Miracle-dz/UniFAR-FTUs huggingface dataset:
Authors’ Reply: The Expected Discounted Penalty at Ruin for a Markov-Modulated Risk Process Perturbed by Diffusion - Discussion by Bangwon Ko

AUTHORS’ REPLY We are grateful to have such an insightful discussion. Mr. Ko provides a unified and efficient method to derive the systems of integro-differential equations satisfied by the expected discounted penalty functions at ruin caused by a claim and oscillation by introducing a concept of the contingent payoff for the underlying model. We believe that this method can be used for further research on the risk processes perturbed by diffusion. Mr. Ko also pointed out that equations (2.3) and (2.5) can be derived (without using equation (2.7) of Cai and Xu 2006) by lemma for jump-diffusion processes. Actually, equation (2.7) of Cai and Ito’s ˆ Xu (2006) is a special case of equation (2.6) of Paulsen and Gjessing (1997), which was also derived by lemma for a diffusion-perturbed risk process with stochastic interest rate. Alternatively, a Ito’s ˆ traditional approach can be used to obtain equations (2.3) and (2.5) (see Tsai and Willmot 2002). We illustrate the derivation below. First, we write equation (2.2) again as follows:
Evaluation of MAI Effect in Encoding Techniques for an Infrared Positioning System

Signal attenuation and multipath effect limit the behaviour of Global Navigation Satellite System (GNSS) in outdoor environments. Thus, there is a current trend on finding a centimetric accuracy three-dimension optical indoor positioning system using LEDs and photodiodes. There are several works that rely on encoding techniques to distinguish between transmitters. Due to the simultaneous reception, interferences between the cross-correlation signals may appear (Multiple Access Interference, MAI). In this way, the implemented encoding technique is crucial to remove the existent Multiple Access Interference (MAI) effect. In this work, Kasami, LS (Loosely Synchronized) and T-ZCZ (Three Zero-Correlation Zone) sequences with different lengths from 71 to 1024 bits have been analysed with the final goal of mitigating the MAI effect in the estimation of the receiver’s position. Simulations and experimental results, at a distance of 2m between transmitters and receiver, prove a better behaviour with the 1151-bit LS sequences achieving standard deviations below 0.25cm for plane XY and average absolute errors below 0.3 and 7.4cm in simulations and experimental tests, respectively.
Usage of Psychophysiological Data as an Improvement in the Context of Software Engineering: A Systematic Mapping Study

A systematic mapping had been developed seeking for answering six research questions regarding using of psychophysiological data in the Software Engineering domain. Employing it was selected 2084 studies from 7 digital databases, reaching a final amount of 27 articles. Mostly of experimental nature, marked by usage of the sensing devices and integrated development environments (IDEs), looking for analysis of developers’ psychophysiological attributes applied to comprehension and debugging of source code. It was not identified as native mechanisms to support psychophysiological data integration and analysis within the integrated development environment.
Evaluation of In Vitro Antioxidant Activity of stem-bark and stem-wood of Premna serratifolia Lin., (Verbenaceae)

Premna serratifolia Lin. , is widely used in Ayurvedic system medicine for the treatment of cardiovascular disorders, arthritis, inflammation etc. The stem-bark and stem-wood were extracted with 95% ethanol and double distilled water and these extracts were screened for their in-vitro antioxidant potential. Inhibition of oxygen-derived free radicals, viz., assays for free radical scavenging by DPPH, reducing power ability and nitric oxide scavenging were performed. All the antioxidant activities were compared with standard antioxidant such as ascorbic acid. Both the extracts of this plant showed effective free radical scavenging activity, reducing power and nitric oxide scavenging activity. All these antioxidant properties were concentration dependent. The highest antioxidant activity was observed with ethanol extracts. Preliminary phytochemical screening revealed the presence of flavonoids, steroids, alkaloids, glycosides and phenolic compounds in the extracts and the results obtained from the current study indicate that Premna serratifolia Lin. , is a potential source of natural antioxidants and the extracts have constituents which were capable of showing anti-oxidant activity and the said in-vitro anti-oxidant activity may also be due to the presence of anti-oxidant principles present in the extracts like flavonoids and phenolic compounds. These findings confirm the great interest of the Premna serratifolia whose phytochemistry and phytopharmacology should be investigated further in order to detect possible phytotherapeutic uses in the prevention of ageing related diseases, cardiovascular disorders and Alzheimer disease.
A Novel ‘I-V Spectroscopy’ Technique to Deconvolve Threshold Voltage and Mobility Degradation in LDMOS Transistors

Although the CMOS-compatible Laterally Diffused MOSFET (LDMOS) is widely used in various applications as a versatile and efficient power electronic device, its hot carrier degradation (HCD) remains a persistent and important design challenge. None of the classical HCD models apply, because the geometric and doping complexities of the channel and drift regions create multiple hotspots with bias-dependent hot carrier injection into the oxide. To address these challenges, here we: 1) propose a novel geometrical partition of the LDMOS and represent each part by a TCAD-calibrated and experimentally validated tandem-FET compact model; 2) use the new compact model to propose an ‘ I − V spectroscopy’ methodology to deconvolve mobility and threshold degradation in the channel and the drift regions; 3) separate the degradation in the two regions by postprocessing measured I-V curves; 4) demonstrate that ΔVth determined by classical techniques, e.g., constant current (CC) or maximum transconductance (Gmmax), are contaminated by mobility degradation and must be corrected by the proposed technique for accurate lifetime projection.
An op amp-less Electrochemical Impedance Spectroscopy System

This paper describes an extremely low-cost device for performing Electrochemical Impedance Spectroscopy (EIS) measurements. The proposed instrument is arranged by using a simple Teensyduino board and it does not require any additional analog amplifier. The instrument is capable of measuring impedance values which can span about three decades, in the frequency range from 0.01 Hz to 10000 Hz. The proposed measuring system can be inserted in a remote laboratory infrastructure so as to allow the user to assess the corrosion behavior of metals not only performing single measurements but also during in situ long term monitoring.
ReGra: Accelerating Graph Traversal Applications Using ReRAM With Lower Communication Cost

There is a growing gap between data explosion speed and the improvement of graph processing systems on conventional architectures. The main reason lies in the large overhead of random access and data movement, as well as the unbalanced and unordered communication cost. The emerging metal-oxide resistive random access memory (ReRAM) has great potential to solve these in the context of processing-in-memory (PIM) technology. However, the unbalanced and irregular communication under different graph organizations is not well addressed. In this paper, we present a PIM graph traversal accelerator using ReRAM with a lower communication cost named ReGra. ReGra optimizes the graph organization and communication efficiency in graph traversal. Benefiting from high density and efficient access of ReRAM, graphs are organized compactly and partitioned into processing cubes by the proposed Interval-Block Hash Balance (IBHB) method to balance graph distribution. Moreover, remote cube updates in graph traversal are converged into batched messages and transferred in a concentrated period via the custom circular round communication phase. This eliminates irregular and unpredictable inter-cube communication and overlaps partial computation and communication. Comparative experiments with previous work like Tesseract and RPBFS show that ReGra achieves better performance and yields a speedup of up to $2.2\times $ . Besides the communication cost is reduced by up to 76%. It also achieves an average reduction in energy consumption of 70%.
A new Satsuma species (Pulmonata: Camaenidae) endemic to Taiwan

A new species of camaenid land snail, Satsuma longkiauwensis sp. nov. from southern Taiwan is established. This large terrestrial and herbivorous snail inhabits the lowland forests with a narrow geographical distribution. The species is characterized by having a large shell, roundly angulated peripheries adjacent to the peristome, an open umbilicus, a robust flagellum, a weak expansion on male genitalia instead of a penial caecum externally and a hemispherical verge instead of an elongated pilaster internally. A key is provided for the first time to identify camaenids from Taiwan.
Event-Based Neuromorphic Vision for Autonomous Driving: A Paradigm Shift for Bio-Inspired Visual Sensing and Perception

As a bio-inspired and emerging sensor, an event-based neuromorphic vision sensor has a different working principle compared to the standard frame-based cameras, which leads to promising properties of low energy consumption, low latency, high dynamic range (HDR), and high temporal resolution. It poses a paradigm shift to sense and perceive the environment by capturing local pixel-level light intensity changes and producing asynchronous event streams. Advanced technologies for the visual sensing system of autonomous vehicles from standard computer vision to event-based neuromorphic vision have been developed. In this tutorial-like article, a comprehensive review of the emerging technology is given. First, the course of the development of the neuromorphic vision sensor that is derived from the understanding of biological retina is introduced. The signal processing techniques for event noise processing and event data representation are then discussed. Next, the signal processing algorithms and applications for event-based neuromorphic vision in autonomous driving and various assistance systems are reviewed. Finally, challenges and future research directions are pointed out. It is expected that this article will serve as a starting point for new researchers and engineers in the autonomous driving field and provide a bird's-eye view to both neuromorphic vision and autonomous driving research communities.
A fast and test-proven methodology of assessing RTN/fluctuation on deeply scaled nano pMOSFETs

Random Telegraph Noise (RTN)/fluctuation is one of the most serious reliability issues in modern deeply scaled CMOS. The current RTN characterization methods need to select devices and can only capture the fast traps, thus it is very difficult to predict and validate device long-term fluctuation behavior. A new fast and test-proven methodology of assessing RTN/fluctuation is proposed in this work. By using the Within Device Fluctuation (WDF), all the devices’ fluctuation can be captured. Moreover, WDF can be well explained and simulated as a sum of all the As-grown Traps (AT) induced RTN.
Exploring the Role of Palm Concavity and Adaptability in Soft Synergistic Robotic Hands

Robotic hand engineers usually focus on finger capabilities, often disregarding the palm contribution. Inspired by human anatomy, this paper explores the advantages of including a flexible concave palm into the design of a robotic hand actuated by soft synergies. We analyse how the inclusion of an articulated palm improves finger workspace and manipulability. We propose a mechanical design of a modular palm with two elastic rolling-contact palmar joints, that can be integrated on the Pisa/IIT SoftHand, without introducing additional motors. With this prototype, we evaluate experimentally the grasping capabilities of a robotic palm. We compare its performance to that of the same robotic hand with the palm fixed, and to that of a human hand. To assess the effective grasp quality achieved by the three systems, we measure the contact area using paint-transfer patterns in different grasping actions. Preliminary grasping experiments show a closer resemblance of the soft-palm robotic hand to the human hand. Results evidence a higher adaptive capability and a larger involvement of all fingers in grasping.
Research Addendum

lthough they do not affect our findings in a significant way, some problems in the survey data we used for the analyses reported in our article, “Russian Public Opinion on Human Rights and the War in Chechnya” (Post-Soviet Affairs, vol. 18, no. 4, 2002, pp. 271–305), have been brought to our attention. We feel it important to share both the problem and the solution with readers of PSA. The data producer, VTsIOM, discovered that its Altay regional department did not follow proper quality-control procedures from October 2001 through May 2002. As a result, some of the surveys delivered by this department over the course of that period were found to be invalid. In particular, 27 of the 2,405 surveys included in the October 2001 supplemental Monitoring survey—which we used for the article—were found to have been falsified. Fortunately, the removal of these 27 observations from the data set does not affect any of our findings. This is not surprising, given the relatively small number of affected observations. But to make sure that our findings did not depend on the bad observations, we re-estimated every model and compared the results to those reported in the article. Of course, there are minor differences in the magnitudes of many descriptive statistics and coefficients. However, without exception, these differences are trivial and the same inferences result. We will gladly furnish the corrected tables upon request. Since the inception of survey research in Russia, critics have raised questions about the integrity of the data produced by Russian survey firms. Naturally, we regret having to confirm that some of these concerns appear to be justified in this case. On the other hand, we are heartened by the thoroughness of VTsIOM’s investigation into the matter, as well the forthright manner in which the results of the investigation were shared with us. We are also encouraged by VTsIOM’s responsive actions: VTsIOM immediately severed all ties with its Altay affiliate and has now begun implementing more thorough checks by the Moscow staff of the quality-control procedures employed by the
Identifying Surface Defect Opening Profiles Based on the Uniform Magnetic Field Distortion

Accurate identification of the defect opening profile is significant to quantify the size of defects for the ferromagnetic components. However, traditional non-destructive testing methods are difficult to obtain the image of defect opening contours precisely, especially the complex opening shapes. To solve the problem, we developed a novel opening profile identification method based on the distortion of the uniform magnetic field (UMF). This method has the same detection sensitivity to the defect edge in any direction, and accurate imaging of the defect opening profile can be achieved using the vertical component of the UMF distortion signal merely. In order to examine the feasibility and accuracy of the proposed method, regular and irregular defect models are simulated. In addition, an experiment for an artificial defect is conducted. All results show that the novel method has great promise in practical application.
Radar Interference Mitigation for Automated Driving: Exploring Proactive Strategies

Autonomous driving relies on a variety of sensors, especially radars, which have unique robustness under heavy rain/fog/snow and poor light conditions. With the rapid increase of the amount of radars used on modern vehicles, where most radars operate in the same frequency band, the risk of radar interference becomes a compelling issue. This article analyzes automotive radar interference and proposes several new approaches that combine industrial and academic expertise toward the goal of achieving interference-free autonomous driving (AD).
Nanoindentation to investigate IC stability using ring oscillator circuits as a CPI sensor

The impact of strain, induced by nanoindentation, on integrated circuit performance is measured. Localized strain caused by chip- package interaction alters the charge carrier mobility in the transistor channel due to the piezoresistive effect. Instrumented indentation enables to induce controlled localized loads with high lateral precision, and it is used to apply consecutive loading conditions to a single test device. Newly designed ring oscillator test structures manufactured in 22 nm FDSOI technology are used as a sensor to monitor the strain effect on transistor performance. Novel tip geometries provide insight into the direction dependent strain impact. Strain/stress fields at transistor level are determined by complementary FEM simulation. Board bending experiments with uniaxial stress/strain conditions are performed to verify the approach. The established correlation of mechanical load and device performance is used to provide an estimate for the effect of package related stress on transistor performance.
Training Musculoskeletal Arm Play Taichi with Deep Reinforcement Learning

Musculoskeletal robot arm driven by pneumatic artificial muscle actuators is secure, lightweight and compliant, which makes it an ideal solution for prosthetics and rehabilitation equipment. However, there exists conflicts between anatomical accuracy and engineering feasibility, and the nonlinearity of muscle actuators brings difficulty in accurate mathematical modeling. To overcome these problems, in this paper, we propose an optimized musculoskeletal arm design of ten muscles and four degrees-offreedom, employ Deep Deterministic Policy Gradient (DDPG) to train a data driven controller, and combine the off-policy reinforcement learning algorithm with Hindsight Experience Replay (HER) to deal with sparse rewards situation. TaiChi motion sequence is acquired using Perception Neuron and the trajectory tracking experiments are carried out in simulation platform. Experiment results demonstrate that, the controlled musculoskeletal arm is able to track the TaiChi trajectory and learn well in sparse rewards situation.
Machine Learning for Driver Detection through CAN bus

In last years vehicular network safety and security are attracting interest from both industries and researchers. In this paper, starting from a set of features gathered from the in-vehicle CAN bus, we show how machine learning algorithms can be useful to discriminate between the car owner and impostors. Furthermore, we assess several machine learning classifiers ability to predict instances not evaluated in the training set.
IoT via Satellite: Asynchronous Random Access for the Maritime Channel

Asynchronous random access protocols have become attractive for several satellite applications of interest, reducing the complexity at the transmitter side while granting good performance. These schemes typically follow two paradigms, using either (i) spread spectrum techniques or (ii) replication of the transmitted packets to achieve time diversity. In both cases, the receiver employs successive interference cancellation to resolve collisions. In this paper we offer a comparison of the two approaches in a narrowband scenario, discussing the relevant use case of the upcoming ITU VDES standard for maritime communications.
A Divide-and-Cooperate Machine Learning Model-Based RBF With Its VC Dimension Analysis

In this paper, a Divide-and-Cooperate Machine Learning Model (DCML) based Radial Basis Function Network (RBF) is constructed. This DCML is composed of several sub-RBF networks that take some variables as their inputs. The output of DCML is the sum of sub-RBF networks’ outputs. The analysis of VC dimension of DCML shows in theory that its structural complexity is less than conventional Extended Radial Basis Function Network (ENRBF). The experimental results have verified that the DCML outperforms conventional ENRBF.
Survival of white-tailed deer in an intensively farmed region of Minnesota

Abstract Survival and cause-specific mortality of white-tailed deer (Odocoileus virginianus) have been well documented in forested habitat, but limited information has been collected in intensively farmed regions. The objectives of this study were to determine survival and cause-specific mortality of neonate, fawn female, and adult female white-tailed deer in an intensively farmed (>80% land cover) region of Minnesota. We captured and radiocollared 77 female deer >8 months old (61 adults, 16 fawns) and 39 neonates (17 male, 22 female). Hunting was the greatest cause of mortality among adult deer, with 43% of mortalities attributed to firearms hunters. Annual survival rate of all adult and fawn (≥8 months) radiocollared deer was 0.77 (n = 58, SE = 0.06). Overall (Jan. 2001-Aug. 2002) adult survival was 0.75 (n = 77, SE = 0.05) and was similar to survival rates reported elsewhere for female white-tailed deer. Natural causes (e.g., disease, predation) of mortality were minor compared to human-related causes (e.g., hunting, vehicle collision). In total, 67% of neonate mortalities were due to predators. Neonate summer survival rate pooled over years was 0.84 (n = 39, SE = 0.06) and was high compared to other studies. High neonate survival was likely associated with a low predator density, quality vegetation structure at neonate bed sites, and high nutritional condition of dams. Deer management in the highly fragmented and intensively farmed regions of Minnesota relies on hunter harvest to maintain deer populations at levels tolerable to landowners.
WDM-Based Fiber-Optic Time Synchronization Without Requiring Link Calibration

In this paper, we propose a fiber-optic time synchronization technique based on the bidirectional wavelength division multiplexing (WDM) transmission over a fiber link. The effect of fiber dispersion on the uncertainty of the system is effectively suppressed by properly allocating the forward and backward wavelength maps. Thus, only an initial easy-to-implement calibration in a back-to-back configuration instead of multiple complicated link calibrations is required. To compensate the propagation delay fluctuations, a large-dynamic-range time pre-compensator with high precision is implemented at the local site, enabling a time signal at the remote site is accurately synchronized with the clock at the local site. Our experiments demonstrate that stabilities in terms of time deviation (TDEV) of less than 29.8 ps at 1s and 5.2 ps at 104s and the clock difference of less than 28 ps can be achieved for the fiber link up to 200 km.
The sparse and low-rank interpretation of SVD-based denoising for vibration signals

Vibration signal denoising is one of the most important steps in condition monitoring and fault diagnosis, and SVD-based methods are a vital part of advanced signal denoising due to their non-parametric and simple properties. The relation-ships between SVD-based denoising and other advanced signal processing methods are very significant and can help speed up the development of SVD-based denoising methods. There is limited prior work into the sparse and low-rank meaning of SVD-based denoising. In this paper, we build the relationships among SVD-based denoising, sparse l0-norm minimization, sparse weighted l1-norm minimization, and weighted low-rank models, when the dictionary is designed by left and right singular matrices in sparse minimization. Using the derived conclusion, we establish weighted soft singular value decomposition (WSSVD) for vibration signal denoising. Finally, we perform one experimental study to verify the effectiveness of WSSVD considering impulse interference and amplitude fidelity.