Miracle-dz/UniFAR-FTUs huggingface dataset:
The Right Music at the Right Time: Adaptive Personalized Playlists Based on Sequence Modeling

Recent years have seen a growing focus on automated personalized services, with music recommendations a particularly prominent domain for such contributions. However, while most prior work on music recommender systems has focused on preferences for songs and artists, a fundamental aspect of human music perception is that music is experienced in a temporal context and in sequence. Hence, listeners’ preferences also may be affected by the sequence in which songs are being played and the corresponding song transitions. Moreover, a listener’s sequential preferences may vary across circumstances, such as in response to different emotional or functional needs, so that different song sequences may be more satisfying at different times. It is therefore useful to develop methods that can learn and adapt to individuals’ sequential preferences in real time, so as to adapt to a listener’s contextual preferences during a listening session. Prior work on personalized playlists either considered batch learning from large historical data sets, attempted to learn preferences for songs or artists irrespective of the sequence in which they are played, or assumed that adaptation occurs over extended periods of time. Hence, this prior work did not aim to adapt to a listener’s current song and sequential preferences in real time, during a listening session. This paper develops and evaluates a novel framework for online learning of and adaptation to a listener’s current song and sequence preferences exclusively by interacting with the listener, during a listening session. We evaluate the framework using both real playlist datasets and an experiment with human listeners. The results establish that the framework effectively learns and adapts to a listeners’ transition preferences during a listening session, and that it yields a significantly better listener experience. Our research also establishes that future advances of online adaptation to listener’s temporal preferences is a valuable avenue for research, and suggests that similar benefits may be possible from exploring online learning of temporal preferences for other personalized services.
Bacteriological Analysis and Hygine Level of Food Outlets within Rufus Giwa Polytechnic, Owo, Ondo State, Nigeria

The bacteriological quality of three major food outlets in Rufus Giwa Polytechnic, Owo, was assessed using standard bacteriological methods. Swabs of hands of food vendors, table and plates in these outlets were assessed for total bacterial count, total coliform count and total E. coli count. A total of 789 bacterial colonies were isolated from hands of food handlers, tables and plates used for eating in the outlets. Eleven genera of bacteria were isolated and identified, they were; klebsiella sp, Enterobacter sp , Staphylococcus sp, Proteus sp, E. coli Salmonella sp, Micrococcus sp, Bacillus sp, Pseudomonas sp, Streptococcus sp and Serratia sp when their morphology and biochemical characteristics were compared with standard reference organisms. The presence of these bacterial isolates has been attributed to ineffective washing technique , rare changing of water used for washing plates and poor personal hygiene of the food handlers which could be enhanced by regular monitoring and supervision of the canteens by the authorities on food safety practices and regular education on food and personal hygiene.
Mixed-marker approach suggests maternal philopatry and sex-biased behaviours of narrow sawfish Anoxypristis cuspidata

The narrow sawfish Anoxypristis cuspidata belongs to the most endangered family of chondrichthyan fishes, the sawfishes (Pristidae). This species has undergone significant de - clines in geographic range and abundance due to anthropogenic activities including fishing and habitat destruction. Very little is known of adult movements within its distribution. In order to better manage and protect this endangered species, understanding patterns of habitat use, connectivity and behaviour is important. Using a combination of partial mitochondrial sequences (control region [CR] and NADH dehydrogenase 4 [ND4]) and nuclear markers (microsatellites), this study assessed the genetic population structure of A. cuspidata in Australia and Papua New Guinea. Significant population structuring using mitochondrial DNA was found between the east Australian coast, Gulf of Papua and Gulf of Carpentaria (using concatenated CR and ND4 markers) (analysis of molecular variance [AMOVA], Φ = 0.082, p = < 0.001). In contrast, no population structure was evident across northern Australia using nuclear microsatellite loci (F = 0.012, p = 1.000). Our results suggest that a combination of historic genetic drift, maternal natal philopatry and possible male-biased dispersal likely drive the genetic patterns observed. Given the endangered status and lack of knowledge for A. cuspidata, this study presents important insights that may be used to inform management efforts.
Separated Flows in Axial Flow Compressor With Variable Stator Vanes at Positive Incidence Angles

A detailed investigation of three-dimensional flow was carried out in a low speed rear axial compressor stage with the change of the stator blade row setting. The stator blade stagger change was in the range of (−14) – (23) degree. Measurements were performed by means of both stationary and rotating pressure probes at seven working points. The origin of large regions of separated flow in blade rows at positive incidence angles was analysed with the use of the spanwise diffusion factor distribution. These areas in the rotor and stator rows originated as the diffusion factor exceeded the critial value D = 0.6 within (1/4 – 1/3) of the blade height near one end-wall. The rotating stall in compressor stage arised when large regions of separated flow occured simultaneously in both rotor and stator blade rows.Copyright © 1994 by ASME
LCD SURFACE DEFECT INSPECTION USING MACHINE VISION

To promote product quality of TFT-LCD in mass manufacturing, development of an automatic defect inspection system to replace human inspection is required. In this paper, we use machine vision for automatic inspection and present several research results for TFT-LCD defects inspection and classification. For MURA defects inspection, Jiang et al. (2003) proposed to use ANOVA and EWMA control charts for detecting non-uniformity areas in a panel, and to design a weighted index mask matrix for MURA defects classification. For Micro defects, including pinholes, scratches, particles and fingerprints on the surface of TFT panels, Lu and Tasi (2004) proposed a global approach that uses an SVD-based image reconstruction technique. In the experiment, we have evaluated a variety defects including MURA, pinholes, scratches, particles and fingerprints on TFT panel surfaces, and the result reveals that the proposed methods are effective for LCD defects inspection.
Effect of Liquidity Management Practices on Profitability of Manufacturing Industry in Kenya

Industrial firms require liquid cash for smooth operations. Failure to convert current assets into liquid cash can force a profitable firm into liquidation. The purpose of this study was to determine the effect of liquidity management practices on profitability of industrial firms in Kenya. The study was explained by two cash management models; Baumol’s cash management model and Miller – Orr cash management model. Correlational research design was adopted. Two types of data were collected. Primary data was collected through the use of a questionnaire and secondary data through the use of a record survey sheet. Stratified random sampling technique was used to determine the sample size. Data analysis was through descriptive and inferential data analysis. The inferential data analysis, Pearson’s correlation, regression and ANOVA analysis were applied. The results of the analysis indicated that the correlation coefficient between liquidity cash management and profitability was 0.711 at 0.01 significant level. This showed a positive and significant relationship between liquidity management practices and profitability of industrial firms. R 2 value was 0.5055 which means that 50.55% of the corresponding variation in profitability can be explained by change in liquidity management practices. The rest 49.45% can be explained by other factors that are not in the model. The ANOVA results on liquidity management practices and profitability had an F-value of 90.677 which was significant with a P value = 0.000 meaning that the overall model was significant in the prediction of profitability in industrial firms in Kenya. It is recommended that the finance managers should establish optimal cash targets, lower and upper cash limits in their industrial firms. They should also invest excess cash into productive assets.
Occupation probability for acceptor in Al-implanted p-type 4H–SiC

Al-implanted p-type 4H–SiC layers with different implantation and annealing temperatures are formed, and the temperature dependence of the hole concentration p(T) is obtained by Hall-effect measurements. The Al acceptor level in SiC is deep (∼180 meV), and its first excited state level calculated by the hydrogenic model is still deep (∼35 meV), which is close to the acceptor level of B in Si. Therefore, in order to determine the reliable acceptor density (NA) from p(T), the Fermi–Dirac distribution function is not appropriate for Al acceptors in SiC, and a distribution function including the influence of the excited states of the Al acceptor is required. It is demonstrated that the proposed distribution function is suitable for obtaining the actual relationship between NA and p(T) in p-type 4H–SiC.
The effects of binaries on the evolution of UV spectral features in massive starbursts

In this paper we investigate the effects of binaries having an initial period between 1 day and 10 years on the theoretical simulation of the evolution of UV spectral features in massive starbursts. The binary evolutionary processes that dominate the evolution of the considered spectral features are the Roche lobe overflow in Case Br systems, the mass transfer rate and the merger rate. They cause UV spectral rejuvenation in starbursts that are older than 5 Myr.
Development of Humane Interpersonal Relationships.

The article reflects some theoretical aspects of humanization of interpersonal relationships in the sphere of education. The notion “humanization of interpersonal relationships” is being analyzed. The authors offer a characterization of some parameters of relationships: orientation, modality, valence, intensity, awareness, differentiation, complexity, level of development, width, emotionality, presence of mutual understanding, cognitive identification of the subjects of interaction with each other. Interpersonal relationships have various qualitative characteristics. We can define negative, indifferent and positive interpersonal relationships. According to the authors` comparative and descriptive position, negative type of interpersonal relationships corresponds to inhumane or egoistic interpersonal relationships, the indifferent type corresponds to neutral interpersonal relationships, and the positive type corresponds to humane interpersonal relationships. We show empiric results of our research of humane interpersonal relationships in the teaching staff of various educational establishments of the Russian Federation.
Structure of plankton communities in the Dogger Bank area (North Sea) during a stratified situation

Plankton dynamics and hydrography were invest~gated in the Dogger Bank area, southern North Sea, In May 1990 after the onset of stratification Greatest phytoplankton biomass and production rates were observed withln a subsurface maximum around the pycnochne. At all 51 stations investigated, fluorescence maxima were found at depths >l5 m and often at depths >30 m. Small flagellates (5 to 7 pm) dominated the phytoplankton. The vertical distributions of the smaller heterotrophs (bacteria, heterotrophic nanoflagellates and cihates) were closely related to the fluorescence distribution. Carbon budgets established for the southern North Sea suggest that, on and south of the Dogger Bank, ca 15 % of phytoplankton production was channelled directly into the larger zooplankton (copepods), while north of the Dogger Bank, ca 30 % was ingested by copepods. The production of the phytoplankton fraction >l 1 pm (i.e. potential copepod prey items) could not alone account for the daily carbon demand of the copepods. The carbon budgets suggest that ciliates could potentially have been of nutritional importance to the copepod populat~on. Calculations showed that copepods possessed the ability to clear a substantial fraction of ciliate production. The high biomass of bacteria, heterotroph~c flagellates and c~liates, as well as the fact that primary production of the larger (I.e. grazable) phytoplankton did not appear to be sufficient to meet copepod energy requirements, suggest the importance of the microbial loop in carbon cycling in the North Sea during the stratified period.
Multichannel quantum-defect theory for magnetic Feshbach resonances in heteronuclear group-I systems

We present a multichannel quantum-defect theory for magnetic Feshbach resonances in the interaction of two heteronuclear group I atoms. The theory provides a unified and a uniform description of resonances in all partial waves, and enables the characterization of large number of resonances in terms of very few parameters. For the sample system of $^6$Li$^{40}$K, we present descriptions of all resonances in $aa$, $ab$, and $ba$ channels, in partial waves $s$ ($l=0$) through $h$ ($l=5$), and in a magnetic field of 0 through 1000 Gauss. All resonances, including those in nonzero partial waves, are fully characterized using the newly developed parametrization of Gao [Phy. Rev. A \textbf{84}, 022706 (2011)].
Static force characterization with Fano anti-resonance in levitated optomechanics

We demonstrate a classical analogy to the Fano anti-resonance in levitated optomechanics by applying a DC electric field. Specifically, we experimentally tune the Fano parameter by applying a DC voltage from 0 kV to 10 kV on a nearby charged needle tip. We find consistent results across negative and positive needle voltages, with the Fano line-shape feature able to exist at both higher and lower frequencies than the fundamental oscillator frequency. We can use the Fano parameter to characterize our system to be sensitive to static interactions which are ever-present. Currently, we can distinguish a static Coulomb force of $2.7 \pm 0.5 \times 10^{-15}$ N with the Fano parameter for only one second of integration time. Furthermore, we are able to extract the charge to mass ratio of the trapped nanoparticle.
Fourier transform profilometry using a binary area modulation technique

Abstract. A recent study found that it is very difficult to use the squared binary defocusing technique to eliminate the influence of third-order harmonics without compromising fringe quality, and thus it is challenging to utilize Fourier transform profilometry to achieve high-quality three-dimensional measurement. A novel approach is presented to effectively eliminate the third-order harmonics by modulating the squared binary structured patterns. Both simulation and experiments are presented to verify the performance of the proposed technique.
MOTIVATIONAL SPECIFICITY IN THREAT-COMPENSATION: TESTING THE EFFECTS OF MORTALITY SALIENCE ON SELF-CONTROL By TREVOR JAMES SWANSON

Self-control is the mental function that allows people to actively suppress unwanted thoughts, emotions, and urges, as well as re-prioritize their goals in accordance with situational demands. However, self-control requires effort, and exerting effort can lead to mental fatigue—a state termed “ego depletion” (Inzlicht & Schmeichel, 2012). When self-control is depleted, people are less motivated to continue exerting effort, and increasingly motivated to pursue other more rewarding activities; satisfying these motives can, in turn, restore one’s capacity for self-control. The present research investigates the idea that the salience of certain psychological threats—such as the awareness of one’s mortality—can impose limits on the sorts of behaviors that people will be motivated to engage in after exerting self-control, and, by extension, what sorts of rewards will be sufficient for restoring mental resources. Across three studies, I draw from research on TMT and the shifting-priorities model of self-control to explore this hypothesis. I investigate whether specialized threat-compensatory motives for coping with the awareness of one’s mortality can constrain the types of rewards that serve to effectively counteract the ego depletion effect. The results of these studies did not support this hypothesis, but critical methodological issues arose that prevented a proper evaluation of its accuracy. These issues are explored further within the General Discussion. I then conclude with a brief overview of the potential neural mechanisms thought to undergird the regulation of self-control and the processing of motivationally salient reward-based stimuli.
Design of Smart Home Energy Management System for Saving Energy

The rapid change and development in human life, information technology, and the increase in using home gadgets, modern appliances, and electric cars, leads to more dependency on electrical resources and consecutive increase in CO2 emission from generation plant. The current world issue is on how to save the energy by reducing the consumption and decreasing global warming. In this research, Smart Home Energy Management System (SHEMS) has been developed to operate home appliances in an optimum approach. It is aimed at reducing the consumption energy by detecting the residents’ activity and identifying it among three states: Active, Away, or Sleep. The SHEMS is designed with an algorithm that is based on Hidden Markov Model (HMM) in order to estimate the probability of the home being in each of the above states. The proposed system uses the WiFi technology for data transmission inside home and the GSM technology for external communication. The proposed system and its algorithm was successfully tested and 18% of energy saving were obtained.
Characterization of Single Superphosphate Powders – a study of Milling Effects on Solubilization Kinetics

Conventional single superphosphate (SSP) is known as one of the most important and common sources of phosphorus in agriculture. Despite SSP has been widely produced as a fertilizer, a few studies have been done to describe the fundamental aspects of this P-fertilizer, i.e., phase composition, thermal degradation behavior, and solubility kinetics. Therefore, this paper reports on the detailed characterization of SSP powders by correlating their properties with particle size and surface area. Commercial SSP fertilizers were milled under different conditions and the resulting powders were characterized by X-ray diffraction, thermogravimetric analyses, scanning electron microscopy, FT-IR spectroscopy, and solubilization tests. It was observed that short milling times favored the solubilization kinetics, whereas long milling times were deleterious due to agglomeration effects. It was pointed out that agglomeration plays an important role in phosphate availability. These results provided a deeper understanding of SSP powders in microstructural terms, and may be used as a foundation for the development of novel strategies of alternative production of phosphorus fertilizers.
Algorithmic composer, an unconventional music classification system

Music is an inherent part of the human existence. As an art, it has mirrored its evolution and captured its thinking and creative process over the years. Given its importance and complexity, machine learning has long embraced the challenge of analyzing music, mainly through recommendation systems, classification and composition tasks. Current classification systems work on the base of feature extraction and analysis. The same applies for music classification algorithms, which require the formulation of characteristics of the songs. Such characteristics can be of varying degrees of complexity, from spectrogram analysis to simpler rhythmic and melodic features. However, finding characteristics to faithfully describe music is not only conceptually hard, but mainly too simplistic and restrictive given its complex nature. A new methodology for music classification systems is proposed in this thesis, which aims to show that the knowledge learned by state of the art composition systems can be used for classification, without need for direct feature extraction. Using an architecture of recurrent neural networks (RNN) and long-short term memory cells (LSTMs) for the composition systems and implementing a voting scheme between them, the classification accuracy of the experiments between classes of the Nottingham dataset ranged between 60% and 95%. These results provide strong evidence that composition systems do indeed possess valuable information to distinguish between classes of music. They also prove that an alternative method to standard classification is possible, as classification targets are not directly used for training. Finally, the extent to which these results can be used for other applications is discussed, namely its added value to more complex classification systems, as well as to recommendation systems.
MMPM: a Generic Platform for Case-Based Planning Research

Computer games are excellent domains for the evaluation of AI and CBR techniques. The main drawback is the big effort needed to connect AI systems to existing games. This paper presents MMPM, a middleware that supports the connection of AI techniques with games. We will describe the features of MMPM, and compare with related systems such as TIELT.
ANTICONVULSANT ACTIVITY OF METHANOLIC EXTRACT OF MELISSA PARVIFLORA IN EXPERIMENTALLY INDUCEDSWISS ALBINO MICE

Epilepsy is a disorder characterized by recurrent seizures of cerebral origin, presenting with episodes of sensory, motor or autonomic phenomenon with or without loss of consciousness. In the present study, anticonvulsant activity of methanolic extract of Melissa parviflora (MP) was evaluated against maximal electroshock (MES) and Pentylenetetrazol (PTZ) induced convulsions in Swiss Albino Mice. The extract showed substantial suppressed hind limb tonic extensions (HLTE) induced by MES and also exhibited protective effect in PTZ-induced seizures. In conclusion, the results of methanolic extract of MP show anticonvulsant effect in both the models, and suggesting their possible depressant action in the central nervous system.