Miracle-dz/UniFAR-FTUs huggingface dataset:
Transformation control to an inverted pendulum mode of a mobile robot with wheel-arms using partial linearization

This paper presents a shape transformation control method of a mobile robot with wheel-arms. The proposed method aims at transformation from a four-wheeled mode for high speed mobility to an inverted pendulum mode, which has advantages of high viewing position and small turning radius. The transformation starts with lifting up the wheel-arms to raise the center of gravity of the whole body. From such initial states, the body is lifted up and controlled to the target angle by partial linearization, while returning the arms to the initial angle. Then, the wheels are slowed down by properly changing the target pitch angle of the body. Stability analysis is carried out by taking into account the transient response of the body angle to the target value, which is neglected in existing work. The effectiveness of the proposed method is demonstrated by experiments.
Automatic construction of an effective training set for prioritizing static analysis warnings

In order to improve ineffective warning prioritization of static analysis tools, various approaches have been proposed to compute a ranking score for each warning. In these approaches, an effective training set is vital in exploring which factors impact the ranking score and how. While manual approaches to build a training set can achieve high effectiveness but suffer from low efficiency (i.e., high cost), existing automatic approaches suffer from low effectiveness. In this paper, we propose an automatic approach for constructing an effective training set. In our approach, we select three categories of impact factors as input attributes of the training set, and propose a new heuristic for identifying actionable warnings to automatically label the training set. Our empirical evaluations show that the precision of the top 22 warnings for Lucene, 20 for ANT, and 6 for Spring can achieve 100% with the help of our constructed training set.
Ovarian cancer: what’s new, where next?

The recent RDOG studies have confirmed the value of CT in the management of ovarian cancer. However we now know that metastases to the ovary may exactly mimic primary cancer. This demands a firm histological diagnosis when surgery is not planned and especially with a history of breast and gastrointestinal tract cancer. CT guided needle biopsy can provide this.
A Non-Inferiority, Individually Randomized Trial of Intermittent Screening and Treatment versus Intermittent Preventive Treatment in the Control of Malaria in Pregnancy

Background The efficacy of intermittent preventive treatment for malaria with sulfadoxine-pyrimethamine (IPTp-SP) in pregnancy is threatened in parts of Africa by the emergence and spread of resistance to SP. Intermittent screening with a rapid diagnostic test (RDT) and treatment of positive women (ISTp) is an alternative approach. Methods and Findings An open, individually randomized, non-inferiority trial of IPTp-SP versus ISTp was conducted in 5,354 primi- or secundigravidae in four West African countries with a low prevalence of resistance to SP (The Gambia, Mali, Burkina Faso and Ghana). Women in the IPTp-SP group received SP on two or three occasions whilst women in the ISTp group were screened two or three times with a RDT and treated if positive for malaria with artemether-lumefantrine (AL). ISTp-AL was non-inferior to IPTp-SP in preventing low birth weight (LBW), anemia and placental malaria, the primary trial endpoints. The prevalence of LBW was 15.1% and 15.6% in the IPTp-SP and ISTp-AL groups respectively (OR = 1.03 [95% CI: 0.88, 1.22]). The mean hemoglobin concentration at the last clinic attendance before delivery was 10.97g/dL and 10.94g/dL in the IPTp-SP and ISTp-AL groups respectively (mean difference: -0.03 g/dL [95% CI: -0.13, +0.06]). Active malaria infection of the placenta was found in 24.5% and in 24.2% of women in the IPTp-SP and ISTp-AL groups respectively (OR = 0.95 [95% CI 0.81, 1.12]). More women in the ISTp-AL than in the IPTp-SP group presented with malaria parasitemia between routine antenatal clinics (310 vs 182 episodes, rate difference: 49.4 per 1,000 pregnancies [95% CI 30.5, 68.3], but the number of hospital admissions for malaria was similar in the two groups. Conclusions Despite low levels of resistance to SP in the study areas, ISTp-AL performed as well as IPTp-SP. In the absence of an effective alternative medication to SP for IPTp, ISTp-AL is a potential alternative to IPTp in areas where SP resistance is high. It may also have a role in areas where malaria transmission is low and for the prevention of malaria in HIV positive women receiving cotrimoxazole prophylaxis in whom SP is contraindicated. Trial Registration ClinicalTrials.gov NCT01084213 Pan African Clinical trials Registry PACT201202000272122
Support vector machine for arrhythmia discrimination with TCI feature selection

Ventricular fibrillation (VF) is a malignant arrhythmia, which belongs to complex and nonlinear signals. To realize the detection of ventricular fibrillation, a new algorithm, which was based on the improved threshold crossing interval (TCI) algorithm and Support vector machine (SVM), was proposed in this paper. The SWM has great advantages in processing classification and pattern recognition. In this paper, 4-s-sliding-window technology and the improved TCI algorithm are applied to extract features of electrocardiogram (ECG). The improved TCI algorithm was implemented as follows: firstly, the average threshold crossing interval value of the middle 2s was calculated by using absolute threshold at each 4-s-sliding-window; secondly, the feature parameter (TCI value) was input to a pre-designed binary classification support vector machine; lastly, the classification was accomplished. For evaluating the reliability of the new algorithm, both MIT-BIH arrhythmia database and CU ventricular tachyarrhythmia database were used to test. By comparing the sensitivity, specificity, positive predictability and accuracy with other well known methods, the conclusion was made that this method is superior to other methods. This new algorithm is easier to implement and has greater advantages in real-time execution. These advantages make it more suitable in real time ECG monitoring and defibrillator.
Dual-Domain Adaptive Beamformer Under Linearly and Quadratically Constrained Minimum Variance

In this paper, a novel adaptive beamforming algorithm is proposed under a linearly and quadratically constrained minimum variance (LQCMV) beamforming framework, based on a dual-domain projection approach that can efficiently implement a quadratic-inequality constraint with a possibly rank-deficient positive semi-definite matrix, and the properties of the proposed algorithm are analyzed. As an application, relaxed zero-forcing (RZF) beamforming is presented which adopts a specific quadratic constraint that bounds the power of residual interference in the beamformer output with the aid of interference-channel side-information available typically in wireless multiple-access systems. The dual-domain projection in this case plays a role in guiding the adaptive algorithm towards a better direction to minimize the interference and noise, leading to considerably faster convergence. The robustness issue against channel mismatch and ill-posedness is also addressed. Numerical examples show that the efficient use of interference side-information brings considerable gains.
A class of genes in the HER2 regulon that is poised for transcription in breast cancer cell lines and expressed in human breast tumors

HER2-positive breast cancer accounts for 25% of all cases and has a poor prognosis. Although progress has been made in understanding signal transduction, little is known of how HER2 achieves gene regulation. We performed whole genome expression analysis on a HER2+ and HER2− breast cancer cell lines and compared these results to expression in 812 primary tumors stratified by their HER2 expression level. Chip-on-chip with anti-RNA polymerase II was compared among breast cancer cell lines to identify genes that are potentially activated by HER2. The expression levels of these HER2-dependent POL II binding genes were determined for the 812 HER2+/− breast cancer tissues. Genes differentially expressed between HER2+/− cell lines were generally regulated in the same direction as in breast cancer tissues. We identified genes that had POLII binding in HER2+ cell lines, but without significant gene expression. Of 737 such genes “poised” for expression in cell lines, 113 genes were significantly differentially expressed in breast tumors in a HER2-dependent manner. Pathway analysis of these 113 genes revealed that a large group of genes were associated with stem cell and progenitor cell control as indicated by networks centered on NANOG, SOX2, OCT3/4. HER2 directs POL II binding to a large number of genes in breast cancer cells. A “poised” class of genes in HER2+ cell lines with POLII binding and low RNA expression but is differentially expressed in primary tumors, strongly suggests a role of the microenvironment and further suggests a role for stem cells proliferation in HER2-regulated breast cancer tissue.
Bone Marrow Derived Mesenchymal Stem Cells Inhibit Inflammation and Preserve Vascular Endothelial Integrity in the Lungs after Hemorrhagic Shock

Hemorrhagic shock (HS) and trauma is currently the leading cause of death in young adults worldwide. Morbidity and mortality after HS and trauma is often the result of multi-organ failure such as acute lung injury (ALI) and acute respiratory distress syndrome (ARDS), conditions with few therapeutic options. Bone marrow derived mesenchymal stem cells (MSCs) are a multipotent stem cell population that has shown therapeutic promise in numerous pre-clinical and clinical models of disease. In this paper, in vitro studies with pulmonary endothelial cells (PECs) reveal that conditioned media (CM) from MSCs and MSC-PEC co-cultures inhibits PEC permeability by preserving adherens junctions (VE-cadherin and β-catenin). Leukocyte adhesion and adhesion molecule expression (VCAM-1 and ICAM-1) are inhibited in PECs treated with CM from MSC-PEC co-cultures. Further support for the modulatory effects of MSCs on pulmonary endothelial function and inflammation is demonstrated in our in vivo studies on HS in the rat. In a rat “fixed volume” model of mild HS, we show that MSCs administered IV potently inhibit systemic levels of inflammatory cytokines and chemokines in the serum of treated animals. In vivo MSCs also inhibit pulmonary endothelial permeability and lung edema with concurrent preservation of the vascular endothelial barrier proteins: VE-cadherin, Claudin-1, and Occludin-1. Leukocyte infiltrates (CD68 and MPO positive cells) are also decreased in lungs with MSC treatment. Taken together, these data suggest that MSCs, acting directly and through soluble factors, are potent stabilizers of the vascular endothelium and inflammation. These data are the first to demonstrate the therapeutic potential of MSCs in HS and have implications for the potential use of MSCs as a cellular therapy in HS-induced lung injury.
An Expert System Based on Soft Computing Techniques for Monitoring Multiphase Flows

The knowledge and the forecast of the parameters which rule the downflow models in oil extraction and transport are today of paramount importance. In particular the extracted oil is mixed with water and gas in rates which differ not only from different wells, but also on the same well during its life. The main problems involved with the measurement of the flow rates are : well exhaustion, critical flow pattern prevision and pipeline leak detection. Today the production of several wells is carried, with short pipelines, to a manifold from which, with a single long pipeline, the total production is carried to the oil centre. In this situation the information concerning the single well is lost so that the main oil industries require monitoring systems which can indicate the individual well flow rates. So far general measurement systems don’t exist and one of the main goals is the development of an instrumentation tool for the mass flow rate measurement of three phase flows (oil-gas-water). Building a single model for the whole range is very difficult because of the high non-linearity effects due to the variation of flow patterns, liquid viscosity and density and therefore different models for the data analysis, based on different approaches corresponding to different fluidynamic hypothesis, have been developed. In this context building up an effective expert system for monitoring oil fields is a very hard challenge for the main oil companies and research institutes.
Inhibition of Specific NF-κB Activity Contributes to the Tumor Suppressor Function of 14-3-3σ in Breast Cancer

14-3-3σ is frequently lost in human breast cancers by genetic deletion or promoter methylation. We have now investigated the involvement of 14-3-3σ in the termination of NF-κB signal in mammary cells and its putative role in cancer relapse and metastasis. Our results show that 14-3-3σ regulates nuclear export of p65-NF-κB following chronic TNFα stimulation. Restoration of 14-3-3σ in breast cancer cells reduces migration capacity and metastatic abilities in vivo. By microarray analysis, we have identified a genetic signature that responds to TNFα in a 14-3-3σ-dependent manner and significantly associates with different breast and other types of cancer. By interrogating public databases, we have found that over-expression of this signature correlates with poor relapse-free survival in breast cancer patients. Finally, screening of 96 human breast tumors showed that NF-κB activation strictly correlates with the absence of 14-3-3σ and it is significantly associated with worse prognosis in the multivariate analysis. Our findings identify a genetic signature that is important for breast cancer prognosis and for future personalized treatments based on NF-κB targeting.
Attachment to friends and psychosocial well‐being: The role of emotion regulation

Background: Attachment insecurity is associated with poor mental health across the life span, and increasing evidence suggests that emotion regulation difficulties are implicated in these associations. To date, research has focused largely on adult attachment in the context of romantic relationships; however, close friendships are well‐established predictors of mental health and well‐being, and little is known about the influence of attachment in the context of close friendships on mental health, and the potential role of emotion regulation. The present research examined whether attachment to friends was associated with mental health and interpersonal functioning, and whether emotion regulation mediated these associations. Method: A sample of 243 adults (Mage = 20.91 years) completed an online questionnaire assessing attachment to friends, emotion regulation, mental health, and interpersonal functioning. Results: Emotion dysregulation mediated the association between attachment anxiety and depression, anxiety, stress, and interpersonal distress. There were also direct effects of attachment anxiety on symptoms of anxiety and interpersonal distress. Emotion dysregulation did not mediate the association between attachment avoidance and psychosocial outcomes, though attachment avoidance directly predicted depression and interpersonal distress. Conclusions: This research highlights that emotion dysregulation may be one mechanism underlying the association between anxious attachment to friends and poor psychosocial functioning. Clinical interventions may therefore benefit from assessing attachment in the context of friendships, and targeting emotion dysregulation for those high in attachment anxiety.
The impact of service quality and relationship quality on E-shop brand image

With the rapid development of internet, shopping online has become one of the mainstream patterns for consumption. As E-consumers will not trust and go shopping from E-shops so easily, building up a good brand image for E-shop to gain the trust from E-consumers become very necessary. Based on 143 questionnaires from Chinese netizens who have the E-shopping experience, this paper implements a structural equation model to test whether and how service quality and relationship quality with E-consumers take effect on the establishment of E-shop brand image. The result shows that service quality has direct positive impact on relationship quality with E-consumers but no direct positive impact on E-shop brand image. In addition, relationship quality plays an intermediary role between service quality and E-shop brand image, and has direct positive impact on E-shop brand image, which indicates that relationship quality is very important to E-shop for brand image building up and increasing E-consumers' buying frequencies.
Exploring the heart and mind of anxiety: a multi-modal approach to examining the neurovisceral integration model in clinically anxious adults

Objective: The purpose of this dissertation was to reproduce Thayer and Lane’s (2000) neurovisceral model by examining both tonic and phasic heart rate variability (HRV) and emotion regulation (ER), and explore the effects of brief evidence-based intervention techniques in a sample of adults with clinically elevated levels of anxiety. Methods: This was a comprehensive multi-methodological study of 34 adults (ages 19 to 63 years) with clinically elevated levels of anxiety. Study 1 examined subjective and physiological effects of implementing ER strategies in response to a well-validated emotion elicitation paradigm consisting of viewing emotion-eliciting aversive images and sentences. Study 2 employed a within-subject RCT design and compared the impact of cognitive restructuring (CR), a topdown ER technique, with open monitoring mindfulness (OM), a bottom-up ER technique. Effects of intervention on self-regulation were assessed at a physiological (i.e. HRV), behavioral (i.e. ER and executive function (EF) computerized task) and subjective (i.e. selfreport questionnaires) level. Results: Study 1 revealed that tonic HRV significantly predicted perceived ER success for both top-down and bottom-up generated emotions, whereas phasic HRV only predicted perceived ER success under conditions of bottom-up emotion generation. Variability emerged in our findings depending on the unique ER strategy used. Study 2 indicated a significant time by intervention effect on phasic HRV on the ER task, where HRV decreased with CR and increased with OM. There was a main effect of age independent of intervention on the EF task, such that increased age was related to increased phasic reactivity. On the ER task, CR led to greater perceived success in cognitive reappraisal. On the EF task, CR became faster, whereas OM became slower but more accurate. Significant intervention effects were also found on self-reported anxiety and aspects of mindfulness, with greatest reductions in anxiety found in OM compared to CR. Conclusions: In keeping with the neurovisceral integration model, HRV was reduced in individuals’ with clinically elevated levels of anxiety. Moreover, our findings illustrate that the method of emotion generation and regulation matters and has a significant impact on the degree to which persons with clinical levels of anxiety are able to successfully self-regulate. Finally, our results demonstrate the utility of multi-modal assessment of cognitive and emotional dysregulation in anxiety disorders, as well as the different pathways through which different interventions can impact HRV and ameliorate symptoms of anxiety.
The Level Paradox of E-Collaboration: Dangers and Solutions

Although e-collaboration phenomena are multilevel in nature, research to date has been conducted from an exclusively single-level focus. This has lead to the level paradox. The dangers of the level paradox are discussed, including the potential that apparent cumulative knowledge may actually be spurious. Solutions to the level paradox are proposed in the form of future opportunities of research from several mixed-level approaches, and the benefits and barriers to mixed-level research are discussed. The article ends with a discussion on the necessity of finding a balance between single-level and mixed-level research, as well as on the necessity of single-level studies explicitly specifying the levels of theory, measurement, and data in their research.
Validation of stratospheric water vapour measurements from the airborne microwave radiometer AMSOS

We present the validation of a water vapour dataset obtained by the Airborne Microwave Stratospheric Observing System AMSOS, a passive microwave radiometer operating at 183 GHz. Vertical profiles are retrieved from spectra by an optimal estimation method. The useful vertical range lies in the upper troposphere up to the mesosphere with an altitude resolution of 8 to 16 km and a horizontal resolution of about 57 km. Flight campaigns were performed once a year from 1998 to 2006 measuring the latitudinal distribution of water vapour from the tropics to the polar regions. The obtained profiles show clearly the main features of stratospheric water vapour in all latitudinal regions. Data are validated against a set of instruments comprising satellite, ground-based, airborne remote sensing and in-situ instruments. It appears that AMSOS profiles have a dry bias of 0 to –20%, when compared to satellite experiments. Also a comparison between AMSOS and in-situ hygrosondes FISH and FLASH have been performed. A matching in the short overlap region in the upper troposphere of the lidar measurements from the DIAL instrument and the AMSOS dataset allowed water vapour profiling from the middle troposphere up to the mesosphere.
An improved CS-LSSVM algorithm-based fault pattern recognition of ship power equipments

A ship power equipments’ fault monitoring signal usually provides few samples and the data’s feature is non-linear in practical situation. This paper adopts the method of the least squares support vector machine (LSSVM) to deal with the problem of fault pattern identification in the case of small sample data. Meanwhile, in order to avoid involving a local extremum and poor convergence precision which are induced by optimizing the kernel function parameter and penalty factor of LSSVM, an improved Cuckoo Search (CS) algorithm is proposed for the purpose of parameter optimization. Based on the dynamic adaptive strategy, the newly proposed algorithm improves the recognition probability and the searching step length, which can effectively solve the problems of slow searching speed and low calculation accuracy of the CS algorithm. A benchmark example demonstrates that the CS-LSSVM algorithm can accurately and effectively identify the fault pattern types of ship power equipments.
Dealing with massive data with a distributed expectation propagation particle filter for object tracking

Target tracking in distributed networks faces the challenge in coping with large volumes of distributed data which requires efficient methods for real time applications with minimal communication overhead. The complexity considered in this paper is when each sensor in a distributed network observes a large number of measurements which are all required to be processed at each time step. The particle filter has been widely used for localisation and tracking in distributed networks with a small number of measurements [1]. This paper goes beyond the current state-of-the-art and presents a novel particle filter approach, combined with the expectation propagation framework, that is capable of dealing with the challenges presented by a large volume of measurements in a distributed network. In the proposed algorithm, the measurements are processed in parallel at each sensor node in the network and the communication overhead is minimised substantially. We show results with large improvements in communication overhead, with a negligible loss in tracking performance, compared with the standard centralised particle filter.