Due to highway real-time monitoring issues, manual monitoring cannot quickly detect abnormalities. Incorrect detection and costly monitoring make it hard to determine traffic's operating state. Experiments show that the YOLOv3 algorithm has improved. Real-time detection improves accuracy. Improving the deep-sort vehicle feature description can speed up vehicle tracking. The system now detects vehicle speeding and congestion in real-time utilizing an upgraded vehicle object recognition, tracking algorithm, and expressway traffic monitoring picture. First, the highway corporation's monitoring system was inspected. After monitoring highway footage in various places, lighting, weather, and other conditions, a comprehensive vehicle data set was developed. A deep learning model for vehicle target detection is built on this data. Second, the labeling tool divides the data set and labels each sample. YOLOv3's border regression loss function increased with the enhanced vehicle detection algorithm. This was achieved through vehicle target identification algorithm research. Build a model of accurate vehicle detection, test the algorithm model, and use the results of the experimental examination of the various loss functions and training data to improve target identification performance and speed. After discussing target tracking, the real-time multi-target monitoring-based deep-sort algorithm will be explained. Trials assess the improved algorithm. If the detection impact is the same, increasing the tracking speed will improve the anomaly detection system's real-time performance. This is true even without boosting tracking speed. Anomaly detection was developed from vehicle target identification and tracking studies. Debugging and analyzing an abnormal event detection system may automatically recognize the speed and congestion of the video vehicle during abnormal occurrences, such as those in expressway surveillance video. It accurately detects real-time anomalous events. Thus, this technology can better track vehicle traffic and predict and identify emergencies. It also supports timeliness and on-site rescue, ensuring lane traffic flows as planned and improving highway business service.

Roadway irregularities including vehicle failures, traffic accidents, and more may cause traffic bottlenecks. Targeted traffic management and control depend on precise evaluation of uncommon occurrences' influence range and increasing tendency. It enhances roadway service and operation. Expressway abnormal incidence estimation uses traffic flow theory. Traffic parameter detection accuracy cannot satisfy model input, making engineering application difficult. Emulation analysis was utilized to assess highway traffic flow space-time correlation and vehicle detector features, and VISSIM simulation system was used to calibrate traffic flow parameters and rectify driving behavior parameters. The authors developed a Dynamic-Data-Driven Application Systems (DDDAS)-based highway exceptional event impact area emulation analysis approach after a particle filtering investigation. Features: Traffic and driving simulation model calibration. Freeway traffic flow, analysis, and vehicle inspection data calibrated traffic flow simulation model parameters. The simulation model driving behavior parameter calibration default value is incorrect, hence weak single factor sensitivity analysis was employed to determine the core adjustment parameters. Study genetic algorithm simulation model driving behavior parameter modification. Finally, car inspection data confirmed the model. The model accurately simulates road traffic. ② Particle filter-based traffic simulation model data assimilation analysis. Traffic wave and threshold theory preprocess highway vehicle inspection data. The DDDAS-based traffic simulation analysis system uses particle filter data assimilation. Show the method using numbers. The particle filter-based traffic simulation model can continuously absorb real-time data to correctly predict event blocking road places and queue lengths. The paper concludes by detailing the traffic simulation model. Combining Beibei tunnel section vehicle detector data of G75 highway, we choose typical and actual traffic exceptional events to build similar simulation scene, verifying the DDDAS-based highway exceptional event impact area emulation analysis method.

*Note: Mol2Net conference is associated to different MDPI journals special issues guest edited by Mol2Net Conference Committee members. This is an strategy to increase the online post-publication visibility of papers and conference, promote post-publication brainstorming discussion, and increase authors feedback. This association implies that our conference perform post-publication indexing of selected papers already published in MDPI journals with the consent of the issue editors. We publish free-of-cost these post-publication summaries. They include a shortened title, corresponding author info, and paper cover pdf file. The cover pdf file contains paper first page with all authors, abstract, full reference , and link to original papers.

Reference: This is a summary for the paper published in the special issue Cardiovascular Disease, Atherosclerosis and Familial Hypercholesterolemia: From Molecular Mechanisms Causing Pathogenicity till New Therapeutic Approaches 2.0. Edited by: Prof. Cesar Martín Plagaro and Dr. Asier Benito-Vicente. Visit the link to see original paper. Reference: Int. J. Mol. Sci. 2022, 23(6), 3346; https://doi.org/10.3390/ijms23063346

Abstract: Atherosclerosis is the main risk factor for cardiovascular disease (CVD), which is the leading cause of mortality worldwide. Atherosclerosis is initiated by endothelium activation and, followed by a cascade of events (accumulation of lipids, fibrous elements, and calcification), triggers the vessel narrowing and activation of inflammatory pathways. The resultant atheroma plaque, along with these processes, results in cardiovascular complications. This review focuses on the different stages of atherosclerosis development, ranging from endothelial dysfunction to plaque rupture. In addition, the post-transcriptional regulation and modulation of atheroma plaque by microRNAs and lncRNAs, the role of microbiota, and the importance of sex as a crucial risk factor in atherosclerosis are covered here in order to provide a global view of the disease.

Bisphenol A (BPA) is regarded as an endocrine disrupting compound (EDC) because of its harmful effects on endocrine system of humans. BPA is releasing to the environment by the way of industrial processes such as epoxy resin and polycarbonate plastic production ^[1]. BPA contained materials are optical and electronic devices, reusable plastic bottles, containers, dishes, cups and bowls which can be used for food protection and put. Besides that, metal food cans also include BPA because they have epoxy resin film ^[2]. Photocatalytic adsorption can be thought as the most energy-saving and economical way to degrade pollutants from water. So, for this purpose the researchers have studied on novel materials which have high removal efficiency. Metal organic Frameworks (MOFs) are important materials which have several features like high surface area, high crystallinity, regular pre structure and adaptable with polymers. As a type of MOFs, ZIF-8 has a skeleton which is composed of 2-methyl imidazole ligand and Zn atoms. ZIF-8 can be synthesized by using so many feasible synthesis methods. Besides that, it has thermal stability up to 500 °C. And, it can keep its skeleton in several organic solvents and water [3]. To the best of the author’s knowledge, there are extremely low papers in literature for BPA removal from water with ZIF-8 photocatalyst. And the topic is new in literature. So, the aim of this study is actually drawing attention to this topic. Shao et al. (2020) were synthesized ZIF-8 on N-K₂Ti₄O₉ surface in methanol environment. They found that this composite had 9 times higher photocatalytic activity than pristine N-K₂Ti₄O₉ for BPA removal under visible light [4]. Zheng et al. (2021) were synthesized a complex photocatalyst by doping ZIF-8 and AgBr on the surface of protonated graphitic carbon nitride (g-C₃N₄). They conducted the experiments at room temperature during 2 hours under xenon light. The results which are obtained by the researchers were the composite including ZIF-8 was stable and good ability to remove BPA (up to 70%) even after four experiments [5].

References

[1] Huang, Z., Yu, H., Wang, L., Wang, M., Liu, X., Shen, D., & Lei, S., Separation and Purification Technology, 2023, 305. 122402

[2] Almeida, S., Raposo, A., Almeida‐González, M., & Carrascosa, C., Comprehensive Reviews in Food Science and Food Safety, 2018, 17(6). 1503-1517.

[3] Dai, H., Yuan, X., Jiang, L., Wang, H., Zhang, J., Zhang, J., & Xiong, T., Coordination Chemistry Reviews, 2021, 441, 213985.

[4] Shao, C., Feng, S., Zhu, G., Zheng, W., Sun, J., Huang, X., & Ni, Z., Materials Letters, 2020, 268, 127334.

[5] Zheng, W., Feng, S., Feng, S., Shao, C., Jiang, Z., Wu, W., & Meng, Q., Research on Chemical Intermediates, 2021, 47(4), 1471-1487.

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*Note: Mol2Net conference is associated to different MDPI journals special issues guest edited by Mol2Net Conference Committee members. This is an strategy to increase the online post-publication visibility of papers and conference, promote post-publication brainstorming discussion, and increase authors feedback. This association implies that our conference perform post-publication indexing of selected papers already published in MDPI journals with the consent of the issue editors. We publish free-of-cost these post-publication summaries. They include a shortened title, corresponding author info, and paper cover pdf file. The cover pdf file contains paper first page with all authors, abstract, full reference , and link to original papers.

This is a cover for the paper published in the special issue Cardiovascular Disease, Atherosclerosis and Familial Hypercholesterolemia: From Molecular Mechanisms Causing Pathogenicity till New Therapeutic Approaches 2.0. Edited by: Prof. Cesar Martín Plagaro and Dr. Asier Benito-Vicente. Visit the link to see original paper. Reference: Int. J. Mol. Sci. 2022, 23(17), 9553; https://doi.org/10.3390/ijms23179553

Abstract: Atherosclerosis, the underlying cause of coronary artery disease (CAD), has a significant inflammatory component. White blood cell count is an affordable and accessible way to assess the systemic immune response, as it comprises many subgroups with distinct and complex functions. Considering their multidirectional effect on atherosclerosis, new biomarkers integrating various leukocyte subgroups, the Systemic Inflammatory Index (SII) and the Systemic Inflammatory Response Index (SIRI), were recently devised to describe the balance between inflammation and immune reaction. This research aimed to evaluate the relationship of the intensity of inflammation measured by these biomarkers with the severity of CAD assessed with coronary angiography and with the diagnosis of acute coronary syndrome (ACS) or stable CAD in 699 patients. SIRI, but not SII, was associated with the diagnosis, having the highest values for patients with ACS (STEMI), significantly higher than in patients with stable CAD (p < 0.01). The highest SII and SIRI values were observed in patients with three-vessel CAD. SII and SIRI require further in-depth and well-designed research to evaluate their potential in a clinical setting.

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The fast growth in the population density in urban areas demands more facilities and resources. To meet the needs of city development, the use of Internet of Things (IoT) devices and the smart systems is the very quick and valuable source. However, thousands of IoT devices are interconnecting and communicating with each other over the Internet results in generating a huge amount of data, termed as Big Data. To integrate IoT services and processing Big Data in an efficient way aimed at smart city is a challenging task. Therefore, in this paper, we proposed a system for smart city development based on IoT using Big Data Analytics. We use sensors deployment including smart home sensors, vehicular networking, weather and water sensors, smart parking sensor, and surveillance objects, etc. initially a four-tier architecture is proposed, which includes 1) Bottom Tier: which is responsible for IoT sources, data generations, and collections 2) Intermediate Tier-1: That is responsible for all type of communication between sensors, relays, base stations, the internet, etc. 3) Intermediate Tier 2: it is responsible for data management and processing using Hadoop framework, and 4) Top tier: is responsible for application and usage of the data analysis and results generated. The collected data from all smart system is processed at real-time to achieve smart cities using Hadoop with Spark, VoltDB, Storm or S4. We use existing datasets by various researchers including smart homes, smart parking weather, pollution, and vehicle for analysis and testing. All the datasets are replayed to test the real-time efficiency of the system. Finally, we evaluated the system by efficiency in term of throughput and processing time.

Internet of Things,Big Data, Smart Systems, Smart City and Hadoop.

Temperature changes affect all physiological processes, such as modification of membrane fluidity and local transitions of the lipid bilayer, which can affect membrane integrity and permeability, as well as the mobility and function of membrane receptors.

This research studies the effect of temperature variations and Cd/Ca interaction, on the growth of Paramecium sp. The concentrations of Cadmium Chloride were used (0.5, 1, and 10 µM) in addition to two concentrations of Calcium Chloride (20 µM and 2 mM). Paramecia were acclimated at 28° (the optimal temperature) and at 16° (low temperature).

The results show that temperature variations affect the growth of paramecia by slowing down their multiplication and affecting the absorption and bioaccumulation of the toxic metals present.

At the same time, the presence of calcium in high concentrations strongly reduces the observed effects of cadmium.