bluuebunny/crossref_metadata_2025_split huggingface dataset:
Investigation of social and cognitive predictors in non-transition ultra-high-risk’ individuals for psychosis using spiking neural networks
Authors: Doborjeh Zohreh , Doborjeh Maryam , Sumich Alexander , Singh Balkaran , Merkin Alexander , Budhraja Sugam , Goh Wilson , Lai Edmund M-K , Williams Margaret , Tan Samuel , Lee Jimmy , Kasabov Nikola 
Published: February 2023

AbstractFinding predictors of social and cognitive impairment in non-transition Ultra-High-Risk individuals (UHR) is critical in prognosis and planning of potential personalised intervention strategies. Social and cognitive functioning observed in youth at UHR for psychosis may be protective against transition to clinically relevant illness. The current study used a computational method known as Spiking Neural Network (SNN) to identify the cognitive and social predictors of transitioning outcome. Participants (90 UHR, 81 Healthy Control (HC)) completed batteries of neuropsychological tests in the domains of verbal memory, working memory, processing speed, attention, executive function along with social skills-based performance at baseline and 4 × 6-month follow-up intervals. The UHR status was recorded as Remitters, Converters or Maintained. SNN were used to model interactions between variables across groups over time and classify UHR status. The performance of SNN was examined relative to other machine learning methods. Higher interaction between social and cognitive variables was seen for the Maintained, than Remitter subgroup. Findings identified the most important cognitive and social variables (particularly verbal memory, processing speed, attention, affect and interpersonal social functioning) that showed discriminative patterns in the SNN models of HC vs UHR subgroups, with accuracies up to 80%; outperforming other machine learning models (56–64% based on 18 months data). This finding is indicative of a promising direction for early detection of social and cognitive impairment in UHR individuals that may not anticipate transition to psychosis and implicate early initiated interventions to stem the impact of clinical symptoms of psychosis.
A distinction between Fritillaria Cirrhosa Bulbus and Fritillaria Pallidiflora Bulbus via LC–MS/MS in conjunction with principal component analysis and hierarchical cluster analysis
Authors: Liu Chuanlan , Liu Simei , Tse Wai Ming , Tse Kathy Wai Gaun , Erbu Aga , Xiong Hai , Lanzi Gongga , Liu Yanyong , Ye Bengui 
Published: February 2023

AbstractFritillaria Cirrhosa Bulbus (known as chuanbeimu in Chinese, FCB) is one of the most used Chinese medicines for lung disease. However, a variety of substitutes have entered the market, with Fritillaria Pallidiflora Bulbus (FPB) being the most common. Due to their similarity in appearance, morphology, and chemical composition but a large price difference, the FCB has frequently been adulterated with the FPB, posing a serious challenge to the distinction and quality of the FCB. Therefore, we aimed to distinguish FCB and FPB based on their main nine isosteroidal alkaloid contents and test the potential of chemometrics as a discrimination approach for evaluating quality. The nine major isosteroidal alkaloids were measured using a liquid chromatography with tandem mass spectrometry (LC–MS/MS) approach in 41 batches of FCB and 17 batches of FPB. Additionally, they were categorized and distinguished using the methods of hierarchical cluster analysis (HCA) and principal component analysis (PCA). Quantitative analysis revealed that the nine alkaloids were present in different amounts in the two types of Fritillariae bulbus. In FCB, the highest amount was peimisine (17.92–123.53 μg/g) and the lowest was delavine (0.42–29.18 μg/g), while in FPB, imperialine was higher (78.05–344.09 μg/g), but verticinone and verticine were less than the other seven alkaloids. The FCB and FPB were successfully classified and distinguished by the HCA and PCA. Taken together, the method has a good linear relationship (R2 > 0.9975). The LOD and LOQ of the nine alkaloids were in the range of 0.0651–0.6510 and 0.1953–1.9531 ng/mL, respectively. The intra- and inter-day precision were shown to be excellent, with relative standard deviations (RSDs) below 1.63% and 2.39%, respectively. The LC–MS/MS method in conjunction with HCA and PCA can effectively differentiate FCB and FPB. It may be a promising strategy for quality evaluation and control at the FCB.
Automatic diagnosis of retention pseudocyst in the maxillary sinus on panoramic radiographs using a convolutional neural network algorithm
Authors: Ha Eun-Gyu , Jeon Kug Jin , Choi Hanseung , Lee Chena , Choi Yoon Joo , Han Sang-Sun 
Published: February 2023

AbstractThe evaluation of the maxillary sinus is very important in dental practice such as tooth extraction and implantation because of its proximity to the teeth, but it is not easy to evaluate because of the overlapping structures such as the maxilla and the zygoma on panoramic radiographs. When doom-shaped retention pseudocysts are observed in sinus on panoramic radiographs, they are often misdiagnosed as cysts or tumors, and additional computed tomography is performed, resulting in unnecessary radiation exposure and cost. The purpose of this study was to develop a deep learning model that automatically classifies retention pseudocysts in the maxillary sinuses on panoramic radiographs. A total of 426 maxillary sinuses from panoramic radiographs of 213 patients were included in this study. These maxillary sinuses included 86 sinuses with retention pseudocysts, 261 healthy sinuses, and 79 sinuses with cysts or tumors. An EfficientDet model first introduced by Tan for detecting and classifying the maxillary sinuses was developed. The developed model was trained for 200 times on the training and validation datasets (342 sinuses), and the model performance was evaluated in terms of accuracy, sensitivity, and specificity on the test dataset (21 retention pseudocysts, 43 healthy sinuses, and 20 cysts or tumors). The accuracy of the model for classifying retention pseudocysts was 81%, and the model also showed higher accuracy for classifying healthy sinuses and cysts or tumors (98% and 90%, respectively). One of the 21 retention pseudocysts in the test dataset was misdiagnosed as a cyst or tumor. The proposed model for automatically classifying retention pseudocysts in the maxillary sinuses on panoramic radiographs showed excellent diagnostic performance. This model could help clinicians automatically diagnose the maxillary sinuses on panoramic radiographs.
Advances in NK cell therapy for brain tumors
Authors: Fares Jawad , Davis Zachary B. , Rechberger Julian S. , Toll Stephanie A. , Schwartz Jonathan D. , Daniels David J. , Miller Jeffrey S. , Khatua Soumen 
Published: February 2023

AbstractDespite advances in treatment regimens that comprise surgery, chemotherapy, and radiation, outcome of many brain tumors remains dismal, more so when they recur. The proximity of brain tumors to delicate neural structures often precludes complete surgical resection. Toxicity and long-term side effects of systemic therapy remain a concern. Novel therapies are warranted. The field of NK cell-based cancer therapy has grown exponentially and currently constitutes a major area of immunotherapy innovation. This provides a new avenue for the treatment of cancerous lesions in the brain. In this review, we explore the mechanisms by which the brain tumor microenvironment suppresses NK cell mediated tumor control, and the methods being used to create NK cell products that subvert immune suppression. We discuss the pre-clinical studies evaluating NK cell-based immunotherapies that target several neuro-malignancies and highlight advances in molecular imaging of NK cells that allow monitoring of NK cell-based therapeutics. We review current and ongoing NK cell based clinical trials in neuro-oncology.
Enhanced hexamerization of insulin via assembly pathway rerouting revealed by single particle studies
Authors: Bohr Freja , Bohr Søren S. -R. , Mishra Narendra Kumar , González-Foutel Nicolás Sebastian , Pinholt Henrik Dahl , Wu Shunliang , Nielsen Emilie Milan , Zhang Min , Kjaergaard Magnus , Jensen Knud J. , Hatzakis Nikos S. 
Published: February 2023

AbstractInsulin formulations with diverse oligomerization states are the hallmark of interventions for the treatment of diabetes. Here using single-molecule recordings we firstly reveal that insulin oligomerization can operate via monomeric additions and secondly quantify the existence, abundance and kinetic characterization of diverse insulin assembly and disassembly pathways involving addition of monomeric, dimeric or tetrameric insulin species. We propose and experimentally validate a model where the insulin self-assembly pathway is rerouted, favoring monomeric or oligomeric assembly, by solution concentration, additives and formulations. Combining our practically complete kinetic characterization with rate simulations, we calculate the abundance of each oligomeric species from nM to mM offering mechanistic insights and the relative abundance of all oligomeric forms at concentrations relevant both for secreted and administrated insulin. These reveal a high abundance of all oligomers and a significant fraction of hexamer resulting in practically halved bioavailable monomer concentration. In addition to providing fundamental new insights, the results and toolbox presented here can be universally applied, contributing to the development of optimal insulin formulations and the deciphering of oligomerization mechanisms for additional proteins.
Blockchain‐oriented location privacy preserving for cooperative spectrum sensing in 6G wireless networks
Authors: Vuppula Roopa , Pradhan Himansu Shekhar 
Published: February 2023

AbstractIn this article, the authors proposed a novel blockchain‐oriented location privacy‐preserving (BoLPP) for the Cooperative Spectrum Sensing (CSS) in 6G networks. In order to attain the sustainability of privacy and security for 6G wireless networks, it is a great challenge in this sensing as it faces various malicious attacks while the secondary user (SU) is active. To tackle these issues, the authors proposed a novel framework for blockchain‐oriented Cognitive Radio Networks (CRNs) for CSS using an energy detection technique. Moreover, the authors implemented another novel paradigm BoLPP, to attain the privacy of SUs location for CSS in 6G networks. This approach preserves the SUs’ location and makes the BoLPP framework immune to all malicious attackers. The simulation results have been undergone based on the performance metrics such as response time, consistency, probability of false alarm, frame loss (%), average network throughput, energy efficiency, and security. The outcomes reveal that the proposed scheme achieves high security, privacy, energy efficiency, average network throughput, and low probability of false alarm and frame loss (%) when compared with the existing frameworks such as Friend or Foe (FoF) and Tidal Trust Algorithm (TTA) mechanisms. It is observed that the proposed BoLPP mechanism provides better security and privacy in 6G wireless networks.
Observer‐based adaptive emotional command‐filtered backstepping for cooperative control of input‐saturated uncertain strict‐feedback multi‐agent systems
Authors: Parsa Pooya , Akbarzadeh‐T Mohammad‐Reza , Baghbani Fahimeh 
Published: February 2023

AbstractThis paper introduces a distributed observer‐based emotional command‐filtered backstepping (DOECFB) approach for leader‐following cooperative output‐feedback control of heterogenous strict‐feedback multi‐agent systems (MAS) under mismatched uncertainties and input saturation. A novel state observer is designed based on radial‐basis emotional neural networks (RBENNs) that approximate uncertainties of model dynamics. To model inter‐agent dynamics with less complexity, emotion‐inspired approximated dynamics are shared among neighbouring followers, like emotional contagion in a group of people. An auxiliary system is also used to attenuate input saturation's negative effect on the cooperative tracking performance. Also, command filters and compensating signals are applied to avoid the ‘explosion of complexity’ in the backstepping design. Only local information from other agents is required for the proposed approach to guarantee convergence of the cooperative tracking error to a small region around zero and cooperatively semi‐globally uniformly ultimately boundedness of closed‐loop signals. Simulation examples on a second‐order uncertain MAS and multiple forced‐damped pendulums are conducted, and quantitative comparisons verify the effectiveness of DOECFB and the proposed observer.
Intelligent energy management scheme‐based coordinated control for reducing peak load in grid‐connected photovoltaic‐powered electric vehicle charging stations
Authors: Amir Mohammad , Zaheeruddin  , Haque Ahteshamul , Bakhsh Farhad Ilahi , Kurukuru V. S. Bharath , Sedighizadeh Mostafa 
Published: February 2023

AbstractSolar‐based Distributed Generation (DG) powered Electric Vehicles (EVs) charging stations are widely adopted nowadays in the power system networks. In this process, the distribution grid faces various challenges caused by intermittent solar irradiance, peak EVs load, while controlling the state of charge (SoC) of batteries during dis(charging) phenomena. In this paper, an intelligent energy management scheme (IEMS)‐based coordinated control for photovoltaic (PV)‐based EVs charging stations is proposed. The proposed IEMS optimizes the PV generation and grid power utilization for EV charging stations (EVCS) by analysing real‐time meteorological and load demand data. The coordinated control of EMS provides power flow between PV generation, distribution grid, and EVs battery storage in a manner which results in the reduction of peak power demand by a factor of two. Further, the adaptive neuro‐based fuzzy control approach includes forecasting solar‐based electricity generation and EVs loads demand predictions to optimize IEMS according to the Indian power scenario. The proposed IEMS optimally utilizes the buffer batteries system for reducing the peak electricity demand with low system losses and reducing the impact of EVs charging load on distribution grid. The results are analysed using the digital simulation model and validated with real‐time hardware‐in‐loop experimental setup.
WEAVE-StePS: A stellar population survey using WEAVE at WHT
Authors: Iovino A. , Poggianti B. M. , Mercurio A. , Longhetti M. , Bolzonella M. , Busarello G. , Gullieuszik M. , La Barbera F. , Merluzzi P. , Morelli L. , Tortora C. , Vergani D. , Zibetti S. , Haines C. P. , Costantin L. , Ditrani F. R. , Pozzetti L. , Angthopo J. , Balcells M. , Bardelli S. , Benn C. R. , Bianconi M. , Cassarà L. P. , Corsini E. M. , Cucciati O. , Dalton G. , Ferré-Mateu A. , Fossati M. , Gallazzi A. , García-Benito R. , Granett B. , González Delgado R. M. , Ikhsanova A. , Iodice E. , Jin S. , Knapen J. H. , McGee S. , Moretti A. , Murphy D. N. A. , Peralta de Arriba L. , Pizzella A. , Sánchez-Blázquez P. , Spiniello C. , Talia M. , Trager S. C. , Vazdekis A. , Vulcani B. , Zucca E. 
Published: February 2023

Context.The upcoming new generation of optical spectrographs on four-meter-class telescopes will provide valuable opportunities for forthcoming galaxy surveys through their huge multiplexing capabilities, excellent spectral resolution, and unprecedented wavelength coverage.Aims.WEAVE is a new wide-field spectroscopic facility mounted on the 4.2 mWilliam HerschelTelescope in La Palma. WEAVE-StePS is one of the five extragalactic surveys that will use WEAVE during its first five years of operations. It will observe galaxies using WEAVE MOS (∼950 fibres distributed across a field of view of ∼3 square degrees on the sky) in low-resolution mode (R ∼ 5000, spanning the wavelength range 3660 − 9590 Å).Methods.WEAVE-StePS will obtain high-quality spectra (S/N ∼ 10 Å−1atR ∼ 5000) for a magnitude-limited (IAB = 20.5) sample of ∼25 000 galaxies, the majority selected atz ≥ 0.3. The survey goal is to provide precise spectral measurements in the crucial interval that bridges the gap between LEGA-C and SDSS data. The wide area coverage of ∼25 square degrees will enable us to observe galaxies in a variety of environments. The ancillary data available in each of the observed fields (including X-ray coverage, multi-narrow-band photometry and spectroscopic redshift information) will provide an environmental characterisation for each observed galaxy.Results.This paper presents the science case of WEAVE-StePS, the fields to be observed, the parent catalogues used to define the target sample, and the observing strategy that was chosen after a forecast of the expected performance of the instrument for our typical targets.Conclusions.WEAVE-StePS will go back further in cosmic time than SDSS, extending its reach to encompass more than ∼6 Gyr. This is nearly half of the age of the Universe. The spectral and redshift range covered by WEAVE-StePS will open a new observational window by continuously tracing the evolutionary path of galaxies in the largely unexplored intermediate-redshift range.
Implementation Fidelity of Chatbot Screening for Social Needs: Acceptability, Feasibility, Appropriateness
Authors: Langevin Raina , Berry Andrew B. L. , Zhang Jinyang , Fockele Callan E. , Anderson Layla , Hsieh Dennis , Hartzler Andrea , Duber Herbert C. , Hsieh Gary 
Published: February 2023

Abstract
Objectives Patient and provider-facing screening tools for social determinants of health have been explored in a variety of contexts; however, effective screening and resource referral remain challenging, and less is known about how patients perceive chatbots as potential social needs screening tools. We investigated patient perceptions of a chatbot for social needs screening using three implementation outcome measures: acceptability, feasibility, and appropriateness.
Methods We implemented a chatbot for social needs screening at one large public hospital emergency department (ED) and used concurrent triangulation to assess perceptions of the chatbot use for screening. A total of 350 ED visitors completed the social needs screening and rated the chatbot on implementation outcome measures, and 22 participants engaged in follow-up phone interviews.
Results The screened participants ranged in age from 18 to 90 years old and were diverse in race/ethnicity, education, and insurance status. Participants (n = 350) rated the chatbot as an acceptable, feasible, and appropriate way of screening. Through interviews (n = 22), participants explained that the chatbot was a responsive, private, easy to use, efficient, and comfortable channel to report social needs in the ED, but wanted more information on data use and more support in accessing resources.
Conclusion In this study, we deployed a chatbot for social needs screening in a real-world context and found patients perceived the chatbot to be an acceptable, feasible, and appropriate modality for social needs screening. Findings suggest that chatbots are a promising modality for social needs screening and can successfully engage a large, diverse patient population in the ED. This is significant, as it suggests that chatbots could facilitate a screening process that ultimately connects patients to care for social needs, improving health and well-being for members of vulnerable patient populations.
Amide N–C Bond Activation: A Graphical Overview of Acyl and Decarbonylative Coupling
Authors: Liu Chengwei , Szostak Michal 
Published: February 2023

AbstractThis Graphical Review provides an overview of amide bond activation achieved by selective oxidative addition of the N–C(O) acyl bond to transition metals and nucleophilic acyl addition, resulting in acyl and decarbonylative coupling, together with key mechanistic details pertaining to amide bond distortion underlying this reactivity manifold.
Presurgical Perspective and Postsurgical Evaluation of Tibial Pilon Fractures
Authors: Piña-Rivas Alexandra , Mut-Pons Raul , Llopis Eva 
Published: February 2023

AbstractTibial pilon fractures represent only a small percentage of all fractures of the lower limb. But they are a feared entity, both for the interpreting radiologist and the treating surgeon and, ultimately, for the patient because they involve the weight-bearing area of the joint and often have associated soft tissue injury. These factors make them technically challenging, with poor clinical and functional results in many patients, even when a perfect joint reduction is achieved. Presurgical evaluation with computed tomography and individualized staged management is critical for the prognosis, a definitive treatment strategy, and the prevention of future complications.
Presurgical Perspective and Postsurgical Evaluation of the Plantar Fascia
Authors: Beltran Luis S. 
Published: February 2023

AbstractThe plantar fascia is an important structure in the foot that acts as a major stabilizer of the longitudinal arch, along with the midfoot ligaments and intrinsic and extrinsic muscles. It is composed predominantly of longitudinally oriented collagen fibers that vary in thickness and are organized into bundles closely associated with the interstitial tissues of the foot. This composition enables the plantar fascia to withstand the weight-bearing forces concentrated on the foot while standing, jumping, walking, or running. This article discusses the normal anatomy and the various pathologies that affect the plantar fascia with an emphasis on presurgical and postoperative appearances on magnetic resonance and ultrasonography imaging.
Presurgical Perspective and Postsurgical Evaluation of Morton's Neuroma and Other Nerve Lesions
Authors: Zanetti Marco , Saupe Nadja 
Published: February 2023

AbstractMagnetic resonance imaging (MRI) is a robust method used for both preoperative and postoperative evaluation of Morton's neuroma and other neural lesions. MRI is used to confirm the diagnosis and for precise localization, estimation of outcome, and differential diagnoses. The differential diagnoses include mechanically induced plantar plate ruptures with associated Morton's neuroma–like tumors in the intermetatarsal/interdigital spaces; mechanical fibrosis cushion formations and pseudo bursae in the plantar foot adipose tissue; rheumatologic affections, such as rheumatoid nodules, gouty nodules, and intermetatarsal bursitis; and lastly the tenosynovial giant cell tumor (formerly called pigmented villonodular synovitis). In the postoperative evaluation after resection of Morton's neuroma, the same differential diagnoses must be considered as in the preoperative evaluation. Similarly, a high prevalence (up to 25%) of asymptomatic Morton's neuroma–like findings in the intermetatarsal and interdigital spaces should be kept in mind when interpreting postoperative recurrent forefoot pain after Morton's neuroma resection.