Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigations on Dynamical Stability in 3D Quadrupole Ion Traps

We firstly discuss classical stability for a dynamical system of two ions levitated in a 3D Radio-Frequency (RF) trap, assimilated with two coupled oscillators. We obtain the solutions of the coupled system of equations that characterizes the associated dynamics. In addition, we supply the modes of oscillation and demonstrate the weak coupling condition is inappropriate in practice, while for collective modes of motion (and strong coupling) only a peak of the mass can be detected. Phase portraits and power spectra are employed to illustrate how the trajectory executes quasiperiodic motion on the surface of torus, namely a Kolmogorov–Arnold–Moser (KAM) torus. In an attempt to better describe dynamical stability of the system, we introduce a model that characterizes dynamical stability and the critical points based on the Hessian matrix approach. The model is then applied to investigate quantum dynamics for many-body systems consisting of identical ions, levitated in 2D and 3D ion traps. Finally, the same model is applied to the case of a combined 3D Quadrupole Ion Trap (QIT) with axial symmetry, for which we obtain the associated Hamilton function. The ion distribution can be described by means of numerical modeling, based on the Hamilton function we assign to the system. The approach we introduce is effective to infer the parameters of distinct types of traps by applying a unitary and coherent method, and especially for identifying equilibrium configurations, of large interest for ion crystals or quantum logic.
Managing Heat Transfer Issues in Thermoelectric Microgenerators

This chapter deals with heat transfer challenges in the microdomain. It focuses on practical issues regarding this matter when attempting the fabrication of small footprint thermoelectric generators (μTEGs). Thermoelectric devices are designed to bridge a heat source (e.g. hot surface) and a heat sink (e.g. ambient) assuring that a significant fraction of the available temperature difference is captured across the active thermoelectric materials. Coexistence of those contrasted temperatures in small devices is challenging. It requires careful decisions about the geometry and the intrinsic thermal properties of the materials involved. The geometrical challenges lead to micromachined architectures, which silicon technologies provide in a controlled way, but leading to fragile structures, too. In addition, extracting heat from small systems is problematic because of the high thermal resistance associated to heat exchanged by natural convection between the surrounding air and small bare surfaces. Forced convection or the application of a cold finger clearly shows the usefulness of assembling a heat exchanger in a way that is effective and compliant with the mechanical constraints of micromachined devices. Simulations and characterization of fabricated structures illustrate the effectiveness of this element integration and its impact on the trade-off between electrical and thermal behavior of the active materials in device performance.
The magnetic tunnel junction device and fabrication

Magnetic tunnel junction (MTJ) devices and fabrication methods are disclosed. In certain embodiments, the method comprising the steps of forming a magnetic tunnel junction (MTJ) device on the structure including the bottom bottom metal-filled trench having a cap layer and the vertical axis is disclosed magnetic tunnel junction device, the bottom electrodes, wherein the MTJ layer, a magnetic tunnel junction seal layer, an upper electrode, and the logic cap layer, a magnetic tunnel junction device has a MTJ axis that is offset from the vertical axis.
Can a Remote Sensing Approach with Hyperspectral Data Provide Early Detection and Mapping of Spatial Patterns of Black Bear Bark Stripping in Coast Redwoods?

The prevalence of black bear (Ursus americanus) bark stripping in commercial redwood (Sequoia sempervirens (D. Don) Endl. ) timber stands has been increasing in recent years. This stripping is a threat to commercial timber production because of the deleterious effects on redwood tree fitness. This study sought to unveil a remote sensing method to detect these damaged trees early and map their spatial patterns. By developing a timely monitoring method, forest timber companies can manipulate their timber harvesting routines to adapt to the consequences of the problem. We explored the utility of high spatial resolution UAV-collected hyperspectral imagery as a means for early detection of individual trees stripped by black bears. A hyperspectral sensor was used to capture ultra-high spatial and spectral information pertaining to redwood trees with no damage, those that have been recently attacked by bears, and those with old bear damage. This spectral information was assessed using the Jeffries-Matusita (JM) distance to determine regions along the electromagnetic spectrum that are useful for discerning these three-health classes. While we were able to distinguish healthy trees from trees with old damage, we were unable to distinguish healthy trees from recently damaged trees due to the inherent characteristics of redwood tree growth and the subtle spectral changes within individual tree crowns for the time period assessed. The results, however, showed that with further assessment, a time window may be identified that informs damage before trees completely lose value.
Serendipity in doctoral education: the importance of chance and the prepared mind in the PhD

ABSTRACT When Louis Pasteur remarked that chance favours the prepared mind, he was commenting on the important role played by serendipity in scientific discovery. That role is well known (most know of the story of Fleming’s accidental discovery of penicillin) but much of the literature focuses on the STEM disciplines, on ‘big’ science, and concentrates on the work of established scientists. There is virtually no discussion of the role of serendipity in the doctoral research arena, an arena which contributes significantly to contemporary scientific endeavour and the associated publications. This article reports the initial results from a survey of doctoral students and PhD graduates which explores how serendipity contributes to the PhD process and also the forms serendipity takes in this arena. Following the conceptual differentiation of serendipity from accident or chance, the article explores the intersection of serendipity with doctoral research. Most respondents reported serendipitous occurrences happening in the doctoral experience, with the most important involving them stumbling across unexpected and unsearched-for literature, meeting others who proved to be significant for both their research and also their future development and careers, and finding project-related artefacts which expanded their projects and thinking. There were also reports of second-hand serendipity a hitherto uncommented on phenomenon. Many of the serendipitous occurrences involved a social context and actors other than the doctoral student, placing a focus on the researcher as someone with the ability and opportunities to make connections rather than simply relying on luck.
Triple Modular Redundancy Optimization for Threshold Determination in Intrusion Detection Systems

This paper presents a novel approach for an Intrusion Detection System (IDS) based on one kind of asymmetric optimization which use any three already well-known IDS algorithms and Triple Modular Redundancy (TMR) algorithm together. Namely, a variable threshold which indicates an attack on an observed and protected network is determined by using all three values obtained with three known IDS algorithms i.e., on previously recorded data by making a decision by majority. For these algorithms authors used algorithm of k-nearest neighbors, cumulative sum algorithm, and algorithm of exponentially weighted moving average. Using a proposed method we can get a threshold that is more precisely determined than in the case of any method individual. Practically, using TMR we obtain a dynamically threshold adjustment of IDS software, which reduces the existence of false alarms and undetected attacks, so the efficiency of such IDS software is notably higher and can get better results. Today, Denial of Service attacks (DoS) are one of the most present type of attacks and the reason for the special attention paid to them in this paper. In addition, the authors of the proposed method for IDS software used a known CIC-DDoS2019 dataset, which contains various data recordings of such attacks. Obtained results with the proposed solution showed better characteristics than each individual used algorithm in this solution. IDS software with the proposed method worked precisely and timely, which means alarms were triggered properly
Improvement Performances of Sensorless Control for PMSM Based on DTC Strategy Using SMO Observer and RL-TD3 Agent

One of the elements that contribute to increasing the reliability of the control system of a Permanent Magnet Synchronous Motor (PMSM) is the replacement of the speed transducers with software-implemented speed observers. Based on this, this paper concern on the sensorless control of a PMSM using the Direct Torque Control (DTC) control type strategy, in which a speed observer is used in combination with a Reinforcement Learning - Twin Delayed Deep Deterministic Policy Gradient (RL-TD3) type agent to increase the accuracy of the PMSM rotor speed estimation. The latter, after the training stage, can provide correction signals to the speed observer so that the estimated speed is as close as possible to the estimated speed. The control structures, control algorithms and operating equations of the PMSM, the DTC-type control strategy and speed observer are presented in this article. Numerical simulations realized in the Matlab/Simulink programming environment validate the superiority of the PMSM rotor speed estimation performance in case of using an RL-TD3 type agent in join with a speed observer, compared to the case of using the speed observer alone.
Multisourced Flood Inventories over the Contiguous United States for Actual and Natural Conditions

A reliable flood event inventory that reflects the occurrence and evolution of past floods is important for studies of flood hazards and risks, hydroclimatic extremes, and future flood projections. However, currently available flood inventories are based on single-sourced data and often neglect underreported or less impactful flood events. Furthermore, traditional archives store flood events only at sparse geographic points, which significantly limits their further applicability. Also, few publicly available archives contain all-inclusive records of potential natural flooded area over time. To tackle these challenges, we construct two types of multisourced flood event inventories (MFI) for all river basins across the contiguous United States covering the period 1998–2013 on daily and subcatchment scales, which is publicly available at http://flood.umd. edu/download/CONUS/. These archives integrate flood information from in situ observations, remote sensing observations, hydrological model simulations, and five high-quality precipitation products. The first inventory (MFI-Actual) includes all actual floods that occurred in the presence of flood protection infrastructures, while the second, “natural (undefended)” inventory (MFI-Natural) reconstructs the possible “historical” floods without flood protection, which could be more directly influenced by climate variation. In the proposed two inventories, 2,755 and 4,661 flood events were estimated, respectively. MFI-Natural reconstructed 1,597 floods in ungauged basins, and recovered 608 extreme streamflow events in gauged subcatchments where floods would have happened if there were no flood protection. There is an average of four upstream dams located in these flood-recovered subcatchments, which indicates that modern flood defenses efficiently prevent significant flooding from extreme precipitation in many catchments over the country.
Analytical solution for flange/web distortional buckling of cold-formed steel beams with circular web perforations

Abstract Perforated cold-formed steel (PCFS) beams are increasingly used in constructional industry and become popular due to their advantages and economic benefit. Apart from the light weight, the openings in PCFS beams can also be used for services such as pipe utilities to release more building space. However, beams with web perforations may collapse as the result of web-distortional buckling or flange/web distortional buckling due to the web weakness caused by perforations. In this paper a study on the flange/web distortional buckling of PCFS beams is presented. An analytical solution to determine the critical stress of flange/web distortional buckling of PCFS beams is derived by using energy method. To demonstrate the analytical solution, finite element analysis is also carried out. The finite element analysis results show that the analytical solution provided can give good and reliable prediction for the flange/web distortional buckling of PCFS beams.
Organic acids induce by metal-tolerant Pantoea sp. WP-5 and biogas residues enhanced phytostabilization of cadmium in soil

This study investigated the phytoremediation potential of maize (Zea mays L.) in Cd contaminated soil through co-inoculation of metal tolerant plant beneficial rhzobacteria (MtPBR: Pantoea sp. strain WP-5) with organic manures (PM: poultry manure and BGR: biogas residues). The objectives of this study were to i) examine comparative efficiency of MtPBR, PM and BGR alone or in combined form to improve maize biomass and physiology, and ii) understand the role of organic acid production in root exudates of maize for Cd accumulation and translocation. Pantoea sp. WP-5 showed tolerance to high Cd concentration (1000 mg L− 1), thereby inoculated to maize seeds sown in soil spiked with 75 mg Cd kg− 1 soil and 500 g each of the organic manures per pot. The co-inoculation of MtPBR + BGR significantly (P < 0.05) increased chlorophyll contents, root/shoot dry weight, photosynthetic rate, stomatal conductance and relative water contents, whereas decreased electrolyte leakage, malondialdehyde contents, ascorbate peroxidase and catalase activity in maize over the control treatment. The co-inoculation of MtPBR + BGR produced significantly (P < 0.05) higher concentrations of acetic and citric acid (52.7 ± 0.5 and 22.8 ± 0.08 µg g− 1 root fwt, respectively) in root exudates of maize, which immobilized Cd within plant roots inferred by the positive relation (root Cd vs. organic acids; R2 = 0.80–0.92) and reduced Cd translocation to shoots inferred by the negative relation (shoot Cd vs. organic acids; R2 = 0.81–0.90). It is concluded that the application of MtPBR + BGR enhanced organic acid induced phyto-stabilization and accumulation of Cd in roots and restricted its translocation to shoots.
Solar Harvesting through Multilayer Spectral Selective Iron Oxide and Porphyrin Transparent Thin Films for Photothermal Energy Generation

A fundamental challenge in energy sustainability is efficient utilization of solar energy towards energy‐neutral systems. The current solar cell technologies have been most widely employed to achieve this goal, but are limited to a single‐layer 2D surface. To harvest solar light more efficiently, a multilayer system capable of harvesting solar light in a cuboid through transparent photothermal thin films of iron oxide and a porphyrin compound is developed. Analogous to a multilayer capacitor, an array of transparent, spectral selective, photothermal thin films allows white light to penetrate them, not only collecting photon energy in a 3D space, but generating sufficient heat on each layer with significantly increased total surface area. In this fashion, thermal energy is generated via a multilayer photothermal system that functions as an efficient solar collector, energy converter and generator with high energy density. A solar‐activated thermal energy generator that can produce heat without any power supply and reach a maximum temperature of 76.1 °C is constructed. With a constant incoming white light (0.4 W cm−2), the thermal energy generated can be amplified 12‐fold via multilayers. The multilayer system extends another dimension in solar harvesting and paves a new path to energy generation for the energy‐neutral system.
Long Short-Term Memory Networks and Bayesian Optimization for Predicting the Time-Weighted Average Pressure of Shield Supporting Cycles

Characteristic parameters of shield supporting in fully mechanized mining, especially time-weighted average pressure (TWAP), are crucial for the analysis and prediction of roof weightings in longwall panels. Despite the leap-forward development of underground data collection and transmission, mining and regional correlation analysis of massive shield data remains challenging. In this study, a hybrid machine learning model integrating the long short-term memory (LSTM) networks and the Bayesian optimization (BO) algorithm was developed to predict TWAP based on the setting pressure (SP), revised setting pressure (RSP), final pressure (FP), number of yielding (NY), TWAP in the last supporting cycle (TWAP (last)), and loading rate in each period. Statistical measures including the mean square error and mean absolute error were used to validate and compare the prediction performances of the BP model, the LSTM model, and the BO-LSTM model. Furthermore, sensitivity studies were carried out to evaluate the importance of input parameters. The results show that the BO-LSTM model is robust in predicting TWAP. FP and TWAP (last) are the most important input parameters in TWAP prediction, followed by RSP and NY. Moreover, the total importance scores of loading rates reach 0.229, indicating the necessity of including these parameters into the dataset. The proposed BO-LSTM model is capable of predicting TWAP which serves for shield-roof status intelligent perception.
Understanding the Stiffness of Porous Asphalt Mixture through Micromechanics

Micromechanics, which can be used to relate the properties of a composite to the properties of individual constituents, is considered a good approach to understanding the fundamental mechanisms behind the behavior of asphalt materials. Compared with the semi-empirical and numerical micromechanical models, analytical micromechanical models do not need calibration factors. In addition, they can provide analytical solutions on the basis of a series of assumptions. Using these models, researchers have separated the effects of different stiffening mechanisms (i.e., the volume-filling reinforcement, the physicochemical reinforcement, and the particle-contact reinforcement) for mastic. However, similar research work has not been conducted for asphalt mixtures and, moreover, the characteristics of the particle-contact reinforcement have not been deeply analyzed by researchers. Therefore, this paper aims to understand the stiffness of asphalt mixture through micromechanics. The focus of this study was on porous asphalt mixture where particle-contact reinforcement plays an important role in its behavior. The stiffening effects of different mechanisms were separated using analytical micromechanical models. The effects of temperature/frequency and the properties of the matrix phase on the stiffening effect of the particle-contact reinforcement were analyzed.
Copper‐Modified Gold Nanoparticles as Highly Selective Catalysts for Glycerol Electro‐Oxidation in Alkaline Solution

The C3 selectivity of carbon‐supported Au nanoparticles for glycerol electro‐oxidation was significantly enhanced by the interaction of Au with electro‐deposited Cu species. Notably, the C3 selectivity of supported Au nanoparticles doubled after 90 min of Cu electro‐deposition at +0.015 V. This result was obtained if glycerol electro‐oxidation was performed at +0.1 V for 2 h. The most selective catalysts contained an Au+ species that was generated by an interaction between Au and electro‐deposited Cu2O. The presence of Au+ increased the selectivity to glycerate and tartronate and suppressed C−C bond cleavage to glycolate and formate simultaneously.
When Is Choice Empowering? Examining Gender Differences in Varietal Adoption through Case Studies from Sub-Saharan Africa

This paper examines the question of what makes choice empowering and critiques prevalent approaches to empowerment focused narrowly on agency as the ability of individuals to make their own free choices and act independently. The implications of a narrow focus on agency are illustrated with the examples of technology choice in agriculture, specifically choices involved in the adoption of improved plant varieties. This example elucidates the limits of individual agency and permits an analysis of how choices may be structured to be either empowering or disempowering, with examples from specific plant breeding cases. In view of the importance given to equitable choice of technology for closing the gender gap in agricultural productivity and sustainability, the paper explores what practical steps can be taken towards a balanced approach to empowerment. An approach to designing a new plant variety by constructing choice differently is illustrated, using information on gender relations. The paper derives lessons from the plant breeding cases to inform other kinds of interventions, so that work on how choices are defined is given as much importance for empowerment as creating the option to choose. Agents who exercise power over rules and resources can either reproduce the status quo or innovate; thus, a balanced approach to empowerment requires careful analysis of the elements of choice.
The Impact of Land Use Change on Disaster Risk from the Perspective of Efficiency

The increasing demand of humankind has caused a large number of land use changes, which pose a direct or indirect threat to the environment while promoting economic growth. The lack of risk-oriented land use changes may increase the disaster risk in the region. Therefore, how to study the relationship between land use change and disaster risk deserves attention. In this study, a research framework with quantitative relationship between land use change and disaster risk was constructed from the perspective of efficiency. The framework integrated land use change, disaster losses and environment variable (runoff increment) into a three-stage data envelopment analysis (DEA) assessment model to dynamically evaluate the impact of land use changes on disasters. The main conclusions include: (I) after the influence of runoff increment and random error was excluded, the overall risk score of counties and cities in Taiwan is 0.643, which represents a relatively high level, indicating that land use changes have caused high disaster risk; and (II) the vulnerability of land development in each county and city can be obtained through the comprehensive score of disaster risk the amount of unused input. The results of this study can help government agencies to rank various types of land development and then determine the acceptable risk level and incorporate disaster risk into land development.