Modification Rules Research Articles

Unveiling Crystal Structure Landscapes and Morphology Modification Rules of Substituted Benzophenone Crystals

Unveiling Crystal Structure Landscapes and Morphology Modification Rules of Substituted Benzophenone Crystals

Modification Rules for Improving Marching Cubes Algorithm to Represent 3D Point Cloud Curve Images

Modification Rules for Improving Marching Cubes Algorithm to Represent 3D Point Cloud Curve Images

Laboratory testing on cracking characteristics and improvement mechanism of coral mud

In recent years, the development and construction of island reefs have been flourishing. Due to the remoteness of island reefs from the mainland, the scarcity of building materials, and the high transportation costs, it is imperative to use local marine resources, and the potential value and status of coral mud on island reefs, which is formed by the remains of corals and other biological entities, is becoming increasingly prominent. Utilization and optimization of natural resources on island reefs have become a brand-new research direction and challenge. This article mainly focuses on the development of a new type of green engineering material, coral mud, for use in building surface layers. Thickness effects, PVA fiber (vinylon staple fiber) modification, and HPMC (Hydroxypropyl Methyl Cellulose) adhesive modification are taken into consideration. Through laboratory tests and image processing technology, fractal theory, and electron microscopy experiments, the macro-meso-microscopic multi-scale cracking rules of the coral mud surface layer and the optimization modification rules of PVA fibers and HPMC adhesives are revealed. The results demonstrate that the performance of the coral mud surface layer is superior to that of the kaolin surface layer, and the 10 mm thickness performs better than the 5 mm and 20 mm thicknesses. As the thickness of the coral mud surface layer increases, the contact between coral mud particles becomes denser, the scale of surface micro-cracks decreases, and the number of micro-pores decreases. PVA fibers can effectively inhibit the further development of macro and micro cracks and play a good bridging role. There is a bonding and adhesion relationship between coral mud and PVA fibers, and they have a good synergistic effect in inhibiting macro and mesoscopic cracks. With the increase in HPMC adhesive content, the number of micro-cracks and the scale of micro-cracks decrease accordingly, and the structure and performance of the coral mud surface layer are further improved. Overall, PVA fibers are more effective than HPMC adhesives in inhibiting the cracking of the coral mud surface layer. This provides valuable guidance for the development and application of coral mud in wall surface materials.

Consensus reaching process using personalized modification rules in large-scale group decision-making

Managing complex decision-making scenarios often hinges on the effectiveness of large-scale group decision-making (LSGDM). When confronted with a significant number of decision-makers (DMs) in LSGDM, each contributing unique backgrounds and perspectives, addressing the issues of reducing dimensionality and fostering consensus becomes a crucial aspect of the decision-making process. This paper addresses these challenges through several innovative approaches. First, we employ clustering methods to reduce the dimensionality of DMs. We introduce a novel fuzzy c-means clustering method that takes into account both the evaluation values and ranking of alternatives. This reduction in dimensionality serves to simplify the decision complexity and enhance the coherence of decision-related information among DMs placed within the same cluster. Once the clustering phase is complete, we propose a weight solution method for DMs within each group. This method combines the consensus level with the Spearman correlation coefficient of DMs, providing an effective means to determine the weights. Additionally, we introduce a weight solution method for each group based on the average consensus level and the number of DMs it contains. In the consensus reaching process (CRP), we implement a personalized modification rule. This rule takes into consideration the evolving consensus levels and the regret psychology exhibited by different DMs at different points in time. This dynamic approach significantly reduces both the cost and time required for consensus modifications. Finally, to validate the applicability of the proposed method, we apply it to a real-life case. Comprehensive qualitative and quantitative comparative analyses are conducted to evaluate the proposed method, along with a stability analysis of the parameters involved.

Change‐aware model checking for evolving concurrent programs based on Program Dependence Net

SummaryConcurrent software needs to be maintained over time, and the differences between continuous versions tend to be localized. The expense that simply reapplying standard model checking techniques to the new version as they evolve may be infeasible. The existing methods reuse partial state‐space to reduce the scope. However, it is obviously costly to analyze on the explosive interleaving space of the evolving concurrent programs. The conservative change‐impact analysis methods without considering the specific property and leveraging the verified result from the prior version often results in exploring redundant state‐space irrelevant to this property. Moreover, the impact of the deleted elements needs to be analyzed on old version, and their impact needs to be mapped to new version, bringing some dispensable costs. In this paper, we propose a change‐aware model checking method based on program dependence net (PDNet) for linear temporal logic (LTL). We first propose an incremental modeling method to construct a PDNet of new version by modification rules. Then, we propose a reuse checking algorithm to judge whether the verified result can be reused based on the PDNet slice. Finally, we implement change‐aware model checking tool (DAMER) and validate the advantages of our methods.

Review on Surface Modification of SnO2 Electron Transport Layer for High-Efficiency Perovskite Solar Cells

In the planar heterojunction perovskite solar cell (PSC) structure, among numerous contenders, tin oxide (SnO2) has been utilized, instead of TiO2, as the material for the electron transport layer (ETL) owing to its good band alignment, ultraviolet light resistance, strong charge extraction, and low photocatalytic activity. However, the morphology of the SnO2 ETL has proven to be unstable under low-temperature processing, leading to low electron extraction in PSCs. Therefore, the surface morphology must be modified to achieve high-performance PSCs. In this review, we provide an overview of the fundamental insights into how surface variations affect the ETL performance. The significance and the design rule of surface modification for an efficient SnO2 ETL, that is, the intentional alteration of the SnO2 interface, are discussed. Based on the evaluations, distinct surface engineering procedures and how they are implemented are presented. The effects of chemical and physical interactions on the properties of SnO2 are elucidated in detail; these have not been considered in previous studies. Finally, we provide an outlook on, highlight the key challenges in, and recommend future research directions for the design of the interfaces of highly efficient and stable PSCs.

Customs binding information decisions according to the law of Canada: peculiarities and lessons for European countries

The purpose of this research is to determine the peculiarities of the legal framework for scope of subject matter and rules for issuing, modification or revocation of customs advance rulings (customs binding information decisions) from the point of view of prospects of their implementation by European countries to further improve the effectiveness of this mean of customs administration within their jurisdictions. The methodological basis of the study comprises of comparative review methods as well as systematic review methods and standard techniques of text analysis with their due adjustment to legislative material. Results: the author studied Canadian legislation making provision for the scope of matters for national customs ruling (customs binding information decisions), the grounds and legal consequences of their modification and revocation or cancellation, including their ultra-active use through postponement of the effective date of the modification or revocation, as well as the procedure for publishing of national customs rulings for ensuring the uniformity of the conclusions of customs authorities expressed in them. The particular attention is attached to those rules and regulations that could serve as a comparative legal basis for the improvement of parts of customs legislation of European countries, which concern customs binding information decisions. Conclusions: in light of the purpose of this research of particular interest are the Canadian legislative solutions concerning: 1) establishing the need for the applicant to indicate in his application for the issuance of a national customs ruling, whether to the best of their knowledge the respective issue was the subject of another/separate request for a national customs ruling, administrative or judicial appeal, which are as grounds for suspending (postponing) consideration of the request for the issuance of a national customs ruling; 2) the grounds for the occurrence of retrospective legal consequences of the modification or revocation of a national customs ruling in relation to goods imported into the customs territory before its modification or revocation; 3) determination for the purposes of ultra-active use (postponement of the effective date of the modification or revocation) of the national customs ruling, which exactly is considered to be the evidence of reliance on the national customs ruling in good faith; 4) formation of a publicly available online repository of national customs rulings to promote the uniformity and transparency of customs administration, as well as the introduction of information and telecommunication tools for submission of requests for national customs rulings, their further implementation, as well as for notification of interested parties regarding changes in their status and other issues, relating to the circulation of national customs rulings.

Insight on the meat quality and carbonylation profile of breast muscle of broilers in response to chronic heat stress: A proteomic research

This study was conducted to explore the influences of carbonyl modification on proteins within the breast muscle of heat-stressed broilers and their correlations to decreased meat quality. The results showed that birds that suffered from heat stress had higher lightness, drip loss, shear force value, and hardness, and lower redness and springiness of breast meat than those under normal control and pair fed treatments. Proteomic analysis identified a total of 921 differentially carbonylated sites, which were allocated to 419 proteins. The modified sites included Lys, Pro, Arg, Trp, Cys, His, and Met. Seven motif sequences were detected, where five motifs neighbored Lys and two neighbored Pro. The differentially carbonylated proteins in heat-stressed birds mainly participated in the glycolytic process, collagen fibril organization, calcium homeostasis, and apoptosis. This study provided a unique landscape of the muscular carbonyl modification rule and unraveled the potential impact of carbonylated protein on meat quality.

Hybrid threshold event-triggered control for sail-assisted USV via the nonlinear modified LVS guidance

This paper presents an adaptive event-triggered control algorithm for sail-assisted unmanned surface vehicle (USV) under nonlinear modified logic virtual ship (LVS) guidance, which addresses the issues of communication load and input saturation constraint. In guidance module, the reference signal generated by LVS guidance is further processed by nonlinear modification rules. That can effectively remove the abrupt phenomenon of actuators. In the control module, a robust adaptive control technique for sail-assisted USV is proposed by fusing adaptive compensation technology and hybrid threshold event-triggered. Unnecessary transmission is reduced between controller and actuator by constructing hybrid threshold event-triggered mechanism. Different from most existing event-triggered mechanism with fixed threshold parameters, threshold parameters in hybrid threshold event-triggered are dynamically adjusted according to the demands of the controller. Furthermore, the compensation effect of sail on the dynamic mechanism is considered. Adaptive parameters of rudder and propeller are constructed to improve the robustness of the closed-loop system. Finally, the theoretical stability of the proposed method is proved by Lyapunov stability theorem, and the control performance is evaluated by simulation platform, which verifies that the scheme has reliable tracking accuracy under time-varying disturbances.

Article: Pillar 2, Tax Competition, and Low Income Sub-Saharan African Countries

This article explores the implications of Pillar 2 of the G20/OECD Inclusive Framework Blueprint for global tax reform on tax incentives and tax competition in the countries of Sub-Saharan Africa (SSA). It addresses both the impact of the minimum effective tax developed under the Global Anti-Base Erosion (GloBE) model rules, and of the Subject to Tax Rule (STTR) for limited modification of existing bi-lateral tax treaties between SSA countries and various treaty partners. In the GloBE context the article examines the interaction of the substance-based income exclusion (SBIE), the qualified domestic minimum tax (DMT) and existing domestic turnover based minimum taxes in the region, and the proposed qualified refundable tax credit (QRTC) rules. In regard to the STTR it looks at the incentives, or lack thereof, for treaty renegotiation in the existing context of multi-national tax planning and income stripping. The article concludes that SSA countries should, if Pillar 2 is ultimately implemented by a critical mass of advanced countries, adopt the qualified domestic minimum top up tax (QDMTT), as proposed in the December 2021 promulgation of the detailed GloBE rules. The benefits of other actions, such as the adoption of QRTCs, or treaty renegotiation under the proposed STTR, are more ambiguous. Pillar 2 would introduce important fundamental changes to the international tax architecture, through agreement, at least, that there should be some limits on tax competition and profit shifting. It is, though, a far cry from the 15% minimum tax on corporate profits generally portrayed. The highly complex exceptions and structure explored in the article illustrate both the technical and political difficulties involved in attempting to stem the erosion of the global corporate profits tax. Corporate tax, International tax, Minimum taxation, Pillar 2

Consensus Model Driven by Interpretable Rules in Large-Scale Group Decision Making With Optimal Allocation of Information Granularity

In group decision making (GDM), consensus level is regarded as a critical criterion to measure the effectiveness and availability of the final group decision solution. Consensus model is aimed at conducting the decision group to reach agreement through the process of group negotiation, advice feedback, and opinion modification, which is time-consuming and rests with the willingness and behavior of individual decision makers. Thus, to guide the shift in the opinions of decision makers within a limited time, it is essential to design an effective, interpretable, and fair consensus mechanism in GDM, which is particularly vital when a mass of decision makers (e.g., more than 30) are involved in the decision process, viz., we encounter a large-scale GDM (LSGDM). With the involvement of information granulation, this study presents a rule-based consensus model in LSGDM by optimally allocating the level of information granularity to each decision maker. The opinions of decision makers in LSGDM are divided into different clusters by engaging the fuzzy <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$C$ </tex-math></inline-formula> -means method. Inspired by a generic fuzzy rule-based model, the radius of the individual preference granule (PG) is calculated by a weighted linear combination of the granularity levels allocated to the clusters. Then, a consensus model with the optimal allocation of information granularity (CMOIG) is built to determine the granularity level for each cluster by minimizing the sum of radii of individual PG. An interactive consensus reaching process is proposed with the proposed CMOIG and fuzzy modification rules. The CMOIG and fuzzy modification rules simultaneously guarantees high efficiency and interpretability, and the generation method of PGs leads to high fairness due to low discrepancy among the decision group. Finally, numerical and comparative experiments are conducted in detail to verify the validity and superiority of the presented models in terms of the efficiency, interpretability, and fairness.

Internality of averaged Gauss quadrature rules for certain modification of Jacobi measures

Internality of averaged Gauss quadrature rules for certain modification of Jacobi measures

Dose modification rules and availability of growth factor support: A cross-sectional study of head-to-head cancer trials used for US FDA approval from 2009 to 2021

Aim of the studyDifferent drug modification rules or growth factor support guidance may affect the results in oncology randomised controlled trials. We aimed to estimate the prevalence of unequal rules for dose modification rules or the use of myeloid growth factors in head-to-head registration Food and Drug Administration trials. MethodsThis cross-sectional analysis included all head-to-head registration randomised controlled trials leading to a US Food and Drug Administration approval between 2009 and 2021. Trials examined anti-cancer drugs in the advanced or metastatic setting where a comparison could be made between arms regarding either dose modification rules or myeloid growth factors recommendations. Sixty-two registration trials met inclusion criteria. Information abstracted for each trial included tumour type, setting, phase, and type of sponsor. We assessed, according to pre-specified rules, imbalance in drug modification rules, myeloid growth factors recommendations or both. ResultsWe find 40 of 62 (65%) selected trials have unequal rules for dose medication, granulocyte colony-stimulating factor (G-CSF) use or both. Six trials (10%) had rules favouring the control arm, while 55% of selected trials (34/62) favoured the experimental arm. Among these, 50% (17/34) had unequal drug modification rules, 41% (14/34) had unequal G-CSF rules and 9% contained both (3/34). ConclusionWe find that 55% of trials testing anti-cancer drugs against each other used protocol rules that favoured the experimental arm. This leaves open the question of whether new molecules are truly superior to older molecules or if instead different outcomes are due to more aggressive dosing or growth factor support. Trials should utilise equal rules for dose medication and G-CSF support.

Information-based massive data retrieval method based on distributed decision tree algorithm

Based on the distributed decision tree algorithm, this paper first proposes a method of vertically partitioning datasets and synchronously updating the hash table to establish an information-based mass data retrieval method in a heterogeneous distributed environment, as well as using interval segmentation and interval filtering technologies for improved algorithm of distributed decision tree. The distributed decision tree algorithm uses the attribute histogram data structure to merge the category list into each attribute list, reducing the amount of data that needs to reside in the memory. Second, we adopt the strategy of vertically dividing the dataset and synchronously updating the hash table, select the hash table entries that can be used to update according to the minimum Gini value, modify the corresponding entries and use the hash table to record and control each sub-site. In the case of node splitting, it has a high accuracy rate. In addition, for classification problems that meet monotonic constraints in a distributed environment, this paper will extend the idea of building a monotonic decision tree in a distributed environment, supplementing the distributed decision tree algorithm, adding a modification rule and modifying the generated nonmonotonic decision tree to monotonicity. In order to solve the high load problem of the privacy-protected data stream classification mining algorithm under a single node, a Storm platform for the parallel algorithm PPFDT_P based on the distributed decision tree algorithm is designed and implemented. At the same time, considering that the word vector model improves the deep representation of features and solves the problem of feature high-dimensional sparseness, and the iterative decision tree algorithm GBDT model is more suitable for non-high-dimensional dense features, the iterative decision tree algorithm will be integrated into the word vector model (GBDT) in the data retrieval application, using the distributed representation of words, namely word vectors, to classify short messages on the GBDT model. Experimental results show that the distributed decision tree algorithm has high efficiency, good speed-up and good scalability, so that there is no need to increase the number of datasets at each sub-site at any time. Only a small number of data items are inserted. By splitting some leaf nodes, a small amount is added by branching to achieve a monotonic decision tree. The proposed system achieves a massive data ratio of 54.1% while compared with other networks of massive data ratio.

A Tool for Supporting Conceptual Design of Multiple State Mechanical Devices

Research into conceptual design of mechanical systems has evolved as an area of interest since last few decades. Conceptual design plays a significant role as an early stage of design to produce designs with higher quality by economically exploring a larger solution space. Several attempts have been made by researchers to automate the conceptual design synthesis process using computer support. However, most of that work has been focused on single state design problems. This paper deals with multiple state mechanical design problems and proposes a systematic method for synthesizing a larger solution space. A web-based tool is developed to guide designers through the step-by-step synthesis process by providing automated retrieval of initial solution proposals and modification rules.

The Role of Intermittent Energy Restriction Diet on Metabolic Profile and Weight Loss among Obese Adults.

Obesity is a disease defined by an elevated body mass index (BMI), which is the result of excessive or abnormal accumulation of fat. Dietary intervention is fundamental and essential as the first-line treatment for obese patients, and the main rule of every dietary modification is calorie restriction and consequent weight loss. Intermittent energy restriction (IER) is a special type of diet consisting of intermittent pauses in eating. There are many variations of IER diets such as alternate-day fasting (ADF) and time-restricted feeding (TRF). In the literature, the IER diet is known as an effective method for bodyweight reduction. Furthermore, IER diets have a beneficial effect on systolic or diastolic pressure, lipid profile, and glucose homeostasis. In addition, IER diets are presented as being as efficient as a continuous energy restriction diet (CER) in losing weight and improving metabolic parameters. Thus, the IER diet could present an alternative option for those who cannot accept a constant food regimen.

Machine learning approaches to optimize small-molecule inhibitors for RNA targeting

In the era of data science, data-driven algorithms have emerged as powerful platforms that can consolidate bioisosteric rules for preferential modifications on small molecules with a common molecular scaffold. Here we present complementary data-driven algorithms to minimize the search in chemical space for phenylthiazole-containing molecules that bind the RNA hairpin within the ribosomal peptidyl transferase center (PTC) of Mycobacterium tuberculosis. Our results indicate visual, geometrical, and chemical features that enhance the binding to the targeted RNA. Functional validation was conducted after synthesizing 10 small molecules pinpointed computationally. Four of the 10 were found to be potent inhibitors that target hairpin 91 in the ribosomal PTC of M. tuberculosis and, as a result, stop translation.Graphical

A Multi-Stage Approach Combining Very High-Resolution Satellite Image, GIS Database and Post-Classification Modification Rules for Habitat Mapping in Hong Kong

Identification and mapping of various habitats with sufficient spatial details are essential to support environmental planning and management. Considering the complexity of diverse habitat types in a heterogeneous landscape, a context-dependent mapping framework is expected to be superior to traditional classification techniques. With the aim to produce a territory-wide habitat map in Hong Kong, a three-stage mapping procedure was developed to identify 21 habitats by combining very-high-resolution satellite images, geographic information system (GIS) layers and knowledge-based modification rules. In stage 1, several classification methods were tested to produce initial results with 11 classes from a WorldView-2/3 image mosaic using a combination of spectral, textural, topographic and geometric variables. In stage 2, modification rules were applied to refine the classification results based on contextual properties and ancillary data layers. Evaluation of the classified maps showed that the highest overall accuracy was obtained from pixel-based random forest classification (84.0%) and the implementation of modification rules led to an average 8.8% increase in the accuracy. In stage 3, the classification scheme was expanded to all 21 habitats through the adoption of additional rules. The resulting habitat map achieved &gt;80% accuracy for most of the evaluated classes and &gt;70% accuracy for the mixed habitats when validated using field-collected points. The proposed mapping framework was able to utilize different information sources in a systematic and controllable workflow. While transitional mixed habitats were mapped using class membership probabilities and a soft classification method, the identification of other habitats benefited from the hybrid use of remote-sensing classification and ancillary data. Adaptive implementation of classification procedures, development of appropriate rules and combination with spatial data are recommended when producing an integrated and accurate map.

LILLIE: Information extraction and database integration using linguistics and learning-based algorithms

Querying both structured and unstructured data via a single common query interface such as SQL or natural language has been a long standing research goal. Moreover, as methods for extracting information from unstructured data become ever more powerful, the desire to integrate the output of such extraction processes with “clean”, structured data grows. We are convinced that for successful integration into databases, such extracted information in the form of “triples” needs to be both (1) of high quality and (2) have the necessary generality to link up with varying forms of structured data. It is the combination of both these aspects, which heretofore have been usually treated in isolation, where our approach breaks new ground.The cornerstone of our work is a novel, generic method for extracting open information triples from unstructured text, using a combination of linguistics and learning-based extraction methods, thus uniquely balancing both precision and recall. Our system called LILLIE (LInked Linguistics and Learning-Based Information Extractor) uses dependency tree modification rules to refine triples from a high-recall learning-based engine, and combines them with syntactic triples from a high-precision engine to increase effectiveness. In addition, our system features several augmentations, which modify the generality and the degree of granularity of the output triples. Even though our focus is on addressing both quality and generality simultaneously, our new method substantially outperforms current state-of-the-art systems on the two widely-used CaRB and Re-OIE16 benchmark sets for information extraction.We have made our code publicly available11https://github.com/OIELILLIE/LILLIE. to facilitate further research.

Gene editing with CRISPR-Cas12a guides possessing ribose-modified pseudoknot handles

CRISPR-Cas12a is a leading technology for development of model organisms, therapeutics, and diagnostics. These applications could benefit from chemical modifications that stabilize or tune enzyme properties. Here we chemically modify ribonucleotides of the AsCas12a CRISPR RNA 5′ handle, a pseudoknot structure that mediates binding to Cas12a. Gene editing in human cells required retention of several native RNA residues corresponding to predicted 2′-hydroxyl contacts. Replacing these RNA residues with a variety of ribose-modified nucleotides revealed 2′-hydroxyl sensitivity. Modified 5′ pseudoknots with as little as six out of nineteen RNA residues, with phosphorothioate linkages at remaining RNA positions, yielded heavily modified pseudoknots with robust cell-based editing. High trans activity was usually preserved with cis activity. We show that the 5′ pseudoknot can tolerate near complete modification when design is guided by structural and chemical compatibility. Rules for modification of the 5′ pseudoknot should accelerate therapeutic development and be valuable for CRISPR-Cas12a diagnostics.