Miracle-dz/UniFAR-FTUs huggingface dataset:
A new perspective of vasculogenic mimicry: EMT and cancer stem cells (Review)

Vasculogenic mimicry (VM), a new pattern of tumor microcirculation, is important for the growth and progression of tumors. Epithelial-mesenchymal transition (EMT) is pivotal in malignant tumor progression and VM formation. With increasing knowledge of cancer stem cell (CSC) phenotypes and functions, increasing evidence suggests that CSCs are involved in VM formation. Recent studies have indicated that EMT is relevant to the acquisition and maintenance of stem cell-like characteristics. Thus, in this review we discuss the correlation between CSCs, EMT and VM formation.
Achievable Rate Regions for Cooperative Relay Broadcast Channels with Rate-limited Feedback

Achievable rate regions for cooperative relay broadcast channels with rate-limited feedback are proposed. Specifically, we consider two-receiver memoryless broadcast channels where each receiver sends feedback signals to the transmitter through a noiseless and rate-limited feedback link, and meanwhile, acts as relay to transmit cooperative information to the other receiver. It's shown that the proposed rate regions improve on the known regions that consider either relaying cooperation or feedback communication, but not both.
An Adaptive Global Reduction Algorithm for Wormhole-routed 2d Mesh Networks an Adaptive Global Reduction Algorithm for Wormhole-routed 2d Mesh Networks

This paper presents a global reduction algorithm for wormhole-routed 2D meshes. Well-known reduction algorithms that are optimized for short vectors have complexity O(M log N), where N = n n is the number of nodes, and M the vector length. Algorithms suitable for long vectors have complexity O(p N +M). Previously known asymptotically optimal algorithms with complexity O(logN + M) incur inherent network contention among constituent messages. This paper proposes a 2D global reduction algorithm that \adapts" to the given vector length. Speciically, the algorithm has complexities O(M logN) for short vectors, O(log N + M) for medium-sized vectors, and O(p N + M) for suuciently long vectors. The O(p N + M) version is preferred to the O(logN + M) version for long vectors, due to its small coeecient associated with M, which is the dominating factor for reduction operations on such vectors. The algorithm is contention-free in a lock-step execution environment, such as an SIMD machine. Under MIMD or asynchronous execution models, depth contention (contention among message-passing steps) may occur. However, simulation studies of the proposed algorithm show that the eeect of depth contention on the actual performance is negligible.
Clutter filter design for ultrasound color flow imaging

For ultrasound color flow images with high quality, it is important to suppress the clutter signals originating from stationary and slowly moving tissue sufficiently. Without sufficient clutter rejection, low velocity blood flow cannot be measured, and estimates of higher velocities will have a large bias. The small number of samples available (8 to 16) makes clutter filtering in color flow imaging a challenging problem. In this paper, we review and analyze three classes of filters: finite impulse response (FIR), infinite impulse response (IIR), and regression filters. The quality of the filters was assessed based on the frequency response, as well as on the bias and variance of a mean blood velocity estimator using an autocorrelation technique. For FIR filters, the frequency response was improved by allowing a non-linear phase response. By estimating the mean blood flow velocity from two vectors filtered in the forward and backward direction, respectively, the standard deviation was significantly lower with a minimum phase filter than with a linear phase filter. For IIR filters applied to short signals, the transient part of the output signal is important. We analyzed zero, step, and projection initialization, and found that projection initialization gave the best filters. For regression filters, polynomial basis functions provide effective clutter suppression. The best filters from each of the three classes gave comparable bias and variance of the mean blood velocity estimates. However, polynomial regression filters and projection-initialized IIR filters had a slightly better frequency response than could be obtained with FIR filters.
Successful Versus Failed Adaptation to High-Fat Diet–Induced Insulin Resistance

OBJECTIVE Obesity is a known risk factor for type 2 diabetes. However, most obese individuals do not develop diabetes because they adapt to insulin resistance by increasing β-cell mass and insulin secretion. Islet pathology in type 2 diabetes is characterized by β-cell loss, islet amyloid derived from islet amyloid polypeptide (IAPP), and increased β-cell apoptosis characterized by endoplasmic reticulum (ER) stress. We hypothesized that IAPP-induced ER stress distinguishes successful versus unsuccessful islet adaptation to insulin resistance. RESEARCH DESIGN AND METHODS To address this, we fed wild-type (WT) and human IAPP transgenic (HIP) rats either 10 weeks of regular chow or a high-fat diet and prospectively examined the relations among β-cell mass and turnover, β-cell ER stress, insulin secretion, and insulin sensitivity. RESULTS A high-fat diet led to comparable insulin resistance in WT and HIP rats. WT rats compensated with increased insulin secretion and β-cell mass. In HIP rats, in contrast, neither β-cell function nor mass compensated for the increased insulin demand, leading to diabetes. The failure to increase β-cell mass in HIP rats was the result of ER stress–induced β-cell apoptosis that increased in proportion to diet-induced insulin resistance. CONCLUSIONS IAPP-induced ER stress distinguishes the successful versus unsuccessful islet adaptation to a high-fat diet in rats. These studies are consistent with the hypothesis that IAPP oligomers contribute to increased β-cell apoptosis and β-cell failure in humans with type 2 diabetes.
College Student Attendance System Based on Face Recognition

In order to improve the efficiency of management and enhance the atmosphere of learning, in this paper, we develop a set of attendance system based on face recognition using the deep semi-NMF algorithm. Specifically, the system can automatically detect and recognize faces from the video images, and then gets its detailed information on attendance from the database. Moreover, the system not only performs simply, but also can be of great benefit to the whole educational field. The experimental results on real applications show that the system is effective and efficient.
Characterizing tropical overshooting deep convection from joint analysis of CloudSat and geostationary satellite observations

Tropical overshooting deep convection (ODC) plays an important role in affecting the heat and constituent budgets of the upper troposphere and lower stratosphere. This study investigates the properties and behaviors of such intense deep convection using a combination of CloudSat observations and geostationary satellite data. Our study approaches the subject from two unique perspectives: first, W‐band cloud profiling radar (CPR) observations from CloudSat are used, which add to our knowledge of the internal vertical structure of tropical ODC; second, each snapshot observation from CloudSat is cast into the time evolution of the convective systems through joint analysis of geostationary satellite data, which provides a lifecycle view of tropical ODC. Climatology of tropical ODC based on CloudSat data is first presented and compared with previous works. Various parameters from CloudSat observations pertaining to cloud vertical extent, convective intensity, and convective environment are analyzed. Although results broadly agree with previous studies, we show that CloudSat CPR is capable of capturing both small cloud particles and large precipitation‐size particles, thus presenting a more complete depiction of the internal vertical structure of tropical ODC. Geostationary satellite observations are analyzed in conjunction with CloudSat data to identify the life stage of the convective systems (CSs) in which ODC is embedded. ODC associated with the growing, mature, and dissipating stage of the CSs represents, respectively, 66.2%, 33.4%, and 0.4% of the total population. Convective intensity of the ODC is found to be stronger during the growing stage than the mature stage.
Realising RosettaNet PIP Compositions as Web Service Orchestrations - A Case Study

A world of ever growing competition not only forces enterprises to continuously optimise their private business processes but also to integrate their business processes with their business partners along the supply chain. RosettaNet is a non-profit standards or- ganisation dedicated to supporting B2B integration. The basis for integrating business processes with RosettaNet are so-called Partner Interface Processes (PIPs) that describe in detail the exchange of business documents for various purposes. We have investigated models for the composition of PIPs for more complex business inter- actions. The implementation of these models frequently demands for truly distributed computation because cen- tral technical infrastructure is either not available or prohibited by business politics. This paper is dedicated to the distributed implementa- tion of RosettaNet PIP compositions. We propose Web Services as enabling technique for implementation and WSBPEL for orchestrating Web Service calls. Speci- fying the correct types of calls in the correct order is a challenging task, particularly if the collaboration itself is complex and is to be executed using insecure communication media. This paper therefore proposes a roadmap for realising RosettaNet PIP compositions as robust and flexible Web Service orchestrations.
Variability in the relationship between mean plasma glucose and HbA1c: implications for the assessment of glycemic control.

BACKGROUND Previous studies have shown a single linear relationship between mean plasma glucose (MPG) and hemoglobin A(1c) (HbA(1c)). We examined the relationship in different treatment groups of patients with type 1 diabetes participating in the Diabetes Control and Complications Trial (DCCT). METHODS Seven-point glucose profiles (premeal, postmeal, and bedtime) and HbA(1c) were measured quarterly during the DCCT. We studied measurements from (a) intensively treated patients at study commencement, (b) intensively treated patients after stabilization of their glycemia (from 6 months onward), and (c) conventionally treated patients from 6 months onward. Only complete glucose profile and HbA(1c) pairings were considered (n = 589, 11 483, and 11 855, respectively). RESULTS From 6 months into the trial, conventionally treated patients had consistently higher MPG concentrations than intensively treated patients at any given HbA(1c) value (mean difference, 1.6 mmol/L at 7% HbA(1c), increasing to 2.8 mmol/L at 11% HbA(1c)). Similarly, at the same HbA(1c), the MPG of intensively treated patients at baseline was higher than in the same individuals after 6 months of intensive treatment (1.2 mmol/L difference at 7% HbA(1c), increasing to 4.6 mmol/L at 11% HbA(1c)). CONCLUSIONS The relationship between MPG and HbA(1c) is not constant but differs depending on the glycemic control of the population being studied. Having lower mean glucose at the same HbA(1c) may help explain why intensive DCCT treatment appeared intrinsically linked to both increased hypoglycemia and decreased microvascular complications compared with conventional treatment. These findings may also have implications for expressing HbA(1c) as mean blood glucose equivalent.
Rapid Inference on a novel AND / OR graph : Detection , Segmentation and Parsing of Articulated Deformable Objects in Cluttered Backgrounds

In this paper we formulate a novel AND/OR graph representation capable of describing the different configurations of deformable articulated objects such as horses. The representation makes use of the summarization principle so that lower level nodes in the graph only pass on summary statistics to the higher level nodes. The probability distributions are invariant to position, orientation, and scale. We develop a novel inference algorithm that combined a bottom-up process for proposing configurations for horses together with a top-down process for refining and validating these proposals.The algorithm was applied to the tasks of detecting, segmenting and parsing horses (to the best of our knowledge, no computer vision algorithms are capable of solving all these tasks). We demonstrate that the algorithm is fast and achieves the state of the art performance (by evaluations on a challenging public dataset). Our approach can be applied to a range of other problems in machine intelligence.
From Semi-Heuristic Fuzzy Techniques to Optimal Fuzzy Methods: Mathematical Foundations and Applications

Fuzzy techniques have been successfully used in various application areas ranging from control to image processing to decision making In all these applications there is usually a general idea and then there are several possible implementations of this idea e g we can use di erent membership functions di erent and and or operations di erent defuzzi cations etc In the rst approximation the results are usually reasonably robust and independent on this choice so any heuristic or semi heuristic choice works OK However if we want to further improve the semi heuristic good enough con trol or image processing techniques we must actually make the selection that would lead to an optimal fuzzy method Even if we know the exact optimality criterion the resulting optimization problem is so complicatedly non linear that often no known optimization techniques can be used In many real life situations we do not even know the exact criterion the relative quality of di erent controls or image processing techniques may be not by exact numerical criteria but rather by expert opinions which are themselves fuzzy In this paper we describe a general mathematical technique for solv ing such optimization problems This technique is based on the group theoretic symmetry methodology a methodology which is one of the main successful tools of modern physics This methodology has lead us to the justi cation of many heuristic formulas in fuzzy logic fuzzy control neural networks etc many examples are presented in our Kluwer book Applications of continuous mathematics to computer science We also present new applications of this techniques including appli cations to optimal fuzzy control and to optimal fuzzy image processing
Implications of Green Tea and Its Constituents in the Prevention of Cancer via the Modulation of Cell Signalling Pathway

Green tea is commonly used as a beverage worldwide, especially in China, Japan, Morocco, and Saudi Arabia. Green tea and its constituents have been considered very effective in the prevention and treatment of various diseases. It contains a variety of catechins, which show a pivotal role in the modulation of biological activities and also act as chemopreventive agents. Earlier studies have confirmed that green tea and its chief constituent epigallocatechin gallate (EGCG) have a potential role in the management of cancer through the modulation of cell signaling pathways. In this review, we focused on the beneficial effects of green tea and its constituents in the cancer prevention and treatment and its impact on modulation of molecular pathways.
Low Complexity With MSF Approach to Acoustic Echo Canceller

In this paper we present the Multiple SubFilters (MSF) parallel structure, LMS adaptive algorithm, for acoustic echo cancellation. The performance of the MSF based echo canceller has been compared with conventional echo canceller which is a Single Long Filter (SLF) used to model the impulse response of the acoustic echo channel. The convergence performance of the MSF parallel structure is studied for common error and different error adaptive algorithms. Simulation results show that MSF with both adaptation algorithms provide better convergence over the SLF. However, the steady state error performance of the different error adaptation algorithm is poor as compared to that of common error as well as that of SLF adaptation algorithm. The sacrifice in steady state error performance can be compensated to achieve fast convergence by introducing independent adaptation step size as there is decoupled weight updation equation of each sub-filter. The combination of both the adaptation algorithm in MSF can achieve a trade-off between steady state and convergence rate. A scheme named as selective coefficient update (SCU) algorithm is proposed in which only few coefficients are updated at each iteration.
The Potential of Accelerating Early Detection of Autism through Content Analysis of YouTube Videos

Abstract Autism is on the rise, with 1 in 88 children receiving a diagnosis in the United States, yet the process for diagnosis remains cumbersome and time consuming. Research has shown that home videos of children can help increase the accuracy of diagnosis. However the use of videos in the diagnostic process is uncommon. In the present study, we assessed the feasibility of applying a gold-standard diagnostic instrument to brief and unstructured home videos and tested whether video analysis can enable more rapid detection of the core features of autism outside of clinical environments. We collected 100 public videos from YouTube of children ages 1–15 with either a self-reported diagnosis of an ASD (N = 45) or not (N = 55). Four non-clinical raters independently scored all videos using one of the most widely adopted tools for behavioral diagnosis of autism, the Autism Diagnostic Observation Schedule-Generic (ADOS). The classification accuracy was 96.8%, with 94.1% sensitivity and 100% specificity, the inter-rater correlation for the behavioral domains on the ADOS was 0.88, and the diagnoses matched a trained clinician in all but 3 of 22 randomly selected video cases. Despite the diversity of videos and non-clinical raters, our results indicate that it is possible to achieve high classification accuracy, sensitivity, and specificity as well as clinically acceptable inter-rater reliability with nonclinical personnel. Our results also demonstrate the potential for video-based detection of autism in short, unstructured home videos and further suggests that at least a percentage of the effort associated with detection and monitoring of autism may be mobilized and moved outside of traditional clinical environments.
Research and Practice on the Teaching Reform of Computer Fundamentals Course

Aiming at the problems in traditional teaching methods of computer fundamentals course, a series of reform measures are put forward, such as innovating teaching methods, paying attention to cultivate the practical ability of students, and constructing network teaching platform to enrich the teaching resources and enhance the communication between teachers and students. Students can download many resources about the course from the network teaching platform, and can also study online, test online, and discuss online with teachers or other classmates freedomly by using the network teaching platform. The teaching practice shows that the teaching reform of the course gets good results, the shortage of teaching resources problem is solved, and the operation ability and innovation consciousness of the students are improved greately.
Sport surfaces in show jumping

Properties of sport surfaces influence the occurrence of injuries and the performance of equine athletes. The sports governing body seeks to develop standards for safety and performance of show jumping surfaces. Limited information is available to guide this process. Objective methods are warranted in order to define surface properties that can be associated to injury and performance data. Description of the discipline-specific interaction between the horse and the ground is important in order to display the characteristics and diversity of loading patterns applied to the sport surfaces as well as to enable understanding of the mechanical challenges that lead to injuries. The aims of this thesis were to describe the hoof-ground interaction in show jumping and to study functional properties of surfaces through rider assessments and by using a standardized biomechanical method that enables comparisons between arenas. Hoof landing characteristics of elite horses in jump landing from 1.30–1.50 m competition fences on two different surfaces were evaluated from high-speed videos. Hoof landing kinematics differed among the leading/trailing fore and hind limbs. Data increased our understanding of hoof-ground interaction and related events, which is a prerequisite for developing surface testing devices. Hoof impact was also investigated using hoof-mounted accelerometers in an experimental setup with five horses in canter, jump take-off and landing. Leading/trailing fore and hind limbs, stride types and surface affected the hoof-surface impact. The vertical deceleration at impact ranked in the same order, for three surface conditions, as when the impact from a metal hoof of a biomechanical surface testing device was measured. Subjective assessments of surface properties by riders were compared to objective in-situ measurements of the same properties with a biomechanical surface tester in 25 show jumping competition and warm-up arena surfaces at top-level events. Significant associations between the subjective and objective assessments were found. The data from this thesis contribute to the description of the discipline-specific hoof-surface interaction in show jumping. The objective method used for in-situ characterisation of functional surface properties can enable further objective comparisons which in the future can be related to injury and performance data of show jumping surfaces.
Investigation of Matlab® as Platform in Navigation and Control of an Automatic Guided Vehicle Utilising an Omnivision Sensor

Automatic Guided Vehicles (AGVs) are navigated utilising multiple types of sensors for detecting the environment. In this investigation such sensors are replaced and/or minimized by the use of a single omnidirectional camera picture stream. An area of interest is extracted, and by using image processing the vehicle is navigated on a set path. Reconfigurability is added to the route layout by signs incorporated in the navigation process. The result is the possible manipulation of a number of AGVs, each on its own designated colour-signed path. This route is reconfigurable by the operator with no programming alteration or intervention. A low resolution camera and a Matlab® software development platform are utilised. The use of Matlab® lends itself to speedy evaluation and implementation of image processing options on the AGV, but its functioning in such an environment needs to be assessed.