bluuebunny/crossref_metadata_2025 huggingface dataset:
Sleeve gastrectomy with antral resection provides more effective weight loss in patients with super obesity
Authors: Hamantepe Ahmet Tarik , Gönüllü Emre , Fırtına Gizem , İlhan Onur , Yüksel Adem , Karaman Kerem
Published: January 2025

Background

Obesity is a growing health issue that contributes to numerous diseases and lowers quality of life. In patients with super obesity (BMI > 50 kg/m²), bariatric surgery, particularly laparoscopic sleeve gastrectomy (LSG), is a common treatment option. However, the role of antral resection (AR) in LSG remains unclear, especially in this high-risk population. This study aims to compare the effectiveness of LSG with antral resection (LSG-AR) and LSG with antrum preservation (LSG-AP) on weight loss and postoperative complaints in patients with super obesity.

Methods

The medical records of patients with a BMI > 50 kg/m² who underwent LSG between 2016 and 2022 were retrospectively reviewed. Weight data were collected at admission, and at the first, second, and fifth-year follow-up. Patients were divided into two groups based on LSG-AR or LSG-AP procedures.

Results

Seventy-two patients were included. No significant difference was found in postoperative vomiting complaints between the groups (p = 0.67). First-year outcomes showed no significant differences in weight, BMI, or % Total Weight Loss (%TWL). However, second and fifth-year %TWL values were significantly higher in the LSG-AR group (p = 0.003 for both).

Conclusion

LSG-AR provides more effective long-term weight loss in patients with super obesity. Early postoperative vomiting complaints diminish over time, suggesting LSG-AR as a viable one-stage procedure for this patient population.
Guarding Polyominoes Under k-Hop Visibility
Authors: Filtser Omrit , Krohn Erik , Nilsson Bengt J. , Rieck Christian , Schmidt Christiane
Published: January 2025

We study the Art Gallery Problem under k-hop visibility in polyominoes. In this visibility model, two unit squares of a polyomino can see each other if and only if the shortest path between the respective vertices in the dual graph of the polyomino has length at most k. In this paper, we show that the VC dimension of this problem is 3 in simple polyominoes, and 4 in polyominoes with holes. Furthermore, we provide a reduction from Planar Monotone 3Sat, thereby showing that the problem is -complete even in thin polyominoes (i.e., polyominoes that do not a contain a $$2\times 2$$

2
×
2

block of cells). Complementarily, we present a linear-time 4-approximation algorithm for simple 2-thin polyominoes (which do not contain a $$3\times 3$$

3
×
3

block of cells) for all $$k\in {\mathbb {N}}$$

k
∈
N

.
Endoscopic third ventriculostomy for hydrocephalus accompanied by dural arteriovenous fistulae: a case report and literature review
Authors: Wajima Daisuke , Kamide Tomoya , Sasagawa Yasuo , Takata Sho , Misaki Kouichi , Nakada Mitsutoshi
Published: January 2025

A 54-year-old man presented with gait disturbances, urinary incontinence, and headache for 6 months. Head computed tomography indicated several high-density mass lesions in the quadrigeminal cistern, causing occlusive hydrocephalus. Digital subtraction angiography confirmed tentorial dural arteriovenous fistulae (AVF). Transarterial embolization (TAE) achieved complete angiographic resolution. However, acute occlusive hydrocephalus worsened, necessitating endoscopic third ventriculostomy (ETV). The patient was discharged without new symptoms and no hydrocephalus recurrence at six-month follow-up. Hydrocephalus is rare in patients with dural AVF and mostly resolves spontaneously after treatment; however, if thrombosis and enlargement of the varix occur after treatment, acute occlusive hydrocephalus can develop.
The anatomy and histology of the midgut and Malpighian tubules of Copris felschei Reitter, 1892 (Coleoptera: Scarabaeidae)
Authors: Özyurt Koçakoğlu Nurcan , Ersoy Doğan Erhan , Arslan Hicret , Candan Selami
Published: January 2025

Copris are part of the Scarabaeidae family of Coleoptera. Copris are dung beetles or coprophagous beetles. These insects are called tunnelers because they excavate channels in the substrate. They use dead organisms and non-living organic compounds as a nutrient source. By breaking down dead matter, they provide nutrients that are important to the environment and necessary for the survival of other organisms. No studies have yet examined the midgut structure and Malpighian tubules of Copris. Therefore, this study investigated the histo-anatomical structure of the midgut and Malpighian tubules of Copris felschei Reitter, 1892 (Coleoptera: Scarabaeidae) using light and scanning electron microscopy (SEM) in detail. The midgut of C. felschei represents the largest part of the alimentary canal. Muscle layers and a monolayer of cylindrical epithelium surround the midgut wall. A peritrophic membrane envelops food in the midgut lumen, and crystals were observed within the lumen. The surface of the midgut has regenerative crypts and tracheae. The Malpighian tubules are arranged in two pairs and connect proximally between the midgut and hindgut. The Malpighian tubules are composed of a single layer of cuboidal epithelium. Numerous balloon-like tracheae were observed interspersed between the midgut and Malpighian tubules. Light and SEM images of the tracheae reveal a spongy structure with hollow chambers. These findings are anticipated to advance future research and deepen our understanding of the alimentary canal in Coleoptera, particularly within the Scarabaeidae family.
Beyond traditional prognostics: integrating RAG-enhanced AtlasGPT and ChatGPT 4.0 into aneurysmal subarachnoid hemorrhage outcome prediction
Authors: Basaran Alim Emre , Güresir Agi , Knoch Hanna , Vychopen Martin , Güresir Erdem , Wach Johannes
Published: January 2025

To assess the predictive accuracy of advanced AI language models and established clinical scales in prognosticating outcomes for patients with aneurysmal subarachnoid hemorrhage (aSAH). This retrospective cohort study included 82 patients suffering from aSAH. We evaluated the predictive efficacy of AtlasGPT and ChatGPT 4.0 by examining the area under the curve (AUC), sensitivity, specificity, and Youden’s Index, in comparison to established clinical grading scales such as the World Federation of Neurological Surgeons (WFNS) scale, Simplified Endovascular Brain Edema Score (SEBES), and Fisher scale. This assessment focused on four endpoints: in-hospital mortality, need for decompressive hemicraniectomy, and functional outcomes at discharge and after 6-month follow-up. In-hospital mortality occurred in 22% of the cohort, and 34.1% required decompressive hemicraniectomy during treatment. At hospital discharge, 28% of patients exhibited a favorable outcome (mRS ≤ 2), which improved to 46.9% at the 6-month follow-up. Prognostication utilizing the WFNS grading scale for 30-day in-hospital survival revealed an AUC of 0.72 with 59.4% sensitivity and 83.3% specificity. AtlasGPT provided the highest diagnostic accuracy (AUC 0.80, 95% CI: 0.70–0.91) for predicting the need for decompressive hemicraniectomy, with 82.1% sensitivity and 77.8% specificity. Similarly, for discharge outcomes, the WFNS score and AtlasGPT demonstrated high prognostic values with AUCs of 0.74 and 0.75, respectively. Long-term functional outcome predictions were best indicated by the WFNS scale, with an AUC of 0.76. The study demonstrates the potential of integrating AI models such as AtlasGPT with clinical scales to enhance outcome prediction in aSAH patients. While established scales like WFNS remain reliable, AI language models show promise, particularly in predicting the necessity for surgical intervention and short-term functional outcomes. The study explored the use of advanced AI language models, AtlasGPT and ChatGPT 4.0, to predict outcomes for patients with aneurysmal subarachnoid hemorrhage (aSAH). It found that AtlasGPT provided the highest diagnostic accuracy for predicting the need for decompressive hemicraniectomy, outperforming traditional clinical scales, while both AI models showed promise in enhancing outcome predictions when integrated with established clinical assessment tools.
Phenacoscorpius trispinis, a new species of scorpionfish (Teleostei: Scorpaenidae) from Sagami Bay, Japan
Authors: Matsumoto Tatsuya , Motomura Hiroyuki
Published: January 2025

Phenacoscorpius trispinis (Teleostei: Scorpaenidae), a new species of scorpionfish is described from Sagami Bay, Japan. The new species is characterized by the following combination of characteristics: pectoral-fin rays 16 or 17, middle rays branched; pored lateral-line scales 4; upper gill rakers 6, lower gill rakers 14 (10 and 4 on ceratobranchial and hypobranchial, respectively), total gill rakers 20; no slit behind last gill arch; palatine teeth absent; anterodorsal and lateral lacrimal spines present; second preopercular spine smaller than third or fourth spines; nuchal and parietal spines distinct; head length 45.2% of SL (standard length); body depth 38.1% of SL; head width 17.2% of SL; snout length 11.2% of SL; maxillary depth 7.6% of SL; postorbital length 21.2% of SL; first dorsal-fin spine length 6.8% of SL; second dorsal-fin spine length 13.6% of SL; pelvic-fin spine length 19.9% of SL; longest pelvic-fin ray 23.2% of SL; longest pectoral-fin ray 39.0% of SL; caudal-fin length 25.3% of SL; caudal-peduncle length 17.2% of SL. A molecular genetic analysis based on the mitochondrial marker Cytochrome c oxidase subunit I showed that the new species formed a clade distinct from congeneric species. New standard Japanese names are proposed for both the genus Phenacoscorpius and the new species.
Captive-introduced tortoises in wild populations: can we identify them by shell morphology?
Authors: Semaha Mohamed Jaouhar , Rodríguez-Caro Roberto C. , Giménez Andrés , Fahd Soumia , Graciá Eva
Published: January 2025

Direct exploitation and wildlife trade pose significant threats to global biodiversity, particularly impacting reptiles, such as tortoises, which are highly vulnerable. Moreover, the releases of captive-held animals into the wild can lead to potential negative consequences, including genetic introgression, disease transmission, and parasite spread. Therefore, diagnostic assessments are essential to evaluate the impact of release practices. In this study, we analyzed the shell morphology of Testudo graeca tortoises to assess the effectiveness of morphological analysis in identifying captive-introduced tortoises and quantifying tortoise releases in SE Spain. Despite being illegal, the cultural tradition of keeping and breeding tortoises at home persists in this region. Principal component analyses identified significant morphological differences between captive and wild tortoises. Captive tortoises generally exhibited larger shell sizes and greater morphological variability compared to wild tortoises. Accordingly, linear discriminant analyses accurately identified approximately 99% of wild tortoises, but the identification of captive tortoises was only 50% accurate because some captive tortoises show shell morphologies identical to wild ones. These results likely reflect the diverse origins and growth conditions of captive tortoises. Although this is likely an underestimation, our approach classified 7% of 125 wildlife tortoises across 13 natural sites such as captive-introduced tortoises. These findings highlight the potential impact of tortoise releases in wild populations and underscore the value of morphological analyses as an initial tool for diagnosing such impacts. Furthermore, integrating genetic and isotopic methods could further enhance the precision of these assessments.
Forecasting China’s Short-Term Energy Futures Price Using a Novel Secondary Decomposition-Optimized System
Authors: Jiang Zhe , Zhang Zili , Zhang Lin
Published: January 2025

Energy futures price forecasting is challenging due to the nonlinear and fluctuant characteristics. Existing literature mainly uses decomposition and ensemble method which neglects the intrinsic mode function obtained by the first decomposition could be irregular and thus reduces the prediction accuracy. To fill the research gap, a novel secondary decomposition-optimized-KELM-ensemble forecasting system is proposed to perform short-term forecasting in this study, which synthesizes two-stage data decomposition method, Sparrow search optimization algorithm, and extreme learning machine with kernel. We test the method with two energy futures prices in China, demonstrating that both one-day and three-day ahead forecasting results obtained are more accurate and stable compared to existing models in the literature, such as BPNN (improved by 58.42% on one-day ahead and 56.44% on three-day ahead by MAE) and KELM (improved by 56.40% on one-day ahead and 49.04% on three-day ahead by MAE). Therefore, the forecasting system introduced in this paper can provide useful implications for both policy makers and financial practitioners in the energy sector.
Evaluation of Wildland Fire Detection Methods Using Expert Input
Authors: Björck Johan , McNamee Margaret
Published: January 2025

Recently the Intergovernmental Panel on Climate Change released their 6th Assessment reports which confirm that the impact of climate change is visible, e.g. through an increased weather volatility leading both to hotter drier weather and increased flooding in some regions globally. One clear example of this is the increased prevalence of wildfires in recent years and increasing wildfire potential in the future in some regions. Sweden is in the northern most part of Europe and has the highest forest density in the European Union. In total, nearly 17 percent of all forests in Europe are located in Sweden. Even in a global sense, Sweden has extensive forestry, and provides 10 percent of the sawn timber, pulp and paper that is traded on the global market. Given these preconditions, in 2020 the Swedish Civil Contingencies Agency (MSB) identified the need to investigate the conditions for current and possible future detection methods for wildfires in Sweden. An overview of common current methods was made and review of these methods was conducted through interviews with national experts. The expert evaluation indicated an opportunity to build wildfire detection in Sweden based on weather radar, radar/satellite combinations, and/or airborne radar. The development of such detection systems could repurpose existing infrastructure and reduce the overall investment needs, implying that Sweden could adopt such methods rapidly provided there is sufficient political will. The methodology shows the advantage of using expert input to identify appropriate technical measures for further research investments given limited resources.
Effect of Probiotics on the Symptomatology of Autism Spectrum Disorder and/or Attention Deficit/Hyperactivity Disorder in Children and Adolescents: Pilot Study
Authors: Rojo-Marticella Meritxell , Arija Victoria , Canals-Sans Josefa
Published: January 2025

The aim of this study is to investigate the impact of using probiotics with strains related to dopamine and gamma-aminobutyric acid production on clinical features of autism spectrum disorder (ASD) and/or attention deficit/hyperactivity disorder (ADHD). This randomized, controlled trial involved 38 children with ADHD and 42 children with ASD, aged 5–16 years, who received probiotics (Lactiplantibacillus plantarum and Levilactobacillus brevis 109/cfu/daily) or placebo for 12 weeks. Parent-reported symptoms were assessed using Conners' 3rd-Ed and the Social Responsiveness Scale Test, 2nd-Ed (SRS-2), and children completed the Conners Continuous Performance Test, 3rd-Ed (CPT 3) or Conners Kiddie CPT, 2nd-Ed (K-CPT 2). Executive functions, quality of life and sleep patterns were also parent-assessed. Intention-to-treat analyses, controlling for sociodemographic and nutritional covariates, revealed no significant inter-group differences in parent-reported or neuropsychological data after the probiotic intervention. However, age-stratified analyses showed improved hyperactivity-impulsivity symptoms in younger children with ASD (Cohen’s d = 1.245) and ADHD (Cohen’s d = 0.692). Intra-group analyses supported these findings in the aforementioned age and intervention group for both diagnoses. An improvement in impulsivity for children with ASD was also observed in the intra-group analysis of the CPT commissions scores (probiotic: p = 0.001, Cohen’s d = -1.216; placebo: p = 0.013, Cohen’s d = -0.721). A better comfort score (quality of life) was shown in children with ASD (probiotic: p = 0.010, Cohen’s d = 0.722; placebo: p = 0.099, Cohen’s d = 0.456). The probiotics used, may improve hyperactivity-impulsivity in children with ASD or/and ADHD and quality of life in children with ASD. Further research is warranted to explore probiotics as an adjunctive therapeutic intervention for NDs.

Trial registration: clinicaltrials.gov Identifier: NCT05167110.
Consumption Trends, Trading Patterns and Economic Development in Italy Across Centuries: Data Analysis of Roman Amphorae in a Long-Term Perspective
Authors: Komar Paulina , Brughmans Tom , Borisova Ekaterina
Published: January 2025

This paper presents novel insights into the long-term chronological patterns related to the distribution and consumption of amphora-borne foodstuffs in Italy. The study specifically focuses on the consumption of wine, olive oil and fish sauces, which exhibit diverse provenances. Notably, it contributes significantly to our understanding of the Roman economy by utilising an open dataset and a replicable research method. The analysis reveals a pronounced growth pattern during the late Republican to early Imperial period. Importantly, quantitative evidence demonstrates that the diverse consumption pattern observed in the capital city of Rome is less exceptional than previously believed. The study draws upon a substantial dataset comprising 28,851 diagnostic amphora fragments excavated and documented from 28 different urban and rural settlements in the North Adriatic and Central Italy, spanning the period from the 4th c. BCE to the 7th c. CE. The analytical approach employs a probabilistic aoristic method, evenly distributing amphora frequencies across relevant date ranges.
Optimized workflow with hybrid (very) high-power short-duration radiofrequency ablation renders point-by-point pulmonary vein isolation as fast and effective as cryoballoon ablation
Authors: Fusaroli Marco , Hoogendijk Mark G. , Bhagwandien Rohit E. , Wijchers Sip A. , van Boven Nick , Mahmoodi Bakthawar K. , Yap Sing-Chien
Published: January 2025

Introduction

A hybrid approach with very high-power short-duration (vHPSD) posteriorly and ablation-index guided HPSD (50 W) anteriorly seems to be an optimal balance between efficiency and effectiveness for point-by-point pulmonary vein isolation (PVI). The aim of the current study is to compare vHPSD/HPSD ablation to cryoballoon ablation (CBA) in patients with symptomatic atrial fibrillation (AF).

Methods and results

In this retrospective single-center study, we identified 110 consecutive patients who underwent their first PVI with either vHPSD/HPSD (n = 54) or CBA (n = 56). We compared procedural efficacy, efficiency, safety, and long-term outcomes. Baseline characteristics of both groups were comparable; however, patients in the vHPSD/HPSD group had larger left atrial volume index (35, IQR 27–45 vs. 28, IQR 21–36 ml/m2, P = 0.005). Complete PVI was achieved in all patients except two CBA cases (100% vs. 96.4%, P = 0.50). First-pass isolation rate was 79.6% in the hybrid group. Procedure times were similar between groups (53, IQR 47–63 vs. 55, IQR 49–65 min, P = 0.35), but fluoroscopy time was shorter in the vHPSD/HPSD group (3.9 [2.7, 5.6] vs. 11.9 [9.3, 14.9] min, P < 0.001). There were 3 temporary phrenic nerve palsies (5.4%) in the CBA group which resolved within 1 year. The 1-year freedom from any atrial tachyarrhythmias after a single procedure was similar between groups (68.5% vs. 73.2%, P = 0.56). During repeat procedure, the durability of PVI was comparable.

Conclusions

The use of vHPSD/HPSD ablation renders point-by-point PVI as fast and effective as CBA. Furthermore, it has lower radiation exposure compared to CBA.

Graphical abstract
A Comparative Study of Rapidly-exploring Random Tree Algorithms Applied to Ship Trajectory Planning and Behavior Generation
Authors: Tengesdal Trym , Pedersen Tom Arne , Johansen Tor Arne
Published: January 2025

Rapidly Exploring Random Tree (RRT) algorithms, notably used for nonholonomic vehicle navigation in complex environments, are often not thoroughly evaluated for their specific challenges. This paper presents a first such comparison study of the variants Potential-Quick RRT* (PQ-RRT*), Informed RRT* (IRRT*), RRT*, and RRT, in maritime single-query nonholonomic motion planning. Additionally, the practicalities of using these algorithms in maritime environments are discussed and outlined. We also contend that these algorithms are beneficial not only for trajectory planning in Collision Avoidance Systems (CAS) but also for CAS verification when used as vessel behavior generators. Optimal RRT variants tend to produce more distance-optimal paths but require more computational time due to complex tree wiring and nearest neighbor searches. Our findings, supported by Welch’s t-test at a significance level of $$\alpha =0.05$$

α
=
0.05

, indicate that PQ-RRT* slightly outperform IRRT* and RRT* in achieving shorter trajectory length but at the expense of higher tuning complexity and longer run-times. Based on the results, we argue that these RRT algorithms are better suited for smaller-scale problems or environments with low obstacle congestion ratio. This is attributed to the curse of dimensionality, and trade-off with available memory and computational resources.
LiDAR Loop Closure Detection using Semantic Graphs with Graph Attention Networks
Authors: Yang Liudi , Mascaro Ruben , Alzugaray Ignacio , Prakhya Sai Manoj , Karrer Marco , Liu Ziyuan , Chli Margarita
Published: January 2025

In this paper, we propose a novel loop closure detection algorithm that uses graph attention neural networks to encode semantic graphs to perform place recognition and then use semantic registration to estimate the 6 DoF relative pose constraint. Our place recognition algorithm has two key modules, namely, a semantic graph encoder module and a graph comparison module. The semantic graph encoder employs graph attention networks to efficiently encode spatial, semantic and geometric information from the semantic graph of the input point cloud. We then use self-attention mechanism in both node-embedding and graph-embedding steps to create distinctive graph vectors. The graph vectors of the current scan and a keyframe scan are then compared in the graph comparison module to identify a possible loop closure. Specifically, employing the difference of the two graph vectors showed a significant improvement in performance, as shown in ablation studies. Lastly, we implemented a semantic registration algorithm that takes in loop closure candidate scans and estimates the relative 6 DoF pose constraint for the LiDAR SLAM system. Extensive evaluation on public datasets shows that our model is more accurate and robust, achieving 13% improvement in maximum F1 score on the SemanticKITTI dataset, when compared to the baseline semantic graph algorithm. For the benefit of the community, we open-source the complete implementation of our proposed algorithm and custom implementation of semantic registration at https://github.com/crepuscularlight/SemanticLoopClosure.
Improving rPET/PBT Bead Foam Structure via Chain Extender Modification and Blend Variance
Authors: Himmelsbach Andreas , Akdevelioglu Yavuz , Nofar Mohammadreza , Ruckdäschel Holger
Published: January 2025

In this study, the influence of the chain extender (CE) and the blend ratio on the bead foam extrusion of rPET/PBT is investigated. The shape and density of the bead foams were analyzed during extrusion using a camera scanner while the morphology of the foam was investigated using scanning electron microscopy (SEM). Melt strength and thermal behavior were also investigated with Rheotens and differential scanning calorimetry (DSC), respectively. Both chain extender and blend ratio had pronounced effect on the foaming behavior. Significant improvements were observed up to 0.8 wt.-% CE in rPET50PBT50, which achieved an average cell size of 107 ± 17 μm and a density of 182 kg/m³, representing a weight reduction of 86.4% compared to the bulk material. In addition, rPET40PBT60 with 0.8 wt.-% CE gave an average cell size of 108 ± 23 μm and a foam density of 170 kg/m³, with a comparable cell size distribution. After CE modification, the melt strength of rPET-dominant blends obtained higher values but a strong decrease in elongation was observed. In contrast, the CE-modified rPET40PBT60 and rPET30PBT70 blends exhibited much higher elongation with a moderate increase in melt strength which resulted in better bead and foam morphologies. DSC analysis revealed lowest crystallization temperature in rPET50PBT50 with deviations shifting towards higher temperatures. All blends except rPET70PBT30 shows double melting peak formation, with higher rPET formulations also exhibiting cold crystallization. These findings provide crucial insight for development of rPET/PBT foams by controlling the blend and CE composition, which is critical for achieving temperature-resistant bead foams with improved structural integrity.

Graphical Abstract
The Role of Aspect During Deverbal Word Processing in Greek
Authors: Tsaprouni Eleni , Manouilidou Christina
Published: January 2025

Deverbal formations in Greek, e.g. miˈrazo ‘to distribute’ < ˈmirazma ‘distributing’ are considered morphologically complex lexical items. Previous psycholinguistic studies in Greek and English already highlighted the importance of lexical category and argument structure of the base verb in the processing of deverbal pseudowords violating constraints pertaining to these properties. A similar study in Slovenian brought into light the role of aspectual properties of the base verb during deverbal word processing. The present study revisits the role of aspect in morphological processing of deverbal word formations by looking at Greek. To this end, an offline acceptability judgement task and an online lexical decision task were conducted using different types of pseudowords, violating derivational rules. Results provide evidence that aspect affects deverbal pseudoword processing in Greek. Aspectual rules have a distinct role in relation to categorial and argument structure ones for the suffix that creates formations with unambiguous, eventive readings and which has clear event implications but not for other suffixes. The current study extends the literature to include the role of this feature in the processing of deverbal formations.
Problem-Solving Strategies in Stoichiometry Across Two Intelligent Tutoring Systems: A Cross-National Study
Authors: Borchers Conrad , Fleischer Hendrik , Yaron David J. , McLaren Bruce M. , Scheiter Katharina , Aleven Vincent , Schanze Sascha
Published: January 2025

Intelligent tutoring system (ITS) provides learners with step-by-step problem-solving support through scaffolding. Most ITSs have been developed in the USA and incorporate American instructional strategies. How do non-American students perceive and use ITS with different native problem-solving strategies? The present study compares Stoich Tutor, an ITS with a high level of scaffolding, with ORCCA, an ITS with dynamic scaffolds that can support a range of problem-solving strategies. We conducted a think-aloud study with university students in the USA (N = 10) and Germany (N = 11), where students worked with either Stoich Tutor and ORCCA before solving stoichiometry problems on paper. Two human coders derived a coding scheme to investigate the strategies American and German students employ during problem solving on paper without instructional support. We derive a taxonomy of three stoichiometry problem-solving strategies. Next to the American factor labeling method, this taxonomy includes a strategy based on equation transformations and a previously undocumented strategy using abstract symbols to isolate a target variable and then pluck in given values and compute the solution. German students exclusively used the latter strategy, which was not explicitly supported by any of the two tutoring systems. Further, students who did not use the factor-label method for paper-based problem solving, most of whom were German, initially had difficulty setting appropriate goals and working with fractions in the Stoich Tutor. While German students preferred ORCCA based on short interviews, they more often successfully solved problems in Stoich Tutor. Therefore, Stoich Tutor, although misaligned with German instruction, could still support German students’ learning. Still, revisions to ITS based on local instructional cultures could make them potentially more effective and aligned with curricular goals.
Crop diversification for pollinator conservation
Authors: Fijen Thijs P. M. , Eeraerts Maxime , Osterman Julia , Beyer Nicole , Hass Annika , Lundin Ola , Westphal Catrin
Published: January 2025

Context

Intensive agriculture drives insect decline impacting insect-mediated ecosystem services that support production. Crop diversification shows promise in increasing crop productivity and enhancing ecosystem services, however, the impact on biodiversity conservation, particularly of pollinators, is unclear.

Objectives

Here, we synthesize the mechanisms and current evidence base of how increasing the spatial and temporal diversity of crops within and across agricultural fields can benefit pollinator biodiversity.

Methods

We focus on research in the highly intensified agricultural regions, in Western Europe and North America, from which we know a lot about pollinator decline, but use inspiration from tropical regions.

Results

We find that higher crop diversity, with sequentially flowering cultivars, intercropping practices, and a larger coverage of flowering crops, for example through integrating the cultivation of forgotten, novel, and woody crops increases flower resource availability throughout the active flight period of pollinators. All practices can increase landscape heterogeneity, which is further enhanced by decreasing field sizes. As a result, the functional connectivity increases, which improves the flower accessibility within the foraging ranges of pollinators.

Conclusions

Our review highlights the potential benefit of various crop diversification measures for supporting pollinating insects without taking land out of production, as well as the limitations, including that only a subset of pollinator species may benefit. Empirical evidence suggest that diversification practices could benefit pollinators, but landscape-wide studies are needed to properly evaluate the true potential of crop diversification for pollinator conservation as part of the solution for bending the curve of pollinator decline.
Lateral load response of a dry-joint masonry arch subject to vertical support displacements by rigid block analysis
Authors: Ferrero Chiara , Portioli Francesco P. A. , Calderini Chiara
Published: January 2025

Masonry arches play a crucial role in the seismic response of historic masonry buildings. Although masonry arches are often subjected to large support displacements that alter and deform their geometries over time, their response to seismic actions is generally analysed using idealized, perfect geometries. This paper aims to assess the effect of large support displacements on the response of masonry arches to lateral loads. To this end, a small-scale segmental dry-joint masonry arch subjected to the vertical displacement of one support was investigated. Using a rigid block modelling approach recently proposed in the literature, the arch was modelled as an assemblage of rigid voussoirs connected by no-tension frictional contact interfaces. The response of the arch to lateral loads, applied in one direction, and to vertical support displacements was assessed through nonlinear static analyses. To evaluate the effect of support displacements, lateral loads were applied to a series of deformed arch geometries resulting from the application of increasing values of the imposed vertical displacement. The results of the numerical analyses provided new insights into how support displacements affect the lateral load response of masonry arches, showing that they may significantly reduce both the horizontal action triggering collapse and the ultimate displacement capacity.
Development of natural regeneration after different regeneration cuttings in a Norway spruce peatland forest in northern Finland
Authors: Hökkä Hannu , Miettinen Janne , Karhu Jouni
Published: January 2025

As the clearcutting of peatland forests is known to cause harmful consequences especially for the water environment, there is increasing interest in alternative natural regeneration methods. We studied the regeneration stocking development on a southern Lapland site, where shelterwood cutting, heavy selection cutting, patch clearcutting (≤ 0.3 ha) treatments, and a non-treated control with three replicates had been established in the winter of 2013. Regeneration stocking was inventoried in the springs of 2013, 2016, 2018, and 2021 from 16 seedling survey plots (size 5 m2), which were systematically located in each of the 12 treatment plots. The number of small spruce seedlings (< 10 cm height) was largest in 2016 and then started to decrease. The number of large (> 10 cm) spruce seedlings increased two- to three-fold (4,500–9,000 ha− 1) towards the end of the study period for all cutting treatments. The number of large birch seedlings also increased especially for heavy selection and clearcutting and was 2–10 times higher than that of spruce. Birch was less abundant in shelterwood cutting. The tallest spruce and birch seedlings were found in clearcuts. Large spruce and birch seedlings were most evenly distributed for heavy selection and clearcut treatments. All cutting treatments showed high average regeneration density for a mixed seedling stand of Norway spruce and downy birch within the eight post-cutting years.
Improving flood hazard susceptibility assessment by integrating hydrodynamic modeling with remote sensing and ensemble machine learning
Authors: Ahmad Izhar , Farooq Rashid , Ashraf Muhammad , Waseem Muhammad , Shangguan Donghui
Published: January 2025

Floods are natural disasters with significant economic and infrastructural impacts. Assessing flood susceptibility in mountainous urban regions is particularly challenging due to the complicated interaction in which urban structures and mountainous terrain affect flood behavior. This study employs two ensemble machine learning algorithms, Extreme Gradient Boosting (XGBoost) and Random Forest (RF), to develop flood susceptibility maps for the Hunza-Nagar region, which has been experiencing frequent flooding for the past three decades. An unsteady flow simulation is carried out in HEC-RAS utilizing a 100-year return period flood hydrograph as an input boundary condition, the output of which provided the spatial inundation extents necessary for developing the flood inventory. Ten explanatory factors, including climatic, geological, and geomorphological features namely elevation, slope, curvature, topographic wetness index (TWI), normalized difference vegetation index (NDVI), land use land cover (LULC), rainfall, lithology, distance to roads and distance to rivers are considered for the flood susceptibility mapping. For developing flood inventory, random sampling technique is adopted to create a spatial repository of flood and non-flood points, incorporating the ten geo-environmental flood conditioning factors. The models’ accuracy is assessed using the area under the curve (AUC) of receiver operating characteristics (ROC). The prediction rate AUC values are 0.912 for RF and 0.893 for XGBoost, with RF also demonstrating superior performance in accuracy, precision, recall, F1-score, and kappa evaluation metrics. Consequently, the RF model is selected to represent the flood susceptibility map for the study area. The resulting flood susceptibility maps will assist national disaster management and infrastructure development authorities in identifying high flood susceptible zones and carrying out early mitigation actions for future floods.
Photonic circuit of arbitrary non-unitary systems
Authors: Talib Hussein , Sewell Phillip D. , Vukovic Ana , Phang Sendy
Published: January 2025

A design framework to implement non-unitary input–output operations to a practical unitary photonic integrated circuit is described. This is achieved by utilising the cosine-sine decomposition to recover the unitarity of the original operation. The recovered unitary operation is decomposed into fundamental unitary building blocks, forming a photonic integrated circuit network based on directional couplers and waveguide phase shifters. The individual building blocks are designed and optimised by three-dimensional full-wave simulations and scaled up using a circuit approach. The paper investigates the scalability and robustness of the design approach. Our study demonstrates that the proposed approach of performing unitary matrix completion can be applied to any arbitrary matrices. This design approach allows for implementation of non-unitary operations to perform various linear functions in neuromorphic photonics for computing, sensing, signal processing and communications.
Deep learning and machine learning based highly accurate reflection prediction model for multi layers anti-reflection coatings
Authors: Oktay Semih , Duru İremnur , Bakır Halit , Tabaru Timuçin Emre
Published: January 2025

This study focuses on creating an accurate reflection prediction model that will guide the design of filters with multilayer Anti-Reflection Coating (ARC) to optimize the thickness parameters using Machine Learning (ML) and Deep Learning (DL) techniques. This model aims to shed light on the design process of a multilayer optical filter, making it more cost-effective by providing faster and more precise production. In creating this model, a dataset containing data obtained from 3000 (1500 Ge–Al2O3, 1500 Ge–SiO2) simulations previously performed on a computer based on the thicknesses of multilayer structural materials was used. The data are generated using Computational Electromagnetic simulation software based on the Finite-Difference Time-Domain method. To understand the mechanism of the proposed model, two different two-layer coating simulations were studied. While Ge was used as the substrate in both coatings, Al2O3 and SiO2 were used as the second layers. The data set consists of the 3–5 µm and 8–12 µm bands typical for the mid-wave infrared (MWIR) and long-wave infrared (LWIR) bands and includes reflectance values for wavelengths ranging between these spectra. In the specified 2-layer data set, the average reflectance was obtained with a minimum of 0.36 at 515 nm Ge and 910 nm SiO2 thicknesses. This value can be increased by adapting the proposed model to more than 2 layers. Six ML algorithms and a DL model, including artificial neural networks and convolutional neural networks, are evaluated to determine the most effective approach for predicting reflectance properties. Furthermore, in the proposed model, a hyperparameter tuning phase is used in the study to compare the efficiency of ML and DL methods to generate dual-band ARC and maximize the prediction accuracy of the DL algorithm. To our knowledge, this is the first time this has been implemented in this field. The results show that ML models, particularly decision tree (MSE: 0.00000069, RMSE: 0.00083), random forest (MSE: 0.00000525, RMSE: 0.00229), and bagging (MSE: 0.00000667, RMSE: 0.00258) methods, outperform the DL model (MSE: 0.0040107, RMSE: 0.06333) in predicting reflectance values and provide a valuable reference for designing and fabricating optical thin-film filters.
A physics-aware neural network for effective refractive index prediction of photonic waveguides
Authors: Ünal Hasan Said , Durgun Ahmet Cemal
Published: January 2025

Neural network (NN)—based surrogates have been effectively used for modeling dynamic systems, including photonic devices. However, black-box data-driven modeling approaches significantly suffer from performance reduction in high-dimensional spaces.As a remedy, we propose a novel physics-aware NN architecture for the effective index prediction of photonic strip waveguides. The model learns a translation between the strip waveguide and an equivalent infinite slab waveguide by employing physical loss terms in the loss function. The proposed method exhibits significantly lower error, with more than

$$50\%$$

50
%

reduction, compared to a black-box NN and a variational method. Because of its physical basis, the proposed NN can predict field distributions in rectangular waveguides and the effective indices of higher-order modes.
Free Algebras in Finitely Generated Varieties of Commutative BCK-algebras
Authors: Cenker Václav
Published: January 2025

The article aims at describing finitely generated free algebras in certain finitely generated varieties of commutative BCK-algebras. To achieve this, we first investigate homomorphisms from free commutative BCK-algebras to free ŁBCK-algebras that extend the insertion of generators. The approach allows us to utilize existing results on free ŁBCK-algebras. The second step involves valuations and their equivalence. An essential part is to count the number of non-equivalent valuations with specific properties. With the number in hand, we can provide a comprehensive description of the free algebras.
Disentangling patent quality: using a large language model for a systematic literature review
Authors: Schmitt Valentin J.
Published: January 2025

Assessing patent quality has long been the subject of research interest due to interchangeable terminology, overlapping indicators, and diverse perspectives. To address these challenges, this study presents a comprehensive framework for assessing patent quality, that draws on stakeholder theory and adopts a multidimensional perspective encompassing economic, legal, and technological dimensions, each of which is clearly defined within the study. Using the capabilities of the large language model GPT-4, a systematic literature review was conducted, analyzing an initial sample of 5141 scientific articles and selecting 762 as relevant. From these selected articles, 985 distinct indicators for assessing patent quality were identified and classifed in accordance with the dimensions of patent quality. The findings reveal that forward citations, family size, and the number of claims are among the most frequently used indicators, highlighting a predominant focus on technological quality in nearly two-thirds of the literature. In addition, the study highlights several challenges in patent quality assessment, such as poor research reproducibility due to inconsistent definitions and applications of indicators such as family size. In response, eight research propositions are proposed, emphasizing the critical evaluation of indicators, the application of sophisticated methods, and the quantification of complex metrics. As a contribution to management and scholarship, this research underscores the complexity of patent quality assessment and provides a structured framework for future studies, emphasizing the importance of a multidimensional perspective. It also illustrates the transformative potential of large language models in enhancing systematic literature reviews, setting a new standard for future research.
Biodegradation of Benzophenone-3 in Non-Sterile Culture Process Using Klebsiella huaxiensis W2
Authors: Omeroglu Mehmet Akif , Bakan Buket , Baltaci Mustafa Ozkan , Arslan Nazli Pinar , Ucar Sefa , Elmas Seydanur , Adiguzel Ahmet , Taskin Mesut
Published: January 2025

Benzophenone-3 (BP3) is an organic pollutant widely detected in soil and aquatic environments. The aims of this study were to isolate a bacterium which is capable of degrading BP3 and converting it into non-toxic products, and to design a non-sterile culture process which may be applied to the real biological treatment systems for the bioremediation of BP3. Klebsiella huaxiensis W2 (GenBank accession number: PQ143284) isolated from a wastewater treatment system was found to have high potency to degrade BP3. This bacterium degraded BP3 into two byproducts: phenol, 2,4-bis-(1,1-dimethylethyl) and benzyl benzoate. Oxygenases (P450 monooxygenases, dioxygenases etc.) were predicted to be effective in BP3 degradation. BP3-degradation products did not cause a toxicity on fibroblast cell line. Optimizing inoculum size, that is, inoculating the high size (1–2%) of the bacterial preculture into the wastewater-based medium, make the bacterium more dominant in this medium, thus enabling the bacterial cells to degrade BP3 under non-sterile culture conditions. In this process, biodegradation efficiency was not affected notably from temperature variations, and the bacterium was able to hydrolyze about 99.33% of 1 g/L BP3 within 120 h. Overall, K. huaxiensis W2 was deduced to possess the potency for being used as a bioremediation agent in non-sterile biological treatment systems, in which sterilization process, temperature control, and nutrient supplementation were not needed. The designed process may find applications in the bioremediation of wastewater and sewage effluents. This is the first study using K. huaxiensis in a non-sterile environment for BP3 degradation.
Automatic 4D mitral valve segmentation from transesophageal echocardiography: a semi-supervised learning approach
Authors: Munafò Riccardo , Saitta Simone , Tondi Davide , Ingallina Giacomo , Denti Paolo , Maisano Francesco , Agricola Eustachio , Votta Emiliano
Published: January 2025

Performing automatic and standardized 4D TEE segmentation and mitral valve analysis is challenging due to the limitations of echocardiography and the scarcity of manually annotated 4D images. This work proposes a semi-supervised training strategy using pseudo labelling for MV segmentation in 4D TEE; it employs a Teacher-Student framework to ensure reliable pseudo-label generation. 120 4D TEE recordings from 60 candidates for MV repair are used. The Teacher model, an ensemble of three convolutional neural networks, is trained on end-systole and end-diastole frames and is used to generate MV pseudo-segmentations on intermediate frames of the cardiac cycle. The pseudo-annotated frames augment the Student model’s training set, improving segmentation accuracy and temporal consistency. The Student outperforms individual Teachers, achieving a Dice score of 0.82, an average surface distance of 0.37 mm, and a 95% Hausdorff distance of 1.72 mm for MV leaflets. The Student model demonstrates reliable frame-by-frame MV segmentation, accurately capturing leaflet morphology and dynamics throughout the cardiac cycle, with a significant reduction in inference time compared to the ensemble. This approach greatly reduces manual annotation workload and ensures reliable, repeatable, and time-efficient MV analysis. Our method holds strong potential to enhance the precision and efficiency of MV diagnostics and treatment planning in clinical settings.

Graphical abstract