bluuebunny/crossref_metadata_2025 huggingface dataset:
Why did you delete my comment? Investigating observing consumers' reactions to comment‐deletion‐clues during a brand crisis
Authors: Liao Junyun , Ye Yaohua , Filieri Raffaele , Du Peng , Jiang Ying
Published: June 2024

Many users criticize brands by posting negative comments on their social media pages when a brand crisis occurs. Brands often choose to delete negative comments when coping with brand crises. While deleting comments often goes unnoticed, complaints about comment deletion from users whose comments are deleted (e.g., “Why did you delete my comment?”) serve as clues for observers after a crisis. Drawing from Warranting Theory, this study examines comment‐deletion‐clues' impact on observers' forgiveness and negative word‐of‐mouth (NWOM) transmission and how two types of brand explanations (custom vs. general) alter this impact. Four studies show that the comment‐deletion‐clues reduce observers' intention to forgive the brand and increase the spread of NWOM. Furthermore, the results indicate that brands' custom explanations mitigate the adverse effects of comment‐deletion‐clues. This article is among the first to explore the role of content moderation during brand crises and extends the brand crisis literature and the emerging content moderation literature.
Downregulation of ALDH5A1 suppresses cisplatin resistance in esophageal squamous cell carcinoma by regulating ferroptosis signaling pathways
Authors: Song Kewei , Ma Chenhui , Maswikiti Ewetse Paul , Gu Baohong , Wang Bofang , Wang Na , Jiang Pei , Chen Hao
Published: June 2024

This study explores the specific role and underlying mechanisms of ALDH5A1 in the chemoresistance of esophageal squamous cell carcinoma (ESCC). The levels of cleaved caspase‐3, 4‐hydroxynonenal (4‐HNE), intracellular Fe2+, and lipid reactive oxygen species (ROS) were evaluated via immunofluorescence. Cell viability and migration were quantified using cell counting kit‐8 assays and wound healing assays, respectively. Flow cytometry was utilized to analyze cell apoptosis and ROS production. The concentrations of malondialdehyde (MDA) and reduced glutathione were determined by enzyme‐linked immunosorbent assay. Proteome profiling was performed using data‐independent acquisition. Additionally, a xenograft mouse model of ESCC was established to investigate the relationship between ALDH5A1 expression and the cisplatin (DDP)‐resistance mechanism in vivo. ALDH5A1 is overexpressed in both ESCC patients and ESCC/DDP cells. Silencing of ALDH5A1 significantly enhances the inhibitory effects of DDP treatment on the viability and migration of KYSE30/DDP and KYSE150/DDP cells and promotes apoptosis. Furthermore, it intensifies DDP's suppressive effects on tumor volume and weight in nude mice. Gene ontology biological process analysis has shown that ferroptosis plays a crucial role in both KYSE30/DDP cells and KYSE30/DDP cells transfected with si‐ALDH5A1. Our in vitro and in vivo experiments demonstrate that DDP treatment promotes the accumulation of ROS, lipid ROS, MDA, LPO, and intracellular Fe2+ content, increases the levels of proteins that promote ferroptosis (ACSL4 and FTH1), and decreases the expression of anti‐ferroptosis proteins (SLC7A11, FTL, and GPX4). Silencing of ALDH5A1 further amplifies the regulatory effects of DDP both in vitro and in vivo. ALDH5A1 potentially acts as an oncogene in ESCC chemoresistance. Silencing of ALDH5A1 can reduce DDP resistance in ESCC through promoting ferroptosis signaling pathways. These findings suggest a promising strategy for the treatment of ESCC in clinical practice.
Mapping Motor Cortical Network Excitability and Connectivity Changes in De Novo Parkinson's Disease
Authors: Leodori Giorgio , De Bartolo Maria Ilenia , Piervincenzi Claudia , Mancuso Marco , Ojha Abhineet , Costanzo Matteo , Aiello Flavia , Vivacqua Giorgio , Fabbrini Giovanni , Conte Antonella , Pantano Patrizia , Berardelli Alfredo , Belvisi Daniele
Published: June 2024

Background

Transcranial magnetic stimulation‐electroencephalography (TMS‐EEG) has demonstrated decreased excitability in the primary motor cortex (M1) and increased excitability in the pre‐supplementary motor area (pre‐SMA) in moderate‐advanced Parkinson's disease (PD).

Objectives

The aim was to investigate whether these abnormalities are evident from the early stages of the disease, their behavioral correlates, and relationship to cortico‐subcortical connections.

Methods

Twenty‐eight early, drug‐naive (de novo) PD patients and 28 healthy controls (HCs) underwent TMS‐EEG to record TMS‐evoked potentials (TEPs) from the primary motor cortex (M1) and the pre‐SMA, kinematic recording of finger‐tapping movements, and a 3T‐MRI (magnetic resonance imaging) scan to obtain diffusion tensor imaging (DTI) reconstruction of white matter (WM) tracts connecting M1 to the ventral lateral anterior thalamic nucleus and pre‐SMA to the anterior putamen.

Results

We found reduced M1 TEP P30 amplitude in de novo PD patients compared to HCs and similar pre‐SMA TEP N40 amplitude between groups. PD patients exhibited smaller amplitude and slower velocity in finger‐tapping movements and altered structural integrity in WM tracts of interest, although these changes did not correlate with TEPs.

Conclusions

M1 hypoexcitability is a characteristic of PD from early phases and may be a marker of the parkinsonian state. Pre‐SMA hyperexcitability is not evident in early PD and possibly emerges at later stages of the disease. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
Using passive and active data to predict posttraumatic stress disorder symptoms and cannabis use in recently discharged UK veterans: A protocol for the MAVERICK feasibility study
Authors: Williamson Grace , Trompeter Nora , Murphy Dominic , Saba Shaddy , Pedersen Eric R. , Davis Jordan P. , Leightley Daniel
Published: June 2024

Posttraumatic stress disorder (PTSD) and comorbid cannabis use disorder (CUD) is a growing concern amongst UK veterans. Co‐occurrence of problematic cannabis use, and PTSD is associated with greater PTSD symptom severity, decreased likelihood of cannabis use cessation, worse clinical outcomes, and increased societal burden. Despite increased screening efforts among veterans, there are no effective strategies for predicting risk for PTSD and problematic drug use escalation before these conditions develop, worsen, or become chronic. This feasibility study employs a 4‐week (28‐day) longitudinal design (daily data collection), multiple passive data collection features via a bespoke study smartphone app called MAVERICK, and active data collection via wearable technology to predict clinically meaningful escalations in cannabis use and PTSD symptoms in UK veterans. Questionnaire data will be collected between 06:00 a.m. and 10:00 a.m. each day. Passive data will be collected continuously in the background. The study will begin recruitment in June 2023 and will require 18 months to complete. Study results are expected to be published in January 2024. This trial will provide information on the feasibility and utility of a smartphone app (MAVERICK) to collect both active and passive data to predict PTSD symptoms and cannabis use in a UK veteran population. If the smartphone app is deemed feasible and acceptable to users, it has the potential to provide an effective measurement tool to mitigate risk of PTSD and problematic cannabis use among veterans.
Potential Impact of Bioactive Peptides from Foods in the Treatment of Hypertension
Authors: Ichim Natalia , Marín Francisco , Orenes‐Piñero Esteban
Published: June 2024

Scope

High blood pressure (BP) is the main preventable risk factor for cardiovascular diseases (CVDs). Much research is aimed at finding natural alternatives to control or prevent hypertension (HT), since some hypertensive patients do not respond to current pharmacological treatments or show undesirable side effects.

Methods and results

Forty relevant articles have been selected from various scientific literature databases. The results reveal that angiotensin‐converting enzyme (ACE) inhibition is the most reported mechanism of action of antihypertensive peptides. The active peptides have a great variety of origins. Biopeptides with a molecular weight of <3 kDa, short chain <20 amino acids, and a hydrophobic amino acid sequence at the C‐ and N‐terminus exhibit higher antihypertensive activity. They also show good stability to enzymatic hydrolysis and gastrointestinal digestion, and no toxicity. To determine antihypertensive effectiveness, in vitro and in vivo animal studies are the most frequent developed, with few in silico studies and only one human clinical trial.

Conclusion

There is interesting potential for antihypertensive peptides as promising natural candidates for the development of functional foods, nutraceuticals and drugs for preventive or therapeutic treatment of hypertension. The aim of this review is to study the role of food‐derived bioactive peptides in HT.
Amide proton transfer MRI at 9.4 T for differentiating tissue acidosis in a rodent model of ischemic stroke
Authors: Jin Tao , Wang Jicheng , Chung Julius , Hitchens T. Kevin , Sun Dandan , Mettenburg Joseph , Wang Ping
Published: June 2024

Purpose

Differentiating ischemic brain damage is critical for decision making in acute stroke treatment for better outcomes. We examined the sensitivity of amide proton transfer (APT) MRI, a pH‐weighted imaging technique, to achieve this differentiation.

Methods

In a rat stroke model, the ischemic core, oligemia, and the infarct‐growth region (IGR) were identified by tracking the progression of the lesions. APT MRI signals were measured alongside ADC, T1, and T2 maps to evaluate their sensitivity in distinguishing ischemic tissues. Additionally, stroke under hyperglycemic conditions was studied.

Results

The APT signal in the IGR decreased by about 10% shortly after stroke onset, and further decreased to 35% at 5 h, indicating a progression from mild to severe acidosis as the lesion evolved into infarction. Although ADC, T1, and T2 contrasts can only detect significant differences between the IGR and oligemia for a portion of the stroke duration, APT contrast consistently differentiates between them at all time points. However, the contrast to variation ratio at 1 h is only about 20% of the contrast to variation ratio between the core and normal tissues, indicating limited sensitivity. In the ischemic core, the APT signal decreases to about 45% and 33% of normal tissue level at 1 h for the normoglycemic and hyperglycemic groups, respectively, confirming more severe acidosis under hyperglycemia.

Conclusion

The sensitivity of APT MRI is high in detecting severe acidosis of the ischemic core but is much lower in detecting mild acidosis, which may affect the accuracy of differentiation between the IGR and oligemia.
Quantification of the rotating frame relaxation time T2ρ: Comparison of balanced spin‐lock and continuous‐wave Malcolm‐Levitt preparations
Authors: Gram Maximilian , Christa Martin , Gutjahr Fabian Tobias , Albertova Petra , Williams Tatjana , Jakob Peter Michael , Bauer Wolfgang Rudolf , Nordbeck Peter
Published: June 2024

For the quantification of rotating frame relaxation times, the T2ρ relaxation pathway plays an essential role. Nevertheless, T2ρ imaging has been studied only to a small extent compared with T1ρ, and preparation techniques for T2ρ have so far been adapted from T1ρ methods. In this work, two different preparation concepts are compared specifically for the use of T2ρ mapping. The first approach involves transferring the balanced spin‐locking (B‐SL) concept of T1ρ imaging. The second and newly proposed approach is a continuous‐wave Malcolm‐Levitt (CW‐MLEV) pulse train with zero echo times and was motivated from T2 preparation strategies. The modules are tested in Bloch simulations for their intrinsic sensitivity to field inhomogeneities and validated in phantom experiments. In addition, myocardial T2ρ mapping was performed in mice as an exemplary application. Our results demonstrate that the CW‐MLEV approach provides superior robustness and thus suggest that established methods of T1ρ imaging are not best suited for T2ρ experiments. In the presence of field inhomogeneities, the simulations indicated an increased banding compensation by a factor of 4.1 compared with B‐SL. Quantification of left ventricular T2ρ time in mice yielded more consistent results, and values in the range of 59.2–61.1 ms (R2 = 0.986–0.992) were observed at 7 T.
Effect of filling materials on the tribological performance of polytetrafluoroethylene in different wear modes
Authors: Fidan Sinan , Korkusuz Orkan Baran , Toker Pelin Özzaim , Gültürk Elif , Ateş Bülent Hayri , Sınmazçelik Tamer
Published: June 2024

As it is known, Polytetrafluoroethylene (PTFE) is one of the most preferred polymeric materials for tribological applications. This study investigates the performance of PTFE and its composites under different tribological conditions. The effects of short glass fiber (GF), carbon particle (CP) and bronze particle (BP) reinforcement agents and their hybrid filling with molybdenum disulfide (MoS2) on sliding, erosive and abrasive wear were examined. Sliding tests were carried out with a ball‐on‐disc test apparatus, erosive wear tests were carried out with solid particle erosion and abrasive wear tests were carried out with a scratch test. It has been found that reinforcement agents improve sliding and abrasive wear resistance but worsen the erosion resistance. The hardness and contact angle of the samples were associated with their wear performances. Topographic and morphological analyzes of worn surfaces were performed using optical profilometer and scanning electron microscopy (SEM), respectively, and wear mechanisms were discussed.

Highlights

Filling materials (glass fiber, carbon particle and bronze particle) increase the adhesion and abrasion resistance of PTFE, while decreasing its erosion resistance.

The effect of hybrid addition of MoS2 solid lubricant on wear performances depends on the type of filler.

There is a correlation between surface properties (hardness and contact angle) and wear performances.

Optical profilometer and scanning electron microscopy were used to examine wear mechanisms.
Preparation and properties of biodegradable directional water transport composite fabrics
Authors: Yang Hui , Wang Yuxin , Fan Zihan , Jia Qingxiu , Hu Shui , Pei Guangling
Published: June 2024

Moisture (i.e., sweat) management is essential for maintaining human physiological comfort. But conventional fabrics and moisture‐absorbent and quick‐drying fabrics cannot simultaneously possess directional water transport (DWT) functionality and environmental protection characteristics, while also causing a sticky sensation on the skin when worn. Herein, the polylactic acid (PLA) electrospun membranes were deposited on the PLA side of a double‐yarn weft‐knitted fabric (hydrophobic PLA filament and hydrophilic cotton yarn) with asymmetric wettability, and green composite fabrics with papillary structures and unidirectional moisture transport capability were obtained using hot‐press. The properties of these composite fabrics were evaluated by scanning electron microscopy, moisture management testing, dynamic scanning calorimetry, water contact angle (WCA), and water permeability. The results showed that the wettability gradient difference between the two sides of the fabric increased, enhancing the unidirectional moisture transport capability. The optimal performance composite fabric achieved an accumulative one‐way transport capacity of 1285% and an overall moisture management capacity of 0.693. Additionally, the WCA on the hydrophobic side measured 150°, remaining at 146.8° after two washes. Overall, this composite fabric strikes a balance between biodegradability and exceptional DWT performance, rendering it an environmentally friendly and recyclable choice for moisture‐wicking and quick‐drying apparel applications.

Highlights

Created PLA/cotton‐knitted fabric with asymmetric wettability.

Hydrophobic PLA membrane deposited on fabric surface using electrospinning.

Green composite fabrics with excellent DWT functionality were made by hot‐press.

Best composite fabric: R‐value 1285.6%, OMMC 0.696, WCA 150°.

Best composite fabric retains WCA of 146.8° after two washes.
Utilization of MOF‐enhanced hydrophilic nanocomposite reverse osmosis membrane for desalination with antifouling capabilities
Authors: Zhang Jiaying , Soliman Aya , El‐marghany Adel , Morsy Ahmed , Mohamed Asmaa , Shehata Nader , Fadl Eman A. , Morsy Ashraf
Published: June 2024

Cellulose acetate (CA) membranes used in reverse osmosis (RO) desalination techniques often face fouling challenges. In this experimental study, the phase inversion method was employed to investigate the incorporation of graphene oxide nanoparticles (GONP) metal–organic frameworks (MOF), into the casting solution for composite CA‐RO membranes. The effects of varying GONP concentrations on fouling resistance and hydrophilicity were evaluated using scanning electron microscopy (SEM), contact angle measurements, and water content analysis. The results demonstrated that the modified CA membrane with 0.05 wt% GONP exhibited improved water permeability (10.3 L/m2 h) and salt rejection (95.8%) compared with the pristine CA membrane. These improvements stem from increased hydrophilicity and reduced fouling. This study's findings suggest that incorporating GONP into the polymeric doped solution can effectively mitigate fouling issues and enhance the performance of RO membranes in desalination applications.

Highlights

GONP enhances hydrophilicity, reducing fouling in desalination.

Effects of varying GONP concentrations were studied.

GONP‐CA membrane shows better permeability and salt rejection than pristine.

Nanocomposite membranes promise in overcoming fouling in RO membranes.
Effectiveness and acceptability of remote consultation to promote positive behaviors in preschoolers
Authors: Kahan Sara , Rahill Stephanie
Published: June 2024

One of the roles of school psychologists is consultation, an indirect service delivery method in which the consultant (i.e., the school psychologist) supports students' academic, behavioral, and social‐emotional functioning through collaborating with teachers and parents. Conjoint Behavioral Consultation (CBC), also known as Teachers and Parents as Partners (TAPP), is unique in that teachers and parents work together during the consultation process to improve elementary, middle, and high school students' functioning. This study evaluted the effects of CBC for children in early childhood when conducted via remote delivery. A nonconcurrent multiple baseline across participants design was used to evaluate the efficacy of CBC at improving outcomes for children in early childhood at home and school. Additionally, teacher and parent acceptability of CBC and CBC provided remotely were assessed. Participants included four parent‐teacher‐student triads. Results found CBC to improve difficulties for preschool children across settings. Additionally, CBC acceptability via remote delivery was high for both parents and teachers.
Can growth mindset always promote students' math achievement? Perspectives from Chinese university students
Authors: He Guohao , Hua Tian , Liang Fang , Su Aoxue
Published: June 2024

Although the growth mindset is essential to students' math achievement, its mechanism of influence remains uncertain, particularly for college students. Accordingly, this study explored the relationship between college students' growth mindset and their math achievement, as mediated by their self‐efficacy and reasoning ability. The study data were gathered by surveying 576 undergraduates taking various undergraduate programs at a Chinese university. Our results showed that (1) students' growth mindset did not directly predict their math achievement; (2) self‐efficacy mediated the relationship between students' growth mindset and their math achievement; and (3) the growth mindset affected students' math achievement through the chain‐mediation of self‐efficacy and reasoning ability. Overall, the finding that the growth mindset indirectly benefits Chinese college students' math achievement provides invaluable guidance to higher education professionals aiming to develop more effective math programs. Moreover, the mediating effects of self‐efficacy and reasoning ability were also theoretically important to better understand the potential influence mechanism of the growth mindset on college students' math achievement.
Including families in the implementation of school‐wide positive behavioral interventions and support: Dutch administrators and SWPBIS‐leadership team experiences
Authors: Willemse T. Martijn , Nelen Monique J. M. , Blonk Anita
Published: June 2024

Despite the fact that research shows that collaboration between families and schools contribute to academic achievement, social‐emotional development and sense of well‐being of students, many schools struggle to establish family‐school partnerships. The current study explores keys to success and challenges in engaging families to the design and implementation of School Wide Positive Behavioral Interventions and Supports (SWPBIS). In a two‐step systematic assessment, consisting of an online survey (n = 27 participants) and five focus group interviews with administrators and members of SWPBIS leadership teams in schools for primary education (n = 15 participants), we found that all 27 participating schools considered partnerships and communication with parents important. However, most participating schools did not have a policy or strategic planning for engaging families, nor did they systematically evaluate their actions. Schools used one‐way approaches of communicating with parents and found it hard to adapt their communication to a diverse population of new parents and parents already familiar with SWPBIS. Schools did not communicate about what was achieved by implementing SWPBIS in their school. Including families in the SWPBIS leadership team was often considered challenging. Input from families on SWPBIS was not collected, nor did schools gather information about family's needs, (cultural) backgrounds to develop strategies for engaging families. Further research on actual school practices in engaging families is recommended.
Psychotomimetic compensation versus sensitization
Authors: Brouwer Ari , Carhart‐Harris Robin L. , Raison Charles L.
Published: June 2024

It is a paradox that psychotomimetic drugs can relieve symptoms that increase risk of and cooccur with psychosis, such as attention and motivational deficits (e.g., amphetamines), pain (e.g., cannabis) and symptoms of depression (e.g., psychedelics, dissociatives). We introduce the ideas of psychotomimetic compensation and psychotomimetic sensitization to explain this paradox. Psychotomimetic compensation refers to a short‐term stressor or drug‐induced compensation against stress that is facilitated by engagement of neurotransmitter/modulator systems (endocannabinoid, serotonergic, glutamatergic and dopaminergic) that mediate the effects of common psychotomimetic drugs. Psychotomimetic sensitization occurs after repeated exposure to stress and/or drugs and is evidenced by the gradual intensification and increase of psychotic‐like experiences over time. Theoretical and practical implications of this model are discussed.
Teaching an old drug new tricks: Regulatory insights for the repurposing of hemin in cardiovascular disease
Authors: Eadie Ashley L. , Simpson Jeremy A. , Brunt Keith R.
Published: June 2024

Drug repurposing has gained significant interest in recent years due to the high costs associated with de novo drug development; however, comprehensive pharmacological information is needed for the translation of pre‐existing drugs across clinical applications. In the present study, we explore the current pharmacological understanding of the orphan drug, hemin, and identify remaining knowledge gaps with regard to hemin repurposing for the treatment of cardiovascular disease. Originally approved by the United States Food and Drug Administration in 1983 for the treatment of porphyria, hemin has attracted significant interest for therapeutic repurposing across a variety of pathophysiological conditions. Yet, the clinical translation of hemin remains limited to porphyria. Understanding hemin's pharmacological profile in health and disease strengthens our ability to treat patients effectively, identify therapeutic opportunities or limitations, and predict and prevent adverse side effects. However, requirements for the pre‐clinical and clinical characterization of biologics approved under the U.S. FDA's Orphan Drug Act in 1983 (such as hemin) differed significantly from current standards, presenting fundamental gaps in our collective understanding of hemin pharmacology as well as knowledge barriers to clinical translation for future applications. Using information extracted from the primary and regulatory literature (including documents submitted to Health Canada in support of hemin's approval for the Canadian market in 2018), we present a comprehensive case study of current knowledge related to hemin's biopharmaceutical properties, pre‐clinical/clinical pharmacokinetics, pharmacodynamics, dosing, and safety, focusing specifically on the drug's effects on heme regulation and in the context of acute myocardial infarction.
Enablers and obstacles for designing and implementing intersectoral health policies: Lessons from Mexico
Authors: Martinez‐Valle Adolfo , Figueroa‐Lara Alejandro
Published: June 2024

Background

This study analyzes how national intersectoral public policy experiences have been adopted and implemented using a Health in All Policies (HiAP) approach in the past two decades. It seeks to provide evidence on enabling factors that triggered three effective intersectoral public policies to improve population health in Mexico by improving nutritional, educational, and healthcare access conditions, reducing road traffic injuries, and addressing obesogenic feeding practices.

Methods

We followed a qualitative approach to analyze the three intersectoral public policies selected as case studies. First, we designed an analytical framework to assess how intersectoral public policies are adopted, implemented, and sustained. The proposed framework is based on peer‐reviewed articles and gray public policy literature. Second, we used information from eleven semi‐structured interviews with key stakeholders conducted in previous research to identify more specific enablers and barriers of the three intersectoral policies selected according to predefined analytical categories used in the questionnaire.

Results

The analysis showed three overall key findings. First, sound empirical evidence is essential for adopting a HiAP approach. Second, effective intersectoral mechanisms enhance implementation feasibility. Third, results‐based monitoring and evaluation contribute to the continuity of the analyzed intersectoral public policies. Finally, political support is needed throughout the policy process to maintain governance capacity and deliver results.

Conclusion

We drew five global policy lessons that may be applicable in similar public policy settings in other countries. First, both technical and political enablers help set the intersectoral agenda. Second, effective communication is instrumental in convincing all stakeholders to address public health‐related policy issues. Third, political support at the highest level possible and the federal government's capacity are essential to implement sound policies. Fourth, several enablers exist for enhancing collaboration between ministries during implementation. Finally, monitoring and evaluation results are necessary for sustaining intersectoral policies beyond administrations.
Event‐triggered stabilization for systems with an unknown control direction
Authors: Zhu Lijun , Chen Zhiyong
Published: June 2024

In this article, we present an event‐triggered control law for systems with an unknown control direction, where the adaptation dynamics of the Nussbaum gain are sampled. Specifically, we employ the emulation method and introduce a specific set of sampling errors. This approach enables the design of an event‐triggered law without encountering Zeno behavior. Additionally, we introduce a lemma to address the non‐integrability issue of the Nussbaum gain dynamics during the event‐triggered law design. We apply this design philosophy to co‐design both the continuous‐time controller and the event‐triggered law, aiming to achieve the global stabilization of systems with an unknown control direction. Finally, we validate the theoretical results through a numerical example.
Robust multiple fault detection and estimation approaches based on adaptive finite‐time observer for nonlinear systems
Authors: Qiu Bingzhao , Ban Mingfei , Li Xin , Liu Yiqi , Zhu Liangkuan , Song Wenlong
Published: June 2024

This article investigates robust multiple fault detection (FD) and fault estimation (FE) schemes, based on adaptive finite‐time observer (AFTO), applied to nonlinear systems with disturbances, actuator faults, and sensor faults. The AFTO is designed, and a parameter adaptive law is constructed to continuously optimize the residual based performance function to improve the AFTO robustness. The schemes are able to simultaneously detect and estimate unknown states, disturbances, and faults. The AFTO's design, finite‐time convergence and stability conditions are guaranteed in terms of linear matrix inequalities. Finally, simulation results, based on two typical practical systems, are given to illustrate the effectiveness of the proposed approaches. The simulation results also show that the designed AFTO can offer faster convergence speed, higher estimation accuracy, and stronger robustness than conventional observer and sliding mode observer.
A multivariate to multivariate approach for voxel‐wise genome‐wide association analysis
Authors: Wu Qiong , Zhang Yuan , Huang Xiaoqi , Ma Tianzhou , Hong L. Elliot , Kochunov Peter , Chen Shuo
Published: June 2024

The joint analysis of imaging‐genetics data facilitates the systematic investigation of genetic effects on brain structures and functions with spatial specificity. We focus on voxel‐wise genome‐wide association analysis, which may involve trillions of single nucleotide polymorphism (SNP)‐voxel pairs. We attempt to identify underlying organized association patterns of SNP‐voxel pairs and understand the polygenic and pleiotropic networks on brain imaging traits. We propose a bi‐clique graph structure (ie, a set of SNPs highly correlated with a cluster of voxels) for the systematic association pattern. Next, we develop computational strategies to detect latent SNP‐voxel bi‐cliques and an inference model for statistical testing. We further provide theoretical results to guarantee the accuracy of our computational algorithms and statistical inference. We validate our method by extensive simulation studies, and then apply it to the whole genome genetic and voxel‐level white matter integrity data collected from 1052 participants of the human connectome project. The results demonstrate multiple genetic loci influencing white matter integrity measures on splenium and genu of the corpus callosum.
Bayesian survival analysis with INLA
Authors: Alvares Danilo , van Niekerk Janet , Krainski Elias Teixeira , Rue Håvard , Rustand Denis
Published: June 2024

This tutorial shows how various Bayesian survival models can be fitted using the integrated nested Laplace approximation in a clear, legible, and comprehensible manner using the INLA and INLAjoint
R‐packages. Such models include accelerated failure time, proportional hazards, mixture cure, competing risks, multi‐state, frailty, and joint models of longitudinal and survival data, originally presented in the article “Bayesian survival analysis with BUGS.” In addition, we illustrate the implementation of a new joint model for a longitudinal semicontinuous marker, recurrent events, and a terminal event. Our proposal aims to provide the reader with syntax examples for implementing survival models using a fast and accurate approximate Bayesian inferential approach.
Negative Thermal Expansion in ABC(MoO4)3 Compounds
Authors: Zhao Huan , Qiao Yongqiang , Zhao Kaiyue , Wang Qingjie , Zhang Peixian , Guo Juan , Chao Mingju , Liang Erjun , Gao Qilong
Published: June 2024

Negative thermal expansion (NTE) compounds provide a solution for the mismatch of coefficients of thermal expansion in highly integrated device design. However, the current NTE compounds are rare, and how to effectively design new NTE compounds is still challenging. Here, a new concept is proposed to design NTE compounds, that is, to increase the flexibility of framework structure by expanding the space in framework structure compounds. Taking the parent compound NaZr2(PO4)3 as a case, a new NTE system AIBIICIII(MoO4)3 (A = Li, Na, K, and Rb; B = Mg and Mn; C = Sc, In, and Lu) is designed. In these compounds, the large volume of MoO4 tetrahedron is used to replace the small volume of PO4 tetrahedron in NaZr2(PO4)3 to enhance structural space and NTE performance. Simultaneously, a joint study of temperature‐dependent X‐ray diffraction, Raman spectroscopy, and the first principles calculation reveals that the NTE in AIBIICIII(MoO4)3 series compounds arise from the coupled oscillation of polyhedral. Large‐radius ions are conducive to enhancing the space and softening the framework structure to achieve the enhancement of NTE. The current strategy for designing NTE compounds is expected to be adopted in other compounds to obtain more NTE compounds.
Transformer Connections: Improving Segmentation in Blurred Near‐Infrared Blood Vessel Image in Different Depth
Authors: Wang Jiazhe , Shimizu Koichi , Yoshie Osamu
Published: June 2024

High‐fidelity segmentation of blood vessels plays a pivotal role in numerous biomedical applications, such as injection assistance, cancer detection, various surgeries, and vein authentication. Near‐infrared (NIR) transillumination imaging is an effective and safe method to visualize the subcutaneous blood vessel network. However, such images are severely blurred because of the light scattering in body tissues. Inspired by the Vision Transformer model, this paper proposes a novel deep learning network known as transformer connection (TRC)‐Unet to capture global blurred and local clear correlations while using multi‐layer attention. Our method mainly consists of two blocks, thereby aiming to remap skip connection information flow and fuse different domain features. Specifically, the TRC extracts global blurred information from multiple layers and suppresses scattering to increase the clarity of vessel features. Transformer feature fusion eliminates the domain gap between the highly semantic feature maps of the convolutional neural network backbone and the adaptive self‐attention maps of TRCs. Benefiting from the long‐range dependencies of transformers, we achieved competitive results in relation to various competing methods on different data sets, including retinal vessel segmentation, simulated blur image segmentation, and real NIR blood vessel image segmentation. Moreover, our method remarkably improved the segmentation results of simulated blur image data sets and a real NIR vessel image data set. The quantitative results of ablation studies and visualizations are also reported to demonstrate the superiority of the TRC‐Unet design. © 2024 The Author(s). IEEJ Transactions on Electrical and Electronic Engineering published by Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.
Time to Proficiency in Young English Learners and Factors That Affect Progress
Authors: Zhang Xiaowan , Winke Paula
Published: June 2024

We investigated the time it takes 54,146 English learners (ELs) to attain English proficiency as they progressed from age 5 to 11 on average (Kindergarten through fifth grade in the United States). We also examine to what extent the time‐to‐proficiency estimate is affected by child‐internal and child‐external factors, including primary disability status, primary home language, home English use, instructional programming, and retention status. We used discrete‐time survival analysis to analyze the children's English growth. Survival analysis often concerns time from treatment until death: Here, “survival” is the time from EL‐program entry until “proficiency,” indicated via standardized testing. Half of the students attained proficiency in 5 years. Literacy skills (reading and writing) in general developed at slower rates than oral language skills (speaking and listening), with writing being ELs' biggest barrier to proficiency. While time to proficiency was significantly related to primary disability status, primary home language, and retention status, exposing ELs to their home language at home or at school does not have a substantial effect on their rates of English acquisition. The results are discussed for their research and practical implications.
Sex trafficking in the Caribbean: A comparative analysis of policy responses in the Dominican Republic and Trinidad and Tobago
Authors: Hem‐Lee‐Forsyth Shivaughn , Viechweg N'Diera , Estevez Eden , Walcott‐Pierre Terrisha , Wong Lauren
Published: June 2024

Human trafficking poses a global humanitarian and public health concern, particularly affecting women and migrants in many countries. This article assessed existing policies and laws addressing human trafficking and the sexual exploitation of women in the Caribbean nations of the Dominican Republic and Trinidad and Tobago. It identified the legislative frameworks and procedures for anti‐trafficking efforts in the Dominican Republic and Trinidad and Tobago through a comprehensive review of academic literature and policy documents. The analysis focused on evaluating the successes and challenges in implementing these policies. Findings revealed that while both countries had established anti‐trafficking laws, several structural, economic, social, and political barriers prevented effective interventions catering to the needs of vulnerable populations. Based on the analysis, recommendations were made to mitigate country and regional human trafficking, with a focus on the protection of women. Key recommendations include enhancing economic opportunities, strengthening social protections, and improving the criminal justice system's capacity to combat trafficking. A reduction in trafficking and sexual exploitation in the Dominican Republic and Trinidad and Tobago requires comprehensive policy implementation strategies aimed at protecting and supporting at‐risk native and migrant populations, providing sound economic opportunities and social protection, and strengthening effective legal responses to combat trafficking.
Innovation and AI: An Opportunity for Spanish Tourism in the Post COVID-19 Era
Authors: Torres-Penalva Aimée , Moreno-Izquierdo Luis
Published: June 2024

The value of innovation in economic activity is undeniable, as is the importance of tourism in the Spanish economy. However, tourism has traditionally been considered less innovative than other sectors, which has led to less attention being paid to research in this area. With the arrival of the pandemic and its destructive impact on tourism, interest in new technologies applied to the sector has reached its peak. For this reason, this paper seeks to determine whether the use of these technologies, and specifically AI, represents an opportunity for the Spanish tourism sector in the post-COVID-19 crisis. To this end, a descriptive analysis of several successful cases of the application of this technology in the sector is carried out, as well as a solution to one of the problems arising from this new situation: the use of face masks.
Big Data in Real Time for the Management of Tourist Destinations: The TOURETHOS Platform Technological Model
Authors: Hernández-Cabrera José Juan , Plácido-Castro Ana María , Bulchand-Gidumal Jacques
Published: June 2024

Big data is one of the main existing promises for improving the management of tourist destinations. The acquisition of large amounts of data from different sources, their consolidation and exploitation by means of artificial intelligence algorithms will allow the achievement of various objectives for destination management, such as understanding tourist flows, an increase and better distribution of tourist spending, improving the quality of life of residents and achieving better sustainability. Additional benefits could even be obtained if this big data were to be managed in real time. To achieve these objectives, it is necessary to have high quality and reliable data sources. This article describes a technological platform called Tourethos, which allows active collaboration between different stakeholders to collect data on the movements of tourists in the territory based on their connections to Wi-Fi networks in the area. This data source has interesting and valuable characteristics: it is relatively simple to collect, it can be easily anonymized and it offers a sufficient level of precision to draw valuable conclusions for the management of tourist destinations in real time.
Framework for a Tourism Intelligence System Based on Knowledge Governance: A Conceptual Model
Authors: Emmendoerfer Luana , Biz Alexandre Augusto , de Sá Ferreira Patrícia
Published: June 2024

The objective of this article is to present a framework of Tourism Intelligence System (TIS) with support in Knowledge Governance (GovC) to support decision making in tourist destinations. The form of cooperation and use of knowledge should be structured through mechanisms that allow availability and reliability. The methodological framework is structured in Design Science Research (DSR) of technological and applied nature, with data collection method using a qualitative approach, classified as exploratory and descriptive, from the validation of semi-structured interviews with experts in the tourism sector and technology. This architecture was composed of three layers: knowledge application, knowledge generation and application, and knowledge generation. It focuses on the extraction of data generated by the tourist trip in the pre-trip, during trip, and post-trip phases, using Knowledge Management (KM) processes such as knowledge identification, acquisition, and use. The GovC aspect considered the mechanisms aimed at the sustainability and evolution of the TIS, as well as the hybrid structure through network and market formation, by means of knowledge centers with actors involved in the segments of the tourism production chain.
Funding Policies, Tourism Entrepreneurship and Innovation in the Territory: Emprendetur (Spain)
Authors: Figueroa-Domecq Cristina , Fuentes-Moraleda Laura , González-Rodríguez María Rosario , Flecha-Barrio María Dolores
Published: June 2024

Innovation is a vehicle for modernization and competitiveness in tourism and, even so, the report on Tourism Innovation and Smart Specialization of SEGITTUR and COTEC (2021) confirms that the tourism sector does not innovate enough. This article evaluates the call for funding for tourism entrepreneurship Emprendetur, developed by SEGITTUR (2012–2016). Through an exploratory analysis, the objective is to examine the geographical distribution of tourism entrepreneurship and innovation, as well as the type of innovation developed in each territory and the success in obtaining funding for these innovations. The main conclusion of the study is that there is a geographical inequality in the distribution of entrepreneurship and innovation in tourism in Spain. There is a concentration of applications from entrepreneurs in urban areas such as Madrid and Catalonia, as well as greater success of these applications, due to a greater emphasis on entrepreneurship and innovation focused on Information and Communication Technologies (ICTs). These results show how the design of policies to support innovation in tourism must consider regional disparities, to close the gaps generated and promote sustainable and egalitarian development.
The Why, the How and the When of Educational Process Mining in R
Authors: López-Pernas Sonsoles , Saqr Mohammed
Published: June 2024

This chapter presents the topic of process mining applied to learning analytics data. The chapter begins by introducing the fundamental concepts of the method, with a focus on event log construction and visual representation using directly-follows graphs. A review of the existing literature on educational process mining is also presented to introduce the reader to the state of the art of the field. The chapter follows with a guided tutorial in R on how to apply process mining to trace log data extracted from an online learning management system. The tutorial uses the framework for data handling and visualization. We finish the chapter with a reflection on the method and its reliability and applicability.
Epistemic Network Analysis and Ordered Network Analysis in Learning Analytics
Authors: Tan Yuanru , Swiecki Zachari , Ruis A. R. , Shaffer David
Published: June 2024

This chapter provides a tutorial on conducting epistemic network analysis (ENA) and ordered network analysis (ONA) using R. We introduce these two techniques together because they share similar theoretical foundations, but each addresses a different challenge for analyzing large-scale qualitative data on learning processes. ENA and ONA are methods for quantifying, visualizing, and interpreting network data. Taking coded data as input, ENA and ONA represent associations between codes in undirected or directed weighted network models, respectively. Both techniques measure the strength of association among codes and illustrate the structure of connections in network graphs, and they quantify changes in the composition and strength of those connections over time. Importantly, ENA and ONA enable comparison of networks both visually and via summary statistics, so they can be used to explore a wide range of research questions in contexts where patterns of association in coded data are hypothesized to be meaningful and where comparing those patterns across individuals or groups is important.
An Introduction and R Tutorial to Model-Based Clustering in Education via Latent Profile Analysis
Authors: Scrucca Luca , Saqr Mohammed , López-Pernas Sonsoles , Murphy Keefe
Published: June 2024

Heterogeneity has been a hot topic in recent educational literature. Several calls have been voiced to adopt methods that capture different patterns or subgroups within students’ behavior or functioning. Assuming that there is “an average” pattern that represents the entirety of student populations requires the measured construct to have the same causal mechanism, same development pattern, and affect students in exactly the same way. Using a person-centered method (finite Gaussian mixture model or latent profile analysis), the present tutorial shows how to uncover the heterogeneity within engagement data by identifying three latent or unobserved clusters. This chapter offers an introduction to the model-based clustering that includes the principles of the methods, a guide to choice of number of clusters, evaluation of clustering results and a detailed guide with code and a real-life dataset. The discussion elaborates on the interpretation of the results, the advantages of model-based clustering as well as how it compares with other methods.