Redundancy in ship systems is provided to ensure operational resilience through equipment backups which ensures system availability and offline repairs of machinery. The electric power generation system of ships provides the most utility of all systems, hence is provided with good level of standby units to ensure reliable operations. Nonetheless, the occurrence of undesired black outs are common onboard ships and portends a serious danger to ship security and safety. Therefore, understanding the contributing factors affecting system reliability through component criticality analysis is essential to ensure a more robust maintenance and support platform for efficient ship operations. In this regard hybrid reliability and fault detection analysis were conducted to establish component criticality and related fault conditions. A case study was conducted on a ship power generation system consisting of 4 marine diesel power generation plants onboard an Offshore Patrol Vessel (OPV). Results from the reliability analysis indicate overall low system reliability of less than 70 per cent within the first 24 months of the 78 operational months. Component criticality using reliability importance measures was used to identify all components with more than 40 per cent contribution to sub systems failure. Additionally, machine learning was used to aid the reliability analysis through feature engineering and fault identification using Artificial Neural Networks classification. The ANN has identified failure patten threshold at about 200kva which can be attributed to overheating, hence establishing link between component failure and generator performance.

We investigated the properties of architected materials made from UV-cured urethane elastomers and the use of such materials for insoles. The durability and reliability of various materials currently used in medical insoles were compared with those of architected materials with microlattice. The results show that architected materials made from UV-cured urethane elastomers have high impact resilience and grip, and the hardness can easily be changed by adjusting the column diameter of the unit cell. Compared with the foam materials used for medical insoles today, these architected materials also demonstrate superior UV resistance, suggesting that, after being washed in water, they can be air-dried outdoors.

The concept of Design Fatigue Factors (DFFs) was introduced for providing desired level of safety in structural fatigue design, often associated with damage calculated from S-N curves. Calculation of fatigue damage from S-N curves can be affected by multiple factors, e.g. types of weld class, corrosion condition, loading conditions, stress concentration on different geometries etc. Each of them can be subject to different level of uncertainties. This study intends to recalibrate the DFFs from a detailed reliability analysis by investigating the probabilistic models derived from the database of S-N curves that has been most frequently used in offshore wind industry. The results of such study indicate that the DFFs can be reduced substantially for the corrosive environmental fatigue models from current standards to the same level of target reliability.

This review and meta-analysis (PROSPERO registration number: CRD42020138845) critically evaluates test-retest reliability, concurrent validity and criterion validity of different physical activity (PA) levels of three most-common used international PA questionnaires (PAQs) in national language versions of EU-28: IPAQ-SF, GPAQ, and EHIS-PAQ. In total, 4969 abstracts were read, 287 full-text articles were identified as relvant to the study objectives, and 19 studies were included in the final meta-analysis. The studies’ results and quality were evaluated using the Quality Assessment of Physical Activity Questionnaires (QAPAQ) checklist. Results indicate that only five EU-28 countries validated national language versions of selected PAQs. Meta analysis revealed that assessment of moderate-to-vigourus PA (MVPA) is the most relevant PA level outcome, since no publication bias in any of measurement properties was detected while test-retest reliability was the moderately-high (rw=0.74), and moderate for both criterion (rw=0.41) and concurrent validity (rw=0.72). Reporting of methods and results of the studies was poor with overall moderate risk of bias with total score of 0.43. In conclusion, where only self-reporting is feasible, assessment of MVPA with selected PAQs in EU-28 adult population is recommended for policymaking.

The IEEE 802.15.4-2015 standard includes the SUN (Smart Utility Networks) modulations, i.e., SUN-FSK, SUN-OQPSK and SUN-OFDM, which provide long range communications and allow to trade data rate, occupied bandwidth and reliability. However, given the constraints of low-power devices and the challenges of the wireless channel, communication reliability cannot still meet the PDR (Packet Delivery Ratio) requirements of industrial applications, i.e., PDR>99%. Hence, in this paper we evaluate the benefits of improving communication reliability by combining packet transmissions with modulation diversity using multiple IEEE 802.15.4g SUN modulations. The results derived from a real-world deployment show that going from 1 to 3 packet transmissions with the same SUN modulation can increase PDR from 85.0/84.6/71.3% to 94.2/94.1/86.0% using SUN-FSK, SUN-OQPSK and SUN-OFDM, respectively. Combining the same number of packet transmissions with modulation diversity allows to further increase the average PDR to 97.1%, indicating its potential as a tool to help meeting the reliability requirements of industrial applications.

Dams design and their operation cause strong environmental alteration and therefore a long-term debate is ongoing for the scale of these projects. At the same time, the concept of Environmental Flow Assessment (EFA) is a crucial element of modified ecosystems featuring large infrastructure such as dams and reservoirs for mitigating potential environmental degradation while they operate. Nowadays, integrated scientific frameworks are required to quantify the risks caused by large infrastructure. Through the use of stochastic analysis, it is possible to quantify these uncertainties, and present a solution that incorporates long-term persistence and environmental sustainability into a balanced reservoir simulation model. In this work, an attempt is made to determine a benchmark reservoir size incorporating hydrological and ecological criteria though stochastic analysis. The primary goal is to ensure the best possible conditions for the ecosystem, and then secondarily to allow a steady supply of water for other uses. Using a synthetic timeseries based on historical inputs, it is possible to determine and preserve essential statistical characteristics of a river’s streamflow, and use these to detect the optimal reservoir capacity that maximizes environmental and local water demand reliability.

The issue of measurement reliability is certainly undervalued in the local agricultural marketplace organization. Besides, there was nothing identified concerning the extent of cereal commodity trade measurement cost. Hence, this paper aimed to estimate the magnitude of cereals trade quantity measurement cost caused by instrument error and unreliability; mainly by targeting the local marketplace in Ethiopia. The survey was conducted in six different districts’ marketplaces (n = 602) of Oromia region by employing administered structured questionnaires and site mass measurement calibration. The gathered data were analyzed using independent samples t-test, one sample t-test, and analysis of variance. According to the findings, the actual value measurement means of the quantity of most local units of the farmers were greater than small traders. The independent t-test result indicated that the average values of the quantity of the majority of units of measurement between farmers and small traders were varied significantly. Estimated measuring instruments’ error and unreliability associated average measurement cost of one-day market transaction over total cereals marketed amount were higher comparatively for a sack, bowl, and glass units. This study demonstrates that homogeneity in measurement, policy, and institutions that aid cereals trade would have an indispensable role to reduce measurement costs and ensure equitable exchange.

A reliability-based criterion to estimate strength amplification factors for buildings with asymmetric yielding located within a seismic region presenting different soil conditions is proposed and applied. The approach involves the calculation of the mean annual rate of exceedance of structural demands of systems with different levels of asymmetric yielding. Two simplified mathematical expressions are developed considering different soil conditions of the valley of Mexico. The mathematical expressions depend on the ductility of the structural systems, their level of asymmetric yielding, their fundamental vibration period and the dominant period of the soil. In addition, the proposed expressions are compared with that recommended by the current Mexico City Building Code (MCBC). Since the expressions are developed with the help of simplified structural systems, the validity of such expressions is corroborated by comparing the expected ductility demand of multi-degree of freedom (MDOF) structural systems with respect to that of their equivalent simplified systems. Both structural representations are associated with a given annual rate of exceedance value of an engineering demand parameter. The expressions proposed in this study will be incorporated in the new version of the MCBC.

The objective of this study was to develop guidelines for rainwater harvesting system sizing of shopping centres in South Africa. Three generalized dimensionless relationships relating rainwater supply and demand to tank size, yield and reliability were developed based on 101 years long daily time step simulations of rainwater harvesting of 19 shopping centres located in four regions. Daily rainfalls were obtained from nearby rainfall stations and daily non-potable demands were based on the size of the retail area. The simulations revealed within-year storage behaviour with considerable variation of the yield specified as the number of days for which demand was met each year. The Weibull plotting position formula was applied on the time series of yields to obtain yield-reliability relationships. Simulation results of the hydrologically optimum systems were used to develop two of the generalized relationships and an additional one based on the dependence of the slope of the reliability – yield plots on the optimum yield was formulated to enable analysis of hydrologically non-optimal systems. Most of the relationships fitted best to the non-linear power law form with high correlation coefficients averaging 0.92 and ranging from 0.82 to 1.00. The application of the models for tank sizing and assessing system performance is demonstrated.

This paper aims to develop a low-cost, high-performance and high-reliability computing system to process large-scale data using common data mining algorithms in the Internet of Things computing. Considering the characteristics of IoT data processing, similar to mainstream high performance computing, we use a GPU cluster to achieve better IoT services. Firstly, we present an energy consumption calculation method (ECCM) based on WSN. Then, using the CUDA Programming model, we propose a Two-level Parallel Optimization Model (TLPOM) which exploits reasonable resource planning and common compiler optimization techniques to obtain the best blocks and threads configuration considering the resource constraints of each node. The key to this part is dynamic coupling Thread-Level Parallelism (TLP) and Instruction-Level Parallelism (ILP) to improve the performance of the algorithms without additional energy consumption. Finally, combining the ECCM and the TLPOM, we use the Reliable GPU Cluster Architecture (RGCA) to obtain a high-reliability computing system considering the nodes’ diversity, algorithm characteristics, etc. The results show that the performance of the algorithms significantly increased by 34.1%, 33.96% and 24.07% for Fermi, Kepler and Maxwell on average with TLPOM and the RGCA ensures that our IoT computing system provides low-cost and high-reliability services.

The software industry has adopted component-based software development (CBSD) to rapidly build and deploy large and complex software systems with significant savings at minimal engineering effort, cost, and time. However, CBSD encounters issues on security trust, mainly with respect to dependability attributes. A system is considered dependable when it can produce the outputs for which it was designed with no adverse effect on its intended environment. Dependability consists of several attributes that imply availability, confidentiality, integrity, reliability, safety, and maintainability. Dependability attributes must be embedded in a CBSD model to develop dependable component software. Motivated by the importance of these attributes, this paper pursues two objectives: to design a model for developing a dependable system that mitigates the vulnerabilities of software components, and to evaluate the proposed model. The model proposed in this study is labelled as developing dependable component-based software (2DCBS). To develop this model, the CBSD architectural phases and processes must be framed and the six dependability attributes embedded according to the best practice method. The expert opinion approach was applied to evaluate 2DCBS framing. In addition, the 2DCBS model was applied to the development of an information communication technology (ICT) portal through an empirical study method. Vulnerability assessment tools (VATs) were employed to verify the dependability attributes of the developed ICT portal. Results show that the 2DCBS model can be adopted to develop web application systems and to mitigate the vulnerabilities of the developed systems. This study contributes to CBSD and facilitates the specification and evaluation of dependability attributes throughout model development. Furthermore, the reliability of the dependable model can increase confidence in the use of CBSD for industries.

High-power lasers play an important role in modern science, industry, and medicine. A signifi-cant milestone was reached on December 5, 2022, when Inertial Confinement Nuclear Fusion (ICF) achieved scientific breakeven, releasing more energy than the input laser energy. Additionally, Extreme Ultraviolet Lithography (EUVL) has enabled the development of microchips with 3 nm process nodes, marking a leap in semiconductor technology. These examples together with the recent achievement of a 10 PW (1015 W) laser output heralds remarkable advancements in technology and science soon. Laser systems are broadly classified based on their operating re-gimes into two main categories: Continuous Wave (CW) operation, where the laser is continuously pumped and emits a steady beam of light, and the pulsed regime, in which the laser pro-duces single or multiple pulses at various repetition rates. This review will primarily focus on pulsed laser systems, exploring their various types and recent technological advancements.

Rocks are materials with a wide variety of structures and properties. These can be unprocessed conglomerates of conglomerated minerals as well as crystallized outcrop or metamorphic rocks. Their processing, especially shaping, poses many technological difficulties. Therefore, it is very important to answer the question of how these natural materials yield to high-pressure water jet and abrasive water. It is equally important to determine the effect of key process parameters such as pressure, water nozzle diameter and feed rate on cutting efficiency. The first two parameters determine the water output and power of the jet, while the third determines the jet erosion time per unit volume of material. Their interdependence, using appropriate evaluation indicators, allows to determine the energy intensity of processing and directions for its minimization.

In the recent concrete industry, high fluidity concrete is being widely used for the pouring of dense reinforced concrete. Normally, in the case of high fluidity concrete, it includes high binder contents, so it is necessary to replace part of the cement through admixtures such as fly ash to procure economic feasibility and durability. This study shows the mechanical properties and field applicability of high fluidity concrete that using mass of fly ash as alternative materials of cement. The high fluidity concrete mixed with 50% fly ash was measured to manufacture concrete that applies low water/binder ratio to measure the mechanical characteristics as compressive strength and elastic modulus. Also, in order to evaluate the field applicability, high fluidity concrete containing high volume fly ash was evaluated that fluidity, compressive strength, heat of hydration and drying shrinkage of concrete.

Femtosecond laser two-photon polymerization (TPP) technology, known for its high precision and capability to fabricate arbitrary 3D structures, has been widely applied in the production of various micro-nano optical devices, achieving significant advancements particularly in the field of photonic wire bonding (PWB) for optical interconnects. Currently, research on optimizing both the optical loss and production reliability of polymeric photonic wires is still in its early stages. One of the key challenges is that inadequate metrology methods cannot meet the demand for multiphysical measurements in practical scenarios. This study utilizes in-situ scanning electron microscopy (SEM), for the first time, to monitor the working PWBs fabricated by TPP technology at the microscale. Optical and mechanical measurements are made simultaneously to evaluate the production qualities and to study the multiphysical coupling effects of PWBs. The results reveal that photonic wires with larger local curvature radii are more prone to plastic failure, while those with smaller local curvature radii recover elastically. Furthermore, larger cross-sectional dimensions contribute dominantly to the improved mechanical robustness. The optical loss deterioration of the elastically deformed photonic wire is only temporary, which can be fully recovered when the load is removed. After further optimization based on the results of multiphysical metrology, the PWBs fabricated in this work achieve a minimum insertion loss of 0.6 dB. In this study, the multiphysical analysis of PWBs carried out by in-situ SEM metrology offers a novel perspective for optimizing the design and performance of microscale polymeric waveguides, which could potentially promote the mass production reliability of TPP technology in the field of chip-level optical interconnection.

In this paper, based on the cumulated damage generated by the cyclical application of the testing vibration profile, a methodology to determine the reliability index of the analyzed component is given. In the analysis, the testing time, component geometry, applied weight, and material resonant frequency are all of them considered by using a dynamic, and amplitude factor. Then, from the generated vibration response data of the analysis, the corresponding bending stress is determined for each one of the rows of the testing profile. And by the cyclical application of the whole testing profile, the corresponding damage is cumulated to each profile cycle until the cumulated damage is D=1. Finally, the reliability that each one of the cumulated blocks (cyclical profile application) is determined by considering, the random vibration is a stress variable. Thus, we use the cumulative damage model with the inverse power law stress/life relationship to determine the two parameter Weibull distribution used to estimate the reliability index of each cumulated block. As a numerical application, we analyze a cantilever aluminum beam Al 6061-T6.

While advances in information and communication technology have increased the efficiency of information distribution, it has also brought several challenges to the database industry. One of the main challenges is ensuring the real-time availability of data, which is critical. In addition, downtime in centralized database systems can cause significant failures. Therefore this research applies database replication, especially the multi-master method, is used to increase availability and reduce the possibility of failure. For distributed transaction distribution, this research uses the auto-promote master method and web services for PostgreSQL database replication. The focus of the research is on real-world college site selection transactions, where speed, scalability, and high data availability are critical. The results show that combining these methods can improve system performance and protect data availability. With fast response time, high throughput, and low error rate, the API performs well with various loads. As a testament to scalability and reliability, the system can handle large volumes of traffic without experiencing significant crashes. For containerization, Docker supports efficient and stable performance and ensures consistency and manageability. Future recommendations include improving the data security mechanism and further efforts to optimize the distribution system architecture.

Abstract: Understanding the reliability and sensitivity of jump testing is essential to determine the neuromuscular progress of athletes and make informed decisions. This study aimed to assess the reliability and sensitivity of countermovement jump (CMJ) and drop jump (DJ) tests metrics in female volleyball players. Sixteen semi-professional female volleyball players participated in the study. Intrasession and intersession reliability of CMJ and DJ metrics were evaluated using a randomized cross-over design. Dual force platform was used to collect data, and several dependent variables were calculated using forward dynamics. Intraclass correlation coefficients (ICC), coefficients of variation (CV) and minimum difference (MD) were calculated. The third attempt presented the highest values for both test, and changes in jump strategy in DJ. CMJ is consistent across sessions, while DJ also shows intersession differences (p<0.05) in 11 out of 15 variables. Most CMJ variables exhibit excellent reliability while DJ variables have lower reliability and higher variability. Concentric and eccentric impulses for DJ showed excellent reliability. Most CMJ variables showed excellent reliability and variability, DJ had lower reliability, higher variability, and lower sensitivity. These findings provide valuable information when assessing athletes' performance and highlight the reliability, sensitivity, and variability in jump performance for CMJ and DJ tests.

This paper presents the development of an underwater crack detection system for structural integrity assessment of submerged structures, like offshore oil and gas installations, underwater pipelines, underwater foundations for bridges, dams etc. Focus is on use of machine learning based approaches. First a detailed literature review of state of the current methods for underwater surface crack detection is presented highlighting challenges and opportunities. An overview of image augmentation approach for creation of underwater optical effects is also presented. Experimental results using standard network based machine learning approach, used for surface crack detection in onshore environment, is presented. Series of Test cases are presented where existing networks performance are improved using augmented images for underwater conditions. The experimental results demonstrate the effectiveness and accuracy of the proposed system in detecting cracks in underwater structures. The system has the potential to improve the safety and reliability of underwater structures and prevent catastrophic failures.

This paper considers the application of two selected algorithms (Cuckoo Search CS, Firefly Algorithm FA) to determine and maximize the reliability of a two complex system known from the literature. This system operates with resource constraints. In addition, several classical methods for determining the reliability of systems have been applied. Although the CS algorithm is known for its effectiveness as it uses the Lévy flight, for the presented optimization tasks the FA firefly algorithm in the considered parameter range proved to be more effective. The presented results broaden the existing discussion on the application of nature-inspired algorithms for solving RRAP (Reliability Redundancy Allocation Problem) problems. From this point of view, two described test scenarios can be considered as a suitable tool for validating other algorithms in RRAP problems. Not only the values of the criterion functions can be compared, but also other introduced parameters and statistical analyse of variance (ANOVA) with post-hoc RIR Tuckey test was discussed.

First responders, such as police officers, paramedics, and fire-fighters are at an increased risk of experiencing negative mental health outcomes compared to the general population. This predisposition can partially be attributed to common occupational stressors, such as poor workplace culture and mistreatment from leadership, which may provoke strong feelings of betrayal and humiliation. The Workplace Assessment Scale (WAS) was developed as there is currently no appropriate measure to assess such feelings in the first responder population. The scale consists of the Betrayal Subscale and the Humiliation Subscale, each comprised of 5 Likert scale questions which ask participants to report the frequency at which they experience specific feelings associated with their workplace. This pilot validation study was conducted to assess preliminary reliability and validity of the WAS, using data which was originally collected as part of a larger first responder-based observational study. Based on 21/22 (95%) participant responses, the internal consistency appeared to be strong for both sub-scales as well as the overall questionnaire. However, item 9 will likely require modification or deletion from the scale. The validity analysis found no significant correlations between WAS and other psychiatric scales. Additional research is needed for further analysis and validation of the WAS.

Drivers of L3 automated vehicles (AVs) are not required to continuously monitor the AV system. However, they must be prepared to take over when requested. Therefore, it is necessary to design an in-vehicle environment that allows drivers to adapt their levels of preparedness to the likelihood of control transition. This study evaluates ambient in-vehicle lighting that continuously communicates the current level of AV reliability, specifically on how it could influence drivers' take-over performance and mental workload (MW). We conducted an experiment in a driving simulator with 42 participants who experienced 10 take-over requests (TORs). The experimental group experienced a four-stage ambient light display that communicated the current level of AV reliability, which was not provided to the control group. The experimental group demonstrated better take-over performance, based on lower vehicle jerks. Notably, perceived MW did not differ between the groups, and the EEG indices of MW (frontal theta power, parietal alpha power, Task-Load Index) did not differ between the groups. These findings suggest that communicating the current level of reliability using ambient light might help drivers be better prepared for TORs and perform better without increasing their MW.

Huntington's disease (HD) is a rare genetic neurodegenerative disorder that causes motor disorders, neuropsychiatric symptoms and a progressing deterioration of cognitive functions. Complex issues resulting from the hereditary nature of HD, the complexity of symptoms and the concealed onset of the disease have a great impact on the quality of life of family carers. The caregivers are called as “forgotten people” in HD family, also in genetic counseling. This study aims to explore the reliability and validity of the Huntington’s Disease Quality of Life Battery for carers (HDQoL-C) within a Polish population. 90 carers recruited from the Enroll-HD study in Polish research centres of the European Huntington`s Disease Network completed a polish translation of the HDQoL-C. Data was subjected to Principle Components Analysis and reliability measures. The Polish version of the shortened versions of the HDQoL–C is similarly valid compared to the original English version and suitable for use within this population. The HDQoL-C has previously demonstrated a wide range of benefits for practitioners in capturing and understanding carer experience and these benefits can now be extended to Polish speaking populations.

The main objective was to analyze the influence of silicon content on high-temperature oxidation of low-alloy steels. Samples of AISI 1045, AISI 5160, and AISI 9254 steels, with different silicon contents, were oxidized at an isothermal temperature of 1000°C for times of 20 minutes, 40 minutes, and 60 minutes. The oxide layers formed mainly contain hematite, magnetite wustite, and fayalite. The average thickness of the oxide layer can decrease with an increase in silicon content below 1% but can increase for contents greater than 1% due to the difference in density between fayalite and iron oxides. Silicon tends to accumulate on the surface of steel and form a SiO2 film in the early stages of oxidation, which can control the oxidation process. The eutectic compound FeO+Fe2SiO4 forms at the oxide-steel interface, and its thickness increases with oxidation time and the silicon content present. The SiO2 film tends to decrease with oxidation time and silicon content.

Chemical flooding methods are used to recover the remaining oil after water flooding, and surfactant-polymer (SP) flooding is an important chemical flooding technology. It is of great significance to design and screen high-performance oil displacement agents in order to overcome the increasingly challenging high temperature (&gt;70 ℃) and high salinity (>10,000 mg/L) reservoirs. Based on the characteristics of high temperature (70 ℃) and high salinity (151,000 mg/L) in the Qinghai Gasi reservoir, the performance of the SP flooding system was studied. This study considered interfacial tension, emulsification, viscosity, compatibility, and oil displacement efficiency. The selected formula demonstrated high resistance to both salinity (151,000 mg/L) and temperature (70 ℃), characterized by a low oil-water interfacial tension (10-2 mN/m) and high viscosity (18.13 mPa.s). After water flooding achieved an oil recovery rate of 64.64%, the subsequent replacement rate of crude oil increased by 26.95%, confirming that SP flooding can be used as a technology for enhancing oil recovery in high-temperature, high-salinity reservoirs represented by Qinghai Gasi reservoirs.

Intended for the high voltage gain and wide-range operation of DC/DC converters for photovoltaic energy storage systems, a topology for four-phase interleaved DC/DC converters for photovoltaic power generation is proposed. This topology increases output voltage for output in series, and reduces the input current ripple by paralleling the input. Compared with traditional boost converter topology, the proposed topology reduces the output current and output voltage ripple, reduces the stress of the switching device, and reduces the withstanding voltage of the output capacitor under the premise of ensuring the boost ratio. Experimental results show that the maximum efficiency of the converter reaches 95.37%. Compared with traditional boost converters, the proposed converter offers obvious advantages in efficiency under the conditions that the output voltage and load are variable.

China is facing the development requirements of the dual carbon goal and the construction needs of resilient cities. Currently, high-strength composite structural systems are a feasible solution, but their research and application in the construction field are insufficient, especially for the combination forms of concrete above C100 and steel above Q550. In response to this issue, this paper proposes a new high-performance structural system, namely the composite frame - high-strength steel plate wall core tube resilient structure system, which includes high-strength steel plate (Q550) - ultra-high strength concrete (C100) shear walls, replaceable energy dissipation coupling beams, and composite frames. Taking a 200 meter building as an example, this paper designs and establishes calculation models for a conventional reinforced concrete frame-core tube structure and a high-performance structure based on PKPM software, and establishes elastoplastic analysis models for both based on SAUSAGE software, and then conducts dynamic elastoplastic time history analysis and seismic resilience assessment of structures under design basis earthquakes (DBEs), maximum considered earthquake (MCEs) and extremely rare earthquakes (EREs). Research has shown that compared to conventional structures, new high-performance structures can effectively reduce the size of shear walls, reduce the self-weight of the structure, and enhance the space for building use; The story drift ratio has higher redundancy than specification limits, lower plastic damage and overall stiffness degradation of the structure, and better seismic performance; The seismic resilience has significantly improved, especially in the case of casualties, which can better ensure the safety of people's lives and property.

To investigate the composition of caproic acid-producing bacterial communities in sub-high-temperature Daqu, we analyzed four different Daqu samples from Sichuan. After enriching the samples with a specialized medium, we performed high-throughput sequencing of 16S rRNA gene amplicons on the metagenomic DNA from both the Daqu samples and the enrichment cultures. Our analysis focused on identifying and characterizing the caproic acid-producing bacterial communities present in Daqu. The results revealed that enrichment increased both the diversity and abundance of potential caproic acid-producing bacteria in Daqu. The predominant caproic acid-producing bacteria, with a relative abundance greater than 1%, included Clostridium sensu stricto 18 (2.19% to 69.00%), Clostridium sensu stricto 15 (1.76% to 7.65%), as well as smaller amounts of Clostridium sensu stricto 12, Clostridium sensu stricto 1, Clostridium sensu stricto 10, Clostridium sensu stricto 7, and Caproiciproducens. Specifically, Q1 Daqu was characterized by the presence of Clostridium sensu stricto 18 and Clostridium sensu stricto 15. Q2 Daqu featured Clostridium sensu stricto 1, Caproiciproducens, and Clostridium sensu stricto 18. Q3 Daqu included Clostridium sensu stricto 18 and Caproiciproducens. Q4 Daqu contained Clostridium sensu stricto 18 and Clostridium sensu stricto 1. These findings indicate that there are variations in the composition of caproic acid-producing bacterial communities among different sub-high-temperature Daqu samples from Sichuan. This preliminary analysis provides a theoretical basis for further studies on caproic acid bacteria in Daqu and offers insights into the development of high-quality Daqu, which may enhance the quality of Nongxiangxing liquor.

The gas-water relative permeability curve plays a crucial role in reservoir simulation and development for condensate gas reservoirs. In this study, we conducted a series of high temperature and high pressure analysis experiments on real gas cores from Wells A and B in Block L of the Yinggehai Basin to investigate the effects of temperature, pressure, and different types of gas media on gas-water seepage. The experimental results demonstrate that: Temperature has a significant impact on both gas and water relative permeability, particularly on the former. As temperature increases, gas relative permeability shows a substantial increase while water relative permeability remains relatively unchanged. Under the same effective stress, increasing pressure causes downward shifts in both the gas and water relative permeability curves; however, there is a more pronounced decrease in gas relative permeability. Gas type has minimal influence on phase permeability except at higher water saturation where differences become apparent. When water saturation ranges from 80% to 50%, there is no significant variation observed in the measured relative permeability of different displacement gases; however, as water saturation exceeds 80%, distinctions gradually emerge. At bound water saturation conditions, nitrogen exhibits lower relative permeability compared to simulated gases with approximately 92% similarity between them. This investigation into the characteristics of gas-water relative permeability in high temperature and high pressure condensate reservoirs within Yinggehai Basin provides valuable insights for efficient development strategies for similar reservoirs.

This paper presents the design and experimental results of a long cavity length Nd: YAG laser with large stable zone for water jet guided laser (WJGL) applications. The design is based on the light transmission matrix and resonator stability conditions, aiming to achieve a large stable zone and a short cut-off thermal focal length (CTFL). A folded concave resonator is researched to enhance the cavity length, and the influence of the tun-able cavity arm length on the oscillating beam in the resonator and in the YAG crystal is theoretically studied. Moreover, the effects of the output mirror curvature and the cavity arm length on the range of the stable area and the cut-off thermal focal length are also investigated. Experimental results show that a stable green laser output is obtained after second harmonic generation (SHG), with a pulse width ranging from 43ns to 143ns within the laser operating frequency range of 5-20kHz. At an operation frequency of 10kHz, the output power is 21.33W, and the instability of the output power within 400 minutes is 0.88%. The laser source achieves a maximum power of 25.7W at 20kHz, and the maximum single pulse energy reaches 2.7mJ at 6kHz. Finally, this is used as the laser source to couple with a water jet with a diameter of 100 microns, achieving a lossless water conductivity transmission over 60mm length with a peak power density of 0.742GW/cm2. These results demonstrate the suitability of the designed laser source for WJGL technology research.

Indonesia's SUMBAGUT 150 kV transmission of High Voltage Alternating Current Network (HVAC) system has considerable power losses. These power losses are a critical problem in the transmission network system. Meanwhile, this study provides one solution to reduce power losses using a High Voltage Direct Current (HVDC) network system. Determining the location to convert HVAC into HVDC is very important. The authors use Particle Swarm Optimization (PSO) to get the optimal location on the 150 kV SUMBAGUT HVAC transmission network system. The study results showed that before using the HVDC network system, the power losses were 122.26 MW. Meanwhile, power losses with one transmission HVDC in the "Paya Pasir-Sei Rotan" are 84.16 MW, "Porsa-P. Siantar" 90.83 MW, "Paya Pasir-Paya Geli" 104.14 MW. Then power losses with two transmission HVDC in "Paya Pasir-Sei Rattan" and "Porsa-P. Siantar" is 71.24 MW, "Paya Pasir-Sei Rotan" and "Paya Pasir-Paya Geli" 77.46 MW, "Porsa-P. Siantar" and "Paya Pasir-Paya Geli" 78.52 MW. The last result, power losses with three transmission HVDC in "Paya Pasir-Sei Rotan," "Porsa-P. Siantar," and "Paya Pasir-Paya Geli" lost 64.57 MW.

This study analyses some of the leading technologies for the construction and configuration of IT infrastructures to provide services to users. For modern applications, guaranteeing service continuity even in very high computational load or network problems is essential. Our configuration has among the main objectives of being highly available (HA) and horizontally scalable, that is, able to increase the computational resources that can be delivered when needed and reduce them when they are no longer necessary. Various architectural possibilities are analysed, and the central schemes used to tackle problems of this type are also described in terms of disaster recovery. The benefits offered by virtualisation technologies are highlighted and are bought with modern techniques for managing Docker containers that will be used to build the back-end of a sample infrastructure related to a use-case we have developed. In addition to this, an in-depth analysis is reported on the central autoscaling policies that can help manage high loads of requests from users to the services provided by the infrastructure. The results we have presented show an average response time of 21.7 milliseconds with a standard deviation of 76.3 milliseconds showing excellent responsiveness. Some peaks are associated with high-stress events for the infrastructure, but the response time does not exceed 2 seconds even in this case. The results of the considered use case studied for nine months are presented and discussed. In the study period, we improved the back-end configuration and defined the main metrics to deploy the web application efficiently.

Background/Objectives: This study aimed to evaluate the impact of image enhancement techniques on the interobserver reliability of tear breakup time (TBUT), tear meniscus height (TMH), corneal fluorescein staining (CFS) scoring, and conjunctivochalasis detection using the Smart Eye Camera (SEC), a portable device for anterior segment examination. Methods: A retrospective analysis was conducted on video recordings captured by SEC from 46 patients with dry eye disease (DED). Three video sets were created: unenhanced (G0), mildly enhanced (G3), and strongly enhanced (G7). Three observers—two DED specialists and one general ophthalmologist—assessed TBUT, TMH, CFS scores, and conjunctivochalasis. Interobserver reliability was evaluated using intraclass correlation coefficients (ICCs) for each image set. Results: Interobserver reliability for CFS scores significantly improved with G3, yielding an ICC of 0.8413. In contrast, G7 improved reliability for TBUT measurements (ICC = 0.7381) but led to a notable decrease in reliability for both CFS scoring (ICC = 0.2259) and conjunctivochalasis detection (ICC = 0.0786). Furthermore, the assessment of TMH demonstrated a progressive decline in accuracy with increasing levels of image enhancement. Conclusions: Image enhancement using SEC improves diagnostic consistency between dry eye specialists and general ophthalmologists, especially for TBUT and CFS assessments. However, excessive enhancement may obscure key diagnostic features, indicating the need for careful optimization of image processing techniques depending on the diagnostic focus.

Objectives: The aim of this study was to determinate the validity and the reliability of the self-administered Timed Up and Go (TUG) test, a gold standard test for fall risk screening, when compared to the traditional face-to-face assessment carried out by a physiotherapist. Methods: A total of 37 community-dwelling adults, mean age 61.78±6.88, 73% female, who took part in fall risk screening actions in the central region of Portugal, were assessed. The protocol included sociodemographic and history of falls questions, the Self-Efficacy for Exercise questionnaire, the Activities and Participation Profile Related to Mobility (PAPM) and three functional tests, namely the 10-Meter Walking Speed (10-MWS), TUG and 30 Seconds Sit to Stand (30s STS) tests. Within an interval of 18-24 hours after the face-to-face moment, the participants were instructed to self-administer the TUG test at home. The validity and reliability of self-administered TUG test were examined using the limits of agreement, clinically acceptable limit, intra-class correlation coefficients (ICC), paired t-tests and Pearson´s coefficient correlation (r). Results: The limits of agreement for self-administered assessment were within the clinically acceptable limits. The average result of the face-to-face TUG test and self-administered TUG test was 7.47 ± 2.45 and 7.57 ± 3.10 seconds, respectively. When comparing the two evaluations, they were strongly associated (r=0.716, p<0.001), with an excellent ICC of 0.82 (0.65-0.91), for a 95% confidence interval. Conclusion: The use of the self-administered TUG test for the screening of risk of fall, using low-cost technology, appears to be valid and reliable in community-dwelling adults aged 50 and over.

Background: The chin tuck maneuver has been suggested to increase suprahyoid muscle activation, but a method to measure the strength of the chin tuck maneuver has not been established. We developed a method to measure the strength of the chin tuck maneuver (chin tuck strength) and examined the reliability and validity of chin tuck strength measurement in community-dwelling older adults. Subjects and Methods: The participants were 233 older adults aged ≥65 years without dysphagia or physical disability. Chin tuck strength was measured twice consecutively using the developed device, and reproducibility was analyzed using intraclass correlation coefficients (ICCs). In addition, maximum tongue pressure, oral diadochokinesis, grip strength, knee extension strength, and the timed up and go test (TUGT) were measured as indices of swallowing-related muscle function and appendicular muscle function. The associations of chin tuck strength with swallowing-related muscle function and appendicular muscle function were analyzed statistically. Results: The ICCs for chin tuck strength were 0.82 (95% confidence interval [CI]: 0.73-0.88) in males and 0.87 (95%CI: 0.70-0.93) in females. Chin tuck strength was significantly associated with maximum tongue pressure, grip strength, knee extension strength, and TUGT. Conclusions: This study suggests that chin tuck strength is a reliable and valid assessment of swallowing-related muscle strength.

Tegucigalpa, the capital city of Honduras, has the highest number of landslides recorded in the country. In a previous study, landslides were found to be mainly concentrated in areas with colluvium and residual soils. The present study focused on assessing the physical vulnerability of houses and the risk linked to landslides in these types of soils. As an input for this assessment, the study generated landslide risk vulnerability functions based on empirical data. The study's findings suggest that the estimated Annual Average Losses associated with landslides in this region is USD 7.26 million. Moreover, the study developed a novel approach for the spatial and temporal estimation of landslide hazard probability, which overcomes some of the limitations identified in previous landslide risk assessment studies.

Plug and abandonment (P&amp;A) operations demand valuable time and resources with operational procedures and materials to establish the well barrier element. This study proposes the use of a water-based fluid as a liquid well barrier element for temporary abandonment, based on esti-mates of its lifespan and survival probability on downhole conditions acquired through acceler-ated life tests. For that, the water-based formulation was tested and exposed to 95, 110, 140 and 150°C, for time intervals ranging from 1 to 10 days. After temperature exposure, the fluid prop-erties were verified and failure was detected by accounting for any deterioration in rheological parameters and/or a substantial increase in filtrate volume. Statistical analysis of failure data was performed in R software using Weibull Model, and fluid average lifespan and survival probability were estimated for P&amp;A temperatures. The results obtained demonstrates that the degradation of the fluid only was observed for 140 and 150°C and is mostly related to the CMC deterioration. The reliability metrics shows that until 80°C the fluid is a promising alternative for temporary abandonment, with no need of monitoring. For higher downhole temperatures, theses metrics should be considered to define the maximum time of operation and requirements for monitoring management in the operation design.

The present study is to address performance of the dairy supply chain and emphasizes the significance of reliability of the chain as a fundamental and critical attribute for fulfilling the safety requirements. In order to evaluate the performance of the dairy supply chain, the present study utilizes the reliability attribute, which is an essential and informative system performance indicator. The study considers not only the inputs and outputs but also internal activities and relationships between customers, manufacturers, and suppliers. To minimize calculations and resolve uncertainties and vagueness that may be experienced in the performance evaluation process, this study proposes the use of the Fuzzy Inference System (FIS) approach and evaluates the reliability at each level of the supply chain: supply, manufacturing, and distribution. Combining the reliability of different levels, the study finally calculates the reliability of the entire supply chain. The proposed methodology offers a practical approach for evaluating the reliability performance of a dairy supply chain and can be easily extended to other industries as well. To verify the proposed methodology, a real case in the Iranian dairy industry is chosen to be studied. Results indicate that the proposed methodology can effectively identify bottlenecks or weaknesses in the dairy supply chain and help develop effective strategies to address them. Analyzing factors influencing supply chain reliability can optimize operations, reduce costs, and improve the overall quality of dairy product quality delivered to consumers.

The critical systems, which the failure and malfunction may result in human, environment and financial severe damages, are essential components in various sectors and particularly in energy domains. Although unwished, integration error problems in supervision of critical systems occurs, incurring significant expenses because of operator’s subjective analysis and on hardware topology failures. In this work, a malleable model design approach is proposed to formulate and solve the integration error problem in the critical systems supervision in terms of reliability. A real Hybrid Power Plant (HPP) case is considered as a requirement for a study case with simulated data. A method framework with informal approach (C4 diagram) and formal approach (Hierarchical Coloured Petri Nets) in radial spectrum is applied to the HPP supervision design. Using formal methods, a formulation and solution to this problem through structured, scalable and compact mathematical representations are possible. This malleable model intends to guarantee functional correctness and then reliability of the plant supervision system based on system software architecture. Outcomes suggest corroboration that the malleable model is appropriate for energy domain, and can be used for other types of critical systems, bringing all the benefits of this methodology to the context in which it will be applied.

Wireless Sensor networks (WSNs) are gaining more and more research interest due to their ability to monitor large areas more or less independent. However, their reliability is an important issue, since their system reliability is influenced from a hardware, a data and an energetic point of view due to different factors like loading conditions, signal attenuation and battery lifetime. Regarding these issues, the positions of sensor nodes have to be chosen correctly to maximize the system reliability, which has to be considered during the development of new products equipped with WSNs. In this paper, an approach to estimate a WSNs system reliability during the development phase based on the analysis of the measurements on the example of strain measurements in finite elements (FE) models is presented. For that, the part under consideration is divided into regions with similar strains by the use of a Region Growing Algorithm (RGA). Afterwards, the WSN’s configuration is analyzed regarding its reliability in accordance to the data paths and measurement redundancy due to the sensor positions in the found measuring regions. This methodology is tested on an exemplary WSN configuration at an aircraft wing box under bending load and was found to work very well regarding the estimation of the hardware perspective on the system reliability. Therefore, the methodology and the developed algorithm show potentials for optimizations in sensor node positions for better reliability results.

The Planetary Roller Screw Mechanisms (PRSMs), alongside Ball Screw Mechanisms (BSMs) and Electromechanical Actuators (EMAs), occupies a pivotal role in advancing the precision and efficiency of various industrial applications, including aerospace, automotive, and high-precision machining tools. Despite their critical advantages such as high load capacity, superior precision, and extended lifespan, the deployment of PRSMs in complex operational conditions reveals a landscape rife with challenges and opportunities for further research. This comprehensive review endeavors to dissect the multifaceted aspects of PRSMs, focusing on their mechanics and dynamics, tribology and thermal behavior, and the paramount importance of reliability and condition monitoring. By synthesizing current research findings, this paper highlights the significant advancements in understanding the static and dynamic characteristics of PRSMs, the intricate interplay between lubrication conditions and wear mechanisms, and the critical role of thermal effects on operational performance. Moreover, it delves into the dynamic models that address the impact of manufacturing imperfections, such as waviness and defects, on the reliability of these mechanisms. Despite the strides made, the review identifies critical gaps in the existing literature, particularly under conditions of extreme temperatures, large deformations, and multifaceted loads, advocating for a holistic approach to research. By proposing integrated thermo-mechanical models and emphasizing the need for empirical validations, this paper outlines a roadmap for future studies aimed at facilitating the development of more robust and reliable PRSMs, capable of meeting the demands of complex operational scenarios and advancing the field of high-precision applications in aerospace, robotics, and beyond.

To enhance the overall reliability of the power system, engineers have redirected their focus toward health monitoring and early detection of faults in transformers. Among these faults, transformer core defects demand particular attention. While fault simulation using software has traditionally been the preferred approach, these methods suffer from data inaccuracies in real-world conditions. Consequently, conducting actual experimental setups with induced faults is imperative to investigate core issues. This study uses Hilbert Transform (HT) as a signal processing technique to extract crucial data characteristics, thereby enhancing the performance of the classifier model. The research involves analyzing electric current signals from a single-phase 1kVA transformer. A comparative assessment of our proposed model was conducted using raw data and Fast Fourier Transform (FFT), evaluating accuracy, precision, recall, F1-score, and computational time. The results demonstrate a significant improvement in all metrics for the classifier models, particularly the k-nearest neighbor (KNN) algorithm, which exhibited values of 83.89%, 84.39%, 83.89%, 83.79%, and 0.0156 seconds, respectively. Future work aims to extend this analysis under different loading conditions.

Stochastic modelling of geometrically imperfect steel frame structures requires inputs of statistical values of the imperfection parameters, in some cases also with suitably selected mutual correlations between these input parameters. The paper presents a verification study of two stochastic methods to directly model the initial global geometrical imperfections of the steel frame structures. The stochastic input values of geometrical imperfections are derived from the tolerance criteria of the corresponding European Standard. Two advanced stochastic methods have been developed, referred as #RSS (random story sway) and #RSP (random story position). These methods are verified using random sampling simulations. This study provides useful provisions for the advanced numerical analyses of multi-story steel frames of various geometries. The proposed methods are verified for equidistant story heights and for structures of up to 24 stories, hence might be used for the most types of the standard steel frame structures.

The feasibility of recovering bioactive antioxidants from Phyllantus emblica leaves using ethanol -water mixture (0 – 100%) and heat-assisted extraction technology (HAE-T) was investigated in this present study. To this effect, the process parameter of operating temperature (OT: 30 -50 oC), solid -to-liquid ratio (S:L: 1:20 - 1:60 g/mL) and extraction time (ET: 45 - 180 min) were investigated on the extract total phenolic content (TPC, mg GAE/g d.w), yield (EY, %) and antioxidant activity (μM AAE/g d.w) by employing the Box-Behnken experimental design (BBD) available in response surface methodology (RSM). Multi-objective process optimization using the desirability function algorithm to determine set of process variables that simultaneously optimize process responses of TPC, EY and AA was also investigated. The recovery process was thereafter modeled with BBD-RSM and multi gene genetic programming (MGGP) algorithm and model reliability assessment via Monte Carlo simulation were conducted for the best performing set of models for predicting TPC, EY and AA values. The HPLC characterization of the recovered extract was carried out to ascertain the phenolic compound constituents of the Phyllantus emblica leaf extract. The 50% ethanol solution was found to be the best for the optimal extraction of antioxidants from Phyllantus emblica leaves. The HAE-T was suitable for recovering bioactive extract from Phyllantus emblica leaves and investigated process parameters have impacts on the recovery process. The process parameters that simultaneously gave the optimum EY of 21.6565%, TPC of 67.116 mg GAE/g and AA of 3.68583 µM AAE/g were OT of 41.61 oC, S:L of 1:60 g/mL and ET of 180 min. The HPLC extract profiling revealed that the bioactive constituents present in the recovered extract were betulinic acid, gallic acid, chlorogenic acid, caffeic acid, ellagic acid, and ferulic acid. Both the developed BBD-RSM and evolved MGGP-based models predicted the observed process response of TPC, EY and AA satisfactorily with BBD-RSM models marginally better in their predictions. The reliability results showed that the BBD-RSM models predicted TPC, EY and AA values with high certainty of 99.985%, 97.569% and 98.661%, respectively.

The entry and exit method is a simple and practical method to determine the critical slip surface of slope. However, it has the drawback of sacrificing computational efficiency to improve search accuracy. To solve this problem, this paper proposes an improved entry and exit method to search for the critical slip surface. Based on the random fields generated by using Karhunen–Loève expansion method, the simplified Bishop’s method combined with the improved entry and exit method is used to determine the critical slip surface and its corresponding minimum factor of safety. Then, the failure probability is calculated by conducting Monte Carlo simulation. Two examples are reanalyzed to verify the accuracy and efficiency of the proposed method. Meaningful comparisons are made to demonstrate the calculating accuracy and calculating efficiency of the improved entry and exit method in searching for the minimum safety factor of slope, based on which the effect of the reduced searching range on slope reliability was explored. The results indicate that the proposed method provides a practical tool for evaluating the reliability of slopes in spatially variable soils. It can greatly improve the computational efficiency in relatively high-computational accuracy of slope reliability analysis.

Frailty, an age-related decline in homeostatic reserves, markedly proceeded during the coronavirus disease 2019 pandemic. To continuously assess frailty status, a remote system is urgently required. We aimed to co-design/co-develop an online frailty check (FC) application alongside FC supporters who were facilitators in a pre-existing onsite FC program. The online FC included a screening measurement for sarcopenia and an 11-item questionnaire covering dietary, physical, and social behaviors. Using prototype applications, 55 opinions obtained from 32 FC supporters (median 74.0 years) were categorized and reflected refinement. Regarding the self-efficacy of FC supporters, a significant increase in social positioning was seen after the mock test (P=.031). For FC supporters and participants, the average system usability scale (SUS) score was 70.2±10.3 points, which was “marginally high” for acceptability and “good” for the adjective range. Multiple regression analysis showed that the SUS score was significantly correlated with online-onsite reliability but not online communication, even after adjusting by age, sex, education level, and ICT proficiency (b=0.400, 95% CI: 0.243-1.951, P=.013). Additionally, a significant association between onsite and online FC scores was observed (R=0.670, P=.001). Our online FC application was evaluated to be a valuable tool to practically assess frailty status remotely.

Assessment of stigma among cancer patients is of utmost importance as stigma may lead to various psychological sequelae and lower quality of life. This study aimed to translate the English version of the Shame and Stigma Scale (SSS) into Malay and validate the Malay version of the SSS (SSS-M) among cancer patients in Malaysia. Initially, concurrent translation and back translation of the SSS-M was performed, and face and content validity were assessed. Then, the SSS-M was administered to a total of 234 patients of mixed types of cancer to assess its reliability (internal consistency and test-retest reliability), construct validity (convergent and discriminant validity), exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). The SSS-M total score registered good internal consistency (Cronbach’s α of 0.886) and test-retest reliability (intraclass correlation coefficient of 0.846, p < 0.001). EFA and CFA confirmed that the SSS-M consisted of 20 items in 5 domains. Its convergent and discriminant validity were achieved. Hence, the SSS-M demonstrated good psychometric properties and is available for use to assess stigma among cancer patients in Malaysia.

Steam Generator Level Control System (SGLCS) is one of the key instrumentations and control subsystems to ensure the safe operation of nuclear power plants. It is highly recommended to perform reliability analysis for SGLCS for making better maintenance strategy. SGLCS is a digital control system with complex redundant configuration and failure\self-diagnosis\repair action, traditional fault tree is not applicable due to its static property, Markov model is not a good choice too because of heavy burden of creating state transition graph for even medium-size system. Boolean Logic Driven Markov Process (BDMP) can describe complex failure-repair state transition via ‘trigger link’ and three kinds of leaf nodes, as well as keep compact and easy-read struct like fault tree. So BDMP is adopted to analysis reliability of SGLCS. Graphical BDMP modeling environment KB3 and Monte Carlo simulator YAMS is used for BDMP modeling and quantitative analysis respectively, and unavailability of SGLCS is obtained. The contribution of three parts of SGLCS to the unavailability of the system is also evaluated, and it is found that the water supply flow control part contributes the most to the failure of SGLCS.

The fault diagnosis of safety critical systems such as wind turbine installations includes extremely challenging aspects that motivate the research issues considered in this paper. In fact, the prompt detection and the reliable diagnosis of faults in their earlier occurrence represent the key point especially for offshore installations. For these plants, operation and maintenance procedures in harsh environments would inevitably increase the cost of the energy production. Therefore, this work investigates fault diagnosis solutions that are considered in a viable way and used as advanced techniques for condition monitoring of dynamic processes. To this end, the work proposes the design of fault diagnosis strategies that exploit the estimation of the fault by means of data--driven approaches. This solution leads to the development of effective methods allowing the management of partially unknown information of the system dynamics, while coping with measurement errors, the model--reality mismatch and other disturbance effects. In mode detail, the proposed data--driven methodologies exploit fuzzy systems and neural networks in order to estimate the nonlinear dynamic relations between the input and output measurements of the considered process and the faults. To this end, the fuzzy and neural network structures are integrated with auto--regressive with exogenous input descriptions, thus making them able to approximate unknown nonlinear dynamic functions with arbitrary degree of accuracy. Once these models are estimated from the input and output data measurement acquired from the considered dynamic process, the capabilities of their fault diagnosis capabilities are validated by using a high--fidelity benchmark that simulates the healthy and the faulty behaviour of a wind turbine system. Moreover, at this stage the benchmark is also useful to analyse the robustness and the reliability characteristics of the developed tools in the presence of model--reality mismatch and modelling error effects featured by the wind turbine simulator. On the other hand, a hardware--in--the--loop tool is finally implemented for testing and comparing the performance of the developed fault diagnosis strategies in a more realistic environment and with respect to different fault diagnosis approaches.

In this paper, the power quality of interconnected microgrids is managed using a Model Predictive Control (MPC) methodology which manipulates the power converters of the microgrids in order to achieve the requirements. The control algorithm is developed for the microgrids working modes: grid-connected, islanded and interconnected. The results and simulations are also applied to the transition between the different working modes. In order to show the potential of the control algorithm, a comparison study is carried out with classical Proportional-Integral Pulse Width Modulation (PI-PWM) based controllers. The proposed control algorithm not only improves the transient response in comparison with classical methods but also shows an optimal behavior in all the working modes, minimizing the harmonics content in current and voltage even with the presence of non-balanced and non-harmonic-free three-phase voltage and current systems

In our previous study, a novel barrier processing on a porous low-dielectric constant (low-k) film was developed: an ultrathin Mn oxide on a nitrogen-stuffed porous carbon-doped organosilica film (p-SiOCH(N)) as a barrier of the Cu film was fabricated. To form a better barrier Mn₂O_3-xN film, an additional annealing at 450°C was implemented. In this study, the electrical characteristics and reliability of this integrated Cu/Mn₂O_3-xN/p-SiOCH(N)/Si structure is investigated. The proposed Cu/Mn₂O_3-xN/p-SiOCH(N)/Si capacitors exhibited poor dielectric breakdown characteristics in the as-fabricted stage, although, less degradation was found after thermal stress. Moreover, its time-dependence-dielectric-breakdown electric-field acceleration factor slightly increased after thermal stress, leading to a larger dielectric lifetime in a low electric-field as compared to other MIS capacitors. Furthermore, its Cu barrier ability under electrical or thermal stress was improved. As a consequent, the proposed Cu/Mn₂O_3-xN/p-SiCOH(N) scheme is a promising integrity for back-end-of-line interconnects.

Some time ago, Kobayashi et al. experimentally studied the so-called Lee-Naughton-Lebed's (LNL) angular effect in strong electric fields [K. Kobayashi, M. Saito, E. Omichi, and T. Osada, Phys. Rev. Lett. \textbf{96}, 126601 (2006)]. They found that strong electric fields split the LNL conductivity maxima in $\alpha$-(ET)$_2$-based organic conductor and hypothetically introduced the corresponding equation for conductivity. In this Letter, for the first time we suggest quantum mechanical theory of the LNL angular oscillations in moderately strong electric fields. In particular, we demonstrate that the obtained by us approximate theoretical formula coincides with the hypothetical one and well describes the above mentioned experiments.

: The stability of semiconductor catalysts is a very important property in the field of catalytic reactions. Materials necessitate resistance to mechanical abrasion and chemical erosion for better overall performance. In this work, high crystallinity BiOCl nanosheets were prepared by a simple hydrothermal method. The photocatalysts demonstrate full UV light absorption ability and excellent photocatalytic norfloxacin degradation performance. 84 % of highly toxic norfloxacin were photocatalytically eliminated within 180 min. The internal structure and surface chemical state of BiOCl were analyzed by SEM, TEM, Raman, FTIR, UV-vis, XPS, and other techniques. Such high crystallinity makes BiOCl molecules closely arranged and the molecular chains strongly connected, thus exhibiting a high level of photocatalytic stability and recyclability.

UHPC is a type of cement-based composite used in new construction and/or rehabilitation of existing buildings to extend service life. It is a novel composite material that can serve as an alternative to concrete construction in hostile climates. Following decades of study and production, a diverse variety of commercial UHPC compositions are now available globally to meet the rising number of applicants and demand for high-quality building materials. Although UHPC offers major benefits over normal concrete, its utilization is restricted due to restrictive design rules and exorbitant costs. As a result, a thorough examination of the durability properties of UHPC is required to give important information for material testing requirements and processes, as well as to broaden its practical uses. This report is aimed at increasing basic understanding of UHPC and supporting more UHPC research and applications.

The dependence of the critical temperature $T_c$ of high-temperature superconductors of various families on their composition and structure is proposed. A clear dependence of the critical temperature of high-temperature superconductors (hydrides, Hg- and Y-based cuprates) on the serial number of the constituent elements, their valence and crystal lattice structure has been revealed. For cuprates, it is shown that it is possible to obtain even higher temperatures of superconducting transitions at normal pressure by implanting mercury atoms into the crystal lattice of cuprate.

The oral cavity harbors hundreds of microbial species that are present either as planktonic cells, or incorporated into biofilms. The majority of the oral microbes are commensal organisms. Those that are pathogenic microbes can result in oral infections, and at times initiate systemic diseases. Biofilms that contain pathogens have been challenging to control. Many conventional antimicrobials have proven to be ineffective. Recent advances in science and technology are providing new approaches for pathogen control and containment and methods to characterize biofilms. This perspective provides: 1) A general understanding of biofilm development; 2) A description of emerging chemical and biological methods to control oral biofilms; 3) An overview of high-throughput analytical approaches to analyze biofilms.

The management of the electrical energy still raises a huge interest for end-users at the household level. Home electricity management systems (HEMS) have recently emerged both to warrant uninterruptible power and high power quality, and to decrease the cost of electricity consumption, by either shifting it in off peak time or smoothing it. Such a HEMS requires a bidirectional DC-AC converter, specifically when an energy transfer is required between a storage system and the AC-grid, and vice versa. This article points out the relevance of an innovative topology based on sinusoidal waveforms from the generation of sine half-waves. Such a topology is based on a DC-DC stage equivalent to an adjustable output voltage source and a DC-AC stage (H-bridge) which are in series. The results of a complete experimental procedure prove the feasibility to improve the power quality of the output signals in terms of total harmonic distortion (THD-values about 5%). The complexity of the proposed converter is minimized in comparison with multilevel topologies. Finally, wide band-gap semiconductor devices (SiC MOSFETs) are helpful both to warrant the compactness and the high efficiency (about 96%) of the bidirectional converter, whatever its operation mode (inverter or rectifier mode).

This paper presents a hybrid probability distribution known as the FCD, which is based on the hazard functions of the Fréchet and Chen distributions. A notable characteristic of the FCD is its ability to model monotonic (increasing and decreasing) and non-monotonic (bathtub-shaped) behaviors, commonly linked to electrical and electronic device failure times in reliability analysis. The paper explores the statistical properties relevant to the reliability analysis of these devices. It proposes a Maximum Likelihood Estimator (MLE) and Bayesian Analysis equations for estimating the parameters of the FCD. Three case studies of electronic device lifetimes with varying behaviors were analyzed to validate the proposed methodology. The FCD was compared to other distributions with similar characteristics, and the results from each case study demonstrated that the proposed distribution yields competitive outcomes, closely reflecting the behavior of the devices analyzed, making it a valuable option for reliability engineering practitioners in warranty and maintenance time evaluations

Localizing faults in a software is a tedious process. The manual approach is becoming impractical because of the large size and complexity of contemporary computer systems as well as their logs, which are often the primary source of information about the fault. Log-based Fault Localization (LBFL) is a popular method applied for this purpose. However, in real-world scenarios, this method is vulnerable to a large number of previously unseen log lines. In this paper, we propose a novel method that can guide programmers to the location of a fault by creating a hierarchy of log lines with the highest rank, selected by the traditional LBFL method. We use the intuition that the symptoms of faults are in the context of normal behavior, whereas suspicious log lines grouped together are from new or additional functionalities turned on during faulty execution. To obtain this context, we used unsupervised log sequence segmentation, which has been previously used to segment log sequences into meaningful segments. Experiments on real-life examples show that our method reduces the effort to find the most crucial logs by up to 64% compared to the traditional timestamp approach. We demonstrated that context is highly useful in advancing fault localization, showing the possibility of further speeding up the process.

State-of-the-art augmented-reality (AR) glasses record their position and orientation in space, enabling measurements and analyses of clinical gait-and-balance tests. This study’s objective was to evaluate concurrent validity and test-retest reliability for common clinical gait-and-balance tests in people with Parkinson’s disease: the Five Times Sit-To-Stand (FTSTS) and Timed Up-and-Go (TUG) tests. Position and orientation data was collected in 22 participants with Parkinson's disease using HoloLens 2 and Magic Leap 2 AR glasses, from which test-completion durations and durations of distinct sub-parts (e.g., sit-to-stand, turning) were derived and compared to reference systems and over test repetitions. Regarding concurrent validity, for both tests an excellent between-systems agreement was found for position and orientation time series and test-completion durations. Between-systems agreement for FTSTS (sub-)durations were all excellent, while TUG turning sub-durations were excellent (turn 1) and moderate (turn 2). Regarding test-retest reliability, the within-system test-retest variation in test-completion times and sub-durations was always much greater than the between-systems variation, implying that these (sub-)durations may be derived interchangeably from AR and reference-system data. In conclusion, AR data are of sufficient quality to evaluate gait and balance in people with Parkinson's disease, with valid quantification of test-completion durations and sub-durations of distinct FTSTS and TUG sub-parts.

With the engineering system becoming more and more complex, the uncertainty factors have a more and more profound influence on the reliability and security of the engineering system. In recent years, Reliability-Based Design Optimization (RBDO) has been studied extensively in complex engineering system design. The research on reliability optimization design considering stochastic uncertainty has been comprehensive and widely used. However, the reliability optimization design considering mixed uncertainty has the disadvantages of large computation and imprecise convergence. This study proposes an RBDO method based on Particle Swarm Optimization (PSO) and Simulated Annealing (SA) to overcome this challenge. In the method, PSO is used to solve the most probable point, while SA has excellent global optimization capability to acquire the global optimal solution. Finally, three examples are given to illustrate the advantages of the proposed method.

Quantification of bone loss for follow-up comparisons has not been routinely performed in patients with parietal thinning so far. This study compares different methodological approaches including both 2- and 3-dimensional methods in computerized tomographies of a single patient. The 2-dimensional method provides accurate measurements of bone thickness, while the 3-dimensional method allows for a more comprehensive view of the bone's structure, including parameters like shape, size, and thickness. The techniques provided valuable data for the treating physician and suggest a possible effect of corticosteroids in this individual patient. The study concludes that 3-dimensional reconstruction of computerized tomographies with subsequent 2-dimensional analyses appears justified for routine radiological practice to increase clinical awareness of the size of the parietal bone defects and allow for quantification of bone loss during long-term follow-ups. Further validation of the proposed analytical approaches is warranted in larger studies to investigate patterns of bone thinning across the skull and changes in bone volumes over time, with specialized software to be approved for such analyses.

Software reliability is an important characteristic for ensuring the qualities of software products. Predicting the potential number of bugs from the beginning of a development project allows practitioners to make the appropriate decisions regarding testing activities. In the initial development phases, applying traditional software reliability growth models (SRGMs) with limited past data does not always provide reliable prediction result for decision making. To overcome this, herein we propose a new software reliability modeling method called deep cross-project software reliability growth model (DC-SRGM). DC-SRGM is a cross-project prediction method that uses features of previous projects’ data through project similarity. Specifically, the proposed method applies cluster-based project selection for training data source and modeling by a deep learning method. Experiments involving 15 real datasets from a company and 11 open source software datasets show that DC-SRGM can more precisely describe the reliability of ongoing development projects than existing traditional SRGMs and the LSTM model.

Enhancing the degree of functional multiplexing while assuring operational reliability and manufacturability at competitive costs are crucial ingredients for enabling comprehensive sample-to-answer automation, e.g., for use in common, decentralized “Point-of-Care” or “Point-of-Use” scenarios. This paper demonstrates a model-based ‘digital twin’ approach which efficiently supports the algorithmic design optimization of exemplary centrifugo-pneumatic (CP) dissolvable-film (DF) siphon valves towards larger-scale integration (LSI) of well-established “Lab-on-a-Disc” (LoaD) systems. Obviously, the spatial footprint of the valves and their upstream laboratory unit operations (LUOs) have to fit, at a given radial position prescribed by its occurrence in the assay protocol, into the locally accessible disc space. At the same time, the retention rate of a rotationally actuated CP-DF siphon valve and, most challenging, its band width related to unavoidable tolerances of experimental input parameters, need to slot into a defined interval of the practically allowed frequency envelope. To accomplish particular design goals, a set of parametrized metrics is defined, which are to be met within their practical boundaries while (numerically) minimizing the band width in the frequency domain. While each LSI scenario needs to be addressed individually on the basis of the digital twin, a suite of qualitative design rules and instructive showcases structures are presented.

An attractive option for realizing applications in radiation environments is to employ All-Programmable System-on-Chips (APSoCs) thanks to their high-performance computing and power efficiency merits. Despite APSoC's advantages, like any other electronic device, they are prone to radiation effects. Processors found in APSoCs must, therefore, be adequately hardened against ionizing-radiation to become a viable alternative for harsh environments. This paper proposes a novel triple-core lockstep (TCLS) approach to secure the Xilinx Zynq-7000 APSoC dual-core ARM Cortex-A9 processor against radiation-induced soft errors by coupling it with a MicroBlaze TMR subsystem in Zynq's programmable logic (PL) layer. The proposed strategy uses software-level checkpointing principles along with roll-back and roll-forward mechanisms (i.e. software redundancy), and hardware-level processor replication as well as checker circuits (i.e. hardware redundancy). Results of fault injection experiments show that the proposed solution achieved high soft error security by mitigating about 99% of bit-flips injected into both ARM cores' register data.

Adaptive mechanisms, such as channel hopping and packet replication, are used in low-power wireless networks to deal with the spatial and temporal variations in the link quality, and meet the reliability requirements of industrial applications (i.e., PDR>99%). However, the benefits of such mechanisms are limited and may have a large impact on end-to-end latency and energy consumption. Hence, in this paper we propose using adaptive modulation diversity, which allows to dynamically select different modulations, to improve link reliability. We present three adaptive modulation diversity selection strategies and validate them using the data derived from a real-world deployment using the IEEE 802.15.4g SUN modulations (i.e., SUN-FSK, SUN-OQPSK and SUN-ODFM) in an industrial environment. The results show that by using adaptive modulation diversity it is possible to improve link reliability regardless of node conditions.

Based on the topology of wide area protection system (WAPS), after studying the reliability of hardware system and information flow in the WAPS and establishing the reliability assessment model, the multi-service reliability analysis method with multi monitoring and protection tasks in WAPS was proposed. In the model, the impact of network quality of service (QoS) such as information flow loss and delay, is studied. On the base of the model, the multi-service reliability evaluation method is employed to analyze the reliability of a WAPS of IEEE14 node power system, and the key nodes of the WAPS is given, which provides a basis for improving the reliability of the WAPS.

Energy-efficient microprocessors are essential for a wide range of applications. While near-threshold computing is a promising technique to improve energy efficiency, optimal supply demands from logic core and on-chip memory are conflicting. In this paper, we perform static reliability analysis of 6T SRAM and discover the variance among different sizing configuration and asymmetric minimum voltage requirements between read and write operations. We leverage this asymmetric property in near-threshold processors equipped with voltage boosting capability by proposing an opportunistic dual-supply switching scheme with a write aggregation buffer. Our results show that proposed technique improves energy efficiency by more than 21.45% with approximate 10.19% performance speed-up.

Nowadays, the research and development of on-chip LiDAR sensors for vehicle collision avoidance is growing very fast. Therefore, the assessment of the reliability in obstacle detection using the information provided by LiDAR sensors has become a key issue to be explored by the scientific community. This paper presents the design and implementation of a self-tuning method in order to maximize the reliability of an Internet-of-Things sensors network and to minimize the number of sensors to localize with the required accuracy obstacles by a detection threshold. In order to achieve this goal, models that predict accuracy (i.e., prediction error) for object localization using data collected by LIDAR sensors are designed and implemented in Webots Automobile 3D simulation tool. The approach is based on combining different techniques. Firstly, point-cloud clustering technique and an error prediction model library composed by a multilayer perceptron neural network with backpropagation, k-nearest neighbors and linear regression are explored. Secondly the above-mentioned techniques for modeling are also combined with a supervised and reinforcement machine learning technique, Q-learning in order to minimize the detection threshold. In addition, a IoT driving assistance simulated scenario with a LiDAR sensor network is designed in order to validate the prediction model and the optimal configuration of the sensor network to guarantee reliability in obstacle localization. The results demonstrate that the self-tuning method is appropriate to increase the reliability of the sensor network whereas minimizing the detection threshold

Ultrasonic imaging & NDE applications can greatly improve their signal-to-noise ratios (SNR) by driving each transducer (composing piezoelectric arrays) with a spike giving pulsed power of k-Watts, repetitively at a PRF = 5000 spikes/s, by using a HV capacitive-discharge generator. However very-high levels, of pulsed intensities (3-10 A) and voltages (300-700 V) must be considered for a rigorous spike modeling. Even though the consumed "average" power will be small, the intensity through each transducer achieves several amperes, so the pulsed powers delivered by each HV generator can attain levels higher than in CW high-power ultrasonic applications: e.g., up to 5 kW / spike. This is concluded here from a transient modeling of the loaded generator. Then, unforeseen phenomena rise: intense brief pulses of driving power & emitted force in transducers, and non-linearities in driver semiconductors, because their characteristic curves only include linear ranges. But fortunately, piezoelectric devices working in this intense regime do not show serious heating problems, because the average power remains being moderate. Intensity, power and voltage, driving a broadband transducer from a HV capacitive pulser, are calculated to drastically improve (in ≅ 40 dB) the ultrasonic net dynamic range available, with emitted forces ≅ 250 Newtons pp and E/R received pulses of 70 V pp.

In veterinary medicine, the significance of High-Density Lipoprotein (HDL) measurements is not well-documented than it is in humans. The HDL level can be measured in dogs, and through referring to the normal range, it is possible to find out what this means for various endocrine diseases and hyperlipidemia diseases. Aim of this study is to measure the HDL levels in dogs with various conditions and to evaluate whether the Total Cholesterol (TC), HDL ratio is effective as a prognostic indicator in various hyperlipidemia and endocrine diseases. Through prospective clinical trial, sixteen client-owned dogs and cats visiting a local private practice were divided into three groups; five dogs without hyperlipidemia or metabolic disease (Group 1); eight animals with Cushing's, hypothyroidism, and gallbladder sludge (Group 2) and three diabetics, urinary disorders, and healthy cats (Group 3). In two dogs, the TC/HDL values were between 2 and 3; in two dogs, the values were between 3 and 4; in two dogs, the values were between 4 and 5. In three dogs, the TC/HDL values were between 5 and 6 and in three dogs, the ratio values were between 6 and 7. The other value was higher than 8. Except two dogs which showed lower value than 3, all dogs had concurrent endocrine disease including Cushing’s disease, hypothyroidism, gall bladder mucocele, hyperlipidemia. There was a difference in each group in terms of the TC/HDL value compared to the group with underlying disease. This means that TC/HDL values can be an excellent indicator of endocrine disease in dogs as well. In cats, although this is a very small sample, a high TC/HDL value of 9 points are shown in the cat which had diabetes mellitus. However, for more statistically significant results, a larger sample group for further investigation is needed.

Hypertension is one of the most common primary cardiometabolic diseases and is a major contributor to cardiac mortality and morbidity. Furthermore, cardiac risk factors such as obesity and sedentary lifestyle are often seen in hypertensive patients. Regular exercise acts against these risk factors and improves the overall health of an individual. High-intensity interval training appears to do so in a more efficient way. We used a systematic literature review (SLR) approach to provide an overview of the present literature highlighting the cardiovascular advantages of HIIT in hypertensive individuals. We reviewed 4004 articles from reputable journals published between 2013 and August 14, 2023, focusing on 7 selected papers for in-depth analysis. This systematic review revealed the protective effects of HIIT against cardiac complications in hypertension. All the reviewed articles showed a decrease in blood pressure and many other risk variables of cardiovascular diseases. However, guidelines for this exercise are needed for maximum benefits. Therefore, further research on HIIT is necessary to fully harness its potential.

In order to create a smart mine, it is necessary to digitize the existing emulsion pumping station. Existing research does not achieve this task, this paper designs and manufactures a high-pressure, high-flow, high-water-based mining digital controlled unloading valve (abbreviated as HLHMDCUV), which achieves good results in both theoretical analysis and experimental testing. In order to obtain the accurate dynamic characteristics, this valve was analyzed by simulation using AMESim. Based on the dynamic performance analysis and the flow field analysis inside the valve body, the structure has been optimized to improve the performance of HLHMDCUV. The results show that the HLHMDCUV has a better dynamic characteristics, which were also demonstrated in the experiment. At the same time, the HLHMDCUV is easy to disassemble and maintain. This paper provides a theoretical basis for the design of such valves, which is conducive to the subsequent promotion of intelligent mine transformation.

Although many policosanols from different sources, such as sugar cane, rice bran, and insects, have been marketed worldwide, there has been no comparative study of the in vivo efficacy using a hyperlipidemic animal model. This study compared the efficacy of treating dyslipidemia with four different policosanols, including one sugar cane wax alcohol from Cuba (Raydel®) and three policosanols from China (Xi’an Natural sugar cane, Xi’an Realin sugar cane, and Shaanxi rice bran) in hyperlipidemic zebrafish. After 12 weeks of consumption of each policosanol (final 0.1% in diet, wt/wt) and high cholesterol diet (HCD, final 4%, wt/wt) in a tetrabit, the Raydel policosanol group and Xi’an Natural policosanol group showed the highest survivability of approximately 81%, whereas the Xi’an Realin policosanol group and Shaanxi policosanol group showed 57% and 67% survivability, respectively. Among five HCD groups, the Raydel policosanol group showed the lowest serum total cholesterol (TC, p<0.001 versus HCD control) and triglyceride (TG, p<0.001 versus HCD control) with the highest percentage of high-density lipoproteins (HDL)-C in TC. The Raydel policosanol group also showed the lowest serum aspartate aminotransferase (AST) and alanine aminotransferase (ALT) levels with the least infiltration of inflammatory cells and interleukin-6 production in hepatocytes. In the ovary, the Raydel policosanol group also showed the highest contents of mature vitellogenic oocytes with the lowest production of reactive oxygen species and cellular apoptosis in ovarian cells. In the testis, the Raydel policosanol group also showed the healthiest morphology for spermatogenesis with the least interstitial area and reactive oxygen species (ROS) production in testicular cells. In conclusion, 12 weeks of Raydel policosanol consumption resulted in remarkable improvement of the blood lipid profile, amelioration of inflammation in the liver, and enhancement of the cell morphology in the ovary and testis with the highest survivability under the HCD.

The poor oxidation resistance of refractory high-entropy alloys (RHEAs) is a major obstacle for their use in high-temperature engineering applications. Anti-oxidation coating technology is an effective method for improving the oxidation resistance. In this paper, the Si-20Cr-20Fe coating was prepared on MoNbTaTiW RHEA by a fused slurry method. The microstructural evolution and compositions of the silicide coating under high-temperature oxidation environment were studied. The results show that the silicide coating could effectively prevent the oxidation of the MoNbTaTiW RHEA. The initial silicide coating had a double-layer structure; a high silicon-content layer mainly composed of MSi2 as the outer layer and a low silicon-content layer mainly contained M5Si3 as the inner layer. Under high-temperature oxidation conditions, the silicon element diffused from the silicide coating to the RHEA substrate while the oxidation of the coating occurred. After oxidation, the coating was composed of an outer oxide layer and an inner silicide layer. The silicide layer moved toward the inside of the substrate, led to the increase of its thickness. Compared with the initial silicified layer, its structure did not change significantly. The structure and compositions of the oxide layer on the outer surface strongly depended on the oxidation temperature. This paper provides a strategy for protecting RHEAs from oxidation at high-temperature environments.

The purpose of this study was to conduct a meta-analysis that shows the influence of fiber on ultimate compressive strength and tensile strength of ultra-high performance concrete. The internet scholarly search engines and ScienceDirect article references were used to illustrate the papers concerning the experimental investigations of mechanical properties of ultra-high strength concrete with and without fiber with clearly, completely and comparative raw data. The normal concrete test results were dismissed from this search. Seven trials were identified based on the adopted inclusion and exclusion criteria above. The meta-analysis based on standardized mean difference was carried out on the basis of a fixed-effects model for the major outcomes of the ultimate compressive and tensile properties of ultra-high performance concrete. A total of 888 test specimens were enrolled in these seven trials. The combined analysis yielded a sign of a significant improvement in ultimate compressive strength and tensile strength of ultra-high strength concrete with fiber addition of 2% by concrete volume. The summary effect size of ultimate compressive strength was 2.34 while a more improvement in term of tensile strength with effect size of 2.64. By addition fiber of 2% provides a significant benefit in mechanical properties of ultra-high performance concrete.

With the existence of several programming languages such as C/C++, Java, C#, LISP, Prolog, Python, Simula, F#, Go, Haskell, Scala, Ruby, Dart, Swift, Groovy etc. and diverse paradigms like structured, object-oriented, list, aspect-oriented, service-oriented, web, mobile and logic programming, there is a need to perform an exhaustive comparative analysis of diverse compilers and environments before making a choice of implementation technology in software engineering. Optimization of compilers helps to reduce execution time by making use of high speed processor registers, thereby, eliminating redundant computation. This paper reports some series of performance analysis done with some popular programming languages including Java, C++, Python and PHP. Programs involving recursive and iterative functions like factorial of large numbers and binary search of large arrays were run on the various platforms with the execution time recorded in milliseconds and represented in a chart. This can aid in making a selection of the appropriate language to use for a given application domain.

Acute high altitude illnesses are of great concern for physicians and people traveling to high altitude. High Altitude Pulmonary Edema (HAPE) can be better understood through the Oxygen Transport Triad which involves the Pneumo-Dynamic Pump (Ventilation), the Hemo-Dynamic Pump (Heart and circulation), and Hemoglobin. The two pumps are the first physiologic response upon initial exposure to hypobaric hypoxia. Hemoglobin is the balancing energy-saving time-evolving equilibrating factor. The increased hemoglobin at high altitude reduces the percentage of dissolved oxygen in the arterial oxygen content with respect to sea level. At high altitude, the acid-base balance must be adequately interpreted using the high altitude Van-Slyke correction factors. Pulse-oximetry measurements during breath-holding at high altitude allow for the evaluation of high altitude diseases. The Tolerance to Hypoxia Formula shows that, paradoxically, the higher the altitude the more tolerance to hypoxia. All organisms adapt physiologically and optimally to a high-altitude environment to survive. Reduction of pulmonary hypertension in HAPE through oxygen administration results in a favorable outcome.

The main source of electricity worldwide stems from fossil fuels, contributing to air pollution, global warming, and associated adverse effects. This study explores wind energy as a potential alternative. Nevertheless, the variable nature of wind introduces uncertainty in its reliability. Thus, it is necessary to identify an appropriate machine learning model capable of reliably forecasting wind speed under various environmental conditions. This research compares the effectiveness of artificial neural networks (ANN) and convolutional neural networks (CNN) in predicting wind speed across three locations in South Africa, characterised by different weather patterns. Empirical results show that CNN outperforms ANN in accurately forecasting wind speed under different weather conditions. This superiority is likely due to the inherent architectural attributes of CNNs, including feature extraction capabilities, spatial hierarchy learning, and resilience to spatial variability. These results could be useful to decision-makers in the energy sector.

Accounting studies neglected to link corporate social responsibility to accounting information, the theoretical background revealed the study gap and the paper referred to it in the question: Do the corporate social responsibility CSR dimensions affect the accounting information quality? as the study aimed to reveal the effect of corporate social responsibility dimensions (economic, ethical, legal, and philanthropic) on accounting information quality (relevance and reliability) in banks in the Riyadh Governorate in Saudi Arabia. The researcher used a questionnaire to collect data from the study sample, and the data analysis was done using SPSS and smart partial least squares (pls), and its reliability and validity have been confirmed. Result revealed a positive effect of CSR (economic, ethical) dimension on the relevance of accounting information, a negative effect of CSR Legal dimension on the relevance of accounting information, and no effect of CSR philanthropic dimension on the relevance of accounting information, a positive effect of CSR (ethical, philanthropic) dimension on the reliability of accounting information and no effect of CSR economic and legal dimension on the reliability of accounting information.

Artificial intelligence (AI)-based conversational models, such as ChatGPT, Microsoft Bing, and Google Bard, emerged as valuable sources of health information for the lay individuals. However, the accuracy of information provided by these AI models remains a significant concern. This pilot study aimed to test a new tool referred to as “CLEAR”, designed to assess the quality of health information delivered by AI-based models. Tool development involved a literature review on health information quality, followed by initial establishment of the CLEAR tool comprising five items that aimed to assess the following: completeness of content in response to the prompt, lack of false information, evidence support, appropriateness, and relevance of the generated content. Each item was scored on a 5-point Likert scale from excellent to poor. Content validity was checked by expert review of the initial items. Pilot testing involved 32 healthcare professionals using the CLEAR tool to assess content on eight different health topics deliberately designed with varying qualities. The internal consistency was checked using the Cronbach α. Feedback through the pilot test resulted in language modifications to improve the clarity of the items. The final CLEAR tool was used to assess health information quality generated through four different AI-based models in five different, yet common health topics. The AI models were ChatGPT 3.5, ChatGPT 4, Bing, and Bard, and the content generated was scored by two independent raters with Cohen κ to assess the inter-rater agreement. The final five CLEAR items were: (1) Is the content sufficient? (2) Is the content accurate? (3) Is the content evidence-based? (4) Is the content clear, concise, and easy to understand? and (5) Is the content free from irrelevant information? Pilot testing using the eight different health topics revealed an acceptable internal consistency with a Cronbach α range of 0.669–0.981. The use of the final CLEAR tool yielded the following average scores: Bing (mean=24.4±0.42), ChatGPT-4 (mean=23.6±0.96), Bard (mean=21.2±1.79), and ChatGPT-3.5 (mean=20.6±5.20). The inter-rater agreement revealed the following Cohen κ values: for ChatGPT-3.5 (κ=0.875, P<.001), ChatGPT-4 (κ=0.780, P<.001), Bing (κ=0.348, P=.037), and Bard (κ=.749, P<.001). The CLEAR tool is a brief yet helpful tool that can aid to standardize testing of the quality of health information generated by the AI-based conversational models. Future studies are recommended to validate the utility of the CLEAR tool to assess the quality of the AI-generated health-related content using a larger sample across various complex health topics.

This paper utilizes a life cycle assessment to evaluate the energy resources and environmental impacts of three heating systems. In the first step, life cycle assessments (LCAs) are prepared for the renewable, conventional, and combined systems. The system boundary of the LCA method is "cradle to gate," which means it includes the entire life cycle of a product or process. This includes energy supply, transport, energy generation, and operational energy use. The system scenarios were compared based on ecological and energy loads in the second step. Primary energy, resources, emissions, and environmental potentials are calculated for the system scenarios using the life cycle assessment methods CML 2016 and ReCiPe 2016. Finally, models for environmental reliability and complex decision-support tools have been developed. This work addresses two main questions: how to characterize the environmental and energy impacts of the systems under study, and what is the optimal scenario for the system? The research results show that the gas boiler system has a greater environmental impact. The most significant differences between the systems relate to the degrada-tion of abiotic fossil fuels when using a gas boiler and the process of acidification when using an electric heat pump. The results can be used to develop sustainable heating systems with reduced environmental impacts and enhanced energy efficiency.

In this paper, stochastic multi-objective intelligent framework (MOIF) is performed for distribution network reconfiguration to minimize power losses, the number of voltage sags, the system's average RMS fluctuation, the average system interruption frequency (ASIFI), the momentary average interruption frequency (MAIFI), and the system average interruption frequency (SAIFI) considering the network uncertainty. The unscented transformation (UT) approach is applied to model the demand uncertainty due to simplicity to implement and no presumptions to simplify. A human-inspired intelligent method named improved mountaineering team-based optimization (IMTBO) is applied to determine the decision variables defined as the network's optimal configuration. The conventional MTBO is improved using a quasi-opposition-based learning strategy to overcome premature convergence and achieve the optimal solution. The simulation results showed that in single- and double-objective optimization, some objectives are weakened compared to their base value, while the results of the MOIF indicated a fair compromise between different objectives, and all objectives are improved. The results of MOIF based on the IMTBO cleared that the losses are reduced by 30.94%, the voltage sag numbers and average RMS fluctuation are reduced by 33.68% and 33.65%, and also ASIFI, MAIFI, and SAIFI are improved by 6.80%, 44.61%, and 0.73%, respectively. Also, the superior capability of the MOIF based on the IMTBO is proved compared to the conventional MTBO, particle swarm optimization, and artificial electric field algorithm. Moreover, the results of the stochastic MOIF based on the UT showed the power loss increased by 7.62%, voltage sag, and SARFI increased by 5.39% and 5.31%, and ASIFI, MAIFI, and SAIFI weakened by 2.28%, 6.61%, and 1.48%, respectively compared to the deterministic MOIF model.

Centrifugal pumps are widely employed in the oil refinery industry due to their efficiency and effectiveness in fluid transfer applications. The reliability of pumps plays a pivotal role in ensuring uninterrupted plant productivity and safe operations. Analysis of failure history data shows that bearings have been identified as critical components in oil refinery pump groups. However, traditional reliability estimation theories may not apply when data is limited or subject to right censoring. This paper addresses the complexity of estimating the Weibull distribution parameters using the maximum-likelihood method under the abovementioned conditions. The likelihood equation lacks an explicit analytical solution, necessitating the use of numerical methods for resolution. The proposed approach presented in this article leverages the Expectation-Maximization (EM) algorithm for estimating the Weibull distribution parameters. This method provides more accurate estimates of failure rates and probabilities by accounting for limited and censored data. The findings are demonstrated through a case study, showcasing the practical application of the proposed approach.

(1) Background: The mediolateral patella displacement is of interest for diagnostics and clinically relevant research questions. Apart from manual testing, no standardized method is currently available. Proper quantification of patella mobility is necessary to understand pathologies at the patellofemoral joint better; (2) Methods: Patella mobility was assessed in 25 healthy individuals using a Patellostabilometer, a new prototype instrument for quantification of the mediolateral patella displacement. The participants underwent measurements of the mediolateral displacement three times using the Patellostabilometer. A maximal force of 10N was applied for patella movement. Additionally, leg length, circumference of the knee, upper- and lower leg was measured. (3) Results: Lateral patella displacement of 18.27±3.76 mm (range 15.85-20.64mm, interquartile range (IQR) of 4.79) was measured. The medial patella displacement showed 24.47±6.59mm (range 19.29-29.76mm, IQR of 10.47). The test-retest measurement error was 2.32±1.76mm (IQR of 2.38mm), with five outliers. There was greater test-retest variability between the measurements of the medial displacement comparing to the lateral one (4) Conclusions: The test-retest variability reached 7% of the patella displacement. Other parameters provided no significant correlations. Based on the natural patellofemoral mobility a precise and clinically relevant quantification of patella mobility is allowed.

The Performance Assessment for California Teachers (PACT) is a high stakes summative assessment that was designed to measure pre-service teacher readiness. We examined the inter-rater reliability (IRR) of trained PACT evaluators who rated 19 candidates. As measured by Cohen’s weighted kappa, the overall IRR estimate was .17 (poor strength of agreement). IRR estimates ranged from -.29 (worse than expected by chance) to .54 (moderate strength of agreement); all were below the standard of .70 for consensus agreement. Follow up interviews of 10 evaluators revealed possible reasons we observed low IRR, such as departures from established PACT scoring protocol, and lack of, or inconsistent, use of a scoring aid document. Evaluators reported difficulties scoring the materials that candidates submitted, particularly the use of Academic Language. Cognitive Task Analysis (CTA) is suggested as a method to improve IRR in the PACT and other teacher performance assessments such as the edTPA.

The oil and gas sector has recognised structural integrity assessment of ageing platform for prospective life extension as a rising concern, particularly in encountering the randomness of the harsh ocean environments. This condition leads to uncertainty in wave-in-deck load estimates and a high load level being imposed on offshore structures. This emphasises the necessity of enhanced reliability, as failure might result in inaccessibility because of the uncertainties related to long-distance services, such as accuracy of predictions of loads and responses. Even though the established guidelines present a fundamental assessment, additionally, comprehensive rules are required. This paper performed a reliability analysis incorporating practical approaches that can more accurately represent time-dependent structural deterioration. The following two procedures have been adopted by a majority of significant oil and gas operators to monitor the safety and integrity of these structures: a) Ultimate Strength Assessment (USA) method and b) Reliability Design Assessment (ReDA) method. A comparison of these two reliability approaches was performed on selected ageing jacket structures in the region of the Malaysian sea. The comparative findings, namely, reserve strength ratio (RSR) at various years of the return period (RP) and ratio value for risk of failure regarding the probability of failure (POF), provided a check and balance in strengthening confidence in the results. The findings showed that the structural components might safely survive either using the USA and ReDA method in such conditions, as the reliability indexes were determined to be satisfactory compared to allowable values from ISO 19902 design specifications. Therefore, these evaluations were determined to control the risk level of the structure during the remaining of its lifetime and undertake cost-effective inspections or mitigation strategies when necessary.

An iterative outlier elimination procedure based on hypothesis testing, commonly known as Iterative Data Snooping (IDS) among geodesists, is often used for the quality control of the modern measurement systems in geodesy and surveying. The test statistic associated with IDS is the extreme normalised least-squares residual. It is well-known in the literature that critical values (quantile values) of such a test statistic cannot be derived from well-known test distributions, but must be computed numerically by means of Monte Carlo. This paper provides the first results about Monte Carlo-based critical value inserted to different scenarios of correlation between the outlier statistics. From the Monte Carlo evaluation, we compute the probabilities of correct identification, missed detection, wrong exclusion, overidentifications and statistical overlap associated with IDS in the presence of a single outlier. Based on such probability levels we obtain the Minimal Detectable Bias (MDB) and Minimal Identifiable Bias (MIB) for the case where IDS is in play. MDB and MIB are sensitivity indicators for outlier detection and identification, respectively. The results show that there are circumstances that the larger the Type I decision error (smaller critical value), the higher the rates of outlier detection, but the lower the rates of outlier identification. For that case, the larger the Type I Error, the larger the ratio between MIB and MDB. We also highlight that an outlier becomes identifiable when the contribution of the measures to the wrong exclusion rate decline simultaneously. In that case, we verify that the effect of the correlation between the outlier statistics on the wrong exclusion rates becomes insignificant from a certain outlier magnitude, which increases the probability of identification.

This study presents the validation process of the Questionnaire on Academic Stress in Secondary Education –QASSE-, designed to assess the wide variety of school sources and situations related to academic stress in adolescence, and their relationship with students’ physical and psychological well-being. Participants were 860 Spanish high school students (52.9% girls) with an average age of 14.62 years (SD = 1.8). Through a cross-validation process, EFA and CFA supported QASSE multifactorial structure with four first-order factors -academic overload, interaction with classmates, family pressure, and future-oriented perspective- and a second-order factor of academic stress, showing a significant and intense relationship with adolescents’ psychological and physical well-being. Results also highlight the effects of the gender*educational level interaction on the students’ stress, with girls showing higher levels of stress in the transition courses between educational phases (sophomore and junior years). The QASSE demonstrates good validity and reliability, showing potential for both research and educational application. The results show the high impact of the QASSE dimensions on psychological and physical well-being in adolescence, highlighting its special usefulness for designing and adjusting educational prevention and intervention actions in this area to the students’ specific characteristics and needs

This article investigates and studies the current situation of implementing the credit system in ordinary high schools in Zhejiang Province, and puts forward relevant suggestions. Firstly, analyze the background and objectives of implementing the credit system in ordinary high schools in Zhejiang Province. Then, through a questionnaire survey method, a sample survey was conducted on the current status of the implementation of the credit system in ordinary high schools in Zhejiang Province. The results showed that there are some problems in the management of the credit system in schools, such as unreasonable credit course settings, inaccurate recording and statistics of credits, etc. Further analysis reveals that students and parents have biases and utilitarian motives in their understanding and evaluation of the credit system.

When water molecules or other particles collide with protein molecules in a solution, the protein molecules absorb some of the momentum and deform, forming a certain molecular potential energy. When a protein molecule in a high-energy state changes to a stable state, if there is a suitable substrate binding and the potential energy of the protein molecule is greater than the energy required to break the substrate chemical bond, catalytic action will occur. The α-helices and β-folds in protein molecules play a major role in converting the kinetic energy of water molecules into their own potential energy due to the large number of amino acids involved and their regular structure. The internal structural deformation of proteins caused by the impact of water molecules on α-helices and β-folds also has a profound impact on the structure of substrates. ‌

Yttria stabilized zirconia materials are frequently used in mechanical engineering and biomedical applications. Demanding loading conditions require materials combining a high level of strength and fracture toughness. A ready to press alumina doped 2 mol% yttria stabilized zirconia powder was shaped by axial pressing and sintering in air at 1250 - 1500 °C for 2 h. The best combination of strength and toughness value of 7.8 MPa√m. Materials sintered in the middle of the chosen temperature range combine fully density, high transformability and small grain size. Toughness measurements by direct crack length measurements delivered unrealistically high fracture toughness values.

Background: Pulmonary embolism (PE) is a common multifactorial disease, but high-risk PE s a life-threatening condition associated with high mortality and morbidity and a heavy prognostic burden. Systemic thrombolysis is the first-line treatment approach for severe high-risk PE, but only few agents are indicated for use by international guidelines. Tenecteplase, a thrombolytic agent, is proven to reduce mortality and right ventricle dysfunction in high-risk PE, but is not approved yet by major recommendations. Aim: We present a series of cases of high-risk PE treated with Tenecteplase, with satisfying hemodynamic and clinical outcomes. Our goal is to encourage the usage of Tenecteplase with secure safety and efficacy in situations of unavailability of guidelines-approved fibrinolytic agents. Cases : Patients were included from January 2022 to January 2024. We report 3 cases of patients with high-risk PE treated with Tenecteplase where rtPA and other second-generations agents were not available. Clinical, biological and imaging data were detailed for each case. Conclusion: Tenecteplase was effective in our patients, without bleeding complications, and should be suggested in settings of unavailability of first-line recommended agents.

Advanced lithography requires highly sensitive photoresists to improve lithographic efficiency, and it is critical yet challenging to develop high-sensitivity photoresists and imaging strategies. Here, we report a novel strategy for ultra-high sensitivity using hexafluoroisopropanol (HFIP)-containing fluoropolymer photoresists. The incorporation of HFIP, with its strong electrophilic property and electron-withdrawing effect of the fluorine atoms, significantly increases the acidity of the photoresist after exposure, enabling imaging without conventional photoacid generators (PAGs). The HFIP-containing photoresist has been evaluated by electron beam lithography to achieve a trench of ~40 nm at an extremely low dose of 3 μC/cm2, which shows sensitivity enhancement by ~10 times to the commercial PAGs involved system, revealing its high-sensitivity and high-resolution features. Our results demonstrate a new type of PAGs and a novel approach to higher-performance imaging beyond conventional photoresist performance tuning.

The Antarctica and High Arctic regions are extreme environments, with average maximum temperatures below 0 °C for most days of the year. Interestingly, fungi inhabit these regions. This review describes the history of fungal surveys near the Syowa Station and the fungal diversity in this region. In the High Arctic region, I summarized the changes in fungal communities in glacial retreat areas of Ny-Ålesund, Norway and Ellesmere Island, Canada in response to climate change. In addition, growth and enzyme secretion ability of Antarctic and Arctic fungi at sub-zero temperatures are presented. Finally, I have also provided the future directions of Antarctic and Arctic fungal research.

Background of the Study: We investigated the link between hypertension and cancer since it has been suggested that hypertension may raise the long-term risk of cancer. Previous large observational cohort studies found that greater blood pressure (BP) was related to a higher risk of cancer. Mendelian randomization (MR) was utilized to produce less confounded blood pressure estimates (BP) on overall and site-specific malignancies. The study aims to draw conclusions on the relationship between high blood pressure and cancer. Methods: Studies on high blood pressure and various malignancies are inconclusive, except for renal cell carcinoma. However, given that most meta-analyses only contained a limited number of trials, some relative risks had small to moderate magnitudes, and several may have been impacted by residual confounding, careful interpretation is necessary. The study was conducted using the meta-analysis technique. Cochran's Q test and I2 test were used to assess statistical heterogeneity between studies in the current investigation for research involving two or more cause and outcome combinations. Results: Positive correlations were also reported between high blood pressure and esophageal adenocarcinoma, squamous cell carcinoma, liver, and squamous cell carcinoma. However, most studies lacked multivariable adjustments. Physical and numerical risk of cardiovascular disease is linked to bowel cancer but no other cancers. According to a meta-analysis, hypertensive persons could also be at increased danger of gastrointestinal and breast cancer. Most meta-analyses comprised several trials with moderate or mild hazard ratios.ConclusionDifferent types of cancers have been noted to be directly caused by hypertension. In addition, some treatments have also been associated with the side effects of cancer treatments to cause hypertension. Women facing hypertension have an increased risk of getting breast cancer. Although some cancers showed a real relationship with hypertension, others had no connection at all.

This research work studies the characteristics of wear and wear resistance of composite powder coatings, deposited by high-velocity oxygen fuel, which contain composite mixtures Ni-Cr-B-Si having different chromium concentrations – 9.9%; 13.2%; 14%; 16% and 20% , at one and the same size of the particles and the same content of the remaining elements. The coating of 20% Cr does not contain B and Si. Out of each powder, composite coatings have been prepared without any preliminary thermal treatment of the substrate and with preliminary thermal treatment of the substrate up to 650оС. The coatings have been tested under identical conditions of dry friction over a surface of solid firmly attached abrasive particles using the tribological testing device „Pin-on-disk“. Results have been obtained and the dependences of the hardness, mass wear, intensity of the wearing process, absolute and relative wear resistance on the Cr concentration under identical conditions of friction. It has been found out that for all the coatings the preliminary thermal treatment of the substrate leads to a decrease in the wear intensity. Upon increasing Cr concentration the wear intensity diminishes and it reaches minimal values at 16% Cr. In the case of coatings having 20% Cr concentration, the wear intensity is increased, which is due to the absence of the components B and Si in the composite mixture, whereupon no inter-metallic structures are formed having high hardness and wear resistance. The obtained results have no analogues in the current literature and they have not been published by the authors.

Soliton crystal micro-combs are powerful tools as sources of multiple wavelength channels for radio frequency (RF) signal processing. They offer a compact device footprint, large numbers of wavelengths, very high versatility, and wide Nyquist bandwidths. Here, we demonstrate integral order RF signal processing functions based on a soliton crystal micro-comb, including a Hilbert transformer and first- to third-order differentiators. We compare and contrast results achieved and the tradeoffs involved with varying comb spacing, tap design methods, as well as shaping methods.

Background Pregnancy is a process of maturity for women that requires adaptation to the changes in their new roles. Adjustment to a new role is not easy, especially if the pregnancy is accompanied by risks, so it is necessary to get treatment to minimize complications. Dyad models that optimize husband or family support are very important to prevent the risk of complications and adapt mothers to their new roles. The purpose of this study was to determine the effect of the dyad model on high-risk pregnancies. The method used with a literature review is through the collection of articles from Scopus, ebsco, ProQuest and PubMed. The results obtained were articles from Scopus 9, Ebsco 107, PubMed 214 and ProQuest 85 which carried out identification, screening and eligibility for 25 articles. Overall results mention. Journals are categorized into 4 groups, Dyad Model and social support, high-risk pregnancy, maternal role and Self Efficacy. Conclusion, there is an effect of the dyad model on care for high-risk pregnancies.

We demonstrate an RF photonic fractional Hilbert transformer based on an integrated Kerr micro-comb source featuring a record low free spectral range of 49 GHz. By programming and shaping the comb lines according to calculated tap weights for up to 39 wavelengths across the C-band, we achieve tunable bandwidths ranging from 1.2 to 15.3 GHz as well as variable center frequencies from baseband to 9.5 GHz, for both standard integral and arbitrary fractional orders. We experimentally characterize the RF amplitude and phase response of the tunable bandpass and lowpass Hilbert transformers with 90 and 45-degree phase shifts. The experimental results show good agreement with theory, confirming the effectiveness of our approach as a powerful way to implement standard and fractional order Hilbert transformers with broad and variable bandwidths and center frequencies, with high reconfigurability and greatly reduced size and complexity. Tan, and D. J. Moss are with the Optical Sciences Centre, Swinburne University of Technology, Hawthorn, VIC 3122, Australia. (Corresponding e-mail: dmoss@swin.edu.au). Xu is with the Electro-Photonics Laboratory, Department of Electrical and Computer System Engineering, Monash University, Clayton, 3800 VIC, Australia