Miracle-dz/UniFAR-FTUs huggingface dataset:
Graph Theoretical View on Text Understanding

The system STAVEK-02 described in the contribution is concentrated on yielding supplemental information (besides parsing/tagging of words) for text understanding through the clustering of nouns and/or verbs according to their meanings and common features. The system consists of two word processing blocks. The first block is a vocabulary of 149,000 Slovenian word-roots and 3,100 endings and assigns the grammatical feature to the words by the grammatical rules without any link to pre-tagged lexical corpora. The second block is a Network of meanings of Slovenian words which in principle is a graph connecting 45,000 and 15,000 noun and verb lexemes, respectively, all of them hierarchically clustered into larger and larger groups having /exhibiting specific features and/or common properties of the words encompassed Such formations are in a similar lexical systems usually called synsets. Due to the complete connectivity between the synsets (groups) in the graph it is possible to find all possible property/feature paths between any pair of two words (nouns and/or verbs) in the network. Because clustering of words according to their meanings is made during the parsing of one, a pair, or several consecutive sentences, the features and properties that appear on the closest path between the particular words within the sentence are quite informative for their interpretation of the text. Clustering of the words according to their meanings during the parsing of text is a novel concept of the text interpretation. Ob the basis of a simple example of parsing a sentence and clustering of the nouns within it the concept using the network of meanings in the program STAVEK-02 is described and discussed.
Development and validation of two clinical prediction models to inform clinical decision-making for lumbar spinal fusion surgery for degenerative disorders and rehabilitation following surgery: protocol for a prospective observational study

Introduction Potential predictors of poor outcome will be measured at baseline: (1) preoperatively to develop a clinical prediction model to predict which patients are likely to have favourable outcome following lumbar spinal fusion surgery (LSFS) and (2) postoperatively to predict which patients are likely to have favourable long-term outcomes (to inform rehabilitation). Methods and analysis Prospective observational study with a defined episode inception of the point of surgery. Electronic data will be collected through the British Spine Registry and will include patient-reported outcome measures (eg, Fear-Avoidance Beliefs Questionnaire) and data items (eg, smoking status). Consecutive patients (≥18 years) undergoing LSFS for back and/or leg pain of degenerative cause will be recruited. Exclusion criteria: LSFS for spinal fracture, inflammatory disease, malignancy, infection, deformity and revision surgery. 1000 participants will be recruited (n=600 prediction model development, n=400 internal validation derived model; planning 10 events per candidate prognostic factor). The outcome being predicted is an individual’s absolute risk of poor outcome (disability and pain) at 6 weeks (objective 1) and 12 months postsurgery (objective 2). Disability and pain will be measured using the Oswestry Disability Index (ODI), and severity of pain in the previous week with a Numerical Rating Scale (NRS 0–10), respectively. Good outcome is defined as a change of 1.7 on the NRS for pain, and a change of 14.3 on the ODI. Both linear and logistic (to dichotomise outcome into low and high risk) multivariable regression models will be fitted and mean differences or ORs for each candidate predictive factor reported. Internal validation of the derived model will use a further set of British Spine Registry data. External validation will be geographical using two spinal registries in The Netherlands and Switzerland. Ethics and dissemination Ethical approval (University of Birmingham ERN_17-0446A). Dissemination through peer-reviewed journals and conferences.
Extracting Positive Mentions of Adverse Drug Reactions from Product Labels using a Machine Learning Centric Approach

Product labels are an authoritative source of information about the risks, benefits, and pharmacological properties of drugs. As such, extracting the information stored in product labels, and making it available in the form of computationally accessible knowledge bases would benefit several applications in the area of drug safety surveillance and assessment1-4. For example, during post-marketing safety assessments is important to determine whether an investigated adverse drug reaction (ADR) is already labeled.
The dynamics of a healthy and infected red blood cell in flow through constricted channels: A DPD simulation

Understanding the dynamics of red blood cell (RBC) motion under in silico conditions is central to the development of cost‐effective diagnostic tools. Specifically, unraveling the relationship between the rheological properties and the nature of shape change in the RBC (healthy or infected) can be extremely useful. In case of malarial infection, RBC progressively loses its deformability and tends to occlude the microvessel. In the present study, detailed mesoscopic simulations are performed to investigate the deformation dynamics of an RBC in flow through a constricted channel. Specifically, the manifestation of viscous forces (through flow rates) on the passage and blockage characteristics of a healthy red blood cell (hRBC) vis‐á‐vis an infected red blood cell (iRBC) are investigated. A finite‐sized dissipative particle dynamics framework is used to model plasma in conjunction with a discrete model for the RBC. Instantaneous wall boundary method was used to model no‐slip wall boundary conditions with a good control on the near‐wall density fluctuations and compressibility effects. To investigate the microvascular occlusion, the RBC motion through 2 types of constricted channels, viz, (1) a tapered microchannel and (2) a stenosed‐type microchannel, were simulated. It was observed that the deformation of an infected cell was much less compared with a healthy cell, with an attendant increase in the passage time. Apart from the qualitative features, deformation indices were obtained. The deformation of hRBC was sudden, while the iRBC deformed slowly as it traversed through the constriction. For higher flow rates, both hRBC and iRBC were found to undergo severe deformation. Even under low flow rates, hRBC could easily traverse past the constricted channel. However, for sufficiently slow flow rates (eg, capillary flows), the microchannel was found to be completely blocked by the iRBC.
Selection of Optimal Adjuvant Chemotherapy and Targeted Therapy for Early Breast Cancer: ASCO Clinical Practice Guideline Focused Update.

Purpose To update key recommendations of the ASCO guideline adaptation of the Cancer Care Ontario guideline on the selection of optimal adjuvant chemotherapy regimens for early breast cancer and adjuvant targeted therapy for breast cancer. Methods An Expert Panel conducted targeted systematic literature reviews guided by a signals approach to identify new, potentially practice-changing data that might translate to revised practice recommendations. Results The Expert Panel reviewed phase III trials that evaluated adjuvant capecitabine after completion of standard preoperative anthracycline- and taxane-based combination chemotherapy by patients with early-stage breast cancer HER2-negative breast cancer with residual invasive disease at surgery; the addition of 1 year of adjuvant pertuzumab to combination chemotherapy and trastuzumab for patients with early-stage, HER2-positive breast cancer; and the use of neratinib as extended adjuvant therapy for patients after combination chemotherapy and trastuzumab-based adjuvant therapy with early-stage, HER2-positive breast cancer. Recommendations Patients with early-stage HER2-negative breast cancer with pathologic, invasive residual disease at surgery following standard anthracycline- and taxane-based preoperative therapy may be offered up to six to eight cycles of adjuvant capecitabine. Clinicians may add 1 year of adjuvant pertuzumab to trastuzumab-based combination chemotherapy in patients with high-risk, early-stage, HER2-positive breast cancer. Clinicians may use extended adjuvant therapy with neratinib to follow trastuzumab in patients with early-stage, HER2-positive breast cancer. Neratinib causes substantial diarrhea, and diarrhea prophylaxis must be used. Additional information can be found at www.asco. org/breast-cancer-guidelines .
Effects of astragaloside IV on the pharmacokinetics of puerarin in rats

Abstract Radix astragali and puerarin are always used together for cardiovascular disease in China clinics. This study investigates the effects of astragaloside IV (AS-IV, the main components of radix astragali) on the pharmacokinetics of puerarin in rats. The pharmacokinetics of orally administered puerarin (50 mg/kg) with or without AS-IV pretreatment (100 mg/kg/day for seven days) were investigated. The plasma concentration of puerarin was determined using LC–MS/MS method, and the pharmacokinetics profiles were calculated and compared. Caco-2 cell transwell model was also used to investigate the effects of AS-IV on the transport pf puerarin. The results showed that when the rats were pretreated with AS-IV, the maximum concentration (Cmax) of puerarin decreased from 760 to 467 ng/mL (p < .05, n = 6, 90% CI, 293 ± 61.28), and the area under the concentration-time curve from zero to infinity (AUC0–inf) also decreased from 4097 to 2330 μg·h/L (p < .05, n = 6). The oral clearance of puerarin increased significantly from 11.9 to 22.4 L/h/kg (p < .05, n = 6). The Caco-2 cell transwell experiments indicated that AS-IV could increase the efflux ratio of puerarin from 1.81 to 2.79 through inducing the activity of P-gp. In conclusion, these results indicated that AS-IV could affect the pharmacokinetics of puerarin, possibly by decreasing the systemic exposure of puerarin by inducing the activity of P-gp.
Prediction of Sentiment from Macaronic Reviews

Language used by people in the online content has not any proper format. For their own convenience, they also use some native language words while writing anything online i.e. reviews, blogs, etc. The presence of native words along with base language is known as macaronic language. The use of macaronic languages is on the rise these days. It also facilitates the need of expert analysers for the processing of such content to take effective decisions. The performance of various decision support systems is dependable over these analysers. Therefore, in this paper, an algorithm is developed which is a hybridised algorithm which first normalize the content to its base language later sentiment analysis is performed over it. The experimental results using proposed algorithm indicates a trade-off between various performance aspects.Computer
Fast Decoding of Dual Multipoint Codes From Algebraic Curves Up to the Kirfel–Pellikaan Bound

The multipoint codes from algebraic curves are a broad class of algebraic geometry codes derived from algebraic functions, which have multiple poles/zeros on their defining curves. Each of them is defined as either a primal code or a dual code. The dual one-point codes which are viewed as a subclass can be decoded efficiently up to the Feng–Rao bound by using the Berlekamp–Massey–Sakata (BMS) algorithm with majority logic. Since a primal code is equivalent to a dual code, one can decode as either of them, while their decoding methods are different. Recently, we published a fast method for decoding primal multipoint codes from curves based on the vectorial BMS algorithm. But, that is neither for dual codes nor up to the Goppa bound <inline-formula> <tex-math notation="LaTeX">$d_{\mathrm{ Goppa}}$ </tex-math></inline-formula>. Although we can guarantee theoretically that every error vector of weight only up to <inline-formula> <tex-math notation="LaTeX">$({1}/{2})(d_{\mathrm{ Goppa}}-g)$ </tex-math></inline-formula> can be corrected, where the integer <inline-formula> <tex-math notation="LaTeX">$g$ </tex-math></inline-formula> is the genus of the defining curve, the simulation shows that the method can correct most error patterns of weight up to <inline-formula> <tex-math notation="LaTeX">$({1}/{2})d_{\mathrm{ Goppa}}$ </tex-math></inline-formula>. In this paper we present a fast method for decoding dual multipoint codes from algebraic curves up to the Kirfel–Pellikaan bound, based on the vectorial BMS algorithm with majority logic, and show that algebraic geometry codes from generic algebraic curves can be decoded up to the Goppa bound efficiently. Similar to the case of one-point codes, the computational complexity of decoding is <inline-formula> <tex-math notation="LaTeX">${\mathcal{ O}}(a_{1}n^{2})$ </tex-math></inline-formula>, where the integer <inline-formula> <tex-math notation="LaTeX">$a_{1}$ </tex-math></inline-formula> is the minimum nonzero pole order of algebraic functions on the defining curve and the integer <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula> is the code length, and in particular, <inline-formula> <tex-math notation="LaTeX">${\mathcal{ O}}(n^{({7}/{3})})$ </tex-math></inline-formula> for Hermitian codes. This complexity is less than the complexity <inline-formula> <tex-math notation="LaTeX">${\mathcal{ O}}(a_{1}gn^{2})$ </tex-math></inline-formula> of Lee’s method for decoding dual multipoint codes as a unique alternative.
Nonparametric indices of dependence between components for inhomogeneous multivariate random measures and marked sets

We propose new summary statistics to quantify the association between the components in coverage‐reweighted moment stationary multivariate random sets and measures. They are defined in terms of the coverage‐reweighted cumulant densities and extend classic functional statistics for stationary random closed sets. We study the relations between these statistics and evaluate them explicitly for a range of models. Unbiased estimators are given for all statistics and applied to simulated examples and to tropical rain forest data.
Phase behavior of symmetric rod-plate mixtures revisited: Biaxiality versus demixing

The phase behavior of symmetric binary rod–plate mixtures has been investigated by numerical minimization of a free energy functional derived by Parsons [J. D. Parsons, Phys. Rev. A 19, 1225 (1979)] and Lee [S. D. Lee, J. Chem. Phys. 87, 4972 (1987)]. Both rod and plate molecules are represented by hard cylinders, with aspect ratios chosen so that the molecular and pair excluded volumes are equal; in this way symmetric phase diagrams in composition are found. The subtle competition between the packing entropy and the entropy of mixing rules out the possibility of a uniaxial nematic–biaxial nematic phase transition and instead favors a demixing phase transition between a rod-rich and a plate-rich nematic phase. It is shown that the biaxial nematic phase is unstable relative to demixing even for symmetric mixtures of very long rod and very flat plates, where the Parsons–Lee theory becomes identical with the Onsager theory. The contradictory predictions obtained in recent studies regarding the stability of t.
Re-visiting the repeatability issues of the type-N connectors

The type-N coaxial connector was introduced to the market in 1942. The precision type N connector that is in use today emerged in 1965. The repeatability for the type N connectors is a key factor for improved measurement accuracy. There were several studies being reported on this subject for the last few years. They have tried to resolve the repeatability and reproducibility problems by focusing on the following issues: the effect of pin gap, slotted vs. slotless female connectors, connector coupling technique, connector defect modeling and theory, connector orientations, and etc. No conclusive solutions can be made on how to reduce the un-repeatability of type N connectors. During our study, we have come across a better approach of using the power sensor testing system to monitor the mating of connector pair. It is now used to improve the measurement repeatability. The standard deviation of the connector repeatability can be controlled within 0.1% for the whole frequency range.
VISUALIZATION OF Nd 3 +-DOPED LaF 3 NANOPARTICLES FOR NEAR INFRARED BIOIMAGING VIA UPCONVERSION LUMINESCENCE AT MULTIPHOTON EXCITATION MICROSCOPY

Ryabova A.V. 1, Keevend K.2, Tsolaki E.3, Bertazzo S.3, Pominova D.V. 1, Romanishkin I.D. 1, Grachev P.V. 1, Makarov V.I. 1, Burmistrov I.A. 4, Vanetsev A.S. 1,6, Orlovskaya E.O. 1, Baranchikov A.E. 5, R hn M.6, Sildos I.6, Sammelselg V.6, Loschenov V.B. 1, Orlovskii Y.V. 1,6 General Physics Institute of the Russian Academy of Sciences, Moscow, Russia Swiss Federal Laboratories for Materials Science and Technology (Empa), St. Gallen, Switzerland University College London (UCL), London, United Kingdom Lomonosov Moscow State University, Moscow, Russia Kurnakov Institute of General and Inorganic Chemistry RAS, Moscow, Russia Institute of Physics, University of Tartu, Tartu, Estonia
Learning Over Multitask Graphs—Part II: Performance Analysis

Part I of this paper formulated a multitask optimization problem where agents in the network have individual objectives to meet, or individual parameter vectors to estimate, subject to a smoothness condition over the graph. A diffusion strategy was devised that responds to streaming data and employs stochastic approximations in place of actual gradient vectors, which are generally unavailable. The approach relied on minimizing a global cost consisting of the aggregate sum of individual costs regularized by a term that promotes smoothness. We examined the first-order, the second-order, and the fourth-order stability of the multitask learning algorithm. The results identified conditions on the step-size parameter, regularization strength, and data characteristics in order to ensure stability. This Part II examines steady-state performance of the strategy. The results reveal explicitly the influence of the network topology and the regularization strength on the network performance and provide insights into the design of effective multitask strategies for distributed inference over networks.
Control Theory for Synthetic Biology: Recent Advances in System Characterization, Control Design, and Controller Implementation for Synthetic Biology

Living organisms are differentiated by their genetic material-millions to billions of DNA bases encoding thousands of genes. These genes are translated into a vast array of proteins, many of which have functions that are still unknown. Previously, it was believed that simply knowing the genetic sequence of an organism would be the key to unlocking all understanding. However, as DNA sequencing technology has become affordable, it has become clear that living cells are governed by complex, multilayered networks of gene regulation that cannot be deduced from sequence alone. Synthetic biology as a field might best be characterized as a learn-by-building approach, in which scientists attempt to engineer molecular pathways that do not exist in nature. In doing so, they test the limits of both natural and engineered organisms.
The Sanguicolous Apostome Metacollinia luciensis Jankowski 1980 (Colliniidae, Apostomatia, Ciliophora) Is Not Closely Related to Other Sanguicolous Apostomes

The apostome family Colliniidae includes species that are adapted to the hemocoel/blood of various invertebrates, particularly crustaceans. To explore the phylogeny of these sanguicolous apostomes, Metacollinia luciensis was collected in August 2015 at Roscoff from the amphipod host, Orchestia gammarellus. Ciliates were Protargol stained and DNA was extracted. The small subunit rRNA (SSUrRNA) and cytochrome c oxidase subunit I (cox1) genes were amplified. Molecular phylogenetic analyses of the SSUrRNA genes unambiguously grouped M. luciensis with other apostomes with robust bootstrap support, but separated it distinctly from the pseudocolliniid clade. While there are only cox1 sequences for a subset of these apostomes, M. luciensis was also distant from the pseudocolliniids and separated from them by species of the exuviotrophic apostome Hyalophysa. These results confirm the distinctness of the families Colliniidae and Pseudocolliniidae.
Repair of Temporal Bone Defects via the Middle Cranial Fossa Approach: Treatment of 2 Pathologies With 1 Operation.

BACKGROUND Temporal bone dehiscence (TBD) often results in leakage of cerebrospinal fluid (CSF) and/or encephalocele. TBD can also occur over the superior semicircular canal, causing debilitating vertigo. Both can be repaired surgically, but traditional treatment is focused only on one pathology, not both. OBJECTIVE To report our experience in the treatment of TBD via the middle cranial fossa (MCF) approach. METHODS A retrospective review was conducted for all patients who underwent MCF approach for surgical repair of any temporal fossa dehiscence. RESULTS A total of 34 patients underwent a total of 37 surgeries. Obesity was prevalent; 21 patients (61.8%) were obese (BMI [body mass index] > 30 kg/m2), and 7 (20.6%) were overweight (BMI 25-30 kg/m2). The most common presenting symptom was hearing disturbance (70.3%), followed by otorrhea (51.4%). Empty sella was noted on computed tomography or magnetic resonance imaging in 15 patients (45.5%). Eight of the 34 patients (23.5%) were found to have superior semicircular canal dehiscence (SCD). Hearing improved with surgical intervention in 25 of 26 patients with hearing loss as a presenting symptom (96%). CSF resolved in 18 of 19 cases (95%). Seventy-three percent of patients reported at least minimal improvement in vertigo. CONCLUSION TBD may present with symptoms of CSF leak/encephalocele, but may also present with superior SCD. We recommend consistent review of the temporal bone imaging to check for superior SCD, and repair of the SCD first to prevent complications involving the labyrinth and cochlea. MCF approach using a multilayer repair without a lumbar drain is highly effective with minimal risk of complications.
Towards A Dual Process Approach to Computational Explanationon in Human-Robot Socia Interaction

The capacity for AI systems of explaining their decisions represents nowadays a huge challenge for both academia and industry (e.g. let us think at the autonomous cars sector). In this paper we sketch a preliminary proposal suggesting the adoption of a dual process approach for computational explanation. Our proposal is declined in the ﬁeld of Human-Robot Social Interaction; namely, in a gesture recognition task.
An Experimental Comparative Evaluation of Machine Learning Techniques for Motor Fault Diagnosis Under Various Operating Conditions

The diagnosis of electric machines, such as induction motors, is one of the key tasks that needs to be performed to guarantee their right operation as electromechanical energy converters in most industrial facilities. The ability to reliably identify a mechanical fault occurrence before it becomes catastrophic can reduce risks related to the productive chain. Recently, different intelligent approaches have been proposed to develop feature-based methods for automatic rotor fault diagnosis of induction motors. This paper provides an experimental comparative evaluation of different machine learning techniques for rotor fault identifications. The classifiers are tested with data obtained under different operating conditions of the ones used to train them, as it is usual in industry. The input information is obtained from current signals of an induction motor with two states of rotor bar degradation under two preestablished load levels.