bluuebunny/crossref_metadata_2025_split huggingface dataset:
A skin-specific α-Synuclein seeding amplification assay for diagnosing Parkinson’s disease
Authors: Kuang Yaoyun , Mao Hengxu , Gan Tingting , Guo Wenyuan , Dai Wei , Huang Weimeng , Wu Zhuohua , Li Hongyan , Huang Xiaoyun , Yang Xinling , Xu Ping-Yi 
Published: July 2024

AbstractThe seeding amplification assay (SAA) has recently emerged as a valuable tool for detecting α-synuclein (αSyn) aggregates in various clinically accessible biospecimens. Despite its efficiency and specificity, optimal tissue-specific conditions for distinguishing Parkinson’s disease (PD) from non-PD outside the brain remain underexplored. This study systematically evaluated 150 reaction conditions to identify the one with the highest discriminatory potential between PD and non-synucleinopathy controls using skin samples, resulting in a modified SAA. The streamlined SAA achieved an overall sensitivity of 92.46% and specificity of 93.33% on biopsy skin samples from 332 PD patients and 285 controls within 24 h. Inter-laboratory reproducibility demonstrated a Cohen’s kappa value of 0.87 (95% CI 0.69–1.00), indicating nearly perfect agreement. Additionally, αSyn seeds in the skin were stable at −80 °C but were vulnerable to short-term exposure to non-ultra-low temperatures and grinding. This study thoroughly investigated procedures for sample preprocessing, seed amplification, and storage, introducing a well-structured experimental framework for PD diagnosis using skin samples.
Global evaluation of current and future threats to drylands and their vertebrate biodiversity
Authors: Lewin Amir , Murali Gopal , Rachmilevitch Shimon , Roll Uri 
Published: July 2024

AbstractDrylands are often overlooked in broad conservation frameworks and development priorities and face increasing threats from human activities. Here we evaluated the formal degree of protection of global drylands, their land vertebrate biodiversity and current threats, and projected human-induced land-use changes to drylands under different future climate change and socioeconomic scenarios. Overall, drylands have lower protected-area coverage (12%) compared to non-drylands (21%). Consequently, most dryland vertebrates including many endemic and narrow-ranging species are inadequately protected (0–2% range coverage). Dryland vertebrates are threatened by varied anthropogenic factors—including agricultural and infrastructure development (that is, artificial structures, surfaces, roads and industrial sites). Alarmingly, by 2100 drylands are projected to experience some degree of land conversion in 95–100% of their current natural habitat due to urban, agricultural and alternative energy expansion. This loss of undisturbed dryland regions is expected across different socioeconomic pathways, even under optimistic scenarios characterized by progressive climate policies and moderate socioeconomic trends.
AI-based differential diagnosis of dementia etiologies on multimodal data
Authors: Xue Chonghua , Kowshik Sahana S. , Lteif Diala , Puducheri Shreyas , Jasodanand Varuna H. , Zhou Olivia T. , Walia Anika S. , Guney Osman B. , Zhang J. Diana , Poésy Serena , Kaliaev Artem , Andreu-Arasa V. Carlota , Dwyer Brigid C. , Farris Chad W. , Hao Honglin , Kedar Sachin , Mian Asim Z. , Murman Daniel L. , O’Shea Sarah A. , Paul Aaron B. , Rohatgi Saurabh , Saint-Hilaire Marie-Helene , Sartor Emmett A. , Setty Bindu N. , Small Juan E. , Swaminathan Arun , Taraschenko Olga , Yuan Jing , Zhou Yan , Zhu Shuhan , Karjadi Cody , Alvin Ang Ting Fang , Bargal Sarah A. , Plummer Bryan A. , Poston Kathleen L. , Ahangaran Meysam , Au Rhoda , Kolachalama Vijaya B. 
Published: July 2024

Abstract
Differential diagnosis of dementia remains a challenge in neurology due to symptom overlap across etiologies, yet it is crucial for formulating early, personalized management strategies. Here, we present an artificial intelligence (AI) model that harnesses a broad array of data, including demographics, individual and family medical history, medication use, neuropsychological assessments, functional evaluations and multimodal neuroimaging, to identify the etiologies contributing to dementia in individuals. The study, drawing on 51,269 participants across 9 independent, geographically diverse datasets, facilitated the identification of 10 distinct dementia etiologies. It aligns diagnoses with similar management strategies, ensuring robust predictions even with incomplete data. Our model achieved a microaveraged area under the receiver operating characteristic curve (AUROC) of 0.94 in classifying individuals with normal cognition, mild cognitive impairment and dementia. Also, the microaveraged AUROC was 0.96 in differentiating the dementia etiologies. Our model demonstrated proficiency in addressing mixed dementia cases, with a mean AUROC of 0.78 for two co-occurring pathologies. In a randomly selected subset of 100 cases, the AUROC of neurologist assessments augmented by our AI model exceeded neurologist-only evaluations by 26.25%. Furthermore, our model predictions aligned with biomarker evidence and its associations with different proteinopathies were substantiated through postmortem findings. Our framework has the potential to be integrated as a screening tool for dementia in clinical settings and drug trials. Further prospective studies are needed to confirm its ability to improve patient care.
Fake views removal and popularity on YouTube
Authors: Castaldo Maria , Frasca Paolo , Venturini Tommaso , Gargiulo Floriana 
Published: July 2024

AbstractThis paper analyses how YouTube authenticates engagement metrics and, more specifically, how the platform corrects view counts by removing “fake views” (i.e., views considered artificial or illegitimate by the platform). Working with one and a half years of data extracted from a thousand French YouTube channels, we show the massive extent of the corrections done by YouTube, which concern the large majority of the channels and over 78% of the videos in our corpus. Our analysis shows that corrections are not done continuously as videos collect new views, but instead occur in batches, generally around 5 p.m. every day. More significantly, most corrections occur relatively late in the life of the videos, after they have reached most of their audience, and the delay in correction is not independent of the final popularity of videos: videos corrected later in their life are more popular on average than those corrected earlier. We discuss the probable causes of this phenomenon and its possible negative consequences on content diffusion. By inflating view counts, fake views could make videos appear more popular than they are and unwarrantedly encourage their recommendation, thus potentially altering the public debate on the platform. This could have implications on the spread of online misinformation, but their in-depth exploration requires first-hand information on view corrections, which YouTube does not provide through its API. This paper presents a series of experimental techniques to work around this limitation, offering a practical contribution to the study of online attention cycles (as described in the “Data and methods” section). At the same time, this paper is also a call for greater transparency by YouTube and other online platforms about information with crucial implications for the quality of online debate.
Leveraging AI techniques for predicting spatial distribution and determinants of carbon emission in China's Yangtze River Delta
Authors: Zhang Wen , Yuan Weijun , Xuan Wei , Lu Yanfei , Huang Zhaoxu 
Published: July 2024

AbstractThis study focuses on the prediction and management of carbon emissions (CE) under the backdrop of global warming, with a particular emphasis on developing spatial planning strategies for urban clusters. In this context, we integrate artificial intelligence technologies to devise an optimized spatial analysis method based on the attributes of multi-source, urban-level spatio-temporal big data on CE. This method enhances both the accuracy and interpretability of CE data processing. Our objectives are to accurately analyze the current status of CE, predict the future spatial distribution of urban CE in the Yangtze River Delta (YRD), and identify key driving factors. We aim to provide pragmatic recommendations for sustainable urban carbon management planning. The findings indicate that: (1) the algorithm designed by us demonstrates excellent fitting capabilities in the analysis of CE data in the YRD, achieving a fitting accuracy of 0.93; (2) it is predicted that from 2025 to 2030, areas with higher CE in the YRD will be primarily concentrated in the 'Provincial Capital Belt' and the 'Heavy Industry Belt'; (3) the economic foundation has been identified as the most significant factor influencing CE in the YRD; (4) projections suggest that CE in the YRD are likely to peak by 2030.
Advanced extraction of PV parameters’ models based on electric field impacts on semiconductor conductivity using QIO algorithm
Authors: Bayoumi Ahmed S. A. , El Sehiemy Ragab A. , El-Kemary Maged , Abaza Amlak 
Published: July 2024

AbstractThis article presents a novel approach for parameters estimation of photovoltaic cells/modules using a recent optimization algorithm called quadratic interpolation optimization algorithm (QIOA). The proposed formula is dependent on variable voltage resistances (VVR) implementation of the series and shunt resistances. The variable resistances reduced from the effect of the electric field on the semiconductor conductivity should be included to get more accurate representation. Minimizing the mean root square error (MRSE) between the measured (I–V) dataset and the extracted (V–I) curve from the proposed electrical model is the main goal of the current optimization problem. The unknown parameters of the proposed PV models under the considered operating conditions are identified and optimally extracted using the proposed QIOA. Two distinct PV types are employed with normal and low radiation conditions. The VVR TDM is proposed for (R.T.C. France) silicon PV operating at normal radiation, and eleven unknown parameters are optimized. Additionally, twelve unknown parameters are optimized for a Q6-1380 multi-crystalline silicon (MCS) (area 7.7 cm2) operating under low radiation. The efficacy of the QIOA is demonstrated through comparison with four established optimizers: Grey Wolf Optimization (GWO), Particle Swarm Optimization (PSO), Salp Swarm Algorithm (SSA), and Sine Cosine Algorithm (SCA). The proposed QIO method achieves the lowest absolute current error values in both cases, highlighting its superiority and efficiency in extracting optimal parameters for both Single-Crystalline Silicon (SCS) and MCS cells under varying irradiance levels. Furthermore, simulation results emphasize the effectiveness of QIO compared to other algorithms in terms of convergence speed and robustness, making it a promising tool for accurate and efficient PV parameter estimation.
Electrophysiological and biochemical effect of zinc oxide nanoparticles on heart functions of male Wistar rats
Authors: Hussein Aida Ahmed , Moatamed Eman Raafat , El-desoky Mohamed Mahmoud , El Khayat Zakaria 
Published: July 2024

AbstractZinc oxide nanoparticles (ZnO NPs) are one of the most abundantly used nanomaterials in cosmetics and topical products, and nowadays, they are explored in drug delivery and tissue engineering. Some recent data evidenced that they are responsible for cardiotoxic effects and systemic toxicity. The present study aimed to investigate the toxic effect of ZnO NPs (39 nm) on the heart of Wistar rats and to perform a dose–response relationship using three different dose levels (25, 50, 100 mg/kg bw) of ZnO NPs on the electrocardiogram (ECG) readings, the levels of biochemical function parameters of heart, and the oxidative stress and antioxidant biomarkers. Furthermore, zinc concentration level and histopathological examination of heart tissues were determined. ZnO NPs showed a dose-dependent effect, as the 100 mg/kg bw ZnO NPs treated group showed the most significant changes in ECGs parameters: R–R distance, P–R interval, R and T amplitudes, and increased levels of heart enzymes Creatine Kinase- MB (CK-MB) and Lactate dehydrogenase (LDH). On the other hand, elevated zinc concentration levels, oxidative stress biomarkers MDA and NO, and decreased GSH levels were found also in a dose-dependent manner, the results were supported by impairment in the histopathological structure of heart tissues. While the dose of 100 mg/kg bw of ZnO bulk group showed no significant effects on heart function. The present study concluded that ZnO NPs could induce cardiac dysfunctions and pathological lesions mainly in the high dose.
A smartphone application toward detection of systolic hypertension in underserved populations
Authors: Landry Cederick , Dhamotharan Vishaal , Freithaler Mark , Hauspurg Alisse , Muldoon Matthew F. , Shroff Sanjeev G. , Chandrasekhar Anand , Mukkamala Ramakrishna 
Published: July 2024

AbstractHigh systolic blood pressure (BP) is the most important modifiable risk factor for cardiovascular disease. Managing systolic hypertension is especially difficult in underserved populations wherein access to cuff BP devices is limited. We showed that ubiquitous smartphones without force sensing can be converted into absolute pulse pressure (PP) monitors. The concept is for the user to perform guided thumb and hand maneuvers with the phone to induce cuff-like actuation and allow built-in sensors to make cuff-like measurements for computing PP. We developed an Android smartphone PP application. The ‘app’ could be learned by volunteers and yielded PP with total error < 8 mmHg against cuff PP (N = 24). We also analyzed a large population-level database comprising adults less than 65 years old to show that PP plus other basic information can detect systolic hypertension with ROC AUC of 0.9. The smartphone PP app could ultimately help reduce the burden of systolic hypertension in underserved populations and thus health disparities.
Stabilized voltage source inverter for sensitive loads in nuclear installations
Authors: Mousa Marwa M. , Hussein Khalid F. A. , Matter Z. , Eleissawi Hussein 
Published: July 2024

AbstractThe present paper proposes a novel design of a stabilized single-phase voltage-source inverter with pure sinusoidal output voltage for photovoltaic systems employed for feeding sensitive loads in nuclear installations. Such types of loads require a voltage source with quite stabilized magnitude and frequency and pure sinusoidal shape that is free from higher-order harmonics. The inverter is based on an H-bridge four insulated gate bipolar transistors (IGBTs) with gate drivers and optocoupler isolators. A control system based on a fast DSP unit and a microcontroller is designed for cancelation of the higher-order harmonics to produce a pure sinusoidal output with almost zero total harmonic distortion (THD). The sinusoidal purity, frequency and magnitude stabilization are achieved through pulse width modulation (PWM) controlled by a fast-response feedback system that measures the time wave form of the output voltage applied to the load and then calculates the THD, frequency and amplitude. The sinusoidal shaping is performed with aid of a sinusoidal shaping filter (SSF) to fasten the operation of higher-order harmonic cancellation. The frequency measurement is achieved through a frequency counter whereas the amplitude measurement is carried out through a differential amplifier that amplifies the difference between the output voltage of the inverter (while being applied to the load) and reference voltage that determines the desired amplitude. A prototype of the entire system of the proposed voltage-source inverter is fabricated for experimental evaluation of its performance. It is shown through simulation and experimental work that the proposed control system of the inverter output voltage is able to stabilize both the amplitude and frequency of the voltage applied to the load irrespective of the load impedance. Also, it is shown that the THD of the output voltage is $$-57 \text{ dB}$$

-
57

dB

($$0.00025 \%$$

0.00025
%

), which is almost zero. Moreover, the switching losses are considerably reduced and can be negligible owing to the use of the appropriate IGBTs. The efficiency of the proposed inverter is obtained by simulation taking into account all types of losses. Also, the dependence of the inverter efficiency on the load current is investigated. The average efficiency of the proposed voltage-source inverter is shown to be higher than $$97\%$$

97
%

.
Venom gland organogenesis in the common house spider
Authors: Hassan Afrah , Blakeley Grace , McGregor Alistair P. , Zancolli Giulia 
Published: July 2024

AbstractVenom is a remarkable innovation found across the animal kingdom, yet the evolutionary origins of venom systems in various groups, including spiders, remain enigmatic. Here, we investigated the organogenesis of the venom apparatus in the common house spider,Parasteatoda tepidariorum. The venom apparatus consists of a pair of secretory glands, each connected to an opening at the fang tip by a duct that runs through the chelicerae. We performed bulk RNA-seq to identify venom gland-specific markers and assayed their expression using RNA in situ hybridisation experiments on whole-mount time-series. These revealed that the gland primordium emerges during embryonic stage 13 at the chelicera tip, progresses proximally by the end of embryonic development and extends into the prosoma post-eclosion. The initiation of expression of an important toxin component in late postembryos marks the activation of venom-secreting cells. Our selected markers also exhibited distinct expression patterns in adult venom glands:sageand the toxin marker were expressed in the secretory epithelium,forkheadandsum-1in the surrounding muscle layer, whileDistal-lesswas predominantly expressed at the gland extremities. Our study provides the first comprehensive analysis of venom gland morphogenesis in spiders, offering key insights into their evolution and development.
Explicit and implicit sense of agency in depersonalisation experiences
Authors: Ciaunica Anna , Ayache Julia , Haggard Patrick , Nakul Estelle , Bonnet Emmanuelle , Auvray Malika 
Published: July 2024

AbstractThe sense of agency, the feeling of controlling one’s bodily actions and the world is altered in Depersonalisation (DP), a condition that makes people feel detached from one’s self and body. To investigate the link between depersonalisation and both implicit and explicit sense of agency, an online study was conducted using the influential Intentional Binding paradigm in a sample of non-clinical DP participants. The results did not reveal significant differences between individuals with low and high occurrences of DP experiences on the implicit and explicit sense of agency. However, participants with high occurrences of DP experiences showed a more time-sensitive explicit sense of agency and greater temporal distortions for short intervals in the absence of self-initiated motion. These results suggest that there is a discrepancy between implicit and explicit sense of agency in people with high levels of depersonalisation. Altogether, these findings call for further investigations of the key role of time perception on altered sense of self and agency in both non-clinical and clinical populations, to disentangle the mechanisms associated with the explicit and implicit sense of agency.
Universal terminal for cloud quantum computing
Authors: Khazali Mohammadsadegh 
Published: July 2024

AbstractTo bring the quantum computing capacities to the personal edge devices, the optimum approach is to have simple non-error-corrected personal devices that offload the computational tasks to scalable quantum computers via edge servers with cryogenic components and fault-tolerant schemes. Hence the network elements deploy different encoding protocols. This article proposes quantum terminals that are compatible with different encoding protocols; paving the way for realizing mobile edge-quantum computing. By accommodating the atomic lattice processor inside a cavity, the entangling mechanism is provided by the Rydberg cavity-QED technology. The auxiliary atom, responsible for photon emission, senses the logical qubit state via the long-range Rydberg interaction. In other words, the state of logical qubit determines the interaction-induced level-shift at the central atom and hence derives the system over distinguished eigenstates, featuring photon emission at the early or late times controlled by quantum interference. Applying an entanglement-swapping gate on two emitted photons would make the far-separated logical qubits entangled regardless of their encoding protocols. The proposed scheme provides a universal photonic interface for clustering the processors and connecting them with the quantum memories and quantum cloud compatible with different encoding formats.
Longitudinal association between maternal cardiovascular health in pregnancy and child birth outcomes
Authors: Jing Guangzhuang , Wei Qian , Zou Jiaojiao , Zhang Yunhui , Shi Huijing , Gao Xiang 
Published: July 2024

AbstractThe American Heart Association has updated its definition of cardiovascular health (CVH) with a new framework known as Life's Essential 8 (LE8). Although gestational CVH assessment has been recommended, its significance based on LE8 for birth outcomes is unknown. We thus evaluated the status of gestational CVH based on LE8 in 3036 pregnant women of the Shanghai Maternal-Child Pairs Cohort and the population of China Maternal Nutrition and Health Sciences Survey, and also examined the association between gestational CVH and child birth outcomes. We found that only a small proportion (12.84%) had high CVH, while 1.98% had low CVH in this cohort study. In adjusted models, a 10-point increase in the gestational CVH score, indicating a more favorable score, was associated with lower neonatal size such as birth weight (β: − 37.05 [95% confidence interval: − 52.93, − 21.16]), birth length (− 0.12[− 0.22, − 0.01]), weight-for-height z-score (− 0.07[− 0.12, − 0.03]), body mass index z-score (− 0.09 [− 0.13, − 0.04]), length-for-age Z-score (− 0.03 [− 0.06, − 0.01]), and weight-for-age z-score (− 0.08 [− 0.12, − 0.05]). Also, a 10-point increase in the gestational CVH score was associated with the lower risk of large for gestational age (LGA) (0.82 [0.73, 0.92]) and macrosomia infant (0.75 [0.64, 0.88]). CVH categories showed similar results. That is, better maternal CVH status in pregnancy was associated with lower neonatal size and lower risks for LGA and macrosomia in newborns.