bluuebunny/crossref_metadata_2025 huggingface dataset:
Geometric Property of Off Resonance Error Robust Composite Pulse
Authors: Kukita Shingo , Kiya Haruki , Kondo Yasushi
Published: November 2021

The precision of quantum operations is affected by unavoidable systematic errors. A composite pulse (CP), which has been well investigated in nuclear magnetic resonance (NMR), is a technique that suppresses the influence of systematic errors by replacing a single operation with a sequence of operations. In NMR, there are two typical systematic errors, Pulse Length Error (PLE) and Off Resonance Error (ORE). Recently, it was found that PLE robust CPs have a clear geometric property. In this study, we show that ORE robust CPs also have a simple geometric property, which is associated with trajectories on the Bloch sphere of the corresponding operations. We discuss the geometric property of ORE robust CPs using two examples.
Continuous cropping of cut chrysanthemum reduces rhizospheric soil microbial populations, diversity and network complexity
Authors: Li Jun , Cheng Xiaoyu , Chen Wei , Zhang Hanjie , Chen Tianlang , Chu Guixin , Tao Rui
Published: November 2021

Continuous cropping of cut chrysanthemum causes soil degradation and chrysanthemum quality decline, but the biotic and abiotic mechanisms behind it remain unclear. This impedes our ability to assess the true effects of continuous cropping on agricultural soil functions and our ability to repair impaired soils. Here we examined the impact of different replanting years on microbial communities and enzyme activities in rhizosphere soil of cut chrysanthemum (Chrysanthemum morifolium). Our results showed that soil total nitrogen (TN) and organic carbon (SOC) contents were significantly lower in the soil with 12 years of continuous cropping (Y12) than that in the soil with 1 year of cropping (Y1). Compared with Y1, Y12 treatment decreased alkaline phosphatase and β -glucosidase by 12.1 and 24.4%, but increased the activities of soil urease and catalase by 98.2 and 34.8%, respectively. Soil bacterial populations in Y6 (continuous cropping for 6 years) and Y12 treatments decreased by 52.3 and 87.5% compared with that in Y1 treatment. Moreover, the bacterial α-diversity (Shannon index) significantly decreased by 37.3 and 57.6% over 6 and 12 years of continuous cropping, respectively. Long-term monoculture cropping shifted the bacterial community composition, with decreased abundances of dominant phyla such as Proteobacteria and Acidobacteria, but with an increase in the relative abundances of Actinobacteria and Chloroflexi, and Gemmatimonadetes. Moreover, Y6 and Y12 treatments harbored less microbial network complexity, lower bacterial taxa, and fewer linkages among bacterial taxa, relative to Y1. Soil pH, SOC, and TN were the main edaphic factors affecting soil bacterial community compositions and diversity. Overall, our results demonstrate that continuous cropping has a significant negative impact on soil microbial diversity and complexity.
Forming Limit Diagrams of Perforated St12 Steel Sheets
Authors: Sehhat M. Hossein , Mahdianikhotbesara Ali , Hadad Mohammadjafar
Published: November 2021

One of the unique characteristics of sheet metals is their formability, which is determined by the forming limit diagrams. These diagrams specify the maximum deformation limit before part’s failure. For several applications of metal sheets, they have to be in the perforated format. Existence of holes in the perforated sheets may adversely deteriorate the forming limit of metal sheets. In this study, the effect of perforated sheets’ hole size and hole layout on their formability are investigated. Several specimens of St12 steel with 0.6 mm thickness, different widths, two various hole sizes of 2 and 4 mm, and two layouts of triangular and square were prepared. The specimens were tested using Nakajima test (stretch with a hemispherical punch) to generate the forming limit diagrams. It was observed that both the diameter and layout of the punched holes have a significant effect on the formability of the perforated sheets. The perforated sheets with triangular hole layout showed higher forming limits due to their larger ligament ratios.
Mobility Aware Displacement Approximation Technique Based LSS and Privacy Preservation for Effective Data Routing in WSN with IoT Devices
Authors: Rajasekar S S , Palanisamy C. , Saranya K.
Published: November 2021

The Location based Service Selection (LSS) in WSN has been well studied. Towards effective LSS, an efficient Mobility Aware Displacement Approximation (MADA-LSS) based approach is presented in this article. The model monitors the mobility of mobile device and predict the possible location at different future time stamp. According to the future time stamp, the list of service locations are identified at different possible locations. According to the possible locations and service set, the method discover set of routes to reach each of the service points. For each of the route, the method estimates Data Arrival Rate (DAR), Data Claim Rate (DCR) and Data Rate Support Measure (DRSM) for both Access Point as well as route identified. Also, the method ranks the service points according to DRSM value and estimates the Trusted Handover Measure (THM) for the routes according to IoT (Internet of Things) devices of any route. By considering both THM and DSRM values an optimal service point as well as route has been selected to perform data transmission. Also, the privacy preservation is performed by using the same set of displacement approximation scheme which selects optimal encryption based on mobility parameters and time complexity and security of different encryption schemes. The proposed method improves the performance of LSS and secure routing.
A time-saving automobile assembly state monitoring system based on channel-pruned YOLOv4 algorithm
Authors: Daqi Jiang , Wang Hong
Published: November 2021

A time-saving automobile assembly state monitoring system in industrial environment is presented in this paper. The system only needs to input a video which contains the whole detected parts and manually label in the first frame. By finding the best point for tracking and tracking the point, the dataset can be automatically generated which saves time spent on manufacturing the dataset and makes the assembly state monitoring system easy to deploy into a practical industrial environment. The target detection algorithm uses the channel-pruned YOLOv4 neural network. The experimental result shows the algorithm balances speed and accuracy. Compared to original YOLOv4, our proposed method is two times faster and the mAP is nearly equal to it. It shows that the channel pruning process dynamically improves the speed of the forward propagation without sacrifice accuracy.
Investigation of Geometric Deformations of The Lumbar Disc During Axial Body Rotations
Authors: Xu Haoxiang , Wen Wangqiang , Zhang Zepei , Bai Jianqiang , Kou Bowen , Miao Jun
Published: November 2021

BackgroundQuantitative data on in vivo vertebral disc deformations are critical for enhancing our understanding of spinal pathology and improving the design of surgical materials. This study investigated in vivo lumbar intervertebral disc deformations during axial rotations under different load-bearing conditions.MethodsTwelve healthy subjects (7 males and 5 females) between the ages of 25 and 39 were recruited. Using a combination of a dual fluoroscopic imaging system (DFIS) and CT, the images of L3-5 segments scanned by CT were transformed into three-dimensional models, which matched the instantaneous images of the lumbar spine taken by a double fluorescent X-ray system during axial rotations to reproduce motions. Then, the kinematic data of the compression and shear deformations of the lumbar disc and the coupled bending of the vertebral body were obtained.ResultsRelative to the supine position, the average compression deformation caused by rotation is between +10% and -40%, and the shear deformation is between 17% and 50%. Under physiological weightbearing loads, different levels of lumbar discs exhibit similar deformation patterns, and the deformation patterns of left and right rotations are approximately symmetrical. The deformation patterns change significantly under a 10 kg load, with the exception of the L3-4 disc during the right rotation.ConclusionThe deformation of the lumbar disc was direction-specific and level-specific during axial rotations and was affected by extra weight. These data can provide new insights into the biomechanics of the lumbar spine and optimize the parameters of artificial lumbar spine devices.
Mps1 contributes to tamoxifen resistance in Breast Cancer through phosphorylation of ERα
Authors: Zhang Xuemiao , Gao Qi , Zong Yulong , Ma Xueping , Duan Cuijuan , liu Jialong , Huang Linfei , Feng Jiangyue , Wan Luming , Yang Xiaopan , Zhang Yanhong , Li Jingfei , Liu Muyi , Liu Jing , Zhong Hui , Tai Yanhong , Wei Congwen , Yang Xiaoli
Published: November 2021

Overexpression of mitotic kinase monopolar spindle 1 (Mps1) has been identified in many tumor types and targeting Mps1 for tumor therapy has been shown great promise in multiple preclinical cancer models. However, the role of Mps1 in tamoxifen resistance in breast cancer has never been reported. Here in this study, we report that Mps1 determined the sensitivity of breast cancer cells to tamoxifen treatment. Mps1 overexpression rendered breast cancer cells more resistant to tamoxifen, while Mps1 inhibitor or siMps1 oligos could overcome tamoxifen resistance. Mechanistically, Mps1 interacted with ERα and stimulated its transcriptional activity in kinase activity-dependent manner. Mps1 was responsible for ERα phosphorylation at S559 and T224 sites. Importantly, Mps1 failed to enhance the transcriptional activity of ERα in the presence of ERα S559A or T224A mutant. Collectively, our findings suggest that Mps1 contributes to tamoxifen resistance in breast cancer and is a potential therapeutic to overcome tamoxifen resistance in breast cancer.
Iron Hydride in the Earth's Inner Core
Authors: Yang Hua , Muir Joshua M.R. , Zhang Feiwu
Published: November 2021

Hydrogen is potentially a key light element in the Earth’s core. Determining the stability of iron hydride is essential for Earth's core mineralogy applications. We investigated the thermal stabilities and seismic properties of a range of Fe-H binary at core P-T conditions. It is concluded that H induces a phase change in the Fe lattice, converting it from hcp to fcc. With 1 wt.% H incorporation, the density of Fe decreases by 7.6%, both the compressional and shear wave velocities increase by 2.3% and 1.5%, respectively. The maximum H concentration is estimated to be ~0.57 wt.% to explain the density deficit of the inner core, which corresponds to 3 times as much as seawater, indicating that a large amount of water has been brought to the Earth's interior during its formation and a relatively low inner core temperature thus induced. H alongside other light elements are required to account for the geophysical observations of the Earth's inner core.
Time series assessment of biocompatibility of decellularized bovine tendon in rat anterior cruciate ligament reconstruction model up to 52 weeks
Authors: Itoh Masafumi , Imasu Hiroki , Takano Kazuya , Umezu Mitsuo , Okazaki Ken , Iwasaki Kiyotaka
Published: November 2021

There is an essential demand for the development of biocompatible graft substitute for knee anterior cruciate ligament reconstruction (ACLR). We aimed to investigate biocompatibility of decellularized bovine-derived tendon using rat knee ACLR model. The Sprague–Dawley rats with 12 weeks old were used. At weeks 1, 2, 4, 8, 16, 26, and 52 (each period, n = 6) after ACLR, rats using decellularized bovine tendon (group D, n = 42) and rats using autologous flexor digitorum longus tendon as a graft (group A, n = 42) were assessed for bone mineral density (BMD) of the peritibial bone tunnel, histology, and immunohistology. BMD increased over time in both groups until week 16 and then maintained without significant group differences. Initially, cellularity in group D was lower than in group A, but by weeks 4–8, both groups were comparable to native anterior cruciate ligament and were maintained until week 52. Initially, group A had more M1 macrophages, which represent inflammation, while group D had more M2 macrophages, which represent tissue regeneration. However, at most periods, the counts of M1 and M2 macrophages were comparable in both groups. This study revealed excellent biocompatibility of the decellularized tendon in the cross-species model.
Novel Global Interconnect structure with improved Elmore Delay Estimation for Low-Power Applications
Authors: Bhardwaj Himani , Jain Shruti , Sohal Harsh
Published: November 2021

With advancements in technology, size and speed have been the important facet in VLSI interconnects. Interconnects are known as the basic building block that provide a connection between two or more blocks and have scaling problems that an IC designer faces while designing. As scaling increases, the impact of interconnect in the VLSI circuits became even more important. It controls all the important electrical characteristics on the chip. With scale-down technology, interconnects not only become closer with each other but their dimensions also change which can directly impact the circuit parameters. Certain RC structures have already been defined to control these parameters but in this paper, authors have proposed a new interconnect structure with improved Elmore delay estimation to reduce delay and power consumption in lumped and distributed interconnect circuits using Pulse and Ramp inputs. Further, the proposed model is estimated and verified theoretically. The linear relationship of power consumption and delay for the RC structure has been observed. The proposed structure with improved Elmore delay estimation shows improvement in delay by 64.25% in lumped circuits and 68.75% in distributed circuits in comparison to existing Elmore delay calculations which help in increasing the overall speed of the interconnect circuit.
Numerical Modeling of Changes In Groundwater Storage And Nitrate Load in The Unconfined Aquifer Near a River Receiving Reclaimed Water
Authors: Jiang Ruixue , Han Dongmei , Song Xianfang , Zheng Fandong
Published: November 2021

Reclaimed water (RW) has been widely used as an alternative water resource to recharge rivers in mega-city Beijing. At the same time, the RW also recharges the ambient aquifers through riverbank filtration, and modifies the subsurface hydrodynamic system and hydrochemical characteristics. To assess the impact of RW recharge on the unconfined groundwater system, we conducted a 3D groundwater flow and solute transport model based on 10 years of sequenced groundwater monitoring data to analyze the changes of the groundwater table, Cl- loads, and NO3-N loads in the shallow aquifer after RW recharge to the river channel. The results show that the groundwater table around the river channel elevated by about 3~4 m quickly after RW recharge from Dec. 2007 to Dec. 2009, and then remained stable due to the continuous RW infiltration. However, the unconfined groundwater storage still declined overall from 2007 to 2014 due to groundwater exploitation. The storage began to recover after groundwater extraction reduction, rising from 3.76×108 m3 at the end of 2014 to 3.85×108 m3 at the end of 2017. Cl- concentrations varied from 5~75 mg/L before RW recharge to 50~130 mg/L in two years (2007–2009), and then remained stable. The zones of the unconfined groundwater quality-affected by RW infiltration increased from 11.7 km2 in 2008 to 26.7 km2 in 2017. Cl- loads of the unconfined groundwater increased from 1.66×104 t in 2008 to 3.8×103 t in 2017, while NO3-N loads decreased from 29.8 t in 2008 to 11.9 t in 2017 annually in the zones. We determined the maximum area of the unconfined groundwater quality affected by RW, and groundwater outside this area not affected by RW recharge keeps its original state. The RW recharge to the river channel in the study area is beneficial to increase the groundwater table and unconfined groundwater storage with lesser environmental impacts.
Clinical Outcomes of S2 Alar-Iliac (S2AI) Screw Technique in The Treatment of Severe Spinal Sagittal Imbalance: A Retrospective 2-Year Follow-Up Study
Authors: Zhao Yao , Xu Beiyu , Qi Longtao , Li Chunde , Yu Zhengrong , Sun Haolin , Wang Shijun
Published: November 2021

Background

The treatment of adult spinal deformity (ASD) remains a significant challenge, especially in elderly patients. This study aimed to evaluate the outcomes of the S2AI screw technique in the treatment of severe spinal sagittal imbalance with a minimum 2-year follow-up.
Methods

From January 2015 to December 2018, 23 patients with severe degenerative thoracolumbar kyphosis who underwent placement of S2AI screws for long segment fusion were retrospectively reviewed. Patients were divided into group A (no mechanical complications, 13 cases) and group B (with mechanical complications, 10 cases) according to the occurrence of mechanical complications at the last follow-up. Radiographic parameters were compared between groups preoperatively, 1 month postoperatively, and at the last follow-up. Risk factors for mechanical complications were analyzed.
Results

The incidence of mechanical complications was 43.5%, and the revision rate was 17.4%. At 1 month postoperatively, sagittal correction was better in group A than in group B (P<0.05). The lumbar lordosis (LL), pelvic incidence minus lumbar lordosis (PI-LL), T1 pelvic angle (TPA), and sagittal vertical axis (SVA) of both groups at the last follow-up were significantly different from corresponding values at 1 month postoperatively (P<0.05), and the sagittal correction was partially lost. Pearson correlation analysis revealed that the occurrence of mechanical complications was associated with sacral slope (SS), LL, PI-LL, and global alignment and proportion (GAP) score at 1 month postoperatively.
Conclusion

A high incidence of mechanical complications was observed in long-segment corrective surgery with the S2AI screw technique for severe spinal sagittal imbalance. Inadequate sagittal correction is a risk factor for the development of mechanical complications.
Survival Status and Predictors of Mortality Among Preterm Neonates in Southwest Ethiopia: A Retrospective Cohort Study
Authors: Toma Temesgen Mohammed , Merga Hailu , Dube Lamessa
Published: November 2021

Background: Prematurity is a global public health priority linked with high neonatal morbidity and mortality. There is limited evidence regarding preterm neonatal mortality and its predictors to inform programs and policies in Ethiopia. The aim of this study was therefore to assess survival status and predictors of mortality among preterm neonates admitted to the neonatal intensive care unit of Jimma University Medical Center. Methods: Facility-based retrospective cohort study was conducted from March 11 to April 20, 2020, among 505 randomly selected preterm neonates admitted to the Neonatal Intensive Care Unit (NICU) of Jimma University Medical Center (JUMC). Data were collected from medical records and registers using a structured data collection checklist. Data were entered into Epi-Data 3.1, exported to, and analyzed with STATA version 15. Kaplan Meir method and log-rank test were used to estimate survival time, and compare survival experience. Cox-regression analysis was fitted to identify predictors of time to death. The assumption of the proportional hazard model was checked using Schoenfeld residual test. Adjusted hazard ratio (AHR) with its 95% confidence interval (CI) and corresponding p-value <0.05 was set to declare statistical significance. Result: In this study, 127 (25.1%) neonates died with neonatal morality rate of 28.9 deaths per 1,000 neonate-days [95%CI: 24.33, 34.46]. About 103 (81.1%) deaths occurred during early neonatal period. Antenatal steroid use [AHR=0.55, 95%CI: 0.34, 0.90], obstetric complications [AHR=1.84, 95%CI: 1.20, 2.82], gestational age increment by week [AHR= 0.81, 95%CI: 0.75, 0.87], respiratory distress syndrome [AHR=1.52, 95%CI: 1.01, 2.29], neonatal sepsis [AHR=1.71, 95%CI: 1.18, 2.49], perinatal asphyxia [AHR=2.44, 95%CI: 1.33, 4.49], and receiving kangaroo-mother care [AHR=0.48, 95%CI: 0.30, 0.77] were predictors of preterm neonatal mortality.Conclusion: Preterm neonatal mortality rate was high. Most neonatal deaths occurred in the early neonatal period. Predictors of preterm neonatal mortality were antenatal steroid use, obstetric complications, gestational age increment by week, respiratory distress syndrome, neonatal sepsis, perinatal asphyxia, and receiving kangaroo-mother care. Hence, early detection and management of obstetric and neonatal complications, use of antenatal steroids, kangaroo-mother care, and ensuring a continuum of care should be strengthened to increase preterm neonatal survival.
Forecasting the Reaction of DNA Modifying Enzymes on DNA Nanostructures by Coarse Grained Model for Stimuli-Responsive Drug Delivery
Authors: Deng Yingnan , Tan Yuanhang , Zhang Linghao , Zhang Chunyi , Su Xin
Published: November 2021

The reactivity of DNA modifying enzymes on their natural nucleic acid substrates has been fully understood. However, their reactivity on self-assembled nanostructures of nucleic acid is complicated and unpredictable. Here, we employed the molecular dynamic simulation to forecast the reactivity of tumor biomarker enzymes on DNA nanotubes by coarse grained model. It is found that the enzyme accessibility and the potential energy of the reaction products co-determine the structural change of DNA nanotubes. The reactivity can be regulated by the position of enzyme recognition site. According to the simulation results, stimuli-responsive drug nanocarrier with superior sensitivity and selectivity was developed. Drug payloads released in cancer cells is 3.7~5.5-fold higher than that in normal cells. The DNA nanocarrier equipped with cancer-specific aptamer AS1411 is used to deliver doxorubicin (DOX) to tumor-bearing mice not only effectively inhibiting tumor growth but also protecting major organs from drug-caused damage. This work provides new insights into the enzymatic reactivity of DNA nanostructures enriching the library of DNA-based reactions and heralding broad applications in nanomedicine.
Filler Dependent Microstructural and Optical Properties of PVDF/PEG Blends Versus PVDF/GO Nanocomposites
Authors: Panda Maheswar
Published: November 2021

The micro-structural features and the optical properties of polymer blends (PB) of polyvinylidene fluoride (PVDF) base with polyethylene glycol (PEG) and polymer nanocomposites (PNC) of PVDF base with graphene oxide (GO) as fillers are compared. Different weight fractions of PVDF/PEG and PVDF/GO samples were prepared through solution casting followed by spin coating. The microstructure of PVDF/PEG and PVDF/GO shows formation of immiscible/compatible/ homogenous microstructures over different extents of loading of the filler components. UV-Visible spectrometry revealed an increase in absorbance with the amount of filler and the absorbance was found to be lesser and highly dispersive for the PB as compared to PNC, attributed to the heterogeneity/electrical conductivity of the respective fillers of the two systems. Spectroscopic ellipsometry was used to study the various optical constants (e.g. refractive index, extinction co-efficient, etc.) & their dispersion behavior over the visible range of wavelengths. The parameters show large variation as a function of component fillers due to the different extent of interaction of matrix/filler. The optimized parameters were obtained for the 20% PB & the 5% PNC samples respectively, suggesting PNC with nano fillers are always to be a better choice for developing them as materials suitable for various optical applications.
A New Prediction Model Integrated Serum Lipid Profile for Patients with Multiple Myeloma
Authors: Wang Huizhong , Chen Biyun , Shao Ruonan , Liu Wenjian , Xiong Lang , Li Li , Lu Yue
Published: November 2021

This study aimed to explore a predictive risk-stratification model combing clinical characteristics and lipid profiles in multiple myeloma (MM) patients. The data of 275 patients in Sun Yat-Sen University Cancer Center were retrospectively analyzed and randomly divided into the training (n = 138) and validation (n = 137) cohorts. Triglyceride, low-density lipoprotein (LDL), high-density lipoprotein (HDL), lactate dehydrogenase (LDH), Apolipoprotein B (Apo B) and Apo B / Apolipoprotein A1 (Apo A1) ratio were the prognostic factors identified through univariate and multivariate Cox analysis. A 6-prognostic factor model was constructed based on Lasso regression. Patients were divided into low- and high-risk groups and the former group showed longer overall survival (OS) time (p<0.05). The area under the curve (AUC) of the risk score model for 5-and 10-year OS were 0.756 [95% CI: 0.661-0.850] and 0.940 [95% CI: 0.883-0.997], which exhibited better accuracy than International Staging System (ISS) and Durie and Salmon (DS) stage. The nomogram integrating ISS stage and risk score increased the prediction accuracy. The model can be used to help monitor the metabolic state and to establish primary prevention strategies to identify new therapeutic targets.
The dopamine transporter counter-transports potassium to increase the uptake of dopamine
Authors: Loland Claus , Schmidt Solveig , Malle Mette , Nielsen Anne , Bohr Søren , Pugh Ciara , Nielsen Jeppe , Poulsen Ida , Rand Kasper , Hatzakis Nikos
Published: November 2021

The dopamine transporter (DAT) facilitates dopamine reuptake from the extracellular space, and thereby terminates neurotransmission and refills cellular stores of dopamine. DAT belongs to the neurotransmitter:sodium symporter (NSS) family, which includes similar transporters for serotonin, norepinephrine, and GABA. A hallmark of NSS proteins is their ability to utilize the energy stored in the inward-directed Na+ gradient to drive the uphill transport of substrate. Decades ago, it was shown that the serotonin transporter also counter-transports K+, but investigations of K+-coupled transport in other NSSs have been inconclusive. Here, we show that the Drosophila dopamine transporter (dDAT) counter-transports K+. We found that ligand binding to both dDAT and human DAT is inhibited by K+ and that the conformational dynamics of dDAT in K+ is highly divergent from both the apo- and Na+-bound conformations. Furthermore, we found that K+ increased dopamine uptake by purified dDAT reconstituted in liposomes, and we visualized, in real-time, Na+ and K+ fluxes in single proteoliposomes using fluorescent ion indicators. Our results expand on the fundamentals of dopamine transport and prompt a reevaluation of the impact of K+ on other NSSs, including whether K+ counter-transport is a common mechanism for this pharmacologically important protein family.
Correlation of regional cerebral blood flow with brain structural changes in mild cognitive impairment and Alzheimer's disease
Authors: Nabizadeh Fardin , Rostami Mohammad Reza , Balabandian Mohammad , Mehrabi Soraya , Sedighi Mohsen
Published: November 2021

Objectives

Brain atrophy and structural changes due to aging contribute strongly in the pathophysiology of mild cognitive impairment (MCI) and Alzheimer’s Disease (AD). Regional cerebral blood flow (CBF) impairment is believed to be one of the initial changes in the AD continuum. In this study, we investigated the association between CBF and brain structural changes associated with aging and neurodegeneration.
Methods

Data from three groups of participants including 39 control normal (CN), 82 MCI, and 28 AD subjects were downloaded from the Alzheimer’s disease Neuroimaging Initiative (ADNI). Magnetic resonance images (MRI) of participants were automatically segmented by FreeSurfer V 7.0 software and arterial spin labeling (ASL) MRI was applied to measure CBF and investigate effect of aging and structural changes on CBF in experimental groups. One way ANOVA and Pearson correlation coefficient were used to compare data and find correlation between CBF and structural changes in the brain.
Results

AD patients had significantly lower Mini-Mental State Examination (MMSE) score (p=0.001) and more APOE-ε4 carriers (p=0.001) as compared to the MCI and CN groups. Our findings revealed a wide spread significant correlation between the CBF and structural changes, including cortical volume, subcortical volume, surface area, and thickness in all participants, particularly AD patients after adjusting for age, sex, and APOE genotyping status.
Conclusion

Several structural abnormalities correlated with declined CBF and could potentially be used as imaging biological correlates biomarkers to predict early onset of AD, regardless of Aβ or tau accumulation.
Effective of Fusion in the Treatment of Lumbar Spinal Stenosis：A Systematic Review Andmeta-Analysis
Authors: Yang Yang , Tang Shi-tian , Chen Qian , chen fang
Published: November 2021

Objective: The debate on efficacy of fusion added to decompression for lumbar spinal stenosis (LSS) is ongoing. The primary objective of this systematic review is to compare the outcome after decompression with and without fusion in patients with lumbar spinal stenosis .Methods: A literature search was performed in the Web of Science, EMBASE, Pubmed,and Cochrane Libraryfrom January 1990 to May 2021.The information of screened studies included clinical outcomes, and secondary measures, then data synthesis and meta-analysis were progressed.Data analysis was conducted using the Review Manager 5.0 software.Results: 17 studies were included in the analysis involving 2947 patients in total. In the majority of studies, including seven RCTs and ten observational studies. The pooled data revealed that fusion was associated with signifificantly higher rates of back pain scores when compared with decompression alone in RCT subgroup(SMD=-0.42, 95% CI (–0.60, -0.23), Z=4.31 P<0.0001).However, fusion signifificantly increased the intraoperative blood loss, operative time and hospital stay. Both techniques had similar leg Pain scores , EQ-5D, walking ability，ODI，major complication,clinical satisfactions and reoperation rate.Conclusions: Our studies showed that the additional fusion in the management of LSS yielded no clinical improvements over decompression alone within a 1-year follow-up period. We suggested that the least invasive and least costly procedure, being decompression alone, is preferred in patients with degenerative lumbar spinal stenosis. The appropriate surgical protocol for LSS should be discussed further.
An Efficient Hybrid Grey Wolf Optimization Based KELM Approach for Prediction of the Discharge Coefficient of Submerged Radial Gates
Authors: Roushangar Kiyoumars , Shahnazi Saman , Sadaghiani Arman Alirezazadeh
Published: November 2021

Radial gates are widely used hydraulic structures for flow control in irrigation canals. Accurately prediction of discharge coefficient through radial gates is considered as a challenging hydraulic subject, particularly under highly submerged flow conditions. Incurring the advantages of Kernel-depend Extreme Learning Machine (KELM), this study offers a Grey Wolf Optimization-based KELM (GWO-KELM) for effective prediction of discharge coefficient through submerged radial gates. Additionally, Support Vector Machine (SVM), and Gaussian Process Regression (GPR) methods are also presented for comparative purposes. To build prediction models using GWO-KELM, GPR, and SVM an extensive experimental database was established, consisting of 2125 data samples gathered by the US Bureau of Reclamation. From simulation results, it is observed that the proposed GWO-KELM approach with input parameters of the ratio of the downstream flow depth to the gate opening (y3/w) and submergence ratio (y1-y3/w) provides the best performance with the correlation coefficient (R) of 0.983, the Determination Coefficient (DC) of 0.966 and the Root Mean Squared Error (RMSE) of 0.027. Furthermore, the obtained results showed that the employed kernel-depend methods are capable of a statistically predicting the discharge coefficient under varied submergence conditions with satisfactory level of accuracy.
Performance Evaluation of Machine Learning Models with Ensemble Learning approach in Classification of Water Quality Indices Based on Different Subset of Features
Authors: GARABAGHI FARID HASSANBAKI , Benzer Semra , Benzer Recep
Published: November 2021

Since fresh water resources in form of groundwaters which are the most available water resources for human consumption are extremely limited and due to uncontrolled human activities are prone to contamination, it’s of a great importance to constantly monitor the quality of the ground fresh water resources to provide a sustainable drinking water for people as well as protecting the ecosystem. One tool for modeling the water quality of a basin is Water Quality Index (WQI). However, calculating WQI is complicated and time- consuming, therefore, today, scientists are being inclined to propose simpler ways for modeling the quality of the water resources such as machine learning algorithms. In this study the performance of four machine learning algorithms with ensemble learning approach were evaluated to propose a classification model (classifier) with highest performance. Moreover, to identify the most important water quality parameters in the classification process, three feature selection methods with machine learning approach were applied. As a result, among four classifiers, XGBoost showed outstanding performance, with the accuracy of 96.9696% when all the parameters of interest were involved in the classification process. However, in order to make the model cost-effective it is suggested to conduct the classification with optimum parameters which in this case, for the dataset which was used in this study XGBoost classifier is suggested as the best classifier with the maximum accuracy of 95.606% with 10-Fold Cross Validation when seven parameters which were identified by Backward Feature Elimination Feature selector were involved in the classification process.
Treatment outcome and its predictors among diabetic patients attending at selected hospitals of southern ethiopia.
Authors: Beyene Bereket , Hoyiso Dawit , Woldu Kinfe
Published: November 2021

Background: Diabetes is one of the largest health emergencies of the 21st century. The World Health Organization (WHO) estimates that globally, hyperglycaemia is the third highest risk factor for premature mortality, after high blood pressure and tobacco use. It is an important cause of blindness, kidney failure, lower limb amputation and other long-term consequences that impact significantly on quality of life. It result peoples in a disease, death and increase a health care expenditure.Objectives: To determine treatment outcome of Diabetes mellitus and its predictors among patients attending diabetes treatments at selected hospitals of southern Ethiopia, 2021.Methods: All diabetic patients who attended selected hospitals of southern Ethiopia were a source population. Institution based cross-sectional study design was conducted at selected hospitals of southern Ethiopia. Patient’s data was collected using pretested questionnaire. After cleaning and checking for errors, the data was entered in to Epi-data to minimize error then exported to SPSS for analysis. Descriptive findings were presented by tables and charts. The outcome variable was analyzed by using logistic regression model to identify predictors after assumptions of regression analysis had checked. All the independent variables with p<0.25 was used as a candidate for multivariate analysis. Then the level of significance will be set at p<0.05 and AOR with 95% CL was done as the final model.Result: From the total sample; 277 (65.6%) were found to be good treatment outcome. The number of medication taken AOR 95%CI; 0.924 (0.869, 0.983), presence of complication AOR 95%CI; 0.425 (0.217, .832), increased fasting blood glucose AOR 95%CI; 0.080 (0.034, 0.188) were found to be independent predictors. Since the magnitude of treatment outcome found to be low, provision of health information about the adhering to prescribed medication and monitoring fasting blood glucose level will bring good clinical outcome.
Prognostic Nomogram in Children and Adolescents With Central Nervous System Germ Cell Tumors
Authors: Jia Zetian , Yan Yaqi , Wang Jiuxin , Yang He , Liu Shuo , Han Chengxi , Hu Yuhua
Published: November 2021

Background: The prognostic risk factors for primary central nervous system (CNS) germ cell tumors (GCTs) in children and adolescents remain controversial. This study aimed to develop and validate a nomogram that predicts 5-and 10-year survival rates for CNS GCTs in children and adolescents.Methods: Pediatric with intracranial GCTs in the Surveillance, Epidemiology, and End Results (SEER) database from 2000 to 2018 were analyzed. All GCTs children were randomly divided into the development group (70%) and the validation group (30%). The least absolute shrinkage and selection operator (LASSO) was used to screen the characteristic variables, and the 5- and 10-year survival probability nomogram was constructed. The accuracy of the nomogram was evaluated by consistency index (C-index), calibration plot, receiver operating characteristic curve (ROC), decision curve analysis (DCA) and survival curve.Results: We identified 819 cases of CNS GCTs in children. Three variables (histology, site and size) were selected by lasso regression to construct the nomogram. The C-index of the development group and verification group is 0.744 and 0.759. According to the time points of 5 and 10 years, the area under the curve of the development group is 0.753 and 0.696, and the verification set is 0.787 and 0.718. The results show that the prognostic nomogram developed by us has good accuracy.Conclusions: This is the first prognostic nomogram of CNS GCTs in children and adolescents. It can effectively predict the 5- and 10-year survival probability of children. It provides a useful prediction tool for clinicians.
Association Rule Mining Algorithms for Big Data using RDD-ECLAT Algorithms
Authors: Martha  , Vankdothu Ramdas , Abdul Hameed Mohd , Gangula Rekha
Published: November 2021

The revolution in technology for storing and processing big data leads to data intensive computing as a new paradigm. To find the valuable and precise big data knowledge, efficient and scalable data mining techniques are required. In data mining, different techniques are applied depending on the kind of knowledge to be mined. Association rules are generated from the frequent itemsets computed by frequent itemset mining (FIM) algorithms. The problem of designing scalable and efficient frequent itemset mining algorithms on the Spark RDD framework. The research done in this thesis aims to improve the performance (in terms of execution time) of the existing Spark-based frequent itemset mining algorithms and efficiently re-design other frequent itemset mining algorithms on Spark. The particular problem of interest is re-designing the Eclat algorithm in the distributed computing environment of the Spark. The paper proposes and implements a parallel Eclat algorithm using the Spark RDD architecture, dubbed RDD-Eclat. EclatV1 is the earliest version, followed by EclatV2, EclatV3, EclatV4, and EclatV5. Each version is the consequence of a different technique and heuristic being applied to the preceding variant. Following EclatV1, the filtered transaction technique is used, followed by heuristics for equivalence class partitioning in EclatV4 and EclatV5. EclatV2 and EclatV3 are slightly different algorithmically, as are EclatV4 and EclatV5. Experiments on synthetic and real-world datasets.
Synoptic Climatology of Weather Parameters Associated With Tropical Cyclone Events In The Coastal Areas of Bay of Bengal
Authors: Badhan Mehnaz Abbasi , Farukh Murad Ahmed , Hossen Md. Al- Mussabbir , I Abu Reza Md. Towfiqul
Published: November 2021

Tropical cyclones (TCs) are the most devastating weather phenomena that trigger massive loss of property and life in the coastal areas of the Bay of Bengal (BoB). Scientific understanding of TCs occurrence can aid policy-makers and residents in coastal areas to take necessary actions and appropriate planning in advance. In this study, we aimed to examine the possible linkage of weather parameters with deadly 22 TCs events in the BoB from 1975 to 2014 using principal component analysis, K-mean clustering and General circulation model (GCMs). Results showed that among 22 TCs, cluster 1 belongs to 12 TCs which occurred under the same atmospheric situation when the sea level pressure (SLP) was below 990hPa, and the temperature ranged from 300C to 390C. A deep negative anomaly of SLP and temperature was observed up to 500hPa levels. In contrast, a negative depression was found at 300hPa geopotential height (GPH) over the study area. Cluster 2 consisted of 9 TCs when SLP was below 1000hPa, and the average temperature was 33.50C. A strong negative anomaly was noticed when surface level up to 500 hPa GPH, but dramatically this depression was completely absent at 300hPa geopotential height over the BoB and entire coastal region. Cluster 3 contained only 1 TCs when the atmospheric circumstance was completely diverse, and the SLP was above 1000hPa. The results of the GCM model revealed that the SLP was lower, and the temperature was higher over BoB compared to the North Indian Ocean. We identified the larger depression of SLP and unpredictable temperature anomalies at the upper atmosphere that can trigger an enormous unpredictability throughout the atmospheric level, leading to severe TCs. The outcomes of this study can improve our understanding of weather variables in the upper atmospheric column for forecasting the TCs system more accurately in the future.
Identifying and handling unbalanced baseline characteristics in a non-randomized, controlled, multicenter social care nurse intervention study for patients in advanced stages of cancer
Authors: Schindel Daniel
Published: November 2021

Purpose: Given the psychosocial burdens patients in advanced stages of cancer face, innovative care concepts are needed. At the same time, such vulnerable patient groups are difficult to reach for participation in intervention studies and randomized patient inclusion may not be feasible. This article aims to identify systematic biases respectively selection effects occurring during the recruitment phase and to discuss their potential causes based on a non-randomized, multicenter intervention study with patients in advanced stages of cancer.Methods: Patients diagnosed with at least one of 16 predefined cancers were recruited at four hospitals in three German cities. The effect of social care nurses’ continuous involvement in acute oncology wards was measured by health-related quality of life (EORTC QLQ-C30) and other patient-reported outcomes. Absolute standardized mean difference was calculated as a standardized effect size to test baseline characteristics balance between the intervention and control groups.Results: The study enrolled 362 patients, 150 in the intervention and 212 in the control group. Except for gender, both groups differed in relevant socio-demographic characteristics, e.g. regarding age and educational background. With respect to the distribution of diagnoses, the intervention group showed a higher symptom burden than the control group. Moreover, the control group reported better quality of life at baseline compared to the intervention group (52.6 (SD 21.7); 47.8 points (SD 22.0), ASMD=0.218, p=0.044). Conclusion: Overall, the intervention group showed more social and health vulnerability than the control group. Among other factors, the wide range of diagnoses included and structural variation between the recruiting clinics increased the risk for bias. We recommend a close, continuous monitoring of relevant social and health-related characteristics during the recruitment phase as well as the use of appropriate statistical analysis strategies for adjustment, such as propensity score methods. Trial registration: German Clinical Trials Register (DRKS-ID: DRKS00013640); registered on 29th December 2017.
Identification of Therapeutic Targets and Prognostic Biomarkers of IGF2BPs in the Lung Cancer Microenvironment
Authors: Wang Xuanzheng , Kong Weina , Guo Fan , Sha Ruocheng , Zhao Gang , Qiao Wenbin , Xu Keming , Feng Yangchun , Sun Wei , Ma Xiumin
Published: November 2021

Background: Lung cancer is one of the most common malignances with an ever-increasing incidence and high mortality. The insulin-like growth factor 2 mRNA-binding proteins (IGF2BPs) as RNA-binding proteins play an important role in messenger RNA (mRNA) regulation during tumor development. Even so, the expression and prognostic values of IGF2BPs in lung cancer have not been clarified.Main methods: To address this issue, the study investigated the roles of IGF2BPs in the prognosis of lung cancer by using public databases and quantitative real-time PCR (Q-PCR).Results: The transcriptional levels of IGF2BP1/2/3 in lung cancer tissues were significantly elevated, associating with pathological stages and poor prognosis of overall survival (OS) and progression-free survival (FP) in lung cancer patients. A high mutation rate of IGF2BPs (24%) was also observed of patients with lung cancer. The functions of differentially expressed IGF2BPs are primarily related to the spliceosome, hippo signaling pathway and transcriptional misregulation in cancer. Finally, we found significant correlations among the expression of IGF2BPs and the infiltration of six types of immune cells (B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells).Conclusions: The results indicated that high mRNA expression of IGF2BP1/2/3 was found in lung cancer tissues, significantly associating with tumor grades and poor prognosis of OS and FP. Our results may provide insights for the selection of therapeutic targets and prognostic biomarkers for lung cancer patients.
In-hospital Cardiac Arrest in Patients With Heart Failure: Long- and Short-term Survival and Trends
Authors: Aune Emma , McMurray John , Lundgren Peter , Sattar Naveed , Israelsson Johan , Nordberg Per , Herlitz Johan , Rawshani Araz
Published: November 2021

In patients with heart failure (HF) who suffered in-hospital cardiac arrest (IHCA), little is known about the characteristics, survival and neurological outcome. We used the Swedish Registry of Cardiopulmonary Resuscitation to study this, including patients aged ≥18 years suffering IHCA (2008-2019), categorised as HF alone, HF with acute myocardial infarction (AMI), AMI alone, or other. Odds ratios (OR) for 30-day survival, trends in 30-day survival, and the implication of HF phenotype was studied. 6378 patients had HF alone, 2111 had HF with AMI, 4210 had AMI alone. Crude 5-year survival was 9.6% for HF alone, 12.9% for HF with AMI and 34.6% for AMI alone. The 5-year survival was 7.9% for patients with HF and left ventricular ejection fraction (LVEF) ≥50%, 15.4% for LVEF <40% and 12.3% for LVEF 40-49%. Compared with AMI alone, adjusted OR (95% CI) for 30-day survival was 0.66 (0.60-0.74) for HF alone, and 0.49 (0.43-0.57) for HF with AMI. OR for 30-day survival in 2017-2019 compared with 2008-2010 were 1.55 (1.24-1.93) for AMI alone, 1.37 (1.00-1.87) for HF with AMI and 1.30 (1.07-1.58) for HF alone. Survivors with HF had good neurological outcome in 92% of cases.