Miracle-dz/UniFAR-FTUs huggingface dataset:
Hybrid Redundancy Fault Tolerant Codec in Distributed Storage System

Reed-Solomon erasure codes is the most widely used multi-binary codes which could correct the random errors and unexpected errors. Its characteristics include: It has the strongest capability to correct random errors and burst errors under the same coding redundancy and larger coding gain under the same coding efficiency, Secondly, it is close to the limit in the case of short codes and medium codes and it can greatly improve the performance of the error correction when it is combined with the data interleaving technology, Finally, it has strict algebraic structure which is shown as the linear cyclic polynomials. This paper develops a new merge approach of nonlinear self-repairing code and Reed-Solomon codes. When the network condition is good, Reed-Solomon erasure codes is adopted, and in poor network conditions, nonlinear self-repairing codes is used. The efficiency of maintaining redundant data is improved by a few of damaged information. The experiments show that this method can reduce the amount of network transmission data, at the same time it can shorten the amount data of recovery operation and reconstruction time.
System design and control algorithm for a 150W portable fuel cell power pack

Fuel cell has a lot of advantages like zero emission, high efficiency, little noise, and extremely low vibration. So, it is considered as a suitable alternative source for the portable power supply. However, it needs to be made up for the weak points such as high cost and slow dynamic response. As a representative useful solution to remedy fuel cell's shortcomings, battery is being utilized in various hybrid systems. In this paper, five fuel cell-battery hybrid system structures are analyzed in order to find the optimal structure for a 150W portable fuel cell power pack. Then, each main part is designed to achieve compact size, simple control, high efficiency, and low cost. Also, this paper suggests an automatic mode change algorithm considering the state of fuel cell, battery, and load. Experimental results show stable mode changes and the performance of a 150W prototype.
Peripheral Inflammation Sensitizes P2X Receptor-Mediated Responses in Rat Dorsal Root Ganglion Neurons

ATP-gated P2X receptors in nociceptive sensory neurons participate in transmission of pain signals from the periphery to the spinal cord. To determine the role of P2X receptors under injurious conditions, we examined ATP-evoked responses in dorsal root ganglion (DRG) neurons isolated from rats with peripheral inflammation, induced by injections of complete Freund's adjuvant (CFA) into the hindpaw. Application of ATP induced both fast- and slow-inactivating currents in control and inflamed neurons. CFA treatment had no effect on the affinity of ATP for its receptors or receptor phenotypes. On the other hand, inflammation caused a twofold to threefold increase in both ATP-activated currents, altered the voltage dependence of P2X receptors, and enhanced the expression of P2X2 and P2X3 receptors. The increase in ATP responses gave rise to large depolarizations that exceeded the threshold of action potentials in inflamed DRG neurons. Thus, P2X receptor upregulation could account for neuronal hypersensitivity and contribute to abnormal pain responses associated with inflammatory injuries. These results suggest that P2X receptors are useful targets for inflammatory pain therapy.
In storage process, the next generation of storage system

In conventional computer systems, software relies on the CPU to handle the process applications and assign computation tasks to heterogeneous accelerators such as GPU, TPU and FPGA. It requires the CPU to fetch data out of the storage device and move the data to the heterogeneous accelerators. After the accelerators complete computation tasks, the results are flushed to the main memory of the host server for software applications. In this architecture, the heterogeneous accelerators are located far away from the storage device. There are data movements on the system bus (NVM-express/PCI-express), which requires a lot of transmission time and bus bandwidth. When data move back and forth on the storage data bus, it decreases the overall performance of the storage system. This dissertation presents the in-storage processing (ISP) architecture that offloads the computation tasks into the storage device. The proposed ISP architecture eliminates the back and forth data movements on the system bus. It only delivers the computation results to the host memory, saving the storage bus bandwidth. The ISP uses FPGA as a data processing unit to process computation tasks in real-time. Due to the parallel and pipeline architecture of the FPGA implementation, the ISP architecture processes data in short latency, and it has minimal effects on the data flow of the original storage system. In this dissertation, we proposed four ISP applications. The first ISP application is the Hardware Object Deserialization in SSD (HODS), which is designed to tailor to the high-speed data conversion inside the storage device. The HODS shows visible differences compared to software object deserialization regarding application execution time while running Matlab, 3D modeling, and other scientific computations. The second ISP application is called the CISC: Coordinating Intelligent SSD and CPU. It speeds up the Minimum Spanning Tree (MST) applications in graph processing. The CISC coordinates the computing power inside SSD storage with the host CPU cores. It outperforms the traditional software MST by 35%. The third application speeds up the data fingerprint computation inside the storage device. By pipelining multi data computation units, the proposed architecture processes the Rabin fingerprint computation in wire speed of the storage data bus transmission. The scheme is extensible to other types of fingerprint/CRC computations and readily applicable to primary storage and caches in hybrid storage systems. The fourth application is data deduplication. It eliminates duplicate date inside the storage and provides at least six times speedup in throughput over software. The proposed ISP applications in this dissertation prove the concept of computational storage. In the future, more compute-intensive tasks can be deployed into the storage device instead of processing in the CPU or heterogeneous accelerators (GPU, TPU/FPGA). The ISP is extensible to the primary storage and applicable for the next generation of the storage system.
Protective Effect of Hesperidin, a Citrus Bioflavonoid, on Diabetes-Induced Brain Damage in Rats

Among t he num erous co-adjuvant therapies, which co uld influence the i ncidence and progression of diabetic co mplications, flavonoids, naturally occurring ant ioxidants, are currently being tested in several clinical and e xperimental trials. However, the protective efficiency of these compounds against complications in diabetic rat brain have rarely been investigated. 2- The aim of the present study is to e valuate the protective effect of hesperidin against diabetes-induced n europathy in rat. 3- STZ- induced diabetes showed a significant (p < 0.05) increase in fasting plasma glucose, glycated Hb a nd fructosamine levels. The content of DNA; RNA and GSH significantly (p < 0.05) decreased whereas the content of lipid peroxi de, as malondialdehyde ( MDA), and ni tric oxi de ( NO) significantly increased i n r at brain. The activities o f aldose re ductase (AR); sorbitol dehydrogenase (S D) an d cytochrome o xidase significantly increased whereas the act ivities of the ant ioxidant enzymes: glutathione reduc tase (GR); glutathione peroxidase (GPX); glutathione S-transferase (GST) and superoxide dismutase (SOD) significantly decreased in diabetic rat b rain. 4- O ral a dministration of he speridin ( 200 mg/kg b wt) to diabetic rats f or 35 days resulted in significant (p < 0.05) improvement in the parameters studied. A decrease of p lasma glucose, glycated Hb, brain N O levels and the act ivities of brain A R and cytochrome oxidase were observed along with the increase in brain D NA level an d GST activity. Additionally, hesperidin ad ministration pro duced a res toration of brain M DA; GSH and RNA levels and the activities o f brain SD; GR; GPX and SOD. 5- The current results sugg est that hesperidin e xerts, efficiently, an attenuating effect on the progression of hyperglycemia a nd al so on some di abetes-induced complications in rat b rain.
Knowledge integration processes within the context of enterprise resources planning (ERP) systems implementation

The empirical findings from an organization, which adopted and implemented ERP, are presented. The focus of this empirical research was to understand the nature and processes of knowledge integration that occur during ERP implementation. While one objective of this paper then is to develop a conceptual framework of knowledge integration, a second objective is to focus on the methodology and demonstrate the various steps involved in adopting a grounded theory approach. In particular this paper takes the reader through the various stages of data analysis, moving from open coding, through axial coding through to selective coding, which leads to the development of the theoretical framework. The theoretical framework suggests that generating ERP awareness prior to adopting the technology, sustaining support from various hierarchical levels throughout the implementation process, and reinforcing the process innovation through the Knowledge Integration Processes within The Context of Enterprise Resources Planning (ERP) Systems Implementation [Case Study] 1215 introduction of new technology are all vital to ensuring the knowledge integration that is necessary for ERP implementation.
A Systematic Mapping Study on the Current Status of Total Cost of Ownership for Information Systems

Context: More and more industries and businesses are being run on software, making information systems a pivotal component of our lives. Because of globalization and harsh competition, strategic cost management has become essential to keep or gain competitive advantage. These two trends make the investigation of Total Cost of Ownership (TCO) for information systems crucial. Objective: We aim to identify how and to what extent TCO concept is used for information systems. Method: We used systematic mapping study (SMS) to identify the use of TCO in information systems context. We defined 7 research questions (RQs). To answer these RQs, we selected 75 relevant publications by applying our inclusion and exclusion criteria. Results: An increased interest in TCO for information systems is observed over the years. We classified these publications per research type and main motivation of dealing with TCO. The results show that 76% of the selected publications (opinion and solution proposal) lack validation and evaluation. The main motivation behind the 72% of the publications is reduction of TCO. According to the results, essential means of reducing TCO are cloud computing, SaaS model, and multi-tenancy. TCO calculations are also generally made to compare cloud-based infrastructures with in-house infrastructures and SaaS model with on-premise software. TCO is an important criterion in making investment decisions for information systems such as ERP, CRM. Conclusions: To the best of our knowledge, this study is the first SMS on TCO for information systems. We observed limited collaboration between academia and industry. More collaboration would enable to gather data for validation and evaluation. Moreover, methods and frameworks for calculating TCO for information systems are needed. Benefit realization exercises will complement TCO analysis to assess success of investments in information systems.
Sherlock: A Deep Learning Approach to Semantic Data Type Detection

Correctly detecting the semantic type of data columns is crucial for data science tasks such as automated data cleaning, schema matching, and data discovery. Existing data preparation and analysis systems rely on dictionary lookups and regular expression matching to detect semantic types. However, these matching-based approaches often are not robust to dirty data and only detect a limited number of types. We introduce Sherlock, a multi-input deep neural network for detecting semantic types. We train Sherlock on $686,765$ data columns retrieved from the VizNet corpus by matching $78$ semantic types from DBpedia to column headers. We characterize each matched column with $1,588$ features describing the statistical properties, character distributions, word embeddings, and paragraph vectors of column values. Sherlock achieves a support-weighted F$_1$ score of $0.89$, exceeding that of machine learning baselines, dictionary and regular expression benchmarks, and the consensus of crowdsourced annotations.
An Experimental Investigation of the Hydraulic and Durability Properties of Cement Treated Permeable Basecourses ( CTPBs )

An experimental program was conducted to determine the hydraulic and durability properties of cement treated permeable bases using three different aggregate types, two gradations types and three targeted percent air voids content of 15, 25, and 35. It was observed that the CTPBs does have appreciable coefficient of hydraulic conductivity but that both the freeze-thaw and unconfined compressive test does not give any meaningful indication of the durability of CTPBs since the differences in UCS values between the control and conditioned samples can be attributed to differences in percent air voids content rather than due to the effect of freeze-thaw environmental procedure they were subjected to.
THE SPITZER c2d SURVEY OF NEARBY DENSE CORES. VII. CHEMISTRY AND DYNAMICS IN L43

We present results from the Spitzer Space Telescope and molecular line observations of nine species toward the dark cloud L43. The Spitzer images and molecular line maps suggest that it has a starless core and a Class I protostar evolving in the same environment. CO depletion is seen in both sources, and DCO+ lines are stronger toward the starless core. With a goal of testing the chemical characteristics from pre- to protostellar stages, we adopt an evolutionary chemical model to calculate the molecular abundances and compare with our observations. Among the different model parameters we tested, the best-fit model suggests a longer total timescale at the pre-protostellar stage, but with faster evolution at the later steps with higher densities.
Bargaining and market power in a GIS-based hedonic pricing model of the agricultural land market

Agricultural land markets differ greatly from the textbook-case of perfect competition. This is why standard hedonic pricing techniques should be revised before applying this technique to this market. The objective of this paper is to determine (a) the deviation from the competitive market price of agricultural land in the Netherlands due to market power and the existence of an excess surplus and (b) the effect of bargaining power on the division of excess surplus between the eventual seller and the buyer in the market for agricultural land.
Contextual semantics for sentiment analysis of Twitter Journal Item

Sentiment analysis on Twitter has attracted much attention recently due to its wide applications in both, commercial and public sectors. In this paper we present SentiCircles, a lexicon-based approach for sentiment analysis on Twitter. Different from typical lexicon-based approaches, which offer a fixed and static prior sentiment polarities of words regardless of their context, SentiCircles takes into account the co-occurrence patterns of words in different contexts in tweets to capture their semantics and update their pre-assigned strength and polarity in sentiment lexicons accordingly. Our approach allows for the detection of sentiment at both entity-level and tweet-level. We evaluate our proposed approach on three Twitter datasets using three different sentiment lexicons to derive word prior sentiments. Results show that our approach significantly outperforms the baselines in accuracy and F-measure for entity-level subjectivity (neutral vs. polar) and polarity (positive vs. negative) detections. For tweet-level sentiment detection, our approach performs better than the state-of-the-art SentiStrength by 4-5% in accuracy in two datasets, but falls marginally behind by 1% in F-measure in the third dataset.
Effect of Coriandrum sativum hydroalcoholic extract and its essential oil on acetic acid- induced acute colitis in rats

Objective: The aim of this study was to determine the protective effects of Coriandrum sativum on acetic acid-inducedcolitis in rats. C. sativum (Coriander) has long been used in Iranian traditional medicine and its use as an anti-inflammatory agent is still common in some herbal formulations. Materials and Methods: Colitis was induced by intra-rectal administration of 2ml acetic acid 4% in fasted male Wistar rats. Treatment was carried out using three increasing doses of extract (250, 500, 1000 mg/kg) and essential oil (0.25, 0.5, 1 ml/kg) of coriander started 2 h before colitis induction and continued for a five-day period. Colon biopsies were taken for weighting, macroscopic scoring of injured tissue, histopathological examination and measuring myeloperoxidase (MPO) activity. Results: Colon weight was decreased in the groups treated with extract (500 and 1000 mg/kg) and essential oil (0.5 ml/kg) compared to the control group. Regarding MPO levels, ulcer severity and area as well as the total colitis index, same results indicating meaningful alleviation of colitis was achieved after treatment with oral extract and essential oil. Conclusion: Since the present experiment was made by oral fractions of coriander thus the resulting effects could be due to both the absorption of the active ingredients and/or the effect of non-absorbable materials on colitis after reaching the colon. In this regard, we propose more toxicological and clinical experiments to warranty its beneficial application in human inflammatory bowel diseases.
A translation model for languages of accessing countries

The paper proposes a model for translation between syntactically similar languages of acceding countries. This model is based on the presupposition that the translation of related languages should exploit the relatedness by using as simple methods and tools as possible. In the first part the paper discusses the properties of some “new” languages, the second part describes a simple translation model which has already been tested on several pairs of syntactically similar languages.
Personal Health Record feeding via Medical Forums

The huge amount of textual data uploaded in virtual social networks can be effectively exploited to provide (possibly accidental) information in many scenarios. In healthcare discussion forums, users interact to educate themselves about treatments, symptoms, diseases, therapies, usually providing personal health-related information when posting questions or answers. Medical Forum data can be used for feeding Personal Health Record (PHR), the part of EHR where the person can directly manage his personal medical-related information. In this work, we propose an agent-based architecture to first extract textual data from html pages in a set of medical oriented Italian social forum. Then, text mining techniques allow to discover health related information coming from the same user in different threads and/or different forums, finally feeding the PHR with such information. The architecture is presented together with a first implementation where 10 medical discussion forums are analyzed, showing promising results when extracting medical information from a subset of 3 over 10 forums.
Does the Laser-Microtextured Short Implant Collar Design Reduce Marginal Bone Loss in Comparison with a Machined Collar?

Purpose. To compare marginal bone loss between subgingivally placed short-collar implants with machined collars and those with machined and laser-microtextured collars. Materials and Methods. The investigators used a retrospective study design and included patients who needed missing posterior teeth replaced with implants. Short-collar implants with identical geometries were divided into two groups: an M group, machined collar; and an L group, machined and laser-microtextured collar. Implants were evaluated according to marginal bone loss, implant success, and probing depth (PD) at 3 years of follow-up. Results. Sixty-two patients received 103 implants (56 in the M group and 47 in the L group). The cumulative survival rate was 100%. All implants showed clinically acceptable marginal bone loss, although bone resorption was lower in the L group (0.49 mm) than in the M group (1.38 mm) at 3 years (p < 0.01). A significantly shallower PD was found for the implants in the L group during follow-up (p < 0.01). Conclusions. Our results suggest predictable outcomes with regard to bone loss for both groups; however, bone resorption was less in the L group than in the M group before and after loading. The laser-microtextured collar implant may provide a shallower PD than the machined collar implant.
Control of liquid slosh in an industrial packaging machine

Linear movement of open containers containing liquid is considered. The design is based on a simple linearized slosh model. An open-loop acceleration trajectory is calculated using optimal control techniques. The calculated acceleration profiles are evaluated using experiments with a laser-based sensor and recordings by a video camera. The performance is better than previous ad-hoc controllers.
Papers in Evolutionary Economic Geography # 08 . 04 From Average to the Frontier : A Nonparametric Frontier Approach to the Analysis of Externalities and Regional Innovation Performance :

Although a rich literature has emerged analyzing the impact of localization, urbanization, and Jacobs externalities on regional innovativeness, the findings are still contradictory. Traditional studies differ mainly in the employed data but rely on similar empirical approaches. This paper argues in favor of using in this context production frontier approaches instead of the commonly employed production function approaches. In addition, a nonparametric frontier approach is used to empirically examine the influence of the externalities on regions' innovativeness. For four different industries positive effect of localization and urbanization externalities are found. In contrast, with the exception of the transport equipment industry, Jacobs externalities seem to be of minor importance. I greatly thank Thomas Brenner for helpful comments and suggestions, and Cinzia Daraio for her assistance in the implementation of the conditional order-m analysis.
Supplement to “ Inference for the Number of Topics in the Latent Dirichlet Allocation Model via Bayesian Mixture Modelling ”

This document consists of three parts. The first derives an expression for the conditional distributions needed to run the Collapsed Gibbs Sampler of Griffiths and Steyvers (2004). The second part provides a version of Theorem 3 of “Inference for the Number of Topics in the Latent Dirichlet Allocation Model via Bayesian Mixture Modelling” without the condition that T is finite. The third part provides additional simulations to compare the PMMH algorithm with other methods for choosing the number of topics. Throughout, equations, conditions, etc. refer to the main paper; also, notation is as in the main paper. Derivation of the Conditional Distribution of zdi Given z(−di) and w In order to obtain p(zdit = 1 | z(−di),w), we will obtain, up to a constant of proportionality, an expression for p ( zdit = 1,β,θ ∣∣ z(−di),w), from which we will integrate out β and θ. We have p ( zdit = 1,β,θ ∣∣ z(−di),w) = p(zdit = 1,β,θ ∣∣wdi, z(−di),w(−di)) ∝ p ( wdi, zdit = 1,β,θ ∣∣ z(−di),w(−di)) = p ( wdi ∣∣ zdit = 1,β,θ, z(−di),w(−di)) × p ( zdit = 1 ∣∣β,θ, z(−di),w(−di))p(β,θ ∣∣ z(−di),w(−di)). (1)