Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving detectability of dolphin signature whistles for capture‐recapture analysis: an examination of array configuration using real‐world data

Abundance estimates of cetaceans are often acquired through capture-recapture analysis of photographically identified individuals. An alternative method, using capture-recapture of individually distinct signature whistles detected from acoustic underwater recording units, has recently been demonstrated. Here we investigate the effect of array configuration (1 – 3 hydrophones within 0.45 km 2 ) and recording duty cycles (six variations of 33%, 50%, or 66% sampling periods) on the detection rate of dolphin signature whistles. Twenty-one signature whistle types were identified and used to create capture histories for each hydrophone and all potential array configurations. Open population models were used to estimate capture probabilities and precision for all data sets. The effect of different duty cycles on detectability were investigated by artificially applying six duty cycles to the continuously recorded data. Results demonstrate that location is more important than redundancy in
Inactivation of foodborne viruses by the cold plasma technology

Cold plasma (CP) is an innovative non-thermal food processing method. CP refers to a partially or completely ionized gas containing reactive chemical species, which are active against microorganisms, including viruses or enzymes of foods. CP has a minimal effect on the quality attributes of foods and can also elongate the shelf life of foods. Foodborne outbreaks caused by viruses have been increased in various countries in recent years. The research works on the inactivation effect of CP against viruses including foodborne viruses have been also increased in recent years. The most important foodborne viruses are human norovirus (HuNoV) and hepatitis A virus (HAV), involved in several outbreaks worldwide. Human astrovirus (HAstV), human adenovirus (HuAdV), Aichi virus (AiV), sapovirus (SaV) and enterovirus (EV) are also notable foodborne viruses and were associated in sporadic cases. The CP treatment proved efficient for the inactivation of foodborne viruses such as HuNoV and HAV. The present work reviews the CP as a non-thermal food processing technology and present the published data on the effect of CP process on foodborne viruses in foods.
Optimization of Milling Parameters for Low Metal Contamination in Bead Milling Technology

This study aimed to develop a contamination-less bead milling technology using zirconia beads, by optimizing milling parameters. We evaluated the effects of bead milling parameters on milling time and metal con tamination; focusing on bead diameter, rotation speed, and bead filling rate as they are the critical parame ters determining bead milling efficiency. We studied the milling time required to grind a drug to 0.2 μm size and quantified the extent of metal contamination that arises from the grinding procedure. With optimal bead milling parameters, the minimum concentration of the metal contaminants was 1.27 ± 0.08 μg/mL (zirconium: 0.73 ± 0.09 μg/mL; yttrium: 0.35 ± 0.03 μg/mL; aluminum: 0.19 ± 0.05 μg/mL), when the rotation speed, bead diame -ter, and bead filling rate were set to 2 m/s, 0.3 mm, and 75% (v/v), respectively. Additionally, under optimized conditions, it was possible to reduce the metal contamination per weight of the drug by increasing the drug concentration to up to 40% (w/w). Under the optimized conditions for drug concentrations of 30–40% (w/w), metal contamination from the grinding process was minimized and reduced to < 10 μg/g, which is comparable to that achieved by the NanoCrystal ® technology. These results indicate that contamination-less bead milling using zirconia beads can be achieved when bead milling parameters are optimized.
Impact of Endoluminal Radiofrequency Ablation on Immunity in Pancreatic Cancer and Cholangiocarcinoma

Radiofrequency ablation (RFA) is a mini-invasive loco-regional ablation technique that is increasingly being used as a palliative treatment for pancreatic cancer and cholangiocarcinoma. Ablation-triggered immune system stimulation has been proposed as a mechanism behind the systemic effects of RFA. The aim of our study was to investigate the immune response to endoluminal biliary RFA. Peripheral blood samples were collected from patients with pancreatic cancer and cholangiocarcinoma randomised to receive endoluminal biliary radiofrequency ablation + stent (19 patients) or stent only (21 patients). We observed an early increase in IL-6 levels and a delayed increase in CXCL1, CXCL5, and CXCL11 levels as well as an increase in CD8+ and NK cells. However, these changes were not specific to RFA treatment. Explicitly in response to RFA, we observed a delayed increase in serum CXCL1 levels and an early decrease in the number of anti-inflammatory CD206+ blood monocytes. Our study provides the first evidence of endoluminal biliary RFA-based regulation of the systemic immune response in patients with pancreatic cancer and cholangiocarcinoma. These changes were characterised by a general inflammatory response. RFA-specific activation of the adaptive immune system was not confirmed.
A Machine Learning approach for Early Detection of Parkinson’s Disease Using acoustic traces

Parkinson’s disease is one of the most common diseases of the nervous system, which although typically develops after age 50, in some cases it also affects younger individuals. Its diagnosis is mainly based on the analysis of symptoms, it affects movement, coordination, and muscle control. Doctors generally analyse tremors, stiffness, slow movement, and difficulty walking as symptoms of the disease. Furthermore, changes in the voice are very common in patients with Parkinson’s disease, although such changes are not easily noticeable at an early stage. The disease can change your breathing, tone of voice, or lower the volume by up to 10 decibels. Therefore, speech recognition can introduce a new methodology of investigation in the diagnosis and monitoring of Parkinson’s disease. This study aims at the development of a model based on the use of Neural Networks for the diagnosis of the disease on voice recordings of different nature, made by both healthy and sick patients. In particular, three types of networks were used: Long Short Term Memory (LSTM) and Convolutional Neural Network (CNN) with one and two dimensions. The results are very satisfactory, highlighting the excellent performance of the LSTM with an F-Score of 97%. These results are very encouraging, suggesting that the use of the proposed approach can improve the Parkinson’s diagnostic, making it less costly in terms of time and effort.
Nanoincorporation of Plumbagin in Micelles Increase Its in Vivo Anti-Plasmodial Properties

Background: The application of plumbagin (PLN), with a wide use in pharmaceutical science, is limited due to its low water solubility and poor bioavailability. Micelles can encapsulate hydrophobic drugs due to their hydrophobic core. The aim of this study was to develop and characterize a polymeric micelle formulation of PLN and evaluate its in vivo anti-plasmodial property. Methods: The study was conducted at Zanjan University of Medical Sciences, Zanjan, Iran in 2018. The triblock copolymeric micelles of PLN was prepared by e-caprolactone ring-opening polymerization, by PEG as the macroinitiator and using Sn(Oct)2 for its catalytic properties. The synthesized nanoparticles were characterized by 1H NMR, FTIR, GPC, AFM, and DLS. The encapsulation efficiency, drug loading capacity, and drug release were measured by UV-Vis at 520 nm. Also in vivo anti-plasmodial potential of fabricated drug loaded micelle was investigated using the 4-day suppressive test against Plasmodium berghei infection in mice. Results: The nanoparticles average diameter was obtained less than 80 nm. The loading capacity and encapsulation efficiencies were 18.9±1.3% and 81±0.78%, respectively. In vitro, PLN release studies showed a sustained-release pattern until 7 days in PLN-loaded micelles (M-PLN) and drug release rate in acidic condition was higher than neutral condition. In vivo, anti-plasmodial results against P. berghei displayed an 8-fold increase in anti-plasmodial activity of M-PLN when compared to free PLN at the tested dosage level on the 7th day. Conclusion: Based on these results, PCL–PEG–PCL micelles have a great potential to be the carrier for PLN for the malaria targeting.
Hard and Soft Selection in the Laboratory: Dissecting the Mechanisms of Polymorphism Maintenance in Spatially Heterogeneous Environments

Predicting and managing contemporary adaption requires a proper understanding of the determinants of genetic variation. Spatial heterogeneity of the environment may stably maintain polymorphism when habitat contribution to the next generation can be considered independent of the degree of adaptation of local populations within habitats (i.e., under soft selection). In contrast, when habitats contribute proportionally to the mean fitness of the populations they host (hard selection), polymorphism is not expected to be maintained by selection. Although mathematically established decades ago, this prediction had never been properly tested. Here we provide an experimental test in which polymorphic populations of Escherichia coli growing in heterogeneous habitats were exposed to hard and soft selection regimes. As predicted by theory, polymorphism was longer preserved in asymmetric environments under soft selection. Complementary tests established that soft selection actually protected polymorphism even when one genotype was present at low frequency.
CAN DIGITAL LITERACY PRACTICES MOTIVATE INTERNATIONAL STUDENTS TO UPGRADE THEIR ENGLISH AS A SECOND LANGUAGE (L2)?: AN ETHNOGRAPHY CASE STUDY

This article discussed how to bridge communication between international students studying at host universities in other countries through digital literacy practices and is a model for global social interaction. This article also investigates the use of English proficiency, specifically for students in Indonesia and Thailand via online platform. It is based on semi structure interviews synchronously and asynchronously conducted with international students in both countries. The article focuses on five international students studying abroad from five different countries. This article uses an ethnography case study which describes some images from the results and findings in greater depth. The findings indicate the reasons for analysis and effectiveness in moving literacy practice toward digitalization for L2 students. These findings suggest that new literacy learning is rapidly evolving with advanced technology, necessitating the use of a high-speed Internet connection. This study contributes to language planning as L2 based on ethnography which has also been adapted into digital literacy for Thai and Indonesian students. In addition, this research's contribution is to give some people more about the importance of digital literacy practices, especially for an institution that has international students in teaching and learning. The authors' focus is on their personal experiences with digital literacy practices
A Genome Wide Linkage Scan for Dizygotic Twinning in 525 Families of Mothers of Dizygotic Twins

background: The tendency to conceive dizygotic (DZ) twins is a complex trait influenced by genetic and environmental factors. To search for new candidate loci for twinning, we conducted a genome-wide linkage scan in 525 families using microsatellite and single nucleotide polymorphism marker panels. methods and results: Non-parametric linkage analyses, including 523 families containing a total of 1115 mothers of DZ twins (MODZT) from Australia and New Zealand (ANZ) and The Netherlands (NL), produced four linkage peaks above the threshold for suggestive linkage, including a highly suggestive peak at the extreme telomeric end of chromosome 6 with an exponential logarithm of odds [(exp)LOD] score of 2.813 (P ¼ 0.0002). Since the DZ twinning rate increases steeply with maternal age independent of genetic effects, we also investigated linkage including only families where at least one MODZT gave birth to her first set of twins before the age of 30. These analyses produced a maximum expLOD score of 2.718 (P ¼ 0.0002), largely due to linkage signal from the ANZ cohort, however, ordered subset analyses indicated this result is most likely a chance finding in the combined dataset. Linkage analyses were also performed for two large DZ twinning families from the USA, one of which produced a peak on chromosome 2 in the region of two potential candidate genes. Sequencing of FSHR and FIGLA, along with INHBB in MODZTs from two large NL families with family specific linkage peaks directly over this gene, revealed a potentially functional variant in the 5 ′ untranslated region of FSHR that segregated with the DZ twinning phenotype in the Utah family. conclusion: Our data provide further evidence for complex inheritance of familial DZ twinning.
Group-split attention network for crowd counting

Abstract. Crowd counting is a considerable yet challenging task in intelligent video surveillance and urban security systems. The performance has been significantly boosted along with the springing up of the convolutional neural networks (CNNs). However, accurate and efficient crowd counting in congested scenes remains under-explored due to scale variation and cluttered background. To address these problems, we propose a biologically inspired crowd counting method named group-split attention network (GSANet). The GSANet consists of three principal modules, namely GS module, dual-aware attention module, and aggregation module. The GS module processes the subfeatures of each group in parallel, and groups the input feature map to reduce the computational cost. The dual-aware attention module synergies the spatial and channel dimensional information to alleviate the estimation error in background regions. The aggregation module adopts a learning-based cross-group strategy to aggregate and facilitate the fusion of feature maps along different channel dimensions. Extensive experimental results on five benchmark crowd datasets demonstrate that the GSANet achieves superior performances in terms of accuracy and efficiency.
Coseismic Surface Deformation, Fault Modeling, and Coulomb Stress Changes of the March 2021 Thessaly, Greece, Earthquake Sequence Based on InSAR and GPS Data

In March 2021 three strong earthquakes with magnitudes (Mw) of 6.3, 6.0, and 5.2 occurred in Thessaly plain, Greece, on 3, 4, and 12 March, respectively. The modeling of all the three sources, by inversion of Interferometric Synthetic Aperture Radar and Global Positioning System data, indicates a northeast–southwest-trending extensional stress field with indications for northeast-dipping sources. The unmapped fault source of the first mainshock (Mw 6.3) is located approximately 6 km to the southwest of the known Larissa fault (LF). Moreover, the fault that was activated during the second mainshock (Mw 6.0) appears to be located more to the north, bordering the Titarisios river valley to the southwest, whereas the third mainshock (Mw 5.2) appears to be triggered at a fault segment located further to the northwest. The Coulomb stress analysis using the slip distributions of the three aforementioned mainshocks revealed a unilateral triggering of the second and third event toward the northwest, and explained the spatial development of the entire aftershock sequence. Furthermore, among the already known active faults in the broader area, only the LF was brought closer to failure as a result of the imparted stress changes.
On the eventual periodicity of fractional order dispersive wave equations using RBFS and transform

In this research work, let’s focus on the construction of numerical scheme based on radial basis functions finite difference (RBF-FD) method combined with the Laplace transform for the solution of fractional order dispersive wave equations. The numerical scheme is then applied to examine the eventual periodicity of the proposed model subject to the periodic boundary conditions. The implementation of proposed technique for high order fractional and integer type nonlinear partial differential equations (PDEs) is beneficial because this method is local in nature, therefore it yields and resulted in sparse differentiation matrices instead of full and dense matrices. Only small dimensions of linear systems of equations are to be solved for every center in the domain and hence this procedure is more reliable and efficient to solve large scale physical and engineering problems in complex domain. Laplace transform is utilized for obtaining the equivalent time-independent equation in Laplace space and also valuable to handle time-fractional derivatives in the Caputo sense. Application of Laplace transform avoids the time steeping procedure which commonly encounters the time instability issues. The solution to the transformed model is then obtained by computing the inversion of Laplace transform with an appropriate contour in a complex space, which is approximated by trapezoidal rule with high accuracy. Also since the Laplace transform operator is linear, it cannot be used to transform non-linear terms therefore let’s use a linearization approach and an appropriate iterative scheme. The proposed approach is tasted for some nonlinear fractional order KdV and Burgers equations. The capacity, high order accuracy and efficiency of our approach are demonstrated using examples and resultsRBFs Methods
Individualising probation conditions in cases of domestic violence: The study of sentencing practice in Lithuania

Based on an empirical quantitative study, the paper examines the sentencing trends and individualisation of probation conditions in domestic violence cases. The study sample included 577 Lithuanian court verdicts for moderate bodily injury in a domestic setting between 2015 and 2019. The study results suggest that the length of the probation period imposed by the courts may depend on the offender’s conviction history but is not related to the offender’s socio-demographic characteristics and the mitigating or aggravating circumstances. Such characteristics as employment and marital status, mitigating and aggravating circumstances may relate to the type of sentence decisions. The study revealed a discrepancy between the main characteristics of the offender and the nature of probation conditions imposed by courts. Based on study results, the authors of this paper presume that Lithuanian sentencing practice lacks evidence-based individualisation of probation conditions.
Nutritional evaluation of the agro-industrial by-products and waste fruits-vegetable for sustainable ruminant nutrition

The growing consumption of ruminant animal products gives rise to a huge demand of animal feed in growing countries. By-product feeds, waste fruits-vegetables, and crop residues should be considered as a valuable alternative feed resource in ruminant nutrition. This waste can be reutilized and converted by ruminants to valuable products for human benefits as a new resource and in return to increase the effectiveness of limited feed sources. But, there are limited new information and research regarding the nutritive value of this waste for ruminants. For this purpose, the experiment was conducted to evaluate the nutritional potential of some agro-industrial by-products, waste fruits-vegetable, and crop residue for ruminants specifically. Fourteen by-products, waste fruits-vegetable and crop residue were collected from the west part regions of Turkey. Nine by-product feeds (whole cottonseed, rice bran, soybean hull, apple pomade, citrus pulp, grape pomade, tomato pomade, grape stalk, rice hull), three waste fruits (dry grape, dry fig, carrot), one waste vegetable (potato) and also one crop residue (cornstalk) were analyzed for nutritional composition and metabolizable energy values were calculated by crude nutrients for ruminants. Further, energy, DMD, and OMD of these samples were investigated by using the cellulose enzyme method. All samples were analyzed the macro minerals (Ca, P, Na, K, and Mg) and the microelements (Fe, Cu, Mn, and Zn) contents. In the research, all samples regarding the parameters in DM, ash, OM, CP, EE, CF, NFE, NSC, NDF, ADF, starch, sugar, Ca, P, Na, K, Mg, Fe, Cu, Mn, Zn, DMD, OMD, MECN, and MECEL were different (P<0.05). The study showed that the waste fruits, vegetable, and by-products have valuable sugar (grape, fig, and carrot), starch (potato, rice bran), NSC (citrus pulp), and oil (cottonseed) content that is the main compounds making them high energetic feeds for ruminants. Also, most of these research materials have enough or much more macro and micro mineral concentrations for ruminant nutrition.
Working outside of the system: engaging in Web 2.0 to enhance learning and teaching in the design studio

The Deakin Studies Online (DSO) Learning Management System (LMS) forms the fundamental basis for tertiary education at Deakin University. This LMS is founded on Web 1.0 principles, however signifi cant potential exists for engagement in Web 2.0 technologies to support learning and teaching in the design studio. A digitally enhanced design curriculum is discussed starting with html-based refl ective folios in 2001, the use of blogs for refl ection and resource creation and culminating in a Web 2.0 design studio based on social networking.
The Perceptions of Students and Lecturers on the Use of Animals in Biomedical Science Undergraduate Education in Brazil

The use of animals in research and education is a controversial topic that has raised extensive debates. Undergraduate students (n = 404) and lecturers (n = 62) from biomedical science schools at the Federal University of Goiás (UFG) in the municipality of Goiânia, Jataí and Catalão, Goiás, Brazil, were asked about their knowledge and opinions on bioethics, the use and importance of animals in education, the replacement of animal use with non-animal alternatives, and the current legislation of the National Council for the Control of Animal Experimentation (CONCEA) that bans animal use in some practical classes within technical and higher education (i.e. Resolution No. 53/2021). Most students and lecturers agreed not only that animal use can contribute to education, but also that it is important to replace this animal use with innovative non-animal alternatives where appropriate. The lecturers emphasised that the replacement of animal models will be possible only with the provision of appropriate training to improve the skills of educators in their use, as well as ensuring reliable access to suitable facilities and materials.
Automated segmentation of blood vessels in retinal images based on entropy weighted thresholding

ABSTRACT Automated extraction of retinal vasculature is becoming a crucial task during the study of pathological disorders present in the retinal fundus image. In this work, we propose an unsupervised approach for automatically extracting blood vessels from fundus photographs. In this paper, Logarithmic transformation (Log) and contrast limited adaptive histogram equalisation (CLAHE) are being used to boost the contrast level of the fundus photographs. After that, Matched filtering technique is used for further vessel enhancement. Then, different thresholding techniques are evaluated and compared to find out the best thresholding scheme for this segmentation. We have found that Otsu with entropy weighting thresholding is the best threshold method for segmenting the blood vessels. In the post-processing step, the area-based thresholding process is considered, and it gives the final vessel segmented image. Using the following statistical measures, the final vessel segmented image is compared to the ground truth image, such as sensitivity (Sens), precision (Spec), and accuracy (Acc). This work is evaluated by freely accessible DRIVE (Digital Retinal Images for Vessel Extraction), STARE (Structured Analysis of the Retina), and CHASE_DB1 (Child Heart and Health Study in England) datasets. This work achieves an average accuracy of 0.9562, 0.946, and 0.946 on the DRIVE, STARE, and CHASE_DB1 datasets, respectively.