Miracle-dz/UniFAR-FTUs huggingface dataset:
Micropropagation of New Jersey tea (Ceanothus americanus), sand cherry (Prunus pumila), and sweetbells (Eubotrys racemosa)

ABSTRACT:New Jersey tea (Ceanothus americanus L. [Rhamnaceae]), sand cherry (Prunus pumila L. [Rosaceae]), and sweetbells (Eubotrys racemosa L. [Ericaceae]) are eastern US native shrubs with high potential for expanded landscape use because of their numerous ornamental attributes and adaptability. Micropropagation protocols were developed for these species that produce acceptable shoot multiplication rates, 100% microcutting rooting, and high-quality liner plants. New Jersey tea is not easily produced from seed or stem cuttings for commercial purposes, but we have demonstrated that micropropagation is a viable method for commercial propagation. In addition, micropropagation can be effectively used to rapidly propagate new superior genotypes of sand cherry and sweetbells.
High-Accuracy and Adaptive Fault Diagnosis of High-Speed Train Bogie Using Dense-Squeeze Network

As one of the most important systems of high-speed train (HST), bogie system matters when it comes to the safety and reliability of HST operation. In order to strengthen feature propagation and alleviate vanishing gradients problems in training deep-learning networks, a novel Dense-Squeeze Network based on one-dimensional convolutional neural networks (1D-CNN) is proposed for bogie fault diagnosis. On the one hand, dense blocks are capable of facilitating feature reuse and increasing the depth of feature propagation. On the other hand, the squeeze operation automatically measures the importance level of each feature channel, and then enhance the useful features and suppress the useless features for the current task. The experimental results tested by the HST model CRH380 A at different speeds verify the effectiveness of the proposed method, and the accuracy of fault diagnosis converges to 99.66%. Compared with other deep-learning-based methods, such as 1D-CNN, Long Short-Term Memory (LSTM) and DenseNet, the superiority of the proposed scheme is demonstrated clearly.
End-Effector Velocity and Input Frequency Effects on Teleoperator Performance

End-effector velocity defines two types of servomanipulators: operator-paced systems and machine-paced systems. Input frequency limits below human bandwidth may also cause machine-pacing. Two experiments varied end-effector velocity limits (1.01 meters per second, 86.4 centimeters per second, and 76.2 centimeters per second) and input frequency limits (0.16 Hz, 0.32 Hz, 0.64 Hz, and 1.27 Hz). Multivariate analyses of variance found statistically significant input frequency limit effects in one experiment, and significant input frequency and velocity limit effects in the second experiment. Machine-pacing caused by input frequency occurred in the range hypothesized (between 0.32 Hz and 0.64 Hz). The critical velocity limit appeared to be lower than expected (between 76.2 cm and 86.4 cm per second). These results are valuable for future teleoperator designs.
Closed Incision Negative Pressure Therapy Versus Traditional Dressings for Low Transverse Abdominal Incisions Healing by Primary Closure: A Systematic Review and Meta-Analysis

Background: Closed incision negative pressure therapy (ciNPT) devices may reduce wound healing complications when applied to closed surgical incisions. The aim of this review was to assess the effects of ciNPT versus standard dressings in patients undergoing primary closure of high tension, lower transverse abdominal incisions. Methods: This review was registered a priori on PROSPERO (CRD42021252048). A search of the following databases was performed in February 2021: Medline, EMBASE, and CENTRAL. Unpublished trials were searched using clinicaltrials.gov. All randomized and nonrandomized studies comparing ciNPT to standard dressings were included. Two independent reviewers performed screening and data extraction. Outcomes evaluated the incidence of wound dehiscence, surgical site infection, total abdominal complications, time to drain removal, and seroma formation. Main Results: Ten studies were included in quantitative and narrative synthesis. Observational study evidence suggests ciNPT likely reduces the incidence of wound dehiscence (odds ratio [OR] 0.57 [0.44-0.96], P = .03) and total abdominal complications (OR 0.34 [0.21-0.54], P < .01). Decreased incidence of seroma formation favored ciNPT (OR 0.65 [0.24-1.76], P = .40); however, this did not achieve significance. Randomized and non-randomized study evidence was very uncertain about the effect of ciNPT on the remaining outcomes. Conclusions: The current best randomized study evidence is very uncertain about the effect of ciNPT on these outcomes. Observational study evidence suggests ciNPT likely results in a statistically significant reduction in abdominal wound dehiscence and total abdominal complications. Additional randomized trials are warranted to limit the impact of bias on the overall certainty of the evidence.
Slip detecting by tactile sensor using Acoustic Resonant Tensor Cell and its application for grasping

This paper describes a slip sensor using Acoustic Resonant Tensor Cell (ARTC) . This slip sensor is made smaller than previous researches. We conducted a finite element method simulation to ensure the hypothesis of slip detection. Then we propose how to feedback the slip information to grasping force. Furthermore its performance of slip detection is shown through experiments for evalueation.
Techniques for clock skew reduction over intra-die process, voltage, and temperature variations

ii PREFACE. iii TABLE OF CONTENTS. iv LIST OF TABLES . viii LIST OF FIGURES . ix LIST OF SYMBOLS. xi ACKNOWLEDGEMENTS . xii CHAPTER 1 : INTRODUCTION AND OVERVIEW. 1 1.1 MOTIVATION.1 1.2 SYNCHRONOUS CLOCK DESIGN ISSUES . 2 1.3 PVT VARIATIONS.5 1.4 SKEW AND JITTER REDUCTION AND COMPENSATION.7 1.5 RESEARCH STATEMENT . 9 1.6 THESIS ORGANIZATION. 10 CHAPTER 2 : SYNCHRONOUS CLOCK BACKGROUND . 11 2.1 CLOCK FUNCTION AND DESIGN ISSUES. 11 2.1.1 Clock Source. 12 2.1.2 Flip­Flop Timing Issues . 12 2.1.3 Clock Distribution Network Design . 15 2.1.3.1 Basics of Clock Networks . 15 2.1.3.2 Basics of Clock Buffer Design . 16 2.1.3.3 Other Clock Design Issues.19 2.1.4 Clock Timing Metrics . 19 2.2 PVT VARIATIONS AND SKEW . 22 2.3 SKEW REDUCTION TECHNIQUES. 24 2.3.1 Pre­silicon Techniques . 24 2.3.1.1 Balancing Clock Distribution Wires.25 2.3.1.2 Balancing Clock Buffers . 26 2.3.2 Post­silicon Techniques (Active De­skewing). 28 2.3.2.1 Multiple Tuning Zone Synchronization . 30
Modeling Technique of Ship Grounding with Rigid Slope

The explicit nonlinear finite element analysis has gradually become an important method in dealing with the ship grounding problem,in which the modeling technique is the key to the numerical simulation.The grounding ship is treated as a deformable structure and the whole ship is modeled by using the elastoplastic material.The slope is treated as a rigid body and modeled by using the rigid material.A master-slave contact is defined between the ship and the slope.A self-contact is defined in the bow.A number of numerical results are obtained through the simulation.The results include the movement of ship,the time history curves of the grounding force,the time history curves of energy transition and the deformation of the ship.The example shows that the modeling technique can be used in the simulation of ship grounding.
Analysis and Measurement of Two Tone intermodulation distortion in Wideband Power Amplifier

Wideband power amplifiers (PAs) generally have large memory effect and high nonlinearity. In non-linearity, Inter modulation distortion (IMD) is an important metric. For a wide range of RF components, the usual AM-AM and AMPM data cannot properly describe the large distortion characteristics. So an accurate amplifier behavioral modeling method based on two-tone transfer characteristics is presented, which is quite useful to analyze memory effects for third and fifth order harmonic in terms of intercept points, and these are calculated using the harmonic balance test. PA gain for harmonic level simulation and circuit level simulation is calculated. The memory effects are analyzed up to 5th order and the dominance of memory effects in third order has been verified with the simulation results
The Peak-Average Power Ratio Reduction Method Based on Statistic Companding for SC-FDMA Systems

In order to reduce the peak-average power ratio(PAPR) of single carrier-frequency division multiple access(SC-FDMA) system,a new method based on statistic companding was proposed.The proposed method is the first method that combines the statistic feature of SC-FDMA transmitting signals and the companding technology,so as to reduce the PAPR as well as BER.The result shows that the proposed method can not only reduce the PAPR of SC-FDMA to 2 dB in mean,but also reduce the BER to a quarter of its original value.The proposed method can be a better choice for PAPR reduction scheme in LTE standardization.
Multistep Forecasting of Soil Moisture Using Spatiotemporal Deep Encoder–Decoder Networks

Accurate spatiotemporal predictions of surface soil moisture (SM) are important for many critical applications. Machine learning models provide a powerful method for building an accurate and reliable predictive model of SM. However, the models used in recent studies have some limitations, including lack of spatial autocorrelation (SAC), vague representation of important features, and primarily focused on the one-step forecast. Thus, we proposed an attention based convolutional long-short term memory model (AttConvLSTM) for multistep forecasting. The model includes three layers; spatial compression, axial attention, and encoder-decoder prediction, which are used for compressing spatial information, feature extraction, and multistep prediction, respectively. The model was trained using surface SM from Soil Moisture Active Passive L4 product at 18km spatial resolution over the United States. The results show that AttConvLSTM predicts 24 hours ahead SM with mean R2 and RMSE is equal to 0.82 and 0.02, respectively. Compared with LSTM, AttConvLSTM improves the model performance over 73.6% of regions, with an improvement of 8.4% and 17.4% in R2 and RMSE, respectively. The performance of the model is mainly influenced by temporal autocorrelation (TAC). Moreover, we also highlight the importance of SAC on model performance, especially over regions with high SAC and low TAC. Moreover, our model is also competent for SM predictions from several hours to several days, which could be a useful tool for predicting all meteorological variables and forecasting extremes.
Proactive Resilient Day-Ahead Unit Commitment With Cloud Computing Data Centers

To enhance the resilience of power systems toward the temporal and spatial impacts caused by extreme weather events, e.g., hurricanes, the flexibility of cloud data centers (CDCs) is treated as a kind of efficient demand response. Since the workloads of CDCs have the shifting capacity between different locations and time slots, a day-ahead unit commitment problem including data centers is proposed to explore the integrated spatial and temporal flexibility of the workloads to its full extent through task migration. Considering the uncertainty of probability density functions, the line failure rates, workload arrival rates, power loads are integrated into an ambiguity set. The scheduling process of generators and CDCs is modeled as a two-stage distributionally robust optimization problem, which is reformulated as a large-scale deterministic mixed-integer linear programming problem and solved by the multicuts Benders decomposition method. The performance of the proposed scheduling strategy is tested in both the IEEE 24-bus RTS system and the three-area RTS-96 system. The results reveal that the method could mitigate the adverse impacts of hurricanes by enhancing the resilience of power systems and decreasing the dropping workloads of CDCs.
Remote Vital Sign Monitoring With Reduced Random Body Swaying Motion Using Heartbeat Template and Wavelet Transform Based on Constellation Diagrams

Remote vital signs monitoring using millimeter-wave (mmWave) sensors has gained lots of attention because of their contactless, portable advantages. However, their received signals are more sensitive to random body motions (RBM) which degrades the accuracy of heart rate (HR) detection. To overcome this challenge, multi-input multi-output (MIMO) configuration can be used to reduce RBM's impact as each channel has different points of view with respect to the subject under test (SUT). Here we propose the use of a Frequency Modulated Continuous Wave (FMCW) radar from Texas Instruments (TI) at 77 GHz to collect data from its 192-channel configuration. Since vital sign information extracted using Arctangent Demodulation (AD) could be corrupted by either RBM or respiratory harmonics, a method is needed to minimize such effects. Hence, we develop an algorithm where a Heartbeat Template (HBT) is extruded based on the Constellation Diagram that shows the Quadrature signals from the target's range profile. The HBT is then used to design an adapted-wavelet for Continuous Wavelet Transform (CWT) to magnify the heartbeat signals. Under circumstances where RBM overwhelms the heartbeat signal that the HBT cannot completely reduce its effects, a spectral-based HR selection method is also developed to estimate the HR. By employing the proposed methods, we have reduced mean-error ${\mu _e}$ of HR estimation significantly from 9 bpm to less than 2 bpm.
Anthropometric parameters as alternatives to identify visceral fat and cardiovascular risk in hepatitis C patients

Objective: To analyze the anthropometric parameters used as alternatives to identify visceral fat and cardiovascular risk in patients with hepatitis C. Methodology: Study carried out between June to November of 2017, with hepatitis C patients. Social data, lifestyle and biochemical parameters were collected. Anthropometric assessment was carried out, being measured height, weight, waist circumference and hip circumference were measured. Then, body mass index, waist and height ratio, waist-to-hip ratio, visceral adiposity index and Framinghan risk score were calculated. For statistical analysis, chi-square test was applied, and simple and multiple logistic regressions have been performed to explore the correlation between anthropometric parameters and Framingham risk score, adopting a 5% significance level. Statistical Package for Social Science software was used. Results: 55 patients evaluated. It was observed that 56.36% presented cardiovascular risk according to waist circumference and waist-to-hip ratio, 78.18% according to the waist and height ratio, and 74.55% according to the visceral adiposity index. In the relation between Framingham risk score and anthropometric parameters it was observed that waist-to-hip ratio was considered a significant independent predictor (OR=14.7000; CI95% = 3.5360 – 61.1180). Conclusion: For the identification of visceral fat, it is suggested to use the waist-to-hip ratio because it indicated a probability for the development of cardiovascular events in individuals with hepatitis C.
Crafting Alliances between a Mexican Agribusiness and the Base of the Pyramid: An Action Research into Strategizing

Crafting Alliances Between A Mexican Agribusiness And The Base Of The Pyramid: An Action Research Into Strategizing By Sergio Quinones-Romandia May 2016 Committee Chair: Lars Mathiassen Major Academic Unit: J. Mack Robinson College of Business More than 4 billion people in the world face hunger every day. In addition to this imperative shortcoming, the world’s poor confront other side effects of poverty as well, including violence, forced mobility, lack of access to education and early death. In a globalized world where capitalism has become the prevailing economic ideology, alleviating poverty can no longer be the exclusive responsibility of governments, richer nations, and non-governmental organizations (NGOs). Today, the private sector must also “take the torch” and contribute to easing the suffering of more than half the world’s population. The Base of the Pyramid (BOP) strategy is an important opportunity for the world’s private sector to create new business opportunities while at the same time helping address and alleviate poverty. However, while the literature describes several study cases, we still have limited knowledge about the process through which managers engage in BOP strategizing. Against this backdrop, this dissertation provides a detailed account of how a Mexican agribusiness: Agroservicios Nacionales, SAPI de CV (ANSA) developed and implemented a BOP strategy to co-create value with its distributors and poor corn farmers. Our Georgia State University (GSU) research team combined Dynamic Capability
Future of Edge Computing for Real Time Devices in Internet of Things

Rapid growth of IoT applications and their interference in our daily lives led to many different IoT devices which generates enormous data. The IoT devices’ resources are very limited, so storing and processing IoT data in the devices is very inefficient. Several resources of cloud-computing are efficiently used to handle some IoT resources issues. While using resources in the cloud centers cause some other issues, like latency in the IoT applications, which are time-critical. Thus, the technology of edge cloud has evolved recently. This technology permits storage and data processing at the network edge. This paper studies edge computing in-depth for timeless sensitive devices in IoT. In-depth, cutting-edge IoT computing systems (ECAs-IoT) are evaluated and characterized in this paper according to numerous criteria, such as information placement, improvisation facilities, reliability, and data visualization. Moreover, according to distinctive properties, the paper aims at comparing each structure in detail. The paper also highlights the significant limitations of the new ECAs-IoT and recommends solutions to them. The studies also introduce and propose solutions to some of the most important restrictions of the current ECAs-IoT. Consequently, in the edge computing domain, this survey outlines the IoT implementations. Lastly, with the use of IoT implementations for ECAs-IoT, the paper suggests four distinct scenarios.
Supporting vulnerable students: Staff and parents speak

Background: Schools are at the forefront of promoting positive mental health and wellbeing through the implementation of evidence-based actions. Few Australian studies however have explored the views and experiences of school staff and parents as to what best supports secondary school students who struggle with positive mental health. Aims: This article describes findings from an exploratory study looking at the views and experiences of 74 staff and parents at four Melbourne Catholic Secondary schools. The study sought to understand how staff and parents experienced, offered and understood support to vulnerable secondary school students. Methods: The review and analysis drew on data collected from four staff groups and four parent focus groups. Participants in each group shared their views as to what they considered effective support to vulnerable secondary school students. Results: Findings indicated that the destigmatisation of mental ill-health conditions, greater attention to the transition between primary and secondary school, and the display of unconditional positive regard are critical to supporting vulnerable young students. Conclusion: Strengthening support to vulnerable young students requires school structures that (a) mitigate against stigmatisation, (b) recognise the period between childhood and adulthood as a time of heightened risk and (c) include staff whose posture towards vulnerable young students is one of unconditional positive regard.
Interagent Distance Control in a Cooperative Multiagent Target–Missile–Defender Engagement

A cooperative interception scenario between a maneuvering target, its defenders, and missiles attacking the said target is considered. The straightforward approach for optimal guidance laws synthesis for the scenario participants is to adopt objectives from the single agent target–missile–defender engagement analysis. This leads to a multiobjective optimization problem in which the cost function consists out of the squared miss distance and the control effort. In this article, we suggest to alter the aforementioned cost function in order to address the need to control the proximity level between the agents, a concept that is usually not accounted for in guidance law development. This approach utilizes the same quadratic framework, making it easy to add/include into traditional systems. Defensive (defenders collision avoidance) and offensive (missiles collision encouragement) cooperative distance control laws are developed for the end game phase using the same information used to implement the guidance law. Simulation results show that the desired distance control behavior can be achieved via the proposed method.
Development and Validation of a Risk Nomogram Model for Predicting Contrast-Induced Acute Kidney Injury in Patients with Non-ST-Elevation Acute Coronary Syndrome Undergoing Primary Percutaneous Coronary Intervention

Objective To establish a nomogram model to predict the risk of contrast-induced acute kidney injury (CI-AKI) by analyzing the risk factors of CI-AKI and to evaluate its effectiveness. Methods Retrospectively analyze the clinical data of non-ST-elevation acute coronary syndrome (NSTE-ACS) patients who underwent percutaneous coronary intervention (PCI) in our cardiology department from September 2018 to June 2021. Of these, patients who underwent PCI in an earlier period formed the training cohort (70%; n = 809) for nomogram development, and those who underwent PCI thereafter formed the validation cohort (30%; n = 347) to confirm the model’s performance. The independent risk factors of CI-AKI were determined by LASSO regression and multivariable logistic regression analysis. By using R software from which nomogram models were subsequently generated. The nomogram was developed and evaluated based on discrimination, calibration, and clinical efficacy using the concordance statistic (C-statistic), calibration plot, and decision curve analysis (DCA), respectively. Results The nomogram consisted of six variables: age >75, left ventricular ejection fraction, diabetes mellitus, fibrinogen-to-albumin ratio, high-sensitive C-reactive protein, and lymphocyte count. The C-index of the nomogram is 0.835 (95% CI: 0.800–0.871) in the training cohort and 0.767 (95% CI: 0.711–0.824) in the validation cohort, respectively. The calibration plots exhibited that the nomogram was in good agreement between prediction and observation in the training and validation cohorts. Decision curve analysis and clinical impact curve suggested that the predictive nomogram had clinical utility. Conclusion The nomogram model established has a good degree of differentiation and accuracy, which is intuitively and individually to screen high-risk groups and has a certain predictive value for the occurrence of CI-AKI in NSTE-ACS patients after PCI.