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.

Long read sequencers, known for their effectiveness in detecting genomic structural variations (SV), are becoming a standard in comprehensive genetic analysis. In preimplantation genetic testing (PGT) for SV carriers, information on breakpoint junctions is required for the determination of carrier status in embryo selection. These sequencers are employed for challenging cases involving SVs that are difficult to analyze with conventional cytogenetical methods or detailed junctions of chromosomal translocations, providing valuable insights. They also play a crucial role in acquiring simultaneous information on surrounding single-nucleotide polymorphisms (SNPs) around causative variants in PGT. Despite their advantages, challenges related to sequencing accuracy and testing costs exist. Thus, understanding long read sequencers’ characteristics is essential for their effective utilization. This review summarizes the advanced applications of long read sequencers in preclinical workups and their integration into PGT. It also highlights in-house clinical cases, showing the implementation of long-read sequencing and discussing prospects in the field.

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 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.

On-stream inspections are the most appropriate method for routine inspections during plant operation without going through production downtime. Ultrasonic inspection, one of the on-stream inspection methods, faces challenges when performed at high temperatures exceeding the recommended 52°C. This study aims to determine the ultrasonic velocity and attenuation with the known material grade, thickness, and temperatures by comparing theory calculation versus experiment with temperatures ranging between 30°C to 250°C on low carbon steel covering most petrochemical equipment material and working conditions. The theoretical analysis was to obtain Young's modulus, Poisson's ratio, and longitudinal velocity at different temperatures. The experiments validated the predicted results of ultrasonic change due to temperature increase and showed a maximum error of 3%. The experimental data of velocity and decibel change from the temperature range provide a reference for the future when dealing with unknown materials information on site that require a quick corrosion status determination.

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.

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.

The question whether a given set of test items can be considered “identical” is often addressed in terms of the homogeneity of the test material from which said items were taken. However, for some types of matrices – in particular, for matrices consisting of minute separate particles, only some of which carry the analyte under consideration – even in the case of homogenous test material, an irreducible source of variability between test items may remain: the fundamental variability. In this paper, the concept of fundamental variability is explained, and procedures for reducing and characterizing it are described.

We have previously reported that a single test measuring oVEMP n10 to 4000Hz stimuli (either bone-conducted vibration (BCV) or air-conducted sound (ACS)) provides a definitive diagnosis of semicircular canal dehiscence (SCD) in 22 CT-verified patients with a sensitivity of 1.0 and specificity of 1.0. Such a single short screening test has great advantages of speed, minimizing testing time and the exposure of patients to stimulation. However some studies of the 4000Hz test for SCD have reported sensitivity and sensitivity values somewhat less that what we reported.

Rapid SARS-CoV-2 self-tests have the potential to expand access to COVID-19 testing and improve community-level case detection, particularly in resource-constrained countries such as Kenya. However, prior to their introduction, their acceptability must be assessed. This qualitative study explored key decision-takers’ values towards SARS-CoV-2 self-testing in Kenya. Healthcare workers, representatives of civil society, and potential implementors from Mombasa and Taita-Taveta were selected as decision-takers. Semi-structured interviews and focus group discussions were used to collect data on their values towards self-testing. A thematic analysis approach was applied. Most informants considered that the Kenyan public is equipped to accept and use self-testing safely as an approach to help to reduce workload at public healthcare facilities, and know one’s COVID-19 status in a private manner. The informants emphasized the need to provide counselling to end-users, to support those needing to self-isolate, and to engage different civil society stakeholders in information provision on self-testing. Fear of stigma and of forced isolation were noted as potential deterrents to self-testing uptake for some individuals. In conclusion, there is high acceptability of self-testing in Kenya among decision-takers. However, enhanced education, counselling, and addressing deterrents to testing would be helpful to ensure effective use of SARS-CoV-2 self-testing in Kenya.

Dry powder inhalers are used by a large number of patients worldwide to treat respiratory diseases. The objective of this work is to experimentally investigate changes in aerosol particle diameter and particle number concentration of pharmaceutical aerosols generated by five dry powder inhalers under realistic inhalation and exhalation conditions. The active respiratory system model (xPULM™) was used as a model of the human respiratory system and to simulate a patient undergoing inhalation therapy. A mechanical upper airway model was developed, manufactured and introduced as a part of the xPULM™ to represent the human upper respiratory tract with high fidelity. Integration of optical aerosol spectrometry technique into the setup allowed for evaluation of pharmaceutical aerosols. The results show that the upper airway model increases the resistance of the overall system and act as a filter for bigger particles (>3 µm). Furthermore, there is a significant difference (p < 0.05) in mean particle diameter between inhaled and exhaled particles with the majority of the particles depositing in the lung. The minimum deposition is reached for particle size of 0.5 µm. The mean particle number concentrations exhaled are 2.94% (BreezHaler®), 2.66% (Diskus®), 10.24% (Ellipta®) 2.13% (HandiHaler®) and 6.22% (Turbohaler®). In conclusion, the xPULM™ active respiratory system model is a viable option for studying interactions of pharmaceutical aerosols and the respiratory tract in terms of applicable deposition mechanisms. The model can support the reduction of animal experimentation in aerosol research and provide an alternative to experiments with human subjects.

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.

The reliability analysis allows to estimate the system's probability of detecting and identifying outlier. Failure to identify an outlier can jeopardise the reliability level of a system. Due to its importance, outliers must be appropriately treated to ensure the normal operation of a system. The system models are usually developed from certain constraints. Constraints play a central role in model precision and validity. In this work, we present a detailed optical investigation of the effects of the hard and soft constraints on the reliability of a measurement system model. Hard constraints represent a case in which there exist known functional relations between the unknown model parameters, whereas the soft constraints are employed for the case where such functional relations can slightly be violated depending on their uncertainty. The results highlighted that the success rate of identifying an outlier for the case of hard constraints is larger than soft constraints. This suggested that hard constraints should be used in the stage of pre-processing data for the purpose of identifying and removing possible outlying measurements. After identifying and removing possible outliers, one should set up the soft constraints to propagate the uncertainties of the constraints during the data processing. This recommendation is valid for outlier detection and identification purpose.

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.

IoT is a fast growing technology that has Promising potential for shaping our future. In this fast growing world of IoT, IoT systems are released without proper testing which effect its quality and does not guarantee user satisfaction. Different testing methodologies are carried out to ensure Quality assurance of IoT before releasing it to the market. In this paper we have reviewed different testing techniques using AI and different tools to ensure Quality of IoT. In this paper we have also reviewed different IoT challenges related to its quality.

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.

3D-printing with foam concrete, which is known for its distinct physical and mechanical properties, has not yet been purposefully investigated. The article at hand presents a methodological approach for the mixture design of 3D-printable foam concretes and a systematic investigation of the potential application of this type of material in digital construction. Three different foam concrete compositions with water-to-binder ratios between 0.33 and 0.36 and having densities of 1100 to 1580 kg/m³ in the fresh state were produced with a pre-foaming technique using a protein-based foaming agent. Based on the fresh-state tests, including 3D-printing as such, an optimum composition was identified and its compressive and flexural strengths were characterised. The printable foam concrete showed compressive strength above 10 MPa and low thermal conductivity, which make it suitable for 3D-printing applications, while fulfilling both load-carrying and insulating functions.

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.

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.

Pigeonpea (Cajanus cajan (L.) of Fabaceae family belongs to genus Cajanus usually grown in semi-arid tropics of Asia and Oceania, Africa and America. This crop has been a best source for improving food and soil quality amongst farmers. However, its seed have been always questioned for purity. This problem is managed by using polymorphic SSR markers. In present study, a DNA fingerprints generated by seven SSR markers and hybrid testing is performed on Pigeonpea test samples along with parental lines. The seed samples of pigeonpea were germinated in laboratory and three week old leaves samples were used for DNA isolation by CTAB method. A total of 9 alleles were observed in three test samples using three primers out of seven primers. The screening of the allelic data associated with the three cultivated varieties, revealed markers (CcM0246) displayed unique allelic profiles for one variety. Yet, the genetic fingerprinting data is not well resolved to potentially distinguished two bands of hybrid that are merely of 4–8 bp to confirm hybrid testing of seed. Hybrid testing of may be confirmed including more SSR primers prepared from genomic DNA of pigeonpea.

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.

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.

Our primary objectives were a) to determine the need for, and the availability of point-of-care testing (POCT) for infectious diseases and b) to recommend point-of-care testing strategies and spatial care paths (SCPs) that enhance public health preparedness in regional districts of Thua Thien Hue Province (TTHP), Central Vietnam, where we conducted field surveys. Medical professionals in 7 community health centers (CHCs), 7 district hospitals (DHs) and 1 provincial hospital (PH) participated. Survey questions (English and Vietnamese) determined the status of diagnostic testing capabilities for infectious diseases and other acute medical challenges in TTHP. Infectious disease testing was limited: 6 of 7 CHCs (86%) lacked infectious disease tests. One CHC (14%, 1/7) had two forms of diagnostic tests available for the detection of Malaria. All CHCs lacked adequate microbiology laboratories. District hospitals had few diagnostic tests for infectious diseases (Tuberculosis, Syphilis), blood culture (29%, 2/7), and pathogen culture (57%, 4/7) available. The PH had broader diagnostic testing capabilities but lacked preparedness for highly infectious disease threats (e.g., Ebola, MERS-CoV, SARS, Zika, and Monkeypox). All sites reported having COVID-19 rapid antigen tests; COVID-19 RT-PCR tests were limited to higher tier hospitals. We conclude that infectious disease diagnostic testing should be improved and POC tests must be supplied near patients’ homes and in primary care settings for the early detection of infected individuals and mitigation of the spread of new COVID-19 variants and other highly infectious diseases.

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.

A new Mg-Zn-Zr-Ca alloy in powder state was obtained via mechanical alloying method, from pure elemental powder. Further, the obtained powder-alloy was processed by selective laser melting (SLM) procedure to obtain 3D printed samples for small biodegradable implants. A series of microstructural, mechanical and corrosion analysis were performed. The SEM analysis of powder-alloy reveal a good dimensional homogeneity, with uniform colored, no agglutinated and almost rounded particles, suitable for selective laser melting procedure. Further, the SLM samples reveal a robust and unbreakable morphology, with a suitable porosity and without undesirable balling effect. The tested Young’s modulus of the SLM samples, of 42 GPa, is close to cortical bone one, of 30 GPa. The corrosion tests performed in PBS (Phosphate-buffered saline) solution show that the corrosion parameters have a satisfactory evolution.

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.

We investigated the development of a simple and sensitive assay for the identification of minute amounts of animal and human biological material. The suggested system uses isothermal amplification of DNA in a rapid assay format, which returns the results in as little as 40 minutes from sampling. The assay used for the proof of concept employs the novel handheld SaLux19 device (Max-Planck Innovation prototype, Germany). This well-established infield detection system could also be utilized for forensic scenarios. The results presented here demonstrated that the assay is sufficiently specific and sensitive and can detect the presence of Sus scrofa nucleic acids.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

For polymicrobial infections, AtbFinder utilizes a novel paradigm of the population response to antibiotics, enabling bacterial growth in the form of a mixed microbial community and selecting the antibiotics targeting not only the principal pathogen, but also those bacteria that support their growth. TGV medium allowed culturing a more diverse set of bacteria from polymicrobial biospecimens, compared with that achieved with the standard media and enabled, already within 4h, accurate selection of the antibiotics that completely eliminated all cultivatable bacteria from clinical samples. In conclusion, AtbFinder system may be a valuable tool in improving antibiotic selection, enabling targeted empirical therapy and accurate antibiotic replacement, which is especially important in high-risk patients.

(1) Background: the NGS based mutational study of hereditary cancer genes is crucial to design tailored prevention strategies in subjects with different hereditary cancer risk. The ease of amplicon-based NGS library construction protocols contrasts with the greater uniformity of enrichment provided by capture-based protocols and so with greater chances for detecting larger genomic rearrangements and copy-number variations. Capture-based protocols, however, are characterized by a higher level of complexity of sample handling, extremely susceptible to human bias. Robotics platforms may definitely help dealing with these limits, reducing hands-on time, limiting random errors and guaranteeing process standardization. (2) Methods: We implemented and validated the complete automation of the SOPHiA GENETICS’ CE-IVD Hereditary Cancer Solution™ (HCS) libraries preparation workflow on the Hamilton’s STARlet platform. (3) Results: We demonstrate that this automated workflow, used for more than 1000 samples achieved the same performances of manual setup in terms of coverages and reads uniformity, with extremely lower variability of reads mapping rate onto the regions of interest. (4) Conclusions: This automated solution offers same reliable and affordable NGS data, but with the essential advantages of a flexible, automated and integrated framework, minimizing possible human errors and depicting a laboratory’s walk-away scenario.

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.

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.

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 one 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. The BARD1-BRCA1 complex is involved in genetic stabilization at the cellular level. It allows to mark abnormal DNA fragments by attaching ubiquitin to them. In addition, it blocks (by ubiquitination of RNA polymerase II) the transcription of damaged DNA. 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.

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.

This paper investigates whether optimisation methods with the population made up of one solution can suffer from structural bias just like their multisolution variants. Following recent results highlighting the importance of choice of strategy for handling solutions generated outside the domain, a selection of single solution methods are considered in conjunction with several such strategies. Obtained results are tested for the presence of structural bias by means of a traditional approach from literature and a newly proposed here statistical approach. These two tests are demonstrated to be not fully consistent. All tested methods are found to be structurally biased with at least one of the tested strategies. Confirming results for multisolution methods, it is such strategy that is shown to control the emergence of structural bias in single solution methods. Some of the tested methods exhibit a kind of structural bias that has not been observed before.

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.

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.

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.

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

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.

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.

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.

Cystic fibrosis (CF) is characterized by mutations of CFTR that lead to increased viscous secretions, bacterial colonization and recurrent infections. Chronic P. aeruginosa infection in persons with CF is associated with progressive and accelerated lung function decline despite aggressive antibiotic treatment. We report the management of respiratory infections in persons with CF with antibiotic therapy that was based on the recommendations of AtbFinder, a novel, rapid, culture-based diagnostic test system that employs a novel paradigm of antibiotic selection. AtbFinder mimics bacterial interactions with antibiotics at concentrations that can be achieved in affected tissues or organs, and models conditions of interbacterial interactions within polymicrobial biofilms. This open-label, single-arm, investigator‐initiated clinical study was designed to identify the efficacy of antibiotics selected using AtbFinder in persons with CF. Microbiological and clinical parameters were assessed following the change of antibiotic therapy to antibiotics selected with AtbFinder between January 2016 and December 2018 and retrospectively compared with clinical data collected between January 2013 and December 2015.We enrolled 35 persons with CF (33 with chronic P. aeruginosa colonization). Antibiotics selected using AtbFinder resulted in clearance of P. aeruginosa in 81.8% of subsequent cultures, decreased pulmonary exacerbations from 1.21 per patient per annum to 0, and an increase in predicted FEV1% up to 28.4% from baseline. The number of systemic antibiotic courses used in patients after switching to the AtbFinder selected therapy was reduced from 355 to 178. These findings describe the superiority of antibiotic regimens selected with AtbFinder compared with routine antimicrobial susceptibility testing.

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.

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.

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.

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.

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.

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.

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.

It is unclear why European countries have been more severely affected by COVID-19 than East Asian countries. In this ecological study we compared the COVID-19 epidemics (cumulative incidence and mortality rates), host genetic susceptibility and national responses (testing intensity) in all European versus all Western Pacific/East Asian countries reporting cases in the first month of the epidemic. The host-genetic-susceptibility assessment was limited to the frequency of the D-allele of the angiotensin converting enzyme-1 (ACE-1) which has been found to be positively associated with COVID-19 incidence within European countries. Despite earlier epidemics, countries from the Western Pacific reported lower cumulative numbers of COVID-19 cases/100 000 inhabitants than European countries (P=0.0002). The Western Pacific countries also reported fewer cumulative COVID-19 deaths/100 000 (P=0.0024). Whilst there was little difference in the cumulative number of tests conducted/100 000, the percent of COVID-19 tests reported positive was higher in Europe than the Western Pacific (P=0.0076). The frequency of the ACE-1 D-allele was lower in the Western Pacific than European countries (P=0.0007). Our results suggest that a combination of different testing strategies and host genetic susceptibility contribute to difference in severity of the COVID-19 epidemics in the Western Pacific/East Asia and Europe.

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.

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.

Georgia is ranked fifth highest among states for rates of HIV diagnosis. About 4% of persons living with HIV infection in the United States reside in Georgia, and almost 19% of these people do not know their HIV status. The present study examined the trends and associated factors of HIV testing among adults in Georgia between 2010 and 2014 by analyzing data of the Behavioral Risk Factor Surveillance System (BRFSS). A total of 30,791 persons aged ≥18 years were identified who responded to the question “Have you ever been tested for HIV?” Overall, there were 11,543 respondents who had been tested for HIV, with a decrease in percentage from 49.4% in 2010 to 43.7% in 2014 (p<0.001). Factors associated with HIV testing were being black (p<0.001), being younger than 55 years (p<0.001), single (p=0.02), attaining education level above high school (P<0.001), engaging in HIV high-risk behaviors (p<0.001), and not having healthcare coverage (p=0.03). Overall in Georgia, there has been a decline in the temporal trend of HIV testing, and more than half of adults have never been tested for HIV. For reducing HIV transmission in Georgia, enhancing access and utilization of HIV testing should be a public health priority.

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.

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.

The APIS Breast Cancer Subtyping Kit is an mRNA-based assessment of the three biomarkers routinely assessed in all newly diagnosed breast cancers (BC), estrogen receptor (ER), progesterone receptor (PR), and HER2 as well as an additional four genes that create a novel proliferation signature, MKI67, PCNA, CCNA2, KIF23. Taken together the data is used to produce a molecular sub-type for every sample. The kit was evaluated against the current standard protocol of immunohistochemistry (IHC) and/or in situ hybridization (ISH) in breast cancer patients. The data was presented at the weekly breast Multidisciplinary Team (MDT) meeting. 98 consecutive cases of pre-operative breast cancer core biopsies and two core biopsy of nodal metastases yielding 100 cases were assessed. IHC and APIS Results were available for 100 and 99 cases. ER was concordant in 97% cases, PR in 89% and HER2 results were concordant with IHC/ISH in 100% of the cases. Ki-67 IHC was discordant in 3% cases when compared with MK167 alone but discordant in 24% when compared with the four gene proliferation signature. In conclusion, our study, indicates that the APIS Breast Cancer Subtyping Kit is highly concordant when compared to the results produced for ER/PR/HER2 by IHC and/or ISH. The assay could play a role in the routine assessment of newly diagnoses Breast Cancer (BC) specimens.

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.

Alternative food sources are essential in both low-resource settings or during emergencies like abrupt sunlight reduction scenarios. Seaweed presents a promising option but requires investigation into the viability of unconventionally sourced ropes for harvesting. As such, a low-cost reliable method to test the tensile strength of rope is needed to validate alternative materials for use in harvesting seaweed. Unfortunately, commercial rope testing jigs alone range in price from several thousand to tens of thousands of dollars. To fill this need, this article reports on an open-source design for tensile strength rope testing hardware. The hardware design focuses on using readily available parts that can be both sourced from a hardware store and manufactured with simple tools to provide for the greatest geographic accessibility. The jig design, which can be fabricated for CAD$20 is two to three orders of magnitude less expensive than commercially available solutions. The jig was built and tested using a case study example investigating denim materials (of 1 5/8”, 3 1/4", 4 7/8”, 6 1/2", and 8 1/8” widths) as a potential alternative rope material for seaweed farming. Denim demonstrated strength up to 1.65kN for the widest sample and the jig demonstrated sufficient strength and stiffness for operating at forces below 4kN. The results are discussed and areas for future improvements are outlined to adapt the device to other circumstances and increase the strength of materials that can be tested.

In this paper, we propose a method for the generation of simulation test scenarios for autonomous driving. Based on the requirements of standard regulatory test scenarios, we can generate virtual simulation scenarios and functional scenario libraries for autonomous driving, which can be used for simulation verification of different ADAS functions. Firstly, the design operation domain (ODD) of the functional scenario is selected and the weight values of the ODD elements taken are calculated; then a combination test algorithm based on parameter weights is improved to generate autonomous driving virtual simulation test cases for the ODD elements, which can effectively reduce the number of generated test cases compared with the traditional combination test algorithm; then the traffic participant elements under each test case are Then, the values of the subelements under the traffic participant element in each test case are sampled and clustered to obtain hazard specific scenarios. Finally, the specific scenarios are applied to the automatic emergency braking (AEB) system on the model-in-the-loop (MIL) testbed to verify the effectiveness of this scenario generation method.

A friction loss model for brake testing platform is constructed to revise the braking force test results, which can largely improve the accuracy of automotive brake performance testing. Specifically, the influence of tire pressure, vehicle axle load, placement angle and vehicle speed on the friction loss is tested and analyzed on a wheelbase adjustable automotive anti-force brake testing platform. The friction loss model for the platform is constructed based on the defined relative slip and placement angle, which is validated through actual tests on four types of vehicles. The results showed that the maximum relative error between the values of the model calculated simulation and the measured was 2.2%, indicating the friction loss model is valid and can provide a basis for revising the braking force of automotive brake. Meanwhile, the maximum braking force increases from 3982 N to 4772 N, increased by 19.8%, when the placement angle increased from 36.9° to 47.0°. Accordingly, in order to improve the accuracy of detection results of the automotive anti-force rolling brake testing platform, the friction loss caused by the change in the placement angle should be revised, and then braking rate of the vehicle should be judged according to GB 7258-2017 and GB 38900-2020.

With the continuous development of digital transformation and upgrading of Chinese construction enterprises, it is becoming increasingly important to measure their digital level, find the problems in the enterprise transformation process, and identify the key factors of enterprise digital capacity enhancement. This paper constructs a construction enterprise digital transformation maturity evaluation model from six first-level indicators and 20 second-level indicators, including digital strategy, digital business application, digital technology capability, data capability, digital organization capability, and change management. Digital maturity is divided into five levels: business management, process operation, intelligent construction, intelligent scene application, and industrial ecological collaboration. A detailed process of digital maturity evaluation based on the method of Analytic Hierarchy Process (AHP)-Decision Testing and Evaluation Laboratory (DEMATEL) is then developed. A questionnaire survey of 25 experts is used to weight the various parameters in the model, which is then demonstrated with an example construction enterprise. The model comprehensively reflects digital levels under the background of the digital economy. Its application will help understand the advantages and disadvantages enterprises face in their digital transformation to enable targeted measures to improve their digital transformation capabilities and efficiency, enhance their core competitiveness of enterprises, and promote the development of digital transformation in the construction industry.

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.

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.

This paper presents the development of an underwater crack detection system for structural integrity assessment of submerged structures, like offshore oil and gas installations, underwater pipelines, underwater foundations for bridges, dams etc. Focus is on use of machine learning based approaches. First a detailed literature review of state of the current methods for underwater surface crack detection is presented highlighting challenges and opportunities. An overview of image augmentation approach for creation of underwater optical effects is also presented. Experimental results using standard network based machine learning approach, used for surface crack detection in onshore environment, is presented. Series of Test cases are presented where existing networks performance are improved using augmented images for underwater conditions. The experimental results demonstrate the effectiveness and accuracy of the proposed system in detecting cracks in underwater structures. The system has the potential to improve the safety and reliability of underwater structures and prevent catastrophic failures.

This paper proposes an optimal trading algorithm based on a novel application of the conventional Control Engineering (CE). We consider a fundamental CE concept, namely, the feedback control and apply it to the Algorithmic Trading (AT). The concrete feedback control strategy is designed in a form of the celebrated Proportional-Integral-Derivative (PID) model. The highly fluctuating nature of the modern financial markets has led to the adoption of a model-free realisation of the generic PID framework. The control theoretical methodology we propose is combined with the advanced statistics for the historical market data. We obtain a specific log-normal probability distribution function (pdf) associated with the specific quantities associated with the available stock data. The empirical log-normal pdf mentioned above makes it possible the necessary PID gains optimization. For this aim, we apply the data-driven optimization approaches and consider the corresponding Monte Carlo solution procedure. The optimized PID trading algorithm we propose is also studied in the Fourier analysis framework. This equivalent frequency domain representation involves a new concept in the financial engineering, namely, the "stock market energy" concept. For the evaluation, we implement the proposed PID optimal trading algorithm and develop a Python based prototype software. We finally apply the corresponding prototype software to a dataset from the Binance BTC / USDT stock market. The experimental result illustrates the implementability of the proposed optimal PID trading scheme and also shows the effectiveness of the proposed CE methods in the modern AT.

Human adenoviruses are one of the most important pathogens detected in acute respiratory diseases in pediatrics and immunocompromised patients. In 1953, Wallace Rowe described it for the first time in oropharyngeal lymphatic tissue. To date, more than 85 types of HAdV have been described, with different cellular tropisms. They can cause respiratory and gastrointestinal symptoms, even urinary tract inflammation, although most infections are asymptomatic. However, there is a population at risk that can develop serious and even lethal conditions. These viruses have a double-stranded DNA genome, 25-48 kbp, 90 nm in diameter, without a mantle, stable in the environment, and resistant to fat-soluble detergents. Currently the diagnosis is made with lateral flow immunochromatography or molecular biology through a polymerase chain reaction. The objective of this review is to recognize the variability of HAdV, the pandemic potential that a recombinant could present between HAdV-3 and 7 viral types, known to produce aggressive outbreaks in health facilities. The review determined the characteristics of HAdV, from the infection to treatment, vaccine development and the evaluation of the social determinants of health associated with HAdV, guiding the necessary measures for future sanitary control, and preventing disasters such as the SARS-CoV-2 pandemic.

Scientific, technical and bioinformatics advances have made it possible to establish analytics-based molecular biosimilarity for the approval of biosimilars. If the molecular structure and other product- and process-related attributes are comparable within the limits of testing then a biosimilar candidate would have safe safety and efficacy as its reference products. The current model of animal and human testing becomes redundant since all of these studies have much lower sensitivity and reproducibility in confirming biosimilarity. The recent AI-based protein structure prediction model has confirmed that the 3D structure can be predicted from the amino acid sequence, reducing the need for structural analysis; however, the new test methods based on MS are millions of times more sensitive and accurate. While the regulatory agencies have begun waiving animal testing and, in some cases, clinical efficacy testing, removing clinical pharmacology profiling brings a dramatic paradigm shift, reducing development costs without compromising safety and efficacy. Also shared is a list of 160+ products ready to enter as biosimilars. Major actions from regulatory agencies and developers are required to make this paradigm shift.

Ayurveda as a healthcare system has survived for thousands of years but continues to be dogged by reported lack of efficacy of the treatments in clinical trials. The reported lack of efficacy could be due to a real lack of efficacy (which then contradicts the survival of Ayurveda as a functional medical system enjoying considerable public patronage) or could be attributed to inadequacies in the efforts towards evidence generation or in a larger context the overall scientific conduct of research in Ayurveda. In an effort towards better evidence generation, there is an immediate need for standardizing the design, conduct and reporting of clinical trials of Ayurveda but it is a daunting task. For this effort to benefit the scientific endeavors of Ayurveda researchers, it should allow the researchers to be able to apply Ayurveda’s multi-component, individualized and inherently holistic approach. Statistical principles can benefit this effort. Statistical hypothesis testing (SHT) is central to these statistical principles and also aligns well with conventional scientific principles of evidence generation. Although there are challenges with SHT, good practitioners engaged in it do much more than just apply the mathematical theory behind it. As a particular example, lot of time in clinical trial designing is spent in addressing biases and designing trials prudently by minimizing the effect of such biases. SHT can benefit such an effort objectively. There is a need for Ayurveda researchers to engage deeply and mindfully about biases in study design in order to gain scientific validity and acceptability. The article highlights issues that arise in Ayurveda research, and discusses few ways of dealing with these issues using statistical principles.

Alternating current field measurement (ACFM) testing is one of promising techniques in the field of non-destructive testing with advantages of the non-contact capability and the reduction of lift-off effects. In this paper, a novel crack detection approach is proposed to reduce the effect of the angled crack (cack orientation) by using rotated ACFM techniques. The sensor probe is composed of an excitation coil and two receiving coils. Two receiving coils are orthogonally placed in the centre of the excitation coil where the magnetic field is measured. It is found that the change of the x component and the peak value of the z component of the magnetic field when the sensor probe rotates around a crack follows a sine wave shape. A customised accelerated finite element method solver programmed in MATLAB is adopted to simulate the performance of the designed sensor probe which can significantly improve the computation efficiency due to the small crack perturbation. The experiments have also been carried out to validate the simulations. It is found that the ratio between the z and x components of the magnetic field remains stable under various rotation angles. It shows the potential to estimate the depth of the crack from the ratio detected by combining the magnetic fields from both receiving coils (i.e., the x and z components of the magnetic field) using the rotated ACFM technique.

3D-printed aluminium alloy fabrications made by selective laser melting (SLM) offer a promising route for the production of small series of custom-designed heat exchangers with complex geometry and shape and miniature size. Alloy composition and printing parameters need to be optimized to mitigate fabrication defects (pores and microcracks) and enhance the part performance. The deformation response needs to be studied with adequate characterization techniques at relevant dimensional scale capturing the peculiarities of micro-mechanical behavior relevant to the particular article and specimen dimensions. Purposefully designed Al-Si-Mg 3D-printable RS-333 alloy was investigated with a number of microscopy techniques including in situ mechanical testing with a Deben Microtest 1 kN stage integrated and synchronized with Tescan Vega3 SEM to acquire high resolution image datasets for Digital Image Correlation (DIC) analysis. Dog bone specimens were 3D-printed in different orientation of gauge zone cross-section with respect to the fast laser beam scanning and growth directions. This corresponds to varying local conditions of metal solidification and cooling. Specimens show variation in mechanical properties, namely, Young’s modulus (65…78 GPa), yield stress (80–150 MPa), ultimate tensile strength (115–225 MPa) and elongation at break (0,75–1,4 %). Furthermore, the failure localization and character was altered with the change of gauge cross-section orientation. DIC analysis allowed correct strain evaluation that overcame the load frame compliance effect and helped to identify the unevenness of deformation distribution (plasticity waves) that ultimately resulted in exceptionally high strain localization near the ultimate failure crack position.

Electromagnetic sensors have been used for inspecting small surface defects of metals. Based on the eddy-current thin-skin regime, a revised algorithm is proposed for a triple-coil drive-pickup eddy-current sensor scanning over long surface crack slots (10 mm) with different rotary angles. The method is validated by the voltage measurement of the designed EC sensor scanning over a benchmark (ferromagnetic) steel with surface defects of different depths and rotary angles. With an additional sensing coil for the designed EC sensor, the defect angle (or orientation) can be measured without spatially and coaxially rotating the excitation coil. By referring to the voltage change (due to the defect) diagram (voltage sum versus voltage different) of two sensing pairs, the rotary angle of the surface crack is retrieved with a maximum residual deviation of 3.5 %.

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 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.

Continuous ultrasonic in-situ monitoring for industrial applications is difficult owing to the high operating temperatures in industrial fields. It is expected that ultrasonic transducers consisting of CaBi4Ti4O15(CBT)/Pb(Zr,Ti)O3(PZT) sol-gel composite could be one solution for ultrasonic nondestructive testing (NDT) above 500 C because no couplant is required and CBT has a high Curie temperature. To verify the high temperature durability, CBT/PZT sol-gel composite films were fabricated on titanium substrates by spray coating, and the CBT/PZT samples were tested in a furnace at various temperatures. Reflected echoes with a high signal-to-noise ratio were observed up to 600 C. A thermal cycle test was conducted from room temperature to 600 C, and no significant deterioration was found after the second thermal cycle. To investigate the long-term high-temperature durability, a CBT/PZT ultrasonic transducer was tested in the furnace at 600 °C for 36 h. Ultrasonic responses were recorded every 3 h, and the sensitivity and signal-to-noise ratio were stable throughout the experiment.

In the field of railroad safety, effective detection of surface cracks is critical, necessitating reliable, high-speed non-destructive testing (NDT) methods. This study introduces a hybrid Eddy Current Testing (ECT) probe, specifically engineered for railroad inspection, to address the common issue of ’lift-off noise’ due to varying distances between the probe and test material. Unlike traditional ECT methods, this probe integrates transmit and differential receiver coils, aiming to enhance detection sensitivity and minimize lift-off impact. The study optimizes ECT probes employing different driver coils, emphasizing three main objectives: a) quantitatively evaluating each probe using signal- to-noise ratio (SNR) and outlining a real-time data processing algorithm based on SNR methodology; b) exploring the frequency range proximal to the electrical resonance of the receiver coil; c) examining sensitivity variations across varying lift-off distances. The experimental outcomes indicate that the newly designed probe with figure 8-shape driver coil significantly improves sensitivity in detecting surface cracks on railroads. It achieves an impressive SNR exceeding 100 for defects with minimal dimensions of 1 mm in width and depth. Simulation results closely align with experimental findings, validating the investigation of optimal operational frequency and lift-off distance for selected probe performance, determined to be 0.3 MHz and 0.5 mm, respectively. The realization of this project would lead to notable advancements in enhancing railroad safety by improving crack detection efficiency.

Parkinson’s disease (PD) is the second-most common neurodegenerative disorder worldwide and is diagnosed based upon motor impairments. Non-motor symptoms are well-recognized in PD, and peripheral neuropathy is a frequent but poorly appreciated non-motor sign. Study of how the central and peripheral sensory systems are affected can contribute to the development of targeted therapies and deepen the understanding of the pathophysiology of PD. Although the cause of sporadic PD is unknown, chronic exposure to the pesticide rotenone in humans increases the risk of development of PD. Here, we aimed to investigate whether peripheral neuropathy is present in a traditional model of PD. Mice receiving intrastriatal rotenone showed greatly reduced dopamine terminals in the striatum and reduction in tyrosine hydroxylase-positive neurons in the Substantia nigra pars compacta and developed progressive motor impairments in hindlimb stepping and rotarod but no change in spontaneous activity. Interestingly, repeated testing using gold-standard protocols showed no change in gut motility, a well-known non-motor symptom of PD. Importantly, we did not observe any change in heat, cold, or touch sensitivity, again based upon repeated testing with well-validated protocols that were statistically well-powered. Therefore, this traditional model fails to replicate PD, and our data again reiterate the importance of the periphery to the disorder that is PD.

Growth environment greatly alters many facets of pathogen physiology, including pathogenesis and antimicrobial tolerance. The importance of host-mimicking environments for attaining an accurate picture of pathogen behaviour is widely recognised. Whilst this recognition has translated into the extensive development of artificial cystic fibrosis (CF) sputum medium, attempts to mimic the growth environment in other respiratory disease states have been completely neglected. The composition of the airway surface liquid (ASL) in different pulmonary diseases is far less well characterised than CF sputum, making it very difficult for researchers to model these infection environments. In this review we discuss the components of human ASL, how different lung pathologies affect ASL composition, and how different pathogens interact with these components. This will provide researchers interested in mimicking different respiratory environments with the information necessary to design a host-mimicking medium, allowing for better understanding of how to treat pathogens causing infection in these environments.

Techniques for the controlled seeding and growth of cracks are urgently required for non-destructive testing technique evaluation, particularly for additive manufactured (AM) samples. This paper describes a method which uses a combination of tensile load and resonance excitation of notched AM samples, with in-situ monitoring of the resonance frequency serving to track crack dimensions. Mechanical low-cycle fatigue cracks, ranging in length from ~0.3 mm to ~5 mm, are successfully created in five AM samples using this technique. The samples are non-destructively characterized using optical microscopy and Nonlinear Resonance (NLR) testing. The exploitation of resonance enables the concentration of a significant number of stress cycles on the samples in much shorter timespans than conventional fatigue testing, enabling high throughput, while utilising compact components. Furthermore, the tracking of resonance frequency shift throughout the process enables non-invasive and non-contact real-time condition monitoring.

Even though, graphene family materials (GFMs) hold great promise for various applications, there are still significant knowledge gaps in ecotoxicology and environmental risk assessment associated with their potential environmental impacts. Here, we provide a critical perspective on published ecotoxicity studies of GFMs based on a meticulous bibliometric research. Analysis of the available data revealed that to date, ecotoxicity studies with GFMs have been carried out predominantly using freshwater species (82%), while their effects on marine or terrestrial or-ganisms are understudied. Three groups of organisms were found dominating ecotoxicological research: fish (39%), algae (20%) and arthropoda (20%) predominantly applying small, planktonic crustaceans. It was also revealed that despite their widespread detection in different environ-mental compartments the potential impacts of GFMs in complex test systems with hierarchical trophic organisation or in trophic transfer studies are significantly under-represented. One of the main causes was identified as the difficulties in the physicochemical characterisation of GFMs in complex terrestrial test systems or in aquatic micro- and mesocosm studies containing a sediment phase. The lack of tools for adequate characterisation of GFMs in these complex test systems may discourage researchers from conducting experiments under environmentally relevant test condi-tions. However, in the coming years, fundamental research about these complex test systems will con-tinue to better understand the mechanism behind GFMs toxicity affecting organisms in different environmental compartments and to ensure their safe and sustainable use in the future.

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.

Background: Multiple system atrophy (MSA) is a rapidly progressive neurodegenerative disorder that has no curative treatment. Diagnosis is based on a set of criteria established by Gilman (1998 and 2008) and recently updated by Wenning (2022). We aim to determine the effectiveness of [123I]Ioflupane SPECT in MSA, especially at the initial clinical suspicion. Methods: Cross-sectional study of patients at initial clinical suspicion of MSA, referred for [123I]Ioflupane SPECT. Results: 139 patients (68 men, 71 women) were included, 104 being MSA-probable and 35 MSA-possible. MRI was normal in 89.2% while SPECT was positive in 78.45%. SPECT showed high sensitivity (82.46%) and positive predictive value (86.24), reaching maximum sensitivity in MSA-P (97.26%). Significant differences were found when relating both SPECT assessments in the healthy-sick and inconclusive-sick groups. We also found an association when relating SPECT to the subtype (MSA-C or MSA-P), as well as to the presence of parkinsonian symptoms. Lateralization of striatal involvement was detected (left side). Conclusions: [123I]Ioflupane SPECT is a useful and reliable tool for diagnosing MSA, with good effectiveness and accuracy. Qualitative assessment shows a clear superiority when distinguishing between the healthy-sick categories, as well as between the parkinsonian (MSA-P) and cerebellar (MSA-C) subtypes at initial clinical suspicion.

Industrial data scarcity is one of the largest factors holding back the widespread use of machine learning in manufacturing. To overcome this problem, the concept of transfer learning was developed and it achieved high attention in recent industrial research. Our paper focuses on the problem of time series segmentation and presents the first in-depth research about transfer learning for deep-learning based time series segmentation on the example of industrial end-of-line pump testing. In particularly, we investigate if the performance of deep learning models can be increased by pretraining the network with data from other domains. Three different scenarios are analyzed: source and target data being closely related, source and target data being distantly related, and source and target data being non-related. The results demonstrate that transfer learning can enhance the performance of time series segmentation models in respect to accuracy and training speed. The benefit is most clearly seen in scenarios where source and training data are closely related and the number of target training data samples is lowest. However, in the scenario of non-related datasets, cases of negative Transfer Learning were observed as well. Thus, the research emphasizes the potential, but also the challenges of industrial Transfer Learning.

Biological drugs are inaccessible to more than 80% of the world population due mainly to their high costs; this is a significant concern of the World Health Organization. Biosimilars are supposed to reduce the cost burden, but their approval process is complex, including expensive and irrelevant studies. While the Stringent Regulatory Authorities (SRAs) have adopted the guidance of the FDA or EMA, such adoptions are neither necessary nor practical for the rest of the world (ROW). We present a science-driven, rational approach to formulate regulatory guidelines that will enable faster biosimilars' entry into the ROW without compromising their safety and efficacy. The key recommendations include removing animal and safety efficacy testing, making analytical assessment more robust, and cGMP compliance assured through third-party audits. The ROW countries are also recommended to initiate a rapporteur system available in the EU, to overcome the biases and assure state-of-the-science evaluation as the common understanding of the critical quality attributes evolves. It is anticipated that stronger regional agencies like those in the MENA region, with the leadership of the Kingdom of Saudi Arabia, will help propel the idea faster across the globe.

In an industrial environment, the quality assurance of weld seams requires extensive efforts. The most commonly used methods for that are expensive and time-consuming destructive tests, since quality assurance procedures are difficult to integrate into production processes. Beyond that, available test methods allow only the assessment of a very limited set of characteristics. They are either suitable for determining selected geometric features or for locating and evaluating internal seam defects. The presented work describes an evaluation methodology based on microfocus X-ray computed tomography scans (µCT scans) which enable the 3D characterization of weld seams, including internal defects such as cracks and pores. A 3D representation of the weld contour, i.e., the complete geometry of the joint area in the component with all quality-relevant geometric criteria, is an unprecedented novelty. Both the dimensions of the weld seam and internal defects can be revealed, quantified with a resolution down to a few micrometers and precisely assigned to the welded component. On the basis of the methodology developed within the framework of this study, the results of the scans performed on the alloy AA 2219 can be transferred to other aluminum alloys. In this way, the data evaluation framework can be used to obtain extensive reference data for the calibration and validation of inline process monitoring systems employing Deep Learning-based data processing.

This paper proposes a linear eddy-current feature to determine the radius of a metallic ball in a non-contact manner. An electromagnetic eddy-current sensor with two coils is placed co-axially to the metal ball during measurement. It is well known that the distance between the sensor and test piece (i.e. lift-off) affects eddy-current signals. In this paper, it is found that the peak frequency feature of inductance spectrum is linear to the lift-off spacing between the centre of coil and ball. Besides, the slope of peak frequencies versus lift-offs is linked to the radius of ball. The radius of metallic balls is retrieved from the experimental and embedded analytical result of the slope. Measurements have been carried out on 6 metallic balls with different radii. The radius of the metallic ball can be retrieved with an error of less than 2 %.

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.

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: It is unclear why certain countries have been more severely affected by COVID-19 than other countries. Methods: In this ecological study we compared COVID-19 mortality and incidence/100,000 as well as 4 putative explanatory factors by WHO world region. Linear regression was then used to assess the country-level predictors of COVID-19 mortality/100,000 and incidence/100,000 in 204 countries with available data. Results: COVID-19 incidence and mortality/capita were greater in Europe than other regions. This was despite a higher testing rate in Europe than other regions. Europe had an older population than all other regions and a higher prevalence of obesity than Africa, South East Asia and the Eastern Mediterranean. Country level multiple linear regression revealed positive associations between mortality/capita and testing rate, percent of the population 65 years or older, and Europe compared to Western Pacific and South East Asia (all P<0.005). Results for the analyses with cases/100,000 as outcome variable were similar. Conclusion: Our results suggest that older populations as well as other undefined regional and national factors, possibly related to efficacy of control efforts, are responsible for differences in national severity COVID-19 epidemics.

There is much discussion among clinicians, epidemiologists, and public health experts about why case fatality rate from COVID-19 in Italy (at 13.3% as of April 20, 2020, versus a global case fatality rate of 6.9%) is considerably higher than estimates from other countries (especially China, South Korea, and Germany). In this article, we propose several potential explanations for these differences. We suggest that Italy’s overall and relative case fatality rate, as reported by public health authorities, is likely to be inflated by such factors as heterogeneous reporting of coronavirus-related fatalities across countries and the iceberg effect of under-testing, yielding a distorted view of the global severity of the COVID-19 pandemic. We also acknowledge that deaths from COVID-19 in Italy are still likely to be higher than in other equally affected nations due to its unique demographic and socio-economic profile. Lastly, we discuss the important role of the stress imparted by the epidemic on the Italian healthcare system, which weakened its capacity to adequately respond to the sudden influx of COVID-19 patients in the most affected areas of the country, especially in the Lombardy region.

This paper presents the latest developments in microCT, both globally and locally, for supporting the additive manufacturing industry. There are a number of recently developed capabilities which are especially relevant to the non-destructive quality inspection of additive manufactured parts; and also for advanced process optimization. These new capabilities are all locally available but not yet utilized to their full potential, most likely due to a lack of knowledge of these capabilities. The aim of this paper is therefore to fill this gap and provide an overview of these latest capabilities, showcasing numerous local examples.