Miracle-dz/UniFAR-FTUs huggingface dataset:
Design of a Fluidized Drum Granulator for Ammonium Nitrate Production

There are various difficulties with theoretical modeling of a fluidized drum granulator owing to the mathematical modeling of the movement of fluidized solid particles. Many models are available for the movement of fluidized drums such as rotary drum dryers. This study examined the manufacturing process of dried ammonium nitrate. The process was assumed to have two phases in the drum and during transfer of the obtained granules in the drum granulator, and the retention time was calculated. Data reported in the literature were used to design a fluidized drum granulator for ammonium nitrate production. For the design, the dimensions of the drum in the granulator, slope, rotation speed, lifter number, geometry, dimensions of the fluidized bed table, and location were described. In addition, the retention time of the ammonium nitrate particles was calculated according to the production capacity.
Language Evolution : A Martian Perspective

Using neural nets to simulate learning and the genetic algorithm to simulate evolution in a toy world of mushrooms and mushroom-foragers, we place two ways of acquiring categories into direct competition with one another: In (1) "sensorimotor toil,” new categories are acquired through real-time, feedbackcorrected, trial and error experience in sorting them. In (2) "symbolic theft,” new categories are acquired by hearsay from propositions – boolean combinations of symbols describing them. In competition, symbolic theft always beats sensorimotor toil. We hypothesize that this is the basis of the adaptive advantage of language. Entry-level categories must still be learned by toil, however, to avoid an infinite regress (the “symbol grounding problem”). Changes in the internal representations of categories must take place during the course of learning by toil. These changes can be analyzed in terms of the compression of within-category similarities and the expansion of between-category differences. These allow regions of similarity space to be separated, bounded and named, and then the names can be combined and recombined to describe new categories, grounded recursively in the old ones. Such compression/expansion effects, called "categorical perception" (CP), have previously been reported with categories acquired by sensorimotor toil; we show that they can also arise from symbolic theft alone. The picture of natural language and its origins that emerges from this analysis is that of a powerful hybrid symbolic/sensorimotor capacity, infinitely superior to its purely sensorimotor precursors, but still grounded in and dependent on them. It can spare us from untold time and effort learning things the hard way, through direct experience, but it remain anchored in and translatable into the language of experience.
Obstetric complications in mothers with ADHD

Background There is currently limited research on the intersection of pregnancy and ADHD and the unique pregnancy risk factors for mothers with an ADHD diagnosis. With an increased population of patients with ADHD in the recent decades and an increase in ADHD medication use during pregnancy it is important to consider what unique risks mothers with ADHD face during the perinatal period. Objective Investigate a variety of outcomes in maternal ADHD. Methods We identified female patients with a diagnosis of pregnancy and ADHD diagnosis. We also further separated the ADHD cohort for separate sub-analyses based on medication type. Odds ratios and relative risk were calculated from outcome incidence within each cohort. Cohorts were balanced on age, sex, and race. Results We identified 45,737 pregnant females with ADHD. We matched these patients to pregnant females without ADHD, for a total of 42,916 pairs. Compared to the group without ADHD, mothers with ADHD had higher rates of every outcome except for HPV infection, which was statistically insignificant (P = 0.768). The odds ratios ranged from 1.08 for anemia complicating pregnancy to 2.63 for depressive episodes. Most outcomes were between 1.2 and 1.8 times more likely to occur in the cohort with ADHD. Conclusion This study presents substantial advancements in our knowledge of pregnancy-related ADHD care. Armed with an increased awareness of these potential complications and their relationship with ADHD, obstetricians, psychiatrists, and providers of all specialties may be able to reduce the rate of complications within this specific patient population.
FOXC2 as a prognostic marker and a potential molecular target in patients with human solid tumors

Background Forkhead Box Protein C2 (FOXC2) belongs to the Forkhead/Wing-helix family. The regulatory role of this transcription factor in physiological function and carcinogenic activity has been proven in subsequent investigations. However, there is still scarcity of evidence on the relationship between FOXC2 expression and prognosis in human solid tumors. We conducted this meta-analysis to evaluate the role of FOXC2 as a prognosis factor and a possible target marker in human solid tumors. Methods PubMed, Web of Science, Embase, and the Cochrane library database were all searched methodically. Eligible publications on FOXC2 in human solid tumors were gathered and reviewed. The effect sizes were calculated using pooled hazard ratios (HRs) or odds ratios (ORs) with the corresponding 95% confidence interval (CI). Statistical analysis was conducted with Stata SE12.0. Results This meta-analysis comprised 3,267 patients from 20 studies covering a variety of solid tumors. Increased FOXC2 expression was related to shorter overall survival (OS) (HR = 2.05, 95% CI: 1.73–2.42). High expression of FOXC2 is associated with lymph node metastases (OR = 3.33, 95% CI: 2.65–4.19), TNM stage (OR = 3.09, 95% CI: 2.00–4.78), and age (OR = 1.26, 95% CI: 1.06–1.50), according to the pooled ORs. However, no significant association was observed between the high expression of FOXC2 and sex, tumor size or tumor differentiation. Conclusion Increased expression of FOXC2 is associated with unfavored OS, lymph node metastases, TNM stage, and age. FOXC2 is a promising prognostic marker and a novel target marker in human solid tumors.
Panorama: BBN Participation in SM-KBP 2019

We describe the BBN submission to the TAC 2019 Streaming Multimedia Knowledge Base Population (SM-KBP) track. In a pipeline similar to that of our 2018 submission with enhancements to usability and several analytic modules, we processed multimedia data to create coherent knowledge elements (entities, relations, and events) in NIST-restricted AIDA Interchange Format.
Graph Neural Networks with High-order Feature Interactions

Network representation learning, a fundamental research problem which aims at learning low-dimension node representations on graph-structured data, has been extensively studied in the research community. By generalizing the power of neural networks on graph-structured data, graph neural networks (GNNs) achieve superior capability in network representation learning. However, the node features of many real-world graphs could be high-dimensional and sparse, rendering the learned node representations from existing GNN architectures less expressive. The main reason lies in that those models directly makes use of the raw features of nodes as input for the message-passing and have limited power in capturing sophisticated interactions between features. In this paper, we propose a novel GNN framework for learning node representations that incorporate high-order feature interactions on feature-sparse graphs. Specifically, the proposed message aggregator and feature factorizer extract two channels of embeddings from the feature-sparse graph, characterizing the aggregated node features and high-order feature interactions, respectively. Furthermore, we develop an attentive fusion network to seamlessly combine the information from two different channels and learn the feature interaction-aware node representations. Extensive experiments on various datasets demonstrate the effectiveness of the proposed framework on a variety of graph learning tasks.
Cruciform welded joints : hot-dip galvanization effect on the fatigue life and local energetic analysis

During their operation, modern aircraft engine components are subjected to increasingly demanding operating conditions, especially the high pressure turbine (HPT) blades. Such conditions cause these parts to undergo different types of time-dependent degradation, one of which is creep. A model using the finite element method (FEM) was developed, in order to be able to predict the creep behaviour of HPT blades. Flight data records (FDR) for a specific aircraft, provided by a commercial aviation company, were used to obtain thermal and mechanical data for three different flight cycles. In order to create the 3D model needed for the FEM analysis, a HPT blade scrap was scanned, and its chemical composition and material properties were obtained. The data that was gathered was fed into the FEM model and different simulations were run, first with a simplified 3D rectangular block shape, in order to better establish the model, and then with the real 3D mesh obtained from the blade scrap. The overall expected behaviour in terms of displacement was observed, in particular at the trailing edge of the blade. Therefore such a model can be useful in the goal of predicting turbine blade life, given a set of FDR data. © 2016 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the Scientific Committee of PCF 2016.
Academic Performance Prediction for Success Rate Improvement in Higher Institutions of Learning : An Application of Data Mining Classification Algorithms

The abolition of pass grade for any degree course and the consequent change in cumulative grade point for any student to remain within an academic system at University level in Nigeria has led to withdrawal of many students. Thus, it becomes imperative for academic institutions managements to ensure that all necessary steps are taken to enable student graduate successfully. This study explores the usefulness of data mining in unravelling hidden knowledge in students’ academic record, particularly the students’ specific characteristics which managements or decision makers can leverage upon to ensure improvement in academic success rate of the students. In addition, the study provides a guide through which predicting algorithms can be used by senior academics to predict the performances of students in their respective classes. The conclusion of the study advocates for the use of data mining as decision making tool in academic institutions. General Terms Data Mining, Algorithms
Prediction model of interaction anxiousness based on Weibo data

Adolescents who face social distress in real life are often accompanied by interaction anxiousness. To avoid direct social activities, they prefer to indulge in social networks to satisfy their psychological needs for interpersonal communication. Sina Weibo, China's leading social media platform, has a markedly young user base. It provides a rich sample of adolescents with interaction anxiousness and conditions for real-time monitoring. In this study, various word categories, such as perception of spatial distance and positional relationships, morality, and emotion, showed a significant relationship with interaction anxiousness. Furthermore, prediction models were established based on the original Weibo data of 839 active Sina Weibo users through a variety of machine learning algorithms to predict the scores of users' interaction anxiousness. The results showed that the performance of the prediction model established by the fully connected neural network was the best, and both criterion validity and split-half reliability were good (rcriterionvalidity = 0.30, rsplit − halfreliability = 0.76). This study confirms the validity of the prediction model of interaction anxiousness based on social media behavior data, provides a feasible solution to examine adolescents' interaction anxiousness, and provides a scientific basis for more targeted mental health interventions.
Interactive Trajectory Adaptation through Force-guided Bayesian Optimization

Flexible manufacturing processes demand robots to easily adapt to changes in the environment and interact with humans. In such dynamic scenarios, robotic tasks may be programmed through learning-from-demonstration (LfD) approaches, where a nominal plan of the task is learned by the robot. However, the learned plan may need to be adapted in order to fulfill additional requirements or overcome unexpected environment changes. When the required adaptation occurs at the end-effector trajectory level, a human operator may want to intuitively show the robot the desired changes by physically interacting with it. In this scenario, the robot needs to understand the human intended changes from noisy haptic data, quickly adapt accordingly and execute the nominal task plan when no further adaptation is needed. This paper addresses the aforementioned challenges by leveraging LfD and Bayesian optimization to endow the robot with data-efficient adaptation capabilities. Our approach exploits the sensed interaction forces to guide the robot adaptation, and speeds up the optimization process by defining local search spaces extracted from the learned task model. We show how our framework quickly adapts the learned spatial-temporal patterns of the task, leading to deformed trajectory distributions that are consistent with the nominal plan and the changes introduced by the human.
Optical follow-up of the tidal disruption event iPTF16fnl: new insights from X-shooter observations

We present the results from Nordic Optical Telescope and X-shooter follow-up campaigns of the tidal disruption event (TDE) iPTF16fnl, covering the first ∼100 d after the transient discovery. We followed the source photometrically until the TDE emission was no longer detected above the host galaxy light. The bolometric luminosity evolution of the TDE is consistent with an exponential decay with e-folding constant t0 = 17.6 ± 0.2 d. The early-time spectra of the transient are dominated by broad He ii λ4686, H $\beta$, H $\alpha$, and N iii λ4100 emission lines. The latter is known to be produced together with the N iii λ4640 in the Bowen fluorescence mechanism. Due to the medium-resolution X-shooter spectra we have been able to separate the Bowen blend contribution from the broad He ii emission line. The detection of the Bowen fluorescence lines in iPTF16fnl place this transient among the N-rich TDE subset. In the late-time X-shooter spectra, narrow emission lines of [O iii] and [N ii] originating from the host galaxy are detected, suggesting that the host galaxy harbours a weak active galactic nucleus in its core. The properties of all broad emission lines evolve with time. The equivalent widths follow an exponential decay compatible with the bolometric luminosity evolution. The full width at half-maximum of the broad lines decline with time and the line profiles develop a narrow core at later epochs. Overall, the optical emission of iPTF16fnl can be explained by being produced in an optically thick region in which high densities favour the Bowen fluorescence mechanism and where multiple electron scatterings are responsible for the line broadening.
Try It On! Contingency Effects of Virtual Fitting Rooms

Abstract A revolutionary application of the virtual reality technology in online retailing, virtual fitting room (VFR), has attracted attention of researchers and practitioners recently. However, it remains unclear whether and how VFR influences sales and post-sales outcomes based on the limited literature, and retailers hesitate in adopting the technology due to concerns about its profit prospects. In this research, we conduct two large-scale field experiments to test the causal effects of different VFR designs, and a lab experiment to unveil the underlying theoretical mechanisms. We find that, although VFR can have a sizeable positive effect on sales, it can be counterproductive when used improperly. Specifically, personalized VFR may not increase sales if used in combination with conventional product visualizations because self-discrepancy becomes salient under this condition. Moreover, VFR significantly influences post-sales outcomes, i.e., it enhances customer satisfaction and reduces product return rate. The findings provide distinct theoretical contributions and managerial implications.
AMPE-2017 Proceedings , 12-13 December , 2017 NED / Pakistan 6 FULLERENE BASED NANOCOMPOSITES FOR ADVANCED OIL / GAS APPLICATIONS

Fullerenes, novel forms of super carbonaceous materials are subject of significant research for their utilization in an increasing number of applications like petrochemical, energy, transportation, automotive, aerospace, defence, sporting goods and infrastructure development. In particular, carbon nanotubes and graphene are some of the common types of fullerenes that offer unique combinations of superlative chemical and physical properties. This keynote speech will look into how a simple chemical manipulation at nano-scale of a superlative chicken wire structure of graphene can be exploited to address major engineering challenges we are now encountering in the development of subsea engineering products used for oil/ gas applications. Substituting monolithic materials with nanofiller reinforced composites would not just bring major performance uplift but also significant reduction in manufacturing and related economics. However, there are several key challenges prior to this forthcoming substitution which will be detailed in this work.
Gastrodin attenuates vincristine- induced mechanical hyperalgesia through serotonin 5-HT1A receptors

Gastrodia elata Blume (Orchidaceae) is an old traditional Chinese medicine with demonstrated analgesic efficacy in humans. However, the potential analgesic effect of its active component, gastrodin, has not been systematically studied. This work described the anti-hyperalgesic effect of gastrodin in a mouse model of chemotherapeutic agent vincristine-induced neuropathic pain. Gastrodin (0.05-0.8 mg/kg) dose-dependently reverted the mechanical hyperalgesia in mice. In addition, the anti-hyperalgesic effect of gastrodin was significantly blocked by a selective serotonin 5-HT1A receptor antagonist WAY100635 (1 mg/kg). In contrast, gastrodin did not significantly alter the general locomotor activity in mice. Taken together, this study demonstrated that gastrodin possesses robust analgesic efficacy in mice and may be a novel analgesic for the management of neuropathic pain. Article Info Received: 4 November 2013 Accepted: 19 November 2013 Available Online: 25 December 2013 DOI: 10.3329/bjp.v8i4. 16836 Cite this article: Guo ZG, Jia XP, Su XJ, Li P, Hao JH. Gastrodin attenuates vincristineinduced mechanical hyperalgesia through serotonin 5-HT1A receptors. Bangladesh J Pharmacol. 2013; 8: 41419. This work is licensed under a Creative Commons Attribution 3.0 License. You are free to copy, distribute and perform the work. You must attribute the work in the manner specified by the author or licensor. Gastrodin attenuates vincristine-induced mechanical hyperalgesia through serotonin 5-HT1A receptors Zheng Gang Guo, Xiao Pen Jia, Xiao Jun Su, Ping Li and Jian Hua Hao Department of Anesthesiology, The First Affiliation Hospital, Chinese PLA Hospital, Beijing 100 048, China. gastrodin, suggesting that the observed antinociceptive effect of gastrodin was partially media-ted by 5-HT1A receptors.
Modélisation de la performance des refroidisseurs a ` deux lits à adsorption utilisant le gel de silice / eau

This article presents a transient model for a two-bed, silica gel-water adsorption chiller. Compared with our previous cyclicsteady-state model, we found very good agreement between our model prediction and experimental data. We found that, regardless of the initial mass distribution, the chiller was able to achieve the same cyclic-steady-state within four cycles or 1800 s. We also demonstrated that the manufacturer had empirically evolved to select a fixed switching and cycle time such that the best peak evaporator temperature suppression, and near maximum cooling capacity can be achieved by a compact design. q 1999 Elsevier Science Ltd and IIR. All rights reserved.
INVESTIGATION OF EFFECTIVE PERMITTIVITY AND PERMEABILITY FOR A NOVEL V-SHAPED METAMATERIAL USING SIMULATED S-PARAMETERS

In this paper, it is demonstrated that a structure which consists of V-shaped anti-parallel conducting strips over both faces of a substrate can be used as a magnetic resonator to achieve effective negative permeability. The simulations for this metamaterial have been done using Ansoft HFSS software to obtain the transmission characteristics and the location of the resonant frequency. Furthermore, material parameters such as effective permeability (μ) and effective permittivity (ε) have been extracted from simulated Sparameters.
Combined effect of traditional Chinese herbal-based formulations Jing Si herbal tea and Jing Si nasal drop inhibits adhesion and transmission of SARS-CoV2 in diabetic SKH-1 mice

Multiple studies show increased severity of SARS-CoV2-infection in patients with comorbidities such as hypertension and diabetes. In this study, we have prepared two herbal-based formulations, a pleiotropic herbal drink (Jin Si Herbal Tea, JHT) and a nasal drop (Jin Si nasal drop, JND), to provide preventive care against SARS-CoV2 infection. The effect of JHT and JND was determined in SARS-CoV2-S-pseudotyped lentivirus-infected bronchial and colorectal cell lines and in SKH-1 mouse models. For preliminary studies, ACE2 receptor abundant bronchial (Calu-3) and colorectal cells (Caco-2) were used to determine the effect of JHT and JND on the host entry of various variants of SARS-CoV2-S-pseudotyped lentivirus. A series of experiments were performed to understand the infection rate in SKH-1 mice (6 weeks old, n = 9), find the effective dosage of JHT and JND, and determine the combination effect of JHT and JND on the entry and adhesion of various variant SARS-CoV2-S-pseudotyped lentiviruses, which included highly transmissible delta and gamma mutants. Furthermore, the effect of combined JHT and JND was determined on diabetes-induced SKH-1 mice against the comorbidity-associated intense viral entry and accumulation. In addition, the effect of combined JHT and JND administration on viral transmission from infected SKH-1 mice to uninfected cage mate mice was determined. The results showed that both JHT and JND were effective in alleviating the viral entry and accumulation in the thorax and the abdominal area. While JHT showed a dose-dependent decrease in the viral load, JND showed early inhibition of viral entry from day 1 of the infection. Combined administration of 48.66 mg of JHT and 20 µL of JND showed rapid reduction in the viral entry and reduced the viral load (97–99%) in the infected mice within 3 days of treatment. Moreover, 16.22 mg of JHT and 20 µL JND reduced the viral infection in STZ-induced diabetic SKH-1 mice. Interestingly, combined JHT and JND also inhibited viral transmission among cage mates. The results, therefore, showed that combined administration of JHT and JND is a novel and an efficient strategy to potentially prevent SARS-CoV2 infection.