Local Database Research Articles

Comparison of traditional and molecular surveys of fish biodiversity in southern Te Wāhipounamu/Fiordland (Aotearoa/New Zealand)

AbstractEffective management of biodiversity requires regular surveillance of multiple species. Analysis of environmental DNA (eDNA) by metabarcoding holds promise to achieve this relatively easily. However, taxonomy‐focused eDNA surveys need suitable molecular reference data, which are often lacking, particularly at the species level and for remote locations. To evaluate the comparability of environmental DNA surveys and traditional surveys in a real‐life case study in a marine area of high conservation value, we conducted a biodiversity survey of the fish in remote and pristine Te Wāhipounamu/Fiordland (Aotearoa/New Zealand), incorporating multiple data sources. We compared eDNA‐derived species identifications against Baited Remote Underwater Video (BRUV) data collected at the same time and locations as eDNA. We also cross‐referenced both eDNA and BRUV data against literature and the Ocean Biodiversity Information System (OBIS), with literature and OBIS data representing a summary of multiple traditional surveying approaches. In total, we found 116 fish species in our study area. Environmental DNA detected 43 species; however, only three of those species overlap with species known from the literature, OBIS, or our BRUV analyses. A total of 61 fish species were known from the region from the literature, while OBIS listed 28 species, and our BRUV analyses picked up 26 species. BRUV data coincided more strongly than eDNA data with literature and OBIS data. Twenty of the 26 species detected by BRUV were known from literature and OBIS. We argue that limitated DNA reference databases are the main cause of this discrepancy, and our results indicate that eDNA of rare and endangered species can be detected if matching reference data were available. Environmental DNA analyses can only identify species present among reference data and with relaxed taxonomic assignment parameters may converge on relatives of detected species if the actually existing species themselves are missing among reference data. However, the high number of species detected by our eDNA analyses confirms that eDNA could be a powerful tool for biodiversity surveys if suitable investments in local reference databases were made.

A first-principles exploration of the conformational space of sodiated di-saccharides assisted by semi-empirical methods and neural network potentials.

Previous exploration of the conformational space of sodiated mono-saccharides using a random search algorithm leads to ∼103 structurally distinct conformers covering an energy range of ∼150 kJ mol-1. Thus, it is reasonable to expect that the number of distinct conformers for a given disaccharide would be on the order of 106. Efficient identification of distinct conformers at the first-principles level has been demonstrated with the assistance of neural network potential (NNP) with an accuracy of ∼1 kJ mol-1 compared to DFT. Leveraging a local minima database of neutral and sodiated glucose (Glc), we develop algorithms to systematically explore the conformation landscape of 19 Glc-based sodiated disaccharides. To accelerate the exploration, the NNP method is implemented. The NNP achieves an accuracy of ∼2.3 kJ mol-1 compared to DFT, offering a comparable quality to that of DFT. Through a multi-model approach integrating DFTB3, NNP and DFT, we can rapidly locate low-energy disaccharide conformers at the first-principles level. The methodology we show here can be used to efficiently explore the potential energy landscape of any di-saccharides when first-principles accuracy is required.

Trends in obstructive sleep apnea disease severity over nearly two decades: update on the VA San Diego experience.

The Sleep Program at the VA San Diego Healthcare System (VASDHS) started a patient database over twenty years ago for its home sleep apnea testing (HSAT) program. An analysis of ten years of diagnostic HSAT data was reported on over 12500 patients in 2014. Over this time period, severe obstructive sleep apnea (OSA) decreased in frequency. In contrast, mild OSA increased in frequency and was the most frequently reported severity in our analysis. In more recent times, the 2021 continuous positive airway pressure (CPAP) crisis created difficulties in dispersing CPAP therapies to individuals including Veterans with OSA, prompting our group to reexamine the HSAT database. A retrospective review was performed of the local clinical database of HSAT diagnostic testing of 8,928 sleep studies from 2018 to 2022. The overall mean apnea-hypopnea index (AHI) decreased from 40.4/hour (2004) to 24.3/hour (2022) (p < .001). The two time periods were examined separately. For 2004-2013, it was found that the mean AHI in 2004 was not significantly different from the mean AHI in 2005, 2006, or 2007 but was significantly different from the mean AHI in each year from 2008 (mean AHI = 30.7/h) to 2013 (mean AHI = 26.1/hour). For 2019-2022, the mean AHI did not significantly differ between the 4 years. These findings have implications for OSA therapies. Additionally, the high prevalence of mild sleep apnea, which is typically associated with lesser adherence to PAP therapy, further highlights the importance of non-PAP alternatives to improve treatment effectiveness.

Exploring dietitians' views on digital nutrition educational tools in Malaysia: a qualitative study.

Dietitians frequently use nutrition education tools to facilitate dietary counselling sessions. Nevertheless, these tools may require adaptation to keep pace with technological advancements. This study had a 2-fold purpose: first, to identify the types of nutrition education tools currently in use, identify their limitations, and explore dietitians' perspectives on the importance of these tools; second, to investigate the features that dietitians prefer in digital nutrition education tools. A semi-structured face-to-face interview was conducted among 15 dietitians from selected public hospitals, primary care clinics, and teaching hospitals in Malaysia. Inductive thematic analysis of the responses was conducted using NVivo version 12 software. Most dietitians used physical education tools including the healthy plate model, pamphlets, food models, and flip charts. These tools were perceived as important as they facilitate the nutrition assessment process, deliver nutrition intervention, and are time efficient. However, dietitians described the current educational tools as impersonal, outdated, limited in availability due to financial constraints, unhandy, and difficult to visualise. Alternatively, they strongly favoured digital education tools that provided instant feedback, utilised an automated system, included a local food database, were user-friendly, developed by experts in the field, and seamlessly integrated into the healthcare system. Presently, although dietitians have a preference for digital educational tools, they heavily rely on physical nutrition education tools due to their availability despite the perception that these tools are outdated, impersonal, and inconvenient. Transitioning to digital dietary education tools could potentially address these issues.

Phytophthora: taxonomic and phylogenetic revision of the genus-SUPP

Supplementary files:&lt;br /&gt;Supplementary File S1. Methods for isolation, maintenance, sporulation, and storage of Phytophthora species.&lt;br /&gt;Supplementary File S2. IDphy2 Molecular Protocols for Sanger Sequencing with seven genes. &lt;br /&gt;Supplementary File S3. ITS rDNA, COI, MOTUs, 3G HTS and 2G HTS local databases.&lt;br /&gt;Supplementary Fig. S1. Order Peronosporales. Maximum likelihood tree inferred with IQ-TREE v. 2 from a three-locus (ITS, COI and β-tub) alignment (Supplementary Table S1). Ultrafast bootstrap support values ≥ 50 % are shown above and posterior probabilities ≥ 0.90 from a Bayesian analysis are below branches.&lt;br /&gt;Supplementary Fig. S2. Phytophthora and related obligate biotrophic taxa. Maximum likelihood tree inferred with IQ-TREE v. 2 from a five-locus (COI, β-tub, EF1α, L10 and HSP90) alignment (Supplementary Table S1). Ultrafast bootstrap support values ≥ 50 % are shown above and posterior probabilities ≥ 0.90 from a Bayesian analysis are below branches.&lt;br /&gt;Supplementary Fig. S3. Seven-locus Phytophthora phylogeny featuring 213 described species. Bayesian tree inferred with MrBayes v. 3.2.7. Posterior probabilities ≥ 0.90 are shown. Sequence accessions are listed in Table 2.&lt;br /&gt;Supplementary Fig. S4. ITS-only maximum likelihood tree. Tree inferred using IQ-TREE v. 2 from a 217 taxon alignment with 1 178 nucleotide positions and 404 binary gap positions. Ultrafast bootstrap support values ≥ 50 % are shown above and posterior probabilities ≥ 0.90 from a Bayesian analysis are below branches.&lt;br /&gt; Supplementary Fig. S5. COI-only maximum likelihood tree. Tree inferred using IQ-TREE v. 2 from a 190 taxon alignment with 744 nucleotide positions. Ultrafast bootstrap support values ≥ 50 % are shown above and posterior probabilities ≥ 0.90 from a Bayesian analysis are below branches.&lt;br /&gt; Supplementary Fig. S6. YPT1-only maximum likelihood tree. Tree inferred using IQ-TREE v. 2 from a 180 taxon alignment with 850 nucleotide positions and 322 binary gap positions. Ultrafast bootstrap support values ≥ 50 % are shown above and posterior probabilities ≥ 0.90 from a Bayesian analysis are below branches.&lt;br /&gt; Supplementary Fig. S7. β-tub-only maximum likelihood tree. Tree inferred using IQ-TREE v. 2 from a 213 taxon alignment with 1 053 nucleotide positions. Ultrafast bootstrap support values ≥ 50 % are shown above and posterior probabilities ≥ 0.90 from a Bayesian analysis are below branches. &lt;br /&gt;Supplementary Fig. S8. EF1α-only maximum likelihood tree. Tree inferred using IQ-TREE v. 2 from a 192 taxon alignment with 879 nucleotide positions. Ultrafast bootstrap support values ≥ 50 % are shown above and posterior probabilities ≥ 0.90 from a Bayesian analysis are below branches. &lt;br /&gt;Supplementary Fig. S9. L10-only maximum likelihood tree. Tree inferred using IQ-TREE v. 2 from a 186 taxon alignment with 465 nucleotide positions. Ultrafast bootstrap support values ≥ 50 % are shown above and posterior probabilities ≥ 0.90 from a Bayesian analysis are below branches. &lt;br /&gt;Supplementary Fig. S10. HSP90-only maximum likelihood tree. Tree inferred using IQ-TREE v. 2 from a 190 alignment with 933 nucleotide positions. Ultrafast bootstrap support values ≥ 50 % are shown above and posterior probabilities ≥ 0.90 from a Bayesian analysis are below branches.&lt;br /&gt; Supplementary Table S1. Taxa added for Figs. 1, 2.Bourret, Tyler; Abad, Gloria; Burgess, Treena (2023), “Supporting data for taxonomic and phylogenetic revision of the genus Phytophthora based on the types”, Mendeley Data, V1, doi: 10.17632/yg2rmfzstw.1

A locally optimised machine learning approach to early prognostication of long-term neurological outcomes after out-of-hospital cardiac arrest.

Out-of-hospital cardiac arrest (OHCA) represents a major burden for society and health care, with an average incidence in adults of 67 to 170 cases per 100,000 person-years in Europe and in-hospital survival rates of less than 10%. Patients and practitioners would benefit from a prognostication tool for long-term good neurological outcomes. We aim to develop a machine learning (ML) pipeline on a local database to classify patients according to their neurological outcomes and identify prognostic features. We collected clinical and biological data consecutively from 595 patients who presented OHCA and were routed to a single regional cardiac arrest centre in the south of France. We applied recursive feature elimination and ML analyses to identify the main features associated with a good neurological outcome, defined as a Cerebral Performance Category score less than or equal to 2 at six months post-OHCA. We identified 12 variables 24 h after admission, capable of predicting a six-month good neurological outcome. The best model (extreme gradient boosting) achieved an AUC of 0.96 and an accuracy of 0.92 in the test cohort. We demonstrated that it is possible to build accurate, locally optimised prediction and prognostication scores using datasets of limited size and breadth. We proposed and shared a generic machine-learning pipeline which allows external teams to replicate the approach locally.

Cloning and functional analysis of flavanone synthase Ⅱ from Dendrobium huoshanense

Flavonoid C-glycosides are a class of natural products that are widely involved in plant defense responses and have diverse pharmacological activities. They are also important active ingredients of Dendrobium huoshanense. Flavanone synthase Ⅱ has been proven to be a key enzyme in the synthesis pathway of flavonoid C-glycosides in plants, and their catalytic product 2-hydroxyflavanone is the precursor compound for the synthesis of various reported flavonoid C-glycosides. In this study, based on the reported amino acid sequence of flavanone synthase Ⅱ, a flavanone synthase Ⅱ gene(DhuFNSⅡ) was screened and verified from the constructed D. huoshanense genome localization database. Functional validation of the enzyme showed that it could in vitro catalyze naringenin and pinocembrin to produce apigenin and chrysin, respectively. The open reading frame(ORF) of DhuFNSⅡ was 1 644 bp in length, encoding 547 amino acids. Subcellular localization showed that the protein was localized on the endoplasmic reticulum. RT-qPCR results showed that DhuFNSⅡ had the highest expression in stems, followed by leaves and roots. The expression levels of DhuFNSⅡ and other target genes in various tissues of D. huoshanense were significantly up-regulated after four kinds of abiotic stresses commonly encountered in the growth process, but the extent of up-regulation varied among treatment groups, with drought and cold stress having more significant effects on gene expression levels. Through the identification and functional analysis of DhuFNSⅡ, this study is expected to contribute to the elucidation of the molecular mechanism of the formation of quality metabolites of D. huoshanense, flavonoid C-glycosides, and provide a reference for its quality formation and scientific cultivation.

Barriers to Discharge of Hip Fracture Patients From An Academic Hospital: A Retrospective Data Analysis.

Adherence to best practices for care of hip fracture patients is fundamental to decreasing morbidity and mortality in older adults. This includes timely transfer from the hospital to rehabilitation soon after their surgical care. Hospitals experience challenges in implementing several best practices. We examined the potential barriers associated with timely discharge for patients who underwent a hip fracture surgery in an academic hospital in Ontario, Canada. We conducted a retrospective cross-sectional review of a local database. We used descriptive statistics to characterize individuals according to the time of discharge after surgery. Multivariable binary logistic regression was used to evaluate factors associated with delayed discharge (>6days post-surgery). A total of 492 patients who underwent hip fracture surgery between September 2019 and August 2020 were included in the study. The odds of having a delayed discharge occurred when patients had a higher frailty score (odds ratios [OR] 1.19, 95% confidence interval [CI] 1.02;1.38), experienced an episode of delirium (OR 2.54, 95% CI 1.35;4.79), or were non-weightbearing (OR 3.00, 95% CI 1.07;8.43). Patients were less likely to have a delayed discharge when the surgery was on a weekend (OR .50, 95% CI .32;.79) compared to a weekday, patients had a total hip replacement (OR .28, 95% CI .10;.80) or dynamic hip screw fixation (OR .49, 95% CI .25;.98) compared to intramedullary nails, or patients who were discharged to long-term care (OR .05, 95% CI .02;.13), home (OR .26, 95% CI .15;.46), or transferred to another specialty in the hospital (OR .49, 95% CI .29;.84) compared to inpatient rehabilitation. Clinical and organizational factors can operate as potential barriers to timely discharge after hip fracture surgery. Further research is needed to understand how to overcome these barriers and implement strategies to improve best practice for post-surgery hip fracture care.

A STUDY ON THE SPATIAL DIFFERENTIATION OF THE SOCIO-ECONOMIC AND TOURIST SITUATION OF SELECTED MUNICIPALITIES OF THE WEST POMERANIAN VOIVODESHIP

Aim: The aim of the article was to develop an original classification of municipalities in the West Pomeranian Voivodeship, Poland, with particular emphasis on measuring local development, taking into account the de­velopment of health tourism. Methods: The research procedure consisted of the following stages: collection of data and assessment of their completeness for the West Pomeranian region, calculating the values of the indicators, constructing rankings of municipalities in a one-dimensional space of characteristics-indicators and distinguishing typological groups of municipalities similar in terms of the degree of development of the socio-economic and tourist situation. The classification of sub-regions was carried out using discriminant analysis. For this purpose, the indicators characterizing the socio-economic and tourist situation in the selected West Pomeranian Voivodeship municipalities were used, taking into account the division into municipalities: urban (1), rural (2), and urban-rural (3). The preliminary classification of the objects into groups, and thus the selection of the grouping variable, was carried out using the k-means method. The study used secondary data from the Local Data Base – GUS. Results: As a result of the survey, the analyzed local government units were divided into three groups. However, the presented results of the classification do not indicate the dependence of the improvement of socio-economic characteristics on the provision of tourism services in the municipality (including health tourism). Conclusions: Empirical studies show that the placement of munici­palities in the West Pomeranian Voivodeship reveals clear relationships between the territorial distribution of health tourism units and the territorial distribution of natural assets and access to the Baltic Sea.

Performance analysis of a cloud database on mobile devices

The article presents a performance analysis of Firebase cloud database. Two services, namely Realtime Database and Cloud Firestore, are examined, and their query speed are compared to those of the local SQLite database. Basic CRUD operations were examined, taking into account the number of records in the database, the size of individual records and the complexity of the database structure. Upon completion of the research, it was concluded that Realtime Database outperforms Cloud Firestore and cloud databases are slower than the local database when it comes to operations on a single record. However, when working with a larger volume of data, cloud database can achieve better results than SQLite. The accuracy of the outcome is also influenced by the stability of the network connection and the distance from the cloud server.

Screening of Phytochemicals for Antisickling effects

Background: Sickle cell disease is an autosomal recessive disorder caused due to point mutation on a single gene on chromosome 11 resulting in substitution of valine in place of glutamic acid at sixth position of beta-chain of adult hemoglobin (HbA). The purpose of the current study is to evaluate the effectiveness of phytochemicals (Rutin and its derivatives) for antisickling effects. Methods: The structure of Rutin is obtained in Simplified Molecular Input Line Entry System (SMILES) format and is subjected to chemical similarity search using Extended-connectivity fingerprints (ECFP4) fingerprints. The Tanimoto coefficient is used as the similarity metric and top compounds obtained on chemical similarity search are further subjected to molecular docking based screening analysis. A local database of phytochemicals is created using the IMPAAT database. Molecular docking approach is implemented using iGEMDOCK for screening and ranking of Rutin and its derivatives. The docking is implemented with standard docking protocol with population size of 200 and number of generations= 70. Results: All the ligand molecules showed acceptable binding energies with the 2HBS receptor molecule ranging between -124.87 to-79.59kcal/mol. Koprutin showed the highest binding affinity against the 2HBS (2HBS-DEOXYHEMOGLOBIN S) and which can be further developed as an antisickling agent. Conclusion: The integration of insilico modelling techniques with the wet lab based experimental methods can significantly reduce the cost in terms of time and other resources. Further the intricacies of molecular interactions taking place between ligands and receptors can be better understood with the help of molecular modelling techniques.

Design of Intelligent Customer Service Knowledge Base for Medical Insurance Based on Foundation-scale Models

In this paper, we propose a method for constructing an intelligent customer service knowledge base system for medical insurance based on natural language processing (NLP) models. This method utilizes a local vector database to construct the knowledge base system and retrieves industry knowledge by calling the vector database through foundation-scale models. The use of this technology ensures the security of business data and reduces platform training costs. The intelligent knowledge base of medical insurance constructed using this method can automatically handle user’s inquiries, complaints, and general business transactions, effectively improving the efficiency and intelligence level of customer service.

ANALYSIS OF THE UTILIZATION OF ALTMAN Z-SCORE, BENEISH M-SCORE, AND F-SCORE MODEL IN DETECTING FRAUDULENT OF FINANCIAL REPORTING: A LITERATURE REVIEW

Financial statement fraud has serious implications, and early detection through methods like Altman Z-Score, Beneish M-Score, and F-Score can help prevent losses. Although each method has strengths and weaknesses, combining them or adding additional measures can enhance fraud detection accuracy. This research aims to explore the use of Altman Z-Score, Beneish M-Score, and F-Score in detecting Fraudulent Financial Reporting. we intend to examine whether Altman Z-Score, Beneish M-Score, or F-Score have influence on detecting financial statement fraud, and what the comparative level is among these methods. The methodology employs a literature review approach using the SINTA and Scopus databases to gather information from scholarly publications in the last 10 years. The choice of these databases is based on the excellence of SINTA as a local Indonesian database and Scopus as a deep international data source. The research objectives include testing the influence of each method in detecting Fraudulent Financial Reporting and analyzing their comparative levels. The theoretical contribution involves enhancing knowledge for readers and researchers, providing references for further research. In practical terms, the research is expected to offer insights to readers, especially investors, for considering the most appropriate analytical method in identifying and preventing Fraudulent Financial Reporting in investment decision-making.

Multi-Network Latency Prediction for IoT and WSNs

The domain of Multi-Network Latency Prediction for IoT and Wireless Sensor Networks (WSNs) confronts significant challenges. However, continuous research efforts and progress in areas such as machine learning, edge computing, security technologies, and hybrid modelling are actively influencing the closure of identified gaps. Effectively addressing the inherent complexities in this field will play a crucial role in unlocking the full potential of latency prediction systems within the dynamic and diverse landscape of the Internet of Things (IoT). Using linear interpolation and extrapolation algorithms, the study explores the use of multi-network real-time end-to-end latency data for precise prediction. This approach has significantly improved network performance through throughput and response time optimization. The findings indicate prediction accuracy, with the majority of experimental connection pairs achieving over 95% accuracy, and within a 70% to 95% accuracy range. This research provides tangible evidence that data packet and end-to-end latency time predictions for heterogeneous low-rate and low-power WSNs, facilitated by a localized database, can substantially enhance network performance, and minimize latency. Our proposed JosNet model simplifies and streamlines WSN prediction by employing linear interpolation and extrapolation techniques. The research findings also underscore the potential of this approach to revolutionize the management and control of data packets in WSNs, paving the way for more efficient and responsive wireless sensor networks.

Environmental DNA in a Biofilm Can Be Used to Assess Diatom Ecological Health in Stream Water Ecology

In urban and agricultural streams, assessing aquatic ecosystem health is critical due to widespread pollution. Traditional methods for evaluating attached diatoms crucial for ecosystem monitoring face limitations such as species misidentification and sample damage. This study was conducted in the Miho River within the Geum River system and highlights the effectiveness of environmental DNA (eDNA) techniques for more accurate and efficient genetic-based analysis than conventional microscopic analysis methods. When eDNA-based assessments were compared with traditional microscopic methods, this study found that eDNA analysis often revealed poorer ecosystem health. Notably, eDNA assessments showed a stronger correlation with phosphorus concentrations, underlining their precision and importance in ecological studies. These findings suggest that eDNA has potential as a valuable tool for comprehensive biomonitoring. However, the use of international genetic barcode databases in eDNA analysis could lead to the identification of unrecorded species in Korea. Therefore, this study recommends developing a localized genetic barcode database and constructing eDNA information through meta-barcoding, focusing on native species. This approach is crucial for enhancing the accuracy and applicability of eDNA-based health assessments in national biomonitoring efforts.

A population-based study of the trend in SARS-CoV-2 diagnostic modalities from the beginning of the pandemic to the Omicron surge in Kyoto City, Kyoto, Japan

BackgroundThe coronavirus disease 2019 (COVID-19) presents critical diagnostic challenges for managing the pandemic. We investigated the 30-month changes in COVID-19 testing modalities and functional testing sites from the early period of the pandemic to the most recent Omicron surge in 2022 in Kyoto City, Japan.MethodsThis is a retrospective-observational study using a local anonymized population database that included patients' demographic and clinical information, testing methods and facilities from January 2020 to June 2022, a total of 30 months. We computed the distribution of symptomatic presentation, testing methods, and testing facilities among cases. Differences over time were tested using chi-square tests of independence.ResultsDuring the study period, 133,115 confirmed COVID-19 cases were reported, of which 90.9% were symptomatic. Although nucleic acid amplification testing occupied 68.9% of all testing, the ratio of lateral flow devices (LFDs) rapidly increased in 2022. As the pandemic continued, the testing capability was shifted from COVID-19 designated facilities to general practitioners, who became the leading testing providers (57.3% of 99,945 tests in 2022).ConclusionsThere was a dynamic shift in testing modality during the first 30 months of the pandemic in Kyoto City. General practitioners increased their role substantially as the use of LFDs spread dramatically in 2022. By comprehending and documenting the evolution of testing methods and testing locations, it is anticipated that this will contribute to the establishment of an even more efficient testing infrastructure for the next pandemic.

Effects of medication on dopamine transporter imaging using [123I]I-FP-CIT SPECT in routine practice.

Dopamine transporter (DAT) imaging is used to support the diagnosis of neurodegenerative parkinsonian disorders. Specific medications have been reported to confound the interpretation of[123I]I-FP-CIT SPECT scans, but there is limited data. The aim of the current study is to identify potential medication effects on the interpretation of[123I]I-FP-CIT SPECT scans in routine practice. Consecutive patients undergoing a[123I]I-FP-CIT SPECT/CT scan on a 360° CZT camera between September 2019 and December 2022 were included. An exhaustive review of patient medications (antidepressants, antipsychotics, anti-epileptics, anti-parkinsonians, benzodiazepines, lithium, opioids, and stimulants) was performed. Two experienced nuclear physicians, blinded to the medication reports, interpreted the[123I]I-FP-CIT SPECT scans visually and a semi-quantitative analysis was performed using a local normal database. The study included 305 patients (71.0 ± 10.4, 135 women) and 145 (47.5%) visually interpreted normal scans. In normal scans, the striatum/occiput radioligand uptake ratio was decreased by noradrenergic and specific serotonergic antidepressants (NASSAs) (n = 15, z-score of - 0.93) and opioid medication (tramadol, n = 6, z-score of - 0.85) and was associated with a younger age in the multivariate analysis. In the overall population, the striatum/occiput ratio was influenced by NASSAs and associated with consensual visual analysis, age, sex, and anti-parkinsonian medications related to the status of the disease. Our study confirms the potential impact of antidepressant (NASSA) and opioid (tramadol) medications on the semi-quantitative analysis of[123I]I-FP-CIT SPECT scans. However, when performing a visual analysis, only NASSAs significantly impacted the interpretation of[123I]I-FP-CIT SPECT scans.

American local government elections database

The study of urban and local politics in the United States has long been hindered by a lack of centralized sources of election data. We introduce a new database of about 78,000 candidates in 57,000 electoral contests that encompasses races for seven distinct local political offices in most medium and large cities and counties in the U.S. over the last three decades. This is the most comprehensive publicly-available source of information on local elections across the country. We provide partisan and demographic information about candidates in these races as well as electoral outcomes. This new database will facilitate a myriad of new research on representation and elections in local governments.

From Rheic ocean opening to Pangea breakup: a chronostratigraphic and isotopic database of key localities in Mexico

This database includes a wealth of geochronologic, isotopic, and provenance data, published or in publication, which constitutes an effort to unravel the evolution of Mexican, pre-Cretaceous geological units that are key in reconstructing the history of the Rheic Ocean, from its opening to its closure, and the initial breakup of Pangea. The database is built on reference geological maps, that the authors compile from published works and that locally, contain novel cartographic data. Since the localities studied in this work contain successions that are different in age, P-T conditions, lithology, and geologic significance, and given that each stand-alone work (research, undergraduate and graduate theses, etc.) focused on resolving the central theme of the Rheic ocean evolution and Pangea amalgamation and breakup, we generate an open database that will be continuously updated, as soon as new data are available. Initially intended as a database to present the results of several present and previous grants obtained by the authors, and make them available to collaborators, this contribution evolved to be an open source for all the researchers that are interested in the Paleozoic–early Mesozoic Mexican tectonic evolution and the pre-Mesozoic basement characterization.&#x0D;

Graph-based representation of history-dependent material response in the Data-Driven Computational Mechanics framework

This work develops an extension of the Data-Driven Computational Mechanics approach introduced by Kirchdoerfer and Ortiz (2016) to history-dependent behaviour. The material database is replaced by a material directed graph, where vertices represent strain–stress pairs and arcs encode thermomechanically admissible transitions between them. A graph search algorithm is used to select local material databases representative of the incremental material behaviour. This study thus gives the mathematical tools for a structured data-driven representation of the material behaviour, designed to minimise the increase of the problem dimensionality. The performances of the proposed approach applied to elastoplasticity are studied on a single-element structure and a larger truss structure. A two-step solver is proposed to address numerical accuracy issues in the latter case.