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Training LiDAR point clouds object detectors requires a significant amount of annotated data, which is time-consuming and effort-demanding. Although weakly supervised 3D LiDAR-based methods have been proposed to reduce the annotation cost, their performance could be further improved. In this work, we propose a weakly supervised LiDAR-based point clouds vehicle detector that does not require any labels for the proposal generation stage and needs only a few labels for the refinement stage. It comprises two primary modules. The first is an unsupervised proposal generation module based on the geometry of point clouds. The second is the pseudo-label refinement module. We validate our method on two point clouds based object detection datasets, namely KITTI and ONCE, and compare it with various existing weakly supervised point clouds object detection methods. The experimental results demonstrate the method’s effectiveness with a small amount of labeled LiDAR point clouds.

Hydrologic and geomorphic processes are intricately linked within the Earth system, jointly characterizing terrestrial hydrological behaviors and biogeochemical cycles across diverse temporal and spatial scales. The Tibetan Plateau provides an ideal setting for investigating the interactions between hydrological and geomorphic processes in a largely pristine natural environment. Nonetheless, the interactions remain largely unknown due to challenging physical conditions and data limitations. This study presents the inaugural version of a hydrogeomorphic dataset encompassing 18 440 catchments across the region. The dataset comprises 18 hydrogeomorphic metrics along with, in particular, the width-function-based instantaneous unit hydrograph (WFIUH) of each catchment. We find that the peak flow of WFIUH is positively related to slope and curvature but negatively related to catchment area, perimeter, length and circularity. The relationships of time to peak with the hydrogeomorphic metrics are similar to those of peak flow but in an oppositive direction. Catchment concentration time shows a positive relationship with catchment size but a strong negative correlation with catchment slope. The validity of the derived WFIUH has been confirmed by its successful integration into an hourly hydrological model for simulating flash-flood events. Uncertainties in the WFIUH can be attributed to the resolution of the digital elevation model (DEM) and the methods employed for calculating flow velocity. The dataset is publicly available via the Zenodo portal: https://doi.org/10.5281/zenodo.8280786 (Guo and Zheng, 2023). It can contribute to advancing our understanding of catchment hydrological behaviors and can provide simple and fast-routing unit hydrograph calculation for ungauged catchments in the Tibetan Plateau and hence improve water resources management and disaster mitigation in the region and its downstream areas.

Objective: Knee osteoarthritis (OA) is a complex disease with heterogeneous representations. Although it is modifiable to prevention and early treatment, there still lacks a reliable and accurate prognostic tool. Hence, we aim to develop a quantitative and self-administrable knee replacement (KR) risk stratification system for knee osteoarthritis (KOA) patients with clinical features. Method: A total of 14 baseline features were extracted from 9592 cases in the Osteoarthritis Initiative (OAI) cohort. A survival model was constructed using the Random Survival Forests algorithm. The prediction performance was evaluated with the concordance index (C-index) and average receiver operating characteristic curve (AUC). A three-class KR risk stratification system was built to differentiate three distinct KR-free survival groups. Thereafter, Shapley Additive Explanations (SHAP) was introduced for model explanation. Results: KR incidence was accurately predicted by the model with a C-index of 0.770 (±0.0215) and an average AUC of 0.807 (±0.0181) with 14 clinical features. Three distinct survival groups were observed from the ten-point KR risk stratification system with a four-year KR rate of 0.79%, 5.78%, and 16.2% from the low, medium, and high-risk groups respectively. KR is mainly caused by pain medication use, age, surgery history, diabetes, and a high body mass index, as revealed by SHAP. Conclusion: A self-administrable and interpretable KR survival model was developed, underscoring a KR risk scoring system to stratify KOA patients. It will encourage regular self-assessments within the community and facilitate personalised healthcare for both primary and secondary prevention of KOA.

INTRODUCTION: Anaemia in geriatric populations poses challenges to healthcare systems worldwide. Hence, this study was done to investigate the incidence of anemia among the geriatric population of South India. METHODS: Retrospective, cross-sectional study with 144 patients aged 65 years and above. Socio-demographic data and laboratory findings were recorded in a validated proforma format. Data were analyzed using SPSS. RESULTS: 36.1% of the study population was anemic, and 63.9% were non-anemic. The prevalence of anemia was higher among females (36.36%) than males (35.82%). The prevalence of anemia was significantly correlated with advanced age (r=0.21; p < 0.05) and female sex (r=0.25; p < 0.05). Thirty-six patients were mild anemic (69%), 13 had moderate (25%), and 3 (6%) had severe anemia. Nutritional anemia was most common (80%), followed by hemorrhagic anemia (18%) and hemolytic anemia (2%). Among the 52 patients who were anemic, the most common comorbidities associated were Type 2 diabetes mellitus (69.2%) and hypertension (53.8%). Liver diseases were present in 5 cases (9.62%), renal insufficiency in 14 cases (26.9%), hypercholesterolemia in 5 cases (9.62%), and 6 cases (11.5%) were associated with other diseases. All the patients were managed conservatively with treatment, and anemia improved in 36.5% of cases. CONCLUSION: Anaemia was frequently diagnosed in the studied geriatric population. Nutritional deficiencies were the most common cause, followed by hemorrhagic and hemolytic anemia. The impact of anemia on quality of life, recovery from illness, and functional abilities must be further investigated in future geriatric studies.

We report on the interplay between a van Hove singularity and a charge density wave state in 2H-TaSe_{2}. We use angle-resolved photoemission spectroscopy to investigate changes in the Fermi surface of this material under surface doping with potassium. At high doping, we observe modifications which imply the disappearance of the (3×3) charge density wave and formation of a different correlated state. Using a tight-binding-based approach as well as an effective model, we explain our observations as a consequence of coupling between the single-particle Lifshitz transition during which the Fermi level passes a van Hove singularity and the charge density order. In this scenario, the high electronic density of states associated with the van Hove singularity induces a change in the periodicity of the charge density wave from the known (3×3) to a new (2×2) superlattice.

ABSTRACT: This study was conducted to investigate the effect of anhydrous betaine and hydrochloride betaine on growth performance, meat quality, relaxometry, postmortem glycolysis, and antioxidant capacity of partridge shank broiler chickens. A total of 400 one-day-old male broilers were randomly divided into 5 treatments and fed basal diets supplemented with 0 (control), 500 (L-AB) or 1,000 (H-AB) mg/kg anhydrous betaine, and 642.23 (L-HB) or 1,284.46 (H-HB) mg/kg hydrochloride betaine, respectively. Compared with the control group, anhydrous betaine supplementation significantly increased (P < 0.05) average daily gain and decreased (P < 0.05) drip loss24h in breast and thigh muscles of broilers. The H-AB group further increased (P < 0.05) breast muscle yield, pH24h, immobile water proportion (P21), the contents of crude protein and glutathione (GSH), the activities of creatine kinase (CK) and glutathione peroxidase (GPX), the mRNA expressions of glucose transporter 4 (GLUT4), protein kinase AMP-activated non-catalytic subunit gamma 3 (PRKAG3), nuclear factor erythroid 2-related factor 2 (Nrf2) and heme oxygenase 1 (HO-1) in breast muscle, and a*45min, GLUT4 mRNA expression in thigh muscle, and decreased (P < 0.05) drip loss48h, free water proportion (P22), the contents of lactate and malondialdehyde (MDA) in breast muscle. Moreover, the H-HB group significantly increased (P < 0.05) pH24h, P21 proportion, the activities of CK, total antioxidant capacity (T-AOC), total superoxide dismutase (T-SOD), and GPX, the content of GSH, the mRNA levels of Nrf2, HO-1, GPX, and γ-glutamate-cysteine ligase catalytic subunit (γ-GCLc) in breast muscle, and the activity and mRNA expression of GPX in thigh muscle, and decreased (P < 0.05) drip loss24h, P22 proportion in breast muscle, and MDA content in breast and thigh muscles. In conclusion, anhydrous betaine showed better effects than hydrochloride betaine in improving growth performance and breast muscle yield of broilers. Moreover, anhydrous betaine (1,000 mg/kg) or equimolar hydrochloride betaine supplementation could improve meat quality by decreasing drip loss, free water proportion, and lactate content, and enhancing muscle antioxidant capacity.

ABSTRACT: This study aimed to investigate the effects of chitooligosaccharide (COS) on intestinal barrier, antioxidant capacity, and immunity of lipopolysaccharide (LPS)-challenged laying hens. A total of 360 Hy-line Brown laying hens (80-wk-old) were randomly divided into 5 groups with 6 replicates of 12 birds. Hens were fed a corn-soybean meal basal diet supplemented with different COS levels (0; 5; 10; 15; 20 mg/kg) for 8 wk. The results showed that 15 mg/kg COS administration elevated albumen height and Haugh unit (P < 0.05), and numerically optimized productive performance (P > 0.05), therefore, the dosage of 15 mg/kg was chosen for the subsequent experiment. Thereafter, 12 birds from non-supplemented group were randomly selected and assigned into 2 groups, and birds in each group were administered (1.5 mg/kg BW, i.p.) with saline (control group) or LPS (challenge group). Another 6 hens from 15 mg/kg COS-supplemented group were selected and injected with LPS in the same way. Compared with the control group, LPS-challenged birds exhibited elevated circulating diamine oxidase activity, and reduced jejunal villus height and ratio of villus height to crypt depth, and these indices were reversed to control levels by COS (P < 0.05). Also, LPS increased malondialdehyde accumulation and reduced several antioxidant enzyme activities in the intestinal mucosa (P < 0.05). Additionally, LPS increased jejunal secretory IgA and interferon-γ (IFN-γ), and ileal secretory IgA, IgM, and interleukin-1β (IL-1β) concentrations, whereas COS reduced jejunal IFN-γ and IL-1β, and ileal IgM levels (P < 0.05). Moreover, LPS down-regulated mRNA abundance of jejunal occludin and claudin 2, and upregulated expression of jejunal nuclear factor erythroid-2 related factor 2, superoxide dismutase 1, and IFN-γ as well as ileal IL-1β (P < 0.05). Besides, COS increased jejunal occludin and ileal claudin 2, nuclear factor erythroid-2 related factor 2, and heme oxygenase-1 expression, and decreased jejunal IFN-γ and IL-1β abundance (P < 0.05). These results suggested that COS could alleviate LPS-induced intestinal barrier impairment, and oxidative and immunological stress in laying hens.

On-road information, including road boundaries, road markings, and road cracks, provides significant guidance or warning to all road users. Recently, the on-road information extraction from LiDAR data have been widely studied. However, for the LiDAR data with lower accuracy and higher noise, some detailed information, such as road boundary, is difficult to be extracted correctly. Furthermore, most of previous studies lack an exploration of efficiently extracting multiple on-road information from a single framework. In this paper, we propose a new framework that can simultaneously extract multiple on-road information from high accuracy LiDAR data and can also more robustly extract detailed road boundaries from low accuracy LiDAR data. First, we propose a Curb-Aware Ground Filter to extract ground points with rich curb structure features. Second, we transform the vertical density, elevation gradient and intensity features of the ground points into multiple feature maps and extract multiple on-road information from the feature maps by employing a semantic segmentation network. Experimental results on three datasets with different data accuracy demonstrate that our method outperforms other recent competitive methods.

In this paper, we present a publicly available benchmark dataset on multisensorial indoor mapping and positioning (MiMAP), which is sponsored by ISPRS scientific initiatives. The benchmark dataset includes point clouds captured by an indoor mobile laser scanning system in indoor environments of various complexity. The benchmark aims to stimulate and promote research in the following three fields: (1) LiDAR-based Simultaneous Localization and Mapping (SLAM); (2) automated Building Information Model (BIM) feature extraction; and (3) multisensory indoor positioning. The MiMAP project provides a common framework for the evaluation and comparison of LiDAR-based SLAM, BIM feature extraction, and smartphone-based indoor positioning methods. This paper describes the multisensory setup, data acquisition process, data description, challenges, and evaluation metrics included in the MiMAP project.

Columnar apple is a valuable resource for genetic improvement of cultivated apples due to its special tree architecture. Strigolactones (SLs) are a novel class of plant hormones controlling shoot branching. The content of SLs is higher in columnar apple than in standard apples. In this study, the members of major gene families involved in SLs biosynthesis and signaling were identified from apple genomic sequences and their expression profiles were characterized in columnar and standard apples using reverse transcription quantitative polymerase chain reactions. In comparison with standard apple, the higher expressions of MORE AXILLARY GROWTH genes MdMAX3-1 and MdMAX4-4 were detected in both buds and shoots of columnar apple but the expression of DWARF gene MdD53-4 showed a lower expression in columnar apple. Overexpression of Columnar gene MdCo31 in tobacco increased SLs content and weakened the inhibition of SLs signal transduction by increasing expression of MAX3 and down-regulating the transcription of D53. Thus MdCo31 could be a strong candidate gene for the control of columnar habit.

ABSTRACT: This study aimed to investigate the age-related changes of hepatic metabolism and antioxidant capacity of laying hens at 3 different ages. A total of 192 Hy-line Brown laying hens were assigned into 3 groups: 1) 195-day-old (D195 group); 2) 340-day-old (D340 group); 3) 525-day-old (D525 group). Each group replicated 8 times with 8 hens at the same age. Higher activity of aspartate aminotransferase and lower contents of total protein and globulin were observed in the serum of 525-day-old hens in comparison with their 195-day-old counterparts (P < 0.05). The 525-day-old hens accumulated higher contents of total cholesterol and triglyceride in the liver than 195-day-old birds. Additionally, compared with hens from D195 or D340 group, 525-day-old birds exhibited a lower circulating estradiol level (P < 0.05). For antioxidant capacity, birds in the D525 group showed a higher malondialdehyde concentration in both serum and liver as compared with D195 or D340 group (P < 0.05). The 525-day-old hens also exhibited lower glutathione peroxidase activities in both serum and liver when compared with 195-day-old birds (P < 0.05). Simultaneously, there was a decline of hepatic superoxide dismutase activity in the D525 group in comparison with D195 group (P < 0.05). Compared with 195-day-old counterparts, 340-day-old birds upregulated the mRNA abundance of nuclear factor erythroid-2 related factor 2 and glutathione peroxidase 1 in the liver (P < 0.05). In contrast, hens from D525 group showed the downregulation of hepatic nuclear factor erythroid-2 related factor 2, NAD(P)H quinone dehydrogenase 1, and superoxide dismutase 1 when compared with D340 group (P < 0.05). These results indicated that increasing age can adversely affect liver metabolism and function of laying hens.

This paper presents the design of the benchmark dataset on multisensory indoor mapping and position (MIMAP) which is sponsored by ISPRS scientific initiatives. The benchmark dataset including point clouds captured by indoor mobile laser scanning system (IMLS) in indoor environments of various complexity. The benchmark aims to stimulate and promote research in the following three fields: (1) SLAM-based indoor point cloud generation; (2) automated BIM feature extraction from point clouds, with an emphasis on the elements, such as floors, walls, ceilings, doors, windows, stairs, lamps, switches, air outlets, that are involved in building management and navigation tasks ; and (3) low-cost multisensory indoor positioning, focusing on the smartphone platform solution. MIMAP provides a common framework for the evaluation and comparison of LiDAR-based SLAM, BIM feature extraction, and smartphone indoor positioning methods.

Most existing lidar odometry estimation strategies are formulated under a standard framework that includes feature selection, and pose estimation through feature matching. In this work, we present a novel pipeline called LO-Net for lidar odometry estimation from 3D lidar scanning data using deep convolutional networks. The network is trained in an end-to-end manner, it infers 6-DoF poses from the encoded sequential lidar data. Based on the new designed mask-weighted geometric constraint loss, the network automatically learns effective feature representation for the lidar odometry estimation problem, and implicitly exploits the sequential dependencies and dynamics. Experiments on benchmark datasets demonstrate that LO-Net has similar accuracy with the geometry-based approach.

This paper presents a deep learning feature-based method for registration of indoor mobile LiDAR data. Our method is to input point cloud directly, which is more robust to noise than traditional algorithms. The proposed method involves three steps. We first extract the key points by Harris3D algorithm and get their local patches by our sampling method. Second, a Siamese network is trained to describe the patches as local descriptors. Finally, we obtain the final matching pairs depends on the distance which is between two descriptors, and then solve the transformation matrix. The accuracy of registration is within 6 cm when the overlap is greater than 35%. In order to improve the registration accuracy, the ICP algorithm is used to fine-tuning the registration results. And the final registration accuracy is within 3.5 cm. The experiments show that our method applied to the registration of indoor mobile LiDAR data robustly and accurately.

An overall reduction factor (ORF) is introduced for studying the quenching of single-particle strengths through nucleon transfer reactions. The ORF includes contributions of all the probed bound states of the residual nucleus in a transfer reaction and permits a proper comparison with results of inclusive knockout reactions. A systematic analysis is made with 103 sets of angular distribution data of (p,d) reactions on 21 even–even targets with atomic mass numbers from 8 to 56 using the consistent three-body model reaction methodology proposed in Lee et al. (2006) [25]. The extracted ORFs are found to be nearly independent on the proton–neutron asymmetry, which is different from the systematics of inclusive knockout reactions but is consistent with the recent measurement of (d,t), (d,He3), (p,2p), and (p,pn) reactions on nitrogen and oxygen isotopes and ab initio calculations. Keywords: (p,d) reactions, Spectroscopic factors, Quenching factors, Reduced single-particle strength

Intestinal integrity, digestive enzyme activity, nutrient utilization, and egg quality of laying hens at different ages were evaluated and compared in this study. A total of 192 Hy-line Brown laying hens at 195-d-old (D195 group), 340-d-old (D340 group), and 525-d-old (D525 group) were allocated into one of 3 groups in accordance with their ages. Each group had 8 replicates of 8 birds each, and all birds were fed a maize-soybean meal basal diet for a 2-wk experiment. Compared with the D195 group, intestinal villus height and ratio of villus height to crypt depth, as well as serum D-lactate content increased in the D525 group (P

Objectives: By deploying a novel combination of machine learning approaches, we aim to investigate the contributions of each local and systemic risk factors in multi-etiology of knee osteoarthritis (KOA) to disease onset and deterioration. Methods: A machine-learning-based KOA progression prediction model is developed using the data from the National Institute of Health Osteoarthritis Biomarkers Consortium. According to Kellgren-Lawrence (KL) grade of plain radiographs at baseline, the subjects are divided into either KOA onset or deterioration study groups. The disease progression is defined as the changes in both joint space width (JSW) and WOMAC pain score. In addition to radiographic and symptomatic data, the anthropological particulars, history of the knee injury and surgery, metabolic syndrome and living habits were deployed in a multi-layer perceptron (MLP) to predict disease progression in each study group. The relative contributions of each risk factors were weighted via DeepLIFT gradient. Additionally, statistical interactions among risk factors were identified compared. Results: Our model achieved AUC of 0.843 (95% CI 0.824, 0.862) and 0.765 (95% CI 0.756, 0.774) in prediction of KOA onset and deterioration, respectively. For KOA onset prediction, history of injury has attained the highest DeepLIFT gradient except medial joint space narrowing; while for KOA deterioration prediction, diabetes and habit of smoking obtained second and third highest gradients respectively aside from medial joint space narrowing, surpassing the impact of the injury. Conclusion: We developed a machine learning workflow which effectively dissects the risk factors’ contributions and their mutual interactions for onset and deterioration of KOA respectively.

Indoor 3D mapping provides a useful three-dimensional structure via an indoor map for many applications. To acquire highly efficient and relatively accurate mapping for large-scale GPS/GNSS-denied scene, we present an upgraded backpacked laser scanning system and a car-mounted indoor mobile laser scanning system. The systems provide both 3D laser scanning point cloud and camera images. In this paper, a simultaneous extrinsic calibration approach for multiple multi-beam LIDAR and multiple cameras is also proposed using the Simultaneous Localization and Mapping (SLAM)-based algorithm. The proposed approach uses the SLAM-based algorithm to achieve a large calibration scene using mobile platforms, registers an acquired multi-beam LIDAR point cloud to the terrestrial LIDAR point cloud to acquire denser points for corner feature extraction, and finally achieves simultaneous calibration. With the proposed mapping and calibration algorithms, we can provide centimetre-lever coloured point cloud with relatively high efficiency and accuracy.

A new 11Be(d,p)12Be transfer reaction experiment was carried out in inverse kinematics at 26.9A MeV, with special efforts devoted to the determination of the deuteron target thickness and of the required optical potentials from the present elastic scattering data. In addition a direct measurement of the cross section for the 02+ state was realized by applying an isomer-tagging technique. The s-wave spectroscopic factors of 0.20−0.04+0.03 and 0.41−0.11+0.11 were extracted for the 01+ and 02+ states, respectively, in 12Be. Using the ratio of these spectroscopic factors, together with the previously reported results for the p-wave components, the single-particle component intensities in the bound 0+ states of 12Be were deduced, allowing a direct comparison with the theoretical predictions. It is evidenced that the ground-state configuration of 12Be is dominated by the d-wave intruder, exhibiting a dramatic evolution of the intruding mechanism from 11Be to 12Be, with a persistence of the N=8 magic number broken. Keywords: Transfer reaction, 12Be, Intruder configuration

In order to perform precise identification and location of artificial coded targets in natural scenes, a novel design of circle-based coded target and the corresponding coarse-fine extraction algorithm are presented. The designed target separates the target box and coding box totally and owns an advantage of rotation invariance. Based on the original target, templates are prepared by three geometric transformations and are used as the input of shape-based template matching. Finally, region growing and parity check methods are used to extract the coded targets as final results. No human involvement is required except for the preparation of templates and adjustment of thresholds in the beginning, which is conducive to the automation of close-range photogrammetry. The experimental results show that the proposed recognition method for the designed coded target is robust and accurate.

This study was conducted to investigate effects of heat-oxidized soy protein isolate (HSPI) on growth performance, serum biochemical indices, apparent nutrient digestibility and digestive function of broiler chickens. A total of 320 1-day-old Arbor Acres chicks were randomly divided into 4 groups with 8 replicates of 10 birds, receiving diets containing soy protein isolate (SPI, control group) or the same amount of SPI heated in an oven at 100°C for 1, 4, or 8 h, for 21 days, respectively. The results indicated that compared with the control group, body weight gain and feed intake of birds fed diet containing SPI heated for 8 h were significantly lower (p

Point clouds acquired by RGB-D camera-based indoor mobile mapping system suffer the problems of being noisy, exhibiting an uneven distribution, and incompleteness, which are the problems that introduce difficulties for point cloud planar surface segmentation. This paper presents a novel color-enhanced hybrid planar surface segmentation model for RGB-D camera-based indoor mobile mapping point clouds based on region growing method, and the model specially addresses the planar surface extraction task over point cloud according to the noisy and incomplete indoor mobile mapping point clouds. The proposed model combines the color moments features with the curvature feature to select the seed points better. Additionally, a more robust growing criteria based on the hybrid features is developed to avoid the generation of excessive over-segmentation debris. A segmentation evaluation process with a small set of labeled segmented data is used to determine the optimal hybrid weight. Several comparative experiments were conducted to evaluate the segmentation model, and the experimental results demonstrate the effectiveness and efficiency of the proposed hybrid segmentation method for indoor mobile mapping three-dimensional (3D) point cloud data.

The stacking faults (SFs) in an AlSb/GaAs (001) interface were investigated using a 300 kV spherical aberration-corrected high-resolution transmission electron microscope (HRTEM). The structure and strain distribution of the single and intersecting (V-shaped) SFs associated with partial dislocations (PDs) were characterized by the [110] HRTEM images and geometric phase analysis, respectively. In the biaxial strain maps εxx and εyy, a SF can be divided into several sections under different strain states (positive or negative strain values). Furthermore, the strain state for the same section of a SF is in contrast to each other in εxx and εyy strain maps. The modification in the strain states was attributed to the variation in the local atomic displacements for the SF in the AlSb film on the GaAs substrate recorded in the lattice image. Finally, the single SF was found to be bounded by two 30° PDs. A pair of 30° PDs near the heteroepitaxial interface reacted to form a Lomer-Cottrell sessile dislocation located at the vertices of V-shaped SFs with opposite screw components. The roles of misfit dislocations, such as the PDs, in strain relaxation were also discussed.

Dideoxy fingerprinting (ddF) was used as a tool to search for a generic set of conditions with sufficient power to detect virtually all mutations. For each condition tested, a very large sample of mutation-containing, single-stranded segments (about 1500) were analyzed with ddF. Correlation coefficients identified pairs of conditions in which single-strand conformation polymorphism (SSCP) mobilities were poorly correlated. The data strongly suggest that tertiary structure (e.g., base-sugar and sugar-sugar interactions) rather than secondary structure is the predominant determinant of mobility shifts by SSCP. Five conditions were selected with sufficient redundancy to detect all the mutations. The sensitivity of detection of virtually all mutations-SSCP (DOVAM-S) was determined by blinded analyses on samples containing additional mutations scattered throughout the eight exons and splice junctions in the factor IX gene. The factor IX gene sequence (2.5 kb) was scanned in one lane by 15 PCR-amplified segments (125 kb of sequence scanned per gel). All of the 84 single-base substitutions were detected in the blinded analyses, the first consisting of 50 hemizygous mutant and wild-type (WT) samples and the second consisting of 50 heterozygous mutant and WT samples. DOVAM-S is estimated to be five times faster than fluorescent DNA sequencing for the detection of virtually all mutations when the five conditions are applied.

The ForMAX beamline at the MAX IV Laboratory provides multiscale and multimodal structural characterization of hierarchical materials in the nanometre to millimetre range by combining small- and wide-angle X-ray scattering with full-field microtomography. The modular design of the beamline is optimized for easy switching between different experimental modalities. The beamline has a special focus on the development of novel fibrous materials from forest resources, but it is also well suited for studies within, for example, food science and biomedical research.