Miracle-dz/UniFAR-FTUs huggingface dataset:
Homogeneity Property Based Two Wheeler Detection Research Using Histogram of Oriented Gradients and Soft Computing

We describe an algorithm to detect two-wheelers with various shapes and viewpoints using the homogeneity property and Histograms of Gradients (HOG). The typical shape of a two-wheeler is can be divided into two parts: human body (upper area) and assembled complex components (bottom). The upper area is substantially homogeneous, because the front and rear body views are simple, whereas the bottom part consists of complex shapes and shows little homogeneity. And the bottom area has very little homogeneity, because it is consisted of complicated shapes. Our algorithm using HOG features based on homogeneity to the upper and lower parts separately and uses Adaboost as the classifier. Furthermore, this paper applied the Adaboost algorithm to classify the objects as the soft computing. Our improved algorithm correctly identified more than 84% of the hardest case tested – motorcycles leaning at 60º - and more than 98% of all types of two-wheelers at 90º.
DDDT_A_260253 5205..5215

*These authors contributed equally to this work Purpose: Prodrug technology-based combination drug therapy has been exploited as a promising treatment strategy to achieve synergistic lung cancer therapy, reduce drug dose, and decrease side effects. In the present study, we synthesized a pH and glutathione (GSH) sensitive prodrug, cisplatin (CIS) and doxorubicin (DOX) conjugates (CIS-DOXp). CIS-DOXp was loaded by nanocarriers and delivered into the tumor site. Methods: pH and GSH sensitive CIS-DOX prodrug (CIS-DOXp) was synthesized by conjugating GSH responsive CIS prodrug with pH sensitive DOX prodrug. CIS-DOXp-loaded nanocarriers (CIS-DOXp NC) were prepared using emulsification and solvent evaporation method. The morphology, particle size, polydispersity index (PDI) and zeta potential of nanocarriers were measured. In vitro cytotoxicity of nanocarriers and the corresponding free drugs was examined using the MTT assay. In vivo anti-tumor efficiency and biodistribution behaviors were evaluated on lung cancer mice models. Results: The size, PDI, zeta potential, CIS loading efficiency, and DOX loading efficiency of CIS-DOXp NC were 128.6 ± 3.2 nm, 0.196 ± 0.021, 15.7 ± 1.7 mV, 92.1 ± 2.1%, and 90.4 ± 1.8%, respectively. The best cell killing ability (the lowest combination index of 0.57) was found at the combination ratio of 1:3 (CIS:DOX, w/w) in the drugs co-loaded formulations, indicating the strongest synergism effect. CIS-DOXp NC showed the best tumor inhibition efficiency (79.9%) in mice with negligible body weight lost. Conclusion: CIS-DOXp NC could be applied as a promising system for the synergistic chemotherapy of lung cancer.
An alkaline b -glucosidase isolated from an olive brine strain of Wickerhamomycesanomalus

An efﬁcient b -glucosidase ( b G)-producing strain, Wickerhamomyces anomalus BS81, was isolated from naturally fermented olive brine and identiﬁed based on PCR/restriction fragment length polymorphism of the rDNA internal transcribed spacer and sequence analysis of the D1/D2 region of the 26S rRNA gene. The hydrolytic activity of the b G had an optimum pH of 8.5 and an optimum temperature of 35 1 C. The enzyme had high substrate speciﬁcity and high catalytic efﬁciency ( K m 0.99 mM, V max 14 Ug (cid:2) 1 of cells) for p -nitrophenyl- b - D -glucopyr-anoside. The enzyme was activated by increasing concentrations of NaCl, with maximum activity at 150 g L (cid:2) of 94 1 C for 30 s, 55 1 C for 30 s and 72 1 C for 1 min, and a ﬁnal at for digestion was performed directly on m L of ampliﬁed DNA in a ﬁnal volume of 20 m Lwith HaeIII, HinfI, HhaI and MspI (New England BioLabs, Beverly, MA). Restriction fragments were separated for 1.5 h in a 2% Nusieve 3 : 1 agarose gel containing ethidium bromide in 0.5 (cid:4) TBE buffer. Strain CBS 5759 of W. anomalus was used as a reference.
Toward a New Paradigm for Imitation Learning and Explainable AI Inspired by Cognitive Memory

—We introduce an algorithm for learning structures of symbolic concepts in an ontology through on-line observations of the environment. The algorithm recognises scenes and sub-scenes based on a general-purpose taxonomy we formalised, which should be implemented for each application. The algorithm is used to implement cognitive-like abilities, such as: consolidating, retrieving and forgetting. We also introduce tools we developed to evaluate the algorithm in a human-robot collaboration scenario
A one-stage modiﬁed Tiny-YOLOv3 method for Real time Moroccan license plate recognition

—Automatic license plate recognition systems (AL-PRS) have a major signiﬁcant role in supporting smart city initiatives because of their promising applications in various areas, such as road safety, trafﬁc control, smart parking, toll management, and security. Owing to ALPRS’s importance, numerous methods have been developed. However, many of the present solutions are still suffering from some inefﬁciencies in real-world situations, generally related to many constraints. In this work, we address the problem of Moroccan car license plate detection and recognition based on the state-of-the-art YOLO deep learning framework. To this end, we have made improvements in the Tiny-YOLOv3’s network structure to make it more rigorous. We proposed a real-time end-to-end ALPRS using a one-stage approach. The network is trained using images from a collected large-scale dataset of Moroccan license plates taken from different real-world scenarios, with the addition of various data augmentation techniques, to ensure robustness and efﬁciency under different conditions. To improve the generalization ability and accuracy of our system, we also combined the proposed algorithm with the transfer learning technique. Extensive experiments prove that the proposed method achieves an excellent trade-off between speed and accuracy as well as the system executes the detection /recognition process in a single phase with 98.45% of accuracy and 59.5 Frames Per Second (FPS). Also, a comparative evaluation demonstrates the effectiveness of the proposed method compared to previous state-of-the-art methods.
DoS and DDoS Attacks at OSI Layers

— Among different online attacks obstructing IT security, Denial of Service (DoS) and Distributed Denial of Service (DDoS) are the most devastating attack. It also put the security experts under enormous pressure recently in finding efficient defiance methods. DoS attack can be performed variously with diverse codes and tools and can be launched form different OSI model layers. This paper describes in details DoS and DDoS attack, and explains how different types of attacks can be implemented and launched from different OSI model layers. It provides a better understanding of these increasing occurrences in order to improve efficient countermeasures.
The Geography and Equity of Crowdsourced Public Participation for Active Transportation Planning

Transportation planners increasingly use new forms of online public participation alongside traditional in-person approaches, including crowdsourcing tools capable of encouraging geographically specific input. Digital involvement may be particularly valuable in exploring methods to plan at a megaregional scale. Research is beginning to address digital inequalities, recognizing that broadband and smartphone access may restrict opportunities for disadvantaged groups. However, the geography and equity of participation remain pragmatic issues for practice and research. This paper reviews the geography and equity of the participation methods in Austin, Texas for active transportation (bicycling and pedestrian) through three approaches to co-produce informed plans: in-person meetings, public participation geographic information system (PPGIS), and an emerging smartphone platform that logs trips and encourages input on route quality. In addition to spatial analysis with standard deviational ellipses, we include qualitative case analysis to contextualize the geographic and equity implications of different participation approaches. Results show that both online techniques resulted in a larger geography for participation than in-person meetings, with the regional PPGIS covering the most area. However, review of the income levels in each area shows that use of the smartphone-based crowdsourcing platform was aligned with lowest-income areas. This study shows that online participation methods are not homogeneous regarding geography or equity. In some contexts, smartphone applications can help reach lower-income communities, even when compared with in-person meetings. Crowdsourcing tools can be valuable approaches to increase geography and equity of public participation in transportation planning.
Fish species richness and habitat quality mapping with geographical information system across Cauvery River in Tamil Nadu, India

Geographical information system (GIS) is associated as an essential tool and as a part of natural resource management activities worldwide. Though GIS is receiving special attention in the field of hydrology, and the aquaculture management, their deployment for spatial decision support in this domain continues to be very slow. This situation is owing to a variety of constraints together with an absence of appreciation of the technology, restricted understanding of GIS principles and associated methodology, and inadequate structure commitment to confirm continuity of these spatial decision support tools. This paper addresses these constraints and includes the use of basic GIS techniques. Fish and water samples were collected and analyzed from seven sites along the Cauvery river basin, Tamil Nadu, India, and the results were incorporated into GIS platform. The section on GIS terminology addresses the two fundamental types of GIS (mapping and interpretative analysis) and discusses the aspects related to the visualization of outcomes. Spatial distribution maps were prepared for the above-analyzed parameters. Inverse distance weighting tool have been applied to express the results obtained from the study area.
Identi cation of Potential Markers for Differentiating Epithelial Ovarian Cancer from Ovarian Low Malignant Potential Tumors through Integrated Bioinformatics Analysis

Wende Hao Capital Medical University Hongyu Zhao Capital Medical University Zhefeng Li Capital Medical University Jie Li Capital Medical University Jiahao Guo Capital Medical University Qi Chen Capital Medical University Yan Gao Capital Medical University Meng Ren Capital Medical University Xiaoting Zhao Capital Medical University Wentao Yue (  yuewt@ccmu.edu.cn ) Beijing Obstetrics and Gynecology Hospital https://orcid.org/0000-0002-5917-1125
Destiny by Signal Strength Quantitative Regulation of B Cell Division

Differentiation to Ab secreting and isotype-switched effector cells is tightly linked to cell division and therefore the degree of proliferation strongly inﬂuences the nature of the immune response. The maximum number of divisions reached, termed the population division destiny, is stochastically distributed in the population and is an important parameter in the quantitative outcome of lymphocyte responses. In this study, we further assessed the variables that regulate B cell division destiny in vitro in response to T cell- and TLR-dependent stimuli. Both the concentration and duration of stimulation were able to regulate the average maximum number of divisions undergone for each stimulus. Notably, a maximum division destiny was reached during provision of repeated saturating stimulation, revealing that an intrinsic limit to proliferation exists even under these conditions. This limit was linked directly to division number rather than time of exposure to stimulation and operated independently of the survival regulation of the cells. These results demonstrate that a B cell population’s division destiny is regulable by the stimulatory conditions up to an inherent maximum value. Division destiny is a crucial parameter in regulating the extent of B cell responses and thereby also the nature of the immune response mounted. The Journal of Immunology, 2008, 181: 374–382. the maximum number of divisions each participating cell would undergo. In this study, we examine in greater detail the regulation of division destiny during B cell proliferation. We demonstrate that in vitro B cell division progression is different for different stimuli and is further regulated by the concentration of the stimulatory molecule and the timing of exposure to stimulation. Our results reveal that B cells have an intrinsic division number restriction, even under the optimal stimulation conditions used in our experiments, which represents the maximum of the division destiny continuum. We also provide evidence supporting the hypothesis that the implementation of division destiny is likely to be achieved via division counting rather than a timing mechanism.
Hyperspectral Image Content Identification Using Kernel Based Neural Network

 Abstract — L arge dimension data of Hyperspectral Image (HSI) leads to high computation cost, more execution time and increase the memory demand; therefore, difficulty arises during the classification of HSI. Unsupervised-BSA (band selection algorithm) using linear projection (LP) dependent band metric similarity has considered for informatics band selection of HSI. However, space complexity and time constrain is very big challenge for many feature algorithm. In this paper, we will use monogenetic binary feature (MBF) to get the local and monogenic feature from each pixel. The extracted feature from the combined monogenetic parameter will be used for effective classification process. In post processing, the classification of extracted feature from the MBF is perform by the Neural Network (NN) and to provide an enhanced generalization ability we introduce a kernel based NN, and considering the unknown feature mapping. To validate the performance of proposed hyperspectral classification algorithm, we will compared with several state-of-the-art.
Assessment of Chemical Compounds for in vitro and in vivo Activity against Bacterial Black Spot of Mango

Bacterial black spot of mango caused by Xanthomonas campestris pv. mangiferaeindicae (Xcm) produces considerable economic losses in many parts in india. The extent to which bactericides control this disease effectively is low. In this study the bactericidal effect of different products was assessed in vitro and in vivo in mango plants under greenhouse conditions. Thirteen antibacterial substances, one commercial formulate and also combinations were tested. In vitro analysis showed that minimal inhibitory concentration (MIC) of antibacterial substances was between 2–8 µgml -1 , except for copper sulphate with a MIC value of 100 µgml -1 and Vancomycin, Amoxycillin which was not active at 1000 µgml -1 . MIC values of commercial formulate bactrinashak ranged between 5 and 30 µgml -1 , and combinations of ciprofloxacin + copper sulphate; ciprofloxacin + bactrinashak; ciprofloxacin + copper oxychloride, ciprofloxacin + tetracycline and tetracycline + bactrinashak, showed a great effect at sub-inhibitory concentrations. Treatments including copper sulphate and copper oxychloride significantly reduced disease symptoms on plants, whereas bacitracin was less effective, where as fluconozole and penicillin does not show any inhibition. In two different field trials, the percentage of leaves symptoms was lower, after treatment with copper sulphate combinations than in inoculated controls. These combinations of different antibacterial substances results were better than copper sulphate alone. We conclude that the combination of copper sulphate with ciproflaxacin may be useful in controlling symptoms of this disease in greenhouses.
Incentive issues in the South African construction industry: Preliminary findings from project stakeholders

Incentives are regarded as motivational tools which can be used to propel construction workforces to achieve project objectives. This article contributes to the existing body of knowledge by evaluating the current practices of incentive mechanisms in the South African construction industry and identifying the challenges confronting the use of incentives. The study adopts both qualitative and quantitative methods for data collection. For the quantitative approach, a total number of 52 project stakeholders practising in Gauteng participated in the survey by completing the structured questionnaire. The questionnaire survey is used to obtain information from respondents, in order to assess their perceptions on the impact of current practices of incentives on work productivity and the construction industry. For the qualitative approach, personal interviews were conducted with selected respondents to clarify their answers. The findings reveal ‘unattainable project goals’, ‘poor communication processes’, and ‘inappropriate contractual arrangement’ as the most significant challenges confronting the use of incentives in the South African construction industry. The findings reported in this article show problems frustrating the absolute absorption of incentives in the industry, and also contribute to redesigning the incentive plan so as to improve project performance.
Surgical ligation of patent ductus arteriosus in preterm neonates weighing less than 1,500 g: A 9- year single center experience

Jun Ho Lee Hanyang University Seoul Hospital Hyun Ju Lee Hanyang University Seoul Hospital Hyun-Kyung Park Hanyang University Seoul Hospital Ja-Hye Ahn Hanyang University Seoul Hospital Hee Sun Kim Hanyang University Seoul Hospital Hyo Jun Jang Hanyang University Seoul Hospital Sun Kyun Ro Hanyang University Seoul Hospital Hyuck Kim (  khkim@hanyang.ac.kr ) Hanyang University Seoul Hospital https://orcid.org/0000-0003-4152-5754
Application of Compressed Sensing Algorithms in Multipath Interference of Time-of-Flight Imaging

A Time-of-Flight(ToF) camera is a compact device, which can provide highly-resolved depth information between camera and scenery. However, on account of multipath interference (MPI), distortion in the measurements appears, leading to an erroneous depth estimate. A possible solution for resolving this issue is by means of algorithms that exploit sparse regularization to recover multiple return paths from multiple frequency measurements. In this paper, three diﬀer-ent sparse reconstruction algorithms, namely, Orthogonal Matching Pursuit (OMP) and l 1 -minimization approaches like Kalman ﬁlter and Chambolle and Pock’s primal-dual algorithm are applied on real data aﬀected by MPI. All the three algorithms generate an accurate depth map, among which OMP works the fastest. In addition, the convergence-accelerated algorithms of Kalman ﬁlter and Chambolle and Pock’s primal-dual algorithm are adopted, the depth map generated by the convergence-accelerated Kalman ﬁlter shows the smaller error areas in comparison with the other four algorithms.
MODELING THE IMPACTS OF LAKES AND WETLANDS ON STREAMFLOW

Author: Kines, Stephen, J. MSABE Institution: Purdue University Degree Received: May 2020 Title: Modeling the Impacts of Lakes and Wetlands on Streamflow Committee Chair: Keith Cherkauer Lakes and wetlands cover a large portion of the earth’s surface and play a crucial role in hydrology. They provide permanent and temporary storage for water within the landscape allowing for greater infiltration and evaporation along with a reduction in peak flooding events. Lakes and wetlands also provide many other non-hydrological benefits such as their ability to improve water quality and provide wildlife and fisheries habitat. Despite their known benefits, wetland destruction has been a prominent issue for many years. This study quantifies the hydrologic effects of lakes and wetlands by introducing a parametrization method for hydrologic model simulations in the North American Land Data Assimilation System (NLDAS) domain. Lake profiles were created based on the geospatial lake depth-area relationship through interpolation of known lake depths and areas throughout the domain. Wetlands were parametrized based on topographic wetness index (TWI) calculated using high-resolution DEM imagery. Wetland profiles were created using a binning technique along with the DEM and land use classifications. The Variable Infiltration Capacity (VIC) macroscale hydrologic grid-based model and its associated lake and wetland algorithm were used to quantify the effects of lakes and wetlands on streamflow. Profiles were generated for every corresponding VIC grid cell in the NLDAS domain, but for this study two watersheds, the Buttahatchee River in Mississippi and the Black River in North Carolina, were selected to test the parametrization and quantify the impact of lakes and wetlands on watershed hydrology. The Buttahatchee River watershed contains 6.6% lakes and wetlands, which were predominantly clustered near the stream channel, and the Black River watershed contained 19.2% lakes and wetlands which were spread out across the entirety of the watershed. Simulated daily streamflow with and without the lake and wetland algorithm activated was used to evaluate impacts on flood frequency as well as components of the water balance. Flood magnitude decreased due to the presence of lakes and wetlands. This decrease was 5.8% and 29.6% for a 10-year return period flood for the
A Set of Stabilizing PID Controllers for Multi input-Multi output Systems

This paper is directed at the problem of designing a set of stabilizing proportional-integral-derivative (PID) controllers for each decoupled subsystem of a multi-input multi-output system based on PID stabilization theorem [1]. It is well known that state interconnection terms of i th subsystem are arising out of N-interconnected subsystem dynamics can be treated as perturbation acting on that subsystem. An LMI optimization problem is formulated to ensure the stability of the composite system while the designed decentralized controllers are employed. A genetic algorithm based search technique is adopted to select an optimal PID controller gains from a designed search space of stabilizing controllers in order to have an optimum value of performance index. A linearized model of multi-machine infinite-bus system is considered for simulation to show the effectiveness of the design procedure.
Haplotype Diversity in 11 Candidate Genes across 4 Populations

Analysis of haplotypes based on multiple single nucleotide polymorphism (SNP) marker data is becoming more common for both candidate and fine mapping studies. Before embarking on large-scale haplotype-based studies on samples from genetically distinct populations, however, it is important to consider variation both in linkage disequilibrium (LD) and in haplotype frequencies within and across populations, as both vary considerably. Such diversity will ultimately impact the choice and number of ‘tagging’ SNPs to be typed for studies of candidate genes or for whole genome association studies because some markers will not be polymorphic in all samples and some haplotypes will either be poorly represented or completely absent. Here we present data on 11 genes, originally chosen as candidate genes for oral clefts, where multiple SNP markers were genotyped on individuals from 4 distinct populations. Estimated haplotype frequencies, measures of pair-wise LD, and measures of genetic diversity were computed for 135 European Americans, 57 Chinese Singaporeans, 45 Malay Singaporeans and 46 Indian Singaporeans. Patterns of pair-wise LD were compared across these 4 populations and their haplotype frequencies were used to assess genetic variation. Although these populations are fairly similar in their allele frequencies and overall patterns of pair-wise LD, both haplotype frequencies and genetic diversity varied significantly among populations. Such haplotype diversity has implications for the design of studies testing for association involving samples from genetically distinct populations.