Miracle-dz/UniFAR-FTUs huggingface dataset:
PII: S1010-7940(00)00382-1

Objective: To investigate the alterations of structure and mechanical properties of the aortic wall, resulting from impairment of vasa vasorum ̄ow. Methods: Eight healthy Landrace pigs were subjected to interruption of vasa vasorum ̄ow to the upper segment of their descending thoracic aorta. Under sterile conditions, the periaortic tissue was excised and the contiguous intercostal arteries were ligated. Ten sham-operated pigs were used as controls. Fifteen days postoperatively, the animals were sacri®ced and their upper descending thoracic aortas were removed. Histology, and collagen and elastin content determination by image analysis technique were performed. Mechanical analysis of aortic strips was carried out with a uniaxial tension device and stress±strain curves were obtained. Results: In contrast to normal aortic walls of the control group, histology of the avascular aortas revealed severe ischemic necrosis of the outer media along with abnormal straightening of the elastin and collagen ®bers, without signi®cant collagen and elastin content changes. The borderline between the outer ischemic and inner non-ischemic media was sharp, and an outset of dissection was observed at this point. Mechanical analysis showed that at the same level of strain, the ischemic aorta was signi®cantly stiffer at both low (P  0:03) and high strains (P  0:003). Conclusions: Impairment of blood supply to the thoracic aorta leads to abnormal morphology of elastin and collagen ®bers of the outer media, resulting in increased aortic stiffness under a wide range of stresses. In the clinical setting, decreased vasa vasorum ̄ow, reportedly occurring in arterial hypertension, may increase the stiffness of the outer media of the thoracic aorta and produce interlaminar shear stresses, contributing to the development of aortic dissection. q 2000 Elsevier Science B.V. All rights reserved.
high-throughput genome editing toolkit for kinetoplastids

regularly interspaced short palindromic repeats CRISPR-associated gene (Cas9) is set to revolutionize genetic manipulation of the opportunity to develop scalable methods for high-throughput production of mutant phenotypes. Here, we report development of a CRISPR-Cas9 toolkit that allows rapid tagging and gene knockout in diverse kinetoplastid species without requiring the user to perform any DNA cloning. We developed a new protocol for single-guide RNA (sgRNA) delivery using PCR-generated DNA templates which are in vivo by T7 RNA polymerase and an online resource (LeishGEdit.net) for automated primer design. We produced a set of plasmids that allows easy and scalable generation of DNA constructs for transfections in just a few hours. We show how these tools allow knock-in of ﬂuorescent protein tags, modiﬁed biotin ligase BirA*, luciferase, HaloTag and small epitope tags, which can be fused to proteins at the N- or C-terminus, for functional studies of proteins and localization screening. These tools enabled generation of null mutants in a single round of transfection in promastigote form Leishmania major , Leishmania mexicana and bloodstream form Trypanosoma brucei ; deleted genes were undetectable in non-clonal populations, enabling for the ﬁrst time rapid and large-scale knockout screens. for tagging with YFP , linked to a blasticidin-resistance gene, or mCherry , linked to a neomycin-resistance gene. Co-transfection of the two cassettes with in vitro transcribed sgRNA and simultaneous selection with two drugs yielded cells with doubly ﬂuorescent ﬂagella (ﬁgure 2 b ) at a rate of 1 × 10 − 6 per transfected cell. These doubly tagged cells remained motile, indicating that expression of two tagged PF16 alleles was compatible with normal ﬂagellar function.
The Impact Of Investor’s Personality Traits Over Their Investment Decisions With The Mediating Role Of Finanicial Self Efficacy And Emotional Biases And The Moderating Role Of Need For Cognition And The Individual Mood In Pakistan Stock Exchange

The main objective of the study is to examine the impact of investor’s personality traits over their investment decisions with the mediating role of financial self-efficacy and emotional biases and the moderating role of need for cognition and the individual mood in Pakistan stock exchange. In this regard, a survey instrument was designed to collect the data. Data from 500 respondents have been collected thereafter analyzed via IBM SPSS and Smart PLS using descriptive and multiple regression analysis. The results revealed that individual personality traits significantly predict mangers financial self-efficacy and emotional biases, personality traits also significantly relate to financial behavior of managers furthermore all of proposed sub-hypotheses were supported except two path relationships due to insignificant effect size and relevance. The result of mediation paths shows that both manger’s financial self-efficacy and biases mediate the relationship between personality traits and financial decision-making behaviors. In addition to this the moderation effects of need for cognition in the relationship between personality traits and emotional biases which is insignificant. However, need for cognition plays a significant role in strengthening the effects of personality traits in improving the manager’s financial self-efficacy. Also the results of personality traits with respect to short and long term decision making only neuroticism is not supported rest openness and consciousness result showed support towards long and short term decision making. Furthermore, the moderating role of individual mood between financial self-efficacy and decision-making behavior is stronger for manager having high sense of individual mood is supported. Additionally the study implication from theoretical perspective is that it proves that need for cognition of neurotic, investor’s financial self-efficacy and individual mood act as facilitators for doing investment decision and the model used is tend to be considered more useful for research in the associated fields and from practical perspective this research study has implication in the shape of significant influence on investors behavior for making investment decision and has valuable contribution for investment marketers investment advisors and investors, while doing investment in the stock market. General Factor Personality (GFP). A multi method quality research was conducted to find the correlation among the GFP, and supervisor rated task outcome. The conclusion of meta-analysis giving supporting-evidence for
L IPPIA ALBA (V ERBENACEAE ): A NEW TROPICAL AUTOPOLYPLOID COMPLEX ? 1

(cid:129) Premise of the study: Tropical regions have high species diversity, and polyploidization is a major mechanism of speciation in plants. However, few cases of natural polyploidy have been reported in tropical regions. Lippia alba , is a tropical, aromatic shrub with a wide distribution, extensive morphological plasticity, and several chemotypes. The species has long been recognized as a diploid with 2 n = 30 chromosomes. Recently, two variations in chromosome number (2 n = 60; 2 n = 12–60) have been reported, suggesting the occurrence of polyploidy within the species. (cid:129) Methods: Flow cytometry was used to investigate the genome size in 106 accessions from 14 Brazilian States. Conventional and molecular cytogenetic techniques and pollen viability analysis were employed to characterize each chromosome number observed. Key results: The DNA 1C-value varied from 1.17 to 3.45 pg, showing a large variation in genome size. Five distinct chromosome numbers were observed (2 n = 30, 38, 45, 60, 90); three are cytogenetically described here for the ﬁ rst time. The 5S rDNA signals varied proportionally according to each chromosome number, but 45S rDNA sites did not. High rates of meiotic irregularity were observed, mainly in cytotypes with higher chromosome numbers. (cid:129) Conclusions: The data provide new support for the occurrence of a polyploid series in Lippia alba . We provide a hypothesis for how this complex may have arisen. Other cryptic polyploid complexes may remain undiscovered in tropical regions.
OPTH_A_280654 4125..4133

Department of Diabetic Eye Diseases, National Centre of Ophthalmology Named After Acad. Zarifa Aliyeva, Baku, Azerbaijan Purpose of the Study: To study preoperative and postoperative optical coherence tomography features and the outcomes of pars plana vitrectomy (PPV) with internal limiting membrane (ILM) peeling for full-thickness macular holes (MHs) associated with proliferative diabetic retinopathy. Methods: The data from 14 eyes of 11 patients with full-thickness macular holes and active diabetic fibrovascular proliferation (FVP) with/without tractional retinal detachment who underwent pars plana vitrectomy and standard ILM peeling at Zarifa Aliyeva National Ophthalmology Centre in Baku were analysed. Bilateral surgery for diabetic MHs was performed in 27.3% of patients. The minimum follow-up duration was 6 months. Results: All eyes (100%) achieved type 1 macular hole closure, with residual macular subretinal fluid (SRF) present in 13 cases after surgery (92.9%). The SRF resolved gradually without any interventions. The incidence of SRF was 92.9% at 1 month, 85.7% at 3 months, 50% at 6 months, and 14.3% at 9 months (Cochran’s Q test, χ2 (4) =37.44, p<0.001). Visual acuity improved after surgery in 13 cases (92.9%), with a mean difference of 0.75 ±0.71 LogMAR between the preoperative and final values, rs=0.608, 95% BCa CI [0.037–0.969], p=0.021. Conclusion: The standard ILM peeling technique for full-thickness MHs in eyes with active diabetic fibrovascular proliferation can help restore the anatomy and function of the macula in diabetic patients. Close follow-up is important for unilateral cases. Residual SRF in the perifoveal area is detectable by OCT after surgery in patients with macular holes associated with diabetic tractional retinal detachment, and it usually resorbs gradually without any interventions.
Soft Skills Assessment between Diploma and Degree Students During Industrial Training: an Industry’s Observation

Industrial training program is one of the main university-industry linkages that serves the sole purpose of improving the employability of university graduates. Feedbacks from industries on graduate’s performances often become a benchmark for universities to measure their graduates’ competencies. It is therefore essential to obtain industry’s observation on the graduates to ensure that the university’s academic curriculums are appropriately aligned to meet industry requirements. This paper examines the observations of employers with regards to interns’ soft skills at workplace. A sample of 298 respondents participated in this survey. The sample includes 40.6% (n=121) respondents for degree programmes and 59.4% (n=177) respondents for diploma programmes. A total of 28 soft skills attributes were used to examine intern’s performance at the organization and these attributes were classified into seven key skills competency i.e. (1) interpersonal skills, (2) communication skills, (3) intellectual skills, (4) initiative taking, (5) job attitude, (6) personal efficiency, and (7) leadership skills. The results showed that employer’s observation on degree students gave higher mean scores in all of the skill categories. A t-test was executed to determine if the difference in their mean scores was significant. The result showed that there was a significant difference in the job attitude category (p value = 0.04). This directly states that degree students showed better job attitude than diploma student during industrial training in the following contexts: (1) they are more responsible to the task given, (2) they are highly motivated to complete the task given, (3) they are positive in stressful situation, (4) they are punctual and (5) they frequently come to work. Future work from this study will involve determining the possible association between job attitudes of degree students with project management skills such as in the final year project.
TgROP18 Targets IL20RB for Host Defence Related-STAT3 Activation During T. gondii Infection CURRENT STATUS: REVIEW

Background: Toxoplasma gondii is an opportunistic protozoan infecting almost one third of the world’s population. T. gondii rhoptry protein 18 ( Tg ROP18) is a key virulence factor determining parasite’s acute virulence and secreted into host cells during infection. We previously identified the interaction of Tg ROP18 and host cell immune-related receptor protein IL20RB, and observed the activation of STAT3 in human keratinocytes (HaCaT) cells infected by the rop16 knockout RH strain, though Tg ROP16 is regarded responsible for host STAT3 activation during T. gondii invasion. Therefore, we hypothesize Tg ROP18 can activate host STAT3 through binding to IL20RB. Methods: CRISPR-CAS9 technology was used to generate the ROP16 and ROP8 double knockout RH strain, RH-∆rop16∆rop18. SDS-PAGE and western blot was used to detect STAT3 activation in different T. gondii tachyzoites infected, recombinant ROP18 or IL-20 treated HaCaT cells with high endogenous IL20RB expression. FRET and Co-immunoprecipitation (Co-IP) was used to detect the protein-protein interaction. Results: We observed that TgROP18 was involved in a synergic activation of host JAK/STAT3 pathway together with TgROP16 in human HaCaT cells infected with T. gondii or treated with recombinant TgROP18 protein, stimulating host proinflammatory immune responses such as expression of TNF-a. The effect of recombinant ROP18 on STAT3 phosphorylation was presented in a dose-dependent manner. Additionally, TgROP18 was identified to target IL20RB on its extracellular domain. When we treated different cell lines with the recombinant ROP18 , STAT3 phosphorylation could only be observed in the cells with endogenous IL20RB expression, such as HaCaT cells. Conclusions: These findings indicated that TgROP18-IL20RB interaction was involved in STAT3 activation upon T. gondii invasion, which is associated with host cell defence. Bi-molecular fluorescence complementation (BiFc) protein interaction screening used to screen the human interactom of TgROP18, the Fluorescence resonance energy transfer (FRET) was conducted to further confirm this interaction. The results indicated that the FRET efficiency and intermolecular distance of CFP-TgROP18 and IL20RB-YFP (in pCFPN1-ROP18/ pYFPC1-IL20RB co-transfection group ) was not significantly different from which of CFP-YFP (in the positive control group); but was significantly
Pipeline-Invariant Representation Learning for Neuroimaging

Deep learning has been widely applied in neuroimaging, including predicting brain-phenotype relationships from magnetic resonance imaging (MRI) volumes. MRI data usually requires extensive preprocessing prior to modeling, but variation introduced by different MRI preprocessing pipelines may lead to different scientific findings, even when using the identical data. Motivated by the data-centric perspective, we first evaluate how preprocessing pipeline selection can impact the downstream performance of a supervised learning model. We next propose two pipeline-invariant representation learning methodologies, MPSL and PXL, to improve robustness in classification performance and to capture similar neural network representations. Using 2000 human subjects from the UK Biobank dataset, we demonstrate that proposed models present unique and shared advantages, in particular that MPSL can be used to improve out-of-sample generalization to new pipelines, while PXL can be used to improve within-sample prediction performance. Both MPSL and PXL can learn more similar between-pipeline representations. These results suggest that our proposed models can be applied to mitigate pipeline-related biases, and to improve prediction robustness in brain-phenotype modeling.
Homologous self-assembled superlattices: What causes their periodic polarity switching? Review, model, and experimental test

Quantum semiconductor structures are commonly achieved by bandgap engineering that relies on the ability to switch from one semiconductor to another during their growth. Growth of a superlattice is typically demanding technologically. In contrast, accumulated evidence points to a tendency among a certain class of multiple-cation binary oxides to self-assemble spontaneously as superlattice structures. This class has been dubbed the homologous superlattices. For a famous example, when a mixture of indium and zinc is oxidized, the phases of In-O and ZnO separate in an orderly periodic manner, along the ZnO polar axis, with polarity inversion taking place between consecutive ZnO sections. As we review here, the same structure has been observed when the indium was replaced with other metals, and perhaps even in ZnO alone. This peculiar self-assembled structure has been attracting research over the past decade. The purpose of this study is to gain understanding of the physics underlying the formation of this unique structure. Here, we first provide an extensive review of the accumulated literature on these spontaneously-formed structures and then propose an explanation for the long-standing mystery of this intriguing self-assembly in the form of an electrostatic growth phenomenon and test the proposed model on experimental data.
Extra DoF of Near-Field Holographic MIMO Communications Leveraging Evanescent Waves

In this letter, we consider transceivers with spatially-constrained antenna apertures of rectangular symmetry, and aim to improve of spatial degrees of freedom (DoF) and channel capacity leveraging evanescent waves for information transmission in near-field scenarios based on the Fourier plane-wave series expansion. The treatment is limited to an isotropic scattering environment but can be extended to the non-isotropic case through the linear-system theoretic interpretation of plane-wave propagation. Numerical results show that evanescent waves have the significant potential to provide additional DoF and capacity in the reactive near-field region.
Exploring Semantic Attributes from A Foundation Model for Federated Learning of Disjoint Label Spaces

Conventional centralised deep learning paradigms are not feasible when data from different sources cannot be shared due to data privacy or transmission limitation. To resolve this problem, federated learning has been introduced to transfer knowledge across multiple sources (clients) with non-shared data while optimising a globally generalised central model (server). Existing federated learning paradigms mostly focus on transferring holistic high-level knowledge (such as class) across models, which are closely related to specific objects of interest so may suffer from inverse attack. In contrast, in this work, we consider transferring mid-level semantic knowledge (such as attribute) which is not sensitive to specific objects of interest and therefore is more privacy-preserving and scalable. To this end, we formulate a new Federated Zero-Shot Learning (FZSL) paradigm to learn mid-level semantic knowledge at multiple local clients with non-shared local data and cumulatively aggregate a globally generalised central model for deployment. To improve model discriminative ability, we propose to explore semantic knowledge augmentation from external knowledge for enriching the mid-level semantic space in FZSL. Extensive experiments on five zeroshot learning benchmark datasets validate the effectiveness of our approach for optimising a generalisable federated learning model with mid-level semantic knowledge transfer.
How to Teach: Learning Data-Free Knowledge Distillation from Curriculum

—Data-free knowledge distillation (DFKD) aims at training lightweight student networks from teacher networks without training data. Existing approaches mainly follow the paradigm of generating informative samples and progressively updating student models by targeting data priors, boundary samples or memory samples. However, it is difﬁcult for the previous DFKD methods to dynamically adjust the generation strategy at different training stages, which in turn makes it difﬁcult to achieve efﬁcient and stable training. In this paper, we explore how to teach students the model from a curriculum learning (CL) perspective and propose a new approach, namely ”CuDFKD”, i.e., ”Data-Free Knowledge Distillation with Curriculum”. It gradually learns from easy samples to difﬁcult samples, which is similar to the way humans learn. In addition, we provide a theoretical analysis of the majorization minimization (MM) algorithm and explain the convergence of CuDFKD. Experiments conducted on benchmark datasets show that with a simple course design strategy, CuDFKD achieves the best performance over state-of-the-art DFKD methods and different benchmarks, such as 95.28% top1 accuracy of the ResNet18 model on CIFAR10, which is better than training from scratch with data. The training is fast, reaching the highest accuracy of 90% within 30 epochs, and the variance during training is stable. Also in this paper, the applicability of CuDFKD is also analyzed and discussed.
Industrial requirements for supporting AI-enhanced model-driven engineering

There is an increasing interest in research on the combination of AI techniques and methods with MDE. However, there is a gap between AI and MDE practices, as well as between researchers and practitioners. This paper tackles this gap by reporting on industrial requirements in this field. In the AIDOaRt research project, practitioners and researchers collaborate on AI-augmented automation supporting modeling, coding, testing, monitoring, and continuous development in cyber-physical systems. The project specifically lies at the intersection of industry and academia collaboration with several industrial use cases. Through a process of elicitation and refinement, 78 high-level requirements were defined, and generalized into 30 generic requirements by the AIDOaRt partners. The main contribution of this paper is the set of generic requirements from the project for enhancing the development of cyber-physical systems with artificial intelligence, DevOps, and model-driven engineering, identifying the hot spots of industry needs in the interactions of MDE and AI. Future work will refine, implement and evaluate solutions toward these requirements in industry contexts.
Localized creation of yellow single photon emitting carbon complexes in hexagonal boron nitride

Single photon emitters in solid-state crystals have received a lot of attention as building blocks for numerous quantum technology applications. Fluorescent defects in hexagonal boron nitride (hBN) stand out due to their high luminosity and robust operation at room temperature. The fabrication of identical emitters at pre-defined sites is still challenging, which hampers the integration of these defects in optical systems and electro-optical devices. Here, we demonstrate the localized fabrication of hBN emitter arrays by electron beam irradiation using a standard scanning electron microscope with deep sub-micron lateral precision. The emitters are created with a high yield and a reproducible spectrum peaking at 575 nm. Our measurements of optically detected magnetic resonance have not revealed any addressable spin states. Using density functional theory, we attribute the experimentally observed emission lines to carbon-related defects, which are activated by the electron beam. Our scalable approach provides a promising pathway for fabricating room temperature single photon emitters in integrated quantum devices.
Darcy's problem coupled with the heat equation under singular forcing: analysis and discretization

We study the existence of solutions for Darcy’s problem coupled with the heat equation under singular forcing; the right-hand side of the heat equation corresponds to a Dirac measure. The studied model allows thermal diﬀusion and viscosity depending on the temperature. We propose a ﬁnite element solution technique and analyze its convergence properties. In the case that the thermal diﬀusion is constant, we propose an a posteriori error estimator and investigate reliability and eﬃciency properties. We illustrate the theory with numerical examples.