bluuebunny/crossref_metadata_2025 huggingface dataset:
Mathematical and Physical Characteristics of the Phase Spectrum of Earthquake Ground Motions
Authors: Ding Yanqiong , Xu Yazhou , Miao Huiquan
Published: April 2024

This study presents a rigorous investigation into the mathematical and physical properties inherent in the Fourier phase spectrum of earthquake ground motions. This exploration includes a detailed examination of the probability distribution of phase angles and differences, elucidated through two novel numerical experiments utilizing the reduction ad absurdum approach. Moreover, the study scrutinizes the physical attributes of earthquake ground motion’s phase spectrum, employing the circular frequency-dependent phase derivative as a key analytical factor. In a novel approach, the research delves into the relationship between circular frequency-dependent phase derivatives and Fourier amplitudes, shedding light on essential connections within earthquake phenomena, particularly addressing non-stationarity. Expanding the scope, the study comprehensively examines the influence of source, propagation path, and site on both the phase spectrum and accelerogram. Employing the control variate technique facilitates this analysis, providing valuable insights into the underlying physical mechanisms governing earthquake wave behavior. The findings highlight the temporal properties of the phase spectrum, attributing its complexity to the temporal heterogeneity in energy release during the fault rupture and dispersion of earthquake waves. This novel approach not only enhances the understanding of earthquake dynamics, but also underscores the significance of considering temporal variations in earthquake events.
Investigation of Key Parameters Influencing Shear Behavior in Glass-Fiber-Reinforced Polymer (GFRP)-Reinforced Concrete (RC) Interior Slab–Column Connections
Authors: Alkhattabi Loai , Ayash Nehal M. , Hassan Mohamed , Gouda Ahmed
Published: April 2024

This article explores the punching shear behavior of GFRP-RC interior slab–column connections. The parameters tested included the column–aspect ratio (1.0, 2.0, 3.0, 4.0, and 5.0), perimeter-to-depth ratio for square column stubs with side lengths of 0.3, 0.4, 0.5, 0.6, and 0.7 m, and span-to-depth ratios of 4, 6, 8, 10, and 12. A review of the literature revealed that no previous study has investigated the effect of these parameters or their interactions on this type of connection. Numerically, twenty-five slabs were created using finite element (FE) software (V3), each with square dimensions of 2.5 m and a constant thickness of 0.2 m. The central column extended 0.3 m from the top and bottom of the slab. All four sides of the slabs were supported, and the specimens underwent pure static shear load testing. The test results demonstrated that all slabs failed due to punching shear. Increasing any parameter value reduced the punching shear stresses. Additionally, the results indicated that Canadian (CSA-S806-12) and Japanese (JSCE-97) standards for FRP-RC materials generally provided the closest predictions of punching shear capacity compared to the American guideline, ACI 440.1R-22. However, all standards exhibited shortcomings and require enhancement and modifications, particularly to consider the impact of the span-to-depth ratio. Therefore, three equations were developed to predict the shear strength of the connections, yielding better results than those prescribed by the North American and Japanese standards.
Dissecting the Puzzling Roles of FAM46C: A Multifaceted Pan-Cancer Tumour Suppressor with Increasing Clinical Relevance
Authors: Lai Giancarlo , De Grossi Federica , Catusi Ilaria , Pesce Elisa , Manfrini Nicola
Published: April 2024

FAM46C is a well-established tumour suppressor with a role that is not completely defined or universally accepted. Although FAM46C expression is down-modulated in several tumours, significant mutations in the FAM46C gene are only found in multiple myeloma (MM). Consequently, its tumour suppressor activity has primarily been studied in the MM context. However, emerging evidence suggests that FAM46C is involved also in other cancer types, namely colorectal, prostate and gastric cancer and squamous cell and hepatocellular carcinoma, where FAM46C expression was found to be significantly reduced in tumoural versus non-tumoural tissues and where FAM46C was shown to possess anti-proliferative properties. Accordingly, FAM46C was recently proposed to function as a pan-cancer prognostic marker, bringing FAM46C under the spotlight and attracting growing interest from the scientific community in the pathways modulated by FAM46C and in its mechanistic activity. Here, we will provide the first comprehensive review regarding FAM46C by covering (1) the intracellular pathways regulated by FAM46C, namely the MAPK/ERK, PI3K/AKT, β-catenin and TGF-β/SMAD pathways; (2) the models regarding its mode of action, specifically the poly(A) polymerase, intracellular trafficking modulator and inhibitor of centriole duplication models, focusing on connections and interdependencies; (3) the regulation of FAM46C expression in different environments by interferons, IL-4, TLR engagement or transcriptional modulators; and, lastly, (4) how FAM46C expression levels associate with increased/decreased tumour cell sensitivity to anticancer agents, such as bortezomib, dexamethasone, lenalidomide, pomalidomide, doxorubicin, melphalan, SK1-I, docetaxel and norcantharidin.
Prognosis and Treatment of Gastric Cancer: A 2024 Update
Authors: Burz Claudia , Pop Vlad , Silaghi Ciprian , Lupan Iulia , Samasca Gabriel
Published: April 2024

Due to the high death rate associated with gastric cancer, a great deal of research has been conducted on this disease. The goal of this paper was to start a trimestral review of 2024 for the year that had just started. The scientific literature from 1 January 2024 was chosen with consideration of the the guidelines of the European Society of Medical Oncology (ESMO), which are updated with new findings but not systematically reviewed annually. We used the search term “gastric cancer” to find the most current publications in the PubMed database related to the prognosis and treatment of gastric cancer. As previously said, the only articles that satisfied the inclusion criteria were those from 2024. Articles with case reports were eliminated since they had nothing to do with our research. The treatment of gastric cancer is the focus of the majority of articles from 2024. The primary research axes include surgery and immunonutrition, immunotherapy and Helicobacter pylori, and therapeutic targets. Patients with GC may experience less psychological, social, and financial hardship if the recently identified markers discovered in circulation are better assessed and validated. This could be achieved by either including the markers in an artificial intelligence-based diagnostic score or by using them in conjunction with traditional diagnostic methods. Due to the rising death rate associated with GC, funding for research into diagnosis, prognosis, therapy, and therapeutic targets is essential.
Immune System Disorder and Cancer-Associated Cachexia
Authors: Zhang Lingbing , Bonomi Philip D.
Published: April 2024

Cancer-associated cachexia (CAC) is a debilitating condition marked by muscle and fat loss, that is unresponsive to nutritional support and contributes significantly to morbidity and mortality in patients with cancer. Immune dysfunction, driven by cytokine imbalance, contributes to CAC progression. This review explores the potential relationship between CAC and anti-cancer immune response in pre-clinical and clinical studies. Pre-clinical studies showcase the involvement of cytokines like IL-1β, IL-6, IL-8, IFN-γ, TNF-α, and TGF-β, in CAC. IL-6 and TNF-α, interacting with muscle and adipose tissues, induce wasting through JAK/STAT and NF-κB pathways. Myeloid-derived suppressor cells (MDSCs) exacerbate CAC by promoting inflammation. Clinical studies confirm elevated pro-inflammatory cytokines (IL-6, IL-8, TNFα) and immune markers like the neutrophil-to-lymphocyte ratio (NLR) in patients with CAC. Thus, immunomodulatory mechanisms involved in CAC may impact the anti-neoplastic immune response. Inhibiting CAC mechanisms could enhance anti-cancer therapies, notably immunotherapy. R-ketorolac, a new immunomodulator, reversed the weight loss and increased survival in mice. Combining these agents with immunotherapy may benefit patients with cancer experiencing CAC. Further research is vital to understand the complex interplay between tumor-induced immune dysregulation and CAC during immunotherapy.
Ex Vivo Confocal Laser Scanning Microscopy in Rare Skin Diseases
Authors: Messner Luis , Deußing Maximilian , Maurer Michaela , Buttgereit Lisa , Stärr Lara , French Lars E. , Hartmann Daniela
Published: April 2024

While ex vivo confocal laser scanning microscopy has previously demonstrated its utility in most common skin diseases, its use in the assessment of dermatological entities with lower incidence remains unexplored in most cases. We therefore aimed to evaluate the diagnostic efficacy of some rare skin tumors as well as a few inflammatory skin diseases, that have not yet been studied in ex vivo confocal laser scanning microscopy. A total of 50 tissue samples comprising 10 healthy controls, 10 basal cell carcinoma, 10 squamous cell carcinoma, and 20 rare skin conditions were imaged using the newest generation ex vivo confocal microscopy (Vivascope 2500 M-G4, Vivascope GmbH, Munich, Germany). Three blinded investigators were asked to identify characteristic features of rare skin disorders and distinguish them from more common skin diseases in the ex vivo confocal microscopy images. Our findings present the capability of ex vivo confocal microscopy to display distinctive morphologic patterns in common and rare skin diseases. As might be expected, we found a strong correlation between imaging experience and diagnostic accuracy. While the imaging inexperienced dermatohistopathologist reached 60% concordance, the imaging-trained dermatologist obtained 88% agreement with dermatohistopathology. The imaging-trained dermatohistopathologist achieved concordance up to 92% with gold-standard dermatohistopathology. This study highlights the potential of ex vivo confocal laser scanning microscopy as a promising adjunct to conventional dermatohistopathology for the early and precise identification of rare dermatological disorders.
The Role of Surgery in Pleural Mesothelioma
Authors: Lapidot Moshe , Sattler Martin
Published: April 2024

Surgery plays a central role in the diagnosis, staging, and management of pleural mesothelioma. Achieving an accurate diagnosis through surgical intervention and identifying the specific histologic subtype is crucial for determining the appropriate course of treatment. The histologic subtype guides decisions regarding the use of chemotherapy, immunotherapy, or multimodality treatment. The goal of surgery as part of multimodality treatment is to accomplish macroscopic complete resection with the eradication of grossly visible and palpable disease. Over the past two decades, many medical centers worldwide have shifted from performing extra-pleural pneumonectomy (EPP) to pleurectomy decortication (PD). This transition is motivated by the lower rates of short-term mortality and morbidity associated with PD and similar or even better long-term survival outcomes, compared to EPP. This review aims to outline the role of surgery in diagnosing, staging, and treating patients with pleural mesothelioma.
Adverse Reactions in Relapsed/Refractory B-Cell Lymphoma Administered with Chimeric Antigen Receptor T Cell Alone or in Combination with Autologous Stem Cell Transplantation
Authors: Lin Haolong , Deng Ting , Jiang Lijun , Meng Fankai , Cao Yang , Zhang Yicheng , Ge Renying , Zhu Xiaojian
Published: April 2024

(1) Background: The combination of CAR-T with ASCT has been observed to enhance the efficacy of CAR-T cell therapy. However, the impact of this combination on adverse reactions is still uncertain. (2) Methods: Between January 2019 and February 2023, 292 patients diagnosed with r/r B-cell lymphoma received either CAR-T therapy alone or in combination with ASCT at our institution. We evaluated the incidence of CRS and CRES and utilized a logistic regression model to identify factors contributing to severe CRS (grade 3–4) and CRES (grade 3–4). (3) Results: The overall incidence of CRS and CRES was 78.9% and 8.2% in 147 patients receiving CAR-T alone, and 95.9% and 15.2% in 145 patients receiving CAR-T combined with ASCT, respectively. The incidence of overall CRS (p < 0.0001) and mild CRS (grade 1–2) (p = 0.021) was elevated in the ASCT combined with CAR-T group. No significant difference was observed in severe CRS and CRES between the groups. Among the 26 cases of lymphoma involving the central nervous system (CNS), 96.2% (25/26) developed CRS (15.4% grade 3–4), and 34.6% (9/26) manifested CRES (7.7% grade 3–4). Female patients had a lower incidence of severe CRS but a higher incidence of severe CRES. Lymphomas with CNS involvement demonstrated a higher risk of CRES compared to those without central involvement. (4) Conclusions: The combination of ASCT with CAR-T demonstrated a preferable option in r/r B-cell lymphoma without an increased incidence of severe CRS and CRES.
C-Reactive Protein Is a Potential Prognostic Marker in Patient with Advanced or Metastatic Urothelial Carcinoma Treated with Enfortumab Vedotin: A Multi-Center Retrospective Study
Authors: Morikawa Toshiharu , Naiki Taku , Sugiyama Yosuke , Naiki-Ito Aya , Nagai Takashi , Etani Toshiki , Iida Keitaro , Isobe Teruki , Noda Yusuke , Shimizu Nobuhiko , Aoki Maria , Gonda Masakazu , Banno Rika , Kubota Hiroki , Ando Ryosuke , Umemoto Yukihiro , Kawai Noriyasu , Yasui Takahiro
Published: April 2024

Background: In the EV-301 trial, enfortumab vedotin prolonged survival in patients with locally advanced or metastatic urothelial carcinoma previously treated with platinum-based therapy and programmed cell death 1/programmed death-ligand 1 inhibitor. However, real-world Asian data are limited, and potential prognostic markers are non-existent. We aimed to investigate potential prognostic markers for enfortumab vedotin therapy in Asian patients. Methods: We retrospectively enrolled 61 Japanese patients treated with enfortumab vedotin therapy at our hospital and affiliated hospitals between January 2019 and September 2023. Results: Enrolled patients (38 men, 23 women; median age 74 [IQR: 68–79] years) had bladder cancer (26 patients) or upper-tract urothelial carcinoma (35 patients). Fifty-four patients reported adverse events (grade >3 in 12). Skin disorders, pruritus, and neuropathy were common adverse effects. The median overall survival was 17.1 months (95% confidence interval: 10.0–not applicable). In multivariate analysis, the C-reactive protein level was an independent marker predicting favorable overall survival with enfortumab vedotin. Patient characteristics did not differ between C-reactive protein-high and -low groups. Conclusions: Our study provides real-world data showing that enfortumab vedotin prolonged survival in Asian patients similar to the EV-301 trial. Additionally, the C-reactive protein level might be considered a prognostic marker of enfortumab vedotin therapy in such patients.
FDG-PET in Chimeric Antigen Receptor T-Cell (CAR T-Cell) Therapy Toxicity: A Systematic Review
Authors: Al-Ibraheem Akram , Abdlkadir Ahmed Saad , Lopci Egesta , Allouzi Sudqi , Paez Diana , Alkuwari Maryam , Makoseh Mohammad , Novruzov Fuad , Usmani Sharjeel , Al-Rabi Kamal , Mansour Asem
Published: April 2024

The utilization of chimeric antigen receptor (CAR) T-cell therapy to target cluster of differentiation (CD)19 in cancer immunotherapy has been a recent and significant advancement. Although this approach is highly specific and selective, it is not without complications. Therefore, a systematic review was conducted to assess the current state of positron emission tomography (PET) in evaluating the adverse effects induced by CAR T-cell therapy. A thorough search of relevant articles was performed in databases such as PubMed, Scopus, and Web of Science up until March 2024. Two reviewers independently selected articles and extracted data, which was then organized and categorized using Microsoft Excel. The risk of bias and methodological quality was assessed. In total, 18 articles were examined, involving a total of 753 patients, in this study. A wide range of utilities were analyzed, including predictive, correlative, and diagnostic utilities. While positive outcomes were observed in all the mentioned areas, quantitative analysis of the included studies was hindered by their heterogeneity and use of varying PET-derived parameters. This study offers a pioneering exploration of this promising field, with the goal of encouraging further and more focused research in upcoming clinical trials.
Phenotype Transformation of PitNETs
Authors: Li Zhenwei , Wu Yinzi , He Guannan , Wang Renzhi , Bao Xinjie
Published: April 2024

Phenotype transformation in pituitary neuroendocrine tumors is a little-known and unpredictable clinical phenomenon. Previous studies have not clearly defined and systematically concluded on the causes of this rare phenomenon. Additionally, the mechanisms of phenotype transformation are not well known. We reviewed cases reported in the literature with the aim of defining phenotype transformation in pituitary neuroendocrine tumors. We present an overview of the wide spectrum of phenotype transformation and its clinical features. We also discuss findings on the potential mechanism of this rare transformation, which may be related to PC1/3, the bioactivity of secretory hormones, gene mutations and the plasticity of pituitary neuroendocrine tumors. Clinicians should be aware of this rare phenomenon and more studies on the underlying mechanisms are required.
Treatment Strategies for Non-Small-Cell Lung Cancer with Comorbid Respiratory Disease; Interstitial Pneumonia, Chronic Obstructive Pulmonary Disease, and Tuberculosis
Authors: Otoshi Ryota , Ikeda Satoshi , Kaneko Taichi , Sagawa Shinobu , Yamada Chieri , Kumagai Kosumi , Moriuchi Asami , Sekine Akimasa , Baba Tomohisa , Ogura Takashi
Published: April 2024

Non-small cell lung cancer (NSCLC) patients are often complicated by other respiratory diseases, including interstitial pneumonia (IP), chronic obstructive pulmonary disease (COPD), and pulmonary tuberculosis (TB), and the management of which can be problematic. NSCLC patients with IP sometimes develop fatal acute exacerbation induced by pharmacotherapy, and the establishment of a safe treatment strategy is desirable. For advanced NSCLC with IP, carboplatin plus nanoparticle albumin-bound paclitaxel is a relatively safe and effective first-line treatment option. Although the safety of immune checkpoint inhibitors (ICIs) for these populations remains controversial, ICIs have the potential to provide long-term survival. The severity of COPD is an important prognostic factor in NSCLC patients. Although COPD complications do not necessarily limit treatment options, it is important to select drugs with fewer side effects on the heart and blood vessels as well as the lungs. Active TB is complicated by 2–5% of NSCLC cases during their disease course. Since pharmacotherapy, especially ICIs, reportedly induces the development of TB, the possibility of developing TB should always be kept in mind during NSCLC treatment. To date, there is no coherent review article on NSCLC with these pulmonary complications. This review article summarizes the current evidence and discusses future prospects for treatment strategies for NSCLC patients complicated with IP, severe COPD, and TB.
Management of High-Risk Neuroblastoma with Soft-Tissue-Only Disease in the Era of Anti-GD2 Immunotherapy
Authors: Gorostegui Maite , Muñoz Juan Pablo , Perez-Jaume Sara , Simao-Rafael Margarida , Larrosa Cristina , Garraus Moira , Salvador Noelia , Lavarino Cinzia , Krauel Lucas , Mañe Salvador , Castañeda Alicia , Mora Jaume
Published: April 2024

Neuroblastoma presents with two patterns of disease: locoregional or systemic. The poor prognostic risk factors of locoregional neuroblastoma (LR-NB) include age, MYCN or MDM2-CDK4 amplification, 11q, histology, diploidy with ALK or TERT mutations, and ATRX aberrations. Anti-GD2 immunotherapy has significantly improved the outcome of high-risk (HR) NB and is mostly effective against osteomedullary minimal residual disease (MRD), but less so against soft tissue disease. The question is whether adding anti-GD2 monoclonal antibodies (mAbs) benefits patients with HR-NB compounded by only soft tissue. We reviewed 31 patients treated at SJD for HR-NB with no osteomedullary involvement at diagnosis. All tumors had molecular genetic features of HR-NB. The outcome after first-line treatment showed 25 (80.6%) patients achieving CR. Thirteen patients remain in continued CR, median follow-up 3.9 years. We analyzed whether adding anti-GD2 immunotherapy to first-line treatment had any prognostic significance. The EFS analysis using Cox models showed a HR of 0.20, p = 0.0054, and an 80% decrease in the risk of relapse in patients treated with anti-GD2 immunotherapy in the first line. Neither EFS nor OS were significantly different by CR status after first-line treatment. In conclusion, adding treatment with anti-GD2 mAbs at the stage of MRD helps prevent relapse that unequivocally portends poor survival.
High Serum Levels of CCL20 Are Associated with Recurrence and Unfavorable Overall Survival in Advanced Melanoma Patients Receiving Immunotherapy
Authors: Kött Julian , Hoehne Inka Lilott , Heidrich Isabel , Zimmermann Noah , Reese Kim-Lea , Zell Tim , Geidel Glenn , Rünger Alessandra , Schneider Stefan W. , Pantel Klaus , Smit Daniel J. , Gebhardt Christoffer
Published: April 2024

Background: Immune checkpoint inhibition has revolutionized melanoma therapy, but many patients show primary or secondary resistance. Biomarkers are, therefore, urgently required to predict response prior to the initiation of therapy and to monitor disease progression. Methods: In this prospective study, we analyzed the serum C-C motif chemokine ligand 20 (CCL20) concentration using an enzyme-linked immunosorbent assay. Blood was obtained at baseline before the initiation of immunotherapy with anti-PD-1 monotherapy or Nivolumab and Ipilimumab in advanced melanoma patients (stages III and IV) enrolled at the University Medical Center Hamburg-Eppendorf. The CCL20 levels were correlated with clinico-pathological parameters and disease-related outcomes. Results: An increased C-C motif chemokine ligand 20 (CCL20) concentration (≥0.34 pg/mL) at baseline was associated with a significantly impaired progression-free survival (PFS) in the high-CCL20 group (3 months (95% CI: 2–6 months) vs. 11 months (95% CI: 6–26 months)) (p = 0.0033) and could be identified as an independent negative prognostic factor for PFS in univariate (Hazard Ratio (HR): 1.98, 95% CI 1.25–3.12, p = 0.004) and multivariate (HR: 1.99, 95% CI 1.21–3.29, p = 0.007) Cox regression analysis, which was associated with a higher risk than S100 (HR: 1.74). Moreover, high CCL20 levels were associated with impaired overall survival (median OS not reached for low-CCL20 group, p = 0.042) with an HR of 1.85 (95% CI 1.02–3.37, p = 0.043) in univariate analysis similar to the established prognostic marker S100 (HR: 1.99, 95% CI: 1.02–3.88, p = 0.043). Conclusions: CCL20 may represent a novel blood-based biomarker for the prediction of resistance to immunotherapy that can be used in combination with established strong clinical predictors (e.g., ECOG performance score) and laboratory markers (e.g., S100) in advanced melanoma patients. Future prospective randomized trials are needed to establish CCL20 as a liquid biopsy-based biomarker in advanced melanoma.
The Impact of the COVID-19 Pandemic on Time to Treatment in Surgical Oncology: A National Registry Study in The Netherlands
Authors: van Vuren Roos M. G. , Janssen Yester F. , Hogenbirk Rianne N. M. , de Graaff Michelle R. , van den Hoek Rinske , Kruijff Schelto , Heineman David J. , van der Plas Willemijn Y. , Wouters Michel W. J. M.
Published: April 2024

To avoid delay in oncological treatment, a 6-weeks norm for time to treatment has been agreed on in The Netherlands. However, the impact of the COVID-19 pandemic on health systems resulted in reduced capacity for regular surgical care. In this study, we investigated the impact of the COVID-19 pandemic on time to treatment in surgical oncology in The Netherlands. Methods: A population-based analysis of data derived from five surgical audits, including patients who underwent surgery for lung cancer, colorectal cancer, upper gastro-intestinal, and hepato-pancreato-biliary (HPB) malignancies, was performed. The COVID-19 cohort of 2020 was compared to the historic cohorts of 2018 and 2019. Primary endpoints were time to treatment initiation and the proportion of patients whose treatment started within 6 weeks. The secondary objective was to evaluate the differences in characteristics and tumour stage distribution between patients treated before and during the COVID-19 pandemic. Results: A total of 14,567 surgical cancer patients were included in this study, of these 3292 treatments were started during the COVID-19 pandemic. The median time to treatment decreased during the pandemic (26 vs. 27 days, p < 0.001) and the proportion of patients whose treatment started within 6 weeks increased (76% vs. 73%, p < 0.001). In a multivariate logistic regression analysis, adjusting for patient characteristics, no significant difference in post-operative outcomes between patients who started treatment before or after 6 weeks was found. Overall, the number of procedures performed per week decreased by 8.1% during the pandemic. This reduction was most profound for patients with stage I lung carcinoma and colorectal carcinoma. There were fewer patients with pulmonary comorbidities in the pandemic cohort (11% vs. 13%, p = 0.003). Conclusions: Despite pressure on the capacity of the healthcare system during the COVID-19 pandemic, a larger proportion of surgical oncological patients started treatment within six weeks, possibly due to prioritisation of cancer care and reductions in elective procedures. However, during the pandemic, a decrease in the number of surgical oncological procedures performed in The Netherlands was observed, especially for patients with stage I disease.
Large-Scale and Simple Synthesis of NiFe(OH)x Electrode Derived from Raney Ni Precursor for Efficient Alkaline Water Electrolyzer
Authors: Li Tianshui , Liu Wei , Xin Huijun , Sha Qihao , Xu Haijun , Kuang Yun , Sun Xiaoming
Published: April 2024

Water electrolysis is a crucial technology in the production of hydrogen energy. Due to the escalating industrial demand for green hydrogen, the required electrode size for a traditional alkaline water electrolyzer has been increasing. Numerous studies have focused on developing highly active oxygen evolution reaction (OER) catalysts for water electrolysis. However, there remains a significant gap between the microscale synthesis of catalysts in laboratory settings and the macroscale preparation required for industrial scenarios. This challenge is particularly pronounced in the synthesis of sizable self-supported electrodes. In this work, we employed a commercially available Raney Ni-coated Ni mesh as a precursor material to fabricate a self-supported NiFe(OH)x@Raney Ni anode with a substantial dimension exceeding 300 mm through a straightforward immersion technique. The as-prepared electrode exhibited remarkable electrocatalytic OER activity, as an overpotential of only 240 mV is required to achieve 10 mA cm−2. This performance is comparable to that of NiFe-LDHs synthesized via a hydrothermal method, which is difficult to scale up for industrial applications. Furthermore, the electrode demonstrated exceptional durability, maintaining stable operation for over 100 h at a current density of 500 mA cm−2. The large-scale electrode displayed consistent overpotentials across various areas, indicating uniform catalytic activity. When integrated into an alkaline water electrolysis device, it delivered an average cell voltage of 1.80 V at 200 mA cm−2 and achieved a direct current hydrogen production energy consumption as low as 4.3 kWh/Nm3. These findings underline the suitability of electrodes for industrial scale applications, offering a promising alternative for energy-efficient hydrogen production.
Catalytic Hydrogenation of γ-Butyrolactone to Butanediol over a High-Performance Cu-SiO2 Catalyst
Authors: Ren Xiaoni , Zhou Mo , Yu Wenguang , Zheng Mingyuan , An Qingda
Published: April 2024

High-performance Cu catalysts were developed for the selective hydrogenation of γ-butyrolactone (GBL) to 1,4-butanediol (BDO). Among the various catalysts prepared by ammonia evaporation (AE) and impregnation (IM) methods with silica or MFI zeolite supports, the 5% Cu-SiO2-AE catalyst was the best one. It exhibited 95% selectivity for BDO and 71% conversion of GBL after 2–8 h reaction at 200 °C and 4 MPa H2, with high stability in five-cycle runs. Comprehensive characterizations showed that the AE method favored generating nano Cu particles with an average size of 2.9 nm on the 5% Cu-SiO2-AE catalyst. The silica support derived from a sol demonstrated an advantage over the MFI zeolite in the preparation of a highly dispersed and stable Cu catalyst, in view of its anti-sintering and robust composition of Cu0, Cu+, and Cu2+ in the cycling operation. The reaction pathways for GBL to BDO over the Cu catalysts were found to commonly involve reversible reactions of hydrogenation and dehydrogenation, along with subsequent dehydration to form THF. The high performance of the Cu catalysts in the conversion of GBL to BDO was attributed to the high dispersion of Cu, the presence of stable active sites, and fewer strong acid sites in the catalyst.
Participatory System Mapping for Food Systems: Lessons Learned from a Case Study of Comox Valley, Canada
Authors: Ghadiri Mohaddese , Newell Robert , Krawchenko Tamara
Published: April 2024

Food systems are complex and multifaceted, comprising a diverse range of actors, processes, and interactions. Participatory system mapping can be employed to help understand this complexity and support the development of sustainable and resilient food systems. This article shares a participatory mapping approach that has been developed as part of the Climate–Biodiversity–Health (CBH) Nexus project in the Comox Valley, British Columbia, Canada. This research pursues two main aims: (1) to ground truth in the CBH system map of food systems, developed with the participation of stakeholders; and (2) to explain how participatory system mapping can be employed to clarify the complexity of food systems in a clear and concise manner for all stakeholders. This research contributes to the literature on participatory system mapping, including critiques of its practical utility, by employing participatory approaches to visualize multi-dimensional and multi-level system maps with an emphasis on verifying that they are clear, understandable/useful, and reliable for diverse stakeholder audiences.
The Impact of Utilizing Waste Sunflower Oil as a Biodiesel Blend on Four-Stroke Engine Performance and Emissions
Authors: Hassan Qais Hussein , Araibi Alaa Salahuddin , Shather Akram Hatem , Mohammed Malik Mustafa , Alalwan Hayder Abdulkhaleq
Published: April 2024

The blending of biodiesel with petroleum diesel attracts much attention due to its high potential in reducing emissions. In this work, waste sunflower oil was converted to biodiesel by the trans-esterification method, and it was blended with petroleum diesel in three ratios (10, 30, and 50%). The impact of using these blended fuels in a four-stroke engine on engine performance and exhaust emissions at three engine loads (2, 4, and 6 N.m) was investigated and compared with the use of petroleum diesel and biodiesel. The engine performance was evaluated by determining the brake-specific fuel consumption (BSFC), engine effective power (Ne), brake-specific energy consumption (BSEC), brake thermal efficiency (BTE), and noise intensity. The evaluation of emissions from the engine exhaust was carried out by measuring the levels of carbon oxides (CO and CO2), hydrocarbons (HC), nitrogen oxides (NO and NO2), and particulate matter (PM). The results show that blending diesel with up to 30% biodiesel can reduce CO, HC, and PM emissions by 29.6 ± 1%, 26.0 ± 4%, and 31.0 ± 3%, respectively. However, this decrease is associated with increasing CO2 and NOx emissions by 18.5 ± 2.5% and 29.0 ± 6%, respectively. In addition, the engine showed acceptable performance when using up to 30% biodiesel, where the increase in fuel consumption was limited to 5.8 ± 0.3%. In addition, the engine’s effective power increased with the blending ratio of 10% by 2.0 ± 0.6%, but then decreased with the blending ratio of 30% by only 2.0 ± 0.6%. The noise intensity was also decreased by 2.4%, while BSEC and BTE were reduced by only 2.9 ± 0.9% and 3.5 ± 1%, respectively. The results of this work provide deep insights regarding the utilization of waste sunflower oil as biodiesel to be blended with petroleum diesel, which is a considerable novel approach in the energy and environmental sectors.
Manipulating Camera Gimbal Positioning by Deep Deterministic Policy Gradient Reinforcement Learning for Drone Object Detection
Authors: Ma Ming-You , Huang Yu-Hsiang , Shen Shang-En , Huang Yi-Cheng
Published: April 2024

The object recognition technology of unmanned aerial vehicles (UAVs) equipped with “You Only Look Once” (YOLO) has been validated in actual flights. However, here, the challenge lies in efficiently utilizing camera gimbal control technology to swiftly capture images of YOLO-identified target objects in aerial search missions. Enhancing the UAV’s energy efficiency and search effectiveness is imperative. This study aims to establish a simulation environment by employing the Unity simulation software for target tracking by controlling the gimbal. This approach involves the development of deep deterministic policy-gradient (DDPG) reinforcement-learning techniques to train the gimbal in executing effective tracking actions. The outcomes of the simulations indicate that when actions are appropriately rewarded or penalized in the form of scores, the reward value can be consistently converged within the range of 19–35. This convergence implies that a successful strategy leads to consistently high rewards. Consequently, a refined set of training procedures is devised, enabling the gimbal to accurately track the target. Moreover, this strategy minimizes unnecessary tracking actions, thus enhancing tracking efficiency. Numerous benefits arise from training in a simulated environment. For instance, the training in this simulated environment is facilitated through a dataset composed of actual flight photographs. Furthermore, offline operations can be conducted at any given time without any constraint of time and space. Thus, this approach effectively enables the training and enhancement of the gimbal’s action strategies. The findings of this study demonstrate that a coherent set of action strategies can be proficiently cultivated by employing DDPG reinforcement learning. Furthermore, these strategies empower the UAV’s gimbal to rapidly and precisely track designated targets. Therefore, this approach provides both convenience and opportunities to gather more flight-scenario training data in the future. This gathering of data will lead to immediate training opportunities and help improve the system’s energy consumption.
Integration of UAV Digital Surface Model and HEC-HMS Hydrological Model System in iRIC Hydrological Simulation—A Case Study of Wu River
Authors: Huang Yen-Po , Tsai Hui-Ping , Chiang Li-Chi
Published: April 2024

This research investigates flood susceptibility in the mid- and downstream areas of Taiwan’s Wu River, historically prone to flooding in central Taiwan. The study integrates the Hydrologic Engineering Center—Hydrologic Modeling System (HEC-HMS) for flow simulations with unmanned aerial vehicle (UAV)-derived digital surface models (DSMs) at varying resolutions. Flood simulations, executed through the International River Interface Cooperative (iRIC), assess flood depths using diverse DSM resolutions. Notably, HEC-HMS simulations exhibit commendable Nash–Sutcliffe efficiency (NSE) exceeding 0.88 and a peak flow percentage error (PEPF) below 5%, indicating excellent suitability. In iRIC flood simulations, optimal results emerge with a 2 m resolution UAV-DSM. Furthermore, the study incorporates rainfall data at different recurrence intervals in iRIC flood simulations, presenting an alternative flood modeling approach. This research underscores the efficacy of integrating UAV-DSM into iRIC flood simulations, enabling precise flood depth assessment and risk analysis for flood control management.
The Nexus between Oil Consumption, Economic Growth, and Crude Oil Prices in Saudi Arabia
Authors: Alkofahi Kolthoom , Bousrih Jihen
Published: April 2024

The energy revolution in Saudi Arabia has accelerated significantly since 2016, driven by the National Vision 2030. Significant changes to energy subsidies took place, and the renewable energy sector has seen rapid growth. The paper presents an empirical analysis of the Saudi energy transition by emphasizing the drivers of fuel consumption in KSA. It primarily attempts to explore the long-run (LR) connection between oil consumption and several economic variables such as economic growth, crude oil prices, investment, and the labor force in Saudi Arabia (KSA) from 1991 up to 2021. The paper implemented the vector error correction model (VECM) and performed different diagnostic tests to provide more evidence about the validity and robustness of the tests. The empirical findings highlighted how important the labor force, savings, GDP, and crude oil price are in determining oil consumption for KSA. The law of demand is significantly present, which negatively affects oil consumption for KSA as an oil exporting country. The results also supported the existence of a long-term direct correlation between the variables and oil consumption. Furthermore, the short-term estimation highlighted that only saving has a negative impact on oil consumption for a single lagged period. Our findings provide governments and regulators with further incentive to slow the expansion in oil consumption, as a larger labor force is demanding more oil to attain the target, faster economic growth, and increased savings are all contributing factors. Our findings are significant because they can assist policymakers, investors, and regulators in generating more efficient oil substitutes and making them affordable for the economy.
Characterization of Unit Cells of a Reconfigurable Intelligence Surface Integrated with Sensing Capability at the mmWave Frequency Band
Authors: Rana Biswarup , Cho Sung-Sil , Hong Ic-Pyo
Published: April 2024

Integrated sensing and communication (ISAC) is emerging as a main feature for 5G/6G communications. To enhance spectral and energy efficiencies in wireless environments, reconfigurable intelligent surfaces (RISs) will play a significant role in beyond-5G/6G communications. Multi-functional RISs, capable of not only reflecting or transmitting the beam in desired directions but also sensing the signal, wirelessly transferring power to nearby devices, harvesting energy, etc., will be highly beneficial for beyond-5G/6G applications. In this paper, we propose a nearly 2-bit unit cell of RISs integrated with sensing capabilities in the millimeter wave (mmWave) frequency band. To collect a very small fraction of the impinging signals through vias, we employed substrate integrated waveguide (SIW) technology at the bottom of the unit cell and a via. This enabled the sensing of incoming signals, requiring only a small amount of the impinging signal to be collected through SIW. Initially, we utilized Floquet ports and boundary conditions to obtain various parameters of the unit cells. Subsequently, we examined 1 × 3-unit cells, placing them on the waveguide model to obtain the required parameters of the unit cell. By using the waveguide and 1 × 3-unit cell arrays, the sensing amount was also determined.
ML-Based Software Defect Prediction in Embedded Software for Telecommunication Systems (Focusing on the Case of SAMSUNG ELECTRONICS)
Authors: Kang Hongkoo , Do Sungryong
Published: April 2024

Software stands out as one of the most rapidly evolving technologies in the present era, characterized by its swift expansion in both scale and complexity, which leads to challenges in quality assurance. Software defect prediction (SDP) has emerged as a methodology crafted to anticipate undiscovered defects, leveraging known defect data from existing codes. This methodology serves to facilitate software quality management, thereby ensuring overall product quality. The methodologies of machine learning (ML) and one of its branches, deep learning (DL), exhibit superior accuracy and adaptability compared to traditional statistical approaches, catalyzing active research in this domain. However, it makes it hard to generalize, not only because of the disparity between open-source projects and commercial projects but also due to the differences in each industrial sector. Consequently, further research utilizing datasets sourced from diverse real-world sectors has become imperative to bolster the applicability of these findings. For this study, we utilized embedded software for use with the telecommunication systems of Samsung Electronics, supplemented by the introduction of nine novel features to train the model, and a subsequent analysis of the results ensued. The experimental outcomes revealed that the F-measurement metric has been enhanced from 0.58 to 0.63 upon integration of the new features, thereby signifying a performance augmentation of 8.62%. This case study is anticipated to contribute to bolstering the application of SDP methodologies within analogous industrial sectors.
Function-Level Compilation Provenance Identification with Multi-Faceted Neural Feature Distillation and Fusion
Authors: Gao Yang , Liang Lunjin , Li Yifei , Li Rui , Wang Yu
Published: April 2024

In the landscape of software development, the selection of compilation tools and settings plays a pivotal role in the creation of executable binaries. This diversity, while beneficial, introduces significant challenges for reverse engineers and security analysts in deciphering the compilation provenance of binary code. To this end, we present MulCPI, short for Multi-representation Fusion-based Compilation Provenance Identification, which integrates the features collected from multiple distinct intermediate representations of the binary code for better discernment of the fine-grained function-level compilation details. In particular, we devise a novel graph-oriented neural encoder improved upon the gated graph neural network by subtly introducing an attention mechanism into the neighborhood nodes’ information aggregation computation, in order to better distill the more informative features from the attributed control flow graph. By further integrating the features collected from the normalized assembly sequence with an advanced Transformer encoder, MulCPI is capable of capturing a more comprehensive set of features manifesting the multi-faceted lexical, syntactic, and structural insights of the binary code. Extensive evaluation on a public dataset comprising 854,858 unique functions demonstrates that MulCPI exceeds the performance of current leading methods in identifying the compiler family, optimization level, compiler version, and the combination of compilation settings. It achieves average accuracy rates of 99.3%, 96.4%, 90.7%, and 85.3% on these tasks, respectively. Additionally, an ablation study highlights the significance of MulCPI’s core designs, validating the efficiency of the proposed attention-enhanced gated graph neural network encoder and the advantages of incorporating multiple code representations.
Blood Cell Attribute Classification Algorithm Based on Partial Label Learning
Authors: Feng Junxin , Guo Qianhang , Luo Shiling , Chen Letao , Ma Qiongxiong
Published: April 2024

Hematological morphology examinations, essential for diagnosing blood disorders, increasingly utilize deep learning. Blood cell classification, determined by combinations of cell attributes, is complicated by the complex relationships and subtle differences among the attributes, resulting in significant time and cost penalties. This study introduces the Partial Label Learning for Blood Cell Classification (P4BC) strategy, a method that trains neural networks using the blood cell attribute labeling data of weak annotations. Using morphological knowledge, we predefined candidate label sets for the blood cell attributes to blend this knowledge with deep learning. This improves the model’s prediction accuracy and interpretability in classifying attributes. This method effectively combines morphological knowledge with deep learning, an approach we refer to as knowledge alignment. It results in an 8.66% increase in attribute recognition accuracy and a 1.09% improvement in matching predictions to the candidate label sets, compared to the original method. These results confirm our method’s ability to grasp the characteristic information of blood cell attributes, enhancing the model interpretability and achieving knowledge alignment between hematological morphology and deep learning. Our algorithm ensures attribute classification accuracy and shows excellent cell category classification, highlighting its wide application potential and practical value in blood cell category classification.
OpenWeedGUI: An Open-Source Graphical Tool for Weed Imaging and YOLO-Based Weed Detection
Authors: Xu Jiajun , Lu Yuzhen , Deng Boyang
Published: April 2024

Weed management impacts crop yield and quality. Machine vision technology is crucial to the realization of site-specific precision weeding for sustainable crop production. Progress has been made in developing computer vision algorithms, machine learning models, and datasets for weed recognition, but there has been a lack of open-source, publicly available software tools that link imaging hardware and offline trained models for system prototyping and evaluation, hindering community-wise development efforts. Graphical user interfaces (GUIs) are among such tools that can integrate hardware, data, and models to accelerate the deployment and adoption of machine vision-based weeding technology. This study introduces a novel GUI called OpenWeedGUI, designed for the ease of acquiring images and deploying YOLO (You Only Look Once) models for real-time weed detection, bridging the gap between machine vision and artificial intelligence (AI) technologies and users. The GUI was created in the framework of PyQt with the aid of open-source libraries for image collection, transformation, weed detection, and visualization. It consists of various functional modules for flexible user controls and a live display window for visualizing weed imagery and detection. Notably, it supports the deployment of a large suite of 31 different YOLO weed detection models, providing flexibility in model selection. Extensive indoor and field tests demonstrated the competencies of the developed software program. The OpenWeedGUI is expected to be a useful tool for promoting community efforts to advance precision weeding technology.