Miracle-dz/UniFAR-FTUs huggingface dataset:
Emotion Classification of Song Lyrics using Bidirectional LSTM Method with GloVe Word Representation Weighting

The rapid change of the music market from analog to digital has caused a rapid increase in the amount of music that is spread throughout the world as well because music is easier to make and sell. The amount of music available has changed the way people find music, one of which is based on the emotion of the song. The existence of music emotion recognition and recommendation helps music listeners find songs in accordance with their emotions. Therefore, the classification of emotions is needed to determine the emotions of a song. The emotional classification of a song is largely based on feature extraction and learning from the available data sets. Various learning algorithms have been used to classify song emotions and produce different accuracy. In this study, the Bidirectional Long-short Term Memory (Bi-LSTM) deep learning method with weighting words using GloVe is used to classify the song's emotions using the lyrics of the song. The result shows that the Bi-LSTM model with dropout layer and activity regularization can produce an accuracy of 91.08%. Dropout, activity regularization and learning rate decay parameters can reduce the difference between training loss and validation loss by 0.15.
Technical Note: Estimation of global loss of freshwater based on sea level changes over geological time

Abstract. Water vapour at the upper layer of the atmosphere undergoes light-dependent photolysis generating reactive hydrogen ions in statu nascendi that escape to space by different mechanisms. Besides hydrogen, other volatile gases such as methane molecules and helium atoms also escape to space in smaller quantities or traces such as oxygen. The escape of hydrogen through the planetary air leak cannot be reliably judged. Our estimation of global freshwater loss used another approach based on the sea-level changes that continuously fluctuated over geological time. The most reliable evidence for eustatic sea-level changes was provided by geologists estimating the shifts of shorelines generating sedimentary deposits. The sea-level changes turned to volumetric used data of a) radii of the Earth (r1) to calculate the volume of the geoid Earth (V1) comparing and validating them with available estimations, b) average sea depth (r2) comparing volumetric values of the sea with best-fitting values (V2). c) showing the correlation between geological changes (r3) and corresponding sea volumes (V3). These data, along with the sea volume of the infant Earth, allowed to plot a calibration curve to calculate the sea level belonging to the volume and vice versa. Geologic data indicate the shrinkage of freshwater pools during interglacial dilution periods and the remarkable long-term salination of the ocean.
DATA CO-ORDINATION OF SEMANTIC SUPERVISING IN P2P DATABASE SYSTEM

The peer-to-peer database management System (P2PDBMS) runs to the high level of the standard database management system, to connect its database with other peer databases on the network. The P2PDBMS are completely independent in which no central server (or) any other centralization are not present. Peers are mostly independent from other peers and they interoperate in a local point-point links. Peer-to-peer is a decentralized model where each peer has equivalent abilities providing the data (or) services to other peers. Each peer manages its own data. In this paper P2P system, we will have some new idea to contribute the databases through a number of techniques for semantic based data modeling, Query management, and update processing and data coordination mechanism. We allow peer to specify Coordination formula to explain how the data which is in one peer should relate to data in an acquaintances. In effective P2P databases, the data placement and data Coordination plays an important role. The data placement is to distribute data among peers so that queries can be executed. The data Coordination will have the ability of peers to manage at runtime semantic interdependence in a decentralized and distributed manner among databases. The main focus of the proposed work is the adaptive techniques for development of a databases management system compatible with the P2P paradigm.
Self-nanoemulsifying Delivery of Andrographolide: Ameliorating Islet Beta Cells and Inhibiting Adipocyte Differentiation

Purpose: Insulin resistance is a characteristic of non-insulin-dependent diabetes mellitus associated with obesity and caused by the failure of pancreatic beta cells to secrete sufficient amount of insulin. Andrographolide (AND) improves beta-cell reconstruction and inhibits fat-cell formation. This research aimed to improve the delivery of water-insoluble AND in self-nanoemulsifying (ASNE) formulation, tested in streptozotocin (STZ)-induced diabetic rats and 3T3-L1 preadipocyte cells. Methods: A conventional formulation of AND in suspension was used as a control. The experimental rats were orally administered with self-nanoemulsifying (SNE) and suspension of AND for 8 days. Measurements were performed to evaluate blood glucose levels in preprandial and postprandial conditions. Immunohistochemistry was used to assess the process of islet beta cell reconstruction. In vitro study was performed using cell viability and adipocyte differentiation assay to determine the delivery of AND in the formulation. Results: ASNE lowered blood glucose levels (day 4) faster than AND suspension (day 6). The histological testing showed that ASNE could regenerate pancreatic beta cells. Therefore, ASNE ameliorated pancreatic beta cells. The in vitro evaluation indicated the inhibition of adipocyte differentiation by both AND and ASNE, which occurred in a time-dependent manner. ASNE formulation had better delivery than AND. Conclusion: ASNE could improve the antidiabetic activity by lowering blood glucose levels, enhancing pancreatic beta cells, and inhibiting lipid formation in adipocyte cells.
Study on Developing Regional Grid-Based Geoid Model Using GPS and Leveling Data

The height difference between the geodetic height h and the orthometric height H is called undulation N. The key issue of transforming the GPS height is to determine the undulation value accurately. If the undulation N for a point determined by a GPS receiver can be estimated in the field, then the 3-D geocentric coordinate in WGS-84 can be transformed to local coordinate system and orthometric height in real-time. In this paper an algorithm to develop a regional grid-based geoid model using GPS data (e.g. ellipsoidal height) and the spiritual leveling data (e.g. orthometric height) is proposed. In brief, the proposed algorithm includes the following steps: (1) establishing the functional relationship between the point’s plane coordinates (such as Northing and Easting) and the undulation (N) using back-propagation artificial neural network according to the measured GPS data and leveling data; (2) developing a regional grid-based geoid (undulation) model using the simulated grid plane coordinates with constant grid interval (e.g. 1500 m) and the generated functional relationship from step 1; (3) developing an undulation interpolation algorithm using the grid-based geoid model given a point’s plane coordinates, and developing a computer program according this algorithm, then transforming this program to a pocket PC; (4) estimating the interested point’s undulation in the field using the pocket PC and transforming the GPS height to orthometric height in real-time. Data from a series of 2,065 first-order bench marks (including GPS and leveling) around Taiwan are used to test the proposed algorithm. The test results show that the GPS height transformation accuracy using the grid-based geoid is on the order of 4 cm. The proposed algorithm and the detailed test results will be presented in this paper.
R4-B.2: Multi-Energy, Limited-View Computed Tomography

The development of new scanning technologies by Rapiscan Systems has led to the analysis of novel integral transforms and inversion methods in Bragg Scattering Tomography (BST) and Compton Scattering Tomography (CST). The advances made by the teams at Tufts and Rapiscan Systems this year lay the groundwork for better material characterizations and for modification of the currently employed threat detection algorithms, with the ultimate goal to improve the false alarm rates.
R2D2: Accounting for temporal dependences in multivariate bias correction via analogue ranks resampling

Abstract. Over the last few years, multivariate bias correction methods have been developed to adjust spatial and/or inter-variable dependence properties of climate simulations. Most of them do not correct – and sometimes even degrade – the associated temporal features. Here, we propose a multivariate method to adjust the spatial and/or inter-variable properties while also accounting for the temporal dependence, such as autocorrelations. Our method consists in an extension of a previously developed approach that relies on an analogue-based method applied to the ranks of the time series to be corrected, rather than applied to their ``raw’’ values. Several configurations are tested and compared on daily temperature and precipitation simulations over Europe from one Earth System Model. Those differ by the conditioning information used to compute the analogues, and can include multiple variables at each given time, a univariate variable lagged over several time steps, or both – multiple variables lagged over time steps. Compared to the initial approach, results of the multivariate corrections show that, while the spatial and inter-variable correlations are still satisfactorily corrected even when increasing the dimension of the conditioning, the temporal autocorrelations are improved with some of the tested configurations of this extension. A major result is also that the choice of the information to condition the analogues is key since it partially drives the capability of the proposed method to reconstruct proper multivariate dependencies.
ArticleProteome Cold-Shock Response in the Extremely Acidophilic Archaeon

The archaeon Cuniculiplasma divulgatum is ubiquitous in acidic environments with lowto-moderate temperatures. However, molecular mechanisms underlying its ability to thrive at lower temperatures remain unexplored. Using mass spectrometry (MS)-based proteomics, we analysed the effect of short-term (3 h) exposure to cold. The C. divulgatum genome encodes 2016 protein-coding genes, from which 819 proteins were identified in the cells grown under optimal conditions. In line with the peptidolytic lifestyle of C. divulgatum, its intracellular proteome revealed the abundance of proteases, ABC transporters and cytochrome C oxidase. From 747 quantifiable polypeptides, the levels of 582 proteins showed no change after the cold shock, whereas 104 proteins were upregulated suggesting that they might be contributing to cold adaptation. The highest increase in expression appeared in low-abundance (0.001–0.005 fmol%) proteins for polypeptides’ hydrolysis (metaldependent hydrolase), oxidation of amino acids (FAD-dependent oxidoreductase), pyrimidine biosynthesis (aspartate carbamoyltransferase regulatory chain proteins), citrate cycle (2-oxoacid ferredoxin oxidoreductase) and ATP production (V type ATP synthase). Importantly, the cold shock induced a substantial increase (6% and 9%) in expression of the most-abundant proteins, thermosome beta subunit and glutamate dehydrogenase. This study has outlined potential mechanisms of environmental fitness of Cuniculiplasma spp. allowing them to colonise acidic settings at low/moderate temperatures.
Dynamic contrast-enhanced near-infrared spectroscopy using indocyanine green on moderate and severe traumatic brain injury: a prospective observational study.

Background The care given to moderate and severe traumatic brain injury (TBI) patients may be hampered by the inability to tailor their treatments according to their neurological status. Contrast-enhanced near-infrared spectroscopy (NIRS) with indocyanine green (ICG) could be a suitable neuromonitoring tool. Methods Monitoring the effective attenuation coefficients (EAC), we compared the ICG kinetics between five TBI and five extracranial trauma patients, following a venous-injection of 5 mL of 1 mg/mL ICG, using two commercially available NIRS devices. Results A significantly slower passage of the dye through the brain of the TBI group was observed in two parameters related to the first ICG inflow into the brain (P=0.04; P=0.01). This is likely related to the reduction of cerebral perfusion following TBI. Significant changes in ICG optical properties minutes after injection (P=0.04) were registered. The acquisition of valid optical data in a clinical environment was challenging. Conclusions Future research should analyze abnormalities in the ICG kinetic following brain trauma, test how these values can enhance care in TBI, and adapt the current optical devices to clinical settings. Also, studies on the pattern in changes of ICG optical properties after venous injection can improve the accuracy of the values detected.
Modeling Rainfall Runoff Relations at Arid Catchments Using Conceptual Hydrological Modeling Approach

Objective: To develop a simple deterministic lumped conceptual rainfall-runoff model. Methods/statistical analysis: This study developed a model based on the water balance, in which the model tracks precipitation, simulated soil water content, surface runoff, evapotranspiration, percolation, and return streamflow. The major input requirements for this model are hourly rainfall, hourly potential evaporation and the average daily streamflow record. The model is calibrated and tested using the available data collected from only one semi-arid ephemeral catchment located in the central part of Jordan. The model was optimized using Shuffle Complex Evolution (SCE.UA) optimization method. The performance of the model was evaluated using the goodness of fit measures. Findings: The simulation results obtained show that the proposed model has a good match between observed and simulated streamflow for both optimization and validation stages. Application/improvements: The good simulation results obtained indicate that the model will be useful in design of hydraulic structures and for effective management of water resources at arid and semi-arid catchments. In order to strengthen the validation and applicability of the proposed model, empirical research needs to be conducted. Further research is required to assess the predictive uncertainty associated with model parameters and other inputs. Keywords: Hydrological Modeling, Rainfall-Runoff Relation, Streamflow Forecasting, Conceptual Model, Arid Catchments.
ZigBee-based Parameter Monitoring and Controlling Scheme for Multiple DC Motors

Objective/aim: This study suggests a safe and economical wireless control and monitoring system for multiple DC motors based on ZigBee wireless communication. Methods: A set of sensors is used to control and monitor the information regarding the multiple DC motors parameters such as voltage, speed, temperature, and over-current and then transmit this information through the wireless ZigBee Protocol. A microcontroller is used for information collection and storage. According to monitored information, the DC motor will be stopped or started by the control signal via the computer interface produced with ZigBee when a certain condition is accomplished. Findings: The developed system can perform various operations like the automatic on/off of multiple DC motors, forward & reverse, speed control, checking overload condition, current measuring, and voltage measuring. The parameters: voltage, current, temperature, revolution per minute (RPM) can be detected in real-time by sensors and transferred to the host computer, displayed and store in an excel file. A ZigBee device is used to receive and transmit data efficiently from microcontroller to the PC and vice versa. In the past, similar systems were used for a single DC motor which was expensive such as PLC and Wi-Fi. In this work, a cost-effective ZigBee-based system is used for multiple DC motors. Applications/improvements: The proposed system can be further improved and modified for the real-time measuring system for AC machines. Moreover, the proposed wireless monitoring system can be enhanced with artificial intelligence. Keyword: DC Motor, Wireless Control and ZigBee Module, Microcontroller, Monitoring System. Article Type: Article Article Citation: Naqeeb Ullah, Muhammad Shakeel Akram, Hameed Ullah Buzdar, Atiq Ur Rehman, Muhammad Abbas Khan, Saifullah Khan. ZigBee-based parameter monitoring and controlling scheme for multiple DC motors. Indian Journal of Science and Technology. 2020; 13(06), 725-734. DOI: 10.17485/ijst/2020/ v013i06/149098 Received date: November 22, 2019 Accepted date: January 24, 2020 *Author for correspondence: Muhammad Abbas Khan @ Muhammad.Abbas@buitms.edu. pk Faculty of Information and Communication Technology, Balochistan University of Information Technology, Engineering and Management Sciences (BUITEMS), Quetta, Pakistan ZigBee-based Parameter Monitoring and Controlling Scheme for Multiple DC Motors 726 / 734 Indian Journal of Science and Technology Vol 13(06), DOI: 10.17485/ijst/2020/v13i06/149098, February 2020
The Effect of Supplement of Rare Earth on the Digestion and Metabolism of Sheep

In this experiment,4 of Small Tail Han ewes with the body weight of 55 kg,were fitted with the permanent duodenum and ileum canula,fed with the diet consisted of 50% corn stalk,and were supplied with rare earth at the dose of 0(control) and 216.5 mg/kg ration,to study the effect of supplement of rare earth on the digestion and metabolism of sheep.The results showed that the supplement of rare earth increased the voluntary intake of sheep by 7.4%-13.0%;increased the digested amounts of DM,OM,cellulose and semi-cellulose in forestomach by 5.61%(P0.05),6.41%(P0.05),30.09%(P0.01) and 27.73%(P0.01) respectively;increased the amounts of the DM,OM,CP,microprotein,by-pass protein,total amino acids and lysine arriving at small intestine by 22.40%(P0.01),22.40%(P0.01),23.56%(P0.01),34.32%(P0.01),8.19%(P0.05),17.41%(P0.05) and 17.30%(P0.01) respectively;increased the amounts of the DM,OM,CP,total amino acids and lysine absorbed in small intestine by 37.42%(P0.05),41.79%(P0.05),37.43%(P0.05),18.96%(P0.05) and 12.11%(P0.05) respectively;increased the retention of the nitrogen,calcium and phosphorous by 27.04%(P0.05),40.00%(P0.05) and 39.44%(P0.05) respectively.It is concluded that supplement of rare earth may increase the intake,the digestibility of the diet in forestomach,and the absorbed nutrients,especially amino acids,in small intestine,therefore would significantly improve the nutritional status of the sheep.
Tautomerism in Fuscin - A DFT Treatment

Fuscin, a natural product having various functionalities, may exhibit 1,3- and 1,5-proton tautomerism, as well as valence tautomerism via its 1,5-proton tautomer. All those possible forms are investigated within the realm of density functional theory with the constraints of B3LYP/6-311+G(d,p) level. NICS(0) calculation has been performed for the valence tautomer which possesses a benzenoid ring. The tautomers are found to be stable structures but the valence tautomer is the least likely one. Some QSAR, quantum chemical and spectral properties are obtained and discussed.
Bulky chemical modifications of siRNAs impair interaction with the SIDT2 endosomal RNA transporter

Since the discovery of RNA interference (RNAi), substantial efforts have been made to develop RNAi therapeutics for human disease. However, despite ~50 clinical trials involving short interfering RNAs (siRNAs), only a single RNAi therapeutics has been approved for clinical use. This lack of success is largely due to a common problem: namely, ineffective endosomal escape. Achieving safe and effective cytosolic delivery of siRNAs remains the key technological obstacle in the design of RNAi therapeutics and solving this challenge has the potential to improve treatments for a diversity of diseases, including various cancers, infections, and genetic disorders. The ubiquitously expressed endo-lysosomal protein SIDT2 specifically recognizes and transports viral double-stranded RNA (dsRNA) from endosomes into the cytosol to mediate innate immune recognition. Here, we show that SIDT2 also interacts with siRNA, suggesting that SIDT2 similarly mediates endosomal escape of siRNA. Moreover, we find that this interaction with SIDT2 is disrupted by bulky chemical modifications of the siRNA (e.g. phosphothiorate, 2′-O-methyl) that are commonly used to improve RNA therapeutic stability, immunogenicity, and off-target effects. In this way, such modifications might be inadvertently contributing to ineffective endosomal escape, and we suggest that the success of future RNAi-based treatments would be improved if SIDT2-mediated endosomal escape is optimized.
Enhanced Design Pattern Definition Language

—Design patterns are abstract descriptions of object-oriented designs, which appear repeatedly for a possible high-quality solution. Many design pattern description languages have been proposed. These languages use a combination of a natural language, UML-style diagrams, complex mathematical or logic based formalisms, or eXtensible Markup Language (XML). In this paper, we propose an extension to the Design Pattern Description Language (DPDL), which is based on XML to support composite design patterns. A composite pattern is a special type of design patterns that is formed from a composition of other patterns. Composite patterns capture the synergy arising from the different roles an object plays in the overall composition structure. The enhanced Design Pattern Description Language (eDPDL) is found to be effective in capturing the composite design pattern while representing the whole composite design pattern in a single description.
Impact of Work-Family Interface on Job Satisfaction of Teachers-The Mediating Role of Perceived Organizational Support

Work-family balance or conflicts has considerable impact on job satisfaction, and the perceived organizational support of employees plays a decisive role in determining the degree of the impact. Through questionnaire surveys, this study distributed among teachers in off-campus training schools 400 questionnaires, 358 of which were collected and deemed effective. The survey results show that except emotional support, other factors including work-family conflicts, instrumental support and supervisor support have significant positive correlation to the respondents’ job satisfaction; work-family enrichment, instrumental support, and supervisor support have significant positive correlation to job satisfaction; both instrumental support and supervisor support play a mediating role in the impact of all sub-factors of work-family interface on job satisfaction, while emotional support does not. Moreover, the job demands-resources model and the organization theory are employed to analyze the research results.