bluuebunny/crossref_metadata_2025 huggingface dataset:
Protocol for a systematic review with prospective individual patient data meta-analysis in EGFR-mutant NSCLC with brain metastases to assess the effect of SRS+osimertinib compared to osimertinib alone: the STARLET Collaboration
Authors: Robledo Kristy P , Lefresne Shilo , Soon Yu Yang , Sahgal Arjun , Pinkham Mark B , Nichol Alan , Soo Ross Andrew , Parmar Ambika , Hegi-Johnson Fiona , Doherty Mark , Solomon Benjamin J , Shultz David B , Tham Ivan WK , Sacher Adrian G , Tey Jeremy , Leong Cheng Nang , Koh Wee Yao , Huang Yiqing , Ang Yvonne Li En , Low Jiali , Yong Clement , Lim Mei Chin , Tan Ai Peng , Lee Chee Khoon , Ho Cheryl
Published: July 2024

Background

Patients with advanced non-small-cell lung cancer (NSCLC) with activating mutations in the epidermal growth factor receptor (EGFR) gene are a heterogeneous population who often develop brain metastases (BM). The optimal management of patients with asymptomatic brain metastases is unclear given the activity of newer-generation targeted therapies in the central nervous system. We present a protocol for an individual patient data (IPD) prospective meta-analysis to evaluate whether the addition of stereotactic radiosurgery (SRS) before osimertinib treatment will lead to better control of intracranial metastatic disease. This is a clinically relevant question that will inform practice.

Methods

Randomised controlled trials will be eligible if they include participants with BM arising fromEGFR-mutant NSCLC and suitable to receive osimertinib both in the first-line and second-line settings (P); comparisons of SRS followed by osimertinib versus osimertinib alone (I, C) and intracranial disease control included as an endpoint (O). Systematic searches of Medline (Ovid), Embase (Ovid), Cochrane Central Register of Controlled Trials (CENTRAL), CINAHL (EBSCO), PsychInfo, ClinicalTrials.gov and the WHO’s International Clinical Trials Registry Platform’s Search Portal will be undertaken. An IPD meta-analysis will be performed using methodologies recommended by the Cochrane Collaboration. The primary outcome is intracranial progression-free survival, as determined by response assessment in neuro-oncology-BM criteria. Secondary outcomes include overall survival, time to whole brain radiotherapy, quality of life, and adverse events of special interest. Effect differences will be explored among prespecified subgroups.

Ethics and dissemination

Approved by each trial’s ethics committee. Results will be relevant to clinicians, researchers, policymakers and patients, and will be disseminated via publications, presentations and media releases.

Prospero registration

CRD42022330532.
Effect of occupational stress and resilience on insomnia among nurses during COVID-19 in China: a structural equation modelling analysis
Authors: Cao Qiyuan , Wu Huiyi , Tang Xiumei , Zhang Qin , Zhang Yang
Published: July 2024

Objectives

To explore the effects of occupational stress and resilience on insomnia among Chinese nurses during the COVID-19 pandemic.

Design, settings and participants

A quantitative description study. The data were collected via a cross-sectional survey. A total of 725 front-line nurses at three tertiary hospitals in western China were included from December 2022 to January 2023. The Connor-Davidson Resilience Scale, Job Content Questionnaire, and Athens Insomnia Scale were used to collect data from a self-reported online questionnaire.

Outcome measures

The outcome variable was insomnia, and structural equation modelling was used to assess the associations among resilience, occupational stress and insomnia.

Results

The prevalence of insomnia among the participants was 58.76%. The structural equation model showed that resilience had a negative direct effect on insomnia and occupational stress, and occupational stress had a positive direct effect on insomnia. Involvement in COVID-19-related work has a positive effect on insomnia through occupational stress. In contrast, higher education levels improved insomnia through increased resilience.

Conclusion

A significantly higher prevalence of insomnia has been observed among Chinese nurses during the COVID-19 pandemic. Our study suggests that better resilience may improve insomnia by relieving occupational stress, and implementing measures to promote resilience is essential to reduce occupational stress in nurses and improve their sleep quality.
Vascular access specialist teams versus standard practice for catheter insertion and prevention of failure: a systematic review
Authors: Fernandez-Fernandez Ismael , Parra-García Gaizka , Blanco-Mavillard Ian , Carr Peter , Santos-Costa Paulo , Rodríguez-Calero Miguel Ángel
Published: July 2024

Objective

Billions of vascular access devices (VADs) are inserted annually for intravenous therapy worldwide. However, their use is not without challenges. Facilitating the process and enhancing results, hospital authorities have created vascular access specialist teams (VASTs) with advanced competencies in the evaluation, insertion, care and management of VADs. The objective is to compare the effectiveness of VASTs versus standard practice regarding cannulation success and vascular access maintenance in hospitalised adults.

Design

Systematic review, using the Mixed Methods Appraisal Tool.

Data sources

We conducted a structured data search on Cochrane Library, MEDLINE, Web of Science, Scopus and EBSCOhost up to 31 May 2023. We did not impose a time limit regarding the date of publication.

Eligibility criteria

Studies were eligible for inclusion in the review if they were randomised and non-randomised trials and observational studies.

Data extraction and synthesis

We included studies that described or evaluated the activity of VASTs compared with clinical practitioners. The outcomes analysed were the success of the cannulation and the incidence of associated adverse effects.

Results

The search strategy produced 3053 papers published between 1984 and 2020, from which 12 were selected for analysis. VASTs are heterogeneously described among these studies, which mainly focus on insertions, frequently for patients with difficult intravenous access. Some patients presented with specific needs or requirement for specific insertion technique or catheter type. Compared with usual practice, these studies indicate that the involvement of a VAST is associated with a higher effectiveness in terms of first attempt insertions and insertion success rates, and a reduction in catheter-associated adverse events. However, meta-analyses confirming this trend are not currently possible.

Conclusions

It seems apparent that VASTS contribute to improving the health of patients during the administration of intravenous. VASTs seem to increase the effectiveness of VAD insertion and care and reduce complications.

PROSPERO registration number

CRD42021231259.
Microbial keratitis in the subtropical region of Korea: a comprehensive 12-year retrospective review at a single referral center
Authors: Ji Man , Park Joong Hyun , Ha Ahnul , Jeong Jinho
Published: July 2024

Objectives

To investigate the epidemiological characteristics and clinical outcomes of culture-proven bacterial and fungal keratitis at a single tertiary referral centre on Jeju Island, South Korea.

Design

A retrospective study design.

Setting

Data from a solitary referral centre on Jeju Island spanning January 2011 to December 2022.

Participants

Among the 245 patients clinically diagnosed with infectious microbial keratitis, 110 individuals had culture-positive results.

Primary and secondary outcome measures

The primary outcome was the identification of causative microbial profiles and epidemiological characteristics, while the secondary outcome was the correlation of these factors with treatment outcomes.

Results

Of 245 patients, 110 (44.9%) had culture-positive infectious keratitis, showing 69 bacterial, 32 fungal, 4 superimposed bacterial and 5 cases with coinfection by bacteria and fungus. The most common pathogen wasPseudomonasspecies in 14.4% of the bacterial keratitis cases, followed byStaphylococcus epidermidis(9%),Staphylococcus aureus(8%) and Moraxella species (7%). The total treatment success rate for bacterial keratitis was 67.5%. The frequency of methicillin-resistantStaphylococcuson Jeju Island did increase during the study period. Fusarium species had the highest incidence at 22.2%, followed byCandida(16.7%) andColletotrichumspecies (11.1%). 56.7% of fungal keratitis patients were successfully treated. An initial large corneal lesion (>3 mm) showed a statistically significant association with treatment failure.

Conclusion

The incidence ofMoraxellaandColletotrichumspecies in our study was higher than that reported in other districts with different climates and environments. The results reported here reflect the unique environmental features of Jeju Island, characterised by high humidity and temperatures.
Development and external validation of machine learning-based models to predict patients with cellulitis developing sepsis during hospitalisation
Authors: Chen Xilingyuan , Hu Li , Yu Rentao
Published: July 2024

Objective

Cellulitis is the most common cause of skin-related hospitalisations, and the mortality of patients with sepsis remains high. Some stratification models have been developed, but their performance in external validation has been unsatisfactory. This study was designed to develop and compare different models for predicting patients with cellulitis developing sepsis during hospitalisation.

Design

This is a retrospective cohort study.

Setting

This study included both the development and the external-validation phases from two independent large cohorts internationally.

Participants and methods

A total of 6695 patients with cellulitis in the Medical Information Mart for Intensive care (MIMIC)-IV database were used to develop models with different machine-learning algorithms. The best models were selected and then externally validated in 2506 patients with cellulitis from the YiduCloud database of our university. The performances and robustness of selected models were further compared in the external-validation group by area under the curve (AUC), diagnostic accuracy, sensitivity, specificity and diagnostic OR.

Primary outcome measures

The primary outcome of interest in this study was the development based on the Sepsis-3.0 criteria during hospitalisation.

Results

Patient characteristics were significantly different between the two groups. In internal validation, XGBoost was the best model, with an AUC of 0.780, and AdaBoost was the worst model, with an AUC of 0.585. In external validation, the AUC of the artificial neural network (ANN) model was the highest, 0.830, while the AUC of the logistic regression (LR) model was the lowest, 0.792. The AUC values changed less in the boosting and ANN models than in the LR model when variables were deleted.

Conclusions

Boosting and neural network models performed slightly better than the LR model and were more robust in complex clinical situations. The results could provide a tool for clinicians to detect hospitalised patients with cellulitis developing sepsis early.
Infliximab in steroid-refractory immune-related hepatitis does not demonstrate hepatotoxicity and may shorten time on steroids
Authors: Burri Elias , Mangana Joanna , Cheng Phil F , Schneider Alia , Weber Achim , Dummer Reinhard , Ramelyte Egle
Published: July 2024

Background

Immune-related hepatitis (irHepatitis) is a relatively common immune-related adverse event (irAE) of checkpoint inhibitors. Often, it responds well to steroids; however, in refractory cases, further therapy is needed. Anti-tumor necrosis factor (TNF) antibodies are used for management of multiple irAEs, but there are little data in irHepatitis. Here, we report on safety and efficacy of infliximab in 10 cases of steroid-refractory irHepatitis.

Methods

We retrospectively reviewed patients treated with infliximab for steroid-refractory grade ≥3 irHepatitis at the Department of Dermatology, University Hospital Zurich. The positive response to infliximab was defined as no further increase in alanine aminotransferase (ALT)/aspartate aminotransferase (AST) above 50% than at the time of first infliximab infusion and control of irHepatitis without therapies other than steroids and infliximab.

Results

10 patients with steroid-resistant irHepatitis grade ≥3 were treated with infliximab 5 mg/kg, of whom 7 (70%) responded positively. In two cases, the liver values increased over 50% before the irHepatitis could be controlled. In another case, therapies other than infliximab and steroids were given. At the median follow-up of 487 days, 90% of the patients demonstrated resolved irHepatitis without AST/ALT elevation following infliximab infusions.

Conclusions

Treatment of irHepatitis with infliximab did not result in hepatotoxicity and led to long-lasting positive response in 9 of 10 of the cases. Further research is needed to evaluate the role of anti-TNF antibodies in management of irHepatitis.
TCF1-positive and TCF1-negative TRM CD8 T cell subsets and cDC1s orchestrate melanoma protection and immunotherapy response
Authors: De León-Rodríguez Saraí G , Aguilar-Flores Cristina , Gajón Julián A , Juárez-Flores Ángel , Mantilla Alejandra , Gerson-Cwilich Raquel , Martínez-Herrera José Fabián , Villegas-Osorno Diana Alejandra , Gutiérrez-Quiroz Claudia T , Buenaventura-Cisneros Sergio , Sánchez-Prieto Mario Alberto , Castelán-Maldonado Edmundo , Rivera Rivera Samuel , Fuentes-Pananá Ezequiel M , Bonifaz Laura C
Published: July 2024

Background

Melanoma, the most lethal form of skin cancer, has undergone a transformative treatment shift with the advent of checkpoint blockade immunotherapy (CBI). Understanding the intricate network of immune cells infiltrating the tumor and orchestrating the control of melanoma cells and the response to CBI is currently of utmost importance. There is evidence underscoring the significance of tissue-resident memory (TRM) CD8 T cells and classic dendritic cell type 1 (cDC1) in cancer protection. Transcriptomic studies also support the existence of aTCF7+ (encoding TCF1) T cell as the most important for immunotherapy response, although uncertainty exists about whether there is a TCF1+TRM T cell due to evidence indicating TCF1 downregulation for tissue residency activation.

Methods

We used multiplexed immunofluorescence and spectral flow cytometry to evaluate TRM CD8 T cells and cDC1 in two melanoma patient cohorts: one immunotherapy-naive and the other receiving immunotherapy. The first cohort was divided between patients free of disease or with metastasis 2 years postdiagnosis while the second between CBI responders and non-responders.

Results

Our study identifies two CD8+TRM subsets, TCF1+ and TCF1−, correlating with melanoma protection. TCF1+TRM cells show heightened expression of IFN-γ and Ki67 while TCF1− TRM cells exhibit increased expression of cytotoxic molecules. In metastatic patients, TRM subsets undergo a shift in marker expression, with the TCF1− subset displaying increased expression of exhaustion markers. We observed a close spatial correlation between cDC1s and TRMs, with TCF1+TRM/cDC1 pairs enriched in the stroma and TCF1− TRM/cDC1 pairs in tumor areas. Notably, these TCF1− TRMs express cytotoxic molecules and are associated with apoptotic melanoma cells. Both TCF1+ and TCF1− TRM subsets, alongside cDC1, prove relevant to CBI response.

Conclusions

Our study supports the importance of TRM CD8 T cells and cDC1 in melanoma protection while also highlighting the existence of functionally distinctive TCF1+ and TCF1− TRM subsets, both crucial for melanoma control and CBI response.
Using microfluidic shear to assess transfusion requirements in trauma patients
Authors: Vuoncino Leslie H , Robles Anamaria J , Barnes Ashli C , Ross James T , Graeff Leonardo W , Anway Taylor L , Vincent Nico T , Tippireddy Nithya , Tanaka Kimi M , Mays Randi J , Callcut Rachael A
Published: July 2024

Background

Viscoelastic assays have widely been used for evaluating coagulopathies but lack the addition of shear stress important toin vivoclot formation. Stasys technology subjects whole blood to shear forces over factor-coated surfaces. Microclot formation is analyzed to determine clot area (CA) and platelet contractile forces (PCFs). We hypothesize the CA and PCF from this novel assay will provide information that correlates with trauma-induced coagulopathy and transfusion requirements.

Methods

Blood samples were collected on adult trauma patients from a single-institution prospective cohort study of high-level activations. Patient and injury characteristics, transfusion data, and outcomes were collected. Thromboelastography, coagulation studies, and Stasys assays were run on paired samples collected at admission. Stasys CA and PCFs were quantified as area under the curve calculations and maximum values. Normal ranges for Stasys assays were determined using healthy donors. Data were compared using Kruskal-Wallis tests and simple linear regression.

Results

From March 2021 to January 2023, 108 samples were obtained. Median age was 37.5 (IQR 27.5–52) years; patients were 77% male. 71% suffered blunt trauma, 26% had an Injury Severity Score of ≥25. An elevated international normalized ratio significantly correlated with decreased cumulative PCF (p=0.05), maximum PCF (p=0.05) and CA (p=0.02). Lower cumulative PCF significantly correlated with transfusion of any products at 6 and 24 hours (p=0.04 and p=0.05) as well as packed red blood cells (pRBCs) at 6 and 24 hours (p=0.04 and p=0.03). A decreased maximum PCF showed significant correlation with receiving any transfusion at 6 (p=0.04) and 24 hours (p=0.02) as well as transfusion of pRBCs, fresh frozen plasma, and platelets in the first 6 hours (p=0.03, p=0.03, p=0.03, respectively).

Conclusions

Assessing coagulopathy in real time remains challenging in trauma patients. In this pilot study, we demonstrated that microfluidic approaches incorporating shear stress could predict transfusion requirements at time of admission as well as requirements in the first 24 hours.

Level of evidence

Level II.
A comprehensive forecast for cosmological parameter estimation using joint observations of gravitational waves and short $$\gamma $$-ray bursts
Authors: Han Tao , Jin Shang-Jie , Zhang Jing-Fei , Zhang Xin
Published: July 2024

In the third-generation (3G) gravitational-wave (GW) detector era, multi-messenger GW observation for binary neutron star (BNS) merger events can exert great impacts on exploring cosmic expansion history. In this work, we comprehensively explore the potential of 3G GW standard siren observations in cosmological parameter estimations by considering 3G GW detectors and the future short $$\gamma $$
γ
-ray burst (GRB) detector THESEUS-like telescope joint observations. Based on a 10-year observation of different detection strategies, we predict that the numbers of detectable GW-GRB events are 334–674 with the redshifts $$z<3.5$$

z
<
3.5

and the inclination angles $$\iota <15^{\circ }$$

ι
<

15
∘

. For the cosmological analysis, we consider the $$\Lambda $$
Λ
CDM, wCDM, $$w_0w_a$$

w
0

w
a

CDM, and interacting dark energy (IDE) models. We find that GW can tightly constrain the Hubble constant with precision of 0.345–0.065%, but does not perform well in constraining other cosmological parameters. Fortunately, GW detection could effectively break the cosmological parameter degeneracies generated by the mainstream EM observations, CMB + BAO + SN (CBS). When combining mock GW data with CBS data, CBS + GW can tightly constrain the equation of state of dark energy w with a precision of 1.26%, close to the standard of precision cosmology. Meanwhile, the addition of GW to CBS could improve constraints on cosmological parameters by 34.2–94.9%. In conclusion, GW standard siren observations from 3G GW detectors could play a crucial role in helping solve the Hubble tension and probe the fundamental nature of dark energy.
Can the induced increase in the angular velocity prevent the overspinning of BTZ black holes?
Authors: Düztaş Koray
Published: July 2024

Previously we showed that nearly extremal Bañados–Teitelboim–Zanelli (BTZ) black holes can be overspun by test bodies and fields, following the work of Rocha and Cardoso for the extremal case. The naked singularities in AdS space-times correspond to states rotating faster than light in the Ads/CFT correspondence. Therefore, overspinning turns out to be a drastic problem in a (2 + 1) dimensional AdS space-time, where one cannot invoke backreaction effects. Here, we consider the induced increase in the angular velocity of the event horizon which modifies the condition to allow the absorption of the perturbations satisfying the null energy condition. We show that its magnitude is sufficiently large to prevent the absorption of the challenging modes both for test bodies and scalar fields. We bring a solution to the notorious overspinning problem which does not involve any reference to self-energy or gravitational radiation
Accumulated laser-photoneutron generation
Authors: Cohen Itamar , Cohen Tamir , Levinson Aviv , Elkind Michael , Rakovsky Yonatan , Levanon Assaf , Michaeli David , Cohen Erez , Beck Arie , Pomerantz Ishay
Published: July 2024

We present repeated generation of photoneutrons by double-pulse irradiation of ultrathin foils. A ~ mJ prepulse turns a foil into a 100-μm scale plasma plume from which a beam of MeV electrons is generated by the main pulse. Neutrons are generated in a secondary metal target placed downstream to the electron beam. We utilize an automated target system capable of delivering ultrathin foils to the laser focus at an average rate of 0.1 Hz. With 153 consecutive laser shots taken over the course of 24 min, we generated a total 2.6 × 107 neutrons. We present a method for evaluating how the number of photoneutrons scales with the laser intensity in this experimental scenario, which we validate against the measured yields.
The experimental and numerical studies of formation and collapse processes of ventilated supercavitating flow
Authors: Kamali Hossein Ali , Erfanian Mohammad-Reza
Published: July 2024

The aim of this paper is to investigate the ventilated cavitating flow behavior, through experimental and numerical methods. The experiments are performed for a test model placed in a water tunnel and a high-speed camera is used to image the formation and collapse of the supercavity. For the numerical simulations, Ansys CFX commercial software is employed to solve the Reynolds-averaged Navier–Stokes (RANS) equations and additional transport equation for the liquid volume fraction in the unsteady condition. Both the experimental observation and numerical prediction show a hysteresis behavior for ventilated supercavity in which the value of the air entrainment coefficient required to maintain the supercavity in the formation process is less than the amount required to form it. The good agreement observed between the numerical prediction and experimental data, revealed the accuracy and capability of the numerical scheme. Also, the numerical simulation shows that the variations in the supercavity length, in addition to the air entrainment, are a function of the air leakage regime from the closure region of supercavity.
Dynamics of drug trafficking: Results from a simple compartmental model
Authors: Crokidakis Nuno
Published: July 2024

In this work we propose a simple model for the emergence of drug dealers. For this purpose, we built a compartmental model considering four subpopulations, namely susceptibles, passive supporters, drug dealers and arrested drug dealers. The target is to study the influence of the passive supporters on the long-time prevalence of drug dealers. Passive supporters are people who are passively consenting to the drug trafficking cause. First we consider the model on a fully connected network, in such a way that we can write a rate equation for each subpopulation. Our analytical and numerical results show that the emergence of drug dealers is a consequence of the rapid increase in the number of passive supporters. Such increase is associated with a nonequilibrium active-absorbing phase transition. After that, we consider the model on a two-dimensional square lattice, in order to compare the results in the presence of a simple social network with the previous results. The Monte Carlo simulation results suggest a similar behavior in comparison with the fully connected network case, but the location of the critical point of the transition is distinct, due to the neighbors’ correlations introduced by the presence of the lattice.
A numerical investigation of a new horizontal wind turbine performance for rural use
Authors: Akram Adjlout , Omar Ladjedel , Tayeb Yahiaoui , Šikula Ondřej , Omar Imine , Lahouari Adjlout
Published: July 2024

In this paper, a new configuration of a horizontal axis wind turbine with three blades for domestic electricity production on farms was numerically simulated. Three configurations were tested numerically: a standard single-blade wind turbine (STWT), a single wind turbine (SWT), and a tandem three-blade wind turbine (TWT) for rural use. For the tandem wind turbine, the effects of pitch angle and the distance between the blades were also investigated. The Gambit and Fluent 19.2 codes were, respectively, used to generate different meshes and determine various parameters. The resolution of the averaged Navier–Stokes equations (RANS) using a finite volume method was conducted. The k–[Formula: see text] realizable two-equation model was chosen for turbulence calculation. The obtained results showed that the maximum power coefficient (Cp) was 0.444 for one of the tandem configurations (TWT), compared to the conventional blade (STWT). The maximum Cp obtained in this study is slightly greater than the experimental results found in the literature. It has also been observed that the flow on these new turbines exhibits a complex phenomenon on both surfaces.
Hard confinement of a two-particle quantum system using the variational method
Authors: Sabbah Nataly Rafat , Al-Masaeed Mohamed Ghaleb , Al-Jamel Ahmed
Published: July 2024

The variational method is used to study the hard confinement of a two-particle quantum system in two potential models, the Cornell potential and the global potential, with Dirichlet-type boundary conditions at various cut-off radii. The trial wave function is constructed as the product of the [Formula: see text] free hydrogen atom wave function or [Formula: see text] harmonic oscillator wave function times a linear cut-off function of the form [Formula: see text] to ensure hard entrapment within a sphere of radius z. The behavior of [Formula: see text], the wave function at the origin (WFO) and the mean radius [Formula: see text] are computed for different situations and compared for the two potential models.
The virial theorem for nondifferentiable dynamical paths in resolution-scale relativity and possible implications
Authors: LeBohec Tugdual
Published: July 2024

The virial theorem is established in the framework of resolution-scale relativity for stochastic dynamics characterized by a diffusion constant [Formula: see text]. It only relies on a simple time average just like the classical virial theorem, while the quantum mechanical virial theorem involves the expectation values of the observables. Nevertheless, by the emergence of a quantum-like potential term, the resolution-scale relativity virial theorem also encompasses quantum mechanical dynamics under the identification [Formula: see text]. This provides an illustration of the resolution-scale relativistic approach to the foundation of standard quantum mechanics. Furthermore, it is pointed out that if the resolution-scale relativity principle is implemented in macroscopic systems that are complex and/or chaotic, then the application of the classical virial theorem in the analysis of the dynamics of astrophysical systems neglects the contribution from a resolution-scale relativistic quantum-like potential. It is shown that this quantum-like potential could account for some fraction of the dark matter hypothesis.
ShNFN: Shepard Neuro-Fuzzy Network for Intrusion Detection in Fog Computing
Authors: Ganeshan R , Sravani Meesala , Kalidindi Archana , Om Prakash P G
Published: July 2024

Fog computing is a type of distributed computing that makes data storage and computation closer to the network edge. While fog computing offers numerous advantages, it also introduces several challenges, particularly in terms of security. Intrusion Detection System (IDS) plays a crucial role in securing fog computing environments by monitoring network traffic and system activities for signs of malicious behavior. Several techniques can be employed to enhance intrusion detection in fog computing environments. Accordingly, this paper proposes a Shepard Neuro-Fuzzy Network (ShNFN) for intrusion detection in fog computing. Initially, in the cloud layer, the input data are passed to data transformation to transform the unstructured data into structured form. Here, data transformation is done employing the Box-Cox transformation. Following this, the feature selection is done in terms of information gain and symmetric uncertainty process and it is used to create a relationship between two variables. After that, the data are classified by employing the proposed ShNFN. The ShNFN is attained by fusing two networks, such as Cascade Neuro-Fuzzy Network (Cascade NFN) and Shepard Convolutional Neural Networks (ShCNN). After this, the physical process is executed at the endpoint layer. Finally, intrusion detection is accomplished in the fog layer by the proposed ShNFN method. The performance of the intrusion detection using ShNFN is calculated by the metrics of recall, F-measure and precision. The proposed method achieves the values of 93.3%, 92.5% and 94.8% for recall, F-measure, and precision, respectively.
Authenticity Verification of Alcoholic Beverages in IoT Environment through Fluorescence Hyperspectral Technology and Machine Learning
Authors: Zhou Futao , Wu Youli , Zeng Xiaoyong , Zhang Zixi , Wang Silu , Huang Peng , Kang Zhiliang
Published: July 2024

In the Internet of Things (IoT) environment, verifying the authenticity of beverages is an important issue. Baijiu, a unique Chinese distilled liquor, has gained popularity among people due to its distinctive flavor. In recent years, there has been increasing concern about the adulteration of baijiu. Many studies in this field have attempted to combine chemometrics, electronic nose, Raman spectroscopy, and other detection technologies with machine learning for baijiu detection. However, no research has yet applied the mature detection technology of fluorescence hyperspectral technology to this field. Additionally, existing studies have mainly focused on branded baijiu, without addressing the problem of adulteration in bulk baijiu, which remains a long-standing issue. In this study, a combination of fluorescence hyperspectral and machine learning was used for rapid and nondestructive adulteration detection of bulk liquor in Chengdu. The fluorescence hyperspectral data of three types of samples, namely, original liquor, adulterated liquor with water, and adulterated liquor with industrial alcohol, were obtained, and the raw data were preprocessed using Savitzky–Golay (SG), baseline correction (BL), multivariate scatter correction (MSC), and the combination of Savitzky–Golay and baseline correction (SG-BL). Finally, PCA and MDS are also used to extract spectral data characteristics, respectively. For model selection, three models were chosen: back-propagation artificial neural network (BP-ANN), support vector machine (SVM), and one-dimensional convolutional neural network (1D-CNN). For model evaluation, we choose accuracy, recall, precision, F1-score, memory occupied, and time consumed by the model to evaluate. The experiments show that the combination of fluorescence hyperspectral technology and machine learning can provide a new method, MSC-PCA-SVM, for bulk liquor detection, with a final classification accuracy, recall, precision, and F1-score all reaching 100%, The effectiveness and application potential of this method in the IoT environment have been demonstrated. The results of this study can not only be applied to liquor detection but also have the value of reference for the adulthood and detection of the entire food industry. It is of great significance to standardize the market and protect consumer rights.
Gibbons’ conjecture for entire solutions of master equations
Authors: Chen Wenxiong , Ma Lingwei
Published: July 2024

In this paper, we establish a generalized version of Gibbons’ conjecture in the context of the master equation [Formula: see text] We show that, for each [Formula: see text], the bounded entire solution [Formula: see text] must be monotone increasing in one direction, and furthermore it is one-dimensional symmetric under certain uniform convergence assumption on [Formula: see text] and an appropriate decreasing condition on [Formula: see text]. These conditions are slightly weaker than their counter parts proposed in the original Gibbons’ conjecture. To overcome the difficulties in proving the Gibbons’ conjecture and the impediments caused by the strong correlation between space and time of fully fractional heat operator [Formula: see text], we introduce some new ideas and provide several new insights. More precisely, we first derive a weighted average inequality, which not only provides a straightforward proof for the maximum principle in bounded domains, but also plays a crucial role in further deducing the maximum principle in unbounded domains. Such average inequality and maximum principles are essential ingredients to carry out the sliding method, and then we apply this direct method to prove the Gibbons’ conjecture in the setting of the master equation. It is important to note that the holistic approach developed in this paper is highly versatile, and will become useful tools in investigating various qualitative properties of solutions as well as in establishing the Gibbons’ conjecture for a broad range of fractional elliptic and parabolic equations and systems.
Mechanical Quantities Prediction of Metal Cutting by Machine Learning and Simulation Data
Authors: Cheng Yijin , Li Yan , Cong Yu , Joli Pierre , Feng Zhiqiang
Published: July 2024

Metal cutting is an important process in industrial manufacturing. Using the mechanical quantities of metal cutting to optimize process design is helpful to improve productivity. However, it is expensive to obtain these quantities due to the complexity of the cutting process, including material nonlinearity, geometric nonlinearity, state nonlinearity and their interactions. In this paper, a prediction model is constructed by combining machine learning (ML) and simulation data to quickly acquire multi-difficult-to-obtain metal cutting mechanical quantities to solve this problem. First, Adaptive Smoothed Particle Hydrodynamics (ASPH) is used to generate a simulation dataset of 2000 metal cutting cases. Based on the simulation data, six machine learning (ML) methods are employed to establish two prediction models, single-task learning and multi-task learning, to predict the mechanical quantities of metal cutting. The experimental results demonstrate that the ML method can predict abundant reference data efficiently after understanding the relationship between simulation parameters and mechanical quantities from simulation data, which is expected to replace some similar and repetitive simulation work. The Multilayer Perceptron (MLP) model under the multi-task setting provides the best prediction performance, fastest prediction time efficiency, and stable model behavior. Additionally, input erasure experiments reveal that the prediction of maximum equivalent plastic strain is significantly affected by particle spacing, and cutting speed plays a vital role in predicting maximum velocity. This work highlights the promotion of the data-driven ML method in quickly obtaining abundant reference data for the metal cutting process, and provides an auxiliary means for process optimization.
The state-of-the-art research on the smart roll forming process
Authors: Han Fei , Chen Xi
Published: July 2024

This paper focuses on the most recent developments in roll forming technology research within the context of smart manufacturing. First, roll forming process simulation and optimisation are common applications of virtual manufacturing technology. Using numerical simulation analysis, this technique can accurately predict the stress distribution, deformation, and final forming quality of materials, allowing for process parameter optimisation and profile defect compensation. Second, the use of Flexible Roll Forming (FRF) technology. Traditional roll forming uses fixed rolls, resulting in less variation in profile shapes. To meet the demands of complex curve sheet metal forming, FRF technology uses adjustable rolls that can achieve real-time deformation throughout the forming process. Ultimately, the development of smart roll forming equipment has emerged as a prominent area of research. Smart roll forming equipment may accomplish automated operation, precise control, and real-time monitoring by integrating advanced technology, including sensors, control systems, and Artificial Intelligence (AI) algorithms.
Modelling of anisotropic and asymmetric deformation behaviours of premium threaded connections during cyclic loading
Authors: Wang Peng , Zhou Junyuan , Xiang Zhiyu , Li Hongwei
Published: July 2024

Premium threaded connections (PTCs) act as an important part to connect the martensitic stainless-steel tubes in deep wells under the co-action of cyclic loads by axial tension–compression and radial internal–external pressure. Local elasto-plastic deformation and crack are usually found to occur at PTCs, which result in leakage, raw material waste and environmental pollution. Therefore, predicting the deformation behaviours of PTCs and then to find the load boundary for crack mean a lot. However, since the obvious anisotropy, tension–compression asymmetry and Bauschinger effect of the material dynamically evolve with deformation, the challenge for modelling lies in the determination of mass of constitutive parameters which also dynamically evolves with deformation. To solve the problems above, a J2–J3 anisotropic yield criterion together with an Armstrong–Frederick (A-F) kinematic hardening equations are adopted in this work, and a microstructure-based crystal plasticity finite element model (CPFEM) is utilised to produce data for the determination of constitutive parameters. The established model is applied to predict the local elasto-plastic deformation of PTCs to investigate the rule of plastic strain distribution and the effects of cyclic load on it. The results show that the Bauschinger effect caused by the cyclic internal pressure has a large impact on the deformation of PTCs in the early few cycles. The radial internal pressure is the main factor that causes high contact stress and the accumulation of plastic deformation at the sealing surface and the shoulder of PTCs. The combined effect of radial internal pressure and axial tension exits and extremely large magnitude of load (tension force > 1400 MPa, compression force >1000 MPa) may cause failure of PTCs.
Vision-Guided Grasping Policy Learning from Demonstrations for Robotic Manipulators
Authors: Jiang Lei , Wang Feiyan , Liu Yueyue
Published: July 2024

The integration of robotics into domestic environments poses significant challenges due to the dynamic and varied nature of these settings. This paper introduces a new framework that combines vision-guided object recognition with adaptive grasping policies learned from human demonstrations. By harnessing computer vision technology, our system employs deep learning algorithms, particularly Convolutional Neural Networks (CNNs), to precisely detect and classify household objects. Simultaneously, the system uses imitation learning to refine grasping policies, enabling the robotic manipulator to dynamically adapt to new target objects. We validated our framework through a series of experimental setups that simulate typical kitchen tasks, such as manipulating utensils and preparing ingredients. These tasks, which primarily involve picking up and placing objects, served as practical tests for our system. The results demonstrate the system’s ability to effectively recognize a broad array of objects and adapt its grasping policies, thereby enhancing operational efficiency.
Cryptocurrency Frauds for Dummies: How ChatGPT introduces us to fraud?
Authors: Zellagui Wail , Imine Abdessamad , Tadjeddine Yamina
Published: July 2024

Recent advances in the field of large language models (LLMs), particularly the ChatGPT family, have given rise to a powerful and versatile machine interlocutor, packed with knowledge and challenging our understanding of learning. This interlocutor is a double-edged sword: it can be harnessed for a wide variety of beneficial tasks, but it can also be used to cause harm. This study explores the complicated interaction between ChatGPT and the growing problem of cryptocurrency fraud. Although ChatGPT is known for its adaptability and ethical considerations when used for harmful purposes, we highlight the deep connection that may exist between ChatGPT and fraudulent actions in the volatile cryptocurrency ecosystem. Based on our categorization of cryptocurrency frauds, we show how to influence outputs, bypass ethical terms, and achieve specific fraud goals by manipulating ChatGPT prompts. Furthermore, our findings emphasize the importance of realizing that ChatGPT could be a valuable instructor even for novice fraudsters, as well as understanding and safely deploying complex language models, particularly in the context of cryptocurrency frauds. Finally, our study underlines the importance of using LLMs responsibly and ethically in the digital currency sector, identifying potential risks and resolving ethical issues. It should be noted that our work is not intended to encourage and promote fraud, but rather to raise awareness of the risks of fraud associated with the use of ChatGPT.
SoK: Fully Homomorphic Encryption Accelerators
Authors: Zhang Junxue , Cheng Xiaodian , Yang Liu , Hu Jinbin , Liu Ximeng , Chen Kai
Published: July 2024

Fully Homomorphic Encryption (FHE) is a key technology enabling privacy-preserving computing. However, the fundamental challenge of FHE is its inefficiency, due primarily to the underlying polynomial computations with high computation complexity and extremely time-consuming ciphertext maintenance operations. To tackle this challenge, various FHE accelerators have recently been proposed by both research and industrial communities. This article takes the first initiative to conduct a systematic study on the 14 FHE accelerators: cuHE/cuFHE, nuFHE, HEAT, HEAX, HEXL, HEXL-FPGA, 100×, F1, CraterLake, BTS, ARK, Poseidon, FAB, and TensorFHE. We first make our observations on the evolution trajectory of these existing FHE accelerators to establish a qualitative connection between them. Then, we perform testbed evaluations of representative open-source FHE accelerators to provide a quantitative comparison on them. Finally, with the insights learned from both qualitative and quantitative studies, we discuss potential directions to inform the future design and implementation for FHE accelerators.
Origin and Innovations of CMP Slurry
Authors: Morinaga Hitoshi
Published: July 2024

This paper reviews how today’s CMP (Chemical Mechanical Polishing) slurries have been innovated and explores ideas for driving further evolution. In early semiconductor polishing, Mechanical Polishing was used, focusing on controlling abrasive particle sizes, leading to the use of alumina abrasives via wet classification. As materials shifted from germanium to silicon and applications transitioned from radios to integrated circuits, research was conducted on the material and size of abrasives to improve polishing accuracy, and silica was finally adopted. Subsequently, in pursuit of higher purity, ultrapure colloidal silica using organic raw materials was introduced in 1985 and became the standard in current semiconductor CMP. The first report on CMP dates back to Schmidt’s 1962 paper. Although the report was based on visual inspection, the approach was validated to be reasonable with today’s inspection technology. CMP achieved further defect reduction by integrating with Clean Technology. Throughout its history, polishing consistently pursued uniform action on surfaces, driving contaminant reduction, and occasionally achieving significant breakthroughs through the combination of diverse technologies. Innovations are born when disparate technologies, evolving independently until a certain point, interact and combine according to market needs.
“Sand Types”: A New Physicochemical Classification of Sand and Its Mapping Using Conditional Strings in ArcGIS10.x
Authors: Dinesh A. C. , Nisha N. V. , Rachna Pillai
Published: July 2024

The economic viability of sand in the construction industry depends on its size, shape, shell content, etc. It is imperative to understand the proportions of sand subclasses and shell content in sand sediment while planning exploration and mining. The existing sediment classifications (Particle Size Distribution Classifications) based on Sand‐Silt‐Clay (SSC) or Gravel‐Sand‐Mud (GSM) of different authors have not addressed these issues and it remains as a gap area till now. Hence, a new physicochemical classification (“Sand Types”) of sand that falls in the “sand fields” of SSC plots pertaining to two famous authors is being proposed. The freeware program “Sand Types” developed for plotting types of sand in the ternary diagram helps to plot the data in a triangular diagram and identify their physicochemical properties. The program also offers conditional strings that are prepared based on the proposed classification and are coupled with that of SSC classifications. These conditional strings work in ArcGIS10.x platform for the preparation of sediment distribution maps with meaningful information. This would enable construction industry/end‐users to plan and execute detailed exploration and mining programs at great ease.