Miracle-dz/UniFAR-FTUs huggingface dataset:
An Empirical Study of Relationship between Monetary Policy and Stock Market Performance in Malaysia

This study examined the relationship between monetary policy and stock market performance for sample data from first quarter of 1991 to first quarter of 2011 in Malaysia. The result of Unit Root test revealed the monetary supply variables namely; M1, M2, and M3 were stationary only after first difference. The results also show same characteristic within market index of Kuala Lumpur Composite Index. Real interest rate was level stationary as well. The Augmented Dickey Fuller (ADF) and Phillip-Perron (PP) tests confirmed each other. Co-integration analysis and Vector Error Correction Models (VECM) were also suggested a possibility of merely one long-run equilibrium relationship between real Kuala Lumpur Composite Index regards to M1, M2, M3, and real interest rate. On the other hand, results of trace and maximum Eigenvalue methods suggested only one co-integration equation amongst research variables. The Vector Error Correction Models analysis shows a statistically significant relationship between M1 and M2 as a monetary supply variable included in the model; so that M1 and M2 has long term influence on Kuala Lumpur Composite Index. All in all, the research findings suggested that by increasing the money supply, the market index of Kuala Lumpur Composite Index would growth in long term.
Radiographic evaluation of marginal bone level around implants with different neck designs after 1 year.

PURPOSE To evaluate the influence of macro- and microstructure of the implant surface at the marginal bone level after functional loading. MATERIALS AND METHODS Sixty-eight patients were randomly assigned to 1 of 3 groups. The first group received 35 implants with a machined neck (Ankylos); the second group, 34 implants with a rough-surfaced neck (Stage 1); and the third, 38 implants with a rough-surfaced neck with microthreads (Oneplant). Clinical and radiographic examinations were conducted at baseline (implant loading) and 3, 6, and 12 months postloading. Two-way repeated analysis of variance (ANOVA) was used to test the significance of marginal bone change of each tested group at baseline, 3, 6, and 12 month follow-ups and 1-way ANOVA was also used to compare the bone loss of each time interval within the same implant group (P < .05). RESULTS At 12 months, significant differences were noted in the amount of alveolar bone loss recorded for the 3 groups (P < .05). The group with the rough-surfaced microthreaded neck had a mean crestal bone loss of 0.18 +/- 0.16 mm; the group with the rough-surfaced neck, 0.76 +/- 0.21 mm; and the group with the machined neck, 1.32 +/- 0.27 mm. In the rough-surfaced group and the rough-surfaced microthreaded group, no statistically significant changes were observed after 3 months, whereas the machined-surface group showed significant bone loss for every interval (P < .05). DISCUSSION To minimize marginal bone loss, in addition to the use of a rough surface at the marginal bone level, a macroscopic modification such as the addition of microthreads could be recommended. A rough surface and microthreads at the implant neck not only reduce crestal bone loss but also help with early biomechanical adaptation against loading in comparison to the machined neck design. CONCLUSION A rough surface with microthreads at the implant neck was the most effective design to maintain the marginal bone level against functional loading.
Statistical models for text normalization and machine translation

Irish and Scottish Gaelic are closely-related languages that together with Manx Gaelic make up the Goidelic branch of the Celtic family. We present a statistical model for translation from Scottish Gaelic to Irish that we hope will facilitate communication between the two language communities, especially in social media. An important aspect of this work is to overcome the orthographical differences between the languages, many of which were introduced in a major spelling reform of Irish in the 1940’s and 1950’s. Prior to that date, the orthographies of the two languages were quite similar, thanks in part to a shared literary tradition. As a consequence of this, machine translation from Scottish Gaelic to Irish has a great deal in common with the problem of normalizing pre-standard Irish texts, a problem with applications to lexicography and information retrieval. We show how a single statistical model can be used effectively in both contexts.
A 60 GHz frequency divider with quadrature outputs in 130nm SiGe BiCMOS technology for optical OFDM systems

A frequency divider providing quadrature outputs up to 30GHz is presented. Rms phase error and rms clock jitter are discussed in the context of OFDM systems, where the usual phase error correction in the digital baseband processor is included. A measurement technique for the static phase error between the in-phase and quadrature signal is proposed using an integrated single-sideband mixer in conjunction with an integrated 1:256 frequency divider. For a 20GHz I/Q output signal a static phase error of 0.16° is obtained from these measurements. The quadrature divider core draws 35mA from a 3.3 V supply and occupies 0.2 mm2 chip area, including output buffers and two differential delay lines for I/Q adjustment.
Learning what to ignore: Memetic climbing in topology and weight space

We present the memetic climber, a simple search algorithm that learns topology and weights of neural networks on different time scales. When applied to the problem of learning control for a simulated racing task with carefully selected inputs to the neural network, the memetic climber outperforms a standard hill-climber. When inputs to the network are less carefully selected, the difference is drastic. We also present two variations of the memetic climber and discuss the generalization of the underlying principle to population-based neuroevolution algorithms.
Helicobacter pylori Vaccine Development in the Post‐genomic Era: Can In Silico translate to In Vivo

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Home exercise programmes supported by video and automated reminders compared with standard paper-based home exercise programmes in patients with stroke: a randomized controlled trial

Objective: To determine whether patients with stroke receiving rehabilitation for upper limb deficits using smart technology (video and reminder functions) demonstrate greater adherence to prescribed home exercise programmes and better functional outcomes when compared with traditional paper-based exercise prescription. Design: Randomized controlled trial comparing upper limb home exercise programmes supported by video and automated reminders on smart technology, with standard paper-based home exercise programmes. Setting: A community rehabilitation programme within a large metropolitan health service. Subjects: Patients with stroke with upper limb deficits, referred for outpatient rehabilitation. Interventions: Participants were randomly assigned to the control (paper-based home exercise programme) or intervention group (home exercise programme filmed on an electronic tablet, with an automated reminder). Both groups completed their prescribed home exercise programme for four weeks. Main measures: The primary outcome was adherence using a self-reported log book. Secondary outcomes were change in upper limb function and patient satisfaction. Results: A total of 62 participants were allocated to the intervention (n = 30) and control groups (n = 32). There were no differences between the groups for measures of adherence (mean difference 2%, 95% CI −12 to 17) or change in the Wolf Motor Function Test log transformed time (mean difference 0.02 seconds, 95% CI −0.1 to 0.1). There were no between-group differences in how participants found instructions (p = 0.452), whether they remembered to do their exercises (p = 0.485), or whether they enjoyed doing their exercises (p = 0.864). Conclusions: The use of smart technology was not superior to standard paper-based home exercise programmes for patients recovering from stroke. This trial design was registered prospectively with the Australian and New Zealand Clinical Trials Register, ID: ACTRN 12613000786796. http://www.anzctr. org.au/trialSearch.aspx
Chunk-Based Verb Reordering in VSO Sentences for Arabic-English Statistical Machine Translation

In Arabic-to-English phrase-based statistical machine translation, a large number of syntactic disfluencies are due to wrong long-range reordering of the verb in VSO sentences, where the verb is anticipated with respect to the English word order. In this paper, we propose a chunk-based reordering technique to automatically detect and displace clause-initial verbs in the Arabic side of a word-aligned parallel corpus. This method is applied to preprocess the training data, and to collect statistics about verb movements. From this analysis, specific verb reordering lattices are then built on the test sentences before decoding them. The application of our reordering methods on the training and test sets results in consistent BLEU score improvements on the NIST-MT 2009 Arabic-English benchmark.
Impact of mutations in FLT3, PTPN11 and RAS genes on the overall survival of pediatric B cell precursor acute lymphoblastic leukemia in Brazil

Abstract We analyzed mutations in four genes (FLT3, KRAS/NRAS and PTPN11) that might disrupt the RAS/mitogen activated protein kinase (MAPKinase) signaling pathway, to evaluate their prognostic value in children younger than 16 years old with B-cell precursor acute lymphoblastic leukemia (Bcp-ALL). The overall survival (OS) was determined with the Kaplan–Meier method. MAPKinase genes were mutated in 25.4% and 20.1% of childhood and infant Bcp-ALL, respectively. Children with hyperdiploidy were more prone to harboring a MAPKinase gene mutation (odds ratio [OR] 3.18; 95% confidence interval [CI] 1.07–9.49). The mean OS of all cases was 54.0 months. FLT3 and PTPN11 mutations had no impact on OS. K/NRAS mutations were strongly associated with MLL–AFF1 (OR 5.78; 95% CI 1.00–33.24), and conferred poorer OS (p = 0.034) in univariate analysis.
On the complexity of statistical reasoning

We show that basic problems in reasoning about statistics are NP-hard to even approximately solve. We consider the problem of detecting internal inconsistencies in a set of statistics. We say that a set of statistics is /spl epsiv/-inconsistent if one of the probabilities must be off by at least /spl epsiv/. For a positive constant /spl epsiv/, we show NP-hard to distinguish /spl epsiv/-inconsistent statistics from self-consistent statistics. This result holds when restricted to complete sets of pairwise statistics over Boolean domains. We next consider what may, be determined about distributions with a given (consistent) set of pairwise statistics over Boolean domains. We show it NP-hard to distinguish between the case that Pr(X/sub i//spl and/X/sub j/) is necessarily 0 and the case that Pr(X/sub i//spl and/X/sub j/) can have any value in [0, 1/2 ]. Similarly, we show it NP-hard to distinguish between the case that |Corr(X/sub i/, X/sub j/)|=-1 and the case that |Corr(X/sub i/, X/sub j/)| is unconstrained. Whereas the connection between PCP and hardness of approximations has been known since Feige et al. (1991), we introduce the application of "zero-knowledge" PCP's as a tool for proving NP-hardness results for approximation problems. <<ETX>>
Enhancing Textured Digital Elevation Models Using Photographs

We present a method for enhancing the visual quality of existing digital elevation models textured with orthophotos, using a sparse set of unordered, high resolution photographs. After an initial manual selection of correspondence points, we automatically register the input photographs to the given terrain data set using robust imagebased modeling techniques. To combine the geo-registered images on the terrain surface, we propose a compositing algorithm that ensures smooth transitions between the images while at the same time preserving the fine details. The resulting textures are inserted into the quadtree representation of a terrain rendering engine to allow an efficient realtime visualization. We demonstrate our method on an HRSC terrain data set and a collection of high resolution photos of Turtmann valley in Switzerland.
BK virus nephropathy in a patient with ABO‐incompatible renal transplantation

Abstract: A 43‐year‐old woman with end‐stage renal disease originating from IgA nephropathy entered chronic haemodialysis therapy. She then received an ABO‐incompatible living related renal transplantation. Initial immunosuppression consisted of azathioprine, methylprednisolone and tacrolimus. At 155 days after transplantation, the azathioprine was changed to mycophenolate mofetil for continuous graft dysfunction. Furthermore, a total of three courses of anti‐rejection therapy was given. At 665 days after transplantation, diagnosis of BK‐virus nephropathy was made by immunohistochemical analysis and viral DNA assay. Therefore the immunosuppression therapy was reduced for graft dysfunction. All five renal biopsy specimens were examined retrospectively in order to determine when the BK virus nephropathy had developed. The expressions of SV40 large T antigens were detected from the third (117 days) to the fifth (665 days) biopsies, with increasing numbers of SV40 large T antigen positive cells. In addition, many cells contained inclusion bodies which were already present in the urinary sediment for 3 months post‐transplantation. Although it is difficult to make a diagnosis of early stage of BKVN, we have to consider with caution if urinary cells with inclusion body are seen. Awareness of BKVN at the earliest opportunity is important in order to avoid over‐immunosuppression.
An Investigation of the Use of KMS on Clinical Performance

Use of Information Technology (IT) to facilitate storage, search and access to codified knowledge can enhance organizational performance. Considering the knowledge intensive nature of medical decision making, use of knowledge management systems (KMS) can potentially enhance delivery of patient care. This paper reports on a field study that investigated the impact of use of a KMS by emergency physicians on their decision making behaviors (admission of patients for in-hospital care) and efficiency of care. The findings indicate that in the emergency room (ER) under study, the use of a KMS for placing diagnostic orders resulted in lower hospital admissions, cost savings, and a shorter ER stay.
A review of PARP inhibitors: from bench to bedside.

BACKGROUND Poly(adenosine diphosphate [ADP]-ribose) polymerase (PARP) inhibitors, with novel and selective mechanisms of action, have moved from the laboratory to the clinic in just the last few years. DESIGN We conducted an extensive review of PARP inhibitors using a Medline search. We also searched abstracts in databases of major international oncology meetings from the last 4 years. RESULTS To understand the mechanisms of action of PARP inhibitors requires a basic understanding of DNA repair mechanisms and the critical role of the PARP enzyme. We briefly review these DNA repair mechanisms, the concept of 'synthetic lethality', and how PARP inhibitors play a role to selectively disrupt DNA repair in cells with absent or dysfunctional BRCA genes. We review the preclinical data highlighting this unique and selective mechanism of action and we discuss early but highly promising clinical data and ongoing studies. CONCLUSION PARP inhibitors show promise as a powerful therapeutic tool, especially in the management of BRCA-associated breast and ovarian cancers but also in tumours where BRCA genes may be dysfunctional. Clinical studies are ongoing and many translational questions remain unanswered that will help clarify how to determine the best way to use PARP inhibitors.
Long-term anticoagulation in questions and answers.

Which anticoagulants should be used for patients with atrial fibrillation and cancer? In the management of patients with atrial fibrillation (AF) and can‐ cer, VKAs or NOACs can be used for stroke pre‐ vention. However, the effectiveness and safety of treatment with NOACs in this specific group of patients are poorly documented because these pa‐ tients have not been included in large randomized clinical trials on the use of NOACs in AF. How‐ ever, clinical practice shows that NOACs are well tolerated by most cancer patients in good general condition, receiving outpatient cancer treatment, and with low ‐to ‐moderate bleeding risk, and not taking antifungal drugs or cyclosporine. In every‐ day practice, however, LMWH are mostly used in patients with venous thromboembolism (VTE), and not with AF, except when such management is planned only for a short time and because of invasive procedures, nausea, vomiting, or diar‐ rhea, and other complications of an underlying disease. The effectiveness of LMWH (particular‐ ly at prophylactic or moderate doses) in AF, es‐ pecially in high ‐risk patients is unknown; how‐ ever, in high ‐risk cancer inpatients with elevat‐ ed risk of bleeding LMWH should be considered. Anticoagulation strategy should be individualized in cancer patients especially if both bleeding and thrombosis risks are high.
Invisible Ties: Finding Learning as It Happens

Why is finding the learning important? Because as teachers we can feel when a class is going well and think we can explain why: we’re getting our content across — and all (or enough) of it and in an order that makes sense; we’re making sense; we’re feeling in control or challenged, depending on our preferred style; we’ve plenty of questions or dialogue; we notice that the class is busy and noisy — or the opposite, depending on the discipline. If we feel that a class is going well, most of us would say that there must be learning going on. We don’t know, of course, because students might just be playing along or they might be good at pretending, that is, they might be playing at being good learners. It’s hard to know. (Most of us teachers are, of course, just playing at being good teachers; we’re just “muddling through,” as Stephen Brookfield [2006] puts it [p. 1].)
Place recognition and heading retrieval are mediated by dissociable cognitive systems in mice

Significance The ability to recover one’s bearings when lost is critical for successful navigation. To accomplish this feat, a navigator must identify its current location (place recognition), and it must also recover its facing direction (heading retrieval). Using a novel behavioral paradigm, we demonstrate that mice use one set of cues to determine their location and then ignore these same cues when determining their heading, although the cues are informative in both cases. These results suggest that place recognition and heading retrieval are mediated by different processing systems that operate in partial independence of each other. This finding has important implications for understanding the cognitive architecture underlying spatial navigation. A lost navigator must identify its current location and recover its facing direction to restore its bearings. We tested the idea that these two tasks—place recognition and heading retrieval—might be mediated by distinct cognitive systems in mice. Previous work has shown that numerous species, including young children and rodents, use the geometric shape of local space to regain their sense of direction after disorientation, often ignoring nongeometric cues even when they are informative. Notably, these experiments have almost always been performed in single-chamber environments in which there is no ambiguity about place identity. We examined the navigational behavior of mice in a two-chamber paradigm in which animals had to both recognize the chamber in which they were located (place recognition) and recover their facing direction within that chamber (heading retrieval). In two experiments, we found that mice used nongeometric features for place recognition, but simultaneously failed to use these same features for heading retrieval, instead relying exclusively on spatial geometry. These results suggest the existence of separate systems for place recognition and heading retrieval in mice that are differentially sensitive to geometric and nongeometric cues. We speculate that a similar cognitive architecture may underlie human navigational behavior.
Robust short-term load forecasting

Analyzing the stochastic characteristics of electric consumption series in many countries shows the presence of atypical observations or outliers. Outliers are deviant data points that do not follow the model of the majority of observations. They significantly degrade the accuracy of conventional day-ahead estimation and forecasting methods even if they are present in a very low fraction. Thus, both their identification and separate treatment are important in practice. In this paper, we evaluate by a comparison analysis the performance of some robust estimation methods. Namely, the robust filtered S- and filtered τ-estimators, the minimum covariance determinant (MCD), and the 3-σ rejection rule. The performance of these methods has been evaluated on the French electric demand in terms of forecasting accuracy. The sophisticated robust methods exhibit the best reliability if compared to non-robust or basic robust methods. Practical load forecasting confirms the necessary good theoretical tradeoff between robustness and efficiency under the nominal model.
An ensemble based incremental learning framework for concept drift and class imbalance

We have recently introduced an incremental learning algorithm, Learn++. NSE, designed to learn in nonstationary environments, and has been shown to provide an attractive solution to a number of concept drift problems under different drift scenarios. However, Learn++. NSE relies on error to weigh the classifiers in the ensemble on the most recent data. For balanced class distributions, this approach works very well, but when faced with imbalanced data, error is no longer an acceptable measure of performance. On the other hand, the well-established SMOTE algorithm can address the class imbalance issue, however, it cannot learn in nonstationary environments. While there is some literature available for learning in nonstationary environments and imbalanced data separately, the combined problem of learning from imbalanced data coming from nonstationary environments is underexplored. Therefore, in this work we propose two modified frameworks for an algorithm that can be used to incrementally learn from imbalanced data coming from a nonstationary environment.
Comments on: A methodology for evaluation of boundary detection algorithms on medical images

In this paper we analyze a result previously published about a comparison between two statistical tests used for evaluation of boundary detection algorithms on medical images. We conclude that the statement made by Chalana and Kim (1997) about the performance of the percentage test has a weak theoretical foundation, and according to our results, is not correct. In addition, we propose a one-sided hypothesis test for which the acceptance region can be determined in advance, as opposed to the two-sided confidence intervals proposed in the original paper, which change according to the estimated quantity.