Manual composition of tasks and exams is a challenging and time-consuming task. Especially when exams are taken remotely without the personal monitoring by examiners, most exams can easily lose their integrity with the use of previously done exercises or student communication. This research introduces an approach that incorporates the principles of the generative software development and aspects of the feature-oriented product line engineering process into the field of question creation and generation. The resulting generator can be used to generate single-choice-question-families by means of written question templates. The generated questions within a question-family differ based on the set features and parameters and can be imported into the target learning management system ILIAS. Without much effort, examiners and educators can use the generator to create variants of their questions and deliver them to their students. Constructing exam questions is without saying a very time-consuming and challenging task for all examiners. Especially when teaching, learning and assessment concepts are moving more towards hand-on approaches with many exercises. This in turn drives educators to use automated and rapid feedback mechanisms further facilitated through smaller scaled learning experiences. In such a way, content is clustered to be absorbed through small units of learning and to be made available on demand, so that learning is neither location- nor time-bound.Additionally, through the pandemic years, many changes had to be made and new situations had to be accounted for. The COVID-19 pandemic situation not only forced the teaching to be in digital spaces, but also many exams had to be made available in some remote way. This not only meant that in comparison with in person examinations, students were often able to use all of the lecture materials and notes, but this also opened up the possibility for students to easier communicate with each other.In the specific case of the University of Leipzig, the institution interpreted both German and EU law in such a way that virtually all exams were conducted online. Due to data privacy, no identity check was carried out apart from the login to the exam. Furthermore, it was not allowed that the examinees and their surroundings were monitored. Therefore, examiners had to assume that the students would use aids or solve the exams together. To prevent such actions, many educators started to create multiple versions of the same questions to at least hinder communication. All in all, this requires a lot of time and effort to ensure that the questions possess an equal quality and difficulty. In order to ensure examination fairness, task variations or task specification can be used so that the tasks differ from each other and are designed differently.The prototype presented in this paper focuses on multiple-choice, or more specifically single-choice questions. In the approach presented here, which is part of an ongoing research, different impulses from different fields are combined. At the forefront of this research stands the paradigm of generative software development according to the principles of Czarnecki , whose aProduct line engineering is an approach to software development that emphasizes the reuse of existing assets and knowledge in order to develop and maintain a product line of related software products more efficiently . Aldabe et al. , VimalakDescribed in this paper, the FeatureIDEAs described in the introduction, the methodology is based on the paradigm of generative software development and aims to transfer its essential aspects into the domain of question generation. According to Czarnecki , generatApel et al. , p. 19 sFor this reason, it is important to clarify the main aspects and process steps that are relevant for the adaption. Firstly, a feature is a characteristic or end-user-visible behavior, that is used to specify commonalities and differences for communication between stakeholders, system structure, reuse and for the software life cycle  to replace the parameter itself with a value from its value range.For the specific question generator, the following Fig. Inside the process of domain implementation reusable artefacts are to be developed that correspond to the previously identified features. These artefacts usually contain the design, tests, documentation and source code, but this basic idea can also be applied to non-code-artefacts. Since this step specifically targets the solution space, a general implementation strategy has to be chosen to create a reusable framework . A DSL is a language that is created to solve specific problems in a particular domain Martin, . The impBased on this, each template consists of at least the five sections that were identified as mandatory features in the domain analysis. In addition, there are the eleven optional sections that can be present. Each section is initiated by the identifier @-character like @AUTHOR and is followed by a predefined structure to efficiently read in files as shown in line 3 and 4 or Fig. After the template is parsed, the generator proceeds to first generate all valid combinations of answer possibilities and parameters with respect to the set criteria, exclusions or dependencies. When all combinations are created, the questions are put together for either a specified amount, of semi-randomized questions, or all valid combinations of answer possibilities combined with all valid parameter combinations.c = number of correct answer possibilities, w = number of distractors, p = number of parameter values.For the case that there are no exclusions for answers and no dependencies between parameters the formula for all questions is based on the combination without repetition, multiplied by the number of correct answer possibilities and multiplied by the product of the number of values in the parameter value ranges.As shown in Eq. After the generation of all valid questions, the generator proceeds to create a corresponding output for the import into ILIAS. Since the generator is designed to generate whole question pools, a corresponding folder structure and the necessary XML-files are generated. The whole structure can then be easily packed into a Zip-file and imported into ILIAS as a question pool. The programme sequence described here is illustrated again in Fig. For the development of the generator, a reactive approach was chosen to realize an initial version of the envisioned product line and to progressively further develop the system (Metzger & Pohl, The product derivation or in other cases product—generation, -configuration or -assembly, is the production step of application engineering, where the reusable artefacts are combined with the results of the requirements analysis. This more or less automatable process can involve several other development or customization steps (Apel et al., Overall this step represents the creation of the question-template including the specification of the used parameters. Additionally, a few different steps are checked throughout the generation. This starts with the verification of the parsed template, by using the requirements from the domain and requirements analysis to assess if certain criteria are met, for example, if every parameter has a valid value range. At different stages the validity of the generation gets checked and the question generation is skipped or stopped if it is faulty.As the creation of the question-template is necessary for the creation of question families, Fig. Figure To now express much more variety the question template can be parameterized. As shown in Fig. Of course, the question-template of Fig. As this paper is part of an ongoing research activity, its aim is to introduce a tool and a methodological approach to generate question families based on the principles of software product line engineering, which can be developed further. These principles and corresponding development process were applied to the creation of a single-choice-question-generator. The resulting generator enables educators to design question-templates by the use of a simple and lightweight domain specific language. The templates get generated by either use of multiple manually written answer possibilities, or the use of question and in turn answer parameterization. After the generation process, examiners receive the generated questions as importable files for the use in the learning management system ILIAS.By the use of this system, a few examinations have been conducted in the summer term of 2022. In result, for example a single-choice exam was conducted with 40 questions for each participant, wherein total 538 different generated questions were used for the examinations. By the use of the generator, the examiners were able to create question-families via the question-templates, so the participants received comparably similar questions, according to the judgement of the examiners. In particular, only one question-template had to be created at a time to generate multiple questions, in turn saving time in creation, quality assurance and import into the system. In addition, the generator will further be used in the following terms for self- and online-assessments so that students can check their own knowledge and understanding.The generator can easily be used by educators and examiners outside of the computer science field, with or without changes to the question-templates. In addition, it can be adapted for other online learning platforms to use such an approach to semi-automate task generation, where students are provided with similar tasks to improve their skills in the respective field or with specific task types. This would include for example the combination with different learning taxonomies like the revised Bloom taxonomy (Krathwohl, Finally, such a generator can help educators and examiners when creating questions and students when learning with different iterations of questions. But even though the question-templates in their simple form are easily created, creating complex templates can still be time consuming for complex templates, since the overall question quality depends more on the user and less on the functionality of the generator.Since the questions are not created and parameterized by the generator itself but by the examiner, it is important to highlight that the comparability and difficulty of the answer alternatives is still up to the examiner. Therefore, the actual similarity in difficulty level, could be investigated as the subject of a follow-up study. In addition, by using this kind of question generation for multiple-choice questions the common item analysis methods like Cronbach’s alpha/Tau-equivalent reliability, selectivity and difficulty index are not applicable, since the questions are only similar but otherwise unique with respect to their combination of answer possibilities and parameters. Additionally, most of our exams at the university are conducted with a smaller number of students so that most of the unique questions are only provided to a very small fraction of students, which in turn makes the methods unavailable or very inaccurate. Therefore, it must be explored, which methods can be used to analyze such parameterized tasks, so that in the long term the similarity and difficulty of examinations for different students can be guaranteed. If such methods do not already exist, alternative static quality assurance methods must be developed.For the generator itself, there are many possibilities to extend its functionality, that can currently be seen as shortcomings. First of all, the used DSL is rather rigid in its applicability. Therefore, certain features can and should be extended or reworked, like the ability to parameterize the picture section to include specific images based on the specified parameters. Additionally, analog to the approach of Nagasaka  it is poAlthough most features are independently defined and implemented, which eases the capability to change them, some features like the parameters, their value range and the dependencies/interactions are strongly coupled, whereby adapting them would require a greater effort. This may also apply to certain features to be changed or newly created, as they have been designed for use in our specific cases, whereby other study courses would have different requirements. As the generator is a research prototype, the source code itself might currently not be a good representation of the principles for software development. Therefore, the generator must be further developed or, if necessary, newly developed, considering various aspects of software engineering. For this reason, additional aspects of software product line management should be introduced, to enable the sharing of artifacts for reuse and adaption.Additionally, the generator can be extended to generate output for other learning management systems and to generate further question types, surveys or images. For the future work with template-based question generation, the approach is to be further developed to be used for generating programming exercises and images especially various types of diagrams like flowcharts or UML class diagrams.With the emergence of ChatGPT respectively models of the GPT 03 family and other AI-driven approaches, most online exams can for the most part be nullified. Our approach should be no different, as such a system can provide an answer within seconds and a parameterized task is not a major obstacle, as it would be for a student. Therefore, in the educational domain, research must be done to determine which testing methods can be used to test the skills of students, but which an AI is not capable of. However, it should be noted that the generator is still operational and useful, for example for examinations that are conducted in several rounds, so that students cannot exchange the specific answers. However, through the use of AI-driven approaches like Vimalaksha et al.  and VachFinally, it should be pointed out that the system is currently only designed for the parameterization of single choice tasks, which is mainly useful for knowledge testing. As there are many more aspects throughout the learning process, future research should be concerned with investigating to what extent feature orientation of tasks can be used to ensure a better learning process. For example, feature decomposition of tasks can be used to create an adaptive system to help students overcome learning problems, and parameterization can allow students to test their knowledge in a repeatable and independent way.https://github.com/NWillert/Template-basedGeneratorForSingleChoice.Generator source code available under:


This 3D network hindering the stacking of graphene sheets provided channels for hydrogen diffusion to improve the hydrogen adsorption kinetics. Importantly, the construction of the three-dimensional palladium-phosphide-modified P-doped graphene hydrogen storage material improved the hydrogen absorption kinetics and mass transfer process. Furthermore, while acknowledging the limitations of primitive graphene as a medium in hydrogen storage, this study addressed the need for improved graphene-based materials and highlighted the significance of our research in exploring three-dimensional configurations. The hydrogen absorption rate of the material increased obviously in the first 2 h compared with two-dimensional sheets of Pd3P/P-rGO. Meanwhile, the corresponding 3D Pd3P0.95/P-rGO-500 sample, which was calcinated at 500 °C, achieved the optimal hydrogen storage capacity of 3.79 wt% at 298 K/4 MPa. According to molecular dynamics, the structure was thermodynamically stable, and the calculated adsorption energy of a single H2 molecule was −0.59 eV/H2, which was in the ideal range of hydrogen ad/desorption. These findings pave the way for the development of efficient hydrogen storage systems and advance the progress of hydrogen-based energy technologies.The development of efficient hydrogen storage materials is crucial for advancing hydrogen-based energy systems. In this study, we prepared a highly innovative palladium-phosphide-modified P-doped graphene hydrogen storage material with a three-dimensional configuration (3D Pd As a consequence of population expansion and evolving lifestyles, global requirements are progressively escalating while encountering environmental problems and an alarming resource depletion rate. The damage that fossil fuel usage has caused to the environment has increased the demand for clean, sustainable energy ,2,3. Hydgraphene .However, as a two-dimensional material with a thin sheet structure, graphene sheets tend to stack together spontaneously due to van der Waals forces and π-π bond interactions ,26. Irre3O4 nanosheet hybrid decorated with Pd for hydrogen evolution. They confirmed that the 3D network architecture was favorable for the mass transport of produced hydrogen [Furthermore, adsorption is also a mass transfer process. Increasing the specific surface area of materials can improve the adsorption sites and subsequent capacity. Constructing a three-dimensional graphene network may provide a valid solution to prevent the graphene sheets from aggregating. The unique three-dimensional lamellar folds and pore structure of graphene can effectively prevent this interlayer accumulation, which is the intrinsic reason for the stable existence of 3D graphene . Bi et ahydrogen . Jiang ehydrogen . Thus, shydrogen .3P0.95/P-rGO was obtained by thermal reduction in a H2/Ar atmosphere. Palladium phosphide was grown directly on the three-dimensional graphene substrate. This 3D structure could effectively promote mass transfer. The multi-stage gap structure helped the gas be transported to/separate from the reaction center to promote molecular dynamics. Therefore, the as-prepared 3D Pd3P0.95/P-rGO-500, which was calcinated at 500 °C, achieved a hydrogen storage capacity of 3.79 wt% at 298 K/4 MPa. Meanwhile, the hydrogen absorption rate of the material increased obviously in the first 2 h compared with 2D sheets of Pd3P/P-rGO.Based on our previous work, herein, a 3D Pd/P co-modified graphene hydrogel material was successfully prepared by a hydrothermal method, and 3D Pd3 were first added to a 1000 mL beaker. After that, 100 mL of concentrated sulfuric acid was slowly added to the beaker, and 12 g of KMnO4 was slowly incorporated with continuous high-speed stirring. The as-obtained mixture was thoroughly stirred in an ice water bath for 8 h. Afterward, 3 vol% H2O2 solution was added to the beaker to completely reduce the excess KMnO4 until the brown solution turned yellow. The GO solution after the reaction was kept static at room temperature and was observed to change from bright yellow to brown with obvious stratification. The supernatant was poured out, and the precipitate was washed twice with concentrated hydrochloric acid. Then, deionized water was added repeatedly for cleaning until the pH value of the solution was close to neutral. The GO solution with 3 wt% content was obtained after filling to a constant volume of 1000 mL.The modified Hummers method was used to produce graphene oxide. Briefly, 5 g of graphite powders and 1 g of NaNO2, 120 μL phytic acid, and 33 mL deionized water in a 100 mL beaker using ultrasound for 30 min. Then, the above solution was transferred to a 100 mL Teflon lining. After that, the lining was sealed in a stainless-steel high-pressure reaction kettle for 12 h for the hydrothermal reaction, and the temperature was kept at 160 °C. After the reaction, the cylindrical hydrogel material was freeze-dried and then heated to 900 °C, 700 °C, 500 °C, and 300 °C for 1 h in a 10 vol% H2/Ar atmosphere. The 3D-configuration Pd3P0.95/P-rGO prepared at different thermal reduction temperatures is denoted as 3D Pd3P0.95/P-rGO-Y , where the numbers 300, 500, 700, and 900 represent the reduction temperatures.We mixed 33 mL GO solution, 78 mg Pd(OAc)2 adsorption energy, transition state, and energy barrier, with a focus on characterizing the hydrogen migration through the Pd3P cluster sites to the P-rGO surface. The Vienna Ab initio Simulation Package (VASP) was used to perform the calculations. Ab initio molecular dynamics (AIMD) was utilized to study the model. The exchange and correlation interactions were described using generalized gradient approximation (GGA) in the form of the Perdew–Burke–Ernzerhof (PBE) functional. The calculations used a Brillouin region of 5 × 5 × 1 as the k-point value; the geometry optimization structure was obtained by relaxation until the force on each atom was less than 0.02 eV/Å; and the convergence criterion for energy was set as 1 × 10−4 eV. The cutoff energy was 450 eV, and all calculations considered spin polarization. The study employed an equation to determine the adsorption energy of the H2 molecule, taking into account the vibration effect for a gas phase, only as it is nearly negligible for a solid system.2 adsorption energy, 2 molecule, and A graphene surface model consisting of 60 atoms was utilized in this study, and a vacuum layer of 15 Å was added along the Z-direction to avoid any interactions between neighboring layers. The single graphene model with 59 atoms was obtained by substituting a carbon atom with a phosphorus atom from the graphene sheet and attaching the oxygen atom to the slab, thus creating phosphorus-reduced graphene oxide (P-rGO). The structure was subsequently optimized. The study employed density functional theory (DFT) to calculate the binding energy, H3P0.95/P-rGO, mainly showing a fluffy columnar structure. The SEM images of the as-prepared materials  prepared at different thermal reduction temperatures. With the increase in the thermal reduction temperature, more oxygen-containing groups in the graphene were reduced, thus forming defects similar to vacancies. At the same time, the doping degree of P atoms further increased, leading to an increment in the ID/IG value of the sample  prepared at different thermal reduction temperatures, and the inset shows the particle size distribution. The N2 adsorption–desorption curves of the Pd3P0.95/P-rGO-Y  at 77 K showed the characteristics of a type IV isothermal adsorption line, and an obvious hysteresis phenomenon occurred during the N2 desorption of the four samples, which indicated that the material had a rich pore structure, that is, a large number of mesopores existed. We found that the average pore sizes of the four samples were all distributed around ~3.8 nm, except for Pd3P0.95/P-rGO-300, in which the number of 3.8 nm mesopores was lower, as shown in the inset in 3P0.95/P-rGO-Y . Pd3P0.95/P-rGO-900 had the largest surface area and pore volume at 339.67 m2/g and 0.379 cm3/g, respectively. The specific surface area and pore volume of Pd3P0.95/P-rGO-300 decreased to 50.51 m2/g and 0.130 cm3/g, respectively, when the thermal reduction temperature dropped to 300 °C. With the decrease in the thermal reduction temperature, Pd ions could not be reduced to obtain the expected palladium phosphide, and nor could the oxygen-containing groups be completely reduced.3P0.95/P-rGO-300 were reduced, leading to an obvious reduction in the specific surface area and pore volume. This showed that both the defect degree and the micro-structure in the material were closely related to the thermal reduction temperature. The influence of metal and non-metal doping on the surface area and pore characteristics of particles was investigated by Safia et al. [BET of the catalysts. Furthermore, Sahoo et al. [Combined with the Raman test results in a et al. . In a sea et al.  demonstro et al.  reportedo et al. .3P0.95/P-rGO-Y  samples, as shown in 3/2 and P 2p1/2, respectively, which corresponded to Pd-P bonds, indicating the successful synthesis of Pd3P0.95 particles in the material [5/2 and 3d3/2 orbits of Pd(0), respectively. The peaks located near 336 eV and ~342 eV correspond to the 3d5/2 and 3d3/2 orbitals of Pd(II), indicating that Pd with a high valence state existed due to the formation of a Pd-O bond [To further study the electronic structure and chemical valence of the elements on the surface of the material, X-ray photoelectron spectroscopy (XPS) was performed on the 3D-configuration Pdmaterial . The EDXd-O bond .3P0.95/P-rGO-Y  prepared at different thermal reduction temperatures under the conditions of 4 MPa/298 K and the corresponding hydrogen storage capacity. With the decrease in the thermal reduction temperature, the hydrogen storage capacity of the material increased first and then decreased, reaching the maximum value (3.79 wt%) when the thermal reduction temperature was 500 °C. This was because reducing the thermal reduction temperature could effectively prevent the nanoparticles in the material from agglomerating and subsequently falling off. Thus, the size of the modified nanoparticles in the material was well controlled, and the hydrogen spillover capacity was enhanced, contributing to an obvious increase in the hydrogen storage capacity. However, we found that the Pd could not be fully phosphatized at 300 °C. Therefore, the hydrogen spillover effect of the Pd3P0.95/P-rGO-300 was greatly reduced, and the hydrogen storage performance decreased sharply.3P0.95/P-rGO-900 showed the lowest hydrogen absorption amount of 72.5% in the first 2 h, indicating that the hydrogen absorption rate was directly related to the particle size of the modified particles in the material. The smaller the particle size, the higher the hydrogen absorption rate. The hydrogen absorption rates of the four samples were significantly higher than in our previous work for 2D Pd3P/P-rGO (61.8%) [3P0.95/P-rGO was mainly due to the formation of a 3D structure, which could greatly enrich the pore structure in the material and provide channels for hydrogen diffusion, thus accelerating the hydrogen absorption process. During the spillover process, the hydrogen molecules underwent dissociation on the Pd3P0.95 nanoparticles and subsequently migrated to the surface of the graphene. The dissociated hydrogen species, chemisorbed onto the surface, involved covalent interactions, whereas the absorption of hydrogen molecules onto the graphene was governed by weaker van der Waals forces, which represented non-covalent interactions. Additionally, it is noteworthy that the environmental temperature and pressure exerted a significant influence on the hydrogen storage capacity. Experimental results indicate that reducing the test temperature and increasing the pressure of hydrogen has a favorable effect on hydrogen adsorption [ (61.8%) . The impsorption .3P, P-rGO, and P-doped graphene (P-G) were calculated based on DFT, and the optimized structures are shown in 3P and P-rGO and −2.14 eV between Pd3P and P-G. The results showed that the reduction of the oxygen atoms could increase the binding energy of the cluster and slab. The higher the binding energy, the lower the chance of the agglomeration of transition metal (TM) atoms and vice versa. DFT simulations were performed at 0 K, and the structural integrity of the system had to be checked at room temperature (300 K). In our case, wherein Pd3P was attached to the P-rGO, it was critical that the TM atoms did not dislodge from the P-rGO at higher temperatures. The AIMD simulations considered these concerns. The simulations were carried out at a temperature of 300 K in a canonical ensemble (NVT) for 1 ps with a time step of 1 fs. The MD snapshots of Pd3P/P-rGO are shown in 3P cluster and the change in the C-C bond length were negligible, highlighting the thermal stability of the structure and supporting the material’s practical application in hydrogen storage systems. Because the probability of metal atoms or clusters aggregating on supports is a major downside of transition metals in graphene-based materials, we know that the metal–metal interactions are stronger than chemical interactions between metal atoms and carbon atoms in the support [2 desorption [The binding energies of Pd support . This MDsorption . In our sorption .2 molecule is shown in 2 when the zero-point energy correction was taken into account. A negative adsorption energy value indicates the attraction of H2 molecules to the cluster, implying favorable adsorption. Adsorption mechanisms that fall between physical and chemical adsorption are required for the successful implementation of hydrogen storage in ambient conditions. Previous research has suggested an adsorption energy range of −0.20 to −0.60 eV [2 molecule, the stretching of the H-H bond length was found to be minimal, with a difference of less than 0.3 Å [2 was preserved during adsorption and the association between the H2 molecule and the Pd atom was of the Kubas type.The optimized structure of a single adsorbed H−0.60 eV , which aan 0.3 Å , indicat2 molecules and the migration of H atoms from the site of dissociation to the supporting substrate. In this study, the spillover process of a single hydrogen molecule adsorbed on Pd3P/P-rGO was computed using the nudged elastic band (NEB) and climbing image nudged elastic band (CINEB) [2 adsorbed on Pd3P/P-rGO, spillover occurred at higher temperatures due to the higher energy migration barrier. The DFT results were in line with experimental data showing that Pd3P0.95/P-rGO-300’s hydrogen spillover effect was substantially reduced. The relationship between temperature and spillover reaction time is depicted in 3P0.95/P-rGO-Y  samples were much higher than those of some graphene-based materials previously reported in the literature   methods.ture see  under am3P0.95/P-rGO) using a hydrothermal method followed by calcination. The three-dimensional network structure of the material hindered the stacking of graphene sheets and provided channels for improved hydrogen diffusion, thereby enhancing the hydrogen adsorption kinetics and mass transfer process. The research findings demonstrated that the constructed three-dimensional palladium-phosphide-modified P-doped graphene material exhibited significantly higher hydrogen absorption rates in the initial 2 h compared to its two-dimensional counterparts, highlighting the advantages of the three-dimensional configuration. Specifically, the 3D Pd3P0.95/P-rGO-500 sample, calcinated at 500 °C, achieved an optimal hydrogen storage capacity of 3.79 wt% at 298 K/4 MPa. The thermodynamic stability of the structure was confirmed by molecular dynamics simulations, which also revealed an adsorption energy of −0.59 eV/H2 for a single H2 molecule, falling within the ideal range for efficient hydrogen adsorption/desorption. The significance of this research lies in its addressing the need for improved graphene-based hydrogen storage to overcome the limitations of pure graphene in hydrogen storage. By exploring three-dimensional configurations, this study opened up new possibilities for the development of efficient hydrogen storage systems and advanced the progress of hydrogen-based energy technologies. The innovative approach presented in this study has the potential to contribute significantly to the advancement of hydrogen-based energy systems, offering a promising avenue for further research and development in this field.In conclusion, this study presented a highly innovative approach to the development of hydrogen storage materials by preparing a three-dimensional configuration of palladium-phosphide-modified P-doped graphene (3D Pd


These elements act as open platforms for recruiting both positive- and negative-acting transcription factors, and as such, chromatin accessibility is an important signature for their identification.The genetic information contained in the genome of an organism is organized in genes and regulatory elements that control gene expression. The genomes of multiple plants species have already been sequenced and the gene repertory have been annotated, however, cis-regulatory elements that have been functionally validated in wheat, and a good correlation between normalized accessibility and gene expression levels.In this work we developed a transgenic INTACT [isolation of nuclei tagged in specific cell types] system in tetraploid wheat for nuclei purifications. Then, we combined the INTACT system together with the assay for transposase-accessible chromatin with sequencing [ATAC-seq] to identify open chromatin regions in wheat root tip samples. Our ATAC-seq results showed a large enrichment of open chromatin regions in intergenic and promoter regions, which is expected for regulatory elements and that is similar to ATAC-seq results obtained in other plant species. In addition, root ATAC-seq peaks showed a significant overlap with a previously published ATAC-seq data from wheat leaf protoplast, indicating a high reproducibility between the two experiments and a large overlap between open chromatin regions in root and leaf tissues. Importantly, we observed overlap between ATAC-seq peaks and We have developed and validated an INTACT system in tetraploid wheat that allows rapid and high-quality nuclei purification from root tips. Those nuclei were successfully used to performed ATAC-seq experiments that revealed open chromatin regions in the wheat genome that will be useful to identify cis-regulatory elements. The INTACT system presented here will facilitate the development of ATAC-seq datasets in other tissues, growth stages, and under different growing conditions to generate a more complete landscape of the accessible DNA regions in the wheat genome.The online version contains supplementary material available at 10.1186/s12870-023-04281-0. During the last 20 years, the significant progress in DNA sequencing technologies has allowed the rapid sequencing of complete genomes from multiple species, including a large number of varieties within each species. Today we have good reference genomes and pangenomes for the principal crop species, and that information has been critical to understand the genetic basis of biological processes, to identify natural variation responsible for phenotypic diversity, and for other applications.cis-regulatory elements and modules, which represents an important gap in our understanding of genome functionality . The re) genome , 3.Epigenome maps have contributed to the identification of regulatory regions, which are characterized by specific chromatin marks or signatures –6. AnothOryza sativa L.), maize, and Arabidopsis thaliana (L.) Heynh . Those nd wheat –22.An important parameter to assess chromatin accessibility in all these methods is the quality of the cell nuclei isolations. Broken DNA generated during extraction reduces signal/noise ratio and reduces the ability to detect open chromatin regions, so it is critical to start these experiments with high quality chromatin . For ATAHigh quality ATAC-seq data was recently reported in wheat using nuclei isolated from leaf protoplast . HoweverTriticum turgidum subsp. durum (Desf.) Husn.) and showed that it can be used to purify nuclei using a simple and rapid protocol. We then combined our INTACT system with an ATAC-seq protocol and tested different conditions to optimize enrichment of open chromatin regions. Finally, we generated INTACT-ATAC-seq data from wheat root tip samples from frozen and fresh material. Our root ATAC-seq results showed good reproducibility and enrichment of open chromatin regions in intergenic and promoter regions, which is expected for regulatory elements. A similar distribution of accessible DNA was observed when we re-analyzed published wheat ATAC-seq data generated from wheat leaf protoplast , 40 ml dH2O, 25 ul β-mercaptoethanol and 250ul 0.5 M spermidine, and keep on ice until used. After collection, the root tips were transferred to a weigh boat on ice containing 1 mL of ice-cold 1X CB, and chopped for 2.5 min using a sharp razor blade. The resulting extract was decanted into a 50 mL Falcon tube. Next, 2 mL of 1X CB were added to the samples and chopped again for 2 min. The extracts were combined to a final volume of ~ 4 mL, filtered through one layer of Miracloth and centrifuged in 50 mL tubes for 7 min at 1000 g at 4 °C. The nuclei pellets were carefully resuspended in 3 mL 1X CB using a wide-bore pipet tip to reduce mechanical shearing, and divided into two 2 mL-tubes (1.5 mL extract per tube). In parallel, 50 µL/per sample of Streptavidin Dynabeads (NEB S1420S) were pre-washed in 1X CB, of which 30 µL were added to each tube having the nuclei extract. The tubes with the bead-extract mix were placed in a rotator and incubated for 30 min at 4 °C with gentle rotation. Then, the tubes were incubated for 10 min in a magnet and the supernatant removed. Next, 1.8 mL of fresh ice-cold 1X CB + triton (to 50 ml of fresh 1X CB add 2.5 ml of 20% Triton X) were added to the tubes, which were rotated for 5 min at 4 °C, incubated in a magnet for 5 min and the supernatant removed. This procedure was repeated two more times, and finally the bead-bound nuclei were resuspended in 500 µL of 1X CB and placed on ice until transposition. Freshly purified nuclei in 1X CB to be used for ATAC-seq were kept on ice prior to the transposase integration reaction and never frozen.Our biotin labeled nuclei isolation protocol is an adaptation of a previous protocol from Queitsch Lab  [A + B + Unassigned], chloroplast (MH051715.1), and mitochondria (MH051716.1) genomes using bwa v0.7.15. Leaf protoplast ATAC-seq data  was geneAggregate plots of per base TN5 insertion counts (Fig. To compare the relative accessibility and the expression level of the genes, we stratified genes by expression level using previously published RNA-seq for root at “First leaf through coleoptile” stage, and leaf at “3 leaves unfolded” stage . FPKMs wAdditional file 1:Figure S1. Validation of INTACT system in tetraploid wheat Kronos.Additional file 2:Figure S2. Effect of the number of sequencing reads on the detected ATAC-seq peaks.Additional file 3:Table S1. Sequencing stats.Additional file 4: Table S2. Intact results and distribution in different genome regions.Additional file 5:Table S3. Overlap between peaks from fresh and frozen roots ATAC-seq data. Additional file 6: Table S4. Primers used in this study.Additional file 7:Table S5. Expression of genes associated with ATAC seq peaks in different tissues.


The prepared samples are named G50-1B to 3B and G100-1B and G100-2B. The prepared GO and graphenes were also analyzed under various characterization techniques to confirm their morphology and structural integrity. The obtained results suggest that the ORR electrocatalytic activity of graphene may differ based on the pyrolysis conditions. We found that G100-1B  and G100-2B  displayed better electrocatalytic ORR activity, as did Pt/C electrode . These results display the wide use of the prepared graphene for ORR and also can be used for fuel cell and metal–air battery applications.Graphene is a well-known two-dimensional material with a large surface area and is used for numerous applications in a variety of fields. Metal-free carbon materials such as graphene-based materials are widely used as an electrocatalyst for oxygen reduction reactions (ORRs). Recently, more attention has been paid to developing metal-free graphenes doped with heteroatoms such as N, S, and P as efficient electrocatalysts for ORR. In contrast, we found our prepared graphene from graphene oxide (GO) by the pyrolysis method under a nitrogen atmosphere at 900 °C has shown better ORR activity in aqueous 0.1 M potassium hydroxide solution electrolyte as compared with the electrocatalytic activity of pristine GO. At first, we prepared various graphene by pyrolysis of 50 mg and 100 mg of GO in one to three alumina boats and pyrolyzed the samples under a N Over the past few decades, oxygen-related electrocatalysis has garnered attention, and much work has been performed to reduce the need for noble metal catalysts or create new, alternative catalysts . To obta2-hybridized carbon atoms [2 g−1 and electrical conductivity, better thermal conductivity of 5000 W−1 K−1, optical transmittance (97.7%), Young’s modulus of 1.0 TPa, and intrinsic mobility of 200,000 cm2 v−1 s−1 [Graphite is a cheap carbon-based material that can be readily converted to highly valuable and accessible materials by chemical and thermal treatments ,9. Graphon atoms ,11. Grap4, were used in chemical reduction [Numerous uses for graphene-based materials are found in the fields of energy conversion and storage, construction, health, and the environment. Several routes also exist for obtaining graphenes, such as the exfoliation of graphite, chemical vapor deposition, solvothermal synthesis, the micromechanical cleavage of graphite, and epitaxial growth on an electrically insulating surface ,12. To meduction . On the eduction ,14. Moreeduction . The oxieduction ,14. The eduction ,14,15. MRecently, graphene and carbon-based materials were used largely as an electrocatalyst for ORR ,18,19,20In this work, we synthesized GO from graphite by modifying Hummer’s method according to the report method with partial changes in the experimental conditions ,39. To o2S2O8, ≥99.0%), phosphorus pentoxide , potassium hydroxide (KOH) powder, Nafion™ perfluorinated resin solution, and anhydrous ethanol were purchased from Sigma-Aldrich Inc. . Sulfuric acid  and hydrochloric acid  was bought from Matsuneon Chemical Ltd. . Potassium permanganate  was supplied by Katayama Chemical Industries Co., Ltd. . Hydrogen peroxide  was obtained from Junsei Chemical Co., Ltd. . Double deionized water was used in all experiments. All chemicals were used without further purification.Graphite powder , potassium persulfate  of nitrogen (N2)  . The qua−1 and 400 and 3300 cm−1, respectively. X-ray photoelectron spectroscopy (XPS) was utilized to acquire information regarding the surface’s chemical state . The CASA XPS software was used to perform peak-fitting analyses and quantitative observations. An electrochemical workstation and rotating ring-disk electrode device  with a three-electrode electrochemical cell was used to perform the cyclic voltammetry (CV), linear sweep voltammetry (LSV), and ring-disk electrodes performance at 25 °C. A catalyst sample served as the working electrode while a saturated calomel electrode (SCE) and a graphite rod served as the reference and counter electrodes.The surface morphology of the samples was analyzed by the use of field emission scanning electron microscopy  and field emission transmission electron microscopy . The samples were evenly put on carbon tape and platinum coated on the substrate before the measurement. The sample was dispersed in ethanol and loaded on a copper grid and dried before measuring with FETEM. An X-ray diffractometer  equipped with a Cu anode material and operating at 40 kV in the scanning range of 5–80° 2θ was used to determine the crystalline phase of the samples. Both Fourier transform infrared spectroscopy , Easton, MD, USA) and Raman spectroscopy were able to validate the presence of functional groups in graphene and GO (RAMANtouch). Recordings of FTIR and Raman spectra were made using a scanning range of between 400 and 4000 cmcat.cmdisk−2, catalyst inks were dripped over the polished glassy carbon-based rotating ring-disk electrode  and allowed to dry at 60 °C overnight. After this, the ORR activity and electron selectivity of the catalysts were evaluated. The electrocatalytic ORR activity was measured at a scan rate of 10 mV s−1 in a N2 or oxygen (O2) saturated 0.1 M aqueous KOH solution (pH = 13).The catalyst ink was created by sonicating 5 mg of catalyst powder with 140 µL of anhydrous ethanol, 140 µL of deionized water, and 20 µL of 5% Nafion solution for 30 min. Before beginning the electrochemical test, the working electrodes  of the RRDE were finished with an application of alumina slurry to smooth out any rough edges. After pipetting 7.0 µL of the ink containing a catalyst loading of ~0.117 mgUsing the following equation (1), all potentials were calibrated to a reversible hydrogen electrode ,26.E, bulk oxygen concentration (1.2 × 10−6 mol cm−3 for 0.1 M KOH solution), oxygen diffusion coefficient (1.9 × 10−5 cm2 s−1), and kinetic viscosity of the electrolyte (0.01 cm2 s−1 for 0.1 M KOH solution).The Koutecky–Levich equation can be used to calculate the number of electron transfers per oxygen molecule involved in oxygen reduction based on Equations (2)–(4) ,26.(2)1The surface morphology of GO and graphene were shown in Transmission electron microscopy (TEM) is another useful tool for determining the quality of exfoliated graphene. The FETEM image of a graphene sheet shown in It is well known that pure graphite has a major X-ray diffraction (XRD) peak at 2θ = 26.5° and a subtle peak at 2θ = 54.5° . These p−1 and 1588 cm−1, as well as the other functional groups such as hydroxyl , methyl , epoxy C-O-C (1222 cm−1), and C-O (1042 cm−1), respectively  and G (1585 cm−1) bands of the graphene’s Raman spectra , which was indicative of a rising trend for G50-1B (1.21), G100-1B (1.15) and also illustrates the growth of sp2 clusters and the potential for the creation of further graphitic domains [Raman spectroscopy is a crucial tool for characterizing carbon materials because it can tell the difference between single-layer and multi-layered graphene, as well as the size and degree of disorder in the crystals . Figure is of GO . The D bis of GO ,41. The onal way ,41. The  spectra b,c [14,4 spectra b,c. The  the D 13 cm−1 and2 carbon (C-C), ether (C-O-C), carbonyl carbon (C=O), and carboxylate carbon (O-C=O) at 284.8 eV, 286.82 eV, 288.3 eV, and 289.7 eV, respectively  showed two major bands at 285 eV and 532 eV which are due to the presence of the C 1S and O 1s functional groups in the samples . We performed cyclic voltammetry (CV) and linear sweep voltammetry (LSV) to predict and confirm the preliminary electrocatalytic ORR activity. These methods are very useful and straightforward to provide a clear view of the electrocatalytic activity of the prepared electrocatalysts and their effectiveness in electron transfers.Recently, carbon-based ORR electrocatalysts that don’t rely on any metals have been proven to be viable low-cost alternatives to platinum-based catalysis because of their stability, accessibility, environmental acceptability, and surface properties ,23,46. A2-saturated aqueous 0.1 M KOH electrolyte (pH = 13)  and half-wave potential (E1/2) are the two major parameters used to predict the performance of electrocatalysts for ORR. The CV and LSV graphs of GO under the O2-saturated 0.1 M KOH electrolyte display the occurrence of a reduction peak as compared to the GO electrocatalysts under a N2-saturated electrolyte  values of 0.797, 0.664, and 2.254, respectively. The pyrolysis of GO at 900 °C has shown different ORR responses based on the number of boats kept during the thermal annealing process. G50-1B displayed a better ORR response with Eonset and E1/2 of 0.802 and 0.656 as compared to G50-2B (Eonset and E1/2 of 0.785 and 0.640) and G50-3B (Eonset and E1/2 of 0.763 and 0.618) of GO together at the pyrolysis temperature at 900 °C. Likewise, G50-1B (4.797) presented a higher JL value as compared to G50-2B (3.500) and G50-3B (3.019). The use of 50 mg of GO in a single boat in a tubular furnace would facilitate the uniform transfer of heat throughout the alumina boat, and the pyrolysis process also occurred uniformly on the GO, whereas the introduction of two or three boats (each 50 mg of GO) together would reduce the effectiveness of heat dissipation throughout the samples which may slightly alter graphene preparation and their properties so that the ORR performance is also reduced when introducing more than one boat during the pyrolysis process.At first, we carried the CV of the prepared electrocatalysts such as GO, G50-1B, G50-2B, G50-3B, G100-1B, and G100-2B, respectively, at the NpH = 13) A. The LS results C. It is mosphere . We alsoctrolyte B,D. Thisonset, E1/2, and JL values of 0.843, 0.774, and 4.558, respectively) and G100-2B , with a more positive onset potential and stable reduction of oxygen taking place for these electrocatalysts. The electron transfer number was predicted from the LSV carried out at various rotations per minute  at the O2-saturated aqueous 0.1 M KOH electrolyte. The LSV graphs of GO, G50-1B-3B performed at different rpms indicated the three stages of ORR activity in O2-saturated aqueous 0.1 M KOH electrolyte which indicates fairly lower performance in ORR activity  from the LSV graphs performed at different rpms. The slopes of the K-L plots can be used to calculate the number of transferred electrons (n) involved in oxygen reduction as shown in n values of GO, GX 1B, GX 2B, GX 3B, GY 1B, and GY 2B at 0.4 V were 1.69, 2.69, 2.54, 0.68, 3.76, and 3.41, respectively. These results proved the superior ORR activity for G100-1B and G100-2B as compared to other electrocatalysts. The G100-1B and G100-2B electrocatalytic activity can suggest that almost a direct four-electron transfer reaction occurred and may help to produce water as an end product. The better ORR activity of the optimized graphenes may be due to the presence of the higher valence orbital energies of the ORR active atom, which increases the adsorption of OOH* and OH* intermediates.The study on the Koutecky–Levich (K-L) plot is the most common method to prove the electron transfer number  and Pt/C electrocatalysts have displayed superior ORR with an n value close to four, which suggests the direct production of water during the electrocatalytic reaction.We also performed a comparison study with commercial Pt/C electrocatalysts due to the benchmark electrocatalytic activity of Pt/C electrocatalysts for ORR. The CV and LSV graphs of Pt/C electrocatalysts performed with Nctrolyte . In addient flow . The EonK-L plot . The est2 gas during the pyrolysis of GO at 900 °C may show no stronger sorption of N atoms at the graphene basal planes and edges. At the same time, we discussed the better electrocatalytic ORR activity of graphene prepared at 900 °C under a N2 atmosphere as compared with GO and rGO prepared at 250 °C may suggest some atomic-scale N atoms may exist on the graphene or that these may create some defects on the graphene which may be responsible for superior ORR activity. Using an FTIR study, it was also difficult to exactly predict the N-doping on graphene due to the presence of C-N, N-H bending, and C=C stretching peaks present at 1187 cm−1 and 1571 cm−1 that may overlap with other functional groups as explained above . We studied the effect of crystallinity and the expansion of GO under thermal annealing temperatures via XRD and also confirmed the surface property and structural behaviors under various characterization techniques. The overall study conveys the successful synthesis of GO and the effective production of graphene based on tubular furnace diameter and annealing temperatures. Our preliminary results hypothesize that the graphene production may differ based on the tubular furnace quartz tube diameter. Based on the tubular furnace quartz tube diameter the use of the alumina boat size also differs, which may affect the graphene production. Furthermore, we studied the electrocatalytic activity of GO and graphenes. We noticed excellent electrocatalytic behaviors of graphene prepared by the introduction of 100 mg of GO in one or two boats (G100-1B and 2B) at the pyrolysis temperature of 900 °C under an O2 atmosphere as compared to GO and G50-1B to 3B. We found that G100-1B  and G100-2B  displayed better electrocatalytic ORR activity similarly to Pt/C electrodes . We strongly believe that the G100-1B electrocatalytic ORR activity (without any doping) is almost closer to the electrocatalytic ORR of commercial Pt/C electrocatalysts. These findings open up wider opportunities and the graphene properties can be easily turned with slight modifications. We also hope that the ORR activity can be enhanced further by the introduction of atomic-scale noble metals or heteroatoms in prepared graphene. More detailed studies need to be performed on the optimized electrocatalyst to improve the activity further for superior electrocatalytic ORR activity. Our initial findings point to the potential utility of graphene as an electrocatalyst for ORR in fuel cells and metal–air batteries.In this work, we synthesized GO from graphite by modifying Hummer’s method followed by preparing graphene via the thermal annealing method under a N


Our proposed method, network decoupling, is based on analyzing the communities in each network layer individually and then aggregating the analysis results. We (i) describe our network decoupling algorithms for finding communities, (ii) present how network decoupling can be used to express different types of communities in multilayer networks, and (iii) demonstrate the effectiveness of using network decoupling for detecting communities in real-world and synthetic data sets. Compared to other algorithms for detecting communities in multilayer networks, our proposed network decoupling method requires significantly lower computation time while producing results of high accuracy. Based on these results, we anticipate that our proposed network decoupling technique will enable a more detailed analysis of multilayer networks in an efficient manner.Networks (or graphs) are used to model the dyadic relations between entities in complex systems. Analyzing the properties of the networks reveal important characteristics of the underlying system. However, in many disciplines, including social sciences, bioinformatics, and technological systems, multiple relations exist between entities. In such cases, a simple graph is not sufficient to model these multiple relations, and a multilayer network is a more appropriate model. In this paper, we explore community detection in multilayer networks. Specifically, we propose a novel  However, in reality, most systems are defined, not by a single, but by multiple types of relations. For example, a group of friends may be connected through multiple social networking platforms such as Facebook, Twitter as well as by email. Technological networks such as transportation networks can consist of airline, train, or bus routes. To accommodate multiple types of relations, the systems are modeled as a set of networks. This set of networks, each representing a different relation, forms a multilayer network. Here, we focus on composed network), and then apply the existing analysis algorithms for single networks. Given an undirected and unweighted network, the layers can be combined using the primitive Boolean operations AND, OR and NOT.The typical approach to analyzing multilayer networks is to combine all, or a subset, of the layers to form a single network  to use for transporting material, under limited resources. They may want to select combination of which two routes would give the most connectivity. If the relations with respect to each condition is represented as a layer, then only one composed network, formed by combining all or a subset of the layers using an OR operation. The problem of efficiently creating different composed networks through varying combinations of layers and operations has been rarely addressed.These examples demonstrate that the number of composed networks increases exponentially with the layers of the multiplex, and analyzing the entire set is computationally expensive. To date, as discussed in Section 2.2, most multilayer analysis is based on creating We propose to reduce the number of redundant computations through a novel method of network decoupling. In network decoupling, each individual network layer is analyzed independently once and only once, and then the results are combined as required. Network decoupling  has several advantages as follows;Analysis of the different composed networks will incur some redundant computations, since different composed networks can have some of the layers in common. Computational efficiency. Network decoupling reduces the time for analysis. Analyzing each layer separately helps in identifying the relevant edges per layer, and reduces the number of edges to combine.Flexibility of combination. Network decoupling facilitates incorporating changes to the multilayer network, such as addition of a new layer or change in the structure of an old layer. Using decoupling, only the added or changed layer has to be analyzed, and combined as required.Reduced information loss. When analyzing a composed network, it is challenging to understand how the individual layers contributed to the analysis. Using network decoupling, since each layer is analyzed individually, their respective contributions can also be identified.The primary challenge is to design appropriate aggregation functions, such that the communities obtained using network decoupling are similar to those obtained by applying community detection on the composed networkHere, we focus on computing communities in multilayer networks using decoupling. Communities are groups of tightly connected nodes. Using network decoupling, we first find the communities in each individual network and then develop aggregation functions, such that the communities from each layer can be combined to produce the communities in the composed network . The priG1, G2, …, Gx, that are combined using a Boolean operation ⊕ to form the composed network, and a community detection algorithm COMM, that is used to find communities, develop an aggregation algorithm Π, such thatGiven a set of layers the results of finding the communities in the individual layers and then aggregating them via Π, should be similar to the communities obtained from the composed network where the layers are combined using the Boolean operator ⊕. Developing the aggregation algorithm is challenging, since the structure of the composed network can change after combination, and the aggregation process has to account for that change when combining the communities.In other words, we aim to find an aggregation algorithm Π, such that We provide an overview of multilayer network, creation, type of communities in MLN and how boolean operations can be used to combine the layers.A multi-relational data set, can be represented as a homogeneous multilayer network. Each feature is represented as a separate layer. The set of entities remain the same in each layer. The edges, based on relations between the entities, change across the layers with respect to the corresponding feature.We use the Internet Movie Database (IMDb) to illustrate how a multiplex is constructed. The IMDb is an online database that contains information on television programs and movies including actors, directors, genre, and year of release , 2018. Wf1) and drama (f2) to form the two layers, G1 and G2, respectively, and modeled the co-actor relationship among 18 actors (denoted by nodes numbered from 1 to 18). Two actors are connected if they acted in movies of the same genre. Note that although the same 18 actors are present in both layers, the structure varies due to the difference in relations. By taking the information from the two networks together we can gain interesting insights to the data. For example, actors I3 and I8 have never worked together in a drama, but have worked together in a comedy. Also, observe that the actors I4 and I14 have the most connections in the drama genre, whereas actors I9, I10, and I11 are the nodes with the most connections in comedy.An example of the multilayer network is given in an actor is defined as an entity that can represent a particular person, animal, organization, city, country etc. In In recent literature, Hanteer  and BrauA node is the existence of a given actor in a given layer. The same actor present in different layers represents different nodes. In k representing actor i, is denoted as We also differentiate between the actor and their existence in a layer. i et al.  as folloThe pillar community extends across all the layers. For each actor that belongs to a community, all the nodes belonging to the actor must belong to the same community. An example of pillar community is presented in k<NL. Here, NL is the total number of layers. As before, for each actor that belongs to a community, all the nodes belonging to the actor must belong to the same community for k layers. We see a structure of semi-pillar community in The semi-pillar community extends across k layers where 2 ≤ GAND21 (AND composition) and GOR21 (OR composition) for multiplex in We now demonstrate how the different layers of the multiplex can be combined, and how communities are detected in them. Communities in AND-Composed Layers. AND composition allows users to find communities that are related across all the features. C-SG-AND) shows the steps of finding communities in the composed network, using a standard community detection algorithm such as Infomap .Groups of actors who have expertise in working together in all of these conferences: ICDM, SIGMOD and VLDB (DBLP multiplex).Authors who have co-authored a paper published in all of these features: light conditions, weather conditions, road conditions, and speed limit (Accident Multiplex).Accidents that have similar conditions for Communities in OR-composed layers. OR-composition forms a composed network that includes an edge if it appears in at least one of the layers. C-SG-OR. In an OR composition, the composed network is formed of the union of the edges from all the networks, and then the communities are found in the composed network. Examples of queries that can be addressed by the OR composition are;or drama (IMDb multiplex).Actors who have acted together in either a comedy at least one conference (DBLP multiplex).Authors who have co-authored a paper published in at least one condition in common (Accident Multiplex).Accidents that have bridge edges. Formally, if there exists an edge, m in layer k) and n in layer k) where m≠n, then this edge is a bridge edge. In the AND and OR composed-layer of I1 and I5 belong to different communities, but are connected by a bridge edge. The actors I9 and I15 have a bridge edge in the OR composed network, but not in the AND-composed network.We term the external edges that connect two communities as The AND composed networks have smaller, but more communities, than the OR composed networks. In general, the communities in the AND composed layer form subsets of the communities in the OR composed layer. We will leverage this property to develop our aggregation algorithms.G1, G2, G3, and G4. Also consider two composed networks formed from the multiplex, namely, GAND2AND31 and GAND2AND41. In this case, the composed layer related to GAND21 remains unchanged, but has to be recomputed, leading to extra computations.The traditional method of first forming the composed network and then analyzing can be computationally expensive when multiple composed networks have to be considered. This approach can lead to redundant operations. Consider a multiplex with four layers We propose network decoupling for efficient community detection on multiplex networks. The communities in each layer are identified separately and the results are then aggregated to obtain the results with respect to the composed network. The challenge is to develop aggregation algorithms, that can correctly aggregate the communities from each of the layers to obtain the communities over the composed network. We now present the aggregation methods for AND and OR composition. For ease of understanding we will discuss the algorithms with respect to two layers. Note, however, that our algorithms can be easily extended to multiple layers.AND_composed network) in Santra et al.  rather than being fully or partially merged with other communities, then C is a self-preserving community. A community is self preserving if the vertices in it are other communities in the graph. Thus, the subgraph forming a self-preserving community is not affected by changes to the remainder of the network. The communities in Layer 2 in A self-preserving community indicates that the community is loosely connected with the remainder of the network. Removing parts of the community will not change the structure or composition of the if the communities from the layers are self preserving, then the communities of the AND-composed graph can be obtained by taking the intersection of the vertices of the communities from the individual layers.When two layers are combined using an AND operation, then certain edges are deleted from each layer, and thus from certain communities. If the communities are self preserving, then this deletion will only affect that community and not the others. This is the main result of Santra et al. , which iCV-AND , then, two dissimilar groups are marked to be similar, which is incorrect.As an example, consider the community  network , which iedges rather than vertices as follows. Here we consider pairs of communities, one from the first layer and the other from the second layer, and obtain the new community by taking the common edges among the pair. For every pair of communities, Gi and Gj, the edge-based community intersection, We address these limitations by developing a community detection method, CE-AND see , that islabel an edge as internal (if both end points are in the same community) and external or bridge otherwise.We assume that the communities in the individual layers and the composed network have high clustering coefficients. That is, we do not consider accidental communities such as an edge or a line graph, that are formed due to an algorithmic artifact rather than the structure of the network. If such trivial communities are formed, we consider each vertex in them as a singleton community. The clusters formed by the intersection algorithms do not have this restriction, since they are not obtained using community detection algorithms.We now present a proof of how well the clusters obtain by X∈Ψ, there will exist a set of communities i ≤ m, that form a partition of the vertices in X, if and only if, the set of edges common to all layers have the same label in all the layers.Lemma 3.1. For any given cluster Proof. We first prove the condition that if the common edges have the same label in all the layers, then the set of the union of vertices in X∈Ψ.X be UX. Let the set of vertices belonging to community VX. Since the communities are disjoint to prove that VX is a partition of UX, we have to prove that VX = UX.Let the set of vertices belonging to the cluster UX ⊆ VX. We simply select the communities such that all vertices in UX are included.It is easy to show that there exists a set of communities such that VX⊆UX by contradiction. Let v be a vertex that is in set VX but not in UX. Since CE-AND retains all the common internal edges, and v is not in UX, therefore v will be connected to its neighbors in VX by one or more external (or bridge) edges. Since we assume that all common edges have the same labels, therefore in none of the layers v is tightly connected to any subset of VX. Moreover, the communities in the composed network have high clustering co-efficient (or are singletons). Since v is not tightly connected to vertices in VX it cannot be part of the community. Thus our assumption was wrong, and VX ⊆ UX. Taken together, VX ⊆ UX and UX ⊆ VX; thus UX = VX, and VX is a partition of UX.We prove For the only if part we show that if the common edges do not have the same labels in all the layers, then there may not exist a set of communities that form a partition of the vertices in a given cluster.We provide such an example in The community in all layers are considered, CE-AND produces two communities, Also consider the community OR composed networks). The number of edges in the OR-composed network is the union of the edges in each layer. For any two layers Gi and Gj, the total number of edges is |Ei∪Ej|.We now consider how to obtain communities in composed networks formed using the OR operation . Vertices that are not assigned into communities are each separately assigned to a metanode (Line 5–9). Connect two metanodes, U and V via a metaedge, if there exists an internal edge, in at least one of the layers between an element (node) of U and an element (node) of V (Line 10-14). Apply appropriate weights to these edges (Line 15). Apply community detection on the metagraph (Line 16). The communities in the OR-composed network are obtained by expanding the metanodes in the communities obtained by the CE-OR algorithm.Find the common communities in all the network layers (Line 1) by using CE-AND. Then construct a metagraph (OR-MG), as follows. Each metanode represents in at least one of the layers.The metanodes represent vertex sets of varying sizes, and the number of edges between them represent the degree of similarity. Although the original graph is unweighted, the edges in the metagraph are weighted to quantify the extent of this similarity. A critical component of the CE-OR algorithm is based on correctly assigning these weights. We connect two meta nodes only if at least one pair of vertices from each meta node are connected by an internal edge, A, B), let VA and VB be the set of nodes in the meta communities A and B, respectively. Further, let the set of all edges  between VA and VB be EA, B. We use the following two strategies to compute the weight of the metaedge;For any meta edge  = |EA, B|Fractional is the fraction of connected nodes between the two communities; I8 are used to form the metanodes . Thus at least one of the communities has an internal edge that was bridge edge in all the layers. This goes against our criteria that all internal edges for communities in the composed network, should be internal in at least one of the layers. Thus our assumption is wrong and VK ⊆ UK. Since the communities are disjoint and UK = VK, thus the statement is proven.To prove the only if direction, we show that if the communities in the OR-composed layers have internal edges that were bridge edges in all the layers, then there may not exist a set of communities that form a partition for the vertices in a given metanode clusters.An example of this is given in Consider the community However in the community The implication of Lemma 3.1 and Lemma 3.2 is that the CE-AND or CE-OR operations are successful if they create clusters that contain one or more communities in the composed networks in their entirety. Thus the communities can be divided into groups, such that each group can be mapped to exactly one cluster formed by the CE-AND or CE-OR operation. Therefore, the vertices in the composed network can be partitioned into subgraphs, with each subgraph relating to a cluster. Hence CE-AND and CE-OR operations are successful when each layer is formed of several loosely connected subgraphs, and bridges connecting the subgraphs do not change across the layers.The primary limitations of our CE-AND and CE-OR algorithms is due to the non-inclusion of bridge edges. In the AND-composed network, we rationalize this non-inclusion by positing that communities formed solely of bridge edges cannot be dense, and hence are not strong communities. In the OR-composed network, we only exclude an edge if it is a bridge edge in all the layers.We demonstrate how CE-AND and CE-OR can be used as building blocks for the pillar and semi-pillar communities described in Section 2.2. Note that pillar and non-pillar communities are not dependent on how the networks/layers are combined, but on which communities are common across a given set of layers.Since in pillar communities the same set of vertices form communities in every layer, therefore as per Lemma 3.1, the communities formed by CE-AND will be pillar communities. However, due to the strict restrictions of the CE-AND criteria, i.e. the edge has to be present in every layer, some vertices from pillar communities may be missed. To obtain these missing vertices, we then extend the communities found in CE-AND as per p<k. For each combination of layers we compute the communities using CE-AND. Note that since we use the decoupling method, therefore we need to compute the communities in each layer exactly once, and then combine the results. We identify the communities with the highest number of nodes, and extend them when possible using CE-OR. These communities across the layers form the semi-pillar communities.To find the semi-pillar communities, we take combination of all possible p layers from k layers, where 2 ≤ Infomap  was the graph obtained by the generator. We applied cross perturbation to create layers (L2 and L3), as follows We selected two edges  and , and replaced them with new edges  and . Thus the number of edges and the degree distribution remain the same but the structure changes. In layer L2 we applied this perturbation to 1% of the edges and in layer L3 to 5% of the edges. Vertices:32,768; Edges in L1:230,445; Edges in L2: 230,445; Edges in L3:230,445.Ground Truth and Accuracy Metrics: We use the communities obtained using C-SG-AND and C-SG-OR as the ground truth. We disregard singleton communities. We use two metrics to evaluate the accuracy of the communities - i) Normalized Mutual Information (NMI) that measures the quality with respect to the participating entity nodes only and ii) modified-NMI that also takes into account the topology of the communities. For both metrics higher is better, with maximum value of 1 and minimum of 0 [definitions in Labatut ( Labatut ]. Each maccuracy obtained with CE-AND is higher than that from CV-AND.For the AND-composed networks we show in wa) and Fractional (wf). The results show that the accuracy obtained using both the metrics are similar.For the OR-composed networks we show in We now compare the time taken to obtain the communities using the aggregation methods  with respect to C-SG-AND and C-SG-OR. community edges is required to generate the meta graph (OR-MG) on which we apply Infomap. If the layers are sparse and the multiplex contains many bridge nodes, then cost of generating the meta graph and applying Infomap will become an overhead as compared to simply applying Infomap on OR graph (C-SG-OR approach). This can be seen from the DBLP multiplex where sparse layers (density of densest layer (SIGMOD) = 0.0001) make the CE-OR 67% less efficient as compared to C-SG-OR. However, for multiplexes with fewer bridge edges , CE-OR is significantly faster.CE-OR algorithm achieves a better accuracy as compared to the baseline algorithms across a number of ground truth data sets.We compare the performance of our proposed decoupling based community detection algorithms against 16 community detection algorithms for multiplexes presented in  in both community sets, it is called an agreement. The value of omega index ranges between 0 and 1. Here, 1 means two sets of communities are identical to each other. Formally, the omega index is computed as;Omega index value is calculated by taking the mean of the number of agreements on two community sets l = the maximum number of times a node pair appears together in both C1 and C2 at the same time,N = total number of possible node pairs,Aj = number of node pairs that are grouped together j times in both communities, andNj, 1, Nj, 2 = number of node pairs that have been grouped together j times in C1, C2, respectively.We have the ground truth communities available for real world and synthetic data sets. We apply our aggregation algorithms (CE-OR) on the data set AUCS which is 90 percent pillar, DKPOL, PEP and PNP which are 100 percent pillar, and SEP and SNP, which are semi-pillar.on an average the CE-OR (Metric-Aggregate) algorithm has 89% accuracy and CE-OR (Metric-Fraction) algorithm has 82% accuracy, which is significantly higher than the other methods.We compared the accuracy of 17 community detection algorithms along with our proposed CE-OR aggregation algorithm over real world and synthetic data sets which have ground truth community structure available. The algorithms used are: flat_nw and flat_ec  values for the 16 existing community detection algorithms along with our proposed CE-OR aggregation algorithm for each data set. However, for AUCS data set, CE-OR does not perform better than many of the existing algorithms as AUCS does not have complete pillar partitioning. Our CE-OR algorithm improves the accuracy for data sets with 100% pillar partitioning community structure or known semi-pillar community structure. All other data sets with pillar partitioning the accuracy of CE-OR ranges from 85% (DKPOL) to 100% (PEP).In We now define the NOT composition, and demonstrate our proposed network decoupling methods can be used to efficiently and accurately analyze networks composed of a combination of Boolean expressions.complement of the edge set of that layer, i.e. the new layer will have all those edges that are not part of the original layer. Communities in a NOT layer will represent the groups of nodes that are not strongly connected. Examples of queries that can be answered using NOT areNOT of a layer will represent the not acted together in a comedy (IMDb multiplex)Groups of actors who have never co-authored a paper in VLDB (DBLP multiplex)Groups of authors who have did not have same Light condition (Accident multiplex)Groups of accidents that With respect to the single graph approach, these types of analysis can be handled by first generating the NOT layer and then applying community detection. AND, OR and NOT can be applied in different combinations, expanding the spectrum of analysis options. Although taking the complement of a layer is expensive and increases the number of edges in that layer, the cost depends on the graph density of the layer. Also, rewriting the expressions using the De Morgan's law can reduce the costs.We demonstrate how general Boolean expressions can be computed using the decoupling approach. We use the DBLP multiplex with authors who publish papers at different conferences to address interesting analysis objectives. We consider all papers that were published from 2003 to 2007 in two high ranked conferences (VLDB and SIGMOD) and two medium ranked conferences (DASFAA and DaWaK). Based on whether two authors (nodes) have co-authored a paper in a particular conference, four layers were generated - all with the same 5116 vertices. VLDB , SIGMOD , DASFAA  and DaWaK .Few interesting analysis objectives that can be computed on the DBLP multiplex using Boolean expressions are as follows:both the highly ranked conferences, but have never published in either of the medium ranked conferences?Which collaborating groups who have published in Which co-author groups have only been able to publish in the low to medium rank conferences?Which author groups have published only in VLDB?Which are collaboration groups who have published inboth the highly ranked conferences, but havenever published in either of themedium ranked conferences?”, we will compare the evaluation process for the traditional single graph approach and the proposed decoupling approach. Single graph approach (SG): For the SG approach, the Boolean expression will correspond to SG: COMM[(VLDB AND SIGMOD) AND NOT (DASFAA OR DaWaK)]Based on the requirements of the analysis, it is important to figure out (a) the multiplex layers required and (b) the order in which the layers have to be composed using AND, OR, NOT. For the first analysis, “This corresponds to first generating the required composed single graph and then applying the community detection algorithm to find the final set of communities. These communities acts as the ground truth. We used Louvain Blondel et al.  to find DEC1: COMM(VLDB) CE-ANDCOMM(SIGMOD) CE-ANDCOMM (NOT (DASFAA OR DaWaK))Using network decoupling, this expression will correspond to That is, the layer-wise communities are composed to obtain the final set of communities. Alternatively, De Morgan's Laws can be applied to obtain another expression for the decoupling based boolean composition -DEC2: COMM(VLDB) CE-ANDCOMM(SIGMOD) CE-ANDCOMM (NOT(DASFAA)) CE-ANDCOMM(NOT (DaWaK))NOT (DASFAA OR DaWaK) by using the traditional OR of two layers and then take its complement. DEC2 uses the decoupling approach using operators CE-AND, and NOT as discussed in this paper. The layers of DBLP used above are very sparse, especially DASFAA and DaWaK. Hence, DEC2 will not be as efficient as DEC1 since it has to compute the complement of two layers (resulting in dense graphs) and then apply the decoupling approach. DEC1, on the other hand, has only one complement to compute.We compare the efficiency of DEC1 and DEC2 with the single graph approach. We will evaluate the For accuracy, the NMI and m-NMI values for the communities obtained by DEC1 and DEC2 have been compared against the communities obtained by SG. Both method, DEC1 and DEC2, provide more than 95% accuracy.same set of communities. In DEC1, the number of CE-AND compositions are 2 whereas in DEC2 there are 3. Moreover, as the layers of the DBLP multiplex are sparse, their complement is dense. Thus, in DEC2 the Louvain is applied to two dense NOT layers. Thus, DEC2 will have a higher cost as compared to DEC1. Our results show that DEC1 is 2 times faster than DEC2. Therefore, it is very important to understand when to rewrite the expression  especially when the NOT operator is used on a composition of layers. Finally, it is interesting to note that even with 2 dense graphs, DEC2 comes out better than the single graph approach. This further validates our decoupling approach even in the presence of NOT operator.Both DEC1 and DEC2 resulted in the One hundred and two communities are obtained from DEC1 and DEC2 that satisfy the requirement. Surajit Chaudhari who won the VLDB 10-Year Best Paper Award (2007) with Vivek Narasayya and VLDB Best Paper Award (2008) with Nicolas Bruno, apart from winning ACM SIGMOD Contributions Award (2004).Divyakant Agrawal who has 24000+ citations (Google scholar).Peter A. Boncz and Stefan Manegold from highly cited paper (350+ citations for MonetDB/XQuery) in SIGMOD 2006, and also won the VLDB 10-year award.Recently, many analytical tasks have used multilayer networks to handle varying interactions among the same or different sets of entities such as co-authorship network in different conferences  layers of a HoMLN using Boolean and other operators or by considering the entire MLN as a whole, leading to issues with respect to loss of information and computational inefficiency.Recently, community detection algorithms have been extended to Homogeneous MLNs (see reviews Fortunato and Castellano, Recent works include Jin et al.  using a To identify the communities in the temporal multiplex graph, the authors in Rebhi et al.  proposedBio-inspired optimization has successfully solved the problem of community detection in network that we observe from the work Osaba et al.  where thWe presented algorithms for efficiently finding communities in Boolean composed layers of multiplex networks. The results show that for most cases our algorithms are significantly faster than the standard methods and produce results of similar quality. The only cases that our algorithm fails is when the layers have significantly more bridge edges. We further demonstrated that our network decoupling methods can be used as building blocks for different types of multilayer communities in literature, such as pillar and semi-pillar communities. In these cases too, network decoupling produces results with higher accuracy compared to other baseline methods. The only case our method produces lower accuracy is when a network designated to have pillar communities does not have the complete pillar information. Given these results we can posit that network decoupling is an effcient and effective method for finding communities in homogeneous multilayer networks.In future, we will investigate how to include some percentage of bridge edges without increasing the computation time. We also plan to explore adaptive techniques that can select between the network decoupling and standard methods as suitable. Finally, we also aim to develop methods to include meaningful NON-BOOLEAN combinations for weighted networks.The original contributions presented in the study are included in the article/AS and FI conducted the experiments and wrote the paper. SC, SB, and KM helped in designing the experiments. SC and SB helped in writing and editing. All authors contributed to the article and approved the submitted version.


Our fabricated device affords an interesting label-free, rapid, and reproducible bacterial sample analysis based on the density of the AuNRs when functionalizing flake-like 3D graphene, which can help facilitate label-free bacteria sensing platforms.Surface-enhanced Raman spectroscopy (SERS) is an effective technique for biosensing, enabling label-free detection of biomolecules with enhanced sensitivity. There is a tremendous probability of signal failure in Raman frequencies because of the scattering of the Raman radiation in liquids, effective SERS improvement is required to reduce this issue when considering liquid specimens. We examined a liquid bacterial sample, investigating the electrostatic interactions of the bacterial samples with gold nanorods (AuNRs) and graphene. We established a voltage-gated 3D graphene functionalized with an AuNR-based device on the silicon substrate for SERS measurements when the applied voltage ranges from 0 to 3 V. Moreover, AuNRs density-susceptible bacterial sample analysis with varied concentrations of bacterial samples has also been described. Using bacterial SERS analysis, the bacterial components amide II (1555–1565 cm Graphene is a two-dimensional atomically thick substance that has been enormously researched for extensive applications because of its remarkable electrical and thermal properties ,2,3,4,5.There are several papers that have shown the improvement in SERS enhancement, introducing several techniques such as the combination of metal–organic frameworks (MOFs) with plasmonic metal nanoparticles , silver S. typhi and Gram-positive Listeria monocytogenes as model bacteria for studying the interaction of bacteria between the AuNRs and 3D graphene in a 10 × 10 mm fabricated device when the applied voltage ranges from 0 to 3 V. In this study, our Raman spectra results showed that the spectral values are consistent with their corresponding bacteria and are reproducible. The interaction between the graphene and bacterial surface is known and the chemical potential of the bacterial membrane can change the vibrational properties of graphene  and Listeria monocytogenes [ATCC 15313] were cultured in Luria–Bertani broth  medium until the optical density came to 0.15, 0.10, and 0.05 for three different bacterial suspensions. Afterward, the LB medium was removed by subjecting it to centrifugation at 8000 rpm for 10 min, removing the supernatant, and dispersed in DI water for 3 different concentrations of bacteria. The concentration of the bacteria was calculated by the previously introduced method [8, 8.0 × 107, and 4.0 × 107 cells/mL.d method . The thr2/Si substrate. The electrode was prepared by keeping the device on the hot plate and heating it to 160 °C and some indium was placed on the device edge which covered the area of graphene and we waited 1 min to melt the indium. Thereby, the copper tape was attached to the melted indium and kept at room temperature to harden the attachment between the copper tape and the device. Then, the 4 different concentrations of hydrophobic AuNRs such as 10, 20, 40, and 80 µg/mL with a volume of 20 µL were deposited on the surface (10 × 10 mm) of the graphene by solvent evaporation.Our device consists of directly grown MOCVD 3D graphene on a SiORaman spectroscopy was performed with a commercial Raman system , equipped with a YAG laser, wavelength of 532 nm, a laser spot size of 1 μm and a power of 70 μW was used during the measurement. For collecting the Raman spectra, a distance of 8 mm, and a 10× objective lens from Olympus were used and the acquisition time was 5–10 s. For every measurement, 5 µL of the bacterial suspension was placed into the well of the device. We have performed all the measurements three times to maintain the accuracy associated with the integrated area enhancement.−1, the G peak at ~1585 cm−1, and the 2D peak at ~2700 cm−1. The copper precursor acts as a catalyst to enhance the formation of graphene, just like regular Cu catalytic substrates. Therefore, the precursor remains in gas form and does not deposit on the substrate. We also did not observe any Cu-related peak on Raman spectra above baseline which normally forms in the 300~700 regime.The characterization of flake-like 3D graphene has been performed by using a scanning electron microscope (SEM), and the Raman spectra of graphene see . The sca2. the size of the flake-like protruded part of graphene film varies, but typically does not exceed 100 nm.Since the described synthesis method is a CVD-based method, the size of graphene is continuous throughout the entire substrate, which is ~1 cm−1 represent S-H stretching that confirmed the thiol functional group in AuNRs, and the visual observations of the AuNRs from aqueous to organic solvent also confirm the hydrophobication of the AuNRs and redispersion in an organic solvent  with a quartz cell in the wavelength range 450–850 nm. However, the hydrophobication of the AuNRs was characterized by FT-IR manufactured by Thermo Scientific, Waltham, MA, USA. The FTIR spectra at 2550–2600 cmvent see . The meavent see . A previAtomic force microscopy (AFM) is one of the most acceptable techniques for measuring the height profile of the adsorbed molecules on a substrate. The height profiles of the adsorbed and unabsorbed AuNRs on the graphene surface have been compared in 7 cells/mL. Moreover, we are the first to report the functionalization of 3D graphene surfaces with the AuNRs and it enables both CM and EM ways together to study concentration-based bacteria sensing in a label-free biosensing platform. However, electromagnetic enhancement for graphene has been widely studied [Herein, we introduced a 3D graphene-AuNR-based voltage-gated device for liquid bacterial SERS analysis for large-area SERS enhancement. We study how the density of AuNRs on 3D graphene affects bacterial SERS analysis. We also study how bacterial surface charge affects the analysis of bacterial SERS using a 3D graphene system. We analyzed the best amount of AuNRs on 3D graphene to improve SERS spectra in both CM and EM enhancements. As a result, we successfully detected the liquid bacterial SERS signature even at a low concentration of 4.0 × 10 studied ,45. EM o studied ,47. The Our synthesized Au rods are sensitive to polarization (direction of the electric field oscillation of the incident light). We investigate the density controllability of the decorated AuNRs on the graphene for bacteria sensors using the SERS platform. We control the density of the AuNRs on the top of the graphene by changing the concentration of the AuNRs during the deposition of AuNRs on the graphene by solvent evaporation, AFM image is shown in −1) [Listeria monocytogenes, shown in S. typhi bacteria. The integrated area enhancement of the D band is shown in The amide group is a constituent of bacteria. We have shown the integrated area for the D band of 3D graphene with increasing density of AuNRs on its surface and the amide III vibrations (1250~1350 cm−1)  superimp−1) also showed a similar enhancement because of the superimposing of amide II (1555–1565 cm−1) [Listeria monocytogenes and S. typhi, respectively, which is drastically increased with the high density of AuNRs.However, the G band of graphene (~1585 cm65 cm−1)  bands wiGram-negative bacteria have an isoelectric point of approximately ~5 and Gram-positive bacteria of approximately ~3 . So, it Listeria monocytogenes and S. typhi bacteria and their interaction with the 3D graphene-AuNRs at different concentrations may affect the intensity ratio of D and G bands. A Gram-negative bacterial cell has a thin peptidoglycan layer and a surface membrane made up of proteins, phospholipids, and lipopolysaccharides, whereas a Gram-positive cell has a thick peptidoglycan layer made up of teichoic and lipoteichoic acids. Gram-negative cells have an additional layer of the outer membrane while having a much thinner coating of peptidoglycan. In contrast to Gram-positive bacteria (Listeria monocytogenes), Gram-negative bacteria (S. typhi) maintain a stronger cell wall that offers higher resistance to the sharp edges of graphene. At higher concentrations of bacteria, the D band intensity is typically higher than the G band intensity, showing a more disordered graphene structure. This could be due to several factors, such as increased physical contact between the bacteria and the graphene surface [2 hybridized carbon atoms, while the G band corresponds to the stretching modes of the same. When bacteria are present on the graphene-based material, the interactions between the bacteria and the graphene surface can affect the vibrational modes of the graphene sheet. The intensity ratio of the D and G bands in Raman spectroscopy can provide information about disorders in the graphene structure [To closely figure out the concentration effects of the bacteria on the SERS platform, we performed concentration-based SERS analysis for both bacteria. The result shows the close binding of the Gram-negative to the AuNRs and graphene by charge transfer and the increasing concentration of the bacteria provides higher Raman intensity whereas the Gram-positive bacteria showed less affinity compared to the Gram-negative bacteria . The dif surface  The D antructure . The pretructure . However7 cells/mL. This demonstration showed that for a 80 µg/mL conc. of AuNR sample and 20 µL, the deposition volume on 10 × 10 mm of graphene surface provides the highest SERS integrated area enhancement. Additionally, the bacterial concentration-based study will provide significant information for the further development of label-free bacterial biosensing devices for quantitative studies. In our current system, we have not used polarization-controlled light sources for Raman measurement. We could perform further studies using a polarization-controlled light system to develop a novel Raman biosensor system.In summary, we have shown a voltage-gated liquid Raman setup and analyzed the effect of AuNRs density on flake-like 3D graphene for label-free bacteria sensing at low concentrations of bacteria. The deposition of the AuNRs on the graphene enables the large-area SERS enhancement while handling the liquid samples. Our results showed the relationship between the AuNRs density on the graphene and the rate of integrated area enhancement of SERS and the SERS enhancement factor when comparing with and without bacterial suspension with a concentration as low as 4.0 × 10Our work could clear the way for the application of Raman spectroscopy for the rapid analysis of the bacterial samples for clinical samples as we showed the liquid bacterial sample analysis as a label-free biosensor—for example, the rapid and quantitative bacterial sample analysis directly after collecting the sample from the patients. Additionally, the liquid-SERS enables a culture-free and less time-consuming method to analyze the liquid samples and provides a foundation for label-free and quantitative bacterial sample analysis.