Miracle-dz/UniFAR-FTUs huggingface dataset:
Emerging Energy-Efficient Technologies for Hybrid Electric Vehicles

With ever-increasing oil prices, there is fast growing interest in hybrid electric vehicles (HEVs) globally. Thus, it is a pressing need for researchers to develop emerging energy-efficient devices for various kinds of HEVs, including the micro hybrids, mild hybrids, and full hybrids. In this paper, three key emerging energy-efficient technologies are identified and discussed: 1) the thermoelectric waste-heat recovery and temperature control systems for all hybrids, especially micro hybrids; 2) the integrated-starter-generator for mild hybrids; and 3) the electronic continuously variable transmission propulsion for full hybrids
On the Complexity of Evaluating Order Queries with the Crowd

One of the foremost challenges for information technology over the last few years has been to explore, understand, and extract useful information from large amounts of data. Some particular tasks such as annotating data or matching entities have been outsourced to human workers for many years. But the last few years have seen the rise of a new research field called crowdsourcing that aims at delegating a wide range of tasks to human workers, building formal frameworks, and improving the efficiency of these processes. The database community has thus been suggesting algorithms to process traditional data manipulation operators with the crowd, such as joins or filtering. This is even more useful when comparing the underlying “tuples” is a subjective decision – e.g., when they are photos, text, or simply noisy data with different variations and interpretations – and can presumably be done better and faster by humans than by machines. The problems considered in this article aim to retrieve a subset of preferred items from a set of items by delegating pairwise comparison operations to the crowd. The most obvious example is finding the maximum of a set of items (called max). We also consider two natural generalizations of the max problem:
Flow-Diversion Panacea or Poison?

Endovascular therapy is now the treatment of choice for intracranial aneurysms (IAs) for its efficacy and safety profile. The use of flow diversion (FD) has recently expanded to cover many types of IAs in various locations. Some institutions even attempt FD as first line treatment for unruptured IAs. The most widely used devices are the pipeline embolization device (PED), the SILK flow diverter (SFD), the flow redirection endoluminal device (FRED), and Surpass. Many questions were raised regarding the long-term complications, the optimal regimen of dual antiplatelet therapy, and the durability of treatment effect. We reviewed the literature to address these questions as well as other concerns on FD when treating IAs.
Efficiency in Islamic Banking: An Empirical Analysis of Eighteen Banks

Are Islamic banks stable and efficient? This paper addresses this question. Technical, pure technical, and scale efficiency measures are calculated by utilizing non-parametric technique, Data Envelopment Analysis. Several conclusions emerge. First, the overall efficiency results suggest that inefficiency across 18 Islamic banks is small at just over 10 percent, which is quite low compared to many conventional counterparts. Islamic banks in the sample suffered from the global crisis in 1998-1999 but performed very well after the difficult periods. The findings indicate that there are diseconomies of scale for small-to-medium Islamic banks which suggests that mergers should be encouraged.
A Generic Digital Forensic Investigation Framework for Internet of Things (IoT)

Although numerous researches have been carried on Internet of Things (IoT), little focus has been employed on how Digital Forensics (DF) techniques can be used to conduct Digital Forensic Investigations (DFIs) in IoT-based infrastructures. Up to this point, IoT has not fully adapted to DF techniques owing to the fact that the current DF tools and procedures are not able to meet the heterogeneity and distributed nature of the IoT infrastructures. As a result, gathering, examining and analysing potential evidence from IoT environments that may be used as admissible evidence in a court of law poses a challenge to DF investigators and Law Enforcement Agencies (LEA). Therefore, the problem addressed is that, at the time of writing this paper, there currently exist no accepted DF frameworks that can help to conduct DFIs in an IoT-based environment. Based on this premise, the authors have proposed a generic Digital Forensic Investigation Framework for IoT (DFIF-IoT) that is able to support future IoT investigative capabilities with a degree of certainty. The proposed framework includes the following advantage: It complies with the ISO/IEC 27043: 2015 which is an international standard for information technology, security techniques, incident investigation principles, and process. It is, therefore, the authors' opinion that if the proposed framework is successfully incorporated in future DF tool development, it will facilitate effective digital forensic crime investigation for IoT infrastructures.
A robust multi-objective compatible optimization control algorithm for traffic signal control

Conventional methods used for solving traffic signal control problems used the mean value of traffic flow as the input of traffic system which may differ greatly from the real circumstance. In this paper, we propose a modified robust multi-objective compatible optimization control(RMOOC) algorithm which adopting interval or region control objectives instead of point control objectives, and a min-max robust optimization model is proposed to solve the traffic signal control problem, Simulation results show that better performance may be obtained without loss of too much optimality when the variation of traffic flow is in a limited region, and the proposed robust multi-objective compatible optimization control algorithm is effective in coordinating network control and decreasing delay.
FAST: near real-time data analytics for the cloud

Existing cloud storage systems have largely failed to offer an adequate capability for real-time data analytics. Since the true value of data heavily depends on how efficiently data analytics can be carried out on the data in (near-) real-time, large fractions of data unfortunately end up with their values being lost or significantly reduced due to the staleness of data. To address this problem, we propose a near real-time and cost-effective data analytics methodology, called FAST, in the cloud. FAST explores and exploits the semantic correlation property within and among datasets via correlation-aware hashing and manageable flat-structured addressing to significantly reduce the processing latency, while incurring acceptably small loss of accuracy. FAST is demonstrated to be a useful tool in supporting near real-time processing of real-world cloud applications.
Mobilization of Endothelial Progenitor Cells in Patients With Acute Myocardial Infarction

Background—Endothelial progenitor cells (EPCs) circulate in adult peripheral blood (PB) and contribute to neovascularization. However, little is known regarding whether EPCs and their putative precursor, CD34-positive mononuclear cells (MNCCD34+), are mobilized into PB in acute ischemic events in humans. Methods and Results—Flow cytometry revealed that circulating MNCCD34+ counts significantly increased in patients with acute myocardial infarction (n=16), peaking on day 7 after onset, whereas they were unchanged in control subjects (n=8) who had no evidence of cardiac ischemia. During culture, PB-MNCs formed multiple cell clusters, and EPC-like attaching cells with endothelial cell lineage markers (CD31, vascular endothelial cadherin, and kinase insert domain receptor) sprouted from clusters. In patients with acute myocardial infarction, more cell clusters and EPCs developed from cultured PB-MNCs obtained on day 7 than those on day 1. Plasma levels of vascular endothelial growth factor significantly increased, peaking on day 7, and they positively correlated with circulating MNCCD34+ counts (r =0.35, P =0.01). Conclusions—This is the first clinical demonstration showing that lineage-committed EPCs and MNCCD34+, their putative precursors, are mobilized during an acute ischemic event in humans.
Evaluation of a new device for rapidly separating serum or plasma from blood.

I have evaluated the suitability of a new device for the rapid and efficient separation of cell-free serum or plasma from whole blood. Thirty-four clinical chemistry procedures were used in the analysis of 750 paired blood samples. One sample from each pair was processed by double centrifugation, the other by single centrifugation with the new device. Differences between means for the paired samples were evaluated by Student's t -test. At a significance level of P ≤ 0.05, only uric acid, lactate dehydrogenase, lactate dehydrogenase isoenzyme 2, and CO2 show a statistically significant difference between the two separation procedures. These differences do not appear to be of sufficient magnitude to preclude use of the device in the clinical chemistry laboratory.
Prevalence of fimA genotypes of Porphyromonas gingivalis and other periodontal bacteria in a Spanish population with chronic periodontitis

Objectives: The aim of this study was to determine the prevalence of the different fimA genotypes of Porphyromonas gingivalis in adult Spanish patients with chronic periodontitis, patients with gingivitis and periodontally healthy subjects, and the relationship between these genotypes and other periodontopathogenic bacteria. Study design: Samples of subgingival plaque were taken from 86 patients (33 with chronic periodontitis, 16 with gingivitis, and 37 periodontally healthy) in the course of a full periodontal examination. PCR was employed to determine the presence of the 6 fimA genotypes of Porphyromonas gingivalis (I-V and Ib) and of Aggregatibacter actinomycetemcomitans, Tannerella forsythia and Treponema denticola. Results: Porphyromonas gingivalis fimA genotypes II and Ib were present in significantly higher percentages in periodontal patients (39.4% and 12.1% respectively) than in healthy or gingivitis subjects. The prevalence of Tannerella forsythia, Treponema denticola, and Porphyromonas gingivalis fimA genotype IV was significantly higher in the group that presented bleeding greater than 30%. A positive correlation was found between Porphyromonas gingivalis fimA genotype IV and Treponema denticola. Conclusions: A strong association between Porphyromonas gingivalis fimA genotypes II and Ib and chronic periodontitis exists in the Spanish population. The most prevalent genotype in periodontal patients is II. Key words:Periodontitis, Porphyromonas gingivalis, fimA genotype, periodontal bacteria, polymerase chain reaction.
Information Technology and Financial Services Competition

We analyze how two dimensions of technological progress affect competition in financial services. While better technology may result in improved information processing, it might also lead to low-cost or even free access to information through, for example, informational spillovers. In the context of credit screening, we show that better access to information decreases interest rates and the returns from screening. However, an improved ability to process information increases interest rates and bank profits. Hence predictions regarding financial claims' pricing hinge on the overall effect ascribed to technological progress. Our results generalize to other financial markets where informational asymmetries drive profitability, such as insurance and securities markets. Copyright 2003, Oxford University Press.
Searching and Finding Strikes in the New York Times

The huge digitization step that archives, publishers, and libraries are currently undertaking enables access to a vast amount of information for historians. Yet, this does not necessarily make life easier for historians, as the main problem remains how to find relevant sources in this sea of information. We present a case study demonstrating how automatic text analysis can aid historians in finding relevant primary sources. We focus on strike events in the 1980s in the USA. In earlier work on strikes, researchers did not have at their disposal a full and comprehensive list of major strike events. Existing databases of this kind (e.g [19, 22]) are the result of intensive manual work and took years to build. Natural language processing (NLP) tools allow for faster assembly of datasets of this kind on the basis of collections of free texts that contain the information that should be in the database. We aim to construct a database of events using a digital newspaper archive and unsupervised NLP methods such as Latent Dirichlet Allocation (LDA) and clustering techniques to group together newspaper articles that describe the same strike. We study the effect of different feature representations, such as simple bagof-words features, named entities, and time stamp information. We evaluate our results on a manually labeled sample of news articles describing a small set of strikes.
Factors Affecting the Water Holding Capacity of Red Meat Products: A Review of Recent Research Advances

The water holding capacity of meat products is a very important quality attribute which has an influence on product yield, which in turn has economic implications, but is also important in terms of eating quality. A number of pre-and post-mortem factors influence the water holding capacity (WHC) of meat. During the growth and development of meat animals, genotype and animal diet are important due to their direct influence on muscle characteristics. In the immediate pre-slaughter period, stresses on the animal such as fasting, and different stunning methods are likely to influence meat WHC. In the post-slaughter period chilling, ageing, injecting non-meat ingredients, as well as tumbling have important influences on WHC. Furthermore, cooking and cooling procedures for the final meat products can also affect the WHC of the product, in particular the cooking and the cooling methods, the heating and the cooling rate, the cooking temperature, and the endpoint temperature. This paper provides an overview of recent research on important intrinsic and extrinsic factors that affect the WHC of beef, pork, and lamb products, and reveals explanations and solutions to some of the critical problems related to WHC and product quality.
A Survey on Privacy Preserving Data Mining Techniques

The process of extracting interesting patterns or knowledge from a huge amount of data is known as Data Mining. Now a day's information like PAN No data collection is ubiquitous, and every transaction is recorded somewhere. The resulting data sets can consist of terabytes or even pet bytes of data, so efficiency and scalability is the primary consideration of most data mining algorithms. Increasing data collection, along with the influx of analysis tools capable of handling huge volumes of information, has led to privacy concerns. Protecting private data is an important concern for society, several laws now require explicit consent prior to analysis of an individual's data, but its importance is not limited to individuals: corporations might also need to protect their information's privacy, even though sharing it for analysis could benefit the company. Clearly, the trade-off between sharing information for analysis and keeping it secret to preserve corporate trade secrets and customer privacy is a growing challenge. In recent years, with the explosive development in Internet, data storage and data processing technologies, privacy preservation has been one of the greater concerns in data mining. A variety of methods and approaches have been introduced and developed for privacy preserving data mining. This paper provides a basic survey of different privacy preserving data mining methods and analyses the representative techniques for privacy preserving data mining, and points out their Pros and Cons of techniques. Finally present problems and directions for future scope were discussed.
Texture Recognition by Fusion of Optimized Moment Based and Gabor Energy Features

Use of a single technique for the extraction of diverse features in a texture image usually shows limited capabilities for texture description. Texture features extracted using different techniques can be merged in an attempt to enhance their texture description capability. This paper explores the fusion of optimized moment and Gabor energy texture features. The Fisher linear discriminant analysis is used to show that the discrimination effectiveness of the features increases as a result of the proposed fusion. Preliminary simulation results have been validated experimentally through the classification and segmentation of real texture images. Keywords—Moment based texture features, Gabor energy features, Texture classification, Fisher's criterion Texture Segmentation, Fusion
Distributed Optimization in Multi-Agent Systems: Game Theory Based Sensor Coverage and Continuous-Time Convex Optimization

Author(s): Rahili, Salar | Advisor(s): Ren, Wei | Abstract: A multi-agent system is defined as a collection of autonomous agents which are able to interact with each other or with their environments to accomplish a task. The distributed control of MSNs is the main focus of recent research in this area. Examples of cooperative tasks include mobile sensor networks, distributed optimization, automated parallel delivery of payloads, region following formation control and coordinated path planning. One of the most important and well known task in multi-agent system is optimizing a cost function ( utility function) in a distributed manner. In this task, the action of each agent affects the team cost function, which is unknown to individual agents. Here our goal is to design a control algorithm for individual selfish agents to optimize the team cost function. In this dissertation, two optimization problems are investigated, where two different methods of game theory and convex optimization are employed to solve these problems.In our first problem, the coverage problem in an unknown environment by a Mobile Sensor Network (MSN) is studied. An algorithm based on game theory is proposed, where a collection of distributed agents communicate with local neighbors and use their local information to make decisions.In our second problem, a time-varying distributed convex optimization problem is studied for continuous-time multi-agent systems.The objective is to minimize the sum of local time-varying cost functions, each of which is known to only an individual agent, through local interaction. Here the optimal point is time varying and creates an optimal trajectory.In last part of this dissertation, the distributed average tracking problem is addressed for a group of heterogeneous physical agents consisting of single-integrator, double-integrator and Euler-Lagrange dynamics. Here, the goal is that each agent uses local information and local interaction to calculate the average of individual time-varying reference inputs, one per agent. Dynamic average tracking is the main challenge in many other distributed algorithms, such as distributed optimization, and distributed Kalman filtering.
Updates on acute and chronic rejection in small bowel and multivisceral allografts

Purpose of reviewThe surgical management of short bowel syndrome now includes intestinal (ITx) and multivisceral transplantation (MVTx), which has advanced and is now a sustainable option for the treatment of intestinal failure. Improvements in immunosuppressive therapies, excellence in surgical and medical management and enhanced post-transplant monitoring have all contributed to optimizing this solid organ transplant as a means of supplanting the diseased native bowel and alimentary tract with a functional alternative. Recent findingsPost-transplant management is a critical and challenging phase of gastrointestinal transplantation, and the transplant pathologist is an essential member of the transplant team who identifies many of the early and late complications after ITx and MVTx. Among the most injurious and common complications of ITx and MVTx is acute rejection and, to a lesser degree, chronic rejection. Both of these broad categories of rejection are principally identified by histopathological changes in the allograft; however, biomarkers and other laboratory analytes are rapidly evolving into critical ancillary tools in identifying and further characterizing the rejection process. Thus, the transplant pathologist must also be able to utilize numerous other laboratory tests and panels of molecular biomarkers that provide supplementary information to accompany the biopsy interpretation and clinical suspicion of rejection. SummaryUsing biopsies and an assortment of additional approaches, the transplant pathologist is now able to provide swift and detailed information regarding the rejection process in the gastrointestinal transplant. This enables the clinical team to properly and successfully intercede, contributing to enhanced patient and graft survival.
Three‐dimensional mechanisms of increased vulnerability to electric shocks in myocardial infarction: Altered virtual electrode polarizations and conduction delay in the peri‐infarct zone

• Defibrillation is known to be less efficient in infarcted than in healthy hearts. • In a rabbit model of myocardial infarction, altered 3D distribution of virtual electrodes and propagation delay in the peri‐infarct zone caused increased vulnerability to electric shocks in infarcted hearts. • The infarct scar alone – without the presence of a peri‐infarct zone – did not cause an increase in vulnerability. • The results help us to understand the mechanisms of increased vulnerability and decreased defibrillation efficacy in infarcted hearts.
High plasticity in epithelial morphogenesis during insect dorsal closure

Summary Insect embryos complete the outer form of the body via dorsal closure (DC) of the epidermal flanks, replacing the transient extraembryonic (EE) tissue. Cell shape changes and morphogenetic behavior are well characterized for DC in Drosophila, but these data represent a single species with a secondarily reduced EE component (the amnioserosa) that is not representative across the insects. Here, we examine DC in the red flour beetle, Tribolium castaneum, providing the first detailed, functional analysis of DC in an insect with complete EE tissues (distinct amnion and serosa). Surprisingly, we find that differences between Drosophila and Tribolium DC are not restricted to the EE tissue, but also encompass the dorsal epidermis, which differs in cellular architecture and method of final closure (zippering). We then experimentally manipulated EE tissue complement via RNAi for Tc-zen1, allowing us to eliminate the serosa and still examine viable DC in a system with a single EE tissue (the amnion). We find that the EE domain is particularly plastic in morphogenetic behavior and tissue structure. In contrast, embryonic features and overall kinetics are robust to Tc-zen1RNAi manipulation in Tribolium and conserved with a more distantly related insect, but remain substantially different from Drosophila. Although correct DC is essential, plasticity and regulative, compensatory capacity have permitted DC to evolve within the insects. Thus, DC does not represent a strong developmental constraint on the nature of EE development, a property that may have contributed to the reduction of the EE component in the fly lineage.