Miracle-dz/UniFAR-FTUs huggingface dataset:
‘You need to be flexible normally, and here, even more flexible’: teaching academics’ experiences and perceptions of Covid-19 disruptions to teaching, learning, and assessment

ABSTRACT Alongside unprecedented shifts in health care, and widespread lockdowns and stay-at-home orders, the Covid-19 pandemic brought an almost immediate shift towards digitally supported remote delivery in higher education. This paper explores the experiences and perceptions of 15 teaching academics from five universities in Victoria, Australia during this time. Semi-structured interviews were conducted with academics after they had been delivering teaching, learning and assessment remotely for a six-month period. The analysis showed that while the remote delivery environment enhanced many aspects of teaching and learning, including agile and adaptable academic skill-sets, there were challenges. The academics’ sophisticated teaching skills and experience, that were intuitively relied upon in the face-to-face setting, did not always translate to the online environment. In particular, this was noticed in terms of the relational approach to teaching and learning, including relationships, rapport, and connectedness within classes, and the absence of social formative assessment cues to evaluate learners’ understandings. Students were not asking questions in class and required additional support from academics, which subsequently increased already overburdened workloads. After considering the findings of our work and others, we provide recommendations to support high quality teaching and learning in digitally supported remote delivery.
Theoretical Development of Third-Order Susceptibility as Related to Coherent Antistokes Raman Spectroscopy (CARS).

Abstract : The basic theory for coherent anti-stokes Raman spectroscopy has been developed by two methods: a classical approach and a quantum mechanical development. Standard methods of perturbation theory, Maxwell's equation, harmonic oscillator approximation, and density matrix theory are applied to the third-order nonlinear effect of generating anti-Stokes photons from the mixing of two intense laser beams. Each mathematical step has been explicitly included in the derivations comparisons between the expressions obtained here and those published in the literature are made. Where possible, clarification with respect to differences of factors of '2' or '3' which appear in various references have been included.
Identification and misidentifications in the genus Inurous (Lepidoptera: Geometridae) with description of a new species

The article considers the history of descriptions and misidentifications in the genus Inurois Butler, 1879 (Lepidoptera: Geometridae). A catalogue of species of the genus with notes, a key to species from I. punctigera and I. tenuis species-group by the wing pattern and by the male genitalia are given. Based on morphological and genetic data a new species, Inurois pseudopunctigera sp. n. , is described from the continental East Asia.
Focal points and sup-norms of eigenfunctions

If $(M,g)$ is a compact real analytic Riemannian manifold, we give a necessary and sufficient condition for there to be a sequence of quasimodes of order $o(\lambda)$ saturating sup-norm estimates. In particular, it gives optimal conditions for existence of eigenfunctions satisfying maximal sup norm bounds. The condition is that there exists a self-focal point $x_0\in M$ for the geodesic flow at which the associated Perron-Frobenius operator $U_{x_0}: L^2(S_{x_0}^*M) \to L^2(S_{x_0}^*M)$ has a nontrivial invariant $L^2$ function. The proof is based on an explict Duistermaat-Guillemin-Safarov pre-trace formula and von Neumann's ergodic theorem.
Numerical Stability in Linear Programming and Semidefinite Programming

We study numerical stability for interior-point methods applied to Linear Programming, LP, and Semidefinite Programming, SDP. We analyze the difficulties inherent in current methods and present robust algorithms. We start with the error bound analysis of the search directions for the normal equation approach for LP. Our error analysis explains the surprising fact that the ill-conditioning is not a significant problem for the normal equation system. We also explain why most of the popular LP solvers have a default stop tolerance of only 10−8 when the machine precision on a 32-bit computer is approximately 10−16. We then propose a simple alternative approach for the normal equation based interiorpoint method. This approach has better numerical stability than the normal equation based method. Although, our approach is not competitive in terms of CPU time for the NETLIB problem set, we do obtain higher accuracy. In addition, we obtain significantly smaller CPU times compared to the normal equation based direct solver, when we solve well-conditioned, huge, and sparse problems by using our iterative based linear solver. Additional techniques discussed are: crossover; purification step; and no backtracking. Finally, we present an algorithm to construct SDP problem instances with prescribed strict complementarity gaps. We then introduce two measures of strict complementarity gaps. We empirically show that: (i) these measures can be evaluated accurately; (ii) the size of the strict complementarity gaps correlate well with the number of iteration for the SDPT3 solver, as well as with the local asymptotic convergence rate; and (iii) large strict complementarity gaps, coupled with the failure of Slater’s condition, correlate well with loss of accuracy in the solutions. In addition, the numerical tests show that there is no correlation between the strict complementarity gaps and the geometrical measure used in [31], or with Renegar’s condition number.
Quantum Biochemistry Screening and In Vitro Evaluation of Leishmania Metalloproteinase Inhibitors

Leishmanolysin, also known as major promastigote protease (PSP) or gp63, is the most abundant surface glycoprotein of Leishmania spp. , and has been extensively studied and recognized as the main parasite virulence factor. Characterized as a metalloprotease, gp63 can be powerfully inactivated in the presence of a metal chelator. In this study, we first used the structural parameters of a 7-hydroxycoumarin derivative, L1 compound, to evaluate the theoretical–computational experiments against gp63, comparing it with an available metal chelator already described. The methodology followed was (i) analysis of the three-dimensional structure of gp63 as well as its active site, and searching the literature and molecular databases for possible inhibitors; (ii) molecular docking simulations and investigation of the interactions in the generated protein–ligand complexes; and (iii) the individual energy of the gp63 amino acids that interacted most with the ligands of interest was quantified by ab initio calculations using Molecular Fraction with Conjugated Caps (MFCC). MFCC still allowed the final quantum balance calculations of the protein interaction to be obtained with each inhibitor candidate binder. L1 obtained the best energy quantum balance result with −2 eV, followed by DETC (−1.4 eV), doxycycline (−1.3 eV), and 4-terpineol (−0.6 eV), and showed evidence of covalent binding in the enzyme active site. In vitro experiments confirmed L1 as highly effective against L. amazonensis parasites. The compound also exhibited a low cytotoxicity profile against mammalian RAW and 3T3 cells lines, presenting a selective index of 149.19 and 380.64 µM, respectively. L1 induced promastigote forms’ death by necrosis and the ultrastructural analysis revealed disruption in membrane integrity. Furthermore, leakage of the contents and destruction of the parasite were confirmed by Spectroscopy Dispersion analysis. These results together suggested L1 has a potential effect against L. amazonensis, the etiologic agent of diffuse leishmaniasis, and the only one that currently does not have a satisfactory treatment.
Using Machine Learning to Predict Freight Vehicles’ Demand for Loading Zones in Urban Environments

This paper studies demand for public loading zones in urban environments and seeks to develop a machine learning algorithm to predict their demand. Understanding and predicting demand for public loading zones can: (i) support better management of the loading zones and (ii) provide better pre-advice so that transport operators can plan their routes in an optimal way. The methods used are linear regression analysis and neural networks. Six months of parking data from the city of Vic in Spain are used to calibrate and test the models, where the parking data is transformed into a time-series format with forecasting targets. For each loading zone, a different model is calibrated to test which model has the best performance for the loading zone’s particular demand pattern. To evaluate each model’s performance, both root mean square error and mean absolute error are computed. The results show that, for different loading zone demand patterns, different models are better suited. As the prediction horizon increases, predicting further into the future, the neural network approaches start to give better predictions than linear models.
The role of miRNAs in metabolic diseases.

Metabolic diseases such as obesity, diabetes, dyslipidemia, and insulin resistance are characterized by glucose and lipid metabolism alterations and represent a global health problem. Many studies have established the crucial role of micro-ribonucleic acids (miRNAs) in controlling metabolic processes in various tissues. miRNAs are single-stranded, highly conserved non-coding RNAs containing 20-24 oligonucleotides that are expressed in a tissue-specific manner. miRNAs mainly interact through base pairing with 3' untranslated regions of target gene mRNAs to promote inhibition of their translation. miRNAs regulate the expression of as many as 30% of the human genes and have a role in crucial physiological processes such as human growth and development, cell proliferation, apoptosis, and metabolism. The number of miRNA molecules with a confirmed role in the pathogenesis of metabolic diseases is quickly expanding due to the availability of high-throughput methodologies for their identification. In this review, we present recent findings regarding the role of miRNAs as endocrine signaling molecules involved in the regulation of insulin production and fat metabolism. We discuss the potential of extracellular miRNAs present in biological fluids miRNAs as biomarkers for the prediction of diabetes and MetS. We also give an updated overview of therapeutic interventions based on antisense oligonucleotides and the CRISPR/Cas9 editing platform for manipulations of levels of miRNAs involved in metabolic disorders.
FROM ENERGY SECURITY TO SECURITY OF ENERGY SERVICES: THE ROLE OF GENDERED INNOVATIONS IN LIVING LABS

Energy security remains a concern in Sub-Saharan Africa. The conceptualisation of energy security at the urban household level has shifted from the security of energy supply to the security of energy services, which is focused more on the demand side. Women and young girls are affected the most by insecure energy services. However, energy policy discourses often fail to focus on the security of energy services or to recognise gender roles in the provision of energy services at the household level. It is therefore imperative to develop innovative and gender-sensitive energy services solutions with a new paradigm of participatory solution design, such as living labs. We assessed living labs and the energy security landscape in poor urban environments through a systematic literature review, and proposed a framework for demonstrating how living labs could be used as a lever to promote the security of energy services. The security of energy services in poor urban households could be improved by harnessing the different innovative strengths of the respective genders. Living labs provide an ideal space for co-generating, co-designing, and co-learning to produce tailored energy services solutions. There is a need for a collaborative effort in resourcing researchers to undertake practical investigations of interactive multi-stakeholder platforms with those who are intended to benefit from the policy to increase its impact and to bridge the science-policy divide. Keywords energy security, energy services, gendered innovations, living labs, poor urban environments
E cient XPath Axis Evaluation for DOM Data Structures

In this article we propose algorithms for implementing the axes for element nodes in XPath given a DOM-like representation of the document. Each algorithm assumes an input list that is sorted in document order and duplicate-free and returns a sorted and duplicate-free list of the result of following a certain axis from the nodes in the input list. The time complexity of all presented algorithms is at most O(l +m) where l is the size of the input list andm the size of the output list. This improves upon results in [4] where also algorithms with linear time complexity are presented, but these are linear in the size of the entire document whereas our algorithms are linear in the size of the intermediate results which are often much smaller.
Evaluating Fidelity to the National Extension Dining with Diabetes Program: Challenges and Opportunities

The objective of this study was to evaluate fidelity to the Dining with Diabetes (DWD) program. Data were gathered cross-sectionally in 2019 using class profile forms (i.e., checklists) containing items reflecting the core components of DWD: delivery personnel, curriculum, hands-on cooking, and goal setting. Fidelity was calculated as the proportion of core components completed as intended. Educators (N = 9) completed class profile forms for 10 complete DWD programs (i.e., all four classes). Fidelity to components of completed DWD programs and individual DWD classes was high (over 70% in each category). Overall, fidelity was high, and adaptations reported likely did not detract from effectiveness (e.g., a 2-hour class lasted 2.5 hours). However, the response rate was low and may not reflect those who deliver with lower fidelity. Assessing fidelity should be incorporated as a standard part of community-based diabetes management program evaluation; these data can inform changes to programs to make them more effective in the “real world. ”
Calculations on Unsteady Type IV Interaction at Mach 8

Abstract : The viscous unsteady flow due to a Type IV shock-on-shock interaction at Mach 8 is examined with an implicit flux-split scheme. A sequence of grids is utilized to perform a grid resolution study and the results are compared with experimental values. The formulation is finite-volume with higher order accuracy obtained with the MUSCL approach in conjunction with a limiter to prevent oscillations. Viscous terms are centrally differenced. The flow exhibits a limit cycle in aggregate quantities which can be related to the details for the flow structure. The supersonic jet bounded by the two shear layers displays large scale movement at a dominant frequency of 32 kHz. This is accompanied by variation in the angle between the terminating jet bow shock and the surface tangent. Unsteady separation regions are observed both above and below the point of jet impingement. Hypersonic, High-speed, Type IV Interaction Flux- splitting, Upwinding, Implicit, Unsteady
Measuring teachers’ attitudes and intentions towards inclusion: Portuguese validation of Attitudes to Inclusion Scale (AIS) and Intention to Teach in Inclusive Classroom Scale (ITICS)

ABSTRACT Successful implementation of inclusive practices depends on the extent of which school educators believe in this and are well prepared to implement include all learners. It is therefore relevant to study the variables that influence pedagogical practices of educators to teach in inclusive classrooms, namely attitudes and intentions regarding inclusion. This study was undertaken to test the psychometric validation of Attitudes Towards Inclusion Scale (AIS) and the Intention to Teach in an Inclusive Classroom Scale (ITICS) for Portugal. The sample comprised 171 teachers (86% female) in primary and secondary schools. The results confirmed the two-factor structure of the original versions of the AIS (beliefs and feelings) and ITICS (curriculum changes and consultation). Teachers with inclusion training had more positive attitudes and higher level of intentions than their colleagues without training in this area. We analysed the correlations between attitudes, intentions, and perceived efficacy relative to inclusive practices as an indicator of concurrent validity and found adequate indicators of internal consistency (ω = 0.70 to 0.94) and convergent and discriminant validity. Our analysis suggests that adding new items to ITICS can further enhance the psychometric properties of the scale. We discuss implications of our research for researchers, educators and policy makers.
Reconstructing a Deblurred 3D Structure in a Turbid Medium from a Single Blurred 2D Image—For Near-Infrared Transillumination Imaging of a Human Body

To provide another modality for three-dimensional (3D) medical imaging, new techniques were developed to reconstruct a 3D structure in a turbid medium from a single blurred 2D image obtained using near-infrared transillumination imaging. One technique uses 1D information of a curvilinear absorber, or the intensity profile across the absorber image. Profiles in different conditions are calculated by convolution with the depth-dependent point spread function (PSF) of the transillumination image. In databanks, profiles are stored as lookup tables to connect the contrast and spread of the profile to the absorber depth. One-to-one correspondence from the contrast and spread to the absorber depth and thickness were newly found. Another technique uses 2D information of the transillumination image of a volumetric absorber. A blurred 2D image is deconvolved with the depth-dependent PSF, thereby producing many images with points of focus on different parts. The depth of the image part can be estimated by searching the deconvolved images for the image part in the best focus. To suppress difficulties of high-spatial-frequency noise, we applied a noise-robust focus stacking method. Experimentation verified the feasibility of the proposed techniques, and suggested their applicability to curvilinear and volumetric absorbers such as blood vessel networks and cancerous lesions in tissues.
Estimating chorusing activity by quantifying total acoustic energy

Passive acoustics provides a powerful method for localizing vocalizing animals and estimating species abundance. A passive acoustics method previously used to census dense populations of flying bats is applied here to estimate chorusing activity of male bullfrogs vocalizing against anthropogenic noise. There are significant links between manual counts of the numbers of advertisement call notes and automatically detected notes and two measures of acoustic energy. These data provide a foundation for the use of acoustic energy measures to census vocal activity in different habitats.
Therapeutic Effects and Metabolic Spectrum of Traditional Chinese Medicine Hengqing II Prescription on Alzheimer's Disease

Alzheimer's disease (AD) seriously damages elders' social and daily abilities around the world. Traditional Chinese medicine (TCM), a rich drug resource bank, could help research AD. In order to explore the role of TCM in AD treatment, 86 AD patients were recruited from the hospital, then treated with Hengqing II prescription and donepezil hydrochloride. The cognitive and serum lipid levels were investigated before and after treatment. The patient's urine was collected after three months of treatment. Metabolites in the urine samples were extracted with methanol and detected on the UHPLC-MS platform. Results proved that Hengqing II can improve cognitive levels and reduce the levels of Hcy, D-D, FIB, Apo B, TC, and LDL-C compared with donepezil hydrochloride (P < 0.05). The results of multivariate statistical analysis revealed that the metabolism of HQII was significantly different compared with Control groups. A total of 66 differential metabolites were found in this comparison (50 were down-regulated and 16 were up-regulated). Four amino acid pathways and one linoleic acid pathway were found through these metabolites. After receiver operating characteristic analysis, it was suggested that palmitic acid, palmitoleic acid, linoleic acid, oleic acid, SAH, and methionine can be used as biomarkers for treating AD, while the effects of daidzein, genistein, and naringenin on the treatment of AD need to be further studied.
Relationship between Fungal Communities and Volatile Flavor Components during the Traditional Chinese Fermentation of Capsicum annuum L. Var. Dactylus M

Microbial diversity and dynamic changes play an important role in the production of fermented peppers. In this study, the relationship between fungal communities and the volatile flavor compounds of traditional Chinese fermented peppers was investigated by high-throughput sequencing technology. The results showed that Hanseniaspora was a dominant fungus during the whole fermentation course and accounted for 82.22% of the fungal community on average (ranging from 50.44% to 98.15%). Bidirectional orthogonal partial least squares (O2PLS) analysis between fungal community and volatile flavor compounds showed that Pichia, Hanseniaspora, Cryptococcus, Debarvomvces, and Trichosporon were closely correlated with the concentrations of the volatile flavor components such as α-terpineol, trans-3-tetradecene, 4-methylpentyl 3-methylbutanoate, and 11 other volatile flavor compounds. This study elucidated the dynamics of fungal communities and volatile flavor compounds during pepper fermentation and the correlation between them. Our analysis of the relationships between fungal communities and volatile flavor compounds advanced our understanding of the formation mechanism of volatile flavor compounds in fermented peppers.
Hyperkalemia in Chronic Kidney Disease: Links, Risks and Management

Abstract Hyperkalemia is a common clinical problem with potentially fatal consequences. The prevalence of hyperkalemia is increasing, partially due to wide-scale utilization of prognostically beneficial medications that inhibit the renin-angiotensin-aldosterone-system (RAASi). Chronic kidney disease (CKD) is one of the multitude of risk factors for and associations with hyperkalemia. Reductions in urinary potassium excretion that occur in CKD can lead to an inability to maintain potassium homeostasis. In CKD patients, there are a variety of strategies to tackle acute and chronic hyperkalemia, including protecting myocardium from arrhythmias, shifting potassium into cells, increasing potassium excretion from the body, addressing dietary intake and treating associated conditions, which may exacerbate problems such as metabolic acidosis. The evidence base is variable but has recently been supplemented with the discovery of novel oral potassium binders, which have shown promise and efficacy in studies. Their use is likely to become widespread and offers another tool to the clinician treating hyperkalemia. Our review article provides an overview of hyperkalemia in CKD patients, including an exploration of relevant guidelines and nuances around management.