Miracle-dz/UniFAR-FTUs huggingface dataset:
A Comprehensive Comparison in the Heat Transfer Performance of Pure Water-Based and Liquid Gallium-Based Hybrid Nanofluid Flows through a Minichannel, Using Two-Phase Eulerian–Eulerian Model

Abstract An in-house Fortran-based two-phase Eulerian–Eulerian solver is used to numerically study water-based and liquid metal gallium-based alumina-copper hybrid nanofluid forced convection flow through a wide rectangular mini channel in the laminar regime. The governing equations of liquid and solid phases are solved using sixth-order compact finite difference method. A parametric study involving Reynolds number, particle concentration and mixture ratios has been reported. From the study it is found that pure liquid gallium has 43.5% greater heat transfer enhancement compared to pure water. The ‘heat transfer performance parameter’ is used to analyze the heat transfer characteristics of all the nanofluids considered. Addition of copper nanoparticles into base fluid improves the heat transfer performance of liquid gallium by 10.73% and pure water by 46.9%, at 1% particle concentration and a Reynolds number of 100. A significant change in heat transfer performance is found with a change in the Reynolds number and particle concentration for water-based hybrid nanofluids compared to liquid gallium-based hybrid nanofluids. A Nusselt number correlation is proposed for alumina-copper water-based hybrid nanofluids. Present results are validated with numerical and experimental results available in the literature.
Selective Detection of Legionella pneumophila Serogroup 1 and 5 with a Digital Photocorrosion Biosensor Using Antimicrobial Peptide-Antibody Sandwich Strategy

Rapid detection of Legionella pneumophila (L. pneumophila) is important for monitoring the presence of these bacteria in water sources and preventing the transmission of the Legionnaires’ disease. We report improved biosensing of L. pneumophila with a digital photocorrosion (DIP) biosensor functionalized with an innovative structure of cysteine-modified warnericin antimicrobial peptides for capturing bacteria that are subsequently decorated with anti-L. pneumophila polyclonal antibodies (pAbs). The application of peptides for the operation of a biosensing device was enabled by the higher bacterial-capture efficiency of peptides compared to other traditional ligands, such as those based on antibodies or aptamers. At the same time, the significantly stronger affinity of pAbs decorating the L. pneumophila serogroup-1 (SG-1) compared to serogroup-5 (SG-5) allowed for the selective detection of L. pneumophila SG-1 at 50 CFU/mL. The results suggest that the attractive sensitivity of the investigated sandwich method is related to the flow of an extra electric charge between the pAb and a charge-sensing DIP biosensor. The method has the potential to offer highly specific and sensitive detection of L. pneumophila as well as other pathogenic bacteria and viruses.
Monitoring and designing predictable time-triggered software architecture for real-time embedded applications

Modern industrial applications often employ embedded processors – programmed with dedicated software – to perform some tasks in real time. In many such designs, the software running on the processor is developed according to rigorous industry standards. Even with such state-of-the art designs, problems can occur “in the field” due to unforeseen circumstances – such as electromagnetic interference – that could undermine the underlying assumptions made at design time. It therefore remains essential to monitor the system at run-time, in order to detect any deviations from the required system behaviour. However, monitoring embedded systems is a far from trivial process, not least because such systems are becoming increasingly complex. Also, variations in task execution times are likely to occur, and can have negative impacts on system predictability particularly in the presence of jitter-sensitive tasks. In addition, it is rarely possible (or cost-effective) to add precise monitoring capabilities to a system which has not been developed from the outset with such requirements in mind. The work described in this thesis seeks to address these issues by introducing and evaluating a “predictable time-triggered” (pTT) framework that combines: a pTT scheduling algorithm and a hardware-based pTT monitor. A novel jitter-reduction technique in a pTT algorithm allows jitter-sensitive tasks to be executed in constant periods without the need to re-compute the entire task schedule. The studies reported in this thesis show that, with existing jitter-reduction methodologies, a pTT algorithm can provide extremely predictable temporal behaviour. The studies also show that the novel low-cost pTT monitor – that operates by monitoring fluctuations in the processor power consumption through a simple hardware interface – adds an additional level of safety by allowing runtime errors to be detected at a time resolution of microseconds. These findings provide sufficient evidence that the pTT framework could be an appropriate model for safety-critical system design.
PREDIKCIJA POPULARNOSTI OBJAVA NA SAJTU 9GAG KORIŠĆENJEM MULTIMODALNIH PODATAKA SA FOKUSOM NA TEKSTUALNE PODATKE

Predikcija popularnosti objava na sajtu 9gag bi mogla da bude od značaja za prepoznavanje i analizu faktora koji su bitni kod popularnosti sadržaja na društvenim mrežama. Ova istraživanja mogu biti korisna pre svega za oblast marketinga. U ovom radu predstavljena je arhitektura sistema za predikciju popu­larnosti objava. Fokus je bio na analizi onih elemenata objava koje se tiču teksta objave (komentara, naslova,.). Isprobana su dva načina, od prvi predstavlja testiranje više različitih klasifikatora, a drugi stekovanje klasifi­katora. Na kraju su predstavljeni i analizirani rezultati, a predložena su i dalja unapređenja sistema.
INDIGENOUS CONSERVATION OF CROP GENETIC RESOURCES IN THE UPPER EAST REGION OF GHANA

Traditional farmers are aware of crop genetic erosion and use various indigenous conservation methods in their farming systems to protect and sustain crop production. The objective of the study was to assess the indigenous conservation methods and practices for some selected crop genetic resources (CGRs) in the Kassena-Nankana and Bolgatanga areas of Ghana. Data was gathered with the aid of a questionnaire, secondary data and first-hand observations. The primary subject for the study were farmers. The study communities were selected by convenient sampling and based on key informants’ information. Two hundred farmers from ten communities each from Kassena-Nankana and Bolgatanga municipalities served as subjects in this study. The results revealed that, farmer’s choice of CGRs for cultivation was based on food preference, marketability, and early maturing crops among others. Maize, millet, rice and groundnut were the most cultivated crops in the two study areas making up 15-25%. In both areas, 52-65% of the farmers were males and 35-48% females. Use of preserved seeds as planting materials was practiced by 41-49% of farmers, 21-26% purchased their planting materials and 21-23% practiced a combination of the two. The indigenous conservation practices were pot preservation, bunch hanging, bottle preservation, sack preservation and local silos/barns. Methods employed to achieve CGRs conservation included the use of ashes from burnt plant residue and plant parts and plant extracts. The findings of the study revealed that some indigenous practices are moderately practiced by the farmers in the surveyed areas to ensure CGRs conservation and food security. Keywords: Conservation practices, Crop, Genetic resources, Farmers, Indigenous, Ghana
A comparative study of time-based maintenance and condition-based maintenance for optimal choice of maintenance policy

Abstract Cost-effective maintenance of infrastructure systems within an acceptable level of safety and performance is the major concern of managing agencies. Recent maintenance approaches have offered two distinct maintenance policies: time-based maintenance (TBM) and condition-based maintenance (CBM). This paper compares the two policies under different cost environments for stochastically deteriorating infrastructures. The performance of TBM and CBM is evaluated from the viewpoint of condition transition and life cycle cost. We found the optimal maintenance solutions for TBM and CBM using dynamic programming and performed a simulation study. The simulation study showed that TBM causes some unexpected deterioration that leads to high cost, while CBM maintains a certain level of condition steadily under consistent inspection, which enables steady spending at the management level. The life cycle cost under CBM is relatively symmetric and has a more concentrated distribution than TBM, which has a large number of outliers from unexpected deteriorations. Finally, we evaluated the life cycle cost with a change in the inspection–repair cost ratio to find the most appropriate cost environment for each maintenance policy. While CBM needs periodic inspections, it still has more advantages than TBM when the inspection cost is relatively low.
Biomolecule-Mediated Therapeutics of the Dentin–Pulp Complex: A Systematic Review

The aim of this systematic review was to evaluate the application of potential therapeutic signaling molecules on complete dentin-pulp complex and pulp tissue regeneration in orthotopic and ectopic animal studies. A search strategy was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement in the MEDLINE/PubMed database. Animal studies evaluating the application of signaling molecules to pulpectomized teeth for pulp tissue or dentin-pulp complex regeneration were included. From 2530 identified records, 18 fulfilled the eligibility criteria and were subjected to detailed qualitative analysis. Among the applied molecules, basic fibroblast growth factor, vascular endothelial growth factor, bone morphogenetic factor-7, nerve growth factor, and platelet-derived growth factor were the most frequently studied. The clinical, radiographical and histological outcome measures included healing of periapical lesions, root development, and apical closure, cellular recolonization of the pulp space, ingrowth of pulp-like connective tissue (vascularization and innervation), mineralized dentin-like tissue formation along the internal dentin walls, and odontoblast-like cells in contact with the internal dentin walls. The results indicate that signaling molecules play an important role in dentin/pulp regeneration. However, further studies are needed to determine a more specific subset combination of molecules to achieve greater efficiency towards the desired tissue engineering applications.
PRIMENA TEHNOLOGIJA RAČUNARSTVA VISOKIH PERFORMANSI U ISTRAŽIVANJU BEZBEDNOSTI SAOBRAĆAJA

Ovaj rad opisuje postupak primene tehnologija računarstva visokih performansi u analizi faktora koji utiču na stepen ozbiljnosti saobraćajnih nesreća. U radu su navedeni upotrebljene tehnologije i algoritmi mašinskog učenja, skupovi podataka sa kojima je rađeno i primenjena metodologija uz prikazane rezultate istraživanja. Rešenja su implementirana uz pomoć programskog jezika R i sistema za distribuiranu obradu podataka Apache Spark.
Comparisons of Dementia Knowledge and Attitudes among the Youth and Older Adults: Insights from the Construal Level Theory Perspective

Based on Construal Level Theory (CLT), the youth and older adults have different psychological distances towards dementia that may lead to different dementia knowledge and attitudes. A cross-sectional survey among 239 youth and 62 older adults using a two-step sampling approach in Macao aimed to examine the hypothesis. Results showed older adults had a higher score of dementia knowledge (F(1,299) = 45.692, p <0.001) but a lower score of dementia attitudes (F(1,299) = 161.887, p <0.001) compared to the youth. Age group explained the majority of the variances in the hierarchical multiple regressions for dementia knowledge (R2 = 0.178, F = 9.059, p < 0.001) and for dementia attitudes (R2 = 0.399, F = 24.233, p < 0.001), which are β = 0.47 and −0.56, respectively. Thus, the hypothesis was supported and revealed an interesting pattern of dementia knowledge and attitudes among the youth and older adults. From the CLT perspective, the study implies that reducing and bridging the psychological distance of dementia would probably be an effective strategy to increase dementia awareness among young people, and intergenerational programs may be a good option to increase community acceptance and support for people with dementia.
Factors Affecting Young Adults’ Decision Making to Undergo COVID-19 Vaccination: A Patient Preference Study

Young adults are a substantial driver of lagging vaccination against COVID-19 worldwide. We aimed to understand what vaccine or vaccination environment attributes may affect young adults’ vaccine inclination. We contacted a convenience sample of 1415 students to recruit a minimum of 150 individuals for a web-based discrete choice experiment. The respondents were asked to choose one of two hypothetical vaccines, defined by six attributes—vaccine efficacy, risk of mild side effects, protection duration, administration route, recommender, and travel time to the vaccination site. Individual preferences were calculated with the Markov chain Monte Carlo hierarchical Bayes estimation. A total of 445 individuals (mean age 24.4 years, 272 (61.1%) women) completed the survey between 22 March and 3 May 2021. Vaccine protection duration (28.3 (95% CI, 27.0–29.6)) and vaccine efficacy in preventing COVID-19 (27.5 (95% CI, 26.3–28.8)) were the most important, followed by the risk of vaccine side effects (17.3 (95% CI, 16.2–18.4)). Individuals reluctant or unsure about vaccination (21.1%) prioritized the potential for mild side effects higher and vaccine efficacy lower than the vaccine-inclined individuals. New vaccination programs that target young adults should emphasize the protection duration, low risk of vaccine side effects, and high efficacy.
How do the poor survive in an unaffordable city? – An empirical study of informal housing households living in Hong Kong

ABSTRACT In urban economics, tenants are commonly assumed to substitute between accessibility and housing size and the substitution would become inelastic when the size is small. It explains how the poor survive in city centres. However, limited empirical study on this hypothesis is conducted because minimum housing size is commonly regulated in formal housing. Informal housing, in which the living area is not regulated, offers an opportunity for researchers to examine this hypothesis. Yet, differences between the two markets render them non-comparable. This paper contributes by conducting empirical tests on size elasticity on rent by studying Hong Kong’s sub-divided units (SDUs), which are mostly informally subdivided in housing flats, and the effect of proximity to public transportation on size elasticity of housing. The results suggest that size elasticity on smaller-sized housing rent is lower. Size elasticity of SDUs (with one-fourth of the average whole flat size) is about half of the whole flats. We further found that SDU tenants have to pay more for the same size increase when they live closer to the metro station. Compared with whole flat households, they are less willing to pay more for larger floor area.
EFFECTS OF PLANT PREPARATIONS OF PURE SAPONINS AND METHOXYFLAVONOIDS ON THE EXPRESSION OF IMMUNE RESPONSE GENES

Studies on the immunostimulating properties of saponins and methoxyflavonoids obtained from plants provides a theoretical basis for development of new immunopotentiators, thereby increasing effectiveness of immunotherapy and prophylaxis of viral infections. Expression of major genes of the immune response were significantly up-regulated upon introduction of plant-based immunostimulators into the body. These compounds were a mixture of purified saponin betulin isolated from plants of Betula sp. (Betula pendula) and purified methoxyflavonoids of plants of Polygonum sp. (Polygonum persicaria) and Cytrus sp. (Cytrus sinensis). The strength and specificity of the body's immune response can be adjusted by changing the structure of the methoxyflavonoid in the complex immunostimulator, which makes it possible to stimulate targeted immunostimulators that act on certain parts of the immune system.
Experimental and Computational Interaction Studies of (E)-N’-Benzylidene-5-Methyl-1H-Pyrazole-3-Carbohydrazide with α-Glucosidase and α-Amylase Enzymes: A Detailed Structural, Spectroscopic, and Biophysical Study

Abstract Herein we report the synthesis, DFT calculations, and molecular docking studies of a pyrazole derivative, (E)-N'-benzylidene-5-methyl-1H-pyrazole-3-carbohydrazide (E-BMPC) as α-glucosidase and α-amylase inhibitor. Molecular structure of E-BMPC has been confirmed by single crystal X-ray diffraction (XRD), FTIR, 1H, and 13C NMR spectra. In addition, density functional theory (DFT) calculations on E-BMPC were carried out to obtain frontier molecular orbital energies and first-order static hyperpolarizability (β). The α-amylase and α-glucosidase enzyme inhibitory of E-BMPC was also tested. E-BMPC displayed moderate inhibitory activity with IC50 values 310.57 ± 2.67 and 182.19 ± 3.20 against α-glucosidase and α-amylase enzymes, respectively. Molecular docking analysis provided the inhibition constant of E-BMPC molecule for α-amylase enzyme as 33.60 µM. Both in vitro and in silico enzyme inhibition studies showed that E-BMPC molecule is a better inhibitor for α-amylase than α-glucosidase. The β parameter for the molecule under investigation was also calculated as 4.2 × 10−30 esu.
Adaptive Vector-Based Sample Consensus Model for Moving Target Detection in Infrared Video

The detection of moving targets in infrared video with competitive accuracy and less computation time is an intractable task for daily security. The background subtraction method is typically used for such tasks. However, owing to the particular characteristics of infrared videos, only a few techniques are suitable. Because most classic background models cannot deal with low signal-to-noise ratios and small targets, an adaptive vector-based background subtraction model is proposed to detect moving objects in infrared video. For each pixel, several filters are employed to take past values, and a vector is assigned to each filter to represent the information in the neighborhood of the pixel. Then, the series of vectors comprises the background model, and the collinearity between the vector of the current pixel and the vectors in the background model is calculated based on cosine similarity. The current pixel is classified as foreground or background according to the times of collinearity. Finally, a random update scheme is employed to update the model. Extensive qualitative and quantitative experimental results have revealed that the proposed technique can achieve competitive performance than existing unsupervised state-of-the-art algorithms for tackling low signal-to-noise ratio and small target.
Improved Multimodal Tumor Necrosis Imaging with IRDye800CW-DOTA Conjugated to an Albumin-Binding Domain

Simple Summary Anti-tumor treatment efficacy is determined by tumor shrinkage, which takes valuable time to become apparent and poses a risk of unnecessary treatment with severe side effects. Therefore, there is an unmet need for more reliable and specific methods to monitor treatment efficacy. We explore radiolabeled cyanines for imaging tumor necrosis as a unique marker for therapy efficacy. Moreover, spontaneous tumor necrosis is a hallmark for aggressively growing tumor types with poor prognosis. We improved the binding properties of a previously reported necrosis-avid contrast agent (NACA) and successfully detected spontaneous and therapy-induced tumor necrosis in mice using radioactivity and fluorescence imaging modalities. This NACA may pave the way to in vivo detection of tumor necrosis for early-stage determination of tumor aggressiveness and therapy efficacy. Abstract Purpose: To assess our improved NACA for the detection of tumor necrosis. Methods: We increased the blood circulation time of our NACA by adding an albumin-binding domain to the molecular structure. We tested the necrosis avidity on dead or alive cultured cells and performed SPECT and fluorescence imaging of both spontaneous and treatment-induced necrosis in murine breast cancer models. We simultaneously recorded [18F]FDG-PET and bioluminescence images for complementary detection of tumor viability. Results: We generated two albumin-binding IRDye800CW derivatives which were labeled with indium-111 with high radiochemical purity. Surprisingly, both albumin-binding NACAs had >10x higher in vitro binding towards dead cells. We selected [111In]3 for in vivo experiments which showed higher dead cell binding in vitro and in vivo stability. The doxorubicin-treated tumors showed increased [111In]3-uptake (1.74 ± 0.08%ID/g after saline treatment, 2.25 ± 0.16%ID/g after doxorubicin treatment, p = 0.044) and decreased [18F]FDG-uptake (3.02 ± 0.51%ID/g after saline treatment, 1.79 ± 0.11%ID/g after doxorubicin treatment, p = 0.040), indicating therapy efficacy. Moreover, we detected increased [111In]3-uptake and tumor necrosis in more rapidly growing EMT6 tumors. Conclusions: Our albumin-binding NACA based on IRDye800CW facilitates tumor-necrosis imaging for assessment of therapy efficacy and aggressiveness in solid tumors using both fluorescence and SPECT imaging.
Conservative Significance Testing of Tripartite Interactions in Multivariate Neural Data

An important goal in systems neuroscience is to understand the structure of neuronal interactions, frequently approached by studying functional relations between recorded neuronal signals. Commonly used pairwise metrics (e.g. correlation coefficient) offer limited insight, neither addressing the specificity of estimated neuronal interactions nor potential synergistic coupling between neuronal signals. Tripartite metrics, such as partial correlation, variance partitioning, and partial information decomposition, address these questions by disentangling functional relations into interpretable information atoms (unique, redundant and synergistic). Here, we apply these tripartite metrics to simulated neuronal recordings to investigate their sensitivity to impurities (like noise or other unexplained variance) in the data. We find that all considered metrics are accurate and specific for pure signals but experience significant bias for impure signals. We show that permutation-testing of such metrics results in high false positive rates even for small impurities and large data sizes. We present a conservative null hypothesis for significance testing of tripartite metrics, which significantly decreases false positive rate at a tolerable expense of increasing false negative rate. We hope our study raises awareness about the potential pitfalls of significance testing and of interpretation of functional relations, offering both conceptual and practical advice. Author Summary Tripartite functional relation metrics enable the study of interesting effects in neural recordings, such as redundancy, functional connection specificity and synergistic coupling. However, common estimators of such relations are designed for pure (e.g. non-noisy) signals rare for such recordings. We study the performance of tripartite estimators using simulated impure neural signals. We demonstrate that permutation-testing is not a robust procedure for inferring ground truth interactions from studied estimators. We develop an adjusted conservative testing procedure, reducing false positive rate of studied estimators for impure data. Besides addressing significance testing, our results should aid in accurate interpretation of tripartite functional relations and functional connectivity.