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Over the past few years, there have been tremendous developments in the design and synthesis of organic optoelectronic materials with appealing applications in device fabrication of organic light-emitting diodes, superconductors, organic lasers, organic field-effect transistors, clean energy-producing organic solar cells, etc. There is an increasing demand for the synthesis of green, highly efficient organic optoelectronic materials to cope with the issue of efficiency roll-off in organic semiconductor-based devices. This review systematically summarized the recent progress in the design and synthesis of small organic molecules having promising optoelectronic properties for their potential applications in optoelectronic devices during the last 10-year range (2010–early 2021). There is a surge of interest in small organic molecules with optoelectronic properties due to various advantages over other organic semiconductors. The novel synthesized materials advance the field of optoelectronics by fabrication of high-efficiency devices, such as optical biosensors, OLEDs, Solar cells, lasers, and optic fibers. [ABSTRACT FROM AUTHOR]

In the digital age, social media has emerged as a significant platform, generating a vast amount of raw data daily. This data reflects the opinions of individuals from diverse backgrounds, races, cultures, and age groups, spanning a wide range of topics. Businesses can leverage this data to extract valuable insights, improve their services, and effectively reach a broader audience based on users' expressed opinions on social media platforms. To harness the potential of this extensive and unstructured data, a deep understanding of Natural Language Processing (NLP) is crucial. Existing approaches for sentiment analysis (SA) often rely on word co-occurrence frequencies, which prove inefficient in practical scenarios. Identifying this research gap, this paper presents a framework for concept-level sentiment analysis, aiming to enhance the accuracy of sentiment analysis (SA). A comprehensive Urdu language dataset was constructed by collecting data from YouTube, consisting of various talks and reviews on topics such as movies, politics, and commercial products. The dataset was further enriched by incorporating language rules and Deep Neural Networks (DNN) to optimize polarity detection. For sentiment analysis, the proposed framework employs predefined rules to trigger sentiment flow from words to concepts, leveraging the dependency relations among different words in a sentence based on Urdu language grammatical rules. In cases where predefined patterns are not triggered, the framework seamlessly switches to its sub-symbolic counterpart, passing the data to the DNN for sentence classification. Experimental results demonstrate that the proposed framework surpasses state-of-the-art approaches, including LSTM, CNN, SVM, LR, and MLP, achieving an improvement of 6–7% on Urdu dataset. In conclusion, this research paper introduces a novel framework for concept-level sentiment analysis of Urdu language data sourced from social media platforms. By combining language rules and DNN, the proposed framework demonstrates superior performance compared to existing methodologies, showcasing its effectiveness in accurately analyzing sentiment in Urdu text data. [ABSTRACT FROM AUTHOR]

Background: In primary care risk stratification, automated algorithms do not consider the same factors as providers. The process of adjudication, in which providers review and adjust algorithm-derived risk scores, may improve the prediction of adverse outcomes. Objective: We assessed the patient factors that influenced provider adjudication behavior and evaluated the performance of an adjudicated risk model against a commercial algorithm. Design: (1) Structured interviews with primary care providers (PCP) and multivariable regression analysis and (2) receiver operating characteristic curves (ROC) with sensitivity analyses. Participants: Primary care patients aged 18 years and older with an adjudicated risk score. Approach and Main Measures: (1) Themes from structured interviews and discrete variables associated with provider adjudication behavior; (2) comparison of concordance statistics and sensitivities between risk models. Key Results: 47,940 patients were adjudicated by PCPs in 2018. Interviews revealed that, in adjudication, providers consider disease severity, presence of self-management skills, behavioral health, and whether a risk score is actionable. Provider up-scoring from the algorithmic risk score was significantly associated with patient male sex (OR 1.24, CI 1.15–1.34), age > 65 (OR 2.55, CI 2.24–2.91), Black race (1.26, CI 1.02–1.55), polypharmacy >10 medications (OR 4.87, CI 4.27–5.56), a positive depression screen (OR 1.57, CI 1.43–1.72), and hemoglobin A1c >9 (OR 1.89, CI 1.52–2.33). Overall, the adjudicated risk model performed better than the commercial algorithm for all outcomes: ED visits (c-statistic 0.689 vs. 0.684, p < 0.01), hospital admissions (c-statistic 0.663 vs. 0.649, p < 0.01), and death (c-statistic 0.753 vs. 0.721, p < 0.01). When limited to males or seniors, the adjudicated models displayed either improved or non-inferior performance compared to the commercial model. Conclusions: Provider adjudication of risk stratification improves model performance because providers have a personal understanding of their patients and are able to apply their training to clinical decision-making. [ABSTRACT FROM AUTHOR]

Main conclusion: Salicylic acid (SA) and drought stress promote more flowering in sweet orange. The physiological response and molecular mechanism underlying stress-induced floral initiation were discovered by transcriptome profiling. Numerous flowering-regulated genes were identified, and ectopically expressed CsLIP2A promotes early flowering in Arabidopsis. Floral initiation is a critical developmental mechanism associated with external factors, and citrus flowering is mainly regulated by drought stress. However, little is known about the intricate regulatory network involved in stress-induced flowering in citrus. To understand the molecular mechanism of floral initiation in citrus, flower induction was performed on potted Citrus sinensis trees under the combined treatment of salicylic acid (SA) and drought (DR). Physiological analysis revealed that SA treatment significantly normalized the drastic effect of drought stress by increasing antioxidant enzyme activities (SOD, POD, and CAT), relative leaf water content, total chlorophyll, and proline contents and promoting more flowering than drought treatment. Analysis of transcriptome changes in leaves from different treatments showed that 1135, 2728 and 957 differentially expressed genes (DEGs) were revealed in response to DR, SD (SA + DR), and SA (SA + well water) treatments in comparison with the well watered plants, respectively. A total of 2415, 2318 and 1933 DEGs were expressed in DR, SD, and SA in comparison with water recovery, respectively. Some key flowering genes were more highly expressed in SA-treated drought plants than in DR-treated plants. GO enrichment revealed that SA treatment enhances the regulation and growth of meristem activity under drought conditions, but no such a pathway was found to be highly enriched in the control. Furthermore, we focused on various hormones, sugars, starch metabolism, and biosynthesis-related genes. The KEGG analysis demonstrated that DEGs enriched in starch sucrose metabolism and hormonal signal transduction pathways probably account for stress-induced floral initiation in citrus. In addition, a citrus LIPOYLTRANSFERSAE 2A homologous (LIP2A) gene was upregulated by SD treatment. Ectopic expression of CsLIP2A exhibited early flowering in transgenic Arabidopsis. Taken together, this study provides new insight that contributes to citrus tree floral initiation under the SA-drought scenario as well as an excellent reference for stress-induced floral initiation in woody trees. [ABSTRACT FROM AUTHOR]

Patient reminders are a specific type of clinical decision support (CDS) and have been shown to improve adherence to preventative performance measures.[5] We incorporated the cognitive assessment performance into standard patient rooming workflows for improved reliability and durability. The provider could then update the patient reminder for cognitive screening as complete or contact the scheduler to follow up with any patient due for assessment. [Extracted from the article]

The effect of the FePO material phase transformation in the direct selective oxidation of methane to methanol was studied using various oxidants, i.e. O, HO and NO. The phases of the heterogeneous catalyst applied, before and after the reactions, were characterized by M¨ossbauer spectroscopy. The main reaction products were methanol, carbon monoxide and carbon dioxide, whereas formaldehyde was produced in rather minute amounts. The Mössbauer spectra showed the change of the initial catalyst material, FePO (tridymite-like phase (tdm)), to the reduced metal form, iron(II) pyrophosphate, FePO, and thereafter, the material phase change was governed by the oxidation with individual oxidizing species.Mössbauer spectroscopy measurements applied along with X-ray diffraction (XRD) studies on fresh, reduced and spent catalytic materials demonstrated a transformation of the catalyst to a mixture of phases which depended on operating process conditions. Generally, activity was low and should be a subject of further material optimization and engineering, while the selectivity towards methanol at low temperatures applied was adequate. The proceeding redox mechanism should thus play a key role in catalytic material design, while the advantage of iron-based heterogeneous catalysts primarily lies in them being comparably inexpensive and comprising non-critical raw materials only. [ABSTRACT FROM AUTHOR]

This paper aims at providing further evidence on stochastic income convergence for a group of 30 countries over a century long period, from 1900 to 2008, utilizing novel econometric methods for determining structural breaks and unit roots. Recent studies have noted the problem of low power and size distortions in unit root tests, and spurious rejections that plague unit root tests which treat structural breaks asymmetrically. The proposed methodology used in this paper enables robust detection and estimation of breaks, and reliable inference regarding the presence of unit roots conditional on the presence or absence of breaks. We find that the periods of War, the Great Depression and oil price shocks to be possible reasons for the occurrence of breaks. The unit root test results indicate limited evidence of stochastic income convergence. We find none of the current upper-middle-income and lower-middle-income countries to show convergence, while high-income countries such as Australia, Canada, the Netherlands, Norway, Portugal and USA show signs of convergence toward the world average. [ABSTRACT FROM AUTHOR]

A phase specific iron orthophosphate catalyst, FePO, was synthesized and promoted with cesium. This catalyst was subjected to oxidative dehydrogenation reactions to form an alkyl methacrylate. The phases of the catalyst, before and after the reactions, were studied as a function of different cesium loading. Mössbauer spectra of the catalysts show the change of the catalyst precursor FePO, to i) the tridymite-like phase, ii) the reduced form, iron(II) pyrophosphate and Fe P O and iii) the α-phase of iron phosphate which is governed by the temperatures of oxidation. X-ray diffraction and Mössbauer measurements on the spent catalyst show a transformation of the catalyst to a mixture of phases. [ABSTRACT FROM AUTHOR]

Vanadium-magnesium oxide (VMgO) catalysts with vanadium loadings of 15 and 20 wt% were prepared by the method of wet impregnation. The prepared catalyst were characterized by IR and Raman spectroscopy, Powder XRD, ICP-OES, N adsorption desorption isotherms, oxygen chemisorption, TPR, TPD, SEM, SEM-EDX and TEM. From XRD and IR analyses, vanadium was found to be present in two phases i.e. orthovanadate and pyrovanadate. Dispersion of vanadium on the MgO was in the range of 30-40 % and oxygen chemisorption capacity increased with the vanadium loading. The catalysts were tested in a continuous flow fixed bed reactor at a GHSV of 4,000 h over a temperature range of 350-550 °C at an n-heptane to oxygen molar ratio of 1:1. Oxidative dehydrogenation of n-heptane showed that product selectivity depends on the phase of vanadium present on the MgO catalysts and conversion is proportional to the amount of chemisorbed oxygen on the surface of the catalyst. Carbon oxides are the major products over the MgO support, whereas heptene isomers are the major products over the VMgO catalysts. 2-Heptene, toluene and 2-heptanol are the dominant products in the heptene isomers, aromatics and oxygenate products respectively. Graphical Abstract: [Figure not available: see fulltext.] [ABSTRACT FROM AUTHOR]

A letter to the editor is presented about the clinical case of a 65-year-old woman who received airway management for osteogenesis imperfecta.