Miracle-dz/UniFAR-FTUs huggingface dataset:
Perinatal Outcomes were Associated with the Positional Relationship between Placenta and Adenomyotic Lesion in Pregnant Patients with Adenomyosis

Background : The adverse perinatal outcome caused by adenomyosis has been widely concerned recently, but little attention has been paid to whether the positional relationship between placenta and adenomyotic lesion influences the maternal and perinatal outcomes. Methods : A total of 311 women with adenomyosis who were pregnant greater than 20 weeks gestation and delivered at Women’s Hospital, Zhejiang University School of Medicine between January 2010 and December 2021 were recruited. The positional relationships between placenta and adenomyotic lesions were determined. The patients were divided into two subgroups: group 1, placenta located on or above the adenomyotic lesion; and group 2, placenta located far away from the adenomyotic lesion. The clinical data of two groups were retrospectively analyzed. Results : We found a higher rate of diffuse adenomyosis (62.65% vs . 46.21%, p = 0.01), coexisting endometriosis (31.93% vs . 15.86%, p = 0.002), preterm delivery (34.94% vs .15.17%, p < 0.001) and placenta malposition (19.88% vs . 6.90%, p = 0.002) in group I compared to group II. Compared with group II, group I had lower birth weight ( p = 0.02). After adjustment using multiple logistic regression analysis, maternal adverse outcome was only correlated with age ( p = 0.02). Neonatal adverse outcomes were closely correlated with group I ( p = 0.004), including pregnancy induced hypertension ( p = 0.01), placenta malposition ( p = 0.02), placental abruption ( p = 0.003), and scarred uterus ( p = 0.02). Conclusions : The positional relationships between the placenta and adenomyotic lesions were graphically presented. Placental position near or above adenomyosis lesions might correlate to the adverse perinatal outcomes of pregnant women with adenomyosis and thereby deserve more attention.
Assessing the e(cid:14)cacy of haplotype inference by pure parsimony on biological data

Motivation: Mutation in DNA is the principal factor responsible for the di(cid:11)erences among human beings, and Single Nucleotide Polymorphisms (SNPs) are the most common mutations. Hence, it is fundamental to complete a map of haplotypes (which identify SNPs) in the human population. However, due to technological limitations, genotype data rather than haplotype data is usually obtained. The haplotype inference by pure parsimony (HIPP) problem consists in inferring haplotypes from genotypes s.t. the number of required haplotypes is minimum. Experimental results provide support for this method: the number of haplotypes in a large population is typically very small, although genotypes exhibit a great diversity. Results: We de(cid:12)ne a new method for solving the HIPP problem using Boolean satis(cid:12)ability (SAT). Experimental results clearly demonstrate that our SAT-based tool is by far more e(cid:14)cient than the existing tools following the pure parsimony approach. Besides being more e(cid:14)cient, our tool is also the only capable of computing the solution for a large number of instances. Hence, we have been able to infer haplotypes for a wide variety of biological data, that no other tool following the pure parsimony approach is able to. Additionally, we compare the accuracy of the results obtained with our tool with the accuracy of the results obtained with tools following statistical approaches, and conclude that the pure parsimony criterion used by our methods leads to good results in terms of precision of inferred haplotypes.
BLAISE PASCAL

We study the discrete groups Λ whose duals embed into a given compact quantum group, b Λ ⊂ G . In the matrix case G ⊂ U + n the embedding condition is equivalent to having a quotient map Γ U → Λ, where F = { Γ U | U ∈ U n } is a certain family of groups associated to G . We develop here a number of techniques for computing F , partly inspired from Bichon’s classiﬁcation of group dual sub-groups b Λ ⊂ S + n . These results are motivated by Goswami’s notion of quantum isometry group, because a compact connected Riemannian manifold cannot have non-abelian group dual isometries.
The effect of GCM biases on global runoff simulations of a land surface model

Abstract. Global climate model (GCM) outputs feature systematic biases that render them unsuitable for direct use by impact models, especially for hydrological studies. To deal with this issue, many bias correction techniques have been developed to adjust the modelled variables against observations, focusing mainly on precipitation and temperature. However, most state-of-the-art hydrological models require more forcing variables, in addition to precipitation and temperature, such as radiation, humidity, air pressure, and wind speed. The biases in these additional variables can hinder hydrological simulations, but the effect of the bias of each variable is unexplored. Here we examine the effect of GCM biases on historical runoff simulations for each forcing variable individually, using the JULES land surface model set up at the global scale. Based on the quantified effect, we assess which variables should be included in bias correction procedures. To this end, a partial correction bias assessment experiment is conducted, to test the effect of the biases of six climate variables from a set of three GCMs. The effect of the bias of each climate variable individually is quantified by comparing the changes in simulated runoff that correspond to the bias of each tested variable. A methodology for the classification of the effect of biases in four effect categories (ECs), based on the magnitude and sensitivity of runoff changes, is developed and applied. Our results show that, while globally the largest changes in modelled runoff are caused by precipitation and temperature biases, there are regions where runoff is substantially affected by and/or more sensitive to radiation and humidity. Global maps of bias ECs reveal the regions mostly affected by the bias of each variable. Based on our findings, for global-scale applications, bias correction of radiation and humidity, in addition to that of precipitation and temperature, is advised. Finer spatial-scale information is also provided, to suggest bias correction of variables beyond precipitation and temperature for regional studies.
Under-utilized andean food crops : Status and prospects of plant biotechnology for the conservation and sustainable agricultural use of genetic resources

In line with the strategic recommendations of the Global Plan of Action for the Conservation and Sustainable Utilisation of Plant Genetic Resources for Food and Agriculture approved at the Fourth International Technical Conference on Plant Genetic Resources (ITCPGR), Leipzig, Germany, June, 1996 and of the Global Plan of Action on Food Security approved at the World Food Summit on Food Security (WFS), Rome, November, 1996, the Andean Countries of Latin America (LAC) face the need to strengthen the use of modern plant biotechnology for the conservation and sustainable agricultural use of genetic resources of under-utilized crops. Advanced biotechnologies as cell and tissue culture, molecular genome analysis, plant genetic transformation, molecular plant disease diagnosis and germplasm cryo-conservation can be successfully used to cope genetic erosion, to reinforce ex-situ collections and in in-situ conservation, to upgrade the supply of improved and healthy seed and planting materials to farmers and to integrate a new approach into the development programmes for food production and food security in mountain lands. Over the centuries, more than seventy crops have been domesticated by the Andes inhabitants. Presently, on twenty eight crop species, selected under the basis of adaptation to high altitude, agronomic use and yield, nutritional value and market potential, there are relative developments in term of agronomic cultural management and scarce genetic conservation activities. The Technical Co-operation Network on Plant Biotechnology (REDBIO) for the Latin American Countries (LAC), sponsored by FAO since, 1990 have detected for this subregion technical constrains in terms of scarcity of human resources, limitation in technology development and use. infrastructure and lack of information/data banks on plant biotechnology. Eighty six plant biotechnology laboratories from the Andean Countries of LAC (Colombia, Peru, Ecuador, Bolivia, Venezuela are members of REDBIO. On several of these institutions there are research and transfer of technology projects, including plant biotechnology, on Andean under-utilized food crops as arracacha (Arracacia xanthorrhiza), achira (Canna edulis), yacon (Polymnia sonchifolia), mashua (Tropaeolum tuberosum), oca (Oxalis tuberosa), ulluco (Ullucus tuberosus), quinoa (Chenopodium quinoa), amaranto o kiwicha (Amaranthus caudatus), popping beans -nunas' (Phaseolus vulgaris), tarwi (Lupinus mutabilis), goldenberry-capuli (Physalis peruviana), cherimoya (Annona eherimola) and passion -fruit (Passiflora sp.). The paper summarizes the main parameters and characteristics of 13 selected crops including the state of the art of plant biotechnology in the Andean countries and main applications and discusses perspectives and future impact of plant biotechnology for the conservation and development of food crops.
FPGA-Accelerated Sim-to-Real Control Policy Learning for Robotic Arms

Sim-to-real robot learning has been used in various applications, but its implementation in software may not provide the best performance. This tutorial describes how hardware acceleration based on Field-Programmable Gate Array (FPGA) technology for deep reinforcement learning can improve sim-to-real robot control policy learning. A novel architecture for the Deep Deterministic Policy Gradient (DDPG) algorithm is developed for a full-stack sim-to-real development platform to learn control policies for robotic arms. The capability of our development platform is illustrated by transferring learned policies encoded as fixed-point numbers from our implementation to a miniature robotic arm.
Phonological and acoustic properties of ATR in the vowel system of Akebu (Kwa)

This study examines phonological and phonetic properties of ATR contrasts in the vowel system of Akebu (Kwa). The sum of descriptive evidence, including vowel harmony, vowel distribution in non-harmonising contexts, vowel reduction and typological and etymological considerations, indicates a rare vowel inventory with an ATR contrast in front/back vowels but a height contrast in the three redundantly [ $-$ ATR] central vowels /ᵻ, ə, a/. This analysis was checked against four common acoustic metrics of ATR: F1 and F2 frequencies, spectral slope and F1 bandwidth size (B1). As expected, the results for the last three metrics were variable across speakers and vowel types, and are therefore inconclusive. The results for F1 were consistent but do not distinguish between ATR and vowel height. Two results nonetheless suggest the [ $-$ ATR] status of central vowels: they occupy the same belt of F1 frequencies and show the same position of observed-over-predicted B1 values as front and back [ $-$ ATR] vowels.
Description of the vaginal microbiota in nulliparous ewes during natural mating and pregnancy: preliminary signs of the male preputial microbiota modulation

The vaginal microbiota plays a key role in animals’ health. Understanding its diversity and composition and associated changes occurring through the reproductive cycle represents valuable knowledge to disclose the mechanisms leading to dysbiosis and eventually to infection. Even if the human vaginal microbiota has been thoroughly studied, scarce research has been conducted on the vaginal microbiota of livestock. In this study, 16S rRNA gene-based sequencing was performed on vaginal samples of ten nulliparous ewes at three different sampling points: before the estrus synchronization protocol (T0), at the time of estrus before mating (Testrus), and the day of the pregnancy diagnosis (Tpreg). Preputial samples from the three males collected pre and post-mating were also analyzed. Firmicutes, Proteobacteria, Bacteroidetes, and Actinobacteria were the most abundant phyla in vaginal samples. The most abundant genera were Porphyromonas, Anaerococcus, and Peptinophilius. Vaginal microbiota biodiversity decreased during pregnancy. Tenericutes (Ureaplasma spp.) increased significantly at Tpreg in both pregnant and non-pregnant ewes. Differences were observed between pregnant and non-pregnant ewes at Tpreg where pregnant ewes had a significantly higher abundance of Actinobacillus spp. and Ureaplasma spp. Ewes that were diagnosed with pregnancy at Tpreg showed a decreased abundance of gram-negative bacteria such as Bacteroidales, Campylobacterales, and Enterobacteriales. In addition, a significant decrease in the relative abundances of genera within Firmicutes, such as Alloicoccus (Lactobacillales), Atopostipes (Lactobacillales), and an uncultured bacteria W5053 from Family XI (Firmicutes, Clostridiales) was observed in non-pregnant ewes at Tpreg. The four most abundant phyla in the rams’ prepuce were the same as in the ewes’ vagina. The most abundant genus was Corynebacterium. No major differences were observed in the ram’s preputial microbiota between pre and post-mating samples. Nevertheless, the differences in the taxonomic composition of ewes’ vaginal microbiota between Testrus and Tpreg could be explained by the exposure to the preputial microbiota. This study offers new insights into the effects of several key steps of the ewe’s reproductive cycle such as estrus-synchronization protocol, mating, and pregnancy on ovine vaginal microbiota. The knowledge of the microbiota dynamics during the reproductive cycle can help improve the reproductive outcomes of dams by identifying biomarkers and putative probiotics.
Distributed Bernoulli Filter Based on Weighted Conservative Fusion

This letter presents a novel distributed Bernoulli filter for tracking a target over a peer-to-peer sensor network. For the case where the Bernoulli random finite set is either empty or singleton, two types of fusion weights are designed based on the information of sensor capabilities and environmental factors. Further, novel weighted conservative fusion approaches including geometric average and arithmetic average are derived to fuse local Bernoulli densities. The Gaussian mixture implementations of the proposed algorithms are given, which are subsequently combined with distributed flooding protocol for distributed averaging. Simulation results demonstrate the outperformance of the proposed approaches compared to the state-of-the-art approaches.
Bioaccessibility of Carotenoids and Polyphenols in Organic Butternut Squash (Cucurbita moschata): Impact of Industrial Freezing Process

Butternut squash (Cucurbita moschata) is recognized as a functional food due to its abundant content of health-promoting compounds, including carotenoids and polyphenols. The aim of this study was to examine the impact of industrial freezing stages on the bioaccessibility of carotenoids and polyphenols in organic Butternut squash supplied for baby food. Identification and quantification of bioactive compounds were carried out using UPLC-ESI-MS/MS and HPLC-PDA, respectively. The results revealed that industrial freezing of squash did not cause a significant change in bioaccessibility of α- and β-carotene. On the other hand, frozen squash was found to contain higher levels of bioaccessible epicatechin (main flavonoid) (117.5 mg/kg) and syringic acid (main phenolic acid) (32.0 mg/kg) compared to fresh internal fruit. Moreover, the levels of bioaccessible epicatechin and syringic acid were found to be the highest in discarded pomace and seed sample (454.0 and 132.4 mg/kg, respectively). Overall, this study emphasized that industrial freezing could be an effective strategy for preserving carotenoid bioaccessibility in organic Butternut squash, while also enhancing the levels of bioaccessible polyphenols. In addition, we also demonstrated that pomace and seed, which are discarded as waste, have significant potential to be utilized as a food source rich in bioactive compounds.
The influence of latent heat on the superelastic behavior Shape Memory Alloy

— Superelasticity is a unique behavior of Shape Memory Alloys (SMA), and it has numerous applications in fields such as robotics, electro-mechanics, aerospace, and biomedical. However, this behavior is influenced by various factors such as temperature, load, strain rate, latent heat. Especially at high strain rates, the influence of latent heat on super-elastic behavior becomes significant. Therefore, in this research work, we focus on a one-dimensional numerical simulation of the impact of latent heat on super-elastic behavior. By considering the contribution of temperature in the Helmholtz free energy combined with the principles of thermodynamics, we can observe the influence of latent heat in the phase transformation processes of super-elastic behavior. The simulation results are compared with cases where latent heat has no effect and with experimental data.
Effect of Over-the-counter Whitening Toothpaste and Mouthwash in Orthodontics: A Literature Review

Abstract Aim To summarize and analyze all the available literature on the use of over-the-counter toothpaste and mouthwashes with whitening agents and their possible effects on orthodontic treatment. Background Tooth color change frequently occurs during orthodontic treatment and represents a self-perceived need. According to the patient's perspective, there is a preference for the use of toothpaste and mouthwashes with some whitening effect. Materials and methods An electronic bibliographic search in English was carried out until June 2022, in PubMed, Scopus, and Web of Science databases. Randomized or nonrandomized clinical trials and experimental laboratory studies were included. Review results A total of 57 papers were obtained from an electronic search and 11 studies were included in the review. Outcomes such as strength force elastomeric, color stability, frictional resistance, ion release, shear bond strength (SBS), and adhesive remnant index (ARI) were evaluated. Conclusion Toothpaste and mouthwashes with whitening action did not have a favorable effect on most of the outcomes evaluated. In some cases regular toothpaste showed a better effect and in other cases, there were no differences with the control group. Only in the outcome release of ions from wires to whitening effect in teeth with or without attached brackets, they have a better performance. Clinical significance Due to the unfavorable effects of over-the-counter whitening toothpaste and mouthwashes on orthodontic materials and appliances, their use should be justified during treatment. How to cite this article Chinchay-Ruesta S, Ortiz-Pizarro M, Rodríguez-Díaz DR, et al. Effect of Over-the-counter Whitening Toothpaste and Mouthwash in Orthodontics: A Literature Review. Int J Clin Pediatr Dent 2023;16(S-3):S311–S316.
Vaccination Training for Pharmacy Undergraduates as a Compulsory Part of the Curriculum?—A Multicentric Observation

In order to increase vaccination rates, the Government of Germany introduced vaccination against influenza and COVID-19 into the regular care administered by pharmacists. However, vaccination training is yet not integrated into the German pharmacy curriculum. Therefore, the Institute for Clinical Pharmacy and Pharmacotherapy in Duesseldorf had developed an innovative vaccination course using high-fidelity simulation for students. To investigate the acceptance further, the course was carried out at three different German universities (Bonn, Duesseldorf, Greifswald). Students were asked to give their self-assessment before and after and satisfaction only after the training course. Responses from 33 participants from the University of Bonn, 42 from the University of Duesseldorf and 49 from the University of Greifswald were analyzed. Every participant at the respective universities showed a significant increase in their self-assessment and indicated a high level of satisfaction with the course. The results also did not differ significantly between the respective universities. Consequently, the results lead to the hypothesis that the satisfaction of pharmacy students with this kind of training using high-fidelity simulation is very high and attractive, and can be recommended for other German universities. The integration of such vaccination training into the German pharmacy curriculum might be a future step.
Digital Therapeutics for Improving Effectiveness of Pharmaceutical Drugs and Biological Products: Preclinical and Clinical Studies Supporting Development of Drug + Digital Combination Therapies for Chronic Diseases

Limitations of pharmaceutical drugs and biologics for chronic diseases (e.g., medication non-adherence, adverse effects, toxicity, or inadequate efficacy) can be mitigated by mobile medical apps, known as digital therapeutics (DTx). Authorization of adjunct DTx by the US Food and Drug Administration and draft guidelines on “prescription drug use-related software” illustrate opportunities to create drug + digital combination therapies, ultimately leading towards drug–device combination products (DTx has a status of medical devices). Digital interventions (mobile, web-based, virtual reality, and video game applications) demonstrate clinically meaningful benefits for people living with Alzheimer’s disease, dementia, rheumatoid arthritis, cancer, chronic pain, epilepsy, depression, and anxiety. In the respective animal disease models, preclinical studies on environmental enrichment and other non-pharmacological modalities (physical activity, social interactions, learning, and music) as surrogates for DTx “active ingredients” also show improved outcomes. In this narrative review, we discuss how drug + digital combination therapies can impact translational research, drug discovery and development, generic drug repurposing, and gene therapies. Market-driven incentives to create drug–device combination products are illustrated by Humira® (adalimumab) facing a “patent-cliff” competition with cheaper and more effective biosimilars seamlessly integrated with DTx. In conclusion, pharma and biotech companies, patients, and healthcare professionals will benefit from accelerating integration of digital interventions with pharmacotherapies.
MAFE-Net: retinal vessel segmentation based on a multiple attention-guided fusion mechanism and ensemble learning network

The precise and automatic recognition of retinal vessels is of utmost importance in the prevention, diagnosis and assessment of certain eye diseases, yet it brings a nontrivial uncertainty for this challenging detection mission due to the presence of intricate factors, such as uneven and indistinct curvilinear shapes, unpredictable pathological deformations, and non-uniform contrast. Therefore, we propose a unique and practical approach based on a multiple attention-guided fusion mechanism and ensemble learning network (MAFE-Net) for retinal vessel segmentation. In conventional UNet-based models, long-distance dependencies are explicitly modeled, which may cause partial scene information loss. To compensate for the deficiency, various blood vessel features can be extracted from retinal images by using an attention-guided fusion module. In the skip connection part, a unique spatial attention module is applied to remove redundant and irrelevant information; this structure helps to better integrate low-level and high-level features. The final step involves a DropOut layer that removes some neurons randomly to prevent overfitting and improve generalization. Moreover, an ensemble learning framework is designed to detect retinal vessels by combining different deep learning models. To demonstrate the effectiveness of the proposed model, experimental results were verified in public datasets STARE, DRIVE, and CHASEDB1, which achieved F1 scores of 0.842, 0.825, and 0.814, and Accuracy values of 0.975, 0.969, and 0.975, respectively. Compared with eight state-of-the-art models, the designed model produces satisfactory results both visually and quantitatively.