Miracle-dz/UniFAR-FTUs huggingface dataset:
A scalable model of planning perlocutionary acts

We propose a new model of perlocution-ary acts, in which perlocutionary effects of communicative actions are simply effects of operators in a planning problem. A plan using such operators can be computed ef-ﬁciently, under the assumption that all per-locutionary effects come true as intended; the speaker then monitors the plan execution to detect it when they don’t. By scaling the complexity of the execution monitor up or down, we can reconstruct previous approaches to speech act planning and grounding, or build an instruction generation system with real-time performance.
Directed Network Mapping Approach to Rotor Localization in Atrial Fibrillation Simulation

Catheter ablation for atrial fibrillation (AF) is one of the most commonly performed electrophysiology procedures. Despite significant advances in our understanding of AF mechanisms in the last years, ablation outcomes remain suboptimal for many patients, particularly those with persistent or long-standing AF. A possible reason is that ablation techniques mainly focus on anatomic, rather than patient-specific functional targets for ablation. The identification of such ablation targets remains challenging. The purpose of this study is to investigate a novel approach based on directed networks, which allow the automatic detection of important arrhythmia mechanisms, that can be convenient for guiding the ablation strategy. The networks are generated by processing unipolar electrograms (EGMs) collected by the catheters positioned at the different regions of the atria. Network vertices represent the locations of the recordings and edges are determined using cross-covariance time-delay estimation method. The algorithm identifies rotational activity, spreading from vertex to vertex creating a cycle. This work is a simulation study and it uses a highly detailed computational 3D model of human atria in which sustained rotor activation of the atria was achieved. Virtual electrodes were placed on the endocardial surface, and EGMs were calculated at each of these electrodes. The propagation of the electric wave fronts in the atrial myocardium during AF is very complex, so in order to properly capture wave propagation patterns, we split EGMs into multiple short time frames. Then, a specific network for each of these time frames was generated, and the cycles repeating in consecutive networks point us to the stable rotor's location. The respective atrial voltage map served as reference. By detecting a cycle between the same 3 nodes in 19 out of 58 networks, where 10 of these networks were in consecutive time frames, a stable rotor was successfully located.
The Application of Fuzzy Modeling and PSO in Spaces Allocation of Naval Ship

A semi-automated general arrangement technique of naval ship is discussed, it approached by a series of two essentially two-dimensional problems: the allocation of spaces to Zone-decks (one deck within one vertical zone), after that, implement the detailed arrangement of spaces to each Zone-deck. In this context, fuzzy modeling is introduced for evaluating environmental loadings (noise, vibration and ship motion) and Naval Equipment Standards, and then these measures are translated to fuzzy utility values which express the satisfaction location of each group spaces. The fuzzy location preference values are combined with Zone-deck utilization utility to establish the objective function using fuzzy product inference. Lastly, the particle swarm optimization (PSO) is performed on the objective function to acquire the allocation plan of spaces in each Zone-deck.
Novel multi-satellite transmit diversity schemes

Space-time coding based on transmit diversity have recently proposed as a design art of signals for transmit diversity in satellite-data communications. The paper mainly discusses the performance of some STCs applied to the forward link of a WCDMA multi-satellite UMTS environment. MRC, STBC, SDT and STTC have been firstly considered. Furthermore, outer convolutional encoder have been considered to concatenate with MRC, STBC and STD, while for STTC, a convolutional encoder plus an iterative decoding has been used to perform a STTCM. Simulation results show that STD outperforms all the other schemes in terms of BER and FER for lower values of SNR. While the SNR is increasing, STTC and STTCM have shown the best performances in terms of FER. Performance results with various modulation methods for the serially concatenated convolutional STBC system are also presented here.
EEG-based Major Depressive Disorder Detection Using Data Mining Techniques

Major depressive disorder (MDD) is a common mental illness characterized by a persistent feeling of low mood, sadness, fatigue, despair, etc. In a serious case, patients with MDD may have suicidal thoughts or even suicidal behaviors. In clinical practice, a widely used method of MDD detection is based on a professional rating scale. However, the scale-based diagnostic method is highly subjective, and requires a professional assessment from a trained staff. In this work, 92 participants were recruited to collect EEG signals in the Shenzhen Traditional Chinese Medicine Hospital, assessing MDD severity with the HAMD-17 rating scale by a trained physician. Two data mining methods of logistic regression (LR) and support vector machine (SVM) with derived EEG-based beta-alpha-ratio features, namely LR-DF and SVM-DF, are employed to screen out patients with MDD. Experimental results show that the presented the LR-DF and SVM-DF achieved F 1 scores of 0:76 0:30 and 0:92 0:18, respectively, which have obvious superiority to the LR and SVM without derived EEG-based beta-alpha-ratio features.
Mobile robot for a ham industry

A mobile robot for a ham industry has been developed. The features of the factory, limited environment, sliding floor, and the necessity for a high storage flexibility makes impossible the usage of conventional transport systems, conveyors, automatic guided vehicles, etc. The developed system permits us to integrate the pervious transport system, that was based on fork lift trucks, with the advantage that in the case of contingency an operator can drive the mobile robot as a fork lift truck. In this way, the transport and storage can be done using fork lift trucks, mobile robots, or both, and all of them controlled by a planning program running in a Sun Sparcstation10.
Effects of wipe on contact resistance of aged surfaces

Probe measurements were made on corroded test coupons to show the effects wipe has on contact resistance. Data are provided for two types of films; oxidized copper and corrosion on porous gold due to flowing mixed gas tests (FMG). The results in both cases show contact resistance is reduced by nearly two orders of magnitude for 0.25-mm wipe. In addition, a Monte Carlo analysis was conducted using a modified version of a previously developed model of degradation. This included adding film resistivity as a random variable for asperities that were previously considered nonconductive, and incorporating wipe in the model by considering shear forces to produce additional asperity deformation. The Monte Carlo results agree reasonably well with observation as differences can be explained within the framework of the model. It is believed improvements can be made on the predictions of the model if the mechanism of film removal and adhesion, and the variation of film resistivity are better understood. >
Cognitive performance drop detection during daily activities using EEG

Investing long hours in a cognitively demanding activity without adequate rest has been shown to lead to a decline in cognitive capacity. For this reason, it is crucial to know the moments in which the mental performance is low, to disconnect and recover. This paper presents the design of brain signal processing pipeline using electroencephalographic (EEG) signals to detect cognitive performance drops during sessions that require low physical activity, to determine when users should pause the execution of their current task to take a rest. The developed system is adaptable to any user without requiring prior training. The evaluation considers three mental states: attention, mental fatigue and stress as the most representative; these mental states were re-referenced using the first five minutes of each recording as a calibration period, before applying a set of rules to determine cognitive performance drops. The results showed that, for sixty-two monotonous driving simulation sessions (78.5 ± 22.4 minutes), the detection time occurred at 35.3 ± 18.9 minutes in 80.6% of the sessions, and for three studying sessions (30, 20 and 30 minutes each) the detection time occurred at 11.9, 12.3 and 8.3 minutes, respectively.
A SURVEY OF RELATION EXTRACTION TECHNIQUES USING HYBRID CLASSICAL AND STATE OF THE ART METHODS

The extraction of named entities and their relationships from unstructured biomedical texts has long been a topic of great interest. The challenges that arise when undertaking a project in the subdomain of biomedical text information extraction (IE) are well known, yet the inﬂux of research projects and interest in the domain is accelerating rapidly. Much of this interest relates to recent advances in Natural Language Processing (NLP) methodologies (e
Team Elsevier Health Data Science at BioCreative VII LitCovid Track: Fine-Tuning Transformer Models for COVID-19 Literature Annotation A

— The vast and growing body of Covid-19 literature poses a challenge for parsing, interpretation, and curation. In order to address that, the BioCreative Challenge called for approaches to automate topic classification, based on the topics and current labelled data available in the LitCovid database. Our approach involved fine-tuning pre-trained transformer models with a classification head to label Covid-19 literature according to the LitCovid database’s topic framework. The models we experimented with included Distilbert, Longformer, and Scibert. We also experimented with fine-tuning on different features of the training data – the article abstracts, article titles, and all the information together. The best performing model was a version of Scibert pre-trained on a corpus including Covid-19 papers. This model was then fine-tuned on the title, abstracts, keywords, and journal name concatenated together, with weighting during the training process to account for class imbalances.
Identification of COVID-19 Type Respiratory Disorders Using Channel State Analysis of Wireless Communications Links

One deadly aspect of COVID-19 is that those infected can often be contagious before exhibiting overt symptoms. While methods such as temperature checks and sinus swabs have aided with early detection, the former does not always provide a reliable indicator of COVID-19, and the latter is invasive and requires significant human and material resources to administer. This paper presents a non-invasive COVID-19 early screening system implementable with commercial off-the-shelf wireless communications devices. The system leverages the Doppler radar principle to monitor respiratory-related chest motion and identifies breathing rates that indicate COVID-19 infection. A prototype was developed from software-defined radios (SDRs) designed for 5G NR wireless communications and system performance was evaluated using a robotic mover simulating human breathing, and using actual breathing, resulting in a consistent respiratory rate accuracy better than one breath per minute, exceeding that used in common medical practice.Clinical Relevance—This establishes the potential efficacy of wireless communications based radar for recognizing respiratory disorders such as COVID-19.
Evaluation of a dual-PPG system for pulse transit time monitoring

This work presents a new dual-photoplethysmographic (PPG) system for pulse transit time (PTT) monitoring. An experiment has been set up in order to compare the PTT measurement between carotid and radial arteries from two systems: our physiological multimodal platform (PMP) and the Complior® tonometer. This work explores the comparison between such optical and mechanical modalities. The results show that the PPG device tends to overestimate the PTT (RMSE = 16 ms). Furthermore, both mechanical and optical signals have been superposed and demonstrated that pulse morphologies are quite similar.Clinical Relevance—Carotid-radial pulse wave velocity (PWV) is compared on a small cohort of subjects and significant differences are observed between optical and mechanical-based systems.
glioma cells by inhibiting long noncoding RNA FOXD 2 ‐ As 1 ‐ promoted EZH 2 activation

Currently, conventional treatment is not sufficient to improve the survival of glioma patients. Hence, adopting novel personalized treatment programs is imperative. Curcumol, a Chinese herbal medicine extract from the roots of Rhizoma Curcumae, has attracted significant interest due to its beneficial pharmacological activities. The current study revealed that curcumol inhibited the proliferation, metastasis, self‐renewal ability, and TMZ resistance in glioma cells in vitro and in vivo. Next, the potential molecular mechanisms of curcumol in inhibiting glioma were investigated. We found that the long non‐coding RNA (lncRNA) FOXD2‐As1 might contribute to the effects of curcumol on glioma cells. Enforced expression of FOXD2‐As1 attenuated the curcumol‐induced reduction in glioma cell proliferation, metastasis, self‐renewal ability, and TMZ resistance. Moreover, the forced expression of FOXD2‐As1 reversed the inhibitory effect of curcumol on the binding ability of EZH2 and H3K27me3 modification in the promoter regions of anti‐oncogenes. Our results showed for the first time that curcumol is effective in inhibiting malignant biological behaviors and TMZ‐resistance of glioma cells by suppressing FOXD2‐As1‐mediated EZH2 activation. Our study offers the possibility of exploiting curcumol as a promising therapeutic agent for glioma treatment and may provide an option for the clinical application of this natural herbal medicine.
New Combined Adaptive (NCA) Algorithm for Smart Antenna System Applications

ABSTRACT This paper proposes a new combined algorithm for performance enhancement of smart antenna systems in mobile communications. The new combined algorithm (NCA) uses sample matrix inversion (SMI) initialization with a modified version of normalized least mean square (NLMS) algorithm (MNLMS). The MNLMS algorithm is regarded as time-varying regularization parameter ϵ(k) that is fixed in the conventional NLMS algorithm. The MNLMS algorithm uses a reciprocal of the estimation error square term in the denominator of the learning rate of NLMS instead of fixed regularization parameter (ϵ). Through simulation results of smart antennas for an additive white Gaussian noise channel model, the NCA algorithm achieves about 15 and 19 dB improvement in interference suppression compared with NLMS and another proposed previously matrix inversion NLMS (MI-NLMS) algorithms, respectively. While the NLMS algorithm starts to converge from 50 iterations, the MI-NLMS and NCA algorithms start to converge from the initial iteration. Moreover, when this algorithm applied for the Rayleigh fading channel with a Jakes power spectral density, it provides about 7 dB improvements over NLMS and MI-NLMS algorithms and starts converge from the initial iteration. The NCA provides improved performance in weight stability for both channels.
Prevention of venous thromboembolism with aspirin following knee surgery: A systematic review and meta-analysis

Venous thromboembolism (VTE) is a well-known complication following orthopaedic surgery. The incidence of this complication has decreased substantially since the introduction of routine thromboprophylaxis. However, concerns have been raised about increased bleeding complications caused by aggressive thromboprophylaxis. Attention has grown for aspirin as a safer thromboprophylactic agent following orthopaedic surgery. A systematic review using MEDLINE, Embase and Web of Science databases was undertaken to compare the effectiveness of aspirin prophylaxis following knee surgery with the current standard prophylactic agents (low molecular weight heparin [LMWH], vitamin K antagonists and factor Xa inhibitors). No significant difference in effectiveness of VTE prevention was found between aspirin, LMWH and warfarin. Factor Xa inhibitors were more effective, but increased bleeding complications were reported. As evidence is limited and of low quality with substantial heterogeneity, further research with high-quality, adequately powered trials is needed. Cite this article: EFORT Open Rev 2021;6:892-904. DOI: 10.1302/2058-5241.6. 200120
Neck Circumference as a Predictor of Obesity and Metabolic Syndrome in Bangladeshi Women with Polycystic Ovary Syndrome

Background and Objective: Researchers have identified neck circumference (NC) as a valuable tool to detect obesity and metabolic syndrome (MS). We conducted this study to define cutoffs of NC to identify obesity, abdominal obesity, and MS in adult women diagnosed with polycystic ovary syndrome (PCOS). Methods: Adult women newly diagnosed with PCOS using the revised Rotterdam criteria having NC measure data in a cross-sectional study titled “Biochemical and Hormonal Profile of Patients with Polycystic Ovary Syndrome” were analyzed. Results: Finally, 200 women were analyzed; their mean age was 23.3 (±4.9) years, body mass index (BMI) 26.47 (±5.09) kg/m2, NC 34.6 (±3.04) cm, waist circumference (WC) 88.18 (±11.98) cm, and visceral adiposity index (VAI) was 3.31 (±1.37). NC had positive correlations with age, BMI, WC, systolic and diastolic blood pressure, serum triglyceride, VAI, and testosterone levels. NC cutoff 32.75 cm showed 87.3% sensitivity and 74.4% specificity in detecting abdominal obesity (AUC 0.889, P < 0.001) and 88.0% sensitivity and 68.0% specificity for diagnosis of overweight/obesity (AUC 0.877, P < 0.001). NC 34.25 cm showed 63.0% sensitivity and 64.0% specificity for diagnosis of MS (AUC 0.681, P < 0.001). Conclusion: Neck circumference may be a simple and convenient tool in assessing obesity, central obesity, and MS in women with PCOS.
Study of aerobic and anaerobic bacterial profile of nosocomial infections and their antibiotic resistance in a referral center, Southwest Iran: A three year cross-sectional study

Background The drug resistance is expected to be the most important challenge in infection control in Iran, where there is no local report or standard drug resistance monitoring system. Therefore, this study aimed to investigate the aerobic and anaerobic bacterial profile of nosocomial infections and their antibiotic resistance in Ahvaz, southwest Iran. Methodology The gram-positive and gram-negative bacteria were identified on the basis of conventional culture and biochemical tests. The antibiotic resistance of the bacterial isolates against antibiotics was determined by the disk diffusion method. Results Among total 1156 collected positive samples, E. coli and coagulase-negative staphylococci (CoNS) were the most frequent pathogenic gram negative bacteria (GNB) and gram positive bacteria (GPB) respectively. Drug susceptibility testing revealed that among GNB, P. aeruginosa was 100% resistant to amikacin, cefepime, ciprofloxacin and tetracycline. In the case of E. coli, the resistance rate was (98%) for trimethoprim sulfamethoxazole and cefepime. For GPB, S. aureus showed the highest resistance rates to amikacin (100%) and clindamycin (100%). In addition, CoNS strains showed a high level of resistance to doxycycline (100%), erythromycin (100%) and cefoxitin (97%). In Bacteroeides fragilis isolates, the highest resistance rate belonged to clindamycin (72%), and Clostridium perfringens strains showed high level of resistance to penicillin (46%). Conclusion The results highlighted that there are distinct factors leading to antimicrobial resistance in Ahvaz, southwest Iran. The primary contributors to the resistance development, include poor surveillance of drug-resistant infections, poor quality of available antibiotics, clinical misuse, and the ease of access to antibiotics. Moreover, similar factors such as self-medication and the lack of regulation on medication imports play a role in antibiotic resistance in the region.
Successful management of a tooth with canal obstruction using “cold ceramic”

One of the causes of treatment failure is calcification in the canal pathway, which prevents complete access to proper working length, and one of the most difficult and challenging cases of root canal treatment has been reported. In some cases, the dentist will not be able to open the calcified canal. Therefore, the prognosis of root canal treatment in these cases has been reported poor, and the dentist will offer a plan for possible treatments, including tooth extraction or apical surgery. The presented case is one example of those cases with a periapical lesion, which as a temporary treatment, the pulp chamber was filled with cold ceramic. This material, which is an MTA-like (Mineral Trioxide Aggregate) bioceramic with proper sealing ability, has been introduced as a root-end filling material. After 6 years of which the patient returned, he did not express any pain or discomfort during these 6 years. Furthermore, in radiograph that was taken, periapical lesion relative healing and bone regeneration were amazingly seen.
Effect of zinc oxide nanoparticles on physical and antimicrobial properties of resin-modified glass ionomer cement

Background: To improve the limitations, many modifications in the resin-modified glass ionomer (RMGI) composition have been proposed. In this study, we evaluated the effect of different concentrations of zinc oxide (ZnO) nanoparticles incorporated into RMGI cement on its physical and antimicrobial properties. Materials and Methods: In this in vitro study, ZnO nanoparticles with 0–4 wt. % concentrations were incorporated into RMGI. The following tests were carried out: (a) Antibacterial activity against Streptococcus mutans tested by disc diffusion method, (b) mechanical behavior assessment by measuring flexural strength (FS) and flexural modulus (FM), (c) micro-shear bond strength (μ-SBS), and (d) fluoride and zinc release. Data were analyzed using the statistical tests of ANOVA, t-test, and Tukey's HSD post hoc in SPSS V22. The level of significancy was 0.05. Results: In the disc diffusion method, specimens with 2 wt. % ZnO nanoparticles showed the highest antimicrobial efficacy (P < 0.05). After 1 month of water storage, no significant difference was observed in FS and FM of the samples (P > 0.05). In 2 wt. % ZnO nanoparticles group, μSBS increased in the first 7 days but decreased by 17% after one month, which showed a significant difference with that of the control group. The fluoride release did no change in the ZnO nanoparticle-containing group compared with the control group at all time intervals. Conclusion: Incorporation of 2 wt. % ZnO nanoparticles into the RMGI cement adds antimicrobial activity to the cement without sacrificing FS and fluoride release properties, while decreased μSBS.
Wide input range, high-efficiency magnetic resonant wireless power receiver

This article presents a full-CMOS receiver for magnetic resonant wireless battery charging system. A wide-input range CMOS multi-mode active rectifier is proposed for a magnetic resonant wireless battery charging system. The configuration is automatically changed with respect to the magnitude of the input AC voltage. The output voltage of the multi-mode rectifier is sensed by a comparator. Furthermore, the configuration of the multi-mode rectifier is automatically selected by switches as original rectifier mode, one-stage voltage multiplier or two-stage voltage multiplier mode. As a result, a rectified DC output voltage is from 7.5 to 19 V for an input AC voltage of 5–20 V. This chip is implemented using 0.35 μm BCD technology with an active area of around 5 × 2.5 mm2. When the magnitude of the input AC voltage is 10 V, the power conversion efficiency of the multi-mode active rectifier is about 94%. The efficiency of the receiver is about 60% when the distance between the transmitter and receiver is about 1 m.