Miracle-dz/UniFAR-FTUs huggingface dataset:
A Qualitative Study on the Relationship Between Cavitation Structure and Erosion Region around a 3D Twisted Hydrofoil by Painting Method

Cavitation erosion usually can be seen on shaft brackets and rudders of ships, which is generally considered to be related to cloud cavitation that contains high erosive potential. However, little has been known about the relationship between the cavitaton structure and erosion region. In this paper, a 3D twisted hydrofoil was selected to investigate the relationship between cloud cavitation resulting from the shedding of sheet cavitation and its reduced erosion region qualitatively by painting method in a cavitation tunnel. The erosion region was evaluated with the extent of paint loss, and the structure of cloud cavitation was recorded by high speed cameras. The results showed that the unsteady part of cavitation sheet might be the most erosive structure in the process of cloud cavitation evolution, and U-shaped vortex structure could also be erosive but causes much less damage. In the end, three role of U-shaped vortex in erosion were proposed.
Beam Allocation based on Spatial Compatibility for Hybrid Beamforming C-RAN Networks

In this work, we consider a beam allocation problem in hybrid beamforming (HBF) cloud radio access networks (C-RANs) to maximize the sum rate. The problem considers a codebook-based analog beamforming performed at the remote radio head (RRH) and digital beamforming at the baseband unit (BBU). Differently from previous works, we assume that a given user equipment (UE) can be served by multiple beams, without being specifically associated to a given RRH. Due to the relation between the analog beam allocation and the digital beamforming, we consider a new metric based on channel correlation and channel attenuation for the analog beamforming solution. The metric measures the spatial compatibility in order to improve the spectral efficiency before the digital beamforming solution. In order to evaluate the proposed metric we present a low-complexity greedy algorithm, which is shown to provide a reasonable performance/complexity trade-off.
Glimpsed periodicity features and recursive Bayesian estimation for modeling attentive voice tracking

Computational models are a way of approaching research questions related to auditory perception. One relevant question is how we are able to follow and understand speech in complex acoustic scenes. Previous studies suggest that for tracking a speaker in such conditions, humans use (1) sparse, speaker-related bits of robust information - ’auditory glimpses’ and (2) a mechanism of predictive coding with a movable locus of attention. The goal of the present study is to develop a computational model for attentive tracking of voices, which takes these two aspects into account. We model auditory glimpses using Glimpsed Periodicity Features and predictive coding using Recursive Bayesian Estimation. We assume that perception is organized into an attended foreground and unattended background. We propose parallel particle ﬁlters - one for each category - to track the concurrent events. In this approach, each incoming glimpse is associated with either foreground or background based on accumulated evidence. Simulations with artiﬁcially generated data of a ’glimpsing’ nature (sparse, robust) showed that this approach is suitable to track multidimensional parameter trajectories of two competing sources. This suggests the potential of the method to track simultaneously active voices based on the Glimpsed Periodicity Features.
3D shape and full-field strain measurement in a coronary artery using 3D-DIC

In the present work, three dimensional digital image correlation (3D-DIC) has been investigated to reconstruct the 3D shape and full-field strain of a porcine coronary artery. Methylene blue has been applied for the first time to a coronary artery surface to enhance the contrast of the speckle pattern and reduce reflection issues common with soft tissue and cylindrical geometries. The mean uncertainty of DIC strain measurements evaluated under rigid body motion (RBM) conditions were less than 0.7%, with a standard deviation ~ 3%. This demonstrates potential of this approach to measure large deformations of arterial tissues at small length scales.
Chubby Children: The Role of Social Norms on Parents Food Choices

The prevalence of childhood overweight and obesity is high in urban Vietnam. Understanding parents' perceptions on child weight and food choices may help to understand this high prevalence. The goal of this study was to examine and compare parents’ perception of a child’s weight, and the effect of unhealthy social norms on food choices. The first study (n = 342), assessed the perceptions on child weight using a pictorial vignette. Participants were asked to respond to a situation illustrated in a vignette by stating how they imagine a third person would react. In the second study (n = 330), participants were exposed to either a social norm message (e.g. “Did you know that some Vietnamese mothers prefer chubbier kids? ”), and/or a health message (e.g. “Did you know that 33.7% of the primary school children are overweight, which can profoundly affect children's physical health”). Following the message, participants were asked to divide vouchers between snacks they would purchase for their children. Effects of these messages on food choice were compared against each other and a no-message control condition. Overall, the study included 345 parents of first graders from three schools in Dong Anh district. These three schools were randomly selected out of 12 schools that were part of an overarching project. In each of these three schools, four classes were selected to be in the sample. The results did not reveal differences in the perception of parents between a healthy weight and a chubby weight child. Apparently, these parents did not perceive chubbier children as differently as previous research might have caused us to expect. The results also showed no effect of the messages on parents’ food selection. Further testing of the effectiveness of such messages is advised to discover how to make effective interventions targeting food choices as emphasizing these message alone are not sufficient to shift behavior. The implication of these findings concerning theory and practice, and suggestions for improvements of future studies are also
Relationships between the methods of problem solving ( retrieval , discovery , or search ) and the kinds of acquired problem solving skills

There are three methods for deriving a solution for a problem with which a person is facing, which are 1) retrieval of an existing solution from his/her own memory or from available external resources including human resources, digital resources, 2) clarifying the constraints to meet and discovering a solution that should satisfy them by exploring the problem space, or 3) deriving a solution by applying inference rules successively until the goal state is achieved. This paper describes the distinctive cognitive processes that respective methods should follow when deriving a solution. On the assumption that the ultimately needed problem solving skill would be the one which makes a person solve any problem by himself or herself without reliance on any external resources other than himself/herself, this paper discusses the implications of the respective methods of problem solving to acquiring the required problem solving skill. 概要:直面している課題に対する解決策は質的に異なる3つの方法で得ようとすることができる。 1) 既に存在している解決策を検索する(自分の記憶の利用、または、他の情報を利用)2)解が満たす べき制約を明らかにして、制約を満たす解を発見する、3)現状に対して手続き的知識を連鎖的に適 用し解状態に到達する。 これらの方法は異なった認知プロセスを伴うので、認知プロセスを動かすこ とによって獲得される知識やメタ認知スキルも異なる。 本稿では、人間の記憶と行動選択プロセスに 関する理論に基づいて、上記の3つの課題解決方法の特徴を、究極的に求められている自分自身の力 のみで課題に立ち向かうことを可能とする「問題解決」能力の視点から、教育現場での実践の可能性
A DATA AUTHENTICATION SOLUTION OF ADS-B SYSTEM BASED ON X.509 CERTIFICATE

A major characteristic of Automatic Dependent Surveillance Broadcast (ADS-B) technology is to broadcast the sender’s location data periodically. It leads to several severe security problems respectively, such as data spoofing which has not been solved perfectly. A solution to the problem of data authentication of ADS-B systems based on the ECC and X.509 certificate is proposed in this paper, which may avoid the key distribution problems combined with the symmetric key algorithm, preventing ADS-B data spoofing thoroughly.
A Study of Fluid Flow and Heat Transfer in a Liquid Metal in a Backward-Facing Step under Combined Electric and Magnetic Fields

This study used COMSOL Multiphysics as the analytical tool to investigate the effect of applied magnetic and electric fields on the flow phenomena of an electrically conducting fluid in a backward step configuration. The magnetohydrodynamic (MHD) approach was validated by comparison with the existing solution for the Hartmann problem while the back step flow was validated by comparison with previously obtained solutions. The implementation of the magnetic and electric field has significant impact on the effective Reynolds number and thus leads to changes in the separation and reattachment point downstream the step. Depending on the strength of the fields, the recirculation regions downstream could become smaller/vanish due to the change in the pressure and velocity distribution. In addition, this change in the velocity profile due to the MHD effect in a back-step flow also affects the heat transfer mechanism in the flow since convection is very dependent on the velocity distribution.
Where you are is what you are

Comment on Hardtke et al, page [1924][1] In this issue, Hardtke and colleagues conclusively demonstrate that expression on T cells of the B-cell–associated chemokine receptor, CXCR5, is essential for migration into B follicles (follicular B helper T cells [TFH]) and, further, that T cells are
Water, sanitation and hygiene partners collaborating to combat severe cholera outbreaks during the State of Emergency in Zimbabwe

This paper aims to understand the value of collaboration in a ‘state of emergency’ situation, featuring the case of the water, sanitation and hygiene (WASH) sector in Zimbabwe over the period 2008–2012. During this period, a group of stakeholders engaged in a structured collaboration, called the WASH cluster. This initiative was taken to respond to severe and frequent cholera outbreaks. Over these 5 years, the collaborating partners engaged in a voluntary partnership, which attracted attention due to the ascribed improvements of some key health indicators. Drawing from the body of literature on collaboration, the research confirms the applicability of findings on both the process and key features of successful collaboration and was able to position the evolution of the Zimbabwean case in the continuum of collaboration arrangements proposed in the literature. Likewise, the specific sequencing and causality of steps in the creation and development of the Zimbabwean WASH cluster were found to match those of the collaborative pathway. Finally, the findings confirm the general applicability of principles of collaboration, although the evaluation of its outcomes poses challenges. In addition, the research found that inasmuch as prominent leaders enhance collaboration, leadership by permanent government bodies promotes sustainability of the collaborative approach.
Object Recognition and Positioning with the Kinect Camera

Robocup Middle Size League (MSL) is an international robot competition, in which 5 robots play soccer like human beings. This project is based on the hardware platform (TURTLE) which is currently used by Tech United MSL team. Before this project, the Kinect camera from Microsoft was used solely for detection of a standard yellow ball, and this was done using color segmentation and blob detection techniques. The intention for this project is to develop a new algorithm to improve the performance and functionality of the Kinect camera. A framework of object recognition and positioning is proposed in this report, with combining the color image and the depth image in a proper designed way, to achieve real-time object recognition and positioning task. The algorithm designed in this project focuses on peer robot detection and positioning, but if needed, in principle any object can be added into this framework. This algorithm first detects candidate objects in the depth image, after which they are mapped onto the corresponding color image, where high quality texture information exists. On the extracted color image, a trained Cascade AdaBoost classifier is applied to verify the candidate objects. This algorithm can run in a efficient way. On NVidia Jetson TK1 board, it can obtain the frequency of 28 Hz (the highest record, with detecting arbitrarily number of peer robots). Object Recognition and Positioning with the Kinect Camera iii
AFFECTING EACH OF RIDGER FURROW OPENER PARAMETERS AND PLANTING METHODS ON WATER USE EFFICENCY AND SUGAR BEET YIELD

Design parameters of the ridger furrow opener directly affecting the furrow profile characteristics and the amount of applied water. Furrow-bed irrigation technique is usually used for water conservation, efficient fertilizer use and many other benefits. This study is to evaluate the impact of design parameters of the ridger furrow opener and planting methods on sugar beet yield and water use efficiency. Therefore, field experiments are conducted to (i) investigate the effects of share rake angles (20 o , 25 o and 30 o ), opener wing angles (35 o and 45 o ) and wing shape configurations (straight and curved) on the furrow profile characteristics, transverse scattering, draft force, and (ii) evaluate planting methods (i.e. ridges with 50 cm rows spacing and pair of rows on bed with 30, 35 and 40 cm rows spacing), the wing shape and angles on the emergence, sugar percentage, root and sugar yield, applied water and water use efficiency. The results showed that the curved shape and the wing angle of 45 o produced wider furrows than those produced by the straight shape and 35 o wing angle. Minimum transverse scattering is associated with the curved wing, wing angle of 35 o and share rake angle of 20 o . Increasing the share rake and wing angles increased the required draft force. The highest average values of root and sugar yields have been achieved at beet planting in beds with 30 cm rows spacing flowed by beds with 35 and 40 cm rows spacing, respectively. The lowest value of the water use efficiency is achieved at planting on ridges compared to the other planting methods. The maximum emergence percentage, root and sugar yields, sugar percentage and water use efficiency are associated with a wing angle of 45 o and the curved wing shape.
Novel antioxidant production by Cladophora sp . and Spirogyra sp

Reactive oxygen species (ROS), such as the superoxide anion, hydroxyl radicals, and hydrogen peroxide, cause lipid oxidation and thereby decrease the nutritional value and appearance of food Cladophora sp is one of the largest filamentous green alga commonly available in the ponds of Puri district, Odisha. The antioxidant activities of Cladophora sp and Spirogyra sp. were measured by free radical scavenging assays. The study aimed at assaying the antioxidant activities both the species. of Puri distict, Odisha. The antioxidant activity of the extracts was investigated including the total phenolic contents). IC for the DPPH radical scavenging activity was 920 ± 42 μg ml-1. The IC values for ascorbic acid, quercetin and BHA were 5.05 ± 0.1, 5.28 ± 0.2 and 53.96 ± 3.1 μg ml-1, respectively. Phenol and flavonoid contents of this alga may have led to its good DPPH-scavenging activity. These results indicate that further investigation is needed to identify and purify the responsible antioxidative components. The present study confirms the production of antioxidants from cladophora sp. And Spirogyra sp. of Puri District,Odisha state and suggests that two species constitute a potential source for producing antioxidant. Hence cladophora sp and Spirogyra sp. can be used as a novel source of natural antioxidant agents for pharmaceutical industries.
The influence of fixation stability on balance in central vision loss

Abstract Background: Some major visual disorders damage the central retina and to compensate for the loss of a functioning fovea, those affected use their remaining peripheral retina to accomplish daily tasks. This results in the formation of an unstable, non-central fixation point, which compromises ability to detect obstacles and acquire visual information from the environment. The purpose of this study was to determine if there is a measurable (and significant) difference in balance ability and fall risk between visually impaired people with stable fixation and those with unstable fixation. Method: Individuals (n = 44) with a visual acuity of >20/400 in the better eye and a diagnosis of a retinal disorder affecting the macula were recruited for this study. Fixation stability was determined using the Mirametrix Eye Tracker and participants were then divided into two groups: stable fixation and unstable fixation. Functional balance was measured using the Timed Get-Up-and-Go (TUG) and the Berg Balance Scale (BBS). Balance confidence was assessed using the Activities-Specific Balance (ABC) Scale. Results: Performance on the TUG test was significantly different between the groups, with the poor-fixation group having a slower TUG time than the stable-fixation group, t (42) = −1.763, P = 0.043. Subjects with poor fixation stability scored lower on the ABC scale and on the BBS compared to the stable fixation group, but the difference was not significant. Significance: Based on the TUG, those with unstable fixation are at a higher risk of falls compared to individuals with stable fixation. Given fixation stability is a visual factor that can be trained and improved upon, these findings warrant further research into the relationship between fixation stability and balance.
ADMM-Net for Robust Compressive Sensing Image Reconstruction in the Presence of Symmetric \alpha-Stable Noise

This work aims at reconstructing image from compressed-measured data in the presence of symmetric αstable (SαS) noise. We first employ the l1-norm as the estimator to depress the influence of SαS noise, and then the ADMM framework is employed to address the resulting optimization problem. Moreover, a smoothing strategy is adopted to address the l1-norm resulting in a nonsmooth optimization problem. To exploit more prior knowledge and image features, a robust composite regularization model is proposed for training by deep neural network (DNN). In the training phase, the DNN can be utilized to train the samples for the optimal parameters, the optimal shrinkage function and the optimal transform domain. Experiments show that our proposed algorithm can obtain higher reconstruction Peak Signal to Noise Ratio (PSNRs) than some existing state-of-the-art robust CS methods.
Sunk-Cost Fallacy with Partial Reversibility: An Experimental Investigation

This study contributes to the literature attempting to document the sunk-cost fallacy in laboratory. I study the bias in a simple experimental setting, void of the previously acknowledged psychological roots of the sunk-cost fallacy. Under this design (i) the subjects have the possibility to partially recoup the investment in the initial course of action, (ii) the alternative course of action is made explicit and obvious and (iii) the associated returns of each course of action are deterministic. The sunk-cost fallacy hypothesis is not confirmed on the sample as a whole. However, I find evidence of its manifestation on subsamples for which I make the conjecture of having a better comprehension of the experimental task. Nevertheless, the bias appears to be independent of the size of the investment in the initial course of action. After controlling for mistakes in decisions and the effort put in the experimental task, I find that higher cognitive ability subjects are more prone to the bias. Finally, I argue that the previously acknowledged psychological drivers of the sunk-cost fallacy are not needed for the bias to manifest itself. Instead, I put forward the realization utility as the most likely underlying reason behind the manifestation of the sunk-cost fallacy under the current design.
PROTECTIVE ROLE OF METHANOLIC LEAF EXTRACT OF Holarrhena floribunda AGAINST SODIUM ARSENITE INDUCED LUNG OXIDATIVE STRESS IN MALE ALBINO RATS

Plant-based dietary components and added substances are known to shield cells from oxidative stress. This research was conducted to ascertain the protective effect of methanolic extract of Holarrhena floribunda against arsenite-initiated oxidative stress in the lungs of male albino rats. Thirty-six (36) adult rats with normal weight of 160 g were partitioned into six (6) groups marked A-F and treated as follows; Group A (negative control) was given distilled water, while 100 and 200 mg/kg weight of the leaf extract were given by oral gavage to groups C and D, and groups E and F individually, for 14 consecutive days. 5 mg/kg weight of Sodium arsenite was intraperitoneally administered to groups B (positive control), D and F, 24 h before sacrifice. Aftereffects of Glutathione reductase (GSH), Glutathione peroxidase (GPX) and total protein on post-mitochondrial portion of the lung homogenates demonstrated that sodium arsenite decreased GSH and GPX, while increment in total protein was observed. Co-administration of extract at 100 and 200 mg/kg with sodium arsenite expanded GSH by 5 and 44.3%, and GPX by 38.6 and 10%, while total protein diminished by 10 and 7.5% separately. The investigation demonstrated that the extract can possibly improve arsenite-induced lung oxidative stress and toxicity.
Stochastic Models for Greenhouse Whitefly Flight Behavior based on Wireless Image Monitoring System Measurements

One of the most harmful greenhouse insect pests is the Trialeurodes vaporariorum or most commonly known as the greenhouse whitefly. The easiest way to monitor the population of greenhouse whiteflies is by the use of yellow sticky paper traps. The insect count information from the traps can be used for analyzing insect behavior by constructing biological models. In this work, stochastic models describing the effects of temperature and the time of day on the flight behavior of greenhouse whiteflies were developed. Sticky paper images and temperature data were collected from an organic tomato seedling greenhouse by using integrated wireless imaging and environmental sensors. The greenhouse whitefly counts were determined by processing the images using an insect counting algorithm. From the results obtained, differences between the flight rates of the greenhouse whiteflies for different ranges of temperature were observed. The relationship was shown to be best fit using a double Weibull distribution function with an r2 of 0.988 and mean squared error of prediction (MSEP) of 0.001. Using the model, it was found that the optimal temperature for flight of greenhouse whiteflies was around 20-26oC. From the real-time counting data, different daily peak flight times were discovered. The peak flight rates were modeled using multi-peak probability distribution functions where it shows that the multipeak Gaussian distribution has the best fit with an r2 of 0.961 and MSEP of 0.006. The developed models can be used for developing insect pest control methods such as fuzzy temperature control and pesticide application scheduling.