General Rule Research Articles

Deep learning model for optimizing control and planning in stochastic manufacturing environments

Within the context of Industry 4.0, manufacturing plants implement smart technologies, which adopt machine learning and deep learning, to identify manufacturing problems and provide sensible solutions to the experts. In literature, such applications have demonstrated high-performance in terms of feature extraction and big data analysis compared to typical machine learning methods. However, in the context of control and planning, the research efforts are still focused on integrating ad-hoc solutions, e.g., heuristic algorithms and deep reinforcement learning, thus making it difficult to generate general scheduling rules for manufacturing processes that could be easily applied to a variety of stochastic manufacturing systems. To this end, this paper considers a deep learning application for addressing the scheduling optimization problem in multi-stage stochastic manufacturing environments. The aim is the formulation of a predictive model that could derive suitable authorizations for activities under uncertainty. Findings demonstrate that the proposed predictive model generates policies that improve the performance of the integrated operations within manufacturing systems, constituting to efficient and sustainable manufacturing with effective material management and near-to-zero waste.

Commercial book keeping electronically according to Algerian Law - A comparativ study

Keeping the commercial books, one of the most important obligations of the merchant, its role is to determine his financial situation such as it used in proof. The law allows merchant to use computer technology to fulfill its accounting obligations, is indirectly recorded with using micro-films, or is done directly: when pounds or accountancy will be electronic with the aid of computer system in all stages of recording. The legal organization of this accounting defers between legislation that sets out provisions for the regulated and subjecting it to the general rules of traditional books-like the Algerian law-, and legislation to which certain provisions are applied, without the subjecting at the general dispositions of commercial code to hold pounds of trade-like the UAE law-. In spite of this difference, they are assimilated with books traditional in the field of proof. Key- words: the merchant, traditional trade books, electronic accounting, electronic support, computer system.

A semi-phenomenological dynamics model for full-life predictions of stress corrosion cracking

A semi-phenomenological model mimicking the full-time process of stress corrosion cracking (SCC) is proposed, and its attractive characteristics can be summarised as follows. Firstly, the role played by the hydrostatic pressure gradient at a crack tip in anodic dissolution is centralised by the proposed partial differential equation system, so as to formulate the interplay of load and corrosion in a mechanistic manner. As a result, the model can naturally reproduce the repeated film rupture mechanism that is believed central to general SCC phenomena. Secondly, the model implementation is extremely efficient, outputting a full-life SCC prediction within a few seconds on a normal laptop computer. Thirdly, a general rule for model calibration is introduced against limited experimental data, enabling its predictability over SCC indices that are not experimentally trackable. The efficacy and the generality of the proposed model are examined with three SCC scenarios, including (a) Inconel 600 alloys in nuclear pipelines, (b) stainless steels in oil pipelines, and (c) magnesium alloys used as structural materials in blood vessels. It is shown that SCC indices such as the SCC incubation period, which may be too long to be experimentally measured, can be quickly predicted with the present model after being calibrated.

Opacity enforcement in discrete event systems using differential privacy

Opacity is an important information security property that characterizes whether the secret of a system can be inferred by an intruder who can partially observe the behavior of the system. In this paper, we touch upon the enforcement of the current-state opacity and initial-state opacity of discrete event systems modeled by automata. Specifically, given a partially observed discrete event system that is not current-state opaque (resp., initial-state opaque), by observing the system's behavior, the intruder stands a chance to infer that the current state (resp., initial state) is within the secret of the system. To prevent the exposure of secret information, we introduce a differential privacy mechanism to enforce a non-opaque system to be opaque. Particularly, the designed mechanism is settled to receive the observations of the system. Suppose that there are two observations such that one of them can lead to the exposure of the secret and the other is randomly observed. When the two observations are received by the designed mechanism that provides differential privacy, a randomly modified output with an approximate probability is exported, exposing to the intruder. In this way, since the observation from which the secret can be inferred by the intruder, is befuddled with one randomly generated by the system, he/she is not able to deduce which one is truly generated and received by the mechanism, even if the probabilistic generation rule of the mechanism is public.

Olfactory trademarks: peculiarities of obtaining legal protection

The article is focuses on the research of issues concerning the acquisition of legal protection by olfactory trademarks. As a result of unceasing technological development, means of individualization in the marketing of services or products are acquiring new patterns of expression, in particular in the form of olfactory trademarks. Nowadays, the legislation of only a few countries provides for the possibility of obtaining legal protection for trademarks with this form of expression. It is obvious that with the further development of technology, the registration of olfactory trademarks is bound to become more widespread. This is due to the likelihood that technology will in the future be able to adequately transmit scents at a distance, based on its success over the past centuries in transmitting sound and images. However, since the transmission of scents at a distance by technological means is not currently provided for, the legislator faces a significant dilemma with respect to the legal protection of olfactory trademarks. Since, as a general rule, in order to obtain legal protection, a trademark must be represented in the register, the question arise how to represent olfactory trademark in the register in such a way in the same unambiguous and certain manner as other trademarks. The presence of this aspect which is caused by the specifics of olfactory trademarks naturally raises the question of the legal protection of such trademarks. Thus, the issue of legal protection of olfactory trademarks has thus been reflected the scientific legal doctrine. However, the absence of an unequivocal approach to the legal protection of olfactory trademarks requires further research on this issue. In this study the author examines the specifics of olfactory trademarks, the peculiarities of obtaining legal protection, and the legal approaches to ensuring legal protection of olfactory trademarks. In the course of the study, the author established the criteria for obtaining legal protection for olfactory trademarks and considered the prospects for granting legal protection to such trademarks in Ukraine.

Identifying diseases symptoms and general rules using supervised and unsupervised machine learning

The symptoms of diseases can vary among individuals and may remain undetected in the early stages. Detecting these symptoms is crucial in the initial stage to effectively manage and treat cases of varying severity. Machine learning has made major advances in recent years, proving its effectiveness in various healthcare applications. This study aims to identify patterns of symptoms and general rules regarding symptoms among patients using supervised and unsupervised machine learning. The integration of a rule-based machine learning technique and classification methods is utilized to extend a prediction model. This study analyzes patient data that was available online through the Kaggle repository. After preprocessing the data and exploring descriptive statistics, the Apriori algorithm was applied to identify frequent symptoms and patterns in the discovered rules. Additionally, the study applied several machine learning models for predicting diseases, including stepwise regression, support vector machine, bootstrap forest, boosted trees, and neural-boosted methods. Several predictive machine learning models were applied to the dataset to predict diseases. It was discovered that the stepwise method for fitting outperformed all competitors in this study, as determined through cross-validation conducted for each model based on established criteria. Moreover, numerous significant decision rules were extracted in the study, which can streamline clinical applications without the need for additional expertise. These rules enable the prediction of relationships between symptoms and diseases, as well as between different diseases. Therefore, the results obtained in this study have the potential to improve the performance of prediction models. We can discover diseases symptoms and general rules using supervised and unsupervised machine learning for the dataset. Overall, the proposed algorithm can support not only healthcare professionals but also patients who face cost and time constraints in diagnosing and treating these diseases.

AS DECISÕES DOS TRIBUNAIS E POSSÍVEIS SOLUÇÕES À GUARDA COMPARTILHADA EM CASOS DE VIOLÊNCIA DOMÉSTICA

This article analyzes how the issue of shared custody in cases of domestic violence has been approached and decided by Brazilian courts. The study covers legislation, doctrine and jurisprudence to understand the practical application of the relevant laws. The Civil Code of 2002 and Law 13,058/2014, which establish shared custody as a rule, are discussed, but the recent Law 14,713/2023 significantly changed the rules, prohibiting shared custody in cases of domestic violence. Historically, Brazilian civil legislation has always prioritized the protection of minors, establishing that custody can be unilateral or shared. Shared custody, where both parents have equal responsibilities and rights, was the general rule, except in specific cases such as domestic violence, where the law previously allowed sole custody when justified. With the introduction of Law 14,713/2023, shared custody was prohibited in situations of domestic violence. This legislative change aims to protect children and victims of violence, ensuring that the aggressor cannot have joint custody. The article cites court decisions that confirm the prevalence of shared custody as a general rule and exceptions in cases of violence. In summary, Law 14,713/2023 represents a significant advance by prohibiting shared custody in cases of domestic violence, reflecting the need to protect victims and guarantee the safety of children. The article concludes that, despite improvements, there are still challenges in applying and raising awareness of legal changes.

Contributory Fault in International Investment Arbitration

As a general rule, if a state commits a wrongful act, it is under an obligation to make full reparation for the injury caused. Yet, arbitral tribunals have used the doctrine of contributory fault to reduce the amount of damages awarded to the investor for the state’s breach of an investment treaty. This article analyses fifteen arbitration cases in which the respondent argued that the claimant contributed to its injury, either as a result of the investor’s bad business judgment or because the investor’s behaviour provoked the state’s wrongful conduct. The analysis shows that arbitral tribunals supported their decisions to reduce the amount of compensation by as much as 50% with strikingly brief reasoning and instead relied on their wide margin of discretion. The article discusses possible avenues to remedy deficiencies in arbitral practice dealing with contributory fault, both through the reform of investor-state dispute settlement and practical solutions that may be adopted by arbitral tribunals when considering allegations of contributory fault.

Activity evaluation and reaction mechanisms of highly efficient dual-atom transition metal catalysts in Li-CO2 batteries

Lithium-carbon dioxide (Li-CO2) batteries have received increased attention due to their high energy density and fixing CO2 as a major greenhouse gas. At the same time, there are challenges including low activity of cathode and high overpotential in Li-CO2 batteries. Herein, 45 dual-atom catalysts (DACs) composed of 9 transition metal (TM) atoms doped in nitrogen-doped graphene (M1M2-N-G, M1, M2 = Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn), as cathode catalysts of Li-CO2 batteries, have been studied by using first-principles calculations. According to the thermodynamic stability of the DACs and the ability of CO2 activation, 25 catalysts candidates were screened out. Then, the reaction activity and selectivity of DACs were evaluated by thermodynamical reaction energy and overpotential. Finally, TiMn-N-G displayed the smallest total electrode overpotential 1.83 V during the pathway of Li2CO3 and CrNi-N-G exhibited the smallest total electrode overpotential 0.08 V during the in Li2C2O4 pathway, respectively, which proved that they possessed better catalytic activity tendency in Li-CO2 batteries. This work provides not only a rational design to identify promising graphene-based catalysts, but also a general screen rule for atomic catalysts in Li-CO2 batteries.

En Route to Diastereopure Polycyclic γ‐Lactones by Iridium‐Catalyzed Hydride Transfer†

Comprehensive SummaryThe reductive lactonization strategy provides an efficient access to diastereoenriched polycyclic γ‐lactones. However, it is still a formidable challenge to develop an efficient and versatile protocol with excellent levels of diastereocontrol. Herein, we provide a highly diastereoselective and efficient route to diastereopure bi‐ and polycyclic γ‐lactones, by means of an iridium‐catalyzed hydride transfer strategy. This method features high levels of diastereocontrol, broad substrate scope, and high catalyst efficiency (S/C = up to 5000). Mechanistic studies suggest that the iridium hydride formation might be the rate‐determining step, and that the hydride transfer step be the diastereo‐determining step. The large steric hindrance of the iridium hydride species and intramolecular hydrogen bonding are critically key to the diastereocontrol of the hydride transfer process. From the perspectives of configurational analysis and Duniz angles of attack, the nature of diastereocontrol is well rationalized. A more general empirical rule based on facial selectivity analysis for explaining and predicting the stereochemistry is also proposed.

Prognostic significance of metastatic lymph node size and extra-nodal extension in papillary thyroid carcinoma according to the 9th edition of general rules for the description of thyroid cancer risk stratification: a single center validation study.

In the 9th edition of general rules for the description of thyroid cancer (GRDTC), the N factor was subdivided according to the maximum diameter of metastatic lymph nodes, presence of extra-nodal extension (ENE), and location of mediastinal lymph nodes. This study aimed to investigate the clinical usefulness of the 9th GRDTC risk stratification in papillary thyroid carcinoma (PTC) patients with lymph node metastasis. A total of 703 PTC patients with lymph node metastasis who underwent initial thyroidectomy at our institution between January 2000 and October 2023 were included. Among the 703 patients with PTC, the 10-year cause specific survival rates of patients with pN1a-1 (n = 383), pN1a-2 (n = 13), pN1b-1 (n = 234), and pN1b-2 (n = 73) were 97.9%, 100%, 95.4%, and 76.2%, respectively (p < 0.001). Therefore, the pN1b-2 classification identified patients with a worse prognosis among those with pN1b. Among the 664 patients with M0 PTC, the 10-year disease free survival (DFS) rates of the patients with pN1a-1 (n = 378), pN1a-2 (n = 13), pN1b-1 (n = 215), and pN1b-2 (n = 58) were 86.9%, 62.5%, 79.9%, and 59.4%, respectively (p < 0.001). The pN1b-2 category was associated with worse DFS in pN1b patients. The 9th edition of the GRDTC may be useful for stratifying the prognosis of patients with PTC. The risk assessment of PTC-related death and recurrence will be more accurate by considering the size of lymph node metastasis and ENE in GRDTC.

Kesehatan Mental Perempuan dan Sinergitas Kebijakan Kesehatan Mental di Indonesia Terhadap Norma Internasional

Indonesia is experiencing a mental health emergency. Mental health has long been an international norm thatratified by countries, including Indonesia. Global data and cases in Indonesia show that women suffer from more mental disorders than men. The causes of mental health disorders experienced by women come from biological factors due to hormonal changes, psychological reasons, social relationship, and the impact of environmental damage. So it is time for women's mental health to be given serious attention. Unfortunately, in this research found that Indonesia does not yet have specific regulations regarding mental health for women, only general rules that are implicitly stated in Law Number 17 of 2023 Article 76 that “everyone has the right to access mental health services that are safe, quality and affordable” also psychiatric research regarding mental disorders in Indonesia is still limited. Second, this research found that the contents of Article 76 do not match the reality on the ground which is still far from the goals. Third, the role of actors from femocrats, women's activists, and academics have built collaborative relationships through the formation of a cross-sector coordination forum, namely the Community Mental Health Steering Team (TPKJM) from the provincial, district/city and sub-districtlevels. Keywords: Women's Mental Health Indonesia; National Policy; International Norms; Velvet Triangles Concept,TPKJM.

Structure of epoxide hydrolase 2 from Mangifera indica throws light on the substrate specificity determinants of plant epoxide hydrolases

Epoxide hydrolases (EHs) are a group of ubiquitous enzymes that catalyze hydrolysis of chemically reactive epoxides to yield corresponding dihydrodiols. Despite extensive studies on EHs from different clades, generic rules governing their substrate specificity determinants have remained elusive. Here, we present structural, biochemical and molecular dynamics simulation studies on MiEH2, a plant epoxide hydrolase from Mangifera indica. Comparative structure-function analysis of nine homologs of MiEH2, which include a few AlphaFold structural models, show that the two conserved tyrosines (MiEH2Y152 and MiEH2Y232) from the lid domain dissect substrate binding tunnel into two halves, forming substrate-binding-pocket one (BP1) and two (BP2). This compartmentalization offers diverse binding modes to their substrates, as exemplified by the binding of smaller aromatic substrates, such as styrene oxide (SO). Docking and molecular dynamics simulations reveal that the linear epoxy fatty acid substrates predominantly occupy BP1, while the aromatic substrates can bind to either BP1 or BP2. Furthermore, SO preferentially binds to BP2, by stacking against catalytically important histidine (MiEH2H297) with the conserved lid tyrosines engaging its epoxide oxygen. Residue (MiEH2L263) next to the catalytic aspartate (MiEH2D262) modulates substrate binding modes. Thus, the divergent binding modes correlate with the differential affinities of the EHs for their substrates. Furthermore, long-range dynamical coupling between the lid and core domains critically influences substrate enantioselectivity in plant EHs.

Topological Interlocking Assembly: Introduction to Computational Architecture

Topological interlocking assembly (TIA) and computational architecture treat form as an emergent property of a material system, where the final shape results from the interplay of geometries and geometric interdependencies influenced by contextual constraints (material, structure, and fabrication). This paper posits that TIA is an ideal pedagogical tool for introducing students to computational architecture, and its theoretical foundations and design principles. Specifically, defining TIA as a material system provides a robust educational approach for engaging students with computation; fostering design processes through bottom-up, hands-on investigations; expressing design intents as procedural logic; understanding generative geometric rules; and exploring the flexibility of parametric variations. The methodology is detailed and illustrated through a design workshop and study unit from the Bachelor’s and Master’s programs at the Faculty for the Built Environment, University of Malta. Four case studies of TIA—of tetrahedra, cones, octahedra, and osteomorphic blocks—demonstrate how these exercises introduce students to computational thinking, parametric design, and fabrication techniques. This paper discusses the advantages and limitations of this pedagogical methodology, concluding that integrating computational architecture in education shifts students’ design processes to investigation and innovation-based approaches, enabling them to address contemporary design challenges through context-driven solutions.

Convergent expansions of keystone gene families drive metabolic innovation in a major eukaryotic clade.

Many remarkable innovations have repeatedly occurred across vast evolutionary distances. When convergent traits emerge on the tree of life, they are sometimes driven by the same underlying gene families, while other times many different gene families are involved. Conversely, a gene family may be repeatedly recruited for a single trait or many different traits. To understand the general rules governing convergence at both genomic and phenotypic levels, we systematically tested associations between 56 binary metabolic traits and gene count in 14,710 gene families from 993 species of Saccharomycotina yeasts. Using a recently developed phylogenetic approach that reduces spurious correlations, we discovered that gene family expansion and contraction was significantly linked to trait gain and loss in 45/56 (80%) of traits. While 601/746 (81%) of significant gene families were associated with only one trait, we also identified several 'keystone' gene families that were significantly associated with up to 13/56 (23%) of all traits. These results indicate that metabolic innovations in yeasts are governed by a narrow set of major genetic elements and mechanisms.

Vibration Control Solutions for Microscopy

Abstract Vibration is always present in our environment at some level. It can have a deleterious effect on all types of microscopes and should always be considered when installing a microscope in a facility. Some microscope manufacturers, particularly those who make charged electron or particle beam microscopes, have detailed vibration specifications; others do not. In this article we discuss sources of vibration, techniques for mitigating vibration, and some general rules about which types of vibration control to use based on the type of microscope being used.

Preambulum az idegenjogi szakigazgatás rendszerében

Aim: The aim of this paper is to present - in addition to the preambles of the legislation on alien policy from 1903 to the present day - the preamble of Act XC of 2023 on the General Rules for the Entry and Residence of Third-Country Nationals. Methodology: This study considers the practice of the specifications of the preambles of the legislations on the entry and residence of foreigners, and compares, according to grammatical and logical criteria, the certain sentences of the introductory text of Act XC of 2023 on the General Rules for the Entry and Residence of Third-Country Nationals with the normative provisions of this Act and other legislations, in particular the Fundamental Law of Hungary. Findings: The preamble of Act XC of 2023 on the General Rules for the Entry and Residence of Third-Country Nationals introduces the normative provisions of the Act with an unusual content compared to the legislation so far. This content cannot, however, be examined in isolation, but only in the light of the specific legal provisions (constitutional, statutory, regulatory) establishing rights and obligations. Value: The value of the study is to draw attention to the fact that in the system of legislation, only the specific provisions of individual pieces of legislation have normative force, and that the texts and preambles introducing individual pieces of legislation can contribute to the interpretation of these legislative provisions.

Machine learning technique for generation of human readable rules to detect software code smells in open-source software

Machine learning technique for generation of human readable rules to detect software code smells in open-source software

Nonlinear Multivariable System Identification: A Novel Method Integrating T-S Identification and Multidimensional Membership Functions

In this paper, a new multidimensional Takagi–Sugeno (T-S) identification technique is proposed for multivariable nonlinear systems. In this technique, multidimensional membership functions are designed using concepts from solid mechanics. The design of membership functions is carried out in multidimensional space, defining the principal axes from the eigenvectors of the inertia matrix, and it has the characteristic of dividing the space into regions with the same inertia. These regions are analyzed to define the center of gravity for each rule. Illustrative examples of multivariable nonlinear systems, such as a thermal mixing process and a binary distillation column, are selected to evaluate the effectiveness of the proposed method. The proposed method is compared with traditional T-S identification that uses one-dimensional membership functions and shows a reduction in the relative identification error and the algorithm execution time. Additionally, the proposed method prevents rules from being positioned outside the system’s range, thereby avoiding the generation of unnecessary rules.

Multiple factors-based damage level assessment method of concrete structures based on evidential reasoning and particle swarm optimization

Previous damage prediction methods of concrete structures usually fall into subjective and unreasonable assessments, which are usually limited to the special application scene with complex physical modeling depending on professional knowledges and experience. To overcome the above limitations, a multiple factors-based damage level assessment method of concrete structures is proposed based on evidential reasoning and particle swarm optimization. According to the method, multi-source data can be integrated for damage rules generation and quantitative damage level assessment automatically. The number and types of the used multi-source data can be chosen freely according to the special application scene. Finally, multi-source data including the normal strain in X-direction, normal strain in Y-direction, and the corresponding shear strain of two concrete structures under cyclic loads are utilized to verify the developed method. The results show that the damage level assessment results match well with the corresponding experimental results, which has a high reliability index based on the developed method. The ability of the method with good generality and flexibility is verified, which shows that the method can be used to achieve the reasonable damage level assessment of concrete structures.