Development Process Research Articles

Limitations in creating artificial populations in agent-based epidemic modeling: a systematic review

Introduction. The key step in agent-based modeling of epidemics, which allows researchers to take into account individual characteristics of people, is the creation of an artificial population. The main difficulty of this procedure is finding a balance between the detail of the population description and the computational efficiency of the calculations. The aim and objectives of the review: Critically analyze and summarize the current evidence on how to create artificial populations; evaluate the limitations and advantages of available approaches in solving various problems in epidemiology. Materials and methods. An analysis of literature sources devoted to agent-based modeling has been performed. The analysis is focused on algorithms for creating an artificial population with a given level of detail for modeling human respiratory infections. Results. The approaches to the creation of artificial populations are generalized. The main principles of realization of interaction between agents are revealed: by means of networks of contacts between agents and on the basis of taking into account the movement of agents between locations. The first approach is the most computationally efficient and simple; the second approach allows to better take into account the change in the behavior of agents during the development of the epidemic process. Conclusion. Agent-based modeling is an optimal tool for selecting the best scenario for epidemic control and investigating the role of individual characteristics of people in the development of epidemics. When creating an artificial population, it is important to include in the model factors that can be targeted for control. A significant limitation is the lack of factual data on population structure, but this can be overcome by using indirect data.

Development and performance investigation of a novel ultrasonic-assisted non-contact membrane distillation process to prevent membrane fouling

A novel non-contact membrane distillation (NCMD) process is proposed that prevents membrane fouling by preventing direct physical contact between the feed and membrane. The feed channel of the NCMD module is equipped with an ultrasonic transducer that provides high-frequency mechanical oscillations to the feed film, which forms a fine mist of droplets and water column. Experiments are conducted to determine the feed height required to maximize the evaporation rate, and the effects of feed temperature, flow rate, and ultrasonic power on the permeation flux. The results reveal that the highest permeation flux occurs at a feed height of 20 mm, and an increase in the feed height and flow rate decreases the ultrasonic cavitation effect, while a higher feed temperature and ultrasonic power significantly increases the permeation flux. At the feed temperature of 60 °C, feed flow rate of 1.0 L/min, and ultrasonic current of 600 mA, the permeation flux is 6.3 kg/m2h, which is 8.4 times greater than that of the NCMD process without ultrasonic treatment. The corresponding specific energy consumptions with and without the ultrasonication are 647 and 6028 kWh/m3, respectively. Moreover, the long-term experimental results indicate that the proposed system is unaffected by high feed concentrations.

Development of an efficient pretreatment process and multi-functional acetate co-metabolism strategy for the treatment of high strength biogas slurry using a newly isolated Chlorella sorokiniana

The efficient treatment of biogas slurry (BS) to meet the government’s discharge standards is a major challenge for most livestock and poultry enterprises. Although microalgae-based wastewater treatment has many significant benefits over traditional technologies, the poor ammonium tolerance of regular algal species, the pH imbalance during microalgae cultivation, and the complex and expensive BS pretreatment process greatly limit its application in BS treatment. Aimed at these issues, this study firstly isolated a robust Chlorella sp. with strong ammonium and acidic tolerance, as well as heterotrophy ability. To facilitate optimal pH stability and growth enhancement, a co-metabolism cultivation strategy based on the addition of 0.1 g·L-1 acetate in the form of fed-batch was developed. In addition, an efficient pretreatment process integrating ammonia reduction by air stripping with turbidity and chromaticity reduction by acidic precipitation was developed for the elimination of inhibitory factors of microalgal growth in BS. The isolated Chlorella sp. was capable of growing in the pretreated real BS and no growth inhibition was observed even in the undiluted BS. The acetate co-metabolism cultivation strategy obviously enhanced cell growth and pollutant removal and both NH4+ and total phosphorus were reduced to meet the discharge standards of China via 2.5-fold dilutions of BS. The accumulation of high-value biomass could not only fully cover the cost of wastewater treatment, but also bring significant returns. The net profit from treating 1 m3 of BS reached $ 116.2. This study provides a simple and efficient packaged process for the treatment of high strength BS and is expected to greatly reduce the process cost of BS.

Evaluation of symbiotic relationships of oral microorganisms and their effect on the development of inflammatory changes of the oral mucosa in the complete absence of teeth

Introduction. By fixing on the exposed surfaces of complete removable dentures and oral soft tissues, bacteria form a biofilm, thereby increasing their overall virulence and resistance. The microorganisms that make up the biofilm are often in a symbiotic relationship, which allows them to increase their pathogenic potential and cause the development of denture stomatitis. Accordingly, when a particular strain is present in the oral cavity, the risks of symbiosis are significantly increased. The aim of the study was to evaluate the effect of symbiotic relationships of oral bacteria on the development of inflammatory changes in the oral cavity in the absence of teeth. Materials and methods. Two groups of patients belonging to the elderly age according to WHO systematization (60–74 years) with complete absence of teeth (K08.1) were formed, differing in the presence of clinical manifestations of inflammation (82 men and 49 women). Biological material sampled from the oral cavity of patients was studied using the culture method and RT-PCR. To quantify the interaction between members of the microbiocenosis, we used the Jaccard similarity coefficient. Results. Coagulase-negative and coagulase-positive staphylococci, Neisseria, Candida spp., Enterobacterales and F. nucleatum were more frequently found in patients with complete absence of teeth. Expressed symbiotic relations between microorganisms of the Enterobacterales order, Lactobacillus, Neisseria and Corynebacterium genera, as well as S. salivarius, C. albicans, F. nucleatum were established. The nature of these relations depended on the presence of inflammatory changes in the oral mucosa and, in turn, influenced the development of the latter. Thus, in the absence of inflammation, Corynebacterium, Lactobacillus and S. salivarius showed stable synergism. In case of inflammation, the association between these bacteria was accompanied by the introduction of F. nucleatum and displacement of S. salivarius. Conclusion. Thus, conditionally pathogenic microorganisms, forming microbial associations with multidirectional symbiotic relations increase their virulence, which allows them to occupy free niches in the oral cavity and subsequently trigger the development of pathological process of inflammatory character of prosthetic bed tissues.

Mechanistic Insights into Substrate Recognition of Human Nucleoside Diphosphate Kinase C Based on Nucleotide-Induced Structural Changes

Nucleoside diphosphate kinases (NDPKs) are encoded by nme genes and exist in various isoforms. Based on interactions with other proteins, they are involved in signal transduction, development and pathological processes such as tumorigenesis, metastasis and heart failure. In this study, we report a 1.25 Å resolution structure of human homohexameric NDPK-C bound to ADP and describe the yet unknown complexes formed with GDP, UDP and cAMP, all obtained at a high resolution via X-ray crystallography. Each nucleotide represents a distinct group of mono- or diphosphate purine or pyrimidine bases. We analyzed different NDPK-C nucleotide complexes in the presence and absence of Mg2+ and explain how this ion plays an essential role in NDPKs’ phosphotransferase activity. By analyzing a nucleotide-depleted NDPK-C structure, we detected conformational changes upon substrate binding and identify flexible regions in the substrate binding site. A comparison of NDPK-C with other human isoforms revealed a strong similarity in the overall composition with regard to the 3D structure, but significant differences in the charge and hydrophobicity of the isoforms’ surfaces. This may play a role in isoform-specific NDPK interactions with ligands and/or important complex partners like other NDPK isoforms, as well as monomeric and heterotrimeric G proteins. Considering the recently discovered role of NDPK-C in different pathologies, these high-resolution structures thus might provide a basis for interaction studies with other proteins or small ligands, like activators or inhibitors.

Development of an interprofessional diagnostic toolkit to enhance outside walking gait-related participation of people after stroke in Germany: study protocol of an ongoing multi-methods study

IntroductionPersons after stroke experience limitations in activities of daily living even in the chronic phase. Many patients who had a stroke report mobility limitations with loss of social roles such...

Investigating the simulation test and acoustic emission characteristics of structural-control type rockbursts in deep underground environments

Deep underground projects are in a complex in-situ stress environment, and rock burst disasters induced by the hard and brittle failure of the rock mass are prone to occur around the tunnel openings. In this study, we aim to investigate the impacts of geological weak surfaces in rock masses on rockbursts and the spatiotemporal evolution of microcracks during the development of rockbursts. To achieve this objective, two sets of cubic specimens containing a circular through-hole were designed. One set of specimens had prefabricated unfilled cracks around the openings. Subsequently, the rockburst development process within the deep tunnel was replicated by subjecting both groups of specimens to identical gradient loading using a true triaxial test system. During the test, a micro camera was used to record the failure of the borehole wall in real-time, and an acoustic emission monitoring system was utilized to capture the stress waves released during structural damage. Finally, a multi-level synergistic analysis of the rockburst damage mechanism was carried out based on the macro-imaging data and micro-acoustic emission data. The results show that failure in high-stress environments within tunnels mainly includes microcrack initiation, particle ejection, crack propagation, local cracking, slabbing spalling, damage penetration, and rockburst damage. The time–frequency domain information of acoustic emission signals is highly perceptive and representative of the structural damage state of the specimens. The mutation characteristics observed in time-domain parameters, such as acoustic emission amplitude, event rate, ringing, and cumulative energy, correspond to drastic alterations in the internal structure of the rock. The distribution characteristics of frequency-domain parameters, such as acoustic emission peak frequency, dominant frequency energy, and frequency centroid, reflect different crack scales and damage modes. The diffusion of frequency centroid indicates that the damage and failure patterns within the rock are evolving towards a more complex direction. The energy magnitude of acoustic emissions represents the damage intensity during the development of rockburst. The root causes of induced structural-control type rockbursts in deep hard brittle rock masses are the combined effects of localized high-stress concentrations and large-scale discontinuous geological structures, such as natural joints, fissures, and structural planes. The naturally occurring large-scale through-type geological weak surfaces within the rock mass reduce the strength of the surrounding rock, alter the location of stress concentration, and change the initial damage characteristics. Moreover, they promote the evolution of rockbursts, thereby increasing their destructive intensity.

Data Integration to Support Child Care Business Sustainability: Iowa’s Child Care Connect

Working parents need access to childcare, and the unprecedented COVID-19 pandemic highlighted critical gaps in data system capacities to meet this need. This was particularly acute in the US where many child care providers closed their doors permanently because they could not sustain their business. The state of Iowa estimates losses over $930 million per year to businesses and individuals due to a lack of childcare. Childcare businesses are not sustainable if they cannot fill slots and be consistently paid for care – and families need to be able to find care when they need it to fill those slots. Iowa is addressing this gap by developing a real-time, integrated data solution that includes historically disparate data systems to better identify childcare supply and demand. Through intensive community engagement processes including leadership from state agencies, the development team created a system that includes multiple technology solutions for real-time data sharing; a secure cloud-based system for storage, integration, and analysis; and two public-facing applications that allow data to be aggregated and shared for strategic decision-making as well as used by families to identify available care when and where they need it. This presentation will discuss challenges in cross-sector data linkage with a focus on child care providers, families, and population demand. It will include an overview of the development process, governance structure, and analytic uses of the system. Highlights include identification of real-time vacancies by age group, geography, quality rating, and in relation to estimated potential demand using additional integrated data resources.

Design of customized business process management with implementation in the apparel industry as a solution to achieve operational excellence

Textile industry companies are required to compete optimally with competitors to generate higher revenues for the sustainability of the company. In addition, companies must be responsive to market demands because of the dynamic nature of the market. One of the systems used to meet these needs is the Enterprise Resource Planning (ERP) information system. PT Rofina Indah Jaya (Poshboy) has obstacles in implementing ERP in the apparel industry because it is still too generic and has not been optimal in using the existing ERP system. This study aims to improve the performance and efficiency of the industry that produces real-time business reports, so that effective and efficient coordination is created. The methodology used in this study is to take a qualitative and quantitative approach to investigate the design of business process management that is adjusted to the implementation in the apparel industry as a solution to achieve operational excellence. Designing ERP based on customized business processes with implementation in the apparel industry is waterfall is a sequential development process and RACI Matrix that can be adopted to ensure the improvement process runs consistently. Optimization of the ERP business process uses Business Process Management (BPM) by identifying processes that require improvement through comprehensive process mapping to understand the overall workflow. So that ERP can manage customer relationship management (CRM), stock availability updates, warehouse stock positions, goods in transit, order placement, delivery orders, as well as recording and finance used for management decision-making analysis

A novel model to estimate the structural properties of PLA-FFF components along any non-orthogonal direction

Purpose This study aims to present and evaluate a novel analytical model to predict the structural properties of parts fabricated by fused filament fabrication (FFF) along any non-orthogonal direction. Design/methodology/approach A new analytical model to estimate the ultimate tensile stress (UTS) and elastic modulus (E) of polylactic acid (PLA)-FFF parts fabricated in any non-orthogonal build orientation, is proposed. The new model is based on an ellipsoid, two angles that define the orientation with respect to the build axes, the infill value and the structural properties along the build axes. The proposed model is evaluated by comparing the UTS and E properties predicted by this model, with the results obtained from experimental tensile tests on PLA-FFF specimens manufactured using variable infill values and non-orthogonal build orientations. Findings The proposed model is able to predict with good precision the structural properties of PLA-FFF parts along any direction and infill value. Research limitations/implications Although the study and results are limited to the UTS and E tensile properties of PLA-FFF components, the model may be extended to other materials or similar additive manufacturing processes. Practical implications The new proposed model is able to determine the structural properties of FFF components in any direction, so it can be used during the design process of FFF parts, reducing the need for experimental tests and speeding up the product development process. Originality/value Existing models to predict the structural properties of FFF components are limited to orthogonal build orientations (X, Y and Z); however, the new proposed model is able to predict the tensile properties in any direction and infill value. In addition, a new set of experimental data about the structural behaviour of PLA-FFF parts along non-orthogonal build orientations is provided, extending the existing results in the literature.

Decoding environmental impact with image-based CO2 emission analytics

As per the regulations of Intergovernmental Panel on Climate Change (IPCC), the country’s carbon emission data hold primacy. Nevertheless, establishing and utilizing a database pose a daunting challenge. This study presents the “Carbon Seer System,” a novel software prototype designed to inform and educate users about the carbon footprint during their production and in daily life. The development process involved a three-stage user interview process, ensuring system’s alignment with user needs and preferences. The system employs machine learning and visual recognition technology, including convolutional neural networks (CNNs), feature pyramid networks, and self-attention mechanisms, enabling users to analyze captured images for carbon emission factors. It automatically identifies the carbon emission factors of industrial products, energy producers, household producers, waste treatment, and transportation. A unique “group detection” method allows for the simultaneous analysis of multiple objects in a single image, enhancing user convenience. Additionally, the software features a carbon footprint tracker and a carbon sink dashboard, providing users with insights into their carbon emissions and the efforts needed for offsetting. The study concludes that the “Carbon Seer System” represents a significant step towards individual enablement at understanding and actively participating in a low-carbon lifestyle.

Research on Innovative Application and Practical Challenges of Generative Artificial Intelligence in English Teaching

With rapid IT advancements, generative AI is gradually transforming education, notably in English language teaching, displaying significant potential. This paper explores the application of generative AI in English teaching and the accompanying challenges. Firstly, through literature review, we summarize the development process of generative artificial intelligence technology, relevant theoretical basis and its application status in the field of education. The paper examines generative AI's application in English teaching, analyzing scenarios like personalized learning, interactive dialogues, automated assessment & feedback, and teacher tools. It also delves into practical impacts via case studies and discusses challenges like technical hurdles, integration difficulties, and ethical considerations. Finally, this paper summarizes the major contributions of generative AI in English teaching and puts forward suggestions for future development trends.

Assessment of data‐driven modeling approaches for chromatographic separation processes

AbstractChromatographic separation processes are described by nonlinear partial differential and algebraic equations, which may result in high computational cost, hindering further online applications. To decrease the computational burden, different data‐driven modeling approaches can be implemented. In this work, we investigate different strategies of data‐driven modeling for chromatographic processes, using artificial neural networks to predict pseudo‐dynamic elution profiles, without the use of explicit temporal information. We assess the performance of the surrogates trained on different dataset sizes, achieving good predictions with a minimum of 3400 data points. Different activation functions are used and evaluated against the original high‐fidelity model, using accuracy, interpolation, and simulation time as performance metrics. Based on these metrics, the best performing data‐driven models are implemented in a process optimization framework. The results indicate that data‐driven models can capture the nonlinear profile of the process and that can be considered as reliable surrogates used to aid process development.

Heterogeneous E‐Textiles: Materials, Manufacturing and Sustainability

AbstractElectronic textiles (e‐textiles) combine electronic functions (e.g., sensing, actuating, data processing) with textiles. E‐textiles are a platform technology with the potential for ubiquitous deployment in any application scenario where textiles can be found. E‐textiles have attracted significant research interests from materials and manufacturing process development to applications such as sports/fitness, healthcare, and workwear. While significant advances have been made in the research domain regarding the integration of electronic functionality, the technology is relatively immature and significant challenges remain in the manufacturing of commercialized e‐textile systems. This paper reviews the state of the art in e‐textile manufacturing including materials (e.g., yarns, inks), fabrication (e.g., weaving, knitting, printing), electronic integration and interconnections. This paper also reviews the key principles of textile sustainability and electronic waste (e‐wastemanagement, which provide useful guidance on e‐textile design and manufacturing to minimize their impact on the environment. Examples are given to demonstrate the early work toward sustainable e‐textiles. The remaining research challenges regarding scalable and sustainable manufacturing of e‐textiles are presented.

Effectiveness of interprofessional development of foundational lactation open education resources

The purpose of this manuscript is to share the interprofessional development of foundational lactation open education resources (OERs) for prebriefing prior to simulation. A team of health faculty, students, and practitioners developed five lactation modules with an Equity Diversity Inclusion (EDI) framework representing diverse families. Participants (n=1453) answered a survey at the end of the OER modules including a variety of healthcare professional faculty, students, practitioners, and parents. The process of development, effectiveness, and usability of these modules were used for prebriefing prior to teaching/learning opportunities. The findings from use of the five OERs provide descriptive data on the usefulness for interprofessional education and professional development. The creation of five OER lactation modules provide an equity and inclusion lens to model consistent approaches to support the needs of diverse families allowing interprofessional students to develop shared mental models and psychological safety prior to clinical experiences.

Observation on embryonic development of Gymnodiptychus dybowskii (Kessler, 1874) in Manas River, Xinjiang, China

To protect the germplasm resources of Gymnodiptychus dybowskii (Kessler, 1874), a species endemic to Xinjiang, the key stages of embryonic development of G. dybowskii were studied. From May to July 2021, the artificial breeding of G. dybowskii was carried out at the fish breeding station of the Kenswart Water Conservancy Project. The embryos and early larvae were obtained using temperature promotion, water stimulation, hormone induction, and dry insemination techniques. their development process was observed, and morphological characteristics of each developmental stage were recorded. The results showed that the mature oocyte was round, heavy, and light yellow, with an egg diameter of (2.32 ± 0.21) mm. The fertilized egg was slightly viscous, and the viscosity disappeared after water absorption. Under the temperature of 15.6-17.7 ℃ (16.23 ± 0.52) ℃, the embryonic development of G. dybowskii lasted for 142 h and 33 min and went through 7 stages of fertilization, cleavage, blastula, gastrula, neurula embryo, organ formation, and membrane hatching, with a total of 26 periods. The membrane broke after 2376.724 ℃·h. The embryonic development of G. dybowskii follows the rule of freshwater bony fish, but it differs from other Schizothorax species in the muscular effect period and membrane emergence mode. In addition, differences in hatching water temperature among different geographic populations lead to differences in embryo development duration and accumulated temperature, which further proves that G. dybowskii is highly adaptive to the ecological environment of its habitat water, and these characteristics together constitute its survival and reproduction strategy in the natural environment. In this study, through the artificial breeding experiment of G. dybowskii, the characteristics of its embryonic development were explored, which laid the foundation for the cultivation of unique fish seedlings, enriched the early life history data of G. dybowskii, and further provided basic data for its resource protection.

The Development of Interactive Powerpoint Learning Media to Increase Students’ Critical Thinking Ability

Mathematics learning can develop students' creativity to solve problems in various life situations. Learning mathematics helps train students to think critically and creatively to solve problems. Considering the reality on the ground and the importance of critical thinking skills. from an early age. One effort to develop critical thinking abilities is to use media directed at these abilities. The method used in this research is research and development, with a modified 4-D development model in three stages, namely determination, design and development. This research aims to determine the development of interactive teaching materials assisted by power points, on Statistics material. The subjects of this research were 3 mathematics teachers at SMP Mutiara 4 Bandung. The instrument for developing teaching materials uses interview instruments. The teaching materials validated by three validators have a total score on the interactive power point of 275 with a maximum ideal score of 300 and have a percentage of 92.31% in the valid category based on the teaching material criteria. The validator's assessment of the interaction strength score shows that the percentage score for each aspect and the total percentage score are both in the valid category. Based on the research and development process and results, the following conclusions were obtained. Developing learning media using interactive Powerpoint, critical thinking skills are within valid criteria. The results obtained can be tested on junior high school or MTs students in accordance with the considerations and assessments of validator experts.

Using Artificial Intelligence to Advance the Research and Development of Orphan Drugs

While artificial intelligence has successful and innovative applications in common medicine, could its application facilitate research on rare diseases? This study explores the application of artificial intelligence (AI) in orphan drug research, focusing on how AI can address three major barriers: high financial risk, development complexity, and low trialability. This paper begins with an overview of orphan drug development and AI applications, defining key concepts and providing a background on the regulatory framework of and AI’s role in medical research. Next, it examines how AI can lower financial risks by streamlining drug discovery and development processes, analyzing complex data, and predicting outcomes to improve our understanding of rare diseases. This study then explores how AI can enhance clinical trials through simulations and virtual trials, compensating for the limited patient populations available for rare disease research. Finally, it discusses the broader implications of integrating AI in orphan drug development, emphasizing the potential for AI to accelerate drug discovery and improve treatment success rates, and highlights the need for ongoing innovation and regulatory support to maximize the benefits of AI-driven research in healthcare. Based on those results, we discuss the implications for traditional and AI-powered business in the drug industry.

Entrepreneurs in Africa – the agenda for Business History in Africa: Complexity and continuity

Abstract Africa has been the location of centuries of business activity. African business displays a complex development path through early indigenous kingdoms, colonial control and post–1950 independence. The historiography on these developments is unbalanced in favour of the role performed by enterprises embedded in capitalist metropolitan economies. Complex and dynamic African entrepreneurial activity persisted but adapted to global market changes. Business historians have not systematically explored African agencies in business, the management systems and the organisational evolution of enterprise in Africa. As market liberalisation provided new business opportunities, African businesses emerged to complement and compete with foreign-owned enterprises. As market liberalisation stimulated globalisation, multi-national companies returned to African markets, fostering competition and collaboration. Changes in the political economy of many African states gave rise to more dynamic regulatory contexts and public-private partnerships in different sectors of developing African economies. These trends appear in the Business History of Africa from the perspective of African business, owned by Africans from diverse ethnic origins as proof of the complex trends and processes in African enterprise development. This contribution seeks to refine the focus on business and entrepreneurs in Africa as agents in the continent’s business landscape. The manuscript acknowledges the diversity among African entrepreneurs and the dynamically changing state-business nexus through history. Can one identify a distinct «African» nature of enterprise? This manuscript addresses aspects of conceptual clarity on what constitutes African business in an attempt to map the agenda for Business History in Africa.

EnzChemRED, a rich enzyme chemistry relation extraction dataset

Expert curation is essential to capture knowledge of enzyme functions from the scientific literature in FAIR open knowledgebases but cannot keep pace with the rate of new discoveries and new publications. In this work we present EnzChemRED, for Enzyme Chemistry Relation Extraction Dataset, a new training and benchmarking dataset to support the development of Natural Language Processing (NLP) methods such as (large) language models that can assist enzyme curation. EnzChemRED consists of 1,210 expert curated PubMed abstracts where enzymes and the chemical reactions they catalyze are annotated using identifiers from the protein knowledgebase UniProtKB and the chemical ontology ChEBI. We show that fine-tuning language models with EnzChemRED significantly boosts their ability to identify proteins and chemicals in text (86.30% F1 score) and to extract the chemical conversions (86.66% F1 score) and the enzymes that catalyze those conversions (83.79% F1 score). We apply our methods to abstracts at PubMed scale to create a draft map of enzyme functions in literature to guide curation efforts in UniProtKB and the reaction knowledgebase Rhea.