Crucial Rules Research Articles

Transposing of the Cognitive-Centered Space to Marginal in Mohsin Hamid’s The Last White Man

Cognition always mirrors human psychology; the more it is acknowledged, the more it highlights human behavior. The individual's ‘cognitive space’ in Western society is entangled and has broken away to worsen. People of color in the West are going through the stereotypical pandemonium of racially discriminatory remarks. The bewilderingly baffled racial incidents jeopardize the identity of the people of color. Each day in the West, people are curious about their survival. It seems all the circumstances after each turmoil incident threaten the foundations of humanity. The human cognitive space stance insists on acquiring, systematizing, utilizing, and revising the environmentally received knowledge, but this outer space-societal received knowledge imprints various psychosis. The paper hits the nail on the head that socioenvironmental factors directly challenge the embodied human mind. Evidence that overshadowed racial incidents aligned in the present commenced in the past. Then, the study gives various examples of postcolonial binaries to examine how the individual-centered space is marginal. The study provides multiple possible solutions and crucial rules to educate societies on geopolitical tolerance and individual freedom. In conclusion, the article critically highlights a white man who has witnessed misfortune after turning black one morning in Mohsin Hamid's The Last White Man.

Key Factors in the Multiple Mechanisms of Virus Entry

Review Key Factors in the Multiple Mechanisms of Virus Entry Yifan Wang 1,2, Quanxiang Yu 1,3, Shuru Lin 1,3, Wenqi Jiang 1,3, Zhengfei Qi 1,3,4, Lina Wang 1,3, Lian Wu 1,3, Rui Ma 1,3, Kexin Zhang 1,3, Shurong Chen 1,3,4, Jiayi Xie 1,3, Lingli Zheng 1,3,4, Min Zhou 1,3,4 and Qingshan Bill Fu 1,3,4,* 1 Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China 2 School of Life Science and Medicine, Dalian University of Technology, Dalian 124000, China 3 Shanghai Institute of Materia Medica, Zhongshan Institute for Drug Discovery, Chinese Academy of Sciences, Zhongshan 528400, China 4 University of Chinese Academy of Sciences, Beijing 100049, China * Correspondence: fuqingshan@simm.ac.cn Received: 22 October 2024; Revised: 12 November 2024; Accepted: 19 December 2024; Published: 2 January 2025 Abstract: Viruses are non-cellular organisms that must parasitize and multiply within living cells to achieve their replicative procedures. Viral assaults can affect bacteria, eukaryotes, and archaea. Well-known viral illnesses in human history include smallpox, Ebola, the black death, the Spanish flu, human immunodeficiency virus (HIV), rabies, SARS, etc. Each of these diseases has caused countless deaths and severe consequences, greatly hindering the progress of human civilization and economic growth. Invasion of host cells by viruses can be broadly divided into several steps: adhesion, entry, replication, assembly, and release. Viral entry is particularly essential for viral invasion of host cells to cause infection. Different methods are employed by enveloped and non-enveloped viruses to mediate virus entry. Whichever entry technique is used, a few essential proteins (virus membrane proteins and cell receptor proteins) play crucial rules. Our knowledge of the structures of important proteins is also essential since it can inform us of the precise steps involved in this procedure. This review discusses the various methods of virus entry (such as Clathrin/Caveolae-mediated endocytosis, Lipid raft, and Macropinocytosis), lists a few typical fusion proteins in virus entry, and offers brief information on the structural characteristics of virus entry for diseases caused by the HIV and the recently discovered virus SARS-CoV-2. The intention of this page is to provide readers with an overall overview of virus entry pathways and to serve as a theoretical foundation for pertinent researches.

Dynamic Hydroxylation Enhances Hydrogen Atom Abstraction from Water for Nitrogen Fixation Revealed by Isotope Labeling in Situ Fourier-Transform Infrared Spectroscopy.

Employing water as a hydrogen source to participate in the hydrogen atom transfer (HAT) process is a low-cost and carbon-free process demonstrating great economic and environmental potential in catalysis. However, the low efficiency of hydrogen atom abstraction from water leads to slow kinetics of HAT for most hydrogenative reactions. Here, we prepared ultrathin Bi4O5Cl2 nanosheets where the surface can be in situ reconstructed via hydroxylation under light illumination to facilitate the abstraction of hydrogen atoms from pure water for efficient nitrogen fixation. Consequently, the isotope labeling in situ Fourier-transform infrared spectroscopy (FT-IR) involving H2O and D2O has clearly revealed that the hydroxyl groups tend to be adsorbed on the chloride vacancy sites on the Bi4O5Cl2 surface to form hydroxylated surfaces, where the hydroxylated photocatalyst surface enables partial dehydrogenation of water into H2O2, allowing the utilization of H atoms for efficient of N2 hydrogenation via HAT steps. This work elucidates the in-depth reaction mechanism of hydrogen atom extraction from H2O molecules via the light-generated chloride vacancy to promote photocatalytic nitrogen fixation, ultimately enabling the inspiration and providing crucial rules for the design of important functional materials that can efficiently deliver active hydrogen for chemical synthesis.

MolNet_Equi: A Chemically Intuitive, Rotation-Equivariant Graph Neural Network.

Although deep-learning (DL) models suggest unprecedented prediction capabilities in tackling various chemical problems, their demonstrated tasks have so far been limited to the scalar properties including the magnitude of vectorial properties, such as molecular dipole moments. A rotation-equivariant MolNet_Equi model, proposed in this paper, understands and recognizes the molecular rotation in the 3D Euclidean space, and exhibits the ability to predict directional dipole moments in the rotation-sensitive mode, as well as showing superior performance for the prediction of scalar properties. Three consecutive operations of molecular rotation , dipole-moment prediction , and dipole-moment inverse-rotation do not alter the original prediction of the total dipole moment of a molecule , assuring the rotational equivariance of MolNet_Equi. Furthermore, MolNet_Equi faithfully predicts the absolute direction of dipole moments given molecular poses, albeit the model has been trained only with the information on dipole-moment magnitudes, not directions. This work highlights the potential of incorporating fundamental yet crucial chemical rules and concepts into DL models, leading to the development of chemically intuitive models.

Inconsistent Cores for ASP: The Perks and Perils of Non-monotonicity

Answer Set Programming (ASP) is a prominent modeling and solving framework. An inconsistent core (IC) of an ASP program is an inconsistent subset of rules. In the case of inconsistent programs, a smallest or subset-minimal IC contains crucial rules for the inconsistency. In this work, we study fnding minimal ICs of ASP programs and key fragments from a complexity-theoretic perspective. Interestingly, due to ASP’s non-monotonic behavior, also consistent programs admit ICs. It turns out that there is an entire landscape of problems involving ICs with a diverse range of complexities up to the fourth level of the Polynomial Hierarchy. Deciding the existence of an IC is, already for tight programs, on the second level of the Polynomial Hierarchy. Furthermore, we give encodings for IC-related problems on the fragment of tight programs and illustrate feasibility on small instance sets.

Design tradeoffs between traditional hexagonal and emerging cubic InXGa(1–X)N/GaN-based green light-emitting diodes

Here, we report on the design tradeoffs between traditional hexagonal and emerging cubic InXGa(1−X)N/GaN-based green (520nm≤λ≤550nm) light-emitting diodes with special emphasis on the electron blocking layer, number of quantum wells, and thicknesses of quantum wells and barriers. We identified three crucial design rules for cubic green light-emitting diodes: (1) no need for an electron blocking layer; (2) use of a wide quantum well; and (3) choice of thin quantum barriers in multi-quantum well light-emitting diode designs. These design rules increase the internal quantum efficiency of cubic green light-emitting diodes by ∼30.5% under 100A/cm2 injection with respect to traditional designs. Overall, the design rules of cubic light-emitting diodes and their differentiating nature from the traditional, hexagonal ones are crucial for the advent of next-generation cubic light-emitting diodes.

Artificial Intelligence in Weaning Clinical Practice: Finding New Rules in Ventilator Support Care

When patients depend on ventilators for a long period of time, it will increase the risk of complexity and the risk of death. Thus, medical professionals try to help patients to wean off from the ventilator as soon as possible to minimize the adverse effects of the respiratory machine. This study analyzed historical clinical data to evaluate and improve the weaning protocol in operation. This study adopted a retrospective approach by collecting 1,014 weaning cases from Taiwan in 2012. We extracted the crucial rules describing the results of weaning from the ventilator using the machine learning algorithm - C4.5, which help medical professionals revise the existing weaning protocol and as supplementary indicators in a new version of the weaning protocol.

Inhibition of alpha-glucosidase enzyme and antioxidant activity of the metabolites purified from an endophytic fungus of Simarouba glauca DC.

Exploring new bioactive compounds from endophytic fungi with the anticipation of novel alpha-glucosidase inhibitors (AGIs) has led to the identification of few interesting small compounds. In the present study, the major chunk of purified fraction (‘DFR8’: Diaporthe sp. Fraction number 8) had a compound 3-hydroxybenzoic acid (compound 4), reported for the first time in an endophytic fungus Diaporthe sp. isolated from a medicinal plant, Simarouba glauca DC. The fraction (‘DFR8’) was purified from ethyl acetate extract of Diaporthe sp. using the activity-based column purification method, and the fraction showed the highest AG inhibition (IC50 = 22.85 μg/mL). The fraction also showed significant antioxidant properties (DPPH: IC50=206.60 µg/mL and ABTS: IC50=59.65 µg/mL) and contained phenolic compounds. Apart from compound 4, the GC–MS analysis of ‘DFR8’ revealed the presence of 16 other compounds at lesser concentrations, and some of them are already known for their antioxidant and alpha-glucosidase inhibition (AGI) activities. Interestingly, compound 4 (3-hydroxybenzoic acid) had the highest binding energy against both yeast and human AG enzymes when compared to the remaining compounds. Additionally, 3-hydroxybenzoic acid obeyed the crucial rules of drug-likeness properties during ADME/Toxicity evaluations, indicating that the compound could be developed into an effective AG inhibitor, which needs further detailed investigations.

Analysis of the cybersecurity ecosystem in the European Union

The information society is a complex network of interconnected public and private entities and human beings. Many of them choose a certain level of technological development from the generally available solutions to support internal processes attaining objectives that support operations, creating technological dependence via internal or external services of the information and communication technologies (ICTs). Due to the technological development and technological dependence caused by ICTs, a society-wide political need has arisen for tackling security requirements for cyberspace in several sectors to satisfy the individuals’ needs that directly or indirectly define the requirements for such services, resulting in a complex ecosystem with several participants. Although the European Union has formulated some crucial rules via regulations and directives with which it increasingly defined cybersecurity stakeholders from time to time, there are several missing affected parties. This paper aims to review the relevant technological, societal, and economic factors of the information society creating the necessity to strictly handle cybersecurity requirements and analyse decisive stakeholders via a theoretical framework. Furthermore, it also identifies the current legislative framework issues to identify pain points.

Remote virtual regulatory inspections of facilities and practices utilising ionising radiation and MRI installations during the Covid-19 pandemic

Covid-19 pandemic imposes crucial social distancing rules and restriction measures; therefore, the access to facilities and sites, in order to perform on-site inspections, became difficult or not feasible. Greek Atomic Energy Commission (EEAE) adopted remote virtual inspections (RVIs) of facilities and practices applying ionising radiation and magnetic resonance imaging installations, in order to continue discharging its regulatory duty of inspection, effectively. This study presents the experience gained and lessons learnt from the implementation of the RVIs and explores the RVIs perception by the stakeholders. Moreover, the effectiveness and the capability of RVIs to identify ‘findings’, is assessed by comparing the on-site and the remote inspections outcomes. The presented study showed that RVIs could not replace the on-site inspections, entirely; however, they could support and contribute to the inspection activities and program, in certain circumstances. RVIs were proven to be a valuable tool for the inspection of procedures, documents and records as well as the design and operational conditions of the facilities. The performance of remote verification tests and measurements, although feasible, was challenging, due to the technical issues needed to be resolved in advance. The comparison between remote and on-site inspections outcomes showed that both inspection options had similar capability to identify ‘findings’, indicating the validity of the RVIs as an inspection methodology in certain inspection thematic areas. The perception of the RVIs was positive and the added value and usefulness was acknowledged by the inspected facilities’ personnel and the EEAE’s inspectors, although the latter mainly considered RVIs as complementary and supportive to the on-site inspections.

Intramolecular Hydrogen Bond, Hirshfeld Analysis, AIM; DFT Studies of Pyran-2,4-dione Derivatives

Intra and intermolecular interactions found in the developed crystals of the synthesized py-ron-2,4-dione derivatives play crucial rules in the molecular conformations and crystal stabili-ties, respectively. In this regard, Hirshfeld calculations were used to quantitatively analyze the different intermolecular interactions in the crystal structures of some functionalized py-ran-2,4-dione derivatives. The X-ray structure of pyran-2,4-dione derivative namely (3E,3′E)-3,3′-((ethane-1,2-diylbis(azanediyl))bis(phenylmethanylylidene))bis(6-phenyl-2H-pyran-2,4(3H)-dione) was determined. It crystallized in the monoclinic crystal system and C2/c space group with unit cell parameters: a = 14.0869(4) Å, b = 20.9041(5) Å, c = 10.1444(2) Å and β = 99.687(2)°. Generally, the H…H, H…C, O…H and C…C contacts are the most important interactions in the molecular packing of the studied pyran-2,4-diones. The molecular structure of these compounds is stabilized by intramolecular O…H hydrogen bond. The nature and strength of the O…H hy-drogen bonds were analyzed using atoms in molecules calculations. In all compounds, the O…H hydrogen bond belongs to closed-shell interactions where the interaction energies are higher at the optimized geometry than the X-ray one due to the shortening in the A…H distance as a con-sequence of the geometry optimization. These compounds have polar characters with different charged regions which explored using molecular electrostatic potential map. Their natural charges, reactivity descriptors and NMR chemical shifts were computed, discussed and compared.

Dispute Resolution of Islamic Financial Institutions, Court Litigation and Negotiation

Dispute resolution in the Islamic financial sector is one of the current debates among regulators and Sharia scholars. When Islamic financial institutions have a dispute with their customers, have to search for a solution. The first step for the Islamic financial institutions for resolving the dispute is to start negotiation with their clients. Islamic financial institution negotiates with the client through Shariah supervisory committee members. Sharia scholars of the committee are experts in Shariah law. These Shariah members have an excellent reputation and well-known in society. Hence, the negotiation starts with the client resolving the dispute in order to not go to court. The advantages of the negotiation are taking less cost and less time and it is confidential which is very important for the Islamic financial institution. However, the decision that is reached by negotiation maybe not binding on the parties which consider a disadvantage of the negotiation method. If the parties could not resolve the dispute by negotiation, then the case will go to court. Most of the courts either based on the civil or common law system. Therefore, the decision made by these courts maybe not the right decision as the judges decide on the Shariah case according to civil or common law. Despite the court process take long time and is costly, but the decision that is made by the court is binding on the institution and the client. Some countries decide on Islamic financial legal cases in Shariah courts, such as the Kingdom of Bahrain. In a country like the UK, the decision on the Islamic financial cases will be under the English law system. Therefore, the Bahraini approach is an ideal solution, and the Malaysian approach is one of the best solutions, as the court refers to Shariah Advisory Council when the case is about Islamic finance. Purpose of This Paper: This paper purposes to observe the dispute resolution of Islamic financial legal cases and find solutions for the disputes between the Islamic financial institutions and their customer according to the current legal system in the world. Research Method: This research applies a qualitative descriptive method and analysis legal cases related to Islamic finance. the researcher describes the dispute resolution of Islamic financial institutions and then analyses the result of the research. The data collection for this research is from primary and secondary sources. Thus, court cases, books, journals, and related websites are the main source for data collection for this study. Findings: It is found that the current legal court system in many countries is not proper for resolving issues that arise between Islamic financial institutions and their clients. Thus, dispute resolution in the Islamic financial industry needs to be resolved by negotiation and mediation between the Islamic financial institutions and their customers. Furthermore, the courts have crucial rules in resolving these issues. However, lack of the Shariah courts in many countries in the world makes civil or common law courts decide on the issues, which judges are appointed on these courts do not have Shariah background. Keywords: Dispute resolution, Civil law court, Common law court, Negotiation, and Court litigation. DOI: 10.7176/IAGS/90-04 Publication date: March 31 st 2021

Shallow destructive earthquakes

Depths of earthquake occurrence and large slip distribution are critical for seismic hazard assessment. Numerous examples show that earthquakes with similar magnitudes, however, can result in significantly different ground shaking and damage. One of the critical factors is that whether the large slip was generated near the ground surface. In this article, we reviewed two aspects that are important on this regard, shallow slip deficit and nucleation depth. Understanding how shallow future earthquakes may nucleate in particular regions, such as shale gas fields, is critical for hazard assessment. Whether or not a strong earthquake may slip significantly at shallow depths (less than 3 km) plays crucial rules in seismic hazard preparation and should be further investigated by integrating high-resolution fault zone observations, dynamic rupture simulation, and fault zone properties. Moreover, precisely resolving shallow depth and slip distribution of earthquakes demands InSAR and/or other image data that can better capture the near-fault deformation to constrain the source parameters of earthquakes.

Research of insomnia on traditional Chinese medicine diagnosis and treatment based on machine learning

BackgroundInsomnia as one of the dominant diseases of traditional Chinese medicine (TCM) has been extensively studied in recent years. To explore the novel approaches of research on TCM diagnosis and treatment, this paper presents a strategy for the research of insomnia based on machine learning.MethodsFirst of all, 654 insomnia cases have been collected from an experienced doctor of TCM as sample data. Secondly, in the light of the characteristics of TCM diagnosis and treatment, the contents of research samples have been divided into four parts: the basic information, the four diagnostic methods, the treatment based on syndrome differentiation and the main prescription. And then, these four parts have been analyzed by three analysis methods, including frequency analysis, association rules and hierarchical cluster analysis. Finally, a comprehensive study of the whole four parts has been conducted by random forest.ResultsResearches of the above four parts revealed some essential connections. Simultaneously, based on the algorithm model established by the random forest, the accuracy of predicting the main prescription by the combinations of the four diagnostic methods and the treatment based on syndrome differentiation was 0.85. Furthermore, having been extracted features through applying the random forest, the syndrome differentiation of five zang-organs was proven to be the most significant parameter of the TCM diagnosis and treatment.ConclusionsThe results indicate that the machine learning methods are worthy of being adopted to study the dominant diseases of TCM for exploring the crucial rules of the diagnosis and treatment.

Design Principles for Cation‐Mixed Sodium Solid Electrolytes

AbstractAll‐solid‐state sodium‐ion batteries are highly promising for next generation grid energy storage with improved safety. Among the known sodium superionic conductors, the Na3PnS4 family and the recently discovered Na11Sn2PnS12 (Pn = P, Sb) have garnered major interest due to their extremely high ionic conductivities. In this work, comprehensive investigation of the Na3PnS4‐Na4TtS4 (Pn = P/As/Sb, Tt = Si/Ge/Sn) phase space of superionic conductors using density functional theory calculations, as well as AIMD simulations on the promising new Na11Sn2PnS12 (Pn=P/As/Sb) structures are presented. Crucial design rules on the effect of cation mixing are extracted on relative phase stability, electrochemical stability, moisture stability, and ionic conductivity. In particular, it is shown that while larger cations can substantially improve the ionic conductivity and moisture stability in these structures, there is an inherent trade‐off in terms of electrochemical stability. Na11Sn2AsS12 is also identified as a hitherto unexplored stable sodium superionic conductor with higher Na+ conductivity and better moisture stability than the Na11Sn2PS12 and Na11Sn2SbS12 phases already reported experimentally.

Influence of insolvency of a football club in Poland on the right to participate in league games

The study is devoted to the issue of the impact of sports club insolvency in Poland on the right to participate in league games. In this respect, not only the regulation of insolvency law is of the key importance. There are also crucial organizational rules established by the sports association (the Polish Football Association—Polski Związek Piłki Nożnej) determining admission to league games of only such sports clubs which have adequate financial liquidity. It should be stressed that the Polish Football Association (hereinafter “PZPN”) regulations do not allow to take part in competitions sports club in bankruptcy. This topic has become particularly relevant in 2020 in the context of the economic consequences of the unexpected pandemic of SARS-CoV-2. The paper deals with some legal aspects of lex sportiva and with the basic model of organization of the professional football league in Poland as well.

Studying Sea Level Variability in Indonesia Sea Based on Satellite Altimetry

Sea level variability is one of the fundamental parameters for scientific development such as modeling the Earth’s climate. In addition, this parameter also playing crucial rules to mitigate socio-economic hazards due to sea-level changes, especially in coastal areas. Mitigating the sea-level hazards in an archipelagic country like Indonesia becomes more essential since the country is geographically constructed by various bathymetric depths with different types of seas. One of the attempts to study sea-level variability is to take benefit from satellite altimetry data. The satellite altimetry missions have observed the sea level more than 25 years, and hence the rate of sea-level variability can thoroughly be studied by comparing Mean Dynamic Topography with Sea Level Rise in the research area. The result shows positive and negative correlation in several areas that can be examined as regional-scale variations in sea level over the Indonesian sea.

Efficient Learning with Exponentially-Many Conjunctive Precursors for Interpretable Spatial Event Forecasting

Forecasting spatial societal events in social media is significant and challenging. Most existing methods consider the frequencies of keywords or n-grams to be features, but have not explored the exponentially large space of the conjunctions of those features, such as keyword co-occurrence in messages, which can serve as crucial precursor rules. Due to the inherent exponential complexity of ensemble rule learning, existing work typically adopts greedy/heuristic strategies. This means that they cannot guarantee the solution's optimality, which would require a considerably more sophisticated model for spatial event forecasting, while still suffering from major challenges: 1) Exponentially-dimensional feature learning with distant supervision, 2) Numerical values of conjunctive features, and 3) Spatially heterogeneous conjunction patterns. To concurrently address all these challenges with a theoretical guarantee, we propose a novel spatial event forecasting model which learns numerical conjunctive features efficiently. Specifically, to consider their magnitude, traditional Boolean rules are innovatively generalized to deal with numerical conjunctive features with amenable computational properties. To handle the geographical similarity and heterogeneity in numerical conjunctive feature learning, we propose a new model that implements through a new bi-space hierarchical sparsity regularization for locations and features. Moreover, we propose a new algorithm to optimize the model parameters and prove that it enjoys theoretical guarantees for both the error bounds and time efficiency. Extensive experiments on multiple datasets demonstrate the effectiveness and efficiency of the proposed method.

Choice between Surgery and Conservative Treatment for Patients with Lumbar Spinal Stenosis: Predicting Results through Data Mining Technology

Currently, patients with lumbar spinal stenosis (LSS) have two treatment options: nonoperative conservative treatment and surgical treatment. Because surgery is invasive, patients often prefer conservative treatment as their first choice to avoid risks from surgery. However, the effectiveness of nonoperative conservative treatment for patients with LSS may be lower than expected because of individual differences. Rules to determine whether patients with LSS should undergo surgical treatment merits exploration. In addition, without a decision-making system to assist patients undergoing conservative treatment to decide whether to undergo surgical treatment, medical professionals may encounter difficulty in providing the best treatment advice. This study collected medical record data and magnetic resonance imaging diagnostic data from patients with LSS, analyzed and consolidated the data through data mining techniques, identified crucial factors and rules affecting the final outcome the patients with LSS who opted for conservative treatment and ultimately underwent surgical treatment, and, finally, established an effective prediction model. This study applied logistic regression (LGR) and decision tree algorithms to extract the crucial features and combined them with back propagation neural networks (BPNN) and support vector machines (SVM) to establish the prediction model. The crucial features obtained are as follows: reduction of the intervertebral disc height, age, blood pressure difference, leg pain, gender, etc. Among the models predicting whether patients with LSS ultimately underwent surgical treatment, the model combining LGR and the decision tree for feature selection with a BPNN has a testing accuracy rate of 94.87%, sensitivity of 0.9, specificity of 1, and area under the receiver operating characteristic curve of 0.952. Adopting these data mining techniques to predict whether patients with LSS who opted for conservative treatment ultimately underwent surgical treatment may assist medical professionals in reaching a treatment decision and provide clearer treatment. This may effectively mitigate disease progression, aid the goals of precision medicine, and ultimately enhance the quality of health care.

Glycosyl ortho-(1-phenylvinyl)benzoates versatile glycosyl donors for highly efficient synthesis of both O-glycosides and nucleosides

Both of O-glycosides and nucleosides are important biomolecules with crucial rules in numerous biological processes. Chemical synthesis is an efficient and scalable method to produce well-defined and pure carbohydrate-containing molecules for deciphering their functions and developing therapeutic agents. However, the development of glycosylation methods for efficient synthesis of both O-glycosides and nucleosides is one of the long-standing challenges in chemistry. Here, we report a highly efficient and versatile glycosylation method for efficient synthesis of both O-glycosides and nucleosides, which uses glycosyl ortho-(1-phenylvinyl)benzoates as donors. This glycosylation protocol enjoys the various features, including readily prepared and stable donors, cheap and readily available promoters, mild reaction conditions, good to excellent yields, and broad substrate scopes. In particular, the applications of the current glycosylation protocol are demonstrated by one-pot synthesis of several bioactive oligosaccharides and highly efficient synthesis of nucleosides drugs capecitabine, galocitabine and doxifluridine.