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In this paper we study the (Cohen-Macaulay) type of orders over Dedekind domains in étale algebras. We provide a bound for the type, and give formulas to compute it. We relate the type of the overorders of a given order to the size of minimal generating sets of its fractional ideals, generalizing known results for Gorenstein and Bass orders. Finally, we give a classification of the ideal classes with multiplicator ring of type 2, with applications to the computations of the conjugacy classes of integral matrices and the isomorphism classes of abelian varieties over finite fields. [ABSTRACT FROM AUTHOR]

Ionic diode‐based generators show great superiority in harvesting low‐frequency mechanical energy from human motions for various wearable applications. The major challenge is to improve their extremely limited output voltage for the miniaturization/simplicity of ionic diode‐based self‐powered devices as well as further improvement of mechanoelectric conversion performance. Herein, the construction of gradient polycation/polyanion heterojunction is demonstrated to vastly boost the output voltage, energy‐harvesting efficiency, and sensing performance of ionic diode. Besides an inherent potential at the polyanion/polycation heterojunction interface, the additional transmembrane potentials can be generated across gradient polyanion and polycation conductors of ionic diodes due to their gradient charge distribution. Consequently, the gradient ionic diode‐based generators produce much higher output voltage (306.53 mV) than previously reported homogeneous ones (4.1–135 mV). Meanwhile, the high output voltage imparts gradient ionic diode‐based generator with ultrahigh power density (50.16 µW cm−2 or 250.8 µW cm−3) and pressure‐perception sensitivity (43582 mV/MPa), which are dramatically increased by 162.76% and 128.71%, respectively, compare to those of homogeneous one. Impressively, the resulting diode‐based generators can generate ultralarge current density (≈0.52 mA cm−2) with ultralong discharge time (>400 s), thus enabling the continuous power generation under the low‐frequency pressure for various wearable and implantable applications. [ABSTRACT FROM AUTHOR]

This paper provides an in‐depth study of the winding mechanical properties in generators under rotor interturn short circuit (RISC) cases. Unlike previous studies, this research investigates not only the influence of RISC degrees, but also the RISC positions and the eccentricity on the winding mechanical properties. The electromagnetic force (EF) formulas as well as the electromagnetic‐structure coupling model are first proposed to derive the mechanical winding response characteristics, such as the vibration, deformation, the strain, and the stress. Subsequently, both finite element analysis (FEA) and experimental investigations are conducted to validate the theoretical findings. The results reveal that RISC introduces additional harmonics to the EF. Furthermore, as the eccentricity/RISC degree or the distance between the short circuit position and the N‐pole increases, the end winding vibrations become more pronounced. When comparing single eccentricity and RISC faults to cases where both faults occur simultaneously, it is observed that the combined faults have a more detrimental impact on the end winding mechanical properties. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

In this paper, we consider endomorphisms of an undirected cycle graph from Semigroup Theory perspective. Our main aim is to present a process to determine sets of generators with minimal cardinality for the monoids wEndCn and EndCn of all weak endomorphisms and all endomorphisms of an undirected cycle graph Cn with n vertices. We also describe Green's relations and regularity of these monoids and calculate their cardinalities. [ABSTRACT FROM AUTHOR]

Owing to their high specific energy capabilities, ultramicrogas turbines (UMGT) are a high-potential technology to provide portable electric power supply for applications with demand of less than 1 kW. UMGT conceptual design is challenged by small-scale effects augmenting interdisciplinary dependencies leading to highly coupled, nonlinear component interactions. This work provides a novel approach to conceptual UMGT design by combining reduced order component and system modeling with constrained multi-objective optimization. Hereby, Part I presents integrated design and performance modeling of compressor, turbine, combustor, and generator. In Part II, the heat engine and generator modules are merged into a system framework by establishing conceptual UMGT rotor geometry and engine design. Following bearing selection and lifetime assessment, experimentally validated reduced order models are developed for heat transfer and rotordynamic analysis. Using the elaborated framework, a constrained multi-objective system optimization of a 300 W engine is performed based on ten design parameters and comparing SiAlON and Inconel 718 as potential rotor materials available for additive manufacturing. Hereby, bearing lifetime, system efficiency, and specific power are maximized while meeting rotordynamic, structural, and thermal requirements. Evaluating the results, interdisciplinary effects are highlighted, and two optimum engine configurations are suggested. [ABSTRACT FROM AUTHOR]

Ultramicrogas turbines (UMGTs) for electric power generation up to 1 kW are a viable replacement technology for lithium batteries in drones due to their high energy density. Previous research has shown that small-scale effects disqualify conceptual design practices applied to larger gas turbines owing to highly coupled, nonlinear component interactions. To fill this gap, we propose an interdisciplinary conceptual design and analysis framework based on reduced order models. To this end, the current work is divided into two parts covering component design and system integration, analysis, and optimization. In Part I, automated conceptual design of all engine subcomponents is elaborated facilitating interdependent reduced order models for compressor, turbine, combustor and high-speed generator while also considering additive manufacturing constraints. In a second step, the reduced order performance models are compared to computational fluid dynamics (CFD) Reynolds-averaged-Navier-Stokes (RANS) simulations of various turbomachinery geometries as well as experimental data of combustor and high-speed generator prototypes, showing good agreement and thus validating the component modules. In conclusion, the first part of this work elaborates an automated and efficient method to conceptual design of all components required for a functional UMGT. Since the strategy is applicable independent of component arrangement and engine layout, the proposed methods offer a universal framework for small gas turbine generators. [ABSTRACT FROM AUTHOR]

Introduction Inhaled nitric oxide (INO) is a selective pulmonary vasodilator delivered from compressed gas cylinders filled to 2,200 psig (137.8 bar) with 800 ppm of NO in a balance of nitrogen. NO is currently FDA-approved for use in term or near-term infants with hypoxemia and signs of pulmonary hypertension in the absence of cardiac disease. INO has also been shown to improve oxygenation in adults with refractory hypoxemia. Current doctrine precludes the use of NO during military aeromedical transport owing to the requirement for large compressed gas cylinders. We performed a bench evaluation of 2 delivery systems that create NO from room air without the need for pressurized cylinders, Materials and Methods We evaluated 2 portable nitric oxide INO generation systems (LungFit PH, Beyond Air Inc, Garden City, NJ and a prototype NO generator, Odic Inc, Littleton, MA) at ground level, 8,000, and 14,000 feet (2,437 and 4,267 meter) simulated altitude in an altitude chamber. The output from each device was injected into the inspiratory limb of the ventilator circuit that was attached to a test lung. A 731 ventilator (Zoll Medical, Chelmsford, MA) and T1 (Hamilton Medical, Reno, NV) were used employing 24 combinations of ventilator settings each repeated in duplicate. An INOmax DS IR was used to measure delivered INO and NO2 via a sampling line attached in the ventilator circuit inspiratory limb. A fast response oxygen analyzer (O2CAP, Oxigraf Inc, Sunnyvale, CA) was used to measure inspired FiO2. Target INO concentration was 20 ppm. Results Across all ventilator settings, the LungFit device delivered INO was 19.8 ± 1.6 ppm, 16.1 ± 1.9 ppm, and 11.6 ± 1.7 ppm at ground level, 8,000 ft (2,437 meter), and 14,000 ft (4,267 meter), respectively. The Odic device delivered INO dose was 20.6 ± 1.4 ppm, 21.3 ± 5.5 ppm, and 20.4 ± 9.1 ppm at ground level, 8,000 ft (2,437 meter), and 14,000 ft (4,267 meter), respectively. Conclusions Both devices delivered a reliable INO dose at ground level. Altitude significantly affected INO delivery accuracy at 14,000 ft (4,267 meter) (P  < 0.01) with both devices and at 8,000 ft (2,437 meter) (P  < 0.01) with LungFit. Differences in INO dosage were not statistically significant with the Odic device at 8,000 ft (2,437 meter)(P  > 0.05) although there were large variations with selected ventilator settings. With careful monitoring, devices creating INO from room air without cylinders could be used during aeromedical transport without the need for pressurized cylinders. [ABSTRACT FROM AUTHOR]

There are numerous methods for detecting interturn faults (ITFs) in the field winding of synchronous machines (SMs). One effective approach is based on comparing theoretical and measured excitation currents. This method is unaffected by rotor temperature in static excitation SMs. However, this paper investigates the influence of rotor temperature in brushless synchronous machines (BSMs), where rotor temperature significantly impacts the exciter excitation current. Extensive experimental tests were conducted on a special BSM with measurable rotor temperature. Given the challenges of measuring rotor temperature in industrial machines, this paper explores the feasibility of using stator temperature in the exciter field current estimation model. The theoretical exciter field current is calculated using a deep neural network (DNN), which incorporates electrical brushless synchronous generator output values and stator temperature, and it is subsequently compared with the measured exciter field current. This method achieves an error rate below 0.5% under healthy conditions, demonstrating its potential for simple implementation in industrial BSMs for ITF detection. [ABSTRACT FROM AUTHOR]

We study the minimum number of elements in the conjugacy class of an automorphism of a sporadic simple group that generate a subgroup containing all inner automorphisms. These results refine the estimates obtained earlier in the papers by Guralnick and Saxl and by Di Martino, Pellegrini, and Zalesski.

We propose a new generator which has been used as a generalized class, and can also be helpful in generating new flexible generalized classes of distributions for continuous random variable. The newly proposed generator-cum-generalized class does not involve any extra parameter, and its functional form plays an important role along with baseline models to develop flexible models. In literature, such classes had been reported as Marshall-Olkin G-class, exponentiated G-class, Transmuted G-class, exponentiated generalized G-class, and Flexible G-class. So, any parent (or baseline) model can be substituted in the proposed class which has no extra burden on the parameters of the class. Some needful characteristics of the newly proposed class are obtained. Furthermore, a special model of the class, that is, the flexible Kumaraswamy distribution is considered and its properties are reported. The parameters estimation is dealt through the method of maximum likelihood, and a simulation is carried out to assess the performance of model’s parameters. Four real-life data sets are analyzed to show usefulness of the proposed model in comparison to some well-established competitive models. It is found that the proposed model yields low values of the goodness-of-fit statistics as compared to the other models, and hence our proposed model performed better as compared to others on these four data sets.

We described a minimal separating set for the algebra of O 2 + (F q) -invariant polynomial functions of m -tuples of two-dimensional vectors over a finite field F q. [ABSTRACT FROM AUTHOR]

This study presents a novel approach for solving the economic dispatch (ED) problem in groups of generating units communicating through a communication network. The suggested strategy is a consensus-based dynamic event-triggered (ET) distributed optimization method. Our methodology considers the sharing of the local information between generators and their convex cost functions to address the total cost function and offers a decentralized optimization solution over a network. The proposed distributed method addresses the ED problem by considering the criterion of optimal cost and by offering efficient communication. Generating units are grouped according to their generation operational limits, that is, total capacity and dynamic ET distributed protocols are developed to ensure the consensus of cost variables among generating units, operating under normal capacity conditions. The remaining generating agents work on their operating limits, which are segregated through the sharing of flag information through a switching mechanism. Consequently, in contrast to the existing methods, the recommended protocol allows nodes to function in groups, based on the power supply, for ED with geographical clustering and capacity restrictions, in addition to handling the system constraints. Furthermore, the proposed technique employs a dynamic triggering method to manage bandwidth and guarantee the elimination of Zeno behavior. The simulation results validate the efficacy of the proposed approach. [ABSTRACT FROM AUTHOR]

This article proposes a data-driven approach for generating personalized smile style images for neutral expressions, which aims to produce diverse smile styles while preserving individual features. Unlike other generator models that require expensive manual facial attribute labeling, we designed an auxiliary expression attention Siamese network (EASN) to extract identity-irrelevant facial expression attention regions and guide the proposed two-stage style-expression generative adversarial network (style-exprGAN). The first generator stage generates the overall facial geometry and virtual smile features, while the second stage refines the image quality. Additionally, we introduced traditional geometry warping methods to include registered neutral expression images for consistent transformation and realistic texture fusion. Results show that the proposed method effectively synthesizes realistic and diverse smile styles while preserving individual features. Furthermore, we demonstrate the potential of our data-driven approach by applying the generated personalized smile style images to image augmentation tasks, improving the stability and robustness of facial recognition models. [ABSTRACT FROM AUTHOR]

At the heart of the debate about generative or autonomous AI is the concern that it could take action away from humans. Hannah Arendt, who gave the concept of action a political profile and opposed the automation tendencies of modernity, provides a basis for assessing fears that humans will cede their political action to AI. After an introduction to Arendt's political theory of action, the paper examines whether AI can and should act. The focus is on linguistic models. [ABSTRACT FROM AUTHOR]

The issues of selecting the frequency and power of high-frequency heating in soldering electronic modules and device enclosures are thoroughly examined. High-frequency electromagnetic energy is explored for its efficient non-contact heating capabilities, enabling rapid heating to soldering temperatures through the induction of eddy currents in the metal components and solder. Compared to convective heat sources, high-frequency heating can achieve heating rates up to 10 times faster, with the heating zone precisely localized within the area defined by the inductor design. Methods and device schematics for high-frequency soldering processes are provided, alongside descriptions of the technological equipment and fixtures utilized in these processes. Transistor generators operating at medium (66 kHz) and high frequencies (440 and 1760 kHz) have gained widespread adoption for high-frequency heating applications. To enhance the quality of solder joints and increase product yield, computer-controlled thermal profiles are essential for high-frequency soldering processes. The advantages of high-frequency heating, including locality, simplicity of design, high environmental cleanliness, and the ability to leverage electromagnetic forces for improving solder flow, make it an optimal choice for surface mounting of electronic modules. Induction devices constructed on magnetic cores are also viable for soldering power contacts, connectors, and wires to printed circuit boards, coaxial cables, and sealing metal-glass housings of integrated circuits. These applications highlight the versatility and efficacy of high-frequency heating techniques in modern electronic assembly processes. [ABSTRACT FROM AUTHOR]

Using wind turbines (WTs) equipped with doubly fed induction generators (DFIG) is a popular technology for generating renewable energy. To ensure safe operation, prompt maintenance, and better operational reliability, the induction generator used in wind energy must be monitored. In this paper, an analysis is carried out on stator currents of the DFIG machine in a wind farm to identify any blade imbalances in the wind farm. A fault characteristics extraction analysis is carried out on the machine stator currents to detect the fault in the system. Firstly, the mathematical equation of the DFIG blade unbalanced stator current is generated using the DFIG model. Secondly, Park's Transformation is used to modify the stator's 3-phase current. Further, by evaluating the feature frequency amplitude variation in the squared signal by doing a spectral analysis on the stator current vector's squared signal. Lastly, a Simulink model for the DFIG is developed. The suggested approach analyses the fault signal of the imbalanced blade fault at various wind velocities. The outcomes show that the suggested method for diagnosing impeller imbalance faults can successfully locate the fault. [ABSTRACT FROM AUTHOR]

Modern multicore processors use network-on-chip (NoC) as the communication backbone. With aggressive product release deadlines due to competition from peers, the usage of third-party intellectual property (IP) blocks for NoCs is a common practice. Hardware Trojans in NoC can lead to performance degradation and the exposure of sensitive information through data leakage. We address this problem by devising a secure, lightweight cryptosystem called secure NoC (Sec-NoC) to be used for on-chip communications, ensuring confidentiality and integrity. The Sec-NoC implements authenticated packet encryption as well as an integrity check at network interfaces. The recovery from faults is facilitated by injecting NACKs and retransmissions into the network. Unlike the existing works, a key-encapsulation method is also discussed for sharing the symmetric key between two nodes. Experimental results show that the Sec-NoC experiences a latency overhead of 1.3% only with minimal area and power overhead. [ABSTRACT FROM AUTHOR]

A software tool based on dimensional chains is developed for determining stator and rotor misalignment in an automobile generator. [ABSTRACT FROM AUTHOR]

The effects of perforation on the characteristics of the downstream vortex of a microvortex generator (MVG) mounted on a flat plate, are numerically investigated in this paper. A single rectangular MVG with circular and square perforation, at different locations on the MVG, is mounted on a flat plate at 16 deg installation angle with respect to the flow direction. The MVG is placed inside a turbulent boundary layer at Reynolds number of 16,293 based on MVG height and freestream velocity. The analysis is conducted using the Reynolds-averaged Navier-Stokes (RANS) modeling. The results of the analysis show that the MVG vortex is most effective when the perforation is located at the center and lower side of the MVG. The vortex strength for MVG with this perforated location is found to be much higher than the MVG without any perforation. [ABSTRACT FROM AUTHOR]

There are numerous methods for detecting interturn faults (ITFs) in the field winding of synchronous machines (SMs). One effective approach is based on comparing theoretical and measured excitation currents. This method is unaffected by rotor temperature in static excitation SMs. However, this paper investigates the influence of rotor temperature in brushless synchronous machines (BSMs), where rotor temperature significantly impacts the exciter excitation current. Extensive experimental tests were conducted on a special BSM with measurable rotor temperature. Given the challenges of measuring rotor temperature in industrial machines, this paper explores the feasibility of using stator temperature in the exciter field current estimation model. The theoretical exciter field current is calculated using a deep neural network (DNN), which incorporates electrical brushless synchronous generator output values and stator temperature, and it is subsequently compared with the measured exciter field current. This method achieves an error rate below 0.5% under healthy conditions, demonstrating its potential for simple implementation in industrial BSMs for ITF detection.

This paper addresses the quality control of the photolithography process in the semiconductor industry. Overlay errors in the process seriously affect the wafer yield, and cause the wafer to be forced to rework and affect the production efficiency of the equipment. We examine the current state of its process control, develop a novel overlay predict model, and verify the prediction results. This study proposes a Global Attention Generative Adversarial Networks (GAGAN) model to precisely predict the overlay error for the feed-forward data of the front layer, which is used as the important information and process parameters for the advanced process control of the current layer. Experiment results on a semiconductor shop-floor confirms that our proposed method achieves high predictive performance while maintaining extensibility and visual quality. [ABSTRACT FROM AUTHOR]

How to model the effect of reflection is crucial for single image reflection removal (SIRR) task. Modern SIRR methods usually simplify the reflection formulation with the assumption of linear combination of a transmission layer and a reflection layer. However, the large variations in image content and the real-world picture-taking conditions often result in far more complex reflection. In this paper, we introduce a new screen-blur combination based on two important factors, namely the intensity and the blurriness of reflection, to better characterize the reflection formulation in SIRR. Specifically, we present Screen-blur Reflection Networks (SRNet), which executes the screen-blur formulation in its network design and adapts to the complex reflection on real scenes. Technically, SRNet consists of three components: a blended image generator, a reflection estimator and a reflection removal module. The image generator exploits the screen-blur combination to synthesize the training blended images. The reflection estimator learns the reflection layer and a blur degree that measures the level of blurriness for reflection. The reflection removal module further uses the blended image, blur degree and reflection layer to filter out the transmission layer in a cascaded manner. Superior results on three different SIRR methods are reported when generating the training data on the principle of the screen-blur combination. Moreover, extensive experiments on six datasets quantitatively and qualitatively demonstrate the efficacy of SRNet over the state-of-the-art methods. [ABSTRACT FROM AUTHOR]

With the growing use of mobile devices, location-based services (LBS) are becoming increasingly popular. BLS deliver accurate services to individuals according to their geographical locations, but privacy issues have been the primary concerns of users. Privacy-preserving LBS (PPLBS) were proposed to protect location privacy, but there are still some problems: 1) a semi-trusted third party (STTP) is required to blur users’ locations; 2) both the computation and communication costs of generating a query are linear with the size of queried areas; 3) the schemes were not formally treated, in terms of definition, security model, security proof, etc. In this paper, to protect location privacy and improve query efficiency, an oblivious location-based services (OLBS) scheme is proposed. Our scheme captures the following features: 1) an STTP is not required; 2) users can query services without revealing their exact location information; 3) the service provider only knows the size of queried areas and nothing else; and 4) both the computation and communication costs of generating a query is constant, instead of linear with the size of queried areas. We formalise both the definition and security model of our OLBS scheme, and propose a concrete construction. Furthermore, the implementation is conducted to show its efficiency. The security of our scheme is reduced to well-known complexity assumptions. The novelty is to reduce the computation and communication costs of generating a query and enable the service provider to obliviously generate decrypt keys for queried services. This contributes to the growing work of formalising PPLBS schemes and improving query efficiency. [ABSTRACT FROM AUTHOR]

Phase unwrapping (PU) is a critical processing step for obtaining information on land surface deformation from interferometric synthetic aperture radar (InSAR) images. Traditional PU methods take the phase continuity assumption as the precondition. However, in actual applications, there are many factors that can cause phase discontinuities, resulting in large errors in the PU results. With the fast development of deep learning, the data-driven deep learning methods for PU may help address this issue. Therefore, this study proposes a coherence-guided InSAR PU method with cycle-consistent adversarial networks. In this method, PU was considered a pixel-level regression problem from the interferogram to the unwrapped phase; cycle-consistent adversarial networks as one-step PU model were imported with the interferogram as the input and the unwrapped phase as the output. Except for adversarial loss and cycle consistency loss, based on the PU theory and the coherence of SAR images, the $\mathcal {L}_{1}$ loss with the weight of the coherence coefficient was added to guide the training process of networks. In addition to the traditional mean square error index, the root mean square value of the phase loop closure was introduced to evaluate the quality of the generated unwrapped phase. The results show that the proposed method can not only achieve the accuracy of the traditional PU method in the region with good coherence but also obtain better unwrapping results in the region with poor coherence, where the traditional PU method is restricted. It is also superior to the existing PU method with a conditional adversarial network. [ABSTRACT FROM AUTHOR]

The potential for generating electricity from solar energy as one of the renewable energies is suitable for rural areas, small populations, or communal systems. However, this type of power plant requires a high investment budget. Photovoltaic power systems must be designed to meet the demand for electrical energy but require a large supply. To build a more efficient system, it is necessary to build a communal system. For a small population, a 3000-watt power generation system is made. It will be distributed directly to users; a 5000-watt system is made for a larger area. It will be distributed directly to users and interconnected between generators with the principle of load control. In this study, a solar power plant (PLTS) was designed with an on-grid bidirectional system. Solar panels' conversion of electrical energy is channeled to users and stored in a battery backup system. This PLTS system produces a maximum power of 3000 watts by using 8 units of 450wp solar panels, an inverter with a 48-volt on or off-grid mode system, and 4 12V 200 Ah backup batteries. From the measurement results, the PLTS system will start converting DC current into AC with a radiation value of 356 to 1258 W/m2. Produce on-grid AC current energy, a maximum of 2297 watts, and charge backup batteries with DC current, a maximum of 14.3 A. This on-grid (bidirectional) backup PLTS system can convert DC current into AC, supply it directly to the network electricity (grid), and perform energy backups when solar energy is not energized. [ABSTRACT FROM AUTHOR]

The potential for generating electricity from solar energy as one of the renewable energies is suitable for rural areas, small populations, or communal systems. However, this type of power plant requires a high investment budget. Photovoltaic power systems must be designed to meet the demand for electrical energy but require a large supply. To build a more efficient system, it is necessary to build a communal system. For a small population, a 3000-watt power generation system is made. It will be distributed directly to users; a 5000-watt system is made for a larger area. It will be distributed directly to users and interconnected between generators with the principle of load control. In this study, a solar power plant (PLTS) was designed with an on-grid bidirectional system. Solar panels' conversion of electrical energy is channeled to users and stored in a battery backup system. This PLTS system produces a maximum power of 3000 watts by using 8 units of 450wp solar panels, an inverter with a 48-volt on or off-grid mode system, and 4 12V 200 Ah backup batteries. From the measurement results, the PLTS system will start converting DC current into AC with a radiation value of 356 to 1258 W/m2. Produce on-grid AC current energy, a maximum of 2297 watts, and charge backup batteries with DC current, a maximum of 14.3 A. This on-grid (bidirectional) backup PLTS system can convert DC current into AC, supply it directly to the network electricity (grid), and perform energy backups when solar energy is not energized.

Almost all applications stop scaling at some point; those that don't are seldom performant when considering time to solution on anything but aspirational/unicorn resources. Recognizing these tradeoffs as well as greater user functionality in a near-term exascale computing era, we present libEnsemble, a library aimed at particular scalability- and capability-stretching uses. libEnsemble enables running concurrent instances of an application in dynamically allocated ensembles through an extensible Python library. We highlight the structure, execution, and capabilities of the library on leading pre-exascale environments as well as advanced capabilities for exascale environments and beyond.

Harvesting various mechanical energy from the daily environment has been proposed as a promising way to power electronic devices in the era of Internet of Things. However, most of existing generators are troubled by complex surface structures to achieve higher power output because of the limitations by interfacial effects and unable to achieve direct current (DC) output in the vertical direction. Herein, by introducing the polarized water molecules at the solid contact interface, a vertical structure dynamic diode DC generator is proposed. In the process of polarization and depolarization, water molecules induce, accumulate and rebound charges at the interfaces, and form a voltage output up to 1.7 V based on a solid‐liquid‐solid structure. Furthermore, through integrating series of water molecular generators, a voltage of 4.5 V can be achieved and effectively power commercial LED. This generator has been proven to harvest mechanical energy in the vertical direction to output DC power and excellent potential for applications in distributed energy supply. [ABSTRACT FROM AUTHOR]

We present an algorithm for calculating a minimal generating set of a finite algebra. Despite the fact that the problem is in NP, a single call to a SAT solver is impractical since the encoding is cubic. Instead, the proposed algorithm solves a series of smaller subproblems. The individual subproblems are formulated as integer linear programs (ILP) that are solved by an off-the-shelf solver. Our implementation shows that the proposed algorithm is highly efficient and is able to compute minimal generators for algebras of orders approximately 2000. In our experiments we focus on Moufang loops, a variety of loops with properties close to groups. For Moufang loops of prime power order, we are able to calculate a minimal generating set by another method, using theoretical results on the Frattini subloop and algorithms for permutation groups, of which some are reported here for the first time. This second method does not cover all cases, but in the covered cases it serves as a check of correctness of the ILP-based algorithm. [ABSTRACT FROM AUTHOR]

In this work, a new micro-electrode bubble generator is presented that employs a micro-electrode installed inside a small nozzle enabling the production of bubbles with controllable size and frequency. This bubble generator can be employed as a simple and potentially cheap method for the generation of single bubbles in a liquid, as long as it enables ion exchange, as an alternative to more complicated methods such as timely injection of a gas through a nozzle, which requires sophisticated nozzle design, manufacturing, and monitoring of the injected gas flow rate. A systematic investigation was conducted to assess the effect of the bubble generator dimensions, applied voltage, and electrolyte flow conditions on the size and frequency of the generated bubbles. It was shown that when the micro-electrode is thinly concealed within the nozzle, this bubble generator can successfully produce bubbles covering a wide range of diameters from 0.4 to 1.4 mm with a size distribution standard deviation of about 25%. The mechanism of single and continuous bubbles formation from the proposed bubble generator is also discussed. While this paper introduces this new micro-electrode bubble generator, further work is required to optimize it, enabling more accurate control over bubble size and frequency. [ABSTRACT FROM AUTHOR]

This survey paper wants to highlight the mathematical impact of the celebrated paper by Gaschütz in which the concepts of prefrattini subgroups and crowns were introduced. [ABSTRACT FROM AUTHOR]

For n ∈ N , let [ n ] = { 1 , 2 , ... , n } be an n - element set. As usual, we denote by I n the symmetric inverse semigroup on [n], i.e. the partial one-to-one transformation semigroup on [n] under composition of mappings. The crown (cycle) C n is an n-ordered set with the partial order ≺ on [n], where the only comparabilities are 1 ≺ 2 ≻ 3 ≺ 4 ≻ ⋯ ≺ n ≻ 1 or 1 ≻ 2 ≺ 3 ≻ 4 ≺ ⋯ ≻ n ≺ 1. We say that a transformation α ∈ I n is order-preserving if x ≺ y implies that x α ≺ y α , for all x, y from the domain of α . In this paper, we study the inverse semigroup I C n of all partial automorphisms on a finite crown C n . We consider the elements, determine a generating set of minimal size and calculate the rank of I C n . [ABSTRACT FROM AUTHOR]

Given an algebra F[H]G of polynomial invariants of an action of the group G over the vector space H, a subset S of F[H]G is called separating if S separates all orbits that can be separated by F[H]G. A minimal separating set is found for some algebras of matrix invariants of several matrices over an infinite field of arbitrary characteristic different from two in case of the orthogonal group. Namely, we consider the following cases: • GL(3) -invariants of two matrices; • O(3) -invariants of d > 0 skew-symmetric matrices; • O(4) -invariants of two skew-symmetric matrices; • O(3) -invariants of two symmetric matrices. A minimal generating set is also given for the algebra of orthogonal invariants of three 3×3 symmetric matrices. [ABSTRACT FROM AUTHOR]

Intelligent reflecting surfaces (IRS) have been proposed as a revolutionary technology owing to its capability of adaptively reconfiguring the propagation environment in a cost-effective and hardware-efficient fashion. While the application of IRS as a passive reflector to enhance the performance of wireless communications has been widely investigated in the literature, using IRS as a passive transmitter recently is emerging as a new concept and attracting steadily growing interest. In this paper, we propose two novel IRS-based passive information transmission systems using advanced symbol-level precoding. One is a standalone passive information transmission system, where the IRS operates as a passive transmitter serving multiple receivers by adjusting its elements to reflect unmodulated carrier signals. The other is a joint passive reflection and information transmission system, where the IRS not only enhances transmissions for multiple primary information receivers (PIRs) by passive reflection, but also simultaneously delivers additional information to a secondary information receiver (SIR) by embedding its information into the primary signals at the symbol level. Two typical optimization problems, i.e., power minimization and quality-of-service (QoS) balancing, are investigated for the proposed IRS-based passive information transmission systems. Simulation results demonstrate the feasibility of IRS-based passive information transmission and the effectiveness of our proposed algorithms, as compared to other benchmark schemes.

Nigeria is endowed with abundant sunshine year-round; thus, solar PV would solve the environmental problems associated with petrol-powered generators. However, it is unclear whether households are willing to transition. Thus, we analyze households' willingness to pay (WTP) for solar PV under four scenarios: (i) WTP when a solar PV is complemented with a generator, (ii) WTP when a solar PV completely displaces a generator, (iii) WTP when a solar PV is complemented with a generator, plus a subsidy, and (iv) WTP when a solar PV completely displaces a generator, given a subsidy. We find that WTP for solar PV is higher when it can displace generators completely. Subsidy plus monthly rather than upfront payment would scale up the adoption of solar PV by about 6 per cent. Furthermore, the cost benefit analysis results show that solar PV investment is profitable. Thus, there is a need to implement policies aimed at scaling up the energy transition. [ABSTRACT FROM AUTHOR]

The level of electricity generation in Nigeria is presently grossly inadequate. Consequently, the productive sectors of the economy do not presently enjoy an uninterrupted supply of electrical energy from the country’s national grid and the downtime is in most cases too much. Using diesel-fueled electric power generators has become an attractive alternative to meet the shortfall in the energy supply gap. In this study, the levels of polycyclic aromatic hydrocarbons in the vicinity of the diesel-fueled electric power generators operated by Osun State University, Osogbo, Nigeria were investigated with a view to ascertain the priority levels and carcinogenic PAHs. Since the generators were recently relocated, the study covered the old and the new sites. Polyurethane foam passive samplers were deployed at the old and new sites for 28 days. They were subjected to sohxlet extraction using dichloromethane to extract the PAHs from the PUFs. Cleaning up and elution were done with 5 g of silica gel column and 40 mL 1:1, DCM:Hexane followed by concentration in a rotary evaporator using a stream of nitrogen. Gas chromatographymass spectrometry (GC-MS) analysis was used to determine of PAHs. The Ʃ priority PAHs around the old and new sites were in the range of 4.43-5.44 μg/m3 and 4.47-5.35 μg/m³, respectively. The Ʃ carcinogenic PAHs at the sites were 2.98 -3.42 μg/m³ and 3.35 - 4.17 μg/m³ . Higher molecular weight PAHs dominated the measured PAHs with benzo[a]pyrene being the most significant contributor to the computed total toxicity equivalence (TTEQ). The PAHs diagnostic ratios affirmed that the measured PAHs were from dieselrelated sources. The levels of the PAHs obtained in this study are above permissible limits specified for ambient air; hence, the air around the power plant is considered unsafe. [ABSTRACT FROM AUTHOR]

We explore the structure of the cohomology ring of the moduli space of stable 1-dimensional sheaves on P2 of any degree. We obtain a minimal set of tautological generators, which implies an optimal generation result for both the cohomology and the Chow ring of the moduli space. Our approach is through a geometric study of tautological relations. [ABSTRACT FROM AUTHOR]

Prediction of human actions in social interactions has important applications in the design of social robots or artificial avatars. In this paper, we focus on a unimodal representation of interactions and propose to tackle interaction generation in a data-driven fashion. In particular, we model human interaction generation as a discrete multi-sequence generation problem and present SocialInteractionGAN, a novel adversarial architecture for conditional interaction generation. Our model builds on a recurrent encoder-decoder generator network and a dual-stream discriminator, that jointly evaluates the realism of interactions and individual action sequences and operates at different time scales. Crucially, contextual information on interacting participants is shared among agents and reinjected in both the generation and the discriminator evaluation processes. Experiments show that albeit dealing with low dimensional data, SocialInteractionGAN succeeds in producing high realism action sequences of interacting people, comparing favorably to a diversity of recurrent and convolutional discriminator baselines, and we argue that this work will constitute a first stone towards higher dimensional and multimodal interaction generation. Evaluations are conducted using classical GAN metrics, that we specifically adapt for discrete sequential data. Our model is shown to properly learn the dynamics of interaction sequences, while exploiting the full range of available actions. [ABSTRACT FROM AUTHOR]

Despite the recent advancement in speech emotion recognition (SER) within a single corpus setting, the performance of these SER systems degrades significantly for cross-corpus and cross-language scenarios. The key reason is the lack of generalisation in SER systems towards unseen conditions, which causes them to perform poorly in cross-corpus and cross-language settings. Recent studies focus on utilising adversarial methods to learn domain generalised representation for improving cross-corpus and cross-language SER to address this issue. However, many of these methods only focus on cross-corpus SER without addressing the cross-language SER performance degradation due to a larger domain gap between source and target language data. This contribution proposes an adversarial dual discriminator (ADDi) network that uses the three-players adversarial game to learn generalised representations without requiring any target data labels. We also introduce a self-supervised ADDi (sADDi) network that utilises self-supervised pre-training with unlabelled data. We propose synthetic data generation as a pretext task in sADDi, enabling the network to produce emotionally discriminative and domain invariant representations and providing complementary synthetic data to augment the system. The proposed model is rigorously evaluated using five publicly available datasets in three languages and compared with multiple studies on cross-corpus and cross-language SER. Experimental results demonstrate that the proposed model achieves improved performance compared to the state-of-the-art methods. [ABSTRACT FROM AUTHOR]