bluuebunny/crossref_metadata_2025 huggingface dataset:
Ellagic Acid Alleviates Rheumatoid Arthritis in Rats through Inhibiting MTA1/HDAC1-Mediated Nur77 Deacetylation
Authors: Song Huanjin , Wu Hao , Dong Jun , Huang Sihua , Ye Jintao , Liu Ruoxi
Published: December 2021

Ellagic acid (EA) was reported to play protective roles in rheumatoid arthritis (RA). It was found that the level of metastasis-associated gene 1 (MTA1)/histone deacetylase 1 (HDAC1) protein complex was downregulated by polyphenols in several human disorders. Notably, inhibition of MTA1 or HDAC1 has anti-inflammatory effects on RA. Therefore, our study is aimed at investigating whether EA prevents RA progression through regulating the MTA1/HDAC1 complex. Herein, the human fibroblast-like synoviocyte (FLS) cell line MH7A was treated with TNF-α to induce an inflammation model in vitro and then incubated with different concentrations of EA. Western blot analysis showed that EA reduced MTA1 expression in a dose-dependent manner in MH7A cells. Then, TNF-α-treated MH7A cells were incubated with EA alone or together with MTA1 overexpression plasmid (pcDNA-MTA1), and we found that EA inhibited proliferation, inflammation cytokine levels, and oxidative stress marker protein levels and promoted apoptosis in MH7A cells, while MTA1 overexpression abolished these effects. Moreover, coimmunoprecipitation assay verified the interaction between MTA1 and HDAC1. EA downregulated the MTA1/HDAC1 complex in MH7A cells. MTA1 knockdown inhibited proliferation, inflammation, and oxidative stress and promoted apoptosis in MH7A cells, while HDAC1 overexpression reversed these effects. Moreover, chromatin immunoprecipitation assay indicated that EA inhibited HDAC1-mediated Nur77 deacetylation. Rescue experiments demonstrated that Nur77 knockdown reversed the effects of EA on MH7A cell biological behaviors. Additionally, EA treatment attenuated arthritis index, paw swelling, synovial hyperplasia, and inflammation in collagen-induced arthritis (CIA) rats. In conclusion, EA inhibited proliferation, inflammation, and oxidative stress and promoted apoptosis in MH7A cells and alleviated the severity of RA in CIA rats though downregulating MTA1/HDAC1 complex and promoting HDAC1 deacetylation-mediated Nur77 expression.
A Comparison of GFR Calculated by Cockcroft-Gault vs. MDRD Formula in the Prognostic Assessment of Patients with Acute Pulmonary Embolism
Authors: Pływaczewska Magdalena , Jiménez David , Lankeit Mareike , Pruszczyk Piotr , Kostrubiec Maciej
Published: December 2021

Introduction. Risk stratification is mandatory for optimal management of patients with acute pulmonary embolism (APE). Previous studies indicated that renal dysfunction predicts outcome and can improve risk assessment in APE. Aim. The aim of the study was a comparison of estimated glomerular filtration rate (eGFR) formulas, MDRD, and Cockcroft-Gault (CG), in the prognostic assessment of patients with APE. Materials and Methods. Data from 2274 (1147 M/1127 F, median 71 years) hospitalised patients with APE prospectively included in a multicenter, observational, cohort study were analysed. A serum creatinine measurement as a routine laboratory parameter at the cooperating centers and eGFR calculation were performed on admission. Patients were followed for 180 days. The primary outcome was death from any cause within 30 days. Results. The eGFR levels assessed by both, MDRD (eGFRMDRD) and CG formula (eGFRCG), were highest in patients with low-risk APE and lowest in high-risk APE. The eGFR (using both methods) was significantly lower in nonsurvivors compared to survivors. Using a threshold of <60 ml/min/1.73 m2, eGFRMDRD revealed the primary outcome with sensitivity 67%, specificity 52%, PPV 8%, and NPV 97%, while eGFRCG had a sensitivity 62%, specificity 62%, PPV 8.6%, and NPV 96%. The area under the ROC curve for eGFRCG tended to be higher than that for eGFRMDRD: 0.658 (95% CI: 0.608-0.709) vs. 0.631 (95% CI: 0.578-0.683),

p
=
0.12

. A subanalysis of ROC curves in a population above 65 yrs showed a higher AUC for eGFRCG than based on MDRD. Kaplan-Meier analysis showed a worse long-term outcome in patients with impaired renal function. Conclusion. eGFRMDRD and eGFRCG assessed on admission significant short- and long-term mortality predictors in patients with APE. The eGFRCG seems to be a slightly better 30-day mortality predictor than eGFRMDRD in the elderly.
Dynamic Mechanical Properties and Damage Mechanism of Freeze-Thaw Sandstone under Acid Corrosion
Authors: Cao Xiaoxiao , Feng Meimei , Yuan Kangsheng
Published: December 2021

During the construction of geotechnical engineering in cold regions, the stability of rock is inevitably affected by freeze-thaw cycles and hydrochemical corrosion. In order to study the effect of hydrochemical corrosion on dynamic mechanical properties of freeze-thaw rocks, dynamic compression tests were carried out on sandstone samples corroded by four different concentrations of HCl solutions with the same number of freeze-thaw cycles using split-Hopkinson pressure bar (SHPB) test system. The coupling effects of freeze-thaw cycles with different concentrations of HCl solutions and strain rate on mechanical properties of sandstones were explored. The results showed that strain rate could enhance the dynamic compressive strength and peak strain but had no significant effect on the elastic modulus. The coupling effect of freeze-thaw cycles and acid corrosion weakened the dynamic compressive strength, and elastic modulus but enhanced the peak strain. In addition, X-ray diffractometer (XRD) and scanning electron microscope (SEM) were used to analyze the changes of mineral composition and microstructure damage of sandstone samples under the coupling effect of acid corrosion and freeze-thaw cycles. The analysis results were basically consistent with the damage characteristics of macro mechanical properties. The research results can provide reference for open pit coal mining in cold regions.
Period Analysis of Intraracial Differences in Incidence and Survival Rates in Epithelial Ovarian Cancer
Authors: Han Lili , Husaiyin Sulaiya , Liu Jing , Maimaiti Miherinisha , Niyazi Mayinuer , Li Li
Published: December 2021

Background. To explain the difference in the incidence and relative survival in a population-based cohort of women with epithelial ovarian cancer (EOC) postdiagnosis in the last forty years. EOC is the most common type of all ovarian cancers, but there is inadequate information about the variations related to long-term EOC survival. Methods. We acquired the incidence and relative survival rate data from the Surveillance, Epidemiology, and End Results (SEER) registries to analyze the epidemiological variations from 1974 to 2013 in EOC-affected individuals. The survival disparities in EOC-specific individuals due to age, race, and socioeconomic status (SES) were performed by Kaplan-Meier analysis. The Results. The overall incidence of EOC progressively declined to 9.0 per 100,000 from 11.4 in the last forty years. The median survival rate improved to 48 months in the first decade from a previous of 27 months in the fourth decade. The 5-year relative survival rate (RSR) increased to 44.3% that was previously 32.3% at the same time. However, between whites and blacks, an increase from 11 to 18 months was observed in the median survival differences. Between the low and high poverty groups, it was increased from 7 months to 12 months, respectively. Conclusions. The incidence rate of RSR and EOC-specific individuals in the last forty years was improved. However, the survival rates among different races and SES differed over time.
Aprepitant Promotes Caspase‐Dependent Apoptotic Cell Death and G2/M Arrest through PI3K/Akt/NF‐κB Axis in Cancer Stem‐Like Esophageal Squamous Cell Carcinoma Spheres
Authors: Javid Hossein , Afshari Amir R. , Zahedi Avval Farnaz , Asadi Jahanbakhsh , Hashemy Seyed Isaac
Published: December 2021

The antagonists of the neurokinin‐1 receptor (NK1R) are known for their anti‐inflammatory, anxiolytic, antiemetic, and anticancer activities. Aprepitant, a nonpeptide NK1R antagonist, is used in nausea and vomiting, the most common side effects of cancer chemotherapy in patients. It has been established that NK1R activation by substance P (SP), which links cancer promotion and progression to a neurokinin‐mediated environment, became one mechanism that corresponds to the mitogenesis of tumor cells. Therefore, this study is aimed at explaining and evaluating the anticancer impacts of aprepitant on esophageal squamous cancer cell (ESCC) spheres by using in vitro experiments, such as resazurin, ROS, annexin‐V binding, RT‐PCR, and Western blot analysis. As a result, we showed that aprepitant had strong antiproliferative and cytotoxic effects on ESCC cell spheres. Also, aprepitant caused significant G2‐M cell cycle arrest depending on concentration increase. Further, exposure of cells to this agent resulted in caspase ‐8/‐9‐dependent apoptotic pathway activation by modifying the expression of genes involved in apoptosis. Besides, treatment of the cells by aprepitant abrogates of the PI3K/Akt pathway, as shown by reducing the level of Akt, induces apoptotic cell death. In summary, pharmacological inhibition of NK1R with aprepitant seems to have a significant chance of treating ESCC as a single agent or in conjunction with other chemotherapeutic drugs.
Interventional Treatment of Bronchiectasis Macrosomia Based on Multirow CT Tomography Monitoring
Authors: Lu DongDong , Chai Wenshu , Gao Xue , Yan Xue
Published: December 2021

We present in this paper an in-depth study and analysis of bronchiectasis haemoptysis by multirow CT tomography and a multifaceted treatment and analysis of the interventions monitored by the scan. Although coronary CT is of great clinical value in the diagnosis and monitoring of coronary artery disease, the potential radiation damage caused by coronary CT should not be underestimated because CT imaging is based on X-rays and the actual effective dose is 5–30 mSv, which is reported in the literature to be high when using conventional imaging modalities for coronary CT. Although there is no direct evidence of a definite causal relationship between X-ray exposure during CT examinations and tumorigenesis, theoretically, even small doses of radiation exposure may pose some potential health risk. Therefore, in clinical practice, coronary CT examinations should be performed in strict compliance with the radiation protection rule “as low as reasonably achievable” (ALARA) recognized by the radiation industry. For longitudinal openings in the range of 0° to 59° and transverse openings in the range of 0° to 44°, the CB2 catheter is significantly more stable than the MIK catheter, and for longitudinal openings in the range of 60° to 119° and transverse openings in the range of 0° to 44°, the CB2 catheter is more stable than the MIK catheter. For longitudinal openings from 0° to 120° and lateral openings from 45° to 90°, there was no significant difference in cannulation stability between the CB2 and MIK catheters. There was a potential tendency for MIK cannulation stability to be higher than CB2 for longitudinal openings in the range of 120° to 180° and lateral openings in the range of 45° to 90°, but there was no significant difference.
One‐Step Robust Low‐Rank Subspace Segmentation for Tumor Sample Clustering
Authors: Liu Jian , Cheng Yuhu , Wang Xuesong , Ge Shuguang
Published: December 2021

Clustering of tumor samples can help identify cancer types and discover new cancer subtypes, which is essential for effective cancer treatment. Although many traditional clustering methods have been proposed for tumor sample clustering, advanced algorithms with better performance are still needed. Low‐rank subspace clustering is a popular algorithm in recent years. In this paper, we propose a novel one‐step robust low‐rank subspace segmentation method (ORLRS) for clustering the tumor sample. For a gene expression data set, we seek its lowest rank representation matrix and the noise matrix. By imposing the discrete constraint on the low‐rank matrix, without performing spectral clustering, ORLRS learns the cluster indicators of subspaces directly, i.e., performing the clustering task in one step. To improve the robustness of the method, capped norm is adopted to remove the extreme data outliers in the noise matrix. Furthermore, we conduct an efficient solution to solve the problem of ORLRS. Experiments on several tumor gene expression data demonstrate the effectiveness of ORLRS.
Trilaciclib Prior to Chemotherapy in Patients with Metastatic Triple-Negative Breast Cancer: Final Efficacy and Subgroup Analysis from a Randomized Phase II Study
Authors: Tan Antoinette R. , Wright Gail S. , Thummala Anu R. , Danso Michael A. , Popovic Lazar , Pluard Timothy J. , Han Hyo S. , Vojnović Željko , Vasev Nikola , Ma Ling , Richards Donald A. , Wilks Sharon T. , Milenković Dušan , Xiao Jie , Sorrentino Jessica , Horton Janet , O'Shaughnessy Joyce
Published: December 2021

Purpose:

We report final antitumor efficacy results from a phase II study of trilaciclib, an intravenous cyclin-dependent kinase 4/6 (CDK4/6) inhibitor, administered prior to gemcitabine plus carboplatin (GCb) in patients with metastatic triple-negative breast cancer (NCT02978716).

Patients and Methods:

Patients were randomized (1:1:1) to group 1 [GCb (days 1, 8); n = 34], group 2 [trilaciclib prior to GCb (days 1, 8); n = 33], or group 3 [trilaciclib (days 1, 8) and trilaciclib prior to GCb (days 2, 9); n = 35]. Subgroup analyses were performed according to CDK4/6 dependence, level of programmed death-ligand 1 (PD-L1) expression, and RNA-based immune signatures using proportional hazards regression. T-cell receptor (TCR) β CDR3 regions were amplified and sequenced to identify, quantify, and compare the abundance of each unique TCRβ CDR3 at baseline and on treatment.

Results:

Median overall survival (OS) was 12.6 months in group 1, not reached in group 2 (HR = 0.31; P = 0.0016), 17.8 months in group 3 (HR = 0.40; P = 0.0004), and 19.8 months in groups 2 and 3 combined (HR = 0.37; P < 0.0001). Efficacy outcomes were comparable regardless of cancer CDK4/6 dependence status and immune signatures. Administering trilaciclib prior to GCb prolonged OS irrespective of PD-L1 status but had greater benefit in the PD-L1–positive population. T-cell activation was enhanced in patients receiving trilaciclib.

Conclusions:

Administering trilaciclib prior to GCb enhanced antitumor efficacy, with significant improvements in OS. Efficacy outcomes in immunologic subgroups and enhancements in T-cell activation suggest these improvements may be mediated via immunologic mechanisms.
Three Generations of FLNA-Associated Periventricular Nodular Heterotopia
Authors: Eisenbiegler Grace E. , Brown Stephen A.
Published: December 2021

We present a family with 3 generations of FLNA gene-associated periventricular nodular heterotopia (PVNH), with a unique presentation in a fetus with multiple neurologic malformations. Neurologic abnormalities were noted on routine fetal imaging for a 33-year-old G1P0 woman; absence of the corpus callosum and PVNH was confirmed on follow-up MRI. This prompted genetic evaluation, revealing a nonsense mutation in the FLNA gene. Familial genetic analysis and neuroimaging revealed the same variant and MRI evidence of PVNH in the fetus’s asymptomatic mother, and maternal grandmother, who had a long history of seizure disorder. Such phenotypic variability within a single family demonstrates the spectrum of PVNH and the importance of genetic counseling for patients with PVNH. This case also adds to existing literature on the rare but not unique presentation of FLNA-associated fetal malformations.
Epidemiology of Primary Brain Tumors in the Province of Catania during the 2003–2016 Period
Authors: Chebil Chaima , Boumediene Farid , Cicero Calogero E. , Rascunà Cristina , Di Prima Alessia , Torrisi Antonietta A.M. , Ippolito Antonella , Sciacca Salvatore , Zappia Mario , Preux Pierre-Marie , Ferrante Margherita , Nicoletti Alessandra ,   on behalf of CT-ME-EN Cancer Registry Workers
Published: December 2021

Introduction: Primary brain tumors (PBTs) account for approximately 2% of all cancers and are associated with significant morbidity and mortality. However, only few epidemiological studies focus on PBTs in Italy. The aim of this study was to evaluate incidence, temporal trend, and survival rate of all PBTs in the province of Catania during the study period. Methods: All patients diagnosed with PBTs in the province of Catania during the 2003-2016 were identified through the local cancer registry. All cases were classified by histology according to 2007 WHO classification of central nervous system tumors, using the International Classification of Diseases for Oncology, 3rd edition codes. The incidence rate (IR) was calculated for all PBTs and by gender, histology, age-groups, and behavior. Trend analysis was performed using a piecewise log-linear model. Results: A total of 3,819 cases were identified with a female/male ratio of 1.45. The IR for all PBTs was 25.3/100,000 person-years (95% confidence interval 24.5–26.1). Most PBTs were nonmalignant (59.5%, IR = 15.0) with a female predominance. Conversely, malignant tumors (32.4%, IR = 8.2) were more common among men, with a female/male ratio of 0.9. The most frequently reported histology was meningioma (39.0%, IR = 9.8), followed by glioblastoma (11.6%, IR = 2.9). A peak of incidence was found in the 75–84 years age-group, with an IR of 77.6/100,000 person-years. Overall, no increase in incidence was observed along the study period. Conclusions: The IR of PBTs in the province of Catania is close to incidence reported worldwide. Further studies on risk factors are necessary.
Communicating Bad News to Older Patients from the Physician’s Point of View: Focus on the Influence of Gender and Length of Work Experience
Authors: Vogliotti Edoardo , Pintore Giulia , Zoccarato Francesca , Biasin Matteo , Sergi Giuseppe , Inelmen Emine Meral , Trevisan Caterina
Published: December 2021

Background: Communicating bad news is of great interest in the geriatric field, but few works have considered the physician’s point of view in this regard. Objectives: The aim of this study was to explore possible differences related to physicians’ gender and work experience in how a terminal diagnosis is disclosed to older patients. Methods: Study participants were 420 Italian physicians (277 M, 143 F) working in clinical medicine (58.2%), surgery (33.3%), or other medical departments (8.5%). They completed an anonymous multiple-choice questionnaire that investigated various issues associated with communicating bad news to terminally ill older patients. Results: Men had more work experience than women (55.6% vs. 44.8% had worked for ≥23 years) and were more likely to work in surgery departments, while more women worked in clinical medicine. Most physicians declared that terminally ill older patients, if mentally competent, should always (14.4%) or generally (64.3%) be directly and openly informed of their condition. With no difference in gender, length of work experience, or specialty area, 36.9% of physicians thought that this was a human right and 18% that it would improve the patient’s quality of life. Where older patients were alone, male physicians were more likely than female (30.2% vs. 8.9%) to always communicate bad news directly to them. More than 70% of physicians, especially those with longer work experience, declared that they always or often took enough time to inform the patient. Female physicians and those working in clinical medicine were more likely to need psychological help when deciding to break bad news, but only a smaller proportion declared to have received it. Conclusions: Gender and work experience may influence how physicians communicate with patients and how often they seek psychological support.
Frequent Placental SARS-CoV-2 in Patients with COVID-19-Associated Hypertensive Disorders of Pregnancy
Authors: Fabre Marta , Calvo Pilar , Ruiz-Martinez Sara , Peran Maria , Oros Daniel , Medel-Martinez Ana , Strunk Mark , Benito Ruesca Rafael , Schoorlemmer Jon , Paules Cristina
Published: December 2021

Introduction: Studies described an increased frequency of hypertensive disorders of pregnancy (HDP) after a COVID-19 episode. There is limited evidence about SARS-CoV-2 viral load in placenta. This study aimed to investigate the relationship between SARS-CoV-2 viral load in the placenta and clinical development of HDP after COVID-19 throughout different periods of gestation. Methods: This is a case-control study in women with and without gestational hypertensive disorders after SARS-CoV-2 infection diagnosed by RT-PCR during pregnancy. Patients were matched by gestational age at the moment of COVID-19 diagnosis. We performed an analysis of SARS-CoV-2 RNA levels in placenta. Results: A total of 28 women were enrolled. Sixteen patients were diagnosed with COVID-19 during the third trimester and the remaining 12 patients in the other trimesters. Ten placentas (35.7%) were positive for SARS-CoV-2, 9 of them (9/14, 64.3%) belonged to the HDP group versus 1 (1/14, 7.2%) in the control group (p = 0.009). Those cases with the highest loads of viral RNA developed severe preeclampsia (PE). Conclusion: Among women diagnosed with COVID-19 during pregnancy, the presence of SARS-CoV-2 in the placenta was more frequent among women suffering from PE or gestational hypertension. Furthermore, the most severe cases of HDP were associated with high placental viral load, not necessarily associated with a positive nasopharyngeal RT-PCR at delivery. Our data suggest that SARS-CoV-2 infection during pregnancy could trigger gestational hypertensive disorders through persistent placental infection and resulting placental damage.
Course of Stress during the Neonatal Intensive Care Unit Stay in Preterm Infants
Authors: van Dokkum Nienke H. , de Kroon Marlou L.A. , Dijk Peter H. , Kraft Karianne E. , Reijneveld Sijmen A. , Bos Arend F.
Published: December 2021

Introduction: Understanding the course of stress during the neonatal intensive care unit stay may provide targets for interventions. Our aim was to describe the course of stress in preterm infants during the first 28 days of life, the influence of gestational age, and associations with clinical characteristics. Methods: In a single centre prospective cohort study, we included infants with a gestational age <30 weeks and/or birth weight <1,000 g. We measured stress over the first 28 days using the Neonatal Infant Stressor Scale (NISS). We plotted daily NISS total and subcategory scores by gestational age. The subcategories were (1) nursing, (2) skin-breaking, (3) monitoring and imaging, and (4) medical morbidity-related scores. We assessed associations of cumulative NISS scores over the first 7, 14, and 28 days with clinical characteristics using regression analyses. Results: We included 45 infants, with a median gestational age of 27 weeks. The mean daily NISS score was 66.5 (SD 8.7), with highest scores in the first 7 days of life. Scores decreased the slowest for the lowest gestational ages, in particular for nursing scores, rather than skin-breaking, monitoring and imaging, and medical morbidity-related scores. Adjusted for gestational age, infants with lower Apgar scores, sepsis, intraventricular haemorrhages, and on mechanical ventilation had significantly higher cumulative NISS scores at 7, 14, and 28 days. Conclusion: NISS scores varied greatly within infants and over time, with the highest mean scores in the first week after birth. The course of declining NISS scores in the first 28 days depended on gestational age at birth.
Identification of 8 Feature Genes Related to Clear Cell Renal Cell Carcinoma Progression Based on Co-Expression Analysis
Authors: Yu Xiaoxia , Wu Hua , Wang Hongmei , Dong He , Gao Bihu
Published: December 2021

Background: The aim of the study was to screen biomarkers related to clear cell renal cell carcinoma (ccRCC) progression and prognosis. Methods: 1,026 ccRCC-related genes were dug from 494 ccRCC samples in TCGA based on weighted gene co-expression network analysis, and 7 modules were identified. Afterward, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were conducted on modules of interest. Genes in these modules were taken as the input to construct a protein-protein interaction network. Thereafter, 30 genes with the highest connectivity were taken as core genes. Univariate Cox regression, LASSO Cox regression, and multivariate Cox regression analyses were performed on core genes. Univariate and multivariate Cox regression analyses were performed on patients’ clinical characteristics and risk scores. Results: Stage displayed significantly strong correlations with green module and red module (p < 0.001). Genes in modules participated in biological functions including T-cell proliferation and regulation of lymphocyte activation. GSEA showed that high- and low-risk groups exhibited significant enrichment differences in pathways related to immunity, cell migration, and invasion. Immune infiltration analysis also presented a strong correlation between the expression of these 8 genes and immune cell infiltration in ccRCC samples. It was displayed that risk score could be an independent factor to assess patients’ prognosis. Conclusion: We determined biomarkers relevant to ccRCC progression, offering candidate targets for ccRCC treatment.
Systemic Immune-Inflammatory Index Association with Survival in Patients Undergoing Trimodality Therapy for Lung Cancer
Authors: Coutu Brendan G. , Johnson Kurtis C. , Bhirud Abhi , Baine Michael J. , Zhen Weining , Zhang Chi , Trujillo Karin P. , Bennion Nathan R.
Published: December 2021

Purpose: The systemic immune-inflammation index (SII) is correlated with patient survival in various solid malignancies including non-small-cell lung cancer (NSCLC). However, limited information is available on the prognostic implication of the SII in patients undergoing trimodality therapy for stage III NSCLC. Methods: At our institution, 81 patients underwent curative intent trimodality therapy (neoadjuvant chemoradiotherapy followed by surgical resection) for stage III NSCLC from 2004 to 2019. The SII was calculated at the time of diagnosis as platelet count × neutrophil count/lymphocyte count. χ2 analysis was used to compare categorical variables. A Kaplan-Meier analysis was performed to estimate disease-free survival (DFS), overall survival (OS), and freedom from recurrence (FFR) rates, with Cox regression used to determine absolute hazards. Results: Patients underwent neoadjuvant radiation therapy to a median dose of 4,500 cGy concurrent with a median of 3 cycles of chemotherapy (most commonly carboplatin and paclitaxel) followed by surgical resection (86.4% lobectomy and 13.6% pneumonectomy) with mediastinal lymph node dissection. At a median follow-up of 68.4 months, a low SII (<1,260) at diagnosis was independently associated with an improved OS (hazard ratio [HR]: 0.448, p = 0.004), DFS (HR: 0.366, p < 0.001), and FFR (HR: 0.325, p = 0.002). Conclusions: We identified that a low SII was associated with improved OS, DFS, and FFR in patients undergoing trimodality therapy for stage III NSCLC. The interplay of the immune system and lung cancer outcomes remains an active area of investigation for which further study is warranted.
Plant leaf identification system using convolutional neural network
Authors: Taslim Amiruzzaki , Saon Sharifah , Mahamad Abd Kadir , Muladi Muladi , Hidayat Wahyu Nur
Published: December 2021

This paper proposes a leaf identification system using convolutional neural network (CNN). This proposed system can identify five types of local Malaysia leaf which were acacia, papaya, cherry, mango and rambutan. By using CNN from deep learning, the network is trained from the database that acquired from leaf images captured by mobile phone for image classification. ResNet-50 was the architecture has been used for neural networks image classification and training the network for leaf identification. The recognition of photographs leaves requested several numbers of steps, starting with image pre-processing, feature extraction, plant identification, matching and testing, and finally extracting the results achieved in MATLAB. Testing sets of the system consists of 3 types of images which were white background, and noise added and random background images. Finally, interfaces for the leaf identification system have developed as the end software product using MATLAB app designer. As a result, the accuracy achieved for each training sets on five leaf classes are recorded above 98%, thus recognition process was successfully implemented.
Single phase inverter fed through a regulated SEPIC converter
Authors: Mahmood Adil Hasan , Mohammed Mustafa F. , Omar Mohammed , Ahmad Ali H.
Published: December 2021

In power electronics, it is necessary to select the best converter circuit topology that has good performance among different converters. The single-ended primary inductor converter (SEPIC) has good performance and is advantageous among different direct current/direct current (DC/DC) converters. In this paper, a design of a SEPIC converter is made by selecting the values of its components according to the required output voltage and power. The design is made by an assumption that both of its inductors have the same value. The converter is tested by using MATLAB Simulink successfully. Later, its output voltage is regulated by using a proportional integral (PI-controller) through tuning its proportional and integral gains. Finally, the SEPIC converter is connected to a single-phase full-bridge inverter to supply its required DC voltage. The role of the SEPIC converter is to regulate the dc-link voltage between its output side and the inverter. The results showed the success of this connection to supply alternating current (AC) loads with low total harmonic distortion (THD).
Comparing the performance of linear regression versus deep learning on detecting melanoma skin cancer using apple core ML
Authors: Sujaini Herry , Ramadhan Enriko Yudhistira , Novriando Haried
Published: December 2021

Melanoma is a type of deadly skin cancer. The survival rate of the patients can fall as low as 15.7% if the cancer cell has reached its final stage. Delayed treatment of melanoma can be attributed to its likeness to that of common nevus (moles). Two machine learning models were developed, each with a different approach and algorithm, to detect the presence of melanoma. Image classification is using the regression algorithm, and object detection is using deep learning. The two models are then compared, and the best model is determined according to the achieved metrics. The testing was conducted using 120 testing data and is made up of 60 positive data and 60 negative data. The testing result shows that object detection achieved 70% accuracy than image classification’s 68%. More importantly, linear regression’s 43% false-negative rate is noticeably high compared to convolutional neural network’s (CNN) 25%. A false-negative rate of 43% means almost half of sick patients tested using image classification will be diagnosed as healthy. This is dangerous as it can lead to delayed treatment and, ultimately, death. Thus it can be concluded that CNN is the best method in detecting the presence of melanoma.
E-commerce online review for detecting influencing factors users perception
Authors: Arsad Irvan Krisna , Setyohadi Djoko Budiyanto , Mudjihartono Paulus
Published: December 2021

To date, online shopping using e-commerce services becomes a trend. The emergence of e-commerce truly helps people to shop more effectively and efficiently. However, there are still some problems encountered in e-commerce, especially from the user perspective. This research aims to explore user review data, particularly on factors that influence user perception of e-commerce applications, classify, and identify potential solutions to finding problems in e-commerce applications. Data is grabbed using web scraping techniques and classified using proper machine learning, i.e., support vector machine (SVM). Text associations and fishbone analysis are performed based on the classified user review data. The results of this study show that the user satisfaction problem can be captured. Furthermore, various services that should be provided as a potential solution to experienced customers' problems or application users' perception problems can be generated. A detailed discussion of these findings is available in this article.
Non-linear behavior of root and stem diameter changes in monopodial orchid
Authors: Nordin Mohd Khairi , Saaid Mohammad Farid , Tahir Nooritawati Md , Ihsan Mohd Yassin Ahmad , Syahirul Amin Megat Ali Megat
Published: December 2021

Precision agriculture aims to maximize yield with optimum resources. Vast majority of natural systems are acknowledged as complex and non-linear. However, prior to formulation of precise models, linearity tests are performed to validate plant behavior. This study has presented proof that the water uptake system in monopodial orchid is indeed non-linear. The change in physical growth of root and stem due to temperature and relative humidity factors are observed. The work focused on Ascocenda Fuchs Harvest Moon x (V. Chaophraya x Boots) orchid hybrid. Three complementary methods are presented: linearity tests through 1) regression fitting; 2) scatter plots; and 3) cross-correlation function tests. Root diameter, stem diameter, temperature, and relative humidity are logged at 15 minutes interval for a duration of 71 days. The polynomial equations derived for root diameter and stem diameter changes attained strong regression coefficients. The non-linear behavior is further confirmed by the scatter plots where no linear associations are present between the independent and dependent variables. Subsequently, the cross-correlation function tests conducted on temperature-root diameter, temperature-stem diameter, relative humidity-root diameter, and relative humidity-stem diameter combinations also revealed weak correlation. Despite using different techniques, the behavior of physical changes has been consistently proven to be non-linear.
Assessing mangrove deforestation using pixel-based image: a machine learning approach
Authors: Dawod Ahmad Yahya , Sharafuddin Mohammed Ali
Published: December 2021

Mangrove is one of the most productive global forest ecosystems and unique in linking terrestrial and marine environment. This study aims to clarify and understand artificial intelligence (AI) adoption in remote sensing mangrove forests. The performance of machine learning algorithms such as random forest (RF), support vector machine (SVM), decision tree (DT), and object-based nearest neighbors (NN) algorithms were used in this study to automatically classify mangrove forests using orthophotography and applying an object-based approach to examine three features (tree cover loss, above-ground carbon dioxide (CO2) emissions, and above-ground biomass loss). SVM with a radial basis function was used to classify the remainder of the images, resulting in an overall accuracy of 96.83%. Precision and recall reached 93.33 and 96%, respectively. RF performed better than other algorithms where there is no orthophotography.
A multi-task learning based hybrid prediction algorithm for privacy preserving human activity recognition framework
Authors: Kambala Vijaya Kumar , Jonnadula Harikiran
Published: December 2021

There is ever increasing need to use computer vision devices to capture videos as part of many real-world applications. However, invading privacy of people is the cause of concern. There is need for protecting privacy of people while videos are used purposefully based on objective functions. One such use case is human activity recognition without disclosing human identity. In this paper, we proposed a multi-task learning based hybrid prediction algorithm (MTL-HPA) towards realising privacy preserving human activity recognition framework (PPHARF). It serves the purpose by recognizing human activities from videos while preserving identity of humans present in the multimedia object. Face of any person in the video is anonymized to preserve privacy while the actions of the person are exposed to get them extracted. Without losing utility of human activity recognition, anonymization is achieved. Humans and face detection methods file to reveal identity of the persons in video. We experimentally confirm with joint-annotated human motion data base (JHMDB) and daily action localization in YouTube (DALY) datasets that the framework recognises human activities and ensures non-disclosure of privacy information. Our approach is better than many traditional anonymization techniques such as noise adding, blurring, and masking.
Micro hydropower plant potential study based on Landsat 8 operational land imager satellite data
Authors: Susilowati Yuliana , Irasari Pudji , Kumoro Yugo , Nur Wawan Hendriawan , Yunarto Yunarto
Published: December 2021

Remote sensing technology has been widely applied in various fields, including oil, gas, and mineral exploration, spatial planning, and environmental monitoring. This paper describes the application of remote sensing technology for the potential study of a renewable micro hydropower plant (MHP) using Landsat 8 satellite data. The Sukaati Watershed, West Java, Indonesia, was selected as the case study area. Landsat 8 satellite data, acquired on August 21, 2020, was applied to extract information on land use, geology, and potential landslides. Drainage patterns, watershed boundaries, and head height were obtained from topographic map data. Drainage patterns, watershed boundaries, and land use are used to calculate flow rates. Geological map and landslide are the basis of layout of MHP components, such as water intake, dam, waterway, settling tank, penstock, and powerhouse. A field survey to acquire actual flow rate and head height was conducted to validate the results of the remote sensing data interpretation. Two potential sites of MHP were selected with a hydropower design of 129 kW and 5.18 MW. This study showed that remote sensing technology is beneficial for studying the potential of MHP because fieldwork can be done more quickly and efficiently.
Symptoms based endometriosis prediction using machine learning
Authors: Sankaravadivel Visalaxi , Thalavaipillai Sudalaimuthu
Published: December 2021

Endometriosis a painful disorder that stripes the uterus both inside and outside. Endometriosis can be diagnosed by the medical practitioners with the help of traditional scanning procedures. Laparoscopic surgery is the authentic method for identifying the advanced stages of endometriosis. The statistical approach is a state-of-art method for identifying the various stages of endometriosis using laparoscopic images. The paper focuses on a well-known statistical method known as chi-square and correlation coefficients are implemented for identifying the symptoms that are correlated with various stages of endometriosis. Chi-square analysis performs the association between symptoms and stages of endometriosis. With these analysis, an algorithm was proposed known as endometriosis prediction factor algorithm (EPF). The EPF algorithm predicts the presence of endometriosis if the derived value is greater than 1. From the chi-square analysis, it is identified that mild endometriosis is influenced 34% by menstrual flow, minimal endometriosis is influenced 40% by dysmenorrhea, where moderate endometriosis is influenced 31% by tenderness and deep infiltrating endometriosis is influenced 22% by adnexal mass.
Overview of microgrid systems
Authors: Saravanan V. , Venkatachalam K. M. , Arumugam M. , Borelessa M. A. K. , Hemapala K.T. M.U.
Published: December 2021

This research paper discusses the different types of microgrids, their structural arrangements and the technology adopted for different power management projects. It also deals with various control strategies and security plans used for optimal performance. A detailed overview of the direct current (DC) microgrid system is discussed, outlining its configurations and technical-economic aspects. Performance evaluation of microgrid carried out through various reliability codes is also provided.
A comparative study on radio frequency identification system and its various applications
Authors: Ahmad Muhammad Baballe , Nababa Fatima Alkasim
Published: December 2021

The radio frequency identification (RFID), is a wireless technology system that is used for identifying an individual or objects through the means of radio waves that transfer information from an electronic tag, called an RFID tag. RFID consists of two main components the interrogator and the transponder. The Interrogator, which is the RFID reader, the interrogator usually transmits and receives the signal while the transponder that is the tag, is attached to the object. In the RFID system, an RFID reader interrogates the RFID tags. This tag reader generates a radio frequency interrogation, which communicates with the tags been registered in the system. This reader likewise has a receiver that captures a reply signal generated from the tags and decodes the signal. This reply signal from the tags reflects the tag's information content. Each tag of the employee or student consists of a unique identity, identification card (ID) that is assigned to a single employee or student ID card, which is recorded, in the database of the system. This research reviews some recent designs and implementation of internet of things (IoT) attendance systems using the concept of the RFID system. The analysis found that the RFID system is a very advanced technology for an automatic attendance system in an institution, organization, or university and it provides a very higher performance and accuracy than the traditional paper-based system that the employees or students normally used to sign. The use of the RFID technology enables the institution, authorities, or management to evade attendance documents from damages such as misplacement, tear, or even got lost. A combination of the model is needed which will confirm higher security, better performance, and consistency of the system.
Comparison of color-based feature extraction methods in banana leaf diseases classification using SVM and K-NN
Authors: Said Nur Sholehah Mat , Madzin Hizmawati , Ali Siti Khadijah , Beng Ng Seng
Published: December 2021

In Malaysia, banana is a top fruit production which contribute to the economy growth in agriculture field. Hence, it is significant to have a quality production of banana and important to detect the plant diseases at the early stage. There are many types of banana leaf diseases such as Banana Mosaic, Black Sigatoka and Yellow Sigatoka. These three diseases are related to color changes at banana. This research paper is an experiment based and need to identify the best color feature extraction method to classify banana leaf diseases. Total of 48 banana leaf images that are used in this research paper. Four types of color feature extraction methods which are color histogram, color moment, hue, saturation, and value (HSV) histogram and color auto correlogram are experimented to determine the best method for banana leaf diseases classification. While for the classifiers, support vector machine (SVM) and k-Nearest neighbors (k-NN) are used to evaluate the performance and accuracy of each color feature extraction methods. There are also preliminary experiments to identify accurate parameters to use during classification for both classifiers. Our experimental result express that HSV histogram is the best method to classify banana leaf diseases with 83.33% of accuracy and SVM classifier perform better compared to k-NN.
Virtual education and student perception of teacher performance in the distance learning environment
Authors: Flores-Cáceres Richard , León-Velarde Cesar , Díaz-Leyva Teodoro , Escobedo-Bailón Frank , Ortega-Galicio Orlando , Chirinos-Mendoza Antuanet , Tasayco-Jala Abel
Published: December 2021

This article aims to carry out a descriptive analysis of the performance of teachers qualified as researchers, in the distance education environment according to the student's perspective. The results will be a frame of reference for university authorities on the path of continuous improvement of virtual education. When carrying out the research, a general qualification of the teaching performance of 14.20 was determined, established the highest grade equal to 20, it can be indicated that there is a good performance of the teacher in the virtual education environment. In addition, the results show that the highest evaluation corresponds to the indicator management of the group and fulfillment of the objectives, which is directly related to the administration of the class, while the lowest rating is for the indicator "Teacher effectiveness so that their students acquire relevant knowledge, skills and attitudes”, which is directly related to the didactic strategies used, that is, to the use of technological tools that today are more than just an option. Finally, it can be noted that of the total of 17 teaching, 23.5% present a very good performance, 35.3% present a good performance and 41.2% present a regular performance.
Bayesian estimate of system availability for consecutive k-out-of-n:F system
Authors: J. Madhumitha , Vijayalakshmi G.
Published: December 2021

In the efficient design and functionality of complex systems, redundancy problems in systems play a key role. The consecutive-k-out-of-n:F structure, which has broad application in street light arrangements, vacuum systems in an accelerator, sliding window detection, relay stations for a communication system. Availability is one of the significant measures for a maintained device because availability accounts for the repair capability. A very significant feature is the steady-state availability of a repairable device. For the repairable consecutive k-out-of-n:F system with independent and identically distributed components, the Bayesian point estimate (B.P.E) of steady-state availability under squared error loss function (SELF) and confidence interval are obtained.
Speed control in DC and AC drives
Authors: Aguedo Reinel Beltran , Lussón Cervantes Ania , Núñez Alvarez José Ricardo , Llosas Albuerne Yolanda
Published: December 2021

Three speed-control strategies for DC and AC drives are presented in this study: a proportional integral derivative (PID) control strategy; an internal model control (IMC); and a state-space control by pole assignment with full state observer (ESSO). The three strategies are applied to a case study, demonstrating the potential of each one. Experimental identification was used to obtain the drive models used for the synthesis of the controllers. The three strategies showed satisfactory results when compared with the requirements imposed on the system, in addition to the good rejection of disturbances. However, the IMC strategy showed itself to be a little softer and with no maximum overshoot, which in some cases and some applications is usually a restriction.
A novel direct torque and flux control of permanent magnet synchronous motor with analytically-tuned PI controllers
Authors: Odo Kenneth , Ohanu Chibuike , Chinaeke-Ogbuka Ifeanyi , Ajibo Augustine , Ogbuka Cosmas , Ejiogu Emenike
Published: December 2021

This work presents a novel direct torque and flux control (DTFC) of permanent magnet synchronous motor (PMSM) with analytically-tuned proportional integral (PI) controllers. The proportional (K_p) and integral (K_i) gains of the PI controllers were accurately determined, from first principle, using the model of the control system. The PI flux and torque controllers were then developed in rotor reference frame. The designed PI controllers, together with the torque and flux controllers, were tested on a permanent magnet synchronous motor (PMSM). The results obtained were compared with results from conventional DTFC system using manually-tuned PI controllers. The total harmonic distortion (THD) of motor phase currents is 18.80% and 4.81% for the conventional and proposed models respectively. This confirms a significant reduction in torque ripples. The control system was tested for step torque loading and found to offer excellent performance both during load changes, speed reversal, and constant load conditions.