Miracle-dz/UniFAR-FTUs huggingface dataset:
Using dual-task gait to recognize Alzheimer’s disease and mild cognitive impairment: a cross-sectional study

Background Gait is a potential diagnostic tool for detecting mild cognitive impairment (MCI) and Alzheimer’s disease (AD). Nevertheless, little attention has been paid to arm movements during walking, and there is currently no consensus on gait asymmetry. Therefore, in this study, we aimed to determine whether arm motion and gait asymmetry could be utilized for identifying MCI and AD. Methods In total, 102 middle-aged and elderly individuals were included in the final analysis and were assigned to the following three groups: AD (n = 27), MCI (n = 35), and a normal control group (n = 40). Gait and cognitive assessments were conducted for all participants. Gait detection included a single-task gait with free-speed walking and a dual-task gait with adding a cognitive task of successive minus seven to walking. Original gait parameters were collected using a wearable device featuring the MATRIX system 2.0. Gait parameters were shortened to several main gait domains through factor analysis using principal component extraction with varimax rotation. Subsequently, the extracted gait domains were used to differentiate the three groups, and the area under the receiver operating characteristic curve was calculated. Results Factor analysis of single-task gait identified five independent gait domains: rhythm symmetry, rhythm, pace asymmetry, arm motion, and variability. Factor analysis of the dual-task gait identified four gait domains: rhythm, variability, symmetry, and arm motion. During single-task walking, pace asymmetry was negatively correlated with MoCA scores and could distinguish between the AD group and the other two groups. Arm motion was not associated with MoCA scores, and did not exhibit adequate discrimination in either task. Conclusion Currently, there is no reliable evidence suggesting that arm motion can be used to recognize AD or MCI. Gait asymmetry can serve as a potential gait marker for the auxiliary diagnosis of AD but not for MCI.
Exploration of the prospective utilization of educational robotics by preschool and primary education teachers

Educational robotics integrates aspects from various scientific disciplines, encompassing the entire spectrum of science, technology, engineering, and mathematics (STEM) education. Its effective application is heavily reliant on educators tasked with implementing it within a school setting. This study aimed to investigate the potential adoption of educational robotics among preschool and primary education teachers. The study involved 191 preschool teachers (62.2%) and 115 primary school teachers (37.8%). Data was gathered using a structured questionnaire, AKAER, demonstrating strong internal consistency with a Cronbach’s alpha reliability coefficient of α=. 892. Educators, irrespective of their specialization, gender, or scientific background, acknowledge the significance of educational robotics and express eagerness to incorporate it. A substantial percentage of educators expressed discomfort in using educational robotics and related if they had trained or not. Nonetheless, more than 70.0% of the surveyed educators expressed interest in receiving training on educational robotics to proficiently integrate it into their teaching methodologies. To ensure that the new generation of students can reap the benefits of modern teaching tools like educational robotics, closely tied to STEM education and the cultivation of 21st century skills, we must not only supply schools with the required materials but prioritize the provision of adequately trained and informed educators.
Personal Identification Based on Fusion of Iris and Periocular Information Using Convolutional Neural Networks

Iris recognition has long been a security verification and identification tool in the field of computer vision, frequently utilized in security and forensic science applications. However, the performance of current iris recognition systems remains unsatisfactory, particularly when capturing images under challenging conditions such as poor lighting, iris occlusion, eye misalignment, or increased distance. Despite this, recent advancements in neural network-based image recognition systems, such as convolutional neural networks (CNN), have shown the potential to tackle these problems by extracting complex features within images and delivering performance that is either comparable to or surpasses that of traditional iris recognition methods. In this paper, we proposes a novel approach that fuses iris recognition techniques with periocular information using CNN to address these challenges. Our approach was evaluated by using the CASIA-Iris-Thousand dataset. The evaluation results showed that the accuracy was improved from 93.64% to 99.80% compared with using the iris recognition alone. The false acceptance rate and false rejection rate were reduced noticeably from 6.30% to 0.17% and from 12.33% to 5.00%, respectively. We also discuss the potential for real-world application of such a system.
Configuration and dimensions of burgage plots in the burgh of Edinburgh

The paper presents a study in occupational mapping, the focus of which is on combining locational data for early modern occupations with a contemporaneous town plan of Edinburgh, in order to study occupational distribution in the urban environment. By combining data from a 1635 tax roll with the corresponding section of the 1647 Gordon of Rothiemay map of Edinburgh, a new tool was formed for visualizing the distribution and physical patterns of urban occupations in the southeast quarter of Scotland's capital.
Giant Cluster Emergence and Functionality in Social Systems

The emergence of a giant cluster, in which bits and pieces of otherwise unconnected parts of a system come together, has been extensively studied in nonsocial contexts. This phenomenon has attracted substantial attention because it allows researchers to understand and predict the collective behavior of a system. In this paper, we formalize the emergence and functionality of a giant cluster within a social system. It has been well established that giant clusters can easily emerge in systems with few triads and abundant bridges. However, studies have shown that social networks are characterized by abundant triads and a limited number of bridges. This finding implies that people are more likely to interact with others and form ties within a common shared context. The finding also suggests that it is costly for people to cross the boundaries of their own social circle and to build bridges connecting to the outside world. A question is whether a giant cluster can also emerge even under these seemingly unfavorable conditions. In our paper, we develop simple models to address this question. Our models reveal that even if bridges constitute only a tiny fraction of the ties in a system, a giant cluster can emerge. Furthermore, we find that giant clusters in systems with a limited number of bridges are more conducive to innovation than giant clusters with abundant bridges, which tend to stifle knowledge creation.
Linking Sierra Nevada, California, uplift to subsidence of the Tulare basin using a seismically derived density model

Seismic tomography has previously imaged the high‐velocity “Isabella anomaly” southwest of the Sierra Nevada beneath the Tulare basin, a region of ~1 km of anomalous Pliocene subsidence. Additionally, it has been proposed that the eastern Sierra has risen 1–2 km since the Miocene in response to removal of dense lithospheric material. The Isabella anomaly has been variably interpreted as either this lithospheric material or a neutrally buoyant stalled fragment of the Farallon slab. To discriminate between these two, we estimate upper mantle density variations from seismic velocities and show that the estimated mass anomaly accords with 60 km of cold lithospheric material removed from beneath the southern Sierra, sufficient for 1.3 km of range uplift. A flexural model of the surface response to mantle loads predicts 1.3–1.7 km of anomalous subsidence of the Tulare basin, several hundred meters more than is observed. Nevertheless, beam‐formed receiver functions show up to 10 km of crustal thickening beneath the basin, which we attribute to viscous response of the crust to mantle loading. This anomalous crustal thickness, the post‐Miocene subsidence of the Tulare basin, and the uplift of the Sierra can all be explained by redistribution of cold continental mantle lithosphere; therefore, the Isabella anomaly is more plausibly such continental material than a stalled Farallon slab fragment.
The Management of Acute Exacerbations in COPD: A Retrospective Observational Study and Clinical Audit

(1) Background: Acute exacerbations of chronic obstructive pulmonary disease (COPD) are not only associated with increased patient morbidity and mortality, but with extensive healthcare costs. Thus, adequate clinical management is crucial. The aim of this project was to evaluate the management of acute COPD exacerbations in a public teaching hospital in Switzerland. (2) Methods: We retrospectively analyzed clinical routine data of patients presenting with an acute exacerbation of COPD at the emergency department of a Swiss hospital between January 2019 and February 2020. Management was evaluated against recommendations from the GOLD 2019 report and previous audits. (3) Results: The data of 184 patients (mean age 73.5 years, range 41–95 years, 53% male) with 226 visits were included. While the documentation of GOLD stage (I-IV) and smoking status was consistent (81.0% and 91.6%), GOLD risk category (A-D) was only documented in 36% of the cases. Patients’ respiratory rate upon presentation was measured in 73%, and blood gas analysis was performed in 70%. A total of 94% of the patients received a chest imaging; spirometry was performed in 10%. Initial symptomatic therapy with short acting bronchodilators was applied in 56%. Systemic steroid treatment was installed in 86%. Antibiotics were given in 56%, but in one fourth the indication was not clear. Non-invasive ventilation was applied in 25% of the indicated cases. Smoking cessation was recommended to 26% of the current smokers and referral to pulmonary rehabilitation was given in 16%. (4) Conclusion: GOLD recommendations were not comprehensively implemented, especially with regard to the assessment of severity, initial symptomatic therapy, and non-invasive ventilation. These results show the importance of the frequent revision of routine practice and may help to create awareness among practitioners and ultimately improve the quality of COPD management.
Albedo as a Competing Warming Effect of Urban Greening

Urban greening is often proposed for urban heat island (UHI) mitigation because vegetation provides shade and increases evapotranspiration. However, vegetation has lower albedo and higher emissivity than the bare soil it often replaces, which increases incoming energy fluxes. Here, we use the Weather Research and Forecasting model to quantify and compare the albedo and non‐albedo effects (i.e., changes in emissivity, surface roughness, and evaporative fluxes) of urban greening in the Los Angeles Basin under policy relevant urban greening scenarios. When albedo‐induced effects were included in the model, daytime surface temperatures in urban areas warmed by 0.70 ± 0.89°C with increases in the sensible heat flux outweighing increases in the latent heat flux from increased evapotranspiration. In contrast, daytime surface temperatures cooled by 0.27 ± 0.72°C when the albedo‐induced effects were ignored. At night, including albedo‐induced effects of urban greening resulted in only half the cooling modeled in the non‐albedo simulations. Near surface air temperatures also had contrasting model results, with nighttime cooling of 0.21 ± 0.47°C outweighing slight daytime warming of 0.04 ± 0.32°C in the non‐albedo simulations and daytime warming of 0.33 ± 0.41°C outweighing slight nighttime cooling of 0.05 ± 0.46°C in the albedo simulations. Our results reveal the critical role that albedo plays in determining the net surface climate effects of urban greening. Reductions in albedo from urban greening should be carefully considered by policy makers and urban planners, especially as high albedo roofs and pavements are simultaneously being deployed for UHI mitigation in many cities.
A High-Gain Filtering Fabry-Perot Antenna With RCS Reduction

A high-gain filtering Fabry-Perot antenna (FPA) with radar cross Section (RCS) reduction is proposed. The design utilizes a partially reflecting surface (PRS) which is integrated with a chessboard arranged metasurface (CAMS) in a single-layered substrate. The CAMS is composed of periodic strip arrays to reduce monostatic RCS based on the phase cancellation principle. The PRS structure is a cross-slot array which is designed to work with both orthogonal orientations of the CAMS elements while yielding a high reflection magnitude. Accordingly, the proposed FPA achieves a high-gain broadside radiation and wideband RCS reduction. The filtering functionality is achieved from a T-shaped feed patch, which is, interestingly, enhanced by the integration of CAMS in the PRS. For validation, a prototype operating at 6.0 GHz has been fabricated and measured. The antenna with an overall size of $3.2\lambda _{{0}} \times 3.2\lambda _{{0}} \times 0.57\lambda _{{0}}$ at 6.0 GHz exhibits an impedance matching bandwidth (BW) of 5.73 – 6.23 GHz, a 3-dB gain BW of 5.76 – 6.17 GHz with the peak gain of 14.63 dBi, and an out-of-band suppression of ≥20 dB. Meanwhile, it achieves an RCS-reduction bandwidth of about 4.0 to 9.0 GHz (76.9%).
Changes in potential evapotranspiration and surface runoff in 1981–2010 and the driving factors in Upper Heihe River Basin in Northwest China

Changes in potential evapotranspiration and surface runoff can have profound implications for hydrological processes in arid and semiarid regions. In this study, we investigated the response of hydrological processes to climate change in Upper Heihe River Basin in Northwest China for the period from 1981 to 2010. We used agronomic, climatic and hydrological data to drive the Soil and Water Assessment Tool model for changes in potential evapotranspiration (ET0) and surface runoff and the driving factors in the study area. The results showed that increasing autumn temperature increased snow melt, resulting in increased surface runoff, especially in September and October. The spatial distribution of annual runoff was different from that of seasonal runoff, with the highest runoff in Yeniugou River, followed by Babaohe River and then the tributaries in the northern of the basin. There was no evaporation paradox at annual and seasonal time scales, and annual ET0 was driven mainly by wind speed. ET0 was driven by relative humidity in spring, sunshine hour duration in autumn and both sunshine hour duration and relative humility in summer. Surface runoff was controlled by temperature in spring and winter and by precipitation in summer (flood season). Although surface runoff increased in autumn with increasing temperature, it depended on rainfall in September and on temperature in October and November. Copyright © 2016 John Wiley & Sons, Ltd.
Prediction of Fractured Reservoir Production Trends and Compartmentalization Using an Integrated Analysis of Basement Structures in the Piceance Basin, Western Colorado

Subsurface structures control fractured production trends in most Cretaceous-age Mesaverde Group gas reservoirs in the Piceance Basin. Nearly all of these subsurface structures are directly related to deeper basement fault trends. Above these basement zones, fracture permeability is enhanced in the tip zone terminations where these basement-related thrusts terminate up-section. To identify these basement structural trends, a new integrated interpretation of basement structure and shallower production trends was conducted using gas production data, detailed aeromagnetic data, seismic surveys, well data, Landsat Thematic Mapper (TM), Side-Looking Airborne Radar (SLAR), aerial photography, and published outcrop maps. This new interpretation illustrates the critical control of basement structures on the development of shallow structures and related fracture-controlled production in the hydrocarbon-bearing intervals. We have demonstrated the ability of the methodology to accurately predict fractured reservoir production trends in Grand Valley-Parachute and Rulison fields in the Central Piceance Basin. We have used the Divide Creek Field in the southeast Piceance Basin to illustrate that reservoir compartmentalization can also be identified and predicted using the integrated methodology. The most prolific gas fields in the Piceance Basin (Grand Valley, Parachute, Rulison, Plateau, Shire Gulch, White River Dome, and Divide Creek fields) produce gas from fractured tight gas sands and interstratified coal reservoirs within the Mesaverde Group. Given the low matrix permeability of this stratigraphic interval, tectonic fracturing related to basement structures is critical to the development of permeability and concomitant economic production. The close relationship between basement structures and fracture-controlled production trends underscores the importance of using an integrated methodology to characterize basement deformation and fractured reservoir production. data from sources detailed remote sensing and regional geologic syntheses to develop and calibrate an internally consistent interpretative tool. The tool predicts subsurface fractured reservoirs controlled by basement features as target areas for exploration drilling, and related development programs. This internally consistent interpretation minimizes the subjectivity that has long plagued the results which arise from use of these methods by themselves.
Method for Segmentation of Bean Crop and Weeds Based on Improved UperNet

Bean crop and weed detection is a key component of precision agriculture, which can distinguish between bean crop and weeds. Accurate identification of weeds is essential for precision weed management. This study introduces PF-UperNet, a semantic segmentation approach rooted in an encoder-decoder architecture, designed to autonomously distinguish between bean crop and weeds using advanced computer vision techniques. Our methodology refines the foundational UperNet in several significant ways: Firstly, we adopt the PoolFormer-S12 as a substitute for UperNet’s backbone structure, aiming to reduce the model parameters and boost its performance metrics. Secondly, the Efficient Channel Attention (ECA) mechanism is integrated into both the PoolFormer-S12 and the Decoder, sharpening the network’s focus on extracting salient channel features. Then, within the Decoder, the Feature Alignment Pyramid Network (FaPN) supplants the conventional Feature Pyramid Network (FPN) module, remedying the misalignment issues observed in UperNet’s FPN feature maps. Lastly, we replace the Cross-Entropy loss with a combination of Cross-Entropy loss and Dice coefficient loss to increase the model’s attention on regions to be detected. Empirical evidence underlines the efficacy of our technique, with a Mean Intersection over Union (MIoU) of 87.45%, a Mean Pixel Accuracy (MPA) of 96.82%, and a total of 46.16M parameters encapsulated. Relative to the benchmark UperNet, our model demonstrates enhancements of 1.08% and 0.25% in MIoU and MPA, respectively, and accomplishes a parameter reduction of 27.92%. Experimental results demonstrate that the proposed model achieves remarkable detection performance in terms of MIoU, MPA, and model parameters. It can provide an effective detection method for weed management.
Mitigating Scar Tissue Formation in Tendon Injuries: Targeting HMGB1, AMPK Activation, and Myofibroblast Migration All at Once

Tendon injuries, while prevalent, present significant challenges regarding their structural and functional restoration. Utilizing alpha-smooth muscle actin (α-SMA)-Ai9-scleraxis (Scx)-green fluorescent protein (GFP) transgenic mice, which exhibit both Scx (a tendon cell marker) and α-SMA (a myofibroblast marker), we explored the effects of metformin (Met) on tendon healing, repair, and its mechanisms of action. Our findings revealed that intraperitoneal (IP) injections of Met, administered before or after injury, as well as both, effectively prevented the release of HMGB1 into the tendon matrix and reduced circulating levels of HMGB1. Additionally, Met treatment increased and activated AMPK and suppressed TGF-β1 levels within the healing tendon. Tendon healing was also improved by blocking the migration of α-SMA+ myofibroblasts, reducing the prevalence of disorganized collagen fibers and collagen type III. It also enhanced the presence of collagen type I. These outcomes highlight Met’s anti-fibrotic properties in acutely injured tendons and suggest its potential for repurposing as a therapeutic agent to minimize scar tissue formation in tendon injuries, which could have profound implications in clinical practice.
Bioremediation of Petroleum Hydrocarbons in Cold Regions: Analytical methods for petroleum in cold region soils

Introduction In order to demonstrate the effectiveness of a bioremediation project, one must have an accurate measure of the contaminants, both at the start of the project and throughout the treatment process. The measurement of the contaminants throughout the process is important to demonstrate that the treatment is successful and to identify advances or set-backs quickly and effectively. Proving the disappearance of hydrocarbons is important to the success of a bioremediation project. An accurate measurement of hydrocarbons and their biodegradation products is needed to confirm that petroleum was actually consumed by bacteria (discussed in Chapter 7, Section 7.3). One method of confirming biodegradation of petroleum is the coupled measurement of biodegradation rates by proxy methods and the disappearance of the contaminant. Biodegradation rates do not, in and of themselves, prove the decomposition of contaminants. Measurement of biodegradation rates, however, can be an easy way to demonstrate that the potential exists for contaminant removal. While measures of biodegradation rates are often used to estimate time to closure for a site, or proof of technology, biodegradation rates can be unreliable. Common measures of aerobic biodegradation are loss of contaminants, oxygen (O 2 ) consumption, and carbon dioxide (CO 2 ) evolution. Unfortunately, the CO 2 can result from non-biological sources (see Chapter 7, Section 7.2.2.2 for additional discussion). Particularly in low pH groundwater, pH adjustment made during bioremediation could result in CO 2 off-gassing from groundwater. Oxygen depletion in the subsurface is also not proof of biodegradation.