Absolute Value Of Difference Research Articles

Reassessing ISO 9972 constraints: A mathematical analysis of errors in building airtightness tests due to steady wind and stack effect

Building airtightness significantly impacts its energy use estimation. The fan pressurization test, outlined in ISO 9972, is the most commonly used assessment method. A crucial component is the zero-flow pressure difference, influenced only by wind and stack effects. The ISO 9972 mandates that the absolute value of this pressure difference be less than 5 Pa and the minimum pressure station be either 10 Pa or five times the zero-flow pressure difference. The rationale behind these constraints is not evident, often excluding high-rise and buildings in wind-prone areas from standardized testing.This research examines these ISO 9972 requirements, aiming to clarify their basis and propose alternatives. Equations were developed to connect airflow estimation error with the ratio of the measured pressure station to zero-flow pressure difference. The external pressure measurement location during the test was found pivotal in determining airflow errors due to ISO constraints. While existing constraints limit airflow errors in many scenarios, enhancements are possible. If ISO 9972 conditions are unfeasible, always maintaining a 10 Pa buffer across façades can contain maximum airflow errors. This study suggests an alternative constraint with a similar error range (about 15 %) to current ones, enabling standardized testing in environments where existing ISO conditions are unattainable.

Green Accounting Memoderasi Material Flow Cost Accounting terhadap Peningkatan Keberlangsungan Perusahaan

This study aims to test and find out the material flow cost accounting in increasing the sustainability of the company. In addition, this study also aims to test whether the green accounting variable moderates the relationship between each MFCA variable (production costs, and production yield/value) in increasing the sustainability of the company. The sample used in this research is energy companies listed on the Indonesia Stock Exchange (IDX) during the 2017-2022 period. The total sample is 55 out of 11 companies using a purposive sampling technique. Methods of data analysis using multiple regression and moderating regression analysis with the absolute difference value approach. Multiple linear regression analysis for the MFCA hypothesis (production costs, and production yield/value). Multiple linear regression analysis with absolute difference value test for the MFCA hypothesis (production costs, and yield/production value) moderated by green accounting. The results of the study show that MFCA (production costs) has no effect on green accounting. MFCA (Production Results) has a positive effect in increasing the sustainability of the company. The results of research related to moderating variables show that green accounting as a moderating variable strengthens the relationship between MFCA (yield/production value) in increasing company sustainability. Conversely, in the fourth and fifth hypotheses, green accounting weakens the MFCA (production costs) relationship in increasing the sustainability of the company.

Decoupling power and type I error rate considerations when incorporating historical control data using a test-then-pool approach.

To accelerate a randomized controlled trial, historical control data may be used after ensuring little heterogeneity between the historical and current trials. The test-then-pool approach is a simple frequentist borrowing method that assesses the similarity between historical and current control data using a two-sided test. A limitation of the conventional test-then-pool method is the inability to control the type I error rate and power for the primary hypothesis separately and flexibly for heterogeneity between trials. This is because the two-sided test focuses on the absolute value of the mean difference between the historical and current controls. In this paper, we propose a new test-then-pool method that splits the two-sided hypothesis of the conventional method into two one-sided hypotheses. Testing each one-sided hypothesis with different significance levels allows for the separate control of the type I error rate and power for heterogeneity between trials. We also propose a significance-level selection approach based on the maximum type I error rate and the minimum power. The proposed method prevented a decrease in power even when there was heterogeneity between trials while controlling type I error at a maximum tolerable type I error rate larger than the targeted type I error rate. The application of depression trial data and hypothetical trial data further supported the usefulness of the proposed method.

The impact of inhalation versus total intravenous anesthesia on the immune status in patients undergoing breast cancer surgery: a double-blind randomized clinical trial (TeMP).

Breast cancer (BC) mortality primarily stems from metastases rather than the primary tumor itself. Perioperative stress, encompassing both surgical and anesthetic factors, profoundly impacts the immune system, leading to alterations in neuroendocrine pathways and immune functions, potentially facilitating tumor progression and metastasis. Understanding the immunomodulatory effects of different anesthesia techniques is crucial for optimizing perioperative care in patients with BC. The neutrophil-to-lymphocyte ratio (NLR) serves as one of the key indicators of perioperative immune response. To compare the effects of inhalation anesthesia (IA) and total intravenous anesthesia (TIVA) on perioperative immune response in BC surgery patients. In this randomized, double-blind clinical trial, BC surgery patients were randomized to receive either TIVA with propofol or IA with sevoflurane. The primary endpoint was NLR assessment. Secondary immune parameters measured included natural killer cells, various T cell subsets, B cells, the immuno-regulatory index [T-helpers (CD3+CD4+)/cytotoxic T-cells (CD3+CD8+)], matrix metallopeptidases (MMP-9), complement components, and immunoglobulins, preoperatively and at 1 and 24 hours postoperatively. The study included 98 patients (IA: 48, TIVA: 50). The baseline characteristics exhibited remarkable similarity across the groups. No significant difference in absolute NLR values was found between IA and TIVA groups at any time point (1 hour: p = 0.519, 24 hours: p = 0.333). Decreased IgA and IgM levels post-surgery suggested potential negative impacts of IA on humoral immunity compared to TIVA. CRP levels increased more by 24 hours (p = 0.044) in IA compared to TIVA. No significant differences were observed in natural killer cells, T cell subsets, B cells, MMP-9 levels or complement components between groups. Significant differences in the immuno-regulatory index between the TIVA and IA groups at one hour postoperatively (p = 0.033) were not maintained at 24 hours. While there were no notable differences in NLR among the types of anesthesia, the observed disparities in immunoglobulin content and C-reactive protein levels between groups suggest that we cannot dismiss the potential immunosuppressive effects of inhalational anesthesia in breast cancer surgeries. Further investigation needed to clarify the impact of various anesthesia methods on immune function and their implications for long-term cancer outcomes.

Characteristics of Peripheral Retinal Refraction and Its Role in Children with Different Refractive States.

Peripheral retinal refraction plays a crucial role in myopia, but the specific mechanism is not clear. We refined the retinal partitions to explore the characteristics of peripheral retinal refraction and its role in emmetropic, low, and moderate myopic children aged 6 to 12 years. A total of 814 subjects (814 eyes) were enrolled in the study. The participants were divided into three groups according to the central spherical equivalent refraction (SER), which were emmetropia group (E), low myopia group (LM) and moderate myopia group (MM). Multispectral refractive topography (MRT) was used to measure the retinal absolute and relative refractive difference value (RDV) in different regions. The range was divided into superior, inferior, temporal, and nasal RDV (SRDV, IRDV, TRDV, and NRDV) on the basis of several concentric circles extending outward from the macular fovea (RDV15, RDV30, RDV45, RDV30-15, RDV45-30, and RDV-45). Kruskal-Wallis test was used to analyze the differences of peripheral refraction for all the regions among the three groups. Spearman rank correlation was performed to explore correlations between SER and RDV, axial length (AL) and RDV. The absolute value of RDV decreased with increasing degree of myopia in all regions (P < 0.01). Subjects with different refractive degrees had different relative value of RDV. In nasal position within 45° and temporal position within 30°, the peripheral retina exhibited significantly different relative hyperopic refractive status among Group E, Group LM, and Group MM (P < 0.05). SER was negatively correlated with NRDV within 30° (especially in the range of NRDV30-15) (r = -0.141, P < 0.01), positively correlated with TRDV within 15° (r = 0.080, P = 0.023), and not significantly correlated with SRDV and IRDV when the retina was divided into four parts. AL was positively correlated with NRDV within 30° (especially in the range of NRDV30-15) (r = 0.109, P = 0.002), negatively correlated with TRDV within 15° (r = -0.095, P = 0.007). The peripheral defocus has significant implications for the genesis of myopia. The peripheral defocus of the horizontal direction, especially within the range of NRDV30, has greater effect on the development of myopia in children. Higher NRDV30 is associated with lower SER and longer AL.

Thermally modified nanocrystalline snail shell adsorbent for methylene blue sequestration: equilibrium, kinetic, thermodynamic, artificial intelligence, and DFT studies.

In recent years, the quest for an efficient and sustainable adsorbent material that can effectively remove harmful and hazardous dyes from industrial effluent has become more intense. The goal is to explore the capability of thermally modified nanocrystalline snail shells (TMNSS) as a new biosorbent for removing methylene blue (MB) dye from contaminated wastewater. TMNSS was employed in batch adsorption experiments to remove MB dye from its solutions, taking into account various adsorption parameters such as contact time, temperature, pH, adsorbent dosage, and initial concentration. SEM, EDS, XRD, and FTIR were used to characterize the adsorbent. The study further developed and adopted adaptive neuro-fuzzy inference system (ANFIS) and density functional theory (DFT) studies to holistically examine the adsorption process of MB onto the adsorbent. EDX and FTIR confirm the formation of CaO with a sharp peak at 547 cm-1, and C-O and O-H are present, as well. SEM and XRD show an irregularly shaped highly crystalline nanosized (65 ± 2.81 nm) particle with a lattice parameter value of 8.611617 Å. The adsorption efficiency of 96.48 ± 0.58% was recorded with a pH of 3.0 and an adsorbent dose of 10 mg at 30 °C. The findings from the study fit nicely onto Freundlich isotherms, with Qm = 31.7853 mg g-1 and R2 = 0.9985. Pseudo-second-order kinetics recorded the least error value of 0.8792 and R2 = 0.9868, thus indicating chemisorption and multilayer adsorption processes. The exothermic and spontaneous nature of the adsorption process are demonstrated by ΔH° and ΔG°. The performance of the ANFIS-based prediction of removal rate, which was demonstrated by a root mean square error (RMSE) value of 2.2077, mean absolute deviation (MAD) value of 1.1429, mean absolute error (MAE) value of 1.8786, and mean absolute percentage error (MAPE) value of 2.0178, revealed that the ANFIS model predictions and experimental findings are in good agreement. More so, DFT provides insights into the molecular interactions between MB and the adsorbent surface, with a calculated adsorbate-adsorbent binding affinity value of -1.3 kcal mol-1, thus confirming the ability of TMNSS for MB sequestration. The findings of this study highlight the promising potential of thermally modified nanocrystalline snail shells as sustainable and efficient adsorbents for MB sequestration.

Biomass‐based lateral root morphological parameter models for rapeseed (Brassica napus L.)

AbstractLateral roots, including adventitious roots, are the main component of rapeseed roots with support, absorb, and synthesis functions and their morphological parameters directly affecting the plant's aboveground growth and yield. Root biomass, as a material base for lateral root growth, can be used as a link between plant phenotypes and their physiological processes, as well as to enhance root 3D growth model mechanisms and accuracy. To quantify the relationships between lateral root morphological indices and the corresponding organ biomass for rapeseed, we used two cultivars, NY 22 (conventional) and NZ 1818 (hybrid), and conducted cultivar and fertilizing cylindrical tube experiments during the 2016–2019, with two fertilizer levels, no fertilizer, and 180 kg N ha−1 fertilizer. The lateral root biomass and morphological parameters were determined during the whole growth period. The biomass‐based lateral root morphological parameter models were developed by analyzing the quantitative relationship between the lateral root morphological indices and their corresponding biomass, and the descriptive models were verified with independent experimental data. The results showed that the correlation (r) of simulated and observed values for the lateral root morphological parameters are all greater than 0.9 with significant levels at p &lt; 0.001. The absolute values of the average absolute difference (da) of simulated and observed values for the lateral root length (LLR), lateral root average diameter (ADLR), lateral root surface area (SALR), and lateral root volume (VLR) are −30.408 cm, −0.003 mm, 12.902 cm2, and 0.039 cm3, respectively. The RMSE values are 175.183 cm, 0.010 mm, 59.710 cm2, and 1.513 cm3, respectively. The ratio of da to the average observed values (dap) for the LLR and VLR are all less than 5%, and the ADLR and SALR are all &lt;6%. The models developed in this paper have good performance and reliability for predicting lateral root morphological parameters of rapeseed. The study provides a mechanistic method for linking the rapeseed growth model with the morphological model using corresponding organic biomass and laying a good foundation for establishing a 3D morphological model for rapeseed root system based on biomass.

Implementasi Metode Peramalan (Forecasting) Pada Penjualan Kuas di PT ABC

PT ABC is a company engaged in the distribution of various kinds of building materials, wood construction materials, chemicals, office machines, glass, porcelain, cement, household equip-ment and supplies, and dairy products. The aim of this research is to meet fluctuating product demand. In this article, there are four forecasting methods used based on historical data graphic patterns, namely Naïve, Simple Moving Average, Weighted Moving Average, and Exponential Smoothing. Then, the best forecasting method with the smallest error rate was determined for the X Brush product at PT ABC. From the research results, it is known that the forecasting graph has a trend pattern due to an increase or decrease in data in the long term. The appropriate method for forecasting is using the Exponential Smoothing method with α = 0.1 with a Mean Absolute Deviation (MAD) value of 132.48, Mean Square Error (MSE) of 21981, and Mean Absolute Percentage Error (MAPE) of 61.73%%..

Employing RSM and ANN-based applications for modelling enhanced bacterial cellulose production from pineapple peel waste using Komagateibacter saccharivorans APPK1

Bacterial cellulose (BC) is a bio-polymer with variety of applications in diverse fields such as biomedical, cosmetics, environment and food. Owing to its superior crystallinity, purity and other unique properties BC outshines plant cellulose in several aspects. The current study focuses on a cost-effective method for BC production from pineapple waste using Komagateibacter saccharivorans APPK1. The research includes a systematic optimisation approach that includes screening of various components in the medium. The variables under investigation in this study were ammonium sulphate, ethanol volume and incubation days. These variables were selected and evaluated using the Plackett-Burman experimental design model. Additionally, the engineering of process parameters using a process-driven approach i.e., response surface methodology (RSM) and a data-driven approach i.e., artificial neural network (ANN) were employed. BC production was increased up to 43 % with a maximum yield of 47.5 g/100 mL using RSM. However, on comparing RSM and ANN models for enhanced BC production based on error functions such as R2 value, mean absolute percentage error, root mean square error, and mean absolute deviation values, the ANN model emerged as the superior one. As this is the first report to the authors’ best knowledge on model development using a hybrid approach of RSM and ANN for enhanced BC production using Komagateibacter saccharivorans APPK1, this could lead to more in-depth and large-scale production of BC.

Cone-beam computed-tomography-based delta-radiomic analysis for investigating prognostic power for esophageal squamous cell cancer patients undergoing concurrent chemoradiotherapy

PurposeTo investigate the prognostic power of cone-beam computed-tomography (CBCT)-based delta-radiomics in esophageal squamous cell cancer (ESCC) patients treated with concurrent chemoradiotherapy (CCRT). MethodsWe collected data from 26 ESCC patients treated with CCRT. CBCT images acquired at five time points (1st–5th week) per patient during CCRT were used in this study. Radiomic features were extracted from the five CBCT images on the gross tumor volumes. Then, 17 delta-radiomic feature sets derived from five types of calculations were obtained for all the cases. Leave-one-out cross-validation was applied to investigate the prognostic power of CBCT-based delta-radiomic features. Feature selection and construction of a prediction model using Coxnet were performed using training samples. Then, the test sample was classified into high or low risk in each cross-validation fold. Survival analysis for the two groups were performed to evaluate the prognostic power of the extracted CBCT-based delta-radiomic features. ResultsFour delta-radiomic feature sets indicated significant differences between the high- and low-risk groups (p < 0.05). The highest C-index in the 17 delta-radiomic feature sets was 0.821 (95 % confidence interval, 0.735–0.907). That feature set had p-value of the log-rank test and hazard ratio of 0.003 and 4.940 (95 % confidence interval, 1.391–17.544), respectively. ConclusionsWe investigated the potential of using CBCT-based delta-radiomics for prognosis of ESCC patients treated with CCRT. It was demonstrated that delta-radiomic feature sets based on the absolute value of relative difference obtained from the early to the middle treatment stages have high prognostic power for ESCC.

Mind the gap: Concordance between perceptions regarding vaccination as declared by patients and their evaluation by their general practitioner

BackgroundThe high level of vaccine hesitancy reported in the French population may lead general practitioners to anticipate difficult discussions on this topic. We aimed to assess the extent to which general practitioners’ evaluation of their patients’ vaccine hesitancy was correlated with the real vaccine hesitancy expressed by these patients. MethodsThe study was based on two brief paper questionnaires completed in private by the general practitioner and the patient at the beginning of a medical appointment: one for the physician to evaluate on three quantitative and non-graduated visual scales (then analysed as a 0–100 scale) their patients’ perceptions regarding vaccine safety, vaccine efficacy and ‘being in favour of vaccination’; and one for the patient to express their perceptions for the same three axes using the same scales. ResultsOverall, 31 physicians participated in the study, with 540 physician-patient pairs being included. The physicians’ evaluation of patient perceptions was more positive when the physician was male (vs female), when the patient was male (vs female) and when both were males (vs both females). The median differences (in absolute values) between the physician evaluations and the patient perceptions were between 9 and 11 (on the 0–100 scale) for the three axes (vaccine safety, vaccine efficacy and ‘being in favour’). A correlation was observed between the physicians’ evaluation and the patients’ declaration (Kendall test: vaccine efficacy: tau = 0.199, p < 0.001; vaccine safety: tau = 0.234, p < 0.001; being in favour of vaccination: tau = 0.365, p < 0.001). Physicians correctly classified 83.4 % of the patients with high perceptions of vaccine safety and efficacy (>75/100 for both scales) but only 54.5 % of those with low perceptions (<75/100 for both scales). ConclusionPhysicians tend to correctly identify patients with the most favourable perceptions about vaccination but not those with the least favourable perceptions.

First Line Therapy Evaluation Using Propensity Score Approach in Newly Diagnosed Advanced Classical Hodgkin Lymphoma Patients from Prospective Real-World Realysa Cohort and Phase 3 AHL2011 Trial

Background: AHL2011, a randomized phase III trial demonstrated that PET-CT after two cycles of BEACOPP escalated chemotherapy safely guided treatment of patients aged 16-60 years with newly diagnosed advanced classical Hodgkin lymphoma (cHL) and allowed the use of ABVD in early responders with reduced toxicities and no impaired disease control. REALYSA study, a real-life multicentric cohort set up in France since 2018, included 6000 newly diagnosed lymphoma patients with over 1000 cHL patients. In the present study, we investigated whether real-world data could reproduce results issued from a randomized phase III clinical trial using the propensity score approach. Methods: After stringent propensity score matching (PSM) on 10 baseline parameters (gender, age, Ann Arbor stage, ECOG Performance Status, number of extranodal sites involved, B symptoms, albumin, hemoglobin, white blood cell count and lymphocytes), we performed a PSM testing ratios 1:1 (one patient from AHL2011 trial and one patient from REALYSA cohort). All patients from AHL2011 and REALYSA included in this study had PET-CT monitoring after two cycles of BEACOPP escalated. This approach allowed us to build well-balanced pairs as demonstrated by the absolute values of the standardize mean differences (SMDs) below 0.1 for all matching covariates except for ECOG (SMD=0.15). We also used the Inverse Probability of Treatment Weighting (IPTW, IPTW stabilized) to compare the experimental arm of the AHL2011 trial with a synthetic control arm established with real-world data from REALYSA cHL patients who respected the main inclusion criteria of AHL2011 trial and were treated following this PET-guided approach. The median follow-up was censored in the AHL2011 data in order to be comparable to the median follow-up observed in the REALYSA cohort. Results: Among the 823 patients of AHL2011 and 942 patients of REALYSA with newly diagnosed cHL, 390 and 100 patients respectively were eligible for propensity score calculation, corresponding to AHL2011 TEP-guided therapy, aged between 16 and 60 years, no missing data for the covariates included in the PSM and at least 12 months of follow-up in the REALYSA study. After 1:1 PSM (n=98 AHL2011 and n=98 REALYSA), the overall response rate at the end of induction was 91.8% vs 89.8% (p=0.81) for patients included in AHL2011 and REALYSA, respectively. The proportion of patients with positive PET-CT after 2 cycles was similar in AHL2011 (13%) and REALYSA (14%). After a median follow-up of 13 months, the 1-year progression free survival rates were 93.8% and 87.8% (HR=0.87; 95%CI 0.4-2.0; P=0.74) in AHL2011 and REALYSA, respectively (Figure 1A). Using IPTW model including covariates from the PSM, similar PFS were obtained between experimental arm of AHL2011 and patients included in REALYSA (Figure 1B). IPTW stabilized and other IPTW models also showed similar results for PFS. Conclusions: In this study, we demonstrated using a propensity score approach that patients with newly diagnosed advanced cHL treated according to the AHL2011 PET-guided frontline approach in routine care and included in REALYSA cohort reached similar outcomes as patients included in prospective phase III clinical trial. Beyond the relevant validation of the AHL2011 trial results in real-life, which will need longer follow up, these data could be used to design composite control arm for future clinical trials.

Optimized steganography techniques based on PVDS and genetic algorithm

Due to the rapid development of confidential digital communication over international networks, security is the most significant factor. Steganography is the science of concealed communication and is used to conceal the presence of secret information among the various methods of hiding data in communications. Steganography techniques are usually implemented either in spatial or frequency domains. Some spatial domain methods fundamentally utilize the absolute difference value between neighbor pixels to encode the secret message, categorized as Pixel-Value Differencing Steganography methods (PVDS). In PVDS, the hiding capacity of the adjacent pixels depends on their difference value. Consequently, the secret data will be embedded with a high visual quality of the stego-image. Indicator-based PVDS (IPVDS) technique is derived from the PVDS method. It depends on an Indicator pixel (IP) to extract the secret data correctly. The Genetic Algorithm (GA) approach to optimization depends on the concept of survival of the fittest. This paper introduces two proposals, GA-based steganography schemes (GA-IPVD) and (GA-IPVDM). These new techniques encoded secret data using the IPVDS method. Before embedding data in the cover image, the order of the pixels corresponding to the secret data is modified and rearranged. GA controls the operation of rearranging and modifying the order of pixels and all parameters. The current paper addresses steganography as an optimization problem and seeks to determine the optimal order of the pixels that enhance the matching between the cover image and stego-image to reduce distortion despite high embedded capacity. In the first proposed technique GA-IPVD, GA concentrates on the imperceptibility of embedded data and maximizes the quality of the stego-image according to the given secret data. In contrast, the GA maximizes the capacity of embedded data while maintaining an acceptable amount of stego-image quality in the second proposed technique GA-IPVDM. The proposed systems have embedding key that increase the security of proposed schemes. The experimental results demonstrate that the proposed methods can embed a large quantity of secret data while maintaining an acceptable visual quality of the stego-images. The proposed technique has also demonstrated excellent resistance to a variety of stego-attacks, including the pixel difference histogram (PDH) as well as regular and singular (RS) analyses. Additionally, the out-of-boundary pixel issue (BI), which endures in the majority of modern data hiding algorithms, has been successfully resolved.

Global horizontal irradiance prediction model considering the effect of aerosol optical depth based on the Informer model

Accurate and reliable global horizontal irradiance (GHI) prediction helps respond to the volatility of solar power output in advance. Aerosol optical depth (AOD) is the primary factor affecting the GHI in clear skies. In this study, the Informer model was first used to predict the GHI over the next 8 h by considering the AOD, meteorological parameters, and historical GHI data of Beijing as input variables, and the prediction of the GHI without AOD as a feature was calculated. The comparison results showed that the prediction errors of the models that considered AOD were lower than those of the models that did not. Moreover, when the AOD of the predicted day was larger, the difference in the mean absolute percentage error values between the two models was more significant. Hence, we proposed Planck's average AOD as a feature input to the GHI prediction model and found that the accuracy of the model improved regardless of the AOD size on the prediction day. The applicability of the developed model was verified using Golden's data. Overall, these findings indicate that this model can improve computational efficiency while maintaining good predictive performance.

Variable Performance of Lupus Anticoagulant Testing: The Australasian/Asia-Pacific Experience.

Lupus anticoagulant (LA) is one of three tests identified as laboratory criteria for definite antiphospholipid syndrome (APS). The other two tests are anticardiolipin antibody (aCL) and anti-β2-glycoprotein I (aβ2GPI) antibody. The presence of LA is assessed using clot-based tests, while the presence of aCL and aβ2GPI is assessed by immunological assays. Since no test can be considered 100% sensitive or specific for LA, current guidelines recommend using two different clot-based assays reflecting different principles, with the dilute Russell viper venom time (dRVVT) and activated partial thromboplastin time (aPTT) recommended. Initially, LA-sensitive reagents are used to screen for LA, and then, in "screen-positive" samples, LA-"insensitive" reagents are used to confirm LA. Because LA assays are based on clot detection, anything that can interfere with fibrin clot development may affect test results. In particular, in addition to LA, the tests are also sensitive to the presence of a wide range of clinical anticoagulants, reflecting preanalytical issues for testing. We provide updated findings for LA testing in our geographic region, using recent data from the Royal College of Pathologists of Australasia Quality Assurance Programs, an international external quality assessment program with approximately 120 participants. Data show a wide variety of assays in use, especially for aPTT testing, and variable outcomes in reported numerical values with these assays when assessing proficiency samples. dRVVT testing mostly comprised reagents from three main manufacturing suppliers, which also showed differences in numerical values for the same homogeneous tested samples. Nevertheless, despite the use of different test reagents and processes, >98% of participants correctly identified LA-negative samples as LA-negative and LA-positive samples as LA positive. We hope our findings, reflecting on the heterogeneity of test processes and test data, help improve diagnostic testing for LA in the future.

Deep Learning Approach for Human Action Recognition Using a Time Saliency Map Based on Motion Features Considering Camera Movement and Shot in Video Image Sequences

In this article, a hierarchical method for action recognition based on temporal and spatial features is proposed. In current HAR methods, camera movement, sensor movement, sudden scene changes, and scene movement can increase motion feature errors and decrease accuracy. Another important aspect to take into account in a HAR method is the required computational cost. The proposed method provides a preprocessing step to address these challenges. As a preprocessing step, the method uses optical flow to detect camera movements and shots in input video image sequences. In the temporal processing block, the optical flow technique is combined with the absolute value of frame differences to obtain a time saliency map. The detection of shots, cancellation of camera movement, and the building of a time saliency map minimise movement detection errors. The time saliency map is then passed to the spatial processing block to segment the moving persons and/or objects in the scene. Because the search region for spatial processing is limited based on the temporal processing results, the computations in the spatial domain are drastically reduced. In the spatial processing block, the scene foreground is extracted in three steps: silhouette extraction, active contour segmentation, and colour segmentation. Key points are selected at the borders of the segmented foreground. The last used features are the intensity and angle of the optical flow of detected key points. Using key point features for action detection reduces the computational cost of the classification step and the required training time. Finally, the features are submitted to a Recurrent Neural Network (RNN) to recognise the involved action. The proposed method was tested using four well-known action datasets: KTH, Weizmann, HMDB51, and UCF101 datasets and its efficiency was evaluated. Since the proposed approach segments salient objects based on motion, edges, and colour features, it can be added as a preprocessing step to most current HAR systems to improve performance.

Global dataset of soil organic carbon in tidal marshes

Tidal marshes store large amounts of organic carbon in their soils. Field data quantifying soil organic carbon (SOC) stocks provide an important resource for researchers, natural resource managers, and policy-makers working towards the protection, restoration, and valuation of these ecosystems. We collated a global dataset of tidal marsh soil organic carbon (MarSOC) from 99 studies that includes location, soil depth, site name, dry bulk density, SOC, and/or soil organic matter (SOM). The MarSOC dataset includes 17,454 data points from 2,329 unique locations, and 29 countries. We generated a general transfer function for the conversion of SOM to SOC. Using this data we estimated a median (± median absolute deviation) value of 79.2 ± 38.1 Mg SOC ha−1 in the top 30 cm and 231 ± 134 Mg SOC ha−1 in the top 1 m of tidal marsh soils globally. This data can serve as a basis for future work, and may contribute to incorporation of tidal marsh ecosystems into climate change mitigation and adaptation strategies and policies.

Effects of Daily Posttraumatic Stress Disorder Symptoms on Heart Rate Variability.

Posttraumatic stress disorder (PTSD) is common, debilitating, and associated with an increased risk of health problems, including cardiovascular disease. PTSD is related to poor autonomic function indicated by reduced heart rate variability (HRV). However, very little work has tested the timescale or direction of these effects, given that most evidence comes from cross-sectional studies. Documentation of when effects occur and in what direction can shed light on mechanisms of cardiovascular disease risk and inform treatment. The present study of 169 World Trade Center responders, oversampled for PTSD, tested how daily PTSD symptoms were associated with autonomic function as reflected through HRV. Participants ( N = 169) completed surveys of PTSD symptoms three times a day at 5-hour intervals for 4 days while also wearing ambulatory monitors to record electrocardiograms to derive HRV (i.e., mean absolute value of successive differences between beat-to-beat intervals). HRV did not predict PTSD symptoms. However, PTSD symptoms during a 5-hour interval predicted reduced HRV at the next 5-hour interval ( β = -0.09, 95% confidence interval = -0.16 to -0.02, p = .008). Results held adjusting for baseline age, current heart problems, and current PTSD diagnosis. Findings underscore growing awareness that PTSD symptoms are not static. Even their short-term fluctuations may affect cardiovascular functioning, which could have more severe impacts if disruption accumulates over time. Research is needed to determine if momentary interventions can halt increases in PTSD symptoms or mitigate their impact on cardiovascular health.

Linearization interpolation method with high robustness and high accuracy for sinusoidal encoders

This paper presents a linearization interpolation method with high robustness and high accuracy for sinusoidal encoders. Based on the pseudo-linearized signal constructed by the ratio of absolute values difference and absolute values sum of the sine and cosine signals, a compensation coefficient is designed to amplify pseudo-linearized signal to approximate ideal linearized signal for improving the linearity. The linearity is improved from 9.05% to 0.015%, which means that the linearized signal can be used to accurately determine the phase angle. This method is easy to implement, has high accuracy, and does not require the lookup tables (LUTs) or processors. The theoretical phase error is less than 0.007° over 0° ∼ 360°, corresponding to about 15-bit accuracy per signal period. In addition, the proposed method is implemented on the hardware platform with a field-programmable gate array (FPGA). Finally, the effectiveness of proposed method is demonstrated by experiments using simulated sinusoidal encoder.

Disease progression and changes in KL-6 in patients with limited cutaneous systemic sclerosis-associated interstitial lung disease

BackgroundLittle is known about the annual change in Krebs von Lungen-6 (KL-6) and its correlation with forced vital capacity (FVC) in limited cutaneous systemic sclerosis-associated interstitial lung disease (lcSSc-ILD). We aimed to clarify the correlation during the clinical course. MethodsWe retrospectively reviewed data from consecutive patients with lcSSc-ILD. We measured FVC and KL-6 annually and calculated their annual changes using the difference in absolute values. Decline in FVC was defined as annual decline in FVC ≥5 %. ResultsThirty-eight patients with SSc-ILD were included. The median age was 62 years and 58 % were female. The median FVC was 87.3 % and the median KL-6 was 1629 U/ml. The median observation period was 55.2 months and the annual changes in FVC and KL-6 were evaluated 151 times simultaneously. The annual change in KL-6 had a significant negative correlation with that in FVC in the first year from the initial evaluation (from the baseline to one-year follow-up) (r = −0.819, p < 0.01), but not after the first year. In the multivariable analysis adjusted by age, sex, and FVC at each year, the annual change of KL-6 (per 100 U/ml) was significantly associated with decline in FVC in the first year (odds ratio: 3.03, 95 % confidence interval: 1.21–7.59, p = 0.02), but not after the first year. ConclusionsOnly in the first year from the initial evaluation, there was negative correlation between the annual change in FVC and that in KL-6 and the annual elevation in KL-6 was associated with decline in FVC in patients with lcSSc-ILD.