Miracle-dz/UniFAR-FTUs huggingface dataset:
The Inhibition of Aldose Reductase Accelerates Liver Regeneration through Regulating Energy Metabolism

Objectives Our previous study showed that aldose reductase (AR) played key roles in fatty liver ischemia-reperfusion (IR) injury by regulating inflammatory response and energy metabolism. Here, we aim to investigate the role and mechanism of AR in the regeneration of normal and fatty livers after liver surgery. Methods The association of AR expression with liver regeneration was studied in the rat small-for-size liver transplantation model and the mice major hepatectomy and hepatic IR injury model with or without fatty change. The direct role and mechanism of AR in liver regeneration was explored in the AR knockout mouse model. Results Delayed regeneration was detected in fatty liver after liver surgery in both rat and mouse models. Furthermore, the expression of AR was increased in liver after liver surgery, especially in fatty liver. In a functional study, the knockout of AR promoted liver regeneration at day 2 after major hepatectomy and IR injury. Compared to wild-type groups, the expressions of cyclins were increased in normal and fatty livers of AR knockout mice. AR inhibition increased the expressions of PPAR-α and PPAR-γ in both normal liver and fatty liver groups after major hepatectomy and IR injury. In addition, the knockout of AR promoted the expressions of SDHB, AMPK, SIRT1, and PGC1-α and PPAR- Conclusions The knockout of AR promoted the regeneration of normal and fatty livers through regulating energy metabolism. AR may be a new potential therapeutic target to accelerate liver regeneration after surgery.
How to Copy Files

Making logical copies, or clones, of files and directories is critical to many real-world applications and workflows, including backups, virtual machines, and containers. An ideal clone implementation meets the following performance goals: (1) creating the clone has low latency; (2) reads are fast in all versions (i.e., spatial locality is always maintained, even after modifications); (3) writes are fast in all versions; (4) the overall system is space efficient. Implementing a clone operation that realizes all four properties, which we call a nimble clone, is a long-standing open problem. This paper describes nimble clones in BetrFS, an opensource, full-path-indexed, and write-optimized file system. The key observation behind our work is that standard copyon-write heuristics can be too coarse to be space efficient, or too fine-grained to preserve locality. On the other hand, a write-optimized key-value store, as used in BetrFS or an LSMtree, can decouple the logical application of updates from the granularity at which data is physically copied. In our writeoptimized clone implementation, data sharing among clones is only broken when a clone has changed enough to warrant making a copy, a policy we call copy-on-abundant-write. We demonstrate that the algorithmic work needed to batch and amortize the cost of BetrFS clone operations does not erode the performance advantages of baseline BetrFS; BetrFS performance even improves in a few cases. BetrFS cloning is efficient; for example, when using the clone operation for container creation, BetrFS outperforms a simple recursive copy by up to two orders-of-magnitude and outperforms file systems that have specialized LXC backends by 3–4×.
Foreign Exchange Crises, International Currency Exposure and Elections

If democracies are more prone to currency crises, how does this impact incumbents’ electoral fortunes? This paper hypothesizes, (i), that the relation between crises and elections is related to the length and severity of the economic consequences of the currency crises, which in turn, (ii), depends on the degree of mismatch between a country’s trade relations and its international indebtedness. A mismatch index is thus computed for 48 Middle and Low Income Countries over the period 1976-2014, and the evolution of the mismatch over time is analyzed. The relation between the mismatch index and the labor share of GDP and incumbent politicians’ electoral fortunes is then estimated for the 1990-2014 period. The empirical results bring mixed support to the reasoning, as labor share is shown to be related to the mismatch indicator, while the influence of mismatch on the electoral fortunes of the incumbents is, at best, weak.
Background errors in HIRLAM variational data assimilation

The data assimilation system of HIRLAM is based on a variational approach (Gustafsson et al., 2001; Lindskog et al., 2001). The HIRLAM 3-dimensional variational data assimilation (3D-Var) system became operational in 2000 and HIRLAM 4-dimensional variational data assimilation (4D-Var) is planned to become operational in 2007. An incremental formulation (Courtier et al., 1994) is used and the assimilation consists in finding the model state increment vector that minimizes the following cost function problem:
Revision 1 1 Sound wave velocities of Fe 5 Si at high pressure and high temperature conditions : implications to 2 lunar and planetary cores 3

15 Elastic properties of Fe alloys are critical in constraining the compositions of planetary 16 bodies by comparing to the planetary observations. The sound wave velocities and density of an 17 Fe5Si (9 wt% Si) alloy in body centered cubic (bcc) structure were measured by combining an 18 ultrasonic technique with synchrotron X-ray radiography at pressure (P) and temperature (T) 19 conditions of 2.6-7.5 GPa and 300-1173 K, respectively. At room temperature, it is observed that 20
The Impact of an International Competitive Pressure on the French Exports Portfolio

This paper studies the effect of the origin of an international competitive pressure on the change in the composition of the French exports portfolio. Using harmonized trade data from BACI, we build an argumentation in three steps as specified below. Firstly, we decompose the French exports portfolio between an intensive and an extensive margins over the period 1996-2013. Secondly, we split the international competition between a cost competition from developing countries and a technological competition from developed countries in order to provide a signal about which French markets are most exposed to trade with lowor high-income countries. Thirdly, we define a measure of competitive pressure based on the relative market shares, on the imports penetration (Bernard et al., 2006), and on the exports sophistication (Hausmann et al., 2007a). Two main results show: (i) while lowand middle-income countries exert a negative competitive pressure on the French exports portfolio, high-income countries with similar export and productive structures (such as Germany or the United States) do not exert a negative one. (ii) Among lowand middle-income countries, we distinguish a negative competitive pressure on the double scale of products and destinations (from China or Equatorial Guinea for instance) and a negative competitive pressure on the single scale of destinations (from Chile or Hungary for instance).
Deep-Sparse Array Cognitive Radar

In antenna array based radar applications, it is often desirable to choose an optimum subarray from a full array to achieve a balance between hardware cost and resolution. Moreover, in a cognitive radar system, the sparse subarrays are chosen based on the target scenario at that instant. Recently, a deep-learning based antenna selection technique was proposed for a single target scenario. In this paper, we extend this approach to multiple targets and assess the performance of state-of-the-art direction of arrival estimation techniques in conjunction with the proposed antenna selection method. To optimally choose the subarrays based on the target DOAs, we design a convolutional neural network which accepts the array covariance matrix as an input and selects the best sparse subarray that minimizes the error. Once the optimum sparse subarray is obtained, the signals from the selected antennas are used to estimate the DOAs. We provide numerical simulations to validate the performance of the proposed cognitive array selection strategy. We show that the proposed approach outperforms random sparse antenna selection and it leads to a higher DOA estimation accuracy by 6 dB.
A novel image retrieval technique using automatic and interactive segmentation

In this paper, we present a new region-based image retrieval technique based on robust image segmentation. Traditional content-based image retrieval deals with the global description of a query image. We combine the state-of-the-art segmentation algorithms with the traditional approach to narrow the area of interest to a specific region within a query image. In case of automatic segmentation, the algorithm divides a query image automatically and computes Zernike moments for each region. For interactive segmentation, our proposed scheme takes as input a query image and some information regarding the region of interest. The proposed scheme then works by computing the Geodesic-based segmentation of the query image. The segmented image is our region of interest which is then used for computing the Zernike moments. The Euclidean distance is then used to retrieve different relevant images. The experimental results clearly show that the proposed scheme works efficiently and produces excellent results.
Random Normal Contact Laws for Particles with Rough Surface in Discrete Element Modelling

Particles are assumed smooth in classical discrete element modelling, but real particles have random rough surfaces which may influence their mechanical properties. It is necessary therefore to quantitatively improve the conventional discrete element model by taking the surface roughness into consideration. In this work, a new normal contact law is established for particles that have random rough surfaces. The contact law, based on the classic Greenwood and Williamson (GW) model, is derived by both theoretical derivation and numerical calculations. Instead of a complicated integral expression involved in the GW model, the resulting empirical formula of the law retains the closed form and simplicity of the Hertz model, with only one added parameter, , the standard derivation of a surface roughness, and therefore can be readily incorporated into the current discrete element modelling framework.
Composition and hygroscopicity of aerosol particles at Mt. Lu in South China: Implications for acid precipitation

Publisher Rights Statement: NOTICE: this is the author’s version of a work that was accepted for publication in Atmospheric Environment. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Atmospheric Environment, Volume 94, September 2014, Pages 626–636 DOI: 10.1016/j.atmosenv. 2014.06. 003 Checked for repository 30/10/2014
Winning Advantage and Its Applications∗

In most team sports, the whole game can be broken up into a sequence of plays, each of which involves a subset of players and contributes differently to the game’s outcome. We develop an innovative concept—called the winning advantage—to quantify the value of each play, and use it to evaluate each player’s contribution toward winning or losing a game. Winning advantage evaluates all plays on the same scale, so that contributions from all players in different types of plays can be directly compared. An example in baseball is provided to demonstrate the winning advantage and its applications.
ISPRS Archives XXXVIII-8/W3 Workshop Proceedings: Impact of Climate Change on Agriculture 385 STUDY OF INTER-ANNUAL Ku-BAND BACKSCATTER VARIATIONS OF AMERY ICE SHELF, EAST ANTARCTICA

The widespread retreat of glaciers can be considered as response to the climate change. Being the largest retreating glacier-ice shelf system in East Antarctica, the Amery Ice Shelf-Lambert Glacier system plays an important role in contributing to sea level rise as well as surrounding environment and climate. The present study is focused on the investigation of this ice shelf system using mid-month Ku-band scatterometer data from January 2000 to July 2009. The corresponding monthly weather data of Davis Station was obtained from the web site of Australian Antarctic Division. Average backscatter of all the pixels, within the selected sites, was generated and Microwave Polarization Difference Index (MPDI) was computed. It was observed that backscattering coefficients of Hand V-components increase from January 2000 to June 2006. A very prominent dip in the backscatter observed in the month of January is a distinct signature taking place due to physical process of large scale melting of ice/snow surface. The increase in February is attributed to the initiation of the freezing phenomenon. The comparison with monthly air-temperature data shows significant correlation with MPDI. The correlation of the order of 0.99 of annual maximum MPDI with the annual maximum and minimum air-temperatures has been found for the site adjacent to the Lambert Glacier. The change in backscatter behavior from year 2006 is evident as decreasing trend is observed after July 2006 in the time series data. This could be due to cyclic behavior of the system with half cycle of 6-years; however, it needs further investigations
Dispersion characterization of microstructured optical fibers

The chromatic dispersion of optical fibers and its management plays an important role for a variety of applications like ultra short pulse fiber lasers, supercontinuum sources and soliton generation. Microstructured optical fibers (MOFs) form a new class of waveguides whose dispersion characteristics can be changed over a wide range [1, 2]. MOFs usually consist of a hexagonal lattice of air holes running along the fiber axis with a core formed by a missing hole in the center (see Fig. 1). By varying the hole diameters and pitches, the optical properties of such fibers can be designed in a quite simple way.
Interpretable Perceived Topics in Online Customer Reviews for Product Management

Online customer reviews contain useful and important information, because customers tend to praise or criticize certain features or attributes of goods in their reviews. We propose a model that extracts the perceived topics from textual reviews under the restrictions of their interpretability and predictability of product satisfaction as current product evaluation and expectation as future possible demand by supervised learning. The empirical analysis on of food reviews shows that our proposed model performs better than alternative models, and it suggests product managers the necessity of improving some specific attributes to fulfill customer needs.
HotRing: A Hotspot-Aware In-Memory Key-Value Store

In-memory key-value stores (KVSes) are widely used to cache hot data, in order to solve the hotspot issue in diskbased storage or distributed systems. The hotspot issue inside in-memory KVSes is however being overlooked. Due to the recent trend that hotspot issue becomes more serious, the lack of hotspot-awareness in existing KVSes make them poorly performed and unreliable on highly skewed workloads. In this paper, we explore hotspot-aware designs for inmemory index structures in KVSes. We first analyze the potential benefits from ideal hotspot-aware indexes, and discuss challenges (i.e., hotspot shift and concurrent access issues) in effectively leveraging hotspot-awareness. Based on these insights, we propose a novel hotspot-aware KVS, named HotRing1, that is optimized for massively concurrent accesses to a small portion of items. HotRing is based on an orderedring hash index structure, which provides fast access to hot items by moving head pointers closer to them. It also applies a lightweight strategy to detect hotspot shifts at run-time. HotRing comprehensively adopts lock-free structures in its design, for both common operations (i.e., read, update) and HotRing-specific operations (i.e., hotspot shift detection, head pointer movement and ordered-ring rehash), so that massively concurrent requests can better leverage multi-core architectures. The extensive experiments show that our approach is able to achieve 2.58⇥ improvement compared to other inmemory KVSes on highly skewed workloads.
Enhancement of the heuristic optimization based on extended space forests using classifier ensembles

Extended space forests are a matter of common knowledge for ensuring improvements on classification problems. They provide richer feature space and present better performance than the original feature space-based forests. Most of the contemporary studies employs original features as well as various combinations of them as input vectors for extended space forest approach. In this study, we seek to boost the performance of classifier ensembles by integrating them with heuristic optimization-based features. The contributions of this paper are fivefold. First, richer feature space is developed by using random combinations of input vectors and features picked out with ant colony optimization method which have high importance and not have been associated before. Second, we propose widely used classification algorithm which is utilized baseline classifier. Third, three ensemble strategies, namely bagging, random subspace, and random forests are proposed to ensure diversity. Fourth, a wide range of comparative experiments are conducted on widely used biomedicine datasets gathered from the University of California Irvine (UCI) machine learning repository to contribute to the advancement of proposed study. Finally, extended space forest approach with the proposed technique turns out remarkable experimental results compared to the original version and various extended versions of recent state-of-art studies
Rex: Preventing Bugs and Misconfiguration in Large Services Using Correlated Change Analysis

Large services experience extremely frequent changes to code and configuration. In many cases, these changes are correlated across files. For example, an engineer introduces a new feature following which they also change a configuration file to enable the feature only on a small number of experimental machines. This example captures only one of numerous types of correlations that emerge organically in large services. Unfortunately, in almost all such cases, no documentation or specification guides engineers on how to make correlated changes and they often miss making them. Such misses can be vastly disruptive to the service. We have designed and deployed Rex, a tool that, using a combination of machine-learning and program analysis, learns change-rules that capture such correlations. When an engineer changes only a subset of files in a change-rule, Rex suggests additional changes to the engineer based on the change-rule. Rex has been deployed for 14 months on 360 repositories within Microsoft that hold code and configuration for services such as Office 365 and Azure. Rex has so far positively affected 4926 changes without which, at the very least, code-quality would have degraded and, in some cases, the service would have been severely disrupted.
Ecological Momentary Intervention via Text Message Reminders for Collegiate Female Athletes at Risk for the Female Athlete Triad

Female athletes are at an increased risk of developing the female athlete triad, which is associated with negative consequences to the performance and health of the athlete. An intervention for this population must be brief and easily incorporated into their daily schedule. Cell phones offer a viable option for connecting with female athletes who are at risk for the female athlete triad. The purpose of this study was to assess the utility of using text message reminders as a way to encourage female athletes at risk for the female athlete triad to increase their energy intake. Female athletes viewed a brief educational video about the signs and risks of the female athlete triad. Change in nutrition was examined by assessing knowledge from a questionnaire before and after receiving brief nutrition education related to the female athlete triad. Athletes selected times to receive an ecological momentary intervention via text message reminder for a 2-week period. Energy intake was assessed before and during the intervention using a 3-day dietary recall. The intervention did not significantly increase energy intake. Text messages may be a beneficial tool for reminding busy female athletes to eat in an effort to increase energy intake and decrease risk for the female athlete triad. This method presents challenges and needs to be developed further based on suggestion from athletes to be successful.
Qualitative Analysis of Interpersonal Oral Health Communication between Providers and Caregivers in the Medical Home: A Pilot Study

Using qualitative analysis, 15 transcripts of caregiver-provider interactions collected in 2008 were assessed during visits for 0-42 month old children. Preventive messages by five providers participating in a Medicaid preventive oral health initiative in North Carolina were evaluated. The American Academy of Pediatrics (AAP) 2008 oral health guidelines and American Dental Association’s communication domains were used as standards to examine information and communication styles.
Contextualizing Statistical Suppression Within Pretest-Posttest Designs

Statistical suppression occurs when adjusting for some third variable enhances or substantially modifies the association between an initial predictor and an outcome. Although many methodologists have discussed this phenomenon, very little work has examined suppression in longitudinal regression models such as the pretest-posttest design. This research addressed this gap with two separate studies. Study One was a literature review that reviewed 80 articles from a variety of fields within psychology. Study Twowas an analysis of a large longitudinal clinical dataset via 925 statistical models. Both studies revealed consistent results: in approximately 20% of instances, suppression effects were observed and were attributable to the inclusion of a pretest measure. Results underscore that controlling for pretest measures when assessing change may be of value, as this can help clarify the associations between predictors and posttest outcomes.