Miracle-dz/UniFAR-FTUs huggingface dataset:
Rhythm and Music-Based Interventions in Motor Rehabilitation: Current Evidence and Future Perspectives

Research in basic and clinical neuroscience of music conducted over the past decades has begun to uncover music’s high potential as a tool for rehabilitation. Advances in our understanding of how music engages parallel brain networks underpinning sensory and motor processes, arousal, reward, and affective regulation, have laid a sound neuroscientific foundation for the development of theory-driven music interventions that have been systematically tested in clinical settings. Of particular significance in the context of motor rehabilitation is the notion that musical rhythms can entrain movement patterns in patients with movement-related disorders, serving as a continuous time reference that can help regulate movement timing and pace. To date, a significant number of clinical and experimental studies have tested the application of rhythm- and music-based interventions to improve motor functions following central nervous injury and/or degeneration. The goal of this review is to appraise the current state of knowledge on the effectiveness of music and rhythm to modulate movement spatiotemporal patterns and restore motor function. By organizing and providing a critical appraisal of a large body of research, we hope to provide a revised framework for future research on the effectiveness of rhythm- and music-based interventions to restore and (re)train motor function.
Micrococcal Nuclease stimulates Staphylococcus aureus Biofilm Formation in a Murine Implant Infection Model

Advancements in contemporary medicine have led to an increasing life expectancy which has broadened the application of biomaterial implants. As each implant procedure has an innate risk of infection, the number of biomaterial-associated infections keeps rising. Staphylococcus aureus causes 34% of such infections and is known as a potent biofilm producer. By secreting micrococcal nuclease S. aureus is able to escape neutrophil extracellular traps by cleaving their DNA-backbone. Also, micrococcal nuclease potentially limits biofilm growth and adhesion by cleaving extracellular DNA, an important constituent of biofilms. This study aimed to evaluate the impact of micrococcal nuclease on infection persistence and biofilm formation in a murine biomaterial-associated infection-model with polyvinylidene-fluoride mesh implants inoculated with bioluminescent S. aureus or its isogenic micrococcal nuclease deficient mutant. Supported by results based on in-vivo bioluminescence imaging, ex-vivo colony forming unit counts, and histological analysis it was found that production of micrococcal nuclease enables S. aureus bacteria to evade the immune response around an implant resulting in a persistent infection. As a novel finding, histological analysis provided clear indications that the production of micrococcal nuclease stimulates S. aureus to form biofilms, the presence of which extended neutrophil extracellular trap formation up to 13 days after mesh implantation. Since micrococcal nuclease production appeared vital for the persistence of S. aureus biomaterial-associated infection, targeting its production could be a novel strategy in preventing biomaterial-associated infection.
Cheating Promotes Coexistence in a Two-Species One-Substrate Culture Model

Cheating in microbial communities is often regarded as a precursor to a “tragedy of the commons,” ultimately leading to over-exploitation by a few species and destabilization of the community. While current evidence suggests that cheaters are evolutionarily and ecologically abundant, they can also play important roles in communities, such as promoting cooperative behaviors of other species. We developed a closed culture model with two microbial species and a single, complex nutrient substrate (the metaphorical “common”). One of the organisms, an enzyme producer, degrades the substrate, releasing an essential and limiting resource that it can use both to grow and produce more enzymes, but at a cost. The second organism, a cheater, does not produce the enzyme but can access the diffused resource produced by the other species, allowing it to benefit from the public good without contributing to it. We investigated evolutionarily stable states of coexistence between the two organisms and described how enzyme production rates and resource diffusion influence organism abundances. Our model shows that, in the long-term evolutionary scale, monocultures of the producer species drive themselves extinct because selection always favors mutant invaders that invest less in enzyme production, ultimately driving down the release of resources. However, the presence of a cheater buffers this process by reducing the fitness advantage of lower enzyme production, thereby preventing runaway selection in the producer, and promoting coexistence. Resource diffusion rate controls cheater growth, preventing it from outcompeting the producer. These results show that competition from cheaters can force producers to maintain adequate enzyme production to sustain both itself and the cheater. This is similar to what is known in evolutionary game theory as a “snowdrift game” – a metaphor describing a snow shoveler and a cheater following in their clean tracks. We move further to show that cheating can stabilize communities and possibly be a precursor to cooperation, rather than extinction.
R2R3-MYB Transcription Factor NtMYB330 Regulates Proanthocyanidin Biosynthesis and Seed Germination in Tobacco (Nicotiana tabacum L.)

Proanthocyanidins (PAs) are important phenolic compounds and PA biosynthesis is regulated by a ternary MBW complex consisting of a R2R3-MYB regulator, a bHLH factor and a WDR protein. In this study, a tobacco R2R3-MYB factor NtMYB330 was characterized as the PA-specific regulator in which the PA biosynthesis was promoted in the flowers of NtMYB330-overexpressing lines while decreased in the flowers of ntmyb330 mutants. NtMYB330 can interact with flavonoid-related bHLH partner NtAn1b and WDR protein NtAn11-1, and the NtMYB330-NtAn1b complex is required to achieve strong transcriptional activation of the PA-related structural genes NtDFR1, NtANS1, NtLAR1 and NtANR1. Our data reveal that NtMYB330 regulates PA biosynthesis in seeds and affects seed germination, in which NtMYB330-overexpressing lines showed higher PA accumulations in seed coats and inhibited germination, while ntmyb330 mutants had reduced seed coat PAs and improved germination. NtMYB330 affects seed germination possibly through two mechanisms: modulating seed coat PAs to affect coat-imposed dormancy. In addition, NtMYB330 regulates the expressions of abscisic acid (ABA) and gibberellin acid (GA) signaling-related genes, affecting ABA-GA crosstalk and seed germination. This study reveals that NtMYB330 specifically regulates PA biosynthesis via formation of the MBW complex in tobacco flowers and affects germination through adjustment of PA concentrations and ABA/GA signaling in tobacco seeds.
The Regulation Mechanisms and Clinical Application of MicroRNAs in Myocardial Infarction: A Review of the Recent 5 Years

Myocardial infarction (MI) is the most frequent end-point of cardiovascular pathology, leading to higher mortality worldwide. Due to the particularity of the heart tissue, patients who experience ischemic infarction of the heart, still suffered irreversible damage to the heart even if the vascular reflow by treatment, and severe ones can lead to heart failure or even death. In recent years, several studies have shown that microRNAs (miRNAs), playing a regulatory role in damaged hearts, bring light for patients to alleviate MI. In this review, we summarized the effect of miRNAs on MI with some mechanisms, such as apoptosis, autophagy, proliferation, inflammatory; the regulation of miRNAs on cardiac structural changes after MI, including angiogenesis, myocardial remodeling, fibrosis; the application of miRNAs in stem cell therapy and clinical diagnosis; other non-coding RNAs related to miRNAs in MI during the past 5 years.
Pose Generation for Social Robots in Conversational Group Formations

We study two approaches for predicting an appropriate pose for a robot to take part in group formations typical of social human conversations subject to the physical layout of the surrounding environment. One method is model-based and explicitly encodes key geometric aspects of conversational formations. The other method is data-driven. It implicitly models key properties of spatial arrangements using graph neural networks and an adversarial training regimen. We evaluate the proposed approaches through quantitative metrics designed for this problem domain and via a human experiment. Our results suggest that the proposed methods are effective at reasoning about the environment layout and conversational group formations. They can also be used repeatedly to simulate conversational spatial arrangements despite being designed to output a single pose at a time. However, the methods showed different strengths. For example, the geometric approach was more successful at avoiding poses generated in nonfree areas of the environment, but the data-driven method was better at capturing the variability of conversational spatial formations. We discuss ways to address open challenges for the pose generation problem and other interesting avenues for future work.
Reproduction in farmed red deer. 2. Calf growth and mortality

SUMMARY The sex and number of calves born to a breeding herd of red deer kept under farm conditions are analysed together with information on mortality and on growth rate of the calves until weaning in September–October. The results showed some anomalous deviations of the sex ratio from a 50:50 expectation. Birth weight was related to the weight of the hind at the time of the rut, and so too was the subsequent daily rate of gain of the calf. Stag calves weighed more than hind calves and there was no effect of age of hind on birth weight once weight of hind had been discounted. Mortality was divided into two components; perinatal mortality included stillbirths, deaths at parturition and during the first 24 h of life and an unidentified mortality representing failure to find a calf although the hind had calved. Postnatal mortality was defined to include all deaths from after 24 h of life to weaning. Mortality was related to the weight of the calf at birth, being 100 % for calves weighing less than 4·0 kg and declining to 5 % for calves weighing 6·0–7·0 kg. The data are discussed and the effect of size of hind at the time of the rut on her fertility, the time at which she calves, the birth weight and growth rate of her calf and its survival rate are combined to estimate the annual number of viable weaned calves and the total weight of calves produced by herds of hinds of different weights. An increase in hind weight of 50 % (from 60 to 90 kg) results in a doubling of the number of calves born and surviving to September and an increase in the weight of the calf crop by 160%. Reasons are given to suggest that total calf mortality could be reduced to 7 %.
Research on mechanism of chaotic vibration screen

An mechanism design for chaotic vibration screen which is under-actuated and the redundant degree of freedom is "1"was proposed.The dynamic model of the mechanism was established by using Lagrange's formulation,and the simulation was carried out by applying Simulink in Matlab.The simulation results show that the motion of the screen box is chaotic.
IMPLEMENTATION OF BIOMETRIC RECOGNITION SYSTEM FOR FINGERPRINT, IRIS AND FACE

: We have to make sure actual presence of a real legal feature in response to a fake reconstructed sample which is important problem in biometric authentication, which can be resolved with the development of new ,efficient and effective protection measures. In this process we apply a software detection method which is a fake which can be used in multiple biometric systems which help in detecting different types of fake access attempt. The main aim and objective of this system is that the biometric recognition security must be enhanced by improving livens assessment in a fast, which must be user friendly, which are not interfering and disturbing with the help of image quality assessment. The present approach has a very low complexity, which makes it suitable for real-time applications, using different sample of image quality features extracted from one image which is used to compare the difference between real and fake samples. The result which is obtained from general public sample datasets of iris, fingerprint and face, show that present method is competitive as compared with other state-of-the-art approach and the study of the general image quality of real biometric samples expose valuable information which help to make a difference between real and fake traits.
Detection and Analysis of Malicious URLs

Social Network Sites(SNS) is the soul of the Internet. It has become a global phenomenon with enormous social as well as economic importance within a few years of their launch. Because of larger user space SNS has become popular day by day. Information exploitation popularity in SNS has attracted not only novice users but also spammers. In SNS spammers are using evolving technology and they safely trading their illegal activities by phishing through e-mails, Social Reverse Engineering(SRE), by posting some incite messages. The novice users often becomes victim to these malicious activity which impacts them both socially and economically. The study show that because of this illegal activity the SNS organisers and users are loosing $2 million for three months. In this thesis we exploited the security gap that many popular SNS services like Twitter, Facebook do not provide to its users. We have collected a large scale of long URLs and short URLs from multiple sources of SNS which are checked against malicious and non-malicious detectors and we analyse their features to classify the URLs. Our result shows that Naive Bayes classifier performs better then other classifier algorithm with accuracy 95.4%
Movable model of a car to dynamic testing

A remote controlled model of a car is described in the paper. The model can be used to preliminary simulating investigations of the car movement. The vehicle model simulates all the most important components of the transmission, suspension and steering system. Owing to a suitable structure it is possible to change the position of the vehicle mass center. The model is equipped with the indicator of the danger of overturning and the sensors of the longitudinal and transverse accelerations, whose read-outs are transmitted telemetrically to a portable computer. It was fixed that the indicator begins its function when the established margin of accelerations is crossed. The modulation of acoustic and optical indicator signals increases with approaching to the limit of overturn of the vehicle. Authors analyze the matter of possible faults of registered movement parameters of the car as can mainly appear from the lack of the similarity of the stiffness of tires, suspensions and the bearing constructions of the vehicle. However, because of very high investigation costs of real car the model investigation can be applied instead of preliminary investigations of real object. Investigations of the indicator of exceeding the limiting lateral accelerations worked out by authors are introduced in the paper. The crossing of acceleration limit can cause the overturning the vehicle. The paper presents test results of sharp turn on the horizontal plane and on circular path drive on a flat surface with constant slope. It was showed in the paper that one can lead functional dynamic investigations on the mobile car model in the range of preliminary investigations.
SELF-POSSESSEMENT WITH PROTECTED ACCREDITED HYBRID CLOUDS

: Data deduplication is a critical system in support dispose of excess information as an option of enthralling records; it provisions simply distinct copy of file. Together with the whole associations stockpiling pattern and numerous associations encase more bits of copy in sequence. Holder in point different clients stores comparative documents in a few superior spaces. Deduplication nullify these extra duplicates by sparing as single duplicate of information and restore alternate duplicates alongside pointers that flipside to the first duplicate. It be the information pressure procedure for to build the data transfer capacity proficiency and capacity misuse. Information deduplication is tremendously utilizing as a part of distributed computing currently. Feature information administration versatile and stockpiling setback in distributed computing. Information deduplication protect the privacy of touchy data. It lives up to expectations with merged encryption system to scramble the information before convey. Administrations frequentlyutilize Deduplication in reinforcement and disaster recuperation functions. Here we attempt the approved deduplication ensure,meet with simultaneous encryption to supervise the cost of security for touchy information with half and half distributed computing.
DESIGN OF RELIABLE MULTIPLIER USING ADAPTIVE HOLD LOGIC

The semiconductor technology and therefore the decreasing of device geometries square measure increasingly increases: the ensuing processors square measure more and more changing into vulnerable to effects like aging and soft errors. As number ages, the semiconductor unit shift time can increase and its electrical characteristics scale back. Hence, supported the turnout of the number style, the general performance of the digital filters depends. Aging downside of semiconductor unit has important result on the performance of those digital systems and in long run, the system could fail attributable to delay issues. Hence, the processor or number cannot continue error free operation at an equivalent clock frequency and/or voltage that it had been originally designed. So, to scale back such effects, recent analysis proposes to supply processors with special electronic equipment that mechanically modify its circuit level temporal order properties. From the attitude of tasks running on these processors, by mistreatment over style approaches, aging result will be reduced, however these approaches ends up in space unskillfulness. And conjointly temporal order violations occur once mounted latency styles square measure used. This must be analyzed rigorously, notably within the context of laborious real time. during this paper we have a tendency to propose a reliable number mistreatment AHL during which, aging iatrogenic degradation and changes in temporal order properties of the processor, once planning laborious real time systems. particularly, by taking a time period constraint of the system into consideration we have a tendency to address the schedulability and task mapping downside. In alternative words, till a given minimum amount of your time (i.e., life time) the system style to be absolutely operational (i.e., meet all deadlines). The experimental results show that our planned design with thirty two ×32 and sixty four ×64 changed booth multipliers mistreatment AHL. The Verilog language is employed for coding; synthesis was done by mistreatment Xilinx ISE
Performance Analysis and Improvement of the Equalization Algorithm Based on Fourier Transform for Radar Channel

The performance analysis of a kind equalization algorithm based on Fourier Transform for radar channel is carried out.The factors including Signal-to-noise ratio,relationship between bandwidth and sampling rate and group delay affecting the algorithm's performance are analyzed and solutions are proposed.According to the principle of circular convolution,a method of realizing non-causal equalizer is proposed to suppress the influence of the group delay effect.All analysis is based on experiment data.The results show that the modified algorithm could achieve good performance after avoiding the influence of the several factors.
Error Compensation of Joint Angles Based on RBF Neural Networks

Joint angle errors have important influence on the accuracy of articulated arm coordinate measuring machines (AACMMs). There are many factors causing joint angle errors,so it is difficult to describe them accurately with mathematic models.A compensation method based on radial basis function (RBF) neural networks is presented to solve the problem.A practical method to calibrate errors of joint angles with a coordinate measuring machine is designed,thereafter the angle errors of six joints of an AACMM are calibrated discretely.The calibration data is used to train the RBF neural networks,after training the RBF neural networks are used to compensate the angle errors of six joints respectively.Experimental tests are carried out to evaluate the efficiency of the RBF neural network compensation method,showing that after compensation the rotation accuracy of the joints angle is improved greatly,and the RBF neural network compensation method is more efficient than a compensation model of sine function,therefore,it is valuable for engineering applications.
On Modern Management

Management is not only the manager's personal practice but also the result of culture. Culture always exercises its restraints upon management and it influences the decision and judgment of the managers. To put away the bondage of preconceived ideas and to be able to make conscious dynamic and objective judgments, a manager must know the specific management conditions with relation to culture.
PROCESSING OF ECG SIGNALS TO DETECT CARDIOVASCULAR DISEASES

Electrocardiogram (ECG) has been the preliminary diagnostic tool to detect cardiovascular diseases. ECG is generally recorded on a thermal paper which cannot be stored for a long time for analysis, as the thermal trace gets erased gradually. To store the trace, the records are scanned and saved as images to maintain medical record. The memory occupied by this method is high and the regeneration of signal accuracy is less.
OPINION MINING TO PREDICT ELECTION RESULTS

: An expeditious development of the web Application has created countless opportunities for the public to vocalize their Opinions. Web Applications like Social Media, Blogs, News Portal, E-commerce Sites etc. has created huge buzz amongst people. Now a days amongst all above web applications Social media has become the mirror of the society. Starting from giving opinions about the movies or checking popularity of any celebrity, or discussion about political parties during elections or predicting box-office results or predicating election results or starting of new trend all things become easier because of the gaining popularity of Social media. Amongst all Social Media twitter has huge tie up with all the above mentioned stuffs. Now all this discussions, or giving an opinion or giving star credits or reviews generate huge amount of user generated content, to analyze and summarize this content is the job of natural language processing and machine learning techniques. For example opinion mining or Sentiment Analysis, text mining, graph mining etc. In this paper all opinion mining techniques and supervised machine learning techniques will be discussed which will be useful to predict election results from the tweets. And we will also compare weka results with our own implemented results. This paper contains introduction following by related work, opinion mining techniques, purposed method and results and conclusion.