Miracle-dz/UniFAR-FTUs huggingface dataset:
Addressing the STEM Gender Gap by Designing and Implementing an Educational Outreach Chemistry Camp for Middle School Girls

There continues to be a persistent, widespread gender gap in multiple STEM disciplines at all educational and professional levels: from the self-reported interest of preschool aged students in scientific exploration to the percentages of tenured faculty in these disciplines, more men than women express an interest in science, a confidence in their scientific abilities, and ultimately decide to pursue scientific careers. Reported herein is an intensive outreach effort focused on addressing this gender gap: a full-time, week-long chemistry camp that was designed and implemented for middle school girls in the state of Rhode Island. The camp schedule included multiple hands-on experiments, field trips, and significant interactions with female scientists, all of which were designed to increase the participants’ interest in and enthusiasm for science. The success of the program in changing the participants’ attitudes toward science was measured through administration of a precamp and postcamp survey, and the su.
Polyphenol profile of buckwheat honey, nectar and pollen

A focus of research in recent years is the comparison of honey as the final product of bees with pollen and nectar of the plant from which the honey originates, as the main food source for bees. Buckwheat honey is recognized as a nutritionally valuable product, which provides a scientifically proven health benefit and is confirmed as a functional food. The quality of this type of honey is attributed to high levels of phytochemicals in buckwheat. The purpose of this study was the examination of similarity between buckwheat honey and buckwheat nectar and pollen, as well as simultaneous investigation of their chemical profiles and the origin of the honey. The phenolic profile of buckwheat pollen showed a lower number of flavonoids and phenolic acids than those of nectar and honey samples, but confirmed the presence of the most characteristic polyphenols derived from the buckwheat plant. The notable difference was found to be the presence of (epi)catechin units, its galloylated derivatives and procyanidin dimers, which were not present in honey. Honey polyphenols displayed a pronounced correlation with those of nectar, but not with those of pollen. Finally, by comparing the polyphenolic profiles of honey, nectar and pollen sharing the same geographical origin, new data could be provided for a potential assessment of the botanical origin of buckwheat honey.
H loss mechanism during anneal of silicon nitride: Chemical dissociation

Remote plasma enhanced chemical vapor deposited silicon nitride (SixNyHz), produced at high ammonia to silane flow rates (ammonia rich) shows a reduction of hydrogen during rapid thermal anneal at temperatures that exceed the deposition temperature. This H release could be either due to a “slow” atomic diffusion of the covalent bonded atoms between bonding sites, or to a “fast” molecular diffusion of hydrogen containing molecules (e.g., H2, NH3, SiH4), which dissociate from the network before they diffuse. In order to determine the dominant mechanism, layers of deuterated and hydrogenated silicon nitride on top of a crystalline Si substrate were annealed and the development of the NH- and ND-area densities were measured with Fourier transform infrared spectroscopy. Comparison of theoretical models with the measurements showed that chemical dissociation and subsequent rapid diffusion are the dominant processes. These results were confirmed by secondary ion mass spectroscopy. The experiments indicate that t.
Target-capture phylogenomics provide insights on gene and species tree discordances in Old World treefrogs (Anura: Rhacophoridae)

Genome-scale data have greatly facilitated the resolution of recalcitrant nodes that Sanger-based datasets have been unable to resolve. However, phylogenomic studies continue to use traditional methods such as bootstrapping to estimate branch support; and high bootstrap values are still interpreted as providing strong support for the correct topology. Furthermore, relatively little attention has been given to assessing discordances between gene and species trees, and the underlying processes that produce phylogenetic conflict. We generated novel genomic datasets to characterize and determine the causes of discordance in Old World treefrogs (Family: Rhacophoridae)—a group that is fraught with conflicting and poorly supported topologies among major clades. Additionally, a suite of data filtering strategies and analytical methods were applied to assess their impact on phylogenetic inference. We showed that incomplete lineage sorting was detected at all nodes that exhibited high levels of discordance. Those nodes were also associated with extremely short internal branches. We also clearly demonstrate that bootstrap values do not reflect uncertainty or confidence for the correct topology and, hence, should not be used as a measure of branch support in phylogenomic datasets. Overall, we showed that phylogenetic discordances in Old World treefrogs resulted from incomplete lineage sorting and that species tree inference can be improved using a multi-faceted, total-evidence approach, which uses the most amount of data and considers results from different analytical methods and datasets.
A Siamese CNN Architecture for Learning Chinese Sentence Similarity

This paper presents a deep neural architecture which applies the siamese convolutional neural network sharing model parameters for learning a semantic similarity metric between two sentences. In addition, two different similarity metrics (i.e., the Cosine Similarity and Manhattan similarity) are compared based on this architecture. Our experiments in binary similarity classification for Chinese sentence pairs show that the proposed siamese convolutional architecture with Manhattan similarity outperforms the baselines (i.e., the siamese Long Short-Term Memory architecture and the siamese Bidirectional Long Short-Term Memory architecture) by 8.7 points in accuracy.
Systematics and Multi-Gene Phylogeny of the Subfamily Nothoholostichinae (Ciliophora, Hypotrichia), With Integrative Description of a New Marine Species Nothoholosticha luporinii n. sp.

Morphogenesis of ciliated protists attracts a lot of attention, because their huge morphological diversity is related to formation of ciliary structures during cell division. In the present work, the morphology and morphogenesis as well as the phylogenetic position of a new, marine hypotrich ciliate, Nothoholosticha luporinii n. sp. , were investigated. The new species is characterized by having a combination of the following features: a bicorona whose anterior row contains four frontal cirri and posterior row includes only two cirri, a single buccal cirrus, midventral complex composed of about 30 cirral pairs, one pretransverse cirrus, 3–6 transverse cirri, one left and one right marginal cirral row; three bipolar dorsal kineties; contractile vacuole located in about 2/3 of the body length, two types of cortical granules, and many macronuclear nodules scattered throughout the cytoplasm. The morphogenesis of N. luporinii follows the ontogenetic mode of Pseudokeronopsis, a well-known and closely related genus except that the macronucleus fuses into a single mass in the middle fission stage. Phylogenetic analyses based on the rDNA operon classify Nothoholosticha in the family Pseudokeronopsidae and support the distinctness of the new taxon as well as the monophyletic origin of the subfamily Nothoholostichinae.
The Gut Microbiome Is Associated With Therapeutic Responses and Toxicities of Neoadjuvant Chemoradiotherapy in Rectal Cancer Patients—A Pilot Study

Responses to neoadjuvant chemoradiotherapy (nCRT) and therapy-related toxicities in rectal cancer vary among patients. To provide the individualized therapeutic option for each patient, predictive markers of therapeutic responses and toxicities are in critical need. We aimed to identify the association of gut microbiome with and its potential predictive value for therapeutic responses and toxicities. In the present study, we collected fecal microbiome samples from patients with rectal cancer at treatment initiation and just after nCRT. Taxonomic profiling via 16S ribosomal RNA gene sequencing was performed on all samples. Patients were classified as responders versus non-responders. Patients were grouped into no or mild diarrhea and severe diarrhea. STAMP and high-dimensional class comparisons via linear discriminant analysis of effect size (LEfSe) were used to compare the compositional differences between groups. Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) was utilized to predict differences in metabolic function between groups. Ten patients were classified as responders and 12 patients were classified as non-responders. Fourteen patients experienced no or mild diarrhea and 8 patients experienced severe diarrhea. Several bacteria taxa with significantly different relative abundances before and after nCRT were identified. Similarly, several baseline bacteria taxa and predicted pathways with significantly different relative abundances between responders and non-responders or between patients no or mild diarrhea and severe diarrhea were identified. Specifically, Shuttleworthia was identified as enriched in responders and several bacteria taxa in the Clostridiales order etc. were identified as enriched in non-responders. Pathways including fatty acid metabolism were predicted to be enriched in responders. In addition, Bifidobacterium, Clostridia, and Bacteroides etc. were identified as enriched in patients with no or mild diarrhea. Pathways including primary bile acid biosynthesis were predicted to be enriched in patients with no or mild diarrhea. Together, the microbiota and pathway markers identified in this study may be utilized to predict the therapeutic responses and therapy-related toxicities of nCRT in patients with rectal cancer. More patient data is needed to verify the current findings and the results of metagenomic, metatranscriptomic, and metabolomic analyses will further mine key biomarkers at the compositional and functional level.
Compassion: From Its Evolution to a Psychotherapy

The concept, benefits and recommendations for the cultivation of compassion have been recognized in the contemplative traditions for thousands of years. In the last 30 years or so, the study of compassion has revealed it to have major physiological and psychological effects influencing well-being, addressing mental health difficulties, and promoting prosocial behavior. This paper outlines an evolution informed biopsychosocial, multicomponent model to caring behavior and its derivative “compassion” that underpins newer approaches to psychotherapy. The paper explores the origins of caring motives and the nature and biopsychosocial functions of caring-attachment behavior. These include providing a secure base (sources of protection, validation, encouragement and guidance) and safe haven (source of soothing and comfort) for offspring along with physiological regulating functions, which are also central for compassion focused therapy. Second, it suggests that it is the way recent human cognitive competencies give rise to different types of “mind awareness” and “knowing intentionality” that transform basic caring motives into potentials for compassion. While we can care for our gardens and treasured objects, the concept of compassion is only used for sentient beings who can “suffer. ” As psychotherapy addresses mental suffering, cultivating the motives and competencies of compassion to self and others can be a central focus for psychotherapy.
D-dimer, Troponin, and Urea Level at Presentation With COVID-19 can Predict ICU Admission: A Single Centered Study

Background: Identifying clinical-features or a scoring-system to predict a benefit from hospital admission for patients with COVID-19 can be of great value for the decision-makers in the health sector. We aimed to identify differences in patients' demographic, clinical, laboratory, and radiological findings of COVID-19 positive cases to develop and validate a diagnostic-model predicting who will develop severe-form and who will need critical-care in the future. Methods: In this observational retrospective study, COVID-19 positive cases (total 417) diagnosed in Al Kuwait Hospital, Dubai, UAE were recruited, and their prognosis in terms of admission to the hospital and the need for intensive care was reviewed until their tests turned negative. Patients were classified according to their clinical state into mild, moderate, severe, and critical. We retrieved all the baseline clinical data, laboratory, and radiological results and used them to identify parameters that can predict admission to the intensive care unit (ICU). Results: Patients with ICU admission showed a distinct clinical, demographic as well as laboratory features when compared to patients who did not need ICU admission. This includes the elder age group, male gender, and presence of comorbidities like diabetes and history of hypertension. ROC and Precision-Recall curves showed that among all variables, D dimers (>1.5 mg/dl), Urea (>6.5 mmol/L), and Troponin (>13.5 ng/ml) could positively predict the admission to ICU in patients with COVID-19. On the other hand, decreased Lymphocyte count and albumin can predict admission to ICU in patients with COVID-19 with acceptable sensitivity (59.32, 95% CI [49.89–68.27]) and specificity (79.31, 95% CI [72.53–85.07]). Conclusion: Using these three predictors with their cut of values can identify patients who are at risk of developing critical COVID-19 and might need aggressive intervention earlier in the course of the disease.
Photoinduced and thermal isomerization processes for bis-oxonols: rotor volume, stereochemical and viscosity effects

Four bis-oxonols have been synthesized which possess different alkyl substituents appended to the thiobarbiturate subunit. The nature of the alkyl substituent affects the photophysical properties of the dye in solution since it modulates the rate of rotation of the thiobarbiturate subunit around one of the double bonds in the connecting trimethine bridge. Rates of light-induced (trans to cis) and thermal (cis to trans) isomerization processes have been measured for one of the dyes in protic (i.e. alkanols) and aprotic solvents at various temperatures. These rates, together with activation energies derived from Arrhenius plots, are discussed in terms of the hydrogen bonding and stereochemical properties of the solvent. The thermal step is very sensitive to the stereochemistry of the solvent while the light-induced process is controlled mostly by the size of the rotor and the solvent viscosity. The overall effects may be explained, at least in a qualitative sense, in terms of the medium-enhanced barrier model.
Crystal structure of bis(4-aminobenzoato)aquacadmium dihydrate, [Cd(H2NC6H4COO)2(H2O)]n · 2nH2O

C28H36CCI2N4O14, triclinic, PI (No. 2), a = 6.2028(7) Ä, b = 8.253(1) Ä, с = 17.592(2) Ä, α = 94.295(1)°, β = 100.153(1)°, γ = 112.072(4)°, V = 811.6 Ä, Ζ = 1, R0(F) = 0.044, wRzt(F) = 0.089, Τ = 273 К. * Correspondence author (e-mail: ki taga@sbchem.kyoto-u.ac. jn) Source of material An aqueous solution (10 ml) of sodium p-aminobenzoate (2 mmol) was transferred to a test tube, then a methanolic solution (10 ml) of cadmium(II) nitrate (1 mmol) was poured into the tube without mixing the two solutions. Colourless crystals were obtained after one week.
Development and Validation of a Nomogram for Differentiating Combined Hepatocellular Cholangiocarcinoma From Intrahepatic Cholangiocarcinoma

Objectives To establish a nomogram based on preoperative laboratory study variables using least absolute shrinkage and selection operator (LASSO) regression for differentiating combined hepatocellular cholangiocarcinoma (cHCC) from intrahepatic cholangiocarcinoma (iCCA). Methods We performed a retrospective analysis of iCCA and cHCC patients who underwent liver resection. Blood signatures were established using LASSO regression, and then, the clinical risk factors based on the multivariate logistic regression and blood signatures were combined to establish a nomogram for a differential preoperative diagnosis between iCCA and cHCC. The differential accuracy ability of the nomogram was determined by Harrell’s index (C-index) and decision curve analysis, and the results were validated using a validation set. Furthermore, patients were categorized into two groups according to the optimal cut-off values of the nomogram-based scores, and their survival differences were assessed using Kaplan-Meier curves. Results A total of 587 patients who underwent curative liver resection for iCCA or cHCC between January 2008 and December 2017 at West China Hospital were enrolled in this study. The cHCC score was based on the personalized levels of the seven laboratory study variables. On multivariate logistic analysis, the independent factors for distinguishing cHCC were age, sex, biliary duct stones, and portal hypertension, all of which were incorporated into the nomogram combined with the cHCC-score. The nomogram had a good discriminating capability, with a C-index of 0.796 (95% CI, 0.752–0.840). The calibration plot for distinguishing cHCC from iCCA showed optimal agreement between the nomogram prediction and actual observation in the training and validation sets. The decision curves indicated significant clinical usefulness. Conclusion The nomogram showed good accuracy for the differential diagnosis between iCCA and cHCC preoperatively, and therapeutic decisions would improve if it was applied in clinical practice.
How Features of the Implementation Process Shape the Success of an Observation-Based Coaching Program

Studies investigating the effectiveness of professional development (PD) programs have provided no conclusive findings on what exactly makes a PD effort effective. Using an observation-based coaching PD program, we explore which features in the PD implementation process facilitated or impeded teachers’ meaningful engagement in and learning from the PD program. We interviewed seven PD coaches and a selection of 11 teachers involved in a 3-year PD project. We found that how the school and the coach implemented the PD project played a critical role in shaping teachers’ willingness to participate in the program. We conclude that the success of a PD program depends not only on enduring effective PD features but also and especially on the PD implementation process within the context of daily school life.
Probabilistic Reversal Learning Deficits in Patients With Methamphetamine Use Disorder—A Longitudinal Pilot Study

Methamphetamine use disorder (MUD) is increasing worldwide and commonly associated with learning deficits. Little is known the about underlying trajectories, i.e., how the affected higher-order cognitive functions develop over time and with respect to abstinence and relapse. A probabilistic reversal learning (PRL) paradigm was implemented to uncover the microstructure of impulsive choice and maladaptive learning strategies in 23 patients with MUD in comparison with 24 controls. Baseline data revealed fewer optimal choices and a pattern of altered learning behavior from negative and positive feedback in patients suggesting impairments in flexibly-adapting behavior to changes of reward contingencies. Integrating longitudinal data from a follow-up assessment after 3 months of specific treatment revealed a group-by-time interaction indicating a normalization of these cognitive impairments in patients with MUD. In summary, our study demonstrates behavioral correlates of maladaptive decision-making processes in patients with MUD, which may recover after 3 months of MUD-specific therapy paving the way for further learning-based interventions. Limited by a small sample size, the results of this pilot study warrant replication in larger populations.
Appendicitis in Children in a Large Italian COVID-19 Pandemic Area

Introduction: The coronavirus disease 2019 (COVID-19) pandemic has dramatically changed the routine activities of pediatric surgical centers, and it determined the reduction of admissions in the pediatric emergency departments (PED). We reviewed the records of patients affected by acute appendicitis (AA) during the COVID-19 pandemic period in a large Italian COVID-19 pandemic area. Methods: Data regarding demographics, age, macroscopic and microscopic findings, and time between symptom onset and PED admission of patients affected by confirmed AA in the period between March and April 2020 were considered. The data were compared with those obtained during the same period of 2019, 2018, and 2017 in the included centers. Data were quoted as median (range) or absolute number. Non-parametric statistical tests were used to compare groups. A p ≤ 0.05 was regarded as significant. Since only anonymous data have been used and the data storage meets current data protection regulations, ethical committee approval was not required for this study. Results: Eighty-six patients underwent surgical appendectomy for AA between February 20th, 2020 and April 20th, 2020; 32.5% were complicated appendicitis and 67.5% were uncomplicated. Fifty-three patients were males and 33 were females. Patients' age ranged from 3 to 17 years and the median age was 10 years. The median time between the onset of symptoms and the admission in PED was 1.85 days. The average time between the symptom onset and PED admission was 1.8 days. Conclusions: Although fear from the COVID-19 pandemic determined a delayed diagnosis of serious pediatric diseases, the increasing prevalence and severity of AA were not demonstrated in the most COVID-19-affected areas of Italy.
Sensitivity of a Satellite Algorithm for Harmful Algal Bloom Discrimination to the Use of Laboratory Bio-optical Data for Training

Early detection of dense harmful algal blooms (HABs) is possible using ocean colour remote sensing. Some algorithms require a training dataset, usually constructed from satellite images with a priori knowledge of the existence of the bloom. This approach can be limited if there is a lack of in situ observations, coincident with satellite images. A laboratory experiment collected biological and bio-optical data from a culture of Karenia mikimotoi, a harmful phytoplankton dinoflagellate. These data showed characteristic signals in chlorophyll-specific absorption and backscattering coefficients. The bio-optical data from the culture and a bio-optical model were used to construct a training dataset for an existing statistical classifier. MERIS imagery over the European continental shelf were processed with the classifier using different training datasets. The differences in positive rates of detection of K. mikimotoi between using an algorithm trained with purely manually selected areas on satellite images and using laboratory data as training was overall <1%. The difference was higher, <15%, when using modeled optical data rather than laboratory data, with potential for improvement if local average chlorophyll concentrations are used. Using a laboratory-derived training dataset improved the ability of the algorithm to distinguish high turbidity from high chlorophyll concentrations. However, additional in situ observations of non-harmful high chlorophyll blooms in the area would improve testing of the ability to distinguish harmful from non-harmful high chlorophyll blooms. This approach can be expanded to use additional wavelengths, different satellite sensors and different phytoplankton genera.