Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep Recurrent Neural Network for Agricultural Classification using multitemporal SAR Sentinel-1 for Camargue, France

The development and improvement of methods to map agricultural land cover are currently major challenges, especially for radar images. This is due to the speckle noise nature of radar, leading to a less intensive use of radar rather than optical images. The European Space Agency Sentinel-1 constellation, which recently became operational, is a satellite system providing global coverage of Synthetic Aperture Radar (SAR) with a 6-days revisit period at a high spatial resolution of about 20 m. These data are valuable, as they provide spatial information on agricultural crops. The aim of this paper is to provide a better understanding of the capabilities of Sentinel-1 radar images for agricultural land cover mapping through the use of deep learning techniques. The analysis is carried out on multitemporal Sentinel-1 data over an area in Camargue, France. The data set was processed in order to produce an intensity radar data stack from May 2017 to September 2017. We improved this radar time series dataset by exploiting temporal filtering to reduce noise, while retaining as much as possible the fine structures present in the images. We revealed that even with classical machine learning approaches (K nearest neighbors, random forest, and support vector machines), good performance classification could be achieved with F-measure/Accuracy greater than 86% and Kappa coefficient better than 0.82. We found that the results of the two deep recurrent neural network (RNN)-based classifiers clearly outperformed the classical approaches. Finally, our analyses of the Camargue area results show that the same performance was obtained with two different RNN-based classifiers on the Rice class, which is the most dominant crop of this region, with a F-measure metric of 96%. These results thus highlight that in the near future these RNN-based techniques will play an important role in the analysis of remote sensing time series.
Carotid Artery Calcification on Orthopantomograms (CACO Study) – is it indicative of carotid stenosis?

It is unclear whether incidental carotid artery calcification (CAC) on radiographs has a defined relationship to clinically significant carotid artery stenosis, and therefore risk of stroke. The primary objective of this study was to ascertain the relationship between dental radiograph detected carotid calcification and carotid artery stenoses ≥50% on carotid duplex ultrasound. We carried out an observational study of patients undergoing routine dental orthopantomogram (OPG) examinations. Consecutive patients with CAC on OPG were prospectively matched to those without CAC based on age and gender. Ultrasound of the carotid arteries was performed to determine the presence of stenosis (≥50%) in either vessel. Of 5780 consecutive OPG examinations with suitable images for analysis, CAC was detected in 10.8%. A total of 233 patients underwent carotid ultrasound (130 with and 103 without CAC on OPG). The prevalence of a clinically significant (≥50%) carotid stenosis on ultrasound was 15.4% (20/130) in those with CAC and 5.8% (6/103) for those without CAC on OPG. Incidental CAC detected on routine OPG requires both radiological reporting and clinical follow-up since 1 in 7 patients will have a clinically significant carotid artery stenosis as compared with 1 in 20 patients who do not have CAC. Trial Registration: Australian and New Zealand Clinical Trials Registry website (U1111-1148-1066). http://www.ANZCTR. org.au/ACTRN12613001038785.aspx.
Lead Detection in Polar Oceans - A Comparison of Different Classification Methods for Cryosat-2 SAR Data

In polar regions, sea-ice hinders the precise observation of Sea Surface Heights (SSH) by satellite altimetry. In order to derive reliable heights for the openings within the ice, two steps have to be fulfilled: (1) the correct identification of water (e.g., in leads or polynias), a process known as lead classification; and (2) dedicated retracking algorithms to extract the ranges from the radar echoes. This study focuses on the first point and aims at identifying the best available lead classification method for Cryosat-2 SAR data. Four different altimeter lead classification methods are compared and assessed with respect to very high resolution airborne imagery. These methods are the maximum power classifier; multi-parameter classification method primarily based on pulse peakiness; multi-observation analysis of stack peakiness; and an unsupervised classification method. The unsupervised classification method with 25 clusters consistently performs best with an overall accuracy of 97%. Furthermore, this method does not require any knowledge of specific ice characteristics within the study area and is therefore the recommended lead detection algorithm for Cryosat-2 SAR in polar oceans.
Quantifying Drought Propagation from Soil Moisture to Vegetation Dynamics Using a Newly Developed Ecohydrological Land Reanalysis

Despite the importance of the interaction between soil moisture and vegetation dynamics to understand the complex nature of drought, few land reanalyses explicitly simulate vegetation growth and senescence. In this study, I provide a new land reanalysis which explicitly simulates the interaction between sub-surface soil moisture and vegetation dynamics by the sequential assimilation of satellite microwave brightness temperature observations into a land surface model (LSM). Assimilating satellite microwave brightness temperature observations improves the skill of a LSM to simultaneously simulate soil moisture and the seasonal cycle of leaf area index (LAI). By analyzing soil moisture and LAI simulated by this new land reanalysis, I identify the drought events which significantly damage LAI on the climatological day-of-year of the LAI’s seasonal peak and quantify drought propagation from soil moisture to LAI in the global snow-free region. On average, soil moisture in the shallow soil layers (0–0.45 m) quickly recovers from the drought condition before the climatological day-of-year of the LAI’s seasonal peak while soil moisture in the deeper soil layer (1.05–2.05 m) and LAI recover from the drought condition approximately 100 days after the climatological day-of-year of the LAI’s seasonal peak.
The Transferability of Random Forest in Canopy Height Estimation from Multi-Source Remote Sensing Data

Canopy height is an important forest structure parameter for understanding forest ecosystem and improving global carbon stock quantification accuracy. Light detection and ranging (LiDAR) can provide accurate canopy height measurements, but its application at large scales is limited. Using LiDAR-derived canopy height as ground truth to train the Random Forest (RF) algorithm and therefore predict canopy height from other remotely sensed datasets in areas without LiDAR coverage has been one of the most commonly used method in large-scale canopy height mapping. However, how variances in location, vegetation type, and spatial scale of study sites influence the RF modelling results is still a question that needs to be addressed. In this study, we selected 16 study sites (100 km2 each) with full airborne LiDAR coverage across the United States, and used the LiDAR-derived canopy height along with optical imagery, topographic data, and climate surfaces to evaluate the transferability of the RF-based canopy height prediction method. The results show a series of findings from general to complex. The RF model trained at a certain location or vegetation type cannot be transferred to other locations or vegetation types. However, by training the RF algorithm using samples from all sites with various vegetation types, a universal model can be achieved for predicting canopy height at different locations and different vegetation types with self-predicted R2 higher than 0.6 and RMSE lower than 6 m. Moreover, the influence of spatial scales on the RF prediction accuracy is noticeable when spatial extent of the study site is less than 50 km2 or the spatial resolution of the training pixel is finer than 500 m. The canopy height prediction accuracy increases with the spatial extent and the targeted spatial resolution.
Periodontitis causes abnormalities in the liver of rats

BACKGROUND Periodontitis not only causes injury to the periodontium, but also damages other tissues such as: articulate, renal, cardiac, and hepatic. The objective of this study was to investigate periodontitis induced alterations in liver function and structure using an experimental model. METHODS Twenty female rats (Rattus norvegicus) were allocated into two groups: control and periodontitis. Gingival bleeding index and oxidative stress parameters and specific circulating biomarkers were measured. Immunohistochemistry was carried out using alkaline phosphatase (AlkP) staining of the liver. Hepatic tissues, cytokines, and lipid contents were measured. Histopathologic evaluation of the liver was carried out using light and electron microscopy. RESULTS Liver histopathologic and immunohistochemistry assessment showed increase in steatosis score, and presence of binucleate hepatocytes and positive cells for AlkP in periodontitis versus control group. Ultrastructural evaluation showed significant increase in size and number of lipid droplets (LD), distance between the cisterns of rough endoplasmic reticulum (RER), mitochondria size, foamy cytoplasm, and glycogen accumulation in the liver of the periodontitis group compared with the control group. In addition, plasma levels of AlkP, high-density lipoprotein (HDL), triglycerides, and total cholesterol were also changed. CONCLUSION Experimental periodontitis caused immunohistochemistry, histopathologic, ultrastructural, oxidative, and biochemical changes in the liver of rats.
PA-SSD: A Page-Type Aware TLC SSD for Improved Write/Read Performance and Storage Efficiency

TLC flash has three types of pages to accommodate the three bits in each TLC physical cell exhibiting very different program latencies, LSB (fast), CSB (medium), and MSB (slow). Conventional TLC SSD designs on page allocation to write requests do not take page types and their latency difference into consideration, missing on an important opportunity to exploit the potentials of fast writes. This paper proposes PA-SSD, a page-type aware TLC SSD design, to effectively improve the overall performance by judiciously and coordinately utilizing the three types of pages on TLC flash when serving user write requests. The main idea behind PA-SSD is to coordinately allocate the same type of pages for sub-requests of any given user write request, to mitigate the potential program latency imbalance among the sub-requests. We achieve the PA-SSD design goal by addressing two key research problems: (1) how to properly determine page-type for each user write request and (2) how to allocate a physical page for each sub-request with an assigned page type from (1). For the first problem, seven page-type specifying schemes are proposed to investigate their effects under different workloads. On the other hand, we approach the second problem by redesigning the page allocation strategy in TLC SSD to uniformly and sequentially determine pages for allocation following the programming process of TLC flash. Under a wide range of workloads, our experiments show that PA-SSD can accelerate both the write and read performance without any sacrifice to storage capacity. Particularly, our proposed queue-depth based page-type specifying scheme improves write performance by 2.4 times and read performance by 1.5 times over the conventional TLC SSD.
Variability of serum concentrations of cystatin C and urinary retinol‐binding protein, neutrophil gelatinase‐associated lipocalin, immunoglobulin G, and C‐reactive protein in dogs

Background Markers of kidney dysfunction and damage have potential to detect chronic kidney disease (CKD) in early stages. However, data on long‐term variation of these markers in healthy dogs is lacking and is crucial for the interpretation of results. Hypothesis/Objectives To determine temporal variations of serum cystatin C (sCysC) and urinary retinol‐binding protein (uRBP), neutrophil gelatinase‐associated lipocalin (uNGAL), immunoglobulin G (uIgG), and C‐reactive protein (uCRP) in healthy dogs. Animals Eight clinically healthy adult Beagles were evaluated. Methods Longitudinal observational study. Serum cystatin C was determined by particle‐enhanced nephelometric immunoassay. Urinary retinol‐binding protein, uNGAL, uIgG and uCRP were determined by ELISA and concentrations were indexed to urinary creatinine. Within‐ and between‐dog variance components (VC) and within‐dog coefficients of variation (CV) were determined from blood and urine collected at eight time points over 1.5 years. Results Urinary C‐reactive protein (uCRP) concentrations were consistently below the detection limit (5.28 ng/mL). Mean ± within‐dog standard deviation for sCysC, uRBP/c, uNGAL/c and uIgG/c was 0.15 ± 0.01 mg/L, 0.09 ± 0.03 mg/g, 2.32 ± 2.03 μg/g and 12.47 ± 10.98 mg/g, respectively. Within‐dog CV for sCysC, uRBP/c, uNGAL/c and uIgG/c was 8.1%, 33.7%, 87.2% and 88.1%, respectively. Conclusions and clinical importance Serum cystatin C, uRBP/c, uNGAL/c and uIgG/c exhibit a wide range of long‐term within‐dog variability. Researchers and veterinarians might need to take this into account when interpreting their results. To assess their diagnostic and predictive ability, future studies need to establish reference ranges for healthy dogs and dogs with CKD.
Trends of admission and predictors of neonatal mortality: A hospital based retrospective cohort study in Somali region of Ethiopia

Background In Ethiopia, the trend of neonatal mortality showed slow pace of reduction from 2000–2016 compared to the reduction in infant and under-five mortality over the same period. This study aimed at unpacking the trends of admission, specific causes and rate of neonatal mortality as well as predictors of neonatal mortality at a general hospital in Somali region of Ethiopia. Methods A hospital based retrospective cohort study was conducted from 25th of May 2017to 10th of June, 2017. All the new-borns admitted in the neonatal Intensive Care Unit of the hospital were reviewed over three years period (Aug2014-May2017). Data were cleaned and exported to SPSS version 20 and both descriptive and analytical analysis were executed. The level of significance was set at P<0.05. Binary logistic regression was used to produce summary of statistics including crude and adjusted odds ratio and 95% confidence intervals. Results This study reviewed a total of 792 new-borns below the age of 28 days admitted in the NICU of Karamara hospital over a period of three years (August, 2014 to May, 2017). The mean birth weight was 2733 ± 740 g and neonates with normal birth weight stood at 64%. Seven hundred forty seven new-borns (94.3%) were discharged alive while 45 (5.7%) new-borns died in the course of hospitalization making a Neonatal Mortality Rate (NMR) of 5.7% (57 per 1000 live births), and 96 percent of these deaths were early neonatal deaths that occurred in the first one week of life (i.e. <7 days). After all variables which had an association with neonatal mortality (P <0.05) were entered in to a multivariate logistic model to control the effect of confounders: prematurity (AOR = 0.492(0.253, 0.957), P = 0.037) and average length of stay below two days (AOR = 0.418(0.186, 0.936), P = 0.034) were independently associated with neonatal mortality showing protective effect. Conclusion The causes of neonatal death reported in this study are preventable, the neonatal mortality rate is high compared to the national and regional figures. Prematurity and shorter length of stay in the NICU of less than two days showed independent association with neonatal mortality. This calls for more work along the continuum of care, improving the quality of care, early transfer of sick neonates to the NICU along with scaling up establishment of the NICUs in other hospitals of the region.
Autophagy in osteoporosis: Relation to oxidative stress

Impaired autophagy and oxidative stress are implicated in the development of many diseases. This study aimed to investigate the involvement of autophagy represented by autophagy‐related gene 7 (Atg7) and oxidative stress represented by superoxide dismutase 2 (SOD2) gene expression and enzyme activity in the pathogenesis of osteoporosis. Atg7 and SOD2 gene relative expression were evaluated by SYBR green quantitative real‐time‐polymerase chain reaction in the osteoporotic group (n = 26) versus the osteoporosis free group (n = 14). SOD2 enzyme activity was evaluated by colorimetric method in both study groups. Both Atg7 and SOD2 relative expression showed highly significant decrease (P < 0.01) between both groups. However, SOD2 enzyme activity showed no significant difference between the two groups. There was a significant direct correlation between Atg7 and SOD2 gene expression in both study groups. Atg7 relative expression showed significant ( P < 0.01) direct correlation with vitamin D serum levels and body mass index in osteoporotic group. In conclusion, both genes are involved in the pathogenesis of osteoporosis and this could be amenable to future therapeutic intervention.
The feasibility and promise of mobile technology with community health worker reinforcement to reduce rural preterm birth

OBJECTIVES (1) Assess feasibility of a smartphone platform intervention combined with Community Health Worker (CHW) reinforcement in rural pregnant women; (2) Obtain data on the promise of the intervention on birth outcomes, patient activation, and medical care adherence; and (3) Explore financial implications of the intervention using return on investment (ROI). SAMPLE A total of 98 rural pregnant women were enrolled and assigned to intervention or control groups in this two-group experimental design. INTERVENTION The intervention group received usual prenatal care plus a smartphone preloaded with a tailored prenatal platform with automated texting, chat function, and hyperlinks and weekly contact from the CHW. The control group received usual prenatal care and printed educational materials. MEASUREMENTS Demographics, health risk data, interaction with platform, medical records, hospital billing charges, Client Satisfaction Questionnaire-8, satisfaction comments, and the Patient Activation Measure. RESULTS A total of 77 women completed the study. The intervention was well-received, showed promise for improving birth outcomes, patient activation, and medical care adherence. Financial analysis showed a positive ROI under two scenarios. CONCLUSIONS Despite several practical issues, the study appears feasible. The intervention shows promise for extending prenatal care and improving birth outcomes in rural communities. Further research is needed with a larger and more at-risk population to appreciate the impact of the intervention.
Astaxanthin Prevents Alcoholic Fatty Liver Disease by Modulating Mouse Gut Microbiota

The development and progression of alcoholic fatty liver disease (AFLD) is influenced by the intestinal microbiota. Astaxanthin, a type of oxygenated carotenoid with strong antioxidant and anti-inflammatory properties, has been proven to relieve liver injury. However, the relationship between the gut microbiota regulation effect of astaxanthin and AFLD improvement remains unclear. The effects of astaxanthin on the AFLD phenotype, overall structure, and composition of gut microbiota were assessed in ethanol-fed C57BL/6J mice. The results showed that astaxanthin treatment significantly relieves inflammation and decreases excessive lipid accumulation and serum markers of liver injury. Furthermore, astaxanthin was shown to significantly decrease species from the phyla Bacteroidetes and Proteobacteria and the genera Butyricimonas, Bilophila, and Parabacteroides, as well as increase species from Verrucomicrobia and Akkermansia compared with the Et (ethanol)group. Thirteen phylotypes related to inflammation as well as correlated with metabolic parameters were significantly altered by ethanol, and then notably reversed by astaxanthin. Additionally, astaxanthin altered 18 and 128 KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways involved in lipid metabolism and xenobiotic biodegradation and metabolism at levels 2 and 3, respectively. These findings suggest that Aakkermansia may be a potential target for the astaxanthin-induced alleviation of AFLD and may be a potential treatment for bacterial disorders induced by AFLD.
Lidar Studies of Wind Turbulence in the Stable Atmospheric Boundary Layer

The kinetic energy of turbulence, the dissipation rate of turbulent energy, and the integral scale of turbulence in the stable atmospheric boundary layer at the location heights of low-level jets (LLJs) have been measured with a coherent Doppler light detection and ranging (lidar) system. The turbulence is shown to be weak in the central part of LLJs. The kinetic energy of turbulence at the maximum velocity heights of the jet does not exceed 0.1 (m/s)2, while the dissipation rate is about 10−5 m2/s3. On average, the integral scale of turbulence in the central part of the jet is about 100 m, which is two to three times less than the effective vertical size of the LLJ.
Meaning Through Attachment: An Integrative Framework

We propose an integrative framework, advancing attachment as a vital factor in the development and maintenance of meaning throughout life. First, early attachment experiences provide a foundation for recognizing patterns and acquiring a sense of order and coherence. Furthermore, interactions with sensitive attachment figures stimulate mentalization capacities and exploration of the inner and outer environment, enabling the formation of complex representations of self, others, and the world, ultimately also molding how individuals appraise meaning in their lives. Second, attachment security can serve as an enduring and powerful resource for handling threats to meaning. When confronted with disruptions to meaning, secure attachment provides a coherent set of representations to fall back on and maintain or regain a firm sense of order and meaning under challenging circumstances. Moreover, by promoting cognitive openness and tolerance of ambiguity, secure attachment facilitates flexible and realistic adjustment of meaning representations when encountering discrepant information.
The Evolving Story of Pterygium

Abstract: Pterygium is a fibrovascular subepithelial growth of degenerative tissue over the limbus. It is a common condition worldwide that is especially prevalent in tropical countries within the “pterygium belt. ” Its exact etiology remains to be elucidated; however, it is strongly associated with exposure to ultraviolet light. The high expression levels of tumor protein p53 (TP53) observed in laboratory studies of pterygium seem to contradict the fast-growing nature of its clinical behavior, and TP53 mutations have been suggested. We demonstrated that mouse double minute 2 (MDM2), a TP53-binding protein, contributes to the inhibition of TP53 activity in human pterygium. Thus, disruption of the MDM2-TP53 interaction should attenuate human pterygium cell growth. For primary pterygium, treatment is relatively straightforward and involves surgical excision. To minimize the risk of recurrence, many adjunctive therapies are adopted, including antimetabolites, such as mitomycin C and 5-fluorouracil, amniotic membrane, different variations on conjunctival and/or limbal conjunctival grafts, and other medications such as anti-vascular endothelial growth factor. In the future, MDM2 antagonists may help further lower the recurrence rates after the treatment of pterygium.