Miracle-dz/UniFAR-FTUs huggingface dataset:
Low-fouling SPR detection of lysozyme and its aggregates

Protein aggregates adsorb to material surfaces in a different manner than protein monomers and pose additional challenges for biosensor development with regard to non-specific adsorption (NSA). In this context, we describe herein the performance of a new antifouling thiol in a sensor coating resistant to NSA from lysozyme monomers and aggregates. Coatings were prepared as mixed self-assembling monolayers (SAMs) using a long polyethylene glycol carboxyl-terminated thiol (“PEG-COOH”) for the first time in conjunction with a shorter monoethylene glycol hydroxyl-terminated diluent thiol (“MEG-OH”). SAMs and their antifouling properties were characterized by a variety of surface analysis techniques. A key result was that the cleaning procedure drastically affects the antifouling properties of resulting MEG-OH based SAMs. Mixed PEG-COOH/MEG-OH SAMs formed on borohydride cleaned interfaces are able to reduce lysozyme NSA by >90% compared to bare gold; a remarkable performance also displayed for oligomers regardless of their stage of aggregation. Gratifyingly, subsequent SAM functionalisation with an anchoring layer of neutravidin for the preparation of a lysozyme sensor did not significantly alter the antifouling properties of the resulting assembly. The limit of detection for monomeric lysozyme by surface plasmon resonance was 0.3 μg mL−1 with a dynamic range of 3–50 μg mL−1 (R2 = 0.9993). The sensitivity of the technique for the aggregated lysozyme was almost two times higher than that for the protein monomer.
A NUMERICAL INVESTIGATION OF THE FLUID FLOW IN A CHANDLER LOOP FOR THROMBUS STUDIES

The Chandler loop is an artificial circulatory platform for in vitro hemodynamic experiments. In most experiments, the working fluid is subjected to a stress field via rotation of the Chandler loop, which, in turn, induces biochemical responses of the suspended cells. For very low rotation rates, the stress field can be approximated using laminar flow in a straight tube as a model. However, as the rotation rate increases while still maintaining laminar flow, the effect of the tube curvature causes the stress field to deviate considerably from the straight tube approximation. In this manuscript, we investigate the flow and associated strain rate field of an incompressible Newtonian fluid in a Chandler loop as a function of the governing non-dimensional fluid dynamic parameters. We find that the Dean number, which is proportional to the rotation rate, is the dominant parameter in determining the fluid strain rate. We propose an empirical formula for predicting the average fluid strain rate magnitude in the working fluid that is valid over a wide parameter space to be used in lieu of the common, yet restrictive, straight tube-based prediction.
Analytical Study on Effect of Bar Size on Pull-out force for Reinforcing Bar Embedded in Concrete Blocks

The most commonly used test method for measuring the bond strength between reinforcing bars and concrete is the pull-out test of pulling a reinforcing bar out of a concrete block. During serviceability and durability design the bond of reinforcing bars is important in crack control. This paper presents numerical model for studying the size effect on pull-out force. This research considers three bar size diameter, which is 10, 12 and 16 mm bar diameter. The finite element ANSYS software was used for the numerical analysis. The specimens are analyzed until the specimens failure were occurred. The analytical results indicate that the pull-out force increase with increasing bar diameter. The pullout force for specimens S12 and S16 are increase (7% and 35%) compared with specimen S10 respectively.
Testing of Ni‐Plated Ferritic Steel Interconnect in SOFC Stacks

Stack tests were run at 850 °C for periods from 80 hours to 1,150 hours to develop contacting procedures and at the same time evaluate the performance of a 5 μm electroplated nickel coating on a ferritic Fe22Cr interconnect. The metallic nickel coating reacted relatively quickly during the initial heating to 1,030 °C. During this time, 20–70 μm thick surface layers of austenitic steel were formed, which were covered by a 1–4 μm chromia layer on the anode side and by a layer of mixed Cr‐Fe‐Ni‐spinels over a 1–4 μm chromia layer on the cathode side. The microstructure and composition of the protective scale on the cathode side was susceptible to pitting‐type corrosion patterns, which may limit the life expectancy to less than 2,000 hours for the 200 μm thick interconnect tested. The initial area‐specific resistances (ASR) at the interconnect/cathode current collector interface and the interconnect/anode current collector interface were very low (2 and 10 mΩ cm2, respectively). The cathode side interface resistance increased over the 1,150 hours by ∼7 mΩ cm2/103�h, but the anode side interface resistance decreased during the first 600 hours of the experiment before it started to show a slight increase, < 1 mΩ cm2/103�h, maintaining values below 1 mΩ cm2.
EIT Digital: leveraging ecosystems for international entrepreneurial innovation

Building on earlier work on entrepreneurship and holistic innovation policy, the paper elaborates on the concept of “entrepreneurial innovation ecosystem” and applies it in the empirical analysis of the European Institute of Innovation and Technology (EIT) partnership operations. The analysis focuses on the EIT Digital, which is one of the EIT “Knowledge and Innovation Communities” (KICs) formed by partners from higher education, research and business. The empirical research with primary data from semi-structured interviews and secondary data from desk research provides evidence on the different perceptions between EIT Digital managers in six accelerators around Europe compared to partners and start-ups in the Madrid co-location centre. Ecosystem dimensions are intertwined in EIT Digital activities and the actual performance of the whole depends on their effective alignment. Hence, further research is suggested on the interconnections between the ecosystem dimensions with particular attention to ecosystem integration, international networking and adaptive governance.
“MYCO SYNTHESIS OF SILVER NANOPARTICLES USING GLIOCLADIUM ROSEUM (CLONOSTACHYS ROSEA (LINK) SCHROERS, SAMUELS) AND ITS ANTIMICROBIAL EFFICACY AGAINST SELECTED PATHOGENS”

Objective: Antimicrobial efficacy of silver nanoparticles from Gliocladium roseum, culture filtrate (C. F.) and mycelial mat extract (M. E.) against selected pathogens. Methods: Culture filtrate (C. F.) and Mycelial mat extract (M. E.) of Gliocladium roseum were subjected to 10 Mm silver nitrate solution for the synthesis of silver nanoparticles. Formed silver nanoparticles were evaluated via UV-vis spectroscopy and the structural elucidation was done by FT-IR and TEM. Antimicrobial efficacy was tested against bacterial (Salmonella typhi and Klebsiella pneumonia) and fungal (Cladosporium cladosporioides and Alternaria alternata) pathogens. Different nanoparticle concentrations-50, 100, 150 and 200 µl were checked via disc diffusion method. Results: Gliocladium roseum (C. F. and M. E.) on interaction with silver nitrate solution effectively reduced metallic silver exhibiting a colour change from yellow to dark brown within 24 h due to the formation of silver nanoparticles. The UV-vis spectrum of C. F. and M. E. showed maximum absorption peaks at 350-400 nm and 400-450 nm respectively and FT-IR and TEM showed strong N-H bonding and spherical shaped silver nanoparticles with the size of 11-19 nm (C. F.) and 25-38 nm (M. E.). Antimicrobial analysis resulted in efficient inhibitory activity against Salmonella typhi, Klebsiella pneumonia and also showed moderate inhibitory activity against Alternaria alternata and Cladosporium cladopsorioides. Conclusion: The synthesis of silver nanoparticles from fungus Gliocladium roseum is simple, cheap, safe and eco-friendly thus emphasising on large scale scientific application.
The design and development of a digital contact tracing application to better facilitate the tracing of passengers in the event of a biological threat/ pandemic

ABSTRACT With increasing air travel, contagion can spread anywhere in the world within 24 hours. As a result, the potential risk of introduction and spread of infectious disease is on the rise. Recently, we the global spread of the coronavirus disease (COVID-19) showed the potential of a contagion to emerge, spread and effect the health, social and economic life of people globally. Contact tracing represents an important factor in mitigating the global spread of a pandemic. This research in progress paper explores the design and development of a ‘contact tracing’ application in relation to airline passengers in the event of a biological threat or pandemic. The current paper-based method of contact tracing has many limitations that can lead to delayed identification of at-risk passengers and ultimately increased the spread of contagion. The use of a digital contact tracing application provides a method of rapidly collecting passenger contact information.
Sociocultural Adaptation and Program Management Strategies for International Doctoral Students of the “Confucius China Studies Program”

The purpose of this study was to understand the sociocultural adaptation status for international doctoral students of the “Confucius China Studies Program” (CCSP), as well as obtain suggestions from those students to the management of the program. This qualitative study applied an instrumental case study at a research site university in Beijing. Through distributing questionnaires to international students who participated in the program, as well as conducting one-to-one interviews with seven international students and two program management teachers, this study found that the sociocultural adaptation status of the international students of CCSP was generally high. The sociocultural adaptation status for doctoral students of the CCSP was analyzed from five aspects including interpersonal communication, academic performance, personal interest and social participation, environmental adaptation, and language proficiency. The interviewed international students proposed three suggestions to the management of the CCSP, including holding exchange and sharing activities for international doctoral students of the CCSP, compiling CCSP manual for international students of the program, and the establishment of a student writing center. This study also provides implications to administrators of the CCSP, international doctoral students, and policy-makers of this issue. https://orcid.org/0000-0002-2856-5957
The artificial intelligence system in prediction of the prevalence of acute coronary syndromes based on weather conditions

It was shown that different individual weather conditions are associated with the incidence of acute coronary syndromes (ACS). Despite this, the prediction of the number of ACS depending on the weather conditions in the given place and time is not effective to date. We sought to investigate whether the artificial intelligence system might be useful in prediction of the prevalence of ACS based on weather conditions. In this study, data of 159307 consecutive patients obtained from National Health Service registry, hospitalized due to ACS in Lesser Poland Province (province area of 15008 km2, population of 3.4 M in 2014) between 2008 and 2018 have been compared with meteorological conditions collected in the Institute of Meteorology and Water Management from five weather stations scattered across Lesser Poland Province. Because of small sample size in three of them, only data from two stations (Krakow-Balice, n=75565, Tarnow, n=30079) were used for further analysis. In four separate seasons, the number of ACS events in each day was compared with meteorological conditions on a given day and six days before. We analysed weather conditions such as: wind 10 metres above ground (W_10), temperature (T), dew point temperature (T_dp), relative humidity 2 metres above the ground (Hum_2), atmospheric pressure reduced to mean sea level (Pres), atmospheric precipitation (Prec), and 3 hours atmospheric pressure changes (Pres_3h). For all parameters extreme (maximum – max, minimum – min) values and ranges of these parameters in each day were analysed. All data were used in a system based on machine learning (Random Forest), which allowed to create a model that predicted the incidence of ACS and to determine importance of each inputted weather parameter in this prediction. All weather parameters were divided into machine learning data (70%) and test data (30%) to verify functioning of the model. The correlation between real number of ACS and predicted number of ACS for two meteorological stations for spring ranges from 0.69 to 0.71 with confidence intervals (CI) of 0.63–0.77, for summer the correlation was 0.66–0.75 with CI of 0.59–79, for autumn 0.69–0.74 with CI of 0.63–0.79 and for winter 0.69–0.72 with CI 0.63–0.77 (P<0.0001 for each prediction, example of prediction in the Figure 1A). Among all analysed meteorological parameters the most important in the machine learning were range of relative humidity, range of dew point temperature and maximal relative humidity (Figure 1B). Artificial intelligence system seems to be useful in predicting the prevalence of ACS with model based on weather conditions. Figure 1. ACS prediction for summer in Krakow Type of funding source: None
An Environmental Characterization Method for Monocular Vision Obstacle of Rotor Aircraft

Combining the structure of coding and anti-coding in the field of deep learning, we explore a method to represent the complex environment of four rotor aircraft. First, we use this structure to explore the process of dimensionality reduction and reconstruction of high dimensional image data. Second, combining this structure, we use the concept of transposition convolution to propose a network structure for depth distance estimation using monocular vision images. Finally, we get the direct physical feature information used to describe complex environment.
X-ray crystal structure of synthetic REEAl2.07(B4O10)O0.60 (REE = (La, Ce); Ce; Nd) dimetaborates

Abstract Nonstoichiometric REEAl2.07(B4O10)O0.60 (REE = (La, Ce); Ce; Nd) dimetaborates have been crystallized and analyzed by means of single crystal X-ray diffraction. The compounds resulted to be isostructural within hexagonal space group P-62m (n. 189), with the following unit cell parameters: a = 4.6060(6) Å, c = 9.3510(8) Å and V = 171.81(3) Å3; (La, Ce); a = 4.5960(6) Å; c = 9.3170(10) Å and V = 170.44(4) Å3 (Ce); a = 4.5830(7) Å, c = 9.2810(14) Å and V = 168.82(4) Å3 (Nd). The REE cations are surrounded by six oxygen atoms, making up a trigonal prismatic coordination; Al cation is surrounded by five oxygen atoms, resembling a square pyramidal coordination, while the BO4 group displays tetrahedral arrangement. The three-dimensional framework can be described as a mica-like structure packed down crystallographic axis c, with layers of six-membered rings of B tetrahedra alternated by inter-layers REE cations and layers of Al polyhedra. A complex network of REE … O and Al … O interactions concur to stabilize the framework.
Effect of Corrosion Inhibitors Admixtures on Corrosion Rate of Steel Reinforcement in Concrete (Dept.C)

Reinforcement corrosion is the main cause of damage and early failure of reinforced concrete structures. The protection system of embedded steel reinforcement from chloride induced corrosion involves several methods and techniques. One of these methods and techniques is using corrosion inhibitors admixtures (CIA) which added to concrete mix during mixing stage of concrete. These research aims to evaluate these admixtures (Sika Ferrogard®-901) in prevent corrosion of steel in concrete and their effect on concrete properties for fresh and hardened concrete. In this paper (CIA) used with different concrete contents and proportions. In this study, 150-mm concrete cubes specimens with high tensile steel bar grade (36/52) of 10 mm in diameter and 150 mm in length were embedded in each specimen during its casting such that 100 mm was fixed inside the concrete while the reminder 50 mm was kept outside. Three thicknesses of concrete cover were used; 25, 50 and 75 mm. After 28 days of water curing, specimens were transferred to dry for 24 hour, then the specimens were partially submerged in plastic tank filled with 6% NaCl solution Acceleration of corrosion rate test is achieved by continuous electrical current produced from power supply 30 volts for 240 hour, where volts difference was measured in volts between resistance 100 ohm and the reading was record every 12 hour. The corrosion current (Icon in Ampere) was calculated during the accelerated corrosion regime by using ohm's law by knowing measured volts difference and resistance. Faraday's law describes the relationship between section loss and corrosion current. Hence, calculate corrosion rate of steel reinforcement in concrete. The results show that for all mixes the increasing of concrete cover thickness reduces the corrosion rate of steel. Using 5% (CIA) by weight of cement where the optimum dosage of Corrosion inhibitors admixture from experimental tests is 5% by weight of cement reduce corrosion rate by 80 % with no side effect on concrete properties except bond strength decreased by 10%. (CIA) gave best results with concrete mixes which contains 15% silica fume and water to cement ratio 0.35 · (CIA) decreasing concrete cover required to prevent corrosion from 75 mm to 50 mm. (CIA) accelerate setting time of concrete, so it needs a retarded when used with concrete mixes.
Design and Implementation of Network Information Service Platform Based on Microservice Architecture

In this paper, based on the development of network information microservice platform, and according to the business characteristics of the platform, the overall architecture model of the microservice platform was designed. Besides, the system is hierarchically managed by basic equipment area, standard area, hub area, and application service area. Hence, the problems of independent deployment, data transmission sharing, service monitoring, and authority management of the microservice system are solved. Moreover, the system development process, the development efficiency, and the system reliability are also improved. The project which is supplemented by a sound management mechanism implements the framework of service platform based on Spring Cloud technology, establishes the business container of microservice, analyzes the value of the system, and then forms a sustainable optimization system.
The Dominant Nodes Index in Shortest Paths (DNISP) as A Local Measure of Source Looking for the Target in Complex Networks

When there are multiple alternate shortest paths between any two nodes in a complex network, there is a need to know details about the content of the paths and the dominance of the nodes within it, this need comes to maximize, control and speed of the information diffusion. This paper discusses the creation of a new special measure as a local scale for any X node in the network. This measure will give each neighbour of the node X a domination value to access the rest of the network, in other words any nodes included in the shortest path (X,Y) will be given a control value, taking into account the existence of more than one shortest path between (X,Y). Such a measure is called a DNISP, which stands for Dominant Nodes Index in Shortest Paths. The X-node needs to examine all shortest paths that connect it with any other nodes across the ones that are directly associated with it. This measure provides an insight into how information flows between nodes according to dominant values with each node.
Are online job quality quizzes of any value? Selecting questions, maximising quiz completions and estimating biases

Purpose: This paper compares two ways of collecting job quality data in Britain using a common set of questions. One way is through a short quiz taken by a self-selected sample and completed by clicking on a web link www.howgoodismyjob. com. The other way is via an invitation to take part in a long-running survey of working life – the Skills and Employment Survey. The survey takes much longer to complete, is carried out face-to-face and is based on random probability principles.
Prevalence and Phenotypic Impact of Rare Likely Pathogenic Variants in Autism Spectrum Disorder

Background: Copy number variants (CNVs) and single nucleotide variants (SNVs) are sources of risk for autism spectrum disorder (ASD). The distribution of such pathogenic variants in individuals with ASD and the characterization of those who carry such variants versus those who do not are understudied at the population level. We describe a population sample from Sweden, evaluating the distribution of likely pathogenic variants and their impact on medical, neurological, and psychiatric phenotypes.Methods: The genotyped sample consisted of 1,236 children born in Sweden with autistic disorder, a severe form of ASD (International Classification of Diseases, Tenth Revision, code F84.0.) Of these individuals, CNVs were called from 997, while SNVs were called from 808. Results: Out of 997 individuals from whom CNVs were called, 104 (10.4 %) carried one or more likely pathogenic CNV, including 15q11q13 (n=8), 15q13.3 (n=5), 16p13.11 (n=5), 16p11.11 (n=5), 22q11.2 (n=5). Of 808 individuals assessed by whole-exome sequencing, 69 (8.5%) had a likely pathogenic SNV, including in GRIN2B (n = 6), POGZ (n = 5), SATB1 (n=4), DYNC1H1 (n=4), and CREBBP (n=3). Fourteen individuals carried two likely pathogenic CNVs, and 5 carried a likely pathogenic CNV and SNV. Carriers of likely pathogenic CNVs or SNVs were more likely to have intellectual disability (ID), scholastic skill disorders, and epilepsy, with odds ratios of 2.31 (95%CI, 1.55,3.47), 1.98 (95%CI, 1.19,3.21), and 1.63 (95%CI, 1.08,2.44) respectively. Carriers of likely pathogenic CNVs also showed significant increased rates of congenital anomalies. We compared rates of likely pathogenic CNVs, SNVs, and phenotypes from genotyped AD subjects with and without ID: rates were not significantly different between groups. Limitations: As a case-control cohort, we did not have de novo information to aid in classification. More broadly, there were judgment calls involved in identifying likely pathogenic variants. For these reasons, some misclassification is possible. In addition, phenotypes are defined from medical registers, which may lead to underestimates of milder findings.Conclusions: People with ASD who carry likely pathogenic CNVs or SNVs show increased rates of various comorbidities, most prominently ID. Despite the strong association with ID, conditioning on its presence explains little of the variation for other comorbidities and physical traits.
Mental Stress Assessment Using PPG Signal a Deep Neural Network Approach

Due to the pace of modern life and the shift of nature of work from physical to cognitive, mental stress is increasing in every profession. Mental stress has now become a leading cause of work-related illness. There are numerous sedentary occupations, such as those in the IT industry, where individuals are required to work for extended periods of time, leading to stress. Working for extended periods under mental stress can increase the risk of life-threatening diseases like cardiovascular diseases, mental health disorders etc. There is, thus, a requirement for a non-obtrusive tool to detect mental stress. In this work, pulse rate variability (PRV) of 15 subjects during 5 cognitive states (relaxation, deep breathing, and during three mental tasks involving three levels of mental stress) was examined using photoplethysmography (PPG). The result of this study indicates that 18 features (9-time domain and 9 frequency domain) are statistically significant at p < 0.05 as per the Friedman test in 5 cognitive states. The machine-learning algorithm based upon a multi-layer perceptron (MLP) was able to classify with an overall accuracy of 85.1±1.1%. Classification accuracy further improved by using deep neural networks (DNN) to 91±1.1%.