bluuebunny/crossref_metadata_2025 huggingface dataset:
Earth’s core composition constrained by H partitioning at the inner core boundary
Authors: Jing Zhicheng , Liu Tao
Published: February 2024

Recent studies suggest that H is an important light element in the Earth’s core for its high cosmochemical abundance and strong affinity to Fe under core-formation conditions. Thus, constraining the light element contents in the core requires knowledge on the distribution of H between the liquid outer core and solid inner core. Here we investigate the chemical equilibrium of H at the inner-core boundary (ICB) by calculating the chemical potential of H in solid and liquid Fe-H alloys, respectively, using first-principles molecular dynamic simulations in conjunction with the particle insertion and neural network methods. We find that H partitions preferentially into the outer core and provides a major contribution to the density jump across the ICB boundary. Combining geophysical constraints, mineral physics data, and chemical equilibrium at the ICB, we evaluated light element abundances in the outer and inner cores simultaneously. Our results suggest H and Si are the preferred light elements in the core, implying a relatively reduced environment during the Earth’s accretion and core-formation processes.
Comparison of methods of positioning ROI and whole-tumor histogram analysis of ADC maps for differentiating hyperperfused primary central nervous system lymphoma from atypical glioblastoma
Authors: Yu Lan , Yang Feiman , Wang Feng , Kang Jie , Zhou Xiaofang , Song Yang , Cao Dairong , Xing Zhen
Published: February 2024

Purpose: Apparent diffusion coefficient (ADC) is important parameter to identify glioblastoma (GBM) and primary central nervous system lymphoma (PCNSL), but its discriminatory value is unclear in atypical GBM (aGBM) and hyperperfused PCNSL (hPCNSL). The aim of this study is to investigate the differential diagnostic value of different ADC measurements for aGBM and hPCNSL.
Materials and Methods: This retrospective study included 65 patients with aGBM (n = 33, solid enhancement with no visible necrosis) and hPCNSL (n = 32, PCNSL performed greater than or equal 25% relative cerebral blood volume of aGBM as hPCNSL). All patients evaluated the ADC using three-ROIs, single-section, and whole-volume methods in the enhancing (n = 65) and perienhancing (n = 50) lesions. Moreover, ADC histogram parameters for the enhancing and perienhancing lesions were extracted from aGBM and hPCNSL. The student’s t-test or Mann-Whitney U test was utilized to compare values. Parameters with significant differences between the two groups were included for receiver operating characteristic analysis. The DeLong test was used to compare AUCs.
Results: For the enhancing lesions, ADCs of three methods and 10th percentile histogram parameter were significantly lower in patients with hPCNSL than in those with aGBM (p < 0.05, all). Compared to single-section, whole-volume methods and other histogram parameters, the three-ROIs method and 10th percentile histogram parameter had well diagnostic performance (AUC = 0.804 and 0.783, Delong test, p > 0.05) to accurately predict these two diseases in enhancing lesions. For the perienhancing lesions, all parameters were not significantly different between aGBM and hPCNSL (p > 0.05, all).
Conclusions: ADC is important for the identification of aGBM and hPCNSL. Among different measures, three-ROIs method and 10th percentile histogram parameter have the highest value in the differential diagnosis of these two specific types of tumors.
Target Detection Algorithm Based on Efficient Self-Attention-Convolution Enhanced Transformer
Authors: An Fengping , Wang Jianrong , Liu Ruijun
Published: February 2024

Since the target detection algorithm based on convolutional neural network suffers from limited convolutional kernel receptive field, it leads to the model's inability to perceive the remote semantic information in the image. Because the Transformer model does not have the limitation of local receptive fields, it is introduced into the field of target detection, and many scholars have proposed target detection algorithms based on Transformer and its variants. However, the Transformer model has the difficulties of not being able to extract the deep feature information and the high computational complexity of the standard self-attention mechanism in the process of target detection and recognition applications. Aiming at the above two core problems, we have carried out in-depth analysis and research, and proposed an encoder-decoder model consisting of a convolutional layer and a Transformer module. And then, we constructed the efficient multi-head self-attention mechanism, which can capture both local and remote contextual information of target image features. Then, we design efficient convolutional module-enhanced cross-window connectivity, which can significantly improve the characterization and global modeling capabilities of Transformer model. In addition, we propose the convolution-enhanced Transformer learning framework, which improves the adaptability to different datasets, which also integrates the sparse sampling strategy. It can significantly reduce the memory and computational requirements in large-scale image processing. Finally, we propose a target detection algorithm based on a new Transformer framework. We conducted ablation experiments and computational performance comparison experiments on several HRRS scenes and natural scene datasets. The experimental results confirm that our proposed method obtains optimal results in terms of weighted F-measure, average F-measure and MAE. Moreover, our proposed method has clearer edge information and more accurate target localization information in the visual effect of detection results.
ICP variability associates with 3-month outcomes in spontaneous intracerebral hemorrhage: a retrospective analysis of 597 patients
Authors: Yang Lei , Wang Mei-Hua , Song Jie , Bao Yi-Feng , Yuan Qiang , Wang Yue , Hu Jin , Yu Jian , Wu Gang , Zhao Jian-Lan
Published: February 2024

Background
Invasive intracranial pressure (ICP) monitoring is frequently employed in spontaneous intracerebral hemorrhage (ICH) treatment, but its benefit to ICH patients’ outcomes is debated. ICP variability (IPV) has been linked to poor outcomes in patients with subarachnoid hemorrhage (SAH) and traumatic brain injury (TBI), but this association with outcomes in ICH has yet to be definitively established. We hypothesized that IPV within the initial 72 hours following ICP probe insertion is predictive of outcomes in ICH patient.
Methods
A retrospective chart review analysis of adult ICH patients, who received ICP monitoring at Huashan Hospital Fudan University between Jan. 2016 and Jan. 2023, was performed. We included ICH patients within 6 hours of signs or symptoms onset. Outcomes of ICH patients were assessed using 3-month mRS, and were dichotomized into poor (mRS 4 to 6) and good (mRS 0 to 3) outcome group. ICPs were recorded from the implantation of invasive ICP probe until it was removed. ICP was analyzed in the acute period, from 0 to 72 hours after ICP implantation. IPV was analyzed by SD (Standard deviation), CV (Coefficient of variation) and SV (Successive variation) of ICP.
Results
We analyzed 597 patients’ charts. The 1st ICP assessment, immediately after ICP implantation, at median 117 minutes (interquartile range, 82–231 minutes) after admission was mean 20.5 ± 7.8 mmHg. The 2nd ICP assessment, on NICU arrival after operation, was mean 14.6 ± 8.3 mmHg. Poor outcomes occurred in 213 patients (35.68%). In univariate analysis, univariate quintile analysis or multivariate analysis, SBPSD, SBPCV and SBPSV were associated with poor outcomes.
Conclusions
IPV within the first 72 hours post-ICP probe implantation in ICH patients independently correlates with poor 3-month functional outcome. Stabilization of IPV with initial 72 hours following ICP probe insertion maybe a potential therapeutic target to improve functional outcomes of these patients.
Comparison of medial cuboid/cuneiform osteotomy technique with medial cuneiform/metatarsal osteotomy in correction of residual metatarsus adductus deformity
Authors: Gholipour Morteza , Bonakdar Sona , Gorji Mona Gorji , Minaei Reza
Published: February 2024

Background: Treatment of metatarsus adductus (MA) is surgical in cases of nonresponse to non-operative treatment. Several surgical procedures have been described to correct MA, including soft tissue release or bone osteotomy. So far in the previous literature, the preference of any other osteotomy has not been done Therefore, our aim in this study was to evaluate the extent of foot fore deformity by osteotomy based on radiographic criteria.
Patients and Methods: This was a retrospective study from July 2019 to July 2020, which included 22 patients (30 feet), ranging in age from 5 to 14 years, who were admitted with a diagnosis of MT and underwent corrective osteotomy. Radiographs of deformity corrections in the AP view (tarso-first metatarsal angle –calcane-second metatarsal angle -cuboid length and the laterah view ,medial cunieform length an, length of cuboid and medial length of cunieform were examined.
Results: Thirty patients (40 feet) were diagnosed with MA deformity. A total of 22 patients (30 feet) underwent corrective osteotomy. The mean age of patients in the first group was 8.87±3.56 years (means: 3-14 years) and the second group was 8±2.46 years (means: 13-13 years). In terms of sex distribution, eight patients were female and 14 patients were male. surgery has improved the angles and length of the medial and lateral columns in control radiographs after surgery and three months later,in both group and the adductus deformity has been significantly corrected (p<0.05). However, both types of osteotomies had acceptable deformity improvement results within 3 months in terms of radiographic criteria, but there is no statistically significant difference (P >0.05) between preoperative and postoperative and three months of follow-up in radiographic parameters of the two groups and only this amount was significant in medial cunieform length correction in lateral radiograph and statistically Was significant. (P<0.05). There is no statistical difference in terms of changes in values in terms of angle and length in the two osteotomy methods (P>0.05).
Conclusion: Due to complete deformity corrections and high patient satisfaction in both groups, none of the conventional osteotomy methods (cuboid-medial cunieform and medial cunieform-metatarsal 2-5) was superior to the other and both methods were safe. It is effective for cases of idiopathic idiopathic MA and clubfoot cases.
Level of evidence: IV
Development and validation of a clinical prediction model for concurrent pulmonary infection in convalescent patients with intracerebral hemorrhage
Authors: Xu Jixiang , Li Yan , Li Shaomin , Han Xiaoxiao , QI Ynliang , Zhou Xiaomei
Published: February 2024

Objectives: This study aims to develop and validate a clinical prediction model for assessing the risk of concurrent pulmonary infection（PI）in patients recovering from intracerebral hemorrhage（ICH）.
Methods: In this retrospective study, we compiled clinical data from 761 patients in the recovery phase of intracerebral hemorrhage, with 504 cases included in the PI group and 254 in the no PI group. Initially, univariate logistic regression was used to screen predictive factors. Subsequently, the Least Absolute Shrinkage and Selection Operator (LASSO) regression was employed to optimize these predictors. Variables identified from LASSO regression were included in a multivariable logistic regression analysis, incorporating variables with P < 0.05 into the final model. A nomogram was constructed, and its discriminative ability was evaluated using the Receiver Operating Characteristic (ROC) curve and Area Under the Curve (AUC). Model performance was assessed using calibration plots and the Hosmer-Lemeshow goodness-of-fit test (HL test). Additionally, the net clinical benefit was evaluated through clinical decision curve （DOC）analysis.
Results Key predictors of PI included age, antibiotic use, consciousness disturbances, tracheotomy, dysphagia, bed rest duration, nasal feeding, and procalcitonin levels. The model demonstrated strong discrimination (C-index: 0.901, 95%CI: 0.878~0.924) and fit (Hosmer-Lemeshow test P=0.982), with significant clinical utility as per DCA.
Conclusion This study constructed a nomogram prediction model based on the demographic and clinical characteristics of convalescent patients with intracerebral hemorrhage. Further studies showed that this model is of great value in the prediction of pulmonary infection in convalescent patients with intracerebral hemorrhage.
Electronic structure and superconductivity in bilayer La3Ni2O7
Authors: Jiang Kun , Wang Yuxin , Wang Ziqiang , Zhang Fu-Chun , Hu Jiangping
Published: February 2024

We show that the crystal field splitting, the bilayer coupling, and electron-electron correlations all play a crucial role in creating an electronic environment similar to hole-doped cuprates for high temperature superconductivity in bilayer La3Ni2O7 under high pressure. The previous density functional theory calculations highly underestimated the crystal field splitting and bilayer coupling. Employing the hybrid exchange-correlation functional,
we show that the exchange-correlation pushes the antibonding dz2 bands below the Fermi level to be fully occupied in both the low-pressure (LP) non-superconducting phase and the high-pressure (HP) phase exhibiting superconductivity.
In the LP phase, the calculated Fermi surfaces and the correlation normalized band structure match well with the experimental findings at ambient pressure.
Moreover, the electronic susceptibility calculated for this new band structure features nesting-induced peaks near the wave vector Q=(π/2, π/2), suggesting a possible density wave instability in agreement with recent experiments.
In the HP phase, an inversion symmetry between the bilayer emerges and produces a very different band structure and Fermi surface, which can be described by low-energy effective models for the inversion antisymmetric β and symmetric α bands.
The β band turns out to be close to half-filling while the α band is highly overdoped. Considering the strong local Coulomb repulsion, we find a dominant pairing with B1g symmetry in the β band that, upon Josephson coupling to the α band, drives a superconducting ground state with a congruent d-wave symmetry.
Our results capture the essential physics of La3Ni2O7 in both the LP and HP phases and reveal its similarity and difference from the hole-doped cuprate high-temperature superconductors.
Peculiarities of the nematic transition in FeSe0.675Te0.3S0.025 and its proximity to the quantum critical point
Authors: Ovchenkov Y.A. , Chareev D.A. , Gippius A.A. , Presnov D.E. , Puzanova I.G. , Tkachev A.V. , Volkova O.S. , Zhurenko S.V. , Vasiliev A.N.
Published: February 2024

In this work, we present the studies of structural phase transitions in FeSe0.675Te0.3S0.025 crystals. The data obtained indicate a significant change in the behavior of many characteristics during the transition in this composition compared to the case of the unsubstituted FeSe. The resistivity at low temperatures for the studied FeSe0.675Te0.3S0.025 is proportional to the square of the temperature, while for pure FeSe below the structural transition it depends almost linearly on temperature. 77Se NMR studies also confirm a change in the type of phase transition. The NMR data showed a noticeable line broadening below the structural transition and an anomaly in the temperature dependence of the relaxation rate, which was not observed in FeSe. Our results confirm the quantum criticality of Fe(Se,Te) at a low Te content or existence of the nematicity change point (NCP). This makes the phase diagram of quasi-binary Fe(Se,Te) compounds generally consistent with the phase diagram of FeSe under pressure. In both cases, there is a local minimum in the superconducting critical temperature near NCP and a strong increase in the superconducting critical temperature near the point of complete suppression of nematicity.
The drivers of minimum acceptable diet among children aged 6–23 months in Ethiopia: community-based cross-sectional study
Authors: Bikila Girma Cheru , Arero Godana , Kalu Sultan , Roba Kedir Teji , Charkos Tesfaye
Published: February 2024

Background: A minimum acceptable diet is a combination of the minimum dietary diversity and the minimum meal frequency for a child aged 6-23 months. Globally, only one in six children receives a minimum acceptable diet, and the proportion has been reduced to one in nine in Ethiopia.
Objective: To assess the prevalence of the minimum acceptable diet and associated factors among children aged 6- 23 months in Dera town, Oromia, Ethiopia.
Methods: A community-based cross-sectional study was conducted. Systematic random sampling techniques were used to select the study subjects. The data was coded, entered into Epi-Info version 7, and then exported to SPSS version 24 for analysis. The variance inflation factor and tolerance test are used to check multicollinearity. Descriptive statistics of frequency (%) were used. Hosmer and Lemeshow's goodness-of-fit test at a P-value > 0.05 is considered the model fit. Bivariate and multivariate logistic regression analyses were computed with a 95% confidence interval, and a P-value < 0.05 was, considered statistically significant.
Results: A total of 430 study subjects were included in this study. The prevalence of a minimum acceptable diet was 36.5% (95% CI: 32, 41%). In the adjusted model, mothers attaining a primary school (AOR = 2.7, 95%CI: 1.3, 4.8), college and above education (AOR = 4.3, 95%CI: 1.4, 13), child age between 12–17 months (AOR = 6.2, 95%CI: 2.80, 13.50) and 18–23 months (AOR = 4.61, 95%CI: 2.04, 10.40), ANC visit four or more (AOR = 2.0, 95%CI: 1.2, 3.4), and not feeding breast (AOR = 0.15, 95% CI: 0.07, 0.31) were significantly associated with meeting the minimum acceptable diet.
Conclusion: This study showed that the practice of a minimum acceptable diet was low, according to the World Food Program target. Mothers' educational status, antenatal care visits, age of the child, and breastfeeding were the predictors of the minimum acceptable diet.
Background of MIGS-adapted patients for cataract surgery in glaucoma
Authors: Hayakawa Yasunari , Inada Takayuki
Published: February 2024

Purpose To investigate whether it is better to perform minimally invasive glaucoma surgery (MIGS) when performing cataract surgery on glaucoma patients.
Methods The study enrolled subjects with mild-to-moderate glaucoma including primary open angle glaucoma (POAG), normal tension glaucoma (NTG) and combined mechanism glaucoma (CMG) with visually significant cataract who were treated with one or more ophthalmic antiglaucoma agents. Phacoemulsification and aspiration with intraocular lens insertion (PEA + IOL, phaco group) or MIGS with PEA + IOL (µLot-phaco group) was performed on patients with glaucoma. Age, sex, glaucoma type, pre- and post-operative IOP, and ratio of IOP reduction were estimated.
Results The rate of IOP reduction of µLot-phaco group was significantly higher than phaco group at 6 months after the surgery. Preoperative IOP, POAG, and age in µLot-phaco group were significantly correlated with IOP reduction at 6 months after the surgery.
Conclusion Simultaneous cataract and MIGS was found to be more effective in older POAG patients with higher preoperative IOP.
Factors Associated With Preoperative Quality of Life in Patients With Rotator Cuff Injury
Authors: Brune Daniela , Stojanov Thomas , Müller Andreas Marc , Weibel David , Hunziker Sabina , Erdbrink Stephanie , Audigé Laurent
Published: February 2024

BACKGROUND Assessing health-related quality of life (HRQoL) is a widely employed method in orthopedics to evaluate patient well-being and measure the effectiveness of surgical interventions. Understanding the relationship between specific baseline factors and preoperative HRQoL can help clinicians identify patients at risk for low quality of life and thus, develop preventive strategies that adequately address individual patient needs. The objective was to assess associations between baseline factors and preoperative HRQoL in patients undergoing arthroscopic rotator cuff repair (ARCR).METHODS This study is part of a multicenter prospective Swiss cohort study that included patients undergoing ARCR between June 2020 and November 2021. Data were derived from baseline and surgery forms. We examined possible associations between 5 sociodemographic, 7 patient- and 9 injury-related factors and preoperative HRQoL. HRQoL was assessed using the European Quality of Life 5-Dimension 5-Level (EQ-5D-5L) questionnaire to calculate EQ-5D index and EQ VAS scores. We followed the conceptual model of HRQoL for variable selection. Univariable and multivariable linear regression models examined associations between the 21 factors and preoperative HRQoL. Final models were determined using stepwise backward regression.RESULTS A total of 973 included patients (mean age [SD], 57.3 [9.4] years; 611 men [63%]) had a mean [SD] EQ-5D index and EQ VAS of 0.70 [0.23] and 68.7 [19.8], respectively. Being male (regression coefficient (β), 0.05; 95% CI [0.02–0.08]), having a higher age (β, 0.02; 95% CI [0.01–0.03]) and higher education levels (e.g., university, college: β, 0.11; 95% CI [0.06–0.16]) were associated with a higher EQ-5D index. Increased body mass index (β, -0.02; 95% CI [-0.04 to -0.01]) and worse sleep quality (β, -0.03; 95% CI [-0.04 to -0.03]) were associated with a lower EQ-5D index. Factors negatively associated with overall EQ VAS health were depression (e.g., moderate: β, -12.70; 95% CI [-16.18 to -9.21]), presence of at least one comorbidity (β, -3.71; 95% CI [-5.91 to -1.52]), and pain (β, -1.81; 95% CI [-2.36 to -1.26]).CONCLUSION Our results suggest that preoperative HRQoL is highly associated with sociodemographic and patient-related factors. Specifically addressing these factors may improve orthopedic care.
Multicenter study on clinical outcomes and risk factors in patients with Klebsiella pneumoniae bacteremia receiving cefoperazone/sulbactam treatment
Authors: Chiang Tsung-Ta , Chiang Ming-Hsien , Tang Hung-Jen , Shi Zhi-Yuan , Ho Mao-Wang , Chou Chia-Hui , Lin Shang-Yi , Lu Po-Liang , Wu Ting-Shu , Shie Shian-Sen , Liu Jien-Wei , Chang Feng-Yee , Chuang Yin-Ching , Wang Fu-Der , Yang Ya-Sung
Published: February 2024

Background
Infections caused by Klebsiella pneumoniae are common and result in high mortality rates. In vitro studies demonstrated the potency of cefoperazone/sulbactam (CPZ/SUL) against Klebsiella pneumoniae. However, the clinical efficacy of CPZ/SUL for the treatment of K. pneumoniae bacteremia has not been studied.
Objectives
This study aimed to correlate the clinical outcomes of patients with bacteremia with the minimal inhibitory concentrations (MICs) of CPZ/SUL against the causative K. pneumoniae isolates.
Methods
This multicenter, retrospective observational study was conducted in Taiwan between July 2017 and April 2021. Patients with K. pneumoniae bacteremia treated with CPZ/SUL were enrolled in this study. CPZ/SUL MICs were determined using the agar dilution method. Data on the patients’ clinical outcomes and characteristics were collected and analyzed.
Results
In total, 201 patients were enrolled. Among the causative K. pneumoniae isolates, 180 (89.5%) were susceptible to CPZ/SUL. Most patients (n = 156, 77.6%) had favorable outcomes. The 30-day mortality rate was 11.9% (n = 24). Multivariate risk analyses showed that higher APACHE II score (Odds Ratio (OR), 1.14; Confidence Interval (CI), 1.07–1.21; p < 0.001), metastatic tumors (OR, 5.76; CI, 2.31–14.40; p < 0.001), and causative K. pneumoniae CPZ/SUL MICs > 16 µg/ml (OR, 4.30; CI, 1.50–12.27; p = 0.006) were independently associated with unfavorable outcomes.
Conclusion
Patients with K. pneumoniae bacteremia treated with CPZ/SUL at a ratio 1:1 had favorable outcomes when the CPZ/SUL MICs were ≤ 16 µg/ml. Patients with higher APACHE II scores and metastatic tumors had unfavorable outcomes.
Estimation the Health Literacy Score of Syrian Immigrants Using Support Vector Regression, Decision Tree, Extreme Learning Machine, and Deep Autoencoder
Authors: Tuncer Kevser , Seçkin Kübra , TAŞAR Beyda , TANYLDIZI Nural IMIK , PIRINÇCI Edibe
Published: February 2024

Health literacy is defined as social policy. This study aims to determine the health literacy level of Syrian immigrants living in Elazig, Turkey and its relevant factors and to predict it with artificial intelligence methods.
The minimum sample size was calculated as 373 by using the Epi Info program. The questionnaire included socio-demographic information and the health literacy scale (HLS) EU-16. Means were presented with standard deviation (mean±SD), and p<0.05. was considered statistically significant. Besides performance evaluation, Support Vector Regression (SVR), Decision Tree (DT), Extreme Learning Machines (ELM), and Autoencoder Regression (AR) were used to estimate the HLS score.
The mean age of 404 Syrian immigrants who participated in the study was 32.64±10.97 years. They had been in Turkey for an average of 5.00±2.267 years. The mean total HLS score was 51.55±12.915. The HLS value of the Syrian immigrants was calculated using four different regression methods based on machine learning according to three basic criteria (Age, Duration of Stay in Turkey, and Monthly Income). Autoencoder, ELM, and DT regression methods indicated that the average estimation success was above 91% according to the R2 performance criterion, and the highest success rate of 98% was achieved with the autoencoder method.
Spatial clustering between socioeconomic inequalities and COVID-19 mortality rate in African continent
Authors: Ogunsakin Ropo , Akeju Kemi , Abimbola Adigun
Published: February 2024

Although local spatiotemporal analysis can improve understanding of the geographic variation of infectious diseases, its drivers, and the search for targeted interventions, it is limited in Africa; therefore, monitoring the spread and pattern is essential. Information on the spatial patterns will have substantial inferences for real awareness in future pandemics. Primarily, the linkage between infectious disease and socioeconomic indicators based on the perception of spatial connectivity should be understood as the spread nowadays between regions is progressively connected. This study applied spatial analysis, including the Moran-I index, the Local Indicator of Spatial Association (LISA) and spatial regression models to study the spatial variations in the effects of socioeconomic indicators on COVID-19 mortality in the African region. The preliminary test on the spatial correlation of COVID-19 showed a significant result; thus, a spatial regression approach was employed. The spatial clustering relationships between COVID-19 mortality and the socioeconomic indicators were analyzed in all five regions of Africa using ordinary least squares (OLS), spatial lag models (SLM), and spatial error models (SEM). We observed the clustering of countries for COVID-19 mortality, signifying spatial correlation within the countries of Africa. In addition, among all the socioeconomic indicators included, the effects of Gross Domestic Product and age dependency ratio on COVID-19 mortality were the most critical indicators that described the pandemic evolution across the subregion. These results highlight the need to draw preventive and response policies applicable to infectious diseases with more significant consideration of the different geographical points in the region.
Predicting risk factors for postoperative pneumonia in patients with lower limb fractures based on logistic regression model
Authors: Wei Conghui , Xiao Yiqinwen , Lin Xiaodan , Liu Ji , Luo Jun
Published: February 2024

Purpose: Lower limb fracture is a frequent cause of hospitalization, and postoperative pneumonia is an important marker of hospital cost and quality of care provided. As an extension of traditional statistical methods, machine learning provides the possibility of accurately predicting the postoperative pneumonia. The aim of this paper is to retrospectively identify predictive factors of postoperative pneumonia by using multivariate logistic regression model.
Methods: The incidence and admission of postoperative pneumonia in patients with lower limb fractures in the Second Affiliated Hospital of Nanchang University from 2017 to 2023 were retrospectively analysed. Patients who developed postoperative pneumonia during hospitalisation were defined as the pneumonia group, and those who did not develop postoperative pneumonia were defined as the no pneumonia group. Then logistic regression model of the postoperative pneumonia was developed and evaluated.
Results: The incidence of postoperative pneumonia was 6.44%, and the AUC values was 0.821, indicating that the module could predict the occurrence of postoperative pneumonia to a large extent. Sex, age, smoking history, alcohol consumption history, operation time, cerebrovascular disease, hypertension, diabetes, fracture type, surgical grade, globulin ratio, platelets, and C-reactive protein were identifed as signifcant factors for postoperative pneumonia.
Conclusions: Our proposed model corresponding to the predictors is designed to be convenient for clinical use. This model offers promising potential as a tool for the prevention and treatment of postoperative pneumonia in patients with lower limb fractures. Adopting appropriate health management methods may reduce the risk of postoperative pneumonia in patients with lower limb fractures.
Aharonov-Bohm interference and the evolution of phase jumps in fractional quantum Hall Fabry-Perot interferometers based on bi-layer graphene
Authors: Ronen Yuval , Kim Jehyun , Dev Himanshu , Kumar Ravi , Ilin Alexey , Haug André , Bhardwaj Vishal , Hong Changki , Watanabe Kenji , Taniguchi Takashi , Stern Ady
Published: February 2024

Quasi-particles in fractional quantum Hall states are collective excitations that carry fractional charge and anyonic statistics. While the fractional charge affects semi-classical characteristics such as shot noise and charging energies, the anyonic statistics is most notable in quantum interference phenomena. In this study, we utilize a versatile bilayer graphene-based Fabry-Pérot Interferometer (FPI) that facilitates the study of a broad spectrum of operating regimes, from Coulomb-dominated to Aharonov-Bohm, for both integer and fractional quantum Hall states. Focusing on the ν=1⁄3 fractional quantum Hall state, we study the Aharonov-Bohm interference of quasi-particles when the magnetic flux through an interference loop and the charge density within the loop are independently varied. When their combined variation is such that the Landau filling remains 1/3 we observe pristine Aharonov-Bohm oscillations with a period of three flux quanta, as is expected from the interference of quasi-particles of one-third of the electron charge. When the combined variation is such that it leads to quasi-particles addition or removal from the loop, phase jumps emerge, and alter the phase evolution. Notably, across all cases, the average phase consistently increases by 2π with each addition of one electron to the loop.
Real-Time Measurement and Analysis of Electromagnetic Fields from Some Typical Base Transceiver Stations
Authors: Lal Radhey , Singh Rajiv Kumar
Published: February 2024

In this study, RF electromagnetic field (EMF) levels produced by GSM 900, and GSM 2100 cellular base stations installed in various locations in Sitapur, UP, India, are measured and evaluated. Utilizing a Selective Radiation Meter (SRM-3006) to detect the power density of EMF levels close to cellular base stations is the measurement technique. An acceptable distance from the cellular base station was used to take the measurement. For the research of EMF levels, four different cellular base station locations in Sitapur, UP, India were selected. The measured results are compared to international standards including the Department of Telecommunication (DoT), Government of India (GoI), and International Commission on Non-Ionizing Radiation Protection (ICNIRP) standards. As a consequence of the research, it has been determined that there are no negative effects on human health or the environment in the area chosen for the study because all measured values of power densities fall well below the established set criteria.
Treatment of Iliac Arteriovenous Malformation Associated with Trisomy 21: A Case Report
Authors: Yang Jinming , Zhao Weichao , Liang Liping , Chi Guoqing
Published: February 2024

Both arteriovenous malformation (AVM) and trisomy 21 are rare diseases. Studies have shown that individuals with trisomy 21 may have potential vascular malformations, with the main site of onset being the portal system. This case involved an adult patient with trisomy 21 who presented with pelvic iliac arteriovenous malformations. The patient underwent interventional treatment, and the prognosis was favorable. It is important to enhance the screening for vascular malformations in patients with trisomy 21 syndrome. At the same time, interventional treatment for AVMs is effective and increasingly important for managing AVMs.
Effects of boric acid on proliferation, apoptosis and miRNAs in medullary thyroid cancer cells
Authors: Yıldırım Onurcan , Seçme Mücahit , Dodurga Yavuz , Mete Gülçin Abban , Fenkci Semin Melahat
Published: February 2024

Background: Medullary thyroid cancer (MTC) is a highly aggressive and chemotherapy-resistant cancer that originates from the thyroid's parafollicular C cells. Due to its resistance to conventional treatments, alternative treatments such as boric acid have been explored.Boric acid, a boron-based compound, has demonstrated anticarcinogenic effects, making it a potential candidate for MTC treatment.
Methods: Cell viability was assessed using the 2,3-bis(2-methoxy-4-nitro-5-sulfophenyl)-2H-tetrazolium-5-carboxanilide (XTT) assay. Total RNA was extracted using Trizol reagent for gene expression and microRNA (miRNA) analysis via reverse transcription-polymerase chain reaction (RT-PCR). The extent of apoptosis induced by boric acid was determined using the terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) assay. Colony formation assays were also conducted to evaluate the impact of boric acid on the colony-forming ability of MTC cells.
Results: At 48 hours, The 50% inhibitory concentration (IC50) of boric acid was found to be 35 μM. Treatment with boric acid resulted in significant modulation of apoptosis-related genes and miRNAs, including increased expression of NOXA, apoptotic protease activating factor 1 (APAF-1), Bcl-2-associated X protein (Bax), caspase-3,and caspase-9, which are associated with apoptosis. In contrast, the expression of B-cell lymphoma 2 (Bcl2) , B‐ cell lymphoma‐ extra-large (Bcl-xl) and microRNA-21 (miR-21), which are linked to the aggressiveness of MTC, was significantly reduced. The TUNEL assay indicated a 14% apoptosis rate, and there was a 67.9% reduction in colony formation, as shown by the colony formation assay.
Conclusion: Our study suggests that boric acid may have anticancer activity in MTC by modulating apoptotic pathways. These findings suggest that boric acid could be a potential therapeutic agent for MTC, and possibly for other malignancies with similar pathogenic mechanisms.
Quantitative DCE-MRI for prediction of pathological complete response prior to neoadjuvant systemic therapy
Authors: Wang Xingrui , Xiao Xuehong , Yang Ang , Zeng Shuyan , Chen Wenxi , Chen Yi , Cui Shien , Huang Zhihua , Zeng Yumei , Huang Xiaoxing
Published: February 2024

Purpose
To explore the correlation between quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI)-derived tumour characteristics prior to neoadjuvant systemic therapy (NST) and pathological complete response (pCR) in patients with breast cancer patients.
Methods
Among 120 randomly selected patients with breast neoplasms, 28 diagnosed with invasive ductal carcinoma underwent NST. All patients underwent at least three MRI examinations: preoperative and before and after NST. Spearman correlation analysis was used to assess the correlation between pCR and Miller–Payne (MP) scores with pharmacokinetic parameters (Ktrans, Kep, Ve, Vp) in the regions of interest (ROI) in the tumour (ROI1), tumoural junction with the normal gland (ROI2), peritumoural region (ROI3), and background parenchymal enhancement; tumour morphological characteristics (type, location, quantity, margin, and maximum diameter); enhancement or shrinkage mode; and residual condition following preoperative MRI.
Results
A positive correlation was observed between pCR and tumour HER2 expression (r = 0.546); and Kep (r = 0.427) and Ve of ROI3 (r = 0.564) (P < 0.05). A negative correlation between pCR, tumour shrinkage pattern (r=-0.506) and residual tumours (r=-0.551) was observed by preoperative MRI (r=-0.551) (P < 0.05). MP associated with progesterone receptor (r=-0.37), HER2 (r = 0.608), and Ki-67 (r = 0.393) expression; tumour shrinkage pattern (r=-0.625); and preoperative MRI residual tumour (r=-0.715) (P < 0.05). Preoperative MRI tumour residual status associated with Ki-67 (r=-0.465) and tumour shrinkage pattern (r = 0.677) (P < 0.05).
Conclusions
A correlation was observed between DCE-MRI of the peritumoural region prior to NST and pCR. Early MRI evaluation of tumour shrinkage patterns following NST and preoperative tumour residual status showed predictive value for pCR and tumour burden.
FS-mutant: A Few-shot Learning Benchmark for Protein Mutants Mining
Authors: Li Mingchen , Yu Huiqun , Fan Guisheng , Zhou Ziyi , Tan Pan , Hong Liang
Published: February 2024

AI-assisted protein engineering means using machine learning models to mine mutants of a protein from its huge mutant library. Existed techniques, such as supervised models and zero-shot models, have received a lot of attention. The supervised approaches require a lot of data for optimal performance while the zero-shot models do not need assay-labeled data but their performance cannot be improved with labeled data increasing. In practice, researchers only have a small number of data, which is more like a few-shot learning problem. However, the few-shot learning within this domain has remained relatively unexplored. Moreover, there exist no standardized datasets and benchmarks that offer comprehensive basis for evaluating few-shot learning methods. In this paper, we present a few-shot learning dataset (FS-mutant) and benchmarking procedure. The dataset contains mutant data from eleven proteins with a variety of functions while the training set size are limited to 20, 40, 80, 160, and 320. In addition, we implement some zero-shot learning, supervised-learning, and meta-learning baselines and evaluate their performance on FS-mutant. We hope that FS-mutant will encourage future work on this extremely challenging domain. Data, code, and scripts can be found at https://github.com/ginnm/fs-mutant.
Sentiment Analyis and Bitcoin Price Prediction
Authors: BAMIDELE TOYOSI
Published: February 2024

The emergence of Bitcoin as a decentralized digital currency has underscored the importance of developing advanced techniques for predicting its price fluctuations. This study evaluates the predictive power of Bitcoin-related Google search volumes and Twitter sentiment analysis within short time frames. By leveraging machine learning algorithms and opinion mining, we identify correlations between online behaviors and Bitcoin price movements. Our methodology encompasses data sourcing, preprocessing, exploratory analysis, feature selection using Correlation Analysis, F-regression, Shapley values, and price prediction with a Long Short-Term Memory (LSTM) model. Findings reveal that Google search data, compared to Twitter sentiment, significantly enhances model accuracy and reduces prediction errors. The study suggests future research to investigate other search engines and online news sentiment, acknowledging limitations in data quality and accessibility of historical Twitter data.
The Impact of Natural Disasters on the Financialization of enterprises: Facilitation or Inhibition
Authors: Tang Rui , Zhao Mengchan , Wu Yigen
Published: February 2024

When faced with the impact of a disaster, do enterprises focus more on industrial development or try to allocate financial assets to smooth out the impact of the disaster on performance? Based on the sample of non-financial listed enterprises in Shanghai and Shenzhen A-shares, it is found that (1) Episodic and compound natural disasters significantly inhibit enterprise financialization (2) Compound disasters leads to an increase in the holding of short-term financial assets. Episodic and compound disasters inhibit the allocation of long-term financial assets. (3) Private enterprises tend to increase holdings of financial assets under compound disaster shocks, and non-high-tech enterprises and enterprises with low financing constraints contract financial asset allocation more significantly under disaster shocks. (4) Enterprises’ self-help behavior and government humanitarian aid during disaster shocks may inhibit their financialisation behavior. The results provide useful guidance for the smooth functioning of the real economy under uncertainty shocks.
Enhancing Low Voltage Ride-Through Resilience in Grid-Connected Doubly-Fed-Induction-Generator with Sliding Mode Controller
Authors: Ananth D. V.N. , Vineela K. S. T.
Published: February 2024

In power systems, grid disturbances are prevalent, causing significant challenges for Doubly-Fed Induction Generators (DFIGs). During these disturbances, the windings of DFIGs are exposed to large offset inrush currents, which can damage the converter switches and capacitors. Additionally, low voltage faults result in a dip in the rotor speed, leading to current injection in the rotor windings at the changed rotor slip frequency during the fault. This behaviour can be detected using stator two-axis instantaneous voltage and flux. In this study, we propose an innovative application of Sliding Mode Control (SMC) in both the rotor-side converter (RSC) and grid-side converter (GSC) control schemes of a DFIG. The primary objective is to effectively control the flux decay and reduce torque pulsations, rotor speed variations, and current deviations through an enhanced SMC approach. The proposed technique compensates and rapidly decomposes the stator dc-offset flux component based on deviations in the speed of the rotor with the reference value and the dc flux. To assess the effectiveness of the proposed approach, we conduct a comparative analysis between the conventional Proportional-Integral (PI) control and the proposed SMC technique under symmetrical grid fault conditions. The results demonstrate the superior performance of the enhanced SMC in mitigating the adverse effects of grid disturbances on DFIGs.
Relationship between Conjunctival Impression Cytology, the Type of Eye Rubbing and the Stages of Keratoconus
Authors: Rodriguez Luis A. , Guerrero Sara Elena , Rodriguez-Gutierrez Luis A. , Porras Dianela , Orellano María Eugenia
Published: February 2024

Purpose To describe the conjunctival impression cytology changes in keratoconus patients with eye rubbing, dry eye and ocular allergy.Methods Descriptive, cross-sectional study. Forty-four eyes of 22 patients with keratoconus, ocular allergy, eye rubbing and dry eye were included. Ocular Surface Disease Index (OSDI) and Ocular Allergy Index (OAI) questionnaires were given to all participants and impression cytology was performed to obtain Nelson’s classification.Results Stage II-IV keratoconus patients had higher grades of squamous metaplasia (p < 0.01979). Eye rubbing with the index and middle finger was related to Nelson grade 3 (p < 0.0032), stage IV keratoconus (p < 0.0007), and a severe OSDI result (p < 0.0035). A severe result in the OAI was associated with stage IV keratoconus (p < 0.0035) and eye rubbing with the knuckles (p < 0.000024).Conclusion Keratoconus is a multifactorial disease where eye rubbing plays an important role in disease progression. Persistent eye rubbing may increase the levels and activity of inflammatory mediators, leading to the development of the disease. Our study suggests that eye rubbing with the knuckles, the index and middle finger can lead to advanced stages of keratoconus. Keratoconus stage IV was associated with a severe OSDI result, and higher degrees of squamous metaplasia (Nelson grade 3).
Effects of forest structure from graph theory connectivity indicators on river water quality in the Caspian Sea Basin
Authors: Masteali Sahar Heidari , Bayat Mahmoud , Khalyani Azad Henareh
Published: February 2024

Landscape structure is one of the most important factors affecting the sources of food and organic matter in rivers. The spatial patterns of landscape patches including dimension variability and gap sizes between patches contribute in the amount and type of materials discharged to waterbodies and watercourses. We studied the effects of forest-patch connectivity and landscape corridors on water quality in the Greater Caspian Sea Basin. We used 10 landscape metrics and 11 water-quality indicators developed from graph theory to examine if contiguous/unfractured landscapes enhance water quality. We used independent calculations of Pearson’s and Spearman’s correlation coefficients to explore the association of forest-patch connectivity and water quality metrics. Stepwise regression was also used to generate allometry-based power, exponential, and logarithmic models. The results of correlation between forest-patch connectivity indicators and water quality parameters showed that several forest-patch metrics indicating connectivity including dLCP (Landscape coincidence probability) and dIIC (Integral Index of Connectivity) had a significant negative correlation with water quality metrics indicating pollution. This means that increasing forest connectivity is associated with improvement in water quality. The modeling results also showed that almost all selected models with acceptable AIC coefficients were nonlinear models. As connectivity of forest patches decreases and more fragmentation occurs in a watershed, the parameters of water pollution increase and the quality of water decreases. Models showed high R2 values for water quality metrics including CO3 (0.82), water discharge (0.73), Ca (0.77), and TDS (Total Dissolve Solids) (0.70).
Spatial Zoning and Comparison of Mesoscale Coastal Waters Schemes
Authors: Chen Zhou , Haifeng Zhang , Zhao Lin , Du Wen , Xu Min
Published: February 2024

Comprehensive zoning of coastal waters based on the ecosystem is the key to the compilation and effective management of coastal waters spatial planning. In this study, a comprehensive zoning scheme was developed based on ecological zoning of the Marxan model and resource use zoning. Resource use zoning was then used as an ecological protection cost to optimize comprehensive zoning. By comparing and evaluating the spatial structure and benefits of comprehensive zoning optimized schemes, it was found to shorten the boundary length of the protection zone, increase connectivity, and reduce fragmentation between the protection zones. This study is significant in enriching and improving the theoretical and technical methodological system of city-level mesoscale coastal waters spatial planning in China, therefore improving the science and evaluability of planning, and providing spatial guidance and decision-making references for ecological environmental protection and the sustainable use of resources in the coastal waters of Nantong.