Miracle-dz/UniFAR-FTUs huggingface dataset:
11β-Hydroxysteroid Dehydrogenase 1 Specific Inhibitor Increased Dermal Collagen Content and Promotes Fibroblast Proliferation

Glucocorticoids (GCs) are one of the most effective anti-inflammatory drugs for treating acute and chronic inflammatory diseases. However, several studies have shown that GCs alter collagen metabolism in the skin and induce skin atrophy. Cortisol is the endogenous GC that is released in response to various stressors. Over the last decade, extraadrenal cortisol production in various tissues has been reported. Skin also synthesizes cortisol through a de novo pathway and through an activating enzyme. 11β-hydroxysteroid dehydrogenase 1 (11β-HSD1) is the enzyme that catalyzes the conversion of hormonally inactive cortisone to active cortisol in cells. We previously found that 11β-HSD1 negatively regulates proliferation of keratinocytes. To determine the function of 11β-HSD1 in dermal fibroblasts and collagen metabolism, the effect of a selective 11β-HSD1 inhibitor was studied in mouse tissues and dermal fibroblasts. The expression of 11β-HSD1 increased with age in mouse skin. Subcutaneous injection of a selective 11β-HSD1 inhibitor increased dermal thickness and collagen content in the mouse skin. In vitro, proliferation of dermal fibroblasts derived from 11β-HSD1 null mice (Hsd11b1−/− mice) was significantly increased compared with fibroblasts from wild-type mice. However, in vivo, dermal thickness of Hsd11b1−/− mice was not altered in 3-month-old and 1-year-old mouse skin compared with wild-type mouse skin. These in vivo findings suggest the presence of compensatory mechanisms in Hsd11b1−/− mice. Our findings suggest that 11β-HSD1 inhibition may reverse the decreased collagen content observed in intrinsically and extrinsically aged skin and in skin atrophy that is induced by GC treatment.
Fibroblast Growth Factor Receptor 1 Amplification in Non-Small Cell Lung Cancer by Quantitative Real-Time PCR

Introduction Amplification of the fibroblast growth factor receptor 1 (FGFR1) gene has been described in tumors of non-small-cell lung cancer (NSCLC) patients. Prior reports showed conflicting rates of amplification frequency and clinical relevance. Materials and Methods We developed a reliable real-time quantitative PCR assay to assess the frequency of FGFR1 amplification and assessed the optimal cutoff level of amplification for clinical application. Results In a training cohort of 203 NSCLCs, we established that a 3.5-fold amplification optimally divided patients into groups with different survival rates with a clear threshold level. Those with FGFR1 amplification levels above 3.5-fold had an inferior survival. These data were confirmed in a validation cohort of 142 NSCLC. After adjusting for age, sex, performance status, stage, and histology, patients with FGFR1 amplification levels above 3.5 fold had a hazard ratio of 2.91 (95% CI- 1.14, 7.41; pvalue-0.025) for death in the validation cohort. The rates of FGFR1 amplification using the cutoff level of 3.5 were 5.1% in squamous cell and 4.1% in adenocarcinomas. There was a non-significant trend towards higher amplifications rates in heavy smokers (> 15 pack-years of cigarette consumption) as compared to light smokers. Discussion Our data suggest that a 3.5-fold amplification of FGFR1 is of clinical importance in NSCLC. Our cutpoint analysis showed a clear threshold effect for the impact of FGFR1 amplification on patients’ survival, which can be used as an initial guide for patient selection in trials assessing efficacy of novel FGFR inhibitors.
Does the type of first-line regimens influence the receipt of second-line chemotherapy treatment? An analysis of 3211 metastatic colon cancer patients

With new agents entering the market, the sequencing of first‐line (Tx1), second‐line (Tx2), and subsequent chemotherapy/biologics regimens are being examined. We examined how Tx1 regimens impacted the likelihood of receiving Tx2 among metastatic colon cancer (mCC) patients. Surveillance, Epidemiology and End Results (SEER)‐Medicare data were used to identify elderly mCC patients between 2003 and 2007. The inverse probability weighting Cox regression method was utilized to study the relationship between receipt of Tx2 and Tx1 regimens, controlling for patient‐level factors. Of the 7895 elderly patients identified, 3211 (41%) received Tx1 of which 1440 proceeded to Tx2. The impact of Tx1 on receipt of Tx2 varied by the specific regimens utilized. As compared to 5FU/LV users, IROX (Hazard Ratio [HR] = 0.03; P < 0.01) and IROX + Biologics (HR = 0.20; P < 0.01) users were less likely to receive Tx2; (oxaliplatin) OX + Biologics (HR = 1.26; P < 0.01) users were more likely to receive Tx2. Significant patient‐level factors included: Hispanic ethnicity (HR = 0.67; P < 0.01); being married (HR = 0.87; P = 0.01); proxy for poor performance status (HR = 0.82; P = 0.05); each 10‐year age increment (HR = 1.14; P < 0.01); and State buy‐in status (HR = 1.21; P = 0.01). The specific first‐line regimen does impact mCC patients' likelihood of receiving Tx2 in clinical practice. Elderly mCC patients, their health care providers, and policy makers will benefit from new evidence about the impact of sequencing of treatment lines.
Cooperative Advertising and Pricing in a Dynamic Stochastic Supply Chain: Feedback Stackelberg Strategies

Cooperative (co‐op) advertising is an important instrument for aligning manufacturer and retailer decisions in supply chains. In this, the manufacturer announces a co‐op advertising policy, i.e., a participation rate that specifies the percentage of the retailer's advertising expenditure that it will provide. In addition, it also announces the wholesale price. In response, the retailer chooses its optimal advertising and pricing policies. We model this supply chain problem as a stochastic Stackelberg differential game whose dynamics follows Sethi's stochastic sales‐advertising model. We obtain the condition when offering co‐op advertising is optimal for the manufacturer. We provide in feedback form the optimal advertising and pricing policies for the manufacturer and the retailer. We contrast the results with the advertising and price decisions of the vertically integrated channel, and suggest a method for coordinating the channel.
A Mutation/Injection-Based Automatic Framework for Evaluating Code Clone Detection Tools

In recent years many methods and tools for software clone detection have been proposed. While some work has been done on assessing and comparing performance of these tools, very little empirical evaluation has been done. In particular, accuracy measures such as precision and recall have only been roughly estimated, due both to problems in creating a validated clone benchmark against which toolscan be compared, and to the manual effort required to hand check large numbers of candidate clones. In this paper we propose an automated method for empirically evaluating clone detection tools that leverages mutation-based techniques to overcome these limitations by automatically synthesizing large numbers of known clones based on an editing theory of clone creation. Our framework is effective in measuring recall and precision of clone detection tools for various types of fine-grained clones in real systems without manual intervention.
A Semi-Automatic Framework to Discover Epistemic Modalities in Scientific Articles

Documents in scientific newspapers are often marked by attitudes and opinions of the author and/or other persons, who contribute with objective and subjective statements and arguments as well. In this respect, the attitude is often accomplished by a linguistic modality. As in languages like english, french and german, the modality is expressed by special verbs like can, must, may, etc. and the subjunctive mood, an occurrence of modalities often induces that these verbs take over the role of modality. This is not correct as it is proven that modality is the instrument of the whole sentence where both the adverbs, modal particles, punctuation marks, and the intonation of a sentence contribute. Often, a combination of all these instruments are necessary to express a modality. In this work, we concern with the finding of modal verbs in scientific texts as a pre-step towards the discovery of the attitude of an author. Whereas the input will be an arbitrary text, the output consists of zones representing modalities.
Consensus-based formation control for multiple nonholonomic robots

This paper presents a decentralized consensus-based formation controller that considers both, the kinematic and the dynamic model, to asymptotically drive a network composed of N nonholonomic mobile robots to a desired formation with a given orientation. The network is modeled as an undirected, static and connected graph. The controller is a simple time-varying PD-like scheme. Simulations, using a network with six nonholonomic mobile robots are reported to support the theoretical contributions.
A Quadrature RC Oscillator With Noise Reduction by Voltage Swing Control

This paper presents a low power and low noise quadrature RC oscillator based on a frequency locked loop. Voltage swing control of each of the two sub-oscillators reduces the effect of 1/f noise on the accumulated jitter. In addition, the use of quadrature phases greatly relieves timing constraints of sampling operations and helps the reduction of power consumption. With a discrete-time modeling of the quadrature oscillator, noise analysis is also provided for quantitative estimation of the circuit-driven effects on the phase noise. The proposed oscillator is fabricated using 180-nm CMOS process in an active area of 0.058mm2. The measurement shows a period jitter of 0.047% and a standard deviation of 0.94% in untrimmed frequency (444.9kHz) in a wafer. The oscillator achieves a figure-of-merit of 155 dBc/Hz at 100 Hz offset frequency.
The Relation between Quantitative EEG Coherence and Self-Report ADHD Behavior Scale Responses

iii LIST OF ABBREVIATIONS . v CHAPTER 1: INTRODUCTION . 1 CHAPTER 2: METHOD . 24 CHAPTER 3: RESULTS . 34 CHAPTER 4: DISCUSSION . 43 REFERENCES . 51
Speech-Based Visual Concept Learning Using Wordnet

Modeling visual concepts using supervised or unsupervised machine learning approaches are becoming increasing important for video semantic indexing, retrieval, and filtering applications. Naturally, videos include multimodality data such as audio, speech, visual and text, which are combined to infer therein the overall semantic concepts. However, in the literature, most researches were conducted within only one single domain. In this paper we propose an unsupervised technique that builds context-independent keyword lists for desired visual concept modeling using WordNet. Furthermore, we propose an extended speech-based visual concept (ESVC) model to reorder and extend the above keyword lists by supervised learning based on multimodality annotation. Experimental results show that the context-independent models can achieve comparable performance compared to conventional supervised learning algorithms, and the ESVC model achieves about 53% and 28.4% improvement in two testing subsets of the TRECVID 2003 corpus over a state-of-the-art speech-based video concept detection algorithm
Changing attitudes toward needle biopsies of breast cancer in Shanghai: experience and current status over the past 8 years

Diagnostic patterns in breast cancer have greatly changed over the past few decades, and core needle biopsy (CNB) has become a reliable procedure for detecting breast cancer without invasive surgery. To estimate the changing diagnostic patterns of breast cancer in urban Shanghai, 11,947 women with breast lesions detected by preoperative needle biopsy between January 1995 and December 2012 were selected from the Shanghai Cancer Data base, which integrates information from approximately 50% of breast cancer patients in Shanghai. The CNB procedure uses an automated prone unit, biopsy gun, and 14-gauge needles under freehand or ultrasound guidance and was performed by experienced radiologists and surgeons specializing in needle biopsies. Diagnosis and classification for each patient were independently evaluated by pathologists. Over the indicated 8-year period, biopsy type consisted of 11,947 ultrasound-guided core needle biopsies (UCNBs), 2,015 ultrasound-guided vacuum-assisted biopsies (UVABs), and 654 stereotactic X-ray-guided vacuum-assisted biopsies (XVABs). For all the 11,947 women included in this study, image-guided needle biopsy was the initial diagnostic procedure. Approximately 81.0% of biopsied samples were histopathologically determined to be malignant lesions, 5.5% were determined to be high-risk lesions, and 13.5% were determined to be benign lesions. The number of patients choosing UCNB increased at the greatest rate, and UCNB has become a standard procedure for histodiagnosis because it is inexpensive, convenient, and accurate. The overall false-negative rate of CNB was 1.7%, and the specific false-negative rates for UCNB, UVAB, and XVAB, were 1.7%, 0%, and 0%, respectively. This study suggests that the use of preoperative needle biopsy as the initial breast cancer diagnostic procedure is acceptable in urban Shanghai. Preoperative needle biopsy is now a standard procedure in the Shanghai Cancer Center because it may reduce the number of surgeries needed to treat breast cancer.
Taking Positive Interest Rates Seriously

We present a dynamic term structure model in which interest rates of all maturities are bounded from below at zero. Positivity and continuity, combined with no arbitrage, result in only one functional form for the term structure with three sources of risk. One dynamic factor controls the level of the interest rate and follows a special two-parameter square-root process under the risk-neutral measure. The two parameters of the process determine the other two sources of risk and act as two static factors. This model has no other parameters to estimate and hence bears no other risks.
DROid: Adapting to individual mobility pays off in mobile data offloading

Cellular operators count on the potentials of offloading techniques to relieve their overloaded data channels. Beyond standard access point-based offloading strategies, a promising alternative is to exploit opportunistic direct communication links between mobile devices. Nevertheless, achieving efficient device-to-device offloading is challenging, as communication opportunities are, by nature, dependent on individual mobility patterns. We propose, design, and evaluate DROiD (Derivative Re-injection to Offload Data), an original method to finely control the distribution of popular contents throughout a mobile network. The idea is to use the infrastructure resources as seldom as possible. To this end, DROiD injects copies through the infrastructure only when needed: (i) at the beginning, in order to trigger the dissemination, (ii) if the evolution of the opportunistic dissemination is below some expected pace, and (iii) when the delivery delay is about to expire, in order to guarantee 100% diffusion. Our strategy is particularly effective in highly dynamic scenarios, where sudden creation and dissolution of clusters of mobile nodes prevent contents to diffuse properly. We assess the performance of DROiD by simulating a traffic information service on a realistic large-scale vehicular dataset composed of more than 10,000 nodes. DROiD substantially outperforms other offloading strategies, saving more than 50% of the infrastructure traffic even in the case of tight delivery delay constraints. DROiD allows terminal-to-terminal offloading of data with very short maximum reception delay, in the order of minutes, which is a realistic bound for cellular user acceptance.
Curve Space: Classifying Curves On Surfaces

We design signatures for curves defined on genus zero surfaces. The signature classifies curves according to the conformal geometry of the given curves and their embedded surface. Based on Teichmuller theory, our signature describes not only the curve shape but also the intrinsic relationship between the curve and its embedded surface. Furthermore, the signature metric is stable, it is close to identity between surfaces sharing similar Riemannian geometry metrics. Based on this, we propose a surface matching framework: first, with curve signatures, we match the partitioning of two surfaces defined by simple closed curves on them; second, the segmented subregions are pairwisely matched and then compared on canonical planar domains. 1. Introduction. Shape analysis and shape comparison are fundamental prob- lems in computer vision, graphics and modeling fields with many important appli- cations. Lots of 2D and 3D shape analysis techniques have been developed in the past couple of decades, most of which are based on comparing curvature or spacial positions of the points on the curve. A complete different way is to consider all the closed curves on the surface. The curve space on surface conveys rich geometric information of the surface itself and is easy to process. The philosophy of analyzing shapes by their associated curve spaces has deep root in algebraic topology (8), infinite dimensional Morse theory (18) and Teichmuller space theory in complex geometry (31). Suppose M is a surface (a 2-manifold), a closed curve on M is a map
Viable and testable SUSY GUTs with Yukawa unification: the case of split trilinears

We explore general SUSY GUT models with exact third-generation Yukawa unification, but where the requirement of universal soft terms at the GUT scale is relaxed. We consider the scenario in which the breaking of universality inherits from the Yukawa couplings, i.e. is of minimal flavor violating (MFV) type. In particular, the MFV principle allows for a splitting between the up-type and the down-type soft trilinear couplings. We explore the viability of this trilinear splitting scenario by means of a fitting procedure to electroweak observables, quark masses as well as flavor-changing neutral current processes. Phenomenological viability singles out one main scenario. This scenario is characterized by a sizable splitting between the trilinear soft terms and a large μ term. Remarkably, this scenario does not invoke a partial decoupling of the sparticle spectrum, as in the case of universal soft terms, but instead it requires part of the spectrum, notably the lightest stop, the gluino and the lightest charginos and neutralinos to be very close to the current experimental limits. The above mechanism is mostly triggered by a non-trivial interplay between the requirements of negative, sizable SUSY threshold corrections to mb and an instead negligible modification of the B → Xsγ decay rate, in presence of various other constraints, most notably a successful EWSB and a not too large BR(Bs → μ+μ−). We present a model-building interpretation of our discussed scenario and emphasize the crucial role of SUSY spectrum determinations at the LHC for either falsifying Yukawa unification or else providing important hints on the mechanism of SUSY breaking at work.
The harmonious robot

Purpose – To describe the design methodology and human‐centre functionality of the whole arm manipulator (WAM) developed originally at MIT and brought to commercial fruition by Barrett Technology.Design/methodology/approach – The WAM arm is driven by cable‐and‐cylinder transmissions, which uniquely exhibits zero backlash with low friction and low inertia, endowing the WAM with good open‐loop “backdrivability”. Two key benefits of the high backdrivability are: motion control through joint torque control, which enables the intrinsic sensing of forces over the whole arm and makes it inherently safe to humans; operation directly in the Cartesian domain without the need for inverse kinematics calculations, providing very rapid responsiveness as demonstrated in the “baseball robot” of Tokyo University. Another benefit of the WAM is its kinematic redundancy through the 4‐dof (degrees‐of‐freedom) main axes (7‐dof with the wrist). Recent major advances in the WAM include the “puck”, the world's smallest fully‐feat.
Metabolic Imaging in Prostate Cancer: Where We Are

In recent years, the development of diagnostic methods based on metabolic imaging has been aimed at improving diagnosis of prostate cancer (PCa) and perhaps at improving therapy. Molecular imaging methods can detect specific biological processes that are different when detected within cancer cells relative to those taking place in surrounding normal tissues. Many methods are sensitive to tissue metabolism; among them, positron emission tomography (PET) and magnetic resonance spectroscopic imaging (MRSI) are widely used in clinical practice and clinical research. There is a rich literature that establishes the role of these metabolic imaging techniques as valid tools for the diagnosis, staging, and monitoring of PCa. Until recently, European guidelines for PCa detection still considered both MRSI/MRI and PET/CT to be under evaluation, even though they had demonstrated their value in the staging of high risk PCa, and in the restaging of patients presenting elevated prostatic-specific antigen levels following radical treatment of PCa, respectively. Very recently, advanced methods for metabolic imaging have been proposed in the literature: multiparametric MRI (mpMRI), hyperpolarized MRSI, PET/CT with the use of new tracers and finally PET/MRI. Their detection capabilities are currently under evaluation, as is the feasibility of using such techniques in clinical studies.
Data Partitioning for Video-on-Demand Services

Streaming video over the Internet has become a popular service that is projected to outstrip demand over most other real-time streaming services. Thus, it is essential to provide scalable server storage and services without which video-on-demand services will not be able to provide good performance in the face of increasing demand. In this paper, we study algorithms, and propose one, for simple partitioning video-on-demand storage to distribute content and workload among servers within a master-slave architecture. We show the effectiveness of the partitioning strategies by conducting experiments on an actual system to quantify trade-offs between the algorithms.
A Method for Network Vulnerability Analysis Using Colored Petri Net

Traditional methods for evaluating network security neglect the correlation of network vulnerabilities. To solve this problem, a method based on Colored Petri Net (CPN) modeling is presented. Potential attack sequences are built according to the correlation of network vulnerabilities. The weakness and key paths can be found through analyzing the attack sequences. Simulation results show that the proposed method can help network managers to find the hidden danger actively and make security strategies effectively.