Miracle-dz/UniFAR-FTUs huggingface dataset:
Lie Group Approach to Dynamic-model-aided Navigation of Multirotor Unmanned Aerial Vehicles

In this study, the Lie group approach was used for state estimation of the dynamic-model-aided navigation (DMAN) of a small multirotor unmanned aerial vehicle. The unit quaternions constituting a Lie group called the three-sphere space (S³) were used to represent the attitude in the dynamic equations for the process and measurement models. The linearization of these models is presented in terms of Lie algebra corresponding to S³. The use of Lie algebra to describe the attitude increment conforms to the linearity assumption, on which the measurement update of the extended Kalman filter (EKF) is based. In this study, it was experimentally validated that the Lie group approach combined with DMAN performs better than the EKF that uses the conventional linearization of the process and measurement models under the assumption that the nonlinearity effect is negligible for a small attitude increment. It was demonstrated that the navigation states estimated using the proposed model are better than or comparable to those obtained using the current methods, and the proposed method significantly improves the internal properties.
High-Throughput Deep Unfolding Network for Compressive Sensing MRI

Deep unfolding network (DUN) has become the mainstream for compressive sensing MRI (CS-MRI) due to its good interpretability and high performance. Different optimization algorithms are usually unfolded into deep networks with different architectures, in which one iteration corresponds to one stage of DUN. However, there are few works discussing the following two questions: Which optimization algorithm is better after being unfolded into a DUN? What are the bottlenecks in existing DUNs? This paper attempts to answer these questions and give a feasible solution. For the first question, our mathematical and empirical analysis verifies the similarity of DUNs unfolded by alternating minimization (AM), alternating iterative shrinkage-thresholding algorithm (ISTA) and alternating direction method of multipliers (ADMM). For the second question, we point out that one major bottleneck of existing DUNs is that the input and output of each stage are just images of one channel, which greatly limits the transmission of network information. To break the information bottleneck, this paper proposes a novel, simple yet powerful high-throughput deep unfolding network (HiTDUN), which is not constrained by any optimization algorithm and can transmit multi-channel information between adjacent network stages. The developed multi-channel fusion strategy can also be easily incorporated into existing DUNs to further boost their performance. Extensive CS-MRI experiments on three benchmark datasets demonstrate that the proposed HiTDUN outperforms existing state-of-the-art DUNs by large margins while maintaining fast computational speed.11For reproducible research, the source codes and training models of our HiTDUN. [Online]. Available: https://github.com/jianzhangcs/HiTDUN.
A Semantic Approach to Ranking Techniques: Improving Web Page Searches for Educational Purposes

The Web offers an unprecedented number of resources and has become the most popular source of information for students shaping their understanding of a new topic, and for instructors selecting relevant material for learning and teaching activities. Even though search engines are the most widely used tools for searching for educational content, the realities of the learning and teaching processes make the retrieval and evaluation of educational resources more complex than they are for other goods or services. The lack of recourse to educational metadata in web pages, as well as the size of the Web itself, call for specific techniques to be adopted for a more effective ranking of educational content. In this study, we propose an innovative approach based on semantic technologies. The SemanticSearch approach described in this paper leverages knowledge graph representation of teaching contexts and proposes a new ranking method for rating educational web content. In the literature we find an Educational Ranking Principle that ranks web pages for a specific teaching context. In this study, we integrate the Educational Ranking Principle with semantic data to extend the experimentation and analyse performance further. We undertake an evaluation involving university teachers, considering more than 70 queries to measure the SemanticSearch performance against the Educational Ranking Principle in addition to two state-of-the-art methodologies: Tf-Idf and BM25F. Paired t-tests of four accuracy measures provide statistical evidence for improvements made using SemanticSearch method accuracy in evaluating web pages when compared to the three baselines.
The Future Roadmap of In-Vehicle Network Processing: a HW-centric (R-)evolution

The automotive industry is undergoing a deep revolution. With the race towards autonomous driving, the amount of technologies, sensors and actuators that need to be integrated in the vehicle increases exponentially. This imposes new great challenges in the vehicle electric/electronic (E/E) architecture and, especially, in the In-Vehicle Network (IVN). In this work, we analyze the evolution of IVNs, and focus on the main network processing platform integrated in them: the Gateway (GW). We derive the requirements of Network Processing Platforms that need to be fulfilled by future GW controllers focusing on two perspectives: functional requirements and structural requirements. Functional requirements refer to the functionalities that need to be delivered by these network processing platforms. Structural requirements refer to design aspects which ensure the feasibility, usability and future evolution of the design. By focusing on the Network Processing architecture, we review the available options in the state of the art, both in industry and academia. We evaluate the strengths and weaknesses of each architecture in terms of the coverage provided for the functional and structural requirements. In our analysis, we detect a gap in this area: there is currently no architecture fulfilling all the requirements of future automotive GW controllers. In light of the available network processing architectures and the current technology landscape, we identify Hardware (HW) accelerators and custom processor design as a key differentiation factor which boosts the devices performance. From our perspective, this points to a need - and a research opportunity - to explore network processing architectures with a strong HW focus, unleashing the potential of next-generation network processors and supporting the demanding requirements of future autonomous and connected vehicles.
The effect of gas removal on the dynamical evolution of young stellar clusters

Un modele decrivant le retrait rapide du gaz des jeunes regions de formation stellaire est developpe. Le retrait rapide du gaz d'un etat non-virialise et pendant les oscillations autour de l'etat d'equilibre de viriel est etudie. Une simulation numerique pour un amas ouvert est realisee
Motor Overvoltage Mitigation on SiC MOSFET Drives Exploiting an Open-End Winding Configuration

Voltage wave reflection phenomena along power cables are particularly threatening on ac motor drives equipped with silicon carbide power mosfets due to very short switching times and high switching frequency. Overvoltage suppression resistance inductance capacitance (RLC) networks are usually added but leading to extra cost and a lower efficiency. A completely different overvoltage mitigation approach is presented in this paper exploiting an open-end winding motor configuration. Overvoltage occurring on the terminals of motor phase windings are, in fact, mitigated by simply coordinating the operations of the two inverters; thus, no passive RLC networks are required. The proposed approach is intended as a mean to provide a further valuable feature to open-winding systems at no extra cost, but it can be also valued as an alternative to conventional bridge inverters equipped with overvoltage mitigation devices.
PERSPECTIVES AND FUTURE OUTLOOK OF DEEP LEARNING AI

— Deep learning is an emerging AI based technology that has provided breakthroughs in different areas such as Visual Object Recognition, Natural language processing and Speech recognition either matching or surpassing Human Performance. Affordable high computing power, specialized hardware and advancement of machine learning algorithms have provided the growth acceleration for deep learning. The paper provides a high level classification of the Deep learning based architectures, top level view of the recent industry based developments undertaken on a global scale for embracing this technology, current features that have achieved state of the art performance in various fields such as Computer Vision, Speech Processing, Cloud Computing, Healthcare, Robotics, Nanotechnology, Genetics. Finally the paper looks at the forthcoming features in pipeline in all major fields and future of AI .
Capacity Market Implementation in Poland: Analysis of a Survey on Consequences for the Electricity Market and for Energy Management

The power sector is currently experiencing a dynamic transformation, resulting not only from EU directives, but also from current problems, mainly related to ensuring energy security for customers. For this reason, in Poland, it was decided that the model of electricity market operation needed to be changed. A dual market has been created, and a separated segment is the capacity market. This solution operates, in addition to other power mechanisms, in many European Union countries, e.g., in France, Great Britain, and Italy. The experience of these countries indicates the positive impact of the power market on various aspects of the power sector, such as legal, economic, technical and technological, social, and infrastructural aspects, mainly due to technological neutrality and open competition between power suppliers. The creation of the structure of an energy market drastically changes the rules of energy management, which requires investigations concerning the impact of those factors on the energy sector in Poland. The aim of this work is to examine the impact of the power market on the Polish power sector, and to determine the impact of individual consequences on several predefined areas. For this purpose, a questionnaire survey was used. The purpose of a detailed analysis is to develop probable scenarios for the sustainable development of the Polish energy sector.
Identify and Ranking the Factors Influencing Insurance Company’s Competitive Advantage with Qualitative and Quantitative Methods

This research has been performed to identify the factors that can help to attain competitive advantage in insurance companies. In addition, in order to determine which factors have more priorities to attain by insurance companies, their ranking also been considered. The research way is exploratory mixed method. First, the factors affecting on attain competitive advantage of insurance have been identified through selecting the factors that were mist frequent, this factors were ranked with fuzzy AHP technique using paired comparisons questionnaire. In order to do an interview, by using the purposive sampling, 17 experts and top managers of insurance were selected as a sample and also then these people responded to paired comparisons questionnaire. Identified factors were divided to six criteria including comfort, quality, customer responsiveness, creativity, services and brands. The research results showed that among comfort and welfare criteria, the number of representatives with fuzzy weight 0/2722 is in first priorities and the flexibility in presenting insurance services based on the conditions of policyholders with 0/2004 weight have second priority. Among services qualitative criteria, the way of communication of employee of insurance company with 0/2173 weight is in first place. Also, for ranking and identifying the fuzzy weights, the indices of respond to customers, innovation, internet service and brand was done.
Impact of Integrated Vector Control Strategy on Malaria Incidence and Disability Adjusted Life Years (Daly) at Bharat Heavy Electricals Limited, Hardwar, India-Results of 25 Years Study

A project on Integrated Vector Control strategy on malaria was launched at Bharat Heavy Electricals Limited, Hardwar, Uttarakhand, India in 1986. Major components of intervention strategy were source reduction, improving drainage, application of Expanded Polysterene Beads (EPS), biological control, use of larvivorous fishes Poecilia reticulata and Gambusia affinis , bacterial larvicides Bactoculicide ( Bacillus thuringiensis israelensis and Spherix ( B. sphaericus ), limited use of fogging with malathion for the control of Culex mosquitoes, health education and community participation, prompt case detection, proper treatment and follow up of all malaria positive cases. Impact of Integrated Vector Control strategy on malaria incidence with time and estimation of diseases burden in term of Disability Adjusted Life Years (DALY) are presented in this paper. Implementation of Integrated Vector Control strategy on malaria incidence, at BHEL, Hardwar drastically reduced malaria cases from 2733 in 1986 to 593 in 1987 and constantly decreased up to 1994 with total cases of 96 which implied that there is no indigenous transmission in BHEL area. A slight increase of malaria cases was recorded from 1995 to 1997 with the total cases of 245, 286 and 238 respectively and then decreased constantly till 2011with an overall reduction above 95%. Highest DALY lost was estimated for the age category ≥ 14 in 1986, which showed a sharp decline over the years. However a general decline in DALY was observed in all age groups. Integrated Vector Control strategy on malaria incidence in industries complex at BHEL Hardwar with limited use of insecticide is highly effective, sustainable in long run, economical and resulted drastic reduction in DALY besides major reduction in malaria cases.
The ideal urban soundscape : Investigating the sound quality of french cities

A questionnaire study was conducted to investigate the sound quality of urban environments. Seventy-seven participants living in large French cities were questioned about their appraisal of familiar urban soundscapes in a free-response format questionnaire. A psycholinguistic analysis of spontaneous verbal descriptions was conducted to identify semantic categories of environmental sounds and relevant sound quality criteria for urban soundscapes. Our results confirm the influence of semantic features, besides physical ones, on auditory judgments, and further reveal the salience of human sounds.
S 1 Supporting Information for : “ Mechanosensitive Ion Permeation across Sub-Nanoporous MoS 2 Monolayers ”

All charges were calculated according to the density functional theory (DFT)-based procedure utilized earlier for bulk MoS2 [1]. For our DFT calculations, the total charges of the structures were set to be -2e or +2e as described in the main text, with a spin multiplicity of 1, corresponding to no dangling bonds. The complete set of partial electrostatic charges obtained from converged DFT calculations and used in the molecular dynamics (MD) simulations is shown in Fig. S1. All atoms without specific charge labels were assigned bulk atomic charges of +0.5e and -0.25e for Mo and S atoms, respectively [1]. All bonded (harmonic bonds and angles) and non-bonded (Lennard-Jones interactions) parameters were assigned according to the bulk MoS2 parameterization [1], with the exception of the atoms selected in black rectangles in the S2-lined pore in Fig. S1. For these atoms, to achieve a better agreement between the relaxed pore structures obtained from DFT calculations and their MD counterparts, the θ0 parameter for the corresponding S-Mo-S angle was reduced from 83.8 to 37.0 degrees due to S-S bond formation.
Evaluation of in-vitro antioxidant activity of marketed Tobacco products

Objective: In this study, the antioxidant activities of methanolic extract of marketed tobacco products were evaluated by different in vitro antioxidant methods. Materials and methods: The different marketed tobacco products were extracted with methanol by means of maceration process. These extracts were screened for antioxidant activity by different in vitro assay methods including Reducing power assay, Phosphomolybdenum assay, Iron chelating assay and Nitric oxide scavenging activity. The screening was carried out at different concentration including 100, 200, and 300µg/ml in reducing power assay, phosphomolybdate assay and Nitric oxide scavenging activity while in chelating assay the extract was used in concentration of 50, 100, 150 and 200µg/ml. Results: All Tobacco products exhibit the antioxidant potential with increasing concentration. The anti-oxidant activity of the marketed tobacco product might be attributed to its polyphenolic content and other phytochemical constituents. Hence, further investigation need to be carried out to isolate and identify the anti-oxidant compounds present in the Tobacco extract. Conclusion: Our study concluded that, the Tobacco causes addiction and dependence but till it has many folklore traditional medicinal uses. If it is used in positive way then it has power to treat and protect but if misused then it have power to harm the body. assay, Nitric oxide scavenging assay.
Cholinergic signals promote esophageal squamous cell carcinoma metastasis by activating EGFR/AKT signaling pathway

Tao Wang The A liated Huaian No.1 People’s Hospital of Nanjing Medical University Bei-Bei Ge The A liated Huaian No.1 People’s Hospital of Nanjing Medical University Chang Liu The A liated Huaian No.1 People’s Hospital of Nanjing Medical University Li-Juan Xu The A liated Huaian No.1 People’s Hospital of Nanjing Medical University Bin Wei The A liated Huaian No.1 People’s Hospital of Nanjing Medical University Yong Gao (  hayygaoy@njmu.edu.cn ) The A liated Huaian No.1 People’s Hospital of Nanjing Medical University
Study of the Brand and Bound Algorithm Performance on Traveling Salesman Problem Variants

Traveling salesman problem (TSP) can be applied to distribution problems, namely determining the minimum route from the depot to all customers exactly once and back to the depot. Some constraints can be added to the problem such as time constraints, additional salesmen on the route that is passed, the need for an order of delivery, and passing one-way road. This article will discuss TSP variants developed from basic TSP, namely TSPTW, MTSP, TSPPC, and ATSPTW. The differences in formulations of these variants are described and the branch and bound algorithm is used to solve them. There are three main steps to the branch and bound algorithm namely the initialization stage to obtain the initial solution, the process stage and solution improvement, and the determination of the optimum solution. Identification of the similarities and differences in the application of the branch and bound algorithm steps on these variants are discussed in this article. An example is given of the application of the branch and bound algorithm to the four variants of 8 customers and one depot. The results of the application examples are depicted on a graph in order of the minimum total distance, namely ATSPTW, TSPTW, TSPPC, and MTSP.
Comparing the Performance of Evolutionary Algorithms for Sparse Multi-Objective Optimization via a Comprehensive Indicator [Research Frontier]

Many real-world multi-objective optimization problems (MOPs) are characterized by a large number of decision variables, where the decision variables are mostly set to zero in the Pareto optimal solutions. Although some multi-objective evolutionary algorithms (MOEAs) have been tailored for large-scale MOPs in recent years, most of them do not consider the sparse nature of Pareto optimal solutions, and their effectiveness to sparse MOPs has not been investigated. Therefore, this work aims to compare the performance of MOEAs on sparse MOPs by suggesting a comprehensive performance indicator. In comparison to existing indicators assessing the convergence and diversity of a solution set according to predefined reference points, the proposed indicator can assess the convergence, diversity, and sparsity without using any reference point. Based on the proposed indicator, an experiment is conducted to compare the performance of 11 state-of-the-art MOEAs on 60 test instances taken from benchmark suites and real-world applications. The statistical results show that some MOEAs are significantly better than the others for solving sparse MOPs, and the proposed indicator is effective for the performance assessment on sparse MOPs.
JOKR: Joint Keypoint Representation for Unsupervised Video Retargeting

In unsupervised video retargeting, content is transferred from one video to another while preserving the original appearance and style, without any additional annotations. While this challenge has seen substantial advancements through the use of deep neural networks, current methods struggle when the source and target videos are of shapes that are different in limb lengths or other body proportions. In this work, we consider this task for the case of objects of different shapes and appearances, that consist of similar skeleton connectivity and depict similar motion. We introduce JOKR—a JOint Keypoint Representation that captures the geometry common to both videos, while being disentangled from their unique styles. Our model first extracts unsupervised keypoints from the given videos. From this representation, two decoders reconstruct geometry and appearance, one for each of the input sequences. By employing an affine‐invariant domain confusion term over the keypoints bottleneck, we enforce the unsupervised keypoint representations of both videos to be indistinguishable. This encourages the aforementioned disentanglement between motion and appearance, mapping similar poses from both domains to the same representation. This allows yielding a sequence with the appearance and style of one video, but the content of the other. Our applicability is demonstrated through challenging video pairs compared to state‐of‐the‐art methods. Furthermore, we demonstrate that this geometry‐driven representation enables intuitive control, such as temporal coherence and manual pose editing. Videos can be viewed in the supplement HTML.
Evaluation of existing infiltration models used in building energy simulation

Infiltration modeling is one of the major sources of uncertainty in building energy simulation. Although many infiltration models exist, their structures and assumptions vary, and many of them are inaccurate for commercial buildings. The use of these models are rarely updated or revised due to the high cost for tests that are used to determine infiltration rates. In this study, tracer gas decay and whole-building pressurization tests were performed in a full-scale, two story, unoccupied commercial building. Three different infiltration models within EnergyPlus were used to simulate infiltration rates. The pressurization test result was converted to the design infiltration rate used in each infiltration model. The simulation results were compared with the infiltration rate estimated from the field measurements. The results showed that the predicted infiltration rate and the estimated heating energy consumption can be significantly affected by the infiltration model selection.