Safety learning in anxiety, Pavlovian conditioned inhibition and Covid concerns

Experimental studies of fear conditioning have identified the effectiveness of safety signals in inhibiting fear and maintaining fear-motivated behaviours. In fear conditioning procedures, the presence of safety signals means that the otherwise expected feared outcome will not now occur. Differences in the inhibitory learning processes needed to learn safety are being identified in various psychological and psychiatric conditions. However, despite early theoretical interest, the role of conditioned inhibitors as safety signals in anxiety has been under-investigated to date, in part because of the stringent test procedures required to confirm the demonstration of conditioned inhibition as such. Nonetheless, the theoretical implications of an inhibitory learning perspective continue to influence clinical practice. Moreover, our understanding of safety signals is of additional importance in the context of the increased health anxiety and safety behaviours generated by the Covid-19 pandemic.

Development and testing of procedures for detecting HPV 6 and HPV 16 DNA in water samples

The present study aims to develop and test procedures for detecting the DNA of dangerous human papillomaviruses (HPV) types 6 and 16 in water samples. The conserved segments of HPV 6 L1 and HPV 16 L1 nucleic acid sequences were studied using bioinformatic methods with the help of the NCBI (National Center for Biotechnology Information) database and the BioEdit program. A total of 135 nucleic acid sequences of HPV6 L1 and 945 nucleic acid sequences of HPV16 L1 were examined. Five pairs of specific primers were developed for the identified conserved segments of nucleic acid sequences using specialized programs (PerlPrimer v.1.1.21, FastPCR 6.6, and Primer3Plus). In addition, several procedures for collecting samples from various water bodies located near Listvyanka settlement (Lake Baikal) were tested. The samples were subjected to comprehensive purification from insoluble particles and bacterial contamination to be tested for the presence of HPV DNA via PCR analysis using primers complementary to the nucleic acid sequences of HPV6 L1 and HPV16 L1. The conducted studies revealed HPV 6 and HPV 16 DNA in the water samples. Due to the use of the developed and tested procedures for collecting and examining samples from various water sources in the Baikal Natural Territory followed by a PCR analysis, it was possible to detect the presence of dangerous viruses. The proposed procedure of testing water samples for the presence of HPV can be useful in developing effective monitoring of water bodies and wastewater both in Baikal and other regions.

Process optimization for the production of biodiesel from Azolla Microphylla oil and its fuel characterization

The most competent and operative use of renewable feedstock is super critical for the production of biodiesel which has increased attention worldwide pertaining to aquatic fern Azolla. Maximizing the biodiesel yield by optimizing the process parameters of the low-frequency ultrasonic energy-assisted transesterification process of Azolla oil is the need of the hour for minimizing the production cost of biodiesel. Response Surface Methodology (RSM) was applied using central composite rotatable design (CCRD) to find the best optimum reaction parameters for this transesterification process. The optimized reaction parameters arrived from the design of experiments were as following: methanol/Azolla oils molar ratio (A) = 6.49 mole/mole, KOH catalyst concentration (B) = 1.69 (weight% of oil), reactiion time (C) = 34.74 min and reaction temperature (D) = 38.87°C. The best higher theoretical predicted Azolla Fatty Acid Methyl Ester (FAME) yield was Y = 99.76% which is in well coincidence with the actual yield. The extracted Azolla biodiesel was tested for various fuel properties with standard test procedures and found to be in agreement with various Biodiesel standards and the results are promising in terms of utilizing Azolla oil as an inexhaustible and potentially economical source of biodiesel.

Stress analysis of double-walled pipes undergone mechanical drawing process

Double-walled metal pipes are important components for heat exchange and liquid transportation. They can be manufactured by mechanical drawing of two concentric pipes. In this work, a mechanical model is developed to analyze the stress state evolution during the manufacturing process, and the criterion for forming the double-walled pipe was given under the ideal elastoplastic and thick-walled assumptions. The model also encompasses the results deduced under the thin-walled assumption. Numerical simulations confirmed that the accuracy of the analytical model was within 5%. The application on actual steel materials with various parameters varied, including the wall thickness and initial gap, was analyzed. This work can provide theoretical support to industrial manufacturing procedures and help to reduce costs by eliminating required test procedures.

Standardisation efforts of ISO/TC 261 “Additive Manufacturing”: 17th plenary meeting of ISO/TC 261 “Additive Manufacturing”

The main objective of ISO/TC 261 is to standardise the processes of additive manufacturing, the process chains (data, materials, processes, hard- and software, applications), test procedures, quality parameters, supply agreements, environment, health and safety, fundamentals and vocabularies. This section provides readers with news regarding standardisation efforts of ISO/TC 261.

What Makes Babies Musical? Conceptions of Musicality in Infants and Toddlers

Despite major advances in research on musical ability in infants, relatively little attention has been paid to individual differences in general musicality in infants. A fundamental problem has been the lack of a clear definition of what constitutes “general musicality” or “musical ability” in infants and toddlers, resulting in a wide range of test procedures that rely on different models of musicality. However, musicality can be seen as a social construct that can take on different meanings across cultures, sub-groups, and individuals, and may be subject to change over time. Therefore, one way to get a clearer picture of infant musicality is to assess conceptions of musicality in the general population. Using this approach, we surveyed 174 German adults, asking about their view and conceptions regarding behaviors that characterize a musical child under 3 years. Based on previous studies on adult and child musicality, we designed a survey containing 41 statements describing musical behaviors in children. Participants were asked to rate how indicative these behaviors were of musicality in infants and toddlers. PCA analysis revealed 4 components of musical abilities and behaviors in under-3-year-olds: Musical Communication, Enthusiasm and Motivation, Adaptive Expressiveness, and Musical Abilities as traditionally defined. Professional background and musical expertise of the respondents did not significantly influence participants’ conceptions. Our results suggest that, in order to capture musicality in young children, a wider range of skills and observable behaviors should be taken into account than those assessed by traditional musical ability tests for young children.

Field Tests on Bearing Characteristics of Large-Diameter Combined Tip-and-Side Post Grouted Drilled Shafts

This paper presents a field study on the axial behavior of four large-diameter drilled shafts embedded in coarse sand. The grouting and loading test procedures were reported. The bearing capacity of shafts (TS1 and TS2) and grouted drilled shafts (TS3 and TS4) were herein determined by the bi-directional static test and top-down load test, respectively. The enhancement mechanism of bearing characteristics of the grouted shafts was discussed in detail. The test results indicate that the bearing characteristics and load transfer mechanisms of the test shafts were significantly affected by the quantity of pressurized cement slurry and the mechanical properties of the soil surrounding the shafts. Furthermore, the tip resistance of shaft can be mobilized more rapidly and fully after grouting, the side and tip resistance are mobilized in a more synchronized and coordinated manner due to the pre-mobilization of the grouted cement. Additionally, the standard penetration test (SPT) prediction model was introduced to calculate and predict the SPT blow counts of soil after grouting. The results show that the post grouting has a more obvious improvement on the strength of cohesionless soil.

Detecting Process Anomalies in the GMAW Process by Acoustic Sensing with a Convolutional Neural Network (CNN) for Classification

Today, the quality of welded seams is often examined off-line with either destructive or non-destructive testing. These test procedures are time-consuming and therefore costly. This is especially true if the welds are not welded accurately due to process anomalies. In manual welding, experienced welders are able to detect process anomalies by listening to the sound of the welding process. In this paper, an approach to transfer the “hearing” of an experienced welder into an automated testing process is presented. An acoustic measuring device for recording audible sound is installed for this purpose on a fully automated welding fixture. The processing of the sound information by means of machine learning methods enables in-line process control. Existing research results until now show that the arc is the main sound source. However, both the outflow of the shielding gas and the wire feed emit sound information. Other investigations describe welding irregularities by evaluating and assessing existing sound recordings. Descriptive analysis was performed to find a connection between certain sound patterns and welding irregularities. Recent contributions have used machine learning to identify the degree of welding penetration. The basic assumption of the presented investigations is that process anomalies are the cause of welding irregularities. The focus was on detecting deviating shielding gas flow rates based on audio recordings, processed by a convolutional neural network (CNN). After adjusting the hyperparameters of the CNN it was capable of distinguishing between different flow rates of shielding gas.