Miracle-dz/UniFAR-FTUs huggingface dataset:
SELECTIVE CHLORINATION OF GLYCEROL TO 3-CHLORO-1,2-PROPANEDIOL CATALYZED BY BRØNSTED ACIDIC IONIC LIQUIDS

Brønsted acidic ionic liquids composed of 1-butyl-3-methylimidazolium, triethylbutylammonium, and 1-butylpyridinium cation counterparts and HSO4 ̅ and H2PO4 ̅ anion counterparts were used as the catalysts for the selective chlorination of glycerol with hydrogen chloride to 3-chloro-1,2-propandiol. From the perspective of the glycerol conversion and product yields, the catalytic activities of the ionic liquids containing HSO4 ̅ were higher than the ionic liquids containing H2PO4 ̅. As compared with the carboxylic acid catalysts, Brønsted acidic ionic liquids favored the catalytic chlorination of glycerol to 3-chloro-1,2-propandiol. When the glycerol chlorination was catalyzed by the Brønsted acidic ionic liquids at 110 oC for 12 h with the catalyst loading of 0.75 mol·kg ̅1 glycerol, the 3-chloro-1,2-propandiol yield was more than 81% at the complete conversion of glycerol.
Merging Subject Matter Expertise and Deep Convolutional Neural Network for State-Based Online Machine-Part Interaction Classification

Machine-part interaction classification is a key capability required by Cyber-Physical Systems (CPS), a pivotal enabler of Smart Manufacturing (SM). While previous relevant studies on the subject have primarily focused on time series classification, change point detection is equally important because it provides temporal information on changes in behavior of the machine. In this work, we address point detection and time series classification for machine-part interactions with a deep Convolutional Neural Network (CNN) based framework. The CNN in this framework utilizes a two-stage encoder-classifier structure for efficient feature representation and convenient deployment customization for CPS. Though data-driven, the design and optimization of the framework are Subject Matter Expertise (SME) guided. An SME defined Finite State Machine (FSM) is incorporated into the framework to prohibit intermittent misclassifications. In the case study, we implement the framework to perform machine-part interaction classification on a milling machine, and the performance is evaluated using a testing dataset and deployment simulations. The implementation achieved an average F1-Score of 0.946 across classes on the testing dataset and an average delay of 0.24 seconds on the deployment simulations.
Standardization and Study of Some Psychometric Properties of the Washington University Sentence Completion Test (Long-form) among the Iranian Students

Introduction and Objectives: The Washington University Sentence Completion Test (WUSCT) is one of the tools used to assess personality. Personality assessment helps to make decisions, diagnose, and choose the right treatments. Therefore, this study aimed to investigate the standardization of some psychometric properties of the WUSCT among Iranian students. Materials and Methods: The statistical population of this descriptive survey study included 287 medical students who were studying in Tehran, Iran, in the academic year 2015. Internal consistency, test-retest reliability, and inter-rater agreement were used to assess the reliability; moreover, the convergent validity was utilized to evaluate the construct validity of the WUSCT. The obtained data were analyzed in SPSS software (version 21). Results: The results of the present study indicated that the acceptable internal consistency of the WUSCT (P<0.001). Furthermore, the test re-test reliability of the WUSCT was determined at 0.86 (P<0.001). The correlation between the total scores of the two examiners was obtained at 0.88 (P <0.001). Moreover, the results of the convergent validity indicated the strongest correlation between ego development and ego strength (P<0.001). Conclusion: The results of the present study indicated that the WUSCT had the appropriate and acceptable validity and reliability in Iranian society. Accordingly, this test can be an appropriate tool for measuring persona
The relationship between managers’ ideal intelligence as a hybrid model and employees’ organizational commitment: a case study in Tehran University of Medical Sciences

High ideal hybrid intelligence of managers is among the factors that can improve employees’ organizational commitment. Therefore, this study aimed to determine the relationship between managers’ ideal hybrid intelligence and employees’ organizational commitment in the Vice Chancellors’ Headquarters of Tehran University of Medical Sciences. This was a descriptive-analytical and cross-sectional study conducted in 2017 - 2018. The research sample size consisted of 86 senior and middle-level managers selected through census method, as well as 181 employees, selected using the Kerjecie and Morgan table. The research tool was an ideal hybrid intelligence questionnaire consisting of 102 questions on cultural, moral and spiritual intelligence, and also Meyer and Allens’ organizational commitment questionnaire including 24 questions. Face validity and reliability of each questionnaire were confirmed by an expert panel and Chronbach’s alpha method. The data were analyzed by SPSS software, and descriptive results were shown through mean and standard deviation, and analytical results by inferential tests. The results showed that the ideal hybrid intelligence of the Vice Chancellors’ Headquarters managers and employees’ organizational commitment were at a desirable level. Also, there was a significant correlation between cultural, moral and spiritual intelligence as constituents of the ideal hybrid intelligence of managers and employees’ organizational commitment. We found that ideal hybrid intelligence may affect employees’ organizational commitment, but it should be mentioned that other forms of intelligence may also affect organizational commitment.
Socially Driven Joint Optimization of Communication, Caching, and Computing Resources in Vehicular Networks

To support multifarious vehicular applications, content sharing among vehicles or between vehicles and infrastructures can enable efficient service provisioning. In this work, we investigate joint communication, caching, and computing (3C) resource allocation to support efficient content sharing between content providers (CPs) and content requesters (CRs) in vehicular networks. To tackle the high complexity of joint 3C resource allocation, we decouple the problem into a long-term content caching strategy to allocate caching resources plus a method for short-term CP-CR pairing and corresponding communication-computing resource allocation. Specifically, a popularity and social similarity (P-SS) based caching strategy is proposed by incorporating both physical and social information. As selfish CRs may refuse to reveal their quality of service (QoS) requirements to the CPs and lead to the information asymmetry, we adopt contract theory to allocate communication and computing resources for each potential CR-CP pair. We then propose a stable-matching based algorithm to match CPs and CRs for efficient content sharing. Simulation results verify that the proposed scheme can effectively solve the problem with low complexity.
Investigation on the Aha-Experience as an Indicator of Correct Solutions in Functional Analysis in Engineering Design

Abstract The functional analysis of technical systems is an important part of the design process. To further improve the design process, especially the functional analysis, it must not be viewed as a monodisciplinary process. To this end, cognitive factors such as the aha-experience must also be included in studies of analysis processes to a greater extent. This paper investigates the relationship between the occurrence of aha-experiences and the correctness of solutions in the analysis of a technical system. An aha-experience is a strong feeling of subjective certainty that accompanies the cognitive process of suddenly finding a previously unknown solution. For this purpose, a study on the functional analysis was evaluated. The results show that many identified subfunctions of the system under investigation were identified with an aha-experience and that these subfunctions are more often correct. The results also suggest that aha-experiences occur more often among students than among experienced design engineers. Especially among students, a positive relation of aha-experiences on the correctness of the identified subfunction can be seen. This offers potential for further investigations to make aha-experiences useful in design methods.
Interpreting learning progress using assessment scores: what is there to gain?

Using assessment scores to quantify gains and growth trajectories for individuals and groups can provide a valuable lens on learning progress for all students. This paper summarises some commonly observed patterns of progress and illustrates these using data from ACER’s Progressive Achievement Test (PAT) assessments. While growth trajectory measurement requires scores for the same individuals over at least three but preferably more occasions, scores from only two occasions are naturally more readily available. The difference between two successive scores is usually referred to as gain. Some common approaches and pitfalls when interpreting individual student gain data are illustrated. It is concluded that pairs of consecutive scores are best considered as part of a longer-term trajectory of learning progress, and that caveated gain information might at best play a peripheral role until additional scores are available for individuals. This review is part of a larger program of research to inform future reporting developments at ACER.
MOLECULAR DOCKING ANALYSIS OF THIRTEEN COMPOUNDS AS MODULATOR OF IONOTROPIC GLUTAMATE RECEPTOR

Objectives: Ionotropic glutamate receptors (iGluRs) play a key role in the development and function of the nervous system. They also play an important in memory and learning process. They are implicated in various pathological conditions such as Alzheimer’s, Epilepsy, Huntington’s, and Parkinson’s diseases. This prompted us to carry out the present study on 13 selected compounds.Methods: These 13 compounds were evaluated on the docking behavior of iGluR-2 (iGluR2) using PatchDock. In addition, molecular physicochemical, drug-likeness, absorption, distribution, metabolism, and excretion analyses were also carried out.Results: The molecular physiochemical analysis revealed that all the 13 ligands showed nil violation and complied well with the Lipinski’s rule of five. ADME analysis showed that all the ligands (except ligands 1 and 12) predicated to have high gastrointestinal absorption property. Docking studies revealed that ligand 8 (dopamine) showed the highest atomic contact energy (ACE) (−78.14 kcal/mol), while ligand 9 (6-hydroxydopamine) showed the least ACE (−14.34 kcal/mol) with that of iGluR2. Similarly, ligand 8 (dopamine) has shown to interact with Ser 142 amino acid residue of iGluR2.Conclusion: Thus, the present study showed the potential of 13 compounds as a modulator of iGluR-2.
Coalitional strategies of the pharmaceutical supply chain with an option contract to cope with disruption risks

ABSTRACT After reviewing the problems of supply disruption caused by worldwide public health events, a two-echelon dual-marketing-channel supply model is presented in this paper, whose participants are one pharmaceutical company with disruption risks, one pharmaceutical company without disruption risks (NDPC), and one pharmaceutical retailer (PR). Their marketing consists of online and offline marketing channels. The PR signs an option contract with the NDPC to secure an adaptive and continuous pharmaceutical supply. The model is divided into three sub-models: single coalition structure, double coalition structure, and multi-party coalition structure, whose coalitional strategies and profits are investigated respectively. Their optimal decisions under disruption risks also are compared, and their pharmaceutical quality and process resilience are discussed. The merit of the model is to combine option contracts, government double subsidies, and business interruption insurance in the supply chain.
Importance of prognostic nutritional index in on-pump coronary artery bypass graft surgery

Objectives: A simple and appropriate risk index is still required to show the patient's nutritional status undergoing coronary artery bypass graft (CABG) surgery. This study aimed to evaluate the Prognostic Nutritional Index (PNI) value as a predictor of in-hospital mortality in patients undergoing CABG surgery. Methods: In this study, we scanned the medical data of 742 patients’ who underwent on-pump CABG surgery retrospectively. Patients' were divided into two groups based on the PNI cut-off value (high-risk group, PNI < 45.85, n = 230; low-risk group, PNI ≥ 45.85, n = 512). Results: To analyze the factors affecting in-hospital mortality in the postoperative period, univariate and multivariate logistic regression analysis was performed. In univariate analysis, advanced age (Odds ratio (OR): 1.219, 95% confidence interval (CI): 1.194-2.669, p < 0.001), left ventricular ejection fraction (LVEF) (OR: 3.471, 95% CI: 2.854-6.927, p < 0.001), total perfusion time (OR: 0.876, 95% CI: 0.690-0.954, p = 0.012), intra-aortic balloon pump (IABP) use (OR: 2.148, 95% CI: 1.394-2.889, p = 0.002), preoperative high creatinine (OR: 1.229, 95% CI: 1.066-2.118, p = 0.019), low lymphocyte count (OR: 0.879, 95% CI: 0.789-0.945, p = 0.017), low albumin (OR: 1.682, 95% CI: 1.433-2.765, p = 0.003), high C-reactive protein (CRP) (OR: 1.0.790, 95% CI: 0.678-0.927, p = 0.042) and low PNI (OR: 1.290, 95% CI: 1.119-1.654, p < 0.001) were correlated with the postoperative mortality. In multivariate logistic regression analysis, advanced age (OR: 1.145, 95% CI: 1.110-1.938, p = 0.017), LVEF (OR: 2.916, 95% CI: 1.768-4.928, p < 0.001), IABP use (OR: 1.880, 95% CI: 1.350-2.554, p = 0.032) and PNI (OR: 0.932, 95% CI: 0.889-0.978, p = 0.004) were independent predictors of mortality. Conclusions: In on-pump CABG surgery, postoperative mortality is associated with low preoperative PNI, and can be a useful and suitable parameter for preoperative risk evaluation.
The epidemiology and outcome of burn injuries in Iran: A ten-year systematic review and meta-analysis

Background: Burns, has always been one of the most catastrophic injuries. More than 3000000 people lose their lives every year due to burn and its results. Burn injury is the seventh major cause of disease burden of injuries in Iran. The evidence clearly shows that burns are preventable. It is necessary to update existing information and a more detailed assessment of burn aspects. Material-Method: Web of Science, PubMed, Scopus, and Embase databases were searched for published studies from Jan. 2010 to Dec. 2020, with the MeSH term ‘Burns’ and keywords such as burn, burn injury, burn injuries, Iran, epidemiology, and epidemio* combined by OR; AND, for published retrospective studies that focus on the epidemiology of burns in Iran. Results: Our systematic search identified seventeen studies containing epidemiological characteristics of burn injuries in Iran with a total number of 61662 patients. Results revealed that: The highest and lowest percentage of the burn was related to the age group of 20-29 and 0-9 years and 50-59 years; men were burned more than women. The urban residents and the person under the diploma have experienced more burns; married and single people were equally burned; burns caused by flame occurred more than the other cause of burn; male and female were burned almost equally by flame; Contact and electrical burns in men were more than women; most burn accidents occurred at home and winter; 14/23 % patient were expired, and men were discharged more than women but the death rate was higher in women.Conclusion: We conclude that burn injuries are common indoors, caused by flames, and in young patients with a low educational state, and the overall mortality of female burn victims is more remarkable than male burn victims. On the other hand, the mean TBSA of burn patients in Iran was 31%, and the mean rate of mortality was 14%, both of which are greater than the statistics reported by WHO. This review shows that further research is required to summarize the situation and the effectiveness of any preventive interventions.
SPNet: Siamese-Prototype Network for Few-Shot Remote Sensing Image Scene Classification

Few-shot image classification has attracted extensive attention, which aims to recognize unseen classes given only a few labeled samples. Due to the large intraclass variances and interclass similarity of remote sensing scenes, the task under such circumstance is much more challenging than general few-shot image classification. Most existing prototype-based few-shot algorithms usually calculate prototypes directly from support samples and ignore the validity of prototypes, which results in a decline in the accuracy of subsequent inferences based on prototypes. To tackle this problem, we propose a Siamese-prototype network (SPNet) with prototype self-calibration (SC) and intercalibration (IC). First, to acquire more accurate prototypes, we utilize the supervision information from support labels to calibrate the prototypes generated from support features. This process is called SC. Second, we propose to consider the confidence scores of the query samples as another type of prototypes, which are then used to predict the support samples in the same way. Thus, the information interaction between support and query samples is implicitly a further calibration for prototypes (so-called IC). Our model is optimized with three losses, of which two additional losses help the model to learn more representative prototypes and make more accurate predictions. With no additional parameters to be learned, our model is very lightweight and convenient to employ. The experiments on three public remote sensing image datasets demonstrate competitive performance compared with other advanced few-shot image classification approaches. The source code is available at https://github.com/zoraup/SPNet.
RIS-Assisted Advanced Spatial Modulation Techniques for Ambient Backscattering Communications

The dynamic control of wireless channels is a trending field of research which has been made possible by the advent of metamaterial-based reconfigurable intelligent surfaces (RIS). Moreover, for future applications in 5G and beyond, the device size constraints and power supply issues also need to be resolved before RIS can be deployed at large scale. Keeping these problems in mind, we propose RIS-assisted ambient backscattering (ABSc) communication framework utilizing advanced spatial modulation (ASM) techniques for spectral- and energy-efficient communication. Here, ABSc technique is leveraged for harnessing the power from ambient RF waves, while ASM techniques are deployed to ensure high spectral efficiencies by activating more than one but not the full set of antennas for transmission. Extensive performance analysis of ASM techniques are carried out, and upper-bounds on the ensuing error rates are derived. We corroborate the error rate upper-bound results with Monte-Carlo simulation results, and also provide comparative results to reveal the benefits of the proposed framework. In particular, it is shown that the ASM technique of improved quadrature spatial modulation (IQSM) can achieve the highest spectral efficiency. All the ASM techniques can perform better than the conventional spatial modulation technique by offering signal-to-noise power ratio gains of more than 2 dB. Additionally, RIS-assisted ASM techniques with ABSc perform better than the conventional frameworks without RIS.
Enhanced thermal stability and adsorption performance of MIL-53(Fe)@montmorillonite

Abstract Montmorillonite (Mnt), a clay mineral with a nanolayered structure, was combined with an Fe-based metal–organic framework (MOF; MIL-53(Fe)) using an in situ growth technique that yielded a novel eco-friendly clay-based adsorbent (MIL-53(Fe)@Mnt). The adsorbent was characterized by scanning electron microscopy, Fourier-transform infrared spectroscopy, X-ray diffraction, thermogravimetric analysis and N2 gas adsorption. The MIL-53(Fe) particles grew on the surface of the nanolayered Mnt and the MIL-53(Fe) particle size became smaller. The adsorption performance of MIL-53(Fe)@Mnt was investigated by removing methylene blue (MB), and optimization experiments were carried out to study the effects of contact time, pH, initial dye concentration and adsorbent mass on the adsorption processes. The MIL-53(Fe)@Mnt exhibited excellent adsorption capacity for MB, namely 313.7 mg g−1, which was 3.02 times and 3.54 times greater than that of pure Mnt and MIL-53(Fe), respectively. Adsorption was fitted with the Langmuir isotherm model and followed a pseudo-second order kinetic model. The MIL-53(Fe)@Mnt obtained is a low-cost and eco-friendly adsorbing material and might be a candidate for removing dyes during water treatment.
Mg isotope variations in microphases of unequilibrated enstatite chondrites

Magnesium, a major mineral‐forming element of the inner solar system, is partitioned between the silicate and the unique sulfidic phases (niningerite, MgS) of enstatite chondrites (ECs) owing to the formation of EC under exceptionally reducing conditions. In this study, we have carried out mineralogical characterization of the distinct Mg‐ and Si‐bearing phases of unequilibrated ECs (EH3). To evaluate the Mg isotope variations in such reduced planetary bodies, we have analyzed the Mg isotope composition of several enstatitic silicate phases, matrices (composed of mixed proportions of silicate and sulfidic phases), and bulk meteorite fractions micro milled from three EH3 chondrites. We found that the stable Mg isotope composition (expressed as δ25Mg) of the microphase separates of EH3 chondrites ranged from −0.216 ± 0.014‰ to −0.094 ± 0.014‰. Despite the dispersion in Mg isotope values, the average δ25Mg of the silicate fractions of the studied EH3 chondrites was similar to its matrix and bulk meteorite fractions. Mass‐dependent Mg isotope fractionation was evinced among the phase separates of EH3 chondrites with the slope of the fractionation line on a δ25Mg versus δ26Mg plot being closer to kinetic fractionation trend. Experimental and theoretical considerations hint that Mg isotope exchange between the silicate and sulfide phases might have generated the observed Mg isotope variations among the microphase separates of EH3 chondrites. Based on our Mg isotope data, in combination with the Si isotope composition obtained in the same aliquot of silicate–matrix fractions of EH3 chondrites and its subsolar Al/Si ratio, we suggest that the high abundance of Si in EC (due to the partitioning of Si among diverse silicates, silica, and metallic phases) and the loss of Mg and refractory components from EC‐forming regions could explain the lower Mg/Si ratio of EC compared to that of ordinary and carbonaceous chondrites.