bluuebunny/crossref_metadata_2025 huggingface dataset:
Efficient image restoration with style-guided context cluster and interaction
Authors: Qiao Fengjuan , Zhu Yonggui , Meng Ming
Published: February 2024

Recently, convolutional neural networks (CNNs) and vision transformers (ViTs) have emerged as powerful tools for image restoration (IR). Nonetheless, they encountered some limitations due to their characteristics, such as CNNs sacrificing global reception and ViTs requiring large memory and graphics resources. To address these limitations and explore an alternative approach for improved IR performance, we propose two clustering-based frameworks for general IR tasks, which are style-guided context cluster U-Net (SCoC-UNet) and style-guided clustered point interaction U-Net (SCPI-UNet). The SCoC-UNet adopts a U-shaped architecture, comprising position embedding, Encoder, Decoder, and reconstruction block. Specifically, the input low-quality image is viewed as a set of unorganized points, each of which is first given location information by the continuous relative position embedding method. These points are then fed into a symmetric Encoder and Decoder which utilize style-guided context cluster (SCoC) blocks to extract potential context features and high-frequency information. Although SCoC-UNet has obtained decent performance for image restoration, its SCoC block can only capture connectivity at points within the same cluster, which may ignore long-range dependencies in different clusters. To address this issue, we further propose a SCPI-UNet based on SCoC-UNet, which leverages a style-guided clustered point interaction (SCPI) block in place of the SCoC block. The SCPI block utilizes a cross-attention mechanism to establish the connections of feature points between different clusters. Extensive experimental results demonstrate that the proposed SCoC-UNet and SCPI-UNet can handle several typical IR tasks (i.e., JPEG compression artifact reduction, image denoising, and super-resolution) and achieve superior quantitative and qualitative performance over some state-of-the-art methods.
A new hybrid approach for grapevine leaves recognition based on ESRGAN data augmentation and GASVM feature selection
Authors: Doğan Gürkan , Imak Andaç , Ergen Burhan , Sengur Abdulkadir
Published: February 2024

Grapevine leaf is a commodity that is collected only once a year and has a high return on investment due to its export. However, only certain types of grapevine leaves are consumed. Therefore, it is extremely important to distinguish the types of grapevine leaves. In particular, performing this process automatically on industrial machines will reduce human errors, workload, and thus cost. In this study, a new hybrid approach based on a convolutional neural network is proposed that can automatically distinguish the types of grapevine leaves. In the proposed approach, firstly, the overfitting of network models is prevented by applying data augmentation techniques. Second, new synthetic images were created with the ESRGAN technique to obtain detailed texture information. Third, the top blocks of the MobileNetV2 and VGG19 CNN models were replaced with the newly designed top block, effectively extracting features with the data. Fourthly, the GASVM algorithm was adapted and used to create a subset of the features to eliminate the ineffective and unimportant ones from the obtained features. Finally, SVM classification was performed with the feature subset consisting of 314 features, and approximately 2% higher accuracy and MCC score were obtained compared to the approaches in the literature.
Passive or active drainage system for chronic subdural haematoma—a single-center retrospective follow-up study
Authors: Majewska Paulina , Madsbu Mattis A. , Sagberg Lisa Millgård , Gulati Sasha , Jakola Asgeir Store , Solheim Ole
Published: February 2024

Background

Postoperative drainage systems have become a standard treatment for chronic subdural hematoma (CSDH). We previously compared treatment results from three Scandinavian centers using three different postoperative drainage systems and concluded that the active subgaleal drainage was associated with lower recurrence and complication rates than the passive subdural drainage. We consequently changed clinical practice from using the passive subdural drainage to the active subgaleal drainage.

Objective

The aim of the present study was to assess a potential change in reoperation rates for CSDH after conversion to the active subgaleal drainage.

Methods

This single-center cohort study compared the reoperation rates for recurrent same-sided CSDH and postoperative complication rates between patients treated during two study periods (passive subdural drainage cohort versus active subgaleal drainage cohort).

Results

In total, 594 patients were included in the study. We found no significant difference in reoperation rates between the passive subdural drain group and the active subgaleal drain group (21.6%, 95% CI 17.5–26.4% vs. 18.0%, 95% CI 13.8–23.2%; p = 0.275). There was no statistical difference in the rate of serious complications between the groups. The operating time was significantly shorter for patients operated with the active subgaleal drain than patients with the passive subdural drain (32.8 min, 95% CI 31.2–34.5 min vs. 47.6 min, 95% CI 44.7–50.4 min; p < 0.001).

Conclusions

Conversion from the passive subdural to the active subgaleal drainage did not result in a clear reduction of reoperation rates for CSDH in our center.
Developmental origins of psycho-cardiometabolic multimorbidity in adolescence and their underlying pathways through methylation markers: a two-cohort study
Authors: Choudhary Priyanka , Ronkainen Justiina , Carson Jennie , Karhunen Ville , Lin Ashleigh , Melton Phillip E. , Jarvelin Marjo-Riitta , Miettunen Jouko , Huang Rae-Chi , Sebert Sylvain
Published: February 2024

Understanding the biological mechanisms behind multimorbidity patterns in adolescence is important as they may act as intermediary risk factor for long-term health. We aimed to explore relationship between prenatal exposures and adolescent’s psycho-cardiometabolic intermediary traits mediated through epigenetic biomarkers, using structural equation modeling (SEM). We used data from mother–child dyads from pregnancy and adolescents at 16–17 years from two prospective cohorts: Northern Finland Birth Cohort 1986 (NFBC1986) and Raine Study from Australia. Factor analysis was applied to generate two different latent factor structures: (a) prenatal exposures and (b) adolescence psycho-cardiometabolic intermediary traits. Furthermore, three types of epigenetic biomarkers were included: (1) DNA methylation score for maternal smoking during pregnancy (DNAmMSS), (2) DNAm age estimate PhenoAge and (3) DNAm estimate for telomere length (DNAmTL). Similar factor structure was observed between both cohorts yielding three prenatal factors, namely BMI (Body Mass Index), SOP (Socio-Obstetric-Profile), and Lifestyle, and four adolescent factors: Anthropometric, Insulin-Triglycerides, Blood Pressure, and Mental health. In the SEM pathways, stronger direct effects of F1prenatal-BMI (NFBC1986 = β: 0.27; Raine = β: 0.39) and F2prenatal-SOP (β: −0.11) factors were observed on adolescent psycho-cardiometabolic multimorbidity. We observed an indirect effect of prenatal latent factors through epigenetic markers on a psycho-cardiometabolic multimorbidity factor in Raine study (P < 0.05). The present study exemplifies an evidence-based approach in two different birth cohorts to demonstrate similar composite structure of prenatal exposures and psycho-cardiometabolic traits (despite cultural, social, and genetic differences) and a common plausible pathway between them through underlying epigenetic markers.
Human-centered design and evaluation of a workplace for the remote assistance of highly automated vehicles
Authors: Schrank Andreas , Walocha Fabian , Brandenburg Stefan , Oehl Michael
Published: February 2024

Remotely operating vehicles utilize the benefits of vehicle automation when fully automated driving is not yet possible. A human operator ensures safety and availability from afar and supports the vehicle automation when its capabilities are exceeded. The remote operator, conceptualized as remote assistant, fulfills the legal requirements in Germany as a Technical Supervisor to operate highly automated vehicles at Society of Automotive Engineers 4. To integrate the remote operator into the automated driving system, a novel user-centered human–machine interface (HMI) for a remote assistant’s workplace was developed and initially evaluated. The insights gained in this process were incorporated into the design of a workplace prototype for remote assistance. This prototype was tested in the study reported here by 34 participants meeting the professional background criteria for the role of Technical Supervisor according to the German law. Typical scenarios that may occur in highly automated driving and require remote assistance were created in a simulation environment. Even under elevated cognitive load induced by simultaneously engaging in a secondary task, participants were able to obtain sufficient situation awareness and quickly resolve the scenarios. The HMI also yielded favorable usability and acceptance ratings. The results of this study inform the iterative workplace development and further research on the remote assistance of highly automated vehicles.
When competence and confidence are at odds: a cross-country examination of the Dunning–Kruger effect
Authors: Yang Hansen Kajsa , Thorsen Cecilia , Radišić Jelena , Peixoto Francisco , Laine Anu , Liu Xin
Published: February 2024

Research has shown that some students who underperform in mathematics overestimate their performance, while others who excel in mathematics underestimate it. Looking at this mismatch of performance and confidence judgement—the Dunning–Kruger effect (DKE)—the current study investigates how well students’ confidence judgement and item-specific mathematics competence relate with each other and whether such a relationship differs across six European countries (i.e., Norway, Sweden, Finland, Estonia, Serbia and Portugal). We also examine whether perceived competence, mathematics identity, gender, socioeconomic status and immigration background predict this mismatch and whether these demographic factors function differently between the examined countries. The results show that the DKE could be found across grades three and four in all six countries. However, there are country-specific patterns regarding the relationship between performance, mathematics identity and perceived competence; the DKE; and how different demographic variables predict its occurrences in particular subpopulations.
A New Strategy for the Regulation of Neuroinflammation: Exosomes Derived from Mesenchymal Stem Cells
Authors: Ge Ying , Wu Jingjing , Zhang Li , Huang Nanqu , Luo Yong
Published: February 2024

Neuroinflammation is an important pathogenesis of neurological diseases and causes a series of physiopathological changes, such as abnormal activation of glial cells, neuronal degeneration and death, and disruption of the blood‒brain barrier. Therefore, modulating inflammation may be an important therapeutic tool for treating neurological diseases. Mesenchymal stem cells (MSCs), as pluripotent stem cells, have great therapeutic potential for neurological diseases due to their regenerative ability, immunity, and ability to regulate inflammation. However, recent studies have shown that MSC-derived exosomes (MSC-Exos) play a major role in this process and play a key role in neuroprotection by regulating neuroglia. This review summarizes the recent progress made in regulating neuroinflammation by focusing on the mechanisms by which MSC-Exos are involved in the regulation of glial cells through signaling pathways such as the TLR, NF-κB, MAPK, STAT, and NLRP3 pathways to provide some references for subsequent research and therapy.

Graphical Abstract

Exosomes derived from MSCs exhibit neuroprotective effects by regulating signaling pathways and mitigating neuroinflammation triggered by glial cells.
Mental imagery scaffolding: The effects of detail richness and text load on geography learning
Authors: Zhou Yun , Yi Fanqi , Dong Bingyu , Zhang Guangli , Zhang Yi , Xu Tao
Published: February 2024

The growing importance of 3D animations in current teaching approaches becomes increasingly apparent, offering an effective way to visualize complex spatial concepts and processes in geography learning through outstanding visual representation and details. However, the effects of detail richness and text load of 3D animation on learning about processes remain unclear. Addressing this research gap, the present study adopts a quasi-experimental design involving four classes (n = 106) in the context of a geography lesson and evaluates four conditions in a 2 × 2 between-subjects design consisting of detail richness (high vs. low) and text load (high vs. low). The lessons on the rotation and revolution of the Earth were delivered by the same instructor across all conditions. Knowledge acquisition, cognitive load, learning experience, and emotions of students were measured. The results revealed that students were significantly better able to acquire knowledge immediately when exposed to the high detailed visuals but low text load condition. Low detail richness and high text load independently resulted in increased cognitive load. We also observed a significant effect of detail richness on the dimensions of pleasure and arousal, with higher levels of details associated with larger values in these dimensions. This research suggests that when the learning objective necessitates the engagement of mental imagery, incorporating detailed visuals can facilitate learning. The findings contribute to our understanding of how detailed imagery is linked to learning objectives about processes and expand our knowledge regarding the design of detail richness and text of 3D animation in the context of geography learning.
A nose for trouble: ecotoxicological implications for climate change and disease in Saiga antelope (S. t. tatarica)
Authors: Mullineaux S. T. , McKinley J. M. , Marks N. J. , Doherty R. , Scantlebury D. M.
Published: February 2024

In recent decades, Saiga antelope (Saiga t. tatarica) mass die-offs have become more common. The mass die-off of 2015 in central Kazakhstan, recorded 140,000 individual deaths across multiple herds. Previously, research has shown atmospheric humidity, the bacterium Pasteurella multocida serotype B, and resultant haemorrhagic septicaemia, were the primary cause. However, other synergistic factors may have impacted this process. Here we use a multivariate compositional data analysis (CoDA) approach to assess what other factors may have been involved. We show a pollutant linkage mechanism where relative humidity and dewpoint temperature combine with environmental pollutants, potentially toxic elements (e.g., Hg, As), complex carbon compounds (e.g., Acetone, Toluene), and inorganic compounds (e.g., CHx, SO2) which affected the Saiga during the calving season (start and peak) and at the onset of the mass die-off. We suggest a mechanism for this process. Upon arrival at their carving grounds, the Saiga experienced a sudden precipitation event, a spike in temperatures, and resultant high humidity occurs. The infectious bacterium P. multocida serotype B then spreads. Further, environmental pollutants contained within steppe soils are released to the air, forming localised smog events, these synergistically combine, and mass die-off occurs.
The biochemical composition and its relation to color of Ulva spp. upon harvest time
Authors: Nissen Signe H. , Juul Louise , Bruhn Annette , Søndergaard Jens , Dalsgaard Trine K.
Published: February 2024

Green seaweed species of the genus Ulva are promising protein sources for food production. Various factors affect the biochemical composition of Ulva spp. (hereafter Ulva), which can complicate the utilization in a commercial scale food production. This study investigated the composition of Ulva harvested in 2021 in May (dark green/black biomass), June (light green biomass) and August (mixed colored biomass). The August harvest was divided into three different color codes: light green, green, and dark green/black, to explore a relation between color and composition as an indicator for biomass quality. The crude protein (CP) and ash contents were highest in the dark August biomass (16.4±0.4% and 35.9±3.0% of dry matter (DM), respectively) and in the dark biomass harvested in May (20.6±0.5% and 41.2±3.9% of DM, respectively). The light green Ulva harvested in June had a lower CP content (6.5±1.5% of DM) similarly to what was observed for light green biomass in August (7.7±0.1% of DM). The light green biomasses were found to have a higher nitrogen to amino acid (N-to-AA) conversion factor and proportion of essential amino acids (EAA). The lipid content ranged between 1.0-2.2±0.1-0.2% of DM for the different biomasses and a higher lipid content was related with a lighter biomass color. Phosphorus and potassium concentrations were highest in the green fraction, whereas the darker green/black biomass had higher contents of all other elements, including the toxic elements, arsenic and cadmium.

Graphical abstract
Sublimation enthalpies of organic compounds by isothermal thermogravimetry
Authors: Treviño-Kauffmann Marco Antonio , Esparza-Rivera Daniel , Rojas Aarón
Published: February 2024

An improved method has been developed to determine the sublimation enthalpies of solid organic compounds using thermogravimetric analysis and applying an isothermal methodology with a TA Instruments® SDTQ600 equipment. This was achieved by measuring the rate of mass loss as a function of the temperature from isothermal experiments in an interval of temperature of 10 to 20 K below the melting temperature of the sample. The resulting rates of mass loss were used by applying the Pieterse and Focke equation, then combined with the integrated Clausius–Clapeyron equation to calculate the heat of sublimation at the experimental temperature and it was corrected to T = 298.15 K. In order to demonstrate the reliability of this methodology, the results for benzoic acid, pyrene and phenanthrene are presented, which are respectively primary, secondary, and tertiary reference compounds in the measurement of enthalpies of sublimation, along with the sublimation enthalpies of picolinic acid, nicotinic acid and isonicotinic acid which are three pyridinecarboxylic acids isomers with the carboxyl group in the ortho, meta and para position, respectively, to the nitrogen of the pyridine.
A multi-scale approach to study palm-weevils in a tropical agroecosystem
Authors: Vásquez-Ordóñez Aymer Andrés , Torres-López Wilmar , Monmany-Garzia A. Carolina
Published: February 2024

Context

The recent phytosanitary crisis caused by the stem borer weevils Dynamis borassi and Rhynchophorus palmarum in peach palms (Bactris gasipaes) seriously affects the economy of rural families in Colombia. To understand the possible ecological mechanisms favoring the pest, the weevil-palm system needs to be studied from a multi-scale perspective.

Objectives

We evaluated the combined effects of agricultural management, landscape, topography, soil, and climate variables on infestation levels of peach palm caused by the weevils D. borassi and R. palmarum in the Colombian southwest to understand underlying ecological drivers of the current phytosanitary crisis.

Methods

The palm infestation levels (response variable) and local agronomic practices were recorded in 32 sites across Colombia's Pacific, Andes, and Amazon natural regions. For each peach palm crop, landscape variables were estimated from classified Sentinel-2 images, soil variables were extracted from the Soil Grids 250 m database, and climate variables were extracted from the CHIRPS and CHIRTS databases. Explanatory variables were analyzed using Generalized Linear Models and Partial Least Squares-Generalized Linear Models.

Results

Landscape variables, specifically the number and shape of non-forest patches, had a greater influence on peach palm infestation levels than other environmental variables, possibly related to the decrease in the density of Oenocarpus batatua, the natural palm host for D. borassi, leading it to switch to the peach palm.

Conclusions

A multi-scale approach of the weevil-palm interaction enabled us to identify an ecological mechanism that has not been proposed before. Our recommendation for families depending on peach palm is to design palm management with a landscape perspective that considers the conservation of alternative hosts for the weevils in agroforestal plots.
A double-bounded risk-risk trade-off analysis of heatwave-related mortality risk: Evidence from India
Authors: Chilton Susan , Duxbury Darren , Mussio Irene , Nielsen Jytte Seested , Sharma Smriti
Published: February 2024

As climate variability is increasing, extreme events such as temperature fluctuations are expected to become more frequent. Low- and middle-income countries (LMICs) are especially vulnerable to heat-related variability and its ensuing impacts on mortality. Therefore, there is an urgent need to understand how citizens in LMICs trade-off climate-related mortality risks with other risks such as traffic accidents, and what values they place on reducing such risks. As populations in LMICs are income-constrained, we adopt a non-monetary, risk-risk trade-off (RRTO) valuation method instead of the standard willingness-to-pay stated preference-based approach. We estimate the resulting risk premium for heatwave-related mortality risks through an adapted double-bounded, dichotomous choice approach to establish whether, on average, people value avoiding these risks more compared to reducing traffic risks. Using a sample of over 2,300 individuals from across seven states in India, a country with one of the highest heat-related mortality globally, we estimate the heatwave risk mortality premium to be between 2.2–2.9, indicating that on average, individuals weigh reducing heatwave-related mortality risks more than two times that of reducing traffic accident mortality risks. Based on a standard benefit transfer methodology for LMICs, this premium translates to a Value of Statistical Life (VSL) of USD 0.37–2.61 million for India.
Learning from different types of failure: evidence from non-severe and severe work accidents in SMEs
Authors: Lafuente Esteban
Published: February 2024

This paper investigates the learning patterns of small and medium-sized enterprises (SMEs) from heterogeneous work accidents (i.e., minor and severe and fatal accidents). Work safety cannot be overlooked, and the focus of this study on learning from failure allows to understand how SMEs match safety problems with solutions generated by past experience with work accidents and knowledge acquisition; while acknowledging that accident heterogeneity influences SMEs’ learning. The analysis uses a sample of 108 Spanish SMEs during 2006–2009. The results show that SMEs learn to modify safety practices, and that experience with both minor and severe and fatal accidents impact learning outcomes—measured as changes in the unit accident cost—through different mechanisms. Cumulative experience with past work accidents supports exploitative learning, but this effect was found only for minor accidents. Although the adoption of safety-enhancing tools (i.e., OHSAS 18001) does not affect learning, the findings reveal the value of ambidextrous learning: SMEs adopting the OHSAS 18001 learn more from severe and fatal accidents than from minor accidents by triggering drastic modifications in their safety practices.
The McNish and Lincoln Solar-Activity Predictions: The Method and Its Performance
Authors: Clette Frédéric , Jain Shantanu , Podladchikova Tatiana
Published: February 2024

The McNish and Lincoln (ML) method, introduced in 1949, was one of the first attempts to produce midterm forecasts of solar activity, up to 12 months ahead. However, it has been poorly described and evaluated in the past literature, in particular its actual operational implementation by NOAA. Here, we reconstruct the exact formulation of the method, as it was applied since the early 1970s, and we provide a full mathematical derivation of the prediction errors. For bench-marking the method, we also produce monthly predictions over the past 190 years, from 1833 (Cycle 8) to 2023 (Cycle 25), and develop statistics of the differences between the predictions and the observed 13-month smoothed sunspot-number (SSN) time series, according to the phase in the solar cycle. Our analysis shows that the ML method is heavily constrained because it is primarily based on the mean of all past cycles, which imposes a fixed amplitude and length and suffers from a temporal smearing that grows towards the end of the solar cycle. We find that predictions are completely unreliable in the first 12 months of the cycle, and over the last two years preceding the ending minimum (around 130 months), and beyond this minimum. By contrast, in the course of the cycle (months 18 to 65), ML predictions prove to be reliable over a time range of up to 50 months (4.2 years), thus much longer than the 12-month conventional range used so far. However, we find that predictions then suffer from systematic under-(over-)estimates for cycles that have a higher (lower) amplitude than the base mean cycle. Overall, we conclude that although the ML method provides valid prediction errors, it suffers from strong limitations, with very little room for improvement, as it indifferently merges all past cycles into a single fixed statistics.
Can Community Music Contribute to More Equitable Societies? A Critical Interpretive Synthesis
Authors: Bartleet Brydie-Leigh , Heard Emma
Published: February 2024

This article presents outcomes from a critical interpretive synthesis inquiry exploring whether community music can contribute to more equitable societies. Drawing on 74 cross-disciplinary articles, we identify equity-related outcomes across three key categories: outcomes to improve the immediate wellbeing and life trajectories for individuals experiencing disadvantage; outcomes relating to the development of skills, knowledge and understandings empowering individual participants to enact positive social change within their communities; and outcomes with the potential to affect the root causes of social inequity. This review provides a solid foundation for further conceptual and theoretical development within and beyond the fields of social justice research and community music. Our findings will also be helpful for translating the creative and cultural benefits that community music practice could bring to addressing social justice issues in a wide range of complex contexts.
Long-Term Evolution of the Saturnian System
Authors: Ćuk Matija , El Moutamid Maryame , Lari Giacomo , Neveu Marc , Nimmo Francis , Noyelles Benoît , Rhoden Alyssa , Saillenfest Melaine
Published: February 2024

Here we present the current state of knowledge on the long-term evolution of Saturn’s moon system due to tides within Saturn. First we provide some background on tidal evolution, orbital resonances and satellite tides. Then we address in detail some of the present and past orbital resonances between Saturn’s moons (including the Enceladus-Dione and Titan-Hyperion resonances) and what they can tell us about the evolution of the system. We also present the current state of knowledge on the spin-axis dynamics of Saturn: we discuss arguments for a (past or current) secular resonance of Saturn’s spin precession with planetary orbits, and explain the links of this resonance to the tidal evolution of Titan and a possible recent cataclysm in the Saturnian system. We also address how the moons’ orbital evolution, including resonances, affects the evolution of their interiors. Finally, we summarize the state of knowledge about the Saturnian system’s long-term evolution and discuss prospects for future progress.
Practical perceptual representations: a contemporary defense of an old idea
Authors: Springle Alison A. , Buccella Alessandra
Published: February 2024

According to ‘orthodox’ representationalism, perceptual states possess constitutive veridicality (truth, accuracy, or satisfaction) conditions. Typically, philosophers who deny orthodox representationalism endorse some variety of anti-representationalism. But we argue that these haven’t always been, and needn’t continue to be, the only options. Philosophers including Descartes, Malebranche and Helmholtz appear to have rejected orthodox representationalism while nonetheless endorsing perceptual representations of a fundamentally practical kind not captured by orthodox representationalism. Moreover, we argue that the perceptual science called on by contemporary philosophers to defend orthodox representationalism instead motivates a return to this older view, and we suggest that contemporary philosophers may conceptualize fundamentally practical perceptual representations as‘de agendo’representations, a species of representation that has constitutive appropriateness rather than veridicality conditions.
Bayesian Semiparametric Longitudinal Inverse-Probit Mixed Models for Category Learning
Authors: Mukhopadhyay Minerva , McHaney Jacie R. , Chandrasekaran Bharath , Sarkar Abhra
Published: February 2024

Understanding how the adult human brain learns novel categories is an important problem in neuroscience. Drift-diffusion models are popular in such contexts for their ability to mimic the underlying neural mechanisms. One such model for gradual longitudinal learning was recently developed in Paulon et al. (J Am Stat Assoc 116:1114–1127, 2021). In practice, category response accuracies are often the only reliable measure recorded by behavioral scientists to describe human learning. Category response accuracies are, however, often the only reliable measure recorded by behavioral scientists to describe human learning. To our knowledge, however, drift-diffusion models for such scenarios have never been considered in the literature before. To address this gap, in this article, we build carefully on Paulon et al. (J Am Stat Assoc 116:1114–1127, 2021), but now with latent response times integrated out, to derive a novel biologically interpretable class of ‘inverse-probit’ categorical probability models for observed categories alone. However, this new marginal model presents significant identifiability and inferential challenges not encountered originally for the joint model in Paulon et al. (J Am Stat Assoc 116:1114–1127, 2021). We address these new challenges using a novel projection-based approach with a symmetry-preserving identifiability constraint that allows us to work with conjugate priors in an unconstrained space. We adapt the model for group and individual-level inference in longitudinal settings. Building again on the model’s latent variable representation, we design an efficient Markov chain Monte Carlo algorithm for posterior computation. We evaluate the empirical performance of the method through simulation experiments. The practical efficacy of the method is illustrated in applications to longitudinal tone learning studies.
Evaluation of different QuEChERS-based methods for the extraction of 48 wastewater-derived organic contaminants from soil and lettuce root using high-resolution LC-QTOF with MRMHR and SWATH acquisition modes
Authors: Montemurro Nicola , Manasfi Rayana , Chiron Serge , Perez Sandra
Published: February 2024

The reuse of treated wastewater in agriculture is an important route of introducing a large number of organic contaminants into the agroecosystem. In this study, a modified QuEChERS-based approach was developed for rapid, simple, and simultaneous extraction of 48 organic wastewater-derived contaminants from soil and lettuce root. Twenty-two different (modification) scenarios of the known (or original) QuEChERS method have been tested, in order to obtain best and well-compromised recoveries for all target compounds for soil and roots. Finally, a common method was chosen for both matrices consisting of a single extraction step using EDTA-Mcllvaine buffer and the unbuffered Original QuEChERS salts. Method performance was accomplished by liquid chromatography coupled with high-resolution mass spectrometry on a QToF-MS system using two different acquisition modes, the ultra-fast high-resolution multiple reaction monitoring (MRMHR) mode and the innovative Sequential Window Acquisition of All Theoretical Fragment-Ion (SWATH) mode. Performance characterization was evaluated in terms of recovery, linearity, intra-day precision, method detection limits (MDLs), method quantification limits (MQLs), and matrix effect (ME). Recoveries in MRMHR mode ranged from 63 to 111% and 54 to 104% for lettuce root and soil, respectively, for most of compounds in MRMHR mode and from 56 to 121% and 54 to 104% for lettuce root and soil, respectively, for most of compounds in SWATH. Whereas, MQLs ranged from 0.03 to 0.92 ng g−1 in MRMHR and from 0.03 to 82 ng g−1 in SWATH for lettuce root, and from 0.02 to 0.44 ng g−1 in MRMHR and 0.02 to 0.14 ng g−1 in SWATH for soil. The method was then applied to follow the target compounds in soil and lettuce root, where the system lettuce-soil was irrigated with treated wastewater under real greenhouse conditions. Five and 17 compounds were detected in lettuce root and soil, respectively.

Graphical Abstract
Prediction of antenatal bleeding and preterm deliveries using placental magnetic resonance imaging in patients with placenta previa
Authors: Otake Yuko , Ugajin Atsushi , Takahashi Hironori , Tanaka Yuya , Fujii Hiroyuki , Matsuki Mitsuru , Mori Harushi
Published: February 2024

Purpose

This study aimed to clarify associations between subacute hematoma on placental magnetic resonance imaging (MRI), antenatal bleeding, and preterm deliveries in patients with placenta previa (PP) without placenta accreta spectrum (PAS).

Materials and methods

This retrospective study investigated 78 consecutive patients with PP (median age, 34.5 years; interquartile range [IQR], 31–37 years) who underwent placental MRI in the third trimester. Patients with PAS detected intraoperatively or pathologically were excluded. Two radiologists evaluated the presence of subacute hematomas and their locations on placental MRI. We examined associations between presence of subacute hematoma and antenatal bleeding, emergency cesarean section (CS), hysterectomy, gestational age (GA) at delivery, birth weight, and amount of blood loss at CS. We also examined the association between perinatal outcome and subacute hematoma location: marginal, retro-placental, or intra-placental. Inter-observer agreement for the detection of subacute hematoma was calculated using kappa analysis.

Results

Subacute hematomas were identified on MRI in 39 of the 78 patients (50.0%). Antenatal bleeding and emergency CS were more prevalent in patients with subacute hematoma on MRI (20 patients [51.3%] and 18 patients [46.2%], respectively) than in patients without (7 patients [17.9%], Fisher’s exact test, p = 0.004 and 7 patients [17.9%], p = 0.014, respectively). GA at delivery was significantly lower in patients with subacute hematoma (median 36w3d, IQR 35w4d–37w1d) than in patients without (median 37w1d, IQR 36w4d–37w2d; Mann–Whitney test: p = 0.048). Marginal hematoma was significantly associated with antenatal bleeding and emergency CS. Inter-observer agreement for the presence of subacute hematoma was moderate (κ = 0.573).

Conclusion

Subacute hematoma on placental MRI was associated with antenatal bleeding, emergency CS and shorter GA at delivery in patients with PP. Marginal hematoma was also associated with antenatal bleeding and emergency CS. Placental MRI appears useful for predicting antenatal bleeding and preterm delivery in patients with PP.
Factors that influence the extraction methods of terpenes from natural sources
Authors: González-Hernández Ricardo A. , Valdez-Cruz Norma A. , Trujillo-Roldán Mauricio A.
Published: February 2024

Due to their various applications, terpenes and terpenoids are secondary metabolites of industrial interest. These compounds can be found in a wide variety of organisms from virtually all biological kingdoms. However, it has been identified that various factors in the production process, such as the place and time of harvest, pretreatments, extraction, and purification, generate differences in the profile of terpenes and terpenoids that can be obtained from organisms. The first factor that influences the extraction of compounds is drying since an inappropriate choice of the drying method can lead to the loss of the compounds of interest or the appearance of others that arise due to the decomposition of the original molecules. Similarly, Soxhlet extraction is the most used method in the recovery of terpenoids due to its high extraction efficiency. However, unconventional extraction methods have proven to be effective alternatives for terpenoid recovery, particularly the use of microwave and high-pressure extraction, as well as the use of unconventional solvents, achieving extraction efficiencies equal to or greater than Soxhlet in shorter times. This review will address the differences observed in the extraction of terpenoids and the main factors that cause them, as well as a comparison of the advantages and disadvantages of the various methodologies for drying, extraction, and separation of these compounds.
Harnessing the Potential of Real-World Evidence in the Treatment of Colorectal Cancer: Where Do We Stand?
Authors: van Nassau Sietske C. M. W. , Bol Guus M. , van der Baan Frederieke H. , Roodhart Jeanine M. L. , Vink Geraldine R. , Punt Cornelis J. A. , May Anne M. , Koopman Miriam , Derksen Jeroen W. G.
Published: February 2024

Opinion statement

Treatment guidelines for colorectal cancer (CRC) are primarily based on the results of randomized clinical trials (RCTs), the gold standard methodology to evaluate safety and efficacy of oncological treatments. However, generalizability of trial results is often limited due to stringent eligibility criteria, underrepresentation of specific populations, and more heterogeneity in clinical practice. This may result in an efficacy-effectiveness gap and uncertainty regarding meaningful benefit versus treatment harm. Meanwhile, conduct of traditional RCTs has become increasingly challenging due to identification of a growing number of (small) molecular subtypes. These challenges—combined with the digitalization of health records—have led to growing interest in use of real-world data (RWD) to complement evidence from RCTs. RWD is used to evaluate epidemiological trends, quality of care, treatment effectiveness, long-term (rare) safety, and quality of life (QoL) measures. In addition, RWD is increasingly considered in decision-making by clinicians, regulators, and payers. In this narrative review, we elaborate on these applications in CRC, and provide illustrative examples. As long as the quality of RWD is safeguarded, ongoing developments, such as common data models, federated learning, and predictive modelling, will further unfold its potential. First, whenever possible, we recommend conducting pragmatic trials, such as registry-based RCTs, to optimize generalizability and answer clinical questions that are not addressed in registrational trials. Second, we argue that marketing approval should be conditional for patients who would have been ineligible for the registrational trial, awaiting planned (non) randomized evaluation of outcomes in the real world. Third, high-quality effectiveness results should be incorporated in treatment guidelines to aid in patient counseling. We believe that a coordinated effort from all stakeholders is essential to improve the quality of RWD, create a learning healthcare system with optimal use of trials and real-world evidence (RWE), and ultimately ensure personalized care for every CRC patient.
Effect of Osteoporosis Treatments on Osteoarthritis Progression in Postmenopausal Women: A Review of the Literature
Authors: Ho Wang-Chun , Chang Chung-Chih , Wu Wen-Tien , Lee Ru-Ping , Yao Ting-Kuo , Peng Cheng-Huan , Yeh Kuang-Ting
Published: February 2024

Purpose of Review

The purpose of this literature review was to determine if medications used to treat osteoporosis are also effective for treating osteoarthritis (OA).

Recent Findings

A total of 40 relevant articles were identified. Studies were categorized into those (1) discussing estrogen and selective estrogen receptor modulators (SERMs), (2) bisphosphonates, (3) parathyroid hormone (PTH) analogs, and (4) denosumab, and (5) prior review articles. A large amount of evidence suggests that estrogen and SERMs are effective at reducing OA symptoms and disease progression. Evidence suggests that bisphosphonates, the most common medications used to treat osteoporosis, can reduce OA symptoms and disease progression. In vivo studies suggest that PTH analogs may improve the cartilage destruction associated with OA; however, few human trials have examined its use for OA. Denosumab is approved to treat osteoporosis, bone metastases, and certain types of breast cancer, but little study has been done with respect to its effect on OA.

The current evidence indicates that medications used to treat osteoporosis are also effective for treating OA. Estrogen, SERMs, and bisphosphonates have the most potential as OA therapies. Less is known regarding the effectiveness of PTH analogs and denosumab in OA, and more research is needed.
Nervous System Response to Neurotrauma: A Narrative Review of Cerebrovascular and Cellular Changes After Neurotrauma
Authors: Ali Hossam Tharwat , Sula Idris , AbuHamdia Abrar , Elejla Sewar A. , Elrefaey Ahmed , Hamdar Hiba , Elfil Mohamed
Published: February 2024

Neurotrauma is a significant cause of morbidity and mortality worldwide. For instance, traumatic brain injury (TBI) causes more than 30% of all injury-related deaths in the USA annually. The underlying cause and clinical sequela vary among cases. Patients are liable to both acute and chronic changes in the nervous system after such a type of injury. Cerebrovascular disruption has the most common and serious effect in such cases because cerebrovascular autoregulation, which is one of the main determinants of cerebral perfusion pressure, can be effaced in brain injuries even in the absence of evident vascular injury. Disruption of the blood–brain barrier regulatory function may also ensue whether due to direct injury to its structure or metabolic changes. Furthermore, the autonomic nervous system (ANS) can be affected leading to sympathetic hyperactivity in many patients. On a cellular scale, the neuroinflammatory cascade medicated by the glial cells gets triggered in response to TBI. Nevertheless, cellular and molecular reactions involved in cerebrovascular repair are not fully understood yet. Most studies were done on animals with many drawbacks in interpreting results. Therefore, future studies including human subjects are necessarily needed. This review will be of relevance to clinicians and researchers interested in understanding the underlying mechanisms in neurotrauma cases and the development of proper therapies as well as those with a general interest in the neurotrauma field.
Analysis on a nonlinear fractional differential equations in a bounded domain $$[1,\mathcal {T}]$$
Authors: Awadalla Muath , Buvaneswari K. , Karthikeyan P. , Hannabou Mohamed , Karthikeyan K. , AlAdsani Feryal , Alahmadi Jihan
Published: February 2024

In this manuscript, based on the most widespread fixed point theories in literature. The existence of solutions to the system of nonlinear fractional differential equations with Caputo Hadmard fractional operator in a bounded domain is verified by using Mönoch’s fixed point theorem, The stability of the coupled system is also investigated via Ulam-Hyer technique. Finally, an applied numerical example is presented to illustrate the theoretical results obtained.
On the analysis of fractional calculus operators with bivariate Mittag Leffler function in the kernel
Authors: Elidemir İlkay Onbaşı , Özarslan Mehmet Ali , Buranay Suzan Cival
Published: February 2024

Bivariate Mittag-Leffler (ML) functions are a substantial generalization of the univariate ML functions, which are widely recognized for their significance in fractional calculus. In the present paper, our initial focus is to investigate the fractional calculus properties of the integral and derivative operators with kernels including the Bivariate ML functions. Further, certain fractional Cauchy-type problems including these operators are considered. Also the numerical approximations of the Caputo type derivative operator are investigated. The theoretical results are justified by applications on examples. Furthermore, the theory of applying the same operators with respect to arbitrary monotonic functions is analyzed in this research.
Controlled-environment agriculture for an urbanised world? A comparative analysis of the innovation systems in London, Nairobi and Singapore
Authors: Dietze Victoria , Alhashemi Amna , Feindt Peter H.
Published: February 2024

Multiple crises and challenges in the food sector are driving a rising need for innovative food production methods that could provide a growing urban population with high-quality, sustainable and healthy food while strengthening the resilience of food systems. Controlled-environment agriculture (CEA) in urban areas has been proposed as one possible pathway to address these demands. Despite its various potential benefits, CEA is still in a conceptual or experimental stage and there has been less research that focuses on the specificities of urban areas where it could be implemented. Using the Urban Food Production Innovation System (UFoPrInS) concept, this paper analyses the urban contexts and enabling and impeding factors for implementing CEA in three contrasting locations: London, Nairobi and Singapore. Based on document analysis and semi-structured expert interviews, our findings show that Singapore is a favourable location because public policies support the implementation of CEA to reduce food import dependency and enhance the resilience of food supply. In London, high food import dependency is increasingly seen as problematic, but the implementation of CEA has been hampered by other policy priorities. In Nairobi, where over half of the population lives in informal settlements without adequate food, water and sanitation, CEA is unlikely to make an economically efficient contribution to food security. We conclude that the implementation of CEA might be suitable in locations with ample capital and knowledge, stable political, social, and infrastructure conditions, and limited space, where value can be linked to hospitality and tourism, supported by positive pricing for resource savings.
Implicit quiescent optical solitons For Lakshmanan–Porsezian–Daniel model having nonlinear chromatic dispersion and power-law of self-phase modulation by lie symmetry
Authors: Adem Abdullahi Rashid , Biswas Anjan , Yıldırım Yakup , Alshomrani Ali Saleh
Published: February 2024

This paper recovers implicit quiescent optical solitons for the Lakshmanan–Porsezian–Daniel equation that is studied with nonlinear chromatic dispersion and power-law of self-phase modulation. The Lie symmetry analysis has made this retrieval possible. An interesting observation has been made with the results that was not recoverable from the prequel paper.
The Incalculability of the Generated Text
Authors: Kuchtová Alžbeta
Published: February 2024

In this paper, I explore Derrida’s concept of exteriorization in relation to texts generated by machine learning. I first discuss Heidegger’s view of machine creation and then present Derrida’s criticism of Heidegger. I explain the concept of iterability, which is the central notion on which Derrida’s criticism is based. The thesis defended in the paper is that Derrida’s account of iterability provides a helpful framework for understanding the phenomenon of machine learning–generated literature. His account of textuality highlights the incalculability and mechanical elements characteristic of all texts, including machine-generated texts. By applying Derrida’s concept to the phenomenon of machine creation, we can deconstruct the distinction between human and non-human creation. As I propose in the conclusion to this paper, this provides a basis on which to consider potential positive uses of machine learning.