Standard Descriptors Research Articles

A new lineage nomenclature to aid genomic surveillance of dengue virus.

Dengue virus (DENV) is currently causing epidemics of unprecedented scope in endemic settings and expanding to new geographical areas. It is therefore critical to track this virus using genomic surveillance. However, the complex patterns of viral genomic diversity make it challenging to use the existing genotype classification system. Here, we propose adding 2 sub-genotypic levels of virus classification, named major and minor lineages. These lineages have high thresholds for phylogenetic distance and clade size, rendering them stable between phylogenetic studies. We present assignment tools to show that the proposed lineages are useful for regional, national, and subnational discussions of relevant DENV diversity. Moreover, the proposed lineages are robust to classification using partial genome sequences. We provide a standardized neutral descriptor of DENV diversity with which we can identify and track lineages of potential epidemiological and/or clinical importance. Information about our lineage system, including methods to assign lineages to sequence data and propose new lineages, can be found at: dengue-lineages.org.

The application of chemical similarity measures in an unconventional modeling framework c-RASAR along with dimensionality reduction techniques to a representative hepatotoxicity dataset

With the exponential progress in the field of cheminformatics, the conventional modeling approaches have so far been to employ supervised and unsupervised machine learning (ML) and deep learning models, utilizing the standard molecular descriptors, which represent the structural, physicochemical, and electronic properties of a particular compound. Deviating from the conventional approach, in this investigation, we have employed the classification Read-Across Structure-Activity Relationship (c-RASAR), which involves the amalgamation of the concepts of classification-based quantitative structure-activity relationship (QSAR) and Read-Across to incorporate Read-Across-derived similarity and error-based descriptors into a statistical and machine learning modeling framework. ML models developed from these RASAR descriptors use similarity-based information from the close source neighbors of a particular query compound. We have employed different classification modeling algorithms on the selected QSAR and RASAR descriptors to develop predictive models for efficient prediction of query compounds’ hepatotoxicity. The predictivity of each of these models was evaluated on a large number of test set compounds. The best-performing model was also used to screen a true external data set. The concepts of explainable AI (XAI) coupled with Read-Across were used to interpret the contributions of the RASAR descriptors in the best c-RASAR model and to explain the chemical diversity in the dataset. The application of various unsupervised dimensionality reduction techniques like t-SNE and UMAP and the supervised ARKA framework showed the usefulness of the RASAR descriptors over the selected QSAR descriptors in their ability to group similar compounds, enhancing the modelability of the dataset and efficiently identifying activity cliffs. Furthermore, the activity cliffs were also identified from Read-Across by observing the nature of compounds constituting the nearest neighbors for a particular query compound. On comparing our simple linear c-RASAR model with the previously reported models developed using the same dataset derived from the US FDA Orange Book (https://www.accessdata.fda.gov/scripts/cder/ob/index.cfm), it was observed that our model is simple, reproducible, transferable, and highly predictive. The performance of the LDA c-RASAR model on the true external set supersedes that of the previously reported work. Therefore, the present simple LDA c-RASAR model can efficiently be used to predict the hepatotoxicity of query chemicals.

Face-degree-based topological descriptors of germanium phosphide

In graph theory, topological indices are numerical metrics that give information about a graph’s structural traits. The face index is one such topological index that describes planar networks. Since the discovery of graphene, the genealogy of two-dimensional 2D crystals has expanded and currently contains a large variety that has all logical electrical properties required for nano electronics. Nanotechnology benefits from the use of materials that resemble Dirac, such as silicon, graphite, semiconductors, and germanene, as well as TMDC (phosporene), a transition metal dichalcogenide. In contrast with standard topological descriptors, which are numerical values utilised to characterise molecular structures, the face index presents a potentially more comprehensive method for obtaining structural details. In investigations involving quantitative structure-property relationships (QSPR), this may result in more precise predictions. We calculated the recently created face index of Germanium Phosphide (GeP) and its many shapes, including triangle, rhombus, hourglass, and concentric circles.

Kernel Trait and Genetic Variability Analysis in BC2F1 Maize Lines Derived from Zea nicaraguensis Crosses

Maize (Zea mays L.) is an important cereal crop with significant applications in food, feed and industrial applications. This study aimed to increase maize yield and quality by evaluating core traits in introgressed Zea nicaraguensis individual’s recipients of LM13 and LM14 maize inbred lines. Kernel type, shape, color, dimensions and weight were assessed in 35 BC2F1 plants using standardized descriptor guidelines. Analysis of genotypic and phenotypic coefficients of variation, heritability and genetic progress showed significant genetic diversity and the influence of environmental factors. Significant sources of variability highlighted by principal component analysis were kernel color, endosperm color, and 100-seed weight. High heritability and genetic progress in kernel color and length-to-width ratio indicate great selection potential. Reintroducing the diversity lost in cultivated maize inherent in Zea nicaraguensis has the potential to improve both its agronomic performance and quality. Future research should aim to identify genetic markers and examine the interaction between genetic and environmental influences to optimize maize varieties for specific environments and consumer preferences, ultimately contributing to global food security and agricultural sustainability.

Grain diversity of rice collection from South Sulawesi, Indonesia

Abstract South Sulawesi province is among the Indonesia rice barns, which is expected to buffer the national rice supply. Although rice stock is mainly produced from high-yielding superior varieties, local germplasm is still the main basis for variety development. Local germplasm has been adapted to various agro-ecosystems and thus has potential as a genetic source for adaptation to climate change. This study was aimed at measuring the diversity of rice germplasm from South Sulawesi based on its grain characteristics. A total of 98 rice accessions that were conserved in the agricultural genebank were examined. Grain length, shape, color, and other grain-related characters were observed following the international standard descriptors for rice. NTSYS-PC software version 2.2 was used to perform clustering analysis. Rice collections from South Sulawesi showed diversity in their grain characteristics. The majority of seeds are awnless, have medium length, medium shape, and straw-colored lemmae-palea and attributed with medium-sized and straw-colored sterile lemmae, and the dehulled grain bran is predominantly white. The rice accessions can be grouped into eight clusters at a similarity level of 52%. This diversity and similarity information is important for germplasm management and utilization. However, due to the limited number of characters used, information from this study cannot yet be used as a basis for their management. More comprehensive characterization efforts need to be conducted in order to make this study more usable, both in supporting conservation and for their utilization

Terminologia Anatomica in Latin-American countries: a systematic review.

Terminologia Anatomica (TA) is a unique collection of technical terms that allow communication in anatomy and medicine around the world. Considering this, we reviewed articles published by Latin American authors on Terminologia Anatomica and synthesized the main results found in this article. This study is a systematic review about Terminologia Anatomica that focuses on non-English-speaking countries in Latin America. The database used was Scopus via Elsevier. 207, and candidate articles were identified after applying the search strategy and with no restriction of year of publication. After the exclusion of articles whose authorship was not Latin American, 68 articles were filtered based on their titles and abstracts without the exclusion of any of them. These articles were fully evaluated resulting in 66 articles that met all the inclusion criteria of this review. We collected the following data: title of the article, year of publication, journal of publication, keywords of the study, country of origin, and aim of the article. Among the analyzed articles, 22 proposed changes to terms present in Terminologia Anatomica, 15 of them proposed the inclusion of terms for Terminologia Anatomica, and several articles sought to explain the existence of the existing terms. It is necessary to analyze the terms that are and their origins in the Latin America languages to evaluate their coherence and anatomical correspondence. A standard descriptor for Terminologia Anatomica was not obtained and it is a limitation since eventual articles may not have been obtained. As the study evaluates only articles that were published in journals indexed in Scopus, some articles published in non-indexed journals were not included.

Novel Detection and Progression Markers for Diabetes Based on Continuous Glucose Monitoring Data Dynamics.

Develop a diabetes diagnostic tool based on two markers of continuous glucose monitoring (CGM) dynamics: CGM entropy rate (ER) and Poincaré plot (PP) ellipse area (S). 5,754 daily CGM profiles from 843 individuals with type 1, type 2 diabetes, or healthy individuals with or without islet autoantibody status were used to compute two individual dynamic markers: ER (in bits per transition; BPT) of daily probability matrices describing CGM transitions between eight glycemic states, and the area S (mg2/dL2) of individual CGM PP ellipses using standard PP descriptors. The Youden's index was used to determine "optimal" cut-points for ER and S for health vs. diabetes (case 1); type 1 vs. type 2 (case 2); and low vs. high type 1 immunological risk (case 3). The markers' discriminative power was assessed through the area under the receiver operating characteristics curves (AUC). Optimal cut-off points were determined for ER and S for each of the three cases. ER and S discriminated case 1 with AUC = 0.98 (95% CI: 0.97-0.99) and AUC = 0.99 (95% CI: 0.99-1.00), respectively, (cut-offs ERcase1 = 0.76 BPT, Scase1 = 1993.91 mg2/dL2), case 2 with AUC = 0.81 (95% CI, 0.77-0.84) and AUC = 0.76 (95% CI, 0.72-0.81), respectively (ERcase2 = 1.00 BPT, Scase2 = 5112.98 mg2/dL2), and case 3 with AUC = 0.81 (95% CI, 0.77-0.84) and AUC = 0.76 (95% CI, 0.72-0.81), respectively (ERcase3 = 0.52 BPT, Scase3 = 923.65 mg2/dL2). CGM dynamics markers can be an alternative to fasting plasma glucose or glucose tolerance testing and identifying individuals at higher immunological risk of progressing to type 1 diabetes.

Morpho-genetic Diversity and Traits’ Relationship in Castor Germplasm

Adequate knowledge of the extent of dissimilarity among germplasm accessions and traits’ relationships are of great importance in active breeding programme. In the present study, genetic diversity and traits’ relationship were assessed among 74 castor germplasm accessions collected at the National Cereals Research Institute Badeggi, Nigeria. The accessions were evaluated on replicated plots of 7.5m2 size, arranged in a randomized complete block design. The data were taken on 20 individual plants, using standard castor descriptors. The results revealed significant variations for all the traits studied among the entries. Phenotypic and genotypic coefficients of variation estimated showed low environmental effects on the observed variations. High (≥ 70%) broad sense heritability coupled with high (≥ 20%) genetic advance as percentage of mean were observed in all the traits except days to days to first raceme maturity, number of leaf lobes and seed yield. Six cluster groups, with 4 to 38 members, were identified among the accessions. Significant positive correlations were observed between the seed yield and leaf length (0.269*), and spike length (0.972**). The partitioning of the correlations into direct and indirect yield contributors showed positive direct effects for number of internodes to first raceme, spike length and height to first raceme. The findings showed that selection for long spike early accessions could result in constituting a high yielding breeding population. The identified superior accessions could serve as good germplasm sources for castor breeding programme in Nigeria.

228 Utility of standardized FIGO descriptors for reporting of intra-operative findings of placenta accreta spectrum disorders.

228 Utility of standardized FIGO descriptors for reporting of intra-operative findings of placenta accreta spectrum disorders.

Fine classification and phenological analysis of rice paddy based on multi-temporal general compact polarimetric SAR data.

Fine classification and phenological information of rice paddy are of great significance for precision agricultural management. General compact polarimetric (CP) synthetic aperture radar (SAR) offers the advantage of providing rich polarimetric information, making it an important means of monitoring rice growth. Therefore, in response to the current challenges of difficulty in rice type classification and the small differences in phenological polarimetric characteristics, a novel strategy for fine classification and phenological analysis of rice paddy is proposed. This strategy thoroughly explores the polarimetric information of general CP SAR data and the target scattering characterization capabilities under different imaging modes. Firstly, the general CP SAR data is formalized using the standard CP descriptors, followed by the extraction of general CP features through the ΔαB /αB target decomposition method. optimal CP features are generated to achieve fine classification of rice paddy. Finally, 6 phenological stages of rice are analyzed based on the general CP features. The experiment results of rice classification show that the classification accuracy based on this strategy exceeds 90%, with a Kappa coefficient above 0.88. The highest classification accuracies were observed for transplanting hybrid rice paddy (T-H) and direct-sown japonica rice paddy (D-J), at 80.9% and 89.9%, respectively. The phenological evolution rule of the two rice types indicate that from early June (seedling stage) to late July (elongation stage), the CP feature variation trends of T-H and D-J are generally consistent. However, from October (mature stage) to November (harvest stage), the variation trends of the CP features for T-H and D-J are significantly different. The study found that from the booting-heading stage to the harvest stage, the linear π/4 mode outperforms circular and elliptical polarimetric modes in distinguishing different types of rice. Throughout the entire phenological period of rice growth, CP SAR of linear π/4 mode is surpasses that of other linear modes in discriminating different type of rice. The proposed strategy enables high-precision fine classification rice paddy, and the extracted general CP αB parameter effectively reflects the phenological change trends in rice growth.

The Covid-19 Vaccine on TikTok: A Study of Emotional Expression in The Brazilian Contexto

In this article, our objective was to analyze the emotions expressed regarding the Covid-19 vaccine in content published in Brazilian Portuguese on TikTok, a video sharing platform that has recently experienced global popularity. Our data set for this investigation was comprised of posts including the hashtag #vacina (vaccine), extracted using the Python TikTokAPI library. Emotions were identified and classified using standardized descriptors from the Human-Machine Interaction Network on Emotion (HUMAINE) and the Core Affect Model. Given the diversity of content on TikTok, videos with emotional content were also separated into categories. Results revealed a prevalence of positive emotions such as contentment, enthusiasm, and interest regarding the vaccines, especially in videos of a personal and informative character. Negative emotions, such as doubt and disapproval, were associated with contextual and strategic factors, with significant expression in humorous and infotainment publications.

Assessment of the suitability of selected non-measuring models for dermal exposure estimation for the purposes of assessing compliance of working conditions with restrictions 71 and 76 in Annex XVII of the REACH regulation

Occupational exposure to chemicals occurs mainly through inhalation and the skin. The inhalation exposure assessment is regulated by law, while in Poland the method of conducting measurements for dermal exposure has not been indicated in the law. However, due to the restrictions 71 and 76 from Annex XVII of REACH for 1-methyl-2-pyrrolidone (NMP) and N,N-dimethylformamide (DMF), exposure assessment by the dermal route is necessary. These restrictions require to ensure that exposure of workers is below the derived no-effect levels (DNELs) for dermal exposure. The aim of the work was assessment of suitability of selected non-measurement forecasting models for the estimation of dermal occupational exposure to chemicals for the purposes of assessing compliance of working conditions with the restrictions 71 and 76 of the REACH regulation. Three tools estimating dermal exposure, recommended by European Chemical Agency (ECHA), were selected: ECETOC TRA, RISKOFDERM and IH SkinPerm, which were used to estimate 2 exemplary workplaces. Results of the estimations of dermal exposure showed that non-measuring models are useful for fulfilling the obligations under restrictions 71 and 76 of Annex XVII of REACH. The type of exposure scenario and amount of data available for the workplace are crucial for the selection of the model. The ECETOC TRA was considered the best model for this type of analysis, whose main advantages are direct comparison of the output data in mg/kg/day with the DNEL value and use of standardized descriptors system. Exposure modeling is a good and cheap way to determine the dermal exposure magnitude at workplaces, also to comply with the requirements of restrictions 71 and 76 of Annex XVII of REACH. The application of modeling in the case of occupational exposure by the dermal route is one of the solutions when it is necessary to comply with the DNEL for dermal exposure. Med Pr Work Health Saf. 2023;74(6):487-500.

Acoustic noise levels and field distribution in 7 T MRI scanners

Acoustic noise production during Magnetic Resonance Imaging is an important source of patient discomfort and leads to verbal communication problems, difficulties in sedation, and hearing impairment. To address these issues, in this paper we present a systematic characterization of the acoustic field distribution in a MRI cavity in a last generation 7 T scanner, in different spatial locations, with and without a phantom head. Analysis and comparison of various MRI sequences like Echo-planar imaging”, “Gradient echo”, “Spin echo” are carried out. Sound pressure levels are measured using standard statistical descriptors (Leq,Lmean, L90, and Lmode) using two prepolarized free-field microphones measuring pressure levels generated inside scanner cavities in a 50 Hz to 10 kHz range. Acoustic eigenmodes of the cavity are derived numerically in finite element simulations and compared to measurements. Equivalent sound pressure levels exceed 85 dB in the range between 500 and 3,000 Hz, and peak levels are consistently above 100 dB, i.e., the noise levels of 7 T scanners are higher than 3T and 1.5 T counterparts. The presence of the phantom head in the MRI scanner leads to increased noise levels (by 5–10 dB) in its vicinity, as a result of reflections occurring between the head and the bore reflective walls. Numerical finite element simulations allow to extrapolate the noise distribution in the entire cavity and to interpret experimental results and indicate that the frequencies at which the highest noise levels occur correspond to azimuthal or radial resonant modes of the MRI cavity, i.e., with a radially and azimuthally varying pressure field. These results can be useful for the design of future acoustic noise mitigation solutions.

Variations in Phenotypic Characteristics of Vigna Unguiculata (L) Walp. Seeds Sourced From Open Markets in Benin City, Nigeria

Vigna unguiculata, ‘cowpea,’ is a crop of numerous varieties. In Benin City, Nigeria, the three common varieties are “Ife Brown”, “Ekpoma Local”, and “Sokoto White”. Being a very common delicacy and perhaps a cheap source of protein for the population, it is sold in nearly all available open markets. The crop is mainly consigned from numerous farms in the north and thus, is very amenable to genetic diversity. This study was undertaken to investigate the differences within and between these varieties. The seeds obtained from major open markets in Benin City were morphologically characterised quantitatively and qualitatively using standard descriptors. Seed length, width, thickness, weight, and volume were the quantitative parameters, while the qualitative parameters included seed brilliance, shape, eye colour, eye pattern, splitting of testa, testa texture, basal colour, pattern of variegation, colour of variegation, and basal colour of variegated seeds. Only “Ife Brown” varied in qualitative parameters, particularly the seed colour. Among the seed quantitative parameters measured, seed volume was the most diverse, with “Sokoto White” being significantly diverse compared to the others. “Ife Brown” was the most varied species among the three in the markets of Benin City, with a group mean sum of squares of 146.95.

Analysis of the pointwise completeness and the pointwise degeneracy of the standard and fractional descriptor linear systems and electrical circuits

The Drazin inverse of matrices is applied to analysis of the pointwise completeness and the pointwise degeneracy of the descriptor standard and fractional linear continuous-time and discrete-time systems. It is shown that: 1) The descriptor linear continuous-time system is pointwise complete if and only if the initial and final states belong to the same subspace. 2) The descriptor linear discrete-time system is not pointwise complete if its system matrix is singular. 3) System obtained by discretization of continuous-time system is always not pointwise complete. 4) The descriptor linear continuous-time system is not pointwise degenerated in any nonzero direction for all nonzero initial conditions. 5) The descriptor fractional system is pointwise complete if the matrix defined by (36) is invertible. 6) The descriptor fractional system is pointwise degenerated if and only if the condition (41) is satisfied. Considerations are illustrated by examples of descriptor linear electrical circuits.

Investigation on the physical dose filtered by linear energy transfer for treatment plan evaluation in carbon ion therapy.

Large tumor size has been reported as a predicting factor for inferior clinical outcome in carbon ion radiotherapy (CIRT). Besides the clinical factors accompanied with such tumors, larger tumors receive typically more low linear energy transfer (LET) contributions than small ones which may be the underlying physical cause. Although dose averaged LET is often used as a single parameter descriptor to quantify the beam quality, there is no evidence that this parameter is the optimal clinical predictor for the complex mixed radiation fields in CIRT. Purpose of this study was to investigate on a novel dosimetric quantity, namely high-LET-dose ( , the physical dose filtered based on an LET threshold) as a single parameter estimator to differentiate between carbon ion treatment plans (cTP) with a small and large tumorvolume. Ten cTPs with a planning target volume, (large) and nine with a (small) were selected for this study. To find a reasonable LET threshold ( ) that results in a significant difference in terms of , the voxel based normalized high-LET-dose ( ) distribution in the clinical target volume (CTV) was studied on a subset (12 out of 19 cTPs) for 18 LET thresholds, using standard distribution descriptors (mean, variance and skewness). The classical dose volume histogram concept was used to evaluate the and distributions within the target of all 19 cTPs at the before determined . Statistical significance of the difference between the two groups in terms of mean and volume histogram parameters was evaluated by means of (two-sided) t-test or Mann-Whitney-U-test. In addition, the minimum target coverage at the above determined was compared and validated against three other thresholds to verify its potential in differentiation between small and large volumetumors. An of approximately was found to be a reasonable threshold to classify the two groups. At this threshold, the and were significantly larger ( ) in small CTVs. For the small tumor group, the near-minimum and median (and ) in the CTV were in average (0.31 ± 0.08) and (0.46 ± 0.06), respectively. For the large tumors, these parameters were (0.20 ± 0.01) and (0.28 ± 0.02). The difference between the two groups in terms of mean near-minimum and median ( ) was 2.7 Gy (11%) and 5.0 Gy (18%),respectively. The feasibility of high-LET-dose based evaluation was shown in this study where a lower was found in cTPs with a large tumor size. Further investigation is needed to draw clinical conclusions. The proposed methodology in this work can be utilized for future high-LET-dose basedstudies.

Management and publication of scientific data on traditional mycological and lichenological knowledge in Africa

AbstractAfrica is an important global reservoir for biological, cultural and traditional knowledge about fungi and lichens, which are used as food, medicine and in mythology, among other things. African human populations are undergoing highly significant changes and adaptation processes, which are accompanied by rapid urbanization, meeting with western civilization, high rural migration and the loss of natural ecosystems. Indigenous knowledge is being lost, including that concerning fungi and lichens. Ethnomycology and ethnolichenology provide a diversity of knowledge about beneficial and poisonous fungi and lichens, and give insights into their sociological impact on human behaviour and use. Here we present a working and publishing environment established with the Diversity Workbench software in line with national and international initiatives for FAIR guided provision of research data. The database application called ‘EthnoMycAfrica’ contains published ethnomycological and ethnolichenological information from Africa. The content is created and curated by team partners from Central, East, West, North and Southern Africa. Data entry is performed both online and offline, optionally via a mobile device. Currently, the system with the tools DiversityDescriptions and DiversityNaviKey contains a total of 1350 well-structured and freely and openly accessible data records. EthnoMycAfrica is the first database with a data schema, standard descriptors and data content created mainly by African scholars. The data can be useful for researchers, students, conservationists, policy makers, and others. It will also provide a basis for facilitating hypothesis generation and meta-analysis.

Reichardt’s Dye-Based Solvent Polarity and Abraham Solvent Parameters: Examining Correlations and Predictive Modeling

The concept of “solvent polarity” is widely used to explain the effects of using different solvents in various scientific applications. However, a consensus regarding its definition and quantitative measure is still lacking, hindering progress in solvent-based research. This study hopes to add to the conversation by presenting the development of two linear regression models for solvent polarity, based on Reichardt’s ET(30) solvent polarity scale, using Abraham solvent parameters and a transformer-based model for predicting solvent polarity directly from molecular structure. The first linear model incorporates the standard Abraham solvent descriptors s, a, b, and the extended model ionic descriptors j+ and j−, achieving impressive test-set statistics of R2 = 0.940 (coefficient of determination), MAE = 0.037 (mean absolute error), and RMSE = 0.050 (Root-Mean-Square Error). The second model, covering a more extensive chemical space but only using the descriptors s, a, and b, achieves test-set statistics of R2 = 0.842, MAE = 0.085, and RMSE = 0.104. The transformer-based model, applicable to any solvent with an associated SMILES string, achieves test-set statistics of R2 = 0.824, MAE = 0.066, and RMSE = 0.095. Our findings highlight the significance of Abraham solvent parameters, especially the dipolarity/polarizability, hydrogen-bond acidity/basicity, and ionic descriptors, in predicting solvent polarity. These models offer valuable insights for researchers interested in Reichardt’s ET(30) solvent polarity parameter and solvent polarity in general.

A standard descriptor for fixed-target serial crystallography.

Fixed-target crystallography has become a widely used approach for serial crystallography at both synchrotron and X-ray free-electron laser (XFEL) sources. A plethora of fixed targets have been developed at different facilities and by various manufacturers, with different characteristics and dimensions and with little or no emphasis on standardization. These many fixed targets have good reasons for their design, shapes, fabrication materials and the presence or absence of apertures and fiducials, reflecting the diversity of serial experiments. Given this, it would be a Sisyphean task to design and manufacture a new standard fixed target that would satisfy all possible experimental configurations. Therefore, a simple standardized descriptor to fully describe fixed targets is proposed rather than a standardized device. This descriptor is a dictionary that could be read by fixed-target beamline software and straightforwardly allow data collection from fixed targets new to that beamline. The descriptor would therefore allow a much easier exchange of fixed targets between sources and facilitate the uptake of new fixed targets, benefiting beamlines, users and manufacturers. This descriptor was first presented at, and was developed following, a meeting of representatives from multiple synchrotron and XFEL sources in Hamburg in January 2023.

Piano Soundboard Analysis at Radiated Sound

The piano is a complex musical instrument consisting of several components influencing vibration and sound production. By understanding the sound production mechanism virtual instruments can be created (physics-based sound synthesis) and the design and manufacturing of soundboards can be supported (virtual prototyping). Based on previous results published in the literature, a piano model was built and extended by a near field sound radiation model capable for physics-based sound synthesis. In this paper a simplified piano model is presented, including hammer strike and hysteretic felt models, coupled lossy string model and a 2D FEM based stiffened plate model for soundboard. This paper contains a parametric study where the soundboard parameters, such as its material characteristics and boundary conditions, are modified and their effect on the soundboard's modal behavior and the radiated sound is analyzed. Instead of using only musical (qualitative) descriptors, e.g. brightness or coloring, the piano sounds are characterized based on standard quantitative descriptors (e.g. harmonic ratio, spectral centroid). It is shown that these descriptors are determined by soundboard admittance, string characteristics and position on the soundboard; radiated sound from wooden soundboards can be characterized as harmonic for wide range of initial material descriptors; the string position is essential, and the perceived sound can differ significantly for different listening positions, even for the same harmonic decay pattern.