bluuebunny/crossref_metadata_2025_split huggingface dataset:
Silicon photomultiplier signal readout and multiplexing techniques for positron emission tomography: a review
Authors: Park Haewook , Yi Minseok , Lee Jae Sung 
Published: July 2022

AbstractIn recent years, silicon photomultiplier (SiPM) is replacing the photomultiplier tube (PMT) in positron emission tomography (PET) systems due to its superior properties, such as fast single-photon timing response, small gap between adjacent photosensitive pixels in the array, and insensitivity to magnetic fields. One of the technical challenges when developing SiPM-based PET systems or other position-sensitive radiation detectors is the large number of output channels coming from the SiPM array. Therefore, various signal multiplexing methods have been proposed to reduce the number of output channels and the load on the subsequent data acquisition (DAQ) system. However, the large PN-junction capacitance and quenching resistance of the SiPM yield undesirable resistance–capacitance delay when multiple SiPMs are combined, which subsequently causes the accumulation of dark counts and signal fluctuation of SiPMs. Therefore, without proper SiPM signal handling and processing, the SiPMs may yield worse timing characteristics than the PMTs. This article reviews the evolution of signal readout and multiplexing methods for the SiPM. In this review, we focus primarily on analog electronics for SiPM signal multiplexing, which allows for the reduction of DAQ channels required for the SiPM-based position-sensitive detectors used in PET and other radiation detector systems. Although the applications of most technologies described in the article are not limited to PET systems, the review highlights efforts to improve the physical performance (e.g. spatial, energy, and timing resolutions) of PET detectors and systems.
Loneliness in Autism and Its Association with Anxiety and Depression: A Systematic Review with Meta-Analyses
Authors: Hymas Rebecca , Badcock Johanna C. , Milne Elizabeth 
Published: July 2022

Abstract
Objectives
This systematic review aimed to quantify differences in loneliness levels between autistic and neurotypical samples and investigate the association between loneliness and mental health in autistic individuals.

Methods
Three meta-analyses were conducted. Studies were methodologically appraised using established tools.

Results
Overall, 39 studies were included. The majority of these achieved moderate methodological quality ratings. The primary meta-analysis (N = 23) found autistic samples reported higher loneliness compared with neurotypical samples (Hedges’ g = .89). The meta-analyses on the associations between loneliness and anxiety (N = 14) and depression (N = 11) in autistic samples found significant pooled correlations (r = .29 and r = .48, respectively).

Conclusions
This review highlights numerous limitations within current autism and loneliness research. Nevertheless, loneliness in autism merits targeted clinical and research attention.
Bounding open space risk with decoupling autoencoders in open set recognition
Authors: Lübbering Max , Gebauer Michael , Ramamurthy Rajkumar , Bauckhage Christian , Sifa Rafet 
Published: July 2022

AbstractOne-vs-Rest (OVR) classification aims to distinguish a single class of interest (COI) from other classes. The concept of novelty detection and robustness to dataset shift becomes crucial in OVR when the scope of the rest class is extended from the classes observed during training to unseen and possibly unrelated classes, a setting referred to as open set recognition (OSR). In this work, we propose a novel architecture, namely decoupling autoencoder (DAE), which provides a proven upper bound on the open space risk and minimizes open space risk via a dedicated training routine. Our method is benchmarked within three different scenarios, each isolating different aspects of OSR, namely plain classification, outlier detection, and dataset shift. The results conclusively show that DAE achieves robust performance across all three tasks. This level of cross-task robustness is not observed for any of the seven potent baselines from the OSR, OVR, outlier detection, and ensembling domain which, apart from ATA (Lübbering et al., From imbalanced classification to supervised outlier detection problems: adversarially trained auto encoders. In: Artificial neural networks and machine learning—ICANN 2020, 2020), tend to fail on either one of the tasks. Similar to DAE, ATA is based on autoencoders and facilitates the reconstruction error to predict the inlierness of a sample. However unlike DAE, it does not provide any uncertainty scores and therefore lacks rudimentary means of interpretation. Our adversarial robustness and local stability results further support DAE’s superiority in the OSR setting, emphasizing its applicability in safety-critical systems.
Current Status, Emerging Challenges, and Future Prospects of Industrial Symbiosis in Africa
Authors: Oni Oluwatosin Omolola , Nevo Chinedu Miracle , Hampo Chima Cyril , Ozobodo KingDavid Onyedika , Olajide Ismail Olayinka , Ibidokun Adebowale Olaolu , Ugwuanyi Mathew Chidera , Nwoha Solomon Uchechukwu , Okonkwo Ugochukwu Udonna , Aransiola Emmanuel Sunday , Ikpeama Chimdi Cynthia 
Published: July 2022

AbstractThe concept of industrial symbiosis have contributed to the achievement of a circular economy—a production and consumption model that promotes sustainability and also benefits countries economically, socially, and environmentally. There exists a variety of literature that highlights several cases of the application of industrial symbiosis in different geographical locations of the world. However, only a few of these studies have investigated its prevalence in Africa. Therefore, the goal of this study is to analyze the few cases of industrial symbiosis in Africa, highlight the current status, the current regulatory context, the challenges to the implementation of this model, and propose new paths for industrial symbiosis in Africa. The study carried out shows that there exists good potential for industrial symbiosis to thrive in Africa, owing to the type of economic activities and the waste generated in Africa. It also shows that if industrial symbiosis is implemented on a larger scale, it would contribute to the reduction of carbon emissions, reduce waste, and help Africa make more efficient use of its resources. However, for this to become a reality, concrete, well-thought-out actions must be taken at various levels to encourage all organizations to develop great synergy. Providing specific Industrial symbiosis-focused legislative frameworks, funding intervention from the government, and involvement of the government in the implementation of concise action plans are some aspects that can help increase the prospects of industrial symbiosis in African countries.
Bridging the Gap: Human Emotions and Animal Emotions
Authors: Mendl Michael , Neville Vikki , Paul Elizabeth S. 
Published: July 2022

AbstractOur experiences of the conscious mental states that we call emotions drive our interest in whether such states also exist in other animals. Because linguistic report can be used as a gold standard (albeit indirect) indicator of subjectiveemotional feelingsin humans but not other species, how can we investigate animal emotions and what exactly do we mean when we use this term? Linguistic reports of human emotion give rise toemotion concepts(discrete emotions; dimensional models), associated objectively measurable behavioral and bodilyemotion indicators, and understanding of theemotion contextsthat generate specific states. We argue that many animal studies implicitly translate human emotionconcepts,indicatorsandcontexts, but that explicit consideration of the underlying pathways of inference, their theoretical basis, assumptions, and pitfalls, and how they relate toconscious emotional feelings, is needed to provide greater clarity and less confusion in the conceptualization and scientific study of animal emotion.
Intimate hygiene practices and reproductive tract infections: A systematic review
Authors: Daher Alaa , Albaini Obey , Siff Lauren , Farah Stephanie , Jallad Karl 
Published: July 2022

AbstractIntroductionWorldwide, women perform a variety of vaginal practices to enhance their intimate hygiene and sexual health.ObjectiveTo conduct a systematic review to assess the different kinds of intimate hygiene practices and their association with reproductive tract infections and complications.MethodsPubMed, Medline and The Cochrane Library were used. Both observational and interventional studies targeting the urogenital infections and their association with hygiene practices were included. Exclusion criteria included studies that assessed the knowledge and attitudes towards intimate hygiene practices rather than their relation to infections. The design of this systematic review complied with the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA).ResultsFifteen articles were included. Intravaginal practices were found to be associated with reproductive tract infections. Reusable absorbent material used during menstruation increased the risk of Candida infection with an adjusted proportional reported ratio (aPRR) of 1.54 (95% CI 1.2–2.0), but no association with bacterial vaginosis ortrichomonas vaginalisinfection was noted. Bathing or vaginal washing during menstruation with water only showed a higher association with symptoms of urogenital infections when compared with washing with both soap and water during menstruation. Drying reusable pads inside the house and storing them inside the toilet was found to be associated with a higher candida infection prevalence. Moreover, bathing in sitting position during menstruation, not drying the genital area or using cloth for drying it, and not paying attention to hand washing, were all associated with a higher risk of genital infections. Finally, postpartum use of native homemade vaginal preparations might be a risk factor for ascending vaginal infections, and the use of inappropriate material for menstrual blood absorption was associated with secondary infertility.ConclusionSeveral hygiene practices put women at higher risk for reproductive tract infections. We should continue to increase awareness to counter the misinformation resulting from marketing campaigns and common misconceptions.
A Comparative Study of Vertical Mixing Schemes in Modeling the Bay of Bengal Dynamics
Authors: Tirodkar Siddhesh , Murtugudde Raghu , Behera Manasa R. , Balasubramanian Sridhar 
Published: July 2022

AbstractThe choice of vertical mixing scheme in ocean models plays an important role in modeling the surface and subsurface circulation and the vertical structure. This work performs a comparative study between K‐profile parametrization (KPP) and k‐ϵ mixing schemes for a regional domain in the Bay of Bengal (BoB) using the Modular Ocean Model version 5 (MOM5). It is observed that sea surface temperature (SST) and the mixed layer depth (MLD) show significant improvement with the k‐ϵ mixing scheme. Energetic analysis shows that changes in the viscous dissipation and turbulent buoyancy flux are the primary reason for improvement with k‐ϵ. The overestimation of viscous dissipation in the KPP scheme is corrected by k‐ϵ, resulting in a deeper mixed layer closer to observations. The tendency of buoyancy flux to retain stability in the water column also results in a better representation of SST in k‐ϵ. Overall, we conclude that the k‐ϵ mixing scheme works better for the BoB region.
Statistical Study on Small‐Scale (≤1,000 km) Density Irregularities in the Inner Magnetosphere
Authors: Gu Wenyao , Liu Xu , Xia Zhiyang , Chen Lunjin 
Published: July 2022

AbstractA statistical survey of small‐scale density irregularities near the magnetic equatorial region of the inner magnetosphere was performed using 7‐year Van Allen Probes data. The cross‐field sizes of these density irregularities are within the order of 1,000 km, corresponding to typical whistler‐mode wave ducts. Spatial distributions on L‐shells and magnetic local times as well as temporal distributions on geomagnetic indices were analyzed using density data in the plasmasphere, the plasmasphere boundary layer (PBL), and the plasma trough. Inside the plasmasphere, the density fluctuations occur predominantly in the night and dawn sectors at L = 2.5–5. They occur far from PBL and show no significant relation with geomagnetic indices. In the PBL at L > 4.5 and the plasma trough, density irregularities are concentrated in post‐midnight during quiet times and extend to all night sectors during active times. Density fluctuation values in the PBL are much higher than those in the other two regions. We discuss connections of irregularities deep inside the plasmasphere to ionospheric electric field disturbances and those in and near the PBL to interchange instabilities.
Intrinsic Dimensionality as a Metric for the Impact of Mission Design Parameters
Authors: Cawse‐Nicholson K. , Raiho A. M. , Thompson D. R. , Hulley G. C. , Miller C. E. , Miner K. R. , Poulter B. , Schimel D. , Schneider F. D. , Townsend P. A. , Zareh S. K. 
Published: July 2022

AbstractHigh‐resolution space‐based spectral imaging of the Earth's surface delivers critical information for monitoring changes in the Earth system as well as resource management and utilization. Orbiting spectrometers are built according to multiple design parameters, including ground sampling distance (GSD), spectral resolution, temporal resolution, and signal‐to‐noise ratio. Different applications drive divergent instrument designs, so optimization for wide‐reaching missions is complex. The Surface Biology and Geology component of NASA's Earth System Observatory addresses science questions and meets applications needs across diverse fields, including terrestrial and aquatic ecosystems, natural disasters, and the cryosphere. The algorithms required to generate the geophysical variables from the observed spectral imagery each have their own inherent dependencies and sensitivities, and weighting these objectively is challenging. Here, we introduce intrinsic dimensionality (ID), a measure of information content, as an applications‐agnostic, data‐driven metric to quantify performance sensitivity to various design parameters. ID is computed through the analysis of the eigenvalues of the image covariance matrix, and can be thought of as the number of significant principal components. This metric is extremely powerful for quantifying the information content in high‐dimensional data, such as spectrally resolved radiances and their changes over space and time. We find that the ID decreases for coarser GSD, decreased spectral resolution and range, less frequent acquisitions, and lower signal‐to‐noise levels. This decrease in information content has implications for all derived products. ID is simple to compute, providing a single quantitative standard to evaluate combinations of design parameters, irrespective of higher‐level algorithms, products, applications, or disciplines.
Integrating Connectivity Into Hydrodynamic Models: An Automated Open‐Source Method to Refine an Unstructured Mesh Using Remote Sensing
Authors: Wright Kyle , Passalacqua Paola , Simard Marc , Jones Cathleen E. 
Published: July 2022

AbstractHydrodynamic models are an essential tool for studying the movement of water and other materials across the Earth surface. However, models remain limited by practical constraints on size and resolution, particularly in coastal environments containing topologically complex and multi‐scale channel/wetland networks. Unstructured meshes have helped address this problem by allowing resolution to vary spatially, and many models support local mesh refinement using breaklines or internal regions‐of‐interest. However, there remains no standardized, objective, or easily reproducible method to implement internal features between different users. The present study aims to address whether remote sensing can fill in that gap, by embedding information about landscape structure and connectivity directly into model meshes. We present an automated image processing methodology for preserving dynamically active connected features in the unstructured shallow‐water model ANUGA, while reducing computational demand in less active areas of the domain. The Unstructured Mesh Refinement Method (UMRM) converts a binary input raster into a collection of closed, simple polygons which can be used to refine the mesh, meanwhile preserving connectivity and enforcing model‐related constraints. We apply this workflow to a large‐scale model of two coastal river deltas, and refine our mesh using time‐series of optical Planet imagery, InSAR measurements of water level change, and topographic data. We compare the results of the connectivity‐preserving mesh to results from a mesh using a uniform mesh resolution, and find that the UMRM decreased the computational demand by a third, without any discernible loss in accuracy when compared to in‐situ and remotely sensed water level measurements.
Reconstruction of the Regional Total Electron Content Maps Over the Korean Peninsula Using Deep Convolutional Generative Adversarial Network and Poisson Blending
Authors: Jeong Se‐Heon , Lee Woo Kyoung , Jang Soojeong , Kil Hyosub , Kim Jeong‐Heon , Kwak Young‐Sil , Kim Yong Ha , Hong Junseok , Choi Byung‐Kyu 
Published: July 2022

AbstractThis study reconstructs total electron content (TEC) maps in the vicinity of the Korean Peninsula by employing a deep convolutional generative adversarial network and Poisson blending (DCGAN‐PB). Our interest is to rebuild small‐scale ionosphere structures on the TEC map in a local region where pronounced ionospheric structures, such as the equatorial ionization anomaly, are absent. The reconstructed regional TEC maps have a domain of 120°–135.5°E longitude and 25.5°–41°N latitude with 0.5° resolution. To achieve this, we first train a DCGAN model by using the International Reference Ionosphere‐based TEC maps from 2002 to 2019 (except for 2010 and 2014) as a training data set. Next, the trained DCGAN model generates synthetic complete TEC maps from observation‐based incomplete TEC maps. Final TEC maps are produced by blending of synthetic TEC maps with observed TEC data by PB. The performance of the DCGAN‐PB model is evaluated by testing the regeneration of the masked TEC observations in 2010 (solar minimum) and 2014 (solar maximum). Our results show that a good correlation between the masked and model‐generated TEC values is maintained even with a large percentage (∼80%) of masking. The performance of the DCGAN‐PB model is not sensitive to local time, solar activity, and magnetic activity. Thus, the DCGAN‐PB model can reconstruct fine ionospheric structures in regions where observations are sparse and distinguishing ionospheric structures are absent. This model can contribute to near real‐time monitoring of the ionosphere by immediately providing complete TEC maps.
Views of health care users and providers: Solutions to improve the prevention of secondary health conditions among people with spinal cord injury, South Africa
Authors: Pilusa Sonti , Myezwa Hellen , Potterton Joanne 
Published: July 2022

Abstract
Study design
Explorative- qualitative study.

Objective
This study explored solutions to improve the prevention of secondary health conditions in people with spinal cord injury.

Setting
Rehabilitation hospital, South Africa.

Methods
Face to face semi-structured interviews were conducted with 21 therapists and 17 people with spinal cord injury at a public rehabilitation hospital. All the interviews were transcribed verbatim. Content analysis was conducted on the transcripts to identify proposed solutions to improve the prevention of secondary health conditions.

Results
The main theme that emerged was access to adequate health care. The categories linked to the main theme were: availability of health services, patient-centred care, strengthening rehabilitation care, access to resources and training health professionals.

Conclusions
Access to adequate health is central to preventing and managing secondary health conditions. Care for people with spinal cord injury needs to be empowering and address rehabilitation care needs across the lifespan. The proposed solutions will inform the development of a prevention care model for secondary health conditions in people with spinal cord injury.
Interplay of Nrf2 and BACH1 in inducing ferroportin expression and enhancing resistance of human macrophages towards ferroptosis
Authors: Namgaladze Dmitry , Fuhrmann Dominik C. , Brüne Bernhard 
Published: July 2022

AbstractCompared to cancer cells, macrophages are inert to lipid peroxidation-triggered, iron-dependent cell death known as ferroptosis. Mechanisms underlying macrophage resistance towards ferroptosis are largely obscure. Here, we show that human primary macrophages respond to RSL3, a ferroptosis-inducing inhibitor of glutathione peroxidase 4, by upregulating mRNA expression of the iron transporter ferroportin. RSL3 induces lipid peroxidation, and both, lipid peroxidation as well as ferroportin induction were attenuated by liproxstatin-1, an inhibitor of lipid peroxidation and ferroptosis blocker. At the same time, system xc– inhibitor erastin fails to elicit lipid peroxidation or ferroportin expression. Ferroportin induction in response to RSL3 demands nuclear accumulation of the redox-sensitive transcription factor Nrf2 and downregulation of the transcriptional repressor BACH1. Silencing ferroportin or Nrf2 increases the cellular labile iron pool and lipid peroxidation, thereby sensitizing cells towards ferroptosis following RSL3 treatments. In contrast, silencing BACH1 decreases the labile iron pool and lipid peroxidation, enhancing macrophage resistance towards ferroptosis. Our findings reveal Nrf2, BACH1, and ferroportin as important regulators, protecting human macrophages against ferroptosis.
The splicing factor SF3B4 drives proliferation and invasion in cervical cancer by regulating SPAG5
Authors: Li Yingwei , Diao Yuchao , Wang Zixiang , Wang Shourong , Peng Jiali , Kong Beihua 
Published: July 2022

AbstractRegulation of alternative splicing (AS) by the splicing factor 3b (SF3B) family plays an essential role in cancer. However, the biological function of SF3B family members in cervical cancer (CC) needs to be further elucidated. In this study, we found that splicing factor 3b subunit 4 (SF3B4) was highly expressed in CC by bioinformatics analysis using cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) data from The Cancer Genome Atlas (TCGA). Then, we demonstrated that high expression of SF3B4 promoted proliferation and invasion abilities of CC cells in vitro and in vivo and that reduced expression of SF3B4 performed the opposite effect. Further RNA-seq and AS analysis showed that sperm-associated antigen 5 (SPAG5) was a downstream target gene of SF3B4. Interestingly, SPAG5 expression was decreased after SF3B4 knockdown because of retained introns (RIs) and reduced maturation of SPAG5 pre-mRNA. Importantly, SPAG5 deficiency impaired the oncogenic effects of SF3B4 overexpression on CC cells. In conclusion, SF3B4 promotes CC progression by regulating the effective splicing of SPAG5. SF3B4 could be a promising target for CC.