Miracle-dz/UniFAR-FTUs huggingface dataset:
A comparison of two different treadmill protocols in measuring maximal oxygen consumption in highly trained distance runners

RYAN ADAM VANHOY: A comparison of two different treadmill protocols in measuring maximal oxygen consumption in highly trained distance runners (Under the direction of Dr. Claudio L. Battaglini) The purpose of this study was to prospectively investigate the specificity effect of two different treadmill protocols on maximal oxygen consumption (VO 2max) in highly-trained distance runners (n=16). The secondary purpose examined if the ventilatory threshold (VT) attained during different protocols occurred at the same percent of VO 2max (% VO 2max @ VT). After a familiarization session performing the Bruce Protocol, VO 2max was evaluated using two graded treadmill protocols; a horizontal (increment in speed only) (SOVO 2max) and inclined (constant speed with increment in grade only) (GOVO 2max). VO 2max values were significantly higher from the GOVO 2max in comparison to the SOVO 2max protocol (76.1 and 71.2 mLO 2 /kg/min, p=. 005). The % VO 2max @ VT was not significantly different between the GOVO 2max and SOVO 2max protocols. The results indicate that, based on runner specialty (flat versus hill runners), either SOVO 2max or GOVO 2max protocols can be used to determine the % VO 2max @ VT in highly-trained distance runners.
Angiogenic Activity of Cytochalasin B-Induced Membrane Vesicles of Human Mesenchymal Stem Cells

Background The cytochalasin B-induced membrane vesicles (CIMVs) are suggested to be used as a vehicle for the delivery of therapeutics. However, the angiogenic activity and therapeutic potential of human mesenchymal stem cells (MSCs) derived CIMVs (CIMVs-MSCs) remains unknown. Objectives The objectives of this study were to analyzed the morphology, size distribution, molecular composition and angiogenic properties of CIMVs-MSCs. Methods The morphology of CIMVs-MSC was analyzed by scanning electron microscopy. The proteomic analysis, multiplex analysis and immunostaining were used to characterize the molecular composition of the CIMVs-MSCs. The transfer of surface proteins from a donor to a recipient cell mediated by CIMVs-MSCs was demonstrated using immunostaining and confocal microscopy. The angiogenic potential of CIMVs-MSCs was evaluated using in vivo approach of subcutaneous implantation of CIMVs-MSCs in mixture with Matrigel matrix. Results Human CIMVs-MSCs retain parental MSCs content such as growth factors, cytokines, chemokines: EGF, FGF-2, Eotaxin, TGF-α, G-CSF, Flt-3L, GM-CSF, Fractalkine, IFNα2, IFN-γ, GRO, IL-10, MCP-3, IL-12p40, MDC, IL-12p70, IL-15, sCD40L, IL-17A, IL-1RA, IL-1a, IL-9, IL-1b, IL-2, IL-4, IL-5, IL-6, IL-7, IL-8, IP-10, MCP-1, MIP_1a, MIP-1b, TNF-α, TNF-β, VEGF. CIMVs-MSCs also have the expression of surface receptors similar to those in parental human MSCs (CD90+, CD29+, CD44+, CD73+). Additionally, CIMVs-MSCs could transfer membrane receptors to the surfaces of target cells in vitro. Finally, CIMVs-MSCs can induce angiogenesis in vivo after subcutaneous injection into adult rats. Conclusions Human CIMVs-MSCs have similar content, immunophenotype and angiogenic activity to those of the parental MSCs. Therefore, we believe that human CIMVs-MSCs could be used for cell free therapy of degenerative diseases.
Quercetin abates induction of hepatic and renal oxidative damage, inflammation, and apoptosis in carbendazim-treated rats

Exposure to the fungicide carbendazim (CBZ) has been associated with hepatorenal dysfunction. Quercetin, a naturally occurring polyphenolic phytochemical, reportedly possesses beneficial health effects. However, there is paucity of scientific information on the impact of quercetin on CBZ-induced hepatorenal damage. The present study investigated the protective mechanism of quercetin in CBZ-induced hepatic and renal damage in rats. The treatment groups consisted of control, CBZ alone (50 mg/kg), quercetin alone (20 mg/kg), and rats co-treated with CBZ and quercetin for 14 consecutive days. Quercetin co-treatment significantly (p < 0.05) abated CBZ-induced increase in biomarkers of hepatorenal damage when compared to CBZ alone. Also, quercetin abrogated CBZ-mediated decrease in antioxidant status as well as the increase in reactive oxygen and nitrogen species and lipid peroxidation in the treated rats. Furthermore, quercetin significantly suppressed CBZ-mediated increase in interleukin-1β, tumor necrosis factor alpha, and caspase-3 activity in the liver and kidney of the rats. Histopathological examination demonstrated that the severity of CBZ-induced hepatic and renal injury was ameliorated in rats co-treated with quercetin. Taken together, quercetin-mediated hepatorenal protection in CBZ-treated rats involves antioxidant, anti-inflammatory, and antiapoptotic mechanisms.
All-Fiber Vortex Laser Based on a Nonlinear Amplifying Loop Mirror and a Coupler

We constructed an all-fiber pulsed vortex laser based on a nonlinear amplifying loop mirror (NALM) and a coupler that was fused with a single-mode fiber (SMF) and a few-mode fiber (FMF). The cavity, including an NALM, was in charge of the generation of pulses. The coupler inserted into the cavity acted as a mode converter. The produced 393-fs vortex beam had a spectrum width of 12 nm and centered at 1567 nm.
Determinants and Management of Patient Waiting Time in the General Outpatient Department in Kibabii University Health Clinic, Kenya

The purpose of this paper is to determine the time that a patient can spend waiting for service in Kibabii University Healthcare Clinic in Bungoma County (Kenya). The main objective was to provide necessary information to service facility managers, stakeholders, hospital staffs and other related institutions with the knowledge to improve the queuing system or to curb long waiting time of patients seeking services which can cause deterioration of the disease and sudden demise. This project also aims at providing suggestions to various factors identified to be the causes of long waiting time in the outpatient department at Kibabii University healthcare to help the smooth running of the clinic. The ODK tool was used in data collection procedure to capture the opinions of the respondents. The results from the ODK Tool was exported to XLS which is an export feature of data to excel, later data was exported to SPSS for analysis from excel.
Robust Single Accelerometer-Based Activity Recognition Using Modified Recurrence Plot

Using a single 3-axis accelerometer for human activity recognition is challenging but attractive in daily healthcare and monitoring with wearable sensors and devices. In this paper, an effective and efficient framework is proposed to address the recognition problem without any heavy preprocessing. We encode 3-axis signals as 3-channel images using a modified recurrence plot (RP) and train a tiny residual neural network to do image classification. The modified RP is first proposed in our paper to overcome its tendency confusion problem, which has improved our system performance significantly. We evaluate our algorithm on a new database and a public dataset. Results show that our recognition framework achieves highly competitive accuracies and good efficiencies with other state-of-the-art methods on both datasets. Moreover, our method shows stronger robustness to noise and low decimation rate through comparison experiments. Finally, we provide detailed discussion and analysis of our approach from two perspectives: the pattern analysis of encoding algorithm and the interpretation of classification model.
Global Access to the Internet for All

This document presents a taxonomy of "Alternative Network deployments", and a set of definitions and shared characteristics. This term includes a set of network access models emerged in the last decade with the aim of bringing Internet connectivity to people, using topological, architectural and business models different from the so-called "traditional" ones, where a company deploys the network infrastructure for connecting the users, who pay for it. Several initiatives throughout the world have built large scale networks that are alternative to the traditional network operator deployments using predominately wireless technologies (including long distance) due to the reduced cost of using the unlicensed spectrum. Wired technologies such as Fiber are also used in some of these alternate networks. There are several types of such alternate network: networks such as community networks are self-organized and decentralized networks wholly owned by the community; networks owned by individuals who act as wireless internet service providers (WISPs), networks owned by individuals but leased out to network operators who use such networks as a low-cost medium to reach the underserved population and finally there are networks that provide connectivity by sharing wireless resources of the users. The emergence of these networks can be motivated by different causes such as the reluctance, or the impossibility, of network operators to Saldana, et al. Expires July 25, 2015 [Page 1] Internet-Draft Alternative Network Deployments January 2015 provide wired and cellular infrastructures to rural/remote areas. In these cases, the networks have self sustainable business models that provide more localised communication services as well as Internet backhaul support through peering agreements with traditional network operators. Some other times, networks are built as a complement and an alternative to commercial Internet access provided by "traditional" network operators. The present classification considers different existing network models such as Community Networks, open wireless services, userextensible services, traditional local Internet Service Providers (ISPs), new global ISPs, etc. Different criteria are used in order to build a classification as e.g., the ownership of the equipment, the way the network is organized, the participatory model, the extensibility, if they are driven by a community, a company or a local (public or private) stakeholder, etc. According to the developed taxonomy, a characterization of each kind of network is presented, in terms of specific network characteristics related to architecture, organization, etc.
Code Design Based on Connecting Spatially Coupled Graph Chains

A novel code construction based on spatially coupled low-density parity-check (SC-LDPC) codes is presented. The proposed code ensembles are comprised of several protograph-based chains characterizing individual SC-LDPC codes. We demonstrate that the code ensembles obtained by connecting appropriately chosen individual SC-LDPC code chains at specific points have improved iterative decoding thresholds. In addition, the connected chain ensembles have a smaller decoding complexity required to achieve a specific bit error probability compared to the individual code chains. Moreover, we demonstrate that, like the individual component chains, the proposed constructions have a typical minimum distance that grows linearly with block length. Finally, we show that the improved asymptotic properties of the connected chain ensembles also translate into improved finite length performance.
Short-Term Forecasting of Electricity Spot Prices Containing Random Spikes Using a Time-Varying Autoregressive Model Combined With Kernel Regression

Forecasting spot prices of electricity is challenging because it not only contains seasonal variations, but also random, abrupt spikes, which depend on market conditions and network contingencies. In this paper, a hybrid model has been developed to forecast the spot prices of electricity in two main stages. In the first stage, the prices are forecasted using autoregressive time varying (ARXTV) model with exogenous variables. To improve the forecasting ability of the ARXTV model, the price variations in the training process have been smoothened using the wavelet technique. In the second stage, a kernel regression is used to estimate the price spikes, which are detected using support vector machine based model. In addition, mutual information technique is employed to select appropriate input variables for the model. A case study is carried out with the aid of price data obtained from the Australian energy market operator. It is demonstrated that the proposed hybrid method can accurately forecast electricity prices containing spikes.
Hip retraction enhances walking stability on a ramp: an equilibrium point hypothesis-based study

Hip retraction is a phenomenon observed in human walking. The swing leg rotates backward at the end of the motion. Its positive effect on motion stability was reported in the literature based on some simple models for running or walking. In this study, it is shown that hip retraction angle increases in humans during their ascending and descending walk on a stair. In previous studies, hip retraction was modeled by defining a proper motion for the swing leg. According to the equilibrium point hypothesis, the central nervous system (CNS) defines only the equilibrium point(s) and stiffness(es) for body joint(s) to control the human motion. Human body motion emerges as its natural response as a result of the external forces and the defined equilibrium points of joints. Considering the hip torque as a spring-like model with an equilibrium point and stiffness, this study revealed that the hip retraction can be generated by the natural response of the swing leg. Besides, the stabilizing effect of hip retraction was demonstrated by a model for human’s ascending and descending walking on a ramp with a range of positive and negative angles, respectively. The findings suggest that the CNS needs to define equilibrium point just ahead of the stance leg to take advantage of the hip retraction effect on ascending and descending walks on a ramp.
An Extensible Overlay Infrastructure for Wide-Area Stream Processing and Dissemination

nomics and Business, Athens, Greece. She worked as a software engineer for the Athens Stock Exchange untill 2002. She then joined the graduate program in Brown University, where she received her Sc. Acknowledgments The first person I would like to thank is my advisor, Ugur Cetintemel. Ugur's positive attitude inspired me from the first time I met him, in my visit at Brown as a perspective student. During my studies in Brown, he continued to be an endless source of motivation and encouragement for me. Ugur taught me how to be a researcher, invested a lot of time teaching me how to effectively present my ideas and provided his valuable advice on many critical points in my career and personal life. I will always be grateful to him for his guidance, his support and his patience all of these years. I would like also to thank my committee member and co-author, John Jannotti. His interesting questions and feedback helped me understand my own work in more depth and had an important impact on this dissertation. Thanks are also due to my third committee member, Stan Zdonik, whose support and encouragement helped me pursue my career goals. I would also like to thank the student members of the Data Management Group in Brown. I am really happy I met and worked with all of you! Nesime, you have inspired me in many different ways, in my research, in my career choices (and even during our gym classes! ). My dear officemates, Ying and Jeong-Hyon, thank you for sharing with me many stressful moments. Yanif, I really appreciate the effort and time you spent discussing the details of XPORT and building our demonstration. Finally, I would like to thank the summer interns who contributed to the prototyping of my work: The years I spent at Brown were the best years of my life thanks to my friends. Manos Renieris, Yiannis Tsochantaridis and Aris Anagnostopoulos patiently listened and advised me, especially in the early years. Ioanna Papaefthimiou and Ioanna Grypari were always bringing out the positive aspect of any situation and they made my life so much more fun. I would like also to thank Cleopatra Stefan Roth and Yiannis Vergados for all the laughs we shared. Finally, the last couple of years were much more enjoyable and less lonely than I ever expected thanks to Menia Pavlakou, Sofocles Mavroeidis, Babis Papamanthou and Dimitra …
Uncoordinated Pseudonym Changes for Privacy Preserving in Distributed Networks

Pseudonyms have been adopted to preserve identity privacy of nodes in distributed networks. Frequent and unlinkable changes of pseudonyms need to be enabled by having at least <inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="liu-ieq1-2911279.gif"/></alternatives></inline-formula> nodes change together to confuse potential eavesdroppers. Existing approaches either depend on the coordination from central controllers, or involve interactive signaling between the nodes. This can potentially compromise privacy. This paper proposes a fully uncoordinated approach to change pseudonyms in distributed networks, where each node uses a pseudonym until its expiration and then changes after a random delay. We develop a new model to analyse the time-varying population of changing pseudonyms. Critical conditions are analytically established, under which individual nodes can independently change their pseudonyms while their identity privacy is preserved. The conditions are validated by illustrative examples. Corroborated by simulations, the accuracy of the analytical model improves, as the number of nodes increases. The analysis confirms that, the <inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="liu-ieq2-2911279.gif"/></alternatives></inline-formula>-anonymity can be achieved at a negligible throughput loss in the case of large networks.
What Do We Really Know About Corporate Governance? A Review of the Empirical Research Since 2000

Corporate governance is currently understood by most legal actors to lie at the heart of corporate law. In addition to the explosion in academic interest in governance over the past three decades, it has increasingly been seen as a way to address a wide array of economic and social problems. In order for corporate governance to do the work assigned it, however, it must take the form of “best practices” that are generalizable across a wide variety of firms and circumstances. These best practices have been subject to extensive empirical research since the 1990s. This article examines this body of research, with particular attention to the studies published since 2000, which correct prior flaws and take advantage of the earlier papers for meta-analysis. The article focuses on what the author understands to be the current board best practices: (1) independent directors; (2) board committees of independent directors (particularly the audit committee); (3) board diversity; (4) separating the CEO and board chair roles; (5) director overboarding (also known as director busyness): and (6) interlocking directorships. When the empirical research in this area is looked at in its totality, there is surprisingly strong agreement that none of the best practices contribute in a measurable way to firm performance, or to other outcomes that are value-enhancing to firms. There is evidence, visible here and there in the research, that corporate governance arrangements do matter, but that imposing the same arrangements on all companies regardless of circumstances has the effect of benefitting some companies and damaging others in such a way that, as a group, North American businesses are left worse off. The article concludes by recommending regulatory responses in an era when faith in one-size-fits-all corporate governance best practices can no longer be sustained.
Pattern Synthesis via Complex-Coefficient Weight Vector Orthogonal Decomposition--Part I: Fundamentals

This paper presents a new array response control scheme named complex-coefficient weight vector orthogonal decomposition ($ \textrm{C}^2\textrm{-WORD} $) and its application to pattern synthesis. The proposed $ \textrm{C}^2\textrm{-WORD} $ algorithm is a modified version of the existing WORD approach. We extend WORD by allowing a complex-valued combining coefficient in $ \textrm{C}^2\textrm{-WORD} $, and find the optimal combining coefficient by maximizing white noise gain (WNG). Our algorithm offers a closed-from expression to precisely control the array response level of a given point starting from an arbitrarily-specified weight vector. In addition, it results less pattern variations on the uncontrolled angles. Elaborate analysis shows that the proposed $ \textrm{C}^2\textrm{-WORD} $ scheme performs at least as good as the state-of-the-art $\textrm{A}^\textrm{2}\textrm{RC} $ or WORD approach. By applying $ \textrm{C}^2\textrm{-WORD} $ successively, we present a flexible and effective approach to pattern synthesis. Numerical examples are provided to demonstrate the flexibility and effectiveness of $ \textrm{C}^2\textrm{-WORD} $ in array response control as well as pattern synthesis.
Sensorless Unbalance Modeling and Estimation as an Ancillary Service for LV Four-Wire/Three-Phase Power Converters

This paper describes a method to provide low-voltage four-wire three-phase power converters with the capability of unbalance estimation as an ancillary service to the main role that they play in the distribution system (distributed generator, energy storage system, drive, etc.). Typically, dedicated grid/load current sensors are needed to effectively comply with unbalance compensation tasks, increasing system cost and reducing reliability. This is due to the difficulties that arise in the extraction of the zero- and negative-voltage components from the voltages at the point of common coupling, such as the inadequate resolution of full-scaled voltage sensors and limited spectral separation. In this paper, the proposed method does not rely on additional sensors to those typically used in voltage-source converters, and in any case, those sensors are limited to the point of connection of the power converter. Impedance estimation only using converter-side current sensors is implemented by adding a high-frequency voltage excitation over the fundamental command. A new model approach is proposed for the real-time extraction of system impedance using a complex-valued compact form. Considering the voltage source at that frequency to be unique in the grid, it will be proved that the impedance and, thus, the resulting negative-sequence current, which is used for unbalance compensation, can be estimated. For the zero sequence, a special arrangement of the converter voltage sensors together with a repetitive controller is used.
Molten Steel Level Detection by Temperature Gradients With a Neural Network

Molten steel level is difficult to measure as a result of the high-temperature melt and the covering flux. For the measurement, in our previous work, a novel principle by using the temperature gradient was proposed, and a refractory sensor was inserted into the metallurgical container to sense the temperature gradients of the flux and the molten steel. However, variations of temperature gradient distributions are large when the fluctuation speed of the molten steel level is fast, causing difficulties in the detection of the flux-steel interface. For this issue, a neural network is introduced to learn the features of the temperature gradients around the flux-steel interface, and the convolution of the neural network is developed to detect the flux-steel interface from the temperature gradient distribution. The numerical data obtained from the heat transfer model is used to train and test the detection method. The detection method gives a good performance with the numerical data. But for actual on-site applications, noise in the temperature gradient distributions affects the reliability and accuracy of the detection results. To improve the reliability of the detection method in practice, lifting of the sensor at the wave crest of the flux level is adopted to ensure the large temperature gradients around the flux-steel interface. The statistics show that the detection errors of the flux-steel interface are within ±5 mm with a confidence of 98.3%.