Quality Checks Research Articles

Seismic net-to-gross estimation for a geologic model update: A case study from a turbidite lobe reservoir in the deepwater of the Niger Delta

Geologic model updates are routinely performed in mature fields to obtain improved descriptions of facies distributions and reservoir properties such as volume of shale, net to gross (NTG), and porosity, for better understanding of the static and dynamic behaviors of reservoirs for effective well placement, improved production, and monitoring. A simple but integrated seismic NTG estimation approach, using detuned seismic amplitudes is used in guiding NTG modeling during the geologic model update of a thin turbidite lobe reservoir in a mature oil field in the deep offshore Niger Delta. The objective is to address NTG overestimation and gross rock volume (GRV) uncertainty in a previous model arising from seismic amplitude tuning effects. A seismic NTG approach is chosen relative to sophisticated deterministic or stochastic inversion techniques to avoid tuning effects, which usually bias NTG estimates in thin turbidite reservoirs. The primary data set is a 2019 reprocessed prestack depth-migrated (PSDM) seismic data vintage, which had better resolution, higher signal-to-noise ratio, and more appropriate angle-stack apertures for amplitude variation with angle fidelity, than the older 2011 PSDM seismic data that are used in the previous geologic model. The methodology involved rock-physics analysis, seismic data quality checks (QCs), tuned area determination, detuning of composite seismic amplitudes of the top and base reservoir, and their direct calibration to NTG at wells. Good correlations are obtained between the detuned composite seismic amplitudes and NTG at wells. The seismic NTG map shows good calibrations at wells and provides a robust trend for net sand modeling in the oil pool and aquifer. Static model QCs and dynamic simulations prove that the seismic NTG attribute addressed the GRV uncertainty in the earlier model, thus giving confidence for using the updated model for the planning and geosteering of infill wells, sand completions, reservoir monitoring, and production.

A precise performance-based reimbursement model for the multi-centre NAPKON cohorts – development and evaluation

Fair allocation of funding in multi-centre clinical studies is challenging. Models commonly used in Germany - the case fees (“fixed-rate model”, FRM) and up-front staffing and consumables (“up-front allocation model”, UFAM) lack transparency and fail to suitably accommodate variations in centre performance. We developed a performance-based reimbursement model (PBRM) with automated calculation of conducted activities and applied it to the cohorts of the National Pandemic Cohort Network (NAPKON) within the Network of University Medicine (NUM). The study protocol activities, which were derived from data management systems, underwent validation through standardized quality checks by multiple stakeholders. The PBRM output (first funding period) was compared among centres and cohorts, and the cost-efficiency of the models was evaluated. Cases per centre varied from one to 164. The mean case reimbursement differed among the cohorts (1173.21€ [95% CI 645.68–1700.73] to 3863.43€ [95% CI 1468.89–6257.96]) and centres and mostly fell short of the expected amount. Model comparisons revealed higher cost-efficiency of the PBRM compared to FRM and UFAM, especially for low recruitment outliers. In conclusion, we have developed a reimbursement model that is transparent, accurate, and flexible. In multi-centre collaborations where heterogeneity between centres is expected, a PBRM could be used as a model to address performance discrepancies.Trial registration: https://clinicaltrials.gov/ct2/show/NCT04768998; https://clinicaltrials.gov/ct2/show/NCT04747366; https://clinicaltrials.gov/ct2/show/NCT04679584.

Otb: an automated HiC/HiFi pipeline assembles the Prosapia bicincta Genome.

The implementation of a new genomic assembly pipeline named only the best (otb) has effectively addressed various challenges associated with data management during the development and storage of genome assemblies. otb, which incorporates a comprehensive pipeline involving a setup layer, quality checks, templating, and the integration of Nextflow and Singularity. The primary objective of otb is to streamline the process of creating a HiFi/HiC genome, aiming to minimize the manual intervention required in the genome assembly process. The 2-lined spittlebug, (Prosapia bicincta, Hemiptera: Cercopidae), a true bug insect herbivore, serves as a practical test case for evaluating otb. The 2-lined spittlebug is both a crucial agricultural pest and a genomically understudied insect belonging to the order Hemiptera. This insect is a significant threat to grasslands and pastures, leading to plant wilting and phytotoxemia when infested. Its presence in tropical and subtropical regions around the world poses a long-term threat to the composition of plant communities in grassland landscapes, impacting rangelands, and posing a substantial risk to cattle production.

Despite short-lived changes, COVID-19 pandemic had minimal large-scale impact on citizen science participation in India

ABSTRACT Many parts of the world lack the large and coordinated volunteer networks required for systematic monitoring of bird populations. In these regions, citizen science (CS) programs offer an alternative with their semi-structured data, but the utility of these data are contingent on how, where, and how comparably birdwatchers watch birds, year on year. Trends inferred from the data can be confounded during years when birdwatchers may behave differently, such as during the COVID-19 pandemic. We wanted to ascertain how the data uploaded from India to one such CS platform, eBird, were impacted by this deadly global pandemic. To understand whether eBird data from the pandemic years in India are comparable to data from adjacent years, we explored several characteristics of the data, such as how often people watched birds in groups or at public locations, at multiple spatial and temporal scales. We found that the volume of data generated increased during the pandemic years 2020–2021 compared to 2019. Data characteristics changed largely only during the peak pandemic months (April–May 2020 and April–May 2021) associated with high fatality rates and strict lockdowns. These changes in data characteristics (e.g., greater site fidelity and less group birding) were possibly due to the decreased human mobility and social interaction in these periods. The data from the remainder of these restrictive years remained similar to those of the adjacent years, thereby reducing the impact of the aberrant peak months on any annual inference. Our findings show that birdwatchers in India as contributors to CS rapidly returned to their pre-pandemic behavior, and that the effects of the pandemic on birdwatching effort and birdwatcher behavior are scale- and context-dependent. In summary, eBird data from the pandemic years in India remain useful for abundance trend estimation and similar large-scale applications, but will benefit from preliminary data quality checks when utilized at a fine scale.

Статистичні тести для перевірки незалежності випадкових величин, що описують генерацію послідовностей в криптоалгоритмах

When a crypto-primitive, whose functions include the generation of a random/pseudo-random gamma, is admitted to operation, a necessary part of its quality checking is a sta-tistical testing of its output gamma and, often, intermediate gamma(s). Such requirement is applied, for example, to random/pseudo-random number generators (RNG/PRNG), stream ciphers, and block ciphers in different "stream" modes (such as OFB, CBC, etc). There exist widely used and well-known tools for checking the statistical properties of se-quences and generators, which are based on a set of statistical tests, like NIST STS set, Diehard, etc. At the same time, the other and very similar question, about independence of the se-quences (more precisely — independence of the corresponding random variables, that the considered sequences are their realizations) generated in such cryptoalgorithms, usually doesn’t attract enough attention. Nevertheless, it is also of great importance, because the dependence of the sequences can lead to predictability of the output gamma, which makes the cryptoprimitive vulnerable to statistical attacks. Therefore, there are no adequate and suitable tools for checking independence of different sequences, generated in the algo-rithms. In this work we deve¬loped and justified new set of three statistical tests for check-ing independence of random va¬riables, which realizations are internal or output sequences in encryption algorithms or RNG/PRNG. We also calculated reference values for limit sta-tistics for different parameters of sequences and different significance levels of tests. Re-sults of tests applications for independent and dependent random variables are given, which confirm correctness of proposed tests.

Who’s testing and who’s being tested: A cautionary tale of citizen science within applied animal behaviour science

Citizen science has become a popular means to collect data in many research fields, including animal behaviour science. Using this approach has numerous potential benefits (e.g. larger sample sizes, decreased strain on resources, increasing the public’s engagement in science), but there are also issues and assumptions relating to data quality that should be considered. The aim of this study was to assess the reliability of a battery of game-like tests developed to assess behavioural flexibility in dogs. The battery was administered to samples of shelter dogs and owned dogs who had remained in homes long-term. From the two populations, four test groups were created: shelter dogs assessed by the principal investigator (n=85), shelter dogs assessed by shelter staff/volunteers (n=34), long-term owned dogs assessed by the principal investigator (n=21), and long-term dogs assessed by their owners (n=29). Shelter staff/volunteers and dog owners participated as “citizen scientists”. It is accepted that using less skilled “citizen” researchers increases the error within the data, but often claimed that this is offset by larger sample sizes. This implies that the increased error is random and not systematic. Whether who (citizen versus trained researcher) tested the group in a given context was associated with overall test item outcomes was evaluated. In two of the tests, the Alone Time Test and the Three-Toy Test, tester was found to be associated with outcomes. In the Alone Time Test, tester was associated with four items in the shelter dog samples and with three in the long-term owned dog samples. In the Three Toy Test, a series of subsequent items were contingent on the first, and the outcome of that initial item was related to tester. These results demonstrate that it is unwise to assume that the increased error from citizen science work is largely random and thus evened out by the use of a large sample of researchers. Unexpected systematic error might arise within citizen science projects so controls need to be introduced to test for these effects, so that unsound assumptions are not made. There may also be relatively unique factors, beyond researcher objectivity, to consider when using a citizen science approach to study domestic dogs, such as the bidirectional influence on behaviour of any emotional bond between the owner or shelter staff/volunteer and the dog being tested. These results highlight the need for quality checks and preliminary analysis to ensure the identification of any relevant tester effects.

Comparison of Activation Function Performance in the Resnet Algorithm for Rice Type Classification

Quality checking of rice seed varieties (Oryza sativa) is an important procedure for quality assessment in the agricultural sector. The application of transfer learning algorithms has shown good results in image recognition tasks, so this algorithm is suitable for classifying rice variety images automatically. The data classes to be analyzed are Arborio, Basmati, Ipsala, Jasmine and Karacadag based on morphological, shape and color features analysis using the ResNet algorithm. The experiment used three types of models, namely ResNet-TopHat-ReLU, ResNet-TopHat-LeakyReLU and ResNet-TopHat-eLU. The ResNet-TopHat-eLU model is the best model with training accuracy of 96.61%, validation accuracy of 95.12% and testing accuracy of 78.17%.

Enhancing Reliability in Automated Pavement Condition Data with a Data Quality Check Approach for Highway Agencies

Automated methods have been widely used by highway agencies to collect pavement condition data. However, there are still accuracy and precision issues associated with the reliability of the existing automated data collection methods. Therefore, this research aims to develop data quality check procedures to improve the reliability of automated pavement condition data for highway agencies. The study comprises three main components: identification of data quality check indexes; establishment of data quality thresholds; and implementation of data quality check procedures. Annual pavement rating data collected by a vendor using automated technologies and manual audit data from an independent third party were utilized to develop thresholds and test the procedures. Three districts, including two urban and one rural districts in Texas, were selected for the data quality check implementation. The results indicate that the proposed procedures, along with defined indexes and thresholds, efficiently identify pavements with data quality issues at both the section level and the county level. By pinpointing problematic areas, highway agencies can allocate resources for quick quality checks, enhancing the accuracy and precision of automated pavement condition data. The study can help highway agencies enhance the accuracy and precision of automated pavement condition data, ultimately leading to improvements in their pavement conditions.

First findings of Sarcocystis species in game deer and feral pigs in Australia

Several wild game meat species, including deer and feral pigs are hunted and consumed in Australia. Feral pigs and deer are not indigenous to Australia, but they have proliferated extensively and established their presence in every state and territory. Following the report of a sambar deer displaying Sarcocystis like white cysts in its rump muscles, the present study was conducted to explore the prevalence of Sarcocystis infections in wild deer and feral pigs in the southeastern regions of Australia. Oesophagus, diaphragm, and heart tissue from 90 deer and eight feral pigs were examined visually for sarcocysts. All results were negative. PCR testing of randomly selected deer and feral pigs yielded positive results, which were subsequently supported by histopathology. This is the first study to report the presence of Sarcocystis spp. in deer and feral pigs in Australia. As no visual cysts were found on the heart or oesophagus that came back positive with PCR, infected animals, particularly those reared free-range, could be passing through meat quality checks unidentified. If people consume this meat without cooking it properly, it may lead to a human infection of Sarcocystis. However, a more targeted study focused on determining the parasite's prevalence and assessing its risks is necessary to determine if it constitutes a food safety issue. As this species has been found not only in feral pigs but also in domestic pigs, the potential for infection spreading between feral pigs and pigs in free-range livestock systems is high, potentially posing a large problem for the Australian pork industry, particularly with the increased emphasis on free-range pig husbandry. Future studies should concentrate on determining the species of Sarcocystis in feral animals commonly consumed as game meat to determine potential zoonotic risks. This could also include a more in-depth look at the prevalence of Sarcocystis infections in other game animals. Identifying where these parasites are present and to what extent, are important areas for future studies.

Relationship between infiltration of tissue-resident memory T cells (TRM) in head and neck squamous cell carcinoma (HNSCC) tissue and localization and age.

6089 Background: Elevated levels of tumor-infiltrating lymphocytes (TILs) have been correlated with improved survival rates in cancer patients. Among TIL subgroups, tissue-resident memory T cells (TRM, CD8+CD103+) are recognized as pivotal contributors to the anti-cancer immune response. In this study, we aimed to evaluate TRM presence in Head and Neck Squamous Cell Carcinoma (HNSCC) tissue utilizing a developed tissue microarray (TMA) and a multiplex immunohistochemistry (MxIHC) approach. Methods: HNSCC cases from Southampton Hospital spanning the years 2000 to 2016 were reviewed, resulting in the identification of approximately 300 cases with sufficient primary tumor material. A TMA was constructed by triplicate coring of marked tumor areas on all slides. Subsequently, MxIHC, incorporating markers such as CD8 and CD103, was performed using a stain-scan-strip methodology. Digital image analysis software was employed to analyze scanned slides, and a quality check (QC) was conducted. Results: Following QC, 193 primary tumors remained (hypopharynx and larynx: n = 28, lip and oral cavity: n = 51, oropharynx: n = 114). Significantly higher counts of CD8 T cells and TRM were observed in the combined group of oropharynx, lip and oral cavity compared to the combined group of larynx and hypopharynx. This significance persisted even after excluding HPV negative oropharynx cases. HNSCC of the lip and oral cavity itself had statistically more TRM than larynx and hypopharynx. No differences were found in the subgroups between tonsil and tongue base. Stratifying the analysis by age revealed a statistically significant increase in TRM infiltration in HNSCC among young patients (≤50 years) compared to the 51-60 years and 61-70 years age groups, a pattern not observed for CD8 alone. Conclusions: This study underscores the importance of HNSCC heterogeneity and highlights the impact of age on immune infiltration, emphasizing the unique contribution of TRM in the anti-cancer immune response.

Tumor microbiome differences in early-onset versus average-onset pancreatic adenocarcinoma.

4016 Background: The rise in early-onset gastrointestinal cancers includes an increased risk of pancreatic adenocarcinoma (PDAC), but the underlying pathogenesis is incompletely understood. The tumor microbiome is an increasing focus of research given its impact on tumor pathogenesis and outcomes. We evaluated microbiome profiles in resected specimens from early-onset PDAC (eoPDAC) and average-onset PDAC (aoPDAC). Methods: PDAC specimens were selected consecutively from Cleveland Clinic and Roswell Park Cancer Institute biorepositories and categorized on age at diagnosis ( < 50 years defined as eoPDAC, and > 50 years as aoPDAC). The tissue microbiome was characterized using shotgun metagenomic sequencing. Alpha diversity, denoting the richness and evenness of microbial species within a specific sample, was compared using the Wilcoxon rank-sum test. The differential test of Beta-diversity distances (Bray Curtis distance), representing microbial taxonomic differences between the specimens was performed using Permutational MANOVA. All p-values were adjusted for multiple testing. Results: The study comprised 44 individuals with resected PDAC (24 eoPDAC and 20 aoPDAC). After quality checks, 63 tissue specimens were selected for analysis (13 tumor and 10 adjacent normal specimens for eoPDAC, 20 each of tumor and adjacent normal specimens for aoPDAC). eoPDAC tumor demonstrated significantly higher alpha diversity compared to adjacent normal tissue (P = 0.02) and aoPDAC (P = 0.0062) while aoPDAC did not (tumor vs normal alpha diversity P = 0.31). Beta diversity analysis demonstrated significantly different diversity of genera between all the groups (P < 0.05). Consistent with this finding, the majority of the species - 259/302 (85.8%) in eo vs aoPDAC comparison and 262/366 (71.6%) for eoPDAC vs normal comparison did not overlap. Differential abundance analysis revealed a significant variation of tumor microbiome in eoPDAC vs aoPDAC (P < 0.05). Prevalent bacterial genera (tumor specimens) are listed in the Table. eoPDAC tumor tissues were enriched in Enterobacter, Neisseria,and Escherichia genera, while aoPDAC tumor tissues were enriched in Klebsiella and Bacillus genera. Conclusions: eoPDAC has a distinct microbiome profile compared to aoPDAC. The correlation with several microbial genera associated with pancreatic diseases is a significant finding and warrants further exploration. This is relevant considering the rising incidence of eoPDAC of unknown etiology, and ongoing efforts to develop microbiome-based biomarkers for screening and treatment. [Table: see text]

Home-Based EEG Hyperscanning for Infant-Caregiver Social Interactions.

Prior hyperscanning studies that record the brain activities of caregivers and children concurrently have primarily been conducted within the confines of the laboratory, thus limiting the generalizability of results to real-life settings. Here, a comprehensive protocol for capturing synchronized electroencephalography (EEG), electrocardiography (ECG), and behavioral recordings from infant-caregiver dyads during various interactive tasks at home is proposed. This protocol demonstrates how to synchronize the different data streams and report EEG data retention rates and quality checks. Additionally, critical issues and possible solutions with respect to the experimental setup, tasks, and data collection in home settings are discussed. The protocol is not limited to infant-caregiver dyads but can be applied to various dyadic constellations. Overall, we demonstrate the flexibility of EEG hyperscanning setups, which allow experiments to be conducted outside of the laboratory to capture participants' brain activities in more ecologically valid environmental settings. Yet, movement and other types of artifacts still constrain the experimental tasks that can be performed in the home setting.

ChatGPT-generated help produces learning gains equivalent to human tutor-authored help on mathematics skills.

Authoring of help content within educational technologies is labor intensive, requiring many iterations of content creation, refining, and proofreading. In this paper, we conduct an efficacy evaluation of ChatGPT-generated help using a 3 x 4 study design (N = 274) to compare the learning gains of ChatGPT to human tutor-authored help across four mathematics problem subject areas. Participants are randomly assigned to one of three hint conditions (control, human tutor, or ChatGPT) paired with one of four randomly assigned subject areas (Elementary Algebra, Intermediate Algebra, College Algebra, or Statistics). We find that only the ChatGPT condition produces statistically significant learning gains compared to a no-help control, with no statistically significant differences in gains or time-on-task observed between learners receiving ChatGPT vs human tutor help. Notably, ChatGPT-generated help failed quality checks on 32% of problems. This was, however, reducible to nearly 0% for algebra problems and 13% for statistics problems after applying self-consistency, a "hallucination" mitigation technique for Large Language Models.

Transparency, reproducibility, and replicability of pharmacoepidemiology studies in a distributed network environment.

Our objective is to describe how the U.S. Food and Drug Administration (FDA)'s Sentinel System implements best practices to ensure trust in drug safety studies using real-world data from disparate sources. We present a stepwise schematic for Sentinel's data harmonization, data quality check, query design and implementation, and reporting practices, and describe approaches to enhancing the transparency, reproducibility, and replicability of studies at each step. Each Sentinel data partner converts its source data into the Sentinel Common Data Model. The transformed data undergoes rigorous quality checks before it can be used for Sentinel queries. The Sentinel Common Data Model framework, data transformation codes for several data sources, and data quality assurance packages are publicly available. Designed to run against the Sentinel Common Data Model, Sentinel's querying system comprises a suite of pre-tested, parametrizable computer programs that allow users to perform sophisticated descriptive and inferential analysis without having to exchange individual-level data across sites. Detailed documentation of capabilities of the programs as well as the codes and information required to execute them are publicly available on the Sentinel website. Sentinel also provides public trainings and online resources to facilitate use of its data model and querying system. Its study specifications conform to established reporting frameworks aimed at facilitating reproducibility and replicability of real-world data studies. Reports from Sentinel queries and associated design and analytic specifications are available for download on the Sentinel website. Sentinel is an example of how real-world data can be used to generate regulatory-grade evidence at scale using a transparent, reproducible, and replicable process.

Evaluating of the accuracy of the DTU22MDT mean dynamic topography model based on the tidal gauge data in Vietnam’s coastal areas

In this study, the accuracy of the latest mean dynamic topography model (MDT), DTU22MDT, is determined based on data collected from 14 tide gauge stations along the coast of Vietnam, from the North to the South. The process of assessing the accuracy of the DTU22MDT model is carried out carefully and precisely, involving determining the model’s height at tide gauge stations, quality checks of the data, and evaluation of the model’s accuracy. The research results indicate that, compared to the local sea surface in Vietnam, the DTU22MDT model has a higher height of approximately 0.7 meters. This model represents the global MDT with the highest accuracy in Vietnam, with a mean square error of about 9.0 cm. This information provides a basis for applying the model in scientific research and practical applications, such as constructing a national height system, planning the economic development of coastal areas, generating specialized maps, designing structures, and other activities in the maritime regions of Vietnam. The method used to evaluate the accuracy of the MDT in this study can be applied to other research areas and to different MDTs.

ANALISIS PENGENDALIAN KUALITAS UNTUK MENGURANGI DEFECT PADA GLASS BOTTLE DENGAN MENGGUNAKAN METODE QUALITY CONTROL CIRCLE PT MULIAGLASS CONTAINER DIVISION CIKARANG JAWA BARAT

PT Muliaglass Container Division is a subsidiary of PT Mulia Industrindo, Tbk which is engaged in the glass industry by producing flat glass, glass block, glass packaging, and automotive safety glass as a result of its production. PT Muliaglass Container Division was founded in 1989. The quality control carried out by PT Muliaglass Container Division experienced problems in the Quality Control section or checking checkers, resulting in the defect pass rate so far exceeding the tolerance limits set by the company. There are several types of product defects in glass bottle packaging at PT Muliaglass Container Division, namely Check Ring, Check Under Ring, Leaner, Hot Mold Check, and others. To overcome the problems encountered, research is needed using the Quality Control Circle Method and Statistical Quality Control which are used to calculate how big the reasonable limit is in the product pass rate. After processing Statistical Quality Control data and knowing the number of acceptable quality labels for passing controlled defects or not, proceed with the Quality Control Circle Method, to find out what causes product defects to pass.

Zamzam Water Surpasses Global Standards in Quality and Mineral Content

This study investigates the physical, chemical, and bacteriological properties of Zamzam tap water and two popular bottled waters, "Rounaq" and "Naba' Al- Rayan," in Diyala Governorate. Conducted at Al-Rafidain University College and the Central Public Health Laboratory in Baghdad, the research analyzes taste, odor, color, pH, essential minerals, and bacterial contamination. Findings indicate that Zamzam water excels in sensory qualities and contains beneficial minerals like potassium and magnesium within safe limits, with no bacterial contamination detected. These results affirm Zamzam's superior quality and underline the necessity for regular quality checks of bottled waters to ensure public health safety. Highlights: Superior Sensory Qualities: Zamzam water was notably superior in taste, odor, and color compared to the other bottled waters tested. Mineral Content and Safety: All water samples contained essential minerals like potassium and magnesium within safe limits, confirming their nutritional value and compliance with health standards. Bacterial Purity: No bacterial or pathogenic contamination was detected in any of the water samples, ensuring their safety for consumption. Keywords: Zamzam Water, Bottled Water Quality, Mineral Content, Bacteriological Safety, Sensory Properties

Proximate and microbial quality of processed grubs of African palm weevil (<i>Rhynchophorus phoenicis</i> F., Coleoptera: Curculionidae) sold at Toru-Orua, Bayelsa State, Southern Nigeria

The African palm weevil, Rhynchophorus phoenicis F. (Coleoptera: Curculionidae) constitutes a significant component in diets of the Niger Delta of Nigeria. This study aimed to determine the proximate composition and microbiological quality of processed grubs (steamed, dried, fried and fresh which served as control) purchased from food vendors in Toru-Orua community. Proximate composition determinations followed official methods recommended by the Association of Official and Analytical Chemicals (AOAC), while microbial load was determined by total plate count. Steamed grubs had the highest moisture content of 15% while fresh had the least moisture content of 9.3%. Steamed grubs had the highest ash content of 11.47% while fresh had the least ash content of 4.73%. Fresh grubs had the highest crude protein of 41.75% while fresh had the least crude protein of 30.13%. Steamed grubs had the highest crude fibre content of 18.07% while fresh had the least crude fibre of 13.7%. Steamed and fried grubs had the highest crude fat content of 10.93% while fresh had the least crude fat content of 2.8%. Steamed grubs had the highest moisture content of 28.35% while dried grubs had the least moisture content of 20.66%. The total heterotrophic bacteria count ranged from 8.5 x 102 CFU/g – 3.7 x 106 CFU/g. Fungal count ranged from 2.2 x 102 - 3.4 x 103 CFU/g. The microbial investigations showed Pseudomonas aeruginosa, Escherichia coli and Staphylococcus aureus were the common microorganisms on the grubs. Frequent microbiological quality checks on such ready-to-eat foods, along with public enlightenment campaigns for food vendors is recommended, to guarantee food safety for consumers during processing/handling, storage and consumption.

Real-time quality assurance and quality control for a high frequency radar network

This paper recommends end to end quality assurance methods and quality control tests for High Frequency Radar Networks. We focus on the network that is operated by the Mid Atlantic Regional Association Coastal Ocean Observing System (MARACOOS). The network currently consists of 38 radars making real-time measurements of the surface currents over the continental shelf for a variety of applications including search and rescue planning, oil spill trajectory modelling and providing a transport context for marine biodiversity observing networks. MARACOOS has been delivering surface current measurements to the United States Coast Guard (USCG) since May 2009. Data quality is important for all applications; however, since the USCG uses this surface current information to plan life-saving missions, delivery of the best quality data is crucial. We have mapped the components of the HF radar data processing chain onto the data levels presented in the NASA Earth Science Reference Handbook and have applied quality assurance and quality control techniques at each data level to achieve the highest quality data. There are approximately 400 High Frequency radars (HFRs) deployed globally and the presented techniques can provide a foundation for data quality checks and standardization of the data collected by the large number of systems operating today.

Critical Role of Manufacturing Execution Systems in Digital Transformation of Manufacturing Industry

The manufacturing industry is undergoing a significant digital transformation, propelled by advancements in technology. Central to this evolution is the implementation of Manufacturing Execution Systems (MES), which act as a vital link between the shop floor and enterprise-level systems. This paper explores the critical role of MES in the digital transformation of the manufacturing industry, focusing on how it enhances operational efficiency, improves product quality, and enables real-time decision-making. Manufacturing Execution Systems are software platforms designed to monitor, control, and optimize production processes from the initiation of orders to the delivery of finished goods. MES provides real-time data on production activities, enabling manufacturers to make informed decisions, reduce production costs, and increase overall productivity. The integration of MES with advanced technologies such as the Internet of Things (IoT), Big Data analytics, and cloud computing has further amplified its impact, leading to smarter and more agile manufacturing processes. One of the key benefits of MES is its ability to improve operational efficiency. MES offers real-time visibility into the production process, allowing manufacturers to identify and resolve bottlenecks, minimize downtime, and optimize resource utilization. Predictive maintenance capabilities, enabled by IoT integration, prevent unexpected equipment failures and reduce maintenance costs. MES also plays a crucial role in enhancing product quality. By monitoring each stage of production, MES ensures adherence to quality standards and facilitates traceability. In the event of a quality issue, MES allows for quick identification of the root cause and implementation of corrective actions. Real-time quality checks at critical points in the production process help detect and address defects promptly. Moreover, MES supports real-time decision-making by providing up-to-date data that allows production managers to respond swiftly to changes in demand or production conditions. This agility is essential in today's fast-paced manufacturing environment. In conclusion, Manufacturing Execution Systems are indispensable in the digital transformation of the manufacturing industry. By improving efficiency, product quality, and decision-making capabilities, MES equips manufacturers to succeed in the era of Industry 4.0. This paper highlights the benefits and challenges of MES implementation, offering valuable insights for manufacturers aiming to leverage MES in their digital transformation efforts