Miracle-dz/UniFAR-FTUs huggingface dataset:
Benzoic acid derivatives from Piper species and their antiparasitic activity.

Piper glabratum and P. acutifolium were analyzed for their content of main secondary constituents, affording nine new benzoic acid derivatives (1, 2, 4, 5, 7, and 10-13), in addition to four known compounds (3, 6, 8, and 9). Their structures were elucidated on the basis of spectroscopic data. Riguera ester reactions and optical rotation measurements established the new compounds as racemates. In the search for antiparasitic agents, the compounds were evaluated in vitro against the promastigote forms of Leishmania spp. , Trypanosoma cruzi, and Plasmodium falciparum. Among the evaluated compounds, methyl 3,4-dihydroxy-5-(3'-methyl-2'-butenyl)benzoate (7) exhibited leishmanicidal effect (IC50 13.8-18.5 microg/mL) against the three Leishmania strains used, and methyl 3,4-dihydroxy-5-(2-hydroxy-3-methylbutenyl)benzoate (1), methyl 4-hydroxy-3-(2-hydroxy-3-methyl-3-butenyl)benzoate (3), and methyl 3,4-dihydroxy-5-(3-methyl-2-butenyl) benzoate (7) showed significant trypanocidal activity, with IC50 values of 16.4, 15.6, and 18.5 microg/mL, respectively.
Global Ensemble Forecast System (GEFS) Predictions of Days 1–15 U.S. Tornado and Hail Frequencies

U.S. severe convective storms have grown to represent a 10 billion dollar annual peril for the insurance industry, and their accurate prediction remains a challenging task. This study examines days 1–15 severe convective storm predictions from the Global Ensemble Forecast System (GEFS). GEFS forecasts are based on the Supercell Composite Parameter and verified against spatially smoothed tornado and hail reports over the periods 1 March to 31 May 2016–2017. Skill is analyzed for deterministic forecasts (ensemble mean Supercell Composite Parameter exceeding specified thresholds) and probabilistic forecasts (fraction of ensemble members exceeding specified thresholds). Deterministic forecasts of tornado and hail activities are statistically more skillful than a random no‐skill reference to days 9 and 12, respectively. Probabilistic forecasts are skillful relative to climatological no‐skill reference to day 9 for tornado and day 12 for hail activity. These results provide a useful baseline for further improvement of tornado and hail forecasts at these ranges.
Face recognition based on Gradient Gabor feature

In this paper, a novel gradient Gabor (GGabor) filter is proposed to extract multi-scale and multi-orientation features to represent and classify faces. Gradient Gabor combines the derivative of Gaussian functions and the harmonic functions to capture the features in both spatial and frequency domains to deliver orientation and scale information. The spatial positions are combined into Gaussian derivatives which allows it to provide more stable information. An efficient Kernel Fisher analysis method is proposed to find multiple subspaces based on both GGabor magnitude and phase features, which is a local kernel mapping method to capture the structure information in faces. Experiments on two face databases, FRGC Version 1 and FRGC Version 2, are conducted to compare the performances of the Gabor and GGabor features, which show that GGabor can also be a powerful tool to model faces, and the Efficient Kernel Fisher classifier can improve the efficiency of the original kernel fisher method.
A Dynamic Multiarmed Bandit-Gene Expression Programming Hyper-Heuristic for Combinatorial Optimization Problems

Hyper-heuristics are search methodologies that aim to provide high-quality solutions across a wide variety of problem domains, rather than developing tailor-made methodologies for each problem instance/domain. A traditional hyper-heuristic framework has two levels, namely, the high level strategy (heuristic selection mechanism and the acceptance criterion) and low level heuristics (a set of problem specific heuristics). Due to the different landscape structures of different problem instances, the high level strategy plays an important role in the design of a hyper-heuristic framework. In this paper, we propose a new high level strategy for a hyper-heuristic framework. The proposed high-level strategy utilizes a dynamic multiarmed bandit-extreme value-based reward as an online heuristic selection mechanism to select the appropriate heuristic to be applied at each iteration. In addition, we propose a gene expression programming framework to automatically generate the acceptance criterion for each problem instance, instead of using human-designed criteria. Two well-known, and very different, combinatorial optimization problems, one static (exam timetabling) and one dynamic (dynamic vehicle routing) are used to demonstrate the generality of the proposed framework. Compared with state-of-the-art hyper-heuristics and other bespoke methods, empirical results demonstrate that the proposed framework is able to generalize well across both domains. We obtain competitive, if not better results, when compared to the best known results obtained from other methods that have been presented in the scientific literature. We also compare our approach against the recently released hyper-heuristic competition test suite. We again demonstrate the generality of our approach when we compare against other methods that have utilized the same six benchmark datasets from this test suite.
Red fluorescence in coral larvae is associated with a diapause‐like state

Effective dispersal across environmental gradients is the key to species resilience to environmental perturbation, including climate change. Coral reefs are among the most sensitive ecosystems to global warming, but factors predicting coral dispersal potential remain unknown. In a reef‐building coral Acropora millepora, larval fluorescence emerged as a possible indicator of dispersal potential since it correlates with responsiveness to a settlement cue. Here, we show that gene expression in red fluorescent larvae of A. millepora is correlated with diapause‐like characteristics highly likely to be associated with extended dispersal. We compared gene expression among three larval fluorescent morphs under three coloured light treatments. While colour morphs did not differ in their gene expression responses to light colour, red larvae demonstrated gene expression signatures of cell cycle arrest and decreased transcription accompanied by elevated ribosome production and heightened defenses against oxidative stress. A meta‐analysis revealed that this profile was highly similar to the signatures of elevated thermal tolerance in the same coral species, and moreover, functionally resembled diapause states in an insect and a nematode. Our results support a connection between red fluorescence and long‐range dispersal, which offers a new perspective on the molecular underpinnings of coral larval dispersal and the biological function of GFP‐like fluorescent proteins.
Innovative Mobile Robot Method: Improving the Learning of Programming Languages in Engineering Degrees

This paper describes a study of teaching a programming language in a C programming course by having students assemble and program a low-cost mobile robot. Writing their own programs to define the robot’s behavior raised students’ motivation. Working in small groups, students programmed the robots by using the control structures of structured programming. Over the course, there was a significant improvement in students’ academic performance and motivation. The approach took into account four of the motivational factors that feature in the ARCS model: 1) attention; 2) relevance; 3) confidence; and 4) satisfaction. The main achievements of the approach were to be able to: 1) catch and hold students’ attention throughout the course; 2) increase students’ confidence in the learning process; 3) achieve a high student satisfaction level with their acquired skills; and 4) demonstrate to students the practical usefulness of the knowledge they had learned. This paper also determines the extent to which this strategy was effective in meeting the teaching goals.
Preserving Versatility in Event-Based Middleware

Existing commercial and research event-based middleware are limited in their ability to evolve in order to support the requirements of novel applications. As a result, new infrastructures are being proposed to attend to widening scope and changing demands. In this paper, we define the concept of versatility generally and survey existing approaches that can be used to develop and preserve versatility in middleware. We discuss our research in designing, implementing, and preserving versatility in event-based middleware using YANCEES, a versatile event notification service we are developing. The design of the system is briefly presented and the lessons learned
Option Pricing by Fuzzy Logic Based Signal Processing

One of the best examples of mathematically rigorous signal processing in finance is the Black-Scholes model for price evolution of financial options. To address the same problem, this paper proposes a Takagi-SugenoKang (TSK) fuzzy rule-based option pricing model that requires only a small number of rules to describe highly complex financial signals such as option prices. The findings for this data-driven approach indicate that the TSK model presents a robust option pricing tool that is superior to an array of well-known parametric models from the literature, including the Black-Scholes model. In addition, its predictive performance is consistently no worse than that of a non-parametric feedforward neural network model.
Tuberculosis Incidence Rates during 8 Years of Follow-Up of an Antiretroviral Treatment Cohort in South Africa: Comparison with Rates in the Community

Background Although antiretroviral therapy (ART) is known to be associated with time-dependent reductions in tuberculosis (TB) incidence, the long-term impact of ART on incidence remains imprecisely defined due to limited duration of follow-up and incomplete CD4 cell count recovery in existing studies. We determined TB incidence in a South African ART cohort with up to 8 years of follow-up and stratified rates according to CD4 cell count recovery. We compared these rates with those of HIV-uninfected individuals living in the same community. Methodology/Principal Findings Prospectively collected clinical data on patients receiving ART in a community-based cohort in Cape Town were analysed. 1544 patients with a median follow-up of 5.0 years (IQR 2.4–5.8) were included in the analysis. 484 episodes of incident TB (73.6% culture-confirmed) were diagnosed in 424 patients during 6506 person-years (PYs) of follow-up. The TB incidence rate during the first year of ART was 12.4 (95% CI 10.8–14.4) cases/100PYs and decreased to 4.92 (95% CI 3.64–8.62) cases/100PYs between 5 and 8 years of ART. During person-time accrued within CD4 cell strata 0–100, 101–200, 201–300, 301–400, 401–500, 501–700 and ≥700 cells/µL, TB incidence rates (95% CI) were 25.5 (21.6–30.3), 11.2 (9.4–13.5), 7.9 (6.4–9.7), 5.0 (3.9–6.6), 5.1 (3.8–6.8), 4.1 (3.1–5.4) and 2.7 (1.7–4.5) cases/100PYs, respectively. Overall, 75% (95% CI 70.9–78.8) of TB episodes were recurrent cases. Updated CD4 cell count and viral load measurements were independently associated with long-term TB risk. TB rates during person-time accrued in the highest CD4 cell count stratum (>700 cells/µL) were 4.4-fold higher that the rate in HIV uninfected individuals living in the same community (2.7 versus 0.62 cases/100PYs; 95%CI 0.58–0.65). Conclusions/Significance TB rates during long-term ART remained substantially greater than rates in the local HIV uninfected populations regardless of duration of ART or attainment of CD4 cell counts exceeding 700 cells/µL.
Motor and Sensory Impairments in Children with Intractable Epilepsy

During a 3‐year period (1988–1991), 72 children with severe intractable epilepsy were studied. A standardized protocol for assessment of motor and sensory function was designed for school age children. Function was quantified on a 4‐point scale on 47 items, including gross motor function, balance, coordination, strength, range of motion (ROM), velocity, fine motor function, sensation, perception, and neurologic tests. Classification of handicaps according to World Health Organization (WHO) definitions was performed. Videotape documentation completed the assessment. Evaluation of treatment services showed that provision of rehabilitation services had been insufficient and provided only for children with additional major movement disorders, mainly cerebral palsy (CP) cases. To minimize the handicap in children with severe epilepsy, it is essential to clarify the total sensorimotor impairment pattern, including balance, co‐ordination, and perceptual capacity. Impairments in these functions are, as shown in this study, frequent and exist independent of major disabilities such as mental retardation or cerebral palsy. When several neuroimpairments were identified, a multiplicative rather than an additive effect on the total handicap was evident.
Vaccine-Induced Boosting of Influenza Virus-Specific CD4 T Cells in Younger and Aged Humans

Current yearly influenza virus vaccines induce strain-specific neutralizing antibody (NAb) responses providing protective immunity to closely matched viruses. However, these vaccines are often poorly effective in high-risk groups such as the elderly and challenges exist in predicting yearly or emerging pandemic influenza virus strains to include in the vaccines. Thus, there has been considerable emphasis on understanding broadly protective immunological mechanisms for influenza virus. Recent studies have implicated memory CD4 T cells in heterotypic immunity in animal models and in human challenge studies. Here we examined how influenza virus vaccination boosted CD4 T cell responses in younger versus aged humans. Our results demonstrate that while the magnitude of the vaccine-induced CD4 T cell response and number of subjects responding on day 7 did not differ between younger and aged subjects, fewer aged subjects had peak responses on day 14. While CD4 T cell responses were inefficiently boosted against NA, both HA and especially nucleocaspid protein- and matrix-(NP+M) specific responses were robustly boosted. Pre-existing CD4 T cell responses were associated with more robust responses to influenza virus NP+M, but not H1 or H3. Finally pre-existing strain-specific NAb decreased the boosting of CD4 T cell responses. Thus, accumulation of pre-existing influenza virus-specific immunity in the form of NAb and cross-reactive T cells to conserved virus proteins (e.g. NP and M) over a lifetime of exposure to infection and vaccination may influence vaccine-induced CD4 T cell responses in the aged.
Factors Contributing Towards Technology Development in Small Firms

The importance of MSMEs in India became crucial in rural areas because it promoted economic growth. MSMEs play a significant role in the economic growth of the country owing to production, exports and employment. Technology development reflect a critical way in which organization respond to either technological or market challenges. The present survey examines the characteristics of technology development in MSMEs. The results show that Indian MSMEs do not co-operate with universities and R&D institutes. Government policies also affect the technology development activities. The awareness about the R&D infrastructure is very low as shown by the results in the study. There is a need to understand and assess the real needs of the MSMEs and accordingly devise approaches that ensure their sustainable growth. Keywords—MSMEs, technology development, networks, financial management and R&D infrastructure.
Identifying regulatory signals in DNA-sequences with a nonstatistical approximation approach

The identification of regulatory signals is one of the most challenging tasks in bioinformatics. The development of gene-profiling technologies now makes it possible to obtain vast data on gene expression in a particular organism under various conditions. This has created the opportunity to identify and analyze the parts of the genome believed to be responsible for transcription control-the transcription factor DNA-binding motifs (TFBMs). Developing a practical and efficient computational tool to identify TFBMs will enable us to better understand the interplay among thousands of genes in a complex eukaryotic organism. This problem, which is mathematically formulated as the motif finding problem in computer science, has been studied extensively in recent years. We develop a new mathematical model and approximation technique for motif searching. Based on the graph theoretic and geometric properties of this approach, we propose a nonstatistical approximation algorithm to find motifs in a set of genome sequences.
The Use of Cryogenic HEMT Amplifiers in Wide Band Radiometers

Advances in device fabrication, modelling and design techniques have made wide band, low noise cryogenic amplifiers available at frequencies up to 106 GHz. Microwave radiometry applications as used in radio astronomy capitalize on the low noise and large bandwidths of these amplifiers. Radiometers must be carefully designed so as to preclude sensitivity degradations caused by small, low frequency gain fluctuations inherent in these amplifiers.
Gamifying Collaborative Activities in MOOCs

MOOCs can bring together thousands of students with different background in the same course. This fact presents a good opportunity for instructors to design and enact collaborative activities that may involve groups. However, MOOCs present some drawbacks that can hinder the completion of this kind of activities such as the high dropout rates, the self-paced character or the resistance of the students to abandon their comfort zone. The use of gamification in MOOC contexts has shown potential benefits to enhance students’ engagement, encourage students to interact with others and promote activity submission, which can be useful for increasing the completion of such collaborative activities. This paper shows the gamification design, and the first outcomes, of a MOOC that involves gamified and collaborative activities. To carry this out, the course was configured with 15 badges that students can achieve when performing social and optional actions for completing the course.
Dystocia in beef heifers: A review of genetic and nutritional influences

Abstract Breeding beef heifers for the first time at 15 months of age has potential to increase the efficiency of the beef breeding-cow herd. An increased incidence of dystocia in heifers calving at 2 years of age, compared to mature cows, is a major reason many farmers in New Zealand have not adopted the practice. The predominant type of dystocia affecting 2-year-old heifers is feto-maternal disproportion, a condition in which the fetus is too large relative to the size of the heifer's pelvis. Reducing birthweight of the calf is a means of reducing the incidence of dystocia. Birthweight and length of gestation are determined by genotype of the calf, maternal genetic effects and environmental effects. Bulls with low estimated breeding values for birthweight have been selected for mating heifers; however, the positive genetic correlation between birthweight and mature weight meant that the progeny of these bulls tended to be lighter at finishing, making them less desirable in the beef industry. The genotype of the dam also plays a role in determining the risk of dystocia; the maternal ability of the dam to nurture the fetus influences birth- weight, and the dam's genetic potential for growth influences the size of her pelvic area. Heavy heifers tend to produce high- birthweight calves, counteracting the reduction in the incidence of dystocia resulting from the larger pelvis in larger heifers. Manipulating feeding level during pregnancy offers an alternative method for manipulating the birthweight of calves. Little is known about the effects of nutrition in early gestation on placental development or birthweight of calves. No differences in the birthweight of calves have been observed in response to variation in feeding in mid-pregnancy, and variable responses in birthweight and the incidence of dystocia to feeding in the third trimester of pregnancy have been reported. Differences in birthweight have not always resulted in differences in the incidence of dystocia, primarily due to differences in liveweight of the heifer also induced by feeding regimens. Variability in the incidence of dystocia in response to feeding level in the third trimester of pregnancy makes it difficult to make recommendations for the feeding of heifers at this stage of gestation. More research is needed into the effects of nutrition in early gestation on fetal and placental development in cattle.
Bifurcation and control of a delayed diffusive logistic model in online social networks

Online social networks have become a popular source for disseminating information and facilitating the building of social relations among a huge number of people. Recently, several partial differential equations were proposed to model the spatio-temporal dynamics of information diffusion in online social networks. As a result, mathematical results of reaction-diffusion equations can be used to help understand the mechanism of information diffusion and, in particular, increase the efficiency of distributing positive information while reducing unwanted information. In this paper, we develop a Partial Differential Equation (PDE) with a delayed feedback controller to effectively control the spread of harmful information. Applying the theory of partial function differential equation, we present verifiable control conditions for stability and Hopf bifurcation of the feedback control system. Examples are given to demonstrate that the delayed feedback controller can reduce the density of influenced users effectively and delay the onset of Hopf bifurcation as well.
Teaching analytics: towards automatic extraction of orchestration graphs using wearable sensors

'Teaching analytics' is the application of learning analytics techniques to understand teaching and learning processes, and eventually enable supportive interventions. However, in the case of (often, half-improvised) teaching in face-to-face classrooms, such interventions would require first an understanding of what the teacher actually did, as the starting point for teacher reflection and inquiry. Currently, such teacher enactment characterization requires costly manual coding by researchers. This paper presents a case study exploring the potential of machine learning techniques to automatically extract teaching actions during classroom enactment, from five data sources collected using wearable sensors (eye-tracking, EEG, accelerometer, audio and video). Our results highlight the feasibility of this approach, with high levels of accuracy in determining the social plane of interaction (90%, κ=0.8). The reliable detection of concrete teaching activity (e.g., explanation vs. questioning) accurately still remains challenging (67%, κ=0.56), a fact that will prompt further research on multimodal features and models for teaching activity extraction, as well as the collection of a larger multimodal dataset to improve the accuracy and generalizability of these methods.
A Dynamically Reconfigurable Platform for Fixed-Point FIR Filters

Many DSP, image and video processing applications use Finite Impulse Response (FIR) filters as basic computing blocks. Our paper introduces an efficient dynamically reconfigurable FIR system that can adapt the number of filter coefficients, and their values, in real time. Here, dynamic reconfiguration is used to switch between different, pre-computed, fixed-point realizations of different digital filters. Our platform relies on the use of Distributed Arithmetic blocks, mapped to the specific LUTs of the underlying FPGA. Dynamic reconfiguration of the coefficients is limited to changing a small number of relevant LUT contents, while leaving the rest of the architecture intact. We investigate the dynamic system throughput as a function of the dynamic reconfiguration rate.