Miracle-dz/UniFAR-FTUs huggingface dataset:
UNCERTAINTIES IN CLIMATE TRENDS Lessons from Upper-Air Temperature Records

Historically, meteorological observations have been made for operational forecasting rather than long-term monitoring purposes, so that there have been numerous changes in instrumentation and procedures. Hence to create climate quality datasets requires the identification, estimation, and removal of many nonclimatic biases from the historical data. Construction of a number of new tropospheric temperature climate datasets has highlighted previously unrecognized uncertainty in multidecadal temperature trends aloft. The choice of dataset can even change the sign of upper-air trends relative to those reported at the surface. So structural uncertainty introduced unintentionally through dataset construction choices is important and needs to be understood and mitigated. A number of ways that this could be addressed for historical records are discussed, as is the question of How it needs to be reduced through future coordinated observing systems with long-term monitoring as a driver, enabling explicit calculation.
Virtual Commissioning Simulation as OpenAI Gym - A Reinforcement Learning Environment for Control Systems

Manual development of control systems’ software is time-consuming and error-prone. Thus, high costs are already incurred in this phase of mechatronic system development. Virtual prototypes have so far only been used for testing purposes, such as virtual commissioning, but not for the automated creation of the control. A good test environment can also be extended to a learning environment with appropriate trial and error based algorithms. This work shows an approach to extend an industrial software tool for virtual commissioning as a standardized OpenAI gym environment. Thereby, established reinforcement learning algorithms can be used more easily and a step towards an industrial application of self-learning control systems can be made. The goal of this work is to provide industry and research with a platform for easy entry into the field of reinforcement learning.
Training Deep Learning Spacecraft Component Detection Algorithms Using Synthetic Image Data

On-orbit satellite servicing can benefit from increased local autonomy when long time delays prevent effective teleoperation. One required perception capability is automated detection and classification of spacecraft components. Recent developments in Deep Learning (DL) object detection can be applied to spacecraft component detection and classification. However, training such algorithms requires large amounts of labeled training images. In the satellite servicing domain, large datasets of labeled on-orbit satellite images generally do not exist. In this paper, we compare two approaches for training DL object detectors for data starved applications. In the first approach, a small number of real satellite images were manually labeled and then augmented via transformations to obtain sufficient training images. In the second, synthetic images were generated in simulation and automatically labeled, creating four datasets, one the same size as the augmented real dataset and three larger datasets. Our main objective was to demonstrate that synthetic images can be used to successfully train spacecraft component detectors, eliminating the need to collect and manually label large sets of real satellite images. Our secondary objective was to assess the effect of the size of the synthetic training dataset on detection performance. The small set of real images used are photographs of the Hubble Space Telescope (HST) taken during HST servicing missions. The Unity video game engine was used to simulate the HST and space environment, and to generate synthetic image datasets in which the lighting, viewing geometry, and surface material properties were varied. Labeling involved drawing bounding boxes around five object classes: the telescope aperture cover, telescope baffle, solar panels, antennas, and spacecraft bus. Multiple DL Faster Regional Convolutional Neural Network (Faster R-CNN) object detectors were trained to detect all five classes using multiple random subsets of the augmented real dataset and of the synthetic datasets. All of the detectors were tested on random subsets of images from the augmented real dataset. Receiver Operating Characteristic (ROC) curves were generated and the Area Under the Curve (AUC) was calculated for each class. For each Faster R-CNN detector, the average AUC across all classes was used as a single figure of merit for object detection performance. We found that detectors trained on synthetic Unity images can perform as well or better than detectors trained on an augmented set of a small number of real images, and that performance improves as the number of synthetic training images increases.
Development of a Monolithic Pneumatic Soft Actuator for Fruit Grasping*

In soft grippers, deformable materials are crucial for safety and adaptability. However, materials alone are not enough to ensure a successful grip. Soft grippers are generally designed to exploit precision or power grasp but still show limited versatility in handling objects whose characteristics are widely different. This paper presents a soft gripper with a monolithic pneumatic artificial muscle (M-PAM) design. The monolithic approach prevents failure from delamination while it improves lifetime. Concurrently, adjustable finger distance and a foam interface improve stability during grasping. The resulting structure exerts a maximum force of 1.95 N and reaches a bending angle of 78.27° corresponding to a positive pressure of 18 kPa. Furthermore, an optimized geometry increases the contact area and grasping strength. A soft gripper integrating two M-PAMs is demonstrated grasping fruit with dimensions ranging from 0.5 to 65 mm.
Avoidant/Restrictive Food Disorder (ARFID), Food Neophobia, Other Eating-Related Behaviours and Feeding Practices among Children with Autism Spectrum Disorder and in Non-Clinical Sample: A Preliminary Study

Previous research shows that children with autism spectrum disorder (ASD) may experience several difficulties—including those related to eating—and this area of research needs to be explored further. This study had two main objectives: (1) comparison of the clinical (autism spectrum disorder) and non-clinical sample of children in terms of avoidant/restrictive food disorder, food neophobia, other eating-related behaviours and feeding practices; (2) assessment of selected predictors of food neophobia. The final sample included 54 children and parents from the clinical sample (ASD) and 51 from the non-clinical sample. Parents completed: the autism spectrum rating scales (ASRS), the eating disorders in youth questionnaire (EDY-Q), the children food neophobia scale (CFNS), the child eating behaviour questionnaire (CEBQ), the child feeding questionnaire (CFQ), and a socio-demographic survey. Our analysis allowed us to partially confirm the first hypothesis since the clinical sample (vs. the non-clinical group) had significantly higher scores in such variables as (a) avoidant/restrictive food disorder (ARFID), (b) food neophobia, (c) other eating-related behaviours: emotional under-eating, desire to drink, food fussiness, (d) feeding practices: pressure to eat. Moreover, our analysis of predictors of food neophobia in the clinical and non-clinical samples also allowed us to partially confirm the second hypothesis because it turned out that only in the clinical sample (vs. the non-clinical sample) were the predictors significantly associated with food neophobia, but only two of them (food fussiness and selective eating). In conclusion, our study showed that children with ASD (compared to children without this diagnosis) experience increased difficulties in eating behaviours, and their parents present a stronger intensity of the feeding practice based on pressure to eat. This study showed that feeding problems for children in the ASD sample are a significant problem, and it is still worth exploring this area in research.
Robotic Fish driven by Twisted and Coiled Polymer Actuators at High Frequencies

Twisted and coiled polymer (TCP) actuator is a promising novel actuator, exhibiting attractive properties of light weight, low cost, high energy density and simple fabrication process. However, coiled polymer actuators have low non-resonant actuation frequencies because of the time needed for heat dissipation during the relaxation phase. This restricts them to applications where frequencies are less than 0.5 Hz. In this paper, we present a robotic fish driven by a novel TCP-spring antagonistic pair at high frequencies in water. By minimizing the distance between the TCP and the spring, the robot achieved a maximum swimming velocity of 25.7 mm/s (11.5% body length/s) by undulatory flapping of its caudal fin at a frequency of 2 Hz using periodic Joule heating. This demonstrates the highest frequency and swimming speed achieved for a TCP actuator in a practical aquatic application. The design, fabrication and verification of the fish robot, including characterisation of the TCP actuators in air and water, are presented. A study on different fin stiffness is also presented. This paper provides a new route to raising the actuation frequency of TCPs through thermomechanical design and shows the possibility of using TCPs at high frequency in aqueous environments.
Chromosomal aberrations and prognostic analysis of secondary acute myeloid leukemia—a retrospective study

Background Secondary acute myeloid leukemia (S-AML) patients generally have a poor prognosis, but the chromosomal aberrations of S-AML have been rarely reported. We aimed to explore the chromosomal aberrations and clinical significance in patients with S-AML. Patients and methods The clinical characteristics and karyotypes of 26 patients with S-AML were retrospectively analyzed. The overall survival (OS) was measured from the time of the patients’ transition to AML (i.e., at S-AML diagnosis). Results The study included 26 S-AML patients (13 males and 13 females), with a median age of 63 years (range, 20–77 years). They transformed from various hematologic malignancies or solid tumors; most of them were secondary to myelodysplastic syndrome (MDS). About 62% of the S-AML patients showed chromosomal aberrations. The serum lactate dehydrogenase (LDH) level in S-AML patients with abnormal karyotype was higher than those with normal karyotype. Apart from the differences in treatment regimens, S-AML patients with chromosomal aberrations had shorter OS (P < 0.05). Conclusion S-AML patients with abnormal karyotype have higher LDH levels and shorter OS than normal karyotype patients, and the OS of hypodiploidy was much shorter than hyperdiploid.
FIXED POINT THEOREMS FOR CONTRACTION MAPPINGS SATISFYING ASYMPTOTICALLY REGULARITY IN INTEGRAL SETTING

In the present paper, we prove analogues of some fixed pointic results for contraction type mappings having asymptotic regularity property in integral setting. 2000 Mathematics Subject Classification: Primary 47H10; Secondary 54H25. Key words and phrases: fixed point, general contractive condition, integral type.
Progress and Challenges of Chloride–Iodide Perovskite Solar Cells: A Critical Review

Chloride–iodide perovskites have received substantial interest due to their better photovoltaic performance compared to pure iodide ones. The superior properties of chloride–iodide perovskites boost photovoltaic performance. However, quantifying the Cl composition in perovskite films remains challenging. Hence, it is not easy to correlate the Cl quantity with the improved photovoltaic performance. Considering this critical issue, it is still necessary to determine the correlation between the Cl quantity and the improved photovoltaic performance to solve this puzzle. Here, a critical review is presented showcasing the significant impacts of the Cl quantity on chloride–iodide perovskites and related solar cell devices. This review provides an up-to-date picture of different strategic methods to overcome the challenges of Cl incorporation in I-based perovskites, aiming to improve photovoltaic performance. Finally, some valuable remedies are prescribed for potential future research strategies to study the photovoltaic performance of chloride–iodide perovskite solar cells. Hopefully, this review will be a noteworthy scientific contribution to the advancement of the continuous progress of perovskite solar cells.
Analysis of Speech Emotion Recognition and Detection using Deep Learning

Speech emotion recognition (SER) is a mechanism to identify emotions from speech or voice. With the help of SER, robots can understand human feelings. In this challenging world, SER is one of the latest inventions that help to know about human emotion when saying words. Before the widespread use of deep learning, SER relied on various approaches, including support vector machines (SVM) and hidden Markov models (HMM) with several distinct and preprocessing technical features. SER is a challenging task of computational human interaction. This topic has gotten so much attention in the past couple of years. Numerous techniques have been used in speech emotion recognition to extract emotions from voice signals, including several well-developed speech examinations and classification methods. In the traditional way of speech emotion, recognition features are extracted from the speech signals. Then the features are selected, which is collectively known as the selection module, and then the emotions are recognized. This is a very lengthy and time taking process. This paper design an algorithm based on feature extraction and model creation that recognizes the emotion based on the deep learning technique.
GeDeE - an application for generating, deriving and evaluating mathematical expressions

GeDeE is and application for generating expressions and handling them, for deriving expressions and interpreting them numerically. In this paper, the GeDeE structure has been presented and its using way has been exemplified for a 3D inverse kinematics application for hyper-redundant robots. This is only one example, the GeDeE structure allowing easy adaptability for any other type of expressions application. An expressions' generator has been built in order to store the values of the operational coordinates and then to determine an expressions' Jacobian. Algorithms for generation and deriving expressions have been created. Derivation and decryption have been achieved using an interpreter.
Vector model-based robot-assisted control system for a wheeled mobile robot

ABSTRACT A robot-assisted control system based on the vector model is proposed for a wheeled mobile robot. According to the closed-loop control structure, the system is constituted of two parts – localization and path planning. The localization algorithm, which is enhanced from Monte Carlo localization, is more effective, stable, and robust than the traditional algorithm because of using many strengthening mechanisms, such as using a vector model, re-initialization, and reverse convergence. The path planning algorithm includes three stages to obtain a path with a motion plan. Firstly, a path from the current position to the goal is planned by an enhanced A* algorithm. Secondly, a smooth mechanism is applied to the path to obtain the continuity of orientation. Finally, a motion design based on the trapezoidal-curve velocity profile is implemented to the smoothed path in both linear and angular velocities to obtain the estimated moving time, position schedule, and velocity schedule. With the assisted control system, the robot knows its current position, the path with motion planning to the destination and its estimated arrival time. If the robot deviates from the move plan, the system will reschedule based on the current state. The experimental results show the great performance of our proposed method.
Work Stressors and the Buffering Functions of the Sense of Control in the United States and Japan: A Test of the Diminished Buffering Hypothesis

In the Stress Process Model, the sense of control is situated as a central psychosocial resource that buffers the effect of stressors on psychological distress. Although studies support this proposition, scholars have called for more research on whether buffering effects generalize across social contexts and groups. I address this call by examining cross-cultural differences in the sense of control’s buffering effects. Prior studies suggest that perceived control is a less important resource for well-being among individuals in collectivistic cultures compared with those in individualistic cultures. This has stimulated the diminished buffering hypothesis, which predicts weaker stress-buffering of perceived control among those in collectivistic cultures. This study tests this hypothesis using population-based data of Americans and Japanese, two groups that have been deemed quintessentially individualistic and collectivistic, respectively. Results show that across a set of five prominent work stressors, there are no differences in the stress-buffering functions of the sense of control between Americans and Japanese. These patterns pose questions about the view that sense of control is a less important resource for those in collectivistic cultures. As a stress-buffering resource, the sense of control appears to be just as important for Japanese as it is for Americans.
Design and Analysis of a Novel Reversible Airfoil Mechanism

Stop-rotor aircraft, which utilize a central lifting surface capable of transitioning between rotation and fixed configurations, offer a promising option for improving the efficiency of vertical take-off and landing aircraft. However, across the transition between rotation and fixed configurations, the necessary airfoil directionality for efficient aerodynamic performance changes. This work presents the design and experimental analysis of a novel reversible morphing airfoil capable of altering the airfoil directionality necessitated for stop-rotor aircraft. Inspired by roll-up chair design by Uros Vitas, the proposed morphing reversible airfoil, henceforth referred to as the folding slat method, takes shape primarily through a flexible strip that is symmetric about the center and consists of a series of rigid trapezoidal extrusions, forming slats, that are mounted on a flexible substrate. The directionality of the airfoil is switched by altering the compression and tension of each side of the strip, thereby pressing and releasing the contact points between the trapezoidal sections. While the proposed folding slat successfully morphed the leading and trailing edge, the experimental evaluation of the morphing airfoil was critical to justify its usage in a real system. As such, a suite of tests evaluating the compression, bending, and fatigue behaviors were performed. From this testing, it was shown that the folding slat could transfer up to a 150 N load without any added electrical energy usage and was able to switch the orientation of the leading and trailing edge at least 1,000 times, while still maintaining adequate stiffness.
The Fall Armyworm, Spodoptera frugiperda (Lepidoptera: Noctuidae), Influences Nilaparvata lugens Population Growth Directly, by Preying on Its Eggs, and Indirectly, by Inducing Defenses in Rice

The fall armyworm (FAW), Spodoptera frugiperda, has become one of the most important pests on corn in China since it invaded in 2019. Although FAW has not been reported to cause widespread damage to rice plants in China, it has been sporadically found feeding in the field. If FAW infests rice in China, the fitness of other insect pests on rice may be influenced. However, how FAW and other insect pests on rice interact remains unknown. In this study, we found that the infestation of FAW larvae on rice plants prolonged the developmental duration of the brown planthopper (BPH, Nilaparvata lugens (Stål)) eggs and plants damaged by gravid BPH females did not induce defenses that influenced the growth of FAW larvae. Moreover, co-infestation by FAW larvae on rice plants did not influence the attractiveness of volatiles emitted from BPH-infested plants to Anagrus nilaparvatae, an egg parasitoid of rice planthoppers. FAW larvae were able to prey on BPH eggs laid on rice plants and grew faster compared to those larvae that lacked available eggs. Studies revealed that the delay in the development of BPH eggs on FAW-infested plants was probably related to the increase in levels of jasmonoyl-isoleucine, abscisic acid and the defensive compounds in the rice leaf sheaths on which BPH eggs were laid. These findings indicate that, if FAW invades rice plants in China, the population density of BPH may be decreased by intraguild predation and induced plant defenses, whereas the population density of FAW may be increased.
SCoReR: Sensorized Collision Resilient Aerial Robot

Detection and control of the physical contact/impact between micro aerial vehicles and the surrounding obstacles have become a significant issue with the rapid growth of their use in inspection and mapping missions in confined, obstacle-cluttered environments. In this work, we introduce a collision-resilient compliant micro quadcopter equipped with soft coil-spring type force sensors to passively resist and detect the physical contact/impact of the drone. The sensors act as resistive elements with a nominal resistance of 130–150 kΩ. They are manufactured from a conductive material via FDM 3D printing. We install these sensors on the protective bumpers of the collision-resilient foldable body of the drone. Any contact/impact between the bumpers and an obstacle results in deformation and buckling of the soft sensors, which results in a drastic change in their resistance, making it possible to detect the contacts/impacts of the bumpers. With a total weight of 220g and dimensions of 22cmx22cmx9cm, SCoReR successfully detects and recovers 100% of the contacts/impacts when it approaches a rigid wall with a velocity in the range of [0.1-1] m/s.
Continuous Attribute Discretization Based on Inflection Point

Continuous attribute discretization plays an important role in data mining. A novel discretization method based on inflection point of curve is presented, which includes calculating the all inflexion points as a candidate discrete point based on the mathematical definition of inflection point, then using decision attribute types of sample as constraint condition, and obtaining the final discrete segment points by Nearest Neighbor Rule. After the actual processing for logging attributes discretization and comparative analysis, the results show that the compatibility of presented discretization method is high in the condition of keeping indiscernibility relation, and its effect is superior to that of the discretization algorithm based on attribute importance.
Current Scalability Issues in Multi-Bank 5V PMOS ESD structures: Root cause and Design Guideline

In this work, a unique Human Body Model (HBM) failure is presented in 5V-PMOS multi-finger structures. The failure is sensitive to the multi-bank layout, generally used to achieve higher holding voltage. Missing Transmission Line Pulse (TLP) failure current (It2) scalability is detected with pulse width, in multi-bank structures and a correlation is established with lower HBM failure. A detailed 3D- TCAD analysis approach is used to understand the PMOS turn-on in the single-bank and multi-bank structures, in turn, the It2 scalability for longer pulse width. The obtained insights are used to provide design guidelines for developing robust PMOS devices.