Miracle-dz/UniFAR-FTUs huggingface dataset:
Tackling Vaccine Hesitancy and Increasing Vaccine Willingness Among Parents of Unvaccinated Children in Austria

Objectives: In autumn 2021, there was a surge of COVID-19 infections in Austria, and vaccination coverage stagnated at a below-average level compared to the rest of Europe. Surveys showed that both children and adolescents were the main drivers of the rising infection rates and that vaccination numbers were particularly low in this age group. This was due to widespread vaccination skepticism and hesitancy among parents of unvaccinated children and adolescents. Methods: Here, we describe a novel intervention concept that allowed us to efficiently tackle parental vaccine hesitancy. We designed an intervention series that followed a reproducible format based on online face-to-face seminars in groups of a maximum of twenty people. Each seminar included an anonymous online questionnaire for internal quality control. Moreover, we assessed the motives of parental vaccine hesitancy and asked participants to rate subjective vaccine willingness for their children on a scale of zero to ten. Results: Within 8 weeks, more than 580 people participated in the seminar series. We found that concerns about the side effects of the vaccine were the predominant motive of vaccination hesitancy among the study population. Overall, the intervention could successfully increase the median parental vaccination willingness of participants from a score of five to eight. We identified tree hesitancy motives (distrust towards the pharmaceutical industry, the government, or feelings of restriction from personal freedom) that were associated with below-average vaccination willingness and significant lower increase. Conclusion: With this study we analyzed motives driving COVID-19 vaccination hesitancy among parents of unvaccinated children and reasons of parents to restrain their children from getting vaccinated. The intervention method described here, could effectively address individual concerns on a personal level while at the same time reach a large number of people across geographical and language barriers. Thereby we could significantly increase subjective vaccination willingness of the participants. Our approach is easy to apply, highly cost-effective, and can be used to tackle any kind of medical misinformation.
Complex battlefields favor strong soldiers over large armies in social animal warfare

Significance Warfare is fundamental to the outcome of competition in social species from humans to insects and is of global interest and appeal to scientific and public audiences alike. Although theory predicts that the environment in which group battles take place will affect the optimal strategy, empirical tests are difficult. Here, we use simulated battles in a gaming construct to demonstrate that investing in smaller armies of stronger soldiers is more effective in complex battlefields. We then use a real-world system for group battle studies—social ants—to validate our findings in an empirical setting and find that small armies of large ants perform better against large armies of small ants in complex environments.
$\pi_{\mathbf{RA}}$: A $\pi\text{-calculus}$ for Verifying Protocols that Use Remote Attestation

Remote attestation (RA) is a primitive that allows the authentication of software components on untrusted systems by relying on a root of trust. Network protocols can use the primitive to establish trust in remote software components they communicate with. As such, RA can be regarded as a first-class security primitive like (a)symmetric encryption, message authentication, etc. However, current formal models of RA do not allow analysing protocols that use the primitive without tying them to specific platforms, low-level languages, memory protection models, or implementation details. In this paper, we propose and demonstrate a new model, called $\pi_{\mathbf{RA}}$, that supports RA at a high level of abstraction by treating it as a cryptographic primitive in a variant of the applied $\pi- \mathbf{calculus}$. To demonstrate the use of $\pi_{\mathbf{RA}}$, we use it to formalise and analyse the security of MAGE, an SGX-based framework that allows mutual attestation of multiple enclaves. The protocol is formalised in the form of a compiler that implements actor-based communication primitives in a source language $(\pi_{\text{Actor}})$ in terms of remote attestation primitives in $\pi_{\text{RA}}$. Our security analysis uncovers a caveat in the security of MAGE that was left unmentioned in the original paper.
Soil surface-seal measurement using high-resolution x-ray computed tomography (HRCT)

Rainfall on bare soil breaks soil aggregates, detaching particles, plugging pores and decreasing porosity in the top few mm of soil. This reduces hydraulic conductivity and increases runoff through a process known as surface sealing. The objectives of this study are to measure saturated hydraulic conductivity (Ksat) of surface seals developed on bare Mexico silt loam (Aeric Vertic Epiaqualfs) during a simulated rainfall event, to evaluate the effect of anionic polyacrylamide (PAM) for maintaining high Ksat, and to evaluate models of sealing using total porosity, pore-size distribution collected with highresolution X-ray computed tomography (HRCT). The study used a factorial design. Factors included rainfall duration (0-, 7.5-, 15-, 30-, and 60-min) at 55-mm hr rainfall intensity, and an untreated soil or a soil amended with 20-kg ha PAM. Pore characteristics analyzed included number of pores, total porosity, and pore-size distribution. Application of PAM for various rainfall durations maintained from 20% to 41% higher Ksat than did untreated soil, for all times tested. Use of PAM produced different seal density (ρ). Results indicated ρ increased, and total porosity and pore-size decreased rapidly after a 15-min rainfall. HRCT-ρ data helped identify the best model selection for characterizing seal ρ profile. A sigmoidal model (Roth, 1997; r=0.68) and a mixed exponential model (Mualem and Assouline, 1989; r=0.67) both described seal ρ profiles well. Although the cost is expensive, HRCT-image is a valuable tool to measure soil properties by analyzing soil thickness down to 0.015-mm. The study confirms that HRCT-analysis of soil allows accurate and direct measurements of seal effects on water flow and documents the usefulness of PAM for reducing surface sealing.
Towards Automatic Design of Soft Pneumatic Actuators: Inner Structure Design Using CNN Model and Bézier Curve-Based Genetic Algorithm

In this letter, the development of a method for the design of soft pneumatic actuators is described. The focus is given on the interest of using a deep learning model to explore the design space with a genetic algorithm. In particular, we propose to perform the automatic synthesis of the inner structure of pneumatic actuators using Bézier curves and Gaussian Mixture Points, to have a simple representation of the actuator genotype. This makes it possible to represent a wide variety of structures and to take into account the presence of the actuator pneumatic supply. It is shown a CNN model can interestingly be used in conjunction with FEM. FEM is being used to train initially the CNN model and for the control of accuracy, while the CNN model reduces the computational cost, offering a sufficient accuracy during the synthesis thanks to transfer learning. Through two case studies, the capacity of generating geometrically complex designs such as a double-helix network for a twisting actuator is outlined. Its possible extension and further use are also discussed.
Carbon Status of Indian Soils : An Overview

Restoration of soil health through soil organic carbon (SOC) management is a major concern for tropical soils. The accelerated decomposition of SOC due to agriculture, resulting in loss of carbon to the atmosphere and its contribution to the green house effect, is a serious global problem. The contribution of SOC to improving soil physical, chemical and biological properties and maintaining soils integrity for sustaining soil productivity is well known. Important factors controlling
An Approach of the Electric Field Strength Prediction Using Time Series Analysis

The paper describes an approach of modelling and prediction of the electric field strength (EFS) using classical time series analysis. Based on knowledge of field strength variability, it is assumed that EFS can be modeled as a sum of constant, periodic and stochastic component, modelled as an autoregressive process. Analyzing the case study of data collected during 2022, by a sensor of the Serbian EMF RATEL monitoring network, located in University of Novi Sad (UNS) campus, significant differences in EFS levels were observed, thus separate model parameters have been used for working and non-working days.
Mental stress recognition based on electrocardiogram

In this study, we constructed a mental stress recognition model with Electrocardiogram (ECG) signals by machine learning. Firstly, we collected the ECG signals while students are explaining simple math exercises, located the R-wave peak of the QRS wave group, and calculated the R-wave to R-wave (RR) interval. Then we extracted the characteristic parameters of autonomic nervous response from the RR interval, carried out statistical analysis and sequential forward selection and finally constructed a psychological stress recognition model. The accuracy of the model in the test set and the independent subject validation set was 79% and 83%, respectively. The results show that it is feasible to recognize strong or weak psychological stress state through machine learning method.
A Hybrid 2D-1D CNN for Scanner Device Linking Based on Scanning Noise

Ensuring the authenticity of scanned documents is of major concern, these ones being often admitted as evidence by organizations. “Is there any way to verify that a document was scanned by a device without having access physically to the source device itself? ” is a wide-open question. In this paper, we aim at answering it in the affirmative by means of the first data-driven hybrid machine learning framework that compares image noise features to check if two documents have been digitized with the same scanner or not. Such a problem is known as device linking function. Different comparative experiments conducted on the same and different scanner models on a broad set of administrative documents demonstrate that our method is efficient in linking scanned images even if scanner devices are unknown to the investigator. Our success rate of 96% appears to be the novel state of art reference in such application domain.
Socio-economic considerations for land-use planning: the case of Kapuas Hulu, West Kalimantan.

Understanding the socio-economic conditions, the drivers for land use change and economic development, along with cultural and social characteristics, is essential to ensure that land use decisions are made that ensure positive economic and social outcomes are optimised. The CoLUPSIA socio-economic team researched the conditions facing communities and individual households across four pilot areas, each area representing different socio-economic and environmental/ bio-physical conditions. Household, village, key interview surveys and focus group discussions, were completed for 876 households, 22 villages, equivalent to approximately 7.2% of the total number of households and 10% of villages in Kapuas Hulu Regency, West Kalimantan. The results highlight the challenges that face the communities and how these vary across the pilot sites. For example in Pilot 1 is located within the boundaries of two national parks, land is more restricted as communities face unclear boundaries, and Pilot 2 located to the east of Putussibau, the villagers are heavily dependent on natural resources, with relatively limited economic opportunities but gold mining which has environmental consequence and face a legality issues. In Pilot 3 and 4, exhibit case of communities are more dependent on diverse source of livelihoods such as rubber production, gold mining and paid employment. Oil palm plantations increasingly become an alternative employment as well as has potential negative impact to environment. The results of the socio-economic survey aim to provide a baseline that provides an understanding of the relationship between the communities in Kapuas Hulu regency and the natural resources - use and non- use, coupled with the needs for economic development. The resulting challenges and opportunities are identified and can be used in the development of land use planning processes and where possibly in the development of Payment for Ecosystem Service (PES) schemes.
End-to-end Slicing of RAN based on Next Generation Optical Access Network

Due to their large diffusion, optical access networks represent a viable supporting infrastructure for mobile networks and services. The heterogeneity of services supported by mobile networks calls for the implementation of slicing mechanisms able to accommodate resources in all the involved network segments from the mobile user up to the core network.In this work, we demonstrate a fully-functional and integrated 5G network deployment to satisfy real end-to-end slicing in next-generation access networks. We evaluate the impact of optical access network resources allocation mechanisms on slice performance in terms latency and jitter experienced by mobile users.
Development of Silk Fibroin-Based Non-Crosslinking Thermosensitive Bioinks for 3D Bioprinting

Three-dimensional (3D) bioprinting holds great promise for tissue engineering, allowing cells to thrive in a 3D environment. However, the applicability of natural polymers such as silk fibroin (SF) in 3D bioprinting faces hurdles due to limited mechanical strength and printability. SF, derived from the silkworm Bombyx mori, is emerging as a potential bioink due to its inherent physical gelling properties. However, research on inducing thermosensitive behavior in SF-based bioinks and tailoring their mechanical properties to specific tissue requirements is notably lacking. This study addresses these gaps through the development of silk fibroin-based thermosensitive bioinks (SF-TPBs). Precise modulation of gelation time and mechanical robustness is achieved by manipulating glycerol content without recourse to cross-linkers. Chemical analysis confirms β-sheet conformation in SF-TPBs independent of glycerol concentration. Increased glycerol content improves gelation kinetics and results in rheological properties suitable for 3D printing. Overall, SF-TPBs offer promising prospects for realizing the potential of 3D bioprinting using natural polymers.
Conservative Tryptophan Residue in the Vicinity of an Active Site of the M15 Family l,d-Peptidases: A Key Element in the Catalysis

Bioinformatics analysis of the sequences of orthologous zinc-containing peptidases of the M15_C subfamily revealed the presence of a conserved tryptophan residue near the active site, which is not involved in the formation of the protein core. Site-directed mutagenesis of this Trp114/109 residue using two representatives of the family, l-alanoyl-d-glutamate peptidases of bacteriophages T5 (calcium-activated EndoT5) and RB49 (EndoRB49, without ion regulation) as examples, and further analysis of the 1H NMR spectra of the mutants showed that a decrease in the volume of the W → F → A residue leads to changes in the hydrophobic core and active center of the protein, and also decreases the affinity for regulatory Ca2+ in the EndoT5 mutants. The inactive T5W114A mutant lacks the ability to bind the substrate. In general, the conserved Trp114/109 residue, due to the spatial restrictions of its side chain, significantly affects the formation of the catalytically active form of the enzyme and is critical for catalysis.
Soft Normal and Shear Force Sensor for Underwater Robotic Applications

Tactile perception is a fundamental requirement to perceive and control the manipulation of an object via physical interaction. However, contemporary sensing technologies have some shortcomings in terms of directional force recognition such as inflexibility, intricate design, expensive fabrication methodology, and most importantly incompatibility with underwater applications. In this work, we report a facile and cost-effective methodology to build a soft and multi-directional force sensor especially focusing on its applicability in the underwater environment. The sensor consists of a silicone cover, a 3D printed pyramidal shape, piezo-resistive sensor nodes, and a silicone base. Whenever there is any force applied normal to the sensor, the pyramid shape would distribute the force equally to all the nodes and provide similar outputs from them whereas any other directional force would result in putting differential forces on the nodes and generate distinctive output patterns. The developed sensor was characterized experimentally and tested successfully for underwater demonstrations.
Response of the Elemental Chemistry of Carbonate Phases to Secular Change in Ocean Chemistry.

Abstract Calcium carbonate is the dominant inorganic mineral precipitate of the global ocean and by no coincidence, it is also the most abundant mineral produced by life. Secular variation in the paleontologic, stratigraphic, petrographic, and geochemical character of limestones argues that the physicochemical conditions under which it has precipitated from seawater have not been constant over geologic time. A major aspect of this variation has been the modality in the primary mineralogy between times of dominantly low-Mg calcite and times of aragonite and high-Mg calcite. Because these minerals have different chemical characteristics, they respond differently during diagenesis and thus affect the evolution of important limestone attributes such as porosity and permeability. Seawater Mg/Ca likely controls this modality. To estimate seawater Mg/Ca from calcite Mg/Ca it has been customary to assume a linear relationship between these two quantities. However, experiments where biotic and abiotic calcites were precipitated in the laboratory suggest that this relationship is a power function. This power function, a “partition power function” , accounts for the observation that partition coefficients tend to decrease at high solution Mg/Ca because of interference with the growing calcite crystal surface by Mg. This method more accurately estimates paleoseawater Mg/Ca from ancient calcite phases. Partition power functions can be used to model the change in the Mg/Ca of calcite phases in response to secular variation in seawater Mg/Ca. The smaller range and average
Systematic Review and Metaanalysis Comparing the Bias and Accuracy of the Modification of Diet in Renal Disease and Chronic Kidney Disease Epidemiology Collaboration Equations in Community-Based Populations.

BACKGROUND The majority of patients with chronic kidney disease are diagnosed and monitored in primary care. Glomerular filtration rate (GFR) is a key marker of renal function, but direct measurement is invasive; in routine practice, equations are used for estimated GFR (eGFR) from serum creatinine. We systematically assessed bias and accuracy of commonly used eGFR equations in populations relevant to primary care. CONTENT MEDLINE, EMBASE, and the Cochrane Library were searched for studies comparing measured GFR (mGFR) with eGFR in adult populations comparable to primary care and reporting both the Modification of Diet in Renal Disease (MDRD) and the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations based on standardized creatinine measurements. We pooled data on mean bias (difference between eGFR and mGFR) and on mean accuracy (proportion of eGFR within 30% of mGFR) using a random-effects inverse-variance weighted metaanalysis. We included 48 studies of 26875 patients that reported data on bias and/or accuracy. Metaanalysis of within-study comparisons in which both formulae were tested on the same patient cohorts using isotope dilution-mass spectrometry-traceable creatinine showed a lower mean bias in eGFR using CKD-EPI of 2.2 mL/min/1.73 m2 (95% CI, 1.1-3.2; 30 studies; I2 = 74.4%) and a higher mean accuracy of CKD-EPI of 2.7% (1.6-3.8; 47 studies; I2 = 55.5%). Metaregression showed that in both equations bias and accuracy favored the CKD-EPI equation at higher mGFR values. SUMMARY Both equations underestimated mGFR, but CKD-EPI gave more accurate estimates of GFR.
Feature extraction through cross-phase congruency for facial expression analysis

Human face analysis has attracted a large number of researchers from various fields, such as computer vision, image processing, neurophysiology or psychology. One of the particular aspects of human face analysis is encompassed by facial expression recognition task. A novel method based on phase congruency for extracting the facial features used in the facial expression classification procedure is developed. Considering a set of image samples comprising humans expressing various expressions, this new approach computes the phase congruency map between the samples. The analysis is performed in the frequency space where the similarity (or dissimilarity) between sample phases is measured to form discriminant features. The experiments were run using samples from two facial expression databases. To assess the method’s performance, the technique is compared to the state-of-the art techniques utilized for classifying facial expressions, such as Principal Component Analysis (PCA), Independent Component Analysis (ICA), Linear Discriminant Analysis (LDA), and Gabor jets. The features extracted by the aforementioned techniques are further classified using two classifiers: a distance-based classifier and a Support Vector Machine based classifier. Experiments reveal superior facial expression recognition performance for the proposed approach with respect to other techniques.
Updating snow reservoir in hydrological models from satellite-observed snow coverd areas

Operational use of satellite-observed snow covered area (SCA) in the HBV-model has been carried out using two different snow distribution functions. SCA could be included in the model calibration with only small reduction in runoff performance. Updating the runoff models based on the satellite derived SCA showed ambiguous results. The success rate of the updates was only 28 % for the traditional snow model. Studies using a dynamic snow distribution function for the snow reservoir showed comparable results to the traditional lognormal snow distribution for prediction of discharge and better for the prediction of SCA. Updating the new model from satellite derived SCA consistently gave improvements on the prediction of discharge. Keyword: Snow; Runoff simulations; Satellite derived snow covered area Norwegian Water Resources and Energy Directorate Middelthuns gate 29 P.O. Box 5091 Majorstua N-0301 OSLO Telephone: 22 95 95 95 Telefax: 22 95 90 00 Internet: www.nve. no