bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on the Evaluation and Spatial Layout of High Quality Development of Higher Education in China
Authors: Li Wen , Shi Jinfa , Zuo Qiting , Ma Jianqin , Qiu Meng
Published: February 2024

As a social subsystem, the layout of higher education is related to the degree of harmony in the economy and society. Based on the panel data from the “China Statistical Yearbook”, “China Education Statistical Yearbook” and the “Education Statistical Yearbook” of China’s provincial administrative regions from 2000 to 2022, considering factors such as sustainable economic and social development capacity, regional scientific and technological cultural development level, and spatial layout of higher education, the degree of harmonious development among the three is determined. This paper constructs an indicator system for harmonious development of China’s higher education, and uses the method of “single indicator quantification-multi indicator synthesis-multi criteria integration” (SMI-P) to determine the harmonious development index of China’s higher education. The ArcGIS spatial analysis method is used to study the spatial distribution changes of higher education harmonious development in China’s 31 provincial administrative regions. Then, the Tobit model is used to analyze the impact of various economic and social factors, scientific and cultural factors or layout of higher education factors on the harmonious development of higher education, in order to optimize the spatial layout of China’s higher education resources, balance education development, narrow regional disparities, promote regional coordination, and enhance the overall competitiveness of higher education. Research has found that: (1) The development of higher education subsystems shows a trend of convergence; (2) Over the past 23 years (from 2000 to 2023), the spatial centroid of harmonious development of higher education (HDHE) in China shifted southward; (3) There is a strong spatial interaction between 3 subsystems of harmonious development of higher education in China(economic society subsystem, technology and culture subsystem, and higher education subsystem); (4) The main factors affecting HDHE in China include the degree of regional ecological civilization, the ratio of university students to teachers and the per capita domestic patent application authorization.
Improved Reservoir Mapping and Gas Initial in Place Estimation through Broadening the Frequency Spectrum of Seismic Data, East Mediterranean, Egypt
Authors: Attia Ibrahim , Helal Abd El-Naser , Rawy Azza El
Published: February 2024

In recent years, the East Mediterranean region of Egypt has garnered significant attention due to its abundant hydrocarbon resources. One of the key challenges faced by the exploration and development of these reserves is the complex reservoir sequence developed during the Pliocene-Pleistocene period. This complexity has resulted in inconsistencies between the static volumes computed for different Direct Hydrocarbon Indicator (DHI) and those generated through dynamic modeling. These inconsistencies have led to an underestimate of the gas volumes in certain gas-producing levels, hindering accurate reserve estimation. In an effort to address this issue, this paper aims to expand and enhance the frequency spectrum of seismic data to improve seismic data resolution hence image the complexity of the reservoir. To achieve this objective, several techniques are presented that seismic colored inversion (CI), seismic spectral blueing (SSB), and spectral decomposition attribute extractions. By increasing the frequency bandwidth of the seismic data, these techniques enhance the resolution of seismic attributes and improve the accuracy of reservoir characterization. The implementation of seismic CI and SSB techniques has been revealed successfully increase the vertical resolution of seismic data from 31 meters to 17 meters using SSB and to 23 meters using CI. These improvements have positively matched drilled wells, providing a more accurate estimate of the hydrocarbon reserves.
The Central Composite Design and Artificial Neural Network in Optimization and Modeling of Radiolabeling Process of 177Lu-hydroxyapatite as a Potential Radiosynovectomy Agent
Authors: Nosrati S. Attar , Salahinejad M. , Aboudzadeh M.R. , Amiri M. , Roozbahani A.
Published: February 2024

Background
A promising material used in radiation synovectomy of small joints is hydroxyapatite which has been labeled with 177Lu. During the design and production of radiopharmaceuticals, the condition of the radiolabeling process, directly influences the radiochemical yield and consequently the quality of the final product so this process necessitates a precise optimization. In this investigation, central composite design based on response surface methodology and artificial neural networks are applied to build predictive models and explore the effect of key parameters in the radiolabeling process of hydroxyapatite with 177Lu radionuclide. The variables that directly affected the labeling reaction were the initial 177Lu radionuclide concentration, pH, radiolabeling reaction time and temperature.
Results
Based on the validation data set, the statistical values demonstrate that the artificial neural networks model performs better than the response surface methodology model. The artificial neural networks model has a small mean squared error (9.08 artificial neural networks < 12.36 response surface methodology) and a high coefficient of determination (R2: 0.99 artificial neural networks > 0.93 response surface methodology). In addition, the maximum radiochemical yield is found at the initial concentration of 177Lu radionuclide = 0.128 megabecquerel (MBq), pH = 6.1, and temperature = 38.9 (oC), by performing the response surface methodology.
Conclusion
The ability to generate more data with fewer experiments for optimization and improved production is a pertinent advantage of multivariate optimization methods over traditional methods in radiation-related activities. The central composite design optimization and artificial neural networks modeling are successfully utilized to create prediction models and investigate the impact of critical variables in the radiolabeling of hydroxyapatite with 177Lu radionuclide.
Revealing the atomic and electronic mechanism of human manganese superoxide dismutase product inhibition
Authors: Borgstahl Gloria , Azadmanesh Jahaun , Slobodnik Katelyn , Struble Lucas , Lutz William , Coates Leighton , Weiss Kevin , Myles Dean , Kroll Thomas
Published: February 2024

Human manganese superoxide dismutase (MnSOD) is a crucial oxidoreductase that maintains the vitality of mitochondria by converting O2•− to O2 and H2O2 with proton-coupled electron transfers (PCETs). Since changes in mitochondrial H2O2 concentrations are capable of stimulating apoptotic signaling pathways, human MnSOD has evolutionarily gained the ability to be highly inhibited by its own product, H2O2. A separate set of PCETs is thought to regulate product inhibition, though mechanisms of PCETs are typically unknown due to difficulties in detecting the protonation states of specific residues that coincide with the electronic state of the redox center. To shed light on the underlying mechanism, we combined neutron diffraction and X-ray absorption spectroscopy of the product-bound, trivalent, and divalent states to reveal the all-atom structures and electronic configuration of the metal. The data identifies the product-inhibited complex for the first time and a PCET mechanism of inhibition is constructed.
Xanthoma Combining Osteonecrosis in Knee Joint: A Case Report
Authors: Su Hai , Gong Yichen , Chen Lei , Zhou Haojing , Huang Hua , Yu Shengxu , Wang Chundan , Tong Peijian , Xu Taotao
Published: February 2024

Xanthoma typically occurs in the subcutaneous tissues, with rare cases of osseous xanthoma. However, the occurrence of knee joint osteonecrosis combined with xanthoma is even more uncommon. To the best of our knowledge, this is the first reported case. In this article, we describe a 50-year-old female patient who developed xanthoma on the basis of osteonecrosis of the knee joint. The primary clinical symptoms were knee joint pain and limited mobility. Despite conventional treatments for osteonecrosis, there was no significant improvement. Subsequently, she underwent arthroscopic excision of the knee joint xanthoma. Following the procedure, her VAS score decreased from 7 to 2, and knee joint mobility increased from 10-103° to 10-140°. Through our follow-up, the patient did not exhibit symptom recurrence. This case is valuable and provides a feasible therapeutic approach for future clinical applications.
Probenecid, a Pannexin1 inhibitor, restores deranged NMDA receptor and nNOS profiles in cerebellum of minimal hepatic encephalopathy rats
Authors: Acharjee Papia , Acharjee Arup , Prasad Shambhu Kumar , Singh Vishal Vikram , Mallick Debasmit , Trigun Surendra K
Published: February 2024

Modulating Pannexin1 (Panx1), an ATP exit channel, in brain cells as a therapeutic option for neurological disorders, is an evolving concept. Our previous report on concordant increase in Panx1 vs neuronal nitric oxide synthase (nNOS) in cerebellum of the minimal hepatic encephalopathy (MHE) rats led us to explore whether Panx1 could be modulated to ameliorate the neurochemical aberrations related to MHE pathogenesis. This article describes the effect of Panx1 inhibition by probenecid (PB) on the relative profile of NMDA receptor (NMDAR)-nNOS axis and the level of degenerating cerebellar Purkinje cells vs recovery in the motor function deficit in a neurobehaviorily characterized MHE rats developed by administering 50 mg/kg bw thioacetamide intraperitoneally for 14 days. As compared to the control group rats, cerebellum of the MHE rats showed concordant increases in the level and activities of Panx1 and nNOS with a concomitant decline in the ratio of NMDAR subunit 2A/2B coinciding with atrophy of the purkinje cells. Moreover, all these parameters were observed to be recovered back to their control levels due to the treatment with a Panx1 inhibitor, Probenecid (PB), to the MHE rats. Such a recovery in the neurochemical parameters were found to be consistent with the restoration of Purkinje cell population and the MHE associated impaired rota-rod performance tests. The findings underscore PB-mediated Panx1 inhibition as a promising therapeutic avenue for ameliorating the MHE pathogenesis related neurochemical aberration and motor coordination deficits.
3D structure of microbunched plasma-wakefield-accelerated electron beams
Authors: Downer Michael , LaBerge Maxwell , Bowers Brant , Chang Yen-Yu , Cabadag Jurjen Couperus , Debus Alexander , Hannasch Andrea , Pausch Richard , Schobel Susanne , Tiebel Jessica , Ufer Patrick , Willmann Anna , Zarini Omid , Zgadzaj Rafal , Lumpkin Alex , Schramm Ulrich , Irman Arie
Published: February 2024

Plasma wakefield accelerators use tabletop equipment to produce relativistic femtosecond electron bunches. Optical and x-ray diagnostics have established that their charge concentrates within a micrometer-sized volume, but its sub-micrometer internal distribution, which critically influences gain in free-electron lasers or particle yield in colliders, has proven elusive to characterize. Here, by simultaneously imaging different
wavelengths of coherent optical transition radiation (COTR) that
a laser-wakefield-accelerated e-bunch generated when exiting a metal foil, we elucidated the structure of the coherently-radiating component of bunch charge. Key features of the images correlated uniquely with how plasma electrons injected into the wake: by a plasma-density discontinuity, by ionising high-Z gas-target dopants, or by uncontrolled laser-plasma dynamics. With additional input from electron spectra, spatially-averaged COTR spectra, and particle-in-cell simulations, we reconstructed coherent 3D charge structures. The results demonstrate
essential metrology for next-generation X-ray free-electron lasers.
The chloroplast genome sequence and phylogenetic analysis of Rubia alata Wall and Rubia ovatifolia Z. Ying Zhang.(Rubiaceae)
Authors: Shi JiaZhou , Chen XiaoYing , Jing YiYao , Yan Yonggang , Zhang Gang , Yang BingYue , Peng Liang
Published: February 2024

Background Rubiaceae, a genus encompassing approximately 70 species distributed globally, includes Rubia alata Wall and Rubia ovatifolia Z. Ying Zhang, distinctive medicinal plants native to China. The acquisition of chloroplast genome sequences of R. alata and R. ovatifolia holds paramount significance for elucidating species divergence, constructing phylogenetic relationships, and comprehending RNA editing processes
Result In this study, the complete chloroplast genome of R. alata and R. ovatifolia were obtained based on the sequences generated by Illumina HiSeq. The chloroplast genome of R. alata is 154,973 base pairs (bp) in length, containing a large single-copy region (LSC) of 84,801 bp, a small single-copy region (SSC) 17,138 bp, and a pair of inverted repeats (IRs) of the same length. The length is 26,517 bp, and the length of the LSC, SSC, and IR regions of R. ovatifolia is 84,716, 17,116 and 26,517 bp, respectively. The chloroplast genomes in both varieties cover 130 genes, including 85 protein-coding genes, 37 transfer-RNA genes (tRNA), 8 ribosomal RNA genes (rRNA). There were differences in the size of the chloroplast genome, while the genome structure was conservative and the composition was similar. Although there was a small degree of variation, it still had high homology. The assembled chloroplast genome in this study provided useful molecular information about the evolution of R. alata and R. ovatifolia which was a basis for phylogenetic analyses of Rubiaceae.
Conclusions The findings of this study have improved our understanding of the internal structure of the chloroplast genome of Rubia plants and are of great value for the future development and utilization of R. alata and R. ovatifoliaresources.
Event-Driven Figure-Ground Organisation model for the humanoid robot iCub
Authors: D'Angelo Giulia , Voto Simone , Iacono Massimiliano , Glover Arren , Niebur Ernst , Bartolozzi Chiara
Published: February 2024

Figure-ground organisation is a mechanism of perceptual grouping that serves the detection of objects and their boundaries, needed by any agent to interact with the environment.
Current approaches to figure-ground segmentation rely on classical computer vision or deep learning, requiring vast computational resources, in particular during the training phase of the latter.
Inspired by the primate visual system, we developed a bio-inspired perception system to compute figure-ground organisation for the neuromorphic robot iCub.
The proposed model distinguishes foreground objects from the background, thanks to a hierarchical biologically plausible architecture, exploiting event-driven vision.
Differing from classical approaches, the use of event-driven cameras reduces data redundancy and computation.
The system has been qualitatively and quantitatively assessed both in simulation and using the event-driven cameras mounted on the iCub looking at different scenarios and stimuli. The model successfully segments items in diverse real-world scenarios, showing comparable results against its frame-based version on simple stimuli and on the Berkeley Segmentation dataset benchmark (D. Martin, 2001). This model further offers a valuable addition to hybrid systems, complementing conventional computer vision deep learning models by processing only relevant data in detected Regions of Interest (ROI), thereby enabling low-latency autonomous robotic applications without redundant information.
Effect of neostigmine antagonizing non-depolarizing muscle relaxants on postoperative pulmonary complications in patients after lobectomy：a retrospective cohort study
Authors: Shang Ziqi , Weng Yan , Chen Yong , Dai Wei , Zhang Hua , Zhong Qing
Published: February 2024

Objective
To investigate the effect of neostigmine, which was used to antagonistic muscle relaxant, on the incidence of postoperative pulmonary complications (PPCs) in patients with lobectomy.
Methods
This is a retrospective cohort study using electronic medical information and telephone followed-up information of patients who admitted in the thoracic surgery department, the People’s Hospital of Jianyang from Jun 2021 to May 2022. All patients were divided into 2 groups according to whether PPCs occurred or not: Neostigmine antagonists (NEO group) and non-Neostigmine antagonists (N group). The outcomes of the two groups were compared with the T-test, Mann-Whitney U test and Pearson Chi-square test.
Results
A total of 227 patients were analyzed, there was no significant difference in baseline data between the two groups (P > 0.05); the incidence of PPCs during postoperative hospitalization was significantly different between the two groups (𝛘2 = 4.143, P = 0.042 < 0.05); 30 days after discharge, there was no significant difference in the incidence of PPCs between the two groups (𝛘2, 0.715, P = 0.398 > 0.05); there was no significant difference in the length of hospital stay between the two groups (Wilcoxon rank sum test, Z = 0.411, P = 0.681 > 0.05);there was no significant difference between the two groups (F = 0.404, P = 0.668 > 0.05) of Steward scores at 10min (T1), 30min (T2) and 60min (T3) after tracheal catheter removal; there was no significant difference in PACU residence time between the two groups (Z = 0.954, P = 0.340 > 0.05).
Conclusions
In patients with elective lobectomy, the postoperative choice of neostigmine for muscle loosening antagonism can reduce the incidence of PPCs during postoperative hospitalization, but it has no effect on the incidence of PPCs within 30 days after surgery.
Extraction of Cynaroside from Honeysuckle by Nonionic Surfactant-mediated Aqueous Extraction with Cloud Point Enrichment and Purification by Metal Complexation
Authors: Zhu Wen , Zhao Xiuhua , Tang Cuiman , Wang Bin , Lv Yue , Liu Jialin , Sun Chaofan , Zu Yuangang
Published: February 2024

Honeysuckle is rich in cynaroside (Cy), but its extraction and purification are difficult due to its poor solubility in water. Therefore, nonionic surfactants were used to extract Cy from honeysuckle plants, enabling the formation of micelles that solubilized Cy in aqueous solution. The effects of temperature, extraction time, surfactant concentration, and the solid-liquid ratio on the extraction rate of Cy were investigated to determine the optimal extraction conditions. The cloud point effect of the optimal nonionic surfactant was exploited to separate the extracting solution into two distinct phases, which resulted in the concentration of Cy into the up phase. The phase containing the extracted Cy was then purified by metal complexation after phase separation using CaCl2 followed by EDTA, resulting in a purity of Cy of 93.7%. Surfactants have high biological safety, making the extraction process safer and more environmentally friendly. As a result, the process developed in this study enabled the efficient and environmentally friendly extraction of Cy from plants, which has potential value in the production of various medicines and health products containing natural botanicals, such as Cy.
Interpersonal adjustment and depression in college students: mediation of core self-evaluation and moderating effects of gender
Authors: Ma Siqi
Published: February 2024

Background With the high incidence of college student suicides due to depression, it is critical to understand the factors that influence depression in college students. This study addresses the interconnected relationships among interpersonal adjustment, depression, core self-evaluation and gender among college students.
Objectives This study aims is to explore how college students’ interpersonal adjustment is to influence and provide due insights for effective interventions for college students’ depression.
Methodology We used the Interpersonal Adjustment Scale for College Students, Center for Epidemiological Studies Depression Scales, and the Core Self-Evaluation Scale, and recruited 1920 college students to fill out the questionnaire, and finally obtained 1748 valid participants.
Results The results showed that college students’ interpersonal adjustment and core self-evaluation negatively predicted depression, and core self-evaluation mediated the relationship between college students’ interpersonal adjustment and depression. While gender moderated the relationship between college students’ interpersonal adjustment and core self-evaluation.
Conclusions and implications Interpersonal adjustment and core self-evaluation can serve as significant predictors of depression in college students. Moreover, interpersonal adjustment has a significantly higher effect on depression among female college students than male college students. Based on the results of the study, we proposes to enhance the college students’ interpersonal and core self-evaluation adaptability to cope with the problem of college students’ depression, and we should pay more attention to female college students.
Determination of Precise Galileo and Sentinel-6A Orbits through the Integration of GNSS and SLR Data
Authors: Jiang Weiping , Cui Zilu , Chen Hua , Zhou Xingyu , Liu Tianjun , Li Zhao
Published: February 2024

Both Galileo and Sentinel-6A satellites are equipped with GNSS and SLR observation capabilities, which shows the potential to improve the orbits by combining both GNSS and SLR data. In this study, Galileo and Sentinel-6A satellites reduced dynamic orbits were determined by integrating GNSS and SLR data at the observation level, where two weighting strategies and the impact of SLR data on the final orbits were assessed. Data over 300 days were adopted in the experiments. It is found that the 3D RMS between dynamic and kinematic orbits for Sentinel-6A during the satellite maneuvers on DOY 173 is reduced by 10\%, which indicate the SLR data could bring a significant improvement to the dynamic Sentinel-6A orbits when satellite maneuvers. Moreover, in comparison to GNSS-only solutions, the adoption of the dynamic weighting strategy during orbital maneuvers has demonstrated a decrease in SLR residuals STD values by 9\% to 46\%. The results also show that introducing the SLR data can lead to a reduction of approximately 5\% in the averaged overlapping RMS for Galileo satellites. Nonetheless, the integration of SLR observations could enhance the accuracy and reliability of both Galileo and Sentinel-6A orbits, especially during orbital maneuvers.
Comparing methods for risk prediction of multicategory outcomes: dichotomized logistic regression vs. multinomial logit regression
Authors: li lei , Rysavy Matthew A. , Bobashev Georgiy , Das Abhik
Published: February 2024

Background
Medical outcomes of interest to clinicians may have multiple categories. Researchers face several options for risk prediction of such outcomes, including dichotomized logistic regression and multinomial logit regression modeling. We aimed to compare these methods and provide practical guidance needed.
Methods
We described dichotomized logistic regression and competing risks regression, and an alternative to standard multinomial logit regression, continuation-ratio logit regression for ordinal outcomes. We then applied these methods to develop prediction models of survival and growth outcomes based on the NICHD Extremely Preterm Birth Outcome Tool model. The statistical and practical advantages and flaws of these methods were examined and both discrimination and calibration of the estimated models were assessed.
Results
The dichotomized logistic models and multinomial continuation-ratio logit model had similar discrimination and calibration in predicting death and survival without neurodevelopmental impairment. But the continuation-ratio logit model had better discrimination and calibration in predicting probabilities of neurodevelopmental impairment. The sum of predicted probabilities of outcome categories from the logistic models did not equal 100% for about half of the study infants, ranging from 87.7% to 124.0%, and the logistic model of neurodevelopmental impairment greatly overpredicted the risk among low-risk infants and underpredicted among high-risk infants.
Conclusions
Estimating multiple logistic regression models of dichotomized outcomes may result in poorly calibrated predictions. For an outcome with multiple ordinal categories, continuation-ratio logit regression is a useful alternative to standard multinomial logit regression. It produces better calibrated predictions and has the advantages of simplicity in model interpretation and flexibility to include outcome category-specific predictors and random-effect terms for patient heterogeneity by hospital.
Asymptomatic malaria in pregnancy and associated risk factors in Majang Zone, Gambella Region, Southwest Ethiopia: A hard-to-reach malaria hotspot
Authors: Alemayehu Aklilu , Abossie Ashenafi , Zeynudin Ahmed , Yewhalaw Delenasaw , Beyene Joseph
Published: February 2024

Background
Asymptomatic malaria in pregnancy (AMiP) is a daunting public health problem with multifaceted adverse outcomes for mothers, fetuses, newborns and beyond. This study aimed to assess the prevalence and risk factors of AMiP in Majang Zone, Gambella Region, Southwest Ethiopia.
Method
A facility-based cross-sectional study was conducted among 425 pregnant women attending the ANC clinics of five health facilities in the Majang Zone from November 01, 2022, to February 28, 2023. Sociodemographic, obstetric, and antimalarial intervention data were collected using an interviewer-administered questionnaire. Capillary blood specimen was collected to diagnose malaria and anemia as well as determine blood group. Malaria was diagnosed by rapid diagnostic test (RDT), microscopy, and quantitative Polymerase Chain Reaction (qPCR). Statistical analyses were done by SPSS version 26.0 for Windows. The associations between dependent and independent variables were assessed by multivariable binary logistic regression considering P < 0.05 statistically significant. The magnitude of associations was quantified with the AOR along with the corresponding 95% CI.
Results
The prevalence of AMiP was 11.3%, 11.7%, and 15.3% by RDT, microscopy and qPCR, respectively. More than half of the infections were due to P. falciparum (55.4%). Moderate parasitemia accounted for half (50.8%) of the overall infection severity and a geometric mean asexual parasitemia was 2,683/µl. Approximately 32.3% of pregnant women with AMiP carried gametocytes with a geometric mean density of 1,213/µl. Not using ITN in the last week (AOR: 9.43 95% CI: 1.57, 56.62), having a history of malaria in the last year (AOR: 2.26 95% CI: 1.16, 4.42), lack of IRS spraying in the last year (AOR: 3.00 95% CI: 1.50, 6.00), and ANC contact less than two (AOR: 4.28 95% CI: 2.06, 8.87) were identified as risk factors associated with AMiP.
Conclusion
The prevalence of AMiP was high, and remained as an important public health problem in the study area. The identified risk factors should be considered to mitigate AMiP in the study area.
Molecular modeling studies of Pyrazolopyrimidine Derivatives as potent Cyclin Dependent Kinase-2 inhibitors
Authors: Chagaleti Bharath Kumar , K Kathiravan Muthu
Published: February 2024

This study addresses the pressing need for innovative cancer treatments in the face of global challenges posed by the widespread occurrence of cancer and increasing treatment resistance. The study looks at cyclin-dependent kinase-2 (CDK2) and uses a methodical computer approach to find possible anticancer compounds with pyrazole and pyrimidine structures. (QSAR) quantitative structure-activity relationship has become crucial in lead optimization over the last three decades. A set of 45 pyrazolopyrimidine derivatives with known IC50 values were used to create and test models using QSARINS software. Model 4, with its high predictive performance (R2 = 0.9100, R2adj = 0.8900, LOF = 0.0394), emerges as the most reliable. The resulting QSAR model proves stable, predictive, and robust, effectively representing the original dataset. Active molecular descriptors are identified for predicting the structure-activity relationship. We used SAR analysis and model equation parameters to create sixty compounds and tested them for their predicted bioactivity using Model 4. These compounds are a series with pyrazolopyrimidine-fused piperidine and hybrid moieties, such as methanethione (20), ethenone (20), and benzamide (20). Among the designed series, 16 compounds exhibited pIC50 values exceeding 7, indicating that they were hit molecules represented as C1-C16. These obtained hit molecules undergo further screening with ADMET, molecular docking, and molecular dynamics simulations. C3 and C7, revealed in docking studies with low-energy conformations and sustained binding during simulations, consistently align their binding modes with the standard drug roscovitine. These compounds emerge as promising leads for targeting CDK2 in the development of groundbreaking cancer therapies.
Environmental Kuznets Curve Hypothesis in Ethiopia
Authors: Derege Alemayehu Ethiopia
Published: February 2024

This study used regional panel data from Ethiopia to examine the degree to which Ethiopia adhere to the environmental Kuznets curve hypothesis and, in turn, estimate the extent to which its people are willing to contribute to environmental development. According to the research, the country complies with the environmental Kuznets curve hypothesis; though environmental resources are regarded either basic or inferior commodity. In relatively more urbanized regions (Harari and Addis Ababa), EKC is U-shaped, negating the hypothesis. During the short run, environmental willingness to pay is typically seen to be low across the nation, with residents of states with higher levels of forestation being more ready to pay for a cleaner environment. The study concludes that economic development takes precedence over environmental development and suggests pro-growth economic policies backed by environmental development assistances.
Heatwave Magnitude Impact and Projected Changes Over Himachal Pradesh: Cmip 6 Projections
Authors: Rana Saksham , Meena Ray Singh
Published: February 2024

Being a hilly state Himachal Pradesh, heatwave incidents are not associated with each other, yet recent news and incidents are concerning. Numerous studies have shown that climate change has an extremely unexpected effect on the planet, causing natural disasters such as heatwaves and floods to become more intense everywhere. With the help of the daily maximum temperature dataset from 13 General Circular Models (GCMs) of CMIP-6 projection from to 2020–2100 of four SSPs (126, 245, 370, and 585) scenarios, this study is an attempt to predict the impact of climate change on Himachal Pradesh at the district level in terms of heatwaves, comparing their intensity and frequency over the entire area. This research aids in determining the most vulnerable regions in Himachal Pradesh as well as the ways in which variations in altitude and varying degrees of climate change affect heatwave patterns, trends, and intensity. These findings imply that as altitude rises, so does the frequency and intensity of heatwaves, which in turn increase with the effects of climate change.
Discovering critical nodes in transportation network for traffic speed prediction: A deep learning approach
Authors: Chen Xiaoming , Wang Jiali , Zhang Weijie , Shen Zhou
Published: February 2024

Intelligent transportation systems play a pivotal role in addressing the growing challenges of urban mobility. This paper introduces the Spatial-Temporal Traffic Predictor (STTP), a novel deep learning approach designed for accurate traffic speed prediction within transportation networks. Motivated by the need for advanced models to optimize traffic flow and mitigate congestion, STTP strategically integrates spatial and temporal dependencies, capturing intricate patterns crucial for precise predictions. Through extensive experiments on real-world datasets, including diverse urban contexts, STTP demonstrates superior performance compared to state-of-the-art methods. The model excels in capturing both spatial and temporal dynamics, identifies critical nodes within transportation networks, and showcases robust generalization across different cities. The findings affirm STTP's potential as a versatile tool for enhancing traffic management and contributing to the development of smarter transportation infrastructures.
Diagnostic and prognostic role of microRNA-525 in different cancers: A systematic review and meta-analysis
Authors: ZHAO MENG , PAN YUN , GAO BO , LI YAN , HE YALING , ZHANG PINGXI , LI YUYANG , WANG JUE
Published: February 2024

Background
New prospect of cancer therapeutical management seems to be early diagnosis and prognosis prediction by microRNAs. The aim of our study is to explore the role of miR-525 in cancer diagnosis and prognosis through a systematic review and meta-analysis.
Methods
We conducted systematic search through PubMed, Embase, Web of Science, Scopus, Medline, Chinese National Knowledge Infrastructure (CNKI) and Wanfang databases up to November 25, 2023, regardless of language restrictions. Sensitivity, specificity, and diagnostic odds ratio (DOR) were extracted for diagnostic meta-analysis, while hazard ratio (HR) with 95% confidence interval (CI) for prognostic meta-analysis. Subgroup analysis and publication bias analysis were performed appropriately to investigate possible sources of heterogeneity.
Results
A total of 8 studies were included in the meta-analysis, of which 7 were used for diagnostic meta-analysis, covering 559 patients, and 3 were used for prognostic meta-analysis, covering 324 patients. The pooled sensitivity was 0.75 (95%CI = 0.70 to 0.79), specificity was 0.73 (95%CI = 0.68 to 0.78), DOR was 13.08 (95%CI = 4.18 ~ 40.91), and the area under the curve ratio (AUC) was 0.86 (95%CI = 0.83–0.89). Subgroup analysis showed that miR-525 may have good diagnostic ability in the early TNM stage of cancer. Prognostic meta-analysis showed that low miR-525 expression in patients was associated with preferable survival (HR = 0.17, 95%CI = 0.07–0.9).
Conclusions
Our findings suggest that miR-525 could be used as a potential biomarker for cancer patients. Low expression of miR-525 in cancers predicted a good prognosis.
Non‑motor Symptoms in Parkinson’s Disease and their clinical correlates: A prevalence study in Tertiary Care Center in Turkey
Authors: Onder Halil , Comoglu Selcuk
Published: February 2024

Objective
We aimed to investigate the involvement of non-motor symptoms (NMSs) in our consecutive Parkinson’s disease (PD) cohort systematically and reveal the possible clinical correlates.
Methods
We enrolled all consecutive PD subjects who applied to our movement disorders outpatient clinics between January/2023 and December/2023; and accepted to participate in the study. In addition to the evaluation of the demographic and clinical features, clinical scales, including the MDS-UPDRS, NMSS, and FOOGQ were performed.
Results
Overall, we enrolled 163 PD subjects with a mean age of 63.9 ± 10.4 (F/M = 27/136). The disease duration was 3.5 (20) y [median (range)]. The median score of the NMSS was 41 points. The NMSs burden levels were severe in 25.2%, and very severe in 25.2% of the subjects. The subitems with the highest scores were sleep/fatigue, mood/cognition, urinary, and miscellaneous. The correlation analyses between the clinical scales and the NMSS scores revealed positive correlations between the NMSS scores and the results of all the clinical scales including the MDS-UPDRS 1,2, 3, 4, and FOGQ. The analyses within the patient group with newly diagnosed PD also revealed also high NMSS scores.
Conclusion
We reported the first data regarding the NMS burden in PD subjects from Turkey. We found a high prevalence and severity of various domains of NMSs, most being sleep/fatigue, mood/cognition, urinary, and miscellaneous. More than half of the patients had an NMS burden of severe to very severe level. We found that NMSs were prevalent even in the subgroup with newly diagnosed patients.
Retrospective registry of patients with locally advanced/metastatic HR+/HER2− breast cancer treated in clinical practice in Andalusia.
Authors: Piudo Natalia Chavarría , López-Barajas Isabel Blancas , Flores Encarna González , Carrasco Fernando Henao , Álvarez Pilar López , Pancorbo David Morales , Casado Salvador Gámez , Garrido María de la Cabeza Lomas , García José Manuel Rodríguez , Guisado Antonia Martínez , Vega Adrián Sánchez , Borrego Manuel Ruiz
Published: February 2024

Background Limited data are available regarding the real-world effectiveness and safety of Cyclin Dependent Kinase 4/6 inhibitor (CDK4/6i) (palbociclib/ribociclib) just as a first-line treatment for patients with hormone receptor-positive/human epidermal growth factor receptor 2-negative (HR+/HER2‒) metastatic breast cancer (MBC). Objective To assess whether clinical or demographic characteristics limit access to first line CDK4/6i treatment in clinical practice in the Autonomous Community of Andalusia (Spain) between November 2017, and April 2020. In addition, effectiveness will be described in an exploratory analysis. Methods Physicians from 12 centers abstracted demographic and clinical characteristics, treatment and outcome data for women with HR+/HER2- MBC receiving and not receiving CDK4/6i in addition to hormonal treatment in the first-line setting a 3:1 proportion. Kaplan–Meier analysis estimated progression-free rates (PFRs) and survival rates (SRs). Results A total of 212 patients were included, of whom 175 (82.5%) were in the CDK4/6i treatment group and 37 (17.5%) were in the non-CDK4/6i treatment group (control group). CDK 4/6i treated patients were younger (p = 0.0011), and biopsies of the metastatic disease were done more frequently (p = 0.0454), with multiple metastases, and with differences in relation to the time of diagnosis of metastatic disease (p = 0.0304). The clinical benefit rate (CBR) was 82.3% in the CDK4/6i group and 67.8% in the control group. Median time to a progression event or death (PFS) was 20.4 months (95%CI 15.6–28) in the CDK4/6i group and 12.1 months (95%CI 7.9-not reached) in the control group. Conclusions Younger patients, biopsies of metastatic disease and with multiple metastases were more frequently treated with CDK4/6i.
Causal Relationships of 38 Risk Factors with Chronic Rhinosinusitis: A Mendelian Randomization Study
Authors: Jia Guobing , Guo Tao , Liu Lei , He Chengshi
Published: February 2024

Background
At present, the identification of risk factors associated with chronic rhinosinusitis (CRS) remains elusive. Our goal was to systematically investigate modifiable risk factors linked to CRS.
Methods
We conducted univariable Mendelian randomization (MR) based on genome-wide association studies (GWAS) to assess the causal relationships between 38 risk factors and CRS. The primary statistical analysis employed the inverse variance weighted (IVW) method, complemented by MR Egger and weighted median methods, in addition to multiple sensitivity analyses. Following this, we performed multivariable MR to consider the potential confounding effects of gastroesophageal reflux disease (GERD) and evaluate direct causal relationships between risk factors and CRS.
Results
Univariable MR results indicated that cigarettes per day, short sleep duration, overall health rating (OHR), hypertension, allergic rhinitis (AR), GERD, bronchial asthma (asthma), atopic dermatitis (AD), and rheumatoid arthritis (RA) were linked to an increased risk of CRS. Conversely, coffee intake, years of schooling, and apolipoprotein A-I were associated with a reduced risk of CRS. No other risk factors showed an association with CRS. When we adjusted for GERD using multivariable MR, the associations of OHR, RA, asthma, AD, and RA with CRS remained statistically significant. However, the previously observed effects of cigarettes per day, coffee intake, short sleep duration, years of schooling, apolipoprotein A-I, and hypertension were no longer apparent.
Conclusions
Our study suggests direct causal relationships between genetically predicted OHR, RA, asthma, AD, and increased risk of CRS. These findings will significantly contribute to advancing the exploration of CRS etiology.
Ancient DNA: a promising tool for understanding the evolutionary history of and human pressure on the highly endangered limpet Patella ferruginea
Authors: Espinosa Free , Haile James , Finlayson Stewart , Giles-Guzman Francisco , Finlayson Geraldine , Finlayson Clive , Fa Darren A.
Published: February 2024

The use of ancient DNA has been proven to be a powerful tool in phylogenetic and phylogeographic studies. Nonetheless, its application in the field of conservation has been limited. Moreover, marine mollusc shells are well preserved in the fossil record, providing invaluable information about the past. However, the extraction of DNA from ancient shells is challenging and has only recently been performed. In this context, Patella ferruginea has been the target of intense research due to its endangered status in the Mediterranean, with several genetic approaches involving the use of fresh soft tissue samples. In the present study, for the first time, DNA from modern and ancient shells was successfully extracted and sequenced for this species, indicating that the COI haplotypes were the same as those already sequenced in previous studies based on fresh soft tissue samples. The fact that DNA retrieved from the Middle Ages had been sequenced for this species prompted further research to compare genetic diversity between ancient and present populations to assess the impact of glacial periods or human harvesting in shaping the genetic diversity of this flagship species.
Epileptic seizure prediction based on Convolutional neural networks and optimization techniques
Authors: shanmugam Dineshkumar , NALLASAMY Viswanathan
Published: February 2024

According to the World Health Organization, fifty million individuals worldwide suffer from epilepsy, a neurological condition. While electroencephalography (EEG) is crucial for diagnosing epilepsy and monitoring the brain activity of epilepsy patients, it requires a specialist to examine all EEG recordings to find epileptic activity. The automatic recognition of epilepsy is becoming a crucial concern since manual detection is a tedious and time-consuming process that imposes a tremendous burden on neurologists. To overcome this issue, a seizure prediction technique is proposed based on convolutional neural networks (CNN) for feature extraction and an extreme gradient boosting (XGBoost) algorithm for seizure classification. CHB-MIT dataset is used for training and testing. Moreover , the proposed framework is optimized using a meta-heuristic algorithm called Aquila optimization for efficient and robust performance. The proposed method shows qualitative results achieving 99.02% of accuracy, 98.67% of specificity and 98.12% of sensitivity and the proposed method is compared with state-of-the-art methods.
Bearing fault detection method based on machine learning
Authors: Liu Yong , Xu Xiao-jie , Fu Xiang-jie
Published: February 2024

Traditional fault diagnosis for bearing usually requires a large amount of labeled data for training and deliberate selection of features and the diagnostic results are often too scattered to provide a thorough fault diagnosis procedure. To address these issues, we use data mining techniques to analyze the raw vibration signals of rolling bearings in various fault states under different operating conditions and construct labeled training and test datasets. By introducing the attention mechanism, we utilize convolutional neural networks and bidirectional long and short-term memory prediction models to diagnose deep fault categories and improve prediction accuracy from the perspective of machine learning. In addition, to intuitively describe the operating state of equipment bearings, we construct a visualization interface based on the prediction model. After example analysis, the model constructed in this paper has certain feasibility and effectiveness.
Experimentally-driven mathematical model to understand the effects of matrix deprivation in breast cancer metastasis
Authors: Maiti Sayoni , Rangarajan Annapoorni , Venkatesh K.
Published: February 2024

Normal epithelial cells receive proper signals for growth and survival from their attachment to the underlying extracellular matrix (ECM). They perceive detachment from the ECM as a stress and die. This cell death triggered by matrix detachment is known as anoikis. However, cancer cells are anoikis-resistant. Under normal (adherent) growth conditions, the serine-threonine protein kinase Akt plays a major role in cell proliferation and protein synthesis, maintaining an anabolic state in the cancer cell. In contrast, we showed that the stress due to matrix deprivation is sensed by yet another serine-threonine kinase AMP-activated protein kinase (AMPK) in response to a spike in intracellular calcium. We also showed the existence of an AMPK-Akt double-negative feedback loop in breast cancer cells that regulates their adaptation to matrix deprivation. We illustrated a metabolic switching from an anabolic to a catabolic state upon matrix-deprivation, which aids cancer cell stress-survival. In this study, we utilized these experimental data and developed a mathematical model to capture the pathophysiology of matrix-deprived state in breast cancer cells. To do so, we used the mathematical framework of an insulin-glucagon hormone signaling network that maintains the balance between anabolism and catabolism to maintain metabolic homeostasis. Using this model, we identified several proteins which are perturbed upon matrix deprivation in addition to AMPK and Akt. These include IRS, PI3K, GLUT1, IP3, DAG cAMP, PKA and PDE3. Molecular perturbations revealed that several feedback/crosstalks like PKC to IRS, S6K1 to IRS, cAMP to PKA, AMPK to Akt and DAG to PKC are crucial in maintaining the metabolic switching from an anabolic to catabolic state upon matrix deprivation. Upon removal of these feedback/crosstalks, metabolic switching is curbed. Thus, we have developed a unique mathematical framework to simulate the molecular interplay with metabolic adaptations critical for cancer metastasis.
Pelanggaran-Pelanggaran Teritorialitas di Gerai Mixue Urip Sumoharjo
Authors: Kusumastuti Maria Hesti , Nainggolan Freddy Marihot Rotua , Panjaitan Irwin
Published: February 2024

Title: Violations of Territoriality at Mixue Urip Sumoharjo Outlet

The food and beverage industry in Indonesia is growing rapidly. One of them is the Mixue outlet, which has mushroomed since 2020. In its development, the strategic location of the Mixue Urip Sumoharjo outlet has made this outlet relatively busy with visitors. This study aims to analyze territorial violations committed by visitors to the Mixue Urip Sumoharjo outlet in response to the narrow dimensions of the Mixue outlet space. The author made systematic observations and analyzed the spatial layout in the first stage. After that, they observed the dine-in area and divided the space into three categories: primary territory, secondary territory, and public territory. The next stage is to analyze and describe territorial violations through layout diagrams in each area. This study found that the dimensions of space influence the user's behavioral response to fulfilling personal space.