Special Case Research Articles

MULTIDRUG RESISTANT DYSLIPIDEMIA: A CASE REPORT

Abstract Introduction Recently introduced lipid–lowering agents (PCSK9–i, bempedoic acid) can efficiently treat statin–intolerant patients, who couldn‘t reach LDL target before. Nonetheless, there are still cases where the pharmacological management may have strong limitations. Case Report A 71 year–old woman, with multiple cardiovascular risk factors (diabetes, hypertension and familial dylipidemia, LDL–C 276) underwent heart transplantation for a hypertrophic cardiomyopathy with an evolution towards a dilated phenotype in 2005. Before the transplant, she was on low–dose statin treatment (pravastatin 10 mg/die) that was suspended years later owing to hyper–CKemia (600 U/L), despite her being totally asymptomatic. A second attempt with simvastatin/ezetimibe 40/10 mg resulted again in elevation of CK levels, associated with significant muscular pain. Thus, just ezetimibe was continued. In 2020, 15 years after the transplant, the patient underwent a coronary angiography showing a moderate coronary allograft vasculopathy (ISHLT CAV2). Specifically, a sub occlusive ostial left main coronary artery lesion was treated by percutaneous angioplasty and stent implantation. Since a lower LDL target was needed (LDL–C 55 mg/dL), Alirocumab was introduced. However, 6 months later, no significant LDL levels reduction had been observed. The shift to evolocumab led to the same result, although the patient reported full therapeutic compliance. In the suspicion of anti–drug antibodies development, we opted for Inclisiran without achieving a significant decrease in LDL–C levels. In parallel with the search for genetic mutations in the PCSK9 gene and other genes involved in cholesterol metabolism (including LDLR, APOB, and LDLRAP1 and resulting positive only for common variants in LDLR receptor), therapy with bempedoic acid was initiated, again without substantial benefit (LDL–C 118 mg/dL). Conclusion Despite cholesterol management has been simplified by the introduction of new drugs, it may still be complex in patients requiring very low LDL–C levels in some specific cases. Drugs with a LDL receptor–independent mechanism of action (e.g., evinacumab) may allow the achievement of therapeutic goals suggested by clinical guidelines.

FAIR assessment of nanosafety data reusability with community standards.

Nanomaterials hold great promise for improving our society, and it is crucial to understand their effects on biological systems in order to enhance their properties and ensure their safety. However, the lack of consistency in experimental reporting, the absence of universally accepted machine-readable metadata standards, and the challenge of combining such standards hamper the reusability of previously produced data for risk assessment. Fortunately, the research community has responded to these challenges by developing minimum reporting standards that address several of these issues. By converting twelve published minimum reporting standards into a machine-readable representation using FAIR maturity indicators, we have created a machine-friendly approach to annotate and assess datasets' reusability according to those standards. Furthermore, our NanoSafety Data Reusability Assessment (NSDRA) framework includes a metadata generator web application that can be integrated into experimental data management, and a new web application that can summarize the reusability of nanosafety datasets for one or more subsets of maturity indicators, tailored to specific computational risk assessment use cases. This approach enhances the transparency, communication, and reusability of experimental data and metadata. With this improved FAIR approach, we can facilitate the reuse of nanosafety research for exploration, toxicity prediction, and regulation, thereby advancing the field and benefiting society as a whole.

Beyond subcultures: A literature review of gaming communities and sociological analysis

This article is a critical review of studies on gaming communities. In particular, it analyses the use of subcultural, post-subcultural and postmodern subcultural theorists in relation to video games players. Academic use of sociological concepts to study gaming communities, such as neo-tribe, subculture, lifestyle, and scene, is not always explained and almost all sociological instruments show limits in engaging the complex and changing phenomena of video gaming cultures. The article focuses on the misleading use of the term subculture and, therefore, analyses effective applications of post-subcultural and post-modern subcultural approaches to specific case studies. Eventually, the relation between gamers and video games cultures is analysed. In this sense, I argue that the complexity of gaming communities is difficult to be framed and I suggest the use of the Bourdieusian concept of champ.

The significance of structural components of lignocellulosic biomass on volatile organic compounds presence on biochar - a review

AbstractThe product of thermochemical processing of lignocellulosic biomass is biochar. It has a range of properties that make it suitable for a variety of economic applications. However, during pyrolysis and torrefaction, volatile organic compounds (VOCs) are released and may redeposit on the surface of the biochar. Some of these compounds may be harmful to the environment and humans. Bibliometric study shows that, to date, studies on the release of VOCs from biochar have been of an inventory nature and concerned with specific case studies of the specific types of biomass. To date, there has been no comprehensive and systematic analysis of the influence of lignocellulosic biomass properties and pyrolysis/torrefaction process parameters on VOC formation and redeposition on biochar. In this paper, the analysis is presented of the potential harmfulness of VOCs released during the thermochemical processing of lignocellulosic biomass components, based on cellulose, hemicellulose, and lignin pyrolysis/torrefaction chemistry data. 10 volatile organic compounds from cellulose, hemicellulose, and lignin pyrolysis were identified as potentially harmful due to the following properties: carcinogenicity, toxicity, flammability, skin corrosion/irritation, eye irritation, and mutagenicity, with different degrees of harmfulness. Additionally, the VOCs identified on biochar samples show a potential hazard. Among 140 identified compounds, 33 of them had harmful properties. Therefore, the redeposition on biochar of ketones, aldehydes, cyclic and aromatic hydrocarbons including polyaromatic hydrocarbons, and their derivatives, esters, and furans may lead to environmental contamination due to their release from biochar. A new niche for systematic research on the development of new knowledge regarding the biochars produced from biomass as a source of pollutant emission has been identified.

CEPB dataset: a photorealistic dataset to foster the research on bin picking in cluttered environments

Several datasets have been proposed in the literature, focusing on object detection and pose estimation. The majority of them are interested in recognizing isolated objects or the pose of objects in well-organized scenarios. This work introduces a novel dataset that aims to stress vision algorithms in the difficult task of object detection and pose estimation in highly cluttered scenes concerning the specific case of bin picking for the Cluttered Environment Picking Benchmark (CEPB). The dataset provides about 1.5M virtually generated photo-realistic images (RGB + depth + normals + segmentation) of 50K annotated cluttered scenes mixing rigid, soft, and deformable objects of varying sizes used in existing robotic picking benchmarks together with their 3D models (40 objects). Such images include three different camera positions, three light conditions, and multiple High Dynamic Range Imaging (HDRI) maps for domain randomization purposes. The annotations contain the 2D and 3D bounding boxes of the involved objects, the centroids’ poses (translation + quaternion), and the visibility percentage of the objects’ surfaces. Nearly 10K separated object images are presented to perform simple tests and compare them with more complex cluttered scenarios tests. A baseline performed with the DOPE neural network is reported to highlight the challenges introduced by the novel dataset.

New Uses of q-Generalized Janowski Function in q-Bounded Turning Functions

In this paper, we discussed a new subclass JQ⅁,AB(q) of bi-univalent functions in the unit disk U using q-generalized Janowski function and q-derivative. Additionally, certain properties were examined and effectively demonstrated, such as the second Hankel determinant, Fekete–Szegö estimates, and Coefficients Bounds. Each of these bounds were precise and were confirmed by finding the extremal function for the new class. Furthermore, there are in-depth conversations available regarding certain intriguing specific cases of the outcomes achieved.

Lightweight Potential of Anisotropic Plate Lattice Metamaterials

Additive manufacturing enables the production of lattice structures, which have been proven to be a superior class of lightweight mechanical metamaterials whose specific stiffness can reach the theoretical limit of the upper Hashin–Shtrikman bound for isotropic cellular materials. To achieve isotropy, complex structures are required, which can be challenging in powder bed additive manufacturing, especially with regard to subsequent powder removal. The present study focuses on the Finite Element Method simulation of 2,5D anisotropic plate lattice metamaterials and the investigation of their lightweight potential. The intentional use of anisotropic structures allows the production of a cell architecture that is easily manufacturable via Laser Powder Bed Fusion (LPBF) while also enabling straightforward optimization for specific load cases. The work demonstrates that the considered anisotropic plate lattices exhibit high weight-specific stiffnesses, superior to those of honeycomb structures, and, simultaneously, a good de-powdering capability. A significant increase in stiffness and the associated surpassing of the upper Hashin–Shtrikman bound due to anisotropy is achievable by optimizing wall thicknesses depending on specific load cases. A stability analysis reveals that, in all lattice structures, plastic deformation is initiated before linear buckling occurs. An analysis of stress concentrations indicates that the introduction of radii at the plate intersections reduces stress peaks and simultaneously increases the weight-specific stiffnesses and thus the lightweight potential. Exemplary samples illustrate the feasibility of manufacturing the analyzed metamaterials within the LPBF process.

Integrating generative AI into financial market prediction for improved decision making

This study provides an in-depth analysis of the model architecture and key technologies of generative artificial intelligence, combined with specific application cases, and uses conditional generative adversarial networks ( cGAN ) and time series analysis methods to simulate and predict dynamic changes in financial markets. The research results show that the cGAN model can effectively capture the complexity of financial market data, and the deviation between the prediction results and the actual market performance is minimal, showing a high degree of accuracy. Through investment return analysis, the application value of model predictions in actual investment strategies is confirmed, providing investors with new ways to improve the decision-making process. In addition, the evaluation of model stability and reliability also shows that although there are still challenges in responding to market emergencies, overall, GAI technology has shown great potential and application value in the field of financial market prediction. The conclusion points out that integrating generative artificial intelligence into financial market forecasts can not only improve the accuracy of forecasts, but also provide powerful data support for financial decisions, helping investors make more informed decisions in a complex and ever-changing market environment. choose.

Asset pricing and hedging in financial markets with fixed and proportional transaction costs

AbstractWe establish the asset pricing and hedging principle in a financial market model, which is a specific case of the von Neumann-Gale dynamical system, with both fixed and proportional transaction costs and trading constraints. The main results are hedging criteria stated in terms of consistent valuation systems, generalizing the notion of an equivalent martingale measure.

Assessing the Impact of Climate Changes, Building Characteristics, and HVAC Control on Energy Requirements under a Mediterranean Climate

Despite efforts to mitigate climate change, annual greenhouse gas emissions continue to rise, which may lead to the global warming of our planet. Buildings’ thermal energy needs are inherently linked to climate conditions. Consequently, it is crucial to evaluate how climate change affects these energy demands. Despite extensive analysis, a comprehensive assessment involving a diverse range of building types has not been consistently conducted. The primary objective of this research is to perform a coherent evaluation of the influence of climate changes, construction element properties, and the Heating, Ventilation, and Air Conditioning (HVAC) system type of control on the energy requirements of six buildings (residential, services, and commercial). The buildings are considered to be located in a temperate Mediterranean climate. Our focus is on the year 2070, considering three distinct climatic scenarios: (i) maintaining the current climate without further changes, (ii) moderate climate changes, and (iii) extreme climate changes. The buildings are distributed across three different locations, each characterized by unique climatic conditions. Buildings’ envelope features a traditional External Thermal Insulation Composite System (ETICS) and expanded polystyrene (EPS) serves as thermal insulation material. Two critical design factors are explored: EPS thickness ranging from 0 (no insulation) to 12 cm; and horizontal external fixed shading elements varying lengths from 0 (absence) to 150 cm. Six alternative setpoint ranges are assessed for the HVAC system control: three based on the Predicted Mean Vote (PMV) and three based on indoor air temperature (Tair). Results were obtained with a validated in-home software tool. They show that, even under extreme climate conditions, the application of thermal insulation remains energetically favorable; however, its relative importance diminishes as climate severity increases. Then, proper insulation design remains important for energy efficiency. The use of external shading elements for glazing (e.g., overhangs, louvers) proves beneficial in specific cases. As climate changes intensify, the significance of shading elements grows. Thus, strategic placement and design are necessary for good results. The HVAC system’s energy consumption depends on the level of thermal comfort requirements, on the climate characteristics, and on the building’s type of use. As climate change severity intensifies, energy demands for cooling increase, whereas energy needs for heating decrease. However, it is essential to recognize that the impact of climate changes on HVAC system energy consumption significantly depends on the type of building.

The Importance of Analysis of Judicial Circumstances in the Sentence Dosimetry Process

The Constitution plays an important role as a point of reference for the critical analysis of the criminal system, not only because it derives from the legal assets susceptible to punitive protection, but also and among other reasons, because the principles enshrined as a government norm in the Penal Code governing The imposition of sanctions is a clear development of the constitutional text and doctrine that the Constitutional Court has been building with its pronouncements, in the form that criminal law must acquire. The dosimetry of punishment in Brazil takes a three-step approach, pushing the system of fixed sanctions implemented by the legislature or the full discretion of the judge, promoting, on the other hand, a distribution of functions between the two, as he chooses the minimum and maximum sentence levels and dosage parameters, and this determines the sanction in the specific case from the legal criteria. In this sense, the present research aims to analyze the importance of analyzing judicial circumstances in the process of penalty dosimetry. The specific objectives are: to present a brief history of criminal legislation in Brazil, to review the most recent literature on the application of the penalty and its principles, to analyze the relationship between the dosimetry of the penalty and judicial circumstances and to point out cases in the jurisprudence that materialize the revised theory. Thus, given the relevance of the theme in the current legal scenario, the research is justified by discussing a contemporary theme. Through research on the principles of exceptionality, state of innocence, motivation of decisions and proportionality and the dosimetry of the penalty, possible judgments of the judge that relate the dosimetry of the penalty with the principles of human rights will be discussed. The judge should take charge of the evidence produced in relation to the facts that, in his opinion, influence the minor or major measure of the exact penalty to be imposed. The lack of motivation currently constitutes a violation of the constitutional guarantee of due process and absolute grounds for invalidity under the Criminal Procedure Code.

A Balancing Act: Data Protection Compliance of Artificial Intelligence

Abstract Neural network based generative artificial intelligence (GenAI) systems, in particular large language models (LLMs), hold huge potential for economic, scientific, and artistic progress. However, they are also the subject of ongoing fierce data protection debates. Some even doubt whether GenAI systems can4, at least in principle, comply with the General Data Protection Regulation (EU) 2016/679 (GDPR). This issue was highlighted by a temporary ban of ChatGPT by the Italian data protection authority in March 2023. To answer the question of possible compliance with the GDPR, this paper will first illustrate relevant technical aspects and then examine the extent to which GenAI systems process personal data. A distinction will be made between training, use, and the system itself as stored on a hard drive. On this basis, this paper addresses the key question of the lawfulness of the respective processing activities, bearing in mind that each specific use case of any GenAI system requires a specific data protection assessment. While the issues discussed in this paper are relevant to GenAI systems in general, they are particularly relevant to LLMs trained on large amounts of text-based personal data. As one result, the analysis identifies serious challenges in the application of the GDPR to LLMs. However, with no significant updates to the relevant GDPR provisions in sight, this paper aims to show how pragmatic solutions are both necessary and largely possible even under the current legal framework. This includes practical guidance for developers and users on how to ensure compliance.

Simulation of Sloped-Bed Tuned Liquid Dampers Using a Nonlinear Shallow Water Model

Simulation of Sloped-Bed Tuned Liquid Dampers Using a Nonlinear Shallow Water Model

Does Fertility Culture Matter in Reproductive Decision Making? A Case Study of a Chinese Multi-child Family

This study delves into individual cases within multi-child families, building upon a literature review of sociocultural factors influencing reproductive decision-making. Although previous research has highlighted the significant influence of societal factors on reproductive choices, there is a knowledge gap regarding specific cases within multi-child families, necessitating a more in-depth investigation. The research question is framed as follows: "How do sociocultural factors interact in the reproductive decision-making of multi-child families, influencing family interactions and dynamics?" Using a case study approach, this paper employs a qualitative methodology by conducting semi-structured interviews to gather data. Grounded theory is applied for in-depth qualitative analysis. Findings reveal the pivotal role of sociocultural factors in internal family dynamics, supporting and extending previous research. Theoretical implications highlight a nuanced understanding of multi-child family dynamics, while practical implications underscore the need for tailored family support programs. This research contributes theoretical insights and practical guidance for addressing the unique needs of multi-child families in reproductive decision-making processes.

Study on the Determination of the Nature of Trademark Dilution--Taking the "Lao Gan Ma Case" as an Example

China's current legislation does not make clear provisions for the dilution of well-known trademarks, resulting in difficulties in identifying dilution cases in practice. One such notable instance is the "Lao Gan Ma" dispute, which serves as a telling example of this legal gray area. Consequently, it becomes imperative to delve into typical cases like the "Lao Gan Ma Case" to gain clarity on the disputed actions' legal nature, and then demonstrate how the dilution theory can be applied in the determination of specific cases. Utilizing the case study method, this paper aims to examine a particular case of trademark dilution in detail. The initial focus is on clarifying the concept of trademark dilution and its constituent elements of determination. This theoretical foundation is essential for accurately analyzing the nature of the complained-of infringing act. The significance of this paper is to theoretically solve the problem of determining the nature of dilution under the system of China's Trademark Law, to provide a reference for the determination of the same type of cases in the future, and hopefully to provide ideas for the future legislation on trademark dilution in China.

Fuzzy-Based Robot Behavior with the Application of Emotional Pattern Generator

The article deals with the development of human–robot interaction, where the robot measures the user’s emotional state as well as environmental factors by different devices, and it responds to the user with colorful patterns and controls the smart home through the guidance of the Internet of Things system. Before the design process, robots and their functions currently on the market, the role of emotions in communication, and technologies for measuring emotion (such as face recognition, measurement of heart rate, breath, and physical changes) are presented in detail. The designed robot (Em-Patty) uses a previously developed emotion-based automatic pattern generation system based on a fuzzy system, which is a suitable tool for handling emotions. A main and three fuzzy subsystems are fusioned in order to create the most efficient control system for Em-Patty. The nature-inspired design of the robot is also presented, as well as a description of its behavior with the help of a specific case study.

A digital twin model of the axial temperature field of a DC cable for millisecond calculations

The most important features of digital twin technology for transmission and transformation equipment are symbiotic evolution and state prediction. In constructing the digital twin model for DC cables, the transient and steady-state temperature fields need to be considered comprehensively in the modeling process to consider the multi-physical field coupling, mathematical model, operational data, and environmental conditions in specific cases, which makes it difficult to satisfy the real-time requirements of the digital twin. To solve this problem, in this paper, a digital twin technology architecture for DC cables is proposed, and a neural network learning model is constructed to minimize the latency due to the complexity of the model simulation. Moreover, an efficient digital twin model that is based on the model-driven approach is developed for the fast computation of the axial temperature field of DC cables. The use of the Sequence-to-Sequence residual neural network algorithm for the reduced-order multi-physics field coupling modeling reduces the computational time and ensures as much accuracy as possible up to the finite element model simulation. The simulation results show that the use of the digital twin model reduces the simulation time from 275 s to 0.56 s, and the relative error between the accuracy of the digital twin model and the finite element model for the axial temperature field of the DC cable is 0.46 %. Finally, verification of the reasonableness and feasibility of the proposed method is carried out via an experimental platform according to the standard of CIGRE TB496. In particular, the maximum value of the DC cable temperature is verified to have a small error compared with the result of the Sequence-to-Sequence calculation under specific working conditions.

Penerapan Etika Komunikasi Reception Pada Divisi Kantor Depan Dalam Pelayanan Tamu Check In Di Javana Royal Vila Seminyak Bali

The Increasing competition among accommodation supplies require it to keep optimizing its services in order to give the impression of loyalty to guests to stay. In more specific case, receptionists hold important rules to improve their services, especially in communication ethics. This study is conducted in Javana Royal Villa Seminyak Bali, under the title of Penerapan Etika Komunikasi Reception Pada Front Office Department Dalam Pelayanan Tamu Check in di Javana Royal Villa Seminyak. Bali. This research aims to determine the application of reception communication ethics and the influence of the application of reception communication ethics toward room occupancy rate at Javana Royal Villa Seminyak Bali. This study uses qualitative descriptive in which the translation of words or sentences are explained in the presentation. Moreover, the data collection techniques used are observation, interviews and documentation. The types of data used are primary data and secondary data. The study showed that by not concerning attention to communication ethics, it will greatly impact the comfort of guests in staying which results in bad reviews on the online travel agent so that in this case it certainly has a huge impact on the level of room reservations or on room occupancy in Javana Royal Villa Seminyak Bali.

Exploring feminist translation in Liu Cixin’s The Three-Body Trilogy

ABSTRACT According to the interventionist feminist translation theory, sexist ideas found in source texts should be questioned and corrected. In some materials, signs of sexism are embodied in some unnecessary and inappropriate emphases regarding women’s gender attributes, which are almost related to certain stereotypical images. The present paper aims to explore how these problematic emphases could be treated in a feminist translation praxis applying a contrastive study of the original texts and some solutions provided by translators. To this end, the current work is designed to focus on the study of six specific cases that have been collected from Liu Cixin’s The Three-Body Trilogy, a well-known Chinese science fiction novel that has sparked widespread controversy in terms of sexism. In each case, after studying the questionable original Chinese fragment, I will analyze its translations into English and Spanish to assess whether the sexism found in the source text can be attenuated or avoided after the translation process. This study will shed some light on how translators could deal with sexist emphases from a feminist approach.

Analysis of pipeline leakage in unsaturated stratum: A new seepage-diffusion model

Accurate prediction of the spread of fluids leaking from underground pipelines is crucial for risk assessment. In this study, we developed a method for predicting the diffusion range of pipeline seepage fluids within an unsaturated stratum. First, we derived a seepage–diffusion equation based on the generalized Darcy’s law and subsequently analyzed the mechanism of fluid diffusion in the unsaturated stratum. We then constructed a model for the seepage–diffusion of a pipeline leakage fluid, incorporating variables such as the saturation, permeability coefficient, diffusion pressure, and diffusion distance of soil microelements across various time intervals, using a stepwise algorithm in tandem with the Green–Ampt model and VG–Mualen permeability coefficient function. We investigated the influence of fluid self-gravity, saturated permeability coefficient, initial saturation, and intra-pipe pressure on the diffusion distance of the pipeline leakage fluid in an unsaturated stratum, focusing on specific cases. The results indicate that an increase in the saturated permeability coefficient, initial saturation, and intra-pipe pressure leads to an increase in the fluid diffusion distance. A simulation test was conducted to validate the proposed seepage–diffusion model. The findings of this study can be employed to predict the diffusion range of pipeline leakage fluids in various formation types, providing a vital foundation for pipeline leakage accident management.