Systematic Statistical Analysis Research Articles

Spa(tia) – a diffusion-oriented method of territorial impact assessment

ABSTRACT In this paper we consider the options for policymakers in performing territorial impact assessment (TIA) of various policies. Hybrid methods combining stakeholder involvement with systematic statistical analysis are a good compromise between the analytical capabilities of the tool and the required time and resources needed to use it. However, the existing hybrid methods focus on the direct effects of the intervention, while neglecting the territorial diffusion of the policy outcomes. To address this gap, we propose a new method, which uses a spatial proximity matrix to incorporate diffusion effects into TIA. We discuss an example application of the new method for the ex-ante evaluation of the ‘European Funds for Western Pomerania’ programme.

КЛИМАТИЧЕСКИЕ ОСОБЕННОСТИ ТЕМПЕРАТУРЫ ВОЗДУХА НА ЮГЕ КАЗАХСТАНА В ВЕСЕННЕ-ЛЕТНЕЕ ПОЛУГОДИЕ

Scientific results of a study of temperature changes in the southern region of the Republic of Kazakhstan are presented based on long-term climate data for 1990-2020. by 11 meteorological stations: Almaty, Aidarly, Zharkent, Lepsy, Matai, Kazalinsk, Kyzylorda, Tasty, Taraz, Turkestan, Shymkent. The main goal of the work is to identify the conditions for the formation of large anomalies of average monthly temperature in the spring in the southern region against the background of ongoing climate changes and determine the trend of its change. The relevance of the work lies in the fact that air temperature is one of the indicators of climate change. Large air temperature anomalies in the warm half of the year can lead to catastrophic droughts, which will have a detrimental effect on agricultural yields. For the study area, a systematic statistical analysis of the spatiotemporal distribution of temperature anomalies was carried out. Extreme temperature months will be considered. Circulation conditions for the formation of spring-summer months extreme in temperature. The results obtained can be used in developing methods for predicting extreme hazardous phenomena.

Statistical Analysis of Copper(I) Iodide and Bis(Diphenylphosphino)alkane-Based Complexes and Coordination Polymers

The prediction of the metal cluster within a coordination polymer or complex, as well as the dimensionality of the resulting polymer or complex (i.e., 0D, 1D, 2D, or 3D), is often challenging. This is the case for Ph2P(CH2)mPPh2 ligands (1 ≤ m ≤ 8) and CuX salts, particularly for X = I. This work endeavors a systematic statistical analysis combining studies in the literature and new data, mapping the nature of the resulting CuI aggregates with eight different diphoshphines in 2:1, 3:2, 1:1, 2:3, and 1:2 CuI:Ph2P(CH2)mPPh2 molar ratios as a function of m, which lead to either pure products or mixtures. Several trends are made relating stoichiometry and chain length to the CuI cluster formed (i.e., globular vs. quasi-planar). Four new X-ray structures were determined: [Cu3I2(L1)3]I, Cu3I3(L2)2, Cu2I2(L6)2, and Cu4I4(L8)2, where m is, respectively, 1, 2, 6, and 8, in which the CuxIy central aggregates adopt triangular bipyramid, diamond, rhomboid, and cubane shaped motifs, respectively. Photophysical measurements assisted the establishment of trends considering the paucity of the crystallographic structures. During this study, it was also found that the 0D-complex Cu2I2(Ph2P(CH2)5PPh2)2 exhibits thermally activated delayed fluorescence.

Heavy-tailed distributions of confirmed COVID-19 cases and deaths in spatiotemporal space.

This paper conducts a systematic statistical analysis of the characteristics of the geographical empirical distributions for the numbers of both cumulative and daily confirmed COVID-19 cases and deaths at county, city, and state levels over a time span from January 2020 to June 2022. The mathematical heavy-tailed distributions can be used for fitting the empirical distributions observed in different temporal stages and geographical scales. The estimations of the shape parameter of the tail distributions using the Generalized Pareto Distribution also support the observations of the heavy-tailed distributions. According to the characteristics of the heavy-tailed distributions, the evolution course of the geographical empirical distributions can be divided into three distinct phases, namely the power-law phase, the lognormal phase I, and the lognormal phase II. These three phases could serve as an indicator of the severity degree of the COVID-19 pandemic within an area. The empirical results suggest important intrinsic dynamics of a human infectious virus spread in the human interconnected physical complex network. The findings extend previous empirical studies and could provide more strict constraints for current mathematical and physical modeling studies, such as the SIR model and its variants based on the theory of complex networks.

Effect of Curing Condition on the Strength Evolution of Polyether Polyurethane Concrete

Polyether polyurethane concrete (PPC) is a new type of cold-mixed and cold-paved material. In this study, the strength evaluation mechanism of PPC was systematically investigated through test methods at different scales. First, the strength evolution mechanism of the polyurethane binder itself was characterized by Fourier transform infrared spectrometer (FTIR). Subsequently, different significant influence factors including temperature, humidity, and catalyst dosage on the strength evolution of PPC were analyzed and quantified by indirect tensile test. Third, a systematic statistical analysis of these influencing factors was performed by statistical methods to quantify their contribution to the strength formation of PPC. The strength of PPC was closely related to the strength evolution of polyurethane binder, and the order of influence factors on strength evolution was temperature > humidity > catalyst dosage. Finally, considering these influence factors, a prediction model of PPC curing time was established. The predicted curing time was compared with the outdoor test results, and the results verified the validity and rationality of the model.

On the critical role of martensite hardening behavior in the paradox of local and global ductility in dual-phase steels

The ductility of sheet metal is typically limited by either localized necking or by damage and fracture. A recent ductility classification refers to these failure modes respectively as “global” and “local” formability. The forming limit curve (FLC) and the uniaxial tensile test assess global formability, whereas the fracture forming limit (FFL), the true thickness fracture strain, hole expansion ratios (HER), etc. are indicators of local formability. Experimental hole expansion data in the literature for different dual-phase (DP) steel grades of similar strength and composition presents a paradox: grades which are found to be ductile in a tensile test and/or FLC show a low ductility in hole expansion, whereas other grades with a low ductility in conventional tests perform surprisingly well at cut edges. In this work, an in-depth systematic statistical analysis of idealized artificial two-phase microstructures is carried out to unravel the underlying mechanisms of the observed paradoxical trends. This is done by scaling the hardness of martensite and its volume fraction to generate virtual DP steels of the same strength but different strain hardening and mechanical phase contrast (hardness difference). The proposed micromechanical model adequately reproduces the experimentally observed trends. The results show that in DP steels, a higher global (necking-driven) ductility is obtained upon delaying martensite plasticity by increasing the mechanical contrast of the two phases. Consequently, the stress–strain distributions becomes more heterogeneous, resulting in a lower fracture limit of one of the phases or interfaces in shear loading, thereby, reducing the local ductility. Global ductility is improved by higher mechanical phase contrast and lower martensite volume fraction, whereas local ductility is improved by low phase contrast and higher martensite volume fraction. The hardening behavior of martensite is the key to avoiding the above trade-off between local and global ductility. It is shown that if the strain hardening capacity of martensite in the later stages of deformation (in high strains) can be increased, this would result in removing the observed paradoxical trends of local and global ductility in DP steels.

Characterizing the visualization design space of distant and close reading of poetic rhythm.

Metrical and rhythmical poetry analysis is founded on the systematic statistical analysis and comparison of sonic devices (e.g., rhythmic patterns) that emerge from a combination of pre-established aesthetic and structural rules and the poet's abilities and creative genius to convey a given message adhering to the said constraints. These rhythmical patterns, which have been traditionally obtained by means of a careful close reading of the poems, in a process known as "scansion," can now be obtained and made visible by automatic means. However, the visualization literature is still scarce on approaches that allow an insightful close and distant reading of the rhythmical patterns in a poetry corpus. In this work, we report our initial efforts in characterizing of the visualization design space of distant and close reading of poetic rhythm. By employing a digital version of a corpus of 11,268 verses originally written by the Spanish poet and playwright Federico García-Lorca (1898-1936), we could craft several prototypical visualizations representative of the inherent complexity of the problem which we expect to employ in future user studies and that we share here with the rest of the community to foster further discussion around this interesting topic.

Turbulence in compact to giant H ii regions

ABSTRACT Radial velocity fluctuations on the plane of the sky are a powerful tool for studying the turbulent dynamics of emission line regions. We conduct a systematic statistical analysis of the H α velocity field for a diverse sample of nine ${\rm H\, \small{II}}$ regions, spanning two orders of magnitude in size and luminosity, located in the Milky Way and other Local Group galaxies. By fitting a simple model to the second-order spatial structure function of velocity fluctuations, we extract three fundamental parameters: the velocity dispersion, the correlation length, and the power-law slope. We determine credibility limits for these parameters in each region, accounting for observational limitations of noise, atmospheric seeing, and the finite map size. The plane-of-sky velocity dispersion is found to be a better diagnostic of turbulent motions than the line width, especially for lower luminosity regions where the turbulence is subsonic. The correlation length of velocity fluctuations is found to be always roughly 2 per cent of the ${\rm H\, \small{II}}$ region diameter, implying that turbulence is driven on relatively small scales. No evidence is found for any steepening of the structure function in the transition from subsonic to supersonic turbulence, possibly due to the countervailing effect of projection smoothing. Ionized density fluctuations are too large to be explained by the action of the turbulence in any but the highest luminosity sources. A variety of behaviours are seen on scales larger than the correlation length, with only a minority of sources showing evidence for homogeneity on the largest scales.

Multi-directional irregular wave forces acting on a tandem pile group

In this study, the interactions between multi-directional irregular waves and a tandem pile group are experimentally investigated. A systematic statistical analysis of the force coefficients of the pile group and the wave force on a tandem pile group under multi-directional waves is first carried out. The results show that the wave force of the pile group is significantly affected by the wave directionality. Further, Reynolds-averaged Navier–Stokes equations are used to establish a 3D numerical wave tank by considering the interactions between the waves and the pile groups, and this is verified by using experimental data. The characteristics of the wave force on the first and the last pile in the tandem pile group were numerically examined. The flow field around the front first pile was affected by its rear pile such that the pressure at its rear increased. However, without the rear pile, the pressure difference between the upward and rearward zone of the last pile significantly increased compared with that of the first pile, and this caused the wave force of the last pile to be larger than that of the first pile.

Statistical Rule Extraction for Gas Turbine Trip Prediction

Abstract Gas turbine trip is an operational event that arises when undesirable operating conditions are approached or exceeded, and predicting its onset is a largely unexplored area. The application of novel artificial intelligence methods to this problem is interesting both from the computer science and the engineering point of view, and the results may be relevant in both the academia and the industry. In this paper, we consider data gathered from a fleet of Siemens industrial gas turbines in operation that includes several thermodynamic variables observed during a long period of operation. To assess the possibility of predicting trip events, we first apply a new, systematic statistical analysis to identify the most important variables, then we use a novel machine learning technique known as temporal decision tree, which differs from canonical decision tree because it allows a native treatment of the temporal component, and has an elegant logical interpretation that eases the posthoc validation of the results. Finally, we use the learned models to extract statistical rules. As a result, we are able to select the five most informative variables, build a predictive model with an average accuracy of 73%, and extract several rules. To our knowledge, this is the first attempt to use such an approach not only in the gas turbine field but also in the whole industry domain.

Seasonal and interannual variations in sea surface temperature in the Tatar Strait according to satellite data

The aim of the work was to conduct a systematic statistical analysis of the spatial and temporal variability of sea surface temperature (SST) in the waters of the Tatar Strait based on satellite data accumulated in the Sakhalin branch of VNIRO using the TeraScan receiving station for 1998‒2021. It was revealed that in different seasons of the year the SST structure is similar and characterized by the highest values in the southeast and the lowest in the northwest of the strait. An important new result was obtained by expanding of the SST field in terms of the EOF, which is associated with a sharp change in the nature of the time function of the third mode, which occurred in 2013–2014. Such changes can be considered as a climatic shift in the studied area most pronounced in the northwestern part of the strait and near the southwestern coast of Sakhalin Island, where the change was about 1 °C. This circumstance can have a noticeable effect on the state of populations of several species of shrimp and commercial fish.

DEFECT SENSITIVITY OF DUAL-PHASE STEELS: A STATISTICAL MICROMECHANICAL INVESTIGATION OF THE DUCTILITY LOSS DUE TO PREEXISTING DEFECTS

As a result of their heterogeneous two-phase microstructure, dual-phase (DP) steels reveal various damage mechanisms leading to the nucleation of voids, microcracks, and other defects at all stages of deformation. Defects may also preexist in the microstructure due to thermomechanical processing of the material. The literature has ample evidence that DP steels, while offering a good compromise between ductility and strength, are sensitive to these types of preexisting defects. However, the quantitative dependency of mechanical properties of DP steels on such preexisting defects is still to be explored. In this paper, a systematic statistical analysis of this sensitivity is carried out using an idealized microstructural model of randomly generated two-phase volume elements with embedded preexisting defects. The proposed model also enables a methodological study probing the influence of mechanical phase contrast (i.e., the hardness difference between the constituent phases) and volume fractions. It is observed that high phase contrast microstructures are less sensitive to initial defects since the inherent extreme heterogeneity of the microstructure leads to the nucleation of new damage incidents irrespective of the presence of preexisting defects. At constant contrast, the volume fraction of the hard phase has less influence. These conclusions are insensitive to the precise type of defect considered.

On Pan-Atlantic cold, wet and windy compound extremes

The co-occurrence of extreme weather in geographically distinct regions can result in larger impacts than the sum of those associated with the individual events occurring in isolation. Previous work has proposed a connection between extreme cold temperatures over North America and wet and windy weather over Europe. Here, we present a systematic statistical analysis of this link, focusing on extreme occurrences in both continents. We identify wintertime cold air outbreaks (CAOs) for 38 overlapping domains over North America between 1979 and 2020 using ERA5 data. The occurrence of these regional CAOs is then matched to extreme precipitation and wind events over 6 domains in western and central Europe. We find CAOs over the eastern and central USA co-occur with more frequent wind extremes over Iberia, whilst CAOs over eastern Canada are followed by wind extremes over northern Europe and the British Isles. Precipitation extremes exhibit greater variability and typically occur prior to the peak of the CAOs. We find significant increases in Iberian and southern European precipitation extremes occurring in conjunction with CAOs over the eastern USA, consistent with what we found for wind extremes. Indeed, Iberia is one of the hotspot regions for wet and windy extremes co-occurring with CAOs in North America: depending on CAO region, the frequency of extreme precipitation and wind events over Iberia locally can more than double relative to climatology. Results indicate that the location of wet and windy European extremes substantially depends on the North American region affected by CAOs. Although pan-Atlantic extremes are associated with an enhanced upper-level jet stream, their complete dynamical description requires further investigation.

Systematic analysis of the impact of slurry coating on manufacture of Li-ion battery electrodes via explainable machine learning

The manufacturing process strongly affects the electrochemical properties and performance of lithium-ion batteries. In particular, the flow of electrode slurry during the coating process is key to the final electrode properties and hence the characteristics of lithium-ion cells, however it is given little consideration. In this paper the effect of slurry structure is studied through the physical and rheological properties and their impact on the final electrode characteristics, for a graphite anode. As quantifying the impact of the large number of interconnected control variables on the electrode is a challenging task via traditional trial-and-error approaches, an explainable machine learning methodology as well as a systematic statistical analysis method is proposed for comprehensive assessments. The analysis is based upon an experimental dataset in lab-scale involving 9 main factors and 6 interest variables which cover practical range of variables through various combinations. While the predictability of response variables is evaluated via linear and nonlinear models, complementary techniques are utilised for variables importance, contribution, and first and second order effects to increase the model transparency. While coating gap is identified as the most influential factor for all considered responses, other subtle relationships are also extracted, highlighting that dimensionless numbers can serve as strong predictors for models. The impact of slurry viscosity and surface tension on electrode thickness, coat weight and porosity are also extracted, demonstrating their importance for electrode quality. These variables have been rarely considered in previous works, as the relationships are difficult to extract by trial and error due to interdependencies. Here we demonstrate how model-based analysis can overcome these difficulties and pave the way towards an optimised electrode manufacturing process of next generation Lithium-ion batteries.

An Analyzing on Statistical Data Analysis Skill Needs Among Graduates

The skill of analyzing statistical data is a skill that uses quantitative or numerical methods. The need for a systematic research process usually requires a foundation of quantitative skills even if little other than its importance in the realm of future employment and important knowledge for every student, especially for those who conduct research scientifically. Creative arts students are students who venture into the field of arts and creative studies who mostly use qualitative methods in their research. Yet is there a need for systematic statistical data analysis skills in the scope of their study? Therefore, to answer this question, this study examines the need for data analysis skills among creative arts students. A total of 102 sets of questionnaires were distributed to undergraduate students from various programs of the Faculty of Applied and Creative Arts UNIMAS. Descriptive analysis was used to analyze the questionnaire data using Statistical Package for the Social Science (SPSS) version 26.0. Overall finding showed that statistical data analysis skills are very necessary among creative arts students.

Statistical Data Analysis Skills Needs Among Creative Arts Students

Knowledge of data analysis skills is an important knowledge for every student, especially for those who conduct research scientifically. However, is there a need for systematic statistical data analysis skills in the scope of their study among creative arts students? Therefore, this study examines the need for quantitative data analysis skills among creative arts students in the perspective of Alumni, Academician and Industry. This study interviewed 12 alumni, 13 academicians and 10 representatives from the Creative Arts Industry to analyse their perspective. Qualitative analysis method is used to analyze the results of interviews with former students, academicians and the industry. As result, all sample of informants interviewed agreed that Creative Arts Students need data analysis skill using quantitative method.

AN OPTIMIZED REMOTE SENSING RECOGNITION APPROACH FOR STRAW BURNING IN HENAN PROVINCE, CHINA

Abstract. In the paper, Henan Province with prevalent straw burning was taken as the study case. Aimed at remote sensing recognition of the straw burning fire points in a large-scale area with complex terrain and climate conditions, an optimized recognition strategy of straw burning was proposed based on the MOD021KM data. In our new recognition strategy, the threshold determination method was optimised by systematic statistical analysis of spectral features. Then the non-straw burning fire points were eliminated by extracting the agricultural land from MCD12Q1 image. Thus, the true straw-burning fire points were determined. The results showed that the recognition accuracy of straw burning fire points was effectively improved by optimized threshold determination method.

Did Billboard, Cash Box, and Record World Charts Tell the Same Story? Perception and Reality, 1960-1979

ABSTRACT Billboard, Cash Box, and Record World had different reputations regarding the way they ranked records in their weekly charts; however, no systematic statistical analysis has been done to test those perceptions. This paper reports such a statistical analysis of chart behavior of 4,578 record sides, each with a unique and complete chart lifecycle, peaking at position 1–40 in all three magazines. Comparison was done at three levels: magazine, record, and year/decade. The magazines were found to have statistically significant differences of fractions of a week in some components of record lifecycle (rise, peak, fall, and length of time on the charts); however, those differences are not large enough to be perceived in chart behavior, where data granularity is one week. There are significant and perceptible differences, however, between the 1960s and 1970s, due largely to the differences in the number of chart entries. At record level, Billboard tended to score the highest-ranked records slightly higher than the other two magazines. Approximately 1.5% of the records show one magazine scoring the record significantly differently than the other two. Only fractional-week differences were found among the magazines in Entry, Peak, and Exit dates. Thus, on a macro basis, the magazines tended to tell the same story; on a micro basis they could tell very different stories for reasons that are not obvious.

EFFICACY OF ADDITION OF MAGNESIUM AS AN ADJUVANT TO LOCAL ANAESTHETICS IN PERIBULBAR BLOCK: A PROSPECTIVE RANDOMIZED DOUBLE-BLIND STUDY

Introduction: Topical, regional or general anesthesia can be used for ocular surgery. Among regional blocks, Peribulbar block is a good choice as it provides efficient anesthesia with good lid and globe akinesia with low incidence of complications.1 However the time for onset of akinesia with Peribulbar block is much longer in comparison to retro bulbar block,2which may lead to a delay to start the surgery. The incidence of inadequate analgesia is also more frequent with Peribulbar block2 in comparison to retro bulbar block, which may lead to the requirement of supplementary injection before the start of surgery or intraoperatively. Aims And Objectives: To evaluate the effect of addition of magnesium sulphate to standard local anesthetics mixture for peribulbar blocks in ophthalmic surgeries. Material And Methods: 60 patients who underwent ocular surgery under local anesthesia admitted at Malla Reddy Narayana Multispecialty Hospital, Hyderabad from May2018- october2018(6 months) were enrolled in the study.It was Prospective Randomized controlled double blind study.Inclusion criteria was patients between 20-70 years of either sex with ASA group 1-3 with both anterior and posterior chamber surgery under peribulbar block.Exclusion criteria were patient with mental retardation, allergic to local anesthetics, history of bleeding disorder, cardiac and respiratory diseases and ASA group4-5. Results: After studying 60 patients, out of which 30 patients included in control group (Group NS) and 30 patients in study (Group MS) group,a systematic statistical analysis done for Age and All patients were in age group of 20-70 years. Mean age was 59.0667 +- 7.08049 in the control group (Group NS) and 58.1667 +- 5.73605 in study group (Group MS). The p-value 0.591,which is statistically nonsignificant. Discussion:Anaesthesia plays a vital role in ophthalmic surgery.Most ophthalmic surgeries are carried out under local anaesthesia although topical anaesthesia is soon gaining popularity.The goal of anaesthesia in opthalmic surgery is to provide adequate analgesia and akinesia.Peribulbar block has been used widely for ophthalmic surgery as it is safer than a retrobulbar block. The time for onset of akinesia with peribulbar block is much longer in comparison to retrobulbar block2, which may lead to a delay to start the surgery.The incidence of inadequate analgesia is also more frequent with peribulbar block2 in comparison to retrobulbar block, which may lead to the requirement of supplementary injection before the start of surgery or intraoperatively. Conclusions: Faster onset of globe and lid akinesia after addition of Magnesium sulphate to the mixture of local anaesthetics in peribulbar block.The duration of globe and lid akinesia is prolonged but difference is not statistically significant in Group MS as compared to Group NS.

Synergic use of two-dimensional materials to tailor interfaces in large area perovskite modules

In the field of halide perovskite solar cells (PSCs), interface engineering has been conceptualized and exploited as a powerful mean to improve solar cell performance, stability, and scalability. In this regard, here we propose the use of a multi two-dimensional (2D) materials as intra and inter layers in a mesoscopic PSCs. By combining graphene into both compact and mesoporous TiO2, Ti3C2Tx MXenes into the perovskite absorbing layer and functionalized-MoS2 at the interface between perovskite and the hole transporting layer, we boost the efficiency of PSCs (i.e., +10%) compared to the 2D materials-free PSCs. The optimized 2D materials-based structure has been successfully extended from lab-scale cell dimensions to large area module on 121 cm2 substrates (11 ×11 cm2) till to 210 cm2 substrates (14.5 ×14.5 cm2) with active area efficiency of 17.2% and 14.7%, respectively. The remarkable results are supported by a systematic statistical analysis, testifying the effectiveness of 2D materials interface engineering also on large area devices, extending the 2D materials-perovskite photovoltaic technology to the industrial exploitation.