Local Monitoring Research Articles

A novel Q-learning-based secure routing scheme with a robust defensive system against wormhole attacks in flying ad hoc networks

Nowadays, unmanned aerial vehicles (UAVs) organized in a flying ad hoc network (FANET) can successfully carry out complex missions. Due to the limitations of these networks, including the lack of infrastructure, wireless communication channels, dynamic topology, and unreliable communication between UAVs, cyberattacks, especially wormholes, weaken the performance of routing schemes. Therefore, maintaining communication security and guaranteeing the quality of service (QoS) are very challenging. In this paper, a novel Q-learning-based secure routing scheme (QSR) is presented for FANETs. QSR seeks to provide a robust defensive system against wormhole attacks, especially wormhole through encapsulation and wormhole through packet relay. QSR includes a secure neighbor discovery process and a Q-learning-based secure routing process. Firstly, each UAV gets information about its neighboring UAVs securely. To secure communication in this process, a local monitoring system is designed to counteract the wormhole attack through packet relay. This system checks data packets exchanged between neighboring UAVs and defines three rules according to the behavior of wormholes. In the second process, UAVs perform a distributed Q-learning-based routing process to counteract the wormhole attack through encapsulation. To reward the safest paths, a reward function is introduced based on five factors, the average one-hop delay, hop count, data loss ratio, packet transmission frequency (PTF), and packet reception frequency (PRF). Finally, the NS2 simulator is applied for implementing QSR and executing different scenarios. The evaluation results show that QSR works better than TOPCM, MNRiRIP, and MNDA in terms of accuracy, malicious node detection rate, data delivery ratio, and data loss ratio. However, it has more delay than TOPCM.

Antimicrobial resistance trends among Klebsiella pneumoniae associated with urinary tract infections in Crete, Greece, 2017-2022.

Klebsiella pneumoniae is one of the most prevalent bacteria causing urinary tract infections (UTIs). Its increasing resistance to a wide array of antibiotics limits available treatment options. This study investigated the characteristics and trends of antimicrobial resistance in K. pneumoniae isolated from UTIs in Crete, Greece, during 2017 and 2022. Among the 11,946 Enterobacteriaceae isolated from urine specimens, a total of 1,771 K. pneumoniae isolates were identified (14.8%), with an isolation frequency secondary to Escherichia coli (66.3%). K. pneumoniae isolates increased over the years, with a peak in the year 2022. Higher resistance rates were detected in ciprofloxacin (41%), trimethoprim/sulfamethoxazole (TMP/SMX) (38.1%) and nitrofurantoin (33.9%). Resistance to ciprofloxacin, amoxicillin/clavulanic acid, tigecycline, and TMP/SMX significantly increased from 33.7%, 24%, 6%, and 33.1%, respectively, over the years 2017-2019, to 47.8%, 34.2%, 14.3% and 42.8%, respectively, over the period 2020-2022. ESBL production and carbapenem resistance were decreased by 2.2% and 3.7%, respectively, over the two three-year periods (2017-2019 and 2020-2022). Among the 278 carbapenem-resistant K.pneumoniae (CRKP) isolates, 164 (59%), 66 (23.7%), 18 (6.5%) and 16 (5.8%) were positive for KPC, NDM, VIM and OXA-48 enzymes, respectively. Only 14 (5%) isolates harboured two carbapenemase genes, namely 10 (3.6%) both blaNDM and blaVIM, and 4 (1.4%) both blaKPC and blaNDM. Females, inpatients and the elderly were more frequently affected by CRKP. The frequency of multidrug-resistant (MDR) and extensively drug-resistant (XDR) isolates were 32.6% and 7.7%, respectively. Continuous surveillance of local microbial prevalence and monitoring of antimicrobial resistance patterns provide critical information to guide the empiric therapy for UTIs and control the spread of MDR bacteria.

Benthic diatom eDNA metabarcoding for ecological assessment of an urban river: A comparison with morphological method

Benthic diatoms have been widely utilized for assessing the ecological status of rivers, due to their ability to reflect the environmental changes from natural and anthropogenic disturbance. However, the recognized limitations of traditional morphological method for diatom identification hinder its widespread application in local department monitoring and assessment efforts. Recently, eDNA metabarcoding methods have emerged as a promising alternative for efficient diatom identification. To reveal the feasibility of eDNA metabarcoding methods in diatom-based evaluation, this study comprehensively compared them with the traditional morphological method. The results revealed that eDNA metabarcoding effectively reflected diatom composition at genus but not species level. It recognized 80.4 % of genera identified morphologically through rbcL identification and 66.7 % through 18S rDNA identification. Despite species-level discrepancies in taxonomic composition, eDNA metabarcoding accurately indicated alpha diversity of diatoms, while also provided better illustration of beta diversity. Additionally, comparisons were performed in taxonomy-based and trait-based indices. It was suggested that no significance was observed between identification methods in any index. Linear regression analyses further supported rbcL identification as a preferred option over 18S rDNA identification due to its stronger congruency with morphological method. In all, this study presented two key suggestions: 1) rbcL identification is preferable to 18S rDNA identification in diatom taxonomy, and 2) eDNA metabarcoding is proposed to be a promising technique to assess river ecological status.

Data Evaluation of a Low-Cost Sensor Network for Atmospheric Particulate Matter Monitoring in 15 Municipalities in Serbia.

Conventional air quality monitoring networks typically tend to be sparse over areas of interest. Because of the high cost of establishing such monitoring systems, some areas are often completely left out of regulatory monitoring networks. Recently, a new paradigm in monitoring has emerged that utilizes low-cost air pollution sensors, thus making it possible to reduce the knowledge gap in air pollution levels for areas not covered by regulatory monitoring networks and increase the spatial resolution of monitoring in others. The benefits of such networks for the community are almost self-evident since information about the level of air pollution can be transmitted in real time and the data can be analysed immediately over the wider area. However, the accuracy and reliability of newly produced data must also be taken into account in order to be able to correctly interpret the results. In this study, we analyse particulate matter pollution data from a large network of low-cost particulate matter monitors that was deployed and placed in outdoor spaces in schools in central and western Serbia under the Schools for Better Air Quality UNICEF pilot initiative in the period from April 2022 to June 2023. The network consisted of 129 devices in 15 municipalities, with 11 of the municipalities having such extensive real-time measurements of particulate matter concentration for the first time. The analysis showed that the maximum concentrations of PM2.5 and PM10 were in the winter months (heating season), while during the summer months (non-heating season), the concentrations were several times lower. Also, in some municipalities, the maximum values and number of daily exceedances of PM10 (50 μg/m3) were much higher than in the others because of diversity and differences in the low-cost sensor sampling sites. The particulate matter mass daily concentrations obtained by low-cost sensors were analysed and also classified according to the European AQI (air quality index) applied to low-cost sensor data. This study confirmed that the large network of low-cost air pollution sensors can be useful in providing real-time information and warnings about higher pollution days and episodes, particularly in situations where there is a lack of local or national regulatory monitoring stations in the area.

Pioneering a sustainable development goals monitoring framework for European regions

The adoption of the 2030 Agenda for Sustainable Development by the United Nations General Assembly, encompassing 17 Sustainable Development Goals (SDGs), established a universal framework for addressing global challenges. Within the European Union (EU), the commitment to these goals has prompted the integration of the SDGs into a strategic framework for sustainable and inclusive growth. Recognizing the need for localized and detailed monitoring to capture the nuanced progress and challenges across Europe’s diverse regions, this paper proposes a comprehensive set of regional indicators specifically designed for the European context. Through a systematic review of existing SDG monitoring frameworks at different territorial levels and an extensive methodological process, the paper identifies 116 indicators that address 75 SDG targets. This tailored set is derived from a combination of national, regional, and supranational sources. The paper discusses the critical balance between standardization for comparability and customization to accommodate unique regional characteristics. The proposed indicator set is evaluated for its capacity to reflect the holistic vision of the SDGs while allowing for effective regional benchmarking. The research emphasizes the need for robust regional data infrastructure, the importance of aligning policies with broader sustainability objectives, and the dynamic nature of indicators that can adapt to societal changes such as demographic shifts. Finally, the paper highlights the significance of a pragmatic and adaptive regional approach to SDG monitoring. The proposed indicator set is a strategic tool for policymakers, stakeholders, and practitioners, guiding Europe’s regions towards a sustainable future and contributing to the global effort to achieve the SDGs by 2030.

“Mail-slot” Technique for Minimally Invasive Placement of Subdural Grid Electrodes: A Single-institution Experience

BackgroundIn the management of multi-drug-resistant focal epilepsies, intracranial electrode implantation is employed for precise localization of the ictal onset zone. In select patients, subdural grid electrode implantation is utilized. Subdural grid placement traditionally requires large craniotomies to visualize the cortex prior to mapping. However, smaller craniotomies may enable shorter operations and reduced risks. We aimed to compare surgical outcomes between patients undergoing traditional large craniotomies with those undergoing tailored 'mini' craniotomies (the “Mail-Slot” technique) for subdural grid placement. MethodsThis retrospective cohort study included 23 patients who underwent subdural electrode implantation for epilepsy monitoring between 2014 and 2020. Patients were categorized into mini craniotomies (N=9) and traditional large craniotomies (N=14) groups. Demographics, operative details, and outcomes were reviewed. Craniotomy size and number of electrodes were determined via post-hoc radiographs. ResultsOf the 23 patients studied, the mini group had smaller craniotomy sizes (mean=22.71 cm2 vs. 65.17 cm2, p<0.001) and higher electrode-to-size ratios (mean=4.25 vs. 1.71, p<0.0001). The mini group had slightly fewer total electrodes (mean=88.67 vs. 107.43, p=0.047). No significant differences were found in operative duration, blood loss, invasive EEG duration, complications, or Engel scores between the groups. One patient per group required further invasive epilepsy monitoring for localization; all patients underwent therapeutic surgery. ConclusionOur findings suggest that mini craniotomies for subdural grid placement in epilepsy monitoring offer significant advantages, including smaller craniotomy sizes and shorter operation durations, without compromising safety or efficacy. These results support the trend towards minimally invasive, patient-tailored surgical approaches in epilepsy treatment.

Basic cell carcinoma of the vulva. Case report and literature review

Background: Vulvar carcinoma is rare, 4% of gynecological cancer worldwide and basal cell carcinoma of these represents 2 to 3%; Its diagnosis is delayed due to carelessness of the patient and doctor. Objective: To present a clinical case of basal cell carcinoma of the vulva and review of the literature. Clinical case: A 58-year-old patient, without comorbidities or risk factors, who presented a nodule in the upper third of the right labia majora; Excisional biopsy was performed with margins free of macroscopic tumor, basal cell carcinoma was reported. Methodology: A narrative review is carried out from 2014 to 2021 in PubMed, scholaris, SciELO Google scholar and books, finding 27 articles and only 20 were included for reliability, impact factor. Results: Vulvar cancer represents 4% of gynecological cancer worldwide. 0.4% of all basal cell carcinomas occur in the genital region, and in the vulva it represents 2 to 4% of all vulvar cancers. Basal cell carcinoma of the vulva most commonly presents as a solitary pink or pigmented papule or plaque on the labia majora; bilateral and multifocal lesions may occur. Basal cell carcinoma of the vulva is an extremely rare tumor that rarely metastasizes or spreads. . Primary treatment should consist of wide local excision and continuous monitoring. Conclusion: Any suspicious lesion of the vulva must be biopsied to reach a timely diagnosis and treatment, the rarity of these lesions and the lack of care on the part of the patient and the negligence of the doctor not to perform an examination of the vulva, the lesions progress until symptoms occur or are discovered during medical examination, vulvar cancer is suspected, radical excisional biopsy is the correct therapeutic approach.

МЕТОДОЛОГИЯ КЛИНИЧЕСКИХ АУДИТОВ ОТДЕЛЕНИЙ ЛУЧЕВОЙ ТЕРАПИИ В РФ НА ОСНОВЕ ПРИНЦИПОВ АУДИТА МАГАТЭ QUATRO

Purpose: To describe the essence, tasks and algorithm of comprehensive audit in radiotherapy departments of medical institutions in Rus sian Federation. The methodology of audits conducted by the International Atomic Energy Agency (IAEA) and adapted for its further application, was used as a model. The global goal of the audit project is to standardize and harmonize procedures to ensure safety and quality control of treatment of cancer patients in different institutions, to enable comparison of radiation therapy results among participating institutions, to conduct interclinical studies and, possibly, to create a unified data register. Material and methods: One of the main aspects of clinical audits is the harmonization of standards between different departments. Clinical audits in radiotherapy can be an important tool for interclinical quality assurance (QA) program, effectiveness and safety of radiotherapy, and treatment protocols synchronization. Audits allow an in-depth analysis of the procedures and processes governing patient care in a particular clinic. Such clinical audits cover the whole chain of patients care, the organization of structural units, the infrastructure, clinical, physics and technical aspects underlying the radiotherapy department. This audit is a peer review process conducted by an audit team consisting of a radiation oncologist (RO), medical physicist (MP) and radiation technologist (RTT) and is known as QUATRO and stands for Quality Assurance Team in Radiation Oncology). Possible audit tools include: 1. Saff interviewing. 2. Examination of the structure of the entire department. 3. Review and evaluation of procedures and all relevant documentation, including analysis of patient charts. 4. Conducting independent measurements of absorbed doses and other methods of local procedures monitoring, where relevant and appropriate. 5. Observation of the practical implementation of operating procedures. Results: It was decided to use the IAEA QUATRO methodology for clinical audits and to adapt it to the specifics of radiotherapy in Russian Federation. One of the advantages of such a clinical audit is that the formalism and algorithm of this approach will be identically applied in all departments, which will allow comparing and analyzing the results. In order to obtain structured information, a detailed research protocol, which is a questionnaire, has been developed. The questions in the questionnaire allow to assess key aspects of the radiotherapy process that affect clinical outcomes and treatment efficiency.

The model of choosing a microcontroller for the environmental monitoring system module

Problem. The development and application of modern digital technologies for environmental monitoring is an extremely relevant issue. Such environmental monitoring systems allow for dynamic monitoring of the current state of the studied territories in order to further analyze changes and make decisions on their conservation and development. To improve the environmental situation, it is necessary to constantly improve environmental monitoring systems by creating local environmental monitoring systems operating in real time. Goal. The aim of the study is to develop a model for selecting a microcontroller for an environmental monitoring module based on many functional and cost criteria, which will reduce the time of information collection for a regional environmental monitoring system. Methodology. To achieve this goal, we analyzed the characteristics of microcontrollers. A model for selecting a microcontroller for an environmental monitoring module has been developed based on many functional and cost criteria. An example of using the microcontroller selection model for the environmental monitoring module is given. The method of multicriteria optimization allows the selection of a microcontroller for the module of the environmental monitoring system by calculating the utility function. Results. The paper considers the main tasks of the environmental monitoring system. A mathematical model for selecting a microcontroller for the module of an environmental monitoring system has been developed. It belongs to the class of multicriteria discrete programming models and, unlike the known ones, takes into account the system requirements for the module of the environmental monitoring system as a whole. Originality. The developed model allows us to make a microcontroller according to many functional and cost criteria under conditions of fuzzy input information. Practical value. The use of the proposed model for selecting a microcontroller for the module of the environmental monitoring system will reduce the time of collecting information for the regional environmental monitoring system.

A quality‐related distributed process monitoring framework for large‐scale manufacturing processes with multirate sampling measurements

SummaryQuality‐related process monitoring has become a research hot‐spot in the field of industrial control because it is essential to ensure the process safety and product quality. A great number of data driven quality‐related process monitoring methods have been developed for large‐scale manufacturing processes, and most of them are developed based on homogeneous sampling measurement. Therefore, it is necessary to develop quality‐related monitoring methods for large‐scale processes with multirate sampling measurements. In this paper, a new quality‐related distributed monitoring framework for large‐scale manufacturing processes with multirate sampling measurements is proposed. First, a new subsystem decomposition method for multirate sampling processes combining prior knowledge and mutual information is proposed by introducing mathematic expectations. Second, local monitoring model is designed for each subsystem. Multirate partial least squares regression is adopted for modeling among the process and quality variables. The monitoring metrics of the isolation‐based anomaly detection using nearest‐neighbor ensembles are built in prediction space and process space, respectively. Finally, Bayesian inference is introduced to obtain statistical indicators for the plant‐wide processes. The validity of the proposed framework is verified in Tennessee Eastman process and a real hot strip mill process. The results show that the proposed method has favorable effectiveness and significant performance gains compared with state‐of‐the‐art methods.

Evaluation of Antimicrobial Resistancein Clinical Isolates of Enterococcus spp. Obtained from Hospital Patients in Latvia.

Background and Objective: Enterococci are typically found in a healthy human gastrointestinal tract but can cause severe infections in immunocompromised patients. Such infections are treated with antibiotics. This study addresses the rising concern of antimicrobial resistance (AMR) in Enterococci, focusing on the prevalence of vancomycin-resistant enterococcus (VRE) strains. Materials and Methods: The pilot study involved 140 Enterococci isolates collected between 2021 and 2022 from two multidisciplinary hospitals (with and without local therapeutic drug monitoring protocol of vancomycin) in Latvia. Microbiological assays and whole genome sequencing were used. AMR gene prevalence with resistance profiles were determined and the genetic relationship and outbreak evaluation were made by applying core genome multi-locus sequence typing (cgMLST). Results: The acquired genes and mutations were responsible for resistance against 10 antimicrobial classes, including 25.0% of isolates expressing resistance to vancomycin, predominantly of the vanB type. Genetic diversity among E. faecalis and E. faecium isolates was observed and seven potential outbreak clusters were identified, three of them containing sequence types ST6, ST78 and ST80. The prevalence of vancomycin resistance was highest in the hospital without a therapeutic drug-monitoring protocol and in E. faecium. Notably, a case of linezolid resistance due to a mutation was documented. Conclusions: The study illustrates the concerning prevalence of multidrug-resistant Enterococci in Latvian hospitals, showcasing the rather widespread occurrence of vancomycin-resistant strains. This highlights the urgency of implementing efficient infection control mechanisms and the need for continuous VRE surveillance in Latvia to define the scope and pattern of the problem, influencing clinical decision making and planning further preventative measures.

Sex-specific associations between air pollutants and asthma prevalence in Japanese adults: a population-based study

ABSTRACT This study investigated the association between air pollutants and asthma prevalence in male and female Japanese adults. In this retrospective cross-sectional analysis, annual mean exposure levels of air pollutants, specifically nitrogen dioxide (NO2) and particulate matter with a median aerodynamic diameter ≤2.5 μm (PM2.5), were assessed at a local monitoring site. Multivariable logistic regression models, adjusted for genetic and/or lifestyle factors, were used to explore the association between air pollutants and asthma, with stratification by sex. A total of 1,497 participants aged ≥40 years were included. Their mean age was 65.9 ± 12.4 years, with 847 being women. Overall, 91 participants were diagnosed with asthma. In the multivariable model, ambient exposure levels of NO2 and PM2.5 were significantly associated with asthma in women but not in men. This study highlights sex as a significant determinant of the link between air pollutants and asthma exacerbation, particularly among female Japanese adults.

Seismic Monitoring of a Deep Geothermal Field in Munich (Germany) Using Borehole Distributed Acoustic Sensing.

Geothermal energy exploitation in urban areas necessitates robust real-time seismic monitoring for risk mitigation. While surface-based seismic networks are valuable, they are sensitive to anthropogenic noise. This study investigates the capabilities of borehole Distributed Acoustic Sensing (DAS) for local seismic monitoring of a geothermal field located in Munich, Germany. We leverage the operator's cloud infrastructure for DAS data management and processing. We introduce a comprehensive workflow for the automated processing of DAS data, including seismic event detection, onset time picking, and event characterization. The latter includes the determination of the event hypocenter, origin time, seismic moment, and stress drop. Waveform-based parameters are obtained after the automatic conversion of the DAS strain-rate to acceleration. We present the results of a 6-month monitoring period that demonstrates the capabilities of the proposed monitoring set-up, from the management of DAS data volumes to the establishment of an event catalog. The comparison of the results with seismometer data shows that the phase and amplitude of DAS data can be reliably used for seismic processing. This emphasizes the potential of improving seismic monitoring capabilities with hybrid networks, combining surface and downhole seismometers with borehole DAS. The inherent high-density array configuration of borehole DAS proves particularly advantageous in urban and operational environments. This study stresses that realistic prior knowledge of the seismic velocity model remains essential to prevent a large number of DAS sensing points from biasing results and interpretation. This study suggests the potential for a gradual extension of the network as geothermal exploitation progresses and new wells are equipped, owing to the scalability of the described monitoring system.

5G-enabled, battery-less smart skins for self-monitoring megastructures and digital twin applications.

With the current development of the 5G infrastructure, there presents a unique opportunity for the deployment of battery-less mmWave reflect-array-based sensors. These fully-passive devices benefit from having a larger detectability than alternative battery-less solutions to create self-monitoring megastructures. The presented 'smart' skin sensor uses a Van-Atta array design enabling ubiquitous local strain monitoring for the structural health monitoring of composite materials featuring wide interrogation angles. Proof-of-concept prototypes of these 'smart' skin millimeter-wave identification tags, that can be mounted on or embedded within common materials used in wind turbine blades, present a highly-detectable radar cross-section of - 33.75 dBsm and - 35.00 dBsm for mounted and embedded sensors respectively. Both sensors display a minimum resolution of 202 -strain even at 40 off-axis enabling interrogation of the fully-passive sensor at oblique angles of incidence. When interrogated from a proof-of-concept reader, the fully-passive, sticker-like mmID enables local strain monitoring of both carbon fiber and glass fiber composite materials. The sensors display a repeatable and recoverable response over 0-3000 -strain and a sensitivity of 7.55 kHz/ -strain and 7.92 kHz/ -strain for mounted and embedded sensors, respectively. Thus, the presented 5G-enabled battery-less sensor presents massive potential for the development of ubiquitous Digital Twinning of composite materials in future smart cities architectures.

Theoretical foundations of developing a software-hardware complex for monitoring and managing the geophysical state of regions in Ukraine

This article explores the essence and important aspects of the software and hardware complex for monitoring and managing the geophysical condition of a region. Various structural schemes of the complex are analyzed in the article, including linear sequential, modular, hierarchical, matrix, and integrated. The choice of an optimal scheme determines the efficiency of the monitoring system. Next, the importance of the database structure for effective collection and analysis of geophysical data is discussed. Based on the collected information, a hierarchical structure for monitoring and managing large territories, such as Ukraine, is proposed, providing centralized management, regional subsystems, and local monitoring. Conclusions and recommendations for creating a state program, including the development of a strategic plan, definition of technical requirements, fundraising, and collaboration with partners, are provided. Through these steps, it is possible to create a comprehensive and well-organized system for monitoring and managing the geophysical condition of the region, ensuring the safety, stability, and prosperity of citizens. The presented aspects take into account important requirements and needs for the implementation of similar projects for better management of natural risks and events.

Spatial and Temporal Variability in Oyster Settlement on Intertidal Reefs Support Site-Specific Assessments for Restoration Practices

As some of the most threatened ecosystems in the world, the declining condition and coverage of coastal habitats results in the loss of the myriad ecosystem services they provide. Due to the variability in physical and biological characteristics across sites, it is imperative to increase location-based information to inform local management projects, which will potentially help to reestablish functions of coastal habitats. Since oysters are often used in restoration projects, this study quantified spatial and temporal patterns in eastern oyster spat settlement in a bar-built estuary in northeast Florida, USA that is host to a robust population of intertidal oyster reefs. Spat settlement was found to occur from April to October with small peaks in the spring and large ones around September. Inter-annual differences in spat settlement were likely influenced by existing environmental conditions and heavily affected by large-scale events such as tropical cyclones. Variations in regional spat settlements are possibly driven by the residence times of the watersheds, the density of adult populations, and the location of the spat collectors. The results of this study illustrate place-based variability in oyster settlement patterns and underscore the importance of local monitoring for oyster resource management, restoration, and research.

PERFORMANCE EVALUATION OF TEMPORAL MODEL AND SPATIAL CORRELATION METHODS FOR PERSISTENT SCATTERER DETERMINATION IN LANDSLIDE PRONE AREAS

Abstract. The Philippines is no stranger to natural hazards. Aside from flooding, landslides emerge as a primary contributor to damage dealt by natural hazards. Traditional methods for landslide monitoring require on-site field measurements, which makes them resource-intensive and time-consuming. Moreover, the frequency of updating of existing landslide hazard maps is limited by resources and manpower. This research introduces the application of remote sensing technology, specifically Persistent Scatter Interferometry (PSI), as a complementary tool for updating hazard maps. PSI enables the identification of stable ground points, eliminating the need for labor-intensive fieldwork and facilitating assessments of potential slope instability. Two distinct PSI processing methods are evaluated in the study; the Temporal Model approach and the Spatial Correlation model approach. Findings reveal that the Temporal Model approach successfully detected 11,647 Persistent Scatterers (PS) points, while the Spatial Correlation approach identified 272,614 PS points. Furthermore, the Spatial Correlation approach demonstrated its capability to detect PS points within high landslide susceptibility areas. Consequently, the results highlight the suitability of the Spatial Correlation approach for detecting PS points, particularly in landslide-prone regions, offering support to local landslide hazard monitoring systems. This research supports the initiative to a more efficient and cost-effective approach to maintaining up-to-date landslide susceptibility maps in the Philippines in enhancing disaster preparedness and mitigation efforts.

A novel process monitoring framework combined temporal feedback autoencoder and multilevel correlation analysis for large-scale industrial processes

Modeling and monitoring generally face numerous challenges such as complex characteristics of multi-unit, temporal correlations and strong interaction among subblocks in large-scale industrial processes. To handle those challenges, a novel process monitoring framework combined temporal feedback autoencoder and multilevel correlation analysis is proposed in this paper. Firstly, large-scale industrial processes are decomposed into multiple subblocks in spatial and temporal order based on process knowledge. Secondly, an improved autoencoder with temporal feedback mechanism is constructed as local monitoring model to capture the important latent variables of each subblock. Then, considering the sequential transmission and correlations among subblocks in series, a multilevel correlation analysis method is employed to efficiently extract the unique features of each subblock and the joint features of the whole process. Finally, the irregular contribution indices of the unique features and the joint features are designed for hierarchical process monitoring. The superiority of the proposed framework can be verified by Tennessee Eastman process and a real hot strip mill process.

Reliable urban vehicle localization under faulty satellite navigation signals

Reliable urban navigation using global navigation satellite system requires accurately estimating vehicle position despite measurement faults and monitoring the trustworthiness (or integrity) of the estimated location. However, reflected signals in urban areas introduce biases (or faults) in multiple measurements, while blocked signals reduce the number of available measurements, hindering robust localization and integrity monitoring. This paper presents a novel particle filter framework to address these challenges. First, a Bayesian fault-robust optimization task, formulated through a Gaussian mixture model (GMM) measurement likelihood, is integrated into the particle filter to mitigate faults in multiple measurement for enhanced positioning accuracy. Building on this, a novel test statistic leveraging the particle filter distribution and the GMM likelihood is devised to monitor the integrity of the localization by detecting errors exceeding a safe threshold. The performance of the proposed framework is demonstrated on real-world and simulated urban driving data. Our localization algorithm consistently achieves smaller positioning errors compared to existing filters under multiple faults. Furthermore, the proposed integrity monitor exhibits fewer missed and false alarms in detecting unsafe large localization errors.

Aerobic Microbiological Spectrum and Antibiotic Resistance in Children Operated for Anorectal Abscesses.

(1) Background: Anorectal abscesses are a relatively rare pathology in childhood. Most often, male children under 1 year of age are affected. The importance of microbiological examination for the diagnosis and treatment of such patients remains debatable among surgeons, resulting in scarce data being available in the literature. We aimed to identify the aerobic microbiological spectrum and antibiotic resistance of isolates in children undergoing operation to treat anorectal abscesses. (2) Methods: We performed a case series of 102 children diagnosed and operated for anorectal abscesses over a period of 10 years (2010-2019). Purulent wound exudate was used for microbiological evaluation, which was subsequently cultured on 5% sheep-blood agar and eosin-methylene blue agar. For microbiological identification, conventional biochemical tests and semi-automated (API 20, bioMerieux, Marcy-l'Étoile, France) tests were used, as well as automated systems (Vitek-2 Compact, bioMerieux, France). Antimicrobial susceptibility testing was performed by the disk diffusion method of Bauer-Kirby and by determining the minimal inhibitory concentrations for glycopeptides. The results were interpreted according to the EUCAST standard for the corresponding year. (3) Results: Microbiological testing in children operated for anorectal abscesses mainly identified the gut commensals that normally reside in the rectal mucosa. Monocultures were found in just over half of the cases. Escherichia coli, Klebsiella pneumoniae complex, and Proteus mirabilis were the most frequently isolated. In addition, Staphylococcus aureus was found in 7% of patients. In Gram-negative bacteria, antibiotic resistance was most often observed in penicillins, cephalosporins, sulfonamides, and fluoroquinolones. (4) Conclusions: The increasing rates of antimicrobial resistance impose the need for the local monitoring of circulating commensal bacteria associated with anorectal abscesses in children to guide antibiotic therapy when indicated.