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Aims: The initial bundle of cares strongly affects haemodynamics and outcomes in acute decompensated heart failure cardiogenic shock (ADHF‐CS). We sought to characterize whether 24 h haemodynamic profiling provides superior prognostic information as compared with admission assessment and which haemodynamic parameters best predict in‐hospital death. Methods and results: All patients with ADHF‐CS and with available admission and 24 h invasive haemodynamic assessment from two academic institutions were considered for this study. The primary endpoint was in‐hospital death. Regression analyses were run to identify relevant predictors of study outcome. We included 127 ADHF‐CS patients [65 (inter‐quartile range 52–72) years, 25.2% female]. Overall, in‐hospital mortality occurred in 26.8%. Non‐survivors were older, with greater CS severity. Among admission variables, age [odds ratio (OR) = 1.06; 95% confidence interval (CI): 1.02–1.11; Padj = 0.005] and CPIRAP (OR = 0.62 for 0.1 increment; 95% CI: 0.39–0.95; Padj = 0.034) were found significantly associated with in‐hospital death. Among 24 h haemodynamic univariate predictors of in‐hospital death, pulmonary elastance (PaE) was the strongest (area under the curve of 0.77; 95% CI: 0.68–0.86). PaE (OR = 5.98; 95% CI: 2.29–17.48; Padj < 0.001), pulmonary artery pulsatility index (PAPi, OR = 0.77; 95% CI: 0.62–0.92; Padj = 0.013) and age (OR = 1.06; 95% CI: 1.02–1.11; Padj = 0.010) were independently associated with in‐hospital death. Best cut‐off for PaE was 0.85 mmHg/mL and for PAPi was 2.95; cohort phenotyping based on these PaE and PAPi thresholds further increased in‐hospital death risk stratification; patients with 24 h high PaE and low PAPi exhibited the highest in‐hospital mortality (56.2%). Conclusions: Pulmonary artery elastance has been found to be the most powerful 24 h haemodynamic predictor of in‐hospital death in patients with ADHF‐CS. Age, 24 h PaE, and PAPi are independently associated with hospital mortality. PaE captures ventricular (RV) afterload mismatch and PAPi provides a metric of RV adaptation, thus their combination generates four distinct haemodynamic phenotypes, enhancing in‐hospital death risk stratification. [ABSTRACT FROM AUTHOR]

The Federal Open Market Committee (FOMC) is a component of the Federal Reserve System responsible for overseeing open market operations. The FOMC meets roughly eight or more times per year to assess the economy of the United States. After each meeting, the FOMC releases a statement to the press outlining its assessment of the US economy and its monetary policy stance. The sentiment of these statements may have an influence on the US economy and financial markets. Using sentiment and correlational analyses, this research examines how the sentiment of these statements affects the US economy and financial markets by analyzing how FOMC statement sentiment is correlated with the Consumer Price Index (CPI), the National Financial Conditions Index (NFCI), and the Adjusted National Financial Conditions Index (ANFCI). We find evidence to suggest that there is a moderate negative correlation between an FOMC statement's sentiment and the US City Average CPI value associated with the month before and the month after the statement's release. We also find that there is no evidence to suggest there exists a correlation between an FOMC statement's sentiment and the NFCI value associated with the week before or the week after the statement's release. However, we do find evidence to suggest that there is a moderate negative correlation between an FOMC statement's sentiment and the ANFCI value associated with the week before and the week after the statement's release. We also found that out of the three models we tested (linear regression, vine copula regression, and Gaussian copula regression), the Gaussian copula regression model performs the best when forecasting the CPI and the ANFCI. Additionally, we find that when forecasting CPI values, the models that include FOMC statement sentiment are more accurate than the models that exclude FOMC statement sentiment. [ABSTRACT FROM AUTHOR]

Abstract Aims The initial bundle of cares strongly affects haemodynamics and outcomes in acute decompensated heart failure cardiogenic shock (ADHF‐CS). We sought to characterize whether 24 h haemodynamic profiling provides superior prognostic information as compared with admission assessment and which haemodynamic parameters best predict in‐hospital death. Methods and results All patients with ADHF‐CS and with available admission and 24 h invasive haemodynamic assessment from two academic institutions were considered for this study. The primary endpoint was in‐hospital death. Regression analyses were run to identify relevant predictors of study outcome. We included 127 ADHF‐CS patients [65 (inter‐quartile range 52–72) years, 25.2% female]. Overall, in‐hospital mortality occurred in 26.8%. Non‐survivors were older, with greater CS severity. Among admission variables, age [odds ratio (OR) = 1.06; 95% confidence interval (CI): 1.02–1.11; Padj = 0.005] and CPIRAP (OR = 0.62 for 0.1 increment; 95% CI: 0.39–0.95; Padj = 0.034) were found significantly associated with in‐hospital death. Among 24 h haemodynamic univariate predictors of in‐hospital death, pulmonary elastance (PaE) was the strongest (area under the curve of 0.77; 95% CI: 0.68–0.86). PaE (OR = 5.98; 95% CI: 2.29–17.48; Padj

In the era of rapid technological progress, the influence of dizitalization on different aspects of international economic activity can’t be overstated. The aim of this article is to conduct a comprehensive comparative study of digitalization’s impact on global goods and services markets, with a specific focus on advanced and developing economies using multiple linear regression. The research methodology involved comprehensive data collection for 35-38 advanced economies and 52-66 developing economies depending on the availability of data. The analysis included depended variables (18 export and import goods sectors and 18 export and import services), independent variables (digitalization, consisting of ICT deployment, ICT export and import, ICT investment variables), control variables such as GDP growth, CPI, trade openness, exchange rate and political stability. The findings demonstrate the ICT infrastructure and ICT exports positive impact on export of technology-intensive goods, such as ores and metals, machinery and equipment, and tools and devices in advanced economies. Digitalization’s positive impact on trade in goods appeared weaker in developing economies, potentially due to lower levels of ICT adoption or differing export focuses. ICT export has positive impact on financial services imports, indicating a reliance on imported financial services while exporting ICT capabilities. The model shows a high success rate depending on variables. The study highlights digitalization’s varied impact on advanced and developing economies, emphasizing its importance for trade, competitiveness and policymakers in the global market.

Copyright of International Journal of Social Sciences (IJSS) / Uluslararasi Sosyal Bilimler Dergisi is the property of International Journal of Social Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Rudrasagar Lake, a vital habitat for diverse flora and fauna, supports over 2000 households to sustain their daily livelihoods. The current study attempts to examine the impact of human activities on spatio-temporal variation in the water quality of the study area. The study integrates extensive field surveys, sample processing, and statistical analysis to assess the recent status of wetland health. Latin Square Matrix (LSM) was employed to select the sampling sites while the Inverse Distance Weighting (IDW) interpolation technique was used for spatial variation mapping. Modified Weighted Arithmetic Water Quality Index (MWAWQI) and Comprehensive Pollution Index (CPI) were utilized for assessing seasonal variation water quality and pollution loads, respectively. The results showed that dissolved oxygen (DO) was strongly influenced by the tributaries, and recreational activities have substantially influenced the highest concentrations of biochemical oxygen demand (BOD), and total suspended solids (TSS). The central portion of the lake is particularly susceptible to pollution from extensive fishing and recreational activities while peripheral sites are strongly influenced by agricultural run-offs, seepages from brick industries, and municipal wastes characterized by high concentrations of pH, total hardness (TH), oxidation–reduction potential (ORP). The findings reveal remarkable spatio-temporal fluctuations and highlight the areas within the lake susceptible to anthropogenic activities. The study proposed a sustainable management model to ameliorate anthropogenic threats. Moreover, the study contributes to the scientific understanding of the challenges and ensures the long-term viability of wetland health as a vital ecological and socio-economic resource. [ABSTRACT FROM AUTHOR]

The standard of care for non-metastatic renal cancer is surgical resection followed by adjuvant therapy for those at high risk for recurrences. However, for older patients, surgery may not be an option due to the high risk of complications which may result in death. In the past renal cancer was considered to be radio-resistant, and required a higher dose of radiation leading to excessive complications secondary to damage of the normal organs surrounding the cancer. Advances in radiotherapy technique such as stereotactic body radiotherapy (SBRT) has led to the delivery of a tumoricidal dose of radiation with minimal damage to the normal tissue. Excellent local control and survival have been reported for selective patients with small tumors following SBRT. However, for patients with poor prognostic factors such as large tumor size and aggressive histology, there was a higher rate of loco-regional recurrences and distant metastases. Those tumors frequently carry program death ligand 1 (PDL1) which makes them an ideal target for immunotherapy with check point inhibitors (CPI). Given the synergy between radiotherapy and immunotherapy, we propose an algorithm combining CPI and SBRT for older patients with nonmetastatic renal cancer who are not candidates for surgical resection or decline nephrectomy. [ABSTRACT FROM AUTHOR]

The seasonal water quality of the Surajpur wetland was analysed using 13 physicochemical parameters, including pH, TDS, EC, temperature, total hardness, total alkalinity, DO, BOD, phosphate, fluoride, nitrate, sulphate, and chloride employing standardized procedures. Fifteen samples were collected in triplicate from five distinct locations within the wetland. These samples were then compared to the BIS and WHO standards (2012). The analysis used titrimetric techniques to determine DO, BOD, total hardness, total alkalinity, and chlorides. Moreover, phosphate, sulphate, and nitrate were determined through UV-spectrophotometry. The wetland has an alkaline nature, the hydrogeochemical facies that dominate the surface water are Ca2+, Mg2+, HCO3, and Cl−. The results indicate that TDS, total alkalinity, phosphates, and fluorides exceeded the permissible limits. The evaluation of water quality in the study area was conducted through the implementation of the standard Water Quality Index (WQI), the Canadian Council of Ministers of the Environment Water Quality Index-(CCME-WQI) and the Comprehensive Pollution Index (CPI) and their associated parameters.. The CCME-WQI ranges from 46 to 53, indicating very poor/marginal water quality, the WQI value ranges from 82.80 to 96.18, indicating good water quality, while the CPI ranges from 0.9 to 1.15, indicating very poor/marginal water quality. The pH-EC and pH-TA, TDS-CPI, Cl-TH and the WQI-PO43− are negatively correlated at a significance level p < 0.01. The TA-EC, BOD-DO and TA-PO43− are negatively correlated at a significance level p < 0.05 as per the correlation matrix result. Using hierarchical cluster analysis, 5 sampling sites were divided into two clusters based on the similarity of water quality characteristics: comparatively less polluted and more polluted sites. The four principal components were identified using PCA, principal components contribute to 46.02%, 223.48%, 19.38% and 11.11%, of the total variance of the dataset respectively. The PCA indicate that the variation in water quality is due to anthropogenic activities around the vicinity of the wetland. In order to preserve the wetland's aesthetic value and ecological health, preventive measures such as de-weeding, preventing the infiltration of untreated sewage, and desilting are advised. Incorporating these measures can prevent potential damage to the wetland and ensure the survival of its ecology and aesthetic value. [ABSTRACT FROM AUTHOR]

ABSTRACTBispecific antibodies (bsAbs) are a class of antibodies that can mediate novel mechanisms of action compared to monospecific monoclonal antibodies (mAbs). Since the discovery of mAbs and their adoption as therapeutic agents in the 1980s and 1990s, the development of bsAbs has held substantial appeal. Nevertheless, only three bsAbs (catumaxomab, blinatumomab, emicizumab) were approved through the end of 2020. However, since then, 11 bsAbs received regulatory agency approvals, of which nine (amivantamab, tebentafusp, mosunetuzumab, cadonilimab, teclistamab, glofitamab, epcoritamab, talquetamab, elranatamab) were approved for the treatment of cancer and two (faricimab, ozoralizumab) in non-oncology indications. Notably, of the 13 currently approved bsAbs, two, emicizumab and faricimab, have achieved blockbuster status, showing the promise of this novel class of therapeutics. In the 2020s, the approval of additional bsAbs can be expected in hematological malignancies, solid tumors and non-oncology indications, establishing bsAbs as essential part of the therapeutic armamentarium.

Simple Summary: The low developmental efficiency of cloned pig embryos limits the application of the pig cloning technique. In this study, a small molecule drug called CPI was added to the culture medium of nuclear donor cells to enhance the developmental capacity of subsequent cloned pig embryos. CPI treatment of nuclear donor cells changed the cellular energy metabolism status from oxidative phosphorylation to glycolysis, and significantly improved the developmental competence of subsequent cloned pig embryos. This study provides a simple approach to facilitate the development and application of pig cloning technology. Somatic cell nuclear transfer (SCNT) technology holds great promise for livestock industry, life science and human biomedicine. However, the development and application of this technology is limited by the low developmental potential of SCNT embryos. The developmental competence of cloned embryos is influenced by the energy metabolic status of donor cells. The purpose of this study was to investigate the effects of CPI, an oxidative phosphorylation inhibitor, on the energy metabolism pathways of pig fibroblasts and the development of subsequent SCNT embryos. The results showed that treatment of porcine fibroblasts with CPI changed the cellular energy metabolic pathways from oxidative phosphorylation to glycolysis and enhanced the developmental ability of subsequent SCNT embryos. The present study establishes a simple, new way to improve pig cloning efficiency, helping to promote the development and application of pig SCNT technology. [ABSTRACT FROM AUTHOR]

Abu-Roash-F member (Mb) represents one of the main carbonate source rocks in different oil basins in Egypt that belong to the Upper Cretaceous (Cenomanian) age. Investigated gas chromatograms of five extracted (OM) organic matter samples belonging to the Abu-Roash-F Mb from drilled WON-C-3X borehole, of the Beni-Suef basin, reveal the OM (organic matter) mainly comprising an admixture of the algae and microorganisms of short-chain n-alkanes (average; 37.64%) with sphagnum moss and macrophytes of a mid-chain n-alkanes (average; 24.3%). The investigated Abu-Roash-F Mb in the present study preferred to nominate based on their OM constituents as an algal limestone source rock. The CPI (carbon performance index) of values between 0.88 and 0.92 (average; 0.92) indicates a mature stage of the studied Mb. The average value of the NAR (natural n-alkane) that is close to zero of (0.04) is attributed to petroleum sources. The low values of TAR (terrigenous/aquatic ratio) of average (0.13) and Paq (aquatic macrophyte proxy) of average (0.69) are an indication of the dominance of submerged and floating plants. The n-C27/n-C17 ratio has a value range of 0.31 and 0.34 (average; 0.33) demonstrating the OM affiliation to marine origin. Redox potential was suggested based on Pr/Ph ratios that range from 1.14 to 1.26 (average; 1.22) demonstrating the dysoxic and suboxic of the aqueous depositional medium. The Pr/n-C17 versus Ph/n-C18 diagram illustrates that the kerogen types of the studied samples were a mixture of type II and II/III. It also referred to the deposition that took place within a transitional marine environment of an aquatic coastal setting. A combination of the ACL proxy (average; 27.94) of a moderate value with a low percentage of verylong- chains (average; 3.12%) may suggest the dominance of the grass plants under temperate to cooler paleoclimate synchronizes the deposition environments of the studied Abu-Roash-F Mb. [ABSTRACT FROM AUTHOR]

Copyright of Akademik Hassasiyetler is the property of Huzeyfe Suleyman Arslan and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Flexible OLED displays have become a development trend. CPI film in a flexible panel can improve the bending performance of the panel. However, CPI film is prone to plastic deformation in the bending process, which will affect the reliability and service life of OLED panel. Finite element analysis is employed in this paper to analyze how CPI film affects the bending performance of a flexible OLED panel. The simulation results show that the optimization of the structure of water‐drop‐shaped bending can improve the plastic deformation of CPI film. The reasonable position of CPI film in the stacked structure can also improve its plastic deformation. The increase of the thickness of the OCA located below the CPI film can significantly reduce its plastic deformation. The analysis method used in this paper can help improve the bending performance of a flexible OLED panel. [ABSTRACT FROM AUTHOR]

Copyright of Acta Scientiarum Polonorum. Oeconomia is the property of Wydawnictwo SGGW and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The standard of care for locally advanced rectal cancer is total neoadjuvant therapy followed by surgical resection. Current evidence suggests that selected patients may be able to delay or avoid surgery without affecting survival rates if they achieve a complete clinical response (CCR). However, for older cancer patients who are too frail for surgery or decline the surgical procedure, local recurrence may lead to a deterioration of patient quality of life. Thus, for clinicians, a treatment algorithm which is well tolerated and may improve CCR in older and frail patients with rectal cancer may improve the potential for prolonged remission and potential cure. Recently, immunotherapy with check point inhibitors (CPI) is a promising treatment in selected patients with high expression of program death ligands receptor 1 (PD- L1). Radiotherapy may enhance PD-L1 expression in rectal cancer and may improve response rate to immunotherapy. We propose an algorithm combining immunotherapy and radiotherapy for older patients with locally advanced rectal cancer who are too frail for surgery or who decline surgery. [ABSTRACT FROM AUTHOR]

Due to outdated weighting information, a Laspeyres‐based consumer price index (CPI) is prone to accumulating upward bias. Therefore, the present study introduces and examines simple and transparent revision approaches that retrospectively address the source of the bias. They provide a consistent long‐run time series of the CPI and require no additional information. Furthermore, a coherent decomposition of the bias into the contributions of individual product groups is developed. In a case study, the approaches are applied to a Laspeyres‐based CPI. The empirical results confirm the theoretical predictions. The proposed revision approaches are adoptable not only to most national CPIs but also to other price‐level measures such as the producer price index or the import and export price indices. [ABSTRACT FROM AUTHOR]

Background and Aim: Periodontal disease may result in chronic inflammation and bacteremia in some people. The study aimed to evaluate the connection between periodontal disease and macular degeneration. Materials and Methods: The specialist dental surgeon conducted the dental examination using a community periodontal index probe. An ophthalmologist performed the eye examination. Age-related macular degeneration (AMD) was identified through specific criteria such as the existence of particular types of drusen and pigmentary abnormalities. Results: Two hundred participants were part of the study. According to the data, factors such as advanced age, limited education, low income, hypertension, cardiovascular disease (CVD), and hepatitis B surface antigen (HBsAg) presence were strongly linked to AMD in all participants. Conclusion: Multiple studies have indicated a connection between periodontitis in the mouth and macular degeneration in individuals under 60 years of age.

The study aims to establish the relationship between the level of digitalization of the national economy and the success of the state’s anti-corruption policy. Clarification of the current methods of quantifying corruption has shown that nowadays the only relevant index reflecting the national corruption indicator is CPI. Based on the analysis of its values for 2018–2022, the leaders among European and Asian countries – Denmark and Singapore – were identified, with which a comparative analysis of the digitalization of Russia’s national economy was conducted using the Digital Evolution scorecard. The results showed that the anti-corruption policies of countries that have completed digitalization or are actively pursuing it are the most successful. This suggests that the digitalization of the national economy is one of the key conditions for increasing the effectiveness of anti-corruption policy. In confirmation, the positive effect of the influence of the national economy’s digitalization on the socio-economic system as a whole and a number of groups of factors that lead to the emergence of corruption were noted.

The determination of prices for goods and services in a specific economy is significantly influenced by commodity prices and the distribution of energy. Hence, this study aims to examine the impact of fuel prices and electricity supply on the inflation rate in South Africa. The empirical analysis focuses on a time series data covering the period from January 2009 to December 2021. The study utilizes the Johansen test for cointegration, Vector Error Correction Model (VECM), and Granger approaches to establish the relationship between the variables. The empirical findings indicate the existence of a long-term relationship among the variables, indicating that long-term changes in electricity supply and fuel prices have an influence on South Africa's inflation levels. Similarly, the short-term results suggest an inverse relationship between fuel prices, electricity supply, and the inflation rate. In order to reduce the inflation rate, it is recommended to decrease spending on imported fuel and enhance electricity supply through increased investment in renewable energy and research and development (R and D).

The research aims to show the relationship between the consumer price index (CPI) and inflation on the BI7DRR level. This research uses a quantitative descriptive approach. The data used in this research analysis is secondary data. The population in this study is all Indonesian CPI, inflation, and BI7DRR time series data. The sampling technique for this research uses purposive sampling, namely time series data on CPI, inflation, and Indonesia's BI7DRR from January 2020 to June 2023. The research results show that the CPI has an insignificant negative effect on BI7DRR. Inflation has a significant positive effect on BI7DRR. CPI and inflation have a significant effect on BI7DRR. The results of this research can be used to determine the relationship between CPI and inflation about BI7DR and to decide actions that the government can take to determine monetary policy to stabilize prices.

The Gökova Bay declared as Private Environment Protection Area (PEPA) in Turkey in 1989, where freshwater and seawater ecosystems are intertwined, is an important area that possesses high biodiversity. In the study, the water quality index (WQI), comprehensive pollution index (CPI) were used to determine the water quality and pollution of freshwater sources affecting the Gökova Bay. The water quality parameters were measured for each freshwater at both the dry and rainy seasons and all statistical analyses were carried out for each season, separately. Firstly, factor analysis was performed to determine the correlated water quality parameters and to collect correlated parameters under the common factors. The different factors were obtained from the dry and rainy seasons. This shows that the study area is fed by different water sources in the wet season and that the main factor affecting the area in the dry season is anthropogenic sources. The stations were statistically compared according to the factors. The relationships between the factors and WQI and CPI were investigated and lastly regression models between the factors and WQI and CPI were predicted. The results showed that the water quality parameters deteriorated in all the freshwater sources especially in dry seasons. A thematic map of each water quality and pollution index was developed in Geographic Information Systems (GIS). This study indicates that CPI can be used especially together with GIS as a useful tool for the evaluation of water quality and pollution. [ABSTRACT FROM AUTHOR]

While the relationships between cardiovascular disease (CVD), stress, and financial strain are well studied, the association between recessionary periods and macroeconomic conditions on incidence of disease-specific CVD emergency department (ED) visits is not well established. This retrospective observational study aimed to assess the relationship between macroeconomic trends and CVD ED visits. This study uses data from the National Hospital Ambulatory Care Survey (NHAMCS), Federal Reserve Economic Database (FRED), National Bureau of Economic Research (NBER), and CVD groupings from National Vital Statistics (NVS) and Center for Medicare and Medicaid Services (CMS) from 1999 to 2020 to analyze ED visits in relation to macroeconomic indicators and NBER defined recessions and expansions. CVD ED visits grew by 79.7% from 1999 to 2020, significantly more than total ED visits (27.8%, p < 0.001). A national estimate of 213.2 million CVD ED visits, with 22.9 million visits in economic recessions were analyzed. A secondary group including a 6-month period before and after each recession (defined as a "broadened recession") was also analyzed to account for potential leading and lagging effects of the recession, with a total of 50.0 million visits. A significantly higher proportion of CVD ED visits related to heart failure (HF) and other acute ischemic heart diseases (IHD) was observed during recessionary time periods both directly and with a 6-month lead and lag (p < 0.05). The proportion of aortic aneurysm and dissection (AAA) and atherosclerosis (ASVD) ED visits was significantly higher (p = 0.024) in the recession period with a 6-month lead and lag. When controlled for common demographic factors, economic approximations of recession such as the CPI, federal funds rate, and real disposable income were significantly associated with increased CVD ED visits. Macroeconomic trends have a significant relationship with the overall mix of CVD ED visits and represent an understudied social determinant of health. [ABSTRACT FROM AUTHOR]

Using a multisectoral model and data from the supply and use tables, this article estimates the exchange-rate pass-through to the domestic price level of the Turkish economy. The results indicate that a unit change in the exchange rate leads to 0.61 units of change in the overall price level. This effect comes out mostly through the industry, and the primary sector; while in terms of products, the energy sector is the major actor for the changes in the domestic price level. [ABSTRACT FROM AUTHOR]

While the Consumer Price Index (CPI) has its flaws, I chose to analyze it rather than any other data because it is an essential component for both businesses and consumers to make informed economic decisions as it indicates the change in consumers purchasing power. It is a standard used to guide nationwide economic decisions of government, business, labor, and private citizens. This paper assesses how well ARIMA models perform in different economic regimes to give a historical factor to these functions. This is important because if one uses an ARIMA model to make forecasts, one needs to be aware of how it behaves in different market conditions. This is not a prediction, as the cluster year is required beforehand. This paper investigates different economic regimes using autoregressive integrated moving average (ARIMA) models and a K-means clustering model. In this paper, I utilized the K-means model to first identify clusters of similar years of data. Then, I was able to apply that information to the ARIMA model to compare actual and predicted economic data for similar years (determined by the K-means clustering). The reason for applying this model to years with the same cluster label was to avoid massive fluctuations in economic data across an expansive range of years (1922 to 2022) that might have confused the model. [ABSTRACT FROM AUTHOR]

The food sector is one of the areas that causes a continuous increase in the general price level in the economy. Therefore, it is important to determine the reasons for food inflation, which lead to such increases. The aim of this study is to identify the determinants of food inflation for the Turkish economy. According to the results obtained from the Autoregressive Distributed Lag (ARDL)model using monthly data for the period 2016:M1-2022:M8, the Consumer Price Index for Food and Non-Alcoholic Beverages, which is the dependent variable, is positively affected by the Domestic Producer Price Index for Agriculture, Forestry and, Fishing and the Consumer Price Index for Electricity, Gas, and Other Fuels on the other hand, the Consumer Price Index-Based Real Effective Exchange Rate has a negative impact. Moreover, according to the results of the ARDL Error Correction Model, which analyzes the short-run relationship between the variables, the imbalance that occurs in the short run disappears in the long run. [ABSTRACT FROM AUTHOR]

One of the crucial jobs of central banks is to rein in inflation as it creates uncertainty in the economy and in private investment and ultimately negatively impacts the economy. If the source of inflation is positive demand shock, then raising the federal funds rate target is the right way to rein in inflation. If the source of inflation is negative supply shock, then raising the federal funds rate target will make things worse. In this study, the impact of FFR (federal funds rate) on CPI (consumer price index) and producer price index (PPI) is examined. Findings indicate that raising the federal funds rate will have a negative impact on both CPI and PPI with a 2-period lag. The possible explanation of this finding is that raising federal funds rate lowers aggregate demand, lowers the price level and thereby the CPI. And when CPI falls, it lowers perunit profit, prompting producers to cut supply, which in turn lowers the demand for producer goods and services, and thereby lowers PPI. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Economic Policy Researches / İktisat Politikası Araştırmaları Dergisi is the property of Journal of Economic Policy Researches / Iktisat Politikasi Arastirmalari Dergisi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The aim of the article is to construct an optimal SARIMA model for short-term conditional forecasting (projection) of price dynamics expressed by the Consumer Price Index (CPI), as understood within the extended Box-Jenkins procedure. The construction of such a forecast aims to influence, through the expectations channel, the institutional trust of society in monetary authorities and assess the effectiveness of achieving the monetary policy goal within the framework of the democratic responsibility of the decision-making body of the National Bank of Poland – the Monetary Policy Council. The selection of the optimal SARIMA model was carried out using an iterative method within the BoxJenkins procedure, with the goal of reducing the systematic bias of estimators – coherence with empirical data. The analysis was conducted on compiled secondary data of the monthly Consumer Price Index for goods and services from Statistics Poland (formerly: Central Statistical Office) for the years 2010-2023 (on a monthly basis). Results show that the short-term forecast demonstrated accuracy within a specified confidence interval. The application of the SARIMA model serves as a useful methodological tool for constructing elaborate DSGE models (for example, the NECMOD model) using procedures such as SEM (System for Averaging Models) from Norges Bank. [ABSTRACT FROM AUTHOR]

Copyright of Lex Humana is the property of Lex Humana and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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The standard of care for non-metastatic renal cancer is surgical resection followed by adjuvant therapy for those at high risk for recurrences. However, for older patients, surgery may not be an option due to the high risk of complications which may result in death. In the past renal cancer was considered to be radio-resistant, and required a higher dose of radiation leading to excessive complications secondary to damage of the normal organs surrounding the cancer. Advances in radiotherapy technique such as stereotactic body radiotherapy (SBRT) has led to the delivery of a tumoricidal dose of radiation with minimal damage to the normal tissue. Excellent local control and survival have been reported for selective patients with small tumors following SBRT. However, for patients with poor prognostic factors such as large tumor size and aggressive histology, there was a higher rate of loco-regional recurrences and distant metastases. Those tumors frequently carry program death ligand 1 (PD-L1) which makes them an ideal target for immunotherapy with check point inhibitors (CPI). Given the synergy between radiotherapy and immunotherapy, we propose an algorithm combining CPI and SBRT for older patients with non-metastatic renal cancer who are not candidates for surgical resection or decline nephrectomy.

Cel artykułu/hipoteza: Celem artykułu jest przedstawienie i analiza postrzegania inflacji i wiedzy na jej temat, a także metod ochrony studentów przed jej negatywnymi skutkami. Metodyka: Praca zawiera przegląd literatury w temacie współczesnej inflacji oraz analizę badania naukowego o tytule „Postrzeganie inflacji oraz metody ochrony studentów przed jej negatywnymi skutkami”. Badanie zostało przeprowadzone metodą CAWI na próbie 329 respondentów. Próba była losowa. Wyniki/Rezultaty badania: Analiza przeprowadzonego badania wykazała, że studenci, mimo iż orientują się w obecnej sytuacji inflacyjnej, to słabo rozumieją samo zjawisko. Aby zabezpieczyć się przed negatywnymi skutkami inflacji, stosują różne powszechnie znane metody, takie jak zwracanie uwagi na wydatki, oszczędzanie energii, a także wszelkiego rodzaju inwestycje. Jednakże nie wszyscy starają się uchronić swoje oszczędności przed negatywnymi skutkami inflacji. Działania części ankietowanych uzależnione są od wyższych wartości wskaźnika CPI. Organy publiczne odpowiedzialne za przeciwdziałanie wzrostu cen oraz łagodzenie negatywnych skutków tego zjawiska nie cieszą się zaufaniem studentów. Lecz mimo świadomości na temat destrukcyjnego wpływu wysokiej inflacji na swoje oszczędności oraz na cały obrót gospodarczy, część studentów jest świadoma pozytywnych skutków, jakie niesie ze sobą kontrolowana inflacja.

Abstract Background Inflation is the industrious and non-stop ascent in the overall prices of any given commodity in an economy. During the global food crisis, Ethiopia experienced an unprecedented increase in inflation ranked the highest in Africa. It is among the most macroeconomic variable described nonlinear behavior. Objective The main purpose of this study was intended to modeling inflation rate factors on present consumption price index (CPI) in Ethiopia: using the threshold autoregressive (TAR) models. Methods The study was utilized the secondary data collected from monthly data of CPI for inflation rate from January 1994 to December 2020 which was obtained from central statistical Agency. The forecast was applied between the nonlinear and linear ARMA models using different techniques. The unit root test of Dickey–Fuller test was made for each variables and applied lag length transformation for the variables that had unit root. A threshold autoregressive models was utilized for data handling technique using least square estimation. Results The results showed that monthly rate of inflation was characterized a non-constant mean and an unstable variance. The outcome of Tsay tests was revealed that non linearity of CPI and SETAR(2,4,4) had the smallest value of AIC under this study. The forecasting performance comparison results were showed that the nonlinear SETAR model outperform the linear ARMA models. Moreover, the out-of-sample forecast indicates that the CPI of inflation has almost a constant trend. The in-sample forecast using the best-fit asymmetric for the SETAR(2,4,4) model the CPI series exhibits an upward trade until 2012; decreases until 2011; slightly increase up to 2018 and then decrease at the end of the study period. Conclusion The superiority in performance of nonlinear models was attributed to their ability to capture the stochastic nature of the monthly rates as evident in the pattern of the forecast errors. The investigators are recommended that using TAR models policy makers can be able to capture the price volatility persistence and also forecasting can be made.

Consumer price index (CPI) is a socioeconomic statistic that tracks changes over time in the average price of consumer goods and services such as household purchases of fuel, transportation, food and so on that consumers buy, use, or pay for. The purchasing power of everyone is impacted by rising costs, especially if salaries stay the same. Our ability to purchase more things with our TZS reduces when the CPI increases more quickly than earnings, which has an impact on our cost of living. The aim of this study is to use the CPI monthly data from IMF website for the period from Jan 2010 to Dec 2022 to develop a forecasting model by using Holt Winter’s approach. Holt Winter's model based on four equations and popularly known as Triple exponential smoothing is commonly used in forecasting data with trends and seasonality. Holt Winter’s model is composed of four equations relating to level, trend, seasonal and forecast. The results revealed that the Holt winter’s model with smoothing parameters, 0.9 for level, 0.12 for trend, and 0.03 for seasonal was the best model in forecasting Consumer Price Index. The CPI for Tanzania is predicted for the next eighteen months and it has been observed that the trend of CPI is likely to increase in the next eighteen months.

People must be well-informed on market swings in today's difficult economic times in order to cut excessive spending. Rising expenditures in a variety of sectors, including business, education, and healthcare can be burdensome for consumers, and accurate forecasting of household is necessary given the current technological innovation. The Consumer Price Index (CPI) is one of the statistical indicators used to estimate the changes in prices for commodities. Forecasting CPI can assist individuals in developing a plan for making decisions on their daily consumption. This study seeks to develop a SARIMA model for forecasting consumer price indices (CPI) in Tanzania by using data collected from International Monetary Fund (IMF) website from January 2010 to December 2022. Data were evaluated using time series methods such as time plots and stationarity tests. It was discovered that there is seasonality in the CPI index. However, a serial correlogram test was performed using a residual correlogram after which the variable was estimated using the SARIMA model and SARIMA (0, 1, 0) (1, 1, 1)12 was fitted to the time series variable. The residual analysis was explored and because almost all correlations are zero, the SARIMA (1,1,1) (0,1,2)12 model was appropriate for forecasting CPI index in Tanzania. Consumer price index was predicted for the next eighteen months and it has been observed that the trend of CPI is likely to increase in the next eighteen months.