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Lung cancer is the main cause of cancer-related deaths, with non-small cell lung cancer (NSCLC) being the predominant subtype. At present, immunotherapy represented by immune checkpoint inhibitors (ICIs) of programmed cell death receptor 1 or its ligand has been widely used in the clinical diagnosis and treatment of patients with NSCLC. However, only a few patients can benefit from it, and reliable predictive markers for immunotherapy are lacking. Radiomics is a tool that uses computer software and algorithms to extract a large amount of quantitative information from biomedical images. A large number of studies have confirmed that the radiomic model that predicts the immune efficacy of NSCLC can be used as a new type of immune efficacy predictive marker, which is expected to guide the individualized diagnosis and treatment decisions for patients with lung cancer and has a bright application prospect. This article reviews the research progress of radiomics in predicting the immune therapy response of NSCLC, identifying pseudo-progression and hyperprogression, ICIs-related pneumonia, cachexia risk, and combining with other genomics.

Abstract Background Patients with inflammatory bowel diseases (IBDs) are at increased risk of pancreatitis. Data from a global safety database (GSD) were queried to identify risk factors for pancreatitis in vedolizumab-treated patients with IBD. Methods Takeda’s GSD was retrospectively queried for case reports (CRs) of adverse events (AEs) following vedolizumab treatment, from licensure (May 20, 2014) through March 31, 2021. Unsolicited and solicited CRs of pancreatitis were coded using the Medical Dictionary for Regulatory Activities (MedDRA) High-Level Term “Acute and chronic pancreatitis.” To examine factors associated with severe pancreatitis, serious CRs (serious AEs [SAEs]) were compared with SAEs from a comparator group of 600 random non-pancreatitis AEs. Comparisons were performed using t, χ 2, and Fisher’s exact tests. Logistic regression was performed to adjust for covariates allowing backward selection. Results In total, 196 patients reported pancreatitis in > 700,000 patient-years of vedolizumab exposure. Pancreatitis was serious in 195 patients (99.5%), and non-pancreatitis AEs were serious in 195 of 600 (32.5%) in the random comparator group. In the pancreatitis group, 17 patients (8.7%) had a known history of pancreatitis versus none in the random comparator group. Younger age, vedolizumab indication of ulcerative colitis, concomitant medications (with a risk for pancreatitis), pancreatitis history, and comorbid conditions (especially ongoing pancreatitis) were associated with development of severe pancreatitis. Conclusions These analyses identified factors associated with pancreatitis SAEs in patients with IBD treated with vedolizumab, but do not suggest an increased risk of pancreatitis with vedolizumab. These findings will help inform which patients treated for IBD might have an elevated risk, regardless of treatment.

With the rapid development of intelligent rail transportation, the realization of intelligent detection of railroad foreign body intrusion has become an important topic of current research. Accurate detection of rail edge location, and then delineate the danger area is the premise and basis for railroad track foreign object intrusion detection. The application of a single edge detection algorithm in the process of rail identification is likely to cause the problem of missing important edges and weak gradient change edges of railroad tracks. It will affect the subsequent detection of track foreign objects. A combined global and local edge detection method is proposed to detect the edges of railroad tracks. In the global pixel-level edge detection, an improved blok-matching and 3D filtering (BM3D) algorithm combined with bilateral filtering is used for denoising to eliminate the interference information in the complex environment. Then the gradient direction is added to the Canny operator, the computational template is increased to achieve non-extreme value suppression, and the Otsu thresholding segmentation algorithm is used for thresholding improvement. It can effectively suppress noise while preserving image details, and improve the accuracy and efficiency of detection at the pixel level. For local subpixel-level edge detection, the improved Zernike moment algorithm is used to extract the edges of the obtained pixel-level images and obtain the corresponding subpixel-level images. It can enhance the extraction of tiny feature edges, effectively reduce the computational effort and obtain the subpixel edges of the orbit images. The experimental results show that compared with other improved algorithms, the method proposed in this paper can effectively extract the track edges of the detected images with higher accuracy, better preserve the track edge features, reduce the appearance of pseudo-edges, and shorten the edge detection time with certain noise immunity, which provides a reliable basis for subsequent track detection and analysis.

Abstract This paper mainly solves the individual consistency and group consensus in the decision-making with hesitant fuzzy preference relations (HFPRs). The worst consistency index (WCI) is used to measure the individual consistency level. The envelop of an HFPR called envelop of HFPR (EHFRP) is proposed in the consensus reaching process (CRP). Two algorithms are proposed: one is to improve the WCI, in which only one pair of elements are revised in the consistency improving process each time, which aims to preserve the decision makers’ (DMs’) original information as much as possible. Another algorithm is proposed to improve the consensus in the CRP. To aggregate individual EHFPRs into one group HFPR, a new induced ordered weighted averaging (IOWA) operator is presented, called envelope HFPR-IOWA (EHFPR-IOWA), which allows the experts' preference to be aggregated in such a way that the most consistent ones are given more weight. Finally, an illustrative example and comparisons with the existing methods are provided to show the effectiveness of the proposed method.

BackgroundDespite numerous immunotherapy and chemotherapy regimens available for patients with extensive-stage small cell lung cancer (ES-SCLC), it remains unclear which regimen is the most effective and safest; relative studies comparing such regimens are scarce.ObjectiveThe aim of this study was to investigate the efficacy and safety of first-line immunotherapy combinations with chemotherapy for patients with extensive-stage small cell lung cancer. In addition, for the first time, comparisons among the first-line systemic regimens on OS and PFS in ES-SCLC by each time node were made.MethodsDatabases including PubMed, Embase, Cochrane Library, Scopus, Google Scholars, and ClinicalTrials.gov, and major international conferences were searched for randomized controlled trials (RCTs) regarding comparing immunotherapy combinations with chemotherapy as first-line treatments for patients with advanced ES-SCLC from inception to 1 November. Hazard ratios (HRs) and odds ratios (ORs) were generated for dichotomous variants by RStudio 4.2.1. The outcomes comprised overall survival (OS), progression-free survival (PFS), objective response rate (ORR), and adverse events of grade 3 or higher (Grade ≥ 3 AEs).ResultsEventually, a total of nine RCTs reporting 4,352 individuals with nine regimens were enrolled. The regimens were ipilimumabnu (Ipi), atezolizumab (Atez), durvalumab plus tremelimumab (Durv-Trem), durvalumab (Durv), pembrolizumab (Pemb), adebrelimab (Adeb), serplulimab (Serp), atezolizumab plus tiragolumab (Atez-Tira), and nivolumab (Nivo). With regard to OS, serplulimab (HR = 0.63, 95% CI: 0.49 to 0.81) was found to yield the best OS benefit when compared with chemotherapy. Meanwhile, serplulimab had the highest probability (46.11%) for better OS. Furthermore, compared with chemotherapy, serplulimab significantly increased the OS rate from the 6th to the 21st month. With regard to PFS, serplulimab (HR = 0.47, 95% CI: 0.38 to 0.59) was found to yield the best PFS benefit when compared with chemotherapy. Simultaneously, serplulimab had the highest probability (94.48%) for better PFS. Serplulimab was also a long-lasting first-line regimen in both OS and PFS from a longitudinal perspective. In addition, there was no significant difference among the various treatment options for ORR and grade ≥3 AEs.ConclusionConsidering OS, PFS, ORR, and safety profiles, serplulimab with chemotherapy should be recommended as the best therapy for patients with ES-SCLC. Certainly, more head-to-head studies are needed to confirm these findings.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/, identifier CRD42022373291.

Abstract The main resources needed for human survival are water, energy and food, and the research on the relationship among the three resources has become the research topic. Due to the shortage of natural resources, research on the efficiency of water–energy–food (WEF) nexus has become a hot issue among scholars and governments all over the world. The simple models cannot study the correlation among them; the methods of WEF nexus gradually shift from single to integrated model. The data envelopment analysis (DEA) model is the most simple and effective model, which can measure the efficiency value of each decision-making unit (DMU) and overcomes the shortcoming that the evaluation index system needs to give the weight. The DEA can calculate the efficiency value, but it cannot improve the efficiency value of DMU by changing the input. In this paper, the zero-sum gain (ZSG) DEA model is constructed based on zero-sum game theory. The initial efficiency values of 30 provinces in China are calculated, and each DMU is proportionally allocated according to the proportional subtractive method. After several iterations, the efficiency values of all DMUs reach 1, indicating that global optimization has been achieved. Under the condition of effectiveness, the initial input water resources are reconfigured. Finally, some conclusions are made, and optimization strategies are proposed for 30 provinces in China with low water resource utilization efficiency.

The Ca2+ modulated pulsatile glucagon and insulin secretions by pancreatic α and β cells are critical in glucose homeostasis. Here the authors show that the Ca2+ oscillations of α and β cells are phase-locked, and that the oscillation pattern is tuned by paracrine interactions between α and β cells.

Abstract Background The more selective second-generation BTK inhibitors (BTKi) Acalabrutinib and Zanubrutinib and the first-generation BTKi Ibrutinib are highlighted by their clinical effectiveness in mantle cell lymphoma (MCL), however, similarities and differences of their biological and molecular effects on anti-survival of MCL cells induced by these BTKi with distinct binding selectivity against BTK remain largely unknown. Methods AlamarBlue assays were performed to define cytotoxicity of BTKi against MCL cells, Jeko-1 and Mino. Cleaved PARP and caspase-3 levels were examined by immunoblot analysis to study BTKi-induced apoptotic effects. Biological effects of BTKi on MCL-cell chemotaxis and lipid droplet (LD) accumulation were examined in Jeko-1, Mino and primary MCL cells via Transwell and Stimulated Raman scattering imaging analysis respectively. Enzyme-linked immunoassays were used to determine CCL3 and CCL4 levels in MCL-cell culture supernatants. RNA-seq analyses identified BTKi targets which were validated by quantitative RT-PCR (qRT-PCR) and immunoblot analysis. Results Acalabrutinib and Zanubrutinib induced moderate apoptosis in Ibrutinib high-sensitive JeKo-1 cells and Ibrutinib low-sensitive Mino cells, which was accompanied by cleaved PARP and caspase-3. Such effects might be caused by the stronger ability of Ibrutinib to upregulate the expression of pro-apoptotic genes, such as HRK, GADD45A, and ATM, in JeKo-1 cells than in Mino cells, and the expression of such apoptotic genes was slightly changed by Acalabrutinib and Zanubrutinib in both JeKo-1 and Mino cells. Further, Acalabrutinib, Zanubrutinib and Ibrutinib reduced MCL-cell chemotaxis with similar efficiency, due to their similar abilities to downmodulate chemokines, such as CCL3 and CCL4. Also, these three BTKi similarly suppressed MCL-cell LD accumulation via downregulating lipogenic factors, DGAT2, SCD, ENPP2 and ACACA without significant differences. Conclusion BTKi demonstrated differential capacities to induce MCL-cell apoptosis due to their distinct capabilities to regulate the expression of apoptosis-related genes, and similar biological and molecular inhibitory effects on MCL-cell chemotaxis and LD accumulation.

Renewable energy technologies, particularly in electric vehicles (EVs), have received significant attention in recent years. The wasted energy in a vehicle's shock absorber can be converted into an alternative energy source by regenerative shock absorbers. In this paper, a high-efficiency regenerative shock absorber considering twin ball screws transmissions is proposed for application in range-extended electric vehicles. The proposed regenerative shock absorber can convert vibrational kinetic energy, which is traditionally dissipated as heat in suspension systems, into electricity. The proposed system is divided into four modules: suspension vibration input module, transmission module, generator module and power storage module. Induced by road roughness, the irregular linear oscillations of the suspension are transmitted to the suspension vibration input module. The reciprocating vibrations are converted into unidirectional rotation of the generator by a pair of ball screws, gears, and two overrun clutches in the transmission module. The utilisation of different screw pitches leads to different damping coefficients for upward and downward progress, enabling the shock absorber to fully utilise elastic elements to improve vehicle comfort when compressed and quickly absorb vibrations when stretched. The electricity produced by the generator is stored in supercapacitors to charge the battery and extend the range of EVs. The mechanical properties of the full-scaled fabricated prototype were studied by utilising a mechanical testing and sensing fixture. An average power output of 3.701 W in 1Hz-3 mm sinusoidal vibration input and a peak efficiency of 51.1% and average efficiency of 36.4% were achieved in a bench tests. The range can be approximately extended by 1 mile per 100 miles when EV is driving on the road of class B with a speed of 60 km/h, demonstrating that the proposed high-efficiency regenerative shock absorber is beneficial for harvesting renewable energy, and practical and significant for extending the range of EVs.

Similarity search in metric spaces finds similar objects to a given object, which has received much attention as it is able to support various data types and flexible similarity metrics. In real-life applications, metric spaces might be combined with graphs, resulting in geo-social network, citation graph, social image graph, to name but a few. In this paper, we introduce a new notion called quasi-metric graph that connects metric data using a graph, and formulate similarity search on quasi-metric graphs based on the combined similarity metric considering both the metric data similarity and graph similarity. We propose two simple efficient approaches, the best-first method and the breadth-first method, which traverse the quasi-metric graph following the best-first and the breadth-first paradigms, respectively, and utilize the triangle inequality to prune unnecessary evaluation. Extensive experiments with three real datasets demonstrate, compared with several baseline methods, the effectiveness and efficiency of our proposed methods.

The energy consumption by non-residential consumers in China accounts for a significant proportion of the total energy consumption in the society. Thus, accurate non-residential load forecasting plays an increasingly essential role in the future grid planning and operation. In this paper, a method based on LSTM recurrent neural network is proposed to predict the load of non-residential consumers using multiple correlated sequence information. First, the k-means is employed to analyze the daily load curves of non-residential consumers, classify and mine the consumer’s energy consumption behavior patterns. Then, the Spearman correlation coefficient is applied to investigate the time correlation under multiple time series for non-residential consumers. It is found that there exist multiple related time sequences such as adjacent time points, the same time points in adjacent days, and the same day in adjacent weeks among data samples for a specific consumer. Therefore, a non-residential load forecasting framework based on multiple sequence LSTM recurrent neural networks is presented. The proposed framework is tested on a real data set, which contains 48 non-residential consumers’ energy consumption data in China, and outperforms the other load forecasting approaches. Experiment results show that this method can effectively utilize the multiple sequence information, and successfully capture the dependencies among these sequences.

Water-energy-food (W-E-F) nexus is an essential element for human survival, as well as the basis for the sustainable development of regional economy and ecological environment. Water resource is an important input element of energy production and food production, which makes the W-E-F nexus become closer and more complicated. Taking water resource as the main input variable and grain as the output variable, and taking water resource and grain consumption as the main input variable and energy output as the output variable, the W-F and W/F-E coupling efficiency evaluation index system was constructed. Using data envelopment analysis (DEA) and Malmquist index model, the W-E-F coupling efficiency of 31 regions in China from 2007 to 2016 was evaluated from static and dynamic perspectives. In view of the low comprehensive efficiency in most areas, this paper gives corresponding strategies and suggestions.

This research paper proposes the use of empirical equations to estimate the temporal maximum scour that is induced by twin-propeller ( ε t w i n = Ω t [ l n ( t ) ] Γ t ) when acting over non-cohesive bed materials. A purpose built experimental apparatus is used to obtain the measurement data required for the calculation of the empirical constants. The output from rigorous experimental investigations demonstrates that the maximum scour depth produced from the operation of twin-propeller ( ε t w i n ), within the confines of a harbour basin, varies as a logarithmic function of time. A dimensional analysis of the standard single propeller configuration is used as the foundation upon which the scour equation is postulated. This is extended to include the influence of the operating distance between the twin-propeller configurations for the first time. The division of scours by twin-propeller and single-propeller ( ε twin / ε m ) enables the establishment of mathematical relation to calculate C1, C2, A, and B. The constants are C 1 = 366.11, C 2 = 0.3376, A = 0.859, and B = 0.1571. The proposed scour equation is more reliable within the time zone up to two hours based on the experimental data.

The scouring by a tidal turbine is investigated by using a joint theoretical and experimental approach in this work. The existence of a turbine obstructs a tidal flow to divert the flow passing through the narrow channel in between the blades and seabed. Flow suppression is the main cause behind inducing tidal turbine scouring, and its accelerated velocity is being termed as tip-bed velocity (Vtb). A theoretical equation is currently proposed to predict the tip-bed velocity based on the axial momentum theory and the conservation of mass. The proposed tip-bed velocity equation is a function of four variables of rotor radius (r), tip-bed clearance (C), efflux velocity (V0) and free flow velocity (V∞), and a constant of mass flow coefficient (Cm) of 0.25. An experimental apparatus was built to conduct the scour experiments. The results provide a better understanding of the scour mechanism of the horizontal axis tidal turbine-induced scour. The experimental results show that the scour depth is inversely proportional to tip-bed clearance. Turbine coefficient (Kt) is proposed based on the relationship between the tip-bed velocity and the experimental tidal turbine scour depth. Inclusion of turbine coefficient (Kt) into the existing pier scour equations can predict the maximum scour depth of a tidal turbine with an error range of 5−24%.

The data analysis of blasting sites has always been the research goal of relevant researchers. The rise of mobile blasting robots has aroused many researchers' interest in machine learning methods for target detection in the field of blasting. Serverless Computing can provide a variety of computing services for people without hardware foundations and rich software development experience, which has aroused people's interest in how to use it in the field ofmachine learning. In this paper, we design a distributedmachine learning training application based on the AWS Lambda platform. Based on data parallelism, the data aggregation and training synchronization in Function as a Service (FaaS) are effectively realized. It also encrypts the data set, effectively reducing the risk of data leakage. We rent a cloud server and a Lambda, and then we conduct experiments to evaluate our applications. Our results indicate the effectiveness, rapidity, and economy of distributed training on FaaS. [ABSTRACT FROM AUTHOR]