Miracle-dz/UniFAR-FTUs huggingface dataset:
The Theory of Planned Behavior to Identify Out-of-Hospital Cardiac Arrest (OHCA) Bystanders' Intentions Intensi Bystander Out of Hospital Cardiac Arrest Berdasarkan Theory of Planned Behaviour

The theory of planned behavior states that intention is the best predictor of behavior. The intention to perform a behavior is determined by a person's attitude, subjective norms, and perceived behavioral control. As volunteers in the health sector, volunteers of the Indonesian Red Cross (PMI) have been equipped with knowledge and skills regarding the role of an OHCA bystander. Besides, the intentions of PMI volunteers greatly affect a person's tendency to be willing or unwilling to become an OHCA bystander. This study aims to apply the theory of planned behavior in identifying the factors that influence the intentions of PMI volunteers in acting as OHCA bystanders and the dominant factors that affect intentions. This study used an observational research type with a cross-sectional approach. The respondents in this study were 105 PMI volunteer members in Tuban Regency, which were conducted using the purposive sampling technique. In determining the most dominant factor that influenced intention, ordinal logistic regression analysis was used in which it was shown that the variable used in the last modeling analysis stage was the subjective norm (OR= 6.19). Based on the results of the analysis, it can be concluded that subjective norms are the most predictor factor that influences intentions. Sebagai relawan bidang relawan PMI sebagai bystander OHCA. bystander OHCA, intensi relawan PMI sangat mempengaruhi kecenderungan seseorang untuk bersedia atau tidak bersedia menjadi bystander OHCA. Penelitian ini bertujuan untuk menerapkan theory of planned behaviour dalam mengidentifikasi faktor yang mempengaruhi intensi relawan PMI dalam berperan sebagai bystander OHCA dan factor dominan yang mempengaruhi intensi. Jenis penelitian menggunakan observasional dengan pendekatan cross sectional . Responden yang turut serta sebanyak 105 anggota relawan PMI di Kabupaten Tuban yang dilakukan dengan teknik purposive sampling . Analisis regresi logistic ordinal digunakan untuk mengetahui factor yang paling dominan dalam mempengaruhi intensi menunjukkan bahwa dari semua variabel, variabel yang lolos sampai analisis pemodelan terakhir yaitu variabel norma subyektif (OR= 6,19). Berdasarkan hasil Analisa tersebut dapat ditarik kesimpulan bahwa norma subjektif merupakan factor predictor yang paling mempengaruhi intensi. theory of relawan
The Protective Effect of Chickpea and Lupine variety on rats with fatty liver

: Effect of Chickpea (Cicer arietinum L.) and lupin (Lupinus spp.) on fatty liver, (56) rats were divided into two main groups. The first group (7 rats) fed on basal diet, as a control negative. The second group (49 rats) were randomly assigned to seven equal subgroups (1) fed on high fat diet (HFD) containing (carbohydrate 55.6% sucrose 30%, starch 21.6%, fructose 4%, Fat 27.5%, protein 8.2%, cellulose 4.2%, salt mixture 3.5% and vitamin mixture 1%) and used as a control positive group (+ve). (2) fed on (HFD) + 10% imported chickpea (3) fed on (HFD) + 10% balady chickpea. (4) fed on (HFD) + 10% sweet lupin (5) fed on (HFD) + 10% bitter lupin, (6) fed on (HFD) + 5% imported chickpea + 5% sweet lupin (7) fed on (HFD) + 5% balady chickpea + 5% bitter lupin. The results indicated that, treating rats with (HFD + 5% balady chickpea and 5% bitter lupin and the group fed on (HFD) + 10% bitter lupin led to significant decrease in body weight gain %, organs weight%, lipid profile including (cholesterol, triglycerides, LDL-c and VLDL-c), glucose, leptin and liver enzymes. while these treatments induced significant increase in feed intake, HDL-c and antioxidant enzymes. These results agreement with histopathological examination of liver from group (7) Showing no histopathological changes.
Biochemical, mineral compositions and microbial assessment of smoked hilsa (Tenualosa ilisha) with leaves, juice, and lemon peel

The current study was conducted to investigate the proximate minerals composition and microbial assessment of smoked hilsa (Tenualosa ilisha) with salt, lemon leaves extract, lemon juice and peel treatments under laboratory conditions. A total of 50 fresh hilsa fishes were collected from Meghna River, Bangladesh and were used for this study, with five treatments: T0 (control treatment, raw hilsa), T1 (8% salt), T2 (20% lemon leaves extract), T3 (20% lemon juice) and T4 (20% lemon peel with 8% salt). Proximate composition was analyzed, right after the smoking and 15 days later, for moisture, protein, fat, ash, calcium, magnesium, iron and phosphorous. It can be said that T3 (20% lemon juice) was the best among the four treatments. Smoked hilsa treated with salt and lemon juice may be a future food item for consumption in global markets.
Multi-physics simulation of friction stir welding process

Purpose: The Friction Stir Welding (FSW) process comprises of several highly coupled (and non-linear) physical phenomena: large plastic deformation, material flow transportation, mechanical stirring of the tool, tool-workpiece surface interaction, dynamic structural evolution, heat generation from friction and plastic deformation, etc. In this paper, an advanced Finite Element (FE) model encapsulating this complex behavior is presented and various aspects associated with the FE model such as contact modeling, material model and meshing techniques are discussed in detail. Methodology: The numerical model is continuum solid mechanics-based, fully thermomechanically coupled and has successfully simulated the friction stir welding process including plunging, dwelling and welding stages. Findings: The development of several field variables are quantified by the model: temperature, stress, strain, etc. Material movement is visualized by defining tracer particles at the locations of interest. The numerically computed material flow patterns are in very good agreement with the general findings from experiments. Value: The model is, to the best of the authors’ knowledge, the most advanced simulation of FSW published in the literature.
Design, Fabrication, and Control of an Upper Arm Exoskeleton Assistive Robot

ii Acknowledgment . iii Chapter 1: Introduction . 1 1.1. Stroke [1] . 1 1.1.1. History of Stroke Neuro-Rehabilitation [12] . 2 1.2. Upper-Limb Exoskeleton Robotics and Applications in Assistance and Rehabilitation . 3 1.3. Motivation for Research . 5 1.1. Research Objective . 7 Chapter 2: Literature Review . 8 2.1. Rehabilitation Methods . 8 2.2. Home Rehabilitation Robotic Systems and Tele-Rehabilitation Applications . 10 2.3. Assessment and Evaluation Using Virtual Environment . 12 2.4. Categories of Rehabilitation/Assistive Robots . 13 2.4. 1. Control Approach . 14 2.4. 2. Therapeutic Approach and Physical Shapes . 15 2.4. 3. Actuation and Power Transmission Approach . 24 Chapter 3: Human Anatomy and Mechanical Design . 37 3.
Blast Protection of Unreinforced Masonry Walls: A State-of-the-Art Review

The recent rise of terrorist attacks has reinforced the need for mitigation of damage caused by blast loading on unreinforced masonry walls. The primary goal of the techniques is to prevent the loss of life while simultaneously preserving the integrity of the structure. This paper presents a compilation of recently available literature on blast protection of unreinforced masonry walls. It seeks to present the state of the art in this field, including mitigation techniques considered as well as testing methods selected. Fiber reinforced polymers and polyurea are the two dominant retrofitting techniques being assessed in the field. Other techniques include but are not limited to polyurethane, steel sheets, and aluminum foam. Since there is no widely implemented standard for blast loading test procedures, direct comparisons between the efficiencies of the mitigation techniques proposed are not always feasible. Although fragmentation is an indicator of the efficiency of retrofits, it is currently measured by subjective observation of postblast debris.
Redundant Design and Adaptive Control of an Interleaved Continuum Rigid Manipulator

Continuum manipulator compliance enables operation in delicate environments at the cost of challenging actuation and control. In the case of catheter ablation of atrial fibrillation, the compliance of the continuum backbone lends an inherent safety to the device. This inherent safety frustrates attempts at precise, accurate, and fast control, limiting these devices to simple, static positioning tasks. This dissertation develops Interleaved Continuum-Rigid Manipulation, by which the hysteretic nonlinearities encountered in tendon-actuated continuum manipulators are compensated by discrete rigid joints located between continuum sections. The rigid joints introduce actuation redundancy, which an interleaved controller may use to avoid continuum nonlinearities and dynamic excitations, or to prefer particular configurations that may improve task accuracy, permit greater end-effector forces, or avoid environment obstacles. Two experimental systems explore the potential of these joints to 1) correct for actuation nonlinearities and enhance manipulator performance and 2) increase the manipulator’s dexterous workspace. These experiments expose important design and control observations that were not apparent in the general robotic and continuum literature.
Effect of System of Rice Intensification on Water Productivity and NPS Pollution Discharge

Paddy fields comprise the single largest land use in Korea, occupying nearly 60% of arable land, consuming about 56% of the nation's water supply, and discharging a significant amount of agricultural non‐point source (NPS) pollution to public waters. Rural water resources conservation, the improvement of irrigation water productivity (IWP) and the reduction of NPS pollution from paddy fields are important issues in Korea. To quantify the issue, a field‐size rice‐plot study was conducted for 3 years comparing the treatment of a system of rice intensification (SRI) irrigation management and a conventional practice (CT). The SRI reduced the irrigation requirement at field level by 50% compared to the CT. The IWP of the SRI improved by an average of 94% over that of the CT. The average reductions of the NPS pollutants by SRI was 44.4% (BOD), 38.6% (SS), 35.3% (CODMn), 28.3% (CODCr), 23.8% (TN) and 36.3% (TN). The SRI treatment was concluded to have contributed to healthy rice plant growth, improvement of IWP and reduction of agricultural NPS pollution from paddy fields, which could significantly conserve rural water resources and improve water quality in Korea. Copyright © 2016 John Wiley & Sons, Ltd.
Low-cost crime scene mapping: reviewing emerging freeware, low-cost methods of 3D mapping and applying them to crime scene investigation and forensic evidence

Within the realm of 3D mapping, three technologies dominate; Laser, which excels at long range measurements with relatively high accuracy; Structured light systems, which excel at short range measurements at very high accuracy; and Photogrammetry, which uses only photographs, and can vary heavily with accuracy. Forensic science often utilises laser technology in a surveying role, however the other two are more specialised and used far less often. A barrier to greater use of 3D scanning and recreation is the generally large cost of the devices, some costing more than $100,000. Microsoft Kinect brought an infrared camera to the market as part of a gaming console, the Xbox. This camera functions as a mid-range structured light camera, and modified to map and measure a 3D environment. Kinect sensors are low-cost alternatives, and because of their higher accessibility, development of this technology is faster. Additionally, the development of more sophisticated software, and computational power has meant that photogrammetry has also become far more accessible, requiring only a moderate to high quality digital camera, and the accompanying program. These low-cost alternatives may prove to be invaluable for Police departments to attain greater evidence recovery in times of world-wide budget restrictions.
PIANO KEY WEIRS WITH POSITIVE PARAPET WALL

Piano Key weirs (PKWs) are appropriate alternatives to linear overflow weirs, because of increasing the discharge at the unit length of the unregulated spillway inlet in identical heads and spillway widths. The purpose of this study was to investigate the effect of angled Parapet Wall on the discharge flow and water level upstream piano key weirs and its comparison with the discharge on ogee weirs. To achieve this goal, a Piano Key Weir was constructed as a laboratory model with a constant height of 30 cm and Parapet Wall with positive slopes of 3, 5.5 and 8 degrees in a laboratory flume with 80 cm width, 10 m length and 60 cm height. The results indicated that among the models of Parapet Walls the one with slope of 8 degrees had the greatest impact on the upstream water level of the weir. This increasing relative to the model without Parapet Wall was about of 10 percent. Also, the results showed that at the angle of 8 degrees, the Parapet Wall had lower discharge flow efficiency, as compared to the same at the angles of 3 and 5.5 degrees; but still it was 40 percent more than the discharge flow of the ogee weirs. However, the Parapet Walls with 5.5 and 3 degrees angles led to 7 and 3 percent increase in water level, respectively, compared to the model without Parapet Wall. In addition, the Parapet Wall with 5.5 and 3 degrees angles in comparison to the ogee weirs showed 72% and 140% increase in the discharge flow, respectively. Moreover, it was obtained that the increase of discharge efficiency with increase of Parapet Wall height could occurre up to a specific height.
APPLICATION OF FUZZY LOGIC FOR CONTROLLING MECHANISM OF RELATIVE MANIPULATION ROBOT (MRM ROBOT)

In robot control, mathematical equations describing dynamic behaviors of robots are usually complicated. Additionally, the components such as inertial and friction parameters appearing in these equations are very difficult to determine exactly. With robots having complex structure such as parallel robots, MRM robots etc., the derivation of dynamic equations becomes more difficult and sometimes cannot obtain analytically. In those cases, controlling robot based on its equations of motion is quite hard. Applying fuzzy logic for robot control can overcome the mentioned drawbacks. This is because fuzzy control algorithm gives favorable condition to deal with the lack of adequation as well as inaccuracy of components in robot’s dynamic equations. Furthermore, the fuzzy rules are created by clauses which based on human logic, so it is easily to understand and implement. This paper discusses the application of fuzzy logic for controlling MRM robots. To compare the results obtained from fuzzy control, this paper are also adressed the use of the computed torque algorithm to control MRM robots.
Novel cerebrospinal fluid biomarkers of glucose transporter type 1 deficiency syndrome: Implications beyond the brain's energy deficit

We used next‐generation metabolic screening to identify new biomarkers for improved diagnosis and pathophysiological understanding of glucose transporter type 1 deficiency syndrome (GLUT1DS), comparing metabolic cerebrospinal fluid (CSF) profiles from 12 patients to those of 116 controls. This confirmed decreased CSF glucose and lactate levels in patients with GLUT1DS and increased glutamine at group level. We identified three novel biomarkers significantly decreased in patients, namely gluconic + galactonic acid, xylose‐α1‐3‐glucose, and xylose‐α1‐3‐xylose‐α1‐3‐glucose, of which the latter two have not previously been identified in body fluids. CSF concentrations of gluconic + galactonic acid may be reduced as these metabolites could serve as alternative substrates for the pentose phosphate pathway. Xylose‐α1‐3‐glucose and xylose‐α1‐3‐xylose‐α1‐3‐glucose may originate from glycosylated proteins; their decreased levels are hypothetically the consequence of insufficient glucose, one of two substrates for O‐glucosylation. Since many proteins are O‐glucosylated, this deficiency may affect cellular processes and thus contribute to GLUT1DS pathophysiology. The novel CSF biomarkers have the potential to improve the biochemical diagnosis of GLUT1DS. Our findings imply that brain glucose deficiency in GLUT1DS may cause disruptions at the cellular level that go beyond energy metabolism, underlining the importance of developing treatment strategies that directly target cerebral glucose uptake.
InGaAs focal plane array developments and perspectives

Thanks to the various developments presently available, SWIR technology presents a growing interest and gives the opportunity to address a large spectrum of applications such as defense and security (night vision, active imaging), space (earth observation), transport (automotive safety) or industry (non destructive process control). InGaAs material, initially developed for telecommunications detectors, appears as a good candidate to satisfy SWIR detection needs. The lattice matching with InP constitutes a double advantage to this material: attractive production capacity and uncooled operation thanks to low dark current level induced by high quality material. In the context of this evolving domain, the InGaAs imagery activities from III-VLab were transferred to Sofradir, which provides a framework for the production activity with the manufacturing of high performances products: CACTUS320 and CACTUS640. The developments towards VGA format with 15μm pixel pitch, lead today to the industrialization of a new product: SNAKE SW. On one side, the InGaAs detection array presents high performances in terms of dark current and quantum efficiency. On the other side, the low noise ROIC has different additional functionalities. Then this 640x512 @ 15μm module appears as well suited to answer the needs of a wide range of applications. In this paper, we will present the Sofradir InGaAs technology, the performances of our last product SNAKE SW and the perspectives of InGaAs new developments.
Flow features around double cones at hypersonic speed

Abstract An experimental study of double cone geometries in hypersonic flow (at M∞ of 8·2 and Re d of 0·36 × 106) was performed to provide additional data to a computational simulation study. In this study, depending on how the flow was initialised, the numerical solution yielded a violent pulsation mode of instability or a steady flow. Finally, an analysis of the shock oscillation was made and discussed.
MVSTER: Epipolar Transformer for Efficient Multi-View Stereo

Learning-based Multi-View Stereo (MVS) methods warp source images into the reference camera frustum to form 3D volumes, which are fused as a cost volume to be regularized by subsequent networks. The fusing step plays a vital role in bridging 2D semantics and 3D spatial associations. However, previous methods utilize extra networks to learn 2D information as fusing cues, underusing 3D spatial correlations and bringing additional computation costs. Therefore, we present MVSTER, which leverages the proposed epipolar Transformer to learn both 2D semantics and 3D spatial associations efficiently. Specifically, the epipolar Transformer utilizes a detachable monocular depth estimator to enhance 2D semantics and uses cross-attention to construct data-dependent 3D associations along epipolar line. Additionally, MVSTER is built in a cascade structure, where entropy-regularized optimal transport is leveraged to propagate finer depth estimations in each stage. Extensive experiments show MVSTER achieves state-of-the-art reconstruction performance with significantly higher efficiency: Compared with MVSNet and CasMVSNet, our MVSTER achieves 34% and 14% relative improvements on the DTU benchmark, with 80% and 51% relative reductions in running time. MVSTER also ranks first on Tanks&Temples-Advanced among all published works. Code is released at https://github.com/JeffWang987.
Test-Time Training Can Close the Natural Distribution Shift Performance Gap in Deep Learning Based Compressed Sensing

Deep learning based image reconstruction methods outperform traditional methods. However, neural networks suffer from a performance drop when applied to images from a different distribution than the training images. For example, a model trained for reconstructing knees in accelerated magnetic resonance imaging (MRI) does not reconstruct brains well, even though the same network trained on brains reconstructs brains perfectly well. Thus there is a distribution shift performance gap for a given neural network, defined as the difference in performance when training on a distribution $P$ and training on another distribution $Q$, and evaluating both models on $Q$. In this work, we propose a domain adaptation method for deep learning based compressive sensing that relies on self-supervision during training paired with test-time training at inference. We show that for four natural distribution shifts, this method essentially closes the distribution shift performance gap for state-of-the-art architectures for accelerated MRI.
Summarization with Graphical Elements

Automatic text summarization has experienced substantial progress in recent years. With this progress, the question has arisen whether the types of summaries that are typically generated by automatic summarization models align with users' needs. Ter Hoeve et al (2020) answer this question negatively. Amongst others, they recommend focusing on generating summaries with more graphical elements. This is in line with what we know from the psycholinguistics literature about how humans process text. Motivated from these two angles, we propose a new task: summarization with graphical elements, and we verify that these summaries are helpful for a critical mass of people. We collect a high quality human labeled dataset to support research into the task. We present a number of baseline methods that show that the task is interesting and challenging. Hence, with this work we hope to inspire a new line of research within the automatic summarization community.
The Importance of Credo in Multiagent Learning

We propose a model for multi-objective optimization, a credo, for agents in a system that are configured into multiple groups (i.e., teams). Our model of credo regulates how agents optimize their behavior for the groups they belong to. We evaluate credo in the context of challenging social dilemmas with reinforcement learning agents. Our results indicate that the interests of teammates, or the entire system, are not required to be fully aligned for achieving globally beneficial outcomes. We identify two scenarios without full common interest that achieve high equality and significantly higher mean population rewards compared to when the interests of all agents are aligned.
Power graphs of Moufang loops

Power graphs of both groups and semigroups have been widely studied, for example in [1], [2], [3], [4], [5], [6], [7]. While the power graph of a quasigroup can be defined analogously to that of a group, power graphs of quasigroups and loops have thus far been little studied. In this paper we begin transferring results on the power graphs of groups to the context of loops by addressing a question posed by Peter Cameron: if two Moufang loops have isomorphic undirected power graphs, must they have isomorphic directed power graphs? In [3] Cameron shows that two groups with isomorphic undirected power graphs must have isomorphic directed power graphs. We are able to extend that result to Moufang loops in our main theorem: