The genetic algorithm-aided three-stage ensemble learning method identified a robust survival risk score in patients with glioma.

Ensemble learning is a kind of machine learning method which can integrate multiple basic learners together and achieve higher accuracy. Recently, single machine learning methods have been established to predict survival for patients with cancer. However, it still lacked a robust ensemble learning model with high accuracy to pick out patients with high risks. To achieve this, we proposed a novel genetic algorithm-aided three-stage ensemble learning method (3S score) for survival prediction. During the process of constructing the 3S score, double training sets were used to avoid over-fitting; the gene-pairing method was applied to reduce batch effect; a genetic algorithm was employed to select the best basic learner combination. When used to predict the survival state of glioma patients, this model achieved the highest C-index (0.697) as well as area under the receiver operating characteristic curve (ROC-AUCs) (first year = 0.705, third year = 0.825 and fifth year = 0.839) in the combined test set (n = 1191), compared with 12 other baseline models. Furthermore, the 3S score can distinguish survival significantly in eight cohorts among the total of nine independent test cohorts (P < 0.05), achieving significant improvement of ROC-AUCs. Notably, ablation experiments demonstrated that the gene-pairing method, double training sets and genetic algorithm make sure the robustness and effectiveness of the 3S score. The performance exploration on pan-cancer showed that the 3S score has excellent ability on survival prediction in five kinds of cancers, which was verified by Cox regression, survival curves and ROC curves together. To enable its clinical adoption, we implemented the 3S score and other two clinical factors as an easy-to-use web tool for risk scoring and therapy stratification in glioma patients.

Deep learning-based multimodal fusion of the surface ECG and clinical features in prediction of atrial fibrillation recurrence following catheter ablation.

BACKGROUND: Despite improvement in treatment strategies for atrial fibrillation (AF), a significant proportion of patients still experience recurrence after ablation. This study aims to propose a novel algorithm based on Transformer using surface electrocardiogram (ECG) signals and clinical features can predict AF recurrence. METHODS: Between October 2018 to December 2021, patients who underwent index radiofrequency ablation for AF with at least one standard 10-second surface ECG during sinus rhythm were enrolled. An end-to-end deep learning framework based on Transformer and a fusion module was used to predict AF recurrence using ECG and clinical features. Model performance was evaluated using areas under the receiver operating characteristic curve (AUROC), sensitivity, specificity, accuracy and F1-score. RESULTS: A total of 920 patients (median age 61 [IQR 14] years, 66.3% male) were included. After a median follow-up of 24 months, 253 patients (27.5%) experienced AF recurrence. A single deep learning enabled ECG signals identified AF recurrence with an AUROC of 0.769, sensitivity of 75.5%, specificity of 61.1%, F1 score of 55.6% and overall accuracy of 65.2%. Combining ECG signals and clinical features increased the AUROC to 0.899, sensitivity to 81.1%, specificity to 81.7%, F1 score to 71.7%, and overall accuracy to 81.5%. CONCLUSIONS: The Transformer algorithm demonstrated excellent performance in predicting AF recurrence. Integrating ECG and clinical features enhanced the models' performance and may help identify patients at low risk for AF recurrence after index ablation.

Armcx1 attenuates secondary brain injury in an experimental traumatic brain injury model in male mice by alleviating mitochondrial dysfunction and neuronal cell death.

Armcx1 is highly expressed in the brain and is located in the mitochondrial outer membrane of neurons, where it mediates mitochondrial transport. Mitochondrial transport promotes the removal of damaged mitochondria and the replenishment of healthy mitochondria, which is essential for neuronal survival after traumatic brain injury (TBI). This study investigated the role of Armcx1 and its potential regulator(s) in secondary brain injury (SBI) after TBI. An in vivo TBI model was established in male C57BL/6 mice via controlled cortical impact (CCI). Adeno-associated viruses (AAVs) with Armcx1 overexpression and knockdown were constructed and administered to mice via stereotactic cortical injection. Exogenous miR-223-3p mimic or inhibitor was transfected into cultured cortical neurons, which were then scratched to simulate TBI in vitro. It was found that Armcx1 expression decreased significantly, while miR-223-3p levels increased markedly in peri-lesion tissues after TBI. The overexpression of Armcx1 significantly reduced TBI-induced neurological dysfunction, neuronal cell death, mitochondrial dysfunction, and axonal injury, while the knockdown of Armcx1 had the opposite effect. Armcx1 was potentially a direct target of miR-223-3p. The miR-223-3p mimic obviously reduced the Armcx1 protein level, while the miR-223-3p inhibitor had the opposite effect. Finally, the miR-223-3p inhibitor dramatically improved mitochondrial membrane potential (MMP) and increased the total length of the neurites without affecting branching numbers. In summary, our results suggest that the decreased expression of Armcx1 protein in neurons after experimental TBI aggravates secondary brain injury, which may be regulated by miR-223-3p. Therefore, this study provides a potential therapeutic approach for treating TBI.

Curcumin Induces Apoptosis by Suppressing XRCC4 Expression in Hepatocellular Carcinoma.

Curcumin is a chemical with various pharmacological activities used for cancer treatment. It inhibits hepatocellular carcinoma (HCC) by inducing apoptosis. Here, the mechanism underlying the effect of curcumin on the apoptosis of HCC cells was studied. Cell counting kit-8 and plate cloning assays were used to assess the proliferation of HCC cells, and acridine orange/ethidium bromide and Annexin V/PI staining were used to analyze their apoptosis. HCC xenograft tumor models were established to validate anti-cancer effects of curcumin. Expression levels of XRCC4 protein in tumor tissues were assessed by immunohistochemistry. Correlation between XRCC4 expression and the prognosis of patients with HCC was analyzed by integrating publicly available gene expression data. Curcumin inhibited HCC cells proliferation in a dose-dependent manner. Compared with the control group, curcumin significantly promoted the apoptosis of HCC cells in vitro and in vivo. Immunohistochemical analysis revealed that curcumin downregulated XRCC4 expression levels in HCC tissues. Prognosis of HCC patients with high XRCC4 expression was poorer than that of patients with low XRCC4 expression. Therefore, curcumin exerts anti-cancer effects by inhibiting cell proliferation and promoting cell apoptosis in HCC. This may be due to curcumin interference in the repair process of the nonhomologous DNA terminal link of HCC cells by downregulating XRCC4 expression.

Plasma 8-Hydroxy-2'-Deoxyguanosine, a Potential Valuable Biomarker for Atrial Fibrosis Is Influenced by Polymorphism of DNA Methylation Gene.

BACKGROUND: Previous studies revealed a relationship between 8-hydroxy-2'-deoxyguanosine (8-OHdG) and the occurrence/recurrence of atrial fibrillation (AF). This 2-part study aimed to validate whether DNA damage related to 8-OHdG is associated with left atrial (LA) fibrosis in AF patients quantified by voltage mapping (Part I), and to identify the underlying genetic components regulating the 8-OHdG level (Part II).Methods and Results: Plasma 8-OHdG determination, DNA extraction, and genotyping were conducted before catheter ablation. LA voltage mapping was performed under sinus rhythm. According to the percentage of low voltage area (LVA), patients were categorized as stage I (<5%), stage II (5-10%), stage III (10-20%), and stage IV (>20%). Part I included 209 AF patients. The 8-OHdG level showed an upward trend together with advanced LVA stage (stage I 8.1 [6.1, 10.5] ng/mL, stage II 8.5 [5.7, 14.1] ng/mL, stage III 14.3 [12.1, 16.5] ng/mL, stage IV 13.9 [10.5, 16.0] ng/mL, P<0.000). Part II included 175 of the 209 patients from Part I. Gene-set analysis based on genome-wide association study summary data identified that the gene set named 'DNA methylation on cytosine' was the only genetic component significantly associated with 8-OHdG concentration. CONCLUSIONS: Higher 8-OHdG levels may predict more advanced LVA of the LA in AF patients. DNA methylation is the putative genetic component underlying oxidative DNA damage in AF patients.

Chitooligosaccharides Derivatives Protect ARPE-19 Cells against Acrolein-Induced Oxidative Injury.

Age-related macular degeneration (AMD) is the leading cause of vision loss among the elderly. The progression of AMD is closely related to oxidative stress in the retinal pigment epithelium (RPE). Here, a series of chitosan oligosaccharides (COSs) and N-acetylated derivatives (NACOSs) were prepared, and their protective effects on an acrolein-induced oxidative stress model of ARPE-19 were explored using the MTT assay. The results showed that COSs and NACOs alleviated APRE-19 cell damage induced by acrolein in a concentration-dependent manner. Among these, chitopentaose (COS-5) and its N-acetylated derivative (N-5) showed the best protective activity. Pretreatment with COS-5 or N-5 could reduce intracellular and mitochondrial reactive oxygen species (ROS) production induced by acrolein, increase mitochondrial membrane potential, GSH level, and the enzymatic activity of SOD and GSH-Px. Further study indicated that N-5 increased the level of nuclear Nrf2 and the expression of downstream antioxidant enzymes. This study revealed that COSs and NACOSs reduced the degeneration and apoptosis of retinal pigment epithelial cells by enhancing antioxidant capacity, suggesting that they have the potential to be developed into novel protective agents for AMD treatment and prevention.

Inhibition Effects and Mechanisms of Marine Polysaccharide PSSD against Herpes Simplex Virus Type 2.

Genital herpes is a common sexually transmitted disease mainly caused by herpes simplex virus type 2 (HSV-2), which can increase the risk of HIV transmission and is a major health problem in the world. Thus, it is of great significance to develop new anti-HSV-2 drugs with high efficiency and low toxicity. In this study, the anti-HSV-2 activities of PSSD, a marine sulfated polysaccharide, was deeply explored both in vitro and in vivo. The results showed that PSSD had marked anti-HSV-2 activities in vitro with low cytotoxicity. PSSD can directly interact with virus particles to inhibit the adsorption of virus to the cell surface. PSSD may also interact with virus surface glycoproteins to block virus-induced membrane fusion. Importantly, PSSD can significantly attenuate the symptoms of genital herpes and weight loss in mice after gel smear treatment, as well as reducing the titer of virus shedding in the reproductive tract of mice, superior to the effect of acyclovir. In summary, the marine polysaccharide PSSD possesses anti-HSV-2 effects both in vitro and in vivo, and has potential to be developed into a novel anti-genital herpes agent in the future.

Marine Sulfated Polysaccharide PMGS Synergizes with Paclitaxel in Inhibiting Cervical Cancer In Vitro.

The incidence and mortality of cervical cancer in female malignancies are second only to breast cancer, which brings a heavy health and economic toll worldwide. Paclitaxel (PTX)-based regimens are the first-class choice; however, severe side effects, poor therapeutic effects, and difficulty in effectively preventing tumor recurrence or metastasis are unavoidable. Therefore, it is necessary to explore effective therapeutic interventions for cervical cancer. Our previous studies have shown that PMGS, a marine sulfated polysaccharide, exhibits promising anti-human papillomavirus (anti-HPV) effects through multiple molecular mechanisms. In this article, a continuous study identified that PMGS, as a novel sensitizer, combined with PTX exerted synergistic anti-tumor effects on cervical cancer associated with HPV in vitro. Both PMGS and PTX inhibited the proliferation of cervical cancer cells, and the combination of PMGS with PTX displayed significant synergistic effects on Hela cells. Mechanistically, PMGS synergizes with PTX by enhancing cytotoxicity, inducing cell apoptosis and inhibiting cell migration in Hela cells. Collectively, the combination of PTX and PMGS potentially provides a novel therapeutic strategy for cervical cancer.

Clinical significance of neutrophil gelatinase-associated lipocalin and sdLDL-C for coronary artery disease in patients with type 2 diabetes mellitus aged ≥ 65 years.

BACKGROUND AND AIMS: Although type 2 diabetes mellitus (T2DM) and coronary artery disease (CAD) share many common pathological and physiological characteristics, there are few studies assessing the predictive capacity of novel biomarkers in occurrence and development of CAD in T2DM patients aged ≥ 65 years. In addition, T2DM patients aged ≥ 65 years are prone to CAD. Therefore, it is of great significance to find novel biomarkers for the development CAD in T2DM. METHODS: In this retrospective cohort study, 579 T2DM patients aged ≥ 65 years were consecutively enrolled in this work, and 177 of whom had major adverse cardiovascular and cerebrovascular events (MACCE: cardiovascular or cerebrovascular death, acute coronary syndrome, coronary stent implantation, and stroke) during the follow up. Univariate and multivariate factors were employed to analyze the correlation between each variable and the occurrence of MACCE, and the Spearman's rank correlation analysis was performed to assess the relationships between Neutrophil gelatinase-associated lipocalin (NGAL) and small dense low-density lipoprotein-cholesterol (LDL-C) (sdLDL-C). The receiver operating characteristic (ROC) curve was adopted to determine the predictive value of NGAL and sdLDL-C elevation for MACCE in T2DM patients aged ≥ 65 years. RESULTS: After a median 48 months follow-up [19, (10 ~ 32) ], the levels of NGAL, sdLDL-C, hemoglobin A1c (HbA1c), LDL-C, and apolipoprotein B (ApoB) were significantly higher while those of high-density lipoprotein cholesterol (HDL-C) and apolipoprotein A I (ApoA-I) were lower in MACCE positive group. NGAL correlated to body mass index (BMI) (r = 0.391, P = 0.001) and triglyceride (TG) (r = 0.228, P = 0.032), and high-sensitivity CRP (hsCRP) (r = 0.251, P = 0.007), and neutrophils (r = 0.454, P = 0.001), sdlDL-C level was found to be positively correlated with LDL-C (r = 0.413, P = 0.001), TG (r = 0.432, P = 0.001), and ApoB (r = 0.232, P = 0.002); and it was negatively correlated with HDL-C (r = -0.362, P = 0.031) and ApoA-I (r = -0.402, P = 0.001). Age-adjusted Cox regression analysis showed that NGAL (HR = 1.006, 95% confidence interval (CI): 1.005-1.008, P < 0.001) and sdLDL-C (HR = 1.052, 95% CI: 1.037-1.066, P < 0.001) were independently associated with occurrence of MACCE. ROC curve analysis showed that NGAL (area under ROC (AUC) = 0.79, 95% CI: 0.75-0.84, P < 0.001) and sdlDL-C (AUC = 0.76, 95% CI: 0.72-0.80, P < 0.001) could predict the occurrence of MACCE (area under ROC. NGAL combined with sdlDL-C could predict the occurrence of MACCE well (AUC = 0.87, 95% CI: 0.84-0.90, P < 0.001). CONCLUSION: The higher NGAL and sdLDL-C in T2DM patients aged ≥ 65 years were significantly and independently associated with the risk of MACCE, and showed higher clinical values than other lipid biomarkers or other chronic inflammation, so they were expected to be the most effective predictors of MACCE assessment.

Catheter ablation of atrial tachycardia originated from the left atrial epicardium.

A patient was referred with frequent atrial tachycardia (AT) attacks. Activation mapping showed that the left atrium (LA) roof was earlier activated with a broad region, and right atrial activation was delayed. The far-field A wave corresponding to the pulmonary artery area was advanced with failed ablation. Therefore, the AT could be left atrial epicardial origin, which was further confirmed by the successful ablation at earliest activated site at the epicardium.

Electrochemical Characteristics of Shewanella loihica PV-4 on Reticulated Vitreous Carbon (RVC) with Different Potentials Applied.

The current output of an anodic bioelectrochemical system (BES) depends upon the extracellular electron transfer (EET) rate from electricigens to the electrodes. Thus, investigation of EET mechanisms between electricigens and solid electrodes is essential. Here, reticulated vitreous carbon (RVC) electrodes are used to increase the surface available for biofilm formation of the known electricigen Shewanella loihica PV-4, which is limited in conventional flat electrodes. S. loihica PV-4 utilizes flavin-mediated EET at potential lower than the outer membrane cytochromes (OMC), while at higher potential, both direct electron transfer (DET) and mediated electron transfer (MET) contribute to the current output. Results show that high electrode potential favors cell attachment on RVC, which enhances the current output. DET is the prevailing mechanism in early biofilm, while the contribution of MET to current output increased as the biofilm matured. Electrochemical analysis under starvation shows that the mediators could be confined in the biofilm. The morphology of biofilm shows bacteria distributed on the top layer of honeycomb structures, preferentially on the flat areas. This study provides insights into the EET pathways of S. loihica PV-4 on porous RVC electrodes at different biofilm ages and different set potential, which is important for the design of real-world BES.

NV center pumped and enhanced by nanowire ring resonator laser to integrate a 10 µm-scale spin-based sensor structure.

In this work, we propose a 10 µm-scale spin-based sensor structure, which mainly consists of a nanowire (NW) ring resonator laser, nitrogen-vacancy (NV) defects in a nanodiamond (ND) and a microwave (MW) antenna. The NW laser was bent into a ring with a gap to pump the NV defects in the ND which was assembled in the gap with the diameter of ∼8 µm. And the fluorescent light of NV defects was enhanced by the NW ring resonator about 8 times. Furthermore, the NW laser pulse was produced by the optical switch and a simple plus-sequences was designed to get the Rabi oscillation signal. Based on the Rabi oscillation, a Ramsey-type sequence was used to detect the magnetic field with the sensitivity of 83 nT √Hz-1 for our 10 µm-scale spin-based sensor structure. It proves the spin state in our structure allows for coherent spin manipulation for more complex quantum control schemes. And our structure fulfills the fundamental requirements to develop chip-scale spin-based sensors.

A Novel PTP1B Inhibitor-Phosphate of Polymannuronic Acid Ameliorates Insulin Resistance by Regulating IRS-1/Akt Signaling.

Protein tyrosine phosphatase 1B (PTP1B) is a critical negative modulator of insulin signaling and has attracted considerable attention in treating type 2 diabetes mellitus (T2DM). Low-molecular-weight polymannuronic acid phosphate (LPMP) was found to be a selective PTP1B inhibitor with an IC50 of 1.02 ± 0.17 µM. Cellular glucose consumption was significantly elevated in insulin-resistant HepG2 cells after LPMP treatment. LPMP could alleviate oxidative stress and endoplasmic reticulum stress, which are associated with the development of insulin resistance. Western blot and polymerase chain reaction (PCR) analysis demonstrated that LPMP could enhance insulin sensitivity through the PTP1B/IRS/Akt transduction pathway. Furthermore, animal study confirmed that LPMP could decrease blood glucose, alleviate insulin resistance, and exert hepatoprotective effects in diabetic mice. Taken together, LPMP can effectively inhibit insulin resistance and has high potential as an anti-diabetic drug candidate to be further developed.

Preparation and Evaluation of a Self-Nanoemulsifying Drug Delivery System Loaded with Heparin Phospholipid Complex.

A self-nanoemulsifying drug delivery system (SNEDDS) was developed to enhance the absorption of heparin after oral administration, in which heparin was compounded with phospholipids to achieve better fat solubility in the form of heparin-phospholipid (HEP-Pc) complex. HEP-Pc complex was prepared using the solvent evaporation method, which increased the solubility of heparin in n-octanol. The successful preparation of HEP-Pc complex was confirmed by differential scanning calorimetry (DSC), Fourier-transform infrared (FT-IR) spectroscopy, NMR, and SEM. A heparin lipid microemulsion (HEP-LM) was prepared by high-pressure homogenization and characterized. HEP-LM can enhance the absorption of heparin after oral administration, significantly prolong activated partial thromboplastin time (APTT) and thrombin time (TT) in mice, and reduce fibrinogen (FIB) content. All these outcomes indicate that HEP-LM has great potential as an oral heparin formulation.

Molecular cloning, characterization, and heterologous expression of an acetyl-CoA acetyl transferase gene from Sanghuangporus baumii.

Acetyl-CoA C-acetyltransferase synthase gene (AACT) cDNA, DNA and promoter were cloned from Sanghuangporus baumii. The gene ORF (1260 bp) encoded 419 amino acids. The AACT DNA includes five exons (1-84 bp, 140-513 bp, 570-1027 bp, 1090-1282 bp, 1344-1494 bp) and four introns (85-139 bp, 514-569 bp, 1028-1089 bp, 1283-1343 bp). The molecular weight of AACT protein is 43.40 kDa, it is hydrophilic with a theoretical isoelectric point of 8.96. Furthermore, The region of the transcription start site is 1997-2047 bp of AACT promoter, and it contained promoter elements (TATA Boxs, CAAT Boxs, CAAT-box, ABRE, G-Boxs, Sp1, MSA-like, LTR). AACT recombinant protein (43.40 KDa + Tag protein 22.68 KDa) was subjected in SDS-PAGE. AACT the transcription levels of in different development stages were investigated. The expression of AACT in primordia (2.4-fold) and 15 d mycelia (2.3- fold) were significantly higher than 9 d mycelia (contral). The expression level of the AACT downstream genes and triterpenoids content were determined at different developmental stages. Triterpenoid content reached its peak on day 15(7.21 mg/g).

Visual/CVG-AFS/ICP-MS multi-mode and label-free detection of target nucleic acids based on a selective cation exchange reaction and enzyme-free strand displacement amplification.

Conventional atomic spectrometry biosensors usually require labeling and separation of signaling molecules. Visual assays have direct and effective characteristics; however, they have poor accuracy. We intended to improve the analytical performance of our previous work and simplify the experimental operation while maintaining the advantages of simple operation and low cost. Herein, we describe the development of a visual, chemical vapor generation-atomic fluorescence spectrometry (CVG-AFS) and inductively coupled plasma-mass spectrometry (ICP-MS) three-mode method for the analysis of nucleic acids via CdTe quantum dot (QD)-assisted selective cation exchange reaction and enzyme-free strand displacement amplification. This work mainly utilized the ability of CdTe QDs to selectively differentiate free Hg2+ from the T-Hg2+-T complex in addition to the simple selective membrane filtration separation of Cd2+ from CdTe QDs to improve the performance of label-free bioassay methods. Due to the superior optical features of CdTe QDs, they can not only be used as a signal molecule for atomic spectroscopy, but also for direct use in visual readings. Under optimal experimental conditions, the developed strategy displayed a wide linear range along with limits of detection (LODs) of 10 fM and 3 fM (2 fM) in the linear concentration ranges of 10 fM-100 pM and 10 fM-1 nM with the naked eye and CVG-AFS (ICP-MS) assays, respectively. This method also exhibited excellent DNA sequence specificity. This assay had advantageous characteristics such as an easy operation, simple design, high sensitivity, and diversified signal readout manner, which demonstrate its great potential in medical diagnosis applications.

Iterative Positioning Algorithm for Indoor Node Based on Distance Correction in WSNs.

Node position information is critical in wireless sensor networks (WSN). However, existing positioning algorithms commonly have the issue of low positioning accuracy due to noise interferences in communication. Hence, proposed in this paper is an iterative positioning algorithm based on distance correction to improve the positioning accuracy of target nodes in WSNs, with contributions including (1) a log-distance distribution model of received signal strength indication (RSSI) ranging which is built and from which is derived a noise impact factor based on the model, (2) the initial position coordinates of the target node obtained using a triangle centroid localization algorithm, via which the distance deviation coefficient under the influence of noise is calculated, and (3) the ratio of the distance measured by the log-distance distribution model to the median distance deviation coefficient which is taken as the new distance between the target node and the anchor node. Based on the new distance, the triangular centroid positioning algorithm is applied to calculate the coordinates of the target node, after which the iterative positioning model is constructed and the distance deviation coefficient updated repeatedly to update the positioning result until the criteria of iterations are reached. Experiment results show that the proposed iterative positioning algorithm is promising and effectively improves positioning accuracy.

Feature Selection Method Based on High-Resolution Remote Sensing Images and the Effect of Sensitive Features on Classification Accuracy.

With the advent of high spatial resolution remote sensing imagery, numerous image features can be utilized. Applying a reasonable feature selection approach is critical to effectively reduce feature redundancy and improve the efficiency and accuracy of classification. This paper proposes a novel feature selection approach, in which ReliefF, genetic algorithm, and support vector machine (RFGASVM) are integrated to extract buildings. We adopt the ReliefF algorithm to preliminary filter high-dimensional features in the feature database. After eliminating the sorted features, the feature subset and the C and γ parameters of support vector machine (SVM) are encoded into the chromosome of the genetic algorithm. A fitness function is constructed considering the sample identification accuracy, the number of selected features, and the feature cost. The proposed method was applied to high-resolution images obtained from different sensors, GF-2, BJ-2, and unmanned aerial vehicles (UAV). The confusion matrix, precision, recall and F1-score were applied to assess the accuracy. The results showed that the proposed method achieved feature reduction, and the overall accuracy (OA) was more than 85%, with Kappa coefficient values of 0.80, 0.83 and 0.85, respectively. The precision of each image was more than 85%. The time efficiency of the proposed method was two-fold greater than SVM with all the features. The RFGASVM method has the advantages of large feature reduction and high extraction performance and can be applied in feature selection.

Fine-Scale Population Estimation by 3D Reconstruction of Urban Residential Buildings.

Fine-scale population estimation is essential in emergency response and epidemiological applications as well as urban planning and management. However, representing populations in heterogeneous urban regions with a finer resolution is a challenge. This study aims to obtain fine-scale population distribution based on 3D reconstruction of urban residential buildings with morphological operations using optical high-resolution (HR) images from the Chinese No. 3 Resources Satellite (ZY-3). Specifically, the research area was first divided into three categories when dasymetric mapping was taken into consideration. The results demonstrate that the morphological building index (MBI) yielded better results than built-up presence index (PanTex) in building detection, and the morphological shadow index (MSI) outperformed color invariant indices (CIIT) in shadow extraction and height retrieval. Building extraction and height retrieval were then combined to reconstruct 3D models and to estimate population. Final results show that this approach is effective in fine-scale population estimation, with a mean relative error of 16.46% and an overall Relative Total Absolute Error (RATE) of 0.158. This study gives significant insights into fine-scale population estimation in complicated urban landscapes, when detailed 3D information of buildings is unavailable.

[High Resolution Remote Sensing Monitoring and Assessment of Secondary Geological Disasters Triggered by the Lushan Earthquake].

The secondary geological disasters triggered by the Lushan earthquake on April 20, 2013, such as landslides, collapses, debris flows, etc., had caused great casualties and losses. We monitored the number and spatial distribution of the secondary geological disasters in the earthquake-hit area from airborne remote sensing images, which covered areas about 3 100 km2. The results showed that Lushan County, Baoxing County and Tianquan County were most severely affected; there were 164, 126 and 71 secondary geological disasters in these regions. Moreover, we analyzed the relationship between the distribution of the secondary geological disasters, geological structure and intensity. The results indicate that there were 4 high-hazard zones in the monitored area, one focused within six kilometers from the epicenter, and others are distributed along the two main fault zones of the Longmen Mountain. More than 97% secondary geological disasters occurred in zones with a seismic intensity of VII to IX degrees, a slope between 25 A degrees and 50 A degrees, and an altitude of between 800 and 2 000 m. At last, preliminary suggestions were proposed for the rehabilitation and reconstruction planning of Lushan earthquake. According to the analysis result, airborne and space borne remote sensing can be used accurately and effectively in almost real-time to monitor and assess secondary geological disasters, providing a scientific basis and decision making support for government emergency command and post-disaster reconstruction.