Miracle-dz/UniFAR-FTUs huggingface dataset:
Acquiring phrasal lexicons from corpora

This thesis deals with the acquisition from corpora of information about the phrasal lexicon. While varying greatly in their treatment of such items, all schools of linguistic thought acknowledge that the lexicon contains not only single words, but a consider¬ able number of multiword sequences (multiword expressions or MWEs). As for indi¬ vidual words, an adequate description of MWEs must be based on the systematic study of real usage, which can best be achieved with the use of corpus data. However, lex¬ icographers cannot manually inspect every combination of words in the corpus with a view to deciding whether that phrase should be included in the lexicon. There is therefore considerable need for well-motivated ways of automatically identifying units of interest. We begin this thesis by looking at the range of arguments that have been made for the inclusion of different kinds of multiword expression in the lexicon. We iden¬ tify arguments for inclusion made on the separate grounds of frequency, syntax and meaning. Subsequent chapters look at acquiring information about these three differ¬ ent dimensions, and demonstrate that different varieties of expression require different techniques. In chapter three, we look at the relative frequency of multiword sequences. We consider arguments that MWEs are too inconsistent in occurrence for their frequency profile to be adequately described using existing corpora. We provide experimental ev¬ idence to the contrary, showing that counts for sequences of up to at least length seven are as stable as for individual words of equivalent frequency. We further show that these counts are informative, by providing evidence that they are reflected in speakers' knowledge of the language. In chapter four, we look at the problem of syntactically fixed units. The linguis¬ tic literature contains considerable evidence for the existence of phrases that do not allow one or more syntactic variation that we would expect given their phrase type and consequently require phrasal lexical entries. We present a method for measuring the syntactic flexibility of instance of one phrase type and use this to rank items ac¬ cording to their fixedness. We provide evidence that this technique highlights a set of phrases that are not only valid MWEs, but crucially could not be identified purely on the grounds of relative frequency of occurrence. In chapter five, we look at the phenomena of non-compositionality. Languages contain a great many units whose meaning cannot be derived analytically from the meanings of their component words. We look here at the example of the verb-particle construction. Building on previous work, we use lexical context to model the meaning of words and phrases and show that by quantifying the similarity between the contexts of phrases and the contexts of their component words across the rest of the corpus, we can usefully identify those verb-particle combinations whose meaning cannot be analysed compositionally.
A case of systemic lupus erythematosus complicated by subclinical Cushing’s syndrome: case report

Abstract An 18-year-old female was diagnosed with subclinical Cushing’s syndrome (CS) due to a left adrenal adenoma. When she was 20 years old, she developed lupus nephritis. She was treated with high-dose prednisolone (PSL) and soon developed the symptoms of CS. When she was 25 years old, we evaluated her serum glucocorticoid level while she continued to take oral PSL. The result suggested her CS was affected by both the oral PSL and the endogenous cortisol secreted by the adrenocortical adenoma, which was therefore resected. Seven months after the operation, the patient’s body weight was decreasing, and her SLE remained in clinical remission. CS complicated by SLE is rare, and the decision to surgically remove an adrenal tumor in such a case is even more rare.
Upper Gastrointestinal Manifestation of Bezoars and the Etiological Factors: A Literature Review

A gastric bezoar is a compact mass of indigestible foreign materials that accumulate and consolidate in the stomach; however, it can be found in other sites of the gastrointestinal tract. The causative manner of this condition is complex and multifactorial. The main purpose of the review was to raise awareness among clinicians, particularly gastroenterologists, that patients with certain risk factors or comorbid conditions are predisposed to gastric bezoar formation. Early diagnosis and prompt intervention are crucial to avoid bezoar-induced complications. Upper gastrointestinal endoscopy is the standard diagnostic and therapeutic method for gastric bezoars. However, for large size bezoars, surgical intervention is needed.
An Enhanced Approach for the Prioritisation in Patent Ductus Arteriosus (PDA) Services Using Data Mining Techniques

The past few decades have witnessed a huge increase in the number of heart disease patients globally. An estimated 17.7 million people died from Cardio-Vascular Diseases (CVDs) in 2015, representing 31% of all global deaths. Saudi Arabia is no exception when it comes to the growing number of CVDs patients. The most common CVDs in Saudi Arabia is Patent Ductus Arteriosus (PDA), which is a persistent opening between two major blood vessels leading from the heart. Unlike many other fields of medicine, PDA is timerelated and cannot be delayed. Thus, there is a need to have a Decision Support System (DSS) that can analyze the crucial statistics in deciding the level of urgency for each child that requires PDA surgery. This research proposes an approach to classify the PDA patients according to their urgency level based on their current conditions and the results of scans and tests they have undergone. An enhanced approach, which uses Data Mining (DM) techniques, is proposed to manage waiting lists and determine the priority among patients, as well as diagnosis of certain diseases. This approach aims to support early prevention and intervention to increase life expectancy and well-being of PDA patients. Our proposed approach achieved an accuracy of 99.15%. KeywordsData Mining (DM); Healthcare; Patent Ductus Arteriosus (PDA); Waiting Lists Management.
Are the Fitzpatrick Skin Phototypes Valid for Cancer Risk Assessment in a Racially and Ethnically Diverse Sample of Women?

The Fitzpatrick Skin Phototypes (FSP) were developed to classify skin color and response to ultraviolet radiation. FSP are used clinically to assess risk for sunburn and skin cancer. Our aim was to determine the criterion-related validity of self-reported FSP when compared with skin color and sunburn history, controlling for age, race/ethnicity, and seasonality/geography. We performed a secondary analysis of data (N=466) from an observational study. The racial/ethnic composition of the sample was 45% White/White Hispanic (WWH), 40% Black/Black Hispanic (BBH), and 15% Other Identities. Outcome measures were self-reported FSP and sunburn history, as well as physiological measures of skin color (L* lightness/darkness, a* redness/greenness, b* yellowness/blueness). Correlation between FSP and L* was -. 77 (95% CI -.81, -.73; P<.001). Although 60% of the variance in FSP was accounted for by L* values for the entire sample, only 5% of the variance was accounted for among BBH participants (r=-.23), and up to 30% for WWH/Other Identity participants (r=-.48 and -.52). Multiple regression analysis indicated L* and b* values, sunburn history, and race/ethnicity, but not geography/seasonality or a* values significantly and collectively accounted for 72% of the variance in FSP. While the criterion validity of FSP was established by the strong relationship between L* values and FSP for the entire sample, when examined at the level of individual racial/ethnic subgroups, criterion validity of FSP was not demonstrated. When self-reported FSP are used for clinical skin assessment and sun cancer screening, they provide a restricted range of options for people with darker skin that does not capture variations in their skin color. Inaccuracy of clinical data may lead to unequal treatment or inadequate cancer risk assessment.
On the Use of Convolutional Neural Networks for Specific Emitter Identification

Specific Emitter Identification (SEI) is the association of a received signal to an emitter, and is made possible by the unique and unintentional characteristics an emitter imparts onto each transmission, known as its radio frequency (RF) fingerprint. SEI systems are of vital importance to the military for applications such as early warning systems, emitter tracking, and emitter location. More recently, cognitive radio systems have started making use of SEI systems to enforce Dynamic Spectrum Access (DSA) rules. The use of pre-determined and expert defined signal features to characterize the RF fingerprint of emitters of interest limits current state-of-the-art SEI systems in numerous ways. Recent work in RF Machine Learning (RFML) and Convolutional Neural Networks (CNNs) has shown the capability to perform signal processing tasks such as modulation classification, without the need for pre-defined expert features. Given this success, the work presented in this thesis investigates the ability to use CNNs, in place of a traditional expert-defined feature extraction process, to improve upon traditional SEI systems, by developing and analyzing two distinct approaches for performing SEI using CNNs. Neither approach assumes a priori knowledge of the emitters of interest. Further, both approaches use only raw IQ data as input, and are designed to be easily tuned or modified for new operating environments. Results show CNNs can be used to both estimate expert-defined features and to learn emitter-specific features to effectively identify emitters. On the Use of Convolutional Neural Networks for Specific Emitter Identification
A Quantitative Risk Analysis of the Health Effects of Construction Dust on Patients and Workers

—Aging of the world’s population, coupled with improvements in health care management and medical techniques continues to drive the increasing cost of medical treatment for the United States. A secondary and related cost is the Hospital Acquired Infections (HAI) that strike approximately 2 million patients in the USA each year. 100,000 patients will die each year from these secondary infections. A problem that has developed since the 1970s is a rise in secondary fungal infections for immune compromised patients, who are surviving longer. Fungal infections are nasty and very hard to treat, with a high mortality rate. There are several vectors or systems that move fungi into buildings, these include dust from construction sites and the outside space to the hospital. Careful control of dust is needed to minimize the risk to patients and workers during construction at hospitals. This paper represents part of a long running study at our university into dust movement into buildings. The goal is to develop a computational air, dust and fungi movement model for the problem to assist the statistical analysis of fungi movement rates into buildings. The objective of this paper’s research is to measure the flow of air through closed doors in a typical institutional building. The long term goal is to provide a mathematical model for air and dust movement through a closed door, to be part of the global model.
Investigation on deep learning for off-line handwritten Arabic Character Recognition using Theano research platform

The recognition of Arabic writing is still an important challenge due to its cursive nature and high topological variability. Traditional machine-learning techniques required careful engineering and considerable domain expertise to transform raw data into a feature vector from which the classifier could classify the input pattern. In recent years, deep learning approach has acquired a reputation for solving many computer vision problems, and its application to the field of Handwritten Arabic Character Recognition (HACR) has been shown to provide significantly better results than traditional methods. In this work, we investigate the applicability of Deep Convolutional Neural Network on the recently proposed database, referred to as OIHACDB. The proposed model normalizes the handwritten character images and then employs Deep Convolutional Neural Network to classify them. The model was trained under Theano framework with dropout as a regularization technique to avoid over-fitting to give a better generalization performance. Our results shown satisfactory recognition accuracy (97.32%) and outperform some other prominent exiting methods.
Recommendations for Assessment and Management of Health-Related Quality of Life in Patients with Mucopolysaccharidoses in Latin America

Mucopolysaccharidoses (MPS) constitute a heterogeneous group of rare genetic disorders caused by enzymatic deficiencies that lead to the accumulation of glycosaminoglycans (GAGs). Clinical observations suggest a health-related impairment in quality of life in patients with MPS. Professionals with extensive experience in the care of patients with inborn errors of metabolism, such as MPS, held a meeting in April 2017 to discuss and propose recommendations for the evaluation and management of quality of life in MPS patients in Latin America. In the light of this scenario, the present work summarizes the content of the discussions and presents the recommendations produced at the meeting. The panel had suggested the use of the following tools for the assessment of health-related quality of life (HRQoL): Children’s Health Assessment Questionnaire (CHAQ) for children and patients unable to express their feelings, Health Assessments Questionnaire (HAQ) and EuroQol 5 Domains (EQ-5D) scales for adult patients. Based on the scores verified in these scales, the panel proposes interventions that aim reducing the impairment of the quality of life in patients with MPS disorders.
Language-Specific Dysgraphia in Persian Patients with Right Brain Stroke: Influence of Visuospatial Neglect and Rehabilitation

Background: Writing is a human communication tool. No disability behavioral assessment of dysgraphia due to stroke-induced neglect has been conducted in Iran. Objectives: We investigated rehabilitation of dysgraphia in patients with stroke-related neglect in Persian language- speciﬁc constructive errors of writing. Methods: All patients were suﬀering from stroke-induced visual neglect. Five patients were evaluated for dysgraphia in a spontaneous writing task before and after rehabilitation without writing practice for 10 sessions with prism adaption (PA). Dysgraphia wasclassiﬁedintovisuospatialomissionerror,visuospatialdestructionerror,visuospatialsizeerror,visuospatialtiltingerror,poor handwritingstyle,visuospatialdistanceerror,andvisuospatialperseveration(addition)error. Neglectwasevaluatedusingthestar cancellation test (SCT), and line bisection test (LBT) and activities of daily living (ADL) was assessed by the Barthel index (BI) and the Catherine Bergego scale (CBS). Results: All patients showed signiﬁcant improvement in dysgraphia (measured using spontaneous writing test), ADL (measured usingCBSandBI),andneglect(measuredusingLBTandSCT)(P< 0.05). Visuospatialdestructionerrorswerethemostfrequentand visuospatial omission errors were the least frequent errors. Conclusions: PA is a potential eﬀective strategy in stroke rehabilitation of dysgraphia, visuospatial neglect and ADL. Unilateral spatial neglect and rehabilitation improves dysgraphia in Persian language speaking patients with right brain stroke.
Increased expression of ubiquitin C-terminal hydrolase L1 in astrocytomas of ascending grades

Background: The ubiquitin-proteasome pathway controls the monitoring and degradation of important proteins and is involved in several cellular processes, such as development, differentiation, and transcriptional regulation. Recent evidence has shown that ubiquitin carboxy-terminal hydrolase-L1 (UCH-L1), a member of the deubiquitinating enzyme family that removes ubiquitin from protein substrates, is overexpressed in many types of cancer. Aim: This study thus examined the expression of UCH-L1 in human astrocytoma tissues. Material and methods: Formalin-fixed, paraffin-embedded astrocytoma samples were obtained from 40 patients, after which histopathological examination, typing, and grading were performed. The study group included 10 histologically normal brain tissues, which served as the control group, and 10 WHO grade II, 10 WHO grade III, and 10 WHO grade IV (glioblastoma) samples. Normal brain tissue samples were obtained from the histologically normal, non-tumoral portion of the pathology specimens. UCH-L1 expression was evaluated using quantitative reverse transcription-polymerase chain reaction and immunohistochemistry. Results: Astrocytoma tissues exhibited higher UCH-L1 expression compared to the control group. UCH-L1 overexpression increased significantly together with the increase in astrocytoma grades (from II to IV). Conclusion: UCH-L1 could be a good diagnostic and therapeutic marker for determining astrocytoma development and progression.
Salivary Biomarkers: A Periodontal Overview

4BDS PG Student Sudha Rustagi College of Dental Sciences and Research, Faridabad, Haryana ABSTRACT The current clinical diagnostic criterias which were introduced almost half a century ago continue to function as the basis of oral diagnosis in today’s clinical practice. Evolvement with time is now brought us to the era of biomarkers. It’s a new paradigm for periodontal diagnosis which is of immense benefit in managing periodontitis patients. Biomarkers are tell – tale molecules that can be used to monitor health status, disease onset, treatment response and outcome.
Relation Between SF-36, mHAQ Scores and Disease Activity in Rheumatoid Arthritis

Objective: To investigate the relationship between quality of life (QOL) and disease activity in patients with rheumatoid arthritis (RA). Methods: 200 patients with RA were included in the study. Data were obtained by questionnaires and laboratory investigation. Disease Activity Score (DAS-28) was calculated for assessment of disease activity. Separate dimensions and physical and mental summary scores of the Short form Health survey (SF-36) and Health Assessment Questionnaire (HAQ) were compared to study the relationship between QOL and disease activity in patients with rheumatoid arthritis. Results: There was a significant association between DAS-28 and QOL scores. Conclusions: RA has a significant effect on the health related quality of life of patients, and its activity is ditectly related to worse QOL.
A distributed anomaly detection model for wireless sensor networks based on the one-class principal component classifier

The application of wireless sensor networks (WSN) is increasing with the emergence of the 'Internet of Things' concept. Nonetheless, the sensed data quality and reliability are sometimes affected by factors such as sensor's faults, intrusions and unusual events among others. Consequently, the real time and effective detection mechanisms of anomalous data are necessary for reliable decisions. In this paper, we proposed a one-class principal component classifier (OCPCC) based distributed anomaly detection model for WSN, which utilises the spatial correlations among sensed data in closed neighbourhoods. The feasibility of the model was validated using real world datasets and compared with local detection and some existing detection approaches from literature. The results show that the proposed model improves the detection rate of anomalous data compared to local model. A comparison with existing distributed models reveals the advantages of the proposed model in terms of efficiency while achieving better or comparable detection effectiveness.
Myelomatous Pleural Effusion as a Presenting Symptom: A Case Report

Myelomatous pleural effusion (MPE) is a rare complication in patients suffering from multiple myeloma (MM). Dyspnea is the predominant symptom in the clinical presentation. Poor prognosis and aggressive MM behavior have been linked to this condition. We describe a case of MPE in an undiagnosed MM patient who presented with respiratory discomfort and general malaise.
Protocol for the functional evaluation of the stomatognathic system.

Alterations in breathing, chewing and swallowing are considered risk factors for functional disorders on the stomatognathic system. Thus, there is a need to have a protocol for functional evaluation that contributes to systematize the processes and procedures, unifying criteria for diagnosis. The objective of this study was to design a Protocol for the functional evaluation of the stomatognathic system for the Postgraduate Clinic of Orthopedics of the School of Dentistry of the University of Zulia, Venezuela. In a first stage, a situational diagnosis was made. In a second stage, the documentary analysis technique was used, using the search engines Pubmed, Redalyc, SciELO and ScienceDirect. The third stage consisted in the elaboration of the protocol according to the consensus of the resident postgraduate professionals and the evidence found in the review of the scientific literature. The protocol was drawn up, defining its objectives, population, institutional resources and a systematic and detailed ordering of the procedures and tests to be applied for the evaluation of breathing, chewing and swallowing. This protocol will improve the quality of the evaluations and obtain reliable records of the patient’s clinical condition.
Effect of a multifaceted mobile technology enabled primary care intervention on cardiovascular disease risk management in rural Indonesia: a quasi-experimental study

41 Importance: Cardiovascular diseases (CVD) are the leading cause of disease burden in 42 Indonesia. Implementation of effective interventions for CVD prevention is limited. Objective: To evaluate whether a mobile technology-supported primary healthcare intervention would improve use of preventive drug treatment among people with high CVD 45 risk, vs usual care. Design: Quasi-experimental study involving four intervention and four control villages 47 conducted between September 2016 and March 2018. Median duration of follow-up was 12.2 48 months. 50 Participants: Residents aged ≥40 years were invited to participate. Those with high 51 predicted 10-year CVD risk (previous diagnosed CVD; systolic blood pressure (BP) >160 52 mmHg or diastolic BP >100 mmHg; 10-year predicted CVD risk ≥ 30%; or 10-year predicted 53 CVD risk of 20-29% and a systolic BP>140 mmHg) were followed. Intervention: A multi-faceted mobile technology-supported intervention facilitating 55 community-based CVD risk screening with referral, tailored clinical decision support for 56 drug prescription and patient follow-up. included change in BP
Protective and Therapeutic Effect of Green Tea (Camellia sinesis) against Rat Prostate Cancer

This investigation was conducted to evaluate the protective and therapeutic effect of green tea to ameliorate the deleterious effects of prostate cancer in rats. The obtained data revealed a significant elevation in tumor markers (PSA, TAP and PAP levels) after induction of cancer prostate in rats in comparison with the normal control one. Also, there was a significant decrease in total testosterone, free testosterone and DHEA-S concentrations, but the serum MDA level was increased significantly in rats with cancer prostate as compared with the corresponding levels in control rats. On the other hand, administration of green tea before or/and after induction of prostate cancer in rats led to a considerable improvement in the previous parameters but, their values did not revert to normal level. Any how, the results of the present investigation showed that the green tea when taken before and after induction of cancer prostate gave the prophylactic and therapeutic effects. The underlying mechanisms through which green tea counteracted cancer prostate were discussed.