bluuebunny/crossref_metadata_2025_split huggingface dataset:
Haemodynamic forces predicting remodelling and outcome in patients with heart failure treated with sacubitril/valsartan
Authors: Fabiani Iacopo , Pugliese Nicola Riccardo , Pedrizzetti Gianni , Tonti Giovanni , Castiglione Vincenzo , Chubuchny Vladislav , Taddei Claudia , Gimelli Alessia , Del Punta Lavinia , Balletti Alessio , Del Franco Annamaria , Masi Stefano , Lombardi Carlo Mario , Cameli Matteo , Emdin Michele , Giannoni Alberto 
Published: July 2023

AbstractAimsA novel tool for the evaluation of left ventricular (LV) systo‐diastolic function through echo‐derived haemodynamic forces (HDFs) has been recently proposed. The present study aimed to assess the predictive value of HDFs on (i) 6 month treatment response to sacubitril/valsartan in heart failure with reduced ejection fraction (HFrEF) patients and (ii) cardiovascular events.Methods and resultsEighty‐nine consecutive HFrEF patients [70% males, 65 ± 9 years, LV ejection fraction (LVEF) 27 ± 7%] initiating sacubitril/valsartan underwent clinical, laboratory, ultrasound and cardiopulmonary exercise testing evaluations. Patients experiencing no adverse events and showing ≥50% reduction in plasma N‐terminal pro‐B‐type natriuretic peptide and/or ≥10% LVEF increase over 6 months were considered responders. Patients were followed up for the composite endpoint of HF‐related hospitalisation, atrial fibrillation and cardiovascular death. Forty‐five (51%) patients were responders. Among baseline variables, only HDF‐derived whole cardiac cycle LV strength (wLVS) was higher in responders (4.4 ± 1.3 vs. 3.6 ± 1.2; p = 0.01). wLVS was also the only independent predictor of sacubitril/valsartan response at multivariable logistic regression analysis [odds ratio 1.36; 95% confidence interval (CI) 1.10–1.67], with good accuracy at receiver operating characteristic (ROC) analysis [optimal cutpoint: ≥3.7%; area under the curve (AUC) = 0.736]. During a 33 month (23–41) median follow‐up, a wLVS increase after 6 months (ΔwLVS) showed a high discrimination ability at time‐dependent ROC analysis (optimal cut‐off: ≥0.5%; AUC = 0.811), stratified prognosis (log‐rank p < 0.0001) and remained an independent predictor for the composite endpoint (hazard ratio 0.76; 95% CI 0.61–0.95; p < 0.01), after adjusting for clinical and instrumental variables.ConclusionsHDF analysis predicts sacubitril/valsartan response and might optimise decision‐making in HFrEF patients.
A probabilistic cross‐impact methodology for explorative scenario analysis
Authors: Roponen Juho , Salo Ahti 
Published: July 2023

AbstractAs one of the approaches to scenario analysis, cross‐impact methods provide a structured approach to building scenarios as combinations of outcomes for selected uncertainty factors. Although they vary in their details, cross‐impact methods are similar in that they synthesize expert judgments about probabilistic or causal dependencies between pairs of uncertainty factors and seek to focus attention on scenarios that can be deemed consistent. Still, most cross‐impact methods do not associate probabilities with scenarios, which limits the possibilities of integrating them in risk and decision analysis. Motivated by this recognition, we develop a cross‐impact method that derives a joint probability distribution over all possible scenarios from probabilistically interpreted cross‐impact statements. More specifically, our method (i) admits a broad range of probabilistic statements about the realizations of uncertainty factors, (ii) supports the process of eliciting such statements, (iii) synthesizes these judgments by solving a series of optimization models from which the corresponding scenario probabilities are derived. The resulting scenario probabilities can be used to construct Bayesian networks, which expands the range of analyses that can be carried out. We illustrate our method with a real case study on the impacts of three‐dimensional (3D)‐printing on the Finnish Defense Forces. The scenarios, their probabilities, and the associated Bayesian network resulting from this case study helped explore alternative futures and gave insights into how the Defence Forces could benefit from 3D‐printing.
Establishing Quality Metrics for Systems Engineering Process
Authors: Powell Rusty , Jandreau Tyler 
Published: July 2023

AbstractSoftware engineering companies such as Motorola have clearly defined, robust processes to ensure overall process and system quality. Using Motorola's approach as a baseline, the authors established a process to determine system complexity to support the Systems Engineering & Integration (SE&I) lifecycle. To quantify complexity, the authors established a process including structural complexity (focused on system form), dynamic complexity (focused on system function), and social complexity (focused on identified stakeholders), the sum of which define complexity points. The authors further expanded the process by defining key metrics and parameters to support evaluation throughout the SE&I phases from concept to operationalization. This process, which utilizes fundamentals of Agile Software Development, allows systems engineers (SEs) and program managers (PMs) to quantitatively compare SE&I phases, systems, or projects of different sizes and dollar values to categorize, assess, forecast lifecycle costs, and performance to improve performance with customer satisfaction in mind. Through a satellite system example, the authors present the metrics to support associated analysis through the SE&I lifecycle.
Crafting an Experience‐Based Master's Program in Systems Engineering
Authors: Bronston Marshall , Berenbach Brian , Angel Joe , Doerr Jeremy 
Published: July 2023

AbstractThe Professional Masters in Applied Systems Engineering (PMASE) program provides students with practical and academic material in a setting like a typical work environment. This paper describes the first course in the two‐year program from the perspective of how a “high touch” course provides learning depth. It describes the approach used to provide students with a realistic environment giving academic and practical experience balancing work and studies in an intensive program which culminates in a capstone project. The paper should be of interest to companies and universities interested in a holistic, condensed systems engineering training program.
Configuration Management for Model Based Systems Engineering ‐ An example from the Aerospace Industry
Authors: D'Souza Adriana , Thota Phanikrishna 
Published: July 2023

AbstractModel Based Systems Engineering approach is increasingly used to manage the complexity of modern systems and to reduce costs of their development. In the Aerospace industry, modelling and simulation is not only a cost effective verification and validation strategy where test rigs and flight tests are far more expensive but also is increasingly used in the certification process. Nevertheless, as with any digital artefact, if the models aren't configured and traceability isn't assured, then the models are not of much use. Configuration Management comes into play as a key discipline to enable the use and maintenance of the models. This paper explores the use of Configuration Management for modelling and simulation in an aerospace setting, with a specific example involving landing gear and its surrounding systems.
A generic hierarchical System of Systems Engineering (SOS) Approach for Model based System Engineering (MBSE) Projects
Authors: Pandey Mohinder 
Published: July 2023

AbstractModel based systems engineering (MBSE) has been accepted worldwide by many industries, including the automotive industry, for several years. Hundreds of projects have already been developed and deployed using MBSE approaches. MBSE is gaining importance because it provides systems advantageous life cycle processes, such as returns of investments and meeting the demands of global marketplaces, as they become increasingly complex. Consequently, the number and pace of deployment using MBSE approaches will increase in the future.Our current work objective is to define a generic MBSE methodology compatible with Systems Engineering Body of Knowledge (SEBOK) functional decomposition principles, ‘Automotive open systems architecture’ (AUTOSAR) developments and compliant to ‘Automotive software performance improvement and capability determination’ (ASPICE) processes using the ‘systems modelling language’ (SysML). We have proposed a generic SysML process framework, a hierarchical system of systems (SOS) engineering approach and automation solutions. We have shown that the proposed solution helps meet the defined objectives. The work is targeted and relevant for automotive industry MBSE practitioners. In general, the research, apart from transportation and mobility industries, can also be used in other industries.
Market discipline and the risk‐taking behaviour of banks in India
Authors: Bhat Dilawar Ahmad , Chanda Udayan , Bhat Anil K. 
Published: July 2023

AbstractAfter the financial crisis, the Indian banking system has accumulated a mountain of bad loans which has crippled the banking sector and halted the credit flow to the industry. Several immediate causes for the bad loan crisis have been pointed out. However, poor market discipline, the ultimate root cause of the bad loan crisis, has not been paid adequate attention. This study seeks to investigate how effectively the market disciplinary forces, captured through information disclosure, interbank deposits, concentration and ownership structure, incentivise the Indian banks to adopt prudential risk management by enhancing their risk‐weighted capital ratio. The findings of the study show that information disclosure and interbank deposits do not induce prudential risk behaviour among banks in India. However, with increasing concentration in the banking sector, a higher level of information disclosure effectively induces banks to maintain higher capital ratios, but inter‐bank deposits do not have any significant effect on bank capital. We also observe that government banks maintain lower capital ratios as compared to private banks indicating government banks' higher expectation of government bailout.
Incidence of blast phase in myelofibrosis according to anemia severity
Authors: Mora Barbara , Maffioli Margherita , Rumi Elisa , Guglielmelli Paola , Caramella Marianna , Kuykendall Andrew , Palandri Francesca , Iurlo Alessandra , De Stefano Valerio , Kiladjian Jean‐Jacques , Elli Elena M. , Polverelli Nicola , Gotlib Jason , Albano Francesco , Silver Richard T. , Benevolo Giulia , Ross David M. , Devos Timothy , Borsani Oscar , Barbui Tiziano , Porta Matteo G. Della , Bertù Lorenza , Komrokji Rami , Vannucchi Alessandro M. , Passamonti Francesco 
Published: July 2023

AbstractMyelofibrosis (MF) is a clonal malignancy frequently characterized by anemia and in 10%–20% of cases it can evolve into blast phase (BP). Anemia in MF is associated with reduced survival and ‐in primary MF‐ also with an increased probability of BP. Conventional treatments for anemia have limited effectiveness in MF.Within a dataset of 1752 MF subjects largely unexposed to ruxolitinib (RUX), BP incidence was 2.5% patients per year (p‐y). This rate reached respectively 4.3% and 4.5% p‐y in case of patients with common terminology criteria for adverse events (CTCAE) grade 3/4 and grade 2 anemia, respectively, that represented together 32% of the cohort. Among 273 MF cases treated with RUX, BP incidence was 2.89% p‐y and it reached 4.86% p‐y in subjects who started RUX with CTCAE grade 2 anemia (one third of total). Within patients with red blood cell transfusion‐dependency at 6 months of RUX (21% of the exposed), BP rate was 4.2% p‐y. Our study highlights a relevant incidence of BP in anemic MF patients, with a similar rate whether treated with or without RUX. These findings will help treating physicians to make decisions on the safety profile of innovative anemia treatments.
A low‐spur harmonic‐cancelation digital predistortion based on neural network for frequency‐hopping HF transmitters
Authors: Chen Long , Chen Wenhua , Chen Xiaofan , Liu Youjang , Chu Jiaming , Ghannouchi Fadhel M. , Feng Zhenghe 
Published: July 2023

AbstractHigh frequency (HF) transmitter implemented with the multioctave broadband power amplifier (PA) is always faced with the problem of interfering harmonics because of the nonlinearity of the PA. With the harmonic‐cancelation digital predistortion (HC‐DPD) scheme, the harmonics at lower frequencies can be canceled by the injected components and the harmonics at higher frequencies can be filtered out using a low‐pass filter (LPF). However, the HC‐DPD scheme brings the problem of unwanted spurs while lowering the requirements for sampling rate. In this article, a time‐delay neural network (TDNN) model is used to replace the conventional memory polynomial (MP) model in the forward modeling. Theoretical derivation and simulation results validate the effectiveness of the TDNN model in harmonic cancelation and spur suppression. Further, a frequency‐agile neural network (FANN) model is proposed based on the TDNN model. By adding the carrier frequency to the inputs of the network, the trained model can apply to all the trained carrier frequencies and is more friendly to the frequency‐hopping scenarios. Experiments were carried out on a 2–30 MHz HF transmitter testbench. Measurement results show that the harmonic‐to‐fundamental power ratio, the adjacent channel power ratio (ACPR), and the error vector magnitude (EVM) performances were all improved by more than 20 dB. Compared with the MP model, the unwanted spurs can be suppressed by up to 22 dB. In addition, the number of total model coefficients of the proposed FANN model is only 22% of that of the TDNN model under the frequency‐hopping scenario.
A review of the mechanisms of blood–brain barrier disruption during COVID‐19 infection
Authors: Jamil Al‐Obaidi Mazen M. , Desa Mohd Nasir Mohd 
Published: July 2023

AbstractCoronaviruses are prevalent in mammals and birds, including humans and bats, and they often spread through airborne droplets. In humans, these droplets then interact with angiotensin‐converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2), which are the main receptors for the SARS‐CoV‐2 virus. It can infect several organs, including the brain. The blood–brain barrier (BBB) is designed to maintain the homeostatic neural microenvironment of the brain, which is necessary for healthy neuronal activity, function, and stability. It prevents viruses from entering the brain parenchyma and does not easily allow chemicals to pass into the brain while assisting numerous compounds in exiting the brain. The purpose of this review was to examine how COVID‐19 influences the BBB along with the mechanisms that indicate the BBB's deterioration. In addition, the cellular mechanism through which SARS‐CoV‐2 causes BBB destruction by binding to ACE2 was evaluated and addressed. The mechanisms of the immunological reaction that occurs during COVID‐19 infection that may contribute to the breakdown of the BBB were also reviewed. It was discovered that the integrity of the tight junction (TJs), basement membrane, and adhesion molecules was damaged during COVID‐19 infection, which led to the breakdown of the BBB. Therefore, understanding how the BBB is disrupted by COVID‐19 infection will provide an indication of how the SARS‐CoV‐2 virus is able to reach the central nervous system (CNS). The findings of this research may help in the identification of treatment options for COVID‐19 that can control and manage the infection.
Nano‐enabled stress‐smart agriculture: Can nanotechnology deliver drought and salinity‐smart crops?
Authors: Raza Ali , Charagh Sidra , Salehi Hajar , Abbas Saghir , Saeed Faisal , Poinern Gérrard E. J. , Siddique Kadambot H. M. , Varshney Rajeev K. 
Published: July 2023

AbstractSalinity and drought stress substantially decrease crop yield and superiority, directly threatening the food supply needed to meet the rising food needs of the growing total population. Nanotechnology is a step towards improving agricultural output and stress tolerance by improving the efficacy of inputs in agriculture via targeted delivery, controlled release, and enhanced solubility and adhesion while also reducing significant damage. The direct application of nanoparticles (NPs)/nanomaterials can boost the performance and effectiveness of physio‐biochemical and molecular mechanisms in plants under stress conditions, leading to advanced stress tolerance. Therefore, we presented the effects and plant responses to stress conditions, and also explored the potential of nanomaterials for improving agricultural systems, and discussed the advantages of applying NPs at various developmental stages to alleviate the negative effects of salinity and drought stress. Moreover, we feature the recent innovations in state‐of‐the‐art nanobiotechnology, specifically NP‐mediated genome editing via CRISPR/Cas system, to develop stress‐smart crops. However, further investigations are needed to unravel the role of nanobiotechnology in addressing climate change challenges in modern agricultural systems. We propose that combining nanobiotechnology, genome editing and speed breeding techniques could enable the designing of climate‐smart cultivars (particularly bred or genetically modified plant varieties) to meet the food security needs of the rising world population.
Improving Photoluminescence Emissions and Photostability of Dye/MgAl‐Layered Double Hydroxide Nanohybrids
Authors: Rezvani Zolfaghar , Jafari Foruzin Leila , Nejati Kamellia 
Published: July 2023

AbstractThe purpose of this study was the preparation of layered double hydroxide (LDH) ‐based nanohybrids with improved photoluminescence emission and high photostability. The anion exchange‐based microwave method was applied for the intercalation of mordant orange 1 into MgAl‐LDH. The prepared organic‐inorganic nanohybrid was confirmed by X‐ray diffraction, thermal gravimetric analysis (TGA), inductively coupled plasma spectrometry (ICP), and infrared spectra (FT‐IR). Also, the morphology of the obtained sample was investigated using the field emission‐scanning electron microscopy (FE‐SEM) method. In the MgAl‐LDH interlayer space, a tilted orientation and bilayer arrangement were predicted for the mordant orange 1 anions. Compared with the pure mordant orange 1, the MgAl‐LDH/mordant orange 1‐MA (prepared using the microwave‐based anion exchange method) has improved photoluminescence emission with high Photostability. These findings supply a new approach for designing photoluminescence materials that potentially apply to optical devices with high Photostability.
The Invisibles: Religious and Political Values Among Different Social Classes
Authors: Bréchon Pierre 
Published: July 2023

AbstractPoverty and social exclusion can be defined as an accumulation of impediments: lack of work and income, bad housing, low education, maltreatment, disempowerment, loss of dignity. Types of poverty are indeed diverse, with the poor including both those who have inherited poverty and those who are newly poor in the age of globalisation. The first group is probably less visible than the second, more claiming. The poor present specificities of values. At the religious level, they are rather more believing – particularly in relation to paradise, and they practise their religion more. The discrepancies between social groups are greater when it comes to political matters. The invisibles are more individualistic and less individualised. They are less politicised but nevertheless more dissatisfied with those in power, and they mobilise less strongly in public action (voting and political protest). They do not easily trust others or institutions. They are less attached to democratic values, and they demonstrate greater xenophobia and nationalism. They therefore share many features of populism. These specificities of political values essentially correspond to perennial trends in poor classes. Differences in religious and political values between countries and geographical areas are also very large. But in each part of Europe, we observe value differences between social groups.
Symmetries of κ-Minkowski space-time: a possibility of exotic momentum space geometry?
Authors: Nandi Partha , Chakraborty Anwesha , Pal Sayan Kumar , Chakraborty Biswajit , Scholtz Frederik G. 
Published: July 2023

Abstract
The quest for a quantum gravity phenomenology has inspired a quantum notion of space-time, which motivates us to study the fate of the relativistic symmetries of a particular model of quantum space-time, as well as its intimate connection with the plausible emergent curved “physical momentum space”. We here focus on the problem of Poincare symmetry of κ-Minkowski type non-commutative (quantum) space-time, where the Poincare algebra, on its own, remains undeformed, but in order to preserve the structure of the space-time non-commutative (NC) algebra, the actions of the algebra generators on the operator-valued space-time manifold must be enveloping algebra valued that lives in entire phase space i.e. the cotangent bundle on the space-time manifold (at classical level). Further, we constructed a model for a spin-less relativistic massive particle enjoying the deformed Poincare symmetry, using the first order form of geometric Lagrangian, that satisfies a new deformed dispersion relation and explored a feasible regime of a future Quantum Gravity theory in which the momentum space becomes curved. In this scenario there is only a mass scale (Planck mass mp), but no length scale. Finally, we relate the deformed mass shell to the geodesic distance in this curved momentum space, where the mass of the particle gets renormalized as a result of noncommutativity. We show, that under some circumstances, the Planck mass provides an upper bound for the observed renormalized mass.
FIMP dark matter from flavon portals
Authors: Babu K. S. , Chakdar Shreyashi , Das Nandini , Ghosh Dilip Kumar , Ghosh Purusottam 
Published: July 2023

Abstract
We investigate the phenomenology of a non-thermal dark matter (DM) candidate in the context of flavor models that explain the hierarchy in the masses and mixings of quarks and leptons via the Froggatt-Nielsen (FN) mechanism. A flavor-dependent U(1)FN symmetry explains the fermion mass and mixing hierarchy, and also provides a mechanism for suppressed interactions of the DM, assumed to be a Majorana fermion, with the Standard Model (SM) particles, resulting in its FIMP (feebly interacting massive particle) character. Such feeble interactions are mediated by a flavon field through higher dimensional operators governed by the U(1)FN charges. We point out a natural stabilizing mechanism for the DM within this framework with the choice of half-integer U(1)FN charge n for the DM fermion, along with integer charges for the SM fermions and the flavon field. In this flavon portal scenario, the DM is non-thermally produced from the decay of the flavon in the early universe which becomes a relic through the freeze-in mechanism. We explore the allowed parameter space for this DM candidate from relic abundance by solving the relevant Boltzmann equations. We find that reproducing the correct relic density requires the DM mass to be in the range (100 − 300) keV for n = 7.5 and (3 − 10) MeV for n = 8.5 where n is the U(1)FN charge of the DM fermion.