Miracle-dz/UniFAR-FTUs huggingface dataset:
Research on Mileage Location Method Based on Metro Feature Recognition

Aiming at the problems of low positioning accuracy and poor robustness of traditional odometers, this paper proposes a mileage positioning method based on subway feature recognition. First, use the YOLOv3 target detection method to identify the characteristics of the track fasteners, and obtain the position information of the characteristic points. Then, distance clustering and Lagrangian interpolation are used to complete the feature points that are not detected by deep learning. Finally, the initial mileage value is obtained according to the mileage constraint, and the speed filter method is used to correct the mileage result. In order to verify the reliability of the mileage positioning method, a mobile laser scanning experiment was carried out in Xi’an Metro. Experimental results show that this method has good positioning accuracy and stability. After Kalman speed filter preprocessing, the mileage positioning error is about 7cm, and the standard error is 5.05 × 10-3, which provides accurate mileage results for subway inspections.
HTTP Traffic Analysis based on Multiple Deep Convolution Network Model Generation Algorithms

In recent years, with the development of the Internet, social networking, online banking, e-commerce and other network applications are growing rapidly. At the same time, all kinds of malicious web pages are constantly emerging. Under the new situation, the network security threats are distributed, large-scale and complex. New network attack modes are emerging. With more and more diverse devices access to the Internet, our life is more intelligent and convenient, but also brings more loopholes and hidden dangers. Some malicious web pages through a variety of means to lure users to open URL links and conduct malicious behavior. However, if we can detect the URL of the malicious web page and identify the malicious web page, we can avoid the problems of content variability and behavior tracking. Therefore, traffic analysis based on various deep convolution network model generation algorithms arises at the historic moment, and becomes an important research issue in the field of Internet security.
Early Warning Model of Track and Field Sports Injury Based on RBF Neural Network Algorithm

Track and field events are the foundation of sports events. To learn other sports events well, you must also have a certain grasp of track and field events. As the movements of each track and field event become more and more complex, the competition becomes more and more intense, and the technical requirements are getting higher and higher. Therefore, sports injuries are gradually increasing. The prevention of sports injuries is a hot spot in sports medicine. Studies have found that as many as twenty factors can directly or indirectly cause track and field sports injuries. Based on the collected data on the injury-causing factors of elite athletes’ track and field sports, and on the basis of in-depth research on mobile data processing technology and early warning risks, a mobile early warning system and radial system using sports injury risk early warning algorithms, functional design and architecture are proposed. The basis function (RBF) neural network algorithm is released. Research on Early Warning Model of Sports Injury. This article analyzes and evaluates different hazard factors through the method of literature data, expert review and extensive analysis. In the investigation, the various causes of the injury were analyzed in detail, and it was found that most sports injuries were caused by students’ lack of attention, technical errors, insufficient preparation activities, etc., and finally proposed countermeasures to solve the problem, so that the sports injury situation was obtained improve.
Optimization Research on Server Detection Based on RGB Maximum Mean Features and Deep Belief Network Model

The intelligent detection about the running state of server equipment in computer room is a very important research field. In general, the state recognition research of signal lamp mainly includes the color and shape characteristics of signal lamp, and machine learning models. At present, the research results in this respect are not ideal for the recognition of signal lamps, Due to the small size and high density of the detected server lamp source, its shape characteristics cannot be accurately obtained, and state information is difficult to be perceived. This paper proposes a RGBMM features algorithm and a DBN network model algorithm, which is different from the traditional signal state recognition algorithm. According to the characteristics of server signal lamp, the color state image data of signal lamp is extracted effectively by RGBMM features algorithm, then the DBN network model algorithm is used to evaluate and identify the sampled signals, so as to judge whether the server is working normally. The experimental results show that the state recognition accuracy of the signal lamp is up to 98%, while the recognition rate of the signal lamp color state image using HSV( ( Hue, Saturation, Value) ) transformation is 90.7%. The difference between the three is different the algorithms used. So the RGBMM features algorithm and the DBN network model algorithm have a wider use for the signal lamp color status recognition.
Common Python Data Analysis Method Based on Deep Learning

In recent years, with the continuous development and progress of machine learning technology, especially the successful application of deep learning algorithm in the field of image and big data processing, how to efficiently develop and apply machine learning technology has become a hot issue. This paper focuses on deep learning-based common Python data analysis methods. In this paper, a traffic flow prediction and analysis model based on convolutional neural network is established according to the traffic flow characteristics of the first ring expressway in this city. According to the characteristics of urban expressway traffic flow and the spatial correlation of traffic flow, the traffic flow data in the spatial and temporal dimension are combined in the form of two-dimensional matrix as the network input, and the CAFRE framework based on deep learning is used to design the expressway traffic flow prediction model based on convolutional neural network. The model takes into account the historical traffic flow of the predicted sections and the traffic flow of the upstream and downstream sections, and restricts the model structure by capturing the road range with high spatial correlation.
Research on Conversion of Waste Polyethylene Terephthalate into Value-Added Monomer replacing Landfill and Incineration for Environmental Pollution Control

Traditional Polyethylene terephthalate (PET) disposal methods are mainly mechanical recycling, landfill and incineration, which have some problems such as poor quality of recycled products and environmental pollution. By comparison, the products of chemical recycling can be resynthesized into PET, saving petrochemical resources and reducing environmental pollution. In view of this, some recent chemical recycling methods that convert waste PET into value-added monomers are summarized in this paper. For instance, PET can be reduced by hydrogen into terephthalic acid or other valuable products. And it can be decomposed into bis(2-hydroxyethyl) terephthalate in the presence of ethylene glycol and catalysts such as magnetic metal oxides. Also, it can be hydrolyzed into terephthalic acid and ethylene glycol by green catalyst. Besides, it can be pyrolyzed into benzene catalyzed by non-noble metal oxides. Finally, several possible strategies have been proposed to help convert waste PET into value-added monomers.
“All‐in‐One” Nanoparticles for Trimodality Imaging‐Guided Intracellular Photo‐magnetic Hyperthermia Therapy under Intravenous Administration

Great efforts have been devoted so far to combine nano‐magnetic hyperthermia and nano‐photothermal therapy to achieve encouraging additive therapeutic performance in vitro and in vivo with limitation to direct intratumoral injection and no guidance of multimodality molecular imaging. In this study, a novel multifunctional theranostic nanoplatform (MNP@PES‐Cy7/2‐DG) consisting of magnetic nanoparticles (MNPs), poly(3,4‐ethylenedioxythiophene):poly(4‐styrenesulfonate) (PES), Cyanine7 (Cy7), and 2‐deoxyglucose (2‐DG)‐polyethylene glycol is developed. They are then applied to combined photo‐magnetic hyperthermia therapy under intravenous administration that is simultaneously guided by trimodality molecular imaging. Remarkably, nanoparticles are found aggregated mainly in the cytoplasm of tumor cells in vitro and in vivo, and exhibit stealth‐like behavior with a long second‐phase blood circulation half‐life of 20.38 ± 4.18 h. Under the guidance of photoacoustic/near‐infrared fluorescence/magnetic resonance trimodality imaging, tumors can be completely eliminated under intracellular photo‐magnetic hyperthermia therapy with additive therapeutic effect due to precise hyperthermia. This study may promote a further exploration of such a platform for clinical applications.
Type and placement of zinc fertilizer impacts cadmium content of harvested durum wheat grain

ABSTRACT Due to potential international marketing concerns, North Dakota durum wheat (Triticum turgidum L. Desf.) producers require strategies that limit cadmium (Cd) in harvested grain. These trials were conducted in order to determine the impact of type and placement of zinc (Zn) fertilizer on harvested grain seed Cd levels and to determine the best timing of foliar Zn-ethylenediaminetetraacetic acid (EDTA). Foliar Zn-EDTA applied at Feekes 10 growth stage had the lowest grain Cd of 0.97 mg kg−1 when evaluating different fertilizer sources and application timings. Application of 22.4 kg ha−1 potassium chloride with the seed at planting resulted in the highest grain Cd of 0.151 mg kg−1 and might be a concern when environmental conditions are conducive for Cd uptake from soil. Stepwise linear regression determined that soil pH and chloride explained 96% of the variability of grain Cd. Applying 1.1 kg Zn ha−1 as foliar Zn-EDTA in combination with 33 kg nitrogen ha−1 at Feekes 10.54 growth stage resulted in significantly lower grain Cd, and significantly higher grain Zn, iron, and protein content. Treatments that significantly lowered grain Cd did not decrease grain yield, test weight, or protein content. The treatments that most reduced grain Cd resulted in the most benefits from a production, marketing, and nutritional standpoint and represents an agronomic approach to biofortification of durum wheat.
Influence of organic carbon sources and isotope exchange processes between water and nitrate on the fractionation of the stable isotopes ¹⁵N/¹⁴N and ¹⁸O/¹⁶O in dissolved nitrate during microbial denitrification in groundwater

Stable isotopes of nitrate are commonly used to determine sources and degradation of nitrate. In this study, nitrite oxidizing bacteria were found to promote an oxygen isotope exchange between water and nitrate under anoxic conditions. Also, different carbon sources were found to influence the enrichment of stable isotopes in nitrate during microbial denitrification. Both results refine the stable isotope model of nitrate in respect to nitrate source determination and microbial nitrate reduction.
The Relationship Between Online Referral Marketing and Price Promotion: Evidence from a Large E-Commerce Platform

ABSTRACT We empirically examine the effectiveness of referral marketing and price promotion in generating sales in a large e-commerce platform. Our results show that although referral marketing increases sales, its effect is attenuated by price promotion. We argue that price promotion arouses quality concerns and undermines the credibility of online paid referrals in a weak-tie environment. This finding implies diminishing marginal returns for referral marketing and price promotion spending. We conduct a battery of validation tests to support our argument. Our research highlights the importance of scrutinizing the complementarity of marketing promotions in the unique context of the Internet. Depending on the persuasiveness of the brand and the promotional channel, promotional strategies may conflict in addressing consumers’ quality concerns. Our findings suggest that marketing managers should use discretion in combining online referral marketing and price promotion. We advise sellers against using both marketing tactics if they lack a strong brand image.
Thermal Reactive Ion Etching of Minor Metals with SF6 Plasma

In this study, thermally assisted reactive ion etching (TRIE) was evaluated by both experiments and simulations. TRIE employs a self-heated stage instead of the etching stage of a regular RIE apparatus. The self-heated stage was designed on the base of the simulation results, and its heating characteristics upon the application of radio frequency (RF) power were evaluated. The temperature of the stage increases rapidly within 10 min because of the low thermal capacitance of the stage. An etch rate of 0.6 μm/min and an etch selectivity of about 30 were achieved for titanium etching with SF6 plasma. In addition, we also investigated the application of TRIE for various kinds of minor metals (Mo, Ta, Nb, and Ti alloy) for the first time and achieved higher etch rates and etch selectivities than those of regular reactive ion etching (RIE).
The impact of density heterogeneities on seismic wave propagation

Lateral density variations are the source of mass transport in the Earth at all scales, acting as drivers of convective motion in the mantle. However, the density structure of the Earth remains largely unknown since classic seismic observables and gravity provide only weak constraints with strong trade-offs. Current density models are therefore often based on velocity scaling, making strong assumptions on the origin of structural heterogeneities, which may not necessarily be true.
Localization of ultracold atoms in quasi-periodic optical lattices

Ein hoch angeregtes Vielteilchensystem relaxiert normalerweise in einen Gleichgewichtszustand, in dem alle Observablen ihre thermischen Werte annehmen. Das Verhalten des Systems wird dann effektiv klassisch. Dieses Verhalten, bekannt als Thermalisierung, tritt in fast allen Systemen auf. Bekannte Ausnahmen sind integrierbare Systeme, bei denen eine extensive Anzahl von Erhaltungsgrosen die Dynamik einschrankt, und Vielteilchenlokalisierung, die in nicht-periodischen Potenzialen auftritt. Diese Arbeit befasst sich mit Experimenten zur Lokalisierung von 40K-Atomen in einem quasiperiodischen optischen Gitter. Mithilfe von Messungen der Ausdehnung der Atomwolke, sowie dem Zerfall eines mikroskopischen Dichtemusters im Anfangszustand, charakterisieren wir zunachst das Verhalten einzelner Teilchen in unserem quasi-periodischen Potenzial. Unsere Messungen zeigen, dass sich individuelle Teilchen von einer ausreichend starken Quasiperiodizitat lokalisieren lassen. Wir finden ein Parameterregime, in dem sich das System durch den Aubry-Andre Hamiltonoperator beschreiben lasst. Auserhalb dieses Regimes konnen delokalisierte und lokalisierte Zustande, getrennt von einer Mobilitatskante, koexistieren. Des Weiteren untersuchen wir das Verhalten von Vielteilchensystemen und zeigen, dass die Lokalisierung auch in der Gegenwart von Wechselwirkungen zwischen den Teilchen bestehen bleiben kann. Wir studieren die Dynamik in der Nahe des Phasenubergangs und leiten daraus eine untere Grenze fur die kritische Starke des quasiperiodischen Potenzials ab. Zusatzlich wird ein neu entwickeltes Verfahren zur Implementierung eines gut kontrollierbaren externen Bades vorgestellt. Dieses Bad wird verwendet, um Vielteilchenlokalisierung in offenen Systemen zu erforschen.
Sustainable rubbers and rubber additives

Rubber is one of the most versatile materials having myriad of applications—from niche rubber band and eraser to highly engineered spacecraft seal. Of late, the glittering concept of “sustainability” has been able to infiltrate within the domain of elastomer science and technology to a significant extent - in both academia and industry. This fervent context thus necessitates a systematic documentation of brief history, present research scenario and future perspective of sustainable developments in this field. The present review aims to portray a panoramic sketch of various sustainable rubbers and functional rubber additives in this field and intends to provide a direction to their plausible future developments. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017, 134, 45701.
The role and regulation of cell matrix adhesions during contact inhibition of locomotion

Contact inhibition of locomotion (CIL) was first characterised over 60 years ago and defined as the behaviour of a cell to cease its continued migration in the same direction upon a collision with another cell. It has been implicated in multiple developmental processes including the precise dispersion of haemocytes and the directional migration of the cranial neural crest. In addition its absence has been linked to metastasis in cancer. Although many molecular mechanisms have recently been implicated in CIL, the role of cell-matrix adhesions (CMAs) during this process remains unknown. It has been hypothesised that cellular forces play an important role in CIL; however the role of traction forces generated via CMAs and intercellular tension during CIL is unclear. In this present study neural crest cells are used to elucidate the role and regulation of CMAs during CIL. The findings presented here demonstrate a rapid disassembly of CMAs near the cell-cell contact between colliding cells. This disassembly is shown to be dependent upon the formation of N-cadherin based cellcell adhesions and driven by Src and FAK kinase activity. Furthermore this rapid disassembly of CMAs during CIL leads to a redistribution of intercellular forces from the substrate to the cell-cell contact and is essential to drive cell-cell separation after a collision.
Analysis of Chemical Compositions of 15 Different Cold-Pressed Oils Produced in Turkey: A Case Study of Tocopherol and Fatty Acid Analysis

Many people tend to prefer natural foods and supplements nowadays. Considering this tendency, this study assessed the most significant in quality and purity parameters tocopherol and fatty acid compositions of cold-pressed oils, namely black cumin, sesame, sunflower, poppy, pomegranate, nettle, pumpkin, grape, safflower, flax, canola seed, wheat germ, peanut, hazelnut, and walnut. This study deals with the sample preparation and validation of tocopherols using an HPLC-FLD method for simultaneous determination of α-β-γ-, and δ-tocopherols, and analysis of fatty acid methyl esters (FAME) with using GC-FID. The validated HPLC method was applied for the tocopherols’ analysis and measurement uncertainty was calculated for tocopherols and some fatty acids. The obtained data were evaluated by using principal component analysis to show the relationship between quality parameters and seed oils. Wheat germ, hazelnut, safflower, and sunflower oils have the highest tocopherol contents respectively with a predominance of α-tocopherol. Seed oils’ fatty acid compositions were classified according to proportions of oleic, linoleic, and other fatty acids. This study shows that the evaluated seeds are valuable sources of natural antioxidants and some specific and polyunsaturated fatty acids. The applied method can also be helpful for the industry to obtain quality analysis approach.
Making Sense of MOOCs : Musings in a Maze of Myth, Paradox and Possibility

Well, good morning. Sorry for the delay. But at MIT, you've got to get your technology sorted before you start. Thank you, very much, for inviting me to speak at this most interesting meeting. Your invitation shows admirable broad-mindedness because, last year, I wrote a paper called, "Making Sense of MOOCs, Musings in a Maze of Myth, Paradox and Possibility" that was critical of the MOOCs bandwagon. And six months later, despite the media's feverish enthusiasm for MOOCS, I remain a skeptic.
Enhancing Electron and Hole Extractions for Efficient PbS Quantum Dot Solar Cells

Exploring ways capable of enhancing photocarrier extraction is crucial in further developing the current PbS quantum dots (QDs) solar cells with a standard architecture of ITO/ZnO/PbS-TBAI/PbS-EDT/Au, which are drawing enormous attention due to their high air stabilities and already achieved high power conversion efficiencies. Here, a thin layer of carbon QDs (CQDs) is employed to modify the ZnO film surface to improve photoelectron extraction, and a thin film of PbS QDs treated by a mixed ligand solution of EDT:CuI (PbS-EDT:CuI) is used to replace the PbS-EDT film to improve photohole extraction. This designed device (ITO/ZnO/CQDs/PbS-TBAI/PbS-EDT:CuI/Au) presents significantly improved PCE of 9.95% compared to 8.60% of the reference device (ITO/ZnO/PbS-TBAI/PbS-EDT/Au). In addition, the designed device shows very high air stability.
Modification des propriétés de surface de matériaux lignifiés : impact d'un greffage par voie physique

Dans un contexte de chimie verte, cette these a pour objet les proprietes de surface de materiaux lignifies et se focalise sur l'impact d'un greffage par voie physique, avec comme objectifs : 1) conferer des proprietes hydrophobes a des films d'amidon thermoplastique, 2) controler les reactions de greffage/scission au sein du systeme amidon-lignine lors de l'irradiation et 3) evaluer la contribution de la topographie et de la structure chimique sur le mouillage. Un echantillon de lignine alcaline industrielle de graminees a ete incorpore a hauteur de 20 % a deux types de matrice amidons plastifie par du glycerol (ble ou pomme de terre) pour former des bandes par extrusion. Des proprietes distinctes sont observees en fonction de l'origine de l'amidon, l'amidon de ble etant plus sensible a la formulation et aux conditions de mise en forme. Un traitement par irradiation sous faisceau d'electron a 300 et 350 kGy a ete applique avant ou apres compression des bandes. La compression et l'irradiation conduisent chacune a une diminution de la mouillabilite de surface des bandes, avec obtention de surfaces hydrophobes. L'effet hydrophobant est renforce dans le cas de l'irradiation et augmente avec la dose d'irradiation. Des observations en MEB et AFM ont montre qu'il n'etait pas correle a des variations de rugosite. La reactivite des composes phenoliques a ete etudiee en fonction du traitement. Les acides p-coumarique et ferulique extractibles subissent une conversion pouvant atteindre 60% suite au phenomene de greffage sous irradiation alors que l'extrusion a peu d'effet. La presence de ces composes favorise la condensation des lignines aux depends de leur depolymerisation.
AFDC, SSI, and Welfare Reform Aggressiveness: Caseload Reductions vs. Caseload Shifting

Welfare reform has made receipt of cash benefits more difficult and less attractive for single mothers. We examine whether reforms of AFDC affected caseloads of another program - Supplemental Security Income (SSI). We exploit state variation in welfare reform over time, and find that female-headed households in states aggressively pursuing welfare reform were 21.6 percent more likely to receive SSI. This implies that a decrease in caseloads in one program cannot be interpreted as an equal-sized decrease in the number of families receiving public assistance. In addition, our results have policy implications for the well-being of families affected by welfare reform time limits.