bluuebunny/crossref_metadata_2025 huggingface dataset:
Integrated Soil Fertility and Water Management Practices for Enhanced Agricultural Productivity
Authors: Ndegwa Jackline K. , Gichimu Bernard M. , Mugwe Jayne N. , Mucheru-Muna Monicah , Njiru Daniel M.
Published: June 2023

Declining agricultural productivity has been a challenge worldwide and especially in Sub-Saharan Africa (SSA). Low agricultural productivity has been attributed to factors such as poor farm management practices, soil moisture stress, soil infertility, and soil degradation, among others. The nations in the SSA are prone to insufficient crop yields due to their inadequate capacity to adapt to good agricultural practices that support crop productivity such as integrated soil fertility and water management (ISFWM) practices. This lowers the farmers’ capacity to improve crop productivity, thus contributing in jeopardizing the food and nutritional security in SSA. Past research has shown that ISFWM strategies have not been properly adopted probably due to the lack of adequate awareness among the farmers about them. In addition, there is limited documentation on the importance of ISFWM in enhancement of soil fertility, water use efficiency, and sustainable crop production in SSA. This paper discusses some of the key ISFWM options that have the potential to enhance soil fertility, improve water use efficiency, and consequently increase agricultural productivity. The practices include intercropping, use of tied ridges, minimum tillage, mulching, and combined use of organic and inorganic fertilizers.
Travel Time Probability Prediction Based on Constrained LSTM Quantile Regression
Authors: Li Hao , Wang Zijian , Li Xiantong , Wang Hua , Man Yongxing , Shi Jinyu
Published: June 2023

Travel time reliability assessment has been widely used in recent years to evaluate the performance of transportation networks and measure the operation level of transportation systems. Weather, as one of the important factors influencing travel time reliability, affects the relationship between the supply and requirement of urban road networks. Considering the traffic characteristics under different traffic conditions, a study on the influence of weather on travel time reliability under different conditions is proposed to predict the probability of travelers completing their trips within the expected time under different weather conditions. Based on the urban road network data and cab trajectory data of Harbin city, this paper correlates the floating vehicle location with the road network information through a hidden Markov model to reduce the influence of vehicle trajectory errors on the calculation results of path travel time. To analyze the entire distribution of extreme travel time and its impact on the reliability of travel time under various traffic situations, it captures the tail features of the travel time distribution based on extreme value theory. Then, to increase the predictability of each quantile, it combines a deep-learning LSTM model and a quantile regression model to create a probabilistic travel time prediction model utilizing combined layers. The proposed model is compared with the linear quantile regression and neural network quantile regression models, and the model is evaluated in terms of point prediction results and probabilistic prediction results, respectively, to ensure the accuracy of predictions from the model. As a result, the prediction accuracy of the model in this paper is greatly improved, and the degree of violating quantile constraints is greatly reduced.
Supplementary Tables 1 from Antitumor Efficacy of the Novel KIT Inhibitor IDRX-42 (Formerly M4205) in Patient- and Cell Line–Derived Xenograft Models of Gastrointestinal Stromal Tumor (GIST)
Authors: De Sutter Luna , Wozniak Agnieszka , Verreet Jasper , Vanleeuw Ulla , De Cock Lore , Linde Nina , Drechsler Christine , Esdar Christina , Sciot Raf , Schöffski Patrick
Published: June 2023

Supplementary Tables 1-3
Supplementary Fig. 3 from Antitumor Efficacy of the Novel KIT Inhibitor IDRX-42 (Formerly M4205) in Patient- and Cell Line–Derived Xenograft Models of Gastrointestinal Stromal Tumor (GIST)
Authors: De Sutter Luna , Wozniak Agnieszka , Verreet Jasper , Vanleeuw Ulla , De Cock Lore , Linde Nina , Drechsler Christine , Esdar Christina , Sciot Raf , Schöffski Patrick
Published: June 2023

Supplementary Fig. 3. One histologically representative picture of H&E staining per treatment group in the experiment with GIST882KIT13.
Supplementary Data Tables 1 from Immunogenomic Landscape of Neuroendocrine Prostate Cancer
Authors: Bhinder Bhavneet , Ferguson Alison , Sigouros Michael , Uppal Manik , Elsaeed Ahmed G. , Bareja Rohan , Alnajar Hussein , Eng Kenneth Wha , Conteduca Vincenza , Sboner Andrea , Mosquera Juan Miguel , Elemento Olivier , Beltran Himisha
Published: June 2023

Suppl Table S1. Clinical characteristics of metastatic patient cohort
Suppl Table S2. The 361 gene signature identified in this study to classify T-cell immune clusters
Suppl Table S3. The 80 immune and stroma related gene signatures used to quantify the TME
Suppl Table S4. DEGs for SCLC versus NEPC tumors
Suppl Table S5. NCI-Nature_2016 pathways enriched in the DEGs from SCLC vs NEPC
Supplementary Data S2 from Targeting BET Proteins Downregulates miR-33a To Promote Synergy with PIM Inhibitors in CMML
Authors: Letson Christopher T. , Balasis Maria E. , Newman Hannah , Binder Moritz , Vedder Alexis , Kinose Fumi , Ball Markus , Kruer Traci , Quintana Ariel , Lasho Terra L. , Finke Christy M. , Almada Luciana L. , Grants Jennifer M. , Zhang Guolin , Fernandez-Zapico Martin E. , Gaspar-Maia Alexandre , Lancet Jeffrey , Komrokji Rami , Haura Eric , Sallman David A. , Reuther Gary W. , Karsan Aly , Rix Uwe , Patnaik Mrinal M. , Padron Eric
Published: June 2023

Raw RNAseq data corresponding to Figures 2C, 4D and Supplemental Figure 2B
Supplementary Figure S4 from Autocrine 17-β-Estradiol/Estrogen Receptor-α Loop Determines the Response to Immune Checkpoint Inhibitors in Non–Small Cell Lung Cancer
Authors: Anobile Dario P. , Salaroglio Iris C. , Tabbò Fabrizio , La Vecchia Sofia , Akman Muhlis , Napoli Francesca , Bungaro Maristella , Benso Federica , Aldieri Elisabetta , Bironzo Paolo , Kopecka Joanna , Passiglia Francesco , Righi Luisella , Novello Silvia , Scagliotti Giorgio V. , Riganti Chiara
Published: June 2023

Disaggregated data of PD-L1 and ERα in non-small cell lung cancer patients, according to ages, tumor stages and smoking habits.
Expression of PD-L1 (panel a) and ERα (panel b) mRNA, measured by RT-PCR (technical triplicates) in tumor samples of 35 NSCLC patients, according to pathological classification (T: primary tumors; N: lymph nodes involved; M: metastasis), clinical stages (III-IV stage), smoking habits (never smoker: NSm; former smoker: FSm; current smoker: CSm). *p<0.05, **p<0.01, ***p<0.001: T versus N+M, III vs IV, NSM+FSm vs CSm (ANOVA).
Supplementary Data S1 from Targeting BET Proteins Downregulates miR-33a To Promote Synergy with PIM Inhibitors in CMML
Authors: Letson Christopher T. , Balasis Maria E. , Newman Hannah , Binder Moritz , Vedder Alexis , Kinose Fumi , Ball Markus , Kruer Traci , Quintana Ariel , Lasho Terra L. , Finke Christy M. , Almada Luciana L. , Grants Jennifer M. , Zhang Guolin , Fernandez-Zapico Martin E. , Gaspar-Maia Alexandre , Lancet Jeffrey , Komrokji Rami , Haura Eric , Sallman David A. , Reuther Gary W. , Karsan Aly , Rix Uwe , Patnaik Mrinal M. , Padron Eric
Published: June 2023

Raw data associated with miRNA Array performed for Supplemental Figure 4F
Supplementary Figure S15 from Autocrine 17-β-Estradiol/Estrogen Receptor-α Loop Determines the Response to Immune Checkpoint Inhibitors in Non–Small Cell Lung Cancer
Authors: Anobile Dario P. , Salaroglio Iris C. , Tabbò Fabrizio , La Vecchia Sofia , Akman Muhlis , Napoli Francesca , Bungaro Maristella , Benso Federica , Aldieri Elisabetta , Bironzo Paolo , Kopecka Joanna , Passiglia Francesco , Righi Luisella , Novello Silvia , Scagliotti Giorgio V. , Riganti Chiara
Published: June 2023

Letrozole sensitizes xenografts to a second cycle of pembrolizumab by modulating the tumor-associated immune-environment.
60 Hu-CD34+NSG mice bearing female-derived ERα lowNCI-H11385 and ERα highNCI-H1975 tumors, male-derived ERα lowA549 and ERα highNCI-H1650 tumors (15/tumor type) were treated for 5 weeks with pembrolizumab+letrozole with 10 mg/kg i.p. of 100 µL saline solution of pembrolizumab (day 1) followed by 5 mg/kg i.p. (days 7, 14, 21, 28, 35), and 1 mg/kg per os of 100 µL saline solution of letrozole daily (days 1-35), and then divided into three cohorts of 20 animals (n=5 mice/tumor type within each cohort). The first cohort of animals (left panel) was left untreated until week 15 (-Pemb-Letr); the second cohort (middle panel) was treated with 1 mg/kg per os of 100 µL saline solution of letrozole daily until week 15 (+Letr); the third cohort (right panel) was treated with 1 mg/kg per os of 100 µL saline solution of letrozole daily from week 6 to week 10, and then with pembrolizumab+letrozole from week 11 to week 15 (+Pemb+Letr). a. Tumor growth was monitored daily using calipers. Data are presented as mean volumes+ SD. **p<0.01, ***p<0.001: volume of female ERα lowNCI-H1385 and ERα highNCI-H1975 tumors (left panel), or ERα highNCI-H1975 tumors (middle-right panels) versus mean volume of male ERα lowA549 and ERα highNCI-H1650 tumors. b. PD-L1 expression was measured using flow cytometry on dissociated tumor cells after explants at week 15 (n=5/group). *p<0.05: +Pemb+Letr versus -Pemb-Letr (NCI-H1650 tumors), +Letr versus -Pemb-Letr (NCI-H1385 tumors); **p<0.01: +Pemb+Letr versus -Pemb-Letr (NCI-H1385 tumors); ***p<0.001: +Letr/+Pemb+Letr versus -Pemb-Letr (NCI-H1975 tumors) (ANOVA). c-e. On TILs isolated from tumor extracts (week 15), the percentage of CD8+Ki67+IFNγ+cells (panel c), CD56+Ki67+IFNγ+cells (panel d), and Vγ9+Ki67+IFNγ+cells (panel e) was measured by flow cytometry (n=5/group). CD8+Ki67+IFNγ+cells: *p<0.05: +Pemb+Letr versus -Pemb-Letr (NCI-H1975 and NCI-H1650 tumors), ***p<0.001: +Pemb+Letr versus -Pemb-Letr (NCI-H1385 tumors). CD56+Ki67+IFNγ+cells: *p<0.05: +Pemb+Letr versus -Pemb-Letr (NCI-H1385, NCI-H1975 and NCI-H1650 tumors). Vγ9+Ki67+IFNγ+cells: *p<0.05: +Pemb+Letr versus -Pemb-Letr (NCI-H1385, NCI-H1975 and NCI-H1650 tumors) (ANOVA).
Supplementary Figure S12 from Autocrine 17-β-Estradiol/Estrogen Receptor-α Loop Determines the Response to Immune Checkpoint Inhibitors in Non–Small Cell Lung Cancer
Authors: Anobile Dario P. , Salaroglio Iris C. , Tabbò Fabrizio , La Vecchia Sofia , Akman Muhlis , Napoli Francesca , Bungaro Maristella , Benso Federica , Aldieri Elisabetta , Bironzo Paolo , Kopecka Joanna , Passiglia Francesco , Righi Luisella , Novello Silvia , Scagliotti Giorgio V. , Riganti Chiara
Published: June 2023

Dose-dependent inhibition of Akt, ERK1/2 and EGFR.
ERα highNCI-H1975 cells were grown 24 h in fresh medium (Ctrl) or in medium containing 10 nM, 100 nM, 1 μM of the Akt inhibitor MK-2206 (Akti, panel a), 0.1 μM, 1 μM, 10 μM of the ERK1/2 inhibitor U-0126 (ERKi, panel b), 10 nM, 100 nM, 1 μM of the EGFR inhibitor AZD9291/Osimertinib (EGFRi, panel c). As read-out assays, Akt and ERK1/2 activity were measured by ELISA (technical duplicates), EGFR kinase activity was measured by a chemiluminescence-based assay (technical duplicates). Data are means + SD (n=3, biological replicates). *p<0.05, ***p<0.001: treated cells versus Ctrl cells (ANOVA).
Supplemental Table S2 from Cost-effectiveness of p16/Ki-67 Dual-Stained Cytology Reflex Following Co-testing with hrHPV Genotyping for Cervical Cancer Screening
Authors: Harper Diane M. , Anderson Rye J. , Baker Ed , Yu Tiffany M.
Published: June 2023

Supplemental Table S2 shows the distribution of patient attributes in the prevalent US population of women eligible for cervical cancer screening
Supplemental Table S1 from Cost-effectiveness of p16/Ki-67 Dual-Stained Cytology Reflex Following Co-testing with hrHPV Genotyping for Cervical Cancer Screening
Authors: Harper Diane M. , Anderson Rye J. , Baker Ed , Yu Tiffany M.
Published: June 2023

Supplemental Table S1 shows the unpublished data from the IMPACT clinical trial referenced in for the model inputs
Data from Polymorphisms in the Nonhomologous End-joining DNA Repair Pathway are Associated with HPV Integration in Cervical Dysplasia
Authors: Geris Jennifer M. , Amirian E. Susan , Marquez-Do Deborah A. , Guillaud Martial , Dillon Laura M. , Follen Michele , Scheurer Michael E.
Published: June 2023

Abstract
Previous evidence indicates that human papillomavirus (HPV) integration status may be associated with cervical cancer development and progression. However, host genetic variation within genes that may play important roles in the viral integration process is understudied. The aim of this study was to examine the association between HPV16 and HPV18 viral integration status and SNPs in nonhomologous-end-joining (NHEJ) DNA repair pathway genes on cervical dysplasia. Women enrolled in two large trials of optical technologies for cervical cancer detection and positive for HPV16 or HPV18 were selected for HPV integration analysis and genotyping. Associations between SNPs and cytology (normal, low-grade, or high-grade lesions) were evaluated. Among women with cervical dysplasia, polytomous logistic regression models were used to evaluate the effect of each SNP on viral integration status. Of the 710 women evaluated [149 high-grade squamous intraepithelial lesion (HSIL), 251; low-grade squamous intraepithelial lesion (LSIL, 310 normal)], 395 (55.6%) were positive for HPV16 and 192 (27%) were positive for HPV18. Tag-SNPs in 13 DNA repair genes, including RAD50, WRN, and XRCC4, were significantly associated with cervical dysplasia. HPV16 integration status was differential across cervical cytology, but overall, most participants had a mix of both episomal and integrated HPV16. Four tag-SNPs in the XRCC4 gene were found to be significantly associated with HPV16 integration status. Our findings indicate that host genetic variation in NHEJ DNA repair pathway genes, specifically XRCC4, are significantly associated with HPV integration, and that these genes may play an important role in determining cervical cancer development and progression.
Prevention Relevance:
HPV integration in premalignant lesions and are thought to be an important driver of carcinogenesis. However, it is unclear what factors promote integration. The use of targeted genotyping among women presenting with cervical dysplasia has the potential to be an effective tool in assessing the likelihood of progression to cancer.
Progressive Spreading of DNA Methylation in the GSTP1 Promoter CpG Island across Transitions from Precursors to Invasive Prostate Cancer
Authors: Gupta Harshath , Inoue Hitoshi , Nakai Yasutomo , Nakayama Masashi , Jones Tracy , Hicks Jessica L. , Kumar Balasubramanian , Gurel Meltem , Nelson William G. , De Marzo Angelo M. , Yegnasubramanian Srinivasan
Published: June 2023

Glutathione S-transferase pi 1 (GSTP1) is lowly expressed in normal prostate luminal cells and becomes induced in most proliferative inflammatory atrophy (PIA) lesions. GSTP1 becomes silenced in prostatic intraepithelial neoplasia (PIN) and prostate adenocarcinoma (CaP) via cytosine-phospho-guanine (CpG) island promoter hypermethylation. However, GSTP1 methylation patterns in PIA and PIN, and their relationship to patterns in CaP are poorly understood. We used bisulfite genomic sequencing to examine patterns of GSTP1 promoter CpG island methylation in laser capture microdissected benign, PIA, PIN, and CaP regions from 32 subjects that underwent radical prostatectomy. We analyzed 908 sequence clones across 24 normal epithelium, 37 PIA, 18 PIN, and 23 CaP regions, allowing assessment of 34,863 CpG sites with allelic phasing. Normal and PIA lesions were mostly unmethylated with 0.52 and 1.3% of total CpG sites methylated, respectively. PIN and CaP lesions had greater methylation with 24% and 51% of total CpG sites methylated, respectively. The degree of GSTP1 methylation showed progression from PIA << PIN < CaP. PIN lesions showed more partial methylation compared with CaP lesions. Partially methylated lesions were enriched for methylation changes at AP1 and SP1 transcription factor binding sites. These results demonstrate that methylation density in the GSTP1 CpG island in PIN was intermediate relative to that in normal prostate epithelium/PIA and CaP lesions. These results are consistent with gradual spreading of DNA methylation centered at the SP1/AP1 transcription factor binding sites in precursor lesions, with subsequent spreading of methylation across the entire CpG island in transition to CaP.

Prevention Relevance:

DNA hypermethylation at the GSTP1 promoter progressively spreads from being unmethylated in normal prostate to intermediate levels in precursor lesions to extensive methylation in cancer. This molecular progression of GSTP1 promoter methylation patterns in early prostate carcinogenesis could be useful for identification and interception of prostate cancer precursors.
TABLE 1 from A Mendelian Randomization Analysis of 55 Genetically Predicted Metabolic Traits with Breast Cancer Survival Outcomes in the Pathways Study
Authors: Fiorica Peter N. , Sheng Haiyang , Zhu Qianqian , Roh Janise M. , Laurent Cecile A. , Ergas Isaac J. , Delmerico Jennifer , Kwan Marilyn L. , Kushi Lawrence H. , Ambrosone Christine B. , Yao Song
Published: June 2023

Baseline characteristics of patients with breast cancer in the Pathways Study (n = 3,902)
Supplementary Figure 2 from A Mendelian Randomization Analysis of 55 Genetically Predicted Metabolic Traits with Breast Cancer Survival Outcomes in the Pathways Study
Authors: Fiorica Peter N. , Sheng Haiyang , Zhu Qianqian , Roh Janise M. , Laurent Cecile A. , Ergas Isaac J. , Delmerico Jennifer , Kwan Marilyn L. , Kushi Lawrence H. , Ambrosone Christine B. , Yao Song
Published: June 2023

Dot plot of statistically-significant findings stratified by tumor estrogen receptor (ER) status in whole analytic population, with 3,260 ER+ and 640 ER- individuals
FIGURE 4 from A Mendelian Randomization Analysis of 55 Genetically Predicted Metabolic Traits with Breast Cancer Survival Outcomes in the Pathways Study
Authors: Fiorica Peter N. , Sheng Haiyang , Zhu Qianqian , Roh Janise M. , Laurent Cecile A. , Ergas Isaac J. , Delmerico Jennifer , Kwan Marilyn L. , Kushi Lawrence H. , Ambrosone Christine B. , Yao Song
Published: June 2023

Five forest plots depict the HRs calculated in the ER− group for nominally significant (P < 0.05) survival outcome associations with PGS for five different traits: serum fasting glucose (A), type 2 diabetes (B), AST (C), IGF-1 (D), and total serum protein (E). Each point on the plot represents a test between the PGS-tertile and breast cancer–related survival outcome. Green represents tertile 1. Violet represents tertile 2. Blue represents tertile 3. The y-axis shows the survival outcome, and the x-axis represents the HR. Horizontal lines represent 95% CIs from the Wald test. Associations with P < 0.05, but HR CIs overlapping with one were removed from the plot.
Data from Remodeling of Stromal Immune Microenvironment by Urolithin A Improves Survival with Immune Checkpoint Blockade in Pancreatic Cancer
Authors: Mehra Siddharth , Garrido Vanessa T. , Dosch Austin R. , Lamichhane Purushottam , Srinivasan Supriya , Singh Samara P. , Zhou Zhiqun , De Castro Silva Iago , Joshi Chandrashekar , Ban Yuguang , Datta Jashodeep , Gilboa Eli , Merchant Nipun B. , Nagathihalli Nagaraj S.
Published: June 2023

Pancreatic ductal adenocarcinoma (PDAC) is a significant contributor to cancer-related morbidity and mortality, and it is known for its resistance to conventional treatment regimens, including chemotherapy and immune checkpoint blockade (ICB)-based therapies. We have previously shown that Urolithin A (Uro A), a gut microbial metabolite derived from pomegranates, can target and inhibit KRAS-dependent PI3K/AKT/mTOR signaling pathways to overcome therapeutic resistance and improve survival in PDAC. However, the effect of Uro A on the tumor immune microenvironment and its ability to enhance ICB efficacy has not been explored. This study demonstrates that Uro A treatment reduces stromal fibrosis and reinvigorates the adaptive T-cell immune response to overcome resistance to PD-1 blockade in a genetically engineered mouse model (GEMM) of PDAC. Flow cytometric–based analysis of Uro A-treated mouse tumors revealed a significant attenuation of immunosuppressive tumor-associated M2-like macrophages with a concurrent increase in the infiltration of CD4+ and CD8+ T cells with memory-like phenotype along with reduced expression of the exhaustion-associated protein, PD-1. Importantly, the combination of Uro A treatment with anti-PD-1 immunotherapy promoted enhancement of the antitumor response with increased infiltration of CD4+ Th1 cells, ultimately resulting in a remarkable improvement in overall survival in GEMM of PDAC. Overall, our findings provide preclinical evidence for the potential of Uro A as a novel therapeutic agent to increase sensitivity to immunotherapy in PDAC and warrant further mechanistic exploration in preclinical and clinical studies.
Significance:
Immunotherapeutic agents are ineffective against pancreatic cancer, mainly due to the immunosuppressive tumor microenvironment and stromal desmoplasia. Our current study demonstrates the therapeutic utility of a novel gut microbial metabolite, Uro A, to remodel the stromal-immune microenvironment and improve overall survival with anti-PD-1 therapy in pancreatic cancer.
Use of a Prophylactic Retrograde-Flushing Device in High-Risk Pediatric Patients with Ventriculoperitoneal Shunts: A Technical Note
Authors: Vinzani Michael , Alshareef Mohammed , Eskandari Ramin
Published: June 2023

Introduction: Ventriculoperitoneal shunt (VPS) malfunction rates are as high as 40% in the first year with posthemorrhagic hydrocephalus (PHH) patients having the highest proximal occlusion risk. Debris, protein, and cellular ingrowth most commonly obstruct the proximal ventricular catheter and/or valve. Historically, no preventative methods have demonstrated efficacy. We present a technical note and case series describing the use of a retrograde proximal flushing device and prophylactic flushing protocol to maintain ventricular catheter patency and reduce proximal shunt occlusions. Methods: We present our 2.8–4-year follow-up data on the first 9 pediatric cases of ReFlow (Anuncia Inc, Scottsdale, AZ) device implantation combined with routine prophylactic flushing. Rationale for device implantation, patient selection, surgical procedure details, postoperative follow-up, and prophylactic flushing protocol are discussed as well as pre- and postimplantation ventricular catheter obstruction rates. We include a technical note on the device setup and prophylactic flushing protocol. Results: Patient average age was 5.6 years and all patients had PHH. Minimal follow-up was 2.8 years (range 2.8–4 years). Prophylactic flushing was initiated between 2 and 14 days after ReFlow implantation and has continued as of the last follow-up. In 7 patients, ReFlow implantation occurred during the revision of an existing shunt and in two, implantation was coincident with initial VPS placement. In the 2 years preceding ReFlow and prophylactic flushing, 14 proximal shunt failures occurred in the 7 patients with existing VPS. This was reduced to only one proximal shunt failure in all 9 patients during the full follow-up period after ReFlow and prophylactic flushing. Conclusion: Pediatric VPS placement carries high rates of proximal catheter occlusion, often leading to emergency surgery, morbidity, or even death. The ReFlow device along with routine prophylactic flushing may reduce proximal obstruction and need for revision surgery. Higher patient numbers and longer follow-up periods are necessary to further elucidate the safety and effect of such a device on longer term shunt failures and revision surgery.
An ensemble approach for the identification and classification of crime tweets in the English language
Authors: Siddiqui Tooba , Hina Saman , Asif Raheela , Ahmed Saad , Ahmed Munad
Published: June 2023

Twitter is a famous social media platform, which supports short posts limited to 280 characters. Users tweet about many topics like movie reviews, customer service, meals they just ate, and awareness posts. Tweets carrying information about some crime scenes are crime tweets. Crime tweets are crucial and informative and separate classification is required. Identification and classification of crime tweets is a challenging task and has been the researcher’s latest interest. The researchers used different approaches to identify and classify crime tweets. This research has used an ensemble approach for the identification and classification of crime tweets. Tweepy and Twint libraries were used to collect datasets from Twitter. Both libraries use contrasting methods for extracting tweets from Twitter. This research has applied many ensemble approaches for the identification and classification of crime tweets. Logistic regression (LR), support vector machine (SVM), k-nearest neighbor (KNN), decision tree (DT), and random forest (RF) Classifier assigned with the weights of 1,2,1,1 and 1 respectively ensemble together by a soft weighted Voting classifier along with term frequency – inverse document frequency (TF-IDF) vectorizer gives the best performance with an accuracy of 96.2% on the testing dataset.
Virtual Reality's Effects on Air Crash Accident Investigation Learning Interaction
Authors: Othman H Alburaidi Faisal , Jenkins Karl , Teschner Tom-Robin
Published: June 2023

The objective of this study is to gain a deeper comprehension of the factors that play a role in the evolution of virtual reality (VR) for application in the investigation of aviation disasters. This study was motivated by the concept of utilising VR to create an illusion of the procedures involved in an anviation accident. A conceptual model has been presented, to create the scene that will be simple to understand the procedure of accident following an air crash. The idea is to compile a series of steps that an investigation team will go through and then present them in VR. This stage entails obtaining complete views of the object before it crashes and at ground level. This study contributes to the process of creating the groundwork for adopting VR in air crash investigations to provide instructional experiences. The idea that was presented in this research focuses on feature of the surrounding area of the crash or accident, wreckage distribution, wreckage above the ground, wreckage in motion, wreckage at the ground, spatial view effect, and full view projection as the primary VR features that are required for teaching and learning about air crash accident investigations using VR.
Fuzzy logic-based controller of the bidirectional direct current to direct current converter in microgrid
Authors: Boujoudar Younes , Azeroual Mohamed , Eliysaouy Lahcen , Bassine Fatima Zahra , Albarakati Aiman J. , Aljarbouh Ayman , Knyazkov Alexey , El Moussaoui Hassan , Lamhamdi Tijani
Published: June 2023

Microgrids are small-scale power networks that include renewable energy sources, load, energy storage systems, and energy management systems (EMS). Lithium-ion batteries are the most used battery for energy storage in microgrids due to their advantages over other types of batteries. However, to protect the battery from the explosion and to manage to charge and discharge based on state-of-charge (SoC) value, this type of battery requires the use of an energy management system. The main objective of this paper is to propose an intelligent control strategy for energy management in the microgrid to control the charge and discharge of Li-ion batteries to stabilize the system and reduce the cost of electricity due to the high cost of grid electricity. The proposed technique is based on a fuzzy logic controller (FLC) for voltage control. The FLC is based on the measured voltage of the direct current (DC) bus and the fixed reference voltage to generate buck/boost converter signal control. The proposed technique has been simulated and tested using MATLAB/Simulink software which illustrates the tracking of desired power and DC bus voltage regulation. The simulation results confirm that the proposed systems can diminish the deviations of the system's voltage.
Multi-objective distributed generation integration in radial distribution system using modified neural network algorithm
Authors: Tarraq Ali , El Mariami Faissal , Belfqih Abdelaziz
Published: June 2023

This paper introduces a new approach based on a chaotic strategy and a neural network algorithm (NNA), called chaotic-based NNA (CNNA), to solve the optimal distributed generation allocation (ODGA), in the radial distribution system (RDS). This consists of determining the optimal locations and sizes of one or several distributed generations (DGs) to be inserted into the RDS to minimize one or multiple objectives while meeting a set of security limits. The robustness of the proposed method is demonstrated by applying it to two different typical RDSs, namely IEEE 33-bus and 69-bus. In this regard, simulations are performed for three DGs in the cases of unity power factor (UPF) and optimal power factor (OPF), considering single and multi-objective optimization, by minimizing the total active losses and improving the voltage profile, voltage deviation (VD) and voltage stability index (VSI). Compared to its original version and recently reported methods, the CNNA solutions are more competitive without increasing the complexity of the optimization algorithm, especially when the RDS size and problem dimension are extended.
Technical and market evaluation of thermal generation power plants in the Colombia power system
Authors: Silva-Ortega Jorge , Calvo Cervantes Jean Carlos , Rodriguez Acosta Eliab de Jesus , Isaac Millán Idi Amin , Rivera-Alvarado Juan , Berdugo Sarmiento Kelly Margarita
Published: June 2023

Thermal power plants are the widely conventional generation unit technology used to produce electricity being controllable and dispatchable. The location of thermal power plants depends on the energy availability conditions of the areas and the capacity to fuels access. Their location and geographical distribution define a high level of concentration in areas defined as thermal districts and its location define reliability, security, availability, and flexibility indices to avoid critical scenario or support system from contingencies. However, in many cases the electrical configuration does not correspond to requirements. This paper links the concentration by political distribution in Colombia and the configuration used in the generating substations to guarantee requirements. The Hirschman-Herfindahl index as a market tool is used to evaluate energy concentration facing representative participation in certain departments of Colombia. Results evidenced configurations and concentration in a study case, results and analysis could be used for planner to promote participation, reliability and promote. The paper’s contribution and conclusions are linked to guide planners towards market and technical tool to evaluate installed capacities, avoid market concentration, and reduce risky scenarios.
Quality control test for unreliable meteorological and electrical photovoltaic measurements
Authors: Galarza Jose , Condezo David
Published: June 2023

Meteorological and electrical measurements using predictive computational techniques have been used in the analysis of photovoltaic system operation and maintenance. International standards establish general and no standardized criteria on the quality control and validation of these measurements. In the present work, a methodology has been developed to correct erroneous photovoltaic experimental measurements: radiation, temperature, current, and voltage. We validated the proposed approach with 12 case studies with more than 5,000 meteorological and electric measurements from an experimental 3 kWp photovoltaic system. The approach is based on a set of non-intrusive criteria developed from the one diode model, the approach allowed to correct about 80% of the erroneous data, 30% more using polynomial regression. As for the regression methodology, we have shown that the proposed methodology includes 4 meteorologicalelectrical variables allowing a more rigorous analysis. For 75% of the cases evaluated, the proposed methodology achieves a better data correction.
Optimal artificial neural network configurations for hourly solar irradiation estimation
Authors: Dhiaeddine Mostefaoui Mohamed , Khalil Benmouiza , Youcef Oubbati
Published: June 2023

Solar energy is widely used in order to generate clean electric energy. However, due to its intermittent nature, this resource is only inserted in a limited way within the electrical networks. To increase the share of solar energy in the energy balance and allow better management of its production, it is necessary to know precisely the available solar potential at a fine time step to take into account all these stochastic variations. In this paper, a comparison between different artificial neural network (ANN) configurations is elaborated to estimate the hourly solar irradiation. An investigation of the optimal neurons and layers is investigated. To this end, feedforward neural network, cascade forward neural network and fitting neural network have been applied for this purpose. In this context, we have used different meteorological parameters to estimate the hourly global solar irirradiation in the region of Laghouat, Algeria. The validation process shows that choosing the cascade forward neural network two inputs gives an R2 value equal to 97.24% and an normalized root mean square error (NRMSE) equals to 0.1678 compared to the results of three inputs, which gives an R2 value equaled to 95.54% and an NRMSE equals to 0.2252. The comparison between different existing methods in literature show the goodness of the proposed models.
Optimal tuning proportional integral derivative controller on direct current motor using reptile search algorithm
Authors: Aribowo Widi , Suprianto Bambang , Kartini Unit Three , Wardani Ayusta Lukita
Published: June 2023

This paper presents the reptile search algorithm (RSA) method to optimize the proportional integral derivative (PID) parameters on direct current (DC) motors. RSA was adopted from crocodile hunting behavior. Crocodile behavior is modeled in two important steps: surrounding and attacking prey. The RSA method was applied using twenty-three classical test functions. The search method of the proposed RSA method with other existing algorithms such as particle swarm optimization (PSO), and differential evolution (DE). Integral multiplied by absolute error (ITAE) and integral of time multiplied squared error (ITSE) were used as comparisons in measuring the performance of the RSA method. The results show that the proposed method, namely RSA, has better efficiency. Optimization of PID parameters with RSA on DC motor control shows superior performance. From the experiment, the ITSE average value of the RSA method is 4.17% better than the conventional PID method.
New typical power curves generation approach for accurate renewable distributed generation placement in the radial distribution system
Authors: Tarraq Ali , El Mariami Faissal , Belfqih Abdelaziz
Published: June 2023

This paper investigates, for the first time, the accuracy of normalized power curves (NPCs), often used to incorporate uncertainties related to wind and solar power generation, when integrating renewable distributed generation (RDG), in the radial distribution system (RDS). In this regard, the present study proposes a comprehensive, simple, and more accurate model, for estimating the expected hourly solar and wind power generation, by adopting a purely probabilistic approach. Actually, in the case of solar RDG, the proposed model allows the calculation of the expected power, without going through a specific probability density function (PDF). The validation of this model is performed through a case study comparing between the classical and the proposed model. The results show that the proposed model generates seasonal NPCs in a less complex and more relevant way compared to the discrete classical model. Furthermore, the margin of error of the classical model for estimating the expected supplied energy is about 12.6% for the photovoltaic (PV) system, and 9% for the wind turbine (WT) system. This introduces an offset of about 10% when calculating the total active losses of the RDS after two RDGs integration.
Improved spectral mismatch and performance of a phosphor-converted light-emitting diode solar simulator
Authors: Watjanatepin Napat , Wannakam Khanittha , Kiatsookkanatorn Paiboon , Boonmee Chaiyant , Sritanauthaikorn Patcharanan
Published: June 2023

A phosphor-converted light-emitting diode (LED) solar simulator is an illuminance device that produced irradiance intensity and spectral close to the sunlight. It is determined as spectral mismatch, non-uniformity of irradiance, and temporal instability. This paper has improved the LED solar simulator (LSS) system to have a spectral distribution consistent with the AM1.5G spectrum at 100%. It was developed as a new prototype to have the AAA class spectral characteristics, time instability, and inconsistency according to IEC 60904-9. The results showed that an optimal approach was to use phosphor-converted natural white LED (pc-nWLED), combining a monochromatic near-infrared (NIR) (730, 800, 850, 940, and 1,000 nm) as well as the proposed LSS system capable of generating 1,000 W/m2 irradiation over the test plane of 125×125 mm and operated continuously in a constant temperature LED state for at least 2 hours, therefore suitable for demonstration of solar cell features under standard test condition (STC) in the laboratory.
A cost-effective and optimized maximum powerpoint tracking system for the photovoltaic model
Authors: Puttalingaiah Yoganandini Arehalli , Shesadri Anitha Gowda
Published: June 2023

Solar energy is naturally available from sun, and it can be extracted by using a photovoltaic (PV) cell. However, solar energy extraction entirely depends on the climatic conditions and angle of rays falling on PV cells. Hence, maximum powerpoint tracking (MPPT) is considered in most areas under variable climatic conditions, which acts as a controller unit for PV cells. MPPT can enhance the efficiency of PV cells. However, designing an MPPT model is challenging as different uncertainties in the climatic condition may lead to more fluctuations in voltage and current in PV cells. Under the shaded condition, the PV cell may have other MPPT points that lead to the PV cell’s low efficiency in analyzing maximum power. Hence, this paper introduces a cost-effective and optimized system for the PV model that can find optimal power and improve PV cells’ efficiency. The proposed system achieves better computational performance with ~35% and ~42% than existing MPPT techniques. The improved particle swarm optimization (PSO) is smoother due to the enhanced form of MPP tracking. Hence, improved PSO takes 0.038 sec while the existing PSO technique takes 0.045 sec to obtain the MPP tracking.
BaAl1.4Si0.6O3.4N0.6:Eu2+ green phosphors’ application for improving luminous performance
Authors: Nguyen Thi My Hanh , Le Thai Nguyen , Minh Bui Thuc , Nguyen Kieu Tam
Published: June 2023

The molten salt synthesis (MSS) method was used to effectively prepare green phosphors BaAl1.4Si0.6O3.4N0.6:Eu2+ (or BSON:Eu2+) via one homogeneous sphere-like morphology utilizing NaNO3 in the form of the reacting agent. The phosphors produced one wide stimulation spectrum between 250 and 460 nm, as well as a significant green emission has a maximum point at 510 nm owing to the 4f65d1-4f7 (8S7/2) shifts for Eu2+ ions. With illumination under 365 as well as 450 nm, the ideal discharge strengths for the specimen prepared utilizing melted salt would receive a boost of 17% and 13%, surpassing the specimen prepared utilizing the traditional solid-state reaction (SSR) approach. The abatement of concentration for the ions of Eu2+ from BSON:Eu2+ is 5 mol%. In addition, the interactivity of dipole-dipole would be the cause of said abatement. Heat abatement would be studied utilizing the formation coordinate method with abatement temperature reaching ∼200 oC. Elemental mapping as well as power-dispersing X-ray spectroscopy (EDS) spectra demonstrated that the expected BaAl1.4Si0.6O3.4N0.6:Eu2+ materials were formed.
A thermally aware performance analysis of quantum cellular automata logic gates
Authors: Kotte Sujatha , Durga Ganapavarapu Kanaka
Published: June 2023

The high-performance digital circuits can be constructed at high operating frequency, reduced power dissipation, portability, and large density. Using conventional complementary-metal-oxide-semiconductor (CMOS) design process, it is quite difficult to achieve ultra-high-speed circuits due to scaling problems. Recently quantum dot cellular automata (QCA) are prosed to develop logic circuits at atomic level. In this paper, we analyzed the performance of QCA circuits under different temperature effects and observed that polarization of the cells is highly sensitive to temperature. In case of the 3-input majority gate the cell polarization drops to 50% with an increase in the temperature of 18 K and for 5 input majority gate the cell polarization drops more quickly than the 3-input majority. Further, the performance of majority gates also compared in terms of area and power dissipation. It has been noticed that the proposed logic gates can also be used for developing simple and complex and memory circuits.
Bio-inspired algorithm for decisioning wireless access point installation
Authors: Thitinaruemit Aphirak , Sitjongsataporn Suchada , Prongnuch Sethakarn
Published: June 2023

This paper presents the bio-inspired algorithms for decisioning wireless access point (AP) installation. In order to achieve the desired coverage capability of APs, the bio-inspired algorithms are applied for robust competition and optimization. The main objective is to determine the optimal number of APs with the high coverage capability in the concerning area using the genetic and ant colony optimization algorithms. Received signal strength indicator (RSSI) and line-of-sight (LoS) gradient approach are the most important parameters for AP installation depending on the AP signal strength. Practical experiments are tested on the embedded system using Xilinx Kria KR260 and Raspberry Pi Zero 2W boards at the tested room size about 16 m wide and 40 m long inside the building. Xilinx Kria KR260 board is used to calculate the number of AP installation and localization compared to Xcode. Then, Raspberry Pi Zero 2W board is the representation of wireless AP for measuring the signal in the testing area. Experiment results show that maximum received signals strength is equal to -35 dBm at 6 m and there are six APs installation with high coverage area and maximum received signal strength at the area of 16×40 m2.
Unknown input observer for Takagi-Sugeno implicit models with unmeasurable premise variables
Authors: Essabre Mohamed , Hmaiddouch Ilham , El Assoudi Abdellatif , El Yaagoubi El Hassane
Published: June 2023

Recent years have seen a great deal of interest in implicit nonlinear systems, which are used in many different engineering applications. This study is dedicated to presenting a new method of fuzzy unknown inputs observer design to estimate simultaneously both non-measurable states and unknown inputs of continuous-time nonlinear implicit systems defined by Takagi-Sugeno (T-S) models with unmeasurable premise variables. The suggested observer is based on the singular value decomposition approach and rewritten the continuous-time T-S implicit models into an augmented fuzzy system, which gathers the unknown inputs and the state vector. The exponential convergence condition of the observer is established by using the Lyapunov theory and linear matrix inequalities are solved to determine the gains of the observer. Finally, the effectiveness of the suggested method is then assessed using a numerical application. It demonstrates that the estimated variables and the unknown input converge to the real variables accurately and quickly (less than 0.5 s).
State of charge estimation based on a modified extended Kalman filter
Authors: Omiloli Koto , Awelewa Ayokunle , Samuel Isaac , Obiazi Oghorchukwuyem , Katende James
Published: June 2023

The global transition from fossil-based automobile systems to their
 electric-driven counterparts has made the use of a storage device inevitable. Owing to its high energy density, lower self-discharge, and higher cycle lifetime the lithium-ion battery is of significant consideration and usage in electric vehicles. Nevertheless, the state of charge (SOC) of the battery, which cannot be measured directly, must be calculated using an estimator. This paper proposes, by means of a modiﬁed priori estimate and a compensating proportional gain, an improved extended Kalman ﬁlter (IEKF) for the estimation task due to its nonlinear application and adaptiveness to noise. The improvement was achieved by incorporating the residuals of the previous state matrices to the current state predictor and introducing an attenuating factor in the Kalman gain, which was chosen to counteract the effect of the measurement and process noise resulting in better accuracy performance than the conventional SOC curve fitting-based estimation and ampere hour methods. Simulation results show that the standard EKF estimator results in performance with an error bound of 12.9% due to an unstable start, while the modified EKF reduces the maximum error to within 2.05% demonstrating the quality of the estimator.
Sensor fault reconstruction for wind turbine benchmark model using a modified sliding mode observer
Authors: Taouil Mohammed , El Ougli Abdelghani , Tidhaf Belkassem , Zrouri Hafida
Published: June 2023

This paper proposes a fault diagnosis scheme applied to a wind turbine system. The technique used is based on a modified sliding mode observer (SMO), which permits the reconstruction of actuator and sensor faults. A wind turbine benchmark with a real sequence of wind speed is exploited to validate the proposed fault detection and diagnosis scheme. Rotor speed, generator speed, blade pitch angle, and generator torque have different orders of magnitude. As a result, the dedicated sensors are susceptible to faults of quite varying magnitudes, and estimating simultaneous sensor faults with accuracy using a classical SMO is difficult. To address this issue, some modifications are made to the classic SMO. In order to test the efficiency of the modified SMO, several sensor fault scenarios have been simulated, first in the case of separate faults and then in the case of simultaneous faults. The simulation results show that the sensor faults are isolated, detected, and reconstructed accurately in the case of separate faults. In the case of simultaneous faults, with the proposed modification of SMO, the faults are precisely isolated, detected, and reconstructed, even though they have quite different amplitudes; thus, the relative gap does not exceed 0.08% for the generator speed sensor fault.