Recent technical advances in the stem cell field have enabled the in vitro generation of complex structures resembling whole organs termed organoids. Most of these approaches employ culture systems that allow stem cell-derived or tissue progenitor cells to self-organize into three-dimensional (3D)-structures. Since organoids can be grown from various species, organs and from patient-derived induced pluripotent stem cells, they create significant prospects for modelling development and diseases, for toxicology and drug discovery studies, and in the field of regenerative medicine. Here, we report on intestinal stem cells, organoid culture, organoid disease modeling, transplantation, current and future uses of this exciting new insight model to veterinary medicine field.

From gene expression studies to identifying microbes quantitative polymerase chain reaction (qPCR) is widely used in research and medical diagnostics. In transmittable diseases like the Ebola outbreak in West Africa (2014-2016), or the present SARS-CoV2 pandemic qPCR plays a key role in the detection of infected patients. Although the technique itself is decades old with reliable approaches (eg. TaqMan essay) in the diagnosis of pathogens many people showed distrust in it during the SARS-CoV2 outbreak. This came mainly from not understanding or misunderstanding the principles of qPCR. This situation motivated us to design a simple laboratory practical class, in which students have opportunities to understand the underlying principles of qPCR and its advantages in microbiological diagnosis. Moreover, during the exercise, students can develop skills such as handling experimental assays, and the ability to solve problems, discuss their observations. Finally, this activity brings them closer to the clinical practice and they can see the impact of the science on real life. The class is addressed to undergraduate students of biological sciences.

The nature of fluid mechanics makes experimentation an important part of a course taught in the subject. Presented here is the application of a novel, large scale multidisciplinary model of practical education in a fluids engineering laboratory. Advantages of this approach include efficiencies through economy of scale leading to better pedagogy for students. The scale justifies dedicated academic resources to focus on developing laboratory classes and giving specific attention to designing activities that meet learning outcomes. Four examples of applying this approach to fluids mechanics experiments are discussed, illustrating tactics that have been developed and honed through many repeated instances of delivery. “The measurement lab” uses a flow measurement context to teach identifying and managing general experimental uncertainty. New students, unfamiliar with fluid mechanics are guided through a process to gain understanding that can be applied to all future experimental activities. The “pressure loss in pipes” lab discusses the advantage and process for sharing equipment and teaching resources between multiple cohorts. The provision for students is adapted for context, such as the degree program or year of study. The “weirs big and small” lab provides a methodology to teach the power of dimensional analysis to mechanical engineers using a field of fluid mechanics that is outside their usual theoretical studies. Finally, the “spillway design” lab discusses mechanisms to deliver student independent, open ended experiments at scale, without excessive staff resource requirement.

At the start of 2020 the rapid onset of the coronavirus pandemic forced higher education institutions across the world to pivot from face to face to remote teaching. For teaching methods that involve the transmission and dissemination of verbal/visual information between academic staff and students, video technologies provided immediate methods to respond to the restricted access to campus. Practical activities, that usually involve interaction with equipment, presented a greater challenge to adapt for remote delivery. With restrictions on higher education being partially lifted, many institutions worldwide intend to offer blended learning, prioritizing in-person activities that are troublesome to deliver online, such as practicals. Social distancing measures are reducing capacity and placing increased pressure on space, creating a need to optimise limited time students have in the lab and strategies to determine which activities can best utilize this limited resource. Time is constrained, leaving little opportunity to make radical changes to learning and teaching structures. In this publication, The department of Mulicdipalnary Engineering Education (MEE) at the University of Sheffield, utilise their experiences in practical teaching to provide simple, implementable ideas for blended practicals which maximize students’ learning and experiences within the envelope of available resources.

Multidisciplinary Engineering Education (MEE) at the University of Sheffield is dedicated to delivering, at scale, practical teaching to students in the Faculty of Engineering. The COVID-19 pandemic initiated the sudden suspension of face to face teaching required MEE to translate over 600 in-lab practicals to a remote delivery format. With little opportunity to coordinate, academic staff independently adopted a variety of tactics to ensure practical learning outcomes were maintained. Following the reactive response, a proactive reflection was conducted and six categories of tactics for remote practicals have been established. These categories are Provide digital artefacts; Simulated practicals; Synchronous remote participation; Asynchronous participation by proxy; Perform procedure in alternative environment; Remote staff support. The advantages and drawbacks of each of these categories is discussed and it is suggested which tactics are appropriate for particular learning outcomes or operational and environmental outcomes of equivalent in-lab practicals. Further work to comprehensively align outcomes to tactics is proposed and lasting benefit from the analysis can be realized by adopting a principle of Remote Enhanced Practicals.

Mathematical models of cognition measure individual differences in cognitive processes, such as processing speed, working memory capacity, and executive functions, that may underlie general intelligence. As such, cognitive models allow identifying associations between specific cognitive processes and tracking the effect of experimental interventions aimed at the enhancement of intelligence on mediating process parameters. Moreover, cognitive models provide an explicit theoretical formalization of theories regarding specific cognitive process that may help overcoming ambiguities in the interpretation of fuzzy verbal theories. In this paper, we give an overview of the advantages of cognitive modeling in intelligence research and present models in the domains of processing speed, working memory, and selective attention that may be of particular interest for intelligence research. Moreover, we provide guidelines for the application of cognitive models in intelligence research, including data collection, the evaluation of model fit, and statistical analyses.

The paper investigates the issues of transliteration of Russian toponyms in a city environment and studies the efficiency of the Technical Reference Manual for the Standardization of Geographical Names published by the United Nations group of experts. The paper demonstrates the feasibility of the UN and Russian official transliteration standards and compares the suggested theoretical models with the practical applications found on the street signs, labels, maps, and other sources of navigation. The author presents a comprehensive account of practical transcription methods used in Moscow and offers a solution to a number of issues and discrepancies between popular transliteration models and their real-life application.

We discuss some of the fundamental practical limitations of the Fluctuation-Enhanced Sensing of odors and gases. We address resolution, measurement speed, reproducibility, memory and other problems such as humidity. Various techniques and ideas are presented to overcome these problems. Circuit solutions are also discussed.

This study aimed to identify the most relevant factors of absenteeism in the perception of nursing technicians from a regional reference hospital in Brazil. A cross-sectional study, based on a case study, was conducted from August 2018 to July 2021, with 324 nursing technicians from a Brazilian macroregional reference hospital in Northwestern Ceará. Data were collected through Google Forms® via the Scale of Factors of Work Absenteeism (EFAL). For data analysis, the overall mean and means of the four EFAL factors were calculated. The individuals were grouped by rating level and data were presented descriptively. The results showed that fatigue, low pay, work overload, need to resolve unpostponable personal/family bureaucratic matters, and need for time to continue/post-graduate education were the main causes of absenteeism. In general, nursing technicians' perceptions varied between low and medium relevance to the factors that contributed to work absenteeism. We can associate these results to the low frequency of absen-teeism among the professionals of the institution.

The Covid-19 pandemic is a tragedy for those who have been hard hit worldwide. At the same time, it is also a test of concepts and practices of what good care is and requires, and how quality of care can be accounted for. In this paper, we present our Care-Ethical Model of Quality (CEMQ) and apply it to the case of residential care for older people in the Netherlands during the Covid-19 pandemic. Instead of thinking about care in healthcare and social welfare as a set of separate care acts, we think about care as a complex practice of relational caring, crossed by other practices. Instead of thinking about professional caregivers as functionaries obeying external rules, we think about them as practically wise professionals. Instead of thinking about developing external quality criteria and systems, we think about cultivating (self-)reflective quality awareness. Instead of abstracting from societal forces that make care possible but also limit it, we acknowledge them and find ways to deal with them. Based on these critical insights, the CEMQ model can be helpful to describe, interrogate, evaluate, and improve existing care practices. It has four entries: (i) the care receiver considered from their humanness, (ii) the caregiver considered from their solicitude, (iii) the care facility considered from its habitability and (iv) the societal, institutional and scholarly context considered from the perspective of the good life, justice and decency. The crux is enabling all these different entries with all their different aspects to be taken into account. In Corona times this turns out to be more crucial than ever.

(1) The article is devoted to the development of a theoretical and algorithmic basis for numerical modeling of the spontaneous potential method (SP) as applied to the study of sandy-argillaceous reservoirs. (2) In terms of coupled flows, we consider a physical-mathematical model of SP signals from an electrochemical source, with regard to the case of fluid-saturated shaly sandstone. (3) An algorithm for 2D finite-element modeling of SP signals was developed and implemented in software, along with its internal and external testing with analytical solutions. The numerical SP modeling was carried out, with determining the dependences on the reservoir thickness and porosity, the amount of argillaceous material and the type of minerals. We performed a comparative analysis of the simulated and field SP data, using the results of laboratory core examinations taken from wells in a number of fields in the Latitudinal Ob Region of Western Siberia. (4) The results of the study may be used either for the development of the existing SP techniques, by providing them with a consistent computational model, or for the design of new experimental approaches.

Blockchain technology has been gaining great interest from a variety of sectors including healthcare, supply chain, and cryptocurrencies. However, Blockchain suffers from its limited ability to scale (i.e. low throughput and high latency). Several solutions have been proposed to tackle this. In particular, sharding proved that it is one of the most promising solutions to Blockchain’s scalability issue. Sharding can be divided into two major categories: (1) Sharding-based Proof-of-Work (PoW) Blockchain protocols, and (2) Sharding-based Proof-of-Stake (PoS) Blockchain protocols. The two categories achieve good performances (i.e. good throughput with a reasonable latency), but raise security issues. This article focuses on the second category. In this paper, we start by introducing the key components of sharding-based PoS Blockchain protocols. Then, we briefly introduce two consensus mechanisms, namely PoS and practical Byzantine Fault Tolerance (pBFT), and discuss their use and limitations in the context of sharding-based Blockchain protocols. Next, we provide a probabilistic model to analyze the security of these protocols. More specifically, we compute the probability of committing a faulty block and measure the security by computing the number of years to fail. Finally, we evaluate the effectiveness of the proposed model via numerical analysis.

Management of crowding at subway platform is essential to improving services, preventing train delays and ensuring passenger safety. Establishing effective measures to mitigate crowding at platform requires accurate estimation of actual crowding levels. At present, there are temporal and spatial constraints since subway platform crowding is assessed only at certain locations, done every 1~2 years, and counting is performed manually Notwithstanding, data from smart cards is considered real-time big data that is generated 24 hours a day and thus, deemed appropriate basic data for estimating crowding. This study proposes the use of smart card data in creating a model that dynamically estimates crowding. It first defines crowding as demand, which can be translated into passengers dynamically moving along a subway network. In line with this, our model also identifies the travel trajectory of individual passengers, and is able to calculate passenger flow, which concentrates and disperses at the platform, every minute. Lastly, the level of platform crowding is estimated in a way that considers the effective waiting area of each platform structure.

The paper presents an analysis of the latest developments in the field of stereo vision in the low-cost segment, both for prototypes and for industrial designs. We described the theory of stereo vision and presented information about cameras and data transfer protocols and their compatibility with various devices. The theory in the field of image processing for stereo vision processes is considered and the calibration process is described in detail. Ultimately, we presented the developed stereo vision system and provided the main points that need to be considered when developing such systems. The final, we presented software for adjusting stereo vision parameters in real-time in the python language in the Windows operating system.

The use of New-age (Nano) Modified Emulsions (NME) for the stabilisation of marginal materials for use in the upper-pavement layers of roads have been proven in laboratories, through Accelerated Pavement Tests (APT) and in practice. In addition, material design methods have been developed based on the scientific analysis of granular material mineralogy and the chemical interaction with the binder to design a material compatible NME stabilising agent for naturally available (often marginal) materials. However, the introduction of any new disruptive technology in a traditionally well-established industry, such as the road construction industry, is usually associated with considerable resistance. This is especially relevant when the new technology enables the use of granular materials traditionally considered to be of an unacceptable quality in combination with relatively new concepts such as New-age (Nano) Modified Emulsions (NME). In practice, few road construction projects are without any problems. The introduction of new-technologies obviously makes it an easy target to blame for any non-related problem that may arise during construction. This article aims to assist in pre-empting, recognising, preventing and resolving material or non-material related construction problems through the correct identification of the cause of the problem and recommending the best, most cost-effective way to correct any deficiencies on site.