Average Loss Research Articles

Analysis of partial load loss of the PCS and internal storage battery loss in residential PV power generation and storage battery systems

AbstractThis study aims to quantify the amount of loss due to partial load of power conditioning system (PCS) and internal loss of storage battery in residential photovoltaic (PV) power generation and storage battery system by using home energy management system (HEMS) data. After identifying the configuration of the PV power generation and storage battery system, HEMS data on PV power generation, household demand, storage battery charging, storage battery discharging, purchased power and sold power were extracted and analyzed according to the research purpose. As a result, the loss due to partial load of the PCS and the average internal loss of the storage battery were quantified. In addition, it was confirmed that a more realistic system simulation could be performed by considering the impact of the partial load of the PCS and the average internal loss of the storage battery.

Detailed Investigation of the Eddy Current and Core Losses in Coaxial Magnetic Gears through a Two-Dimensional Analytical Model

This work introduces a 2D model that calculates power losses in coaxial magnetic gears (CMGs). The eddy current losses of the magnets are computed analytically, whereas the core losses of the ferromagnetic segments are computed using an analytical–finite element hybrid model. The results were within 1.51% and 3.18% of those obtained from an FEA for the eddy current and core losses in the CMG for an indicative inner rotor speed of 2500 rpm. In addition, the significance of the circumferential magnet segmentation is demonstrated in the CMGs. Furthermore, a parametric investigation of the efficiency of the system for different applied external loads is carried out. Finally, a mesh sensitivity analysis is performed, along with the computation of the average power losses throughout one full period, resulting in an at least 80% reduction in computational costs with a negligible effect on accuracy. The developed model could be a valuable tool for the minimization of power losses in CMGs since it combines high accuracy with a low computational cost.

The management of goal-directed fluid therapy during cytoreductive surgery and hyperthermic intraperitoneal chemotherapy.

Cytoreductive surgery is a surgical treatment approach that has been applied over the last 3 decades in patients with peritoneal metastases originating from intraabdominal organs. Goal-directed fluid therapy (GDFT) is an approach in which a patient fluid therapy during a medical procedure or surgery is carefully managed based on a specific goal. In this study, we aimed to present the results of GDFT in patients who underwent cytoreductive surgery for peritoneal carcinomatosis (PC) during the perioperative period. This retrospective study included 398 patients patient who underwent cytoreductive surgery + hyperthermic intraperitoneal chemotherapy (CRS + HIPEC) due to PC originating from intraabdominal malignancies. Of the cases, 233 (58.6%) were female, and 165 (41.4%) were male patients. The mean age was 58.9. Perioperative findings revealed an average PC score of 12 (3-24), average lactate levels of 3 (2-7) mmol/L, Pao2/fio2 of 3.3 (2.4-4.1) mm Hg, mean arterial pressure (MAP) of 60 (55-70), average surgery duration of 6.5 hours (3-14), and average blood loss of 400 (200-4000) cc. The mean intraoperative fluid rate was 6.4 mL/kg/h (IQR 5.8-7.1). Sixteen (16.3%) patients experienced Clavien-Dindo Grade 3-4 adverse events. Within 30 days, 25 patients (6.3%) died. CRS + HIPEC procedures utilizing perioperative GDFT along with advanced anesthesia monitoring devices have shown successful application, offering an alternative to traditional and restrictive fluid management approaches.

Management and Outcomes of Kidney Transplant Candidates With Severe Pulmonary Hypertension: A Single-center Strategy and Experience.

Severe pulmonary hypertension (PH) is associated with high mortality posttransplant and thus is considered a contraindication to kidney transplantation. In this study, we describe the pretransplant management and posttransplant outcomes in patients with severe PH using a multidisciplinary approach. Between 11 of 2013 and 8 of 2022, we identified all patients with severe PH on initial pretransplant workup who underwent ultrafiltration (UF) or medical therapy for PH before transplant. Posttransplant we evaluated the perioperative course, renal function, graft, and patient survival. We compared survival to those who remained waitlisted or were delisted. Three-two patients (mean age = 55.03 ± 10.22 y) diagnosed with severe PH on pretransplant screening echocardiogram. Thirty patients (94%) were subjected to a median of 4 (range, 3-8) UF sessions with an average weight loss of 4.33 ± 2.6 kg. Repeat assessment of PH revealed a decline in mean pulmonary artery systolic pressure from 67 ± 12 mm Hg to 43 ± 13 mm Hg (P < 0.0001). Seventeen patients (53%) received a kidney transplant. The mean estimated Glomerular Filtration Rate at 3, 6, 9, and 12 mo was 72 ± 27, 72 ± 28, 75 ± 29, and 75 ± 29 mL/min/1.73 m2. Among, those who underwent transplantation both graft and patient survival was 100% at 1-y posttransplant. Overall, since the UF intervention, at a median follow-up of 88 ± 12 mo those transplanted had a patient survival of 88% while those who remained on dialysis had a survival of 53% (P = 0.0003). In this single-center study, we report postcapillary PH can be a significant contributor to elevations in pulmonary artery systolic pressure. Using a multidisciplinary approach, PH can improve with volume removal and phosphodiesterase 5 inhibitors therapy leading to a successful posttransplant outcome.

Ecological and socioeconomic impacts of Lantana camara invasion: A case study in central India

The study investigates the impact of Lantana camara, an invasive alien species, on biodiversity, agricultural productivity, and non-timber forest products (NTFP) in central India. The aggressive growth and spread of the weed have resulted in the displacement of native flora and fauna, leading to substantial ecological and economic consequences. Regression analysis reveals a statistically significant negative correlation between proximity to Lantana camara infested plots and average annual crop loss, with closer proximity resulting in higher crop destruction. Additionally, a Wilcoxon signed-rank test confirms substantial reductions in NTFP collection post-infestation, highlighting significant economic losses for local communities reliant on these resources. The study also employs linear and non-linear regression analyses to assess the impact of Lantana camara infestation on species richness across various vegetation species, revealing a consistent negative effect on biodiversity. ANOVA and SIMPER analyses further corroborate these findings, indicating significant decreases in species richness, particularly among NTFP species. The results underscore the urgent need for effective management strategies to mitigate the adverse ecological and socioeconomic effects of Lantana camara invasions, emphasizing conservation efforts and sustainable practices to support the livelihoods of affected communities.

Surgical treatment of Nutcracker Syndrome

The objective of this paper is to report early and mid-term outcomes of the surgical treatment Nutcracker Syndrome (NCS) in a single-center prospective study. Between January 2019 and September 2023, five patients with symptomatic NCS were treated at our center using left renal vein caudal transposition on the inferior vena cava, conducted through a midline incision of approximately 12 cm and a transperitoneal technique. Patient characteristics, presentation, length of hospital stay, and complications were analyzed. All diagnoses were established after clinical evaluation, ultrasound scanning, and radiological investigations, which confirmed left renal vein compression between the aorta and the Superior Mesenteric Artery (SMA). The average operating time was 159 minutes, with an average blood loss of 205 mL. There was no need for blood transfusions. Intensive care stay was not required and there were no early complications. The mean length of stay was 3.5 days. At a mean follow-up of 18.8 months, one patient reported persistent hematuria, and therefore underwent a secondary procedure, which incorporated patch venoplasty using the great saphenous vein. In our experience, left renal vein transposition appears to be a safe and effective procedure for the surgical management of severe NCS.

Online sorting of surface defective walnuts based on deep learning

To address concerns regarding walnut shell damage and inadequate sorting precision during the mechanized sorting of walnuts, a walnut automatic sorting machine was designed based on deep learning and experimental research. Initially, the rationality of the design was verified through experiment. Then, three deep learning semantic segmentation algorithms, namely PSPnet, U-net, and Deeplabv3+, were selected to train walnut detection models. Results indicated that the U-net algorithm proved to be the most effective, achieving a Mean Intersection over Union of 96.71% and a Mean Pixel Accuracy value of 98.52%. Finally, performance tests were conducted on the prototype machine, yielding results with an average sorting efficiency of 51.70 kg/h, an average loss rate of 6.50%, and an average accuracy of sorting walnuts of 92.98%. The findings can provide insights for future structural improvements and operational parameter optimization of walnut automatic sorting machines.

Solving large-scale electricity market pricing problems in polynomial time

In centralized wholesale electricity markets worldwide, market operators use mixed-integer linear programming to solve the allocation problem. Prices are typically determined based on the duals of relaxed versions of this optimization problem. The resulting outcomes are efficient, but market operators must pay out-of-market uplifts to some market participants and incur a considerable budget deficit that was criticized by regulators. As the share of renewables increases, the number of market participants will grow, leading to larger optimization problems and runtime issues. At the same time, non-convexities will continue to matter, e.g., due to ramping constraints of the generators required to address the variability of renewables or non-convex curtailment costs. We draw on recent theoretical advances in the approximation of competitive equilibrium to compute allocations and prices in electricity markets using convex optimization. The proposed mechanism promises approximate efficiency, no budget deficit, and computational tractability. We present experimental results for this new mechanism in the context of electricity markets, and compare the runtimes, the average efficiency loss of the method, and the uplifts paid with standard pricing rules. We find that the computations with the new algorithm are considerably faster for relevant problem sizes. In general, the computational advantages come at the cost of efficiency losses and a price markup for the demand side. Interestingly, both are small with realistic problem instances. Importantly, the market operator does not incur a budget deficit and the uplifts paid to market participants are significantly lower compared to standard pricing rules.

A simulation-based genetic algorithm for a semi-automated warehouse scheduling problem with processing time variability

For warehouse operations, efficiently scheduling the available resources is crucial to improve the productivity and customer satisfaction. This paper proposes a simulation-based evolutionary algorithm for order scheduling and multi-robot task assignment in a robotic mobile fulfillment system. The algorithm proactively deals with the effects of the processing time variability by evaluating schedules based on both its system performance as well as its robustness under uncertain conditions. The algorithm implements an efficient resource allocation method and a variance reduction technique to reduce the overall computational burden. The experimental results show that the techniques to reduce the computational time are effective and can significantly reduce the amount of simulations required for the fitness evaluation. If a candidate schedule is allocated insufficient simulation replications it can lead to an inaccurate estimate of its long-term average performance. This could lead to an average performance loss of 7.3 %. Furthermore, the proactive scheduler is able to generate schedules that are more robust compared to deterministically generated. A reduction in the average operational cost of about 5 % can be reached, compared to a deterministically generated schedule. The paper reveals the relevance of identifying and modeling uncertainty when designing schedules in an operational system, rather than looking for optimal schedules for ideal scenarios.

SchNetPack Hyperparameter Optimization for a More Reliable Top Docking Scores Prediction.

Options to improve the extrapolation power of the neural network designed using the SchNetPack package with respect to top docking scores prediction are presented. It is shown that hyperparameter tuning of the atomistic model representation (in the schnetpack.representation) improves the prediction of the top scoring compounds, which have characteristically a low incidence in randomized data sets for training of machine learning models. The prediction robustness is evaluated according to the mean square error (MSE) and the entropy of the average loss landscape decrease. Admittedly, the improvement of the top scoring compounds' prediction accuracy comes with the penalty of worsening the overall prediction power. It is revealed that the most impactful hyperparameter is the cutoff (5 Å is reported as the optimal choice). Other parameters (e.g., number of radial basis functions, number of interaction layers of the neural network, feature vector size or its batch size) are found to not affect the prediction robustness of the top scoring compounds in any comparable way relative to the cutoff. The MSE of the best docking score prediction (below -13 kcal/mol) improves from ca. 3.5 to 0.9 kcal/mol, while the prediction of less potent compounds (-13 to -11 kcal/mol) shows a lesser improvement, i.e., a decrease of MSE from 1.6 to 1.3 kcal/mol. Additionally, oversampling and undersampling of the training set with respect to the top scoring compounds' abundance is presented. The results indicate that the cutoff choice performs better than over- or undersampling of the training set, with undersampling performing better than oversampling.

Evaluation of metabolic changes in clinic attendees with therapeutic carbohydrate restriction

Background: Obesity and related metabolic health disorders are major clinical problems that have become increasingly prevalent worldwide.Aim: This before-after study examined the impact of therapeutic carbohydrate restriction (TCR) in managing metabolic health and promoting weight loss in a clinical setting using indirect calorimetry (IC).Setting: Data were collected from medical records obtained from a specialised allied health clinic focusing on metabolic health.Methods: The study analysed retrospective data from 202 overweight or obese participants (77% female, mean age 47.3) who received TCR as part of a behavioural modification programme involving multiple visits where their lifestyle, body composition and respiratory quotient (RQ), a key indicator of fat oxidation were recorded.Results: The study found that TCR improved fat oxidation in 84% of participants at short term visit (around 2 weeks), with an average weight loss of 1.8 kg. At medium term visit (around 12 weeks), 82% of participants maintained an increase in fat oxidation rate, with an average weight loss of 3.9 kg. In addition, among those with recorded body composition and waist circumference, 71% of weight lost was from fat, with an average reduction of 4.9 cm in waist measurements.Conclusion: This real-world study suggests that personalised TCR guided by IC can be an effective strategy for improving metabolic flexibility to help manage excess weight and related co-morbidities in a free-living population. Further research is needed to examine the long-term effects of TCR using this approach.Contribution: The utilisation of IC allows for the examination of individual shifts and improvements in metabolism among patients undergoing TCR.

Navigating Insurance Challenges: A Decision Tree Model for Insurance Pricing and Risk Strategy

Amid escalating natural disasters intensified by climate change, accurately assessing risks and determining insurance rates in disaster-prone areas present significant challenges to the insurance industry, impacting the underwriting decisions and strategies correspondingly. This article employs a frequency-loss degree framework to quantify meteorological disaster risk as the Annual Average Loss (AAL), which was classified into three categories (severe, moderate, and mild) further. Utilizing a Poisson Distribution to process extreme event data and integrating it with data from typical years into a comprehensive prediction model, this approach facilitates enhanced risk assessment and premium estimation. A decision tree model was further established to explore insurance institution’s underwriting decisions and risk strategies on the basis of monetary benefits and mental utility respectively, highlighted by case studies in Australia and the Philippines. The findings underscore the necessity for insurers to incorporate advanced decision-making tools taking utility factors into account, to navigate the complexities of risk and pricing in vulnerable areas efficiently. A tendency was observed among insurers to prefer conservative strategies in medium-risk areas, like the Philippines, over aggressive underwriting in high-risk zones, such as Western Australia. This suggests further research into expanding the model's applicability and delving into the evolving influence of climate change on the insurance industry.

Pricing and replenishment decision problem based on time series prediction and optimization algorithm

The pricing of vegetable products is an important research topic that involves multiple aspects such as agricultural production, market supply and demand, consumer interests, and social benefits. Vegetable products have characteristics such as short production cycles, short shelf life, large price fluctuations, and high demand elasticity, which pose challenges to pricing decisions. To develop replenishment decisions that maximize the profits of supermarkets, the author establishes a mathematical model for the total sales volume and cost add-on pricing of each vegetable category. First, the cost, cost add-on coefficient, and loss rate of individual products in the same category are summed according to the weight of sales, and the corresponding average cost, cost add-on coefficient, and average loss rate of the category are obtained. This initially achieves a negative correlation between the sales trend and the cost add-on coefficient using a function. Then, by constructing a LSTM neural network model and using known data to predict the sales of each category, the predicted sales volume of the model is used as the sales benchmark value. The relationship function between the sales trend and the cost add-on coefficient is supplemented, and the optimization algorithm is used to find the cost add-on coefficient value, the total daily replenishment quantity, and the maximum profit value that maximize the profits of supermarkets.

Study on the clinical characteristics of auditory neuropathy patients with normal pure tone average or mild hearing loss

Objective: The purpose of this study was to analyze the clinical characteristics of auditory neuropathy (AN) patients with normal hearing or mild hearing loss. Methods: Data from Multicenter Study on Clinical Diagnosis and Intervention of Acoustic Neuropathy (registration number: ChiCTR2100050125). According to the Chinese clinical practice guideline of auditory neuropathy (version 2022), these patients divided into two groups: the normal hearing group (PTA Normal, PTAN group, the average hearing threshold<20 dB HL) and the mild hearing loss group (PTA Mild hearing loss, PTAM group, the average hearing threshold between 20-35 dBHL). The audiology characteristics, clinical features, and follow-up were analyzed. Data analysis was conducted using GraphPad Prism 8 and SPSS 20.0 software. Results: A total of 75 AN with normal hearing or mild hearing loss were included in this study. The PTAN group consisted of 19 patients (38 ears), including 12 males and 7 females. The average onset age was (16.9±4.5) years old, while the test age was (22.1±5.8) years old for PTAN group. The PTAM group consisted of 56 patients (112 ears), including 29 males and 27 females. The average onset age was (16.2±7.9) years old, while the test age was (23.9±9.0) yeas old for PTAM group. The average hearing threshold of low frequency (0.125-0.5 kHz) was significantly decreased. ABR disappeared in 86.00% (126/150) of the patients. The speech recognition rate was 71.80±22.44% in the PTAN group and 58.08±29.28% in the PTAM group.-SP/AP was 0.98±0.47 in the PTAN and 1.07±0.63 in PTAM group; 40 (53.33%) patients had tinnitus. 29 patients (58 ears) were followed up, including 10 patients (20 ears) in the PTAN group and 19 patients (38 ears) in the PTAM group. There was no significant change in hearing threshold in short-term follow-up (<3 years). With the extension of the disease duration (>3 years), the PTAN group tended to decrease at low frequency, and the PTAM group decreased at high frequency first. The hearing threshold at 0.25 kHz in the PTAN group and 4 kHz in the PTAM group decreased significantly. Conclusions: AN patients with normal hearing or mild hearing loss exhibit abnormal results in audiological examination results, including ABR, electrocochleography and speech discrimination score. A combination of audiological tests should be used to make the diagnosis of AN. With the progression of the disease, AN with normal hearing or mild hearing loss tends to decrease.

Bismuth-constructed high-speed channeled for Bi/Sb2SnO5@PCFs composite as high-rate and long-life anode for sodium-ion batteries

To cope with the charging-time and driving-range issues of the power batteries, a composite and phase modification tactics is manifested to increase the cycling stability and rate capability of the Sb2SnO5 (SSO) anode for sodium-ion batteries (SIBs). The as-fabricated Bi/SSO@PCFs composite with Bi nanocrystals homogeneously dispersed on and around the SSO surface is prepared by an electrospinning method. The excellently dispersed Bi nanocrystals realize an effective contact with SSO, which effectively lowers the electron conduction barriers and promotes the sodium ion release as well as the transport upon the desodiation/sodiation process, increasing the rate capacity and cycle stability of the SSO anode. Importantly, a high-speed ion channel is constructed through the special layered Bi, and SbBi phase. The prepared Bi/SSO@PCFs anodes deliver a high rate capacity up to 25 A g−1 and long cycle life of 5000 cycles with 83 % capacity retention rate, sustaining an average capacity loss of 0.0034 % for each cycle. Particularly, the intercalation of Na+ between layer-structure Bi and SbBi galleries provides a good basis for excellent cycle performance due to small volume change and unobstructed ion channels. This finding provides an effective strategy to establish ion transport highways, which essentially increase the rate-capacity and cycle-life of the SSO-based anodes for SIBs.

114 Effects of greater levels of soy protein and methionine on periparturient health of sows

Abstract Sow prolificacy in the U.S. continues to trend greater, as does sow mortality. Replacement of soy protein (SBM) in sow diets with corn and purified amino acids (AA), may impact the health of highly prolific sows. In 2015, Denmark increased recommendations for SID methionine (MET) to SID lysine (LYS), MET:LYS to 32%, NRC (2012) recommend 27%. The primary objective of this research was to evaluate SBM and MET at greater levels for their effects on markers of health in the peripartum and lactation periods. A total of 38 parity 1 to 3 females (PIC 1050) were utilized with a starting body weight (BW) of 223.4kg ± 13.0 SD. On d 85 of gestation, sows were allocated by BW and parity to one of four treatments: 1 - 30% SBM (30% of diet), 36% MET:LYS; 2 - 15% SBM, 36% MET:LYS; 3 - 30% SBM, 27% MET:LYS; 4 - 15% SBM, 27% MET:LYS. Sows were fed dietary treatments 28 d pre-farrow, according to BW, and ad libitum throughout lactation. Body condition by caliper (BCS), BW, and backfat (BF) were measured on d 0, 21, 2 d post-farrow, and weaning. Sows were assigned a farrowing ease score of 1 to 4 (1-easy to 4-difficult) based on duration, restless activity, savaging, and assistance required. Continuous glucose monitors (CGM) were placed on a subset of sows (n = 12) on d 113 of gestation through 3 d post-farrow. Data were analyzed using the GLM procedure in SAS with sow serving as the experimental unit. A planned t-test was performed on CGM glucose data. Two sows were removed during lactation. The combined effect of 30% SBM and 36% MET:LYS produced an average lactation BW loss of 0.3 kg, while the 15% SBM and 27% MET:LYS treatment, diets similar to NRC, lost an average of 18.1kg. Sows fed the 30% SBM diets had less lactation BW loss than 15% SBM (Table 1; P &amp;lt; 0.10). Sows fed 36% MET:LYS lost less BW than those fed 27% MET:LYS (P &amp;lt; 0.05). The 36% MET:LYS group also lost less backfat during lactation and had lower pre- and post-farrow body temperatures than 27% MET:LYS (P &amp;lt; 0.01 and P &amp;lt; 0.05, respectively). While no differences in blood glucose were observed, in sows with CGM, greater levels of SBM decreased interstitial glucose concentrations (P = 0.055). In conclusion, greater inclusion of SBM and increasing the MET:LYS ratio in sow diets may improve periparturient changes in body condition and health outcomes.

Export priority technique for Uni-portal thoracoscopic left upper lobectomy

BackgroundFurther explore the safety and feasibility of Uni-portal video assisted thoracoscopic (UVATS) left upper lobectomy by optimizing the treatment of incisions and blood vessels.MethodsWe conducted a retrospective analysis of data from 32 patients who underwent UVATS left upper lobectomy and systematic mediastinal lymph node dissection utilizing the Export priority technique between January 2021 and December 2022. We documented perioperative indicators, including surgical time, intraoperative blood loss, the number of lymph nodes dissected, and postoperative pathological staging.ResultsAll surgeries were conducted utilizing the Export priority technique in UVATS. The mean surgical duration was (98.93 ± 14.98) minutes, with an average intraoperative blood loss of (79.53 ± 37.96) ml. The mean count of dissected lymph nodes was (13.96 ± 2.69). The length of hospital Stay averaged (5.62 ± 1.81) days. On the first postoperative day, the thoracic drainage volume was (101.87 ± 49.46) ml. The mean duration of postoperative thoracic tube insertion was (3.1 ± 1.84) days. No occurrences of postoperative hoarseness, pulmonary infection, or complications such as bronchopleural fistula were observed.ConclusionThe application of the Export priority technique improves the safety and feasibility of UVATS left upper lobectomy.

Whole-farm yield map datasets – Data validation for exploring spatiotemporal yield and economic stability

CONTEXTStatistical methods used for delineation of field management zones and yield stability are frequently only applied to relatively small areas, with few studies performing rotational, whole-farm economic spatiotemporal appraisals. To enable accurate economic analysis, yield map datasets must contain minimal errors while cleaning procedures are often used to remove errors, it is rare that cleaned data is validated before its application. OBJECTIVEThe objective of this study was to process, validate and combine spatial statistical approaches for a rotational yield map dataset from a whole-farm across 7 crops in a winter wheat based rotation. Developing a framework for using validated yield map datasets to support precision agriculture techniques that are applicable for farm-level decision making. METHODSThe rotational completeness of a 10 year combine yield map dataset for a 435 ha farm in Eastern England was assessed. The dataset was cleaned statistically, and its accuracy assessed by comparison with recorded yields from trailer weigh cells. The cleaned, validated, and corrected yield map dataset was used to identify management zones across the whole farm using fuzzy clustering. The temporal stability of management zones and economic performance across the rotation was also assessed. RESULTS AND DISSCUSIONData cleaning methods removed 16% of data points, improving the degree of spatial correlation within the individual yield maps. Independent validation demonstrated varied accuracy of yield maps from combine harvester data and errors in wheat ranged from 0.53 to 1.53 t/ha RMSE. These errors have implications for researchers using combine yield data to develop and validate precision agriculture technologies. This data set required correction before yield data can be applied with confidence for on-farm decision making. Compared to the zones with the highest margin in each field, 34% of zones had an average annual margin loss of >£100 ha. The temporal stability of the resulting management zones also varied. Areas with the lowest economic performance and greatest yield stability across years will potentially see the greatest economic and environmental benefits from precision agriculture techniques. SIGNIFICANCEThe accuracy of combine yield map data should not be assumed. The application of these datasets, including for the identification of management zones or in developing precision agriculture techniques should attempt to address this through data cleaning and validation procedures. Only then should it be used for on farm decision making, such as identifying areas with the most economic benefit by applying precision agriculture tools such as variable rate nutrient applications.

Rate of Initial Optic Nerve Head Capillary Density Loss and Risk of Visual Field Progression

Rapid initial optic nerve head capillary density loss may be used to assess the risk of glaucoma visual field progression. To investigate the association between the rate of initial optic nerve head capillary density loss from optical coherence tomography angiography (OCTA) and visual field progression. This was a retrospective study of a longitudinal cohort at a glaucoma referral center. A total of 167 eyes (96 with primary open-angle glaucoma and 71 with glaucoma suspect) of 109 patients were monitored for a mean (SD) of 5.7 (1.4) years from January 2015 to December 2022. Data analysis was undertaken in April 2023. The rates of initial capillary density and average retinal nerve fiber layer loss were calculated from the first 3 optic nerve head OCTA and OCT scans, respectively, during the initial follow-up (mean [SD], 2.0 [1.0] years). Based on the median rate, eyes were categorized into fast and slow progressor groups. The association between initial capillary density change or retinal nerve fiber layer thinning and visual field progression was evaluated using linear-mixed and time-varying Cox models. A total of 167 eyes of 109 patients (mean [SD] age, 69.0 [11.1] years; 56 [51.4%] female and 53 [48.6%] male) were assessed. Eighty-three eyes were slow OCTA progressors, while 84 eyes were fast with mean capillary density loss of -0.45% per year and -1.17% per year, respectively (mean difference, -0.72%/year; 95% CI,-0.84 to -0.60; P < .001). Similarly, 83 eyes were slow OCT progressors, while 84 eyes were fast with mean retinal nerve fiber layer thinning of -0.09 μm per year and -0.60 μm per year, respectively (mean difference, -0.51 μm/year; 95% CI,-0.59 to -0.43; P < .001). The fast OCTA and OCT progressors were associated with more rapid visual field loss (mean difference, -0.18 dB/year; 95% CI,-0.30 to -0.06; P = .004 and -0.17 dB/year; 95% CI,-0.29 to -0.06; P = .002, respectively). Fast OCTA progressing eyes were more likely to have visual field progression (hazard ratio, 1.96; 95% CI, 1.04-3.69; P = .04). Seventeen of 52 eyes (32.7%; 95% CI, 32.5-32.8) with fast OCTA and OCT progression developed subsequent visual field likely progression. Rapid initial optic nerve head capillary density loss from OCTA was associated with a faster rate of visual field progression and a doubling of the risk of developing event progression in this study. These findings may support clinical use of OCTA and OCT optic nerve head measurements for risk assessment of glaucoma progression.

Effects of damage initiation points of depth-damage function on flood risk assessment

The flood depth in a structure is a key factor in flood loss models, influencing the estimation of building and contents losses, as well as overall flood risk. Recent studies have emphasized the importance of determining the damage initiation point (DIP) of depth-damage functions, where the flood damage is assumed to initiate with respect to the first-floor height of the building. Here we investigate the effects of DIP selection on the flood risk assessment of buildings located in Special Flood Hazard Areas. We characterize flood using the Gumbel extreme value distribution’s location (μ) and scale (α) parameters. Results reveal that average annual flood loss (AAL) values do not depend on μ, but instead follow an exponential decay pattern with α when damage initiates below the first-floor height of a building (i.e., negative DIP). A linear increasing pattern of the AAL with α is achieved by changing the DIP to the first-floor height (i.e., DIP = 0). The study also demonstrates that negative DIPs have larger associated AAL, thus contributing substantially to the overall AAL, compared to positive DIPs. The study underscores the significance of proper DIP selection in flood risk assessment.