bluuebunny/crossref_metadata_2025 huggingface dataset:
Carbon Decorated Ni(OH)2 Nanoflakes on Ni Foam as a Binder-Free Cathode for Lithium–Oxygen Batteries
Authors: Wang Yu , Zhu Xingbao , Qin Jin , Wang Zhihong , Wu Yuanguo , Man Zining , Yuan Chengyin , Lü Zhe
Published: March 2021

Herein, we report a binder-free, low-cost and high performance cathode for lithium-oxygen batteries based on carbon black BP2000 decorated Ni(OH)2 nanoflakes array on Ni foam. The Ni(OH)2 nanoflakes array is fabricated by hydrothermal treatment of Ni foam in acidic medium without nickel salt. The highly organized structure of Ni(OH)2 nanoflakes array provides a more uniform distribution of catalysts and discharge products, resulting in high capacity with a relatively stable cycling voltage profile. The cathode outputs a discharge capacity as high as 12400 mAh gcarbon
−1 at 160 mA gcarbon
−1, which is 244% higher than that of BP2000 decorated Ni foam electrode without Ni(OH)2 nanoflakes array. The cathode can sustain 100 cycles under a capacity limitation of 320 mAh gcarbon
−1 with high energy efficiency (∼67%). Our work points out the key issues and suggests an effective method for the surface modification technology.
Transthyretin contributes to insulin resistance and diminishes exercise-induced insulin sensitivity in obese mice by inhibiting AMPK activity in skeletal muscle
Authors: He Yingzi , Qiu Ruojun , Wu Beibei , Gui Weiwei , Lin Xihua , Li Hong , Zheng Fenping
Published: March 2021

Exercise improves obesity-induced insulin resistance via mechanisms that remain unclear. The novel findings of the study are that circulating TTR (a hepatokine) level is decreased by exercise, and the elevated circulating TTR, as was the elevated transthyretin internalization mediated by Grp78, counteracts the exercise-induced insulin sensitivity by downregulating AMPK activity in skeletal muscle of obese mice. These data suggest that TTR suppression might be an adaptive response to exercise through the crosstalk between liver and muscle.
Appendiceal Diverticulitis in a Young Female Diagnosed on Pathology after Laparoscopic Appendectomy for Acute Appendicitis
Authors: Onafowokan Oluwatobi O. , Khairat Aboubakr , Bonatti Hugo J. R.
Published: March 2021

Background. Appendiceal diverticulitis is a rare cause of inflammation of the appendix, which may mimic acute appendicitis. Its diagnosis is often delayed, and its occurrence carries an increased risk of significant complications, such as perforation. Case Presentation. A 23-year-old woman presented with sudden onset, severe, right lower quadrant abdominal pain and nausea. Her WBC was elevated, and abdominal CT showed findings indicative of acute appendicitis with a 13 mm fluid-filled appendix and local stranding. During laparoscopic appendectomy, significant inflammation was found around the appendix with some mucous material around the tip. The appendix base was not involved, and an endoloop was used to secure the stump. No other intra-abdominal abnormalities were observed. The patient recovered uneventfully. Pathology showed no classic appendicitis but appendiceal diverticulitis with signs of perforation. Discussion. Appendiceal diverticulitis is a rare condition which cannot be distinguished from acute appendicits clinically and on imaging. Diagnosis may be established based on pathology such as in our case. Appendectomy is indicated in appendiceal diverticulitis, and an appendix diverticulum is incidentally found during surgery or other investigations. This is due to the increased risk of perforation and the reported development of malignant tumors, including the appendix carcinoid.
Correlation Coefficient and Entropy Measures Based on Complex Dual Type-2 Hesitant Fuzzy Sets and Their Applications
Authors: Mahmood Tahir , Ali Zeeshan , Garg Harish , Zedam Lemnaouar , Chinram Ronnason
Published: March 2021

The theory of complex dual type-2 hesitant fuzzy sets (CDT-2HFSs) is a blend of two different modifications of fuzzy sets (FSs), called complex fuzzy sets (CFSs) and dual type-2 hesitant fuzzy sets (DT-2HFSs). CDT-2HFS is a proficient technique to cope with unpredictable and awkward information in realistic decision problems. CDT-2HFS is composed of the grade of truth and the grade of falsity, and the grade of truth (also for grade of falsity) contains the grade of primary and secondary parts in the form of polar coordinates with the condition that the sum of the maximum of the real part (also for the imaginary part) of the primary grade (also for the secondary grade) cannot exceed the unit interval [0, 1]. The aims of this manuscript are to discover the novel approach of CDT-2HFS and its operational laws. These operational laws are also justified with the help of an example. Additionally, based on a novel CDT-2HFS, we explored the correlation coefficient (CC) and entropy measures (EMs), and their special cases are also discussed. TOPSIS method based on CDT-2HFS is also explored. Then, we applied our explored measures based on CDT-2HFSs in the environment of the TOPSIS method, medical diagnosis, pattern recognition, and clustering algorithm to cope with the awkward and complicated information in realistic decision issues. Finally, some numerical examples are given to examine the proficiency and validity of the explored measures. Comparative analysis, advantages, and graphical interpretation of the explored measures with some other existing measures are also discussed.
Diet Quality Indices and Their Correlation with Glycemic Status and Lipid Profile in Patients with Type 2 Diabetes
Authors: Ziaee Roxaneh Sadat , Keshani Parisa , Salehi Moosa , Ghaem Haleh
Published: March 2021

Background. The study aimed to determine the correlation between different diet quality indices and glycemic status and lipid profile in patients with diabetes. Methods. This study was carried out on 235 patients with type 2 diabetes referred to Martyr Motahari Diabetes Clinic of Shiraz city so as to investigate the relationship between glycemic status and lipid profile and the diet quality using Healthy Eating Index (HEI-2010), phytochemical index (PI), and Diet Quality Index-International (DQI_I). Results. A positive correlation was indicated between the serum levels of LDL-C and HEI-2010 scores

p
=
0.026

. Furthermore, there was a positive correlation between the patients’ age and scores of PI

p
=
0.006

and between PI and DQI_I

p
<
0.001

. There was no significant relationship between the scores for all three indicators and biochemical parameters. Conclusion. The results of this study indicated that there was a significant correlation between the serum LDL-C levels and the HEI-2010 scores. Moreover, the age of the patients had a direct correlation with the PI scores.
Premature Ventricular Contractions’ Detection Based on Active Learning
Authors: Zhang Xianrong , Shafiq Muhammad , Zheng Guijun , Wan Junping , Sun Zhe
Published: March 2021

Premature ventricular contractions (PVCs) are one of the most common cardiovascular diseases with high risk to a large population of patients. It has been shown that supervised learning algorithms can detect PVCs from beat-level ECG data. However, a huge human effort is needed in order to achieve an accurate detection rate. A convolutional autoencoder was trained in this work in an unsupervised fashion to extract features automatically with zero prior specialized knowledge. Random forest was adopted as a supervised algorithm trained on the features generated by the autoencoder. Various active learning selection strategies, uncertainty-based and diversity-based, were studied on top of the random forest. In each iteration of active learning, the training data are updated with newly selected samples and fed into the classifier. The performance on an independent validation set is recorded in each iteration. As a result, among the different uncertainty sampling strategies, the least confidence score shows a better F1 score of 0.85 than other methods. In between the two diversity-based strategies, the representative clustering sample had the best F1 score than the k-center-greedy algorithm. By comparing the performance of different active learning methods trained on half of the original data size with the same classifier trained on the full set, the F1 score of least confidence is still better than the full set. This study demonstrates that active learning could help reduce human annotation effort by achieving the same level of performance as the classifier trained on the fully annotated training data.
Pancreatic Metastasis of Renal Cell Carcinoma: A Surgical Indication for a Disseminated Disease
Authors: Letaief Ksontini Feryel , Khrouf Salim , Kacem Selma , Haddad Anis , Magherbi Houcine , Chaker Youssef , Ayadi Mouna , Ben Safta Zoubair
Published: March 2021

Pancreatic metastasis (PM) of renal cancer is a rare condition. It is characterized by a long period after initial nephrectomy and a favorable prognosis compared to other pancreatic malignancies. Its diagnosis may confuse clinicians if the medical history is not known. In the era of targeted therapies for metastatic renal carcinoma, surgery stands as the best treatment option for PM of renal cancer. We report the case of a woman who underwent successfully left splenopancreatectomy for corporeal PM of renal cancer treated seven years ago. This case underlines the necessity of long-term follow-up of patients treated for kidney cancer.
Robust Kalman Filter-Based Dynamic State Estimation of Natural Gas Pipeline Networks
Authors: Chen Liang , Jin Peng , Yang Jing , Li Yang , Song Yi
Published: March 2021

To obtain the accurate transient states of the big scale natural gas pipeline networks under the bad data and non-zero mean noises conditions, a robust Kalman filter-based dynamic state estimation method is proposed using the linearized gas pipeline transient flow equations in this paper. Firstly, the dynamic state estimation model is built. Since the gas pipeline transient flow equations are less than the states, the boundary conditions are used as supplementary constraints to predict the transient states. To increase the measurement redundancy, the zero mass flow rate constraints at the sink nodes are taken as virtual measurements. Secondly, to ensure the stability under bad data condition, the robust Kalman filter algorithm is proposed by introducing a time-varying scalar matrix to regulate the measurement error variances correctly according to the innovation vector at every time step. At last, the proposed method is applied to a 30-node gas pipeline network in several kinds of measurement conditions. The simulation shows that the proposed robust dynamic state estimation can decrease the effects of bad data and achieve better estimating results.
Perforated Meckel’s Diverticulitis in a Patient with Unknown Intestinal Malrotation: Clinical Pitfall
Authors: Burgard Marie , Cherbanyk Floryn , Pugin François , Egger Bernhard
Published: March 2021

Symptomatic Meckel’s diverticulum is rare in adults. The most frequent complications are intestinal obstruction and diverticulitis. Diagnosis of Meckel’s diverticulitis can be challenging due to nonspecific clinical manifestation of pain in the right lower abdominal quadrant, mimicking acute appendicitis. If associated with congenital malformation, such as intestinal malrotation, the anomalous anatomy makes the diagnosis even more challenging. In such cases, radiological imaging is essential to guide further management. We present a case of Meckel’s diverticulitis in which physicians were initially misguided because of the atypical clinical presentation. Yet, anamnestic details directed to a potential underlying malformation, leading to supplementary radiological examination and the final diagnosis.
An Ensemble Model of Wind Speed Forecasting Based on Variational Mode Decomposition and Bare-Bones Fireworks Algorithm
Authors: Quan Jicheng , Shang Li
Published: March 2021

Wind energy is one of the fastest growing renewable energy sources. Wind speed forecasting is essential to enhance the utilization of wind energy. Various prediction models have been developed to improve the prediction accuracy of wind speed. However, wind speed time series has nonlinearity, fluctuation, and intermittence, which makes the prediction difficult. Existing prediction models ignore data decomposition and feature reduction and suffer from the deficiency of individual models. This paper proposes a novel ensemble prediction model, which integrates data preprocessing, feature selection, parameter optimization, three intelligent prediction models, and an ensemble strategy. To improve prediction performance, a highly efficient optimization algorithm is applied to determine the individual models’ optimal parameters. Furthermore, partial least square regression is used to calculate combination weight. Additionally, two 10 min datasets from the National Renewable Energy Laboratory (NREL) are employed for one-step-ahead prediction. Among the involved models, the proposed model can obtain the best prediction accuracy. The experimental results indicate that the mean absolute percent errors of the proposed model are 7.97% and 9.99%, which are lower than the comparison methods. Pearson’s test reveals that the proposed approach can have the strongest association between the actual data and the prediction results.
Lithium and Copper Induce the Osteogenesis-Angiogenesis Coupling of Bone Marrow Mesenchymal Stem Cells via Crosstalk between Canonical Wnt and HIF-1α Signaling Pathways
Authors: Tan Zhen , Zhou Baochun , Zheng Jianrui , Huang Yongcan , Zeng Hui , Xue Lixiang , Wang Deli
Published: March 2021

The combination of osteogenesis and angiogenesis dual-delivery trace element-carrying bioactive scaffolds and stem cells is a promising method for bone regeneration and repair. Canonical Wnt and HIF-1α signaling pathways are vital for BMSCs’ osteogenic differentiation and secretion of osteogenic factors, respectively. Simultaneously, lithium (Li) and copper (Cu) can activate the canonical Wnt and HIF-1α signaling pathway, respectively. Moreover, emerging evidence has shown that the canonical Wnt and HIF signaling pathways are related to coupling osteogenesis and angiogenesis. However, it is still unclear whether the lithium- and copper-doped bioactive scaffold can induce the coupling of the osteogenesis and angiogenesis in BMSCs and the underlying mechanism. So, we fabricated a lithium- (Li+-) and copper- (Cu2+-) doped organic/inorganic (Li 2.5-Cu 1.0-HA/Col) scaffold to evaluate the coupling osteogenesis and angiogenesis effects of lithium and copper on BMSCs and further explore its mechanism. We investigated that the sustained release of lithium and copper from the Li 2.5-Cu 1.0-HA/Col scaffold could couple the osteogenesis- and angiogenesis-related factor secretion in BMSCs seeding on it. Moreover, our results showed that 500 μM Li+ could activate the canonical Wnt signaling pathway and rescue the XAV-939 inhibition on it. In addition, we demonstrated that the 25 μM Cu2+ was similar to 1% oxygen environment in terms of the effectiveness of activating the HIF-1α signaling pathway. More importantly, the combination stimuli of Li+ and Cu2+ could couple the osteogenesis and angiogenesis process and further upregulate the osteogenesis- and angiogenesis-related gene expression via crosstalk between the canonical Wnt and HIF-1α signaling pathway. In conclusion, this study revealed that lithium and copper could crosstalk between the canonical Wnt and HIF-1α signaling pathways to couple the osteogenesis and angiogenesis in BMSCs when they are sustainably released from the Li-Cu-HA/Col scaffold.
Upregulation of miR‐138 Increases Sensitivity to Cisplatin in Hepatocellular Carcinoma by Regulating EZH2
Authors: Zeng Taohui , Luo Lin , Huang Yuye , Ye Xiaoli , Lin Jinhai
Published: March 2021

Chemotherapeutic insensitivity is a major obstacle for effective treatment of hepatocellular carcinoma (HCC). Recently, new evidence showed that microRNAs (miRNAs) are closely related to drug sensitivity. This study aimed to investigate the relationship between miR‐138 expression and cisplatin sensitivity of HCC cells by regulation of EZH2. CCK‐8, EdU, and western blotting are determining the cell viability, proliferation, EZH2, and EMT‐related protein expression. It was found that compared with normal samples, miR‐138 expression was lower in cancer tissue; it was also downregulated in HCC cells. Transfected with miR‐138 mimic increased sensitivity of HCC cells to cisplatin. Mechanistically, Luciferase Reporter analysis verified the interaction between miR‐138 and target gene EZH2. Inhibition of EZH2 enhanced cisplatin sensitivity and transfection with EZH2 mimic mirrored the function of miR‐138 in cisplatin sensitivity. Furthermore, the role of miR‐138 on reversed cisplatin‐induced epithelial–mesenchymal transition (EMT) was attenuated when combined with EZH2 plasmid. In conclusion, all data from this study illustrate that miR‐138 may as a tumor suppressor provides a potential treatment method to treating HCC.
Feasibility of Right Upper Transversal Hepatectomy in the Absence of an Inferior Right Hepatic Vein: New Insights regarding This Complex Procedure
Authors: Makdissi Fabio Ferrari , Kruger Jaime Arthur Pirola , Jeismann Vagner Birk , Herman Paulo
Published: March 2021

Background. Right upper transversal hepatectomy (RUTH) is defined as the removal of liver segments 7, 8, and 4A with ligature of the right and middle hepatic veins and is considered one of the most complex techniques of parenchymal-sparing hepatectomies. This procedure can be performed, without venous reconstruction, if collateral veins are present communicating within remnant liver segments to a large inferior right hepatic vein and/or to the left hepatic vein. This venous network could maintain outflow from the inferior right segments (S5, S6) to the left liver when a RUTH is performed, even in the absence of an inferior right hepatic vein. The aim of this study is to present our experience with RUTH without venous reconstruction in patients with and without the presence of an inferior right hepatic vein (IRHV). Methods. Patients submitted to RUTH for treatment of liver metastases were selected from our database. The presence of an IRHV, clinical and surgical characteristics of the patients, immediate outcomes, viability of liver segments 5 and 6, and long-term survival were analyzed. Results. RUTH was successfully performed in four patients. In two patients, IRHV was not present, but intrahepatic communicating veins between proximal right and middle hepatic veins and left hepatic vein were present. No venous reconstructions were performed. Mild congestion of the inferior right segments occurred in the patients where there was no IRHV but no immediate, early, or late complications were observed. Conclusions. RUTH is feasible and can be performed even in the absence of an IRHV, without venous reconstruction. Some degree of congestion of the right inferior liver segments might occur when an IRHV is absent, yet this is not clinically significant when communicating veins are present. Maximum parenchyma preservation might prevent postoperative liver failure and allow repeated resections in case of hepatic recurrence.
Choroidal Detachment after XEN Gel Stent Implantation
Authors: Cutolo Carlo Alberto , Negri Letizia , Olivari Sara , Cappelli Francesca , Traverso Carlo Enrico , Iester Michele
Published: March 2021

Background. The purpose of this study is to estimate the incidence of choroidal detachment (CD) after XEN gel stent implant surgery and to evaluate the associated factors. Methods. We reviewed the clinical charts of 126 patients who underwent XEN implantation between March 1, 2016, and December 31, 2018 at the University Eye Clinic of Genoa. Ocular, demographics, and perioperative factor were registered and analysed. Univariate and multivariate logistic analysis were performed to investigate factors associated with CD occurrence. Results. Of the 126 patients, 25 (19.8%) developed a choroidal detachment after XEN gel stent implant surgery. The mean period between surgery and CD detection was 5.84 ± 1.77 days. The mean intraocular pressure (IOP) at the time of CD diagnosis was 6.4 ± 3.1 mmHg. Age (OR = 1.10,p<0.019), early postoperative IOP (OR = 0.70,p<0.001), and number of preoperative IOP-lowering drugs (OR = 5.70,p<0.001) were significantly associated with CD presence. Complete resolution was observed in all the cases. Wide-field imaging and ultrasonography were useful tools to diagnose and follow up CD until resolution. Conclusions. When carefully investigated, CD is a relatively common complication after XEN gel stent implant procedure. Older age, lower postoperative IOP, and higher number of preoperative IOP-lowering drugs were significantly associated with the development of CD.
Ultimate Limit Design of Strengthened Steel Columns by Mortar-Filled FRP Tubes
Authors: Hou Jian , Song Li
Published: March 2021

The present study investigated the various failure modes of strengthened steel columns by mortar-filled fiber-reinforced polymer (FRP) tubes to analytically formulate the ultimate capacities of these steel columns. A simple and effective method, wherein a mortar-filled FRP tube was sleeved outside the steel member, was also formulated to enhance the buckling resistance capacity of compressed steel members. In addition, to facilitate the connection of the column to other structural members, the length of the sleeved mortar-filled FRP tubes is less than that of the original steel columns. Theoretical analyses were also performed on the critical sections of such composite columns at their ultimate states to identify their potential failure modes, such as FRP-tube splitting at the ends or on the insides of wrapped areas, local buckling at the steel ends of transition zones, and global buckling of the composite columns. The corresponding ultimate capacity of each failure mode was then analytically formulated to characterize the critical failure mode and ultimate load capacity of the columns. The current theoretical results were compared with those from literature to validate the applicability of the developed ultimate limit design approaches for FRP-mortar-steel composite columns.
Synergistic Effect of Heating pH and Transglutaminase on the Gelation Kinetics and Texture of Yak Skim Milk Gels
Authors: Yang Lin , Li Zhaomin , Gu Xuedong , Chi Fumin , Zhu Yahui
Published: March 2021

Textural defects (including syneresis and poor consistency) often occur in yogurt gels produced from yak milk. In this research, the synergistic effects of transglutaminase (TGase) and heating pH on the textural properties of acidified yak skim milk gels, as well as the related mechanism of action, were investigated. The pH values of yak skim milk were adjusted to 6.3, 6.7, and 7.1, respectively. The samples were heated at 80°C for 30 min and then cooled to 42°C. After treatment with different contents of TGase (0, 3, and 10 U TGase per gram proteins), the samples were acidified with glucono-delta-lactone. For a given TGase content, the final storage modulus (G′) of gels was positively related to the heating pH, whereas the opposite trend was observed for the gelation time. This effect was obvious between pH 6.3 and 6.7. At a definite heating pH value, the final G′ of the gels was highest at 3 U TGase per gram proteins. The highest water holding capacity and firmness value were observed in gels prepared using pH 7.1 and 3 U TGase per gram proteins. In the samples treated with 3 U TGase per gram proteins (preheating pH 7.1), more rigid network structures were seen in the gel than 0 or 10 U TGase per gram proteins. Therefore, adjusting the heating pH values and TGase contents is an effective way of improving the textural properties of yak milk gels.
Molecular Characteristics, Synthase, and Food Application of Cereal β-Glucan
Authors: Sun Lijing , Hu Mengyun , Zhao Jie , Lv Liangjie , Zhang Yelun , Liu Qian , Zhang Li , Yu Cuihong , Wang Peinan , Li Qianying , Li Hui , Zhang Yingjun
Published: March 2021

Cereal β-glucan is a type of valuable dietary fiber that mainly exists in the aleurone, subaleurone, and endosperm of some cereal grains. β-Glucan is acknowledged as a functional food ingredient owing to its multiple health benefits, including the prevention of diabetes, reduction in the incidence of cardiovascular disease, antitumor effects, antioxidant activities, and immunostimulation. It is well documented that cellulose synthase-like CslF/H/J genes encode synthases responsible for β-glucan biosynthesis in cereal grains. Recently, β-glucan has been widely applied as an emulsion stabilizer, thickening agent, fat substitute, and bioactive ingredient in the food industry due to its water solubility, viscosity, gelation property, and health benefits. Therefore, the present paper aims to review the molecular characteristics, synthase gene family, and food application of cereal β-glucan in recent years.
Dynamic Incentive Mechanism of Multitask Cooperation in Logistics Supply Chain
Authors: Wang Song , Zhao Yang , Liu Lanfeng , Huang Fuhua
Published: March 2021

This paper studies the incentive mechanism of multitask cooperation in logistics service supply chain (LSSC) by building a dynamic incentive model. Research shows the following: (1) the implicit reputation in dynamic cooperation can effectively improve system incentive effectiveness; (2) the difference in the contribution of different logistics cooperation to the performance of the LSSC has a significant impact on the incentive effect; (3) when two kinds of cooperation tasks have complementary relationships, both the LSP’s choice of logistics tasks and the incentives will simultaneously act on the two types of cooperation tasks; and (4) the antirisk degree of LSI and the environment uncertainty will also have a certain impact on the incentive effect of the LSSC. Therefore, the LSI should comprehensively consider the requirements of logistics cooperation and the risk tolerance of LSI to be chosen.
A Personalized Mean-CVaR Portfolio Optimization Model for Individual Investment
Authors: Yu Chunxia , Liu Yuru
Published: March 2021

Investment as an important issue in daily life is accompanied by the occurrence of various financial assets, such as stocks, bonds, and mutual funds. However, risk tolerances vary across individuals. Individual investors have to select corresponding personalized investment portfolios to satisfy their own needs. Moreover, it is difficult for ordinary people to select a personalized investment portfolio by themselves, and it is too expensive and inefficient to look for professional consultation. Therefore, the objective of this research is to propose a personalized portfolio recommendation model, which can build the personalized portfolio based on investors’ risk tolerances. In this research, investors’ risk tolerance is determined by the fuzzy comprehensive evaluation method based on investors’ demographic characteristics. The CVaR is used as the risk measurement of financial assets. The dynamics of the distribution of returns are described in the combined Copula-GARCH model, and the future scenarios of returns are generated by the Monte Carlo simulation based on the combined Copula-GARCH model to estimate CVaR. The mean-CVaR portfolio optimization model is used to find out the best personalized portfolio. Finally, experiments are conducted to validate the applicability and feasibility of the personalized investment portfolio optimization model. Results show that the proposed investment portfolio optimization model can recommend personalized investment portfolio according to investor’s risk tolerance.
A Study on the Influence of Different Constraint Modes and Number of Disc Springs on the Dynamics of Disc Spring System
Authors: Zhou Jiacheng , Zhang Chuzhe , Wang Ziqiu , Mao Kuanmin , Wang Xiaoyu
Published: March 2021

In this work, the influences of constraint modes and the number of disc springs on the dynamic characteristics of the disc spring system are studied by simulation and experiment. The amplitudes and amplification factors of the disc spring system under different constraint modes and different numbers of disc springs are obtained. The results show that the maximum amplitude and amplification factor both appear at the constraint modes of locking and no preloading, which indicates that the locking and no preloading is the best constraint mode among the four different constraint modes. Moreover, the amplitude of the disc spring system first increases and then decreases with the number of disc springs increasing, while the amplification factor increases with the number of disc springs increasing. The maximum amplification factor (10.21 in experiment) of the disc spring system appears at 10 disc springs. By studying the relationship between the number of disc springs and amplification factor and damping, we find that the damping of the disc spring system can be reduced by increasing the disc spring numbers, and thus, the corresponding amplification factor can be improved. Furthermore, as the number of disc spring increases, the height differences of disc springs before and after locking are all close to 3 mm, which indicates that the amount of locking compression in the assembly process has a good consistency when the number of disc springs changes. The aforementioned works can provide guidance for the industrial production in screen vibration.
Distribution of Lipids and Prevalence of Dyslipidemia among Indian Expatriates in Qatar
Authors: Nirwan R. , Singh D.
Published: March 2021

Background. Dyslipidemia is a significant risk factor for cardiovascular diseases (CVD). If detected and managed in the early stages of life, can reduce morbidity and mortality associated with CVD in a vulnerable population. Out of the 94 expatriate nationalities in Qatar, Indians constitute the most prominent single nationality, accounting for 21.8% of the total population (2,773,885 in 2019). This study aims to determine the status of the lipid profile among Indians in Qatar. Study Design. We conducted an observational retrospective study on lipid profile test data of Indian expatriates visiting a private healthcare facility in Qatar from Oct 17 to Oct 2018 to evaluate the gender and age-specific distribution of lipids and the prevalence of dyslipidemia. Results. Among the total 4483 Indian expatriates (3891 men and 592 women), the mean (SD) mg/dL levels of total cholesterol (TC), triglycerides (TG), and low-density lipoprotein cholesterol (LDL-C) were higher in men TC 196.9 (40.6), TG 168.9 (114.6), and LDL-C 122.9 (37.2) mg/dL compared to women TC 185 (38.1), TG 117.7 (78.2), and LDL-C 114.1 (31.1) mg/dL,

p

value < 0.0001. Utilizing predefined National Cholesterol Education Program-Adult Treatment Panel III (NCEP ATP III) limits to categorize dyslipidemias; the greater prevalence of elevated TC, TG, and LDL-C was noted in men 44.7%, 45.8%, and 40.9% than women 31.6%, 22%, and 28.7%, respectively. However, women had higher levels of mean high-density lipoprotein cholesterol (HDL-C) as 47.1 (9.8) mg/dL vs. 40.6 (8.3) mg/dL in men,

p

value < 0.05, the prevalence of dyslipidemia, low HDL-C was also more 65.7% vs. 48.9% in women than men. With age, men showed a declining trend while women showed a rising trend for mean lipid levels as well as for the prevalence of dyslipidemia, high TC, TG, and LDL-C (

p

value < 0.0001). The mean HDL-C cholesterol increased, and the prevalence of dyslipidemia, low HDL-C decreased with age in both the genders. Conclusion. Our results demonstrate the higher mean lipid levels and prevalence of atherogenic dyslipidemia among Indian expatriate men than women counterparts at the younger age group. The screening programs and awareness campaigns must be initiated to prevent the early onset of dyslipidemia induced atherosclerosis leading to CVD. Future controlled studies are needed to estimate the prevalence of dyslipidemias among Indian migrants in Qatar.
Preemptive Oral Etoricoxib on Health‐Related Quality of Life after Mandibular Third Molar Surgery: A Randomized, Double‐Blind, Placebo‐Controlled Clinical Trial
Authors: Xie Long , Li Zhi , Shang Zheng-Jun
Published: March 2021

This study was aimed at evaluating the use of oral etoricoxib for preemptive analgesia on the health‐related quality of life (QoL) outcome after the extraction of mandibular third molar. The study population consisted of 60 participants that required extraction of a single partial bony impacted mandibular third molar under local anesthesia and met the inclusion criteria. The participants were randomized into two groups. The etoricoxib group orally received 60 mg etoricoxib 30 min before surgery, whereas the control group was given a placebo. The patients were assessed postoperatively after 1, 2, 3, 4, 5, 6, and 7 days using the United Kingdom oral health‐related QoL questionnaire and visual analog scale for maximum postoperative pain. The total dose of ibuprofen rescue intake and total number of days the drug was taken were recorded. Surgical removal of impacted teeth had a negative influence on the patient’s QoL across various physical, social, and psychological aspects. The scores for postoperative pain in the etoricoxib group were significantly lower than those in the control group on each postoperative observation day. The number of patients without analgesic rescue medication, the average amount, and total number of days emergency analgesics were taken were significantly lower in the etoricoxib group than in the control group. The etoricoxib group showed better QoL score than the control group. Preemptive oral etoricoxib is an effective therapeutic strategy for improving the QoL after surgical removal of the impacted lower third molar.
Estimating one-diode-PV model using autonomous groups particle swarm optimization
Authors: AlShabi Mohammad , Ghenai Chaouki , Bettayeb Maamar , Faraz Ahmad Fahad
Published: March 2021

In this paper, the one-diode model of a photovoltaic PV solar cell (PVSC) is estimated for an experimental characteristic curves data by using a recently proposed version of the Particle Swarm Optimization (PSO) algorithm, which is known as the Autonomous Groups Particles Swarm Optimization (PSOAG). This meta-heuristic algorithm is used to identify the model of the PVSC. The PSOAG divides the particles into groups and then, uses different functions to tune the social and cognitive parameters of these groups. This is done to show the individuals’ diversity inside the swarm. Although, these individuals do their duties as part of the society, they are not similar in terms of intelligence and ability. By using these groups, the performance of the PSO is improved in terms of convergence rate and escaping the local minima/maxima. Six versions of PSOAG algorithms were developed in this work. Therefore, nine versions of PSOAG, including these six algorithms and three newly developed PSOAG reported previously, will be used in this research to cover more social’s behaviors. The results are compared to the original PSO and other versions of PSO like conventional and Asymmetric Time-varying Accelerated Coefficient PSOs, and the improved PSO. The result shows that the proposed methods improve the performance by up to 14% in terms of root mean squared error and maximum absolute error, and by up to 20% in term of convergence rate, when these were compared to the best results obtained from the other algorithms.
Massively scalable density based clustering (DBSCAN) on the HPCC systems big data platform
Authors: H. R. Yatish , Milind Phal Shubham , Sanjay Hukkeri Tanmay , Xu Lili , G Shobha , Shetty Jyoti , Chala Arjuna
Published: March 2021

Dealing with large samples of unlabeled data is a key challenge in today’s world, especially in applications such as traffic pattern analysis and disaster management. DBSCAN, or density based spatial clustering of applications with noise, is a well-known density-based clustering algorithm. Its key strengths lie in its capability to detect outliers and handle arbitrarily shaped clusters. However, the algorithm, being fundamentally sequential in nature, proves expensive and time consuming when operated on extensively large data chunks. This paper thus presents a novel implementation of a parallel and distributed DBSCAN algorithm on the HPCC Systems platform. The algorithm seeks to fully parallelize the algorithm implementation by making use of HPCC Systems optimal distributed architecture and performing a tree-based union to merge local clusters. The proposed approach* was tested both on synthetic as well as standard datasets (MFCCs Data Set) and found to be completely accurate. Additionally, when compared against a single node setup, a significant decrease in computation time was observed with no impact to accuracy. The parallelized algorithm performed eight times better for higher number of data points and takes exponentially lesser time as the number of data points increases.
Effect of data-augmentation on fine-tuned CNN model performance
Authors: Poojary Ramaprasad , Raina Roma , Kumar Mondal Amit
Published: March 2021

During the last few years, deep learning achieved remarkable results in the field of machine learning when used for computer vision tasks. Among many of its architectures, deep neural network-based architecture known as convolutional neural networks are recently used widely for image detection and classification. Although it is a great tool for computer vision tasks, it demands a large amount of training data to yield high performance. In this paper, the data augmentation method is proposed to overcome the challenges faced due to a lack of insufficient training data. To analyze the effect of data augmentation, the proposed method uses two convolutional neural network architectures. To minimize the training time without compromising accuracy, models are built by fine-tuning pre-trained networks VGG16 and ResNet50. To evaluate the performance of the models, loss functions and accuracies are used. Proposed models are constructed using Keras deep learning framework and models are trained on a custom dataset created from Kaggle CAT vs DOG database. Experimental results showed that both the models achieved better test accuracy when data augmentation is employed, and model constructed using ResNet50 outperformed VGG16 based model with a test accuracy of 90% with data augmentation & 82% without data augmentation.
Crucial problems in arranged the lesson plan of vocational teacher
Authors: Nurtanto Muhammad , Kholifah Nur , Masek Alias , Sudira Putu , Samsudin Achmad
Published: March 2021

This study aimed to explore the implementation of the 2013 curriculum in vocational schools, Banten in terms of the readiness and quality of the learning tools that have been prepared. A total of 957 respondents from 2017 to 2018, consisting of four cities and three districts in Banten Province were involved in the training and mentoring program, namely vocational teachers and vice-principals in the curriculum field. Data were collected using questionnaire sheets, FGD notes, and observation check dates. The data obtained are analyzed and interpreted based on the specified categories. The results showed that: 1) Teacher readiness for learning tools in the components a) Core Competencies (CC) and Basic Competencies (BC) analysis of 45.31%, b) Program mapping of 38.37%, learning plan preparation of 39.45% and c) Learning evaluation of 36.78%; 2) The quality of lesson plan (LP) the science lesson plan analysis instrument (SLPAI) based is divided into two groups. The category "Quality" in the instructional program and instructional plan aspects, and the category "Moderate" in the instructional media and assessment and others aspects; and 3) The difficulty of learning device components, including authentic assessment, use of methods, literacy approaches, and lesson planning. The implementation of training, mentoring, and supervision programs are adjusted to the experience of vocational teachers taking into account the teacher's involvement in the implementation of the curriculum, age, and school readiness.
Evaluation of healthcare science student learning styles based VARK analysis technique
Authors: Kamal Izdihar , Abdul Karim Muhammad Khalis , Awang Kechik Mohd Mustafa , Ni Xinni , Abdul Razak Hairil Rashmizal
Published: March 2021

This study aimed to evaluate the learning styles among healthcare students and to study the relationship with their academic achievement. This cross-sectional study was conducted among 137 healthcare students from six different courses. Data was collected using a self-administered questionnaire and developed based on the original visual, aural/auditory, read/write, and kinesthetic (VARK) assessment. The questionnaire was divided into two sections: the demographic status and the learning style perspective. A total of 119 respondents (86.8%) has chosen unimodal as their learning styles, while the rest of the 18 respondents (13.2%) choose multimodal as their preferred learning method. Among the unimodal learning styles, visual (32%) and reading (26%) were most preferred among respondents. The auditory and kinesthetic methods of learning were less and accounted for 10% to 20%. Notably, in multimodal learning styles preferences, 4% of students prefer a combination learning style of visual and kinesthetic methods. There was no significant relationship between learning styles and academic achievement using Pearson’s Chi-square test (p>0.05). Hence, both were independent of one another. Hence, some of the dominant learning styles needed to be considered based on their future profession.
Arabic language learning reconstruction as a response to strengthen Al-Islam studies at higher education
Authors: Ritonga Mahyudin , Widodo Hendro , Munirah Munirah , Nurdianto Talqis
Published: March 2021

Knowledge of the Islam at every student is supported by many factors, one of which is the Arabic language compentence. This research aimed to evaluate and find Arabic language learning construction in strengthening al-Islam at higher education. The desire to find the construction is because there is no visible connection between Arabic language learning and al-Islam learning so that clarity of learning objectives, learning materials, learning implementation, and evaluation systems of Arabic language learning at higher education is needed. In line with this purpose, this study used a qualitative method with a phenomenological approach. The sources of data were facts, Arabic language lecturers, al-Islam lecturers, and students purposively. Data were analyzed by using critical realism. The results of the study proved that the reconstruction of learning objectives, materials, implementation, and evaluation systems is needed to realize Arabic language learning that can strengthen al-Islam at higer education.
The relationship between management styles and trainers’ job motivation in the public institutions
Authors: Malkoc Nedim , Dal Suzan
Published: March 2021

The study aimed to determine the relationship between perceptions of management styles and trainers' motivation in the public sports institutions, and to examine the effect of management styles on job motivation. The sample of the research consists of 190 trainers, 18 of whom are women and 172 of whom are men working in the public sports institutions. In the study, descriptive scanning method was used, and the data obtained were analyzed by making statistical procedures such as frequency, correlation, regression analysis. It was found that democratic management style and paternalist management style had a positive effect on trainers’ job motivation. However, the liberal management style and authoritarian management style were found to have a negative effect on trainers’ job motivation.
Assessing students’ errors in mathematical translation: From symbolic to verbal and graphic representations
Authors: Nurrahmawati Nurrahmawati , Sa'dijah Cholis , Sudirman Sudirman , Muksar Makbul
Published: March 2021

Translation skills are very important possessed by students, but currently, there are still many students who have difficulty in translating between representations. The purpose of this study is to analyze students' errors in translating from symbolic representations to verbal and graphic representations. This research was descriptive study with qualitative approach. Tests are given to junior high school students. From the results of data analysis, it is obtained that in translating from symbolic to verbal forms (problems in daily life) that are following the given system of equations, students are still unable to make representations correctly. When students are asked to translate into graphical form, students are still unable to draw complete graphs and errors made by students are misinterpretation and implementation errors, so they cannot maintain the semantic congruence between source representation and target representation. Based on this, it is necessary to make a learning plan that can improve students’ ability to translate between representations.
Educational data mining in moodle data
Authors: Shrestha Sushil , Pokharel Manish
Published: March 2021

The main purpose of this research paper is to analyze the moodle data and identify the most influencing features to develop the predictive model. The research applies a wrapper-based feature selection method called Boruta for the selection of best predicting features. Data were collected from eighty-one students who were enrolled in the course called Human Computer Interaction (COMP341), offered by the Department of Computer Science and Engineering at Kathmandu University, Nepal. Kathmandu University uses Moodle as an e-learning platform. The dataset contained eight features where Assignment.Click, Chat.Click, File.Click, Forum.Click, System.Click, Url.Click, and Wiki.Click was used as the independent features and Grade as the dependent feature. Five classification algorithms such as K Nearest Neighbour, Naïve Bayes, and Support Vector Machine (SVM), Random Forest, and CART decision tree were applied in the moodle data. The finding shows that SVM has the highest accuracy in comparison to other algorithms. It suggested that File.Click and System.Click was the most significant feature. This type of research helps in the early identification of students’ performance. The growing popularity of the teaching-learning process through an online learning system has attracted researchers to work in the field of Educational Data Mining (EDM). Varieties of data are generated through several online activities that can be analyzed to understand the student’s performance which helps in the overall teaching-learning process. Academicians especially course instructors who use e-learning platforms for the delivery of the course contents and the learners who use these platforms are highly benefited from this research.
A nationwide survey of psychological distress among Indonesian residents during the COVID-19 pandemic
Authors: Respati Titik , Irasanti Siska Nia , Sartika Dewi , Akbar Ieva Baniyah , Marzo Roy Rillera
Published: March 2021

The Coronavirus disease (COVID-19) has become a public health emergency. The speed at which COVID-19 become pandemic and spread all over the world is alarming. A critical aspect of this type of pandemic is on the mental health of the community. This survey aimed to describe psychological distress in Indonesia's general population during the COVID-19 pandemic. Data collection began on 1st April 2020 to 30th April 2020. An online survey using Google Form with snowball sampling method used in this study. A modified version of the COVID-19 peri-traumatic distress index (CPDI) with 24 items used. The survey questionnaire included socio-economic and demographic variables. The study's total responses were 1,287, with 33 excluded from the analysis because of incomplete responses or not meeting inclusion criteria. Results showed that 63.5% of respondents reported having normal or no distress, 34% were having mild to moderate levels of distress, and 2.8% having severe distress. Age is the only variable that correlates with the level of distress. Healthcare workers and the general population showed no significant differences in the level of distress. During the early break of the COVID-19 pandemic, around 40% of respondents rated their psychological state having moderate to severe distress. These findings can be used to develop better psychological intervention measures and prevention of mental health during the pandemic.