bluuebunny/crossref_metadata_2025_split huggingface dataset:
Benthos meets plankton: isopods sampled in the Japan Trench by means of plankton nets fixed to large bottom trawls
Authors: Brandt Angelika , Bergmeier Franziska , Casaubon Anchita , Kano Yasunori , Kelch Andreas , Knauber Henry , Okamoto Kai , Ohta Mizuki , Shiraki Shoki , Yamamoto Daiki , Kojima Shigeaki 
Published: May 2024

AbstractDuring the KH-23–5 expedition aboard the RV Hakuho Maru to the Kuril-Kamchatka (KKT) and Japan Trenches (JT) in September 2023, we deployed bottom trawls equipped with plankton nets, resulting in a high number of supra- and epibenthic benthic organisms, particularly of isopod crustaceans (Peracarida, Malacostraca). In total, we sampled 2656 specimens of Isopoda spanning at least 14 families and the suborder Epicaridea across 28 stations. Notably, five families were represented by more than 100 specimens each: Munnopsidae led with the highest number of specimens (1123 individuals), followed by Haploniscidae with 564, Macrostylidae with 430, Ischnomesidae with 245, and Desmosomatidae with 188 individuals. Station C8 yielded the highest number of individuals (502), while only one isopod was retrieved from station F11. Our findings document the efficacy of employing additional plankton nets,and we recommend the increased use of bottom trawls deployed with plankton nets in future expeditions.
A dance fly (Empididae: Hilarempis Bezzi) from the Foulden Maar Fossil-Lagerstätte (Early Miocene, New Zealand)
Authors: Kaulfuss Uwe , Sinclair Bradley J. 
Published: May 2024

AbstractNew Zealand has a diverse and highly endemic fauna of dance flies (Empididae) with much of its diversity found in the tribe Hilarini. Here we report the first fossil of a dance fly from New Zealand from lacustrine diatomites of the earliest Miocene Foulden Maar Fossil-Lagerstätte in Otago. Hilarempis otagoensis sp. nov. is described from a single male specimen and assigned to the tribe Hilarini based on characters of the wing venation. This new species represents the first fossil record of the predominantly southern temperate genus Hilarempis Bezzi and the second fossil record of the subfamily Empidinae from the Southern Hemisphere. The articulated preservation suggests that Hilarempis otagoensis sp. nov. lived among riparian vegetation on the shore of the Foulden Maar palaeolake and probably drowned while skimming the water surface in search for prey or nuptial gifts.
Inflammatory myofibroblastic tumor of the liver after adrenal neuroblastoma surgery: a case report
Authors: Shen Qiyang , Liu Xingyu , Zhang Lijie , Li Tao , Zhou Jianfeng 
Published: May 2024

AbstractA boy aged 55 months was diagnosed with stage IV Neuroblastoma (NB) of the right adrenal gland 2 years ago. Preoperative chemotherapy was given and he was then treated with retroperitoneal tumor resection and lymph node dissection. After surgery, the children were transferred to the Hemato-Oncology Department for chemotherapy according to the high-risk group NB, with outpatient follow-up every 6 months. In the second postoperative year, abdominal computed tomography (CT) scan revealed a rounded hypodense area in the upper part of the right posterior lobe of the liver, with marked inhomogeneous enhancement in the venous phase after enhancement, which was surgically resected, and postoperative pathology confirmed inflammatory myofibroblastic tumor (IMT) of liver. The patient was not given any special treatment after surgery. In this study, whole transcriptome sequencing was performed on the postoperative specimen of adrenal NB and the specimen of IMT of liver. This unusual case emphasizes the need for close monitoring of second tumor development in NB survivors even in the absence of known predisposing factors.
Green Innovation Adoption in Turkish and Iranian SMEs: The Effect of Dynamic Capabilities and the Mediating Role of Absorptive Capacity
Authors: Çeli̇k Ali Kemal , Yildiz Tayfun , Aykanat Zafer , Kazemzadeh Siamak 
Published: May 2024

AbstractGreen innovation (GI) adoption of small and medium-sized enterprises (SMEs) especially in middle-income economies plays a significant role to reduce negative impacts of environmental issues and to gain competitive advantage. The main objective of the present paper is to examine the mediating role of absorptive capacity (ACAP) on the relationship between dynamic capabilities (DC) and GI adoption in the context of Turkish and Iranian SMEs, two middle-income economies. For this purpose, a well-established online questionnaire is administered to 296 top executives of Turkish and Iranian SMEs operating in energy industry, a highly dynamic market. Using Hayes Process Macro Model, the results of this paper reveal that ACAP has a significant effect on GI adoption of Iranian SMEs but this effect of ACAP is insignificant in terms of Turkish SMEs. The empirical evidence obtained from the present paper also puts forward that DC positively influnce GI adoption in Turkish SMEs, however, the corresponding relationship is not significant for Iranian counterparts. For both middle-income economies, ACAP has a statistically significant mediating role on the relationship between DC and GI adoption of SMEs. Strategic alliances engagement and governmental incentives on GI investments are recommended to overcome certain barriers of SMEs including resource shortages and to improve ACAP and DC that enhance GI adoption of Turkish and Iranian SMEs in the future. As far as is known, this is the first study that compares possible antecedents of SMEs’ GI adoption in two middle-income economies.
Generation of induced pluripotent stem cells from an individual with early onset and severe hypertrophic cardiomyopathy linked to MYBPC3: c.772G > A mutation
Authors: Ribeiro Marta , Jager Joanna , Furtado Marta , Carvalho Teresa , Cabral Joaquim M. S. , Brito Dulce , Carmo-Fonseca Maria , Martins Sandra , da Rocha Simão Teixeira 
Published: May 2024

AbstractHypertrophic cardiomyopathy (HCM) is frequently caused by mutations in the MYPBC3 gene, which encodes the cardiac myosin-binding protein C (cMyBP-C). Most pathogenic variants in MYPBC3 are either nonsense mutations or result in frameshifts, suggesting that the primary disease mechanism involves reduced functional cMyBP-C protein levels within sarcomeres. However, a subset of MYPBC3 variants are missense mutations, and the molecular mechanisms underlying their pathogenicity remain elusive. Upon in vitro differentiation into cardiomyocytes, induced pluripotent stem cells (iPSCs) derived from HCM patients represent a valuable resource for disease modeling. In this study, we generated two iPSC lines from peripheral blood mononuclear cells (PBMCs) of a female with early onset and severe HCM linked to the MYBPC3: c.772G > A variant. Although this variant was initially classified as a missense mutation, recent studies indicate that it interferes with splicing and results in a frameshift. The generated iPSC lines exhibit a normal karyotype and display hallmark characteristics of pluripotency, including the ability to undergo trilineage differentiation. These novel iPSCs expand the existing repertoire of MYPBC3-mutated cell lines, broadening the spectrum of resources for exploring how diverse mutations induce HCM. They additionally offer a platform to study potential secondary genetic elements contributing to the pronounced disease severity observed in this individual.
Node classification in complex networks based on multi-view debiased contrastive learning
Authors: Li Zhe , Zhou Lei , Hou Yandong , Ji Min , Hang Zhuanzheng , Chen Bolun 
Published: May 2024

AbstractIn complex networks, contrastive learning has emerged as a crucial technique for acquiring discriminative representations from graph data. Maximizing the similarity among relevant sample pairs while minimizing that among irrelevant pairs is pivotal in contrastive learning. Therefore, careful consideration must be given to the design of sample pairs in contrastive learning. However, existing node-level self-supervised contrastive learning often treats the enhanced representation of a central node as a positive sample, while considering representations of all other nodes as negative samples. This approach can lead to conflicts in downstream tasks on some graph data, as nodes of the same class are treated as negatives during learning. Precision in sample pair design is essential for enhancing the performance of contrastive learning. To address this issue, this paper introduces a negative sample debiased sampling contrastive learning (NDSCL), specifically tailored for node classification tasks. In particular, this method integrates contrastive learning with semi-supervised learning. A trained classifier assigns pseudo-labels to unlabeled data, and debiased sampling is applied to negative samples. Unlike other methods that focus on negative sample selection, NDSCL also addresses the imbalance in pseudo-label distribution by employing debiasing techniques. Finally, in conjunction with diffusion augmentation, the model is provided with diverse views as inputs to maximize the retention of underlying semantic information. Experimental results demonstrate that the proposed model significantly outperforms baseline models in node-level classification tasks across multiple network datasets. Moreover, the model not only enhances accuracy but also improves computational speed and memory requirements for handling large-scale graph data structures.
Sla-former: conformer using shifted linear attention for audio-visual speech recognition
Authors: Xiao Yewei , Huang Jian , Liu Xuanming , Zhu Aosu 
Published: May 2024

AbstractConformer-based models have proven highly effective in Audio-visual Speech Recognition, integrating auditory and visual inputs to significantly enhance speech recognition accuracy. However, the widely utilized softmax attention mechanism within conformer models encounters scalability issues, with its spatial and temporal complexity escalating quadratically with sequence length. To address these challenges, this paper introduces the Shifted Linear Attention Conformer, an evolved iteration of the conformer architecture. Shifted Linear Attention Conformer adopts shifted linear attention as a scalable alternative to softmax attention. We conducted a thorough analysis of the factors constraining the efficiency of linear attention. To mitigate these issues, we propose the utilization of a straightforward yet potent mapping function and an efficient rank restoration module, enhancing the effectiveness of self-attention while maintaining low computational complexity. Furthermore, we integrate an advanced attention-shifting technique facilitating token manipulation within attentional mechanisms, thereby enhancing information flow across various groups. This three-part approach enhances cognitive computations, particularly beneficial for processing longer sequences. Our model achieves exceptional Word Error Rates of 1.9% and 1.5% on the Lip Reading Sentences 2 and Lip Reading Sentences 3 datasets, respectively, showcasing its state-of-the-art performance in audio-visual speech recognition tasks.
Dynamic programming with meta-reinforcement learning: a novel approach for multi-objective optimization
Authors: Wang Qi , Zhang Chengwei , Hu Bin 
Published: May 2024

AbstractMulti-objective optimization (MOO) endeavors to identify optimal solutions from a finite array of possibilities. In recent years, deep reinforcement learning (RL) has exhibited promise through its well-crafted heuristics in tackling NP-hard combinatorial optimization (CO) problems. Nonetheless, current methodologies grapple with two key challenges: (1) They primarily concentrate on single-objective optimization quandaries, rendering them less adaptable to the more prevalent MOO scenarios encountered in real-world applications. (2) These approaches furnish an approximate solution by imbibing heuristics, lacking a systematic means to enhance or substantiate optimality. Given these challenges, this study introduces an overarching hybrid strategy, dynamic programming with meta-reinforcement learning (DPML), to resolve MOO predicaments. The approach melds meta-learning into an RL framework, addressing multiple subproblems inherent to MOO. Furthermore, the precision of solutions is elevated by endowing exact dynamic programming with the prowess of meta-graph neural networks. Empirical results substantiate the supremacy of our methodology over previous RL and heuristics approaches, bridging the chasm between theoretical underpinnings and real-world applicability within this domain.
Observed Characterization of Multi‑level Retaining Structure for Deep Excavation of Subway Station
Authors: Cui Xiangyang , Li Zhaoping , He Huafei , Liu Teng , Wang Jiahao 
Published: May 2024

AbstractTraditional support structures cannot meet the complex conditions of different excavation depths and areas in underground transportation hubs. On the basis of fully considering the spatial position relationship of foundation pit groups, this article proposes a multilevel retaining system that meets the requirements of multilevel foundation pit excavation. The evolution law of the support structure during the excavation process of the inner pit was explored using on-site monitoring and numerical simulation methods. The results indicate that the excavation of the inner pit reduces the passive earth pressure, and the deformation of the outer support structure can be effectively suppressed by setting a retaining structure or a bottom slab in the bench zone. The excavation of the inner pit causes significant vertical deformation of the support structure adjacent to the foundation pit, while the impact on the structure far away from the foundation pit is relatively small. According to the contact force chain and soil pressure between the two rows of support structure, the soil in this area is divided into a “relaxation zone” and a “compression zone.” The evolution mechanism of earth pressure in the case of mutual-effect failure between two rows of piles is revealed. This paper addresses the deformation properties of multilevel support structures as well as the mechanism of earth pressure evolution between structures.
First Record of Partial Albinism in the Chinese Fanray, Platyrhina Sinensis (Elasmobranchii: Myliobatiformes: Platyrhinidae)
Authors: Zhuang Yan , Ke Shuting , Chen Mingru , Xiao Jiamei 
Published: May 2024

AbstractA female albino fanray specimen was collected by trawl from the southern Taiwan Strait on April 11, 2022. This unique individual was identified as the Chinese fanray, Platyrhina sinensis (Bloch & Schneider, 1801), based on morphological identification and DNA barcoding. It was classified as partial albinism (leucism) due to the absence of pigmentation in the skin and normal pigmentation in the irises. This specimen represents the first reported case of albinism within the family Platyrhinidae, providing valuable insights for physiological and ecological research on albino fish.
Martial Arts Interventions for Inclusion and Wellness: A Case of Children with Special Educational Needs and Disability (SEND)
Authors: Spring Charles , Ramkissoon Haywantee 
Published: May 2024

AbstractMartial arts are a Broad set of Activities that Offer the Opportunity to Engage in a Physical Activity that can Produce a Range of Benefits for Young People. The Broad Nature of Martial arts also Brings Merits to Children with Special Educational Needs and Disability (SEND) as they have an Opportunity to Engage Better in more Activities and are not Limited to just Traditional Physical Activity Offered in Their Educational Settings. This Paper Draws on the Literature to show how Martial arts is Linked to Leisure Research and how it also fits into the Realm of Wellness Benefits for Young Children on SEND. The Paper Highlights the Potential Benefits of Martial arts Interventions and Discusses its Usefulness in Promoting Inclusion. The Preliminary Findings from a Pilot Study Suggest that SEND Children do Indicate some Changes in Their Behaviours through the Martial arts Interventions. Reduced Scores were Observed in Areas around those that might Cause Anxiety, Anger and Frustration, whilst Excitement and Calmness was Improved. The Reactions of Carers and Teaching Assistants Displayed Improvements in Anxiety and Positive Behaviours.
Three-dimensional Computed Tomography Features of Recurrent Laryngeal Nerve Paralysis Due to Aortic Aneurysm
Authors: Sasakawa Jumpei , Goto Takao , Sato Taku , Koyama Misaki , Ueha Rumi , Yamasoba Tatsuya 
Published: May 2024

Abstract
Detailed reports on the stretching and compression of the recurrent laryngeal nerve by aortic aneurysms are unavailable. Therefore, we evaluated three-dimensional computed tomography images of patients with aortic aneurysm-associated recurrent laryngeal nerve paralysis. We enrolled patients with vocal-fold paralysis without aortic aneurysms (control group), vocal-fold paralysis before aortic aneurysm surgery (preoperative group), and vocal-fold paralysis after aortic aneurysm surgery (postoperative group). Using image reconstruction software, three-dimensional computed tomography images were constructed and cross-sections along the recurrent laryngeal nerve were obtained. Compression of the pulmonary artery by the aortic aneurysm was evaluated, and the aortic circumference in the cross-sections was compared between the groups. All cases in the preoperative group showed pulmonary artery and surrounding tissue compression. The aortic aneurysm circumference in the preoperative group was significantly greater than that in other groups. In patients with aortic aneurysms, three-dimensional computed tomography along the recurrent laryngeal nerve is useful for assessing the risk of recurrent laryngeal nerve paralysis.
Quantum support vector machines for classification and regression on a trapped-ion quantum computer
Authors: Suzuki Teppei , Hasebe Takashi , Miyazaki Tsubasa 
Published: May 2024

AbstractQuantum machine learning is a rapidly growing field at the intersection of quantum computing and machine learning. In this work, we examine our quantum machine learning models, which are based on quantum support vector classification (QSVC) and quantum support vector regression (QSVR). We investigate these models using a quantum circuit simulator, both with and without noise, as well as the IonQ Harmony quantum processor. For the QSVC tasks, we use a dataset containing fraudulent credit card transactions and image datasets (the MNIST and the Fashion-MNIST datasets); for the QSVR tasks, we use a financial dataset and a materials dataset. For the classification tasks, the performance of our QSVC models using 4 qubits of the trapped-ion quantum computer was comparable to that obtained from noiseless quantum circuit simulations. The result is consistent with the analysis of our device noise simulations with varying qubit gate error rates. For the regression tasks, applying a low-rank approximation to the noisy quantum kernel, in combination with hyperparameter tuning in ε-SVR, improved the performance of the QSVR models on the near-term quantum device. The alignment, as measured by the Frobenius inner product between the noiseless and noisy quantum kernels, can serve as an indicator of the relative prediction performance on noisy quantum devices in comparison with their ideal counterparts. Our results suggest that the quantum kernel, as described by our shallow quantum circuit, can be effectively used for both QSVC and QSVR tasks, indicating its resistance to noise and its adaptability to various datasets.
Application of Artificial Intelligence in Justice: Current Trends and Future Prospects
Authors: Laptev Vasiliy A. , Feyzrakhmanova Daria R. 
Published: May 2024

Abstract
Background
Modern digital technologies are actively being introduced into spheres of society, including justice. Electronic justice at the present stage of development of information technology has moved to a qualitatively new level. It has become obvious that artificial intelligence (AI) is our present, not our future.

Objective
This article analyzes foreign experience in the implementation and use of AI in justice, identifies possible areas for the use of AI in justice, examines the legal personality of AI and the scope of its competence, and evaluates the prospects for the development of AI in justice.

Results
The authors identified the following areas of use of AI in justice: organizational sphere of activity of courts; assessment of evidence and establishment of legally significant circumstances; consideration of the case by AI. Also in this study, the stages of introducing AI into justice: short-term perspective, medium-term perspective (5–10 years), long-term perspective. It is noted that at present the work of AI is possible only in conjunction with a human judge.

Conclusions
The authors noted the feasibility of using AI in resolving issues that require processing a large amount of information and documents in electronic form. This will ensure procedural savings and reduction of time for consideration of disputes on the merits through speed and error-free calculations.
Three‐Dimensional Electrical Resistivity Structure Beneath a Strain Concentration Area in the Back‐Arc Side of the Northeastern Japan Arc
Authors: Usui Yoshiya , Uyeshima Makoto , Hase Hideaki , Ichihara Hiroshi , Aizawa Koki , Koyama Takao , Sakanaka Shin'ya , Ogawa Tsutomu , Yamaya Yusuke , Nishitani Tadashi , Asamori Koichi , Ogawa Yasuo , Yoshimura Ryokei , Takakura Shinichi , Mishina Masaaki , Morita Yuichi 
Published: May 2024

AbstractIntraplate earthquakes occur more frequently in the Japanese islands than in other regions. Large intraplate earthquakes in the island arc preferentially occur in strain concentration zones detected by geological and geodetic studies. Crustal heterogeneity plays a crucial role in generating large intraplate earthquakes and strain concentrations. Thus, we elucidated the crustal heterogeneities beneath a strain concentration area on the back‐arc side of the northeastern Japan Arc based on electrical resistivity, which is sensitive to weak zones in the crust. By deploying wideband magnetotelluric surveys, we revealed the three‐dimensional electrical resistivity structure in the crust, suggesting the coexistence of two different types of strain‐concentration mechanisms in the strain‐concentration area. The shallow conductive layers and lower‐crustal conductors appear to act as low‐elastic‐modulus and low‐viscosity areas, respectively, and are responsible for the strain concentration. We found shallow and lower‐crustal conductors in the strain concentration zone revealed by geological studies. Those conductive areas are considered to act as mechanically weak zones and cause stress loading on the brittle pars of pre‐existing faults, resulting in large intraplate earthquakes. The resultant earthquakes presumably contribute to strain accumulation on a geological timescale. In addition, a spatial correlation between the epicenters of large intraplate earthquakes and edges of lower‐crustal conductors implies the contribution of the fluids in the lower crust to the generation of large earthquakes. We also identified vertical conductors ranging from the lower crust to Quaternary volcanoes, which may indicate trans‐crustal magmatic systems under these volcanoes.