bluuebunny/crossref_metadata_2025_split huggingface dataset:
The emerging threat of artificial intelligence on competition in liberalized electricity markets: A deep Q-network approach
Authors: Aliabadi Danial Esmaeili , Chan Katrina 
Published: October 2021

Abstract
BackgroundAccording to sustainable development goals (SDGs), societies should have access to affordable, reliable, and sustainable energy. Deregulated electricity markets have been established to provide affordable electricity for end-users through advertising competition. Although these liberalized markets are expected to serve this purpose, they are far from perfect and are prone to threats, such as collusion. Tacit collusion is a condition, in which power generating companies (GenCos) disrupt the competition by exploiting their market power. MethodsIn this manuscript, a novel deep Q-network (DQN) model is developed, which GenCos can use to determine the bidding strategies to maximize average long-term payoffs using available information. In the presence of collusive equilibria, the results are compared with a conventional Q-learning model that solely relies on past outcomes. With that, this manuscript aims to investigate the impact of emerging DQN models on the establishment of collusive equilibrium in markets with repetitive interactions among players. Results and ConclusionsThe outcomes show that GenCos may be able to collude unintentionally while trying to ameliorate long-term profits. Collusive strategies can lead to exorbitant electric bills for end-users, which is one of the influential factors in energy poverty. Thus, policymakers and market designers should be vigilant regarding the combined effect of information disclosure and autonomous pricing, as new models exploit information more effectively.
Comparison of Short-Term Toxicity of 14 Common Phycotoxins (Alone and in Combination) To The Survival of Brine Shrimp Artemia Salina
Authors: Zhang Yu Ting , SONG Shanshan , ZHANG Bin , ZHANG Yang , TIAN Miao , CHEN Huorong , DING Guangmao , LIU Renyan , Mu Jingli 
Published: October 2021

Abstract
Toxic harmful algal blooms (HABs) can cause deleterious effects in marine organisms, threatening the stability of marine ecosystems. It is well known that different strains, natural populations and growth conditions of the same toxic algal species may lead to different amount of phycotoxin production and the ensuing toxicity. To fully assess the ecological risk of toxic HABs, it is of great importance to investigate the toxic effects of phycotoxins in marine organisms. In this study, the short-term toxicity of 14 common phycotoxins (alone and in combination) in the marine zooplankton Artemia salina was investigated. On the basis of 48 h LC50, the order of toxicity in A. salina was AZA3 (with a LC50 of 0.0203 µg/ml)＞AZA2 (0.0273 µg/ml) ＞PTX2 (0.0396 µg/ml)＞DTX1 (0.0819 µg/ml)＞AZA1 (0.106 µg/ml)＞ SPX1 (0.144 µg/ml)＞YTX (0.172 µg/ml)＞dcSTX (0.668 µg/ml)＞OA (0.728 µg/ml)＞STX (1.042 µg/ml)＞GYM (1.069 µg/ml)＞PbTx3 (1.239 µg/ml)＞hYTX (1.799 µg/ml)＞PbTx2 (2.415 µg/ml). For the binary exposure, additive effects of OA and DTX1, DTX1 and hYTX; antagonistic effects of OA and PTX2, OA and STX; and synergetic effects of DTX1 and STX, DTX1 and YTX, DTX1 and PTX2, PTX2 and hYTX on the mortality of A. salina were observed. These results provide valuable toxicological data for assessing the impact of phycotoxins on marine planktonic species and highlight the potential ecological risk of toxic HABs in marine ecosystems.
Prediction of COVID-19 Diagnosis Based on OpenEHR Artefacts
Authors: Oliveira Daniela , Ferreira Diana , Abreu Nuno , Leuschner Pedro , Abelha António , Machado José 
Published: October 2021

Abstract
The complexity and momentum of monitoring COVID-19 patients calls for the usage of agile and scalable data structure methodologies. A system for tracking symptoms and health conditions of suspected or confirmed SARS-CoV-2 infected patients was developed based on the openEHR architecture. All data on the evolutionary status of patients in home care as well as the results of their COVID-19 test were used to train different machine learning algorithms, with the aim of developing a predictive model capable of identifying COVID-19 infections according to the severity of symptoms identified by patients. The results obtained were promising, with the best model achieving an accuracy of 96.25%, a precision of 99.91%, a sensitivity of 92.58%, and a specificity of 99.92%, using the Decision Tree algorithm and the Split Validation method.
Morphological and Molecular Identification of Oyster Mushroom [Pleurotus Ostreatus (Jacq.) P. Kumm]
Authors: Kotadiya Urvashi , Talaviya Jayadipkmuar , Shah Kalpit , Lathiya Sandip 
Published: October 2021

Abstract
Oyster mushroom (Pleurotus ostreatus) is fleshy, edible fungi and used throughout the world. Among the most well-known species of mushrooms, Pleurotus sp. is the third most popularly grown mushroom in the world and rank second in India. The most well-known species of Pleurotus are P. ostreatus, P. florida, P. eryngii, P. cystidiosis, P. flabellatus, P. cornucopie, and P. sajor-caju. According to the morphological, molecular character and ITS sequencing, the Pleurotus ostreatus was distinguish from the other species. The cap (pileus) of the oyster mushroom has whitish to grey color and fleshy. Stipe cream and smooth surface. Spores are whitish to lilac grey in mass, cylindrical to oblong shape. Spore print was white in color. Whitish mycelium growth in PDA plate. The ITS sequence was submitted to gene bank NCBI and it was accepted by NCBI with accession number MW446165.
Hidden Markov Modeling for Maximum Probability Neuron Reconstruction
Authors: Athey Thomas , Tward Daniel , Mueller Ulrich , Vogelstein Joshua , Miller Michael 
Published: October 2021

Abstract
Recent advances in brain clearing and imaging have made it possible to image entire mammalian brains at sub-micron resolution. These images offer the potential to assemble brain-wide atlases of neuron morphology, but manual neuron reconstruction remains a bottleneck. Several automatic reconstruction algorithms exist, but most focus on single neuron images. In this paper, we present a probabilistic reconstruction method, ViterBrain, which combines a hidden Markov state process that encodes neuron geometry with a random field appearance model of neuron flourescence. Our method utilizes dynamic programming to compute the global maximizers of what we call the ``most probable'' neuron path. Our most probable estimation method models the task of reconstructing neuronal processes in the presence of other neurons, and thus is applicable in images with several neurons. Our method operates on image segmentations in order to leverage cutting edge computer vision technology. We applied our algorithm to imperfect image segmentations where false negatives severed neuronal processes, and showed that it can follow axons in the presence of noise or nearby neurons. Additionally, it creates a framework where users can intervene to, for example, fit start and endpoints. The code used in this work is available in our open-source Python package brainlit.
Association of the Healthy Beverage Index With Metabolic Syndrome and Stroke in U.S. Adults: The National Health and Nutrition Examination Survey 2013-2014
Authors: Liu Jinxiao , Zhu Qiushuang , Dong Yuanjie , Yan Qingna , Li Yuqiao , Tang Xuanfeng , Wang Ruohua , Li Xiaoqing , Lv Xinyi , Niu Yucun 
Published: October 2021

Abstract
Background: Whether beverage consumption pattern is associated with risk of metanolic syndrome (MetS) and stroke is of public health interest. Methods: We examined the associations between the healthy beverage index (HBI) scores with prevalence of MetS and stroke among 4162 participants aged 20-80 years from the National Health and Nutrition Examination Survey (2013-2014) in U.S. Binary logistic regression was used to estimate odd ratios (OR) and 95% confidence intervals (95% CI), while adjusting for potential confounders and stratifying by gender. Results: For the prevalence of stroke, there was an inverse association between HBI scores and stroke (adj. OR for Q4 versus Q1: 0.47; 95% CI: 0.27–0.81), and gender stratified models were similar. However, there was a positive association between HBI scores and MetS (adj. OR for Q4 versus Q1: 1.38; 95% CI: 1.46–1.79) in the total participants, and gender stratified models were different. Higher HBI scores was associated with lower prevalence of MetS in females (adj. OR for Q4 versus Q1: 0.95; 95% CI: 0.65–1.38), but with higher prevalence of MetS in males (adj. OR for Q4 versus Q1: 2.02; 95% CI: 1.37–2.99). Further analyses demonstrated differences in the association of SSBs, coffee and tea, alcohol, diet drinks and full-fat milk consumption with MetS and stroke in the total subjects, males and females. Conclusions: Our findings suggested that the HBI scores was a negative association with stroke in a representative U.S. population, and the higher HBI scores was associated with increased prevalence of MetS in males but decreased in females, which may be caused by the same beverage may play a different role in the prevalence of MetS and stroke in the total participants,males and females.
TNF-α plays a role in sleep disturbance in patients with rotator cuff tear
Authors: Cho Chul-Hyun , Kim Du Hwan , Baek Eun Hee , Kim Du-Han 
Published: October 2021

Abstract
Background

The purpose of this study was to determine serum levels of sleep-related cytokines in patients with rotator cuff tear (RCT) and to investigate the correlations between serum levels of sleep-related cytokines and clinical scores.
Methods

Peripheral blood samples were collected from 63 study participants were divided into three groups: RCT patients with sleep disturbance (sleep disturbance group; SD group) (n = 21), RCT patients without sleep disturbance (normal sleep group; NS group) (n = 21), and patients with shoulder instability (control group) (n = 21). Serum concentration levels of sleep-related cytokines including interleukin-1α (IL-1α), IL-1β, IL-2, IL-6, IL-8, IL-10, and tumor necrosis factor-α (TNF-α) were measured via enzyme-linked immunosorbent assay. The associations between serum levels of sleep-related cytokines and clinical scores including the Visual Analogue Scale (VAS) pain score, the University of California at Los Angeles (UCLA) score, and the Pittsburgh Sleep Quality Index (PSQI) were analyzed.
Results

Serum concentration levels of TNF-α were significantly higher in the SD group compared with those of the NS and control groups (P = < 0.001 and 0.05). Serum levels of IL-8 and IL-10 were significantly higher in the SD group compared with those of control group (P = 0.01 and = 0.05), but did not differ significantly from that of the NS group (P > 0.05). Serum level of IL-6 was significantly lower in the SD group compared with those of the NS and control groups (P = < 0.001 and 0.01). There were no associations between serum levels of sleep-related cytokines and all clinical scores including VAS pain, UCLA, and PSQI scores (all P > 0.05).
Conclusion

The current findings suggest that TNF-α may play a significant role in the pathophysiology of sleep disturbance in patients with RCT and be a possible therapeutic target to improve sleep disturbance in patients with RCT.
Interactive Effects of Intraspecific Competition and Drought on Stomatal Conductance and Hormone Concentrations in Different Tomato Genotypes
Authors: Gao Yang , Liang Yueping , Li Shuang , Si Zhuanyun , Hamani Abdoul.Kader.Mounkaila 
Published: October 2021

Abstract
We elucidated the effects of intraspecific competition on plant growth, stomatal opening and hormone concentrations in different tomato genotypes under different water regimes. Intraspecific competition reduced plant leaf area and stomatal conductance (gs) of wild-type tomato (Ailsa Craig), which was accompanied by abscisic acid (ABA) accumulation and ethylene evolution. Intraspecific competition-induced decrease in gs was absent in flacca, an ABA-deficient mutant, and in never-ripe, a partially ethylene-insensitive genotype, indicating ABA and ethylene involved in plant response to intraspecific competition. As soil water becomes dry, the competition decreased gs by elevating ABA and ethylene accumulations. Under severe drought, the competition-induced decline in gs was covered by the severe drought-induced decrease in gs, as hydraulic signals most probably dominate. Absence of canopy competition had no significant influence on plant stomatal opening of well-watered tomato, due to canopy separation minimized the plant neighbor sensing by ethylene and other signals. Whereas under water deficit condition, absence of canopy competition significantly reduced ABA accumulation in roots and then stomatal conductance, indicating the belowground neighbour detection signals maybe enhanced by soil drought. Absence of root competition increased ethylene evolution, confirming the importance of ethylene in neighbor detection and plant response to environmental stress.
A Case Report of HIV-Related Bilateral Inflammatory Myofibroblastic Tumors of Adrenal Gland
Authors: Zhang Mengmeng , Liu Hui , Zhu Zhiqiang , Zhang Yu , Zhang Yanyan 
Published: October 2021

Abstract
Inflammatory myofibroblastic tumor (IMT) is a rare disease which mostly occurs at younger age and locates in lung in general population. We report a rare case of 44-year-old man diagnosed adrenal IMT with HIV infection, who refused regular highly active antiretroviral therapy (HAART) 13 years ago until in hospital because of findings of adrenal masses. The patient underwent CT-guided needle biopsy successfully, and the pathological analysis documented the diagnosis of IMT by the feature of proliferation of fibroblastic-myofibroblastic with inflammatory infiltration. We failed to perform tumor complete resection due to diffuse invasion of tumor under laparoscope. The patient was complicated with severely multiple pulmonary infection post to surgery because of immunodeficiency, that eventually caused the death of patient 2 months later. This case reminds us that IMTs may be too aggressive and progressed in HIV-positive patients with irregular HAART to perform surgical resections, and severe immunodeficiency can be more fatal. To our knowledge, this case is the second IMT patient with HIV infection worldwide, but the first case occurs at adrenal gland rather than lung in adult.
Origin and Evolution Analysis and Genetic Characteristics of Echovirus 9 in China
Authors: SI Fenfen , JI Tianjiao , WANG Dongyan , ZHANG Yong , ZHU Shuangli , LI Junhan , XU Wenbo , YAN Dongmei 
Published: October 2021

Abstract
BackgroundEchovirus 9 (E9) is associated with a wide variety of diseases and medical conditions, and the clinical symptoms of sporadic cases caused by E9 often are severe. With a high global prevalence, E9 has caused multiple outbreaks worldwide. However, little is known about the genetic and geographic population dynamics of E9.MethodA total of 131 VP1 gene sequences, including15 generated in this study and 116 obtained from GenBank, were used to coestimate time-resolved phylogenies to infer viral evolution and transmission in worldwide. Overlapping fragments representing whole genomes were amplified by reverse transcription polymerase chain reaction (RT-PCR) using specific primers. Then, we reported the genetic characteristics of fifteen E9 strains in the Chinese Mainland. Similarity plots and bootscanning analysis were used to determine recombination patterns of E9.ResultsThe estimated mean evolutionary rate of global E9 VP1 gene was 4.278 × 10−3 substitutions per site per year (95% confidence interval [CI], 3.822× 10−3/site/year to 4.710× 10−3/site/year), and the common ancestor of E9 likely emerged around 1868 (95% CI, 1840 to 1892). The full-length genomic sequences of the fifteen E9 strains showed 76.9-79.6% nucleotide identity and 95.3–95.9% amino acid identity with E9 Barty strain. 11 of 15 E9 whole genome sequence present four recombination patterns, and E9 recombinants have extensive genetic exchanges in the 2C and P3 regions with other Enterovirus B (EV-B) circulated in China. Four of six E9 strains were temperature sensitive, and two were temperature resistant, and a comparative genomics analysis suggested that 411, 865 and 867 amino acid substitution in the P1 region was related to temperature sensitivity.ConclusionThis study highlights a persistent transmission network of E9 in worldwide, provides valuable information regarding the molecular epidemiology of E9.
Serum Urea Acid and Urea Nitrogen Levels are Risk Factors for Maternal and Fetal Outcomes of Pregnancy: A Retrospective Cohort Study
Authors: Wu Lanlan , Liu Yao , Liu Zengyou , Chen Hengying , Shen Siwen , Wei Yuanhuan , Sun Ruifang , Deng Guifang 
Published: October 2021

Abstract
Background

In recent years, results on the association between serum uric acid (UA) and pregnancy outcomes have been inconsistent, and the association between urea nitrogen (UN) and adverse pregnancy outcomes in normal pregnant women has not been reported. Thus, we examined the association of UA and UN levels during gestation with the risk of adverse pregnancy outcomes in a relatively large population.
Methods

A total of 1602 singleton mothers were included. Both UA and UN levels were collected and measured during the second (16–18th week) and third (28–30th week) trimesters of gestation respectively. Statistical analysis was performed using multivariate logistic regression.
Results

After adjustment, the highest quartile of UA in the third trimester increased the risk of premature rupture of membranes (PROM) and small for gestational age infants (SGA) by 48% (odds ratio [OR]: 1.48, 95% confidence interval [CI]: 1.04–2.10) and 99% (95% CI: 1.01–3.89) compared to those in the lowest quartile. The adjusted OR (95% CI) in the highest quartile of UN for the risk of SGA was 2.18 (95% CI: 1.16–4.13) and 2.29 (95% CI: 1.20–4.36) in the second and third trimester, respectively. In the second trimester, when UA and UN levels were both in the highest quartile, the adjusted OR (95% CI) for the risk of SGA was 2.51 (95% CI: 1.23–5.10). In the third trimester, when the group 1 (both indicators are in the first quartile) was compared, the adjusted ORs (95% CI) for the risk of SGA were 1.98 (95% CI: 1.22–3.23) and 2.31 (95% CI: 1.16–4.61) for group 2 (UA or UN is in the second or third quartile) and group 3 (both indicators are in the fourth quartile), respectively.
Conclusions

Higher UA and UN levels increased the risk of maternal and fetal outcomes. The simultaneous elevation of UA and UN levels was a high-risk factors for the development of SGA, regardless of whether they were in the second or third trimester.
Effects of waste milk on growth performance, immunity, and gut health of dairy calves
Authors: Zhang Xinyue , Ma Tao , Cheng Chuanteng , Lv Jingyi , Bai Haixin , Jiang Xin , Zhang Yonggen , Xin Hangshu 
Published: October 2021

Abstract
Background
Liquid feed are the major nutrient source that can have a significant impact on the growth and development of immune system of calves before weaning. Waste milk containing antibiotic residue has been produced because of the continuous expansion of dairy farms. In order to reduce economic loss and prevent environmental pollution, most farms seem waste milk as one of the calves’ liquid feeds. However, there is limited information to report the effects of waste milk on growth performance, especially immunity function of calves. Thus, the objective of this study was to investigate the effects of waste milk on growth, immunity and gut health of dairy calves.
Results
Feeding WM improved hip width, hip height, heart girth, final body weight, and feed efficiency of dairy calves compared to MR. Plasma concentrations of IgA, IgM, IgG and IL-10 were higher and TNF-α was lower in WM group. In addition, treatment and time interactively affected plasma concentrations of IgG and IL-2, which increased and decreased in WM group but decreased and increased in MR group, respectively, from 49 to 70 d of age. There was no difference in diarrhea case and average days of diarrhea among treatments. Difference in fecal microbiota was observed between MR and WM groups only at 49 d of age. Analysis of differential abundance showed that the increase in the relative abundance of Prevotellaceae NK3B31 group and the decrease in that of Bacteroides was higher in WM than MM group from 49 to 70 d of age.
Conclusions
WM had beneficial effects on growth performance and did not affect health statue, which might be explained by enhanced immune function modulated by fecal microbiota.
Clinical Data Classification With Noisy Intermediate Scale Quantum Computers
Authors: Moradi Sasan , Brandner Christoph , Spielvogel Clemens , Krajnc Denis , Hillmich Stefan , Wille Robert , Drexler Wolfgang , Papp Laszlo 
Published: October 2021

Abstract
Quantum machine learning has experienced a significant progress in both software and hardware development in the recent years and has emerged as an applicable area of near-term quantum computers. In this work, we investigate the feasibility of utilizing quantum machine learning (QML) on real clinical datasets. We propose two QML algorithms for data classification on IBM quantum hardware: a quantum distance classifier (qDS) and a simplified quantum-kernel support vector machine (sqKSVM). We utilize these different methods using the linear time quantum data encoding technique (\({\text{log}}_{2}N\)) for embedding classical data into quantum states and estimating the inner product on 15-qubit IBMQ Melbourne quantum computer. We match the predictive performance of our QML approaches with prior QML methods and with their classical counterpart algorithms for three open-access clinical datasets. Our results imply that the qDS in small sample and feature count datasets outperforms kernel-based methods. In contrast, quantum kernel approaches outperform qDS in high sample and feature count datasets. We demonstrate that the \({\text{log}}_{2}N\) encoding increases predictive performance with up to +2% area under the receiver operator characteristics curve across all quantum machine learning approaches, thus, making it ideal for machine learning tasks executed in Noisy Intermediate Scale Quantum computers.
Initial Medication Adherence by Psychiatric Outpatients in a General Hospital and Relevant Factors
Authors: Chen Minhua , Zhou Lina , Ye Li , Lin Gelin , Pang Yongli , Lu Liyun , Wang Xianglan 
Published: October 2021

Abstract
Background: The International Society for Pharmacoeconomics and Outcomes Research proposed two types of medication adherence: initial and long-term. Initial adherence is a predictor of long-term adherence and thus is a crucial metric to explore and support. This study aimed to investigate initial medication adherence by psychiatric outpatients and relevant factors. Methods: The study surveyed psychiatric outpatients using a 30-day timely return visit rate (TRVR) after the first visit to indicate initial adherence. All participants agreed to engage in the self-designed survey and assessments of the Eysenck Personality Questionnaire (EPQ) and Symptoms Checklist-90 (SCL-90). Clients who missed timely return visits received telephone follow-up to determine the main reasons. Results: The overall TRVR was 59.4%, and 40.6% of clients missed return visits. Logistic regression analysis revealed risk factors for initial adherence were work, tense family atmosphere, negative attitudes towards medication, higher EPQ psychoticism score, and lower SCL-90 phobic anxiety score. The main reasons given for non-timely return visits were improvement suggesting lack of need for a return visit, various limitations, no improvement, and side effects. Conclusion: Psychiatric outpatients had poor initial medication adherence related to multiple dimensional factors, including job, family, personality characteristics, mental status, and thoughts about mental illness and treatments.