An entirely new approach based on remote sensing data to calculate the nitrogen nutrition index of winter wheat

The nitrogen nutrition index(NNI)is a reliable indicator for diagnosing crop nitrogen(N)status.However,there is currently no specific vegetation index for the NNI inversion across multiple growth periods.To overcome the limitations of the traditional direct NNI inversion method(NNI_(T1))of the vegetation index and traditional indirect NNI inversion method(NNI_(T2))by inverting intermediate variables including the aboveground dry biomass(AGB)and plant N concentration(PNC),this study proposed a new NNI remote sensing index(NNI_(RS)).A remote-sensing-based critical N dilution curve(Nc_(_RS))was set up directly from two vegetation indices and then used to calculate NNI_(RS).Field data including AGB,PNC,and canopy hyperspectral data were collected over four growing seasons(2012–2013(Exp.1),2013–2014(Exp.2),2014–2015(Exp.3),2015–2016(Exp.4))in Beijing,China.All experimental datasets were cross-validated to each of the NNI models(NNI_(T1),NNI_(T2)and NNI_(RS)).The results showed that:(1)the NNI_(RS)models were represented by the standardized leaf area index determining index(sLAIDI)and the red-edge chlorophyll index(CI_(red edge))in the form of NNI_(RS)=CI_(red edge)/(a×sLAIDI~b),where"a"equals 2.06,2.10,2.08 and 2.02 and"b"equals 0.66,0.73,0.67 and 0.62 when the modeling set data came from Exp.1/2/4,Exp.1/2/3,Exp.1/3/4,and Exp.2/3/4,respectively;(2)the NNI_(RS)models achieved better performance than the other two NNI revised methods,and the ranges of R2 and RMSE were 0.50–0.82 and 0.12–0.14,respectively;(3)when the remaining data were used for verification,the NNI_(RS)models also showed good stability,with RMSE values of 0.09,0.18,0.13 and 0.10,respectively.Therefore,it is concluded that the NNI_(RS)method is promising for the remote assessment of crop N status.

Use of the Crohn's disease activity index in clinical trials of biological agents

The Crohn＇s disease activity index （CDAI） has been commonly used to assess the effects of treatment with different agents in Crohn＇s disease （CD）. However, these studies may be compromised, if the results compared to a placebo or standard therapy group （in the absence of a placebo） substantially differ from the expected response. In addition, significant concerns have been raised regarding the reliability and validity of the CDAI. Reproducibility of the CDAI may be limited as significant inter-observer error has been recorded, even if measurements are done by experienced clinicians with expertise in the diagnosis and treatment of CD. Finally, many CDAI endpoints are open to subjective interpretation and have the potential for manipulation. This is worrisome as there is the potential for significant financial gain, if the results of a clinical trial appear to provide a positive result. Physicians caring for patients should be concerned about the positive results in clinical trials that are sponsored by industry, even if the trials involve respected centers and the results appear in highly ranked medical journals.

A Discrimination Index Based on Jain's Fairness Index to Differentiate Researchers with Identical H-index Values

Purpose:This paper proposes a discrimination index method based on the Jain’s fairness index to distinguish researchers with the same H-index.Design/methodology/approach:A validity test is used to measure the correlation of D-offset with the parameters,i.e.H-index,the number of cited papers,the total number of citations,the number of indexed papers,and the number of uncited papers.The correlation test is based on the Saphiro-Wilk method and Pearson’s product-moment correlation.Findings:The result from the discrimination index calculation is a two-digit decimal value called the discrimination-offset(D-offset),with a range of D-offset from 0.00 to 0.99.The result of the correlation value between the D-offset and the number of uncited papers is 0.35,D-offset with the number of indexed papers is 0.24,and the number of cited papers is 0.27.The test provides the result that it is very unlikely that there exists no relationship between the parameters.Practical implications:For this reason,D-offset is proposed as an additional parameter for H-index to differentiate researchers with the same H-index.The H-index for researchers can be written with the format of“H-index:D-offset”.Originality/value:D-offset is worthy to be considered as a complement value to add the H-index value.If the D-offset is added in the H-index value,the H-index will have more discrimination power to differentiate the rank of the researchers who have the same H-index.

Assessing disease activity using the pediatric Crohn’s disease activity index:Can we use subjective or objective parameters alone?

BACKGROUND The pediatric Crohn’s disease activity index(PCDAI)is used as a standard tool to assess disease activity in clinical trials for pediatric Crohn’s disease.AIM To examine which items on the PCDAI drive assessment of disease activity,and how subgroups of subjective and objective items reflect change in disease state over time.METHODS Selective raw data from three prospectively collected datasets were combined,including 703 children with full PCDAI data at baseline,at 3-mo(Q1,n=670),and 1-year(Q4,n=474).Change in individual PCDAI scores from baseline to Q1 and to Q4 were examined using the non-weighted PCDAI.RESULTS Abdominal pain,well-being,weight,and stooling had the highest change scores over time.Objective indicators including albumin,abdominal exam,and height velocity followed.Change scores for well-being and abdominal exam did not explain significant variance at Q1 but were significant predictors at Q4(P<0.001 and P<0.05).Subjective and objective subgroups of items predicted less variance(18%and 22%)on total PCDAI scores at Q1 and Q4 compared to the full PCDAI,or a composite scale(both 32%)containing significant predictors.CONCLUSION Although subjective items on the PCDAI change the most over time,the full PCDAI or a smaller composite of items including a combination of subjective and objective components classifies disease activity better than a subgroup of either subjective or objective items alone.Reliance on subjective or objective items as stand-alone proxies for disease activity measurement could result in misclassification of disease state.

Onodera's Prognostic Nutritional Index is a novel and useful prognostic marker for gastrointestinal stromal tumors

BACKGROUND Immunoinflammatory markers such as the peripheral blood neutrophil-tolymphocyte ratio(NLR)and the platelet-to-lymphocyte ratio(PLR)have gained considerable attention as prognostic markers in gastrointestinal stromal tumors(GISTs).AIM To assess the prognostic value of Onodera’s Prognostic Nutritional Index(OPNI)for GISTs.METHODS All patients who had undergone surgical resection for a primary,localized GIST from 2009 to 2016 at our cancer center were initially and retrospectively identified.Recurrence-free survival(RFS)was calculated by the Kaplan-Meier method and compared by the log-rank test.We used multivariate Cox proportional hazard regression models to identify associations with outcome variables.RESULTS A total of 235 GISTs were identified and included for analysis under our inclusion criteria.Univariate and multivariate analyses both identified the OPNI as an independent prognostic marker,and the OPNI was associated with the primary site,tumor size,mitotic index,tumor rupture,necrosis,and modified NIH risk classification.Low OPNI(<51.30;hazard ratio=5.852;95% confidence interval:1.072–31.964;P=0.0414)was associated with worse RFS.The 2-and 5-year RFS rates of the patients with a low OPNI were 92.83% and 76.22%,respectively,whereas 100% and 98.41% were achieved by the patients with a high OPNI.CONCLUSION The preoperative OPNI is a novel and useful prognostic marker for GISTs.

Relationship of Parental Indica-Japonica Indexes with Yield and Grain Quality Traits of Japonica Hybrid Rice in Northern China

Taking the main parents （10 male sterile lines and 10 restorer lines） and their 100 combinations of japonica hybrid rice in northern China as materials, the relationships of parental indica-japonica indexes determined by the methods of the Cheng’s index as well as simple sequence repeat （SSR） markers with yield and grain quality traits of hybrid rice were studied. For the parents, the Cheng’s index （Chi） ranged from 13.5 to 19.3 and the indica index in SSR markers （ADi） were from 0.12 to 0.38. The classification of parents by Chi was not completely consistent with that by ADi. The Chi of male parent was more closely related to hybrid traits than that of female parent, as contrasted to ADi. At the same time, the difference between parents （PD） in Chi was more closely related to hybrid traits than that in ADi. The indica-japonica indexes of parents and their difference between parents appeared quadratic relationship to hybrid traits with the critical extremum. The directions of the correlation of indica-japonica indexes of parents and their differences with hybrid yield traits were on the opposition to those with hybrid grain quality traits. Therefore, the female parent should match the male parent moderately in indica-japonica index to obtain the optimum of hybrid traits, high yield as well as good quality.

Magnetic resonance imaging and Crohn's disease endoscopic index of severity: Correlations and concordance

AIM To examine the correlation between magnetic resonance imaging(MRI) and endoscopic index of severity(CDEIS) in patients with Crohn's disease(CD).METHODS This was a retrospective study of 104 patients with CD that were treated at the Ruijin Hospital between March 2015 and May 2016. Among them, 61 patients with active CD were evaluated before/after treatment. MRI and endoscopy were performed within 7 d. CDEIS was evaluated. MRI parameters included Ma RIA scores, total relative contrast enhancement(tRCE), arterialRCE(aRCE), portalRCE(pRCE), delay phaseRCE(dRCE), and apparent diffusion coefficient. The correlation and concordance between multiple MRI findings and CDEIS changes before and after CD treatment were examined.RESULTS Among the 104 patients, 61 patients were classified as active CD and 43 patients as inactive CD. Gender, age, disease duration, and disease location were not significantly different between the two groups(all P > 0.05). CRP levels were higher in the active group than in the inactive group(25.12 ± 4.12 vs 5.14 ± 0.98 mg/L, P < 0.001). Before treatment, the correlations between CDEIS and MaRIAs in all patients were r = 0.772 for tRCE, r = 0.754 for aRCE, r = 0.738 for pRCE, and r = 0.712 for dRCE(all MaRIAs, P < 0.001), followed by MRI single indexes. Among the active CD patients, 44 cases were remitted to inactive CD after treatment. The correlations between CDEIS and MaRIAs were r = 0.712 for aRCE, r = 0.705 for tRCE, r = 0.685 for pRCE, and r = 0.634 for dRCE(all MaRIAs, P < 0.001).CONCLUSION Arterial Ma RIA should be an indicator for CD follow-up and dynamic assessment. CD treatment assessment was not completely concordant between CDEIS and MRI.

Weighted Gini-Simpson Quadratic Index of Biodiversity for Interdependent Species

The weighted Gini-Simpson quadratic index is the simplest measure of biodiversity which takes into account the relative abundance of species and some weights assigned to the species. These weights could be assigned based on factors such as the phylogenetic distance between species, or their relative conservation values, or even the species richness or vulnerability of the habitats where these species live. In the vast majority of cases where the biodiversity is measured the species are supposed to be independent, which means that the relative proportion of a pair of species is the product of the relative proportions of the component species making up the respective pair. In the first section of the paper, the main versions of the weighted Gini-Simpson index of biodiversity for the pairs and triads of independent species are presented. In the second section of the paper, the weighted Gini-Simpson quadratic index is calculated for the general case when the species are interdependent. In this instance, the weights reflect the conservation values of the species and the distribution pattern variability of the subsets of species in the respective habitat induced by the inter-dependence between species. The third section contains a numerical example.

The weighted quadratic index of biodiversity for pairs of species: a generalization of Rao’s index

The distribution of biodiversity at multiple sites of a region has been traditionally investigated through the additive partitioning of the regional biodiversity, called γ-diversity, into the average within-site biodiversity or α-diversity, and the biodiversity among sites, or β-diversity. The standard additive partitioning of diversity requires the use of a measure of diversity which is a concave function of the relative abundance of species, like the Shannon entropy or the Gini- Simpson index, for instance. When a phylogenetic distance between species is also taken into account, Rao’s quadratic index has been used as a measure of dissimilarity. Rao’s index, however, is not a concave function of the distribution of relative abundance of either individual species or pairs of species and, consequently, only some nonstandard additive partitionings of diversity have been given using this index. The objective of this paper is to show that the weighted quadratic index of biodiversity, a generalization of the weighted Gini-Simpson index to the pairs of species, is a concave function of the joint distribution of the relative abundance of pairs of species and, therefore, may be used in the standard additive partitioning of diversity instead of Rao’s index. The replication property of this new measure is also discussed.

Joint Detection of Serum Vitamin D,Body Mass Index,and Tumor Necrosis Factor Alpha for the Diagnosis of Crohn’s Disease

Objective Vitamin D(VD)deficiency was reported to contribute to the progression of Crohn’s disease(CD)and affect the prognosis of CD patients.This study investigated the role of serum VD,body mass index(BMI),and tumor necrosis factor alpha(TNF-α)in the diagnosis of Crohn’s disease.Methods CD patients(n=76)and healthy subjects(n=76)were enrolled between May 2019 and December 2020.The serum 25-hydroxyvitamin D[25(OH)D]levels,BMI,and TNF-αlevels,together with other biochemical parameters,were assessed before treatment.The diagnostic efficacy of the single and joint detection of serum 25(OH)D,BMI,and TNF-αwas determined using receiver operating characteristic(ROC)curves.Results The levels of 25(OH)D,BMI,and nutritional indicators,including hemoglobin,total protein,albumin,and high-density lipoprotein cholesterol,were much lower,and the TNF-αlevels were much higher in the CD patients than in the healthy subjects(P<0.05 for all).The areas under the ROC curve for the single detection of 25(OH)D,BMI,and TNF-αwere 0.887,0.896,and 0.838,respectively,with the optimal cutoff values being 20.64 ng/mL,19.77 kg/m^(2),and 6.85 fmol/mL,respectively.The diagnostic efficacy of the joint detection of 25(OH)D,BMI,and TNF-αwas the highest,with an area under the ROC curve of 0.988(95%CI:0.968–1.000).Conclusion The joint detection of 25(OH)D,TNF-α,and BMI showed high sensitivity,specificity,and accuracy in CD diagnosis;thus,it would be effective for the diagnosis of CD in clinical practice.

Assessment of a Precaution Index for Environmental Evaluation: An Example of Application to the Cow’s Milk Production

The paper presents a Precaution Index (P) developed to create an instrument to assess the potential risk related to the presence of pollution sources next to milk production farms. The methodology starts from the inventory and geo-referencing of all pollution sources in an area, with the help of the multi-criteria decision analysis. Results are represented in a map of P, which highlights which areas are most at risk and need monitoring, and which pollutants may be involved. This may help in the early identification of emerging hazards to food safety. P was calculated for the milk production in an Italian region. Results show that 97% of the area is in a condition of minimum precaution that would be needed in controlling the safety of dairy products.

A Novel Hybrid Method for Measuring the Spatial Autocorrelation of Vehicular Crashes: Combining Moran’s Index and Getis-Ord G_i<sup style='margin-left:-7px;'>*</sup>Statistic

Spatial autocorrelation is a measure of the correlation of an observation with other observations through space. Most statistical analyses are based on the assumption that the values of observations are independent of one another. Spatial autocorrelation violates this assumption, because observations at near-by locations are related to each other, and hence, the consideration of spatial autocorrelations has been gaining attention in crash data modeling in recent years, and research have shown that ignoring this factor may lead to a biased estimation of the modeling parameters. This paper examines two spatial autocorrelation indices: Moran’s Index;and Getis-Ord Gi* statistic to measure the spatial autocorrelation of vehicle crashes occurred in Boone County roads in the state of Missouri, USA for the years 2013-2015. Since each index can identify different clustering patterns of crashes, therefore this paper introduces a new hybrid method to identify the crash clustering patterns by combining both Moran’s Index and Gi*?statistic. Results show that the new method can effectively improve the number, extent, and type of crash clustering along roadways.

Influence of Coordinate Field Index on Upconversion Luminescence in Er ^(3+) Doped Tellurite Glasses

The upconversion luminescence in Er 3+ doped tellurite glasses (MKT: TeO_2-MgO-K_2O) were performed. Two green emission bands at 521 and 550 nm, corresponding to the 2H_ 11/2→4I_ 15/2 and 4S_ 3/2→4I_ 15/2 transitions, respectively, were observed. Coordinate field index, which was proposed by deducing from Pauling′s rules on the basis of Zachariasen′s random network theory, can be used to rationalize the remarkable variation in the intensity of upconversion luminescence.

Association between childhood obesity and gut microbiota:16S rRNA gene sequencing-based cohort study

BACKGROUND This study aimed to identify characteristic gut genera in obese and normal-weight children(8-12 years old)using 16S rDNA sequencing.The research aimed to provide insights for mechanistic studies and prevention strategies for childhood obesity.Thirty normal-weight and thirty age-and sex-matched obese children were included.Questionnaires and body measurements were collected,and fecal samples underwent 16S rDNA sequencing.Significant differences in body mass index(BMI)and body-fat percentage were observed between the groups.Analysis of gut microbiota diversity revealed lowerα-diversity in obese children.Differences in gut microbiota composition were found between the two groups.Prevotella and Firmicutes were more abundant in the obese group,while Bacteroides and Sanguibacteroides were more prevalent in the control group.AIM To identify the characteristic gut genera in obese and normal-weight children(8-12-year-old)using 16S rDNA sequencing,and provide a basis for subsequent mechanistic studies and prevention strategies for childhood obesity.METHODS Thirty each normal-weight,1:1 matched for age and sex,and obese children,with an obese status from 2020 to 2022,were included in the control and obese groups,respectively.Basic information was collected through questionnaires and body measurements were obtained from both obese and normal-weight children.Fecal samples were collected from both groups and subjected to 16S rDNA sequencing using an Illumina MiSeq sequencing platform for gut microbiota diversity analysis.RESULTS Significant differences in BMI and body-fat percentage were observed between the two groups.The Ace and Chao1 indices were significantly lower in the obese group than those in the control group,whereas differences were not significant in the Shannon and Simpson indices.Kruskal-Wallis tests indicated significant differences in unweighted and weighted UniFrac distances between the gut microbiota of normal-weight and obese children(P<0.01),suggesting substantial disparities in both the species and quantity of gut microbiota between the two groups.Prevotella,Firmicutes,Bacteroides,and Sanguibacteroides were more abundant in the obese and control groups,respectively.Heatmap results demonstrated significant differences in the gut microbiota composition between obese and normal-weight children.CONCLUSION Obese children exhibited lowerα-diversity in their gut microbiota than did the normal-weight children.Significant differences were observed in the composition of gut microbiota between obese and normal-weight children.

Did weekly economic index and volatility index impact US food sales during the first year of the pandemic?

We explore the impacts of economic and financial dislocations caused by COVID-19 pandemic shocks on food sales in the United States from January 2020 to January 2021.We use the US weekly economic index(WEI)to measure economic dislocations and the Chicago Board Options Exchange volatility index(VIX)to capture the broader stock market dislocations.We validate the NARDL model by testing a battery of models using the autoregressive distributed lags(ARDL)methodology(ARDL,NARDL,and QARDL specifications).Our study postulates that an increase in WEI has a significant negative long-term effect on food sales,whereas a decrease in WEI has no statistically significant(long-run)effect.Thus,policy responses that ignore asymmetric effects and hidden cointegration may fail to promote food security during pandemics.

Forecasting S&P 500 Stock Index Using Statistical Learning Models

Forecasting the movement of stock market is a long-time attractive topic. This paper implements different statistical learning models to predict the movement of S&P 500 index. The S&P 500 index is influenced by other important financial indexes across the world such as commodity price and financial technical indicators. This paper systematically investigated four supervised learning models, including Logistic Regression, Gaussian Discriminant Analysis (GDA), Naive Bayes and Support Vector Machine (SVM) in the forecast of S&P 500 index. After several experiments of optimization in features and models, especially the SVM kernel selection and feature selection for different models, this paper concludes that a SVM model with a Radial Basis Function (RBF) kernel can achieve an accuracy rate of 62.51% for the future market trend of the S&P 500 index.