Miracle-dz/UniFAR-FTUs huggingface dataset:
A Comparison of Deep Learning Methods for Language Understanding

In this paper, we compare a suite of neural networks (recurrent, convolutional, and the recently proposed BERT model) to a CRF with hand-crafted features on three semantic tagging corpora: the Air Travel Information System (ATIS) benchmark, restaurant queries, and written and spoken meal descriptions. Our motivation is to investigate pre-trained BERT’s transferability to the domains we are interested in. We demonstrate that neural networks without feature engineering outperform state-of-the-art statistical and deep learning approaches on all three tasks (except written meal descriptions, where the CRF is slightly better) and that deep, attention-based BERT, in particular, surpasses state-of-the-art results on these tasks. Error analysis shows the models are less confident when making errors, enabling the system to follow up with the user when uncertain.
TEMPERATURE PRECISE CONTROL IN A LARGE SCALE HELIUM REFRIGERATOR

Precise control of operating load temperature is a key requirement for application of a large scale helium refrigerator. Strict control logic and time sequence are necessary in the process related to main components including a control load, turbine expanders and compressors. However control process sequence may become disordered due to improper PID parameter settings and logic equations, and causes temperature fluctuation, load augmentation or protection of the compressors and cryogenic valve function failure etc. The experimental study, PID parameters for temperature adjustment, in a large scale helium refrigerator of 2kW@20K at TIPC is present. The methods and rules of general parameter settings are revealed and the suitable control logic equations are discussed for temperature stabilization.
1 Transforming Growth Factor-β 3 Chitosan Sponge ( TGF-2 β 3 / CS ) Facilitates Osteogenic Differentiation of 3 Human Periodontal Ligament Stem Cells 4

Periodontal disease is the main reason for tooth loss in adults. Tissue engineering and 15 regenerative medicine are the advanced technologies used to manage soft and hard tissue defects 16 caused by periodontal disease. We developed a transforming growth factor-β3 chitosan sponge 17 (TGF-β3/CS) to repair periodontal soft and hard tissue defects. We investigated the proliferation 18 and osteogenic differentiation behaviors of primary human periodontal ligament stem cells 19 (hPDLSCs) to discuss the bioactivity and application of TGF-β3 in periodontal disease. We 20 separately used Calcein-AM/PI double-labeling or CM-Dil-labeling coupled with fluorescence 21 microscopy to trace the survival and function of the cells after implantation in vitro or in vivo. The 22 mineralization of osteogenic differentiated hPDLSCs was confirmed by measuring ALP activity and 23 calcium content. The levels of COL I, ALPL, TGF-βRI, TGF-βRII, and Pp38/t-p38 were tested using 24 Western blot to explore the mechanism of bone repair prompted by TGF-β3. When hPDLSCs were 25 inoculated with different concentrations of TGF-β3/CS (62.5–500 ng/mL), ALP activity was the 26 highest in TGF-β3 (250 ng/mL) group after seven days (P < 0.05 vs. control); the calcium content in 27 each group increased significantly after 21 and 28 days (P < 0.001 vs. control). The best result was 28 achieved in the TGF-β3 (500 ng/mL) group. All results showed that TGF-β3/CS can promote 29 osteogenic differentiation of hPDLSC and may be involved in the p38 MAPK signaling pathway. 30 TGF-β3/CS has the potential for application in the repair of incomplete alveolar bone defects. 31
Aircraft Preliminary Design : a windowless concept

This paper describes the preliminary design of a short-medium range windowless aircraft, with the aim to reduce fuselage weight. As a matter of fact, the aircraft weight reduction is the main element to reduce fuel consumption providing advantages in terms of operational costs reduction and environmental impact of the flight operations. An innovative solution based on OLED (Organic Light Emitting Diode) technology is considered to improve passengers’ comfort avoiding claustrophobic effects that can arise from the elimination of traditional windows. A traditional configuration is considered as reference: weight and cost reduction provided by the introduction of a windowless configuration are assessed by means of analytical study. Moreover, the preliminary design activity has been coupled with the development of a digital mock-up. A small-scale demonstrator of the selected configuration has been manufactured by means of a rapid prototyping technique.
GPU Accelerated Graph Analytics Using Abstract Sparse Linear Algebra

Large-scale graph analytics using conventional processing systems often involves prohibitively excessive runtimes. Phrasing graph operations as abstract linear algebra operations offers potential for leveraging backend processing engines that scale better on modern heterogeneous computing platforms. To achieve this goal, we present a language for graph analytics that allows users to write in a familiar, vertex-centric API while leveraging the computational power of many-core accelerators. Our prototype toolchain automatically employs abstract sparse linear algebra (ASLA) operations using custom semi-rings in order to maximize performance. We use a C++ EDSL to map the user’s algorithm to efficient, fused ASLA operations at compile time with no runtime overhead. Using this technique, we have implemented several algorithms, including single-source shortest path, PageRank and single-source widest path. With a GPU-accelerated linear algebra backend, we can achieve better than 500% speedup over a multi-core ASLA library, using real and synthetic datasets. Keywords—Graph Analytics, GPU Acceleration, Linear Algebra
Investigating novel therapeutic approaches for sporadic inclusion body myositis (sIBM)

Sporadic inclusion body myositis (sIBM) is the most common acquired muscle disease affecting adults over the age of 50. Although the aetiology of this disease remains unclear, there is evidence for both inflammatory and myodegenerative processes in sIBM muscle pathology. In particular, abnormal protein aggregation is characteristic of affected muscle, with inclusion bodies incorporating amyloid-beta precursor protein (β-APP) among many others. Therapeutic interventions tested to date for sIBM have targeted the immune system; but none have been beneficial and sIBM currently remains untreatable. In this study, an in vitro model of the degenerative pathology seen in sIBM was established by over-expressing β-APP in primary muscle cultures. This resulted in the formation of inclusion bodies immuno-reactive for β-APP and other sIBM-relevant proteins, as well as increased cytotoxicity, proteasome dysfunction, mitochondrial abnormalities and TDP-43 mis-localisation; all observed in sIBM patient muscle. The heat shock response (HSR) is an acute endogenous cytoprotective mechanism that responds to misfolded proteins. Up-regulation of the HSR was examined by treatment with Arimoclomol, a co-inducer of the HSR, which showed beneficial effects in this in vitro model of IBM by significantly improving cell survival and attenuating cellular pathology. Since proteasome dysfunction has been implicated in sIBM pathology, I also examined the effects of pharmacological inhibition of the proteasome on muscle cells in culture. Proteasome inhibition did not result in the appearance of several key features of sIBM, suggesting that this is not a suitable approach to modeling sIBM. However, treatment with Arimoclomol was seen to significantly improve proteasome function and cell survival in these experiments. Using the β-APP model, eight novel pharmacological agents, with known anti-aggregation properties, were subsequently screened and one agent was found to significantly ameliorate the disease outcomes established in this model. The results of this Thesis show that β-APP over-expression in vitro recapitulates many of the characteristic features of sIBM and can be used successfully to screen potential therapies. In particular, Arimoclomol and one novel agent have been identified as potential therapeutic agents for IBM.
Some Observations on the Structure , Type Frequencies and Spelling of English Compounds

This paper deals with the structure, type frequencies and spelling of English noun – noun compounds. On the basis of a corpus extracted from LDCE (2000), I note some regularities governing the structure, type frequencies and spelling of this type of English compounds. My main point is that the type frequencies and spelling of English compounds depend on the complexity of their constituents. The relevant generalization seems to be that spellers tend to insert a space in noun – noun compounds if any of its constituents is morphologically complex. In respect to the first constituent this tendency is particularly strong, so that solid compouds in English are overwhelmingly written with a monomorphemic first constituent. The exceptions to this generalization are not numerous and almost all can be accounted for in a principled way. The compound types which are easier to process are more frequent, and are also more often spelled solid. According to the proposed analysis of English compounds, solid compounds seem to differ from open compounds in four important features: spelling, morphological structure, type frequency and productivity.
OROGRAPHIC INFLUENCES ON VEGETATION AND BIOPROSPECTING POTENTIAL AT THE CONFLUENCE OF THE BAYAMO , GUAMÁ AND GUISA RIVERS

This paper is part of a plan to develop the Peña Prieta Institute to bio-prospect on family land between the Bayamo and the Guamá Rivers in the rain forests of the Sierra Maestra of old Oriente Province. These are the lands originally held by seven times wounded Mambí Colonel Don Benjamín Ramírez. On this land many desperate struggles took place during the Cuban Wars of Independence, and various conflicts of the Cuban Republican era, including the actions during the sad 1912 “Guerra de los Negros” and resistance against Batista in 1933-34 and 1957-58 (L. Daley manuscript in preparation).
Standardization of In-vitro Genetic Transformation Technique in Chickpea ( Cicer arietinum L . ) for Pod-borer Resistance

Here we report the establishment of an efficient Agrobacteriummediated genetic transformation in chickpea (Cicer arietinum L.) using cryIIAa gene of Bacillus thuringiensis. Precultured single cotyledonary node along with embryo axes (EA1C) were injected by Agrobacterium suspension of OD 600 = 0.3-0.5, co-cultivated for 48 h on precultured medium containing 0.5 mg l-1 TDZ and 400 mg l-1 Cefotaxime without selection pressure. For the selection of transformants 1000 mg l-1 kanamycin was employed on well established plants by using different explants from putatively transgenic plants. The percentage of the kanamycin resistant plants varied from 6.62 to 16.12%. The results of PCR, RT-PCR and further Southern blotting of genomic DNA of kanamycin resistant plants showed that the synthetic gene cryIIAa had been integrated into the genome of some transformed plants. The transgenic plants with cryIIAa gene of B. thuringiensis showed improved tolerance than the controls by insect bioassay. cryIIAa gene inherited in some transgenic lines as Mendelian segregation pattern. The results of the present study indicate that highest transformation frequency (15.05%) could be achieved by Agrobacteriummediated transformation.
1 Algorithms for Assistive Technology for Blind Pedestrians to Cross Roads Safely

In this article a traffic light recognition with status detection system is introduced. The system is evaluated from a generic point of view but the applications range from Intelligent Transportation System (ITS) to visual impaired and color vision deficiencies aid to safely cross streets. The algorithm is based on color segmentation in HSV color space. After that candidates reduction is performed using a pipeline approach to speed up the algorithm. Resulting candidates are input to feature extraction and support vector machine is then applied. For the training of the Support Vector Machine a database with images collected in Chicago is used. Unlike other works the purpose is to evaluate different performance according to the feature extraction. In particular HOG, HAAR and LBP features are compared. The purpose is also to create a database to be used from other researchers. The result is accurate and reliable provided that good quality images are input to the system. Keywords—Traffic Light Recognition; SVM; Driver Assistance Systems
BIO-MEDICAL DATA ACQUISITION AND TRANSMISSION USING BLUETOOTH TECHNOLOGY FOR MEDICAL APPLICATION

This paper presents the biological data acquisition and transmission for the remote monitoring of some severe diseases and disorders e.g. Diabetes and Cardiac activity. These types of patients have to need close and continual monitoring in order to prevent further damage. Patient monitoring and the acquired data are transmitted through wireless medium by using BLUETOOTH technology. Bio-signal can be acquired and high frequency noise cancellation also be processed with the help of MATLAB Digital Filter Design Tool (FDA Tool). Data or signal is transmitted to the patients’ mobile continually using BLUETOOTH. Security is the main problem in wireless transmission but it can be solved by using frequency hopping technique which is broadly used in BLUETOOTH technology and moreover, to increase the security level, we can use link level security where the security procedure initiates before the channel established.
Unsupervised Acoustic Segmentation and Clustering Using Siamese Network Embeddings

Unsupervised discovery of acoustic units from the raw speech signal forms the core objective of zero-resource speech processing. It involves identifying the acoustic segment boundaries and consistently assigning unique labels to acoustically similar segments. In this work, the possible candidates for segment boundaries are identified in an unsupervised manner from the kernel Gram matrix computed from the Mel-frequency cepstral coefficients (MFCC). These segment boundary candidates are used to train a siamese network, that is intended to learn embeddings that minimize intrasegment distances and maximize the intersegment distances. The siamese embeddings capture phonetic information from longer contexts of the speech signal and enhance the intersegment discriminability. These properties make the siamese embeddings better suited for acoustic segmentation and clustering than the raw MFCC features. The Gram matrix computed from the siamese embeddings provides unambiguous evidence for boundary locations. The initial candidate boundaries are refined using this evidence, and siamese embeddings are extracted for the new acoustic segments. A graph growing approach is used to cluster the siamese embeddings, and a unique label is assigned to acoustically similar segments. The performance of the proposed method for acoustic segmentation and clustering is evaluated on Zero Resource 2017 database.
FarsBase: The Persian knowledge graph

Over the last decade, extensive research has been done on automatic construction of knowledge graphs from Web resources, resulting in a number of large-scale knowledge graphs such as YAGO, DBpedia, BabelNet, and Wikidata. Despite that some of these knowledge graphs are multilingual, they contain few or no linked data in Persian, and do not support tools for extracting knowledge from Persian information sources. FarsBase is the first Persian multi-source knowledge graph, which is specifically designed for semantic search engines to support Persian knowledge. FarsBase uses a diverse set of hybrid and flexible techniques to extract and integrate knowledge from various sources, such as Wikipedia, Web tables and unstructured texts. It also supports entity linking, which allows integration with other knowledge graphs. To maintain a high accuracy for triples, we adopt a low-cost mechanism for verifying candidate knowledge by human experts, where the candidates for human verification are prioritized using different heuristics. FarsBase is being used as the semantic-search system of a Persian search engine and efficiently answers hundreds of semantic queries per second.
Title Associations between catecholaminergic , GABAergic , and serotonergic genes and self-reported attentional function in oncology patients and their family caregivers

Purpose of the research—Evaluate for associations between variations in genes involved in catecholaminergic, gamma-aminobutyric acid (GABA)-ergic, and serotonergic mechanisms of neurotransmission and attentional function latent classes. Patients and methods—This descriptive, longitudinal study was conducted at two radiation therapy departments. The sample included three latent classes of individuals with distinct trajectories of self-reported attentional function during radiation therapy, who were previously identified using growth mixture modeling among 167 oncology patients and 85 of their family caregivers. Multivariable models were used to evaluate for genotypic associations of neurotransmission genes with attentional function latent class membership, after controlling for covariates. Results—Variations in catecholaminergic (i.e., ADRA1D rs4815675, SLC6A3 rs37022), GABAergic (i.e., SLC6A1 rs2697138), and serotonergic (i.e., HTR2A rs2296972, rs9534496) © 2014 Elsevier Ltd. All rights reserved. Corresponding author. University of California, San Francisco; 2 Koret Way, Box 0610, San Francisco, CA 94143-0610, USA. Tel. : +1 415 476 9407; fax: +1 415 476 8899. chris.miaskowski@nursing.ucsf. edu (C. Miaskowski). 1Present address for John D. Merriman: School of Nursing, University of Pittsburgh, 3500 Victoria Street, CRE Room 364A, Pittsburgh, PA 15261, USA. Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. Conflict of interest – The authors have no conflicts of interest to declare. HHS Public Access Author manuscript Eur J Oncol Nurs. Author manuscript; available in PMC 2016 June 01. Published in final edited form as: Eur J Oncol Nurs. 2015 June ; 19(3): 251–259. doi:10.1016/j.ejon. 2014.11. 004. A uhor M anscript
ANALYSIS OF GENETIC DIVERSITY AMONG RAPESEED CULTIVARS AND BREEDING LINES BY SRAP AND SSR MOLECULAR MARKERS

The knowledge of genetic diversity is very important for developing new rapeseed (Brassica napus L.) cultivars. The genetic diversity among 77 rapeseed accessions, including 22 varieties and 55 advanced breeding lines were analyzed by 47 sequence-related amplified polymorphism (SRAP) and 56 simple sequence repeat (SSR) primers. A total of 270 SRAP and 194 SSR polymorphic fragments were detected with an average of 5.74 and 3.46 for SRAP and SSR primer, respectively. The cluster analysis grouped the 77 accessions into five major clusters. Cluster I contained spring and winter type varieties from Czech Republic and semi-winter varieties and their respective breeding lines from China. The 16 elite breeding lines discovered in Cluster II, III, IV and V indicated higher genetic distance than accessions in Cluster I. The principal component analysis and structure analysis exhibited similar results to the cluster analysis. Analysis of molecular variance revealed that genetic diversity of the selected breeding lines was comparable to the rapeseed varieties, and variation among varieties and lines was significant. The diverse and unique group of 16 elite breeding lines detected in this study can be utilized in the future breeding program as a source for development of commercial varieties with more desirable characters.
E-Governance in Public Transportation : U . P . S . R . T . C .-A Case Study

Abstract: As we know that an effective e-Governance will provide an efficient solution for most of the problems in many government and public sectors in India. Transportation sector is not the exception for the e-Governance. The use of Information and communication technology (ICT) in Transport sector causes drastic change in the exploration of various services, provided by Vahan and Sarathi projects. Vahan project supports all transactions related to vehicles such as issue registration certificate, fitness certificate, receipts and permits etc, whereas Sarathi issue’s Learner Licence, Permanent Driving Licence and conductor licence to the applicants. But this development in Transport sector is entirely different from the governance of State Road Transport Corporation. This paper highlights some feeble features in governance of the Uttar Pradesh State Road Transport Corporation (UPSRTC) which was found by an extensive survey, performed on commuters as well as officials of UPSRTC.
Tracking the New Zealand English NEAR/SQUARE Merger Using Functional Principal Components Analysis

Copyright © 2019 ISCA The focus of the study is the application of functional principal components analysis (FPCA) to a sound change in progress in which the SQUARE and NEAR falling diphthongs are merging in New Zealand English. FPCA approximated the trajectory shapes of the first two formant frequencies (F1/F2) in a large acoustic database of read New Zealand English speech spanning three different age groups and two regions. The derived FPCA parameters showed a greater degree of centralisation and monophthongisation in SQUARE than in NEAR. Compatibly with the evidence of an ongoing sound change in which SQUARE is shifting towards NEAR, these shape differences were more marked for older than for younger/mid-age speakers. There was no effect of region nor of place of articulation of the preceding consonant; there was a trend for the merger to be more advanced in low frequency words. The study underlines the benefits of FPCA for quantifying the many types of sound changes involving subtle shifts in speech dynamics. In particular, multi-dimensional trajectory shape differences can be quantified without the need for vowel targets nor for determining the influence of the parameters - in this case of the first two formant frequencies - independently of each other.
Towards a Classification View of Personalized e-Learning with Social Collaboration Support

With the emergence of Web 2.0 technologies, interaction and collaboration support in the educational field have been augmented. These types of support embrace researchers to enrich the e-learning environment with personalized characteristics with the utilization of the collaboration support outputs. Achieving this requires understanding the existing environments and highlights their eminence. As a result, there are many attempts to state the current status of personalized e-learning environment from different perspectives. However, these attempts targeted a specific view and direction which failed to provide us with the general view of the adoption of personalized e-learning environment with the support of social collaboration tools. This paper provides a classified view of the current status of personalized e-learning environments which incorporate social collaboration tools for providing the personalization feature. The classification adopts four different views to carry out the classification; these views are subject, purpose, method, and tool. The findings show that the utilization of the user-generated contents and social interaction functionalities for personalization is tight and not fully consumed. In short, the potential of providing personalized learning with social interaction and collaboration features remains not fully explored. Keywords—Classification review; collaboration; personalized elearning; social media