Essential Data Research Articles

Mount SMB.pcap: Reconstructing file systems and file operations from network traffic

File system and network forensics are fundamental in forensic investigations, but are often treated as distinct disciplines. This work seeks to unify these fields by introducing a novel framework capable of mounting network captures, enabling investigators to seamlessly browse data using conventional tools. Although our implementation supports various protocols such as HTTP, TLS, and FTP, this work will particularly focus on the complexities of the Server Message Block (SMB) protocol, which is fundamental for shared file system access, especially within local networks.For this, we present a detailed methodology to extract essential file system data from SMB network traffic, aiming to reconstruct the share's file system as accurately as the original. Our approach goes beyond traditional tools like Wireshark, which typically only extract individual files from SMB transmissions. Instead, we reconstruct the entire file system hierarchy, retrieve all associated metadata, and handle multiple versions of files captured within the same network traffic. In addition, we also investigate how file operations impact SMB commands and show how these can be used to accurately recreate user activities on an SMB share based solely on network traffic. Although both methodologies and implementations can be applied independently, their combination provides investigators with a comprehensive view of the reconstructed file system along with the corresponding user activities extracted from network traffic.

An intelligent character segmentation system coupled with deep learning based recognition for the digitization of ancient Tamil palm leaf manuscripts

Palm-leaf manuscripts, rich with ancient knowledge in areas such as history, art, and medicine, are vital cultural treasures, making their digitization essential for preserving this heritage. Digitization of these organic and fragile manuscripts is required to safeguard the essential ancient data. This requires optimal character segmentation and recognition algorithms. A limited number of studies have been carried out in Tamil character recognition in literature. Handling row-overlapped characters, noise introduced due to lightning issues, and dirt, as well as the removal of punch holes, auto-cropping the content, filtering out noisy or improper segmentation, etc. are the essential concerns carried out in our proposed work. This work is executed as a four-step process (1) Palm Leaf Manuscript Acquisition (2) Pre-Processing (3) Segmentation of Tamil Characters and (4) Tamil Character Recognition. During acquisition, the scanners are used for recording palm leaf manuscripts from the Tamil Nadu-oriented manuscript library. In the Pre-processing step, the Fast Non-Local Means (Fast-NLM) method, paired with median filtering is used for Denoising the scanner output image. Later, the pixels that make the characters and borders (i.e., the foreground) are identified using Sauvola thresholding. The proposed methodology introduces efficient techniques to remove Punch hole impressions from the pre-processed image, and to crop the written content from the edges. After pre-processing, the Segmentation of Tamil Characters is performed as a three-step process (a) Manuscript (b) Line, and (c) character segmentation, which addresses conjoined lines, partially/completely empty segmentations that are not previously addressed by existing techniques. This work introduces an Augmented HPP line-splitting algorithm that accurately segments written lines, handling wrong segmentation cases that were previously not considered by existing techniques. The system achieves an average segmentation accuracy of 98.25%, which far outperforms existing techniques. It also proposes a novel Punch hole removal algorithm that can locate and remove the punch-hole impressions in the manuscript image. This algorithm, along with the automated content cropping technique, increases recognition accuracy and eliminates any manual labor needed. These features make the proposed methodology highly suitable for real-time archaeological and historical researches that include manuscripts. All 247 letters and 12 numeric digits are analyzed and separated into 125 distinct writable characters. In our work, characters are segmented and used for recognition of all 247 letters and 12 digits in Tamil using a multi-class CNN with 125 classes, which drastically reduces the complexity of the neural network compared to having 257 output nodes. It offered a notable performance of 96.04% accuracy. As compared with existing Tamil and other character recognitions, this work is effective in essence of considering real-time images and the increased number of characters used.

Evaluation of completeness of commonly used data elements for clinical trial eligibility criteria using a registry-enhanced data collection process: Results from patients with non-small cell lung cancer (NSCLC) and colorectal cancer (CRC) at three community oncology practices.

346 Background: Data elements required for clinical trial eligibility assessments are often unstandardized and incomplete in EHR making clinical research participant identification a challenging and biased process. Moreover, the absence of new patient records and disease codes results in monitoring large patient populations until records are completed. These issues can lead to missed opportunities for timely patient identification. N-Power Medicine (NPM) developed a registry-enhanced oncology network platform for unbiased, and real-time quality data collection. We report from this platform on completeness rates of key variables for eligibility assessment in NSCLC and CRC clinical trials. Methods: NPM’s platform consists of 3 parts: patient registry (Kaleido), onsite and remote staff to consent patients and ensure data completeness, quality and standardization, and technology to structure and process the data. Patients with NSCLC and CRC from 3 community oncology practices across different US regions were enrolled in Kaleido and visited the clinic between February and May 2024. Data for 11 key variables were abstracted. To minimize the need for extensive monitoring until a diagnosis was confirmed, we developed a machine learning (ML) model for lung cancer using non-C34 ICD10 codes to construct multiple classes of tunable predictive models. Results: A total of 728 (NSCLC=281, CRC=447) patients were evaluated. The male-to-female ratio was 1 for NSCLC and 1.3 for CRC and 90% of NSCLC and 68% of CRC patients were over 60 years of age. The platform achieved 99% completeness for critical data points such as diagnosis date, histology, metastatic status, recent systemic anti-cancer treatments, ECOG performance status and other cancer diagnoses with diagnosis date. 47% of NSCLC and 43% of CRC patients had metastatic disease at the time of evaluation. Over 90% of patients with metastasis had their current therapy line and relevant genomic test results successfully documented. Imaging-based cancer status completeness was 95% for NSCLC and 89% for CRC. The ML model would identify over 50% of all patients that would eventually receive a lung cancer diagnosis, with over 80% specificity up to 3 weeks before a diagnosis. Conclusions: NPM’s platform demonstrated high completeness rates for the majority of essential data elements, improving the inclusion of all eligible patients in clinical trials. The predictive ML model shows promise in identifying suitable patients before an ICD10 code is assigned, reducing the need for extensive monitoring and ensuring timely completeness of necessary assessments for eligibility. Importantly, these advancements were achieved without adding financial or resource burdens to clinical workflows.

Review of diver propulsion vehicle: A review

The ocean serves as a vital arena for resource exploitation, scientific inquiry, and strategic endeavors. Among the array of underwater propulsion technologies, diver propulsion vehicles (DPVs) stand out for their exceptional integration, concealability, and maneuverability. They hold a pivotal role in both marine scientific exploration and military operations beneath the waves, thus carrying significant research implications. However, the existing literature on DPVs remains limited, lacking comprehensive examinations of their design processes and parameters. This review systematically surveys and assesses the current landscape of DPV development and research. Three key facets—propeller design, performance assessment, and equipment engineering—are scrutinized and analyzed. By consolidating essential data from ongoing studies, this review offers valuable insights. Additionally, it forecasts potential directions and emerging focal points in the evolution of underwater propulsion for frogmen, drawing from current advancements. The objective is to furnish foundational data to support the design and study of frogman underwater propulsion systems, thereby advancing engineering applications in this domain.

Health Parameters Monitoring System

In today's society, there are an increasing number of people whose health need regular health examinations. The other category consists of people who have died or are suffering from specific diseases, the consequences of which can occur unexpectedly and result in a grave health crisis. The idea is to provide constant remote monitoring of particular patient functions that are critical to their survival, as well as the necessary assistance. The sensing of essential data related to a person's health wherever they are can be transmitted into a technical centre where it will be reviewed and understood under remote monitoring. This concept's applicability has a lot of potential. This work considers non-invasive sensors for monitoring of some physiologic parameters, data transit and processing, archiving, and visualization in addition to the aforementioned groups. This methodology served as the foundation for subsequent applied research projects established in collaboration with hospitals.

Using Dynamic Stereo X-ray Imaging for In Vivo Acromioclavicular Joint Kinematics Assessment: A Preliminary Investigation.

Acromioclavicular joint (ACJ) disruption occurs frequently in athletes engaged in contact sports. However, the current understanding of ACJ biomechanics during muscle-driven functional activities and the influence of different treatment approaches (eg, reconstruction surgery vs nonoperative methods) on ACJ kinematics and stability remains limited. The absence of precise in vivo biomechanical measurement modalities for scapular and clavicular kinematics contributes significantly to this lack of understanding. The purposes of this study were to determine whether dynamic stereo x-ray (DSX) imaging can be used to evaluate the in vivo kinematics of the ACJ and to provide preliminary comparative data on ACJ kinematics, range of motion, and isometric strength of surgically reconstructed or nonoperatively treated ACJ shoulders and their uninjured contralateral shoulders. It was hypothesized that ACJ kinematics could be measured successfully using DSX and that surgically and nonoperatively treated shoulders would show abnormal 3-dimensional (3-D) ACJ kinematics compared with the uninjured contralateral. Controlled laboratory study. In this cross-sectional study, 11 participants who had undergone unilateral ACJ reconstruction surgery and 3 patients who received nonoperative treatment were enrolled. ACJ kinematics were assessed during active forward flexion, scaption, and abduction through high-speed DSX imaging, complemented by 3-D bone models obtained via computed tomography (CT) scans. To gauge kinematic differences, a 1-dimensional statistical parametric mapping method was employed, which compared outcomes in the index limb to those in the uninjured counterpart. In addition, the range of motion and isometric strength at various abduction angles were analyzed, employing a repeated-measures analysis of variance to compare the affected and uninjured sides. Leveraging a combination of DSX imaging and patient-specific CT bone models, ACJ kinematics was measured successfully during movements along anatomic planes. Preliminary findings from this investigation revealed no detectable differences between the surgically reconstructed and uninjured sides in ACJ biomechanics, shoulder range of motion, and isometric strength outcomes. However, on average, the nonoperatively treated shoulders demonstrated increased internal rotation, upward rotation, and posterior tilting of the scapula relative to the clavicle (no statistical analyses were performed due to the small sample size). DSX imaging is a promising tool for evaluating potential in vivo kinematic abnormalities in the ACJ during muscle-driven activities, laying the groundwork for further investigations in both ACJ-reconstructed and nonreconstructed patients. This study furnished essential data for conducting power analyses and designing future studies with an adequate sample size to investigate the impact of different treatment approaches on shoulder girdle mechanics. With its potential for accurately characterizing shoulder girdle kinematics post-ACJ injury, DSX imaging can offer valuable insights for future clinical studies, facilitating informed decisions regarding the short- and long-term impacts of treatment choices on shoulder health and function.

Remote sensing assessment of wildfire using high-resolution PlanetScope satellite observations: A case study on Co Tien Mountain, Nha Trang City, Vietnam

In this study, high spatial resolution (3 m) PlanetScope (PS) imagery was utilized to map burned areas caused by a wildfire occurring on January 10, 2024, on Co Tien Mountain in Nha Trang city, Khanh Hoa province, South Central Coast of Vietnam. A pre-fire image, acquired ten days earlier, on December 31, 2023, and a post-fire one, acquired nearly one month after, on February 04, 2024, were used to create pre- and post-fire Normalized Difference Vegetation Index (NDVI) maps of the study area, then the difference of NDVI (dNDVI). A threshold (T = 0.20), proposed by the author, was applied to the histogram of the dNDVI product to classify the study area into two clusters: burned pixels (dNDVI > T) and unburned pixels (dNDVI <= T). Classification results estimate that a total of 16.11 ha of grass, reeds, small shrubs and vegetation have been burned out during the wildfire. A field trip is required to map the burned areas using unmanned aerial vehicles (UAVs) for an accurate validation of results derived purely from PS satellite observations. Although lacking a ground truth dataset for validation is a significant limitation, the proposed approach remains beneficial for local managers and decision-makers. It enables the rapid assessment of damages caused by small wildfires and provides essential data for effective disaster management and recovery planning, particularly in remote areas.

Seroprevalence of Theileria ovis in Goats from M’Sila Region, Central Algeria

Background: In Algeria, data on the epidemiology of theileriosis in small ruminants are limited. Objectives: The current study investigates the seroprevalence of Theileria spp. in goats from the M’Sila region, Central Algeria. Methods: Blood samples of 128 goats from 19 farms were collected from the locality of Maâdid. The indirect fluorescence antibody test (IFAT) was performed to test the goats’ sera for antibodies against Theileria ovis and Theileria lestoquardi. Results: Out of 128 tested samples, 21 sera (16.40%) were positive for T. ovis antibodies. All samples were seronegative for T. lestoquardi. The seroprevalence of T. ovis varied from 10% to 30% on farms. The seropositivity rates did not differ significantly with age, sex, or breeding system of goats. Tick-infested goats were significantly more seropositive than no-infested goats. Conclusion: The present study reports essential data on the epidemiology of caprine theileriosis from Central Algeria.

A novel dynamic structural adaptive multivariable grey model and its application in China's solar energy generation forecasting

Accurately predicting China's solar energy generation is crucial for energy planning and environmental protection. However, the nonlinearity and complexity of the data pose challenges to prediction. This article proposes a dynamic structural adaptive multivariate grey model to overcome these challenges. The model constructs a dynamic nonlinear correction function with an uncertain structure that can adaptively adjust to the data characteristics. Additionally, the Gaussian function is utilized to derive the time response function, overcoming the mechanism defects present in traditional multivariate grey models. The whale optimization algorithm is applied to optimize the background value of the model, improving accuracy. The model is compatible with 14 classical models via parameter changes and has strong compatibility. The results show that the fitting error and test error of the model are 0.23 % and 1.95 % respectively, which is significantly better than the other 11 methods, indicative of strong robustness and accuracy. The forecast indicates that China's solar energy generation will experience a consistent upward trajectory from 2023 to 2030, with an average annual growth rate of 12.11 %. This study significantly contributes to the advancement of the theory of multivariate grey dynamic prediction and provides essential data support for strategic planning within China's solar power industry.

Fingerprint of Plio–Quaternary detrital zircon geochronology: Implications for sediment provenances and geomorphological evolution of the Yangtze Delta

The Yangtze (Changjiang River) Delta serves as a prominent depocenter for siliciclastic sediments from the Tibetan Plateau and Yangtze Craton, providing essential data on sediment source-to-sink dynamics and geomorphological evolution of large river drainage systems. This study presents the detrital zircon geochronology of Plio–Pleistocene sediments in the Yangtze Delta, alongside the data from modern river sediments, to elucidate provenance evolution since the Pliocene. The zircon geochronology reveals a considerable shift in sediment provenance during the Pliocene–Pleistocene transition. The Pliocene sediments exhibit a straightforward and predominant zircon age spectrum characterized by a typical peak age of 100–200 Ma. This spectrum markedly differs from the modern upper–middle Yangtze River sediments but closely resembles those of local rivers in the lower Yangtze River region. This demonstrates that the Pliocene sediments originated from local mountainous rivers, indicating the paleo-Yangtze River channelization prior to the Quaternary. In contrast, the zircon age spectra of Pleistocene sediments in the present-day delta reveal several dominant age groups ranging from 11.9 ± 1 to 3643 ± 30 Ma, similar to those found in present-day upper–middle Yangtze River sediments. This implies that the Pleistocene sediments were mainly derived from the upper–middle Yangtze River, showing a diversity of source rocks with varying geological ages and origins. The presence of the upper Yangtze River provenance signal, characterized by Cenozoic (<65 Ma) zircons, in early Pleistocene strata (ca. 1.6 Ma) of the delta suggests that the paleo-Yangtze River transported Tibet-sourced sediments into the modern delta area no later than that time. These findings indicate the geomorphological evolution of the Yangtze River Delta from an intermontane basin in the Pliocene to an alluvial–fluvial plain during the Quaternary. This geomorphological and geographic evolution, along with changes in sediment source, directly reflect extensive tectonic subsidence in eastern China since the late Cenozoic.

Establishment of a rhesus macaque model for Coxsackievirus A6 infection: Pilot study to evaluate infection initiated through the respiratory or digestive track

Coxsackievirus A6 (CVA6) is a primary pathogen associated with hand, foot, and mouth disease (HFMD) and is typified by fever, rashes or herpetic lesions at distinct locations. Although HFMD patients exhibit mild symptoms, a subset of patients may develop severe complications, such as viral encephalitis, myocarditis, pneumonia, and neurological disorders. However, in addition to rodent models, such as the CVA6-infected mouse model, no definitive nonhuman primate animal model or related research or analysis tool is available, which makes the development of suitable nonhuman primate animal models particularly crucial. In this study, 3- to 4-month-old rhesus monkeys were infected via the respiratory or digestive tract, and the pathogenic, pathological, and immunological alterations following CVA6 infection were investigated. The results revealed that the infected rhesus monkeys exhibited symptoms similar to those of patients, including signs of HFMD, blood cell changes, viremia, viral excretion, and inflammatory reactions during the acute phase (1-11 days). Pathological observations revealed inflammatory reactions in the intestinal and lymph node tissues. Notably, the acute symptoms gradually waned in the recovery phase (12-120 days), and a high level of neutralizing antibodies was sustained. Intriguingly, no significant disparity was observed between the infections initiated via the respiratory or digestive tract in terms of clinical symptoms, hemogram results or virus shedding. Overall, this study yielded a comprehensive dataset regarding the physiological, pathological, and immunological outcomes of CVA6 infection in a primate host, enhancing our comprehension of the mechanism of CVA6 infection and providing essential data for related vaccine and drug development.

Supporting critical downlink traffic in LoRaWAN

LoRaWAN, a low-power wide-area network (LPWAN) technology, has been successfully used in the Internet of Things (IoT) industry over the last decade. It is an easy-to-use, long-distance communication protocol combined with minimal power consumption. Supporting critical downlink traffic in LoRaWAN networks is crucial for ensuring the reliable and efficient delivery of essential data in certain actuating applications. However, challenges arise when prioritizing critical downlink traffic, including commands, alerts, and emergency notifications that demand immediate attention from actuating devices. This paper explores strategies to improve downlink traffic delivery in LoRaWAN networks, focusing on enhancing reliability, fairness, and energy efficiency through prioritization techniques and network parameter configurations in the EU868 spectrum. Theoretical as well as simulation results provide insights into the effectiveness of the available solutions for supporting critical downlink traffic in LoRaWAN networks.

Development of a minimum data set for a blockchain-based personal health records (PHRs), for patient/physician interaction in family medicine

BACKGROUND: The primary requirement for a capable patient health record (PHR) that can interact appropriately with the family medicine system and collect and share qualified data is a minimum data set (MDS) aligned with family medicine’s functions and goals. The aim of this research was to determine the MDS for a blockchain-based PHR system that can effectively interact with family medicine providers and collect and share qualified data. This MDS is intended to be applicable to all members of the community covered by family medicine. MATERIALS AND METHODS: This applied study was conducted in 2022 in a cross-sectional and descriptive approach in three phases. In the first phase, a content analysis related to the research objectives was conducted in scientific databases, search engines, and websites of the centers and scientific research organizations with publications and policy-making in this field. Consequently, 11 studies were selected for use in the second and third phases. In the second phase, to determine information needs, a researcher-developed questionnaire including 17 classes was given to 50 people under the cover of the family medicine plan in Shiraz city. By choosing one of the two options “Yes” or “No” by them, the necessary data classes were determined. In the third phase, the second researcher-developed questionnaire was designed and administered to 100 family physicians in Shiraz city. This questionnaire included the data elements corresponding to the data classes approved in the previous phase. The family physicians were asked to rate the importance of each data element using a Likert scale with five options, ranging from “very unimportant” to “very important.” The necessary data elements were determined based on these scores. RESULTS: In the first questionnaire, 16 of the 17 data classes received approval from individuals covered by the family medicine plan. Consequently, a questionnaire comprising 16 classes and 105 data elements was administered to the family physicians. Ultimately, the MDS was determined to include 16 classes and 72 data elements. CONCLUSIONS: Determining essential data elements, especially for patient/physician interaction in family medicine, should be such that they can be managed by the person while being comprehensive and providing sufficient help to the physician during the treatment process. This MDS can be used to interact with and refer PHRs to other physicians and specialists, as well as help interoperability between the PHR and other health systems, such as hospital information systems (HIS) and electronic health records (EHRs).

Enhancing sustainable healthcare practices through energy-efficient wireless body area networks

This paper explores how the integration and performance of Wireless Body Area Networks (WBANs) contribute to sustainable healthcare practices. WBANs play a crucial role in reducing the environmental footprint of healthcare systems by providing continuous monitoring that can prevent unnecessary hospitalizations and reduce the consumption of disposable medical supplies. Additionally, the design of WBANs using environmentally friendly materials, low-power devices, and recyclable components is discussed to optimize the sustainability of healthcare practices. To enhance infrastructure, services, and quality of life, new technologies have been integrated to improve WBANs. Patients' essential health data may be continuously and instantly collected thanks to these networks, and healthcare providers can receive the data right away for quick analysis and action. WBANs have healthcare benefits, but there are also major drawbacks. Technologies that can combine low power consumption, minimal delay, and high enough data rates are needed for WBANs in order to support a variety of medical applications. The effectiveness of the LoRaWAN and IEEE 802.15.6 technologies in WBAN is assessed in this paper. With the use of seven crucial metrics which are throughput, arrival rate, delay, energy consumption, residual energy, network lifetime, and packet delivery ratio (PDR), this paper seeks to study which technology is appropriate with WBANs using NS3 as a simulation program. With network parameters, 1000 seconds, and 50 nodes, the paper evaluated the performance of each technology. The results show that IEEE 802.15.6 is superior in terms of throughput, PDR, and arrival rate whereas LoRaWAN is superior in terms of energy consumption, residual energy, network lifetime, and delay.

Analysis of Image Encryption using Triple DES

Abstract: Keeping your essential data secure in today’s world is very essential. There are different types of cyber-attacks which attackers can use to exploit your personal or confidential data for their own needs. Cryptography and its algorithms in cybersecurity has been an important part in providing secure methods to hide or encrypt information or sensitive data which only the person who was intended to be send can access it. This paper presents the triple Data Encryption Standard (DES) approach for secure image encryption from malicious users. This paper provides an efficient, easy and secure approach for encryption of images which is essential in today’s scenario.

Annual Variations of PM10, PM2.5 and PM1.0 Fraction at an Urban Site in Ansan, Korea

This study examines particulate matter (PM) concentrations, specifically PM10, PM2.5, and PM1.0, at an urban site in Ansan, South Korea. Three BAM-1020 continuous monitors measured PM10, PM2.5, and PM1.0 hourly from January to December 2021, with data acquisition rates of 97.1%, 97.3%, and 93.4%, respectively. Average annual concentrations were 45.7±48.4 µg/m³ (PM10), 26.4±22.7 µg/m³ (PM2.5), and 18.5±14.5 µg/m³ (PM1.0). PM10 was 91% of the annual air quality standard, while PM2.5 exceeded this standard by 176%, indicating severe pollution. Statistical analyses using probability density function (PDF) and cumulative distribution function (CDF) showed 98.5% of data converged at 150 µg/m³ (PM10), 75 µg/m³ (PM2.5), and 50 µg/m³ (PM1.0), with the remaining 1.5% corresponding to approximately 131 hours, annually. In 2021, all six observed yellow dust events occurred in spring (March to May). PM10, PM2.5, and PM1.0 concentrations increased from January to March, peaked in March, decreased until September, and rose again. The coarse fraction ratio increased stepwise from February to May, likely due to yellow dust and episodes of high PM concentration in the spring. The PM1.0 concentration was higher in summer and fall compared with that in spring and winter. The PM1.0/PM2.5 ratio was highest in summer and fall even though the annual PM1.0concentration was lowest, suggesting a higher secondary formation rate of fine particles during these periods. This underscores the need for further scientific investigation on PM1.0. The study provides insights into the simultaneous observation and distribution characteristics of PM10, PM2.5, and PM1.0, highlighting the mass concentration, distribution, and ratio of PM1.0. These findings are crucial for understanding PM distribution in Ansan, an industrial complex, and can serve as essential data for chemical composition comparisons, data validation, public health strategies, and cost-benefit analyses for regional PM improvement.

Annual emissions of N2O, NO, HONO, and NH3 from maize-wheat fields in the North China Plain

Fertilized agricultural soil is a significant source of gaseous nitrogen compounds (GNCs), including N2O, NO, HONO, and NH3. The North China Plain (NCP) is the “hot region” for the release of these GNCs due to intensive fertilization practices. However, existing research has primarily focused on N2O emissions from fertilized farmland in the NCP, lacking comprehensive observational studies on other GNCs. Therefore, a continuous cumulative sampling technique (open-top dynamic chamber system) was utilized in this study to simultaneously measure the exchange fluxes of N2O, NO, HONO, and NH3 over summer maize-winter wheat rotation fields in the NCP. Results showed that GNC emissions from the soil displayed distinct diurnal variations, with higher emissions during the day attributed to elevated soil temperature. However, N2O emissions remained consistent between day and night, potentially influenced not only by soil temperature but also by soil humidity. Annual cumulative emissions and emission factors (EFs) for four GNCs were determined, indicating that N2O, NO, and NH3 emissions during the maize season were 1.38–2.37 times higher than those during the wheat season, with 98 % of HONO emissions occurring in the maize season. Additionally, the study first presented the annual HONO EFs of 0.36 ± 0.03 % in fertilized farmland. Furthermore, a comparison revealed that the fluxes of N2O, NO, NH3, and HONO using the conventional single-point sampling method were 26.4 %, 13.9 %, and 8.10 % lower, and 7.86 % higher compared to the continuous cumulative sampling method recommended in this study. In general, this study provided precise measurements of GNC emissions from farmland, offering essential foundational data for modeling parameters and contributing to the formulation of regional air pollution prevention and control policies.

Prevalence Estimation of the PALB2 Germline Variant in East Asians and Koreans through Population Database Analysis.

PALB2 is a tumor suppressor gene. Heterozygous germline pathogenic variants of PALB2 significantly increase the lifetime risk of breast cancer and moderately increase the risk of ovarian and pancreatic cancers. This study analyzed the estimated prevalence of PALB2 variants globally, focusing on East Asian and Korean populations, where limited data were previously available. We examined 125,748 exomes from the Genome Aggregation Database (gnomAD), including 9197 East Asians, and additional data from 5305 individuals in the Korean Variant Archive and 1722 in the Korean Reference Genome Database. All PALB2 variants were interpreted according to guidelines from the American College of Medical Genetics and Genomics and the Clinical Genome Resource. The global prevalence of PALB2 variants was 0.18%, with the highest prevalence in Finnish populations (0.41%) and the lowest in Ashkenazi Jewish populations (0.04%). East Asians had a prevalence of 0.09%. By combining data from Korean genome databases and gnomAD totaling 8936 individuals, the overall prevalence of PALB2 variants in the Korean population was determined to be 0.13%. This study is the first comprehensive investigation of PALB2 variant prevalence in East Asians and Koreans using gnomAD and Korean genome databases. These findings provide essential reference data for future research and highlight the importance of region-specific genetic studies that will inform genetic counseling and hereditary cancer risk management.

Distribution and Ecological Risk of Ludwigia peploides in South Korea.

The number of alien species introduced into South Korea continues to increase over the years. In particular, several plants have been introduced as ornamentals. Ludwigia peploides, which is native to the Americas and Australia, is believed to have been planted as an ornamental aquatic plant called "water primrose" and "primrose". It spread to natural ecosystems through rivers, and its distribution is gradually expanding in Suwon, Hwaseong, Busan, and Jeju. However, there has been no specific study on the ecological risk of L. peploides introduced into South Korea. This study, therefore, investigates the distribution status and ecological risks of L. peploides in South Korea through field surveys and allelopathic material analysis, as well as assessing abiotic risk factors. The distribution was confirmed at a total of 19 sites, with high-density mats of a single species forming along the water's edge and on the water surface. The maximum distribution area was 13,922 m2 in Chilgok Reservoir in Anseong. Stems and plant fragments transported along waterways were continuously forming colonies through vegetative propagation. When evaluating the overall risk, it is determined that L. peploides has a high potential to cause significant damage to the ecosystem if not managed promptly. Therefore, continuous monitoring is necessary to effectively manage and prevent the habitat expansion of L. peploides. The results of this study are expected to aid in the identification of the current distribution and potential ecological risks of L. peploides in South Korea, providing essential data for ecological risk assessment and the development of effective management strategies.

A Novel Murine Model Enabling rAAV8-PC Gene Therapy for Severe Protein C Deficiency.

Severe protein C deficiency (SPCD) is a rare inherited thrombotic disease associated with high morbidity and mortality. In the current study, we established a viable murine model of SPCD, enabling preclinical gene therapy studies. By creating SPCD mice with severe hemophilia A (PROC-/-/F8-), the multi-month survival of SPCD mice enabled the exploration of recombinant adeno-associated viral vector-PC (rAAV8-PC) gene therapy (GT). rAAV8- PC (1012 vg/kg of AAV8-PC) was injected via the tail vein into 6-8-week-old PROC-/-/F8- mice. Their plasma PC antigen levels (median of 714 ng/mL, range 166-2488 ng/mL) and activity (303.5 ± 59%) significantly increased to the normal range after GT compared to untreated control animals. PC's presence in the liver after GT was also confirmed by immunofluorescence staining. Our translational research results provide the first proof of concept that an infusion of rAAV8-PC increases PC antigen and activity in mice and may contribute to future GT in SPCD. Further basic research of SPCD mice with prolonged survival due to the rebalancing of this disorder using severe hemophilia A may provide essential data regarding PC's contribution to specific tissues' development, local PC generation, and its regulation in inflammatory conditions.