Current oncological developments are based on improved understanding of genetics, and especially the discovery of genes whose alterations affect cell functions with consequences for the whole body. Our work is focused on the most important of these genes, the BARD1 and its oncogenic role in breast cancer. Most importantly, the study points to new avenues in the treatment and prevention of the most frequent female cancer based on BARD1 research. The BARD1 and BRCA1 proteins have similar structures and functions, and they combine to form the new molecule BARD1-BRCA1 heterodimer. Through ubiquitination, this heterodimer has significant effects on individual proteins, enabling, among others, the destruction of damaged DNA fragments. Ubiquitination, as well as stabilizing chromatin, or regulating the number of centrosomes, confirms the protective cooperation of BARD1 and BRCA1 in the stabilization of the genome. The overexpression of the oncogenic isoforms BARD1β and BARD1δ permit cancer development. The introduction of routine tests, for instance, to identify the presence of the BARD1β isoform, would make it possible to detect patients at high risk of developing cancer. On the other hand, introducing BARD1δ isoform blocking therapy, which would reduce estrogen sensitivity, may be a new line of cancer therapy with potential to modulate responses to existing treatments. It is possible that the BARD 1 gene offers new hope for improving breast cancer therapy.

Stess in laser cladding coating is an important factor affecting the safe operation of remanufacturing components. Ultrasonic testing has become a hot direction in nondestructive evaluation of stress, because it has the advantages of safety, non-destructive and on-line detection. This paper provides a review of ultrasonic testing for stress in remanufacturing laser cladding coating. It summarizes the recent research outcomes on ultrasonic testing for stress, analyzes mechanism of ultrasonic testing for stress. Remanufacturing laser cladding coating shows typical anisotropic behaviors, the ultrasonic testing signal in laser cladding coating is influenced by many complex factors, such as microstructure, defect, temperature and surface roughness, etc. At present, ultrasonic testing for stress in laser cladding coating can only be done roughly. The paper discusses active mechanism of micro / macro factors to the reliability of stress measurement and the impact of stress measurement to the quality and safety of remanufacturing components. Base on the discussion, the paper proposes strategies for acquisition of nondestructive, rapid and accurate measurement of stress in remanufacturing laser cladding coating.

Objective: This paper aims to build an Effort Estimation Model for design, coding and testing Web Applications Based Fuzzy and Practical Models, which will help in optimizing the efforts in software development. Methods/Analysis: Soft computing approach is adopted and applied in the effort estimation and then compared with practical efforts in the development process with interpreting the historical data available for the existing functionalities. Findings: The effort estimation model presented in this paper focuses on the first level estimates published by Project Managers and the second level estimates presented by Project Leaders or Developers for any new requirement or enhancement for a web application built on 3-tier architecture using Microsoft technologies. The model considers the classification of each task as either Low or Medium or High complexity. These tasks pertain to the lowest level parts in bottom-up estimation. Efforts are estimated for designing, coding and unit testing of these tasks and the efforts are summed up to get the effort estimation for the higher level which is a feature to be implemented. Novelty/Improvement: The paper also discusses about the application of the effort estimation model by taking a new requirement as a case study. The first level estimates calculated using the effort estimation model has a variance of about 25% when compared with the actual effort. This variance is very much acceptable considering the fact that the first level estimates can be tolerable up to 35%. The proposed effort estimation tool would help the project managers to efficiently control the project, manage the resources effectively, and improve the software development process and also trade off analyses among schedule, performance, quality and functionality. Fuzzy logic is used to verify the claims made in efforts estimation. It is proposed a new relation between the number of data and efforts value membership for actual data. And converts it into crisp value in the range [0…1] which helps to classify the complexity of the task and subtask in the design, coding and testing phases.

The testing of high-dimensional normality has been an important issue and has been intensively studied in literatures, it depends on the Variance-Covariance matrix of the sample, numerous methods have been proposed to reduce the complex of the Variance-Covariance matrix. The principle component analysis(PCA) was widely used since it can project the high-dimensional data into lower dimensional orthogonal space, and the normality of the reduced data can be evaluated by Jarque-Bera(JB) statistic on each principle direction. We propose two combined statistics, the summation and the maximum of one-way JB statistics, upon the independency of each principle direction, to test the multivariate normality of data in high dimensions. The performance of the proposed methods is illustrated by the empirical power of the simulated data of normal data and non-normal data. Two real examples show the validity of our proposed methods.

Acute vertigo and dizziness are frequent presenting symptoms in patients on the emergency department. With a broad differential diagnosis and symptoms/signs often subtle and transient, the diagnostic approach to the dizzy patient remains challenging. Previous work emphasized the value of combining structured history-taking and a targeted examination focusing on subtle oculomotor signs. Here I review different bedside algorithms proposed for the acutely dizzy patient. Comparing area-under-the-curve ROC-characteristics and sensitivity/specificity, highest diagnostic accuracy was observed for algorithms focusing on subtle oculomotor signs. Both the HINTS+ bedside-exam and the STANDING algorithm have demonstrated higher diagnostic accuracy for identifying strokes than early (<24-48h after symptom-onset) MRI-DWI. Importantly, HINTS and STANDING require moderate training to allow reliable application. Thus, for physicians lacking dedicated training, other approaches are needed. Various scores that rely on vascular risk-factors, clinical symptoms and focal neurologic findings have been proposed (e.g., ABCD2-score, PCI-score, TriAGe+-score). While these scores are more readily applicable for frontline providers, they provide intermediate diagnostic accuracy at best and often lack external validation, thus are an insufficient substitute for algorithms assessing subtle oculomotor findings. Providing dedicated training in HINTS+ or STANDING techniques will be key to improve the diagnostic accuracy and to avoid unnecessary brain imaging.

The novel COVID-19 pandemic prompted an unprecedented Institutional reaction to aggregate existing capacity from silos of research laboratories to establish a multidisciplinary research laboratory for COVID19 testing. In less than two weeks, resources were mobilized from the community to strengthen public health response and epidemic control. Such strengthening of institutional research capacity to support public health response contributes to a natural knowledge transfer, facilitates collaboration, and generates new frontiers for knowledge production that should ultimately lead to professional development and retention of skilled human resources. This report describes the pre-established mechanisms and involvement of the authors that made it possible to set-up a multidisciplinary laboratory in a remarkably short period of time. We also discuss the opportunities and sustainability of multidisciplinary laboratory research post-COVID19. Existing institutional capacity can be repurposed to establish multidisciplinary research laboratories to support the strengthening of basic and clinical translational research capacity in resource limited settings and impact on public health and scientific knowledge for socioeconomic development.

It is well known that fiber sizing is one of the most important component in the manufacturing of composites, and it does affect the mechanical properties including strength and stiffness. In this work, the influence of fiber sizing levels on the mechanical properties of carbon fibers (CF) is reported at room temperature by using single fiber tensile testing (Favimat+), single fiber pullout testing (SFPO), and interfacial elemental analysis using X-ray photoelectron spectroscopy (XPS). Standard modulus of CF (7±0.2 μm in diameter) were sized using two Michelman commercially available sizing formulations. The average solid content for each sizing formulation is 26.3 ± 0.2% and 34.1 ± 0.2%, respectively. HEXION RIMR 135 with curing agent RIMH 137 was used as a model thermoset epoxy matrix during the SFPO measurements. A predictive engineering fiber sizing methodology is also developed. Sizing amounts of 0.5, 1, and 2 wt. % on the surface of the fiber is achieved for both sizing formulations. For each fiber sizing level, 50 single fiber tensile testing experiments and 20 single fiber pull-out tests were conducted. The ultimate tensile strength (σult) of the carbon fibers and the interfacial shear strength (τ_app) of the single fiber composite were analyzed. it is also investigated the effect of the sizing levels on the interfacial shear stress and the O/C (Oxygen/Carbon) surface composition ratio. As a result, generalized fiber sizing and characterization methods were established. The developed methods can be used to characterize the strength and interfacial shear strength of any man-made fibers with different sizing formulations and solid contents, irrespective of the matrix i.e. thermoset or thermoplastic.

The seed industry plays a crucial role in the global food production, but it faces a persistent challenge in ensuring the health and quality of seeds, particularly those of tomato and pepper, which represent key seed commodities on the global market. Seeds can serve as potential pathways for the introduction and dissemination of seed-borne bacteria, which may have devastating effects on crop yield, farmers’ remunerability, and food security. Therefore, fungicides and other anti-microbial compounds are extensively used to disinfect the seeds, thus increasing the input of chemicals in the agri-enviroment. In this review, we address aspects that connect disease epide-miology with seed infection and health, including seed contamination, endophytic colonization, and seed-borne infections. We focused on the main bacterial diseases affecting tomato and pepper by discussing their official seed testing methods as requirements supporting a smooth seed trade. Moreover, we present a survey on the past and recent innovations for seed treatments, focusing on sustainable disinfection methods. Therefore, this review will be a short, but indispensable guide for seed technologists and pathologists involved in the production of high-quality seeds, providing indications and suggestions to contrast seed-borne pathogens dissemination, avoid international controversies and complaints by phytosanitary authorities, extension services and farmers.

In this paper we evaluate the effects of hard and soft constraints on the Iterative Data Snooping (IDS), an iterative outlier elimination procedure. Here, the measurements of a levelling geodetic network were classified according to the local redundancy and maximum absolute correlation between the outlier test statistics, referred to as clusters. We highlight that the larger the relaxation of the constraints, the higher the sensitivity indicators MDB (Minimal Detectable Bias) and MIB (Minimal Identifiable Bias) for both the clustering of measurements and the clustering of constraints. There are circumstances that increase the family-wise error rate (FWE) of the test statistics, increase the performance of the IDS. Under a scenario of soft constraints, one should set out at least three soft constraints in order to identify an outlier in the constraints. In general, hard constraints should be used in the stage of pre-processing data for the purpose of identifying and removing possible outlying measurements. In that process, one should opt to set out the redundant hard constraints. After identifying and removing possible outliers, the soft constraints should be employed to propagate their uncertainties to the model parameters during the process of least-squares estimation.

The authors of the paper have made an attempt to detect the fibre content and fibre spacing in a steel fibre reinforced concrete (SFRC) industrial floor. Two non-destructive testing (NDT) methods: an electromagnetic induction technique and a radar-based technique were applied. The first method allowed to detect the spacing in subsequent layers located in the thickness of the slab. The result of the second method was a 3D visualization of the detected fibre in the volume of concrete slab. The conducted tests showed aptitude and limitations of the applied methods in estimating fibre volume and spacing. The two techniques also allowed to locate the areas with relatively low fibre concentration which are very likely to be characterized by low mechanical properties.

Eddy current sensors can be used to test the characteristics and measure the parameters of the conductive samples. As the main obstacle of the multi-frequency eddy current sensor, the lift-off distance affects the effectiveness and accuracy of the measurement. In this paper, a material-independent algorithm has been proposed for the restoration of the lift-off distance when using the multi-frequency eddy current sensor, which is based on the approximation under the thin-skin effect. Experiment testing on the performance of the proposed method is presented. Results show that from the dual-frequency inductance, the lift-off distance could be restored with a maximum error of 0.24 mm for the distance up to 12 mm. Besides, the derived lift-off distance is used for the inversion of the magnetic permeability. Based on a lift-off insensitive inductance (LII) feature, the magnetic permeability of steels can be inversed in an iterative manner, with an error of less than 0.6 % for the lift-off distance up to 12 mm.

Burkina Faso is a sub-Saharan African country with a high poverty rate that has quadruplicated its population in the last half fifty years, that is, from 4.5 to 18 million inhabitants. Such demographic changes together with an intense migration process from rural areas to large cities, among other issues, are contributing to a rapid process of socio-cultural transformation. In this context, changes in both traditional and contemporary housing are analyzed and a complete ther-mo-hygrometric evaluation is carried out by processing significant data from on-site measure-ments to shed new light on the response of the said dwellings to the environmental and local cultural values. Results show that the introduction of land ownership linked to climate change and the increasing scarcity of natural resources are forcing native ethnic groups to modify their traditional ways of life, threatening their subsistence. Consequently, we can prove that the new building typologies are not in the least suitable for the climatic conditions nor the rich cultural heritage of Burkina Faso. This fact, negatively affects the possibility of revitalizing vernacular and environmentally-oriented solutions for the contemporary world and the necessary advance to-wards a more sustainable architecture.

Purpose: Determine the internal consistency and reproducibility test-retest of the Barrier Scale for Cardiac Rehabilitation (BSCR) in Colombian population. Methods: 190 patients (67% men, average age = 65 ± 12 years) completed the scale in two moments, with an average of eight days between applications. Cronbach's Alpha and Intraclass Correlation (ICC) coefficients were calculated. Results: The internal consistency of the Colombian version of the BSCR was good (Cronbach's alpha = 0.85). The ICC of the instrument was 0.69 (95% CI 0.61-0.76), 0.78 (95% CI 0.71-0.84) when used in the interview type, and 0.47 (95% CI 0, 21-0.67) when it was self-completing. Conclusions: The EBRC has an acceptable reliability in the Colombian population, however, its reproducibility decreases when it is self-directed. Identifying barriers using this scale will allow developing strategies to increase participation and adherence to cardiac rehabilitation programs focused on the real needs of patients.

The existence of the hole on a plate affects the calculation of eddy current problems. Consequently, the accuracy for the prediction of the material properties decreases if the effect of the hole is not taken into account. In this paper, a novel analytical method based on the modified integration range is proposed which can address the presence of the hole. Due to the presence of the hole, the conventional Dodd-Deeds analytical solution cannot be used to calculate the inductance change. Therefore, a revised upper integration limit is introduced to replace the original limit -- ∞ when using the co-axially air-core electromagnetic sensor. With the presence of the hole, the magnitude of the received signal reduces, and the peak frequency feature changes. The analytical method is validated by measured and numerical simulation results. It is found that the upper limit is related to the radius of the open hole. With the new technique, the thickness of sample plates with holes can be estimated based on the peak frequency feature.

Blood testing is a crucial medical application. In this study, we applied Raman spectroscopy to test blood samples and obtained complete biological information, including the main components and compositions in these samples. Short-wavelength (532-nm green light) Raman scattering spectroscopy was conducted on samples of normal blood, abnormal blood in 3 types of preparation including whole blood, plasma, and serum, and the underlying information reflected by the biological characteristics detected in each sample type were analyzed. Raman spectroscopy results indicated that normal blood had high hemoglobin content, which suggests that hemoglobin is a major component of blood. Hemoglobin affects blood oxygen level. The characteristic peaks of hemoglobin were observed at 690, 989, 1015, 1182, 1233, 1315, and 1562–1649 cm−1. Analysis of plasma and serum samples indicated the presence of β-carotene, which exhibited characteristic peaks at 1013, 1172, and 1526 cm−1. In addition, surface-enhanced Raman spectroscopy was used to collect biological signals that are difficult to obtain in conventional Raman spectroscopy, including those of small molecules such as hormones, antibodies, and enzymes. Changes in biological information collected in this manner can be used as a basis for potentially diagnosing clinical diseases.

This research work has been based on a previous study by the authors that characterized the behavior of a polyimide-coated FBG sensor in a structural monitoring system. Sensors applied to structural health monitoring are affected in the presence of a state of multidirectional strains simultaneously. The previous study observed the influence of transverse strain (ε_y) while keeping longitudinal strain constant (ε_x), where the direction x is the direction of the optical fiber. The present study developed an experimental methodology which has consisted of carrying out a campaign of biaxial tests on cruciform specimens with three embedded FBG sensors coated with polyimide, acrylate and ORMOCER®. Applying the Strain–Optic Theory as reference, a comparison of the results obtained with the different coatings has been studied. This experimental work has done it possible to study the influence of transverse strain (ε_y) in the longitudinal measurement of each of the FBG sensor and the influence of the coating material. Finally, the calibration procedure as well as the strain sensitivity factor K for each sensor has been defined.

In attempting to predict the further course of the novel coronavirus (COVID-19) pandemic caused by SARS-CoV-2, mathematical models of different types are frequently employed and calibrated to reported case numbers. Among the major challenges in interpreting these data is the uncertainty about the amount of undetected infections, or conversely: the detection ratio. As a result, some models include assumptions about the percentage of detected cases among total infections while others completely neglect undetected cases. Here, we illustrate how model projections about case and fatality numbers vary significantly under varying assumptions on the detection ratio. Uncertainties in model predictions can be significantly reduced by representative testing, both for antibodies and active virus RNA, to uncover past and current infections that have gone undetected thus far.

The capacitor-mismatch among diverse defects caused by the manufacturing process variations significantly affects the linearity of capacitor-array used to implement the capacitive digital-to-analog converter (CDAC) in the successive-approximation-register (SAR) analog-to-digital converter (ADC). Accordingly, the linearity of the SAR ADC is limited by that of capacitor-array, resulting in serious yield loss. This paper proposes an efficient foreground self-calibration technique to enhance the linearity of the SAR ADCs by mitigating the capacitor-mismatch based on the split ADC architecture along with variable capacitors. In this work, two ADC channels (i.e., ADC1 and ADC2) for the split ADC architecture include their capacitive DACs (CDACs) whose binary-weighted capacitor-arrays consist of variable capacitors. A charge-sharing SAR ADC is used for each ADC channel. In the normal operation mode, their digital outputs are averaged to be the final ADC output, as in a conventional split ADC. In the calibration mode, every single binary-weighted capacitor for the two ADCs is sequentially calibrated by making parallel or/and antiparallel connection among two or thee capacitors from the two channels. For instance, because the capacitors of the CDACs ideally exhibit the binary-weighted relation as Cn=2×Cn−1, variable capacitor Cn of ADC1 can be updated to be closest to the sum of Cn−1 of ADC1 and Cn−1 of ADC2 for the calibration. For the process, the two capacitor-arrays of the two ADCs can be reconfigured to be connected to each other, so that Cn of ADC1 can be connected with two of Cn−1 of ADC1 and ADC2 in antiparallel. The two voltages at the top and the bottom plates of the CDAC are compared by a comparator of ADC1, and the comparison results are used to update Cn. This process is iterated, until Cn is in agreement with the sum of two of Cn−1. Finally, all the capacitors can be calibrated in this way to have the binary-weighted relation. The simulation results based on the proposed work with a split SAR ADC model verified that the proposed technique can be practically used, by showing that the total-harmonic-distortion and the signal-to-noise-and-distortion ratio were enhanced by 21.8-dB and 6.4-dB, respectively.

Genetics plays an integral role in athletic performance and is increasingly becoming recognised as an important risk factor for injury. Ankle and knee injuries are the most common injuries sustained by soccer players. Often these injuries result in players missing training and matches, which can incur significant costs to clubs. This study aimed to identify genotypes associated with ankle and knee injuries in soccer players and how these impacted the number of matches played. 289 soccer players including 46 professional, 98 semi-professional and 145 amateur players were genetically tested. Ankle and knee injuries and the number of matches played were recorded during the 2014/15 season. Four genes were assessed in relation to injury. Genotypes found to be associated with injury included the TT genotype of the GDF5 gene, TT and CT genotypes of AMPD1 gene, TT genotype of COL5A1 and GG genotype of IGF2 gene. These genes were also associated with a decrease in the number of matches played.

Meier–Gorlin syndrome (MGS) is a rare genetic developmental disorder that causes primordial proportional dwarfism, microtia, absent or hypoplastic patellae and other skeletal anomalies. Overlapping skeletal symptoms make MGS difficult to diagnose clinically. We describe a 3-year-old boy with short stature, recurrent respiratory infections, short-rib dysplasia, tower head and facial dysmorphisms who was admitted to the Tomsk Genetic Clinic to verify a clinical diagnosis of Jeune syndrome. Clinical Exome sequencing revealed two variants (compound heterozygosity) in the ORC6 gene: c.2T&gt;C(p.Met1Thr) and c.449+5G&gt;A. In silico analysis showed the pathogenicity of these two mutations and predicted a decrease in donor splicing site strength for c.449+5G&gt;A. An in vitro minigene assay demonstrated that variant c.449+5G&gt;A causes a complete skipping of exon 4 in ORC6 gene. The parents asked for urgent prenatal testing for MGS for the next pregnancy, but it ended in a miscarriage. Thus, this case report may help to prevent MGS misdiagnosis in the future. We also performed in silico and functional analyses of ORC6 mutations and developed a restriction fragment length polymorphism and haplotype-based short-tandem-repeat assay for prenatal genetic testing for MGS. These findings should elucidate MGS aetiology and improve the quality of genetic counselling for affected families.

In the first part of this article, we discuss and generalize the complete convergence introduced by Hsu and Robbins (1947) to the r-complete convergence introduced by Tartakovsky (1998). We also establish its relation to the r-quick convergence first introduced by Strassen (1967) and extensively studied by Lai (1976). Our work is motivated by various statistical problems, mostly in sequential analysis. As we show in the second part, generalizing and studying these convergence modes is important not only in probability theory but also to solve challenging statistical problems in hypothesis testing and changepoint detection for general stochastic non-i.i.d. models.

Since the first published genome sequence of Trypanosoma cruzi in 2005, there has been tremendous technological advance in genomics, reverse genetics, and assay development for this elusive pathogen. However, there is still an unmet need for new and better drugs to treat Chagas disease. Here we introduce a T. cruzi assay strain that is useful for drug research as well as basic studies in host-pathogen interaction. Trypanosoma cruzi STIB980 is a strain of discrete typing unit TcI that grows well in culture as axenic epimastigotes or intracellular amastigotes. We have evaluated the optimal parameters for genetic transfection and constructed derivatives of T. cruzi STIB980 that express reporter genes for fluorescence- or bioluminescence-based drug efficacy testing, as well as a Cas9-expressing line for CRISPR/Cas9-mediated gene editing. The genome of T. cruzi STIB980 was sequenced by combining short-read Illumina with long-read Oxford Nanopore technologies. The latter served for the primary assembly, the former to correct mistakes and fill the gaps. This resulted in a high-quality nuclear haplotype assembly of 28 Mb in 400 contigs, containing 10,043 open-reading frames with a median length of 1077 bp. We believe that T. cruzi STIB980 is a useful addition to the antichagasic toolbox, and propose that it can serve as a DTU TcI reference strain for drug efficacy testing.

Since sensor-based perception systems are used in autonomous vehicle applications, validating such systems is imperative to guarantee the robustness of the systems before they are being put to use. In this study, a comprehensive corruption-related simulation-based robustness verification and enhancement process for sensor-based perception systems is proposed. Firstly, we present a methodology and scenario-based corruption generation tools for creating diverse simulated test scenarios that can analogously represent real-world traffic environments, especially considering corruption types related to safety concern. Then, an effective corruption similarity filtering algorithm is proposed to remove corruption types with high similarity and identify the representative corruption types to represent all considered corruption types. As a result, we can generate efficient corruption-related robustness test scenarios with less testing time and good scenario coverage. Subsequently, we perform the vulnerability analysis of object detection models to identify model weaknesses and construct an effective training dataset for model vulnerability enhancement. This enhances the tolerance of object detection models to weather and noise-related corruptions, ultimately improving the robustness of the perception system. We employ case studies to demonstrate the feasibility and effectiveness of the proposed robustness verification and enhancement procedures. Additionally, we explore the impact of different "similarity overlap threshold" parameter settings on scenario coverage, effectiveness, scenario complexity (size of training and testing datasets), and time costs.

Background: The COVID-19 pandemic has promoted a shortage of filtering facepiece respirators (FFRs) and the emergence of new FFRs brands. We aimed to determine the fit provided by in-use FFRs in Peruvian healthcare workers (HCWs) during the COVID-19 pandemic. Methods: We enrolled 279 HCWs from 37 primary healthcare centers with highest burden of care for TB in Peru, of which 263 were assessed using quantitative fit tests (QNFT). Results were expressed as real-time fit factor (rt-FF) and overall fit factor (overall-FF), which was categorized as ≥100 (optimal result), 50-99, and <50. Results: We identified 3M 1860 FFRs (33.1%), Xiantao Zhong Yi ZYB-11 FFRs (24.7%) and Makrite 9500 FFRs (20.5%), mainly. Eighty-seven HCWs (33.1%) had an optimal overall-FF, 27 (10.3%) between 50-99, and 149 (56.7%) less than 50. Of the 87 HCWs with optimal over-all-FF, 73 (83.9%) were 3M 1860 FFR. Of the 27 participants with overall-FF between 50-99, 7 (25.9%) were Makrite 9500, while of the 149 with overall-FF less than 50, 58 (38.9%), and 47 (31.5%) were Xiantao Zhong Yi ZYB-11 and Makrite 9500, respectively. Conclusion: The Xiantao Zhong Yi and Makrite FFRs do not adapt adequately to the face of Peruvian HCWs, most having fit factors less than 50.

In the advent of COVID-19 pandemic, testing is highly essential to be able to isolate, treat infected persons, and finally curb transmission of this infectious respiratory disease. Group testing has been used previously for various infectious diseases and recently reported for large-scale population testing of COVID-19. However, possible sample dilution as a result of large pool sizes has been reported, limiting testing methods’ detection sensitivity. Moreover, the need to sample all individuals prior to pooling overburden the limited resources such as test kits. An alternative proposed strategy where test is performed on pooled samples from individuals representing different households is presented here. This strategy intends to improve group testing method through the reduction in the number of samples collected and pooled during large-scale population testing. Moreover, it introduces database system which enables continuous monitoring of the population’s virus exposure for better decision making.

Guided by the Conceptual Model of Implementation Research, we explored the acceptability, appropriateness, and feasibility of: 1) automated screening approaches utilizing existing health data to identify those who require subsequent diagnostic evaluation for familial hypercholesterolemia (FH) and 2) family communication methods including chatbots and direct contact to communicate information about inherited risk for FH. Focus groups were conducted with 22 individuals with FH (2 groups) and 20 clinicians (3 groups). These were recorded, transcribed, and analyzed using deductive (coded to implementation outcomes) and inductive (themes based on focus group discussions) methods. All stakeholders described these initiatives as: 1) acceptable and appropriate to identify individuals with FH and communicate risk with at-risk relatives; and 2) feasible to implement in current practice. Stakeholders cited current initiatives, outside of FH (e.g., pneumonia protocols, colon cancer and breast cancer screenings), that gave them confidence for successful implementation. Stakeholders described perceived obstacles, such as nonfamiliarity with FH, that could hinder implementation and potential solutions to improve systematic uptake of these initiatives. Automated health data screening, chatbots, and direct contact approaches may be useful for patients and clinicians to improve FH diagnosis and cascade screening.

Model-based image reconstruction has brought improvements in terms of contrast and spatial resolution to imaging applications such as magnetic resonance imaging and emission computed tomography. However, their use for pulse-echo techniques like ultrasound imaging is limited by the fact that model-based algorithms assume a finite grid of possible locations of scatterers in a medium -- which does not reflect the continuous nature of real world objects and creates a problem known as off-grid deviation. To cope with this problem, we present a method of dictionary expansion and constrained reconstruction that approximates the continuous manifold of all possible scatterer locations within a region of interest. The expanded dictionary is created using a highly coherent sampling of the region of interest, followed by a rank reduction procedure based on a truncated singular value decomposition. We develop a greedy algorithm, based on the Orthogonal Matching Pursuit (OMP), that uses a correlation-based non-convex constraint set that allows for the division of the region of interest into cells of any size. To evaluate the performance of the method, we present results of 2-dimensional ultrasound image reconstructions with simulated data in a nondestructive testing application. Our method succeeds in the reconstructions of sparse images from noisy measurements, providing higher accuracy than previous approaches based on regular discrete models.

Appropriate diagnostic testing to identify persons infected with SARS-COV-2 is a vital part of a health system’s ability to control the global pandemic of COVID-19 disease. The primary purpose of this review is to provide an overview of the mass testing strategy implemented throughout the UAE and the overall impact it has made on containing and controlling the spread of the disease. This study describes the mass testing strategy and capacity of the UAE during the pandemic of the new coronavirus SARS-COV-2. The UAE has conducted 15 million polymerase chain reaction (PCR) tests to SARS-COV-2, as of 15 November 2020. The number of tests per day varied from 10,000 by the end of March to 120,000 tests per day in November 2020. The mass testing initiative across the entire UAE forms an integral part of a bigger strategy focusing on testing, tracing contacts and isolating positive cases.

Globally, the use of whole-cell matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) in clinical microbiology laboratories has increased considerably. With the rapid growth of artificial intelligence technology, there is an increasing number of areas devoted to solving problems by implementing machine learning-based methods. Applying the use of artificial intelligence to the analysis of the massive amount of information obtained in the mass spectrum derived from MALDI-TOF MS should be a breakthrough in clinical microbiology. Specifically, it would facilitate a more rapid and accurate strain typing or antibiotic susceptibility test (AST) based on whole-cell MALDI-TOF MS spectra, and hence, it is a promising solution. Even though the reproducibility of peaks could result in some critical problems, computational methods have been developed to address this issue. Therefore, clinical microbiologists are able to perform strain typing or an AST as smoothly and easily as identifying species by using MALDI-TOF MS and artificial intelligence.

Blood testing is a crucial application in the field of clinical studies for disease diagnosis and screening, biomarkers discovery, organ function assessment, and personalized medication. Therefore, it is of utmost importance to collect precise data in a short time. In this study, we utilized Raman spectroscopy to analyze blood samples and extracted comprehensive biological information, including the primary components and compositions present in the blood. We conducted short-wavelength (532 nm green light) Raman scattering spectroscopy on blood samples, plasma, and serum, and subsequently analyzed the biological characteristics detected in each sample type. Our results indicated that whole blood had high hemoglobin content, which suggests that hemoglobin is a major component of blood. The characteristic Raman peaks of hemoglobin were observed at 690, 989, 1015, 1182, 1233, 1315, and 1562–1649 cm−1. Analysis of plasma and serum samples indicated the presence of β-carotene, which exhibited characteristic peaks at 1013, 1172, and 1526 cm−1. Additionally, in the field of medical blood testing, the novel 3D Silicon micro-channel device technology holds immense potential. It can serve as a substrate and helps to detect various diseases and biomarkers, providing real-time data to help medical professionals and patients better understand their health conditions. Changes in biological data collected in this manner could potentially be used to diagnose clinical diseases.

Chemical and mechanical properties of plasma-assisted nitrided (PAN), TiN cathodic arc coated, and PAN with TiN coated samples were thoroughly evaluated on tool steel samples of 1.2379. The evaluation involved SEM, nano-indentation, profilometer, micro scratch, and corrosion tests. The results revealed that PAN treatment alters the roughness of the surface, while it has minimal impact on the coefficient of friction. However, it increases the substrate's hardness, making it twice as hard and three times more resilient against scratch tests, along with improved corrosion resistance. TiN-coated samples are four times harder than untreated ones, but they exhibit a higher elastic modulus (E), leading to a lower H/E index. The most promising results were obtained with PAN+TiN treatment, combining high hardness (H) with lower E, resulting in a high H/E index, a crucial criterion for wear resistance. These samples also demonstrated superior scratch hardness and corrosion resistance, despite being thinner and rougher.

This paper presents an investigation of the oxidation of Alloy X-750 containing 5% Fe in a simulated boiling water reactor (BWR) environment. To mimic the conditions in which the bare metal is exposed to the reactor water the samples were not pre-oxidized. The specimens were exposed for durations ranging from 2 to 840 hours, and the development of the oxide microstructure was mainly studied using electron microscopy. The results showed that the oxide scale consisted of blocky crystals of trevorite on top of a porous inner layer rich in Ni and Cr. After the longest exposure time, the trevorite crystals completely covered the specimen surface. The study further revealed that the speed at which the oxide grew and the metal dissolved both decreased with time. Additionally, the metal thinning process was found to be sub-parabolic. Given the significant variation in iron content in the X-750 specification, the influence of this element on the material's corrosion performance in BWR was examined by comparing the results from this investigation with those from previous work on material containing 8 wt% Fe. The study demonstrated that the oxide growth, metal dissolution and metal thinning were slower in the material with higher Fe content, indicating the importance of this element in limiting the degradation of Alloy X-750 in BWR environments.

We investigated 328 SARS-CoV-2 cases in Barwon South West Victoria, Australia, in the 2020 pre-vaccination period, comparing infections with symptoms to those that remained asymptomatic. De-identified self-reported data from three sequential questionnaires on case characteristics and symptom progression were examined. Multivariable logistic regression were used to model associations between demographic profile and symptoms. Asymptomatic cases were more than three times as likely to be from ethnic minority groups [OR 3.2, 95% CI 1.5 – 6.7, p&lt;0.01], and approximately seven times more likely to be seniors (≥ 65 years) [OR 7.3, 95% CI 1.0 – 50.1] after adjusting for sex and occupation. The overrepresentation of ethnic minority groups among asymptomatic infections is suggestive of genetic haplotype variability by ethnic group, conferring greater cross protection from other coronaviruses in the early stages of the COVID-19 pandemic. This research should be repeated post-vaccination to reassess symptom expression according to ethnicity, and better comprehend case ascertainment impacts of cultural biases in testing and infection reporting, and the reliance on symptoms to trigger testing. These findings may in part reflect differences in testing patterns by ethnicity and true differences in disease expression, both important for appropriate transmission prevention strategies, and tailoring testing messaging towards ethnic minority communities.

For the soil in different regions, the nutrient fertility contained in it is different, and the detection and zoning management of soil nutrients before tillage every year can improve grain yield. In this paper, an integrated learning strategy model based on black soil hyperspectral data is designed for rapid classification of organic matter content classification of black soil. Soil hyperspectral image dataset of Xiangyang Experimental Base was collected; by changing the internal structure of the stacking model, an LSVM-stacking model with (MLP, SVC, DTree, XGBl, kNN) five classifiers as the L1 layer was built, and the simulated annealing algorithm was used for hyperparameter optimization. Compared to other stacking models, the LSVM-stacking metrics are significantly improved. The accuracy rate of hyperparameter optimization is improved by 38.6515%, the accuracy rate of the independent test data set is 0.9488, and the comparison of individual learners can improve the recognition classification accuracy of label"1" to 1.0.

Simultaneous measurement of different substances from a single sample is an emerging issue to achieve efficient and high-throughput detection in several fields of application. Although immunoanalytical techniques have well-established and prevailing advantages over alternative screening analytical platforms, one of the incoming challenges for immunoassay is exactly multiplexing. The Lateral Flow Immunoassay (LFIA) is a leading immunoanalytical technique for onsite analysis thanks to its simplicity, rapidity and cost-effectiveness. Moreover, LFIA architecture is adaptable to multiplexing and therefore candidates as a possible answer to the pressing demand of multiplexing point-of-need analysis. The review present an overview of diverse approaches for multiplex LFIA, with a special focus on strategies based on new types of magnetic, fluorescent and colored labels

Petrochemical plants use on-stream inspection more often to detect and monitor the corrosion on the equipment and piping system. Compared to ultrasonic thickness gauging and pulse-echo A-scan, phased array corrosion mapping has better coverability and can scan a large area to detect general and localized corrosion. This paper's objective is to obtain documentary evidence on the accuracy of corrosion detection from 30°C to 250°C on A36 low-carbon steel by carrying out simulation experiments every 10°C steps. A minimum of three sets of phased array corrosion mapping data in each temperature were collected to study and evaluate the detectability. The data evidence could enhance the confidence level of the plant's end users to use the phased array mapping in the future during an inspection. The experiments were found to be insufficiently thorough despite addressing the initial concerns, leaving more area for discussion in further studies, such as expanding the investigation to thicker carbon steel, stainless steel, and wedge materials.

The paper is focused on the examination of the internal quality of joints created in a multi-material - additive manufacturing process. The main part of the work focuses on experimental production and non-destructive testing of restrained joints of modified PLA (polylactic acid) and ABS (Acrylonitrile butadiene styrene) 3Dprinted on RepRap 3D device that works on the "open source" principle. The article presents the outcomes of non-destructive materials test in the form of the data from the Laser Amplified Ultrasonography, microscopic observations of the joints area and tensile tests of the specially designed samples. The samples with designed joints were additively manufactured of two materials: specially blended PLA (Market name – PLA Tough) and conventionally made ABS. The tests are mainly focused on the determination of the quality of material connection in the joints area. Based on the results obtained, the samples made of two materials were compared in the end to establish which produced material joint is stronger and have a lower amount of defects.

The performance of a normal-strength SHCC under impact loading was studied using the results obtained from a split Hopkinson tension bar (SHTB). The focus of the investigation is to explain the mechanisms behind the peculiar rate-dependent behavior of SHCC under tensile loading. With the help of frames obtained by high-speed cameras and the subsequent Digital Image Correlation (DIC) analysis, the stress-strain relation of the SHCC obtained in SHTB was analyzed. The investigation of the composite’s behavior was supported by constituent-level experiments on the non-reinforced matrix of the SHCC and on the fiber-matrix bond. In the case of the constituent matrix, the well-known apparent increase in the tensile strength of the cement-based matrix and its influence on the behavior of SHCC was studied. For this purpose, experiments on the SHCC specimens with different geometries were performed in the SHTB. The results obtained from these experiments and those obtained by DIC show that commonly used analytical models, in which the specimen is assumed elastic, cannot capture the effects of structural inertia on the results. Thus, an alternative novel method based on the results of DIC has been used to explain and quantify the contribution of structural inertia. The rate-dependent behavior of the fiber-matrix bond was studied by performing high-speed single fiber pullout tests in a miniaturized split Hopkinson tension bar. This novel experimental technique enabled explanation of the rate-dependent bridging action of the fibers in SHCC. Based on the results, the enhanced behavior of SHCC under impact loading is explained.

it still undergoes corrosion when exposed to corrosive environments. This paper proposes an evaluation method for assessing the corrosion level of SPCC steel specimens using traditional eddy current testing (ECT), along with two different machine learning approaches. The objective is to classify the corroded state of the specimens into two states: a less corroded state (state-1) and a highly corroded state (state-2). Generative and discriminative models were implemented for classification. The generative classifier was based on the Gaussian mixture model (GMM), while the discriminative model was based on the logistic regression model. The models used features based on the absolute maximum of the perturbation magnetic field components at two different frequencies. The performance of the classifiers was evaluated using metrics such as absolute error, accuracy, precision, recall, and F1 score. The results indicate that high classification accuracy can be achieved based on both methods using traditional eddy current testing.

The plate heat exchanger (PHE) is a component that provides heat to be transferred from hot water to domestic cold water without mixing them with high efficiency. Over the lifetime of the PHE, cyclic pressures act on the brazing points and the plates, and this may lead to fatigue failure. The fatigue behaviour of the PHE, designed by using copper-brazed 316L stainless steel, was investigated in this study. First, the fatigue tests under the load ratio R = 0.1 were performed on the Vibrophore 100 testing machine to obtain the S-N curve of the analysed brazed joint. Based on the obtained experimental results, an appropriate material model of the analysed brazed joint has been created, which was validated with numerical calculation in the framework of a program code Ansys. A validated material model was then used for the subsequent numerical analysis of PHE. In order to carry out a numerical calculation using the finite element method (FEM), a 3D model of the heat exchanger was created based on the previous scanning of PHE-geometry. Thereafter, the geometry was parameterised, which allowed us to perform parametric simulations (monitoring different responses depending on the input geometry). Numerical simulations were carried out in the framework of the Ansys software, whereby the obtained results were analysed, and the responses were appropriately characterised according to previously determined load cases.

Flare stacks are a key element in the safety of petrochemical and refinery industries; the correct operating conditions thereof must be ensured through a schedule for the periodic reviewing of all parts thereof. Advances in Non-Destructive Testing (NDT) in recent years and the application thereof to this field allow reliable, objective information to be obtained. This article describes and groups together the main applicable NDT techniques, analysing their advantages and disadvantages, updated with the new possibilities offered by unmanned aircraft or drones.

This work investigates the influence of strain rate on the stress/strain behaviour of Scalmalloy. This material is an aluminium-scandium-magnesium alloy, specifically developed for additive manufacturing. The bulk yield stress of the material processed by Selective Laser Melting is approximately 340 MPa which can be increased by heat-treating to approximately 530 MPa. These numbers, combined with the low mass density of 2.7 g/cm3, make Scalmalloy an interesting candidate for lightweight crash-absorbing structures. As this application is inherently dynamic, it is of interest to study the loading rate sensitivity, which is difficult to predict: Al-Sc alloys exhibit classic strain rate sensitivity with an increased yield stress at elevated strain rates. However, Al-Mg alloys are known to show the contrary effect, they exhibit less strength as strain rate is increased. To answer the question how these effects combine, we study the dynamic behaviour at four different strain rates ranging from 10−3 /s to 1000 /s using servo-hydraulic and Split-Hopkinson testing methods. The resulting data is analysed in terms of strain rate sensitivity of tensile strength and failure strain. A constitutive model based on a simplified Johnson-Cook approach is employed to simulate the tensile tests and provides good agreement with the experimental observations.

Nitrogen and phosphorous support the ecosystem by supplying nutrients to algae and aquatic plants. Having them in excess results in the eutrophication of waters creating quality problems. In the past, nitrogen has been widely investigated for wells in the context of groundwater flow. However, a national-scale nitrogen assessment in rivers and streams has not received enough attention. In this research, the Wilcoxon rank sum test, as a non-parametric hypothesis testing method, has been applied to nitrogen concentration in the form of nitrate-nitrogen and nitrite-nitrogen in rivers and streams of the Contiguous United States. This approach was particularly selected because of the non-normal and positively skewed nitrogen levels occurring in the surface flow. This method was able to identify the impaired body of waters as well as quantify the confidence, significance, and errors involved. The Northern Appalachians (NAP), Northern Plains (NPL), and Xeric (XER) ecoregions were worsening in the nitrogen-nitrate condition with NAP, and XER needed immediate actions. The nitrite-nitrogen condition did not pose an immediate threat, so mitigation plans should focus more on nitrate-nitrogen remediation. It was shown that the method was superior to the two-sample t-test by yielding lower type II errors.

It is generally accepted that the human abdominal wall is comprised of skin, subcutaneous tissues, muscles and their aponeuroses, and the parietal peritoneum. Understanding these layers and their mechanical properties provides valuable information to those designing procedural skills trainers, supporting surgical procedures (hernia repair), and engineering-based work (in silico simulation). However, there is little literature available on the mechanical properties of the abdominal wall in layers or as a composite. This work characterizes the tensile properties of the human abdominal wall by layer and as a partial composite. Tissues were collected from fresh-never-frozen and fresh-frozen cadavers and tested in uniaxial tension at a rate of 5 mm/min until failure. Stress-strain curves were created for each sample, and the values for elastic moduli, ultimate tensile strength, and strain at failure were obtained. The experimental outcomes from this study demonstrated variation of tensile properties within and between tissues. The data also suggest that the tensile properties of composite abdominal walls are not additive. Ultimately, this body of work contributes to a deeper comprehension of these mechanical properties and will serve to enhance patient care, refine surgical interventions, and assist with more sophisticated engineering solutions.

In this paper, a non-destructive test to diagnose wear of blade´s compressor of a gas turbine is reported. Gas turbine was operating in Campeche City, Mexico, in a very aggressive environment, where the entry of solid particles is unavoidable. The objective was to reduce cost of maintenance in this equipment. Analysis on a blade of gas turbine was performed, which was in operation on an offshore platform. Compressor blade was exposed to a severe damage by the impact of particles and environmental pollutants such as salts, sands and sulphurs. In first stage of this analysis, a visual inspection with a borescope was performed, which has the ability to illuminate dark internal areas, with a bright light for visual examination and/or make a photographic reproduction in semi-annual maintenance cycles. Images analysis was used to determine the typical failure modes. In a second stage, a tribological characterization was carried out. Chemical composition of the material of blades was obtained. Scanning electron microscopy (SEM) was used to measure roughness and evaluate degradation of surfaces of blades after 30,000 service hours. The points, where peak stresses were calculated, correspond to those places in witch corrosion and some irregular scratches similar to plowing action, was observed. These are the points in which failures take place. Results showed wear modes were originated by a severe stinging action. Also, large craters, similar to those observed in solid particle erosion, were developed by at normal impact. In the same way it could be found some localized areas with a witch corrosion and irregular scratches similar to plowing action, was observed. These are the points in which failures take place.

In modern Commercial Off-The-Shelf (COTS) multicore systems, cores can produce several simultaneous memory requests. The processing of such requests over the memory controller negatively impacts the interference delay triggered by running parallel tasks on the platform. In this paper, we propose a software-based testing approach for analyzing memory interference delay, when cores are exposed to extensive read/write requests that access in parallel their Cache Coherent Interconnect. The hardware targeted in this work is the well-known LayerScape QorIQ LS2085A, which can be approached as a potential successor to the Freescale QorIQ P4080. The test analysis was conducted based on a bare-metal operating system that we developed to guarantee a deterministic execution environment at all time points. Our testing was accomplished using a set of carefully designed synthetic benchmarks as well as TACLeBench benchmarks.

Titanium’s accelerating usage in global markets is attributable to its distinctive combination of physical and metallurgical properties. The key to best utilizing titanium is to exploit these characteristics, especially as they complement one another in a given application, rather than to just directly substitute titanium for another metal. Titanium alloy are extensively used in aerospace applications such as components in aero-engines and space shuttles, mainly due to their superior strength to weight ratio. For these demanding applications functionality and reliability of components are of great importance. To increase flight safety, higher sensitivity inspections are sought for rotating parts. Increased sensitivity can be applied at the billet stage, the forging stage, or both. Inspection of the forging geometry affords the opportunity to apply the highest sensitivity due to the shorter material paths when compared to those required for billet inspections. Forging inspection is typically performed for titanium (Ti) rotating parts with immersion inspection and fixed-focus, single-element transducers. Increased gain is required with depth because the ultrasonic beam attenuates with distance and diverges beyond the focus position that is placed near the surface. The higher gain that is applied with depth has the effect of increasing the UT noise with depth. The relationships between the UT noise, selection of the examination technique and the smallest detectable defect are presented in this material.

The relative dislocation density of aluminum and copper samples is quantitatively measured using linear Resonant Ultrasound Spectroscopy (RUS). For each metallic group, four samples were prepared with different thermomechanical treatments in order to induce changes in their dislocation densities. The RUS results are compared with Nonlinear Resonant Ultrasound Spectroscopy (NRUS) as well as Second Harmonic Generation (SHG) measurements. NRUS has a higher sensitivity by a factor of two to six and SHG by 14% to 62%. The latter technique is, however, faster and simpler. As main a result we obtain a quantitative relation between the changes in the nonlinear parameters and the dislocation density variations, which in a first approximation is a linear relation between these differences. We also present a simple theoretical expression that explains the better sensitivity to dislocation content of the nonlinear parameters with respect to the linear ones. X-Ray diffraction measurements, although intrusive and less accurate, support the acoustics results.

In recent decades, low-yielding seismic devices based on the use of friction dampers have emerged as an excellent solution for the development of building structures with improved reparability and resilience. Achieving an optimal design for such low-yielding seismic devices requires precise control of bolt preloading levels and predictability of the friction coefficient (CoF) between the damper interfaces. While various types of friction devices exist, capable of providing significant energy dissipation, ongoing research is focused on the development of novel friction materials that exhibit a stable hysteretic response, high CoF values, minimal differences between static and dynamic CoF, and predictable slip resistance. In this context, an experimental campaign was conducted at the STRENGTH Laboratory of the University of Salerno to evaluate the behaviour of new friction shims employing specially developed metal alloys. Specifically, the influence of the characteristics of the contact surfaces in the sliding area on the behaviour and performance of the friction device was analysed. The tests followed the loading protocol recommended by EN12159 for seismic device qualification. Monitored parameters included preloading force values and the evolution of slip resistance. The friction value was determined, along with its degradation over time. Finally, the material's performance in terms of hysteretic behaviour was assessed, providing a comparison of the tested specimens in terms of slip force degradation and energy dissipation capacity.

Dermatophytes are the most common cause of fungal infections worldwide, affecting millions of people annually. The emergence of resistance among dermatophytes along with the availability of antifungal susceptibility procedures suitable for testing antifungal agents against this group of fungi make the combinatorial approach particularly interesting to be investigated. Therefore, we reviewed the scientific literature concerning the antifungal combinations in dermatophytes. A literature search on the subject performed in PubMed yielded 68 publications: 37 articles referring to in vitro studies, and 31 articles referring to case reports/clinical studies. In vitro studies involved over 400 clinical isolates of dermatophytes (69% Trichophyton spp., 29% Microsporum spp., and 2% Epidermophyton floccosum). Combinations included two antifungal agents or an antifungal agent plus another chemical compound including plant extracts/essential oils, calcineurin inhibitors, peptides, disinfectant agents and others. In general, drug combinations yielded variable results spanning from synergism to indifference. Antagonism was rarely seen. In over 700 patients with documented dermatophyte infections an antifungal combination approach could be evaluated. The most frequent combination included a systemic antifungal agent administered orally (i.e.: azole [mainly itraconazole], terbinafine or griseofulvin) plus a topical medication (i.e.: azole, terbinafine, ciclopirox, amorolfine) for several weeks. Clinical results indicate that association of antifungal agents is effective, and it might be useful in accelerate the clinical and microbiological healing of a superficial infection. Antifungal combinations in dermatophytes have gained considerable scientific interest over the years and, in consideration of the interesting results available as far, it is desirable to continue the research in this field.

The issue of optimising the initial stand density (ISD) of tree plantations has high practical importance. The objective of this study was to nondestructively evaluate the influence of the initial stand density of Scots pine plantations located in the European part of the Russian Federation on wood basic density (BD), moisture content (MC), ultrasound velocity (UV), latewood content, and drilling resistance (DR). 45-year-old trees with stand densities of 500, 1000, 3000, 5000, and 10000 trees/ha were tested by a 5-cm-long core sample for gravimetric MCGM and BD, by PULSAR-2.2 for UV along the height (UVH) and through the tree trunk diameter (UVD), by the IML-RESI PD-400 tool for DR, and by GANN HT 85T for MC based on the electrical resistance method (MCERM). A significant influence of ISD was found on DBH, UVD, MCGM, and MCERM. ISD had no significant impact on BD, UVH, and DR. The wood BD ranged from 356 to 578 kg/m-3, with a mean value of 434±3.3 kg/m-3, and was restricted by the soil and environmental factors. DBH and 70% MCERM were good indicators of tree vitality. Linear correlations between DBH and MCERM (R2=0.67), DBH and MCGM (R2=0.74), DR and BD (R2=0.71), and the two-factor model MCGM=f(DBH, BD), (R2=0.76) were found.

Currently, many manufacturing industries use machine learning, artificial intelligence, robotics, and blockchain technologies as process-streamlining instruments of industry 4.0. Before implementing industry 4.0 tools in any process of a manufacturing industry's supply chain, it is essential to evaluate their adaptability. In this paper, the adaptability of industry 4.0 procurement tools to an oil and gas-related manufacturing company's procurement process is evaluated to determine the company's level of maturity. The active participation of participants is evaluated to determine the level of maturity of the main procurement process areas. The results identified the areas of the procurement process that can be improved by implementing the suggested industry 4.0 tools and techniques.

The FDA has concluded that a biosimilar candidate capable of demonstrating pharmacodynamic biomarkers in a healthy subject need not be tested for clinical efficacy in patients, regardless of if the biomarker correlates with clinical response. Since monoclonal antibodies (mAbs) do not trig-ger pharmacodynamic response, they can be substituted with robust functional disqualifying them for this waiver that can be overcome by allowing comparison of functional properties that eventually result in clinical response. This suggestion is based on the FDA's preference for more sensitive testing methods. However, clinical efficacy testing in patients is the least sensitive method, as confirmed by statistical modeling, a fact that regulatory agencies need to admit. In this paper, I present a logical and rational argument to establish the biosimilarity of products that do not have pharmacodynamic biomarkers based on their orthogonally proven functional bio-similarity. This understanding will significantly lower the development cost of biosimilars, a goal that the FDA outlined in all its guidance. Keywords: biosimilarity 1; biosimilars 2; pharmacodynamic biomarkers 3; monoclonal antibodies 4; FDA 5; clinical efficacy testing in healthy subjects 6; clinical efficacy testing in patients 7; functional assays 8; receptor binding 9.

Three-point shooting plays an important role in determining the outcome of the basketball games, and could be relevant for player selection. However, there has been little research into the relationship between basketball players' physical capacities, metabolic capacities and three-point shooting accuracy, particularly among female players. The aim of this study was to examine the relationship between physical capacities, metabolic capacities and dynamic three-point shooting accuracy in female professional basketball players. Twelve female professional basketball players from the Women’s Chinese Basketball Association (WCBA) league (age: 19.04±1.31 years, height: 181.33±4.90cm, playing experience: 7.83±1.7 years) were recruited for this study. Pearson correlations and multiple linear regression analysis were run to assess the relationship between physical capacities, metabolic capacities and dynamic three-point shooting. Results showed that coordination, balance, core strength and relative average power were positively correlated with the three-point shooting accuracy (r>0.58, P<0.05), while no other variables showed significant correlations. The current study suggests that coaching staff should consider coordination, balance, core strength and anaerobic capacities when selecting players as well as in their training periodization if three-point shooting accuracy is considered relevant.

For the electromagnetic eddy current testing, various methods have been proposed for reducing the lift-off error on the measurement of samples. In this paper, instead of eliminating the measurement error caused by the lift-off effect, an algorithm has been proposed to directly measure the lift-off distance between the sensor and non-magnetic conductive plates. The algorithm is based on a sample-independent inductance (SII) feature. That is, under high working frequencies, the inductance is found sensitive to the lift-off distance and independent of the test piece under an optimal single high working frequency (43.87 kHz). Furthermore, the predicted lift-off distance is used for the thickness prediction of the non-magnetic conductive samples using an iterative method. Considering the eddy current skin depth, the thickness prediction is operated under a single lower frequency (0.20 kHz). As the inductance has different sensitivities to the lift-off and thickness, the prediction error of the sample thickness is different from that of the lift-off distance. From the experiments on three different nonmagnetic samples – aluminium, copper, and brass, the maximum prediction error of the lift-off distance and sample thickness is 1.1 mm and 5.42 % respectively at the lift-off of 12.0 mm.

This essay is a personal insight based on my own experience in the Iberian Pyrenees, which addresses three situations common in paleoecological research, such as the verification of previously devised hypotheses (anticipation), the finding on unknown events in unstudied sites (discovery) and the finding of unexpected outputs in already known areas (serendipity). The account is concentrated on the value of the coring sites by themselves as generators of paleoecological knowledge, rather than on the actual findings, which are presented and discussed in the corresponding data papers. The main aim is to show that there is still much room for new findings, even in areas that have been surveyed for long time and are supposed to be well known, from a paleoecological perspective. Finally, some general lessons are derived and conceptualized.

The emerging industry of offshore wind turbines mounted on floating bases has garnered significant attention from both academia and industry. The desire to understand the complex physics of these floating structures has led to the development of numerical and physical modelling techniques. While physical testing has traditionally been employed, there is a growing focus on cost-effective and accurate high-fidelity numerical modelling as a potential alternative or supplement. However, commonly used numerical engineering tools in the offshore industry are considered mid- to low-fidelity and may lack the desired precision for floating offshore wind turbines (FOWTs). Given the complexity of these simulation codes, it is crucial to validate their accuracy. To address this, the International Energy Agency (IEA) Wind Technology Collaboration Programme initiated various research endeavors, including the Offshore Code Comparison Collaboration (OC3), Offshore Code Comparison Collaboration Continuation (OC4), Offshore Code Comparison Collaboration Continuation with Correlation (OC5), and the recent Offshore Code Comparison Collaboration Continued with Correlation and Uncertainty (OC6) projects. This study offers a comprehensive survey of the simulation tools available for FOWTs which were part of OC projects, focusing particularly on horizontal axis wind turbines (HAWTs) and highlighting their capabilities and fundamental theories.

The manual muscle test (MMT) is a flexible diagnostic tool, which is used in many disciplines, applied in several ways. The main problem is the subjectivity of the test. The MMT in the version of a “break test” depends on the tester’s force rise and the patient’s ability to resist the applied force. As a first step, the investigation of the reproducibility of the testers’ force profiles is required for valid application. The study examined the force profiles of n=29 testers (n=9 experiences (Exp), n=8 little experienced (LitExp), n =12 beginners (Beg)). The testers performed 10 MMTs according to the test of hip flexors, but against a fixed leg to exclude the patient’s reaction. A handheld device recorded the temporal course of the applied force. The results show significant differences between Exp and Beg concerning the starting force (padj=0.029), the ratio of starting to maximum force (padj=0.005) and the normalized mean Euclidean distances between the 10 trials (padj=0.015). The slope is significantly higher in Exp vs. LitExp (p=0.006) and Beg (p=0.005). The results also indicate that experienced testers show inter-tester differences and partly even a low intra-tester reproducibility. That highlights the necessity of an objective MMT-assessment. Furthermore, an agreement on a standardized force profile is required – a suggestion is given.

In vitro testing is the first important step in the development of new biomaterials. The human fetal osteoblast cell line hFOB 1.19 is a very promising cell model; however, there are vast discrepancies in cultivation protocols, especially in the cultivation temperature and the presence of selection reagent, geneticin (G418). We intended to use hFOB 1.19 for the testing of Zn-based degradable metallic materials. However, the sensitivity of hFOB 1.19 to zinc ions has not yet been studied. Therefore, we compared the toxicity of zinc towards hFOB 1.19 under different conditions and compared it with that of the L929 mouse fibroblast cell line. We also tested the cytotoxicity of three types of Zn-based biomaterials in two types of media. The presence of G418 used as a selection reagent decreased the sensitivity of hFOB 1.19 to Zn2+. hFOB 1.19 were more sensitive to Zn2+ at elevated (restrictive) temperatures. hFOB 1.19 were less sensitive to Zn2+ than L929 (both as ZnCl2 and extracts of alloys). Therefore, the appropriate cultivation conditions of hFOB 1.19 during biomaterial testing should be chosen with caution.

Genetic testing has expanded out of the research laboratory into medical practice and the direct-to-consumer market, and rapid analysis of the resulting genotype data can now have significant impact. We present a method for summarizing personal genotypes as ‘genotype fingerprints’ that meet these needs. Genotype fingerprints can be derived from any single nucleotide polymorphism (SNP)-based assay, and remain comparable as chip designs evolve to higher marker densities. We demonstrate that they support distinguishing types of relationships among closely related individuals and closely related individuals from individuals from the same background population, as well as high-throughput identification of identical genotypes, individuals in known background populations, and de novo separation of subpopulations within a large cohort through extremely rapid comparisons. While fingerprints do not preserve anonymity, they provide a useful degree of privacy by summarizing a genotype in a way that prevents reconstruction of individual marker states. Genotype fingerprints are therefore well-suited as a format for public aggregation of genetic information to support ancestry and relatedness determination without revealing personal health risk status.

Diagnosis and prognosis of failures for aircrafts’ integrity are some of the most important regular functionalities in complex and safety-critical aircraft structures. Further, development of failure diagnostic tools such as Non-Destructive Testing (NDT) techniques, in particular, for aircraft composite materials, has been seen as a subject of intensive research over the last decades. The need for diagnostic and prognostic tools for composite materials in aircraft applications rises and draws increasing attention. Yet, there is still an ongoing need for developing new failure diagnostic tools to respond to the rapid industrial development and complex machine design. Such tools will ease the early detection and isolation of developing defects and the prediction of damages propagation; thus allowing for early implementation of preventive maintenance and serve as a countermeasure to the potential of catastrophic failure. In this paper, following a short introductory summary and definitions, this paper provides a brief literature review of recent research on failure diagnosis of composite materials with an emphasis on the use of NDT techniques in aerospace industry. In addition to this, within a some of significant NDT application extents, prognosis of composites is also briefly discussed.

As with every new technology, safety demonstration is a critical component of bringing products to market and gaining public acceptance for cultured meat and seafood. This manuscript develops research priorities from the findings from a series of interviews and workshops with governmental scientists and regulators from food safety agencies in fifteen jurisdictions globally.  The interviews and workshops aimed to identify the key safety questions and priority areas of research. Participants raised questions about which aspects of cultured meat and seafood production are novel, and the implications of the paucity of public information on the topic. Novel parameters and targets may require the development of new analytical methods or adaptation and validation of existing ones, including for a diversity of product types and processes. Participants emphasized that data sharing of these efforts would be valuable, similar to those already developed and used in the food and pharmaceutical fields. Contributions to such databases from the private and public sectors would speed general understanding as well as efforts to make evaluations more efficient. In turn, these resources, combined with transparent risk assessment, will be critical elements of building consumer trust in cultured meat and seafood products.

This work exclusively focuses on the assessment of the thermal performance of a multifunctional facade panel incorporating PCM in foam layers, recurring to a hot box heat flux meter method to determine the thermal transmittance (U-value). The experimental setup is based on the steady-state approach using climatic chambers, assuring a stable thermal environment. Even small fractions of PCM achieved a small reduction in thermal amplitude. Numerical simulations using Ansys Fluent were developed to evaluate the performance of PCM use over a wide range of temperature boundary conditions and operating modes. These numerical models were calibrated and validated using the results of experimental tests, achieving a correlation factor of 0.9674, thus accurately representing a real-world scenario. The decrement factor (f) was used to analyse the data. It was identified that the efficiency of the panel and size of the optimum region increased with the PCM fraction growth. The simulated behaviour was optimum when the input mean temperature is of 20 °C for a room temperature of between 18-20 °C. The results show the significant potential of the multi-layered panel and the thermal regulator effect of the PCM incorporated on indoor space temperature to reach good thermal comfort levels.

We present a simulation library in Python 3 called Lumos. Different optimization routines areimplemented using multiple instruments. Automated measurements are implemented in this librarywhich lead to faster measurements as compared to manual sweeps. We elaborate on the experimentalmethods and also example usage is mentioned.

We address Multi-Wall Carbon NanoTubes (MWCNTs) for structural health monitoring in adhesive bonds such as in building structures. MWCNT-loaded composites are employed to sense strain changes under tension load using an AC impedance measurement setup. Different weight percentages of 1, 1.5, 2 and 3 wt.% MWCNT are added to the base epoxy resin using different dispersion times, i.e. 5, 10 and 15 minutes. The equivalent parallel resistance of the specimens is measured by applying an alternating voltage at different frequencies. To determine the mechanical as well as sensory properties, the specimens are subjected to a tensile test with concurrent impedance measurement. Using alternating voltage, a higher sensitivity of the impedance reading can be achieved. Employing these sensors in buildings and combining the readings of a network of such devices can significantly improve the buildings’ safety. Additionally, networks of such sensors can be used to identify necessary maintenance actions and locations.

This report describes the collection of a large dataset (6930 measurement) on dimensional error in the fused deposition modeling (FDM) additive manufacturing process for full-density parts. Three different print orientations were studied, as well as seven raster angles (0°, 15°, 30°, 45°, 60°, 75°, and 90°) for the rectilinear infill pattern. All measurements were replicated ten times on ten different samples to ensure a comprehensive dataset. Eleven polymer materials were considered: acrylonitrile butadiene styrene (ABS), polylactic acid (PLA), high-temperature PLA, wood-composite PLA, carbon-fiber-composite PLA, copper-composite PLA, aluminum-composite PLA, high-impact polystyrene (HIPS), polyethylene terephthalate glycol-enhanced (PETG), polycarbonate, and synthetic polyamide (nylon). The samples were ASTM-standard impact testing samples, since this geometry allows the measurement of error on three different scales; the nominal dimensions were 3.25mm thick, 63.5mm long, and 12.7mm wide. This dataset is intended to give engineers and product designers a benchmark for judging the accuracy and repeatability of the FDM process for use in manufacturing of end-user products.

The neuroglial extracellular matrix (ECM) provides critical support and physiological cues for the proper growth, differentiation, and function of neuronal cells in the brain. However, in most in vitro settings that study neural physiology, cells are grown as monolayers on stiff surfaces that maximize adhesion and proliferation, and therefore lack the physiological cues that ECM in native neuronal tissues provides. Macromolecular crowding (MMC) is a biophysical phenomenon based on the principle of excluded volume that can be harnessed to induce native ECM deposition by cells in culture. Here, we show that MMC using two species of Ficoll with vitamin C supplementation significantly boosts deposition of relevant brain ECM by cultured human astrocytes. Dopaminergic neurons co-cultured on this astrocyte-ECM bed prepared under MMC treatment showed longer and denser neuronal extensions, a higher number of pre ad post synaptic contacts, and increased physiological activity as evidenced by higher frequency calcium oscillation, compared to standard co-culture conditions. When the pharmacological activity of various compounds was tested on MMC-treated co-cultures, their responses were enhanced, and for apomorphine, a D2-receptor agonist, it was inverted in comparison to control cell culture conditions, thus emulating responses observed in in vivo settings. These results indicate that macromolecular crowding can harness the ECM-building potential of human astrocytes in vitro forming an ultra-flat 3D microenvironment that makes neural cultures more physiological and pharmacological relevant.

A COVID-19 disease threatens the population and the economies of the countries significantly. Till now, this pandemic has affected 215 counties or territories. Unavailability of vaccine is the primary concern for the society. To avoid the spread of this disease, social isolation must be preserved and the inter and intra-population movement must be minimized. To reduce the possibility of transmission, the categorization of regions based on susceptibility to COVID-19 infection is a must.Due to the unavailability of a large amount of paper collection for this novel COVID-19 diseases, we used current literature available on a COVID-19 susceptibility of the diabetic patient, human reproductivity, hemodialysis patient’s, pregnant women and meteorological factors and geographical location. Countries in the cold region are more susceptible to the risk of COVID-19 transmission. There was no evidence of the spread of this disease from non-respiratory bodies. Diabetic patients and pregnant women were found to be more susceptible to COVID-19 infection. Anosmia was observed in the majority of the COVID-19 infected cases in European countries. No evidence indicates COVID-19's impact on the human reproductive system explicitly. No cases of vertical transmission of this disease have been observed until now. All the studies available till now is the small scale study. Correlation with something always does not mean causation. There are certain factor like pollution level, temperature Diurnal temperature range, geographical factor, humidity, pollution level, wind speed, population density, medical healthcare facilities social and political factor plays a critical role in transmitting the SARS-COV-2 virus. Besides the adverse effects, it has taught us to shed our selfish goals and to promote the welfare of all.

The azimuth wheel-rail of large aperture radio telescope is the key component, it not only sup-ports the whole weight of the antenna, but also directly affects the pointing performance of the antenna with its surface accuracy. The whole weight of the radio telescope is hundreds or even thousands of tons, its azimuth frame rollers have great contact stress with the wheel-rail surface, repeated rolling can cause rolling contact fatigue on the wheel-rail surface, resulting in wear, cracks and other damage to the wheel-rail, and even lead to failure or fracture of the wheel-rail in serious cases, so it is very important to monitor the damage of the antenna wheel-rail. In order to visually detect the use of antenna wheel-rail surface, this paper proposed the method using electromagnetic ultrasonic detection to detect the damage of antenna wheel-rail surface for the first time. Based on the electromagnetic ultrasonic nondestructive testing principle, the simplified wheel-rail model containing wear, corrosion and crack damage is simulated. The results show that this method can effectively detect the surface damage of the antenna wheel-rail surface, and it can provide an important reference for the research of wheel-rail damage detection of large radio telescope.

In this case study, we describe a well-resourced private school system that implemented COVID-19 mitigation measures based on public health expert guidance as well as the lessons learned from this process. Avenues is a 10-year-old private school with campuses in NYC, São Paulo, Shenzhen, Silicon Valley, as well as online, which offers education at sixteen grades: 2 early learning years, followed by a pre-kindergarten–grade 12 school. We describe the mitigation measures Avenues implemented. We compare COVID-19 case prevalence at the school to the reported case prevalence in New York City, as reported by the New York State Department of Health. We compare the school's indoor air quality (IAQ) to ambient IAQ measures reported in the literature. The school's COVID-19 transmission mitigation measures successfully reduced the prevalence of COVID-19 among its students, staff, and faculty. The school also established a consistent high level of IAQ through various ventilation mechanisms. The school received positive parent and community feedback on the policies and procedures it established, with many parents commenting on the high level of communication and trust established by the school. This successful school reopening provides useful data for school closure and reopening standards to prepare for future pandemic and epidemic events.

In Los Angeles, at one point, the Covid-19 testing positivity rate was 6.25%, or one in sixteen. This translates to, on average, one in sixteen specimens testing positive and the vast majority testing negative. Usually, we run sixteen tests on sixteen specimens to identify the positive one(s). This process can be time consuming and expensive. Since a group of negative specimens pooled together for testing will produce a negative result, one single test could potentially eliminate many specimens. Only when the pooled specimen tests positive do we need further testing to identify the positive one(s). Based on this concept, we designed a strategy that will identify the positive specimen(s) efficiently. Assuming one in sixteen specimens is positive, we find that only four tests are needed. Furthermore, we can run them simultaneously, saving both resources and time. Although, in the real world, we cannot make the assumption of only one positive specimen, the same strategy works with slight modification and proves to be much more efficient than the conventional testing. Our strategy returns an answer 48% of the time in four tests and one time cycle. Overall, the average number of tests is seven or eight depending on the follow-up testing, and the average time cycle is about one and a half.

Accurate clinical diagnosis of patients presenting to primary care settings with acute sore throat remains challenging, often resulting in the over-prescribing of antibiotics. Using point-of-care tests (POCTs) to differentiate between respiratory infections is well-accepted, yet evidence on the application within primary care is sparse. We assessed the application of testing patients (n=160) from three family practices with suspected Streptococcal infections using rapid molecular tests (ID NOW Strep A2, Abbott). In addition to comparing clinical evaluation and prescription rates with either usual care or with testing, patients and staff completed a questionnaire about their experience of molecular POCT in primary care. The immediate availability of the result was important to patients (100%) and staff (≈90%) stated that molecular testing improved quality of care. Interestingly, only 22.73% of patients with a Centor score >2 tested positive for Strep A and overall, less than 50% of Centor scores 3 and 4 tested positive for Strep A with the ID NOW testing platform. The addition of rapid molecular POCTs to clinical assessment resulted in a 55- 65% reduction in immediate and deferred antibiotic prescriptions. The intervention was popular with patients and medical staff but was associated with increased cost and a longer appointment length.

Modal testing is a common step in aerostructure design, serving to validate the predicted natural frequencies and mode shapes obtained through computational methods. The strategic placement of sensors during testing is crucial to accurately measuring the intended natural frequencies. However, conventional methodologies for sensor placement are often time-consuming and involve iterative processes. This study explores the potential of machine learning techniques to enhance sensor selection methodologies. Three machine learning-based approaches are introduced and assessed, comparing their efficiency with established techniques. The evaluation of these methodologies is conducted using a numerical model of a beam to simulate real-world scenarios. The results offer insights into the efficacy of machine learning in optimizing sensor placement, presenting an innovative perspective on enhancing the efficiency and precision of modal testing procedures in aerostructure design.

A significant amount of data is available for bench-scale fire assessments. However, there is little surrounding large-scale tests and even less so for bench-to-large scale comparisons. Large-scale tests require more material, time and preparation, making them more expensive than bench-scale assessments. However, large-scale testing is an essential component to bench-scale fire testing. The bench-scale tests must be representative of both large-scale and real fire behaviour to provide an insight into how a material or product will behave in the event of a fire during its end use application. The few existing studies reviewed in this study show more guidance and data is needed, especially on a large-scale. Unfortunately, the data that is presented is done so in an inconsistent manner using various means of presentation, statistical analysis, and modelling that doesn’t show clear comparisons between bench and large scale. Currently, no bench-scale method shows good agreement with large-scale fire behaviour. Overall, there is a need for more large-scale testing and data for direct comparisons to be made.

Abstract Introduction: With the containment of the COVID-19 pandemic in Côte d'Ivoire, efforts were made to seamlessly integrate COVID-19 vaccination into the national immunization program. A collaborative initiative involving UNICEF, WHO, GAVI, and partner organizations resulted in the creation of the COVID-19 Vaccine Integration Mapping Tool. This paper presents a case study documenting the field testing of the Integration Mapping Tool and assessing the integration of COVID-19 vaccination within primary healthcare and routine immunization in Côte d'Ivoire. The study aims to describe the pilot process, gather feedback on tool usefulness and challenges, and establish integration priorities through roadmap development. Methods: Under the guidance of the Ministry of Health and Universal Coverage Cabinet, a workshop was conducted with participants from major health programs to field test the tool. Data analysis was performed using Excel, and the results were presented through tables, heat maps, and line graphs. Results: The first-of-its-kind field test of the Integration Mapping Tool in Cote d'Ivoire showcased its potential to bring key partners together to discuss the current state of integration, to improve transparency about resource allocation resource allocation, and enhance data management for the successful incorporation of COVID-19 vaccination into existing immunization systems. The integration of COVID-19 vaccines in Côte d'Ivoire showed a moderate level of progress, with improvement needed in resource allocation, payment systems, targeting of highest risk groups and vaccine administration. Support should be increased for target population identification, distribution points, quality of care mechanisms, and health personnel training. Health information systems and access to essential medicines were relatively satisfactory. Integration into existing programs, intersectoral collaboration, national health strategy, communication strategy, community participation, and data utilization require improvement. The post-workshop satisfaction survey gave the tool a score of .7 out of 10. Early lessons from Côte d'Ivoire provide guidance for enhancing integration, focusing on data-driven decision-making, collaboration, stakeholder engagement, and effective leadership. Conclusion: The successful field test of the Integration Mapping Tool (IMT) in Côte d'Ivoire marks a groundbreaking milestone, exemplifying the transformative potential of innovative tools in immunization practices. The IMT's application sets a precedent for seamless COVID-19 vaccination integration worldwide, emphasizing data-driven decision-making, collaboration, timing, and leadership. The pilot exercise's success in Côte d'Ivoire was attributed to political commitment, well-facilitated workshops, assessments, and the fact that the team in CI had previously already developed some initial integration plan.

Abstract: Our goal is to create point-of-care (POC) strategies that accelerate decision making, increase efficiency, improve outcomes, and enhance standards of care in island communities faced with global warming, rising oceans, population migration, and intensifying weather disasters. We assessed needs in the Bantayan Archipelago and mainland Cebu Province, Visayas Islands, Philippines, to map POC diagnostics, rescue times, and spatial care paths. Significant deficiencies were lack of cardiac troponin testing for rapid diagnosis of acute myocardial infarction, absence of blood gas and pH testing for support of critically ill patients, and geographic gaps prolonging patient transfers and delaying treatment. Strengths comprised primary care that can be facilitated by POC testing, logical inter-island transfers for which decision making and triage could be accelerated with onboard diagnostic testing, and healthcare small-world networks amenable to POC advances, such as pre-hospital testing, that avoid overloading emergency rooms. Healthcare resources must be distributed to archipelago islands, not concentrated in large metropolitan areas inaccessible for emergency interventions. We conclude that a point-of-need focus will help improve public health, decrease disparities in mortality among rural islanders versus urban dwellers, and pave the way for heightened resilience in anticipation of the adverse impact of global warming on vulnerable coastal areas.

We aimed to explore student and staff perceptions and experiences of a pilot COVID-19 asymptomatic testing service (P-ATS) in a UK university campus setting. This was a mixed-method study comprised of an online survey, and thematic analysis of qualitative data from interviews and focus groups conducted at the end of the 12-week P-ATS programme. Ninety-nine students (84.8% female, 70% first year; 93.9% P-ATS participants) completed an online survey, 41 individuals attended interviews or focus groups, including 31 students (21 first year; 10 final year) and 10 staff. All types of testing and logistics were highly acceptable (virus: swab, saliva; antibody: finger prick) and 94.9% would participate again. Reported adherence to weekly virus testing was high (92.4% completed ≥6 tests; 70.8% submitted all 10 swabs; 89.2% completed ≥1 saliva sample) and 76.9% submitted ≥3 blood samples. Students tested to ‘keep campus safe’, ‘contribute to national efforts to control COVID-19’, and ‘protect others’. 31.3% had high anxiety as measured by the Generalized Anxiety Disorder scale (GAD-7) (27.1% of first year). Students with lower levels of anxiety and greater satisfaction with university communications around P-ATS were more likely to adhere to virus and antibody tests. Increased adherence to testing was associated with higher perceived risk of COVID-19 to self (virus) and others (antibody). Qualitative findings revealed 5 themes and 13 sub-themes: ‘emotional responses to COVID-19’, ‘university life during COVID-19’, ‘influences on testing participation’, ‘testing physical and logistical factors’ and ‘testing effects on mental wellbeing’. Asymptomatic COVID-19 testing (virus/antibodies) is highly acceptable to students and staff in a university campus setting. Clear communications and support for mental wellbeing is likely to be important for testing uptake and adherence. Strategies are needed to facilitate social connections and mitigate the mental health impacts of COVID-19 and self-isolation.

This study investigates the influence of economic growth on CO2 emissions levels in three developed countries—Argentina, Equatorial Guinea, and South Korea—based on their status as high-income countries. We test the environmental Kuznets curve (EKC) hypothesis using the time series approaches to check the relationship and direction of causality among the variables over a sample spanning 1974–2020. The results show an inverted U-shaped short-run relationship in all three countries. In the long run, only South Korea supports the EKC hypothesis. Further, Granger causality results indicate the existence of causality. These long-run causal relationships between economic growth and emissions recommend one policy implication that wealthy governments must expand investments in renewable clean energy projects and R&D, with regulatory measures to suppress harmful environmental procedures and support environmentally friendly development.

The Gurney flap (GF) is a miniature lift-enhancement device and is usually mounted at the trailing edge of an airfoil. The GF and has been successfully applied to isolated airfoils, multi-element airfoils, and aircraft wings as well as helicopter rotor due to its attractive features of simplicity, cost-effective and separation control. The GF also has aroused the attention of researchers in the turbomachinery industry. However, limited studies are currently available on the application of a GF to an axial fan.Hence, in this paper, we conduct a wind tunnel and computational fluid dynamic (CFD) investigation on an axial fan profiled with a NACA 65-(12)10 airfoil to evaluate the effect of the GF on the performance of the fan. We also present the detailed flow features of the fan with and without the GF after validating the simulation results with the experimental results. The experimental results show that as the GF is installed higher on the fan blade, it can produce a higher total pressure rise accompanied with a greater loss of efficiency. The installation of the GF also enlarges the work capacity of the fan. Detailed flow field analysis, including the surface pressure distribution, vorticity distribution at the trailing edge and streamline distribution of the fan, is carried out to understand the mechanisms of the effect of the GF on the performance of the fan.

Electromagnetic sensing has been used for diverse applications of non-destructive testing, including the surface inspection, measurement of properties, object characterization. However, the measurement accuracy could be significantly influenced by the lift-off between sensors and samples. To address the issue caused by lift-offs, various strategies have been proposed for the permeability measurement of ferromagnetic steels, which mainly involves different sensor designs and signal features (e.g., the zero-crossing feature). In this paper, a single high-frequency scenario for the permeability retrieval is introduced. By combining the signal of two sensing pairs, the retrieval of magnetic permeability is less affected by the lift-off of sensors. Unlike the previous strategy on reducing the lift-off effect (directly taking the phase term out of the integration) using the Dodd-Deeds analytical method, the proposed method is based on a high-frequency linear feature of the phase term. Therefore, this method has the merit of high accuracy and fast processing for the permeability retrieval (a simplified version of Dodd-Deeds analytical formulas after the integration). Experimental measurement has been carried out on the impedance measurement of designed sensors interrogating ferromagnetic dual-phase steels. For sensor lift-offs of up to 10 mm, the error of the permeability retrieval is controlled within 4 % under the optimal frequency.

Goals: To use visual logistics for interpreting COVID-19 molecular and rapid antigen test (RAgT) performance, determine prevalence boundaries where risk exceeds expectations, and evaluate benefits of recursive testing along home, community, and emergency spatial care paths. Methods: Mathematica/open access software helped graph relationships, compare performance patterns, and perform recursive computations. Results: Tiered sensitivity/specificity comprise: T1) 90%/95%; T2) 95%/97.5%; and T3) 100%/≥99%, respectively. In emergency medicine, median RAgT performance peaks at 13.2% prevalence, then falls below T1, generating risky prevalence boundaries. RAgTs in pediatric ERs/EDs parallel this pattern with asymptomatic worse than symptomatic performance. In communities, RAgTs display large uncertainty with median prevalence boundary of 14.8% for 1/20 missed diagnoses, and at prevalence >33.3-36.9% risk 10% false omissions for symptomatic subjects. Recursive testing improves home RAgT performance. Home molecular tests elevate performance above T1, but lack adequate validation. Conclusions: Widespread RAgT availability encourages self-testing. Asymptomatic RAgT and PCR-based saliva testing present the highest chance of missed diagnoses. Home testing twice, once just before mingling, and molecular-based self-testing help avoid false omissions. Community and ER/ED RAgTs can identify contagiousness in low prevalence (<22%). Real-world trials of performance, cost-effectiveness, and public health impact could identify home molecular diagnostics as the optimal diagnostic portal.

Hepatocellular carcinoma (HCC) results in high mortality due to ineffective systemic therapy. Human immortalized cell lines are commonly used to study anti-tumour effects in the context of new anti-tumour therapies and tumour biology. As immortalized cell lines have limited biological relevance and heterogeneity compared to primary cells, patient-derived tumour tissues and corresponding immune cells are the gold standards for studying the complexity of individual tumour entities. However, culturing primary HCC cells has a low success rate. Here, we aimed to establish a reproducible approach to preserve the patient-derived liver cancer cells for in vitro and in vivo studies. The underlying study aimed to establish an in vitro pre-screening platform to test treatment options' effectivity and dosage, e.g., for new substances, autologous modified immune cells, or combined therapies in HCC. We initially employed 15 surgical resection specimens from patients with different HCC entities for isolation and preservation. The isolated liver cancer cells from four HCC-diagnosed patients were used for orthotopic transplantation into the healthy liver of immunodeficient mice, allowing them to grow for six months before human liver cancer cells were isolated and cultured. As a result, we generated and characterized four new primary-like liver cancer cell lines. Compared to immortalized HCC cell lines, freshly generated liver cancer cells displayed individual morphologies and heterogenous protein-level characteristics. We assessed their ability to proliferate, migrate, form spheroids, and react to common medications compared to immortalized HCC cell lines. All four liver cancer cell lines exhibit strong migration and colony-forming characteristics in vitro, comparable to extensively investigated immortalized HCC cell lines. Moreover, the four etiological different liver cancer cell lines displayed differences in the response to 5-FU, Sorafenib, Axitinib and Interferon-alpha treatment, ranking from non-responders to responders depending on the applicated medication. In sum, we generated individual patient-derived liver cancer cell lines suitable for predictive in vitro drug screenings and moreover for xenograft transplantations to realize the in vivo investigation of drug candidates. We overcame the low cultivation success rate of liver cancer cells derived from patients and analyzed their potential to serve a pre-clinical model.

This article presents raw data of biaxial tensile measurements of rat heart passive myocardium conducted in lab scale environment. The passive myocardium of the rat was divided into three regions, namely: left ventricle, mid-wall and right ventricle. The biaxial dataset of passive rat myocardia is presented as stress vs strain of the passive rat myocardium in various regions. The determination of valid material properties of the heart plays an important role in the development computational models. These computational models are useful in studying various scenarios and mechanisms of heart diseases. In addition, valid and accurate materials are critical in the development of new therapies. The dataset presented here is useful in the area of soft tissue mechanics including studying the mechanisms of heart diseases such as myocardial infarction. Accordingly, the evaluation of stress and strain in left ventricle, mid-wall and right ventricle was performed.

Abstract: A prevalence boundary (PB) marks the point in prevalence where the false omission rate, RFO=FN/(TN+FN), exceeds the tolerance limit for missed diagnoses. Objectives were to mathematically analyze rapid antigen test (RAgT) performance, determine why PBs are breeched, and evaluate the merits of testing three times over five days, now required by the US Food and Drug Administration for asymptomatic persons. Equations were derived to compare test performance patterns, calculate PBs, and perform recursive computations. An independent July 2023 FDA-university-commercial evaluation of RAgTs provided performance data used in theoretical calculations. Tiered sensitivity/specificity comprise: Tier-1) 90%, 95%; Tier-2) 95%, 97.5%; and Tier-3) 100%, ≥99%, respectively. Repeating a T2 test improves the PB from 44.6% to 95.2% (RFO 5%). In the FDA-university-commercial evaluation, RAgTs generated sensitivity of 34.4%, which improved to 55.3% when repeated, then 68.5% with the third test. With RFO=5%, PBs were 7.37/10.46/14.22%, respectively. PB analysis suggests RAgTs should achieve clinically proven sensitivity of 91.0-91.4%. When prevalence exceeds PBs, missed diagnoses can perpetuate virus transmission. Repeating low-sensitivity RAgTs delays diagnosis. In homes, high-risk settings, and hotspots, PB breaches may prolong contagion, defeat mitigation, facilitate new variants, and transform outbreaks into endemic disease. Molecular diagnostics can help avoid these potential vicious cycles

One of the main challenges in geodetic deformation analysis is to infer whether the geometry of some engineering structures or zones of natural hazards has changed from their initial state or not. The pillar that supports such an analysis is tightly based on the fundamentals of statistical hypothesis testing. The null hypothesis model indicates that no displacement has occurred. It is tested against a class of alternative models, which stipulate different displacement patterns. In this contribution, we present an innovative geodetic displacement detection which integrates combinatorial analysis and likelihood ratio tests into a sequential procedure for the case where the differences between observations of two epochs are in play. This framework is applied and investigated to two test scenarios: a synthetic and a real simulated trilateration network. From a statistical point of view, our approach is rigorous, because the alternative model can identify simultaneously more than one unstable point. In addition, the relationship between the unknown parameters and the observations is always linear, even if the problem manifests itself as non-linear. Consequently, we avoid a potential loss of statistical test power due to the model linearization. In addition, the proposed method controls the false positive rate efficiently. One of the problems that arise here is also related to the selection of the maximum number of points to be considered in the test procedure ( ). Here, we provide an innovative methodology based on rank computation of the design matrices to define , which can even be extended to the problem of outlier detection. Determining avoids the problem of having non-separable models in identifying unstable points. The algorithms and data are available in the repository.

Evaluating mutation testing behavior can help decide whether refactoring successfully maintains the expected initial test results. Moreover, manually performing this analytical work is both time-consuming and prone to errors. This paper extends an approach to assess test code behavior and proposes a tool called MeteoR. This tool comprises an IDE plugin to detect issues that may arise during test code refactoring, reducing the effort required to perform evaluations. A preliminary assessment was conducted to validate the tool and ensure the proposed test code refactoring approach is adequate. By analyzing not only the mutation score but also the generated mutants in the pre- and post-refactoring process, results show that the approach is capable of checking whether the behavior of the mutants remains unchanged throughout the refactoring process. This proposal represents one more step toward the practice of test code refactoring. It can improve overall software quality, allowing developers and testers to safely refactor the test code in a scalable and automated way.

A better understanding of diseases progress in tissues vest on the accurate understanding of tissues under mechanical loading. Also, development of therapies for injuries may depend on the available mechanical data for soft tissues. In this study, the raw data of biaxial tensile testing of sclera soft tissue is presented in this paper. Biaxial mechanical testing of soft tissues presents details understanding of how soft tissues behave when compared to uniaxial testing. Biomechanical properties of soft tissues are vital in the development of accurate computational models. Reliable computational models of studying mechanisms of diseases depends mainly on the accurate and more details mechanical behavior of soft tissues. These accurate and detailed computational models may be utilized to further develop the understanding and therapies of various diseases. The mechanical tensile testing was conducted on the passive sheep sclera. Engineering stress vs strain of several samples of the sheep sclera are further presented determined from force and displacement experimental data. The goal of this paper is to make available biaxial data of sheep sclera soft tissue that can be further utilized.

The COVID-19 pandemic had profound negative effects on millions of couples affected by infertility and in need to resort to assisted reproductive technologies. There is no consensus over the optimal way and moment of screening triage-negative asymptomatic patients and staff. We present SARS-CoV-2 antibodies’ (IgM, IgG) seroprevalence in 516 triage-negative patients and 30 fertility care providers. The sampling for SARS-CoV-2 serological assays took place from the lockdown release throughout the second half of 2020 (17.05 - 01.12.2020). It revealed an increased seroprevalence of antibodies that closely followed the local epidemiology of COVID-19, with the highest rate of seropositivity coincident with the peak of the second wave. From 546 triage-negative individuals whose blood samples were assessed for SARS-CoV-2 antibodies, 6% yielded positive results. The overall seroconversion rate was 2.8% for IgG and 5.1% for IgM. In the group with positive IgM, we observed a negative predictive value for IgM of 98.36% (95% CI: 88.79 – 99.78%), which is clinically meaningful. Serological testing of triage-negative patients up to seven days prior to the actual fertility procedure might avoid the more expensive and not more sensitive molecular testing currently being used for patient screening in most fertility units.

Background: Removable prostheses have seen a fundamental change recently because of advances in polymer materials, allowing improved durability and performance. Despite these advancements, notable differences still occur amongst various polymer materials and processing technologies, requiring a thorough grasp of their mechanical, physical, and therapeutic implications. Methods: Fours different processing techniques, all utilizing Polymethyl methacrylate (PMMA) as the main material, were used to construct complete dentures. The specimens underwent a mechanical test. Results: All the specimens broke under the influence of a certain force, rather than yielding through flow, as is characteristic for plastic materials. For each specimen, the maximum force (N) was recorded (figure 4), as well as the breaking energy, Conclusions: The best results were obtained in the case of the thermoplastic injection system and, surprisingly and contrary to those in the specialized literature, the worst results were recorded in the case of 3D printed samples.

Insecticide testing facilities that evaluate a variety of vector control products may generate large amount of hazardous wastes from routine operations. These wastes originate from degraded technical grade materials, sprayed substrates, redundant stock or working insecticidal solutions. The washing of Long-Lasting Insecticidal Nets (LLINs) during preparation for laboratory and experimental hut trials also contribute to waste water with insecticide content. Human and environmental exposure to insecticidal waste can occur during transport, categorization, storage and disposal in resulting in environmental pollution and potential health effects. Various national and international guidelines have been devised for safe disposal and should be strictly followed to avoid adverse effects on humans or environment. The current paper describes a case study from insecticide test facility in north-eastern Tanzania in management of insecticidal waste.

High-dimensional measurement error data are becoming more prevalent across various fields. Research on measurement error regression models has gained increasing attention due to the risk of drawing inaccurate conclusions if measurement errors are ignored. When the dimension p is larger than the sample size n, it is challenging to develop statistical inference methods for high-dimensional measurement error regression models due to the existence of bias, nonconvexity of objective function, high computational cost and many other difficulties. Over the past few years, some works have overcome the aforementioned difficulties and proposed several statistical inference methods. This paper mainly reviews the current development on estimation, hypothesis testing and variable screening methods for high-dimensional measurement error regression models and shows the theoretical results of these methods with some directions worthy of exploring for future research.

Duchenne muscular dystrophy (DMD) is a fatal X-linked recessive neuromuscular disorder most commonly caused by mutations disrupting the reading frame of the dystrophin (DMD) gene. DMD codes for dystrophin, which is critical for maintaining the integrity of muscle cell membranes. Without dystrophin, muscle cells receive heightened mechanical stress, becoming more susceptible to damage. An active body of research continues to explore therapeutic treatments for DMD as well as to further our understanding of the disease. These efforts rely on having reliable animal models that accurately recapitulate disease presentation in humans. While current animal models of DMD have served this purpose quite well, each comes with their own limitations. To help overcome this, clustered regularly interspaced short palindromic repeats (CRISPR)-based technology has been extremely useful in creating novel animal models for DMD. This review focuses on animal models developed for DMD that have been created using CRISPR, their advantages and disadvantages as well as their applications in the DMD field.

Human exposure to foodborne inorganic nanoparticles (NPs) is a growing concern. However, identifying potential hazards linked to NP ingestion often requires long-term exposure in animals. Owing these constraints, intestinal organoids are a promising alternative to in vivo experiments, as such an in vitro approach should enable rapid and reliable assessment of the effects on the gut of ingested chemicals. However, this remains to be validated for inorganic substances. In our study, a transcriptomic analysis and immunofluorescence staining were performed to compare the effects of food-grade TiO2 (fg-TiO2) on enteroid-derived monolayers (EDMs) from murine intestinal organoids to known impacts of TiO2 on intestinal epithelium. After validating their ability to dose-dependently respond to a pro-inflammatory cytokine cocktail, EDMs were exposed to 0.1, 1 or 10 µg fg-TiO2/mL for 24h. In line with known data, a dose-related increase of muc2, vilin 1 and chromogranin A gene markers of cell differentiation was observed. In addition, fg-TiO2 induced apoptosis and dose-dependent genotoxicity, while a decreased expression of genes encoding for antimicrobial peptides, and of genes related to tight junction function was observed. These results validated the use of EDMs as a reliable model for toxicity testing of foodborne NPs likely to affect the intestinal barrier.

COVID-19 has harmful impact on health. It is especially important for endurance athletes (EAs). Sleep and psychology influence sport performance. Aims of this study were: (1) investigation of the consequences of mild COVID-19 on sleep and psychology and (2) assessment of the conse-quences of the infection on cardiopulmonary exercise test (CPET) results. 49 EAs (males= 43; 87.76%, females= 6; 12.24%, age= 39.9±7.8 years, height= 178.4±6.8 cm, weight= 76.3±10.4 kg; BMI= 24.0±2.6 kg·m−2) underwent maximal cycling or running CPET pre- and post- COVID-19 and completed a survey. Exercise performance was deteriorated after COVID-19 (maximal oxy-gen uptake; VO2max= 47.81±7.81 vs 44.97±7.00 ml·kg·min−1 respectively pre- and post- infection; p<0.001). Waking up at night affected heart rate (HR) at the respiratory compensation point (RCP) (p=0.028). Sleep time influenced pulmonary ventilation (p=0.013), breathing frequency (p=0.010), and blood lactate concentration (Lac) (p=0.013) at RCP. Maximal power/speed (p=0.046) and HR (p=0.070) linked with the quality of sleep. Stress management and relaxation techniques linked with VO2max (p=0.046), maximal power/speed (p=0.033), and maximal Lac (p=0.045). Cardiorespiratory fitness was deteriorated after mild COVID-19 and was correlated with sleep and mental health. Medical Professionals should encourage EAs to maintain proper mental health and sleep after COVID-19 infection to facilitate recovery.

This study aimed evaluating 7 years’ outcome in 118 very preterm newborn (VPN, gestational age=26±1.4wks) involved in a randomized controlled trial. They presented neonatal respiratory distress (RDS) requiring ventilation for 14±2 days post-natal age (PNA). Repeated instillation of 200mg/kg Poractant alfa (SURF) did not improve early bronchopulmonary dysplasia, but SURF infants needed less re-hospitalization than controls for respiratory problem at 1- and 2-years PNA. There was no growth difference at 7.1±0.3 years for 41 SURF vs. 36 controls (80% eligible children); 7.9% SURF vs. 28.6% controls presented asthma (p=0.021). Children underwent cogni-tive assessment (WISC IV) and pulmonary function testing (PFT) measuring spirometry, lung volumes and airway resistance. Spirometry showed differences (p<0.05) between SURF and con-trols (mean±standard deviation (median z-score)) for FEV1 (L/s) (1.188±0.690(-0.803) vs. 1.080±0.243(-1.446)); FEV1 after betamimetics (1.244±0.183(-0.525) vs. 1.091±0.209(-1.342)); FVC (L) (1.402±0.217 (-0.406) vs. 1.265±0.267(-1.141)), and FVC after betamimetics 1.452±0.237 (-0.241) vs. 1.279±0.264(-1.020)). PFT showed no difference in volumes or airway resistance. Global IQ median [Inter-quartile Range] was 89[82:99] vs. 89[76:98] with 61% children >85 in both groups. Former VPN presenting severe neonatal RDS treated with repeated Surfactant have improved lung function and less asthma at 7 years PNA. There were no differences in neurodevelopmental outcome

Holographic subsurface radar (HSR) is currently not in widespread usage. This is due to an historical perspective in the ground penetrating radar (GPR) community that the high attenuation of electromagnetic waves in most media of interest, and the inability to apply time-varying gain to the continuous wave (CW) HSR signal precludes sufficient effective penetration depth. While it is true that the fundamental physics of HSR, with its use of a CW signal, does not allow amplification of later (i.e. deeper) arrivals in lossy media (as is possible with impulse subsurface radar — ISR), HSR has distinct some distinctive advantages. The most important of these is the ability to do shallow subsurface imaging with a resolution that is not possible with ISR. In addition, the design of an HSR system is simpler than for ISR due to the relatively low-tech transmitting and receiving antennae. This paper provides a review of the main principles of HSR through an optical analogy and describes possible algorithms for radar hologram reconstruction. We also present a review of the history of development of systems and applications for HSR of the “RASCAN” type which is possibly the only holographic subsurface radar that is produced in lots. Among the subsurface imaging and remote sensing applications considered are humanitarian demining, construction inspection, surveys of historic architecture and artworks, nondestructive testing of dielectric aerospace materials, security applications, paleontology, detection of wood-boring insect damage, and others. Each application is illustrated with relevant data acquired in laboratory and/or field experiments.

Holographic subsurface radar (HSR) is currently not in widespread usage. This is due to an historical perspective in the ground penetrating radar (GPR) community that the high attenuation of electromagnetic waves in most media of interest, and the inability to apply time-varying gain to the continuous wave (CW) HSR signal precludes sufficient effective penetration depth. While it is true that the fundamental physics of HSR, with its use of a CW signal, does not allow amplification of later (i.e. deeper) arrivals in lossy media (as is possible with impulse subsurface radar — ISR), HSR has distinct some distinctive advantages. The most important of these is the ability to do shallow subsurface imaging with a resolution that is not possible with ISR. In addition, the design of an HSR system is simpler than for ISR due to the relatively low-tech transmitting and receiving antennae. This paper provides a review of the main principles of HSR through an optical analogy and describes possible algorithms for radar hologram reconstruction. We also present a review of the history of development of systems and applications for HSR of the “RASCAN” type which is possibly the only holographic subsurface radar that is produced in lots. Among the subsurface imaging and remote sensing applications considered are humanitarian demining, construction inspection, surveys of historic architecture and artworks, nondestructive testing of dielectric aerospace materials, security applications, paleontology, detection of wood-boring insect damage, and others. Each application is illustrated with relevant data acquired in laboratory and/or field experiments.

Conventional economic theory outlines that developing countries experience economic growth through an undervalued exchange rate and that exchange rate overvaluations has negative long term effects on economic growth. This paper examined the impact of exchange rate movements as well as exchange rate misalignments on economic growth for the Trinidad and Tobago economy over the period 1960 to 2016. We find statistically significant evidence that both exchange rate appreciation and misalignments impact negatively on economic growth in the T&T economy. Drilling deeper we find interestingly that there exist no non-linear effects of exchange rate misalignments on growth. Specifically we find statistically significant evidence that both overvaluations and undervaluations hamper economic growth in the Trinidad and Tobago economy. We attribute this to T&T’s small and underdeveloped manufacturing sector that tends to be overlooked on account of its energy resources, in addition to the fact that its manufacturing sector is highly import oriented. A major policy recommendation would be for the critical reassessment of the rules governing the HSF, as government expenditure was allowed to follow energy revenues due to its current limitations.

In this study, we investigate the influence of control type and strain rate on the lifetime of specimens manufactured from 50CrMo4. This influence is described by a strain rate dependent method that uses cyclic stress strain curves to correct displacement controlled cyclic test results. The objective of this correction is to eliminate the stress related differences between displacement controlled cyclic test results and force controlled cyclic test results. The method is applied to the results of ultrasonic fatigue tests of six different combinations of heat treatment, specimen geometry (notch factor) and atmosphere. The corrected results show an improved agreement with test results obtained on conventional fatigue testing equipment with similar specimens: the standard deviation in combined data sets is significantly reduced (p=4.1%). We discuss the literature on intrinsic and extrinsic strain rate effects in carbon steels.

In ancient buildings, timber members could need specific on-site interventions, including reinforcement or repair, sometimes inserting of reinforcing material into grooves routed in the original sound wood. Grooves number, positions and dimensions, and strengthening materials may differ, according to the desired increase of bending stiffness and strength. The Modulus-of-Elasticity (MOE) of each beam is of key importance, but the incisions can affect it, net of the reduction of the removed wood. In this study 12 old beams were accurately measured and their static and dynamic MOEs calculated before and after the grooves processing, to simulate the operations of typical reinforcing interventions. One groove was routed along the length of each beam and deepened progressively by three steps. Tests have showed how the MOE is affected by the groove depth, decreasing up to one third. The paper proves how the weakening effect of grooves on-site can be assessed with dynamic MOE and roughly predicted by means of visual survey. Grooves need for strengthening beams, must be carefully evaluated because of the variation of the actual mechanical properties, net to lost wood.