Average Monthly Research Articles

A Quality Improvement Project to Reduce Rapid Response System Inequities for Patients with Limited English Proficiency at a Quaternary Academic Medical Center.

Recognition of clinically deteriorating hospitalized patients with activation of rapid response (RR) systems can prevent patient harm. Patients with limited English proficiency (LEP), however, experience less benefit from RR systems than do their English-speaking counterparts. To improve outcomes among hospitalized LEP patients experiencing clinical deteriorations. Quasi-experimental pre-post design using quality improvement (QI) statistics. All adult hospitalized non-intensive care patients with LEP who were admitted to a large academic medical center from May 2021 through March 2023 and experienced RR system activation were included in the evaluation. All patients included after May 2022 were exposed to the intervention. Implementation of a modified RR system for LEP patients in May 2022 that included electronic dashboard monitoring of early warning scores (EWSs) based on electronic medical record data; RR nurse initiation of consults or full RR system activation; and systematic engagement of interpreters. Process of care measures included monthly rates of RR system activation, critical response nurse consultations, and disease severity scores prior to activation. Main outcomes included average post-RR system activation length of stay, escalation of care, and in-hospital mortality. Analyses used QI statistics to identify special cause variation in pre-post control charts based on monthly data aggregates. In total, 222 patients experienced at least one RR system activation during the study period. We saw no special cause variation for process measures, or for length of hospitalization or escalation of care. There was, however, special cause variation in mortality rates with an overall pre-post decrease in average monthly mortality from 7.42% (n = 8/107) to 6.09% (n = 7/115). In this pilot study, prioritized tracking, utilization of EWS-triggered evaluations, and interpreter integration into the RR system for LEP patients were feasible to implement and showed promise for reducing post-RR system activation mortality.

Impact of household income on the risk of overweight and obesity over time among preschool-aged children: a population-based cohort study

BackgroundThe temporality of household income level with overweight/obesity in children has not been extensively studied. Little research has been conducted to determine the impact of household income on the risk of childhood overweight/obesity over time. This population-based cohort study aimed to investigate the impact of household income on the risk of overweight/obesity over time among preschool-aged children in Taiwan.MethodsFrom 2009 to 2018, we recruited 1,482 preschool-aged children ( ≦ 7 y of age) from low-income households and selected age- and sex-matched controls from non-low-income households for comparison; All participants were selected from those who consistently participated in the Taipei Child Development Screening Program and were monitored for overweight/obesity using body mass index (BMI) until December 31, 2018. Low-income households were defined as those with an average monthly disposable income < 60% of the minimum standard of living expense in Taiwan. The primary outcome was childhood overweight or obesity in study participants, defined as BMI (kg/m2) ≥ 85th percentile or ≥ 95th percentile, respectively. The generalized estimating equations (GEE) model was used to determine the impact of low-income households on the risk of overweight/obesity in study participants.ResultsOver 21,450 person-years of follow-up, 1,782 participants developed overweight /obesity, including 452 (30.5%) and 1,330 (22.4%) children from low- and non-low-income households, respectively. The GEE model showed that the first group had a significantly higher risk of becoming overweight/obese than the other during the follow-up period (adjusted odds ratio [aOR] = 1.44, 95% CI: 1.29–1.60). Moreover, children of foreign mothers had a higher risk of becoming overweight/obese than those of Taiwanese mothers during the follow-up period (aOR = 1.51, 95% CI: 1.24–1.8). The subgroup analysis revealed a significant association between low-income households and an increased risk of overweight/obesity in children aged 2–7 years (P =.01). However, this association was not observed in children aged 0–1 years (P >.999).ConclusionsDuring the follow-up period, there was a notable correlation between low-income households and an increased risk of preschool-aged children developing overweight or obesity. Implementing health promotion initiatives aimed at reducing overweight and obesity in this demographic is crucial.

Modern Portfolio Theory and Its Applications

According to the modern portfolio theory, the monthly return data of 4 groups of portfolios (40 stocks) from November 5, 2011, to November 5, 2023, are empirically found: (1) the average monthly yield curve of stock portfolios group#1 and group#4 fluctuates significantly, while the volatility of equity portfolios group#2 and group#3 is relatively moderate. Especially after the new crown epidemic outbreak in 2020, the average monthly returns of all portfolios fluctuated sharply. (2) The expected return of NVDA is the highest among all stocks in the portfolio, and the IMB is the lowest. (3) Compared to the given portfolio returns, the #3 portfolio performs best, while the fund of group #1 performs the worst, and the remaining two portfolios perform well. In addition, if only the portfolio return and standard deviation are used as the portfolio return risk measures, the theoretical portfolio is better than the existing actual portfolio. Therefore, the return of a portfolio of securities will not exceed the yield of the benchmark portfolio at the same level of risk, which, to some extent, supports the hypothesis of the effectiveness of the securities market.

Artificial Neural Network for Forecasting Reference Evapotranspiration in Semi-Arid Bioclimatic Regions

A correct determination of irrigation water requirements necessitates an adequate estimation of reference evapotranspiration (ETo). In this study, monthly ETo is estimated using artificial neural network (ANN) models. Eleven combinations of long-term average monthly climatic data of air temperature (min and max), wind speed (WS), relative humidity (RH), and solar radiation (SR) recorded at nine different weather stations in Tunisia are used as inputs to the ANN models to calculate ETo given by the FAO-56 PM (Penman–Monteith) equation. This research study proposes to: (i) compare the FAO-24 BC, Riou, and Turc equations with the universal PM equation for estimating ETo; (ii) compare the PM method with the ANN technique; (iii) determine the meteorological parameters with the greatest impact on ETo prediction; and (iv) determine how accurate the ANN technique is in estimating ETo using data from nearby weather stations and compare it to the PM method. Four statistical criteria were used to evaluate the model’s predictive quality: the determination coefficient (R2), the index of agreement (d), the root mean square error (RMSE), and the mean absolute error (MAE). It is quite evident that the Blaney–Criddle, Riou, and Turc equations underestimate or overestimate the ETo values when compared to the PM method. Values of ETo underestimation ranged from 1.9% to 66.1%, while values of overestimation varied from 0.9% to 25.0%. The comparisons revealed that the ANN technique could be adeptly utilized to model ETo using the available meteorological data. Generally, the ANN technique performs better on the estimates of ETo than the conventional equations studied. Among the meteorological parameters considered, maximum temperature was identified as the most significant climatic parameter in ETo modeling, reaching values of R and d of 0.936 and 0.983, respectively. The research showed that trained ANNs could be used to yield ETo estimates using new data from nearby stations not included in the training process, reaching high average values of R and d values of 0.992 and 0.997, respectively. Very low values of MAE (0.233 mm day−1) and RMSE (0.326 mm day−1) were also obtained.

Влияние безработицы на уровень оплаты труда и прибыль

This work is devoted to an attempt to study the nature of the impact of unemployment on the level of wages and profits of enterprises. Based on Rosstat data on the unemployment rate, the average monthly nominal accrued wages of employees of organizations and the profitability of assets of industrial enterprises in the regions of the country, correlations of unemployment identified and linear regression models of these connections built. It been established that with a high level of unemployment, an increase in unemployment contributes to a decrease in wages; this influence is very small. At a low level of unemployment, starting from a level of less than 7–8%, the impact of unemployment on the level of wages begins to grow as the unemployment rate decreases until it reaches a value of 42–45% of the level of explanation of wages by the level of unemployment. This level of explanation observed at an unemployment rate of no more than 3–3.5%. If the unemployment rate does not exceed 3–3.5%, the degree of influence of unemployment on wages stabilizes and the decrease in unemployment determines the increase in wages by no more than 42–45%. Thus, the ideas about the wage curve and the Phillips curve are very simplified and do not reflect the complex nature of the influence of the unemployment level on wages. With a high level of unemployment, the growth of unemployment contributes to a decrease in the profitability of assets and, consequently, the profits of industrial enterprises. With an unemployment rate of no more than 4%, an increase in unemployment contributes to an increase in the profitability of assets and, consequently, the profits of industrial enterprises. Consequently, the idea that rising unemployment causes declining profits is overly simplistic and partly erroneous.

Fertilizer price behavior in Brazil - 2018 to 2021

The aim of this paper is to track the behavior of fertilizer prices from 2018 to 2021, highlighting the determinants and consequences. We used data on the average monthly national prices of urea, potassium chloride and monoammonium phosphate fertilizers, obtained from the National Supply Company (CONAB). A comparative analysis was carried out to show the variation in prices over the period studied, taking into account indicators such as the dollar index, oil prices, agricultural production, fertilizer import data, national fertilizer production and freight rates. The results of the research indicate that Brazil's external dependence on fertilizer-exporting countries makes it susceptible to exchange rate fluctuations, the prices of raw materials, such as oil, and global political relations, in addition to the law of supply and demand in the market.

Study of Global Horizontal and Vertical Solar Irradiance Components Under Different Sky Conditions for Sustainable Building Design In Bali Of Indonesia

The study of global and vertical solar irradiance components under different sky conditions is very important for building design applications. This research has been carried out by analyzing the components of solar radiation based on global horizontal irradiance (GHI) data, and global vertical irradiance for east, west, north, and south oriented. Observational data was acquired for one year starting from July 2022 to June 2023 in Jembrana-Bali of Indonesia. The solar radiation component has been analyzed based on sub-diurnal (daytime) and annual patterns. The clearness index (Kt) was calculated based on the ratio of extra-terrestrial solar radiation to global solar radiation measured at the surface. Sun-path analysis was carried out by considering the relationship of the zenith angle, azimuth angle, and the intensity of each solar radiation component to changes in time. The results show that in all-sky conditions, the average monthly maximum global horizontal irradiance occurs in January at 432.4 W/m², while the minimum monthly average global horizontal irradiance occurs in July at 327.9 W/m². The clearness index statistic shows that the hourly average ranges from 0.12 to 0.68 with an average of 0.47. Based on sun-path analysis, east, north, and west orientations receive more solar radiation in the Jembrana-Bali area. The findings from the study provide important information for architects, engineers, and policymakers that can be used for sustainable building design and building energy planning.

A Study of Households’ Perception towards Solar Panel Installation Case Study: Villagers of Techno-park nearby Faculty of Technology, University of Sri Jayewardenepura

In Sri Lanka, energy demand has been exponentially increasing with the outage of non-renewable energy sources. There is significant solar intensity in most of the areas in Sri Lanka. This study focused on the domestic solar power system since domestic solar panel usage (700 MW) is the country's highest contributor to solar energy usage. A photovoltaic (PV) system can supply electric energy to loads by directly converting solar energy through the photovoltaic effect with a flexible structure. This study aimed to analyze households' perceptions of solar panel installation. The study was conducted within a 5 km radius around the Faculty of Technology, the University of Sri Jayewardenepura, to analyze the awareness of solar-related technologies. A systematically developed questionnaire was used for the survey to collect the peoples' awareness based on environmental, social &amp; economic beliefs. Thirty residential places (30) were interviewed. According to the results, a residential house's average monthly electricity consumption is 137.67 kWh. The mean monthly income in the area is sixty-eight thousand one hundred and sixty-six rupees and sixty-seven cents. Moreover, most people had solar energy knowledge (93.33%). Among them, 53.57% of the majority were willing to install Domestic Solar PV systems for residential places. From the consumers, 76.66% of the majority had an average level of awareness of the Environmental benefits of using renewable energy and 70.00% of the majority had an excellent awareness of government intervention in rooftop solar energy projects such as "Soorya Bala Sangramaya‖. From the defined awareness levels, further analysis was done on the lowest level of Awareness of Solar Energy to identify their characteristics. The majority of them were those who had lower energy consumption, were over the age of 60 and had a monthly income below twenty thousand rupees. According to the consumers, the best strategy for promoting Solar PV Systems was to lower the prices of existing Solar PV systems. Regulating the efficiency of the Solar PV system was identified by the existing Solar PV system owners. &#x0D; Keywords: Solar PV system, Techno-park, Photovoltaic panels

Economic Feasibility of Reverse Osmosis (RO) Water Treatment Plants: A Case Study from Dimbulagala, Polonnaruwa, Sri Lanka

Social wellbeing is strongly linked with economic feasibility when it needs to attain with the technological advancements. Installation of Reverse Osmosis (RO) water treatment plants have been considered as a promising solution to provide clean water for human consumption, especially in the areas where the CKDu (chronic kidney disease of unknown etiology) prevails. At present, over 2,000 RO treatment plants were installed in the dry zone of Sri Lanka, yet economic feasibility for operation and maintenance of RO plants has not been assessed so far. The present study was intended to identify economic feasibility of operation and maintenance of RO plants. Investigations were carried out in six community RO plants which provided drinking water for over 17,000 people which accounts for 20% of total population in Dimbulagala Divisional Secretariat over a period of 12 months. Six in-depth interviews and questionnaire survey were caried out with RO plant operators. The operational cost per production of cubic meter of filtered water was computed by considering electricity consumption bills. The maintenance costs and service charges were also obtained from the records available with RO plant operators. The results found that the average electricity consumption to produce 1 cube of filtered water is approximately 9kWh and cost is LKR 734 (based on 2021 rates). The average water selling price ranged between LKR 1.00-2.50 per liter. The average monthly income generation from one RO plant is approximately between LKR 561- 875 per cube of filtered water and it largely depended on the type of water source, climatic conditions. It was found that the income generated from RO plants was sufficient enough to cover the operation cost (monthly electricity bill) and for the subsequent maintenance and service charges whenever required. It can be concluded that the use of RO treated water is an economically viable option to provide portable drinking water. &#x0D; Keywords: CKDu, Economic sustainability, Drinking water, Purification cost

Influence of Social Vulnerability in Treatment and Prognosis of Squamous Cell Carcinoma of the Tongue.

To investigate the association of social determinants of health (SDoH) in squamous cell carcinoma of the tongue in the United States and to evaluate the real-world contribution of specific disparities. Retrospective cohort study. United States. The Centers for Disease Control and Prevention-Social Vulnerability Index (SVI) and National Cancer Institute-Surveillance, Epidemiology, and End Results Programdatabase were used to study 62,103 adult tongue squamous cell carcinoma patients from 1975 to 2017. Regression analysis assessed trends in months of follow-up and survival across social vulnerability and 4 subcategories of social vulnerability. As overall SVI score increases (increased social vulnerability), there is a significant decrease in the average length of follow-up (22.95% decrease from 63.99 to 49.31 months; P < .001) across patients from the lowest and highest social vulnerability groups. As overall SVI score increases, there is a significant decrease in the average months of survival (28.00% decrease from 49.20 to 35.43 months; P < .001). There is also a significantly greater odds ratio (OR = 1.05; P < .001) of advanced cancer staging upon presentation at higher SVI scores. Patients with higher SVI scores have a lower OR (0.93; P < .001) of receiving surgery as their primary treatment when compared to patients with lower SVI scores. Patients with higher SVI scores also have a significantly greater OR (OR = 1.05; P < .001) of receiving chemotherapy as their primary treatment when compared to patients with lower SVI scores. Increased social vulnerability is shown to have a detrimental impact on the treatment and prognosis of patients with squamous cell carcinoma of the tongue.

A latent profile analysis of resilience and their relation to differences in sleep quality in patients with lung cancer.

Sleep problems are a significant issue in patients with lung cancer, and resilience is a closely related factor. However, few studies have identified subgroups of resilience and their relationship with sleep quality. This study aimed to investigate whether there are different profiles of resilience in patients with lung cancer, to determine the sociodemographic characteristics of each subgroup, and to determine the relationship between resilience and sleep quality in different subgroups. A total of 303 patients with lung cancer from four tertiary hospitals in China completed the General Sociodemographic sheet, the Connor-Davidson Resilience Scale, and the Pittsburgh Sleep Quality Index. Latent profile analysis was applied to explore the latent profiles of resilience. Multivariate logistic regression was used to analyze the sociodemographic variables in each profile, and ANOVA was used to explore the relationships between resilience profiles and sleep quality. The following three latent profiles were identified: the "high-resilience group" (30.2%), the "moderate-resilience group" (46.0%), and the "low-resilience group" (23.8%). Gender, place of residence, and average monthly household income significantly influenced the distribution of resilience in patients with lung cancer. The resilience patterns of patients with lung cancer varied. It is suggested that health care providers screen out various types of patients with multiple levels of resilience and pay more attention to female, rural, and poor patients. Additionally, individual differences in resilience may provide an actionable means for addressing sleep problems.

The Variation in the Water Level of Lake Baikal and Its Relationship with the Inflow and Outflow

Lake Baikal is the largest freshwater lake in the world, accounting for about 20% of the world’s fresh surface water. The lake’s outflow to the ocean occurs only via the Angara River, which has several hydroelectric power plants (HPPs) along its watercourse. The first such HPP, Irkutsk HPP, was built in 1956 and is located 60 km from the Angara River’s source. After two years, the backwater from this HPP expanded to the lake shores and began raising the Baikal Lake level. Currently, there is a dynamic balance between the new lake level, the lake inflow from its tributaries, and the Angara River discharge through the Irkutsk HPP. However, both the Angara River discharge and the Baikal Lake level were distorted by the HPP construction. Thus, to understand the changes to the lake basin over the past century, we first needed to estimate naturalized lake levels that would be if no HPP was ever built. This was an important task that allowed (a) the actual impact of global changes on the regional hydrological processes to be estimated and (b) better management of the HPP itself to be provided through future changes. With these objectives in mind, we accumulated multi-year data on the observed levels of Lake Baikal, and components of its water budget (discharge of main tributaries and the Angara River, precipitation, and evaporation). Thereafter, we assessed the temporal patterns and degree of coupling of multi-year and intra-annual changes in the lake’s monthly, seasonal, and annual characteristics. The reconstruction of the average monthly levels of Lake Baikal and the Angara River water discharge after the construction of the Irkutsk HPP was based on the relationship of the fluctuations with the components of the Lake water budget before regulation. As a result, 123-year time series of “conditionally natural” levels of Lake Baikal and the Angara River discharge were reconstructed and statistically analyzed. Our results indicated high inertia in the fluctuations in the lake level. Additionally, we found a century-long tendency of increases in the lake level of about 15 cm per 100 years, and we quantified the low-frequency changes in Lake Baikal’s water levels, the discharge of the Angara River, and the main lake tributaries. An assessment of the impact of the Irkutsk HPP on the multi-year and intra-annual changes in the Lake Baikal water level and the Angara River discharge showed that the restrictions on the discharge through the HPP and the legislative limitations of the Lake Baikal level regime have considerably limited the fluctuations in the lake level. These fluctuations can lead to regulation violations and adverse regimes during low-water or high-water periods.

Socio-Demographic Factors Associated with the Uptake of Community Led Total Sanitation: An Empirical Study among the Residents of Isiolo County, Kenya

Despite Kenya aiming to achieve 100% ODF status by 2030 and adopting CLTS, about 5.6 million (14%) of the population practice OD. Thus, this study was guided by the research question: What is the level of uptake of community led total sanitation among residents of Isiolo County? The study used a descriptive cross-sectional methodology and conducted among residents of Isiolo Sub-County, Kenya. The study sampled 373 household heads from population of about 21,870 household heads for the study. Systematic random sampling was used to select the participants. An inclusion and exclusion criteria-based period lived in the county and consent to participate in the study were used. Data collection instruments entailed structured questionnaires for households’ heads, key informant interview (KII) guides for opinion leaders, and an observation checklist. The content validity of the tools was assessed by expert from the department of Environmental Health at Kenyatta University. The tools were piloted in Longopito Sub-location with 37 households. Reliability of the tools was assessed using the piloted data through the test-retest technique. The paired data sets were correlated, giving R=0.75. The study found an association between demographic factors and the uptake of CLTS in Isiolo county. The uptake of CLTS was found to be low with almost half of the sampled residents lacking latrines. The study concludes there were a number of demographic factors that were significantly associated with the utilization of CLTS including the highest level of education (χ2=66.866, p = 0.001), Occupation (χ2=12.690, p = 0.002), Average monthly family income (KShs) (χ2=43.373, p = 0.012) and number of household members (χ2=6.948, p = 0.044). The study also found that Isiolo County had a low uptake rate for community-led total sanitation. Only three out of ten households in the county uptake CLTS. The study recommends that the County Government of Isiolo should scale up health education programs on community led total sanitation

AN ANALYSIS OF THE CAPITAL ASSET AND INVENTORY OF ZUANGTUI HANDLOOM ENTERPRISES IN AIZAWL, MIZORAM

Handloom as defined by the Merriam-Webster dictionary is any weaving device operated wholly or partially by hand or foot power. Handloom has always occupied an important position both in the economy of the country and in the hearts of the people. Handloom is the second largest provider of employment, providing employment to 31.45 lakh households through weaving and allied activities. In Mizoram, handloom provides employment to 27402 households (NCAER, 2020). The Zuangtui handloom cluster, located in the heart of Zuangtui Industrial Estate has provided great impetus to the economic development of the state. The paper aims to study the capital asset and inventory of the handloom enterprises of Zuangtui cluster such as ownership of work shed, means of transportation, types of products, loom type and quantity, etc. The study ventures into establishing the existence of correlation between the number of looms and average monthly income of the entrepreneurs. KEYWORDS: capital, entrepreneurs, handloom, loom, puan, work shed.

Evaluation of climate change impact on plants and hydrology

Climate change (CC) is the menace of the hour impacting every facet of human existence. Regional CC and its impact studies are crucial in that they contribute to global change. The current study aims to investigate the prevalence of CC in Charsadda, Pakistan and its impact on vegetation and hydrology of the region to understand microclimate variability contribution to global CC. Utilizing local climate data for 20 years (2001–2020), Modified Mann-Kendall and Sen’s Slope statistics were employed to determine monthly and seasonal trends in climate variables. Significant changing climate variables were regressed on Moderate resolution Imaging Spectroradiometer (MODIS) satellite dataset viz. normalized difference vegetation index (NDVI). Due to the prominent climate factor impacting vegetation, NDVI was further correlated to MODIS land surface temperature (LST). Floods being the conspicuous climate calamity were mapped for 2005 and 2010 using satellites Landsat 5 and 7 dataset viz. normalized difference water index (NDWI) with flood risk assessment by watershed delineation. The findings revealed significant (p &amp;lt; 0.05) variability in climate variables (average monthly and summer maximum temperature, and average monthly and summer precipitation) that are driving CC and impacting vegetation and hydrology in the region. Temperature and solar radiation affect NDVI adversely while precipitation and relative humidity has positive impact on vegetation. NDVI varied greatly spatiotemporally, often increasing but worsening in some areas (Shabqadar, Abazai, Palai and Charsadda city with NDVI = 0.1–0.3) of the study region as a result of extreme weather events. Temporally, NDVI improved with an overall positive trend with a stage (2007–2016) of noticeable zigzag fluctuation. Spatial grids with higher LST (&amp;gt;40°C) were either devoid of or with sparse NDVI (&amp;lt;0.3) presenting global warming as peril to vegetation. NDWI maps (2005, 2010 floods) indicate that after floods wreaked havoc on the region altering the vegetation pattern revealing heavy irregular precipitation as the next to temperature in jeopardizing vegetation of the region. Lower elevation regions along the Swat and Kabul Rivers with a greater risk of flooding were identified by watershed delineation. The study suggests that local governments and stakeholders implement CC mitigation strategies and plans for vegetation restoration, flood alerts with post-flood management for regional sustainable development.

Hilsa fisheries in India: a socio-economic analysis of fishers in deltaic Ganga region of river Hooghly

Hilsa (Tenualosa ilisha) is a premium table fish in the eastern and some parts of the north-eastern region of India, especially for the Bengali community, contributing uniquely to the societal and economic significance of artisanal fisheries of the country. The major distribution of the fish species in India lies in the Bhagirathi–Hooghly component of the Ganga River system. The aim of the study was to examine if traditional Hilsa fisheries in India are sustainable as the livelihood of artisanal fishers in light of the socio-economic conditions of Hilsa fishers in West Bengal. Structured socio-economic surveys were conducted with 402 fishermen from the upper stretch of river Hooghly to its lower stretch (300 km) in West Bengal during 2020–2021. The average monthly income of the Hilsa fishers in the lower stretch of river Hooghly (Godakhali) (₹25,000–30,000/USD 301–361) was higher than that in the upper stretch at Farakka (₹10,000–15,000/USD 120–180). However, fish species other than Hilsa are generating significantly higher returns for 56% of fishers in the Hooghly district; 40% of Hilsa fishers in South 24 Parganas and Murshidabad (Farakka) districts are engaged in non-fishery activities for livelihood. There are significant differences between Hilsa fishers with other fisheries as secondary occupations and those with non-fishery activities as secondary occupations in terms of socio-economic characteristics. These imply that Hilsa fisheries are profitable as a continued traditional livelihood, but it alone is not sufficient enough to support the livelihood of the artisanal fishers. This indicates the threatened economic sustainability of the Hilsa fisheries sector at present. Considering the high market demand for Hilsa in the eastern and north-eastern regions of India and the market complexities, more significant investments need to be channeled into the Hilsa fisheries of the northern Bay of Bengal region. Such investments encompass a wholesome approach, including more governmental initiatives for conservation and management.

A study on the Driving factors of Foreign Institutional Investment in Indian Stock Market (BSE)

India's stock market is essential to the country's economic progress. The market for stocks is an assembly point where investors, including residents and non-residents, may invest or withdraw money in the hope of seeing a capital increase. The stock market is an essential actor in the financial industry because it gives users and suppliers of financial resources a place to invest in company stocks. Examine the FII’s link with the stock market of India’s average monthly return. Monthly statistics were gathered for six years, from the beginning of 2016 to the end of 2021, to assess the impact of FII on the comeback of stock market of India. The relationship between the return of stocks and these variables was investigated using economic analysis.&#x0D; Every factor, such as the Sensex (BSE), and FII (both dependent and independent) are included in the analysis to check the stationary before being employed in the econometric analysis. The ADF test was used to assess the validity of the unit root test. The preceding study demonstrates that there is a causal link between the FII and the Sensex has been studied using correlation and the Granger causality test.

Seasonal variation of net ecosystem carbon exchange and gross primary production over a Loess Plateau semi-arid grassland of northwest China

Grassland ecosystems store approximately one-third of the global terrestrial carbon stocks, which play a crucial role in regulating the carbon cycle on regional and global scales, but the current scientific understanding of the variation in net carbon dioxide exchange (NEE) on grassland ecosystems is still limited. Based on the eddy covariance technique, this study investigated the seasonal variation of ecosystem respiration (Reco) and gross primary production (GPP) from 2018 to 2020 in a semi-arid grassland on the Loess Plateau in northwest China. The results indicated that the annual cumulative average NEE value was − 0.778 kg C/m2, the growing season cumulative value accounted for approximately 83.81%, which suggested that the semiarid grassland showed a notable soil carbon sink. The correlation analysis revealed that soil temperature (Ts) (RReco = 0.71, RGPP = 0.61) and soil water content (SWC) (RReco = 0.47, RGPP = 0.44) were the two main driving factors in modulating the variation of daily average GPP and Reco (P < 0.01). Therefore, the monthly average of GPP and Reco increased with the increase in Ts (RGPP = 0.716, P < 0.01; RReco = 0.586, P < 0.05), resulting in an increase in the carbon sequestration capacity of the grass ecosystem. This study also showed that soil moisture has a promoting effect on the response of Reco and GPP to Ts, and the correlation among GPP, Reco, and Ts was much stronger under wet conditions. For instance, the coefficient of determination of Reco and GPP with Ts under wet conditions in 2018 increased by 0.248 and 0.286, respectively, compared to those under droughty conditions. Additionally, the temperature sensitivity of Reco (Q10) increased by 46.13% compared to dry conditions. In addition, carbon exchange models should consider the synergistic effect of Ts and SWC as one of the main driving factors for theoretical interpretation or modeling. Under the potential scenario of future global warming and the frequent extreme weather events, our findings have important implications for predicting future CO2 exchange and establishing an optimal ecological model of carbon flux exchange.

Changes in the Step Counts of University Students Living in Hokkaido during the COVID-19 Pandemic

Background. Coronavirus disease (COVID-19) countermeasures, such as lockdowns, have been reported to reduce people’s physical activity levels. Purpose. To determine changes in the step counts among university students before and after the COVID-19 pandemic and identify the risk factors for decreased step counts. Materials and Methods. An online questionnaire was sent by e-mail to 1,851 students enrolled in a university in Hokkaido, Japan; of these, 127 participated. The questionnaire items were average monthly step counts from October 2019 to March 2022, type of residence, part-time job, club activities, personal demographics, height, and weight. The average step counts in October/November 2019 (before the pandemic) were used as the baseline, and changes in step counts were studied at five time points (every 6 months): April/May 2020 (first state of emergency declared), October/November 2020 (period of contained infection), April/May 2021 (second state of emergency declared), and October/November 2021 (period of contained infection). We also examined changes in the number of steps due to different lifestyle factors and factors that contributed to decreased step counts during the study period. Results. Significantly lower step counts than those at baseline were observed in April/May 2020 and April/May 2021; however, there was no significant difference in October/November 2020 and October/November 2021 compared with baseline. In addition, significantly lower step counts were observed in April/May 2020 than in April/May 2021. The risk of decreased step counts was significantly associated with nonparticipation in club activities, even after adjustment for other variables. Conclusion. The step counts of university students decreased significantly during the declaration of a state of emergency and recovered to pre-pandemic levels after the declaration was lifted. Lifestyle status revealed differences in the number of steps taken before and after the pandemic. Nonparticipation in club activities was identified as a major risk factor for a decrease in step counts.

Abstract B042: Analysis of predictive indicators of invasive breast cancer: Modeling survival rates

Abstract Objective: We aim to investigate indicators of risk for invasive breast cancer (IBC) and to predict and assess the impact of these risk indicators on survival rates in breast cancer (BC) patients who received various therapies. Background: It has been identified that several indicators including BC subtypes, age at diagnosis, history of breast disease, menopausal status, estrogen receptor (ER) status, progesterone receptor (PR) status, human epidermal growth receptor (HER2) status, tumor stage, tumor size, among others, can cause genomic alterations and driver mutations in BC, leading to invasive carcinogenesis. To assure improved BC outcomes, we investigate the influence of BC indicators on survival rates in patients receiving hormone therapy, chemotherapy and radiotherapy. Methods: This study uses the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset, which included 31 clinical indicators, m-RNA levels z-score for 331 genes, and mutation in 175 genes for 1904 BC patients. Both bivariate and multivariate associations were examined using logistic regression and Cox proportional hazard models. The multivariate logistic regression analysis is used to determine predictors of IBC. The Cox proportional hazard model was also used to evaluate the magnitude of the impacts of clinical and demographic variables on IBC, as well as the effects of therapy on survival. All analyses for this investigation were carried out using SAS. A p-value &amp;lt; 0.05 was considered statistically significant. Results: We examined 1,043 patients (with the median age 61±13.1 years) from a total of 1904 for this study: 78.8% of patients had breast invasive ductal carcinoma; 87.4% were HER2 negative; 22.8%, 60.7%, and 67.6% received chemotherapy, hormone therapy, and radiotherapy treatments, respectively; 56.9% died but only 34.6% died from the disease; the average overall survival months was 127.3±77.6 months; and the most common age group was "65+ years" (39.4%). Chemotherapy (p=0.0474), neoplasm histologic grade (p=0.0015), Nottingham prognostic index (p&amp;lt;.0001), radiation (p=0.0068), and BReast CAncer gene 1 (BRCA1) (p=0.0251) were all associated with IBC. Overall survival was also correlated to age at diagnosis (p=0.0002), neoplasm histologic grade (p&amp;lt;.0001), lymph nodes (p&amp;lt;.0001), mutation count (p&amp;lt;.0001), Nottingham prognostic index (p&amp;lt;.0001), radiotherapy (p=0005), tumor size (p&amp;lt;.0001), tumor stage (p&amp;lt;.0001), BRCA1 (p=0.250), PTEN (p&amp;lt;.0001), and TP53 (p=0.0248). The overall accuracy of the model for each IBC and survival status was 82.1% and 74.2%, respectively. Conclusion: Our analysis demonstrated the importance of predictive analysis using the logistic regression model and survival analysis using the Cox proportional hazard model in cancer research. Predictive and survival analysis results aided in predicting the invasiveness and survival rate of BC among the study participants. In general, predictive and survival analyses are more accurate and may be used to make more realistic treatment decisions and precision oncology. Citation Format: Olumide Arigbede, Gebre-Egziabhe Kiros. Analysis of predictive indicators of invasive breast cancer: Modeling survival rates [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr B042.