Miracle-dz/UniFAR-FTUs huggingface dataset:
Nitric Oxide Resistance in Leishmania (Viannia) braziliensis Involves Regulation of Glucose Consumption, Glutathione Metabolism and Abundance of Pentose Phosphate Pathway Enzymes

In American Tegumentary Leishmaniasis production of cytokines, reactive oxygen species and nitric oxide (NO) by host macrophages normally lead to parasite death. However, some Leishmania braziliensis strains exhibit natural NO resistance. NO-resistant strains cause more lesions and are frequently more resistant to antimonial treatment than NO-susceptible ones, suggesting that NO-resistant parasites are endowed with specific mechanisms of survival and persistence. To tests this, we analyzed the effect of pro- and antioxidant molecules on the infectivity in vitro of L. braziliensis strains exhibiting polar phenotypes of resistance or susceptibility to NO. In addition, we conducted a comprehensive quantitative mass spectrometry-based proteomics analysis of those parasites. NO-resistant parasites were more infective to peritoneal macrophages, even in the presence of high levels of reactive species. Principal component analysis of protein concentration values clearly differentiated NO-resistant from NO-susceptible parasites, suggesting that there are natural intrinsic differences at molecular level among those strains. Upon NO exposure, NO-resistant parasites rapidly modulated their proteome, increasing their total protein content and glutathione (GSH) metabolism. Furthermore, NO-resistant parasites showed increased glucose analogue uptake, and increased abundance of phosphotransferase and G6PDH after nitrosative challenge, which can contribute to NADPH pool maintenance and fuel the reducing conditions for the recovery of GSH upon NO exposure. Thus, increased glucose consumption and GSH-mediated redox capability may explain the natural resistance of L. braziliensis against NO.
Utilizing Structural Network Positions to Diversify People Recommendations on Twitter

Social recommender systems, such as “Who to follow” on Twitter, utilize approaches that recommend friends of a friend or interest-wise similar people. Such algorithmic approaches have been criticized for resulting in filter bubbles and echo chambers, calling for diversity-enhancing recommendation strategies. Consequently, this article proposes a social diversification strategy for recommending potentially relevant people based on three structural positions in egocentric networks: dormant ties, mentions of mentions, and community membership. In addition to describing our analytical approach, we report an experiment with 39 Twitter users who evaluated 72 recommendations from each proposed network structural position altogether. The users were able to identify relevant connections from all recommendation groups. Yet, perceived familiarity had a strong effect on perceptions of relevance and willingness to follow-up on the recommendations. The proposed strategy contributes to the design of a people recommender system, which exposes users to diverse recommendations and facilitates new social ties in online social networks. In addition, we advance user-centered evaluation methods by proposing measures for subjective perceptions of people recommendations.
Knowledge transfer between communities, practitioners, and researchers: A case study for community resilience in Wellington, New Zealand

In 2014 the Integrated Research for Disaster Risk programme endorsed the establishment of the International Centre of Excellence in Community Resilience, Wellington, NZ. This Centre of Excellence is co-hosted by the Joint Centre for Disaster Research (Massey University/GNS Science) and the Wellington Region Emergency Management Office, with the objective of enhancing collaboration between researchers and individuals, organisations, and communities in the Wellington Region. Through a range of activities the International Centre of Excellence in Community Resilience aims to provide an evidence base for the Wellington Region Emergency Management Office’s Community Resilience Strategy, act as a vehicle to share good practice in Community Resilience, and promote the Wellington Region as a living laboratory for research and learning. The current article reports on the recent International Centre of Excellence in Community Resilience transdisciplinary workshop on knowledge sharing which aimed to investigate challenges to, and solutions for, enhanced collaboration. Over 50 participants attended this workshop, including practitioners, researchers, community leaders, and business representatives. Participants identified a number of key issues that create challenges to collaborative knowledge sharing, ranging from adequate communication and resources through to political influence and partner equity. Solutions ranged from creative resourcing to personalisation of issues. Facilitation and the question of who should be the appropriate facilitator (internal or external) was identified as vital for knowledge transfer and community resilience building.
Identifying Cardiovascular Risk Profiles Clusters among Mediterranean Adolescents across Seven Countries

Cardiovascular diseases (CVDs) are the number one cause of death globally and are partially due to the inability to control modifiable lifestyle risk factors. The aim of this study was to analyze the profiles of adolescents from seven Mediterranean countries (Greece, Israel, Italy, Macedonia, Malta, Portugal, Spain) according to their modifiable lifestyle risk factors for CVD (overweight/obesity, physical activity, smoking, alcohol consumption). The sample consisted of 26,110 adolescents (52.3% girls) aged 11, 13, and 15 years who participated in the Health Behavior in School-aged Children (HBSC) survey in 2018 across the seven countries. Sociodemographic characteristics (sex, age, country of residence, socioeconomic status) and CVD modifiable lifestyle risk factors (overweight/obesity, physical activity, smoking, alcohol consumption) were recorded. A two-step cluster analysis, one-way analysis of variance, and chi-square test were performed. Four different cluster groups were identified: two low-risk groups (64.46%), with risk among those with low physical activity levels; moderate-risk group (14.83%), with two risk factors (unhealthy weight and low physical activity level); and a high-risk group (20.7%), which presented risk in all modifiable lifestyle risk factors. Older adolescents reported a higher likelihood of being in the high-risk group. Given that the adolescence period constitutes an important time for interventions aimed at CVD prevention, identifying profiles of moderate- and high-risk adolescents is crucial.
Energy Modeling of a Lead-Acid Battery within Hybrid Wind/Photovoltaic Systems

Within the scope of full-scale energy modeling of a hybrid wind / photovoltaic system coupled to the network, our focus herein lies in a battery set-up that makes use of the CIEMAT model. The implementation and energy-based analysis of this model are conducted with emphasis on the continuous estimation of battery capacity. A measurement vs. model results comparison is then performed under actual operating conditions.
Performance of a Double Uniform Circular Array in a Three-Dimensional Environment

ABSTRACT In this paper, an array configuration with double uniform circular arrays (DUCAs) is provided in a three-dimensional environment with the goal of optimizing compact multiantenna user terminals. The DUCA extends the general two-dimensional multiantenna model to three-dimensional space. To accurately consider the spatial fading correlation (SFC) between antennas and the capacity of multiple input multiple output (MIMO) multipath channels, this paper uses the equivalent network model under mutual coupling (MC). Furthermore, the methods for calculating SFC with and without MC and capacity for a frequency non-selective Rayleigh fading channel are given. For simplicity, the azimuth and elevation angle distributions are assumed to be uniform. Simulation results show that the DUCA provided by this paper can decrease SFC between antennas, hence increasing capacity compared with UCAs of the same size. Taking MC into consideration, capacity will increase when the radius of the circle is smaller than . The parameters of arrival signals have a significant impact on the system performance as well. This investigation expands the application of a statistical channel model and optimizes the study of the terminal antenna array.
Identifying and correcting bias in big crowd-sourced online genealogies

Human societies have long valued genealogies as repositories of historical information. However, historical research has shown that genealogies are ﬂawed and should not be taken at face-value. In recent years, online communities have produced big genealogies connecting all continents over multiple centuries. We present the ﬁrst attempt to characterize and account for systematic biases in demographic rates inferred from online genealogy proﬁles. We construct a Bayesian model to compare life event data in a crowd-sourced genealogical dataset with data from the Human Mortality Database (HMD) in four European countries. We ﬁnd that mortality in the genealogy data is under-reported, and propose a method to adjust mortality rates by calibrating against high quality data. To evaluate the method, we estimate out-of-sample adjusted mortality rates for 1835-1900 Finland, and ﬁnd that they are much closer to the HMD over the period where HMD estimates are available (1878 onward). Finally, we obtain adjusted mortality rates for the United States 1835-1900 for which, to our knowledge, no high quality data exist. We expect this to be the ﬁrst of many studies to harvest online genealogical data to improve our understanding of historical human dynamics.
Therapeutic Metabolic Reprograming Using microRNAs: From Cancer to HIV Infection

MicroRNAs (miRNAs) are crucial regulators of cellular processes, including metabolism. Attempts to use miRNAs as therapeutic agents are being explored in several areas, including the control of cancer progression. Recent evidence suggests fine tuning miRNA activity to reprogram tumor cell metabolism has enormous potential as an alternative treatment option. Indeed, cancer growth is known to be linked to profound metabolic changes. Likewise, the emerging field of immunometabolism is leading to a refined understanding of how immune cell proliferation and function is governed by glucose homeostasis. Different immune cell types are now known to have unique metabolic signatures that switch in response to a changing environment. T-cell subsets exhibit distinct metabolic profiles which underlie their alternative differentiation and phenotypic functions. Recent evidence shows that the susceptibility of CD4+ T-cells to HIV infection is intimately linked to their metabolic activity, with many of the metabolic features of HIV-1-infected cells resembling those found in tumor cells. In this review, we discuss the use of miRNA modulation to achieve metabolic reprogramming for cancer therapy and explore the idea that the same approach may serve as an effective mechanism to restrict HIV replication and eliminate infected cells.
Do Data-Driven Decision-Making Efficacy and Anxiety Inventory Scores Mean the Same Thing for Pre-Service and In-Service Teachers?

Teacher data-driven decision making (DDDM) is a professional practice of great prominence in the current K-12 education system. Moreover, teacher self-efficacy and anxiety around DDDM represent important measurement targets in both research and practice. This study consequently examined the validity, reliability, and invariance of data collected via the Data-Driven Decision-Making Efficacy and Anxiety (3D-MEA) Inventory among U.S. in-service (N = 365) and pre-service (N = 457) teachers. The 3D-MEA is intended to measure four dimensions of self-efficacy related to DDDM, as well as anxiety related to DDDM. Multi-group confirmatory factor analyses established structural measurement invariance, which supports meaningful and effectively interchangeable interpretation of 3D-MEA scores with both in-service and pre-service teachers. Reliability estimates were also high in both populations. Limitations and future directions are discussed.
Transcriptome profiling provides preliminary molecular insights into adventitious bud formation in herbaceous peony (Paeonia × ‘Coral Charm’)

ABSTRACT Herbaceous peony is a kind of perennial herbaceous flowering plant and most varieties are highly dependent on ramet propagation. Some varieties, such as Paeonia × ‘Coral Charm’, have characteristics of relatively easy root cutting propagation. However, underlying adventitious buds of root cutting, the molecular mechanisms are still not completely understood. Here, we collected four key stages of adventitious bud formation of P. × ‘Coral Charm’ for transcriptome sequencing, and assembled and annotated 326,139 transcripts. By carrying out weighted gene co-expression network analysis, three functional modules and several biological and metabolic pathways related to the adventitious bud formation were identified. Finally, we determined six transcription factors in the MYB, HD-ZIP, C2H2 and bZIP gene family that may play a key role in the adventitious bud formation. These results provided insights into the adventitious bud formation of herbaceous peony, and laid a theoretical foundation for the rapid propagation of Paeonia.
Dynamic Mode Decomposition of Backward Facing Step Flow Simulation Data

Improved delayed detached eddy (IDDES) simulation results of a backward facing step flow are analyzed using dynamic mode decomposition (DMD). Different flow variables and the time-resolved skin friction coefficient are investigated and compared to a spectral analysis of the wall pressure fluctations. Although the flow field does not contain single dominant modes, two distinct flow features can be extracted and visualized using the DMD mode shapes. A low frequency flapping motion of the shear layer is found in the mode decomposition of the pressure, the wall-normal velocity and the skin friction coefficient. At higher frequencies, a wake mode similar to a von Karman vortex street is identified in the streamwise velocity, the pressure and the vorticity field.
Vehicle Handling Improving By Active Steering

This PSM project is about improving handling behavior of car by using active fiont steering. Active Front Steering (AFS) is a newly developed technology for passenger cars. It provides an electronically controlled superposition of an angle to the hand steering wheel angle that is prescribed by the driver. This additional degree of freedom enables a continuous and driving-situation dependent adaptation of the steering characteristics. At the heart of the new Active Steering system is the planetary gear set integrated into the steering column. An electric motor in the joint adjusts the front wheels' steering angle in proportion to the vehicle current speed. This active steering is evaluated by simulating different steering inputs. The active steering solution has been implemented in MatlabISimulink. A vehicle model is also implemented in Matlab/Simulink. This paper focuses on comparison both two systems: a conventional vehicle and a controlled vehicle. Simulation is made for a constant speed and a specific changeable road adhesion coefficient. The motivation for this work is to understand and characterize the response of a vehicle with a complementary steering system. Improved stability is obtained for the vehicle during slippery road driving.
An efficient ICA-DW-SVDD fault detection and diagnosis method for non-Gaussian processes

Independent Component Analysis (ICA) has been extensively used for detecting faults in industrial processes. While applying ICA to process monitoring, the inability of identifying the important components affect the fault diagnosis ability. For further improving the competence of ICA, this paper proposes an approach integrating ICA, Durbin Watson (DW) criterion and Support Vector Data Description (SVDD) to monitor non-Gaussian process for detecting faults. In the proposed approach, namely ICA–DW–SVDD, ICA is a non-Gaussian information extractor from original variables, DW identifies dominating ICs, and SVDD plays the role of fault detector. This paper also discusses the retracing method to detect original variables causing disturbance in the process. One simulation case and the Tennessee Eastman Process are used to demonstrate the effectiveness of our proposed approach.
Psychosocial Needs and Preferences for Care among Adolescent and Young Adult Cancer Patients (Ages 15–39): A Qualitative Study

Simple Summary Adolescents and young adults (AYAs) are a unique population: they are a diverse group between the ages of 15–39 years with distinct needs and experience numerous developmental milestones during this age range. Notably, AYAs have faced worse outcomes in cancer care, both with shorter survival and worse quality of life compared to children and older adults. Understanding AYAs’ psychosocial, communication and informational needs is crucial to addressing this disparity and improving cancer care delivery. By hearing directly from AYAs, we are able to capture nuances of their experiences and provide clinical recommendations to healthcare providers involved in the care of AYAs with cancer. This study specifically interviewed AYAs with cancer to understand their perspectives, identify needs and to develop recommendations for cancer care delivery and accommodations across the cancer experience. Abstract Adolescents and young adults (AYAs) require a multidisciplinary approach to cancer care due to their complex biopsychosocial situations and varied developmental maturity. Currently, age and diagnosis determine referral to pediatric or adult oncology, with differing treatment paradigms and service utilization patterns, contributing to suboptimal improvements in outcomes. Understanding the unique perspectives of AYAs is essential to designing patient-centered AYA services. Thus, we conducted six focus groups with AYAs (n = 25) treated by medical or pediatric oncologists to evaluate: (1) the unique experiences of cancer care as an AYA; (2) AYA-specific information needs and communication preferences; and (3) recommendations for service provision, delivery and accommodations for AYAs. Transcripts were analyzed using inductive thematic content analysis and identified six major themes to inform clinically-actionable recommendations and the development of a patient-reported outcome measure: (1) AYAs experience social isolation and loss of independence; (2) AYAs have an uncertain sense of the future and need conversations around survivorship and long-term and late effects; (3) AYAs desire greater control over discussions with their care team; (4) AYAs need additional navigational and social/caregiver supports; (5) AYAs prefer an inclusive AYA space in the hospital; and (6) LGBTQ+ patients experience distinct concerns as AYA cancer patients. These will form the basis for specific and tailored clinical recommendations to improve AYA cancer care delivery.
A Study on proportion of frontal plane knee deviations in football players of mangalore and its association with medical-lateral hamstring strenghth ratio: A cross sectional study

Determinants of frontal plane knee deviations is essential in football players because signsof osteoarthritis increases with age than the random population of same age . Kicking and cutting maneuver in football causes external loading of knee joint that shows varus-valgus stresses and causes chances of losing stability medially and laterally. 136 male football players with age group between 15-30 years participated in the study.The inclusion criteria were competitive football players playing since one year . Measurement of Intercondylar,intermalleolartibiofemoral angle and medial and lateral hamstring strength was done. Result showed correlation between number of years of playing football and the lateral hamstring strength of the dominant leg, as well as medial hamstring strength of the non-dominant leg but there was no correlations found between the tibio-femoral angle, the medial- lateral hamstring strength ratios of dominant or the non-dominant leg of the football players .
Identification, Structure and Characterization of Bacillus tequilensis Biofilm with the Use of Electrophoresis and Complementary Approaches

Biofilm is a complex structure formed as a result of the accumulation of bacterial cell clusters on a surface, surrounded by extracellular polysaccharide substances (EPSs). Biofilm-related bacterial infections are a significant challenge for clinical treatment. Therefore, the main goal of our study was to design a complementary approach in biofilm characterization before and after the antibiotic treatment. The 16S rRNA gene sequencing allowed for the identification of Bacillus tequilensis, as a microbial model of the biofilm formation. Capillary electrophoresis demonstrates the capability to characterize and show the differences of the electrophoretic mobility between biofilms untreated and treated with antibiotics: amoxicillin, gentamicin and metronidazole. Electrophoretic results show the clumping phenomenon (amoxicillin and gentamicin) as a result of a significant change on the surface electric charge of the cells. The stability of the dispersion study, the molecular profile analysis, the viability of bacterial cells and the scanning morphology imaging were also investigated. The microscopic and spectrometry study pointed out the degradation/remodeling of the EPSs matrix, the inhibition of the cell wall synthesis and blocking the ribosomal protein synthesis by amoxicillin and gentamicin. However, untreated and treated bacterial cells show a high stability for the biofilm formation system. Moreover, on the basis of the type of the antibiotic treatment, the mechanism of used antibiotics in cell clumping and degradation were proposed.
SUBJECT-SPECIFIC MUSCULOSKELETAL MODEL TO IDENTIFY MUSCLE CONTRIBUTION TO THE ACCELERATION PHASE IN ELITE SPRINTING

The purpose of this study was to identify which lower limb joint moments of force and lower limb muscles had the highest contribution to the forward and upward acceleration of the Body Centre of Gravity (BCG) in an elite sprinter during the first step after starting from blocks in 100 meters dash. An induced acceleration analysis approach was used to mechanically ascertain this contribution. Two models were used, one based in a simple multilink rigid body’s model and a second using a musculoskeletal model developed using Opensim. Our results showed a possible synergist action between hip and ankle extensors that allow an optimal combination that resulted in a forward propulsion of the BCG, this results seem to be corroborated using an Opensim musculoskeletal model.
Power Graphs of Finite Groups Determined by Hosoya Properties

Suppose G is a finite group. The power graph represented by P(G) of G is a graph, whose node set is G, and two different elements are adjacent if and only if one is an integral power of the other. The Hosoya polynomial contains much information regarding graph invariants depending on the distance. In this article, we discuss the Hosoya characteristics (the Hosoya polynomial and its reciprocal) of the power graph related to an algebraic structure formed by the symmetries of regular molecular gones. As a consequence, we determined the Hosoya index of the power graphs of the dihedral and the generalized groups. This information is useful in determining the renowned chemical descriptors depending on the distance. The total number of matchings in a graph Γ is known as the Z-index or Hosoya index. The Z-index is a well-known type of topological index, which is popular in combinatorial chemistry and can be used to deal with a variety of chemical characteristics in molecular structures.