bluuebunny/crossref_metadata_2025 huggingface dataset:
On computing the closures of solvable permutation groups
Authors: Ponomarenko Ilia , Vasil’ev Andrey V.
Published: January 2024

Let [Formula: see text] be an integer. It is proved that the m-closure of a given solvable permutation group of degree n can be constructed in time [Formula: see text].
A particle method for non-local advection–selection–mutation equations
Authors: Alvarez Frank Ernesto , Guilberteau Jules
Published: January 2024

The well-posedness of a non-local advection–selection–mutation problem deriving from adaptive dynamics models is shown for a wide family of initial data. A particle method is then developed, in order to approximate the solution of such problem by a regularized sum of weighted Dirac masses whose characteristics solve a suitably defined ODE system. The convergence of the particle method over any finite interval is shown and an explicit rate of convergence is given. Furthermore, we investigate the asymptotic-preserving properties of the method in large times, providing sufficient conditions for it to hold true as well as examples and counter-examples. Finally, we illustrate the method in two cases taken from the literature.
Weak solutions to the heat conducting compressible self-gravitating flows in time-dependent domains
Authors: Bhandari Kuntal , Huang Bingkang , Nečasová Šárka
Published: January 2024

In this paper, we consider the heat-conducting compressible self-gravitating fluids in time-dependent domains, which typically describe the motion of viscous gaseous stars. The flow is governed by the 3D Navier–Stokes–Fourier–Poisson equations where the velocity is supposed to fulfill the full-slip boundary condition and the temperature on the boundary is given by a non-homogeneous Dirichlet condition. We establish the global-in-time weak solution to the system. Our approach is based on the penalization of the boundary behavior, viscosity, and the pressure in the weak formulation. Moreover, to accommodate the non-homogeneous boundary heat flux, the concept of ballistic energy is utilized in this work.
Elementary computation of the Jones polynomials for Torus links modulo primes
Authors: Kim Joonoh , Kim Kyoung-Tark
Published: January 2024

We present simple congruences modulo [Formula: see text] of the Jones polynomial for the torus link [Formula: see text], where [Formula: see text] is a prime number and [Formula: see text] is a nonzero integer. These congruences are expressed in terms of Chebyshev polynomials and quantum numbers. The approach makes elementary use of the Kauffman bracket and does not require any representation theory.
A Super Hydrophilic Material for Self-Cleaning by Cold Plasma of Zinc Selenite Nanostructure
Authors: Khalaf Sura Y. , Abdalameer Nisreen Kh. , Hussain Tamara S.
Published: January 2024

This research is devoted to the fabrication of zinc selenide nanostructures using the pulsed laser deposition (PLD) technique in a vacuum under a pressure of [Formula: see text] mbar. The structure and structural properties were studied, as it was observed that it had polycrystalline structures and showed peaks for zinc and selenium and peaks belonging to the compound zinc selenide. As for the morphological characteristics of the nanostructures, the structures showed the nature of the surface and the roughness to identify its surface properties. Photocatalysis was carried out using several techniques (visible light, ultraviolet radiation and cold plasma), where a plasma jet system produced under normal atmospheric pressure was used in the treatment, with an exposure time of 4[Formula: see text]min and an argon gas flow rate of 3[Formula: see text]l/min. The hydrophilic properties were studied to apply these compositions in the self-cleaning process and photocatalytic activity. The results show that the ZnSe nanostructures have high wettability under UV light which has been shown to have excellent catalysis in the UV region, making its application as a self-cleaning material an attractive option.
THE IMPACT OF CLIMATE CHANGE ON THE RISK-TAKING LEVEL OF CHINESE COMMERCIAL BANKS: EMPIRICAL EVIDENCE FROM CHINESE LOCAL COMMERCIAL BANKS
Authors: SONG YUEGANG , CHEN WENYUAN , ZHANG KANYU
Published: January 2024

China’s risk disasters caused by climate change have increased the risk-taking level of China’s commercial banks, posing a threat to the stable development of financial markets. Based on the data from 152 commercial banks in China from 2011 to 2021, this paper uses the fixed effect model to analyze the effect and mechanism of China’s climate change on the risk-taking level of Chinese commercial banks. The main conclusions are as follows. (1) Climate change has significantly improved the risk-taking level of Chinese commercial banks. The results remain significant under the robustness and endogenous tests, such as dealing with endogenous problems, changing variables and adjusting sample intervals. (2) The results of heterogeneity analysis show that under different regions and different types of conditions, the impact of climate change on the risk-taking level of China’s commercial banks is heterogeneous, and the impact is stronger in urban commercial banks and eastern China. (3) The direct economic losses caused by natural disasters caused by climate change affect the risk-taking level of Chinese commercial banks; however, the adjustment of ex ante disaster insurance can weaken the impact of climate change on the risk-taking level of Chinese commercial banks. This paper studies the impact of climate change on the risk-taking level of Chinese commercial banks from the perspective of bank risk-taking level, which is of great significance to enhance the risk prevention awareness of Chinese commercial banks in response to climate change.
SurfShare
Authors: Huang Xincheng , Xiao Robert
Published: January 2024

Shared Mixed Reality experiences allow two co-located users to collaborate on both physical and digital tasks with familiar social protocols. However, extending the same to remote collaboration is limited by cumbersome setups for aligning distinct physical environments and the lack of access to remote physical artifacts. We present SurfShare, a general-purpose symmetric remote collaboration system with mixed-reality head-mounted displays (HMDs). Our system shares a spatially consistent physical-virtual workspace between two remote users, anchored on a physical plane in each environment (e.g., a desk or wall). The video feed of each user's physical surface is overlaid virtually on the other side, creating a shared view of the physical space. We integrate the physical and virtual workspace through virtual replication. Users can transmute physical objects to the virtual space as virtual replicas. Our system is lightweight, implemented using only the capabilities of the headset, without requiring any modifications to the environment (e.g. cameras or motion tracking hardware). We discuss the design, implementation, and interaction capabilities of our prototype, and demonstrate the utility of SurfShare through four example applications. In a user experiment with a comprehensive prototyping task, we found that SurfShare provides a physical-virtual workspace that supports low-fi prototyping with flexible proxemics and fluid collaboration dynamics.
Reenvisioning Patient Education with Smart Hospital Patient Rooms
Authors: Dawson Joshua , Phanich K. Jens , Wiese Jason
Published: January 2024

Smart hospital patient rooms incorporate various smart devices to allow digital control of the entertainment --- such as TV and soundbar --- and the environment --- including lights, blinds, and thermostat. This technology can benefit patients by providing a more accessible, engaging, and personalized approach to their care. Many patients arrive at a rehabilitation hospital because they suffered a life-changing event such as a spinal cord injury or stroke. It can be challenging for patients to learn to cope with the changed abilities that are the new norm in their lives. This study explores ways smart patient rooms can support rehabilitation education to prepare patients for life outside the hospital's care. We conducted 20 contextual inquiries and four interviews with rehabilitation educators as they performed education sessions with patients and informal caregivers. Using thematic analysis, our findings offer insights into how smart patient rooms could revolutionize patient education by fostering better engagement with educational content, reducing interruptions during sessions, providing more agile education content management, and customizing therapy elements for each patient's unique needs. Lastly, we discuss design opportunities for future smart patient room implementations for a better educational experience in any healthcare context.
SweatSkin
Authors: Lee Chi-Jung , Yang David , Ku Pin-Sung , Kao Hsin-Liu Cindy
Published: January 2024

Sweat sensing affords monitoring essential bio-signals tailored for various well-being inspections. We present SweatSkin, the fabrication approach for customizable sweat-sensing on-skin interfaces. SweatSkin is unique in exploiting on-skin microfluidic channels to access bio-fluid secretes within the skin for personalized health monitoring. To lower the barrier to creating skin-conformable microfluidics capable of collecting and analyzing sweat, four fabrication methods utilizing accessible materials are proposed. Technical characterizations of paper- and polymer-based devices indicate that colorimetric analysis can effectively visualize sweat loss, chloride, glucose, and pH values. To support general to extreme sweating scenarios, we consulted five athletic experts on the SweatSkin devices' customization guidelines, application potential, and envisioned usages. The two-session fabrication workshop study with ten participants verified that the four fabrication methods are easy to learn and easy to make. Overall, SweatSkin is an extensible and user-friendly platform for designing and creating customizable on-skin sweat-sensing interfaces for UbiComp and HCI, affording ubiquitous personalized health sensing.
A User-Centered Framework to Empower People with Parkinson's Disease
Authors: Rahman Wasifur , Abdelkader Abdelrahman , Lee Sangwu , Yang Phillip , Islam Md Saiful , Adnan Tariq , Hasan Masum , Wagner Ellen , Park Sooyong , Dorsey E. Ray , Schwartz Catherine , Jaffe Karen , Hoque Ehsan
Published: January 2024

We present a user-centric validation of a teleneurology platform, assessing its effectiveness in conveying screening information, facilitating user queries, and offering resources to enhance user empowerment. This validation process is implemented in the setting of Parkinson's disease (PD), in collaboration with a neurology department of a major medical center in the USA. Our intention is that with this platform, anyone globally with a webcam and microphone-equipped computer can carry out a series of speech, motor, and facial mimicry tasks. Our validation method demonstrates to users a mock PD risk assessment and provides access to relevant resources, including a chatbot driven by GPT, locations of local neurologists, and actionable and scientifically-backed PD prevention and management recommendations. We share findings from 91 participants (48 with PD, 43 without) aimed at evaluating the user experience and collecting feedback. Our framework was rated positively by 80.85% (standard deviation ± 8.92%) of the participants, and it achieved an above-average 70.42 (standard deviation ± 13.85) System-Usability-Scale (SUS) score. We also conducted a thematic analysis of open-ended feedback to further inform our future work. When given the option to ask any questions to the chatbot, participants typically asked for information about neurologists, screening results, and the community support group. We also provide a roadmap of how the knowledge generated in this paper can be generalized to screening frameworks for other diseases through designing appropriate recording environments, appropriate tasks, and tailored user-interfaces.
DIPA2
Authors: Xu Anran , Zhou Zhongyi , Miyazaki Kakeru , Yoshikawa Ryo , Hosio Simo , Yatani Koji
Published: January 2024

The world today is increasingly visual. Many of the most popular online social networking services are largely powered by images, making image privacy protection a critical research topic in the fields of ubiquitous computing, usable security, and human-computer interaction (HCI). One topical issue is understanding privacy-threatening content in images that are shared online. This dataset article introduces DIPA2, an open-sourced image dataset that offers object-level annotations with high-level reasoning properties to show perceptions of privacy among different cultures. DIPA2 provides 5,897 annotations describing perceived privacy risks of 3,347 objects in 1,304 images. The annotations contain the type of the object and four additional privacy metrics: 1) information type indicating what kind of information may leak if the image containing the object is shared, 2) a 7-point Likert item estimating the perceived severity of privacy leakages, and 3) intended recipient scopes when annotators assume they are either image owners or allowing others to repost the image. Our dataset contains unique data from two cultures: We recruited annotators from both Japan and the U.K. to demonstrate the impact of culture on object-level privacy perceptions. In this paper, we first illustrate how we designed and performed the construction of DIPA2, along with data analysis of the collected annotations. Second, we provide two machine-learning baselines to demonstrate how DIPA2 challenges the current image privacy recognition task. DIPA2 facilitates various types of research on image privacy, including machine learning methods inferring privacy threats in complex scenarios, quantitative analysis of cultural influences on privacy preferences, understanding of image sharing behaviors, and promotion of cyber hygiene for general user populations.
LiqDetector
Authors: Wang Zhu , Guo Yifan , Ren Zhihui , Song Wenchao , Sun Zhuo , Chen Chao , Guo Bin , Yu Zhiwen
Published: January 2024

With the advancement of wireless sensing technologies, RF-based contact-less liquid detection attracts more and more attention. Compared with other RF devices, the mmWave radar has the advantages of large bandwidth and low cost. While existing radar-based liquid detection systems demonstrate promising performance, they still have a shortcoming that in the detection result depends on container-related factors (e.g., container placement, container caliber, and container material). In this paper, to enable container-independent liquid detection with a COTS mmWave radar, we propose a dual-reflection model by exploring reflections from different interfaces of the liquid container. Specifically, we design a pair of amplitude ratios based on the signals reflected from different interfaces, and theoretically demonstrate how the refractive index of liquids can be estimated by eliminating the container's impact. To validate the proposed approach, we implement a liquid detection system LiqDetector. Experimental results show that LiqDetector achieves cross-container estimation of the liquid's refractive index with a mean absolute percentage error (MAPE) of about 4.4%. Moreover, the classification accuracies for 6 different liquids and alcohol with different strengths (even a difference of 1%) exceed 96% and 95%, respectively. To the best of our knowledge, this is the first study that achieves container-independent liquid detection based on the COTS mmWave radar by leveraging only one pair of Tx-Rx antennas.
TS2ACT
Authors: Xia Kang , Li Wenzhong , Gan Shiwei , Lu Sanglu
Published: January 2024

Human Activity Recognition (HAR) based on embedded sensor data has become a popular research topic in ubiquitous computing, which has a wide range of practical applications in various fields such as human-computer interaction, healthcare, and motion tracking. Due to the difficulties of annotating sensing data, unsupervised and semi-supervised HAR methods are extensively studied, but their performance gap to the fully-supervised methods is notable. In this paper, we proposed a novel cross-modal co-learning approach called TS2ACT to achieve few-shot HAR. It introduces a cross-modal dataset augmentation method that uses the semantic-rich label text to search for human activity images to form an augmented dataset consisting of partially-labeled time series and fully-labeled images. Then it adopts a pre-trained CLIP image encoder to jointly train with a time series encoder using contrastive learning, where the time series and images are brought closer in feature space if they belong to the same activity class. For inference, the feature extracted from the input time series is compared with the embedding of a pre-trained CLIP text encoder using prompt learning, and the best match is output as the HAR classification results. We conducted extensive experiments on four public datasets to evaluate the performance of the proposed method. The numerical results show that TS2ACT significantly outperforms the state-of-the-art HAR methods, and it achieves performance close to or better than the fully supervised methods even using as few as 1% labeled data for model training. The source codes of TS2ACT are publicly available on GitHub1.
Waffle
Authors: Zhang Xusheng , Zhang Duo , Xie Yaxiong , Wu Dan , Li Yang , Zhang Daqing
Published: January 2024

The bathroom has consistently ranked among the most perilous rooms in households, with slip and fall incidents during showers posing a critical threat, particularly to the elders. To address this concern while ensuring privacy and accuracy, the mmWave-based sensing system has emerged as a promising solution. Capable of precisely detecting human activities and promptly triggering alarms in response to critical events, it has proved especially valuable within bathroom environments. However, deploying such a system in bathrooms faces a significant challenge: interference from running water. Similar to the human body, water droplets reflect substantial mmWave signals, presenting a major obstacle to accurate sensing. Through rigorous empirical study, we confirm that the interference caused by running water adheres to a Weibull distribution, offering insight into its behavior. Leveraging this understanding, we propose a customized Constant False Alarm Rate (CFAR) detector, specifically tailored to handle the interference from running water. This innovative detector effectively isolates human-generated signals, thus enabling accurate human detection even in the presence of running water interference. Our implementation of "Waffle" on a commercial off-the-shelf mmWave radar demonstrates exceptional sensing performance. It achieves median errors of 1.8cm and 6.9cm for human height estimation and tracking, respectively, even in the presence of running water. Furthermore, our fall detection system, built upon this technique, achieves remarkable performance (a recall of 97.2% and an accuracy of 97.8%), surpassing the state-of-the-art method.
TrackPose
Authors: He Ke , Li Chentao , Duan Yongjie , Feng Jianjiang , Zhou Jie
Published: January 2024

Several studies have explored the estimation of finger pose/angle to enhance the expressiveness of touchscreens. However, the accuracy of previous algorithms is limited by large estimation errors, and the sequential output angles are unstable, making it difficult to meet the demands of practical applications. We believe the defect arises from improper rotation representation, the lack of time-series modeling, and the difficulty in accommodating individual differences among users. To address these issues, we conduct in-depth study of rotation representation for the 2D pose problem by minimizing the errors between representation space and original space. A deep learning model, TrackPose, using a self-attention mechanism is proposed for time-series modeling to improve accuracy and stability of finger pose. A registration application on a mobile phone is developed to collect touchscreen images of each new user without the use of optical tracking device. The combination of the three measures mentioned above has resulted in a 33% reduction in the angle estimation error, 47% for the yaw angle especially. Additionally, the instability of sequential estimations, measured by the proposed metric MAEΔ, is reduced by 62%. User study further confirms the effectiveness of our proposed algorithm.
PASTEL
Authors: Elhattab Fatima , Bouchenak Sara , Boscher Cédric
Published: January 2024

Federated Learning (FL) aims to improve machine learning privacy by allowing several data owners in edge and ubiquitous computing systems to collaboratively train a model, while preserving their local training data private, and sharing only model training parameters. However, FL systems remain vulnerable to privacy attacks, and in particular, to membership inference attacks that allow adversaries to determine whether a given data sample belongs to participants' training data, thus, raising a significant threat in sensitive ubiquitous computing systems. Indeed, membership inference attacks are based on a binary classifier that is able to differentiate between member data samples used to train a model and non-member data samples not used for training. In this context, several defense mechanisms, including differential privacy, have been proposed to counter such privacy attacks. However, the main drawback of these methods is that they may reduce model accuracy while incurring non-negligible computational costs. In this paper, we precisely address this problem with PASTEL, a FL privacy-preserving mechanism that is based on a novel multi-objective learning function. On the one hand, PASTEL decreases the generalization gap to reduce the difference between member data and non-member data, and on the other hand, PASTEL reduces model loss and leverages adaptive gradient descent optimization for preserving high model accuracy. Our experimental evaluations conducted on eight widely used datasets and five model architectures show that PASTEL significantly reduces membership inference attack success rates by up to -28%, reaching optimal privacy protection in most cases, with low to no perceptible impact on model accuracy.
How to Arrange Texts and Pictures for Online Visitors — Comparing Basic Ceramic Display Forms with Eye Tracking
Authors: Zheng Xia , Jiang Yicheng , Cheng Hua , Nie Aiqing
Published: January 2024

In the context of online text–picture relic exhibitions, two exploratory experiments were conducted to investigate the role of integrated/separate display, background information, and annotation type in learning tangible heritage. Using ceramics as an example, we tracked the eye movement of subjects under different display forms and tested whether they obtained the relevant information. Experiment 1 (N = 48) adopted a 2 (integrated/separate display) × 2 (with/without background information) design and Experiment 2 (N = 93) investigated distinct types of annotation (no annotation, indicative/direct/picture/contour shape annotation). We found that the following. (1) In the segmented relic display, the usage time, fixation count, and total fixation duration of relic names were lower than those in the integrated case. The probability that subjects would learn comparatively was also lower in the separate display. However, the performance on retention or transfer tests did not differ depending on the integrated/separate display. After reading the background information, subjects paid less attention to relic names but had better knowledge transfer performance. (2) The viewers’ attention allocation to the materials was not significantly influenced by the annotations. Mere visual annotations did not provide an advantage for information acquisition. By contrast, indicative verbal annotation required relatively more time for better target information memory, and the direct verbal cue consumed the least time. Based on the results, we discussed the application scenario of multimedia learning principles and potential recommendations for designing online relic displays.
PRogramAR: Augmented Reality End-User Robot Programming
Authors: Ikeda Bryce , Szafir Daniel
Published: January 2024

The field of end-user robot programming seeks to develop methods that empower non-expert programmers to task and modify robot operations. In doing so, researchers may enhance robot flexibility and broaden the scope of robot deployments into the real world. We introduce
PRogramAR
(Programming Robots using Augmented Reality), a novel end-user robot programming system that combines the intuitive visual feedback of augmented reality (AR) with the simplistic and responsive paradigm of trigger-action programming (TAP) to facilitate human-robot collaboration. Through PRogramAR, users are able to rapidly author task rules and desired reactive robot behaviors, while specifying task constraints and observing program feedback contextualized directly in the real world. PRogramAR provides feedback by simulating the robot’s intended behavior and providing instant evaluation of TAP rule executability to help end users better understand and debug their programs during development. In a system validation, 17 end users ranging from ages 18 to 83 used PRogramAR to program a robot to assist them in completing three collaborative tasks. Our results demonstrate how merging the benefits of AR and TAP using elements from prior robot programming research into a single novel system can successfully enhance the robot programming process for non-expert users.
Climate and Tropospheric Oxidizing Capacity
Authors: Fiore Arlene M. , Mickley Loretta J. , Zhu Qindan , Baublitz Colleen B.
Published: January 2024

The hydroxyl radical (OH) largely controls the tropospheric self-cleansing capacity by reacting with gases harmful to the environment and human health. OH concentrations are determined locally by competing production and loss processes. Lacking strong observational constraints, models differ in how they balance these processes, such that the sign of past and future OH changes is uncertain. In a warmer climate, OH production will increase due to its water vapor dependence, partially offset by faster OH-methane loss. Weather-sensitive emissions will also likely increase, although their net impact on global mean OH depends on the balance between source (nitrogen oxides) and sink (reactive carbon) gases. Lightning activity increases OH, but its response to climate warming is of uncertain sign. To enable confident projections of OH, we recommend efforts to reduce uncertainties in kinetic reactions, in measured and modeled OH, in proxies for past OH concentrations, and in source and sink gas emissions.
▪OH is strongly modulated by internal climate variability despite its lifetime of a few seconds at most, with implications for interpreting trends in methane.▪Improved kinetic constraints on key reactions would strengthen confidence in regional and global OH budgets, and in the response of OH to climate change.▪Future OH changes will depend on uncertain and compensating processes involving weather-sensitive chemistry and emissions, plus human choices.▪Technological solutions to climate change will likely impact tropospheric oxidizing capacity and merit further study prior to implementation.
Elderberry, an Ancient Remedy: A Comprehensive Study of the Bioactive Compounds in Three Sambucus nigra L. Subspecies
Authors: Uhl Katherine , Mitchell Alyson E.
Published: January 2024

Elderberry, the fruit of Sambucus nigra, has become a popular inclusion in foods, beverages, supplements, and more in recent years. Although the European subspecies, S. nigra ssp. nigra, has been widely studied for its composition, particularly for phenolic and volatile profiles, other subspecies, such as the American elderberry S. nigra ssp. canadensis and the blue elderberry S. nigra ssp. cerulea, have also become contenders in the elderberry supply chain. For the first time, the composition (including micronutrients, macronutrients, organic acids, titratable acid, soluble solids, phenolic compounds, and cyanogenic glycosides) of these three subspecies of elderberry is compared, highlighting the unique qualities of each subspecies and identifying gaps in the available data on the three subspecies.
Sympathetic determinants of resting blood pressure in males and females
Authors: Nardone Massimo , Foster Monique , O’Brien Myles W. , Coovadia Yasmine , Xie Shengkun , Usselman Charlotte W. , Kimmerly Derek S. , Taylor Chloe E. , Millar Philip J.
Published: January 2024

In a sample of 191 normotensive young adults, we confirm that resting muscle sympathetic nerve activity is a poor predictor of resting blood pressure and now demonstrate that sympathetic baroreflex gain is associated with resting blood pressure in males but not females. In contrast, signal-averaged measures of sympathetic-blood pressure transduction are unrelated to resting blood pressure. These findings highlight sex differences in the neural regulation of blood pressure.
A novel TASK channel antagonist nasal spray reduces sleep apnea severity in physiological responders: a randomized, blinded, trial
Authors: Osman Amal M. , Toson Barbara , Naik Ganesh R. , Mukherjee Sutapa , Delbeck Martina , Hahn Michael , Muller Thomas , Weimann Gerrit , Eckert Danny J.
Published: January 2024

Preclinical findings in pigs and humans indicate that blocking potassium channels in the upper airway with topical nasal application increases pharyngeal dilator muscle activity and reduces upper airway collapsibility. In this study, BAY2586116 nasal spray (potassium channel blocker) reduced sleep apnea severity in those who had physiological improvement in upper airway collapsibility. BAY2586116 lowered the next morning’s blood pressure. These findings highlight the potential for this novel therapeutic approach to improve sleep apnea in certain people.
Initiating your coronation
Authors: Woods Letha , Robinson Douglas L.
Published: January 2024

Earning an advanced degree in biomedical sciences can be a challenging experience, and recent data indicate high levels of stress and anxiety among the current generation of learners. We propose here a new illustration for all graduate students to visualize their didactic journey as a coronation process. Before their coronation, trainees must undergo rigorous preparation. During the training, four key attributes, best described by the acronym COST (Credibility, Opportunity, Strength, and Tenacity), are cultivated. Throughout their academic journey, which is a critical period of intellectual and personal growth, the trainees will enhance their understanding of the responsibility of wearing a CROWN, which requires accepting the Cost of earning a diadem, Revolutionizing their thought construct, being Open to innovation and research, acknowledging that Wealth is intrinsically connected to their health, and Never forsaking their aspiration and pursuits. Executing these principles daily will provide a mechanism on which to rise to the stature of achieving individual career goals (i.e., being a Regent of your life). Actualization of this process requires sacrifice, maturity, and a sense of fearlessness. The results of taking this approach will lead to an educational legacy that establishes a pattern of academic success that can be emulated by future learners.
New Integral Operator for Analytic Functions
Authors: Güney H. Özlem , Owa Shigeyoshi , Attiya Adel A.
Published: January 2024

LetApnbe the class of functionsfzgiven byfz=zp+ap+nzp+n+ap+n+1zp+n+1+⋯which are analytic in the open unit diskU.For

f

z

∈

A

p

n

, new integral operatorsO−jfzandOjfzj=0,1,2,⋯.are considered. The operatorsO−jfzandOjfzsatisfyOjO−jfz=O−jOjfz=fzandO−j∗Ojfz=Oj∗O−jfz=f∗fzfor the convolution∗ofO−jfzandOjfz.In the present paper, the dominants for both operatorsO−jfzandOjfzand subordinations forO−jfzandOjfzare discussed. Also, new subclassTpγm,δ,ρ;m,jconcerning withmdifferent boundary points is defined and discussed. Moreover, some interesting problems ofTpγm,δ,ρ;m,jassociated withOjfzare obtained. Furthermore, some interesting examples for our results are considered.
Design of 3D Environment Combining Digital Image Processing Technology and Convolutional Neural Network
Authors: Lu Xiaofei , Li Shouwang
Published: January 2024

As virtual reality technology advances, 3D environment design and modeling have garnered increasing attention. Applications in networked virtual environments span urban planning, industrial design, and manufacturing, among other fields. However, existing 3D modeling methods exhibit high reconstruction error precision, limiting their practicality in many domains, particularly environmental design. To enhance 3D reconstruction accuracy, this study proposes a digital image processing technology that combines binocular camera calibration, stereo correction, and a convolutional neural network (CNN) algorithm for optimization and improvement. By employing the refined stereo-matching algorithm, a 3D reconstruction model was developed to augment 3D environment design and reconstruction accuracy while optimizing the 3D reconstruction effect. An experiment using the ShapeNet dataset demonstrated that the evaluation indices—Chamfer distance (CD), Earth mover’s distance (EMD), and intersection over union—of the model constructed in this study outperformed those of alternative methods. After incorporating the CNN module in the ablation experiment, CD and EMD increased by an average of 0.1 and 0.06, respectively. This validates that the proposed CNN module effectively enhances point cloud reconstruction accuracy. Upon adding the CNN module, the CD index and EMD index in the dataset increased by an average of 0.34 and 0.54, respectively. These results indicate that the proposed CNN module exhibits strong predictive capabilities for point cloud coordinates. Furthermore, the model demonstrates good generalization performance.
Knowledge Graph-Based Hierarchical Text Semantic Representation
Authors: Wu Yongliang , Pan Xiao , Li Jinghui , Dou Shimao , Dong Jiahao , Wei Dan
Published: January 2024

Document representation is the basis of language modeling. Its goal is to turn natural language text that flows into a structured form that can be stored and processed by a computer. The bag-of-words model is used by most of the text-representation methods that are currently available. And yet, they do not consider how phrases are used in the text, which hurts the performance of tasks that use natural language processing later on. Representing the meaning of text by phrases is a promising area of future research, but it is hard to do well because phrases are organized in a hierarchy and mining efficiency is low. In this paper, we put forward a method called hierarchical text semantic representation using the knowledge graph (HTSRKG), which uses syntactic structure features to find hierarchical phrases and knowledge graphs to improve how phrases are evaluated. First, we use CKY and PCFG to build the syntax tree sentence by sentence. Second, we walk through the parse tree using the hierarchical routing process to obtain the mixed phrase semantics in passages. Finally, the introduction of the knowledge graph improves the efficiency of text semantic extraction and the accuracy of text representation. This gives us a solid foundation for tasks involving natural language processing that come after. Extensive testing on actual datasets shows that HTSRKG surpasses baseline approaches with respect to text semantic representation, and the results of a recent benchmarking study support this.
Nursing Students’ Competency about Writing Nursing Care Plan: An Exploratory Study in Iran
Authors: Jabraeelzadeh Kamblash Ali , Jafari Mohammad Javad , Nemati-Vakilabad Reza , Mojebi Mohammad Reza , Mostafazadeh Pouya , Mirzaei Alireza
Published: January 2024

Background. By utilizing the nursing care process, healthcare professionals can implement nursing knowledge effectively and efficiently, ultimately leading to a significant improvement in the quality of care provided. Objective. This study aimed to assess writing nursing care plan competence among Ardabil nursing students in northwestern Iran. Methods. The study involved 248 nursing students from the second to eighth semesters in three nursing and midwifery schools located in the Ardabil province of northern Iran. The data were collected using a simple random sampling method and included a demographic questionnaire along with a survey questionnaire on nursing care plan writing skills. This was conducted between May and June 2023. Descriptive statistics, Pearson correlation, t-test, ANOVA, and multiple linear regression analyses were conducted for data analysis. Results. The mean score (SD) for writing a nursing care plan in a student survey was 3.35 (0.57) on a scale of 1 to 5. The survey’s weighted mean score for each dimension is as follows: data gathering (D) = 3.40 (0.73), identification of client’s problems (P) = 3.40 (0.73), sustainable goals (G) = 3.31 (0.77), appropriateness of intervention (I) = 3.30 (0.67), and recognizing outcomes (O) = 3.37 (0.69). This indicates that the students performed well overall. However, the lowest score was in the appropriateness of interventions dimension. Multiple linear regression analysis revealed that four variables, mean score of grade point average (GPA), age, academic term, and time spent studying (hours per day), were significant predictors of the student survey’s scores on writing nursing care plans. These variables could predict 61% of the total variance. Implication for Nursing Management. Nursing school administrators can establish programs to improve education and practice in nursing care plan development based on this study. They can use these findings to enhance nursing education and practice for students, which will ultimately lead to better nursing care plans. Administrators should ensure that students have the necessary skills for writing efficient care plans and provide training courses to improve their writing and critical thinking skills. Policies can be implemented to encourage students to increase their study hours and maintain quality care programs. Conclusion. Nursing students are skilled in creating well-written nursing care plans that follow the nursing process. The quality of these plans improves with higher GPAs and longer study hours. To enhance nursing care plans, nursing education should focus on developing skills and allocating sufficient time for studying and practicing. Collaborating with faculty and administrators, as well as using reliable resources, can also help improve the quality of care plans.
How Does Market‐Oriented Environmental Regulation Affect Carbon Emission Performance? A Quasinatural Experiment Based on the Pilot Policy of Energy‐Use Rights Trading
Authors: Li Yang , Wang Xuan , Wang Yilin , Peng Jiachao , Chen Shaofeng
Published: January 2024

In order to evaluate the effect of market‐oriented environmental management measures on regional carbon emission intensity in the pilot areas better, this paper adopts a quasinatural experiment of energy‐use rights trading (EURT) policy by using the difference‐in‐difference method from the perspective of cities in China from 2006 to 2019. The results show that the policy of EURT can significantly reduce regional carbon emission intensity, which varies in different regions and different scales of cities. The main goal of implementing the policy is to reduce regional carbon emission intensity by improving the energy consumption structure and promoting the improvement of industrial structure and green innovation. In addition, the spatial impact of the EURT pilot project is demonstrated by its ability to not only reduce local carbon emission intensity but also decrease carbon intensity in and around the designated areas.
Exploring the Infectious Drug Target Glutathione S-Transferase in Plasmodium falciparum with the Inhibitory Potential of Azadirachta indica Phytocompounds
Authors: Al-Malki Esam S.
Published: January 2024

Background. Neem compounds are being studied for their potential as new and effective antimalarial drugs, and there is mounting evidence that they may help treat malaria. The PfGST enzyme is crucial to the malaria parasite’s survival, making it a desirable target for new antimalarial drugs, and the study aims to examine the bark region compounds as PfGST inhibitors. Methods. The structure of PfGST is examined for quality analysis, the active site is predicted based on a web server, and the bark region compounds are docked for their binding potential. Final molecules are identified for the absorption, distribution, metabolism, and excretion (ADME) analysis to confirm the possible future leads that target malaria. Results. This study reports that IMPHY000093, IMPHY001448, and IMPHY005310 can be potential inhibitors, showing strong binding potential in hydrogen bonds, scoring values, and ADME analysis. Results are confirmed by the possible re-docking poses by the docking method, and the binding score is used for the evaluations. Conclusion. Neem’s active ingredients have shown promise as a new class of antimalarial medications. Neem compounds may boost the efficacy of other antimalarial drugs and the host immune system by inhibiting GST, which is involved in the metabolism of the malaria parasite.
Table S8 from Early Cancer Detection in Li–Fraumeni Syndrome with Cell-Free DNA
Authors: Wong Derek , Luo Ping , Oldfield Leslie E. , Gong Haifan , Brunga Ledia , Rabinowicz Ron , Subasri Vallijah , Chan Clarissa , Downs Tiana , Farncombe Kirsten M. , Luu Beatrice , Norman Maia , Sobotka Julia A. , Uju Precious , Eagles Jenna , Pedersen Stephanie , Wellum Johanna , Danesh Arnavaz , Prokopec Stephenie D. , Stutheit-Zhao Eric Y. , Znassi Nadia , Heisler Lawrence E. , Jovelin Richard , Lam Bernard , Lujan Toro Beatriz E. , Marsh Kayla , Sundaravadanam Yogi , Torti Dax , Man Carina , Goldenberg Anna , Xu Wei , Veit-Haibach Patrick , Doria Andrea S. , Malkin David , Kim Raymond H. , Pugh Trevor J.
Published: January 2024

Supplemental Table 8 – Panel Design
Table S5 from Early Cancer Detection in Li–Fraumeni Syndrome with Cell-Free DNA
Authors: Wong Derek , Luo Ping , Oldfield Leslie E. , Gong Haifan , Brunga Ledia , Rabinowicz Ron , Subasri Vallijah , Chan Clarissa , Downs Tiana , Farncombe Kirsten M. , Luu Beatrice , Norman Maia , Sobotka Julia A. , Uju Precious , Eagles Jenna , Pedersen Stephanie , Wellum Johanna , Danesh Arnavaz , Prokopec Stephenie D. , Stutheit-Zhao Eric Y. , Znassi Nadia , Heisler Lawrence E. , Jovelin Richard , Lam Bernard , Lujan Toro Beatriz E. , Marsh Kayla , Sundaravadanam Yogi , Torti Dax , Man Carina , Goldenberg Anna , Xu Wei , Veit-Haibach Patrick , Doria Andrea S. , Malkin David , Kim Raymond H. , Pugh Trevor J.
Published: January 2024

Supplemental Table 5 – Pan-Cancer Methylation Signature
Table S2 from Early Cancer Detection in Li–Fraumeni Syndrome with Cell-Free DNA
Authors: Wong Derek , Luo Ping , Oldfield Leslie E. , Gong Haifan , Brunga Ledia , Rabinowicz Ron , Subasri Vallijah , Chan Clarissa , Downs Tiana , Farncombe Kirsten M. , Luu Beatrice , Norman Maia , Sobotka Julia A. , Uju Precious , Eagles Jenna , Pedersen Stephanie , Wellum Johanna , Danesh Arnavaz , Prokopec Stephenie D. , Stutheit-Zhao Eric Y. , Znassi Nadia , Heisler Lawrence E. , Jovelin Richard , Lam Bernard , Lujan Toro Beatriz E. , Marsh Kayla , Sundaravadanam Yogi , Torti Dax , Man Carina , Goldenberg Anna , Xu Wei , Veit-Haibach Patrick , Doria Andrea S. , Malkin David , Kim Raymond H. , Pugh Trevor J.
Published: January 2024

Supplemental Table 2 – Panel Mutations
Figure S7 from Early Cancer Detection in Li–Fraumeni Syndrome with Cell-Free DNA
Authors: Wong Derek , Luo Ping , Oldfield Leslie E. , Gong Haifan , Brunga Ledia , Rabinowicz Ron , Subasri Vallijah , Chan Clarissa , Downs Tiana , Farncombe Kirsten M. , Luu Beatrice , Norman Maia , Sobotka Julia A. , Uju Precious , Eagles Jenna , Pedersen Stephanie , Wellum Johanna , Danesh Arnavaz , Prokopec Stephenie D. , Stutheit-Zhao Eric Y. , Znassi Nadia , Heisler Lawrence E. , Jovelin Richard , Lam Bernard , Lujan Toro Beatriz E. , Marsh Kayla , Sundaravadanam Yogi , Torti Dax , Man Carina , Goldenberg Anna , Xu Wei , Veit-Haibach Patrick , Doria Andrea S. , Malkin David , Kim Raymond H. , Pugh Trevor J.
Published: January 2024

Figure S7 showing differences in cfDNA fragment length in TP53m-carriers
Figure S6 from Early Cancer Detection in Li–Fraumeni Syndrome with Cell-Free DNA
Authors: Wong Derek , Luo Ping , Oldfield Leslie E. , Gong Haifan , Brunga Ledia , Rabinowicz Ron , Subasri Vallijah , Chan Clarissa , Downs Tiana , Farncombe Kirsten M. , Luu Beatrice , Norman Maia , Sobotka Julia A. , Uju Precious , Eagles Jenna , Pedersen Stephanie , Wellum Johanna , Danesh Arnavaz , Prokopec Stephenie D. , Stutheit-Zhao Eric Y. , Znassi Nadia , Heisler Lawrence E. , Jovelin Richard , Lam Bernard , Lujan Toro Beatriz E. , Marsh Kayla , Sundaravadanam Yogi , Torti Dax , Man Carina , Goldenberg Anna , Xu Wei , Veit-Haibach Patrick , Doria Andrea S. , Malkin David , Kim Raymond H. , Pugh Trevor J.
Published: January 2024

Figure S6 showing the validation of fragmentation score metrics
Figure S5 from Early Cancer Detection in Li–Fraumeni Syndrome with Cell-Free DNA
Authors: Wong Derek , Luo Ping , Oldfield Leslie E. , Gong Haifan , Brunga Ledia , Rabinowicz Ron , Subasri Vallijah , Chan Clarissa , Downs Tiana , Farncombe Kirsten M. , Luu Beatrice , Norman Maia , Sobotka Julia A. , Uju Precious , Eagles Jenna , Pedersen Stephanie , Wellum Johanna , Danesh Arnavaz , Prokopec Stephenie D. , Stutheit-Zhao Eric Y. , Znassi Nadia , Heisler Lawrence E. , Jovelin Richard , Lam Bernard , Lujan Toro Beatriz E. , Marsh Kayla , Sundaravadanam Yogi , Torti Dax , Man Carina , Goldenberg Anna , Xu Wei , Veit-Haibach Patrick , Doria Andrea S. , Malkin David , Kim Raymond H. , Pugh Trevor J.
Published: January 2024

Figure S5 showing fragment size analysis for the detection of somatic variants
Figure S10 from Early Cancer Detection in Li–Fraumeni Syndrome with Cell-Free DNA
Authors: Wong Derek , Luo Ping , Oldfield Leslie E. , Gong Haifan , Brunga Ledia , Rabinowicz Ron , Subasri Vallijah , Chan Clarissa , Downs Tiana , Farncombe Kirsten M. , Luu Beatrice , Norman Maia , Sobotka Julia A. , Uju Precious , Eagles Jenna , Pedersen Stephanie , Wellum Johanna , Danesh Arnavaz , Prokopec Stephenie D. , Stutheit-Zhao Eric Y. , Znassi Nadia , Heisler Lawrence E. , Jovelin Richard , Lam Bernard , Lujan Toro Beatriz E. , Marsh Kayla , Sundaravadanam Yogi , Torti Dax , Man Carina , Goldenberg Anna , Xu Wei , Veit-Haibach Patrick , Doria Andrea S. , Malkin David , Kim Raymond H. , Pugh Trevor J.
Published: January 2024

Figure S10 showing validation of methylation signatures
Figure S4 from Disruption of SUV39H1-Mediated H3K9 Methylation Sustains CAR T-cell Function
Authors: Jain Nayan , Zhao Zeguo , Koche Richard P. , Antelope Chenling , Gozlan Yosi , Montalbano Antonino , Brocks David , Lopez Michael , Dobrin Anton , Shi Yuzhe , Gunset Gertrude , Giavridis Theodoros , Sadelain Michel
Published: January 2024

Figure S4. Off-target editing of the SUV39H1 gRNA.
Supplementary Data 2 from GTP Signaling Links Metabolism, DNA Repair, and Responses to Genotoxic Stress
Authors: Zhou Weihua , Zhao Zitong , Lin Angelica , Yang John Z. , Xu Jie , Wilder-Romans Kari , Yang Annabel , Li Jing , Solanki Sumeet , Speth Jennifer M. , Walker Natalie , Scott Andrew J. , Wang Lu , Wen Bo , Andren Anthony , Zhang Li , Kothari Ayesha U. , Yao Yangyang , Peterson Erik R. , Korimerla Navyateja , Werner Christian K. , Ullrich Alexander , Liang Jessica , Jacobson Janna , Palavalasa Sravya , O’Brien Alexandra M. , Elaimy Ameer L. , Ferris Sean P. , Zhao Shuang G. , Sarkaria Jann N. , Győrffy Balázs , Zhang Shuqun , Al-Holou Wajd N. , Umemura Yoshie , Morgan Meredith A. , Lawrence Theodore S. , Lyssiotis Costas A. , Peters-Golden Marc , Shah Yatrik M. , Wahl Daniel R.
Published: January 2024

Supplementary Data 2 shows Supplementary Methods, Supplementary Reference, Supplementary Figure S1 and Figure Legends, Supplementary Figure S2 and Figure Legends, Supplementary Figure S3 and Figure Legends, Supplementary Figure S4 and Figure Legends, Supplementary Figure S5 and Figure Legends, Supplementary Figure S6 and Figure Legends, and Supplementary Figure S7 and Figure Legends.