Miracle-dz/UniFAR-FTUs huggingface dataset:
Cross-Validation of a Multiplex LC-MS/MS Method for Assaying mAbs Plasma Levels in Patients with Cancer: A GPCO-UNICANCER Study

Background: Different liquid chromatography tandem mass spectrometry (LC–MS/MS) methods have been published for quantification of monoclonal antibodies (mAbs) in plasma but thus far none allowed the simultaneous quantification of several mAbs, including immune checkpoint inhibitors. We developed and validated an original multiplex LC–MS/MS method using a ready-to-use kit to simultaneously assay 7 mAbs (i.e., bevacizumab, cetuximab, ipilimumab, nivolumab, pembrolizumab, rituximab and trastuzumab) in plasma. This method was next cross-validated with respective reference methods (ELISA or LC–MS/MS). Methods: The mAbXmise kit was used for mAb extraction and full-length stable-isotope-labeled antibodies as internal standards. The LC–MS/MS method was fully validated following current EMA guidelines. Each cross validation between reference methods and ours included 16–28 plasma samples from cancer patients. Results: The method was linear from 2 to 100 µg/mL for all mAbs. Inter- and intra-assay precision was <14.6% and accuracy was 90.1–111.1%. The mean absolute bias of measured concentrations between multiplex and reference methods was 10.6% (range 3.0–19.9%). Conclusions: We developed and cross-validated a simple, accurate and precise method that allows the assay of up to 7 mAbs. Furthermore, the present method is the first to offer a simultaneous quantification of three immune checkpoint inhibitors likely to be associated in patients.
Cystic Fibrosis Clinical Isolates of Aspergillus fumigatus Induce Similar Muco-inflammatory Responses in Primary Airway Epithelial Cells

Aspergillus is increasingly associated with lung inflammation and mucus plugging in early cystic fibrosis (CF) disease during which conidia burden is low and strains appear to be highly diverse. It is unknown whether clinical Aspergillus strains vary in their capacity to induce epithelial inflammation and mucus production. We tested the hypothesis that individual colonising strains of Aspergillus fumigatus would induce different responses. Ten paediatric CF Aspergillus isolates were compared along with two systemically invasive clinical isolates and an ATCC reference strain. Isolates were first characterised by ITS gene sequencing and screened for antifungal susceptibility. Three clusters (A−C) of Aspergillus isolates were identified by ITS. Antifungal susceptibility was variable, particularly for itraconazole. Submerged CF and non-CF monolayers as well as differentiated primary airway epithelial cell cultures were incubated with conidia for 24 h to allow germination. None of the clinical isolates were found to significantly differ from one another in either IL-6 or IL-8 release or gene expression of secretory mucins. Clinical Aspergillus isolates appear to be largely homogenous in their mucostimulatory and immunostimulatory capacities and, therefore, only the antifungal resistance characteristics are likely to be clinically important.
One‐Step Synthesis of 2,5‐Bis(chloromethyl)‐1,4‐dioxane from Epichlorohydrin Using ZIF‐8, Taking Advantage of Structural Defects

We demonstrate herein the ZIF-8-only-mediated catalysis of the cyclodimerization of epichlorohydrin to 2,5-bis(chloromethyl)-1,4-dioxane in the absence of co-catalyst and solvent. The easy handling and economic aspects of ZIF-8, in addition to the one-step reaction to produce the cyclodimer, make this catalyst attractive even for industry. It has been clearly illustrated that the nature of the method used to synthesize ZIF-8 affected the yields of the cyclodimers. Specifically, the method employed to produce ZIF-8 directly influences the amount of crystal structural defects, which in turn impacts their performance as catalysts. To emphasize the role of defects, other physical properties, such as surface area and particle size, were controlled during the synthesis of the ZIF-8 catalysts. Remarkably, the amount of structural defects was quantified by temperature program desorption analysis.
MXenes/graphene heterostructures for Li battery applications: a first principles study

MXenes are the newest class of two-dimensional (2D) materials, and they offer great potential in a wide range of applications including electronic devices, sensors, and thermoelectric and energy storage materials. In this work, we combined the outstanding electrical conductivity, that is essential for battery applications, of graphene with MXene monolayers (M2CX2 where M = Sc, Ti, V and X = OH, O) to explore its potential in Li battery applications. Through first principles calculations, we determined the stable stacking configurations of M2CX2/graphene bilayer heterostructures and their Li atom intercalation by calculating the Li binding energy, diffusion barrier and voltage. We found that: (1) for the ground state stacking, the interlayer binding is strong, yet the interlayer friction is small; (2) Li binds more strongly to the O-terminated monolayer, bilayer and heterostructure MXene systems when compared with the OH-terminated MXenes due to the H+ induced repulsion to the Li atoms. The binding energy of Li decreases as the Li concentration increases due to enhanced repulsive interaction between the positively charged Li ions; (3) Ti2CO2/graphene and V2CO2/graphene heterostructures exhibit large Li atom binding energies making them the most promising candidates for battery applications. When fully loaded with Li atoms, the binding energy is −1.43 eV per Li atom and −1.78 eV per Li atom for Ti2CO2/graphene and V2CO2/graphene, respectively. These two heterostructures exhibit a nice compromise between storage capacity and kinetics. For example, the diffusion barrier of Li in Ti2CO2/graphene is around 0.3 eV which is comparable to that of graphite. Additionally, the calculated average voltages are 1.49 V and 1.93 V for Ti2CO2/graphene and V2CO2/graphene structures, respectively; (4) a small change in the in-plane lattice parameters (<1%), interatomic bond lengths and interlayer distances (<0.5 A) proves the stability of the heterostructures against Li intercalation, and the impending phase separation into constituent layers and capacity fading during charge–discharge cycles in real battery applications; (5) as compared to bare M2CX2 bilayers, M2CX2/graphene heterostructures have lower molecular mass, offering high storage capacity; (6) the presence of graphene ensures good electrical conductivity that is essential for battery applications. Given these advantages, Ti2CO2/graphene and V2CO2/graphene heterostructures are predicted to be promising for lithium-ion battery applications.
Automated diagnosis of atrial fibrillation in 24-hour Holter recording based on deep learningï¼a study with randomized and real-world data validation

Background: With the increasing demand for atrial fibrillation (AF) screening, clinicians spend a significant amount of time in identifying the AF signals from massive electrocardiogram (ECG) data in long-term dynamic ECG monitoring. In this study, we aim to reduce clinicians workload and promote AF screening by using artificial intelligence (AI) to automatically detect AF episodes and identify AF patients in 24 h Holter recording. Methods: We used a total of 22 979 Holter recordings (24 h) from 22 757 adult patients and established accurate annotations for AF by cardiologists. First, a randomized clinical cohort of 3 000 recordings (1 500 AF and 1 500 non-AF) from 3000 patients recorded between April 2012 and May 2020 was collected and randomly divided into training, validation and test sets (10:1:4). Then, a deep-learning-based AI model was developed to automatically detect AF episode using RR intervals and was tested with the test set. Based on AF episode detection results, AF patients were automatically identified by using a criterion of at least one AF episode of 6 min or longer. Finally, the clinical effectiveness of the model was verified with an independent real-world test set including 19 979 recordings (1 006 AF and 18 973 non-AF) from 19 757 consecutive patients recorded between June 2020 and January 2021. Findings: Our model achieved high performance for AF episode detection in both test sets (sensitivity: 0.992 and 0.972; specificity: 0.997 and 0.997, respectively). It also achieved high performance for AF patient identification in both test sets (sensitivity:0.993 and 0.994; specificity: 0.990 and 0.973, respectively). Moreover, it obtained superior and consistent performance in an external public database. Interpretation: Our AI model can automatically identify AF in long-term ECG recording with high accuracy. This cost-effective strategy may promote AF screening by improving diagnostic effectiveness and reducing clinical workload.
The Ethics of Using Digital Trace Data in Education: A Thematic Review of the Research Landscape

This article presents the findings of a systematic qualitative analysis of research in the ethics of digital trace data use in learning and education. From the resulting analysis of 77 peer-reviewed studies, we (1) map the characteristics of research by study type, academic community, institutional setting, and national context; (2) identify the primary ethical concerns and related responses; and (3) highlight the research gaps. Four areas of focus are identified in this emerging area: (1) privacy, informed consent, and data ownership; (2) validity and integrity; (3) ethical decision making; and (4) governance and accountability. We highlight the lack of evidence particularly for preschool and school-aged children and the disparate communities working in this domain, and we suggest a more cohesive approach, where the wider learning and educational ecosystem is recognized, explicit engagement with ethical theory is central, and mid- to long-term ethical issues are considered alongside immediate concerns.
Do Entrepreneurship Skills Improve Project Performance? A Project-Based Learning Perspective

This study examines the effect of entrepreneurship skillsets on project performance. Building upon the theory of planned behaviour, we examine the impact of individual entrepreneurship orientation (IEO) and entrepreneurship self-efficacy (ESE) on project performance, using a sample of 243 observations from students’ projects in areas of science, engineering and technology. We examine our research questions using a combination of multivariate regression analysis and robust regression. The results show that the survey is valid and reliable in measuring IEO and ESE, and the survey can be used to assess the relationship between IEO, ESE and project performance. In addition, the findings indicate that appearance self-efficacy is the variable that most significantly contributes to project performance, followed by social skills, then management skills. The study provides insights into how entrepreneurship skills can be viewed as important skillsets for success in projects and how operations and project managers can emphasise certain entrepreneurship skills to enhance project performance. At the individual level, entrepreneurship skills can be viewed as skillsets that improve project performance even in projects that are less entrepreneurial in nature. The improvement in performance is primarily in projects that are more structured, have a specific timeline and have defined objectives.
Comprehensive Meta-Analysis of Attention-Deficit/Hyperactivity Disorder Psychosocial Treatments Investigated Within Between Group Studies

Interventions for attention-deficit/hyperactivity disorder (ADHD) include positive behavior supports (e.g., parent training, school-based contingency management, behavioral peer interventions), training interventions (e.g., organizational skills training, social skills training, etc.), and other interventions (e.g., academic accommodations/modifications, self-monitoring). There is a need to conduct a comprehensive meta-analysis of psychosocial treatments for ADHD given discrepancies between meta-analyses. The present meta-analysis reports the results of between-group studies that compared a psychosocial treatment to a control condition from 1968 to 2016. In total, 226 studies were identified that met inclusion criteria. Results of the meta-analysis were organized by treatment type, rater, and domain of outcome assessed. Results indicated considerable variability across these parameters, with the strongest effects for proximal outcomes of behavioral parent training (improvements in parenting behaviors yielded a standardized mean difference of 0.70) and improvements in child behavior following implementation of behavioral school intervention (standardized mean difference of 0.66 and 0.72 for teacher ratings of ADHD symptoms and impairment, respectively). Other interventions were not extensively studied as stand-alone approaches. Results are discussed in light of current support for the use of psychosocial interventions for individuals with ADHD.
Cyberspace at the Grassroots: E-Governance and Citizen/Stakeholder Perceptions at the Local Level in Bangladesh

Bangladesh has experimented with e-governance since the early 2000s and currently ranks among the top 10 least developed countries. The deployment of e-governance at the local level has provided benefits to the rural people, with local councils increasingly using information and communications technology (ICT) to expand community-based delivery systems and augment rural service delivery. One-stop cyber centres provide a range of services that are user-friendly, cost-effective and less time-consuming. This study focuses on five sub-districts to inquire about the range of services provided by the e-service centres there. It has recorded citizen perceptions and the level of their satisfaction and the observations of service providers about the e-service mechanism. It also identifies key challenges in service delivery. Citizen satisfaction was measured using 12 indicators, while the service provider observations focused on social issues, governance, resource and technical issues. The study found several issues requiring attention to consolidate the e-governance system in the country.
Pasteur's Quadrant as the Bridge Linking Rigor with Relevance

A tension exists between educational practitioners and researchers, which is often attributed to their dichotomous and oftentimes polarizing professional ideologies or Discourse communities. When determining what works in education, researchers tend to emphasize evidence-based practices (EBPs) supported by research that is rigorous and internally valid, whereas practitioners tend to value practice-based evidence (PBE) that is relevant and externally valid. The authors argue that these separate mindsets stem from the classical view of research as being either rigorous or relevant. In his canonical Pasteur's Quadrant, Stokes (1997) proposed that rigor and relevance are complementary notions that, when merged, further the production, translation, and implementation of instructional practices that are both rigorous (i.e., evidence-based) and relevant (i.e., practice-based). The authors propose educational design research (EDR) and communities of practice (CoPs) as frameworks through which to realize the promise of Pasteur's quadrant.
Dealing with Common Method Variance in International Marketing Research

Common method variance (CMV) is an important concern in international marketing research because presumed substantive relationships may actually be due to shared method variance. Because method effects may vary systematically across cultures and countries, accounting for method effects in international marketing research is particularly critical. A systematic review of Journal of International Marketing articles published during a five-year period (2015–2019, N = 93) shows that (1) authors often report post hoc CMV tests but usually conclude that CMV is not an issue and (2) many post hoc tests are conducted using the Harman one-factor test and the marker variable technique, which have serious deficiencies for detecting and controlling CMV. Drawing on a classification and comparative evaluation of the most common statistical approaches for dealing with CMV, the authors recommend two approaches and propose a procedure for dealing with CMV in international marketing research. The procedure, which is based on multisample structural equation modeling, is illustrated with data from a cross-national pan-European survey (N = 11,970, 14 countries), which shows that even though method variance is present in the data, method effects do not seriously bias the substantive conclusions in this particular study.
Sensing properties, energy transfer mechanism and tuneable particle size processing of luminescent two-dimensional rare earth coordination networks

A new isostructural family of layered coordination networks (CNs) based on rare earth elements and mixed ligands was hydrothermally synthesized and fully characterized. The set of compounds with the general formula [REE(Salicylate)(Succinate)(0.5)(H2O)] (with REE = Ho or Y) belong to the monoclinic P2(1)/c space group. Top-down methods were implemented in order to obtain nano-sized CN particles for potential application in thin film fabrication. The solid state photoluminescence (SSPL) of the Eu, Tb and Eu/Tb doped samples was explored in terms of excitation/emission spectra, lifetime values and quantification of light emission by the CIE chromaticity calculation. Measurement of the triplet state energy of the ligand at low temperature was carried out by analysing the SSPL of the Y-based compound; energy transfer pathways were studied. According to the high performance of the Tb-doped compound as a green emitter, thermal and chemical sensing assays were carried out.
Szabó Exploring equivalence frames : Metaphorical lexical items as means of determining equivalence frames

This paper explores lexical items as possible units with which to detect equivalence-based framing, which shows how a given piece of information is framed. In line with frame semantics and figurative framing, individual words used metaphorically are discussed as tools to determine equivalence frames. The study applies conceptual metaphor theory (CMT) to determine the metaphors evoked by words referring to the demonstrators and their movement used in 81 news articles about the Women’s March in the USA published on the websites of the most widely circulated American newspapers between 2017 and 2019. The analysis reveals that lexical items (e.g., flood, sea, wave) evoking the WATER domain were used to frame the protest; this finding is in contrast to the use of words from other source domains, such as WAR, which are commonly used to frame demonstrations.
Mesoscale Elucidation of Solid Electrolyte Interphase Layer Formation in Li-Ion Battery Anode

Capacity fade in lithium-ion batteries largely originates from the undesired electrolyte decomposition, which results in the formation of solid electrolyte interphase (SEI) and the anode surface passivation. In this work, a mesoscale interfacial modeling approach is developed to investigate the formation and growth of the SEI film on a typical graphite based anode over several cycles. It is found that lithium diffusion kinetics in the SEI film significantly affects the SEI growth rate. A lower lithium diffusion barrier leads to a higher growth rate. The present model demonstrates that the SEI thickness is a linear function of the square root of the charging time over long-time cycling. Growth of multicomponent SEI film is also elucidated. It is found that the heterogeneity of the SEI film may lead to instability in lithium ion concentration distribution.
Nursing and visibility in covid-19 pandemic: social media monitoring/ Enfermagem e visibilidade na pandemia da covid-19: monitoramento de mídia social/ Enfermería y visibilidad en la pandemia del covid-19: monitorización de los medios sociales

Objetivo analisar as publicações de usuários do Twitter direcionadas à campanha de valorização da Enfermagem, impulsionadas pelos termos #LuteComoUmaEnfermeira e #EnfermagemEuValorizo. Método pesquisa quantitativa, fundamentada nos métodos digitais. A busca foi realizada utilizando as hashtags #LuteComoUmaEnfermeira e #EnfermagemEuValorizo para extração de tweets. Foram selecionados para análise 2.613 tweets. Resultados 22,5% das publicações localizam-se na região Sudeste do país e 9,3% na região Nordeste. Houve mais de 18 mil interações (curtidas e compartilhamentos), sendo que os autores das postagens atingem um público estimado de cerca 7 milhões de pessoas. O conteúdo das postagens versava principalmente sobre a regulamentação da jornada de trabalho, Equipamentos de Proteção Individual, combate ao COVID-19, defesa da força de trabalho majoritariamente feminina e luta por direitos. Conclusão a realização da campanha virtual teve visibilidade importante no território nacional e apresentou grande visibilidade à profissão em número e alcance na Internet.
Mechanical failure of mulberry and tasar silk

This article investigates the tensile and twist failure of mulberry and tasar silk fi laments. The mulberry and tasar fi laments were subjected to uniaxial loading on Instron tensile tester at diff erent rate of extensions and gauge lengths. Furthermore, the number of turns to rupture the silk fi laments was tested using a twist tester. The results showed that the mulberry fi lament has higher tensile and twist strength than that of tasar fi lament. The SEM photomicrographs of the region of fracture divulged that the tensile and twist failure of mulberry and tasar fi laments take place in catastrophic and non-catastrophic modes, respectively.
Dynamics-Aware Quality-Diversity for Efficient Learning of Skill Repertoires

Quality-Diversity (QD) algorithms are powerful exploration algorithms that allow robots to discover large repertoires of diverse and high-performing skills. However, QD algorithms are sample inefficient and require millions of evaluations. In this paper, we propose Dynamics-Aware Quality-Diversity (DA-QD), a framework to improve the sample efficiency of QD algorithms through the use of dynamics models. We also show how DA-QD can then be used for continual acquisition of new skill repertoires. To do so, we incrementally train a deep dynamics model from experience obtained when performing skill discovery using QD. We can then perform QD exploration in imagination with an imagined skill repertoire. We evaluate our approach on three robotic experiments. First, our experiments show DA-QD is 20 times more sample efficient than existing QD approaches for skill discovery. Second, we demonstrate learning an entirely new skill repertoire in imagination to perform zero-shot learning. Finally, we show how DA-QD is useful and effective for solving a long horizon navigation task and for damage adaptation in the real world. Videos and source code are available at: https://sites.google. com/view/da-qd.