bluuebunny/crossref_metadata_2025_split huggingface dataset:
Episodic Question Answering for Cognitive Agents
Authors: Singh Shweta , Seshadri Shraddha 
Published: May 2024

Abstract

As the demand for artificial intelligence robots and cognitive agents increases, it becomes essential for these agents to comprehend previous encounters and respond to inquiries based on their past experiences. In essence, they need to maintain their memories in an episodic manner. This paper presents a novel approach to address this demand by leveraging the real-life experiences of robots to enrich their knowledge base. To achieve this goal, we employ diverse artificial intelligence techniques, including computer vision, multimodal cross embeddings, speech processing, and generative AI. These methods are utilised to establish a knowledge base that functions as memories for an agent, enabling it to maintain a memory akin to that of a human.To ensure comprehensive memory retention, an agent encounters diverse scenarios such as interacting with individuals, observing conversations, and visiting various locations. To maintain a robust visual and linguistic knowledge base encompassing these experiences, we employ techniques like scene graphs, along with the aforementioned AI methodologies. Existing approaches that involve understanding language and vision used in problem statements such as video question answering, dialogue understanding, or world understanding often overlook the temporal order in which events are observed by the agent or may be restricted to the set of characters or the world in which it has been trained. They struggle to effectively retrieve memories and generate meaningful answers based on this chronological context or in cases where we may rely on a number of past experiences which may reason an event that happened in the future. So, in our study, we've worked on building a solid knowledge base and a way for an agent to remember and link events, just like people do.In conclusion, our work aims to make AI more like humans by helping agents remember and understand events better. This could lead to smarter AI systems that adapt well to different situations in the real world.
Zinc Manganite as an Efficient Battery-grade Material for Supercapattery Devices
Authors: Nagaraja Pernapati , Rao H. Seshagiri , Rao G. Ranga , Justin Ponniah 
Published: May 2024

Abstract

In the current context, supercapatteries emerge as highly desirable candidates capable of merging both energy and power density within a single device. Battery-type metal oxide materials, combined with capacitive-based materials, stand out as promising candidates for high-performance supercapatteries. This investigation centers on the synthesis of nanocrystalline ZnMn2O4 (ZMO) and CoMn2O4 (CMO) through a straightforward hydrothermal method, followed by their physico-electrochemical characterization. Electrochemical analysis reveals that ZMO exhibits notably enhanced charge storage capability compared to CMO. This superiority can be attributed to favourable electro-structural properties, and stable redox chemistry of ZMO. The real-time performance of ZnMn2O4 was further assessed by fabricating a hybrid asymmetric supercapattery device (ZnMn2O4||NrGO), which achieves a specific capacity of 232 C g− 1 at a current density of 1 A g− 1. The hybrid asymmetric device underwent rigorous stability testing for 4000 cycles at a current density of 2 A g− 1, showcasing remarkable performance with a 92% retention of its initial capacity. The device demonstrated a power density of 10 kW kg− 1 and an energy density of 22 W h kg− 1, highlighting its considerable promise in the field.
Targeting RACGAP1 Suppresses Growth Hormone Pituitary Adenoma Growth
Authors: Sun Feifan , Ji Chenxing , Zhou Xiang , Zhang Yichao , Cheng Haixia , Ye Zhao 
Published: May 2024

Abstract

Purpose: Growth hormone pituitary adenoma (GHPA) is a major subtype of pituitary adenoma (PA), with tumor enlargement and abnormal secretion of growth hormone (GH) often causing complications. Rac GTPase-activating protein 1 (RACGAP1), a member of the guanine triphosphatase-activating protein family, is highly overexpressed in multiple tumors and promotes tumor growth. However, the role of RACGAP1 in GHPA remains unelucidated. Besides, specific inhibitors targeting RACGAP1 have not yet been developed. In this study, we aimed to determine the expression and function of RACGAP1 in GHPA and identify effective inhibitors against RACGAP1.
Methods: Immunohistochemistry was used to detect the expression of RACGAP1 in GHPA and normal pituitary tissues. The effect of RACGAP1 on cell proliferation, apoptosis, and cell cycle was evaluated by knockdown of RACGAP1 in GH3 cells in vitro and xenograft models of GHPA in vivo. The downstream mechanism of RACGAP1 was explored by RNA sequencing, bioinformatic analysis, and Western blot. Inhibitors targeting RACGAP1 were screened and verified through a structure-based virtual docking method, cell viability assays, and surface plasmon resonance (SPR) experiments.
Results: RACGAP1 expression was increased in GHPA compared with normal pituitary tissues. Knocking down RACGAP1 suppressed cell growth in vitro and in vivo. Preliminary mechanism studies indicated that inhibition of RACGAP1 led to the upregulation of p21 and the downregulation of several genes involved in the cell cycle signaling pathway, such as Cyclin A, CDK1, and CDK2. Moreover, DB07268 was identified for the first time as an effective RACGAP1 inhibitor that could prominently restrain the proliferation of GH3 cells.
Conclusion: This study demonstrates that RACGAP1 plays a critical role in GHPA, highlighting the novel inhibitor DB07268 as a promising therapeutic approach.
TourOptiGuide: A Hybrid and Personalized Tourism Recommendation System
Authors: Intissar Hilali , Nouha Arfaoui , Ridha Ejbali 
Published: May 2024

Abstract

When visitors explore a city briefly, they must prioritize the key attractions that align with their interests. These significant points of interest (POIs) can be chosen based on specific criteria tailored to their needs. Additionally, travellers venturing into unfamiliar regions often seek help to plan their itinerary. To address this issue, we developed and presented a novel hybrid and personalized recommendation system aimed at helping tourists choose their next POI. The system tailors its suggestions based on four key factors: the tourist's current location, single preferences, age, and historical experiences. Deep learning models play a crucial role in identifying the tourist's current location from images and predicting age from selfies. In addition, our system leverages a trajectory data warehouse containing extensive historical data of past tourist’s experiences to provide suggestions. The core of our recommendation strategy is a fuzzy logic decision support system. This system effectively synthesizes diverse inputs to produce the top next POI to visit. By integrating various recommendation methods, our hybrid system significantly improves the precision and pertinence of its recommendations, offering a more customized and effective travel experience. Preliminary results demonstrate significant improvements in tourist satisfaction and in the efficiency of itinerary planning.
Effects of heating mediums on microstructure and chemical properties of thermally modified Matoa
Authors: Caishan Ling , Chenyang Cai , xianqing Xiong , Yunfang Shen 
Published: May 2024

Abstract

Thermal modification (TM) is considered to be the most environmentally friendly and effective industrial method to reduce the hygroscopicity of wood. However, different heating mediums of TM often results in various performance. In this study, the changes of microstructure, crystallization, chemical composition and equilibrium moisture content (EMC) of thermally modified wood (TMW) were investigated respectively to explore the effects of heating mediums (saturated steam, superheated steam, air), modification temperature and water leaching post-treatment on TMWs. The results showed the general intensity of TM was in the order of: saturated steam > superheated steam > air. Saturated steam induced severer cell wall destruction than the other two mediums. Although the porosity slightly increased with the increasing TM temperature and leaching treatment, superheated steam and air TM still decreased the porosity compared to that of control, whereas saturated steam TM increased the porosity apparently. Although TM increased both relative crystallinity and crystal size of TMWs. The increasing TM temperature slightly increased the relative crystallinity, but decreased the crystal size. Leaching caused opposite changes in crystal size of TMWs with different heating mediums. The highest crystallinity was observed after saturated steam TM. The increase in relative amount of lignin and cellulose due to the hemicellulose degradation was the main chemical changes of TMWs, further lignin condensation reaction was occurred after saturated steam TM. Although saturated steam TM induced increased porosity, its lowest EMC indicated the decrease of hydroxyl groups was the dominate reason for the decreased hygroscopicity than the changes of microstructure.
scDFN: Enhancing single-cell RNA-seq Clustering with Deep Fusion Networks
Authors: Liu Tianxiang , Bi Yue , Guo Xudong , Zou Quan , Jia Cangzhi , Li Fuyi 
Published: May 2024

Abstract

Single-cell RNA sequencing (scRNA-seq) technology can be used to perform high-resolution analysis of the transcriptomes of individual cells. Therefore, its application has gained popularity for accurately analyzing the ever-increasing content of heterogeneous single-cell datasets. Central to interpreting scRNA-seq data is the clustering of cells to decipher transcriptomic diversity and infer cell behavior patterns. Although clustering plays a key role in the subsequent analysis of single-cell transcriptomics, its complexity necessitates the application of advanced methodologies capable of resolving the inherent heterogeneity and limited gene expression characteristics of single-cell data. In this study, we introduced a novel deep learning-based algorithm for single-cell clustering, designated scFCN, which can significantly enhance the clustering of scRNA-seq data through a fusion network strategy. The scFCN algorithm applies a dual mechanism involving an autoencoder to extract attribute information and an improved graph autoencoder to capture topological nuances, integrated via a cross-network information fusion mechanism complemented by a triple self-supervision strategy. This fusion is optimized through a holistic consideration of four distinct loss functions. A comparative analysis with five leading scRNA-seq clustering methodologies across multiple datasets revealed the superiority of scFCN, as determined by better Normalized Mutual Information (NMI) and Adjusted Rand Index (ARI) metrics. Additionally, scFCN demonstrated robust multi-cluster dataset performance and exceptional resilience to batch effects. Ablation studies highlighted the key roles of the autoencoder and the improved graph autoencoder components, along with the critical contribution of the four joint loss functions to the overall efficacy of the algorithm. Through these advancements, scFCN set a new benchmark in single-cell clustering and can be used as an effective tool for the nuanced analysis of single-cell transcriptomics. The source code of scFCN is publicly available at https://github.com/11051911/scDFN.
Landslide Susceptibility Mapping Using Information Value Model with GIS in Wegeda Area, Northwestern Ethiopia
Authors: Mersha Tilahun 
Published: May 2024

Abstract

The geological and physiographical conditions have made Guna Mountain one of the area’s most vulnerable to disaster since it is a part of the northwestern highlands of Ethiopia. Parts of the Wegeda area are characterized by weathered volcanic rocks, rugged morphology with deeply incised gorges, heavy rainfall, and active surface processes. Many landslide events are frequently occurring in the studied area, mostly triggered by heavy seasonal rainfall and human activity, causing deaths and severe infrastructure damage to the local people. In this study, Information Value (IV) Model was applied to evaluate the landslide causative factors and generate a landslide susceptibility map (LSM). To do this, intensive fieldwork and Google Earth image interpretations were done on active and passive landslide scarps and produced a reliable landslide inventory map. These landslide locations were randomly divided into 80% training and 20% validation datasets. Seven landslide governing factors were combined with a training dataset using GIS tools to generate the LSM of the study area. Then the area was divided into five landslide susceptibility classes: very low, low, moderate, high, and very high. Later, the resulting map has been validated by using the area under the curve (AUC) and landslide density index methods for both the training and validation landslide datasets. According to the AUC graph, the IV model had a success rate and a predictive rate value of 82.4% and 78.3% respectively. This indicated that the produced LSM showed reasonable performance. Finally, the LSM produced by the IV model can be used by decision-makers for land use planning and landslide mitigation purpose.
Qualitative Interferon-γ Release Assay for Predicting Response to BCG instillations in Bladder Cancer
Authors: Köseoğlu Hikmet , Yalçın Berrin , Yücetaş Uğur , Eroğlu Tolga , Mungan Uğur 
Published: May 2024

Abstract

Background This study aims to fill the void in predictive markers for BCG instillation responsiveness in high-risk non-muscle invasive bladder cancer. Focusing on elevated progression risk, it explores the potential of the qualitative interferon-γ release assay T-spot, emphasizing CFP-10 positivity as a marker for BCG efficacy anticipation.
Objective This study aims to investigate the potential of qualitative interferon-γ release assay T-spot testing, specifically focusing on CFP-10 positivity, in predicting the response to intracavitary BCG instillations among patients with high-risk non-muscle invasive bladder cancer.
Materials and Methods Patients with NMIBC were recruited from the database retrospectively and tested with T-spot prospectively. Following sufficient BCG instillations, patients demonstrating unresponsiveness to BCG were designated as the study group, while those with at least one year of recurrence-free status were assigned to the control group.
ResultsIn this cohort of 42 high-risk NMIBC patients, with a median age of 67, 40% displayed BCG unresponsiveness. The distribution included 50% pTa and 81% high-grade cases. Over a median follow-up of 18 months, the positive BCG response varied between pTa (81%) and pT1 (38%) (p=0.005). T-spot testing revealed positivity in 75% of the control group and a higher 92% in BCG unresponsive patients (p=0.235). Significantly, CFP-10 positivity was more pronounced in the BCG unresponsive group at 91.7%, in contrast to 35.7% in the control group (p=0.004).
Conclusions CFP-10 positivity T-spot test may be a marker for predicting the response to BCG instillations.
Development of Micro/Nano Pattern Arrays with Grating-Based Periodic Structures using the Direct Laser Lithography System
Authors: Rajan Rency , Kirubaraj Alfred , Samson Senith , Prince Shajin , Ramson S.R. Jino 
Published: May 2024

Introduction:
This research delves into utilizing the Direct Laser Lithography System
to produce micro/nanopattern arrays with grating-based periodic structures. Initially, refining the
variation in periodic structures within these arrays becomes a pivotal pursuit. This demands a
deep comprehension of how structural variation aligns with specific applications, particularly in
photonics and material science.

Methods:
Advancements in hardware, software, or process optimization techniques hold potential
for reaching this objective. Using an optical beam, this system enables the engraving of moderate periodic and quasi-periodic structures, enhancing pattern formation in a three-dimensional
environment. Through cost-effective direct-beam interferometry systems utilizing 405 nm GaN
and 290 to 780 nm AlInGaN semiconductor laser diodes, patterns ranging from in period were
created, employing 300 nm gratings.

Results:
The system's cost-efficiency and ability to achieve high-resolution permit the creation of
both regular and irregular grating designs. By employing an optical head assembly from a bluray disc recorder, housing a semiconductor laser diode and an objective lens with an NA of 0.85,
this system displays promising potential in progressing the fabrication of micro/nanopattern
arrays.

Conclusion:
Assessing their optical, mechanical, and electrical properties and exploring potential applications across varied fields like optoelectronics, photovoltaics, sensors, and biomedical
devices represent critical strides for further exploration and advancement.
Monitoring Adolescent and Young Adult Patients With Cancer via a Smart T-Shirt: Prospective, Single-Cohort, Mixed Methods Feasibility Study (OncoSmartShirt Study)
Authors: Steen-Olsen Emma Balch , Pappot Helle , Hjerming Maiken , Hanghoej Signe , Holländer-Mieritz Cecilie 
Published: May 2024

Abstract

Background
Wearables that measure vital parameters can be potential tools for monitoring patients at home during cancer treatment. One type of wearable is a smart T-shirt with embedded sensors. Initially, smart T-shirts were designed to aid athletes in their performance analyses. Recently however, researchers have been investigating the use of smart T-shirts as supportive tools in health care. In general, the knowledge on the use of wearables for symptom monitoring during cancer treatment is limited, and consensus and awareness about compliance or adherence are lacking.

Objectives
The aim of this study was to evaluate adherence to and experiences with using a smart T-shirt for the home monitoring of biometric sensor data among adolescent and young adult patients undergoing cancer treatment during a 2-week period.

Methods
This study was a prospective, single-cohort, mixed methods feasibility study. The inclusion criteria were patients aged 18 to 39 years and those who were receiving treatment at Copenhagen University Hospital - Rigshospitalet, Denmark. Consenting patients were asked to wear the Chronolife smart T-shirt for a period of 2 weeks. The smart T-shirt had multiple sensors and electrodes, which engendered the following six measurements: electrocardiogram (ECG) measurements, thoracic respiration, abdominal respiration, thoracic impedance, physical activity (steps), and skin temperature. The primary end point was adherence, which was defined as a wear time of >8 hours per day. The patient experience was investigated via individual, semistructured telephone interviews and a paper questionnaire.

Results
A total of 10 patients were included. The number of days with wear times of >8 hours during the study period (14 d) varied from 0 to 6 (mean 2 d). Further, 3 patients had a mean wear time of >8 hours during each of their days with data registration. The number of days with any data registration ranged from 0 to 10 (mean 6.4 d). The thematic analysis of interviews pointed to the following three main themes: (1) the smart T-shirt is cool but does not fit patients with cancer, (2) the technology limits the use of the smart T-shirt, and (3) the monitoring of data increases the feeling of safety. Results from the questionnaire showed that the patients generally had confidence in the device.

Conclusions
Although the primary end point was not reached, the patients’ experiences with using the smart T-shirt resulted in the knowledge that patients acknowledged the need for new technologies that improve supportive cancer care. The patients were positive when asked to wear the smart T-shirt. However, technical and practical challenges in using the device resulted in low adherence. Although wearables might have potential for home monitoring, the present technology is immature for clinical use.
Knowledge, Skills, and Experience With Technology in Relation to Nutritional Intake and Physical Activity Among Older Adults at Risk of Falls: Semistructured Interview Study
Authors: Kikkenborg Julie , Magelund Emma , Riise Maria Silke , Kayser Lars , Terp Rikke 
Published: May 2024

Background
More than one-third of older adults (aged ≥65 y) experience falls every year. The prevalent modifiable risk factors for falling are malnutrition and physical inactivity, among others. The involvement of older adults in the prevention of falls can decrease injuries, hospitalizations, and dependency on health care professionals. In this regard, eHealth can support older adults’ self-management through more physical activity and adequate food intake. eHealth must be tailored to older adults’ needs and preferences so that they can reap its full benefits. Therefore, it is necessary to gain insight into the knowledge, skills, and mindset of older adults living at home who are at risk of falls regarding eHealth.

Objective
This qualitative study aims to explore older adults’ use of everyday digital services and technology and how they acquire knowledge about and manage their nutritional intake and physical activity in relation to their health.

Methods
Semistructured interviews were conducted with 15 older adults (n=9, 60% women; n=6, 40% men; age range 71-87 y) who had all experienced falls or were at risk of falling. These individuals were recruited from a geriatric outpatient clinic. The interviews were analyzed using deductive content analysis based on a modification of the Readiness and Enablement Index for Health Technology framework.

Results
The qualitative data showed that the informants’ social networks had a positive impact on their self-management, use of technology, and mindset toward nutritional intake and physical activity. Although the informants generally lived active lives, they all lacked knowledge about how their food intake influenced their physical health, including their risk of falling. Another finding was the large diversity in the use of technology among the informants, which was related to their mindset toward technology.

Conclusions
Older adults can use technology for everyday purposes, but some need additional introduction and support to be able to use it for managing their health. They also need to learn about the importance of proper nutritional intake and physical activity in preventing falls. Older adults need a more personalized introduction to technology, nutrition, and physical activity in their contact with health professionals.