Industrial Problems Research Articles

INCREASING THE EFFICIENCY OF USING WOOD BIOMASS BY PROVIDING SPECIAL PROPERTIES

Background. The search for ways to use logging waste is a distinct scientific direction, due to the large number of their permanent formation. The importance of such studies is associated with the need to reduce the loss of valuable wood raw materials in the form of logging waste. One of the possible ways of using waste from logging industries is the production of wood chips using a mobile complex of machines with its further recycling into a wood-fiber semi-finished product. Wood-fiber semi-finished product is, as it is known nowadays, one of the environmentally friendly types of insulation and finishing materials. A significant limitation in the use of wood fiber in various types of production is low fire and bio-resistance. As a consequence, imparting specific properties to a wood-fiber semi-finished product in the form of fire and bio-resistance is an acute problem of the modern wood processing industry.
 Purpose. Synthesis of 4-azofunctionalized pyrazoles with perfluoroalkyl substituent by cyclocondensation of polyfluorinated beta-diketones to confer special properties to the wood-fiber semi-finished product.
 Materials and methods. The 1H, 13C NMR and 1H-13C HSQC spectra were registered at the Krasnoyarsk Regional Center for Collective Use of the FITC KNC SB RAS on a Bruker Avance III Fourier spectrometer with a frequency of 600 MHz equipped with sensitive helium probes with a diameter of 5 mm and 1.7 mm. TMS is used as an internal standard. Chromato-mass spectra were obtained using ISQ 7610 Single Quadrupole GC-MS and Shimadzu LC/MS-2020 instruments. Methyl alcohol was used as the mobile phase. IR spectra were recorded on the FT-801 (FT-801) SIMEX IR Fourier spectrometer with a spectral range from 450 to 5700 cm-1. UV spectra were recorded on a HELIOS OMEGA spectrophotometer equipped with a tungsten-halogen lamp in quartz cuvettes with a diameter of 1 cm at a concentration of 1·10-4 mol/l for 200-400 nm and a concentration of 1·10-2 mol/l for 400-800 nm in ethanol. Melting temperatures were determined in open capillaries on a PTP device (TU 25-11-1144-76).
 Results. 3 new compounds were synthesized: 3(5)-(thiophene-2-yl)-4-nitroso-5(3)-(trifluoromethyl)-1H-pyrazole, 3(5)-phenyl-4-nitroso-5(3)-(trifluoromethyl)-1H-pyrazole and 3(5)-(naphthalene-2-yl)-4-nitroso-5(3)-(trifluoromethyl)-1H-pyrazole.
 Conclusion. Thus, 3(5)-(thiophene-2-yl)-4-nitroso-5(3)-(trifluoromethyl)-1H-pyrazole, 3(5)-phenyl-4-nitroso-5(3)-(trifluoromethyl)-1H-pyrazole and 3(5)-(naphthalene-2-yl)-4-nitroso-5(3)-(trifluoromethyl)-1H-pyrazole. Complex separable mixtures of substances containing pyrazoline, β-diketone and target nitrosopyrazoles were formed by a single-reactor method. The two-stage method of production proposed by us increases the purity and yield of the target products.

Research on Industrial Digital Transformation Strategies for the Construction of a New Industrialized City

Industrial digital transformation is the appropriate intention and an inevitable choice to empower the construction of a new industrialized city, which holds great significance for the efficient allocation of industrial resources, the optimized layout of the industrial structure, and the enhancement of industrial development quality. However, industrial digital transformation will encounter two major problems: the data security of enterprise information-knowledge spillovers and the willingness of enterprises to transform, reflected in the enterprise input-output ratio for industrial digital transformation. Therefore, constructing an industrial digital transformation strategy that can effectively address these two problems has become a focal point. In light of this, the study builds an industrial digital transformation strategy from the perspectives of research institutions such as universities, industrial enterprises, trade associations, and government departments by exploring the causes of industrial digital transformation problems. Universities and research institutions should expedite the construction of compatible big data models for industrial digital transformation paradigms, such as the industrial Internet. Leading manufacturing enterprises should actively establish "satellite-type" industrial digital transformation platforms. Trade associations should redirect their functions toward the construction of standardized industrial know-how systems. Government departments should take a leading role in promoting industrial digital transformation among scientific research institutions, industrial enterprises, trade associations, and government departments. The government should lead efforts to promote synergistic cooperation among research institutions, industrial enterprises, and trade associations to ultimately realize the systematic and holistic promotion of industrial digital transformation.

Supply Chain Innovation in the Catering Industry: An Assessment of the Cost-Effectiveness and Sustainability of the Central Kitchen Model

With the trend of mechanization in the catering industry, the demand for scale, industrialization and standardization of the catering supply chain has increased. As an emerging catering supply chain model, the central kitchen has great potential to meet the demand for mechanization. Central kitchens are an effective way to solve the catering industry's problems in scaling up operations. However, in practice, many issues still need to be researched and explored in the central kitchen based on the enterprise perspective in the context of the Chinese catering industry. This paper collects and analyzes data from Chinas restaurant industry and Shuhais business data to determine whether central kitchens positively impact supply chain management and performance improvement in the context of Chinas restaurant industry. It is found that the central kitchen model effectively reduces supply chain costs, ensures product quality and improves supply chain synergy and integration, which is a theoretical guide and practical revelation for the supply chain decision-making of catering enterprises and the model design of supply chain service enterprises.

Development of an effective risk reduction system at food industry enterprises

The current work is relevant due to the existence of problems in the food industry that are directly related to hazards presented at the earliest stages in the production. For the consumer, to maintain his physical health when eating is of great importance, and for the manufacturer, this is a matter of economic well-being through the production and supply of safe products for consumption. The purpose of the study was to develop suggestions focused on the use of an extended risk-based approach in the format of a food safety management system. If а systematic analysis of the most significant risk-based technologies is applied, it will allow to build a workable and effective protection system and minimise losses from impact of dangerous factors on an organisation’s processes. The authors studied the most interesting international and domestic standards that address the problem of reducing risks and hazards for food industry enterprises, and chose the most effective methods that complement each other. A logically built four-stage model of risk treatment at the operational and organisational levels of the enterprise and recommendations for expanding the risk-based approach in the food safety management system are the results of the work.

ARTIFICIAL INTELLIGENCE AS AN OBJECT OF MANAGEMENT: A BENEFIT FOR CIVILISATION OR A THREAT TO MANKIND?

The authors of the article analyze the reasons for the rapid development and implementation of artificial intelligence achievements, which opens up great opportunities for solving problems in many industries and is a reliable assistant to people in everyday life. The article analyses different approaches to the definition of "artificial intelligence", possible threats to humanity from its implementation, and focuses on the need to increase the responsibility of developers of programs, algorithms, systems and strengthen control over the work of users of equipment and devices with elements of artificial intelligence. People around the world have long been dependent on technical inventions and devices. The achievements of artificial intelligence provide people with convenience and comfortable conditions. The development of intelligent machines is an important area of scientific and technological progress. Artificial intelligence technologies contribute to solving many problems related to various areas of life, including the economy. Today, artificial intelligence is a global trend in technology development and innovation. Advances in computing power, the ability to collect and process huge amounts of information, and instant access to the latest algorithms are important prerequisites for the evolution of intelligent technologies. The development of sophisticated computers and robots poses risks to the world’s people. Without the use of artificial intelligence, the development of scientific and technological progress is impossible. Key words: artificial intelligence, the achievement of civilization, a threat to humanity, strengthening control over the operation of machines. Therefore, the development of intelligent machines and devices must continue, but with the warnings of global authorities who warn of the existing threat to humanity.

Charge weld evolution in hollow aluminum extrusion: Experiments and modeling

Charge welds occur in billet-to-billet extrusion processes due to the transition between successive billets. The material in this transition zone is typically characterized by substandard mechanical properties. In industrial practice, a specified length of the extruded profile is cut away and recycled as in-process scrap. Therefore, understanding the extrusion mechanisms affecting the properties of the charge weld is crucial to controlling product quality, reducing non-conformities and improving the extrusion yield. This paper provides new insights into thermo-mechanical mechanisms associated with charge weld of circular aluminum tubes. A large number of carefully-controlled, full-scale extrusion experiments were conducted in an industrial environment to research charge weld evolution mechanisms and influential parameters. In addition, a finite element (FE) model was developed to predict the charge weld evolution across the cross section and along the profile. The experimental and numerical results show good agreement in terms of the location of the charge weld within the extruded profile. Moreover, a comparison with analytical models in the literature reveals that the FE model provides a significantly more accurate prediction of the length of the extruded profile affected by the charge weld (‘scrap length’). Based on the validated FE model, a sensitivity study was done to explore the effect of process parameters on charge weld evolution, particularly focusing on material flow and dead metal zone. The results show that the ram speed influences the charge weld evolution, while changes in billet temperature are insignificant. In conclusion, the findings presented in this study provide new insights that serve as practical guidance to the mechanism of charge weld evolution. They also highlight the applicability and limitations of numerical and analytical methods in assessing industrial extrusion problems.

Multi-criteria analysis of deep pits sustainable development strategy

Relevance. Long periods of development of steeply dipping deposits necessitate multiple adjustments of mining and technical system throughout an open pit life cycle. The decisions made determine the development strategy of a mining enterprise for a long period. The complexity of making such strategic decisions depends on numerous influencing parameters. These parameters have a different impact, have a variety of units of measurement, target values, and are not only quantitative but also qualitative. There is a need for new approaches to the choice of development strategy of the mining and technical system of an open pit, as well as its main subsystem – the opening-up of an opencast system. It is proposed to base these approaches on multi-criteria decision-making methods that consider many influencing parameters. Aim. Development of a methodology for choosing a strategy for sustainable development of the deep open pit mining and technical system based on multi-criteria decision-making methods and assessment of the opening system parameters. Objects. Mining enterprise, mining and technical systems, opening system. Methods. Literature review, system analysis, multi-criteria decision making. Results. The authors have determined the main strategies for development of the mining and technical system for deep open pits. These strategies aim at achieving the sustainable development of the mining and technical system: adjustment of the current stage mining parameters; transition to a new stage of mining; transition to a combined open-underground mining; mine closure. The key role of the opening system in the structure of the mining and technical system is substantiated to ensure its sustainable development. The authors systematized the main parameters for evaluating the pit opening system and set target values for each parameter. A review of the main multi-criteria decision-making methods used to solve various problems in the mining industry is made. A rank coefficient is proposed for choosing the mining and technical system development strategy. The calculation of this coefficient is based on a combination of the fuzzy AHP and CRADIS multi-criteria methods. A method was developed for selecting a strategy for sustainable development of the mining and technical system of deep open pits. A case study was conducted on the conditions of the Maly Kuibas open pit. The obtained results strongly suggest that the best strategy with the highest ranking is the transition to the combined development method.

Development of Technology for the Production of Meat Products of the "Halal" Category for Functional Nutrition

The article is devoted to the development of technology for meat products of the "Halal" category. The authors consider the main problems of the meat industry in the field of the development of meat products of the "Halal" category in accordance with the National Program "Development of meat farming for 2018-2027", as well as the peculiarities of the production of meat products of the "Halal" category in Kazakhstan. A technology for the production of sausages for frying of the "Halal" category based on minced turkey and beef meat for functional nutrition has been developed, organoleptic, physico-chemical parameters of the new product have been studied. The mass fraction of protein is 8 %, the mass fraction of fat is 7 %. The authors of the article have developed a technological scheme for the production of a new product of the "Halal" category, which includes: acceptance of raw materials, cutting, deboning, veining, grinding to 2-3 mm of meat raw materials. At the next stage, meat is cooked at t 2-4 0C for 12 hours, minced meat is prepared (adding jerusalem artichoke 3 %, adding vitamin premix "Rovifarin" in an amount of 1.0 %, as well as spices and garlic according to the developed recipe). At the next stage, the minced meat is stuffed into natural shells with a diameter of (32-44) mm, cooled at t (4 + 2) 0C, stored at t (4 + 2) 0C for 36 hours. During the microstructural study of a sample of boiled and smoked sausage produced using traditional technology, it was found that the mass of the sample was formed from large fragments of muscle, fat and connective tissue (0.7-1.4) microns. The layout of the structural elements of the minced meat is dense, vacuoles and microcapillaries are rounded in shape, sometimes without clear boundaries, merged, with a size of (60-300) microns.

Flavor production driven by microbial community dynamics and their interactions during two-stage fermentation of Ziziphus jujuba vinegar

Ziziphus jujuba pulp could be utilized for Ziziphus jujuba vinegar (ZJV) production to reduce waste. However, how to specifically regulate microorganisms during ZJV fermentation to improve its flavor remains an industrial problem. This study evaluated the contribution of ZJV's two-stage fermentation (alcohol fermentation (AF) and acetic acid fermentation (AAF)) to flavor metabolites and microbial community assembly. The ZJV production can represent a sustainable strategy in the management of Ziziphus jujuba pulp wastes. Temperature, alcohol and acid were driving forces of microbiota succession. AF is an important stage for the formation of alcohols, esters, non-volatile acids, and various amino acids. Bacteria and fungi mainly generated esters and alcohols in AF, respectively. Microorganisms capable of protease production and strong stress resistance were conducive to amino acid production (e.g., Virgibacillus and Saccharomyces in AF, Bacillus and Xeromyces in AAF). Solid-state AAF was the key step of acetic acid production and flavor metabolite accumulation. Komagataeibacter with higher acid-tolerant than Acetobacter dominated late AAF and showed a positive correlation with acetic acid. Dominant bacteria promoted the accumulation of various volatile flavor substances (esters, acids, aldehydes, and ketones), while low-abundance fungi facilitated the accumulation of functional metabolites (GABA, acetoin, tetramethylpyrazine). These results guided the targeted control of ZJV fermentation to improve its flavor quality and provided valuable insights for ZJV manufacturers.

Kenya’s Mineral Landscape: A Review of the Mining Status and Potential Recovery of Strategic and Critical Metals through Hydrometallurgical and Flotation Techniques

Kenya is an East African country with the third-largest economy in sub-Saharan Africa. The demand for metals and minerals continues to increase due to urbanization, population rise, and new infrastructure growth in different countries. Kenya formally confirmed the discovery of oil and various minerals in April 2013, launching itself as a new player in Africa’s rapidly expanding extractive sector. This review paper highlights the mining status in Kenya and the role of hydrometallurgical and flotation processes in the recovery of deficit metals from ores and mine wastes. The nation’s 2030 Vision is anticipated to benefit greatly from the proceeds from the sale of oil, gas, and valuable metals. Because Kenya was originally mapped as an agricultural region, less mineral prospecting was done in earlier times. The country’s mining industry is now dominated by the manufacture of non-metallic goods, and it is largely neglected for minerals. One of the most serious problems for the mining industry in Kenya is the production of tailings that hold strategic metals. The material is already ground, which means the most energy-consuming process has been already applied, and chemical engineering processes like leaching are more feasible at this point. Hydrometallurgical and flotation recovery of valuable metals from wastes, high and low-grade ores, or tailings is essential. The resources will be preserved, which ensures sustainability in the growth of the mining industry.

IPSAL: Implementation of the module to generate the Sobol sequence and indices

Sensitivity and uncertainty analysis hold significant importance across a range of applications, spanning from industrial problems to climate change, financial risk assessment, as well as mathematical and computational models. These analyses involve identifying influential input parameters in models to comprehend their impact on the output. Sensitivity analysis can be performed locally, examining parameter effects at a fixed value, or globally, evaluating the model across a range of parameter values. The Sobol method stands as a robust approach for global sensitivity analysis, employing a Sobol sequence to create samples more uniformly within the input parameter space, thus enabling efficient exploration of model inputs. This paper aims to introduce a computational implementation in Scilab to generate the Sobol sequence for utilization in sensitivity analysis through the Sobol method. A test case was applied to generate Sobol sequences and discuss the obtained results.

Life Before and After

Abstract ‘Good’ editorial practice – in this case, post-developmental copy-editing work – is typically measured by an editor’s ‘positive invisibility’ (J. Hargrave, Teaching Publishing and Editorial Practice, Cambridge University Press, 2022). Traditionally, editing has been considered a ‘role [that] tends to be pushed into the margins’, taking place ‘behind the scenes’ and existing ‘everywhere and, therefore, nowhere’ (S. Greenberg, ‘When the Editor Disappears, Does Editing Disappear?’, Convergence, 2010, p. 8); a hidden, mysterious business transparent only to those who practise it. Editorial practice is hence often (mis)judged by physical invisibility on the page: that is, an absence of error. An editor’s value is predicated on their positive invisibility, an outcome of which can be their marginalization. With the distinction between work and home life essentially eradicated in the COVID-19 gig economy of 2020–2021, central questions posed for this context were simply: ‘How did editors cope with the work-to-home transition?’, ‘Did editors become more invisible and/or marginalized during COVID-19?’, and, ‘If so, what was the nature of this invisibility and/or marginalization?’ Editors were contacted in 2020 and 2022 to describe their editorial practice and its potential (in)visibility before, during, and after the 2020–2021 pandemic lockdowns. Their responses exposed their at times polarized experiences and work – life challenges, and ongoing systemic problems in industry.

3D Printer Selection for the Sustainable Manufacturing Industry Using an Integrated Decision-Making Model Based on Dombi Operators in the Fermatean Fuzzy Environment

Three-dimensional printers (3DPs), as critical parts of additive manufacturing (AM), are state-of-the-art technologies that can help practitioners with digital transformation in production processes. Three-dimensional printer performance mostly depends on good integration with artificial intelligence (AI) to outperform humans in overcoming complex tasks using 3DPs equipped with AI technology, particularly in producing an object with no smooth surface and a standard geometric shape. Hence, 3DPs also provide an opportunity to improve engineering applications in manufacturing processes. As a result, AM can create more sustainable production systems, protect the environment, and reduce external costs arising from industries’ production activities. Nonetheless, practitioners do not have sufficient willingness since this kind of transformation in production processes is a crucial and irrevocable decision requiring vast knowledge and experience. Thus, presenting a methodological frame and a roadmap may help decision-makers take more responsibility for accelerating the digital transformation of production processes. The current study aims to fill the literature’s critical theoretical and managerial gaps. Therefore, it suggests a powerful and efficient decision model for solving 3DP selection problems for industries. The suggested hybrid FF model combines the Fermatean Fuzzy Stepwise Weight Assessment Ratio Analysis (FF–SWARA) and the Fermatean Ranking of Alternatives through Functional mapping of criterion sub-intervals into a Single Interval (FF–RAFSI) approaches. The novel FF framework is employed to solve a critical problem encountered in the automobile manufacturing industry with the help of two related case studies. In addition, the criteria are identified and categorized regarding their influence degrees using a group decision approach based on an extended form of the Delphi with the aid of the Fermatean fuzzy sets. According to the conclusions of the analysis, the criteria “Accuracy” and “Quality” are the most effective measures. Also, the suggested hybrid model and its outcomes were tested by executing robustness and validation checks. The results of the analyses prove that the suggested integrated framework is a robust and practical decision-making tool.

Toward a better understanding of collaborative research, development, and innovation (R&D&I) - exploring virtual, physical, and cognitive structures

Objective of the study: The research in this paper contributes to the understanding of how physical, virtual, and cognitive structures support innovation ecosystems’ multi-actor research, development, and innovation (R&D&I) collaboration in its different phases. Methodology/Approach: The research’s methodological approach is based on a qualitative case study research strategy. It is done by exploring three innovation ecosystem cases. The case data comprises the case ecosystems’ existing documentation that was supplemented with five semi-structured interviews. Originality/Relevance: Based on the findings of this research, it was possible to explore how industry and academy partners are collaborating through virtual, physical, and cognitive structures. Our cases also provide empirical evidence on how physical industrial sites can be used as environments for collaborative industry-academy R&D&I work. Main Results: As a result, the paper presents lessons learned from three different innovation ecosystem cases that involve industrial, technology, and academy partners to tackle industrial use cases through virtual, physical, and cognitive structures. An example of such lessons learned is assembling dynamic teams to solve industrial problems. Theoretical/Methodological Contributions: This article builds an understanding of how virtual, physical, and cognitive structures support collaboration between different participants in their joint R&D&I work covering industry-academy collaboration. The article also explains practical examples of this using innovation ecosystem cases. Management/Social Contributions: The findings of this study may benefit professionals and managers who have an interest in understanding collaborative R&D&I and how physical, virtual, and cognitive structures can support it. Furthermore, the results provide means and experiences for innovation ecosystem managers to facilitate the definition of operational models suitable for the context of their innovation ecosystems.

Perbandingan Algoritma Multilinear Regression dan Decision Tree Regressor dalam Memprediksi Efisiensi Penghambatan Korosi Piridazin

Corrosion is one of the main problems in various industries, causing increased production costs, maintenance expenses, and decreased equipment efficiency. Inhibitors, especially organic compounds, have become an increasingly sought-after solution to reduce corrosion in an effective and environmentally friendly manner. This research aims to compare linear algorithms based on multilinear regression (MLR) and nonlinear algorithms based on decision tree regressor (DTR) for a case study of predicting corrosion inhibition efficiency (CIE) values of pyridazine derivative compounds as corrosion inhibitors. This research is a data-based theoretical study using a machine learning (ML) approach. In this study, we used a dataset of pyridazine compounds from published literature consisting of 20 pyridazine compounds with molecular properties as features (independent variables) and CIE values as targets (dependent variables). The analysis consists of analyzing the prediction model's performance and important features that support model performance. The research results show that the DTR-based nonlinear model has better performance than the MLR-based linear model based on evaluation metrics and prediction data distribution plots. We also find that the molecular properties fraction of electron transferred (∆N) and electron affinity (A) respectively emerge as the features most responsible for the prediction performance of the DTR model. We conclude that the DTR-based nonlinear algorithm can be used as an accurate and reliable predictive model to predict the corrosion inhibition ability for potential new pyridazine derivative compounds.

Identification of damage and corrosion effect in aging aircraft data transmission lines

Corrosion in aircraft structures and systems persists to pose significant problem in the aircraft industry. It affects both the aircraft structures and all the wiring systems including data transmission lines at the points of mechanical damage (missing or damaged insulation and jacket materials) and connections. Reliability of data transmission through aircraft data transmission lines (ATDL) is essential for maintaining performance capability and safety of flights. Unfortunately, there is no existing method for detecting corrosion and predicting its effect for wiring systems including ADTL. Detecting corrosion and predicting its effect on time would prevent unexpected system failures and catastrophes. This paper presents novel experimental method that has been employed, for the first time, to detect and study the effect of localized corrosion process on reflected and transmitted power signals passing through locally corroded ADTL with mechanically induced damage. ADTL with three types of induced damage were corroded in a Q-Fog cyclic accelerated corrosion chamber for over 14 weeks (2352 h) using ASTM G85-A5 Prohesion test that resembles the environment of aircraft operation. Cable specimens were taken out every week and investigated by measuring transmitted and reflected power signals passing through the corroded ADTL using Vector Network Analyzer (VNA), where signals from 0 to 6 GHz were swept into the ADTL. Reflected and transmitted power signals (S11 and S21 respectively) were acquired in time domain and processed in MATLAB. Analysis of results show that corrosion effect is not arbitrary and can be tracked over time and predicted. Reflected signal peak width changed over time of corrosion exposure and is proportional to corrosion propagation width inside the ADTL. It is also observed that corrosion induced extra distortion of signals passing through the corroded damage region. The results are very promising for detecting corrosion and predicting its effect in ADTL.

Privacy-Preserving Cross-Silo Federated Learning Atop Blockchain for IoT

Cross-silo federated learning (FL) is promising in facilitating data collaboration across various organizations, which greatly alleviates the information silo problem in industries and promotes the data intelligence of internet of things. With the advances of decentralized FL, the higher requirements of trust and privacy are put forward. Traditional FL heavily relies on a central coordinating server, which suffers from single points of failure and lacks trust in the correctness of aggregation results. What’s more, the intrinsic privacy issues of FL have aroused public attention, such as gradient inversion attack in local gradients. However, the privacy of quantized gradients remains serious and lacks attention, especially the most extremely 1-bit quantization in sign-based FL. In this paper, we demonstrate the potential privacy risk in sign-based FL by presenting a new gradient inversion attack, which successfully restores the original data from sign-based quantized gradients. And then we tackle the above two challenges via constructing a self-aggregation privacy-preserving federated learning atop blockchain, which takes advantage of a variant of ElGamal encryption to protect the privacy of local sign-based quantized gradients, and leverages the smart contract to achieve secure self-aggregation for participants without involving a centralized server. Moreover, we analyze that the proposed protocol achieves privacy and public verifiability. Finally, we evaluate the performance of the proposed protocol with a real deep learning model, and the results show that our protocol is resilient against gradient inversion attack in a decentralized environment without sacrificing learning accuracy.

Freeze Drying and Vial Breakage: Misconceptions, Root Causes and Mitigation Strategies for the Pharmaceutical Industry

Vial breakage during or following freeze drying (lyophilization) is a well-known and documented phenomenon in the pharmaceutical industry. However, the underlying mechanism and probable root causes are not well characterized. Mostly, the phenomenon is attributed to the presence of crystallizing excipients, such as mannitol in the formulation, while other potential factors are often underestimated or not well studied. In this work we document a systematic multipronged approach to characterize and identify potential root cause(s) of vial breakage during lyophilization. Factors associated with formulation, product configuration, primary container and production process stress conditions were identified and their impact on vial breakage was studied in both lab and manufacturing scale conditions. Studies included: 1) strain gauge and lyophilization analysis for stress on glass vials with different formulation conditions and fill volumes, 2) manufacturing fill-finish process risk assessment (ex. loading and frictive force impact on the vials), and 3) glass vial design and ruggedness (ex. glass compression resistance or burst strength testing). Importantly, no single factor could be independently related to the extent of vial breakage observed during production. However, a combination of formulation, fill volume, and vial weakening processes encountered during at-scale production, such as vial handling, shelf loading and unloading, were identified to be the most probable root causes for the low levels of vial breakage observed. The work sheds light on an often-encountered problem in the pharmaceutical industry and the results presented in this paper argue against the simplistic root-cause explanations reported in literature. The work also provides insight into the possibility of implementing mitigative approaches to minimize or eliminate vial breakage associated with lyophilized drug products.

Criminal Consequences of Unsustainable Food Systems: Ethical Issues and Future Prospects

A major worldwide issue, criminal aspects of unsustainable agricultural systems pose serious concerns to environmental stability, biodiversity, and food security. The necessity to address environmental harm from a legal and regulatory perspective is highlighted in this survey of the literature from a variety of disciplines that looks at the connections between criminal activity and unsustainable practices in the food business. The analysis delves into foundational works that stress the need for more study on the criminal elements of unsustainable food production, distribution, and consumption. By highlighting the importance of ecological justice and sustainability in regulatory responses, green cultural criminology provides a framework for understanding how environmental harms are criminalized or disregarded within legal systems. According to the study, food fraud is a major problem in the food industry since it uses dangerous or low-quality substances to trick customers. The accidental encouragement of biodiversity loss and ecological disturbance is further highlighted by the connection of illegal wildlife trading with the food business. Age-related environmental crimes such as pesticide abuse, water pollution, and land degradation are major contributors to global environmental deterioration. Context-specific research is essential to address regional issues, but few studies have examined the criminal consequences of unsustainable agriculture systems in Jordan. Increase food supply chain transparency, promote multidisciplinary collaboration, and strengthen regulatory frameworks and enforcement. Ecologically conscientious and secure food systems include fighting food sector corruption, promoting sustainable farming, and raising awareness. To promote environmental stewardship and resilience, it is crucial to identify and address the criminal components of unsustainable food systems. Promoting sustainability, protecting the environment, and guaranteeing global food security all need cooperation between academics, politicians, and stakeholders. Collective action is needed to pave the road toward greener and more secure communities, and establishing sustainable food systems is a crucial first step.

Prospects for the supply of weapons from the US, the eu and the United Kingdom to Ukraine

This study examines the prospects of arms supplies from the United States, the EU and the United Kingdom to Ukraine in the context of the ongoing military conflict. The paper analyzes the issue of expanding the nomenclature, up to the provision of American-made jet aircraft complexes, the supplied equipment and the process of transition from stocks of military equipment both produced by NATO and the Soviet model to newly produced samples. The problem of the impact of a special military operation on the defense industry of London, Washington and Brussels is considered separately. There is a tendency to increase the value of shares of defense companies and their profits. The paper concludes that the increase in military production with the further course of the conflict and the supply of weapons will grow both quantitatively and qualitatively. In addition, the existing problems of the defense industry of the United States, Great Britain and the European Union in the current period are revealed - the high cost of products, issues of standardization with Soviet weapons, its complexity in using and training personnel. The main conclusion of the work can be called the statement of a significant time required for the deployment of mass industrial production.