Miracle-dz/UniFAR-FTUs huggingface dataset:
Illusory bimodality in repeated reconstructions of probability distributions

Probability density estimation is widely-known as an ill-posed statistical problem whose solving depends on extra constraints. We investigated what prior beliefs people might have in their learning of an arbitrary probability distribution, especially whether the distribution is believed to be unimodal or multimodal. In each block of our experiments, participants repeatedly reconstructed a one-dimensional spatial distribution after observing every 60 new samples from the distribution. The probability distribution function (PDF) they reported on each trial was submitted to a spectral analysis, where the powers for 1-cycle, 2-cycle, . , n-cycle components respectively indicate participants’ tendency of reporting unimodal, bimodal, . , n-modal distributions. In two experiments, the reported PDFs showed significant bimodality—that the 2-cycle power was above chance and even larger than the 1-cycle power—not only for bimodal distributions, but also for uniform distribution. Such illusory bimodality for uniform distribution was first found when we used an adaptive procedure analogous to “human MCMC”, updating the generative distribution of samples from trial to trial to reinforce potential biases in PDFs (Experiment 1). However, even when we fixed the generative distribution across trials (Experiment 2), the illusory bimodality did not vanish. The illusory bimodality was even observed before participants experienced any bimodal distributions in the experiment . We considered a few kernel density models and discuss further computational explanations (e.g. prior beliefs following Chinese Restaurant Process) for this new phenomenon.
SPEECH RECOGNITION - A REVIEW

The Speech is most prominent & primary mode of Communication among of human being. The communication among human computer interaction is called human computer interface. Speech has potential of being important mode of interaction with computer . This paper gives an overview of major technological perspective and appreciation of the fundamental progress of speech recognition and also gives overview technique developed in each stage of speech recognition. This paper helps in choosing the technique along with their relative merits & demerits. A comparative study of different technique is done as per stages. Speech recognition is a key element of diverse applications in communication systems, medical transcription systems, security systems etc. This paper is concludes with the decision on feature direction for developing technique in human computer interface system using Marathi and Hindi Language.
Semantic keypoint-based pose estimation from single RGB frames

This paper presents an approach to estimating the continuous 6-DoF pose of an object from a single RGB image. The approach combines semantic keypoints predicted by a convolutional network (convnet) with a deformable shape model. Unlike prior investigators, we are agnostic to whether the object is textured or textureless, as the convnet learns the optimal representation from the available training-image data. Furthermore, the approach can be applied to instanceand class-based pose recovery. Additionally, we accompany our main pipeline with a technique for semi-automatic data generation from unlabeled videos. This procedure allows us to train the learnable components of our method with minimal manual intervention in the labeling process. Empirically, we show that our approach can accurately recover the 6-DoF object pose for both instance- and class-based scenarios even against a cluttered background. We apply our approach both to several, existing, large-scale datasets - including PASCAL3D+, LineMOD-Occluded, YCB-Video, and TUD-Light - and, using our labeling pipeline, to a new dataset with novel object classes that we introduce here. Extensive empirical evaluations show that our approach is able to provide pose estimation results comparable to the state of the art.
Estudo do creme de buriti (Mauritia flexuosa L.) no processo de cicatrização Study of buriti (Mauritia flexuosa L.) cream in the healing process

Objective: To evaluate the effect of buriti (Mauritia flexuosa L.) cream on the healing of skin lesions in mice. Methods: Fifty-six mice underwent surgical procedure of excision of the skin in the dorsal region. After surgery, the groups were treated with saline 0.9%, buriti cream 5% and 10% and Fibrase®. Results: On the seventh day was observed a significant reduction of the wound area in the animals treated with cream buriti 5% and Fibrase® when compared to control. No differences were observed between groups on the 14th day of treatment. Histological examination showed the presence of granulation issue more evolved, fibroblasts and collagen fibers in the samples buriti cream 5% and Fibrase® from the seventh day of treatment. Conclusion: The buriti cream 5% is able to accelerate the healing process.
Mechanisms And Machines Kinematics Dynamics And Synthesis Kinematics Dynamics And Synthesis Kinematics Dynamics And Synthesis Kinematics Dynamics And Synthesis Dynamics And Synthesis

mechanisms. Coverage of a broad range of machines and mechanisms with practical applications given top consideration. Mechanisms and Machines. Motion in Machinery. Velocity Analysis of Mechanisms. Acceleration Analysis of Mechanisms. Cams. Spur Gears. Helical, Worm, and Bevel Gears. Drive Trains. Static-Force Analysis. Dynamic-Force Analysis. Synthesis. Introduction to Robotic Manipulators. from antiquity until the present and its historiography: machines, mechanisms, kinematics, dynamics, concepts and theories, design methods, collections of methods, collections of models, institutions and biographies. of in several modern technical fields such as mechatronics and robotics, biomechanics, machines and apparatus. The original high-quality contributions on topics related to mechanisms within aspects of theory, design, practice and applications in engineering, including but not limited to: theoretical kinematics, computational kinematics, mechanism design, experimental mechanics, mechanics of robots, dynamics of machinery, dynamics of multi-body systems, control issues of mechanical systems, mechanisms for biomechanics, novel designs, mechanical transmissions, linkages and manipulators, micro-mechanisms, teaching methods, history of mechanism science, industrial and non-industrial applications. In connection with these fields, the book combines the theoretical results with experimental tests.
FINITE ELEMENT ANALYSIS OF MECHANICAL PROPERTIES OF REINFORCED E-GLASS FIBER

Assistant Professor, Department of Marine Engineering, Academy of Maritime Education and Training, Chennai, Tamil Nadu, India Assistant Professor, Department of Mechanical Engineering, K. Ramakrishnan College of Technology, Trichy, Tamil Nadu, India Assistant Professor, Department of Mechanical Engineering, Academy of Maritime Education and Training, Chennai, Tamil Nadu, India Professor, Department of Marine Engineering, Academy of Maritime Education and Training, Chennai, Tamil Nadu, India ABSTRACT
PHRASEOLOGY IN AIR TRAFFIC CONTROLLER’S COMMUNICATION

The research design is qualitative research design. The instruments of data collection are voice recorder to record the data, camcorder to interview then observe the subject and a camera is used to capture some photographs to show the real situation in conducting as part of field research method. The findings of the study are drawn. (1) The types of phraseology used by ATC in this study are five; they are General Phraseology (GP), Radar Control Phraseology (RCP), Area Control Phraseology (Area CP), Approach Control Phraseology (App CP), and Aerodrome Control Phraseology (Aerodrome CP) as standard phraseology, and also Non – standard phraseology . (2) The patterns of phraseology used by ATC in communication with pilot are commonly systemized but sometimes it depends on the situation faced by controllers, there is no certain patterns used. (3) ATC commonly use standard phraseology which has been standardized by ICAO. ATC may combine the types of phraseology based on the condition and situation needed. In another case and situation, ATC sometimes used non – standard phraseology in communication with pilot, that’s why phraseology is the unique language used by ATC in their daily job, interact with pilots in a communication in order to prevent collisions, organize and expedite the flow of traffic, and provide information and other support for pilots . Key words: phraseology, air traffic controller, communication
Job Insecurity and Innovative Performance: The Mediating role of Knowledge Hiding in Organizations

Using data from a diverse sample (n=194, paired samples based on data from employeesand their supervisors) from various organizations across Pakistan, this study examined an emergent construct knowledge hiding (which we conceptualized as a silence behavior based on EVLNC, Exit, Voice, Loyalty, Neglect, Cynicism model) and its relation to innovative performance. Against knowledge hiding we also tested job insecurity and innovative performance. Data was analyzed using bootstrapping and regressions analysis. Results supported that knowledge hiding could be significantly predicted by employee’s reaction to job insecurity in organizations. Further our findings also indicated that when people feel insecure at their job they indulge in somewhat counterwork behaviors like hiding knowledge and which can negatively affect their innovative performance.
A brief technical review of emerging waste heat recovery solutions for marine diesel engines

Diesel engines remain the most widely used option to power a wide variety of transport ships. In terms of the maximum installed volume of all shipping vessels, 96% of this energy is generated from diesel engines. Due to the lack of alternative propulsion systems with the same energy density, cost, and fuel efficiency as diesel engines, it is not expected that marine diesel engines will be replaced within an expected 100 years. Modern large diesel engines are about 50% efficient in using the burning thermal energy of the fuel and the rest is lost to the environment as waste heat. The efficient use of waste heat energy can enhance the power system efficiency and reduce emissions, by using a dedicated waste heat recovery system for power generation or heating needs. Technologies that recover waste heat from engines have been around for 30 years, but recovery efficiency, cost of installation, and the ability to take up space in engine room space have caused certain obstacles. This paper conducts a brief review of the techniques and prospects of emerging waste heat recovery technologies from marine diesel engines. The results achieved would be useful suggestions for ship managers and owners in equipping marine fleets with waste heat recovery systems to meet the increasingly stringent IMO requirements for energy efficiency and environmental protection.
Predicting the Expansion of Supernova Shells for High-Resolution Galaxy Simulations Using Deep Learning

Small integration timesteps for a small fraction of the particles become a bottleneck for future galaxy simulations with a higher resolution, especially for massively parallel computing. As we increase the resolution, we must resolve physics on a smaller timescale while the total integration time is fixed as the universe age. The small timesteps for a small fraction of the particles worsen the scalability. More specifically, the regions affected by supernovae (SN) have the smallest timestep in the whole galaxy. Using a Hamiltonian splitting method, we calculate the SN regions with small timesteps using a few thousand CPU cores but integrate the entire galaxy using a shared timestep. For this approach, we need to pick up particles in regions, which will be affected by SN (the target particles) by the next global step (the integration timestep for the entire galaxy) in advance. In this work, we developed the deep learning model to predict the region where the shell due to a supernova explosion expands during one global step. In addition, we identify the target particles using image processing of the density distribution predicted by our deep learning model. Our algorithm could identify the target particles better than the method based on the analytical solution. This particle selection method using deep learning and the Hamiltonian splitting method will improve the performance of galaxy simulations with extremely high resolution.
Quantum Game Theory approach for data network routing: a solution for the congestion problem

Because of the sustained growth of information and mobile users transmitting a great amount of data packets, modern network performances are being seriously affected by congestion problems. In fact, congestion management is a challenging task that can be roughly summarized as a trade off between transmission latency and cost. In this context, a novel framework is proposed for solving the congestion problem on communication networks using a quantum game theory model, where network packets compete selfishly for the shortest route. Simulations show that final network routing and traveling times achieved with the quantum game version outperform those obtained classically. This leads to the opportunity of developing full-stack protocols that may be capable of taking advantage of the quantum properties for optimizing communication systems. Due to its generality, the game theoretic approach can be applied both in local networks and in more complex networks such as 5G or LTE-A.
A multi-wavelength approach to increase polarimeter diagnostic performance in nuclear fusion reactors

In future tokamaks, the huge variation of the plasma parameters during a discharge (ramp up, flat top, and ramp down) may involve that a diagnostic suitable for the flat top is not suitable for transients, and vice versa. Moreover, future reactors will start the experimental campaigns in safe scenarios, where events like disruptions are not critical, and they will increase their parameters gradually. Also in this case, a diagnostic optimised for the final target scenario may fail at the beginning of the experimental campaign. Laser-based polarimetry, a plasma diagnostic used in magnetized plasma to measure quantities that are related to the electron density, the magnetic field, and the electron temperature (in the case of relativistic effects), is a typical diagnostic that must be optimised for specific scenarios, since it is affected by several issues (refraction, type-I approximation, noise sensitivity) that limit its range of applicability. The aim of this work is to present a method to solve, or at least alleviate, this type of problem by using a multi-wavelength approach. The main idea consists of measuring the polarisation effects (Faraday rotation and Cotton-Mouton phase shift) with more than one wavelength and then calculating the plasma parameters by a weighted average of the measurements, where the weights are derived from the theory of polarimetry. The analysis is performed simulating the process of measurement introducing a casual error. The outcomes demonstrate that the adoption of a multi-wavelength polarimeter system brings a more accurate measurement in a wider range. Considering that next tokamaks will be implemented with a dual-wavelength interferometer, like the dispersion interferometer-polarimeter of ITER, this proposed approach could be taken into consideration to increase the performances of polarimetry.
CFD analysis of Effect of journal bearing lubricated with non-Newtonian fluid

The present paper deals with the CFD analysis of hydrodynamic bearing lubricated with a non-Newtonian fluid and the non-Newtonian behaviour of lubricant is represented by a power-law. Bearing parameters such as fluid film pressure and load-carrying capacity are determined by varying the power-law index (n) in terms of its viscosity from 0.8 to 1.2 under steady-state conditions through the CFX 17.2 software module and the flow model opted as Laminar based on Reynolds number calculation as per the geometry developed for the simulation. The relationship between the pressure and load-carrying capacity are also obtained for different relative clearance, revolution per minute and L/D ratio. Fluid film pressure profile was drawn by varying input parameters at different power-law index for understanding the performance of HDB under different regimes i.e. dilatant, Newtonian and pseudoplastic fluids. Plots were also created between Pressure, load carrying capacity and power law index to study the performance of HDB. This has been observed that the bearings lubricated with dilatant fluid (n >1) have higher pressure and load carrying capacity as compared to those lubricated with pseudoplastic fluid (n < 1). Occurrences of cavitation were also seen at lower angle with increases in power law index for 0.0006 relative clearance but increases at 0.0008.
Preparation and characterization of microcrystalline cellulose from lembang (Typha angustifolia L. )

The study of preparation and characterization of microcrystalline cellulose from the Lembang / narrowleaf cattail (Typha angustifolia L.) has been carried out. Alkalinization was done to remove lignin and hemicellulose compounds. The bleaching process was done by adding 4 M HCl at 65 oC for 3 hours and then sonicated for 10 minutes. The cellulose yield obtained was 32.2%. The Fourier Transform Infrared (FTIR) spectra indicated the appearance of some specific functional groups (O-H, -C-H, =C-H and C-O, and C-O-C). Scanning Electron Microscope (SEM) showed that the structure of cellulose is a long crystalline with a diameter of 3.1 µm. Thermogravimetric analysis (TGA) showed decomposition at higher temperatures of 349.13, 366.66 and 353.24 oC for cellulose after hydrolysis, cellulose before hydrolysis, and TaL powder. Crystalline index and crystalline size of microcrystalline cellulose analyzed by X-Ray Diffraction (XRD) were 71.1% and 2.4 nm, respectively.
Propagation of unit location uncertainty in dense storage environments

Dense storage systems provide high-space utilisation; however, because not all units are immediately accessible, selectively offloading units can require shifting of other stored units in order to access the requested unit. Given an initial certainty in unit location, a discrete time Markov Chain is developed to quantify the growth of unit location uncertainty as a function of retrieval requests. As the first to mathematically model uncertainty propagation in dense storage operations, metrics are developed to analyse the model. A theoretical understanding of the relationship among storage density, retrieval times and unit location uncertainty is provided. Finally, a case study using inventory and load plan data from a military application illustrates how the developed models can be used by managers to evaluate selective offloading policies and layouts.
Measurements and Approximations for Submicron‐Aerosol Size Distribution Functions

Results of field measurements taken in the near‐Caspian (2002, 2003, 2007, 2009, 2010, 2011, 2013, 2014, 2016 years) and near‐Aral sea (1998) deserts under the conditions of weak winds (almost in the absence of saltation processes) and strong heating of the land surface are given. These results show that the fine mineral dust aerosol (0.1–1 μ m) considerably contributes to the total aerosol content of the atmospheric surface layer under such conditions. The scaling of daytime mean size d distribution at a height of 2 m is approximated by dependence d−μ , where μ changes from 4 to 6 for different years of measurements, in contrary to the law d−2 for fraction d>1μ m. Different compositions of aerosol particles at 0.11μ m, including multicomponent fractions (less than 1μ m) may result in different probabilities of their integration and disintegration. It is hypothesized that the equilibrium distribution of submicron aerosol is a result of sequential disintegration of aerosol particles with a possibility for their reintegration. The simplest distribution approximations are given based on the Kolmogorov direct differential equation which is usually used in considering the Poisson distributions in equations for queuing systems.
Clinical Decision Support Based on FHIR Data Exchange Standard

With the improvement of the level of medical information, the major hospitals have the appropriate medical information system (Hospital Information System, HIS) to manage clinical medical data. However, because of the difference of HIS, the structure of clinical medical data is also different, which seriously affects the transmission, compatibility and use of clinical data, that making the data incomplete or can’t be effectively used. In this paper, we use the Fast Healthcare Interoperability Resources (FHIR) standard to standardize the exchange of clinical medical data, and build a data sharing platform with multi agent platform, so that the clinical medical data can be integrated by Agent for clinical decisions making.
Pantomime of tool use: looking beyond apraxia

Abstract Pantomime has a long tradition in clinical neuropsychology of apraxia. It has been much more used by researchers and clinicians to assess tool-use disorders than real tool use. Nevertheless, it remains incompletely understood and has given rise to controversies, such as the involvement of the left inferior parietal lobe or the nature of the underlying cognitive processes. The present article offers a comprehensive framework, with the aim of specifying the neural and cognitive bases of pantomime. To do so, we conducted a series of meta-analyses of brain-lesion, neuroimaging and behavioural studies about pantomime and other related tasks (i.e. real tool use, imitation of meaningless postures and semantic knowledge). The first key finding is that the area PF (Area PF complex) within the left inferior parietal lobe is crucially involved in both pantomime and real tool use as well as in the kinematics component of pantomime. The second key finding is the absence of a well-defined neural substrate for the posture component of pantomime (both grip errors and body-part-as-tool responses). The third key finding is the role played by the intraparietal sulcus in both pantomime and imitation of meaningless postures. The fourth key finding is that the left angular gyrus seems to be critical in the production of motor actions directed towards the body. The fifth key finding is that performance on pantomime is strongly correlated with the severity of semantic deficits. Taken together, these findings invite us to offer a neurocognitive model of pantomime, which provides an integrated alternative to the two hypotheses that dominate the field: The gesture-engram hypothesis and the communicative hypothesis. More specifically, this model assumes that technical reasoning (notably the left area PF), the motor-control system (notably the intraparietal sulcus), body structural description (notably the left angular gyrus), semantic knowledge (notably the polar temporal lobes) and potentially theory of mind (notably the middle prefrontal cortex) work in concert to produce pantomime. The original features of this model open new avenues for understanding the neurocognitive bases of pantomime, emphasizing that pantomime is a communicative task that nevertheless originates in specific tool-use (not motor-related) cognitive processes.