Miracle-dz/UniFAR-FTUs huggingface dataset:
Mechanochemical Endovenous Occlusion of Varicose Veins Using the ClariVein® Device.

INTRODUCTION In the last decade, minimally invasive endothermal ablation techniques have replaced surgery for the treatment of superficial venous insufficiency to reduce postoperative complications and recovery time and to improve quality of life. To avoid the risks of nerve damage and need for tumescent anesthesia to improve patient comfort, an alternative heatless technique has been introduced recently. METHODS Endovenous mechanochemical occlusion using the ClariVein® catheter (Vascular Insights LLC, Quincy, MA) is a new technique combining mechanical injury to the venous endothelium coupled with simultaneous catheter-guided infusion of a liquid sclerosant. This produces irreversible damage to the endothelium resulting in fibrosis of the vein. RESULTS The technique is related to a low complication rate and a success rate of 96% at two years and sustained quality of life improvement. This closure rate is comparable to endothermal techniques, but significantly less postoperative pain and earlier return to normal activities and work has been reported with endovenous mechanochemical occlusion. CONCLUSION Mechanochemical occlusion using ClariVein® has proven to be safe and effective and has several advantages compared to endothermal techniques. The possibility of retrograde ablation of distal SSV insufficiency in C6 ulceration is considered a significant advantage. Randomized comparative studies with long-term follow up will continue to define the definite place of mechanochemical occlusion.
Use of Obesity Biomarkers in Cardiovascular Epidemiology

Obesity is an established risk factor for cardiovascular disease (CVD), yet, the underlying mechanisms are only poorly understood. The adipose tissue produces a variety of hormones and cytokines and thereby actively participates in a network of biomarkers that may be relevant for the development of CVD. Such obesity biomarkers have a great potential to better characterize the obesity phenotype that may be relevant for the risk of CVD beyond anthropometric parameters. They may be used to support mechanistic studies, to help identify individuals at risk for CVD, and to evaluate the effect of preventive measures. The present article discusses the role of some of the most promising obesity biomarkers in cardiovascular epidemiology, including inflammatory markers, adiponectin, resistin, and fetuin-A. Importantly, some of these markers have been related to cardiovascular risk even after accounting for anthropometric parameters. Further, the potential ability to manipulate blood levels of some of these biomarkers through medication, diet and lifestyle make them attractive markers for cardiovascular risk. However, many open questions remain – especially with regard to the causal role of the factors as well as with regard to the extent of improvement in CVD prediction by these markers – before measurement of these biomarkers may be recommended on a public health level.
A Robust Image Watermarking in the Ridgelet Domain Using Universally Optimum Decoder

A robust image watermarking scheme in the ridgelet transform domain is proposed in this paper. Due to the use of the ridgelet domain, sparse representation of an image which deals with line singularities is obtained. In order to achieve more robustness and transparency, the watermark data is embedded in selected blocks of the host image by modifying the amplitude of the ridgelet coefficients which represent the most energetic direction. Since the probability distribution function of the ridgelet coefficients is not known, we propose a universally optimum decoder to perform the watermark extraction in a distribution-independent fashion. Decoder extracts the watermark data using the variance of the ridgelet coefficients of the most energetic direction in each block. Furthermore, since the decoder needs the noise variance to perform decoding, a robust noise estimation scheme is proposed. Moreover, the implementation of error correction codes on the proposed method is investigated. Analytical derivation of bit error probability is also carried out and experimental results prove its accuracy. Simulation also shows outstanding robustness of the proposed scheme against common attacks, especially additive white noise and JPEG compression.
Boulder 07 : Modelling Stochastic Gene Expression

A system evolves stochastically if its dynamics is partly generated by a force of random strength or by a force at random times or by both. For stochastic systems, it is not possible to exactly determine the state of the system at later times given its state at the current time. Instead, to describe a stochastic system, we use the probability that the system is in a certain state and can predict exactly how this probability changes with time. Nevertheless, such a calculation is often difficult, and we usually focus on finding the moments of the probability distribution, such as the mean and variance. These two quantities are commonly measured experimentally. The level of stochasticity in a system is often referred to as its ‘noise’. Any chemical reaction is stochastic. Reactants come together by diffusion, their motion driven by rapid and frequent collisions with other molecules. Once together, these same collisions alter the internal energies of the reactants, and so their propensity to react. Both effects cause individual reaction events to occur randomly and drive the overall reaction stochastic. Is stochasticity important in biology? Intuitively, stochasticity is only significant when mean numbers of molecules are low. Then, individual reactions, which at most change the numbers of molecules by one or two, matter. Low numbers are frequent in vivo: gene copy number is typically one or two, and transcription factors often number in the tens, at least in bacteria [1, 2]. Unambiguously measuring stochastic gene expression, however, can be challenging [2]. Naively, we could place Green Fluorescent Protein (GFP) on a bacterial chromosome downstream of a promoter that is activated by the system of interest. By measuring the variation in fluorescence across a population of cells, we could measure the noise in the system. Every biochemical reaction, however, is potentially stochastic. Fluorescence variation could be because of noise in the process under study or could result from the general background ‘hum’ of stochasticity: stochastic effects in ribosome synthesis could lead to different numbers of ribosomes and so to differences in gene expression in each cell; stochastic effects in the cell cycle machinery may desynchronize the population; stochastic effects in signaling networks could cause each cell to respond uniquely, and so on. Variation has then two classes: intrinsic stochasticity — stochasticity inherent in the dynamics of the system and that arises from fluctuations in the reactions occurring in the system — and extrinsic stochasticity — stochasticity originating from fluctuations in other cellular processes that interact with the system under study [3, 4]. To determine whether variation is intrinsic or extrinsic, it helps to visualize an identical second copy of the system, present in the same cell and exposed to the
alpha 1- and beta 2-adrenergic receptor expression in the Madin-Darby canine kidney epithelial cell line

The Madin-Darby canine kidney (MDCK) cell line, derived from distal tubule/collecting duct, expresses differentiated properties of renal tubule epithelium in culture. We studied the expression of adrenergic receptors in MDCK to examine the role of catecholamines in the regulation of renal function. Radioligand-binding studies demonstrated, on the basis of receptor affinities of subtype-selective adrenergic agonists and antagonists, that MDCK cells have both alpha 1- and beta 2- adrenergic receptors. To determine whether these receptor types were expressed by the same cell, we developed a number of clonal MDCK cell lines. The clonal lines had stable but unique morphologies reflecting heterogeneity in the parent cell line. Some clones expressed only beta 2-adrenergic receptors and were nonmotile, whereas others expressed both alpha 1- and beta 2-receptors and demonstrated motility on the culture substrate at low cell densities. In one clone, alpha- and beta- receptor expression was stable for more than 50 passages. Catecholamine agonists increased phosphatidylinositol turnover by activating alpha- adrenergic receptors and cellular cyclic adenosine monophosphate accumulation by activating beta-adrenergic receptors. Guanine nucleotide decreased the affinity of isoproterenol for the beta 2- receptor but did not alter the affinity of epinephrine for the alpha 1- receptor. These results show that alpha 1- and beta 2-receptors can be expressed by a single renal tubular cell and that the two receptors behave as distinct entities in terms of cellular response and receptor regulation. Heterogeneity of adrenergic receptor expression in MDCK clones may reflect properties of different types of renal tubule cells.
Consumption of DHA + EPA by low-income women during pregnancy and lactation.

BACKGROUND The ω-3-fatty acid docosahexaenoic acid (DHA) is important in infant brain development and maturation. The advisable intake of the ω-3 fatty acids DHA and eicosapentaenoic acid (EPA) for pregnant and lactating women is 300 mg/d or 9 g/month. The objective of this cross-sectional study was to test the hypothesis that low-income pregnant/or lactating women do not consume advisable amounts of DHA+EPA and to determine whether any of the measured demographic factors were related to DHA and EPA consumption. METHODS This study was conducted September 2007 to March 2008 and used the N-3 Fatty Acid Food Frequency Questionnaire for dietary assessment in a convenience sample of women (N = 68) enrolled in a local maternal infant health program. Women who reported fish or seafood allergies were excluded. The monthly consumption of DHA+EPA from food sources was measured, and participant race, ethnicity, country of origin, primary language, level of education, marital status, intake of prenatal vitamins containing DHA+EPA, and warnings of fish toxicity were assessed. The data were analyzed using 1-way analysis of variance and t tests. RESULTS The average reported DHA+EPA intake was 1.18 g/month across all race/ethnicities. African Americans consumed significantly more DHA+EPA, 2.79 g/month, compared with Hispanics (1.64 g) and Caucasians (0.93 g). United States natives consumed significantly more DHA+EPA than immigrants (2.45 g vs 1.55 g). CONCLUSIONS Low-income pregnant/and lactating women in the study consumed less than the advisable amounts of DHA+EPA. Both ethnicity and country of origin are related to DHA+EPA intake.
Somatic and germline mosaicism for a R248C missense mutation in FGFR3, resulting in a skeletal dysplasia distinct from thanatophoric dysplasia

In this communication, we report the identification of a mosaic R248C missense mutation in the IgII–III linker region of the gene encoding the fibroblast growth factor receptor‐3 (FGFR3), in an individual who manifests a skeletal dysplasia and epidermal hyperplasia. By means of Denaturing High Performance Liquid Chromatography (DHPLC), we determined that 25% of her lymphocytes are heterozygous for this particular missense mutation in FGFR3, and that 12.5% of her lymphocyte‐derived genomic DNA encodes a cysteine residue at this position. The proposita has disproportionate short stature, radial head dislocation, coxa vara, and bowing of some of the long bones, associated with an S‐shaped deformity of the humerus, accompanied by widespread acanthosis nigricans in the integument. These features do not match any previously described skeletal dysplasia. Further, the proposita's only pregnancy ended in the delivery of a fetus manifesting a lethal short‐limbed dwarfism with pulmonary hypoplasia, strongly suggestive of an undiagnosed thanatophoric dysplasia. These findings confirm the proposita to be a somatic and germline mosaic for this particular missense mutation in FGFR3. Thus far, all reported FGFR3 R248C mutations have resulted in thanatophoric dysplasia type I (TDI). © 2003 Wiley‐Liss, Inc.
Rivastigmine for the treatment of dementia associated with Parkinson’s disease

Parkinson’s disease (PD) afflicts millions of people worldwide and leads to cognitive impairment or dementia in the majority of patients over time. Parkinson’s disease dementia (PDD) is characterized by deficits in attention, executive and visuospatial function, and memory. The clinical diagnostic criteria and neuropathology surrounding PDD remain controversial with evidence of overlap among PDD, dementia with Lewy bodies (DLB) and Alzheimer’s disease (AD). Cortical cholinergic deficits are greater in PDD than in AD, and are well-correlated with the cognitive and neuropsychiatric dysfunction that occurs in PDD. Inhibition of acetylcholine metabolism is therefore a practical therapeutic strategy in PDD. This review examines current evidence for rivastigmine (a cholinesterase/butyrylcholinesterase inhibitor) treatment in PDD. In addition to its efficacy, we examine the safety profile, side effects, and cost effectiveness of rivastigmine in PDD. Rivastigmine provides modest benefit in PDD and further long-term studies are needed to determine the effectiveness and safety of rivastigmine over time. Tolerability is a problem for many PDD patients treated with rivastigmine. Future studies of rivastigmine in PDD should focus on pragmatic outcomes such as time to need for nursing home placement, pharmacoeconomic outcomes and simultaneous patient/caregiver quality of life assessments.
Path loss study for millimeter wave device-to-device communications in urban environment

In the recent years the millimeter wave spectrum is being explored as a prospective band for the next generation (5G) cellular communications. In this paper we study the propagation of the the millimetre wave spectrum using ray tracing model for an urban environment. We consider the ISM bands in 24GHz and 61GHz in particular and conduct ray tracing simulations to study the path loss behaviour in terms of the path loss exponent and the shadowing variance for both Line of Sight and Non Line of Sight conditions. As a potential application we examine the device to device (D2D) communication, which is currently being developed for LTE-A standard. The resulting pathloss exponents and the shadow variances are presented here based on ray tracing simulations for an ITU-R statistical urban model, moreover this paper shows that intelligent beam steering can significantly improve the throughput for the considered D2D scenarios.
Automatic Standard Classification Method for the 2.4 GHz ISM Band

As IoT (Internet of Things) systems using wireless standards sharing the 2.4 GHz ISM band become widespread, radio interference often disturbs data communication. In order to mitigate interference-related problems, it would be helpful to have a method that determines to which standard a received packet belongs. However, conventional methods do not analyze the actual environment of congestion nor do they classify narrowband signals. In this paper, we propose identification algorithms and an automatic standard classification method that identifies WLAN/IEEE 802.15. 4/BT (Bluetooth)/BLE (Bluetooth Low Energy), which are considered typical standards in the 2.4 GHz ISM band. The results show that the identification algorithms improve detection sensitivities compared to conventional ones, and the proposed method of automatic standard classification accurately analyzed the actual situation where radio waves of plural standards overlap one another.
Interhemispheric functional and structural alterations and their relationships with alertness in unilateral temporal lobe epilepsy.

OBJECTIVE Many neuroimaging studies have shown that temporal lobe epilepsy (TLE) is associated with functional and structural abnormalities at speciﬁc brain areas. Unfortunately, relatively limited information has been presented about the alterations of interhemispheric functional and anatomic connectivity in patients with unilateral TLE. In the present study, we investigated interhemispheric functional connectivity using a voxel-mirrored homotopic connectivity (VMHC) method. We further revealed fractional anisotropy (FA) changes in the areas with abnormal VMHC values in TLE patients by diffusion tensor imaging (DTI). Moreover, their relationships with alertness in patients with drug-naive unilateral TLE were also investigated. PATIENTS AND METHODS Forty-three patients with unilateral TLE (21 left TLE and 22 right TLE) and 20 normal controls (NC) were recruited for case-control study. All of the subjects underwent acquisition of resting-state functional magnetic resonance images, Mini-Mental State Examination (MMSE) and the attention network test. DTI images were collected in 26 patients with unilateral TLE (10 left TLE and 16 right TLE) and 20 NCs. Functional connectivity between bilateral homotopic voxels was calculated. Homotopic regions showing abnormal functional connectivity in patients were adopted as regions of interest for the analysis of DTI. The FA values, MMSE scores, and alertness were compared between groups. Correlation analyses were employed to examine the relationships between each radiographic parameter (VMHC and FA) and each clinical and neuropsychological parameter in patients with drug-naive unilateral TLE. RESULTS Compared with NC, patients with left TLE exhibited significantly higher VMHC values in the bilateral angular gyrus, inferior occipital gyrus and superior parietal gyrus and lower VMHC values in the bilateral supplementary motor area, inferior parietal lobule, middle temporal gyrus, and medial superior frontal gyrus. In patients with right TLE, higher VMHC values were found in the bilateral inferior occipital gyrus, parahippocampal gyrus and cerebellum; lower VMHC values were observed in the bilateral middle temporal gyrus and precentral gyrus/inferior frontal gyrus. FA values of the commissural fiber bundles connecting the bilateral parahippocampal gyrus were smaller in the right TLE than those in the NC group. Meanwhile, the alerting effect of patients was determined to be impaired and positively correlated with FA values of the commissural fiber bundles connecting the bilateral parahippocampal gyrus in right TLE patients. CONCLUSIONS Our findings indicate that the bilateral parahippocampal gyrus may be important to the pathophysiology of patients with drug-naive unilateral TLE. The significant correlation between the FA values and alertness indicates that structural changes are involved in the alterations in the alertness network in unilateral right TLE patients.
A Hybrid Collaborative Filtering Approach for Multi-Functional Service Recommendation

As the increasing numbers of various multi-functional Cloud services are rapidly evolving in the Cloud market, how to recommend ideal multi-functional services becomes a great challenge. Due to its simplicity and promising results, collaborative filtering has been one of the most dominant methods used in recommender systems. The fundamental assumption of collaborative filtering is that users rated items similarly will rate other items similarly. However, with regards to a multi-functional service, a user may only use one of the functions and give a post-rating. Such a rating emotionally expresses the user's preference on the function rather than on the whole service. Therefore, it is appropriate to measure similarity at the granularity of functions' ratings. In our proposed approach, each user's rating is assigned to a function according to the usage record. Then, a hybrid user-based and item-based collaborative filtering algorithm is used to recommend multi-functional services. Such approach is experimentally verified at the end of this paper.
Term Recognition Using Technical Dictionary Hierarchy

In recent years, statistical approaches on ATR (Automatic Term Recognition) have achieved good results. However, there are scopes to improve the performance in extracting terms still further. For example, domain dictionaries can improve the performance in ATR. This paper focuses on a method for extracting terms using a dictionary hierarchy. Our method produces relatively good results for this task.
How to find different neural networks by negative correlation learning

Two penalty functions are introduced in the negative correlation learning for finding different neural networks in an ensemble. One is based on the average output of the ensemble. The other is based on the classification. The idea of penalty function based on the average output is to make each individual network has the different output value to that of the ensemble on the same input. In comparison, the penalty function based on the classification is to lead each individual network to have different class to that of the ensemble on the same input. Experiments on a classification task show how the negative correlation learning generates different neural networks with two different penalty functions.
Nonlinear Discriminant Analysis Using Kernel Functions and the Generalized Singular Value Decomposition

Linear discriminant analysis (LDA) has been widely used for linear dimension reduction. However, LDA has limitations in that one of the scatter matrices is required to be nonsingular and the nonlinearly clustered structure is not easily captured. In order to overcome the problems caused by the singularity of the scatter matrices, a generalization of LDA based on the generalized singular value decomposition (GSVD) was recently developed. In this paper, we propose a nonlinear discriminant analysis based on the kernel method and the GSVD. The GSVD is applied to solve the generalized eigenvalue problem which is formulated in the feature space defined by a nonlinear mapping through kernel functions. Our GSVD-based kernel discriminant analysis is theoretically compared with other kernel-based nonlinear discriminant analysis algorithms. The experimental results show that our method is an effective nonlinear dimension reduction method.
Livelihood Options? The Political Economy of Access, Opportunity and Diversification

vi 1 Definitions and Dimensions of Livelihood Diversification 1 1.1 Definitions of diversification: multiplicity and/or change? 1 1.2 Livelihoods in the economy: basic dimensions of livelihood activities 1 2 Structural Transformation and the Non-farm Economy 4 2.1 Industrialisation and urbanisation 4 2.2 Regional growth theory and the rise and fall of the rural non-farm economy 5 2.3 Global structural transformations in agriculture and industry 7 2.4 The impacts of change and transformations 9 2.5 Three approaches to understanding rural change and transformation 11 3 Livelihood Strategies: Assets, Activities and Well-being 14 3.1 Micro-economic models of livelihood 14 3.2 Towards a basic framework 17 3.3 Taking assets further 19 3.4 Terms of transformation 21 3.5 Preference, choice and well-being strategies 24 4 Adaptable Systems: Vulnerability, Coping and Diversification 28 4.1 Exogenous forces and mediating factors 28 4.2 Risk, diversification and insurance 29 4.3 Coping strategies 30 4.4 Vulnerability and capability 31 5 Segmented Opportunity: Social Structures and Processes of Access, Production and Exchange 33 5.1 Theories of distribution, production and exchange 33 5.2 Surplus, access and class 34 5.3 Social processes of production and exchange: interlinked markets in rural India 37 6 Rural Transformation, Occupational Diversification and Social Change 39 6.