Quantity Index Research Articles

Martini Indices, Fisher Indices, and Consistency-in-Aggregation

In this article we consider the price and quantity indices introduced in the nineties by the Italian statistician Marco Martini (1944–2002). It turns out that Fisher indices can be considered as members of the infinite set of Martini indices. In particular attention is paid to the question to what extent these indices exhibit Consistency-in-Aggregation. This throws new light on the behavior of Fisher indices.

Epoxy Value Measurement of E44 Epoxy Resin by Various Chemical Titration Method

AbstractDuring the production of epoxy resins, it is crucial to control or to know the epoxy groups. It is known that epoxy value is the most important analytical index of epoxy resin physical quantity to characterize the number of epoxy groups in epoxy resin. In this paper, two ways for testing the epoxy values of E44 epoxy resin are developed based on chemical titration method: hydrochloric acid‐acetone method and perchloric acid‐tetraethylammonium bromide method. The features of different methods and the influence of approaches on epoxy value are studied systematically. At the significant level of 0.05, for hydrochloric acid‐acetone method, the confidence interval for the mean is (0.454±0.003)eq/100 g, and for perchloric acid‐tetraethylammonium bromide method, the confidence interval for the mean is (0.453±0.003)eq/100 g. It has been proved that the test results of the two methods are basically the same. And the advantages and disadvantages of the two methods have been put forward. In addition, the testing mechanism of hydrochloric acid‐acetone method and perchloric acid‐tetraethylammonium bromide method is illustrated in detail. On the basis of superiority over the two methods, a novel method for testing epoxy resin with rapid and accurate epoxy value can be envisioned.

Preference changes and index number theory

AbstractThe economic approach to the cost of living index assumes that consumer preferences remain constant over time. This assumption poses little risk in calculating a short‐run intertemporal bilateral price index. The assumption, however, breaks down in the case of a fixed‐based time series index spanning a long period and in the context of international comparison. The economic analysis of preference changes, however, is not well‐established. In this paper, we review the economic approach in index numbers under preference changes. Suggestions are made on how to approach the problem and their implications for the measurement of price and quantity indices.

Safety assessment of agricultural products and the pesticide regulation trend in China

The sustainable development of Chinese agriculture needs to coordinate the quality and quantity of agricultural products. To verify whether government regulation can promote agricultural development by controlling pesticides, the indices of government regulation, quantity and quality of agricultural products, and pesticide use per area of cropland were calculated, and a comprehensive evaluation index and the coupling degree and coordination degree of agricultural products were analyzed by coupling function. The results showed that the coupling and coordination degree of the quality and quantity of agricultural products and the comprehensive index are improving. The regulation of pesticide use per area of cropland is a key mechanism in promoting the coordinated development of agricultural product safety. The regulation trend of agricultural development in China is to reduce pesticide usage appropriately and expand the production-possibility frontier of agricultural products.Graphical abstract

Is the output growth rate in NIPA a welfare measure?

Abstract This paper shows that, in a dynamic general equilibrium framework, the rate of output growth as measured by national income and product accounts reflects changes in welfare in the precise sense of equivalent variation. The main argument is straightforward. In a two-sector dynamic general equilibrium model of heterogeneous households, recursive preferences and quasi-concave technology, the Bellman equation provides a representation of household preferences over current consumption and investment. When applied to this representation of preferences, a Fisher–Shell true quantity index turns out to be equal to the Divisia index, closely approximated by the Fisher ideal chain index used in national income and product accounts.

The impact of sleep quality on visual working memory varied with the duration of maintenance.

Sleep quality can affect the performance of visual working memory. However, the effect of sleep quality on the maintenance stage, which is the key to maintain the quality and efficiency of visual working memory representation, remains unclear. This study is the first to explore the effect of sleep quality on the maintenance of visual working memory information. 60 healthy college students completed the Pittsburgh Sleep Quality Index (PSQI) and color recall task of visual working memory. A mixed experimental design of sleep quality (high or low) and delay duration (1, 4, or 6 s) was used to assess the effect of sleep quality on the maintenance phase of visual working memory. The main effects of sleep quality were significant on visual working memory quantity, precision and offset indexes. Among the quantity index, the interaction between sleep quality and delay duration was also significant. This suggests that prolonging the delay time in the maintenance phase leads to difficulty in maintaining attention to the task for those with lower sleep quality, which results in poorer working memory quantitative representations. Increases in the delay duration of the maintenance phase in visual working memory intensify the impact of sleep quality on task performance. Our study provides evidence to reveal the relationship between sleep quality and visual working memory and offers recommendations for improving sleep quality and cognitive functioning in individuals.

Efficiently Quantifying Egocentric Social Network Cannabis Use: Initial Psychometric Validation of the Brief Cannabis Social Density Assessment.

Social environment is a key determinant of substance use, but cannabis-related social network analysis is not common, in part due to the assessment burden of comprehensive egocentric social network analysis. The current pre-registered secondary analysis assessed the psychometric properties (i.e., convergent, criterion-related, incremental validity) of the Brief Cannabis Social Density Assessment (B-CaSDA) in a cross-sectional sample of adults who use cannabis (N = 310) using a survey-based design. The B-CaSDA assesses the quantity and frequency of cannabis use for the respondent's four closest (non-parent) relationships. Cannabis use severity was elevated for each additional person who used cannabis at all or daily in the individual's social network. B-CaSDA indices (i.e., frequency, quantity, total score) were positively correlated with cannabis consumption, cannabis use severity indicators, and established risk factors for harmful cannabis use. B-CaSDA indices also discriminated between those above and below a clinical cutoff on the Cannabis Use Disorder Identification Test - Revised (CUDIT-R). Finally, in omnibus models that included common risk factors for cannabis use severity, the B-CaSDA quantity index contributed additional variance when predicting CUDIT-R total score, and B-CaSDA frequency contributed additional variance in predicting the CUDIT-R quantity-frequency subscale. The results suggest that the B-CaSDA has the potential to expand social network research on cannabis use and misuse by increasing its assessment feasibility in diverse designs.

Incidence and predictors of thermal oesophageal and vagus nerve injuries in Ablation Index-guided high-power-short-duration ablation of atrial fibrillation: a prospective study.

High-power-short-duration (HPSD) ablation is an effective treatment for atrial fibrillation but poses risks of thermal injuries to the oesophagus and vagus nerve. This study aims to investigate incidence and predictors of thermal injuries, employing machine learning. A prospective observational study was conducted at Leipzig Heart Centre, Germany, excluding patients with multiple prior ablations. All patients received Ablation Index-guided HPSD ablation and subsequent oesophagogastroduodenoscopy. A machine learning algorithm categorized ablation points by atrial location and analysed ablation data, including Ablation Index, focusing on the posterior wall. The study is registered in clinicaltrials.gov (NCT05709756). Between February 2021 and August 2023, 238 patients were enrolled, of whom 18 (7.6%; nine oesophagus, eight vagus nerve, one both) developed thermal injuries, including eight oesophageal erythemata, two ulcers, and no fistula. Higher mean force (15.8 ± 3.9 g vs. 13.6 ± 3.9 g, P = 0.022), ablation point quantity (61.50 ± 20.45 vs. 48.16 ± 19.60, P = 0.007), and total and maximum Ablation Index (24 114 ± 8765 vs. 18 894 ± 7863, P = 0.008; 499 ± 95 vs. 473 ± 44, P = 0.04, respectively) at the posterior wall, but not oesophagus location, correlated significantly with thermal injury occurrence. Patients with thermal injuries had significantly lower distances between left atrium and oesophagus (3.0 ± 1.5 mm vs. 4.4 ± 2.1 mm, P = 0.012) and smaller atrial surface areas (24.9 ± 6.5 cm2 vs. 29.5 ± 7.5 cm2, P = 0.032). The low thermal lesion's rate (7.6%) during Ablation Index-guided HPSD ablation for atrial fibrillation is noteworthy. Machine learning based ablation data analysis identified several potential predictors of thermal injuries. The correlation between machine learning output and injury development suggests the potential for a clinical tool to enhance procedural safety.

Shelf life extended: Focus on microbiota identification, nutrition value, color difference and lipid oxidation of puffed bean products

Puffed bean products(PBP)contain a large amount of protein, and are susceptible to microbial contamination or harmful substances during storage and processing. In this study, the migration rule of microbial quantity and basic index during storage of the same batch and taste PBP was analyzed, and the spoilage bacteria in different periods of PBP were identified and analyzed by high-throughput DNA sequencing (HTS) The results showed that the peroxide value, acid value and mold count of PBP did not exceed the Chinese national standard, and the peak heights of the functional group characteristic peaks in different periods did not change significantly, further indicating that the degree of oxidation of fats and oils in the PBP was relatively light. During storage, the total colony count of PBP increased rapidly in the first two weeks, and controlling the microbial count of the products is the key to extend the shelf life of PBP. Bacterial colonisation affected the alkaline nitrogen and free amino acid content, resulting in a small increase in content. There was no significant change in the content of water activity this may be related to the choice of vacuum packaging for PBP. The brightness value in the colour difference value increased and the redness value decreased this may be related to the high temperature during the high temperature refining process of the chilli seasoning, the high temperature destroys the pigment in the chilli. The dominant bacterial genera of puffed soya products within shelf life were Pantoea, Streptococcus, Kocuria and the dominant fungal genera were Altemaria, Aspergillus. The dominant bacterial genera of expired samples were Bacillus, Rhodococcus. The main dominant fungal genus was Aspergillus. Results of the study will help to better control the growth of microorganisms in the future, as well as to improve the shelf-life and taste of the products.

Impact of “Dry Sowing and Wet Emergence” Water Regulation on Physiological Growth Characteristics and Water Productivity of Cotton Fields in Southern Xinjiang Province

Determining a suitable “dry sowing and wet emergence” water control program for cotton fields in the arid regions of Northwest China is of great significance in saving water resources, improving economic efficiency, and promoting sustainable development of agriculture. The objective of this study was to analyze the effects of different “dry sowing and wet emergence” water control treatments on dry matter accumulation, chlorophyll fluorescence, yield quality, and water productivity of cotton, and to determine the optimal “dry sowing and wet emergence” water control program for cotton growth in arid areas. A two-year experiment was carried out in 2021 and 2022 in mulched drip-irrigated cotton fields, with a total of 13 treatments of different seedling water quantities (2021: 67.5 mm, 90 mm, 112.5 mm; 2022: 6 mm, 10.5 mm, 15 mm) and different drip frequencies (frequencies means number of drops at seedling stage) (2021: one, two, three times; 2022: two times, four times) in the “dry sowing and wet emergence”. Results indicated a positive correlation between increased seedling water quantity and growth indexes. High seedling water quantity treatment demonstrated a 14.33% higher cotton yield than the low seedling water quantity treatment. In comparison with low-frequency treatment, the high-frequency treatment exhibited significantly larger cotton plant height, dry matter accumulation, and yield. Over two years, the average values increased by 8.69%, 16.4%, and 15.91%, respectively, with a 14.55% increase in the coefficient of photochemical quenching of the leaf blade (qP). The high frequency and larger amount of seedling water quantity treatments showed significantly higher irrigation water productivity, with increases of 39.2% and 70.2% compared to the winter irrigation control treatment. In summary, the appropriate “dry sowing wet emergence” water regulation mode (the first drip: 15 mm, the second drip: 4.5 mm, the third drip: 22.5 mm, the fourth drip: 15 mm) can ensure crop yield quality under the premise of significantly reducing the agricultural irrigation water, which can provide certain theoretical support for the green, efficient, and sustainable development of the local cotton industry.

Spatial-temporal evolution and influencing factors of ecological resilience in urban agglomerations: a case study of Shanxi section of the Yellow River Basin

Scientific assessment of the development status and factors influencing the urban ecological resilience of the Yellow River Basin (YRB) is highly significant for promoting its development. This study constructed an evaluation index system for urban ecological resilience considering the four dimensions of pressure, state, response, and innovation. The spatiotemporal ecological resilience of the urban agglomeration (UA) in the Shanxi section of the YRB from 2012 to 2021 was studied using kernel density estimation, Dagum Gini coefficient, and standard deviation ellipse, and the influencing factors of urban ecological resilience were analyzed using a geographic detector. This research revealed that (1) the ecological resilience of cities in the Shanxi section of the YRB experienced a fluctuation process of rise—fall—rise. The urban ecological resilience generally reflected a gradient decreasing spatial pattern of Central Shanxi UA > South Shanxi UA > North Shanxi UA, and gradually changed from the dual core of “Taiyuan—Jincheng City” to the single core of Taiyuan City. (2) The migration trajectory of urban ecological resilience center of gravity fluctuated in the direction of “northwest-southeast,” and moved 12.63 km to the southeast overall. (3) The water supply per ten thousand Yuan GDP, occupied area of construction land per ten thousand Yuan GDP, green coverage rate in built-up areas, ratio of research and experimental development funds (R&D) to GDP, proportion of science and technology expenditure in local fiscal expenditure, and patent licensing quantity index have a high influence on urban ecological toughness at all stages. This influence was further strengthened by the interaction between factors. This study provides an important scientific basis for shaping high-quality development advantages in the YRB and creating a resilient and livable environment.

DNA degradation of bloodstains on cotton fabric caused by different washing procedures.

DNA degradation in biological material needs to be better understood. Bloodstains on washed clothing are disturbed by washing procedures, sometimes transferred to other fabrics, often with latent bloodstains and usually with significantly degraded DNA.The samples (cotton fabric with bloodstains) are divided into six main groups, depending on the washing method regarding water temperature (95, 60, and 30°C) and the detergent use. After completing the washing process, samples were stored for a certain period (1day to 6months) and subsequently analyzed. Analyses were performed using standard protocols and commercial kits to measure the remaining DNA quantity (concentration) and DNA degradation index in the processed samples.Our results revealed that the high washing temperature (60 and 95°C) and the application of detergent have a synergic action on DNA degradation, while at 30°C this effect is absent. Furthermore, the effect of detergent on accelerated DNA degradation is observed about a month after the washing. This delayed effect of detergent has no explanation in current literature data.To obtain optimal results from the bloodstains, we recommended that the period from the crime event and attempted cleaning by a perpetrator to the laboratory analysis should be less than 1month.

Community Resilience in Accessing Essential Service Facilities Considering Equity and Aging Demand: A Case of Shanghai, China

The COVID-19 lockdown has deepened inequity among vulnerable groups, such as the elderly. Reducing inequity in access to essential service facilities is an effective way to improve community resilience in dealing with pandemics. In this research, three indexes were created to measure community resilience in accessing essential services. Specifically, we have considered the different walking capacity and different needs of the elderly and the general population. We selected Shanghai as the case for our research and analyzed the spatial patterns of both space-based and population-based essential service facilities. The Lorenz curve and the Gini coefficient were used to measure the spatial equity. And, we attempted to reveal the relationships between the population density and three indexes through bivariate Local Indicators of Spatial Association. The results suggest that the Diversity Index enjoys the highest equity, followed by the Demand Accessibility Index, and the equity of the Per Capita Quantity Index is the lowest. Furthermore, the accessibility of essential services in urban areas is excellent, while in some suburban areas it is low. Our findings contribute valuable scientific insights for policy makers to strengthen community resilience and address inequities for immediate or long-term measures.

Assessment of multi-components and sectoral vulnerability to urban floods in Peshawar – Pakistan

Over the last two decades, urban floods and their impacts have been on the rise worldwide, owing to both climatic changes and human activities. The present study examines different at-risk elements, such as residential, commercial, and critical facilities, to evaluate their multi-components of vulnerability to urban floods in Peshawar, Pakistan. Based on the impacts of urban floods, the weightage of each component of the vulnerability for the selected elements at risk is defined. This study presents and uses the modified Fisher's ideal quantity index to combine the different vulnerability components into a single value. Additionally, the Patnaik and Narayan vulnerability index is employed to generalize sector-wise vulnerabilities across the study area. The results show that the old physical infrastructure of commercial and manufacturing units in the Kohati Gate area is highly vulnerable to urban floods, while the residential units are the least susceptible due to their distanced location from the drainage system. In Hayatabad, encroachments along the torrent's sides, affecting housing and educational institutions, contributed to increased vulnerability to urban floods, despite their relatively lower physical vulnerability. The study provides a new platform for understanding the multi-components of vulnerability to urban floods and tackling the challenges posed by urban floods effectively.

A Methodological Approach for Data Collection and Geospatial Information of Healthy Public Spaces in Peripheral Neighborhoods—Case Studies: La Bota and Toctiuco, Quito, Ecuador

Adequate public spaces and urban green areas are key criteria for urban development and infrastructure implementation in healthy cities. Latterly, there have been an increasing number of research methods using artificial intelligence (AI) to monitor, quantify, and control the state of these spaces with an aim toward pioneering research in urban studies. However, in informal areas, open-data access tends to lack adequate and updated information, making it difficult to use AI methods. Hence, we propose a methodology for restricted open data collection and preparation for future use in machine learning or spatial data science models for similar areas. To that extent, we examine two peripheral and low-income neighborhoods in Quito, Ecuador—La Bota and Toctiuco—to analyze their public spaces, urban green areas, points of interest, and road networks, and how they address healthy cities criteria. We develop an original methodological approach that combines an index of proximity, accessibility, quantity, and quality for these spaces with geospatial and network analysis techniques. Results indicate that the connectivity and structure of these spaces are centralized and nodal, representing exclusion and segregation. This work provides insights into potential healthy spaces and information to urban planners and policymakers in decision-making for healthy urban infrastructure.

A survey on spatial and temporal variations of groundwater quality and quantity index using Geographic Information System and Geostatistics (Case study: Bam- Narmashir plain)

A survey on spatial and temporal variations of groundwater quality and quantity index using Geographic Information System and Geostatistics (Case study: Bam- Narmashir plain)

Cross-regional ecological compensation under the composite index of water quality and quantity: A case study of the Yellow River Basin

The calculation of ecological compensation (EC) constitutes the core element of the EC mechanism, which is related to the practicability of the mechanism. Based on the comprehensive index of water quality and quantity, this study establishes a measurement method for EC across administrative divisions. First, the improved Nemerow pollution index (NPI) is adopted to assess the water quality of specific sections, while the water rights and GDP indicators are employed to characterize the water quantity of each section. Secondly, given the spatial relationship of each region within the basin, two compensation allocation schemes are established referring to the water intake and grey water footprint indicators. Finally, the EC amounts of each region in the Yellow River Basin from 2016 to 2021 are calculated using the proposed method. The results show that: (1) the improved NPI is significantly higher in the upstream than in the downstream, implying better water quality in the upstream region; (2) From 2016 to 2021, both Gansu and Ningxia exhibit negative EC coefficients, suggesting superior water quality in the upper section of these regions, while Henan Province demonstrates the opposite trend; (3) During the same period, Qinghai, Gansu, Shanxi, Shaanxi, and Shandong experience an EC deficit, while Ningxia, Inner Mongolia, Henan, and Yellow River Conservancy Commission exhibit an EC surplus. Using water quality and quantity indicators, this study includes the implementation of basin unification and regional environmental comprehensive management into the scope of responsibility of the basin government, which can effectively solve the drawbacks of unclear responsibilities of stakeholders and ineffective implementation of compensation in the basin EC.

Computed tomography reveals hypertrophic remodelling of the diaphragm in cystic fibrosis but not in COPD.

Computed tomography (CT) is increasingly used for assessing skeletal muscle characteristics. In cystic fibrosis (CF) and chronic obstructive pulmonary disease (COPD), reduced limb muscle mass predicts poor clinical outcomes. However, the degree to which quantity or quality of respiratory and nonrespiratory muscles is affected by these diseases remains controversial. Thoracic CT images of 29 CF, 21 COPD and 20 normal spirometry control subjects were analysed to measure indices of muscle quantity (volume or cross-sectional area) and quality (radiodensity) in respiratory (diaphragm, abdominal) and nonrespiratory (pectoralis, lumbar paraspinal) muscles. Multivariable linear regression assessed relationships of CT measurements with body mass index (BMI), forced expiratory volume in 1 s (FEV1) % pred, inflammation and infection biomarkers, nutritional status and CF genotype. Diaphragm volume in CF was significantly higher than in COPD (by 154%) or controls (by 140%). Abdominal muscle area in CF was also greater than in COPD (by 130%). Nonrespiratory muscles in COPD had more low radiodensity muscle (marker of lipid content) compared to CF and controls. In CF but not COPD, higher BMI and FEV1 % pred were independently associated with higher diaphragm and/or abdominal muscle quantity indices. Serum creatinine also predicted respiratory and nonrespiratory muscle quantity in CF, whereas other biomarkers including genotype correlated poorly with muscle CT parameters. Our data suggest that the CF diaphragm undergoes hypertrophic remodelling, whereas in COPD the nonrespiratory muscles show altered muscle quality consistent with greater lipid content. Thoracic CT can thus identify distinctive respiratory and nonrespiratory muscle remodelling signatures associated with different chronic lung diseases.

Effect of ammonia injection stages and segregation degrees on the characteristics of iron ore sintering process

To reduce solid fuel consumption and carbon emissions during iron ore sintering, ammonia injection-assisted sintering was proposed, and its feasibility was verified through sinter pot experiments. The effects of ammonia injection stages and segregation degrees on the sintering characteristics were investigated based on the uneven heat distribution in the sintering bed. The results show that ammonia injection improves fuel combustion efficiency, sinter bed temperature and melting quantity index. The sinter ore strength and yield were improved, and the effect of injecting ammonia in the early sintering stage was more significant. When the ammonia injection segregation degree is 0.042 %/min, the sinter ore yield and tumbler index increase from 61.93% and 49.4% to 68.85% and 58.8%, respectively, the average fuel combustion efficiency increases from 89.02% to 92.30%. When the segregation degree increases from 0 to 0.125 %/min, the standard deviation of the uniformity coefficient of the high-temperature index first decreases and then increases, reaching the minimum value when the segregation degree is 0.042 %/min. A segregation degree of 0.042 %/min can achieve the most uniform heat distribution in the sintering bed and the best sinter ore quality, which provides a reference for applying ammonia injection-assisted sintering in industrial production.

Collaborative Innovation Ability Cultivation of College Students by Improving Achievement Transformation Efficiency

With the increasingly urgent demand for innovative talents, college students should have strong collaborative innovation ability because they are the backbone of future sci-tech innovation in China. Existing methods can be used to measure and evaluate to some extent the collaborative innovation and achievement transformation efficiency of college students. However, many of the methods focus on data of a certain period and neglect dynamic analysis. Dynamic comparisons of different periods need to be made because innovation activities and achievement transformation may be influenced by time factors in practical situations. In addition, some methods only focus on the quantity index of achievement transformation, and neglect quality evaluation. Therefore, this paper aimed to study the collaborative innovation ability cultivation of college students by improving the achievement transformation efficiency. Three-stage data envelopment analysis (DEA)-Windows model was used to calculate the collaborative innovation and achievement transformation efficiency of college students. This paper elaborated in detail the calculation process of these three stages, namely, the first-stage DEA-Windows analysis, the second-stage panel stochastic frontier analysis (SFA), and the third-stage adjusted DEA-Windows analysis. Based on the research needs of collaborative innovation ability cultivation of college students by improving the achievement transformation efficiency, this paper constructed an evaluation index system using Fare-Primont index model and Pastor method, and focused on the sci-tech innovation achievement transformation factors, such as output results and ability improvement. Finally, this paper showed the analysis results by combining with examples, which verified the proposed method was effective.