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The question of ‘identity’ is being questioned and debated in modern social theory. One way of life is giving one identity and another way of life is giving another identity, which leads to the identity crisis. The formation and transformation of identity is really a matter of concern and introspection in today’s world. As Mercer (1990, Identity: Community, Culture, Difference, 43–71, London: Lawrence & Wishart), observes ‘Identity only becomes an issue when it is in crisis, when something assumed to be fixed, coherent and stable is displaced by the experience of doubt and uncertainty’. The identities of a migrant and to identify who is a migrant are to be answered and analysed in different contexts. Also, it extends the idea of life world of migrants hinting at the complex identity in a new space like Hindustan Aeronautics Limited. The main purpose of this article is to investigate the migrant employees’ perception and construction of multiple identities for each other in their everyday life. Their everyday negotiation and confrontation with respect to identity constructions have been focused on and discussed.

An experiment in teaching students to use the literature to devise and defend a plan for novel research is presented as part of a graduate-level course in heterocyclic chemistry. Students in three successive iterations of the course completed an assignment during which they were assigned novel heterocyclic cores that were selected by varying or relocating the heteroatoms of a known drug. They were then asked to identify potential research areas related to their assigned cores and to determine whether the structures containing these cores were likely to have practical applications. The students presented their results as though they were a collaborative research group in an industrial setting requesting funding for future research. A full description of the assignment and a summary of the student outcomes and ideas for future development are discussed.

A common source of reduced productivity and lost work time in the industrial setting is musculoskeletal discomfort in the feet, knees, hips, and low back. Even when working identical job posts, these symptoms can vary widely between employees, and could potentially be caused by intrinsic foot biomechanics coupled with long-term standing activities. Therefore, to prevent injury and reduce daily discomfort, onesize-fits-all approaches such as anti-fatigue mats or off-the-shelf shoe insoles may be less effective than treating each employee’s specific biomechanical traits. The Quadrastep System is a prefabricated, semi-custom shoe insert system that bridges the gap between more expensive, fully customized orthotics and off-the-shelf options. We studied the effectiveness of the system in a large manufacturing plant by assessing and providing Quadrastep inserts to 28 volunteers. After 2 months of daily wear, 94% of these volunteers said they received some benefit from the inserts, while 52% reported full resolution of daily symptoms.

Software refactoring is an approach that aims to improve software system quality by restructuring its internal design without altering the functionality of the software system. The software refactoring has gained comprehensive attention from the research community in software engineering since its emerging in 1999. Empirical studies were carried out to investigate whether the software refactoring indeed can achieve improvement in the software system quality. It is widely believed that refactoring has a favorable quality impact. However, several researchers have opposed this belief. This paper presents a systematic literature review (SLR) of the empirical studies that have been conducted in the industrial setting. Twenty studies were chosen and analyzed in depth as primary studies.The objectives of this SLR are to identify the refactoring techniques examined, and software quality attributes investigated as well as to analyze the connection between the refactoring techniques and the software quality attributes based on the selected empirical studies to understand the situation. The findings showed a lack of empirical research on the effect of the refactoring on software quality. Additionally, the relationship between the refactoring techniques and software quality attributes is unclear. Thus, several recommendations have been proposed to address these gaps.

The feasibility of using deep learning techniques in industrial cold forging for fault detection was investigated. In this work, vibration data were collected from an industrial setting to detect m...

This paper describes the application of logistic classification for tool life modeling and prediction in an industrial setting using shop floor data. Tool life is treated as a classification problem since tool wear can only be measured at the time of tool replacement in a production environment. Laboratory tool wear experiments are used to simulate shop floor wear data by two states: not worn (class 0); and worn (class 1). To incorporate non-linearity in logistic classification, a log-transformation of input features is performed. The logistic classification approach, results, and interpretability of the logistic model are presented.

The purpose of this research is to investigate the influence of thermal conduction on the stretching behaviour of core spandex cellulosic fabrics. Thermal conduction was carried out with precious temperature so that the desired stretching behaviour of core spandex cellulosic fabric was achieved. Three nomenclature of core spandex cellulosic fabric of different spandex content with same weight, weave, width and thickness were used in this research for experimentation. Thermal conductivity of the nomenclature was investigated using a stenter machine in contradiction to varied temperature and industrial setting of the machine along with the thermal conductivity constant of fabrics. Temperature started from 160 °C and extended to 200 °C was conducted on clothes with a stenter machine named “Monforts Montex 8500”. The influences of thermal conduction on core spandex cellulosic yarns were assessed using projection microscope “Projectina DMM 2000”. Application of temperature on core spandex cellulosic fabrics closely attached the cotton fibre to elastane with improved stability, consequently stretching behaviour such as stretch, growth and recovery were controlled with specific growth values. Overheat spoiled and weakened some of the spandex filaments thus, recovery properties were fallen down after a certain temperature point. This research opens probable ways for the scholars to further study in this field.

The aim of this paper is to present numerous heat equations and also to measure the thermal conductivity of fabrics using heat equations. Five types of cotton spandex woven fabrics of different spandex content were used in this research for experimentation. These fabrics had different thickness, but same weave and width so that the accurate thermal conduction values were measured. Thermal conductivity of the clothes was measured with heat equation stated underneath the paper. A stenter machine named “Montex Stenter Frame 6500” was used in this research for heat setting the clothes. Different temperature ranged from 160 °C to 220 °C was applied on clothes using this stenter machine with varied industrial setting. The findings of this paper are practice based and the outcomes are advantageous to the personnel involved in textile industries who are in charge of heat setting the clothes and to measuring of their thermal conductivity values. This research opens possible ways for the scholars to further study in this field.

Ensuring the geometric accuracy of 3D printed parts has proven to be a significant challenge. A recent body of work has developed strategies for using statistical modeling and machine learning to learn from shape accuracy data of past prints to predict and compensate for errors in future prints. Unfortunately, this approach faces a number of challenges that make it difficult to translate from theory to industrial practice. This paper addresses these challenges by proposing a framework for a distributed system through which this modeling methodology could be deployed in an industrial setting. Further, a prototype of this system is illustrated.

Interactions between ultrashort laser pulses with intensities larger than 1013 W/cm2 and solids during material processing can lead to the emission of X-rays with photon energies above 5 keV, causing radiation hazards to operators. A framework for inspecting X-ray emission hazards during laser material processing has yet to be developed. One requirement for conducting radiation protection inspections is using a reference scenario, i.e., laser settings and process parameters that will lead to an almost constant and high level of X-ray emissions. To study the feasibility of setting up a reference scenario in practice, ambient dose rates and photon energies were measured using traceable measurement equipment in an industrial setting at SCHOTT AG. Ultrashort pulsed (USP) lasers with a maximum average power of 220 W provided the opportunity to measure X-ray emissions at laser peak intensities of up to 3.3 × 1015 W/cm2 at pulse durations of ~1 ps. The results indicate that increasing the laser peak intensity is insufficient to generate high dose rates. The investigations were affected by various constraints which prevented measuring high ambient dose rates. In this work, a list of issues which may be encountered when performing measurements at USP-laser machines in industrial settings is identified.

User experience (UX) is a quality aspect that considers the emotions evoked by the system, extending the usability concept beyond effectiveness, efficiency, and satisfaction. Practitioners and researchers are aware of the importance of evaluating UX. Thus, UX evaluation is a growing field with diverse approaches. Despite various approaches, most of them produce a general indication of the experience as a result and do not seek to capture the problem that gave rise to the bad UX. This information makes it difficult to obtain relevant results to improve the application, making it challenging to identify what caused a negative user experience. To address this gap, we developed a UX evaluation technique called UX-Tips. This paper presents UX-Tips and reports two empirical studies performed in an academic and an industrial setting to evaluate it. Our results show that UX-Tips had good performance in terms of efficiency and effectiveness, making it possible to identify the causes that led to a negative user experience, and it was easy to use. In this sense, we present a new technique suitable for use in both academic and industrial settings, allowing UX evaluation and finding the problems that may lead to a negative experience.

The research field of multimodal interactions has been extremely good at evolving to address new challenges over the years. Those challenges can be expressed in terms of properties, in terms of technologies and devices and in terms of context of use. However, research on Multimodal Interactions has overlooked Safety and Dependability aspects and we argue that this is the reason why deployment of multimodal interactions in industrial setting is below the expected level considering their unquestionable benefits. This Blue Sky paper analyses ICMI contributions on safety and dependability over the years and highlights both research challenges and contributions from other disciplines that could foster research on these aspects and favor deployment of multimodal interactions in industrial and critical contexts.

Background Growing industrial use of carbon nanotubes and nanofibers (CNT/F) warrants consideration of human health outcomes. CNT/F produces pulmonary, cardiovascular, and other toxic effects in animals along with a significant release of bioactive peptides into the circulation, the augmented serum peptidome. While epidemiology among CNT/F workers reports on few acute symptoms, there remains concern over sub-clinical CNT/F effects that may prime for chronic disease, necessitating sensitive health outcome diagnostic markers for longitudinal follow-up. Methods Here, the serum peptidome was assessed for its biomarker potential in detecting sub-symptomatic pathobiology among CNT/F workers using label-free data-independent mass spectrometry. Studies employed a stratified design between High (> 0.5 µg/m3) and Low (3) inhalable CNT/F exposures in the industrial setting. Peptide biomarker model building and refinement employed linear regression and partial least squared discriminant analyses. Top-ranked peptides were then sequence identified and evaluated for pathological-relevance. Results In total, 41 peptides were found to be highly discriminatory after model building with a strong linear correlation to personal CNT/F exposure. The top-five peptide model offered ideal prediction with high accuracy (Q2 = 0.99916). Unsupervised validation affirmed 43.5% of the serum peptidomic variance was attributable to CNT/F exposure. Peptide sequence identification reveals a predominant association with vascular pathology. ARHGAP21, ADAM15 and PLPP3 peptides suggest heightened cardiovasculature permeability and F13A1, FBN1 and VWDE peptides infer a pro-thrombotic state among High CNT/F workers. Conclusions The serum peptidome affords a diagnostic window into sub-symptomatic pathology among CNT/F exposed workers for longitudinal monitoring of systemic health risks. Graphical abstract

The ambition to extend material recycling from end-of-life electric and electronic products seems to lead to an unavoidable trade-off between circularity maximisation and quality concerns. However, optimized pre-treatment can help to assure that both polymer fraction compatibility and imperfect separation with the available technologies are fully taken into account to assure maximum plastics recycling. A systematic approach to determine pre-sorting product and component clusters, that allow recycling with conventional separation techniques, is explained. Using statistical data sets for a case study of selected common WEEE products categories, the clusters in which to sort the products and dismantled components are documented and can support enhanced polymer recycling in an industrial setting.

Gamification is the adoption of game design elements and mechanisms into non-game contexts. As gamification has been a growing approach to increase people’s performance in multiple disciplines such as education, service and marketing, it is necessary to question if gamification is also applicable in the industrial setting. In this paper, we discuss the specific requirements of a gamifed Augmented Reality system in an industrial production setting, its applications as well as challenges.

The World Health Organization has declared the scalding, defeathering, evisceration, and chilling processing stages in industrial poultry slaughterhouses as sites of cross-contamination. In response, we develop a novel ordinary differential equation model describing the transfer and thermal inactivation of pathogens between carcasses in an industrial three-stage scalding tank. The model provides a link between the distribution of bacteria on carcasses before and after scalding using physical mechanisms of transfer and inactivation. A key feature of our model is that it directly quantifies cross-contamination, or microbial transfer between carcasses, via the scald water. We parametrize the model according to the specific pathogen C. jejuni, and then validate the model using numerical simulations against industrial scalding processing data. In particular, the calibrated model predicts a mean pathogen level on individual carcasses of [ 1.15 × 10 4 , 2.6 × 10 4 ] CFU/carcass, capturing the experimentally determined mean of 1.89 × 10 4 CFU/carcass in an industrial setting. We then demonstrate that our framework is amenable to application in quantitative microbial risk assessment and policymaking. In particular, using scalding configurations from an industrial poultry processor in Canada as well as the 2015 USDA-FSIS Campylobacter performance standards as a benchmark, we utilize the developed model to quantify the relationship between pre-scald prevalence and mean pathogen counts and the distribution of post-scald pathogen levels on carcasses.

As global resources are pressed by the demands of modern lifestyles, acquainting students with sustainable chemistry will be crucial in educating responsible chemists of the future. For this undertaking, we present “Redox Aluminophosphates”, a laboratory-based practical with targeted resources that has been designed to relate fundamental catalytic theory to core concepts in green chemistry. As part of this assignment, students are directed in the preparation of aluminophosphate materials using distinctive synthetic protocols (hydrothermal synthesis and calcination), and are required to apply their knowledge of analytical techniques to solid-state characterization. Students then use their heterogeneous redox catalysts in the oxidation of cyclohexane to KA oil (the industrial feedstock of adipic acid, a precursor to nylons), with gas chromatography–mass spectrometry (GC-MS) analyses providing an opportunity to introduce green chemistry metrics. With supporting resources, oral presentation, and student-led discussions, this practical aims to equip the undergraduate student with the tools needed to rationalize structure–activity relationships in porous heterogeneous catalysts. Using a systems thinking approach, Redox Aluminophosphates is a holistic practical, combining empiricism with critical analysis, self-study, and group work to relate undergraduate theory to real-world problems, while demonstrating how laboratory-scale procedures can be extrapolated to the industrial setting.

For the explosion safety assessment in an industrial setting, the knowledge of critical diameter of high explosives provides important information on the sensitivity and conditions whereby detonati...

Applying change‐level software defect prediction (SDP) in practice has several challenges regarding model validation techniques, data accuracy, and prediction performance consistency. A fe...

White wine is among the most widely consumed alcoholic beverages. Varietal discrimination of wines has received increasing attention. Today's consumers require a sense of authenticity and are deterred by falsehood or misrepresentation in product marketing. However, wine can involve various types of frauds, which directly affects the distribution of wine in national and international markets. Right-angle fluorescence spectroscopy is a simple and rapid analytical technique that in combination with chemometric algorithms, constitutes a novel method for wine authentication. In this study, the stepwise-Linear Discriminant Analysis algorithm was applied in three representative spectral regions related to phenolic compounds for the purpose of distinguishing white wines according to the grape variety. The wavelength at 310 nm attributed to the hydroxycinnamic acids and stilbene provided a higher classification rate (95.5%) than the λex 280 and 295 nm regions (79.8%), suggesting that these compounds are highly related to the botanical origin of samples. The chemometric models were validated utilizing cross-validation and an external validation set to enhance the robustness of the proposed methodology. The above-mentioned methodology constitutes a powerful tool for the varietal discrimination of white wines and can be used in industrial setting. The ultimate goal of this study is to contribute to the efforts towards the authentication of Greek white wine which will eventually support producers and suppliers to remain competitive and simultaneously protect the consumers from fraudulent practices., Graphical abstract Image 1, Highlights • Acquisition of fluorescence fingerprint from 140 commercial Greek white wines. • Qualitative study of the main fluorometric regions by standard phenolic compounds. • Distinguish autochthonous commercial Greek white wines based on EEMs using SLDA. • Development of a novel, cheap, and rapid methodology for wine authentication. • Reliable chemometric model by internal and external validation.

The integration of collaborative robots (cobots) is changing manufacturing and production processes in factories. When cobots are designed to be efficient, skillful and safe to interact with, workers can collaborate with them conveniently. As workers often work with cobots intensively, it is crucial to explore the user experience (UX) of cobots. The goal of our research is to explore how factory cobots could be used in ways that support pleasurable worker experiences. We adapted "research through design"(RtD) to conduct exploratory research on novel interactions related to affectiveness, playfulness and relatedness in human-robot collaboration (HRC) using collaborative robot arm, Panda. RtD is a method that utilizes methods and practices of design to produce new knowledge. We conducted an exploratory study with 33 participants to evaluate three HRC storyboards scenarios in two complementary remote workshops. The findings report suitability of affective and playful behavior of cobots in an industrial setting. In addition, we deduced that personality of the robot plays a crutial role in HRC. acceptedVersion

Non-destructive testing (NDT) for eggshell faults is highly important for the egg industry, as cracked eggs account for around 3% of total production. The most commonly used method at present, candling, is labor intensive, while computer vision systems are expensive and complicated. In this paper, we present a simple, yet efficient, novel method for eggshell crack detection by acoustic spectroscopy. Altogether, 693 sound recordings were evaluated by different classification methods. The results show a cross-validated 2.1% total classification error, with only 0.87% false positive rate, which is the crucial metric for fresh eggs. Adapting the developed method to an industrial setting may lead to a reliable, fast and cost-effective detection method.

A key to the success of automatic program repair (APR) techniques is how easily they can be used in an industrial setting. In this article, we describe a collaboration by a team from four U.K.-based universities with Bloomberg (London) in implementing automatic, highquality fixes to its code base. We explain the motivation for adopting APR, the mechanics of the prototype tool that was built, and the practicalities of integrating APR into existing systems.

This paper presents a fully blind false data injection (FDI) attack against an industrial field-bus i.e. PROFINET that is widely used in Siemens distributed Input/Output (I/O) systems. In contrast to the existing academic efforts in the research community which assume that an attacker is already familiar with the target system, and has a full knowledge of what is being transferred from the sensors or to the actuators in the remote I/O module, our attack overcomes these strong assumptions successfully. For a real scenario, we first sniff and capture real time data packets (PNIO-RT) that are exchanged between the IO-Controller and the IO-Device. Based on the collected data, we create an I/O database that is utilized to replace the correct data with false one automatically and online. Our full attack-chain is implemented on a real industrial setting based on Siemens devices, and tested for two scenarios. In the first one, we manipulate the data that represents the actual sensor readings sent from the IO-Device to the IO-Controller, whereas in the second scenario we aim at manipulating the data that represents the actuator values sent from the IO-Controller to the IO-Device. Our results show that compromising PROFINET I/O systems in the both tested scenarios is feasible, and the physical process to be controlled is affected. Eventually we suggest some possible mitigation solutions to secure our systems from such threats.

Aims Detection of bacterial contamination in healthcare and industry takes many hours if not days. Thermal imaging, the measurement of heat by an infrared camera, was investigated as a potential noninvasive method of detecting bacterial growth. Methods and Results Infrared thermography can detect the presence of Escherichia coli and Staphylococcus aureus on solid growth media by an increase in temperature before they are visually observable. A heat decrease is observed after treatment with ultraviolet light and heat increased after incubation with dinitrophenol. Conclusions Infrared thermography can detect early growth of bacteria before they are detectable by other microbiology-based method. The heat observed is due to the cells being viable and metabolically active, as cells killed with ultraviolet light exhibit reduced increase in temperature and treatment with dinitrophenol increases heat detected. Significance and Impact of the Study Infrared thermography detects bacterial growth without the need for specialized temperature control facilities. The method is statistically robust and can be undertaken in situ, thus is highly versatile. These data support the application of infrared thermography in a laboratory, clinical and industrial setting for vegetative bacteria, thus may become into an important methodology for the timely and straightforward detection of early-stage bacterial growth.

The Goldilocks Work Principle expresses that productive work should be redesigned to comprise physical behaviors of different intensities in a composition promoting workers’ health and fitness. This study is the first to assess the feasibility of redesigning work in an industrial setting according to the Goldilocks Work Principle. We recruited workers (n = 20) from a brewery in Denmark, and we conducted a participatory 16-week intervention including a workshop and two consultations. The workshop aimed to support the workers in modifying their work, while the consultations assisted the eventual implementation. Feasibility was evaluated as per three aspects: (1) developing modifications of work, (2) implementing these modifications, and (3) changing physical behavior and self-reported fatigue, pain and energy. The three aspects were addressed through records completed by the workers, measurements of workers’ physical behavior and intensity during ‘control’ workdays (i.e., usual work) and ‘intervention’ workdays (i.e., modified work), and self-reported fatigue, pain and energy level following both types of workday. Five modifications to work were developed, and three of these five modifications were implemented. To some extent, physical behavior and intensity changed as intended during ‘intervention’ workdays compared to ‘control’ workdays. Workers were also less fatigued, had less pain, and had more energy after ‘intervention’ workdays. These results suggest that it is feasible to develop and implement modified work based on the Goldilocks Work Principle among industrial workers. However, we also identified several barriers to the implementation of such modifications.

The present study investigates the oxidation of formic acid by the Fenton and Fenton-like reaction. An experimental study was performed at industrially relevant conditions, which means that the concentrations of reagents were generally higher than concentrations previously reported. The most interesting result is the fast oxidation rate of formic acid in the first two minutes of the Fe(II)/H2O2 reaction. In an industrial setting this fast initial oxidation can be used to remove a significant part of the formic acid without the need for large reactors with long residence times and large excesses of H2O2 and Fe(II). In contrast, the Fe(III)/H2O2 reaction shows a slower, constant decrease of formic acid over time strongly depending on temperature and H2O2 concentration. The initial decrease in formic acid concentration in the Fe(II)/H2O2 reaction could not be explained by previously proposed kinetic models for formic acid oxidation by the Fenton's reagent. The specific conditions used require a more elaborate kinetic model to describe the results obtained. In the Fe(II)/H2O2 reaction, the formic acid reacts with the [rad]OH radical and forms an [rad]OOH radical that regenerates the Fe(II). The reaction of Fe(III) and the [rad]OOH radical to regenerate Fe(II) and thereby restart the Fe(II)/H2O2 reaction can most likely explain the fast initial decrease observed. Furthermore, the addition of reactions describing the formation and decomposition of inorganic and ferric-formate complexes to the kinetic model improved the fit to all experimental data, in particular for the initial part of the reaction of Fe(II)/H2O2 with formic acid.

The United States’ large-scale poultry meat industry is energy and water intensive, and opportunities may exist to improve sustainability during the broiler chilling process. By USDA regulation, after harvest the internal temperature of the chicken must be reduced to 40°F or less within 16 h to inhibit bacterial growth that would otherwise compromise the safety of the product. This step is accomplished most commonly by water immersion chilling in the United States, while air chilling methods dominate other global markets. A comprehensive understanding of the differences between these chilling methods is lacking. Therefore, we assessed the meat quality, shelf-life, microbial ecology, and techno-economic impacts of chilling methods on chicken broilers in a university meat laboratory setting. We discovered that air chilling methods resulted in superior chicken odor and shelf-life, especially prior to 14 days of dark storage. Moreover, we demonstrated that air chilling resulted in a more diverse microbiome that we hypothesize may delay the dominance of the spoilage organism Pseudomonas. Finally, a techno-economic analysis highlighted potential economic advantages to air chilling compared to water chilling in facility locations where water costs are a more significant factor than energy costs. IMPORTANCE As the poultry industry works to become more sustainable and to reduce the volume of food waste, it is critical to consider points in the processing system that can be altered to make the process more efficient. In this study, we demonstrate that the method used during chilling (air versus water chilling) influences the final product microbial community, quality, and physiochemistry. Notably, the use of air chilling appears to delay the bloom of Pseudomonas spp. that are the primary spoilers in packaged meat products. By using air chilling to reduce carcass temperatures instead of water chilling, producers may extend the time until spoilage of the products and, depending on the cost of water in the area, may have economic and sustainability advantages. As a next step, a similar experiment should be done in an industrial setting to confirm these results generated in a small-scale university lab facility.

Detailed characterization of protein reagents and biopharmaceuticals is key in defining successful drug discovery campaigns, aimed at bringing molecules through different discovery stages up to development and commercialization. There are many challenges in this process, with complex and detailed analyses playing paramount roles in modern industry. Mass spectrometry (MS) has become an essential tool for characterization of proteins ever since the onset of soft ionization techniques and has taken the lead in quality assessment of biopharmaceutical molecules, and protein reagents, used in the drug discovery pipeline. MS use spans from identification of correct sequences, to intact molecule analyses, protein complexes and more recently epitope and paratope identification. MS toolkits could be incredibly diverse and with ever evolving instrumentation, increasingly novel MS-based techniques are becoming indispensable tools in the biopharmaceutical industry. Here we discuss application of Ion Mobility MS (IMMS) in an industrial setting, and what the current applications and outlook are for making IMMS more mainstream.

Background Natural products are a valuable source of biologically active compounds that have applications in medicine and agriculture. One disadvantage with natural products is the slow, time-consuming strain improvement regimes that are necessary to ensure sufficient quantities of target compounds for commercial production. Although great efforts have been invested in strain selection methods, many of these technologies have not been improved in decades, which might pose a serious threat to the economic and industrial viability of such important bioprocesses. Results In recent years, introduction of extra copies of an entire biosynthetic pathway that encodes a target product in a single microbial host has become a technically feasible approach. However, this often results in minor to moderate increases in target titers. Strain stability and process reproducibility are the other critical factors in the industrial setting. Industrial Streptomyces rimosus strains for production of oxytetracycline are one of the most economically efficient strains ever developed, and thus these represent a very good industrial case. To evaluate the applicability of amplification of an entire gene cluster in a single host strain, we developed and evaluated various gene tools to introduce multiple copies of the entire oxytetracycline gene cluster into three different Streptomyces rimosus strains: wild-type, and medium and high oxytetracycline-producing strains. We evaluated the production levels of these engineered S. rimosus strains with extra copies of the oxytetracycline gene cluster and their stability, and the oxytetracycline gene cluster expression profiles; we also identified the chromosomal integration sites. Conclusions This study shows that stable and reproducible increases in target secondary metabolite titers can be achieved in wild-type and in high oxytetracycline-producing strains, which always reflects the metabolic background of each independent S. rimosus strain. Although this approach is technically very demanding and requires systematic effort, when combined with modern strain selection methods, it might constitute a very valuable approach in industrial process development.

Today, many products and solutions are provided on the cloud, however, the amount and financial losses due to cloud security incidents illustrate the critical need to do more to protect cloud assets adequately. A gap lies in transferring what cloud and security standards recommend and require to industry practitioners working in the front line. It is of paramount importance to raise awareness about cloud security of these industrial practitioners. Under the guidance of design science paradigm, we introduce a serious game to help participants understand the inherent risks, understand the different roles, and encourage proactive defensive thinking in defending cloud assets. In our game, we designed and implemented an automated evaluator as a novel element. We invite the players to build defense plans and attack plans for which the evaluator calculates success likelihoods. The primary target group is industry practitioners, whereas people with limited background knowledge about cloud security can also participate in and benefit from the game. We design the game and organize several trial runs in an industrial setting. Observations of the trial runs and collected feedback indicate that the game ideas and logic are useful and provide help in raising awareness of cloud security in industry. Our preliminary results share insight into the design of the serious game and are discussed in this paper.

One of the beyond-5G developments that is often highlighted is the integration of wireless communication and radio sensing. This paper addresses the potential of communication-sensing integration of Large Intelligent Surfaces (LIS) in an exemplary Industry 4.0 scenario. Besides the potential for high throughput and efficient multiplexing of wireless links, an LIS can offer a high-resolution rendering of the propagation environment. This is because, in an indoor setting, it can be placed in proximity to the sensed phenomena, while the high resolution is offered by densely spaced tiny antennas deployed over a large area. By treating an LIS as a radio image of the environment, we develop sensing techniques that leverage the usage of computer vision combined with machine learning. We test these methods for a scenario where we need to detect whether an industrial robot deviates from a predefined route. The results show that the LIS-based sensing offers high precision and has a high application potential in indoor industrial environments.

Comprehensive understanding of key players and actions in multiplayer sports broadcast videos is a challenging problem. Unlike in news or finance videos, sports videos have limited text. While both action recognition for multiplayer sports and detection of players has seen robust research, understanding contextual text in video frames still remains one of the most impactful avenues of sports video understanding. In this work we study extremely accurate semantic text detection and recognition in sports clocks, and challenges therein. We observe unique properties of sports clocks, which makes it hard to utilize general-purpose pre-trained detectors and recognizers, so that text can be accurately understood to the degree of being used to align to external knowledge. We propose a novel distant supervision technique to automatically build sports clock datasets. Along with suitable data augmentations, combined with any state-of-the-art text detection and recognition model architectures, we extract extremely accurate semantic text. Finally, we share our computational architecture pipeline to scale this system in industrial setting and proposed a robust dataset for the same to validate our results., Comment: 9 pages, 7 figures and 6 tables. To be published in the proceedings of ACM Multimedia 21, Industrial Track, held from October 20-24 in China

Modeling of absorption, distribution, metabolism and excretion properties is well established in drug discovery. Here we present principles, considerations when and how to build models and how to apply them in real life in the industrial setting. The availability and quality of experimental data is important. However, for in silico models to be utilized availability is a major factor. Additionally, model quality measures need to be presented in an easily understandable manner for chemists and DMPK scientists.

The amazing challenge of orchestrate enzymatic cascades (multi-enzymatic or chemo-enzymatic) usually faces numerous issues to be addressed. Together with the advances in synthetic biology, materials science and protein engineering, the discovery of new reaction media represents a valuable tool in the search towards cost-efficient and sustainable enzymatic cascades in an industrial setting. This chapter showcases the recent developments on the implementation of the so-called non-conventional media in such processes.

This chapter covers the evolutionary development of polymer mass spectrometry-based techniques and presents practical applications to illustrate their utility in materials characterization, especially in an industrial setting. Specifically, areas of interest are thoroughly reviewed, with discussions on their limitations, new trends, and future outlooks. Grouped topics include ionization techniques, modern mass analyzers, common MS/MS fragmentation techniques, ion mobility separations, and selected applications. Additionally, this chapter includes an applications section that discusses analysis approaches for industrial fouling solids, with special emphasis placed upon the use of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry-based techniques for systematically characterizing these intractable materials.