Miracle-dz/UniFAR-FTUs huggingface dataset:
Life History and the Transitions to Eusociality in the Hymenoptera

Although indirect selection through relatives (kin selection) can explain the evolution of effectively sterile offspring that act as helpers at the nest (eusociality) in the ants, bees, and stinging wasps (aculeate Hymenoptera), the genetic, ecological, and life history conditions that favor transitions to eusociality are poorly understood. In this study, ancestral state reconstruction on recently published phylogenies was used to identify the independent transitions to eusociality in each of the taxonomic families that exhibit eusociality. Semisociality, in which a single nest co-foundress monopolizes reproduction, often precedes eusociality outside the vespid wasps. Such a route to eusociality, which is consistent with groups consisting of a mother and her daughters (subsocial) at some stage and ancestral monogamy, is favored by the haplodiploid genetic sex determination of the Hymenoptera (diploid females and haploid males) and thus may explain why eusociality is common in the Hymenoptera. Ancestral states were also reconstructed for life history characters that have been implicated in the origins of eusociality. A loss of larval diapause during unfavorable seasons or conditions precedes, or coincides with, all but one transition to eusociality. This pattern is confirmed using phylogenetic tests of associations between state transition rates for sweat bees and apid bees. A loss of larval diapause may simply reflect the subsocial route to eusociality since subsociality is defined as females interacting with their adult daughters. A loss of larval diapause and a gain of subsociality may be associated with an extended breeding season that permits the production of at least two broods, which is necessary for helpers to evolve. Adult diapause may also lower the selective barrier to a first-brood daughter becoming a helper. Obligate eusociality meets the definition of a major evolutionary transition, and such transitions have occurred five times in the Hymenoptera.
EEG-Microstates Reflect Auditory Distraction After Attentive Audiovisual Perception Recruitment of Cognitive Control Networks

Processing of sensory information is embedded into ongoing neural processes which contribute to brain states. Electroencephalographic microstates are semi-stable short-lived power distributions which have been associated with subsystem activity such as auditory, visual and attention networks. Here we explore changes in electrical brain states in response to an audiovisual perception and memorization task under conditions of auditory distraction. We discovered changes in brain microstates reflecting a weakening of states representing activity of the auditory system and strengthening of salience networks, supporting the idea that salience networks are active after audiovisual encoding and during memorization to protect memories and concentrate on upcoming behavioural response.
Effect of Intensity on Changes in Cardiac Autonomic Control of Heart Rate and Arterial Stiffness After Equated Continuous Running Training Programs

Background: It is well known that exercise training has positive effects on both cardiac autonomic function and arterial stiffness (AS). However, it is not clear that which exercise training variables, intensity or volume, or both, play a crucial role in this regard. This study investigates the chronic effects of high-volume moderate-intensity training (HVMIT) and low-volume high-intensity training (LVHIT) on heart rate variability (HRV) and AS in sedentary adult men. Materials and Methods: Notably, 45 males (age: 42 ± 5.7 years) were randomly assigned to a control (n = 15), HVMIT (n = 15), or LVHIT (n = 15). The HVMIT group ran three times per week on a treadmill at 50–60% of VO2max for 45–60 min, while the LVHIT trained at 70–85% of VO2max for 25–40 min. Both training protocols were equated by caloric expenditure. HRV, pulse wave velocity (PWV), hemodynamic variables, and body composition were measured before and after 12 weeks. Results: Both protocols (i.e., HVMIT and LVHIT) significantly increased the SD of normal sinus beat intervals (SDNN) and high-frequency (HF) bands (p < 0.05) after 12 weeks. Whereas the low-frequency (LF)-HF ratio decreased significantly in both training protocols (p < 0.05); however, these changes were significantly greater in the LVHIT protocol (p < 0.05). Furthermore, the root mean square of successive RR interval differences (RMSSD) significantly increased only in the LVHIT (p < 0.05). Moreover, a significant decrease in LF and PWV was only observed following the LVHIT protocol (p < 0.05). Some measures of HRV and PWV were significantly correlated (r = 0.275–0.559; p < 0.05). Conclusion: These results show that the LVHIT protocol was more efficient for improving HRV variables and PWV than the HVMIT protocol after 12 weeks of continuous running training. Interestingly, changes in some HRV parameters were related to changes in PWV. Further studies should elaborate on the link between central and peripheral cardiovascular adaptations after continuous and intermittent training regimens differing in intensity.
Hepatic Macrophage as a Key Player in Fatty Liver Disease

Fatty liver disease, characterized by excessive inflammation and lipid deposition, is becoming one of the most prevalent liver metabolic diseases worldwide owing to the increasing global incidence of obesity. However, the underlying mechanisms of fatty liver disease are poorly understood. Accumulating evidence suggests that hepatic macrophages, specifically Kupffer cells (KCs), act as key players in the progression of fatty liver disease. Thus, it is essential to examine the current evidence of the roles of hepatic macrophages (both KCs and monocyte-derived macrophages). In this review, we primarily address the heterogeneities and multiple patterns of hepatic macrophages participating in the pathogenesis of fatty liver disease, including Toll-like receptors (TLRs), NLRP3 inflammasome, lipotoxicity, glucotoxicity, metabolic reprogramming, interaction with surrounding cells in the liver, and iron poisoning. A better understanding of the diverse roles of hepatic macrophages in the development of fatty liver disease may provide a more specific and promising macrophage-targeting therapeutic strategy for inflammatory liver diseases.
A Review of Explicit and Implicit Assumptions When Providing Personalized Feedback Based on Self-Report EMA Data

Ecological Momentary Assessment (EMA) in which participants report on their moment-to-moment experiences in their natural environment, is a hot topic. An emerging field in clinical psychology based on either EMA, or what we term Ecological Retrospective Assessment (ERA) as it requires retrospectivity, is the field of personalized feedback. In this field, EMA/ERA-data-driven summaries are presented to participants with the goal of promoting their insight in their experiences. Underlying this procedure are some fundamental assumptions about (i) the relation between true moment-to-moment experiences and retrospective evaluations of those experiences, (ii) the translation of these experiences and evaluations to different types of data, (iii) the comparison of these different types of data, and (iv) the impact of a summary of moment-to-moment experiences on retrospective evaluations of those experiences. We argue that these assumptions deserve further exploration, in order to create a strong evidence-based foundation for the personalized feedback procedure.
Association of the Serum Levels of the Nucleocapsid Antigen of SARS-CoV-2 With the Diagnosis, Disease Severity, and Antibody Titers in Patients With COVID-19: A Retrospective Cross-Sectional Study

Background: Several types of laboratory tests for COVID-19 have been established to date; however, the clinical significance of the serum SARS-CoV-2 nucleocapsid (N) antigen levels remains to be fully elucidated. In the present study, we attempted to elucidate the usefulness and clinical significance of the serum N antigen levels. Methods: We measured the serum N antigen levels in 391 serum samples collected from symptomatic patients with a confirmed diagnosis of COVID-19 and 96 serum samples collected from patients with non-COVID-19, using a fully automated chemiluminescence immunoassay analyzer. Results: Receiver operating characteristic analysis identified the optimal cutoff value of the serum N antigen level (cutoff index, based on Youden’s index) as 0.255, which yielded a sensitivity and specificity for the diagnosis of COVID-19 of 91.0 and 81.3%, respectively. The serum N antigen levels were significantly higher in the patient groups with moderate and severe COVID-19 than with mild disease. Moreover, a significant negative correlation was observed between the serum N antigen levels and the SARS-CoV-2 IgG antibody titers, especially in patients with severe COVID-19. Conclusion: Serum N antigen testing might be useful both for the diagnosis of COVID-19 and for obtaining a better understanding of the clinical features of the disease.
Potential Association Between the Low-Energy Plasma Structure and the Patchy Pulsating Aurora

While the pulsating auroral phenomena have been recognized and studied for decades, our understating of their generation mechanisms remains incomplete to date. In one main class of pulsating auroras which is termed “patchy pulsating auroras” (PPA), the auroral patches are found to basically maintain their shape and size over many pulsation cycles. Also, PPAs are repeatedly found to essentially co-move with the ExB convection drift. The above properties led many researchers to hypothesize that PPA might connect to a structure of enhanced cold plasma in the magnetosphere. In this study, we review the existing evidence, and provide new perspective and support, of the low-energy plasma structure potentially associated with PPA. Based on observations from both the magnetosphere and the topside ionosphere, we suggest that ionospheric auroral outflows might constitute one possible source mechanism of the flux tubes with enhanced low-energy plasma that connect to the PPA. We also review the existing theories of pulsating auroras, with particular focus on the role of low-energy plasma in these theories. To date, none of the existing theories are complete and mature enough to offer a quantitatively satisfactory explanation of pulsating auroras. At last, we suggest a few future research directions to advance our understanding of pulsating auroras: a) more accurate measurements of the cold plasma density, b) more developed theories of the underlying mechanisms of ELF/VLF wave modulation, and c) auxiliary processes in the topside ionosphere or near-Earth region accompanying pulsating auroras.
Transistor sine-wave LC oscillators. Some general considerations and new developments

The paper begins by showing that various well-known simple oscillator circuits, usually analysed separately, are essentially equivalent to one another if certain reasonable assumptions are made, and appreciation of this fact simplifies the design problem. A discussion follows concerning class-C oscillators and the difficulty of combining high efficiency with a satisfactory degree of independence of transistor parameters. The problem of avoiding squegging is also considered. A simple push-pull high-efficiency oscillator is then described, in which substantially constant current flows in each transistor for the whole of its 180° conduction angle. This oscillator is believed to possess a unique combination of desirable features. Another unusual high-efficiency oscillator is then presented, which is more elaborate than the previous one but which has advantages in certain respects. The paper ends with a description of an oscillator based on the `long-tailed-pair? circuit. The oscillator is exceptionally easy to design and make, and is suitable for applications where high efficiency is not important. It can supply either a sine wave or a square wave, or both.
Modelling Particulate Matter Using Multivariate and Multistep Recurrent Neural Networks

Air quality is a major problem in the world, having severe health implications. Long-term exposure to poor air quality causes pulmonary and cardiovascular diseases. Several studies have also found that deteriorating air quality also causes substantial economic losses. Thus, techniques that can forecast air quality with higher accuracy may help reduce health and economic consequences. Prior research has utilized state-of-the-art artificial neural network and recurrent neural network models for forecasting air quality. However, a comprehensive investigation of different architectures of recurrent neural network, especially LSTMs and ensemble techniques, has been less explored. Also, there have been less explorations of long-term air quality forecasts via these methods exists. This research proposes the development and calibration of recurrent neural network models and their ensemble, which can forecast air quality in terms of PM2.5 concentration 6 hours ahead in time. For forecasting air quality, a vanilla-LSTM, a stack-LSTM, a bidirectional-LSTM, a CNN-LSTM, and an ensemble of individual LSTM models were trained on the UCI Machine Learning Beijing dataset. Data were split into two parts, where 80% of data were used for training the models, while the remaining 20% were used for validating the models. For comparative analysis, four regression losses were calculated, namely root mean squared error, mean absolute percentage error, mean absolute error and Pearson’s correlation coefficient. Results revealed that among all models, the ensemble model performed the best in predicting the PM2.5 concentrations. Furthermore, the ensemble model outperformed other models reported in literature by a long margin. Among the individual models, the bidirectional-LSTM performed the best. We highlight the implications of this research on long-term forecasting of air quality via recurrent and ensemble techniques.
Persuasive Apps for Sustainable Waste Management: A Comparative Systematic Evaluation of Behavior Change Strategies and State-of-the-Art

With the proliferation of ubiquitous computing and mobile technologies, mobile apps are tailored to support users to perform target behaviors in various domains, including a sustainable future. This article provides a systematic evaluation of mobile apps for sustainable waste management to deconstruct and compare the persuasive strategies employed and their implementations. Specifically, it targeted apps that support various sustainable waste management activities such as personal tracking, recycling, conference management, data collection, food waste management, do-it-yourself (DIY) projects, games, etc. The authors who are persuasive technology researchers retrieved a total of 244 apps from App Store and Google Play, out of which 148 apps were evaluated. Two researchers independently analyzed and coded the apps and a third researcher was involved to resolve any disagreement. They coded the apps based on the persuasive strategies of the persuasive system design framework. Overall, the findings uncover that out of the 148 sustainable waste management apps evaluated, primary task support was the most employed category by 89% (n = 131) apps, followed by system credibility support implemented by 76% (n = 112) apps. The dialogue support was implemented by 71% (n = 105) apps and social support was the least utilized strategy by 34% (n = 51) apps. Specifically, Reduction (n = 97), personalization (n = 90), real-world feel (n = 83), surface credibility (n = 83), reminder (n = 73), and self-monitoring (n = 50) were the most commonly employed persuasive strategies. The findings established that there is a significant association between the number of persuasive strategies employed and the apps’ effectiveness as indicated by user ratings of the apps. How the apps are implemented differs depending on the kind of sustainable waste management activities it was developed for. Based on the findings, this paper offers design implications for personalizing sustainable waste management apps to improve their persuasiveness and effectiveness.
Oral Microbiota Is Associated With Immune Recovery in Human Immunodeficiency Virus-Infected Individuals

The role of the oral microbiota in HIV-infected individuals deserves attention as either HIV infection or antiretroviral therapy (ART) may have effect on the diversity and the composition of the oral microbiome. However, few studies have addressed the oral microbiota and its interplay with different immune responses to ART in HIV-infected individuals. Salivary microbiota and immune activation were studied in 30 HIV-infected immunological responders (IR) and 34 immunological non-responders (INR) (≥500 and < 200 CD4 + T-cell counts/μl after 2 years of HIV-1 viral suppression, respectively) with no comorbidities. Metagenome sequencing revealed that the IR and the INR group presented similar salivary bacterial richness and diversity. The INR group presented a significantly higher abundance of genus Selenomonas_4, while the IR group manifested higher abundances of Candidatus_Saccharimonas and norank_p_Saccharimonas. Candidatus_Saccharimonas and norank_p_Saccharimonas were positively correlated with the current CD4 + T-cells. Candidatus_Saccharimonas was positively correlated with the markers of adaptive immunity CD4 + CD57 + T-cells, while negative correlation was found between norank _p_Saccharimonas and the CD8 + CD38 + T-cells as well as the CD4/CD8 + HLADR + CD38 + T-cells. The conclusions are that the overall salivary microbiota structure was similar in the immunological responders and immunological non-responders, while there were some taxonomic differences in the salivary bacterial composition. Selenomona_4, Candidatus_Saccharimonas, and norank _p_Saccharimonas might act as important factors of the immune recovery in the immunodeficiency patients, and Candidatus_Saccharimonas could be considered in the future as screening biomarkers for the immune responses in the HIV-infected individuals.
The RyR2-R2474S Mutation Sensitizes Cardiomyocytes and Hearts to Catecholaminergic Stress-Induced Oxidation of the Mitochondrial Glutathione Pool

Missense mutations in the cardiac ryanodine receptor type 2 (RyR2) characteristically cause catecholaminergic arrhythmias. Reminiscent of the phenotype in patients, RyR2-R2474S knockin mice develop exercise-induced ventricular tachyarrhythmias. In cardiomyocytes, increased mitochondrial matrix Ca2+ uptake was recently linked to non-linearly enhanced ATP synthesis with important implications for cardiac redox metabolism. We hypothesize that catecholaminergic stimulation and contractile activity amplify mitochondrial oxidation pathologically in RyR2-R2474S cardiomyocytes. To investigate this question, we generated double transgenic RyR2-R2474S mice expressing a mitochondria-restricted fluorescent biosensor to monitor the glutathione redox potential (EGSH). Electrical field pacing-evoked RyR2-WT and RyR2-R2474S cardiomyocyte contractions resulted in a small but significant baseline EGSH increase. Importantly, β-adrenergic stimulation resulted in excessive EGSH oxidization of the mitochondrial matrix in RyR2-R2474S cardiomyocytes compared to baseline and RyR2-WT control. Physiologically β-adrenergic stimulation significantly increased mitochondrial EGSH further in intact beating RyR2-R2474S but not in RyR2-WT control Langendorff perfused hearts. Finally, this catecholaminergic EGSH increase was significantly attenuated following treatment with the RyR2 channel blocker dantrolene. Together, catecholaminergic stimulation and increased diastolic Ca2+ leak induce a strong, but dantrolene-inhibited mitochondrial EGSH oxidization in RyR2-R2474S cardiomyocytes.
Interaction Effects of Nitrogen Rates and Forms Combined With and Without Zinc Supply on Plant Growth and Nutrient Uptake in Maize Seedlings

Previous studies have shown that zinc (Zn) accumulation in shoot and grain increased as applied nitrogen (N) rate increased only when Zn supply was not limiting, suggesting a synergistic effect of N on plant Zn accumulation. However, little information is available about the effects of different mineral N sources combined with the presence or absence of Zn on the growth of both shoot and root and nutrient uptake. Maize plants were grown under sand-cultured conditions at three N forms as follows: NO3– nutrition alone, mixture of NO3–/NH4+ with molar ratio of 1:1 (recorded as mixed-N), and NH4+ nutrition alone including zero N supply as the control. These treatments were applied together without or with Zn supply. Results showed that N forms, Zn supply, and their interactions exerted a significant effect on the growth of maize seedlings. Under Zn-sufficient conditions, the dry weight (DW) of shoot, root, and whole plant tended to increase in the order of NH4+ < NO3– < mixed-N nutrition. Compared with NH4+ nutrition alone, mixed-N supply resulted in a 27.4 and 28.1% increase in leaf photosynthetic rate and stomatal conductance, which further resulted in 35.7 and 33.5% of increase in shoot carbon (C) accumulation and shoot DW, respectively. Furthermore, mixed-N supply resulted in a 19.7% of higher shoot C/N ratio vs. NH4+ nutrition alone, which means a higher shoot biomass accumulation, because of a significant positive correlation between shoot C/N ratio and shoot DW (R2 = 0.682***). Additionally, mixed-N supply promoted the greatest root DW, total root length, and total root surface area and synchronously improved the root absorption capacity of N, iron, copper, manganese, magnesium, and calcium. However, the above nutrient uptake and the growth of maize seedlings supplied with NH4+ were superior to either NO3– or mixed-N nutrition under Zn-deficient conditions. These results suggested that combined applications of mixed-N nutrition and Zn fertilizer can maximize plant growth. This information may be useful for enabling integrated N management of Zn-deficient and Zn-sufficient soils and increasing plant and grain production in the future.
The Future of Positive Psychology and Disability

For much of the history of the application of psychology to disability, the research and clinical focus of the field was deficits-oriented: documenting what people with disability could not do, proposing theories of why they could not do these things, creating measures to assess this incapacity and incompetence, and building interventions and treatments predicated on disease and pathology. It has been only in the last few decades that conceptualizations of disability allowed for consideration of strengths and positive attributes along with the presence of disability and only in the past two decades that a positive psychology of disability has emerged. This article will briefly summarize the factors that led to the emergence of a focus on the positive psychology of disability and a strength-based approach in the field, examine the state of knowledge and practice as it pertains to the positive psychology of disability, and will examine challenges that serve as barriers to progress in this area and opportunities for advancement. Among these is examining how “optimal human functioning” can be understood in ways that includes, and not excludes, people with disability. The importance of shifting the disability research and practice focus to emphasize flourishing, well-being, and self-determination of and for people with disability will be discussed, as well as the necessity for the field of positive psychology to more aggressively reach out to include people with disability among those populations whom the field values and includes.