An improved genetic algorithm with dynamic neighborhood search for job shop scheduling problem.

The job shop scheduling problem (JSP) has consistently garnered significant attention. This paper introduces an improved genetic algorithm (IGA) with dynamic neighborhood search to tackle job shop scheduling problems with the objective of minimization the makespan. An inserted operation based on idle time is introduced during the decoding phase. An improved POX crossover operator is presented. A novel mutation operation is designed for searching neighborhood solutions. A new genetic recombination strategy based on a dynamic gene bank is provided. The elite retention strategy is presented. Several benchmarks are used to evaluate the algorithm's performance, and the computational results demonstrate that IGA delivers promising and competitive outcomes for the considered JSP.

Using oscillatory and aperiodic neural activity features for identifying idle state in SSVEP-based BCIs reduces false triggers.

Objective.In existing studies, rhythmic (oscillatory) components were used as main features to identify brain states, such as control and idle states, while non-rhythmic (aperiodic) components were ignored. Recent studies have shown that aperiodic (1/f) activity is functionally related to cognitive processes. It is not clear if aperiodic activity can distinguish brain states in asynchronous brain-computer interfaces (BCIs) to reduce false triggers. In this paper, we propose an asynchronous method based on the fusion of oscillatory and aperiodic features for steady-state visual evoked potential-based BCIs.Approach.The proposed method first evaluates the oscillatory and aperiodic components of control and idle states using irregular-resampling auto-spectral analysis. Oscillatory features are then extracted using the spectral power of fundamental, second-harmonic, and third-harmonic frequencies of the oscillatory component, and aperiodic features are extracted using the slope and intercept of the first-order polynomial of the spectral fit of the aperiodic component under a log-logarithmic axis. The process produces two types of feature pools (oscillatory, aperiodic features). Next, feature selection (dimensionality reduction) is applied to the feature pools by Bonferroni correctedp-values from two-way analysis of variance. Last, these spatial-specific statistically significant features are used as input for classification to identify the idle state.Mainresults.On a 7-target dataset from 15 subjects, the mix of oscillatory and aperiodic features achieved an average accuracy of 88.39% compared to 83.53% when using oscillatory features alone (4.86% improvement). The results demonstrated that the proposed idle state recognition method achieved enhanced performance by incorporating aperiodic features.Significance.Our results demonstrated that (1) aperiodic features were effective in recognizing idle states and (2) fusing features of oscillatory and aperiodic components enhanced classification performance by 4.86% compared to oscillatory features alone.

The impact of a structured assessment and decision tool (I-DECIDED®) on improving care of peripheral intravenous catheters: A multicenter, interrupted time-series study.

BACKGROUND: Peripheral intravenous catheters are the most widely used invasive device in hospitals but have serious risks. OBJECTIVE: To determine if a structured assessment and decision tool (I-DECIDED®) improves daily peripheral intravenous catheter assessment and care decisions. DESIGN: Prospective, interrupted time-series study. SETTINGS: Seven adult inpatient wards in three Australian hospitals. PARTICIPANTS: 825 adults with 867 peripheral intravenous catheters. METHODS: Between August 2017 and December 2018, peripheral intravenous catheter assessments and chart audits were undertaken with informed patient consent. Following a 4-month pre-intervention period (with 2-weekly measures), the I-DECIDED® tool was implemented over 3 months (no data collection) using multiple strategies (stakeholder meetings, vascular access device form, education sessions, ward champions, lanyard cards, and posters), followed by a 4-month post-intervention period (with 2-weekly measures). Primary outcomes were device utilization (number of peripheral intravenous catheters per total number of patients screened); idle/unused catheters; insertion site complications, substandard dressing quality; and primary bloodstream infections. RESULTS: Of 2055 patients screened, 1175 (57.2%) had a peripheral intravenous catheter, and 825 patients (867 catheters) consented and were included in the final analysis. Device utilization increased from 42.0% of catheters at baseline to 49.6% post-intervention (absolute risk difference [ARD] 7.5%, 95% confidence interval [CI] 4.8, 10.3; relative risk [RR] 1.18, 95% CI 1.11, 1.25; p < 0.001). The proportion of idle catheters reduced from 12.7% to 8.3% (ARD -4.4%, 95% CI -8.5, -0.3; RR 0.66, 95% CI 0.44, 0.97; p = 0.035). Peripheral intravenous catheter complications reduced from 16.1% to 10.9% (ARD -5.2%, 95% CI -9.7, -0.6; RR 0.68, 95% CI 0.48, 0.96; p = 0.026). Substandard dressings reduced from 24.6% to 19.5% (ARD -5.2%, 95% CI -10.7, 0.4; RR 0.79, 95% CI 0.61, 1.02; p = 0.067). Only one primary bloodstream infection occurred (post-intervention). CONCLUSIONS: Implementation of a comprehensive device assessment and decision tool (I-DECIDED®) reduced idle catheters and catheter complications, despite higher device utilization. Dressing quality improved but was not statistically significant. Further implementation of the tool could improve hospital safety for patients with an intravenous catheter. ANZCTR TRIAL REGISTRATION: ACTRN12617000067370. Date of registration 13 January 2017. Date of first data collection 3rd August 2017. TWEETABLE ABSTRACT: #IDECIDEDassessment reduces prevalence of idle peripheral catheters and device complications.

Biological postural oscillations during facial expression of pain in virtual characters modulate early and late ERP components associated with empathy: A pilot study.

There is a surge in the use of virtual characters in cognitive sciences. However, their behavioural realism remains to be perfected in order to trigger more spontaneous and socially expected reactions in users. It was recently shown that biological postural oscillations (idle motion) were a key ingredient to enhance the empathic response to its facial pain expression. The objective of this study was to examine, using electroencephalography, whether idle motion would modulate the neural response associated with empathy when viewing a pain-expressing virtual character. Twenty healthy young adults were shown video clips of a virtual character displaying a facial expression of pain while its body was either static (Still condition) or animated with pre-recorded human postural oscillations (Idle condition). Participants rated the virtual human's facial expression of pain as significantly more intense in the Idle condition compared to the Still condition. Both the early (N2-N3) and the late (rLPP) event-related potentials (ERPs) associated with distinct dimensions of empathy, affective resonance and perspective-taking, respectively, were greater in the Idle condition compared to the Still condition. These findings confirm the potential of idle motion to increase empathy for pain expressed by virtual characters. They are discussed in line with contemporary empathy models in relation to human-machine interactions.

Enabling the ActiGraph GT9X Link's Idle Sleep Mode and Inertial Measurement Unit Settings Directly Impacts Data Acquisition.

The ActiGraph GT9X has been implemented in clinical trials to track physical activity and sleep. Given recent incidental findings from our laboratory, the overall aim of this study was to notify academic and clinical researchers of the idle sleep mode (ISM) and inertial measurement unit (IMU)'s interaction, as well as their subsequent effect on data acquisition. Investigations were undertaken using a hexapod robot to test the X, Y and Z sensing axes of the accelerometers. Seven GT9X were tested at frequencies ranging from 0.5 to 2 Hz. Testing was performed for three sets of setting parameters: Setting Parameter 1 (ISMONIMUON), Setting Parameter 2 (ISMOFFIMUON), Setting Parameter 3 (ISMONIMUOFF). The minimum, maximum and range of outputs were compared between the settings and frequencies. Findings indicated that Setting Parameters 1 and 2 were not significantly different, but both were significantly different from Setting Parameter 3. Upon inspection, it was discovered that the ISM was only active during Setting Parameter 3 testing, despite it being enabled in Setting Parameter 1. Researchers should be aware of this when conducting future research using the GT9X.

A structural equation model of online learning: investigating self-efficacy, informal digital learning, self-regulated learning, and course satisfaction.

Introduction: English as a Foreign Language (EFL) education increasingly relies on online learning, necessitating a nuanced understanding of crucial factors impacting learning experiences. This research investigates the intricate relationships among online learning self-efficacy, online self-regulated learning, informal digital learning of English (IDLE), and online course satisfaction within the unique context of EFL learners. Methods: The study involved 563 intermediate college students from various national universities in China. Structural Equation Modeling (SEM) was employed to analyze the data, providing comprehensive insights into the relationships among the identified variables. Results: The results revealed significant insights. Both online learning self-efficacy and IDLE exhibited direct and positive influences on online course satisfaction. Furthermore, the study uncovered that online self-regulated learning acted as a partial mediator in the connection between online learning self-efficacy and IDLE with online course satisfaction. This mediation implies that learners' self-regulatory behaviors significantly affect how self-efficacy and informal digital language learning experiences impact overall satisfaction with online courses. Discussion: The findings highlight the pivotal role of nurturing learners' self-efficacy beliefs, fostering IDLE, and promoting effective self-regulated learning strategies in the realm of online language learning. These initiatives are instrumental in enhancing learners' satisfaction and success in online courses. Conclusion: The implications of these findings for EFL instruction are substantial. By emphasizing the importance of self-efficacy, IDLE, and self-regulated learning strategies, educators can significantly contribute to creating more satisfying and successful online learning experiences for EFL students.

Time-Driven, Activity-Based Costing to Reduce Interventional Radiology Suite Idle Time.

Background With the ever-increasing complexity of today's healthcare environment, it is evident that there is a higher demand to deliver high-quality, accessible, efficient, and affordable healthcare. At the same time, these changes are accompanied by decreasing rates of reimbursement. This can be attributed to the shift from fee-for-service to value-based payment methods in the industry. The reception of such changes in the appropriate manner is crucial to improvement and the much-demanded reform in our healthcare system. To adapt to this changing landscape, hospitals and healthcare systems must incorporate proper measures to identify extraneous spending, control costs, and streamline patient care. Our goal in this study was to use the time-driven, activity-based costing (TDABC) model to quantify the costs at every step as an inpatient goes through the care process in an interventional radiology department. Methodology After identification and mapping of all the steps involved from interventional radiology (IR) consult placement to patient transport to the postoperative recovery area, time data were collected for each step of the process. One of the steps was then selected for intervention. Our focus was on the time interval between one patient leaving after a completed procedure and the next scheduled patient entering the IR suite (heretofore referred to as idle time). To decrease the idle room time between patients, the interventional radiologists, IR administrations, nurse manager, transportation manager, and charge nurse first met as a group to set a realistic initial goal. Pre-intervention data were collected. Results After the collection of pre-intervention data, the average idle time of the IR suite was found to be 40 minutes. After a multidisciplinary discussion, our goal was to reduce this time to 25 minutes. Post-intervention data found the average time decreased to 24 minutes. Calculation of average costs per unit time for staff, IR room, and equipment yielded an approximate cost of $57 per minute of time in the IR suite. Conclusions Considering the near 40% decrease in suite idle time as well as the cost per minute of material, equipment, and staff (at ~80% capacity), this study proves that the TDABC system is a viable method of targeting bottlenecks in operations and streamlining patient care by reducing costs while optimizing the process patients go through during care continuum.

Case-Mix Moderation of the Relationship Between OR Performance Metrics and Utilization.

We investigated the impact of the case-mix ratio of inpatients to outpatients on the relationships between OR utilization and late starts, turnover time, delays, cancellations, and idle time at an academic medical center in the southeastern United States. After extracting 55 months of data from the surgical repository, we used simple and multiple linear regression models to analyze the data and determine the strength and direction of the relationships among the variables. We compared models comprising proportionally more inpatients to models comprising proportionally more outpatients for each metric to ascertain the effects of case mix on OR utilization. Idle time had the greatest effect on OR utilization, followed by late starts and turnover time. Case mix moderated the relationship between OR utilization and the metrics of cancellations and turnover time. Perioperative leaders may enhance OR utilization by monitoring and addressing idle time and late starts and scheduling an appropriate mix of inpatients and outpatients.

Effective guide for behaviour of farmers in the withdrawal of rural homesteads: An evolutionary game-based study.

In this study, we determined how farmers can be effectively encouraged to withdraw from their idle homesteads, in addition to revitalising the rural construction land stock and realising the market-oriented allocation of land resources. We constructed an evolutionary game model under three scenarios: without penalty mechanism; with a static penalty mechanism; and with a dynamic penalty mechanism. Further, we explicitly describe the strategic behaviours and dynamic evolution processes of local governments and farmers during withdrawal from their rural homesteads. According to the results of the evolutionary stable strategy, under effect of the dynamic penalty mechanism, the strategy systems formed by local governments as well as farmers can gradually converge and stabilise after short-term shocks, compared with that under the no penalty and static penalty mechanisms. Overall, the penalty mechanism mitigates the instability in the game process during participants' incremental changes and strategy choices, while the dynamic mechanism is optimal. Both static and dynamic penalty mechanisms influence the binary equilibrium strategies of local governments as well as farmers, and farmers' strategies evolve towards this state of withdrawal from their homesteads with increasing penalty. When the model is dynamically improved, the probability of farmers' withdrawal of their homesteads increases with increasing penalty. Thus, clearly, the establishment of a penalty mechanism can promote stability of the participants' system; higher penalty implies higher motivation for farmers to withdraw their idle homesteads, enabling revitalisation of the rural stock of construction land and promotion of the optimal allocation of land resource elements.

Corrigendum: Hyperspectral Video Analysis by Motion and Intensity Preprocessing and Subspace Autoencoding.

[This corrects the article DOI: 10.3389/fchem.2022.818974.].

Comparison of the emission factors of air pollutants from gasoline, CNG, LPG and diesel fueled vehicles at idle speed.

The emission factor (EF) is a parameter used to assess vehicle emissions. Many studies have reported EFs for vehicles in driving conditions. However, the idling emissions should not be neglected in characterizing actual vehicle emissions in congested large cities, where idling is very common on the road. Whereas, EF data for idling vehicles have scarcely been reported in the literature, let alone comparison of different fuels. In this study, the EFs of passenger cars burning four types of fuels - gasoline, compressed natural gas (CNG), diesel, and liquefied petroleum gas (LPG) were measured and compared. The emissions data for CO, CO2, unburned hydrocarbon (HC), and NO were recorded to calculate fuel-based EFs in units of g pollutants/kg fuel burned. EFs for CO, HC, and NO were compared for the four fuels. Diesel vehicles had the highest EF for CO, with an average value of 35.12 ± 21.37 g/kg fuel, due to low concentration of CO2 in lean operation compared to CO emission. CNG vehicles had the highest EF for HC, with an average value of 28.15 ± 11.97 g/kg fuel, due to high concentration of unburned methane gas due to slow CNG flame speed whereas diesel vehicles again had the highest EF for NO due to high temperature and pressure and freezing of NO decomposition reaction, with an average value of 12.07 ± 5.37 g/kg fuel. Further comparison was conducted to analyze the effects of two additional variables on EF: engine displacement volume and model/brand year. Only the gasoline-fueled vehicles showed an increase in EFs (for CO, HC and NO) with the vehicle age according to the model year. However, no clear correlation was observed for CNG, LPG, and diesel-fueled vehicles. Finally, the EF results were compared with those reported in the literature, which have been measured in various countries under both idling and non-idling conditions. Because the idling EFs were not substantially smaller than those under moving conditions, and vehicles spend substantial time idling in large cities, idling emissions should not be ignored in the emission inventories for large cities.

Hyperspectral Video Analysis by Motion and Intensity Preprocessing and Subspace Autoencoding.

Hyperspectral imaging has recently gained increasing attention from academic and industrial world due to its capability of providing both spatial and physico-chemical information about the investigated objects. While this analytical approach is experiencing a substantial success and diffusion in very disparate scenarios, far less exploited is the possibility of collecting sequences of hyperspectral images over time for monitoring dynamic scenes. This trend is mainly justified by the fact that these so-called hyperspectral videos usually result in BIG DATA sets, requiring TBs of computer memory to be both stored and processed. Clearly, standard chemometric techniques do need to be somehow adapted or expanded to be capable of dealing with such massive amounts of information. In addition, hyperspectral video data are often affected by many different sources of variations in sample chemistry (for example, light absorption effects) and sample physics (light scattering effects) as well as by systematic errors (associated, e.g., to fluctuations in the behaviour of the light source and/or of the camera). Therefore, identifying, disentangling and interpreting all these distinct sources of information represents undoubtedly a challenging task. In view of all these aspects, the present work describes a multivariate hybrid modelling framework for the analysis of hyperspectral videos, which involves spatial, spectral and temporal parametrisations of both known and unknown chemical and physical phenomena underlying complex real-world systems. Such a framework encompasses three different computational steps: 1) motions ongoing within the inspected scene are estimated by optical flow analysis and compensated through IDLE modelling; 2) chemical variations are quantified and separated from physical variations by means of Extended Multiplicative Signal Correction (EMSC); 3) the resulting light scattering and light absorption data are subjected to the On-The-Fly Processing and summarised spectrally, spatially and over time. The developed methodology was here tested on a near-infrared hyperspectral video of a piece of wood undergoing drying. It led to a significant reduction of the size of the original measurements recorded and, at the same time, provided valuable information about systematic variations generated by the phenomena behind the monitored process.

A dual meta-learning framework based on idle data for enhancing segmentation of pancreatic cancer.

Automated segmentation of pancreatic cancer is vital for clinical diagnosis and treatment. However, the small size and inconspicuous boundaries limit the segmentation performance, which is further exacerbated for deep learning techniques with the few training samples due to the high threshold of image acquisition and annotation. To alleviate this issue caused by the small-scale dataset, we collect idle multi-parametric MRIs of pancreatic cancer from different studies to construct a relatively large dataset for enhancing the CT pancreatic cancer segmentation. Therefore, we propose a deep learning segmentation model with the dual meta-learning framework for pancreatic cancer. It can integrate the common knowledge of tumors obtained from idle MRIs and salient knowledge from CT images, making high-level features more discriminative. Specifically, the random intermediate modalities between MRIs and CT are first generated to smoothly fill in the gaps in visual appearance and provide rich intermediate representations for ensuing meta-learning scheme. Subsequently, we employ intermediate modalities-based model-agnostic meta-learning to capture and transfer commonalities. At last, a meta-optimizer is utilized to adaptively learn the salient features within CT data, thus alleviating the interference due to internal differences. Comprehensive experimental results demonstrated our method achieved the promising segmentation performance, with a max Dice score of 64.94% on our private dataset, and outperformed state-of-the-art methods on a public pancreatic cancer CT dataset. The proposed method is an effective pancreatic cancer segmentation framework, which can be easily integrated into other segmentation networks and thus promises to be a potential paradigm for alleviating data scarcity challenges using idle data.

The space between notes: emerging roles for translationally silent ribosomes.

In addition to their central functions in translation, ribosomes can adopt inactive structures that are fully assembled yet devoid of mRNA. We describe how the abundance of idle eukaryotic ribosomes is influenced by a broad range of biological conditions spanning viral infection, nutrient deprivation, and developmental cues. Vacant ribosomes may provide a means to exclude ribosomes from translation while also shielding them from degradation, and the variable identity of factors that occlude ribosomes may impart distinct functionality. We propose that regulated changes in the balance of idle and active ribosomes provides a means to fine-tune translation. We provide an overview of idle ribosomes, describe what is known regarding their function, and highlight questions that may clarify their biological roles.

Game Theory-Based Energy-Efficient Clustering Algorithm for Wireless Sensor Networks.

Energy efficiency is one of the critical challenges in wireless sensor networks (WSNs). WSNs collect and transmit data through sensor nodes. However, the energy carried by the sensor nodes is limited. The sensor nodes need to save energy as much as possible to prolong the network lifetime. This paper proposes a game theory-based energy-efficient clustering algorithm (GEC) for wireless sensor networks, where each sensor node is regarded as a player in the game. According to the length of idle listening time in the active state, the sensor node can adopt favorable strategies for itself, and then decide whether to sleep or not. In order to avoid the selfish behavior of sensor nodes, a penalty mechanism is introduced to force the sensor nodes to adopt cooperative strategies in future operations. The simulation results show that the use of game theory can effectively save the energy consumption of the sensor network and increase the amount of network data transmission, so as to achieve the purpose of prolonging the network lifetime.

What to do when there is nothing to do? Toward a better understanding of idle time at work.

Idle time at work is a phase of involuntary downtime during which employees experience that they cannot carry out their work tasks. In contrast to breaks, interruptions, procrastination, or withdrawal behavior, employees cannot work because of the absence of work-related tasks. Based on action regulation theory, we develop an integrative conceptual model on the antecedents and consequences of the subjective experience of idle time. We propose that work constraints (i.e., regulation problems) have negative effects on occupational well-being and task performance, and that these effects are mediated by subjective idle time. The strength of these effects is further assumed to be influenced by individuals' use of proactive (i.e., prevention) and adaptive (i.e., coping) strategies. Results of a supplemental qualitative study, for which we interviewed 20 employees from different occupations, provided preliminary support for the propositions. Finally, we develop theory on how individual, situational, and organizational characteristics may influence the proposed effects on and of idle time. Overall, this conceptual development paper contributes to a better theoretical understanding of idle time at work by extending its definition and applying action regulation theory to this practically important phenomenon.

Idle peripheral intravenous cannulation: an observational cohort study of pre-hospital and emergency department practices.

BACKGROUND: Unused ('idle') peripheral intravenous catheters (PIVC) are those not used within 24 hours of insertion. There is little data on cannulation practices and idle PIVC rates in emergency settings, especially the pre-hospital environment. METHODS: This was an observational cohort study set in south-east Queensland, Australia using data from a large tertiary level emergency department (ED) and the local statutory ambulance service. Demographic, clinical and PIVC data were collected over two periods; 9 February-18 March 2017 and 5 January-4 February 2018. Adult patients were included if they were allocated an Australasian triage scale (ATS) category between 2 and 5, and had a PIVC inserted in the pre-hospital setting or ED. PIVC use was defined as idle if no fluids, medications or contrast were administered intravenously within 24 hours of insertion. Comparisons between pre-hospital and ED practice and idle PIVC status were undertaken using descriptive statistics and logistic regression. RESULTS: A total of 1249 patients with a PIVC (372 pre-hospital; 877 ED) were included. Overall, 366 PIVCs (29.3%; 95% CI 26.9%-31.9%) remained idle at 24 hours. In the pre-hospital group, 147 (39.5%) PIVCs inserted were not used pre-hospital, and 74 (19.9%) remained idle. In comparison, 292 (33.3%) PIVCs placed in the ED remained idle. ED staff more frequently inserted PIVCs in the antecubital fossa than paramedics (65.5% vs. 49.7%), where forearm PIVC insertion was more common pre-hospital than in ED (13.7% vs. 7.4%). Nursing staff inserted idle PIVCs at a rate of (35.1%) compared to doctors (29.6%) and paramedics (19.9%). Having a PIVC inserted in the ED was the only factor significantly (p ≤ .001) predicting an idle outcome (Odds Ratio: 2.4; 95% CI 1.7-3.3). CONCLUSION: One-third of PIVCs inserted within the emergency setting remained idle, suggesting unnecessary risk and costs. Pre-hospital and ED PIVC insertion practices differed, with idle PIVCs 2.4 times more prevalent if inserted in the ED than pre-hospital and with greater use of antecubital insertion. Reasons for these differences are not well understood and requires more targeted research.

Evaluation of an electronic system for monitoring dairy cow rumination in a grazing-based system.

This research aimed to compare the rumination time estimated by an electronic monitoring system with direct visual observations of the rumination of dairy cows in a grazing-based system. Also, it aimed to estimate the agreement between different time intervals of the direct visual observations. To that end, we have observed twelve lactating cows for 16 h a day for 11 days. Then, we compared the data provided by the HealthyCow24® software with the visual observations to use as reference. After that, we estimated the Pearson's correlation coefficients, the linear regression, and the Bland-Altman plot by using the SAS software. Results showed that the rumination data estimated by the HealthyCow24® software and the visual observations were highly correlated (0.81; P < 0.0001). In the Bland-Altman analysis, we observed that the average of the standard deviations between the visual observation and the electronic monitoring system was - 2.14 min during a 2-h period. The upper limit (95%) was 30.61 min/2 h and the lower limit (95%) was - 34.88 min/2 h. Moreover, visual observations at intervals of up to 15 min were correlated with the data estimated by the electronic monitoring system and observed at 5-min intervals. In conclusion, the Allflex SCR electronic monitoring system is efficient in measuring the rumination time of grazing cows. Also, direct visual observations with intervals no longer than 15 min are reliable when used for evaluating the behavior of cows without losing data accuracy.

Nitrification characteristics of long-term idle aerobic activated sludge during domestication.

Nitrite accumulation usually occurred when domesticating the idle aerobic activated sludge. A sequencing batch reactor (SBR) was used to investigate whether the short-cut nitrification sludge could be cultivated using the idle sludge as inoculated sludge. The results showed that the nitrification process consisted of three stages. In the first stage, the activity of ammonia-oxidizing bacteria (AOB) and nitrite-oxidizing bacteria (NOB) were very low with almost no nitrification performance. In the second stage, the activity of AOB started to recover with the effluent NH4+-N gradually decreased to 0.29 mg L-1, while NOB was alternately inhibited by free ammonia (FA), free nitrous acid (FNA), and nitrite. The effluent NOx--N was mainly NO2--N with an average nitrite accumulation ratio of 74.00%. In the third stage, the nitrification altered from short-cut nitrification to complete nitrification, and the nitrification kinetics of AOB and NOB were both well-fitted to the Monod equation (R2 > 0.92). The variations of effluent pH and ORP between cycles could indicate the recovery stage of the nitrifying ability. Through monitoring the curves of effluent pH and ORP, when the domestication process is between the pH peak and ORP plateau, the short-cut nitrification sludge could be cultivated. This study revealed the mechanism of nitrite accumulation during the domestication of long-term idle aerobic activated sludge, and established a control strategy to accelerate the domestication.

The Design of Terahertz Frequency Quadruplers Based on Discrete Schottky Diodes.

On the basis of the W-band power source, a single-stage frequency quadrupler method was used to implement two 335 GHz frequency quadruplers. The two frequency quadruplers adopted a traditional binomial matching structure and an improved gradient line matching structure, respectively. An idle loop was added to the overall circuit in the design of the DC filter and low-pass filter. The improved gradient line matching structure reduced the circuit length while increasing the bandwidth, effectively reducing the power loss on the transmission line. A micro-strip circuit was fabricated with a 50 µm thick quartz circuit and was mounted onto a split waveguide block. The results showed that the output power of the quadrupler with the improved matching structure was better than that of the quadrupler with the conventional matching structure. The peak output power of the improved frequency quadrupler was 4.75 mW at 333 GHz when driven with 200 mW. In contrast, this improved structure broadened the bandwidth by 8 GHz and reduced the length of the substrate by 0.607 mm, effectively reducing the length of the traditionally designed circuit by 11.5%.