cis-Bis(1,10-phenanthroline-κ2 N,N′)bis­(thio­cyanato-κN)magnesium(II)

The title compound, [Mg(NCS)2(C12H8N2)2], has been synthesized from the hydro­thermal reaction of MgCl2, KSCN, 1,10-phenanthroline and H2O. Its structure is isotypic with the MnII, FeII, CoII, NiII, CuII and ZnII analogues. The MgII cation has a slightly distorted octa­hedral geometry containing four N atoms from two 1,10-phenanthroline mol­ecules and two N atoms from two thio­cyanate anions. The asymmetric unit contains one-half mol­ecule, and the complete complex has 2 symmetry

The Impact of Depth and Width on Transformer Language Model Generalization

To process novel sentences, language models (LMs) must generalize compositionally -- combine familiar elements in new ways. What aspects of a model's structure promote compositional generalization? Focusing on transformers, we test the hypothesis, motivated by recent theoretical and empirical work, that transformers generalize more compositionally when they are deeper (have more layers). Because simply adding layers increases the total number of parameters, confounding depth and size, we construct three classes of models which trade off depth for width such that the total number of parameters is kept constant (41M, 134M and 374M parameters). We pretrain all models as LMs and fine-tune them on tasks that test for compositional generalization. We report three main conclusions: (1) after fine-tuning, deeper models generalize better out-of-distribution than shallower models do, but the relative benefit of additional layers diminishes rapidly; (2) within each family, deeper models show better language modeling performance, but returns are similarly diminishing; (3) the benefits of depth for compositional generalization cannot be attributed solely to better performance on language modeling or on in-distribution data

Retrievals of XCO2_{CO2}, XCH4_{CH4} and XCO_{CO} from portable, near-infrared Fourier transform spectrometer solar observations in Antarctica

The COllaborative Carbon Column Observing Network (COCCON) uses low-resolution, portable EM27/SUN Fourier transform spectrometers (FTSs) to make retrievals of column-averaged dry-air mole fractions (DMFs, represented as X$_{gas}$) of CO$_{2}$, CH$_{4}$, CO and H$_{2}$O from near-infrared solar absorption spectra. The COCCON has developed rapidly over recent years and complements the Total Carbon Column Observing Network (TCCON). In this work, we provide details of the first seasonal time series of near-infrared X$_{CO2}$, X$_{CH4}$ and X$_{CO}$ retrievals from measurements made in Antarctica during the deployment of an EM27/SUN to the Arrival Heights laboratory on Ross Island over the austral summer of 2019–2020 under the auspices of the COCCON. The DMFs of all three species were lower in Antarctica than at mid-latitude, and for X$_{CO2}$ and X$_{CO}$, the retrieved values were less variable. For X$_{CH4}$ however, the variability was significantly greater and it was found that this was strongly correlated to the proximity of the polar vortex. In order to ensure the stability of the instrument and the traceability of the retrievals, side-by-side comparisons to the TCCON station at Lauder, New Zealand and retrievals of the instrument line shape (ILS) were made before and after the measurements in Antarctica. These indicate that, over the course of the deployment, the instrument stability was such that the change in retrieved X$_{CO2}$ was well below 0.1%. The value of these data for satellite validation is demonstrated by making comparisons with the TROPOspheric Monitoring Instrument (TROPOMI) on the Sentinel-5 precursor (S5P) satellite. The dataset is available from the COCCON central facility hosted by the ESA Atmospheric Validation Data Centre (EVDC): https://doi.org/10.48477/coccon.pf10.arrivalheights.R02 (Pollard, 2021)

Factors associated with suicidal attempts in female patients with mood disorder

AimThis study aims to establish a nomogram model to predict the relevance of SA in Chinese female patients with mood disorder (MD).MethodThe study included 396 female participants who were diagnosed with MD Diagnostic Group (F30–F39) according to the 10th Edition of Disease and Related Health Problems (ICD-10). Assessing the differences of demographic information and clinical characteristics between the two groups. LASSO Logistic Regression Analyses was used to identify the risk factors of SA. A nomogram was further used to construct a prediction model. Bootstrap re-sampling was used to internally validate the final model. The Receiver Operating Characteristic (ROC) curve and C-index was also used to evaluate the accuracy of the prediction model.ResultLASSO regression analysis showed that five factors led to the occurrence of suicidality, including BMI (β = −0.02, SE = 0.02), social dysfunction (β = 1.72, SE = 0.24), time interval between first onset and first dose (β = 0.03, SE = 0.01), polarity at onset (β = −1.13, SE = 0.25), and times of hospitalization (β = −0.11, SE = 0.06). We assessed the ability of the nomogram model to recognize suicidality, with good results (AUC = 0.76, 95% CI: 0.71–0.80). Indicating that the nomogram had a good consistency (C-index: 0.756, 95% CI: 0.750–0.758). The C-index of bootstrap resampling with 100 replicates for internal validation was 0.740, which further demonstrated the excellent calibration of predicted and observed risks.ConclusionFive factors, namely BMI, social dysfunction, time interval between first onset and first dose, polarity at onset, and times of hospitalization, were found to be significantly associated with the development of suicidality in patients with MD. By incorporating these factors into a nomogram model, we can accurately predict the risk of suicide in MD patients. It is crucial to closely monitor clinical factors from the beginning and throughout the course of MD in order to prevent suicide attempts

Effect of congenital ptosis on astigmatism and axis length

AIM: To investigate the effects of congenital ptosis degree on total astigmatism, corneal astigmatism, intraocular astigmatism and axis length, and to discuss the relation with amblyopia. <p>METHODS: Fifty patients(100 eyes)with congenital ptosis were selected and divided into four groups: 33 eyes in group Ⅰ(normal); 20 eyes in group Ⅱ(mild); 17 eyes in group Ⅲ(moderate); 30 eyes in group Ⅳ(severity). Firstly, they received standardized medical optometry. Absolute value of astigmatism was recorded as total astigmatism. Then, corneal topography was used to measure double eyes for at least 3 times, and the best results were used to record the SimK. Define absolute value of △SimK as corneal astigmatism. Finally, axial length was measured for 5 times by A super-measurement, and take the mean value. Formula: intraocular astigmatism=total astigmatism-corneal astigmatism.<p>RESULTS: There was a significance difference between total astigmatism and cornea astigmatism(<i>P</i>=0.000, 0.002<0.05). Also they were positive correlation with severity of ptosis(Spearman <i>r</i>_s=0.514, 0.721,<i>P</i><0.05), but there was not significance difference in axial orientation, intraocular astigmatism and axial length(all <i>P</i>>0.05). The axial orientation, intraocular astigmatism had no correlation with severity of ptosis.<p>CONCLUSION: The congenital ptosis affects on eye astigmatism through the change of cornea astigmatism, which is related to severity of ptosis, but has no effect on axial length. The rate of amblyopia is higher than normal on congenital ptosisespecially severity. Amblyopia is related to high astigmatism which is moderate astigmatism with rule

Development and validation of a prediction nomogram for non-suicidal self-injury in female patients with mood disorder

BackgroundNon-suicidal self-injury (NSSI) is a highly prevalent behavioral problem among people with mental disorders that can result in numerous adverse outcomes. The present study aimed to systematically analyze the risk factors associated with NSSI to investigate a predictive model for female patients with mood disorders.MethodsA cross-sectional survey among 396 female patients was analyzed. All participants met the mood disorder diagnostic groups (F30–F39) based on the Diseases and Related Health Problems 10th Revision (ICD-10). The Chi-Squared Test, t-test, and the Wilcoxon Rank-Sum Test were used to assess the differences of demographic information and clinical characteristics between the two groups. Logistic LASSO Regression Analyses was then used to identify the risk factors of NSSI. A nomogram was further used to construct a prediction model.ResultsAfter LASSO regression selection, 6 variables remained significant predictors of NSSI. Psychotic symptom at first-episode (β = 0.59) and social dysfunction (β = 1.06) increased the risk of NSSI. Meanwhile, stable marital status (β = −0.48), later age of onset (β = −0.01), no depression at onset (β = −1.13), and timely hospitalizations (β = −0.10) can decrease the risk of NSSI. The C-index of the nomogram was 0.73 in the internal bootstrap validation sets, indicated that the nomogram had a good consistency.ConclusionOur findings suggest that the demographic information and clinical characteristics of NSSI can be used in a nomogram to predict the risk of NSSI in Chinese female patients with mood disorders

Negative Academic Emotion and Psychological Well-being in Chinese Rural-to-Urban Migrant Adolescents: Examining the Moderating Role of Cognitive Reappraisal

The study aimed to explore the relationship among negative academic emotions (e.g., anxiety, shame, anger, boredom, hopelessness, disappointment, and hatred), psychological well-being (including life vitality, health concern, altruism commitment, self-value, friendly relationship, and personal development), and cognitive reappraisal in rural-to-urban migrant adolescents in China. Specifically, it was hypothesized that the relationship between psychological well-being and negative academic emotions is moderated by cognitive reappraisal. A total of 311 migrant adolescents aged 14–20 years were selected, including 132 boys and 179 girls. Results of a regression analysis showed that cognitive reappraisal (positive) and negative academic emotions were significant predictors of psychological well-being. The interaction effect between cognitive reappraisal and negative academic emotion was also a significant predictor of psychological well-being. In the simple slope analysis the group with a below average cognitive reappraisal score the negative academic emotions were associated with lower psychological well-being, whereas in the group with above average cognitive reappraisal the effect of negative academic emotions on psychological well-being was not significant. However, for those with a cognitive reappraisal score of 1 standard deviation above the average, the effect of negative academic emotions on psychological well-being was not significant. These results suggest that cognitive reappraisal was a significant moderator in the relationship between negative academic emotion and psychological well-being

Acute pulmonary embolism combined with acute myocardial infarction as the first manifestation of acute leukemia: a case report

Thrombotic complications in acute myeloid leukemia (AML) are uncommon due to coagulation dysfunction and thrombocytopenia. We report a unique case of AML presenting as concomitant pulmonary embolism and atypical acute myocardial infarction. A 67-year-old male experienced persistent bilateral chest pain. Despite an unremarkable electrocardiogram, elevated D-dimer and mildly increased troponin T levels prompted further investigation, leading to the diagnosis of simultaneous pulmonary embolism and acute myocardial infarction. The patient underwent percutaneous coronary intervention and received triple antithrombotic therapy. However, antithrombotic therapy was discontinued following a sharp decline in hemoglobin and platelet counts, and the patient subsequently developed persistent fever. AML was diagnosed via bone marrow biopsy. Chemotherapy was not initiated due to the patient's deteriorating condition, and he ultimately succumbed to presumed intracranial bleeding