Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling Self-Repetition in Music Generation using Generative Adversarial Networks

In this paper we propose a generative model for music generation focusing on self-repetition. We use a Generative Adversarial Network formulation to learn a model which can generate compositions with long term repetition structures similar to those found in training data. We propose to represent self-repetition in a composition using a self-similarity matrix constructed by computing similarity between pairs of measures. To avoid optimization issues due to discrete nature of notes in musical compositions, and to provide more ﬂexibility in identifying similarity between measure pairs, we propose to encode measures into low dimensional measure embeddings – effectively lifting the discrete observations to a continuous space. Our model reasons about generating structured sequences directly in this lifted space. Preliminary experiments show promising results from our proposed method.
A New Approach for Automating Analysis of Responses on Verbal Fluency Tests from Subjects At-Risk for Schizophrenia

What if young people at risk for developing schizophrenia could be identified early, via a fast, automated, non-invasive test of language, which could be administered remotely? These youths could then receive intervention which might mitigate course and possibly prevent psychosis. Timed word fluency tests, in which individuals name words starting with a designated sound (typically F/A/S) or represent a given concept category (commonly animals/fruits/vegetables), have been used in the assessment of schizophrenia and its risk states, and in many other mental health conditions. Typically, psychologists manually record the number and size of valid phoneme clusters and switches observed in the phonemic tests and count the number of valid words belonging to a given category in the categorical tests. We present a new technique for automating the analysis of category fluency data and apply it to the problem of detecting youths at risk of developing schizophrenia, with best results over 85% accuracy when applying phonemic analysis to categorical data. The technique supports the separate quantification of structural and sequential phonemic similarity measures, supports an arbitrary range of pronunciations and dialects in the analysis, and may be extended to the assessment of other mental and physical health conditions, and their risk states.
seasonal evolution in the North Subtropical free 1 troposphere 2 3

14 Three years of Multi-Axis Differential Optical Absorption Spectroscopy (MAXDOAS) 15 measurements (2011-2013) have been used for estimating the NO2 mixing ratio along a 16 horizontal line of sight from the high mountain Subtropical observatory of Izaña, at 2370 m 17 a.s. l. (NDACC station, 28.3oN, 16.5oW). The method is based on horizontal path calculation 18 from the O2-O2 collisional complex at the 477 nm absorption band which is measured 19 simultaneously to the NO2, and is applicable under low aerosols loading conditions. 20 The MAXDOAS technique, applied in horizontal mode in the free troposphere, minimizes the 21 impact of the NO2 contamination resulting from the arrival of MBL airmasses from thermally 22 forced upwelling breeze during central hours of the day. Comparisons with in situ 23 observations show that during most of measuring period the MAXDOAS is insensitive or 24 very little sensitive to the upwelling breeze. Exceptions are found under pollution events 25 during southern wind conditions. On these occasions, evidence of fast efficient and 26 irreversible transport from the surface to the free troposphere is found. 27 Background NO2 vmr, representative of the remote free troposphere, are in the range of 20-45 28 pptv. The observed seasonal evolution shows an annual wave where the peak is in phase with 29 2 the solar radiation. Model simulations with the chemistry-climate CAM-Chem model are in 1 good agreement with the NO2 measurements, and are used to further investigate the possible 2 drivers of the NO2 seasonality observed at Izaña. 3
Physically Based Estimation of Rainfall Thresholds Triggering Shallow Landslides in Volcanic Slopes of Southern Italy

On the 4th and 5th of March 2005, about 100 rainfall-induced landslides occurred along volcanic slopes of Camaldoli Hill in Naples, Italy. These started as soil slips in the upper substratum of incoherent and welded volcaniclastic deposits, then evolved downslope according to debris avalanche and debris flow mechanisms. This specific case of slope instability on complex volcaniclastic deposits remains poorly characterized and understood, although similar shallow landsliding phenomena have largely been studied in other peri-volcanic areas of the Campania region underlain by carbonate bedrock. Considering the landslide hazard in this urbanized area, this study focused on quantitatively advancing the understanding of the predisposing factors and hydrological conditions contributing to the initial landslide triggering. Borehole drilling, trial pits, dynamic penetrometer tests, topographic surveys, and infiltration tests were conducted on a slope sector of Camaldoli Hill to develop a geological framework model. Undisturbed soil samples were collected for laboratory testing to further characterize hydraulic and geotechnical properties of the soil units identified. In situ soil pressure head monitoring probes were also installed. A numerical model of two-dimensional variably saturated subsurface water flow was parameterized for the monitored hillslope using field and laboratory data. Based on the observed soil pressure head dynamics, the model was calibrated by adjusting the evapotranspiration parameters. This physically based hydrologic model was combined with an infinite-slope stability analysis to reconstruct the critical unsaturated/saturated conditions leading to slope failure. This coupled hydromechanical numerical model was then used to determine intensity–duration (I-D) thresholds for landslide initiation over a range of plausible rainfall intensities and topographic slope angles for the region. The proposed approach can be conceived as a practicable method for defining a warning criterion in urbanized areas threatened by rainfall-induced shallow landslides, given the unavailability of a consistent inventory of past landslide events that prevents a rigorous empirical analysis.
Linguistically-Informed Training of Acoustic Word Embeddings for Low-Resource Languages

Acoustic word embeddings have been proven to be useful in query-by-example keyword search. Such embeddings are typically trained to distinguish the same word from a different word using exact orthographic representations; so, two different words will have dissimilar embeddings even if they are pronounced similarly or share the same stem. However, in real-world applications such as keyword search in low-resource languages, models are expected to find all derived and inflected forms for a certain keyword. In this paper, we address this mismatch by incorporating linguistic information when training neural acoustic word embeddings. We propose two linguistically-informed methods for training these embeddings, both of which, when we use metrics that consider non-exact matches, outperform state-of-the-art models on the Switchboard dataset. We also present results on Sinhala to show that models trained on English can be directly transferred to embed spoken words in a very different language with high accuracy.
Multi-Stride Self-Attention for Speech Recognition

In contrast to the huge success of self-attention based neural networks in various NLP tasks, the efficacy of self-attention in speech applications is yet limited. This is partly because the full effectiveness of the self-attention mechanism could not be achieved without proper down-sampling schemes in speech tasks. To address this issue, we propose a new selfattention mechanism suitable for speech recognition, namely, multi-stride self-attention. The proposed multi-stride approach lets each group of heads in self-attention process speech frames with a unique stride over neighboring frames. Thus, the entire attention mechanism would not be confined in a fixed frame shift and can have diverse contextual views for a given frame to determine attention weights more effectively. To validate our proposal we evaluated it on various speech corpora for speech recognition, both English and Chinese, and observed a consistent improvement, especially in terms of substitution and deletion errors, without the increase of model complexity. The average WER improvement of 7.5% (relative) obtained by the TDNNs having the multi-stride self-attention layer as compared to the baseline TDNN model shows the effectiveness of the proposed multi-stride self-attention mechanism.
THE SELF-CONCEPT IN RELATION TO GOOD AND EVIL ACTS one oPPortunIty to aCt dIsHonestly : self-ConCePt maIntenanCe and tHe “ fudGe faCtor ”

The accounting scandals and the collapse of billion-dollar companies at the beginning of the 21st century have forever changed the business landscape. These cases of corporate corruption add to a long list of instances of unethical behavior in organizations and society more broadly across a variety of settings (e.g., Frank et al., 2003): Employees violate company rules, workers sabotage their peers, consumers shoplift, students cheat on exams, citizens evade taxes, and managers overstate firm performance to shareholders. Such unethical behaviors are costly to organizations and economic systems more broadly (Graham, Litan, & Sukhtankar, 2002; Weber Kurke, & Pentico, 2003). For instance, organizations typically lose 5% of their revenues to fraud each year (Association of Certified
Buoys , break lines , and unique backgrounds : techniques for non-disruptive bidirectional spatial links

We present new user interface techniques to facilitate nondisruptive user interfaces to hypertext, made possible by modern graphics accelerators. Buoys are objects floating in the margin, visibly connected to an anchor in a document. Break lines make fragments look like torn-off pieces of the link targets. Unique backgrounds for documents allow users to recognize a fragment’s source. Using a nadir for orienting the buoys makes them visually distinct. The techniques are especially effective when used in combination. Together, these techniques allow the target anchors of all currently visible links to be shown. Upon traversing a link, the view can fluidly animate to the target, while the originating document remains visible, moving into the margin. As an example, we show screenshots of a prototype for allowing structured user annotations between PDF files.
Effect of Stocking Rate of Thai-Esaan Native Beef Cattle under Alternate Grazing Methods on Growth Performance and Botanical Changes in Grass-Legume Mixture Pastureland

This experiment was carried out at the University Farm, Department of Animal Science, Faculty of Agriculture, Khon Kaen University, Khon Kaen, Thailand during April 2011 to September 2012. The work aimed to study effect of stocking rate of Thai-Esaan native beef cattle carried out under “cut and carry” and alternate grazing methods with respect to beef cattle growth performance and the changes in botanical composition of grass-legume mixture regime of the pastureland. Korat soil series (Oxic paleustults) was used. The experiment was laid in a Completely Randomized Design (CRD) with 3 replications and each replication had 2 heads of Thai-Esaan native beef cattle. The experiment consisted of 4 treatments, i.e. T1 (control, “cut and carry” method) had 0.25 rai/head, T2 had a grazing area of pastureland of 0.25 rai/head, T3 had a grazing area of pastureland of 0.50 rai/head and T4 had a grazing area of pastureland of 0.75 rai/head (1 hectare = 6.25 rai). The results showed that Korat soil series (Oxic Paleustults) is a poor fertility soil with an average pH value of 5.5 and most of the available soil nutrients (NPK) were relatively low. Total dry weights of grass plus legume before grazing were highest for T4 than the rest. This result was also found at the end of the experimental grazing period. Crude protein yields were highest with T3 followed by T4, T2 and least with T1 with mean values of 1,789, 1,740, 1,370 and 951 kg/ha, respectively. Feed intake values were highest with T4 followed by T3, T2 and least with T1 with the mean values of 5.65, 4.95, 3.85 and 3.43 kg/head/day, respectively. The difference was large and highly significant (P < 0.01). Average daily live weight gained was higher for T3 and T4 than T2 and T1 with values of 414, 456, 257 and 190 g/day, respectively. The percentages of total fat in rumen were higher for T3 and T4 than T2 and T1 with values of 0.06, 0.05, 0.02 and 0.02, respectively. The difference was large and statistically significant (P < 0.05). Conjugated linoleic acid values of total fat were highest with T4 followed by T3, T2 and T1 with the values of 1.50, 1.12, 0.17 and 0.11%, respectively. The difference was large and statistically significant. Alternate grazing methods significantly affected dry matter yields, botanical composition changes of the pastureland, and the beef cattle performance and also conjugated linoleic acid in the rumen of the beef cattle. Optimum stocking rate of 0.5 rai/head of T3 was the best recommended treatment for Korat soil series (Oxic Paleustults).
REFERENCE RANGES OF SERUM TOTAL AND FREE TESTOSTERONE IN JAPANESE MALE ADULTS

PURPOSE To establish reference range of serum Total Testosterone (T-T) and Free Testosterone (F-T) in Japanese male adults. SUBJECTS AND METHOD Among 1,172 male adults, who daily lived their healthy life, 1,143 subjects in the year range from 20 to 77 years old, who had serum LH concentration within its reference range (For 20-70 years old: 1.1-25.9 mIU/mL), were selected. As diurnal rhythm of both T-T and F-T was observed, blood samples were collected in the morning when T-T and F-T concentration were relatively stable at their high concentration levels. The collected samples were stored at -20 degree C until they were used for assays. RESULTS Reference range for T-T has decided to express by the mean +/- 2SD calculated from the entire test results, because influence of aging on the results was negligible, Reference range of T-T has established as 2.01-7.50 ng/mL. The other hand, reference ranges of F-T classified for every decade have decided to express by the mean +/- 2SD of each decade subgroup, because great influence of aging on F-T was observed. For each decade from 20 years on and > 70 years, reference ranges of F-T have established as: 8.5-27.9 pg/mL, 7.6-23.1 pg/mL, 7.7-21.6 pg/mL, 6.9-18.4 pg/mL, 5.4-16.7 pg/mL, and 4.5-13.8 pg/ mL, respectively. CONCLUSION Reference ranges of serum T-T and F-T in Japanese male adults have established. And the value of Young Adult Mean (YAM) of F-T calculated for a group of the ages between 20 and 39 years have been proposed as a guideline of requirement for the Androgen Replacement Therapy (HRT). The value of 80% and 70% of YAM were 12.4 pg/mL and 10.9 pg/mL, respectively.
Crafting Sustainable Indian Educational Institutions Through Solar Photovoltaic : A Partial Least Square-Structural Equation Model

The main context and aim of the research paper is to report the findings of the empirical study of the effect of government policy in implementing Grid connected Rooftop Solar Photovoltaic in Educational Institutions in the state of Karnataka, India. The Government policy has initiated the change towards sustainable development in the state of Karnataka. This research paper has used the second generation software Smart PLS3 to measure the reliability and validity. PLS-SEM highlights the effect of exogenous latent variables of Government policy, Reason for Motivation, Advantages, Opportunities and Challenges of implementing Roof top Solar Photovoltaic, as a renewable energy option for the Educational Institution with the three dimensions of sustainability, such as social, economic and environmental benefits, as the endogenous latent variables. Hypotheses are tested through bootstrapping. Effect of each construct is measured by Blindfolding method. Finally, the Importance performance matrix analysis (IPMA) has been done in order to measure the impact of constructs and the indicators on the model. Adoption of renewable energy solution, has been found to cultivate a learning environment that mirror real-world problems and encourage curriculum development in the field. It develops positive attitude of the students towards renewable energy and sustainability thereby encouraging environment conservation leading to environmentally conscious designs and technology to improve sustainability and promote conservation of natural resources.
A Phonetic-Level Analysis of Different Input Features for Articulatory Inversion

The challenge of articulatory inversion is to determine the temporal movement of the articulators from the speech waveform, or from acoustic-phonetic knowledge, e.g. derived from information about the linguistic content of the utterance. The actual position of the articulators is typically obtained from measured data, in our case position measurements obtained using EMA (Electromagnetic articulography). In this paper, we investigate the impact on articulatory inversion problem by using features derived from the acoustic waveform relative to using linguistic features related to the time aligned phone sequence of the utterance. Filterbank energies (FBE) are used as acoustic features, while phoneme identities and (binary) phonetic attributes are used as linguistic features. Experiments are performed on a speech corpus with synchronously recorded EMA measurements and employing a bidirectional long short-term memory (BLSTM) that estimates the articulators’ position. Acoustic FBE features performed better for vowel sounds. Phonetic features attained better results for nasal and fricative sounds except for /h/. Further improvements were obtained by combining FBE and linguistic features, which led to an average relative RMSE reduction of 9.8%, and a 3% relative improvement of the Pearson correlation coefficient.
Three Essays on Health Outcomes

A system and method are disclosed for providing a warning of, and greater immunity from, an impending call drop in a digital wireless telecommunications system. During normal operations, data is transmitted at an initial information frame rate and a corresponding initial physical frame rate. Upon the data transmission producing errors in excess of a threshold, which indicates an impending call drop, the initial information frame rate is reduced while error correction codes are introduced into the data transmission to maintain the initial physical frame rate. The reduction in the information frame rate produces a subtle yet noticeable change in acoustic voice quality, which serves as a warning of the impending call drop. The introduction of error correction codes into the transmission provides greater immunity to the impending call drop by improving data integrity.
Background Image Modelling for Change Detection

Change detection relative to a background image model is a potentially enabling capability for a variety of image analysis tasks, including automated video surveillance and monitoring. In this report, various combinations of chromatic, spatial and dynamic features are proposed and evaluated with reference to background modelling for image change detection. The features are embedded in a popular background modelling framework and empirically evaluated relative to each other as well as the state-of-theart on a standard, publicly available change detection dataset.
New vaccine introduction : strengthening health literacy to increase health equity

Introduction: The human papillomavirus (HPV) vaccine can reduce inequalities in cervical cancer. Countries introducing the vaccine need a strategy and communication plan that address the health literacy of target populations. Aim: To inform HPV vaccine introduction activities aiming to strengthen the health literacy of target groups, through exploring barriers and drivers, as well as seeking ideas for communicating the introduction of the vaccine. Methods: Qualitative studies using focus group discussions and in-depth interviews in Armenia, Georgia and the Republic of Moldova. The 218 participants were parents, teenage girls, doctors (family, school, specialist, paediatricians), nurses, oncologists, teachers and a priest. Data were analysed using thematic analysis. Findings: Many findings were similar across countries and target groups. The key driver was the recognition of the need for vaccines. Barriers ranged from confusion to fears related to adverse effects (including infertility), vaccines’ provenance and the quality of free vaccines. Health-care providers too were sceptical, susceptible to adverse information and willing to bend rules to avoid vaccination. Conclusion: The studies informed tailored strategies to strengthen HPV vaccination-related health literacy of key groups, by using tailored messages targeting misperceptions communicated through health-care providers and a community approach. Furthermore, the studies indicated more generally that increased decision-making power at an individual level creates uncertainty, which also affects health-care providers, who therefore need to be a target group in themselves and not just a channel of communication.
Demonstration of MLflow : A System to Accelerate the Machine Learning Lifecycle

Machine learning development creates new challenges that are not present in a traditional software development lifecycle. These include keeping track of the myriad inputs to an ML application (e.g., data versions, code and hyperparameters), reproducing results, and production deployment. Existing systems built to address these challenges restrict the supported programming languages and ML libraries that developers can use to train and deploy models, creating difficulties for organizations that must leverage a variety of ML libraries and model deployment environments. Accordingly, we propose to demonstrate MLflow: a system that streamlines the machine learning lifecycle and is designed to work with any ML library, algorithm, or programming language. Available at mlflow.org, MLflow is an open source project with over 70 contributors. Through our demonstration, audience members will interact with each of MLflow’s major components, experiencing firsthand how the platform’s open interface enables developers across an organization or research group to collaborate on reproducible machine learning workflows that leverage their preferred languages and ML libraries.
Characteristics of Bacillus Strains with Antifungal Activity against Phytopathogens

Four bacterial isolates that showed antifungal activity against Alternaria alternata and other phytopathogens were isolates from bean rhizosphere. 16S rDNA analysis and phylogenetic relationship indicated that these isolates belong to Genus Bacillus. Isolate A1 clustered with Bacillus licheniformis while other isolates A2, A3 and A4 clustered together with B. pumilus. n-Butanol extract of these isolates strongly inhibited the growth of A. alternata while, chloroform extract of isolate A2 and ethyl acetate extract of A1, A3, and A4 inhibited the test fungus partially. All the isolates except A4 produced chitinase enzyme. None of the isolates solubilized mineral phosphate. Radiation sensitivity of isolates A1, A2, A3 and A4 were assessed and the LD99 values are determined as 0.50, 6.69, 11.60, 1.53 kGy, respectively. Mutant libraries of each isolate were prepared by exposing them to gamma radiation at their respective LD99 dose. Crude metabolite caused drastic changes on A. alternata hyphal morphology. Appearance of shrunken and collapsed hyphae could be due to the leak of cell wall or changes in membrane permeability.