Miracle-dz/UniFAR-FTUs huggingface dataset:
Fully Online Methods Courses? Reconceptualizing STEM Teacher Preparation Thr ough "Spaces of Learning"

Rather than viewing eLearning as being best suited for courses fitting a particular type, we suggest a paradigm shift, involving a reconceiving of the nature of instructional experiences within a course. We share how we have reconceptualized mathematics and science (STEM) teacher preparation at the University of Colorado Denver (CU Denver) through designing and implementing fully online methods courses for our prospective STEM teachers (pSTEMs). Our fully online methods courses incorporate Spaces of Learning (SOL)—multidimensional instructional experiences that provide opportunities for pSTEMs to engage in a variety of activities designed to promote and scaffold their investigation of, reflection on, and response to STEM teaching practices. By reconceptualizing what it means to engage in STEM teacher preparation, we are expanding possibilities for our pSTEMs through their participation in SOL.
Characterizing donation behavior from psychophysiological indices of narrative experience

Research on narrative persuasion has yet to investigate whether this process influences behavior. The current study explored whether: (1) a narrative could persuade participants to donate to a charity, a prosocial, behavioral decision; (2) psychophysiological metrics can delineate the differences between donation/non-donation behaviors; and (3) donation behavior can be correlated with measures of psychophysiology, self-reported reactions to the narrative, and intrinsic characteristics. Participants (n = 49) completed personality/disposition questionnaires, viewed one of two versions of a narrative while EEG and ECG were recorded, completed a questionnaire regarding their reactions to the narrative, and were given an opportunity to donate to a charity related to the themes of the narrative. Results showed that: (1) 34.7% of participants donated; (2) psychophysiological metrics successfully delineated between donation behaviors and the effects of narrative version; and (3) psychophysiology and reactions to the narrative were better able to explain the variance (88 and 65%, respectively) in the amount donated than all 3 metrics combined as well as any metric alone. These findings demonstrate the promise of narrative persuasion for influencing prosocial, behavioral decisions. Our results also illustrate the utility of the previously stated metrics for understanding and possibly even manipulating behaviors resulting from narrative persuasion.
THz water content analysis in biomass material

Biomass material is getting importance thanks to the new developments done in the energetic sector. Quality control is of great interest to optimize its production. Moisture level quality control of the product is a key point in this sector. Therefore, taking advantage of the sensibility presented by THz waves to water, a viability study to control the water content in biomass material in THz frequencies is presented here. Several species, sample granulometries and moisture level have been taken into account. Good agreement between the water content and the measurement has been measured but affected by the influence of the shape of the samples.
To Tree or Not to Tree? Genome-Wide Quantification of Recombination and Reticulate Evolution during the Diversification of Strict Intracellular Bacteria

It is well known that horizontal gene transfer (HGT) is a major force in the evolution of prokaryotes. During the adaptation of a bacterial population to a new ecological niche, and particularly for intracellular bacteria, selective pressures are shifted and ecological niches reduced, resulting in a lower rate of genetic connectivity. HGT and positive selection are therefore two important evolutionary forces in microbial pathogens that drive adaptation to new hosts. In this study, we use genomic distance analyses, phylogenomic networks, tree topology comparisons, and Bayesian inference methods to investigate to what extent HGT has occurred during the evolution of the genus Rickettsia, the effect of the use of different genomic regions in estimating reticulate evolution and HGT events, and the link of these to host range. We show that ecological specialization restricts recombination occurrence in Rickettsia, but other evolutionary processes and genome architecture are also important for the occurrence of HGT. We found that recombination, genomic rearrangements, and genome conservation all show evidence of network-like evolution at whole-genome scale. We show that reticulation occurred mainly, but not only, during the early Rickettsia radiation, and that core proteome genes of every major functional category have experienced reticulated evolution and possibly HGT. Overall, the evolution of Rickettsia bacteria has been tree-like, with evidence of HGT and reticulated evolution for around 10–25% of the core Rickettsia genome. We present evidence of extensive recombination/incomplete lineage sorting (ILS) during the radiation of the genus, probably linked with the emergence of intracellularity in a wide range of hosts.
Implementation of adaptive coded aperture imaging using a digital micro-mirror device for defocus deblurring

Digital image processing (DIP) and computational photography are ever growing fields with new focuses on coded aperture imaging and its real world applications. Traditional coded aperture imaging systems consisted of statically coded masks that were designed and constructed from cardboard or other opaque materials and could not be altered once their shape had been defined. This is undesirable as numerous aperture pattern masks exist, each with their own advantages and disadvantages, and alternating between aperture shapes with a traditional camera quickly and efficiently is impractical. This paper aims towards developing an adaptive coded aperture imaging system utilizing a digital micro-mirror device (DMD) as a programmable aperture that is able to switch between different aperture patterns quickly and efficiently. This provides all the advantages of traditional coded aperture imaging systems but without the disadvantage of having a static aperture in the aperture plane.
Chronic Kidney Disease and Health Status Outcomes Following Acute Myocardial Infarction

Background The association between chronic kidney disease (CKD) and health status outcomes after acute myocardial infarction (AMI) is unknown. Methods and Results Patients were enrolled between 2005 and 2008 in the Translational Research Investigating Underlying Disparities in Acute Myocardial Infarction Patients' Health Status (TRIUMPH) registry, a prospective multicenter observational study of AMI outcomes. The Seattle Angina Questionnaire and Short Form‐12 were collected at baseline and at 1, 6, and 12 months following AMI. CKD was defined by an estimated glomerular filtration rate <60 mL/min, calculated during the AMI hospitalization. Linear repeated‐measures models assessed the association between CKD and health status after AMI, accounting for the propensity to have follow‐up heath status measures. Of 3617 patients, 576 (16%) had CKD and 3041 (84%) did not have CKD. Patients with CKD were older and had more comorbidity. Patients with CKD were more likely to have multivessel coronary disease and less likely to undergo revascularization. Among AMI survivors, patients with and without CKD had similar health‐related quality of life (adjusted difference of 0.24, 95% CI −1.46 to 1.95), angina frequency (adjusted difference of 1.27, 95% CI −0.05 to 2.58), and mental health (adjusted difference of −0.07, 95% CI −0.90 to 0.75). In contrast, patients with CKD had lower physical health (adjusted difference −1.61, 95% CI −2.49 to −0.74), which was not clinically significant, compared with patients without CKD. Conclusions Among AMI survivors, patients with CKD not only had more comorbidities but also, after adjusting for these patient differences, had similar health status compared with patients without CKD. Interventions aimed at improving health status after AMI should not focus on CKD status.
Overview of wideband Butler matrix in microstrip-slot technology for beamforming antenna applications

This paper describes the development of 4×4 wideband compact Butler matrix operating between 1.6 GHz and 2.4 GHz. In order to attain wideband characteristics, the matrix uses microstrip-slot technology, which involves two microstrip dielectric layers with a shared ground plane and a coupling slot. The multilayer beamforming network design is compact in size and avoids the use of crossovers, which makes it more advantageous than the conventional Butler matrix. To verify the performances of the beamformer, a four-antenna array is connected to the proposed 4×4 Butler matrix to shape a switched-beam system. Simulation results are presented and discussed.
Operational and fairness issues with connection-less traffic over IEEE802.11b

The IEEE802.11 group has ratified high rate (HR) extensions to enable high speed wireless communications over WLANs. The HR extensions specified in revision IEEE802.11b, encompass mainly new RF modulation schemes. This paper attempts an experimental evaluation of the performance characteristics of 802.11b in terms of throughput and loss over high speed transmission rates with respect to connection-less network traffic. We present a simple analysis of the protocol's throughput capacity over high speed rates while we reveal fundamental design considerations that prevent 802.11b from reaching its true throughput potentials in the light of rate adaptivity. We further recommend some extensions to the medium access control (MAC) protocol sub-layer that reconsider the multi-rate compatibility requirement while maintaining fairness in throughput between nodes at short or long distances within range from a base station (BS). The recommendations subject to simulations as work in-progress, expect to effect improvements in throughput over a proportionally-fair rate fallback scheme, in the order of 15% for transmission rates of 11 Mbps. We also provide some key observations to enable efficient protocol design for adaptive mobile environments.
Trip Recommendation Meets Real-World Constraints

As location-based social network (LBSN) services become increasingly popular, trip recommendation that recommends a sequence of points of interest (POIs) to visit for a user emerges as one of many important applications of LBSNs. Personalized trip recommendation tailors to users’ specific tastes by learning from past check-in behaviors of users and their peers. Finding the optimal trip that maximizes user’s experiences for a given time budget constraint is an NP-hard problem and previous solutions do not consider three practical and important constraints. One constraint is POI availability, where a POI may be only available during a certain time window. Another constraint is uncertain traveling time, where the traveling time between two POIs is uncertain. In addition, the diversity of the POIs included in the trip plays an important role in user’s final adoptions. This work presents efficient solutions to personalized trip recommendation by incorporating these constraints and leveraging them to prune the search space. We evaluated the efficiency and effectiveness of our solutions on real-life LBSN datasets.
Improving intention realisation using emotional cues and implementation intentions.

Background: Remembering to act to realise an intention in the future is an important ability that comprises several cognitive processes, known collectively as prospective memory. Prospective memory failures can be costly, and so the effectiveness of strategies to improve prospective memory is an important area of investigation. Aim: To investigate whether ‘if [cue] – then [response]’ plans, known as implementation intentions, are effective at improving prospective memory and whether their effectiveness can be enhanced by the use of emotionally-valenced cues. Method: A systematic review and set of meta-analyses were conducted to consolidate the current knowledge on the effectiveness of emotional cues at improving prospective memory. Two experimental studies were then conducted which utilised implementation intentions in combination with emotional cues to improve prospective memory in a computer-based task (Experiment 1) and a naturalistic hand-washing task (Experiment 2). Results: The results of the meta-analyses confirmed that despite contradictory results, emotional cues can improve prospective memory. However, the benefit is dependent on both the valence of the emotional cues and the timing of the manipulation of the valence of the cues. The results of the two experimental studies were inconclusive as to whether the strategies of emotional cues and implementation intentions are effective together. In the first experiment, emotional cues were effective at improving prospective memory whereas implementation intentions were not, and in the second experiment the opposite pattern was observed. Conclusion: Although the use of emotional cues and implementation intentions were not observed to be effective together in the present research, important moderating variables were identified that improve our knowledge of the parameters of effectiveness of both implementation intentions and emotional cues. Further research is suggested to continue this line of investigation.
Self-Triggered Feedback Control Systems With Finite-Gain ${\cal L}_{2}$  Stability

This paper examines a class of real-time control systems in which each control task triggers its next release based on the value of the last sampled state. Prior work used simulations to demonstrate that self-triggered control systems can be remarkably robust to task delay. This paper derives bounds on a task's sampling period and deadline to quantify how robust the control system's performance will be to variations in these parameters. In particular we establish inequality constraints on a control task's period and deadline whose satisfaction ensures that the closed-loop system's induced L 2 gain lies below a specified performance threshold. The results apply to linear time-invariant systems driven by external disturbances whose magnitude is bounded by a linear function of the system state's norm. The plant is regulated by a full-information H infin controller. These results can serve as the basis for the design of soft real-time systems that guarantee closed-loop control system performance at levels traditionally seen in hard real-time systems.
Methylation of Cervical Neoplastic Cells Infected With Human Papillomavirus 16

Objective This study was conducted to evaluate the role of methylation of adenylate cyclase activating peptide 1 (ADCYAP1), paired box gene 1 (PAX1), cell adhesion molecule 1 (CADM1), and T-lymphocyte maturation–associated protein (MAL) during carcinogenesis. Methods We evaluated the methylation of 4 genes by using the cervical carcinoma cell lines (CaSki, SiHa, HeLa, and C33A) and cervical neoplastic cells from 56 subjects with human papillomavirus 16 (HPV16)–infected low-grade squamous intraepithelial lesions (LSILs), 50 subjects with HPV16-infected high-grade squamous intraepithelial lesions (HSILs), and 24 subjects with HPV16-infected invasive cervical cancer who attended Seoul St. Mary’s Hospital. Methylation of the 4 genes was evaluated using quantitative bisulfate pyrosequencing. Results The ADCYAP1 promoter was hypermethylated in the 4 cell lines (CaSki, 97.40 ± 1.39; SiHa, 82.04 ± 17.02; HeLa, 96.14 ± 2.08; and C33A, 78 ± 10.18). PAX1 and CADM1 were hypermethylated in the HPV16/18-infected cell lines CaSki (PAX1, 91.18 ± 9.91; CADM1, 93.5 ± 7.33), SiHa (PAX1, 96.14 ± 2.08; CADM1, 93.15 ± 8.81), and HeLa (PAX1, 82.04 ± 17.02; CADM1, 92.43 ± 9.95). MAL was hypermethylated in the CaSki cell line (96.04 ± 4.74). Among human cervical neoplastic cells, the methylation indices of ADCYAP1 were 7.8 (95% confidence interval [95% CI], 7.0–8.6) in subjects with LSILs and 39.8 (95% CI, 29.0–54.7) in those with cervical cancer (P < 0.001); for PAX1, 7.2 (95% CI, 6.1–8.5) and 37.8 (95% CI, 27.1–52.7), respectively; for CADM1, 3.5 (95% CI, 3.0–4.0) and 17.7 (95% CI, 10.8–29.1), respectively; for MAL, 2.7 (95% CI, 2.5–3.0) and 13.0 (95% CI, 7.6–22.0), respectively (P < 0.001 for each). Immunohistochemical staining results were positive in the cytoplasm of subjects with low methylation of the 4 gene promoters; however, they were negative in the cytoplasm of those with hypermethylation of the 4 gene promoters. Conclusions The results of this study suggest that the methylation of ADCYAP1, PAX1, CADM1, and MAL may be highly associated with the development of cervical cancer, and that gene expression can be suppressed by gene promoter hypermethylation.
Identifying Synonymy between SNOMED Clinical Terms of Varying Length Using Distributional Analysis of Electronic Health Records

Medical terminologies and ontologies are important tools for natural language processing of health record narratives. To account for the variability of language use, synonyms need to be stored in a semantic resource as textual instantiations of a concept. Developing such resources manually is, however, prohibitively expensive and likely to result in low coverage. To facilitate and expedite the process of lexical resource development, distributional analysis of large corpora provides a powerful data-driven means of (semi-)automatically identifying semantic relations, including synonymy, between terms. In this paper, we demonstrate how distributional analysis of a large corpus of electronic health records - the MIMIC-II database - can be employed to extract synonyms of SNOMED CT preferred terms. A distinctive feature of our method is its ability to identify synonymous relations between terms of varying length.
Rule Discovery for Binary Classification Problem using ACO based Antminer

mining can be performed by number of ways. Classification is one of them. Classification is a data mining technique that assigns items to a predefined categories or classes or labels. The aim of classification is to predict the target class for the inputted data. On the other hand biology inspired algorithms such as Genetic Algorithms (GA) and Swarm based approaches like Particle Swarm Optimization (PSO) and Ant Colonies Optimization (ACO) were used in solving many data mining problems and currently the most prominent choice in the area of swarm intelligence. In this paper binary classification is considered as an area of problem and a modified AntMiner is used to solve the problem. The basic algorithm of AntMiner has been modified with a different classification accuracy function.
Blind system identification using minimum noise subspace

Developing fast and robust methods for identifying multiple FIR channels driven by an unknown common source is important for wireless communications. In this letter, we present a new method that exploits a minimum noise subspace (MNS). The MNS is computed from a set of channel output pairs which form a "tree". The "tree" exploits with minimum redundancy the diversity among all channels. The MNS method is much more efficient in computation and only slightly less robust to channel noise than the subspace method by Moulines et al. (1995).
No risk, no fun: implications for positioning of online casinos

Abstract This study uses textual content analysis of online casinos to provide insights into how operators position themselves in the market. Qualitative data from the About Us pages of 19 online gambling websites is gathered and analysed using DICTION software. The resulting z-scores are further analysed using the Hierarchical Clustering on Principal Components (HCPC) function in the FactoMineR software package. Results indicate that the casinos investigated group into three distinct and meaningful clusters (activity/realism; low certainty; high certainty). The results confirm that this exploratory methodology, which combines computerized lexical analysis using DICTION and HCPC, is able to identify positioning differences. In addition, the presence of a relationship between identified clusters and casino rankings is also considered. Its confirmation suggests that casinos that emphasize risk (low certainty) are more likely to obtain higher rankings. The Web has provided a platform for a global online gambling industry where differentiation and positioning is crucial. Therefore, managers need to emphasize in their online and offline communication the often-held perception that one of the attractions of gambling is the thrill or excitement of beating the odds. Limitations are noted and possible areas for further research are indicated.
Study on E-learning System Model based on Affective Computing

Aiming at emotion deficiency in present E-Learning system, a lot of negative effects were analyzed and corresponding countermeasures were proposed. Basing on it, we combined affective computing with the traditional E-Learning system. The model of E-Learning system based on affective computing was constructed by using audiovisual emotion, which took both facial and audio features as input data. Our simulation experiment results showed that rough set theory was effective in emotion recognition, and a high recognition rate is resulted . Besides, other key techniques of realizing the system such as tracking the change of emotion state and adjusting teaching strategies were also introduced.
Analysis of segmentation scheme for diseased rice leaves

For any automated image analysis process, the segmentation is an important task because all subsequent tasks in image processing heavily rely on the quality of image segmentation. It determines the eventual success or failure of the analysis. The problem in image segmentation occurs when an image has a varying gray level background. There are several algorithms and methods are available for image segmentation, but there is a need to develop a unique method for it. In this paper, some of the image segmentation algorithms are compared to segment the diseased portion of rice leaves.
Co-morbidity of gambling and Internet use among Internet and land-based gamblers: classic and network approaches

Abstract This study investigated co-morbidity of problem gambling and problematic Internet use (PIU) among adolescent Internet and land-based gamblers, with the classic approach using sum-scores of symptoms and a promising new method, namely the network perspective. This perspective allows testing for how multiple disorders are associated, showing symptoms overlap and centralities. We used cross-sectional data from two population-based samples of adolescents aged 17 years in France (n = 2,240) and Switzerland (n = 944). Measures included Internet gambling, problem gambling and PIU. The classic approach showed that Internet gambling was associated with increased levels of disordered gambling and PIU, but that correlations between disorders were weak (R2 min = 3.2%, R2 max = 17.6%). The network perspective showed that the co-morbid network of Internet gamblers was more connected in comparison with land-based gamblers. Problem gambling and PIU appeared as separate disorders, but their relationship was increased among Internet gamblers in comparison with land-based gamblers. The network perspective appeared as a promising avenue for a better understanding of addictive disorders, but it should not replace the classic approach, which showed increased levels of addictive behaviours among Internet gamblers.