Analog Processing Research Articles

Goizuetako azentueraren garapena kokatzen Euskara Batu Zaharraren prosodia zehazteko: proposamenen ebaluazioa

The development of the prosodic system of Goizueta is the main point of disagreement the two last hypotheses –Hualde’s and Egurtzegi & Elordieta’s– will be compared, highlighting their main strengths and shortcomings in order to evaluate each proposal’s plausibility. After the comparison, Egurtzegi and Elordieta’s hypothesis is favored, be-cause its main shortcoming (that is, the need of proposing analogical processes between of this proposal are absent in the former.

Influence of Analog and Digital Crease Lines on Mechanical Parameters of Corrugated Board and Packaging.

When producing packaging from corrugated board, material weakening often occurs both during the die-cutting process and during printing. While the analog lamination and/or printing processes that degrade material can be easily replaced with a digital approach, the die-cutting process remains overwhelmingly analog. Recently, new innovative technologies have emerged that have begun to replace or at least supplement old techniques. This paper presents the results of laboratory tests on corrugated board and packaging made using both analog and digital technologies. Cardboard samples with digital and analog creases are subject to various mechanical tests, which allows for an assessment of the impact of creases on the mechanical properties of the cardboard itself, as well as on the behavior of the packaging. It is proven that digital technology is not only more repeatable, but also weakens the structure of corrugated board to a much lesser extent than analog. An updated numerical model of boxes in compression tests is also discussed. The effect of the crushing of the material in the vicinity of the crease lines in the packaging arising during the analog and digital finishing processes is taken into account. The obtained enhanced computer simulation results closely reflect the experimental observations, which prove that the correct numerical analysis of corrugated cardboard packaging should be performed with the model taking into account the crushing.

Nonlinear Computational Edge Detection Metalens

AbstractOptical image processing and computing systems provide supreme information processing rates by utilizing parallel optical architectures. Existing optical analog processing techniques require multiple devices for projecting images and executing computations. In addition, those devices are typically limited to linear operations due to the time‐invariant optical responses of the building materials. In this work, a single metalens with an illumination intensity dependent coherent transfer function (CTF) is proposed and experimentally demonstrated, which performs varying computed imaging without requiring any additional optical components. The metalens consisting of nanoantenna structures with a static geometric phase and a nonlinear metallic quantum well layer offering an intensity‐dependent dynamic phase results in a continuously tunable CTF. The approach allows for a weighted summation of two designed functions based on the metalens design, which potentially enables all optical computations of complex functions. The nonlinear metalens may lead to important applications in optical neural networks and parallel analog computing.

In situ reconstruction of defect-rich SnO2 through an analogous disproportionation process for CO2 electroreduction

Sn-based catalysts have been investigated as efficient catalysts for CO2 electroreduction toward formate production. However, they still suffer from insufficient current densities and narrow potential windows at high formate Faradaic efficiency. Herein, we developed defect-rich SnO2 (e-SnO2) with surface-covered hydroxyls groups in situ derived from SnSO4 through an analogous disproportionation process. The e-SnO2 exhibits excellent formate Faradaic efficiency over 90% at a potential range from −0.68 to −1.14 V vs. RHE. The partial current density of formate reaches 535 ± 12 mA cm−2, which is higher than that of most ever-reported Sn-based catalysts. Density functional theory calculations further reveal that the synergistic effects of oxygen vacancies and surface hydroxyls facilitate formate production by improving CO2 adsorption and balancing the energy barrier for the formation of key intermediate *OCOH.

Modeling of CMOS transistors from 0.18 μm process by artificial neural network

In this work, we developed a new transistor model that can be used to simulate analog circuits. Our model uses artificial neural network to capture the electrical characteristics of transistors instead of the traditional physics-driven model. By preprocessing the transistor data, high-precision modeling is achieved. N-type and p-type transistors with various widths and lengths are fabricated with the 0.18 μm analog process in the foundry. ANN modeling on these transistors shows high precision compared with the BSIM3 transistor model. The results show that the DC characteristics of the ANN model are more accurate than the BSIM3 transistor model, and have better capture on the output-resistance of the MOSFET.

Design, synthesis, and biological evaluation of novel carbazole derivatives as potent DNMT1 inhibitors with reasonable PK properties

The DNA methyltransferases (DNMTs) were found in mammals to maintain DNA methylation. Among them, DNMT1 was the first identified, and it is an attractive target for tumour chemotherapy. DC_05 and DC_517 have been reported in our previous work, which is non-nucleoside DNMT1 inhibitor with low micromolar IC50 values and significant selectivity towards other S-adenosyl-L-methionine (SAM)-dependent protein methyltransferases. In this study, through a process of similarity-based analog searching, a series of DNMT1 inhibitors were designed, synthesized, and evaluated as anticancer agents. SAR studies were conducted based on enzymatic assays. And most of the compounds showed strong inhibitory activity on human DNMT1, especially WK-23 displayed a good inhibitory effect on human DNMT1 with an IC50 value of 5.0 µM. Importantly, the pharmacokinetic (PK) profile of WK-23 was obtained with quite satisfying oral bioavailability and elimination half-life. Taken together, WK-23 is worth developing as DNMT1-selective therapy for the treatment of malignant tumour.

Direct Detection Constraints on Blazar-Boosted Dark Matter.

We explore the possibility that relativistic protons in the extremely powerful jets of blazars may boost via elastic collisions the dark matter particles in the surroundings of the source to high energies. We concentrate on two sample blazars, TXS 0506+056, towards which IceCube recently reported evidence for a high-energy neutrino flux, and BL Lacertae, a representative nearby blazar. We find that the dark matter flux at Earth induced by these sources may be sizable, larger than the flux associated with the analogous process of dark matter boosted by galactic cosmic rays, and relevant to access direct detection for dark matter particle masses lighter than 1GeV. From the null detection of a signal by XENON1T, MiniBooNE, and Borexino, we derive limits on dark matter-nucleus spin-independent and spin-dependent cross sections which, depending on the modelization of the source, improve on other currently available bounds for light dark matter candidates of 1 up to 5 orders of magnitude.

A study on the semantic change of the Chinese negative adverb Bùshèn (不甚)

Abstract This paper aims to account for the multiple interpretations of the Chinese negative degree adverb bùshèn (不甚). In Xiandai Hanyu Dacidian Shangce (Modern Chinese Dictionary Volume I) (Ruan & Guo (eds) 2009), bùshèn is defined as ‘the degree is not very high’, which can be interpreted as ‘not very’; however, in the CCL and BCC Modern Chinese corpora, a few cases showing that bùshèn can only be interpreted as indicating positive degree similar to ‘very’. Using the extensive classical and modern Chinese data, we argue that the semantic change has undergone a process of analogy (cf. Harris & Campbell 1995; Fischer 2007; Traugott & Trousdale 2013). Specifically, the use of positive degree of bùshèn has been analogized to the extant positive degree adverb bùshèng (不胜). The semantic change is observed when bùshèn forms common collocations with an adjective or a verb which convey emotions, such as gǎnxiè ‘grateful’ in bùshèng gǎnxiè ‘very grateful’.

Dynamic Multivariable Algebraic Loop Solver for Input-Constrained Control

We consider a gradient-like system for real-time implementation of multivariable algebraic loops arising in input-constrained control problems. Using results from mathematical programming, we establish global asymptotic convergence under a less stringent condition as compared to existing techniques. We comment on the application of the gradient-like system in antiwindup control implementation where the closed-loop can also be interpreted within the framework of singularly perturbed systems. The proposed system can easily be realized for practical circuit implementation and may be prototyped using fast analog processors.

AERO: Design Space Exploration Framework for Resource-Constrained CNN Mapping on Tile-Based Accelerators

Analog In-Memory Compute (AIMC) arrays can store weights and perform matrix-vector multiplication operations for Deep Convolutional Neural Networks (CNNs). A number of recent efforts have integrated AIMC arrays into hybrid digital-analog accelerators in a multi-layer parallel manner to achieve energy efficiency and high throughput. Multi-layer parallelism on large-scale tile-based architectures need efficient mapping support at the processing element (PE)-level ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">e.g.</i> , digital or analog processing elements) and tile-level. To find the most efficient architectures, fast and accurate design space exploration (DSE) support is required. In this paper, a novel DSE framework, AERO, is presented to characterize a CNN inference workload executing on hybrid tile-based architectures that supports multi-layer parallelism. Three characteristics can be seen in our DSE framework: (1) It presents a hierarchical Tile/PE-level mapping exploration strategy including inter-layer interaction, and allowing layer fusion/splitting configurations for PE-level mapping optimization. (2) It unlocks different Performance, Power and Area (PPA) exploration points under both sufficient and limited resource constraints, while limited resource case is not considered in prior works of multi-layer parallel architectures. The impact of weight loading and weight stationary mapping are analyzed for better insights into hybrid tile-based architectures. (3) It incorporates a detailed PPA model that supports a broad range of hybrid digital and analog units in a tile. Experimental case-studies are performed for realistic and relevant benchmarks such as MLP, CNNs (Lenet-5, Resnet-18,-34,-50 and −101).

Design and Development of Inductive Sensor Mini Trainer Based on Arduino

Sensor and Transducer is one of the subjects that must be followed by students of the Automotive Engineering Department, Faculty of Engineering, Padang State University, which weighs 2 credits. In accordance with the RPS for the Sensor and Transducer Course, there are several types of sensors that are the subject of study, one of which is an inductive sensor. Inductive sensor applications are applied in the automotive world such as Crankshaft Position Sensor (CKP), Camshaft Position Sensor (CMP), Vilocity Sensor. To make it easier to understand each sensor applied in the automotive world, students are required to master the basic concepts of the inductive sensor. One of the ways to increase student competence in the field of inductive sensors is the use of teaching aids during the learning process. Inductive sensor learning media in the Laboratory at the Automotive Engineering Department still uses analog processors, to support the development of digital technology today, so the authors provide an alternative by making teaching aids in the form of an Arduino-based Inductive Sensor Mini Trainer. This study uses the Research and Development (R&amp;D) method which consists of Define, Design, Development, and Desseminate. The assembled inductive sensor mini trainer was tested for accuracy, and repeatibility test as well as feasibility test from media experts and users. The results of the research on the product trials carried out, obtained an accuracy level of 96.21%, the sensor output has linearity, the repeatibility test is obtained with an average of 0.1%. The level of product feasibility from Media Experts, is 94.68% and 96.23% from Respondents. So it can be concluded that the Inductive Sensor Mini Trainer is very suitable to be used as a learning medium.

Digital Optical Ballistocardiographic System for Activity, Heart Rate, and Breath Rate Determination during Sleep.

In this work, we present a ballistocardiographic (BCG) system for the determination of heart and breath rates and activity of a user lying in bed. Our primary goal was to simplify the analog and digital processing usually required in these kinds of systems while retaining high performance. A novel sensing approach is proposed consisting of a white LED facing a digital light detector. This detector provides precise measurements of the variations of the light intensity of the incident light due to the vibrations of the bed produced by the subject’s breathing, heartbeat, or activity. Four small springs, acting as a bandpass filter, connect the boards where the LED and the detector are mounted. Owing to the mechanical bandpass filtering caused by the compressed springs, the proposed system generates a BCG signal that reflects the main frequencies of the heartbeat, breathing, and movement of the lying subject. Without requiring any analog signal processing, this device continuously transmits the measurements to a microcontroller through a two-wire communication protocol, where they are processed to provide an estimation of the parameters of interest in configurable time intervals. The final information of interest is wirelessly sent to the user’s smartphone by means of a Bluetooth connection. For evaluation purposes, the proposed system has been compared with typical BCG systems showing excellent performance for different subject positions. Moreover, applied postprocessing methods have shown good behavior for information separation from a single-channel signal. Therefore, the determination of the heart rate, breathing rate, and activity of the patient is achieved through a highly simplified signal processing without any need for analog signal conditioning.

Q-balls in nonminimally coupled Palatini inflation and their implications for cosmology

We demonstrate the existence of Q-balls in nonminimally coupled inflation models with a complex inflaton in the Palatini formulation of gravity. We show that there exist Q-ball solutions which are compatible with inflation and we derive a window in the inflaton mass squared for which this is the case. In particular, we confirm the existence of Q-ball solutions with $\ensuremath{\phi}\ensuremath{\sim}{10}^{17}--{10}^{18}\text{ }\text{ }\mathrm{GeV}$, consistent with the range of field values following the end of slow-roll Palatini inflation. We study the Q-balls and their properties both numerically and in an analytical approximation. The existence of such Q-balls suggests that the complex inflaton condensate can fragment into Q-balls, and that there may be an analogous process for the case of a real inflaton with fragmentation to neutral oscillons. We discuss the possible postinflationary cosmology following the formation of Q-balls, including an early Q-ball matter domination (eMD) period and the effects of this on the reheating dynamics of the model, gravitational wave signatures which may be detectable in future experiments, and the possibility that Q-balls could lead to the formation of primordial black holes (PBHs). In particular, we show that Palatini Q-balls with field strengths typical of inflaton condensate fragmentation can directly form black holes with masses around 500 kg or more when the self-coupling is $\ensuremath{\lambda}=0.1$, resulting in very low (less than 100 GeV) reheating temperatures from black hole decay, with smaller black hole masses and larger reheating temperatures possible for smaller values of $\ensuremath{\lambda}$. Q-ball dark matter from nonminimally coupled Palatini inflation may also be a direction for future work.

Inovasi Media Pembelajaran Berbasis Problem Based Learning pada Bidang Elektronika Analog Digital

This study aims to produce innovations in the form of interactive, valid and practical learning media, and can support the Problem Based Learning (PBL) method in Analog and Digital Electronics courses. The research method used is the Pre-Experimental method with One Shot Case Study design. The subject of this research is Analog and Digital Electronics course. This learning media innovation was applied to several students of the Electrical Engineering Department, Faculty of Engineering, Universitas Negeri Padang, in 2021 who were taking Analog and Digital Electronics courses. Before being shown to respondents, the learning media is tested for validity/feasibility by media expert lecturers. In view of the feasibility test that has been done, this learning media gets a value of ninety three percent, both with regards to appearance and content of the material. Thus, the media can be declared valid/valid so that the research can be continued in obtaining the value of the practicality of the media from the respondents who have been given treatment. The practicality test which was filled out by eight students, obtained an average data of ninety two percent in the very practical category. Data on the feasibility and practicality of the media were obtained using a validated questionnaire of zero point ninety eight by instrument expert lecturers. So, it tends to be inferred that the learning media in the Analog and Digital Electronics course is valid and practical to use in the Analog and Digital Electronics learning process.

One-Step Solvometallurgical Process for Purification of Lithium Chloride to Battery Grade

The use of lithium in manufacturing of lithium-ion batteries for hybrid and electric vehicles, along with stringent environmental regulations, have strongly increased the need for its sustainable production and recycling. The required purity of lithium compounds used for the production of battery components is very high (> 99.5%). In this work, a solvometallurgical process that exploits the differences in solubility between LiCl and other alkali and alkaline-earth chlorides and hydroxides in ethanolic solutions has been investigated for the purification of LiCl to battery grade at room temperature. A closed-loop flowsheet based on the green solvent ethanol is proposed for purification of LiCl, a precursor for battery-grade LiOH·H2O. High-purity LiCl solution (> 99.5% Li) could be obtained in a single-process step comprising the simultaneous selective dissolution of LiCl and the precipitation of Mg(OH)2 and Ca(OH)2 using LiOH·H2O in 95 vol% ethanol. However, the analogous process in aqueous solution resulted in impure LiCl (typically less than about 75%).Graphical

DFT Study of the BH4− Hydrolysis on Au(111) Surface

The mechanism of the catalytic hydrolysis of BH4 − on Au(111) as studied by DFT is reported. The results are compared to the analogous process on Ag(111) that was recently reported. It is found that the borohydride species are adsorbed stronger on the Au0‐NP surface than on the Ag0‐NP surface. The electron affinity of the Au is larger than that of Ag. The results indicate that only two steps of hydrolysis are happening on the Au(111) surface and the reaction mechanism differs significantly from that on the Ag(111) surface. These remarkable results were experimentally verified. Upon hydrolysis, only three hydrogens of BH4 − are transferred to the Au surface, not all four, and H2 generation is enhanced in the presence of surface H atoms. Thus, it is proposed that the BH4 − hydrolysis and reduction mechanisms catalyzed by M0‐NPs depend considerably on the nature of the metal.

Navigation Map-Based Artificial Intelligence

A biologically inspired cognitive architecture is described which uses navigation maps (i.e., spatial locations of objects) as its main data elements. The navigation maps are also used to represent higher-level concepts as well as to direct operations to perform on other navigation maps. Incoming sensory information is mapped to local sensory navigation maps which then are in turn matched with the closest multisensory maps, and then mapped onto a best-matched multisensory navigation map. Enhancements of the biologically inspired feedback pathways allow the intermediate results of operations performed on the best-matched multisensory navigation map to be fed back, temporarily stored, and re-processed in the next cognitive cycle. This allows the exploration and generation of cause-and-effect behavior. In the re-processing of these intermediate results, navigation maps can, by core analogical mechanisms, lead to other navigation maps which offer an improved solution to many routine problems the architecture is exposed to. Given that the architecture is brain-inspired, analogical processing may also form a key mechanism in the human brain, consistent with psychological evidence. Similarly, for conventional artificial intelligence systems, analogical processing as a core mechanism may possibly allow enhanced performance.

Electromagnetic wave-based extreme deep learning with nonlinear time-Floquet entanglement

Wave-based analog signal processing holds the promise of extremely fast, on-the-fly, power-efficient data processing, occurring as a wave propagates through an artificially engineered medium. Yet, due to the fundamentally weak non-linearities of traditional electromagnetic materials, such analog processors have been so far largely confined to simple linear projections such as image edge detection or matrix multiplications. Complex neuromorphic computing tasks, which inherently require strong non-linearities, have so far remained out-of-reach of wave-based solutions, with a few attempts that implemented non-linearities on the digital front, or used weak and inflexible non-linear sensors, restraining the learning performance. Here, we tackle this issue by demonstrating the relevance of time-Floquet physics to induce a strong non-linear entanglement between signal inputs at different frequencies, enabling a power-efficient and versatile wave platform for analog extreme deep learning involving a single, uniformly modulated dielectric layer and a scattering medium. We prove the efficiency of the method for extreme learning machines and reservoir computing to solve a range of challenging learning tasks, from forecasting chaotic time series to the simultaneous classification of distinct datasets. Our results open the way for optical wave-based machine learning with high energy efficiency, speed and scalability.

On Power’s Doorstep: Gays, Jews, and Liminal Complicity in Reproducing Masculine Domination

This article explores the gender complexities of men caught between social power and powerlessness. Specifically, I consider the cases of Jewish men and gay men in the late modern West, two demographics with deep historic ties to both abjection and privilege. Such "in-between-ness” steers many, especially those who are white, cisgender, and/or otherwise privileged, toward what I term liminal complicity, a normative adaptation whereby men embrace manly ideals while disavowing femininity in themselves and others. I synthesize cultural, interactionist, and psychoanalytic literatures on stigma, boundaries, and gender practice to articulate liminal complicity as both an emotional retreat from stigmatization and a rational means of accruing status and redrawing social boundaries. I conduct a comparative-historical analysis of gendered discourses and practices at different historical junctures to show how analogous processes of (1) normative identification, (2) self-transformation, and (3) distinction from and (4) aggression toward feminized others enable historically subordinated men to elevate themselves without disrupting broader systems of domination.

Narrating from landscape in Andean archaeology: The problem with the suni natural region

Archaeologists use the landscape to explain the past, often referring to traditional or indigenous knowledge to better understand that landscape. But how is this analogical process performed, and how is indigenous knowledge understood and recorded? This article examines Peruvian geographer Javier Pulgar Vidal’s concept of suni—a term with several definitions in Aymara and Quechua, but which was transformed by Pulgar Vidal into a “Natural Region,” in other words a meaningful portion of the landscape—as an entry point into this broader issue. Suni is important because it is a poorly defined part of a wider Andean landscape model supposedly based on indigenous knowledge and because it is commonly used by archaeologists to explain precolonial land use and landscapes. Through analysis of the creation and application of suni, we define major challenges faced by archaeologists when interpreting sites and materials in landscape perspective and present suggestions for moving forward.