Effects of Manganese Hydroxychloride on Growth Performance, Antioxidant Capacity, Tibia Parameters and Manganese Deposition of Broilers

This study was conducted to investigate the effects of dietary supplementation with manganese hydroxychloride (MHC) on production performance, antioxidant capacity, tibial quality, and manganese (Mn) deposition of broilers. A total of 756 one-day-old male Arbor Acres broilers were randomly allotted to 7 treatments of 6 replicates with 18 broilers per replicate. Broilers were fed corn-soybean meal basal diets supplemented of 100 mg/kg Mn as Mn sulfate (MnSO4), or 0, 20, 40, 60, 80, 100 mg/kg Mn as MHC for 42 days. The growth performance of broilers was not affected by dietary MnSO4 or MHC (p > 0.05), whereas the dressing percentage increased linearly (p < 0.05) with increasing of dietary MHC addition level. The activities of catalase (CAT) and manganese superoxide dismutase (MnSOD), and total antioxidant capability (T-AOC) in serum and liver on day 42 increased linearly (p < 0.05) with increasing of dietary MHC level, while malondialdehyde (MDA) concentration reduced linearly (p < 0.05). The length, strength, and density index of tibia increased linearly (p < 0.05) on day 21 as MHC supplementation level increased; there were no differences between MnSO4 group and 40–100 mg/kg Mn as MHC groups in tibial parameters of broilers (p > 0.05). As supplemental MHC levels increased, the Mn contents in heart, liver, kidney, and tibia increased linearly on day 42 (p < 0.05). In summary, dietary supplementation with MHC improved antioxidant capacity, bone quality, and Mn contents in broilers, but no effects on growth performance were detected. Based on the results of this study, dietary inclusion of 50–90 mg/kg Mn in the form of MHC to broilers is recommended.

Linking Microstructural Integrity and Motor Cortex Excitability in Multiple Sclerosis

Motor skills are frequently impaired in multiple sclerosis (MS) patients following grey and white matter damage with cortical excitability abnormalities. We applied advanced diffusion imaging with 3T magnetic resonance tomography for neurite orientation dispersion and density imaging (NODDI), as well as diffusion tensor imaging (DTI) in 50 MS patients and 49 age-matched healthy controls to quantify microstructural integrity of the motor system. To assess excitability, we determined resting motor thresholds using non-invasive transcranial magnetic stimulation. As measures of cognitive-motor performance, we conducted neuropsychological assessments including the Nine-Hole Peg Test, Trail Making Test part A and B (TMT-A and TMT-B) and the Symbol Digit Modalities Test (SDMT). Patients were evaluated clinically including assessments with the Expanded Disability Status Scale. A hierarchical regression model revealed that lower neurite density index (NDI) in primary motor cortex, suggestive for axonal loss in the grey matter, predicted higher motor thresholds, i.e. reduced excitability in MS patients (p = .009, adjusted r² = 0.117). Furthermore, lower NDI was indicative of decreased cognitive-motor performance (p = .007, adjusted r² = .142 for TMT-A; p = .009, adjusted r² = .129 for TMT-B; p = .006, adjusted r² = .142 for SDMT). Motor WM tracts of patients were characterized by overlapping clusters of lowered NDI (p &lt;.05, Cohen’s d = 0.367) and DTI-based fractional anisotropy (FA) (p &lt;.05, Cohen’s d = 0.300), with NDI exclusively detecting a higher amount of abnormally appearing voxels. Further, orientation dispersion index of motor tracts was increased in patients compared to controls, suggesting a decreased fiber coherence (p &lt;.05, Cohen’s d = 0.232). This study establishes a link between microstructural characteristics and excitability of neural tissue, as well as cognitive-motor performance in multiple sclerosis. We further demonstrate that the NODDI parameters neurite density index and orientation dispersion index detect a larger amount of abnormally appearing voxels in patients compared to healthy controls, as opposed to the classical DTI parameter FA. Our work outlines the potential for microstructure imaging using advanced biophysical models to forecast excitability alterations in neuroinflammation.

A PARALLEL ALGORITHM FOR LOCAL POINT DENSITY INDEX COMPUTATION OF LARGE POINT CLOUDS

Point density is an important property that dictates the usability of a point cloud data set. This paper introduces an efficient, scalable, parallel algorithm for computing the local point density index, a sophisticated point cloud density metric. Computing the local point density index is non-trivial, because this computation involves a neighbour search that is required for each, individual point in the potentially large, input point cloud. Most existing algorithms and software are incapable of computing point density at scale. Therefore, the algorithm introduced in this paper aims to address both the needed computational efficiency and scalability for considering this factor in large, modern point clouds such as those collected in national or regional scans. The proposed algorithm is composed of two stages. In stage 1, a point-level, parallel processing step is performed to partition an unstructured input point cloud into partially overlapping, buffered tiles. A buffer is provided around each tile so that the data partitioning does not introduce spatial discontinuity into the final results. In stage 2, the buffered tiles are distributed to different processors for computing the local point density index in parallel. That tile-level parallel processing step is performed using a conventional algorithm with an R-tree data structure. While straight-forward, the proposed algorithm is efficient and particularly suitable for processing large point clouds. Experiments conducted using a 1.4 billion point data set acquired over part of Dublin, Ireland demonstrated an efficiency factor of up to 14.8/16. More specifically, the computational time was reduced by 14.8 times when the number of processes (i.e. executors) increased by 16 times. Computing the local point density index for the 1.4 billion point data set took just over 5 minutes with 16 executors and 8 cores per executor. The reduction in computational time was nearly 70 times compared to the 6 hours required without parallelism.

Validation and optimization of a new instrument for measuring the performances of ultrafiltration membranes

In this study, we introduce the current situation of the membrane inspection industry. We have developed a new integrated rapid membrane inspection machine (MIM) to test the performances of nanofiltration or ultrafiltration membranes by measuring Silt Density Index (SDI) value (i.e., the key performance indicator) of the water filtered. This study optimizes many key conditions include temperature, pH value and pressures, then establishes an SDI detection new method of ultrafiltration membranes by using MIM. We set the temperature of the test liquid to 25 °C, pH in the range of 7–8, and pressure to approximately 0.10 MPa. The results reflect that MIM can be used to effectively determine the SDI of ultrafiltration membranes used the new method and the results of the method validation are satisfactory.

Abnormal Neurite Density and Orientation Dispersion in Frontal Lobe Link to Elevated Hyperactive/Impulsive Behaviors in Young Adults with Traumatic Brain Injury

Traumatic brain injury is a major public health concern. A significant proportion of individuals experience post-traumatic brain injury behavioral impairments, especially in attention and inhibitory control domains. Traditional diffusion-weighted MRI techniques, such as diffusion tensor imaging, have provided tools to assess white matter structural disruptions reflecting the long-term brain tissue alterations associated with traumatic brain injury. The recently developed neurite orientation dispersion and density imaging is a more advanced diffusion-weighted MRI modality, which provides more refined characterization of brain tissue microstructures by assessing the neurite orientation dispersion and neurite density properties. In this study, we investigated the morphometrical and microstructural alterations at chronic brain injury stage and their relationships with the functional outcomes. Neurite orientation dispersion and density imaging data from 44 young adults with chronic traumatic brain injury (ranging from 18 - 27 years of age; 23 males/21 females) who had no prior-traumatic brain injury history of attention deficits and/or hyperactivity and 45 group-matched normal controls (23 males /22 females) were collected. Maps of fractional anisotropy, neurite orientation dispersion index, and neurite density index were calculated. Vertex-wise and voxel-wise analyses were conducted for gray matter and white matter, respectively. Post-hoc region of interest-based analyses were also performed. Compared to the controls, the group of traumatic brain injury showed significantly increased orientation dispersion index in various gray matter regions and significantly decreased orientation dispersion index in several white matter regions. Brain-behavioral association analyses indicated that the reduced neurite density index of left precentral gyrus and the reduced orientation dispersion index of left superior longitudinal fasciculus were significantly associated with elevated hyperactive/impulsive symptoms in the patients with traumatic brain injury. These findings suggest that traumatic brain injury-induced chronic neurite orientation dispersion alterations of left superior longitudinal fasciculus and left precentral may significantly contribute to post-traumatic brain injury hyperactive/impulsive behaviors in young adults with traumatic brain injury.

Evaluation of small-strain shear modulus of Fontainebleau sand based on innovative pressuremeter probe testing in a calibration chamber

This paper presents an experimental study aimed at evaluating the measuring capabilities of an innovative monocellular pressuremeter probe, the Monocell Francis Cour® probe, based on calibration testing in the laboratory. The originality of the tested equipment is to allow to evaluate soil properties in both small and large strain domains, without the need of sophisticated punctual displacement measuring arms. This paper focuses on the evaluation of small strain shear modulus G of Fontainebleau sand, NE34, based on tests carried out with this specific pressuremeter probe. Shear modulus values obtained with this probe are then compared with values resulting from more classical elementary tests, showing a fairly good consistency. It is shown, with satisfactory agreement, that it is possible to quantify the influence of the density index of the sand as well as the influence of the mean effective stress around the probe on the shear modulus, based on the analysis of specific unload-reload loops performed during the test. The experimental programme carried out under well-controlled laboratory conditions allows to propose a validation of a method of identification of the shear modulus of sand at small strain levels using this prototype pressuremeter

Innovative approach to evaluate the wearing of nano TiO2 doped alumina ceramics in the light of image modelling

The present research is emphasized on the microscopic observation of post wear surface of nano TiO2 doped alumina ceramics to accesses wearing by promising image processing algorithms viz. entropy analysis, Sobel edge detection technique and entropy filtered image histogram analysis in relation to the extent of doping. The experimental results of specific wear rate showed an indicator with the extent of micro fracturing of grains, ploughing of materials and debris formation on the wear track after a long wear cycles in terms of entropy level, edge density index, entropy filtered image and the nature of histogram at different doping level. The lowest value of entropy level and edge density index is shown at the level of 1 wt.% TiO2 doped alumina ceramics due to the presence of low number of granularity and microfracture grains on the wear track causes the lowering of specific wear rate. The histogram of entropy filtered image for 1 wt.% doping is more uniformly distributed with the highest frequency and lowest skewness factor over a wide range of intensity values for 1 wt.% doping.

Diversity of Bivalvia, Gastropoda and Holothuroidea in Intertidal Zone of North Javan Sea Coastal, Indonesia

This study aims to know diversity of Bivalvia, Gastropoda and Holothuroidea. Measures used in this study were Density Index (D), Diversity Index (H’), Evennes Index (E’) dan Important Value Index (INP). This study used transect sampling method by 1 × 1 meter quadrant. Target species of this study were member of Bivalvia, Gastropoda and Holothuroidea that inhabit in intertidal zone of north Javan Sea coastal. This intertidal zone was divided into 3 zone; zone I is 50 meter, zone II is 75 meter and zone III is 100 meter from coastal line to sea. Total sample of this species were 1064 individual, that divided into 7 species of Bivalvia, 10 species of Gastropoda and 2 spesies of Holothuridea. The highest Diversity Index was for Gastropoda in zone I (253 individual/m2). Diversity Index was in moderate category (1< H’ < 2) while the zone III was the highest. Evennes Index of all zones were relatively similar. The highest Important Value Index was species of Clypeomorus clypeomorus, that has value 53,06%.