Miracle-dz/UniFAR-FTUs huggingface dataset:
How does soil water content influence permafrost evolution on the Qinghai-Tibet Plateau under climate warming?

The active layer thickness (ALT) in permafrost regions regulates hydrological cycles, water sustainability, and ecosystem functions in the cryosphere and is extremely sensitive to climate change. Previous studies often focused on the impacts of rising temperature on the ALT, while the roles of soil water content and soil granularity have rarely been investigated. Here, we incorporate alterations of soil water contents in soil thermal properties across various soil granularities and assess spatiotemporal ALT dynamics on the Qinghai-Tibet Plateau (QTP). The regional average ALT on the QTP is projected to be nearly 4 m by 2100. Our results indicate that soil wetting decelerates the active layer thickening in response to warming, while latent heat exerts stronger control on ALTs than thermal conductivity does. Under similar warming conditions, active layers thicken faster in coarse soils than in fine soils. An important ramification of this study is that neglecting soil wetting may cause overestimations of active layer thickening on the QTP.
Cloud detection for satellite cloud images based on fused FCN features

ABSTRACT Cloud detection for satellite cloud images is a challenging image processing task owing to the blurring of cloud boundaries, multiplicity, and complexity of cloud types. Currently, the commonly used cloud detection methods include original full convolutional neural network (original FCN), FCN with an 8-pixel stride (FCN- 8s), FCN with a 2-pixel stride (FCN-2s), and so on. However, the aforementioned methods exclusively rely on a single network layer the final layer feature map; thus, shallow cloud image information, such as cloud profile information may not be captured. In this letter, a cloud detection method for satellite cloud images based on fused FCN features is proposed. The proposed method effectively fuses spatial and high-level semantic information, and a voting ensemble strategy is used to improve the accuracy and robustness of cloud detection. Finally, the experimental results demonstrate that the average overall accuracy (OA), average producer’ accuracy (PA), and average user’ accuracy (UA) of the proposed method for multiple training sample sizes and image sizes of the collected Fengyun satellite (FY-2 G) cloud image database increased by 7.15%, 9.04%, and 8.46%, respectively, relative to the average accuracies of the original FCN, FCN-8s, FCN-2s, SegNet, and DeepLabV3 methods.
Revealing Students’ Responses on the Use of Flipgrid in Speaking Class: Survey on ICT

Along with the development of the 4.0 era, the use of ICT media is not a new thing in the world of education. Many previous studies have integrated various technology-based media (ICT) with language learning including speaking lessons. One of the platforms that is currently being widely used is FLIPGRID. The main objective of this research is to reveal how students respond to the use of FLIPGRID as an ICT-based media that focuses on Speaking. The research method used is the qualitative method. The instruments used in this study were questionnaires and interviews. From the results of the study, it was found that there were 26 variants of positive responses from the accessibility, internet connectivity, psychological fulfillment, the interactive features, and 16 variants of negative responses of students to the use of the Flipgrid application ranging from competitiveness, equipment, and originality. The most positive responses that arise are that this application is easy to use, while the most negative responses that arise are difficulties or the upload process is quite long. It can be concluded that the FLIPGRID application has more positive responses than negative responses so that this application can be used by teachers and lecturers in the speaking class.
Minimum dispersion beamforming using modified conjugate gradient method

In order to solve linear constraint minimize dispersion problem in beamforming with non-Gaussian signals or noise, this paper proposed a real time adaptive beamforming technique based on modified conjugate gradient (MCG) method. Compared to conventional adaptive method, MCG have faster convergence rate than stochastic gradient (SG) method, and comparable convergence rate with recursive least square (RLS) method with lower complexity. And it simplifies the procedure of conjugate gradient method with one iteration per snapshots by using inexact line search scheme. Simulation has demonstrated the superior performance in output SINR and its convergence rate.
The RpTOE1-RpFT Module Is Involved in Rejuvenation during Root-Based Vegetative Propagation in Robinia pseudoacacia

Vegetative propagation is an important method of reproduction and rejuvenation in horticulture and forestry plants with a long lifespan. Although substantial juvenile clones have been obtained through the vegetative propagation of ornamental plants, the molecular factors that regulate rejuvenation during vegetative propagation are largely unknown. Here, root sprouting and root cutting of Robinia pseudoacacia were used as two vegetative propagation methods. From two consecutive years of transcriptome data from rejuvenated seedlings and mature trees, one gene module and one miRNA module were found to be specifically associated with rejuvenation during vegetative propagation through weighted gene co-expression network analysis (WGCNA). In the gene module, a transcription factor-encoding gene showed high expression during vegetative propagation, and it was subsequently named RpTOE1 through homology analysis. Heterologous overexpression of RpTOE1 in wild-type Arabidopsis and toe1 toe2 double mutants prolonged the juvenile phase. The qRT-PCR results predicted RpFT to be a downstream gene that was regulated by RpTOE1. Further investigation of the protein-DNA interactions using yeast one-hybrid, electrophoretic mobility shift, and dual luciferase reporter assays confirmed that RpTOE1 negatively regulated RpFT by binding directly to the TOE binding site (TBS)-like motif on its promoter. On the basis of these results, we showed that the high expression of RpTOE1 during vegetative propagation and its inhibition of RpFT played a key role in the phase reversal of R. pseudoacacia.
Performance Evaluation of the Transmission Quality of the Internet of Things in Farmland Environmental Monitoring Based on ns-3

The Internet of Things (IoT) technology focuses on the application of information-sensing equipment, transmission network, and intelligent information processing technology. Through scientific management, it can achieve the rational use of agricultural resources, thus improving the ecological environment, reducing production costs, and improving the yield and quality of agricultural products. At present, the application of agricultural IoT technology faces problems including small network coverage, limited monitoring projects, high transmission cost, and short power supply time, which limit the popularity and ability of farmland environmental monitoring. In this paper, ns-3 is used to simulate the IoT for farmland environmental monitoring based on the long-range wide-area network (LoRaWAN) protocol. The simulation results show the transmission distance with good transmission quality under the LoRaWAN protocol. Furthermore, we analyze the comparison of the combination range of network transmission quality parameters under the two acknowledgment (ACK) mechanisms. Finally, we present the parameter combination range and suggestions to improve the network transmission quality, which provide a new basis for guiding the farmland environmental monitoring system.
Which Frailty Evaluation Method Can Better Improve the Predictive Ability of the SASA for Postoperative Complications of Patients Undergoing Elective Abdominal Surgery?

Purpose To determine which frailty method can better improve the predictive ability of the Surgical Apgar Score combined with American Society of Anesthesiologists physical status classification (SASA). Patients and Methods A prospective cohort study was conducted. A total of 194 elderly patients undergoing elective abdominal surgery were included. Preoperative frailty using FRAIL questionnaire, frailty index (FI), Clinical Frailty Scale (CFS) and SASA scores was assessed. Primary outcome was in-hospital Clavien-Dindo ≥grade II complications. Multiple logistic regression was used to examine the association between frailty and complications. Receiver operating characteristic curves were used to explore the predictive ability of frailty. Results According to the FRAIL, FI and CFS criteria, the prevalence of frailty in the study population was 43.8%, 32.5%, and 36.6%, respectively. After adjusting for all covariates, frailty was significantly associated with postoperative complications in hospital by FRAIL [odds ratio: 5.11, 95% CI: 1.41–18.44, P = 0.013], by FI [OR: 4.25, 95% CI: 1.21–14.90, P = 0.024] and by CFS [OR: 5.10, 95% CI: 1.52–17.17, P = 0.008]. The area under the curve (AUC) for SASA was 0.768 (95% CI: 0.702–0.826). Addition of frailty assessment (FRAIL, FI and CFS) increased the AUC to 0.787 (95% CI: 0.722–0.842), 0.798 (95% CI: 0.734–0.852), and 0.815 (95% CI: 0.753–0.867), respectively. Compared to SASA, only addition of CFS had a significant difference (P = 0.0478). Conclusion Frailty is an effective predictor of postoperative complications in elderly Chinese patients undergoing elective abdominal surgery. Frailty assessment of CFS can better improve the predictive ability of SASA.
Formulation and Biological Evaluation of Mesoporous Silica Nanoparticles Loaded with Combinations of Sortase A Inhibitors and Antimicrobial Peptides

This study aimed to develop synergistic therapies to treat superbug infections through the encapsulation of sortase A inhibitors (SrtAIs; trans-chalcone (TC), curcumin (CUR), quercetin (QC), or berberine chloride (BR)) into MCM-41 mesoporous silica nanoparticles (MSNs) or a phosphonate-modified analogue (MCM-41-PO3−) to overcome their poor aqueous solubility. A resazurin-modified minimum inhibitory concentration (MIC) and checkerboard assays, to measure SrtAI synergy in combination with leading antimicrobial peptides (AMPs; pexiganan (PEX), indolicidin (INDO), and [I5, R8] mastoparan (MASTO)), were determined against methicillin-sensitive (MSSA) and methicillin-resistant (MRSA) Staphylococcus aureus, Escherichia coli, and Pseudomonas aeruginosa. The results demonstrated that the MCM-41 and MCM-41-PO3− formulations significantly improved the aqueous solubility of each SrtAI. The MICs for SrtAI/MCM-41-PO3− formulations were lower compared to the SrtAI/MCM-41 formulations against tested bacterial strains, except for the cases of BR/MCM-41 and QC/MCM-41 against P. aeruginosa. Furthermore, the following combinations demonstrated synergy: PEX with TC/MCM-41 (against all strains) or TC/MCM-41-PO3− (against all strains except P. aeruginosa); PEX with BR/MCM-41 or BR/MCM-41-PO3− (against MSSA and MRSA); INDO with QC/MCM-41 or QC/MCM-41-PO3− (against MRSA); and MASTO with CUR/MCM-41 (against E. coli). These combinations also reduced each components’ toxicity against human embryonic kidney cells. In conclusion, MCM-41 MSNs provide a platform to enhance SrtAI solubility and demonstrated antimicrobial synergy with AMPs and reduced toxicity, providing novel superbug treatment opportunities.
Design an Intelligent Driver Assistance System Based On Traffic Sign Detection with Persian Context

In recent years due to improvements of technology within automobile industry, design process of advanced driver assistance systems for collision avoidance and traffic management has been investigated in both academics and industrial levels. Detection of traffic signs is an effective method to reach the mentioned aims. In this paper a new intelligent driver assistance system based on traffic sign detection with Persian context is designed. The main goal of this system is to assist drivers to choose their path based on traffic signs more precisely. To reach this purpose, a new framework by using of fuzzy logic was used for detection of traffic signs in videos which have has been captured from a vehicle path in highways. Fuzzy logic increases inference and intelligent capabilities in smart systems to make correct decision making in online conditions. Then, the combination of Maximally Stable Extermal Regions (MSER) and Canny Edge Detector Algorithms are used to detect road sign’s texts detection. MSER algorithm is aimed at assists to detect regions in an image that differ in properties, for example in brightness or color, compared to surrounding regions. Also, canny edge detector uses a multi-stage algorithm to detect a wide range of edges in the images. Thereafter, morphological mask operator is used to join individual characters for final detection of texts in the traffic signs. Finally, MATLAB Optical Character Recognition (OCR) is employed to recognize the detected texts. This new framework gives an overall text detection and recognition rate of 90.6%.
Familial, Societal and Situational Factors Influencing Career Choice among Adult Learners in Ghana

This quantitative cross-sectional survey study sought to determine three significant but under-researched factors influencing adult learners' career choice in Ghana. A sample of 350 respondents was selected through stratified sampling to engage in this survey. Analysis of the data obtained showed statistically significant relationships between specific familial, societal, and situational factors and the career choices of the study respondents. Consequently, employing school counselors' services to orient parents/guardians on career choices among trainee teachers is regarded as imperative for developing positive attitudes towards teaching. This outcome was also observed as a measure to mitigate the high turnover rate among professional teachers. Findings from this study set the tone for further studies to investigate the influence of demographic factors on teaching as a career.
Optical Trapping Techniques Applied to the Study of Cell Membranes

Optical tweezers allow for manipulating micron-sized objects using pN level optical forces. In this work, we use an optical trapping setup to aid in three separate experiments, all related to the physics of the cellular membrane. In the first experiment, in conjunction with Brian Henslee, we use optical tweezers to allow for precise positioning and control of cells in suspension to evaluate the cell size dependence of electroporation. Theory predicts that all cells porate at a transmembrane potential VTM of roughly 1 V. The Schwann equation predicts that the transmembrane potential depends linearly on the cell radius r, thus predicting that cells should porate at threshold electric fields that go as 1/r. The threshold field required to induce poration is determined by applying a low voltage pulse to the cell and then applying additional pulses of greater and greater magnitude, checking for poration at each step using propidium iodide dye. We find that, contrary to expectations, cells do not porate at a constant value of the transmembrane potential but at a constant value of the electric field which we find to be 692 V/cm for K562 cells. Delivering precise dosages of nanoparticles into cells is of importance for assessing toxicity of nanoparticles or for genetic research. In the second experiment, we conduct nanoelectroporation—a novel method of applying precise doses of transfection agents to cells—by using optical tweezers in conjunction with a confocal microscope to manipulate cells into contact with 100 nm wide nanochannels. This work was done in collaboration with Pouyan Boukany of Dr. Lee’s group. The small cross sectional area of these nano channels means that the electric field within them is extremely large, 60 MV/m, which allows them to electrophoretically drive transfection agents into the cell. We find that nano electropo-
BEAM: A Network Topology Framework to Detect Weak Signals

—In these days, strategic decision making and im- mediate action are becoming a complex task for companies and policymakers, since the environment is subject to emerging changes that might include unknown factors. When facing these challenges, companies are exposed to opportunities for growth, but also to threats. Therefore, they seek to explore and analyze large amounts of data to detect emerging changes, or so- called weak signals, that can help maintaining their competitive advantages and shaping up their future operational environments. But due to the increasing volume of daily produced data, scalable and automated computer-aided systems are needed to explore and extract these weak signals. To overcome the automation and scalability challenges, and capture early signs of change in a big data environment, we propose a framework for weak signals detection relying on the network topology. It is implemented under the Cocktail project framework whose goal is to create a real-time observatory of trends, innovations and weak signals circulating in the discourses of the food and health sectors on Twitter. This method analyses quantitatively the network local structure using the graphlets (particular type of motifs) to find weak signals. It provides accordingly qualitative elements that contextualise the identified signals, which will allow business experts to interpret and evaluate their dynamics to determine which ones may have a relevant future. After testing this method on different types of networks (we present two of them in this paper), we proved that it is able to detect weak signals and provides a quantifiable signature that allows better decision making.
Adaptive Opportunistic Spatial Modulation for Boosting Transmit Diversity

In this paper, we propose an adaptive opportunistic spatial modulation scheme (AOSM), in which, our unique opportunistic group-antenna-selection scheme is amalgamated with a simple phase alignment (PA) transmit pre-scaling to boost the transmit-diversity of SM. To characterize and analytically evaluate the AOSM, a comprehensive error performance analysis is presented with single antenna reception. We theoretically derive a tight upper-bound for the symbol error probability (SEP) in closed-form based on an improved union-bound. The exact explicit asymptotic formula of the SEP at high SNR is provided as well. These results demonstrate that the transmit-diversity of proposed AOSM-(multiple-input single-output) MISO scheme is not only successfully achieved, but also elevated to be equal to the number of antennas in each antenna group. Moreover, it also reveals an important performance trend: at high SNR, with a fixed number of transmit antennas and a given data-rate, the SEP performance of the AOSM-MISO scheme can be successively enhanced by utilizing less antennas groups and bigger size of the signal constellation, because of the increase in transmit-diversity. Furthermore, the PA-aided SM-MISO is a special case of our AOSM-MISO. We are the first to provide the exact transmit-diversity gain for this conventional system and show that the PA pre-scaling scheme only can not improve the transmit-diversity of SM. This result sharpens the empirical diversity approximation results proposed in the existing literature. Simulation results well validate the analytical derivations, and indicate that our AOSM system can effectively improve system performance with high transmit-diversity at low-complexity.
Context-driven mean residual life estimation of mining machinery

ABSTRACT Maintenance is crucial to ensure production/output and customer satisfaction in the mining sector. The cost of maintenance of mechanised and automated mining systems is very high, necessitating efforts to enhance the effectiveness of maintenance systems and organisation. For effective maintenance planning, it is important to have a good understanding of the reliability and availability characteristics of the systems. Determining the Mean Residual Life (MRL) of systems allows organisations to more effectively plan maintenance tasks. In this paper, we use a statistical approach to estimate MRL and consider a Weibull proportional hazard model (PHM) with time-independent covariates to model the hazard function so that the operating environment could be integrated into the reliability analysis. The paper explains our methods for calculating the conditional reliability function and computing the MRL as a function of the current conditions. The model is verified and validated using data from the hydraulic system of LHD equipment in a Swedish mine. The results are useful to estimate the remaining useful life of such systems; the method can be used for maintenance planning, helping to control unplanned stoppages of highly mechanised and automated systems.
Getting Psyched About Memes in the Psychology Classroom

Internet memes are a ubiquitous part of internet culture and a common communication tool among students. Because they are a good medium for expressing ideas and concepts in a concise and fun manner, memes are a potentially valuable tool for teaching and engaging students. Instructors may not know how to use memes in classroom assignments or activities to support learning objectives. Students finding or creating their own class-related content is an empirically supported way to enhance learning. Instructors can enhance learning by using multimedia approaches (pictures/videos in addition to words), which is a good fit for the use of memes. We include examples of ways that memes have already been used in psychology classrooms. Incorporating meme assignments or activities in the classroom could be beneficial. We describe how students can explain or generate memes that illustrate concepts related to course material. Instructions and supporting information and resources, as well as calls for research into the effectiveness of the use of memes in the classroom, are included.
Angiotensin II Promotes SARS-CoV-2 Infection via Upregulation of ACE2 in Human Bronchial Cells

Blockers of the renin-angiotensin system (RAS) have been reported to increase the angiotensin converting enzyme (ACE)2, the cellular receptor of SARS-CoV-2, and thus the risk and course of COVID-19. Therefore, we investigated if angiotensin (Ang) II and RAS blockers affected ACE2 expression and SARS-CoV-2 infectivity in human epithelial bronchial Calu-3 cells. By infectivity and spike-mediated cell–cell fusion assays, we showed that Ang II acting on the angiotensin type 1 receptor markedly increased ACE2 at mRNA and protein levels, resulting in enhanced SARS-CoV-2 cell entry. These effects were abolished by irbesartan and not affected by the blockade of ACE-1-mediated Ang II formation with ramipril, and of ACE2- mediated Ang II conversion into Ang 1-7 with MLN-4760. Thus, enhanced Ang II production in patients with an activated RAS might expose to a greater spread of COVID-19 infection in lung cells. The protective action of Angiotensin type 1 receptor antagonists (ARBs) documented in these studies provides a mechanistic explanation for the lack of worse outcomes in high-risk COVID-19 patients on RAS blockers.