bluuebunny/crossref_metadata_2025_split huggingface dataset:
Conectividad vial en la gestión territorial: una mirada desde los indicadores sociales
Authors: Aronés Cisneros Angel , Córdova Domínguez Franck Bryan , Sánchez Arias Lizbeth Gesenia , Vilela Aguilera Brayan Pooll , Sánchez Vásquez César Julio , Anampa Huanca Luz Marina , Melgar Aliaga Kevin Celso , Mendoza Ramírez Franz Antony , Montellanos Cabrera Harry Frank , Bautista Salazar Edinsson Manuel 
Published: December 2024

El objetivo de esta investigación es analizar la conectividad vial en relación con los indicadores de analfabetismo, desnutrición, viviendas sin acceso al agua, pobreza no monetaria y acceso a internet. En la metodología, para la elaboración cartográfica de conectividad vial, se utilizó la ponderación por distancia o inverse distance weighting (IDW) en el software de ArcGis 10.8, en tanto los indicadores para los distritos se han extraído desde GeoPerú. Los resultados indican que la conectividad vial desempeña un papel crucial en el desarrollo socioeconómico de los distritos. Aquellos con una alta conectividad, como Moche, Huancán y Perené, presentan índices más bajos de analfabetismo, desnutrición, viviendas sin acceso a agua potable, pobreza no monetaria y hogares sin internet en comparación con los distritos de baja conectividad, como El Porvenir, Santo Domingo de Acobamba y Pichanaqui. Se concluye que la infraestructura vial es un factor clave para reducir la desigualdad y mejorar las condiciones de vida en áreas menos desarrolladas.
La Mojarra Castarrica, Mayaheros urophthalmus: Especie Nativa Mesoamericana, con Alto Potencial Acuícola
Authors: Fernandez-Pérez Mario 
Published: December 2024

Aquaculture allows food production, bringing important social and economic benefits that result in high nutritional value and accessible costs for the population. Mexico has a great diversity of native species with great potential for this activity, such as the Mayan cichlid, Mayaheros urophthalmus. The present bibliographic review was carried out in Google Scholar, libraries and the institutional repository of the Universidad Juárez Autónoma de Tabasco on the advances in the knowledge of the biology, fishery and aquaculture potential of the mojarra castarrica. Among the results, it was found that 60% of them are focused on the biology and ecology of the species, highlighting that it is an omnivorous fish with a carnivorous tendency that normally feeds on fish and invertebrates, presents an important fecundity, reproducing several times during the warm months. The fishery status of the beaver is uncertain; at present, catches are reported as encompassing all cichlids, so there is no basis to indicate its status. However, fishermen report low catches. In aquaculture, there are advances in culture, nutrition and biotechnological aspects, with larval culture being identified as one of the critical phases of development. In the grow-out stage, it can be cultivated in cages, geomembranes or earthen ponds, using a feed containing between 32 and 45% protein. Progress has been made in nutrition, but there is still no feed specifically designed for this species. Many more studies are required to determine its fishing and aquaculture potential.
Estudio comparativo entre peso vivo y dimorfismo sexual en seis generaciones de tilapia nilótica GIFT
Authors: Barrueta-López Daylen Virgen , Damas-Pérez Teresa de Jesus 
Published: December 2024

The present investigation focused on the results obtained to evaluate the traits of live weight and sex through comparative analysis based on the number of generations. A total of 86 groups of GIFT Nile tilapia families were obtained along six generations of the genetic improvement program in Cuba. It was observed how the average live weight of the fish increased when passing from one generation to the next. The best results were found in generations five and six with values greater than 500 g (514 g and 612 g, respectively). A regression analysis was performed, obtaining a coefficient of determination (R2) of 60.9 %, demonstrating that the generation and sex effects explain approximately 61 % of the phenotypic variability shown by the live weight trait. At the same time, the superiority of the males was evident since the beginning of the genetic improvement program, with an average weight of 776 g in the males and 470 g in the females. The main result was a significant increase in live weight in GIFT Nile tilapia with the advance of the selective program applied to both sexes, showing superiority for males.
Venous Air Embolism During Lumbar Spine Surgery Leading to Cardiac Arrest Requiring Prone Chest Compressions
Authors: Nassar Joseph E. , Daher Mohammad , Singh Manjot , Knebel Ashley , Criddle Sarah L. , Diebo Bassel G. , Daniels Alan H. 
Published: December 2024

Case report:
A 76-year-old female patient underwent revision T12-L4 decompression and fusion surgery. During the procedure, a large dural defect occurred associated with an abrupt drop in end-tidal CO2, severe hypotension, bradycardia, and cardiac arrest. Prone chest compressions were initiated, and the patient survived without postoperative comorbidities. The sudden hemodynamic instability was attributed to a venous air embolism (VAE) confirmed by findings on intraoperative capnography.

Conclusion:
Managing cardiac arrest caused by VAE in lumbar spine surgery is challenging. This case showcases that prone chest compressions may lead to better survival chances compared with waiting to initiate supine chest compressions.
Mural inpainting via two-stage generative adversarial network
Authors: Lyu Qiongshuai , Zhao Na , Song Junke , Yang Yu , Gong Yuehong 
Published: December 2024

Abstract

The digital restoration of Dunhuang murals is of extremely high value for the research and dissemination of mural culture and art. However, a large number of murals have been damaged to varying degrees due to factors such as climate change, sand erosion, and human destruction. Most of the existing digital mural restoration methods have problems such as insufficient feature extraction and loss of detail reconstruction. In this paper, we propose a two-stage coarse-to-fine digital mural restoration framework. The first stage is used to achieve coarse-grained semantic reconstruction, and the second stage is used to achieve fine-grained feature reconstruction. To improve the reconstruction performance of the model, we also designed a new building block that integrates the Swin transformer module (SwinT) and the multi-scale dilated convolution attention module. Meanwhile, the proposed loss function is to further empower the proposed model to repair damaged mural paintings. Extensive comparative experiments show that the proposed model can effectively restore the missing content of the mural and exceed the comparative methods in both quantitative and qualitative evaluation.
End-Anchored Externally Bonded BFRP Composites for Shear Strengthening of RC T-Beams
Authors: Kar S. , Biswal K. C. 
Published: December 2024

Abstract

This experimental study explores the behavior of shear-deficient reinforced concrete (RC) T-beams that are strengthened with externally bonded basalt fiber-reinforced polymer (EB-BFRP) composites. The primary aim of this study is to investigate the influence of various types of end-anchorage schemes on the efficacy of BFRP U-jackets. Six different anchorage schemes have been considered, varying in terms of their location and constitutive materials. Additionally, other investigative parameters include the types of strengthening schemes and the orientation of the BFRP composites. Ten RC T-beams were prepared and tested under a four-point loading system. The experimental outcomes showed that the load-carrying capacity of T-beams with EB-BFRP increased by 18–88%, and the end-anchorage schemes enhanced the performance of BFRP U-jackets by 12–44%. The rope-anchorage system located at the web-flange junction was the most effective, followed by the mechanical anchorage system, with the anchorage system comprising horizontal BFRP strips being the least effective. Finally, the test results were compared with the estimations made by ten widely considered design guidelines, revealing that the latter provided more conservative results.
Counterfactual GAN for Debiased Text-to-image Synthesis
Authors: KONG Xianghua , Xu Ning , Sun Zefang , Shen Zhewen , Zheng Bolun , Yan Chenggang , Cao Jinbo , Kang Rongbao , Liu An-An 
Published: December 2024

Abstract

Text-to-image generation (T2I) is a complex task to produce images that accurately reflect the content and meaning of the provided textual descriptions. Essentially, not every word in the sentence has a corresponding visual appearance. For example, the non-visual words “are” and “a” do not have corresponding visual regions, whereas the visual words “men" and “basketball" are crucial to generating visual regions. Existing methods treat all words equally to produce images, without distinguishing between visual and non-visual words. Gradients from non-visual words can introduce harmful bias that diminishes the total effect of textual guidance in generating image content. This paper presents a new debiased text-to-image synthesis method with a counterfactual learning scheme. First, we build a causal graph for text-to-image synthesis, which stands in the cause-effect interpretation of visual and non-visual words. Second, we treat the non-visual words as confounders that introduce misleading associations during the image generation process. To mitigate the influence of non-visual words, we conceptualize the process as calculating the Natural Direct Effect on the generated visual features and use the Total Indirect Effect to produce the final image for debiased text-to-image generation. By using our method on several existing models, significant improvements can be achieved in two prevailing datasets.
CCS Concepts: • Computing methodologies → Artificial intelligence; Machine learning.
The Perspectives of Healthcare Providers, Traditional Healers, and Other Key Informants on the Late Diagnosis of Breast Cancer in Northern Tanzania: A Qualitative Study
Authors: Msoka Elizabeth F. , Abraham Mackenzie , Mulder Bob C. , Beavers Autumn , Gebremariam Alem , Bright Frank B. , Serventi Furaha , Cyril Perry M. , Kitali Brenda C. , Saria Vivian F. , Masenga Gileard G. , Kantelhardit Eva J. , Joffe Maureen , Gutnik Lily , Mmbaga Blandina T. 
Published: December 2024

Abstract

Purpose: Breast cancer (BC) is the most common cancer among women in Tanzania and has one of the highest mortality rates worldwide due to late-stage diagnosis and suboptimal treatment. However, the role of traditional healers in late-stage diagnosis has not been widely studied. We aimed to identify the barriers to early BC diagnosis in Tanzania and possible solutions by interviewing healthcare providers (HCPs), traditional healers (THs), and other key informants (KIs).
Methods: Semi-structured, in-depth interviews were conducted with 20 HCPs (including 10 doctors and 10 nurses), 10 THs, and 9 KIs in community settings in the Kilimanjaro region. A focus group discussion with 8 THs was also conducted. Demographic data were collected from the participants, and the interview data were transcribed, translated, coded and analyzed using NVIVO 12 software to identify themes.
Results: The findings were synthesized into five themes to explain late diagnosis: 1) HCPs and THs have limited knowledge and misconceptions about the causes, signs, and symptoms of breast cancer; 2) patients experience stigma 3) treatment is expensive and difficult to access; 4) patients perceive barriers based on myths, misperceptions and spiritual beliefs; and 5) HCPs and THs often blame each other for ineffective treatment and delays in effective treatment. The participants also provided suggestions to reduce delays in diagnosis and treatment, including enhancing knowledge and awareness among THs and HCPs to help them recognize the signs and symptoms of BC through education campaigns, addressing the cost of access to care and treatment, addressing stigma associated with BC, and developing collaborative efforts between HCPs and THs.
Conclusion: In this study, we successfully identified several themes related to barriers to early BC diagnosis that help to explain the late diagnosis of BC from the perspective of various participants. Raising community awareness and improving understanding of breast cancer is crucial in reducing misconceptions and stigma. Collaboration between healthcare providers and traditional healers could be beneficial in the development of strategies to recognize the early signs and symptoms of BC.
From marine cold spells to heatwaves: Climatic impacts on a polar shallow-water ecosystem
Authors: Fischer Philipp , Brix Holger , Bussmann Ingeborg , Ködel Uta , Schwanitz Max , Schütze Claudia , Anselm Norbert , Brand Markus , Jenniges Yvonne , Kasten Sabine , Kraberg Alexandra , Lienkämper Miriam , Spotowitz Lisa , Weber Ute , Wiltshire Karen , Dietrich Peter 
Published: December 2024

Abstract

Global warming affects the Earth system in complex ways, often preventing a functional understanding of the underlying processes. Disentangling these processes between abiotic drivers and single species or entire communities is, however, essential for an in-depth understanding of climate change impacts on the ecosystem. Using a high-resolution time series on heatwaves and cold spells in an Arctic fjord system, we show that for analysing the effects of environmental stressors on biota, AI supported digital data processing based on state-of-the-art observatory technology can provide insights in habitat-community interactions which are not possible with classic expedition-based sampling methods. Furthermore, our study shows that short-term event-based anomalies in key ocean variables may have an even stronger impact on a communities structure than long-term climate change trends.
International Survey on Training of Residents in Dermatology in Supportive Oncodermatology: The Rescue Study
Authors: Ortiz-Brugués Ariadna , Fattore Davide , Boileau Marie , Forsea Ana-Maria , Apalla Zoe , Nikolaou Vasiliki , Stojkovic-Filipovic Jelena , Freites-Martinez Azael , Kaminska-Winciorek Grazyna , Elshot Yannick , Baltas Eszter , Torre Ana-Clara , Riganti Julia , Anadkat Milan , Bang Alexander , Fida Monika , Richert Bertrand , Kraehenbuehl Lukas , Avitan Emily , Preto-Gomes Nuno-Miguel , Hassel Jessica , Doolan Brent , Kluger Nicolas , Pagès Cécile , Guillon Benoit , Lacroix Noémie , Lacouture Mario , Sibaud Vincent 
Published: December 2024

Abstract

Purpose
Dermatologic management of cancer patients with cutaneous adverse events, acquired during and after oncologic treatments, is known as supportive oncodermatology. This subspecialty within dermatology includes the prevention, early identification, and mitigation of dermatologic toxicities affecting the skin, hair, nails, and mucous membranes resulting from chemotherapy, targeted therapies, immunotherapy, endocrine therapies and radiation therapy.
Methods
The European Academy of Dermatology and Venereology (EADV) Task Force “Dermatology for Cancer Patients,” in partnership with the US Oncodermatology Society conducted this international questionnaire-based study RESCUE (RESIDENTS SURVEY ON TRAINING OF DERMATOLOGY RESIDENTS IN SUPPORTIVE ONCODERMATOLOGY), aiming to evaluate the current state of knowledge and training in supportive oncodermatology.
Results
442 dermatology residents from 20 countries participated in the RESCUE study. Main results showed that dermatology residents declared to be less trained in supportive oncodermatology (only 41% received complete training) compared to immunodermatology (75%), cutaneous oncology (75%), dermoscopy (64%) and dermatologic surgery (50%). Only 17% of residents affirmed feeling comfortable dealing with dermatological toxicities of anticancer treatments. Residents stated being less educated in the management of dermatological toxicities of endocrine therapies (28%). They felt less qualified in nail, hair and oral toxicities. 98% of residents considered that improving training on dermatological toxicities of anticancer therapies is important during residency.
Conclusion
A specific dedicated residency program including a more practical approach, together with an extended training in endocrine therapies, as well as hair, nail and oral toxicities, would improve the skills of dermatology residents in the management of cutaneous adverse events of anticancer therapies.
Two-stage White Blood Cells Detection Combined with Semi-supervised Classification
Authors: SONG HUIHUI , WANG ZHENG 
Published: December 2024

Abstract

The classification and statistics of white blood cells (WBCs) are critical steps in the microscopic examination of blood smears. Traditional manual microscopy methods are time-consuming and labor-intensive, while machine learning-based automated detection approaches require a substantial amount of labeled data for model training, leading to high costs. To address this issue, this paper proposes a two-stage semi-supervised deep learning method for WBC detection. In the first stage, a region proposal network (RPN) with ResNet50 as the backbone is employed for the localization and segmentation of white blood cell images. In the second stage, a semi-supervised learning framework is utilized to train the WBC classifier. The model is trained and tested using 1,510 labeled blood cell microscopy images with WBC localization boxes. The proposed semi-supervised model achieves a classification accuracy of 86%, which is 3.2% higher than that of the fully supervised model. Furthermore, this two-stage model is compared with two end-to-end models, FasterRCNN and RetinaNet. The results demonstrate that the proposed two-stage model achieves an accuracy of 83.7% and a recall of 85.1% in detection tasks, both exceeding those of the FasterRCNN and RetinaNet models. Compared to a one-stage WBC detection model, the two-stage detection method allows for more thorough training of the WBC classifier, thereby enhancing overall detection performance.
Evapotranspiration Dynamics in the Ribb Watershed Upper Blue Nile, Ethiopia.
Authors: Kassie Gebrehiwot Getu , Atanaw Simir B. , Sinshaw Berhanu G. , Ayele Gebiaw T. , Kessie Kidia G. , Kidie Wassie Dessie 
Published: December 2024

Abstract

Assessment of the spatiotemporal distribution of evapotranspiration is crucial for efficient water resource management, especially in irrigation-dependent regions. This study evaluated actual evapotranspiration (AET) in the Ribb watershed, Ethiopia, via the surface energy balance algorithm for land (SEBAL) with remote sensing and climate data. The analysis focuses on the temporal (daily, monthly, and seasonal) and spatial variability of AET under different land uses. The daily AET values ranged from 0 to 10.99 mm/day, with mean values between 1.97 and 5.15 mm/day. The highest AET (5.15 mm/day) occurred during the middle growth stage of irrigated crops in January, whereas the lowest values (1.94 mm/day) were observed during the initial and end growth stages in December and February. The forest areas and water bodies presented high daily and seasonal AET values, whereas the agricultural fields and bare lands, which were mostly dry during the study period, presented lower ET values. Validation against ground-based pan-ET measurements and the Penman-Monteith (PM) method revealed strong correlations (R² values of 0.86 and 0.81, respectively). A comparison with MOD16-ET products revealed lower correlations, particularly for agricultural and forestland use (R² values of 0.33 and 0.4, respectively). This study demonstrates that integrating the SEBAL model with remote sensing data provides a reliable method for estimating the spatiotemporal distribution of AET in various watersheds. This information is vital for optimizing water use, irrigation planning, and sustainable water resource management.
An Android malware detection based on reconstructed API with TextCNN
Authors: Yang Jiyun , Jiang Jingtian , Wang Jianhui , Fan Jiawen , Xiang Tao 
Published: December 2024

Abstract

Most of machine learning-based Android malware detection methods use the application programming interface (API) as features. However, the effectiveness of API-based methods are often compromised by API changes during the evolution of the Android system. At the same time, most of these methods only use system APIs, so they cannot detect malicious apps that realize malicious behavior through third-party APIs. To address this problem, we have proposed an API names reconstruction method and have developed a feature selection approach that leverages the weights of these reconstructed names. Following this, we constructed a TextCNN-based Android malware detection model. To validate the robustness of our method against API changes, we conducted a series of cross-validation experiments using samples from different years. Comparison test also has been conducted, demonstrating that our detection method archives superior performance.
Tsunami Height Estimation via Gaussian Process Regression Using Maximum Absolute Pressure Change and Time from Seafloor Sensors off the Kii Peninsula, Japan
Authors: Iwabuchi Yutaro , Baba Toshitaka , Hori Takane , Okada Masato , Igarashi Yasuhiko 
Published: December 2024

Abstract

The Dense Ocean-floor Network for Earthquakes and Tsunamis (DONET) was recently installed to monitor tsunamis in the Nankai Trough. In this study, an advanced tsunami prediction model using Gaussian process regression that is suitable for seafloor pressure observations is proposed. In traditional approaches, only the maximum absolute pressure change recorded by seafloor pressure sensors was used as an explanatory variable. The proposed method includes the time when the maximum absolute pressure change is recorded as an explanatory variable. Because tsunami data observed by ocean observatories are insufficient for constructing Gaussian regression relationships, numerical tsunami simulations are used for learning and validation. After a tsunami is detected by DONET, the tsunami height prediction accuracy along the coast is increased by considering the time of the maximum absolute pressure change at seafloor pressure sensors. The proposed model enables rapid and effective estimation of coastal tsunami heights.
Multi-dimensional study of Lactate Dehydrogenase A (LDHA) as a Prognostic Indicator and Therapeutic Target in Head and Neck Squamous Cell Carcinoma
Authors: He# Youya , Zhao Xuri , Gu Weiyan , Wang Peng , Sun Wang , Fan Wenxian , Jin Bei , Lin Haisheng 
Published: December 2024

Abstract

Background: Head and neck squamous cell carcinoma (HNSCC) is a highly aggressive cancer type, showing a rising incidence worldwide. Lactate dehydrogenase A (LDHA), which is an essential enzyme involved in glycolysis, plays a significant role in the development of HNSCC, yet its clinical significance and therapeutic potential remain unclear.
Methods: We analyzed LDHA expression in HNSCC using multiple omics data, assessing diagnostic potential via ROC analysis and prognostic value through survival analysis. We explored LDHA-related biological pathways using GSEA and GO/KEGG analyses and investigated its impact on immune infiltration and associations with checkpoints.
Findings: There was a notable increase in LDHA expression in HNSCC, which was linked to a worse prognosis. Elevated levels of LDHA were associated with the infiltration of immune cells., particularly cytotoxic T lymphocytes, and was positively associated with PD-L1. In vitro, LDHA knockdown reduced HNSCC cell proliferation and invasion.
Conclusion: LDHA serves as a promising prognostic biomarker and a therapeutic target in HNSCC, highlighting its significance for immunotherapy. Additional studies are required to confirm these results and to investigate the function of LDHA in the biology of HNSCC.