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Given the complexity of urban transportation networks and the multiple variables that might affect journey times, estimating the length of cab rides in New York City (NYC) is a difficult process. In this study, we provide a unique method for resolving this issue that makes use of machine learning techniques and a wide range of attributes gleaned from taxi trip data. We start by gathering a sizable collection of historical records of NYC taxi trips,providing specifics like pick-up and drop-off points, timestamps, and lengths of trips. To deal with outliers, missing values, and geographical and temporal irregularities, we preprocess the data. Furthermore, we design a broad range of characteristics, such as geographic coordinates, time of day, day of the week, and weather conditions, to capture the spatial, temporal, and contextual elements of each journey. Then, using gradient boosting methods, we create a prediction model that efficiently uncovers the intricate patterns seen in the data. We carefully adjust the model's hyperparameter to enhance performance and use cross-validation techniques to guarantee resilience. In addition, we apply ensemble techniques to enhance prediction precision and minimise model bias. We conduct lengthy tests on a held-out test set and compare the performance of our model to a number of baseline techniques frequently employed in triptime prediction in order to assess the efficacy of our suggested strategy. The outcomes show that our strategy works better than the competition, with lower prediction errors and higher accuracy. We also do interpretability assessments to learn more about the variables that have the most impact on estimates of trip time. Our results demonstrate the potential of feature engineering and M L approaches for precise and trustworthy taxi trip length prediction in NYC. The suggested method not only helps taxi service companies by allowing them to more accurately predict journey lengths, but it also improves customer experience by giving more precise travel time estimates. Additionally, our approach may be used as a starting point for future studies in the field of urban transportation prediction, enabling better efficiency and planning in urban mobility networks.

In this paper, we propose the best approach for a Traffic sign recognition system with a high accuracy rate and less computing time. This process is done with help of CNN and Keras. In fully automatic driving cars, it is difficult to recognize the traffic signs with less computing time and a high accuracy rate. So, to solve this problem, first, we are exploring the sample traffic sign dataset, next images are sorted and their labels are set into a list and those lists are converted into NumPy arrays for feeding to the model. Secondly, the CNN model is built to classify the images into their respective categories, this is the best approach for image classification. After building the model, the model is trained, validated, and tested using the test dataset. Finally, the graphical user interface is built for traffic sign recognition using Tkinter.

This research paper reports that in-cylinder flow formation in a combustion engine has a major influence on the combustion, emission and performance characteristics. Air and fuel enters the combustion chamber of an engine throughout the intake manifold with high velocity. So, it introduces a helical roller in the path of inlet stream of mixture. It achieved the swirl by using a component that could be easily integrated into any existing engines at low engine speed. The performance of the engine increases and completes the combustion, leads to reduced emissions and small change in volumetric efficiency. It is also proved that increased swirl movement introduces helical roller that helps the flame spread which used into constant heat transfer rate. This suggests to a new combustion technique that should be developed to yield improved primary combustion processes in-side the engine with significantly reduced exhaust gas emissions.

Beachpea (Vigna marina) is a halophytic wild leguminous plant which occurs throughout tropical and subtropical beaches of world. As quantitative trait loci (QTLs) for salt tolerance in V. marina and its crossability with other Vigna species are known, the current study was undertaken to know the presence of these QTLs in the V. marina accessions along with check varieties of pulses. Accordingly, 20 Vigna genotypes (15 accessions of V. marina collected from sea-shore areas of Andaman and Nicobar Islands along with five check varieties of green gram and black gram) were subjected to molecular characterization using seven simple sequence repeat (SSR) markers associated with salt tolerance. Of the markers used, only four SSR markers amplified in the studied germplasm. Number of alleles detected per primer and size of alleles ranged from 1 to 3 and 100 to 325 bp, respectively. Polymorphism information content and heterozygosity values ranged from 0.305 to 0.537 and 0.375 to 0.612, respectively. Three major clusters, cluster I, II and III were obtained at Jaccard's similarity coefficient value of 0.48 through the un-weighted paired group method with arithmetic means method of cluster analysis. It grouped green gram and black gram genotypes in clusters I (04) and II (01), whereas all V. marina genotypes were grouped in cluster III (15). Principal co-ordinate analysis explained 85.9% of genetic variation among genotypes which was further confirmed by cluster analysis. This study indicated the effectiveness of SSR markers in separating cultivated Vigna species from wild V. marina. The findings will be useful for transferring trait of robust salt tolerance of V. marina in cultivated Vigna species using marker-assisted breeding.

Water resources are susceptible to different types of pollution among which bacterial contamination is of serious concern. Intake of water contaminated with bacteria especially with coliform leads to several health issues. Therefore, assessing the microbial safety of potable water is indeed an important aspect. In this study, we report the fabrication of a portable sensor strip for a quick detection of coliform content in drinking water. The sensor consists of an adsorbed complex (ferricyanide) along with a metabolic nutrient (glucose). The complex and the nutrient were immobilized on a porous solid support using a crosslinked binder (alginate). When a micro-drop of water sample containing coliform bacteria at concentration more than 5 CFU/100 mL was placed on the strip, a colourless patch was formed at the point of contact due to the reduction of the complex molecule by the bacteria. The kinetics of decolorization was studied using UVvisible spectroscopy and electrochemical measurements. The strips were tested using standard bacterial culture and water samples containing different amounts of coliform bacteria. The sensor strip reported in this study could be applied for real-time detection of pathogens in drinking water. It can be extended to metal-reducing pathogens similar to coliforms found in drinking water.

A subset of individuals who recover from coronavirus disease 2019 (COVID-19) develop post-acute sequelae of SARS-CoV-2 (PASC), but the mechanistic basis of PASC-associated lung abnormalities suffers from a lack of longitudinal tissue samples. The mouse-adapted severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strain MA10 produces an acute respiratory distress syndrome (ARDS) in mice similar to humans. To investigate PASC pathogenesis, studies of MA10-infected mice were extended from acute to clinical recovery phases. At 15 to 120 days post-virus clearance, pulmonary histologic findings included subpleural lesions composed of collagen, proliferative fibroblasts, and chronic inflammation, including tertiary lymphoid structures. Longitudinal spatial transcriptional profiling identified global reparative and fibrotic pathways dysregulated in diseased regions, similar to human COVID-19. Populations of alveolar intermediate cells, coupled with focal up-regulation of pro-fibrotic markers, were identified in persistently diseased regions. Early intervention with antiviral EIDD-2801 reduced chronic disease, and early anti-fibrotic agent (nintedanib) intervention modified early disease severity. This murine model provides opportunities to identify pathways associated with persistent SARS-CoV-2 pulmonary disease and test countermeasures to ameliorate PASC., After recovery from acute SARS-CoV-2 infection, mice exhibit chronic lung disease similar to some humans, allowing for testing of therapeutics.

In this research article reveals that the design fundamentals and the manufacturing procedures of the blackboard cleaner. The goal here is to decrease the labor associated with cleaning the chalkboard after use. Despite the fact that the utilization of smart boards is expanding, numerous organization in the created and creating world despite everything utilize blackboard (or) slate. The chalk powder acquired from chalk pieces while erasing the writing board, when breathed in by human reason's respiratory framework. Different issues like balding, consuming of eyes and so forth. To defeat this causes, programmed board is utilized with remote detecting which assists with working from certain separation. Generally talking, programmed chalkboard is a gadget which is utilized to clean the slate consequently which thusly lessen human work and aides in efficient. This venture is essentially running with the assistance of dc engine with constrained rates. Based on remote detecting gadget and rollers fitted in auto tic board duster is utilized to evacuate dust all around the slate. The fabricated machine is naturally distinguish the writing board chalk stains, delete the text style and keeps the chalkboard clean. These venture give great answers for human work whenever devouring. The cleaning productivity of programmed writing board cleaner is assessed to be superior to anything the manual tasks when the gear is completely finished.

In this paper, we consider a seventh-order generalized Korteweg–de Vries (GKdV) equation and study the boundary stability results concerning the inverse problem of recovering a space-dependent source term. We establish a new boundary Carleman estimate for the seventh-order linear operator with the Dirichlet–Neumann type boundary conditions. Using this crucial estimate along with regularity result of the nonlinear GKdV equation, we establish a Lipschitz stability estimate of GKdV equation.

Soft-rot disease on Dendrobium nobile observed in a commercial farm in the Nilgiris district of Tamil Nadu, India was investigated. Disease etiology is reported along with phenotypic, molecular identification of the pathogen. Infected leaves showed rot symptoms characterized by irregular water-soaked lesions on the leaf margin that rapidly spread over the entire leaf. Milky exudation on the cut end of infected leaves indicated the bacterial etiology of the disease. The bacterial colonies isolated were irregular, whitish-yellow, spindle-shaped with a characteristic raised center. All isolates showed identical phenotypic traits and induced a hypersensitive reaction on Nicotiana tabacum leaves. Pathogenicity assay performed on D. nobile confirmed their pathogenic nature as all three bacterial isolates incited typical soft-rot within 12 h post-inoculation (hpi). In vitro host range studies revealed that all the isolates could cause rot on cut slices of other vegetable crops including potato, carrot, and onion. Additionally, the bacterium incited soft rot on Aloe vera, but not on chrysanthemum and banana transplants. The identity of the bacterial isolates was confirmed as Dickeya fangzhongdai using 16S rRNA gene sequences as well as by their pathogenic behavior. Complete understanding of the etiology of the disease and of the pathogen would be useful to devise suitable management practices for the containment of disease spread in the future.

To determine prevalence of, seroprevalence of, and potential exposure to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) among a cohort of evacuees returning to the United States from Wuhan, China, in January 2020, we conducted a cross-sectional study of quarantined evacuees from 1 repatriation flight. Overall, 193 of 195 evacuees completed exposure surveys and submitted upper respiratory or serum specimens or both at arrival in the United States. Nearly all evacuees had taken preventive measures to limit potential exposure while in Wuhan, and none had detectable SARS-CoV-2 in upper respiratory tract specimens, suggesting the absence of asymptomatic respiratory shedding among this group at the time of testing. Evidence of antibodies to SARS-CoV-2 was detected in 1 evacuee, who reported experiencing no symptoms or high-risk exposures in the previous 2 months. These findings demonstrated that this group of evacuees posed a low risk of introducing SARS-CoV-2 to the United States.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was identified as the etiologic agent associated with coronavirus disease, which emerged in late 2019. In response, we developed a diagnostic panel consisting of 3 real-time reverse transcription PCR assays targeting the nucleocapsid gene and evaluated use of these assays for detecting SARS-CoV-2 infection. All assays demonstrated a linear dynamic range of 8 orders of magnitude and an analytical limit of detection of 5 copies/reaction of quantified RNA transcripts and 1 x 10-1.5 50% tissue culture infectious dose/mL of cell-cultured SARS-CoV-2. All assays performed comparably with nasopharyngeal and oropharyngeal secretions, serum, and fecal specimens spiked with cultured virus. We obtained no false-positive amplifications with other human coronaviruses or common respiratory pathogens. Results from all 3 assays were highly correlated during clinical specimen testing. On February 4, 2020, the Food and Drug Administration issued an Emergency Use Authorization to enable emergency use of this panel.

For sustainable agriculture in saline soil, extensive exploitation of salt-tolerant plant growth-promoting (PGP) bacteria and other symbiotic bacteria is required. This study was carried out to evaluate the efficiency of native salt-tolerant rice rhizobacteria for plant growth promotion under salt stress. A total of 188 bacteria were screened for assessing salt-tolerant capacity and nine isolates tolerating 12% NaCl (w/v) concentration were selected. Biochemical and molecular identification revealed that the salt-tolerant bacteria belonged to Bacillus sp, Exiguobacterium sp, Enterobacter sp, Lysinibacillus sp, Stenotrophomonas sp, Microbacterium sp, and Achromobacter sp. The increase in NaCl concentration from 2 to 4% decreases the PGP activities such as IAA production, P solubilization, K solubilization, and nitrate reduction. The effects of inoculation of salt-tolerant bacteria on the growth and different physiological properties of rice (Oryza sativa) were studied. It was found that the salinity affected the root and shoot length of the control plants; however, bacterial inoculant were found to effectively promote the growth of paddy under salinity stress. Further, bacterial inoculants substantially enhanced total chlorophyll, proline, total phenol, and oxidative damage such as electrolyte leakage and membrane stability index under salt stress. This study suggests that salt-tolerant PGP bacteria may be used for cultivation of O. sativa in salinized agricultural lands.

The etiologic agent of an outbreak of pneumonia in Wuhan, China, was identified as severe acute respiratory syndrome coronavirus 2 in January 2020. A patient in the United States was given a diagnosis of infection with this virus by the state of Washington and the US Centers for Disease Control and Prevention on January 20, 2020. We isolated virus from nasopharyngeal and oropharyngeal specimens from this patient and characterized the viral sequence, replication properties, and cell culture tropism. We found that the virus replicates to high titer in Vero-CCL81 cells and Vero E6 cells in the absence of trypsin. We also deposited the virus into 2 virus repositories, making it broadly available to the public health and research communities. We hope that open access to this reagent will expedite development of medical countermeasures.

In this paper, we address an inverse problem of reconstructing a space-dependent semilinear coefficient in the tumor growth model described by a system of semilinear partial differential equations ...

Abstract. In this work, we study the optimal control of stochastic Burgers equation perturbed by Gaussian and L´evy type noises with distributed control process acting on the state equation. We use the dynamic programming approach for the second order Hamilton-JacobiBellman (HJB) equation consisting of an integro-differential operator with L´evy measure associated with the stochastic control problem. Using the regularizing properties of the transition semigroup corresponding to the stochastic Burgers equation and compactness arguments, we solve the HJB equation and the resultant feedback control problem.

COVID-19 survivors develop post-acute sequelae of SARS-CoV-2 (PASC), but the mechanistic basis of PASC-associated lung abnormalities suffers from a lack of longitudinal samples. Mouse-adapted SARS-CoV-2 MA10 produces an acute respiratory distress syndrome (ARDS) in mice similar to humans. To investigate PASC pathogenesis, studies of MA10-infected mice were extended from acute disease through clinical recovery. At 15-120 days post-virus clearance, histologic evaluation identified subpleural lesions containing collagen, proliferative fibroblasts, and chronic inflammation with tertiary lymphoid structures. Longitudinal spatial transcriptional profiling identified global reparative and fibrotic pathways dysregulated in diseased regions, similar to human COVID-19. Populations of alveolar intermediate cells, coupled with focal upregulation of pro-fibrotic markers, were identified in persistently diseased regions. Early intervention with antiviral EIDD-2801 reduced chronic disease, and early anti-fibrotic agent (nintedanib) intervention modified early disease severity. This murine model provides opportunities to identify pathways associated with persistent SARS-CoV-2 pulmonary disease and test countermeasures to ameliorate PASC.