Ali je Kitajska sposobna prehiteti svet v filozofiji in estetiki? Odziv na komentarje Aleša Erjavca, Ernesta Ženka in Roka Benčina o teorijah zhuyi in Bie-moderni

European philosophers and aestheticians hold that the humanities in China, including philosophy and aesthetics, may have bright prospects, but they do not necessarily regard them as first class. Contrary to this point of view, Bie-modernism (“bie xian dai zhuyi” in Chinese pinyin) believes that China’s humanities have world-class aspirations, although in this respect there are different motivations with regard to the Chinese government and the Chinese people. Lacking the most basic Enlightenment modernity, Chinese society and China’s humanities also lack a real modernity, which has been guiding the discourse of Chinese humanities since 1989. Only exported contemporary Chinese avant-garde art has the modernity of reflection and criticism that is proper to Bie-modernist[1] art. Therefore, if China’s humanities can learn from the Chinese avant-garde art spirit and adhere to Bie-modernism, it is possible to enter the international ranks. Then it will not be impossible to lead the world.[1]     Bie-modern theory, which was published in 2014, includes both the Bie-modern social situation and Bie-modernism, the latter of which counters the Bie-modern social situation. “Bie-modern” means the hybridity of the pre-modern, modern and post-modern, or the mixed social form of feudalism, socialism and capitalism. “Bie-modern” is doubtful modernity or pseudo-modernity, but Bie-modernism aims to eliminate pseudo-modernity and to set up real modernity. In Georgia Southwestern State University (USA), the Center for Chinese Bie-modern Studies (CCBMS) was founded in 2017. Evropski filozofi in estetiki trdijo, da imajo humanistične vede na Kitajskem, vključno s filozofijo in estetiko, morda svetlo prihodnost, vseeno pa v njih ne vidijo nujno nečesa prvorazrednega. V nasprotju s tem pogledom bie-modernizem (bie xian dai zhuyi) verjame, da ima kitajska humanistika pričakovanja svetovnih razsežnosti, čeprav obstajajo glede tega različne motivacije, ko gre za kitajsko vlado in ko gre za kitajsko ljudstvo. Ob tem, da pogrešata najosnovnejšo razsvetljensko modernost, kitajska družba in kitajska humanistika pogrešata tudi dejansko modernost, ki je vodila diskurz kitajske humanistike od leta 1989. Le izvožena sodobna avantgardna kitajska umetnost poseduje modernost refleksije in kritike, ki je lastna bie-modernistični umetnosti.[1] Le če se kitajske humanistične vede lahko učijo od duha kitajske avantgarde ter so zveste bie-modernizmu, lahko vstopijo v mednarodne vrste. pripadajo lahko vstopijo v mednarodni okvir. Potem sveta ne bo nemogoče voditi.[1]     Teorija o bie-modernosti, ki je bila objavljena leta 2014, vsebuje tako bie-moderno družbeno situacijo kot bie-modernizem, drugi od katerih nasprotuje bie-moderni družbeni situaciji. »Bie-moderen« pomeni hibridnost pred-modernega, bie-modernega in postmodernega ali mešano družbeno obliko fevdalizma, socializma in kapitalizma. »Bie-moderen« je dvomeča modernost ali psevdo-modernost, pri čemer skuša bie-modernizem odstraniti psevdo-modernost in vzpostaviti dejansko modernost. Gl. Georgia Southwestern State University, ZDA, Center za kitajske bie-moderne študije (CCBMS), ustanovljen leta 2017.

Moderni mit—primer Kitajske

In the article we argue that the negative influence of globalization on national culture and aesthetics is exaggerated and contradicted by facts, for in reality negative and positive consequences of globalization coexist, not the least because different political systems in different countries and regions within these countries respond differently. China has a long history of strong assimilation capability but this does not signify that it cannot become an object of assimilation. In author’s view both global Americanization and global Sinicization are unsubstantiated modern myths. Globalization and anti-globalization resemble the spear and the shield, for they are a union of opposites of each other in search of self-development. For a small, weak and defensless nation appropriating globalization signifies assimilation. For China it means a multicultural reordering with the Chinese culture as its main corpus.V članku trdimo, da je bila pogosta ocena o negativnem vplivu globalizacije na nacionalno kulturo in estetiko pretirana ter v opreki z dejstvi, saj v resnici negativne in pozitivne posledice globalizacije koeksistirajo, nenazadnje zato, ker se različni politični sistemi v različnih deželah in v regijah teh posameznih dežel odzivajo nanjo različno. Kitajska ima dolgo zgodovino močne asimilacijske sposobnosti, kar pa ne pomeni, da ne more postati predmet asimilacije. Po avtorjevi oceni sta tako globalna amerikanizacija kot globalna sinizacija neutemljena moderna mita. Globalizacija in antiglobalizacija sta kot sulica in ščit, sta enotnost nasprotij drug drugega v iskanju kulturnega samorazvoja. Za majhen in šibek narod brez zaščite pomeni privzeti globalizacije asimilacijo. Za Kitajsko pomeni multikulturno preureditev s kitajsko kulturo kot glavnim korpusom

Joint Route Optimization and Multidimensional Resource Management Scheme for Airborne Radar Network in Target Tracking Application

In this article, we investigate the problem of joint route optimization and multidimensional resource management (JRO-MDRM) for an airborne radar network in target tracking application. The mechanism of the proposed JRO-MDRM scheme is to adopt the optimization technique to collaboratively design the flight route, transmit power, dwell time, waveform bandwidth, and pulselength of each airborne radar node subject to the system kinematic limitations and several resource budgets, with the aim of simultaneously enhancing the target tracking accuracy and low probability of intercept (LPI) performance of the overall system. The predicted Bayesian Cramér–Rao lower bound and the probability of intercept are calculated and employed as the metrics to gauge the target tracking performance and LPI performance, respectively. It is shown that the resulting optimization problem is nonlinear and nonconvex, and the corresponding working parameters are coupled in both objective functions, which is generally intractable. By incorporating the particle swarm optimization and cyclic minimization approaches, an efficient four-step solution algorithm is proposed to deal with the above problem. Extensive numerical results are provided to demonstrate the correctness and advantages of our developed scheme compared with other existing benchmarks

Collaborative Trajectory Planning and Resource Allocation for Multi-Target Tracking in Airborne Radar Networks under Spectral Coexistence

This paper develops a collaborative trajectory planning and resource allocation (CTPRA) strategy for multi-target tracking (MTT) in a spectral coexistence environment utilizing airborne radar networks. The key mechanism of the proposed strategy is to jointly design the flight trajectory and optimize the radar assignment, transmit power, dwell time, and signal effective bandwidth allocation of multiple airborne radars, aiming to enhance the MTT performance under the constraints of the tolerable threshold of interference energy, platform kinematic limitations, and given illumination resource budgets. The closed-form expression for the Bayesian Cramér–Rao lower bound (BCRLB) under the consideration of spectral coexistence is calculated and adopted as the optimization criterion of the CTPRA strategy. It is shown that the formulated CTPRA problem is a mixed-integer programming, non-linear, non-convex optimization model owing to its highly coupled Boolean and continuous parameters. By incorporating semi-definite programming (SDP), particle swarm optimization (PSO), and the cyclic minimization technique, an iterative four-stage solution methodology is proposed to tackle the formulated optimization problem efficiently. The numerical results validate the effectiveness and the MTT performance improvement of the proposed CTPRA strategy in comparison with other benchmarks

Molecular Characterization of a Debilitation-Associated Partitivirus Infecting the Pathogenic Fungus Aspergillus flavus

The opportunistic human pathogenic fungus Aspergillus flavus is known to be infected with mycoviruses. In this study, we report a novel mycovirus A. flavus partitivirus 1 (AfPV1) that was originally isolated from the abnormal colonial morphology isolate LD-3-8 of A. flavus. AfPV1 has spherical virus-like particles about 40 nm in diameter, and three double-stranded RNA (dsRNA) segments (dsRNA1, 2, and 3 with lengths of 1.7, 1.4, and 1.1 kbp, respectively) were packaged in the virions. dsRNA1, dsRNA2, and dsRNA3 each contained a single open reading frame and potentially encoded 62, 42, and 32 kDa proteins, respectively. The dsRNA1 encoded protein shows similarity to the RNA-dependent RNA polymerase (RdRp) of partitiviruses, and the dsRNA2 product has no significant similarity to any other capsid protein (CP) in the GenBank databases, beside some homology with the hypothetical “capsid” protein of a few partitiviruses. The dsRNA3 encodes a protein with no similarity to any protein in the GenBank database. SDS-PAGE and polypeptide mass fingerprint-mass spectrum (PMF-MS) analyses indicated that the CP of the AfPV1 was encoded by dsRNA2. Phylogenetic analysis showed that the AfPV1 and relative viruses were found in an unclassified group inside the Partitiviridae family. AfPV1 seems to result in debilitation symptoms, but had no significant effects to murine pathogenicity. These findings provide new insights into the partitiviruses taxonomy and the interactions between viruses and A. flavus

Automated diagnosis of pancreatic mucinous and serous cystic neoplasms with modality-fusion deep neural network using multi-modality MRIs

BackgroundPancreatic cystic neoplasms are increasingly diagnosed with the development of medical imaging technology and people’s self-care awareness. However, two of their sub-types, serous cystic neoplasms (SCN) and mucinous cystic neoplasms (MCN), are often misclassified from each other. Because SCN is primarily benign and MCN has a high rate of malignant transformation. Distinguishing SCN and MCN is challenging and essential.PurposeMRIs have many different modalities, complete with SCN and MCN diagnosis information. With the help of an artificial intelligence-based algorithm, we aimed to propose a multi-modal hybrid deep learning network that can efficiently diagnose SCN and MCN using multi-modality MRIs.MethodsA cross-modal feature fusion structure was innovatively designed, combining features of seven modalities to realize the classification of SCN and MCN. 69 Patients with multi-modalities of MRIs were included, and experiments showed performances of every modality.ResultsThe proposed method with the optimized settings outperformed all other techniques and human radiologists with high accuracy of 75.07% and an AUC of 82.77%. Besides, the proposed disentanglement method outperformed other fusion methods, and delayed contrast-enhanced T1-weighted MRIs proved most valuable in diagnosing SCN and MCN.ConclusionsThrough the use of a contemporary artificial intelligence algorithm, physicians can attain high performance in the complex challenge of diagnosing SCN and MCN, surpassing human radiologists to a significant degree

Joint Collaborative Radar Selection and Transmit Resource Allocation in Multiple Distributed Radar Networks with Imperfect Detection Performance

In this study, a collaborative radar selection and transmit resource allocation strategy is proposed for multitarget tracking applications in multiple distributed phased array radar networks with imperfect detection performance. The closed-form expression for the Bayesian Cramér-Rao Lower Bound (BCRLB) with imperfect detection performance is obtained and adopted as the criterion function to characterize the precision of target state estimates. The key concept of the developed strategy is to collaboratively adjust the radar node selection, transmitted power, and effective bandwidth allocation of multiple distributed phased array radar networks to minimize the total transmit power consumption in an imperfect detection environment. This will be achieved under the constraints of the predetermined tracking accuracy requirements of multiple targets and several illumination resource budgets to improve its radio frequency stealth performance. The results revealed that the formulated problem is a mixed-integer programming, nonlinear, and nonconvex optimization model. By incorporating the barrier function approach and cyclic minimization technique, an efficient four-step-based solution methodology is proposed to solve the resulting optimization problem. The numerical simulation examples demonstrate that the proposed strategy can effectively reduce the total power consumption of multiple distributed phased array radar networks by at least 32.3% and improve its radio frequency stealth performance while meeting the given multitarget tracking accuracy requirements compared with other existing algorithms