High Performance Research Articles

Modelling and fabrication of flexible strain sensor using the 3D printing technology

The use of additive manufacturing (AM) or 3D printing in sensor technology is increasing daily because it can fabricate complex structures quickly and accurately. This study presents the modeling, fabrication, and characterization processes for the development of a resistance type flexible strain sensor. The finite element model of the sensor was developed using COMSOL software and was verified experimentally. The experimental results agreed well with the simulation results. The fabrication process was performed using the molding technique. The flexible substrate of the strain sensor was fabricated by fused deposition modeling (FDM), an AM method, with dimensions of 20 mm × 60 mm and a thickness of 2 mm. In this process, a flexible and durable elastomer material called thermoplastic polyurethane (TPU) was used. The liquid conductive silver was then injected into the mold channels. The characterization process was performed by establishing experimental and numerical setups. Studies were conducted to maximize sensitivity by changing the geometric properties of the sensor. At the 30% strain level, sensitivity increased by 9% when the sensor thickness decreased from 2 to 1.2 mm. As a result of the gradually applied force, the strain sensor showed a maximum displacement of 34.95 mm. Tensile tests were also conducted to examine the effects of stress accumulation on the flexible base. The results of this study show that the strain sensor exhibits high linearity-sensitivity and low hysteresis performance.

High fault-tolerant performance of the divide-and-swap cube network

Two crucial metrics used to evaluate the fault tolerance of interconnection networks are connectivity and diagnosability. By improving the connectivity and diagnosability of the interconnection network, its fault tolerance can be enhanced. In this paper, we focus on determining the g-extra connectivity (0≤g≤10) of the divide-and-swap cube DSCn, as well as its diagnosability based on the pessimistic diagnosis strategy and g-extra precise diagnosis strategy, under the PMC and MM* models. The research analysis suggests that compared with some other connectivity and diagnosability of DSCn, such as classical connectivity, structure connectivity, super connectivity, and classical diagnosability, the extra connectivity/diagnosability and pessimistic diagnosability of DSCn enable it to have a higher fault tolerance. Moreover, we propose two O(Nlog2⁡N) effective diagnosis algorithms of DSCn: the g-extra diagnosis algorithm (EX-DiagnosisDSCn) and the pessimistic diagnosis algorithm (PE-DiagnosisDSCn), where the EX-DiagnosisDSCn algorithm can accurately diagnose the state of all processors in DSCn.

Research Progress in Starch-based Dye Adsorbents

Abstract: Starch is a typical environment-friendly biomass material and there are considerable quantities of reactive hydroxyl groups in the starch molecule chain. Modifications could introduce a large number of functional groups, which can bind some dyeing contaminants, thereby removing the dyes. According to the different modification methods, starch-based adsorbents can be divided into three categories that are aminated-modified starch, ionic-modified starch, and composite-modified starch. The preparation method, structure properties, and adsorption capacity of modified starch dye adsorbents have been reviewed in this article. It can be concluded that the adsorption property of adsorbents depends on different adsorption conditions and modification methods. The adsorption properties of the adsorbents have been found to be influenced by temperature, initial concentration of dyes, and pH value of solution. Amination modification can introduce amino or amine groups into the starch skeleton to enhance the chelation or electrostatic effect of the adsorbents on dyes. Ion modification can improve the ion exchange and electrostatic interaction between the adsorbents and the dye. Composite modification can improve specific surface area, pore size, adsorption site, and structural stability of the adsorbents. Future studies are required to focus on producing dye adsorbents with high adsorption performance, stable structure, recyclability, and degradability.

Lycium barbarum extract as an environmentally friendly corrosion inhibitor for AISI 52100 bearing steel in hydrochloric acid medium

This study reports the use of Lycium barbarum extract (LBE), a green and environmentally friendly additive, to inhibit the corrosion of AISI 52100 bearing steel in 1 M hydrochloric acid (HCl) solutions. Corrosion inhibition was experimentally investigated via the weight loss method and electrochemical analyses. The surface morphologies were evaluated by scanning electron microscopy (SEM), and the chemical compositions were analyzed via energy-dispersive X-ray spectroscopy (EDS) and Fourier transform infrared spectroscopy (FTIR). The experimental electrochemical and weight loss results demonstrated that LBE has excellent inhibitory properties, with the highest inhibition efficiencies of 92.68 % and 92.31 % when the concentration is 500 ppm, for steel immersed in HCl solutions. Surface coverage studies revealed that the data for the adsorption of LBE on steel were consistent with the Langmuir isotherm. The initial process was investigated via polarization analysis, and the LBE adsorption process was found to be a hybrid of physical and chemical adsorption. To investigate the effectiveness of LBE in preventing corrosion, the corrosion inhibition mechanism was analyzed via a wettability study, high performance liquid chromatography (HPLC) measurements and theoretical quantum chemical calculations. The results indicated that Ara, Rha, Man and Glu played significant effect on the protection of bearing steel in 1 M HCl solution.

Isolation of ovatoxin-a from ostreopsis cf. ovata cultures. A key step for hazard characterization and risk management of ovatoxins

Ostreopsis cf. ovata, a benthic/epiphytic marine dinoflagellate, is currently spreading in tropical, sub-tropical and temperate areas, causing periodic Harmful Algal Blooms (HABs). It produces a wide array of palytoxin-like compounds named ovatoxins (OVTXs), with OVTX-a generally the most abundant congener. Despite numerous cases of human poisonings and environmental damage associated with the presence of OVTXs and O. cf. ovata proliferations, a complete characterization of the toxicity of this class of molecules cannot be performed until Reference Material (RM) for individual congeners is available. This, in turn, requires the availability of sufficient amounts of toxin at a high purity grade. To achieve this goal, herein an analytical re-evaluation of critical-steps of OVTX-a isolation from O. cf. ovata cell pellets is reported. The overall procedure consists of four steps, namely an extraction, a Medium Pressure Liquid Chromatography (MPLC) separation, and two preparative High Performance Liquid Chromatography (HPLC) steps. Particular attention was paid to the extraction step to evaluate the repeatability in OVTX-a yields. For subsequent steps, loading sample preparation and chromatographic conditions were refined. As a result, a significant increase in recovery yields (from 12.5 to 20 ± 3%) and in purity grade (from 51% to 94%) of the isolated OVTX-a was achieved in comparison to previous studies. The improved procedure can easily be applied to isolate sufficient quantities of a good candidate RM for OVTX-a.

High performance rapid single-flux-quantum bit-slice arithmetic logic unit

Two optimization technologies, namely, bypass and carry-control optimization, were demonstrated for enhancing the performance of a bit-slice Arithmetic Logic Unit (ALU) in 2n-bit Rapid Single-Flux-Quantum (RSFQ) microprocessors. These technologies can not only shorten the calculation time but also solve data hazards. Among them, the proposed bypass technology is applicable to any 2n-bit ALU, whether it is bit-serial, bit-slice or bit-parallel. The high performance bit-slice ALU was implemented using the 6 kA/cm2 Nb/AlOx/Nb junction fabrication process from Superconducting Electronics Facility of Shanghai Institute of Microsystem and Information Technology. It consists of 1693 Josephson junctions with an area of 2.46 × 0.81 mm2. All ALU operations of the MIPS32 instruction set are implemented, including two extended instructions, i.e., addition with carry (ADDC) and subtraction with borrow (SUBB). All the ALU operations were successfully obtained in SFQ testing based on OCTOPUX and the measured DC bias current margin can reach 86% - 104%. The ALU achieves a 100% utilization rate, regardless of carry/borrow read-after-write correlations between instructions.

Realizing enhanced photoresponse for self-powered broadband photodetector with asymmetric contacts based MoTe2/WSe2 van der Waals heterostructure

Self-powered photodetectors constructed by two-dimensional (2D) materials are significant in advanced science and technology with the growing focus on green and energy-efficient solutions. The built-in electric field in photodetector drives efficient separation and transfer of photogenerated electron–hole pairs. However, traditional metal-2D material-metal structures have more interface defects and larger Schottky barrier to hinder carrier transport. In this work, an asymmetric electrode material structure is constructed by adding graphene to provide a more efficient transport channel for photogenerated carriers. Graphene electrodes can play a variety of roles in efficient separation and collection of photogenerated carriers, reducing the barrier and improving the contact quality. Compared with the device using symmetric gold electrodes, the device prepared with asymmetric contacts show optimized performance. The MoTe2/WSe2 heterostructure exhibits brilliant self-powered photoresponse (a responsivity of 268 mA/W and a detectivity of 7.48*1011 Jones). And the rise/decay times are up to 145μs/125μs. Additionally, the detector has a broadband detection capability from visible light to near-infrared. These results provide a promising and simple way to fabricate a MoTe2/WSe2 self-powered broadband photodetector with high performance

An encryption algorithm for color images based on an improved dual-chaotic system combined with DNA encoding

This study improves the Logistic chaotic system and combines it with the hyperchaotic Chen system to create a dual chaotic system. The algorithm encrypts images in three stages. In the first stage, a plaintext-related key generation scheme is designed to generate the parameters and initial values of the dual chaotic system. In the second stage, the chaotic sequences generated by the dual chaotic system are used for dynamic DNA encoding and computation. In the third stage, the chaotic sequences generated by the improved Logistic chaotic system are used to perform row-column permutations, completing the scrambling. The security analysis of the encrypted images shows that the algorithm described in this paper is robust and secure, capable of resisting most known attacks. The algorithm is fast in encryption, provides high-quality image reconstruction, and is suitable for scenarios with high comprehensive performance and image quality requirements.

Enhanced Harmonic Partitioned Scheduling of Periodic Real-Time Tasks Based on Slack Analysis.

The adoption of multiprocessor platforms is growing commonplace in Internet of Things (IoT) applications to handle large volumes of sensor data while maintaining real-time performance at a reasonable cost and with low power consumption. Partitioned scheduling is a competitive approach to ensure the temporal constraints of real-time sensor data processing tasks on multiprocessor platforms. However, the problem of partitioning real-time sensor data processing tasks to individual processors is strongly NP-hard, making it crucial to develop efficient partitioning heuristics to achieve high real-time performance. This paper presents an enhanced harmonic partitioned multiprocessor scheduling method for periodic real-time sensor data processing tasks to improve system utilization over the state of the art. Specifically, we introduce a general harmonic index to effectively quantify the harmonicity of a periodic real-time task set. This index is derived by analyzing the variance between the worst-case slack time and the best-case slack time for the lowest-priority task in the task set. Leveraging this harmonic index, we propose two efficient partitioned scheduling methods to optimize the system utilization via strategically allocating the workload among processors by leveraging the task harmonic relationship. Experiments with randomly synthesized task sets demonstrate that our methods significantly surpass existing approaches in terms of schedulability.

Study of Haemoglobinopathies in Paediatric Age Group by High Performance Liquid Chromatography in a Tertiary Care Hospital in Gujarat

Study of Haemoglobinopathies in Paediatric Age Group by High Performance Liquid Chromatography in a Tertiary Care Hospital in Gujarat

A smart system for student performance assessment (SPA)

The proposed smart system for Student Performance Assessment (SPA) is a system that evaluates students' knowledge and skill attainment in a specific course by measuring their achievements of the Course Learning Outcomes (CLOs). The instructor defines the aspects, weights, and rating scale used by SPA to analyze each course. The system calculates the average of students' marks in each learning outcome and compares them with the CLO targets and scores to determine the effectiveness of the teaching and learning methods used. The system uses facts and rules extracted from the course syllabus and Bloom's Taxonomy to build its knowledge base. This paper presents the development of the SPA inference engine, which is used to find CLO targets based on the course level. The inference engine uses efficient procedures and a prediction process to determine the correct target and score, providing a reliable and understandable methodology for reasoning about the information in the knowledge base and formulating conclusions. SPA is a highly responsive and intelligent system that can be a valuable tool for measuring students' achievements. Its characteristics include high performance, reliability, and intelligibility, and its combination of cognitive systems and cognitive theory has led to remarkable progress in measuring student performance. Limitations include dependency on accurate course content and initial setup time, potential bias in CLO weight assignments, challenges in integrating SPA with existing institutional databases, the need for continuous updates to the knowledge base to reflect curriculum changes, and potential resistance from educators to adopt new technologies. Future improvements could involve adaptive learning integrations, enhanced user interfaces, and broader applicability across diverse educational settings.

Chemical growth of Niobium-doped vanadium pentoxide on aminated graphene for all-solid-state asymmetric supercapacitors

In this investigation, niobium-doped vanadium pentoxide (Nb–V2O5) was grown on the surface of amine-functionalized graphene nanosheets (NH2-Gr) using an in-situ hydrothermal method and explored the hybrid material as a positive electrode for the fabrication of an all-solid-state asymmetric supercapacitor (ASC). We have used KOH-loaded poly(acrylonitrile-co-1-vinylimidazole) (KOH/P(AN-Co-VIM)) gel as a solid electrolyte-cum-separator and exfoliated graphene (XGnP) as a negative electrode in the ASC. The morphological analysis of the Nb–V2O5/NH2-Gr hybrid revealed homogeneous growth of Nb–V2O5 on NH2-Gr nanosheets, while surface analysis confirmed a large fraction of mesopores with large surface areas in the hybrid. The hybrid electrode achieved a high specific capacitance of 1141.1 F/g at 1 A/g with 80.3% capacitance retention even after a 10-fold increase in current density, a significantly higher performance than a pure Nb–V2O5 electrode. As-assembled solid-state ASC device delivered a high energy density of 79.39 Wh kg−1 at a power density of 280.3 W kg−1, even though it retained high energy density at a higher power density of 12 kW kg−1. The ASC exhibited slow a self-discharge rate owing to the suppression of Ohmic leakage by the use of KOH/P(AN-co-VIM) gel electrolyte. Thus, the as-synthesized Nb–V2O5/NH2-Gr hybrid is an ideal alternative candidate for future supercapacitors.

A 5D super-extreme-multistability hyperchaotic map based on parallel-cascaded memristors

A new 5-dimensional discrete memristors-based hyperchaotic map (5DMHM) is constructed by introducing four charge-controlled discrete memristors (DMs, coupled through parallel-cascade mixing operation) into the sine map. This 5DMHM has 4-dimensional space fixed points and its stability distributions are partitioned in coupling strength, memristor initial condition, and parameter planes. The dynamics of the map are investigated by employing 2D dynamical behavior and the first Lyapunov exponent (LE) distribution. The super extreme multistability is discovered through the basin of attraction, the initial-value-dependent LE spectra, bifurcation diagrams, the mean value of state variables, and trajectory plots. Moreover, a high level of complexity can be observed by calculating the spectral entropy complexity for various parameter planes. Subsequently, a microcontroller-based digital circuit is designed to implement the 5DMHM. The security analysis of the pseudorandom number generator (PRNG) designed by the 5DMHM is presented and the PRNG passes the NIST SP800-22 test. The comparison of the 5DMHM with the recent maps indicates a higher performance in secure communication and image encryption.

Photocatalytic Reforming of Ethanol in the Liquid Phase Using a Ternary Composite of Rh/TiO2/g-C3N4 as a Catalyst.

Photocatalytic reforming of ethanol provides an effective way to produce hydrogen energy using natural and nontoxic ethanol as raw material. Developing highly efficient catalysts is central to this field. Although traditional semiconductor/metal heterostructures (e.g., Rh/TiO2) can result in relatively high catalyst performance by promoting the separation of photoinduced hot carriers, it will still be highly promising to further improve the catalytic performance via a cost-effective and convenient method. In this study, we developed a highly efficient photocatalyst for ethanol reformation by preparing a ternary composite structure of Rh/TiO2/g-C3N4. Hydrogen is the main product, and the reaction rate could reach up to 27.5 mmol g-1 h-1, which is ∼1.41-fold higher than that of Rh/TiO2. The catalytic performance here is highly dependent on the wavelength of the light illumination. Moreover, the photocatalytic reforming of ethanol and production of hydrogen were also dependent on the Rh loading and g-C3N4:TiO2 ratio in Rh/TiO2/g-C3N4 composites as well as the ethanol content in the reaction system. The mechanism of the enhanced hydrogen production in Rh/TiO2/g-C3N4 is determined as the improvement in the separation of photoinduced hot carriers. This work provides an effective photocatalyst for ethanol reforming, largely expanding its application in the field of renewable energy and interface science.

Metalo Hydrogen-Bonded Organic Frameworks Constructed by Coordinated Chains for Magnetic and Proton-Conductive Bifunctionality.

Metalo hydrogen-bonded organic frameworks (MHOFs) have received growing interest in designing crystalline functional materials. However, reports on bifunctional MHOFs showing magnetic and proton-conductive properties are extremely limited and their design is challenging. Herein, we investigated the magnetic and proton-conductive properties of two sulfonated CoHOF and MnHOF, {M(H2O)2(abs)2}n (M = Co2+ and Mn2+, Habs = 4-aminoazobenzene-4'-sulfonic anion), constructed by coordination chains. The supramolecular frameworks sustained by H bonds between -SO3- and coordinated water show directional ladder-type H bonds with hydrophilic nanochannels, leading to high proton conduction with exceptionally high conductivity around 10-2 S cm-1 at 100 °C under 97% relative humidity. In particular, the maximum σ value of CoHOF, 2.11 × 10-2 S cm-1, recorded the highest value among the reported proton-conducting materials showing slow magnetic relaxation. Meanwhile, the molecular structure of organosulfonate enables the magnetic isolation of high-spin Co2+ and Mn2+ centers in the frameworks. Magnetic measurements indicated that the MHOFs show field-induced single-ion magnet (SIM) properties, making these compounds rare magnetic-proton-conductive MHOFs. The work provides not only two unique MHOFs with SIM behavior and high proton conduction performance but also avenues for designing stable bifunctional MHOFs via a coordination chain approach.

Introducing nanodiamond-modified electrolyte to realize high capacity and rate performance of sodium ion batteries

The solid electrolyte interface (SEI) acts as a channel for sodium ions from electrolyte to anode, its structure and chemical properties are crucial to the Coulombic efficiency, cycling stability, and even safety of rechargeable batteries. In this work, using bio-carbon as an anode, and nanodiamond (ND) as electrolyte additive, the relation between ND and SEI properties and sodium storage performance is explored. It is found that ND is transferred to the surface of bio-carbon anode and induces the formation of stable and inorganic-rich SEI (such as NaF and Na2O). Besides, the introduction of ND significantly increases the ionic conductivity. The sodium-ion batteries with ND-electrolyte exhibit a superior reversible capacity of 340 mA g−1 after 400 cycles at 0.5 A g−1, long-term cycling stability (183 mA g−1 over 1000 cycles at 5 A g−1), and remarkable rate performance (157 mA h g−1 at 10 A g−1), which is attributed to the fact that the presence of ND could provide additional storage sites and improve the stability of SEI. This study provides valuable guidance for improving the electrochemical performance of electrode materials by regulating the SEI in the optimal electrolyte.

Prediction on the spatial distribution of the seropositive rate of schistosomiasis in Hunan Province, China: a machine learning model integrated with the Kriging method.

Schistosomiasis remains a formidable challenge to global public health. This study aims to predict the spatial distribution of schistosomiasis seropositive rates in Hunan Province, pinpointing high-risk transmission areas and advocating for tailored control measures in low-endemic regions. Six machine learning models and their corresponding hybrid machine learning-Kriging models were employed to predict the seropositive rate. The optimal model was selected through internal and external validations to simulate the spatial distribution of seropositive rates. Our results showed that the hybrid machine learning-Kriging model demonstrated superior predictive performance compared to basic machine learning model and the Cubist-Kriging model emerged as the most optimal model for this study. The predictive map revealed elevated seropositive rates around Dongting Lake and its waterways with significant clustering, notably in the central and northern regions of Yiyang City and the northeastern areas of Changde City. The model identified gross domestic product, annual average wind speed and the nearest distance from the river as the top three predictors of seropositive rates, with annual average daytime surface temperature contributing the least. In conclusion, our research has revealed that integrating the Kriging method significantly enhances the predictive performance of machine learning models. We developed a Cubist-Kriging model with high predictive performance to forecast the spatial distribution of schistosomiasis seropositive rates. These findings provide valuable guidance for the precise prevention and control of schistosomiasis.

УПРАВЛЕНИЕ КОМАНДОЙ ВНУТРИКОРПОРАТИВНОГО СТАРТАПА: ПРОЦЕССНОЕ ИССЛЕДОВАНИЕ ДИНАМИКИ РАЗВИТИЯ

Innovative development of the Russian economy is impossible without increasing the efficiency of small innovative enterprises (startups), including those created within companies. The problems of managing internal startups and especially startup teams have been relatively poorly studied by modern science. The high dynamics of startups causes high variability and intensive transformations in team management practices. To create a highper formance startup team, it is necessary to understand the internal logic of change in the parameters of teams and team management. The article studies the dynamics of changes in team characteristics and team management within the startup development process. The research methodology is based on process research and case studies. The work investigates the dynamics of the startup team a cloud gaming service. The startup was organized within one company but was then sold to a large IT corporation. The article examines certain characteristics of the team in their development including management methodologies, team composition, communications, culture, motivation, operational and strategic planning pro cedures.

Automated Association for Osteosynthesis Foundation and Orthopedic Trauma Association classification of pelvic fractures on pelvic radiographs using deep learning

High-energy impacts, like vehicle crashes or falls, can lead to pelvic ring injuries. Rapid diagnosis and treatment are crucial due to the risks of severe bleeding and organ damage. Pelvic radiography promptly assesses fracture extent and location, but struggles to diagnose bleeding. The AO/OTA classification system grades pelvic instability, but its complexity limits its use in emergency settings. This study develops and evaluates a deep learning algorithm to classify pelvic fractures on radiographs per the AO/OTA system. Pelvic radiographs of 773 patients with pelvic fractures and 167 patients without pelvic fractures were retrospectively analyzed at a single center. Pelvic fractures were classified into types A, B, and C using medical records categorized by an orthopedic surgeon according to the AO/OTA classification system. Accuracy, Dice Similarity Coefficient (DSC), and F1 score were measured to evaluate the diagnostic performance of the deep learning algorithms. The segmentation model showed high performance with 0.98 accuracy and 0.96–0.97 DSC. The AO/OTA classification model demonstrated effective performance with a 0.47–0.80 F1 score and 0.69–0.88 accuracy. Additionally, the classification model had a macro average of 0.77–0.94. Performance evaluation of the models showed relatively favorable results, which can aid in early classification of pelvic fractures.

Rational design of anthocyanidins-directed near-infrared two-photon fluorescent probes.

Recently, two-photon fluorescent probes based on anthocyanidin molecules have attracted extensive attention due to their outstanding photophysical properties. However, there are only a few two-photon excited fluorescent probes that really meet the requirements of relatively long emission wavelengths (>600 nm), large two-photon absorption (TPA) cross-sections (300 GM), significant Stokes shift (>80 nm), and high fluorescence intensity. Herein, the photophysical properties of a series of anthocyanidins with the same substituents but different fluorophore skeletons are investigated in detail. Compared with b-series molecules, a-series molecules with a six-membered ring in the backbone have a slightly higher reorganization energy. This results in more energy loss upon light excitation, enabling the reaction products to detect NTR through a larger Stokes shift. More importantly, there is very little decrease in fluorescence intensity as the Stokes shift increases. These features are extremely valuable for high-resolution NTR detection. In light of this, novel 2a-n (n = 1-5) compounds are designed, which are accomplished by inhibiting the twisted intramolecular charge transfer (TICT) effect through alkyl cyclization, azetidine ring and extending π conjugation. Among them, 2a-3 gains a long emission spectrum (λem = 691.4 nm), noticeable TPA cross-section (957 GM), and large Stokes shift (110 nm), indicating that it serves as a promising candidate for two-photon fluorescent dyes. It is hoped that this work will offer some insightful theoretical direction for the development of novel high performance anthocyanin fluorescent materials.