Miracle-dz/UniFAR-FTUs huggingface dataset:
Fatigue Design of Modular Bridge Expansion Joints

Experimental and analytical research was recently performed to develop performance-based specifications and commentary for the fatigue design of modular bridge expansion joints (MBEJ). The resulting proposed fatigue-design and test specifications resulting from this research are discussed. These specifications are intended for integration into the present AASHTO Load and Resistance Factor Design (LRFD) Bridge Design Specifications. For consistency with the bridge design specifications, the proposed MBEJ fatigue-design specifications used the same fatigue-design truck as was used by the present AASHTO bridge specifications. However, one important modification of the AASHTO truck loading for MBEJ is the explicit recognition that the rear axles of the HS series trucks actually represent tandem axles. A simplified method to estimate the distribution factor (i.e., the fraction of the range of the design-wheel load assigned to a single “centerbeam”) is recommended. Dynamic impact on both the vertical and horizontal direction is discussed. Also, guidance on structural analysis of MBEJ, good detailing practice, and fatigue resistance and testing are presented. MBEJ designed under the proposed specifications should be resistant to fatigue cracking. The additional material and the improved details, which will be required to comply with the proposed specifications, are not expected to increase the initial first cost of MBEJ substantially.
Designing Culture: The Technological Imagination at Work

The renowned cultural theorist and media designer Anne Balsamo maintains that technology and culture are inseparable; those who engage in technological innovation are designing the cultures of the future. Designing Culture is a call for taking culture seriously in the design and development of innovative technologies. Balsamo contends that the wellspring of technological innovation is the technological imagination, a quality of mind that enables people to think with technology, to transform what is known into what is possible. She describes the technological imagination at work in several multimedia collaborations in which she was involved as a designer or developer. One of these entailed the creation of an interactive documentary for the NGO Forum held in conjunction with the UN World Conference on Women in Beijing in 1995. (That documentary is included as a DVD in Designing Culture.) Balsamo also recounts the development of the interactive museum exhibit XFR: Experiments in the Future of Reading, created by the group RED (Research in Experimental Documents) at Xerox PARC. She speculates on what it would mean to cultivate imaginations as ingenious in creating new democratic cultural possibilities as they are in creating new kinds of technologies and digital media. Designing Culture is a manifesto for transforming educational programs and developing learning strategies adequate to the task of inspiring culturally attuned technological imaginations.
Wildlife recognition from camera trap data using computer vision algorithms

Camera trap, a digital camera that is automatically triggered by activities around, has been widely used in wildlife conservation for decades to capture animals on film for later analysis. With increasingly available vision data (photos and videos) from camera traps in recent years, it becomes prohibitively costly to manually extract useful information from these data. In this project, I aim to help automate the process of knowledge extraction from the camera trap data with the help of deep learning models. Specifically, a popular convolutional neural network (CNN) architecture called YOLOv3 was used as the pre-trained model through transfer learning. The model was then fine-tuned on thousands of camera trap images that I primitively obtained from a crowdsourced Zooniverse dataset and subsequently labeled using an object tagging tool. Compared to previously proposed work of wildlife recognition, my model further performs wildlife detection by locating the object detected and adding a bounding box in addition to identifying the species. As a result, the trained model is applied to photos of wildlife taken by myself for predictions, and results show that the model is able to accurately and confidently classify and locate multiple wildlife in both photos and real-time videos.
Influence of Injection Well Location on CO2 Geological Storage Efficiency

An analysis of the influence of injection well location on CO2 storage efficiency was carried out for three well-known geological structures (traps) in deep aquifers of the Lower Jurassic Polish Lowlands. Geological models of the structures were used to simulate CO2 injection at fifty different injection well locations. A computer simulation showed that the dynamic CO2 storage capacity varies depending on the injection well location. It was found that the CO2 storage efficiency for structures with good reservoir properties increases with increasing distance of the injection well from the top of the structure and with increasing depth difference to the top of the structure. The opposite is true for a structure with poor reservoir properties. As the quality of the petrophysical reservoir parameters (porosity and permeability) improves, the location of the injection well becomes more important when assessing the CO2 storage efficiency. Maps of dynamic CO2 storage capacity and CO2 storage efficiency are interesting tools to determine the best location of a carbon dioxide injection well in terms of gas storage capacity.
PLECS-piece-wise linear electrical circuit simulation for Simulink

In this paper a new toolbox, PLECS, for the fast simulation of power electronic circuits under Simulink is presented. This toolbox provides the means for modeling large power electronic systems containing both electrical circuits and controllers. The program is based on a state-space formulation for circuits that consist of linear elements (RLC), transformers, sources, meters and ideal switches. Diodes, thyristors, IGBTs and other nonlinear elements such as saturable inductors can be assembled by combining linear elements and switches. Thus, a piece-wise linear model is attained which leads to a stable and fast simulation. An attached benchmark simulation demonstrates the capability of PLECS.
Characteristics of patients who dropped out after multidisciplinary pain management in Japan: A prospective cohort study

BACKGROUND: Because regular visits to distant hospitals may be a burden to patients, both in terms of time and cost, some patients with chronic musculoskeletal pain may discontinue multidisciplinary pain treatment, unable to maintain motivation to attend. OBJECTIVE: To evaluate and compare the pre-program characteristics of patients who dropped out and patients who continued treatment, thereby clarifying the characteristics of patients at risk of dropping out. METHODS: A multidisciplinary pain management treatment program was implemented for patients at the Pain Management Center, Hoshi General Hospital. From April 2015 to March 2018, 23 patients participated in the program. Twelve of the 23 patients lived outside the prefecture where the hospital is located. Of these 12 patients, five completed the program, while seven did not. We compared the dropout and continuation groups in terms of patient characteristics, pain severity, pain-related psychosocial factors, and quality of life. RESULTS: We found significant differences (p< 0.05) in median age, Japanese Orthopaedic Association Back Pain Evaluation Questionnaire walking ability dysfunction score, and Roland-Morris Disability Questionnaire score. CONCLUSIONS: The characteristics of patients who dropped out were older age, walking ability dysfunction, and low quality of life associated with low back pain.
Technological Feasibility of Couscous-Algae-Supplemented Formulae: Process Description, Nutritional Properties and In Vitro Digestibility

The aim of this work was to develop functional couscous in a traditional Tunisian manner (hand rolling), enriched in algae biomass (6% w/w). Four Chlorella vulgaris (C. vulgaris) biomasses and one mixture of C. vulgaris and two macroalgae biomasses (Ulva rigida and Fucus vesiculosus) were used. The C. vulgaris strain was subjected to random mutagenesis and different culture conditions (Allmicroalgae), resulting in different pigmentations and biochemical compositions. Couscous samples were characterized in terms of nutritional properties, oscillatory rheology properties and digestibility. All biomasses provided a significant supplementation of nutrients and excellent acceptance. The enrichment resulted in lower firmness, higher viscoelastic functions (G′ and G″) and a significant improvement in the cooking quality. Major differences between couscous samples with different microalgae were observed in protein and mineral contents, fully meeting Regulation (EC) No. 1924/2006 requirements for health claims made on foodstuffs. The amount of digested proteins was also higher in algae-containing samples. The fatty acid profile of the enriched couscous varied in a biomass-specific way, with a marked increase in linolenic acid (18:3 ω3) and a decrease in the ω6/ω3 ratio. Sensory analysis revealed that microalgae-containing products could compete with conventional goods with an added advantage, that is, having an ameliorated nutritional value using algae as a “trendy” and sustainable ingredient.
Complementary Split Ring Resonator based Sensor for Crack Detection

In this paper, the performance of Complementary Split Ring Resonator (CSRR) based sensor is explored by varying the geometrical parameters of a sub millimeter crack. Behavior analysis of the CSRR based sensor is performed by variation in the parameters of crack. Variation in resonant frequency of sensor is observed in every case and is noteworthy for our purpose. This signifies the sensor’s ability to detect crack of different geometrical parameters on a metal surface.The effectiveness of the sensor is being contemplated through this approach which is appreciable. An illustrious performance of the crack detection sensor has been discovered in this analysis. Simulated results show the feasibility of detecting very small cracks upto 25 􀟤m width, in the metallic surfaces.
Revolutionary flywheel energy storage system for quality power

With the development in the 1970s and 1980s of fibre-reinforced composite materials such as carbon, Arimid and glass fibres, interest in the potential of flywheels in energy storage systems was rekindled. The author describes how it is the use of these materials in combination that gave the technology a potential way forward.
Kinematic Approach to Horizontal Curve Transition Design

Research has shown that vehicles shift laterally in the traffic lane during their entry to (or exit from) a horizontal curve. In addition, research indicates that most drivers momentarily adopt a path radius that is sharper than that of the roadway curve. A study was undertaken to investigate the causes of lateral shift and sharp path radii and to determine if they can be minimized (or eliminated) by modifying the horizontal curve transition design. From a review of the driver–vehicle control process, it was concluded that lane shift is due to unbalanced lateral accelerations that act on the vehicle as it enters the curve. These accelerations result from gravity, as effected through roadway superelevation, and side friction, caused by the steer angle of the vehicle. Kinematic models of lateral acceleration, velocity, and shift were developed. The calibrated models were used to develop design guidelines for superelevation rate and superelevation runoff location.
A MAC Layer Protocol For Smart Indoor Inventory Management System

The indoor inventory system is gaining more research attention and commercial value with the development of IoT. In this thesis, we presented the design of a MAC protocol that allows synchronized transmission of location and sensing data in a wireless positioning and sensor network for an indoor inventory system. The network supports real-life industrial applications and provides a highly specific positioning method.In the network, mobile sensing tags are connected to smart readers that performs localization of tags and gathers sensing data from the tags. The readers are connected to the back-end cloud. The proposed MAC serves multiple classes of mobile tags with different priorities and latency requirements. These tags transmit critical, position and sensing data with different QoS requirements. The proposed MAC is a hybrid MAC that offers contention-based period for tag discovery and scheduled period for the transmission of sensing data with guaranteed latency. We conducted simulation to evaluate the performance of different methods of discovery process and their impact on latency assurance. We also developed a queuing model to analyze the relationship between parameters, acquiring parameters through experiment, and calculation of boundary values.Simulation using MatLabTM software suggests that the joining period in design can increase the transmission success rate of high priority messages at the cost of a slight increment in the delay of low priority messages. Preliminary analysis suggests that by adaptively allocating the channel resources of the network to three types of tags, service efficiency can be improved. This result also guides the direction for further improvement.We explored the performance of two options considered currently, which is selecting the discovery process according to modulo result of unique 16-bit tag ID and random select of an available discovery process. In the current environment where each tag does not have any information about other tags inside the network, the two methods have the same effect on avoiding collisions that could happen in a single discovery cycle.The proposed MAC layer protocol can provide the best service when the available discovery process in the discovery cycle is for initialization and resetting. For an emergency, the joining period designs can still ensure a success rate for critical messages to be over 90%. Hence, the simulation results indicate the joining period method is able to improve MAC-layer performance.
An agent-based negotiation approach to integrate process planning and scheduling

This paper presents the development of an agent-based negotiation approach to integrate process planning and scheduling (IPPS) in a job shop kind of flexible manufacturing environment. The agent-based system comprises two types of agents, part agents and machine agents, to represent parts and machines respectively. For each part, all feasible manufacturing processes and routings are recorded as alternative process plans. Similarly, alternative machines for an operation are also considered. With regard to the scheduling requirements and the alternative process plans of a part, the proposed agent-based IPPS system aims to specify the process routing and to assign the manufacturing resources effectively. To establish task allocations, the part and machine agents have to engage in bidding. Bids are evaluated in accordance with a currency function which considers an agent's multi-objectives and IPPS parameters. A negotiation protocol is developed for negotiations between the part agents and the machine agents. The protocol is modified from the contract net protocol to cater for the multiple-task and many-to-many negotiations in this paper. An agent-based framework is established to simulate the proposed IPPS approach. Experiments are conducted to evaluate the performance of the proposed system. The performance measures, including makespan and flowtime, are compared with those of a search technique based on a co-evolutionary algorithm.
Institutional investor network, analyst public information and extreme risks

Abstract This paper builds the institutional investor network on the basis of the common stock holdings of mutual funds with large positions. Institutional investors share and interact private information through social networks. Seen from separating private and public information, the effects of private information sharing in institutional investor networks and the effects of public information diffusion on extreme risks are examined, respectively. Then, the integrated impact of institutional investor information sharing with analyst on extreme risks is analysed. Empirical research has found that analyst public information spread will decrease the probability of extreme risks. The information sharing in social network of institutional investors will restrain stock market extreme risks. The closer network of institutional investors lower the influence of analyst public information on extreme risks. In addition, we also found that stock liquidity has weakened the inhibition of fund network information sharing on extreme risks. The research results provide reference for the authorities to regulate market participant behaviours so as to avoid risks.
TEMPERATURE FIELDS, EXCHANGES AND DEFORMATIONS OF A PRECISE LENGTH COMPARATOR MICROSCOPE

In this article the influence of internal thermal sources of line position detection microscope onto scale error calibration accuracy is analyzed. Short description of the microscope temperature fields and thermal body deformation modelling methodology is proposed, evaluating internal heat sources of microscope. The modelling results graphs showing the influence heat sources onto microscope temperature field. The resulting temperature deformations are given. Draw conclusions about the processes in question affect the scale calibration accuracy. http://dx.doi. org/10.5755/j01.mech. 17.3. 503
Plenary Session: Four Perspectives on MOOCs MOOCs: What lies beyond the trough of disillusionment?

With universities all over the world now gearing up to offer MOOCs we are reaching the ‘peak of inflated expectations’ that is followed, in the Technology Hype Cycle, by the ‘trough of disillusionment’. But what lies beyond that? Will MOOCs have any lasting impact on higher education? Will universities offering MOOCs ever climb the ‘slope of enlightenment’ and reach the ‘plateau of productivity’ that complete the cycle?
Identification of NUTF2 as a Candidate Diagnostic and Prognostic Biomarker Associated with Immune Infiltration in Head and Neck Squamous Cell Carcinoma

Background Head and neck squamous cell carcinoma (HNSC) is one of the most common tumors worldwide. Nuclear transport factor 2 (NUTF2) plays a key role in cell death and immune processes. However, few reports have studied correlations between NUTF2 gene expression and the occurrence and development of HNSC. Methods The expression of NUTF2 was analyzed using publicly available databases, including the Cancer Genome Atlas and Human Protein Atlas and Gene Expression Omnibus (GEO) database, which was validated by RT-PCR. We evaluated the functions of NUTF2 with Kaplan–Meier curve, logistic regression were used to study the relationship between clinicopathological features and the expression of NUTF2. Cox regression analyses were used to identify the effects of NUTF2 expression on survival. Gene Ontology and Gene Set Enrichment Analysis were used to explore relevant biological pathways. The relationship between NUTF2 and tumor-infiltrating immune cells was investigated with on-line bioinformatic tools. Results NUTF2 was significantly upregulated in HNSC lesions and is associated with tumor size (P < 0.01). Increased expression of NUTF2 was linked to shorter overall and progress-free survival in HNSC. Cox regression analyses revealed that NUTF2 is an independent prognostic factor in HNSC. GSEA analysis demonstrated that NUTF2 negatively regulates several immune pathways. NUTF2 was correlated with the infiltrating levels of B cells and CD8+ T cells and was negatively correlated with diverse immune marker sets in HNSC. Conclusion NUTF2 is highly expressed in HNSC and correlates with poor prognosis. Correlation with immune functions suggests that NUTF2 may serve as a biomarker and therapeutic target for HNSC.
Creativity & Innovation: Variety, Amount, Emphasis, Impact Assessment

Method: 66 global firms, of any size, were randomly selected from all global firms headquartered in Tokyo, Silicon Valley environs, and Berlin. 40 employees in each of the 66 were randomly selected and given a survey instrument measuring which of 60 creativity models, which of 60 innovation models, they or others used at work how frequently and intensely, and which, in their opinion, produced the most novelty of results as seen and rewarded by their bosses and firms. Results: Six patterns (in terms of which of the 120 models were present and used intensely) appeared when the data were hierarchically clustered and factor analyzed. Six clusters, each having from 6 to 11 firms, were found and put in order by amount of total novelty achieved. All firms in each cluster had the models indicated on the results table in this paper (plus extra models less intensively done and/or producing less overall novelty of result). Fill in items were used to specify in this paper what differences besides creativity and innovation models used, distinguished the clusters. Research questions: Is creativity one thing as actually done by firms? Is innovation one thing as actually done by firms? Is the ratio - of amount of models (for creativity versus innovation), of the intensity of applying of models (for creativity versus innovation) - descriptive-of/predictive - of differences in total novelty achieved among firms? Do all firms evolve along some sort of models of creativity/innovation scale when they come to produce more overall novelty achieved? Which extant models of creating or innovating in a firm, if done more intensely would most improve total novelty achieved? Which missing models of creating and innovating in a firm, if done somewhat would most improve total novelty achieved? Would more novelty be achieved by more intensely doing existing model or by doing models now missing?
Evaluating the Impact of Biofortification: A Meta-analysis of Community-level Studies on Quality Protein Maize (QPM)

Biofortification, or the genetic improvement of the nutritional quality of food crops, is a promising strategy to combat undernutrition, particularly among the rural poor in developing countries. However, traditional methods of impact assessment do not apply to biofortified crops as little or no yield increases are expected. Significant progress has been made to develop maize varieties with improved protein quality, collectively known as quality protein maize (QPM). Evidence for the impact of QPM at the community level, as demonstrated by randomized, controlled studies, was evaluated using meta-analysis. A new and generalizable effect size was proposed to quantify the impact of QPM on a key outcome, child growth. The results indicated that consumption of QPM instead of conventional maize leads to an 8% (95% CI: 4-12%) increase in the rate of growth in height and a 9% (95% CI: 4-12%) increase in the rate of growth in weight in infants and young children with mild to moderate undernutrition from populations in which maize is a significant part of the diet. These results are the first step in evaluating the potential economic impact of QPM by establishing and quantifying a link between use of the improved crop and nutritional outcomes. QPM can serve as a model for other biofortification efforts, and in particular, the conceptual framework and methodologies for impact assessment are directly applicable to other biofortified crops.