Main Indices Research Articles

Impact of climate change on vegetation growth trends in a citrus farmland in the south-eastern Sicily

Abstract. The environmental repercussions of climate change triggered substantial alterations in existing ecosystem balances leading to a gradual reduction in biodiversity and the increasing degradation of soil and the built environment. This has a direct effect on agricultural production in particular, leading to increased crop water requirements, the spread of new pests and pathogens that are difficult to manage, and, thus, a general reduction in productivity. Through the analysis of multispectral data remotely sensed with latest generation of optical sensors (RGB, thermal, NIR and multi-spectral cameras), it is possible to recognize the health status and growth stages of crops. In fact, in relation to the amount of radiation reflected in the different bands it is possible to calculate spectral indices, or vegetation indices. The main vegetative indices are NDVI, SAVI, MSAVI2, GNDVI and NDRE, which are calculated by differentially combining the ultraviolet spectrum, the visible range, and the near and mid-infrared band.In this paper the outcomes of a multi-year monitoring of a citrus grove field near Rosolini (Syracuse), in south-eastern Sicily-Italy, are presented. This monitoring activity was conducted to highlight areas of productive greenery under stress, on which to act as a priority with specific agronomic interventions. In parallel with the direct monitoring phases of the citrus grove, the trend of average monthly and annual temperature and precipitation values over the past 24 years was also studied to more specifically contextualize the possible presence of significant variations in climatic trends and relate them to the results returned by the calculation of the indices.

Research on high-quality factor sensing characteristics of all-dielectric nanopore array metasurface based on POA-DELM

Abstract Based on the optical properties of symmetric structures independent of each other in the orthogonal direction, an all-dielectric nano-square hole array metasurface which is symmetric along the diagonal is proposed. By changing the size of square nanopores, the symmetry of the periodic unit structure is broken and the double Fano resonance can be excited. The influence of each structural parameter on the sensing performance of the metasurface is analyzed respectively. As the main structural parameters and performance index, the metasurface height and the lengths of the main and sub-diagonal square nanoholes are selected as the input parameters, and the figure of merit (FOM) value is used as the output value. Then the nonlinear mapping relationship between the input and the output is established through deep extreme learning machine (DELM). Different optimization algorithms are used to optimize the weighted FOM values globally. The four evaluation indicators including root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and model fit (R-squared, R2) are used to assess the training effectiveness of the model. It is shown that the indexes are 0.9986, 0.9725, 3.1612 and 0.9733 respectively, and the FOM values of the dual Fano resonance after pelican optimization algorithm ( POA ) optimization are as high as 9.88 × 103 and 1.28 × 105, which demonstrate the effectiveness of POA-DELM proposed in this paper.

Improvability of Quality Main Indices of a Marl Soil using Endemic Microorganisms

Improvability of Quality Main Indices of a Marl Soil using Endemic Microorganisms

Multi-Objective Optimization and Design for Industrial Vinyl Chloride Reactor by Hybrid Model

The acetylene conversion rate and vinyl chloride production capacity are the main economic indexes for vinyl chloride synthesis, and the reaction temperature is an important operating parameter to prevent the Hg active component from being loss. These three factors have not been taken into consideration simultaneously in the traditional optimization process, making it difficult to achieve optimization targets perfectly for industrial application. To overcome this problem, an efficient strategy framework was proposed based on a hybrid model. Compared with conventional paradigms, the proposed framework could not only reduce computational expense but optimize these two economic indexes with a constrained reaction temperature simultaneously. In addition, a machine learning method was used to conduct a feature analysis, which can reveal the potential interaction between different variables so key variables of this reactor could be identified. To demonstrate and verify this framework, multi-objective optimization involving multiple variables with constrained conditions for the industrial reactor was conducted from design and operation perspectives, respectively. The proposed strategy could provide optimal operational direction for the industrial reactor from these design and operation aspects, which contribute to the sustainable and highly efficient process development in this field. For the first section of an industrial vinyl chloride reactor, this strategy could realize significant improvement in the acetylene conversion rate from 81.34% to over 95.00% and in the vinyl chloride production capacity from 2.60 to above 3.40 mol/h in the operation scenarios, which can meet production requirements. So, the second section of the traditional reactor system is not needed at all.

Combined effect of flocculation and ammonia stripping on different biogas slurries

The combined use of flocculation and ammonia stripping could be an efficient method for treating biogas slurry (BS). In this study, the operating parameters of ammonia stripping after flocculation were optimized. Swine manure biogas slurry (SMBS) and chicken manure biogas slurry (CMBS) were used as raw materials, and the flocculation efficiency and ammonia nitrogen removal rate (ANRR) were the main indices to evaluate the process performance. The bioflocculant (BF), polyaluminium chloride (PAC), ferric chloride (FC), and calcium oxide (CaO) were used as flocculants for the different biogas slurry flocculation. The results showed that CaO was more suitable for SMBS; the flocculation efficiency reached 56.63 % at the additive concentration of 5 g/L. Moreover, the ANRR was significantly improved by over 80 % after flocculation. However, the best flocculation potential on CMBS was achieved at an additive concentration of 0.3 g/L, and the flocculation efficiency reached 44.44 %. The ANRR reached 94.42 % at 45 ℃. This study provides a scientific basis and feasible scheme for treating different BS.

Genetically predicted plasma metabolites mediate the causal relationship between gut microbiota and primary immune thrombocytopenia (ITP).

Primary immune thrombocytopenia (ITP) is an immune-mediated hematologic disorder characterized by a reduction in platelet count, increasing the risk of bleeding. Recent studies have indicated a close association between alterations in gut microbiota and the development of ITP. However, the mechanisms by which gut microbiota influence the occurrence and progression of ITP through plasma metabolites remain poorly understood. Evidence suggests extensive interactions between gut microbiota and plasma metabolites, implying a potential role for gut microbiota in influencing ITP through alterations in plasma metabolites, which requires further investigation. In this study, summarized GWAS data (including 211 gut microbiota taxa, 1,400 plasma metabolites or ratios, and an ITP patient cohort) were retrieved from the MiBioGen and GWAS Catalog databases. Using a two-sample Mendelian randomization (MR) approach, we screened gut microbiota and plasma metabolites potentially causally related to ITP. We further identified plasma metabolites serving as mediators through which gut microbiota affect ITP and calculated the strength of the mediation effect. To ensure result stability, we primarily used the inverse variance weighted (IVW) method as the main judgment index. We also utilized MR Egger and inverse variance weighted methods to detect heterogeneity in the results, and employed MR-Egger and MR-PRESSO methods to assess the presence of pleiotropy. Though two-sample MR analysis, 8 gut microbiota taxa were found to have causal relationships with ITP. After excluding six plasma metabolites with pleiotropy, 39 plasma metabolites were found to be causally related to ITP (P < 0.05). Eleven plasma metabolites were identified as having causal relationships between gut microbiota and plasma metabolites. Finally, using the delta method, it was calculated that Sphingomyelin levels (8.0%, 95%CI: 0.9% to 11.5%, P = 0.047) and Glucose-to-mannose ratio (6.5%, 95%CI: 0.7% to 9.5%, P = 0.039) are intermediates for Intestinimonas influencing ITP, while Bilirubin (Z,Z) to etiocholanolone glucuronide ratio (5.6%, 95%CI: 4.7% to 6.9%, P = 0.043) is an intermediate for Senegalimassilia influencing ITP. Gut microbiota can influence the development of ITP through changes in plasma metabolites. Sphingomyelin levels, Glucose-to-mannose ratio, and Bilirubin (Z,Z) to etiocholanolone glucuronide ratio are newly discovered intermediates through which gut microbiota influence ITP, providing potential indicators and targets for clinical diagnosis and treatment. This study highlights the intricate relationship between gut microbiota and plasma metabolites in the context of ITP, suggesting new avenues for clinical diagnosis and treatment.

A comprehensive Beyond-GDP database to accelerate wellbeing, inclusion, and sustainability research

“Beyond-GDP” metrics are essential for understanding societal progress. Yet despite their importance, these metrics are scattered across various databases, hindering accessibility and interdisciplinary analysis. Addressing this gap, we present the ‘WISE database’ – the first extensive collection of important Beyond-GDP metrics organized by Wellbeing, Inclusion, and Sustainability (WISE) dimensions. The WISE database consolidates data from a variety of sources, including international institutions and academic publications. It encompasses over one million data points across 244 metrics, covering 218 countries and 61 country groupings, from specific social and environmental indicators to the main Beyond-GDP indexes, and is augmented by essential metadata. The data primarily spans from 1995 to 2015, with some metrics extending back to the 19th century. To improve accessibility and data interpretation, a user-friendly online visualization tool has been developed. The WISE database aims to foster a broader view of societal progress, facilitate research on synergies and trade-offs of wellbeing, inclusion, and sustainability, and provide a foundation for interdisciplinary research.

Comparison of the anesthetic effects of remimazolam tosilate and remimazolam besylate in daytime hysteroscopic surgery

ObjectiveThe purpose of this study is to observe whether there is a difference in the anesthetic effect of remimazolam tosilate and remimazolam besylate in daytime hysteroscopic surgery, so as to provide reference for clinical application.MethodsFifty patients, aged 18–65 years, ASA I-II, scheduled for hysteroscopy under total intravenous anesthesia were selected. The patients were randomly divided into two groups (n = 25): remimazolam tosilate group (group T) and remimazolam besylate group ( group R). The main observation index was the induction dose of remimazolam; secondary observation indicators were sleep time, anesthesia maintenance time, recovery time, induction maintenance dose of alfentanil, maintenance dose of remimazolam, and incidence of adverse events during anesthesia ( hypertension, hypotension, bradycardia, tachycardia).ResultsThere was no significant difference in anesthesia induction dose, recovery time, sleep time, anesthesia maintenance time, and incidence of adverse events during anesthesia ( body movement, cough, hypertension, hypotension, bradycardia, tachycardia) between the two groups (P > 0.05).ConclusionThere was no significant difference in the anesthetic effect of remimazolam tosilate and remimazolam besylate in daytime hysteroscopic surgery.Clinical trial RegistrationChinese Clinical Trial Registry, ChiCTR2400081688.

Statistical analysis of apparent morphology and characteristics of corroded rebars of concrete in the marine environment

The residual cross-sectional areas of corroded rebars and their uniformity are the main indexes to evaluate the safety and durability of concrete structures in the marine environment. To evaluate corrosion characteristics of naturally corroded rebars, nineteen corroded rebars were extracted from the prototype components of a high-pile wharf with 35 years of service. The apparent morphology characteristics of corroded rebars were obtained using 3D scanning. The results indicate that the corrosion is non-uniform along both the longitudinal and cross-sectional directions of the corroded rebars. In the marine environment, the residual cross-sectional areas of corroded rebars along the length adhere to a three-parameter Weibull distribution; however, no specific probability distribution model or clear correlation with the distribution pattern exists for rebars with varying corrosion degrees. The spatial heterogeneity factors of the rebars are characterized by a three-parameter Frechet distribution.

The functional activity of the brain in patients with occupational chronic mercury intoxication against background of the treatment of insomnia disorders

Introduction. In patients with chronic mercury intoxication, insomnia disorders are much more common than in the general population. Persistent emotional disorders in combination with severe sleep disturbances may contribute to the progression of cognitive dysfunction in patients in the late post-exposure period of chronic mercury intoxication. The purpose of the study was to analyze the trend in electroencephalography indices and study cognitive evoked potentials in patients with occupational chronic mercury intoxication to optimize the treatment of insomnia. Materials and methods. Two groups of 30 patients with occupational chronic mercury intoxication, who worked at the enterprises of Usolyekhimprom LLC and Sayanskhimplast OJSC, were examined. In the first group of patients received the first treatment option, the average age was 56±0.71 years, in the second group, cases received the second treatment regimen, were of 57.1±3 years. Before and after treatment, there were carried out neurophysiological studies including polysomnography, electroencephalography, and a study of cognitive evoked potentials P300. Results. After the implementation of the treatment regimen in the first group, positive changes in the main indices of polysomnography were revealed as follows: decrease in the time of falling asleep and time of wakefulness in the bed, increase in total sleep time and the representation of delta sleep, increase in the sleep efficiency index, etc., electroencephalography (decrease in the delta index – rhythm and an increase in the alpha rhythm index), and cognitive evoked potentials (decreased latency and increased P300 amplitude). In the second group, there were registered positive alterations only in three neurophysiological indices: a decrease in the latent period of the 1st stage of sleep, a decline in the delta rhythm index and a fall in P300 latency. Limitations. The results cannot be generalized to workers as the group included only men. Conclusion. According to neurophysiological studies, improvement in polysomnography parameters during the treatment of insomnia in patients in the late post-contact period of chronic mercury intoxication was accompanied by an improvement in concentration and an increase in the rate of psychomotor response.

A petrophysically driven seismic inversion method for the total organic carbon content of source rocks

Organic carbon content is the main index for evaluating organic matter abundance of source rocks, and it is still difficult to quantitatively predict total organic carbon (TOC) in source rocks based on seismic data. The study of seismic fluid identification driven by petrophysics can help to understand the fluid characteristics and distribution patterns of subsurface oil and gas reservoirs. First, this paper clarifies the sweet spot parameters (parameters characterizing hydrocarbon enrichment) and sensitive elastic parameters (a parameter characterizing the nature of an ideal elastic body) of source rocks through theoretical petrophysical modeling. Next, the paper establishes the relationship between sensitive elastic parameters and sweet spot parameters TOC and constructs a statistical petrophysical model that can characterize the relationship between the two on this basis. And then we construct the joint distribution of TOC and elastic impedance through the Bayesian theoretical framework to obtain the maximum posterior probability estimate as the final TOC inversion results of source rocks. Our method successfully predicts the spreading of high-quality source rocks in the Wen4 Section of Lufeng 13 Subsag, and the inversion results are within an uncertainty range of ±14 m for well data, which proves the reliability of the method. The prediction results show that the organic matter abundance of source rocks in the Wen4 Section is high, and the organic carbon content is generally higher than 2%, which provides a reliable basis for the further implementation of the resource scale of the depression and the clarification of the hydrocarbon-rich area, which provides technical support for the evaluation of the source rocks of the new depression in the new area.

Fatty Acid Content and Lipid Nutritional Indexes in the Antarctic Krill Euphausia superba Collected from Three Regions of the Atlantic Sector of Antarctica.

The total lipid (TL) and fatty acid (FA) contents in tissues and body segments were studied in adult Antarctic krill (Euphausia superba) caught in three regions of the Atlantic sector of Antarctica with different environmental conditions. Significant differences in lipid and FA status of the Antarctic krill tissues and body segments were observed in the regions. Main metabolic indices indicating quality of lipids showed that E.superba has a high nutritional value. In particular, lipids are highly unsaturated in the species and ratios of physiologically significant and essential FAs are favorable to human health. This was assumed to be a distinctive biochemical characteristic of the species. Data from the study can be used to form a scientifically based approach to further technological processing of raw krill and targeted extraction of certain substances and components of a lipid nature.

The analysis of vegetable and fruit export competitiveness of the Republic of Srpska

The aim of this research is an analysis of the Republic of Srpska's export competitiveness in vegetables and fruit on international markets. Two main evaluation indices were used, namely the trade competitiveness (TC) index and the revealed comparative advantage (RCA) index to measure and analyze the international position of vegetables and fruit during 2015 – 2022. Both indicators were calculated based on statistical data on foreign trade in vegetables and fruit between the Republic of Srpska and the world, EU, and CEFTA countries, and analyzed using descriptive statistics. Vegetables and fruit participate with 7.17% and 15.41% in the total export of the Republic of Srpska’s agri–food sector. Analysis of the export structure of this sector showed an average share of vegetables and fruit of 12.04% and 9.43% in the EU market, i.e., 1.63% and 9.65% in the CEFTA market. The results indicate strong export competitiveness of the Republic of Srpska in vegetables concerning the world and EU markets, but weak export competitiveness in relation with the CEFTA countries. The Republic of Srpska recorded strong export competitiveness in fruit on the world and CEFTA market, while poor export competitiveness in the EU market. Within these two product groups on the world market, cucumbers, apples, pears, and plums achieved strong export competitiveness. Cucumbers and plums were two leading products regarding strong export competitiveness On the EU market, while apples and pears were on the CEFTA market. Considering the favourable agroecological conditions for the production of vegetables and fruit, the Republic of Srpska should continue to promote production and foreign trade in these traditional products and improve their competitiveness on international markets.

Recycling phosphogypsum to produce artificial lightweight aggregates via stirring and pelleting all-in-one technique: Technical assessment and performance optimization

Currently, production of artificial lightweight aggregates (ALAs) is becoming one of the most promising approaches for solid wastes recycling via pelletization technique. In this study, an innovative stirring and pelleting all-in-one technique (S-pelleting) was employed to prepare the ALAs by using phosphogypsum (PG). The effects of different pelleting techniques on properties of the ALAs were investigated. Furthermore, the NaHCO3, Al2(SO4)3+CaCO3 (Al-Ca) and foamed particles (FP) were introduced as foaming agents to optimize the performance of the ALAs. The specific strength was used as the main assessment index for performance of the aggregates. The results indicated that the specific strength of the aggregates was improved to 10.96 MPa⋅cm3/g by S-pelleting, which was 60.7 % and 35.6 % higher than that of one-step pelleting or double-step pelleting technique. Compared to NaHCO3, the Al-Ca was more conducive to the specific strength development of the aggregates, and the FP addition could further improve the specific strength of the ALAs. When the concentration of Al-Ca was 7% and the mass fraction of FP was 10%, the ALAs with high specific strength of 9.6 MPa⋅cm3/g were obtained in this study. Moreover, the mineral composition, microstructure and pore structure of the ALAs were analyzed and the results reveled that the Al-Ca could promote to form more ettringite and reduce the proportion of harmful pores in the aggregates, which was responsible for the improvement in specific strength. The FP acted as a lightweight skeleton supported inside the aggregates and the well bonded ITZ between FP and the matrix could further improve the specific strength of the ALAs. Finally, the durability and environmental impact of the ALAs were evaluated acceptable. Overall, this study not only provided a green approach for PG recycling, but also presented a new technical scheme for more efficient production of ALAs.

Study on stability of rose anthocyanin extracts and physicochemical properties of complex with whey protein isolate after spray drying.

Pingyin rose is an edible flower rich in anthocyanins. In this study, antioxidant capacity and color were used as the main evaluation indexes to investigate the effects of common physical and chemical factors on the stability of rose anthocyanin extracts (RAEs). In addition, the physicochemical properties of the whey protein isolate (WPI)-RAEs complex after spray drying were studied. Vitamin C, temperature, and some metal ions can cause different degrees of discoloration of RAEs solution. More importantly, heat treatment, as well as most metal ions and sugars, had no significant effect on the antioxidant capacity of RAEs solution (p>0.05). Moreover, compared to spray-dried pure WPI, the WPI-RAEs powder was delicate and uniform, and had higher particle size, bulk density, moisture activity, and better gel properties. The release rate of all WPI-RAEs sol/gel to RAEs reached about 89% in the intestinal digestion stage, but the WPI-RAEs interaction reduced the digestibility of protein in the intestinal digestion stage. We hope that this study can provide a theoretical basis for the development and utilization of WPI-RAEs as food ingredients.

Determination of Critical Crop Water Stress Index of Tea under Drought Stress Based on the Intercellular CO2 Concentration

Climatic changes have caused seasonal drought to occur frequently in tea fields of low-mountain and hill regions over the past decades. This leads to huge losses in the quality and yields of famous tea, which restricts the economic development of the tea industry. It is crucial to implement suitable irrigation scheduling. The crop water stress index (CWSI) is the main index to assess the water status of the crop. When the crop suffers irreversible drought stress, its critical water status cannot be easily evaluated using the CWSI. The change from stomatal limitations (SLs) to non-stomatal limitations (NSLs) of photosynthesis is vital for accurately recognizing crop drought stress. Thus, the objective of this research is to determine the critical crop water stress index of tea based on intercellular CO2 concentration (Ci) dynamic responses to drought stress. During two sensitive periods of water stress (famous tea harvest season and summer drought season, which are from March to April and July to August, respectively), the dynamic changes in the CWSI in tea were calculated and analyzed based on the CWSI theoretical model. The upper and lower baselines were determined on a daily basis and during a certain period. A critical value of the CWSI represents irreversible drought damage. This was determined by the characteristic response of the Ci of tea leaves during extreme drought stress. The results showed the following: (1) during the famous tea harvest season and summer drought season, the daily variation in CWSI was similar. During a certain period, the former maintained a stable fluctuation, while the latter increased in fluctuation. (2) The Ci showed a trend of fluctuating downward to a low point and then upward during extreme drought stress. After reaching the low point, it quickly increased in the former and stabilized for a day in the latter. When the Ci reached the low point, the upper benchmark of this critical point was 13.9 μmol·mol−1, the lower benchmark was 3.4, and the CWSI was 0.27. This critical CWSI could be used as an irrigation threshold point to ensure normal production for tea fields.

Perturbational complexity index in assessing responsiveness to rTMS treatment in patients with disorders of consciousness: a cross-over randomized controlled trial study

BackgroundDisorders of Consciousness (DoC) caused by severe brain injuries represent a challenging clinical entity, which is easy to misdiagnosis and lacks effective treatment options. Repetitive Transcranial Magnetic Stimulation (rTMS) is a non-invasive neuroelectric stimulation method that shows promise in improving consciousness for DoC, especially in minimally conscious state (MCS). However, there is little evidence of its effectiveness, especially in RCT studies.MethodsTwenty MCS patients participated in a double-blind, randomized, crossover, sham-controlled clinical study to evaluate the safety and efficacy of rTMS for MCS. Subjects were randomized into two groups: one group received rTMS-active for 10 consecutive days (n = 10), and the other group received rTMS-sham for 10 consecutive days (n = 10). After a 10-day washout period, the two groups were crossed over and received the opposite treatment. the rTMS protocol consisted of 2,000 pulses per day in the left dorsolateral prefrontal cortex (L-DLPFC), sent at 10 Hz. The stimulation intensity was 90% of the resting motor threshold. Coma Recovery Scale Revised (CRS-R), the main evaluation index, was evaluated before and after each phase in a double-blind manner. Meanwhile RS-EEG and TMS-EEG data were acquired and relative alpha power (RAP), and perturbational complexity index based on state transitions (PCIst) were caculated.ResultsOne-way ANOVA revealed significantly higher scores in rTMS-active treatment compared to rTMS-sham across various measures, including CRS-R total score, RAP, PCIst (all P < 0.05). Among the 20 MCS patients, 7 (35%) were identified as responders following rTMS treatment. Compared to rTMS-sham, responder scores for CRS-R, RAP, and PCIst (all P < 0.05) were significantly elevated after rTMS-active treatment. Conversely, there was no significant difference observed in non-responders. Furthermore, post-hoc analysis revealed that baseline PCIst was significantly higher in responders than non-responders. Upon a 6-month follow-up, CRS-R scores significantly increased in all 20 patients (P = 0.026). However, the responder group exhibited a more favorable prognosis compared to the non-responder group (P = 0.031).ConclusionsApplying 10 Hz rTMS to L-DLPFC significantly increased consciousness level in MCS patients. PCIst is a neurophysiological index that has the potential to evaluate and predict therapeutic efficacy.Trial registrationwww.ClinicalTrials.gov, identifier: NCT05187000.

Determination of Drying Characteristics and Physicochemical Properties of Mint (Mentha spicata L.) Leaves Dried in Refractance Window.

Drying is one of the most common and effective techniques for preserving the quantitative and qualitative characteristics of medicinal plants in the post-harvest phase. Therefore, in this research, the effect of the new refractance window (RW) technology on the kinetics, thermodynamics, greenhouse gasses, color indices, bioactive properties, and percentage of mint leaf essential oil was investigated in five different water temperatures in the form of a completely randomized design. This process was modeled by the methods of mathematical models and artificial neural networks (ANNs) with inputs (drying time and water temperature) and an output (moisture ratio). The results showed that with the increase in temperature, the rate of moisture removal from the samples increased and as a result, the drying time, specific energy consumption, CO2, NOx, enthalpy, and entropy decreased significantly (p < 0.05). In addition, the drying water temperature had a significant effect on the rehydration ratio, color indices, bioactive properties, and essential oil percentage of the samples (p < 0.05). The highest value of rehydration ratio was obtained at 80 °C. By increasing temperature, the main color indices such as b*, a*, L*, and Chroma decreased significantly compared to the control (p < 0.05). However, with the increase in temperature, the overall color changes (ΔE) and L* first had a decreasing trend and then an increasing trend, and this trend was the opposite for the rest of the indicators. The application of drying water temperature from 50 to 70 °C increased antioxidant, phenol content, and flavonoid content, and higher drying temperatures led to a significant decrease in these parameters (p < 0.05). On the other hand, the efficiency of the essential oil of the samples was in the range of 0.82 to 2.01%, and the highest value was obtained at the water temperature of 80 °C. Based on the analysis performed on the modeled data, a perceptron artificial neural network with 2-15-14-1 structure with explanation coefficient (0.9999) and mean square error (8.77 × 10-7) performs better than the mathematical methods for predicting the moisture ratio of mint leaves.

Machine-learning-derived online prediction models of outcomes for patients with cholelithiasis-induced acute cholangitis: development and validation in two retrospective cohorts

Cholelithiasis-induced acute cholangitis (CIAC) is an acute inflammatory disease with poor prognosis. This study aimed to create machine-learning (ML) models to predict the outcomes of patients with CIAC. In this retrospective cohort and ML study, patients who met the both diagnosis of 'cholangitis' and 'calculus of gallbladder or bile duct' according to the International Classification of Disease (ICD) 9th revision, or met the diagnosis of 'calculus of bile duct with acute cholangitis with or without obstruction' according to the ICD 10th revision during a single hospitalization were included from the Medical Information Mart for Intensive Care database, which records patient admissions to Beth Israel Deaconess Medical Center, MA, USA, spanning June 1, 2001 to November 16, 2022. Patients who were neither admitted in an emergency department nor underwent biliary drainage within 24h after admission, had an age of less than 18, or lost over 20% of the information were excluded. Nine ML methods, including the Logistic Regression, eXtreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine, Adaptive Boosting, Decision Tree, Gradient Boosting Decision Tree, Gaussian Naive Bayes, Multi-Layer Perceptron, and Support Vector Machine were applied for prediction of in-hospital mortality, re-admission within 30 days after discharge, and mortality within 180 days after discharge. Patients from Zhongda Hospital affiliated to Southeast University in China between January 1, 2019 and July 30, 2023 were enrolled as an external validation set. The area under the receiver operating characteristic curve (AUROC) was the main index for model performance assessment. A total of 1156 patients were included to construct models. We performed stratified analyses on all patients, patients admitted to the intensive care unit (ICU) and those who underwent biliary drainage during ICU treatment. 13-16 features were selected from 186 variables for model training. The XGBoost method demonstrated the most optimal predictive efficacy, as evidenced by training set AUROC of 0.996 (95% CI NaN-NaN) for in-hospital mortality, 0.886 (0.862-0.910) for re-admission within 30 days after discharge, and 0.988 (0.982-0.995) for mortality within 180 days after discharge in all patients, 0.998 (NaN-NaN), 0.933 (0.909-0.957), and 0.988 (0.983-0.993) in patients admitted to the ICU, 0.987 (0.970-0.999), 0.908 (0.873-0.942), and 0.982 (0.971-0.993) in patients underwent biliary drainage during ICU treatment, respectively. Meanwhile, in the internal validation set, the AUROC reached 0.967 (0.933-0.998) for in-hospital mortality, 0.589 (0.502-0.677) for re-admission within 30 days after discharge, and 0.857 (0.782-0.933) for mortality within 180 days after discharge in all patients, 0.963 (NaN-NaN), 0.668 (0.486-0.851), and 0.864 (0.757-0.970) in patients admitted to the ICU, 0.961 (0.922-0.997), 0.669 (0.540-0.799), and 0.828 (0.730-0.925) in patients underwent biliary drainage during ICU treatment, respectively. The AUROC values of external validation set consisting of 61 patients were 0.741 (0.725-0.763), 0.812 (0.798-0.824), and 0.848 (0.841-0.859), respectively. The XGBoost models could be promising tools to predict outcomes in patients with CIAC, and had good clinical applicability. Multi-center validation with a larger sample size is warranted. The Technological Development Program of Nanjing Healthy Commission, and Zhongda Hospital Affiliated to Southeast University, Jiangsu Province High-Level Hospital Construction Funds.

Working Memory Workload When Making Complex Decisions: A Behavioral and EEG Study.

Working memory (WM) is crucial for adequate performance execution in effective decision-making, enabling individuals to identify patterns and link information by focusing on current and past situations. This work explored behavioral and electrophysiological (EEG) WM correlates through a novel decision-making task, based on real-life situations, assessing WM workload related to contextual variables. A total of 24 participants performed three task phases (encoding, retrieval, and metacognition) while their EEG activity (delta, theta, alpha, and beta frequency bands) was continuously recorded. From the three phases, three main behavioral indices were computed: Efficiency in complex Decision-making, Tolerance of Decisional Complexity, and Metacognition of Difficulties. Results showed the central role of alpha and beta bands during encoding and retrieval: decreased alpha/beta activity in temporoparietal areas during encoding might indicate activation of regions related to verbal WM performance and a load-related effect, while decreased alpha activity in the same areas and increased beta activity over posterior areas during retrieval might indicate, respectively, active information processing and focused attention. Evidence from correlational analysis between the three indices and EEG bands are also discussed. Integration of behavioral and metacognitive data gathered through this novel task and their interrelation with EEG correlates during task performance proves useful to assess WM workload during complex managerial decision-making.