Flexible social monitoring as revealed by eye movements: Spontaneous mental state updating triggered by others' unexpected actions.

Successful interactions require not only representing others' mental states but also flexibly updating them, whenever one's original inferences may no longer hold. Such situations arise, for instance, when a partner's behavior is incongruent with one's expectations. Although these situations are rather common, the question whether people update others' mental states spontaneously upon encountering unexpected behaviors and whether they use the updated mental states in novel contexts, has been largely unexplored. We addressed these issues in two experiments. In each experiment participants first performed an anticipatory looking task, reacting to a virtual 'partner', who categorized pictures based on their ambiguous or non-ambiguous color. Importantly, to perform the task participants did not have to track their partner's perspective. Following a correct categorization phase, the 'partner' started to systematically miscategorize one of the ambiguous colors (e.g., as if she would now believe that the greenish blue is green). We measured how participants' anticipatory looking preceding the partner's categorization changed across trials. Afterward, we asked whether participants implicitly transferred their knowledge about the partner's updated perspective to a new task. Finally, they performed an explicit perspective-taking task, to test whether they selectively updated the partner's perspective, but not their own. Results revealed that correct anticipations started to emerge only after a few miscategorizations, indicating the spontaneous updating of the other's perspective regarding the miscategorized color. Signatures of updating emerged somewhat earlier when the partner made similarity judgments (Experiment 2), highlighting the subjective nature of her decisions, compared to when following an explicit color-categorization rule (Experiment 1). In the explicit perspective-taking task of both experiments, roughly half of the participants could categorize items according to the partner's (spontaneously updated) perspective and also used their partner's updated perspective in the implicit transfer task to some degree, while they were the ones who displayed more pronounced anticipatory patterns as well. Such data provides strong evidence that the observed changes in anticipatory looking reflect spontaneous and flexible mental state updating. In addition, the findings also point to a high individual variability both in the updating of attributed mental states and the use of the updated mental state content.

Extraction and characterization of novel fibers from Tecoma stans Linn bark for use as reinforcement in polymer composites.

Embarking on a pioneering investigation, this study unravels the extraordinary qualities of Tecoma stans Fibers (TSFs), freshly harvested from the rachis, establishing them as prospective reinforcements for biocomposites. Delving into their intricate characteristics, TSFs exhibit a unique fusion of physical resilience, with a density of 1.81 ±â€¯0.39 g/cc and a diameter of 234.12 ±â€¯7.63 µm. Complementing their physical prowess, their chemical composition boasts a harmonious blend of cellulose (70.1 ±â€¯9.06 wt%), hemicellulose (13.56 ±â€¯4.29 wt%), lignin (7.62 ±â€¯2.39 wt%), moisture (4.21 ±â€¯1.56 wt%), wax (2.37 ±â€¯0.63 wt%), and ash (1.25 ±â€¯0.36 wt%). In the realm of mechanical strength, TSFs showcase an impressive tensile strength of 639 ±â€¯18.47 MPa, coupled with a robust strain at failure of 1.75 ±â€¯0.13 % and a Young Modulus of 36.51 ±â€¯1.96 GPa. Unveiling their crystalline intricacies, these fibers reveal a microfibril angle of 14.66 ±â€¯0.15°, a crystalline index (CI) of 63.83 %, and a crystallite size (CS) of 9.27 nm. Beyond their mechanical marvels, TSFs exhibit unwavering thermal stability, enduring temperatures up to 297.36 °C, with a Tmax reaching an impressive 392.09 °C.

Occurrence of heavy metals coupled with elevated levels of essential elements in chocolates: Health risk assessment.

The presence of contaminants in cacao-derived products, especially in chocolates, has raised concerns regarding food safety and human health. The study assessed the concentration variation of 16 elements in 155 chocolate samples from the US market by cacao content and country of geographic origin. The study further examined the potential health risks posed by toxic metals and determined the contribution of essential elements to the Daily Recommended Intake (DRI), estimated based on an ounce (∼28.4 g) of daily chocolate consumption. Dark chocolates with ≥50 % cacao exhibited consecutively increasing mean levels from 1.2 to 391 µg/kg for U, Tl, Th, As, Pb, Se, Cd, and Co. Similarly, Ni, Sr, Cu, Mn, Zn, Fe, Ca, and Mg had mean concentrations from 4.0 to 1890 mg/kg. Dark chocolates sourced from Central and South America exhibited the highest mean levels of Cd, and South America samples also contained elevated Pb, whereas those from West Africa and Asia had low Cd and Pb, respectively. Cacao contents showed increasingly strong association with Cd, Co, Mn, Sr, Ni, Cu, Zn, and Mg (r = 0.60-0.84), and moderately with Se, Fe, As, and Tl (r = 0.35-0.49), indicating these elements are primarily derived from cacao beans. Weak association of cacao contents with Pb, Th, and U levels (r < 0.25), indicates post-harvest contaminations. Hazard Quotient (HQ) > 1 was found only for Cd in 4 dark chocolates, and Hazard Index (HI) > 1 for cumulative risk of Cd, Pb, Ni, As, and U was found in 33 dark chocolates, indicating potential non-carcinogenic risks for 15 kg children but none for 70 kg adults. Dark chocolate also substantially contributed to 47-95 % of the DRI of Cu for children and 50 % for adults. Dark chocolates also provided notable Fe, Mn, Mg, and Zn contributions to the DRI. These essential elements are recognized to reduce the bioavailability of toxic metals such as Cd, Pb, or Ni, thereby potentially lowering associated health risks. This study informs consumers, food industries, and regulatory agencies to target cacao origins or chocolate brands with lower toxic metal contents for food safety and minimizing adverse health effects.

Apparent amylose content positively influences the quality of extruded fortified rice kernels.

The present research studies the impact of apparent amylose content (AAC) on the quality of fortified rice kernels (FRK), a health food designed to combat iron deficiency anemia by fortifying with iron, folic acid, and vitamin B12. Five FRK formulations with varying AAC (0.46-23.89 %) were prepared, and AAC influence on the extruder-system parameter and physicochemical, cooking, and textural properties of FRK was investigated. The torque, die-pressure, length, redness, and cooking time increased with an increase in AAC and were in the range of 12.55-22.81 Nm, 58.31-88.96 bar, 4.58-5.09 mm, 0.35-1.15, and 6.1-11.2 min, respectively. The other parameters, such as the breadth, whiteness index, and cooking loss decreased with an increase in AAC. Except for cohesiveness, all other textural properties of cooked FRK increased with an increase in AAC. These correlations of the FRK properties with AAC were confirmed through multivariate analysis. SEM, XRD, FTIR, and rheology supported the observed AAC trends in FRK properties. SEM showed a reduction in pores and cracks with an increase in AAC. The XRD and FTIR showed an increase in crystallinity with an increase in AAC due to better gelatinization leading to rapid retrogradation. This leads to better physical, cooking, and textural properties of FRK.

Content validation of the defining characteristics of the nursing diagnosis "impaired swallowing" using the Delphi technique: A study with dysphagia nursing experts in Japan.

PURPOSE: Nurses' clinical reasoning skills regarding impaired swallowing can help prevent patient complications and maintain quality of life. Clinical reasoning skills need content-validated defining characteristics (DCs). We aimed to validate the content of these DCs for nursing diagnosis "impaired swallowing." METHODS: Content validation of the DCs was performed by 275 dysphagia nursing experts in Japan, using 3 rounds of the Delphi technique and Fehring's Diagnostic Content Validation (DCV) model. Three rounds of questionnaires on 84 DCs were completed via printed mail. FINDINGS: The valid response rates for each round were as follows: round 1, 90.2%; round 2, 77.8%; and round 3, 71.3%. Of the 84 DCs, 77 that met the consensus criteria were categorized as major (n = 18), minor (n = 45), and excluded (n = 14). There were four minor DCs other than the oral, pharyngeal, and esophageal phases. DCs listed from outside NANDA-I included 12 major, 16 minor, and 3 excluded characteristics. Of the NANDA-I DCs, 5 were no consensus and 11 were excluded. The total DCV score for the 63 major and minor DCs was 0.8. CONCLUSIONS: Our results recommend the addition of 28 DCs and the exclusion of 11 for the NANDA-I nursing diagnosis "impaired swallowing" (00103). Major DCs were prominent indicators of impaired swallowing and signs of aspiration or pharyngeal residuals. Minor DCs included not only the three phases but also other signs necessary for a comprehensive understanding of impaired swallowing. IMPLICATIONS FOR NURSING PRACTICE: This validation study strengthens the clinical usefulness of the DCs for impaired swallowing, which can improve nurses' clinical reasoning skills. Major and minor DCs can increase the awareness of impaired swallowing and enable accurate intervention, thereby preventing patient complications and maintaining quality of life.

Dietary probiotic and synbiotic supplementation starting from maternal gestation improves muscular lipid metabolism in offspring piglets by reshaping colonic microbiota and metabolites.

Probiotics and synbiotics have been intensively used in animal husbandry due to their advantageous roles in animals' health. However, there is a paucity of research on probiotic and synbiotic supplementation from maternal gestation to the postnatal growing phases of offspring piglets. Thus, we assessed the effects of dietary supplementation of these two additives to sows and offspring piglets on skeletal muscle and body metabolism, colonic microbiota composition, and metabolite profiles of offspring piglets. Pregnant Bama mini-pigs and their offspring piglets (after weaning) were fed either a basal diet or a basal diet supplemented with antibiotics, probiotics, or synbiotics. At 65, 95, and 125 days old, eight pigs per group were euthanized and sampled for analyses. Probiotics increased the intramuscular fat content in the psoas major muscle (PMM) at 95 days old, polyunsaturated fatty acid (PUFA) and n-3 PUFA levels in the longissimus dorsi muscle (LDM) at 65 days old, C16:1 level in the LDM at 125 days old, and upregulated ATGL, CPT-1, and HSL expressions in the PMM at 65 days old. Synbiotics increased the plasma HDL-C level at 65 days old and TC level at 65 and 125 days old and upregulated the CPT-1 expression in the PMM at 125 days old. In addition, probiotics and synbiotics increased the plasma levels of HDL-C at 65 days old, CHE at 95 days old, and LDL-C at 125 days old, while decreasing the C18:1n9t level in the PMM at 65 days old and the plasma levels of GLU, LDH, and TG at 95 days old. Microbiome analysis showed that probiotic and synbiotic supplementation increased colonic Actinobacteria, Firmicutes, Verrucomicrobia, Faecalibacterium, Pseudobutyrivibrio, and Turicibacter abundances. However, antibiotic supplementation decreased colonic Actinobacteria, Bacteroidetes, Prevotella, and Unclassified_Lachnospiraceae abundances. Furthermore, probiotic and synbiotic supplementation was associated with alterations in 8, 7, and 10 differential metabolites at three different age stages. Both microbiome and metabolome analyses showed that the differential metabolic pathways were associated with carbohydrate, amino acid, and lipid metabolism. However, antibiotic supplementation increased the C18:1n9t level in the PMM at 65 days old and xenobiotic biodegradation and metabolism at 125 days old. In conclusion, sow-offspring's diets supplemented with these two additives showed conducive effects on meat flavor, nutritional composition of skeletal muscles, and body metabolism, which may be associated with the reshaping of colonic microbiota and metabolites. However, antibiotic supplementation has negative effects on colonic microbiota composition and fatty acid composition in the PMM. IMPORTANCE: The integral sow-offspring probiotic and synbiotic supplementation improves the meat flavor and the fatty acid composition of the LDM to some extent. Sow-offspring probiotic and synbiotic supplementation increases the colonic beneficial bacteria (including Firmicutes, Verrucomicrobia, Actinobacteria, Faecalibacterium, Turicibacter, and Pseudobutyrivibrio) and alters the colonic metabolite profiles, such as guanidoacetic acid, beta-sitosterol, inosine, cellobiose, indole, and polyamine. Antibiotic supplementation in sow-offspring's diets decreases several beneficial bacteria (including Bacteroidetes, Actinobacteria, Unclassified_Lachnospiraceae, and Prevotella) and has a favorable effect on improving the fatty acid composition of the LDM to some extent, while presenting the opposite effect on the PMM.

Effect of the storage process on quality characteristics of hemp-enriched "tsoureki" a rich-dough baked Greek product.

The effects of the storage process on the quality characteristics of a hemp-enriched "tsoureki" (a rich-dough baked Greek product, rich-dough baked product [RDBP]) were investigated. The wheat flour was substituted with defatted hemp flour at selected ratios (0%-50% hemp:wheat flour). The baked products were stored at 25°C and at specific time intervals (0, 1, 4, 7, 10, and 14 days), and their properties were determined, including moisture content, water activity, structure, texture, color, total phenolic content (TPC), and antioxidant activity. Moreover, analyses of phenolic compounds were performed using quadrupole time of flight liquid chromatography-mass spectroscopy, identifying 14 compounds. Both the first-order kinetic model and modified Avrami equation, including the hemp-to-wheat ratio effect in the rate constant, well described the changes in the quality characteristics. The results showed that storage time and hemp incorporation significantly affected the quality of the product. Water activity decreased from 0.901 to 0.859, whereas moisture content decreased from 30.52%-32.33% (0 days) to 26.97%-27.02% w.b. (14 days) with storage time for all hemp additions. Hardness was greatly affected by hemp flour addition and approached 14.72 and 17.85 N after 14 days of storage for 30% and 50% substitutions, respectively. Springiness and cohesiveness decreased with hemp addition and storage time. The color difference of the hemp-enriched products compared to the control sample increased during storage. TPC increased due to the addition of hemp flour, whereas 14 compounds were identified. Based on property correlation, the hemp-enriched RDBP-tsoureki held its high-quality characteristics for 7 days of storage and contained a significant amount of bioactive compounds. PRACTICAL APPLICATION: Industrially produced, defatted hemp is a promising byproduct that can be used to nutritionally enhance baked goods. Modeling results can be used for the prediction of the properties that define product storage ability and also that the hemp-enriched, rich dough-baked Greek "tsoureki" could be produced while maintaining total phenolic content and antioxidant activity during 7 days of storage. These findings are expected to be used in the future in baked goods industry applications to produce goods with an improved nutritional profile.

A novel approach for identification of zoonotic trypanosome utilizing deep metric learning and vector database-based image retrieval system.

Trypanosomiasis, a significant health concern in South America, South Asia, and Southeast Asia, requires active surveys to effectively control the disease. To address this, we have developed a hybrid model that combines deep metric learning (DML) and image retrieval. This model is proficient at identifying Trypanosoma species in microscopic images of thin-blood film examinations. Utilizing the ResNet50 backbone neural network, a trained-model has demonstrated outstanding performance, achieving an accuracy exceeding 99.71 % and up to 96 % in recall. Acknowledging the necessity for automated tools in field scenarios, we demonstrated the potential of our model as an autonomous screening approach. This was achieved by using prevailing convolutional neural network (CNN) applications, and vector database based-images returned by the KNN algorithm. This achievement is primarily attributed to the implementation of the Triplet Margin Loss function as 98 % of precision. The robustness of the model demonstrated in five-fold cross-validation highlights the ResNet50 neural network, based on DML, as a state-of-the-art CNN model as AUC >98 %. The adoption of DML significantly improves the performance of the model, remaining unaffected by variations in the dataset and rendering it a useful tool for fieldwork studies. DML offers several advantages over conventional classification model to manage large-scale datasets with a high volume of classes, enhancing scalability. The model has the capacity to generalize to novel classes that were not encountered during training, proving particularly advantageous in scenarios where new classes may consistently emerge. It is also well suited for applications requiring precise recognition, especially in discriminating between closely related classes. Furthermore, the DML exhibits greater resilience to issues related to class imbalance, as it concentrates on learning distances or similarities, which are more tolerant to such imbalances. These contributions significantly make the effectiveness and practicality of DML model, particularly in in fieldwork research.

A kind of multi-dot ensemble regression AI detector for lubricating oil additive content based on lambert-beer law.

In this work, we propose a Multi-dot Ensemble Regression AI detector (MER) based on the Lambert-Beer law. We pre-trained a model using the infrared spectral data of target additives collected in advance to detect the target additives in unknown oil samples. The algorithm's feasibility was validated by assessing the content of additives in a series of simulated commercial oil samples that were not part of the training set. We established models for three common lubricating oil additives (anti-friction, anti-wear, and antioxidant agents), demonstrating their effectiveness in oil sample detection. Additionally, by comparing with other algorithms, we established the superiority of MER in small-sample learning scenarios.

Mast cell-derived interleukin-4 mediates activation of dendritic cell during toll-like receptor 2-mediated inflammation.

Introduction: During an innate inflammation, immune cells form distinct pro- and anti-inflammatory regions around pathogen-containing core-regions. Mast cells are localized in an anti-inflammatory microenvironment during the resolution of an innate inflammation, suggesting antiinflammatory roles of these cells. Methods: High-content imaging was used to investigated mast cell-dependent changes in the regional distribution of immune cells during an inflammation, induced by the toll-like receptor (TLR)-2 agonist zymosan. Results: The distance between the zymosan-containing core-region and the anti-inflammatory region, described by M2-like macrophages, increased in mast cell-deficient mice. Absence of mast cells abolished dendritic cell (DC) activation, as determined by CD86-expression and localized the DCs in greater distance to zymosan particles. The CD86- DCs had a higher expression of the pro-inflammatory interleukins (IL)-1ß and IL-12/23p40 as compared to activated CD86+ DCs. IL-4 administration restored CD86 expression, cytokine expression profile and localization of the DCs in mast cell-deficient mice. The IL-4 effects were mast cell-specific, since IL-4 reduction by eosinophil depletion did not affect activation of DCs. Discussion: We found that mast cells induce DC activation selectively at the site of inflammation and thereby determine their localization within the inflammation. Overall, mast cells have antiinflammatory functions in this inflammation model and limit the size of the pro-inflammatory region surrounding the zymosan-containing core region.

Loneliness and problematic pornography Use: What is the role of emotion regulation and interaction with content Creators?

Problematic pornography use is a growing area of interest necessitating a deeper understanding of its contributing factors. Loneliness and emotion regulation difficulties have been advanced as factors that may exacerbate or perpetuate PPU, however, to date, researchers typically consider these factors in isolation. In addition, the evolving landscape of problematic pornography is further shaped by the emergence of pornography content creators. This study explores the relationships between loneliness, emotion regulation difficulties and problematic pornography use and individuals' interactions with pornography content creators. Specifically, we examine whether emotion regulation difficulties mediate the relationship between loneliness and PPU and whether this mediation is contingent on interactions with content creators. A total of 213 adults (Mage = 35.57 years, SD = 16.90; 77.50 % men) participants completed an online questionnaire assessing PPU, emotion regulation difficulties and loneliness. Results revealed loneliness is associated with increased PPU and emotion regulation difficulties. Emotion regulation difficulties, in turn, relate to PPU. Though interaction with pornographic content creators was associated with reduced PPU, interacting with content creators did not moderate the effect of emotion regulation on the relationship between loneliness and PPU. Our findings support the hypothesised model, suggesting that emotion regulation difficulties mediate the relationship between loneliness and PPU. The identified mediating role of emotion regulation difficulties provides a foundation for further investigations into the underlying mechanisms connecting emotional well-being and problematic pornography use, offering potential directions for future research.

Rapport Building in Written Crisis Services: Qualitative Content Analysis.

BACKGROUND: Building therapeutic relationships and social presence are challenging in digital services and maybe even more difficult in written services. Despite these difficulties, in-person care may not be feasible or accessible in all situations. OBJECTIVE: This study aims to categorize crisis counselors' efforts to build rapport in written conversations by using deidentified conversation transcripts from the text and chat arms of the National Child Abuse Hotline. Using these categories, we identify the common characteristics of successful conversations. We defined success as conversations where help-seekers reported the hotline was a good way to seek help and that they were a lot more hopeful, a lot more informed, a lot more prepared to address the situation, and experiencing less stress, as reported by help-seekers. METHODS: The sample consisted of transcripts from 314 purposely selected conversations from of the 1153 text and chat conversations during July 2020. Hotline users answered a preconversation survey (ie, demographics) and a postconversation survey (ie, their perceptions of the conversation). We used qualitative content analysis to process the conversations. RESULTS: Active listening skills, including asking questions, paraphrasing, reflecting feelings, and interpreting situations, were commonly used by counselors. Validation, unconditional positive regard, and evaluation-based language, such as praise and apologies, were also often used. Compared with less successful conversations, successful conversations tended to include fewer statements that attend to the emotional dynamics. There were qualitative differences in how the counselors applied these approaches. Generally, crisis counselors in positive conversations tended to be more specific and tailor their comments to the situation. CONCLUSIONS: Building therapeutic relationships and social presence are essential to digital interventions involving mental health professionals. Prior research demonstrates that they can be challenging to develop in written conversations. Our work demonstrates characteristics associated with successful conversations that could be adopted in other written help-seeking interventions.

Improving stormwater infiltration and retention in compacted urban soils at impervious/pervious surface disconnections with biochar.

Urban development often results in compacted soils, impairing soil structure and reducing the infiltration and retention of stormwater runoff from impervious features. Biochar is a promising organic soil amendment to improve infiltration and retention of stormwater runoff. Soil at the disconnection between impervious and pervious surfaces represents a critical biochar application point for stormwater management from urban impervious features. This study tested the hypothesis that biochar would significantly improve water retention and transmission at four sites, where varying percentages (0%, 2%, and 4% w/w) of biochar were amended to soils between impervious pavement, and pervious grassed slopes. Field-saturated hydraulic conductivity (Ksat) and easily drainable water storage capacity were monitored at these sites for five months (two sites) and 15 months (two sites). At the end of the monitoring periods, the physical, chemical, and biological properties of each site's soil were assessed to understand the impact of biochar on soil aggregation, which is critical for improved soil structure and water infiltration. Results indicated that the field Ksat, drainable water storage capacity, and plant available water content (AWC) were 7.1 ± 3.6 SE, 2.0 ± 0.3 SE, and 2.1 ± 0.3 SE times higher in soils amended with 4% biochar, respectively, compared to the undisturbed soil. Factor analysis elucidated that biochar amendment increased the organic matter content, aggregate mean weight diameter, organo-mineral content, and fungal hyphal length while decreasing the bulk density. Across the 12 biochar/soil combinations, the multiple linear regression models derived from factor analysis described the changes in Ksat and AWC reasonably well with R2 values of 0.51 and 0.71, respectively. Using soil and biochar properties measured before biochar addition, two recent models, developed from laboratory investigations, were found helpful as screening tools to predict biochar's effect on Ksat and AWC at the four field sites. Overall, the findings illustrate that biochar amendment to compacted urban soils can significantly improve soil structure and hydraulic function at impervious/pervious surface disconnections, and screening models help to predict biochar's effectiveness in this context.

Whole genome resequencing identifies candidate genes and allelic variation in the MdNADP-ME promoter that regulate fruit malate and fructose contents in apple.

Soluble sugar and organic acids are key determinants of fruit organoleptic quality and directly affect the commodity value and economic returns of fruit crops. We conducted whole genome sequencing (WGS) of the apple varieties 'Gala' and 'Xiahongrou', along with their F1 hybrid, to construct a high-density bin map. Our quantitative genetic analysis pinpointed 53 quantitative trait loci (QTL)s related to 11 sugar and acid traits. We identified a candidate gene, MdNADP-ME, responsible for malate degradation, on a stable QTL of linkage group (LG) 15. Sequence analysis revealed an A/C SNP in the promoter region (MEp-799) that influences the binding of the transcription factor MdMYB2, impacting MdNADP-ME expression. In our study of various apple genotypes, this SNP was linked to malate and fructose levels. We also developed a dCAPS marker associated with fruit fructose content. These results substantiate the role of MdNADP-ME in maintaining the equilibrium of sugar and acid content in apple fruits.

Development, content validation and standardization of an adult patient prioritization tool for hospital clinical pharmacy services.

BACKGROUND: Patient prioritization is a effective strategy to identify high risk patients for targeted Clinical Pharmacy Service (CPS) in hospital pharmacy. However, there is a paucity of patient prioritization tool to use in clinical practice. OBJECTIVES: Describe the development, content validation and standardization of an adult patient prioritization tool for hospital CPS named, PrioFarClinH. METHODS: The tool was developed using a stepwise design multi: Scoping Review to identify prioritization criteria/sub-criteria; Delphi technique to obtain consensus under the identified criteria/sub-criteria; Survey with pharmacists evaluating applicability of the criteria/sub-criteria obtained from Delphi; Definition of criteria/sub-criteria to be included in PrioFarClinH attribution of scores. Content validation was performed by a panel of experts evaluating relevance, feasibility, clarity and adequacy of the score. Content Validity Index (CVI) was calculated. Standardization occurred through a retrospective observational study carried out at 24 and 72 h and median of the patient's hospital stay. An intragroup norm was performed, determining percentile ranks of the instrument's total scores. Patients with a P90 score were classified with a high level of prioritization for CPS. RESULTS: PrioFarClinH is divided into three sections, with prioritization criteria for health issues; therapeutic classes; laboratory parameters. It comprises 51 criteria with specific scores with simple total calculation. None of the criteria presented CVI <0.78, maintaining the items from the initial version of PrioFarClinH. The scores were adjusted per suggestions from the panel of judges. Data were collected from 393 patients. The P90 percentile in the three hospitalization stages (24 h, 72 h, and median) was found, respectively, in the following scores: 18.0, 20.0, and 22.6. CONCLUSIONS: PrioFarClinH is a comprehensive tool to target and to prioritize adults patients most likely to benefit from CPS. Evidence for adequate content validity was provided. However, further validation of this tool is necessary to establish tool performance.

Invariant Content Representation for Generalizable Medical Image Segmentation.

Domain generalization (DG) for medical image segmentation due to privacy preservation prefers learning from a single-source domain and expects good robustness on unseen target domains. To achieve this goal, previous methods mainly use data augmentation to expand the distribution of samples and learn invariant content from them. However, most of these methods commonly perform global augmentation, leading to limited augmented sample diversity. In addition, the style of the augmented image is more scattered than the source domain, which may cause the model to overfit the style of the source domain. To address the above issues, we propose an invariant content representation network (ICRN) to enhance the learning of invariant content and suppress the learning of variability styles. Specifically, we first design a gamma correction-based local style augmentation (LSA) to expand the distribution of samples by augmenting foreground and background styles, respectively. Then, based on the augmented samples, we introduce invariant content learning (ICL) to learn generalizable invariant content from both augmented and source-domain samples. Finally, we design domain-specific batch normalization (DSBN) based style adversarial learning (SAL) to suppress the learning of preferences for source-domain styles. Experimental results show that our proposed method improves by 8.74% and 11.33% in overall dice coefficient (Dice) and reduces 15.88 mm and 3.87 mm in overall average surface distance (ASD) on two publicly available cross-domain datasets, Fundus and Prostate, compared to the state-of-the-art DG methods. The code is available at https://github.com/ZMC-IIIM/ICRN-DG .

Beyond disclaimers: the need for a curation-based model of PubMed.

According to its own description, the biomedical meta-database PubMed exists "with the aim of improving health-both globally and personally." Unfortunately, PubMed contains an increasing amount of low-quality research that may detract from this goal. Currently, PubMed warns its users and protects itself from such problems with a disclaimer stating that the presence of any article, book, or document in PubMed does not imply an endorsement of, or concurrence with, its contents by the NLM, the National Institutes of Health (NIH), or the U.S. Federal Government. However, we are critical of a "disclaimer-only" stance and encourage PubMed to take further action against low-quality research being found and indexed in its database, and thus available for use. To address this problem, we offer two lines of reasoning to argue that PubMed should not function merely as a passive index of health-related research. Instead, we first argue that only trustworthy published research is able to further PubMed's goal of health improvement. Secondly, on the basis of surveys, we argue that researchers place a high level of trust in articles that are referenced in this meta-database. We cannot expect any one set of actors to ensure trustworthy content on PubMed, which requires collective responsibility among authors, peer reviewers, editors, and indexers alike. Instead, we propose a curation-based model that incorporates three mechanisms of collaborative content curation: open expert feedback on indexed content, journal auditing, and constant transparent reassessment of indexed entities.

Role of gas-particle conversion of ammonia in haze pollution under ammonia-rich environment in Northern China and prospects of effective emission reduction.

As an important precursor of secondary inorganic aerosols (SIAs), ammonia (NH3) plays a key role in fine particulate matter (PM2.5) formation. In order to investigate its impacts on haze formation in the North China Plain (NCP) during winter, NH3 concentrations were observed at a high-temporal resolution of 1 min by using the SP-DOAS in Tai'an from December 2021 to February 2022. During the observation period, the average NH3 concentration was 11.84 ± 5.9 ppbv, and it was determined as an ammonia-rich environment during different air quality conditions. Furthermore, the average concentrations of sulfate (SO42-), nitrate (NO3-) and ammonium (NH4+) were 9.54 ± 5.97 µg/m3, 19.09 ± 14.18 µg/m3 and 10.72 ± 6.53 µg/m3, respectively. Under the nitrate-dominated atmospheric environment, aerosol liquid water content (ALWC) was crucial for NH3 particle transformation during haze aggravation, and the gas-particle partitioning of ammonia played an important role in the SIAs formation. The reconstruction of the molecular composition further indicated that ammonium nitrate (NH4NO3) plays a dominant role in the increase of PM2.5 during haze events. Consequently, future efforts to mitigate fine particulate pollution in this region should focus on controlling NH4NO3 levels. In ammonia-rich environments, NO3- formation is more dependent on the concentration of nitric acid (HNO3). The sensitive analysis of TNO3 (HNO3 + NO3-) and NHX (NH3 + NH4+) reduction using the thermodynamic model suggested that the NO3- concentration decreases linearly with the reduction of TNO3. And the concentration of NO3- decreases rapidly only when NHX is reduced by 50-60 %. Reducing NOX emissions is the most effective way to alleviate nitrate pollution in this region.

Monitoring of Chlorophyll Content of Potato in Northern Shaanxi Based on Different Spectral Parameters.

Leaf chlorophyll content (LCC) is an important physiological index to evaluate the photosynthetic capacity and growth health of crops. In this investigation, the focus was placed on the chlorophyll content per unit of leaf area (LCCA) and the chlorophyll content per unit of fresh weight (LCCW) during the tuber formation phase of potatoes in Northern Shaanxi. Ground-based hyperspectral data were acquired for this purpose to formulate the vegetation index. The correlation coefficient method was used to obtain the "trilateral" parameters with the best correlation between potato LCCA and LCCW, empirical vegetation index, any two-band vegetation index constructed after 0-2 fractional differential transformation (step size 0.5), and the parameters with the highest correlation among the three spectral parameters, which were divided into four combinations as model inputs. The prediction models of potato LCCA and LCCW were constructed using the support vector machine (SVM), random forest (RF) and back propagation neural network (BPNN) algorithms. The results showed that, compared with the "trilateral" parameter and the empirical vegetation index, the spectral index constructed by the hyperspectral reflectance after differential transformation had a stronger correlation with potato LCCA and LCCW. Compared with no treatment, the correlation between spectral index and potato LCC and the prediction accuracy of the model showed a trend of decreasing after initial growth with the increase in differential order. The highest correlation index after 0-2 order differential treatment is DI, and the maximum correlation coefficients are 0.787, 0.798, 0.792, 0.788 and 0.756, respectively. The maximum value of the spectral index correlation coefficient after each order differential treatment corresponds to the red edge or near-infrared band. A comprehensive comparison shows that in the LCCA and LCCW estimation models, the RF model has the highest accuracy when combination 3 is used as the input variable. Therefore, it is more recommended to use the LCCA to estimate the chlorophyll content of crop leaves in the agricultural practices of the potato industry. The results of this study can enhance the scientific understanding and accurate simulation of potato canopy spectral information, provide a theoretical basis for the remote sensing inversion of crop growth, and promote the development of modern precision agriculture.

Effects of Lactone- and Ketone-Brassinosteroids of the 28-Homobrassinolide Series on Barley Plants under Water Deficit.

The aim of this work was to study the ability of 28-homobrassinolide (HBL) and 28-homocastasterone (HCS) to increase the resistance of barley (Hordeum vulgare L.) plants to drought and to alter their endogenous brassinosteroid status. Germinated barley seeds were treated with 0.1 nM HBL or HCS solutions for two hours. A water deficit was created by stopping the watering of 7-day-old plants for the next two weeks. Plants responded to drought through growth inhibition, impaired water status, increased lipid peroxidation, differential effects on antioxidant enzymes, intense proline accumulation, altered expression of genes involved in metabolism, and decreased endogenous contents of hormones (28-homobrassinolide, B-ketones, and B-lactones). Pretreatment of plants with HBL reduced the inhibitory effect of drought on fresh and dry biomass accumulation and relative water content, whereas HCS partially reversed the negative effect of drought on fresh biomass accumulation, reduced the intensity of lipid peroxidation, and increased the osmotic potential. Compared with drought stress alone, pretreatment of plants with HCS or HBL followed by drought increased superoxide dismutase activity sevenfold or threefold and catalase activity (by 36%). The short-term action of HBL and HCS in subsequent drought conditions partially restored the endogenous B-ketone and B-lactone contents. Thus, the steroidal phytohormones HBL and HCS increased barley plant resistance to subsequent drought, showing some specificity of action.