Miracle-dz/UniFAR-FTUs huggingface dataset:
Parameters optimization of VSC-MTDC control system to improve overall system stability

This paper introduces a multi-objective optimal method to coordinate the VSC-MTDC control system, which is aimed to simultaneously improve the dynamic performance of VSC-MTDC system and the rotor angle stability of the AC system. The coordinated control problem is formulated as an optimization problem where Particle Swarm Optimization (PSO) algorithm with the nonlinear time-domain-based objective function is employed to search the optimized parameters of VSC-MTdC controllers. The DC voltage is chosen as the key indicator that represents the VSC-MTDC system dynamic performance. So the multi-objective problem is mathematically represented by a composite set of objective functions comprising the DC voltage deviation of converters and the rotor angle deviation of generators. Time-domain simulations have been performed to assess the effectiveness of the proposed procedure.
An experimental animal model of spinal cord stimulation for pain.

In spite of the routine usage of spinal cord stimulation (SCS) as treatment of chronic pain, there is an insufficient understanding of the mechanisms underlying its effect. The method was originally developed as a spin-off from experiments demonstrating the inhibitory control of nociceptive signals by the activation of large afferent fibers, and on the basis of these findings the gate-control theory was advanced. Later experiments showed that stimulation of the dorsal columns can inhibit the relay of nociceptive impulses to second-order neurons in the dorsal horn. It should be emphasized that all these experiments were performed with acute noxious stimuli; it is now universally recognized that SCS in patients is preferentially, or exclusively, effective for chronic neuropathic types of pain. For these and other reasons the mode of action of SCS in clinical pain cannot be inferred from these early animal experiments. In ongoing studies we have used animal models of mononeuropathy (rat) in which we have applied SCS acutely or chronically with stimulation parameters similar to those used in patients. In these animals the first component of the flexor reflex appears with a lower stimulus threshold in the nerve lesioned than in the intact, sham-operated leg. SCS was applied at the approximate level of Th-XII during 10-20 min and produced a marked augmentation of the stimulus threshold. This abnormally high threshold was not normalized until 30-60 min after the end of SCS. In awake animals SCS was applied via an implanted spinal electrode and the effect on behavior changes associated with mononeuropathy was studied. (ABSTRACT TRUNCATED AT 250 WORDS)
Direct and indirect effects of light pollution on the performance of an herbivorous insect

Light pollution is a global disturbance with resounding impacts on a wide variety of organisms, but our understanding of these impacts is restricted to relatively few higher vertebrate species. We tested the direct effects of light pollution on herbivore performance as well as indirect effects mediated by host plant quality. We found that artificial light from streetlights alters plant toughness. Additionally, we found evidence of both direct and indirect effects of light pollution on the performance of an herbivorous insect, which indicates that streetlights can have cascading impacts on multiple trophic levels. Our novel findings suggest that light pollution can alter plant–insect interactions and thus may have important community‐wide consequences.
Effects of feedback and test practice on recollection and retrieval monitoring: comparing first graders, third graders, and adults*

ABSTRACT We tested the effects of repeated testing and feedback on recollection accuracy in first graders, third graders, and adults. All participants studied a list of words and pictures, and then took three recollection tests, with each test probing different words and pictures from the earlier study phase. On the first and third tests no feedback was given, whereas on the second test, some subjects received item-level feedback throughout the recollection test. Recollection confusion scores declined across successive tests in all age groups. However, explicit feedback did not improve recollection accuracy or reduce recollection confusions in any age group. We also found that all age groups were able to use picture recollections in a disqualifying monitoring strategy without task experience or feedback. As a whole, these findings suggest that children and adults can use some aspects of retrieval monitoring without feedback or practice, whereas other aspects of retrieval monitoring can benefit from test practice in children and adults. We discuss the potential roles of metacognitive learning and unintended social feedback on these test practice effects.
An optimal sampling-based path planning under uncertainty based on linear quadratic regulator

The navigation of mobile robots is affected by noises from perceptual systems and positioning systems, as well as track deviations from control systems. Therefore, it is significant to ensure the stability of path planning in an uncertain environment. In this paper, an optimal samplingbased path planning method based on linear quadratic regulator is proposed. This method uses heuristic rapid-exploring random tree to generate paths which are executable and asymptotic optimal. Then, the priori distributions of the generated paths are calculated and evaluated through an uncertainty factor. The effectiveness of the proposed method is verified by simulation experiments in a variety of uncertain environments.
Tracking control of inverted pendulum on a cart with disturbance using pole placement and LQR

This paper presents the Mathematical non-linear model of Inverted Pendulum (IP) system on a cart based on Lagrange's Equation. The linearization is done through Tayler's series approximation. Linear Quadratic Regulator (LQR) and Pole Placement control strategy are used for solving tracking problem and stabilization of pendulum around upright position. Square wave is used as reference signal for IP tracking. Simulation results are compared with and without disturbances for both the control strategy. The performance of controllers is obtained based on specification of response time and disturbance rejection level. The performance of LQR is better than pole placement control.
De novo synthesis of C4.4A in hepatocellular carcinoma promotes migration and invasion of tumor cells

C4.4A is a glycoprotein that is upregulated in several human malignancies, including colorectal, breast and renal cell carcinomas. Due to its highly restricted expression in healthy tissue, C4.4A was proposed as a potential diagnostic marker. Thus, the present study was designed to evaluate C4.4A expression and function in hepatocellular carcinoma (HCC) for the first time. Immunohistochemistry was performed to detect expression of C4.4A in human sections of healthy liver, primary HCC in the liver and metastatic HCC in the lung. To assess the contribution of C4.4A to HCC progression proliferation, apoptosis, migration and invasion assays were performed with C4.4A knockdown Huh7 and HepG2 cells. C4.4A is absent in healthy liver tissue. However, intense expression was seen in 59% of primary HCCs and strong expression in 80% of HCC lung metastases. C4.4A expression was also observed in human HCC cell lines, which strongly increased under hypoxic conditions. A C4.4A knock-down revealed that C4.4A is involved in both migration and invasion of HCC cells. Taken together, C4.4A expression in both primary and metastatic HCC suggests its potential value as a diagnostic marker for HCC. Due to its absence in healthy liver tissue, C4.4A might even serve as a possible therapeutic target, particularly for metastatic HCC.
Joint source selection and transfer optimization for erasure coding storage system

With the deployment of big data applications, more and more data are stored in the online storage. Erasure coding storage system has been widely used by companies such as Google and Facebook, since it provides space-optimal data redundancy to protect against data loss. In erasure coding storage system, (n, k) MDS erasure code is used to divide file into n chunks. When a user want to access the file, any subset of k out of n chunks will be needed to reconstruct the file. In this case, how to select k out of n chunks and how to let the chunks transfer quickly become important problems. In this paper, we joint the two problems together to optimize. Our optimization goal is to minimize average file access time (FAT). To achieve this, we propose smallest load first heuristic to do source selection and design an online algorithm to reduce chunks transfer latency. Base on this, we design and implement D-Target, a centralized scheduler that tries to minimize average FAT in distributed erasure coding storage system. We then test D-Target's performance by trace-driven simulation. Results show that, for the trace of AT&T, D-Target performs 2.5×, 1.7×, 1.8×, 3.6× better than TCP, Aalo, Barrat and pFabric respectively.
Semantic typing of linked geoprocessing workflows

In Geographic Information Systems (GIS), geoprocessing workflows allow analysts to organize their methods on spatial data in complex chains. We propose a method for expressing workflows as linked data, and for semi-automatically enriching them with semantics on the level of their operations and datasets. Linked workflows can be easily published on the Web and queried for types of inputs, results, or tools. Thus, GIS analysts can reuse their workflows in a modular way, selecting, adapting, and recommending resources based on compatible semantic types. Our typing approach starts from minimal annotations of workflow operations with classes of GIS tools, and then propagates data types and implicit semantic structures through the workflow using an OWL typing scheme and SPARQL rules by backtracking over GIS operations. The method is implemented in Python and is evaluated on two real-world geoprocessing workflows, generated with Esri's ArcGIS. To illustrate the potential applications of our typing method, we formulate and execute competency questions over these workflows.
Cryptographic key generation from multimodal template using fuzzy extractor

The encryption techniques, biometrics and cryptography integrate to form biometric cryptosystems. These are designed either to bind a cryptographic key or to generate cryptographic key using biometric features. The deployment of bio-cryptosystem technique, namely fuzzy extractor in multimodal biometric system leads to increase in user privacy and system security. This paper provides with a framework where feature level fusion of iris and dual fingerprint forms a multimodal template and key is generated using fuzzy extractors, in order to provide reliability and good recognition performance. The hash function is used to protect the key generated from biometric traits. Since fuzzy extractor operates only on ordered dataset. However the minutiae points of fingerprint are unordered, so an algorithm is designed for conversion of unordered minutiae points to ordered minutiae dataset to make it consistent for key generation methods.
Fermi-to-Bose crossover in a trapped quasi-2D gas of fermionic atoms

The physics of many-body systems where particles are restricted to move in two spatial dimensions is challenging and even controversial: on one hand, neither long-range order nor Bose condensation may appear in infinite uniform 2D systems at finite temperature, on the other hand this does not prohibit superfluidity or superconductivity. Moreover, 2D superconductors, such as cuprates, are among the systems with the highest critical temperatures. Ultracold atoms are a platform for studying 2D physics. Unique from other physical systems, quantum statistics may be completely changed in an ultracold gas: an atomic Fermi gas may be smoothly crossed over into a gas of Bose molecules (or dimers) by tuning interatomic interactions. We review recent experiments where such crossover has been demonstrated, as well as critical phenomena in the Fermi-to-Bose crossover. We also present simple theoretical models describing the gas at different points of the crossover and compare the data to these and more advanced models.
Gas turbine fault diagnostics using fuzzy systems

Gas turbines are clean, compact, cost effective and efficient assets that are being used widely in distributed power generation. They operate at elevated temperature, pressure, high speed and often exposed to erosive materials resulting in several types of failures such as corrosion, fretting fatigue, and fatigue-creep failures. Early detection and diagnostics of a fault is the key to optimize the maintenance cost and reduction in production downtime. While there are assorted approaches in fault detection and diagnostics in gas turbines, this literature provides a useful review on the fault detection and diagnostics methods that have used fuzzy systems only. Publications from years 2001 to 2017 are included. The results show that (i) the gas path analysis models rely on the availability of large amount of data, that is not often the case in the real-life situation, (ii) there is lack of proper documentation for expert opinions done in fuzzy diagnostics, (iii) the hybrid fuzzy systems are gaining more popularity, (iv) the studies on fault diagnostics under dynamic conditions are quite limited, and (v) Wiener-Schetzen model that adopts orthonormal basis functions for the dynamic part is not yet applied to gas turbines. The remarks are useful to further enhance the conventional approach to diagnostics systems design.
Effects of Bioreactor‐Oxygenation During Extracorporeal Granulocytes Treatment in Septic Patients

A granulocyte bioreactor for the extracorporeal treatment was developed to enhance the immune cell function in patients with severe sepsis. The influence of oxygenation on the used cells was tested in a prospective clinical study. Ten patients with severe sepsis were treated twice with the granulocyte bioreactor. The used cells were screened for functionality; values of blood gases, glucose and lactate were obtained from the recirculating bioreactor circuit. Five patients were treated with an oxygenator setup (Oxy group), five without oxygenator (Non‐Oxy group). The overall in‐hospital mortality was 50%. Significantly lower values of oxygen saturation, partial oxygen pressure, lactate, oxyburst and phagocytosis were seen in the Non‐Oxy group compared with the Oxy group in the bioreactor circuit. Further studies with this approach are encouraged and should focus on the influence of oxygenation on production of reactive oxygen species and cytokines of used cells.
Fast Deformable Model for Pedestrian Detection with Haar-like features

This paper proposes a novel Fast Deformable Model for Pedestrian Detection (FDMPD) to detect the pedestrians efficiently and accurately in the crowded environment. Despite of multiple detection methods available, detection becomes difficult due to variety of human postures and perspectives. The proposed study is divided into two parts. First part trains six Adaboost classifiers with Haar-like feature for different body parts (e.g., head, shoulders, and knees) to build the response feature maps. Second part uses these six response feature maps with full-body model to produce spatial deep features. The combined deep features are used as an input to SVM to judge the existence of pedestrian. As per the experiments conducted on the INRIA person dataset, the proposed FDMPD approach shows greater than 44.75 % improvement compared to other state-of-the-art methods in terms of efficiency and robustness.
Methods for Quantifying Patterns of Dynamic Interactions in Dyads

Individuals in both clinical and research settings increasingly provide data across numerous time points. Examples include measurements collected from wearable technology (e.g., accelerometers), psychophysiological measures, coded observations, social media behaviors, and daily diary data. When numerous observations are available for each individual, the data fall under the class of time series data and can be examined from within a dynamic systems perspective. We provide a broad overview of current analytic methods for quantifying relations among dyads using this data type. The techniques include those from within a linear modeling framework, approaches that include a measurement model, and methods for examining cyclical relations. We also discuss some special topics, such as methods that allow for models to shift across time and that accommodate heterogeneity across individuals. Finally, methods that account for similar shapes of nonlinear curves across time are described. From this breadth of options, we hope to help guide practitioners, clinicians, and researchers in choosing the optimal method for their data and line of questions. To further aid in this choice, we indicate programs available for each technique. Example dyads presented here range from mother–infant, patient–caretaker, and husband–wife; however, the analytic methods can be applied to any type of dyad.
European experience with prenatal diagnosis of congenital disease: a survey of 6121 cases.

The results of 6121 prenatal diagnoses established by 46 centers in eight West-European countries are reported. The percentage of "spontaneous" abortions following early amniocentesis (1.4%) does not seem to exceed the normal rate of spontaneous abortion in this period of pregnancy. A total of nearly 300 affected fetuses was detected, and in all but 5 instances the parents asked for interruption of the pregnancy. The majority of prenatal monitoring (75%) was carried out because of an increased risk of chromosomal aberration. In the group with higher maternal age 2.8% of the fetuses were affected; this figure was 4.6% for mothers older than 38 years. Monitoring because of an earlier child with trisomy 21 showed 1.3% fetuses with a chromosomal aberration, and 1.7% abnormal karyotypes were detected in the group where amniocentesis was performed for "miscellaneous reasons. " In pregnancies where a parental translocation has been demonstrated, 6.7% of the fetuses showed an unbalanced karyotype and 25% were balanced carriers. Also discussed are results and organizatioal problems of prenatal monitoring for inherited metabolic disorders (206 analyses for 23 different enzyme defects) and for neural tube defects (about 2700 cases).
Myocardial Turnover of Endogenous Opioids and Calcitonin-Gene-Related Peptide in the Human Heart and the Effects of Spinal Cord Stimulation on Pacing-Induced Angina Pectoris

Earlier studies have shown that spinal cord stimulation (SCS) has antianginal and anti-ischemic effects in severe coronary artery disease. In the present study, 14 patients were subjected to right-sided atrial catheterization and atrial pacing. The patients were paced to angina during a control session and during spinal cord stimulation. Myocardial extraction of β-endorphin (BE) during control pacing (8 ± 22%) changed to release at the maximum pacing rate during treatment (–21 ± 47%, a negative value representing release). Furthermore, the results indicate local myocardial turnover of leuenkephalin, BE and calcitonin-gene-related peptide. In addition, it is implied that SCS may induce myocardial release of BE which could explain the beneficial effects in myocardial ischemia.
Severe Craniofacial Involvement due to Amniotic Band Sequence

ABSTRACT Background: Disruptive amniotic band sequence (DABS) is a sporadic, non-familial disorder with unclear etiology. Diagnosis is based on clinical features because there is currently no reliable laboratory diagnostic tests. Objective: We describe six cases of DABS with severe craniofacial deformations, three with and three without classical constrictive limb deformation. Results: The craniofacial deformities were delimited by peripheral sharply demarcated scarring. Conclusion: When a sharply demarcated linear disruptive craniofacial lesion is observed, DABS should be considered despite the absence of constrictive limb scarring.
A novel heart rate and non-invasive glucose measuring device

At the cross section of the fields of biomedical devices and signal processing, is the work of a novel heart rate and non-invasive blood glucose measuring device capable of measuring these vital medical parameters in parallel. This paper describes different non-invasive methods used to measure these parameters involving concepts from signal processing. The concept of Near Infrared (NIR) photoplethysmography is used to measure the change in the light absorbed by illuminating the skin to compute the pulse rate of a person combined with the help of a proposed novel algorithm while blood glucose is measured optically with the help of an Infrared LED (wavelength of 940nm) in which the amount of light received by the photodiode determines the glucose concentration in the blood. The paper focuses on making a remote, cost effective device capable of efficient measurement combined with a user-friendly GUI. The proposed device also uploads the measured values on the cloud for authentic diagnosis by physicians for far-away patients' lacking state of the art diagnosis.
Dutch Risk Classification and FIGO 2000 for Gestational Trophoblastic Neoplasia Compared

Objective Over the years, there has been a wide variety of classification systems in use worldwide to stratify patients between single-agent versus multi-agent chemotherapy, hindering comparison of international research results. The study presents a retrospective comparison of the International Federation of Gynecology and Obstetrics 2000 and Dutch risk classification system for gestational trophoblastic neoplasia. Methods and Materials All patients diagnosed with gestational trophoblastic neoplasia between January 2003 and December 2012 at the trophoblastic disease centre in London were retrospectively scored according to the Dutch classification system (N = 813). Results An extensive overlap between both scoring systems was seen, even though items and relative value of items were quite distinct. The Dutch system seems to be simpler and easier to apply in all situation; a degree of overtreatment can however be presumed with the use of either system. Conclusions Although it is likely that outcome is indeed affected by the individual factors used in both systems, many factors relate to tumor bulk and may not be independently prognostic. We therefore believe that further refinement of the classification systems and their underlying prognostic items plus any new items that seem promising would be useful.
Convolutional neural network approach for vision based student recognition system

Computers are now too smart to interact with the human in different approaches. This interaction will be more acceptable for both human and computer if it is based on recognition process. In this article, author's concern is to integrate and develop a student recognition system using existing algorithms. Among various face recognition methods, here author use deep learning based face recognition method. This method uses Convolutional Neural Networks (CNN) to generate a low dimensional representation called embeddings. Then those embeddings are used to classify the person's facial image. By this system different types of applications like student attendance-system, building security etc. can be developed. After building the system, a resultant performance is also showed in this article.