bluuebunny/crossref_metadata_2025 huggingface dataset:
Differential Grey Wolf Load-Balanced Stochastic Bellman Deep Reinforced Resource Allocation in Fog Environment
Authors: Nethaji S. V. , Chidambaram M.
Published: August 2022

Fog computing is becoming a dynamic and sought-after computing prototype for Internet of Things (IoT) application deployments. It works in conjunction with the cloud computing environment. Load balancing, which is employed by IoT applications when deciding, which fog or cloud computing nodes to use, is one of the most critical components for enhancing resource efficiency and avoiding problems like overloading or underloading. However, for IoT applications, ensuring that all CPU nodes are evenly distributed in terms of latency and energy utilization remains a challenge. To solve these issues, this work introduces Differential Grey Wolf (DGW) load balancing with stochastic Bellman deep reinforced resource optimization (DGW-SBDR) in fog situations. A Differential Evolution-based Grey Wolf Optimization algorithm based on load balancing has been developed for optimal resource management. The Grey Wolf Optimization algorithm, which employs differential evolution, assigns jobs to virtual machines based on user demands (VMs). In the event of an overutilized VM pool, a grey wolf optimization strategy based on differential evolution can detect both under and overutilized VMs, allowing for smooth transit between fogs. This step disables a number of virtual machines in order to reduce latency. In a Stochastic Gradient and Deep Reinforcement Learning-based Resource Allocation Model, a stochastic gradient bellman optimality function and Deep Reinforcement Learning are integrated for optimal resource allocation. According to the proposed method, QoS may be supplied to end-users by reducing energy consumption and better managing cache resources utilizing stochastic gradient bellman optimality.
Online Simulation of Illustration Patterns Based on Digital Art Design
Authors: Fu Xi , Feng Tao
Published: August 2022

Illustration art is an important part of graphic design, and is an intuitive means of artistic expression. Based on the gradual development of social networks and modern illustration art, digital illustration technology has become the main means of expression in modern graphic design. Starting from the basic concept of illustration art in the digital age, this study analyzes the application of digital illustration art and promotes the innovative development of the artistic expression of graphic design in China. This study will combine the traditional Chinese painting language with digital illustration creation in an inquiry-based manner, optimize the standard genetic algorithm, verify it through experimental simulation, and find that the model is more innovative based on the original model. This study provides a certain theoretical basis for the development of digital illustration in China and has a certain propaganda effect on the traditional Chinese painting language.
Computer Data Encryption System Based on Nonlinear Partial Differential Equations
Authors: Yang Junpu
Published: August 2022

Data encryption is to convert plaintext data into ciphertext through a data encryption algorithm and then transmit the ciphertext. After the recipient receives the ciphertext, the ciphertext is restored to plaintext, which provides protection and technical support for information security. The main purpose of this article is to design a computer data encryption system based on nonlinear partial differential equations. This paper uses the DES encryption algorithm to encrypt data and implements an onion encryption system that encrypts the outer layer of the database and tests and analyzes the encryption efficiency and additional overhead of the database encryption system on a general database to verify the design application prospects of ideas. In addition, the overall scheme of the encryption system, the hardware, and software of the system are designed in detail, the system is debugged, the overall test is tested, and the data encryption and decryption are effective and feasible. The experimental results of this paper show that after the construction of a computer data encryption system based on nonlinear partial differential equations, the overall security of the data is increased by 25%. In addition, after comparison, the security performance of the onion-type data encryption system is higher than that of the MySQL-type data. The performance of the encryption system is 21% lower. It has certain practical value and significance to apply it to the computer data encryption system.
Estimating Performance Efficiency of Mining and Extracting Sectors Using DEA Models: The Case of Jordan
Authors: Jaber Jamil J. , Beldjilali Fatiha , Shehadeh Ali A. , Hamadneh Nawaf N. , Saleh Mohammad , Tahir Muhammad , Al Wadi S.
Published: August 2022

In this study, we estimated the performance efficiency of the Jordanian mining and extracting sector based on Data Envelopment Analysis (DEA). The utilized dataset includes 6 out of 15 corporations that reflect around 90% of the total market capitalization under the mining and extracting sector in the Amman Stock Exchange (ASE). The sample consists of 126 observations from 2000 to 2020. It should be noted that estimating the efficiency of the sector based on time series for each company is not mentioned in the literature review. Therefore, we applied BCC (Banker–Charnes–Cooper) models to estimate performance efficiency and compared between input and output models under DEA. We also estimated the average performance efficiency of the sector to detect weaknesses/strengths among companies. The market capitalization and the operating revenue are used to evaluate the companies’ performance. In addition to the performance variables as output to the DEA models, the current assets, non‐current assets, operating expenses, and general administrative expenses are also used as input variables under the DEA models. This study also examined the effect of Gross Domestic Product (GDP) growth and Return on Assets (ROA) on performance efficiency scores for BCC models. In the results, we found that there are differences in performance efficiency across time series in each company based on dynamic BCC models. It is observed that the performance efficiency of NAST Company is better than the other companies based on BCC (Input/output). The GDP growth and ROA reveal the effect on efficiency performance under BCC models. The proposed model can be used to improve the performance efficiency of companies in stock exchange markets.
[Retracted] A Public Health‐Oriented New Energy Industry Competitiveness Evaluation
Authors: Dou Zhijie , Li Li Shi , Lu Lu
Published: August 2022

This paper develops a regional new energy industry (NEI) competitiveness evaluation index system based on the theoretical framework of the “diamond model” and the unique characteristics of the new energy industry and made an empirical analysis of Jilin province with analytic hierarchy process (AHP) and fuzzy comprehensive evaluation method. The analysis results show that the new energy industry in Jilin Province has a good foundation, and the government’s role, talent support, technological innovation, and market factors are acceptable. However, due to location factors and resource endowments, regional GDP and per capita consumption expenditure are low. The lack of intrinsic motivation of industrial competitive advantage has resulted in the poor overall competitiveness of the new energy industry in Jilin Province. Then, it is advised to take targeted measures to work closely with national NEI development strategy, optimize the industrial technology innovation ability and the talent support, actively guide social capital flows and new energy consumption, optimize regional energy consumption structure and industrial structure by creating a complete NEI chain, and revitalize the whole economy.
Analysis on the Establishment and Management of Library Resource Base Based on Modern Information Technology
Authors: Yao Chiyue , Dung Vinh Phuc
Published: August 2022

The current rapid development of modern network information technology, along with the arrival of this trend, has profoundly changed people’s living and learning methods. In the past, the management of book resources in the traditional period has gradually exposed many drawbacks, and it is difficult to meet the technological development of the information age. Combined with the complexity of book management parameters, high variable dimensions, and the characteristics of multiattribute data points including not only numerical attributes but also category attributes and mixed attributes, the fuzzy clustering algorithm is combined with attribute weighted optimization, and then, the optimization is derived. Iterative formula and form show a weighted clustering algorithm to perform cluster analysis on relevant influencing factors in book data management. Digital library is not a library entity: it corresponds to various real social activities of public information management and dissemination and is manifested in various new information resource organizations and information dissemination services. As a fuzzy association rule mining algorithm, FP-growth algorithm is obviously better than Apriori algorithm in execution efficiency. However, due to the lack of fuzzy attributes and the large space complexity, the FP-growth algorithm cannot achieve effective multilayer association rule mining when dealing with large transaction databases, such as library databases. First, the algorithm divides the large-scale book transaction database into several sub-databases according to the transaction of the first item and constructs the corresponding sub-FP-tree structure; then, the parent items that are not frequent items in the hierarchical tree are filtered out in real time to reduce the scanning space.
Breast Cancer Patients with Brain Metastases: A Cross-Sectional Study
Authors: Simsek Melih , Aliyev Altay , Baydas Tuba , Besiroglu Mehmet , Demir Tarik , Shbair Abdallah TM , Seker Mesut , Turk H. Mehmet
Published: August 2022

The prognosis of breast cancer patients with brain metastasis is poor. It was aimed to define the clinicopathological features of breast cancer patients with brain metastases and to determine the risk factors and survival outcomes associated with brain metastasis. This is a single-center, retrospective, cross-sectional study. A total number of 127 patients diagnosed with breast cancer and who developed brain metastasis between January 2011 and March 2021 were retrospectively analyzed. The survival and clinicopathological data of these patients according to 4 biological subtypes were evaluated (luminal A, luminal B, HER-2 overexpressing, and triple-negative). The median overall survival for all patients was 45.6 months. The median time from the diagnosis of breast cancer to the occurrence of brain metastasis was 29.7 months, and the median survival time after brain metastasis was 7.2 months. The time from the diagnosis of breast cancer to brain metastasis development was significantly shorter in HER-2 overexpressing and triple-negative subtypes than in luminal A and B subtypes. The median time from breast cancer diagnosis to brain metastasis was 33.5 months in luminal A, 40.6 months in luminal B, 16.8 months in HER-2 overexpressing, and 22.8 months in the triple-negative groups (

p
=
0.003

). We found the worst median survival after brain metastasis in the triple-negative group with 3.5 months. Early and close surveillance of high-risk patients may help early diagnosis of brain metastasis and may provide to perform effective treatments leading to longer overall survival times for this patient population.
Data Collection and Management of Digital Process of Painting and Calligraphy Based on Internet of Things
Authors: Sun Chengwu
Published: August 2022

With the advent of the information age, the research on the digitization of calligraphy and painting information is particularly important. In order to improve the efficiency of data management after the digitization of printed information, this paper designs a digital information flow management system and data retrieval model based on the Internet of Things. According to the mismatch between the selected unit and the actual spatial data distribution and the influence of data dispersion, an algorithm for building an r-tree of a digital information flow control system using computer graphics is proposed through efficient data retrieval based on the r-tree index. The experimental results show that the algorithm has good practicability.
MRFDCNet: Multireceptive Field Dense Connection Network for Real-Time Semantic Segmentation
Authors: Wang Xiaotian , Cao Weiqun
Published: August 2022

Semantic segmentation is widely used in automatic driving systems. To quickly and accurately classify objects in emergency situations, a large number of images need to be processed per second. To make a semantic segmentation model run on hardware with low memory and limited computing capacity, this paper proposes a real-time semantic segmentation network called MRFDCNet. This architecture is based on our proposed multireceptive field dense connection (MRFDC) module. The module uses one depthwise separable convolution branch and two depthwise dilated separable convolution branches with a proposed symmetric sequence of dilation rates to obtain local and contextual information under multiple receptive fields. In addition, we utilize a dense connection to allow local and contextual information to complement each other. We design a guided attention (GA) module to effectively utilize deep and shallow features. The GA module uses high-level semantic context to guide low-level spatial details and fuse both types of feature representations. MRFDCNet has only 1.07 M parameters, and it can achieve 72.8% mIoU on the Cityscapes test set with 74 FPS on one NVIDIA GeForce GTX 1080 Ti GPU. Experiments on the Cityscapes and CamVid test sets show that MRFDCNet achieves a balance between accuracy and inference speed. Code is available at https://github.com/Wsky1836/MRFDCNet.
Machine Learning for Predicting Hyperglycemic Cases Induced by PD-1/PD-L1 Inhibitors
Authors: Yang Jincheng , Li Ning , Lin Weilong , Shi Liming , Deng Ming , Tong Qin , Yang Wenjing
Published: August 2022

Objective. Immune checkpoint inhibitors, such as programmed death-1/ligand-1 (PD-1/L1), exhibited autoimmune-like disorders, and hyperglycemia was on the top of grade 3 or higher immune-related adverse events. Machine learning is a model from past data for future data prediction. From post-marketing monitoring, we aimed to construct a machine learning algorithm to efficiently and rapidly predict hyperglycemic adverse reaction in patients using PD-1/L1 inhibitors. Methods. In original data downloaded from Food and Drug Administration Adverse Event Reporting System (US FAERS), a multivariate pattern classification of support vector machine (SVM) was used to construct a classifier to separate adverse hyperglycemic reaction patients. With correct core SVM function, a 10-fold 3-time cross validation optimized parameter value composition in model setup with R language software. Results. The SVM prediction model was set up from the number type/number optimization method, as well as the kernel and type of “rbf” and “nu-regression” composition. Two key values (nu and gamma) and case number displayed high adjusted r2 in curve regressions (

n
u
=
0.5649
×

e

−
 

case

/

6984

, gamma
=
9.005
×

10

−
4

×
case
−
4.877
×

10

−
8

×

case

2

). This SVM model with computable parameters greatly improved the assessing indexes (accuracy, F1 score, and kappa) as well as coequal sensitivity and the area under the curve (AUC). Conclusion. We constructed an effective machine learning model based on compositions of exact kernels and computable parameters; the SVM prediction model can noninvasively and precisely predict hyperglycemic adverse drug reaction (ADR) in patients treated with PD-1/L1 inhibitors, which could greatly help clinical practitioners to identify high-risk patients and perform preventive measurements in time. Besides, this model setup process provided an analytic conception for promotion to other ADR prediction, such ADR information is vital for outcome improvement by identifying high-risk patients, and this machine learning algorithm can eventually add value to clinical decision making.
A Ferroptosis-Related LncRNA Signature Associated with Prognosis, Tumor Immune Environment, and Genome Instability in Hepatocellular Carcinoma
Authors: Lian Jie , Zhang Chaoyu , Lu Haibo
Published: August 2022

Background. Ferroptosis is an iron-dependent form of cell death. In this study, we identified ferroptosis-related long noncoding RNAs (FRlncRNAs) to investigate their association with hepatocellular carcinoma (HCC) in prognosis, tumor immune environment, and genome instability. Methods. Transcriptome profile data of HCC were retrieved from a public database. FRlncRNAs were identified by co-expression analysis. Patients were randomly divided into training and test cohorts. Univariate Cox analysis and Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression were performed to construct a risk model. Patients were divided into high- and low-risk groups based on the risk model. AUC and C index were used to assess the risk model. Survival analysis, immune status, and genome instability were compared between the two groups. Results. Sixteen FRlncRNAs were identified and used to construct an FRlncRNA signature for the risk model. The Kaplan-Meier analysis revealed that patients in the high-risk group had poorer overall survival than patients in the low-risk group. The area under curve of the risk model was 0.879, 0.809, and 0.757 in the training cohort and 0.635, 0.688, and 0.739 in the test cohort at 1, 2, and 3 years, respectively. The risk model was an independent prognostic predictor and showed excellent prediction of prognosis compared with clinicopathological features. For the differentially expressed ferroptosis-related genes, many enriched metabolic pathways were identified in the functional enrichment analysis. Immune cells such as CD8+ T cells, macrophages M1, natural killer cells, and B cells, which may be associated with antitumor immune responses, differed between the high- and low-risk groups. Genome instability based on the risk model was also explored. A total of 61 genes were differently mutated between the two risk groups, and among them, TP53, HECW2, TRIM66, MCTP2, and KIAA1551 had the most significant mutation frequency differences. Conclusion. The FRlncRNA signature is closely related with overall survival, tumor immune environment, and genome instability in HCC.
Synergistic Preparation of Sludge Carbon from Oily Sludge and Walnut Shells
Authors: Tang Chao , Guan Jiaojiao
Published: August 2022

The preparation process of synergistic preparation of sludge carbon by oily sludge and walnut shells are divided into two stages: carbonization preparation of a carbon precursor and activation preparation of sludge carbon. The preparation conditions of the carbon precursor are 2.5:1 mass ratio of oily sludge and walnut shells, carbonization temperature is 450°C, and time is 2 h. There are some pores on the surface of the prepared carbon precursor, the heavy metal content of leachate does not exceed the standard, and the use process will not cause heavy metal pollution. Intensive research is carried out on factors affecting the preparation of sludge carbon by activation of the carbon precursor by the orthogonal experiment and single-factor experiment. The optimal activation conditions are determined by using ZnCl2 as an activator, mass ratio of the carbon precursor to ZnCl2 is 1:4, activation temperature is 800°C, heating rate is 15°C/min, and activation holding time is 1 h. The surface of sludge carbon is distributed with many pores, several layers of small pores can be seen deeply in the large holes, and pore size distribution is dominated by micropores and mesopores. BET Specific surface area, pore volume, average pore, and iodine value are 1772.69 m2/g, 1.98 cm3/g, 1.64 nm, and 1011.65 mg/g, respectively, which surpasses commercially available activated carbon comprehensively.
[Retracted] Model Construction of College Students’ Entrepreneurial Ability Cultivation in Mental Health Education Environment
Authors: Huang Muqian
Published: August 2022

National policies have been very supportive of college students as a new force in IEE (innovation and entrepreneurship education). Universities across the nation have increased their emphasis on entrepreneurship education and put a lot of effort into developing and enhancing college students’ EA (entrepreneurship ability). An important challenge facing universities is how to develop the psychological quality of IEE in college students and create a long‐term training system. The author develops the EA evaluation model for college students based on practical experience with mental health education and applies BPNN (BP neural network) theory to the assessment of IEE in higher education. The scores corresponding to the students’ evaluation indices are used as input vectors, and the innovative EA of the students is evaluated. According to the simulation’s outcomes, the number of hidden neurons is calculated, and the outcomes are assessed through experiments. The outcomes demonstrate that, following the completion of the enhanced BPNN training, the actual value is valid, the expected value is reasonable, and the maximum relative error between them is 1.6 percent, which is essentially the ideal situation. It has been established that the IEE’s established evaluation index system is fair and can accurately capture students’ IEE spirit.
Fractography and Microstructural Analysis of As-Built and Stress Relieved DMLS Ti6Al4V (ELI) Plates Subjected to High Velocity Impact
Authors: Moleko Teboho C. , Maringa Maina , Du Preez Willie B.
Published: August 2022

This paper presents fractographic and microstructural analysis of as-built and stress relieved DMLS Ti6Al4V (ELI) plates with thicknesses of 8 mm, 10 mm, 12 mm, and 14 mm, impacted by high velocity projectiles. Fractography was performed through scanning electron microscopy on the surfaces of the projectile holes, while microstructural analysis of specimens extracted from the plates close to and far from the projectile holes was conducted by way of optical microscopy. Fractography revealed brittle behavior at the entry points of the penetration holes and ductile behavior at the exit points of the penetration holes. Microstructural analysis revealed microstructural changes in the alloy and a gradual increase of the β-phase fraction toward the edge of the projectile holes through all the plate thicknesses.
A Semi‐Analytical Solution of Inverse Laplace Transform
Authors: Luo Shuang , Zhao Fu-yao
Published: August 2022

We propose a general method for constructing the semi‐analytical solution of the inverse Laplace transform, realized through the powerful exponential approximation invented by Wang et al. in 1993. Bearing their credits, this method inherits all the merits such as analytical expression, avoiding free parameters, simple calculation with high accuracy, and the availability of error estimation. Illustrating calculations indicate the potential applications to the vast problems in the fields of mathematical physics as well as engineering and medicine.
A Meta-Analysis of CT as a Tool for Diagnosing and Treating Shoulder Joint Bankart Injuries
Authors: Yang Yibin , Zou Longqiang , Li Zhengnan
Published: August 2022

Objective. The shoulder joint is the most flexible joint in the human body. It is a typical multiaxial ball-and-socket joint. The humeral head is approximately spherical, and the glenoid is small and shallow. This article mainly discusses the application value of computerized tomography (CT) in the early diagnosis of skeletal Bankart injury of the shoulder joint. Methods. The chemical quality was evaluated according to the physical therapy evidence database PEDro scale. The literature quality evaluation scale and the NO scale are also used to evaluate the quality of each nonrandomized study. The standard quality scores of the literature quality evaluation scale are as follows: (1) the selection of the study group; (2) the comparability of the study group; and (3) (cohort study) clear interest results. Outcome measurement: Postoperative shoulder joint stability and range of motion (ROM) are the main results of Bankart injury patients undergoing open repair surgery and arthroscopic repair surgery. The secondary results of the survey included the Rowe score, the shoulder stability score, the American shoulder and elbow surgery score ASES, the University of California, Los Angeles, shoulder score UCLA, and the operation time. Results. Four of the included studies are randomized controlled trials, and the other studies are cohort studies. After meta-analysis, a fixed-effect model (

I

2

=
34
%

) was used to observe the difference in shoulder stability treatment between the two groups and was statistically significant (

P
=
0.008

,

RR
=
0.94

, 95% confidence interval: 0.89~0.98). The analysis results showed that compared with patients undergoing open surgery, patients’ undergoing arthroscopic repair had better postoperative shoulder motion range (

P
<
0.001

,

SMD
=
0.47

, 95% confidence interval: -0.72~0.22), and there is no significant heterogeneity. Conclusion. The Bankart injury of the shoulder joint cannot be diagnosed by X-ray examination alone due to its anatomical location and the size of the fracture fragments. CT examination has a better auxiliary diagnostic effect in the early stage of skeletal Bankart injury.
[Retracted] Analysis of the Effect of DPL Combined with Clarithromycin in the Therapy and Improvement of Rosacea
Authors: Yan Fang , Peng Chao
Published: August 2022

Rosacea is a chronic inflammatory skin disease with a high incidence, and it leads to negative emotions such as inferiority complex, increased psychological pressure, and a greatly reduced quality of life. In order to investigate the clinical efficacy of DPL combined with clarithromycin in the treatment and improvement of rosacea. 86 patients with rosacea were selected and randomly divided into the control group and study group according to the random number table method. The results show that the combination of DPL and clarithromycin in the treatment of rosacea patients can effectively improve the clinical symptoms of patients, improve the therapeutic effect, and the incidence of adverse reactions is low, which ensures that the patients have a good prognosis, which is worthy of clinical application.
Management of COVID-19 in Kidney Transplant Recipients: A Single-Center Case Series
Authors: Marbun Maruhum Bonar H. , Saragih Riahdo J. , Andina Tantika
Published: August 2022

Background. Kidney transplant recipients (KTRs) were reported to be at higher risk of developing severe coronavirus disease-2019 (COVID-19). Despite being one of the most impacted countries, little is known about KTRs with COVID-19 in Indonesia. This report aims to explore the management strategies and short-term clinical outcomes of KTRs with COVID-19 in an Indonesian transplant center. Methods. We observed KTRs who were admitted following COVID-19 diagnosis. Anamnesis, physical, laboratory, and radiologic examinations were performed. Demographic and transplant histories were recorded, along with symptoms, vaccination status, and management related to COVID-19. Results. Nineteen KTRs were observed and 14 (73.6%) were male. The most common presenting symptoms were fever, cough, and shortness of breath. Nine (47.3%) KTRs had severe-critical COVID-19. The mortality rate was 42.1%. Acute kidney injury (AKI) was present in six (31.6%) of KTRs, five (83.3%) of whom were nonsurvivors. The median D-dimer level was higher in nonsurvivors (5,800 versus 670 μL), while other laboratory parameters were comparable. Seven (36.8%) KTRs were vaccinated. The mortality rates of vaccinated and unvaccinated KTRs were 14.2% and 70%, respectively. Antiviral therapy, anticoagulant, intravenous immunoglobulin, and tocilizumab were prescribed to 89.5%, 89.5%, 15.8%, and 10.5%, respectively. Immunosuppressive therapy (IST) was halted in 68% of KTRs, among which 61.5% passed away. Conclusion. The clinical presentation of COVID-19 in KTRs was similar to that in the general population, whereas the mortality rate was higher. Management strategies for KTRs with COVID-19 should include prevention of AKI and hypercoagulation. Vaccination seems to be beneficial for KTRs, while temporary withdrawal of IST does not.
Pharmacologic Inhibition of SHP2 Blocks Both PI3K and MEK Signaling in Low-epiregulin HNSCC via GAB1
Authors: Kurupi Richard , Floros Konstantinos V. , Jacob Sheeba , Chawla Ayesha T. , Cai Jinyang , Hu Bin , Puchalapalli Madhavi , Coon Colin M. , Khatri Rishabh , Crowther Giovanna Stein , Egan Regina K. , Murchie Ellen , Greninger Patricia , Dalton Krista M. , Ghotra Maninderjit S. , Boikos Sosipatros A. , Koblinski Jennifer E. , Harada Hisashi , Sun Yue , Morgan Iain M. , Basu Devraj , Dozmorov Mikhail G. , Benes Cyril H. , Faber Anthony C.
Published: August 2022

Preclinical and clinical studies have evidenced that effective targeted therapy treatment designed against receptor tyrosine kinases (RTKs) in different solid tumor paradigms is predicated on simultaneous inhibition of both the PI3K and MEK intracellular signaling pathways. Indeed, reactivation of either pathway results in resistance to these therapies. Recently, oncogenic phosphatase SHP2 inhibitors have been developed with some now reaching clinical trials. To expand on possible indications for SHP099, we screened over 800 cancer cell lines covering over 25 subsets of cancer. We found head and neck squamous cell carcinoma (HNSCC) was the most sensitive adult subtype of cancer to SHP099. We found that, in addition to the MEK pathway, SHP2 inhibition blocks the PI3K pathway in sensitive HNSCCs, resulting in downregulation of mTORC signaling and antitumor effects across several HNSCC mouse models, including an human papillomavirus (HPV+) patient-derived xenograft. Importantly, we found low levels of the RTK ligand epiregulin identified HNSCCs that were sensitive to SHP2 inhibitor, and, adding exogenous epiregulin mitigated SHP099 efficacy. Mechanistically, epiregulin maintained SHP2–GAB1 complexes in the presence of SHP2 inhibition, preventing downregulation of the MEK and PI3K pathways. In the presence of SHP2 inhibitor, HNSCCs are highly dependent on GAB1 for their survival and knockdown of GAB1 is sufficient to block the ability of epiregulin to rescue MEK and PI3K signaling. These data connect the sensitivity of HNSCC to SHP2 inhibitors and to a broad reliance on GAB1-SHP2, revealing an important and druggable signaling axis. Overall, SHP2 inhibitors are being heavily developed and may have activity in HNSCCs, and in particular those with low levels of epiregulin.

Significance:

This work identifies a novel role of SHP2 inhibitor by dual downregulation of PI3K and MEK pathways, through loss of GAB1 activation and disruption of GAB1 complexes in low-epiregulin HNSCC.
The MDM2 Inhibitor Navtemadlin Arrests Mouse Melanoma GrowthIn Vivoand Potentiates Radiotherapy
Authors: Ingelshed Katrine , Spiegelberg Diana , Kannan Pavitra , Påvénius Linnéa , Hacheney Jessica , Jiang Long , Eisinger Silke , Lianoudaki Danai , Lama Dilraj , Castillo Francisca , Bosdotter Cecilia , Kretzschmar Warren W. , Al-Radi Omayma , Fritz Nicolas , Villablanca Eduardo J. , Karlsson Mikael C. I. , Wermeling Fredrik , Nestor Marika , Lane David P. , Sedimbi Saikiran K.
Published: August 2022

The tumor suppressor protein p53 is mutated in close to 50% of human tumors and is dysregulated in many others, for instance by silencing or loss of p14ARF. Under steady-state conditions, the two E3 ligases MDM2/MDM4 interact with and inhibit the transcriptional activity of p53. Inhibition of p53–MDM2/4 interaction to reactivate p53 in tumors with wild-type (WT) p53 has therefore been considered a therapeutic strategy. Moreover, studies indicate that p53 reactivation may synergize with radiation and increase tumor immunogenicity. In vivo studies of most MDM2 inhibitors have utilized immunodeficient xenograft mouse models, preventing detailed studies of action of these molecules on the immune response. The mouse melanoma cell line B16-F10 carries functional, WT p53 but does not express the MDM2 regulator p19ARF. In this study, we tested a p53-MDM2 protein–protein interaction inhibitor, the small molecule Navtemadlin, which is currently being tested in phase II clinical trials. Using mass spectrometry–based proteomics and imaging flow cytometry, we identified specific protein expression patterns following Navtemadlin treatment of B16-F10 melanoma cells compared with their p53 CRISPR-inactivated control cells. In vitro, Navtemadlin induced a significant, p53-dependent, growth arrest but little apoptosis in B16-F10 cells. When combined with radiotherapy, Navtemadlin showed synergistic effects and increased apoptosis. In vivo, Navtemadlin treatment significantly reduced the growth of B16-F10 melanoma cells implanted in C57Bl/6 mice. Our data highlight the utility of a syngeneic B16-F10 p53+/+ mouse melanoma model for assessing existing and novel p53-MDM2/MDM4 inhibitors and in identifying new combination therapies that can efficiently eliminate tumors in vivo.

Significance:

The MDM2 inhibitor Navtemadlin arrests mouse tumor growth and potentiates radiotherapy. Our results support a threshold model for apoptosis induction that requires a high, prolonged p53 signaling for cancer cells to become apoptotic.
Scleroderma-like Syndrome in the Setting of Pembrolizumab Therapy for Non-Small Cell Lung Cancer: Diagnosis and Dermatologic Management
Authors: Fattore Davide , Battista Teresa , De Lucia Mario , Annunziata Maria Carmela , Fabbrocini Gabriella
Published: August 2022

Immune checkpoint inhibitors play an important role in the treatment of malignancies. ICIs consist of monoclonal antibodies directed against inhibitory immune receptors cytotoxic T-lymphocyte antigen 4 (CTLA-4), programmed cell death 1 (PD-1), or programmed cell death-ligand 1 (PD-L1). PD-1 is a receptor expressed by T lymphocytes and has the role of inhibiting their activation. Pembrolizumab is a humanized anti-PD-1 monoclonal antibody. It can improve the immune function of T-cells, which results in significant clinical benefit in the treatment of cancer. Despite its wide use, immunotherapy is associated with a spectrum of side effects known as immune-related adverse events. We present a case of an 82-year-old patient with widespread fibroatrophic skin areas that occurred during a treatment with pembrolizumab for non-small cell lung cancer. Clinical, serological, and histopathological examinations led to the diagnosis of generalized morphea. The patient discontinued pembrolizumab and switched to chemotherapy with pemetrexed and carboplatin. A good therapeutic response was obtained with phototherapy, corticosteroids, and topical calcineurin inhibitors. A focus on the therapeutic management of this skin toxicity in oncological patients is provided.
Occipital Intradiploic Pseudomeningocele – A Rare Complication of Pediatric Posterior Cranial Fossa Surgery: Case Report and Review of the Literature
Authors: Bonomo Giulio , Rubiu Emanuele , Iess Guglielmo , Bonomo Roberta , Amato Alessia , Restelli Francesco , Falco Jacopo , Mazzapicchi Elio , Locatelli Marco , Rampini Paolo , Carrabba Giorgio G.
Published: August 2022

Introduction: Intradiploic pseudomeningoceles, also called intradiploic cerebrospinal fluid (CSF) fistulas, are abnormal CSF collections between the two bony tables of the calvaria resulting from postsurgical CSF leakage. To date, only six cases of intradiploic pseudomeningocele have been reported, all occurring in the occipital area. In this paper, we report the seventh case of late-onset occipital intradiploic pseudomeningocele (OIP) occurring in a young female patient who underwent surgery for the removal of a cerebellar pilocytic astrocytoma. In this regard, we also review the literature on the few recognized cases of OIP. Case Presentation: The case of an 18-year-old female patient known to our institute for an operation 12 years earlier to remove a pilocytic astrocytoma is illustrated. At admission, the patient complained only of occasional orthostatic headache. Brain imaging demonstrated a pseudomeningocele extended intradiploically from the occipital squama to the condylar and clivus regions, thinning both occipital bone tables and dilating the CSF-filled diploe. Watertight duroplasty and cranioplasty were effectively performed. Conclusion: Pediatric patients undergoing posterior cranial fossa craniotomy/craniectomy may postoperatively develop OIP. In this setting, treatment of any dural CSF fistula should be considered because of the risk of progressive extension and bone erosion.
Development of methods and technologies for creating intelligent scientific and educational internet resources
Authors: Batyrkhanov Ardak G. , Sadirmekova Zhanna B. , Sambetbayeva Madina A. , Nurgulzhanova Assel N. , Ismagulova Zhuldyz S. , Yerimbetova Aigerim S.
Published: August 2022

The purpose of this work is to develop methods, technologies and tools for creating and maintaining intelligent scientific and educational internet resources (ISEIR) based on a service-oriented approach and Semantic Web technologies. The main purpose of ISEIR is to provide meaningful access to scientific and educational information resources of a given field of knowledge and integrated information processing services. According to the preliminary concept, an intelligent scientific and educational internet resource will be an information system accessible via the internet which provides ontology-based systematization and integration of scientific knowledge, data and information resources into a single information space together with a meaningful effective access to them as well as supporting their use in solving various scientific and educational tasks. ISEIR is equipped with an ergonomic web-based user interface and special editors designed to manage the knowledge integrated into it. The proposed approach to the construction of intelligent scientific and educational internet resources is the basis for the developed technology in creating and maintaining information environments for distributed learning.
An insight into the intricacies of lingual paraphrasing pragmatic discourse on the purpose of synonyms
Authors: Nahian Jabir Al , Mohammad Masum Abu Kaisar , Syed Muntaser Mansur , Abujar Sheikh
Published: August 2022

The term "paraphrasing" refers to the process of presenting the sense of an input text in a new way while preserving fluency. Scientific research distribution is gaining traction, allowing both rookie and experienced scientists to participate in their respective fields. As a result, there is now a massive demand for paraphrase tools that may efficiently and effectively assist scientists in modifying statements in order to avoid plagiarism. natural language processing (NLP) is very much important in the realm of the process of document paraphrasing. We analyze and discuss existing studies on paraphrasing in the English language in this paper. Finally, we develop an algorithm to paraphrase any text document or paragraphs using WordNet and natural language tool kit (NLTK) and maintain "Using Synonyms" techniques to achieve our result. For 250 paragraphs, our algorithm achieved a paraphrase accuracy of 94.8%.
Bridgeless single stage AC/DC converter with power factor correction
Authors: Sharma Anurag , Gupta Rajesh
Published: August 2022

This research paper proposes a novel bridgeless single-stage isolated converter with power factor correction and load voltage control. The proposed converter reduces the input diode bridge requirement with reduced passive components and provides a unidirectional flow of power to the load. The single-stage design reduces the use of an electrolytic capacitor, which improves reliability and reduces the size of the converter. The proposed control method is based on a single proportional integral (PI) controller to achieve both power factor correction and input current control. The proposed bridgeless converter is suitable for electric vehicle (EV) charging. A simulation study is performed on the MATLAB/Simulink to verify the effectiveness of the proposed converter. The converter is implemented in the laboratory to obtain the experimental results using typhoon hardware in the loop (HIL) based real time simulator.
Implementation of proportional–integral control in Baglog steamer temperature control
Authors: Fauziyah Mila , Adhisuwignjo Supriatna , Ayu Permatasari Dinda , Aisyah Ibrahim Nadira
Published: August 2022

Sterilization is the oyster mushroom cultivation process. Sterilization is used to kill nuisance microorganisms that can inhibit mushroom growth. The sterilization process is 8 hours at a temperature of 70–95 oC. This process of frequent breakdown is caused by the unstable temperature sterilization space and is controlled manually. Based on these problems, the right solution is to use a steamer that can be controlled automatically using the proportional–integral (PI) control method. PI controller consists of proportional gain and integral gain. To determine the value of proportional gain and integral gain, this study used the Ziegler-Nichols tuning method using the S curve. The results of the PI control parameters obtained the value of Kp=25.2 and Ki=0.302. Thus, producing a transient response graph with Mp=94.5; Os=0.45; PO=0.47; Tr=16,440 s. The system can work according to setpoint 95 oC and maintain a stable temperature according to the setpoint with these results. And the sterilization time becomes fast from 8 hours to 6 hours.
Characteristics with opposite of quranic letters mispronunciation detection: a classifier-based approach
Authors: AlTalmas Tareq , Ahmad Salmiah , Nik Hashim Nik Nur Wahidah , Shahbudin Hassan Surul , Sediono Wahju
Published: August 2022

Reading Quran for non-Arab is a challenge due to different mother tongues. learning Quran face-to-face is considered time-consuming. The correct pronunciation of Makhraj and Sifaat are the two things that are considered difficult. In this paper, Sifaat evaluation system was developed, focusing on Sifaat with opposites for teaching the pronunciation of the Quranic letters. A classifier-based approach has been designed for evaluating the Sifaat with opposites, using machine learning technique; the k-nearest neighbour (KNN), the ensemble random undersampling (RUSBoosted), and the support vector machine (SVM). Five separated classifiers were designed to classify the Quranic letters according to group of Sifaat with opposites, where letters that are classified to the wrong groups are considered mispronounced. The paper started with identifying the acoustic features to represent each group of Sifaat. Then, the classification method was identified to be used with each group of Sifaat, where best models were selected relying on various metrics; accuracy, recall, precision, and F-score. Cross-validation scheme was then used to protect against overfitting and estimate an unbiased generalization performance. Various acoustic features and classification models were investigated, however, only the outperformed models are reported in this paper. The results showed a good performance for the five classification models.
Effect of mixing ratio on the breakdown voltage of mineral and natural ester insulating oil blends
Authors: Ab Ghani Sharin , Sutan Chairul Imran , Ahmad Khiar Mohd Shahril , Hidayah Rahim Nor , Md Arshad@Hashim Syahrun Nizam
Published: August 2022

To date, the most common insulating oil used in oil-immersed transformers is mineral insulating (MI) oil, which is derived from petroleum. Owing to the depletion of petroleum over the years, it can be anticipated that petroleum-derived products such as MI oils will also deplete in the future. MI oils are not only non-renewable, but they are also non-biodegradable, where these oils are harmful to the environment in cases of oil spillage. Therefore, the aim of this study is to investigate the potential of mixing MI oil with natural ester insulating (NEI) oil in order to reduce the high dependency on MI oil for transformer applications. The MI and NEI oils were mixed with different mixing ratios. AC breakdown voltage test was conducted on the MI-NEI oil blends according to the ASTM D1816 standard. From the results, it is found that the following mixing ratios (30% of MI oil + 70% of NEI oil, 20% of MI oil + 80% of NEI oil) result in significant improvement in terms of the AC breakdown voltage compared with unused MI oil. The flash point and corrosivity levels of the oil blends were also examined.
Modeling and parameter estimation of solar photovoltaic based MPPT control using EKF to maximize efficiency
Authors: Kerid Rachid , Bounnah Younes
Published: August 2022

In this paper, we focus on the design, modeling and implementation of a MPPT controller based maximum power tracking of photovoltaic system. The electrical characteristic of The PV system is non-linear and changes with the solar irradiation and the ambient temperature. Therefore, the incremental conductance (IC) method control is known for its stability and robustness, and is used to extract the maximum energy from the PV source using a boost converter topology. It provides a strong basis for the improvement and optimization of control parameters of a photovoltaic system. Implementing MPPT algorithm usually need the use of a lot of sensors if accuracy of the system has to be increased. However, IC method with an extended Kalman ﬁlter (EKF) can be utilized in order to estimate some parameters to reduce the number of Sensors. The EKF is deployed in the optimal position to estimate both current and the capacitor voltage, thus allowing to eliminate two sensors devise from the entire PV system, which increases the system efficiency and reliability, simplifies the control method and decreases the system cost. The performance of the proposed technique is validated by experimental and simulation results under different operating conditions and load changes.
Noise resistance evaluation of spatial-field optical flow using modifying Lorentzian function
Authors: Kesrarat Darun , Patanavijit Vorapoj
Published: August 2022

This paper presents the evaluation of the modifying Lorentzian function on the spatial-field optical flow to examine the validity in the noisy domain of motion estimation. In the routine of the motion estimation, the frame’s motion vector is estimated by the optical flow approach where the flow of the image’s frames is caught to estimate the motion vector. Nevertheless, in the noisy domain, the preciseness of the motion vector is weakened. We operated the measurement along with several non-Gaussian noises standards through several styles of the standard image frame. The determination on error vector magnitude (EVM) was taken into account to consider the preciseness of direction and length of the motion vector (MV) in comparison with various noise resistance techniques in spatial-field optical flow approach. In the achievement results, we found that this modifying Lorentzian norm function added up in the optical flow strengthen the degree of preciseness in the estimation of the spatial-field optical flow approach in the noisy domain.