bluuebunny/crossref_metadata_2025 huggingface dataset:
Data from Bmi1 Functions as an Oncogene Independent of Ink4A/Arf Repression in Hepatic Carcinogenesis
Authors: Xu Chuan-Rui , Lee Susie , Ho Coral , Bommi Prashant , Huang Shi-Ang , Cheung Siu Tim , Dimri Goberdhan P. , Chen Xin
Published: April 2023

Abstract
Bmi1 is a polycomb group proto-oncogene that has been implicated in multiple tumor types. However, its role in hepatocellular carcinoma (HCC) development has not been well studied. In this article, we report that Bmi1 is overexpressed in human HCC samples. When Bmi1 expression is knocked down in human HCC cell lines, it significantly inhibits cell proliferation and perturbs cell cycle regulation. To investigate the role of Bmi1 in promoting liver cancer development in vivo, we stably expressed Bmi1 and/or an activated form of Ras (RasV12) in mouse liver. We found that while Bmi1 or RasV12 alone is not sufficient to promote liver cancer development, coexpression of Bmi1 and RasV12 promotes HCC formation in mice. Tumors induced by Bmi1/RasV12 resemble human HCC by deregulation of genes involved in cell proliferation, apoptosis, and angiogenesis. Intriguingly, we found no evidence that Bmi1 regulates Ink4A/Arf expression in both in vitro and in vivo systems of liver tumor development. In summary, our study shows that Bmi1 can cooperate with other oncogenic signals to promote hepatic carcinogenesis in vivo. Yet Bmi1 functions independent of Ink4A/Arf repression in liver cancer development. (Mol Cancer Res 2009;7(12):1937–45)
Data from Down Syndrome Candidate Region 1 Isoform 1 Mediates Angiogenesis through the Calcineurin-NFAT Pathway
Authors: Qin Liuliang , Zhao Dezheng , Liu Xin , Nagy Janice A. , Hoang Mien Van , Brown Lawrence F. , Dvorak Harold F. , Zeng Huiyan
Published: April 2023

Abstract
Down syndrome candidate region 1 (DSCR1) is one of more than 50 genes located in a region of chromosome 21 that has been implicated in Down syndrome. DSCR1 can be expressed as four isoforms, one of which, isoform 4 (DSCR1-4), has recently been found to be strongly induced by vascular endothelial growth factor A (VEGF-A165) and to provide a negative feedback loop that inhibits VEGF-A165-induced endothelial cell proliferation in vitro and angiogenesis in vivo. We report here that another DSCR1 isoform, DSCR1-1L, is also up-regulated by VEGF-A165 in cultured endothelial cells and is strongly expressed in several types of pathologic angiogenesis in vivo. In contrast to DSCR1-4, the overexpression of DSCR1-1L induced the proliferation and activation of the transcription factor NFAT in cultured endothelial cells and promoted angiogenesis in Matrigel assays in vivo, even in the absence of VEGF-A. Similarly, small interfering RNAs specific for DSCR1-1L and DSCR1-4 had opposing inhibitory and stimulatory effects, respectively, on these same functions. DSCR1-4 is thought to inhibit angiogenesis by inactivating calcineurin, thereby preventing activation and nuclear translocation of NFAT, a key transcription factor. In contrast, DSCR1-1L, regulated by a different promoter than DSCR1-4, activates NFAT and its proangiogenic activity is inhibited by cyclosporin, an inhibitor of calcineurin. In sum, DSCR1-1L, unlike DSCR1-4, potently activates angiogenesis and could be an attractive target for antiangiogenesis therapy. (Mol Cancer Res 2006;4(11):811–20)
Data from Gene Expression Changes in an Animal Melanoma Model Correlate with Aggressiveness of Human Melanoma Metastases
Authors: Xu Lei , Shen Steven S. , Hoshida Yujin , Subramanian Aravind , Ross Ken , Brunet Jean-Philippe , Wagner Stephan N. , Ramaswamy Sridhar , Mesirov Jill P. , Hynes Richard O.
Published: April 2023

Abstract
Metastasis is the deadliest phase of cancer progression. Experimental models using immunodeficient mice have been used to gain insights into the mechanisms of metastasis. We report here the identification of a “metastasis aggressiveness gene expression signature” derived using human melanoma cells selected based on their metastatic potentials in a xenotransplant metastasis model. Comparison with expression data from human melanoma patients shows that this metastasis gene signature correlates with the aggressiveness of melanoma metastases in human patients. Many genes encoding secreted and membrane proteins are included in the signature, suggesting the importance of tumor-microenvironment interactions during metastasis. (Mol Cancer Res 2008;6(5):760–9)
Data from Effect of an Epidermal Growth Factor Receptor Inhibitor in Mouse Models of Lung Cancer
Authors: Yan Ying , Lu Yan , Wang Min , Vikis Haris , Yao Ruisheng , Wang Yian , Lubet Ronald A. , You Ming
Published: April 2023

Abstract
Gefitinib (Iressa, ZD1839) is a potent high-affinity competitive tyrosine kinase inhibitor aimed primarily at epidermal growth factor receptor (EGFR). Inhibitors in this class have recently been approved for clinical use in the treatment of advanced non–small cell lung cancer as monotherapy following failure of chemotherapy. We examined the efficacy of gefitinib on lung tumorigenesis in mouse models using both postinitiation and progression protocols. Gefitinib was given at a dose of 200 mg/kg body weight (i.g.) beginning either 2 or 12 weeks following carcinogen initiation. In the postinitiation protocol, gefitinib significantly inhibited both tumor multiplicity (∼70%) and tumor load (∼90%) in A/J or p53-mutant mice (P < 0.0001). Interestingly, gefitinib was also highly effective against lung carcinogenesis in the progression protocol when individual animals already have multiple preinvasive lesions in the lung. Gefitinib exhibited ∼60% inhibition of tumor multiplicity and ∼80% inhibition of tumor load when compared with control mice (both P < 0.0001). These data show that gefitinib is a potent chemopreventive agent in both wild-type and p53-mutant mice and that a delayed administration was still highly effective. Analyses of mutations in the EGFR and K-ras genes in lung tumors from either control or treatment groups showed no mutations in EGFR and consistent mutation in K-ras. Using an oligonucleotide array on control and gefitinib-treated lesions showed that gefitinib treatment failed to alter the activity or the expression level of EGFR. In contrast, gefitinib treatment significantly altered the expression of a series of genes involved in cell cycle, cell proliferation, cell transformation, angiogenesis, DNA synthesis, cell migration, immune responses, and apoptosis. Thus, gefitinib showed highly promising chemopreventive and chemotherapeutic activity in this mouse model of lung carcinogenesis. (Mol Cancer Res 2006;4(12):971–81)
Data from High-Dose Fenretinide in Oral Leukoplakia
Authors: William William N. , Lee J. Jack , Lippman Scott M. , Martin Jack W. , Chakravarti Nitin , Tran Hai T. , Sabichi Anita L. , Kim Edward S. , Feng Lei , Lotan Reuben , Papadimitrakopoulou Vassiliki A.
Published: April 2023

Abstract
We previously showed that low-dose fenretinide (200 mg/d) had limited activity in retinoid-resistant oral leukoplakia (34% response rate) possibly because serum drug levels were insufficient to induce retinoid receptor–independent apoptosis. Therefore, we designed the single-arm phase II trial reported here to investigate whether higher-dose fenretinide would improve leukoplakia response over that of our previous study. Leukoplakia patients received fenretinide (900 mg/m2 twice daily) in four 3-week cycles (1 week on drug followed by 2 weeks off). At week 12, clinical responses were determined and blood samples were collected for serum drug level assessments. A planned interim futility analysis led to early trial closure after the initial 15 (of 25 planned) patients because only 3 (20%) had a partial response (stopping rule: ≤4 responses in first 16 patients). Fenretinide was well tolerated—only one grade 3 adverse event (diarrhea) occurred. Serum fenretinide levels changed from 0 (baseline) to 0.122 ± 0.093 μmol/L (week 12). In correlative in vitro studies, high-dose fenretinide inhibited the growth of head and neck cancer cells more and oral leukoplakia cells less than did lower doses of fenretinide. This result is consistent with our clinical finding that high-dose fenretinide did not improve on the historical response rate of lower-dose fenretinide in our previous oral leukoplakia trial.
Data from Prevention of Tumorigenesis in p53-Null Mammary Epithelium by Rexinoid Bexarotene, Tyrosine Kinase Inhibitor Gefitinib, and Celecoxib
Authors: Medina Daniel , Kittrell Frances , Hill Jamal , Zhang Yun , Hilsenbeck Susan G. , Bissonette Reid , Brown Powel H.
Published: April 2023

Abstract
The chemopreventive effects of three agents, rexinoid bexarotene, tyrosine kinase inhibitor gefitinib, and celecoxib, were tested on mammary tumor development arising in p53-null mammary epithelium. The rexinoid bexarotene was the most efficacious inhibitor as it reduced mammary tumor development by 75% in virgin mice and significantly delayed mean tumor development by 98 days in hormone-stimulated mice. The tyrosine kinase inhibitor gefitinib reduced mammary tumor incidence by 50% in virgin mice but did not significantly delay mean tumor latency in hormone-stimulated mice. Celecoxib did not reduce tumor incidence or mean tumor latency in either of the two models. The high doses of the rexinoid and the tyrosine kinase inhibitor did not affect the progression of tumors arising from the premalignant mammary outgrowth line, PN8a. A comparison of these agents with tamoxifen shows the superiority of tamoxifen in preventing tumor development in p53-null mammary cells. Similarly, a comparison of the results of the p53 model with other transgenic models in their response to the chemopreventive agents showed that mammary tumors arising from different oncogenic events will respond differently to the different agents.
Data from Increased Susceptibility of Nrf2 Knockout Mice to Colitis-Associated Colorectal Cancer
Authors: Khor Tin Oo , Huang Mou-Tuan , Prawan Auemduan , Liu Yue , Hao Xingpei , Yu Siwang , Cheung William Ka Lung , Chan Jefferson Y. , Reddy Bandaru S. , Yang Chung S. , Kong Ah-Ng
Published: April 2023

Abstract
The nuclear factor-erythroid 2-related factor 2 (Nrf2) plays a critical role in protecting various tissues against inflammation, which is a potential risk factor for colorectal and other cancers. Our previously published mouse model work showed that Nrf2 helps protect against dextran sulfate sodium (DSS)–induced colitis/inflammation, and others have shown that Nrf2 helps protect against inflammation-associated colorectal carcinogenesis (aberrant crypt foci). The present study extended these important earlier findings by exploring the role of Nrf2 in colitis-associated colorectal cancer in a mouse model involving azoxymethane/DSS–induced colorectal carcinogenesis in Nrf2 knockout mice. Azoxymethane/DSS–treated Nrf2 knockout mice had increased incidence, multiplicity, and size of all colorectal tumors, including adenomas, versus treated wild-type (WT) mice, and the proportion of tumors that were adenocarcinoma was much higher in knockout (80%) versus WT (29%) mice. Compared with WT mice, knockout mice also had increased markers of inflammation in tumor tissue (cyclooxygenase-2 and 5-lipoxygenase expressions and prostaglandin E2 and leukotriene B4 levels) and in inflamed colonic mucosa (nitrotyrosine expression), supporting the association of knockout mouse tumor formation with inflammation. The phase II detoxifying/antioxidant enzymes NAD(P)H-quinone reductase 1 and UDP-glucurosyltransferase 1A1 were elevated in the normal mucosa of WT, but not Nrf 2 knockout, mice treated with azoxymethane/DSS. Our findings show that Nrf2 plays a critical role in protecting against inflammation-associated colorectal cancer.
Data from Early Changes in Gene Expression Induced by Tobacco Smoke: Evidence for the Importance of Estrogen within Lung Tissue
Authors: Meireles Sibele I. , Esteves Gustavo H. , Hirata Roberto , Peri Suraj , Devarajan Karthik , Slifker Michael , Mosier Stacy L. , Peng Jing , Vadhanam Manicka V. , Hurst Harrell E. , Neves E. Jordao , Reis Luiz F. , Gairola C. Gary , Gupta Ramesh C. , Clapper Margie L.
Published: April 2023

Abstract
Lung cancer is the leading cause of cancer deaths in the United States, surpassing breast cancer as the primary cause of cancer-related mortality in women. The goal of the present study was to identify early molecular changes in the lung induced by exposure to tobacco smoke and thus identify potential targets for chemoprevention. Female A/J mice were exposed to either tobacco smoke or HEPA-filtered air via a whole-body exposure chamber (6 h/d, 5 d/wk for 3, 8, and 20 weeks). Gene expression profiles of lung tissue from control and smoke-exposed animals were established using a 15K cDNA microarray. Cytochrome P450 1b1, a phase I enzyme involved in both the metabolism of xenobiotics and the 4-hydroxylation of 17β-estradiol (E2), was modulated to the greatest extent following smoke exposure. A panel of 10 genes were found to be differentially expressed in control and smoke-exposed lung tissues at 3, 8, and 20 weeks (P < 0.001). The interaction network of these differentially expressed genes revealed new pathways modulated by short-term smoke exposure, including estrogen metabolism. In addition, E2 was detected within murine lung tissue by gas chromatography-coupled mass spectrometry and immunohistochemistry. Identification of the early molecular events that contribute to lung tumor formation is anticipated to lead to the development of promising targeted chemopreventive therapies. In conclusion, the presence of E2 within lung tissue when combined with the modulation of cytochrome P450 1b1 and other estrogen metabolism genes by tobacco smoke provides novel insight into a possible role for estrogens in lung cancer. Cancer Prev Res; 3(6); 707–17. ©2010 AACR.
The Role of Statins in the Prevention of Ovarian and Endometrial Cancers
Authors: Zeleznik Oana A. , Irvin Sarah R. , Samimi Goli , Trabert Britton
Published: April 2023

Ovarian and endometrial cancers are the most common gynecologic malignancies and emerging evidence suggests that lipid metabolism and subsequent inflammation are important etiologic factors for both tumors. Statins (HMG-CoA reductase inhibitors) are the most widely prescribed lipid-lowering drugs in the United States and are used by 25% of adults aged 40+ years. In addition to their cardio-protective actions, statins have anti-inflammatory effects and have demonstrated antiproliferative and apoptotic properties in cancer cell lines, supporting a potential role in cancer prevention. To appropriately quantify potential public health impact of statin use for cancer prevention, there is a great need to understand the potential risk reduction among individuals at a higher risk of gynecologic cancers, the group that will likely need to be targeted to effectively balance risk/benefit of medications repurposed for cancer prevention. In this commentary, we focus on summarizing emerging evidence suggesting that the anti-inflammatory and lipid-lowering mechanisms of statins may provide important cancer-preventive benefits for gynecologic cancers as well as outline important unanswered questions and future research directions.
Avocados: A Recipe for Good Guacamole or Lower Cancer Risk?
Authors: Galván Gloria Cecilia , Freedland Stephen J.
Published: April 2023

Diet plays a role in modifying cancer risk. This study from Ericsson and colleagues provides new evidence suggesting that avocado intake could aid in cancer prevention. However, these effects were observed only in men, pointing to intriguing key differences by sex. Also, associations were only seen for some (colorectal, lung, and bladder cancers), but not all cancer types. Still, the number of avocado servings and ways to eat avocado to obtain these benefits remain to be determined. This brief commentary discusses the study and provides an opinion on the proposed role of avocados in reducing cancer risk.

See related article by Ericsson et al., p. 211
ADCs or: How I Learned to Stop Worrying and Love Chemotherapy
Authors: Gupta Avantika , Drago Joshua Z. , Chandarlapaty Sarat
Published: April 2023

Antibody–drug conjugates are transforming cancer treatment, and payload characteristics are emerging as crucial determinants of clinical activity. As exemplified by Weng and colleagues, advancements in the linker and payload chemistry may provide the next evolutionary step in enabling this class of drugs to overcome chemoresistance and deliver even more profound responses.

See related article by Weng et al., p. 950 (2).
HPV Integration Can Drive the Formation of Virus–Host Extrachromosomal DNA in Tumors
Authors: McBride Alison A. , White Elizabeth A.
Published: April 2023

Human papillomavirus (HPV)–positive cancer cells contain virus and host DNA and exhibit marked genome instability. In this issue of Cancer Discovery, Akagi and colleagues characterize the remarkably complex landscape of virus–host DNA molecules in HPV-positive cells, providing evidence for diverse integrated and extrachromosomal virus–host hybrid DNAs with the potential to drive clonal evolution.

See related article by Akagi et al., p. 910 (4).
Comparison of Prasugrel and Clopidogrel in Thrombotic Stroke Patients with Risk Factors for Ischemic Stroke Recurrence: An Integrated Analysis of PRASTRO-I, PRASTRO-II, and PRASTRO-III
Authors: Kitazono Takanari , Kamouchi Masahiro , Matsumaru Yuji , Shirai Toshiaki , Takita Atsushi , Kuroda Takeshi , Kimura Kazumi
Published: April 2023

Introduction: Patients with stroke are at a high risk of recurrence, and although they receive antiplatelet therapies such as clopidogrel for secondary prevention of non-cardioembolic stroke, the recurrence rate remains high. Three phase 3 trials (PRASTRO-I/II/III) were conducted to determine the efficacy of prasugrel in preventing recurrent stroke. Here, we performed an integrated analysis of these studies to confirm the generalizability of the PRASTRO-III findings and to supplement the small sample size of the study. Methods: Patients from PRASTRO-I, PRASTRO-II, and PRASTRO-III with ischemic stroke (large-artery atherosclerosis or small-artery occlusion) and at least one of the following were included: hypertension, dyslipidemia, diabetes mellitus, chronic kidney disease, or ischemic stroke history. The primary efficacy endpoint was the composite incidence of ischemic stroke, myocardial infarction (MI), and death from other vascular causes in the intention-to-treat population. Bleeding events (life-threatening bleeding, major bleeding, and clinically relevant bleeding) were evaluated as the primary safety endpoint. Cumulative incidences and 95% confidence intervals (CIs) were calculated for the study outcomes using the Kaplan-Meier method. Hazard ratios (HRs) and 95% CIs were calculated using the Cox regression model. Results: The data of 2,184, 274, and 230 patients from PRASTRO-I, PRASTRO-II, and PRASTRO-III, respectively, were analyzed (N = 2,688; prasugrel, N = 1,337; clopidogrel, N = 1,351). Stroke at enrollment was classified as large-artery atherosclerosis in 49.3% of patients and small-artery occlusion in 50.7% of patients. The primary efficacy endpoint composite incidence (prasugrel vs. clopidogrel) was 3.4% versus 4.3% (HR: 0.771, 95% CI: 0.522–1.138). The incidence of each component of the primary efficacy endpoint for prasugrel versus clopidogrel was 3.1% (n = 41) versus 4.1% (n = 55) for ischemic stroke, 0.3% (n = 4) versus 0.2% (n = 3) for MI, and no events of death from other vascular causes. For the primary safety endpoint, bleeding events were reported in 6.0% of patients in the prasugrel group versus 5.5% of patients in the clopidogrel group (HR: 1.074, 95% CI: 0.783–1.473). Conclusions: This integrated analysis supports the findings of PRASTRO-III. Prasugrel is a promising treatment that results in a numerical reduction in the composite incidence of ischemic stroke, MI, and death from other vascular causes in patients with ischemic stroke who are at a high risk of stroke recurrence. No major safety issues were observed for prasugrel.
Too Early to Abandon Convalescent Plasma for Supportive Treatment of COVID-19
Authors: Seitz Rainer , Gürtler Lutz , Vahlensieck Ute , Hilger Anneliese , Schramm Wolfgang
Published: April 2023

The authors of a systematic review and meta-analysis conclude that the benefit of convalescent plasma (CP) in the treatment of COVID-19 is limited. Among other systematic reviews, only one found an indication of benefit of CP. However, a meta-analysis needs a focused and meaningful clinical question and should include studies which are designed to test a reasonable hypothesis. Clinical trials to support the licensing of medicines should aim to define as exactly as possible the investigational drug and target disease. In the case of COVID-19, trial details (e.g., duration, stage and severity of disease, and antibody content and dose of CP) are quite heterogeneous. The so far available evidence suggests that the hypothesis should be sharpened as to treat COVID -19 patients at risk for developing severe disease as early enough with a sufficiently high dose of specific antibodies. It has been demonstrated that such an approach is feasible, and the lack of an independent reproduction by further trials with a really comparable design can probably not be compensated by compiling all available, heterogenous trials, even with the best methodology of a systematic review and meta-analysis. Though the COVID-19 pandemic appears to be fading, we should not neglect the search for effective prevention and treatments, given the still high death toll of COVID-19. Monoclonal antibodies were found effective in the early phase of the pandemic; however, due to new variants of SARS-COV2 undermining their efficacy they are no longer recommended by the current NIH guidelines. CP can provide a spectrum of polyclonal antibodies in close timely and regional connection to the particular prevalent virus variant. It would be extremely valuable to obtain a solid scientific foundation for the principle of target specific and temporarily adapted passive immunization, which could be a fast and flexible instrument also in future outbreaks of novel pathogens.
Higher Risk of Sarcopenia in Older Adults with Type 2 Diabetes: NHANES 1999–2018
Authors: Dai Siyu , Shu Dingbo , Meng Fanjing , Chen Yajiao , Wang Jianping , Liu Xiaochen , Xiao Xiangyue , Guo Wentong , Chen Feng
Published: April 2023

Introduction: Recent studies suggested that sarcopenia may be a significant comorbidity of diabetes mellitus (DM). Nonetheless, studies with nationally representative data are scarce, and the changing trend of sarcopenia prevalence over time is largely unknown. Therefore, we aimed to estimate and compare the prevalence of sarcopenia in diabetic and nondiabetic US older population, and to explore the potential predictors of sarcopenia as well as the trend of sarcopenia prevalent in the past decades. Methods: Data were retrieved from the National Health and Nutrition Examination Survey (NHANES). Sarcopenia and DM were defined according to corresponding diagnosis criteria. Weighted prevalence was calculated and compared between diabetic and nondiabetic participants. The differences among age and ethnicity groups were explored. Results: A total of 6,381 US adults (>50 years) were involved. The overall prevalence of sarcopenia was 17.8% for US elders, and the prevalence was higher (27.9% vs. 15.7%) in those with diabetes ones than those without. Stepwise regression revealed that sarcopenia was significantly associated with DM (adjusted odds ratio = 1.37, 95% CI: 1.08–1.22; p < 0.05) after controlling for potential confounders including gender, age, ethnicity, educational level, BMI, and muscle strengthening activity. A slight fluctuation but overall increasing trend of sarcopenia prevalence was observed among diabetic elders, while no obvious changing trend was observed in their counterparts in recent decades. Conclusion: Diabetic US older adults face significantly higher risk of sarcopenia when compared with their nondiabetic counterparts. Gender, age, ethnicity, educational level, and obesity were important influencing factors of sarcopenia development.
Prevalence and Risk Score for Hypertonic Dehydration among Community-Dwelling Older Adults: An Analysis of the Bangkok Falls Study
Authors: Sri-on Jiraporn , Thong-on Kwannapa , Kredarunsooksree Thiti , Paksopis Thitiwan , Ruangsiri Rasida
Published: April 2023

Introduction: Dehydration is associated with morbidity, and many factors affect dehydration in older adults including age and medication use. This study determined the prevalence of hypertonic dehydration (HD) and factors affecting HD in older adults and developed a risk score (a set of consistent weights that assign a numerical value to each risk factor) which is potentially useful in predicting HD among community-dwelling Thai older adults. Methods: Data were obtained from a cohort study of community-dwelling older adults aged ≥60 years in Bangkok, Thailand, between October 1, 2019, and September 30, 2021. Current HD was defined as a serum osmolality >300 mOsm/kg. Univariate and multivariate logistic regression analyses were used to identify factors associated with current and impending HD. The risk score for current HD was developed based on the final multiple logistic regression model. Results: A total of 704 participants were included in the final analysis. In this study, 59 (8.4%) participants had current HD and 152 (21.6%) had impending HD. We identified three risk factors for HD in older adults: age ≥75 years (adjusted odds ratio [aORs] 2.0, 95% confidence interval [CI]: 1.16–3.46), underlying diabetes mellitus (aORs 3.07, 95% CI: 1.77–5.31), and use of β-blocker medication (aORs 1.98, 95% CI: 1.04–3.78). The increasing risks of current HD with increasing risk scores were 7.4% for a score of 1, 13.8% for a score of 2, 19.8% for a score of 3, and 32.8% for a score of 4. Conclusion: One-third of the older adults in this study had current or impending HD. We identified risk factors for HD and created a risk score for HD in one group of community-dwelling older adults. Older adults with risk scores of 1–4 were at 7.4%–32.8% risk for current HD. The clinical utility of this risk score requires further study and external validation.
Stability model integration for large scale solar photovoltaic system using Western electricity coordinating council model
Authors: Mohd Tajudin Mohammad Nayeim Fazumy , Mohd Hussain Mohd Najib , Hussain Mashitah Mohd , Ibrahim Intan Rahayu
Published: April 2023

Due to the increased demand for renewable energy, the interest in the large-scale solar photovoltaic (LSSPV) power plant has recently grown dramatically. However, when a large amount of electricity is produced from the LSSPV power plant to the grid interconnection, the system commonly experiences instability and thus disrupt the grid system in disturbance issues such as bus fault, line-to-line fault, three-phase fault, and tripping. This sudden disturbance occurrence is tended to interrupt the stability of the system from providing balanced electrical production within the electrical grid. A dynamics response from the simulation is used to study the stability and the behavior of the photovoltaic (PV) plant into the grid interconnection by developing 118 bus system. The observation of critical clearing time (CCT) duration shows that the result from the simulation where the duration takes less than t=15 s for the system to get back to its pre-fault condition in three-phase fault and tripping in a dynamic simulation to shows that the system reaches its stability been observed through the simulation result by using from user-specific models to generic models like those advocated by the Western electricity coordinating council (WECC) in power system simulator for engineering (PSSE) software.
Adaptive virtual inertia controller based on machine learning for superconducting magnetic energy storage for dynamic response enhanced
Authors: Setiadi Herlambang , Abdillah Muhammad , Afif Yusrizal , Delfianti Rezi
Published: April 2023

The goal of this paper was to create an adaptive virtual inertia controller (VIC) for superconducting magnetic energy storage (SMES). An adaptive virtual inertia controller is designed using an extreme learning machine (ELM). The test system is a 25-bus interconnected Java Indonesian power grid. Time domain simulation is used to evaluate the effectiveness of the proposed controller method. To simulate the case study, the MATLAB/Simulink environment is used. According to the simulation results, an extreme learning machine can be used to make the virtual inertia controller adaptable to system variation. It has also been discovered that designing virtual inertia based on an extreme learning machine not only makes the VIC adaptive to any change in the system but also provides better dynamics performance when compared to other scenarios (the overshoot value of adaptive VIC is less than -5×10-5).
Uncertainty model for rate of change of frequency analysis with high renewable energy participation
Authors: Rubiano Tomas , Rios Mario A.
Published: April 2023

Large-scale integration of inverter-based renewables is displacing synchronous machine generation, causing a reduction in the inertia of electrical power systems. This reduction is reflected in an increase in the rate of change of frequency (RoCoF). Additionally, the variation of the RoCoF will depend on the uncertainty associated with the generation of non-conventional renewable energy sources. For the planning of the operation of the system, it is essential to know the range of variation of the RoCoF when there are disturbances in the system and uncertainties in the generation of non-conventional sources of renewable energy. This paper proposes to establish the calculation of a confidence interval of the RoCoF variation that considers these uncertainties. So, this paper proposes a method to consider these uncertainties based on the probabilistic point estimate method (PEM); considering multiple renewable non-conventional sources with correlated or uncorrelated behavior in their powers injected into the system. On the other hand, as there are different proposals to calculate the RoCoF, this paper presents the application of the uncertainty model with three different RoCoF proposed calculation methods.
Analysis of interference methods on transformers based on the results of dissolved gas analysis tests
Authors: Siregar Yulianta , Hartanto Lumbanraja Timothy Juan
Published: April 2023

In the operation of the power transformer, several maintenance efforts must be made to ensure the condition of the transformer is in good condition. The problems that usually arise are a thermal failure and electrical failure. The use of insulating media such as transformer oil and transformer insulation paper can be disrupted by this failure. Dissolved gas analysis, which identifies the types and concentrations of dissolved gas in transformer oil, can reveal details on fault indicators in power transformers (DGA). In this study, we used the interpretation of the IEEE std 2008-C57.104 (total dissolved combustible gas (TDCG), key gas, Rogers ratio method), the interpretation of IEC 2015-60599 (Duval triangle and basic gas ratio method), and the IEEE Std 2019-C57.104 interpretation (Duval pentagon method). The outcome of the DGA test is used to determine the conditions and indications of disturbances in the transformer for power. Using various gas analysis techniques also impacts the outcome of the fault indication. This variation has affected the types of gas used in the computation and the gas concentration limit value estimation. After the gas analysis, it was found that the oil purification process was also proven to reduce the concentration of combustible gases.
Potential of using photovoltaic systems to power underwater fishing lights in small-scale fishing vessel in Indonesia
Authors: Nugraha I Made Aditya , Luthfiani Febi , Desnanjaya I Gusti Made Ngurah , Siregar Jhon Septin Mourisdo , Boikh Lebrina Ivantry
Published: April 2023

The limited stock and uncertainty of fuel prices as a source of driving the main engine and generator on ships greatly affect the lives of fishermen in Indonesia. Even though there is a policy in the form of assistance from the government in the form of subsidies, fishermen still feel doubtful about being able to get such assistance. To overcome this and with the potential of solar energy in Indonesia, as well as a manifestation of appropriate technology and blue economy policies, a photovoltaic system is made that is combined with underwater lights as a fishing tool. Activities are carried out by measuring environmental conditions and the energy that comes out of the PV system and giving questionnaires to the fishermen. The results showed that the use of PV systems combined with underwater lights in fishing activities gave good results. The result of electrical energy that can be generated is 393.24 Wh/day and can meet the ship’s electricity needs for 4 days. This result is also supported by the Wilcoxon test results for technical, economic, environmental, health, and safety aspects with a significance value of 0.001 (p<0.05).
Numerical analysis in Ar-H2 coupled-coil inductively coupled thermal plasma with Si feedstock for stable operation
Authors: Siregar Yulianta , Tanaka Yasunori
Published: April 2023

In nanopowder synthesis, the starting powder to be evaporated is infused in a plasma torch through the upper coil and the lower coil in the coupled model of inductively coupled thermal plasma (coupled-coil inductively coupled thermal plasma (ICTP)). Mixing these evaporated materials to form the coupled ICTP significantly influences the thermodynamic and transport properties. It is essential to understand these complex interactions between coupled ICTP and feedstock evaporation. This research investigated the thermal interactions between silicon raw material powder (Si) with ICTP in coupled 99%Ar/1%H2 through the numerical model developed for the synthesis of Si nanopowder. The feed rate of the Si raw material was set at 0.05, 0.1, and 0.5 g/min. This implies that the increased Si feed is too heavy to vaporize all the injected feed.
Ecological impact due to the implementation of a modeled and optimized hybrid system
Authors: Echarradi Othmane , Benlafkih Abdessamad , Hadjoudja Abdelkader , Fahoume Mounir
Published: April 2023

This paper presents a very alarming forecasts about our future and particularly for a medium and long-term future. That is to say, several actions are being carried out by different civil and state parties to deal with these very concrete threats. And it is within this framework that this paper fits, and its objective is to highlight the hybrid systems and more precisely the photovoltaic-wind hybrid systems coupled with storage batteries, as an efficient alternative to the classical means of electricity production. This work will adopt a method of obtaining results called performance evaluation, so this manuscript will present firstly the mathematical model of this hybrid system to best conceive what it is about, then as second part will determine the exact figures of the largest amount of carbon dioxide (CO2) that can be avoided using this technology and following a precise methodology, this can be applied to our situation, i.e., a simple house or to any other type of installation.
Development of deep reinforcement learning for inverted pendulum
Authors: Nguyen Dang Khoa , Thi Van Tran , Van Long Vu
Published: April 2023

This paper presents a modification of the deep Q-network (DQN) in deep reinforcement learning to control the angle of the inverted pendulum (IP). The original DQN method often uses two actions related to two force states like constant negative and positive force values which apply to the cart of IP to maintain the angle between the pendulum and the Y-axis. Due to the changing of too much value of force, the IP may make some oscillation which makes the performance system could be declined. Thus, a modified DQN algorithm is developed based on neural network structure to make a range of force selections for IP to improve the performance of IP. To prove our algorithm, the OpenAI/Gym and Keras libraries are used to develop DQN. All results showed that our proposed controller has higher performance than the original DQN and could be applied to a nonlinear system.
Adaptive sliding mode control for uncertain wheel mobile robot
Authors: Doan Hoa Van , Vu Nga Thi-Thuy
Published: April 2023

In this paper a simple adaptive sliding mode controller is proposed for tracking control of the wheel mobile robot (WMR) systems. The WMR are complicated systems with kinematic and dynamic model so the error dynamic model is built to simplify the mathematical model. The sliding mode control then is designed for this error model with the adaptive law to compensate for the mismatched. The proposed control scheme in this work contains only one control loop so it is simple in both implementation and mathematical calculation. Moreover, the requirement of upper bounds of disturbance that is popular in the sliding mode control is cancelled, so it is convenient for real world applications. Finally, the effectiveness of the presented algorithm is verified through mathematical proof and simulations. The comparison with the existing work is also executed to evaluate the correction of the introduced adaptive sliding mode controller. Thoroughly, the settling time, the peak value, the integral square error of the proposed control scheme reduced about 50% in comparison with the compared disturbance observer based sliding mode control.
Application of fuzzy controllers in automatic ship motion control systems
Authors: Melnyk Oleksiy , Onishchenko Oleg , Onyshchenko Svitlana , Shumylo Oleksandr , Volyanskyy Sergiy , Bondar Alla , Cheredarchuk Nataliia
Published: April 2023

Automatic ship heading control is a part of the automatic navigation system. It is charged with the task of maintaining the actual ship’s course angle or actual ship’s course without human intervention in accordance with the set course or setting parameter and maintaining this condition under the effect of disturbing influences. Thus, the corrective influence on deviations from a course can be rendered by the position of a rudder or controlling influence that leads to the rotary movement of a vessel around a vertical axis that represents a problem, which can be solved with the use of fuzzy logic. In this paper, we propose to consider the estimation of the efficiency of fuzzy controllers in systems of automatic control of ship movement, obtained by analysis of a method of the formalized record of a logic conclusion and structure of the fuzzy controller. The realization of this allows to carry out effective stabilization of a course angle of a vessel taking into account existing restrictions.
Design and implementation of a control system for a steel plate cutting production line using programmable logic controller
Authors: Al shamarti‬‏ ‪Basheer NajemAldeen , Selman Nasir Hussein
Published: April 2023

Most of the old machines installed in different industries are managed manually by system operators. This action makes their productivity low and not suitable to cover the needs in other sectors. In addition, these machines are not without risks due to the proximity of the operators to them. The installing a new full system instead of the old one on the same site requires very high costs. So, modernizing the same old system by making its operation automatic has become necessary to reduce the economic cost significantly. In this paper, an automatic control system based on programmable logic controller (PLC) for the cutting steel plate machine that had been managed manually in a factory is designed. The system includes an Encoder that is used to specify the length of the steel plate to be cut by sending a signal to the PLC. The system operation is completed by using human machine interface (HMI) unit to monitor and control the system performance by the system operator. A practical test for the developed system offered more productivity (more than 30%), more safety, reduces human efforts and the total daily production cost (less than one third).
Portable spirometer using pressure-volume method with Bluetooth integration to Android smartphone
Authors: Widianto Eko Didik , Huda Gayuh Nurul , Nurhayati Oky Dwi
Published: April 2023

This paper presents a study on an embedded spirometer using the low-cost MPX5100DP pressure sensor and an Arduino Uno board to measure the air exhaled flow rate and calculate force vital capacity (FVC), forced expiratory volume in 1 s (FEV1), and the FEV1/FVC ratio of human lungs volume. The exhaled air flow rate was measured from differential pressure in the sections of a mouthpiece tube using the venturi effect equation. This constructed mouthpiece and the embedded spirometer resulted in a 96.27% FVC reading accuracy with a deviation of 0.09 L and 98.05% FEV1 accuracy with a deviation of 0.05 L compared to spirometry. This spirometer integrates an HC-05 Bluetooth module for spirometry data transceiving to a smartphone for display and recording in an Android application for further chronic obstructive pulmonary disease (COPD) diagnosis.
Linear regression and R-squared correlation analysis on major nuclear online plant cooling system
Authors: Mohamad Nor Ahmad Azhari , Minhat Mohd Sabri , Ya’acob Norsuzila , Kassim Murizah
Published: April 2023

The primary cooling system is an integral part of a nuclear reactor that maintains reactor operational safety. It is essential to investigate the effects of the cooling system parameter before implementing predictive maintenance techniques in the reactor monitoring system. This paper presents a linear regression and R-squared correlation analysis of the nuclear plant cooling system parameter in the TRIGA PUSPATI Reactor in Malaysia. This research examines the primary cooling system's temperature, conductivity, and flow rate in maintaining the nuclear reactor. Data collection on the primary coolant system has been analyzed, and correlation analysis has been derived using linear regression and R-squared analysis. The result displays the correlation matrix for all sensors in the primary cooling system. The R-squared value for TT5 versus TT2 is 89%, TT5 versus TT3 is 94%, and TT5 against TT4 is 66% which shows an excellent correlation to the linear regression. However, the conductivity sensor CT1 does not correlate with other sensors in the system. The flow rate sensor FT1 positively correlates with the temperature sensor but does not correlate with the conductivity sensor. This finding can help to better develop the predictive maintenance strategy for the reactor monitoring program.
Three-dimensional shape generation via variational autoencoder generative adversarial network with signed distance function
Authors: Ajayi Ebenezer Akinyemi , Lim Kian Ming , Chong Siew-Chin , Lee Chin Poo
Published: April 2023

Mesh-based 3-dimensional (3D) shape generation from a 2-dimensional (2D) image using a convolution neural network (CNN) framework is an open problem in the computer graphics and vision domains. Most existing CNN-based frameworks lack robust algorithms that can scale well without combining different shape parts. Also, most CNN-based algorithms lack suitable 3D data representations that can fit into CNN without modification(s) to produce high-quality 3D shapes. This paper presents an approach that integrates a variational autoencoder (VAE) and a generative adversarial network (GAN) called 3 dimensional variational autoencoder signed distance function generative adversarial network (3D-VAE-SDFGAN) to create a 3D shape from a 2D image that considerably improves scalability and visual quality. The proposed method only feeds a single 2D image into the network to produce a mesh-based 3D shape. The network encodes a 2D image of the 3D object into the latent representations, and implicit surface representations of 3D objects corresponding to those 2D images are subsequently generated. Hence, a signed distance function (SDF) is proposed to maintain object inside-outside information in the implicit surface representation. Polygon mesh surfaces are then produced using the marching cubes algorithm. The ShapeNet dataset was used in the experiments to evaluate the proposed 3D-VAE-SDFGAN. The experimental results show that 3D-VAE-SDFGAN outperforms other state-of-the-art models.
Speech emotion recognition with light gradient boosting decision trees machine
Authors: Ong Kah Liang , Lee Chin Poo , Lim Heng Siong , Lim Kian Ming
Published: April 2023

Speech emotion recognition aims to identify the emotion expressed in the speech by analyzing the audio signals. In this work, data augmentation is first performed on the audio samples to increase the number of samples for better model learning. The audio samples are comprehensively encoded as the frequency and temporal domain features. In the classification, a light gradient boosting machine is leveraged. The hyperparameter tuning of the light gradient boosting machine is performed to determine the optimal hyperparameter settings. As the speech emotion recognition datasets are imbalanced, the class weights are regulated to be inversely proportional to the sample distribution where minority classes are assigned higher class weights. The experimental results demonstrate that the proposed method outshines the state-of-the-art methods with 84.91% accuracy on the emo-DB dataset, 67.72% on the Ryerson audio-visual database of emotional speech and song (RAVDESS) dataset, and 62.94% on the interactive emotional dyadic motion capture (IEMOCAP) dataset.
Improving the intelligibility of dysarthric speech using a time domain pitch synchronous-based approach
Authors: Giri Mahesh , Rayavarapu Neela
Published: April 2023

Dysarthria is a motor speech impairment that reduces the intelligibility of speech. Observations indicate that for different types of dysarthria, the fundamental frequency, intensity, and speech rate of speech are distinct from those of unimpaired speakers. Therefore, the proposed enhancement technique modifies these parameters so that they fall in the range for unimpaired speakers. The fundamental frequency and speech rate of dysarthric speech are modified using the time domain pitch synchronous overlap and add (TD-PSOLA) algorithm. Then its intensity is modified using the fast Fourier transform (FFT) and inverse fast Fourier transform (IFFT)-based approach. This technique is applied to impaired speech samples of ten dysarthric speakers. After enhancement, the intelligibility of impaired and enhanced dysarthric speech is evaluated. The change in the intelligibility of impaired and enhanced dysarthric speech is evaluated using the rating scale and word count methods. The improvement in intelligibility is significant for speakers whose original intelligibility was poor. In contrast, the improvement in intelligibility was minimal for speakers whose intelligibility was already high. According to the rating scale method, for diverse speakers, the change in intelligibility ranges from 9% to 53%. Whereas, according to the word count method, this change in intelligibility ranges from 0% to 53%.
Estimation of satellite link’s fade margin using non-meteorological technique and worst month analysis
Authors: Suhaimi Nur Hanis Sabrina , Ismail Ahmad Fadzil , Badron Khairayu , Ahmad Yasser Asrul
Published: April 2023

Satellite technology is shifting to higher frequencies such as Q or V-band to cater to greater bandwidth and higher data rates applications such as videoconferencing, internet of things (IoT) and telemedicine. The main challenge in deploying high-frequency bands in heavy precipitation areas is severe rain attenuation. In this paper, a frequency scaling technique was developed to estimate the fade margin at a higher frequency. The worst month analysis was also conducted since the analysis is also important in determining dependable fade margin. The result was evaluated and analyzed using root mean square error (RMSE) and percentage error. The proposed model offers the smallest RMSE and lowest percentage error when compared to all existing prediction models. A dependable fade margin acquired from high-accuracy rain attenuation estimation is very important. This is to apply the best mitigation technique in overcoming rain attenuation in the satellite-Earth link so that, the best system performance can be delivered.