Miracle-dz/UniFAR-FTUs huggingface dataset:
Usage of Deep Learning and Blockchain in Compilation and Copyright Protection of Digital Music

In order to explore the application of deep learning algorithms in arrangement and composition, and the role of blockchain in the protection of digital music copyright, a monophonic melody composition model based on the deep generative adversarial networks (DCGANs) is constructed firstly, and the composition performance of the model is analyzed using hymn as input sample in this study. Later, the multi-instrument co-arrangement (MICA) model based on the multi-task learning is proposed, and the composition performance is analyzed by taking the actual music as an input sample. Finally, the improved practical byzantine fault tolerance (IPBFT) algorithm is proposed, and a digital music copyright protection system is designed based on the blockchain in this study. The results indicate that the accuracies constructed DCGANs model in predicting the Soprano and Alto voice melody are higher than those of the DeepBatch model by 2.29% and 3.32%, respectively. The performance on the harmony score, note accuracy, levenshtein similarity (LS), notes distribution mean square error, and empty as well as the convergence speed of the constructed MICA model are better than those of other models. The average transaction per second (TPS) value of the proposed IPBFT algorithm in the real digital music copyright protection system is 3469, which is superior to other blockchain technologies. Finally, the digital music copyright protection system is achieved, the error rate of completing the request is 0% in the state of many users operating concurrently, and a high TPS value can be guaranteed. In short, the DCGANs and MICA models pointed out in this study can be used in the composition of monophonic melodies and complex melodies, and the digital music copyright protection system based on the blockchain has excellent performance in practical applications.
Evaluating Multivariable Statistical Methods for Downscaling Nighttime Land Surface Temperature in Urban Areas

For research and practice in fields such as the environment and meteorology, nighttime land surface temperature (LST) images at fine resolution provide important basic data. Since only a few satellite sensors can take fine-resolution thermal infrared images at night, such images are rather scarce. Downscaling of coarse-resolution LST images is a potential method for obtaining high-resolution LST images. However, downscaling methods have been mostly proposed for daytime LST images. This study aimed to evaluate the performance of methods that combine multiple explanatory variables and machine learning algorithms for downscaling coarse-resolution nighttime LST images in urban areas. Verification showed that the errors in the downscaling results were acceptable (mean absolute errors within 2 K). The resulting images could depict the spatial pattern of night LST in the study area in great detail. It was demonstrated that visible-near infrared images taken in the daytime could be used for downscaling of nighttime LST images, the rationality of which was deduced. It was also demonstrated that the performance of the spectral explanatory variables in nighttime LST downscaling was not lower than that of the mechanism explanatory variables. This method has high application value in many academic and practical efforts, such as land-atmosphere interface radiation budget studies, suitability assessments of human settlement, and urban environmental planning.
Long Short-Term Memory Approach to Estimate Battery Remaining Useful Life Using Partial Data

Due to the increasing demand of electrical vehicles (EVs), prognostics of the battery state is of paramount importance. The nonlinearity of the signal (e.g. voltage) results in the complexity of analyzing the degradation of the battery. Aging characteristics extracted from the voltage, current, and temperature when the battery is fully charged/discharged were commonly used by previous researchers to determine the battery state. The drawbacks of the previous prediction algorithms are insufficient or irrelevant features to explicitly model the battery aging and the use of fully charged/discharged datasets, which might result in poor prediction accuracy. Therefore, this study proposes a feature selection technique to adequately select optimum statistical feature subset and the use of partial charge/discharge data to determine the battery remaining useful life (RUL) using Recurrent Neural Network – Long Short-Term Memory (RNN-LSTM). The proposed approach demonstrated exceptional RUL prediction results, with the root mean square error (RMSE) of 0.00286 and mean average error (MAE) of 0.00222 using partial discharge data. The proposed method shows prediction improvement in comparison with the use of full data and state-of-the-art outcomes from previous studies of the same open data from the National Aeronautics and Space Administration (NASA) prognostic battery data sets.
Muscle and Brain Activations in Cylindrical Rotary Controller Manipulation with Index Finger and Thumb

This study aim to confirm the effect of viscosity characteristics differences on the rotational manipulation of a cylindrical rotary controller with the index finger and thumb through a quantitative analysis and evaluation of muscle and brain activations. The target motion was a rotary manipulation with the index finger and thumb of a cylindrical rotary controller with a 50 mm diameter. The rotary motion of the controller produces a click sensation at every 12 degrees in the rotation. The experimental conditions were three conditions with different viscosity characteristics related to the rotary motion of the controller. The subjects were six right-handed healthy males with a mean age of 21.7 (S. D.: 1.03) years. We analyzed the brain activity from a near– infrared spectroscopy measurement system, the muscles activity using a surface myoelectric potential measurement device, the force data at the index finger and thumb tip using two independent six-axis force/torque sensors, and the position data using a 3D position measurement device. The experimental results showed that there was no significant difference in the questionnaire survey, muscle activity, and grasping force, respectively; however, a significant difference in brain activity was observed with increased controller viscosity. Therefore, it became clear that there was a change in the brain activity when rotating the cylindrical rotary controller with the viscosity characteristics related to the rotary motion.
TON_IoT Telemetry Dataset: A New Generation Dataset of IoT and IIoT for Data-Driven Intrusion Detection Systems

Although the Internet of Things (IoT) can increase efficiency and productivity through intelligent and remote management, it also increases the risk of cyber-attacks. The potential threats to IoT applications and the need to reduce risk have recently become an interesting research topic. It is crucial that effective Intrusion Detection Systems (IDSs) tailored to IoT applications be developed. Such IDSs require an updated and representative IoT dataset for training and evaluation. However, there is a lack of benchmark IoT and IIoT datasets for assessing IDSs-enabled IoT systems. This paper addresses this issue and proposes a new data-driven IoT/IIoT dataset with the ground truth that incorporates a label feature indicating normal and attack classes, as well as a type feature indicating the sub-classes of attacks targeting IoT/IIoT applications for multi-classification problems. The proposed dataset, which is named TON_IoT, includes Telemetry data of IoT/IIoT services, as well as Operating Systems logs and Network traffic of IoT network, collected from a realistic representation of a medium-scale network at the Cyber Range and IoT Labs at the UNSW Canberra (Australia). This paper also describes the proposed dataset of the Telemetry data of IoT/IIoT services and their characteristics. TON_IoT has various advantages that are currently lacking in the state-of-the-art datasets: i) it has various normal and attack events for different IoT/IIoT services, and ii) it includes heterogeneous data sources. We evaluated the performance of several popular Machine Learning (ML) methods and a Deep Learning model in both binary and multi-class classification problems for intrusion detection purposes using the proposed Telemetry dataset.
A Simple Three-Level Switching Architecture to Enhance the Power Delivery Duration of Supercapacitor Banks in Electrified Transportation

Hybridization of supercapacitors (SCs) with batteries in electric vehicular applications improves battery life, acceleration, and driving range. However, the efficiency of the power electronic interface that unites batteries and SCs is affected due to wide voltage variations at the SC bank terminals. Moreover, the SCs in a bank offer low storage capacity that restricts them from serving a series of transients on a single charge. This article aims at improving the power delivery duration and energy utilization of SCs with controlled terminal voltage variations using a new bank switching configuration. A simple three-level transition control scheme is implemented for charge and discharge of the SC bank. The effectiveness of the proposed topology is validated using PLECS simulations and experimental studies on a laboratory-developed prototype. Furthermore, the suitability of the proposed SC bank in a hybrid energy storage system (HESS) for an electric vehicle is verified in accordance with varying load demands. The superiority of the proposed architecture is shown in terms of the SC bank voltage variations and depth of discharge under standard urban and highway drive cycles.
Quantum Enhancements for Deep Reinforcement Learning in Large Spaces

In the past decade, the field of quantum machine learning has drawn significant attention due to the prospect of bringing genuine computational advantages to now widespread algorithmic methods. However, not all domains of machine learning have benefited equally from quantum enhancements. Notably, deep learning and reinforcement learning, despite their tremendous success in the classical domain, both individually and combined, remain relatively unaddressed by the quantum community. Arguably, one reason behind this is the systematic use in these domains of models and methods without prominent computational bottlenecks, leaving little room for quantum improvements. In this work, we study the state-of-the-art neural-network approaches for reinforcement learning with quantum enhancements in mind. We demonstrate the substantial learning advantage that models with a sampling bottleneck can provide over conventional neural network architectures in complex learning environments. These so-called energy-based models, like deep energy-based reinforcement learning, and deep projective simulation that we also introduce in this work, effectively allow to trade off learning performance for efficiency of computation. To alleviate the additional computational costs, we propose to leverage future and near-term quantum algorithms, resulting in overall more advantageous learning algorithms. This is achieved using cutting-edge and new quantum computing machinery to speed-up classical sampling methods and by employing generalized models to gain an additional quantum advantage.
Study on the Effects of Ultrasonic Wave on Hatching of Fertilized Egg in Four Marine Fish

Effects of fixed frequency and intensity ultrasonic waves, with different radiation duration and times, on hatching of fertilized egg in Boleophthalmus pectinirostris (Linnaeus), Bostrichthys sinensis (Lacepede), Pagrosomus major (Temminck et Schlegel) and Pseudosciaena crocea (Richardson) were investigated. The results showed that ultrasonic radiation increased hatching rates of Boleophthalmus pectinirostris fertilized eggs for late developmental embryos, but it had negative effects on the hatching of Boleophthalmus pectinirostris and Bostrichthys sinensis fertilized eggs for early developmental embryos. Ultrasonic radiation, in 1 minute each time and 4 times total, was favorable to the hatching of Pagrosomus major fertilized eggs, whereas the hatching rates decreased if the radiation treatment duration was over 1 minute each time. Hatching rates of Pseudosciaena crocea fertilized eggs, treated with ultrasonic radiation in 10 s or 30 s each time, were 10% or 12% higher than that of the control.
Health hazards of environmental cadmium pollution.

Cadmium, a metal widely used in industrial processes, has been recognized to be a highly toxic and dangerous environmental pollutant. In this article the author describes the sources and occurrence of cadmium, and the intake by human beings. He states that present standards for daily intake do not allow sufficient safety margins. The fate and known effects of cadmium in human beings are summarized; some effects associated with cadmium are renal (kidney) damage, anemia, hypertension, and liver damage. Cadmium was identified as the main cause of the Itai-ltai disease in Japan, and epidemiological studies from various areas of Japan are presented.
Ultrastructure of the flight muscle of female adults in the gregarious phase and solitary phase of the oriental migratory locust,Locusta migratoria manilensis (Meyen) (Orthoptera:Acrididae)

The electron microscope examination of ultrastructure of flight muscle of female adults in both gregarious and solitary phases of the oriental migratory locust, Locusta migratoria manilensis (Meyen) was performed. The results show that 7 days after emergence, the adults of both phases have the similar structures of indirect flight muscle, where the thick and thin filaments form a hexagonal lattice with myosin and actin in the ratio of 1∶3. The development of flight muscle and formation of mitochondrion are gradually changeable process with differences between the different day-old adults. The sarcomere length (2.1-3.4 μm) of 7 or 10 day-old adults in the gregarious phase is shorter than that in the homologous solitary phase. The myofibril diameter of 7 day-old adults in the gregarious phase is thicker than that in the solitary phase. The mitochondrion displays some shapes in the early adult period and grows daily. The mitochondrion content in myofibril is 20%-43%, which are different between the phases: 42.96% in 7 day-old adults of the gregarious phase and 22.45% in those of the solitary phase; 41.32% in 10 day-old adults of the gregarious phase and 29.98% in those of the solitary phase. It is inferred that the above differences in sarcomere length, myofibril diameter and mitochondrion content in flight muscle may contribute to different flight abilities in the two phases of L. migratoria manilensis adults, of which those in the gregarious phase can migrate for longer distance.
Seed quality in relation to fruit maturation and seed dry weight during development in tomato

Variation in seed quality during maturation was determined in tomato (Lycopersicon esculentum Mill.) in two subsequent years in order to relate to changes in seed dry weight and fruit maturity. Seed quality was assessed by germination at low (15, 18°C) and high (35°C) temperatures, germination at low water potential (-0.5 Mpa), emergence percentage and seed quality constant (Ki). Seed dry weight did not change between 60 and 90 and 50 and 80 Days After Anthesis (DAA) in 1998 and 1999, respectively. Whereas, seeds harvested 70 DAA attained not only maximum germination under stress conditions but also maximum emergence and Ki values in both years. Delayed harvests (80, 90 DAA) caused decline in seed quality. Results showed that occurrence of maximum tomato seed quality is related to changes in fruit colour but not in seed dry weight.
Access to multiple mates increases fecundity but does not affect per‐offspring maternal investment in a marine gastropod

Females of many organisms mate more than once and with more than one male, suggesting that polyandry confers some advantage to the female or her offspring. However, variation in maternal investment in response to mate choice and mate number can confound efforts to determine if there are benefits of polyandry. Access to multiple mates could increase maternal investment in offspring via a number of different mechanisms. Few studies have determined if investment is influenced by mate choice and number, and data are particularly lacking for marine invertebrates. This study was designed to determine if maternal investment and offspring size increase with access to increasing numbers of mates in the protandrous intertidal slipper snail Crepidula cf. marginalis. Virgin female slipper limpets were exposed to one, three, or five potential mates and their fecundity, egg size, and hatchling size were measured for multiple clutches. Treatment had a significant effect on fecundity, with fecundity increasing with the number of potential mates. Treatment did not have an effect on the size of eggs or hatchlings, on the variation in egg size or hatchling size within broods, or on the frequency of oviposition. Treatment did alter the variation in average offspring size among females, but not in the way predicted by theory. The main result, that access to multiple mates does not have an effect on per offspring maternal investment, makes C. cf. marginalis an ideal candidate to study the effects of polyandry on offspring fitness without having to take into account confounding effects of variation in maternal investment.
Effects of Hongjingtian capsule on glial fibrillary acidic protein in focal cerebral ischemia/reperfusion injury rat

Objective To observe the effect of Hongjingtian capsule on the expression of glial fibrillary acidic protein(GFAP) in focal cerebral ischemia/reperfusion(I/R) injury rats.Methods 96 healthy Wistar rats were randomly divided into 4 groups:Hongjingtian group,I/R group, sham operation group and control group.The control group was processed without special treatment while the others were made into middle cerebral artery I/R models through the intraluminal filament method.Neurological deficits were observed and infarct sizes were measured with 2,3,5-triphenyl-tetrazolium chloride staining.The expression alternations of GFAP were determined by immunohistochemical labeling method and the neuronal apoptosis was detected by terminal deoxynucleotidyl transferase mediated nick end labeling at corresponding hours.Results Hongjingtian capsule group's neurological impairment have remarkable difference from I/R group's(P0.05),and infarct sizes narrowed(P0.01). The expression of GFAP appeared in 2 hours later,but not evidently.It increased gradually with the time of cerebral ischemia,and the expression of GFAP had become evident from 6 to 72 hours.The expression decreased in the Hongjingtian capsule groups than in I/R group(P0.05) with the duration of I/R,the amount of apoptotic cells increased in the I/R group while only a small amount of apoptotic cells could be observed in the Hongjingtian group,and there were significant differences from I/R group (P0.05). Conclusion Hongjingtian capsule can relieve ischemia reperfusion injury of brain tissue and improve neurologic scores,and by inhibiting the astroglial GFAP expression.
Spawning success of cultured and wild male Atlantic cod Gadus morhua does not differ during paired contests

Culture of Atlantic cod Gadus morhua L. has been proposed as a means of diversifying the aquaculture industry in Canada and other countries within its native range. Lessons gleaned from aquaculture of salmonids suggest that escapes and interactions with wild fish are inevitable. Here, we studied the reproductive interactions of individual cultured and wild male cod in the presence of a cultured female using a series of spawning trios. The spawning success of cultured males, in terms of both overall proportion of eggs fertilized, and number of spawns in which they fertilized the larger proportion of eggs, did not differ from that of wild males. This equality was likely brought about, at least in part, by multiple paternity with appreciable proportions of eggs fertilized by the presumed satellite male. In a subset of spawning events for which behavioural data were available, neither wild nor cultured males were found to be behaviourally dominant during the night of spawning across all spawning events. The spawning success of the males was not influenced by their size or by their agonistic behaviour, but was influenced by their courting behaviour. The courting behaviour of the wild males had a negative influence on their success, while the courting behaviour of the cultured males was found to increase their success. To our knowledge, this is the first study to detect spawning success equality between wild and cultured male cod in competition.
Effects of plateau pikas (Ochotona curzoniae) burrow densities on plant community composition and population diversity in alpine meadow.

After investigating lots of plateau pikas(Ochotona curzoniae)activities plots and then choosing four plots with different rodent burrow densities to find the variation of plant community compostion and population diversity in alpine meadow.The results showed that species diversity and evenness indexes changed as same as the richness index variation tendency for plant communities,however,the dominance index changed with the opposite tendency.When the burrows increased to medium density(MP) with 864 valid entrance to cave per 1 hm2,every index declined to the smallest.The relationship between plant coverage,richness index,diversity index,evenness index and rodent burrow densities could be described with quadratic equation,and also such diversity indexes had the same relationship with aboveground biomass,too.From above all it could be included that the unimodal curve function could elucidate the distribution pattern of diversity indexes,rodent burrow densities and their own aboveground biomass better.At medium density of pikas population and medium aboveground biomass level the plant community diversity indexes were the least,opposite to "Intermediate Disturbance Hypothesis",in alpine kobresia meadow of Three-River Headwaters region.
Basal metabolic rate and risk‐taking behaviour in birds

Basal metabolic rate (BMR) constitutes the minimal metabolic rate in the zone of thermo‐neutrality, where heat production is not elevated for temperature regulation. BMR thus constitutes the minimum metabolic rate that is required for maintenance. Interspecific variation in BMR in birds is correlated with food habits, climate, habitat, flight activity, torpor, altitude, and migration, although the selective forces involved in the evolution of these presumed adaptations are not always obvious. I suggest that BMR constitutes the minimum level required for maintenance, and that variation in this minimum level reflects the fitness costs and benefits in terms of ability to respond to selective agents like predators, implying that an elevated level of BMR is a cost of wariness towards predators. This hypothesis predicts a positive relationship between BMR and measures of risk taking such as flight initiation distance (FID) of individuals approached by a potential predator. Consistent with this suggestion, I show in a comparative analysis of 76 bird species that species with higher BMR for their body mass have longer FID when approached by a potential predator. This effect was independent of potentially confounding variables and similarity among species due to common phylogenetic descent. These results imply that BMR is positively related to risk‐taking behaviour, and that predation constitutes a neglected factor in the evolution of BMR.
Myostatin,a Negative Regulator of Muscle Growth

Myostatin(GDF-8),a member of the transforming growth factor-β(TGF-β)superfamily,is specifically expressed in skeletal muscle where it acts as a negative regulator of skeletal muscle growth.This paper summarized the myostatin gene's localization,structure,biological function and mechanism,then clarified its significance and applied prospect in sports.