Miracle-dz/UniFAR-FTUs huggingface dataset:
Sarawak Traditional Dance Motion Analysis and Comparison using Microsoft Kinect V2

This research project aimed to develop a software program or an interactive dance motion analysis application that utilizes modern technology to preserve and maintain the Sarawak traditional dance culture. The software program employs the Microsoft Kinect V2 to collect the digital dance data. The proposed method analyses the collected dance data for comparison purposes only. The comparison process was executed by displaying a traditional dance on the screen where the user who wants to learn the traditional dance can follow it and obtain results on how similar the dance is compared to the recorded dance data. The comparison of the performed and recorded dance data was visualized in graph form. The comparison graph showed that the Microsoft Kinect V2 sensors were capable of comparing the dance motion but with minor glitches in detecting the joint orientation. Using better depth sensors would make the comparison more accurate and less likely to have problems with figuring out how the joints move.
Optimization of the presampling modulation transfer function of flat-panel detectors for digital radiology

Large area, flat panel solid state detectors are being investigated for digital radiography and fluoroscopy. These detectors employ an x-ray imaging layer of either photoconductor ('direct' conversion method) or phosphor ('indirect' conversion method) to detect x-rays. In both cases the image formed at the surface of the layer is read out in situ using an active matrix array. Depending upon the resolution of the layer compared to the pixel size, undersampling of the image and hence aliasing may occur. Aliasing is always present regardless of the pixel size in direct detectors based on amorphous selenium because of its high intrinsic resolution. Aliasing gives rise to increased noise which results in reduction of detective quantum efficiency DQE at high spatial frequencies. The aliasing can be reduced or even eliminated by blurring prior to pixel sampling (e.g., by scattering in a phosphor layer). However, blurring, which may be quantified by the spatial frequency f dependent modulation transfer function MTF(f), also has a deleterious effect: the imaging system becomes much more susceptible to noise for example that arising in the charge amplifiers or secondary quantum statistics. Note that in principle, the system MTF can be corrected to any desired values in a digital system thus MTF has no predictive value for the quality of an imaging system, rather it is the DQE(f) which determines the overall signal to noise ratio independently of the MTF enhancement chosen. Nevertheless, determining the ideal level of presampling blurring (i.e., the Presampling Modulation Transfer function) is not straightforward. A problem caused by blurring is that the degree of blurring often depends on the depth of absorption of the x-ray in the imaging layer. In such cases (as pointed out by Lubberts) additional noise is transferred to the image. The predictions of a Lubberts model will be compared with published measurements of DQE for both direct and indirect detectors. A preliminary conclusion, is that blurring by CsI phosphor layers is non-ideal and leads to a significant loss of DQE at high spatial frequencies while no such loss is occurring in (alpha) -Se layers due to the equal MTF (in this case MTF(f) approximately equals 1) at all depths. Thus the only method which appears practical to cause blurring so as to avoid noise aliasing while avoiding the Lubberts depth dependent effect is to have a perfect MTF in the imaging layer and then blur before sampling. Such an approach has been proposed for the direct method based on the use of a partially conducting layer. Theoretical estimates of the final DQE(f) to be expected using this variation of the direct conversion method are produced.
Establishing Time-Depth Relationships Constrained by Modes of the Reservoir Architecture

Time-depth relationships (TDRs) can connect seismic and wireline logs, both essential characterization data of reservoirs. The seismic well tie is always a complex work on account of the complicated reservoir structures. Since seismic and logging data are responses of reservoir architectures, the seismic well tie can be efficiently improved constrained by the reservoir architectures. This study adopts a clastic reservoir as the study area. Three architecture modes (i.e., normal cycle mode, inverse-normal cycle mode, and homogeneous-normal cycle mode) are summarized based on combinations of architecture elements. For the generation of the synthetic seismograms, optimized wavelets (i.e., wavelet A, wavelet B, and wavelet C) are suitable for the wells belonging to normal cycle mode, inverse-normal cycle mode, and homogeneous-normal cycle mode, respectively. Precise TDRs are established by matching the synthetics and seismic traces. Wells belong to the same architecture mode and have similar TDRs. The two-way travel time is shortest in the same depth interval of homogeneous-normal cycle mode compared to other architecture modes.
Broken Engagement: Teaching Finance during Pandemic Times

Student engagement is critical to creating a collaborative and involved learning environment. The pandemic brought the class room engagement between the faculty and the students to a halt. We tried to find different avenues for the students to reach out to the faculty and to have an open forum to facilitate discussions among themselves. This approach helped us in increasing engagement and also allowed students who would normally not speak during the class hours to contribute to the overall learning during the course. JEL Codes: I20, I23, I29
Distorted reflector antennas: fast and accurate estimation of the surface distortion profile using a new formula

The high-frequency applicability of reflector antennas is limited by the distortions and the errors on the reflector surface. Different techniques can be used to compensate the degradation of the radiation characteristics if the surface distortion profile is known. Here, a fast and accurate iterative method has been proposed to determine the surface distortion profile which is based on a newly developed variational formula. The surface fitting has been done in the general form of B-splines, which is suitable for both local and global distortions. Different types of the distortions have been studied to check the accuracy of the method. It has been shown that for distortion amplitudes lower than half of wavelength, the proposed algorithm converges with a high accuracy. In comparison with the previous works, the proposed algorithm has higher accuracy and faster convergence and it needs a lower number of far-field measurements. Despite the microwave holography, in the proposed method there is no need to compute the aperture fields.
A SELF-ADAPTIVE TEXT CLASSIFICATION METHOD BASED ON MULTIPLE WORD EMBEDDING AND NEURAL NETWORK

Traditional text classiﬁers often rely on many human-designed features, which is complicated and inconvenient in practical applications. This paper proposes a novel neural network based text classiﬁcation method that uses a self-adaptive mechanism to integrate various pre-trained word embedding. Firstly, the proposed method independently constructs feature vector from various word embedding with rich semantic information. Then, in order to distinguish the contribution of multiple word embedding in classiﬁcation task and revise the inﬂuence of diﬀerent embedding on the ﬁnal text representation, we use Highway network to adjust the weight of feature vectors automatically. Finally, we combine these feature vectors and form the ﬁnal text representation to classify. The experiment has been conducted on sentiment and news classiﬁcation datasets; the results show that the method achieves better results with several benchmarks, and gets the similar performance to the state-of-the-art methods on English news classiﬁcation task. The further contrast experiment also proves that the method has the ability of adaptively integrating multiple word embedding.
Simultaneous Human Action and Motion Prediction

This paper presents a novel approach to solve simultaneously the problems of human whole-body motion prediction and action recognition for real-time applications. Starting from the dynamics of human motion and motor system theory, the notion of mixture of experts from deep learning literature has been extended to solve this problem. The work is accompanied by 66-DoFs human model experiments
USING RANDOM MATRICES IN QUANTUM INFORMATION THEORY

The goal of this series of lectures is to present some recent results in quantum information theory which make use of random matrices. After an introduction to random matrix theory, I will present the method of moments, one of the most successful methods used to study the spectra of large random matrices. This will be the occasion to discuss integration over Gaussian spaces. On the quantum information side, I will focus on two main topics, random quantum states and random quantum channels. I will then prove two recent results, one on the asymptotic eigenvalue distribution of the partial transposition of random quantum states, and another on the output set of random quantum channels. Both will require some terminology and results from free probability, which will also be discussed in detail.
'The' creative class does not exist: Contrasting residential preferences of creative and technical workers in Amsterdam and Eindhoven

The creative class is a much-contested concept, yet still very much in vogue among policy makers. Although a range of studies have built on, refined and improved this concept, there is still a tendency to under-estimate the heterogeneity of higher-skilled workers. Although various scholars, including Florida, also pay some attention to the heterogeneous nature of the creative class, much emphasis is placed on the lifestyles and preferences that these workers supposedly have in common. In this chapter we will focus on the residential preferences of highereducated workers in general, and creative and technical workers in particular. Residential preferences play an important role in Florida’s ‘creative class’ thesis. Florida (2002) claims that the ‘creative class’ have particular preferences in terms of their residential location and environment and their use of amenities that would set this ‘class’ apart from other segments of the working population. In his view the ‘creative class’ would have a strong preference for highly urban environments, including features like a diversity of functions, people and lifestyles, a high level of tolerance for this diversity, a vibrant nightlife, ‘street-level culture’, and ‘third places’ where the borders between work and leisure disappear. He suggests that urban economic strategies should focus on attracting the ‘creative class’, amongst others, by creating or improving the types of highly urban environments they demand. Initially basing his thesis mainly on data from US metropolitan areas, he has meanwhile expanded his ‘creative class’ research network to Canada, Europe, Australia and East Asia (e.g. Mellander et al. 2014).
Analisa Kebijakan Physical Distancing pada penyebaran COVID-19

Diterma: 05-12-2021 Direvisi: 10-12-2021 Diterbitkan: 10-01-2021 Virus SARS-COV-2 yang menyebabkan penyakit COVID-19 telah menyebar ke seluruh dunia. Pada 2 Maret 2020, Indonesia telah mengonfirmasi kasus COVID-19 dan jumlah kasus meningkat dengan cepat dalam beberapa minggu. Pemahaman mengenai dinamika penularan penyakit dan langkah-langkahnya adalah hal penting untuk menangani virus ini. Artikel ini bertujuan untuk mensimulasikan penyebaran COVID-19 dan untuk menganalisa strategi kebijakan yang efektif di Indonesia. Model SEIQRD diusulkan dalam artikel ini dan penerapannya pada data yang tersedia. Selain itu, model ini juga dikembangkan dengan melibatkan faktor intervensi yang memiliki peran dalam penyebaran virus pada suatu wilayah. Strategi intervensi physical distancing ditujukan pada inidividu yang rentan sebagai variabel yang memungkinkannya untuk dikendalikan dengan berbagai kebijakan. Hasil penelitian menunjukkan bahwa adanya penerapan intervensi physical distancing dengan proporsi sebesar 75% memberikan pengaruh besar dalam mengurangi angka infeksi baru dibandingkan dengan penerapan intervensi physical distancing dengan proporsi 25% dan 50%. Kata Kunci:
“I need to be professional until my new team uses emoji, GIFs, or memes first’’: New Collaborators’ Perspectives on Using Non-Textual Communication in Virtual Workspaces

Virtual workspaces rapidly increased during the COVID-19 pandemic, and for many new collaborators, working remotely was their first introduction to their colleagues. Building rapport is essential for a healthy work environment, and while this can be achieved through non-textual responses within chat-based systems (e.g., emoji, GIF, stickers, memes), those non-textual responses are typically associated with personal relationships and informal settings. We studied the experiences of new collaborators (questionnaire N=49; interview N=14) in using non-textual responses to communicate with unacquainted teams and the effect of non-textual responses on new collaborators’ interpersonal bonds. We found new collaborators selectively and progressively use non-textual responses to establish interpersonal bonds. Moreover, the use of non-textual responses has exposed several limitations when used on various platforms. We conclude with design recommendations such as expanding the scope of interpretable non-textual responses and reducing selection time.
IJSRD-International Journal for Scientific Research & Development| Vol. 5, Issue 02, 2017 | ISSN (online): 2321-0613

The use of distributed energy resources is progressively being pursued as a supplement and an alternate to giant standard central power stations. The specification of a power-electronic interface is subject to necessities affiliated not alone to the renewable energy supply itself but also to its result on the power system grid, particularly wherever the intermittent energy supply constitutes a major a part of the entire system capacity. During this paper, new technique in power electronic system for the integration of wind, solar and photo-voltaic power generators are represented. A review of the suitable storage-system technology used for the combination of intermittent renewable energy sources is additionally introduced. Discussions regarding common and future trends in renewable energy systems depends on reliability and maturity of every technology are bestowed.
PP2A Rts1 antagonizes Rck2-mediated hyperosmotic stress signaling in yeast

In Saccharomyces cerevisiae impairment of protein phosphatase PP2A Rts1 leads to temperature and hyperosmotic stress sensitivity, yet the underlying mechanism and the scope of action of the phosphatase in the stress response remain elusive. Using quantitative mass spectrometry-based 27 approaches we have identified a set of putative substrate proteins that show both, hyperosmotic stress- 28 and PP2A Rts1 -dependent changes in their phosphorylation pattern. A comparative analysis with 29 published MS-shotgun data revealed that the phosphorylation status of many of these sites is regulated 30 by the MAPKAP kinase Rck2, suggesting a node of regulation. Detailed gel mobility shift assays and 31 protein-protein interaction analysis strongly suggest that Rck2 activity is directly regulated by 32 PP2A Rts1 via a SLiM B56-family interaction motif, uncovering a previously unknown mechanism of 33 how PP2A influences the response to hyperosmotic stress in Yeast.
IL-flOw: Imitation Learning from Observation using Normalizing Flows

We present an algorithm for Inverse Reinforcement Learning (IRL) from expert state observations only. Our approach decouples reward modelling from policy learning, unlike state-of-the-art adversarial methods which require updating the reward model during policy search and are known to be unstable and difficult to optimize. Our method, IL-flOw, recovers the expert policy by modelling state-state transitions, by generating rewards using deep density estimators trained on the demonstration trajectories, avoiding the instability issues of adversarial methods. We demonstrate that using the state transition log-probability density as a reward signal for forward reinforcement learning translates to matching the trajectory distribution of the expert demonstrations, and experimentally show good recovery of the true reward signal as well as state of the art results for imitation from observation on locomotion and robotic continuous control tasks.
Lung Cancer Cells That Survive Ionizing Radiation Show Increased Integrin alpha 2 beta 1-and EGFR-Dependent Invasiveness

Ionizing radiation (IR)-enhanced tumor invasiveness is emerging as a contributor to the limited benefit of radiotherapy; however, its mechanism is still unclear. We previously showed that subcloned lung adenocarcinoma A549 cells (P cells), which survived 10 Gy IR (IR cells), acquired high invasiveness in vitro . Here, we tried to identify the mechanism by which IR cells increase their invasiveness by examining altered gene expression and signaling pathways in IR cells compared with those in P cells. To simulate the microenvironment in vivo , cells were embedded in a three-dimensional (3D) collagen type I gel, in which the IR cells were elongated, while the P cells were spherical. The integrin expression pattern was surveyed, and expression levels of the integrin a 2 and b 1 subunits were significantly elevated in IR cells. Knockdown of a 2 expression or functional blockade of integrin a 2 b 1 resulted in a round morphology of IR cells, and abrogated their invasion in the collagen matrix, suggesting the molecule’s essential role in cell spread and invasion in 3D collagen. Epidermal growth factor receptor (EGFR) also presented enhanced expression and activation in IR cells. Treatment with EGFR tyrosine kinase inhibitor, PD168393, decreased the ratio of elongated cells and cell invasiveness. Signaling molecules, including extracellular signal- regulated kinase-1/2 (Erk1/2) and Akt, exhibited higher activation in IR cells. Inhibition of Akt activation by treating with phosphoinositide 3-kinase (PI3K) inhibitor LY294002 decreased IR cell invasion, whereas inhibition of Erk1/2 activation by mitogen-activated protein kinase kinase (MEK) inhibitor U0126 did not. Our results show that integrin a 2 b 1 and EGFR cooperatively promote higher invasiveness of IR-survived lung cancer cells, mediated in part by the PI3K/Akt signaling pathway, and might serve as alternative targets in combination with radiotherapy. Science and Technology. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
The effects of β -glucans on intestinal health

also appear to be associated with altered intestinal permeability [5, 7]. However, certain food components can have a positive modulating effect on parameters of intestinal health, either directly or indirectly (through the formation of bioactive metabo-lites), thus reducing the risk of disease. It appears that such a modulation can be achieved Abstract The rising incidence of intestinal diseases combined with the high level of suffering and loss of quality of life leads to a growing interest in prevention strategies that are easy to implement. Such strategies include the deliberate consumption of more fiber-rich foods, and espe-cially those with a high β -glucan content. Whereas there has been much discussion about the potential of β -glucans to lower cholesterol and blood glucose levels to date, the present article focuses on summarizing papers investigating how β -glucans affect the intestinal environment, the intestinal barrier, the intestinal immune system, and intestinal inflammation.
EFFICACY OF BACTERIOPHAGE AGAINST MULTIDRUG RESISTANT PSEUDOMONAS AERUGINOSA ISOLATES

Pseudomonas aeruginosa , an increasingly widespread opportunistic human pathogen, is the most common gram-negative bacterium found in nosocomial infections, the most serious of which include malignant external otitis, endophthalmitis, endocarditis, meningitis, pneumonia, and septicemia. Infections due to Pseudomonas aeruginosa are being treated with different antibiotics but its emerging resistance to several antibiotic groups is leading to difficulty in treatment of infected patients . In order to combat infections of antibiotic resistant P. aeruginosa bacteriophage therapy is a potential substitute. This study isolated P. aeruginosa -lytic bacteriophages from sewage waste water and evaluated their efficacy in vitro and in vivo against multidrug resistant P. aeruginosa isolates from wounds of burn patients attending the Allied Hospital, Faisalabad, Pakistan. In vivo efficacy of bacteriophage was determined using rabbit as a wound model. Prevalence of multidrug (MDR) P. aeruginosa was 60% and among the 6 MDR isolates 4 could be lysed (clear or turbid plaques) by the isolated bacteriophage samples, which was also effective in attenuating MDR P. aeruginosa infected wound healing in rabbit. These results suggest the potential of bacteriophage therapy in the treatment of MDR P. aeruginosa infection.
Non-healing ulcer on great toe treated with ADM

Foot ulcers are a common complication of diabetes that is not being managed through methods such as diet, exercise, and insulin treatment. Ulcers are formed as a result of skin tissue breaking down and exposing the layers underneath. T he management and successful treatment of diabetic wounds represents a significant therapeutic challenge. To this end, the development of novel therapies and biological dressings has gained increased interest. Acellular matrix therapy has shown promise in the treatment of diabetic foot ulcers (DFUs) in several studies.
Hidden Markov Model (HMM) based Intrusion Detection System (IDS)

Networked Telemetry faces the threat of intrusion like any other cyber network. In this paper, we address the problem of modeling an Intrusion Detection System (IDS) using Hidden Markov Model (HMM). It is part of a bigger objective towards capturing and analyzing network traffic to identify anomalous traffic which in turn will be used to alarm a system administrator. The network traffic analysis phase involves feature extraction, dimension reduction and vector quantization (VQ) techniques which play a significant role in large data sets as the number of data being transmitted is increasing day by day from one network to another. The IDS framework developed makes use of multi-class HMM where each of the HMM layers are trained for a specific network traffic type. In order to test the resulting model’s capability to predict anomalous traffic, the system is tested with a testing data set. Performance of the model against the KDD ‘99 dataset demonstrates accuracy greater that 99%.
3,4 Markers of Astrocyte Reactivity in in vitro Models of Blast-Induced Neurotrauma

 Short Abstract — Astrocyte reactivity is a response often to mechanical stimulation that is defined by biochemical changes and increased proliferation. There is a growing need to understand this reactive response in relation to insult associated with common mechanisms of traumatic brain injuries. This study aimed to characterize the response of astrocytes after exposure to overpressure using both two- and three-dimensional models. Structural and other related biomarkers were quantitatively assessed at acute time points after exposure. Results indicate that cytoskeletal structure of the cells was not compromised and some reactive markers indicate different time periods of activation of the two- and three-dimensional