bluuebunny/crossref_metadata_2025 huggingface dataset:
Experimental assessment of counterfog bioaerosol fast sampler for virus detection and decontamination
Authors: Pérez-Díaz José Luis , del Álamo Toraño Cristina , Alcamí Antonio , Vázquez-Calvo Ángela , Rodríguez-Caravaca Gil , Mendez-Vigo Pablo , Sánchez García-Casarrubios Juan , Sanchiz África , Martín Rocío , Hernáez Bruno , Moraga Ana , García-Castey Mayte , González-Serrano Rafael , Fernández-Moyano María del Cermen , Pérez- del Álamo Francisco Javier , Saavedra-González Julio César , Agudiez-Pérez Álvaro , Del-Álamo-Lobo María Pilar
Published: September 2024

The respiratory system is equipped with several defence mechanisms to protect the body from microorganisms and airborne pathogens. There are situations where the respiratory system can be overwhelmed or compromised and infection happens, especially in individuals with weakened immune systems. Airborne pathogens are a serious risk for human and animal health, as exemplified by the challenges faced during the COVID-19 pandemic. The list includes viruses of varying severity such as Influenza virus, SARS-CoV-2, measles virus, Varicella-Zoster Virus, or Respiratory syncytial virus among others. Smaller particles can remain suspended in the air for longer periods and may reach the lower respiratory tract, including the alveoli in the lungs. The real-time detection of these pathogens in the air presents a significant challenge. The aerosols, especially those carrying viruses, are so small that they often elude conventional air samplers, making it difficult both to detect their presence and to remove them effectively from the air. This work introduces a recent technique designed for rapid aerosol sampling, with a particular emphasis on virus sampling. The system underwent calibration using artificial ɸ29 virus aerosols and was subsequently tested with naturally emitted aerosols of SARS-CoV-2. A series of tests were conducted in diverse settings, including hospitals, farms, offices, and railway cars. The equipment is also capable of swiftly removing bioaerosols from the air, thereby facilitating effective decontamination. The relevance of this technology lies in its capability for swift detection and elimination of viruses and other kinds of aerosols from air, facilitating prompt decision-making during high-risk events.
A moth-flame algorithm based on social learning theory for influence maximization
Authors: Zhang Qiwen , Zhang Yitong
Published: September 2024

Swarm intelligent optimization algorithm plays a key role in solving the influence maximization problem. Aiming at the problems of insufficient diversity and overlapping influence when selecting initial nodes in previous influence maximization algorithms, the local influence measure of nodes is constructed considering the network topology, and the population initialization method based on local influence is proposed. Aiming at the traditional moth-flame algorithm which is difficult to deal with the balance between global exploration and local exploitation, resulting in the decline of population diversity and easy to fall into the local optimal solution, combining with the social learning theory, re-planning the population state, defining multiple learning strategies for individuals in different states, and proposing a new method for the moth-flame algorithm based on the social learning theory to solve the problem of maximizing the influence of the social network. Experiments are conducted on six real social networks under the independent cascade model (IC), and the results show that the proposed algorithm can effectively identify the influential node sets.
Information consistency and inhibition impact on diffusion in networks
Authors: Liu Guocui , Nian Fuzhong , Liu Yang
Published: September 2024

This paper introduces the Principal-Agent mechanism to study the diffusion of information in complex networks. Hot list information is defined as principal information, information that is homogeneous with hot list information is defined as homogeneous agent information, and information that is heterogeneous with hot list information is defined as heterogeneous agent information. The theory of diffusion dynamics is used to study the phenomenon that homogeneous information promotes each other and heterogeneous information inhibits each other in the process of competitive diffusion of network information. Based on the traditional SIR model, this paper introduces the Principal-Agent mechanism, establishes the PA_SIR diffusion model and studies the mutual influence of information in the process of competitive diffusion of multiple information. The research shows that in the process of competitive diffusion of multiple information, principal information has a positive incentive effect on homogeneous agent information through people’s interest orientation, herd mentality and topic public opinion and has a negative incentive effect on heterogeneous agent information. Therefore, if you want your published information to attract more attention, the best release time is when homogeneous information is on the hot search list, which will help to attract people’s attention more quickly.
Dielectric properties of dry fruits in powder form at microwave frequencies
Authors: Vijay Ravika , Sharma Krishna S.
Published: September 2024

To facilitate future pasteurization experiments utilizing microwave energy, the dielectric properties of five dried fruits — almond (Prunus dulcis), cashew nut (Anacardium occidentale), pistachio (Pistacia vera), peanut (Arachis hypogea L.) and walnut (Juglans regia) were investigated at room temperature (28∘C). Samples were taken in powder form to investigate the effect of increased surface-to-volume ratio on their dielectric properties, as applicable in the case of nanomaterials. The measurements were conducted at four different frequencies (3.30, 7.50, 9.30[Formula: see text]and 14.70[Formula: see text]GHz) in the microwave spectrum by using the two-point method and a MATLAB program was used for solving the transcendental equation to obtain values of dielectric constant and loss factor. The findings revealed a decreasing trend in the values of dielectric constant of the five dried fruits as the frequency increased. However, no consistent trend was observed for the dielectric loss factor of the fruits with increasing frequency. Further, the penetration depth of electromagnetic waves in all the five dry fruit samples was observed to decrease as the frequency increased. On comparing results for dielectric parameters of dry fruits in powder form with those of whole fruit kernels, no definite trends are observed for [Formula: see text] and [Formula: see text], but the penetration depth is found to decrease when the sample is taken in powder form.
Existence, Uniqueness and Error Analysis of Variable-Order Fractional Lorenz System with Various Type of Delays
Authors: Naveen S. , Parthiban V.
Published: September 2024

This paper examines the variable-order fractional Lorenz system with distinct types of delays. The application of the Arzela–Ascoli theorem is made to prove the existence of solutions for the given problem, while the Banach fixed point theorem is employed to derive the uniqueness results. The utilization of the Adams–Bashforth–Moulton technique facilitates the exploration and resolution of the approximation solution, complemented by a thorough error analysis of particular approaches. The computational simulations showing chaotic behaviors in various delayed systems with different variable orders demonstrate the effectiveness of the approach.
Complex Patterns in a Reaction–Diffusion System with Fear and Anti-Predator Responses
Authors: Mandal Gourav , Guin Lakshmi Narayan , Chakravarty Santabrata
Published: September 2024

The intricate relationship between temporal and spatiotemporal dynamics in a Crowley–Martin predator–prey model, enriched with fear effect and anti-predator behavior, is investigated in this study. A careful mathematical analysis is conducted to explore the feasible equilibria of the model system, followed by an examination of their stability, instability, and all possible bifurcation scenarios. Asymptotic stability, bistability, and various codimension-1 and codimension-2 bifurcations, including transcritical, saddle–node, Hopf, cusp, and Bogdanov–Takens bifurcations, are demonstrated by the model. The analytical findings and the model’s applications are validated through numerical simulations, employing a biparameter bifurcation diagram for quantitative analysis. The study also observes bubbling phenomena and a scenario leading to the density-dependent hydra effect. The diffusion effect is investigated with special attention to the system’s nonlinearity and chosen parameter values. Numerical simulations reveal the emergence of spatiotemporal patterns both within and beyond the Turing space. The evolution of diffusion-driven pattern generation, including cold spots, stripes, labyrinthines, mixtures of stripes and cold spots, and complex non-Turing patterns, is demonstrated on the plane. These spatial patterns are shown to be influenced biologically by both the fear effect and anti-predator behavior.
Study on a growth-expansion model with chemotaxis in nutrient-replete environments
Authors: Zhang Qingshan
Published: September 2024

We consider the no-flux initial-boundary value problem for the growth-expansion model with chemotaxis in nutrient-replete environments in smoothly bounded domains [Formula: see text]. It is shown that if [Formula: see text] or if [Formula: see text] under some structural assumptions on parameter functions therein, for any suitably regular initial data the problem admits a unique global bounded classical solution. For any dimensions [Formula: see text], we also prove that the problem has a unique global classical solution which is bounded under a small assumption on the initial data. Moreover, we obtain that these solutions stabilize to a uniquely determined spatially uniform equilibrium. We also provide exponential rates of convergence of solutions in a special case.
The Automation of Science? Possibilities and Boundaries of AI Applications for Conducting Systematic Literature Reviews
Authors: Tomczyk Przemysław , Brüggemann Philipp , Doligalski Tymoteusz
Published: September 2024

Science automation, driven by advanced technologies, such as artificial intelligence (AI), is reshaping research in a variety of disciplines. The exponential growth of publications increases the need for automation in systematic literature reviews (SLRs). In this study, we investigated how AI applications support SLRs at different stages. After evaluating twenty-two AI applications, we identified the most useful based on their functionalities in the SLR process. This study provides important insights into the dynamic interplay between science automation, AI, and a systematic literature review. The main contribution is the identification and discussion of the relevance of the analyzed applications at different stages of the systematic literature review. We also discuss the potential for the automation and augmentation of research activities to address various scientific problems.
EFFECT OF Y2O3 ON MICROSTRUCTURE AND CRACKING SUSCEPTIBILITY OF Ni45 COATING BY LASER CLADDING WITH SHIELDING AND CARRIER GAS
Authors: LI YUNFENG , QIU YAJIE , TANG SHUFENG , JIANG GUANGJUN
Published: September 2024

The Ni45 alloy composite coating was generated on 42 CrMoA alloy steel through laser cladding utilizing a 5[Formula: see text]kW CO2 laser, four-axis CNC machines, and the coaxial powder feeding system in this study. The effect of Y2O3 on the microstructure and cracking susceptibility of the composite coatings was investigated under different shielding gas and carrier gas flow rate conditions. The macroscopic morphology and microstructure were analyzed by optical microscopy, scanning electron microscopy, XRD, and microhardness tester. The results showed that the increase of shielding gas flow rate could reduce the cracking susceptibility of the composite coatings, and the optimum additional amount of Y2O3 was 0.4[Formula: see text]wt.%. In addition, the variation of the carrier gas flow rate has an effect on the cracking susceptibility: An increase followed by a decrease in the flow rate leads to a decrease in the cracking susceptibility. In order to obtain the lowest cracking sensitivity and the best microstructure, the optimum conditions were a shielding gas flow rate of 15[Formula: see text]l /min and a carrier gas flow rate of 550[Formula: see text]l/h.
Data-Driven Relationship for Reduction Factor of Ballasted Railway Bridge Deflections Due to Load Distribution Within Track
Authors: Allahvirdizadeh Reza , Moliner Emma , Museros Pedro
Published: September 2024

Increasing the operating speed of the trains on modern networks necessitates performing dynamic analyses to assess the performance of bridges under passage of trains. The detailed investigation of their responses requires constructing complex computational models capable to take the train–track–bridge interaction effects into account. Such models have successfully been developed; however, employing those elaborated models for practical engineering applications, or to perform studies that require a large number of analyses may become infeasible. Among such situations are conducting probabilistic investigations, screening of entire networks, or sensitivity analyses. These concerns have been addressed by employing simplified models mostly relying on moving load modeling strategy which disregards the train–track–bridge interaction effects. Those neglected contributions can be compensated by implementing additional correction factors. The distribution of loads within track is one of those disregarded effects where a reduction factor is recommended by design guidelines to take its contribution into account. It has been shown that the existing relationship for these reduction factors delivers an acceptable performance for vertical accelerations, while showing a less favorable performance for displacements. Then, a data-driven strategy is adopted in this study to propose easy-to-apply relationships for reduction factors of deflections, due to load distribution within the track. In this context, three different distributive lengths of triangular load footprints have been considered, namely 2.0, 2.5 and 3.0[Formula: see text]m. The procedure employed has trained and tested for more than 1[Formula: see text]200 train configurations, comprising conventional, articulated and regular vehicles, and including several tens of thousand data points for each distributive length. The performance observed in the new models revealed a considerable improvement with respect to the existing relationship.
Holographic bounce cosmological models induced by viscous dark fluid from a generalized non-singular entropy function
Authors: Elizalde E. , Yurov A. V. , Timoshkin A. V.
Published: September 2024

Bounce cosmological models containing a dark viscous fluid in a spatially flat Friedmann–Robertson–Walker (FRW) universe are considered. The universe’s evolution is described in terms of generalized equation of state (EoS) parameters, in the presence of the bulk viscosity. Entropic cosmology plays a key role in the discussion, and the matter bounce behavior is described based on a nonsingular, generalized entropy function, recently proposed by S. D. Odintsov and T. Paul. Three different forms of the scale factor are investigated: an exponential, a power-law and a double-exponential function, respectively. Appropriate bounce cosmological models are formulated, via the relevant parameters of the modified EoS, and analytical expressions for the corresponding infrared cut-off are obtained, via the particle horizon. Results are displayed in holographic form, making use of generalized holographic cut-offs first introduced by S. Nojiri and S. D. Odintsov. In addition, the viability of the corresponding bounce cosmological models is investigated, taking into account the actual thermodynamic properties of our universe, by means of a no-singular, generalized entropy function. In the asymptotic case, an expression for the generalized entropy is obtained, which remarkably has the additivity property.
A Computational Biophysical Model for Use in Ophthalmology
Authors: Goldman Saul
Published: September 2024

Despite their use in ophthalmology for more than a century, there are no fundamental biophysical models that account for the dissolution rate of intra-ocular gas bubbles in vivo, as a function of their initial size and composition. Any physical model that reliably predicts the evolution of these bubbles would be extremely useful for planning treatment, by predicting their size over time, and their periods of clinical usefulness. A fundamental, computational, biophysical model is developed here with these purposes in mind. The model is fundamental in the sense that the underlying rate equations are derived using linear response theory, wherein the driving force is a solute chemical potential difference. It is computational because the rate equations for the bubble volume and composition are fully coupled and must be integrated numerically and simultaneously. It was rendered clinically relevant by fitting its two adjustable parameters (two rate constants) to recently acquired live human eye data on intra-ocular air bubble dissolution rates. The model consists of an explicitly four-component, dome-shaped gas bubble, comprised of N2, O2, H2O and CO2, which exchanges N2 and O2 with circulating venous blood in the capillaries of the eye. The calibrated model provided an excellent fit to the available data, and interpolated nicely through three points not used for the calibration. It was used to show that by selecting different N2/O2 ratios in the initially injected gas, one can generate intra-ocular gas bubbles with significantly different predicted periods of clinical usefulness. This potentially useful predictive capability does not exist in current clinical practice.
Constructive Approximate Nash Equilibrium for In-Orbit Target Enclosing with Collision Avoidance and Full-state Constraint via Nonzero-Sum Differential Games
Authors: Wei Bosong , Yue Xiaokui , Hao Zhiwei , Liu Zongcheng
Published: September 2024

The problem of in-orbit cooperative target enclosing involving N thrust-limited satellites under collision avoidance and maneuver amplitude constraints is studied. In order to find global optimal trajectories for target enclosing task with all constraints above, by integrating the collision threat and maneuver boundaries into a novel nonlinear cost functional, the studied target enclosing problem is described as a nonlinear nonzero-sum differential game. Further, to avoid iterative calculations caused by traditional nonlinear-game-solving methods, an approximate solution which can be constructed directly is designed. Then the approximate Nash equilibrium strategies can be educed by the constructive approximate solution for the proposed nonzero-sum game. Analysis shows that the proposed control strategies can asymptotically approach the exact one and can ensure a zero-error tracking of the enclosing configuration. Simulation results illustrate lower time costs and better enclosing accuracy while the collision avoidance and maneuver amplitude constraints are satisfied simultaneously.
A Self-Efficacy Theory-Based Study on the Teachers’ Readiness to Teach Artificial Intelligence in Public Schools in Sri Lanka
Authors: Rajapakse Chathura , Ariyarathna Wathsala , Selvakan Shanmugalingam
Published: September 2024

Objectives
. This article explores teacher readiness for introducing artificial intelligence (AI) into Sri Lankan schools, drawing on self-efficacy theory. Similar to some other countries, Sri Lanka plans to integrate AI into the school curriculum soon. However, a key question remains: Are teachers prepared to teach this advanced technical subject to schoolchildren? Assessing teacher readiness is crucial, as it is intricately linked to the overall success of this initiative and will inform the development of appropriate policies.

Participants
. This study surveyed over 1,300 Sri Lankan public school teachers who teach Information and Communication Technology (ICT) using the snowball sampling approach. The respondents represent approximately 20% of the total ICT teacher population in Sri Lanka. Their readiness to teach AI was assessed using a general teacher self-efficacy scale specifically developed based on the well-established Self-Efficacy Theory. While key demographic factors like gender, education level and educational background were also collected, their impact analysis is not included in this article.

Study Method
. The study was conducted based on the premise that teachers’ readiness to teach AI hinges on their self-efficacy towards teaching AI in the classroom. This premise was substantiated through a review of existing research, and a conceptual model of teachers’ self-efficacy for AI instruction was developed. To assess this model, a nationwide survey targeting school ICT teachers was conducted. The questionnaire used in the survey was based on existing research on evaluating teacher self-efficacy. Data analysis, focusing on testing and validating the conceptual model, primarily employed the PLS-SEM approach.

Findings
. This study identified several key findings: (1) Teachers generally reported low self-efficacy regarding their ability to teach AI; (2) Teachers’ self-efficacy was most influenced by their emotional and physiological states, as well as their imaginary experiences related to teaching AI; (3) Surprisingly, mastery experiences had a lesser impact on their self-efficacy for teaching AI; and (4) Neither vicarious experiences (observing others teach AI) nor verbal persuasion had a significant impact on teachers’ self-efficacy. Additionally, the study revealed that the teachers’ own level of expertise in AI, along with their social capital, is insufficient to deliver a standard AI curriculum.

Conclusions
. The analysis of the results found that Sri Lankan teachers currently lack the readiness to teach AI in schools effectively. Potential lapses in certain sources of self-efficacy were also identified. It further revealed the need for a more systemic approach to teacher professional development. Therefore, the study recommends further research exploring the potential of incorporating a socio-technical systems perspective into the government’s teacher training initiatives.
SPATA: Effective OS Bug Detection with Summary-Based, Alias-Aware, and Path-Sensitive Typestate Analysis
Authors: Li Tuo , Bai Jia-Ju , Sui Yulei , Hu Shi-Min
Published: September 2024

The operating system (OS) is the cornerstone for computer systems. It manages hardware and provides fundamental service for user-level applications. Thus, detecting bugs in OSes is important to improve the reliability of computer systems. Static typestate analysis is a common technique for detecting various types of bugs, but it is often inaccurate or unscalable for large-size OS code, due to imprecision of identifying alias relationships as well as high costs of typestate tracking, path-feasibility validation, and inter-procedural analysis.

In this article,

1

we present SPATA, a novel summary-based, alias-aware, and path-sensitive typestate analysis framework to detect OS bugs. To identify precise alias relationships in the OS code, SPATA performs a path-based alias analysis based on control-flow paths and access paths. With these alias relationships, SPATA reduces the costs of typestate tracking and path-feasibility validation, to accelerate path-sensitive typestate analysis for accurate bug detection. Moreover, SPATA uses an alias-summary-based analysis to accelerate inter-procedural bug detection, without time-consuming alias analysis across functions. We have evaluated SPATA on the Linux kernel and three popular IoT OSes, and it finds 651 real bugs with a false-positive rate of 18%. Besides, our alias-summary-based analysis achieves a 6.7x speedup in bug detection compared to non-summary-based analysis.
Timer-based pre-fetching for increasing hazard rates
Authors: Ferragut Andres , Carrasco Matias , Paganini Fernando
Published: September 2024

Caching plays a crucial role in today's networks: keeping popular content close to users reduces latency. Timer-based caching policies (TTL) have long been used to deal with bursts of requests, and their properties are well understood. However, in some scenarios the traffic is more regular. In this work, we define a dual of the TTL policy, dubbed Timerbased Pre-fetching, particularly well suited for these scenarios. We also show how the optimal timers can be computed for a large class of request processes.
Tail Optimality of the Nudge-M Scheduling Algorithm
Authors: Charlet Nils , Van Houdt Benny
Published: September 2024

Recently it was shown that the response time of First-Come- First-Served (FCFS) scheduling can be stochastically and asymptotically improved upon by the Nudge scheduling algorithm in case of light-tailed job size distributions. Such improvements are feasible even when the jobs are partitioned into two types and the scheduler only has information about the type of incoming jobs (but not their size).

In this paper we introduce Nudge-M scheduling, where basically any incoming type-1 job is allowed to pass any type-2 job that is still waiting in the queue given that it arrived as one of the last M jobs. We prove that Nudge- M has an asymptotically optimal response time within a large family of Nudge scheduling algorithms when job sizes are light-tailed. Simple explicit results for the the prefactor of Nudge-M are derived as well as explicit results for the optimal parameter M. An expression for the prefactor that only depends on the type-1 and type-2 mean job sizes and the fraction of type-1 jobs is presented in the heavy traffic setting.
Teaching performance analysis: essential skills andlearning outcomes
Authors: Fiems Dieter
Published: September 2024

In the age of machine learning, traditional performance analysis courses face challenges such as declining student interest and increasing competition from courses within the respective study programmes. At the same time, courses must accommodate increasingly heterogeneous groups of students, both in terms of background, interests and mathematical ability. In this paper, we present a personal perspective on teaching performance evaluation techniques. We argue that stochastic modelling should be the focus in a performance analysis course and that stochastic analysis techniques are a means to an end to solve performance problems, not the main focus.
Intracoronary ECG ST-segment shift remission time during reactive myocardial hyperemia: a new method to assess hemodynamic coronary stenosis severity
Authors: Bigler Marius Reto , Kieninger-Gräfitsch Andrea , Rohla Miklos , Corpateaux Noé , Waldmann Frédéric , Wildhaber Reto , Häner Jonas , Seiler Christian
Published: September 2024

Invasive hemodynamic measurements are recommended by the current cardiology guidelines to guide percutaneous coronary interventions in the setting of chronic coronary syndrome. However, those pressure-derived indices demonstrate several theoretical and practical limitations. Thus, this study demonstrates the accuracy of a novel, pathophysiology-driven approach using intracoronary ECG for the identification of hemodynamically relevant coronary lesions by quantitatively assessing myocardial ischemia remission.
Single‐Center Success of Concomitant Cryothermal Cox‐Maze IV Procedure
Authors: Mayr Benedikt , Kokott Anna Maria , Georgescu Teodora , Voss Bernhard , Krane Markus , Vitanova Keti
Published: September 2024

Background. Despite the guideline recommendation, implementation of the Cox‐maze (CM) IV procedure has been variable and current data are limited. Methods. We reviewed patients with concomitant CM IV procedure (05/2019−05/2020). The primary endpoints of the study were the success rate of surgical ablation and continuity of sinus rhythm (SR) 1 year after surgery. Secondary endpoints included permanent pacemaker (PPM) implantation, postoperative mortality, and identification of predictors for postoperative SR. Results. The concomitant CM IV procedure was performed in 92 patients. Indications were persistent atrial fibrillation (AF) in 40 patients (43.5%), paroxysmal AF in 36 (39.1%), and long‐standing persistent AF in 16 (17.4%). At hospital discharge, SR was achieved in 49 patients (63.6%) and PPM implantation was necessary in 12 patients (13%). At 1 year after surgical ablation, SR was seen in 31 patients (59.6%) and PPM implantation was required in six further patients (6.5%). Patients with long‐standing persistent AF were significantly less likely to achieve SR (odds ratio (OR): 0.18, p = 0.003), and postoperative mortality was significantly increased in this subgroup (hazard ratio (HR): 5.4, p = 0.02). In patients with enlarged left atrial (LA) diameter, the probability of achieving SR was significantly decreased (OR: 0.48, p = 0.045). Need for postoperative dialysis (HR: 12.9, p = 0.02) and prolonged stay in the intensive care unit (HR: 2.2, p = 0.01) were independently associated with increased mortality after CM IV. Conclusions. The cryothermal CM IV procedure has an overall 1‐year success rate of 60% with increased rates of PPM implantation. Patients with long‐standing persistent AF and increased LA diameter were significantly less likely to achieve SR.
Biot Theory Yields a Specific Storage Coefficient With Natural Deformation of Rock
Authors: Li Guangquan , Yang Simeng , Wang Li
Published: September 2024

The traditional specific storage coefficient (Ss) was defined under two assumptions. One is that aquifer rock deforms only in the vertical direction, and the other is that the average rock stress remains unchanged. Consequently, Ss is irrelevant to the shear modulus of rock (G). In this paper, the Biot theory is used to derive a new specific storage coefficient () with the natural deformation of rock. appears to be relevant to G. Compressed glass beads and Berea sandstone are used for illustration. At frequencies lower than 10 kHz, the equation of groundwater flow with yields the same phase velocity and quality factor as the Biot theory, and therefore, it is capable of accurately predicting fluid pressure diffusion in the low‐frequency regime. The results also show that Ss is 16%–17% higher than . In conclusion, the latter one is superior to the former in its consistency with the Biot theory and unconstraint by the aforementioned two assumptions.
Advancements in Heart Disease Diagnosis: Harnessing Predictive Modeling Techniques for Cardiovascular Health Management
Authors: Bakshi Kanishk , Kumar Raj , Setia Harshit , Jinny S. Vinila
Published: September 2024

This research paper investigates predictive modeling techniques for heart disease diagnosis utilizing comprehensive cardiovascular health data. Leveraging a dataset sourced from the University of California, Irvine Machine Learning Repository, the research focuses on 1,236 patients’ attributes, including age, sex, blood pressure, cholesterol levels, and exercise habits, among others. The analysis employs a combination of data preprocessing, exploratory data analysis, and predictive modeling using both traditional machine learning (ML) and deep learning (DL) approaches. The predictive models aim to classify patients into different degrees of coronary artery disease based on their health attributes. Key methodologies include feature normalization, dropout regularization, and weight regularization to enhance model performance and prevent overfitting. The research compares the effectiveness of categorical and binary classification models, evaluating their accuracy, precision, recall, and F1‐score metrics. Results indicate promising performance, with the binary classification model achieving an accuracy of 83.61% on the testing dataset. This research contributes to the ongoing efforts in leveraging advanced computational techniques to aid in the early detection and diagnosis of heart disease, ultimately facilitating better patient care and management strategies.
Supplementary Data from First-in-Human Study of PF-06647020 (Cofetuzumab Pelidotin), an Antibody–Drug Conjugate Targeting Protein Tyrosine Kinase 7, in Advanced Solid Tumors
Authors: Maitland Michael L. , Sachdev Jasgit C. , Sharma Manish R. , Moreno Victor , Boni Valentina , Kummar Shivaani , Stringer-Reasor Erica , Lakhani Nehal , Moreau Allison R. , Xuan Dawei , Li Ray , Powell Eric L. , Jackson-Fisher Amy , Bowers Michelle , Alekar Shilpa , Xin Xiaohua , Tolcher Anthony W. , Calvo Emiliano
Published: September 2024

Figure S1, Figure S2, Table S1, Table S2, Table S3, Table S4
Supplementary Table 6 from Phase I Study of Simlukafusp Alfa (FAP-IL2v) with or without Atezolizumab in Japanese Patients with Advanced Solid Tumors
Authors: Koyama Takafumi , Yonemori Kan , Shimizu Toshio , Sato Jun , Kondo Shunsuke , Sudo Kazuki , Yoshida Tatsuya , Katsuya Yuki , Imaizumi Tatsuki , Enomoto Masashi , Seki Ryoko , Yamamoto Noboru
Published: September 2024

Table S6 shows the biomarker expression status at baseline.
Novel Insights Malalignment or Retronychia: Which Comes First?
Authors: Lencastre André , Richert Bertrand
Published: September 2024

Introduction: Chronic retronychia cases oftentimes look similar to congenital great toenail malalignment. It is quite possible that, on the toenails, both are related as both clinically portray changes in nail growth in a setting of ongoing microtrauma. Case Presentation: A 2-year-old girl presented with a left great toenail change compatible with chronic retronychia. The likely culprit was a lateral deviation of the distal phalanx. Only conservative measures were recommended but an onset of retronychia-related complications was already appreciable. Conclusion: This case illustrates the relationship between retronychia and what could be veritably called acquired great toenail malalignment.
The Effect of Urban Gardening Activities on Physical Activity and Sleep Quality in Middle-Aged Women
Authors: Jung Young-Bin , Yun Hyung-Kwon , Son In-Chang , Choi Se-Na , Song Kwan Jeong
Published: September 2024

Background and objective: Sleep disorders in middle-aged women are said to be related to stress and physical and psychological symptoms of menopause (Chung and Tang, 2006). Therefore, it is necessary to prepare appropriate intervention measures to promote health in middle-aged women. This study empirically examined the effects of urban gardening activities on the health promotion of middle-aged women and sought the development and applicability of urban gardening programs.Methods: Among middle-aged women in their 40s-50s who had no prior experience with urban gardening, 20 women were in the experimental group participating in the urban gardening program for 12 weeks, and 20 women were in the control group not participating in the program.Results: As a result of comparing the physical activity(IPAQ) between the experimental group and the control group according to participation in urban gardening, the experimental group showed an increase from 2663.50 MET-minute/week before participation in the program to 3675.45 MET-minute/week after participation, while the control group showed a decrease from 3297.90 MET-minute/week to 2830.98 MET-minute/week, but there was no statistically significant difference. As a result of analyzing the change in the stress index(PSS), the experimental group showed a decrease from 15.3 before participation in the program to 12.05 after participation, whereas the control group showed an increase from 13 to 14.5, but this was not statistically significant. For sleep quality (PSQI), the experimental group showed an increase from 6.25 before participation in the program to 5.15 after participation, whereas the control group showed an increase from 6.45 to 6.55, but there was not statistically significant difference.Conclusion: The results of this study empirically confirmed that urban gardening activities can contribute to improving the physical activity and sleep quality of middle-aged women. In the future, these findings will help develop and apply health care programs for middle-aged women using urban gardening activities.
Identification of Medicinal Cannabis landraces found in Lusikisiki, Eastern Cape Province, South Africa
Authors: Dumani Azile , Silwana TT. , Mpambani B. , Oyedeji AO. , Egbichi I. , Seepe A.H
Published: September 2024

Background and objective: Identification, best preservation protocol and understanding of landraces is crucial in addressing the current and future agricultural challenges related to medicinal cannabis. Its therapeutic potent and diverse genetic composition amongst others has also geared the need for classification and identifying landraces with desired medicinal properties. This study was conducted to identify the Cannabis landraces found in Lusikisiki, Ingquza Hill, OR Tambo District Municipality, Eastern Cape, South Africa.Methods: Cannabis landraces were collected in three villages where these naturally grow, within the valley forest agroecosystem in Lusikisiki. Prior to specimen collection, each targeted Cannabis were given a unique identifying number to distinguish it amongst the villages and then the plants were tagged for easy identification. Three specimens each were collected from villages 1 and 3, and two specimens were collected from village 2, summing up to a total of eight specimens from the three villages. The sample collection was performed using secateurs and this process was carefully done so that a complete specimen which includes the stem, leaves, and flowers are collected, as these parts are key diagnostic features of the plant. After collection, the samples were placed in a presser for drying for a period of seven days. After the drying process, the specimens were mounted onto a standard 42 cm × 29 cm herbarium sheet and deposited for identification and authentication at Selmar Schonland herbarium, Makhanda, Eastern Cape.Results: Taxonomic analysis indicated that all the eight deposited voucher specimens belong to genus Cannabis and are of sativa specific epithet (binomially known as Cannabis sativa).Conclusion: Therefore, the medicinal Cannabis landraces found in the three villages in Lusikisiki are identified as Cannabis sativa.
Long-day Requirement for Floral Induction in Lythrum salicaria ‘Dwarf Pink’
Authors: Chung Seungeun , Park Ji woo , Im Nam Hyun , Lee Hyo Beom
Published: September 2024

Background and objective: Lythrum salicaria 'Dwarf Pink' is a dwarf-type cultivar of purple loosestrife with a potential ornamental value as a garden plant. This study was conducted to determine a photoperiodic requirement for floral induction and the effects of plant size on flowering characteristics in L. salicaria 'Dwarf Pink'.Methods: In experiment 1, seedlings with an average of 17.7 leaves were grown under five different photoperiods: 9/15, 12/12, 14/10, 16/8, and 24/0 h (day/night hours) for 12 weeks. In experiment 2, the same daylengths were delivered to two groups with different leaf counts of 8.5 (stage 1) and 21.1 (stage 2).Results: In experiment 1, after four weeks of photoperiod treatments, floral buds started to develop under 16/8 and 24/0 h of long-day conditions, and these plants showed 100% flowering. There were no significant differences in the days to visible bud between the plants under 16/8 and 24/0 h. Plants under 9/15 and 12/12 h did not flower. Although floral induction was observed under 14/10 h, the flowering percentage was 17% at the end of the experiment. In experiment 2, plant size did not induce significant differences in the days to flowering and the number of nodes. Under the same long-day condition, when the plant size was large, the number of inflorescences and branches was less than the small plants. However, in both experiments, plant height and the number of branches significantly increased with increasing photoperiod.Conclusion: These results indicated that L. salicaria 'Dwarf Pink' could be categorized as an obligate long-day plant, and under the long-day conditions, the plant size did not affect the days to flowering. However, when the plant size was significantly large under long-day conditions, the number of inflorescences and the number of branches decreased, affecting the quality of flowering.
Some Implications on Pandemic Green Place Planning and Management: Considering the Patients with Depression
Authors: Lee Jae-hyuck , Lee Jeongseok
Published: September 2024

Background and objective: The importance of using green spaces to treat depression caused by reduced face-to-face contact owing to the COVID-19 pandemic has been emphasized. However, while studies have shown the importance of using green spaces during the pandemic, research is lacking on their use to treat and manage depression caused by the pandemic.Methods: This study included in-depth interviews with patients with depression and the general public regarding their use of green spaces during the pandemic, which were analyzed through text mining to suggest alternatives to address the increasing number of patients with depression during the pandemic.Results: The analysis revealed that the reasons for visiting green spaces during the pandemic were activity (exercise and socialization) and nature observation (experiencing ecological scenery); patients with depression were more interested in the activity component.Conclusion: This highlights the necessity of supplementing facilities for exercise and socialization near residential areas to treat depression. Planting of landscape crops to provide landscape resources for the general public is recommended, along with policies to prevent natural damage caused by the increased number of visitors to ecological areas.
Effects of Urban Forest Therapy on Depression, Anxiety, and Sleep Quality in People Experiencing Cancer
Authors: Jeon Youngsin , Kim Ye-Seul , Kim Ga Yeon , Yeon Poung-Sik
Published: September 2024

Background and objective: The cancer survival rate in Korea exceeds 70%, but approximately two million people experiencing cancer face difficulties returning to daily life owing to a lack of appropriate psychological support, leading to depression, anxiety, and fear of recurrence. Despite the achievements of forest therapy, there is a dearth of research, particularly regarding its effects on people experiencing cancer. Therefore, this study examined the psychological effects of forest therapy using highly accessible urban forests after cancer treatment.Methods: The study was conducted between April 11 and June 9, 2023, with 28 participants who had completed cancer treatment and could engage in outdoor activities without difficulty. They were divided into two groups: experimental and control. The experimental group received forest therapeutic program interventions in an urban forest once a week for 8 weeks. To measure the difference in the intervention effects between the two groups, pre-, mid-, and post-assessments were conducted using the Korean version of the Center for Epidemiological Studies-Depression Scale, the Beck Anxiety Inventory, and the Korean version of the Pittsburgh Sleep Quality Index.Results: People experiencing cancer who participated in the urban forest therapeutic program had significantly reduced depression and anxiety than those in the no-treatment group. The experimental group's sleep quality also improved after participating in the program.Conclusion: This study demonstrated that urban forest therapy can alleviate psychological difficulties in people experiencing cancer. These results suggest the need for further research into urban forest therapy as an intervention to improve the quality of life of people experiencing cancer.
Effect of Wood Scent Inhalation on Brain Activity: Focusing on A Multi-Channel Functional Near-Infrared Spectroscopy (fNIRS)
Authors: Kim Choyun , Song Chorong
Published: September 2024

Background and objective: While numerous studies have demonstrated the positive effects of the scent of forests on humans, there has been a lack of research that investigates its effects on brain activity. This study was conducted to investigate the impact of inhaling fir essential oil on brain activity.Methods: Twenty-six university students in their twenties (mean age: 21.5 ± 1.4 years) participated in this study. Participants sat in a chair with their eyes closed and relaxed for one minute. The scent of Abies holophylla (needle fir; hereinafter referred to as "fir") essential oil was dispersed into the air through a digital diffuser for approximately one minute, and the participants then inhaled for two minutes. A control experiment was conducted using the same method without any essential oil (room air). Functional Near-Infrared Spectroscopy (fNIRS) was used as an indicator to measure brain activity, and the oxy-hemoglobin (HbO) concentrations in the fifteen channels located in the prefrontal cortex were measured. The change in the HbO concentration was analyzed: mean concentration during one minute of scent inhalation-mean concentration during two minutes of scents inhalation.Results: By analyzing each of the 15 channels, the decrease in HbO concentration was found to be significantly higher for fir essential oil inhalation compared to room air inhalation. Furthermore, an analysis of the mean HbO concentration across all channels (CH 1-15), right hemisphere channels (CH 1-7), and left hemisphere channels (CH 9-15) showed a significantly higher decrease with fir essential oil inhalation than with room air inhalation. This effect was observed in all channels and left hemisphere channels.Conclusion: It was found that inhaling fir essential oil aids in relaxation brain activity.
Managing E-Motion and Motherhood Among Enslaved Women in East Africa
Authors: McMahon Elisabeth
Published: September 2024

Drawing on the scholarships of ‘intimate mobilities’ and ‘action as proxy for voice’, this article explores how enslaved and emancipated girls and women in Eastern Africa demonstrated the resonance of their emotional lives through their movements. E-motions are defined by Pelckmans and Rodet in the introduction to this special issue as: ‘the gendered mobilities of girls and women who moved and continue to move […] in order to establish, consolidate or move out of emotional ties in intimate, affective and private spheres’. By analysing the choice of movement by recently freed women, this article examines the representations of emotional familial commitments through the actions of women, especially regarding motherhood.
4. Emotive participants?
Authors: Bettarelli Luca , Close Caroline , Jacobs Laura , van Haute Emilie
Published: September 2024

Using the RepResent Voter Panel Survey conducted around the 2019 elections in Belgium, this chapter investigates the affective complexity of resentment and its impact on protest participation, understood as non-electoral protest participation and protest voting. We focus on the combination of two core emotions towards politics and their intensities: anger and hope. We highlight five groups that vary in their intensity of anger and hope: neutral, high-intensity hopeful, high-intensity angry, high-intensity emotive, and apathetic. We then connect these five groups to protest behaviours. Our results indicate that different emotional clusters guide distinct types of protest actions. Apathy leads to electoral exit and decreases the probability of protest participation and protest voting. High intensities of anger turns citizens away from mainstream parties and increases their propensity to vote for protest parties. The combination of high intensities of anger and hope motivates the expression of resentment through non-electoral protest actions. Our findings reaffirm the significance of the affective dimension of political action. They support a conception of affective arrangements in which emotions combine to produce political outcomes. Finally, they nuance the idea that there would be absolute positive vs. negative emotions.