bluuebunny/crossref_metadata_2025_split huggingface dataset:
In situ endoscopic photodynamic therapy combined with immature DC vaccination induces a robust T cell response against peritoneal carcinomatosis
Authors: Degavre Charline , Lepez Anouk , Ibanez Sebastien , François Clémence , Głowacka Katarzyna , Guilbaud Céline , Laloux-Morris Florine , Esfahani Hrag , Brusa Davide , Bouzin Caroline , Feron Olivier 
Published: November 2024

BackgroundImmunogenic cell death (ICD) and ferroptosis have recently emerged as key factors in the anticancer immune response. Among the treatments able to induce ICD and the associated release of danger signals is photodynamic therapy (PDT). Ferroptosis for its part results from lipid peroxidation and is induced by CD8+T cells to kill nearby cancer cells on IFN-γ production. We aimed to combine the two concepts, that is, to evaluate whether the strong pro-oxidant effects of PDT may promote ferroptosis and antigen release and to develop a procedure for in situ PDT to prepare the soil for highly endocytotic immature dendritic cell (iDC) adoptive transfer. This approach was implemented for managing peritoneal carcinomatosis, a lesion often associated with poor outcomes.MethodsWe used three-dimensional (3D) heterotypic spheroids made of cancer cells, exposed them to a white light-activated OR141 photosensitizer (PS), and subsequently complexified them by adding iDC and naive lymphocytes. We next used a model of mouse peritoneal carcinomatosis and administered PDT using laparoscopy to locally induce photoactivation using the endoscope light. The immune response following adoptive transfer of iDC was tracked both in vivo and ex vivo using isolated immune cells from in situ vaccinated mice.ResultsCancer cells undergoing PDT-induced cell death significantly increased ICD markers and the infiltration of iDCs in spheroids, relying on ferroptosis. These actions induced the sequential activation of CD8+and CD4+T cells as revealed by a significant spheroid 3D structure deterioration and, remarkably, were not recapitulated by conventional ferroptosis inducer RSL3. Using LED light from an endoscope for in situ photoactivation of PS enabled us to apply the vaccination modality in mice with peritoneal tumors. Consecutive intraperitoneal injection of iDCs resulted in delayed tumor growth, increased survival rates, and prevented tumor relapse on rechallenge. CD8+T cell response was supported by depletion experiments, nodal detection of early activated T cells, and ex vivo T cell-induced cytotoxicity toward spheroids.ConclusionsThe combination of in situ PDT locally delivered by an endoscope light and iDC administration induces a durable memory immune response against peritoneal carcinomatosis thereby opening new perspectives for the treatment of a life-threatening condition.
Phenomenology of an extended $$1+2$$ Higgs doublet model with $$S_3$$ family symmetry
Authors: Hernández A. E. Cárcamo , Salinas-Arizmendi Daniel , Vignatti Jonatan , Zerwekh Alfonso 
Published: November 2024

AbstractIn order to explain the mass hierarchy and mixing pattern in the leptonic sector, we explore an extension of the Standard Model whose scalar sector includes one active and two inert doublets as well as some scalar singlets. The model includes a $$S_3$$

S
3

family symmetry supplemented by extra cyclic symmetries. As a consequence of our construction, a Dark Matter (DM) candidate is predicted and its properties are consistent with the observed cosmic abundances and the constraints imposed by direct and indirect detection experiments. The model allows Charged Lepton Flavor Violation (CLFV) processes like $$\mu \rightarrow e\gamma $$

μ
→
e
γ

and $$\mu \rightarrow 3e$$

μ
→
3
e

, but the predicted branching ratios align with experimental limits. Additionally, our analysis elucidates the generation of the active neutrino masses through a one-loop radiative seesaw mechanism matching the observed neutrino oscillation data. The model agrees with experimental data on Higgs Diphoton decay rates and on oblique parameters.
How offline meetings affect online activities: the case of Wikipedia
Authors: Schwitter Nicole 
Published: November 2024

AbstractAs open-source communities and other peer production projects face the challenge of sustaining themselves over time, the role of offline gatherings in fostering community resilience becomes a vital question. This study centres on the potential of offline social interactions as a means to mitigate declines within such communities, using Wikipedia as a case example. Using a comprehensive dataset spanning informal meetups within the German-language Wikipedia community from 2001 to 2020 and combining it with large scale online activity data, this study investigates the relationship between offline gatherings and online contribution behaviour. Results show that attending meetups has a positive effect on contributing towards Wikipedia both in the short and long term. By shedding light on the significance of offline social interactions in bolstering online communities, this study offers valuable insights into potential strategies for sustaining collaborative online environments amidst broader declines and further shows how offline and online activities intertwine.
Shallower CNOT Circuits on Realistic Quantum Hardware
Authors: de Brugière Timothée Goubault , Martiel Simon 
Published: November 2024

We focus on the depth optimization of CNOT circuits on hardware with limited connectivity. We adapt the algorithm from Kutin et al. that implements any
n
-qubit CNOT circuit in depth at most
5n
on a Linear Nearest Neighbor architecture. Our proposal is a block version of Kutin et al.’s algorithm that is scalable with the number of interactions available in the hardware: the more interactions we have, the less the depth. We derive better theoretical upper bounds and provide a simple implementation of the algorithm. Overall, we achieve better depth complexity for CNOT circuits on some realistic quantum hardware like a grid or a ladder. For instance, the execution of an
n
-qubit CNOT circuit on a grid can be done in depth
4n+8
.
Scaling Terrain-Aware Spatial Machine Learning for Flood Mapping on Large Scale Earth Imagery Data
Authors: Adhikari Saugat , Yan Da , Jiang Zhe , Han Jiao , Xu Zelin , Zhang Yupu , Sainju Arpan , Zhou Yang 
Published: November 2024

The accurate and prompt mapping of flood-affected regions is important for effective disaster management, including damage assessment and relief efforts. While high-resolution optical imagery from satellites during disasters presents an opportunity for automated flood inundation mapping, existing segmentation models face challenges due to noises like cloud cover and tree canopies. Thanks to the digital elevation model (DEM) data readily available from sources such as United States Geological Survey (USGS), terrain guidance was utilized by recent graphical models such as hidden Markov trees (HMTs) to improve segmentation quality. Unfortunately, these methods either can only handle a small area where water levels at different locations are assumed to be consistent, or require restricted assumptions such as there is only one river channel.
This paper presents an algorithm for flood extent mapping on large-scale Earth imagery, applicable to a large geographic area with multiple river channels. Since water level can vary a lot from upstream to downstream, we propose to detect river pixels in order to partition the remaining pixels into localized zones, each with a unique water level. In each zone, water at all locations flow to the same river entry point. Pixels in each zone are organized by an HMT to capture water flow directions guided by elevations. Moreover, a novel regularization scheme is designed to enforce inter-zone consistency by penalizing pixel-pairs of adjacent zones that violate terrain guidance. Efficient parallelization is made possible by coloring the zone adjacency graph to identify zones and zone-pairs that have no dependency and hence can be processed in parallel, and incremental one-pass terrain-guided scanning is conducted wherever applicable to reuse computations. Experiments demonstrate that our solution is more accurate than existing solutions, and can efficiently and accurately map out flooding pixels in a giant area of size 24,805 × 40,129. Despite the imbalanced workloads caused by a few large zonal HMTs dominating the serial computing time, our parallelization approach is effective and manages to achieve up to 14.3 × speedup on a machine with Intel Xeon Gold 6126 CPU @ 2.60GHz (24 cores, 48 threads) using 32 threads.
Outcomes of Tamoxifen Treatment Alone in Patients With Ductal Carcinoma In Situ or Atypical Ductal Hyperplasia Who Refused Surgery
Authors: Kwak Youngji , Ryu Jai Min , Chae Byung Joo , Yu Jonghan , Kim Seok Won , Nam Seok Jin , Lee Jeong Eon 
Published: November 2024

Objective: Recent trends involving increased screening have led to broad populations being diagnosed with atypical ductal hyperplasia (ADH) or ductal carcinoma in situ (DCIS); as a result, many patients have had to receive surgery followed by standard treatment for ADH or DCIS. The common interest in reducing the use of superfluous invasive treatment has led us to question the necessity of surgical treatment for ADH or DCIS patients in a retrospective review. This work is expected to be a particularly useful reference as there have yet to be any studies describing the outcomes of initial treatment with tamoxifen without curative surgery in Korea.Methods: The clinicopathological characteristics and oncologic outcomes of 36 patients with DCIS or ADH diagnosis who received initial treatment with tamoxifen between 2013 and 2019 were investigated.Results: Among 36 patients enrolled, 30 were diagnosed with DCIS and six were diagnosed with ADH. The median age in the included cohort was 47 years old (range, 26–81 years). There was a change in the follow‐up strategy including the need for surgery in 13.9% of cases. The median time to surgery in those patients was 32 months (IQR, 17.5–63.5 months). Only one patient had upgraded to a higher nuclear grade, which was a case of ADH upgrading to intermediate DCIS. Three (8.3%) of 36 patients were upstaged to an invasive disease. Of them, two patients were upstaged to microinvasive ductal carcinoma, whereas one patient was diagnosed with metastatic invasive ductal carcinoma.Conclusion: The use of endocrine therapy without surgery could be a potential treatment strategy in patients with DCIS or ADH. Further validation in larger cohorts and in the context of clinical trials is needed.
Artemis’ Love and Care for Youths and Children. The Iconography of Artemis on Two Votive Reliefs of the Fourth Century BC from Tegea
Authors: Kapouranis Aeneas 
Published: November 2024

Abstract
This article looks at two reliefs that depict Artemis, in one case with a hero and in the other with two important gods. It is interesting to point out that both reliefs were found by chance at the beginning and the middle of the twentieth century near the modern village of Alea at Tegea. The first embedded in a wall of a Roman house and the other during excavations near the sanctuary of Athena and therefore it does not have the proper context of the relief’s original settings. The reliefs, both unique for their depictions, are two of the few examples from the Peloponnesian iconography of Artemis and reflect different local aspects of the goddess, who was regarded as a protector of the younger citizens and – together with Herakles and Dionysos – one of the main characters in one of Tegea’s most important heroic ancestors, Telephos. Most likely dating from the fourth century BC, they offer some new and essential information on the goddess’ iconography and her meaning both as a protector of future hoplites and as a ‘surrogate mother’, through her doe, during Telephos’ infancy, in a famous Peloponnesian city.
Cross-Modal Cues Improve the Detection of Synchronized Targets during Human Foraging
Authors: Makarov Ivan , Unnthorsson Runar , Kristjánsson Árni , Thornton Ian M. 
Published: November 2024

Abstract
In two experiments, we explored whether cross-modal cues can be used to improve foraging for multiple targets in a novel human foraging paradigm. Foraging arrays consisted of a 6 × 6 grid containing outline circles with a small dot on the circumference. Each dot rotated from a random starting location in steps of 30°, either clockwise or counterclockwise, around the circumference. Targets were defined by a synchronized rate of rotation, which varied from trial-to-trial, and there were two distractor sets, one that rotated faster and one that rotated slower than the target rate. In Experiment 1, we compared baseline performance to a condition in which a nonspatial auditory cue was used to indicate the rate of target rotation. While overall foraging speed remained slow in both conditions, suggesting serial scanning of the display, the auditory cue reduced target detection times by a factor of two. In Experiment 2, we replicated the auditory cue advantage, and also showed that a vibrotactile pulse, delivered to the wrist, could be almost as effective. Interestingly, a visual-cue to rotation rate, in which the frame of the display changed polarity in step with target rotation, did not lead to the same foraging advantage. Our results clearly demonstrate that cross-modal cues to synchrony can be used to improve multitarget foraging, provided that synchrony itself is a defining feature of target identity.
Enhancing the Rainfall Forecasting Accuracy of Ensemble Numerical Prediction Systems via Convolutional Neural Networks
Authors: Lin Kuan-Cheng , Chen Wan-Ting , Chang Pao-Liang , Ye Zhi-Yuan , Tsai Chin-Cheng 
Published: November 2024

Abstract
Ensemble prediction systems are commonly used to demonstrate the potential uncertainty of weather forecasts. These systems also help provide weather predictions to prepare for disasters. Specifically, a type of prediction called a quantitative precipitation forecast (QPF) is calculated from the average of multiple forecasts. The probability-matched mean (PMM) method is used to improve these QPF predictions when they underestimate rainfall. However, the PMM method can exhibit limitations when dealing with certain types of rain patterns. To address this issue, this study focuses on improving short-term heavy rainfall predictions using an artificial intelligence (AI) algorithm that combines deep neural networks (DNNs), including convolutional neural networks (CNNs), with a space-based attention mechanism [convolutional block attention module (CBAM)]. Four experiments were conducted to evaluate the new method, including those performed to optimize the timing of a 24-h QPF model, adjust the training dataset, and refine the training algorithm. Two specific weather events were assessed: rainfall influenced by southwest winds after typhoons and afternoon thunderstorm rainfall. A comparison of the results obtained via the root-mean-square error (RMSE) and structural similarity index measure (SSIM) reveals significant improvements in both accuracy and distribution of the QPF predictions over those of the PMM method. Compared with the PMM method, our approach can reduce the RMSE from 77.51 to 19.52 in the mei-yu case, an improvement of approximately 74.82%. The SSIM also increased from 0.33 to 0.56, indicating a 70.9% enhancement. Overall, the new approach successfully enhances rainfall prediction accuracy via AI techniques and has the potential to be applied in disaster preparedness operations.

Significance Statement
An ensemble prediction system is a tool that is often used to showcase the uncertainty inherent in numerical weather forecasts and to provide critical insights for disaster preparedness. This study attempts to enhance the short-term predictions produced for intense rain events by integrating an AI algorithm, which exploits the advantages of deep neural networks (DNNs), such as convolutional neural networks (CNNs) with a space-based attention mechanism. The methodology underwent rigorous testing, including lead time optimization, training data sensitivity assessment, and algorithm refinement. When applied to weather events, such as rainfall patterns influenced by posttyphoon southwestern winds and afternoon thunderstorms, this approach outperforms traditional methods, as evidenced by verification metrics, such as the RMSE and SSIM. This research introduces an innovative framework that leverages artificial intelligence (AI) and DNNs to achieve enhanced rainfall prediction accuracy, which is a critical advancement for effective disaster readiness.
Unraveling the Relationships between Trend of Dam Inflows, Hydrometeorological Variables, and Vegetation in Western and Southwestern United States
Authors: Cho Eunsaem , Ahmadisharaf Ebrahim , Ahmadisharaf Amin , Nematirad Reza , AghaKouchak Amir 
Published: November 2024

Abstract
This paper explored temporal changes in magnitude and seasonality of low, median, and high inflows of 51 dams across the western and southwestern United States over the 1993–2022 period. Changes in precipitation, air temperature (an indicator of snowpack and evaporation), soil moisture, and vegetation were also examined to identify potential reasons for the temporal trends in dam inflows. Using monotonic and nonmonotonic tests, we found a general downward trend in dam inflows, particularly across the Upper Colorado and California regions. More than 30% of the dams showed a downward trend in their annual median inflows, high inflows during spring, and median inflows during fall. The downward trend of dam inflows was associated with decreasing precipitation and soil moisture and increasing temperatures. While vegetation exhibited positive associations with inflows, it did not seem to be a primary factor for explaining the inflow trends. We also observed shifts in the seasonality of low and high inflows; there was an increase in the proportion of inflows occurring during summer and fall and a decrease in winter proportions for low inflows. Similarly, high inflows exhibited an increase in spring proportions and a decrease in fall proportions. Our changepoint analyses detected nonmonotonic trends between 2002 and 2012 in ∼13% of the dams; the majority were located in the Upper Colorado and California regions. More than half of these changepoints were in 2011, likely due to widespread droughts then. Our study has implications for reservoir managers to identify changes that dams experience over time and assist them in proposing actions that maintain the dams’ functionality.
A qualitative study exploring occupational therapist’s experiences of delivering interventions to patients in seclusion whilst working as part of a multi-disciplinary team
Authors: Bowser Anita , Harwood Beth , Wright Rachael , Donovan-Hall Maggie 
Published: November 2024

Introduction: Although occupational therapists work within mental health settings, there is limited research regarding their role in seclusion. This study aims to explore occupational therapists’ experiences of delivering occupational therapy in seclusion whilst working as part of a multi-disciplinary team. Method: An exploratory qualitative approach using a semi-structured virtual interview approach was adopted. A convenience sample of six participants with experience of working in inpatient mental health seclusions settings were recruited at a national level. Interviews were recorded, transcribed verbatim and analysed using reflexive thematic analysis. Findings: Four key themes were identified: (1) the perception of seclusion as a punitive approach, (2) the role of occupational therapy in improving the patient’s journey through seclusion, (3) grading and adapting occupations to manage risk and increase engagement, and (4) promoting the role of occupational therapy in seclusion. Conclusion: Occupational therapists can play an important role in improving the experience of patients in seclusion. They have unique skills that enable them to work in this challenging environment. It has also highlighted the lack of understanding about occupational therapy within the multi-disciplinary team and how important it is for occupational therapists to promote their role.
Association among therapeutic adherence, health literacy, and engagement in care: How to increase health-conscious management of HIV disease
Authors: Massaroni Valentina , Delle Donne Valentina , Salvo Pierluigi Francesco , Farinacci Damiano , Iannone Valentina , Baldin Gianmaria , Ciccarelli Nicoletta , Di Giambenedetto Simona 
Published: November 2024

Background In the context of People Living with HIV (PLWH), poor health literacy (HL) seems to be linked to poorer health outcomes and reduced engagement in care. Additionally, the level of HL can affect HIV knowledge and may impact adherence to antiretroviral therapy (ART). This research explored the connection between ART adherence, HL, and engagement in care in a cohort of 250 PLWH receiving ART in Italy. Methods A questionnaire was given to PLWH at Policlinico Gemelli in Rome to assess their health literacy and adherence to therapy. The Brief Health Literacy Screening (BHLS) and the Newest Vital Sign (NVS) were used to evaluate subjective and objective HL. Adherence levels were self-reported as poor, good, or excellent, and the assessment included the Patient Health Engagement Scale (PHE-S). Results Notably, the majority of the sample comprised male individuals (67.9%), with 69.2% reporting a 10-years or longer duration between their HIV diagnosis and their initiation of ART. It was found that PLWH with poor adherence had low schooling, had been living with HIV for 1–5 years, were HCV co-infected, had a viremia >50 copies/mL, poor health status, poor engagement in care, and poor HL ( p = <0.001). They exhibited lower mean scores on the subjective HL scale and lower CD4 T-cell counts and nadir CD4 T-cell counts ( p < .001). Conclusion Our study demonstrated a positive correlation between higher HL levels and improved disease management, treatment adherence, and overall physical and mental well-being. Enhanced HL capabilities are paramount in bolstering health management and treatment adherence.
How Advocates Can Support Young Adults Living With Cancer and Their Transition to Palliative Care
Authors: Drake Emily K. , Weeks Lori E. , van Manen Michael , Taylor Dani , Ricci Ian , Curran Janet 
Published: November 2024

While the cancer advocacy community has been pivotal in progressing oncology care, supporting young adults with advanced cancer transitioning to palliative care continues to be a complex challenge. Palliative care services may not be offered by healthcare providers or engaged by young people themselves. This is in the face of the recognized value that palliative care can provide young people and their families. The purpose of this study was to explore what cancer advocates can do to support young adults (18–39 years of age) with advanced cancer in their transition to palliative care. A community-based research perspective supported engagement with members of the #AYACSM (Adolescent and Young Adult Cancer Societal Movement) from the United States and Canada through social media. Analysis was guided by a reflexive thematic analysis approach to articulate four action-oriented themes: advocate for advances in the delivery of care; support healthcare provider education; mobilize knowledge and share stories; and leverage technology for advocacy efforts. Young adult cancer advocacy must span the continuum of cancer care from prevention to end-of-life. There exist gaps in advocacy efforts surrounding support for young people in their transition to and the integration of palliative care services. Creative and innovative advocacy approaches are needed. This study also showed opportunities for conducting qualitative research through an existing online community as an approach conducive to community-based research.