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Once known for slum-like conditions in its immigrant and working-class neighborhoods, New York City's downtown now features luxury housing, chic boutiques and hotels, and, most notably, a vibrant nightlife culture. While a burgeoning bar scene can be viewed as a positive sign of urban transformation, tensions lurk beneath, reflecting the social conflicts within postindustrial cities.Upscaling Downtownexamines the perspectives and actions of disparate social groups who have been affected by or played a role in the nightlife of the Lower East Side, East Village, and Bowery. Using the social world of bars as windows into understanding urban development, Richard Ocejo argues that the gentrifying neighborhoods of postindustrial cities are increasingly influenced by upscale commercial projects, causing significant conflicts for the people involved. Ocejo explores what community institutions, such as neighborhood bars, gain or lose amid gentrification. He considers why residents continue unsuccessfully to protest the arrival of new bars, how new bar owners produce a nightlife culture that attracts visitors rather than locals, and how government actors, including elected officials and the police, regulate and encourage nightlife culture. By focusing on commercial newcomers and the residents who protest local changes, Ocejo illustrates the contested and dynamic process of neighborhood growth. Delving into the social ecosystem of one emblematic section of Manhattan,Upscaling Downtownsheds fresh light on the tensions and consequences of urban progress.

For the purpose of researching the six-bar mechanism for open and close and the improvement and use of the mechanism, improving the work efficiency, the three-dimensional solid model of the mechanism was established with ADAMS. Each part of the model in ADAMS was set up. Simulation analysis on the working process of the mechanism was achieved. The structure optimization parameters of the mechanism were obtained. The result proves that when the vertical location of the upper endpoint of lid were increased the horizontal displacement of the lower endpoint of lid reduced. When the locations of revolute joint of lower rocker and link, the horizontal location of revolute joint of lower rocker and lid, the opening force acting on the lower endpoint of lid were increased the horizontal displacement of the lower endpoint of lid added. The sensitivities of the horizontal displacement of the lower endpoint of lid on the initial values of the locations of revolute joint of lower rocker and link, the horizontal location of revolute joint of lower rocker and lid, the horizontal location of revolute joint of lower rocker and frame are greater. The sensitivities of the horizontal displacement of the lower endpoint of lid on the initial values of the vertical location of revolute joint of upper rocker and link, the vertical location of the upper endpoint of lid, the opening force acting on the lower endpoint of lid are smaller.

For decades, identifying the regions of a bacterial chromosome that are necessary for viability has relied on mapping integration sites in libraries of random transposon mutants to find loci that are unable to sustain insertion. To date, these studies have analyzed subsaturated libraries, necessitating the application of statistical methods to estimate the likelihood that a gap in transposon coverage is the result of biological selection and not the stochasticity of insertion. As a result, the essentiality of many genomic features, particularly small ones, could not be reliably assessed. We sought to overcome this limitation by creating a completely saturated transposon library in Mycobacterium tuberculosis . In assessing the composition of this highly saturated library by deep sequencing, we discovered that a previously unknown sequence bias of the Himar1 element rendered approximately 9% of potential TA dinucleotide insertion sites less permissible for insertion. We used a hidden Markov model of essentiality that accounted for this unanticipated bias, allowing us to confidently evaluate the essentiality of features that contained as few as 2 TA sites, including open reading frames (ORF), experimentally identified noncoding RNAs, methylation sites, and promoters. In addition, several essential regions that did not correspond to known features were identified, suggesting uncharacterized functions that are necessary for growth. This work provides an authoritative catalog of essential regions of the M. tuberculosis genome and a statistical framework for applying saturating mutagenesis to other bacteria. IMPORTANCE Sequencing of transposon-insertion mutant libraries has become a widely used tool for probing the functions of genes under various conditions. The Himar1 transposon is generally believed to insert with equal probabilities at all TA dinucleotides, and therefore its absence in a mutant library is taken to indicate biological selection against the corresponding mutant. Through sequencing of a saturated Himar1 library, we found evidence that TA dinucleotides are not equally permissive for insertion. The insertion bias was observed in multiple prokaryotes and influences the statistical interpretation of transposon insertion (TnSeq) data and characterization of essential genomic regions. Using these insights, we analyzed a fully saturated TnSeq library for M. tuberculosis , enabling us to generate a comprehensive catalog of in vitro essentiality, including ORFs smaller than those found in any previous study, small (noncoding) RNAs (sRNAs), promoters, and other genomic features. Sequencing of transposon-insertion mutant libraries has become a widely used tool for probing the functions of genes under various conditions. The Himar1 transposon is generally believed to insert with equal probabilities at all TA dinucleotides, and therefore its absence in a mutant library is taken to indicate biological selection against the corresponding mutant. Through sequencing of a saturated Himar1 library, we found evidence that TA dinucleotides are not equally permissive for insertion. The insertion bias was observed in multiple prokaryotes and influences the statistical interpretation of transposon insertion (TnSeq) data and characterization of essential genomic regions. Using these insights, we analyzed a fully saturated TnSeq library for M. tuberculosis , enabling us to generate a comprehensive catalog of in vitro essentiality, including ORFs smaller than those found in any previous study, small (noncoding) RNAs (sRNAs), promoters, and other genomic features.

We present a suite of direct N-body simulations of the Hyades open cluster and its tidal stream in a Milky Way potential that includes a rotating bar and spiral arms. Using the high-resolution code PETAR and an AGAMA-based multicomponent Galactic model, we vary the bar and spiral pattern speeds (Ωb, Ωs) on a discrete grid and quantify the resulting changes in stream orientation, length, and internal density structure. We compare the simulations to Gaia EDR3 using the convergent point and compact convergent point methods, followed by an adaptive three-dimensional nearest-neighbor matching in Cartesian space (x, y, z). The Gaia candidate members exhibit a pronounced longitudinal density peak at Yrot ≈ 0.1 kpc in a stream-aligned coordinate system. Models with Ωs = 22.5 km s−1 kpc−1 and Ωb ≃ 40–45 km s−1 kpc−1 best reproduce this feature, while models with a faster bar fail to match the observed density structure. These models are consistent with recent constraints favoring a relatively slow Galactic bar, and they illustrate how nearby open-cluster streams can provide an independent, local constraint on nonaxisymmetric Galactic dynamics.

Stress wave dispersion can result in the loss or distortion of critical high-frequency data during high-strain-rate material tests or blast loading experiments. The purpose of this work is to demonstrate the benefits of correcting stress wave dispersion in split-Hopkinson pressure bar experiments under various testing situations. To do this, an innovative computational algorithm, SHPB_Processing.py, is created. Following the operational run through of SHPB_Processing.py’s capabilities, it is used to process test data acquired from split-Hopkinson pressure bar tests on aluminium, sand and kaolin clay samples, under various testing conditions. When comparing dispersion corrected and simple time shifting data obtained from SHPB experiments, accounting for dispersion removes spurious oscillations and improves the inferred measurement at the front of the specimen. The precision of the stress and strain results gathered from its application emphasises its importance through the striking contrast between its application and omission. This has a significant impact on the validity, accuracy and quality of the results. As a result, in the future, this tool can be utilised for any strain rate testing situation with cylindrical bars that necessitates dispersion correction, confinement, or stress equilibrium analysis.

Open-pit coal mining offers high resource recovery, excellent safety conditions, and large-scale production. However, the process generates significant dust, leading to occupational diseases such as pneumoconiosis among miners and adversely affecting nearby vegetation through dust deposition, which hinders photosynthesis and causes ecological damage. This limits the transition of open-pit mining to a green, low-carbon model. Among these processes, blasting generates the most dust and has the widest impact range, but the specific amount of dust generated has not yet been thoroughly studied. This study integrates indoor experiments, theoretical analyses, and field tests, employing the Split Hopkinson Pressure Bar (SHPB) system to conduct impact loading tests on coal–rock samples under pressures ranging from 0.13 MPa to 2.0 MPa. The results indicate that as the impact load increases, the proportion of large-sized blocks decreases while smaller fragments and powdered samples increase, signifying intensified sample fragmentation. Using stress wave attenuation theory, this study translates indoor impact loadings to field blast shock waves, revealing the relationship between blasting dust mass fraction and impact pressure. Field tests at the Haerwusu open-pit coal mine validated the formula. Using image recognition technology to analyze post-blast muck-pile fragmentation, the estimated dust production closely matched the calculated values, with an error margin of less than 10%. This formula provides valuable insights for estimating dust production and improving dust control measures during open-pit mine blasting operations.

Mid-channel forms are key components of fluvial morphology, particularly in gravel-bed rivers where their development reflects sediment transport dynamics, vegetation establishment, and human impacts. This study investigates the long-term changes in mid-channel forms, including bars, islands, and inter-channel areas (ICAs) in mountain and foreland rivers of the Polish Carpathians over the past 150 years. Based on five historical and contemporary maps from 1869 to 1887, 1906–1913, 1924–1939, 1976–1989, and 2019, a spatial database of nearly 3,000 forms was developed and analyzed using morphometric methods and multivariate statistics, specifically Multivariate Analysis of Variance (MANOVA) and Linear Discriminant Analysis (LDA). The classification of forms into bars, islands, and ICAs was based on land cover and geometric relationships to channel width. Statistical analyses confirmed that ICAs and islands represent two morphometrically distinct types of persistent mid-channel features. A decline in the surface area and shape compactness of these forms was observed over time, followed by a recent resurgence in their number, especially in reaches where river training structures have deteriorated. The findings highlight the dynamic nature of mid-channel forms under long-term anthropogenic and hydromorphological pressures. By offering a standardized morphometric approach and a publicly available vector dataset, this study contributes to the broader understanding of channel pattern evolution in regulated gravel-bed rivers and supports future comparative analyses in fluvial geomorphology and river management.

Agricultural researchers are embracing remote sensing tools to phenotype and monitor agriculture crops. Specifically, large quantities of data are now being collected on small plot research studies using Unoccupied Aerial Systems (UAS, aka drones), ground systems, or other technologies but data processing and analysis lags behind. One major contributor to current data processing bottlenecks has been the lack of publicly available software tools tailored towards remote sensing of small plots and usability for researchers inexperienced in remote sensing. To address these needs we created plot shapefile maker (R/UAS::plotshpcreate): an open source R function which rapidly creates ESRI polygon shapefiles to the desired dimensions of individual agriculture research plots areas of interest and associates plot specific information. Plotshpcreate was developed to utilize inputs containing experimental design, field orientation, and plot dimensions for easily creating a multi-polygon shapefile of an entire small plot experiment. Output shapefiles are based on the user inputs geolocation of the research field ensuring accurate overlay of polygons often without manual user adjustment. The output shapefile is useful in GIS software to extract plot level data tracing back to the unique IDs of the experimental plots. Plotshpcreate is available on GitHub (https://github.com/andersst91/UAStools).

As biological sequence databases continue growing, so do the insight that they promise to shed on the shape of the genetic diversity of life. However, to fulfil this promise the software must remain usable, be able to accommodate a large amount of data and allow use of modern high performance computing infrastructure. In this study we present a reimplementation as well as an extension of a technique using indicator vectors to compute and visualize similarities between sets of nucleotide sequences. We have a flexible and easy to use python program relying on standard and open-source libraries. Our tool allows analysis of very large complement of sequences using code parallelization, as well as by providing routines to split a computational task in smaller and manageable subtasks whose results are then merged. This implementation also facilitates adding new sequences into an indicator vector-based representation without re-computing the whole set. The efficient synthesis of data into knowledge is no trivial matter given the size and rapid growth of biological sequence databases. Based on previous results regarding the properties of indicator vectors, the open-source approach proposed here efficiently and flexibly supports comparative analysis of genetic diversity at a large scale. Our software is freely available at: https://github.com/WandrilleD/pyKleeBarcode .

The tracking of lineage frequencies via DNA barcode sequencing enables the quantification of microbial fitness. However, experimental noise coming from biotic and abiotic sources complicates the computation of a reliable inference. We present a Bayesian pipeline to infer relative microbial fitness from high-throughput lineage tracking assays. Our model accounts for multiple sources of noise and propagates uncertainties throughout all parameters in a systematic way. Furthermore, using modern variational inference methods based on automatic differentiation, we are able to scale the inference to a large number of unique barcodes. We extend this core model to analyze multi-environment assays, replicate experiments, and barcodes linked to genotypes. On simulations, our method recovers known parameters within posterior credible intervals. This work provides a generalizable Bayesian framework to analyze lineage tracking experiments. The accompanying open-source software library enables the adoption of principled statistical methods in experimental evolution.