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Accurate ultra-short-term prediction of UT1-UTC is crucial for real-time applications in high-precision reference frame conversions. Presently, traditional LS + AR and LS + MAR hybrid methods are commonly employed for UT1-UTC prediction. However, inherent unmodeled errors in fitting residuals of these methods often compromise the prediction performance. Thus, mitigating these common unmodeled errors presents an opportunity to enhance UT1-UTC prediction performance. Consequently, we propose a novel hybrid difference method for UT1-UTC ultra-short-term prediction by integrating LOD prediction and the prediction of the sum of the LOD and the first-order-difference UT1-UTC. The evaluation demonstrated promising results: (1) The mean absolute errors (MAEs) of the proposed method range from 21 to 869 µs in 1–10-day UT1-UTC predictions. (2) Comparative analysis against zero-/first-/second-order-difference LS + AR and zero-/first-order-difference LS + MAR hybrid method reveals a substantial reduction in MAEs by an average of 54/64/44 µs, and 47/20 µs, respectively, with the proposed method. (3) Correspondingly, the proposed method achieves average improvement percentages of 17%/18%/15%, and 13%/3% in 1–10-day UT1-UTC predictions.

Mixed city is a term widely used in Israel to describe areas occupied by both Jewish and Arab communities. In a critical examination of such cities, the author shows how a clear spatial and mental division exists between Arabs and Jews in Israel, and how the occurrence of such communities is both exceptional and involuntary. Looking at Jewish-Arab relations in Israel in the context of the built environment, it is argued that there are complex links between socio-political relations and the production of contested urban space. The case study of one particular Jewish-Arab \"mixed city\", the city of Lod, is used as the platform for wider theoretical discussion and political analysis. This city has great significance in the present global context, as more and more cities are becoming polarized, ghettoized, and fragmented in surprisingly similar ways. This book examines the visible planning apparatuses and the \"hidden\" mechanisms of social, political, and cultural control involved in these processes. Focusing on the spatialities of power, this book brings to the fore a critical discussion of the urban processes that shape Jewish-Arab \"mixed cities\" in Israel, and will be of interest to students and scholars of Urban Studies, Middle East Studies and Politics in general. Introduction 1. Orientalism, Modernity and Urban Design in Mandatory Lydda 2. From al-Ludd to Lod 3. Architecture and the Struggle over Geography 4. Territorialization and the City's Geopolitics of Fear 5. Agents, Enemies, and the Privatization of Space 6. Walking, Inhabiting, Narrating. Conclusion Haim Yacobi is an architect and lecturer at the Department of Politics and Government at Ben-Gurion University. His main research interests are the production of urban space, social justice, the politics of identity, migration, globalization and urban planning.

Background: Sensitivity in the determination of the drug concentration is critical in pharmaceutical analysis. This research investigates several approaches for determining two sensitivity parameters, the Limit of Detection (LOD) and the Limit of Quantification (LOQ), in the analysis of the drug concentration using High-Performance Liquid Chromatography (HPLC). Methods: The study evaluates the FDA’s Lower Limit of Quantification (LLOQ) parameter, following global standards and quantitatively comparing sensitivity parameters for an established HPLC-UV method for the analysis of carbamazepine and phenytoin. Results: The study found that the LOD and LOQ values obtained by different methods varied significantly. The signal-to-noise ratio (S/N) method provided the lowest LOD and LOQ values for both drugs, while the standard deviation of the response and slope (SDR) method resulted in the highest values. This highlights the variability in sensitivity depending on the method used. Conclusion: The results show significant differences among calculated sensitivity values, emphasizing the influence of methodological variations on sensitivity values. It recommends following FDA criteria in chromatographic-based pharmaceutical analysis to improve the accuracy of drug concentration determination.

Concomitant with the acceleration of urbanization, the indoor scene of buildings becoming increasingly complex in recent years. In order to meet the needs of diverse indoor application analysis, the multi-level of detail (LOD) model of indoor scene has been paid increasing attention. However, there are two kinds of LODs in the fields of geographic information and building information, which cannot be effectively integrated. From the perspective of geographic scenario, this paper proposes a new concept of LOD to realize the construction of indoor scene model under different details. According to the effects on indoor space, the indoor components are divided into three semantic levels: enclosing component, connecting component and decorating component. Finally, several examples of indoor models combining semantic LOD, geometric LOD and process LOD are introduced.

This paper is focused to address the map display usability for finding given POI addresses in a popular urban city area. LOD 1 of 3D representations of city buildings are presented into a 2.5D map for pedestrian navigation test. This 3D map display is evaluated against familiar 2D map system on the test participants’ smartphones. 16 participants were involved in the field test. The typical walking model of a searching task that is focused only to look for a certain address of building is chosen as the way finding model during the field test. Three kinds of navigation processes i.e. self-orientation, spatial knowledge acquisition and navigation decision for searching task were evaluated for each test participant. Usability measures of 3D map-based display over 2D-map based display for pedestrian navigation were collected from test participants’ mobile devices. In addition to that, activities of test participants in terms of acceleration and orientation information are used to support analysis of pattern and trends of test participants. As the testing app is also intended to support smart city application, its ability to provide user report on complaints was also assessed. Most participants agreed with the statements in the questionnaire that were organized into three sections, i.e. addressing participants’ interaction, participants’ responses in navigation processes and crowdsensing. The results suggest that 3D map-based pedestrian navigation is more usable to be used to look for a certain address of building in central tourist area of urban city.

This paper is devoted to numerical approximations for the wave equation with a multiscale character. Our approach is formulated in the framework of the Localized Orthogonal Decomposition (LOD) interpreted as a numerical homogenization with an L2L^2-projection. We derive explicit convergence rates of the method in the L∞(L2)L^{\\infty }(L^2)-, W1,∞(L2)W^{1,\\infty }(L^2)- and L∞(H1)L^{\\infty }(H^1)-norms without any assumptions on higher order space regularity or scale-separation. The order of the convergence rates depends on further graded assumptions on the initial data. We also prove the convergence of the method in the framework of G-convergence without any structural assumptions on the initial data, i.e. without assuming that it is well-prepared. This rigorously justifies the method. Finally, the performance of the method is demonstrated in numerical experiments.

In the analysis of quantitative PCR (qPCR) data, the quantification cycle (Cq) indicates the position of the amplification curve with respect to the cycle axis. Because Cq is directly related to the starting concentration of the target, and the difference in Cq values is related to the starting concentration ratio, the only results of qPCR analysis reported are often Cq, ΔCq or ΔΔCq values. However, reporting of Cq values ignores the fact that Cq values may differ between runs and machines, and, therefore, cannot be compared between laboratories. Moreover, Cq values are highly dependent on the PCR efficiency, which differs between assays and may differ between samples. Interpreting reported Cq values, assuming a 100% efficient PCR, may lead to assumed gene expression ratios that are 100-fold off. This review describes how differences in quantification threshold setting, PCR efficiency, starting material, PCR artefacts, pipetting errors and sampling variation are at the origin of differences and variability in Cq values and discusses the limits to the interpretation of observed Cq values. These issues can be avoided by calculating efficiency-corrected starting concentrations per reaction. The reporting of gene expression ratios and fold difference between treatments can then easily be based on these starting concentrations.

Length of day (LOD), a critical component of Earth orientation parameters (EOP), represents variations in Earth's rotation rate. It is very difficult to predict accurately due to the effects of atmosphere, ocean, hydrology, the Earth's internal interactions and so on. The international Earth rotation and reference systems service (IERS) EOP C04 series, derived from four space geodetic observations, could offer high accuracy and smooth EOP product. However, this product typically has a latency of about 30 days. It is not adequate for fields requiring strict real-time data processing and applications, such as precise tracking and navigation of interplanetary spacecraft, global navigation satellite system (GNSS) meteorology, real-time precision orbit determination of artificial satellites, real-time kinematic (RTK) positioning and so on. To address the aforementioned issues, we propose an algorithm for predicting LOD that adopts a convolutional long-short-term memory (ConvLSTM) method with different base sequence lengths based on the LOD series from the IERS EOP C04, effective angular momentum (EAM) datasets and GNSS near-real-time (NRT) LOD data from the International GNSS Services (IGS) Rapid Products. Compared to the most accurate models used by participants in the Second Earth Orientation Parameters Prediction Comparison Campaign (2nd EOP PCC), when GNSS NRT data is not used, the proposed model improves LOD ultra-short-term (1-10 days) prediction accuracy by 29.72% and medium- to long-term (60-360 days) prediction accuracy by 11.86%. After incorporating GNSS NRT data, the short-term (10-30 days) LOD prediction accuracy improves by 55.07%. It is shown that the ConvLSTM model, integrated with GNSS NRT data and EAM datasets, could significantly enhance the forecast accuracy of LOD across various time spans. This advancement enriches the Earth's rotation prediction models and holds potential benefits for real time applications such as real-time satellite orbit determination, extreme weather analysis, RTK technology and so on.

Digital Elevation Models (DEMs) are extensively utilized for terrain analysis, representation, and visualization. Various application scenarios require DEMs at different Level of Details (LODs). Although traditional multi-scale landform expression methods primarily target DEMs at small scales, the simplifying Digital Surface Models (DSMs) for urban modeling at large scales remains a significant challenge. By integrating map generalization theory with computer vision techniques, we developed a novel method for urban building simplification in DSMs, termed Building Simplification in Digital Surface Models (BS-DSM). First, the buildings extracted from the DSMs are subjected to morphological analysis and aligned to a specific orientation. Next, the DSMs are divided into rectangular pixel blocks through energy-driven sampling, followed by horizontal simplification of building shapes in a 2D projection plane according to the geometric characteristics of these pixel blocks. Finally, to preserve the average height and total volume of the simplified 3D buildings in the vertical direction, the building heights across different pixel blocks are adjusted and interpolated based on the skeleton lines of building roofs and calculations of adjacent height values. The proposed BS-DSM method was evaluated using the publicly available Vaihingen DSM dataset. The result shows that the BS-DSM method performs better in simplifying building shape and height while meeting basic multi-scale expression constraints compared with traditional filtering methods.

Christine Garcia and colleagues use exome sequencing to identify genetic risk factors for familial pulmonary fibrosis. They observe an excess of rare damaging variants in PARN and RTEL1 in probands with pulmonary fibrosis and show that these variants cosegregate with disease in the affected families. Idiopathic pulmonary fibrosis (IPF) is an age-related disease featuring progressive lung scarring. To elucidate the molecular basis of IPF, we performed exome sequencing of familial kindreds with pulmonary fibrosis. Gene burden analysis comparing 78 European cases and 2,816 controls implicated PARN , an exoribonuclease with no previous connection to telomere biology or disease, with five new heterozygous damaging mutations in unrelated cases and none in controls ( P = 1.3 × 10 −8 ); mutations were shared by all affected relatives (odds in favor of linkage = 4,096:1). RTEL1 , an established locus for dyskeratosis congenita, harbored significantly more new damaging and missense variants at conserved residues in cases than in controls ( P = 1.6 × 10 −6 ). PARN and RTEL1 mutation carriers had shortened leukocyte telomere lengths, and we observed epigenetic inheritance of short telomeres in family members. Together, these genes explain ∼7% of familial pulmonary fibrosis and strengthen the link between lung fibrosis and telomere dysfunction.