Miracle-dz/UniFAR-FTUs huggingface dataset:
Pengaruh Ease of Use, Trust, dan Privacy Concern terhadap Repurchase Intention pada Situs Jual Beli Online Bukalapak

Tujuan dari penelitian ini adalah untuk mengetahui pengaruh ease of use, trust dan privacy concern terhadap repurchase intention pada situs jual beli online Bukalapak. Populasi dari penelitian ini adalah pengguna Marketplace Bukalapak yang sudah pernah bertransaksi di Bukalapak minimal 4 kali. Penelitian ini menggunakan metode non probability. Sampel dipilih menggunakan metode purposive sampling berjumlah 100 responden yang sudah pernah berbelanja di marketplace bukalapak minimal 4 kali. Teknik pengumpulan data menggunakan kuesioner yang disebarkan secara online malalui google form. Penelitian ini menggunakan teknik analisis structural equation modeling (SEM) dengan menggunakan software SMART PLS 3 untuk mengolah data. Hasil penelitian ini menunjukkan bahwa ease of use berpengaruh positif dan signifikan terhadap repurchase intention, trust berpengaruh positif dan signfikan terhadap repurchase intention dan privacy concern berpengaruh positif dan signifikan terhadap repurchase intention. The purpose of this study was to determine the effect of ease of use, trust and privacy on repurchase intentions on the online buying and selling site Bukalapak. Data collection techniques were carried out by distributing questionnaires using a Likert scale of 1-5. Data collection techniques used questionnaires distributed online via google form. The sample selected using the purposive sampling method was 100 respondents who had shopped at the Bukalapak marketplace 4 times. This study uses structural equation modeling (SEM) analysis techniques using SMART PLS 3 software to process data. The results of this study indicate that ease of use has a positive effect on repurchase intentions, trust has a positive effect on repurchase intentions and attention to privacy has a significant effect on repurchase intentions.
The constitutive modelling of London Clay

Advances in understanding real soil behaviour, achieved over the past twenty years, and subsequent developments of relevant soil constitutive models, have greatly enhanced the predictive ability of numerical analyses of geotechnical structures. Of particular relevance, especially for serviceability limit state (SLS) design, has been the understanding of soils' small strain behaviour. For the behaviour of London Clay, initially developed models were simple curve-fitting techniques that reproduce stiffness dependence on stress and strain level, which has shown some successes in predicting SLS behaviours. Modelling failure of London Clay is significantly more complex due to its overconsolidated and fissured nature. More recent developments in soil constitutive modelling have therefore tried to encompass most important aspects of clay behaviour within the unified framework of critical state. However, even these advanced models have insufficient features to simulate the behaviour of overconsolidated clays. In .
Using Fink’s Integrated Course Design Model in Developing a Health It Course

This paper introduces how Fink’s Integrated Course Design model was used to refine a Health Information Technology (HIT) core course – “Clinical Process and Workflow: Analysis and Redesign” – for improving the design and enhancing student learning in this rapidly growing field. The paper describes the course design process centered on Fink’s taxonomy of significant learning – foundational knowledge, application, integration, human dimension, caring, and learning how to learn. Example case study assignment, term project and assessment rubric are provided. Student feedback shows that the course enhances student learning and prepares them to meet the needs of healthcare organizations and HIT development.
Asymptotic attenuation and rejection for a class of cascade systems with general periodic disturbances

In this article, the problem of asymptotic attenuation and rejection is investigated for a class of cascade systems with general periodic disturbances via a non-linear disturbance observer and H ∞ control. First, a novel disturbance observer is developed to estimate general periodic disturbances, where the disturbances are described as a linear uncertain system with a non-linear output function. Then, a composite controller is constructed by combining the disturbance estimation with the partial state feedback control law, such that, the closed-loop system is asymptotically stable and meets H ∞ performance. With the help of the Lyapunov function theory and the linear matrix inequality method, some sufficient conditions for the desired controller and observer gains are established. Finally, numerical and application examples are presented to demonstrate the effectiveness of the proposed scheme.
Report of cerebral vasospasm as a complication of intracranial subarachnoid hemorrhage following traumatic lumbar puncture

Background: This case report is the first documented and illustrated case of the identification and treatment of intracranial vasospasm as a sequalae of traumatic lumbar puncture (LP). LP is a routine procedure performed for both diagnostic and therapeutic purposes. Although rare, this procedure has risks and complications that should be considered before performing. Case Description: A 58-year-old male was found to have intracranial subarachnoid hemorrhage (SAH) 2 days after a traumatic LP which occurred in the setting of subtherapeutic international normalized ratio. During his hospitalization, the patient developed both clinical and radiographic signs of vasospasm. He was taken for angiography, which demonstrated significant vasospasm of bilateral middle cerebral arteries and bilateral anterior cerebral arteries. All vasospasms resolved and the patient improved clinically after intra-arterial spasmolytic therapy. Conclusion: LP is a routine procedure with complications that are often overlooked. The authors describe intracranial vasospasm from traumatic LP before correction of patient’s coagulopathy. Cases with similar hemorrhage occurring in the spine resulting in non-aneurysmal SAH and vasospasm were reviewed.
A Fast Clustering Based Evolutionary Algorithm for Super-Large-Scale Sparse Multi-Objective Optimization

During the last three decades, evolutionary algorithms (EAs) have shown superiority in solving complex optimization problems, especially those with multiple objectives and non-differentiable landscapes. However, due to the stochastic search strategies, the performance of most EAs deteriorates drastically when handling a large number of decision variables. To tackle the curse of dimensionality, this work proposes an efficient EA for solving super-large-scale multi-objective optimization problems with sparse optimal solutions. The proposed algorithm estimates the sparse distribution of optimal solutions by optimizing a binary vector for each solution, and provides a fast clustering method to highly reduce the dimensionality of the search space. More importantly, all the operations related to the decision variables only contain several matrix calculations, which can be directly accelerated by GPUs. While existing EAs are capable of handling fewer than 10 000 real variables, the proposed algorithm is verified to be effective in handling 1 000 000 real variables. Furthermore, since the proposed algorithm handles the large number of variables via accelerated matrix calculations, its runtime can be reduced to less than 10% of the runtime of existing EAs.
Cement-Based Repair Materials and the Interface with Concrete Substrates: Characterization, Evaluation and Improvement

Surface damages usually occur in concrete structures. In order to restore the functions and prolong the service life of concrete structures, their surface damages should be repaired in time. This paper reviews the main requirements for repair materials for concrete structures and the most used inorganic repair materials, such as cement-based materials, alkali-activated materials and polymer modified inorganic repair materials. Moreover, techniques to characterize and even improve the interfaces between these repair materials and concrete substrate are summarized. Cement-based material has the advantages of good mechanical properties and consistency with concrete substrate while having the problems of high shrinkage and low flexibility. Polymer modified materials were found as having lower shrinkage and higher flexural strength. Increasing the roughness or humidity of the surface, adding fibers and applying interfacial agents can improve the bond strength between cement-based repair materials and concrete substrates. All of these repair materials and techniques can help to build a good interfacial bonding, and mechanisms of how they improve the interface are discussed in this article. These are of great importance in guaranteeing the effectiveness of the repair of the concrete surface and to guide the research and development of new repair materials.
Förbränning av biogas/metan i en EcoMarathonmotor

This report is about the process of converting a petrol-fuelled Honda GX35 engine to run on methane gas. The future goal is to use the engine in the engineering competition Shell Eco-marathon, where the aim is to drive a vehicle as far as possible with a set amount of fuel. To enable methane fuelling, the carburator of the GX35 was replaced with a gas fuel injector from the engine accessory company Ecotrons. This was attached to an aluminium intake pipe constructed by the project group. A new flywheel was constructed, equipped with twelve magnetic detection points instead of one for more accurate detection of the crankshaft position. A magnet was also attached to the upper cam pulley to enable position detection. The original exhaust system was replaced by a holder of a lambda sensor and a straight exhaust pipe. Together with the engine control unit (ECU) KATLA, developed earlier for a bachelor’s thesis at Chalmers, this enabled detailed control of ignition and fuel injection, as well as measurement of the air-fuel ratio. In order to test the engine with a load, a brake device was constructed. A moped was acquired, whose gearbox and rear brake was used to brake and gear down the output shaft of the methane engine. The flywheel of the methane engine was connected to the flywheel of the moped through a vibration reducing rubber disc and a steel adapter. The rear wheel of the moped was lifted from the ground with a support so that it could rotate freely. By doing this, the load of the engine could be controlled with the rear brake pedal of the moped. Methane was not available for the project group, so the engine was tested with liquefied petroleum gas instead, which is another gaseous fuel. Before the engine was started, the flow rate through the gas injector was measured. This data was used to set the fuel parameters in the ECU. With some minor adjustments the engine ran well during testing.
O.R. Applications Applying environmental criteria to supplier assessment: A study in the application of the Analytical Hierarchy Process

Increasingly, purchasing managers are being asked not only to transform purchasing into a more strategic function but also to integrate environmental issues in their decisions. Introducing the environmental dimension into purchasing decisions embeds a new set of trade-offs in the decision, complicating the decision-making process with both qualitative and quantitative factors. Yet, few companies use any structured analysis to evaluate suppliers along environmental dimensions. In this study, we illustrate the use of the Analytical Hierarchy Process (AHP) as a decision support model to help managers understand the trade-offs between environmental dimensions. We then demonstrate how AHP can be used to evaluate the relative importance of various environmental traits and to assess the relative performance of several suppliers along these traits. Three case studies were carried out to demonstrate the benefits and weaknesses of using AHP in this manner. Finally, we examine how AHP can be incorporated into a comprehensive information system supporting Environmentally Conscious Purchasing (ECP). � 2002 Elsevier Science B.V. All rights reserved.
Correction of Dropped Frames in High-resolution Push-broom Hyperspectral Images for Cultural Heritage

Dropped frames can occur in line-scan cameras, which result in non-uniform spatial sampling of the scene. A dropped frame occurs when data from an image sensor is not successfully recorded. When mosaicking multiple line-scan images, such as in high-resolution imaging, this can cause misalignment. Much previous work to identify dropped frames in video prioritises fast computation over high accuracy, whereas in heritage imaging, high accuracy is often preferred over short computation time. Two approaches to identify the position of dropped frames are presented, both using the A* search algorithm to correct dropped frames. One method aligns overlapping sections of push-broom images and the other aligns the push-broom image to a lower resolution reference image. The two methods are compared across a range of test images, and the method aligning overlapping sections is shown to perform better than the method using a reference image under most circumstances. The overlap method was applied to hyperspectral images acquired of La Ghirlandata, an 1873 oil on canvas painting by D. G. Rossetti, enabling a high-resolution hyperspectral image mosaic to be produced. The resulting composite image is 10,875 \( \times \) 14,697 pixels each with 500 spectral bands from 400–2,500 nm. This corresponds to a spatial resolution of \( 80 \,\mathrm{\upmu }\mathrm{m} \) and a spectral resolution of 3–6 nm.
Impact of Cultivation Substrate and Microbial Community on Improving Mushroom Productivity: A Review

Simple Summary Lignocellulosic material and substrate formulations affect mushroom productivity. The microbial community in cultivation substrates affects the quality of the substrates and the efficiency of mushroom production. The elucidation of the key microbes and their biochemical function can serve as a useful guide in the development of a more effective system for mushroom cultivation. Abstract Lignocellulosic materials commonly serve as base substrates for mushroom production. Cellulose, hemicellulose, and lignin are the major components of lignocellulose materials. The composition of these components depends upon the plant species. Currently, composted and non-composted lignocellulosic materials are used as substrates in mushroom cultivation depending on the mushroom species. Different substrate compositions can directly affect the quality and quantity of mushroom production yields. Consequently, the microbial dynamics and communities of the composting substrates can significantly affect mushroom production. Therefore, changes in both substrate composition and microbial diversity during the cultivation process can impact the production of high-quality substrates and result in a high degree of biological efficiency. A brief review of the current findings on substrate composition and microbial diversity for mushroom cultivation is provided in this paper. We also summarize the advantages and disadvantages of various methods of mushroom cultivation by analyzing the microbial diversity of the composting substrates during mushroom cultivation. The resulting information will serve as a useful guide for future researchers in their attempts to increase mushroom productivity through the selection of suitable substrate compositions and their relation to the microbial community.
Research on Urban National Sports Fitness Demand Prediction Method Based on Ant Colony Algorithm

With the development of competitive sports, the enthusiasm of the public to participate in sports has gradually increased. At present, almost all streets in the city have their own fitness places, which provide a lot of help for public fitness. However, the existing fitness venues are obviously insufficient, the venues are limited, relatively single, and the open-space area is insufficient, which cannot meet the needs of mass sports fitness. Based on this, this paper studies and analyzes the prediction of urban national sports fitness demand based on the ant colony algorithm. First, this paper analyzes the National Fitness Situation and the related research on demand forecasting and puts forward the use of the ant colony algorithm to realize demand forecasting. This paper expounds on the research methods and algorithms commonly used in demand forecasting. The ant colony algorithm is used to improve the fuzzy analysis. The urban national sports fitness demand is divided into six secondary indicators, and different tertiary indicators are divided under each secondary indicator. Through simulation analysis, it is confirmed that the improved algorithm proposed in this paper converges faster and finds the best path most. At the same time, the weight of the urban national sports fitness demand index is calculated.
Formulation and Characterization of Carbopol-934 Based Kojic Acid-Loaded Smart Nanocrystals: A Solubility Enhancement Approach

Kojic acid (KA) is a BCS class II drug having low solubility and high permeability. This study was designed to enhance the aqueous solubility of KA, as well as its dissolution rate and, in turn, bioavailability, by formulating its smart nanocrystals. Nanocrystals of pure KA were formulated by the top-down method under high-pressure homogenization followed by freeze drying. The nanocrystals were evaluated for stability and other physical characteristics, including zeta sizer analysis, DSC, surface morphology, XRD, drug content, solubility, FTIR and in vitro drug release. The KA nanocrystals were found to be stable when kept at exaggerated conditions. The particle size of the nanocrystals was 137.5 ± 1.7, 150 ± 2.8, and 110 ± 3.0 nm for the F1, F2 and F3 formulations, respectively. There was negative zeta potential for all the formulations. The dispersity index was 0.45 ± 0.2, 0.36 ± 0.4 and 0.41 ± 1.5 for the F1, F2 and F3, respectively. The DSC studies showed that there was no interaction between the KA and the excipients of the nanocrystals. The morphological studies confirmed the presence of rough crystalline surfaces on the nanosized particles. XRD studies showed the successful preparation of nanocrystals. The drug content was in the official range of 90 ± 10%. The solubility of KA was significantly (p < 0.05) enhanced in the formulations of its nanocrystals as compared with pure KA powder. The ATR-FTIR studies revealed the presence of functional groups in both KA and KA-loaded nanocrystals, and no interaction was found between them. The nanocrystals released 83.93 ± 1.22% of KA in 24 h. The study concluded that the nanocrystals were successfully formulated using the top-down method followed by high-pressure homogenization. The solubility, as well as the dissolution, of the KA was enhanced, and this could improve the therapeutic effects of KA.
A Genetic Characterization of the Hays Converter

A GENETIC CHARACTERIZATION OF THE HAYS CONVERTER Allison L. Fleming Advisor: University of Guelph, 2013 S.P. Miller This thesis gives a genetic overview of the Hays Converter, a beef breed developed in Canada in the 1950s. Pedigree records were examined to determine genetic diversity and inbreeding. A positive rate of inbreeding and a decrease in the amount of genetic diversity was found. Single trait and bivariate animal models were used to determine genetic parameters and trends for growth, ultrasound, and carcass traits. An increasing genetic trend was found for growth traits which the breed was selected for. The accuracy of imputation from 6k to 50k marker panels using a reference group of 100 animals was determined. Imputation was performed with a high accuracy (>0.93) for pure Hays Converter animals, but was found to be unsuccessful when individuals had large contributions from additional breeds. This work forms the foundation for future management and advance of the breed while outlining its history and progress.
Semi-Supervised Adversarial Semantic Segmentation Network Using Transformer and Multiscale Convolution for High-Resolution Remote Sensing Imagery

Semantic segmentation is a crucial approach for remote sensing interpretation. High-precision semantic segmentation results are obtained at the cost of manually collecting massive pixelwise annotations. Remote sensing imagery contains complex and variable ground objects and obtaining abundant manual annotations is expensive and arduous. The semi-supervised learning (SSL) strategy can enhance the generalization capability of a model with a small number of labeled samples. In this study, a novel semi-supervised adversarial semantic segmentation network is developed for remote sensing information extraction. A multiscale input convolution module (MICM) is designed to extract sufficient local features, while a Transformer module (TM) is applied for long-range dependency modeling. These modules are integrated to construct a segmentation network with a double-branch encoder. Additionally, a double-branch discriminator network with different convolution kernel sizes is proposed. The segmentation network and discriminator network are jointly trained under the semi-supervised adversarial learning (SSAL) framework to improve its segmentation accuracy in cases with small amounts of labeled data. Taking building extraction as a case study, experiments on three datasets with different resolutions are conducted to validate the proposed network. Semi-supervised semantic segmentation models, in which DeepLabv2, the pyramid scene parsing network (PSPNet), UNet and TransUNet are taken as backbone networks, are utilized for performance comparisons. The results suggest that the approach effectively improves the accuracy of semantic segmentation. The F1 and mean intersection over union (mIoU) accuracy measures are improved by 0.82–11.83% and 0.74–7.5%, respectively, over those of other methods.
The Impact of Variation Orders on Public Building Projects

Variation is common in construction projects due to the complex nature of the construction industry. Variation order is observed as one of the most frequently occurring issues in construction projects in Ethiopia. Variations are known to impact various aspects of construction projects. Due to the background of the problem in public building projects, there is a cause for a study to be made on the assessment of the impact of variation orders on public building projects. The objective of the study was to identify the impacts of variation orders on public building projects. To achieve the stated objective of the study, the scope is limited to public building projects in Addis Ababa. Through a comprehensive study of literature review, resulted in identification of 15 impacts of variation orders on building projects. A desk study, interview and questionnaire survey were carried out to identify the impacts of variation orders on public building projects. The desk study conducted on five selected public building projects and the impacts of variation orders on the projects were identified. Interviews were made with selected experienced public building project participants for expert opinion. The questionnaires were distributed to the relevant project parties and the responses were analyzed using the relative index (RI) method. A triangulation method on the desk study, survey and the literatures was done to improve the validity of the findings from the study. The result showed that completion schedule delay, increase in project cost, additional payments for the contractor, effect on progress, and increase in overhead expenses were the main impacts of variation orders on public building projects.