Search

This study deals with the determination of sites suitable for landfill in the Prefecture of Chalkidiki, North Greece, using Boolean logic and Geographic Information Systems (GIS). Landfill siting is an arduous process as it combines environmental, social, and technical factors. Solid waste management is an urgent requirement in tourist sites worldwide. The Prefecture of Chalkidiki is considered a tourist area where volumes of generated waste increase in the summer. The Boolean logic approach was used in the study area to exclude areas not suitable for the establishment of a landfill site and to select areas that meet all the criteria. Nine criteria were selected to create the final map showing areas with the highest suitability for solid waste disposal. According to the Boolean logic method, suitable areas were given a value of one (1), while unsuitable areas were given a value of zero (0). According to the final thematic map of proposed sites, 12.7% of the study area is suitable for landfill construction. The suitable areas identified include pre-existing landfill sites, thus suggesting that the applied method has a high degree of reliability. [ABSTRACT FROM AUTHOR]

A functionally complete Boolean operator is sufficient for computational circuits of arbitrary complexity. We connected YES (buffer) with NOT (inverter) and two NOT four-way junction (4J) DNA gates to obtain IMPLY and NAND Boolean functions, respectively, each of which represents a functionally complete gate. The results show a technological path towards creating a DNA computational circuit of arbitrary complexity based on singleton NOT or a combination of NOT and YES gates, which is not possible in electronic computers. We, therefore, concluded that DNA-based circuits and molecular computation may offer opportunities unforeseen in electronics. [ABSTRACT FROM AUTHOR]

A miniaturized electrochemical sensor was developed for the remote detection of chemical warfare agent (CWA) simulants. To facilitate drone-based remote sensing, this present study focuses on advancing the miniaturized and compact electrochemical sensor for monitoring two CWA simulants, diisopropyl fluorophosphate (DFP) and O,S-diethylmethylphosphonothioate (O,S-DEMPT). The differential pulse voltammetry (DPV) signal was processed, and the DPV signature features were extracted on the basis of the redox properties associated with the absence and the presence of DFP and O,S-DEMPT. Upon the addition of 0.10 equivalence of DFP or O,S-DEMPT, a shift in potential (E) of ~0.13 V was recorded. The limit of detection (LOD) was calculated to be 0.25 µM (0.046 ppm) and 0.10 µM (0.017 ppm) for DFP and O,S-DEMPT, respectively. These results were validated using a portable Palmsens Emstat HR potentiostat, which corroborated the results obtained using a lab benchtop potentiostat. Additionally, Boolean logic ("AND" operation) was implemented for future drone technology deployment. This advancement enables the fabrication of a networked device capable of autonomously executing tasks without constant oversight. [ABSTRACT FROM AUTHOR]

A miniaturized electrochemical sensor was developed for the remote detection of chemical warfare agent (CWA) simulants. To facilitate drone-based remote sensing, this present study focuses on advancing the miniaturized and compact electrochemical sensor for monitoring two CWA simulants, diisopropyl fluorophosphate (DFP) and O,S-diethylmethylphosphonothioate (O,S-DEMPT). The differential pulse voltammetry (DPV) signal was processed, and the DPV signature features were extracted on the basis of the redox properties associated with the absence and the presence of DFP and O,S-DEMPT. Upon the addition of 0.10 equivalence of DFP or O,S-DEMPT, a shift in potential (E) of ~0.13 V was recorded. The limit of detection (LOD) was calculated to be 0.25 µM (0.046 ppm) and 0.10 µM (0.017 ppm) for DFP and O,S-DEMPT, respectively. These results were validated using a portable Palmsens Emstat HR potentiostat, which corroborated the results obtained using a lab benchtop potentiostat. Additionally, Boolean logic (“AND” operation) was implemented for future drone technology deployment. This advancement enables the fabrication of a networked device capable of autonomously executing tasks without constant oversight.

This study deals with the determination of sites suitable for landfill in the Prefecture of Chalkidiki, North Greece, using Boolean logic and Geographic Information Systems (GIS). Landfill siting is an arduous process as it combines environmental, social, and technical factors. Solid waste management is an urgent requirement in tourist sites worldwide. The Prefecture of Chalkidiki is considered a tourist area where volumes of generated waste increase in the summer. The Boolean logic approach was used in the study area to exclude areas not suitable for the establishment of a landfill site and to select areas that meet all the criteria. Nine criteria were selected to create the final map showing areas with the highest suitability for solid waste disposal. According to the Boolean logic method, suitable areas were given a value of one (1), while unsuitable areas were given a value of zero (0). According to the final thematic map of proposed sites, 12.7% of the study area is suitable for landfill construction. The suitable areas identified include pre-existing landfill sites, thus suggesting that the applied method has a high degree of reliability.

A functionally complete Boolean operator is sufficient for computational circuits of arbitrary complexity. We connected YES (buffer) with NOT (inverter) and two NOT four-way junction (4J) DNA gates to obtain IMPLY and NAND Boolean functions, respectively, each of which represents a functionally complete gate. The results show a technological path towards creating a DNA computational circuit of arbitrary complexity based on singleton NOT or a combination of NOT and YES gates, which is not possible in electronic computers. We, therefore, concluded that DNA-based circuits and molecular computation may offer opportunities unforeseen in electronics.

Logic-in-memory (LIM) architecture holds great potential to break the von Neumann bottleneck. Despite the extensive research on novel devices, challenges persist in developing suitable engineering building blocks for such designs. Herein, we propose a reconfigurable strategy for efficient implementation of Boolean logics based on a hafnium oxide-based ferroelectric field effect transistor (HfO 2 -based FeFET). The logic results are stored within the device itself (in situ) during the computation process, featuring the key characteristics of LIM. The fast switching speed and low power consumption of a HfO 2 -based FeFET enable the execution of Boolean logics with an ultralow energy of lower than 8 attojoule (aJ). This represents a significant milestone in achieving aJ-level computing energy consumption. Furthermore, the system demonstrates exceptional reliability with computing endurance exceeding 10 8 cycles and retention properties exceeding 1000 s. These results highlight the remarkable potential of a FeFET for the realization of high performance beyond the von Neumann LIM computing architectures.

In deeply weathered terrains, with high geological diversity and scarce outcrops, the lateritic regolith features support mineral research. Predictive regolith mapping uses spatial modeling and airborne gamma-ray spectrometric data to locate weathered residual products, such as the ferruginous lateritic duricrusts found in tropical regions. Although the regolith materials exhibit qualitative similarities in their gamma-ray spectrometric responses in RGB (KThU) images, the Boolean and fuzzy approaches highlighted differences that allows for mapping the regolith weathering residual products on a wide geodiversity protoliths. Two inference systems were used, one identified the ferruginous lateritic duricrusts and oxisols derived from the felsic/pelitc and mafic rocks types (TP test procedures), and the other identified solely those derived exclusively from mafic rocks (TPM test procedures). Cutoff values for the conjunction eTh/K ∩ eU/K ∩ eTh ∩ K (TP-4) using Boolean logic, provided the most accurate regolith map (accuracy = 95%) among the various tests carried out and indicate that in 28.6% of the total study area, there are lateritic duricrust and oxisols relative to rocks, saprolites, mottled horizons and other soils type. The eTh cutoff value > 4.4 ppm was used to exclude mafic rocks and associated soils, and the K value < 1.3% to exclude rocks with eTh/K and eU/K values similar to the lateritic duricrusts and oxisols. For mapping the lateritic duricrusts derived exclusively from the mafic rocks the conjunction of eTh ∩ eU/K ∩ eTh/K ∩ K ∩ eU (TPM-3) fuzzified by the large membership function was the most efficient. The eU variable with values < 1.21 ppm helps improve the effectiveness of this procedure. The generated predictive map indicated that in about ∼12% (657.9 km2) of the total study area, there are lateritic duricrusts and oxisols derived from mafic rocks. Therefore, a successful method of mapping vast areas from complicated lateritic regolith mosaic derived from a large geodiversity is to apply specific plugins for data fuzzification, supported by observations from field outcrops. • Boolean and fuzzy techniques in airborne gamma-ray spectrometric data. • Regolith with extensive lateritic residual cover. • The gamma spectrometric data reflects the chemical composition of the regolith. • Prediction of lateritic duricrusts derived from mafic rocks. • Prediction of regolith derived from metasedimentary, felsic metaplutonic and metavolcanosedimentary rocks. [ABSTRACT FROM AUTHOR]

Traditional von Neumann architecture, characterized by separate memory and processing units connected by a limited-capacity memory bus, faces challenges in handling tasks with high energy efficiency requirements. In contrast, the compute-in-memory (CIM) architecture offers a promising alternative, facilitating high parallelism in data processing while integrating storage functions, thereby significantly reducing memory access frequency and power consumption. This study presents a fully digital CIM macro featuring a novel self-write-back 12T cell. This bitcell is capable of performing Boolean logic operations and autonomously writing back results into the in-situ cell, thereby significantly improving energy efficiency.This can be used for binary logical operations between each pixel of two images without requiring additional storage area. A bidirectional read/write architectural design enables matrix transposition. This can achieve image rotation.Additionally, this novel 12T cell also offers the option to choose not to write back the results of logical operations, thereby providing the flexibility and configurability for image processing. Combined with an adder tree, it enables multiply-and-accumulate (MAC) operation for convolutional neural networks(CNNs). This can be used for feature extraction. We propose an 18T full adder structure with lower power-delay product than current state-of-the-art full adders, which is advantageous for improving the synthesis performance of the adder tree.The CIM macro supports a 4-bit × 4-bit MAC operation. The proposed CIM macro, designed and simulated using a 28 nm CMOS process with a 16 Kb static random access memory (SRAM), demonstrates promising results. At VDD = 0.9 V, the logic operation energy consumption is 1.35 fJ/bit with an energy efficiency of 740TOPS/W, and MAC operation energy consumption is 15.91 fJ/bit with an energy efficiency of 62.85 TOPS/W. [ABSTRACT FROM AUTHOR]

Reconfigurable neuromorphic computing holds promise for advancing energy-efficient neural network implementation and functional versatility. Previous work has focused on emulating specific neural functions rather than an integrated approach. We propose an all two-dimensional (2D) material-based heterostructure capable of performing multiple neuromorphic operations by reconfiguring output terminals in response to stimuli. Specifically, our device can synergistically emulate the key neural elements of the synapse, neuron, and dendrite, which play important and interrelated roles in information processing. Dendrites, the branches that receive and transmit presynaptic action potentials, possess the ability to nonlinearly integrate and filter incoming signals. The proposed heterostructure allows reconfiguration between different operation modes, demonstrating its potential for diverse computing tasks. As a proof of concept, we show that the device can perform basic Boolean logic functions. This highlights its applicability to complex neural-network-based information processing problems. Our integrated neuromorphic approach may advance the development of versatile, low-power neuromorphic hardware.