Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessment of Hemoglobin A1c Management and Prescription Cost Due to Polypharmacy Among Patients With Diabetes in Iran Based on the STEPS Iran 2016 Survey and a Prescription Database: A Multi-level, Cross-sectional National Study

Background: Diabetes frequently results in the need for multiple medication therapies, known as ‘Polypharmacy’. This situation can incur significant costs and increase the likelihood of medication errors. This study evaluated the prescriptions of patients with diabetes regarding polypharmacy to assess its effect on the control of hemoglobin A1c (HbA1c) levels and prescription costs. Methods: A cross-sectional national study was conducted based on data from linking the Iranians Health Insurance Service prescriptions in 2015 and 2016 with the STEPS 2016 survey in Iran. The association of the individual and sociodemographic factors, as well as polypharmacy, as independent variables, with control of HbA1c levels and the cost of the prescriptions were assessed among diabetic patients using logistic and linear regression, respectively. Results: Among 205 patients using anti-diabetic medications, 47.8% experienced polypharmacy. The HbA1c of 74 patients (36.1%) was equal to or less than 7, indicating controlled diabetes. HbA1c control showed no significant association with gender. However, prescription costs were notably lower in females (β=0.559 [0.324‒0.964], P=0.036). No significant correlation was found between the area of residence and prescription costs, but HbA1c was significantly more controlled in urban areas (OR=2.667 [1.132‒6.282], P=0.025). Prescription costs were significantly lower in patients without polypharmacy (β=0.211, [0.106‒0.423], P<0.001), though there was no significant association between polypharmacy and HbA1c levels. Conclusion: Our results demonstrated that diabetics with polypharmacy paid significantly more for their prescriptions without experiencing a positive effect on the control of HbA1c levels.
Towards a more effective approach to the development and maintenance of SEA guidance

ABSTRACT Written guidance can contribute to the development of effective SEA, delivering relevant information for those involved in policy, plan and programme making processes. Generally speaking, guidance should aim at setting best practice standards. However, to date, how guidance is impacting on SEA effectiveness and how it is best developed and maintained has not been explored to any great extent. As a consequence, it has remained unclear how a key ingredient of effective SEA, namely the support of an enabling context, should be approached. In this paper, we look at the perceived relevance of written guidance for the delivery of effective SEA, based on a two-stage survey with 26 practitioners (all with over 10 years of experience) from the UK and the Republic of Ireland, conducted between 2015 and 2017. Survey participants included representatives of the regulatory, consultancy and academic sectors. Our findings indicate that guidance can promote SEA effectiveness if it: (a) aims to go beyond basic legislative requirements; (b) is able to respond to the specific situation of application; (c) can establish a minimum standard for SEA; and (d) is able to stimulate the advancement of quality standards within a tiered approach to SEA.
Evaluation of Stiffness in Compression Perpendicular to Grain of Brazilian Tropical Wood Species

It is essential to have full knowledge of wood properties, such as strength and stiffness, for the preparation of reliable structural designs. The Brazilian Code ABNT NBR 7190 (1997) establishes that the modulus of elasticity in compression perpendicular to grain (E c90 ) can be obtained in a Original Research Article simplified way, in the absence of experimental determination, by means of a correlation with the modulus of elasticity in the direction parallel to grain (E c0 = 20 E c90 ). In order to verify the adequacy of this expression, the results obtained for five species of wood, covering the strength classes assumed by the mentioned Code were analyzed: Cambará Rosa ( Erisma sp.), C20; Cedro Amazonense ( Cedrella sp.), C30; Cupiúba ( Goupia glabra ), C40; Itaúba ( Mezilaurus itauba ), C50; Roxinho ( Peltogyne sp.), C60. For each species, from the tests prescribed by ABNT NBR 7190, the elastic moduli were obtained in the directions parallel and normal to grain. In the evaluation of the precision of the proposed estimation, the least squares method was used to determine the coefficient α of the investigated relation. For the data set involving the five species studied, the coefficient resulted in α = 20.64. This value is compatible with the correlation proposed by the Brazilian standard, evidencing its reliability.
Effect of modified basic package of oral care on adolescents dental caries status in Copperbelt Province, Zambia; A Cluster Randomized Trial

Background Dental caries remains the major oral health challenge affecting more than half of adolescents globally. Most of the disease remain untreated, therefore, negatively impacting adolescents general health, well-being, and quality of life. Basic Package of Oral Care (BPOC) is a potential solution to the challenge, however, evidence on its effectiveness is scarce. This study primarily assessed the effects of applying modified BPOC on dental caries prevalence and secondarily on knowledge and behaviours related to dental caries among adolescents in Copperbelt Province, Zambia. Methods A parallel arms cluster randomized field trial (Reg-PACTR202210624926299) including 22 public secondary schools in Copperbelt province, Zambia, was carried out between January 2021 and March 2023. A pre-tested questionnaire was used to collect socio-demographics, knowledge and dental caries related behaviours data, while dental caries was assessed clinically using the caries assessment spectrum and treatment (CAST) at baseline and the follow-ups. The 1st and 2nd follow ups were conducted at 18-and 24 months after baseline respectively. The analysis was based on intention-to-treat protocol using generalized estimating equations (GEE) and results are reported as OR (95% CI). Results Out of 1,794 participants at baseline, 1,690 (94.2%) and 1,597 (89.0%) were seen at 1st and 2nd follow ups respectively. A significant interaction (BPOC x time) for dental caries models at 18 months {OR (95%CI) = 1.3 (1.1, 1.6), p=0.003)} and 24 months {OR (95%CI) = 1.3 (1.1, 1.6), p=0.004)} was observed. Secondary outcomes with significant interactions included adequate knowledge models at 18 months {OR (95%CI) =1.5 (1.2,1.8), p<0.001} and 24 months {OR (95%CI) = 1.6 (1.3, 2.0), p<0.001} as well as use of fluoridated toothpaste twice or more per day at 18 months {OR (95%CI) = 1.6 (1.3, 2.1), p<0.001)} and 24 months {OR (95%CI) = 1.4 (1.2, 1.6), p<0.001)}. Subgroup analysis showed that the intervention group had better outcomes than the control group in terms of dental caries prevalence, adequate knowledge, use of fluoridated toothpaste twice or more per day, at 18- and 24 months. Conclusion The modified BPOC was effective in reducing prevalence of dental caries, improving knowledge on dental caries, and the frequency of using fluoridated toothpaste among Zambian adolescents. Further studies need to be conducted in order to address other factors affecting oral health related behaviours such as the school and home environment, social and cultural factors.
Genome-wide association study between SARS-CoV-2 single nucleotide polymorphisms and virus copies during infections

Variations in viral loads generated during SARS-CoV-2 infections can influence COVID-19 disease progression and the likelihood of onward transmission. However, the host and virus factors that may impact viral loads and infection dynamics are not fully understood. Here, we conducted virus whole genome sequencing and measured viral copies using RT-qPCR from 9,902 SARS-CoV-2 infections over a 2-year period to examine the relative impact of host factors and virus genetic variation on changes in viral copies. We first used statistical regression models to show that host age and SARS-CoV-2 variant significantly impact viral copies, but vaccination status does not. Then, using a genome-wide association study (GWAS) approach, we identified multiple nucleotide substitutions corresponding to amino acid changes in the SARS-CoV-2 genome associated with variations in viral copies. In particular, we analyzed the temporal patterns and found that SNPs associated with higher viral copies were predominantly observed in Omicron BA.2/BA.4/BA.5/XBB infections, whereas those associated with decreased viral copies were mostly observed in infections with Delta and Omicron BA.1 variants. Our work showcases how GWAS can be a useful tool for probing phenotypes related to SNPs in viral genomes, which can be used to characterize emerging variants and monitor therapeutic interventions.
Antipsychotics in Chinese Patients with Schizophrenia: A Within-Subject Approach with modelling of dosage effects

Background: Second-generation antipsychotics (SGAs) are commonly used to treat schizophrenia (SCZ), but SGAs may differ in the severity of side effects. Long-term studies are lacking, and previous observational studies have limitations, such as failure to account for confounding factors and short follow-up duration. Aims: To compare the long-term anthropometric and metabolic side effects of seven SGAs in a Chinese population, using a within-subject approach to reduce the risk of confounding. Method: We collected longitudinal data of SGA prescriptions, concomitant medications, fasting blood glucose (BG), lipid profiles, and BMI in a cohort of 767 patients with SCZ, with follow-up up to 18.7 years (median ~6.2 years). A total of 192,152 prescription records were retrieved, with 27,723 metabolic measures analysed. Linear mixed models were used to estimate the effects of SGA on BG, lipid profiles and BMI. Besides studying the effects of SGA medications (as binary predictors), we also investigated the effects of SGA dosage on metabolic profiles. Results: Considering SGA medications as a binary predictor, overall clozapine and olanzapine were associated with the most substantial worsening of lipid profiles and BMI. A significant increase in BG was observed with clozapine only. Amisulpride, paliperidone and quetiapine were associated with worsened lipid profiles and increased BMI. Conversely, aripiprazole was associated with significant improvement in lipid profiles but a small increase in BMI. When SGA dosage was considered, the model showed consistent results overall. At minimum effective dose, clozapine was associated with the most severe metabolic side effects, followed by olanzapine. Risperidone and aripiprazole showed the least metabolic side effects, with aripiprazole being significantly associated with lower lipids. Conclusions: This study clarified the long-term and dose-dependent effects of different SGAs on anthropometric and metabolic parameters in Chinese SCZ patients. Our findings may inform clinicians and SCZ patients of SGA choices.
High Probability of Lynch Syndrome among colorectal cancer patients in Indonesia is associated with higher occurrence of KRAS and PIK3CA mutations

Background: In Indonesia, early-onset colorectal cancer (EOCRC) rates are higher in patients <50 years old compared to western populations, possibly due to a higher frequency of Lynch Syndrome (LS) in CRC patients. We aim to examine the association of KRAS and PIK3CA mutation with LS. Methods: In this cross-sectional study, the PCR-HRM-based test was used for screening of MSI mononucleotide markers (BAT25, BAT26, BCAT25, MYB, EWSR1), MLH1 promoter methylation, and oncogene mutations of BRAF(V600E), KRAS (exon 2 and 3), and PIK3CA (exon 9 and 20) in FFPE DNA samples. Results: All the samples (n=244) were from Dr. Sardjito General Hospital Yogyakarta, Indonesia. KRAS and PIK3CA mutations were found in 151/244 (61.88%) and 107/244 (43.85%) of samples respectively. KRAS and PIK3CA mutations were significantly associated with MSI status in 32/42 (76.19%) and 25/42 (59.52%) of samples respectively. KRAS mutation was significantly associated with LS status in 26/32 (81.25%) of samples. The PIK3CA mutation was present in a higher proportion in LS samples of 19/32 (59.38%), but not statistically significant. Clinicopathology showed that KRAS mutation was significantly associated with right-sided CRC and higher histology grade in 39/151 (25.83%) and 24/151 (16.44%) samples respectively. PIK3CA mutation was significantly associated with female sex and lower levels of TILs in 62/107 (57.94%) and 26/107 (30.23%) samples respectively. KRAS and PIK3CA mutations did not significantly affect overall survival (120 months) in LS and non-LS patients. Conclusions: High probability of LS in Indonesian CRC patients is associated with KRAS and PIK3CA mutations.
FEW CONSIDERATIONS, WARNINGS AND BENEFITS FOR THE E&P INDUSTRY WHEN INCORPORATING STRATIFICATIONS INSIDE SALT SECTIONS

ABSTRACT. This article presents a review of procedures and techniques describing the importance of considering the stratification within the evaporitic section, combining seismic attributes and well information during the processes of seismic migration, in order to build seismic images closer to the geological realities. A new nomenclature is proposed, reflecting the interval velocity and density behavior of different salt strata. The study also reviews the parameters for geomechanical simulations of the reservoir seals, allowing better decisions in terms of production and/or injection rates, among others. The incorporation of intra-salt heterogeneities, or stratifications, allows for a better prediction of operational aspects such as mud weight and penetration rates, which are essential information for drilling safety, and economy. Important considerations about the lithotypes were carried, especially concerning the accumulated frequency of occurrence, the evaporites cyclicity, salt movements, etc. The resolution, when comparing well models versus seismic models, was another important aspect considered in this review, with emphasis on the uncertainty analysis.Keywords: evaporites, seismic attributes, resolution, uncertainty, model.RESUMO. Este artigo apresenta uma revisão sobre os procedimentos e técnicas que descrevem a importância de considerar estratificações existentes dentro da seção evaporítica, combinando atributos sísmicos e informações de poços para construir imagens sísmicas o mais próximo possível da realidade geológica, através de processos mais robustos de migrações sísmicas. Uma nova nomenclatura é proposta refletindo o comportamento da velocidade intervalar e densidade de cada estrato. Adicionalmente, são abordados os parâmetros para simulação geomecânica das rochas capeadoras dos reservatórios, permitindo melhores decisões sobre taxas de produção e injeção dos campos, entre outras. A incorporação das heterogeneidades, ou estratificações, nas seções evaporíticas também auxilia na definição de aspectos operacionais, tais como peso de fluido e taxas de penetração, informações essenciais para a segurança e economicidade da perfuração. Importantes considerações sobre a frequência de ocorrência dos litotipos, a ciclicidade dos evaporitos, movimentações do sal, etc., são também abordadas. A resolução das informações quando comparamos os modelos oriundos das informações dos poços com os provenientes da sísmica, foram igualmente revistas, com ênfase na análise das incertezas.Palavras-chave: evaporitos, atributos sísmicos, resolução, incerteza, modelo.
Can Transformers Capture Spatial Relations between Objects?

Spatial relationships between objects represent key scene information for humans to understand and interact with the world. To study the capability of current computer vision systems to recognize physically grounded spatial relations, we start by proposing precise relation definitions that permit consistently annotating a benchmark dataset. Despite the apparent simplicity of this task relative to others in the recognition literature, we observe that existing approaches perform poorly on this benchmark. We propose new approaches exploiting the long-range attention capabilities of transformers for this task, and evaluating key design principles. We identify a simple"RelatiViT"architecture and demonstrate that it outperforms all current approaches. To our knowledge, this is the first method to convincingly outperform naive baselines on spatial relation prediction in in-the-wild settings. The code and datasets are available in \url{https://sites.google. com/view/spatial-relation}.
The classification of two-distance transitive dihedrants

A vertex transitive graph $\Gamma$ is said to be $2$-distance transitive if for each vertex $u$, the group of automorphisms of $\Gamma$ fixing the vertex $u$ acts transitively on the set of vertices at distance $1$ and $2$ from $u$, while $\Gamma$ is said to be $2$-arc transitive if its automorphism group is transitive on the set of $2$-arcs. Then $2$-arc transitive graphs are $2$-distance transitive. The classification of $2$-arc transitive Cayley graphs on dihedral groups was given by Du, Malni\v{c} and Maru\v{s}i\v{c} in [Classification of 2-arc-transitive dihedrants, J. Combin. Theory Ser. B 98 (2008), 1349--1372]. In this paper, it is shown that a connected 2-distance transitive Cayley graph on the dihedral group of order $2n$ is either $2$-arc transitive, or isomorphic to the complete multipartite graph $K_{m[b]}$ for some $m\geq3$ and $b\geq2$ with $mb=2n$.
Structure Similarity Preservation Learning for Asymmetric Image Retrieval

Asymmetric image retrieval is a task that seeks to balance retrieval accuracy and efficiency by leveraging lightweight and large models for the query and gallery sides, respectively. The key to asymmetric image retrieval is realizing feature compatibility between different models. Despite the great progress, most existing approaches either rely on classifiers inherited from gallery models or simply impose constraints at the instance level, ignoring the structure of embedding space. In this work, we propose a simple yet effective structure similarity preserving method to achieve feature compatibility between query and gallery models. Specifically, we first train a product quantizer offline with the image features embedded by the gallery model. The centroid vectors in the quantizer serve as anchor points in the embedding space of the gallery model to characterize its structure. During the training of the query model, anchor points are shared by the query and gallery models. The relationships between image features and centroid vectors are considered as structure similarities and constrained to be consistent. Moreover, our approach makes no assumption about the existence of any labeled training data and thus can be extended to an unlimited amount of data. Comprehensive experiments on large-scale landmark retrieval demonstrate the effectiveness of our approach.
Anomalous mass dependency in Hydra endoderm cell cluster diffusion

Tissue organization plays a crucial role in morphogenesis, wound healing and cancer metastasis. Hydra, known for its regenerative capabilities, serves as an excellent model for studying cellular structures, particularly in pattern formation and the diffusion of cell clusters. Established experimental protocols enable the examination of regeneration and tissue segregation through optical microscopy. Recent experiments challenge previous theories by suggesting that cell collective behavior is a key factor in hydra cell aggregate organization. Utilizing image treatment techniques on fluorescent images from Hydra's segregation experiment, we track endoderm cell clusters and investigate the relationship between their diffusion constant and cluster size. In contrast to results observed in non-active matter, we discover a nearly constant dependence of diffusion on cluster mass. This finding contributes to understanding the rapid segregation observed in recent experiments and holds implications for general cellular tissue processes.
Tree-Regularized Tabular Embeddings

Tabular neural network (NN) has attracted remarkable attentions and its recent advances have gradually narrowed the performance gap with respect to tree-based models on many public datasets. While the mainstreams focus on calibrating NN to fit tabular data, we emphasize the importance of homogeneous embeddings and alternately concentrate on regularizing tabular inputs through supervised pretraining. Specifically, we extend a recent work (DeepTLF) and utilize the structure of pretrained tree ensembles to transform raw variables into a single vector (T2V), or an array of tokens (T2T). Without loss of space efficiency, these binarized embeddings can be consumed by canonical tabular NN with fully-connected or attention-based building blocks. Through quantitative experiments on 88 OpenML datasets with binary classification task, we validated that the proposed tree-regularized representation not only tapers the difference with respect to tree-based models, but also achieves on-par and better performance when compared with advanced NN models. Most importantly, it possesses better robustness and can be easily scaled and generalized as standalone encoder for tabular modality. Codes: https://github.com/milanlx/tree-regularized-embedding.
The quark-mass dependence of the potential energy between static colour sources in the QCD vacuum with light and strange quarks

The low-lying energy spectrum of the static-colour-source-anti-source system in a vacuum containing light and strange quarks is computed using lattice QCD for a range of different light quark masses. The resulting levels are described using a simple model Hamiltonian and the parameters in this model are extrapolated to the physical light-quark masses. In this framework, the QCD string tension is found to be $\sqrt{\sigma}=445(3)_{\rm stat}(6)_{\rm sys}$ MeV.
LocalRQA: From Generating Data to Locally Training, Testing, and Deploying Retrieval-Augmented QA Systems

Retrieval-augmented question-answering systems combine retrieval techniques with large language models to provide answers that are more accurate and informative. Many existing toolkits allow users to quickly build such systems using off-the-shelf models, but they fall short in supporting researchers and developers to customize the model training, testing, and deployment process. We propose LocalRQA, an open-source toolkit that features a wide selection of model training algorithms, evaluation methods, and deployment tools curated from the latest research. As a showcase, we build QA systems using online documentation obtained from Databricks and Faire's websites. We find 7B-models trained and deployed using LocalRQA reach a similar performance compared to using OpenAI's text-ada-002 and GPT-4-turbo.
Causal Mode Multiplexer: A Novel Framework for Unbiased Multispectral Pedestrian Detection

RGBT multispectral pedestrian detection has emerged as a promising solution for safety-critical applications that require day/night operations. However, the modality bias problem remains unsolved as multispectral pedestrian detectors learn the statistical bias in datasets. Specifically, datasets in multispectral pedestrian detection mainly distribute between ROTO (day) and RXTO (night) data; the majority of the pedestrian labels statistically co-occur with their thermal features. As a result, multispectral pedestrian detectors show poor generalization ability on examples beyond this statistical correlation, such as ROTX data. To address this problem, we propose a novel Causal Mode Multiplexer (CMM) framework that effectively learns the causalities between multispectral inputs and predictions. Moreover, we construct a new dataset (ROTX-MP) to evaluate modality bias in multispectral pedestrian detection. ROTX-MP mainly includes ROTX examples not presented in previous datasets. Extensive experiments demonstrate that our proposed CMM framework generalizes well on existing datasets (KAIST, CVC-14, FLIR) and the new ROTX-MP. We will release our new dataset to the public for future research.