Miracle-dz/UniFAR-FTUs huggingface dataset:
E3MoP: Efficient Motion Planning Based on Heuristic-Guided Motion Primitives Pruning and Path Optimization With Sparse-Banded Structure

To solve the autonomous navigation problem in complex environments, an efficient motion planning approach is newly presented in this paper. Considering the challenges from large-scale, partially unknown complex environments, a three-layer motion planning framework is elaborately designed, including global path planning, local path optimization, and time-optimal velocity planning. Compared with existing approaches, the novelty of this work is twofold: 1) a novel heuristic-guided pruning strategy of motion primitives is proposed and fully integrated into the state lattice-based global path planner to further improve the computational efficiency of graph search, and 2) a new soft-constrained local path optimization approach is proposed, wherein the sparse-banded system structure of the underlying optimization problem is fully exploited to efficiently solve the problem. We validate the safety, smoothness, flexibility, and efficiency of our approach in various complex simulation scenarios and challenging real-world tasks. It is shown that the computational efficiency is improved by 66.21% in the global planning stage and the motion efficiency of the robot is improved by 22.87% compared with the recent quintic Bézier curve-based state space sampling approach. We name the proposed motion planning framework E $\mathbf {^{3}} $ MoP, where the number 3 not only means our approach is a three-layer framework but also means the proposed approach is efficient in three stages. Note to Practitioners—This paper is motivated by the challenges of motion planning problems of mobile robots. A three-layer motion planning framework is proposed by combining global path planning, local path optimization, and time-optimal velocity planning. For mobile robot navigation applications in semi-structured environments, optimization-based local planners are recommended. Extensive simulation and experimental results show the effectiveness of the proposed motion planning framework. However, due to the non-convexity of the path optimization formulation, the proposed local planner may get stuck in local optima. In future research, we will concentrate on extending the proposed local path optimization approach with the theory of homology classes to maintain several homotopically distinct local paths and seek global optima.
SOME RESULTS ON MAXIMUM LIKELIHOOD OF INCOMPLETE DATA: FINITE SAMPLE PROPERTIES, CONSISTENT SANDWICH ESTIMATOR OF COVARIANCE MATRIX AND RECURSIVE ALGORITHMS

This paper presents some new results on maximum likelihood of incomplete data. Finite sample properties of conditional observed information matrices (the conditional expectation of minus second derivatives of the log-likelihood given incomplete data) are established. In particular, they possess the same Loewner partial ordering properties as the expected information matrices do. In its new form, the observed Fisher information (OFI) simplifies conditional expectation of outer product of the complete-data score function appearing in the Louis (1982) general matrix formula. It verifies positive definiteness and consistency to the expected Fisher information as the sample size increases. Furthermore, it shows a resulting information loss presented in the incomplete data. For this reason, the OFI may not be the right (consistent and efficient) estimator to derive the standard error (SE) of maximum likelihood estimates (MLE) for incomplete data. A sandwich estimator of covariance matrix is developed to provide consistent and efficient estimates of SE. The proposed sandwich estimator coincides with the Huber sandwich estimator for model misspecification under complete data (Huber, 1967; Freedman, 2006; Little and Rubin, 2020). However, in contrast to the latter, the new estimator does not involve OFI which notably gives an appealing feature for application. Recursive algorithms for the MLE, the observed information and the sandwich estimator are presented. Application to parameter estimation of a regime switching conditional Markov jump process is considered to verify the results. The recursive equations for the inverse OFI generalizes the algorithm of Hero and Fessler (1994). The simulation study confirms that the MLEs are accurate and consistent having asymptotic normality. The sandwich estimator produces standard error of the MLE close to their analytic values compared to those overestimated by the OFI.
Mast Cells Differentiated in Synovial Fluid and Resident in Osteophytes Exalt the Inflammatory Pathology of Osteoarthritis

Osteophytes are a prominent feature of osteoarthritis (OA) pathology. RNA-seq of osteophytes revealed patterns corresponding to active ECM re-modulation and participation of mast cells. The cells recruitment and their activity status were confirmed by anti-TPSAB1 and anti-FC epsilon RI antibodies in immunohistochemistry. Besides subchondral bone, which is a logical yet unproven route for the cells deployment into osteophytes, the authors propose that OA synovial fluid (SF) is necessary and sufficient for maturation of mast cell precursors (MCPs) in this channel. The authors present evidences to support their claim in the form of IHC, proteomics analysis of SF samples and in vitro cell differentiation assay, wherein human monocytes (ThP1) and hematopoietic stem cells (HSCs) showed differentiation in HLA-DR+/CD206+ and FCERI+ phenotype respectively after 9 days of SF treatment. These observations expound osteophytes and resident mast cells as yet unexplained functional epicenter in OA pathology.
Copy number heterogeneity identifies ER+ breast cancer patients with adverse outcome after adjuvant endocrine therapy

Background - Endocrine therapy forms the backbone of adjuvant treatment for estrogen-receptor positive (ER+) breast cancer. However, it remains unclear whether adjuvant treatment improves survival rates in low-risk patients . Low intra-tumor heterogeneity (ITH) has been shown to confer low-risk for recurrent disease. Here, it is studied if chromosomal copy number ITH (CNH) can identify low-risk ER+, lymph node-negative breast cancers patients who do not benefit from adjuvant endocrine therapy. Methods - Lymph node-negative ER+ patients from the METABRIC dataset were retrospectively analyzed (n=708). CNH was determined from a single bulk copy number measurement for each patient. Patients were stratified by CNH score as low, medium or high. Overall survival (OS) was compared between patients that did, or did not receive adjuvant endocrine therapy per CNH group with Cox proportional-hazards models, using propensity score weights to correct for confounders. Results - Adjuvant endocrine therapy improved the relapse free survival (RFS) for high-CNH/high-risk patients treatment (Hazard Ratio [HR] = 0.55, 95% Confidence Interval [CI] = 0.35 to 0.87), but not for low CNH/risk patients treatment (HR = 0.88, 95% CI = 0.50 to 1.55). For low-CNH/low-risk patients adjuvant endocrine therapy was associated with impaired OS (HR = 1.62, 95% CI = 1.10 to 2.40). Multivariable Cox analysis identified a significant interaction between CNH and endocrine therapy for OS (HR = 0.77, 95% CI = 0.62 to 0.96). Conclusions - This retrospective study of lymph node-negative, ER+ breast cancer finds that patients identified as low-risk using CNH display reduced OS when treated with adjuvant endocrine therapy.
Development of an Accessible Gene Expression Bioinformatics Pipeline to Study Driver Mutations of Colorectal Cancer

Colorectal cancer (CRC) is a global cause of cancer-related mortality driven by genetic and environmental factors which influence therapeutic outcomes. The emergence of next-generation sequencing technologies enables the rapid and extensive collection and curation of genetic data for each cancer type into clinical gene expression biobanks. We report the application of bioinformatics tools for investigating the expression patterns and prognostic significance of three genes that are commonly dysregulated in colon cancer: adenomatous polyposis coli (APC); B-Raf proto-oncogene (BRAF); and Kirsten rat sarcoma viral oncogene homologue (KRAS). Through the use of bioinformatics tools, we show the patterns of APC, BRAF and KRAS genetic alterations and their role in patient prognosis. Our results show mutation types, the frequency of mutations, tumour anatomical location and differential expression patterns for APC, BRAF and KRAS for colorectal tumour and matched healthy tissue. The prognostic value of APC, BRAF and KRAS genetic alterations was investigated as a function of their expression levels in CRC. In the era of precision medicine, with significant advancements in biobanking and data curation, there is significant scope to use existing clinical data sets for evaluating the role of mutational drivers in carcinogenesis. This approach offers the potential for studying combinations of less well-known genes and the discovery of novel biomarkers, or for studying the association between various effector proteins and pathways.
Semi-Empirical Methods Prediction Noise from Free Supersonic Jets

It is important to assess the effects of missile and rocket launching on the launcher health and surrounding structures. Since an accurate measurement of the launch noise environment is time consuming and extremely cost prohibitive. And nowadays, there is no reliable theoretical method. in order to calculate the sound field generated by high-speed high temperature jets. Therefore, engineering approaches are widely used in practice. In this paper considers semi-empirical jet noise models and their development and application. Listing of some the open questions and future directions concerning supersonic jet noise predictions using semi-empirical methods concludes the survey.
Key quality factors in Web site design and use: an examination

The focus of the research described in this paper was to identify the key quality factors in Web site design and use. From the factors identified, a conceptual model has been developed to assess how a Web site can deliver what its users expect. The model is based on: ease of use, customer confidence, on‐line resources, and relationship services. These facts have been validated in an assessment of a range of Web sites. The model comprises a useful measurement tool which designers can use to suffice the quality of their Web sites.
Unidirectional antenna composed of dipole and loop

A new printed structure composed of a dipole and a loop antenna for achieving a unidirectional antenna is proposed. The proposed antenna demonstrates that when an electric dipole and a magnetic dipole are excited simultaneously, a unidirectional radiation pattern can be obtained. With the absence of any ground plane or reflector, this directional printed antenna with single-layer structure can be used nowadays in small directional wireless systems and some handheld devices that need to radiate in a particular direction. The antenna operates at 2.4 GHz with an impedance bandwidth of 7.4% for S11<−10 dB and a peak measured gain of around 4.3 dBi.
Improved Performance Research Integration Tool (IMPRINT): Human Performance Modeling for Improved System Design

Identifying human factors issues before systems are built and demonstrating the importance of those issues to decision makers outside the human factors community is difficult. Modeling and simulation (M&S) has become a critical part of tackling this challenge, but the true impact of M&S is made when the results can be translated into predictions that are important to the decision makers such as future system performance. Through the use of the Improved Performance Research Integration Tool (IMPRINT), analysts are able to quantify the effect of human operator performance on system performance. IMPRINT is a task network modeling tool designed to help assess the influence of the human operator on system performance throughout the system lifecycle. This demonstration will provide a brief overview of IMPRINT and its capabilities and highlight new features that provide enhanced modeling capabilities and better results visualization. It will also feature a look at the new Multimodal Interface Design Support (MIDS) tool plug-in that provides users with analysis specific multimodal design guidelines they could be implemented into the system design to minimize mental overload and improve system performance.
Transmission line representation of a lightning return stroke

In order to deduce the form of the current pulse in a lightning return stroke at altitude from measurements made at ground level, a model of the channel is required. Inductance and capacitance values for a ladder LCR network representing the lightning channel are deduced from the initial electrostatic field distribution around a simplified model of a charged cloud and a vertical unbranched leader. The resistance of the channel is assumed constant with height, and all the network parameters are assumed independent of time. Current pulses are calculated at ground level and at various heights. The pulse parameters deduced at ground level are in rough agreement with observation. The predicted variation of the current pulse with altitude is discussed, and the implications for assessing the risks to aircraft are briefly described.
Radiation pattern reconfigurable microstrip antenna for WiMAX application

A microstrip antenna with reconfigurable radiation pattern characteristics in the wireless interoperability for microwave access (WiMAX) band is presented. By controlling the states of these four pin diodes, different radiating elements can be activated, which leads to four different radiation patterns for WiMAX application in the 3.44–3.6 GHz range. By sequentially activating the pin diodes, the antenna main beam rotates by 90° in azimuth planes, with 30° deflection in the elevation plane. Moreover, the proposed antenna has a compact structure and good realised gain levels with a minimum value of 8 dBi. The measured results of the fabricated antenna prototype verify the simulation analysis.
A Previously Undiscovered Circular RNA, circTNFAIP3, and Its Role in Coronavirus Replication

CircRNAs, a new class of ncRNAs, play important roles in cell growth, neural development, carcinogenesis, and anticarcinogenesis. Porcine deltacoronavirus is an emerging enteropathogenic coronavirus that causes diarrhea, but the role of host circRNAs in regulating its infection is unknown. ABSTRACT Circular RNAs (circRNAs) are a newly discovered class of noncoding RNAs (ncRNAs) present in various tissues and cells. However, the functions of most circRNAs have not been verified experimentally. Here, using deltacoronavirus as a model, differentially expressed circRNAs in cells with or without deltacoronavirus infection were analyzed by RNA sequencing to characterize the cellular responses to RNA virus infection. More than 57,000 circRNA candidates were detected, and seven significantly dysregulated circRNAs were quantitated by real-time reverse transcription-PCR. We discovered a previously unidentified circRNA derived from the TNFAIP3 gene, named circTNFAIP3, which is distributed and expressed widely in various tissues. RNA viruses, including deltacoronaviruses, rather than DNA viruses tend to activate the expression of endogenous circTNFAIP3. Overexpression of circTNFAIP3 promoted deltacoronavirus replication by reducing the apoptosis, while silencing of circTNFAIP3 inhibited deltacoronavirus replication by enhancing the apoptosis. In summary, our work provides useful circRNA-related information to facilitate investigation of the underlying mechanism of deltacoronavirus infection and identifies a novel circTNFAIP3 that promotes deltacoronavirus replication via regulating apoptosis. IMPORTANCE CircRNAs, a new class of ncRNAs, play important roles in cell growth, neural development, carcinogenesis, and anticarcinogenesis. Porcine deltacoronavirus is an emerging enteropathogenic coronavirus that causes diarrhea, but the role of host circRNAs in regulating its infection is unknown. Here, we performed expression profiling of circRNAs in mock- and deltacoronavirus- infected cells and identified the novel differentially expressed circular RNA circTNFAIP3. We demonstrate that circTNFAIP3 promotes deltacoronavirus replication by inhibiting apoptosis. Our findings first illustrate that circRNA can act as an apoptosis negative regulator during RNA virus infection and help to explore the underlying mechanism of deltacoronavirus infection.
The Epstein-Barr Virus Oncogene EBNA1 Suppresses Natural Killer Cell Responses and Apoptosis Early after Infection of Peripheral B Cells

Epstein-Barr virus (EBV) is a ubiquitous human pathogen, infecting up to 95% of the world’s adult population. Initial infection with EBV can cause infectious mononucleosis. ABSTRACT The innate immune system serves as frontline defense against pathogens, such as bacteria and viruses. Natural killer (NK) cells are a part of innate immunity and can both secrete cytokines and directly target cells for lysis. NK cells express several cell surface receptors, including NKG2D, which bind multiple ligands. People with deficiencies in NK cells are often susceptible to uncontrolled infection by herpesviruses, such as Epstein-Barr virus (EBV). Infection with EBV stimulates both innate and adaptive immunity, yet the virus establishes lifelong latent infection in memory B cells. We show that the EBV oncogene EBNA1, previously known to be necessary for maintaining EBV genomes in latently infected cells, also plays an important role in suppressing NK cell responses and cell death in newly infected cells. EBNA1 does so by downregulating the NKG2D ligands ULBP1 and ULBP5 and modulating expression of c-Myc. B cells infected with a derivative of EBV that lacks EBNA1 are more susceptible to NK cell-mediated killing and show increased levels of apoptosis. Thus, EBNA1 performs a previously unappreciated role in reducing immune response and programmed cell death after EBV infection, helping infected cells avoid immune surveillance and apoptosis and thus persist for the lifetime of the host. IMPORTANCE Epstein-Barr virus (EBV) is a ubiquitous human pathogen, infecting up to 95% of the world’s adult population. Initial infection with EBV can cause infectious mononucleosis. EBV is also linked to several human malignancies, including lymphomas and carcinomas. Although infection by EBV alerts the immune system and causes an immune response, the virus persists for life in memory B cells. We show that the EBV protein EBNA1 can downregulate several components of the innate immune system linked to natural killer (NK) cells. This downregulation of NK cell activity translates to lower killing of EBV-infected cells and is likely one way that EBV escapes immune surveillance after infection. Additionally, we show that EBNA1 reduces apoptosis in newly infected B cells, allowing more of these cells to survive. Taken together, our findings uncover new functions of EBNA1 and provide insights into viral strategies to survive the initial immune response postinfection.
Customer centric practices: implications for banks in India

Researchers and practioners have proclaimed the adoption of customer oriented philosophy in banks as the key to maintaining a sustainable competitive advantage. By considering the views of 232 bank employees, the results indicate that using factor analysis, four factors responsible for customer orientation in Indian banks are customer value creation, better customer understanding, frontline customer relationship and solution through empowerment. The two independent sample t-test indicated the differences on variables such as comprehensive need analysis, frontline customer understanding, tailor products, growth and employee productivity between higher and lower levels of employees. Using regression analysis, we find that comprehensive need analysis and incentives of profitability as the predictor for growth; frontline customer understanding and suggestions for new products for profitability and suggestions for new products and tailor products for employee productivity.
Colliding respiratory jets as a mechanism of air exchange and pathogen transport during conversations

Abstract Air exchange between people has emerged in the COVID-19 pandemic as the important vector for transmission of the SARS-CoV-2 virus. We study the airflow and exchange between two unmasked individuals conversing face-to-face at short range, which can potentially transfer a high dose of a pathogen, because the dilution is small when compared to long-range airborne transmission. We conduct flow visualization experiments and direct numerical simulations of colliding respiratory jets mimicking the initial phase of a conversation. The evolution and dynamics of the jets are affected by the vertical offset between the mouths of the speakers. At low offsets the head-on collision of jets results in a `blocking effect', temporarily shielding the susceptible speaker from the pathogen carrying jet, although, the lateral spread of the jets is enhanced. Sufficiently large offsets prevent the interaction of the jets. At intermediate offsets (8-10 cm for 1 m separation), jet entrainment and the inhaled breath assist the transport of the pathogen-loaded saliva droplets towards the susceptible speaker's mouth. Air exchange is expected, in spite of the blocking effect arising from the interaction of the respiratory jets from the two speakers.
10 Gbit/s optical BPSK homodyne detection experiment with solitary DFB laser diodes

Solitary DFB laser diodes with 174 kHz beat linewidth are applied to a 10 Gbit/s optical BPSK homodyne detection system for the first time: a sensitivity of -38.9 dBm was achieved. A three-electrode laser forms the local oscillator and is modulated with a partial push-pull scheme to improve its frequency response. >
Machine learning approaches for error correction of hydraulic simulation models for canal flow schemes

AbstractModernization of today’s irrigation systems attempts to improve system efficiency and management effectiveness of every component of the system (reservoirs, canals, and gates) using automation technologies, along with hydraulic simulation models. The canal flow control scheme resulting from the coupling of the system automation and the simulation models has proven to be an excellent irrigation water management instrument around the world. Nevertheless, the harsh environment of irrigation systems can induce uncertainties or errors in the components of canal flow control that can worsen over time, misleading or confusing both human and computer controllers. These errors can be attributed to parameter measurement and conceptual sources, with the complexity of locating their individual origin. In this paper, a framework is presented to minimize the collective or aggregate error within an irrigation canal flow control scheme that uses a learning machine algorithm (multilayer perceptron and relevance ve.
Load flow analysis and future development study for an AC electric railway

This study presents a forward/backward sweep (FBS) load flow method for AC autotransformer (AT)-fed electrical railway networks considering dynamic movement of trains. Field measurements of Tehran–Golshahr suburban railway are compared with simulation results. Moreover, effects of the time headway reduction on this suburban railway and its transmission power supply system are investigated. Then, to minimise power losses, two methods of the reactive power compensation are studied; the pulse-width-modulated (PWM) trains and a static var compensator (SVC). For the aforementioned cases, fluctuations of the displacement factors (DISF), defined in p–q–r theory are simulated at the point of common coupling (PCC). MATLAB software is used for programming and simulations.