Miracle-dz/UniFAR-FTUs huggingface dataset:
An Air Stable, Electronically Tunable Negative Electron Affinity Silicon Photocathode

The application of negative electron affinity (NEA) photocathodes as high-frequency and high external quantum efficiency electron emission sources has gained attention due to their potential benefits in various fields, including but not limited to electronics, materials science, and microscopy. NEA photocathodes have been achieved by depositing a Cs/O surface layer on GaAs or other semiconductors [1], [2]. These devices have limited stability and require ultra-high vacuum, cluster tools for deposition and short lifetimes. To overcome these limitations, this work proposes the use of a silicon-insulator-graphene structure, Hot Electron Laser Assisted Cathode (HELAC), which is electronically tunable, air-stable, and can mimic a NEA surface under certain bias conditions. The devices explored here have exhibited an emission current of $\sim 20\mu \mathrm{A}$ under red light illumination, corresponding to a current density of 3.2 A/m2 and an external quantum efficiency (EQE) of 0.2%. In this paper, we have described the semiconductor device physics of this device and identified approaches to improve the photocathode performance.
Two Steps PalmPrint Recognition with Texture Features and SURF Descriptors

In this paper we present a two steps method for palmprint classification, that combine texture feature and SURF descriptors extracted from palmprint images. Depending on the choice of parameters, the use of SURF descriptors can be a time-consuming procedure. Experiments based on the approach proposed in this paper have led to very good results, in a shorter computing time than SURF-based approaches. The experiments results demonstrate that the proposed method can be also used to select a subset of candidates in the classification process of an image, subset that can be further employed in other more computationally expensive methods. The method was tested on five well-known palmprint databases.
Ultra-Low-Noise InGaAs mHEMT Technology and MMICs for Space Missions and Radio Astronomy

This paper demonstrates a set of wideband state-of-the-art low-noise amplifier (LNA) monolithic microwave integrated circuits (MMICs) ranging from 2 to 190 GHz. All MMICs are fabricated in a 50-nm gate-length InGaAs metamorphic high-electron-mobility transistor (mHEMT) technology. The LNAs achieve state-of-the-art noise performance for MMICs at room temperature (RT) and cryogenic conditions. The paper discusses specific design tradeoffs, such as the optimization of the input-matching network for best noise performance at RT or cryogenic condition or a lowest possible S11. The discussion is exemplified with the design and measurement of three different W-band (75–110 GHz) LNAs. Linearity considerations are discussed based on bias-dependent single- and two-tone circuit measurements. An RF stress test and statistics over five runs and 17 wafers of the measured noise performance of W-LNA1 MMICs complete the picture of a highly reliable InGaAs mHEMT technology with state-of-the-art RT and cryogenic noise performance.
High Performance Lamb Wave Resonator Operating in the 900 MHz ISM Band for Wireless Sensing Applications

Precision agriculture systems enabled by passive, wireless, subsurface soil sensors can provide high resolution data on soil conditions and increase crop yield. These frequency-coded sensor nodes are composed of an antenna, acoustic resonator and capacitive soil moisture sensor. Here, a high performance Al0.7Sc0. 3N Lamb-wave resonator (LWR) for operation in the 902-928 MHz industrial, scientific, medical (ISM) band is fabricated. Its figure of merit is 37% larger than state-of-the-art LWR at similar frequency. The LWR is integrated with a capacitive moisture sensor and its frequency tuning capabilities are demonstrated. A sensitivity of 65 kHz at interrogation ranges of up to 150 m is determined.
Robust Consumption Planning from Uncertain Power Demand Predictions

A plug-in hybrid electric vehicle (PHEV) satisfies the driver’s power demand with two types of energy potentials: fuel and electrical energy provided by a battery. Classically, the battery consumption is planned over a trip to minimize the expected fuel consumption. A cautious driver will save battery potential to cross restricted areas (with desired low or even zero fuel consumption) without the fuel engine. This paper proposes an approach to minimize energy consumption while controlling the risk of a PHEV falling short of battery potential when crossing a restricted area. We use a nonlinear Gaussian process, trained on real vehicle data, for predicting the vehicle consumption. We take into account prediction uncertainty by ensuring that the driver’s highest power demand will be satisfied with a high probability. The interest of the approach is demonstrated by a simulated trip around Paris.
A Convolutional Neural Network with Incremental Learning

Nowadays, a convolutional neural network (CNN) is considered as a deep learning method for image and voice recognition. A CNN can achieve higher recognition accuracy than other approaches since it can automatically extract features by its learning procedure. However, the training procedure of a CNN is time-consuming. Since the functions of a CNN are close to those of a human brain, when a CNN is applied to a complex application, it must be trained by a large amount of training data, resulting in the size of the CNN becoming huge. To train such a huge neural network by computers, a tremendous amount of training time is required. In this paper, an efficient approach is proposed that can markedly reduce the training time while only slightly sacrificing the recognition accuracy of the training procedure.
Microwave Sensing for Avoidance of High-Risk Ground Conditions for Mobile Robots

To be useful in a wider range of environments, especially environments that are not sanitized for their use, robots must be able to handle uncertainty in ground conditions. This requires a robot to incorporate new sensors and sources of information, and to be able to use this information to make decisions regarding navigation. When using autonomous mobile robots in unstructured and poorly defined environments, ground condition is of critical importance and is a common cause of failure, an example being the presence of ground water in the operating area. To evaluate a non-contact sensing method to mitigate this risk, Frequency Modulated Continuous Wave (FMCW) radar is integrated with an Unmanned Ground Vehicle (UGV), representing a novel application of FMCW to detect new measurands for Robotic Autonomous Systems (RAS) navigation, informing on ground integrity and adding to the state-of-the-art in sensing for optimized autonomous path planning. In this paper, FMCW is first evaluated in a desktop setting to determine water sensing capability. The FMCW is then fixed to a UGV, and the sensor system is successfully tested and validated in a representative environment containing regions with significant levels of ground water saturation. The successful integration of FMCW radar with autonomous environmental characterization and mapping has the potential to provide new measurands of terrain integrity data, such as the detection of water, snow, ice, oil or other contaminants on the operating surface that may otherwise jeopardize the operation of a UGV.
Linearity Enhanced Broadband Darlington Power Amplifier IC Using InGaP/GaAs HBT for Handset Modules with Fractional Bandwidth of 50%

This letter presents a 0.6–1 GHz broadband Darlington power amplifier using a 2–μm InGaP/GaAs heterojunction bipolar transistor (HBT) process for mobile handset application. The Darlington structure is proposed for high performance broadband PA design, as it improves the gain–bandwidth products of the transistor itself without the problem of reducing the power added efficiency (PAE) of the circuit. A proposed simple tunable linearization circuit operates as a 2nd harmonic resonance circuit to improve linearity over 0.6–1 GHz and is designed to adjust the operating frequency differently according to the control voltage of the diode. Using the continuous wave (CW) signal, the implemented Darlington PA achieves an output power of 34.3–35.5 dBm, a PAE of 51–61 % based on P3dB and a small-signal gain of 27.2–28.16 dB in a fractional bandwidth (FBW) of 50 %. Using the 20 MHz 100 RB BW QPSK LTE signal with a PAPR of 7.22 dB were obtained E-UTRA ACLR of better than -40dBc at Pout of 27.5-28.5 dBm.
Program Repair Competition

Automated Program Repair(APR) is a rapidly de-veloping technology that can assist developers in fixing software system errors. An essential part of any scientific work is a fair and comprehensive evaluation of the state-of-the-art techniques. At present there is no publicly available standard mechanism to perform comparisons for program repair. In this paper, we propose such a standardization in the form of a competition to foster comparability, advancing the state-of-the-art capabilities and to pave the path for the next-generation repair technology.
A review of vision-based road detection technology for unmanned vehicles

With the development of unmanned vehicle technology, unmanned vehicles have played a huge role in logistics transportation, emergency rescue and disaster relief, etc., so the research on unmanned vehicles is becoming more and more important. Road detection is an important part of environmental perception and an important factor in the realization of assisted driving and unmanned driving technology. High-precision road detection technology can provide important environmental information for efficient planning and reasonable decision-making of unmanned vehicles. Firstly, the technical framework of road detection is given, and the road detection process is introduced in detail. Then, the vision-based road detection algorithm is introduced. Finally, some related data sets in the field of road detection are collected, which provides new ideas and methods for road detection researchers.
Fuzzy Family Ties: Familial Similarity Between Melodic Contours of Different Cardinalities

All melodies have shape: a pattern of ascents, descents, and plateaus that occur as music moves through time. This shape—or contour—is one of a melody’s defining characteristics. Music theorists such as Michael Friedmann (1985), Robert Morris (1987), Elizabeth Marvin (1987), and Ian Quinn (1997) have developed models for analyzing contour, but only a few compare contours with different numbers of notes (cardinalities), and fewer still compare entire families of contours. Since these models do not account for familial relations between different-sized contours, they apply only to a limited musical repertoire, and therefore it seems unlikely that they reflect how listeners perceive melodic shape. This dissertation introduces a new method for evaluating familial similarities between related contours, even if the contours have different cardinalities. My Familial Contour Membership model extends theories of contour transformation by using fuzzy set theory and probability. I measure a contour’s degree of familial membership by examining the contour’s transformational pathway and calculating the probability that each move in the pathway is shared by other family members. Through the potential of differing alignments along these pathways, I allow for the possibility that pathways may be omitted or inserted within a contour that exhibits familial resemblance, despite its different cardinality. Integrating variable cardinality into contour similarity relations more adequately accounts for familial relationships between contours, opening up new possibilities for analytical application to a wide variety of repertoires. I examine familial relationships between variants of medieval plainchant, and demonstrate how the sensitivity to familial variation illuminated by fuzzy theoretical models can contribute to our understanding of ii musical ontology. I explain how melodic shape contributes to motivic development and narrative creation in Brahms’s “Regenlied” Op. 59, No. 3, and the related Violin Sonata No. 1, Op. 78. Finally, I explore how melodic shape is perceived within the repetitive context of melodic phasing in Steve Reich’s The Desert Music. Throughout each study, I show that a more flexible attitude toward cardinality can open contour theory to more nuanced judgments of similarity and familial membership, and can provide new and valuable insights into one of music’s most fundamental elements.
Numerical investigation of the saturation process in an incompressible cavity flow

A numerical study of the saturation process inside a rectangular open cavity is presented. Previous experiments and linear stability analysis of the problem completely described the flow in its onset, as well as in a saturated regime, characterized by three-dimensional centrifugal modes. The morphology of the modes found in the experiments matched the ones predicted by linear analysis, but with a shift in frequencies for the oscillating modes. A three-dimensional incompressible direct numerical simulation (DNS) is employed for a detailed investigation of the saturation process inside a cavity with dimensions similar to the one used in the experiments, to further explain the behaviour of these modes. In this work, periodic boundary conditions are first imposed to better understand the effect of the saturation process far from the walls. Then, the effects of spanwise solid wall boundary conditions are investigated with a DNS reproducing the full dynamics of the experiments. The main flow structures are identified using the dynamic mode decomposition technique and compared with previous experimental and linear stability analysis results. The main reason for the aforementioned shift in frequency is explained in this paper, as it is a function of the velocity of the main recirculating vortex.
The asymptotic formulae in the problem on constructing hyperbolicity and stability regions of dynamical systems

The paper proposes a new general method allowing us to study the problem on constructing hyperbolicity and stability regions for nonlinear dynamical systems. The method is based on a modification of the method by M. Rozo for studying the stability of linear systems with periodic coefficients depending on a small parameter and on the asymptotic formulae in the perturbation theory of linear operators. We obtain approximate formulae describing the boundary of hyperbolicity and stability regions. As an example, we provide the scheme for constructing the stability regions for Mathieu equation.
What is Decidable about Perfect Timed Channels?

In this paper, we introduce the model of communicating timed automata (CTA) that extends the classical models of finite-state processes communicating through FIFO perfect channels and timed automata, in the sense that the finite-state processes are replaced by timed automata, and messages inside the perfect channels are equipped with clocks representing their ages. In addition to the standard operations of timed automaton, each automaton can either (1) append a message to the tail of a channel with an initial age or (2) receive the message at the head of a channel if it is age satisfies a set of given constraints. In this paper, we show that the reachability problem is undecidable even in the case of two timed automata connected by one unidirectional timed channel if one allows global clocks (that the two automata can check and manipulate). We prove that this undecidability still holds even for an CTA consisting of three timed automata and two unidirectional timed channels (and without any global clock). However, the reachability problem becomes decidable in the case of two automata linked with one unidirectional timed channel and with no global clock. Finally, we consider the bounded-context case, where in each context only one timed automaton is allowed to receive messages from one channel while being able to send messages to all the other timed channels. In this case we show that the reachability problem is decidable.
Effect of Neighborhood Approximation on Downstream Analytics

EFFECT OF NEIGHBORHOOD APPROXIMATION ON DOWNSTREAM ANALYTICS by Saranya Soundar Rajan Nearest neighbor search algorithms have been successful in finding practically useful solutions to computationally difficult problems. In the nearest neighbor search problem, the brute force approach is often more efficient than other algorithms for high-dimensional spaces. A special case exists for objects represented as sparse vectors, where algorithms take advantage of the fact that an object has a zero value for most features. In general, since exact nearest neighbor search methods suffer from the “curse of dimensionality,” many practitioners use approximate nearest neighbor search algorithms when faced with high dimensionality or large datasets. To a reasonable degree, it is known that relying on approximate nearest neighbors leads to some error in the solutions to the underlying data mining problems the neighbors are used to solve. However, no one has attempted to quantify this error or provide practitioners with guidance in choosing appropriate search methods for their task. In this thesis, we conduct several experiments on recommender systems with a goal to find the degree to which approximate nearest neighbor algorithms are subject to these types of error propagation problems. Additionally, we provide persuasive evidence on the trade-off between search performance and analytics effectiveness. Our experimental evaluation demonstrates that a state-of-the-art approximate nearest neighbor search method (L2KNNGApprox) is not an effective solution in most cases. When tuned to achieve high search recall (80% or higher), it provides a fairly competitive recommendation performance compared to an efficient exact search method but offers no advantage in terms of efficiency (0.1x—1.5x speedup). Low search recall (<60%) leads to poor recommendation performance. Finally, medium recall values (60%—80%) lead to reasonable recommendation performance but are hard to achieve and offer only a modest gain in efficiency (1.5x—2.3x). ACKNOWLEDGMENTS I would like to thank my thesis advisor, professor David C. Anastasiu, of the Computer Engineering Department at San José State University for accepting me as his thesis student, and for being the greatest advisor in the world. Without his supervision, help and valuable suggestions, it would have been impossible for me to complete my thesis. I would also like to thank my committee members, professor Gheorghi Guzun and professor Mahima Agumbe Suresh, for participating in my thesis defense committee and providing valuable comments on my thesis. Last, but not least, I would like to thank my family and my husband for their patience, moral and, financial support, and encouragement. Above all, I thank Almighty God for His grace and countless blessings.
Asiaticoside Mitigates Alzheimer’s Disease Pathology by Attenuating Inflammation and Enhancing Synaptic Function

Alzheimer’s disease (AD) is a prevalent neurodegenerative disorder, hallmarked by the accumulation of amyloid-β (Aβ) plaques and neurofibrillary tangles. Due to the uncertainty of the pathogenesis of AD, strategies aimed at suppressing neuroinflammation and fostering synaptic repair are eagerly sought. Asiaticoside (AS), a natural triterpenoid derivative derived from Centella asiatica, is known for its anti-inflammatory, antioxidant, and wound-healing properties; however, its neuroprotective function in AD remains unclear. Our current study reveals that AS, when administered (40 mg/kg) in vivo, can mitigate cognitive dysfunction and attenuate neuroinflammation by inhibiting the activation of microglia and proinflammatory factors in Aβ1-42-induced AD mice. Further mechanistic investigation suggests that AS may ameliorate cognitive impairment by inhibiting the activation of the p38 MAPK pathway and promoting synaptic repair. Our findings propose that AS could be a promising candidate for AD treatment, offering neuroinflammation inhibition and enhancement of synaptic function.
A Dual-Polarized Bandwidth Enhanced Filtering Dipole Antenna Design for 5G

The present study proposes a dual-polarized bandwidth-enhanced filtering specialized dipole antenna design for 5G by employing a wide printed dipole, filtering resonators, a reflector surface, and specially designed balun structures. Such a configuration is commonly deployed in conventional base stations. To increase the antenna impedance and radiation bandwidth, a specifically designed, wide-printed flared dipole antenna structure is used as the main radiator element. Transmission zeros are introduced at both pass band edges to create a filtering response by engaging parasitic elements. The parasitic element for the higher frequency edge of the filtering is placed close to the maximum amount of the induced current on the radiator at the operating frequency, whereas the parasitic element for the lower frequency edge of the filtering is located close to the perpendicularly polarized structure. The antenna aims to create radiation nulls at the impedance bandwidth limits; therefore, the parasitic arcs are used to create surface currents that cancel the broadside radiation at the limits of the impedance bandwidth. The study illustrates a complete analysis of the broadband printed patch antenna having a filtering effect by parametric investigations on the dimensions and resulting physical phenomenon in detail. To demonstrate the approach, a prototype of the antenna is fabricated and measured. According to the measurement results, the antenna performs 76% impedance bandwidth between 2.49 GHz and 5.59 GHz with <inline-formula> <tex-math notation="LaTeX">$|S_{11}|$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$|S_{22}| < -10$ </tex-math></inline-formula> dB by providing exceptional isolation values of <inline-formula> <tex-math notation="LaTeX">$|S_{21}| < -20$ </tex-math></inline-formula> dB in entire operating band. The fabricated antenna has a stable radiation beamwidth with less than <inline-formula> <tex-math notation="LaTeX">$\pm 5^{0}$ </tex-math></inline-formula> variation and the measured gain in the operating frequency is almost constant and equal to 8.2 dBi.