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Adopting additive manufacturing in investment casting, known as rapid investment casting, can significantly reduce lead time and cost. Despite many publications on these technologies, no quantitative techno-economic analyses refer to rapid investment casting. The paper provides helpful insights and a decision-making approach for replacing conventional production technologies (i.e. wax injection) with additive manufacturing technologies. The study is based on a techno-economic analysis framework. It allows assessing key performance indicators (e.g. crossover points and payback periods) for stakeholders to decide the suitable VAT photopolymerisation processes (i.e. stereolithography, digital light processing, and material jetting) according to specific production scenarios (i.e. load factors). Analytical cost models were developed in the frame of this work to assess the time and cost of the overall manufacturing process of the resin model for investment casting, considering the post-processing stages for each of the technologies investigated. The cost models were used to assess the benefits introduced by additive manufacturing in rapid investment casting. A sensitivity analysis evaluated the impact of energy, material, and labour costs for both key performance indicators (crossover points and payback periods). The techno-economic analysis yielded the following results: (i) crossover points in terms of production costs vary, ranging from thousands of units for small components in the jewellery or fashion industries to a few dozen units for larger parts in the mechanical industry, and (ii) crossover points in terms of time are lower than those related to cost. Additionally, digital light processing is regarded as the most promising technology, offering the best crossover points and payback periods across various scenarios, mainly when 3D printers are used at a low utilisation rate. [ABSTRACT FROM AUTHOR]

Protein aggregation is challenging for biopharmaceutical drug, because it affects the stability of protein formulations in real-time. However, current techniques for protein aggregate indication meet a number of limitations including limited aggregate size range, complex pre-treatments and lack of chromatographic approaches. Herein, a rapid, automatic, non-invasive and wide-scale coverage technique for aggregates indication is developed to overcome these challenges. Firstly, the response of low-field nuclear magnetic resonance (LF-NMR) to the aggregates is explored by making a comparison with certain established techniques. LF-NMR achieves a high sensitivity of water proton transverse relaxation rate (R 2 of H 2 O, hereinafter referred as R 2 (H 2 O)) to protein aggregates from nanometer to micrometer. Then, the quantitative relationship between R 2 (H 2 O) and aggregates is investigated furtherly. R 2 (H 2 O) could serve as an all-size coverage protein aggregates indicator during development. As a non-invasive method, LF-NMR does not need any sample handling. It takes only 44 s for one test, and saves a lot of manpower, materials and costs. Compared with other established analytical techniques, the technique developed here could be a powerful tool for a rapid, automatic, non-invasive and wide-scale coverage technique for aggregates indication in biomacromolecule development. [Display omitted] [ABSTRACT FROM AUTHOR]

Invasive fungal infections are a major health threat with high morbidity and mortality, highlighting the urgent need for rapid diagnostic tools to detect antifungal resistance. Traditional culture-based antifungal susceptibility testing (AFST) methods often fall short due to their lengthy process. In our previous research, we developed a whole-slide imaging (WSI) technique for the high-throughput assessment of bacterial antibiotic resistance. Building on this foundation, this study expands the application of WSI by adapting it for rapid AFST through high-throughput monitoring of the growth of hundreds of individual fungi. Due to the distinct "budding" growth patterns of fungi, we developed a unique approach that utilizes specific cell number change to determine fungi replication, instead of cell area change used for bacteria in our previous study, to accurately determine the growth rates of individual fungal cells. This method not only accelerates the determination of antifungal resistance by directly observing individual fungal cell growth, but also yields accurate results. Employing Candida albicans as a representative model organism, reliable minimum inhibitory concentration (MIC) of fluconazole inhibiting 100% cells of Candida albicans (denoted as MIC100) was obtained within 3h using the developed method, while the modified broth dilution method required 72h for the similar reliable result. In addition, our approach was effectively utilized to test blood culture samples directly, eliminating the need to separate the fungi from whole blood samples spiked with Candida albicans. These features indicate the developed method holds great potential serving as a general tool in rapid antifungal susceptibility testing and MIC determination. [ABSTRACT FROM AUTHOR]

Background: Evidence synthesis organisations are trying to meet commissioners' needs for rapid responses to their evidence synthesis commissions. In this project we piloted an intensive process, working to complete evidence syntheses within six-weeks, rather than the standard lead time of 4–6 months. Our objective was to explore how researchers experience working intensively, identify barriers and facilitators, and determine how a more intensive approach to evidence synthesis could be more systematically introduced in the future. Methods: In a pre-planning phase, an intensive work group was established, and two commissions were selected for this pilot project. The evidence synthesis process was divided into two phases: planning and intensive. The planning phase, involved scheduling the intensive phase, exploring new digital tools, and identifying peer reviewers. The intensive phase encompassed the entire evidence synthesis process. Two review teams were formed, each with a team lead supported by a process lead and leadership contact point. Throughout the project, teams engaged in reflective meetings to evaluate and adjust processes as needed. Results: During the planning phase, teams identified significant uncertainties regarding scopes, research questions, and inclusion criteria. To address this, they engaged with commissioners earlier than originally planned, clarified these aspects, and prepared protocols. Despite some minor deviations from the original plan, both reviews were completed on schedule, with one team expanding their scope due to the absence of eligible studies. Teams operated flexibly, held regular meetings, and found the process seamless due to fewer interruptions. Machine learning tools facilitated rapid study selection. The process lead role, created to guide and evaluate the project, proved beneficial, providing structure and support, although clearer role delineation with the leadership contact point could have improved efficiency. Conclusions: Overall, the intensive process fostered focus and productivity, allowing teams to manage short-term deliverables effectively. The researchers preferred working intensively with one evidence synthesis over being involved with many projects at the same time. They felt that time use was more effective, and they were able to complete the tasks in a focused way. However, there are several implications that should be considered before implementing an intensive approach in future evidence syntheses. [ABSTRACT FROM AUTHOR]

Purpose: To construct and validate nomograms for predicting lung metastasis probability in patients with malignant primary osseous spinal neoplasms (MPOSN) at initial diagnosis and predicting cancer-specific survival (CSS) in the lung metastasis subgroup. Methods: A total of 1,298 patients with spinal primary osteosarcoma, chondrosarcoma, Ewing sarcoma, and chordoma were retrospectively collected. Least absolute shrinkage and selection operator (LASSO) and multivariate logistic analysis were used to identify the predictors for lung metastasis. LASSO and multivariate Cox analysis were used to identify the prognostic factors for 3- and 5-year CSS in the lung metastasis subgroup. Receiver operating characteristic (ROC) curves, calibration curves, and decision curve analyses (DCA) were used to estimate the accuracy and net benefits of nomograms. Results: Histologic type, grade, lymph node involvement, tumor size, tumor extension, and other site metastasis were identified as predictors for lung metastasis. The area under the curve (AUC) for the training and validating cohorts were 0.825 and 0.827, respectively. Age, histologic type, surgery at primary site, and grade were identified as the prognostic factors for the CSS. The AUC for the 3- and 5-year CSS were 0.790 and 0.740, respectively. Calibration curves revealed good agreements, and the Hosmer and Lemeshow test identified the models to be well fitted. DCA curves demonstrated that nomograms were clinically useful. Conclusion: The nomograms constructed and validated by us could provide clinicians with a rapid and user-friendly tool to predict lung metastasis probability in patients with MPOSN at initial diagnosis and make a personalized CSS evaluation for the lung metastasis subgroup. [ABSTRACT FROM AUTHOR]

Healthcare services require rapid assessment tools, as well as the possibility of using them flexibly in different contexts, such as those experienced during the COVID-19 pandemic, that favor remote interaction over traditional care. These needs become especially challenging when assessing language and communication skills, for which few tools exist. This work aimed to develop and evaluate the psychometric properties of a novel test for the rapid and tele-assessment of pragmatic skills in Italian-speaking individuals, including an alternate form to allow for monitoring and follow-up. Inspired by Gricean pragmatics and modelled after the already validated Assessment of Pragmatic Abilities and Cognitive Substrates (APACS) in-person test, the new APACS Brief Remote test includes 18 original items assessing discourse and non-literal language understanding in expressive and receptive modalities. The test lasts approximately 10 min and is suited for videoconference administration. Results from a sample of 141 healthy participants indicate that both reliability (internal consistency, test-retest, and inter-rater) and validity (measured via APACS and verbal and cognitive tests) of the APACS Brief Remote are adequate. The alternate form of the test can be considered as equivalent. Among demographic variables, the analysis highlighted especially the role of age. Perceived experience with the videoconference administration was positive, supporting the feasibility of APACS Brief Remote across ages and educational levels. The APACS Brief Remote represents a useful tool to promote evidence-based tele-assessment practices in the domain of pragmatics, for instance for online follow-up assessment, in a vast range of clinical conditions that might cause communicative difficulties. [ABSTRACT FROM AUTHOR]

Human African trypanosomiasis (HAT) or sleeping sickness is a major public health problem, with epidemics occurring during the early part of the 20th century. Control activities of case-finding, treatment, and vector eradication across northern Nigeria with national and international support drastically reduced the prevalence from 14% between 1931 and 1940 to below 1% by 1980. With these successes, the Nigerian Institute for Trypanosomiasis Research (NITR) became underfunded and stopped regular active surveys. In 1985, a new HAT-endemic Abraka focus in Delta State emerged, and the Institute strengthened its surveillance there and in Benue State. In 1988, all outstations were closed, except for the Sleeping Sickness Reference Diagnostic Centre, Gboko, and Benue State. To date, only the Abraka focus has reported HAT case (s) to the WHO in 2012 and 2013. From 2014 to 2017, the Foundation for Innovative New Diagnostics (FIND), in collaboration with NITR and Ministries of Health, introduced intensive passive surveillance in 51 health centres in Delta State aimed at accelerating the control of HAT using rapid diagnostic tools (RDTs), LEDfluorescent microscopy, and molecular methods of LAMP provided free of charge by FIND. The results indicated 157 sero-positives out of 10,093 patients with HAT suspicion index screened but failed to confirm any HAT case by microscopy or molecular analysis. Of interest was the case of HAT exported to the United Kingdom from the Abraka area in 2017, suggesting continuing transmission. To achieve the 2030 HAT global elimination goal, surveillance programmes with sufficient diagnostic capacities must be implemented in Abraka, Delta State, Nigeria. This is not only important, but will also help in generating additional data and information useful in validating the future status of HAT in Abraka, Delta State Nigeria. [ABSTRACT FROM AUTHOR]

To comply with a more circular and environmentally friendly European common agricultural policy, while also valorising sunflower by-products, an ultrasound assisted extraction (UAE) was tested to optimise ethanol-wash solutes (EWS). Furthermore, the capabilities of DART-HRMS as a rapid and cost-effective tool for determining the biochemical changes after valorisation of these defatted sunflower EWS were investigated. Three batches of EWS were doubly processed into optimised EWS (OEWS) samples, which were analysed via DART-HRMS. Then, the metabolic profiles were submitted to a univariate analysis followed by a partial least square discriminant analysis (PLS-DA) allowing the identification of the 15 most informative ions. The assessment of the metabolomic fingerprinting characterising EWS and OEWS resulted in an accurate and well-defined spatial clusterization based on the retrieved pool of informative ions. The outcomes highlighted a significantly higher relative abundance of phenolipid hydroxycinnamoyl-glyceric acid and a lower incidence of free fatty acids and diglycerides due to the ultrasound treatment. These resulting biochemical changes might turn OEWS into a natural antioxidant supplement useful for controlling lipid oxidation and to prolong the shelf-life of foods and feeds. A standardised processing leading to a selective concentration of the desirable bioactive compounds is also advisable. [ABSTRACT FROM AUTHOR]

The performance of MALDI-TOF MS combined with analysis platform for identification of toxin-producing Clostridiodes difficile is yet to be known. Between August 2018 and September 2020, 61 isolates from stool specimens of patients with C. difficile -associated diarrhea were analyzed using the MALDI Biotyper system. A C. difficile toxin-producer detection model was developed using ClinProTools. The model was validated using 28 known strains that differed from the isolates used to develop the model. The sensitivity and specificity of the Genetic Algorithm (GA) model using isolates grown on Brucella with hemin and vitamin K (BHK) agar plates were 91.7% and 44.4%, respectively. When isolates grown on cycloserine-cefoxitin mannitol agar were analyzed by the model, sensitivity and specificity were 6.3% and 100%, respectively. The GA model using BHK medium showed the highest discriminatory performance in detection of toxin-producing C. difficile. However, a discrepancy in detection of toxin-producing C. difficile was observed in the results generated when the model was being developed and when the model was validated which suggests that incubation conditions may have affected the results. MALDI-TOF analysis using ClinProTools has a potential to be a cost-effective tool for rapid diagnosis and contribute to antimicrobial stewardship by differentiating toxin-producing C. difficile from non-producers. [ABSTRACT FROM AUTHOR]

Arabic is understudied in second-language research (L2) and lacks rapid and adequate tools for measuring proficiency. Drawing inspiration from LexTALE and its extensions, this study created and validated a quick receptive vocabulary size test to estimate L2 Arabic proficiency. In Experiment 1, the initial version of LexArabic was designed and evaluated with 192 L1 and L2 speakers. Item analysis using point-biserial correlations and item response theory (IRT) was conducted to refine the test, resulting in a final version with 90 items (60 words, 30 nonwords). Experiment 2 assessed LexArabic reliability, validity, and accuracy using a new group of 260 L1 and L2 speakers. The validity of LexArabic was evaluated through objective tasks (a general Arabic proficiency test, L1 to L2 translation task, L2 to L1 translation task) as well as subjective tasks (self-rated proficiency). Results showed that LexArabic demonstrated good reliability (α > 90), validity (correlation with two objective tasks and one subjective task), as well as accuracy (AUC value =.88). The introduction of LexArabic has the potential to facilitate experimental research on both L1 and L2 Arabic speakers and contributes to the development of standardized L2 proficiency assessment across languages. [ABSTRACT FROM AUTHOR]

Debris flows show massive threats to mountainous regions. This review paper critically studies the use of the RAMMS (Rapid Mass Movement Simulation) software in debris flow assessment. RAMMS, a widely employed simulation tool, offers a comprehensive framework for predicting the dynamics and runout behaviour and flow pattern of debris flows. The existing literature, encompassing a diverse range of studies that utilize RAMMS for debris flow assessment. This paper first provides an overview of the fundamental principles and capabilities of RAMMS, highlighting its capabilities in simulating complex interactions within debris flows, such as topographic variations, material properties, and dynamic triggering mechanisms along with the velocity, density and frictional coefficient. Subsequently, a synthesis of empirical case studies from different geographical contexts demonstrates the adaptability and applicability of RAMMS in different terrains. The introductory section provides a foundational understanding of RAMMS, explaining its features and functionalities that make it a potent tool for simulating rapid mass movements. The subsequent literature review part critically studies the works of different authors who have contributed significantly to the discourse surrounding RAMMS and its application to debris flow analysis. This section is investigated into the diverse perspectives and insights presented by researchers, offering a comprehensive overview of the model's capabilities and limitations. As an invaluable resource for geoscientists, engineers, and decision-makers, RAMMS simulation contributes significantly to understand and manage of natural hazards in complex landscapes. [ABSTRACT FROM AUTHOR]

Vegetation plays a crucial role in atmosphere‐land water and energy exchanges, global carbon cycle and basin water conservation. Land Surface Models (LSMs) typically represent vegetation characteristics by monthly climatological indices. However, static vegetation parameterization does not fully capture time‐varying vegetation characteristics, such as responses to climatic fluctuations, long‐term trends, and interannual variability. It remains unclear how the interaction between vegetation and climate variability propagates into hydrologic fluxes and water resources. Multi‐source satellite data sets may introduce uncertainties and require extensive time for analysis. This study developes a deep learning surrogate for a widely used LSM (i.e., Noah) as a rapid diagnosic tool. The calibrated surrogate quantifies the impacts of time‐varying vegetation characteristics from multiple remotely sensed GVF products on the magnitude, seasonality, and biotic and abiotic components of hydrologic fluxes. Using the Upper Colorado River Basin (UCRB) as a test case, we found that time‐varying vegetation provides more buffering effect against climate fluctuation than the static vegetation configuration, leading to reduced variability in the abiotic evaporation components (e.g., soil evaporation). In addition, time‐varying vegetation from multi‐source remote sensing products consistently predicts smaller biotic evaporation components (e.g., transpiration), leading to increased water yield in the UCRB (about 14%) compared to the static vegetation scheme. We also highlight the interaction between dynamic vegetation parameterization and static parameterization (e.g., soil) during calibration. Parameter recalibration and a re‐evaluation of certain model assumptions may be required for assessing climate change impacts on vegetation and basin‐wide water resources. Key Points: Machine learning‐based surrogates provide a rapid diagnostic tool to fuse multi‐source remotely sensed parameters into land surface modelsInterannual‐varying vegetation buffers hydroclimatic variability and redistributes evapotranspiration biotic and abiotic componentsMulti‐source remote sensing vegetation products consistently correct the underestimated water yield (as much as 14%) in the UCRB from the static vegetation scheme [ABSTRACT FROM AUTHOR]

From an industrial point of view, the milling of 2.5 D cavities is a frequent operation, consuming time and presenting optimization potential, especially through a judicious choice of the tool trajectory. Among the different types of trajectories, some have a general spiral-like aspect and can potentially offer a reduced machining time. They are called curvilinear trajectories and are obtained by interpolation between structure curves, which are the numerical solutions of a partial differential equation. In this case, the machine tool will connect points, and the trajectory will be made up of small segments. While these trajectories exhibit all the necessary qualities on a macroscopic level for rapid tool movement, the tangential discontinuities at a microscopic scale, inherent in the discretization, significantly increase the machining time. This article proposes a method to reparameterize the structure curves of the curvilinear spiral with a set of C 2 connected Hermit quartic spline patches. This creates a smooth toolpath that can be machined at an average feedrate closer to the programmed one and will, de facto, reduce the machining time. This article shows that the proposed method increases on two representative geometries of cavities and toolpath quality indicators, and reduces the milling time from 10 % to 18 % as compared to the PDE curvilinear spiral generation method proposed by Bieterman and Sandström. In addition, the proposed method is suitable for any non-convex pocket, with or without island(s). [ABSTRACT FROM AUTHOR]

The interest in the quality control of the raw materials, intermediates, and final products, as well as production methods, of beer has increased significantly in recent decades due to the needs and expectations of consumers. Increasing in the industrialization and globalization of beer supply chains led to a need for novel analytical tools suitable for the rapid and reliable characterization of the materials involved. In this study, an ultracompact instrument operating in the NIR region of the spectrum, microNIR, was tested for the chemical investigation of barley malts. The essential raw materials for brewing require careful control since they deeply affect the characteristic flavor and taste of the final products. Therefore, a robust prediction model able to classify base and specialty barley malts was developed starting from NIR measurements. Soft Independent Class Analogy (SIMCA) was selected as the chemometric technique for the optimization of two prediction models, and ground and sieved materials were investigated using spectroscopy. The microNIR/chemometric approach proposed in this study permitted the correct prediction of the malt samples included in the external validation set, providing false positive and false negative rates no higher than 3.41% and 0.25%, respectively, and confirming the feasibility of the novel analytical platform. [ABSTRACT FROM AUTHOR]

Background/objectives: Ocular tools and technologies may be used in the diagnosis of sport-related concussions (SRCs), but their clinical utility can vary. The following study aimed to review the literature pertaining to the reliability and diagnostic accuracy of such assessments. Methods: The preferred reporting items for systematic reviews and meta-analysis (PRISMA) extension for scoping reviews was adhered to. Reference standard reliability (RSR ≥ 0.75) and diagnostic accuracy (RSDA ≥ 0.80) were implemented to aid interpretation. Results: In total, 5223 articles were screened using the PCC acronym (Population, Concept, Context) with 74 included in the final analysis. Assessments included the King-Devick (KD) (n = 34), vestibular-ocular motor screening (VOMs) and/or near point of convergence (NPC) (n = 25), and various alternative tools and technologies (n = 20). The KD met RSR, but RSDA beyond amateur sport was limited. NPC met RSR but did not have RSDA to identify SRCs. The VOMs had conflicting RSR for total score and did not meet RSR in its individual tests. The VOMs total score did perform well in RSDA for SRCs. No alternative tool or technology met both RSR and RSDA. Conclusion: Ocular tools are useful, rapid screening tools but should remain within a multi-modal assessment for SRCs at this time. [ABSTRACT FROM AUTHOR]

The article presents an analysis of the geometric accuracy of wax models produced using PolyJet molds. Photopolymer resin was used to make the molds, and the surface of the model was finished in a gloss mode in the 3D printing process. This allows you to obtain a smooth surface of the molded part model. The geometric accuracy of the models was determined by measurements with the GOM ATOS scanner and analysis of the measurement results in relation to the base model made in the 3D-CAD program. Accuracy analysis was the basis for determining the wear of the mold wear when making subsequent models. [ABSTRACT FROM AUTHOR]

To determine sex and maturity stages accurately without any physical injury and stress, especially for sensitive and high‐value fish species, employing a noninvasive ultrasound imaging technique could be a desirable approach. The ultrasound imaging method as a powerful eco‐friendly tool was established to determine sex, gonad volume, gonadosomatic index (GSI), and reproductive stages in the Indian shad, hilsa (Tenualosa ilisha). About 30 hilsa (15 males and 15 females) of different maturity stages were collected from the river Ganga round the year using gill nets. The ultrasound sonography (USG) was then employed in hilsa to determine the computed GSI. The fresh gonad volume of hilsa was determined using a water displacement method to ascertain actual GSI values. There was no significant difference between the calculated, real, and actual GSIs (P > 0.05) in both males and females. The validation of the precise maturity stages of ultrasound images of the gonad by the histological architecture indicated that USG images of the hilsa gonad depicted exact stages of maturity in both sexes except for stages I and II in males. The sex of the fish was accurately ascertained using ovarian ultrasound scanning for all the specimens. The calculated USG‐based ovarian volume was positively correlated (R2 = 0.97) with the actual and real ovarian volumes. The noninvasive and reliable ultrasonography technique was found to be an accurate and valid tool to track gender and gonadal development and predict the spawning periodicity in hilsa. [ABSTRACT FROM AUTHOR]

Timely and accurate diagnosis is critical for effective healthcare, yet nearly half the global population lacks access to basic diagnostics. Point-of-care (POC) testing offers partial solutions by enabling low-cost, rapid diagnosis at the patient's location. At-home POC devices have the potential to advance preventive care and early disease detection. Nevertheless, effective sample preparation and detection methods are essential for accurate results. This review surveys recent advances in sample preparation and detection methods at POC. The goal is to provide an in-depth understanding of how these technologies can enhance at-home POC devices. Lateral flow assays, nucleic acid tests, and virus detection methods are at the forefront of POC diagnostic technology, offering rapid and sensitive tools for identifying and measuring pathogens, biomarkers, and viral infections. By illuminating cutting-edge research on assay development for POC diagnostics, this review aims to accelerate progress towards widely available, user-friendly, at-home health monitoring tools that empower individuals in personalized healthcare in the future. [ABSTRACT FROM AUTHOR]

Background Surveillance of SARS-CoV-2 circulation is mainly based on real-time reverse transcription–polymerase chain reaction, which requires laboratory facilities and cold chain for sample transportation. This is difficult to achieve in remote rural areas of resource-limited settings. The use of dried blood spots shipped at room temperature has shown good efficiency for the detection of arboviral RNA. Using a similar approach, we conducted a study at 3 provincial hospitals in Laos to compare the detection of SARS-CoV-2 from neat and dried spot samples. Methods Between January 2022 and March 2023, patients with respiratory symptoms were recruited. Nasopharyngeal/oropharyngeal swabs in virus transport medium (VTM), dry swabs, saliva, and dried saliva spotted on filter paper were collected. All samples were tested by SARS-CoV-2 real-time reverse transcription–polymerase chain reaction. Results In total, 479 participants were included. The VTM samples tested positive for 288 (60.1%). High positive percent agreements were observed for dry swab (84.8%; 95% CI, 80.2%–88.8%) and saliva (89.2%; 95% CI, 85.1%–92.6%) as compared with VTM. There was a loss of sensitivity when saliva was dried on filter paper (73.6%; 95% CI, 68.1%–78.6%) as compared with saliva. SARS-CoV-2 variant (Delta or Omicron) had no significant impact on the performance of the different sample types. Conclusions Our findings suggest that dry swabs could be a good alternative for sample collection and permit easy shipping at ambient temperature for subsequent viral SARS-CoV-2 RNA purification and molecular investigation. This is a useful tool to consider for a rapid implementation of large-scale surveillance of SARS-CoV-2 in remote areas, which could be extrapolated to other respiratory targets during routine surveillance or in the case of a novel emerging pandemic. [ABSTRACT FROM AUTHOR]

Background and Objectives Point-of-care testing using nonsputum samples like serum or plasma proteins can improve tuberculosis (TB) patients access to a definitive diagnosis, especially in resource-constrained and remote areas. Recently, approximately 400 proteins were identified as playing a role in the pathogenesis of TB, offering a translational clinical research repository for TB. In a previous manuscript, we proved the potential use of these proteins for point-of-care testing for active TB diagnosis. The present work aims to confirm the performance of single and combination proteins to select the best candidate biomarkers for further development as a diagnostic testing tool for active TB. Methods Seventy-four participants were assessed on the diagnostic performance of 17 single proteins and combinations of 2 to 4 proteins to diagnose active TB. The selection criteria included differential expression of the proteins between active TB and community-acquired pneumonia (CAP) and a performance rate ≥70% for active TB. Results SULT4A1, WASPF3, SPTLC1, FAM107B, SORCS2, and CYTOb561 were differentially expressed in TB compared to CAP patients. Two single proteins, SULT4A1 and WASPF3, performed ≥70% to discriminate active TB from CAP patients. The diagnostic performance of 3 protein-based combinations of active TB was 81% after leave-one-out cross-validation. Conclusion Single proteins and 3 protein-based combinations are candidate biomarkers for diagnosing active TB disease. A large and prospective study will confirm their performance as complementary diagnostic tools to rapid diagnostic methods for detecting active TB. [ABSTRACT FROM AUTHOR]

Soil visible and near–infrared reflectance spectroscopy is an effective tool for the rapid estimation of soil organic carbon (SOC). The development of spectroscopic technology has increased the application of spectral libraries for SOC research. However, the direct application of spectral libraries for SOC prediction remains challenging due to the high variability in soil types and soil–forming factors. This study aims to address this challenge by improving SOC prediction accuracy through spectral classification. We utilized the European Land Use and Cover Area frame Survey (LUCAS) large–scale spectral library and employed a geographically weighted principal component analysis (GWPCA) combined with a fuzzy c–means (FCM) clustering algorithm to classify the spectra. Subsequently, we used partial least squares regression (PLSR) and the Cubist model for SOC prediction. Additionally, we classified the soil data by land cover types and compared the classification prediction results with those obtained from spectral classification. The results showed that (1) the GWPCA–FCM–Cubist model yielded the best predictions, with an average accuracy of R2 = 0.83 and RPIQ = 2.95, representing improvements of 10.33% and 18.00% in R2 and RPIQ, respectively, compared to unclassified full sample modeling. (2) The accuracy of spectral classification modeling based on GWPCA–FCM was significantly superior to that of land cover type classification modeling. Specifically, there was a 7.64% and 14.22% improvement in R2 and RPIQ, respectively, under PLSR, and a 13.36% and 29.10% improvement in R2 and RPIQ, respectively, under Cubist. (3) Overall, the prediction accuracy of Cubist models was better than that of PLSR models. These findings indicate that the application of GWPCA and FCM clustering in conjunction with the Cubist modeling technique can significantly enhance the prediction accuracy of SOC from large–scale spectral libraries. [ABSTRACT FROM AUTHOR]

Background/Objectives: We present a software package called reflimR (Version 1.0.6), which enables rapid and transparent verification of reference intervals from routine laboratory measurements. Our method makes it easy to compare the results with specified target values and facilitates the interpretation of deviations using traffic light colors. Methods: The algorithm includes three procedural steps: (a) definition of an appropriate distribution model, based on Bowley's quartile skewness, (b) iterative truncation, based on a modified boxplot method to obtain the central 95% of presumably inconspicuous results, and (c) extrapolation of reference limits from a truncated normal quantile–quantile plot. Results: All algorithms have been combined into one consolidated library, which can be called in the R environment with a single command reflim (x). Using an example dataset included in the package, we demonstrate that our method can be applied to mixed data containing a substantial proportion of pathological values. It leads to similar results as the direct guideline approach as well as the more sophisticated indirect refineR software package. As compared to the latter, reflimR works much faster and needs smaller datasets for robust estimates. For the interpretation of the results, we present an intuitive color scheme based on tolerance ranges (permissible uncertainty of laboratory results). We show that a relatively high number of published reference limits require careful reevaluation. Conclusions: The reflimR package closes the gap between direct guideline methods and the more sophisticated indirect refineR method. We recommend reflimR for the rapid routine verification of large amounts of reference limits and refineR for a careful analysis of unclear or doubtful results from this check. [ABSTRACT FROM AUTHOR]

Microsatellite instability (MSI) assessment is strongly recommended for colorectal cancer patients, as MSI status is crucial in determining optimal treatment and predicting prognosis. This study evaluated the reliability and accuracy of a novel polymerase chain reaction (PCR)‐based 8‐loci MSI test kit, a rapid test kit designed to detect MSI, by comparing its performance with immunohistochemistry (IHC) and the National Cancer Institute (NCI) 2B3D Panel. MSI status was determined in 186 formalin‐fixed paraffin‐embedded (FFPE) colorectal cancer tissue samples with known mismatch repair (MMR) status by IHC using the novel PCR‐based 8‐loci MSI test kit. Additionally, the consistency between the NCI 2B3D Panel and the novel PCR‐based 8‐loci panel was compared using 69 FFPE tumor tissues paired with adjacent non‐cancerous tissue. The novel PCR‐based 8‐loci MSI test kit and IHC demonstrated high concordance (overall agreement: 97.8%). However, four samples displayed discordant results, exhibiting MMR deficiency using IHC and microsatellite stability using the novel PCR‐based 8‐loci MSI test kit. Of the 69 samples reanalyzed using the NCI 2B3D Panel, high concordance with the novel PCR‐based 8‐loci MSI test kit was observed in 67 of 69 cases (overall agreement: 97.1%). The novel PCR‐based 8‐loci MSI test kit is a rapid and reliable tool for accurately detecting MSI status in colorectal cancer. [ABSTRACT FROM AUTHOR]

To evaluate the resistance of apples to bruising under transient impact loads, a pendulum device was initially employed to gather collision data. Subsequently, an image acquisition and processing system was utilised to compute the apple surface bruise area, and X-ray computed tomography technology was utilised to precisely calculate the bruise volume. Based on the CT image and bruise area image analysis, the difference between bruised area and normal tissue on the apple after collision, and effects of impact energy on apple bruising volume and bruise area has been elaborated in detail. Results analysis revealed a general increase in both bruise volume and bruise area with escalating impact energy, and there is a strong correspondence between bruise volume and bruise area across different storage days and impact energies. The relationship between bruise volume and bruise area under different storage duration were also established. On the base of bruise resistance index (BRI) model utilising impact energy and bruise volume as variables, those analysis led to the establishment of a new bruise resistance index (BRI*) model employing impact energy and bruise area as independent variables. The effectiveness of BRI* model in assessing apple bruise resistance was demonstrated by comparing the corresponding relative error for bruise thresholds of BRI and BRI* under the same condition. The relative error ≤3.3% underscores the accuracy of the new model and proves the proposed BRI* model to be an efficient and rapid tool for assessing the degree of apple bruising. • Apples damage volume calculated utilising X-ray CT was introduced. • The effect of impact energy on both bruise volume and bruise area was analysed. • A novel bruise resistance index model was established to assess apple bruise. • The model can serve as an efficient and rapid tool for assessing bruising degree. [ABSTRACT FROM AUTHOR]

In practical applications, polyurethane (PU) foam must be rigid to meet the demands of various industries and provide comfort and protection in everyday life. PU foam components are extensively used in structural foam, thermal insulation, decorative panels, packaging, imitation wood, and floral foam, as well as in models and prototypes. Conventional technology for producing PU foam parts often leads to defects such as deformation, short shots, entrapped air, warpage, flash, micro-bubbles, weld lines, and voids. Therefore, the development of rigid PU foam parts has become a crucial research focus in the industry. This study proposes an innovative manufacturing process for producing rigid PU foam parts using silicone rubber molds (SRMs). The deformation of the silicone rubber mold can be predicted based on its wall thickness, following a trend equation with a correlation coefficient of 0.9951. The volume of the PU foam part can also be predicted by the weight of the PU foaming agent, as indicated by a trend equation with a correlation coefficient of 0.9824. The optimal weight ratio of the foaming agent to water, yielding the highest surface hardness, was found to be 5:1. The surface hardness of the PU foam part can also be predicted based on the weight of the water used, according to a proposed prediction equation with a correlation coefficient of 0.7517. The average surface hardness of the fabricated PU foam part has a Shore O hardness value of approximately 75. Foam parts made with 1.5 g of water added to 15 g of a foaming agent have the fewest internal pores, resulting in the densest interior. PU foam parts exhibit excellent mechanical properties when 3 g of water is added to the PU foaming agent, as evidenced by their surface hardness and compressive strength. Using rigid PU foam parts as a backing material in the proposed method can reduce rapid tool production costs by about 62%. Finally, an innovative manufacturing process for creating large SRMs using rigid PU foam parts as backing material is demonstrated. [ABSTRACT FROM AUTHOR]

Cystic fibrosis is caused by biallelic pathogenic variants in the CFTR gene, which contains a polymorphic (TG)mTn sequence (the "poly-T/TG tract") in intron 9. While T9 and T7 alleles are benign, T5 alleles with longer TG repeats, e.g., (TG)12T5 and (TG)13T5, are clinically significant. Thus, professional medical societies currently recommend reporting the TG repeat size when T5 is detected. Sanger sequencing is a cost-effective method of genotyping the (TG)mTn tract; however, its polymorphic length substantially complicates data analysis. We developed CFTR-TIPS, a freely available web-based software tool that infers the (TG)mTn genotype from Sanger sequencing data. This tool detects the (TG)mTn tract in the chromatograms, quantifies goodness of fit with expected patterns, and visualizes the results in a graphical user interface. It is broadly compatible with any Sanger chromatogram that contains the (TG)mTn tract ± 15 bp. We evaluated CFTR-TIPS using 835 clinical samples previously analyzed in a CLIA-certified, CAP-accredited laboratory. When operated fully automatically, CFTR-TIPS achieved 99.8% concordance with our clinically validated manual workflow, while generally taking less than 10 s per sample. There were two discordant samples: one due to a co-occurring heterozygous duplication that confounded the tool and the other due to incomplete (TG)mTn tract detection in the reverse chromatogram. No clinically significant misclassifications were observed. CFTR-TIPS is a free, accurate, and rapid tool for CFTR (TG)mTn tract genotyping using cost-effective Sanger sequencing. This tool is suitable both for automated use and as an aid to manual review to enhance accuracy and reduce analysis time. [ABSTRACT FROM AUTHOR]

An ultrasensitive method for the visual detection of microRNAs (miRNAs) in cell lysates using a gold nanorod-based lateral flow nucleic acid biosensor (GN-LFNAB) and exonuclease III (Exo III)-assisted signal amplification. The Exo III-catalyzed target recycling strategy is employed to generate a large number of single-strand DNA products, which can be detected by GN-LFNAB visually. With the implementation of a unique recycling strategy, we have demonstrated that the miRNA in the concentration as low as 0.5 pM can be detected without the need for instrumentation, providing a detection limit that surpasses previous reports. The new biosensor is ultrasensitive and can be applied to the reliable monitoring of miRNAs in cell lysates with high accuracy. The approach offers a simple and rapid tool for cancer diagnosis and clinical biomedicine, thanks to its flexibility, simplicity, cost-effectiveness, and convenience. This new method has the potential to significantly improve the detection and monitoring of cancer biomarkers, ultimately contributing to more effective cancer diagnosis and treatment. [ABSTRACT FROM AUTHOR]

Aquatic ecosystems are among the most affected by anthropogenic impacts, and the rapid detection and measurement of these impacts are of great importance for the maintenance of such environments. The order of aquatic insects Odonata has emerged as an important bioindicator of environmental quality due to its sensitivity to environmental changes and its ecophysiological requirements, which make them closely associated with habitat conditions. The aim of this study was to test whether the Zygoptera/Anisoptera ratio can be used as an effective tool to assess anthropogenic changes in Cerrado streams. Our hypothesis is that the proportion of Zygoptera/Anisoptera is an efficient tool for measuring environmental alterations in Cerrado streams, with a positive relationship between habitat integrity and the proportion of Zygoptera and an inverse relationship with the proportion of Anisoptera. Adults were collected in 44 streams of the Cerrado Biome in the eastern Maranhão state. The Habitat Integrity Index (HII) was used to verify the environmental gradient. Our hypothesis was corroborated, with a positive relationship between the richness and abundance of Zygoptera and HII, while an inverse relationship was observed for Anisoptera. According to our results, streams exhibiting a Zygoptera abundance of 68% or higher and richness of 58% or higher can be classified as preserved, while those showing an Anisoptera abundance and richness surpassing 31% and 41%, respectively, may be deemed altered. The patterns detected in the Cerrado were similar to those found in studies of the Amazon Biome and the Atlantic Forest, confirming the effectiveness of this method even for naturally open environments, such as the Cerrado. We conclude, therefore, that this method can be used as a tool to generate rapid results in monitoring studies, with low cost and easy application, enabling the development of mitigation, control, and conservation measures for extremely threatened environments such as those found in the Cerrado Biome. [ABSTRACT FROM AUTHOR]

As a famous probiotic, Lacticaseibacillus rhamnosus HN001 is widely added to probiotic products. Different L. rhamnosus strains have different probiotic effects, and the active HN001 strain is the key to exerting probiotic effects, so it is of great practical significance for realising the detection of L. rhamnosus HN001 at the strain level in probiotic products. In this study, strain-specific primer pairs and probes were designed. A combined treatment of sodium deoxycholate (SD) and propidium monoazide (PMA) inhibited the amplification of dead bacterial DNA, establishing a SD-PMA-ddPCR system and conditions for detecting live L. rhamnosus HN001 in probiotic powders. Specificity was confirmed using type strains and commercial strains. Sensitivity tests with spiked samples showed a detection limit of 10⁵ CFU/g and a linear quantification range of 1.42 × 10⁵–1.42 × 10⁹ CFU/g. Actual sample testing demonstrated the method's efficiency in quantifying HN001 in compound probiotic products. This method offers a reliable tool for the rapid and precise quantification of viable L. rhamnosus HN001, crucial for the quality monitoring of probiotic products. [ABSTRACT FROM AUTHOR]

Inter‐basin water transfer projects (WTPs) address water scarcity by lifting water uphill, posing energy challenges due to diverse topography. This study therefore analyses historical trends in WTP distance, average annual water volumes delivered, water lift and pumping capacity to develop the Water Transfer Energy Efficiency Index (WTEEI) and apply it for the assessment of WTPs. Results indicate that the WTEEI is a valuable tool for evaluating WTP energy efficiency. While no definitive trend in WTEEI values was observed, the findings suggest the need for monitoring of energy use of WTPs and more research to better understand and improve the energy efficiency of these large‐scale infrastructure projects. By introducing a simple, intuitive and rapid assessment tool for evaluating energy efficiency in WTPs, this study addresses a critical gap in the water–energy field, namely, the evaluation of energy usage in WTPs and the identification of energy‐efficiency improvements for current and future WTPs. Highlights: This study introduces the Water Transfer Energy Efficiency Index (WTEEI) for water transfer projects (WTPs).It applies the WTEEI to quantify the energy efficiency of WTPs globally.It analyses WTP characteristics (distance, volume delivered, height of water lift and pumping capacity).The study addresses a critical gap by providing a method for evaluating energy usage in WTPs and offering energy‐efficiency improvements for current and future WTPs. [ABSTRACT FROM AUTHOR]

Methanotrophs of the genus Methylocystis are frequently found in rice paddies. Although more than ten facultative methanotrophs have been reported since 2005, none of these strains was isolated from paddy soil. Here, a facultative methane-oxidizing bacterium, Methylocystis iwaonis SD4, was isolated and characterized from rhizosphere samples of rice plants in Nanjing, China. This strain grew well on methane or methanol but was able to grow slowly using acetate or ethanol. Moreover, strain SD4 showed sustained growth at low concentrations of methane (100 and 500 ppmv). M. iwaonis SD4 could utilize diverse nitrogen sources, including nitrate, urea, ammonium as well as dinitrogen. Strain SD4 possessed genes encoding both the particulate methane monooxygenase and the soluble methane monooxygenase. Simple and rapid genetic manipulation methods were established for this strain, enabling vector transformation and unmarked genetic manipulation. Fast growth rate and efficient genetic tools make M. iwaonis SD4 an ideal model to study facultative methanotrophs, and the ability to grow on low concentration of methane implies its potential in methane removal. [ABSTRACT FROM AUTHOR]

For the manufacture of extrusion dies, three‐dimensional (3D) printing with photopolymers offers numerous advantages including flexibility, high surface quality, decent build speed, low costs and a reduced amount of waste. However, the majority of photocurable resins used in vat photopolymerization 3D printing rely on acrylates, which entail 3D‐printed objects with poor mechanical properties. In particular, the high brittleness limits their application in rapid tooling, for which tough materials with high glass transition temperatures (Tg) are required. In the present study, we highlight the use of dual curable acrylate‐epoxy resins with dynamic covalent bonds for the direct fabrication of extrusion dies. During digital light processing (DLP) 3D printing the acrylate network is formed, whose toughness and thermal stability are significantly enhanced by the thermoactivated formation of a second network. By following a postbaking procedure, aminoglycidiyl monomers are cured with an anhydride hardener bearing bulky norbornene groups yielding interpenetrating polymer networks with a Tg > 100°C. The tertiary amine groups present in the structure of the aminoglycidyl derivatives do not only accelerate the ring‐opening reaction but also act as internal catalysts and activate bond exchange reactions between free –OH groups and ester moieties available in the photopolymer. This is confirmed by rheometer studies showing a distinctive stress relaxation at elevated temperature and giving rise to a possible reprocessability of the 3D‐printed dies. With a selected resin formulation, a set of dies is printed by DLP 3D printing, with which a highly filled rubber compound is successfully extruded. The results clearly show that dual curable resins with dynamic covalent bonds are a promising class of material for rapid tooling and pave the way towards a customized and convenient fabrication of extrusion dies for rubber processing. [ABSTRACT FROM AUTHOR]

The rapid tooling of mold inserts for injection molding allows for very fast product development, as well as a highly customized design. For this, a combination of rapid prototyping methods with suitable polymer materials, like the high-performance thermoplastic polymer polyetheretherketone (PEEK), should be applied. As a drawback, a huge processing temperature beyond 400 °C is necessary for material extrusion (MEX)-based 3D printing; here, Fused Filament Fabrication (FFF) requires a more sophisticated printing parameter investigation. In this work, suitable MEX printing strategies, covering printing parameters like printing temperature and speed, for the realization of two different mold insert surface geometries were evaluated, and the resulting print quality was inspected. As a proof of concept, ceramic injection molding was used for replication. Under consideration of the two different test structures, the ceramic feedstock could be replicated successfully and to an acceptable quality without significant mold insert deterioration. [ABSTRACT FROM AUTHOR]

A portable liquid scintillation counting system has been used as a rapid screening tool for radiological characterization and in situ measurements of aqueous samples. The methodology was standardized based on the Pulse Length Index for gross α and gross β activity determinations in aqueous solutions by means of a portable Liquid Scintillation Counter (LSC). This single compact PMT system yielded precise results for aqueous test samples, which were validated against a conventional HIDEX 300SL LSC system. The sensitivity of the portable LSC for gross measurements was investigated thoroughly for various combinations of scintillation cocktails and sample proportions, and found to be well below the Operational Intervention Levels (OILs) recommended by Atomic Energy Regulatory Board (AERB) during radiation emergency scenarios. Gross α- and β-activity measurements by means of the portable LSC system have shown this procedure to be effective for preliminary screening and evaluating the total radioactivity in aqueous samples during such radiation emergencies. [ABSTRACT FROM AUTHOR]

Burn severity is fundamental to post‐fire impact assessment and emergency response. Vegetation Burn Severity (VBS) can be derived from satellite observations. However, Soil Burn Severity (SBS) assessment—critical for mitigating hydrologic and geologic hazards—requires costly and laborious field recalibration of VBS maps. Here, we develop a physics‐informed Machine Learning model capable of accurately estimating SBS while revealing the intricate relationships between soil and vegetation burn severities. Our SBS classification model uses VBS, as well as climatological, meteorological, ecological, geological, and topographical wildfire covariates. This model demonstrated an overall accuracy of 89% for out‐of‐sample test data. The model exhibited scalability with additional data, and was able to extract universal functional relationships between vegetation and soil burn severities across the western US. VBS had the largest control on SBS, followed by weather (e.g., wind, fire danger, temperature), climate (e.g., annual precipitation), topography (e.g., elevation), and soil characteristics (e.g., soil organic carbon content). The relative control of processes on SBS changes across regions. Our model revealed nuanced relationships between VBS and SBS; for example, a similar VBS with lower wind speeds—that is, higher fire residence time—translates to a higher SBS. This transferrable model develops reliable and timely SBS maps using satellite and publicly accessible data, providing science‐based insights for managers and diverse stakeholders. Plain Language Summary: Post‐fire impact assessment and hazard mitigation heavily relies on burn severity metrics. Vegetation burn severity (VBS)—most relevant for ecological impacts—can be remotely sensed, but soil burn severity (SBS)—most relevant for hydrological impacts—requires laborious field recalibration of VBS maps. Lack of near real‐time SBS information is currently a data gap. Climate change‐driven weather whiplash can narrow the time interval between large wildfires and the ensuing precipitation events, requiring tools for rapid and accurate assessment of SBS without the need for laborious field recalibration of satellite‐derived metrics. Here we developed a physic‐informed Machine Learning model that can accurately develop SBS maps using readily available data without the need for resource and time intensive field assessments of burn severity. Additionally, SBS maps are developed for only a small fraction (less than 0.1%) of all wildfires in the US. Our model can develop SBS maps for all satellite‐observed wildfires in the western US, and has the potential to accomplish this task globally with further training. Finally, our model exhibited scalability with additional data, and was able to extract universal functional relationships between vegetation and soil burn severities across the western US. Key Points: Soil burn severity (SBS) assessment is key for hydrological hazard mitigationVegetation burn severity (VBS) can be remotely sensed, SBS is measured in the fieldPhysics‐informed Machine Learning models to translate VBS to SBS are developed [ABSTRACT FROM AUTHOR]

Sorghum (Sorghum bicolor [L.] Moench) is the fifth most important cereal grown mostly in arid and semi-arid regions. Climate models predict that there is a risk of drought stress in those regions. Quantifying the physiological traits for developing the tolerant lines is efficient but time-consuming process. Therefore, it is necessary to find a rapid tool to identify the drought tolerant germplasm. With this background, the objectives were framed to assess the genetic variability for chlorophyll index and group the diverse set of sorghum genotypes for drought tolerance/susceptibility. Results proved chlorophyll index as an early phenotypic trait to screen the plants for drought tolerance. Drought stress was imposed at booting stage for the period of three weeks in rain out shelter with 29 sorghum genotypes and 4 checks obtained from Indian Institute of Millet Research, Hyderabad, and Agricultural Research Station, Kovilpatti, Tamil Nadu, India. The genotypes such as PEC 17 and PEC 34 were identified as tolerant and EN 55 and EP 87 as susceptible, based on chlorophyll index recorded one week after stress using Z score index. PEC 17 recorded higher chlorophyll index (15.89), photosynthetic rate (37.77 µmol/m2/sec), stomatal conductance (0.43 mol/m2/sec) and grain yield (50.75 g/plant). The percentage increase in epicuticular wax content was higher in PEC 17 (18.5%) contributing to drought tolerance. Thus, the study concluded that crops with higher chlorophyll index under drought can withstand drought at reproductive phenophase and yield better under stress. [ABSTRACT FROM AUTHOR]

Purpose: Polyurethane (PUR) foam parts are traditionally manufactured using metallic molds, an unsuitable approach for prototyping purposes. Thus, rapid tooling of disposable molds using fused filament fabrication (FFF) with polylactic acid (PLA) and glycol-modified polyethylene terephthalate (PETG) is proposed as an economical, simpler and faster solution compared to traditional metallic molds or three-dimensional (3D) printing with other difficult-to-print thermoplastics, which are prone to shrinkage and delamination (acrylonitrile butadiene styrene, polypropilene-PP) or high-cost due to both material and printing equipment expenses (PEEK, polyamides or polycarbonate-PC). The purpose of this study has been to evaluate the ease of release of PUR foam on these materials in combination with release agents to facilitate the mulding/demoulding process. Design/methodology/approach: PETG, PLA and hardenable polylactic acid (PLA 3D870) have been evaluated as mold materials in combination with aqueous and solvent-based release agents within a full design of experiments by three consecutive molding/demolding cycles. Findings: PLA 3D870 has shown the best demoldability. A mold expressly designed to manufacture a foam cushion has been printed and the prototyping has been successfully achieved. The demolding of the part has been easier using a solvent-based release agent, meanwhile the quality has been better when using a water-based one. Originality/value: The combination of PLA 3D870 and FFF, along with solvent-free water-based release agents, presents a compelling low-cost and eco-friendly alternative to traditional metallic molds and other 3D printing thermoplastics. This innovative approach serves as a viable option for rapid tooling in PUR foam molding. [ABSTRACT FROM AUTHOR]

Rapid Tooling able to produce complex prototypes directly from three-dimensional CAD software using materials such as polymer, wax, and paper, but it is typically used for low-volume production. The current technology uses epoxy filled with metal fillers such as aluminum or copper to enhance the mechanical properties of rapid tooling molds. This study aims to investigate the effect of using recycled brass filler mixed with epoxy resin as mold inserts for Rapid Tooling in injection molding applications. An optimal ratio of brass filler particles will be evaluated to determine the best physical and thermal properties for the mold inserts. Significantly, this study will encourage the use of recycled materials such as metal waste from machining to offer great help in environmental sustainability.

MiFUS® is a tool that can display the patient's infusion condition so that nurses can monitor patients one by one in a short time simultaneously. Several nurses were involved in this study to provide input to the casing. Product design is done at the beginning to know the initial casing design. Next, the manufacture of casing molds is carried out using a 3D printing machine. The results of the 3D printer are used as a Master Mold for the implementation of Rapid Tooling method with Epoxy material. The solution of product development is catalyst ratio analysis on polyester resin to obtain the optimal ratio of properties including shrinkage and strength of the material to withstand mechanical loads. Validation of shrinkage is carried out using 3D Scanning technology to determine the deviation of dimensions in the casing made against CAD data. Meanwhile, to obtain the strength parameters of the material to withstand mechanical loads, tensile testing is carried out. The results of this study are the contribution of design parameters, namely the amount of shrinkage that occurs and the strength parameters of the material to withstand mechanical loads. The Data and information are presented in the form of product prototypes and user analysis feasibility studies.

The treatment of wound inflammation is intricately linked to the concentration of reactive oxygen species (ROS) in the wound microenvironment. Among these ROS, H2O2 serves as a critical signaling molecule and second messenger, necessitating the urgent need for its rapid real-time quantitative detection, as well as effective clearance, in the pursuit of effective wound inflammation treatment. Here, we exploited a sophisticated 3D Cu2-xSe/GO nanostructurebased nanonzymatic H2O2 electrochemical sensor, which is further decorated with evenly distributed Pt nanoparticles (Pt NPs) through electrodeposition. The obtained Cu2-xSe/GO@Pt/SPCE sensing electrode possesses a remarkable increase in specific surface derived from the three-dimensional surface constructed by GO nanosheets. Moreover, the localized surface plasma effect of the Cu2-xSe nanospheres enhances the separation of photogenerated electron-hole pairs between the interface of the Cu2-xSe NPs and the Pt NPs. This innovation enables near-infrared light-enhanced catalysis, significantly reducing the detection limit of the Cu2-xSe/GO@Pt/SPCE sensing electrode for H2O2 (from 1.45 mM to 0.53mM) under NIR light. Furthermore, this biosensor electrode enables in-situ real-time monitoring of H2O2 released by cells. The NIR-enhanced Cu2-xSe/GO@Pt/SPCE sensing electrode provide a simple-yeteffective method to achieve a detection of ROS (H2O2-OH) with high sensitivity and efficiency. This innovation promises to revolutionize the field of wound inflammation treatment by providing clinicians with a powerful tool for accurate and rapid assessment of ROS levels, ultimately leading to improved patient outcomes. [ABSTRACT FROM AUTHOR]

Tubulysins are among the most recent antimitotic compounds to enter into antibody/peptide‐drug conjugate (ADC/PDC) development. Thus far, the design of the most promising tubulysin payloads relied on simplifying their structures, e. g. by using small tertiary amide N‐substituents (Me, Et, Pr) on the tubuvaline residue. Cumbersome solution‐phase approaches are typically used for both syntheses and functionalization with cleavable linkers. p‐Aminobenzyl quaternary ammonium (PABQ) linkers were a remarkable advancement for targeted delivery, but the procedures to incorporate them into tubulysins are only of moderate efficiency. Here we describe a novel all‐on‐resin strategy permitting a loss‐free resin linkage and an improved access to super potent tubulysin analogs showing close resemblance to the natural compounds. For the first time, a protocol enables the integration of on‐resin tubulysin derivatization with, e. g. a maleimido‐Val‐Cit‐PABQ linker, which is a notable progress for the payload‐PABQ‐linker technology. The strategy also allows tubulysin diversification of the internal amide N‐substituent, thus enabling to screen a tubulysin library for the discovery of new potent analogs. This work provides ADC/PDC developers with new tools for both rapid access to new derivatives and easier linker‐attachment and functionalization. [ABSTRACT FROM AUTHOR]

Although current EU regulations, such as EU Directive 2015/1189 on the eco-design of solid fuel boilers and Directive 2015/1188, in accordance with the Machinery Directive 2006/42/EC, require manufacturers to meet specific emission requirements for CE marking, the routine and regular onsite testing of household heating appliances is still not mandatory in many EU countries. This research endeavour addressed this gap by evaluating the effectiveness of the Bacharach method as a rapid and cost-effective tool for assessing flue gas quality, particularly in terms of particulate matter mass concentration. This study also compared the results of the Bacharach method with those obtained from two commercially available portable analysers. The research outcomes demonstrate that the Bacharach method, in combination with an innovative evaluation approach, offers a viable solution, enabling the swift and economical assessment of flue gas quality with the primary objective of determining the boiler class according to the limits specified by standard EN 303-5 under operating conditions. The modified Bacharach method for measuring TSP in solid fuel-fired boilers provides qualitatively similar results to the commercially used SM500 and STM225 instruments. The modified Bacharach methodology was primarily developed for comparison to the boiler class 3 limit (i.e., 125 and 150 mg/m3). The study revealed that the modified Bacharach method, when applied to biomass-based boilers, exhibited higher accuracies in the case of classification into classes 3 and 4, whereas fossil fuel-based boilers demonstrated higher accuracy in the case of class 5 limits. [ABSTRACT FROM AUTHOR]

Bovine leukemia virus (BLV) is prevalent worldwide, causing serious problems in the cattle industry. The BLV proviral load (PVL) is a useful index for estimating disease progression and transmission risk. We previously developed a quantitative real-time PCR (qPCR) assay to measure the PVL using the coordination of common motif (CoCoMo) degenerate primers. Here, we constructed a novel duplex BLV-CoCoMo qPCR assay that can amplify two genes simultaneously using a FAM-labeled MGB probe for the BLV LTR gene and a VIC-labeled MGB probe for the BoLA-DRA gene. This liquid duplex assay maintained its original sensitivity and reproducibility in field samples. Furthermore, we developed a dry duplex assay composed of PCR reagents necessary for the optimized liquid duplex assay. We observed a strong positive correlation between the PVLs measured using the dry and liquid duplex assays. Validation analyses showed that the sensitivity of the dry duplex assay was slightly lower than that of the other methods for the detection of a BLV molecular clone, but it showed similar sensitivity to the singleplex assay and slightly higher sensitivity than the liquid duplex assay for the PVL quantification of 82 field samples. Thus, our liquid and dry duplex assays are useful for measuring the BLV PVL in field samples, similar to the original singleplex assay. [ABSTRACT FROM AUTHOR]

Amino‐acid protein composition plays an important role in biology, medicine, and nutrition. Here, a groundbreaking protein analysis technique that quickly estimates amino acid composition and secondary structure across various protein sizes, while maintaining their natural states is introduced and validated. This method combines multivariate statistics and the thermostable Raman interaction profiling (TRIP) technique, eliminating the need for complex preparations. In order to validate the approach, the Raman spectra are constructed of seven proteins of varying sizes by utilizing their amino acid frequencies and the Raman spectra of individual amino acids. These constructed spectra exhibit a close resemblance to the actual measured Raman spectra. Specific vibrational modes tied to free amino and carboxyl termini of the amino acids disappear as signals linked to secondary structures emerged under TRIP conditions. Furthermore, the technique is used inversely to successfully estimate amino acid compositions and secondary structures of unknown proteins across a range of sizes, achieving impressive accuracy ranging between 1.47% and 5.77% of root mean square errors (RMSE). These results extend the uses for TRIP beyond interaction profiling, to probe amino acid composition and structure. [ABSTRACT FROM AUTHOR]

K-Nearest Neighbor (KNN) is a method that belongs to the group in classifying data that is simple and easy to implement, effective on larger data, and can classify data appropriately. One of the advantages possessed by the K-Nearest Neighbor algorithm is that it can be applied to large amounts of data and has a lot of noise so this method is quite easy to implement. This study aims to utilize the advantages of the K-NN algorithm in data-based classification to increase efficiency and accuracy in the employee selection process in determining suitable employee candidates by the criteria determined by the company. The results showed that the results of employee presets received from 21 testing data were 51% and for employee presentations that failed as much as 49% while from the entire data set of 140 data, the accuracy level produced after being tested using rapid miner tools resulted in 82% accuracy. So it can be concluded that the percentage accuracy of 82% shows that most prospective employees have been predicted or classified correctly by the model. This high level of accuracy can be an indication that the K-Nearest Neighbor method used in combination with Rapidminer can handle prospective employee data well. [ABSTRACT FROM AUTHOR]

The goal of the current work is to analyse the Zn scaffold porosity effects on its corrosion behavior. Organized porous network structure (OPNS) zinc samples with varying porosity were manufactured by a newly developed rapid tooling approach that combined 3D printing and microwave sintering. The outcomes of the OPNS Zn samples were also compared to the dense zinc sample. For the corrosion analysis, porous and dense zinc samples electrochemical corrosion testing were conducted in SBF electrolyte at 37 °C. The zinc samples morphological study was accessed by scanning electron microscopy (SEM). It was confirmed by the findings of the morphological study that the Zn samples contained randomly distributed micropores and designed or organized macropores. The zinc sample corrosion behavior in SBF was analyzed by potentiodynamic (PD) polarisation and electrochemical impedance spectroscopy (EIS) curves. In addition, an electrical equivalent circuit (EEC) model was developed using the EIS experimental data to establish an understanding of the corrosion behavior of Zn samples. Overall corrosion testing results demonstrate that the diffusion mechanism had an impact on the corrosion mechanism of Zn samples and diffusion mechanism during electrochemical reaction supported by the porosity of the sample. The Zn samples corrosion rate was found to be minimum for the dense sample (0.14 mm y−1), while it was maximum for the highest porosity OPNS Zn sample (0.66 mm y−1). The present study corrosion rate of Zn samples was comparable with the required value for bone implants. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to investigate the demoulding characteristics of material-jetted rapid mould inserts having different surface textures for micro-injection moulding using in-line measurements and surface metrology. Design/methodology/approach: Material-jetted inserts with the negative cavity of a circular test product were fabricated using different surface finishes and printing configurations, including glossy, matte and vertical settings. In-line measurements included the recording of demoulding forces at 10 kHz, which was necessary to capture the highly-dynamic characteristics. A robust data processing algorithm was used to extract reliable demoulding energies per moulding run. Thermal imaging captured surface temperatures on the inserts after demoulding. Off-line measurements, including focus variation microscopy and scanning electron microscopy, compared surface textures after a total of 60 moulding runs. Findings: A framework for capturing demoulding energies from material-jetted rapid tools was demonstrated and compared to the literature. Glossy surfaces resulted in significantly reduced demoulding forces compared to the industry standard steel moulds in the literature and their material-jetted counterparts. Minimal changes in the surface textures of the material-jetted inserts were found, which could potentially permit their prolonged usage. Significant correlations between surface temperatures and demoulding energies were demonstrated. Originality/value: The research presented here addresses the very topical issue of demoulding characteristics of soft, rapid tools, which affect the quality of prototyped products and tool durability. This was done using state-of-the-art, high-speed sensing technologies in conjunction with surface metrology and their durability for the first time in the literature. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to address the challenge of reducing the build time of a fused deposition modeling (FDM) system while maintaining part strength, proposing a hybrid technique combining photopolymerization and FDM. Design/methodology/approach: For developing the hybrid system, a standard FDM machine was modified to incorporate necessary components so that the whole system can be operated with a single interface; further, the samples were fabricated with conventional and modified process to evaluate the efficacy of the developed system, to determine the extent of time reduction that the proposed methodology can obtain, additionally different sort of 3D models were selected and their build time was compared. Findings: The modified hybrid mechanism can successfully fabricate parts with a modified G-code. The simulation of the technique shows that a reduction of 34%–87% can be achieved for simpler models such as cube while a reduction ranging from 30.6%–87.8% was observed for complex models. An increase in strength of 6.58%, 11.51% and 37.32% was observed in X, Y and Z directions, along with a significant increase in toughness as compared with FDM parts for parts fabricated with the developed mechanism. Practical implications: The modified mechanism could be used for fast fabrication purposes, which could be very useful for serving situations such as emergency health care, rapid tooling. Originality/value: This research contributes a novel hybrid technique for additive manufacturing, offering a substantial reduction in build time without compromising mechanical properties, even increasing them. [ABSTRACT FROM AUTHOR]

In this study, we introduce a methodology for predicting the behavior of cracks in holed plates. The foundation of our methodology lies in the generation of rich dataset finite element simulations. These simulations capture the complex mechanical responses exhibited by holed plates under varying initial geometries. Using this dataset as training input, we employ a multilayer perceptron deep learning model to discern the underlying relationships between the plate's initial geometry and its subsequent crack behavior. Through meticulous data preprocessing and fine-tuning of the model architecture, the MLP undergoes rigorous training and validation to optimize its predictive capabilities. Mean squared errors are utilized to assess the accuracy and generalization capacity of the trained model. The results suggest that this model can serve as a powerful rapid predictive tool, capable of analyzing crack behavior in new instances of the plate's geometry with remarkable efficiency and accuracy. [ABSTRACT FROM AUTHOR]