The aim of this study is to investigate, by means of experimental measurements and full-wave simulations, the dominant factors for the very high-resolution (VHR) radar image speckles from exponential correlated rough surfaces. A Ka-band radar system was used to collect the return signal from such a surface sample fabricated by 3D printing, and that signal was further processed into images at different resolution scales, where the image samples were obtained by horizontally turning around the surface sample. To cross-validate the results and to further discuss the VHR speckle properties, full wave simulations by full 3D Finite Difference Time Domain (FDTD) method were conducted with 1600 realizations for the speckle analysis. At the considered very high resolution, speckle statistics show divergence from the fully developed Rayleigh distribution. The factors that impact on the high-resolution speckle properties from exponential correlated rough surface, are analyzed in views of the equivalent number of scatterers theory and scattering scales, respectively. From the data results and extended discussions, it is evident that both of the above factors matter for VHR speckle of backscattering, from the exponential correlated rough surface as a good representative for the ground surface.

Land-cover classification that uses very-high-resolution (VHR) remote sensing images is a topic of considerable interest. Although many classification methods have been developed, there is still room for improvements in the accuracy and usability of classification systems. In this paper, a novel post-processing approach based on a dual-adaptive majority voting strategy (D-AMVS) is proposed for improving the performance of initial classification maps. D-AMVS defines a strategy for refining each label of a classified map that is obtained by different classification methods from the same original image and fusing the different refined classification maps to generate a final classification result. The proposed D-AMVS contains three main blocks. 1) An adaptive region is generated by extending gradually the region around a central pixel based on two predefined parameters (T1 and T2) in order to utilize the spatial feature of ground targets in a VHR image. 2) For each classified map, the label of the central pixel is refined according to the majority voting rule within the adaptive region. This is defined as adaptive majority voting (AMV). Each initial classified map is refined in this manner pixel by pixel. 3) Finally, the refined classified maps are used to generate a final classification map, and the label of the central pixel in the final classification map is determined by applying AMV again. Each entire classified map is scanned and refined pixel by pixel based on the proposed D-AMVS. The accuracies of the proposed D-AMVS approach are investigated through two remote sensing images with high spatial resolutions of 1.0 and 1.3 m, respectively. Compared with the classical majority voting method and a relatively new post-processing method called general post-classification framework, the proposed D-AMVS can achieve a land-cover classification map with less noise and higher classification accuracies.

Aerial image classification has become popular and has attracted extensive research efforts in recent decades. The main challenge lies in its very high spatial resolution but relatively insufficient spectral information. To this end, spatial-spectral feature extraction is a popular strategy for classification. However, parameter determination for that feature extraction is usually time-consuming and depends excessively on experience. In this paper, an automatic spatial feature extraction approach based on image raster and segmental vector data cross-analysis is proposed for the classification of very high spatial resolution (VHSR) aerial imagery. First, multi-resolution segmentation is used to generate strongly homogeneous image objects and extract corresponding vectors. Then, to automatically explore the region of a ground target, two rules, which are derived from Tobler’s First Law of Geography (TFL) and a topological relationship of vector data, are integrated to constrain the extension of a region around a central object. Third, the shape and size of the extended region are described. A final classification map is achieved through a supervised classifier using shape, size, and spectral features. Experiments on three real aerial images of VHSR (0.1 to 0.32 m) are done to evaluate effectiveness and robustness of the proposed approach. Comparisons to state-of-the-art methods demonstrate the superiority of the proposed method in VHSR image classification.

The vulnerability of alpine environments to climate change presses an urgent need to accurately model and understand these ecosystems. Popularity in use of digital elevation models (DEMs) to derive proxy environmental variables has increased over the past decade, particularly as DEMs are relatively cheaply acquired at very high resolutions (VHR; <1m spatial resolution). Here, we implement a multiscale framework and compare DEM-derived variables produced by Light Detection and Ranging (LiDAR) and stereo-photogrammetry (PHOTO) methods, with the aims of assessing their relevance and utility in species distribution modelling (SDM). Using a case study on the arctic-alpine plant Arabis alpina in two valleys in the western Swiss Alps, we show that both LiDAR and PHOTO technologies can be relevant for producing DEM-derived variables for use in SDMs. We demonstrate that PHOTO DEMs rivalled the accuracy of LiDAR, putting the current paradigm of LiDAR being the more accurate of the two methods into question. We obtained DEMs at spatial resolutions of 6.25cm-8m for PHOTO and 50cm-32m for LiDAR, where we determined that the optimal spatial resolutions of DEM-derived variables in SDM were between 1 and 32m, depending on the variable and site characteristics. We found that the reduced extent of PHOTO DEMs altered the calculations of all derived variables, which had particular consequences on their relevance at the site with heterogenous terrain. However, for the homogenous site, we found that SDMs based on PHOTO-derived variables generally had higher predictive powers than those derived from LiDAR at matching resolutions. From our results, we recommend carefully considering the required DEM extent to produce relevant derived variables. We also advocate implementing a multiscale framework to appropriately assess the ecological relevance of derived variables, where we caution against the use of VHR-DEMs finer than 50cm in such studies.

The effect of low cycle fatigue (LCF) pre-damage on the subsequent very high cycle fatigue (VHCF) behavior is investigated in TC21 titanium alloy. LCF pre-damage is applied under 1.8% strain amplitude up to various fractions of the expected life and subsequent VHCF properties are determined using ultrasonic fatigue tests. Results show that 5% of LCF pre-damage insignificantly affects the VHCF limit due to the absent of pre-crack, but decreases the subsequent fatigue crack initiation life estimated by Pairs’ law. Pre-cracks introduced by 10% and 20% of LCF pre-damage significantly reduce the subsequent VHCF limits. The crack initiation site shifts from subsurface-induced fracture for undamaged and 5% of LCF pre-damage specimens to surface pre-crack for 10% and 20% of LCF pre-damage specimens in very high cycle region. The fracture mechanism analysis indicate that LCF pre-crack will re-start to propagate under subsequently low stress amplitude when stress intensity factor of pre-crack is larger than its threshold. Furthermore, the predicted fatigue limits based on EI Haddad model for the LCF pre-damage specimens well agree with the experimental results.

Despite significant advances in metallurgy and the potential to create high and very high-strength steel, all international specifications for steel design provided little information about the limits of slenderness for high-strength steel sections (HSSs) and didn’t give anything about the design of very high-strength steel sections (VHSSs). The American structural steel design specification covers circular hollow sections (CHS) of steel grades up to S690, while it isn't in ANSI/AISC 360-16 and ASTM A514/A514M. Euro code EN 1993-1-1 can be applicable only to steel grades up to S460. EN 1993-1-3 and EN 1993-1-12 contain supplementary rules for cold-formed members and HSS (S460- S700), respectively. Though ductility requirements for (HSS) are specifically established in EN 1993-1-12, it is largely a continuation of the normal-strength-steel design procedures standardized in EN 1993-1-1, where (HSSs) are largely treated as normal-strength steels in these rules, and the same design approaches are used. The behavior of high and very high-strength steel circular hollow sections under axial compression load is studied in this research. A total of 16 nonlinear finite-element (FE) models were generated to replicate stub column tests that were experimentally tested by others in previous research. Hence, a parametric study is conducted using forty FE models developed to investigate the local buckling behavior under various slenderness ratios comprehensively. The developed models cover slenderness ratios ranging from 20 to 1226 and steel grades S460 and S1100 with yield stress equal 460 MPa and 1152 MPa, respectively. The FE results were combined with 105 previously collected experimental results to assess the applicability of existing codified design methodologies in the Euro code and the North American codes of cold-formed CHS. Based on the results of this study, new cross-sectional slenderness limits and new design equations for more efficient simple designs were presented for high and very-high strength steel circular hollow sections and Compared with the results of experimental tests and FE models.

Background: Little is known about risk and prognostic factors in very old patients developing sepsis secondary to community-acquired pneumonia (CAP). Methods: We conducted a retrospective observational study of data prospectively collected at the Hospital Clinic of Barcelona over a 13-year period. Consecutive patients hospitalized with CAP were included if they were very old (≥80 years) and divided into those with and without sepsis for comparison. Sepsis was diagnosed based on the Sepsis-3 criteria. The main clinical outcome was 30-day mortality. Results: Among the 4,219 patients hospitalized with CAP during the study period, 1,238 (29%) were very old. The prevalence of sepsis in this aged group was 71%. Male sex, chronic renal disease, and diabetes mellitus were independent risk factors for sepsis, while antibiotic therapy before admission was independently associated with a lower risk of sepsis. Thirty-day and intensive care unit (ICU) mortality did not differ between patients with and without sepsis. In CAP-sepsis group, chronic renal disease and neurological disease were independent risk factors for 30-day mortality. Conclusion: In very old patients hospitalized with CAP, in-hospital and 1-year mortality rates were increased if they developed sepsis. Antibiotic therapy before hospital admission was associated with a lower risk of sepsis.

Introduction: In general, everyone believes that the smallest preterm infants should achieve normal intrauterine growth rates, but many thinks that this is not possible with current nutrition guidelines. There is resistance to giving enough nutrition for fear of "toxicity". The difference in weight Z-score between birth and a corrected gestational age (CGA) at discharge is assess in postnatal growth in our unit. Material and methods: An observational study was done between January 2018 and December 2020 where all cases that had ≤ 29 weeks of GA at birth and survived to 36 weeks corrected GA or that were discharged home. An aggressive nutrition protocol including parenteral as well as enteral nutrition was followed. Patients and their weight trajectory was plotted on the Fenton 2013 growth curve. The patients who had had a smaller WZP difference were also plotted. Results: A total of 32 cases were found. The median change in Z-score between birth and discharge of the whole group was -0.52 (IQR 0.53). Six of 32 (19%) had a more than one WZP, all of whom had severe pathologies. The median decline in Z score for this group with poor growth was 1.24 (IQR 0.22). There were 26 cases with a < 1 WZP (81%) and a median Z score fall of 0.39 (IQR 0.55). No important complications secondary to the ingested volumes or parenteral nutrition were reported. Conclusion: The group of cases with a > 1 WZP drop had severe pathologies. All the other cases had adequate growth parallel to normal weight growth charts and a few cases had some catch-up growth. The study showed that it is possible for many preterm infants to achieve normal intrauterine growth rates if they are given enough nutrition, but bigger multicenter studies are needed to confirm these findings.

In this paper, we examine the performance of several classifiers in the process of searching for very negative opinions. More precisely, we do an empirical study that analyzes the influence of three types of linguistic features (n-grams, word embeddings, and polarity lexicons) and their combinations when they are used to feed different supervised machine learning classifiers: Support Vector Machine (SVM), Naive Bayes (NB), and Decision Tree (DT).

Introduction: Intraventricular Hemorrhage (IVH) is a devastating condition mostly in preterm infants at < 30 weeks GA with large morbidities and mortality usually in the first 72 hours after birth. Prevention seems to be the only way to completely deal with this problem. The IVH prevention in this age group has been studied and includes some strategies such as prenatal corticosteroids, cesarean delivery, careful extraction among others, but still, it has an unacceptably high incidence in this population. A protocol with the name Drive to Zero IVH Prevention Project that was presented in one of EpicLatino conferences some years ago. As with any quality improvement in practices, we adapted this project to our unit. Objective: To compare the IVH incidence in our unit after the protocol implementation with and historic cohort from the same unit and with all other units un the epilactino network. Material and method: In October 2017 we begun to implement a neuro protection protocol. For this analysis we include every patient born <30 weeks of GA, inborn or outborn but less than 2 days old, that survived at least three days and had a neuroimaging preformed. We include cases until July 2022, and we use the EpicLatino, a Latin-American database, from 2018 to 2020 excluding our own unit for comparison as well as an historical cohort from our unit from 2010-2017. The protocol consists of: Minimal manipulation, low volume ventilation, one routine fiscal exam a day, neutral head position, one blood pressure measured per shift, no keel stick measurements, continuous dim light and low noise level, minimal touch, no vasoactive therapy except in extreme cases, temperature and humidity at 80%, catheters, when possible, fluid restriction followed with diuresis, no PDA therapy or Echo if possible and routine therapy with hydrocortisone, erythropoietin, caffeine, parenteral nutrition, and trophic feeding. e performed a univariate analysis for IVH and groups and a logistic regression model with variables that had statistical significance in the univariate analysis. Results: The study group included 64 cases, the historic cohort 123 and the EpicLatino 1029. Demographic characteristics were similar with few statistically significant differences. We found four grade 1-2 and six grade 3-4 IVH in the study group (some caused by very traumatic delivery with multiples hematomas in head, body, and extremities), all significantly lower that the other two groups. The logistic regression model confirmed the independent statistically significant result in the study group. Conclusion: The hemorrhage during delivery must be prevented by the obstetric team. Afterwards, a set of interventions like very gentle handling with minimal manipulation and unnecessary strict lab managing seams to decrease the incidence of IVH.

The regulation of hepatic very-low-density lipoprotein (VLDL) secretion plays an important role in the pathogenesis of dyslipidemia and fatty liver diseases. VLDL is controlled by hepatic microsomal triglyceride transfer protein (MTTP). Mttp is regulated by carbohydrate response element binding protein (ChREBP) and small heterodimer partner (SHP). However, it is unclear whether both coordinately regulate Mttp expression and VLDL secretion. Here, adenoviral overexpression of ChREBP and SHP in rat primary hepatocytes induced and suppressed Mttp mRNA, respectively. However, Mttp induction by ChREBP was much more potent than suppression by SHP. Promoter assays of Mttp and the liver type pyruvate kinase gene revealed that SHP and ChREBP did not affect the transactivity of each other. Mttp mRNA and protein levels of Shp^/– mice were similar to those of wild-type; however, those of Chrebp^–/–Shp^–/– and Chrebp^–/– mice were much lower. Consistent with this, the VLDL particle number and VLDL secretion rates in Shp^–/–- mice were similar to wild-type, but were much lower in Chrebp^–/– and Chrebp^–/–Shp^–/–- mice. These findings suggested that ChREBP rather than SHP regulates VLDL secretion and that ChREBP and SHP do not affect the transactivities of each other.

Post-concussion syndrome, recently recognized as a complication of mild traumatic brain injury, is considered a consequence of the summative effect of multiple concussions received over lifetime. In elderlies, the main mild brain trauma mechanism is fall (low impact force). Many falls are often not reported or noticed but may generate serious medical and medico-legal consequences. Our research question was to find if a single, very mild brain trauma can induce neuro-behavioral consequences in elderlies. One database was queried (PubMed – MeSH terminology) looking for histopathological, neuro-cognitive and behavioral changes that can be generated by sub-concussional trauma in senescent rodents, in comparison with young animals. 41 published research articles were selected. 17 of them used very mild brain trauma in young and senescent animals, in the same experiment (6 rats and 11 mice). 24 articles evaluated the effect of sub-threshold brain trauma in adult animals (no control group). Five trauma models were used (blast models were excluded). Neuro-inflammatory changes were detected immediate after very mild primary impact. In young animals, observed pathology disappeared fast (after 3 to 7 days). Increased apoptosis, mild axonal injury in white matter tracts plus maladaptive astrogliosis and microglial activation was stronger in aged animals, persisted over time (8 months) and significantly altered animals’ cognition and behavior. Associated preexisting pathology (hypertension, tau protein deposits, microbleeds, reactive inflammation) was often responsible for amplification of the primary impact results. As translation of observation is the weak spot of pathology and behavior animal research, further investigation is needed before to conclude that even a single, very mild brain trauma may have medical consequences on human senescent brain.

In this study, we investigate the influence of control type and strain rate on the lifetime of specimens manufactured from 50CrMo4. This influence is described by a strain rate dependent method that uses cyclic stress strain curves to correct displacement controlled cyclic test results. The objective of this correction is to eliminate the stress related differences between displacement controlled cyclic test results and force controlled cyclic test results. The method is applied to the results of ultrasonic fatigue tests of six different combinations of heat treatment, specimen geometry (notch factor) and atmosphere. The corrected results show an improved agreement with test results obtained on conventional fatigue testing equipment with similar specimens: the standard deviation in combined data sets is significantly reduced (p=4.1%). We discuss the literature on intrinsic and extrinsic strain rate effects in carbon steels.

The identification of informal settlements in urban areas is an important step in developing and implementing pro-poor urban policies. Understanding when, where and who lives inside informal settlements is critical to efforts to improve their resilience. This study aims to analyse the capability of machine-learning (ML) methods to map informal areas in Jeddah, Saudi Arabia, using very-high-resolution (VHR) imagery and terrain data. Fourteen indicators of settlement characteristics were derived and mapped using an object-based ML approach and VHR imagery. These indicators were categorised according to three different spatial levels: environ, settlement and object. The most useful indicators for prediction were found to be density and texture measures, (with random forest (RF) relative importance measures of over 25% and 23% respectively). The success of this approach was evaluated using a small, fully independent validation dataset. Informal areas were mapped with an overall accuracy of 91%. Object-based ML as a hybrid approach performed better (8%) than object-based image analysis alone due to its ability to encompass all available geospatial levels.

The salt marshes, lying at the land-sea temperate interface, furnish a plethora of ecosystems services such as biodiversity niche support, ocean-climate change regulation, ornithology recreo-tourism or plant gathering by hand. They undergo significant worldwide losses due to their conversion into crop fields and to their spatial compression between the rising sea-level and the armoring shoreline. Their monitoring however requires to use a suite of remote sensing sensors to embrace the regional scale while capturing the plant details. This research innovatively adopts a multiscale approach using a cascading spaceborne and airborne process, from the 10-m Sentinel-2, through the 3-m Dove, to the 0.03-m unmanned airborne vehicle (UAV) imageries. The high to very high temporal resolution of the Sentinel-2 and Dove enabled to cover twenties and tens of km2 over five and four years, respectively, in the form of normalized difference vegetation index (NDVI) classes, associated with microphytobenthos, low, medium and high salt marsh vegetation, including the opportunistic Elyma genus. The NDVI was then modelled at the UAV scale (a few km2) using a three-layered NN prediction, providing the final near-infrared (NIR), and the intermediate red, green and blue reflectance imageries, calibrated/validated/tested with the Dove reflectance imageries (R2NIR=0.98, R2red=0.88, R2green=0.84, and R2blue=0.90). The 100fold increase in pixel size allowed to detect the decimeter-scale objects of the tidal flats and salt marshes, to enlarge the NDVI class ranges, and hold great promise to model other spectral bands at the UAV scale for further deeply enhancing the salt marsh mapping.

Commercial buildings are a significant consumer of energy worldwide. Logistics facilities, and specifically warehouses, are a common building type yet under-researched in the demand-side energy forecasting literature. Warehouses have an idiosyncratic profile when compared to other commercial and industrial buildings with a significant reliance on a small number of energy systems. As such, warehouse owners and operators are increasingly entering in to energy performance contracts with energy service companies (ESCOs) to minimise environmental impact, reduce costs, and improve competitiveness. ESCOs and warehouse owners and operators require accurate forecasts of their energy consumption so that precautionary and mitigation measures can be taken. This paper explores the performance of three machine learning models (Support Vector Regression (SVR), Random Forest, and Extreme Gradient Boosting (XGBoost)), three deep learning models (Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU)), and a classical time series model, Autoregressive Integrated Moving Average (ARIMA) for predicting daily energy consumption. The dataset comprises 8,040 records generated over an 11-month period from January to November 2020 from a non-refrigerated logistics facility located in Ireland. The grid search method was used to identify the best configurations for each model. The proposed XGBoost models outperform other models for both very short load forecasting (VSTLF) and short term load forecasting (STLF); the ARIMA model performed the worst.

There are many molecules used as drug carrier. TUD-1 is a newly synthesized mesoporous silica (SM) molecule possess two important features; consists of mesoporous so it is very suitable to be drug carrier in addition to that it has the ability to induce apoptosis in cancer cells. However, the effect of TUD-1 appears to act as cell death inducer, regardless of whether it is necrosis or apoptosis. Unfortunately, recent studies indicate that a proportion of cells undergo necrosis rather than apoptosis, which limits the use of TUD-1 as a secure treatment. On the other hand, lithium considered as necrosis inhibitor element. Hence, current study based on the idea of production a new Li/TUD-1 by incorporated mesoporous silica (TUD-1 type) with lithium in order to produce a new compound that has the ability to activate apoptosis by mesoporous silica (TUD-1 type) and at the same time can inhibit the activity of necrosis by lithium. Herein, lithium was incorporated in TUD-1 mesoporous silica by using sol-gel technique in one step synthesis procedure. Moreover, lithium was incorporated in TUD-1 with different loading in order to form different active sites such as isolated lithium ions, nanoparticles of Li2O, and bulky crystals of Li2O. The ability of the new compounds to induce apoptosis and prevent necrosis was evaluated on three different types of cancer cell lines which are; liver HepG-2, Breast MCF-7 and colon HCT116. The obtained results show that Li/TUD-1has the ability to control necrosis and thus reduce the side effects of treatments containing silica in the case of lithium has been added to them, especially in chronic cases. This has been demonstrated by the significant increase in the IC50 value and cell viability comparing to control groups. Consequently, the idea is new, so it definitely needs more develop and test with materials that have more apoptotic impact than silica in order to induce apoptosis without induction of necrosis.