Optimal Starting Time Research Articles

Efficacy of preemptive multimodal analgesia initiated at various time points before total knee arthroplasty: a prospective, double-blind randomized controlled trial.

Preemptive multimodal analgesia (PMA) is commonly employed for pain control after total knee arthroplasty (TKA). However, the optimal timing for initiating PMA remains unclear. This study aimed to compare the efficacy of PMA administered at different time points before TKA. In this prospective, double-blind, placebo-controlled, randomized trial, 120 patients who underwent TKA were randomized into three groups. PMA (200mg celecoxib and 150mg pregabalin administered every 12h) was initiated 48h (group A), 24h (group B), and 1h (group C) before surgery. The primary outcome was the postoperative administration of morphine hydrochloride as a rescue analgesic. Secondary outcomes included time to first rescue analgesia, postoperative pain assessed using the visual analog scale (VAS), functional recovery assessed by knee motion range and ambulation distance, time until hospital discharge, and complication rates. Compared with group C, groups A and B exhibited significantly lower morphine consumption within 24h after surgery, lower total morphine consumption, longer time to first rescue analgesia, and superior range of knee motion on the day of surgery. Groups A and B did not exhibit significant differences in these outcomes. The three groups did not differ significantly in postoperative VAS pain scores, ambulation distance, length of hospital stay, or complication rates. In comparison with PMA starting at 1h preoperatively, initiating PMA at 24 and 48h preoperatively provided better postoperative pain relief. Considering the aim of minimizing the amount of ineffective medication received by patients, initiating PMA at 24h preoperatively may be a more favorable option for patients undergoing TKA. However, the clinical significance of our results and the optimal starting time for PMA require further investigation.

A novel late-stage oscillating discharge current for plasma regulation and its effect in material removal in electrical discharge machining

Abstract Improving the material removal rate (MRR) has recently become one of the most important issues in electrical discharge machining. During the discharge process, a large portion of molten material cannot be sufficiently expelled from the molten pool but re-solidifies, ultimately resulting in low energy utilization and machining efficiency. Unlike existing methods that primarily focus on optimizing general discharge parameters, this study aims to enhance molten material expulsion and MRR through discharge plasma regulation by employing a redesigned late-stage oscillating discharge current. During a single-pulse discharge process, this kind of discharge current firstly remains constant to ensure stable heat transfer from the plasma to the workpiece, then transitions to periodic oscillations to enhance plasma movement and facilitate molten material expulsion. High-speed plasma observations and heat-flow coupling simulations are conducted to analyze the effects of the discharge currents on material removal, and the optimal oscillation start time is obtained. Experimental results in machining stainless steel demonstrate that the use of the late-stage oscillating discharge current, in comparison to the conventional rectangular discharge current, results in a 74% increase in material removal volume per unit of energy and a 56% in average recast layer thickness.

Implementation and validation of optimal start control strategy for air conditioners and heat pumps

Commercial buildings are responsible for approximately 20 % of the total energy consumption and greenhouse gas emissions in the United States. Over 85 % of these buildings lack building automation systems, and many are small (<50,000 square feet), underserved, and use rooftop units (RTUs) for heating, ventilation, and air-conditioning needs. Because these buildings lack proper energy management systems, several operational deficiencies lead to excess energy consumption. Studies have shown that managing the RTUs’ heating and cooling set points, schedules, setbacks, and optimal start can result in a 20 % to 25 % reduction in electricity consumption in small commercial buildings. These buildings typically use fixed schedules to start the RTUs 60 to 120 min before occupancy begins, which results in excess energy consumption. This paper presents research that demonstrates and evaluates the performance of four optimal start methods, which utilize data-based modeling as a key element in facilitating adaptive control in response to time-varying inputs while requiring minimal sensor inputs. The evaluation found energy savings in two commercial buildings equipped with RTUs by periodically alternating four different optimal start models during the cooling and heating season. The resulting energy savings are positive for all models and range from 2 to 5 kWh/day/unit. The units on the east side of the building showed higher savings, while interior units showed greater variability in savings due to the differences in capacities and room sizes. Savings were considerably greater during the heating season compared to the cooling season. The performance of all four models on Mondays was poor; models suggested a shorter optimal start time, which resulted in relatively larger errors. The future work will look at using a different model for the days after weekends and holidays.

A Constraint Programming Approach for Discrete Time–Cost Tradeoff Problems in a Time-Constrained Activity Network

The discrete time-cost tradeoff problem (DTCTP) is a well-researched topic in the field of operations research. The majority of existing DTCTP models are based on traditional activity networks, which permit the execution of an activity as soon as all its predecessors have been completed. This assumption is reasonable, but it is important to note that there are always exceptions. The main work of this study was threefold. Firstly, we expanded the analysis of the DTCTP to encompass time-constrained activity networks (DTCTPTC), which encompassed three different types of time constraints. The first constraint was the time-window constraint, which limited the time interval during which an activity could be executed. The second constraint was the time-schedule constraint, which specified the times at which an activity could begin execution. The third constraint was the time-switch constraint, which required project activities to start at specific times and remain inactive during designated time periods. Secondly, a constraint programming (CP) model was developed for the purpose of solving the DTCTPTC. The model employed interval variables to define the activity and its potential time constraints, while CP expressions were utilized to ensure the feasibility of the solution. The objective was to identify the optimal execution mode for each activity, the optimal start times for time-scheduled activities, and the optimal work/rest patterns for time-switch activities, with the aim of minimizing the total cost of the project. Finally, the efficacy of the proposed CP model was validated through two case studies based on two illustrative projects of varying sizes. The outcomes were then compared against existing algorithms. The results demonstrated that time constraints were important factors affecting schedule optimization, and the proposed CP model had the ability to solve large-scale DTCTPTC.

Effect of radius-dependent diffusion behavior of various gold nanoparticles on photothermal therapy

Among the various anti-cancer treatments, photothermal therapy (PTT) is gaining traction as it is a non-invasive treatment. PTT is a treatment technique involving the use of a laser to raise the temperature of the target tumor until it dies. In this study, the effects of PTT under various conditions of squamous cell carcinoma (SCC) occurring in the skin were numerically analyzed and optimized. Gold nanoparticles (AuNPs) with different radii were injected into the center of the SCC. Subsequently, the diffusion behavior of the AuNPs was analyzed to calculate the distribution area of the AuNPs that changed over time. Furthermore, at each elapsed time point after injection, the temperature distribution in the tissue was calculated, as treatment was performed using varying laser intensities. The diffusion coefficient of AuNPs was calculated using the Stokes–Einstein equation, and diffusion behavior of AuNPs in biological tissues was analyzed using the convection–diffusion equation. Additionally, temperature distribution was analyzed using the Pennes bioheat equation. The effect of PTT under each condition was quantitatively analyzed using apoptotic variables. As a result, As the radius of AuNPs increased, the optimal treatment start time was derived as 2 h, 8 h, 8 h, and 12 h, respectively, and the laser intensity at that time was derived as 0.44 W, 0.46 W, 0.42 W, and 0.42 W, respectively. The study findings will provide reference for the optimization of the efficacy of PTT.

Automatic Control of Nucleation and Crystal Growth Using Online Raman Analyzer

The accurate determination of crystal formation during crystallization is crucial for obtaining crystal products with consistent quality and quantity. In this study, we aimed to identify the feasibility of using Raman spectroscopy to monitor the crystal growth stage in the crystallization process using cephalosporin intermediate 7-ACT as an example molecule. By observing the changes in the characteristic peak of the 7-ACT crystal (504 cm−1) and the characteristic peak of the solvent acetonitrile (914 cm−1), a correlation between the crystal growth stage and the change in the Raman intensity of the crystal solution was discovered. The determination of the optimal starting time for the crystal growth stage through a Raman analyzer significantly improves the consistency of crystal product quality. This led to a fivefold reduction in the variation in the weight and water content of the final 7-ACT crystal products compared to those obtained via manual control. In addition, our experiments also indicated that Raman monitoring could be more efficient at enabling the chemical synthesis reaction to be completed compared to manual control. Thus, our work demonstrates the potential of Raman spectroscopy in the real-time control of chemical synthesis reactions and crystallization processes.

Helmet therapy efficacy and its prediction in Japanese infants with positional plagio- and brachycephaly.

To provide additional information on optimal start times and therapeutic effectiveness based on treatment outcome of Japanese infants with positional plagio- and brachycephaly (PPB) receiving cranial molding helmet therapy (CMHT). In this retrospective cohort study, data from a 3D head scanning system was analyzed from 2173 Japanese infants who completed CMHT. Anterior and posterior symmetry ratio (ASR and PSR) and longitudinal to transverse diagonal ratios (LD/TDR) were calculated based on skull shape at helmet design and at completion of therapy. The outcomes were evaluated using the regression analysis and a predictive model using cranial parameters was developed. The earlier the start of therapy, the greater the therapeutic effect on ASR, PSR, and LD/TDR (ASR, -0.134 percent points (ppt)/day; PSR, -0.086 ppt/day; and LD/TDR, -0.131 ppt/day). In the predictive model, in addition to starting age of the therapy, sex (male), the degree of deformity of the head (DoD) (moderate and severe), quadrant volume, PSR, and head circumference at the start of treatment also had a positive effect on changes in ASR, DoD (moderate and severe), ASR, LD/TDR and transverse diameter for PSR, sex (male), DoD (moderate), quadrant volume, PSR, and head circumference for LD/TDR. The starting age of therapy had a relatively smaller contribution to outcome effects. Applying the cranial parameter obtained at the start of treatment to the predictive model helps to predict the effect of CMHT and whether PPB can be treated with CMHT in infants of older age.

Two‐stage demand‐side management in energy flexible residential buildings

AbstractIn this study, an optimisation model is developed for two‐stage energy management of a residential building to minimise energy cost under monthly power‐based tariffs for peak demand and time‐variable electricity prices. The expected peak demand is determined in the first stage, and then the energy management system minimizes energy costs during the second stage. The second stage's optimisation problem is solved in a rolling time window, facilitating real‐time operation of flexible energy sources in the building. This includes optimal charging and discharging of the battery energy system, electric vehicle battery charging, heating system operation, and determining the optimal start times for washing machines and dishwashers, all close to real‐time. The proposed approach enables users to predict and manage peak demand in daily operation, staying below the predetermined value through a close to real‐time energy management system. The effectiveness of this two‐stage approach in demand‐side management for residential buildings is demonstrated through a realistic case study.

Joint or not: unpacking the decision-making mechanism of pandemic control between two nations – from the perspective of cost optimization

Joint control has been proposed to alleviate the negative spillover of the pandemic. The authority faces a decision dilemma on whether to undertake joint control, which is overlooked by the scientific community. This paper, aiming to clarify the decision-making mechanism under cost optimization, draws on the optimization theory to find the optimal strategies and start time under independent and joint scenarios with an improved infectious disease model. Besides, a simulation analysis, based on the survey in Ruili – a border area between Myanmar and China, is employed. The crucial findings highlight that (1) The control measures contribute to reducing the peak number or peak time of confirmed patients under optimal decision. (2) As the delay of start time, the epidemic control for both countries undergoes from validity to failure. (3) More cost-savings come with earlier joint control but with uneven distribution. Joint strategy mitigates the cost for the one with severe epidemics, but the effect is insignificant for the other. This study, concentrating on cost optimization, provides a novel insight into pandemic control. The results enrich the decision analysis in the context of pandemic joint governance while providing inter-regional control support for the decision-maker to tackle various epidemics.

Implementation Readiness and Initial Effects of a Brief Mindfulness Audio Intervention Compared With a Brief Music Control During Daily Radiation Therapy for Prostate Cancer: A Randomized Pilot Study.

The most common and debilitating side effects of radiation therapy (RT) for prostate cancer (PC) are fatigue, sleep disturbance, anxiety, and depression. Previous research has reported palliative benefits from certain self-management approaches, such as mindfulness meditation. To develop, pre-test, and evaluate the feasibility, acceptability and initial benefit of brief, audio-based mindfulness delivered during daily RT for PC compared to a relaxing music control. Following intervention development, participants were randomized to either brief guided mindfulness audio recordings or a relaxing music control during daily RT. A pre-testing phase was first conducted to determine optimal program start time, length, and content most associated with retention. A final program (n = 26) was delivered daily, starting on day one of week 2 of RT and lasting 4 consecutive weeks. Feasibility was defined as ≥70% on enrollment rate, retention, and audio program adherence. Acceptability was measured with a 12-item post-study survey. A secondary focus compared between group changes on patient reported outcomes of fatigue, anxiety, depression, sleep disturbance, and related outcomes at baseline and follow up assessments. Descriptive statistics and general linear models were used. Overall, 76% (n = 38) of approached men enrolled. Pre-testing retention rates were <70% while the final program's retention rate was 89%. The majority of acceptability criteria were met in both conditions, with relatively higher ratings in the mindfulness arm. Compared to music controls, mindfulness participants demonstrated significantly less uncertainty intolerance at 4-weeks (P = .046, d = .95); and significantly lower fatigue scores (P = .049, d = 1.3) and lower sleep disturbance scores (P = .035, d = 1.1) at the 3months follow up. The final intervention met feasibility and acceptability criteria. Pre-testing refinements played a key role for optimal program delivery and retention. Audio-based mindfulness delivered during RT for PC hold potential to help decrease RT-related physical and emotional side effects.

Entry-exit decisions with output reduction during exit periods

&lt;abstract&gt;&lt;p&gt;In practice, a firm usually reduces the output of a project during exiting the project. We intend to fully analyze the effects of the reduction on the entry-exit decision on the project. To this end, we first obtain the closed expressions of the optimal activating time, optimal start time of the exit, and the maximal expected present value of the project. With these expressions in hand, we completely investigate the effects analytically and numerically. The results show us that the reduction affects the entry-exit decision in different ways due to the different conditions in terms of the parameters involved in the problem. The reduction does not affect the entry-exit decision provided that the firm never exits the project. If the firm exits the project in a finite time, the reduction may postpone or advance the activating time and start time of the exit.&lt;/p&gt;&lt;/abstract&gt;

Batch Settling and Low-Pressure Consolidation Behaviors of Dredged Mud Slurry: Steady-State Evaluation and Mechanism Study

Since the exploration of the characteristics of dredged mud slurry during batch settlement and low-pressure consolidation (less than 100 kPa) is still insufficient, the determination of the optimal time to start the vacuum preloading method (VPM) on dredged-fill foundations is still empirically oriented (due to a lack of enough scientific basis). To further explore the characteristics of dredged mud slurry during batch settlement and low-pressure consolidation, samples from typical dredged-fill land projects were obtained and used to conduct batch sedimentation model experiments and low-pressure (less than 100 kPa) consolidation tests. The results of experiments and analyses showed the following: (1) the clay (d &lt; 0.005 mm) content is a main factor affecting the batch settlement and consolidation characteristics of dredged mud slurry, which is not conducive to the consolidation effect of dredged-fill foundations. (2) For dredged mud slurry whose clay content is within 40% to 60%, the cumulative change rate of the average porosity ratio of 60% to 75% is suitable for evaluating the steady state of its batch sedimentation process, i.e., the optimal starting time of VPM. Finally, based on the experimental analyses, a settlement prediction method that considers both the batch sedimentation and the low-pressure consolidation processes was developed and validated.

Stable power supply system consisting of solar, wind and liquid carbon dioxide energy storage

Renewable energy is becoming the main subject of energy consumption with the accelerating transformation of energy structure. The renewable power supply systems sourced by wind and solar energies have attracted wide attention as they are of great significance to regions that are rich in renewable energy. In this study, the stable power system consisting of solar, wind and liquid carbon dioxide energy storage is proposed for the sake of meeting user electricity load. Thermodynamic and economic performance of the proposed systems with different application scenarios is analyzed and some interesting findings are summarized. The round trip efficiency and energy density of the liquid carbon dioxide energy storage system are 58.34 % and 23.41 kWh/m3, respectively. The start hour of dispatch can cause obvious influence on the energy storage capacity and there is an optimal dispatch start time to achieve the minimum energy storage capacity. The overall energy efficiency of energy storage-aided power system including solar and wind powers is much higher than that of the single sourced system. The energy efficiency of the solar-wind-LCES system is 94.61 % while it is only 80.31 % and 76.29 % for the wind-LCES and solar-LCES systems, respectively. The introduction of the liquid carbon dioxide energy storage into the renewable power supply system can greatly reduce the electricity purchasing investment.

The necessity and timing of exercise after lumbar disc herniation surgery.

Physical therapy and rehabilitation may improve low back pain and quality of life after lumbar disc herniation. However, there is no agreement on its optimal start time and rehabilitative methods. This study evaluates the effects of early and late rehabilitation on low back pain and quality of life following unilateral microdiscectomy. A total of 204 patients who underwent surgery for lumbar disc herniation were included and subsequently randomized into five groups: 1. No exercise, 2. The 2nd-week walking group, 3. 1st-month walking group, 4. 2nd-week waist exercise, 5. 1st-month waist exercise. Visual analog scale (VAS) and Oswestry Disability Index (ODI) were assessed at the 1st week, 1st, 3rd, and 6th, and 12th-month follow-up after surgery. 1st-month VAS scores were analyzed, and a significant difference was found between the VAS scores of the 2nd-week walk (3.60±0.78) and 2nd-week waist exercise (3.38±0.67) groups and the other groups (p<0.001). 3rd-month VAS results were analyzed, and the VAS scores of the 1st-month walk group (2.67±0.48) were significantly higher than those of the 2nd-week walk group (1.73±0.45) (p<0.001). A significant difference was observed between the no-exercise group (2.93±0.91) and the other groups according to the 12-month VAS scores, with the VAS scores of the no-exercise group being significantly higher than the other groups (p<0.001). There was a significant difference between the ODI scores of both the 2nd-week walk (38±8.55) and the 2nd-week waist (33.8±6.61) exercise groups and the other groups according to the 1st-month ODI scores (p<0.001). A significant difference was observed between the no-exercise group (35.2±8.25) and the other groups according to the 12-month ODI scores, and the ODI scores of the no-exercise group were significantly higher than the other groups (p<0.001). Regular exercise is highly recommended for long-term pain relief, as well as for achieving a speedy recovery after surgery, which is crucial to maintaining a high quality of life and preventing loss of earning potential. We believe that early implementation of exercises is ideal, but even if initiated later, standard back exercises can still expedite rehabilitation.

Just-in-Time Precast Production Scheduling Using Dominance Rule-Based Genetic Algorithm.

The objective of this study is to provide a model and method to assist fabricators in making appropriate precast production plans, coordinating factories prefabrication and on-site assembly in construction based on the just-in-time (JIT) philosophy. We propose a JIT precast production scheduling model for the precast production of steel box girders in the Hong Kong-Zhuhai-Macau (HZM) bridge construction project. In order to minimize the total early/tardy costs for this JIT scheduling model, we first present a job batching algorithm (JBA) to group series of jobs into several batches. Then, we model the batch cost function as a piecewise linear convex function and derive its optimal solution, which guides us to propose an optimal shifting algorithm (OSA) to locate the optimal starting time of each batch and minimize the batch cost. In order to get the best job sequence for minimizing the total early/tardy costs and improve search efficiency, we introduce a dominance rule for early/tardy scheduling problem and propose a dominance rule-based genetic algorithm (DBGA) embedded with an optimal timing algorithm, which can find the best job sequence as well as the corresponding optimal schedule. The real-world case study of HZM bridge project demonstrates that our proposed model and algorithm can assist construction practitioners to make better decision on precast production scheduling compared to empirical rule in current engineering practice. In addition, numerical studies prove that our proposed algorithm has a better performance on both effectiveness and efficiency due to the dominance rule.

Rainfall influence and risk analysis on the mural deterioration of Dunhuang Mogao Grottoes, China

The Dunhuang Mogao Grottoes are a significant cultural heritage site in the Silk Road, famous for its wonderful murals and statues. The rainfall causes the changes of humidity in the caves, which can easily activate the salts diseases of murals. In order to prevent the deterioration of the murals, the environmental monitoring tests were conducted to analyze the microclimate changes of the cave in rainfall weather, and proposed the risk prevention measures and suggestions. The results indicate that the temperature of caves has small change, but the humidity shows a clear trend of increase. The humidity and the duration of high humidity increases with the increase of the rainfall grade and frequency. The optimal starting time for environment control in the cave is when aatm and acave are consistent, and the relative humidity is controlled below 62%. The caves with lower layer, larger degree of openness and small volume are most vulnerable to water vapour diffusion. The environment monitoring should pay more attention to the continuous rainfall weather and the vulnerable caves. The research has great significance for the prevention of ancient mural deterioration.

0110 The Influence of Changing School Start Times on Frequency and Timing of Nurse’s Visits for Sleep and Nutrition

Abstract Introduction Healthy school start times are important for ensuring students obtain sufficient sleep, which may impact other health outcomes. Previous studies have not examined the impact of changing school start times on nurses’ visits related to sleep and nutrition in students in grades K-12 after district-wide changes to delay start times in middle and high school and advance start times in elementary school. Methods Electronic medical record data (reason for student visit and time of visit) were retrieved from nursing offices for elementary (n=44), middle (n=14), and high (n=6) schools. For this study, we included sleep and nutrition visits within the first two hours of the school day in April/May for the year prior (pre-change) and two years after (post-change, follow-up) implementing new school start times. Within each school level (i.e., elementary, middle, high), descriptive statistics examined the number of visits by health category. Results In elementary school, nurse visits increased in the first two hours when school start times were moved from 9:00am to 8:00 am for both sleep (pre-change n=45; post-change n=78; follow-up n=58) and nutrition (pre-change n=30; post-change n=63; follow-up n=48). For middle school, nurse visits slightly decreased in the first two hours of school when start times were moved from 8:00am to 8:50am for both sleep (pre-change n=14; post-change n=11; follow-up n=11) and nutrition (pre-change n=47; post-change n=42; follow-up n=6). High school nurse visits also slightly decreased in the first two hours of school when start times moved from 7:10am to 8:20am for both sleep (pre-change n=16; post-change n=7; follow-up n=7) and nutrition (pre-change n=5; post-change n=5; follow-up n=2). Conclusion While not unexpected, elementary school nurse visits for sleep and nutrition increased when start times were moved earlier. However, at follow-up, visit frequency notably decreased, suggesting that it may take time for families to adjust to the new start times. For both middle and high school students, nurse visits for sleep and nutrition slightly decreased with later start times. More research is needed to determine optimal start times for elementary school students, as healthy start times are essential for adolescent health and well-being. Support (if any) RWJF Evidence for Action (#75277)

Optimizing the Planning of Airport Airside Expansion Projects to Minimize Air Traffic Disruptions and Construction Cost

This paper presents the development of a novel multiobjective model for optimizing the planning of airport airside expansion projects that provides the capability of minimizing both airport operations disruption cost and total construction cost. The model computations are performed in four main modules: (1) a simulation module that calculates and quantifies the impact of airport construction activities on airport operations, (2) a multiobjective genetic algorithms optimization module that identifies an optimal schedule for airport airside expansion projects, (3) a scheduling module that calculates the start and finish times of each construction activity, and (4) a cost module that computes the total cost of construction-related disruptions in airport operations and the total construction cost. A real-life case study of an airport airside expansion project is analyzed to illustrate the use of the model and highlight its original contributions to the body of knowledge including its novel methodologies for (1) quantifying and minimizing the impact of construction activities on airport operations, (2) analyzing and minimizing the impact of air traffic data and airport operations on total construction cost, and (3) generating a set of optimal construction plans including optimal project start time, activities start time, and weekly and daily work plans for all activities. The results of the case study clearly illustrate the original contributions of the developed model and its novel capabilities that are expected to support airport and construction planners in their efforts to improve the cost-effectiveness and functional performance of airports during airside expansion projects.

What is the optimal fertigation start time and frequency in lettuce seedlings?

Although lettuce is one of the most important vegetable crops cultivated in Brazil, producers conduct seedling production empirically, as there are no published reports on the optimal start time and management strategy for seedling fertigation. The present aimed to assess the influence of fertigation management on the growth, physiological aspects and nutritional status of lettuce seedlings and to determine the optimal fertigation start time and frequency. Two experiments were conducted, each with a randomized block design and six repetitions. The first consisted of six treatments, namely six fertigation start times at 0, 3, 6, 9, 12, and 15 d after emergence (DAE), and the second consisted of five treatments, representing different application frequencies at 3, 4, 5, 6, and 7 d intervals. The assessment of nutrient accumulation levels and biometric and physiological characteristics of the seedlings were performed after transplanting. Fertigation start times significantly affected 14 of the 18 variables assessed, particularly the number of leaves, shoot dry weight, leaf area, initial chlorophyll fluorescence, and P, K, Ca, Mg, and S accumulation. The best results for ten variables were obtained when fertigation began at emergence, with values 17.77 - 35.63% higher than those at fertigation onset at 15 DAE. Application frequency only influenced chlorophyll content and N, P, K, and S accumulation, with optimal results obtained at 3 - 6 d intervals. Beginning fertigation at plant emergence favors dry weight production, nutrition and photosynthesis and shortens the production time of lettuce seedlings. The optimal start time for lettuce seedling fertigation is at emergence, with application performed every 6 d.

Identification of Optimal Starting Time Instance to Forecast Net Blotch Density in Spring Barley with Meteorological Data in Finland

The performance of meteorological data-based methods to forecast plant diseases strongly depends on temporal weather information. In this paper, a data analysis procedure is presented for finding the optimal starting time for forecasting net blotch density in spring barley based on meteorological data. For this purpose, changes in the information content of typically measured weather variables were systemically quantified in sliding time windows and with additionally generated mathematical transformations, namely with features. Signal-to-noise statistics were applied in a novel way as a metric for identifying the optimal starting time instance and the most important features to successfully distinguish between two net blotch densities during springtime itself. According to the results, the information content of meteorological data used in classifying between nine years with and four years without net blotch reached its maximum in Finnish weather conditions on the 41st day from the beginning of the growing season. Specifically, utilising weather data at 41–55 days from the beginning of the growing season maximises successful forecasting potential of net blotch density. It also seems that this time instance enables a linear classification task with a selected feature subset, since the averages of the metrics in two data groups differ statistically with a minimum 68% confidence level for nine days in a 14-day time window.