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Visible Infrared Imaging Radiometer Suite (VIIRS) and Advanced Baseline Imager (GOES-R ABI) flood products have been widely used by the National Weather Service (NWS) for river flood monitoring, and by the Federal Emergency Management Agency (FEMA) for rescue and relief efforts. Some water bodies, like wetlands, are detected as water but not marked as permanent or normal water, which may result in their misclassification as floodwaters by VIIRS and GOES-R flood products. These water bodies generally do not cause significant property damage or fatalities, but they can complicate the identification of truly hazardous floods. This study utilizes the severe Louisiana flood event caused by Hurricane Ida to demonstrate how to differentiate wetlands from real-hazard flooding. Since Hurricane Ida made landfall in 2021, and there was no major flood event in 2022, VIIRS and ABI flood data from 2021 and 2022 were selected. The difference in annual total flooding days between 2021 and 2022 was calculated and combined with long-time flood frequency to distinguish non-hazard floodwaters due to wetlands identified from real-hazard floods caused by the hurricane. The results were compared with the wetlands from the change detection analysis. The confusion matrix analysis indicated an accuracy of 91.58%, precision of 89.97%, and F1-score of 76.63% for the VIIRS flood products. For the GOES-R ABI flood products, the confusion matrix analysis yielded an accuracy of 86.88%, precision of 97.49%, and F1-score of 75.21%. The accuracy and F1-score values for the GOES-R ABI flood products are slightly lower than those for the VIIRS flood products, possibly due to their lower spatial resolution, but still within a feasible range.

The reliability of circuit systems is primarily affected by cascading failures due to their complex structural and functional coupling. Causes of cascading failure during circuit operation include the continuous degradation process of components and external random shocks. Circuit systems can exhibit asymmetric structural changes and functional loss during cascading failure propagation due to the coupling of degradation and shock and their uncertainty effects. To tackle this issue, this paper abstracts the circuit into an impedance network and constructs a component failure behavior model that considers the correlation between degradation and shock. The interactions between soft and hard failure processes among different components are discussed. Two types of cascading failure propagation processes are described: slow propagation associated with continuous degradation and damage shock, and fast propagation due to fatal shock. Based on this, a cascading failure simulation algorithm is developed. This article presents a case study to demonstrate the proposed models and to analyze the reliability of a typical circuit system.

Cooperative localization (CL) is a popular research topic in the area of localization. Research is becoming more focused on Unmanned Aerial Vehicles (UAVs) and robots and less on pedestrians. This is because UAVs and robots can work in formation, but pedestrians cannot. In this study, we develop an adaptive decentralized cooperative localization (DCL) algorithm for a group of firefighters. Every member maintains a local filter and estimates the position and the relative measurement noise covariance is estimated rather than a fixed value. We derived the explicit expressions for the inter-member collaboration instead of using approximations. This method reduces the influence of non-line-of-sight (NLOS) errors in the ultra-wideband (UWB) ranging on the CL, eliminating the need for fixed UWB anchors. The proposed algorithm was validated by two experiments designed in the building and forest environments. The experimental results demonstrate that the proposed algorithm improved the accuracy of localization, and the proposed algorithm suppressed the localization errors by 14.23% and 47.01% compared to the decentralized cooperative localization extended Kalman filter (DCLEKF) algorithm, respectively.

Background: Our study measured the body composition of Diffuse large B-cell lymphoma (DLBCL) patients receiving rituximab with cyclophosphamide, doxorubicin, vincristine and prednisone (R-CHOP) regimen by computed tomographic (CT) and assessed their correlation with treatment-related toxicity and other adverse outcomes. Methods: We retrospectively analyzed 201 DLBCL patients who underwent pre-treatment abdominal CT examination. CT images were used to assess body composition metrics at the third lumbar vertebrae including fat tissues and muscle. Based on the skeletal muscle area (SMA) and density (SMD), skeletal muscle index (SMI), skeletal muscle gauge (SMG = SMI × SMD) and lean body mass (LBM) were calculated. Also analyzed were the toxicity, adverse events and survival. Results: We found that SMG, SMD, SMI and LBM were correlated with any grade 3–4 toxicity, dose reduction, hospitalization or termination of the treatment due to immunochemotherapy and worse survival. However, multivariate analysis demonstrated SMG [progression-free survival (PFS): hazard ratio (HR), 2.889; 95% CI, 1.401–5.959; p = 0.004; overall survival (OS): HR, 2.655; 95% CI, 1.218–5.787; p = 0.014] was the best predictor of poor prognosis. Conclusions: SMG, SMD, SMI and LBM were identified as predictors of adverse reactions and poor survival. SMG was an innovative and valuable indicator of immunochemotherapy toxicity and other adverse outcomes. Additionally, it can be used to individualize antineoplastic drug dosing.

Infertility affects lots of couples, half of which are caused by male factors. The LanCL1 gene is highly expressed in testis specifically, which might affect the development of sperms. In order to understand the potential functions of the LanCL1 gene in the testis, this study was conducted with constructed transgenic LanCL1 knockout mice. The mouse breeding experiment, semen analysis and single-cell RNAseq of testicular tissue were performed. Results suggested that the LanCL1 gene would significantly influence the reproduction ability and sperm motility of male mice. Single-cell RNAseq also confirmed the high expression of the LanCL1 gene in the spermatocytes and spermatids. Downregulating the LanCL1 gene expression could promote M2 macrophage polarity to maintain testicular homeostasis. Moreover, the LanCL1 gene could affect both the germ cells and stromal cells through various pathways such as the P53 signaling and the PPAR signaling pathway to disturb the normal process of spermatogenesis. However, no effects of the LanCL1 gene in testosterone synthesis and serum testosterone level were shown. Further studies are needed to discuss the mechanisms of the LanCL1 gene in the various cells of the testis independently.

Affibodies targeting intracellular proteins have a great potential to function as ideal therapeutic agents. However, little is known about how the affibodies enter target cells to interact with intracellular target proteins. We have previously developed the HPV16E7 affibody (ZHPV16E7384) for HPV16 positive cervical cancer treatment. Here, we explored the underlying mechanisms of ZHPV16E7384 and found that ZHPV16E7384 significantly inhibited the proliferation of target cells and induced a G1/S phase cell cycle arrest. Furthermore, ZHPV16E7384 treatment resulted in the upregulation of retinoblastoma protein (Rb) and downregulation of phosphorylated Rb (pRb), E2F1, cyclin D1, and CDK4 in the target cells. Moreover, treatment with dynamin or the caveolin-1 inhibitor not only significantly suppressed the internalization of ZHPV16E7384 into target cells but also reversed the regulation of cell cycle factors by ZHPV16E7384. Overall, these results indicate that ZHPV16E7384 was likely internalized specifically into target cells through dynamin- and caveolin-1 mediated endocytosis. ZHPV16E7384 induced the cell cycle arrest in the G1/S phase at least partially by interrupting HPV16E7 binding to and degrading Rb, subsequently leading to the downregulation of E2F1, cyclin D1, CDK4, and pRb, which ultimately inhibited target cell proliferation. These findings provide a rationale of using ZHPV16E7384 to conduct a clinical trial for target therapy in cervical cancer.

Resilience, the ability of a system to withstand disruptions and quickly return to a normal state, is essential for a low-Earth-orbit satellite communication system (LEO-SCS), as its large number of satellites, may encounter various disturbances. As a developing system with asymmetrical and insufficient data, it is with both aleatory and epistemic uncertainties, which renders existing resilience measures inapplicable. This paper utilizes uncertainty theory to define belief instantaneous availability, based on which a new resilience measure for the LEO-SCS is proposed. As the resilience is mainly determined by the dynamic and uncertain characteristics of an LEO-SCS, an uncertain satellite network evolution model is developed to describe its operating patterns, and an evaluation method is proposed to estimate its resilience. To illustrate our proposed uncertain theory-based resilience evaluation method, an LEO-SCS case with 48 satellites is studied, and its resilience values under different backup strategies are compared to assist in system design decisions.

Reliability analysis and trade-offs between safety and cost with insufficient data represent an inevitable problem during the early stage of structural design. In this paper, efficient uncertainty theory-based reliability analysis and a design method are proposed under epistemic uncertainty. The factors influencing the structure are regarded as uncertain variables. Based on this, a new metric termed uncertain measure is employed to define an uncertainty reliability indicator (URI) for estimating the reliable degree of structure. Two solving methods, namely, the crisp equivalent analytical method and uncertain simulation (US) method, are introduced to calculate the URI and acquire reliability. Thereafter, a URI-based design optimization (URBDO) model is constructed with target reliability constraints. To solve the URBDO model and obtain optimal solutions, crisp equivalent programming and a genetic-algorithm combined US approach are developed. Four physical examples are solved to verify the adaptability and advantage of the established model and corresponding solving techniques.

As the gymnasiums in subtropical region with hot and humid climate are naturally ventilated during non-competition periods, occupants exercising indoors often feel uncomfortable, especially in summer. In order to provide thermally comfortable and healthy environment for the occupants, the design on architectural form is found to be an effective solution on improving indoor thermal comfort of naturally ventilated gymnasiums. Therefore, a new perspective regarding optimization of naturally ventilated gymnasiums is proposed in the aspect of the architectural form. This paper presents the optimization of architectural form in naturally ventilated gymnasiums in which simulation and orthogonal experiment methods are combined. Through numerical simulation with FlowDesigner software, the significance of architectural form affecting indoor thermal comfort has been given, and the optimal architectural forms of naturally ventilated gymnasium are determined. The results show that the roof insulation type is the most significant factor influencing indoor thermal comfort; thus, it should be considered primarily in optimization. Moreover, the range analysis and variance analysis reveal the rankings of the factors for the gymnasium thermal comfort. In addition, it is demonstrated that the optimal gymnasium model, when compared with the initial gymnasium model, has a satisfactory effect on improving the indoor thermal comfort, as the average value of Predicted Thermal Sensation (PTS) in August decreased from 1.11 (Slightly hot) to 0.86 (Comfortable). This study provides a new insight for the designers in optimizing the architectural form of gymnasiums for achieving the indoor thermal comfort at hot and humid climate.

The utilization of remotely sensed observations for light use efficiency (LUE) and tower-based gross primary production (GPP) estimates was studied in a USDA cornfield. Nadir hyperspectral reflectance measurements were acquired at canopy level during a collaborative field campaign conducted in four growing seasons. The Photochemical Reflectance Index (PRI) and solar induced chlorophyll fluorescence (SIF), were derived. SIF retrievals were accomplished in the two telluric atmospheric oxygen absorption features centered at 688 nm (O2-B) and 760 nm (O2-A). The PRI and SIF were examined in conjunction with GPP and LUE determined by flux tower-based measurements. All of these fluxes, environmental variables, and the PRI and SIF exhibited diurnal as well as day-to-day dynamics across the four growing seasons. Consistent with previous studies, the PRI was shown to be related to LUE (r2 = 0.54 with a logarithm fit), but the relationship varied each year. By combining the PRI and SIF in a linear regression model, stronger performances for GPP estimation were obtained. The strongest relationship (r2 = 0.80, RMSE = 0.186 mg CO2/m2/s) was achieved when using the PRI and SIF retrievals at 688 nm. Cross-validation approaches were utilized to demonstrate the robustness and consistency of the performance. This study highlights a GPP retrieval method based entirely on hyperspectral remote sensing observations.

The Earth Observing One (EO-1) satellite has completed 16 years of Earth observations in early 2017. What started as a technology mission to test various new advancements turned into a science and application mission that extended many years beyond the satellite’s planned life expectancy. EO-1’s primary instruments are spectral imagers: Hyperion, the only civilian full spectrum spectrometer (430–2400 nm) in orbit, and the Advanced Land Imager (ALI), the prototype for Landsat-8’s pushbroom imaging technology. Both Hyperion and ALI instruments have continued to perform well, but in February 2011, the satellite ran out of the fuel necessary to maintain orbit, which initiated a change in precession rate that led to increasingly earlier equatorial crossing times during its last five years. The change from EO-1’s original orbit, when it was formation flying with Landsat-7 at a 10:01 a.m. equatorial overpass time, to earlier overpass times results in image acquisitions with increasing solar zenith angles (SZAs). This study takes several approaches to characterize data quality as SZAs increased. The results show that for both EO-1 sensors, atmospherically corrected reflectance products, are within 5 to 10% of mean pre-drift products. No marked trend in decreasing quality in ALI or Hyperion is apparent through 2016, and these data remain a high quality resource through the end of the mission.