Miracle-dz/UniFAR-FTUs huggingface dataset:
Online identification of switched linear output error models

In this paper, we describe a modified recursive least squares (RLS) algorithm for the online identification of switched linear systems (SLSs). For this problem, a real time mode detection (MD) method is usually employed to detect the running mode for each output data and this part is very important for the estimation results. In fact, it is rather difficult to design a perfect MD method that can identify the running modes without errors, especially in stochastic systems. As a result, there often exist some mode mismatches in the MD procedure. For this reason, we cope with this problem from the compensation point of view. By introducing a resetting strategy to the RLS algorithm, the negative effects of mode mismatches will be separated into a few resetting intervals, which can effectively avoid them to be accumulated and thereby result in good estimation. The performance of the proposed algorithm is evaluated by Monte Carlo simulations in comparison with another alternative method.
Vascular endothelial growth factors in retinal and choroidal neovascular diseases

Abstract Angiogenesis, or neovascularization, refers to development of new vessels from pre-existing vasculature. Retinal and choroidal neovascularization leads to oedema, haemorrhages, and fibrosis, causing visual impairment and blindness. In multiple studies, vascular endothelial growth factor (VEGF) has been shown to be the most important factor in ocular angiogenesis. Recently discovered anti-VEGF treatments have revolutionized the therapy of neovascular diseases in the eye. These agents have been shown not just to stop the angiogenic process and maintain visual acuity but also improve vision in a great proportion of patients at least during a 2-year follow-up. However, there are also problems with these agents and their delivery regimens, and new therapeutic strategies are needed. This review summarizes the most important growth factors participating in the angiogenic process in the retina and the choroid, diseases where angiogenesis plays the most devastating part causing visual impairment, as well as current antiangiogenic treatments for these diseases.
No!: Not Another Deep Learning Framework

In recent years, deep learning has pervaded many areas of computing due to the confluence of an explosive growth of large-scale computing capabilities, availability of datasets, and advances in learning techniques. While this rapid growth has resulted in diverse deep learning frameworks, it has also led to inefficiencies for both the users and developers of these frameworks. Specifically, adopting useful techniques across frameworks -- both to perform learning tasks and to optimize performance -- involves significant repetitions and reinventions. In this paper, we observe that despite their diverse origins, many of these frameworks share architectural similarities. We argue that by introducing a common representation of learning tasks and a hardware abstraction model to capture compute heterogeneity, we might be able to relieve machine learning researchers from dealing with low-level systems issues and systems researchers from being tied to any specific framework. We expect this decoupling to accelerate progress in both domains.
Diabetes mellitus prevalence is increasing in South Asians but is stable in Chinese living in Singapore and Mauritius

Asia is experiencing a type 2 diabetes epidemic, but prevalence differs by ethnicity and level of socioeconomic development. Singapore and Mauritius have implemented comprehensive campaigns to address this public health problem. We compared diabetes and obesity prevalence trends among Chinese and South Asians living in Singapore and Mauritius to determine the contribution of ethnicity and economic development to diabetes.
Extracting tree crown properties from ground-based scanning laser data

The spatial organization of above-ground plant material plays an important role in controlling not only plant functional activities like photosynthesis and evapotranspiration, but also the photo-vegetation interactions. To improve our understanding of such interactions, the acquisition of highly detailed information about the 3D architecture of individual plants and communities of plants is required. Recently, Light detection and ranging (LiDAR) sensors, both at the ground and the airborne-level, have emerged as useful tools for mapping 3D plant structure. One such ground-based instrument is the Intelligent Laser Ranging and Imaging System (ILRIS 3D), which was developed at Optech Incorporated. This laser scanner, generates a 3D digital reconstruction of any scene, by actively emitting laser pulses and recording the time elapsed for the return of a pulse, thereby measuring the distance of any given object. It is the objective of this research to utilize the ILRIS 3D to measure structural, and biophysical information of individual trees for use as direct inputs into complex radiative transfer models. The key parameters under investigation are crown dimensions (i.e. shape, area, and volume), crown-level gap fraction (GF) and crown- level leaf area index (LAI). The ILRIS 3D was used to acquire 3D point clouds of an artificial 6' Ficus tree, in a controlled laboratory environment. Measured XYZ point cloud data was segmented to retrieve laser pulse return density profiles, which subsequently were used to estimate gap fraction and LAI . Gap fraction estimates were cross-validated with traditional methods of histogram thresholding of digital photographs (r2 = 0.96). Crown LAI estimates were compared with the actual values (r2 = 0.95, RMSE = 0.45). The next challenge was to implement the developed algorithms to real crowns, namely olive (Olea europaea L.) orchards in southern Spain. Individual tree-level ILRIS 3D data was collected from 24 structurally diverse crowns. Crown dimensional profiles were extracted for ILRIS data that was collected from a horizontal view (i.e ground-based) and a nadir view (i.e from platform 12 meters above ground). Preliminary retrievals from the olive orchards dataset is described here, while current ongoing field measurements are being conducted to validate the findings. Successful demonstration of extracting crown-level structural parameters like gap fraction and LAI from ground-based LiDAR will be important new information that can be used for detailed radiative transfer modeling in olive orchards and likely lead to more robust inversion algorithms.
Inshore ship detection in remote sensing images based on deep features

Inshore ship detection in remote sensing images is a challenging task because of the connectivity and similarity between ships and backgrounds. The usual shape feature is not always applicable because sometimes it is hard to be extracted. In this paper, deep features extracted from a convolutional neural network (CNN) are used for inshore ship detection. In order to feed the CNN with exclusively positive and negative samples, a novel parallelogram image cropping (PIC) method is proposed. The traditional cropping method can only generate rectangle image samples along a horizontal or vertical orientation, thus ships and docks often coexist in these samples. The proposed PIC method can generate parallelogram samples that only contain single ship or dock. For a 2-class classification task, the number of neurons in fully-connected layers of the widely used CNN models is too large. Reducing the number from 4096 to 512 can improve training and detection speeds while maintaining accuracies. Experimental results on Google Earth images demonstrate that the proposed method can accurately and robustly detect inshore ships in remote sensing images.
Isolation and characterization of four polycyclic aromatic hydrocarbon degrading bacteria from soil near an oil refinery

Four bacterial strains (I‐IV) capable of optimum growth on 0·1% naphthalene, anthracene or a mixture of naphthalene and phenanthrene were isolated from soil near an oil refinery. Two isolates (I and II) were identified as belonging to the genus Micrococcus, while strains III and IV were identified as Pseudomonas and Atcaligenes respectively. All the isolates were found to bear high molecular weight plasmid DNA (isolate I and IV 89%, II 67·5% and III 92·1% of Λ DNA), which is presumed to aid in the metabolism of polycyclic aromatic hydrocarbons. The strains also showed appreciable growth at high concentrations of NaCl (up to 7·5%).
Characterization of a Siberian Virus Isolated from a Patient with Progressive Chronic Tick-Borne Encephalitis

ABSTRACT A strain of Tick-borne encephalitis virus designated Zausaev (Za) was isolated in Siberia from a patient who died of a progressive (2-year) form of tick-borne encephalitis 10 years after being bitten by a tick. The complete genomic sequence of this virus was determined, and an attempt was made to correlate the sequence with the biological characteristics of the virus. Phylogenetic analysis demonstrated that this virus belongs to the Siberian subtype of Tick-borne encephalitis virus. Comparison of Za virus with two related viruses, a Far Eastern isolate, Sofjin, and a Siberian isolate, Vasilchenko, revealed differences among the three viruses in pathogenicity for Syrian hamsters, cytopathogenicity for PS cells, plaque morphology, and the electrophoretic profiles of virus-specific nonstructural proteins. Comparative amino acid alignments revealed 10 individual amino acid substitutions in the Za virus polyprotein sequence that were different from those of other tick-borne flaviviruses. Notably, the dimeric form of the Za virus NS1 protein migrated in polyacrylamide gels as a heterogeneous group of molecules with a significantly higher electrophoretic mobility than those of the Sofjin and Vasilchenko viruses. Two amino acid substitutions, T277→V and E279→G, within the NS1 dimerization domain are probably responsible for the altered oligomerization of Za virus NS1. These studies suggest that the patient from whom Za virus was isolated died due to increased pathogenicity of the latent virus following spontaneous mutagenesis.
PIK3R3 Induces Epithelial-to-Mesenchymal Transition and Promotes Metastasis in Colorectal Cancer

Class IA PI3K plays an essential role in the invasion and metastasis of cancer. However, the mechanisms and specific functions of PI3K isoforms in tumor invasion and metastasis are not fully understood. We evaluated the role of PIK3R3, a PI3K regulatory subunit encoded by the PIK3R3 gene, in colorectal cancer invasion and metastasis. Clinical specimens and cell lines data show that the expression level of PIK3R3 is associated with colorectal cancer metastasis. Overexpression of PIK3R3 increases tumor migration and invasion in vitro and promotes metastasis of colorectal cancers in vivo. Furthermore, we investigated that the overexpression of PIK3R3 depends on SNAI2, inducing significant epithelial-to-mesenchymal transition (EMT). Downregulation of PIK3R3 reverses this process, which possibly contributes to the enhanced invasive and metastasizing abilities of colorectal cancer cells. In this study, we found that PIK3R3 plays an important role in colorectal cancer metastasis and might be a potential and specific target for therapies against metastatic colorectal cancer. Mol Cancer Ther; 13(7); 1837–47. ©2014 AACR.
Variations in structure and content of online social networks for patients with diabetes.

W ith the exponential growth of Facebook and other social networking sites, patients are increasingly seeking information and emotional support online, from other patients. Recent qualitative studies highlight the great potential that online social networks represent as a source of information and encouragement in chronic disease management. However, recent research has also identified potential pitfalls in these unregulated sites. More than 25% of posts on Facebook sites for diabetic individuals were promotional in nature, largely directing patients to learn about products not approved by the Food and Drug Administration, and substantial efforts to gather data from Web site participants were noted. These findings underscore the need to guarantee the authenticity of participants and to ensure that online social networks are safe locations for patients to share information. We know little about how commonly used sites validate the authenticity of participants’ claimed identities or how they provide oversight over the content posted by participants. In addition, little is known about the structure of communication, the sources of funding, and the presence or use of advertising on these sites. Accordingly, we conducted a survey of online social networking sites to explore characteristics of these communities and to better inform physicians and patients about the choices available to them.
Template matching algorithm for exudates detection from retinal fundus images

Diabetic retinopathy is one of the most common causes of blindness in the working-age population. Screening for diabetic retinopathy represents a good clinical practice and cost-effective healthcare. Early detection and treatment of retinopathy has been shown to be effective in preventing visual impairment. This paper provides an automated system for the identification of exudates for early diagnosis of diabetic retinopathy. The grey scale version of colour retinal fundus image was first produced. It was then enhanced using pre-processing techniques. The template matching TM algorithm was proposed to segment the exudates regions from diabetic retinopathy retinal images. This was experimented with a dataset, DIARETDB0 which consists of 130 colour retinal fundus images. The sensitivity and specificity achieved were 99.45% and 95.68%, respectively. It had shown 98.72% accuracy.
APACHE II score in abdominal sepsis.

To the Editor . —I read with interest the recent article by Bohnen et al 1 that represents the first published prospective effort to validate the pretreatment APACHE II score in abdominal sepsis. During the past 18 months we have been conducting a prospective study examining the value of intraoperative peritoneal lavage with saline solution and antibiotics in the treatment of abdominal infections. The APACHE II score is prospectively measured in all patients in an attempt to facilitate their stratification. All patients admitted to the study are treated by one surgeon in one surgical unit. All variables of the APACHE II score are measured before operation and entered on a study data sheet. The score is calculated by one observer (M.S.). Only patients undergoing formal laparotomy are considered; appendiceal infections are included only if the patient requires a midline laparotomy. Patients with diffuse peritonitis from colonic sources or from operative complications
Diagnosis of neurally mediated syncope at initial evaluation and with tilt table testing compared with that revealed by prolonged ECG monitoring. An analysis from the Third International Study on Syncope of Uncertain Etiology (ISSUE-3)

Objective According to the guidelines of the European Society of Cardiology, a presumed diagnosis of neurally mediated syncope (NMS) can be made when patients have a consistent history and competing diagnoses are excluded. In the present study, we compared the initial diagnosis of NMS by means of implantable loop recorder (ILR) documentation. Methods In this prospective multicentre observational study which involved 51 hospitals in nine countries in Europe and Canada, 504 NMS patients ≥40 years, who had suffered ≥3 syncopal episodes in the previous 2 years received an ILR and were followed up for a mean of 15±11 months. Results ILR recorded a spontaneous syncope in 187 cases, with an estimated diagnostic yield of 47% at 3 years. ILR findings were consistent with the initial diagnosis of presumed NMS in 162 (87%) patients whereas did not confirm NMS in another 25 (13%), who had an intrinsic cardiac arrhythmic cause (atrial tachyarrhythmias (#6), long pause on termination of tachyarrhythmia (#8), persistent bradycardia (#3), ventricular tachycardia (#4)) or a non-arrhythmic loss of consciousness (non-syncopal (#3), orthostatic hypotension (#1)). No clinical baseline feature was able to predict an intrinsic cardiac cause with the exception of more frequent non-syncopal atrial tachyarrhythmias on clinical history, which were present in 38% of cardiac versus 5% of NMS patients (p=0.001). Tilt table testing (TT) was positive in 76/136 (56%) presumed NMS and in 9/21 (43%) non-NMS patients (p=0.35); an asystolic response was present in 28/136 (21%) NMS and in 0/21 (0%) non-NMS patients (p=0.03). Conclusions ILR findings showed results other than NMS in a small, although non-negligible, number of patients older than 40 years. TT was unable to discriminate between presumed NMS and non-NMS with the exception of an asystolic response which was highly specific.
Novel dual-band and arbitrary output-phase crossover based on two-section couplers

A novel crossover prototype with arbitrary output phases at dual frequencies of interest is proposed for the first time. This crossover architecture was composed of a cascade of two identical couplers and the second coupler was connected upside down in order to perform crossover operation. At either frequency of the dual-band scheme, the output phase of the presented crossover is decided by the coupler's output phase difference that can be arbitrarily designed. To support our idea, two crossovers having the output phase realizations of 60°/60° at 2.4/5.2 GHz and 80o/100o at 2.4/5.8 GHz, respectively, were developed, fabricated, and characterized experimentally. Good agreement was obtained between measured and simulated results. The proposed format can be applied to planar crossover with arbitrary phase compensation in a single unit to achieve both size and loss reductions.
Kaposi's Sarcoma-Associated Herpesvirus Viral Interferon Regulatory Factor 4 (vIRF4/K10) Is a Novel Interaction Partner of CSL/CBF1, the Major Downstream Effector of Notch Signaling

ABSTRACT In cells infected with the Kaposi's sarcoma-associated herpesvirus (KSHV), CSL/CBF1 signaling is essential for viral replication and promotes the survival of KSHV-infected cells. CSL/CBF1 is a DNA adaptor molecule which recruits coactivator and corepressor complexes to regulate viral and cellular gene transcription and which is a major downstream effector molecule of activated Notch. The interaction of KSHV RTA and LANA with CSL/CBF1 has been shown to balance the lytic and latent viral life cycle. Here we report that a third KSHV protein, viral interferon regulatory factor 4 (vIRF4/K10), but none of the three other KSHV-encoded vIRFs, interacts with CSL/CBF1. Two regions of vIRF4 with dissimilar affinities contribute to CSL/CBF1 binding. Similar to Notch, vIRF4 targets the hydrophobic pocket in the beta trefoil domain of CSL/CBF1 through a short peptide motif which closely resembles a motif found in Notch but does not strictly follow the ΦWΦP consensus conserved in human and mouse Notch proteins. Our results suggest that vIRF4 might compete with Notch for CSL/CBF1 binding and signaling.
Compensation for nonlinear distortion in MIMO OFDM systems using MMSE receiver

This paper presents a compensating method based on Neural Network (NN) of Non-Linear (NL) distortion, which caused by High Power Amplifier (HPA) in Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (MIMO OFDM) systems. In this work, we present and we evaluate with simulation, the effect of nonlinearity on the system capacity and the performance of NN compensator accompanied with Minimum Mean Square Error (MMSE) receiver in a VBLAST (Vertical Bell Laboratories Layered Space-Time) MIMO OFDM systems running under a Rayleigh fading channel.
Analysis of a Polycomb Group Protein Defines Regions That Link Repressive Activity on Nucleosomal Templates to In Vivo Function

ABSTRACT Polycomb group (PcG) genes propagate patterns of transcriptional repression throughout development. The products of several such genes are part of Polycomb repressive complex 1 (PRC1), which inhibits chromatin remodeling and transcription in vitro. Genetic and biochemical studies suggest the product of the Posterior sex combs (Psc) gene plays a central role in both PcG-mediated gene repression in vivo and PRC1 activity in vitro. To dissect the relationship between the in vivo and in vitro activities of Psc, we identified the lesions associated with 11 genetically characterized Psc mutations and asked how the corresponding mutant proteins affect Psc activity on nucleosomal templates in vitro. Analysis of both single-mutant Psc proteins and recombinant complexes containing mutant protein revealed that Psc encodes at least two functions, complex formation and the inhibition of remodeling and transcription, which require different regions of the protein. There is an excellent correlation between the in vivo phenotypes of mutant Psc alleles and the structure and in vitro activities of the corresponding proteins, suggesting that the in vitro activities of PRC1 reflect essential functions of Psc in vivo.
Joint Non-negative Matrix Factorization for Learning Ideological Leaning on Twitter

People are shifting from traditional news sources to online news at an incredibly fast rate. However, the technology behind online news consumption promotes content that confirms the users» existing point of view. This phenomenon has led to polarization of opinions and intolerance towards opposing views. Thus, a key problem is to model information filter bubbles on social media and design methods to eliminate them. In this paper, we use a machine-learning approach to learn a liberal-conservative ideology space on Twitter, and show how we can use the learned latent space to tackle the filter bubble problem. We model the problem of learning the liberal-conservative ideology space of social media users and media sources as a constrained non-negative matrix-factorization problem. Our model incorporates the social-network structure and content-consumption information in a joint factorization problem with shared latent factors. We validate our model and solution on a real-world Twitter dataset consisting of controversial topics, and show that we are able to separate users by ideology with over 90% purity. When applied to media sources, our approach estimates ideology scores that are highly correlated(Pearson correlation 0.9) with ground-truth ideology scores. Finally, we demonstrate the utility of our model in real-world scenarios, by illustrating how the learned ideology latent space can be used to develop exploratory and interactive interfaces that can help users in diffusing their information filter bubble.