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Inhaled aerosols as carriers of pulmonary medicines and the limitations of in vitro – in vivo correlation (IVIVC) methods
No full textPulmonary drug delivery (PDD) involves flow and deposition of aerosol particles acting as carriers of drugs delivered onto the surface of the airways. As a direct consequence, optimal PDD requires controlling of drug aerosolization processes and deep understanding of multiphase flows in complex geometry of the airways including aerosol particle dynamics during the transient inhalation cycles. A chemical engineering-based approache can be effectively used to analyze these processes and help in designing optimized drug formulations and more effective drug delivery devices (inhalers). One of prerequisites of improved PDD is the knowledge of in vivo–in vitro correlation (IVIVC) for inhaled drugs that would allow establishment of the relationships between aerosol quality determined using ex vivo methods (such as determination of particle size, deposition in reconstructed anatomical structures, pharmacokinetics/pharmacodynamics using in vitro cellular systems, or in silico modeling of aerosol dynamics) in connection to the clinical effects. This manuscript discusses the challenges of the IVIVC analyses for aerosol delivery systems. The primary focus is given to the physical and physicochemical constraints in the PDD that can be effectively described and investigated using engineering approaches
Markov approach for inventory control with meta-heuristics in intermittent demand environment
No full textDemand variability directly affects inventory management. The variability of intermittent demand causes high lost sales or holding costs. While lost sales reduce customer satisfaction, keeping excessive stock also creates high costs for companies. This situation can be prevented with an appropriate inventory policy. In this study, a Markov-based proactive inventory management approach supported by metaheuristic methods is proposed in the inventory management of intermittent demands. The main contribution of the proposed approach is to find a lower and upper limit for stock by modeling the intermittent demands in the past period with the Markov process. With these optimized limits, it is aimed to balance the largest costs caused by intermittent demands, namely stock and lost sales costs. The intermittent demands used were randomly generated in 4 different sizes from small to large. The proposed approach contributes to inventory management by minimizing the negativities caused by demand variability through the Markov process. A mathematical model has been proposed for stock level optimization, but no feasible solution has been found. The mathematical model was transformed into a fitness function and a solution was provided with the Tabu Search Algorithm and Simulated Annealing. The inventory management process of intermittent demand was first evaluated without the Markov approach, and then the Markov approach was included in the process. The results showed that the Markov approach was a good tool for inventory management of intermittent demand. When the results were examined, the stock limits computed with the Markov process balanced the increased inventory cost and lost sales costs due to intermittent demand
High-Level Synthesis using SDF-AP, Template Haskell, QuasiQuotes, and GADTs to Generate Circuits from Hierarchical Input Specification
Get PDFFPGAs provide highly parallel and customizable hardware solutions but are traditionally programmed using low-level Hardware Description Languages (HDLs) like VHDL and Verilog. These languages have a low level of abstraction and require engineers to manage control and scheduling manually. High-Level Synthesis (HLS) tools attempt to lift this level of abstraction by translating C/C++ code into hardware descriptions, but their reliance on imperative paradigms leads to challenges in deriving parallelism due to pointer aliasing and sequential execution models. Functional programming, with its inherent purity, immutability, and parallelism, presents a more natural abstraction for FPGA design. Existing functional hardware description tools such as Clash enable high-level circuit descriptions but lack automated scheduling and control mechanisms. Prior work by Folmer introduced a framework integrating SDF-AP graphs into Haskell for automatic hardware generation, but it lacked hierarchy and reusability. This paper extends that framework by introducing hierarchical pattern specification, enabling structured composition and scalable parallelism. Key contributions include: (1) automatic hardware generation, where both data and control paths are derived from functional specifications with hierarchical patterns, (2) parameterized buffers using GADTs, eliminating the need for manual buffer definitions and facilitating component reuse, and (3) provision of a reference "golden model" that can be simulated in the integrated environment for validation. The core focus of this paper is on methodology. But we also evaluate our approach against Vitis HLS, comparing both notation and resulting hardware architectures. Experimental results demonstrate that our method provides greater transparency in resource utilization and scheduling, often outperforming Vitis in both scheduling and predictability
An ontological lens on attack trees:Toward adequacy and interoperability
Get PDFAttack Trees (AT) are a popular formalism for security analysis. They are meant to display an attacker's goal decomposed into attack steps needed to achieve it and compute certain security metrics (e.g., attack cost, probability, and damage). ATs offer three important services: (a) conceptual modeling capabilities for representing security risk management scenarios, (b) a qualitative assessment to find root causes and minimal conditions of successful attacks, and (c) quantitative analyses via security metrics computation under formal semantics, such as minimal time and cost among all attacks. Still, the AT language presents limitations due to its lack of ontological foundations, thus compromising associated services. Via an ontological analysis grounded in the Common Ontology of Value and Risk (COVER) -- a reference core ontology based on the Unified Foundational Ontology (UFO) -- we investigate the ontological adequacy of AT and reveal four significant shortcomings: (1) ambiguous syntactical terms that can be interpreted in various ways; (2) ontological deficit concerning crucial domain-specific concepts; (3) lacking modeling guidance to construct ATs decomposing a goal; (4) lack of semantic interoperability, resulting in ad hoc stand-alone tools. We also discuss existing incremental solutions and how our analysis paves the way for overcoming those issues through a broader approach to risk management modeling
Sex-based differences in musculoskeletal pain among surgeons:an international survey
Get PDFIntroduction: Musculoskeletal (MSK) injury is a known occupational risk for surgeons. Few studies have focused on the impact of sex in MSK injuries, despite differences in physical characteristics that may influence MSK pain occurrence. The increasing number of female surgeons urges investigation on ergonomic challenges faced by this group. The aim of the survey was to evaluate incidence and impact of MSK pain among surgeons to assess sex-based differences in the occurrence of MSK pain.Methods: A survey comprised of demographic/practice-related questions, validated scales for work-related MSK pain assessment and effect of health impairment on quality of life (QoL) was electronically distributed. Primary outcome was MSK pain incidence across sex evaluated with comparative and logistic regression analysis.Results: 1162 surgeons completed the survey (48.02% females, 51.98% males). Significant differences across demographic factors were identified whereas surgical platforms used were similar across sexes. Female surgeons reported higher frequency of MSK pain (p = < 0.0001), and significant difference in MSK pain location. Higher burden of MSK pain in females was noted, with higher rates of “numbness”, “pain” and “ache” and less often “none” with respect to the male group (p = 0.020). Higher MSK pain frequency was associated with depression-like feelings, painkiller use and work absence (p = < 0.0001).Conclusions: There are striking sex-based differences in work-related MSK pain across surgeons. Female surgeons experience more MSK pain than males and suffer of subsequent impacts on routine work, function, and QoL. These results highlight the need to promote appropriate surgical ergonomics in the operating room for the expanding population of female surgeons.</p
Behavioral Analysis of a Digital Twin using Logging and Model Learning
Get PDFOver the last few years, digital twins (DTs) have attracted increasing attention and uptake in both industry and academia. While several definitions exist for a DT, most of these focus on an exact virtual replica (often called the virtual entity (VE)) of a real-world object or process, which typically consists of several executable models interacting with each other. Furthermore, due to the connection and synchronization with their real-world physical counterpart, DTs evolve continuously across their lifecycle. Often, however, details of construction and internal structure of DTs are left un- or underspecified. Over time, both these factors (un(der)specification and real-time changes due to synchronization) might lead to misuse, undesirable behavior, or runtime issues, like errors, and performance problems. This hinders the (re)use of DTs and/or its components for the intended purpose or any other future purposes. In this paper, we propose a new approach that helps to overcome the above sketched issues. We do so, in a case-driven way, by addressing a DT of an autonomously driving truck, developed by several researchers over a longer period of time, and with input of several MSc and PhD students. As it turns out, this DT lacks overall complete documentation. We demonstrate how logging can be used to learn the actual runtime behavior of a DT and show how this behavior can differ from its intended behavior at design stage. We explore different passive model learning techniques, such as state merging and process mining, to automate the process of obtaining behavioral models of the DT. In addition, we showcase how the learned behavioral model of the DT can be analyzed further to detect underlying causes of perceived runtime issues in DTs.</p
Invited preconference workshop: 'Prolonged grief in adults and children: assessment, theory, and treatment'
No full textProlonged Grief Disorder (PGD) is a trauma- and stressor related disorder, newly included in DSM-5-TR and ICD-11. It occurs in an estimated 5% of people experiencing the death of a close person. Risk factors include close relationship to the lost person and circumstances of the death—with traumatizing circumstances considerably elevating the change of developing PGD (plus symptoms of PTSD, depression, and other disorders). Increasing clinical and research work has increased our understanding of how to diagnose and treat PGD. In this workshop a state-of-the-art overview of the phenomenology, diagnostic assessment, underlying psychological mechanisms, and psychological treatments of PGD will be given. Attention will be paid both to adults, as well as children and adolescent. Issues addressed include: • What are differences between PGD and “healthy” grief?• What instruments and methods can be used to assess PGD and associated problems?• What are risk factors and protective factors (and why is it useful for bereavement care to have knowledge on these matters)?• When are preventive and curative treatments indicated?• How can PGD best be treated from a cognitive behavioral perspective?• What are advances in online treatment?This interactive workshop combines research (e.g., presenting research findings) with practice (e.g., training with screening instruments, providing case examples, demonstrating treatment materials, and conducting role-play exercises)
Guided versus unguided online grief-specific cognitive behavioral therapy for adults who lost a loved one during the COVID-19 pandemic:A controlled trial
Get PDFThe loss of a loved one during the COVID-19 pandemic was considered a potentially traumatic loss, increasing the risk of prolonged grief. This controlled study examined the short- and long-term effects of guided versus self-guided online cognitive behavioral therapy (CBT) on prolonged grief (PG), posttraumatic stress (PTS), and depression symptoms in people bereaved during the pandemic. Dutch adults (N = 131; 84% female) who lost a loved one ≥ 3 months prior were allocated to a therapist-guided (n = 67) or self-guided (n = 64) online CBT. Outcomes were measured using validated instruments through telephone interviews at baseline, immediately post-treatment, and six months post-treatment. Participants completed an 8-week online CBT. Multilevel analyses were performed. Both online CBTs were effective, but guided online CBT led to larger reductions in PG and PTS symptoms immediately post-treatment and at six-month post-treatment (but not depression). Early online CBT can effectively decrease grief-related distress in pandemic-bereaved people
Why Do You Buy?:Introducing a Reflective Café Approach to Foster Mindful Clothing Purchases in Generation Z
Get PDFAddressing experimental self-generation of frequency combs in III-V/SiN hybrid integrated tunable lasers
Get PDFWe present experimental results featuring the self-generation of optical frequency combs in a III-V/SiN hybrid integrated laser with a frequency selective mirror. We model the laser through a set of time-delayed algebraic equations accounting for longitudinal mode competition, non-zero alpha factor and the narrowband SiN mirror. We are able to produce frequency combs matching the experimental case in terms of bandwidth, free-spectral range and optical frequency spectrum. Supported by our model, we demonstrate that the optical frequency combs occur when the laser becomes CW unstable due to the resonance between the relaxation oscillation frequency and the frequency separation between cavity modes, and efficient four-wave mixing allows for the locking mechanism between optical lines. The comb is characterized by both amplitude and frequency modulation.</p