Complexity Of Process Research Articles

Enhancing Financial Decision-Making Through Automated Business Intelligence Systems

In today's competitive IT market, integrating BI tools is crucial for optimizing financial data analysis and decision-making. This study focuses on an automated approach: constructing a robust data warehouse, segmenting data with a hybrid method, and applying advanced data mining for processing complex financial data. The research showcases significant impacts across Metric Companies A, B, and C, which operate in Company A achieved a 15% revenue growth through real-time financial analysis and trend identification, while Company B improved profitability by 20% via insights into cost management and strategic pricing adjustments. Additionally, Company C enhanced asset efficiency and financial performance by 25% by optimizing asset allocation strategies. This study emphasizes the pivotal role of automated BI systems in enhancing financial performance and decision-making across various organizational contexts.

Visual detection of kanamycin with functionalized Au nanoparticles.

A simple and rapid colorimetric detection strategy, based on hydrogen bond identification of 6-thioguanine (6-TG) functionalized Au nanoparticles (AuNPs), is proposed for highly selective and sensitive determinationof kanamycin (KA). In this strategy, the hydrogen bond interaction between 6-TG and kanamycin induces AuNPs to agglomerate, with a consequent color change of AuNPs from wine red to purple or even blue. The kanamycin concentrations can be quantified by employing UV-vis spectrophotometer. The results display that kanamycin concentrations (0.005 to 18µM) are linearly related to A620/A520 (the absorbance ratio of 620nm and 520nm) with a LOD of 1.8nM and a LOQ of 5.9nM (S/N = 3). This strategy also reveals a high degree of selectivity among a series of common interfering species. Moreover, the strategy can be employed to detect trace amounts of kanamycin in real-life samples, and it shows satisfying resultscompared with high performance liquid chromatography. In general, this developed strategy is facile and inexpensive without the need for complex processing procedures and expensive instruments. In addition, this work may further exploit detection strategies for other organic contaminants, as well as make a strong contribution to the development of the colorimetric method.

Addressing the overuse of hospital emergency departments in the Portuguese NHS: a new paradigm.

The escalating trend of inappropriate visits to Emergency Departments (ED) has led to significant concerns, including resource misallocation, compromised patient care, and an increased burden on healthcare workers. Portugal faces a notable challenge, reporting one of the highest per capita ED visit rates, with an annual average of approximately 6 million ED visits from 2013 to 2023. In response, the "Call First, Save Lives" pilot project was launched by the Portuguese NHS Executive Board, in 2023, at the Local Health Unit (LHU) of Póvoa de Varzim/Vila do Conde. This project leverages the SNS 24 telephone triage system to direct patients to the most appropriate care settings, alleviating pressure on ED, and optimizing healthcare resources. The project introduced several strategic enhancements, including optimizations of the SNS 24 system and inter-institutional initiatives to promote interoperability, hospital follow-ups for chronic conditions, and a "reverse referral" system directing non-urgent ED cases to Primary Care Services (PCS). In PCS, the project expanded acute care consultations and introduced complementary health services. The initiative also emphasized communication to improve health literacy and appropriate utilization of the NHS, supported by legal framework development. Since the beginning of the project, the number of calls received by SNS 24 showed an upward trend, both at the local, 27.6%, and national level, 44.5%, having already expanded to other LHU. Nonetheless, challenges such as the "reverse referral" process complexity, healthcare information systems integration, and procedural standardization need addressing, with future plans including satisfaction surveys and patient triage protocol refinements to improve service delivery and patient adherence.

Religious coping in parenting a child with Down syndrome: A case study

The aim of this research is to illuminate (a) how religiosity can be manifest in a coping process associated with parenting a child with Down syndrome and (b) the complexity of this coping process in terms of the interdependence of identity, context, religion and coping. Following methods previously used in qualitative psychology of religious studies on religious people coping with cancer, religiosity is mapped out regarding how it is, and has been, manifest during the life before and after becoming a parent to a child with Down syndrome. An in-depth analysis is conducted on how the various manifestations of religiosity play out, and intervene with identity and context, in the process of coping with various challenges associated with parenting a child with Down syndrome. The results show experiences of personal growth regarding identity as well as experiences of spiritual growth. The most dominant religious manifestation associated to the analysed coping processes is the faith community’s various roles. The results are compared with methodologically, and conceptually, similar studies. In comparison with studies on religious people coping with cancer, the role of the faith community is much more dominant in the presented case. It is argued that this might have to do with the differences in nature between stressors associated with the own health/survival and parenting a child with Down syndrome, and it is suggested that the nature of stressors might play an important role when understanding the varieties of religious manifestations in religious coping.

Design of the Multi-Bioactive Graphene-Oxide/Gelatin/Alginate Scaffolds as Dual ECM-Mimetic and Specific Wound Healing Phase-Target Therapeutic Concept for Advanced Wound Healing.

Objectives: To develop and evaluate graphene oxide/gelatin/alginate scaffolds for advanced wound therapy capable of mimicking the native extracellular matrix (ECM) and bio-stimulating all specific phases of the wound healing process, from inflammation and proliferation to the remodeling of damaged skin tissue in three dimensions. Methods: The scaffolds were engineered as interpenetrating polymeric networks by the crosslinking reaction of gelatin in the presence of alginate and characterized by structural, morphological, mechanical, swelling properties, porosity, adhesion to the skin tissue, wettability, and in vitro simultaneous release of the active agents. Biocompatibility of the scaffolds were evaluated in vitro by MTT test on fibroblasts (MRC5 cells) and in vivo using Caenorhabditis elegans assay. Results: The scaffolds exhibited a highly porous interconnected morphology with adjustable porosity (93-96%) and mechanical strength (1.10-2.90 MPa), hydrophilic nature with high capacity to absorb physiological fluids, and stable adhesion to the skin tissue. The obtained results of MRC5 cell viability indicate that the scaffolds are safe for biomedical applications. No mortality was detected among the Caenorhabditis elegans throughout the incubation period, indicating that the scaffolds are not toxic. The results of in vitro release study of allantoin, quercetin, and caffeic acid confirm the scaffolds' significant potential for simultaneous release. Conclusion: The graphene oxide/gelatin/alginate scaffolds are promising candidates for non-invasive, dual ECM-mimetic, and multi-target wound therapy, offering an innovative strategy to address the complexities of wound healing process.

Maximizing Retail Potential: The Role of Big Data Analytics

The retail industry has been transformed by technological advancements and evolving consumer behavior. This paper examines the benefits, challenges, and strategic implications of Big Data Analytics (BDA) in the retail sector through a comprehensive review of recent literature. The findings highlight three key opportunities for leveraging BDA in retail: enhancing customer relationships, improving operational efficiency, and gaining strategic advantages. However, several challenges persist, including privacy and security concerns, inadequate data-driven support systems, complexities in data visualization and processing, and insufficient governmental support. In addition to exploring the potential advantages and limitations, this study emphasizes the strategic role of BDA in facilitating data-driven decision-making for retailers. By balancing these opportunities and challenges, retail firms can harness Big Data as a critical source of competitive advantage. Finally, the paper identifies future research directions to further advance the application of Big Data in the retail sector, aiming to address existing gaps and unlock its full potential.

Objective study validity diagnostics: a framework requiring pre-specified, empirical verification to increase trust in the reliability of real-world evidence.

Propose a framework to empirically evaluate and report validity of findings from observational studies using pre-specified objective diagnostics, increasing trust in real-world evidence (RWE). The framework employs objective diagnostic measures to assess the appropriateness of study designs, analytic assumptions, and threats to validity in generating reliable evidence addressing causal questions. Diagnostic evaluations should be interpreted before the unblinding of study results or, alternatively, only unblind results from analyses that pass pre-specified thresholds. We provide a conceptual overview of objective diagnostic measures and demonstrate their impact on the validity of RWE from a large-scale comparative new-user study of various antihypertensive medications. We evaluated expected absolute systematic error (EASE) before and after applying diagnostic thresholds, using a large set of negative control outcomes. Applying objective diagnostics reduces bias and improves evidence reliability in observational studies. Among 11716 analyses (EASE = 0.38), 13.9% met pre-specified diagnostic thresholds which reduced EASE to zero. Objective diagnostics provide a comprehensive and empirical set of tests that increase confidence when passed and raise doubts when failed. The increasing use of real-world data presents a scientific opportunity; however, the complexity of the evidence generation process poses challenges for understanding study validity and trusting RWE. Deploying objective diagnostics is crucial to reducing bias and improving reliability in RWE generation. Under ideal conditions, multiple study designs pass diagnostics and generate consistent results, deepening understanding of causal relationships. Open-source, standardized programs can facilitate implementation of diagnostic analyses. Objective diagnostics are a valuable addition to the RWE generation process.

Functional Hydrogel Interfaces for Cartilage and Bone Regeneration.

Effective treatment of bone diseases is quite tricky due to the unique nature of bone tissue and the complexity of the bone repair process. In combination with biological materials, cells and biological factors can provide a highly effective and safe treatment strategy for bone repair and regeneration, especially based on these multifunctional hydrogel interface materials. However, itis still a challenge to formulate hydrogel materials with fascinating properties (e.g., biological activity, controllable biodegradability, mechanical strength, excellent cell/tissue adhesion, and controllable release properties) for their clinical applications in complex bone repair processes. In this review, we will highlight recent advances in developing functional interface hydrogels. We then discuss the barriers to producing of functional hydrogel materials without sacrificing their inherent properties, and potential applications in cartilage and bone repair are discussed. Multifunctional hydrogel interface materials can serve as a fundamental building block for bone tissue engineering.

Pengembangan Sistem Informasi Akuntansi Penerimaan Barang Hotel NS Bandung Berbasis Web

The NS hotel application system in the goods receiving department requires extensive time when handling fluctuations in price, quantity, weight, and taxes between incoming goods data and pre-entered purchase orders. Receiving staff must make adjustments in the system through several different screens and menu options, making the process complex and time-consuming. This study aims to simplify the goods receiving system using PHP for programming and MySQL for data storage. This article applies a qualitative research approach through agile development, designed specifically for accounting information systems. The focus is on coordination and communication to ensure the system meets user needs, thereby allowing users more time for clarification, physical control of goods, and streamlining the inflow of goods in daily operations.

Shoulder and Elbow Surgery Fellowship Applicants with Greater Research Productivity During Residency are Ranked Higher by Fellowship Programs.

Shoulder and elbow surgery fellowships in the United States are recognized for their academic emphasis, yet the correlation between an applicant's research productivity and fellowship match results remains unclear. This study (1) analyzed temporal trends in research productivity among matched fellowship applicants, (2) evaluated the influence of quantity of publications and first authorships on match positions, and (3) investigated program variations in research productivity. This is a retrospective analysis of data from the San Francisco (SF) Match Database for shoulder and elbow surgery applicants matched between 2017 and 2024. Allopathic (MD), osteopathic (DO), and international medical graduates (IMGs) were included. PubMed was queried to quantify publications and first authorship before and during residency, analyzing their association with applicant and fellowship rank. Publication volumes per fellowship program were also calculated for institutions with at least five years of match data. 290 matched applicants were evaluated across 34 fellowship programs, comprising 229 MDs, 29 DOs, and 32 IMGs. There was almost a five-fold increase in the average number of publications per applicant, from 2.72 ± 3.54 in 2017 to 12.80 ± 15.88 in 2024 (B 1.30; p = 0.001). Similarly, first authorship publication counts increased almost three-fold, from 1.31 ± 2.12 in 2017 to 3.66 ± 5.01 in 2024 (B = 0.29, p = 0.02). Fellowship program analysis revealed wide variation in mean publication counts of matched applicants (p = 0.008), with Rush University Medical Center (27.88 ± 33.86), Massachusetts General Hospital (13.65 ± 26.62), Mayo Clinic (13.06 ± 14.77), Thomas Jefferson University Hospital (12.19 ± 10.64) exhibiting the highest averages. Candidates with more publications (p = 0.04), first authorships(p = 0.02), and total first authorships (p = 0.04) during residency were ranked higher by fellowship programs. There was a significant correlation between greater publication count during residency and more favorable fellowship rank (-0.15, p = 0.02) and applicant match position (-0.12, p = 0.049). No significant associations were found between pre-residency publications (p = 0.38), total publications (p = 0.13), and pre-residency first authorships (p = 0.20) with fellowship rank positions. Research productivity has increased substantially among matched applicants. The more academically productive residents tend to be ranked more favorably by fellowship programs and match higher on their list. However, these associations were relatively weak, highlighting the complexity of the fellowship selection process and the notion that research productivity alone does not guarantee placement in preferred programs.

RL4CEP: reinforcement learning for updating CEP rules

This paper presents RL4CEP, a reinforcement learning (RL) approach to dynamically update complex event processing (CEP) rules. RL4CEP uses Double Deep Q-Networks to update the threshold values used by CEP rules. It is implemented using Apache Flink as a CEP engine and Apache Kafka for message distribution. RL4CEP is a generic approach for scenarios in which CEP rules need to be updated dynamically. In this paper, we use RL4CEP in a financial trading use case. Our experimental results based on three financial trading rules and eight financial datasets demonstrate the merits of RL4CEP in improving the overall profit, when compared to baseline and state-of-the-art approaches, with a reasonable consumption of resources, i.e., RAM and CPU. Finally, our experiments indicate that RL4CEP is executed quite fast compared to traditional CEP engines processing static rules.

Microstructural Assessment of Molybdenum Disulfide Coatings Using Nanoindentation Hardness.

MoS2 coatings are used extensively in aerospace and defense applications due to their ultralow friction and high wear resistance. Burnished and resin-bonded MoS2 coatings are commonly used in these applications due to simplicity in deposition and history of use, despite issues with consistency in coating properties and performance. Physical vapor deposition (PVD) of MoS2 thin films has emerged as a process alternative in the past 50 years, promising far greater control over film structure and composition but at a greater cost. Despite PVD's benefits, hesitance to adoption persists in high-consequence applications, not only due to increased costs but variability in resulting coating properties. These variations in properties and subsequent performance are in part due to the complexity of the PVD process and the sensitive interplay between coating process-structure-property relationships. This work aims to demystify the remaining uncertainties of the process-structure-property relationships in PVD MoS2. The microstructure and mechanical and tribological properties of 61 different PVD pure MoS2 coatings are examined herein. Emphasis has been placed on developing performance-based (i.e., hardness, modulus) metrics that can assess microstructural changes (density, orientation, and crystallinity) and be utilized to accelerate process development and coating optimization. Relationships established within suggest that nanoindentation hardness can be used to infer coating performance (i.e., wear rate) and properties (i.e., density, crystalline texture, and stoichiometry). Furthermore, this work demonstrates that PVD MoS2 coatings close to the theoretical density of MoS2 consistently have the best tribological performance and can be reliably identified by their hardness.

Biochemical and physiological characterization of Aedes aegypti midgut chymotrypsin.

The Aedes aegypti mosquito is a vector of dengue, Zika, and chikungunya. The mosquito's reliance on blood facilitates the transmission of these viral pathogens to humans. Digestion of blood proteins depends on the biphasic expression of serine proteases, with trypsin-like activity contributing to most of the activity in the midgut. Other proteases found (serine collagenase- and chymotrypsin-like) are thought to contribute to digestion, but their roles are largely understudied. Thus, elucidating the activity and specific roles of all midgut proteases will help understand the complexity of the digestion process and help validate them as potential targets for the development of a new vector control strategy. Herein, we focused on characterizing the activity profile and role of Ae. aegypti chymotrypsin (AaCHYMO). Knockdown studies resulted in elimination and significant reduction of chymotrypsin-like activity in blood fed midgut extracts, while in vitro fluorescent and blood protein digestion assays revealed important substrate specificity differences. Interestingly, knockdown of AaCHYMO did not impact fecundity, indicating the presence of an intricate network of proteases working collectively to degrade blood proteins. Further, knockdown of the ecdysone receptor (EcR) led to a decrease in overall AaCHYMO expression and activity in the mosquito, which may play an important regulatory role.

Silicon nitride grating coupler with suppressed waveguide backreflection and adaptive grate design.

We present both experimental and simulation results for a fully etched, C-band GC fabricated in an 800 nm silicon nitride platform that significantly reduces backreflections. They are minimized by truncating the initial grates, which deflect reflected light at an oblique angle and excite higher-order modes in the tapered waveguide that is filtered out. Insertion losses resulting from this modification of the grating coupler are mitigated by an adaptive redesign of the grates that corrects incurred errors in the generated phase front. While 2.4 dB of excess insertion losses is first introduced by the grate truncation, reshaping of the grates into ellipses of varying eccentricities reduces the excess losses to less than 1 dB. At the same time, the suppression of the waveguide-to-waveguide backreflection by 10 dB relative to a baseline device without the grate truncation is maintained. This demonstrates improved backreflection with a minimal cost in coupling efficiency and without an increase in the complexity of the fabrication process. Experimentally, insertion losses of -8.8 dB are achieved with a 3 dB passband of 65 nm and less than -25 dB waveguide-to-waveguide backreflections. Simulations show that with the over- and under-cladding thicknesses of a previous fabrication run, this passband and backreflection level can be achieved with -6.4 dB insertion losses.

Preprocessing choices for P3 analyses with mobile EEG: A systematic literature review and interactive exploration.

Preprocessing is necessary to extract meaningful results from electroencephalography (EEG) data. With many possible preprocessing choices, their impact on outcomes is fundamental. While previous studies have explored the effects of preprocessing on stationary EEG data, this research delves into mobile EEG, where complex processing is necessary to address motion artifacts. Specifically, we describe the preprocessing choices studies reported for analyzing the P3 event-related potential (ERP) during walking and standing. A systematic review of 258 studies of the P3 during walking, identified 27 studies meeting the inclusion criteria. Two independent coders extracted preprocessing choices reported in each study. Analysis of preprocessing choices revealed commonalities and differences, such as the widespread use of offline filters but limited application of line noise correction (3 of 27 studies). Notably, 59% of studies involved manual processing steps, and 56% omitted reporting critical parameters for at least one step. All studies employed unique preprocessing strategies. These findings align with stationary EEG preprocessing results, emphasizing the necessity for standardized reporting in mobile EEG research. We implemented an interactive visualization tool (Shiny app) to aid the exploration of the preprocessing landscape. The app allows users to structure the literature regarding different processing steps, enter planned processing methods, and compare them with the literature. The app could be utilized to examine how these choices impact P3 results and understand the robustness of various processing options. We hope to increase awareness regarding the potential influence of preprocessing decisions and advocate for comprehensive reporting standards to foster reproducibility in mobile EEG research.

A multifaceted analysis: Unveiling the complexities of wheat genotypes, fortification, and processing on iron and zinc bioavailability in whole wheat flour and chapati.

This study examines the complex interactions between wheat cultivar selection and fortification with NaFeEDTA and ascorbic acid (AA) on the bioavailability of iron (Fe) and zinc (Zn) in whole wheat flour (WWF) and chapati. Nineteen hexaploid wheat cultivars were rigorously assessed for their intrinsic Fe and Zn profiles, including total content (TC), solubility (S), and bio-accessibility (B), utilizing an in-vitro gastrointestinal model. Significant variations (P<0.05) were observed among cultivars, with Fe content ranging from 32.8mg.kg-1 to 42.8mg.kg-1 and Zn content ranging from 34.5mg.kg-1 to 43.8mg.kg-1 in WWF. Fortification with NaFeEDTA (T3: 250mg.kg-1) significantly increased total Fe TC in WWF by 85.0%, Fe and Zn solubility by 51.2% and 22.3%, and bio-accessibility by 165.5% and 84.2%, respectively, compared to control. Conversely, AA fortification (T3: 250mg.kg-1) elevated Fe and Zn solubility by 98.7% and 62.1%, and bio-accessibility by 282.2% and 230.5%, respectively, compared to control. Notably, cultivar-specific responses to both fortification strategies were also evident. When translated to chapati, both NaFeEDTA and AA fortification (T3) enhanced Fe and Zn bio-accessibility compared to unfortified chapati. The impact of fortification was cultivar-dependent, with certain cultivars showing greater efficacy in improving Fe and Zn bio-accessibility. Correlation analysis revealed intricate relationships among Fe and Zn bioavailability parameters, highlighting the importance of tailored fortification approaches. These findings have significant implications for optimizing fortification strategies to improve bioavailable Fe and Zn intake through wheat-based diets.

Advances and prospects for lactic acid production from lignocellulose.

Lactic acid is a versatile building block that can be produced via microbial fermentation. Owing to the high optical purity, approximately 90 % of lactic acid is produced by microbes. Recently, the biosynthesis of lactic acid from lignocellulose has concerned much attentions. However, the cost-effective process faces several obstacles because of the complex structure of lignocellulose. This review will comprehensively summarize the state-of-the-art lactic acid production from lignocellulose, including the commonly used lactate-producing microorganisms, the co-utilization of glucose and xylose for the lactic acid production, as well as the lactic acid production from lignocellulose hydrolysate. Furthermore, the strategies regarding the lignocellulosic lactic acid production via consolidated bioprocessing will be also discussed, which can greatly reduce the complexity of the fermentation process.

Soil-aged microplastics exhibit stronger effects than air- and rainwater-aged ones on the network complexity and assembly process of soil microbial community

Soil-aged microplastics exhibit stronger effects than air- and rainwater-aged ones on the network complexity and assembly process of soil microbial community

Effective data visualization strategies in untargeted metabolomics.

Covering: 2014 to 2023 for metabolomics, 2002 to 2023 for information visualizationLC-MS/MS-based untargeted metabolomics is a rapidly developing research field spawning increasing numbers of computational metabolomics tools assisting researchers with their complex data processing, analysis, and interpretation tasks. In this article, we review the entire untargeted metabolomics workflow from the perspective of information visualization, visual analytics and visual data integration. Data visualization is a crucial step at every stage of the metabolomics workflow, where it provides core components of data inspection, evaluation, and sharing capabilities. However, due to the large number of available data analysis tools and corresponding visualization components, it is hard for both users and developers to get an overview of what is already available and which tools are suitable for their analysis. In addition, there is little cross-pollination between the fields of data visualization and metabolomics, leaving visual tools to be designed in a secondary and mostly ad hoc fashion. With this review, we aim to bridge the gap between the fields of untargeted metabolomics and data visualization. First, we introduce data visualization to the untargeted metabolomics field as a topic worthy of its own dedicated research, and provide a primer on cutting-edge visualization research into data visualization for both researchers as well as developers active in metabolomics. We extend this primer with a discussion of best practices for data visualization as they have emerged from data visualization studies. Second, we provide a practical roadmap to the visual tool landscape and its use within the untargeted metabolomics field. Here, for several computational analysis stages within the untargeted metabolomics workflow, we provide an overview of commonly used visual strategies with practical examples. In this context, we will also outline promising areas for further research and development. We end the review with a set of recommendations for developers and users on how to make the best use of visualizations for more effective and transparent communication of results.

The Application and Analysis of Emotion Recognition Based on Modern Technology

This article provides a comprehensive analysis of various emotion recognition methods, focusing on speech emotion recognition, facial expression recognition, and physiological signal emotion recognition. The primary aim is to evaluate the advantages and disadvantages of these methods, offering insights into selecting the most appropriate approach for different application scenarios. The study involves collecting and analysing experimental data, exploring their respective strengths and limitations, and proposing potential solutions to enhance their effectiveness. Speech emotion recognition is effective but sensitive to noise and speaker variability, while facial expression recognition excels under controlled conditions but struggles with changes in lighting and angles. Physiological signal recognition offers deep insights into internal emotional states but requires complex signal processing and is vulnerable to external interferences. Despite the growing application of emotion recognition technology across various fields, including healthcare, traffic safety, and security, there remain significant challenges related to accuracy, robustness, and privacy. This study highlights the need for continued research to improve these technologies, particularly in enhancing their robustness and adaptability. The findings provide valuable guidance for researchers and practitioners seeking to optimize emotion recognition systems for diverse real-world applications.