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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]

Magnetic domain wall (DW)-based logic devices offer numerous opportunities for emerging electronics applications allowing superior performance characteristics such as fast motion, high density, and nonvolatility to process information. However, these devices rely on an external magnetic field, which limits their implementation; this is particularly problematic in large-scale applications. Multiferroic systems consisting of a piezoelectric substrate coupled with ferromagnets provide a potential solution that provides the possibility of controlling magnetization through an electric field via magnetoelastic coupling. Strain-induced magnetization anisotropy tilting can influence the DW motion in a controllable way. We demonstrate a method to perform all-electrical logic operations using such a system. Ferromagnetic coupling between neighboring magnetic domains induced by the electric-field-controlled strain has been exploited to promote noncollinear spin alignment, which is used for realizing essential building blocks, including DW generation, propagation, and pinning, in all implementations of Boolean logic, which will pave the way for scalable memory-in-logic applications.

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.

The current research aims to assess the feasibility of groundwater resources in two soft and hard formations of the Shamil-Takht basin using logic and operators Fuzzy and Boolean in the GIS environment. For this purpose, eight and seven thematic layers in the soft and the hard formations were investigated and analyzed separately. The layers were prepared in a raster format in the GIS environment and then each of the layers was classified according to the values of usefulness obtained with Fuzzy membership degree and 0 and 1 Boolean values. In the next step, AND and Gamma operators for Fuzzy layers and Algebraic Multiplication operators for Boolean logic were used in combining layers. The groundwater potential map of the studied area was obtained from the desired pixels resulting from performing the operations at the output. Based on this, in Fuzzy logic, 77.1% of the area of soft formation and 11% of the area of hard formation, and in Boolean logic, 24.1% of the area of soft formation and 1.74% of the area of hard formation had the possibility of water sources. Areas with high potential of groundwater resources were in areas with low slope and cultivated and areas with weak potential of water resources were in areas with alluvial and sedimentary formations. Also, the field investigations confirm that the emerging springs and existing wells in the Shamil-Takht basin are located in the areas with the lowest slope and high density of the waterway.

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.

RNA‐cleaving DNAzymes are promising agents for gene therapy that can overcome the low selectivity of other therapeutic nucleic acid agents, including CRISPR/Cas9, antisense oligonucleotides, and RNA interference agents, in protein‐independent RNA cleavage. To achieve this, DNAzyme gene therapy agents should accurately distinguish cancer from healthy cells. Often, cancer RNA markers are expressed in healthy tissue at lower concentrations. Previously, we developed a DNAzyme thresholding gate (DTh), which must bind to three cancer marker molecules prior to cleaving the RNA target. This article presents the next step in the development of DTh by converting a signal from five microRNA inputs into an output cleavage of the RNA model using an advanced system of molecular logic. We demonstrate that it is possible to broaden the available threshold range by increasing the number of marker recognition modules. The threshold gates can be easily adjusted to cleave a broad range of RNA targets. This approach can be used in cancer diagnostics as well as the computational component of DNA nanorobots, autonomous DNA devices for anti‐cancer gene therapy. [ABSTRACT FROM AUTHOR]

The current research aims to assess the feasibility of groundwater resources in two soft and hard formations of the Shamil-Takht basin using logic and operators Fuzzy and Boolean in the GIS environment. For this purpose, eight and seven thematic layers in the soft and the hard formations were investigated and analyzed separately. The layers were prepared in a raster format in the GIS environment and then each of the layers was classified according to the values of usefulness obtained with Fuzzy membership degree and 0 and 1 Boolean values. In the next step, AND and Gamma operators for Fuzzy layers and Algebraic Multiplication operators for Boolean logic were used in combining layers. The groundwater potential map of the studied area was obtained from the desired pixels resulting from performing the operations at the output. Based on this, in Fuzzy logic, 77.1% of the area of soft formation and 11% of the area of hard formation, and in Boolean logic, 24.1% of the area of soft formation and 1.74% of the area of hard formation had the possibility of water sources. Areas with high potential of groundwater resources were in areas with low slope and cultivated and areas with weak potential of water resources were in areas with alluvial and sedimentary formations. Also, the field investigations confirm that the emerging springs and existing wells in the Shamil-Takht basin are located in the areas with the lowest slope and high density of the waterway. [ABSTRACT FROM AUTHOR]

General‐purpose computers usually use logic gate computing units based on complementary metal oxide semiconductors (CMOS). Due to the separate memory and computing units in Von Neumann architecture, data transmission requires great energy and time consumption. Developing novel neuromorphic devices and comprehensively investigating their logical computing mode are crucial to achieve high‐performance and low‐power neuromorphic computation. Here, a systematic summary of Boolean logic computing based on emerging neuromorphic transistors is presented. This summary encompasses logical operation modes, materials, device structures, and working mechanisms. The input mode of Boolean logic operation is classified into electrical input, optical input, and synergistic optical/electrical input. Besides, additional modulation strategies to construct programmable logic functions by electrical, optical, and thermal signals are also summarized. These strategies hold great significance as they enable dynamic reconfiguration of logic operations and provide neuromorphic devices with decision‐making capabilities. Finally, the application prospects and current challenges to Boolean logic computing based on dendritic integration are discussed from the aspects of device integration, synergistic input/modulation modes, auxiliary peripheral circuit, software/hardware system, etc. It is believed that comprehensive investigations on neuromorphic Boolean logic operations are crucial to push forward the development of future neuromorphic computing toward high efficiency and high integration density. [ABSTRACT FROM AUTHOR]

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Binary operating (YES/NO) biosensors based on unconventional biocomputing concept represent a novel approach to the analysis of various biomarkers and environmental signals. The binary biosensors with implemented Boolean logic process analyte input signals using chemical means without electronic computers. They can be used for extension of the analytical output signals to chemical actuation and can be integrated with wearable analytical devices. The progress in this novel biosensing approach is strongly dependent on achievements in biomolecular computing, particularly based on enzyme-catalyzed reactions. The easy interpretation of the analytical results represented in the binary YES/NO form allows convenient adaptation of the biosensors for end-user and point-ofcare within various biomedical and bioelectronic applications. [ABSTRACT FROM AUTHOR]

Urmia city is a region with high potential for the development of industrial centers. However, in the last few decades, the indiscriminate development of industries in this area has led to environmental and socio-economic problems. This study aimed to identify areas prone to the construction of an industrial town in this city and evaluate the existing areas. In order to collect the required data of this descriptive-analytical study, library studies were used. Moreover, in order to achieve the goals of the research, the combined Boolean and fuzzy multi-criteria evaluation method were used. At first, relying on seven criteria of distance from the city, slope, height, fault, waterway, communication lines and land use, maps of restrictions and factors were drawn. In the second step, the fuzzy primary suitability map and the Boolean primary suitability map were prepared and finally, based on the correlation coefficients and standard deviation of the operators, gamma 0.5 was chosen as the most appropriate gamma to overlap the two mentioned maps. The results showed that about 94% of the area of the region is completely unsuitable for the establishment of industries and only about 6% of the area are approximately suitable to completely suitable. Regarding the evaluation of the establishment of the existing industrial areas, it was found that the industrial town of Phase 1 and 2, Karimabad industrial area and the electronics and food industry town are located in the inappropriate area of establishment. Moreover, 8 square kilometers of the Phase 3 of the industrial town is located in the suitable area for settlement and 1 square kilometer is located in the unsuitable area for settlement. [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.

Background: The intersection of synthetic biology and biomaterials promises to enhance safety and efficacy in novel therapeutics. Both fields increasingly employ Boolean logic, which allows for specific therapeutic outputs (e.g., drug release, peptide synthesis) in response to inputs such as disease markers or bio‐orthogonal stimuli. Examples include stimuli‐responsive drug delivery devices and logic‐gated chimeric antigen receptor (CAR) T cells. In this review, we explore recent manuscripts highlighting the potential of synthetic biology and biomaterials with Boolean logic to create novel and efficacious living therapeutics. Main body: Collaborations in synthetic biology and biomaterials have led to significant advancements in drug delivery and cell therapy. Borrowing from synthetic biology, researchers have created Boolean‐responsive biomaterials sensitive to multiple inputs including pH, light, enzymes and more to produce functional outputs such as degradation, gel‐sol transition and conformational change. Biomaterials also enhance synthetic biology, particularly CAR T and adoptive T cell therapy, by modulating therapeutic immune cells in vivo. Nanoparticles and hydrogels also enable in situ generation of CAR T cells, which promises to drive down production costs and expand access to these therapies to a larger population. Biomaterials are also used to interface with logic‐gated CAR T cell therapies, creating controllable cellular therapies that enhance safety and efficacy. Finally, designer cells acting as living therapeutic factories benefit from biomaterials that improve biocompatibility and stability in vivo. Conclusion: By using Boolean logic in both cellular therapy and drug delivery devices, researchers have achieved better safety and efficacy outcomes. While early projects show incredible promise, coordination between these fields is ongoing and growing. We expect that these collaborations will continue to grow and realize the next generation of living biomaterial therapeutics. [ABSTRACT FROM AUTHOR]

Introduction: The lack of proper management and choosing the right place for disposal and burial of waste creates problems for the environment. Khoda Afarin city has a population of about 34977 people and Kalibar city has a population of about 48837 people. In the last few decades in these cities, with the increase in population, consumerism, and the change in people's eating habits, the increase in the consumption of packaged materials along with the imitation of people's consumption patterns has caused an increase in the production of a large amount of waste. Despite this problem, there is still no proper way to dispose of waste in these cities. The purpose of this research was to locate landfill centers based on the ANP network analysis process model and Boolean logic in the geographic information technologies (GIS) environment by using the opinions of experts in the form of pairwise comparison questionnaires and descriptive-analytical methods. Material and methods: In this research, in order to select landfill centers due to the complexity of the influencing factors, the necessity of using GIS and its integration with other management and planning matters has been proposed. Therefore, in this research, ARC GIS software has been used to create databases, spatial analysis and superimposition of information layers, as well as ANP model and Super Decision software to calculate criteria weight and Boolean logic model. Results and discussion: In this research, 17 layers of information including surface water resources, slope, city and village areas, protected areas, fault, soil, road network, lithology, land use, erosion, NDVI, dem, climate, land side, dam, and aspect were used. Then, in the network analysis process model, Super Decision software was used to apply weights for each of the criteria, and in the ArcGIS environment, the information layers were combined with the final weight, and the value of each cell was determined in the final map. The area of 369221 hectares was divided into four categories: unsuitable 174720 hectares, relatively unsuitable 146677 hectares, suitable 42670 hectares and completely suitable 5154 hectares in terms of landfill location, and in Bolin logic, the estimated area of unsuitable 365457 hectares and suitable 3938 hectares for landfill location were detected. Finally, due to the closeness of the areas to each other, the final maps of both models were overlapped, and after merging the locations of 2679 hectares, a suitable location was determined, which covered 73 percent of the suitable areas of the Boleyn model. Conclusion: The comparative analysis of the results shows that in the ANP model, only 1.4 percent of the area is completely suitable, and in the Boleyn model, 1.2 percent of the area has optimal conditions for the landfill. One of the most important achievements of the results of this research is the use of a completely suitable place and a map. [ABSTRACT FROM AUTHOR]

Burgeoning population growth and subsequent demand for freshwater, besides competition among irrigation, domestic, and industrial sectors, coupled with a changing climate, have necessitated prudent and effective management of water resources. Rainwater harvesting (RWH) is considered one of the most effective strategies for water management. However, the location and design of RWH structures are essential for proper implementation, operation, and maintenance. An attempt has been made in this study to locate the most suitable site for RWH structure and design using one of the robust multi-criteria decision analysis techniques, viz. analytic hierarchy process, using geospatial tools in the Gambhir watershed, Rajasthan, India. High-resolution Sentinel-2A data and a digital elevation model of the Advanced Land Observation Satellite were used in this study. Five biophysical parameters, viz. land use and land cover, slope, soil texture, surface runoff, and drainage density, were considered to identify suitable locations for RWH structures. It was observed that runoff is the prime factor in determining the location of RWH structures compared to other parameters. It was revealed that 75.54 km2 (13% of the total area) was very highly suited for the construction of RWH structures, while 114.56 km2 (19%) was highly suitable. A total of 43.77 km2 (7%) of land was determined to be unsuitable for the construction of any type of RWH structure. Farm ponds, check dams, and percolation ponds were suggested for the study area. Furthermore, Boolean logic was used to target a particular type of RWH structure. The study indicated that a total of 25 farm ponds, 14 check dams, and 16 percolation ponds can be constructed at identified locations in the watershed. Water resource development maps of the watershed generated using an analytical approach would be useful for policymakers and hydrologists for targeting and implementing RWH structures in the study watershed. [ABSTRACT FROM AUTHOR]

In this paper, we study how to represent a directed graph as a SAT problem. We study those directed graphs which consists of two strongly connected components (SCC). We reuse the SAT models which are known as the Black-and-White SAT representations. We present the so-called 3rd Solution Lemma: If a directed graph consists of two SCCs, A and B, and there is an edge from A to B, then the corresponding SAT representation has 3 solutions: the black assignment, the white assignment, and the 3rd solution can be written as ￢A union B. Using this result, we present an important negative result: We cannot represent all SAT problems as directed graphs using the Black-and-White SAT representations. Furthermore, we study the question how to represent an SCC by one Boolean variable to maintain the 3rd Solution Lemma. For that we use extended resolution. [ABSTRACT FROM AUTHOR]

Artificial lift methods are used in oil wells when the natural energy of the reservoir is not enough to bring the reservoir fluids at the surface. Therefore, these methods are used to add the missing energy. There are many types of artificial lift methods with different characteristics. The selection of an artificial lift technique for a well is crucial because it influences long-term well production and operating costs. In our paper, we propose an application that allows a quick screening and selection of the best artificial lift technique. The application uses Boolean logic as a mathematical and conceptual approach. The model is based on a memory set of data which is working like a database and compares the information in order to select the best artificial lift method for a well data set. The results are presented in two layers such as a front page used for input data set and a second one where it will be displayed the selected method and its advantages and disadvantages.

Living cells constantly monitor their external and internal environments for changing conditions, stresses or developmental cues. Networks of genetically encoded components sense and process these signals following pre-defined rules in such a way that specific combinations of the presence or absence of certain signals activate suitable responses. Many biological signal integration mechanisms approximate Boolean logic operations, whereby presence or absence of signals are computed as variables with values described as either true or false, respectively. Boolean logic gates are commonly used in algebra and in computer sciences, and have long been recognized as useful information processing devices in electronic circuits. In these circuits, logic gates integrate multiple input values and produce an output signal according to pre-defined Boolean logic operations. Recent implementation of these logic operations using genetic components to process information in living cells has allowed genetic circuits to enable novel traits with decision-making capabilities. Although several literature reports describe the design and use of these logic gates to introduce new functions in bacterial, yeast and mammalian cells, similar approaches in plants remain scarce, likely due to challenges posed by the complexity of plants and the lack of some technological advances, e.g. , species-independent genetic transformation. In this mini review, we have surveyed recent reports describing synthetic genetic Boolean logic operators in plants and the different gate architectures used. We also briefly discuss the potential of deploying these genetic devices in plants to bring to fruition a new generation of resilient crops and improved biomanufacturing platforms. • Boolean logic operators are commonly used in algebra and computer sciences. • Many biological processes can be modeled as Boolean logic operations. • Genetically encoded Boolean logic operators are powerful tools in synthetic biology. • Only recently Boolean logic has been applied to plant synthetic biology. • Different genetic parts and topologies can be combined to build logic operators. [ABSTRACT FROM AUTHOR]

A method of using non‐volatile and fast ferroelectric field‐effect transistor (FeFET) devices to realize Boolean logic is proposed. First, the internal states are initialized. Then, the gate and body function as input terminals, which are used to write the states of the device, based on the voltage. Finally, the output signals can be easily read through the drain current. Of the 10 Institute of Electrical and Electronics Engineers (IEEE) standard logic gates, eight can be implemented using the proposed operation method alone and by following the definitions listed herein. Thus, to enable FeFET devices to act as functional logic gates, a simple operating method is proposed, providing substantial contributions to the development of computing in memory. The experimental results provide evidence of the efficacy of this method. [ABSTRACT FROM AUTHOR]

Biomolecular materials offer tremendous potential for the development of memristive devices due to their low cost of production, environmental friendliness, and, most notably, biocompatibility. Herein, biocompatible memristive devices based on amyloid–gold nanoparticle hybrids have been investigated. These memristors demonstrate excellent electrical performance, featuring an ultrahigh Roff/Ron ratio (>107), a low switching voltage (<0.8 V), and reliable reproducibility. Additionally, the reversible transition from threshold switching to resistive switching mode was achieved in this work. The arrangement of peptides in amyloid fibrils endows the surface polarity and phenylalanine packing, which provides channels for the migration of Ag ions in the memristors. By modulating voltage pulse signals, the study successfully imitates the synaptic behavior of excitatory postsynaptic current (EPSC), paired-pulse facilitation (PPF), and the transition from short-term plasticity (STP) to long-term plasticity (LTP). More interestingly, Boolean logic standard cells were designed and simulated using the memristive devices. The fundamental and experimental results of this study thus offer insights into the utilization of biomolecular materials for advanced memristive devices. [ABSTRACT FROM AUTHOR]

In this work, we propose a novel diagnostic workflow—DigEST—that will enable stratification of disease states based on severity using multiplexed point of care (POC) biosensors. This work can boost the performance of current POC tests by enabling clear, digestible, and actionable diagnoses to the end user. The scheme can be applied to any disease model, which requires time‐critical disease stratification for personalized treatment. Here, urinary tract infection is explored as the proof‐of‐concept disease model and a four‐class classification of disease severity is discussed. Our method is superior to traditional enzyme‐linked immunosorbent assay (ELISA) as it is faster and can work with multiple disease biomarkers and categorize diseases by endotypes (or disease subtype) and severity. To map the nonlinear nature of biochemical pathways of complex diseases, the method utilizes an established supervised machine learning model for digital classification. This scheme can potentially boost the diagnostic power of current electrochemical biosensors for better precision therapy and improved patient outcomes. [ABSTRACT FROM AUTHOR]

Abstract Background: The intersection of synthetic biology and biomaterials promises to enhance safety and efficacy in novel therapeutics. Both fields increasingly employ Boolean logic, which allows for specific therapeutic outputs (e.g., drug release, peptide synthesis) in response to inputs such as disease markers or bio‐orthogonal stimuli. Examples include stimuli‐responsive drug delivery devices and logic‐gated chimeric antigen receptor (CAR) T cells. In this review, we explore recent manuscripts highlighting the potential of synthetic biology and biomaterials with Boolean logic to create novel and efficacious living therapeutics. Main body: Collaborations in synthetic biology and biomaterials have led to significant advancements in drug delivery and cell therapy. Borrowing from synthetic biology, researchers have created Boolean‐responsive biomaterials sensitive to multiple inputs including pH, light, enzymes and more to produce functional outputs such as degradation, gel‐sol transition and conformational change. Biomaterials also enhance synthetic biology, particularly CAR T and adoptive T cell therapy, by modulating therapeutic immune cells in vivo. Nanoparticles and hydrogels also enable in situ generation of CAR T cells, which promises to drive down production costs and expand access to these therapies to a larger population. Biomaterials are also used to interface with logic‐gated CAR T cell therapies, creating controllable cellular therapies that enhance safety and efficacy. Finally, designer cells acting as living therapeutic factories benefit from biomaterials that improve biocompatibility and stability in vivo. Conclusion: By using Boolean logic in both cellular therapy and drug delivery devices, researchers have achieved better safety and efficacy outcomes. While early projects show incredible promise, coordination between these fields is ongoing and growing. We expect that these collaborations will continue to grow and realize the next generation of living biomaterial therapeutics.

Abstract A method of using non‐volatile and fast ferroelectric field‐effect transistor (FeFET) devices to realize Boolean logic is proposed. First, the internal states are initialized. Then, the gate and body function as input terminals, which are used to write the states of the device, based on the voltage. Finally, the output signals can be easily read through the drain current. Of the 10 Institute of Electrical and Electronics Engineers (IEEE) standard logic gates, eight can be implemented using the proposed operation method alone and by following the definitions listed herein. Thus, to enable FeFET devices to act as functional logic gates, a simple operating method is proposed, providing substantial contributions to the development of computing in memory. The experimental results provide evidence of the efficacy of this method.

Abstract In this work, we propose a novel diagnostic workflow—DigEST—that will enable stratification of disease states based on severity using multiplexed point of care (POC) biosensors. This work can boost the performance of current POC tests by enabling clear, digestible, and actionable diagnoses to the end user. The scheme can be applied to any disease model, which requires time‐critical disease stratification for personalized treatment. Here, urinary tract infection is explored as the proof‐of‐concept disease model and a four‐class classification of disease severity is discussed. Our method is superior to traditional enzyme‐linked immunosorbent assay (ELISA) as it is faster and can work with multiple disease biomarkers and categorize diseases by endotypes (or disease subtype) and severity. To map the nonlinear nature of biochemical pathways of complex diseases, the method utilizes an established supervised machine learning model for digital classification. This scheme can potentially boost the diagnostic power of current electrochemical biosensors for better precision therapy and improved patient outcomes.

To support the increasingly complex circuits needed for plant synthetic biology applications, additional constitutive promoters are essential. Reusing promoter parts can lead to difficulty in cloning, increased heterogeneity between transformants, transgene silencing and trait instability. We have developed a pipeline to identify genes that have stable expression across a wide range of Arabidopsis tissues at different developmental stages and have identified a number of promoters that are well expressed in both transient (Nicotiana benthamiana) and stable (Arabidopsis) transformation assays. We have also introduced two genome-orthogonal gRNA target sites in a subset of the screened promoters, converting them into NOR logic gates. The work here establishes a pipeline to screen for additional constitutive promoters and can form the basis of constructing more complex information processing circuits in the future. [ABSTRACT FROM AUTHOR]

To support the increasingly complex circuits needed for plant synthetic biology applications, additional constitutive promoters are essential. Reusing promoter parts can lead to difficulty in cloning, increased heterogeneity between transformants, transgene silencing and trait instability. We have developed a pipeline to identify genes that have stable expression across a wide range of Arabidopsis tissues at different developmental stages and have identified a number of promoters that are well expressed in both transient (Nicotiana benthamiana) and stable (Arabidopsis) transformation assays. We have also introduced two genome-orthogonal gRNA target sites in a subset of the screened promoters, converting them into NOR logic gates. The work here establishes a pipeline to screen for additional constitutive promoters and can form the basis of constructing more complex information processing circuits in the future.

Groundwater resources in arid and semi-arid environments are of limited availability and variable quality, impacting hence their agricultural development. In this work, an attempt to provide a groundwater management context focusing on irrigation groundwater sustainability and surveys was conducted in Kebili's complex terminal aquifer. The analytical physicochemical data and several hazard groups of irrigation water quality that have negative impacts on the soil quality and cropping performance were evaluated and then processed with the spatial multi-criteria decision analysis (MCDA) models, Hierarchical Classification, and simulations graphics. The evaluation of the hydrochemical characteristics indicated that the increase of groundwater mineralization is governed by the processes of evaporation and the reverse ion exchange effect throughout the water–rock interactions. The final irrigation water quality index (IWQI) maps, obtained from the GIS-based on weighted overlay index (WOvI), analytical hierarchy process (AHP) and Boolean logic (BL) models, produce different findings in both mapping and percentages of the qualitative classes. Indeed, it reveals three classes of suitability (high, medium, and low) with WOvI and AHP. Whereas, Boolean Logic model shows four classes (good, permissible, doubtful, and unsuitable). Additionally, the spatial distribution of the cluster C2 obtained from the hierarchical cluster analysis (HCA) characterized by high levels in all chemical elements globally coincides with the unsuitable areas for irrigation purposes. Moreover, the validation using the receiver operating characteristic (ROC) curve analysis shows an area under the ROC curve value of 81.6% for BL, which is very close to AHP model (81.1%), and both of these are more accurate than WOvI model (AUC = 79.8%). This approves the prediction accuracy of the Boolean integration data processing in assessing and modeling suitability of irrigation water in the study area. In this regard, obtained results may be considered as an appropriate tool for agricultural planning as well as to guide decision‐makers to choose areas where irrigation can be suitable without damaging both soil and water quality. [ABSTRACT FROM AUTHOR]

The potential groundwater zones of the Maputaland coastal plain of Kwazulu-Natal is identified by comparing the analytic hierarchy process (AHP)—multi-criteria decision making (MCDM) technique and Boolean logical approach. The map of groundwater potential zones was prepared by assimilating the eight thematic layers, i.e., geology, geomorphology, lineament density, soils, slope, rainfall, and land use. Each thematic layer was assigned with a subjective relative weight under AHP-MCDM technique and Boolean logic and was overlaid in a GIS platform to identify the groundwater potential zones. The groundwater potential zones were delineated under two different GIS techniques to obtain confident results. Weights of thematic layers were allocated using AHP normalized Eigen vector methodology and weighted linear combination method was employed to find the groundwater potential index. Whereas in a Boolean approach, AND operator was applied to integrate thematic layers to delineate the groundwater potential zones. The delineated groundwater potential maps using AHP-MCDM technique indicates that 6.0% (310.5 km2) from total area falls under very good; 67% (3467 km2) good; 25% (1294 km2) poor and 2% (103.5 km2) under very poor, whereas in Boolean logic about 70% of the area (i.e., 3623 km2) constitutes good and 30% (1552 km2) of the areas constitutes poor groundwater potential zone. Further, the obtained results indicate that the geology, geomorphology, land use and land cover and slope played a vital role in groundwater recharge. This pioneer study in Maputaland coastal plain explores the baseline data of the potential groundwater zones. The results emanating from this study can be used in further understanding of the available groundwater resources and can be helpful in future to find suitable groundwater exploration sites in the area. [ABSTRACT FROM AUTHOR]

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.

Forest planning is a necessary requirement for long-term, economically efficient and environmentally responsible forest management and use. Iran has 12 million ha of forest cover, with 5 million ha in the mountainous Zagros area. Many of the improper uses in these forests, so far removed from the past, have resulted in significant degradation. The purpose of this paper is to check and compare the prepared methods, including the Iranian Ecological Model (with seven classes using Boolean logic), its revised method (with four classes using Boolean logic and four classes using geometric mean evaluation, as well) and a new model for ecological capability evaluation for better planning management for commercial and conservational forestry in Jahrom County located in Fars Province, Iran. In this study, we assessed the potential for conservational forestry in two ways: first, by adjusting the quantitative evaluation threshold of the model's primary topographic criterion, and then, by removing this criterion altogether. It is worth noting that the necessary information, including climatic, topographic, soil and other types, was compiled by national and local organisations in Iran for the research. The improved Boolean technique (with kappa = 0. 5 3) outperformed the Iranian Ecological Model (with kappa = 0. 0 6), while the revised method using geometric mean assessment and calibration (with kappa = 0. 6 5) outperformed the other methods tested. Furthermore, when all of the forestry capacity maps were compared, conservational forestry map demonstrated a higher capability after removing the topographic criterion in the region (with kappa = 0. 9 0 for calibration technique), indicating conservational forestry's potential in Jahrom County. Overall, because of its simplicity and excellent precision, this study may be utilised as a fundamental framework to evaluate ecological capability for other locations with similar conditions, and this model can help users and administrations undertake executive initiatives. [ABSTRACT FROM AUTHOR]

The intersection of mathematical cognition, metacognition, and advanced technologies presents a frontier with profound implications for human learning and artificial intelligence. This paper traces the historical roots of these concepts from the Pythagoreans and Aristotle to modern cognitive science and explores their relevance to contemporary technological applications. We examine how the Pythagoreans' view of mathematics as fundamental to understanding the universe and Aristotle's contributions to logic and categorization have shaped our current understanding of mathematical cognition and metacognition. The paper investigates the role of Boolean logic in computational processes and its relationship to human logical reasoning, as well as the significance of Bayesian inference and fuzzy logic in modelling uncertainty in human cognition and decision-making. We also explore the emerging field of Chemical Artificial Intelligence and its potential applications. We argue for unifying mathematical metacognition with advanced technologies, including artificial intelligence and robotics, while identifying the multifaceted benefits and challenges of such unification. The present paper examines essential research directions for integrating cognitive sciences and advanced technologies, discussing applications in education, healthcare, and business management. We provide suggestions for developing cognitive robots using specific cognitive tasks and explore the ethical implications of these advancements. Our analysis underscores the need for interdisciplinary collaboration to realize the full potential of this integration while mitigating potential risks. [ABSTRACT FROM AUTHOR]

Controlling and managing of seasonal and sudden floods in arid and semi-arid regions, especially in areas where surface water is out of reach is necessary. Flood spreading is one of the best ways to control surface runoff and recharge groundwater resources. In the present study, the appropriate sites for flood spreading project in border area of Taybad county in Khorasan Razavi province is selected using Boolean logic .For prioritization the suitable locations, TOPSIS and VIKOR multi-criteria decision making methods were used. Firstly, using Boolean logic inappropriate areas based were removed on criteria (slopes greater than 8%, urban area, agriculture and covered pediment). Then, 11 zones were selected as the suitable areas of using TOPSIS and VIKOR models based on the criteria of slope, groundwater quality, geology, alluvium thickness, transmission capability, drainage density, surface permeability, groundwater loss, distance from the village, distance from wells and land use.. Results showed that most suitable areas are located in alluvial fans. Based on the TOPSIS model, location J with value of 0.75 was selected as the best site, and using the VIKOR model, location K with a value of 0.96 was selected as the best location for flood spreading projects.

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]

Biomolecular materials offer tremendous potential for the development of memristive devices due to their low cost of production, environmental friendliness, and, most notably, biocompatibility. Herein, biocompatible memristive devices based on amyloid–gold nanoparticle hybrids have been investigated. These memristors demonstrate excellent electrical performance, featuring an ultrahigh Roff/Ron ratio (>107), a low switching voltage (

Bit manipulation plays a significant role in high-speed digital signal processing (DSP) and data computing systems, and shift and rotation operations are crucial functions in it. In general, barrel shifters are used to perform these operations effectively. Nano magnetic logic circuits are among the promising beyond-CMOS alternative technologies for the design of high-speed circuits. Most of the existing circuits that have been developed using nano magnets are combinational circuits. In this work, a barrel shifter is implemented and realised using in-plane nano magnetic logic. The proposed design is the first of its kind nano magnetic logic circuit. The nano magnetic logic circuit implementation, layout generation, simulation, and validation were performed using the ToPoliNano and ModelSim tools. The logical equivalent design was synthesised and evaluated using the Synopsys Design Compiler tool. The proposed barrel shifter was realised using majority logic has 1769037 nano magnets with a boxing area of 481 × 13104 µm2 and 3276 clock zones after optimisation with the Barycenter algorithm. The proposed barrel shifter realised using Boolean logic has 315276 nano magnets with a boxing area of 265 × 5028 µm2 and 1257 clock zones after optimisation with the Barycenter algorithm. The proposed design results demonstrate that complex systems can be developed using nano magnetic logic by combining combinational and sequential circuits. [ABSTRACT FROM AUTHOR]

Background and purpose: In recent years, the rapid growth of cities has been led to an increase in the production of various types of solid wastes in urban areas. Although landfilling is the last step in municipal solid waste management, but it is one of the common methods in developing countries’ municipal solid waste management. The purpose of this study is to accurately locate urban landfills in Naien county by using a combination of fuzzy and boolean methods. Materials and methods: In this study, AHP model was used to standardize and determine the weight of criteria and sub-criteria. The innovation of this research is the combination of the results of fuzzy and boolean logic. The fuzzy method consists of two groups, the first group is calculation the weight of criteria and the other one by calculating the weight of sub-criteria, and the results of boolean logic with five classes including calculation the weight of criteria and sub-criteria. Results: The results of this study show that the mentioned fuzzy and boolean methods have identified 34, 48779, 16000 and 7630 hectares of areas in Nain county as the most suitable areas for creating urban landfills. According to the weight of methods, a single map with four main patches is resulted by combination of these four methods, which includes a total of 5055 hectares in Nain. Conclusion: The results of this study show that the combination of fuzzy and boolean logic results provides better areas for landfill than using the methods individually.

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.

The advent of modern single-cell biology has revealed the striking molecular diversity of cell populations once thought to be more homogeneous. This newly appreciated complexity has made intersectional genetic approaches essential to understanding and probing cellular heterogeneity at the functional level. Here, we build on previous knowledge to develop a simple adeno-associated virus (AAV)-based approach to define specific subpopulations of cells by Boolean exclusion logic (AND NOT). This expression by Boolean exclusion (ExBoX) system encodes for a gene of interest that is turned on by a particular recombinase (Cre or FlpO) and turned off by another. ExBoX allows for the specific transcription of a gene of interest in cells expressing only the activating recombinase, but not in cells expressing both. We show the ability of the ExBoX system to tightly regulate expression of fluorescent reporters in vitro and in vivo, and further demonstrate the adaptability of the system by achieving expression of a variety of virally delivered coding sequences in the mouse brain. This simple strategy will expand the molecular toolkit available for cell- and time-specific gene expression in a variety of systems. [ABSTRACT FROM AUTHOR]