Miracle-dz/UniFAR-FTUs huggingface dataset:
Fast single image dehazing based on color cube constraint

The outdoor images captured in bad weather are prone to yield low and poor visibility, which is a serious issue for most computer vision applications. The majorities of existing dehazing methods rely on the dark channel prior (DCP) assumption and therefore share two mains limitations; the model is invalid when the scene is intrinsically similar to the atmospheric light and the DCP method suffers from high computational cost to refine the transmission map. In this paper, we propose a fast single image dehazing based on color cube constraint based on new haze imaging model to overcome these two limitations. The thickness of the haze can be estimated effectively, and a haze-free image can be recovered by adopting the new method and the new haze imaging model. In this method, we first design a new haze imaging model which enables us to represent the hazy image inside a color cube according to the concentration of the haze. Then, to get an accurate value of the global atmospheric light we took the maximum value of each RGB color channel. Next, we propose a simple but very powerful prior or method called variation of distance prior (VOD), which is a statistic of extensive high resolution outdoor images. Using this prior combined with the designed haze imaging model and improved global atmospheric light, we can directly estimate the transmission map and restore a high quality outdoor haze-free image. The experimental results show that our model is physically valid, and the proposed method outperforms several state-of-the-art single image dehazing methods in terms of effectiveness robustness and speed.
Innovation and Competition

In the literature on innovation and competition, consideration of the ‘innovativeness’ of innovation has been neglected. This paper investigates the relationship between innovation and competition conditional on the innovativeness of innovation and the distance to frontier. We measure the innovativeness of innovation by analyzing whether it is a new-to-the-market innovation or a new-to-the-firm innovation. Further, we develop a new measure of firms’ technological level using firms’ main objective of innovation. Using a dataset from surveys of Korean manufacturing firms from 2002 to 2004, this paper finds that the relationship between competition and innovation is conditional on both the quality of innovation and distance to frontier. The results are: (1) frontiers are more likely to innovate than technological laggard firms, (2) competition has an inverted-U shape relation with new to the market innovation, while there is no such relation with new to the firm only innovation, (3) the inverted-U shape relation between competition and innovation is driven by frontiers, not followers or laggards, and (4) new to the market innovation and R&D expenditure show a similar pattern of an inverted-U shape relation with competition, while new to the firm only innovation and patents exhibit a similar pattern of no relation with competition.
An Intrusion Detection and Prevention Framework for Internet-Integrated CoAP WSN

End-to-end communications between Internet devices and Internet-integrated constrained wireless sensing platforms will provide an important contribution to the enabling of many of the envisioned IoT applications and, in this context, security must be addressed when employing communication technologies such as 6LoWPAN and CoAP. Considering the constraints typically found on sensing devices in terms of energy, memory, and computational capability, the integration of Wireless Sensor Networks (WSN) with the Internet using such technologies will open new threats and attacks that must be dealt with, particularly those originated at devices without the constraints of WSN sensors (e.g., Internet hosts). Existing encryption strategies for communications in IoT environments are unable to protect Internet-integrated WSN environments from Denial of Service (DoS) attacks, as well as from other forms of attacks at the network and application layers using CoAP. We may thus fairly consider that anomaly and intrusion detection will play a major role in the materialization of most of the envisioned IoT applications. In this article, we propose a framework to support intrusion detection and reaction in Internet-integrated CoAP WSN, and in the context of this framework we design and implement various approaches to support security against various classes of attacks. We have implemented and evaluated experimentally the proposed framework and mechanisms, considering various attack scenarios, and our approach was found to be viable, from the point of view of its impact on critical resources of sensing devices and of its efficiency in dealing with the considered attacks.
Free Radical Damage in Ischemia-Reperfusion Injury: An Obstacle in Acute Ischemic Stroke after Revascularization Therapy

Acute ischemic stroke is a common cause of morbidity and mortality worldwide. Thrombolysis with recombinant tissue plasminogen activator and endovascular thrombectomy are the main revascularization therapies for acute ischemic stroke. However, ischemia-reperfusion injury after revascularization therapy can result in worsening outcomes. Among all possible pathological mechanisms of ischemia-reperfusion injury, free radical damage (mainly oxidative/nitrosative stress injury) has been found to play a key role in the process. Free radicals lead to protein dysfunction, DNA damage, and lipid peroxidation, resulting in cell death. Additionally, free radical damage has a strong connection with inducing hemorrhagic transformation and cerebral edema, which are the major complications of revascularization therapy, and mainly influencing neurological outcomes due to the disruption of the blood-brain barrier. In order to get a better clinical prognosis, more and more studies focus on the pharmaceutical and nonpharmaceutical neuroprotective therapies against free radical damage. This review discusses the pathological mechanisms of free radicals in ischemia-reperfusion injury and adjunctive neuroprotective therapies combined with revascularization therapy against free radical damage.
EVALUATION OF BIOLOGICAL ACTIVE COMPOUNDS FOUND IN Silybi mariani fructus

Milk thistle (Silybum marianum L.) is a herbaceous plant, annual or biennial, cultivated, sometimes as sub-spontaneous plant, which is found from the Mediterranean Region to Central Asia. This plant contains biologically active compounds such as flavonoids (quercetin, taxifoline and dehydrokermepherol), lipids (linoleic acid, oleic acid and palmitic acid), sterols and mucilages, sugars (arabinose, rhamnose, xylose, glucose), amines and saponins (cholesterol, campesterol and stigmasterol). This paper describes methods for obtaining extracts, in order to obtain active biological compounds from Silybi mariani fructus, extracts characterised through modern analytical techniques, as well as the evaluation of their antioxidant activity.
A Corpus to Learn Refer-to-as Relations for Nominals

Continuous representations for words or phrases, trained on large unlabeled corpora are proved very useful for many natural language processing tasks. While these vector representations capture many ﬁne-grained syntactic and semantic regularities among words or phrases, it often lacks coreferential information which is useful for many downstream tasks like information extraction, text summarization etc. In this paper, we argue that good word and phrase embeddings should contain information for identifying refer-to-as relationship and construct a corpus from Wikipedia to generate coreferential neural embeddings for nominals. The term nominal refers to a word or a group of words that functions like a noun phrase. In addition, we use coreference resolution as a proxy to evaluate the learned neural embeddings for noun phrases. To simplify the evaluation procedure, we design a coreferential phrase prediction task where the learned nominal embeddings are used to predict which candidate nominals can be referred to a target nominal. We further describe how to construct an evaluation dataset for such task from well known OntoNotes corpus and demonstrate encouraging baseline results.
Reciprocal Negative Regulation Between Lmx1a and Lmo4 Is Required for Inner Ear Formation

LIM-domain containing transcription factors (LIM-TFs) are conserved factors important for embryogenesis. The specificity of these factors in transcriptional regulation is conferred by the complexes that they form with other proteins such as LIM-domain-binding (Ldb) proteins and LIM-domain only (LMO) proteins. Unlike LIM-TFs, these proteins do not bind DNA directly. LMO proteins are negative regulators of LIM-TFs and function by competing with LIM-TFs for binding to Ldb's. Although the LIM-TF Lmx1a is expressed in the developing mouse hindbrain, which provides many of the extrinsic signals for inner ear formation, conditional knock-out embryos of both sexes show that the inner ear source of Lmx1a is the major contributor of ear patterning. In addition, we have found that the reciprocal interaction between Lmx1a and Lmo4 (a LMO protein within the inner ear) mediates the formation of both vestibular and auditory structures. Lmo4 negatively regulates Lmx1a to form the three sensory cristae, the anterior semicircular canal, and the shape of the utricle in the vestibule. Furthermore, this negative regulation blocks ectopic sensory formation in the cochlea. In contrast, Lmx1a negatively regulates Lmo4 in mediating epithelial resorption of the canal pouch, which gives rise to the anterior and posterior semicircular canals. We also found that Lmx1a is independently required for the formation of the endolymphatic duct and hair cells in the basal cochlear region. SIGNIFICANCE STATEMENT The mammalian inner ear is a structurally complex organ responsible for detecting sound and maintaining balance. Failure to form the intricate 3D structure of this organ properly during development most likely will result in sensory deficits on some level. Here, we provide genetic evidence that a transcription factor, Lmx1a, interacts with its negative regulator, Lmo4, to pattern various vestibular and auditory components of the mammalian inner ear. Identifying these key molecules that mediate formation of this important sensory organ will be helpful for designing strategies and therapeutics to alleviate hearing loss and balance disorders.
Anti-jamming power control game for data packets transmission

In this paper, we investigated the anti-jamming power control game problem in which the user aims to maximize the throughput of data packets transmitted successfully. Stackelberg game is utilized to model and analyze the anti-jamming problem. The closed form expressions of the optimal power for both the user and jammer are derived. Simulation results are conducted to validate our theoretical analysis.
Growth, Behavior, And Mating Of Pharaoh Cuttlefish (Sepia Pharaonis Ehrenberg) In Captivity

The pharaoh cuttlefish (Sepia pharaonis) was successfully reared from egg to an average size of 168 mm mantle length and 521 g in 210 days, using simple biological filtration systems. The period of egg incubation was 15 days at a temperature of 27-31˚C. Hatchlings were reared at a stocking density of one animal per liter during the first month; density was reduced as growth proceeded. Food items consisted of live mysids, Artemia salina, juvenile fishes, and prawns. Juveniles were gradually acquainted with dead food items such as caridian prawns and small fishes. The present study shows that the pharaoh cuttlefish can be reared in captivity with a survival rate of 41%, using live feeds during the first 50 days. Future commercial scale culture of this species depends on development of artificial feeds and high density culture systems.
Magmas Erupted during the Main Pulse of Siberian Traps Volcanism were Volatile-poor

This work was supported by a Natural Environment Research Council (NE/H012648/1) and a Natural Environment Research Council Ion Microprobe Facility award. S.S. acknowledges Trinity Hall (Cambridge, UK) for providing a Mann Studentship towards her PhD studies. The Centre for Physics of Geological Processes, University of Oslo, provided the fieldwork funding.
Multilingual Multi-class Sentiment Classification Using Convolutional Neural Networks

This paper describes a language-independent model for multi-class sentiment analysis using a simple neural network architecture of ﬁve layers (Embedding, Conv1D, GlobalMaxPooling and two Fully-Connected). The advantage of the proposed model is that it does not rely on language-speciﬁc features such as ontologies, dictionaries, or morphological or syntactic pre-processing. Equally important, our system does not use pre-trained word2vec embeddings which can be costly to obtain and train for some languages. In this research, we also demonstrate that oversampling can be an effective approach for correcting class imbalance in the data. We evaluate our methods on three publicly available datasets for English, German and Arabic, and the results show that our system’s performance is comparable to, or even better than, the state of the art for these datasets. We make our source-code publicly available.
An Empirical Investigation of a Long-Run Risks Model using Stock and Derivative Data

This paper constructs and estimates a long-run risk (LRR) model of returns on US equity and options and shows that the …tted model simultaneously can explain many cen- tral features of the data such as the equity premium, the slow decay of volatility, and most interestingly, the variance risk premium -the dierence between the option-implied variance and the expected realized variance of the underlying equity-index returns. The model improves on standard LRR models by adding two key features: jumps in the fun- damental state variables and a two-factor volatility structure. Both features are crucial to successfully explain the key stylized facts of the U.S. stock and option markets jointly. Moreover, the fundamental jump risk constitutes about 50% of the equity premium, which reveals a fundamental link between the equity premium and the variance risk premium. Finally, contributing to the growing literature of stock-return predictability by the variance risk premium, I …nd that even this expanded LRR model may not be su¢ cient to explain such a short-run predictability, suggesting that the predictability might not be caused by fundamental consumption risks.
Advances in Intravital Non-Linear Optical Imaging of the Central Nervous System in Rodents

Purpose of review: Highly coordinated cellular interactions occur in the healthy or pathologic adult rodent central nervous system (CNS). Until recently, technical challenges have restricted the analysis of these events to largely static modes of study such as immuno-fluorescence and electron microscopy on fixed tissues. The development of intravital imaging with subcellular resolution is required to probe the dynamics of these events in their natural context, the living brain. Recent findings: This review focuses on the recently developed live non-linear optical imaging modalities, the core principles involved, the identified technical challenges that limit their use and the scope of their applications. We highlight some practical applications for these modalities with a specific attention given to Experimental Autoimmune Encephalomyelitis (EAE), a rodent model of a chronic inflammatory disease of the CNS characterized by the formation of disseminated demyelinating lesions accompanied by axonal degeneration. Summary: We conclude that label-free nonlinear optical imaging combined to two photon imaging will continue to contribute richly to comprehend brain function and pathogenesis and to develop effective therapeutic strategies.
The Relationship Between Population Growth and Economic Growth in Mexico

The relationship between population growth and economic growth is of great interest both for demographers and for development economists. Considering the case of Mexico, the objective of this study was to analyze the dynamic relationship between population growth and economic growth, through a structural break cointegration analysis for the period 1960-2014. The Gregory-Hansen cointegration test confirmed the existence of a long run equilibrium relationship between population and economic growth in Mexico. Based on the results of this test, we used 1985 as the year in which the structural break occurs in the cointegrating equation and therefore we included a dummy variable for this year in the VECM developed in the paper. In the short run, it was found that economic growth has a negative effect on population growth. In the long run, it was found that population has a positive effect on per capita GDP and that per capita GDP positively affects population. Additionally, a Granger causality test indicated that per capita GDP is Granger-caused by population and population is Granger-caused by per capita GDP, thus revealing the presence of a mutually reinforcing relationship between these two variables. In sum, the results found in this study suggest the existence of a bi-directional causality between population growth and economic growth in Mexico.
Does The Expectations Hypothesis Explain The Term Structure Of Treasury Bond Yields In Tunisia

This paper tests the expectations hypothesis (EH) using monthly data for Treasury bond yields (TBYs) over the period 1994m5–2014m12 and ranging in maturity from one year to 10 years. We apply cointegrated-VAR jointly on more than one pair of yields. The results suggest rejection of the EH throughout the medium maturity spectrum. However, for longer maturities they suggest the validity of the EH for the TBYs. This indeed confirms the smooth functioning of Tunisian bond market which gives an indication that the yield curve should serve as an indicator to the monetary policymakers to manage inflation and to influence the aggregate demand in the economy.
Effects of ethanol preservation on otolith microchemistry

Solution-based inductively coupled plasma-mass spectrometry was used to examine the effects of exposure time to ethanol (0, 1, 3, 9, 27 and 81 days) and ethanol quality (ACS- v. HPLC-grade) on strontium (Sr) and barium (Ba) concentrations in sagittal otoliths of hatchery-raised and wild-caught young-of-the-year walleye Stizostedion vitreum. No effect of either attribute on Sr and Ba concentrations were detected, indicating that metabolically inert elements that replace calcium in the calcium carbonate matrix (e.g. Sr and Ba) are not influenced by storage in 95% ethanol.
Echocardiographic assessment of β‐adrenoceptor stimulation‐induced heart failure with reduced heart rate in mice

Chronic injection with the β‐adrenoceptor (β‐AR) agonist isoproterenol (ISO) has been commonly used as an animal model of β‐AR‐induced cardiac remodelling and heart failure. This ISO‐treated model usually exhibits significantly decreased conscious heart rate (HR). However, the HR in treatment groups is usually adjusted to the same levels by anaesthesia to assess cardiac geometry and function. In the present study, we report a method of echocardiographic assessment that represents the true cardiac geometry and function under conditions of ISO withdrawal. Briefly, C57BL/6 mice were treated with 5 mg/kg per day ISO for 12 weeks. Cardiac geometry and function were assessed by high‐resolution echocardiography in vehicle (saline) ‐ and ISO‐treated mice that were either conscious or anaesthetized using different concentrations of isoflurane. The cardiac β‐AR response was decreased in ISO‐treated mice, as evidenced by markedly decreased conscious HR. Vehicle‐ and ISO‐treated mice did not differ in terms of cardiac geometry or function when HR was adjusted to the same level (400 b.p.m.) in both treatment groups, but cardiac geometry and function did differ when a low (1%) rather than high (1.5% or 2%) isoflurane concentration was used to adjust HR. Furthermore, 3 day ISO withdrawal eliminated the difference in conscious HR between the two groups. In addition, the groups differed in cardiac geometry and function regardless of the isoflurane concentration used. In conclusion, using isoflurane to decrease the HR of treated groups to the same level may mask left ventricular dysfunction in ISO‐treated mice. Withdrawal of ISO eliminated the difference in basal HR between the ISO‐treated and control groups on echocardiography, allowing a more accurate assessment of cardiac pathological and functional changes.
DeepEM: Deep 3D ConvNets With EM For Weakly Supervised Pulmonary Nodule Detection

Recently deep learning has been witnessing widespread adoption in various medical image applications. However, training complex deep neural nets requires large-scale datasets labeled with ground truth, which are often unavailable in many medical image domains. For instance, to train a deep neural net to detect pulmonary nodules in lung computed tomography (CT) images, current practice is to manually label nodule locations and sizes in many CT images to construct a sufficiently large training dataset, which is costly and difficult to scale. On the other hand, electronic medical records (EMR) contain plenty of partial information on the content of each medical image. In this work, we explore how to tap this vast, but currently unexplored data source to improve pulmonary nodule detection. We propose DeepEM, a novel deep 3D ConvNet framework augmented with expectation-maximization (EM), to mine weakly supervised labels in EMRs for pulmonary nodule detection. Experimental results show that DeepEM can lead to 1.5% and 3.9% average improvement in free-response receiver operating characteristic (FROC) scores on LUNA16 and Tianchi datasets, respectively, demonstrating the utility of incomplete information in EMRs for improving deep learning algorithms.1
Modeling Continuous Video QoE Evolution: A State Space Approach

A rapid increase in the video traffic together with an increasing demand for higher quality videos has put a significant load on content delivery networks in the recent years. Due to the relatively limited delivery infrastructure, the video users in HTTP streaming often encounter dynamically varying quality over time due to rate adaptation, while the delays in video packet arrivals result in rebuffering events. The user quality-of-experience (QoE) degrades and varies with time because of these factors. Thus, it is imperative to monitor the QoE continuously in order to minimize these degradations and deliver an optimized QoE to the users. Towards this end, we propose a nonlinear state space model for efficiently and effectively predicting the user QoE on a continuous time basis. The QoE prediction using the proposed approach relies on a state space that is defined by a set of carefully chosen time varying QoE determining features. An evaluation of the proposed approach conducted on two publicly available continuous QoE databases shows a superior QoE prediction performance over the state-of-the-art QoE modeling approaches. The evaluation results also demonstrate the efficacy of the selected features and the model order employed for predicting the QoE. Finally, we show that the proposed model is completely state controllable and observable, so that the potential of state space modeling approaches can be exploited for further improving QoE prediction.
Disorder as harmful dysfunction: a conceptual critique of DSM-III-R's definition of mental disorder.

The Diagnostic and Statistical Manual of Mental Disorders (3rd ed., rev.; DSM-III-R) operationally defines disorder essentially as "statistically unexpectable distress or disability. " This definition is an attempt to operationalize 2 basic principles: that a disorder is harmful and that a disorder is a dysfunction (i.e., an inability of some internal mechanism to perform its natural function). However, the definition fails to capture the idea of "dysfunction" and so fails to validly distinguish disorders from nondisorders, leading to invalidities in many of DSM-III-R's specific diagnostic criteria. These problems with validity are traced to DSM-III-R's strategies for increasing reliability.