Simple Analytical Method Research Articles

Lifting the veil off treatment effect heterogeneity

Clinicians often suspect that a treatment effect can vary across individuals. However, they usually lack “evidence-based” guidance regarding potential heterogeneity of treatment effects (HTE). Potentially actionable HTE is rarely discovered in clinical trials and is widely believed (or rationalized) by researchers to be rare. Conventional statistical methods to test for possible HTE are extremely conservative and tend to reinforce this belief. In truth, though, there is no realistic way to know whether a common, or average, effect estimated from a clinical trial is relevant for all, or even most, patients. This absence of evidence, misinterpreted as evidence of absence, may be resulting in sub-optimal treatment for many individuals. We first summarize the historical context in which current statistical methods for randomized controlled trials (RCTs) were developed, focusing on the conceptual and technical limitations that shaped, and restricted, these methods. In particular, we explain how the common-effect assumption came to be virtually unchallenged. Second, we propose a simple graphical method for exploratory data analysis that can provide useful visual evidence of possible HTE. The basic approach is to display the complete distribution of outcome data rather than relying uncritically on simple summary statistics. Modern graphical methods, unavailable when statistical methods were initially formulated a century ago, now render fine-grained interrogation of the data feasible. We propose comparing observed treatment-group data to “pseudo data” engineered to mimic that which would be expected under a particular HTE model, such as the common-effect model. A clear discrepancy between the distributions of the common-effect pseudo data and the actual treatment-effect data provides prima facie evidence of HTE to motivate additional confirmatory investigation. Artificial data are used to illustrate implications of ignoring heterogeneity in practice and how the graphical method can be useful.

Sentimental analysis and prediction of socioeconomic disasters tweets by ML and regular expression

Sentiment analysis is a method of analyzing emotions and using text analysis techniques with natural language processing methods. Sentiment analysis uses data from various sources to identify the user’s attitude through different aspects. It is widely used for extracting opinions and recognizing sentiments, which helps Business organizations understand the user’s needs. This paper proposes a simple but compelling sentiment analysis method, showing the combined scores based on positive and negative words. Then, the tweets are categorized as Neutral, Negative, or Positive according to the scores. Sentiment analysis and opinion mining have grown significantly in the last decade. Different studies in this domain try to determine people’s feelings, opinions, and emotions about something or someone. The main objective of this analysis is to determine the sentiment of the review using a machine learning model and then compare the result with the manual review of the data. This would allow researchers to represent and analyze opinions objectively across different domains. A hybrid method that combines a supervised machine learning algorithm with natural language processing techniques is suggested for review analysis. This project aims to find the best model to predict the sentiment of the tweets on airlines. During the research process and considering various methods and variables that should be considered, we found that methods like naïve Bayes and random forest were not fully explored. The proposed system improves an effective and more feasible method for sentimental analysis using machine learning, multinomialNB, linear regression, and regular expression.

LiteBIRD and CMB-S4 sensitivities to reheating in plateau models of inflation

We study the sensitivity of LiteBIRD and CMB-S4 to the reheating temperature and the inflaton coupling in three types of plateau-potential models of inflation, namely mutated hilltop inflation, radion gauge inflation, and α-attractor T models. We first find relations between model parameters and CMB observables in all models. We then perform Monte Carlo Markov Chain based forecasts to quantify the information gain on the reheating temperature, the inflaton coupling, and the scale of inflation that can be achieved with LiteBIRD and CMB-S4, assuming a fiducial tensor-to-scalar ratio r̅ ∼ 0.02 and neglecting foreground contamination of the B-mode polarization spectrum. We compare the results of the forecasts to those obtained from a recently proposed simple analytic method. We find that both LiteBIRD and CMB-S4 can simultaneously constrain the scale of inflation and the reheating temperature in all three types of models. They can for the first time obtain both an upper and lower bound on the latter, comprising the first ever measurement of the big bang temperature. In the mutated hilltop inflation and radion gauge inflation models this can be translated into a measurement of the inflaton coupling in parts of the parameter space. Constraining this microphysical parameter will help to understand how these models of inflation may be embedded into a more fundamental theory of particle physics.

The Effect of Job Passion on Innovative Work Behaviors: Analytical Research in the Ministry of Higher Education and Scientific Research

The current research aims to test the impact of Job passion on innovative work behaviors, and the idea of the research revolves around providing a job passion that contributes and supports the innovative work behaviors among the employees of the Ministry of Higher Education and Scientific Research, as the job passion variable includes four dimensions (enjoyment at work, self-motivation, self-identity, and a sense of learning). The innovative work behavior variable has addressed four dimensions (the ability to provide creative solutions to problems, the ability to new ideas and proposals, the ability to change as well as initiate, and the spirit of risk), A sample of the employees of the Ministry of Higher Education and Scientific Research, where a random stratified sample of 328 employees were selected from the study community (2229) relied on the questionnaire for collecting data, and the questionnaires valid for statistical analysis were 322 questionnaires. The research used a number of statistical methods to obtain the results of the questionnaire, especially the simple correlation coefficient (Pearson) and descriptive analysis methods using the SPSS.v23 and AMOS.v23). It has proved the validity of the hypotheses through which a set of results were reached, the most prominent of which is the existence of a relationship between the impact of job passion and its dimensions on innovative work behaviors. The dimensions of the variable of innovative work behaviors above are available, but they do not be at the required level, where the ability to change and generate creative solutions. This requires focusing on them in addressing problems and making appropriate decisions that are based on a correct scientific basis, and the management's view of employees is not limited because they represent essential capabilities and tools for implementing decisions and policies. Paper type: Research paper.

A simplified weak coupling dynamic analysis method for running safety evaluation of train on bridges under earthquake excitation

This study proposes a simplified analysis method that couples the bridge and train-track subsystem in a weak form to facilitate the dynamic analysis of the train-track-bridge coupled system (TTBS) under earthquakes. The method includes three main steps: (i) performing dynamic analysis of the bridge under seismic conditions to obtain the response of the bridge deck; (ii) interpolating the bridge displacement beneath each wheelset based on the train's velocity, departure time, and the initial positions of the wheelsets; and (iii) assessing the running safety of the train by incorporating the interpolated bridge response as track irregularity into the train-track coupled system. Steps (i) and (iii) can be analyzed separately using finite element and multibody dynamics software, eliminating the need to create a complex TTBS model that is challenging to achieve within a single software platform. Additionally, based on the method’s assumptions, the earthquake excitation on the train can be separated into the seismic inertial effect and seismic-induced bridge deformation, enabling a quantitative analysis of the impact of these two types of excitations on train safety. Taking a 10-span simply supported bridge and a long-span cable-stayed bridge as examples, the proposed method’s assumptions are verified by comparing its results with those obtained from a complex TTBS model. Furthermore, the impact characteristics of inertial effects and seismic-induced bridge deformation on train safety for these two types of bridges are analyzed. The proposed method offers robust support for seismic design of bridges and facilitates a comprehensive analysis of the mechanisms through which seismic excitations affect train safety.

Softening-based interface model and nonlinear load-settlement response analysis of piles in saturated and unsaturated multi-layered soils

This work presents a simplified method for the nonlinear analysis of the load–displacement response of piles in multi-layered soils. As a starting step, a new interface model based on the disturbed state concept (DSC) is put forth to simulate the interface shear stress-displacement relationship by considering the nonlinear hardening–softening behaviour. In the new model, input parameters can be conveniently calibrated using conventional interface shear tests or on-site tests. The good agreement between predictions and experimental data from interface direct shear tests validated the performance of the proposed DSC model. The DSC model performed better in terms of predictions when compared to the hyperbolic one. Next, the soil-structure interface model and bearing capacity theory are coupled to provide a theoretical framework for the analysis of pile load-transfer in saturated and unsaturated multi-layered soils, where the DSC model is employed to represent base resistance as well as skin friction. This work also discusses the profile of steady-state in-situ matric suction, soil–water characteristic curve, and pore-water pressure of unsaturated soils. The proposed method has the advantage of being used in practice as it is simple to obtain input parameters from laboratory tests, as well as Standard Penetration or Cone Penetration Tests. The proposed framework is finally applied to the analysis of five well-documentedcase studies. The proposed approach and the static load test results from the field measurements are found to be in satisfactory agreement, indicating that the proposed method performs well. The proposed method is suggested to be utilised for preliminary analysis, planning a suitable programme of loading tests, as well as optimizing the pile design by back analysis ofthe load test results.

Green Synthetic Approach for the Preparation of Blue Emitting Gold Nanoclusters: A Simple Analytical Method for Detection of Hexaconazole Fungicide.

Blue emissive Argyreia nervosa-capped gold nanoclusters (A. nervosa-AuNCs) were synthesized via a simple environment-friendly method. The developed probe exhibits rapid response towards the target analyte (hexaconazole fungicide). Several characterizations, including FT-IR, UV-visible, fluorescence, HR-TEM, XPS, and fluorescence lifetime, were studied to confirm the formation of A. nervosa-AuNCs. The A. nervosa-AuNCs displayed emission and excitation peaks at 470 and 390nm, respectively. Furthermore, the quantum yield (QY) of A. nervosa-AuNCs was 21.25%. The as-synthesized A. nervosa-AuNCs showed a good linear response with hexaconazole in the concentration range of 0.025-180μM, with a detection limit (LOD) of 21.94nM, indicating A. nervosa-AuNCs could be used as a sensitive and selective probe for detecting hexaconazole through a fluorescence "turn-off" mechanism. The A. nervosa-AuNCs were successfully used to detect hexaconazole in real samples. Moreover, A. nervosa-AuNCs were used as a bio-imaging probe for visualization of Saccharomyces cerevisiae cells.

Simplified analytical method for predicting the large deformation of stiffened plates with initial cracks under repeated impacts

The impact resistance capacity of structures can be affected by the formation of cracks. To address the issue of repeated impacts on structures with initial cracks, a relationship was established between cracks and the energy dissipation of stiffened plates based on rigid–plastic theory. A simplified analytical method was proposed to predict the large plastic deformation of stiffened plates with initial cracks. To verify the accuracy of the analytical method, repeated impact experiments and numerical simulations were conducted. The influences of crack length and position on the dynamic responses of stiffened plates were explored. The experimental, numerical, and analytical results were in good agreement. The research results showed that the permanent deformations of stiffened plates increases approximately linearly with increasing crack length on the outer plate. However, the influence of stiffener cracks on the permanent deformation of stiffened plates depends on whether the stiffener fractures. The influence of cracks on the load-carrying capacity of the structure is more pronounced when the crack is located in the stiffener.

Ultrasensitive Aptasensor for α-Amatoxin Detection Based on the DNA Tetrahedral Nanostructure Triggering Rolling Circle Amplification and Signal Amplification.

Poisonous mushrooms containing α-amatoxin can be lethal, making it imperative to develop a rapid and sensitive detection method for α-amatoxin. Utilizing the DNA tetrahedral structure as its foundation, the aptamer allows controlled density and orientation. Consequently, we designed aptamer tetrahedral functionalized magnetic beads that specifically target α-amanitin to release complementary DNA (C-DNA) strands. These strands were then employed as primers to initiate rolling circle amplification (RCA) with fluorescent dyes. The combination of SYBR Green I detection probes facilitated the amplification of the detection signal, enhancing the detection sensitivity of the aptasensor. The calculated detection limit was determined to be 3 ng/mL, a magnitude lower than that of other aptasensors by 2 orders of magnitude. The aptasensor integrates the advantages of high sensitivity and specificity, offering a simple and reliable rapid detection method for α-amanitin analysis.

A Green HPLC Approach to Florfenicol Analysis in Pig Urine.

Florfenicol (FF) is a broad-spectrum antibiotic used to treat gastrointestinal and respiratory infections in domestic animals. Considering FF's rapid elimination via urine after drug treatment, its use increases concerns about environmental contamination. The objective of the study was to establish a sustainable chromatographic method for simple analysis of FF in pig urine to investigate the urinary excretion of FF after a single intramuscular administration of 20 mg FF/kg body weight. The urine sample was prepared using a centrifuge and regenerated cellulose filter, and the diluted sample was analyzed. The method was validated in terms of linearity, the limit of detection (0.005 µg/mL) and quantitation (0.016 µg/mL), repeatability and matrix effect (%RSD ranged up to 2.5), accuracy (varied between 98% and 102%), and stability. The concentration-time profile of pig urine samples collected within 48 h post-drug administration showed that 63% of FF's dose was excreted. The developed method and previously published methods used to qualify FF in the urine of animal origin were evaluated by the National Environmental Method Index (NEMI), Green Analytical Procedure Index (GAPI) and Analytical GREENness Metric Approach (AGREE). The greenness profiles of published methods revealed problems with high solvents and energy consumption, while the established method was shown to be more environmentally friendly.

Spectrophotometric Determination of Selenium in Food Items

Selenium (Se) is an essential element that is obtained from food. To increase the level of selenium in the body, we should consume selenium-rich foods in our diet. The objective of this study was to develop a simple spectrophotometric method for the quantitative analysis of selenium present in food. This study included six food items such as broccoli, cabbage, red cabbage, fenugreek, garlic, and ginger. The new method is based on the yellow colour complex formed by the reaction between 2% potassium iodide and 0.2% pyridine in acidic medium with the selenium. Absorbance was measured at 400 nm against the reagent blank. The results of the above proposed method were compared with the reference method of using potassium iodide and starch as reagents. The selenium content in the examined food samples was determined from the regression equation of the calibration curve y= 0.0799x+0.3477 respectively. All the analyses were performed in triplicate, and the results are expressed as mean ± standard deviation. The highest mean selenium value was obtained in ginger and garlic 18.70 & 18.32 µg/g, respectively among all the studied samples, while the lowest value was in fenugreek seeds 7.38 µg/g. The proposed method is simple, rapid, sensitive, and obeys Beer–Lambert’s law. The proposed method was successfully applied to determine food items. Selenium has been quantitatively analysed for its potential to protect the body from many degenerative diseases. Selenium-rich food, as studied here, should be used as a supplement in the human diet.

New simple method for calculating large-strain consolidation settlement of layered soft soils with horizontal drains and vacuum preloading with comparison to test data

Prefabricated horizontal drains and vacuum preloading have advantages in the consolidation of ultra-soft dredged sludge and soils for maintenance dredging, reclamation, and ground improvement in coastal regions. While laboratory tests and field trial projects have been reported, a convenient analysis and design method is still unavailable. This study proposes a new simple method for the settlement analysis of soft soils considering horizontal drains, vacuum preloading, creep, and large-strain effects. A unified equation is constructed to account for various layouts of horizontal drains in consolidation. A new explicit method is developed to consider the large-strain deformation with the nonlinear evolution of permeability and compressibility of ultra-soft soils under vacuum preloading. The viscous compression is taken into account using a simplified Hypothesis B method. The proposed solution also facilitates convenient consideration of multiple layers of soils and drains subjected to staged loading. The proposed method is examined by a series of physical model tests with different horizontal drain dimensions. Finally, the method is applied in the analysis of two well-documented field cases in Hong Kong and Japan, which confirms its effectiveness and accuracy.

Development of a Novel Lightweight Utility Pole Using a New Hybrid Reinforced Composite—Part 1: Fabrication and Experimental Investigation

This paper is the first part of a two-part paper that discusses the development of a novel lightweight and cost-effective hybrid 3D composite material and its and utilization for constructing utility poles. The main objective was to generate a material/pole with a comparable performance to the commercially available poles made of 2D fiber-reinforced polymer (FRP) and examine its feasibility. The novel hybrid composite was configured using a recently developed and marketed 3D E-glass fabric–epoxy composite reinforced with wood dowels, referred to as 3D dowel-reinforced FRPs (3D-drFRPs) hereafter. Firstly, the compressive and flexural properties of the 3D-drFRPs are evaluated. Then, the development of the 3D pole is discussed followed by the fabrication details of two 3D-drFRPs using the standard test method, and their responses are compared. For the second part, robust finite element (FE) models were developed in an LS-DYNA environment and calibrated based on the experimental results. A sophisticated nonlinear FE model was used to simulate the performances of ASTM standard-size compression and three-point bending specimens and tapered 2D and prismatic 3D poles. Moreover, the responses of equivalent 2D and 3D poles were simulated numerically, as the task could not be accommodated experimentally due to our laboratory’s deficiencies. The integrity of the numerical simulation results was validated against experimental results, confirming the accuracy of the developed model. As an example, the stiffness values for the 3-pt bending specimens and the 3D poles obtained through the simulations were very close to the experimentally obtained results, with small margins of errors of 3.2% and 0.89%, respectively. Finally, a simplified analytical calculation method was developed so practicing engineers can determine the stiffnesses of 3D-DrFRP poles very accurately and quickly.

Differentiating the Yield of Chemical Reactions Using Parameters in First-Order Kinetic Equations to Identify Elementary Steps That Control the Reactivity from Complicated Reaction Path Networks.

The yield of a chemical reaction is obtained by solving its rate equation. This study introduces an approach for differentiating yields by utilizing the parameters of the rate equation, which is expressed as a first-order linear differential equation. The yield derivative for a specific pair of reactants and products is derived by mathematically expressing the rate constant matrix contraction method, which is a simple kinetic analysis method. The parameters of the rate equation are the Gibbs energies of the intermediates and transition states in the reaction path network used to formulate the rate equation. Thus, our approach for differentiating the yield allows a numerical evaluation of the contribution of energy variation to the yield for each intermediate and transition state in the reaction path network. In other words, a comparison of these values automatically extracts the factors affecting the yield from a complicated reaction path network consisting of numerous reaction paths and intermediates. This study verifies the behavior of the proposed approach through numerical experiments on the reaction path networks of a model system and the Rh-catalyzed hydroformylation reaction. Moreover, the possibility of using this approach for designing ligands in organometallic catalysts is discussed.

DAMPAK HARGA TANDAN BUAH SEGAR (TBS) TERHADAP KESEJAHTERAAN PETANI KELAPA SAWIT (Elaeis Guineensis Jacq) (Studi Kasus Di Koperasi Unit Desa Makarti Tama, Kecamatan Kamang Baru, Kabupaten Sijunjung)

ABSTRACTThis study aims to analyze fluctuations in the price of TBS on the walfare of elaeis guineenses jacq farmers in Markati Tama (KUD), Kamang Baru District, Sijunjung regency. The method used is a simple linear regression analysis method assisted by SPSS (Statistical Package For Social Science) 25 software, with a sample of 67 sample farmers. The result of this study indicate that : based on the test result for the coefficient of determinations, it was found that the price of elais guineenses jacq TBS had an effect of 87 %. This states that the price of elaies guineenses jacq TBS affect the level of walfare of farmer, especially oil plam farmers in KUD Markati Tama. Then the impact of fluktuations in the variabel price of Fresh Friut Bunches (TBS) on the walfare of elaeis guineenses jacq farmers which can be seen from the results of partial T-test with a t-count value of 32,054 > t-table 0.240, and a sig value of 0,000, then H0 = rejected so that there is a significant influence significant defference between the dependent variabel or price (variable X) with the dependent variabel of walfare (variable Y). Keywords : Elaies Guineenses Jacq Fresh Friut Bunch Price, Fresh friut Bunch Price Fluctuations, Walfare of Elaies Guineenses Jacq Farmers.

A Simplified Method of True Height Analysis to Estimate the Real Height of Sporadic E Layers

AbstractThe sporadic E (Es) layer virtual height and the ordinary wave critical frequency are routinely measured ionogram parameters, used to characterize the Es altitude occurrence and intensity. It has become common practice to take the real height to be about equal to by assuming that signal propagation delays in the E region plasma below the layer are small and can be neglected. Although this applies for nighttime, during daytime it may overestimate significantly. The present paper relies on true height analysis theory to devise a simplified method and propose an algorithm that can estimate Es real heights reasonably well. The method relies on and ionosonde measurements and E region electron density profiles obtained from the International Reference Ionosphere model. The algorithm is applied to a typical set of Digisonde observations to compute and examine real height variations and functional dependencies. Whereas ≃ at nighttime, during daytime there are notable − differences taking values less than 10 km for most of the observed layers. During the early morning and early afternoon hours, however, when weak layers appear at upper heights, the virtual to real height differences become larger reaching 20–25 km. The method proposed here for the estimation of can be easily applied to improve the accuracy of the results of sporadic E layer studies.

There's Something in What We Eat: An Overview on the Extraction Techniques and Chromatographic Analysis for PFAS Identification in Agri-Food Products.

Per- and polyfluorinated alkyl substances (PFASs) are a group of anthropogenic chemicals used in a range of industrial processes and consumer products. Recently, their ubiquitous presence in the environment as well as their toxicological effects in humans have gained relevant attention. Although the occurrence of PFASs is widely investigated in scientific community, the standardization of analytical method for all matrices still remains an important issue. In this review, we discussed extraction and detection methods in depth to evaluate the best procedures of PFAS identification in terms of analytical parameters (e.g., limits of detection (LODs), limits of quantification (LOQs), recoveries). Extraction approaches based on liquid-liquid extraction (LLE), alkaline digestion, and solid phase extraction (SPE), followed by liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS) analysis are the main analytical methods applied in the literature. The results showed detectable recoveries of PFOA and PFOS in meat, milk, vegetables, eggs products (90.6-101.2% and of 89.2-98.4%), and fish (96-108%). Furthermore, the low LOD and LOQ values obtained for meat (0.00592-0.01907 ng g-1; 0.050 ng g-1), milk (0.003-0.009 ng g-1; 0.010-0.027 ng g-1), fruit (0.002-0.009 ng g-1; 0.006-0.024 ng g-1), and fish (0.00369-0.017.33 ng g-1; 0.05 ng g-1) also confirmed the effectiveness of the recent quick, easy, cheap, effective, rugged, and safe method (QuEChERS) for simple, speedy, and sensitive ultra-trace PFAS analysis.

Properties of processing and data acquisition methods in test methods of chemical analysis

Chemical analysis is a crucial source of information for assessing the state of the environment, evaluating the human body condition, and serving as a diagnostic tool for detecting diseases and more. The use of simple, rapid, and cost-effective analysis methods without the need for specialized laboratory conditions and personnel with specific qualifications, such as test methods, contributes to the effective implementation of well-known techniques for analyzing the chemical composition of environmental objects and for use in the field of healthcare. Scanner indication of the analytical signal in chemical analysis is an objective, fast, and automated method for assessing the color characteristics of colored samples. The use of scanner indication in obtaining the analytical signal eliminates errors associated with subjective evaluation and assists individuals with color vision impairments, speeding up data collection and processing operations. Considering and controlling the light source in scanning systems is crucial to ensuring the stability and accuracy of obtained images under different lighting conditions. To obtain the analytical signal, it is primarily necessary to process the image to obtain the region of interest, which is determined by segmentation, manual methods, and using image processing techniques. The analysis of obtained values is carried out by constructing a linear or nonlinear relationship of color values in the selected color model converted to a single value of the analytical signal to concentration. Most existing systems for scanner detection of the analytical signal in analytical test methods require human involvement in obtaining and interpreting results, limiting the application areas of these methods of analytical signal indication. Further research is focused on creating a reliable method for obtaining the analytical signal using a smartphone camera based on image processing techniques, allowing for the automation of obtaining, processing, and improving the reproducibility of results in chemical test analyses.

Relationships Between Partial Milk Yield and Actual Milk Yield According to Parity in Buffaloes

In this study, the relationships between 100-day of partial milk yield and 270-day of additive and total milk yield of buffaloes according to different parity were investigated. A total of 697 lactation records belonging to 135 heads of buffalo and seven lactations were used in the material. The relationships between the animals' 100-day partial milk yield for 270-day and total milk yield were analyzed for seven lactations. In the study, 100-day milk yield was taken as an independent variable, 270-day and total milk yields as dependent variables, and possible relationships were determined according to simple and multiple linear regression analysis methods. The average lactation period was 256.74 ± 2.61 days, the average 270-day additive milk yield was 2078 ± 65.26 litres and the average total milk yield was 1831 ± 89.57 litres. The daily average milk yields were 7.69 ± 0.11 and 7.08 ± 0.07 liters for 270-day and 100-day respectively. The correlation coefficients were calculated for each parity and calculated as 0.901 (p < 0.01) between the 100-day and 270-day additive yield for the general group. The simple and multiple linear regression equations were shown as [V270 = 470.72 + 1.737 V100 (R2 = 80.2%)], [V270 = 966.23 + 0.645 V100 + 0.001V1002 (R2 = 82.4%)] for the groups. As the parity of lactation increased, it was seen that the determination coefficients were increased. Finally, predicting the total lactation yield by using 100-day of partial milk yield has the highest accuracy.

Correction to: Simplified dynamic characteristic analysis method for parallel manipulators with flexure hinges

Correction to: Simplified dynamic characteristic analysis method for parallel manipulators with flexure hinges