Simple Program Research Articles

Flatland: abelian extensions of the Standard Model with semi-simple completions

We parametrise the space of all possible flavour non-universal mathfrak{u} (1)X extensions of the Standard Model that embed inside anomaly-free semi-simple gauge theories, including up to three right-handed neutrinos. More generally, we parametrise all abelian extensions (i.e. by any number of mathfrak{u} (1)’s) of the SM with such semi-simple completions. The resulting space of abelian extensions is a collection of planes of dimensions ≤ 6. Numerically, we find that roughly 2.5% of anomaly-free mathfrak{u} (1)X extensions of the SM with a maximum charge ratio of ±10 can be embedded in such semi-simple gauge theories. Any vector-like anomaly-free abelian extension embeds (at least) inside mathfrak{g} = mathfrak{su} (12) ⊕ mathfrak{su} (2)L ⊕ mathfrak{su} (2)R. We also provide a simple computer program that tests whether a given mathfrak{u}{(1)}_{X^1} ⊕ mathfrak{u}{(1)}_{X^2} ⊕ . charge assignment has a semi-simple completion and, if it does, outputs a set of maximal gauge algebras in which the mathfrak{sm} ⊕ mathfrak{u}{(1)}_{X^1} ⊕ mathfrak{u}{(1)}_{X^2} ⊕ . model may be embedded. We hope this is a useful tool in pointing the way from mathfrak{sm} ⊕ mathfrak{u}{(1)}_{X^1} ⊕ mathfrak{u}{(1)}_{X^2} ⊕ . models, which have many phenomenological uses, to their unified gauge completions in the ultraviolet.

Programming Techniques for Considering m Desired Conditions from n Possible Conditions

The performance of computer programs (or the hardware that can be programmed such as IoTs, embedded computers, and PLCs) is generally based on the complexity of the particular program development technique. High complexity often uses more execution times and system resources. For this reason, the computer program is less computational complexity to be desired. The conditional statements tell computers what certain information is a major cause of computer program complexities, e.g., considering m desired conditions from n possible conditions. To achieve this aim in computer programs, the data combination is often utilized. However, it is high complexity. Moreover, they cannot give that one condition takes precedence over others. To rid these vulnerabilities of combined conditions, a simple programming technique for considering m desired conditions from n possible conditions is proposed in this work, which is based on the summation of the condition weights. It only has the complexity of search spaces and data constructions to be O(n) and each condition can be set to be different precedence from the others. Furthermore, the proposed technique is evaluated by extensive experiments. From the experimental results, they indicate that the proposed technique is more effective and efficient than the comparative technique.

CCIVR facilitates comprehensive identification of cis-natural antisense transcripts with their structural characteristics and expression profiles

Cis-natural antisense transcripts (cis-NATs) are transcribed from the same genomic locus as their partner gene but from the opposite DNA strand and overlap with the partner gene transcript. Here, we developed a simple and convenient program termed CCIVR (comprehensive cis-NATs identifier via RNA-seq data) that comprehensively identifies all kinds of cis-NATs based on genome annotation with expression data obtained from RNA-seq. Using CCIVR with genome databases, we demonstrated total cis-NAT pairs from 11 model organisms. CCIVR analysis with RNA-seq data from parthenogenetic and androgenetic embryonic stem cells identified well-known imprinted cis-NAT pair, KCNQ1/KCNQ1OT1, ensuring the availability of CCIVR. Finally, CCIVR identified cis-NAT pairs that demonstrate inversely correlated expression upon TGFβ stimulation including cis-NATs that functionally repress their partner genes by introducing epigenetic alteration in the promoters of partner genes. Thus, CCIVR facilitates the investigation of structural characteristics and functions of cis-NATs in numerous processes in various species.

Beyond the quadratic norm: Computationally efficient constrained nonlinear MPC using a custom cost function

A new approach to nonlinear Model Predictive Control (MPC) is discussed in this work. A custom user-defined cost function is used in place of the typically considered quadratic norm. An approximator of the cost function is applied to obtain a computationally simple procedure and linearization of two trajectories is carried out online. The predicted output trajectory of the approximator and the predicted trajectory of the manipulated variable, both over the prediction horizon, are repeatedly linearized online. It yields a simple quadratic programming task. The algorithm is implemented for a simulated neutralization benchmark modeled by a neural Wiener model. The resulting control quality is excellent, identical to that observed in the MPC scheme with nonlinear optimization. Validity of the described MPC algorithms is demonstrated when only simple box constraints are considered on the process input variable and in a more demanding case when additional soft limitations are put on the predicted output. Two structures of the approximator are compared: polynomial and neural; the advantages of the latter one are shown and stressed.

A computational design of a programmable biological processor

Basic synthetic information processing structures, such as logic gates, oscillators and flip-flops, have already been implemented in living organisms. Current implementations of these structures have yet to be extended to more complex processing structures that would constitute a biological computer. We make a step forward towards the construction of a biological computer. We describe a model-based computational design of a biological processor that uses transcription and translation resources of the host cell to perform its operations. The proposed processor is composed of an instruction memory containing a biological program, a program counter that is used to address this memory, and a biological oscillator that triggers the execution of the next instruction in the memory. We additionally describe the implementation of a biological compiler that compiles a sequence of human-readable instructions into ordinary differential equation-based models, which can be used to simulate and analyse the dynamics of the processor. The proposed implementation presents the first programmable biological processor that exploits cellular resources to execute the specified instructions. We demonstrate the application of the described processor on a set of simple yet scalable biological programs. Biological descriptions of these programs can be produced manually or automatically using the provided compiler.

A distributed object-oriented simulator framework for marine power plants with weak power grids

ABSTRACT In this work, we discuss and demonstrate how multi-engine marine power plants with weak power grids efficiently can be set up and simulated in a distributed co-simulation framework. To facilitate configuration switching such as starting and stopping, connecting and disconnecting arbitrary gensets online, the generator models are modelled as hybrid causality component models. This implementation enables seamless and energy conservative model switching. Also, the proposed simulator framework is scalable such that the number of gensets in the power plant can be set by a single parameter, which automatically scales the power management system and the tailored simulator master algorithm accordingly. To control the number of active gensets being connected to the power grid while running the simulation, a simple mixed integer linear programming formulation is proposed. A simulation case study including a marine power plant configuration with four equal-sized gensets is conducted in the end to demonstrate the features of the proposed simulator framework, which also can be applied to, e.g. a small wind farm, or an isolated number of islands with interconnected power generators.

Analysis of Generalization of a Problem of Vieta’s Descend Method with Examples and Computing Support

Let and be fixed integer numbers. Assume that (a2+b2+c) is divisible by (ab+d) for some natural numbers a and b. Then the value of the fraction $$k ( = {(a^2+b^2+c) \over (ab+d)})$$ remains the same. Statement of this kind will be proved in pp. 1-3 and illustrated on some examples in pp. 3-10. The general method of proofs will be unified and simplified. Computing support will be provided: in pages 11-19 a simple program code is defined with the help of which one can hunt for natural numbers a, b with the same integer values of c, d and k. Here, a number of examples are given as well.

Pathfinder Networks for Measuring Operator Mental Model Structure with a Simple Autopilot System

Pathfinder networks are a method to represent mental models from empirically generated pairwise relatedness ratings. This study examined the effects of training exposure on mental model structures based on relatedness ratings collected using the Target Rating method. Forty-eight participants read instruction slides with or without explicit information on the functionality of an autopilot system (Advanced Mental Model or Basic Mental Model groups, respectively). Participants provided relatedness ratings and completed a comprehension test. The Advanced Mental Model group had more common links with the expected model, higher within-group network similarity scores, and higher mental model assessment questionnaire scores than the Basic Mental Model group. Both groups had coherence scores above the minimum threshold for internal consistency. Pathfinder network analysis was sensitive to changes produced by a simple exposure training intervention. In practice, a simple training program may effectively influence operator mental models in novel technological environments such as Advanced Air Mobility.

Developing programming language with compilers using JFlex in NetBean: Expanding and testing simple operators by implementing a calculator

Abstract: JFlex is a lexical analyzer generator and takes input requirements with a set of regular expressions and corresponding actions. It creates a program (a lexer) that reads input, matches the input against the regular expressions, and runs the matching action. This paper shows how Programming Language can be developed. This work was done to develop a simple programming language with compilers using JFlex in NetBean so that it can support assignment statements, if then else, while do and type checking and its execution. The data type included are int, real, char, and Boolean/String. The key concept used in this work was the execution of the grammar or rules in the cup file. The parse tree records a sequence of rules the parser applies to recognize the input. The tool used for the development of lexical analyzers was JFlex. JFlex Lexers was based on deterministic finite automata (DFAs). To show the implementation and working of operators, a simple calculator was designed that supports addition and multiplication operations. Further, the key compiler concepts like lexical analyzers, semantic analysis, and parse trees are discussed. This paper will help understand the syntax and way to develop simple language. For the programming language developed, the evaluations of the expressions and statements are recursively done. Type checking and Error checking are also done where two operands are checked for their compatibility with the operator and are shown if incompatible expressions are found.

ModelCraft: an advanced automated model-building pipeline using Buccaneer.

Interactive model building can be a difficult and time-consuming step in the structure-solution process. Automated model-building programs such as Buccaneer often make it quicker and easier by completing most of the model in advance. However, they may fail to do so with low-resolution data or a poor initial model or map. The Buccaneer pipeline is a relatively simple program that iterates Buccaneer with REFMAC to refine the model and update the map. A new pipeline called ModelCraft has been developed that expands on this to include shift-field refinement, machine-learned pruning of incorrect residues, classical density modification, addition of water and dummy atoms, building of nucleic acids and final rebuilding of side chains. Testing was performed on 1180 structures solved by experimental phasing, 1338 structures solved by molecular replacement using homologues and 2030 structures solved by molecular replacement using predicted AlphaFold models. Compared with the previous Buccaneer pipeline, ModelCraft increased the mean completeness of the protein models in the experimental phasing cases from 91% to 95%, the molecular-replacement cases from 50% to 78% and the AlphaFold cases from 82% to 91%.

Enabling Community Curation of Biological Source Annotations of Molecular Data Through PlutoF and the ELIXIR Contextual Data Clearinghouse

The advancements in sequencing technologies have greatly contributed to the documentation of Earth’s biodiversity. However, for exploring the full potential of molecular resources for biodiversity, there needs to be a good linkage between sequence data and its biological source, contributing to a network of connected data in the biodiversity research cycle. This requires a foundation of well-structured and accessible annotations in the molecular sequence repositories. The International Nucleotide Sequence Database Collaboration (INSDC), of which the European Nucleotide Archive (ENA) is its European node, holds a large amount of annotations associated with sequence data, relating to its biological source (e.g., specimens in natural history collections). However, for a number of records, these annotations may be incomplete (e.g., missing voucher information), ambiguous or even inaccurate. Therefore, we have implemented a workflow that allows third-party annotations to be attached to sequence and sample records using two existing services, the PlutoF platform and the ELIXIR Contextual Data ClearingHouse. This work was developed within the scope of the BiCIKL (Biodiversity Community Integrated Knowledge Library) project, which aims to establish open science practices in the biodiversity domain. PlutoF is an online data management platform that also provides computing services for biology-related research. PlutoF features allow registered users to enter their own data and access public data at INSDC. Users can enter and manage a range of data, as taxonomic classifications, occurrences, etc. This platform also includes a module that allows the addition of third-party annotations (on material source, taxonomic identification, etc.) linked to specimens or sequence records. This module was already in use by the UNITE community for annotation of INSDC rDNA Internal Transcribed Spacer sequence datasets (Abarenkov et al. 2021). These UNITE annotations are displayed in the National Centre for Biotechnology Information (NCBI) records through links to the PlutoF platform. However, there was the need for an automated solution that allowed third-party annotations to any sequence or sample record at INSDC. This was implemented through the operation of the ELIXIR Contextual Data ClearingHouse (hereafter as Clearinghouse). The Clearinghouse holds a simple RESTful Application Programming Interface (API) to support the submission of additions and improvements to current metadata attributes, such as information on material sources, on records publicly available in the ELIXIR data resources. The Clearinghouse enables the submission of these corrected metadata from databases (such as the PlutoF platform) to the primary data repositories. The workflow developed is shown in Fig. 1 and consists of the following steps: i) users annotate sequence metadata that is regularly downloaded from INSDC using NCBI’s E-utilities; ii) an annotation proposal is created and a verification notification is sent to an assigned reviewer; iii) the reviewer evaluates the annotation proposal and accepts it or rejects it with comments; iv) if the annotation proposal is accepted, the annotated fields that may be mapped to ENA fields are then pushed to the Clearinghouse using their RESTful API. The annotations when received at ENA are then reviewed before being displayed. This workflow is implemented through a web interface in PlutoF, which allows user-friendly and effortless reporting of corrections or additions to biological source metadata in sequence records. Overall, we expect this tool to contribute to the enrichment of metadata associated with sequence records, and therefore increase the links between the molecular and biodiversity resources, and enable sequencing data to deliver their full potential for biodiversity conservation.

A parametric neutrosophic model for the solid transportation problem

PurposeThis research attempts to present a solid transportation problem (STP) mechanism in uncertain and indeterminate contexts, allowing decision makers to select their acceptance, indeterminacy and untruth levels.Design/methodology/approachDue to the lack of reliable information, changeable economic circumstances, uncontrolled factors and especially variable conditions of available resources to adapt to the real situations, the authors are faced with a kind of uncertainty and indeterminacy in constraints and the nature of the parameters of STP. Therefore, an approach based on neutrosophic logic is offered to make it more applicable to real-world circumstances. In this study, the triangular neutrosophic numbers (TNNs) have been utilized to represent demand, transportation capacity, accessibility and cost. Then, the neutrosophic STP was converted into an interval programming problem with the help of the variation degree concept. Then, two simple linear programming models were extracted to obtain the lower and upper bounds of the optimal solution.FindingsThe results reveal that the new model is not complicated but more flexible and more relevant to real-world issues. In addition, it is evident that the suggested algorithm is effective and allows decision makers to specify their acceptance, indeterminacy and falsehood thresholds.Originality/valueUnder the transportation literature, there are several solutions for TP and STP in crisp, fuzzy set (FS) and intuitionistic fuzzy set (IFS) conditions. However, the STP has never been explored in connection with neutrosophic sets to the best of the authors’ knowledge. So, this work tries to fill this gap by coming up with a new way to solve this model using NSs.

Polynomial Time Reachability Analysis in Discrete State Chemical Reaction Networks Obeying Conservation Laws

In this paper the reachability problem of discrete state Chemical Reaction Networks (d-CRNs) is studied. We consider sub-classes of sub-and superconservative d-CRN network structures and prove that the reachability relation can be decided in polynomial time. We make use of the result that in the studied d-CRN sub-classes, the reachability relation is equivalent to the existence of a non-negative integer solution of the d-CRN state equation. The equivalence implies the reformulation of the reachability problem as integer linear programming decision problem. We show that in the studied classes of d-CRN structures, the state equation has a totally unimodular coefficient matrix. As the reachability relation is equivalent to the non-negative integer solution of the state equation, the resulting integer programming decision program can be relaxed to a simple linear program having polynomial time complexity. Hence, in the studied sub-classes of sub and superconservative reaction network structures, the reachability relation can be decided in polynomial time and the number of continuous decision variables is equal to the number of reactions of the d-CRN.

The Expanded Theory of Planned Behavior in the Context of Environmental Protection Behaviors for Undergraduates: Roles of Moral Norms and University Class Standings.

The expanded Theory of Planned Behavior (ETPB) was applied to examine undergraduates’ environmental protection behaviors. Moral norms were applied into the model as the predictor of attitude, social norms and perceived behavioral control. The effects of different class standings were also examined. A questionnaire survey was conducted and 380 responses underwent data analysis using structural equation modelling. According to Model ETPB, perceived behavioral control and subjective norms were strongly affected by moral norms, while attitude was moderately affected by moral norms. Environmental protection behaviors was moderately affected by environmental protection intention, while environmental protection intention was moderately affected by perceived behavioral control which was the strongest predictor, followed by attitude and subjective norms. Invoking moral emotions through posters or peers leading by examples, which over time might internalize into moral norms, played an important role in positively affecting perceived behavioral control and subjective norms. This could be followed by simple and convenient programs creating a positive self-perception of the abilities to carry out environmental protection behaviors. When separated by class standings, perceived behavioral control was the strongest predictor for the freshmen class, while subjective norms were non-significant. For the class standing of sophomores and above, attitude was the strongest predictor.

Classification of Twitter Vaping Discourse Using BERTweet: Comparative Deep Learning Study.

BackgroundTwitter provides a valuable platform for the surveillance and monitoring of public health topics; however, manually categorizing large quantities of Twitter data is labor intensive and presents barriers to identify major trends and sentiments. Additionally, while machine and deep learning approaches have been proposed with high accuracy, they require large, annotated data sets. Public pretrained deep learning classification models, such as BERTweet, produce higher-quality models while using smaller annotated training sets.ObjectiveThis study aims to derive and evaluate a pretrained deep learning model based on BERTweet that can identify tweets relevant to vaping, tweets (related to vaping) of commercial nature, and tweets with provape sentiment. Additionally, the performance of the BERTweet classifier will be compared against a long short-term memory (LSTM) model to show the improvements a pretrained model has over traditional deep learning approaches.MethodsTwitter data were collected from August to October 2019 using vaping-related search terms. From this set, a random subsample of 2401 English tweets was manually annotated for relevance (vaping related or not), commercial nature (commercial or not), and sentiment (positive, negative, or neutral). Using the annotated data, 3 separate classifiers were built using BERTweet with the default parameters defined by the Simple Transformer application programming interface (API). Each model was trained for 20 iterations and evaluated with a random split of the annotated tweets, reserving 10% (n=165) of tweets for evaluations.ResultsThe relevance, commercial, and sentiment classifiers achieved an area under the receiver operating characteristic curve (AUROC) of 94.5%, 99.3%, and 81.7%, respectively. Additionally, the weighted F1 scores of each were 97.6%, 99.0%, and 86.1%, respectively. We found that BERTweet outperformed the LSTM model in the classification of all categories.ConclusionsLarge, open-source deep learning classifiers, such as BERTweet, can provide researchers the ability to reliably determine if tweets are relevant to vaping; include commercial content; and include positive, negative, or neutral content about vaping with a higher accuracy than traditional natural language processing deep learning models. Such enhancement to the utilization of Twitter data can allow for faster exploration and dissemination of time-sensitive data than traditional methodologies (eg, surveys, polling research).

A novel acceleration method for molecular dynamics of crystal silicon on GPUs using OpenACC

AbstractCompared with CUDA and OpenCL, OpenACC has the advantages of simple programming, openness, and good portability for GPU acceleration. An OpenMP/OpenACC implementation for molecular dynamics of silicon crystal on GPUs is proposed. First, to make effective use of vectorization and streaming, data structure conversion and data dependence elimination are designed. Second, the parallel version on the single GPU is realized by adding OpenACC guidance sentences, with very few modifications. Third, a patch block strategy is proposed to realize the parallel version on single machine multi‐GPUs using OpenMP+OpenACC, which greatly simplifies the construction of shadow area and the exchange of shadow area data. Experimental results show that 23 to 25 speedup is achieved for the single GPU at different scales over the serial program on Intel(R) Xeon(R) CPU E5‐2690 v4, and 6.37 speedup is achieved over the single GPU when the number of atoms reaches 2,097,152 on 8GPUs on single machine.

Effects of Vitamin D, Omega-3 Fatty Acids and a Home Exercise Program on Prevention of Pre-Frailty in Older Adults: The DO-HEALTH Randomized Clinical Trial

BackgroundThe benefits of supplemental vitamin D3, marine omega-3 fatty acids, and a simple home exercise program (SHEP) on frailty prevention in generally healthy community-dwelling older adults are unclear.ObjectiveTo test the effect of vitamin D3, omega-3s, and a SHEP, alone or in combination on incident pre-frailty and frailty in robust older adults over a follow-up of 36 months.MethodsDO-HEALTH is a multi-center, double-blind, placebo-controlled, 2x2x2 factorial randomized clinical trial among generally healthy European adults aged 70 years or older, who had no major health events in the 5 years prior to enrollment, sufficient mobility and intact cognitive function. As a secondary outcome of the DO-HEALTH trial, among the subset of participants who were robust at baseline, we tested the individual and combined benefits of supplemental 2,000 IU/day of vitamin D3, 1 g/day of marine omega-3s, and a SHEP on the odds of being pre-frail and frail over 3 years of follow-up.ResultsAt baseline, 1,137 out of 2,157 participants were robust (mean age 74.3 years, 56.5% women, mean gait speed 1.18 m/s). Over a median follow-up time of 2.9 years, 696 (61.2%) became pre-frail and 29 (2.6%) frail. Odds ratios for becoming pre-frail were not significantly lower for vitamin D3, or omega 3-s, or SHEP, individually, compared to control (placebo for the supplements and control exercise). However, the three treatments combined showed significantly decreased odds (OR 0.61 [95% CI 0.38–0.98; p=0.04) of becoming pre-frail compared to control. None of the individual treatments or their combination significantly reduced the odds of becoming frail.ConclusionRobust, generally healthy and active older adults without major comorbidities, may benefit from a combination of high-dose, supplemental vitamin D3, marine omega-3s, and SHEP with regard to the risk of becoming pre-frail over 3 years.

A novel nature-inspired anisotropic hydrogel with programmable shape deformations

Stimulus-responsive anisotropic hydrogels have attracted tremendous attention in the fields of actuators, soft robots, and artificial muscles due to their ability to perform complex programmable motions. However, it is still challenging to construct anisotropic hydrogels via a simple way without the assistance of external fields. Inspired by gradient dissolved oxygen in seawater, we proposed a novel simple structure programming strategy to prepare anisotropic hydrogels using low-cost natural oxygen as the driving force. Encouragingly, this strategy, which relied on the asymmetric inhibitory behavior of natural gradient dissolved oxygen toward radical polymerization and electrostatic attraction between polyelectrolyte chains, enabled the obtained anisotropic hydrogels with both gradient structure and phase-separated structure. It is found that this complex asymmetric structure allowed anisotropic hydrogels be capable of complex deformations under different environmental conditions (temperature, pH), such as blooming and wilting flower shapes. Additionally, a humidity alarm and a four-armed hydrogel gripper were successfully constructed based on the designed anisotropic hydrogel, which indicated that our work provides a new strategy for the field of smart actuator fabrication.

Computer modeling of electromechanical system of two-speed elevator

Today, elevator production in Ukraine needs innovative solutions and changes, because most of the equipment in operation was built and installed in the 70-80s of the last century. Due to the high cost of new frequency-controlled winches and the complexity of maintenance, the search for modernization and improvement of existing elevator winches remains an alternative. No less important stage of operation is diagnostics. Timely detection of damages and forecasting of future failures allow to provide high-quality work during all term of operation, and also to reduce expenses of budgetary funds for difficult repairs. Computer simulation playsan important role in the modern world both during the design of a new elevator and during operation. Thanks to fairly simple and clear programs, it is possible to reproduce not only the standard modes of operation of the mechanisms, but also to perform calculations of future possible faults. The use of visualization facilitates the perception of information for operators, engineers and other users involved. The paper presents a computer model of a two-speed elevator with an induction motor and a reduction winch. The research used Matlab / Simulink software, which is intuitive to use and, in the full sense of the word, informative. The built model of the elevator has feedback on the calculated load of the cabin. The latter is determined by the transients during engine start-up and affects the positioning accuracy at a stop. The dependences of the influence of the degree of cab loading on the positioning accuracy are found. In the second stage, the supply voltage parameter is added. A change in this parameter within ± 10% affected the previous calculations of the loading degree and deteriorated the accuracy by almost three times.At the same time, most indicators (75%) meet the requirements of international standards EN 81-20: 2014 with positioning accuracy in the range of ± 10 mm. In further studies it is planned to use the obtained results to reduce the sensitivity of the algorithm for calculating theloadingdegree of the cabin to change the supply voltage and ensure the required positioning accuracy in the entire load range of the cabin when changing the supply voltage ± 10%.

Mining the Soma Cube for Gems: Isomorphic Subgraphs Reveal Equivalence Classes

Soma cubes are an example of a dissection puzzle, where an object is broken down into pieces, which must then be reassembled to form either the original shape or some new design. In this paper, we present some interesting discoveries regarding the Soma Cube. Equivalence classes form aesthetically pleasing shapes in the solution set of the puzzle. These gems are identified by subgraph isomorphisms using SNAP!/Edgy, a simple block-based computer programming language. Our preliminary findings offer several opportunities for researchers from middle school to undergraduate to utilize graphs, group theory, topology, and computer science to discover connections between computation and geometric patterns.