bluuebunny/crossref_metadata_2025 huggingface dataset:
Mediating effect of gait speed on the relationship between ankle‐brachial index and mild cognitive impairment in hemodialysis patients
Authors: Zhao Yinjiao , Song Peiyu , Zhang Hui , Chen Xiaoyu , Han Peipei , Xie Danshu , Fan Weifeng , Zhan Qiunan , Zhang Suhua , Hu Xiaohua , Li Xin , Xu Jia , Xie Fandi , Guo Qi
Published: April 2022

Background

Patients undergoing hemodialysis are highly predisposed to arterial disease, poor physical performance, and cognitive impairment. However, the connection between them is not yet known. We aimed to investigate the mediating effect of physical performance on the relationship between arterial stiffness and mild cognitive impairment (MCI).

Methods

We conducted a multicenter cross‐sectional study. The final analyzed hemodialysis patients comprised 616 subjects (men 391, women 225) from seven dialysis units in Shanghai, China. MCI was assessed by Mini‐Mental State Examination (MMSE) and the Instrumental Activities of Daily Living (IADL) scale. Arterial function was measured by ankle‐brachial index (ABI) and branchial‐ankle pulse‐wave velocity (baPWV). Physical function was assessed by the Short Physical Performance Battery (SPPB). Logistic regression and mediation model were used to analysis.

Results

The mean age of the final analysis sample (n = 616) was 59.0 ± 12.0 years. Hemodialysis patients with MCI were more likely to have lower ABI (p < 0.001) and higher baPWV (p < 0.01). After adjusting for covariates, lower ABI (abnormal ≤0.9 and borderline 0.91–0.99) were positively associated with MCI (OR = 4.43, 95% CI = 1.89–10.39; OR = 4.83, 95% CI = 1.61–14.46). SPPB total score and its components standing balance, gait speed score were negatively associated with MCI. In the mediational model, gait speed played a mediating role (indirect effect ab = −0.21; 95% CI = −0.58 to −0.03) in the association of ABI (≤0.9) and MMSE, while standing balance and chair stands did not.

Conclusions

Lower gait speed mediates a positive association between ABI and MCI in hemodialysis patients. Suitable interventions for physical performance, especially gait speed, may reduce the risk of MCI in hemodialysis patients.
BIOMECHANICAL EVALUATION OF LOCKING COMPRESSION PLATE (LCP) VERSUS DYNAMIC COMPRESSION PLATE (DCP): A FINITE ELEMENT ANALYSIS
Authors: Suaimi Muhammad Khairul Asyraf , Ab Rashid Amir Mustakim , Nasution Ahmad Kafrawi , Hong Seng Gan , Abdul Kadir Mohammed Rafiq , Ramlee Muhammad Hanif
Published: April 2022

Internal fixators are commonly used to treat long bone fractures, its aim is to provide interfragmentary compression, allow limited micromotion and provide stability to the bone for ambulation. However, complications such as non-unions, malunions and broken implant, can occur due to the complexity of mechanical force acting on the bone-plate models. Therefore, this study is proposed to investigate the biomechanical characterization of plate design on a tibia bone using finite element method. Two different designs; 1) locking compression plate (LCP) and dynamic compression plate (DCP) were simulated by using Marc.Mentat software. From the findings, the LCP have lower peak von Mises stress (VMS) distribution of 160 MPa compared to DCP with VMS value of 232 MPa. Surprisingly, the VMS of DCP plate system have exceed the yield strength of stainless steel (215 MPa) which translate to higher risk of failures. Moreover, the DCP plate system shows 50% lower stability compared to the LCP plate system, which has the peak displacement at 0.98 mm compared to the DCP bone at 1.53 mm. In conclusion, the LCP provides better stability and stress distribution up to 45% differences as compared to the DCP.
THE EFFECT OF MODIFY NaOH CONCENTRATION ON THE STRUCTURE AND MAGNETIC PROPERTIES IN CO-PRECIPITATED NANOCRYSTALLINE BISMUTH SUBSTITUTED COBALT FERRITE
Authors: Saputro D. E. , Budiawanti S. , Wira Sukarsa Suharno , Rahardjo D. T. , Purnama B.
Published: April 2022

The structural and magnetic properties modification in the bismuth substituted cobalt ferrite nanopowder with various molar concentrations of NaOH has been successfully synthesized by the coprecipitation method. The crystalline structure was measured using X-ray diffraction (XRD), bond groups, and absorption strength was measured by Fourier Transform Infrared spectroscopy (FTIR) studies, and then magnetic properties were measured using a Vibrating Scanning Magnetometer (VSM). The XRD measurement results confirmed that the whole samples of bismuth cobalt ferrite owing single phase of inverse spinel face cubic center (fcc) with space group Fd-3m were obtained for variations in molar concentration of NaOH. The FTIR  measurements obtained that the absorption characteristic in the frequency band 400 - 750 cm-1 according to resonance at octahedral and tetrahedral sites of the occurrence metal oxide. The VSM measurement showed that the magnetic properties of bismuth substituted cobalt ferrite available to tune with modifying NaOH concentration in the co-precipitation procedure. Thus, the effect of increasing the concentration of NaOH into bismuth-substituted cobalt ferrite can change the characteristics of the cobalt ferrite such as lattice parameters, shifts in the absorption peaks of functional groups, and changes in magnetic saturation. The significance of this research is to know the exact concentration value of bismuth substituted cobalt ferrite to obtain the best characteristics.
Particle Scale Investigation of Influencing Factors on Heat Transfer in Nonspherical Particle–Fluid System
Authors: Cao Ze , Tafti Danesh K.
Published: April 2022

Heat transfer characteristics of random suspensions of 0.25 aspect ratio (AR) cylinders are investigated for Reynolds numbers (Re) between 10 and 300 and solid fraction (φ) ranging from 0.1 to 0.3 using particle resolved simulations. The effect of particle inclination with respect to flow and particle clustering on heat transfer is investigated. The Nusselt number decreases with an increase in inclination angle and the dependence becomes stronger as φ and Re increase. On the other hand, while prolate ellipsoid suspensions of AR 2.5 follow the same trend, the Nusselt number increases with inclination angle as AR increases to 5 and 10 and as φ increases. Local particle clustering nominally decreases the Nusselt number because of the dominance of thermal wakes. At low φ, this effect is felt only at low Re, but as φ increases, the effect spreads to higher Re. Similar but weaker trends are also found in suspensions of prolate ellipsoids of AR 2.5, 5, and 10. High AR, low Re prolate ellipsoids exhibit the greatest dependence of Nusselt number on local solid fraction. Implementation of two independent definitions of reference length, i.e., volume equivalent sphere diameter deq for ellipsoids and diameter dp of the cylindrical particle in the correlation of Tavassoli et al. (2015, “Direct Numerical Simulation of Fluid-Particle Heat Transfer in Fixed Random Arrays of Non-Spherical Particles,” Chem. Eng. Sci., 129, pp. 42–48) provides good estimates of the respective suspension mean Nusselt numbers.
Population Pharmacokinetics of Antimalarial Naphthoquine in Combination with Artemisinin in Tanzanian Children and Adults: Dose Optimization
Authors: Ali Ali Mohamed , Gausi Kamunkhwala , Jongo Said A. , Kassim Kamaka R. , Mkindi Catherine , Simon Beatus , Mtoro Ali T. , Juma Omar A. , Lweno Omar N. , Gwandu Conrad H. , Bakari Bakari M. , Mbaga Thabiti A. , Milando Florence A. , Hamad Ali , Shekalaghe Seif A. , Abdulla Salim , Denti Paolo , Penny Melissa A.
Published: April 2022

The combination antimalarial therapy of artemisinin-naphthoquine (ART-NQ) was developed as a single-dose therapy, aiming to improve adherence relative to the multiday schedules of other artemisinin combination therapies. The pharmacokinetics of ART-NQ has not been well characterized, especially in children. A pharmacokinetic study was conducted in adults and children over 5 years of age (6 to 10, 11 to 17, and ≥18 years of age) with uncomplicated malaria in Tanzania.
Epidemiology and Genomic Characterization of Two Novel SARS-Related Coronaviruses in Horseshoe Bats from Guangdong, China
Authors: Li Linmiao , Zhang Libiao , Zhou Jiabin , He Xiangyang , Yu Yepin , Liu Ping , Huang Wenzhong , Xiang Zuofu , Chen Jinping
Published: April 2022

Severe acute respiratory syndrome coronavirus (SARS-CoV) and SARS-CoV-2 probably originated from the SARS-related coronaviruses (SARSr-CoVs) carried by
Rhinolophus
bats from Yunnan, China. Systematic investigations of the reservoir hosts carrying SARSr-CoVs in Guangdong and the reservoir distribution and transmission are urgently needed to prevent future outbreaks.
An Optimal Lysis Time Maximizes Bacteriophage Fitness in Quasi-Continuous Culture
Authors: Kannoly Sherin , Singh Abhyudai , Dennehy John J.
Published: April 2022

Optimality theory presents the idea that natural selection acts on organismal traits to produce genotypes that maximize organismal survival and reproduction. As such, optimality theory is a valuable tool in guiding our understanding of the genetic constraints and tradeoffs organisms experience as their genotypes are selected to produce optimal solutions to biological problems.
Development of a Machine Learning-Based Cysticidal Assay and Identification of an Amebicidal and Cysticidal Marine Microbial Metabolite against
Acanthamoeba
Authors: Shing Brian , Balen Mina , Fenical William , Debnath Anjan
Published: April 2022

The free-living
Acanthamoeba
can exist as a trophozoite or cyst and both stages can cause painful blinding keratitis. Infection recurrence occurs in approximately 10% of cases due to the lack of efficient drugs that can kill both trophozoites and cysts.
Diagnostic Value of IgA Antibody Measurement in Tick-Borne Spotted Fever (Astrakhan Rickettsial Fever)
Authors: Smirnova Nina S. , Kostarnoy Alexey V. , Kondratev Alexey V. , Gancheva Petya G. , Grumov Daniil A. , Gintsburg Alexander L.
Published: April 2022

Tick-borne spotted fevers caused by
Rickettsia
occur worldwide. The symptoms of this bacterial infection are similar to the symptoms of viral infection, and thus, diagnostic accuracy has special clinical importance.
Relative sea level rise contributions to flood construction levels in British Columbia
Authors: Isaacson Michael
Published: April 2022

This paper proposes an updated approach to incorporating relative sea level rise in the estimation of flood construction levels in British Columbia, which are required in coastal planning and infrastructure development. Initially, current guidelines for British Columbia are outlined, and recent information on projected relative sea level rise is summarized. Then, recognizing the uncertainty in sea level rise projections, a probabilistic model of estimating the contribution of relative sea level rise to the flood construction level is described, relying on an available theoretical formulation that is corroborated by the application of a Monte Carlo simulation method. An updated approach to incorporating relative sea level rise in the estimation of flood construction levels is thereby recommended, relying on available data portals for relative sea level rise. Finally, the estimation of the probability of overtopping is described, and the implications of this for making informed decisions on flood construction levels with respect to risk assessments are indicated.
Irreducibly SU(2)-covariant quantum channels of low rank
Authors: Chang Euijung , Kim Jaeyoung , Kwak Hyesun , Lee Hun Hee , Youn Sang-Gyun
Published: April 2022

We investigate information theoretic properties of low rank (less than or equal to 3) quantum channels with [Formula: see text]-symmetry, where we have a complete description. We prove that PPT property coincides with entanglement-breaking property and that degradability seldomly holds in this class. In connection with these results, we will demonstrate how we can compute Holevo and coherent information of those channels. In particular, we exhibit a strong form of additivity violation of coherent information, which resembles the superactivation of coherent information of depolarizing channels.
Singular metrics with negative scalar curvature
Authors: Cheng Man-Chuen , Lee Man-Chun , Tam Luen-Fai
Published: April 2022

Motivated by the work of Li and Mantoulidis [C. Li, C. Mantoulidis, Positive scalar curvature with skeleton singularities, Math. Ann. 374(1–2) (2019) 99–131], we study singular metrics which are uniformly Euclidean [Formula: see text] on a compact manifold [Formula: see text] ([Formula: see text]) with negative Yamabe invariant [Formula: see text]. It is well known that if [Formula: see text] is a smooth metric on [Formula: see text] with unit volume and with scalar curvature [Formula: see text], then [Formula: see text] is Einstein. We show, in all dimensions, the same is true for metrics with edge singularities with cone angles [Formula: see text] along codimension-2 submanifolds. We also show in three dimensions, if the Yamabe invariant of connected sum of two copies of [Formula: see text] attains its minimum, then the same is true for [Formula: see text] metrics with isolated point singularities.
Hybrid Optimization Algorithm-Based Generative Adversarial Network for Change Detection Using Pre-Operative and Post-Operative MRI
Authors: Divya S , Padma Suresh L. , John Ansamma
Published: April 2022

Automatic detection of tumors is important to speed up treatment and to increase the survival rate of patients. In brain tumor detection, Magnetic Resonance Imaging (MRI) is considered an effective imaging model, which offers the internal structure of the brain. Change detection by pre-operative as well as post-operative multimodal images is an important research area in recent decades. Thus, this paper designs a hybrid optimization algorithm-based deep learning classifier to find the percentage of change detection in multimodal images. Initially, preprocessing is progressed to eradicate the noise from MRI images and then segmentation is performed using the modified DeepJoint model. After that, the pre-operative and the post-operative MRI images are engaged for the classification of a tumor. The classification of brain tumors is performed by Deep Convolutional Neural Network (Deep CNN) trained by a Tunicate Exponential Weighted Moving Average (TEWMA) algorithm, which is the integration of Tunicate Swarm Algorithm (TSA) and Exponential Weighted Moving Average (EWMA). After classification, the volume difference and the percentage of change detection are computed by GAN trained by PS-TEWMA, which is the integration of Particle Swarm Optimization (PSO) with TSA and EWMA. The proposed PS-TEWMA-based GAN obtained lower MSE and RMSE of 0.0881 and 0.2968 by measuring the volume detection. Also, it obtained minimal MSE and RMSE of 0.102 and 0.3194 concerning the percentage of change detection.
SHAPE CONTROL IN SURFACE PATTERNING ATOP SHAPE MEMORY POLYMERS VIA INDENTATION, POLISHING AND SHAPE RECOVERY
Authors: PRASAD AYUSH , HUANG WEI MIN
Published: April 2022

This study aims to analyze the surface pattern created on a shape memory polymer (SMP; thermoset polystyrene) after indentation by a spherical indenter, polishing off the top surface and recovery through the shape memory effect (SME) using the finite element method (FEM) and other computational techniques. Depending on how to polish, three different types of patterns are generated, namely the lens-type protrusion, flat-top protrusion and groove. The actual dimensions of the surface patterns are determined by the polishing depth and the coefficient of friction during indentation. The influence of the latter can be fixed if the coefficient of friction is over a certain value. All the lengths in this study are normalized with the respective indent depth. Hence the results can be scaled. The trends obtained here should be applicable to other shape memory polymers.
Characterization of some almost simple groups with socle PSp4(q) by their character degrees
Authors: Madady Moghadam Safoura , Iranmanesh Ali
Published: April 2022

Let [Formula: see text] be a finite group and [Formula: see text] denote the set of irreducible complex character degrees of [Formula: see text]. Suppose that [Formula: see text] is a projective conformal symplectic group [Formula: see text] for some prime power [Formula: see text]. The main result of this paper is to prove that if [Formula: see text], then [Formula: see text] is isomorphic to [Formula: see text]. This confirms a recent generalization of Huppert’s conjecture for the almost simple groups of Lie type.
Third-Order Nonlinear Optical Properties of CDTE Quantum Dots
Authors: Ramya Emusani , Rao D. Narayana
Published: April 2022

Size-dependent optical properties of semiconductor cadmium tellurite (CdTe) quantum dots (QDs) were examined by UV–Visible absorption, photoluminescence, Transmission electron microscope (TEM) and [Formula: see text]-scan. Red shift in the wavelength was observed in absorption and photoluminescence as the size increased. The size of the CdTe QDs is in the range between 3[Formula: see text]nm and 6[Formula: see text]nm. Two-photon absorption with reverse saturable absorption varied with size in picosecond region due to exciton oscillator. CdTe QDs can be used as optical limiters in the region of visibility.
Synthesis, Electrochemical and Antibacterial Studies of hexa-aza-macrocyclic Complexes of Ni(II) and Cu(II) Ions
Authors: Ravinder  , Das Dipak Kumar , Vashistha Vinod Kumar , Kumar Anuj
Published: April 2022

Due to their distinct structural, electrical, and electrochemical properties, macrocyclic complexes have been recognized as potential models in a variety of areas, including electrocatalysis, biology, and medicine. In this study, two hexa-aza-macrocyclic complexes of Ni(II) and Cu(II) transition metals (denoted as [NiL] and [CuL]) were synthesized via template procedure. Based on the results of multiple spectroscopic characterization, a distorted octahedral geometry was proposed for both the complexes. The electrochemical results showed that the macrocyclic framework can stabilize the unusual oxidation states of Ni(II) and Cu(II) transition metal ions, as evidenced by the corresponding quasi-reversible Ni(II)/(III) and Cu(II)/(III) redox couples. Additionally, both the complexes were found to be promising antibacterial agents against the B. subtilis, S. aureus, P. aeruginosa, and E. coli pathogens. The Cu(II) complex had the largest inhibition zone (22[Formula: see text]mm) against B. subtilis, while the Ni(II) complex had the smallest (15[Formula: see text]mm).
Monocular Vision-Based Localization and Pose Estimation with a Nudged Particle Filter and Ellipsoidal Confidence Tubes
Authors: Lin Tony X. , Coogan Samuel , Lofaro Daniel M. , Sofge Donald A. , Zhang Fumin
Published: April 2022

This paper proposes a nudged particle filter for estimating the pose of a camera mounted on flying robots collecting a video sequence. The nudged particle filter leverages two image-to-pose and pose-to-image neural networks trained in an auto-encoder fashion with a dataset of pose-labeled images. Given an image, the retrieved camera pose using the image-to-pose network serves as a special particle to nudge the set of particles generated from the particle filter while the pose-to-image network serves to compute the likelihoods of each particle. We demonstrate that such a nudging scheme effectively mitigates low likelihood samplings during the particle propagation step. Ellipsoidal confidence tubes are constructed from the set of particles to provide a computationally efficient bound on localization error. When an ellipsoidal tube self-intersects, the probability volume of the intersection can be significantly shrunken using a novel Dempster–Shafer probability mass assignment algorithm. Starting from the intersection, a loop closure procedure is developed to move backward in time to shrink the volumes of the entire ellipsoidal tube. Experimental results using the Georgia Tech Miniature Autonomous Blimp platform are provided to demonstrate the feasibility and effectiveness of the proposed algorithms in providing localization and pose estimation based on monocular vision.
Statistical Characterization of Seismic Signals
Authors: Smaragdakis Costas , Mastrokalos John , Taroudakis Michael I.
Published: April 2022

This paper presents a study on the applicability of a method for the statistical characterization of seismic signals which is based on the statistics of their wavelet sub-band coefficients using [Formula: see text] stable distributions. The method was originally applied to underwater acoustic signals of the type used in ocean acoustic tomography and seabed classification applications. The same protocol was applied to seismic signals representing the vertical displacement, measured on a traditional seismograph. The study showed that this process can indeed provide a means of characterizing a seismic signal and be used to estimate similarities between seismic signals, which is an important factor in studying seismic activity in an area.
MANN–KENDALL TREND DETECTION FOR PRECIPITATION AND TEMPERATURE IN BANGLADESH
Authors: DAS LIPON CHANDRA , MOHIUL ISLAM A. S. M. , GHOSH SANJIB
Published: April 2022

This study examined both long-term and short-term trends and fluctuations in rainfall and temperature over 34 meteorological stations located at seven regions in Bangladesh. Descriptive statistical analysis and Mann–Kendall trend test were utilized to investigate the variability of the rainfall and temperature of all stations in Bangladesh. Our research gave some insights into Bangladesh’s rainfall and temperature trends and variability.
Application of New Technology of Intelligent Robot Plant Protection in Ecological Agriculture
Authors: An Zhe , Wang Chunhang , Raj Bincy , Eswaran Sathyapriya , Raffik R. , Debnath Sandip , Rahin Saima Ahmed
Published: April 2022

Crop diseases, pest infestations, water shortages, weed infestations, and other issues affect the agriculture sector. Due to existing agricultural techniques, these issues result in significant crop loss, economic loss, and severe environmental hazards. Because agriculture is such a dynamic industry, robotics cannot solve all of its difficulties; instead, a single solution to a specific complex problem is supplied. To assist with these issues and provide a better approach globally, a variety of systems have been developed. Plant protection robots are characterized by complexity, constraint, and nonlinearity. In order to improve the accuracy and reliability of plant protection robots in agricultural job path planning, we propose a path planning method for agricultural plant protection robots based on a nonlinear algorithm. The ant colony algorithm was selected to plan the path distance index according to the working environment, and the feasibility of the simulation system was calculated. The results show that the fastest time used by the nonlinear algorithm is 5.3, and the path planning accuracy is up to 97.8%. Compared with the traditional algorithm, the algorithm has higher accuracy, less computing time, and higher computing efficiency.
Big Data Fusion Method Based on Internet of Things Collection
Authors: Zhang Tianrong , Li Hongying , Jin Tian , Hu Fengjun
Published: April 2022

With the development of information collection technology, the data that people need to deal with are also increasing, which brings problems such as isomerization of data types, poor data quality, and fast data generation speed. At present, as an important method of data fusion technology, data fusion method based on deep learning has become an effective way of data fusion under the background of big data, which has important research significance. There is a problem with heterogeneous data types between time series data and text data, and it is difficult to fuse them effectively by traditional data fusion methods. In order to make full use of the information contained in text data and improve the accuracy of time series prediction, this paper proposes a data fusion model based on FC-SAE. In this model, GloVe and CNN are used to extract the features of text data, FC neural network is used to extract the potential features of time series data, and then, the SEA model is used to fuse the data, which fully discovers the relationship between data and greatly improves the prediction accuracy.
Economic Policy Uncertainty and Sectoral Trading Volume in the U.S. Stock Market: Evidence from the COVID‐19 Crisis
Authors: Pak Dohyun , Choi Sun-Yong
Published: April 2022

We empirically analyze the impact of economic uncertainty due to the COVID‐19 pandemic on the trading volume of each sector in the S&P 500 index. Wavelet coherence analysis is carried out using economic policy uncertainty data and the trading volume of each sector in the S&P 500 index from July 2004 to September 2020. Furthermore, we apply multifractal detrended fluctuation (MF‐DFA) analysis to the trading volume series of all sectors. The wavelet coherence analysis shows that the COVID‐19 pandemic has substantially influenced trading volume in all sectors. However, the impact of the pandemic is different from that during the global financial crisis in some sectors, such as information technology, consumer discretionary, and communication services. Because of the lockdown taken to suppress COVID‐19, increased remote working and remote learning are the main reasons for these results. Additionally, according to the MF‐DFA analysis, the trading volume of all the sectors has clear multifractal characteristics, and they are all nonpersistent. Specifically, trading volumes of the real estate and materials sector are highly correlated, whereas the trading volumes of industry and information technology sectors are comparatively less correlated.
The Bacterial Profile and Antimicrobial Susceptibility Patterns of Urinary Tract Infection Patients at Pawe General Hospital, Northwest Ethiopia
Authors: Girma Abayeneh , Aemiro Aleka
Published: April 2022

Urinary tract infection remains the most common infection widespread worldwide in both community and hospital settings. Rapidly increasing antibiotic resistance of uropathogens is resulting in limited treatment options. Thus, understanding the current uropathogens and their antimicrobial susceptibilities is essential for effective urinary tract infection treatment. The purpose of this study was to isolate, characterize, and determine the antimicrobial susceptibility patterns of bacterial pathogens associated with urinary tract infection at Pawe General Hospital in Northwest Ethiopia. A hospital-based cross-sectional study design was conducted from January to April, 2020, at Pawe General Hospital. Midstream urine specimens were collected from 141 individuals with suspected urinary tract infection for bacteriological identification and antimicrobial susceptibility testing. Among the 141 study participants, twenty-nine (20.6%) showed significant bacteriuria. Escherichia coli (42.6%) had the highest proportion of isolated uropathogen followed by Klebsiella spp. and Pseudomonas spp. each (10.7%); Proteus spp. (9.3%); coagulase negative staphylococci, Staphylococcus aureus, and Enterobacter spp. each (6.7%); Citrobacter spp. (4%); and Enterococcus faecalis and Streptococcus spp. each (1.3%). Outpatient isolates showed a resistance of 64% and 78.6% to amoxicillin-clavulanic acid and tetracycline, respectively. Inpatients showed 63.9% and 87.2% of resistance to cephalexin and tetracycline. It was also observed that all the isolates have a multiple antimicrobial resistance index greater than 0.20 except Citrobacter spp. (0.142) in inpatients. Even though in this locality, most isolates were sensitive to ceftriaxone, gentamicin, ciprofloxacin, nitrofurantoin, and norfloxacin, they are considered appropriate antimicrobials for empirical treatment of urinary tract bacterial infections. Periodic monitoring of etiology and drug susceptibility is highly recommended, along with health education on the transmission and causes of urinary tract infection.
Analysis of the Role of HS-HKRVM Analytic Hierarchy Process in the Evaluation of English Teaching Quality
Authors: Li Hui
Published: April 2022

With the development of global market integration, the demand for English professionals in various industries is growing, and the professional standards for English professionals are also getting higher and higher. Therefore, English education is also faced with many opportunities and challenges; especially, the comprehensive education quality of English majors is becoming more and more prominent. The traditional teaching method using test scores as the evaluation standard leads to boring courses, students are not very interested in learning, and they cannot appreciate the charm of disciplines and majors, resulting in prominent problems in teaching form. This paper first analyzes the idea of the English learning quality evaluation system and then analyzes the English learning quality evaluation system based on HS-HKRVM. This paper also analyzes the construction of the English learning quality evaluation system based on the analysis layer process and finally studies the construction of the English learning quality evaluation system based on HS-HKRVM. Experiments show that HS-HKRVM can play a great role in the evaluation and improvement of English teaching quality.
Liraglutide Alleviates Diabetic Atherosclerosis through Regulating Calcification of Vascular Smooth Muscle Cells
Authors: Shi Li-Li , Hao Ming , Jin Zhou-Yun , Peng Gui-Fang , Tang Ying-Ying , Kuang Hong-Yu
Published: April 2022

Background. Diabetes mellitus (DM) is a group of metabolic diseases characterized by hyperglycemia, which can induce the development of atherosclerosis (AS). Calcification of vascular smooth muscle cells (VSMCs) exerts an important role in the process of AS. In this study, the effects of liraglutide (LIRA) on VSMC under high-glucose condition and its mechanism were explored. Method. After VSMC was treated by high glucose with or without LIRA in vitro, the alkaline phosphatase (ALP) activity was measured by the detection kit, osteogenic marker protein expression was detected by Western blotting, and calcification was determined by alizarin red staining. Subsequently, the DM rat model was established and the ALP activity, calcification, and osteogenic marker proteins were determined in vivo. Immunohistochemical (IHC) staining and hematoxylin-eosin staining were performed on the thoracic aorta of DM rats. Result. The positive rate of SMα-actin expression in the

DM
+
AS

group was significantly lower than that in control rats, but LIRA administration increased the positive rate in the model. The expression of Cbfα-1 and OPN in the

DM
+
AS

group was significantly higher than that in the control group, while it was decreased after treatment of LIRA. The ALP activity and calcium content were increased in

DM
+
AS

rats, and the treatment of LIRA decreased the phenotypes in the rats, so as to delay the progression of AS in DM rats. Meanwhile, LIRA inhibited the ALP activity, upregulated SM-α expression, and downregulated expression of OPN and Cbfα-1 in VSMC under high-glucose (HG) conditions. Mechanically, HG-enhanced ALP activity, AKT, and ERK phosphorylation were inhibited by LIRA, PI3K antagonist LY294002, or ERK1/2 antagonist PD98059, in which cotreatment of LIRA with LY294002 and PD98059 could further enhance the effect of LIRA on VSMC, and GLP-1R antagonists reversed the phenotypes in the model. LIRA blocked the osteogenic transformation of VSMC through PI3K and ERK1/2 signaling pathways, which can be reversed by GLP-1R antagonists. Conclusion. LIRA inhibited the abnormalities in VSMC calcification mediated by the GLP-1R, which was related to PI3K/Akt and ERK1/2 MAPK pathways. Therefore, the prospect and significance of LIRA in the treatment of DM complicated with AS were clarified.
Discordant Keratoconus in Monozygotic Twins
Authors: Bitton Karen , Dubois Mathieu , Moran Sarah , Gatinel Damien
Published: April 2022

We report a case of discordant keratoconus (KC) in a set of monozygotic twins with contrasting environmental risk factors. Twin one had bilateral, asymmetrical KC. He reported significant eye rubbing using his knuckles during his night-shift work as an emergency doctor. His usual sleeping position on the left side corresponded to the most affected eye. Twin two had normal corneas, with no evidence of KC. He reported mild infrequent eye rubbing, daytime work pattern, and a supine sleeping position. This case report highlights the influence of environmental and behavioural factors in the development of KC, in particular eye rubbing, night work, and sleeping position, in two individuals sharing identical genetic inheritance.
Novel Capped-Needle Device: A Novel Safety Feature to Eliminate Air Bubbles in Hemodialysis
Authors: Shibata Kazuhiko , Shinzato Takahiro , Toma Shigeki , Nakai Shigeru , Kobayashi Yusuke , Hashimoto Tatsuo , Tamura Koichi
Published: April 2022

Introduction: Air bubbles in the dialysis circuit are rarely visible after automatic priming; however, they are often visible after the needles are manually connected to the circuit. To prevent this issue, we thought to prime needles with a circuit at automatic priming by the hemodialysis machine. In order to achieve this idea, we designed and manufactured a novel capped needle to connect the needles to the extracorporeal circuit before the automatic priming of the hemodialysis machine. This study investigated the effectiveness of this novel capped needle and compared it with the conventional method for preventing air bubble contamination. Methods: We tested novel capped needles ten times to evaluate whether the dialysis machine works appropriately and removes air bubbles even with the attached capped needle. Next, we performed 25 trials using the conventional method, in which skilled nurses manually connect the needle. In both methods, we thoroughly counted the air bubbles with our naked eyes. We predicted that the capped needle would leave few bubbles in the circuit. In order to evaluate fewer bubbles, we conducted an additional experiment using a microparticle counter to measure the size and number of the bubbles. Results: We thoroughly searched for air bubbles during each of the ten tests but could not find any bubbles visible to the naked eye. In the conventional method, bubbles were visible in 29 out of 50 cases. The bubble count was significantly lower in the capped-needle method than in the conventional method (p < 0.0001, Pearson’s χ2 test). In the additional experiments using the microparticle counter, the average remaining air volume in the extracorporeal circuit was 0.0999 ± 0.2438 nL when the priming was performed using the novel capped needles. Conclusion: The novel capped needle eliminated all visible bubbles efficiently and effectively; therefore, it could be a valuable device for hemodialysis treatment. The reduction of air from the dialysis circuit may improve patient prognosis.
Rompiendo el paradigma en la oxigenoterapia
Authors: Ceballos-Zuñiga Cecilio Omar
Published: April 2022

Background: Oxygen (O2) is a drug with specific biochemical and physiological properties, a range of effective doses and may have side effects. In 2015, 14% of over 55,000 hospital patients in the UK were using oxygen. 42% of patients received this supplemental oxygen without a valid prescription. Health care professionals are frequently uncertain about the relevance of hypoxemia and have low awareness about the risks of hyperoxemia. Numerous randomized controlled trials about targets of oxygen therapy have been published in recent years. A national guideline is urgently needed. Methods: A national S3 guideline was developed and published within the Program for National Disease Management Guidelines (AWMF) with participation of 10 medical associations. A literature search was performed until February 1, 2021, to answer 10 key questions. The Oxford Centre for Evidence-Based Medicine (CEBM) System («The Oxford 2011 Levels of Evidence») was used to classify types of studies in terms of validity. Grading of Recommendations, Assessment, Development and Evaluation (GRADE) was used for assessing the quality of evidence and for grading guideline recommendation, and a formal consensus-building process was performed. Results: The guideline includes 34 evidence-based recommendations about indications, prescription, monitoring and discontinuation of oxygen therapy in acute care. The main indication for O2 therapy is hypoxemia. In acute care both hypoxemia and hyperoxemia should be avoided. Hyperoxemia also seems to be associated with increased mortality, especially in patients with hypercapnia. The guideline provides recommended target oxygen saturation for acute medicine without differentiating between diagnoses. Target ranges for oxygen saturation are based depending on ventilation status risk for hypercapnia. The guideline provides an overview of available oxygen delivery systems and includes recommendations for their selection based on patient safety and comfort. Conclusion: This is the first national guideline on the use of oxygen in acute care. It addresses health care professionals using oxygen in acute out-of-hospital and in-hospital settings.
Epidemiology of de novo Acute Myeloid Leukemia in Kuwait per the 2016 WHO Classification
Authors: Alshemmari Salem H. , Almazyad Mazyad , Ram Mohan , John Liby Mariamma , Alhuraiji Ahmed
Published: April 2022

Objective: Acute myeloid leukemia (AML) is a hematological malignancy that arises from the clonal proliferation of immature myeloid cells. Although the number of AML cases has dramatically increased worldwide, information on its prevalence and incidence in Kuwait is lacking. This study reports the incidence of AML and patient demographics in the country from 2014 to 2020, based on the 2016 WHO classification of AML. Subjects and Methods: Data on patients with AML, including acute promyelocytic leukemia (APL), were collected from a clinical cohort with 281 cases analyzed in this study. Results: The overall median age of the population was 47 years with a 1.1:1 male-to-female ratio. Over the study period, the incidence of AML demonstrated a general increasing trend, with the highest and lowest overall incidence occurring in 2018 and 2015, respectively. The frequency of APL in our cohort was 8.9%. Regarding the 2017 European LeukemiaNet (ELN) risk stratification of patients with AML, 37%, 46%, and 17% of patients had a favorable, intermediate, and adverse risk, respectively. A total of 57% of cases achieved complete remission post-induction, and the median overall survival was 37 months. Conclusion: Our study may help predict the future trends of AML in Kuwait to help improve clinical management and patient outcomes.
“From So Simple a Beginning”: Species of Artificial
Intelligence
Authors: Shadbolt Nigel
Published: April 2022

Artificial intelligence has a decades-long history that exhibits alternating enthusiasm and disillusionment for the field's scientific insights, technical accomplishments, and socioeconomic impact. Recent achievements have seen renewed claims for the transformative and disruptive effects of AI. Reviewing the history and current state of the art reveals a broad repertoire of methods and techniques developed by AI researchers. In particular, modern machine learning methods have enabled a series of AI systems to achieve superhuman performance. The exponential increases in computing power, open-source software, available data, and embedded services have been crucial to this success. At the same time, there is growing unease around whether the behavior of these systems can be rendered transparent, explainable, unbiased, and accountable. One consequence of recent AI accomplishments is a renaissance of interest around the ethics of such systems. More generally, our AI systems remain singular task-achieving architectures, often termed narrow AI. I will argue that artificial general intelligence-able to range across widely differing tasks and contexts-is unlikely to be developed, or emerge, any time soon.
I Do Not Think It Means What You Think It Means: Artificial Intelligence,
Cognitive Work & Scale
Authors: Scott Kevin
Published: April 2022

Over the past decade, AI technologies have advanced by leaps and bounds. Progress has been so fast, voluminous, and varied that it can be a challenge even for experts to make sense of it all. In this essay, I propose a framework for thinking about AI systems, specifically the idea that they are ultimately tools developed by humans to help other humans perform an increasing breadth of their cognitive work. Our AI systems for assisting us with our cognitive work have become more capable and general over the past few years. This is in part due to a confluence of novel AI algorithms and the availability of massive amounts of data and compute. From this, researchers and engineers have been able to construct large, general models that serve as flexible and powerful building blocks that can be composed with other software to drive breakthroughs in the natural and physical sciences, to solve hard optimization and strategy problems, to perform perception tasks, and even to assist with complex cognitive tasks like coding.
The Machines from Our Future
Authors: Rus Daniela
Published: April 2022

While the last sixty years have defined the field of industrial robots and empowered hard-bodied robots to execute complex assembly tasks in constrained industrial settings, the next sixty years will usher in our time with pervasive robots that come in a diversity of forms and materials and help people with physical tasks. The past sixty years have mostly been inspired by the human form, but the form diversity of the animal kingdom has broader potential. With the development of soft materials, machines and materials are coming closer together: machines are becoming compliant and fluid-like materials, and materials are becoming more intelligent. This progression raises the question: what will be the machines from our future?
Socializing Data
Authors: Coyle Diane
Published: April 2022

Will the proliferation of data enable AI to deliver progress? An ever-growing swath of life is available as digitally captured and stored data records. Effective government, business management, and even personal life are increasingly suggested to be a matter of using AI to interpret and act on the data. This optimism should be tempered with caution. Data cannot capture much of the richness of life, and while AI has great potential for beneficial uses, its delivery of progress in any human sense will depend on not using all the data that can be collected. Moreover, the more digital technology rewires society, creating opportunities for the use of big data and AI, the greater the need for trust and human deliberation.
Reinforcement Technique for Deploying Intelligent Delay Tolerant Network
Authors: Narula Gaurav , Sheikh Tariq Hussain , Nagrath Preeti , Khanna Ashish
Published: April 2022

The erratic environment of Vehicular ad-hoc network (VANET), specifically in challenged areas like military or battle fields, may lose the data while forwarding certain important multimedia files. As we know Vehicular Delay Tolerant Network (VDTNs) lack permanent grid power connections
so to optimize the use of the power of nodes, reinforcement learning techniques to can be applied to the base stations/roadside units (RSUs). The RSUs learn to pick a vehicle based on information gathered about traffic characteristics, budget for infrastructure resources, and the total duration
of a contact time. Based on the cumulative knowledge a compensation metric is evaluated. This acts as a performance metric to determine which vehicular node to select for message forwarding. To make decisions based on observations made by RSUs analyses by applying deep reinforcement learning
augments. This saves the power of the nodes. This novel energy efficient technique by deploying secure, intelligent mechanisms in the vehicular nodes is proposed, which significantly improves the processing of files in the challenges networks. For simulation purpose, a real-time data set is
taken from the crawdad website. Experimental results show that after applying reinforcement technique, there is an increase in 28% of message delivery, decrease in latency of 16% and reduction of 21% in energy consumption.
The Effect of Icing on Hamstring Muscle with Nordic Hamstring Exercise
Authors: Kwon Soo-An , Kwon Hae-Bin , Jung Si-Hyun , Jeon Jeongwoo , Hong Jiheon , Yu Jae-Ho , Kim Jin-Seop , Lee Dong-Yeop
Published: April 2022

The purpose of this study was the effect of icing on the muscle activity of Hamstring muscles during Nordic Hamstring Exercise after applying the icing. Twenty-eight healthy men participated in this study. Subjects were assigned to experiment and control groups. Nordic Hamstring Exercise
was practiced to the experiment and the control groups without applying the icing. The control group rested for 20 minutes with no intervention, while the experiment group was applied 20 minutes of icing. Then Nordic Hamstring Exercise was performed again to compare the differences in muscle
activity between the two groups. No significant differences in muscle activity were observed in the control group. However, In the experimental group, significant differences in muscle activity were found pre and post icing. There were also significant differences between the two groups. In
conclusion, icing is considered to have a positive effect on promoting hamstring muscle activity.
Proposal of Classified Music Recommendation Model Based on Social Media
Authors: Chung Kyoung-Rock , Park Koo-Rack , Chung Young-Suk
Published: April 2022

With the spread of smartphones, it has become common to always listen to music like background music, so it is necessary to create a music database that meets individual needs. By creating a music database using data from social media, music is classified in a different way from collaborative
filtering, which is mainly used by existing music source providing platforms. Various other hashtags attached to posts with music titles used as hashtags are collected using web crawling, and music is classified based on the collected hashtags to reflect actual listeners’ opinions on
music. It uses crawling to find posts on social media with music titles tagged as hashtags, then collects other hashtags attached to those posts. Hashtags collected by performing the same task with multiple music titles are collected, analyzed, and statistics are then classified to determine
when and where the music fits. On social media, the feelings of the person who posted the post and the conditions such as the time zone, place, weather, and situation where the post was posted are reflected as hashtags. By analyzing the hashtags attached to the music title, it is possible
to build a social media-based music database in which the opinions of various people are reflected as collective intelligence. It is possible to derive different results from existing collaborative filtering based on the past listening records of users of the platform used by most of the sound
source providing platforms. Even if music titles are not written in complete form on social media hashtags, we plan to research them so that they can be used to build a database.