bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Electron-Beam Radiation on the Dielectric Properties of PVA/xNiO Nanocomposite for Energy Storage Applications
Authors: Zaghlool R. A. , Moghny A. S. Abdel , Ghobashy M. M. , Nabhan E.
Published: January 2022

For energy storage applications, a material that has high dielectric permittivity, low loss factor, strong thermal resistance, easy processability, and low cost is highly desirable. In the present study, PVA/xNiO nanocomposite films with different NiO contents of (0, 10, and 50) wt% were prepared by casting technique. The PVA/xNiO of 50 wt% NiO has been irradiated with 3 MeV electron beam at a dose of 50 kGy at room temperature in order to investigate the modifications induced in its dielectric properties. The results show that the NiO nanoparticles are well incorporated inside the PVA matrix and the crystallite size of NiO has been decreased upon doping by 50 wt% NiO from 15.45 to 11.44 nm. Also, PVA/(50%)NiO nanocomposite shows indirect allowed optical transition (3.43 eV) with relatively high dielectric constant (7.60 to 9.55) and low loss factor (<0.1) at high frequency (1 MHz) and the entire indicated range of temperature which proposes to use this material in energy storage applications. The electron beam radiation has increased the dielectric constant (10.52 to 13.94) which is preferable. However, a slight increase is observed in the loss factor (<0.109).
FoxO4 controls sGCβ transcription in vascular smooth muscle
Authors: Galley Joseph C. , Miller Megan P. , Sanker Subramaniam , Liu Mingjun , Sharina Iraida , Martin Emil , Gomez Delphine , Straub Adam C.
Published: January 2022

One of the key mechanisms of vascular smooth muscle cell (SMC) dilation occurs through nitric oxide (NO)-dependent induction of soluble guanylyl cyclase (sGC) by means of its β-subunit. Herein, we are the first to identify Forkhead box subclass O protein 4 (FoxO4) as a key transcriptional regulator of GUCY1B3 expression, which codes for sGCβ protein in human and animal SMCs. This discovery will likely have important implications for the future usage of antihypertensive and vasodilatory therapies which target NO production, sGC, or FoxO transcription factors.
Design, Preparation, and Evaluation of Enteric Coating Formulation of HPMC and Eudragit L100 on Carboxylated Agarose Hydrogel by Using Drug Tartrazine
Authors: Khan Muhammad Junaid , Huang Wen-Can , Akhlaq Muhammad , Raza Sajid , Hamadou Alkassoumi Hassane , Yuning Guo , Sun Jianan , Mao Xiangzhao
Published: January 2022

Enteric‐coated application on drug is used to prevent the drug from inactivation which are degraded by gastric enzyme. The present study is aimed at achieving controlled drug delivery in acidic medium of gastrointestinal tract (GIT) by enteric coating of hydroxy propyl methylcellulose (HPMC) and Eudragit L100 on carboxylated agarose hydrogel, creating a pH‐dependent delivery system. Fourier‐transformed infrared spectroscopy (FTIR) was for the detection of carboxylic group on agarose hydrogel, and scanning electron microscope (SEM) was used for the determination surface of prepared formulation. To check the pH sensitivity of enteric‐coated formulation, different pH solution was used. It was found that the formulation was not dissolved in 1.2 but dissolve in pH 6.8 similarly; hydrogels lacking coating showed that tartrazine was more dissolved in pH 1.2, and less dissolved at pH 6.8. The release of tartrazine from the hydrogels was measured by using spectrophotometer and using a scanning electron microscope to examine the morphology and surface appearance of hydrogel capsules. This study revealed cracks on coated samples, while noncoated samples showed clear appearance with no cracks. Our findings revealed that this method could be useful for the development of an enteric coating drug delivery system.
Quality Evaluation of Saposhnikovia divaricata (Turcz.) Schischk from Different Origins Based on HPLC Fingerprint and Chemometrics
Authors: Chen Yuqiu , Xu Zhefeng , Gao Siying , Zhang Tao , Chen Changbao
Published: January 2022

A valid and encyclopedic evaluation method for assessing the quality of Saposhnikovia divaricata has been set up based on the analysis of a high-performance liquid chromatography (HPLC) fingerprint combined with the cluster analysis (CA), principal component analysis (PCA), partial least square discriminant analysis (PLS-DA), and similarity analysis. 15 peaks of the common model were obtained and used for the similarity analysis, CA analysis, PCA analysis, and PLS-DA analysis. The fingerprint of S. divaricata was established, and 15 common peaks were calibrated. The four common peaks were identified as prim-o-glucosylcimifugin, 4-O-β-D-glucosyl-5-O-methylvisamminol, cimifugin, and sec-o-glucosylhamaudol by comparison with the reference substance. The similarity of the fingerprints of the 33 batches of S. divaricata is above 0.9. Cluster analysis divides the 33 batches of S. divaricata into 2 categories. Principal component analysis (PCA) roughly divides them into 4 categories. Partial least squares method-discriminant analysis (PLS-DA) screened to obtain 2 differential markers, the different components were designated by the reference substance as 4-O-β-D-glucosyl-5-O-methylvisamminol and cimifugin. The fingerprint established by this study combined with chemometrics analysis is reasonable, effective, accurate, and simple, which makes the information more comprehensive and can provide a scientific basis and reference for quality control and quality evaluation of S. divaricata.
Comparison of Biochemical Parameters between Mouse Model and Human after Paraquat Poisoning
Authors: Yu Jielun , Zhang Lichun , Li Xiaoshuang , Lv Kaixuan , Sun Shiyu , Wu Weihua , Ping Lifeng , Guo Guifang , Tan Wei , Guo Shoudong , Wang Kezhou , Zhao Aihua , Yang Nana
Published: January 2022

Background. This study was designed to investigate differences in biochemical parameters between mouse and humans after paraquat (PQ) poisoning and develop a suitable animal model for studying organ damage after PQ poisoning. The prognostic factors of PQ‐poisoned patients were further analyzed. Methods. Thirty C57BL/6J mice were randomly divided into five groups (control, sham, and 3 PQ doses), and the mouse model was established by intragastric administration of PQ. Physiological indexes such as the body weight, mental state, and mortality rate were observed. Biochemical parameters were analyzed 24 h after PQ poisoning. We also performed a retrospective analysis of clinical data from 29 patients with PQ poisoning admitted to the Emergency Department of the Affiliated Hospital of Taishan Medical College between April 2016 and February 2018. Biochemical parameters were compared between the mouse model and patients with PQ poisoning. Results. In the PQ poisoning mouse model, the lethal dose group PQ360 showed remarkable increases in serum levels of potassium (K+), carbon dioxide (CO2), alanine aminotransferase (ALT), and aspartate aminotransferase (AST) compared with the nonlethal dose PQ100 and PQ200 groups. The biochemical results of the patients showed that K+ and Cl- levels were significantly reduced in the death group compared to the survival group. Levels of ALT, AST, blood urea nitrogen (BUN), and amylase were higher, and the neutrophil‐to‐lymphocyte ratio (NLR) was increased in the death group compared with the survival group. Conclusions. The combination of age, PQ dosage, K+, Cl-, BUN, ALT, AST, amylase, and NLR can be used to more accurately predict the outcome of patients with PQ poisoning. C57 mice are an appropriate animal model to study liver and kidney functions following PQ exposure.
Effects of Indwelling Pleural Catheter on Severe Acute Pancreatitis: A Retrospective Study
Authors: Yao Qian , Peng Siyang , Wu Yanping , Liu Pi
Published: January 2022

Background. Pleural effusion (PE) is an important predictor for severity and prognosis of severe acute pancreatitis (SAP). However, there are few studies focused on the effects and timing of indwelling pleural catheter (IPC) on SAP. Considering this, we designed a retrospective study to verify the relationship between PE and severity of SAP and observe the effects and timing of IPC in SAP. Methods. A total of 309 SAP patients were enrolled. Based on the presence or absence of PE and IPC and IPC time, the enrolled patients were divided into 6 groups. Then, baseline parameters, disease severity, critical complications, ventilator supporting time (VST), length of stay (LOS), and 60-day mortality were compared between each two groups. Results. PE was a risk factor for death of SAP, but not an independent risk factor. SAP patients with PE rather without PE had higher critical complication rates (

p
<
0.001

), along with longer VST (

p
<
0.001

) and LOS (

p
<
0.001

). And the critical complication rates were lower in group 1 (IPC within 1 week of onset) than group 2 (IPC after 1 week of onset). Further, patients in group 1 also had shorter LOS (

p
=
0.042

) and VST (

p
=
0.001

) than those in group 2. In addition, the survival analysis showed the risk of death in the PE group was higher than the non-PE group (HR 6.6, 95% CI, 3.67–11.86, and

p
<
0.001

). And the risk of death in group 1 was lower than group 2 (HR 0.26, 95% CI, 0.08–0.84, and

p
=
0.025

). Conclusions. PE is a risk factor for death of SAP, but not an independent risk factor. IPC, especially IPC within 1 week of onset, has clinical practical value in SAP.
Auction-Based Capacity Allocation in Two Parallel Machines with Inclusive Processing Set Restrictions
Authors: Zhu Qianqian , Wang Xiuli
Published: January 2022

We consider the scarce capacity allocation problem in two parallel machines with inclusive processing set restrictions. Our focus is to design an auction mechanism to allocate the production capacity among several selfish customers effectively and efficiently. In our iterative ascending auction mechanism, we need to design jointly two things: who wins what and who pays what. First, we propose an adaptive ascending pricing policy to ensure that bidding by truthful processing requirements and keeping on bidding until the ask prices reach his real revenue is a dominant strategy for each customer. Second, we establish a facility owner’s profit maximization model to determine the capacity allocation in two parallel machines with inclusive processing set restrictions; it is an NP hard problem; we also develop a heuristic based on the Lagrangian relaxation technology to obtain the suboptimal solutions. Our computational analysis shows that the auction mechanism can achieve more than 87% of the global system value.
Recent Advances in the Development of Noble Metal NPs for Cancer Therapy
Authors: Zhao Rui , Xiang Jia , Wang Bo , Chen Lin , Tan Songwen
Published: January 2022

With the development of nanotechnology, noble metal nanoparticles are widely used in the treatment of cancer due to their unique optical properties, excellent biocompatibility, surface effects, and small size effects. In recent years, researchers have designed and synthesized a large number of nanomedicines that can be used for cancer treatment based on the morphology, physical and chemical properties, mechanism of action, and toxicological studies of noble metal nanoparticles. Furthermore, the integration of diagnosis and treatment, hyperthermia, cytotoxicity research, and drug delivery system based on the study of noble metal nanoparticles can be used as effective means for cancer treatment. This article focuses on the analysis of noble metal nanoparticles that are widely used in the treatment of cancer, such as gold nanoparticles, silver nanoparticles, platinum nanoparticles, and palladium nanoparticles. The various methods and mechanisms of action of noble metal nanoparticles in the treatment of cancer are objectively summarized in detail. Based on the research on the therapeutic safety and toxicity of noble metal nanoparticles, the development prospect of noble metal nanoparticles in the future clinical application is prospected.
Effective Prediction of Monthly Heat Transfer Characteristics in a Thin-Layer Cascade Reactor Subjected to Outdoor Conditions
Authors: Akhtar Shehnaz , Ali Haider , Park Cheol Woo
Published: January 2022

Algal biofuels are intriguingly a renewable energy source that could partially substitute fossil fuels, but further research is required to optimise the growth parameters and establish competitive large-scale cultivation systems. Algal growth is directly dependent on momentum, heat, and mass transfer within the photobioreactor and environmental conditions. Therefore, in this computational study, the heat transfer between the thin-layer cascade (TLC) reactor and its surrounding was reported based on static (location and reactor geometry) and dynamic (air temperature, solar irradiance, and wind velocity) parameters. The resulting model was validated using experimental data. The Nusselt number and the monthly average water temperature were computed to investigate the heat transfer phenomena between the TLC reactor and atmosphere. In addition, a novel corelation was used to estimate the evaporative losses from the TLC reactor. The effect of geometric properties (inclination angle of the reactor, water depth, and channel width) was evaluated on heat transfer. Results showed that heat transfer rate and the optimum water temperature for algal growth were significantly affected by hydrodynamics, environmental conditions, and reactor design. Water temperature decreased with the increase in channel width, water depth, and slope angle of the reactor. Furthermore, algal productivity declined with the increase in the amount of evaporated water.
Hypermagnesaemia, but Not Hypomagnesaemia, Is a Predictor of Inpatient Mortality in Critically Ill Children with Sepsis
Authors: Wang Huabin , Huang Junbin , Jin Xinghan , Chen Chunmei , Zhang Airun , Wu Yuhui , Chen Chun
Published: January 2022

Objective. The effect of serum magnesium on the prognosis of children with sepsis in the pediatric intensive care unit (PICU) is unclear. This study was designed to assess the risk of inpatient mortality for children with sepsis in the PICU based on serum magnesium levels at admission. Methods. We collected patients’ clinical information from the Pediatric Intensive Care database and then performed locally weighted scatterplot smoothing (LOWESS) analysis, Kaplan–Meier analysis, and multivariate logistic regression to determine the relationship between admission serum magnesium and inpatient mortality in children with sepsis. Results. A total of 974 critically ill children with sepsis were included, with 246 patients in the hypomagnesemia group, 666 in the normal group, and 62 in the hypermagnesemia group. The chi-square test suggested that the hypermagnesemia group had higher in-hospital mortality than the normal group (14.5% vs. 2.4%,

P
<
0.001

). Kaplan–Meier curves revealed that the 30-day overall survival rate was lower in the hypermagnesaemia group than in the normal group (

P
<
0.001

). The multivariate logistic regression model revealed that hypermagnesaemia was a risk factor related to inpatient mortality (odds ratio 4.22, 95% CI 1.55-11.50), while hypomagnesaemia was not a significant factor for inpatient mortality (odds ratio 0.78, 95% CI 0.26-2.32). Conclusion. Hypermagnesaemia, but not hypomagnesaemia, is a predictor of inpatient mortality in critically ill children with sepsis.
Prognostic Role of Biomarkers for Pulmonary Arterial Hypertension Associated with Bronchopulmonary Dysplasia in Extremely Premature Infants
Authors: Chen Chun , Lin Bingchun , Wang Meiqi , Yang Chuanzhong
Published: January 2022

To explore the association of the biochemical markers after birth with BPD-PAH, factors independently predicting BPD-PAH risk were identified by multivariate logistic regression. Cut off values were determined by plotting receiver-operator curve (ROC), for the sake of dichotomizing continuous variables that showed independent relation with BPD-PAH risk. The results show that uric acid (UC) and blood urea nitrogen (BUN) contents markedly increased among infants experiencing BPD-PAH in comparison with those without BPD-PAH (11.6 vs. 9.7 mmol/L,

P
=
0.006

and 482.0 vs. 249.0

μ

mol/L,

P
<
0.001

, separately). As shown by multivariate logistic regression, serum BUN levels (

OR
=
1.143

) and uric acid levels (

OR
=
1.034

) were important risk factors for BPD-PAH. Through a lot of experiments, the effectiveness and the advanced nature of the framework proposed in this paper are proved effectively. The framework proposed in this paper can provide some reference and thinking for follow-up research.
Experimental Performance Analysis of a Pilot-Scale Biomass-Assisted Recirculating Mixed-Flow Dryer for Drying Paddy
Authors: Yahya M. , Fahmi Hendriwan , Hasibuan R.
Published: January 2022

A large amount of heat energy is required for paddy drying processes to evaporate water from paddy grains. Currently, fossil fuels are being used as an energy source to heat air during the drying process. However, fossil fuels cause air pollution, climate change, and disruption of ecological balance. In this study, to reduce the dependence on fossil fuels for paddy drying, a pilot-scale biomass-assisted recirculating mixed-flow drying system (PSBA-RMFD) for drying paddy was designed, installed, and tested. In this PSBA-RMFD, the heat energy required for heating the drying air was provided only by biomass. The PSBA-RMFD comprises a biomass furnace, drying column, vibratory feeder, bucket elevator, and blower. This study is aimed at evaluating the performance of the PSBA-RMFD with a drying capacity of 400 kg/h. The performance metrics of the PSBA-RMFD were specific energy consumption (SEC), specific thermal energy consumption (STEC), specific moisture evaporation rate (SMER), thermal efficiency of the PSBA-RMFD, exergy efficiency of the drying section, and improvement potential of the dryer. From the experiments conducted in this study, the values of the aforementioned performance parameters were as follows: 0.806-8.656 kW h/kg of water evaporated; 0.385-4.136 kW h/kg of water evaporated; 0.122-1.308 kg of water evaporated/kW h; 7.82-83.99%; 15.28-25.64%; and 858.90-1355.62 W, respectively. The paddy moisture content was reduced from 20.90% wet basis (initial weight of 400 kg) to 13.30% wet basis (final weight of 364 kg) in 270 min, with an average temperature of 78.15°C and average relative humidity of 8.55%. The percentage of biomass energy used in the drying system was approximately 47.77% of the overall energy. In addition, the payback period of the PSBA-RMFD was 1.9 years.
Evaluation of Cardiac Function of Pregnant Women with High Blood Pressure during Gestation Period and Coupling of Hearts with Peripheral Vessels by Ultrasonic Cardiogram under Artificial Intelligence Algorithm
Authors: Zhang Xia , Liang Xi , Cao Wen
Published: January 2022

The research was aimed at analyzing the value of the optimized eXtreme Gradient Boosting (XGBoost) algorithm-based ultrasound cardiogram images in the diagnosis of pregnant hypertension patients. A total of 145 pregnant women (85 cases suffered from hypertension disease during pregnancy and 60 other normal women were healthy) were selected as the reference to the comparison and analysis of ultrasound cardiac function parameter, common carotid artery parameter, and the coupling relationship between hearts and cervical vessels of pregnant hypertension patients. The results demonstrated ultrasound cardiac function parameter of pregnant hypertension patients as follows. The maximum volume of the left atrium (LAVmax) was 35.65 mm, left ventricular end-systolic volume (LVESV) was 31.07 mm, and left ventricular end-diastolic volume (LVEDV) was 88.73 mm. All the above indexes were obviously higher than those of the normal control group (

P
<
0.05

). Besides, intima-media thickness (IMT) of common carotid artery (465.84 μm), pulse wave velocity (PWV) (8.09 m/s), pressure of turning point 1 from isovolumic contraction phase to ejection phase (PT1) (126.5 mmHg), arterial enhancement pressure (AP) (6.14 mmHg), and arterial pressure enhancement index (8.58%) were all significantly higher than those of the normal control group (

P
<
0.05

). In addition, the correlation between the coupling (

E
/
A

) of hearts and carotid artery of pregnant hypertension patients and PWV was not obvious (

r
=
−
0.08432

,

P
>
0.05

). The results of the research indicated that intima-media inside carotid artery of pregnant hypertension patients thickened obviously, and it became less elastic compared with that of normal healthy pregnant women. What is more, cardiac morphological changes were manifested mainly as the enlargement of the left atrial chamber and the thickening of the interventricular septum. Volume load and blood flow velocity both increased, and left ventricular diastolic function was damaged. XGBoost algorithm-based ultrasound cardiogram images could improve the diagnostic effects of hypertension during pregnancy effectively.
Collaborative Research on Mouth Shape and Lyrics in Singing Practice Based on Image Processing
Authors: Xu Lujia , Chen Chen
Published: January 2022

Image processing is a mainstream processing method. When people enjoy artists’ singing videos, there will be a problem that the subtitles of the lyrics are out of sync with the singer’s mouth shape. This problem needs to be solved using image processing technology, letting the computer realize lip-reading recognition function and correct the mouth shape and lyrics subtitles in the image according to the extracted lip-reading data, so that the mouth shape and lyrics in singing practice can be synchronized. Lip-reading information can effectively improve the accuracy of language cognition, save part of capital and manpower investment, and make viewers get a good audio-visual interactive experience. The results show the following: (1) After the UI test, the system user interface function design is reasonable and there is no bad BUG. We can find that the average processing time of each frame is 628 ms, the system performance evaluation is good, and the success rate can be as high as 98.80%. 0.36724 s is the average time for each step when the system processes the image. (2) The human image can basically identify the portrait area and lip area from various angles. (3) Compared with DCT and DWT, the recognition rate of the two cascade lip region feature extraction methods is improved by nearly 10%, and the feature vector dimension is reduced by nearly 65%. (4) Classify the mouth shape more finely and optimize the image of the tester’s mouth shape to make the mouth shape closer to the standard mouth shape. (5) After systematic correction of mouth shape and subtitles, the success rate is higher than 90%. Finally, we can find that the running effect is good and the method has achieved high results, which can carry out the details of the next optimization work.
Identification and Verification of Tumor Immune Microenvironment‐Related Prognostic Genes in Kidney Renal Clear Cell Carcinoma
Authors: Kong Gangcheng , Wang Yixuan , Huang Yuanjian , Shi Zhen
Published: January 2022

Background. The tumor immune microenvironment is vital to kidney renal clear cell carcinoma (KIRC) progression, and immunotherapies have been shown to be effective in the management of KIRC. However, the prognostic genes associated with the tumor immune microenvironment in KIRC have not been fully identified. We obtained the KIRC RNA sequencing data and the clinical characteristics from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) database. We screened the gene modules associated with the tumor immune microenvironment based on the ESTIMATE algorithm and weighted gene coexpression network analysis (WGCNA). Univariate Cox analysis and the LASSO method were used to construct a prognostic model. Receiver Operating Characteristic (ROC) curve analysis was performed to evaluate the accuracy of our risk model. TIMER and Single‐Sample Gene Set Enrichment Analysis (ssGSEA) were used to explore the correlation between prognostic genes and immune cell infiltration. Results. Fifty‐four genes in modules were significantly associated with the overall survival (OS) time of patients with KIRC. Furthermore, 12 hub genes were selected to construct the prognostic model. The prognostic model showed superior accuracy in both TCGA and ICGC cohorts using ROC curve analysis. Systematic analysis of immune cell infiltration revealed that nine genes were significantly correlated with levels of tumor‐infiltrating immune cells. Conclusions. Our findings indicated that the tumor immune microenvironment was an important determinant of KIRC outcomes and revealed potential biomarkers for predicting patient OS and for targeted immunotherapies.
Role of Nanoparticles in Biodegradation and Their Importance in Environmental and Biomedical Applications
Authors: Remya R. R. , Julius Angeline , Suman T. Y. , Mohanavel V. , Karthick Alagar , Pazhanimuthu C. , Samrot Antony V. , Muhibbullah M.
Published: January 2022

In recent decades, research in nanomaterial specific to biodegradation has gained attraction owing to its physicochemical characteristics. Biodegradation is the main strategy used in the management of wastes. The role of nanoparticles helps in controlling the biodegradation rate. The biodegradation might not be quite effective in certain cases like high chemical deposition, due to its toxic nature towards microorganisms. The conventional strategies demonstrated a limited use of nature source, and this could be overcome through microbes and enzyme‐based biodegradation. Nanoparticles have improved the biodegradation rate through low‐density polyethylene development, thereby corrupting microbes. Thus, a major problem is confronted. Though innovation in science had a great impact in everyone’s life, it also has a negative impact through the increased use of toxic materials. Recent development and use of biodegradable nano‐based compounds have led to many secured forms of nanomedicines. In this review, we would discuss the more recent findings of nanoparticles related to biodegradation applications and elaborate how their characteristics could influence in various biomedical applications.
Lattice Points on the Fermat Factorization Method
Authors: Babindamana Regis Freguin , Bansimba Gilda Rech , Richard Bossoto Basile Guy
Published: January 2022

In this paper, we study algebraic properties of lattice points of the arc on the conics x2 − dy2 = N especially for d = 1, which is the Fermat factorization equation that is the main idea of many important factorization methods like the quadratic field sieve, using arithmetical results of a particular hyperbola parametrization. As a result, we present a generalization of the forms, the cardinal, and the distribution of its lattice points over the integers. In particular, we prove that if (N − 6) ≡ 0 mod 4, Fermat’s method fails. Otherwise, in terms of cardinality, it has, respectively, 4, 8, 2(α + 1), , and lattice pointts if N is an odd prime, N = Na × Nb with Na and Nb being odd primes, with Na being prime, with pi being distinct primes, and with Ni being odd primes. These results are important since they provide further arithmetical understanding and information on the integer solutions revealing factors of N. These results could be particularly investigated for the purpose of improving the underlying integer factorization methods.
Taxi Dispatch Optimization in Smart Cities Using TOPSIS
Authors: Abid Adnan , Nawaz Naeem A. , Farooq Muhammad Shoaib , Farooq Uzma , Abid Irfan , Obaid Iqra
Published: January 2022

The modern smart cities demand an efficient taxi dispatch system to satisfy the expectations of the passengers while giving justified rides to the drivers. Many a time, the customers have to wait too long for a taxi and the taxi driver wastes a lot of his time and the fuel in finding customers. Furthermore, some customers cancel the ride for not finding suitable category of taxi. Though there exist some algorithms that aim to optimize the assignment of taxis to appropriate customers, yet most of these approaches focus on the positioning of the taxi drivers. This research aims to address the problem of taxi dispatching while keeping in view the preferences of the customer. To this end, this research models taxi dispatch system as a multicriteria decision-making problem where not only is the distance between the passenger and the taxi a parameter, but other user preferences are also incorporated in finalizing a taxi for a given passenger travel request. The proposed method has been compared with the traditional taxi dispatching system. The results reveal more satisfactory taxi dispatching based on the users’ preferences. Furthermore, the precision of the proposed approach has been proven with lesser cancellation, improved driver rating, and reduction in complaints.
“OBE” Concept for New Training Mode of Electronic Information Science and Technology Professionals under Big Data Analysis
Authors: Liang Jifeng
Published: January 2022

As an educational concept based on learning output, OBE (Outcome-Based Education) is student-centered and emphasizes students’ personal progress and learning achievement. Based on BD (big data) analysis, this paper proposes a new talent training mode for the electronic information science and technology specialty. This model employs BD analysis technology to examine the correlation index between social demand and talent cultivation, based on the employment situation of students in the country in previous years. The teaching reform was carried out under the OBE concept, and a new training scheme was formed. Training objectives, graduation requirements, curriculum system, and continuous improvement mechanism were all determined. This paper proposes an algorithm for determining the degree of similarity between the knowledge required by the organization and the knowledge held by its employees. The person with the highest similarity is identified as the training candidate by the algorithm, and the training candidate is then trained according to the knowledge that the organization requires. Talent training in the field of electronic information science and technology has yielded positive results.
Three-Dimensional Skin CT Based on Intelligent Algorithm in the Analysis of Skin Lesion Sites Features in Children with Psoriasis
Authors: Wang Lina , Zheng Youning , Zhou Ran , Liu Wenfang
Published: January 2022

This research was to explore the application value of three-dimensional computed tomography (CT) based on artificial intelligent algorithm in analyzing the characteristics of skin lesions in children with psoriasis. In this study, 15 children with psoriasis were selected as the observation group, and 15 children with other skin diseases were selected as the control group. The CT images were optimized, and the feature selection was carried out based on artificial intelligent algorithm. Firstly, the results were compared with the results of simple skin three-dimensional CT to determine the effectiveness. Then, the two groups of three-dimensional skin CT image features of skin psoriasis-like hyperplasia, Munro microabscess, dermal papillary vascular dilation, and squamous epithelium based on intelligent algorithms were compared. After comparison, the detection rate of psoriasis-like hyperplasia, Munro microabscess, dermal papillary vascular dilation, and squamous epithelium in the observation group was higher than that in the control group, with significant difference and statistical significance (

P
<
0.05

). In addition, the sensitivity of psoriasis-like hyperplasia, Munro microabscess, dermal papilla vascular dilatation, and squamous epithelium in children with psoriasis was 80.0%, 86.7%, 80.0%, and 93.3%, respectively. The specificity of psoriasis-like hyperplasia, Munro microabscess, dermal papilla vascular dilatation, and squamous epithelium in children with psoriasis was 86.7%, 93.3%, 60.0%, and 73.3%, respectively. The results showed that Munro microabscess and psoriasis-like hyperplasia had high sensitivity and specificity in all diagnostic items, which could be used as important features of skin lesion sites in the diagnosis of psoriasis in children. The research provides a basis for the clinical diagnosis of psoriasis in children, which is worthy of clinical promotion.
Metabolic (Dysfunction)-Associated Fatty Liver Disease in Chinese Patients with Type 2 Diabetes from a Subcenter of the National Metabolic Management Center
Authors: Guan Conghui , Fu Songbo , Zhen Donghu , Yang Kuan , An Jinyang , Wang Yapei , Ma Chengxu , Jiang Na , Zhao Nan , Liu Jinjin , Yang Fang , Tang Xulei
Published: January 2022

Background. Few studies have investigated the epidemiological metabolic (dysfunction) associated with fatty liver disease (MAFLD) in China, especially among those with type 2 diabetes. Methods. We recruited 3553 patients aged 18-75 years with type 2 diabetes who underwent abdominal ultrasound and serum biochemical analyses. Patient information including demographic and anthropometric parameters was also collected. Results. Overall, 63.2% of type 2 diabetic patients had MAFLD. Among the MAFLD patients, the proportions of lean, nonobese, and obese MAFLD were 23.1%, 75.7%, and 24.3%, respectively, and the percentage of previously undiagnosed MAFLD was 42.2%. MAFLD patients were younger, had shorter diabetic duration, and had greater BMI, aspartate aminotransferase (AST), alanine aminotransferase (ALT), fasting insulin, postprandial insulin, total cholesterol, and insulin resistance levels (HOMA-IR and TyG index). Liver fibrosis diagnostic panels revealed that the proportions of elevated AST (≥40 U/L) and ALT (≥40 U/L) were 7.3% and 18.5%, respectively. The distributions of AST-to-platelet ratio index (APRI), fibrosis-4 (FIB-4) index, and nonalcoholic fatty liver disease fibrosis score (NFS) per stage were as follows: APRI—low 55.1%, indeterminate 35.3%, and high 9.5%; FIB-4—low 48.2%, indeterminate 45.3%, and high 6.5%; and NFS—low 15.0%, indeterminate 70.0%, and high 13.0%. Conclusions. MAFLD is a very common condition and generally had greater frequency of metabolic characteristics among type 2 diabetics in China. Many MAFLD patients were in the “indeterminate” or “high” stage when APRI, FIB-4, and NFS were assessed. Assessment of MAFLD should be included in the management of type 2 diabetes.
An Intelligent Carbon-Based Prediction of Wastewater Treatment Plants Using Machine Learning Algorithms
Authors: Hilal Anwer Mustafa , Althobaiti Maha M. , Eisa Taiseer Abdalla Elfadil , Alabdan Rana , Hamza Manar Ahmed , Motwakel Abdelwahed , Al Duhayyim Mesfer , Negm Noha
Published: January 2022

Purification of polluted water and return back to the agriculture field is the wastewater treatment for plants. Contaminated water causes illness and health emergencies of public. Also, health risk due release of toxic contaminants brings problem to all living beings. At present, sensors are used in waste water treatment and transfer data via internet of things (IoT). Prediction of wastewater quality content which is presence of total nitrogen (T-N) and total phosphorous (T-P) elements, chemical oxygen demand (COD), biochemical demand (BOD), and total suspended solids (TSS) is associated with eutrophication that should be prevented. This may leads to algal bloom and spoils aquatic life which is consumed by human. The presence of nitrogen and phosphorous elements is in the content of wastewater, and these elements are associated with eutrophication which should be prevented. Adsorption of T-N and T-P activated carbon was predictable as one of the most promising methods for wastewater treatment. Many research works have been done. The issues are inefficiency in the prediction of wastewater treatment. To overcome this issue, this paper proposed fusion of B-KNN with the ELM algorithm that is used. The accuracy of the BKNN-ELM algorithm in classification of water quality status produced the highest accuracy of the highest accuracy which is [Formula: see text] and [Formula: see text] with rate of accuracy which is 93.56%, and the lowest accuracy is [Formula: see text]. Experiment evaluation shows that a total suspended solid predicted by proposed model is 91 with accuracy of 93%. The relative error rate of prediction is 12.03 which is lesser than existing models.
A Novel Molecular Representation Learning for Molecular Property Prediction with a Multiple SMILES-Based Augmentation
Authors: Li Chunyan , Feng Jihua , Liu Shihu , Yao Junfeng
Published: January 2022

Deep learning has brought a rapid development in the aspect of molecular representation for various tasks, such as molecular property prediction. The prediction of molecular properties is a crucial task in the field of drug discovery for finding specific drugs with good pharmacological activity and pharmacokinetic properties. SMILES string is always used as a kind of character approach in deep neural network models, inspired by natural language processing techniques. However, the deep learning models are hindered by the nonunique nature of the SMILES string. To efficiently learn molecular features along all message paths, in this paper we encode multiple SMILES for every molecule as an automated data augmentation for the prediction of molecular properties, which alleviates the overfitting problem caused by the small amount of data in the datasets of molecular property prediction. As a result, by using the multiple SMILES-based augmentation, we obtained better molecular representation and showed superior performance in the tasks of predicting molecular properties.
Breastfeeding and Reduced Risk of Breast Cancer: A Systematic Review and Meta-Analysis
Authors: Qiu Rongbin , Zhong Yangjian , Hu Mengmeng , Wu Biao
Published: January 2022

Background. Evidences which prove relation between breastfeeding women and risk of breast cancer have been limited. Objective. A meta-analysis was carried out on the basis of published literature from clinical trials and studies among different parts of the world. Methods. Studies were analyzed and extracted using PRISMA flowchart. RevMan 5.4.1 was used for analyzing the extracted data. Included studies were fully cited texts with complete information about studies, trails conducted for risk of breast cancer, and breastfeeding correlations. Results. Menarche age, family history, lactation duration, and menopausal status have a strong effect on the risks of breast cancer. Family history studies concluded that for 95% CI, the risk ratio was 2.66 (2.00, 3.52). Conclusion. Findings have suggested that family history and lactation duration affect the risks of breast cancer.
An Intelligent Vision-Based Method of Worker Identification for Industrial Internet of Things (IoT)
Authors: Wang Shuai , Li Xiaoyu , Chen Wei , Fan Weiqiang , Tian Zijian
Published: January 2022

With the rapid development of Internet of things (IoT) and computer vision (CV), the application of combining the IoT platform and CV technology to monitor the worker safety has attracted more and more attention in the field of industrial information. Worker identification is a prerequisite for safety management in industrial production, and safety helmet can not only protect worker’s head from accidental injuries but also help to identify the work types of workers through different colors. Therefore, this study proposes an intelligent method for worker identification based on moving personnel detection and helmet color characteristics. First, the motion objects that contain personnel and nonpersonnel are detected by the Gaussian mixture model (GMM) and extracted to generate the region of interest (RoI) images. Then, the multiple-scale histogram of oriented gradient (MHOG) features of the RoI images are extracted, and the personnel images are identified by the support vector machine (SVM). Third, the workers’ head images are obtained by the OpenPose model and personnel mask, and the GoogLeNet-based transfer learning network is established to extract the head images features and realize worker identification. This method is tested on our dataset, and the average accuracy of worker identification for multiple helmet color combinations reaches 99.43%, which is robust to workers’ angle, scale, and occlusion.
Construction of a Prognosis-Related Gene Signature by Weighted Gene Coexpression Network Analysis in Ewing Sarcoma
Authors: Zhao Runhan , Xiong Chuang , Zhang Chao , Wang Lin , Liang Hao , Luo Xiaoji
Published: January 2022

Background. Ewing sarcoma (ES) is the second most common pediatric bone tumor with a high rate of metastasis, high recurrence, and low survival rate. Therefore, the identification of new biomarkers which can improve the prognosis of ES patients is urgently needed. Methods. Here, GSE17679 dataset was downloaded from GEO databases. WGCNA method was used to identify one module associating with OVS (overall vital survival) and event. cytoHubba was used to screen out 50 hub genes from the module genes. Then, GSE17679 dataset was randomly divided into train cohort and test cohort. Next, univariate Cox analysis, LASSO regression analysis, and multivariate Cox analysis were conducted on 50 hub genes combined with train cohort data to select pivotal genes. Finally, an optimal 7-gene-based risk assessment model was established, which was verified by test cohort, entire GSE17679, and two independent datasets (GSE63157 and TCGA-SARC). Results. The results of the functional enrichment analysis revealed that the OVS and event-associated module were mainly enriched in the protein transcription, cell proliferation, and cell-cycle control. And the train cohort was divided into high-risk and low-risk subgroups based on the median risk score; the results showed that the survival of the low-risk subgroup was significantly longer than high-risk. ROC analysis revealed that AUC values of 1, 3, and 5-year survival were 0.85, 0.94, and 0.88, and Kaplan-Meier analysis also revealed that

P

value < 0.0001, indicating that this model was accurate, which was also verified in the test, entire cohort, and two independent datasets (GSE63157 and TCGA-SARC). Then, we performed a comprehensive analysis (differential expression analysis, correlation analysis and survival analysis) of seven pivotal genes, and found that four genes (NCAPG, KIF4A, NUF2 and CDC20) plays a more crucial role in the prognosis of ES. Conclusion. Taken together, this study established an optimal 7-gene-based risk assessment model and identified 4 potential therapeutic targets, to improve the prognosis of ES patients.
Protective Effect of Qiliqiangxin against Doxorubicin-Induced Cardiomyopathy by Suppressing Excessive Autophagy and Apoptosis
Authors: Qin Yating , Lv Chao , Zhang Xinxin , Ruan Weibin , Xu Xiangyu , Chen Chen , Wan Xiaoning , Ji Xinyun , Zhou Juan , Lu Li , Guo Xiaomei
Published: January 2022

Background. Doxorubicin (DOX) is one of the most potent and widely prescribed antitumor agents; however, its clinical use is limited by cardiac side effects. In this study, we aimed to clarify the protective effects of Qiliqiangxin (QL), a traditional Chinese medicine formulation, on DOX-induced cardiotoxicity and to explore the underlying mechanisms in a rat model. Methods. Male Sprague-Dawley rats were randomly assigned to three groups with different interventions (control, DOX, and DOX plus QL) for 31 days. Cardiac function was monitored. The levels of oxidative stress in plasm were detected, the activities of autophagy and apoptosis in rat hearts were determined, and then, the related PI3K/AKT/mTOR signal pathway regulating apoptosis and autophagy was investigated. Results. QL improved cardiac dysfunction and decreased the increased level of cardiac enzymes in plasm caused by DOX. Moreover, DOX exposure resulted in oxidative stress enhancement, which was suppressed by QL treatment. Then, we discovered that DOX intervention caused the apoptosis of cardiomyocytes by activating the mitochondrial-dependent apoptotic pathway which was strongly inhibited by QL treatment. Furthermore, there was a significant increase in autophagic activities in the DOX-stimulated myocardium. Administration of QL substantially inhibited the enhanced autophagic activities, which might be attributed to the activation of PI3K/AKT/mTOR cascade, followed by suppression of ULK1 activity. Conclusions. QL exhibited protective roles against DOX-induced cardiotoxicity possibly via mediating the PI3K/AKT/mTOR pathway, leading to inhibition of autophagy and subsequent apoptosis activities.
Tumor Genomic Testing for >4,000 Men with Metastatic Castration-resistant Prostate Cancer in the Phase III Trial PROfound (Olaparib)
Authors: Hussain Maha , Corcoran Claire , Sibilla Caroline , Fizazi Karim , Saad Fred , Shore Neal , Sandhu Shahneen , Mateo Joaquin , Olmos David , Mehra Niven , Kolinsky Michael P. , Roubaud Guilhem , Özgüroǧlu Mustafa , Matsubara Nobuaki , Gedye Craig , Choi Young Deuk , Padua Charles , Kohlmann Alexander , Huisden Robert , Elvin Julia A. , Kang Jinyu , Adelman Carrie A. , Allen Allison , Poehlein Christian , de Bono Johann
Published: January 2022

Purpose:

Successful implementation of genomic testing in clinical practice is critical for identification of men with metastatic castration-resistant prostate cancer (mCRPC) eligible for olaparib and future molecularly targeted therapies.

Patients and Methods:

An investigational clinical trial assay, based on the FoundationOneCDx tissue test, was used to prospectively identify patients with qualifying homologous recombination repair gene alterations in the phase III PROfound study. Evaluation of next-generation sequencing (NGS) tissue test outcome against preanalytic parameters was performed to identify key factors influencing NGS result generation.

Results:

A total of 4,858 tissue samples from 4,047 patients were tested and reported centrally. NGS results were obtained in 58% (2,792/4,858) of samples (69% of patients). Of samples submitted, 83% were primary tumor samples (96% were archival and 4% newly obtained). Almost 17% were metastatic tumor samples (60% were archival and 33% newly obtained). NGS results were generated more frequently from newly obtained compared with archival samples (63.9% vs. 56.9%) and metastatic compared with primary samples (63.9% vs. 56.2%). Although generation of an NGS result declined with increasing sample age, approximately 50% of samples ages >10 years generated results. While higher tumor content and DNA yield resulted in greater success in obtaining NGS results, other factors, including selection and preservation of samples, may also have had an impact.

Conclusions:

The PROfound study shows that tissue testing to identify homologous recombination repair alterations is feasible and that high-quality tumor tissue samples are key to obtaining NGS results and identifying patients with mCRPC who may benefit from olaparib treatment.