Miracle-dz/UniFAR-FTUs huggingface dataset:
Clinical features of familial amyloid polyneuropathy carrying transthyretin mutations in four Chinese kindreds

Transthyretin‐related familial amyloid polyneuropathy (TTR‐FAP) is a rare hereditary disorder, characterized by a length‐dependent polyneuropathy and dysfunction of various organs. Wide phenotypic heterogeneity makes early diagnosis difficult. In this study, we reviewed the clinical and electrophysiological features of four unrelated Chinese families with genetically confirmed TTR‐FAP. Sequence analysis of TTR gene revealed the presence of four different mutations: Thr49Ala(p.Thr69Ala), Leu55Arg(p.Leu75Arg), Tyr116Ser(p.Tyr136Ser), and Ala36Pro(p.Ala56Pro) from six affected patients and two asymptomatic individuals. Two mutations, Thr49Ala(p.Thr69Ala) and Tyr116Ser(p.Tyr136 Ser), were detected in Chinese FAP patients for the first time. All affected patients manifested a progressive sensorimotor polyneuropathy starting in the lower limbs. The majority of the examined patients displayed cardiomyopathy and vitreous opacities. To avoid misdiagnosis, clinicians should consider screening for TTR variants in patients presenting with progressive polyneuropathy of undetermined origins.
Tail call elimination and data representation for functional languages on the Java virtual machine

The Java Virtual Machine (JVM) offers an attractive runtime environment for programming language implementers. The JVM has a simple bytecode format, excellent performance, multiple state-of-the art garbage collectors, robust backwards compatibility, and it runs on almost all platforms. Further, the Java ecosystem grants access to a plethora of libraries and tooling, including debuggers and profilers. Yet, the JVM was originally designed for Java, and its representation of code and data may cause difficulties for other languages. In this paper, we discuss how to efficiently implement functional languages on the JVM. We focus on two overall challenges: (a) how to efficiently represent algebraic data types in the presence of tags and tuples, option types, newtypes, and parametric polymorphism, and (b) how to support full tail call elimination on the JVM. We present two technical contributions: A fused representation of tags and tuples and a full tail call elimination strategy that is thread-safe. We implement these techniques in the Flix language and evaluate their performance.
Inorganic polyphosphate promotes cyclin D1 synthesis through activation of mTOR/Wnt/β‐catenin signaling in endothelial cells

Essentials Polyphosphate (polyP) activates mTOR but its role in Wnt/β‐catenin signaling is not known. PolyP‐mediated cyclin D1 expression (β‐catenin target gene) was monitored in endothelial cells. PolyP and boiled platelet‐releasates induced the expression of cyclin D1 by similar mechanisms. PolyP establishes crosstalk between mTOR and Wnt/β‐catenin signaling in endothelial cells.
Evaluation of terminologies acquired from comparable corpora: an application perspective

This paper describes a protocol for the evaluation of bilingual terminologies acquired from comparable corpora. The aim of the protocol is to assess the terminologies’added-value in a task of specialized translation. The protocol consists in having specialized texts translated in various situations: without any specialized resource, with an domain-related bilingual terminology or using Internet. By comparing the quality of the segments translated using these various resources, we are able to assess the impact of our bilingual terminologies on the quality of the translation.
Occupational health risk assessment of volatile organic compounds emitted from the coke production unit of a steel plant

In this study, cancer and non-cancer risks of exposure to volatile organic compounds in the coke production unit of a steel plant were evaluated. To determine individual exposure to benzene, toluene, xylene and ethylbenzene, personal samples were taken from the breathing zone of workers according to National Institute for Occupational Safety and Health (NIOSH) method 1501. Cancer and non-cancer risk assessment was performed, using US Environmental Protection Agency (US EPA) methods. Samples analysis showed that the concentration of benzene in the energy and biochemistry and the benzol refinement sections was higher than occupational exposure limits. The cancer risk for benzene in all sections was significantly higher than allowable limit; the non-cancer risk for benzene in all sections and toluene in the benzol refinement section was also higher than 1.0. In conclusion, the current control measures are not sufficient and should be improved for efficient control of occupational exposures.
Suspected vehicle detection for driving without license plate using symmelets and edge connectivity

This paper proposes a novel suspected vehicle detection (SVD) system for detecting vehicles moving on roads without a license plate. To detect vehicles from a still image, a symmelet-based approach is derived to determine their ROIs without using any motion feature. A symmelet is a pair of an interest point and its corresponding symmetrical one. This paper modifies the non-symmetrical SURF descriptor into a symmetrical one without adding any time complexity. Then, different symmelets can be very efficiently extracted from road scenes. The set of symmelets can be then used to locate the desired vehicle's ROI using a projection technique. To examine whether a license plate exists within this ROI, an edge connectivity scheme is then proposed to highlight possible character regions for plate detection. This SVD system provides two advantages; there is no need of background subtraction and it is extremely efficient for real-time ITS applications without using any GPU.
Towards smart agriculture using FIWARE enablers

With the introduction of paradigms like Internet of Things, Cyber Physical Systems and Cloud Computing, Smart Factories are becoming a central part of today's manufacturing systems. Even though there already are some solutions in the market the full potential for smart manufacturing hasn't yet been achieved. In order to fulfil the gap European researchers are developing vf-OS, a platform that aims to be the future reference in future factories operating systems. In this work is presented some preliminary results regarding the modules related to IoT, event processing, situational awareness and data harmonization that are being researched in the scope of vf-OS to achieve holistic solution for industries, specifically targeting the agriculture domain.
ASPHALT QUALITY AND YIELD PREDICTIONS FROM CRUDE OIL ANALYSES (WITH DISCUSSION)

Asphalt production has historically relied on fixed domestic crude sources and used average bulk measurements such as viscosity and penetration for quality control. With the introduction of foreign crudes and variable crude slates, standard bulk measurements have not been reliable. Paving technologies complain that even when bulk specifications are met, asphalts differ. Common complaints are that the "goodies" are no longer there and that roads are prematurely cracking. This paper describes how, in order to understand these problems, some rapid analytical techniques to measure crude oil and asphalt molecular size distributions and chemical types were developed. The objectives were to use these techniques to: (1) predict yields, viscosities-penetrations, and cracking potentials of asphalts obtainable from crude sources as functions of refining conditions; and (2) determine undesirable asphalt components or component distributions in badly cracked asphalt.
Fitting New Speakers Based on a Short Untranscribed Sample

Learning-based Text To Speech systems have the potential to generalize from one speaker to the next and thus require a relatively short sample of any new voice. However, this promise is currently largely unrealized. We present a method that is designed to capture a new speaker from a short untranscribed audio sample. This is done by employing an additional network that given an audio sample, places the speaker in the embedding space. This network is trained as part of the speech synthesis system using various consistency losses. Our results demonstrate a greatly improved performance on both the dataset speakers, and, more importantly, when fitting new voices, even from very short samples.
The BRCA2 c.68‐7T > A variant is not pathogenic: A model for clinical calibration of spliceogenicity

Although the spliceogenic nature of the BRCA2 c.68‐7T > A variant has been demonstrated, its association with cancer risk remains controversial. In this study, we accurately quantified by real‐time PCR and digital PCR (dPCR), the BRCA2 isoforms retaining or missing exon 3. In addition, the combined odds ratio for causality of the variant was estimated using genetic and clinical data, and its associated cancer risk was estimated by case‐control analysis in 83,636 individuals. Co‐occurrence in trans with pathogenic BRCA2 variants was assessed in 5,382 families. Exon 3 exclusion rate was 4.5‐fold higher in variant carriers (13%) than controls (3%), indicating an exclusion rate for the c.68‐7T > A allele of approximately 20%. The posterior probability of pathogenicity was 7.44 × 10−115. There was neither evidence for increased risk of breast cancer (OR 1.03; 95% CI 0.86–1.24) nor for a deleterious effect of the variant when co‐occurring with pathogenic variants. Our data provide for the first time robust evidence of the nonpathogenicity of the BRCA2 c.68‐7T > A. Genetic and quantitative transcript analyses together inform the threshold for the ratio between functional and altered BRCA2 isoforms compatible with normal cell function. These findings might be exploited to assess the relevance for cancer risk of other BRCA2 spliceogenic variants.
The use of digitized self-learning resources to enhance students' independent learning

Higher educational institutions aim to develop students who take responsibility of their own learning. Such students can manage and assess their own learning and they often perform better than others. Experts believe that one way to develop independent learners are through directed independent learning activities which students are required to complete with some or minimal supervision from instructors. This paper investigates students' perceptions on the use of digitized self-learning resources in enhancing students' independent learning. The participants of this study were 37 Chemistry students enrolled in the Australian Matriculation (AUSMAT) Programme at Sunway College, Malaysia. As part of their directed independent learning, participants were provided with paper-based self-learning material containing a compilation of examination questions on Oxidation and Reduction (Redox) chapter, marking key and solution videos provided in a QR code, as well as, similar past year questions for practice. Data collection tools were a survey questionnaire which consisted of 5-point Likert scale and open-ended questions and teacher reflective notes. Analysis of data revealed that even though most students favoured the use of digitized self-learning resources to support their learning, some were reluctant and preferred the use of more traditional methods of learning. The study provides valuable insights into the importance of preparing students for independent learning and the challenges in preparing digitized self-learning resources that would encourage students to become autonomous learners.
Electrodeposition of arrays of ZnO nanostructures and application to photoelectrochemical devices

ZnO nano/microstructures offer the opportunity to design new types of photoelectrochemical devices. Arrays of single crystal ZnO nanowires present very interesting properties to enhance the performance in these devices. A systematic study of the deposition of single crystal ZnO nanowire arrays from the oxygen electroreduction method is reported in order to gain a further insight into the nanowire growth mechanisms and to develop an efficient electrochemical method which allows tailoring the nanowire dimensions. The influence of deposition parameters such as zinc precursor and supporting electrolyte concentrations on the formation of a polycrystalline compact ZnO layer or a ZnO nanowire array, as well as on the dimensions of the single crystal nanowires is analyzed. The effect of the polycrystalline compact ZnO buffer layer on the nanowire nucleation process and therefore on the nanowire diameter and density is also discussed. The results show that electrodeposition is a versatile and cost-effective technique which allows growing ZnO single crystal nanowire arrays with tailored dimensions. The structural and optical properties of electrodeposited nanowire arrays are discussed. ZnO nanowires can be sensitized by the coating of a thin layer of CdSe. The ZnO/CdSe photoanode exhibits excellent photoelectrochemical properties and external quantum efficiency larger than 70 % are observed in ferri/ferrocyanide solutions.
A functional signal profiling test for identifying a subset of HER2-negative breast cancers with abnormally amplified HER2 signaling activity

The results of clinical trials evaluating the efficacy of HER2 inhibitors in patients with breast cancer indicate that the correlation between HER2 receptor levels and patient outcomes is as low as 50%. The relatively weak correlation between HER2 status and response to HER2-targeting drugs suggests that measurement of HER2 signaling activity, rather than absolute HER2 levels, may more accurately diagnose HER2-driven breast cancer. A new diagnostic test, the CELx HER2 Signaling Profile (CELx HSP) test, is demonstrated to measure real-time HER2 signaling function in live primary cells. In the present study, epithelial cells extracted fresh from breast cancer patient tumors classified as HER2 negative (HER2−, n = 34 of which 33 were estrogen receptor positive) and healthy subjects (n = 16) were evaluated along with reference breast cancer cell lines (n = 19). Live cell response to specific HER2 agonists (NRG1b and EGF) and antagonist (pertuzumab) was measured. Of the HER2− breast tumor cell samples tested, 7 of 34 patients (20.5%; 95% CI = 10%–37%) had HER2 signaling activity that was characterized as abnormally high. Amongst the tumor samples there was no correlation between HER2 protein status (by cell cytometry) and HER2 signaling activity (hyperactive or normal) (Regression analysis P = 0.144, R2 = 0.068). One conclusion is that measurement of HER2 signaling activity can identify a subset of breast cancers with normal HER2 receptor levels with abnormally high levels of HER2 signaling. This result constitutes a new subtype of breast cancer that should be considered for treatment with HER2 pathway inhibitors.
Estimating bradykinesia severity in Parkinson ' s disease by analysing gait through a waist-worn sensor

Bradykinesia is a cardinal symptom of Parkinson's disease (PD) and describes the slowness of movement revealed in patients. Current PD therapies are based on dopamine replacement, and given that bradykinesia is the symptom that best correlates with the dopaminergic deficiency, the knowledge of its fluctuations may be useful in the diagnosis, treatment and better understanding of the disease progression. This paper evaluates a machine learning method that analyses the signals provided by a triaxial accelerometer placed on the waist of PD patients in order to automatically assess bradykinetic gait unobtrusively. This method employs Support Vector Machines to determine those parts of the signals corresponding to gait. The frequency content of strides is then used to determine bradykinetic walking bouts and to estimate bradykinesia severity based on an epsilonSupport Vector Regression model. The method is validated in 12 PD patients, which leads to two main conclusions. Firstly, the frequency content of the strides allows for the dichotomic detection of bradykinesia with an accuracy higher than 90%. This process requires the use of a patient-dependant threshold that is estimated based on a leave-one-patient-out regression model. Secondly, bradykinesia severity measured through UPDRS scores is approximated by means of a regression model with errors below 10%. Although the method has to be further validated in more patients, results obtained suggest that the presented approach can be successfully used to rate bradykinesia in the daily life of PD patients unobtrusively.
Clinical and molecular characteristics of pulmonary sarcomatoid carcinoma

Background/Aims Pulmonary sarcomatoid carcinoma (PSC) is a poorly differentiated non-small cell lung cancer (NSCLC) that contains components of spindle or giant cells. Owing to its low prevalence, there are insufficient data regarding its clinical features, therapeutic strategies and prognosis. Methods The medical records of 26 patients diagnosed with PSC from January 2009 to June 2015 were reviewed and analyzed for clinicopathological characteristics, treatment modality, and outcomes. Results The median age was 69.5 years. Twenty-three patients (88%) were male. Twenty-four patients (92%) were smokers. The median time from symptom onset to diagnosis was one month. Eighteen patients (69%) were diagnosed at an advanced stage. Pleomorphic carcinoma was the most common subtype, and epidermal growth factor receptor (EGFR) mutation was positive in two of 11 patients. Among 13 patients tested for programmed death ligand 1 (PD-L1) immunohistochemistry assay, eight showed high expression of PD-L1. The median overall survival (OS) of all patients was 9.5 months. In total, 12 patients were treated with chemotherapy: nine with platinum-based doublet therapy, two with tyrosine kinase inhibitor, and one with docetaxel. Seven patients showed partial response or stable disease. The median OS and progression-free survival of patients who received chemotherapy were 8.7 and 2.8 months, respectively. Conclusions PSC was more common in males, smokers, and the elderly, with worse prognosis than ordinary NSCLC; chemotherapy response was favorable, and EGFR mutation status and PD-L1 expression may offer more therapeutic options.
Serum carboxypeptidaseA4 levels predict liver metastasis in colorectal carcinoma

Hepatic metastasis is the most critical prognostic factor for colorectal cancer (CRC), and early detection of CRC liver metastasis can significantly improve cancer patient outcomes. In this study, we examined the levels of CPA4 in CRC samples, and assessed the potential of serum CPA4 as a biomarker for predicting CRC liver metastasis. CPA4 positivity was observed in 68.4% (130/190) colorectal cancer tissues, and significantly correlated with Depth of invasion, Lymph node metastasis, Distant metastasis and Stage. In addition, high CPA4 expression was associated with poor overall survival, and was an independent prognostic marker in patients with CRC. In CRC serum samples, serum CPA4 concentrations in CRC-M1(S) patients (3717.89 ± 375.98 pg/mL) were significantly increased as compared to in CRC-M1(H) patients (3692.12 ± 261.51 pg/mL), CRC patients without liver metastasis (2480.47 ± 507.90 pg/mL) or healthy controls (2183.7 ± 621.7 pg/mL) (P < 0.05). Furthermore, high CPA4 concentration was significantly correlated with Distant metastasis, Lymph node involvement, Stage and poor overall survival of the patients with CRC. Logistic regression analysis revealed that serum CPA4 level and Lymph node metastasis were the significant parameters for predicting CRC liver metastasis. In leave-one-out-cross-validation, these two markers resulted in sensitivity (90.0%) and specificity (93.8%) for hepatic metastasis detection. Moreover, this combination could correctly classify 49 cases of the 50 CRC patients with heterochronous liver metastasis in an independent test set. Therefore, our results suggest that CPA4 is closely associated with CRC liver metastasis, and serum CPA4 concentration combined with lymph node involvement may be used as accurate predictors of liver metastasis in colorectal cancer.
Reduction of surface to line integrals in matrix elements for arbitrarily oriented surface elements: The vector green function

We present an approach allowing conversion of surface integrals (over planar surface elements) to line integrals, in evaluating matrix elements of the derivatives of the Helmholtz-equation Green function, in particular the vector Green function in electromagnetics. A general procedure is outlined and explicit expressions are provided in the static limit. In the latter case, the accuracy and the computational cost of the proposed technique are compared to those of a more conventional approach based on evaluating surface integrals of a known closed-form potential.
Framework for assessment of children’s social competence, with particular focus on children with brain injuries

ABSTRACT Children’s social competence is important for their general wellbeing and life satisfaction. Often it is an area identified as problematic for children brought to the attention of a psychologist, particularly for children with brain injuries. However, it can be difficult to pin down exactly where social difficulties lie, and therefore how best to help. The current article draws together the literature on social competence from brain injury and from more general developmental research. A hierarchical model is presented with three layers: social adjustment, social functioning, and social cognition. Additional factors likely to be relevant for children with brain injuries are noted. This framework can be used to guide psychologists’ casework around social competence, aiming to provide a practical and coherent structure for assessment that can then support formulation, person centred planning, and tailored interventions.
Situated Action: A Neuropsychologiwl Interpretation Response to Vera and Simon

Situated cognition research rejects the hypothesis that neurological structures and processes are similar in kind to the symbols we create and use in our everyday lives. The symbolic approach, as described by Vera and Simon (1993), conflates neurological stmctures and processes with physical representations that we perceive and manipulate in our environment (e.g., a journal article) and experiences of representing in our imagination (e.g., visualizing or talking to ourselves). This category error distorts the nature of perception, the nature of conceptual interpretation as we comprehend written plans, and in general the adaptive nature of every thought and action. At its heart, the symbolic approach confuses an agent's deliberated actionin sequences of behavior over time, as cycles of reperceiving and commenting (e.g., in speech, writing, drawing)-with what occurs within every ongoing coordination (Dewey, 1896/198 la). Put another way, the symbolic approach conflates "first-person" representations in our environment (e.g., utterances and drawings) with "thirdperson" representations (e.g., mappings a neurobiologist finds between