On minimal non- MSP -groups

A finite group G is called an MSP-group if all maximal subgroups of the Sylow subgroups of G are Squasinormal in G. In this paper, wc give a complete classification of those groups which are not MSP-groups but whose proper subgroups are all MSP-groups.Скiнченну групу G називають MSP-групою, якщо всi максимальнi пiдгрупи силовських пiдгруп G є S-квазiнормальними в G. Наведено повну класифiкацiю груп, якi не є MSP-групами, але всi їх власнi пiдгрупи є MSP-групами

Surfactant aggregation in hydrophobic ionic liquid to formulate microemulsions for the enhancement of the solubility of enzymes and their catalytic performance

Room temperature ionic liquids (ILs) are molten salts at room temperature or below 100 °C. They are composed of organic cations and inorganic/organic anions. ILs have many advantages such as low volatility, high stability, good miscibility with organic compounds and unique constituents designability. Compared to traditional organic solvents, ILs are usually considered as “green” solvents. The use of ILs as media for enzyme catalysis was tried as early as 2000, and since then, many endeavours have been devoted to the studies. Previous studies indicate that an enzyme usually has catalytic activity in ILs if the enzyme is active in an organic solvent. Also it has been found that the [email protected] performance of enzymes in ILs is correlated with the hydrophilicity/hydrophobicity of ILs. In hydrophobic ILs, such as [Bmim][PF6] and [Bmim][NTf2], enzymes are not soluble, and usually their powders are suspended in ILs. The suspended enzymes exhibit catalytic activity and even good stability, but only small portions are available for catalysis due to their poor dispersion. By contrast, in hydrophilic ILs, enzymes are soluble, but their activity is poor due to the unfavourable interaction between enzymes and ILs. It follows that the major problem for the utilization of ILs as media for enzyme catalysis is how to reconcile the contradiction between the maintenance of the enzyme activity and the solubility of the enzyme in ILs. Reviewing the evolution of the medium engineering for enzyme catalysis, we get a good idea. For hydrophobic ILs (HILs), a good solution to the problem is to create a microenvironment suitable for the dispersion of an enzyme as well as the maintenance of the enzyme activity by dispersing water into HILs; i.e., the so-called microemulsification of HILs with surfactants. The microemulsification results in larger surface area than in the HIL/water two-phase system and makes the reactions of hydrophobic substrates with a hydrophilic enzyme go easily. Moreover, the formed water pool can restrict the change of the conformation of the enzyme. Studies have shown that most enzymes can maintain their catalytic activity and stability in HIL-based microemulsions. In this talk, we make a brief description of the recent progress made in my group in the enzyme catalysis in HIL- based microemulsion. To be relevant to the themes of the Conference, the talk is focused on the aggregation behaviour of different surfactants in HILs as well as the microstructural effect of the formed aggregates on solubilized enzymes. The aggregation of surfactants of different types will be summarized. To circumvent the poor solubility of most ionic surfactants such as NaAOT in HILs, a new strategy has been developed; i.e., the substitution of the inorganic counter ion by its organic counterpart. For example NaAOT, the replacement of the counter ion Na+ by [Bmim]+ not only increases the surface activity of AOT- in water, but also significantly improve its solubility in [Bmim]Tf2N. Also it is found the exchange of the cations helps to formulate a W/HIL microemulsion without any additives. In addition to the construction strategy, we will present detailed studies on the regulation of the microstructure and the consequent water solubilization capacity by salts and alcohols. The catalytic performance of enzymes hosted in HIL-based microemulsions has been characterized. It is found that the formation of the microdroplet of water in HIL facilitates the dispersion of enzymes such as laccase on a molecular level and also greatly reduces the negative effect of the ionic liquid on the enzyme. The catalytic activity of an enzyme hosted in the droplet depends upon the size of the droplets, the interfacial components and charge density. For a given enzyme, an optimal microenvironment could be created via the formulation optimization. All results indicate that HIL-based reverse micelles or microemulsions, which are homogeneous macroscopically but microscopically heterogeneous, are promising media for an enzyme catalyzed reaction

Split, Encode and Aggregate for Long Code Search

Code search with natural language plays a crucial role in reusing existing code snippets and accelerating software development. Thanks to the Transformer-based pretraining models, the performance of code search has been improved significantly compared to traditional information retrieval (IR) based models. However, due to the quadratic complexity of multi-head self-attention, there is a limit on the input token length. For efficient training on standard GPUs like V100, existing pretrained code models, including GraphCodeBERT, CodeBERT, RoBERTa (code), take the first 256 tokens by default, which makes them unable to represent the complete information of long code that is greater than 256 tokens. Unlike long text paragraph that can be regarded as a whole with complete semantics, the semantics of long code is discontinuous as a piece of long code may contain different code modules. Therefore, it is unreasonable to directly apply the long text processing methods to long code. To tackle the long code problem, we propose SEA (Split, Encode and Aggregate for Long Code Search), which splits long code into code blocks, encodes these blocks into embeddings, and aggregates them to obtain a comprehensive long code representation. With SEA, we could directly use Transformer-based pretraining models to model long code without changing their internal structure and repretraining. Leveraging abstract syntax tree (AST) based splitting and attention-based aggregation methods, SEA achieves significant improvements in long code search performance. We also compare SEA with two sparse Trasnformer methods. With GraphCodeBERT as the encoder, SEA achieves an overall mean reciprocal ranking score of 0.785, which is 10.1% higher than GraphCodeBERT on the CodeSearchNet benchmark.Comment: 9 page

Blocking Drug Activation as a Therapeutic Strategy to Attenuate Acute Toxicity and Physiological Effects of Heroin

Heroin is a growing national crisis in America. There is an increasing frequency of heroin overdoses. All of the currently used therapeutic approaches to treatment of heroin abuse and other opioid drugs of abuse focus on antagonizing a brain receptor (particularly µ-opiate receptors). However, it has been known that the therapeutic use of certain µ-opiate receptor antagonist may actually increase heroin overdose. Once overdosed, heroin addicts may continue to get overdosed again and again until fatal. Here we report our design and validation of a novel therapeutic strategy targeting heroin activation based on our analysis of the chemical transformation and functional change of heroin in the body. An effective blocker of heroin activation, such as ethopropazine tested in this study, may be used as a standalone therapy or in combination with a currently available, traditional medications targeting µ-opiate receptors (e.g. naltrexone or its extended-release formulation Vivitrol). The combination therapy would be ideal for heroin abuse treatment as the effects of two therapeutic agents targeting two independent mechanisms are cooperative

Revisiting Code Search in a Two-Stage Paradigm

With a good code search engine, developers can reuse existing code snippets and accelerate software development process. Current code search methods can be divided into two categories: traditional information retrieval (IR) based and deep learning (DL) based approaches. DL-based approaches include the cross-encoder paradigm and the bi-encoder paradigm. However, both approaches have certain limitations. The inference of IR-based and bi-encoder models are fast, however, they are not accurate enough; while cross-encoder models can achieve higher search accuracy but consume more time. In this work, we propose TOSS, a two-stage fusion code search framework that can combine the advantages of different code search methods. TOSS first uses IR-based and bi-encoder models to efficiently recall a small number of top-k code candidates, and then uses fine-grained cross-encoders for finer ranking. Furthermore, we conduct extensive experiments on different code candidate volumes and multiple programming languages to verify the effectiveness of TOSS. We also compare TOSS with six data fusion methods. Experimental results show that TOSS is not only efficient, but also achieves state-of-the-art accuracy with an overall mean reciprocal ranking (MRR) score of 0.763, compared to the best baseline result on the CodeSearchNet benchmark of 0.713. Our source code and experimental data are available at: https://github.com/fly-dragon211/TOSS.Comment: Accepted by WSDM 202

Residue Analysis and Exposure Assessment of Methylsiloxane Oligomers in Fried Chicken and French Fries

The fried food in fast food is deeply loved by consumers. However, with the increasing concern about the safety of volatile methylsiloxanes, the residue of oligomer monomer of methylsiloxanes from defoamer PDMS in fried food needs to be studied urgently. In this study, an efficient and sensitive method for the determination of methylsiloxane oligomers in fried chicken and French fries was established using QuEChERS-gas chromatography-tandem mass spectrometry (GC-MS/MS). A total of 33 fried chickens and 30 French fries purchased from fast food restaurants were analyzed and a preliminary exposure assessment using a point assessment method was carried out. The results showed that octamethyl cyclotetrasiloxane (D4)~hexamethyldisiloxane (D18) and decamethyl tetrasiloxane (L4)~triaconta methyltetradecasiloxane (L14) were detected, and the median total content of methylsiloxane oligomers in fried chicken (514.61 ng·g−1) was higher than that in French fries (83.4 ng·g−1). The estimated daily intake (EDI) of methylsiloxanes (molecular weight <1000) in fried chicken and French fries was 164.94 ng·kg−1·d−1 and 13.09 ng·kg−1·d−1, respectively, which was lower than the PDMS acceptable daily intake (ADI) (0.8 mg·kg−1·d−1). However, the potential hazards of some volatile methylsiloxanes such as D4~dodecamethyl cyclohexasiloxane (D6) need to be further investigated after long-term low dose intake and enrichment. This study provides a scientific basis for the safety evaluation and subsequent in-depth study of methylsiloxanes residues in fried food fast food