Miracle-dz/UniFAR-FTUs huggingface dataset:
Significance of Bitter Leaf (Vernonia Amagdalina) In Tropical Diseases and Beyond: A Review

Vernonia amygdalina Delile (VA), family Asteraceae or Compositae is plants that is consumed locally as food and serve important ethnomedicinal uses. It grows throughout tropical Africa to a height of about 1 – 5 metres and it is indigenous to many West African Countries. Many parts of the plants are useful, they are used locally for the treatment of fever, Stomach disorder, jaundice, worm infestation, constipation, malaria, hiccups, kidney problems, amoebic dysentery, schistosomiasis, cough, wounds, diabetes, laxative, veneral diseases and other bacterial and protozoal infection. This review examines, discusses and summarizes the current evidence of ethnomedicinal uses, phytochemistry and biological activities as well as toxicity of this species with a view to identifying its therapeutic relations and possible contradictions, inconsistencies and gaps that may have arisen in the research literature. This review is based on literature study on journals and books of scientific origin from library, both manual and electronic sources such as PubMed, Science Direct, Elsevier, ACS, google Scholar etc using various combinations of search words. V. amagdalina is a tropical plant with a lot of interesting biological and medicinal uses. The plants are relatively not toxic, safe for consumption and possess a great potential as pharmaceutical leads for the treatment of diseases and beyond. This review will stimulate further research in the pharmacology and phytochemistry of V. amagdalina.
Identification of crystallin modifications in the human lens cortex and nucleus using laser capture microdissection and CyDye labeling

Purpose With aging, lens crystallins undergo post-translational modifications (PTMs) and these modifications are believed to play a major role in age-related cataract development. The purpose of the present study was to determine the protein profiles of crystallins and their PTMs in the cortical and nuclear regions within an aging human lens to gain a better understanding about changes in crystallins as fiber cells migrate from cortical to nuclear region. Methods Laser capture microdissection (LCM) was used to select and capture cells from cortical and nuclear regions of 12 μm, optimum cutting temperature (OCT) compound-embedded frozen lens sections from a 69-year-old human lens. Proteins were extracted and then analyzed by 2-D difference gel electrophoresis (2-D DIGE) with sulfonated indocyanine dye (CyDye) labeling. Crystallin identities and their PTMs were then determined by Matrix-Assisted Laser Desorption/Ionization Time-of-Flight (MALDI-TOF) and Electrospray Ionization Quadripole Linear Ion-Trap Liquid Chromatography (ESI-QTRAP LC-MS/MS) mass spectrometry. Results Crystallin fragments (Mr <20 kDa) were present in both cortical and nuclear regions, while high molecular weight (HMW) aggregates (Mr > 35 kDa) were mostly localized in the nuclear region. HMW complexes contained a relatively large number of truncated and modified β-crystallins, compared to α- and γ-crystallins, and two lens-specific intermediate filaments, CP49 (phakinin) and filensin. Modified α-crystallins were in low abundance in the nuclear region compared to the cortical region. Several PTMs, including deamidation, oxidation, phosphorylation, ethylation, methylation, acetylation, and carbamylation, were identified in virtually all crystallins and CP49. The data provide the first report of human lens crystallin profiling by a combination of LCM, 2D-DIGE, and mass spectrometric analysis. Conclusions The results suggested that as the fiber cells migrate from cortical region to the nuclear region, the crystallin degradation begins in the cortical region and continues in the nuclear region. However, a greater number of the HMW complexes exist mainly in the nuclear region.
Characterization of complex networks: A survey of measurements

Each complex network (or class of networks) presents specific topological features which characterize its connectivity and highly influence the dynamics of processes executed on the network. The analysis, discrimination, and synthesis of complex networks therefore rely on the use of measurements capable of expressing the most relevant topological features. This article presents a survey of such measurements. It includes general considerations about complex network characterization, a brief review of the principal models, and the presentation of the main existing measurements. Important related issues covered in this work comprise the representation of the evolution of complex networks in terms of trajectories in several measurement spaces, the analysis of the correlations between some of the most traditional measurements, perturbation analysis, as well as the use of multivariate statistics for feature selection and network classification. Depending on the network and the analysis task one has in mind, a specific set of features may be chosen. It is hoped that the present survey will help the proper application and interpretation of measurements.
ASSISTing CS1 students to learn: learning approaches and object-oriented programming

Identifying and managing students who experience difficulty with learning to program is a challenge for CS educators. In an attempt to answer the familiar question "What makes for success in CS1? " we have investigated student approaches to learning using the ASSIST measure of learning approach. This measure considers three dimensions related to studying - deep (related to meaning), surface (reproducing) and strategic (achieving). Two cohorts of CS1 students completed an online ASSIST questionnaire midway through their first semester. Their three ASSIST scores were analysed together with their CS1 performance. The strongest relationships were a significant, negative correlation between a surface approach to learning and CS1 performance and a significant positive correlation between a strategic approach to learning and CS1 performance. Participants were classified via a cluster analysis according to the extent to which they showed deep, strategic, and surface learning profiles. Members of the cluster favouring a surface approach had the poorest performances, whereas members of the cluster favouring strategic or deep approaches rather than a surface approach had the best performances.
Type 1 diabetes mellitus (t1dm): induced by environmental, genetic and immunity factors

T1DM is progressively common among children and youths. The combination of environmental factors and immunological disturbances form a sensitivity risk factor that induces T1DM, especially in the presence of genetic factors. The current study focuses on the role of relationship between immune system, viruses and genetic factors with T1DM occurrence. 230 T1DM patients were sampled, based on absolute dependence on insulin with another 130 healthy individuals as control group. Indirect Enzyme-Linked Immuno Sorbent Assay (ELISA), Immuno fluorescent and Polymerase Chain Reaction (PCR) - SSP technique were used for detection of HLA-DR3 and DR4. Significant differences in mean values was observed between the T1DM patients and control group in the quantitative measurement of anti-Cytomegalovirus (CMV) antibody (Ab), rubella, CSV-B, Glutamic Acid Decarboxylase (GAD), insulin receptor (IR) Ab, IL-4, IL-10, CD4, CD8, and the ratio of CD4:CD8 (P-value < 0.05). The results of this study indicate that there are overload of immune responses (cellular &molecular-genetic) among T1DM patients. The presence of human leukocyte antigen (HLA) genes showed significant relationship to viruses that induce T1DM. It also showed an existing link between T1DM occurrence, HLA genes and environmental factors (viruses and consumption cow milk during infancy).
Coevolving Memetic Algorithms: A Review and Progress Report

Coevolving memetic algorithms are a family of metaheuristic search algorithms in which a rule-based representation of local search (LS) is coadapted alongside candidate solutions within a hybrid evolutionary system. Simple versions of these systems have been shown to outperform other nonadaptive memetic and evolutionary algorithms on a range of problems. This paper presents a rationale for such systems and places them in the context of other recent work on adaptive memetic algorithms. It then proposes a general structure within which a population of LS algorithms can be evolved in tandem with the solutions to which they are applied. Previous research started with a simple self-adaptive system before moving on to more complex models. Results showed that the algorithm was able to discover and exploit certain forms of structure and regularities within the problems. This "metalearning" of problem features provided a means of creating highly scalable algorithms. This work is briefly reviewed to highlight some of the important findings and behaviors exhibited. Based on this analysis, new results are then presented from systems with more flexible representations, which, again, show significant improvements. Finally, the current state of, and future directions for, research in this area is discussed
Social norms and cognitive performance

Vigilance, or the ability to sustain attention over prolonged periods of time, is an important component of tasks in a wide variety of settings. A large body of research has demonstrated that performance on these tasks declines with time on watch, a pattern referred to as the vigilance decrement. One factor that has been mostly neglected in prior research is the effect of the presence of a supervisory person during a vigilance task. The purpose of the present investigation was to determine the effect of the presence of a supervisory figure on the performance, perceived workload, and stress associated with vigilance. It was hypothesized that the presence of a supervisory figure would increase overall performance and also attenuate the vigilance decrement. However, it was also expected to increase the perceived workload and stress associated with the task.
Coupled Bulk-Surface Free Boundary Problems Arising from a Mathematical Model of Receptor-Ligand Dynamics

We consider a coupled bulk-surface system of partial differential equations with nonlinear coupling modelling receptor-ligand dynamics. The model arises as a simplification of a mathematical model for the reaction between cell surface resident receptors and ligands present in the extra-cellular medium. We prove the existence and uniqueness of solutions. We also consider a number of biologically relevant asymptotic limits of the model. We prove convergence to limiting problems which take the form of free boundary problems posed on the cell surface. We also report on numerical simulations illustrating convergence to one of the limiting problems as well as the spatio-temporal distributions of the receptors and ligands in a realistic geometry.
Formation of Cortical Fields on a Reduced Cortical Sheet

Theories of both cortical field development and cortical evolution propose that thalamocortical projections play a critical role in the differentiation of cortical fields (O'Leary, 1989; Krubitzer, 1995). In the present study, we examined how changing the size of the immature neocortex before the establishment of thalamocortical connections affects the subsequent development and organization of the adult neocortex. This alteration in cortex is consistent with one of the most profound changes made to the mammalian neocortex throughout evolution: cortical size. Removing the caudal one-third to three-fourths of the cortical neuroepithelial sheet unilaterally at an early stage of development in marsupials resulted in normal spatial relationships between visual, somatosensory, and auditory cortical fields on the remaining cortical sheet. Injections of neuroanatomical tracers into the reduced cortex revealed in an altered distribution of thalamocortical axons; this alteration allowed the maintenance of their original anteroposterior distribution. These results demonstrate the capacity of the cortical neuroepithelium to accommodate different cortical fields at early stages of development, although the anteroposterior and mediolateral relationships between cortical fields appear to be invariant. The shifting of afferents and efferents with cortical reduction or expansion at very early stages of development may have occurred naturally in different lineages over time and may be sufficient to explain much of the phenotypic variation in cortical field number and organization in different mammals.
Why don't adolescent gamblers seek treatment?

Surveys have consistently shown that the prevalence rates for problematic gambling are higher in adolescents than for adults. Given this finding, why is it that so few adolescents, compared to adults, enrol in treatment programs? This paper outlines ten speculative reasons why this situation exists. The possible reasons why adolescent problem gamblers don't seek treatment include the following:
Ser727‐dependent recruitment of MCM5 by Stat1α in IFN‐γ‐induced transcriptional activation

Stat1α is a latent cytoplasmic transcription factor activated in response to interferon‐γ (IFN‐γ). The C‐terminal 38 amino acids of Stat1α are required to trigger transcription and therefore may possibly serve as a transcription activation domain (TAD). Here we show that the C‐terminus of Stat1α is an independent TAD which can interact with a specific group of nuclear proteins. Mutation of the Stat1 Ser727 and Leu724 decreases its transcriptional activity and affinity for the nuclear proteins. One of the interacting proteins was identified as MCM5, a member of the mini‐chromosome maintenance (MCM) family involved in DNA replication. Both in vitro and in vivo interaction of Stat1α and MCM5 were demonstrated. Furthermore, the in vitro interaction required Ser727 and was enhanced by its phosphorylation. Transient over‐expression of MCM5 enhanced transcriptional activation by Stat1α in a Ser727‐dependent manner. Finally, changes in the level of nuclear localized MCM5 during the cell cycle correlated with the changes in transcriptional response to IFN‐γ acting through Stat1α. These results strongly suggest that MCM5 is recruited through interaction with Stat1α in a Ser727‐ and Leu724‐dependent manner to play a role in optimal transcriptional activation.
The Influence of Training and Development on Emotional Intelligence

Successful leadership is about personal characteristics and human qualities that include empathy, compassion, flexibility, and influence. Today’s leaders must have the ability to adapt to an ever-changing diverse workforce, and it’s these human abilities that set apart successful leaders. The information that emotional intelligence functions on is considered emotional knowledge, which can be taught and developed thereby improving emotional intelligence (Mayer et al., 2004). A manager’s awareness and understanding of one’s own emotions and ability to effectively handle others’ emotions may influence the overall success of that individual within the organization (Alston, 2009; Rozell et al., 2001). By measuring emotional intelligence skills, organizations should be able to identify appropriate candidates to train and develop for future leadership positions (Vrab, 2007). This paper reinforces positive results in the literature to support the importance of a manager’s level of emotional intelligence in the training and development process (Kerr et al., 2005).
Climate impact research: beyond patchwork

Abstract. Despite significant progress in climate impact research, the narratives that science can presently piece together of a 2, 3, 4, or 5 °C warmer world remain fragmentary. Here we briefly review past undertakings to characterise comprehensively and quantify climate impacts based on multi-model approaches. We then report on the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), a community-driven effort to compare impact models across sectors and scales systematically, and to quantify the uncertainties along the chain from greenhouse gas emissions and climate input data to the modelling of climate impacts themselves. We show how ISI-MIP and similar efforts can substantially advance the science relevant to impacts, adaptation and vulnerability, and we outline the steps that need to be taken in order to make the most of the available modelling tools. We discuss pertinent limitations of these methods and how they could be tackled. We argue that it is time to consolidate the current patchwork of impact knowledge through integrated cross-sectoral assessments, and that the climate impact community is now in a favourable position to do so.
Efficacy and tolerability of initiating, or switching to, infliximab biosimilar CT-P13 in inflammatory bowel disease (IBD): a large single-centre experience

Abstract Objectives: Recently, the infliximab biosimilar (CT-P13) received market authorisation for inflammatory bowel disease (IBD), allowing cost benefits when switching to CT-P13. We aim to assess the efficacy and safety of switching from originator infliximab to CT-P13 for new and existing patients. Material and methods: Treatment response, remission, primary and secondary loss of response rates, and adverse events in patients who initiated infliximab originator in the 12 months pre-switch (n = 53) were compared with the patients who initiated CT-P13 in the 12 months post-switch (n = 69). Sustained responses were compared for existing infliximab originator patients who switched to CT-P13 (n = 191) and those who continued with the originator (n = 19). Results: There was no difference in remission (58.1% vs. 47.4%, p = .37), response (12.6% vs. 10.5%, p = .80), secondary loss of response (24.6% vs. 42.1%, p = .10), or adverse events (4.7% vs. 0% p = 1.0) between those who switched to CT-P13 and those who continued infliximab originator. There was no difference in remission (42.0% vs. 26.4%, p = .074), response (21.7% vs. 22.6%, p = .91), primary non-response (5.8% vs. 15.1%, p = .09), secondary loss of response (21.7% vs. 22.6%, p = .91), or adverse events (8.7% vs. 11.3%, p = .63) in those who initiated CT-P13 compared with infliximab originator. Conclusions: There was no difference in the efficacy and safety of infliximab originator and CT-P13 during the first 12 months after switching.
Identifying the agricultural imprint on the global N2O budget using stable isotopes

Agricultural soils are the most important anthropogenic source of nitrous oxide to the atmosphere. We observed large shifts with time in the emission rate (from 170 to 16 ng N cm−2 h−1) and in δ15N of N2O emitted (from −46‰ to +5‰ relative to atmospheric N2) from a urea-fertilized and irrigated agricultural field in Mexico. We calculated overall instantaneous enrichment factors for the sampling period, which suggest that the microbial N2O production shifts from nitrification (week 1) to denitrification (week 2). Isotopic signatures of N2O emissions were not always in accord with other proxies (such as NO/N2O emission ratio or water-filled pore space) used to estimate the relative importance of nitrification and denitrification as N2O sources. These observations strongly suggest that the soil surface emissions integrate processes occurring at different depths in the soil and a decoupling of NO and N2O production in this system. Further clues as to the source of N2O come from the positional dependence of 15N in the emitted N2O, reported here for the first time in soil emissions. Enrichment at the central N position increased relative to the terminal N position by 9.3‰ during the first 4 days after irrigation, implying that nitrification preferentially enriches the central N position compared to denitrification. The overall δ15N signature we measured for N2O emitted from N-fertilized agricultural systems is more depleted than observed δ15N values for N2O emitted from more N-limited forest soils. Assuming that one half of the total agricultural N2O emissions associated with the global increase in soil nitrogen fertilizer use have an isotopic composition comparable to those of the agricultural fields reported here, we predict a decline in the isotopic signature of tropospheric N2O during this century of as much as 3‰ for 15N. Although many uncertainties remain, we suggest that measurements of δ15N-N2O in firn air will provide constraints on how the N2O budget has changed during the past century.
Buying or browsing? An exploration of shopping orientations and online purchase intention

Consumer selection of retail patronage mode has been widely researched by marketing scholars. Several researchers have segmented consumers by shopping orientation. However, few have applied such methods to the Internet shopper. Despite the widespread belief that Internet shoppers are primarily motivated by convenience, the authors show empirically that consumers' fundamental shopping orientations have no significant impact on their proclivity to purchase products online. Factors that are more likely to influence purchase intention include product type, prior purchase, and, to a lesser extent, gender.
Exploring Korean dual language immersion programs in the United States: parents’ reasons for enrolling their children

ABSTRACT This study explores parents’ reasons for enrolling their children in a Korean dual language immersion (KDLI) program. The research focuses on parents’ reasons for choosing a school and a KDLI program, respectively, to examine whether a KDLI offering significantly affects parents’ decision to enroll their children in a specific school and to investigate which factors parents tend to prioritize when selecting a KDLI program over other language immersion programs. Given the various contexts in which individual KDLI programs operate, this study also compares different parent groups characterized by Korean ethnicity and school characteristics in terms of their responses. The study surveys more than 450 parents of students enrolled in 7 elementary-level KDLI programs in southern California to determine the extent to which parents’ reasons vary across different groups and examine whether group differences exist between Korean and non-Korean parents as well as between parents whose children attend high socioeconomic and low socioeconomic status schools. The study discusses the findings by comparing the results to prior literature and identifies implications for KDLI and DLI programs in general.
Energy-efficient torque distribution for axle-individually propelled electric vehicles

We propose a novel operation strategy for electric vehicles with axle-individual electric machines to improve their energy efficiency in typical driving situations. The developed algorithm is allocating a total torque requested by a velocity controlling system or the driver to the electric machines such that the energy loss is reduced compared to an equal distribution. By taking near-future forecasts into account, the predictive nature of the algorithm leads to a minimized number of clutching processes compared to previous work and thereby contributes to increased comfort and minimized component wear. Overall, an average reduction of up to 25% in the electric machine losses can be achieved for the ARTEMIS driving cycles. At the same time, a reduction of the clutching operations by 70% is possible due to the forecast, compared to algorithms only considering the momentary state.