Miracle-dz/UniFAR-FTUs huggingface dataset:
Assisting design by analogy

This paper describes research into situated analogy-making and its application to digital design assistants. It is claimed that computational design support systems that provide designers with conceptually distant but contextually appropriate information can assist in designers with the synthesis of creative designs. This claim is supported by an example application of situated analogy-making to architectural design, adapting a solarium using analogy. The potential advantages of analogical design assistants are discussed independently of implementation and a number of possible directions and challenges for future work in design by computational analogy are presented. Conference theme: Digital architecture.
Multi-stream part-fused graph convolutional networks for skeleton-based gait recognition

Gait recognition, a task of identifying people through their walking pattern, has attracted more and more researchers' attention. At present, most skeleton-based gait recognition approaches extract gait features from merely joint coordinates. However, the information, e.g. bone and motion, is equally instructive and discriminative for gait recognition. Thus, this paper proposes a novel multi-stream part-fused graph convolutional network, MS-Gait, to fuse part-level information and capture multi-order features from skeleton data. To be specific, we integrate a channel attention learning mechanism into the graph convolutional networks (GCN) to improve the representational power. In addition, part-level information is merged by capturing features from the skeleton graph and its subgraphs concurrently. Finally, a multi-stream strategy is proposed to model joint, bone, and motion dynamics simultaneously, which is proven to effectively improve the recognition accuracy. On the popular CASIA-B dataset, extensive experiments demonstrate that our method can achieve state-of-the-art performance and is robust to confounding variations.
A Process Evaluation of a Learning Community Program: Implemented as Designed?

Learning communities can be useful to counter some of the challenges encountered by first-semester students as they transition to college. This 2-year process evaluation examines the launch of a campus-wide learning community initiative for developmental reading students at a community college in the USA. Students, instructors, and administrators were interviewed about the implementation of the program, and program-related materials were reviewed. Findings suggested ways to enhance the effectiveness of learning communities of the linked-course variety through program implementation that is more faithful to key design aspects. Suggestions include (1) implement team-teaching across linked courses; (2) carry out an integrated curriculum across courses; (3) provide in-depth and continued instructor training as well as specialized resources; (4) expand support services available to students and require them to use at least some; and (5) create tools/methods for instructors and administrators to regularly assess processual aspects rather than just program outcomes.
The Relative Performance of a Benchtop Scanning Monochromator and Handheld Fourier Transform Near-Infrared Reflectance Spectrometer in Predicting Forage Nutritive Value

Advanced manufacturing techniques have enabled low-cost, on-chip spectrometers. Little research exists, however, on their performance relative to the state of technology systems. The present study compares the utility of a benchtop FOSS NIRSystems 6500 (FOSS) to a handheld NeoSpectra-Scanner (NEO) to develop models that predict the composition of dried and ground grass, and alfalfa forages. Mixed-species prediction models were developed for several forage constituents, and performance was assessed using an independent dataset. Prediction models developed with spectra from the FOSS instrument had a standard error of prediction (SEP, % DM) of 1.4, 1.8, 3.3, 1.0, 0.42, and 1.3, for neutral detergent fiber (NDF), true in vitro digestibility (IVTD), neutral detergent fiber digestibility (NDFD), acid detergent fiber (ADF), acid detergent lignin (ADL), and crude protein (CP), respectively. The R2P for these models ranged from 0.90 to 0.97. Models developed with the NEO resulted in an average increase in SEP of 0.14 and an average decrease in R2P of 0.002.
BIG DATA SYSTEM INFRASTRUCTURE AT EXTREME SCALES

Rapid advances in digital sensors, networks, storage, and computation along with their availability at low cost is leading to the creation of huge collections of data – dubbed as Big Data. This data has the potential for enabling new insights that can change the way business, science, and governments deliver services to their consumers and can impact society as a whole. This has led to the emergence of the Big Data Computing paradigm focusing on sensing, collection, storage, management and analysis of data from variety of sources to enable new value and insights. To realize the full potential of Big Data Computing, we need to address several challenges and develop suitable conceptual and technological solutions for dealing them. Today’s and tomorrow’s extreme-scale computing systems, such as the world’s fastest supercomputers, are generating orders of magnitude more data by a variety of scientific computing applications from all disciplines. This dissertation addresses several big data challenges at extreme scales. First, we quantitatively studied through simulations the predicted performance of existing systems at future scales (for example, exascale 10 flops). Simulation results suggested that current systems would likely fail to deliver the needed performance at exascale. Then, we proposed a new system architecture and implemented a prototype that was evaluated on tens of thousands nodes on par with the scale of today’s largest supercomputers. Micro benchmarks and real-world applications demonstrated the effectiveness of the proposed architecture: the prototype achieved up to two orders of magnitude higher data movement rate than existing approaches. Moreover, the system prototype was incorporated with features that were not well supported in conventional systems, such as distributed metadata management, distributed caching, lightweight provenance, transparent compression, acceleration through GPU encoding, and parallel serialization. Towards exploring the proposed architecture at millions of node scales, simulations were conducted and evaluated with a variety of workloads, showing near linear scalability and orders of
A Micro-Level Explanation for Suicidal Ideation Based on Marriage-Squeeze and Social Support Among Rural Men in China

Higher sex ratio at birth often leads to sex imbalance and a severe squeeze on the marriage market. Up to now, no systematic studies have examined the relationship between marriage squeeze and suicidal ideation among rural men in a context of sex imbalance. Using surveys conducted in Chaohu (Anhui Province) and Ankang (Shaanxi Province) in China, this study analyzed the impact of marriage squeeze and social support on suicidal ideation among rural men. The perceived marriage squeeze significantly and positively affected suicidal ideation and the perceived social support negatively affected suicidal ideation among married and unmarried rural men. Objective social support did not significantly affect suicidal ideation among married men; however, it negatively affected suicidal ideation among unmarried men. Marriage squeeze increased the incidence of suicidal ideation among rural men, but perceived social support acted as a protective factor against suicidal ideation. These findings support the main effect hypothesis of social support. Objective social support is a double-edged sword, which may increase suicidal ideation incidence among rural men. The article ends with the conclusions and limitations of this study.
Analytical soliton solutions for cold bosonic atoms (CBA) in a zigzag optical lattice model employing efficient methods

This research finds an equation in a continuous domain and a discrete equation governing the system of cold bosonic atoms (CBA) in a zigzag optical lattice using a continuum approximation. Many solutions to the equation were obtained using two distinct methods: the three-wave approach (multi-wave interaction, rational solutions, and rational solution interaction) and the extended sub-equation method. These analytical approaches are more effective, consistent, and comprehensive mathematical tools for obtaining various exact closed-form solutions for a wide range of fractional space-time nonlinear evolution equations encountered in optical physics, condensed matter physics, and plasma physics. The solutions generated are in the form of hyperbolic and trigonometric solutions, and other-form solutions are obtained. Three-dimensional graphics and contour plots are often used to depict the graphical representations of the combined soliton solutions. These findings will aid our understanding of the dynamics of the zigzag optical grids and many other structures formed by colder bosonic atoms. The applied approaches are more simple, efficient, and straightforward to obtain the closed-form solutions for various nonlinear evolution equations in the fields of nonlinear sciences and physical engineering.
Application of Deep Learning Technology in Glioma for Healthcare Applications

Glioma is the most common primary brain tumor, and it's extremely dangerous for the patient's health. Magnetic Resonance Imaging (MRI) based glioma segmentation is an important tool for doctors to use when examining, analyzing, and diagnosing glioma's outward appearance both for the indoor and outdoor patients. Among other methods, deep learning-based glioma segmentation is the most widely used in literature. Therefore, in this paper, we have proposed glioma segmentation methods which is primarily based on deep learning more specifically convolution neural networks. A DM-DA-based cascade method for glioma segmentation based on 2DResUnet is proposed to address the problem of insufficient 3D spatial information acquisition in 2D full convolutional networks and the memory consumption problem of 3D full convolutional networks. Use of multiple-scale fusion mechanisms, DenseBlock, Attention, and multi-scale convolutional networks to segment gliomas at different stages and fixed region sampling to reduce the model's three-dimensionality in the Unet model using the glioma image's multi-sequence information, the convolutional network can better segment the tumor by using less memory. Use the BraTS18 data set for local five-fold cross-validation, and use the BraTS17 data set for official online evaluation. The evaluation results show that the average Dice Score of the edema, core and enhancement areas of the glioma segmentation results on the BraTS17 validation set by DM-DA-Unet achieves higher performance. The average sensitivity is also high, which is close to the best model segmentation effect on the BraTS17 validation set, and can accurately segment gliomas.
Right Heart Pulmonary Circulation Unit Response to Exercise in Patients with Controlled Systemic Arterial Hypertension: Insights from the RIGHT Heart International NETwork (RIGHT-NET)

Background. Systemic arterial hypertension (HTN) is the main risk factor for the development of heart failure with preserved ejection fraction (HFpEF). The aim of the study was was to assess the trends in PASP, E/E’ and TAPSE during exercise Doppler echocardiography (EDE) in hypertensive (HTN) patients vs. healthy subjects stratified by age. Methods. EDE was performed in 155 hypertensive patients and in 145 healthy subjects (mean age 62 ± 12.0 vs. 54 ± 14.9 years respectively, p < 0.0001). EDE was undertaken on a semi-recumbent cycle ergometer with load increasing by 25 watts every 2 min. Left ventricular (LV) and right ventricular (RV) dimensions, function and hemodynamics were evaluated. Results. Echo-Doppler parameters of LV and RV function were lower, both at rest and at peak exercise in hypertensives, while pulmonary hemodynamics were higher as compared to healthy subjects. The entire cohort was then divided into tertiles of age: at rest, no significant differences were recorded for each age group between hypertensives and normotensives except for E/E’ that was higher in hypertensives. At peak exercise, hypertensives had higher pulmonary artery systolic pressure (PASP) and E/E’ but lower tricuspid annular plane systolic excursion (TAPSE) as age increased, compared to normotensives. Differences in E/E’ and TAPSE between the 2 groups at peak exercise were explained by the interaction between HTN and age even after adjustment for baseline values (p < 0.001 for E/E’, p = 0.011 for TAPSE). At peak exercise, the oldest group of hypertensive patients had a mean E/E’ of 13.0, suggesting a significant increase in LV diastolic pressure combined with increased PASP. Conclusion. Age and HTN have a synergic negative effect on E/E’ and TAPSE at peak exercise in hypertensive subjects.
A 3D Smooth Mobility Model Based on Semi-random Circular Movement for FANETs

In recent years, the number of applications based on multiple unmanned aerial vehicles (UAVs) for cooperative mission execution has increased. In a search and rescue mission (SAR) scenario, the network solution based on Flying Ad Hoc Networks (FANETs) can meet the special requirements of this mission. However, due to the high cost of establishing a real experimental environment, network simulation is considered to be the most practical research method in most cases. For FANETs, modeling and simulation based on the mobility of a UAV in a specific scene have an important impact on the performance of routing protocols. Therefore, to develop an excellent FANETs routing protocol for SAR task scenarios, it is necessary to design a three-dimensional (3D) mobility model suitable for this scenario. This paper first analyzes the design requirements of FANETs 3D mobility model under the SAR task scene. According to these requirements, we proposed a 3DSRCM mobility model based on semi-random Circular Movement (SRCM). Based on the helix and pheromone, we design the track with its selection and switching mechanism for the model. Subsequently, we tested the relevant performance of the model according to the design requirements, and the test results proved that the model could truly simulate the movement behavior of UAV in the SAR scene, with excellent coverage and smooth three-dimensional trajectory, as well as relatively good spatial node distribution and network connectivity.
Evaluation of Membrane Treatment Technology to Optimize and Reduce Hypersalinity Content of Produced Brine for Reuse in Unconventional Gas Wells

Evaluation of Membrane Treatment Technology to Optimize and Reduce Hypersalinity Content of Produced Brine for Reuse in Unconventional Gas Wells. (August 2011) Uche Marian Eboagwu, B.S., University of Lagos, Nigeria Co-Chairs of Committee: Mr. David Burnett Dr. Gene Beck Over 18 billion barrels of waste fluids are generated annually from oil and gas production in the United States. As a large amount of water is used for oilfield operations, treating and reusing produced water can cut the consumption of fresh water in well sites. This research has helped to develop a membrane process train for a mobile produced water treatment unit for treating oilfield produced brine for reuse. To design the process train, over 30 sets of combination tests at pilot laboratory scale were performed using pretreatment, microfiltration and nanofiltration processes. Membrane performance was selected based on high flux separation efficiency, high tolerance for solids and fluid treatments. Over 95 % solids rejection and greater than 80 % oil removal efficiency were obtained in all these tests. Process train (pre-treatment and membrane) performance was monitored by chemical analysis of permeate models fitting experimental data for the process. From the results, hydrocarbon rejection was analyzed; total organic carbon rejection was 47.9 %, total carbon content averaged 37.3 % rejection and total inorganic carbon rejection was at 3.66 %. BTEX removal efficiency ranged from 0.98 % to 52.7 % with the progressive
Analyzing Topics and Sentiments from Twitter to Gain Insights to Refine Interventions for Family Caregivers of Persons with Alzheimer's Disease and Related Dementias (ADRD) During COVID-19 Pandemic

We randomly extracted Tweets mentioning dementia/Alzheimer's caregiving-related terms (n= 58,094) from Aug 23, 2019, to Sep 14, 2020, via an API. We applied a clustering algorithm and natural language processing (NLP) to publicly available English Tweets to detect topics and sentiment. We compared emotional valence scores of Tweets from before (through the end of 2019) and after the beginning of the COVID-19 pandemic (2020-). Prevalence of topics related to caregiver emotional distress (e.g., depression, helplessness, stigma, loneliness, elder abuse) and caregiver coping (e.g., resilience, love, reading books) increased, and topics related to late-stage dementia caregiving (e.g., nursing home placement, hospice, palliative care) decreased during the pandemic. The mean emotional valence score significantly decreased from 1.18 (SD 1.57; range -7.1 to 7.9) to 0.86 (SD 1.57; range -5.5 to 6.85) after the advent of COVID-19 (difference -0.32 CI: -0.35, -0.29). The application of topic modeling and sentiment analysis to streaming social media provides a foundation for research insights regarding mental health needs for family caregivers of a person with ADRD during COVID-19 pandemic.
Red harvester ant (Order: Hymenoptera) preference for cover crop seeds in South Texas

Harvester ants are known to selectively forage seeds, potentially impacting nearby plant community composition. In agricultural areas, harvester ants may be viewed as pests by foraging on crop seeds or as beneficials by preferentially removing weed seeds. However, little work has been done on harvester ant preferences for cover crop seeds. Local observations suggest that ants may take cover crop seeds, but no studies have evaluated ant agricultural impacts or seed preferences in the Lower Rio Grande Valley (LRGV). We examined red harvester ant (Pogonomyrmex barbatus Smith) preferences for commonly used cover crop seeds in the LRGV (vetch, oat, fescue, sunn hemp, and radish with wheatgrass as a control) and a commonly used bacterial seed inoculation treatment meant to increase root nodulation. We tested seed sets using choice tests housed in seed depots located within the foraging range of ant colonies with no prior exposure to the selected seeds. Of the evaluated cover crop seeds, wheatgrass and oat were the first to be removed entirely from the depot, with vetch remaining after 24 h. When we inoculated the two most preferred seeds to determine if there was a preference for non-inoculated seeds, we found no difference between inoculated and non-inoculated seeds. There were also significant changes in activity over time for both trials. These data indicate that harvester ant foraging preferences and activity can inform grower management recommendations regarding the risks of using certain cover crops and months sowing should be conducted in fields with known harvester ant presence.
Preclinical Validation of a Novel Injection-Molded Swab for the Molecular Assay Detection of SARS-CoV-2

During the COVID-19 public health emergency, many actions have been undertaken to help ensure that patients and health care providers have timely and continued access to high-quality medical devices to respond effectively. The development and validation of new testing supplies and equipment, including collection swabs, has helped to expand the availability and capability for various diagnostic, therapeutic, and protective medical devices in high demand during the COVID-19 emergency. Here, we report the initial validation of a new injection-molded anterior nasal swab, ClearTip™, that was experimentally validated in a laboratory setting as well as in independent clinical studies in comparison to gold standard flocked swabs. We have also developed an in vitro anterior nasal tissue model which offers a novel, efficient, and clinically relevant validation tool to replicate the clinical swabbing workflow with high fidelity, while being accessible, safe, reproducible, and time- and cost-effective. ClearTip™ displayed greater inactivated virus release in the benchtop model, confirmed by its greater ability to report positive samples in a small clinical study in comparison to flocked swabs. We also quantified the detection of biological materials, as a proxy for viral material, in multi-center pre-clinical and clinical studies which showed a statistically significant difference in one study and a reduction in performance in comparison to flocked swabs. Taken together, these results emphasize the compelling benefits of non-absorbent injection-molded anterior nasal swabs for COVID-19 detection, comparable to standard flocked swabs. Injection-molded swabs, as ClearTip™, could have the potential to support future swab shortages, due to its manufacturing advantages, while offering benefits in comparison to highly absorbent swabs in terms of comfort, limited volume collection, and potential multiple usage.
Artist Names as Human Brands: Brand Determinants, Creation and co-Creation Mechanisms

Considering all transactions related to modern and contemporary visual artists mediated by galleries in Italy between 2007 and 2012, we propose an empirical measure of artist brand and explore its relationship with artist-specific characteristics, such as talent, fame, and popularity, through a structural model. We find that artist brand depends positively on talent, fame, and popularity. Moreover, we find that a co-creation mechanism is at work in the Italian art market, where galleries choose their specialization strategies in picking their artist portfolios. We interpret our findings in light of a novel conceptual framework of human branding and co-creation in the visual art market.
Mechatronics Design of Intelligent Robotic Gripper

This work presents multi-functional robot arm gripper design along with vision and tactile sensor for efficient grasping and manipulation tasks. The design emulates human’s hand fingers structure using linkages and direct drive through slider-crank mechanism transmission. The structural elements are optimized for a finest performance in motion and force transmissibility of the gripper fingers. The main future of this design is its reliability to grasp and manipulate unknown object while its system complexity is reduced. The gripper has a tool change fixture incorporated into its palm, which will reduce time wastage and do assembling in one go. The gripper is equipped with two cameras in its palm; subsequently it will efficiently seek the target object and perform its prehensile task with intelligently determined grasping force.