bluuebunny/crossref_metadata_2025 huggingface dataset:
Beyond Economic Allocation: Investigating Alternative Coproduct Treatment Methods in Cotton Life Cycle Assessments
Authors: Daystar Jesse , Barrera Juanita , Pires Steven , Wallace Michele , Mhatre Shah Purva , Bayramova Jeyran , Mertens Joel , Laurin Lise
Published: September 2024

Highlights

The multifunctionality of cotton cultivation is analyzed using different coproduct treatment methods.

Changes in life cycle impacts with different coproduct treatments are higher than uncertainty in global data.

Cereal unit and biophysical allocation are shown to be robust alternatives to economic allocation.

Abstract. Cotton lint represents the largest natural textile fiber production globally, and as organizations strive to reduce their upstream environmental impacts, robust cotton life cycle assessment (LCA) data has never been more important. A key characteristic of cotton is that during its cultivation, it produces an important coproduct – cottonseed, and thus the impacts of the cultivation are partitioned between the cotton lint and cottonseed. How the environmental impacts of cotton production are split between the products is critical for measuring the environmental impacts. This study evaluates the effect of different coproduct treatment approaches on the life cycle impacts of cotton and presents the issues and limitations of these approaches. Approaches include partitioning (mass, economic, biophysical, and cereal units) and substitution, sometimes referred to as system expansion. Results show that when accounting for uncertainty in allocation and inventory, the global warming impact of global average cotton lint ranges between -0.01 and 4.24 CO2/kg of lint at the 95% confidence interval. Comparing the coproduct treatment approaches for cotton lint, a mass partitioning perspective tends to yield the lowest impacts, whereas economic partitioning along with substitution can yield larger impacts in other categories. The more recent cereal unit and biophysical allocation methods are identified as robust alternatives to economic allocation, overcoming its common issues and limitations. This study helps organizations interested in cotton understand the underpinnings of each approach and how coproduct treatment plays a role in LCA results. It also serves as a foundational work on coproduct treatment in agricultural contexts. Keywords: Allocation, Coproduct treatment, Cotton lint, Cotton sustainability, LCA.
Stronger Together: A Successful Model of Health System-Community Collective Action During the COVID-19 Pandemic
Authors: Yang Yihui , Gunn Christine M. , Farnsworth Barbara , Norman Gregory , Kraft Sally
Published: September 2024

Abstract: Background: Discontinuity between health care delivery systems and community-based organizations is a significant barrier to improving population health. Objective: To describe the facilitators and barriers experienced by a health system–community partnership 15 months after implementation. Methods: Coalition members who led committees within the coalition or had active, sustained participation in coalition activities were invited to participate. Qualitative interviews used a semi-structured interview guide that elicited information on coalition functioning. A content analysis used inductive and deductive codes which were reviewed using a consensus process. Final themes centered on factors that facilitated or impeded the coalition’s success in supporting community needs during the COVID-19 pandemic. Lessons Learned: Coalition stakeholder perspectives identified several critical factors: defined governance, a culture of trust that accelerates learning, reliable resources, and a health-care anchor organization committed to shared investment. Conclusions: Lessons from this endeavor contribute to a deeper understanding of successful practices for health system-community partnerships.
Improving the Lives of People with Sickle Cell Disease: Community Organizations and Epidemiologists Working Together
Authors: Young Amanda J. , Maresh Amanda , Pope Shammara , Blaylark Rae , Lakshmanan Sangeetha , Stephens L’Oreal , Aderojou Rebecca , Meier Emily , Gibson Gary , Okolo Amanda , Cromartie Shamaree , Coker Niani , Paulukonis Susan , Fields Jennifer , Kaur Mandip , Desai Jay
Published: September 2024

Abstract: Background: The Centers for Disease Control and Prevention’s Sickle Cell Data Collection (SCDC) program comprises multidisciplinary teams, which include community-based organizations. Partnering with community-based organizations (CBOs) is a novel approach to ensure that SCDC data are actionable. Objective: To better understand areas for mutual capacity building, we explored the relationships and dynamics between CBO and data teams within the SCDC program in 10 states. Methods: We conducted semi-structured interviews with CBO ( n = 13) and SCDC ( n = 10) participants and then categorized and compared text from each interview and across states. Six themes emerged. Lessons Learned: Transparency and trust are essential. Early CBO engagement and leadership are needed for trust and agreed upon priorities. Conclusions: Participants contextualized trust, the most prominent theme, within discussions of racism and health inequities. Relationships between the CBO and data teams bring hard data and human experience together for advocacy, education, improved care, and a platform for the SCD voice.
When “Immersive” Learning Goes Remote: Interdisciplinary Lessons Learned in a Pandemic
Authors: Elias Thistle I. , Thompson Jessica R. , Boak Brandi , Jones Denise , Ziats Brandon
Published: September 2024

Abstract: Background: Due to the COVID-19 pandemic, health professional training programs made substantial changes to shift previously in-person student training opportunities to remote settings. Objectives: We present lessons learned from changes made to one community-engaged internship program, Bridging the Gaps (BTG)-Pittsburgh, that should prove helpful in future times of crisis. Methods: BTG-Pittsburgh places inter-disciplinary graduate pairs of students in community-based organizations that serve marginalized populations, to work directly with program participants and develop tangible products aimed to build organizational capacity. Students get additional training on poverty awareness, health literacy, community violence, food justice, trauma-informed self-care, cultural and academic humility, oral health and advocacy. Upon pandemic onset, given increased community need and community partner feedback, BTG-Pittsburgh pivoted quickly, shifting to remote engagement and making critical adjustments to ensure responsiveness to student and community partner needs. Adjustments included: 1) adopting a trauma-informed approach, 2) developing remote mentoring guidance, and 3) doubling site visits to ensure that students and site mentors felt sufficiently supported. Conclusions: Several program and partnership attributes contributed to our overall program success, including a model of reciprocal benefits, providing supports, flexibility, and long-standing relationships. The university’s quick adoption of remote technology and each participating school’s commitment to supporting the program model, further enabled effective student-organization-program collaboration. These lessons can inform community-partnered experiential learning programs that may need to incorporate remote components moving forward.
Training Dental Teams to Address Community Health: Necessary Partnerships and Evaluation of an Evidence-Based Curriculum
Authors: Schroeder Shawnda , Reiten Julie
Published: September 2024

Abstract: Background: Annually, 27 million Americans visit a dental professional but not a physician. Dental professionals must recognize that they are members of their patients’ primary care teams. Continuing education must then prepare them to appropriately serve their specific communities. Objectives: The objective of this paper was to describe the implementation of an evidence-based model to train dental professionals on how to respond to community-level health needs. The paper details crucial partnerships and provides evidence and key considerations for replicating the curriculum to improve population health. Methods: The Extension for Community Healthcare Outcomes (ECHO) model was used in one state where dental health care use is challenging for persons living rural, eligible for Medicaid, aging, and those who are American Indian. This formative evaluation knowledge assessments, data on participants’ changes in clinical care practice, web analytics, and artifact review to assess effective implementation strategies and necessary community partnerships. Conclusions: Successful implementation of the curriculum required active participation and partnership with state provider associations, the office of Medicaid, the state Board of Dental Licensure, and others. Without engaged partners, the curriculum would not have been community relevant, nor would it have had case presentation from local providers. In a state with only 427 practicing dentists, live attendance ranged between 9 and 22 dental team members, with between 11 and 91 views of the recorded sessions. Using the evidence-based ECHO model, which requires community health partnerships, is a cost-effective, and accessible, method to offering community specific education for dental providers across a large geographic region.
Lessons Learned from Community Partnership During the COVID-19 Pandemic
Authors: Frediani Jennifer K. , Smith Taylor W. , Spires Shelley , Moreland Paula , Thompson Gwin , Henderson Darlene , Smith Sylvia , Maxwell Robert , Hoffman LaShawn M. , Johnson L. Neicey , Bryant Xavier , Jacobs Theresa , Geiger Demetrius , Wilde Gretchen , Weber Mary Beth , Akintobi Tabia Henry , Narayan K.M. Venkat , Quarells Rakale C.
Published: September 2024

Abstract: Underserved communities have been disproportionately affected by the COVID-19 pandemic. The Project Promoting Engagement and COVID-19 Testing for Health (PEACH) study was designed to understand the attitudes, beliefs, and infrastructure associated with COVID-19 risk, testing, and prevention behaviors in people living with, caring for, or at risk for type 2 diabetes. The purpose of this joint community–academic partnered manuscript is to share lessons learned for maintaining community partnerships through the challenging times of a pandemic. New and existing community partners were invited to share their perceptions about the facilitators and barriers of partnering with academia during the COVID-19 public health crisis. Key facilitators included those partners felt heard and their input valued. And the changing nature and demands in response to the pandemic on the partners’ responsibilities were among the key challenges. Successful maintenance of the partnerships required flexibility, creativity, and a willingness to adapt engagement as community partners responded to the needs of their communities.
Being/Becoming
Authors: Peterson II Victor
Published: September 2024

Abstract: Ontology analyzes what can be said to exist given what satisfies the framework employed. Metaphysics covers that much and what can be said about the relationship between these different frames. Therein lies a gap that inspires much controversy. Denise Ferreira da Silva has shown us how taking what is known to be the case as all that can actually be the case runs amok, especially with regard to analyses of race and racialization. This essay offers a treatment of this gap by taking up Sonia Sanchez's protocol from a program developed within the Black Arts Movement wherein what can be said to be can also be said to be significant given the framework employed.
Relieving photobleaching impacts on fluorescence thermometry via neural network predictions
Authors: Wang Jiahao , Wu Binhe , Wang Chunrui , Zhou Jian , Sun Hao , Cao Wenhan , Yu Huimei
Published: September 2024

The thermal sensitivity of luminescence intensities enables fluorescence thermometry for remote temperature probing with high spatial and temporal resolutions. However, its accuracy suffers from factors such as nonlinear thermal response and the photochemical stability of fluorescence sensors. In this work, we realized thermometric measurements with high spatial resolution at micrometer scale using thin films with europium (Eu) complexes and microscopic measurements. We identified tris(dibenzoylmethane)phenanthroline europium(III)/polystyrene (Eu(DBM)3Phen/PS) thin film as an optimal choice for not only its linear dependence on fluorescence intensity for temperatures of biological interest but also its stronger resistance to the photobleaching effect. More importantly, we show that the latter effect can be effectively compensated via neural network methods. This approach has been validated for surface temperature mapping at the thermal equilibrium, where better uniformity as compared with results without correcting the photobleaching effect was achieved. The temperature elevation of resistive wires due to Joule heating can be clearly identified. This work shows that neural network models are powerful tools in improving the accuracy of fluorescence thermometry and beneficial for applications ranging from biology to nanotechnologies.
Intuitive understanding of extinction of small particles in absorbing and active host media within the MLWA
Authors: Utyushev Anton D. , Zakomirnyi Vadim I. , Shcherbakov Alexey A. , Rasskazov Ilia L. , Moroz Alexander
Published: September 2024

In an absorbing or an active host medium characterized by a complex refractive index n2=n2′+in2′′, our previously developed modified dipole long-wave approximation (MLWA) is shown to essentially overlie with the exact Mie theory results for localized surface plasmon resonance of spherical nanoparticles with radius a≲25nm (a≲20nm) in the case of Ag and Au (Al and Mg) nanoparticles. The agreement for Au and Ag (Al and Mg) nanoparticles, slightly better in the case of Au than Ag, continues to be acceptable up to a∼50nm (a∼40nm), and can be used, at least qualitatively, up to a∼70nm (a∼50nm) correspondingly. A first order analytic perturbation theory (PT) in a normalized extinction coefficient, κ¯=n2′′/n2′, around a nonabsorbing host is developed within the dipole MLWA and its properties are investigated. It is shown that, in a suitable parameter range, the PT can reliably isolate and capture the effect of host absorption or host gain on the overall extinction efficiency of various plasmonic nanoparticles.
Fiber Fabry-Perot accelerometer with extended dynamic range and low noise floor
Authors: Qi Yonghong , Zhao Minghui , Xie Zongxiang , Zhang Xiaopeng , Ou Yatong , Wang Hailong , Jiang Zhuangde , Wei Xueyong
Published: September 2024

Optical interferometric accelerometers are widely used in seismic monitoring, petroleum resources exploration, and structural health monitoring due to their low noise floor and resistance to electromagnetic interference (EMI). However, their small working range limits further applications. To broaden the working range of the sensor while ensuring the inherent anti-electromagnetic interference capability of the optical sensor, this paper proposes an orthogonal optical path (OP) range broadening scheme (OORBS). The linear working range is widened by splicing the linear intervals in the two interferometric signals. Subsequently, a platform based on a nano-displacement unit was built to validate the feasibility of the OORBS under static and AC cavity length variations. The experimental results show that the OORBS can recover the cavity length completely. Finally, the OORBS was combined with an accelerometer to realize the range broadening. The OORBS extends the accelerometer’s working range from 0.42 mg to 68 mg while maintaining the high sensitivity, which is about a 162-time improvement. The accelerometer’s noise floor reaches 4.8 ng/Hz1/2 at 15 Hz and accordingly, the dynamic range of the accelerometer increases from 98.8 dB to 143 dB. The proposed method is general to address the Fabry-Perot-based dynamic range limitation and can be adapted for various interferometric sensors, such as Fabry-Perot, grating, and Mach–Zehnder.
Photonic lantern TIRF microscopy for highly efficient, uniform, artifact-free imaging
Authors: Husain Abdullah , Yerolatsitis Stephanos , Amezcua Correa Rodrigo , Han Kyu Young
Published: September 2024

We report a method for generating uniform, artifact-free total internal reflection fluorescence (TIRF) excitation via a photonic lantern. Our tapered waveguide, consisting of a multimode input and nine few-mode outputs, enables single-shot TIRF illumination from nine azimuthal directions simultaneously without the introduction of nonstationary devices. Utilizing the photonic lantern for multi-beam excitation provides a low-loss mechanism that supports a wide range of light sources, including high-coherence lasers and various wavelengths in the visible spectrum. Our excitation system also allows tuning of the TIRF penetration depth. The high-quality excitation produced by photonic lantern TIRF (PL-TIRF) enables unbiased imaging across the entire illumination field-of-view. The simplicity and robustness of our technique provides advantages over other TIRF approaches, which often have complicated setups with scanning devices or other impracticalities. In this paper we discuss the lantern design process, characterize its performance, and demonstrate flat-field super-resolution imaging and shadowless live-cell imaging using PL-TIRF.
Xenon plasma-focused ion beam milling for fabrication of high-purity, bright single-photon sources operating in the C-band
Authors: Jaworski Maciej , Mrowiński Paweł , Mikulicz Marek G. , Holewa Paweł , Zeidler Laura , Syperek Marcin , Semenova Elizaveta , Sęk Grzegorz
Published: September 2024

Electron beam lithography is a standard method for fabricating photonic micro and nanostructures around semiconductor quantum dots (QDs), which are crucial for efficient single and indistinguishable photon sources in quantum information processing. However, this technique is difficult for direct 3D control of the structure shape, complicating the design and enlarging the 2D footprint to suppress in-plane photon leakage while directing photons into the collecting lens aperture. Here, we present an alternative approach to employ xenon plasma-focused ion beam (Xe-PFIB) technology as a reliable method for the 3D shaping of photonic structures containing low-density self-assembled InAs/InP quantum dots emitting in the C-band range of the 3rd telecommunication window. The method is optimized to minimize the possible ion-beam-induced material degradation, which allows exploration of both non-deterministic and deterministic fabrication approaches, resulting in photonic structures naturally shaped as truncated cones. As a demonstration, we fabricate mesas using a heterogeneously integrated structure with a QD membrane atop an aluminum mirror and silicon substrate. Finite-difference time-domain simulations show that the angled sidewalls significantly increase the emission collection efficiency to approx. 0.9 for NA = 0.65. We demonstrate experimentally a high purity of pulsed single-photon emission (∼99%) and a superior extraction efficiency value reported in the C-band of η = 24 ± 4%.
Bias control for optical single-sideband transmitter based on single IQ modulator
Authors: Dong Jun , Bo Tianwai , Tan Zhongwei , Dong Yi
Published: September 2024

The optical in-phase and quadrature modulator (IQM) is typically utilized as an optical single-sideband (SSB) transmitter for its simple structure and low cost. It requires the modulator biases to be slightly offset for generating the optical carrier. However, this poses significant challenges in the bias control circuits, as most off-the-shelf automatic bias control (ABC) modules are designed to stabilize the IQM at its carrier suppression point for coherent optical communication. In this paper, a novel arbitrary ABC scheme is proposed to stabilize the carrier-to-signal power ratio (CSPR) of an optical SSB signal over long-term operation. This scheme uses SSB rather than double-sideband (DSB) sinusoidal signals as the dither signals. It does not violate the minimum phase condition, thus avoiding performance penalties compared to the conventional ABC scheme in which the DSB dither signal is used. We also develop a closed-form expression to reveal the relationship between the control parameter in the ABC algorithm and the CSPR of the optical SSB signal. By this means, the optical SSB transmitter can automatically adjust its bias voltages and stabilize them at a given CSPR value. The experimental results with ∼80 Gb/s optical SSB signal show that our proposed ABC scheme is effective in stabilizing the bias of the IQM at any point and maintains the CSPR value of the optical SSB signal over hours. It is also shown that the proposed method leads to 1 dB improvement in the receiver sensitivity compared with the traditional ABC technique.
High-quality and high-speed computer-generated holography via deep-learning-assisted bidirectional error diffusion method
Authors: Liu Kexuan , Wu Jiachen , Cao Liangcai
Published: September 2024

Computer-generated holography (CGH) is an effective light field manipulation technique based on diffractive optics. Deep learning provides a promising way to break the trade-off between quality and speed in the phase-only hologram (POH) generation process. In this paper, a neural network called BERDNet is proposed for high-quality and high-speed POH generation. A high-quality POH dataset without speckle noise and shifting noise is generated by the band-limited bidirectional error diffusion (BERD) algorithm. Based on the dataset, BERDNet is trained to learn the potential hologram coding method for real-time POH prediction. Furthermore, the training process is constrained by both data loss and physical loss, so it is necessary to explore higher-fidelity reconstructions that are more consistent with the bandwidth limitation. Finally, the POHs of numerical reconstructions with an average of 23.13 dB PSNR can be obtained in 0.037 s, achieving 1-2 orders of magnitude acceleration. Experimental reconstructions validated the generalization of the BERDNet.
MIR laser CEP estimation using machine learning concepts in bulk high harmonic generation
Authors: Nagyillés Balázs , Nagy Gergely N. , Kiss Bálint , Cormier Eric , Földi Péter , Varjú Katalin , Kahaly Subhendu , Kahaly Mousumi Upadhyay , Diveki Zsolt
Published: September 2024

Monitoring the carrier-envelope phase (CEP) is of paramount importance for experiments involving few-cycle intense laser fields. Common measurement techniques include f-2f interferometry or stereo-ATI setups. Here we demonstrate a new concept, both by simulations and by experiments, for CEP estimation in the mid-infrared regime using machine learning (ML) techniques that rely on the observation of the spectrum of high harmonic generation (HHG) in bulk material. Once the ML model is trained, the method provides a way for cheap and compact in-situ CEP tagging. This technique can complement other CEP monitoring methods, can capture the complex correlation between the CEP and the observable HHG spectra, and is readily generalizable for any laser wavelengths.
End-to-end learning of joint noise shaping and probabilistic shaping for OAM mode division multiplexing transmission
Authors: Xu Qi , Gao Ran , Wang Fei , Cheng Zhaohui , Cui Yi , Li Zhipei , Guo Dong , Chang Huan , Zhou Sitong , Zhang Qi , Pan Xiaolong , Wu Tianze , Xu Zhen , Xin Xiangjun
Published: September 2024

Intensity modulation direct detection (IM/DD) orbital angular momentum (OAM) mode division multiplexing (MDM) technology can greatly expand the capacity of a communication system, which is a promising solution for the next generation of high-speed passive optical networks (PONs). However, there are serious obstacles such as mode coupling, device nonlinear impairment, and quantization noise in an IM/DD OAM-MDM system with a low-resolution digital-to-analog converter (DAC). In this Letter, we propose a novel, to the best of our knowledge, end-to-end (E2E) learning scheme based on a double residual feature decoupling network (DRFDnet) emulator with joint probabilistic shaping (PS) and noise shaping (NS) for the OAM-MDM IM/DD transmission. Our DRFDnet emulator can accurately build a complex nonlinear model of an OAM-MDM system by separating the signal impairments into linear and nonlinear. Meanwhile, a DRFDnet-based E2E scheme for joint PS and NS is presented with the aim of compensating the signal impairment for the OAM-MDM IM/DD system. An experiment is carried out on a 200 Gbit/s PON system based on the OAM-MDM IM/DD transmission. The experimental results demonstrate that the proposed DRFDnet-based joint PS and NS scheme is a promising solution to effectively mitigate nonlinear distortions and outperforms the CGAN-based joint PS and NS scheme and traditional joint PS and NS scheme with receiver sensitivity improvements of 1.2 dBm and 2.5 dBm under hard-decision forward error correction (HD-FEC) thresholds, respectively. Our experimental results demonstrate that the proposed DRFDnet emulator-based E2E learning scheme is a viable candidate for future PON.
Low-cost and convenient screening of disease using analysis of physical measurements and recordings
Authors: Chandra Jay , Lin Raymond , Kancherla Devin , Scott Sophia , Sul Daniel , Andrade Daniela , Marzouk Sammer , Iyer Jay M. , Wasswa William , Villanueva Cleva , Celi Leo Anthony
Published: September 2024

In recent years, there has been substantial work in low-cost medical diagnostics based on the physical manifestations of disease. This is due to advancements in data analysis techniques and classification algorithms and the increased availability of computing power through smart devices. Smartphones and their ability to interface with simple sensors such as inertial measurement units (IMUs), microphones, piezoelectric sensors, etc., or with convenient attachments such as lenses have revolutionized the ability collect medically relevant data easily. Even if the data has relatively low resolution or signal to noise ratio, newer algorithms have made it possible to identify disease with this data. Many low-cost diagnostic tools have been created in medical fields spanning from neurology to dermatology to obstetrics. These tools are particularly useful in low-resource areas where access to expensive diagnostic equipment may not be possible. The ultimate goal would be the creation of a “diagnostic toolkit” consisting of a smartphone and a set of sensors and attachments that can be used to screen for a wide set of diseases in a community healthcare setting. However, there are a few concerns that still need to be overcome in low-cost diagnostics: lack of incentives to bring these devices to market, algorithmic bias, “black box” nature of the algorithms, and data storage/transfer concerns.
Impaired belief revision yet intact information seeking in positive schizotypy: A modified task of bias against disconfirmatory evidence
Authors: Zhao Wanchen , Deng Wisteria , Cannon Tyrone
Published: September 2024

Cognitive models of delusions emphasize the role of bias against disconfirmatory evidence (BADE) in maintaining false beliefs, but sources of this tendency remain elusive. While impaired information integration could be an explanation for this tendency, the lack of information seeking motive could also result in disregard for new evidence once a (false) belief is formed. The role of information seeking in the association between psychosis-proneness and belief inflexibility has not been investigated in the context of a social interpretation task. In this study, we modified the Interpretation Inflexibility Task (IIT), which assess bias against disconfirmatory evidence in interpersonal contexts, to permit assessment of information seeking by allowing participants to skip seeing increasingly disambiguating information (in the form of pictures at varying degrees of degradation). A robust regression analysis was conducted to examine whether increasing severity of positive schizotypy is associated with more frequent skipping of later trial stages, to examine information seeking. Controlling for the number of pictures seen by participants, a robust mixed effects analysis was conducted to investigate the associations of positive schizotypy, trait anxiety, and the emotional valence of the scenario with a measure of belief revision. Participants higher in positive schizotypy did not opt out of seeing disambiguating information more frequently, p = 0.65, ß = 0.04; despite this, they still exhibited heightened belief inflexibility by rating the lures and true explanations as equally plausible, p < 0.001, ß = -0.32. These results suggest that bias against disconfirmatory evidence in positive schizotypy is unlikely a result of reduced information seeking, leaving impaired information integration as a more likely source.
Barriers to care for mental health conditions in Canada
Authors: Williams Monnica T. , Osman Muna , Kaplan Aidan , Faber Sonya C.
Published: September 2024

There are growing concerns in Canada about access barriers to quality mental health care, which has worsened significantly by the COVID-19 pandemic and for some Canadians more than others. With a nationally representative sample of 1501 adults, surveyed by the Angus Reid Institute, this study examined the mental health conditions Canadians experience the most difficulties in accessing care. Among half of the respondents who sought mental health care, the majority encountered challenges in accessing help for posttraumatic stress disorder (PTSD) (34%) and depression (33%). When examining the data based only on those seeking care for specific conditions, attention deficit hyperactivity disorder (ADHD), obsessive-compulsive disorder (OCD), substance use disorders, and generalized anxiety disorder (GAD) emerged as those for which it was most difficult to find treatment. Indigenous and Black Canadians had significantly more difficulty finding care across several conditions. We discuss the implications of these findings, including the critical need to increase the supply and diversity of mental health providers across Canada. This study is one of the first to provide quantitative data on the perceived barriers in accessing mental health care, while exploring the role of race and ethnicity and other social identities.
Systematic analysis of SARS-CoV-2 Omicron subvariants’ impact on B and T cell epitopes
Authors: Al Khalaf Ruba , Bernasconi Anna , Pinoli Pietro
Published: September 2024

Introduction

Epitopes are specific structures in antigens that are recognized by the immune system. They are widely used in the context of immunology-related applications, such as vaccine development, drug design, and diagnosis / treatment / prevention of disease. The SARS-CoV-2 virus has represented the main point of interest within the viral and genomic surveillance community in the last four years. Its ability to mutate and acquire new characteristics while it reorganizes into new variants has been analyzed from many perspectives. Understanding how epitopes are impacted by mutations that accumulate on the protein level cannot be underrated.

Methods

With a focus on Omicron-named SARS-CoV-2 lineages, including the last WHO-designated Variants of Interest, we propose a workflow for data retrieval, integration, and analysis pipeline for conducting a database-wide study on the impact of lineages’ characterizing mutations on all T cell and B cell linear epitopes collected in the Immune Epitope Database (IEDB) for SARS-CoV-2.

Results

Our workflow allows us to showcase novel qualitative and quantitative results on 1) coverage of viral proteins by deposited epitopes; 2) distribution of epitopes that are mutated across Omicron variants; 3) distribution of Omicron characterizing mutations across epitopes. Results are discussed based on the type of epitope, the response frequency of the assays, and the sample size. Our proposed workflow can be reproduced at any point in time, given updated variant characterizations and epitopes from IEDB, thereby guaranteeing to observe a quantitative landscape of mutations’ impact on demand.

Conclusion

A big data-driven analysis such as the one provided here can inform the next genomic surveillance policies in combatting SARS-CoV-2 and future epidemic viruses.
Motor variability during resistance training: Acceleration signal as intensity indicator
Authors: López-Fernández Miguel , García-Aguilar Fernando , Asencio Pablo , Caballero Carla , Moreno Francisco J. , Sabido Rafael
Published: September 2024

Analysis of variability in physiological time series has been shown to be an indicator of the state of the organism. Although there is evidence of the usefulness of analysis of the amount and/or structure of variability (complexity) in cycling actions, there is limited knowledge about its application in resistance exercise. The aim of this study is to find out whether variability in acceleration signals can be an indicator of intensity level in a squat task. For this purpose, an experimental design was developed in which the following participated seventy-two participants (age = 25.7 ± 4.4 years; height = 169.2 ± 9.8 cm; body mass = 67.7 ± 11.2 kg; ratio 1RM/body mass = 1.4 ± 0.3). They performed four repetitions of back squat at loads of 10%, 30%, 50%, 70%, and 90% of 1RM. Acceleration during the exercise was recorded using an inertial measurement unit (IMU) and a force platform. The variability of the movement was then analyzed using Standard Deviation (SD), Detrended Fluctuation Analysis (DFA), Fuzzy Entropy (FuzzyEn), and Sample Entropy (SampEn). For the IMU and for the force platform, significant effects were observed in all variables (p < 0.001). In pairwise comparisons, IMU showed a significant increase in motor complexity with increasing intensity, among most intensities, in DFA, FuzzyEn and SampEn. Differences in force platform were more limited, and only DFA detected differences between most intensities. The results suggest that measures of signal and acceleration variability may be a useful indicator of the relative intensity at which a squat exercise is performed.
Evaluating dyadic factors associated with self-care in patients with heart failure and their family caregivers: Using an Actor-Partner Interdependence Model
Authors: Kim JinShil , Kim Kye Hun , Shin Mi-Seung , Heo Seongkum , Lee Jung-Ah , Cho KyungAh , An Minjeong
Published: September 2024

Dyadic conditions of patients with heart failure and their caregivers may affect both patient self-care and caregiver contribution to patient self-care (CCPS). The purpose of this study was to examine the relationships of patient-caregiver physical function and depressive symptoms to the patient self-care (maintenance and management) and CCPS. Data from 55 were analyzed using an Actor–Partner Interdependence Model to address the aim through AMOS. Patient self-care was very poor. Better patient physical function was related to better patient self-care management (actor effect) and poorer CCPS maintenance (partner effect). Better caregiver physical function was related to CCPS management (actor effect). Severer patient depressive symptoms were related to poorer patient self-care maintenance (actor effect) and poorer CCPS management (partner effect). Physical function and depressive symptoms in patient-caregiver dyads were related to patient self-care and CCPS. To improve patient self-care and CCPS, dyadic support for physical function and depressive symptoms is needed.
How to design subsidy policies to better encourage travelers to use car-sharing instead of private cars? An evolutionary game study
Authors: Li Zixun , Sun Yue , Zong Gang , Dong Xianlei
Published: September 2024

Car-sharing is a travel mode that can serve as an alternative to private cars, helping to reduce urban pollution. However, currently, there is a low willingness among travelers to use car-sharing, which is reflected in both low market penetration and user frequency. Therefore, it is essential for the government to encourage the use of car-sharing by providing subsidies. To better encourage the usage of car-sharing, this paper applies a two-fold evolutionary game model involving travelers and the government to explore the impact of subsidies on travelers’ choices, and the factors that could affect the subsidies’ efficiency. A simulation, using data from Beijing, was conducted to determine the implications of subsidy policies. The results show that a mileage-based subsidy and a fixed subsidy are applicable to travel of high and low mileages respectively, and under both subsidy modes, subsidies for trips with short duration or short pick-up and return time are more effective. Furthermore, we find that the efficiency of subsidies increases as the scale of car-sharing users, demand elasticity, or total number of travelers increases. Additionally, the subsidy levels should be lower than the environmental benefits of car-sharing but higher than the difference in travel costs between private cars and car-sharing. Future work will involve other game players such as car-sharing operators in order to draw deeper conclusions, and will involve the collection of data from more countries and cities to develop the robustness of the conclusions.
Effects of changes in the waveform and frequency of radio frequency energy on tissue ablation range
Authors: An Jinsu , Won Dong-Sung , Park Yubeen , Park Jung-Hoon , Park Ki-Hyeon , Lee Ji-Ho , Kim Hyung-Sik
Published: September 2024

This study reports the effects of changes in the waveform and frequency of radio frequency (RF) energy on the tissue ablation range. We developed a 70-watt RFA generator that provides sine and square waves and allows frequency control between 10 Hz and 500 kHz. The changes in the ablation range according to the waveform and frequency were observed using the developed generator. In the waveform variation test, the distance between the electrodes and the electrode type were changed for both waveforms with the frequency set to 500 kHz. In the frequency variation test, the waveform and electrode type were changed with the frequency set to 10, 100, and 500 kHz, while the distance between the electrodes was set to 20 mm. A fixed 45 voltage was applied using the bipolar method. RF energy was applied for 90 s in vitro. The temperature was regulated to not exceed 70°C. The ablation range was calculated using ImageJ software. The analysis results showed that the ablation range was larger with the square wave than with the sine wave and at 10 kHz than at 500 kHz. The developed generator can advance research on ablation area and depth in RF ablation.
Classification of land lot shapes in real estate sector using a convolutional neural network
Authors: Ham Subin , Lee Changro
Published: September 2024

In the agriculture and real estate industries, land lot shapes have mostly been classified by visual inspection or hard-crafted rules. These conventional methods are time-consuming, resource-intensive, and subject to human bias. This study aims to fill this gap and alleviate problems inherent in traditional lot classification approaches. This study attempts to classify lot shapes automatically, using a convolutional neural network. A study area was chosen, image data of the lots in the area were collected and preprocessed, and an Xception neural network was specified to classify land lots according to their shapes. The test applied to a different area adjacent to the study area achieved an accuracy of 90.1% and area under the curve (AUC) of 0.96. Additionally, this study demonstrated that shape regularity can be quantified using the output scores from the neural network analysis. This is the first attempt to employ a deep learning algorithm for land management on a micro-spatial scale. The classification approach proposed in this study is expected to encourage the rapid and accurate classification of various lot shapes.
Paternity success for resident and non-resident males and their influences on paternal sibling cohorts in Japanese macaques (Macaca fuscata) on Shodoshima Island
Authors: Ishizuka Shintaro , Inoue Eiji , Kaji Yuki
Published: September 2024

Reproductive success can be attributed to both resident and non-resident males in non-human primates. However, reproductive success of non-resident males has rarely been investigated at an individual level. As resident males achieve different degree of reproductive success with regard to various factors, such as male dominance relationships or female mate choice, the degree of reproductive success for non-resident males may vary between individuals. As male reproductive success is highly skewed towards specific individuals, the percentage of similar-aged paternal siblings within groups is expected to increase. However, the extent to which each male contributes to the production of cohorts of paternal siblings remains unclear. Here we examined the paternity of offspring born over five consecutive years in a free-ranging group of Japanese macaques Macaca fuscata on Shodoshima Island, Kagawa Prefecture. Genotypes of 87 individuals at 16 autosomal microsatellite loci were analyzed and paternity of 34 offspring was successfully assigned to a single candidate father. We quantitatively assessed paternity success for resident and a few non-resident males whose genetic samples were successfully collected. We quantitatively assessed the percentages of paternal siblings in the same age cohorts produced by those males. Non-resident males sired similar percentage of offspring compared to resident males. A large prime-aged non-resident male was the most successful sire among males in two of the five years. These results provide new insights that male reproductive success could be highly skewed toward a specific non-resident male. Subadult males had a lower percentage of paternity success, which may be because females may prefer physically mature males. Various males, including non-resident males, contributed to the creation of paternal sibling in the same age cohort. The overall results highlighted that not only resident but also non-resident males play an important role in shaping within-group kin structures.
Nonlinear FOPID controller design for pressure regulation of steam condenser via improved metaheuristic algorithm
Authors: Alzakari Sarah A. , Izci Davut , Ekinci Serdar , Alhussan Amel Ali , Hashim Fatma A.
Published: September 2024

Shell and tube heat exchangers are pivotal for efficient heat transfer in various industrial processes. Effective control of these structures is essential for optimizing energy usage and ensuring industrial system reliability. In this regard, this study focuses on adopting a fractional-order proportional-integral-derivative (FOPID) controller for efficient control of shell and tube heat exchanger. The novelty of this work lies in the utilization of an enhanced version of cooperation search algorithm (CSA) for FOPID controller tuning, offering a novel approach to optimization. The enhanced optimizer (en-CSA) integrates a control randomization operator, linear transfer function, and adaptive p-best mutation integrated with original CSA. Through rigorous testing on CEC2020 benchmark functions, en-CSA demonstrates robust performance, surpassing other optimization algorithms. Specifically, en-CSA achieves an average convergence rate improvement of 23% and an enhancement in solution accuracy by 17% compared to standard CSAs. Subsequently, en-CSA is applied to optimize the FOPID controller for steam condenser pressure regulation, a crucial aspect of heat exchanger operation. Nonlinear comparative analysis with contemporary optimization algorithms confirms en-CSA’s superiority, achieving up to 11% faster settling time and up to 55% reduced overshooting. Additionally, en-CSA improves the steady-state error by 8% and enhances the overall stability margin by 12%.
DRPChain: A new blockchain-based trusted DRM scheme for image content protection
Authors: Yun Jian , Liu Xinyu , Lu Yusheng , Guan Jingdan , Liu Xinyang
Published: September 2024

The unauthorized replication and distribution of digital images pose significant challenges to copyright protection. While existing solutions incorporate blockchain-based techniques such as perceptual hashing and digital watermarking, they lack large-scale experimental validation and a dedicated blockchain consensus protocol for image copyright management. This paper introduces DRPChain, a novel digital image copyright management system that addresses these issues. DRPChain employs an efficient cropping-resistant robust image hashing algorithm to defend against 14 common image attacks, demonstrating an 85% success rate in watermark extraction, 10% higher than the original scheme. Moreover, the paper designs the K-Raft consensus algorithm tailored for image copyright protection. Comparative experiments with Raft and benchmarking against PoW and PBFT algorithms show that K-Raft reduces block error rates by 2%, improves efficiency by 300ms compared to Raft, and exhibits superior efficiency,decentralization, and throughput compared to PoW and PBFT. These advantages make K-Raft more suitable for digital image copyright protection. This research contributes valuable insights into using blockchain technology for digital copyright protection, providing a solid foundation for future exploration.
Calculated hydration free energies become less accurate with increases in molecular weight
Authors: Ivanov Stefan M.
Published: September 2024

In order for computer-aided drug design to fulfil its long held promise of delivering new medicines faster and cheaper, extensive development and validation work must be done first. This pertains particularly to molecular dynamics force fields where one important aspect–the hydration free energy (HFE) of small molecules–is often insufficiently analyzed. While most benchmarking studies report excellent accuracies of calculated hydration free energies–usually within 2 kcal/mol of experimental values–we find that deeper analysis reveals significant shortcomings. Herein, we report a dependence of HFE prediction errors on ligand molecular weight–the higher the weight, the bigger the prediction error and the higher the probability the calculated result is erroneous by a large amount. We show that in the drug-like molecular weight region, HFE predictions can easily be off by 5 kcal/mol or more. This is likely to be highly problematic in a drug discovery and development setting. We make our HFE results and molecular descriptors freely and fully available in order to encourage deeper analysis of future molecular dynamics results and facilitate development of the next generation of force fields.