Miracle-dz/UniFAR-FTUs huggingface dataset:
A neural network for composer classification

I present a neural network approach to automatically extract musical features from 20-second audio clips in order to predict their composer. The network is composed of three convolutional layers followed by a long short-term memory recurrent layer. The model reaches an accuracy of 70% on the validation set when classifying amongst 6 composers. The work represents the early stage of a project devoted to automatic feature detection and visualization.
Experimental study of capillary trapping on the pore scale for various sandstone cores

Entrapment of the non-wetting phase in porous media has been observed in a variety of fields such as petroleum engineering, geological storage of carbon dioxide, and remediation of ground water. We investigated gas trapping in porous media from a microscopic point of view. Highresolution, three-dimensional images of pore structure and trapped gas bubbles in Berea sandstones were obtained using a micro-focused X-ray CT scanner. We used vertical and horizontal Berea sandstone cores, 8 mm in diameter and 15 mm long. Based on the three-dimensional image analysis, the statistical distribution of the trapped gas volume was estimated. Trapped bubbles have a pore-network scale size and distribute over several pores. In the case of the vertical core, the porosity fluctuates along the flow direction due to the layered structure. The residual gas saturation also fluctuates with porosity along the flow direction. The higher gas saturation in porous layers at the end of gas injection results in a higher trapped gas saturation compared to dense layers. On the other hand, in dense layers the gas saturation at the end of gas injection is almost the same as the residual gas saturation. Therefore, most of the gas injected into the dense layers would be trapped. In the case of horizontal core, the gas saturation at the irreducible water condition is lower than that for the vertical core, because the injected gas selectively passes through the more permeable layers. However, the residual gas saturation is 29.2% for the horizontal core, which is comparable with that for the vertical core (30.9%). Finally, the effect of capillary number on stability of trapped gas bubbles has been estimated. Trapped gas bubbles are stable against the increased flow rate up to a capillary number of 1.0 ×10. © 2010 Elsevier Ltd. All rights reserved
Design Recommendations for Self-Monitoring in the Workplace

One way to improve the productivity of knowledge workers is to increase their self-awareness about productivity at work through self-monitoring. Yet, little is known about expectations of, the experience with, and the impact of self-monitoring in the workplace. To address this gap, we studied software developers, as one community of knowledge workers. We used an iterative, user-feedback-driven development approach (N=20) and a survey (N=413) to infer design elements for workplace self-monitoring, which we then implemented as a technology probe called WorkAnalytics. We field-tested these design elements during a three-week study with software development professionals (N=43). Based on the results of the field study, we present design recommendations for self-monitoring in the workplace, such as using experience sampling to increase the awareness about work and to create richer insights, the need for a large variety of different metrics to retrospect about work, and that actionable insights, enriched with benchmarking data from co-workers, are likely needed to foster productive behavior change and improve collaboration at work. Our work can serve as a starting point for researchers and practitioners to build self-monitoring tools for the workplace.
Lecture One 1 . 1 Relativistic Dispersion In One Space Dimension

These notes are based on lectures at the PSSCMP/PiTP summer school that was held at Princeton University and the Institute for Advanced Study in July, 2015. They are devoted largely to topological phases of matter that can be understood in terms of free fermions and band theory. They also contain an introduction to the fractional quantum Hall effect from the point of view of effective field theory. ar X iv :1 51 0. 07 69 8v 2 [ co nd -m at . m es -h al l] 1 3 Ju n 20 16
USING SATELLITE MEASUREMENTS OF SURFACE SOIL MOISTURE TO IMPROVE ESTIMATES OF CO 2 AND CH 4 FROM PEATLANDS

Peatlands are important stores of carbon through the partial decomposition of organic matter. However peatlands not only sequester CO2 but they are the main natural source of methane (CH4) due to anaerobic microbial activity under waterlogged conditions. Northern wetlands contribute about 35TgCH4yr [1]. The uncertainty on this estimate is large (from 1mgCH4m y to 2200mgCH4m y), therefore there is a need to better quantify CH4 emissions and their role in the net carbon balance of peatlands. A correct representation of the hydrology of the system is necessary for modelling CH4 flux as the water table depth controls the area where methanogenic bacteria are active. One of the key variables in the calculation of water table depth is the soil moisture. Soil moisture also affects the decomposition rates of carbon in the soil and influences the water and energy fluxes at the land surface atmosphere boundary. Microwave measurements of surface soil moisture from satellites can theoretically be used to improve estimates predicted by models. Results from an Observing System Simulation Experiment (OSSE), designed to investigate how observations from satellites may be able to constrain modelled carbon fluxes, are presented. An adapted version of the Carnegie-Ames-Stanford Approach (CASA) model [2] is used that includes a representation of methane dynamics [3]. Synthetic satellite observations of soil moisture are used to update model estimates using a Metropolis Hastings Markov Chain Monte Carlo (MCMC) approach. The effect of temporal frequency and spacing, and precision of observations, is examined with a view to establishing the set of observations that would make a significant improvement in model uncertainty. The results are compared with the system characteristics of existing satellite soil moisture measurements. We believe this is the first attempt to assimilate surface soil moisture into an ecosystem model that includes a full representation of CH4 flux.
On the Performance of Coded OFDM with and without Spreading in an Interference Limited Environment

We address an OFDM-based air interface operating in an interference limited environment, which might be encountered in a cellular mobile communication system. For enhanced robustness, an OFDM system with spreading, known as multi-carrier (MC) CDMA, may operate not fully loaded. On the other hand, a lower code rate also improves the robustness. In this paper, the trade-off between code rate and system load constraint to the same spectral efficiency is analyzed in a cellular downlink scenario. It is demonstrated through simulations that a fully loaded MC-CDMA system always outperforms a non-fully loaded system, provided the code rate is chosen such that the throughput of both systems is equivalent. Moreover, the MC-CDMA system fails to outperform a coded OFDM system without spreading, even in a cellular environment.
Stem Cells and Metallothionein-A Review

Stem Cells are capable of self renewal and can differentiate into other lineages upon induction with specific growth factors and proteins. Mesenchymal stem cells obtained from various sources like adipose tissue, umbilical cord, bone marrow, umbilical cord blood have been reported to have stem cell characteristic features laid down by International Society for Cellular Therapy. Research so far deals with the differentiation and self renewal properties of stem cells, which needs to be understood further. Metallothionein, is a metal binding protein isolated from equine renal cortex and shown to be present in nearly all of our cells, with differential expression of it’s isoforms. Apart from metal binding properties, this protein expression is deregulated in a variety of diseases and other treatment conditions. With respect to cancer biology, this protein expression is studied in almost all cancer types and results indicate pivotal role of this protein in cancer. Certain cancers are associated with up-regulation while some types are associated with down-regulation. The localization of this protein has also reported to change between actively proliferating and normal cells. Given the importance of this protein in cancer biology, the role of this protein in stem cell renewal as well as differentiation is poorly understood. This review discusses about stem cells, its type and differentiation; metallothioenein – expression, function, review about different cancer types, role in angiogenesis and plausible role of this protein in the self renewal and differentiation of stem cells.
Increasing Resilience in Changing Climate among Rural Households : Evidence from West Shewa , Ethiopia

Shared ranges of complex risks, including climate change, environmental degradation, and conflict are exacerbating the challenges faced by farm households. This research aimed to measure measn to increase farm households resilience to changing climate using seven blocs of the resilience framework. Resilience index was defined as a function of agricultural inputs and technology, social safety nets, access to public services, access to food and income, access to assets, stability and adaptive capacity blocs. The estimation was made separately using principal component analysis. Three components were retained to estimate resilience. Under the first component, all blocs, except social safety nets and adaptive capacity, were positively correlated with resilience. The negative correlation between social safety nets and resilience, for instance, is because social prominence decreases as households becomes poorer. In terms of importance to rural household‟s resilience index, the result indicates that asset ownership and access to food and income play significant role followed by access to inputs and technology and access to public services. These resilience blocs show the likely that when a household experiences any form of climatic shocks, pooled out from the difficult situation and enables them to acquire resources that they did not have acquainted before. In the second component assets and stability were negative but weak, which shows that these blocs make deteriorate resilience capacity of rural farm households. The third component triggers hidden information of the resilience bloc. From all the resilience blocs under the third component, stability is strong and positive, which likely tells common story in terms of food security situations.
Crystallization kinetics of safflower and olive oils during low-temperature storage

The crystallization behaviors of safflower and olive oils were investigated according to changes in volume and transmitted light intensity during isothermal storage at low temperature. The changes between the oils were significantly different even though their fatty acid compositions were similar, with oleic acid accounting for more than 75% (w/w) of the total oil. It was expected that minor components with high melting points would affect the crystallization behaviors of these oils. The crystallization processes of the oils were then analyzed using a kinetic model in which the oil crystallizes through two different processes. It is suggested that although the crystallization behaviors were apparently different, the crystallization mechanisms of these oils are essentially the same.
The Learning Organisation and Emotional Intelligence

Emotional intelligence (EI) can be a diagnostic tool and a set of guiding principals to address the learning organization's concern of overcoming the barriers to collective learning. EI can be defined as "how well you handle yourself. " It refers to "emotional literacy" and a person's capacity to manage emotions and use them as a resource. This is done by knowing one's emotions; managing emotions; motivating oneself; recognizing emotions in others; and handling relationships. The learning organization has emotional underpinnings in that it directly addresses the barriers to such things as collective learning and shared visions. EI has the potential to be a diagnostic tool to assess the 'emotional climate' of the broader organization and the development of specific persons within the organization. There is debate as to whether EI can be measured. Issues with the use of EI as a diagnostic tool include the tendency to take the individual as the unit of analysis, thus ignoring social factors and collective dynamics. EI addresses real workplace issues, it has the potential to guide the management of workplace relationships, remove barriers to collaboration, and manage workplace diversity. (Contains 10 references.) (SLR) Reproductions supplied by EDRS are the best that can be made from the original document. 1 CLMS Working Paper No 31 PERMISSION TO REPRODUCE AND DISSEMINATE THIS MATERIAL HAS BEEN GRANTED BY
On the Usability of a Break-the-Glass Annotation Language for Process Models

Business process design for real-world applications often requires modelling languages of a certain complexity, interweaving several process perspectives, such as the data and the organizational one, and taking contextual process information into account. Ensuring that such languages are indeed usable is not trivial. This paper describes a usability study for a modelling language with those characteristics. More specifically, the so-called BTG! language features the security concept Break the Glass (BTG) that allows to specify exceptional access to data. We investigate usability characteristics of BTG! such as learnability, efficiency, errors, and satisfaction. Our study has helped to increase the usability of the language significantly. To illustrate, we have replaced the language terms with more intuitive ones and have extended the language with some frequently desired features. Our experiences can be applied to process modelling languages that are similarly comprehensive.
Speaker Recognition by Gaussian Filter Based Feature Extraction and Proposed Fuzzy Vector Quantization Modelling Technique

Automatic speaker-recognition systems (ASR) have developed as a vital method for recognition of a person in many applications like e-commerce as well as in common interactions, law enforcement, and forensics. The performance of automatic speaker recognition system depends on the duration of the voice of test and train samples. In this paper, I address the issues in the design of codebook for outlier effect using the fuzzy vector quantization based algorithm for tasks such as speaker recognition for short voice samples. Particularly, I address the issues in partitioning the voice data for matching sequences of speaker specific feature vectors extracted from the voice signal data of utterances of a speaker. The design of codebook based on fuzzy vector quantization (FVQ) and fuzzy c-means (FCM) vector quantization has been proposed previously for matching the test and train voice signal characterized as sets of speakerspecific features vectors for tasks such as distortion measure and speaker recognition. Speaker-specific features Mel Frequency Cepstral Coefficients (MFCC) extracted by the traditional triangular filter as well as Gaussian and Tukey shapes filter. This research paper compares experimental results of three different modelling techniques namely, Fuzzy c-means, Fuzzy Vector Quantization2 (FVQ2) and proposed fuzzy vector quantization (FVQ). ASR efficiency of FVQ shows significant improvement in performance compared to FCM and FVQ2. The efficiency of proposed ASR system is 98.8 % for 2 seconds of training voice data for a set of 100 speakers taken from the Texas Instruments and Massachusetts Institute of Technology (TIMIT) database.
A Study of Person Entity Extraction and Profiling from Classical Chinese Historiography

When historians are interested in demographic and social network information of historical actors in the early Chinese empires (841 BC–1911 AD), very few studies have been done on entity retrieval from classical Chinese historiography.The key challenge lies in the low resource of the language: deep learning requires large amounts of annotated data and becomes impracticablewhen such data is not available. In this study, we employ domain experts (history professors) to curate a set of person entities and their profile attributes (e.g., courtesy name, place of birth, title) and relations (e.g., fatherson,master-disciple) from two books, Records of the Grand Historian and Book of Han. We develop a pattern-based bootstrapping approach to extract the information with a very small number (i.e., 1 or 2) of seed patterns. Experimental results show the effectiveness as well as the limitations of the iterative method. We would appreciate research of digital humanities to address the challenges in entity retrieval from low-resource languages.
State of the art analysis for Connected and Automated Driving within the SCOUT project

This publication gives a short introduction and overview of the European project SCOUT and introduces a methodology for a holistic approach to record the state of the art in technical (vehicle and connectivity, human factors regarding physiologic and ergonomic level) and non-technical enablers (societal, economic, legal, regulatory and policy level) of connected and automated driving in Europe. The paper addresses beside the technical topics of environmental perception, E/E architecture, actuators and security, the state of the art of the legal framework in the context of connected and automated driving.
Localization of fl-oxidation enzymes in peroxisomes isolated from nonfatty plant tissues *

Peroxisomes from spinach leaves, mungbean hypocotyls, and potato tubers catalyze a palmitoyl-CoA-dependent, KCN-insensitive 0 2 uptake. In the course of this reaction 0 2 is reduced to H20 2 in a 1 : 1 stoichiometry and palmitoyl-CoA oxidized, in a 1 : 1 stoichiometry, to a product serving as substrate for enoyl-CoA hydratase. These findings demonstrate the existence of a peroxisomal acyl-CoA oxidase in these tissues. Enoyl-CoA hydratase (EC 4.2.1.17), 3-hydroxyacyl-CoA dehydrogenase (EC 1.1.1.35), and thiolase (EC 2.3.1.9) are also associated with the peroxisomes from mung-bean hypocotyls and potato tubers (as well as with spinach leaf peroxisomes as recently reported; Gerhardt 1981, FEBS Lett. 126, 71). The low activities of these enzymes in mitochondrial fractions seem to be due to contaminating peroxisomes since the ratio offl-oxidation enzyme activities to catalase activity did not significantly differ between peroxisomal and mitochondrial fractions isolated on sucrose density gradients. The proof of localization of fl-oxidation enzymes in peroxisomes without glyoxysomal function leads to the concept that fatty-acid oxidation is a consistent basic function of the peroxisome in cells of higher
MODEL-BASED CONTROL OF SHEAR FLOWS USING LOW-DIMENSIONAL GALERKIN-AND VORTEX MODELS

Mark Pastoor , Rudibert King, Bernd R. Noack , Gilead Tadmor , Marek Morzýnski Institut für Prozesstechnik, Anlagentechnik und Technische Akustik, Te chnische Universität Berlin P2-1, Hardenbergstr. 36a, D-10623 Berlin, Germany Hermann-Föttinger-Institut für Strömungsmechanik, Technische Unive rsität Berlin HF1, Strasse des 17. Juni 135, D-10623 Berlin, Germany Department of Electrical and Computer Engineering, Northeastern Univ ers ty, 440 Dana Research Building, Boston, MA 02115, USA Institute of Combustion Engines and Basics of Machine Design, Poznań U iversity of Technology, ul. Piotrowo 3, PL 60-965 Poznań, Poland
Diagnosis of the Pacific Decadal Oscillation in Global Climate Models

The Pacific Decadal Oscillation (PDO) is a variation in sea surface temperatures in the Northern Pacific Ocean. These variations occur over a period of 10-35 years. The PDO is similar to the El Nino Southern Oscillation (ENSO) pattern in the Southern Pacific and is expected to have the same effects as well. The findings pursued look for reflection of the PDO in past sea surface temperatures within Global Climate Models (GCMs). Global Climate Models integrate a variety of equations describing the atmosphere and oceans to help project the future climate as well as reconstruct the past. If past projections do not match up with what occurred, climate prediction into the future will not be an accurate measure. The information received from the data suggests that GCMs do not depict the exact PDO clearly. However, they do recognize multidecadal patterns of sea surface temperature shifts, but they do not line up accurately to the patterns of the PDO. If the past trends can't be reconstructed, predicting the future trends will be impossible unless the PDO can be clearly accounted for by GCMs.
1 Genetic Algorithms in Shape Optimization of a Paper Machine

The headbox is located at the wet end of a paper machine. Its function is to dist ribute fibre suspension (wood fibres, filler clays and chemicals mixed in water) in an e ven layer, across the width of a paper machine. The fluid (fibre suspension) com ing from a pump enters the first flow passage in the headbox, a header, which distrib utes the fluid equally across the machine width via a bank of manifold tubes. A cont rolled amount of the fluid is recirculated at the far end of the header to provide flow control along the header length. A traditional designing problem in a paper machine headbox is tapering of t he header such that the flow distribution is even across the full width of a paper machine. The problem has already been studied since 50’s [1, 13, 16]. At that time C FD tools were not available and the models for flows in the header were simple and on edimensional. Clearly, when the header design is based on a fluid flow model, t he resulting design can only be as good as the model is. Thus, to answer today ’s he dbox functioningdemands, more sophisticated designing based on more accurate fluid flow modeling is needed. Our approach is to formulate designing of the tapered header as a shape optim ization problem based on today’s CFD modeling and simulation capability. T he cost function to be minimized describes how even the flow distribution fro m the header is. We have chosen it to be the square of the standard deviation of the u let flow rate profile. Fluid flows in the header are solved by Valmet’s own CFD soft ware. A
Ability in Colleges and Universities Based on Discrete Hopfield Neural Network

ABSTRACT. With the development of China's economy and the continuous enhancement of its comprehensive strength, the development of China's higher education has entered the upper-middle level of the world, but the development of education in China is not balanced.Taking Jiangsu Province as an example, this paper gives a comprehensive evaluation of the quality of undergraduate education in 13 prefecture-level cities in Jiangsu Province.This paper firstly reviews the data of relevant indicators given in the paper, and considers the impact of a small number of indicators that cannot be accurately quantified. Combined with the associative memory ability of discrete Hopfield neural networks, an evaluation model of discrete Hopfield undergraduate education quality is established.Secondly, the university is divided into five grades and the average value of each index is used as the ideal evaluation index of each grade, which is the balance point of Hopfield neural network.Finally, the results of the simulation of the example are obtained by using the neural network toolbox that comes with Matlab.