Miracle-dz/UniFAR-FTUs huggingface dataset:
A systematic review of doctoral graduate attributes: Domains and definitions

Doctoral graduate attributes are the qualities, skills, and competencies that graduates possess, having completed their doctorate degree. Graduate attributes, in general, lack conceptual clarity, making the investigation into and quality assurance processes attached to doctoral outcomes challenging. As many graduate attributes are “unseen” or implicit, the full range of attributes that doctoral graduate actually possess needs to be synthesized, so that they may be recognized and utilized by educational stakeholders. The aim of this study was to establish and describe what attributes graduates from doctoral degrees possess. A systematic review of peer-reviewed, primary literature published between January 2016 and June 2021 was conducted, identifying 1668 articles. PRISMA reporting was followed, and after screening and full text critical appraisal, 35 articles remained for summation through thematic synthesis. The doctoral graduate attribute domains identified included knowledge, research skills, communication skills, organizational skills, interpersonal skills, reputation, scholarship, higher order thinking skills, personal resourcefulness, and active citizenship. Many of the domains were conceptualized as transferable or interdisciplinary, highlighting the relevance of the attributes doctoral graduates possess. The review findings align with existing frameworks yet extend those that tend to focus on generic “seen” attributes, and include a range of “unseen”, intrinsic qualities as outcomes of the doctoral degree. The review contributes to the conceptual development of doctoral graduate attributes, by synthesizing actual outcomes, as opposed to prospective attributes or attributes-in-process. Doctoral graduate attributes should be conceptualized to integrate both generic attributes alongside intrinsic qualities that are important for employability. Increased awareness as to the scope of doctoral graduate attributes among stakeholders, such as doctoral supervisors, students, graduates and employers, may facilitate improved educational outcomes and employability. Future research into the contextual relevance of the domains identified and how they are developed may be beneficial. Future research could involve the development of context-relevant scales to empirically measure doctoral graduate attributes among alumni populations, as a quality assurance outcome indicator. Such findings could inform program reform, improving the relevance of doctoral education and the employability of doctoral graduates.
Vortex simulation of three-dimensional, spotlike disturbances in a laminar boundary layer

The growth of a turbulent spot in a laminar boundary layer, as the spot evolves from a localized disturbance in the layer, is simulated numerically using a three-dimensional vortex filament description of the vorticity field. The filaments are marked with a sequence of mode points which are tracked in a Lagrangian reference frame. Velocity computation is done by Biot-Savart integration. Although some discrepancies with experiment appear to exist in the near wall region, the gross properties of the spot, including the velocities of the leading and trailing edges and the velocity perturbations away from the wall, are in good agreement with experiment.
Rapid prediction of winter wheat yield and nitrogen use efficiency using consumer-grade unmanned aerial vehicles multispectral imagery

Rapid and accurate assessment of yield and nitrogen use efficiency (NUE) is essential for growth monitoring, efficient utilization of fertilizer and precision management. This study explored the potential of a consumer-grade DJI Phantom 4 Multispectral (P4M) camera for yield or NUE assessment in winter wheat by using the universal vegetation indices independent of growth period. Three vegetation indices having a strong correlation with yield or NUE during the entire growth season were determined through Pearson’s correlational analysis, while multiple linear regression (MLR), stepwise MLR (SMLR), and partial least-squares regression (PLSR) methods based on the aforementioned vegetation indices were adopted during different growth periods. The cumulative results showed that the reciprocal ratio vegetation index (repRVI) had a high potential for yield assessment throughout the growing season, and the late grain-filling stage was deemed as the optimal single stage with R2, root mean square error (RMSE), and mean absolute error (MAE) of 0.85, 793.96 kg/ha, and 656.31 kg/ha, respectively. MERIS terrestrial chlorophyll index (MTCI) performed better in the vegetative period and provided the best prediction results for the N partial factor productivity (NPFP) at the jointing stage, with R2, RMSE, and MAE of 0.65, 10.53 kg yield/kg N, and 8.90 kg yield/kg N, respectively. At the same time, the modified normalized difference blue index (mNDblue) was more accurate during the reproductive period, providing the best accuracy for agronomical NUE (aNUE) assessment at the late grain-filling stage, with R2, RMSE, and MAE of 0.61, 7.48 kg yield/kg N, and 6.05 kg yield/kg N, respectively. Furthermore, the findings indicated that model accuracy cannot be improved by increasing the number of input features. Overall, these results indicate that the consumer-grade P4M camera is suitable for early and efficient monitoring of important crop traits, providing a cost-effective choice for the development of the precision agricultural system.
Endometriosis-associated infertility: From pathophysiology to tailored treatment

Despite the clinically recognized association between endometriosis and infertility, the mechanisms implicated in endometriosis-associated infertility are not fully understood. Endometriosis is a multifactorial and systemic disease that has pleiotropic direct and indirect effects on reproduction. A complex interaction between endometriosis subtype, pain, inflammation, altered pelvic anatomy, adhesions, disrupted ovarian reserve/function, and compromised endometrial receptivity as well as systemic effects of the disease define endometriosis-associated infertility. The population of infertile women with endometriosis is heterogeneous, and diverse patients’ phenotypes can be observed in the clinical setting, thus making difficult to establish a precise diagnosis and a single mechanism of endometriosis related infertility. Moreover, clinical management of infertility associated with endometriosis can be challenging due to this heterogeneity. Innovative non-invasive diagnostic tools are on the horizon that may allow us to target the specific dysfunctional alteration in the reproduction process. Currently the treatment should be individualized according to the clinical situation and to the suspected level of impairment. Here we review the etiology of endometriosis related infertility as well as current treatment options, including the roles of surgery and assisted reproductive technologies.
Identifying 'Island-Mainland' phase transition using the Euler number

In the present communication we describe the Island-Mainland transition, occurring in a square lattice, when black squares are randomly dropped on a white background. Initially clusters of black squares are observed on the connected white background. But as concentration of black sites increases, at some point the black squares join to form a single continuous black background with white clusters randomly scattered in it. We show that the minimum in the Euler number, defined as the difference between number of white clusters and number of black clusters, reaches a minimum at this point. This occurs at a concentration higher than the well-known percolation phase transition and we show that the phenomenon can be related to experimental observations in several physical systems.
Predictive value of baseline metabolic tumor burden on 18F-FDG PET/CT for brain metastases in patients with locally advanced non-small-cell lung cancer

Objectives Brain metastases (BMs) are a major cause leading to the failure of treatment management for non-small-cell lung cancer (NSCLC) patients. The purpose of this study was to evaluate the predictive value of baseline metabolic tumor burden on 18F-FDG PET/CT measured with metabolic tumor volume (MTV) and total lesion glycolysis (TLG) for brain metastases (BMs) development in patients with locally advanced non-small-cell lung cancer (NSCLC) after treatment. Methods Forty-seven patients with stage IIB-IIIC NSCLC who underwent baseline 18F-FDG PET/CT examinations were retrospectively reviewed. The maximum standardized uptake value (SUVmax), MTV, and TLG of the primary tumor (SUVmaxT, MTVT, and TLGT), metastatic lymph nodes (SUVmaxN, MTVN, and TLGN), and whole-body tumors (SUVmaxWB, MTVWB, and TLGWB) were measured. The optimal cut-off values of PET parameters to predict brain metastasis-free survival were obtained using Receiver operating characteristic (ROC) analysis, and the predictive value of clinical variables and PET parameters were evaluated using Cox proportional hazards regression analysis. Results The median follow-up duration was 25.0 months for surviving patients, and 13 patients (27.7%) developed BM. The optimal cut-off values were 21.1 mL and 150.0 g for MTVT and TLGT, 20.0, 10.9 mL and 55.6 g for SUVmaxN, MTVN and TLGN, and 27.9, 27.4 mL and 161.0 g for SUVmaxWB, MTVWB and TLGWB, respectively. In the Cox proportional hazards models, the risk of BM was significantly associated with MTVN and MTVWB or TLGN and TLGWB after adjusting for histological cell type, N stage, SUVmaxN, and SUVmaxWB. Conclusions Baseline metabolic tumor burden (MTV and TLG) evaluated from the level of metastatic lymph nodes and whole-body tumors are significant predictive factors for BM development in patients with locally advanced NSCLC.
Participant characteristics associated with the effects of a physical and cognitive training program on executive functions

Background Physical and cognitive interventions have been shown to induce positive effects on older adults’ executive functioning. However, since participants with different background characteristics may respond differently to such interventions, we investigated whether training effects on executive functions were associated with sex, training compliance, and age. We also investigated if change in global cognition was associated with physical and cognitive training intervention-induced changes in executive functions. Methods Exploratory data from a randomized controlled trial were analyzed. Participants were 70–85-year-old men and women who received a 12-month physical (PT) or physical and cognitive training (PTCT) intervention. Measurements of executive functions related to inhibition (Stroop), set shifting (Trail Making Test B) and updating (Verbal Fluency) were performed at baseline and 12 months. Data were analyzed using a longitudinal linear path model for the two measurements occasion. Results Stroop improved significantly more in women and participants in the low compliance subgroup who received PTCT than in counterparts in the PT subgroup (difference –8.758, p = 0.001 and difference –8.405, p = 0.010, respectively). In addition, TMT B improved after the intervention in the low compliance PTCT subgroup and worsened in the corresponding PT subgroup (difference –15.034, p = 0.032). No other significant associations were observed. Conclusion Executive functions in women and in the participants, who only occasionally engaged in training showed greater improvement after the PTCT than PT intervention. However, the additional extra benefit gained from the PTCT intervention was uniquely expressed in each executive function measured in this study.
Neuroinflammation in the medial prefrontal cortex exerts a crucial role in bone cancer pain

Bone cancer pain (BCP) is one of the most common types of pain in cancer patients which compromises the patient’s functional status, quality of life, and survival. Central hyperalgesia has increasingly been identified as a crucial factor of BCP, especially in the medial prefrontal cortex (mPFC) which is the main cortical area involved in the process of pain and consequent negative emotion. To explore the genetic changes in the mPFC during BCP occurrence and find possible targets for prediction, we performed transcriptome sequencing of mPFC in the BCP rat model and found a total of 147 differentially expressed mRNAs (DEmRNAs). A protein-protein interaction (PPI) network revealed that the DEmRNAs mainly participate in the inflammatory response. Meanwhile, microglia and astrocytes were activated in the mPFC of BCP rats, further confirming the presence of neuroinflammation. In addition, Gene Ontology (GO) analysis showed that DEmRNAs in the mPFC are mainly involved in antigen processing, presentation of peptide antigen, and immune response, occurring in the MHC protein complex. Besides, the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that DEmRNAs are mainly enriched in the pathways of phagosome, staphylococcus aureus infection, and antigen processing, in which MHCII participate. Furthermore, immunostaining showed that MHCII is mainly located in the microglia. Microglia are believed to be involved in antigen processing, a key cause of BCP. In vivo, minocycline (MC) treatment inhibits the activation of microglia and reduces the expression of MHCII and proinflammatory cytokines, thereby alleviating BCP and pain-related anxiety. Taken together, our study identified differentially expressed genes in the BCP process and demonstrated that the activation of microglia participates in the inflammatory response and antigen process, which may contribute to BCP.
Exploring the design of a sport for employability program: A case study

Rates of young people who are neither in employment, education, or training (NEET) are fairly high in the European Union. Correspondingly, there has been a growing tendency to regard sport as a suitable tool to develop soft skills and raise NEETs' level of employability. However, if and how such sport for employability (SfE) programs are able to realize these major claims has been called into question. The purpose of the present study was, therefore, to explore how an actual SfE initiative constructs and delivers its program. In addition, the article assessed whether the investigated program operates in line with researchers' recent calls for theory-based approaches. Guided by a case study approach set up within an initiative located in Flanders, data were gathered through 12 semi-structured interviews with 8 program providers. Results, analyzed using thematic analysis, indicated that the program was characterized by an absence of well-defined desired outcomes, imprecision as to how the program should contribute to these outcomes, and consequently minimal attention to the follow-up of participants' progress. As such, these findings and the accompanying challenges point to the absence of a theory-based approach. Several possible sources for the lack of a systematic approach are discussed.
Numerical Methods for Nonsmooth Dynamical Systems: Applications in Mechanics and Electronics

This book concerns the numerical simulation of dynamical systems whose trajectories may not be differentiable everywhere. They are named nonsmooth dynamical systems. They make an important class of systems, firstly because of the many applications in which nonsmooth models are useful, secondly because they give rise to new problems in various fields of science. Usually nonsmooth dynamical systems are represented as differential inclusions, complementarity systems, evolution variational inequalities, each of these classes being itself split into several subclasses. With detailed examples of multibody systems with contact, impact and friction and electrical circuits with piecewise linear and ideal components, the book is is mainly intended for researchers in Mechanics and Electrical Engineering, but it will be attractive to researchers from other scientific communities like Systems and Control, Robotics, Physics of Granular Media, Civil Engineering, Virtual Reality, Haptic Systems, Computer Graphics, etc.
Biomarkers of autoimmunity and beta cell metabolism in type 1 diabetes

Posttranslational protein modifications (PTMs) are an inherent response to physiological changes causing altered protein structure and potentially modulating important biological functions of the modified protein. Besides cellular metabolic pathways that may be dictated by PTMs, the subtle change of proteins also may provoke immune attack in numerous autoimmune diseases. Type 1 diabetes (T1D) is a chronic autoimmune disease destroying insulin-producing beta cells within the pancreatic islets, a result of tissue inflammation to specific autoantigens. This review summarizes how PTMs arise and the potential pathological consequence of PTMs, with particular focus on specific autoimmunity to pancreatic beta cells and cellular metabolic dysfunction in T1D. Moreover, we review PTM-associated biomarkers in the prediction, diagnosis and in monitoring disease activity in T1D. Finally, we will discuss potential preventive and therapeutic approaches of targeting PTMs in repairing or restoring normal metabolic pathways in pancreatic islets.
Riverine microplastic contamination in southwest Germany: A large-scale survey

Microplastic (MP) contamination of freshwater ecosystems is still in the focus of research and public attention, as aquatic environments have a high ecological, economic, and recreational value. We now know that rivers do not only function as pathways of MPs into oceans but may also act as temporary MP sinks. However, due to methodological differences, the comparability of studies on MP contamination of rivers is still limited. To compare MP contamination between different river systems, to analyze if there is a constant increase in MP contamination from the upper to the lower course of the river, and to investigate if there are distinct MP distribution patterns, we set up a large-scale survey. We chose two large river systems, the Rhine and Danube catchments with their tributaries and sampled 23 rivers of different sizes at 53 sampling locations in southwest Germany. Surface water sampling, sample processing, and analysis were performed with the same methodology to obtain comparable results on MP number, polymer type, and particle’s size and shape. Fully quantitative data were generated down to 300 µm by using a manta trawl net with a 300-µm mesh size for sampling. Nevertheless, we also included the non-quantitative sampled fraction of particles down to a size of 20 µm in our FTIR analysis after plastic-friendly sample purification by enzymatic oxidative treatment. Plastic concentrations recorded in surface water at the sampling locations ranged from 0.7 to 354.9 particles/m³. Concerning all samples, the number of particles increased toward lower size classes (61.0 ± 34.2% below 300 µm), and fragments were the prevailing shape (90.7 ± 13.6%). Polyethylene (49.2 ± 25.9%) and polypropylene (33.2 ± 22.6%) were the most frequent polymer types. Our survey did not reveal distinct MP distribution patterns or a constant increase of MP abundance within river courses in the investigated river systems. Next, to provide a large-scale dataset of microplastic contamination in surface waters of southwest Germany, our study shows that a representative sampling of MPs in rivers is challenging. MP particles are not homogeneously distributed in rivers, and this indicates that spatial and temporal changes in MP abundance should always be considered in MP monitoring approaches.
Quantitative cell imaging approaches to metastatic state profiling

Genetic heterogeneity of metastatic dissemination has proven challenging to identify exploitable markers of metastasis; this bottom-up approach has caused a stalemate between advances in metastasis and the late stage of the disease. Advancements in quantitative cellular imaging have allowed the detection of morphological phenotype changes specific to metastasis, the morphological changes connected to the underlying complex signaling pathways, and a robust readout of metastatic cell state. This review focuses on the recent machine and deep learning developments to gain detailed information about the metastatic cell state using light microscopy. We describe the latest studies using quantitative cell imaging approaches to identify cell appearance-based metastatic patterns. We discuss how quantitative cancer biologists can use these frameworks to work backward toward exploitable hidden drivers in the metastatic cascade and pioneering new Frontier drug discoveries specific for metastasis.
The concept of tissue regeneration: Epistemological and historical enquiry from early ideas on the regeneration of bone to the microscopic observations of the regeneration of peripheral nerves

This paper examines the epistemological history of physiological tissue regeneration theories from Antiquity to the present time focusing on early clinical observations, microscopic investigations of the 19th C. and molecular aspects of the regeneration of peripheral nerves. We aim to show underlying theoretical implications at stake over centuries, with an extreme diversity of local contexts, while slowly emerging ideas were progressively built in the framework of cell theory and that of molecular biology. The overall epistemological lesson is that this long history is far from finished and requires novel experiments and perspectives, as well as the careful inspection of its rich past, as a true scientific tradition, in order to better understand what is nervous regeneration and how we can use it in medicine.
The synthesis of extracellular vesicles by the protistan parasite Blastocystis

Blastocystis is a genus of single-celled protist belonging to the stramenopile group. Prior studies have shown that isolates of Blastocystis subtype 7 (ST7) induced higher levels of intestinal epithelial cell damage and gut microbiota dysbiosis in comparison to other subtypes in in vivo and in vitro settings. Prior research has shown a link between gut dysbiosis and exposure to extracellular vesicles (EVs) produced by pathogenic microorganisms. This study demonstrates a protocol for the isolation of EVs from Blastocystis ST7 via ultracentrifugation. Nanoparticle tracking analysis and transmission electron microscopy were used to assess EV size and morphology. The protein content of isolated EVs was assessed by mass spectrophotometry and the presence of EV markers were evaluated by Western blotting. Finally, the EVs were cocultured with prominent human gut microbiome species to observe their effect on prokaryote growth. Our data shows that Blastocystis ST7 secretes EVs that are similar in morphology to previously characterized EVs from other organisms and that these EVs contain a limited yet unique protein cargo with functions in host-parasite intercellular communication and cell viability. This cargo may be involved in mediating the effects of Blastocystis on its surrounding environment.