Quantification System Research Articles

Strengthen the sacral ligament and paravagina by equilibrium control severe pelvic organ prolapse.

To evaluate and analyze the clinical effect of the combination of laparoscopic sacrocolpopexy (LSC), sacral ligament fusion and vaginal suspension in the treatment of severe pelvic organ prolapse. A total of 76 cases of patients with pelvic organ prolapse in our hospital between January 2010 to December 2020 were enrolled for research. They had been evaluated pre- and post-operative through pelvic organ prolapse quantification (POP-Q) system, Pelvic Floor Dysfunction Questionnaire Short Form (PFDI-20), Pelvic Floor Function Impact Questionnaire Short form (PFIQ-7), and the Sexual Function Questionnaire Score (PIQS-31). All 76 patients went through the procedure successfully without any complications. None of the 76 cases had relapsed. Post-operational results of PFDI-20 and PFIQ-7 were evidently lower than pre-operational results, post-operational results of PIQS-31 were higher than before operation. For patients with severe pelvic organ prolapse,a balanced control of the pelvic floor centred on the preservation of the stereoscopic ring around the cervix through revascularization is significantly effective, and has no recurrence after surgery, high patient satisfaction, fewer postoperative complications. It is safe and reliable and worthy of clinical application and promotion.

An Optimized CoBRA Method for the Microfluidic Electrophoresis Detection of Breast Cancer Associated RASSF1 Methylation.

Although breast cancer screening assays exist, many are inaccessible and have high turnaround times, leaving a significant need for better alternatives. Hypermethylation of tumor suppressor genes is a common epigenetic marker of breast cancer. Methylation tends to occur most frequently in the promoter and first exon regions of genes. Preliminary screening tests are crucial for informing patients whether they should pursue more involved testing. We selected RASSF1, previously demonstrated to be aberrantly methylated in liquid biopsies from breast cancer patients, as our gene of interest. Using CoBRA as our method for methylation quantification, we designed unique primer sets that amplify a portion of the CpG island spanning the 5' end of the RASSF1 first exon. We integrated the CoBRA approach with a microfluidics-based electrophoresis quantification system (LabChip) and optimized the assay such that insightful results could be obtained without post-PCR purification or concentration, two steps traditionally included in CoBRA assays. Circumventing these steps resulted in a decreased turnaround time and mitigated the laboratory machinery and reagent requirements. Our streamlined technique has an estimated limit of detection of 9.1 ng/μL of input DNA and was able to quantify methylation with an average error of 4.3%.

Direct evaluation of neuroaxonal degeneration with the causative genes of neurodegenerative diseases in Drosophila using the automated axon quantification system, MeDUsA.

Drosophila is an excellent model organism for studying human neurodegenerative diseases (NDs). However, there is still almost no experimental system that could directly observe the degeneration of neurons and automatically quantify axonal degeneration. In this study, we created MeDUsA (a 'method for the quantification of degeneration using fly axons'), a standalone executable computer program based on Python that combines a pre-trained deep-learning masking tool with an axon terminal counting tool. This software automatically quantifies the number of retinal R7 axons in Drosophila from a confocal z-stack image series. Using this software, we were able to directly demonstrate that axons were degenerated by the representative causative genes of NDs for the first time in Drosophila. The fly retinal axon is an excellent experimental system that is capable of mimicking the pathology of axonal degeneration in human NDs. MeDUsA rapidly and accurately quantifies axons in Drosophila photoreceptor neurons. It enables large-scale research into axonal degeneration, including screening to identify genes or drugs that mediate axonal toxicity caused by ND proteins and diagnose the pathological significance of novel variants of human genes in axons.

Characterization of the number of spot samples required for quantification of gas fluxes and metabolic heat production from grazing beef cows using a GreenFeed.

Enteric fermentation from cattle results in greenhouse gas production that is an environmental concern and also an energetic loss. Several methods exist to quantify gas fluxes; however, an open circuit gas quantification system (OCGQS) allows for unencumbered quantification of methane (CH4), carbon dioxide (CO2), and oxygen (O2) from grazing cattle. While previous literature has proven the accuracy of an OCGQS, little work has been done to establish the minimum number of spot samples required to best evaluate an individual grazing animal's gas fluxes and metabolic heat production. A GreenFeed system (C-Lock Inc.) was used to collect at least 100 spot samples each from 17 grazing cows. The mean gas fluxes and metabolic heat production were computed starting from the first 10 visits (forward) and increasing by increments of 10 until an animal had 100 visits. Mean gas fluxes and metabolic heat production were also computed starting from visit 100 (reverse) in increments of 10 using the same approach. Pearson and Spearman correlations were computed between the full 100 visits and each shortened visit interval. A large increase in correlations were seen between 30 and 40 visits. Thus, mean forward and reverse gas fluxes and metabolic heat production were also computed starting at 30 visits and increasing by 2 until 40 visits. The minimum number of spot samples was determined when correlations with the full 100 visits were greater than 0.95. The results indicated that the minimum numbers of spot samples needed for accurate quantification of CH4, CO2, and O2 gas fluxes are 38, 40, and 40, respectively. Metabolic heat production can be calculated using gas fluxes collected by the OCGQS with 36 spot samples. Practically, calculation of metabolic heat production will require 40 spot samples because the component gases for metabolic heat calculation require up to 40 spot samples. Published literature from nongrazing (confined) environments recommended a similar number of total spot samples. Large variation existed around the average number of spot samples for an animal per day, therefore a wide range of test durations may be needed to meet the same number of spot samples in different populations. For this reason, protocols for the OCGQS should be based on the total number of spot samples, rather than a test duration.

Construction of a new extracellular vesicles isolation method and its quantification system

Construction of a new extracellular vesicles isolation method and its quantification system

Plasma Levels of Transforming Growth Factor-Beta 1 in Women with Pelvic Organ Prolapse

Objective: In women with pelvic organ prolapse (POP), decreased expression of transforming growth factor-beta 1 (TGF-β1) has been shown in POP tissues. However, no studies have evaluated plasma TGF-β1 levels in patients with POP, so it is unknown whether they are also changed or not. Therefore, we compared plasma TGF-β1 levels in women with and without POP. Methods: Participants were 49 women with POP and 23 healthy control women. All participants were postmenopausal. We measured plasma TGF-β1 and compared data between patients with POP and controls, and between patients with uterine prolapse (UP, n = 19) and those with a cystocele (CC, n = 30). In addition, in patients, we assessed the POP quantification system (POP-Q) stage. Results: Plasma TGF-β1 levels were significantly lower in patients than in healthy controls. POP-Q stage was not significantly different between the UP and CC subgroups, but POP-Q stage IV was diagnosed in 63% of patients with UP and 7% of those with CC. Plasma TGF-β1 levels were significantly lower in the CC subgroup than in the UP subgroup. Conclusion: Plasma TGF-β1 is decreased in POP. It remains unclear whether the lower levels indicate a reduction in systemic TGF-β1 activity, but they can be assumed to reflect reduced TGF-β1 expression in POP tissues.

Optimal credit strategy for MSMEs

We address two main issues: one is to quantify the credit risk of enterprises and establish a complete credit risk system, and the other is to give the optimal credit risk strategy for banks. We first analyze and pre-process the data. From the data, we extracted a series of indicators such as the total amount of input and output, and the length of operation. We analyze the credit risk in three directions: strength, stability of supply and demand, and creditworthiness, and establish a credit risk quantification system for the enterprise. Then we quantify the credit risk of the enterprise by entropy method and TOPSIS. Second, a function is fitted to the bank’s customer churn rate and the bank’s lending rate. Using a planning-type model, the credit decisions of the firms are required to be given. We follow the principle of maximizing benefits and minimizing risks to build a multi-objective planning model. We base on the scores of each firm that have been solved, for the classification of firms, and follow the principle of low credit risk, low lending rate, and set the corresponding lending rate for each type of firm. The model is solved by the through-order solution method, and the linear weighting method is used to test the comparison. The credit decision for each enterprise is given.

High enrichment and near real-time quantification of airborne viruses using a wet-paper-based electrochemical immunosensor under an electrostatic field.

Conventional airborne virus measurement usually requires appreciable sampling and detection times. Viral aerosols should also be collected or prepared in a liquid medium whose volume typically ranges from milliliters to tens of milliliters; hence, many sampling and detection steps need to be taken with the unit horizontal or immobile. Moreover, viral aerosols need to be sufficiently enriched, which makes real-time monitoring difficult. Herein, we present a near real-time enrichment and quantification system of airborne viruses that consists of a wet-paper-based electrochemical immunosensor with a gel electrolyte and a modified electrostatic particle concentrator. A small amount of phosphate-buffered saline flowed on the electrode, which resulted in sensor electrodes that are barely wet (covered in a thin buffer film measuring several micrometers) to ensure antigen-antibody interaction and the removal of non-target particles on the electrode surface. This system ensures that airborne viruses are highly enriched on the working electrode of the immunosensor, and it is possible to measure the MS2 virus particle concentrations every 10min for 60min stably and selectively against non-target airborne viruses and bacteria at horizontal and tilted measurement configurations. This system thus has the potential to be used in the real-time mobile monitoring of airborne microorganisms.

ЗАСТОСУВАННЯ ПЛАЗМОНІКИ ДЛЯ АНАЛІЗУ ПОЛІДИСПЕРСНИХ СИСТЕМ (ОГЛЯД)

Modern sensor technologies have advantages compared to other classical methods of analysis of liquid and gas environments, in particular, fast analysis and a small volume of the analyzed sample, high sensitivity, the ability to detect the analyzed substance in a polydisperse environment due to the specificity of the sensor. Plasmonics is one of the leading scientific directions, which is actively used in sensor technologies for the development of highly sensitive analytical devices and systems. Precision analytical devices based on SPR are used for research in the food, chemical, pharmaceutical industry, agriculture, medicine, and ecology. However, the interpretation of the measurement result is somewhat complicated when analyzing complex polydisperse systems and the presence of an interferent in the sample, which affects the value of the sensor signal. Therefore, there is a need to study, in particular, liquid polydisperse systems using models of approximate environments and using additional technologies to increase the specificity of the analyzed component by using receptor surfaces. The review provides information on the current state of polydisperse systems research using the example of milk - one of the most common food products. Sensitive, fast and efficient quantification and monitoring systems play a key role in the determination of harmful impurities in dairy products. The need to detect antibiotics with a minimum concentration in food products, in particular in dairy raw materials, which are complex polydisperse systems, is an important scientific problem. Such requirements give rise to the need to develop reliable, highly sensitive analytical methods. In addition, there is a huge demand for rapid analytical devices to detect antibiotic residues in milk samples on the farm before the raw material is sent to the factory, because after sending directly to the factory, in case of antibiotic detection, a large batch of milk is missing, which leads to excessive costs.

Indoor Spatiotemporal Contact Analytics Using Landmark-Aided Pedestrian Dead Reckoning on Smartphones.

Due to the prevalence of COVID-19, providing safe environments and reducing the risks of virus exposure play pivotal roles in our daily lives. Contact tracing is a well-established and widely-used approach to track and suppress the spread of viruses. Most digital contact tracing systems can detect direct face-to-face contact based on estimated proximity, without quantifying the exposed virus concentration. In particular, they rarely allow for quantitative analysis of indirect environmental exposure due to virus survival time in the air and constant airborne transmission. In this work, we propose an indoor spatiotemporal contact awareness framework (iSTCA), which explicitly considers the self-containing quantitative contact analytics approach with spatiotemporal information to provide accurate awareness of the virus quanta concentration in different origins at various times. Smartphone-based pedestrian dead reckoning (PDR) is employed to precisely detect the locations and trajectories for distance estimation and time assessment without the need to deploy extra infrastructure. The PDR technique we employ calibrates the accumulative error by identifying spatial landmarks automatically. We utilized a custom deep learning model composed of bidirectional long short-term memory (Bi-LSTM) and multi-head convolutional neural networks (CNNs) for extracting the local correlation and long-term dependency to recognize landmarks. By considering the spatial distance and time difference in an integrated manner, we can quantify the virus quanta concentration of the entire indoor environment at any time with all contributed virus particles. We conducted an extensive experiment based on practical scenarios to evaluate the performance of the proposed system, showing that the average positioning error is reduced to less than 0.7 m with high confidence and demonstrating the validity of our system for the virus quanta concentration quantification involving virus movement in a complex indoor environment.

Handheld diffuse reflectance spectroscopy system for noninvasive quantification of neonatal bilirubin and hemoglobin concentrations: a pilot study.

The prevalence rate of neonatal jaundice can reach 80%, of which 5% may develop dangerous hemolytic jaundice. The blood test for obtaining bilirubin and hemoglobin concentration is the gold standard for diagnosing hemolytic jaundice; however, frequently drawing blood from jaundice neonates for the screening purpose is not practical. We have developed a handheld diffuse reflectance spectroscopy system to noninvasively determine the bilirubin and hemoglobin levels in neonates. Our study showed that the correlation coefficients were 0.95 and 0.80 for bilirubin and hemoglobin between the results from the blood tests and our handheld system, respectively. This handheld system could be an effective tool for screening hemolytic jaundice.

Information in Streetscapes—Research on Visual Perception Information Quantity of Street Space Based on Information Entropy and Machine Learning

Urban street space is a critical reflection of a city’s vitality and image and a critical component of urban planning. While visual perceptual information about an urban street space can reflect the composition of place elements and spatial relationships, it lacks a unified and comprehensive quantification system. It is frequently presented in the form of element proportions without accounting for realistic factors, such as occlusion, light and shadow, and materials, making it difficult for the data to accurately describe the complex information found in real scenes. The conclusions of related studies are insufficiently focused to serve as a guide for designing solutions, remaining merely theoretical paradigms. As such, this study employed semantic segmentation and information entropy models to generate four visual perceptual information quantity (VPIQ) measures of street space: (1) form; (2) line; (3) texture; and (4) color. Then, at the macro level, the streetscape coefficient of variation (SCV) and K-means cluster entropy (HCK) were proposed to quantify the street’s spatial variation characteristics based on VPIQ. Additionally, we used geographically weighted regression (GWR) to investigate the relationship between VPIQ and street elements at the meso level as well as its practical application. This method can accurately and objectively describe and detect the current state of street spaces, assisting urban planners and decision-makers in making decisions about planning policies, urban regeneration schemes, and how to manage the street environment.

Automating Hair Loss Labels for Universally Scoring Alopecia From Images

Clinical estimation of hair density has an important role in assessing and tracking the severity and progression of alopecia, yet to the authors' knowledge, no automation currently exists for this process. While some algorithms have been developed to assess alopecia presence on a binary level, their scope has been limited by focusing on a re-creation of the Severity of Alopecia Tool (SALT) score for alopecia areata (AA). Yet hair density loss is common to all alopecia forms, and an evaluation of that loss is used in established scoring systems for androgenetic alopecia (AGA), central centrifugal cicatricial alopecia (CCCA), and many more. To develop and validate a new model, HairComb, to automatically compute the percentage hair loss from images regardless of alopecia subtype. In this research study to create a new algorithmic quantification system for all hair loss, computational imaging analysis and algorithm design using retrospective image data collection were performed. This was a multicenter study, where images were collected at the Children's Hospital of Philadelphia, University of Pennsylvania (Penn), and via a Penn Dermatology web interface. Images were collected from 2015 to 2021, and they were analyzed from 2019 to 2021. Scoring systems correlation analysis was measured by linear and logarithmic regressions. Algorithm performance was evaluated using image segmentation accuracy, density probability regression error, and average percentage hair loss error for labeled images, and Pearson correlation for manual scores. There were 404 participants aged 2 years and older that were used for designing and validating HairComb. Scoring systems correlation analysis was performed for 250 participants (70.4% female; mean age, 35.3 years): 75 AGA, 66 AA, 50 CCCA, 27 other alopecia diagnoses (frontal fibrosing alopecia, lichen planopilaris, telogen effluvium, etc), and 32 unaffected scalps without alopecia. Scoring systems showed strong correlations with underlying percentage hair loss, with coefficient of determination R2 values of 0.793 and 0.804 with respect to log of percentage hair loss. Using HairComb, 92% accuracy, 5% regression error, 7% hair loss difference, and predicted scores with errors comparable to annotators were achieved. In this research study,it is shown that an algorithm quantitating percentage hair loss may be applied to all forms of alopecia. A generalizable automated assessment of hair loss would provide a way to standardize measurements of hair loss across a range of conditions.

Comprehensive Analysis of Organic Micropollutants in Fine Particulate Matter in Hanoi Metropolitan Area, Vietnam

Rapid urbanization has led to increased environmental pollution in Vietnam, especially air pollution issues. In this study, we used gas chromatography-mass spectrometry with an automated identification and quantification system database to detect and quantitate compounds in atmospheric fine particulate matter (PM2.5). A total of 288 compounds classified in 19 pollutant categories based on their origins were detected in PM2.5 samples collected in three areas of Hanoi during winter. The total content of substances detected ranged from 41.08 to 795.00 ng.m−3. The characteristics and concentrations of organic pollutants differed among the industrial, urban, and agricultural sampling areas, with average concentrations of 179.00, 112.10, and 529.40 ng.m−3, respectively. In this comprehensive study on trace organic compounds conducted with samples collected at three sites, we investigating the basic impact of three main factors on the environment. This study contributes to the literature by providing a data set on the content of trace organic substances in the air at the study site.

Investigation of Thresholds for Asymmetry Indices to Represent the Visual Assessment of Single Limb Lameness by Expert Veterinarians on Horses Trotting in a Straight Line.

Defining whether a gait asymmetry should be considered as lameness is challenging. Gait analysis systems now provide relatively accurate objective data, but their interpretation remains complex. Thresholds for discriminating between horses that are visually assessed as being lame or sound, as well as thresholds for locating the lame limb with precise sensitivity and specificity are essential for accurate interpretation of asymmetry measures. The goal of this study was to establish the thresholds of asymmetry indices having the best sensitivity and specificity to represent the visual single-limb lameness assessment made by expert veterinarians as part of their routine practice. Horses included in this study were evaluated for locomotor disorders at a clinic and equipped with the EQUISYM® system using inertial measurement unit (IMU) sensors. Visual evaluation by expert clinicians allocated horses into five groups: 49 sound, 62 left forelimb lame, 67 right forelimb lame, 23 left hindlimb lame, and 23 right hindlimb lame horses. 1/10 grade lame horses were excluded. Sensors placed on the head (_H), the withers (_W), and the pelvis (_P) provided vertical displacement. Relative difference of minimal (AI-min) and maximal (AI-max) altitudes, and of upward (AI-up) and downward (AI-down) amplitudes between right and left stance phases were calculated. Receiver operating characteristic (ROC) curves discriminating the sound horses from each lame limb group revealed the threshold of asymmetry indice associated with the best sensitivity and specificity. AI-up_W had the best ability to discriminate forelimb lame horses from sound horses with thresholds (left: -7%; right: +10%) whose sensitivity was greater than 84% and specificity greater than 88%. AI-up_P and AI-max_P discriminated hindlimb lame horses from sound horses with thresholds (left: -7%; right: +18% and left: -10%; right: +6%) whose sensitivity was greater than 78%, and specificity greater than 82%. Identified thresholds will enable the interpretation of quantitative data from lameness quantification systems. This study is mainly limited by the number of included horses and deserves further investigation with additional data, and similar studies on circles are warranted.

A Novel Craniocervical Junction Compression Severity Index-Based Grading System for Multidirectional Quantification of the Biomechanics at Foramen Magnum of Chiari Malformation Type I.

Objective This study aimed to establish a novel grading system, based on the craniovertebral junction compression severity index (CVJCSI) for multidirectional quantification at the foramen magnum plane for Chiari malformation type I (CMI). Methods The CVJCSI grading system was established to stratify patients based on the ventral (modified clivoaxial angle < 138°), dorsal (tonsil herniation), and central (brainstem herniation) CVJ (craniovertebral junction) compression, the CVJCSI grading system was established to stratify patients. The optimal surgical method for each grade was recommended by intragroup comparisons regarding the efficacy of the three operations. Finally, according to the CVJCSI grading system, a prospective validation trial was performed and surgically treated for internal validation. Results Based on the retrospective study ( n = 310), the CVJCSI included six grades: I: syrinx alone without compression; II: dorsal compression; III: dorsal and central compression; IV: ventral compression; V: dorsal and ventral compression; and VI: ventral, dorsal, and central compression. Among all available variables, only the CVJCSI and surgical methods significantly affected the CCOS. The CCOS scores, overall and for each CVJCSI grade, increased in the prospective cohort ( n = 42) compared with that in the retrospective analysis. Conclusions The CVJCSI can be used to stratify CMI patients. The higher the CVJCSI grade, the more severe the CVJ compression and the worse posterior fossa deformity. Meanwhile, the CVJCSI was negatively correlated with the CCOS. The lower the CVJCSI grade, the better the response to surgery, and the less-invasive surgical procedures were warranted. Finally, the prospective cohort study validated the proposed CVJCSI-based surgical protocols.

Quantification of DNA methylation for carcinogenic risk estimation in patients with non-alcoholic steatohepatitis

BackgroundIn recent years, non-alcoholic steatohepatitis (NASH) has become the main cause of hepatocellular carcinoma (HCC). As a means of improving the treatment of NASH-related HCCs based on early detection, this study investigated the feasibility of carcinogenic risk estimation in patients with NASH.ResultsNormal liver tissue (NLT), non-cancerous liver tissue showing histological findings compatible with non-alcoholic fatty liver from patients without HCC (NAFL-O), non-cancerous liver tissue showing NASH from patients without HCC (NASH-O), non-cancerous liver tissue showing non-alcoholic fatty liver from patients with HCC (NAFL-W), non-cancerous liver tissue showing NASH from patients with HCC (NASH-W) and NASH-related HCC were analyzed. An initial cohort of 171 tissue samples and a validation cohort of 55 tissue samples were used. Genome-wide DNA methylation screening using the Infinium HumanMethylation450 BeadChip and DNA methylation quantification using high-performance liquid chromatography (HPLC) with a newly developed anion-exchange column were performed. Based on the Infinium assay, 4050 CpG sites showed alterations of DNA methylation in NASH-W samples relative to NLT samples. Such alterations at the precancerous NASH stage were inherited by or strengthened in HCC samples. Receiver operating characteristic curve analysis identified 415 CpG sites discriminating NASH-W from NLT samples with area under the curve values of more than 0.95. Among them, we focused on 21 CpG sites showing more than 85% specificity, even for discrimination of NASH-W from NASH-O samples. The DNA methylation status of these 21 CpG sites was able to predict the coincidence of HCC independently from histopathological findings such as ballooning and fibrosis stage. The methylation status of 5 candidate marker CpG sites was assessed using a HPLC-based system, and for 3 of them sufficient sensitivity and specificity were successfully validated in the validation cohort. By combining these 3 CpG sites including the ZC3H3 gene, NAFL-W and NASH-W samples from which HCCs had already arisen were confirmed to show carcinogenic risk with 95% sensitivity in the validation cohort.ConclusionsAfter a further prospective validation study using a larger cohort, carcinogenic risk estimation in liver biopsy specimens of patients with NASH may become clinically applicable using this HPLC-based system for quantification of DNA methylation.

Identification of genes regulating stimulus-dependent synaptic assembly in Drosophila using an automated synapse quantification system.

Neural activity-dependent synaptic plasticity is an important physiological phenomenon underlying environmental adaptation, memory and learning. However, its molecular basis, especially in presynaptic neurons, is not well understood. Previous studies have shown that the number of presynaptic active zones in the Drosophila melanogaster photoreceptor R8 is reversibly changed in an activity-dependent manner. During reversible synaptic changes, both synaptic disassembly and assembly processes were observed. Although we have established a paradigm for screening molecules involved in synaptic stability and several genes have been identified, genes involved in stimulus-dependent synaptic assembly are still elusive. Therefore, the aim of this study was to identify genes regulating stimulus-dependent synaptic assembly in Drosophila using an automated synapse quantification system. To this end, we performed RNAi screening against 300 memory-defective, synapse-related or transmembrane molecules in photoreceptor R8 neurons. Candidate genes were narrowed down to 27 genes in the first screen using presynaptic protein aggregation as a sign of synaptic disassembly. In the second screen, we directly quantified the decreasing synapse number using a GFP-tagged presynaptic protein marker. We utilized custom-made image analysis software, which automatically locates synapses and counts their number along individual R8 axons, and identified cirl as a candidate gene responsible for synaptic assembly. Finally, we present a new model of stimulus-dependent synaptic assembly through the interaction of cirl and its possible ligand, ten-a. This study demonstrates the feasibility of using the automated synapse quantification system to explore activity-dependent synaptic plasticity in Drosophila R8 photoreceptors in order to identify molecules involved in stimulus-dependent synaptic assembly.

Automated quantification system for vision through polymer‐dispersed liquid crystal double‐glazed windows: Circuit implementation

Automated quantification system for vision through polymer‐dispersed liquid crystal double‐glazed windows: Circuit implementation

V-FloodNet: A video segmentation system for urban flood detection and quantification

Effective monitoring and forecasting of urban flooding are crucial for climate change adaptation and resilience around the world. We proposed a novel and automatic system for urban flood detection and quantification. Our software takes image/video data of flooding as inputs because the such data source is easy to obtain and widely available compared with conventional water level sensors or flood gauges. First, the kernel of our system is a robust water region segmentation module that detects flooded regions together with surrounding reference objects from the scene. We combine image and video segmentation technologies to make the system reliable under varying weather and illumination conditions. Second, our system uses the detected situated objects to determine the inundation depth. Field experiments demonstrate that our segmentation results are accurate and reliable; and our system can detect flooding and estimate inundation depths from images and time-lapse videos. Our code is available at https://github.com/xmlyqing00/V-FloodNet.