Location-specific Features Research Articles

Toward a dynamic national transportation noise map: Modeling temporal variability of spectral traffic noise emission levels.

The National Transportation Noise Map predicts time-averaged road traffic noise across the continental United States (CONUS) based on annual average daily traffic counts. However, traffic noise can vary greatly with time. This paper outlines a method for predicting nationwide hourly varying source traffic sound emissions called the Vehicular Reduced-Order Observation-based Model (VROOM). The method incorporates three models that predict temporal variability of traffic volume, predict temporal variability of different traffic classes, and use Traffic Noise Model (TNM) 3.0 equations to give traffic noise emission levels based on vehicle numbers and class mix. Location-specific features are used to predict average class mix across CONUS. VROOM then incorporates dynamic traffic class mix data to obtain dynamic traffic class mix. TNM 3.0 equations then give estimated equivalent sound level emission spectra near roads with up to hourly resolution. Important temporal traffic noise characteristics are modeled, including diurnal traffic patterns, rush hours in urban locations, and weekly and yearly variation. Examples of the temporal variability are depicted and possible types of uncertainties are identified. Altogether, VROOM can be used to map national transportation noise with temporal and spectral variability.

Toward a dynamic national transportation noise map: Modeling temporal variability of traffic volume.

The National Transportation Noise Map (NTNM) gives time-averaged traffic noise across the continental United States (CONUS) using annual average daily traffic. However, traffic noise varies significantly with time. This paper outlines the development and utility of a traffic volume model which is part of VROOM, the Vehicular Reduced-Order Observation-based model, which, using hourly traffic volume data from thousands of traffic monitoring stations across CONUS, predicts nationwide hourly varying traffic source noise. Fourier analysis finds daily, weekly, and yearly temporal traffic volume cycles at individual traffic monitoring stations. Then, principal component analysis uses denoised Fourier spectra to find the most widespread cyclic traffic patterns. VROOM uses nine principal components to represent hourly traffic characteristics for any location, encapsulating daily, weekly, and yearly variation. The principal component coefficients are predicted across CONUS using location-specific features. Expected traffic volume model sound level errors-obtained by comparing predicted traffic counts to measured traffic counts-and expected NTNM-like errors, are presented. VROOM errors are typically within a couple of decibels, whereas NTNM-like errors are often inaccurate, even exceeding 10 decibels. This work details the first steps towards creation of a temporally and spectrally variable national transportation noise map.

DETERMINING THE OPTIMUM PHOTOVOLTAIC INSTALLATION ANGLE FOR PROVINCES IN TURKEY

Solar trackers maximize solar radiation collection but are less commonly used due to their high cost, maintenance requirements, and the additional expenses associated with monthly angle adjustments. This paper proposes optimizing solar energy absorption by determining the optimal tilt for fixed-site solar panels in Turkey. It introduces an equation developed with artificial neural networks to forecast the ideal angle based on five location-specific features. Input variables, training procedures, and network design significantly impact the accuracy of Neural Network models' predictions. MATLAB software created three distinct ANN models for this investigation, each employing unique training setups and procedures. Matlab graphs guided the selection of algorithms and models based on minimizing MAE and RMSE while maximizing the linear correlation coefficient (R). The RMSE value obtained according to the calculations was 3.5881e^(-6), and the R value was 0.99998. The network's estimated data was compared to the training and testing cosθ data, yielding an RMSE error of 0.43% and an R2 value of 0.99978, indicating high accuracy. The average annual optimum inclination angles for the studied cities are as follows: Ankara (35.18°), Antalya (34.29°), Ağrı (34.91°), İstanbul (34.50°), Sivas (34.96°), İzmir (35.19°), Sinop (35.06°), and Gaziantep (34.97°).

DUET - Distribution of Understory using Elliptical Transport: A mechanistic model of leaf litter and herbaceous spatial distribution based on tree canopy structure

Heterogeneity in surface fuels produced by overstory trees and understory vegetation is a major driver of fire behavior and ecosystem dynamics. Previous attempts at predicting tree leaf and needle litter accumulation over time have been constrained in scope to probabilistic models that consider a limited number of key factors influencing tree litter dispersal patterns and decomposition processes. We present a mechanistic model for estimating variation in surface fuels called the Distribution of Understory using Elliptical Transport (DUET). DUET uses a pre-generated voxelated canopy array and distributes the leaf litter from the trees in an elliptical shape based on tree species characteristics, wind data, and location-specific features. DUET then calculates grass growth between trees and around the litter patterns and sets moisture levels based on relative humidity. In this study, we use DUET to simulate spatial distributions of leaf litter and illustrate model sensitivity to several parameters, providing inputs for testing fuel spatial heterogeneity impacts on fire behavior using process-based models.

Improving Antibiotic Stewardship for Diarrheal Disease With Probability-Based Electronic Clinical Decision Support

Inappropriate use of antibiotics for diarrheal illness can result in adverse effects and increase in antimicrobial resistance. To determine whether the diarrheal etiology prediction (DEP) algorithm, which uses patient-specific and location-specific features to estimate the probability that diarrhea etiology is exclusively viral, impacts antibiotic prescriptions in patients with acute diarrhea. A randomized crossover study was conducted to evaluate the DEP incorporated into a smartphone-based electronic clinical decision-support (eCDS) tool. The DEP calculated the probability of viral etiology of diarrhea, based on dynamic patient-specific and location-specific features. Physicians were randomized in the first 4-week study period to the intervention arm (eCDS with the DEP) or control arm (eCDS without the DEP), followed by a 1-week washout period before a subsequent 4-week crossover period. The study was conducted at 3 sites in Bangladesh from November 17, 2021, to January 21, 2021, and at 4 sites in Mali from January 6, 2021, to March 5, 2021. Eligible physicians were those who treated children with diarrhea. Eligible patients were children between ages 2 and 59 months with acute diarrhea and household access to a cell phone for follow-up. Use of the eCDS with the DEP (intervention arm) vs use of the eCDS without the DEP (control arm). The primary outcome was the proportion of children prescribed an antibiotic. A total of 30 physician participants and 941 patient participants (57.1% male; median [IQR] age, 12 [8-18] months) were enrolled. There was no evidence of a difference in the proportion of children prescribed antibiotics by physicians using the DEP (risk difference [RD], -4.2%; 95% CI, -10.7% to 1.0%). In a post hoc analysis that accounted for the predicted probability of a viral-only etiology, there was a statistically significant difference in risk of antibiotic prescription between the DEP and control arms (RD, -0.056; 95% CI, -0.128 to -0.01). No known adverse effects of the DEP were detected at 10-day postdischarge. Use of a tool that provides an estimate of etiological likelihood did not result in a significant change in overall antibiotic prescriptions. Post hoc analysis suggests that a higher predicted probability of viral etiology was linked to reductions in antibiotic use. Clinicaltrials.gov Identifier: NCT04602676.

Modern problems and prospects for the agricultural land use development in the Irkutsk region

At present, attention a lot is paid to agriculture development. For example, the “State Program for the Agriculture Development and the Agricultural Products, Raw Materials and Food Markets Regulation”, the May 14 Russian Federation Government Decree, 2021 No. 731 “On the State Program for the Agricultural Lands Effective Involvement and the Russian Federation Land Reclamation Complex Development”, subsidies are allocated for agriculture, etc. But in our country some regions, the agricultural industry is a non-priority. This also applies to the Irkutsk region. The article reveals the reasons for the agriculture backwardness in the Irkutsk region. In particular, the main reasons for this are that the agricultural land use nature idea is usually determined by the agricultural land structure in the district total area; the Irkutsk region land’s natural fertility cannot be considered high; agricultural production low efficiency, etc. The question arises, what are the most realistic directions and prospects for the agricultural land use development in the region in the coming period? It is necessary to develop a concept for agricultural land use in the Irkutsk region, and it should be based on the land intensification basic principles; to bring agricultural products to the consumer, i.e., improve infrastructure and processing services in the region agricultural areas; personal subsidiary and peasant (farm) farms should complement large enterprises, since the first of them can more efficiently use the agricultural land and their location-specific features, etc.

Survey of the extracellular matrix architecture across the rat arterial tree

ObjectiveTo understand arterial remodeling and the pathophysiology of arterial diseases, it is necessary to understand the baseline qualities and variations in arterial structure. Arteries could differ in wall thickness, laminar structure, and laminar fenestration depending on their position within the arterial tree. We endeavored to evaluate and compare the extracellular matrix structure of different arteries throughout the arterial tree, from the aorta to the adductor muscle arteriole, with a particular focus on the internal elastic lamina (IEL). MethodsArterial segments were harvested from male Sprague-Dawley rats and imaged using multiple modalities. En face scans by multiphoton microscopy were used to compare native-state adventitial collagen undulation and IEL fenestration. ResultsCollagen undulation was similar across most examined arteries but straighter in the skeletal muscle arterioles (P < .05). The elastic lamellae showed several differences. The IEL fenestrae were similar in average size among abdominal aorta and celiac, renal, common iliac, and common femoral arteries (range, 14-24 μm2), with wide within-vessel variance (square of the standard deviation, 462-1904 μm4). However, they tended to be smaller (9.08 μm2) and less variable (square of the standard deviation, 88.3 μm4) in the popliteal artery. Fenestrae were greater in number in the superior mesenteric artery (SMA; 6686/mm2; P < .05) and profunda femoris artery (PFA; 11,042/mm2; P < .05) compared with the other examined vessels, which ranged in surface density from 3143/mm2 to 4362/mm2. The SMA and PFA also showed greater total fenestration as a proportion of the IEL surface area (SMA, 15.04%; P < .05; PFA, 24.11%; P < .001) than the other examined arteries (range of means, 4.7%-9.4%). The arteriolar IEL was structurally distinct, comparable to a low-density wireframe. Other structural differences were also noted, including differences in the number of medial lamellae along the arterial tree. ConclusionsWe found that vessels at different locations along the arterial tree differ in structure. The SMA, PFA, and intramuscular arterioles have fundamental differences in the extracellular matrix structure compared with other arteries. Location-specific features such as the medial lamellae number and elastic laminar structure might have relevance to physiology and confer vulnerabilities to the development of pathology.

Large-scale screening to distinguish between COVID-19 and community-acquired pneumonia using infection size-aware classification

The worldwide spread of coronavirus disease (COVID-19) has become a threat to global public health. It is of great importance to rapidly and accurately screen and distinguish patients with COVID-19 from those with community-acquired pneumonia (CAP). In this study, a total of 1,658 patients with COVID-19 and 1,027 CAP patients underwent thin-section CT and were enrolled. All images were preprocessed to obtain the segmentations of infections and lung fields. A set of handcrafted location-specific features was proposed to best capture the COVID-19 distribution pattern, in comparison to the conventional CT severity score (CT-SS) and radiomics features. An infection size-aware random forest method (iSARF) was proposed for discriminating COVID-19 from CAP. Experimental results show that the proposed method yielded its best performance when using the handcrafted features, with a sensitivity of 90.7%, a specificity of 87.2%, and an accuracy of 89.4% over state-of-the-art classifiers. Additional tests on 734 subjects, with thick slice images, demonstrates great generalizability. It is anticipated that our proposed framework could assist clinical decision making.

Transcriptome and chromatin landscape of iNKT cells are shaped by subset differentiation and antigen exposure

Invariant natural killer T cells (iNKT cells) differentiate into thymic and peripheral NKT1, NKT2 and NKT17 subsets. Here we use RNA-seq and ATAC-seq analyses and show iNKT subsets are similar, regardless of tissue location. Lung iNKT cell subsets possess the most distinct location-specific features, shared with other innate lymphocytes in the lung, possibly consistent with increased activation. Following antigenic stimulation, iNKT cells undergo chromatin and transcriptional changes delineating two populations: one similar to follicular helper T cells and the other NK or effector like. Phenotypic analysis indicates these changes are observed long-term, suggesting that iNKT cells gene programs are not fixed, but they are capable of chromatin remodeling after antigen to give rise to additional subsets.

Adaptive Feature Selection Guided Deep Forest for COVID-19 Classification With Chest CT.

Chest computed tomography (CT) becomes an effective tool to assist the diagnosis of coronavirus disease-19 (COVID-19). Due to the outbreak of COVID-19 worldwide, using the computed-aided diagnosis technique for COVID-19 classification based on CT images could largely alleviate the burden of clinicians. In this paper, we propose an Adaptive Feature Selection guided Deep Forest (AFS-DF) for COVID-19 classification based on chest CT images. Specifically, we first extract location-specific features from CT images. Then, in order to capture the high-level representation of these features with the relatively small-scale data, we leverage a deep forest model to learn high-level representation of the features. Moreover, we propose a feature selection method based on the trained deep forest model to reduce the redundancy of features, where the feature selection could be adaptively incorporated with the COVID-19 classification model. We evaluated our proposed AFS-DF on COVID-19 dataset with 1495 patients of COVID-19 and 1027 patients of community acquired pneumonia (CAP). The accuracy (ACC), sensitivity (SEN), specificity (SPE), AUC, precision and F1-score achieved by our method are 91.79%, 93.05%, 89.95%, 96.35%, 93.10% and 93.07%, respectively. Experimental results on the COVID-19 dataset suggest that the proposed AFS-DF achieves superior performance in COVID-19vs. CAP classification, compared with 4 widely used machine learning methods.

CD4+ resident memory T cells dominate immunosurveillance and orchestrate local recall responses

Abstract Migratory dynamics of T cells influence outcomes of infections and cancer. This study addresses how CD4+ T cell immunosurveillance strategies compare to CD8+ T cells by analyzing migration, transcriptome, phenotype, and function. After acute viral infection, memory CD4+ T cells predominantly utilized residence to survey nonlymphoid tissues, albeit not as stringently as observed for CD8+ T cells. In contrast, memory CD4+ T cells were more likely to be resident within lymphoid organs than CD8+ T cells. Migration properties of memory-phenotype CD4+ T cells in non-SPF parabionts were similar, generalizing these results to diverse infections and conditions. CD4+ and CD8+ resident memory T cells (TRM) shared overlapping transcriptional signatures and location-specific features, such as granzyme B expression in the small intestine, revealing tissue-specific and migration property-specific, in addition to lineage-specific, differentiation programs. Functionally, mucosal CD4+ TRM reactivation locally triggered both chemokine expression and broad immune cell activation. Thus, residence provides a dominant mechanism for regionalizing CD4+ T cell immunity, and location enforces shared transcriptional, phenotypic, and functional properties with CD8+ T cells.

Housing features and rent: estimating the microstructures of rental housing

PurposeWhile consumers did not previously have information on detailed housing features via traditional media, such as magazines, nowadays, due to the progress in information technology, they can access detailed information on various housing features via housing information websites. Therefore, detailed housing features may affect current rents to some extent. This paper aims to identify the effects of detailed housing features on rent and on omitted variable bias in Tokyo, Japan.Design/methodology/approachThis paper applies the hedonic approach. To identify the effects of features which are not observed previously, we use a unique data set that contains various housing features and over 200,000 housing units. This data set enables to simulate the situations when the researcher cannot get some variables, and this simulation shows which variables cause omitted variable bias.FindingsThe analysis shows that housing features significantly influence housing rent. If significant housing feature variables are not included in the hedonic model, the estimated coefficients show omitted variable bias. Additionally, unit-specific features such auto-locking door can cause omitted variable bias on location-specific features such accessibility to downtown.Originality/valuesThis paper shows empirical evidence that detailed housing features can cause omitted variable bias on other features including variables which are often used in previous searches. The result from our unique data set can be a guide for variable selection to reduce omitted variable bias.

CD4+ resident memory T cells dominate immunosurveillance and orchestrate local recall responses.

This study examines the extent to which memory CD4+ T cells share immunosurveillance strategies with CD8+ resident memory T cells (TRM). After acute viral infection, memory CD4+ T cells predominantly used residence to survey nonlymphoid tissues, albeit not as stringently as observed for CD8+ T cells. In contrast, memory CD4+ T cells were more likely to be resident within lymphoid organs than CD8+ T cells. Migration properties of memory-phenotype CD4+ T cells in non-SPF parabionts were similar, generalizing these results to diverse infections and conditions. CD4+ and CD8+ TRM shared overlapping transcriptional signatures and location-specific features, such as granzyme B expression in the small intestine, revealing tissue-specific and migration property-specific, in addition to lineage-specific, differentiation programs. Functionally, mucosal CD4+ TRM reactivation locally triggered both chemokine expression and broad immune cell activation. Thus, residence provides a dominant mechanism for regionalizing CD4+ T cell immunity, and location enforces shared transcriptional, phenotypic, and functional properties with CD8+ T cells.

End-to-End Physical Layer Authentication for Dual-Hop Wireless Networks

End-to-end (E2E) physical layer authentication for multi-hop wireless networks is still not well-explored by now. Like one step forward in this direction, this paper focuses on the E2E physical layer authentication in a dual-hop wireless network with an untrusted relay and proposes a corresponding physical layer authentication scheme. The scheme fully utilizes the location-specific features of both channel amplitude and delay interval of cascaded channels and adopts the artificial jamming technique, so that it is not only resistant to the impersonate attack from an unauthorized transmitter but also resilient to the replay attack from the untrusted relay. Theoretical analysis is further conducted to derive the expressions for the probabilities of false alarm and missed detection, which are two fundamental metrics of authentication performance. Finally, the numerical and simulation results are provided to illustrate both the efficiency of these theoretical results and the E2E authentication performance of dual-hop wireless networks under the proposed scheme.

Soundscape stability in king penguin colonies

King penguin colonies present an acoustically rich environment due to the highly vocal nature of these birds and the large abundance of birds within a colony (100.000 + ). Individual identification in adults and chicks is based on vocal signals. Penguins can recognize the call of their partner or chick even among thousands of calling individuals. However, the range of such identification is limited to a few meters, 8.8 m on average in the colony. In spite of the fact that king penguins are famous for their highly developed acoustic abilities, little is known regarding the overall acoustic colony structure. Using a distributed synchronized microphone array, we collected soundscape information over several months at several locations. We find location specific features in the soundscape that are stable over several weeks, regardless of environmental conditions and only require short integration time. We explore if current acoustic indices are able to capture these features, if soundscape stability information might be useful for navigation and if this information can be associated with current colony structure and spatial use.

Innovation in the hospitality industry

The hospitality industry is a rapidly growing revenue generator in many countries and is becoming economically important for generating employment and for integrating of immigrants into the labor market. As an industry where firms face fierce competition, it is important for the firms to maintain their competitiveness by distinguishing themselves from others through continuous improvements and innovations. In this article, we investigate the determinants of innovation in the hospitality industry by analyzing survey data gathered from over 900 firms in Sweden. In the analysis, we differentiate between firm-specific and location-specific features. We conclude that the most important characteristics that explain innovation lie within the firm itself, not the location. These results provide important insights regarding firm- versus location-placed innovation policies.

An intermediary approach to technological innovation systems (TIS)—The case of the cleantech sector in Finland

The Technological Innovation System (TIS) framework has become a popular tool for the analysis of innovation dynamics, particularly on a national scale. There have been calls to utilise the framework at sub-national levels too, and to pay attention to location-specific features and interactions. This article contributes to the discussion by studying how the sub-national intermediary network of the Finnish Carbon-Neutral Municipalities (HINKU) complements and challenges the national cleantech innovation system in Finland. To achieve this, we propose an analytical framework that combines the TIS framework with intermediary functions. Our study shows that the TIS framework is a practical tool for analysing potential discontinuities and policy development possibilities regarding innovation systems across spatial scales. Empirically, the study reveals the ways in which certain technological innovation system functions, such as market formation and experimentation, are particularly important for local-scale cleantech deployment and should be analysed further.

Psoriasis in special localizations

Alarge proportion of patients with plaque psoriasis suffer from psoriatic lesions of the scalp, nails, and intertrigines. These locations can also be soley or predominantly affected. Scalp psoriasis, nail psoriasis, and inverse psoriasis are often perceived as particularly stigmatizing. Involvement of these parts of the body is associated with an increased risk of psoriatic arthritis. Location-specific features must be considered when choosing treatment. Evidence for topical therapy of scalp psoriasis with steroids and combinations of steroids and vitaminD analogues is high. These agents are regarded as safe and effective treatments of first choice. Efficacy of TNF antagonists and apremilast is well documented for refractory scalp psoriasis. Nail psoriasis often responds insufficiently to topical therapy. Several effective systemic medications including methotrexate and TNF antagonists are available for treatment of severe forms. Controlled trials for treatment of inverse psoriasis are scarce. Topical steroids, vitaminD analogues, dithranol, and off-label calcineurin inhibitors are used in clinical practice. This review provides asurvey on the clinical presentation and current evidence for treatment of psoriasis in challenging locations.

Joint met-ocean description for design and operations of marine structures

For several engineering applications, joint met-ocean probabilities are required. Recently increasing attentions have been given to importance of inclusion wind-sea and swell components in the joint description. Presence of wind-sea and swell will affect design and operability of fixed and floating offshore structures as well as LNG terminals. The study presents a joint met-ocean model which can be applied for design and operations of marine structures, including LNG platforms. The model is fitted to hindcast data from four locations: Southern North Sea, West Shetland, and Northwest Shelf of Australia and off coast of Nigeria. Uncertainties related to the proposed fits are examined focusing on location specific features of the wave climate and an adopted partitioning procedure for the wave components. Implications of the uncertainties on design and operation criteria of LNG platforms are discussed and demonstrated by examples.

Spatial patterns of genome‐wide expression profiles reflect anatomic and fiber connectivity architecture of healthy human brain

Unraveling the relationship between molecular signatures in the brain and their functional, architectonic, and anatomic correlates is an important neuroscientific goal. It is still not well understood whether the diversity demonstrated by histological studies in the human brain is reflected in the spatial patterning of whole brain transcriptional profiles. Using genome-wide maps of transcriptional distribution of the human brain by the Allen Brain Institute, we test the hypothesis that gene expression profiles are specific to anatomically described brain regions. In this work, we demonstrate that this is indeed the case by showing that gene similarity clusters appear to respect conventional basal-cortical and caudal-rostral gradients. To fully investigate the causes of this observed spatial clustering, we test a connectionist hypothesis that states that the spatial patterning of gene expression in the brain is simply reflective of the fiber tract connectivity between brain regions. We find that although gene expression and structural connectivity are not determined by each other, they do influence each other with a high statistical significance. This implies that spatial diversity of gene expressions is a result of mainly location-specific features but is influenced by neuronal connectivity, such that like cellular species preferentially connects with like cells.