Miracle-dz/UniFAR-FTUs huggingface dataset:
Testing for Latent Factors in Models with Autocorrelation and Heteroskedasticity of Unknown Form

This article considers the problem of testing for latent factors or reduced rank in a broad class of (multivariate linear stationary) time-series models, wherein model errors have autocorrelation and heteroskedasticity of unknown form. It is easy to motivate these models and methods in the context of finance models, and we illustrate with a familiar macromodel of asset returns, proposed previously by Chen, Roll, and Ross. Unfortunately, previously used tests for reduced rank are not sufficiently robust, so we examine two heteroskedasticity and autocorrelation-consistent (HAC) methods, a HAC version of Hansen's GMM test and a lesser known but more user-friendly minimum-distance or ratio of asymptotic densities (RAD) test. We recommend the RAD test, for which we supply computer code. In application, the tests lend more HAC-robust support to the hypothesis that multiple factors drive the link between the macroeconomy and the returns on bonds and stocks.
Antitissue antibodies in monozygotic twins with systemic lupus erythematosus

The familial occurrence of systemic lupus erythematosus (SLE) is well established (Brunjes, Zike, and Julian, 1961; Leonhardt, 1964), and even monozygotic twins with this disease have been reported by several workers (Davis and Gutridge, 1951; Wagenhals and Burgeson, 1958; Blumenfeld, Kaplan, Mills, and Clark, 1963; Joseph and Zarafonetis, 1965; Lieberman, Heuser, Hanson, Kornreich, Donnell, and Landing, 1968). These observations have been considered to indicate that genetically determined factors may have an important role in the aetiology of SLE. The following is a report of a pair of monozygotic twins both of whom had SLE with a very similar clinical picture and who, in addition, had a very similar antitissue antibody pattern.
How to write an essay.

First and foremost, we must decide on a topic and having decided that, we should collect ideas on that topic. This is the research phase of writing. This research is a combination of two methods. The first method is to gather ideas from external sources, mainly from the writings of others. The other method, which is a bit more difficult, is to bring out ideas from oneself, by the process of reflection. Many find it easier to first gather ideas from external sources and then to reflect on these ideas to distill from them, newer ideas. The gathering of ideas can be a time consuming process and one must determine at the outset, how much time should be devoted to this task. Usually, there is a temptation to collect too much information. Thus, one must be ruthless in putting an end to this phase of information gathering since too much information is often the cause of the disease known as “writer’s block. ” Part of this problem is reduced by determining the audience we are writing for. There is no such thing as the general public. A certain amount of facility emerges when we can visualize our reader since that determines the style, tone and choice of words in our writing.
Predicting Delay in Reading Achievement in a Highly Transparent Language

A random sample of 91 preschool children was assessed prior to receiving formal reading instruction. Verbal and nonverbal measures were used as predictors for the time of instruction required to accurately decode pseudowords in the highly orthographically regular Finnish language. After 2 years, participants were divided into four groups depending on the duration of instruction they had required to reach 90 % accuracy in their reading of pseudowords. Participants were classified as precocious decoders (PD), who could read at school entry; early decoders (ED), who learned to read within the first 4 months of Grade 1; ordinary decoders (OD), who learned to read within 9 months; and late decoders (LD), who failed to reach the criterion after 18 months of reading instruction at Grade 2. Phonological awareness played a significant role only in differentiating PD from ED and OD. However, phonological awareness failed to predict the delayed learning process of LD. LD differed from all other groups in visual analogical reasoning in an analysis not containing phonological awareness measures. Letter knowledge and visual analogical reasoning explained above 90% of the PD-LD difference. Preschool composite (objects, colors, and digits) naming speed measures best predicted reading fluency at the end of Grade 2. The supportive role of orthographic knowledge in phonological awareness, the role of visual analogical reasoning, and the inability of phonological measures to discriminate late decoders are discussed.
A WORLDWIDE TOURISM RECOMMENDATION SYSTEM BASED ON GEOTAGGED WEB PHOTOS

This work aims to build a system to suggest tourist destinations based on visual matching and minimal user input. A user can provide either a photo of the desired scenary or a keyword describing the place of interest, and the system will look into its database for places that share the visual characteristics. To that end, we rst cluster a large-scale geotagged web photo collection into groups by location and then nd the representative images for each group. Tourist destination recommendations are produced by comparing the query against the representative tags or representative images under the premise of “if you like that place, you may also like these places”.
In silico prediction of multiple-category classification model for cytochrome P450 inhibitors and non-inhibitors using machine-learning method$

Abstract The cytochrome P450 (CYP) enzyme superfamily is involved in phase I metabolism which chemically modifies a variety of substrates via oxidative reactions to make them more water-soluble and easier to eliminate. Inhibition of these enzymes leads to undesirable effects, including toxic drug accumulations and adverse drug–drug interactions. Hence, it is necessary to develop in silico models that can predict the inhibition potential of compounds for different CYP isoforms. This study focused on five major CYP isoforms, including CYP1A2, 2C9, 2C19, 2D6 and 3A4, that are responsible for more than 90% of the metabolism of clinical drugs. The main aim of this study is to develop a multiple-category classification model (MCM) for the major CYP isoforms using a Laplacian-modified naïve Bayesian method. The dataset composed of more than 4500 compounds was collected from the PubChem Bioassay database. VolSurf+ descriptors and FCFP_8 fingerprint were used as input features to build classification models. The results demonstrated that the developed MCM using Laplacian-modified naïve Bayesian method was successful in classifying inhibitors and non-inhibitors for each CYP isoform. Moreover, the accuracy, sensitivity and specificity values for both training and test sets were above 80% and also yielded satisfactory area under the receiver operating characteristic curve and Matthews correlation coefficient values.
Constrained minimum cut for classification using labeled and unlabeled data

The use of unlabeled data has lead to an improvement in classification accuracy for a variety of classification problems via co-training approaches. In the co-training approach, the data has to be available in a dual view representation or two distinct classifiers are required. In this paper, a unified energy equation for classification combining labeled data and unlabeled data is introduced. This classification formulation is posed as a constrained minimum cut problem integrating labeling information on labeled data and cluster similarity information on unlabeled data for joint estimation. A novel constrained randomized contraction algorithm is proposed for finding the solution to the constrained minimum cuts problem. Experimental results on standard datasets and synthetic datasets are presented.
Identifying Media Bias by Analyzing Reported Speech

Media analysis can reveal interesting patterns in the way newspapers report the news and how these patterns evolve over time. One example pattern is the quoting choices that media make, which could be used as bias indicators. Media slant can be expressed both with the choice of reporting an event, e.g. a person’s statement, but also with the words used to describe the event. Thus, automatic discovery of systematic quoting patterns in the news could illustrate to the readers the media’ beliefs, such as political preferences. In this paper, we aim to discover political media bias by demonstrating systematic patterns of reporting speech in two major British newspapers. To this end, we analyze news articles from 2000 to 2015. By taking into account different kinds of bias, such as selection, coverage and framing bias, we show that the quoting patterns of newspapers are predictable.
Securing KVM-Based Cloud Systems via Virtualization Introspection

Linux Kernel Virtual Machine (KVM) is one of the most commonly deployed hypervisor drivers in the IaaS layer of cloud computing ecosystems. The hypervisor provides a full-virtualization environment that intends to virtualize as much hardware and systems as possible, including CPUs, network interfaces and chipsets. With KVM, heterogeneous operating systems can be installed in Virtual Machines (VMs) in an homogeneous environment. However, it has been shown that various breaches due to software defects may cause damages on such a cloud ecosystem. We propose a new Virtualization Introspection System (VIS) to protect the host as well as VMs running on a KVM-based cloud structure from malicious attacks. VIS detects and intercepts attacks from VMs by collecting their static and dynamic status. We then replay the attacks on VMs and leverage artificial intelligence techniques to derive effective decision rules with unsupervised learning nature. The preliminary result shows the promise of the presented approach against several modern attacks on CVE-based vulnerabilities.
Exploration of the Bibliometric Coordinates for the Field of 'Geography'

This study is a bibliometric analysis of a highly complex research discipline, namely geography, in order to identify the most used and cited publication channels, to reveal publication strategies, and to analyse the discipline’s coverage in the three main data sources for citation analyses: Web of Science, Scopus and Google Scholar. The results show very heterogeneous and individual publication strategies when considering the selection of adequate publication channels even in the same research fields. Monographs, journal articles (including proceedings papers) and book chapters are the most cited document types. Differences between research fields more related to the natural sciences than to the social sciences are clearly visible but not so considerable when taking into account the higher number of co-authors. General publication strategies are more established in the fields related to the natural sciences. Although an “iceberg citation model” is suggested, citation analyses for monographs, book chapters and reports (working papers) should be conducted separately and include complementary data sources, such as Google Scholar, in order to enhance the coverage and improve the quality of the citation analysis. Conference Topics Citation and co-citation analysis – Social Sciences Introduction and background From a bibliometric point of view, geography is a very challenging discipline, because it belongs to the natural sciences (geography, physical) as well as to the social sciences (geography), as it is clearly depicted in each edition of Journal Citation Reports (see Table 1). Table 1. Category data of geography in both Editions of JCR (2013) Table 1 shows very different citation characteristics according to the corresponding JCR edition. Furthermore, geography is a highly interdisciplinary field, very strongly related to geosciences, environmental sciences, ecology and remote sensing (natural sciences), or to economics, urban studies and political sciences (social science), as a quick search and refine analysis in WoS (Web of Sciences core collection) illustrates. Although there are many studies illustrating the differences between natural and social sciences and the different publication cultures depending on the discipline (e.g. Nederhof, 2006; Australian Research Council, 2012; Ossenblok et al., 2012; van Leeuwen, 2013; Moksony, 2014), no literature focusing on this specific could be retrieved by the authors. The main research questions of this study are: • What are the publication characteristics depending on the different research field? • Can differences be observed concerning research fields? What is their time evolution? JCR EDITION 2013 Category Total Cites Median IF Aggre gate IF Aggre gate Imme diacy Index Aggre gate Cited HalfLife # Journals # Articles Sciences GEOGRAPHY, PHYSICAL 159297 2.152 2.574 0.72 7.5 46 4972 Social Sciences GEOGRAPHY 79207 1.059 1.612 0.343 7.4 76 3762
Brain uptake of methylprednisolone acetate. From the cerebrospinal fluid and systemic sites.

Tritiated-α-methylprednisolone-21-acetate was prepared in a dosage form comparable to commercial Depo-Medrol and administered to adult cats either intracisternally or intraperitoneally. Therapeutic amounts of tritiated methylprednisolone acetate were taken up rapidly from the subarachnoid space of cats into the central nervous system to reach levels five to ten times higher than could be attained by systemic injection. Plasma steroid levels were similar whether the drug was placed in the peritoneal or cisternal space. Although the steroid concentration in brain declined rapidly during the first 24 hours after intrathecal injection, steroid was still detectable seven days later. White matter regions tended to attain and retain larger amounts of steroid than gray. Brain steroid levels after intrathecal administration, probably represent a steady state between the rate of diffusion of steroid into the brain from the cerebrospinal fluid (CSF) and its rate of removal by the circulation. Provided that high CSF steroid levels are attained, higher and more prolonged therapeutic brain levels will result after intrathecal administration than by other routes.
Securing IoT for smart home system

This paper presents an approach to incorporate strong security in deploying Internet of Things (IoT) for smart home system, together with due consideration given to user convenience in operating the system. The IoT smart home system runs on conventional wifi network implemented based on the AllJoyn framework, using an asymmetric Elliptic Curve Cryptography to perform the authentications during system operation. A wifi gateway is used as the center node of the system to perform the system initial configuration. It is then responsible for authenticating the communication between the IoT devices as well as providing a mean for the user to setup, access and control the system through an Android based mobile device running appropriate application program.
First Report of Human Trypanosoma cruzi Infection Attributed to TcBat Genotype

Chagas disease is an endemic disease of the American continent caused by Trypanosoma cruzi and divided into six discrete typing units (TcI – TcVI). Nearly 10 million people harbour the infection representing a serious issue in public health. Epidemiological surveillance allowed us to detect a bat‐related T. cruzi genotype (henceforth named TcBat) in a 5‐year‐old female living in a forest area in northwestern Colombia. Molecular tools determined a mixed infection of T. cruzi I and TcBat genotypes. This represents the first report of TcBat infection in humans; the epidemiological consequences of this finding are discussed herein.
Area method used in the evaluation of resilience implementation approaches in system of systems

System of systems (SoS), like transportation systems and combat systems, is integrated by a set of independently operating systems that interact with each other to provide an end-to-end capability, which cannot be achieved by individual systems. Resilience is the ability of an SoS to recover to a desired performance level after disruptive events. Even though many measures have been proposed to evaluate resilience, there is no one general metric that can be used in all situations. Given that what we actually need is the performance process with time, this paper presents an area method to evaluate resilience by calculating the area below the performance curve after disruption. Meanwhile, we propose the SoS operating time, combined with the area method, to identify which of the recovered performance levels and the recovery speeds is more important according to different situations. Finally, the proposed research enables us to evaluate resilience implementation approaches and select the best one.
Chinese Answer Extraction Based on POS Tree and Genetic Algorithm

Answer extraction is the most important part of a chinese web-based question answering system. In order to enhance the robustness and adaptability of answer extraction to new domains and eliminate the influence of the incomplete and noisy search snippets, we propose two new answer exraction methods. We utilize text patterns to generate Part-of-Speech (POS) patterns. In addition, a method is proposed to construct a POS tree by using these POS patterns. The POS tree is useful to candidate answer extraction of web-based question answering. To retrieve a efficient POS tree, the similarities between questions are used to select the question-answer pairs whose questions are similar to the unanswered question. Then, the POS tree is improved based on these question-answer pairs. In order to rank these candidate answers, the weights of the leaf nodes of the POS tree are calculated using a heuristic method. Moreover, the Genetic Algorithm (GA) is used to train the weights. The experimental results of 10-fold crossvalidation show that the weighted POS tree trained by GA can improve the accuracy of answer extraction.
Dose-response relationship between intensity of exercise and cognitive performance in individuals with Down syndrome: a preliminary study.

BACKGROUND Cognitive performance has been shown to be relevant to the early onset of Alzheimer's disease in individuals with Down syndrome. This study was aimed at investigating the dose-response relationship between acute exercise intensity and cognitive performance in this population. METHODS In the current study, we measured information processing speed and two aspects of executive function (i.e. attention shifting and inhibitory control). Participants were assigned to high-intensity exercise (i.e. 75-85% of predicted maximum heart rate) (N = 6), moderate-intensity exercise (i.e. 50-75% of predicted maximum heart rate) (N = 6) or attentional control (N = 6) groups. Two exercise groups walked on a treadmill using an incremental intensity walking protocol, and the attentional control group watched a video for 20 min. Measures of information processing speed and executive function were tested pre-intervention and post-intervention. RESULTS Our results indicated that the performance in choice reaction time test was impaired in the high-intensity exercise, whereas improved performance was observed in the moderate-intensity exercise. However, moderate-intensity and high-intensity exercises were beneficial for inhibitory control aspect of executive function. Further, inconsistent with previous studies, a quadric trend was seen in information processing speed, and a liner trend was evident in inhibitory control. CONCLUSIONS Future research is needed to examine with a larger sample size, and more physiological measures are necessary to explore the underlying mechanisms in the relationship between exercise intensity and cognitive performance in individuals with Down syndrome.
Triggering changes in adaptive automation evaluation of task performance, priority and frequency

Adaptive automation has been proposed, where changes in automation are triggered based upon operator state to mitigate automation-induced problems such as complacency. This research sought to understand the effect of a weighted method, as compared to a method in which all tasks are weighed equally, when triggering changes in automation within a multitasking environment. The weighted method considered the priority and frequency of each task when computing a measure of operator performance on which to trigger changes in automation. Although overall system performance was not statistically different between the two trigger implementations, the participants with the priority based triggering scheme rated the level of automation change as more aligned with their performance and were less surprised by changes in automation level.
Harmonization of usability measurements in ISO9126 software engineering standards

The measurement of software usability is recommended in ISO 9126-2 to assess the external quality of software by allowing the user to test its usefulness before it is delivered to the client. Later, during the operation and maintenance phases, usability should be maintained, otherwise the software will have to be retired. This then raises harmonization issues about the proper positioning of the usability characteristic: does usability really belong to the external quality view of ISO 9126-2 and should the external quality characteristic of usability be harmonized with that of the quality in use model defined in ISO 9126-1 and ISO 9126-4? This paper analyzes these two questions: first, we identify and analyze the subset of ISO 9126-2 quality subcharacteristics and measures of usability that can be useful for quality in use, and then we recommend improvements to the harmonization of these ISO 9126 models
TRIPLE-STAR : A CODING SCHEME WITH OPTIMAL ENCODING COMPLEXITY FOR TOLERATING TRIPLE DISK FAILURES

Low encoding/decoding complexity is essential for practical storage systems. This paper presents a new Maximum Distance Separable (MDS) array codes, called Triple-Star, for tolerating triple disk failures in Redundant Arrays of Inexpensive Disks (RAID) architecture. Triple-Star is an extension of the double-erasure-correcting Rotarycode and a modification of the generalized triple-erasure-correcting EVENODD code. We construct Triple-Star based on a bit matrix-vector product similar to the Reed-Solomon coding, and provide the geometry encoding method and detailed non-recursive decoding algorithms for correcting various triple node failures. The key novelty in Triple-Star is that it has optimal encoding complexity and lower decoding complexity comparing with existing comparable codes.
[Effects of different doses of dexmedetomidine combined with ropivacaine for brachial plexus nerve block in children undergoing polydactyly surgery].

OBJECTIVE To observe the anesthetic effect and safety of different doses of dexmedetomidine combined with ropivacaine for brachial plexus nerve block in children undergoing polydactyly surgery. METHODS Eighty children undergoing polydactyly surgery were randomized into 4 groups to receive brachial plexus nerve block with dexmedetomidine at 0.25, 0.50 or 0.75 µg/kg combined with 0.25% ropivacaine (0.20 mL/kg) (D1, D2, and D3 groups, respectively) or with 0.25% ropivacaine (0.20 mL/kg) only (control group). The onset time, duration of brachial plexus nerve block, awakening time, success rate, and incidence of complications were compared among the groups. Results In D2 and D3 groups, the onset time and awakening time were shorter and anesthesia lasted longer than those in the control group. The onset time and awakening time were shorter and anesthesia maintenance time was longer in D3 group than in D1 group. The success rates of brachial plexus nerve block were significantly higher in D1-3 groups than in the control group (P<0.05). Hematoma was found in one of the patients. In each of the 4 groups, laryngeal nerve block occurred in 1 child and respiratory depression in another; 2 or 3 patients had Horner syndrome, and 1 patient in D3 group experienced an episode of lowered heart beat to below 70 min-1. All the complications were managed properly and the patients all recovered uneventfully. CONCLUSION Brachial plexus nerve block with 0.5 µg/kg dexmedetomidine combined with 0.25% ropivacaine (0.20 mL/kg) is safe for effective anesthesia in children undergoing surgery for polydactyly.