Computational Logic Research Articles

Selection of Knitted Fabrics Using a Hybrid BBWM-PFTOPSIS Method

ABSTRACT Selecting the best knitted fabric with various comfort properties is considered a complicated multi-criteria decision-making (MCDM) issue that involves ambiguity and vagueness. In such scenarios, Pythagorean fuzzy sets (PFSs) provide an effective tool for addressing uncertainty and ambiguity in MCDM problems that contain human subjective evaluations and judgments. First, this research identifies the factors affecting the comfort of knitted fabrics as the evaluation criteria. Second, the Bayesian best-worst method (BBWM) is preferred for less pairwise comparisons and obtains highly reliable results with a probabilistic perspective for determining the criteria weights. Furthermore, due to its logical computation approach and ease of operation, the technique for order preference by similarity to ideal solution (TOPSIS) is commonly utilized for addressing MCDM problems. Therefore, this research proposes an innovative MCDM framework that combines the BBWM technique with Pythagorean fuzzy TOPSIS (PFTOPSIS). The BBWM determines the criteria weights, and the weighted sine similarity-based PFTOPSIS is utilized to rank alternatives. The proposed BBWM-PFTOPSIS approach was employed to solve a real-world case. Moreover, this article conducts a sensitivity analysis and three comparative analyses to reveal the efficiency and reliability of the BBWM-PFTOPSIS approach. The ranking results establish the viability and effectiveness of BBWM-PFTOPSIS.

Investigations on boiling heat transfer characteristics in non-uniform heating U-Tube bundles under rolling motion

The development of the marine environment necessitates more rapid development of marine nuclear power plants, and the U-tube bundle heat exchangers, which exist in marine nuclear power plants, play a significant role in safety and economy. However, the radial non-uniform heating (NUH) brought on by the specific structure of the U-tube complicates the boiling heat transfer characteristics. Additionally, the environment of ocean rolling motion superimposed with NUH makes heat transfer more complex. The paper analyzes the time-averaged and transient heat transfer performance by contrasting the rolling UH experiments and rolling NUH experiments. The result demonstrates that the addition of NUH causes no impact on the influenced degree of rolling motion on the time-averaged temperature characteristics, which means a weakly coupled action of NUH and rolling motion. Based on the independence principle, considering the influencing factor of rolling motion and NUH, the developed correlation for calculating time-averaged heat transfer coefficient (HTC) can capture 96.67% of the experimental data within 15% of the error line, and the average absolute error is about 5.75%. For instantaneous fluctuated characteristics, the addition of NUH has a greater impact on the fluctuated range of water temperature than that of the wall temperature, and the fluctuation introduced by rolling motion is displayed based on the effect of NUH. Besides, the calculating method for determining the HTC fluctuation amplitude under uniform heating and rolling motion conditions also applies to situations in which NUH and rolling motion coexist, and the mean absolute error is around 13.80%, indicating that the coupled action of NUH and rolling motion is less obvious in forced circulation. The fluctuation amplitude of HTC depends more on the thermal parameters and rolling parameters. Finally, a novel computational logic approach was created and proposed to estimate transient HTC under conditions for NUH and rolling motion, which can anticipate the fluctuated amplitude and period of instantaneous HTC under corresponding conditions.

Performing photonic nonlinear computations by linear operations in a high-dimensional space

Abstract As photonic linear computations are diverse and easy to realize while photonic nonlinear computations are relatively limited and difficult, we propose a novel way to perform photonic nonlinear computations by linear operations in a high-dimensional space, which can achieve many nonlinear functions different from existing optical methods. As a practical application, the arbitrary binary nonlinear computations between two Boolean signals are demonstrated to implement a programmable logic array. In the experiment, by programming the high-dimensional photonic matrix multiplier, we execute fourteen different logic operations with only one fixed nonlinear operation. Then the combined logic functions of half-adder and comparator are demonstrated at 10 Gbit/s. Compared with current methods, the proposed scheme simplifies the devices and the nonlinear operations for programmable logic computing. More importantly, nonlinear realization assisted by space transformation offers a new solution for optical digital computing and enriches the diversity of photonic nonlinear computing.

Vineyard: Optimizing Data Sharing in Data-Intensive Analytics

Modern data analytics and AI jobs become increasingly complex and involve multiple tasks performed on specialized systems. Sharing of intermediate data between different systems is often a significant bottleneck in such jobs. When the intermediate data is large, it is mostly exchanged through files in standard formats (e.g., CSV and ORC), causing high I/O and (de)serialization overheads. To solve these problems, we develop Vineyard, a high-performance, extensible, and cloud-native object store, trying to provide an intuitive experience for users to share data across systems in complex real-life workflows. Since different systems usually work on data structures (e.g., dataframes, graphs, hashmaps) with similar interfaces, and their computation logic is often loosely-coupled with how such interfaces are implemented over specific memory layouts, it enables Vineyard to conduct data sharing efficiently at a high level via memory mapping and method sharing. Vineyard provides an IDL named VCDL to facilitate users to register their own intermediate data types into Vineyard such that objects of the registered types can then be efficiently shared across systems in a polyglot workflow. As a cloud-native system, Vineyard is designed to work closely with Kubernetes, as well as achieve fault-tolerance and high performance in production environments. Evaluations on real-life datasets and data analytics jobs show that the above optimizations of Vineyard can significantly improve the end-to-end performance of data analytics jobs, by reducing their data-sharing time up to 68.4x.

MITra: A Framework for Multi-Instance Graph Traversal

This paper presents MITra, a framework for composing multi-instance graph algorithms that traverse from multiple source vertices simultaneously over a single thread. Underlying MITra is a model of multi-instance traversal that uniformly captures traversal sharing across instances. Based on this, MITra provides a programming model that allows users to express traversals by declaring vertex ranks and specify computation logic via an edge function. It synthesizes multi-instance traversal algorithms from declared vertex ranks and edge functions adopted from classic single-instance algorithms, automatically sharing computation across instances and benefiting from SIMD. We show that MITra can generate multi-instance algorithms provably better than existing ones, while being more expressive than traditional frameworks. In addition to the ease of programming, we experimentally verify that MITra is on average an order of magnitude faster than approaches based on existing frameworks for common graph algorithms, and is comparable to the state-of-the-art highly optimized one-off algorithms.

Electronic phenotyping of community-acquired pneumonia: A tool for inpatient syndrome-specific antimicrobial stewardship

Background: Using patient data from the electronic health record (EHR) and computer logic, an “electronic phenotype” can be created to identify patients with community-acquired pneumonia (CAP) in real time to assist with syndrome-specific antimicrobial stewardship efforts.1 We adapted and validated the performance of an inpatient CAP electronic phenotype for antimicrobial stewardship interventions. Methods: An automated scoring system was created within the EHR (Epic Systems) to identify hospitalized patients with CAP based on the variables and logic listed in Fig. 1B. We adapted a score used by the Michigan Hospital Medicine Safety Consortium (HMS) to identify patients with CAP, with additions made to improve sensitivity (Fig. 1).1 The score can be displayed in a column within the EHR patient list (Fig. 2). We validated the electronic phenotype via chart review of all hospitalized patients on systemic antimicrobials admitted to a medicine team consecutively between November 8 and 18, 2021. Patients who were readmitted within the validation time frame were excluded. We assessed the performance of the electronic phenotype by comparing the score to manual chart review, where “CAP diagnosis” was defined as (1) mention of “pneumonia” or “CAP” as part of the differential diagnosis in the admission documentation, (2) antimicrobials were started within 48 hours of admission, and (3) radiographic findings were suggestive of pneumonia. After initial evaluation, the scoring system was adjusted, and performance was re-evaluated during prospective audit and feedback performed on EHR CAP–positive patients over 13 days between July 2022 and December 2022. Results: We included 191 patients in our initial validation cohort. The CAP score had high sensitivity (95.83%), specificity (92.2%), and negative predictive value (99.35%), though lower positive predictive value (63.89%) was noted (Table 2). The rules were further refined to include bloodstream infection only with Haemophilus influenza or Streptococcus pneumoniae in rule 2B, and azithromycin was removed from “CAP antibiotics.” After these changes, repeated evaluation of 88 patients with positive CAP EHR score was performed, and only 20 (23%) were considered false-positive results. Conclusions: Electronic phenotypes can be used to create automated tools to identify patients with CAP with reasonable performance. Data from this tool can be used to guide more focused antimicrobial stewardship interventions and clinical decision support in the future. Reference: Vaughn VM, et al. A statewide collaborative quality initiative to improve antibiotic duration and outcomes in patients hospitalized with uncomplicated community-acquired pneumonia. Clin Infect Dis 2022;75:460–467.Disclosures: None

Isolation of PD-L1 Extracellular Vesicle Subpopulations Using DNA Computation Mediated Microfluidic Tandem Separation.

Accurate isolation of targeted extracellular vesicle (EV) is challenging due to the antigenic heterogeneity of EV subpopulations which are from different cell origins. Most EV subpopulations lack a single marker whose expression cleanly distinguishes them from mixed populations of closely related EVs. Here, a modular platform capable of taking multiple binding events as input, performing logic computations, and producing two independent outputs for tandem microchips for EV subpopulation isolation, is developed. Taking advantages of the excellent selectivity of dual-aptamer recognition and the sensitivity of tandem microchips, this method achieves, for the first time, sequential isolation of tumor PD-L1 EVs and non-tumor PD-L1 EVs. As a result, the developed platform can not only effectively distinguish cancer patients from healthy donors but also provides new clues for assessing immune heterogeneity. Moreover, the captured EVs can be released through a DNA hydrolysis reaction with high efficiency, which is compatible with downstream mass spectrometry for EV proteome profiling. Overall, this strategy is expected to isolate different EV subpopulations, translate EVs into reliable clinical biomarkers, and accurately investigate the biological functions of different EV subsets.

Triplex-structure based DNA circuits with ultra-low leakage and high signal-to-noise ratio

DNA circuits are powerful tools in various applications such as logical computation, molecular diagnosis and synthetic biology. Leakage is a major problem in constructing complex DNA circuits. It directly affects the output signal and harms the circuit's performance significantly. In the traditional DNA circuits, the gate complex is a duplex structure. There are insufficient energy barriers to prevent spontaneous detachment of strands, resulting in a leak prone. Herein, we have developed triplex-structure based DNA circuit with ultra-low leakage and high signal-to-noise ratio (SNR). The triplex structure improves the stability in the absence of input. At the same time, the driving force of the strand displacement cascades reduces the influence of the triplex structure on the desired reaction. The SNR of the DNA circuit was increased to 695, while the desired reaction rate remained 90% of the conventional translator circuit. The triplex-structure mediated leakage prevention strategy was further tested at different temperatures and in DNA translator and seesaw circuits. We also constructed modular basic logic gates with a high efficiency and low leakage. On this basis, we further constructed triplex-structure based tertiary DNA logic circuits, and the SNR reached 295, which, to the best of our knowledge, was among the highest of the field. We believe that our scheme provides a novel, valid, and general tool for reducing leakages, and we anticipate that it will be widely adopted in DNA nanotechnology.

A DNA Nanodevice-Based Platform with Diverse Capabilities.

Social biotic colonies often perform intricate tasks by interindividual communication and cooperation. Inspired by these biotic behaviors, a DNA nanodevice community is proposed as a universal and scalable platform. The modular nanodevice as the infrastructure of platform contains a DNA origami triangular prism framework and a hairpin-swing arm machinery core. By coding and decoding a signal domain on the shuttled output strand in different nanodevices, an orthogonal inter-nanodevice communication network is established to connect multi-nanodevices into a functional platform. The nanodevice platform enables implementation of diverse tasks, including signal cascading and feedback, molecular input recording, distributed logic computing, and modeling of simulation for virus transmission. The nanodevice platform with powerful compatibility and programmability presents an elegant example of the combination of the distributed operation of multiple devices and the complicated interdevice communication network, and may become a new generation of intelligent DNA nanosystems.

Enabling Logic Computation Between Ta/CoFeB/MgO Nanomagnets

Dipolar coupled magnets proved to have the potential to be capable of successfully performing digital computation in a highly parallel way. For that, nanomagnet-based computation requires precise control of the domain wall nucleation from a well-localized region of the magnet. Co/Pt and Co/Ni multilayer stacks were successfully used to demonstrate a variety of computing devices. However, Ta/CoFeB/MgO appears more promising thanks to the lower switching field required to achieve a full magnetization reversal, reduced thickness (less than 10 nm), and its compatibility with magnetic tunnel junctions. In this work, the switch of the information is achieved through the application of a magnetic field, which allows to scale more the nanomagnets with respect to current-driven magnetization reversal-based devices and to go towards 3D structures. We experimentally demonstrate that Ga <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">+</sup> ions can be used to tune the energy landscape of the structured magnets to provide signal directionality and achieve a distinct logic computation. We prove that it is possible to define the artificial nucleation center in different structures with two irradiation steps and that this approach can enable logic computation in ultra-thin films by dipolar interaction. Moreover, different from previous studies, the results coming from the irradiation analysis are then used for real logic devices. We present the experimental demonstration of a set of fully working planar inverters, showing that it is possible to reach a coupling field between input and output, which is strong enough to reliably implement logic operations. Micromagnetic simulations are used to study the nucleation center’s effectiveness with respect to its position in the magnet and to support the experiments. Our results open the path to the development of more efficient nanomagnet-based logic circuits.

A Reliable and High-Speed 6T Compute-SRAM Design With Dual-Split-V DD Assist and Bitline Leakage Compensation

Compute SRAM (CSRAM) can be configured to execute efficient in-memory logic computation and search operations, which is made possible by the multirow activation scheme. Nevertheless, simultaneous multirow activation introduces notorious compute access disturbance in 6T-based CSRAM designs. Existing solutions aim to mitigate the disturbance issue via weakening the access transistor strength, clamping the sensed bitline voltage swing, or substituting with read-decoupled SRAM bitcell designs. However, these techniques all come with significant design overheads of performance degradation in computational read and write accesses and increased layout area. This article presents multiple circuit-level techniques for the design and optimization of a reliable and high-speed 6T-based CSRAM. First, we propose a novel dual-split- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$V_{\text{DD}}$</tex-math> </inline-formula> (DSV)-assisted scheme for mitigating the compute access disturbance in 6T SRAM and simultaneously improving the computational read access performance. Second, we propose a leakage-compensated asymmetrical differential sense amplifier (LCAD-SA) to further improve the compute access performance. Third, we propose a DSV-assisted columnwise write scheme for accelerating the write performance. The proposed 6T CSRAM was implemented in the 28-nm CMOS, achieving a 1.18-GHz peak operating frequency, which is a 2.36 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times$</tex-math> </inline-formula> throughput improvement compared with that of the state-of-the-art CSRAM designs.

Designing with Iontronic Logic Gates─From a Single Polyelectrolyte Diode to an Integrated Ionic Circuit.

This article presents the implementation of on-chip iontronic circuits via small-scale integration of multiple ionic logic gates made of bipolar polyelectrolyte diodes. These ionic circuits are analogous to solid-state electronic circuits, with ions as the charge carriers instead of electrons/holes. We experimentally characterize the responses of a single fluidic diode made of a junction of oppositely charged polyelectrolytes (i.e., anion and cation exchange membranes), with a similar underlying mechanism as a solid-state p- and n-type junction. This served to carry out predesigned logical computations in various architectures by integrating multiple diode-based logic gates, where the electrical signal between the integrated gates was transmitted entirely through ions. The findings shed light on the limitations affecting the number of logic gates that can be integrated, the degradation of the electrical signal, their transient response, and the design rules that can improve the performance of iontronic circuits.

Sequential-Dependent Synthesis of Bimetallic Silver-Chromium Nanoparticles for Multichannel Sensing, Logic Computing, and 3 in 1 Information Protection.

Bimetallic nanomaterials (BNMs) have been used in sensing, biomedicine, and environmental remediation, but their multipurpose and comprehensive applications in molecular logic computing and information security protection have received little attention. Herein, This synthesis method is achieved by sequentially adding reactants under ice bath conditions. Interestingly, Ag-Cr NPs can dynamically selectively sense anions and reductants in multiple channels. Especially, ClO- can be quantitatively detected by oxidizing Ag-Cr NPs with detection limits of 98.37nM (at 270nm) and 31.83nM (at 394nm). Based on sequential-dependent synthesis process of Ag-Cr NPs, Boolean logic gates and customizable molecular keypad locks are constructed by setting the reactants as the inputs, the states of the resulting solutions as the outputs. Furthermore, dynamically selective response patterns of the Ag-Cr NPs can be converted into binary strings to exploit molecular crypto-steganography to encode, store, and hide information. By integrating the three dimensions of authorization, encryption, and steganography, 3 in 1 advanced information protection based on Ag-Cr nanosensing system can be achieved, which can enhance the anti-cracking ability of information. This research will promote the development and application of nanocomposites in the field of information security and deepen the connection between molecular sensing and the information world.

Carrier Modulation in 2D Transistors by Inserting Interfacial Dielectric Layer for Area-Efficient Computation.

2D materials with atomic thickness display strong gate controllability and emerge as promising materials to build area-efficient electronic circuits. However, achieving the effective and nondestructive modulation of carrier density/type in 2D materials is still challenging because the introduction of dopants will greatly degrade the carrier transport via Coulomb scattering. Here, a strategy to control the polarity of tungsten diselenide (WSe2 ) field-effect transistors (FETs) via introducing hexagonal boron nitride (h-BN) as the interfacial dielectric layer is devised. By modulating the h-BN thickness, the carrier type of WSe2 FETs has been switched from hole to electron. The ultrathin body of WSe2 , combined with the effective polarity control, together contribute to the versatile single-transistor logic gates, including NOR, AND, and XNOR gates, and the operation of only two transistors as a half adder in logic circuits. Compared with the use of 12 transistors based on static Si CMOS technology, the transistor number of the half adder is reduced by 83.3%. Theunique carrier modulation approach has general applicability toward 2D logic gates and circuits for the improvement of area efficiency in logic computation.

Divergences on monads for relational program logics

AbstractSeveral relational program logics have been introduced for integrating reasoning about relational properties of programs and measurement of quantitative difference between computational effects. Toward a general framework for such logics, in this paper, we formalize the concept of quantitative difference between computational effects as divergences on monads, then develop a relational program logic called approximate computational relational logic (acRL for short). It supports generic computational effects and divergences on them. The semantics of the acRL is given by graded strong relational liftings constructed from divergences on monads. We derive two instantiations of the acRL: (1) for the verification of various kinds of differential privacy of higher-order functional probabilistic programs and (2) the other for measuring difference of distributions of cost between higher-order functional probabilistic programs with a cost counting operator.

Special issue for the 36th Italian Conference on Computational Logic (CILC 2021)

This volume contains a selection of the papers presented at the |$36^{\textrm {th}}$|Italian Conference on Computational Logic (CILC 2021), held on September |$7^{\textrm {th}}$|–|$9^{\textrm {th}}$|⁠, |$2021$| in Parma, Italy. The Italian Conference on Computational Logic is the annual conference organized by the Group of researchers and Users of Logic Programming (GULP, www.programmazionelogica.it). Since the first event of the series, which took place in Genoa in |$1986$|⁠, the annual GULP conference represents a major opportunity for researchers and practitioners interested in computational logic to meet and exchange ideas. Furthermore, over the years, the conference broadened its horizons from logic programming to include related topics, such as declarative programming, formal verification of systems, knowledge representation, deductive databases and a wide range of applications in the broader area of Artificial Intelligence. The annual GULP conference is a traditional event of the Italian community of researchers and practitioners interested in logic programming, but its scope has become more and more international over the years. Despite the very peculiar situation caused by the COVID-19 pandemic, the community significantly responded to the call, thus allowing the technical program of CILC |$2021$| to feature |$23$| presentations of high-quality papers, of which |$19$| were original papers. This volume of the Journal of Logic and Computation contains extended and revised versions of a selection of the papers presented at CILC |$2021$|⁠. As a result of an additional review process, during which each submission was reviewed by three referees, |$8$| papers were accepted to be included in this volume. Accepted contributions range from foundations and theoretical results to practical experiences, case studies and applications. They cover a wide range of relevant topics related to computational logic in the broad sense, including agents and multi-agent systems, logic programming, runtime verification and healthcare. In the following, the featured papers are briefly summarized.

Diagram Reasoning and Paraconsistent Thinking: Hieromonk Hierotheos, His Ancestry, and Legacy

"The article is dedicated to the use of logical diagrams in Byzantine Trinitarian theology. Logical diagrams are a kind of logical computation that is often considered to originate with Euler and Leibniz, but they were, in fact, used by Byzantine theologians since at least the ninth century. Nevertheless, logical diagrams were never so widely accepted as they began to be from the late thirteenth century to the early fifteenth century. The diagrams seem to have been introduced into Trinitarian theology by Eustratius of Nicaea (an authoritative philosopher who did not fare as well as a theologian) in his anti-Latin polemics dating to ca. 1112. From there, the use of diagrams was reclaimed in about the 1140s by the Latinophrone Nicetas “of Maroneia” and rejected in 1256 by the anti-Latin theologian Emperor Theodore II Laskaris. Nevertheless, beginning in the 1270s, their popularity and variability exploded. Eventually, triadological diagrams were “canonized” as the legacy of St. Hierotheos of Athens, the teacher of Dionysius the Areopagite, by Joseph Bryennios in the early fifteenth century. Even the “internal” opponent of Palamite theology, Theophanes of Nicaea, resorted to diagrams in defending his own triadology. The figure who rendered diagrams critical for the “Hesychast” theologians was, in the 1270s, hieromonk Hierotheos. He was able to express with diagrams the inconsistency of the mainstream Byzantine understanding of the Trinity. Nevertheless, his own name would come, in the fourteenth century, under a kind of damnatio memoriae, so that his main ideas circulated rather under the name of Hierotheos of Athens. This article argues that hieromonk Hierotheos passed from the Church of Patriarch Joseph to the Church of Patriarch Arsenius (or the Arsenites). Some of the highly authoritative teachers of the Palamites were in disagreement with the Great Church on the Arsenite issue, refusing to accept the act of 1410, where the Great Church had declared the Arsenites to be on the right side of the conflict. This fact could have affected the memory of hieromonk Hierotheos in the milieu where his works were most in demand. Keywords: Byzantine theology, Trinitarian theology, triadology, Eustratius of Nicaea, Nicetas “of Maroneia,” Nicephorus Blemmydes, Theodore II Laskaris, hieromonk Hierotheos, Theophanes of Nicaea, Joseph Bryennios, Arsenites, Arsenite movement, logical diagrams, Filioque "

Van der Waals Ferroelectric Semiconductor Field Effect Transistor for In-Memory Computing.

In-memory computing is a highly efficient approach for breaking the bottleneck of von Neumann architectures, i.e., reducing redundant latency and energy consumption during the data transfer between the physically separated memory and processing units. Herein we have designed a in-memory computing device, a van der Waals ferroelectric semiconductor (InSe) based metal-oxide-ferroelectric semiconductor field-effect transistor (MOfeS-FET). This MOfeS-FET integrates memory and logic functions in the same material, in which the out-of-plane (OOP) ferroelectric polarization in InSe is used for data storage and the semiconducting property is used for the logic computation. The MOfeS-FET shows a long retention time with high on/off ratios (>106), high program/erase (P/E) ratios (103), and stable cyclic endurance. Moreover, inverter, programmable NAND, and NOR Boolean logic operations with nonvolatile storage of the results have all been demonstrated using our approach. These findings highlight the potential of van der Waals ferroelectric semiconductor-based MOfeS-FETs in the in-memory computing and their potential of achieving size scaling beyond Moore's law.

Biogenic fluorescent carbon dots modulated fabrication of concatenate logic library and pattern-mediated molecular keypad lock for chemical sensing application

In recent years, molecular logic gates (MLGs) have gained much attention among researchers to replace conventional silicon-based electronic computers. MLGs are employed for various applications, including biological–chemical sensors, heavy metal ion detection, illness diagnosis, and therapy. In this work, we developed two different chemically functionalized forms of biogenic Carbon (C)-dots synthesized using F. religiose and applied as MLGs for multi-stimulus responsive computing. To mimic the operation of Boolean logic gates, we combined as-synthesized three different C-dot platforms (including bulk C-dots, thiol-functionalized (TC)-dots, and acid-functionalized (AC)-dots) with other analytes such as Fe3+, Hg2+, ascorbic acid (AA), glucose (Glu), dichlorvos (DV), and H2O2 and integrated to build a logic library that represents 15 fundamental logic gates (IMP, INH, NOT, NOR, YES, PASS0, and PASS1) and their combinational operations (IMP-OR, IMP-INH, INH-OR). Furthermore, we have developed a parity checker that distinguishes 0 to 9 natural integers as even or odd by using dual-source responsive C-dots and AC-dots platforms. Further, because of the lack of studies using C-dots in “On-Off-On” and “Off-On-Off” sensing to generate logic computation, we have developed a swiping pattern-mediated molecular keypad lock to promise the confidentiality, integrity, and availability of discrete information. A novel design idea for an advanced molecular keypad lock has been proposed based on the dynamic switching of C-dots photoluminescence emission (PLE) with 9 input keys and 6 input key combinations. The keypad lock can be potentially used in different fields, such as electronic gadgets, security systems, sensors, and therapeutics. This is an approach to replacing conventional silicon-based electronic systems with PLE-based nanoforms.

Applying Probabilistic Model Checking to the Behavior Guidance and Abnormality Detection for A-MCI Patients under Wireless Sensor Network

With the development of the Internet of Medical Things (IoMT) , indoor wireless sensor networks (WSNs) have been used to monitor Alzheimer's disease patients daily and guide their behaviors. Alzheimer's disease may seriously impact patients’ memory, and thoughts of “what should I do” can unexpectedly form in their mind. This cognitive impairment can affect patients’ independence and well-being. As a basic infrastructure for future healthcare systems, WSN can collect patient behaviors, such as their positions and states, to support safety and health analyses. Therefore, this paper proposes a probabilistic model checking-based method to predict patient behaviors and detect abnormal behaviors related to mild cognitive impairment to help patients rebuild their confidence and perception. First, the layout of the home environment is abstracted as a formal grid, and a user activity model (UAM) is proposed in the form of discrete-time Markov chain (DTMC) to describe patients’ activity based on data collected by sensors. Second, because Alzheimer's patients with mild cognitive impairment (A-MCI) often forget their next daily activities, we classify and describe their daily behaviors as verification requirements in the form of probabilistic computational tree logic (PCTL) . Then, the UAM is input into a probabilistic model checking tool and compared against the verification property PCTL to calculate the probability values and assess temporal behaviors. As result, the activity with the largest probability is selected for behavior guidance. Third, we demonstrate the process of detecting abnormalities, including activities with abnormal temporal behaviors and activities with normal temporal behaviors but unexpected probabilities that may be repeated more than twice. The key states are extracted from the UAM to specify the verification properties for abnormality detection. Finally, a case study is presented to demonstrate the usability and feasibility of our proposed method.