Requirements for the content of calibration procedure for measuring instruments

All instruments have errors that gradually increase over time, which leads to a loss of accuracy of the measurements performed. Calibration is one of the main processes used to establish the accuracy of an instrument. The main task of calibration is to establish a relation between the unknown value of the instrument being calibrated and a standard with a known value and its inherent measurement uncertainty [1]. Calibration is often confused with instrument setting, which is erroneously called "self-calibration". Settings are made to make the necessary changes to the operation of the instrument, and calibration is performed to determine the actual values of the instrument's metrological characteristics.Все приборы имеют погрешности, которые со временем постепенно увеличиваются, что приводит к потере точности проводимых измерений. Калибровка является одним из основных процессов используется для определения точности прибора. Основная задача калибровки состоит в том, чтобы установить связь между неизвестным значением калибруемого прибора и эталоном с известное значение и присущая ему неопределенность измерения [1]. Калибровку часто путают с настройка прибора, которую ошибочно называют «самокалибровкой». Настройки сделаны для того, чтобы необходимые изменения в работе прибора, и калибровка выполняется для определить фактические значения метрологических характеристик прибора

Automation of technological process of canned meat production

Food and raw materials of animal and plant origin contain a significant amount of water (30 - 80%), proteins, fats, carbohydrates, organic acids, biologically active and mineral substances, etc. During storage in natural conditions, they undergo various biochemical, physicochemical and microbiological processes, as a result of which the appearance, taste and nutritional value of food and raw materials deteriorate. This leads to rapid spoilage of products that become unfit for consumption. To increase the duration of storage and prolong the life of food and the use of raw materials have long been used methods of their preservation - salting, drying, cooling and freezing. However, the most reliable method of preservation is to store them in airtight containers after processing for some time at a temperature above 100 ° C (sterilization). Food products sealed in airtight containers and processed for some time at a temperature of about 100 ° C are called canned food. During heat treatment at a temperature of about 100 ° C, denaturation and coagulation of proteins occur, as a result of which the activity of microorganisms is suppressed, enzymes are inactivated, and so on. Hermetic barrier packaging protects sterilized products from the environment. If canned food is properly sterilized and the container has proper chemical resistance and mechanical strength, canned food is stored for a long time even under adverse conditions without significant changes in nutritional and biological value. The optimal storage regime for canned meat is a temperature of 1 - 5 ° C and a relative humidity of not more than 75% [1]. Canned food has a pleasant taste, aroma, appearance, convenient for transportation and consumption.Пищевые продукты и сырье животного и растительного происхождения содержат значительное количество воды (30 - 80%), белки, жиры, углеводы, органические кислоты, биологически активные и минеральные вещества и др. При хранении в естественных условиях они подвергаются различным биохимическим, физико-химические и микробиологические процессы, в результате которых внешний вид, вкус и пищевая ценность продуктов питания и сырья ухудшается. Это приводит к быстрой порче продукты, ставшие непригодными к употреблению. Для увеличения срока хранения и продления жизнь продуктов питания и использование сырья уже давно используются методы их консервация - соление, сушка, охлаждение и заморозка. Однако самым надежным методом консервация заключается в хранении их в герметичных контейнерах после обработки в течение некоторого времени в температура выше 100°С (стерилизация). Пищевые продукты упакованы в герметичные контейнеры и обработанные некоторое время при температуре около 100°С, называются консервами. В течение термообработка при температуре около 100°С, денатурация и коагуляция белков происходят, в результате чего активность микроорганизмов подавляется, ферменты инактивирован и так далее. Герметичная барьерная упаковка защищает стерилизованные продукты от Окружающая среда. Если консервы должным образом стерилизованы и контейнер имеет надлежащее химическое устойчивостью и механической прочностью, консервы долго хранятся даже при неблагоприятных условиях без существенных изменений пищевой и биологической ценности. Оптимальное хранение режим для мясных консервов - температура 1 - 5°С и относительная влажность не более 75% [1]. Консервы имеют приятный вкус, аромат, внешний вид, удобны для транспортировки. и потребление

Analysis of quality measure that quality-relevant of bakery products

Introduction. Bakery products are the main food products, which are in the first group (Food products for mass consumption) in the systematization of the main types of food products according to their purpose. Ukraine produces a lot of bakery products, the number of different products related to bakery products exceeds 300. Bakery products include such products as: various types of loaves and bread, braids, bagels, rolls, etc. In this paper, we will consider the example of making a loaf "cut". According to DSTU-P 4587: 2006 "Loaf" "sliced" consists of: wheat flour of the highest grade, prepared drinking water, baking yeast, table salt, white crystalline sugar, skimmed milk powder, table margarine "Special milk" 82% fat (sunflower oil) , drinking water, salt) [1]. As a rule, the main technological processes of bakery production are mechanized. Consider the production of loaf and the processes that accompany it. Description of the technological process and the choice of controlled parameters

Microscopy-BIDS: An extension to the brain imaging data structure for microscopy data

The Brain Imaging Data Structure (BIDS) is a specification for organizing, sharing, and archiving neuroimaging data and metadata in a reusable way. First developed for magnetic resonance imaging (MRI) datasets, the community-led specification evolved rapidly to include other modalities such as magnetoencephalography, positron emission tomography, and quantitative MRI (qMRI). In this work, we present an extension to BIDS for microscopy imaging data, along with example datasets. Microscopy-BIDS supports common imaging methods, including 2D/3D, ex/in vivo, micro-CT, and optical and electron microscopy. Microscopy-BIDS also includes comprehensible metadata definitions for hardware, image acquisition, and sample properties. This extension will facilitate future harmonization efforts in the context of multi-modal, multi-scale imaging such as the characterization of tissue microstructure with qMRI

Improving functional magnetic resonance imaging reproducibility

BACKGROUND: The ability to replicate an entire experiment is crucial to the scientific method. With the development of more and more complex paradigms, and the variety of analysis techniques available, fMRI studies are becoming harder to reproduce. RESULTS: In this article, we aim to provide practical advice to fMRI researchers not versed in computing, in order to make studies more reproducible. All of these steps require researchers to move towards a more open science, in which all aspects of the experimental method are documented and shared. CONCLUSION: Only by sharing experiments, data, metadata, derived data and analysis workflows will neuroimaging establish itself as a true data science

Toward standard practices for sharing computer code and programs in neuroscience

Computational techniques are central in many areas of neuroscience and are relatively easy to share. This paper describes why computer programs underlying scientific publications should be shared and lists simple steps for sharing. Together with ongoing efforts in data sharing, this should aid reproducibility of research.This article is based on discussions from a workshop to encourage sharing in neuroscience, held in Cambridge, UK, December 2014. It was financially supported and organized by the International Neuroinformatics Coordinating Facility (http://www.incf.org), with additional support from the Software Sustainability institute (http://www.software.ac.uk). M.H. was supported by funds from the German federal state of Saxony-Anhalt and the European Regional Development Fund (ERDF), Project: Center for Behavioral Brain Sciences

The Open Brain Consent: Informing research participants and obtaining consent to share brain imaging data

Having the means to share research data openly is essential to modern science. For human research, a key aspect in this endeavor is obtaining consent from participants, not just to take part in a study, which is a basic ethical principle, but also to share their data with the scientific community. To ensure that the participants' privacy is respected, national and/or supranational regulations and laws are in place. It is, however, not always clear to researchers what the implications of those are, nor how to comply with them. The Open Brain Consent (https://open-brain-consent.readthedocs.io) is an international initiative that aims to provide researchers in the brain imaging community with information about data sharing options and tools. We present here a short history of this project and its latest developments, and share pointers to consent forms, including a template consent form that is compliant with the EU general data protection regulation. We also share pointers to an associated data user agreement that is not only useful in the EU context, but also for any researchers dealing with personal (clinical) data elsewhere

SciPy 1.0: fundamental algorithms for scientific computing in Python.

SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments

A multimodal cell census and atlas of the mammalian primary motor cortex

ABSTRACT We report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex (MOp or M1) as the initial product of the BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties, and cellular resolution input-output mapping, integrated through cross-modal computational analysis. Together, our results advance the collective knowledge and understanding of brain cell type organization: First, our study reveals a unified molecular genetic landscape of cortical cell types that congruently integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a unified taxonomy of transcriptomic types and their hierarchical organization that are conserved from mouse to marmoset and human. Third, cross-modal analysis provides compelling evidence for the epigenomic, transcriptomic, and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types and subtypes. Fourth, in situ single-cell transcriptomics provides a spatially-resolved cell type atlas of the motor cortex. Fifth, integrated transcriptomic, epigenomic and anatomical analyses reveal the correspondence between neural circuits and transcriptomic cell types. We further present an extensive genetic toolset for targeting and fate mapping glutamatergic projection neuron types toward linking their developmental trajectory to their circuit function. Together, our results establish a unified and mechanistic framework of neuronal cell type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties