Miracle-dz/UniFAR-FTUs huggingface dataset:
Decellularized extracellular matrix as scaffold for cancer organoid cultures of colorectal peritoneal metastases

ABSTRACT Peritoneal metastases (PM) from colorectal cancer (CRC) are associated with poor survival. The extracellular matrix (ECM) plays a fundamental role in modulating the homing of CRC metastases to the peritoneum. The mechanisms underlying the interactions between metastatic cells and the ECM, however, remain poorly understood, and the number of in vitro models available for the study of the peritoneal metastatic process is limited. Here, we show that decellularized ECM of the peritoneal cavity allows the growth of organoids obtained from PM, favoring the development of three-dimensional (3D) nodules that maintain the characteristics of in vivo PM. Organoids preferentially grow on scaffolds obtained from neoplastic peritoneum, which are characterized by greater stiffness than normal scaffolds. A gene expression analysis of organoids grown on different substrates reflected faithfully the clinical and biological characteristics of the organoids. An impact of the ECM on the response to standard chemotherapy treatment for PM was also observed. The ex vivo 3D model, obtained by combining patient-derived decellularized ECM with organoids to mimic the metastatic niche, could be an innovative tool to develop new therapeutic strategies in a biologically relevant context to personalize treatments.
Saxagliptin: A potential doping agent? A randomized, double‐blinded, placebo‐controlled, and crossover pilot study in young active men

Neuropeptide Ys (NPYs) contribute to sympathetic‐adreno stimulation: NPY1‐36 potentiates the effects of catecholamines (CATs), whereas NPY3‐36 inhibits CAT release. We sought to investigate whether inhibiting dipeptidyl‐peptidase‐4 (DPP4), cleaving NPY1‐36 into NPY3‐36, leads to increased NPY1‐36 potentiating effects and reduced NPY3‐36 inhibitory effects on CATs, thereby improving endurance performance. Seven male participants (age 27 ± 3 years, BMI 23.1 ± 2.4 kg/m2) performed time‐to‐exhaustion cycling exercise at 95% of peak power output with either placebo, or saxagliptin, a DPP4 inhibitor. Oxygen consumption (V̇O2), heart rate variability, NPY1‐36, NPY3‐36, catecholamines, and lactate were measured at several time points before, during, and after exercise. With saxagliptin, DPP4 activity (12.7 ± 1.6 vs. 0.2 ± 0.3 U/L, p = 0.001; d = 10.7) was decreased at rest, while NPY3‐36 (1.94 ± 0.88 vs. 0.73 ± 0.22 pm; p < 0.001; d = 2.04) decreased and NPY1‐36 increased during exercise (2.64 ± 2.22 vs. 4.59 ± 2.98 pm; p < 0.01; d = 0.19). CATs were unchanged. Time‐to‐exhaustion was 32% higher with saxagliptin. The difference in time‐to‐exhaustion between placebo and saxagliptin was correlated with NPY1‐36 differences (R = 0.78, p < 0.05). Peak V̇O2 and other cardio‐respiratory values were not different, whereas peak NPY concentrations were higher with saxagliptin. DPP4 blockade improved performance, increased NPY1‐36, and decreased NPY3‐36 concentrations which may have potentiating effects on the influences of CATs. However, DPP4 is involved in many different actions, thus NPYs are one group of factors that may underly its performance‐enhancing effects; further studies are required to determine the exact mechanisms.
PROX1 transcription factor controls rhabdomyosarcoma growth, stemness, myogenic properties and therapeutic targets

Significance Rhabdomyosarcoma is an aggressive pediatric soft-tissue cancer. Identification of RMS precursor cells and models has been a challenge due to unknown molecular mechanisms that drive the common proliferative myogenic phenotype. Our study revealed that the PROX1 transcription factor is essential for the growth and myogenic features of RMS, and its downregulation reverts RD cells to a phenotype resembling benign mesenchymal stem cells. Our findings demonstrate that the effects of PROX1 on RMS cell growth are mediated by FGFR, predominantly by FGFR1 and FGFR4, which were found to compensate for each other. This study places PROX1 as a major mediator of RMS characteristics and development and suggests that pan-FGFR inhibitors provide a promising option for the treatment of RMS.
On Hotelling's Approach to Testing for a Nonlinear Parameter in Regression

Abstract : The method suggested by Hotelling (1939) to test for a nonlinear parameter in a regression model is reviewed. Using the method of Weyl (1939), we derive a simple expression for the volume of a tube about a two dimensional manifold with boundary embedded in the unit sphere in I delta R sub n. Applications to testing for a single harmonic of undetermined frequency and phase and to testing for a change-point in linear regression are discussed. Keywords: Differential geometry.
Systematic determination of muscle groups and optimal stimulation intensity for simultaneous TMS mapping of multiple muscles in the upper limb

Transcranial magnetic stimulation has been used to assess plastic changes in the cortical motor representations of targeted muscles. The present study explored the optimal settings and stimulation intensity for simultaneous motor mapping of multiple upper‐limb muscles across segments. In 15 healthy volunteers, we evaluated cortical representations simultaneously from one muscle in the shoulder, two in the upper arm, two in the forearm, and two intrinsic hand muscles, using five stimulation intensities, ranging from 40% to 100% of the maximum stimulator output. We represented the motor map area acquired at each intensity as a percentage of the maximum for each muscle. We defined a motor map area between 25% and 75% of the maximum as the optimal area size with sufficient scope for both up‐ and down‐regulation, and stimulation intensities producing the map area size within this range as the optimal intensities. We found that motor maps with optimal area sizes could be produced simultaneously for the four distal muscles of the forearm and hand in most participants when the stimulation intensity was set at 120–140% of the resting motor threshold (RMT) of the first dorsal interosseous. For the remaining three proximal muscles, motor maps with optimal area sizes were produced only in a few participants, even when using a higher intensity (180–220% RMT). These findings suggest that cortical representations can be assessed simultaneously in a group of distal muscles using a relatively low stimulation intensity, while a separate operation is required to assess that of the proximal muscles.
Relation between Raman frequency and triaxial stress in Si for surface and cross-sectional experiments in microelectronics components

This paper provides a detailed description explaining how to calculate the relation between the silicon Raman frequency and local stress or strain in the silicon, applied to stress measurements in microelectronics. This relation is well known for measurements from the (100) surface of silicon. However, it is often used in the wrong way, neglecting non-zero stress tensor elements. Especially, in current 3D microelectronics technology, where the stress caused by through Si vias or micro-bumps is of large importance, the vertical stress component, which highly affects the measured Raman frequency shift, is often erroneously neglected. In addition, the equations for the (100) surface are also often used incorrectly for cross-sectional measurements from a (110) surface. In this paper, different ways to calculate the relation between Raman frequency and triaxial stress, and the related Raman peak intensities, are discussed in detail.
A method of single-line-to-ground fault line selection in distribution network based on the comprehensive wavelet energy ratio

The previous fault line selection method usually used the zero-sequence signal after the fault to select the fault feeders, but the connection of the arc suppression coil reduces the fault current and the fault zero-sequence component, which makes the fault line difficult to select. For the distribution network with mixed cables, the performance of the zero-sequence current flowing through different types of non-faulty lines is also quite different. These circumstances obstructed fault line selection. In this paper, the voltage transient process after fault is analyzed in detail. After a single-phase grounding fault occurs in the system, the characteristic frequency band of fault voltage is extracted by discrete wavelet decomposition, and the comprehensive wavelet energy ratio representing the transient content of fault voltage is constructed to select the fault line of single-phase grounding. Simulation experiments of the algorithm are analyzed by PSCAD / EMTDC, and the results show that the proposed algorithm can accurately and reliably select the faulty line.
Detection of mask-wearing based on improved YOLOv3

To control the spread of the virus, mask detection is crucial in public areas, especially after the outbreak of Covid-19 pneumonia. This paper aims to improve the accuracy and precision of mask detection. This study improves mask-wearing detection by adding data augmentation, using the smooth label to replace the one-hot vector, and customizing the network connection of the YOLOv3 network. Through these targeted improvements, the average precision of face with mask detection has been increased by 0.9%, and the average precision of face without mask detection has been increased by 2.9%, which implies that it is a better strategy to do mask detection based on YOLOv3. By inputting photographs, the network can check, with high accuracy, whether the pedestrians in the picture wear masks or not, which will be a good supplementary to epidemic prevention and control.
Handling Wavelet Expansions in numerical Methods

Wavelet expansions have drawn a lot of attention in recent decades. Wavelets originate from signal analysis, and one of the purposes is data compression. The ability to compress data can also be used to reduce the amount of computation work in a numerical simulation.A family of wavelets forms a basis for a function space. Most adaptive wavelet methods are based on expansions of functions in a freely selectable subset of such a basis. This avoids the often expensive, grid generation step needed in most other adaptive methods, but leads to more complicated bookkeeping.A large part of this thesis is devoted to the problem of performing this bookkeeping efficiently. Some methods divide the wavelet expansion into parts of decreasing importance. Using an approximate division is often more efficient than using the best division, which requires all terms in the expansion to be sorted.
Application of big data analysis in enterprises under the background of intelligent manufacturing

With the widespread promotion of intelligent manufacturing and the rise of cloud computing and artificial intelligence, big data analysis plays an increasingly important role in the production and operation of manufacturing enterprises. Mining and visual analysis of the massive data of manufacturing enterprises is conducive to discovering the hidden laws and causal relationships of the data, so as to extract useful information and help enterprises implement better decision-making. This paper expounds big data analysis from three aspects: data life cycle management, big data analysis types and key technologies involved, analyzes the application of big data analysis in the field of intelligent manufacturing, and proposes a big data analysis architecture for manufacturing enterprises. Finally, corresponding countermeasures and suggestions are put forward for the problems existing in big data analysis under the background of intelligent manufacturing.
Research on upper limb rehabilitation system based on visual feedback

Patients with the loss of limb motor function often suffer from neurological damage of brain in the presence of normal limb neural pathways, resulting in reduced or lost limb movement. By observing the mirror image of the healthy limb movement, the relevant motor perception areas of the patient's brain can be stimulated and the motor and brain functions of the affected limb could also be remodeled. Based on the above theoretical support, this study designed a visual feedback upper limb rehabilitation system based on an attentional neural network, which analyzed and modelled the electromyography (EMG) of the upper limb through a new attentional neural network named MCAT-net. The proposed MCAT-net could determine the movement intention of the healthy upper limb with an accuracy about 91.04%. Further, based on MCAT-net, a visual feedback upper limb rehabilitation system is designed, which could receive and generate the augmented reality models of the affected upper limb for the patients who need the purpose of visual rehabilitating stimulation.
Incremental learning using manifold feature space for synthetic aperture radar target recognition

While deep neural network technology brings high recognition accuracy to the field of synthetic aperture radar automatic target recognition, it also produces the problem of catastrophic forgetting. Currently, how to extract features for distinguishing new and old classes has become the main bottleneck for incremental learning performance improvement. In this paper, we propose a new incremental learning method to better distinguish between new and old classes. We use the trained neural network to extract the features of the old samples and utilize the k -means to select representative old samples in the feature space, and then train the new model with distillation loss. Through the experiments on the MSTAR dataset, our method has better incremental learning performance on SAR images under the same training time.
Direct fabrication of polyimide waveguide grating by synchrotron radiation

Synchrotron radiation induces a change in the refractive index of a fluorinated polyimide by an order of 10−2, which is about ten times larger than the change it induces in silica glass irradiated by ultraviolet light, presumably due to fluorine detachment and subsequent volume compaction. We have fabricated a 0.51-μm-period grating structure in an embedded waveguide through a 15-μm-thick overcladding by using an x-ray mask with a spatially modulated pattern. The grating is fabricated at a dose of 160 A s and shows a reflectivity of 60% and a full width at half maximum as narrow as 0.25 nm at around a wavelength of 1.55 μm.
COVID-19 and pneumonia detection using x-ray image-based deep learning methods

Globally, pneumonia is the leading cause of death for young people and children. An x-ray of the chest is usually used to diagnose pneumonia by a trained specialist. However, the process is tedious and can result in disagreements among radiologists. It is possible to improve diagnostic accuracy through the use of computer-aided diagnostic systems. In this work, the ResNet model was selected to work as the COVID-19 and pneumonia detector based on x-ray image. Several experiments are conducted on to achieve an optimal result.
In-time and real-time intelligent landslide identification method based on CNN

Landslide is a very serious geological disaster. When the heavy rain occurs in the area with loose soil layer, the mountain becomes loose after strong erosion of rain water. As soon as the threshold of adhesion force between mud and mountain base is broken, the powerful harmful force formed by landslides will bury houses, people and cars. Traditional detection methods, represented by InSAR or LIDAR, were capable of identifying landslides to a certain extent, but in-time and real-time performance were not good enough. In this paper, an intelligent identification method based on convolutional neural network(CNN) is proposed, which can in-time and real-time to identify landslides, thus greatly reducing the loss of life, health and property.
Train wheel size prediction based on EEMD-LSTM model

Predicting the wear state of the wheels and predicting the possible problems of the wheels in advance can help guide and optimize the maintenance and repair work of the vehicles, and reduce the economic losses caused by the untimely vehicle maintenance scheduling. In this paper, the long short-term memory (LSTM) recurrent network is used as the prediction model. In order to improve the prediction accuracy of the network model, the Ensemble Empirical Mode Decomposition (EEMD) algorithm is introduced to stabilize the non-stationary wear sequence and improve the training effect neural network. Firstly, the non-stationary original wheel diameter sequence is decomposed into multiple stationary sub-sequences by the EEMD algorithm, and then the training and prediction of the LSTM model are completed separately based on each component. The experimental results show that after EEMD processing, the prediction effect of tread wear has been improved, which verifies the improvement effect of EEMD processing on the prediction accuracy of neural network.
Effect of competency on employee performance and the mediating role of commitment: An empirical investigation in the IT Industry

Abstract Competency and commitment are the two major determinants of employee performance in the IT industry. With growing competition and demand, IT professionals are always at the edge to showcase performance. The present study discusses the issue by utilizing the dimension of competency from the Iceberg model, the commitment model by Allen & Meyer (1990). The study sought to ascertain the influence of competency on employee performance and commitment, as well as the function of commitment in mediating the relationship between competency and employee performance. A standardised questionnaire was created and disseminated to software company workers for this purpose. A total of 242 valid responses were collected from IT companies. SEM was employed to examine the association between the variables analysed as well as the hypothesis. The analysis concluded that the dimension of competence (knowledge, skills, and work attitude) positively impacts employee performance and commitment with (β = 0.57, 0.5, 0.48, 0.37, 0.41, 0.36) with p<0.05, indicating the acceptance of the hypothesis H1, H2, H3, H4, H5 & H6. Also, employee commitment had the highest impact on employee performance at β =0.76, p=. 000, CR =6.21. Hypothesis H7 is accepted and concluded that employee commitment acts and serves as a mediator between employee performance and employee competency. This research will help IT companies to better understand employees and incorporate strategies that will enhance organizational performance.
Ensemble of features for efficient classification of high-resolution remote sensing image

ABSTRACT Extracting feature is one of the important methods in classification of high-resolution remote sensing image. A good feature set can result in an efficient classification process. Recent trend moves in extracting the features from the image using neural networks with no human intervention. Our approach uses the deep convolutional neural network for extracting deep features. To still rise the efficiency of the extracted features, the proposed system combines the deep features with other features like Gabor features and novel reformed local binary pattern features. The features are combined and sent for classification. Then, the classification process is done to classify the images. The proposed system introduces two novel ideas, in its feature extraction implementation, namely (1) initialisation of filter values for the CNN and (2) change in local binary pattern feature extraction process. The experimental results are carried out with LISS IV Madurai image, and evaluation is done for the verification of the results. It is found that the system proposed produces good results when compared with other existing methods.
Comparative assessment of US and India’s exchange traded funds (ETFs): Performance evaluation of tailwinds and headwinds recommendations

Abstract Long-term worldwide investment trends show that exchange-traded funds (ETFs) are becoming popular for passive investing. Nifty Bees established in 2001 was the first ETF to follow passive equities assets in India. Here, we will take a closer look at the Indian ETF market, as well as key policy considerations, and how to proceed. To put things in perspective, given the maturity of the US ETF market, the study compares the Indian ETF market to the US wherever possible on both a qualitative and quantitative basis. That’s how the paper’s laid out. After a quick introduction to ETFs and their history in India, the study looks in detail at how the market is structured and who the major players in the market in detail. These two sections outline the industry’s tailwinds and headwinds. There are certain policy ideas that might help the business grow further. The findings of the study stated that US ETF are more traded in volume in comparison to Indian ETF.
Motion blur-free time-of-flight range sensor

Time-of-flight depth sensor provides faster and easier way to 3D scene capturing and reconstruction. The depth sensor, however, suffers from motion blur caused by any movement of camera or objects. In this manuscript, we propose a novel depth motion blur pixel detection and elimination method that can be implemented on any ToF depth sensor with light memory and computation resources. We propose a blur detection method using the relations of electric charge amount. It detects blur pixel at each depth value calculation step only by checking the four electric charge values by four internal control signals. Once we detect blur pixels, their depth values are replaced by any closest normal pixel values. With this method, we eliminate motion blur before we build the depth image with only few more calculations and memory addition.
Job satisfaction of women employees in different organizational work culture

Abstract Organizational culture is the gathering of ideas, concepts, the pattern of working conditions and relationships that separate one business enterprise from others. This affects unique humans differently due to how they think consciously. Unconsciously, making choices depends on what they see and listen to and do after feeling it. The study hypothesis is that an organization’s organizational tradition can envisage women employees’ job satisfaction. The significant shape of culture changed into domination, solidity and the rule of thumb of law. Most women employees would like to be in friendly surroundings wherein they agree, illicit relationships between colleagues succeed, private pursuits are considered, and crew work is rewarded. Ensuring the properly-being of personnel will enhance their productivity and productiveness and make businesses, organizations and corporations more viable, particularly in instances of economic emergency. The consequences of cutting-edge research can be carried out to develop domestic and overseas markets.