Miracle-dz/UniFAR-FTUs huggingface dataset:
The New Anticoagulants : Which one is for You ? by

Although there is no evidence that otherwise healthy lone afibbers have an increased risk of ischemic stroke, it is clear that atrial fibrillation (AF) patients with heart failure, diabetes or hypertension have a significantly increased risk and this risk is further magnified if the patient has already suffered a heart attack or stroke. To date, oral anticoagulation with vitamin K antagonists such as warfarin (Coumadin) is still considered to be the best preventive therapy for patients at risk for stroke. Unfortunately, warfarin interacts with many foods and drugs and treatment requires constant, costly monitoring. Its use also substantially increases the risk of hemorrhagic stroke and major internal bleeding, particularly in older people, a group that, ironically, is also most at risk for an ischemic stroke. Effective warfarin therapy is based on maintaining an INR (international normalized ratio) between 2.0 and 3.0. In real life this ratio is only achieved on a continuous basis in about 50 to 60% of patients. Too low a ratio increases the risk of ischemic stroke, while too high a ratio increases the risk of hemorrhagic stroke and major bleeding.
Effects of a spaceflight environment on phenotypic, genomic and transcriptomic changes in KPC-2 Klebsiella pneumoniae

As a highly drug-resistant and widely spread pathogen, carbapenemase (KPC)-producing Klebsiella pneumoniae represents an urgent public health crisis. Variations in the ability to cope with environmental hazards increase a microbe’s survival chances. Therefore, understanding such adaptive mechanisms will be beneficial for controlling the spread K. pneumoniae and the development of anti-infective therapies. The extreme environment in spaceflight represents a unique research platform. We compared phenotypic variations and analyzed genomic and transcriptomic variations in KPC-2 K. pneumoniae among three different groups: strains T (15 days of Shenzhou X spaceflight), D (the ground control) and F (the reference strain). We found no obvious variations in the drug susceptibility, carbon source utilization, biofilm-forming capacity, and shapes and arrangements of bacterial cells of the D and T strains; however, the growth rates and final concentrations of the bacterial cells decreased when cultured in hypertonic LB medium (8% sodium chloride). Additionally, high-throughput sequencing revealed some genomic mutations and differentially regulated transcriptomes between the D and T strains. These results provide insights into the environmental adaptation of this widespread pathogen.
Computation of Mean Cerebral Blood Flow Velocity for the Assessment of Cerebral Autoregulation: Comparison of Different Strategies

Cerebral autoregulation (CA) is a complex mechanism stabilizing cerebral blood flow (CBF) against arterial pressure (AP) changes. CBF is commonly surrogated with the CBF velocity (CBFV) recorded via transcranial Doppler device from the middle cerebral artery. Most of the studies evaluating CA compute mean CBFV (MCBFV) on a beat-to-beat basis along with mean AP (MAP), but there is not a standard approach to derive MCBFV. In this study, we compare three different strategies to calculate MCBFV: i) between two consecutive diastolic points detected on the CBFV signal (MCBFVCBFV); ii) between two consecutive diastolic points detected on the AP signal (MCBFVAP); iii) between two consecutive R-wave peaks detected on the ECG (MCBFVECG). We analyzed ECG, noninvasive AP and CBFV signals recorded from 23 subjects (age: 28 ± 9 yrs, 13 female) at rest in supine position (REST) and during head-up tilt at 60° (TILT). While means were similar regardless of the considered strategy, variances significantly varied with MCBFVCBFV and MCBFVECG strategy producing the largest and the smallest variance respectively. This result stresses the need to standardize the approach for MCBFV computation to reduce the variability of the results solely due to the method adopted for its computation and favor clinical applications of CA assessment.
B 100 , 064104 ( 2019 ) Pressure-induced structural dimerization in the hyperhoneycomb iridate β-Li 2 IrO 3 at low temperatures

L. S. I. Veiga ,1,* K. Glazyrin,2 G. Fabbris,3 C. D. Dashwood,1 J. G. Vale,1 H. Park,4,5 M. Etter,2 T. Irifune,6,7 S. Pascarelli,8 D. F. McMorrow,1 T. Takayama,9,10 H. Takagi,9,10 and D. Haskel3,† 1London Centre for Nanotechnology and Department of Physics and Astronomy, University College London, Gower Street, London WC1E6BT, United Kingdom 2Photon Science, Deutsches Elektronen-Synchrotron (DESY), Notkestrasse 85, Hamburg 22607, Germany 3Advanced Photon Source, Argonne National Laboratory, Argonne, Illinois 60439, USA 4Physics Department, University of Illinois at Chicago, Chicago, Illinois 60607, USA 5Materials Science Division, Argonne National Laboratory, Lemont, Illinois 60439, USA 6Geodynamics Research Center, Ehime University, Matsuyama, 790-8577, Japan 7Earth-Life Science Institute, Tokyo Institute of Technology, Tokyo, Japan 8European Synchrotron Radiation Facility, 71 Avenue des Martyrs, 38043 Grenoble, France 9Max Planck Institute for Solid State Research, Heisenbergstrasse 1, 70569 Stuttgart, Germany 10Department of Physics and Department of Advanced Materials, University of Tokyo, 7-3-1 Hongo, Tokyo, 113-0033, Japan
Child Speech Disorder Detection with Siamese Recurrent Network Using Speech Attribute Features

Acoustics-based automatic assessment is a highly desirable approach to detecting speech sound disorder (SSD) in children. The performance of an automatic speech assessment system depends greatly on the availability of a good amount of properly annotated disordered speech, which is a critical problem particularly for child speech. This paper presents a novel design of child speech disorder detection system that requires only normal speech for model training. The system is based on a Siamese recurrent network, which is trained to learn the similarity and discrepancy of pronunciations between a pair of phones in the embedding space. For detection of speech sound disorder, the trained network measures a distance that contrasts the test phone to the desired phone and the distance is used to train a binary classifier. Speech attribute features are incorporated to measure the pronunciation quality and provide diagnostic feedback. Experimental results show that Siamese recurrent network with a combination of speech attribute features and phone posterior features could attain an optimal detection accuracy of 0.941.
An Empirical Analysis of High Frequency Intraday Stock Returns : Evidence from DowJones and NASDAQ Indices

Abstract This paper presents empirical evidence on the properties of high frequency data of stock returns. We employ both time series and panel data from the Dow Jones Industrial Average (DJIA) and the NASDAQ 10-minute intraday intervals from Aug. 1, 1997, to Dec. 31, 2003. Our findings indicate that the statistical properties are highly influenced by the opening returns that contain overnight and non-regular information. The stylized fact of high opening returns tends to generate significant autocorrelation. While examining the AR(1)-GARCH(1,1) pattern across time and frequency, we find consistent negative AR(1) of 10-minute and 30-minute frequencies for the DJIA, positive AR(1) for the NASDAQ stock returns, and no obvious pattern beyond the 30-minute return series. By examining the dynamic conditional correlation coefficients between the DJIA and the NASDAQ over time, we find that the correlations are positive and fluctuate mainly in the range of 0.6 to 0.8. The variance of the correlation coefficients has been declining and appears to be stable for the post-2001 period. By checking the conditions for a stable Lévy distribution, both the DJIA and the NASDAQ can converge to their respective equilibriums after shocks without relying on external regulation or intervention.
Increased Retrieval Performance using Word Sense Discrimination

We show that Mutual Information between word pairs can be successfully used to discriminate between word senses in the query translation step of Cross Language Information Retrieval. The experiment is conducted in the context of Amharic to French Cross Language Information Retrieval. We have performed a number of retrieval experiments in which we compare the performance of the sense discriminated and non-discriminated set of query terms against a ranked document collection. The results show an increased performance for the discriminated queries compared to the alternative approach, which uses the fully expanded set of terms.
Experimental Comparison of ASCII Art Extraction Methods : a Run-Length Encoding based Method and a Byte Pattern based Method

Pictures consisting of computer characters are called ASCII art. They are widely used in computer texts because they enrich expression in texts. To deal with texts including ASCII art objects, ASCII art extraction methods, which detect ASCII art objects in a given text, are now demanded. For example, such methods are needed to find ASCII art objects in texts for sentiment analysis based on ASCII art objects. Such methods are also needed to remove ASCII art objects from texts in preprocess for natural language processing because non-verbal texts of ASCII art makes texts noisy. Our research group and another research group independently proposed two different ASCII art extraction methods, which are a run-length encoding based method and a byte pattern based method respectively. Both of the methods use ASCII art recognizers constructed by machine learning algorithms, but they use different attributes of texts. In this paper, we compare the two methods by ASCII art extraction experiments where training texts and testing texts are in English and Japanese. According to our experimental results, the two methods are competitive if training texts and testing texts are in a same set of languages, but the run-length encoding based method works better than the byte pattern based method if training texts and testing texts are in different sets of languages.
Repetitive transcranial magnetic stimulation significantly influences the eating behavior in depressive patients

Background Depressive syndrome is one of the most common of psychiatric diseases and is ranked as the largest single contributor to global disability. Depression worsens the treatment outcomes of comorbid conditions and is a predictor of an increased mortality rate. Frequent comorbidities accompanying depressive syndrome are eating disorders (ED). The novel brain stimulation technique termed repetitive transcranial magnetic stimulation (rTMS) has been developed as a clinical tool to treat depression. Simultaneously the effect of rTMS has been studied on ED. Purpose The aim of this study was to monitor the correlation between the improvement in depressive symptoms and changes in eating behavior after rTMS treatment, and potential possibility of the utilization of rTMS in the treatment of these frequent comorbid conditions. Methods To map the change in eating behavior, this study follows the changes in answers 5 and 7 in the Zung Self-Rating Depression Scale. The patients were treated with high-frequency rTMS focused on the left dorsolateral prefrontal cortex. Results We observed a significant change in both questions. At the same time, the change in both questions correlates with a variance in the overall depressive symptoms. Conclusion The rTMS treatment of depressive syndrome resulted in significant clinical improvements, including changes in eating behavior.
Simultaneous Detection and Localization of a Wake-Up Word Using Multi-Task Learning of the Duration and Endpoint

This paper proposes a novel method for simultaneous detection and localization of a wake-up word using multi-task learning of the duration and endpoint. An onset of the wake-up word is estimated by going back in time by an estimated duration of the wake-up word from an estimated endpoint. Accurate endpoint estimation is achieved by training the network to fire only at the endpoint in contrast to the entire wake-up word. The accurate endpoint naturally leads to an accurate onset, when it is used as a basis to calculate an onset with an estimated duration that reflects the whole acoustic information over the entire wake-up word. Experimental results with real-environment data show that a relative improvement in accuracy of 41% for onset estimation and 38% for endpoint estimation are achieved compared to a baseline method.
Historic Document Retrieval : Exploring Strategies for 17 th Century Dutch

In this thesis, strategies are explored to retrieve 17th century Dutch documents for modern Dutch queries. Three appraches are proposed, based on different views on historic languages. In addition, a new topic set is constructed. The first approach treats Historic Document Retrieval as monolingual IR. Tokenization methods, including stemming, decompounding and n-gramming, are used to deal with the linguistic variations. The second approach uses the SoundEx algorithm to translate words into phonetic codes. The final approach treats HDR as a form of Cross-Language Information Retrieval (CLIR). Language resources, created by M. Koolen in a related research, are used to translate the documents into the query language and vice versa. The main finding is that Historic Document Retrieval for 17th century Dutch should be treated as a form of Cross-Language Information Retrieval. The best results are obtained by combining high-quality translation resources with effective tokenization methods.
Influence of bio-preparation on cutting characteristics of cannabis residues.

The aim of this work is to determine the influence of bio-preparation for cutting mechanical characteristics of cannabis plant residues, depending on the biological preparation action period and compare the research results with the same researches obtained in natural conditions. The influence of bio-preparation on cannabis residues cutting with different knives was determined. Experimental research in the physicalmechanical properties of plant residues was conducted at the Institute of Agricultural Engineering and Safety of Aleksandras Stulginskis University, using the experimental research machine “Instron 5960”. The results of the experimental research showed that the forces required for cutting of cannabis plant residues are lower using biological preparation than without it. Using an angled knife for cannabis residues cutting left on the soil surface less force is needed than using a vertical knife. Summarising it can be asserted that many factors such as the type of the plant, the time lying on the soil, biological preparation and its action period, constructional parameters of the cutting knives and other factors influence the mechanical characteristics of plant residues cutting forces.
Alignment of Monolingual Corpus by Reduction of the Search Space

Monolingual comparable corpora annotated with alignments between text segments (paragraphs, sentences, etc.) based on similarity are used in a wide range of natural language processing applications like plagiarism detection, information retrieval, summarization and so on. The drawback wanting to use them is that there aren’t many standard corpora which are aligned. Due to this drawback, the corpus is manually created, which is a time consuming and costly task. In this paper, we propose a method to significantly reduce the search space for manual alignment of the monolingual comparable corpus which in turn makes the alignment process faster and easier. This method can be used in making alignments on different levels of text segments. Using this method we create our own gold corpus aligned on the level of paragraph, which will be used for testing and building our algorithms for automatic alignment. We also present some experiments for the reduction of search space on the basis of stem overlap, word overlap, and cosine similarity measure which help us automatize the process to some extent and reduce human effort for alignment.
ANATOMICAL AND PHYSIOLOGICAL EFFECTS OF CADMIUM IN AQUATIC PLANT HYDRILLA VERTICILLATA

The current study was conducted to investigate the anatomical and physiological effects of cadmium in Hydrilla verticillata and plant response when exposed to cadmium metals from (January to March 2017). Hydrilla verticillata was used to expose to different concentrations (0.5, 1, 3, 6 mg / l) for cadmium cd + 2 for 15 days laboratory during days (1, 7 and 15). The physiological tests were measured including (Total chlorophyll content, chlorophyll a, b, protein content, catalase enzyme, Superoxide dismutase (SOD)) and anatomical changes showed by preparation tissues slides for Leaves of plant. The highest values of cadmium was recorded during the experimental period in Hydrilla verticillata Leaves and highest proportion of removal ratio of the metals was (99.4%) at (3) mg / l during the 15th day. The bioaccumulation factor (BCF) of the Cd+2in the plant Leaves recorded the highest value at 0.5 mg / l during the 15th day. The current study showed a decrease in protein content during the experiment period, and a gradual increase in the SOD values during the experimental period compared to the control. The values of the efficiency of catalase enzyme of Cd+2 were observed to be the highest during the 7th day and decreased in the 15th day at concentrations 6 mg / l. The anatomical changes of plant showed increased air spaces and small area and mesophyll cells occupied the Leaves center and epidermis cells increased in thickness at 0.5 mg/l of metal, while at 6 mg/l decreased in thickness of Leaves and air space decreased in number and increased in the area and the mesophyll cells has been degradation and epidermis cells increased in thickness. The study concluded that the high concentration of heavy metals was caused by the dissolution of plant cells and plant death.
Balance Changes in Trained and Untrained Elderly Undergoing a Five-Months Multicomponent Training Program

Balance is a main focus of elderly activity programs which can be assessed by functional tests or stabilometry platforms. Our study aims to compare balance-changes in trained (TRA) and untrained (UNT) elderly following a 5-month Multi-Component Training Program (MCTP), twice a week, one hour per day. 10 TRA (>2-years) and 9 UNT (first year) performed the Romberg ́s test (Open-Eyes 30 seconds/Closed-Eyes 30 seconds ratio) on a stabilometry platform (BT4, Hur Labs). COP displacement (Trace Length: TL) and sway area (C90) were registered twice PRE (1&2), POST (3&4) and 3 months later (Detraining: 5&6) the EFAMUV© program, a Cognitive MCTP based on gait training and Dual-Task neuromuscular proposals in enriched environments. Regarding Open-Eyes, Bonferroni post-hoc comparisons showed significant group-differences in TL for 1, 2, 5 & 6 sample conditions, and a slight trend toward significance in C90 1&5. TL also showed significant group-differences in Closed-Eyes 1, 5 & 6, while C90 only in 5 & 6 Closed-Eyes. Balance indicators TL and C90 show a different way regarding the training status. A 5month MCTP reduces differences, but detraining quickly affects UNT. Although effective, short multicomponent interventions could lead to early worsening, so the ratio training-detraining might be considered in untrained elderly population.
Multimodal Response Obligation Detection with Unsupervised Online Domain Adaptation

Response obligation detection, which determines whether a dialogue robot has to respond to a detected utterance, is an important function for intelligent dialogue robots. Some studies have tackled this problem; however, they narrow their applicability by impractical assumptions or use of scenario-specific features. Some attempts have been made to widen the applicability by avoiding the use of text modality, which is said to be highly domain dependent, but it decreases the detection accuracy. In this paper, we propose a novel multimodal response obligation detector, which uses visual, audio, and text information for highly-accurate detection, with its unsupervised online domain adaptation to solve the domain dependency problem. Our domain adaptation consists of the weights adaptation of the logistic regression for every modality and an embedding assignment for new words to cope with the high domain dependency of text modality. Experimental results on the dataset collected at a station and commercial building showed that our method achieved high response obligation detection accuracy and was able to handle domain change automatically.
THE ROLE OF KNOWLEDGE MANAGEMENT IN ACHIEVING SUSTAINABLE COMPETITIVE ADVANTAGE IN BUSINESS

Companies are struggling to gain sustainable competitive advantage in order to survive among aggressive huge competitors. To achieve that, companies must know how to create, share and use the knowledge through the company and aligning it to the company strategy and process as well. Besides, managers have to realize which knowledge strategy should be chose to improve the company’s activities to gain sustainable competitive advantage. This is a case study that attempt to demonstrate how companies use organizational knowledge and knowledge management to gain sustaining competitive advantage. Knowledge Management Networking Value chain theory has been applyied to explain how the value of a knowledge network increases as the number of the members increases in Toyota. Explaining strategies that Toyota adopted to create and transfer knowledge to subsidiaries abroad in order to give a chance to local markets to create knowledge in foreign markets. In the end of this study, it can be determine how knowledge management concept is a necessary tool to gain competitive advantage for the companies especially automotive industry. KeywordsــــــKnowledge Management, Competitive Advantage, Organizational Knowledge, Knowledge Creation, Knowledge Sharing.
Position Tracking of a Multicopter using a Geometric Backstepping Control Law

In this paper a position tracking controller for a multiroto r helicopter is presented. The controller design exploits the fact that for position tracking, the control of the whole attitude is not needed, but only the control of the body-fixedz-axis. This results in a position controller which is independent o f the heading controller. This is achieved by introducing the thrust vector as a system ’ state, i.e. using the body-fixedz-axis as a reduced attitude parameter and extending the thru st inputT dynamically. This parameter choice also avoids drawbacks o f local attitude parameterizations like singularities or unwinding and thus maxi mizes the flight envelope. The position controller is designed using a three-step back stepping control law, such that no time-scale separation is needed. Furthermore, two h eading controllers are proposed.
HORIZONTAL DIPHTHONG SHIFT IN NEW ZEALAND ENGLISH

The diphthongs PRICE and MOUTH in New Zealand English have been characterised as showing ‘diphthong shift’ and ‘glide weakening’. Like most analyses of diphthongs, previous studies have focussed on changes in the qualities of two temporally fixed targets: the nucleus and the offglide. We model changes in the full formant trajectories of PRICE and MOUTH over a period of 130 years. We first present results from Generalised Additive Models that reveal substantial ‘horizontal’ restructurings in the timing of the trajectories alongside expected ‘vertical’ shifts in nucleus and off-glide targets. We then use computational methods to capture these horizontal changes by identifying points of inflection in F1 and F2 trajectories. The timing of these inflection points moves significantly later for both vowels. We argue that changes in trajectory timing are a significantly overlooked aspect of changing diphthong production.