presence of CLP, appearance happiness, previous history of CLP, and visibility of scar). Children who had been teased were more anxious (p ≤ 0.01), less happy with their appearance (p < 0.001) and had greater behavioral problems (p < 0.001). Conclusions: Parents of children with CLP reported various psychosocial problems among their children. Parents considered children who had been teased to have greater psychosocial problems.
The speed of life in sharks and rays: methods, patterns, and data-poor applications

Since the theory of evolution by natural selection was rst postulated, biologists have noted that life histories evolve following broad patterns across all organisms. Understanding the mechanisms causing these relationships is the central focus of life history theory; these insights can also be used to better estimate the biology and extinction risk of data-poor species. Sharks, rays, and chimaeras (class Chondrichthyes) are an ideal taxon to explore these relationships as they have evolved a broad range of life history strategies. In this thesis, I focus on two key time-related life history parameters that are often used as a measure of productivity: growth coe cient k , which is estimated from the von Bertalan y growth function (VBGF), and maximum intrinsic rate of population increase rmax , estimated by simplifying the Euler-Lotka equation. I begin by clarifying two methodological problems regarding the estimation of growth and productivity. I rst show that xing the y-intercept in the VBGF, a common approach in chondrichthyan age and growth studies, often causes considerable bias in growth coe cient estimates, and recommend using the three-parameter VBGF instead. I then point out an important omission in a method commonly used for estimating rmax in chondrichthyans and clarify the correct way to estimate it. Next I explore the e ect of uncertainty on the estimation of rmax and show that species with low annual reproductive outputs are bound to have very low productivities, thus focus should be placed into accurately estimating litter sizes, breeding intervals, and the variability of these traits. As an example of how these insights can be applied, I better estimate growth and productivity for a data sparse species of conservation concern, the Spinetail Devil Ray (Mobula japanica), and show it has a much lower somatic growth rate than previously thought and one of the lowest productivities among chondrichthyans. Finally, I show that productivity in chondrichthyans varies with temperature as well as depth, and that the scaling of this relationship changes with temperature according to the expectation from Bergman’s rule. My thesis demonstrates that simple insights from life history theory can further our knowledge on the broad patterns that shape the evolution of life histories we see today, which can be used to inform management of data-poor species.
Size and composition measurements of background aerosol and new particle growth in a Finnish forest during QUEST 2 using an Aerodyne Aerosol Mass Spectrometer

The study of the growth of nucleation-mode parti- cles is important, as this prevents their loss through diffusion and allows them to reach sizes where they may become ef- fective cloud condensation nuclei. Hyyti ¨¨ a, a forested site in southern Finland, frequently experiences particle nucle- ation events during the spring and autumn, where particles first appear during the morning and continue to grow for sev- eral hours afterwards. As part of the QUEST 2 intensive field campaign during March and April 2003, an Aerodyne Aerosol Mass Spectrometer (AMS) was deployed alongside other aerosol instrumentation to study the particulate com- position and dynamics of growth events and characterise the background aerosol. Despite the small mass concentrations, the AMS was able to distinguish the grown particles in the <100 nm regime several hours after an event and confirm that the particles were principally organic in composition. The AMS was also able to derive a mass spectral finger- print for the organic species present, and found that it was consistent between events and independent of the mean par- ticle diameter during non-polluted cases, implying the same species were also condensing onto the accumulation mode. The results were compared with those from offline analyses such as GC-MS and were consistent with the hypothesis that the main components were alkanes from plant waxes and the oxidation products of terpenes.
Pediatric anaphylaxis and hyper IgE syndrome

Patients with autosomal-dominant (AD) hyper immunoglobulin E (IgE) syndrome (HIES) or Job syndrome develop frequent dermatologic and pulmonary infections. As patients have an extreme elevation of IgE levels, this database analysis study sought to study the association between AD HIES, Job syndrome, and anaphylaxis. HIES is a heterogeneous group of immune disorders characterized by extremely elevated levels of serum IgE. Although the molecular defects and clinical phenotypes found in association with Job syndrome are well characterized, the association with severe allergic reactions and anaphylaxis is a subject of ongoing investigation.
Monetary and Financial Cooperation in Asia : Emerging Trends and Prospects

Ever since the currency crisis of 1997-98 there has been a great deal of interest in enhancing regional economic cooperation in Asia. It is important to keep in mind that economic regionalism is multidimensional nature. The focus of this paper is on policy initiatives underway in Asia to enhance monetary and financial regionalism and the analytical bases for these initiatives, rather than on examining the de facto level of financial and monetary links that already exists (which may or may not have been facilitated via regional policy mechanisms). There are many gradations of monetary and financial regional cooperation, ranging from the weak form involving regional policy dialogue and surveillance, on the one hand, to exchange rate and monetary coordination, on the other. To maintain focus, this paper concentrates more narrowly on medium forms of monetary and financial regionalism, broadly defined as the development of regional liquidity arrangements and regional financial markets.
Real-time eye gaze tracking for gaming design and consumer electronics systems

Real time face detection combined with eyegaze tracking can provide a means of user input into a gaming environment. Game and CE system designers can use facial and eye-gaze information in various ways to enhance UI design providing smarter modes of gameplay interaction and UI modalities that are sensitive to a users behaviors and mood. Here we review earlier approaches, using wearable sensors, or enhanced IR illumination. Our technique only requires video feed from a low-resolution user-facing camera. The algorithm is described and some comparative results on a range of embedded hardware are provided. The potential for using eye-gaze as a means of direct user input and improving the accuracy of estimation accordingly is also discussed.
Vertical accuracy evaluation of SRTM-GL1, GDEM-V2, AW3D30 and CartoDEM-V3.1 of 30-m resolution with dual frequency GNSS for lower Tapi Basin India

Abstract Shuttle Radar Topography Mission (SRTM-GL1), Advanced Space Borne Thermal Emission and Reflection Radiometer- Global DEM (GDEM-V2), recently released Advanced Land Observing Satellite (‘DAICHI’) DEM (AW3D30) and Indian National Cartosat-1 DEM v3 (CartoDEM-V3.1) provide free topographic data at a 30-m resolution for Indian peninsula. In this research study, the vertical accuracy of DEM is evaluated for above data-sets and compared with high accuracy dual frequency GNSS of a millimetre accuracy. The extensive field investigation is carried out using a stratified random fast static DGPS survey for collecting 117 high accuracy ground control points in a predominantly agriculture catchment. Further, the effect of land cover, slope and low-lying coastal zone on DEM vertical accuracy was also analysed and presented in this study.
Effects of oat bran, processed to different molecular weights of β-glucan, on plasma lipids and caecal formation of SCFA in mice

In the present study, we evaluated the cholesterol-lowering effects of different oat bran (OB) preparations, differing regarding their peak molecular weight (MWp) of β-glucans (2348, 1311, 241, 56, 21 or < 10 kDa), in C57BL/6NCrl mice. The diets were designed to be atherogenic (0·8 % cholesterol and 0·1 % cholic acid), and they reflected the Western diet pattern (41 % energy fat). All OB preparations that were investigated significantly reduced plasma cholesterol when compared with a cellulose-containing control diet, regardless of the molecular weight of β-glucan. Moreover, the difference in viscous properties between the processed OB (from 0·11 to 17·7 l/g) did not appear to play a major role in the cholesterol-lowering properties. In addition, there was no correlation between the molecular weight of β-glucan and the amount of propionic acid formed in caecum. Interestingly, however, there was a significant correlation between the ratio of (propionic acid+butyric acid)/acetic acid and the MWp of β-glucans: the ratio increased with increasing molecular weight. The results of the present study suggest that the molecular weights and viscous properties of β-glucan in oat products may not be crucial parameters for their cholesterol-lowering effects.
Deep Learning Empowers Next-Gen Video Compression: Bridging Quality and Efficiency

Deep learning accelerates video processing. Our digital exchanges increasingly use video. Technology has raised video resolutions and volumes, making collection, distribution, compression, and display tougher. This paper introduces flask-based Deep Learning video compression. Good treatment results. This technique expertly blends Deep Learning's adversarial generative and convolutional neural networks. Convolutional and adversarial generating networks are CNN and GAN. GAN detects minute changes, LSTM captures them, and image repetition reduces video. Reduces files. Steps after layer grouping. GAN's incremental updates compress frames better than the original image. This reduces compressed videos. SVD finds latent components in video frames. This reduces R, G, B utility matrix dimension. KNN calculates each frame image's neighbor connection. Comparison results are classified by K-means. Codecs compare frames to their original video formats. Comparison follows video translation. Resampling rates were statistically significant in many experiments with movies of different lengths, resolutions, FPS, and quality. 10% lower quality and 50% smaller than the original video.