Miracle-dz/UniFAR-FTUs huggingface dataset:
Integration of Bridge Damage Detection Concepts and Components Volume III: Wireless Bridge Monitoring Hardware

In this work, a previously developed structural health monitoring (SHM) system was advanced toward a ready-for-implementation system. Improvements were made with respect to automated data reduction/analysis, data acquisition hardware, sensor types, and communication network architecture. This report volume (Volume III) summarizes the energy harvesting techniques and prototype development for a bridge monitoring system that uses wireless sensors. The wireless sensor nodes are used to collect strain measurements at critical locations on a bridge. The bridge monitoring hardware system consists of a base station and multiple self-powered wireless sensor nodes. The base station is responsible for the synchronization of data sampling on all nodes and data aggregation. Each wireless sensor node include a sensing element, a processing and wireless communication module, and an energy harvesting module. The hardware prototype for a wireless bridge monitoring system was developed and tested on the US 30 Bridge over the South Skunk River in Ames, Iowa. The functions and performance of the developed system, including strain data, energy harvesting capacity, and wireless transmission quality, were studied and are covered in this volume. The Iowa Department of Transportation (DOT) started investing in research (through both the Iowa Highway Research Board and the Office of Bridges and Structures) in 2003 to develop a structural health monitoring (SHM) system capable of identifying damage and able to report on the general operational condition of bridges. In some cases, the precipitous for these developments has been a desire to avoid damage that might go unnoticed until the next biennial inspection. Of specific and immediate concern was the state’s inventory of fracture-critical structures. The goal of this project was to bring together various components of recently-completed research at Iowa’s Regent Universities with the following specific objectives: was performed. The test results were analyzed to validate the wireless sensor data collected. The results demonstrated that using a 270 cm 2 solar panel next to a sensor node, the system can maintain the energy balance to collect strain data with a 16.7 percent duty cycle in a sample frequency of 128 Hz.
Generation and Characterization of Mice with Mutations in Mitochondrial Genome for Examination of Mitochondrial Theory of Aging

Mitochondrial DNA (mtDNA) mutator mice are proposed to express premature aging phenotypes including kyphosis and hair loss (alopecia) due to their carrying a nuclear genome-encoded mtDNA polymerase with a defective proofreading function, which causes accelerated accumulation of random mutations in mtDNA, resulting in expression of respiration defects. On the contrary, trans-mitochondrial mito-miceΔ carrying mtDNA with a large-scale deletion mutation (ΔmtDNA) also express respiration defects, but not express premature aging phenotypes. I resolved this discrepancy by generating mtDNA mutator mice sharing the same C57BL/6J (B6J) nuclear background with that of mito-miceΔ. Expression patterns of premature aging phenotypes are very close, when I compared between homozygous mtDNA mutator mice carrying a B6J nuclear background and selected mito-miceΔ only carrying predominant amounts of ΔmtDNA, in their expression of significant respiration defects, kyphosis, and a short lifespan, but not the alopecia. Therefore, the apparent discrepancy in the presence and absence of premature aging phenotypes in mtDNA mutator mice and mito-miceΔ, respectively, is partly the result of differences in the nuclear background of mtDNA mutator mice and of the broad range of ΔmtDNA proportions of mito-miceΔ used in previous studies. Then I focused on the issue of whether premature aging phenotypes expressed in mtDNA mutator mice are associated with aging or mitochondrial diseases or both by using aged mice and mito-miceΔ as controls of aging and mitochondrial diseases, respectively. I provided convincing evidence that all three mice I used expressed osteoporosis and muscle atrophy, which are supposed to be age-associated phenotypes. However, precise investigation of osteoporosis and muscle atrophy revealed that expression spectra of these phenotypes in mtDNA mutator mice are very close to those of mito-miceΔ, but are different from those of aged mice and elderly human subjects. I also provided direct evidence that mtDNA abnormalities in homozygous mtDNA mutator
A Wearable and Internet-Of-Things (IoT) Application for Sleep Detection and Lighting Control using AI and Machine Learning Techniques

There are many apps that let you control hardwares with the application of the internet-of-thing today, however, I have seen none that lets you customly control the hardwares, most likely you can only use the few controls the developer of the hardware gives you, and there are very few auto control options. This paper designs an application to auto control the hardwares into desired state based on personal status detected [1]. We use a smart watch to detect the heart beat of the user and determine if they are asleep, and once they are asleep, we turn off a light switch in the user's room to create a total darkness environment. Much research done on sleeping quality shows that sleeping in total darkness gives much better sleeping quality, while many, out of fear or sleeping disorders, still leave little lights on when sleeping [3]. This software helps to give these people better sleeping quality with ease [2].
Entrepreneurship as a 21 st century skill: Entrepreneurial alertness and intention in the transition to adulthood

: Given the importance of entrepreneurial thinking and acting as a meta-skill in the future world of work, we focus on the emerging entrepreneurial mindset in the transition to adulthood. We study the role of personality characteristics and age-appropriate entrepreneurial competencies (leadership, self-esteem, creativity, proactivity motivation) in the prediction of entrepreneurial alertness and career intention. Using two-wave longitudinal data from high schools in Helsinki, Finland ( N = 523), we tested a mediation model with competencies as mediators between personality and entrepreneurial alertness and intention. The findings suggest that entrepreneurial alertness and career intention a) are rather independent career development constructs of the emerging entrepreneurial mindset, b) are both an expression of an entrepreneurial personality structure, and c) are predicted by different, underlying competencies: leadership and self-esteem mediated Consistent with the balanced skill approach to entrepreneurship, the intraindividual variety of these competencies was also a valid mediator; it did not show incremental predictive power though. Implications for research and practice are discussed.
D IALOGUE P IDGIN T EXT A DAPTATION VIA C ON - TRASTIVE F INE -T UNING

The surging demand for multilingual dialogue systems often requires a costly labeling process for each language addition. For low resource languages, human annotators are continuously tasked with the adaptation of resource-rich language utterances for each new domain. However, this prohibitive and impractical process can often be a bottleneck for low resource languages that are still without proper translation systems nor parallel corpus. In particular, it is difficult to obtain task-specific low resource language annotations for the English-derived creoles (e.g. Nigerian and Cameroonian Pidgin). To address this issue, we utilize the pretrained language models i.e. BART which has shown great potential in language generation/understanding – we propose to finetune the BART model to generate utterances in Pidgin by leveraging the proximity of the source and target languages, and utilizing positive and negative examples in contrastive training objectives. We collected and released the first parallel PidginEnglish conversation corpus in two dialogue domains and showed that this simple and effective technique is sufficient to yield impressive results for English-to-Pidgin generation, which are two closely-related languages.
Omnidirectional Configuration and Control Approach on Mini Heavy Loaded Forklift Autonomous Guided Vehicle

This paper presents the omnidirectional configuration and control approach on Mini Heavy Loaded Forklift Autonomous Guided Vehicle (MHeLFAGV) for flexibility maneuverability in confine and narrow area. The issue in turning motion for nonholonomic vehicle in confine area becoming a motivation in MHeLFAGV design to provide holonomic vehicle with flexible movement. Therefore an omni-wheeled named Mecanum wheel has been configured in this vehicle design as well as omnidirectional control algorithm. MHeLFAGV system is developed with collaboration and inspired from Vacuumshmelze (M) Sdn. Bhd. Pekan, Pahang in order to have a customized mini forklift that able to work in a very confined warehouse (170cm x 270cm square) with heavy payload in a range of 20-200kg. In electronics control design, two stages of controller boards are developed namely as Board 1 and 2 that specifically for movement controller board and monitoring controller board respectively. In addition separate module of left, right, forward, backward, diagonal and zigzagging movement is developed as embedded modules for MHeLFAGV system’s control architecture. A few experiments are done to verify the algorithm for each omnidirectional movement of MHeLFAGV system in the wide area. The waypoint of MHeLFAGV movement is plotted using Global Positioning System (GPS) as well as a digital compass by mapping the longitude and latitude of the vehicle. There are slightly different between the targeted movements with recorded data since Mecanum wheeled affected by the uneven surface of the landscape. The experiment is also further on moving in confine are on the actual targeted warehouse.
Parametric damage tolerance design of metallic aeronautical stiffened panels

Abstract On the basis of well-known literature, an analytical tool named LEAF (linear elastic analysis of fracture) was developed by the authors to predict the damage tolerance (DT) proprieties of aeronautical stiffened panels. The tool is based on the linear elastic fracture mechanics and the displacement compatibility method. By means of LEAF, an extensive parametric analysis of stiffened panels, representative of typical aeronautical constructions, was performed to provide meaningful design guidelines. The effects of riveted, integral and adhesively bonded stringers on the fatigue crack propagation performances of stiffened panels were investigated, as well as the crack retarder contribution using metallic straps (named doublers) bonded in the middle of the stringers bays. The effect of both perfectly bonded and partially debonded doublers was investigated as well. Adhesively bonded stiffeners showed the best DT properties in comparison with riveted and integral ones. A great reduction of the skin crack growth propagation rate can be achieved with the adoption of additional doublers bonded between the stringers.
Constructing better health and wellbeing? Understanding structural constraints on health and wellbeing in the UK Construction Industry

The construction industry has high rates of work related ill health and early retirement due to stress, injury and illness. W(cid:346)(cid:349)(cid:367)(cid:400)(cid:410) (cid:410)(cid:346)(cid:286)(cid:396)(cid:286) (cid:346)(cid:258)(cid:448)(cid:286) (cid:271)(cid:286)(cid:286)(cid:374) (cid:373)(cid:381)(cid:396)(cid:286) (cid:396)(cid:286)(cid:272)(cid:286)(cid:374)(cid:410) (cid:272)(cid:258)(cid:367)(cid:367)(cid:400) (cid:258) (cid:858)(cid:346)(cid:286)(cid:258)(cid:367)(cid:410)(cid:346) (cid:367)(cid:349)(cid:364)(cid:286) (cid:449)(cid:349)(cid:410)(cid:346)(cid:349)(cid:374) roles and responsibilities within the construction industry to examine their views of the landscape of the construction industry and its relationship to the health and wellbeing of the workforce. Through exploring two key themes; the construction industry as anti-health promoting and understanding industry specific health issues, greater insight into the challenges that exist within construction for promoting positive employee health and wellbeing are explored. The unique insights (cid:381)(cid:296) (cid:410)(cid:346)(cid:381)(cid:400)(cid:286) (cid:858)(cid:349)(cid:374)(cid:400)(cid:349)(cid:282)(cid:286)(cid:859) (cid:410)(cid:346)(cid:286) industry provides a clear exposition of the challenges faced by those seeking to construct better health and wellbeing and we argue that only through understanding the structural constraints of the industry in this way can the possibilities and potentials for undertaking health promotion work be fully embedded within the industry in order to help create meaningful change for both employees and the industry as a whole.
Two-phase simulations of the full load surge in Francis turbines

At off-design conditions, Francis turbines experience cavitation which may reduce the power output and can cause severe damage in the machine. Certain conditions can cause self-excited oscillations of the vortex rope in the draft tube at full load operating point. For the presented work, two-phase simulations are carried out at model scale on a domain ranging from the inlet of the spiral case to the outlet of the draft tube. At different locations, wall pressure measurements are available and compared to the simulation results. Furthermore, the dynamics of the cavity volume in the draft tube cone and at the trailing edge of the runner blades are investigated by comparing with high speed visualization. To account for the selfexcited behaviour, proper boundary conditions need to be set. In this work, the focus lies on the treatment of the boundary condition at the inlet. In the first step, the dynamic behaviour of the cavity regions is investigated using a constant mass flow. Thereafter, oscillations of the total pressure and mass flow rate are prescribed using various frequencies and amplitudes. This methodology enables to examine the response of the cavity dynamics due to different excitations. It can be observed that setting a constant mass flow boundary condition is not suitable to account for the self-excited behaviour. Prescribing the total pressure has the result that the frequency of the vapour volume oscillation is the same as the frequency of the excitation signal. Contrary to that, for an excitation with a mass flow boundary condition, the response of the system is not equal to the excitation.
Probabilistic Two-Ray Model for Air-to-Air Channel in Urban Drone Networks

For reliable and robust communication in drone networks, accurate and realistic channel models are indispensable. We herein propose a probabilistic two-ray (PTR) path loss model for drone-based air-to-air (AA) propagation channels, facing built-up urban environments. Based on a statistical urban layout model, the PTR path loss model applies to suburban, urban, dense urban, and high-rise urban scenarios. In the model, the path loss consists of the loss of the deterministic line-of-sight (LOS) path and probabilistic reflected path, where the reflected waves can impinge on the rooftop of buildings as well as the ground. The good agreements between our model and ray-tracing simulations demonstrate that the proposed model can serve as a useful tool for accurate and generic path loss prediction for aerial platforms in urban scenarios. Moreover, we extract the shadowing factor through numerous simulations and establish an altitude-dependent shadowing model, for predicting shadowing effects caused by buildings. The result shows that the proposed shadowing model is highly consistent with the measurement-based model, which indicates rationality and accuracy.
The Effect of Contextual Mobile Advertising on Purchase Intention: The Moderating Role of Extroversion and Neuroticism

Contextual mobile advertising, with the advantages of high interactivity and immersive experience, is the mainstream trend of future Internet advertising. Current studies have explored the benefits of contextual mobile advertising while lacking the analysis of contextual mobile advertising factors on consumer purchase intentions. This study investigates the mechanisms by which the characteristics of contextual mobile advertising evoke consumers' purchase intentions through advertising attitudes to reveal how extroversion and neuroticism in personal traits moderate the relationship between characteristics of contextual mobile advertising and advertising attitudes. Based on a sample of 543 community residents with mobile shopping experience in China, this study uses structural equation modeling to validate the relationships between the variables and draws conclusions. The findings help advertisers to grasp the important characteristics of contextual mobile advertising, improve consumers' attitudes toward advertising, and enhance purchase intentions. Furthermore, it is possible to expand perceptions of the effectiveness of contextual mobile advertising among consumers with different personality traits.
Identifying Environmental Factors Limiting Recovery of an Imperiled Estuarine Fish

Correctly identifying the environmental factors that limit population growth and recovery of imperiled species is an essential element of any targeted conservation program. Abundance index values for delta smelt (Hypomesus transpacificus), an imperiled fish in the upper San Francisco Estuary, have exhibited substantial inter-annual variation and the population is now at historically low numbers. Drawing from conceptual ecological models, we developed and applied a new multivariate analytical technique that incorporates a fundamental characteristic of limiting environmental factors– recognition that certain factors influence abundance in certain seasons or years, but they may have no influence on the species’ performance at other times. We observe that delta smelt occasionally experience years with population size increases, despite their ongoing long-term downward trajectory in numbers. The differences in environmental conditions that occur in years that prompt different population responses can provide insight into the environmental factors that limit species recovery. Nine temporally and spatially explicit covariates emerged from analyses that explain changes in inter-annual delta smelt abundance indices. We contrast those environmental factors with the factors that influence occupancy because distinguishing and focusing conservation actions on factors affecting delta smelt performance, rather than occupancy, should lead to the implementation of management and habitat-restoration actions that are more likely to benefit the fish. We think that the approach taken in this study can be a model for other species where salient data are limited and information needs are pressing.
How Do Psychological Cognition and Institutional Environment Affect the Unsafe Behavior of Construction Workers?—Research on fsQCA Method

The frequent occurrence of safety accidents is a global problem, and unsafe behavior is the main cause of accidents, which has been unanimously recognized by academia and industry. However, the previous research on unsafe behavior focused on analyzing the linear effects of variables on the results, and it was difficult to systematically analyze the complex mechanism of the results generated by the coupling of each variable. The problem of how to avoid unsafe behavior of construction workers has not been effectively solved. Based on the configuration perspective, on-site observation is organized, 164 construction workers are taken as case samples, the traditional regression analysis method is abandoned, and the fuzzy set qualitative comparative analysis method is used to integrate the theoretical framework of social cognition. From the perspective of psychological cognition and institutional environment, this paper discusses the differential matching of construction workers’ safety attitude, safety motivation, institutional control, safety training, and safety climate, and exploring the causal complex mechanisms that improve unsafe behavior among construction workers. The results show that: (1) The unsafe behavior of construction workers is the result of multiple factors. A single influencing factor does not constitute a necessary condition for the unsafe behavior of construction workers; (2) the path leading to the unsafe behavior phenomenon is not unique. Therefore, the high and unsafe behavior configuration of construction workers is summarized as “psychological cognition scarcity type,” “institutional environment scarcity type,” and “attitude-climate scarcity type”; (3) compared with “psychological cognitive scarcity type” and “institutional environment scarcity type,” “attitude-climate scarcity type” is more likely to cause unsafe behavior of construction workers; (4) a lower level of safety attitude or safety climate is more likely to cause high and unsafe behavior of construction workers; and (5) the non-high and unsafe behavior driving mechanism for construction workers is “comprehensive,” and there is an asymmetric relationship with the driving mechanism of the unsafe behavior of high construction workers. The research conclusions of this paper can help to broaden the theoretical framework of social cognition and provide new ideas and methods for how to improve unsafe behavior.
Effect of Glomerular Filtration Rate by Different Equations on Prediction Models for End-Stage Renal Disease in Diabetes

Background and Objectives The study aimed to evaluate the performance of a predictive model using the kidney failure risk equation (KFRE) for end-stage renal disease (ESRD) in diabetes and to investigate the impact of glomerular filtration rate (GFR) as estimated by different equations on the performance of the KFRE model in diabetes. Design, Setting, Participants, and Measurements A total of 18,928 individuals with diabetes without ESRD history from the UK Biobank, a prospective cohort study initiated in 2006–2010, were included in this study. Modification of diet in renal disease (MDRD), chronic kidney disease epidemiology collaboration (CKD-EPI) or revised Lund–Malmö (r-LM) were used to estimate GFR in the KFRE model. Cox proportional risk regression was used to determine the correlation coefficients between each variable and ESRD risk in each model. Harrell’s C-index and net reclassification improvement (NRI) index were used to evaluate the differentiation of the models. Analysis was repeated in subgroups based on albuminuria and hemoglobin A1C (HbA1c) levels. Results Overall, 132 of the 18,928 patients developed ESRD after a median follow-up of 12 years. The Harrell’s C-index based on GFR estimated by CKD-EPI, MDRD, and r-LM was 0.914 (95% CI = 0.8812–0.9459), 0.908 (95% CI = 0.8727–0.9423), and 0.917 (95% CI = 0.8837–0.9496), respectively. Subgroup analysis revealed that in diabetic patients with macroalbuminuria, the KFRE model based on GFR estimated by r-LM (KFRE-eGFRr-LM) had better differentiation compared to the KFRE model based on GFR estimated by CKD-EPI (KFRE-eGFRCKD-EPI) with a KFRE-eGFRr-LM C-index of 0.846 (95% CI = 0.797–0.894, p = 0.025), while the KFRE model based on GFR estimated by MDRD (KFRE-eGFRMDRD) showed no significant difference compared to the KFRE-eGFRCKD-EPI (KFRE-eGFRMDRD C-index of 0.837, 95% CI = 0.785–0.889, p = 0.765). Subgroup analysis of poor glycemic control (HbA1c >8.5%) demonstrated the same trend. Compared to KFRE-eGFRCKD-EPI (C-index = 0.925, 95% CI = 0.874–0.976), KFRE-eGFRr-LM had a C-index of 0.935 (95% CI = 0.888–0.982, p = 0.071), and KFRE-eGFRMDRD had a C-index of 0.925 (95% CI = 0.874–0.976, p = 0.498). Conclusions In adults with diabetes, the r-LM equation performs better than the CKD-EPI and MDRD equations in the KFRE model for predicting ESRD, especially for those with macroalbuminuria and poor glycemic control (HbA1c >8.5%).