The specificities, influencing factors, and medical implications of bone circadian rhythms.

Physiological processes within the human body are regulated in approximately 24-h cycles known as circadian rhythms, serving to adapt to environmental changes. Bone rhythms play pivotal roles in bone development, metabolism, mineralization, and remodeling processes. Bone rhythms exhibit cell specificity, and different cells in bone display various expressions of clock genes. Multiple environmental factors, including light, feeding, exercise, and temperature, affect bone diurnal rhythms through the sympathetic nervous system and various hormones. Disruptions in bone diurnal rhythms contribute to the onset of skeletal disorders such as osteoporosis, osteoarthritis and skeletal hypoplasia. Conversely, these bone diseases can be effectively treated when aimed at the circadian clock in bone cells, including the rhythmic expressions of clock genes and drug targets. In this review, we describe the unique circadian rhythms in physiological activities of various bone cells. Then we summarize the factors synchronizing the diurnal rhythms of bone with the underlying mechanisms. Based on the review, we aim to build an overall understanding of the diurnal rhythms in bone and summarize the new preventive and therapeutic strategies for bone disorders.

Susceptibility Analysis of Glacier Debris Flow Based on Remote Sensing Imagery and Deep Learning: A Case Study along the G318 Linzhi Section.

Glacial debris flow is a common natural disaster, and its frequency has been increasing in recent years due to the continuous retreat of glaciers caused by global warming. To reduce the damage caused by glacial debris flows to human and physical properties, glacier susceptibility assessment analysis is needed. Most research efforts consider the effect of existing glacier area and ignore the effect of glacier ablation volume change. In this paper, we consider the impact of glacier ablation volume change to investigate the susceptibility of glacial debris flow. The susceptibility to mudslide was evaluated by taking the glacial mudslide-prone ditch of G318 Linzhi section of Sichuan-Tibet Highway as the research object. First, by using a simple band ratio method with manual correction, we produced a glacial mudslide remote sensing image dataset, and second, we proposed a deep-learning-based approach using a weight-optimized glacial mudslide semantic segmentation model for accurately and automatically mapping the boundaries of complex glacial mudslide-covered remote sensing images. Then, we calculated the ablation volume by the change in glacier elevation and ablation area from 2015 to 2020. Finally, glacial debris flow susceptibility was evaluated based on the entropy weight method and Topsis method with glacial melt volume in different watersheds as the main factor. The research results of this paper show that most of the evaluation indices of the model are above 90%, indicating that the model is reasonable for glacier boundary extraction, and remote sensing images and deep learning techniques can effectively assess the glacial debris flow susceptibility and provide support for future glacial debris flow disaster prevention.

A network-based method with privacy-preserving for identifying influential providers in large healthcare service systems.

In data science, networks provide a useful abstraction of the structure of many complex systems, ranging from social systems and computer networks to biological networks and physical systems. Healthcare service systems are one of the main social systems that can also be understood using network-based approaches, for example, to identify and evaluate influential providers. In this paper, we propose a network-based method with privacy-preserving for identifying influential providers in large healthcare service systems. First, the provider-interacting network is constructed by employing publicly available information on locations and types of healthcare services of providers. Second, the ranking of nodes in the generated provider-interacting network is conducted in parallel on the basis of four nodal influence metrics. Third, the impact of the top-ranked influential nodes in the provider-interacting network is evaluated using three indicators. Compared with other research work based on patient-sharing networks, in this paper, the provider-interacting network of healthcare service providers can be roughly created according to the locations and the publicly available types of healthcare services, without the need for personally private electronic medical claims, thus protecting the privacy of patients. The proposed method is demonstrated by employing Physician and Other Supplier Data CY 2017, and can be applied to other similar datasets to help make decisions for the optimization of healthcare resources in the response to public health emergencies.

Genetic diversity analysis reveals that geographical environment plays a more important role than rice cultivar in Villosiclava virens population selection.

Rice false smut caused by Villosiclava virens is an economically important disease of grains worldwide. The genetic diversity of 153 isolates from six fields located in Wuhan (WH), Yichang Wangjia (YCW), Yichang Yaohe (YCY), Huanggang (HG), Yangxin (YX), and Jingzhou (JZ) in Hubei province of China were phylogenetically analyzed to evaluate the influence of environments and rice cultivars on the V. virens populations. Isolates (43) from Wuhan were from two rice cultivars, Wanxian 98 and Huajing 952, while most of the other isolates from fields YCW, YCY, HG, YX, and JZ originated from different rice cultivars with different genetic backgrounds. Genetic diversity of isolates was analyzed using random amplified polymorphic DNA (RAPD) and single-nucleotide polymorphisms (SNP). The isolates from the same cultivars in Wuhan tended to group together, indicating that the cultivars had an important impact on the fungal population. The 110 isolates from individual fields tended to cluster according to geographical origin. The values of Nei's gene diversity (H) and Shannon's information index (I) showed that the genetic diversity among isolates was higher between than within geographical populations. Furthermore, mean genetic distance between groups (0.006) was higher than mean genetic distance within groups (0.0048) according to MEGA 5.2. The pairwise population fixation index (FST) values also showed significant genetic differentiation between most populations. Higher genetic similarity of isolates from individual fields but different rice cultivars suggested that the geographical factor played a more important role in the selection of V. virens isolates than rice cultivars. This information could be used to improve the management strategy for rice false smut by adjusting the cultivation measures, such as controlling fertilizer, water, and planting density, in the rice field to change the microenvironment.

Summary on several key techniques in 3D geological modeling.

Several key techniques in 3D geological modeling including planar mesh generation, spatial interpolation, and surface intersection are summarized in this paper. Note that these techniques are generic and widely used in various applications but play a key role in 3D geological modeling. There are two essential procedures in 3D geological modeling: the first is the simulation of geological interfaces using geometric surfaces and the second is the building of geological objects by means of various geometric computations such as the intersection of surfaces. Discrete geometric surfaces that represent geological interfaces can be generated by creating planar meshes first and then spatially interpolating; those surfaces intersect and then form volumes that represent three-dimensional geological objects such as rock bodies. In this paper, the most commonly used algorithms of the key techniques in 3D geological modeling are summarized.

Evaluating the power of GPU acceleration for IDW interpolation algorithm.

We first present two GPU implementations of the standard Inverse Distance Weighting (IDW) interpolation algorithm, the tiled version that takes advantage of shared memory and the CDP version that is implemented using CUDA Dynamic Parallelism (CDP). Then we evaluate the power of GPU acceleration for IDW interpolation algorithm by comparing the performance of CPU implementation with three GPU implementations, that is, the naive version, the tiled version, and the CDP version. Experimental results show that the tilted version has the speedups of 120x and 670x over the CPU version when the power parameter p is set to 2 and 3.0, respectively. In addition, compared to the naive GPU implementation, the tiled version is about two times faster. However, the CDP version is 4.8x ∼ 6.0x slower than the naive GPU version, and therefore does not have any potential advantages in practical applications.

Substance P activates the Wnt signal transduction pathway and enhances the differentiation of mouse preosteoblastic MC3T3-E1 cells.

Recent experiments have explored the impact of Wnt/ß-catenin signaling and Substance P (SP) on the regulation of osteogenesis. However, the molecular regulatory mechanisms of SP on the formation of osteoblasts is still unknown. In this study, we investigated the impact of SP on the differentiation of MC3T3-E1 cells. The osteogenic effect of SP was observed at different SP concentrations (ranging from 10⁻¹° to 10⁻8 M). To unravel the underlying mechanism, the MC3T3-E1 cells were treated with SP after the pretreatment by neurokinin-1 (NK1) antagonists and Dickkopf-1 (DKK1) and gene expression levels of Wnt/ß-catenin signaling pathway components, as well as osteoblast differentiation markers (collagen type I, alkaline phosphatase, osteocalcin, and Runx2), were measured using quantitative polymerase chain reaction (PCR). Furthermore, protein levels of Wnt/ß-catenin signaling pathway were detected using Western blotting and the effects of SP, NK1 antagonist, and DKK1 on ß-catenin activation were investigated by immunofluorescence staining. Our data indicated that SP (10⁻9 to 10⁻8 M) significantly up-regulated the expressions of osteoblastic genes. SP (10⁻8 M) also elevated the mRNA level of c-myc, cyclin D1, and lymphocyte enhancer factor-1 (Lef1), as well as c-myc and ß-catenin protein levels, but decreased the expression of Tcf7 mRNA. Moreover, SP (10-8 M) promoted the transfer of ß-catenin into nucleus. The effects of SP treatment were inhibited by the NK1 antagonist and DKK1. These findings suggest that SP may enhance differentiation of MC3T3-E1 cells via regulation of the Wnt/ß-catenin signaling pathway.

CTEN-induced TGF-ß1 expression facilitates EMT and enhances paclitaxel resistance in bladder cancer cells.

OBJECTIVES: To investigate the role of C-terminal tensin-like (CTEN) in mediating chemotherapy resistance via epithelial-mesenchymal transition (EMT) in bladder cancer (BC) cells, through the regulation of transforming growth factor-ß1 (TGF-ß1) expression. METHODS: Lentiviral vectors were used to create CTEN overexpression and knockdown constructs, which were then introduced into paclitaxel-resistant BC cell lines. The effects of CTEN manipulation on cell proliferation and drug sensitivity was assessed using the CCK-8 assay, and apoptosis was evaluated by flow cytometry. The expression levels of CTEN, TGF-ß1, and EMT markers were quantified by RT-qPCR and Western blot analysis. The interaction between CTEN and TGF-ß1 and its effect on TGF-ß1 methylation were studied using bisulfite sequencing PCR and co-immunoprecipitation. RESULTS: Overexpression of CTEN in BC cells was associated with decreased paclitaxel efficacy, reduced apoptosis, and elevated levels of TGF-ß1 and EMT-related proteins. CTEN was found to bind TGF-ß1, inhibiting its methylation and thereby promoting TGF-ß1 upregulation. This increase in TGF-ß1 expression facilitated the EMT process and enhanced drug resistance in BC cells. CONCLUSIONS: The induction of TGF-ß1 expression by CTEN promotes EMT and increases chemotherapy resistance in BC cells. Targeting CTEN or the EMT pathway could improve chemosensitivity in treatment-resistant BC, suggesting a novel therapeutic strategy to enhance chemotherapy effectiveness.

Hydrogen/deuterium exchange mass spectrometry and site-directed disulfide cross-linking suggest an important dynamic interface between the two lysostaphin domains.

Lysostaphin is a peptidoglycan hydrolase secreted by Staphylococcus simulans. It can specifically lyse Staphylococcus aureus and is being tested as a novel antibacterial agent. The protein contains an N-terminal catalytic domain and a C-terminal cell wall targeting domain. Although the two domains from homologous enzymes were structurally determined, the structural organization of lysostaphin domains remains unknown. We used hydrogen/deuterium exchange mass spectrometry (H/DX-MS) and site-directed disulfide cross-linking to probe the interface between the lysostaphin catalytic and targeting domains. H/DX-MS-mediated comparison of peptides from full-length lysostaphin and the separated domains identified four peptides of lower solvent accessibility in the full-length protein. Cross-linking analysis using cysteine pair substitutions within those peptides showed that two pairs of cysteines can form disulfide bonds, supporting the domain association role of the targeted peptides. The cross-linked mutant exhibited a binding capacity to S. aureus that was similar to that of the wild-type protein but reduced bacteriolytic activity probably because of restraint in conformation. The diminished activity was further reduced with increasing NaCl concentrations that can cause contractions of bacterial peptidoglycan. The lytic activity, however, could be fully recovered by reducing the disulfide bonds. These results suggest that lysostaphin may require dynamic association of the two domains for coordinating substrate binding and target cleavage on the elastic peptidoglycan. Our study will help develop site-specific PEGylated lysostaphin to treat systemic S. aureus infections.

Insulin-like growth factor binding protein-3 modulates osteoblast differentiation via interaction with vitamin D receptor.

Insulin-like growth factor (IGF) binding protein-3 (IGFBP-3) is a secreted glycoprotein that reduces the bioavailability of IGFs. This glycoprotein has both IGF-dependent and -independent effects on cell growth. However, the mechanisms responsible for the IGF-independent actions of IGFBP-3 are not fully understood. In the present study, we used multiple methodologies including glutathione S-transferase pull-down assay and co-immunoprecipitation to demonstrate that IGFBP-3 can directly interact with vitamin D receptor (VDR) in vitro and in vivo. Furthermore, immunofluorescence co-localization studies showed that IGFBP-3 and VDR could co-localize in the cell nucleus. Reporter gene experiment showed that IGFBP-3 negatively regulates the growth hormone promoter activity induced by ligand-activated VDR. Moreover, real-time RT-PCR demonstrated that IGFBP-3 can inhibit the osteocalcin and CYP24a1 mRNA transcription induced by 1,25-(OH)2D3 in osteoblastic cells. Finally, alkaline phosphatase activity significantly decreased in osteoblastic cells when the cells were transfected with IGFBP-3 in the presence of 1,25-(OH)2D3. In conclusion, these studies provide evidence that overexpression of IGFBP-3 suppresses osteoblastic differentiation regulated by VDR in the presence of 1,25-(OH)2D3. These findings reveal a novel mechanism by which IGFBP-3 functions.

Differences between appressoria formed by germ tubes and appressorium-like structures developed by hyphal tips in Magnaporthe oryzae.

Melanized appressoria are highly specialized infection structures formed by germ tubes of the rice blast fungus Magnaporthe oryzae for plant infection. M. oryzae also forms appressorium-like structures on hyphal tips. Whereas appressorium formation by conidial germ tubes has been well characterized, formation of appressorium-like structures by hyphal tips is under-investigated. In a previous study, we found that the chs7 deletion mutant failed to form appressoria on germ tubes but were normal in the development of appressorium-like structures on artificial hydrophobic surfaces. In this study, we compared the differences between the formation of appressoria by germ tubes and appressorium-like structures by hyphal tips in M. oryzae. Structurally, both appressoria and appressorium-like structures had a melanin layer that was absent in the pore region. In general, the latters were 1.4-fold larger in size but had lower turgor pressure than appressoria, which is consistent with its lower efficiency in plant penetration. Treatments with cAMP, IBMX, or a cutin monomer efficiently induced appressorium formation but not the development of appressorium-like structures. In contrast, coating surfaces with waxes stimulated the formation of both infection structures. Studies with various signaling mutants indicate that Osm1 and Mps1 are dispensable but Pmk1 is essential for both appressorium formation and development of appressorium-like structures on hyphal tips. Interestingly, the cpkA mutant was reduced in the differentiation of appressorium-like structures but not appressorium formation. We also observed that the con7 mutant generated in our lab failed to form appressorium-like structures on hyphal tips but still produced appressoria by germ tubes on hydrophobic surfaces. Con7 is a transcription factor regulating the expression of CHS7. Overall, these results indicate that the development of appressorium-like structures by hyphal tips and formation of appressoria by germ tubes are not identical differentiation processes in M. oryzae and may involve different molecular mechanisms.

Neuropeptide SP activates the WNT signal transduction pathway and enhances the proliferation of bone marrow stromal stem cells.

Substance P (SP) mediates multiple activities in various cell types, such as proliferation, anti-apoptotic response, and inflammation. We have investigated the effects of SP, NK1 antagonist and DKK1 on proliferation of bone marrow stromal stem cells (BMSCs), as well as the underlying mechanism. Isolated BMSCs were exposed to SP (10(-8) M) (group A), SP + NK1 antagonist (1 µM) (group B), SP + DKK1 (0.2 µg/mL) (group C), or the same amount of PBS (group D). Expression of gene and protein of Wnt/ß-catenin signalling was detected using quantitative PCR and western blotting. SP (10(-8) M) significantly enhanced the proliferation of BMSCs and the number of viable cells was reduced by treatment with NK1 antagonist (1 µM) or DKK1 (0.2 µg/mL). SP also significantly increased the expression of C-myc mRNA, Lef1, ß-catenin protein and C-myc protein, but decreased the expression of Tcf7 and p-ß-catenin protein compared to group D. These roles of SP were inhibited by the NK1 antagonist and DKK1. Expression of CyclinD1 and ß-catenin mRNAs, however, was not significantly influenced by SP, NK1 antagonist and DKK1. These findings suggest that SP enhances BMSC proliferation via regulation of the Wnt/ß-catenin signalling pathway.

TPM: cloud-based tele-PTSD monitor using multi-dimensional information.

An automated system that can remotely and non-intrusively screen individuals at high risk for Post-Traumatic Stress Disorder (PTSD) and monitor their progress during treatment would be desired by many Veterans Affairs (VAs) as well as other PTSD treatment and research organizations. In this paper, we present an automated, cloud-based Tele-PTSD Monitor (TPM) system based on the fusion of multiple sources of information. The TPM system can be hosted in a cloud environment and accessed through landline or cell phones, or on the Internet through a web portal or mobile application (app).

Activation of metabotropic glutamate receptor 1 regulates hippocampal CA1 region excitability in rats with status epilepticus by suppressing the HCN1 channel.

Dysregulation of hyperpolarization-activated cyclic nucleotide-gated cation (HCN) channels alters neuronal excitability. However, the role of HCN channels in status epilepticus is not fully understood. In this study, we established rat models of pentylenetetrazole-induced status epilepticus. We performed western blot assays and immunofluorescence staining. Our results showed that HCN1 channel protein expression, particularly HCN1 surface protein, was significantly decreased in the hippocampal CA1 region, whereas the expression of HCN2 channel protein was unchanged. Moreover, metabolic glutamate receptor 1 (mGluR1) protein expression was increased after status epilepticus. The mGluR1 agonist (RS)-3,5-dihydroxyphenylglycine injected intracerebroventricularly increased the sensitivity and severity of pentylenetetrazole-induced status epilepticus, whereas application of the mGluR1 antagonist (+)-2-methyl-4-carboxyphenylglycine (LY367385) alleviated the severity of pentylenetetrazole-induced status epilepticus. The results from double immunofluorescence labeling revealed that mGluR1 and HCN1 were co-localized in the CA1 region. Subsequently, a protein kinase A inhibitor (H89) administered intraperitoneally successfully reversed HCN1 channel inhibition, thereby suppressing the severity and prolonging the latency of pentylenetetrazole-induced status epilepticus. Furthermore, H89 reduced the level of mGluR1, downregulated cyclic adenosine monophosphate (cAMP)/protein kinase A expression, significantly increased tetratricopeptide repeat-containing Rab8b-interacting protein (TRIP8b) (1a-4) expression, and restored TRIP8b (1b-2) levels. TRIP8b (1a-4) and TRIP8b (1b-2) are subunits of Rab8b interacting protein that regulate HCN1 surface protein.

Developmental growth plate cartilage formation suppressed by artificial light at night via inhibiting BMAL1-driven collagen hydroxylation.

Exposure to artificial light at night (LAN) can induce obesity, depressive disorder and osteoporosis, but the pernicious effects of excessive LAN exposure on tissue structure are poorly understood. Here, we demonstrated that artificial LAN can impair developmental growth plate cartilage extracellular matrix (ECM) formation and cause endoplasmic reticulum (ER) dilation, which in turn compromises bone formation. Excessive LAN exposure induces downregulation of the core circadian clock protein BMAL1, which leads to collagen accumulation in the ER. Further investigations suggest that BMAL1 is the direct transcriptional activator of prolyl 4-hydroxylase subunit alpha 1 (P4ha1) in chondrocytes, which orchestrates collagen prolyl hydroxylation and secretion. BMAL1 downregulation induced by LAN markedly inhibits proline hydroxylation and transport of collagen from ER to golgi, thereby inducing ER stress in chondrocytes. Restoration of BMAL1/P4HA1 signaling can effectively rescue the dysregulation of cartilage formation within the developmental growth plate induced by artificial LAN exposure. In summary, our investigations suggested that LAN is a significant risk factor in bone growth and development, and a proposed novel strategy targeting enhancement of BMAL1-mediated collagen hydroxylation could be a potential therapeutic approach to facilitate bone growth.

A voice-based automated system for PTSD screening and monitoring.

Comprehensive evaluation of PTSD includes diagnostic interviews, self-report testing, and physiological reactivity measures. It is often difficult and costly to diagnose PTSD due to patient access and the variability in symptoms presented. Additionally, potential patients are often reluctant to seek help due to the stigma associated with the disorder. A voice-based automated system that is able to remotely screen individuals at high risk for PTSD and monitor their symptoms during treatment has the potential to make great strides in alleviating the barriers to cost effective PTSD assessment and progress monitoring. In this paper we present a voice-based automated Tele-PTSD Monitor (TPM) system currently in development, designed to remotely screen, and provide assistance to clinicians in diagnosing PTSD. The TPM system can be accessed via a Public Switched Telephone Network (PSTN) or the Internet. The acquired voice data is then sent to a secure server to invoke the PTSD Scoring Engine (PTSD-SE) where a PTSD mental health score is computed. If the score exceeds a predefined threshold, the system will notify clinicians (via email or short message service) for confirmation and/or an appropriate follow-up assessment and intervention. The TPM system requires only voice input and performs computer-based automated PTSD scoring, resulting in low cost and easy field-deployment. The concept of the TPM system was supported using a limited dataset with an average detection accuracy of up to 95.88%.

A Deep Learning Approach Considering Image Background for Pneumonia Identification Using Explainable AI (XAI).

Pneumonia mainly refers to lung infections caused by pathogens, such as bacteria and viruses. Currently, deep learning methods have been applied to identify pneumonia. However, the traditional deep learning methods for pneumonia identification take less account of the influence of the lung X-ray image background on the model's testing effect, which limits the improvement of the model's accuracy. In this paper, we propose a deep learning method that considers image background factors and analyzes the proposed method with explainable deep learning for explainability. The essential idea is to remove the image background, improve the pneumonia recognition accuracy, and apply the Grad-CAM method to obtain an explainable deep learning model for pneumonia identification. In the proposed approach, (1) preliminary deep learning models for pneumonia X-ray image identification without considering the background are built; (2) deep learning models for pneumonia X-ray image identification with background consideration are built to improve the accuracy of pneumonia identification; (3) Grad-CAM method is employed to analyze the explainability. The proposed approach improves the accuracy of pneumonia identification, and the highest accuracy of VGG16 reaches 95.6%. The proposed approach can be applied to real pneumonia identification for early detection and treatment.

The effect of TLR-4 on the proliferation and differentiation of bone mesenchymal stem cells and its relationship with the Wnt signal transduction pathway during bone nonunion.

Background: Bone nonunion is a special fracture complication that occurs in about 5% to 10% of cases. This type of fracture is difficult to heal, and causes great pain to patients and affects their quality of life. The mechanism of bone nonunion is not clear. In our study, we investigated the influence of Toll-like receptor (TLR)-3, TLR-4, and Wnt signaling pathways on the occurrence of bone nonunion. Methods: Firstly, we established a Sprague Dawley (SD) rat model of femoral nonunion, and detected the expression levels of TLR-3, TLR-4, ß-catenin, nemo-like kinase (NLK), c-Jun N-terminal kinase (JNK), and other proteins during model construction. For in vitro experiments, primary cultured bone mesenchymal stem cells (BMSCs) were divided into 4 groups: lipopolysaccharide (LPS, agonist of TLR-4) group, LPS + CLI095 (inhibitor of TLR-4) group, control group, and LPS + substance P (SP) group. The expression of ß-catenin, NLK, JNK, and ALP and the osteogenic differentiation ability of cells were detected during culture. Results: X-ray and hematoxylin and eosin (HE) staining results confirmed the successful modeling of bone nonunion. During the formation of the bone nonunion model, the expression of TLR-4 showed an upward trend. In vitro experiment results showed that inhibition of TLR-4 expression could enhance the proliferation and differentiation ability of BMSCs. The expression of ß-catenin, the core protein of the canonical Wnt signaling pathway, increased rapidly in the first 2 weeks of bone nonunion construction, and decreased after 2 weeks. Non-canonical Wnt signaling pathway proteins NLK and JNK had no change in the first 2 weeks, and showed an upward trend after 2 weeks. In vitro experiment results showed that the expression of ß-catenin was dominant in BMSCs with strong proliferation and differentiation ability, while the expression of NLK and JNK was dominant in BMSCs with weak proliferation and differentiation ability. These results suggest that the Wnt signaling pathway may regulate the occurrence of bone nonunion. Conclusions: TLR-4 inhibits the proliferation and differentiation of BMSCs, and the transformation of the canonical Wnt signaling pathway to the non-canonical Wnt signaling pathway may lead to bone nonunion. Our study may provide new insights into the treatment of bone nonunion.

General Paradigm of Edge-Based Internet of Things Data Mining for Geohazard Prevention.

Geological hazards (geohazards) are geological processes or phenomena formed under external-induced factors causing losses to human life and property. Geohazards are sudden, cause great harm, and have broad ranges of influence, which bring considerable challenges to geohazard prevention. Monitoring and early warning are the most common strategies to prevent geohazards. With the development of the internet of things (IoT), IoT-based monitoring devices provide rich and fine data, making geohazard monitoring and early warning more accurate and effective. IoT-based monitoring data can be transmitted to a cloud center for processing to provide credible data references for geohazard early warning. However, the massive numbers of IoT devices occupy most resources of the cloud center, which increases the data processing delay. Moreover, limited bandwidth restricts the transmission of large amounts of geohazard monitoring data. Thus, in some cases, cloud computing is not able to meet the real-time requirements of geohazard early warning. Edge computing technology processes data closer to the data source than to the cloud center, which provides the opportunity for the rapid processing of monitoring data. This article presents the general paradigm of edge-based IoT data mining for geohazard prevention, especially monitoring and early warning. The paradigm mainly includes data acquisition, data mining and analysis, and data interpretation. Moreover, a real case is used to illustrate the details of the presented general paradigm. Finally, this article discusses several key problems for the general paradigm of edge-based IoT data mining for geohazard prevention.

An analytic framework using deep learning for prediction of traffic accident injury severity based on contributing factors.

Vulnerable road users (VRUs) are exposed to the highest risk in the road traffic environment. Analyzing contributing factors that affect injury severity facilitates injury severity prediction and further application in developing countermeasures to guarantee VRUs safety. Recently, machine learning approaches have been introduced, in which analyses tend to be one-sided and may ignore important information. To solve this problem, this paper proposes a comprehensive analytic framework that employs a deep learning model referred to as the stacked sparse autoencoder (SSAE) to predict the injury severity of traffic accidents based on contributing factors. The essential idea of the method is to integrate various analyses into an analytical framework that performs corresponding data processing and analysis by different machine learning approaches. In the proposed method, first, we utilize a machine learning approach (i.e., Catboost) to analyze the importance and dependence of the contributing factors to injury severity and remove low correlation factors; second, according to the geographical information, we classify the data into different classes by utilizing a machine learning approach (i.e., k-means clustering); third, by employing high correlation factors, we employ an SSAE-based deep learning model to perform injury severity prediction in each data class. By experiments with a real-world traffic accident dataset, we demonstrated the effectiveness and applicability of the framework. Specifically, (1) the importance and dependence of contributing factors were obtained by CatBoost and the Shapley value, and (2) the SSAE-based deep learning model achieved the best performance compared to other baseline models. The proposed analytic framework can also be utilized for other accident data for severity or other risk indicator analyses involving VRUs safety.