Search Results (18)

This paper explores the complex nature of land reforms, arguing that they should be considered wicked policy problems by focusing on the Hellenic Land Administration Reform (HLAR). The article reflects on recent contributions that argue that the HLAR’s challenges are associated with the great leap forward shift from a French-influenced deed paper-based system to a German-influenced digital cadastral parcel-based system. Another recent study contended that the legislative overregulation during the sovereign crisis period in the organizations of the diverse land registry systems of the land administration policy domain further complexified the reform process. A lack of consensus on the reform’s main policy thrust and the means to achieve it was present both at the onset of the reform and during the economic crisis period, among the actors in the reform process. This paper contributes to the contemporary scholarly literature on land administration, integrating recent empirical contributions that point toward the wicked nature of land administration reforms. Full article

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide, and, with only 15–20% of HCC patients being suitable for potentially curative treatments, the vast majority of patients with HCC ultimately require systemic therapy. For decades, the choice of effective systemic therapy for HCC remained sparse. In recent years, after the combination of atezolizumab and bevacizumab demonstrated superior overall survival over the first-line standard, sorafenib, there has been a major therapeutic paradigm shift to immunotherapy-based regimens for HCC. While representing a great leap forward for the treatment of this cancer, the reality is that less than one-third of patients achieve an objective response to immune checkpoint inhibitor-based therapy, so there remains a significant clinical need for further therapeutic optimization. In this review, we provide an overview of the current landscape of immunotherapy for unresectable HCC and delve into the tumor intrinsic and extrinsic mechanisms of resistance to established immunotherapies with a focus on novel therapeutic targets with strong translational potential. Following this, we spotlight emerging immunotherapy approaches and notable clinical trials aiming to optimize immunotherapy efficacy in HCC that include novel immune checkpoint inhibitors, tumor microenvironment modulators, targeted delivery systems, and locoregional interventions. Full article

Drawing on Karl Marx’s ecological concepts of the “metabolic rift” and the “emancipation of senses”, this paper explores an alternative ecocinema that integrates the ecological with the social and the economic. Early Hollywood films, such as Sunrise: A Song of Two Humans (1927) and The Good Earth (1937), represent the metabolic rift in human relationships as a byproduct of the metabolic rift with nature created in the process of urbanization; hence, they can be regarded as precursors to an alternative ecocinema, which I refer to as “metabolic cinema”. The Story of the Golden Bell (Jinling Zhuan), a comedy film produced during the Chinese Great Leap Forward in 1958, offers an intriguing case for socialist metabolic cinema as a multisensory medianature that participates in and facilitates the metabolic process between humans and nature, as well as the social metabolism among humans, despite the period’s notorious ecological record. The film not only consciously moves away from the visual-centric model associated with capitalist consumerism by using the aural to rectify the once-aberrant visual but also demonstrates how romantic love, as one of the human senses, must be emancipated along with other senses through denouncing utilitarianism and commercialism and, subsequently, returning to need-based labor as the universal condition for the metabolic interaction between humans and nature. Full article

The feature extraction problem of coupled vibration signals with multiple fault modes of planetary gears has not been solved effectively. At present, kernel principal component analysis (KPCA) is usually used to solve nonlinear feature extraction problems, but the kernel function selection and its blind parameter setting greatly affect the performance of the algorithm. For the optimization of the kernel parameters, it is very urgent to study the theoretical modeling to improve the performance of kernel principal component analysis. Aiming at the deficiency of kernel principal component analysis using the single-kernel function for the nonlinear mapping of feature extraction, a dual-kernel function based on the flexible linear combination of a radial basis kernel function and polynomial kernel function is proposed. In order to increase the scientificity of setting the kernel parameters and the flexible weight coefficient, a mathematical model for dual-kernel parameter optimization was constructed based on a Fisher criterion discriminant analysis. In addition, this paper puts forward a swarm intelligent fusion algorithm to increase this method’s advantages for optimization problems, involving the shuffled frog leaping algorithm combined with particle swarm optimization (SFLA-PSO). The new fusion algorithm was applied to optimize the kernel parameters to improve the performance of KPCA nonlinear mapping. The optimized dual-kernel function KPCA (DKKPCA) was applied to the feature extraction of planetary gear wear damage, and had a good identification effect on the fuzzy damage boundary of the planetary gearbox. The conclusion is that the DKKPCA optimized by the SFLA-PSO swarm intelligent fusion algorithm not only effectively improves the performance of feature extraction, but also enables the adaptive selection of parameters for the dual-kernel function and the adjustment of weights for the basic kernel function through a certain degree of optimization; so, this method has great potential for practical use. Full article

This paper focuses on both voltage transients and short-duration RMS variations, and presents a unique and heterogeneous approach to their assessment by applying AI tools. The database consists of both real (obtained from Lithuanian PQ monitoring campaigns) and synthetic data (obtained from the simulation and literature review). Firstly, this paper investigates the fundamental grid component and its harmonics filtering with an IIR shelving filter. Secondly, in a key part, both SVM and KNN are used to classify PQ events by their primary cause in the voltage–duration plane as well as by the type of short circuit in the three-dimensional voltage space. Thirdly, since it seemed to be difficult to interpret the results in the three-dimensional space, the new method, based on Clarke transformation, is developed to convert it to two-dimensional space. The method shows an outstanding performance by avoiding the loss of important information. In addition, a geometric analysis of the fault voltage in both two-dimensional and three-dimensional spaces revealed certain geometric patterns that are undoubtedly important for PQ classification. Finally, based on the results of a PQ monitoring campaign in the Lithuanian distribution grid, this paper presents a unique discussion regarding PQ assessment gaps that need to be solved in anticipation of a great leap forward and refers them to PQ legislation. Full article

With the great leaps forward in the development of the railway, the importance of safe operation and maintenance has become increasingly prominent. Varistor is the key component insurge protective devices for railway communication and signaling equipment, it is necessary to study a description model of the varistor degradation process and predict its lifetime through condition monitoring. Among the monitoring parameters, nonlinear coefficient is an important index to measure the health of varistors. Considering that the degradation process of varistors is the cumulative effect of surge history, and its nonlinear coefficient has a time–series relationship, a life prediction model for varistors based on BiLSTM is proposed. The model innovatively uses nonlinear coefficient as the characterization of the deterioration degree of varistors and uses a small-scale network to predict the development trend of nonlinear coefficient automatically and accurately. Verified by surge impact experiments, the model can accurately predict the state of nonlinear coefficient according to historical data and has the potential for engineering applications in predicting the life of varistors. Full article

Landslides are one of the most common geological disasters in China, characterized by suddenness and uncertainty. Traditional methods are not sufficient for the accurate identification, early warning, and forecasting of landslide disasters. As high-resolution remote sensing satellites and interferometric synthetic aperture radar (InSAR) surface deformation monitoring technology have been leaping forward, the traditional methods of landslide monitoring data sources are limited, and there have been few effective methods to excavate the characteristics of the spatial distribution of landslide hazards and their triggering factors, etc. In this study, an area extending 10 km from the VII isobar of the Gengma earthquake was taken as the study area, and 13 evaluation factors were screened out by integrating the factors of InSAR surface deformation, topography, and geological environment. Landslide susceptibility was evaluated through the Bayesian optimized convolutional neural network (BO-CNN), and the Bayesian optimized random forests (BO-RF) and particle swarm optimization support vector machines (PSO-SVM) models were selected for comparative analyses. The accuracy of the model was evaluated by using three indices, including the ROC curve, the AUC value, and the FR value. Specifically, the ROC curves of PSO-SVM, BO-RF, and BO-CNN were close to the upper-left corner, indicating excellent model performance. Moreover, the AUC values were computed as 0.9388, 0.9529, and 0.9535, respectively, and the FR value of landslides in the high susceptibility area of BO-CNN reached up to 14.9 and exceeded those of PSO-SVM and BO-RF, respectively. Furthermore, the mentioned values of the SVM and BO-RF models were 4.55 and 3.69 higher. The experimental results indicated that, compared with other models, the BO-CNN model used in this study had a better effect on landslide susceptibility evaluation, and the research results are of great significance to the disaster prevention and mitigation measures of local governments. Full article

Antibody–drug conjugates (ADCs) are at the forefront of the drug development revolution occurring in oncology. Formed from three main components—an antibody, a linker molecule, and a cytotoxic agent (“payload”), ADCs have the unique ability to deliver cytotoxic agents to cells expressing a specific antigen, a great leap forward from traditional chemotherapeutic approaches that cause widespread effects without specificity. A variety of payloads can be used, including most frequently microtubular inhibitors (auristatins and maytansinoids), as well as topoisomerase inhibitors and alkylating agents. Finally, linkers play a critical role in the ADCs’ effect, as cleavable moieties that serve as linkers impact site-specific activation as well as bystander killing effects, an upshot that is especially important in solid tumors that often express a variety of antigens. While ADCs were initially used in hematologic malignancies, their utility has been demonstrated in multiple solid tumor malignancies, including breast, gastrointestinal, lung, cervical, ovarian, and urothelial cancers. Currently, six ADCs are FDA-approved for the treatment of solid tumors: ado-trastuzumab emtansine and trastuzumab deruxtecan, both anti-HER2; enfortumab-vedotin, targeting nectin-4; sacituzuzmab govitecan, targeting Trop2; tisotumab vedotin, targeting tissue factor; and mirvetuximab soravtansine, targeting folate receptor-alpha. Although they demonstrate utility and tolerable safety profiles, ADCs may become ineffective as tumor cells undergo evolution to avoid expressing the specific antigen being targeted. Furthermore, the current cost of ADCs can be limiting their reach. Here, we review the structure and functions of ADCs, as well as ongoing clinical investigations into novel ADCs and their potential as treatments of solid malignancies. Full article

(1) Background: The COVID-19 pandemic posed new challenges to clinical practice and delineated future directions for online interventions in psychological care. The present study aimed to explore Italian psychologists’ and psychotherapists’ experiences of online interventions during the pandemic, focusing on the strategies they used to develop and maintain therapeutic relationships with their patients. (2) Methods: Between February and July 2021, 368 Italian psychologists and/or psychotherapists completed an online survey. A mixed-methods analysis was conducted, using Jamovi to analyze quantitative data and ATLAS.ti 9 to analyze qualitative data. (3) Results: Of the participants, 62% had never delivered online interventions before the pandemic; though 95.4% were delivering online interventions at the time of the survey, many reported facing technical disruptions (77.1%) and having little confidence in the online setting (45.3%). Feeling present in online sessions—facilitated by emotional attunement, active listening, and conversational spontaneity—was reported as “very important” by 93.6%. (4) Conclusions: Overall, the COVID-19 pandemic allowed a great leap forward in the use of online interventions by Italian psychologists and psychotherapists. This period of upheaval generated not only a positive change in their attitudes toward and intention to use online interventions but also revealed associated technical and relational issues that must be properly addressed. Full article

Global environmental governance is the fundamental way to solve the human environmental crisis. With China as the world’s largest emitter of greenhouse gases, the development of China’s environmental law is a key component of global environmental governance. In order to better realize the construction of an ecological civilization, the compilation of China’s Environmental Code has been officially put on the work schedule of the legislature. The compilation of the code is a sincere action, showing that China has taken the initiative to assume its own responsibility for environmental governance. In the past 50 years, China’s environmental legislation has achieved a great leap forward: from nothing to something, from something to something more comprehensive. Aside from this progress, defects such as the internal imbalance of the environmental law system, the backwardness of some environmental legislation ideas, and the inability of environmental legislation and its academic research to fully match China’s national conditions also exist. With the helping hands of conditions and times, it is most appropriate for China to start the compilation of the Environmental Code now. Environmental Codes such as the Swedish Environmental Code, the French Environmental Code and the German Environmental Code (Draft of the Committee of Experts) provide many empirical references for the compilation of China’s Environmental Code. China will make important an contribution to world environmental governance again—an Environmental Code in line with international standards while maintaining native characteristics. Full article

The automated vehicle (AV) industry is a new growing industry of great interest. The environmental friendliness of AVs represents a core characteristic of their leap-forward development. The environmental effect of AVs, including its evaluation framework and algorithm, is a leading research area for continued technological innovation and market development in this field. This study focuses on three environmental aspects: the energy effect of AVs, the traffic effect of AVs on ground space, and the air effect of AVs on three-dimensional atmospheric space. First, an environmental effect evaluation indicator system that includes nine indices for AVs is constructed to be the basis for management decision making. Second, the interval-valued intuitionistic uncertain fuzzy (IVIUF) evaluation variable is used to solve the problem of data features that incorporate “crisp numbers” and “fuzzy numbers”. Moreover, geometric weights are added based on the generalized correlation aggregation operator. Then, the IVIUL-weighted geometric (IVIULWG) operator is developed, which includes the objective and subjective information of “crisp numbers” and “fuzzy numbers” and makes the mathematical characteristics more scientific and accurate. Finally, an evaluation example is used to validate the effectiveness and practicability of the algorithm. Full article

Despite the pandemic, the last five years have been marked by an extraordinary development of new advanced technologies, based not only on new materials but also on modeling, information technology and artificial intelligence, which have allowed for great leaps forward in various research fields [...] Full article

Since the approval of ibrutinib for relapsed/refractory mantle cell lymphoma (MCL), the treatment of this rare mature B-cell neoplasm has taken a great leap forward. Despite promising efficacy of the Bruton tyrosine kinase inhibitor, resistance arises inevitably and the underlying mechanisms remain to be elucidated. Here, we aimed to decipher the response of a sensitive MCL cell line treated with ibrutinib using time-resolved single-cell RNA sequencing. The analysis uncovered five subpopulations and their individual responses to the treatment. The effects on the B cell receptor pathway, cell cycle, surface antigen expression, and metabolism were revealed by the computational analysis and were validated by molecular biological methods. The observed upregulation of B cell receptor signaling, crosstalk with the microenvironment, upregulation of CD52, and metabolic reprogramming towards dependence on oxidative phosphorylation favor resistance to ibrutinib treatment. Targeting these cellular responses provide new therapy options in MCL. Full article

China’s growth miracle has been accompanied by a great leap forward in the development of transport infrastructure. This study examines and compares impacts from the quantity, quality, and structural aspects of transport infrastructure on regional economic growth in China as the country approaches an upper-middle income status. We also incorporate government’s development strategies into the framework for evaluating the growth effect of China’s transport infrastructure. Using a consistent and robust dynamic panel data system generalized method of moments (system-GMM) estimation for identification, we find strong evidence confirming that transport infrastructure contributes to regional economic growth in China during the period 2007–2015, as the country approaches its upper-middle income status. In particular, quality improvements in roads and railways and the structural upgrading of transport infrastructure significantly contribute to growth. However, we do not find that quantity expansion of the overall land transport network has a significant impact. Moreover, government development strategies that defy local comparative advantages not only detract from the growth rate but also potentially restrict the contribution of transport infrastructure. Lastly, the regional heterogeneity for Western China may differ across transport modes, particularly with respect to goods versus passenger transport and roadways versus railways. Full article

The formulation of the 17 sustainable development goals (SDGs) was a major leap forward in humankind’s quest for a sustainable future, which likely began in the 17th century, when declining forest resources in Europe led to proposals for the re-establishment and conservation of forests, a strategy that embodies the great idea that the current generation bears responsibility for future generations. Global progress toward SDG fulfillment is monitored by 231 unique social-ecological indicators spread across 169 targets, and remote sensing (RS) provides Earth observation data, directly or indirectly, for 30 (18%) of these indicators. Unfortunately, the UN Global Sustainable Development Report 2019—The Future is Now: Science for Achieving Sustainable Development concluded that, despite initial efforts, the world is not yet on track for achieving most of the SDG targets. Meanwhile, through the EO4SDG initiative by the Group on Earth Observations, the full potential of RS for SDG monitoring is now being explored at a global scale. As of April 2020, preliminary statistical data were available for 21 (70%) of the 30 RS-based SDG indicators, according to the Global SDG Indicators Database. Ten (33%) of the RS-based SDG indicators have also been included in the SDG Index and Dashboards found in the Sustainable Development Report 2019—Transformations to Achieve the Sustainable Development Goals. These statistics, however, do not necessarily reflect the actual status and availability of raw and processed geospatial data for the RS-based indicators, which remains an important issue. Nevertheless, various initiatives have been started to address the need for open access data. RS data can also help in the development of other potentially relevant complementary indicators or sub-indicators. By doing so, they can help meet one of the current challenges of SDG monitoring, which is how best to operationalize the SDG indicators. Full article