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Introduction: In response to the COVID-19 pandemic, hospitals reported decreased admissions for acute surgical diagnoses, but scant data was available to quantify the decrease and its consequences. The objective of this study was to examine the incidence of acute care surgery encounters before and during the COVID-19 pandemic., Materials and Methods: A retrospective cohort study was performed at a single, urban, United States safety-net hospital. Emergency room encounters, admissions, non-elective surgical procedures, patient acuity, and surgical complications were compared before and after the start of the COVID-19 pandemic. The primary outcome of the study was the incidence rate (IR) and incidence rate ratios (IRR) for surgical admissions, laparoscopic appendectomy, and urgent laparoscopic cholecystectomy., Results: During the COVID-19 (exposure) time period, the number of nonelective procedures was 143 (IR 4.76) which was significantly lower than the control periods (n = 431, IR 7.2), P < 0.001. During the COVID-19 exposure period, there were significantly fewer urgent cholecystectomies performed (1.37 per day versus 2.80-2.93 per day, P < 0.001). There was a trend toward fewer appendectomies performed, but not significant. There was little difference in patient acuity between the exposure and control periods. A higher proportion of patients that underwent urgent cholecystectomy during the COVID time period had been seen in the ED in the prior 30 d (22% versus 5.6%)., Conclusions: Surgical volume significantly decreased during the COVID-19 pandemic. Management of acute cholecystitis may require re-evaluation as nonsurgical management appears to increase repeat presentations., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Background: Laparoscopic hiatal hernia repair is commonly performed with a 1 to 2 night hospitalization. Our aim was to compare the feasibility and short-term outcomes of same-day surgery (SDS) laparoscopic hiatal hernia repair with an opioid-based anesthesia protocol (OBAP) vs an opioid-free anesthesia protocol (OFAP)., Study Design: Outcomes and pharmacy costs of repairs with OBAP were compared with OFAP. Values were expressed as median (interquartile range) and costs as means., Results: There were 244 primary laparoscopic repairs. OBAP was used in 191 of 244 (78.3%) vs OFAP in 53 of 244 (21.7%). The length of stay was 1 day (0 to 2) vs 0 days (0 to 1), p = 0.006. There was no difference between the percentage of patients requiring analgesics and dosage between the 2 groups. SDS was planned in 157 and performed in 74 of 122 (60.7%) vs 33 of 35 (94.3%), p < 0.001. The age was 56 years (45 to 63) vs 60 years (56 to 68), p = 0.025. There were more type I hiatal hernia in SDS-OBAP and more type III and IV in SDS-OFAP, p = 0.031. American Society of Anesthesiologists Physical Status was II (II-III) vs III (II-III), p = 0.045. SDS was not performed in 50 of 157 (31.8%), 48 of 122 (39.3%) vs 2 of 35 (5.7%), p < 0.001. Out of 157 planned SDS, nausea/retching were causes of transition in 19 of 122 (15.6%) vs 0 of 35 (0%), p = 0.020. Multivariable logistic regression showed the odds of SDS were 8.21 times (95% CI 3.10 to 21.71; p < 0.001) greater in OFAP compared with OBAP, adjusting for sex, age, body mass index, American Society of Anesthesiologists Physical Status, type of hiatal hernia, type of procedure, and duration of the operation. Patients with opioid medication after SDS discharge were 74 of 74 (100%) vs 22 of 33 (66.7%), p < 0.001., Conclusions: Opioid-free anesthesia increases the feasibility of SDS hiatal hernia repair with less perioperative nausea and comparable pain control and pharmacy cost., (Copyright © 2022 by the American College of Surgeons. Published by Wolters Kluwer Health, Inc. All rights reserved.)

Background: Biliary anastomotic stricture (BAS) is an uncommon complication of pancreaticoduodenectomy (PD). As PDs are performed more frequently, BAS may become a more common pathologic entity requiring clinical engagement. The aim of this study was to report the incidence of BAS in the modern era of pancreatic surgery and identify risk factors associated with it., Methods: Patients undergoing PD at the Johns Hopkins Hospital between 2007 and 2016 were identified using an institutional registry and clinicopathological features were analyzed to identify risk factors associated with BAS., Results: Of 2125 patients identified, 103 (4.9%) developed BAS. Factors independently associated with BAS included laparoscopic approach (HR:2.83,95%CI:1.35-5.92, p = 0.006), postoperative pancreatic fistula (HR:2.45,95%CI:1.56-4.16,p < 0.001), postoperative bile leak (BL) (HR:5.26,95%CI:2.45-11.28,p < 0.001), and administration of adjuvant radiation therapy (HR:6.01,95%CI:3.19-11.34,p < 0.001). Malignant pathology was associated with lower rates of BAS (HR:0.52,95%CI:0.30-0.92, p = 0.025). BL was associated with higher rates of early-BAS (HR:16.49,95%CI:3.28-82.94, p = 0.001) while use of Vicryl suture for biliary enteric anastomosis was associated with lower rates of early-BAS (HR:0.20,95%CI:0.05-0.93, p = 0.041)., Conclusion: Approximately 5% of patients undergoing PD experience BAS. Multiple factors are associated with the development and timing of BAS., (Copyright © 2021 International Hepato-Pancreato-Biliary Association Inc. Published by Elsevier Ltd. All rights reserved.)

Purpose: To determine the causes of benign hepaticojejunostomy strictures (BHSs) after pancreaticoduodenectomy (PD) and the outcome of endoscopic retrograde cholangiography (ERC) treatment for BHSs. Methods: A total of 175 patients who underwent PD between January 2013 and December 2020 and who were followed up for at least 1 year were included. Preoperative data, operative outcomes, and postoperative courses were compared between the BHS group and the group of patients who did not develop stenosis during follow-up (non-BHS group). The course of treatment in the BHS group was also examined. Results: BHS occurred in 13 of 175 patients (7.4%). Multivariate analysis of the BHS and non-BHS groups revealed that male sex (OR; 3.753, 95% CI; 1.029–18.003, P = 0.0448) and a preoperative bile duct diameter less than 8.8 mm (OR; 7.51, 95% CI; 1.75–52.40, P = 0.0053) were independent risk factors for the development of BHS. In the BHS group, all patients underwent ERC using enteroscopy. The success rate of the ERC approach to the bile duct was 92.3%. Plastic stents were inserted in 6 patients, and metallic stents were inserted in 3 patients. The median observation period since the last ERC was 17.9 months, and there was no recurrence of stenosis in any of the 13 patients. Conclusions: Patients with narrow bile ducts are at greater risk of BHS after PD. Recently, BHS after PD has been treated with ERC-related procedures, which may reduce the burden on patients. [ABSTRACT FROM AUTHOR]

This study introduces a novel method utilizing hyperspectral imaging for instantaneous ore-waste analysis of drill cuttings. To implement this technique, we collected samples of drill cuttings at regular depth intervals from five blast holes in an open pit gold mine and subjected them to scanning using a hyperspectral imaging system. Subsequently, we employed two distinct methods for processing the hyperspectral images. A knowledge-based method was used to estimate ore grade within each sampled interval, and a data-driven technique was employed to distinguish the ore and waste for each sample interval. Firstly, leveraging the mixed mineralogical composition of the samples, the Linear Spectral Unmixing (LSU) technique was utilized to predict ore grade for each sample. Additionally, the Gradient Boosting Classifier (GBC) was used as an efficient data-driven approach to classify ore-waste samples. Both methods rendered accurate results when they were compared with results obtained through laboratory X-ray diffraction (XRD) analysis and gold assay analysis for the same sample intervals. Adopting the proposed methodology in open pit mine operations can significantly enhance the process of grade control during blast hole drilling. This includes reducing costs, saving time, minimizing uncertainty in ore grade estimation, and establishing more precise ore-waste boundaries in resource block models. [ABSTRACT FROM AUTHOR]

The effect of stacking sequence on the physical and chemical properties of a hybrid composite composed of biomass sheep wool fiber and glass fiber reinforced with epoxy was investigated in this study. The hybrid composite was developed as an alternative material for engineering applications to harmful man-made glass fiber composites. The hybrid composite laminates were made by hand and had a total fiber volume fraction of 60% (biomass sheep wool fiber 30% and glass fiber 30%) and 40% reinforcement. Three distinct stacking sequences, STQ1, STQ2, and STQ3, were prepared and tested in accordance with ASTM standards. The results of the tensile and bending tests revealed that STQ1 biocomposites have higher strength and maximum bending than STQ2 and STQ3 composites. Furthermore, STQ1 biocomposite absorbed more moisture and chemicals than STQ2 and STQ3 composite. Morphological studies of fracture surfaces on biocomposites revealed that STQ1 has better interfacial bonding of fiber and matrix than other composites, confirming its suitability for lightweight applications. [ABSTRACT FROM AUTHOR]

We propose two explicit expressions to calculate the settling speed of solid atmospheric particles with prolate spheroidal shapes under the hypothesis of horizontal and vertical orientation. The first formulation is based on theoretical arguments only. The second method, valid for particles with mass median diameter up to 1000 µ m, is based on recent heuristic drag expressions based on numeric simulations. We show that these two formulations show equivalent results within 2 % for deq≤100 µ m and within 10 % for particles with deq≤500 µ m falling with a horizontal orientation, showing that the first, more simple, method is suitable for virtually all atmospheric aerosols, provided their shape can be adequately described as a prolate spheroid. Finally, in order to facilitate the use of our results in chemistry transport models, we provide an implementation of the first of these methods in AerSett v2.0.2, a module written in Fortran. [ABSTRACT FROM AUTHOR]

This study aims to demonstrate the potential of assessing future land cover degradation status by combining the forecasting capabilities of the Cellular-Automata and Markov chain (CA-Markov) models in Idris Selva with the land cover degradation (LCD) model in the Trends.Earth module. The study focuses on the upper Zambezi Basin (UZB) in southern Africa, which is one of the regions with high rates of land degradation globally. Landsat satellite imagery is utilised to generate historical (1993–2023) land cover and land use (LCLU) maps for the UZB, while the global European Space Agency Climate Change Initiative (ESA CCI) LCLU maps are obtained from the Trends.Earth module. The CA-Markov chain model is employed to predict future LCLU changes between 2023 and 2043. The LCD model in the Trends.Earth module in QGIS 3.32.3 is then used to assess the historical and forecasted land cover degradation status. The findings reveal that land cover degradation maps produced from local LCLU classifications provide more detailed information compared to those produced from the global ESA CCI LCLU product. Between 2023 and 2043, the UZB is predicted to experience a net reduction of approximately 3.2 million hectares of forest cover, with an average annual reduction rate of − 0.13%. In terms of land cover degradation, the UZB is forecasted to remain generally stable, with 87% and 96% of the total land cover area expected to be stable during the periods 2023–2033 and 2033–2043, respectively, relative to the base years 2023 and 2033. Reduction in forest cover due to the expansion of grassland, human settlements, and cropland is projected to drive land cover degradation, while improvements in forest cover are anticipated through the conversion of grassland and cropland into forested areas. It appears that using locally produced LCLU with high-resolution images provides better assessments of land degradation in the Trends.Earth module than using global LCLU products. By leveraging the opportunities offered by models with capacity to predict LCLU such as the CA–Markov model and the capabilities of the LCD model, as evidenced in this study, valuable forecasted information can be effectively obtained for monitoring land cover degradation. This information can then be used to implement targeted interventions that align with the objective of realising the United Nations' land degradation neutral world target by 2030. [ABSTRACT FROM AUTHOR]

This paper addresses the current existence of attribute reduction algorithms for incomplete hybrid decision-making systems, including low attribute reduction efficiency, low classification accuracy and lack of consideration of unlabeled data types. To address these issues, this paper first redefines the weakly labeled relative neighborhood discernibility degree and develops a non-dynamic attribute reduction algorithm. In addition, this paper proposes an incremental update mechanism for weakly tagged relative neighborhood discernibility degree and introduces a new dynamic attribute reduction algorithm for increasing the set of objects based on it. Meanwhile, this paper also compares and analyses the improved algorithm proposed in this study with two existing attribute reduction algorithms using 8 data sets in the UCI database. The results show that the dynamic attribute reduction algorithm proposed in this paper achieves higher attribute reduction efficiency and classification accuracy, which further validates the effectiveness of the algorithm proposed in this paper. [ABSTRACT FROM AUTHOR]

The concept of Image Phase Congruency (IPC) is deeply rooted in the way the human visual system interprets and processes spatial frequency information. It plays an important role in visual perception, influencing our capacity to identify objects, recognize textures, and decipher spatial relationships in our environments. IPC is robust to changes in lighting, contrast, and other variables that might modify the amplitude of light waves yet leave their relative phase unchanged. This characteristic is vital for perceptual tasks as it ensures the consistent detection of features regardless of fluctuations in illumination or other environmental factors. It can also impact cognitive and emotional responses; cohesive phase information across elements fosters a perception of unity or harmony, while inconsistencies can engender a sense of discord or tension. In this survey, we begin by examining the evidence from biological vision studies suggesting that IPC is employed by the human perceptual system. We proceed to outline the typical mathematical representation and different computational approaches to IPC. We then summarize the extensive applications of IPC in computer vision, including denoise, image quality assessment, feature detection and description, image segmentation, image registration, image fusion, and object detection, among other uses, and illustrate its advantages with a number of examples. Finally, we discuss the current challenges associated with the practical applications of IPC and potential avenues for enhancement. [ABSTRACT FROM AUTHOR]

The research on automatic monitoring methods for greenhouse gases and hazardous gas emissions is currently a focal point in the fields of environmental science and climatology. Until 2023, the amount of greenhouse gases emitted by the livestock sector accounts for about 11–17% of total global emissions, with enteric fermentation in ruminants being the main source of the gases. With the escalating problem of global climate change, accurate and effective monitoring of gas emissions has become a top priority. Presently, the determination of gas emission indices relies on specialized instrumentation such as breathing chambers, greenfeed systems, methane laser detectors, etc., each characterized by distinct principles, applicability, and accuracy levels. This paper first explains the mechanisms and effects of gas production by ruminant production systems, focusing on the monitoring methods, principles, advantages, and disadvantages of monitoring gas concentrations, and a summary of existing methods reveals their shortcomings, such as limited applicability, low accuracy, and high cost. In response to the current challenges in the field of equipment for monitoring greenhouse and hazardous gas emissions from ruminant production systems, this paper outlines future perspectives with the aim of developing more efficient, user-friendly, and cost-effective monitoring instruments. [ABSTRACT FROM AUTHOR]

The reliance on natural resources has gained extra attention from researchers and scientists due to population awareness, greenhouse depletion, and oil reserve depletion. The development of sustainable and renewable materials from biomass residues is promising biomaterials to substitute synthetic and plastic littering. The abundant availability of coconut shell and husk residues is having great potential for fiber/filler sources to develop biocomposites for structural and industrial applications. In this present study, five different types of biocomposite samples (CRS-0.0, CRS-2.5, CRS-5.0, CRS-7.5, and CRS-10.0) have been fabricated at a 30% constant weight fraction of coconut fiber with bio-epoxy matrix and varying the coconut particles weight faction by 2.5% and characterized their structural, physical, mechanical, and thermal behavior. The results examined that the inclusion of coconut particles improved the overall mechanical performance of the biocomposites and observed CRC-5.0 biocomposites have superior tensile strength (32.58%), and flexural strength (35.45%), and surface hardness (23.61%) compared to CRC-0.0 biocomposites. The impact strength, fracture toughness, and fracture energy are higher for CRC-2.5 biocomposites. CRC-5.0 biocomposites analyzed better thermal stability with a maximum degradation temperature of 358 °C and 24% char residue of coconut biomass at 800 °C. The surface morphology has been also analyzed to examine the fracture/failure behavior of biocomposites. Finally, the samples have been submerged in water, NaOH, and NaCl solution to examine the water uptake and corrosion behavior of developed biocomposites. Therefore, the development of bio-based product by utilizing agro/food waste has great potential and has the capabilities to replace conventional materials for various industrial applications. [ABSTRACT FROM AUTHOR]

Simple Summary: The diagnostic performance and interobserver variability of the contrast-enhanced CT currently used for evaluating arterial involvement from pancreatic cancer has limitations. The purpose of this study was to investigate the utility of reconstructed CT images perpendicular to the artery for assessing arterial involvement from pancreatic cancer and to compare the interobserver variability between it and the current diagnostic imaging method. We found that reconstructed CT images perpendicular to the splenic artery were feasible and showed less interobserver variability than current diagnostic method images. The purpose of this study was to investigate the utility of reconstructed CT images perpendicular to the artery for assessing arterial involvement from pancreatic cancer and compare the interobserver variability between it and the current diagnostic imaging method. This retrospective study included patients with pancreatic cancer in the pancreatic body or tail who underwent preoperative pancreatic protocol CT and distal pancreatectomy. Five radiologists used axial and coronal CT images (current method) and perpendicular reconstructed CT images (proposed method) to determine if the degree of solid soft-tissue contact with the splenic artery was ≤180° or >180°. The generalized estimating equations were used to compare the diagnostic performance of solid soft-tissue contact >180° between the current and proposed methods. Fleiss' ĸ statistics were used to assess interobserver variability. The sensitivity and negative predictive value for diagnosing solid soft-tissue contact >180° were higher (p < 0.001 for each) and the specificity (p = 0.003) and positive predictive value (p = 0.003) were lower in the proposed method than the current method. Interobserver variability was improved in the proposed method compared with the current method (ĸ = 0.87 vs. 0.67). Reconstructed CT images perpendicular to the artery showed higher sensitivity and negative predictive value for diagnosing solid soft-tissue contact >180° than the current method and demonstrated improved interobserver variability. [ABSTRACT FROM AUTHOR]

One of the trendiest areas in the world of materials research is multifunctional polymer nanocomposites. The long-term behaviour of fibre-reinforced polymer composites exposed to cryogenic environments is discussed in this article in light of current advancements. The composites were created using the standard hand layup procedure in order to achieve the aforementioned goals. Crown flower fibre (CF) serves as a reinforcement, while 3 wt.% of nano-SiO2 and 3 wt.% of zinc borates (4ZnO·B2O3·H2O) serve as fillers, and the LY566 type of epoxy resin with the HY 951 type of hardener were considered as a matrix system. To complete the mentioned objectives, three types of composites were fabricated: pure epoxy-based CF laminate, CF/3 wt.% of nano SiO2 hybrid, and CF/3 wt.% of nano 4ZnO·B2O3·H2O-based hybrid laminates. Analysis of the mechanical behaviour of composite materials that had been created was done under both normal and cryogenic circumstances at two distinct temperatures (−60 and 30 °C). To investigate the flammability properties of the hybrid composites, tests with horizontal and vertical flame retardants were conducted. X-ray diffraction and Fourier transform infrared spectroscopy studies were used to validate the nanofiller's existence. The manufactured CF/3 wt.% of SiO2-based hybrid composites have good mechanical capabilities in a cryogenic environment of −60 °C, according to the results. This is because the 3 wt% SiO2-loaded samples are more resistant to deformation and can take more force before breaking at the impact zone because they have a larger surface area per volume fraction and better adhesion. In terms of flammability characteristics, the hybrid CF/ 3 wt.% of 4ZnO.B2O3.H2O (zinc borate) exhibits better results (burning rate of 7.14 mm/min). The burning rate was reduced as a result of the use of nanofillers. This is due to zinc borate's promising flame-retardant qualities, which prevent flame spread and aid in flame extinguishment. [ABSTRACT FROM AUTHOR]

Background: Advanced cancer patients benefit less from aggressive therapies and more from goal-directed palliative management. Early and clearly documented goals-of-care discussions, including end-of-life decision making, are essential in this patient population. Integrated healthcare systems are comprehensive care models associated with improved quality of care and lower mortality compared to other healthcare models. The role of advance care planning within our system is understudied. Methods: Patients 18 years and older with a diagnosis of advanced-stage cancer were identified over a 6-month period. Expert panel review was performed to evaluate medical appropriateness of the selected diagnostic workup and management. The role and extent of care planning was reviewed in association with the clinical context. Results: In a cohort of 82 patients, evidence-based and individualized appropriateness of medical management was found to be consistent for all patients. Eighty-two percent of patients elected for oncologic-based treatment, 5% pursued active surveillance, and 11% did not receive treatment. Seventy-three percent of patients were referred to palliative care. Fifty-six percent of patients had a full goals-of-care conversation documented; yet only 9% of goals-of-care conversations were documented by an oncologist. Prognosis was documented fully for only 22% of patients. At the end of the study period, 43 patients were deceased (52%), further indicating the critical importance of documentation. Conclusions: Within our integrated health system, we found consistent guideline- and patient-directed diagnosis and management, along with frequent integration of palliative care services. Goals-of-care conversation and prognosis documentation, especially by the oncologist, remains an area of needed improvement. [ABSTRACT FROM AUTHOR]

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The team orienteering problem (TOP) is a well-studied optimization challenge in the field of Operations Research, where multiple vehicles aim to maximize the total collected rewards within a given time limit by visiting a subset of nodes in a network. With the goal of including dynamic and uncertain conditions inherent in real-world transportation scenarios, we introduce a novel dynamic variant of the TOP that considers real-time changes in environmental conditions affecting reward acquisition at each node. Specifically, we model the dynamic nature of environmental factors—such as traffic congestion, weather conditions, and battery level of each vehicle—to reflect their impact on the probability of obtaining the reward when visiting each type of node in a heterogeneous network. To address this problem, a learnheuristic optimization framework is proposed. It combines a metaheuristic algorithm with Thompson sampling to make informed decisions in dynamic environments. Furthermore, we conduct empirical experiments to assess the impact of varying reward probabilities on resource allocation and route planning within the context of this dynamic TOP, where nodes might offer a different reward behavior depending upon the environmental conditions. Our numerical results indicate that the proposed learnheuristic algorithm outperforms static approaches, achieving up to 25 % better performance in highly dynamic scenarios. Our findings highlight the effectiveness of our approach in adapting to dynamic conditions and optimizing decision-making processes in transportation systems. [ABSTRACT FROM AUTHOR]

This paper presents an overview on the state of the art in copter drones and their components. It starts by providing an introduction to unmanned aerial vehicles in general, describing their main types, and then shifts its focus mostly to multirotor drones as the most attractive for individual and research use. This paper analyzes various multirotor drone types, their construction, typical areas of implementation, and technology used underneath their construction. Finally, it looks at current challenges and future directions in drone system development, emerging technologies, and future research topics in the area. This paper concludes by highlighting some key challenges that need to be addressed before widespread adoption of drone technologies in everyday life can occur. By summarizing an up-to-date survey on the state of the art in copter drone technology, this paper will provide valuable insights into where this field is heading in terms of progress and innovation. [ABSTRACT FROM AUTHOR]

Hyperspectral data has a significant count of spectral channels with an enhanced spectral resolution, which provides detailed information at each pixel. This data can be used in numerous remote sensing (RS) applications, along with mineral mapping. Mineral mapping is an important component of geological mapping, which helps in investigating the mineralization potential of an area. This work can be completed effectively by applying machine learning (ML) techniques to RS data. This paper proposes a stacked ensemble-based framework for mineral mapping using the dataset obtained by the Airborne Visible Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG). The study area is situated in Jahazpur, Rajasthan, India. The purpose of this stacked ensemble-based model is to enhance the performance of ML-based mineral mapping. The proposed stacked ensemble model consists of two major elements: a base learner (Naïve Bayes, KNN, artificial neural network, decision tree, and support vector machine) and a stacked learner (random forest). The results of the experiments show that the stacked ensemble-based model has a lot of potential for accurately mapping the minerals talc, montmorillonite, kaolionite, and kaosmec. The proposed model has obtained an overall accuracy of 98.96%, an average accuracy of 98.21%, and a Kappa coefficient of 0.9628. Research highlights: A stacked ensemble-based model for mineral mapping is proposed. The well-known five conventional machine learning models (called base models) are investigated for mineral mapping. The performance of the proposed model is evaluated on the AVIRIG–NG dataset. The study area is situated in Jahazpur, Rajasthan, India. The proposed method outperformed all base models. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a novel sim-learnheuristic method designed to address the team orienteering problem (TOP) with a particular focus on its application in the context of unmanned aerial vehicles (UAVs). Unlike most prior research, which primarily focuses on the deterministic and stochastic versions of the TOP, our approach considers a hybrid scenario, which combines deterministic, stochastic, and dynamic characteristics. The TOP involves visiting a set of customers using a team of vehicles to maximize the total collected reward. However, this hybrid version becomes notably complex due to the presence of uncertain travel times with dynamically changing factors. Some travel times are stochastic, while others are subject to dynamic factors such as weather conditions and traffic congestion. Our novel approach combines a savings-based heuristic algorithm, Monte Carlo simulations, and a multiple regression model. This integration incorporates the stochastic and dynamic nature of travel times, considering various dynamic conditions, and generates high-quality solutions in short computational times for the presented problem. [ABSTRACT FROM AUTHOR]

Tectonic features on the Moon can reflect the state of stress during the formation of the structure, and sinuous rilles can provide further insight into the tectonic-thermal evolution of the Moon. Manual visual interpretation is the primary method for extracting these linear structures due to their complex morphology. However, extracting these features from the vast amount of lunar remote sensing data requires significant time and effort from researchers, especially for small-scale tectonic features, such as wrinkle ridges, lobate scarps, and high-relief ridges. In order to enhance the efficiency of linear structure detection, this paper conducts research on the automatic detection method of linear structures using sinuous rilles as an example case. In this paper, a multimodal semantic segmentation method, "Sinuous Rille Network (SR-Net)", for detecting sinuous rilles is proposed based on DeepLabv3+. This method combines advanced techniques such as ECA-ResNet and dynamic feature fusion. Compared to other networks, such as PSPNet, ResUNet, and DeepLabv3+, SR-Net demonstrates superior precision (95.20%) and recall (92.18%) on the multimodal sinuous rille test set. The trained SR-Net was applied in detecting lunar sinuous rilles within the range of 60°S to 60°N latitude. A new catalogue of sinuous rilles was generated based on the results of the detection process. The methodology proposed in this paper is not confined to the detection of sinuous rilles; with further improvements, it can be extended to the detection of other linear structures. [ABSTRACT FROM AUTHOR]

In this paper, we consider a shortest path network interdiction problem with incomplete information and multiple levels of interdiction intensity. The evader knows the attacker's decision on the network arcs that have been interdicted. However, the extent of damage on each arc depends on the interdiction intensity and the amount of budget spent for interdiction. We consider two cases in which the evader has incomplete information about both the intensity of attack on the interdicted arcs and the additional cost imposed for traversing those arcs. In the first case, the evader's perception of this cost falls in an interval of uncertainty. In the second case, it is assumed that the evader estimates a relative frequency for each level of interdiction intensity. This gives rise to multiple uncertainty sets for the evader's estimates of the additional cost. To handle the uncertainty that arises in both cases, a robust optimization approach is employed to derive the mathematical formulation of underlying bilevel optimization problem. For each case, we first take the well-known duality-based approach to reformulate the problem as a single-level model. We show that this method does not always end up with an integer solution or fails in achieving a solution within the time limit. Therefore, we develop an alternative algorithm based on the decomposition approach. Computational results show that the proposed algorithm outperforms the duality-based method to obtain the optimal solution. Last, a real case study is presented to show the applicability of the studied problem. [ABSTRACT FROM AUTHOR]

In this study, we utilize the agriculture waste of Portulaca quadrifida fiber-reinforced composite materials for lightweight structural and other engineering materials. A minimum amount of work was done on this Portulaca quadrifida fiber composite. Foremost is the attempt to extract Portulaca quadrifida fibers from the retting process. The extracted fibers are treated with 5%, 10%, and 15% alkali solutions. The physical, chemical, mechanical, thermal, and morphological properties of Portulaca quadrifida fiber composites are the focus of this investigation. For the 15% alkali-treated single fiber the maximum tensile strength attained is 5.45 MPa, whereas the untreated fiber is 2.70 MPa. From the chemical analysis, results showed that alkali treatment with 15% had a lower cell wall consistent with cellulose, hemicellulose, lignin, etc. On the surface of the treated fiber, the removal of contaminants, oil, particulates, and waxes caused the 5% modified fiber surfaces to be rough. Due to the acid carbonyl's absorption, the band was visible at 1625 cm−1. The non-aromatic C–H stretching in all of the treated fibers is confirmed by the absorption bands at 3700–2950 cm−1 in the case of NaOH with 5%, 10%, and 15% treated composites. Thus, the CI values for untreated, alkali treated with 5%, 10%, and 15% of Portulaca quadrifida composite were 40.02% 56.25%, 84.31%, and 90.06%, respectively. Using Portulaca quadrifida fiber composites, water uptake ability can be decreased after alkali treatment. A lightweight material application is recommended for Portulaca quadrifida fiber composites based on the results of this study. [ABSTRACT FROM AUTHOR]

The Monte‐Carlo ice microphysics model McSnow is extended by an explicit habit prediction scheme, combined with the hydrodynamic theory of Böhm. Böhm's original cylindrical shape assumption for prolates is compared against recent lab results, showing that interpolation between cylinder and prolate yields the best agreement. For constant temperature and supersaturation, the predicted mass, size, and density of the ice crystals agree well with the laboratory results, and a comparison with real clouds using the polarizability ratio shows regimes capable of improvement. An updated form of the inherent growth function to describe the primary habit growth tendencies is proposed and combined with a habit‐dependent ventilation coefficient. The modifications contrast the results from general mass size relations and significantly impact the main ice microphysical processes. Depending on the thermodynamic regime, ice habits significantly alter depositional growth and affect aggregation and riming. The influence of primary ice behavior on precipitation formation needs to be considered in future development of microphysical parameterizations, but the consideration of secondary habits and the geometry of aggregates should be further improved in future work. Plain Language Summary: The McSnow model was extended to predict the shape of ice crystals. A comparison of the falling behavior of modeled and 3D‐printed ice crystals shows a discrepancy that can be improved by interpolation. At constant temperature and supersaturation, simulated crystal properties agree well with laboratory results, and by comparison to real clouds, we have updated the function to describe growth tendencies. Ice shape is shown to have a significant influence on the main microphysical processes. Key Points: McSnow is extended by an explicit habit prediction including the revision of corresponding parameterizationsA new inherent growth ratio overcoming existing deficiencies is proposedThe impact of the modifications on the depositional growth, aggregation, and riming is shown for two distinct case studies [ABSTRACT FROM AUTHOR]

The aim of this work is to analyze the effect of water absorption on the mechanical properties and damage mechanisms of polyester/glass fiber/jute fiber hybrid composites obtained using the compression molding and vacuum-assisted resin transfer molding (VARTM) techniques with different stacking sequences. For this purpose, the mechanical behavior under tensile stress of the samples was evaluated before and after hygrothermal aging at different temperatures: TA, 50 °C, and 70 °C for a period of 696 h. The damage mechanism after the mechanical tests was evaluated using SEM analysis. The results showed a tendency for the mechanical properties of the composites to decrease with exposure to an aqueous ambient, regardless of the molding technique used to conform the composites. It was also observed that the stacking sequence had no significant influence on the dry composites. However, exposure to the aqueous ambient led to a reduction in mechanical properties, both for the molding technique and the stacking sequence. Damage such as delamination, fiber pull-out, fiber/matrix detachment, voids, and matrix removal were observed in the composites in the SEM analyses. [ABSTRACT FROM AUTHOR]

In the geological research of the Moon and other celestial bodies, the identification and analysis of impact craters are crucial for understanding the geological history of these bodies. With the rapid increase in the volume of high-resolution imagery data returned from exploration missions, traditional image retrieval methods face dual challenges of efficiency and accuracy when processing lunar complex crater image data. Deep learning techniques offer a potential solution. This paper proposes an image retrieval model for lunar complex craters that integrates visual and depth features ( LC 2 R - Net ) to overcome these difficulties. For depth feature extraction, we employ the Swin Transformer as the core architecture for feature extraction and enhance the recognition capability for key crater features by integrating the Convolutional Block Attention Module with Effective Channel Attention (CBAMwithECA). Furthermore, a triplet loss function is introduced to generate highly discriminative image embeddings, further optimizing the embedding space for similarity retrieval. In terms of visual feature extraction, we utilize Local Binary Patterns (LBP) and Hu moments to extract the texture and shape features of crater images. By performing a weighted fusion of these features and utilizing Principal Component Analysis (PCA) for dimensionality reduction, we effectively combine visual and depth features and optimize retrieval efficiency. Finally, cosine similarity is used to calculate the similarity between query images and images in the database, returning the most similar images as retrieval results. Validation experiments conducted on the lunar complex impact crater dataset constructed in this article demonstrate that LC 2 R - Net achieves a retrieval precision of 83.75%, showcasing superior efficiency. These experimental results confirm the advantages of LC 2 R - Net in handling the task of lunar complex impact crater image retrieval. [ABSTRACT FROM AUTHOR]

Cellulose is one of the most widely used and widely available materials on the planet, and it has been used for centuries in a wide range of applications. In this paper, a new source of cellulose delonix regia fruits has been explored for the extraction of cellulose at the micro and nanoscale. Cellulose is isolated from the raw delonix regia fruits by sub-sequential chemical methods such as pulping, bleaching, delignification, and acid hydrolysis. PVA/CMF and PVA/CNF composites are prepared by the solvent casting process with 1, 3, 5, 7, and 9 percentages of filler concentration. Mechanical, thermal, morphological, moisture absorption, and biodegradability properties of pure PVA, PVA/CMF, and PVA/CNF composite at different filler concentrations were evaluated using mechanical testing (tensile, flexural, and impact), TGA-DTG, SEM, moisture absorption test and soil burial test respectively. The SEM results showed that at increased filler content concentrations, signs of agglomeration began to occur, and the overall performance of the resulting composite material degraded due to which filler addition should be limited to less than 7wt%. Tensile, flexural, and impact test results revealed that nano-fillers performed better than micro-fillers, and the best performance is obtained with filler content below 7%. The degradation temperature of composites with filler content improved dramatically, according to TGA and DTG curves, and composites with nano-fillers had greater thermal stability than composites with micro- fillers. The inclusion of filler content reduced the tendency of composite materials to absorb moisture and the resulting composite materials had enough biodegradation rate together with higher lifetime and performance, according to the findings of the biodegradability test and moisture absorption test. [ABSTRACT FROM AUTHOR]

With the development of artificial intelligence, the intelligence of agriculture has become a trend. Intelligent monitoring of agricultural activities is an important part of it. However, due to difficulties in achieving a balance between quality and cost, the goal of improving the economic benefits of agricultural activities has not reached the expected level. Farm supervision requires intensive human effort and may not produce satisfactory results. In order to achieve intelligent monitoring of agricultural activities and improve economic benefits, this paper proposes a solution that combines unmanned aerial vehicles (UAVs) with deep learning models. The proposed solution aims to detect and classify objects using UAVs in the agricultural industry, thereby achieving independent agriculture without human intervention. To achieve this, a highly reliable target detection and tracking system is developed using Unmanned Aerial Vehicles. The use of deep learning methods allows the system to effectively solve the target detection and tracking problem. The model utilizes data collected from DJI Mirage 4 unmanned aerial vehicles to detect, track, and classify different types of targets. The performance evaluation of the proposed method shows promising results. By combining UAV technology and deep learning models, this paper provides a cost-effective solution for intelligent monitoring of agricultural activities. The proposed method offers the potential to improve the economic benefits of farming while reducing the need for intensive hum. [ABSTRACT FROM AUTHOR]

Although India's large iron ore reserves are well known, there are still few studies and research on iron ore prospecting in smaller deposits or the deposits with lower grade. Remote sensing concepts are useful to target for mineral exploration, since it covers a large area at low cost. In this research spectral remote sensing and digital image processing of ASTER data to locate and delineate the regions with iron oxide-bearing soils in granulite terrain at Nainnarmalai (southern India) that has hypothetical reserve 8.2 million tons of iron in sub-surface banded magnetite quartzites. The image-based study component involved pre-processing atmospheric correction and processing of the image data reminiscent of band ratio and band mixture to locate iron-bearing soils. We used blending of bands 5/3 + 1/2 to delineate ferrous iron oxide, band combination of 2/1 to delineate ferric iron oxide, and band ratio of 5/4 to delineate the lateritic soil. Further, the linear spectral unmixing outcome of ASRER data was evaluated concerning the ground truth of geochemical compositions of samples from the study area. Our results showed that image processing of the ASTER satellite data has the potential to delineate ferric, ferrous, and lateritic mineral assemblages in the iron-bearing soils with minimal requirement of ground truth verification. This research work aided in increasing trust in the use of space-based data for mineral prospecting. Image processing has demonstrated that ASTER data can be used to enhance iron ore exploration and the discovery of new mineralized areas., (© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Background: Pancreaticoduodenectomy (PD) is a complex procedure and easily accompanied by healthcare-associated infections (HAIs). This study aimed to assess the impact of PBD on postoperative infections and clinical outcomes in PD patients. Methods: The retrospective cohort study were conducted in a tertiary hospital from January 2013 to December 2022. Clinical and epidemiological data were collected from HAIs surveillance system and analyzed. Results: Among 2842 patients who underwent PD, 247 (8.7%) were diagnosed with HAIs, with surgical site infection being the most frequent type (n = 177, 71.7%). A total of 369 pathogenic strains were detected, with Klebsiella pneumoniae having the highest proportion, followed by Enterococcu and Escherichia coli. Although no significant association were observed generally between PBD and postoperative HAIs, subgroup analysis revealed that PBD was associated with postoperative HAIs in patients undergoing robotic PD (aRR = 2.174; 95% CI:1.011–4.674; P = 0.047). Prolonging the interval between PBD and PD could reduce postoperative HAIs in patients with cholangiocarcinoma (≥4 week: aRR = 0.292, 95% CI 0.100–0.853; P = 0.024) and robotic PD (≤2 week: aRR = 3.058, 95% CI 1.178–7.940; P = 0.022). PBD was also found to increase transfer of patients to ICU (aRR = 1.351; 95% CI 1.119–1.632; P = 0.002), extended length of stay (P < 0.001) and postoperative length of stay (P = 0.004). Conclusion: PBD does not exhibit a significant association with postoperative HAIs or other outcomes. However, the implementation of robotic PD, along with a suitable extension of the interval between PBD and PD, appear to confer advantages concerning patients' physiological recuperation. These observations suggest potential strategies that may contribute to enhanced patient outcomes. [ABSTRACT FROM AUTHOR]

Invisible orthodontic aligners are having a great impact on tooth movement in an aesthetic and effective way. Different techniques, models, and clinical aspects have been studied for their proper use. However, the aim of this research has been to determine the effect of the shaping process on mechanical properties and their bacterial behavior. For this study, 40 original polyurethane plates and 40 identical models, obtained by hot forming the original plates, were used. The static tensile mechanical properties were studied with a Zwick testing machine using testing speeds of 5 mm/min at a temperature of 37 °C. The original plate and the aligner have been studied with a creep test by subjecting the samples to a constant tension of 30 N, and determining the elongation using a long-distance, high-resolution microscope at different time periods between 1 and 720 h. Studies of water absorption has been realized with artificial saliva for 5 h. Bacterial cultures of Streptococcus oralis and Actinomyces viscosus strains were grown on the original plates and on new and used models, to determine the proliferation of each bacterium through metabolic activity, colony-forming units, and LIVE/DEAD assays. The mechanical results showed an increase in the strength of the inserts with respect to the models obtained from 3.44 to 3.95 MPa in the elastic limit and a lower deformation capacity. It has been proven that the transition zone in the creep curves lasts longer in the original plate, producing the rapid increase in deformation at a shorter time (400 h) in the aligner. Therefore, the shaping process reduces the time of dental correction exerted by the aligner. The results of the bacterial culture assays show an increase in the number of bacterial colonies when the aligners have been used and when the polyurethane is conformed due to the internal energy of the model, with respect to the original polyurethane. It has been observed that between the original plate and the aligner there are no statistically significant differences in water absorption and therefore the forming process does not affect water absorption. A slight increase in water absorption can be observed, but after five hours of exposure, the increase is very small. [ABSTRACT FROM AUTHOR]

Chlorophyll plays a crucial role in the process of photosynthesis and helps to regulate plants' growth and development. Timely and accurate evaluation of leaf chlorophyll content provides valuable information about the health and productivity of plants as well as the effectiveness of agricultural treatments. For non-contact and high-performance chlorophyll content mapping in plants, spectral imaging techniques are the most widely used. Due to agility and rapid random-spectral-access tuning, acousto-optical imagers seem to be very attractive for the detection of vegetation indices and chlorophyll content assessment. This laboratory study demonstrates the capabilities of an acousto-optic imager for evaluation of leaf chlorophyll content in six crops with different biophysical properties: Ribes rubrum, Betula populifolia, Hibiscus rosa-sinensis, Prunus padus, Hordeum vulgare and Triticum aestivum. The experimental protocol includes plant collecting, reference spectrophotometric measurements, hyperspectral imaging data acquisition, processing and analysis and building a multi-crop chlorophyll model. For 90 inspected samples of plant leaves, the optimal vegetation index and model were found. Obtained values of chlorophyll concentrations correlate well with reference values (determination coefficient of 0.89 and relative error of 15%). Applying a multi-crop model to each pixel, we calculated chlorophyll content maps across all plant samples. The results of this study demonstrate that acousto-optic imagery is very promising for fast chlorophyll content assessment and other laboratory spectral-index-based measurements. [ABSTRACT FROM AUTHOR]

The collision of two spheroidal drops in a shear flow is simulated in this paper using the finite difference/front tracking method. The influences of deformability, initial offset, and the size of drops on their collision dynamics are assessed. It is demonstrated that the non-dimensional relative trajectory of a pair of drops, Δz/R, is enhanced gradually as they approach and then, gains a maximum value and finally, reaches a new constant value after separation. An enhancement in the capillary number results in an increase in the deformation of the drops. The deformation and the time required for the collision of two drops are reduced as their initial offset is enhanced. It is revealed that as the ratio of major diameter to minor diameter of spheroidal drops is intensified, their deformation is enhanced. [ABSTRACT FROM AUTHOR]

The utilization of composite materials in construction has recently exerted a significant impact on society, particularly concerning ecological responsibility and environmental considerations. On a daily basis, proposals advocating the use of emerging materials crafted from discarded or repurposed items are put forth to transcend the limitations posed by conventional resources. One notable aspect of this movement revolves around textile components, encompassing fibres such as wool, cotton, cannabis, and flax. Over the past decade, there has been a heightened focus on worn clothing, as it represents an unprocessed product that holds both commercial viability and ecological benefits. Approximately 1.5 percent of the global waste generated daily comprises textile scraps, with blue jeans, crafted from cotton, standing out as the most prevalent type of apparel worldwide. Textile scraps find new life through recycling, serving various purposes such as the creation of electrical wires, the production of pulverized substances for temperature and acoustic insulation materials, and the incorporation as filler or reinforcement in concrete construction. This paper delves into multiple themes, covering (i) the adverse environmental impacts stemming from the extensive use of clothing; (ii) the recycling and reclamation of textile waste; and (iii) the utilization of waste and reclaimed materials from textiles as building components. [ABSTRACT FROM AUTHOR]

The preservation of the right gastroepiploic vessels is essential to ensure proper perfusion of the gastric conduit following esophagectomy. The loss of these vessels can lead to conduit ischemia or necrosis, resulting in significant postoperative complications. Traditional approaches such as colonic or jejunal interposition require extensive surgery and multiple anastomoses. In this report, we present our successful experience of salvaging the gastric tube through microvascular reconstruction following iatrogenic injury to the right gastroepiploic vessels in two cases. The first case involved re-anastomosis of the right gastroepiploic vein, while the second case required reconstruction of both the artery and vein during esophagectomy in a single setting. The procedures were performed by an experienced surgical team using microvascular techniques. Both patients had uneventful postoperative courses without any anastomotic leakage or major complications. Adequate perfusion of the salvaged gastric tube was confirmed intraoperatively using indocyanine green fluorescence perfusion imaging. In conclusion, immediate microvascular reconstruction offers a viable solution by restoring perfusion of the gastric tube in cases of right gastroepiploic vessel injury during esophagectomy. [ABSTRACT FROM AUTHOR]

The adoption of electric vehicles (EVs) has gained significant momentum in recent years as a sustainable alternative to traditional internal combustion engine vehicles. However, the efficient utilization of batteries in EVs, coupled with the growing demand for sustainable transportation, has posed complex challenges for battery management in the context of electric vehicle routing problems in a broad sense, which includes vehicle routing problems, team orienteering problems, and arc routing problems, all of them using EVs. This paper presents a comprehensive review of the state-of-the-art approaches, methodologies, and strategies for battery management in each of the aforementioned optimization problems. We explore the relevant factors influencing battery performance and the interplay between routing, charging, and energy management in the context of EVs. The paper also discusses the advances in optimization algorithms, vehicle-to-grid integration, and intelligent decision-making techniques aimed at enhancing the range, reliability, and sustainability of EV operations. Key findings indicate a paradigm shift towards addressing uncertainties, dynamic conditions, and synchronization challenges inherent in large-scale and dynamic routing problems within the context of EVs that require efficient battery management. [ABSTRACT FROM AUTHOR]