The presence of mutagenic and carcinogenic N-nitrosamine impurities in medicinal products poses a safety risk. While incorporating antioxidants in formulations is a potential mitigation strategy, concerns arise regarding their interference with drug absorption by inhibiting intestinal drug transporters. Our study screened thirty antioxidants for inhibitory effects on key intestinal transporters—OATP2B1, P-gp, and BCRP in HEK-293 cells (OATP2B1) or membrane vesicles (P-gp, BCRP) using ³H-estrone sulfate, ³H-N-methyl quinidine, and ³H-CCK8 as substrates, respectively. The screen identified that butylated hydroxyanisole (BHA) and carnosic acid inhibited all three transporters (OATP2B1, P-gp, and BCRP), while ascorbyl palmitate (AP) inhibited OATP2B1 by more than 50%. BHA had IC₅₀ values of 71 ± 20 µM, 206 ± 14 µM, and 182 ± 49 µM for OATP2B1, BCRP, and P-gp, respectively. AP exhibited IC₅₀ values of 23 ± 10 µM for OATP2B1. The potency of AP and BHA was tested with valsartan, an OATP2B1 substrate, and revealed IC₅₀ values of 26 ± 17 µM and 19 ± 11 µM, respectively, in HEK-293-OATP2B1 cells. Comparing IC₅₀ values of AP and BHA with estimated intestinal concentrations suggests an unlikely inhibition of intestinal transporters at clinical concentrations of drugs formulated with antioxidants. Full article

Background: High dietary diversity has been found to be associated with frailty. However, the trajectory of dietary diversity intake in relation to frailty is unclear. Methods: Using the latent class trajectory modeling approach, we identified distinctive dietary variety trajectory groups among 2017 participants based on the Chinese Longitudinal Healthy Longevity Survey acquired at four time points within a 10-year period. Frailty status was assessed using a frailty index comprising 37 health deficits. Dietary diversity was quantified using the dietary variety score (DVS), based on food category consumption frequency. Logistic regression analyses were employed to explore the association between DVS change trajectories and frailty. Results: This study identified two distinct DVS trajectories: “Moderate-Slow decline-Slow growth”, encompassing 810 (40.16%) individuals, and “Moderate-Slow growth-Accelerated decline”, including 1207 (59.84%) individuals. After adjusting for covariates, the odds ratio for DVS in the “Moderate-Slow decline-Slow growth” group was 1.326 (95% confidence interval: 1.075–1.636) compared to the “Moderate-Slow growth-Accelerated decline” group. The “Moderate-Slow decline-Slow growth” trajectory continued to decrease and was maintained at a low level in the early stages of aging. Conclusion: Sustaining a high dietary diversity trajectory over time, particularly in the early stages of aging, could potentially decrease the risk of frailty among older Chinese adults. Full article

Histone deacetylases (HDACs) are crucial in gene transcription, removing acetyl groups from histones. They also influence the deacetylation of non-histone proteins, contributing to the regulation of various biological processes. Thus, HDACs play pivotal roles in various diseases, including cancer, neurodegenerative disorders, and inflammatory conditions, highlighting their potential as therapeutic targets. This paper reviews the structure and function of the four classes of human HDACs. While four HDAC inhibitors are currently available for treating hematological malignancies, numerous others are undergoing clinical trials. However, their non-selective toxicity necessitates ongoing research into safer and more efficient class-selective or isoform-selective inhibitors. Computational methods have aided the discovery of HDAC inhibitors with the desired potency and/or selectivity. These methods include ligand-based approaches, such as scaffold hopping, pharmacophore modeling, three-dimensional quantitative structure–activity relationships, and structure-based virtual screening (molecular docking). Moreover, recent developments in the field of molecular dynamics simulations, combined with Poisson–Boltzmann/molecular mechanics generalized Born surface area techniques, have improved the prediction of ligand binding affinity. In this review, we delve into the ways in which these methods have contributed to designing and identifying HDAC inhibitors. Full article

Phenylketonuria is an inherited metabolic disorder that leads to neurobehavioral dysfunction. The main treatment is a low-phenylalanine diet and/or the cofactor tetrahydrobiopterin. Regular outpatient follow-up care and measurement of the phenylalanine levels in the blood are required. We aimed to analyze the economic burden of phenylketonuria on families and the state. The patients with phenylketonuria were divided into three groups according to their treatment: a low-phenylalanine diet group (n = 50), a tetrahydrobiopterin group (n = 44), and a group taking tetrahydrobiopterin together with the diet (n = 25). A comparative cost analysis was carried out. The annual economic burden to the state was calculated to average EUR 18,801 ± 15,345 and was lowest in the diet group, then in the tetrahydrobiopterin group, and highest in the tetrahydrobiopterin + diet group (p < 0.001). Out-of-pocket costs amounted to EUR 1531 ± 1173 per year, and indirect losses averaged EUR 2125 ± 1930 per year for all families. The economic loss was significantly lower in the families taking tetrahydrobiopterin than in the other groups (p = 0.001). The combined use of medical nutrition and BH4 treatments has been shown to increase the economic burden on the state. Reimbursing low-protein products and increasing the number of patients eligible for financial allowances may reduce the economic burden on families. Full article

Artificial Intelligence (AI) has revolutionized the management of non-small-cell lung cancer (NSCLC) by enhancing different aspects, including staging, prognosis assessment, treatment prediction, response evaluation, recurrence/prognosis prediction, and personalized prognostic assessment. AI algorithms may accurately classify NSCLC stages using machine learning techniques and deep imaging data analysis. This could potentially improve precision and efficiency in staging, facilitating personalized treatment decisions. Furthermore, there are data suggesting the potential application of AI-based models in predicting prognosis in terms of survival rates and disease progression by integrating clinical, imaging and molecular data. In the present narrative review, we will analyze the preliminary studies reporting on how AI algorithms could predict responses to various treatment modalities, such as surgery, radiotherapy, chemotherapy, targeted therapy, and immunotherapy. There is robust evidence suggesting that AI also plays a crucial role in predicting the likelihood of tumor recurrence after surgery and the pattern of failure, which has significant implications for tailoring adjuvant treatments. The successful implementation of AI in personalized prognostic assessment requires the integration of different data sources, including clinical, molecular, and imaging data. Machine learning (ML) and deep learning (DL) techniques enable AI models to analyze these data and generate personalized prognostic predictions, allowing for a precise and individualized approach to patient care. However, challenges relating to data quality, interpretability, and the ability of AI models to generalize need to be addressed. Collaboration among clinicians, data scientists, and regulators is critical for the responsible implementation of AI and for maximizing its benefits in providing a more personalized prognostic assessment. Continued research, validation, and collaboration are essential to fully exploit the potential of AI in NSCLC management and improve patient outcomes. Herein, we have summarized the state of the art of applications of AI in lung cancer for predicting staging, prognosis, and pattern of recurrence after treatment in order to provide to the readers a large comprehensive overview of this challenging issue. Full article

Background: Frailty leads to vulnerability to stress, impaired daily functioning, and an increased need for care. Frailty is considered reversible, and it is crucial to detect the risk of frailty early and investigate factors that may delay its progression. Objectives: To identify tests that can explain frailty risk and compare the situation of local residents with and without frailty support. Methods: Participants were recruited in two ways: through public advertisements in Akita City (open recruitment group) and through invites from frailty supporters in their immediate communities (community-based group). We examined the differences in frailty risk and oral, motor, and social functions between the two groups and identified factors associated with frailty risk in both groups. Results: The community-based group exhibited a lower risk of frailty than the open recruitment group despite having more older members on average. Additionally, the community-based group demonstrated better social functioning than the open-recruitment group. Furthermore, factors such as oral diadochokinesis (ODK), one-leg stand test (OLS), and grip strength (GS) showed significant association with frailty risk. Conclusion: The ODK, OLS, and GS were identified as factors explaining frailty risk, and Frailty Supporters may reduce the risk of frailty. Full article

We conducted a comprehensive review of the current literature of published data and clinical trials (MEDLINE), as well as published congress contributions and active recruiting clinical trials on targeted therapies in hepatocellular carcinoma. Combinations of different agents and medical therapy along with radiological interventions were analyzed for the setting of advanced HCC. Those settings were also analyzed in combination with adjuvant situations after resection or radiological treatments. We summarized the current knowledge for each therapeutic setting and combination that currently is or has been under clinical evaluation. We further discuss the results in the background of current treatment guidelines. In addition, we review the pathophysiological mechanisms and pathways for each of these investigated targets and drugs to further elucidate the molecular background and underlying mechanisms of action. Established and recommended targeted treatment options that already exist for patients are considered for systemic treatment: atezolizumab/bevacizumab, durvalumab/tremelimumab, sorafenib, lenvatinib, cabozantinib, regorafenib, and ramucirumab. Combination treatment for systemic treatment and local ablative treatment or transarterial chemoembolization and adjuvant and neoadjuvant treatment strategies are under clinical investigation. Full article

Forest road maps are a fundamental source of information for the sustainable management, protection, and public utilization of forests. However, the precision of these maps is crucial to their use. In this context, we assessed and compared the elevation accuracy of terrain on three forest road surfaces (i.e., asphalt, concrete, and stone), which were derived based on data from three remote sensing technologies (i.e., aerial imaging, airborne laser scanning, and mobile laser scanning) using five geospatial techniques (i.e., inverse distance; natural neighbor; and conversion by average, maximal, and minimal elevation value). Specifically, the elevation accuracy was assessed based on 700 points at which elevation was measured in the field, and these elevations were extracted from fifteen derived forest road maps with a resolution of 0.5 m. The highest precision was found on asphalt roads derived from mobile laser scanning data (RMSE from ±0.01 m to ±0.04 m) and airborne laser scanning data (RMSE from ±0.03 m to ±0.04 m). On the other hand, the lowest precision was found on all roads derived from aerial imaging data (RMSE from ±0.11 m to ±0.23 m). Furthermore, we found significant differences in elevation between the measured and derived terrains. However, the differences in elevation between specific techniques, such as inverse distance, natural neighbor, and conversion by average, were mostly random. Moreover, we found that airborne and mobile laser scanning technologies provided terrain on concrete and stone roads with random elevation differences. In these cases, it is possible to replace a specific technique or technology with one that is similar without significantly decreasing the elevation accuracy (α = 0.05). Full article

In the business of growing and selling ornamental plants, it is important to keep track of plants from nursery to distribution. Radio Frequency Identification (RFID) technology provides an easier tracking method for inventories of plants by attaching tags with unique identifiers. Due to the vast area of most nurseries, there is a need to have an efficient method of scanning RFID tags. This paper investigates the use of drones and RFID, specifically, the effects of RFID reader power and flight altitude on tag counts. The experimental setup evaluated three RFID reader power levels (15 dBm, 20 dBm, and 27 dBm), three flight altitudes (3 m, 5 m, and 7 m), the number of passes (one or two), and two plant types (‘Green Giant’ arborvitae and ‘Sky Pencil’ holly). For RFID tags, four types were used (L5, L6, L8, and L9), with two antenna types (dog-bone and square-wave) and two attachment types (loop-lock and stake). For each power level, the UAV was flown to three different altitudes of 3 m, 5 m, and 7 m above the ground. At each altitude, two scan passes were performed at a constant speed of approximately 1.5 m/s. Each plot of plants (two in total) was randomly tagged with a total of 40 RFID tags per plot. Field data were collected from September to December 2023 (on a total of eight dates). The data showed that a power level of 15 dBm and an altitude of 3 m yielded a tag count of 53%, while counts of 34% and 16% were achieved at 5 m and 7 m, respectively. At 20 dBm and an altitude of 3 m, the count accuracy across all tag types and both plants was 90%. When the altitude was increased to 5 m and 7 m, tag-count accuracy dropped to 75% and 33%, respectively. The highest count accuracy was observed at 27 dBm and an altitude of 3 m, with a reading accuracy of 98%. Tag types L6 and L9 performed better at any power level and altitude, while L5 and L8 performed well at a higher power level and lower altitude. In this experiment, canopy properties (size and shape) had no effect on the number of tags read. This study aimed to evaluate the RFID power and UAV altitude achieving the highest accuracy in scanning the RFID tags. Furthermore, it also assessed the effects of plant growth on the scanning efficiency and accuracy of the system. Full article

To achieve rapid vector maneuvering of a space micro-nano satellite, a micro-sized solid rocket motor was utilized as its propulsion system, and a micro-jet-vane-thrust-vector control system was devised. Computational fluid dynamics (CFD) numerical simulations were conducted on the designed micro-vane structure at various deflection angles to ascertain the lateral force and flow field characteristics. The motor’s combustion temperature is 1380 K. Therefore, materials such as 45 steel, alumina ceramics, and tungsten–molybdenum alloy were chosen for the jet vanes to carry out ground-based-motor-jet-ablation experiments and measure the ablation amount. Concurrently, experimental data, including lateral force, were gathered. The tests demonstrated that despite 45 steel having a higher melting point than the combustion temperature significant ablation still occurred. Alumina ceramics exhibited defects and experienced ablation and fragmentation post-test. In contrast, tungsten–molybdenum alloy, being a refractory metal, showed minimal ablation after testing, making it an ideal material for micro-jet vanes. At a 20° deflection of the jet vanes, the lateral force calculated via numerical simulation was 3.76 N, whereas the lateral force obtained from the test was approximately 3.8 N, resulting in an error within 1% and validating the numerical simulation’s validity and accuracy. The jet vanes can generate a maximum steering angle of 8°, thus ensuring the micro-nano satellite’s swift vector maneuvering at large angles. Full article

Body size may drive the molecular evolution of mitochondrial genes in response to changes in energy requirements across species of different sizes. In this study, we perform selection pressure analysis and phylogenetic independent contrasts (PIC) to investigate the association between molecular evolution of mitochondrial genome protein-coding genes (mtDNA PCGs) and body size in terrestrial Cetartiodactyla. Employing selection pressure analysis, we observe that the average non-synonymous/synonymous substitution rate ratio (ω) of mtDNA PCGs is significantly reduced in small-bodied species relative to their medium and large counterparts. PIC analysis further confirms that ω values are positively correlated with body size (R² = 0.162, p = 0.0016). Our results suggest that mtDNA PCGs of small-bodied species experience much stronger purifying selection as they need to maintain a heightened metabolic rate. On the other hand, larger-bodied species may face less stringent selective pressures on their mtDNA PCGs, potentially due to reduced relative energy expenditure per unit mass. Furthermore, we identify several genes that undergo positive selection, possibly linked to species adaptation to specific environments. Therefore, despite purifying selection being the predominant force in the evolution of mtDNA PCGs, positive selection can also occur during the process of adaptive evolution. Full article

Worms can be produced using special machines or standard lathes equipped with a whirling thread-cutting device. A blank is placed on the mandrel and tightened using the three-jawed chuck of the standard lathe. If the workpiece diameter is excessively large, passage through the driven pulley is not possible, and the workpiece cannot be supported. Therefore, a new tool holder for whirling devices is needed. During the whirling process, vibrations in the form of machine velocity amplitudes were measured. After whirling was complete, roughness values were calculated. Using numerical procedures of Wolfram Mathematica 10, vibration peaks were extracted, from which frequencies and maximum amplitudes were determined. The data were then inputted into Design Expert, and the rotational speed and amount of separated material were optimized. The results of the study showed that the quality of the processed surface did not improve with processing in two passes of the tool. The measured vibration amplitudes on the lathe carrier and thread whirling attachment increased with cutting speed at the same cutting depth, whereas the quality of the machined surface was best at the smallest and largest cutting depths. Full article

Alpha-1 antitrypsin deficiency (AATD) is a genetic disorder characterized by the insufficient production of the AAT protein. Due to availability limitations, not all AATD patients receive protein therapy treatment. In this study, the technoeconomic analysis of different processes (conventional and intensified) producing 200 kg/year of PEGylated recombinant AAT (PEG-AAT) using a Chinese hamster ovary cell line was investigated. All bioprocesses consist of upstream, downstream, and PEGylation sections. A base-case model (process A) of the conventional fed-batch production bioreactor was developed using SuperPro Designer software (Version 13) to evaluate the economic feasibility of the process. The cost of goods (COG) was estimated to be approximately USD 387.6/g. Furthermore, an intensified process (B) was modeled and evaluated to reduce the COG. Process intensification was implemented in the process (N-1 perfusion bioreactor). The specific operating COG for process B was found to be 10% less than that of process A. Scenario analysis was performed to assess the impact of process capacity (100–1000 kg/year) and cell-specific productivity (30–90 pg/cell/day). With an increase in process capacity, the specific operating COG was reduced for all processes. Increasing cell-specific productivity decreases the specific operating COG at different rates for each process, depending on the titer level. Future investigations into the PEGylation section are required since it has the highest COG of all the sections. Full article

Ceramic matrix composites (CMCs) are a significant advancement in materials science and engineering because they combine the remarkable characteristics of ceramics with the strength and toughness of fibers. With their unique properties, which offer better performance and endurance in severe settings, these advanced composites have attracted significant attention in various industries. At the same time, lightweight ceramic matrix composites (LCMCs) provide an appealing alternative for a wide range of industries that require materials with excellent qualities such as high-temperature stability, low density, corrosion resistance, and excellent mechanical performance. CMC uses will expand as production techniques and material research improve, revolutionizing aerospace, automotive, and other industries. The effectiveness of CMCs primarily relies on the composition of their constituent elements and the methods employed in their manufacturing. Therefore, it is crucial to explore the functional properties of various global ceramic matrix reinforcements, their classifications, and the manufacturing techniques used in CMC fabrication. This study aims to overview a diverse range of CMCs reinforced with primary fibers, including their classifications, manufacturing techniques, functional properties, significant applications, and global market size. Full article

Epigenetic alterations that lead to differential expression of microRNAs (miRNAs/miR) are known to regulate tumour cell states, epithelial–mesenchymal transition (EMT) and the progression to metastasis in breast cancer. This study explores the key contribution of miRNA-18a in mediating a hybrid E/M cell state that is pivotal to the malignant transformation and tumour progression in the aggressive ER-negative subtype of breast cancer. The expression status and associated effects of miR-18a were evaluated in patient-derived breast tumour samples in combination with gene expression data from public datasets, and further validated in in vitro and in vivo breast cancer model systems. The clinical relevance of the study findings was corroborated against human breast tumour specimens (n = 446 patients). The down-regulated expression of miR-18a observed in ER-negative tumours was found to drive the enrichment of hybrid epithelial/mesenchymal (E/M) cells with luminal attributes, enhanced traits of migration, stemness, drug-resistance and immunosuppression. Further analysis of the miR-18a targets highlighted possible hypoxia-inducible factor 1-alpha (HIF-1α)-mediated signalling in these tumours. This is a foremost report that validates the dual role of miR-18a in breast cancer that is subtype-specific based on hormone receptor expression. The study also features a novel association of low miR-18a levels and subsequent enrichment of hybrid E/M cells, increased migration and stemness in a subgroup of ER-negative tumours that may be attributed to HIF-1α mediated signalling. The results highlight the possibility of stratifying the ER-negative disease into clinically relevant groups by analysing miRNA signatures. Full article

Toxoplasma gondii is a zoonotic pathogen and the ingestion of tissue cysts by consumption of lamb or mutton has been identified as a possible cause of infection in humans. Many serological surveys in sheep have been performed, showing relevant serological rates; however, while the detection of antibodies indicates an exposure to T. gondii, this does not necessarily imply the presence of tissue cysts in edible tissue. The current study aims to provide further understanding on the occurrence of T. gondii in sheep muscles and the strength of correlation between serological positivity and presence of the parasite in sheep. From 349 sheep, samples (i.e., blood, heart and diaphragm) were collected and subjected to ELISA tests, real-time PCR and histological tests. Despite the high seroprevalence, T. gondii DNA was detected in the heart and/or the diaphragm from 13 out of the 349 tested sheep (3.7%); all were adults (13/191). Furthermore, the histological tests did not reveal the presence of T. gondii tissue cysts in any of the examined portions of interventricular septum. It should be considered that the likelihood of detecting genetic material of the parasite is probably influenced by the uneven distribution of the tissue cysts in the carcass as well as the methodology applied. The findings of this study support the importance of describing the uncertainty associated with the data used for risk assessment to reduce inaccurate estimation or risk overestimation. Full article

Classical Hodgkin Lymphoma (cHL) is a highly curable disease, but around 20% of patients experience progression or relapse after standard frontline chemotherapy regimens. Salvage regimens followed by autologous stem cell transplants represent the historical treatment approach for these cases. In the last decade, with the increasing understanding of cHL biology and tumor microenvironment role in disease course, novel molecules have been introduced in clinical practice, improving outcomes in the relapsed/refractory setting. The anti-CD30 antibody-drug conjugated brentuximab vedotin and PD-1/PD-L1 checkpoint inhibitors represent nowadays curative options for chemorefractory patients, and randomized trials recently demonstrated their efficacy in frontline immune-chemo-combined modalities. Several drugs able to modulate the patients’ T-lymphocytes and NK cell activity are under development, as well as many anti-CD30 chimeric antigen receptor T-cell products. Multiple tumor aberrant epigenetic mechanisms are being investigated as targets for antineoplastic compounds such as histone deacetylase inhibitors and hypomethylating agents. Moreover, JAK2 inhibition combined with anti-PD1 blockade revealed a potential complementary therapeutic pathway in cHL. In this review, we will summarize recent findings on cHL biology and novel treatment options clinically available, as well as promising future perspectives in the field. Full article

Experimental validation of computational simulations is important because it provides empirical evidence to verify the accuracy and reliability of the simulated results. This validation ensures that the simulation accurately represents real-world phenomena, increasing confidence in the model’s predictive capabilities and its applicability to practical scenarios. The use of musculoskeletal models in orthopedic surgery allows for objective prediction of postoperative function and optimization of results for each patient. To ensure that simulations are trustworthy and can be used for predictive purposes, comparing simulation results with experimental data is crucial. Although progress has been made in obtaining 3D bone geometry and estimating contact forces, validation of these predictions has been limited due to the lack of direct in vivo measurements and the economic and ethical constraints associated with available alternatives. In this study, an existing commercial surgical training station was transformed into a sensorized test bench to replicate a knee subject to a total knee replacement. The original knee inserts of the training station were replaced with personalized 3D-printed bones incorporating their corresponding implants, and multiple sensors with their respective supports were added. The recorded movement of the patella was used in combination with the forces recorded by the pressure sensor and the load cells, to validate the results obtained from the simulation, which was performed by means of a multibody dynamics formulation implemented in a custom-developed library. The utilization of 3D-printed models and sensors facilitated cost-effective and replicable experimental validation of computational simulations, thereby advancing orthopedic surgery while circumventing ethical concerns. Full article

French Guiana is a French territory in South America. The exposome of persons living there is quite different from that in mainland France and the ethnic make-up of the population is also quite different. Poverty is also widespread with difficulties in accessing care magnified by the low medical-professional density. In this singular context, we aimed to measure the incidence of pediatric cancers and to compare it with other continents. We used French Guiana’s certified cancer registry to study this between 2003 and 2017. Incidences were standardized using the world population with three strata: 0–4 years, 5–9 years, and 10–14 years. There were 164 solid tumors or hematologic malignancies diagnosed in children under the age of 15 (92 in boys and 72 in girls). Over the study period, the standardized incidence rate was 14.1 per 100,000 among children aged under 15 years. There was no significant trend during the study period. The three most common causes of cancer were leukemias—mostly lymphoblastic—CNS tumors, and sarcoma. The standardized incidence of pediatric cancers in French Guiana was similar to those in Western Europe and North America. As others have discovered, we found that males tended to be more likely to develop cancer, notably leukemia, CNS tumors, sarcoma, and retinoblastoma. As elsewhere, the predominant cancer types changed with age. Our initial assumption was that given the singular context of French Guiana, there may have been differences in pediatric cancer incidences. Here we showed that overall, contrary to our assumption and to trends in tropical countries, the incidence of pediatric cancers was in a range between Western Europe and North America with some apparent but non-significant differences in the main types of cancers observed in global statistics. Quality cancer registry data in this tropical region confirm the suspicion that lower incidences in tropical low- and middle-income countries are likely to result from incomplete diagnosis and data collection. Full article

With the rapid development of electric vehicles (EVs) in Chinese cities, accurately forecasting the number of EVs used by urban residents in the next five years and more long term is beneficial for the government to adjust industrial policies of EVs, guide the rational planning of urban charging facilities and supporting distribution network, and achieve the rational and orderly development of the EV industry. The paper considers the advantages of using the grey GM(1,1) prediction model to predict the short-term ownership of EVs by urban residents. Then, by forecasting the number of EV users in a certain city in the future and predicting the number of private vehicles in the future, the boundary conditions for long-term year ownership of EVs by residents are determined. Combined with historical data and short-term forecast data generated by the grey prediction model, the model parameters that include the innovation coefficient and imitation coefficient of the Bass model are trained using a genetic algorithm. Finally, the Bass model is used for medium- to long-term ownership forecasting from 2023 to 2040. The prediction error for the target year is provided. The simulation results indicate that the ownership of resident EVs in this city will experience rapid growth in the next five years. Full article

We present the use of interconnected optical mesh networks for early earthquake detection and localization, exploiting the existing terrestrial fiber infrastructure. Employing a waveplate model, we integrate real ground displacement data from seven earthquakes with magnitudes ranging from four to six to simulate the strains within fiber cables and collect a large set of light polarization evolution data. These simulations help to enhance a machine learning model that is trained and validated to detect primary wave arrivals that precede earthquakes’ destructive surface waves. The validation results show that the model achieves over 95% accuracy. The machine learning model is then tested against an M4.3 earthquake, exploiting three interconnected mesh networks as a smart sensing grid. Each network is equipped with a sensing fiber placed to correspond with three distinct seismic stations. The objective is to confirm earthquake detection across the interconnected networks, localize the epicenter coordinates via a triangulation method and calculate the fiber-to-epicenter distance. This setup allows early warning generation for municipalities close to the epicenter location, progressing to those further away. The model testing shows a 98% accuracy in detecting primary waves and a one second detection time, affording nearby areas 21 s to take countermeasures, which extends to 57 s in more distant areas. Full article