Largest Negative Effect Research Articles

Society-related Fears and Personal Mental Health

This paper explores the relationship between society-related fears and personal mental health. Respondents of an online survey representing the German population (18 + years) answered how much they are worried about eight societal developments (armed conflicts, social inequality, rise of right-wing extremism, crime and terror, immigration, climate change, artificial intelligence, pandemics). The analysis demonstrate that the sum score of society-related fears is significantly associated with higher levels of anxiety and depression. Particularly concerns about poverty, digitalization and pandemics are associated with higher anxiety and depression scores. Further explorations show that specific fears are intermingled with political ideologies, i.e. people fear different societal developments according to their ideological standpoints. Politically left-leaning individuals regard climate change and rising right-wing extremism as more threatening, while politically right-leaning individuals’ fears relate more strongly to migrants, terror and crime. The fears with the largest negative effect on mental health are poverty and armed conflicts for individuals who identify as left and digitalization for individuals who identify as right. Overall, findings lend support to the general notion that the world’s current ‘polycrisis’ is highly relevant and generally detrimental for mental health and human wellbeing.

Public Views on Whether the Use of Pharmaceutical Neuroenhancements Should Be Allowed.

Some individuals are using drugs to try to enhance cognitive and social-affective functioning and asking physicians for off-label prescriptions for neuroenhancement (e.g., stimulants). Several medical societies released guidance on prescribing neuroenhancers, some of which refer to potential societal effects of neuroenhancement (e.g., distributive justice), besides risks and benefits to users. Which institutions (e.g., medical societies, government, universities) should make decisions on allowing neuroenhancement and whether they should consider potential societal effects are unclear. We examined whether and how much support for allowing pharmaceutical neuroenhancers was influenced by the institution and potential individual and societal effects of neuroenhancers. We conducted a discrete-choice experiment using a constructed representative sample of the US adult public. Multinomial logit models were used to analyze the data. Participants (n = 927) demographically resembled the US population. Risks of serious side effects (OR 0.20, CI 0.18-0.22) and a lack of benefits for users (OR 0.31, CI 0.26-0.38) had the largest negative effect on participants' support for allowing neuroenhancers. A risk of mild side effects had a moderate negative effect on participants' support for allowing neuroenhancers (OR 0.67, CI 0.62-0.74) and the prospect of more meaningful, long-lasting benefits for users a moderate positive effect (OR 1.74, CI 1.61-1.87). Positive or negative effects of neuroenhancers on the average well-being of people in society and on equality had moderate effects on participants' support for allowing neuroenhancers. For example, the odds of participants' support for allowing enhancers with a negative effect on societal well-being were around half (OR 0.45, CI 0.40-0.50) and the odds of allowing enhancers that worsen inequality were approximately 40% lower compared with enhancers without such effects (OR 0.62, CI 0.55-0.71). The odds of participants allowing neuroenhancers were slightly (10%) lower if enhancers reduced users' authenticity (OR 0.90, CI 0.84-0.97). The institution regulating neuroenhancers and neuroenhancers providing users with an unfair advantage did not affect participants' decisions. When presented with both individual and societal considerations, the public seems to support medical societies and other institutions making policy decisions about neuroenhancers based on risks and benefits for users, as well as, but to a lesser extent, effects on equality and societal well-being.

Spatial–Temporal Variations of the Gross Ecosystem Product under the Influence of the Spatial Spillover Effect of Urbanization and Ecological Construction in the Yangtze River Delta Region of China

Rapid development of urbanization and intense human activities had a profound influence on the ecosystem service functions. As an integrated monetary index for the evaluation of final ecosystem services, the gross ecosystem product (GEP) is widely used in the quantification of ecosystem service value (ESV). This study initially assessed and analyzed the spatial distribution of the GEP at the county-level scale using multisource data spanning 2000, 2005, 2010, 2015, and 2020. Then, the spatial transfer characteristics of the GEP were measured. Finally, the study employed spatial panel econometric models and the geographically weighted regression (GWR) model to investigate the spatial effect of urbanization and ecological construction on the GEP. The results indicated that: (1) In 2020, the GEP in the Yangtze River Delta Region was RMB 15.24 trillion, and the GEP per unit area was RMB 42.58 million per square kilometer. It exhibited a cumulative decrease of RMB 298.72 billion from 2000 to 2020. (2) The spatial transfer efficiency of the GEP in urban agglomerations showed a clear decline trend. During the period of 2000–2020, over 96% of county-level units exhibited a decline with RMB 90,076,103.17/km2, indicating a consistent downward trend from the central regions towards the periphery. (3) Based on the decomposition effects of the spatial Durbin mode, urbanization and the ecological construction indicator showed spatial spillover effects on the GEP, but their impact mechanisms varied substantially. Among them, the urbanization rate (UR), population density (PD), and the proportion of impervious land (ILP) had the largest negative effect on the GEP, and a 1% rise in ILP locally resulted in a 0.044% decline in the local GEP and a 0.078% rise in the GEP of neighboring units. And the area of ecological land had a positive effect on the GEP of both local and neighboring areas. Those conclusions can offer evidence in favor of encouraging ecologically responsible building practices and sustainable growth in urban agglomerations.

Research on habitat quality in arid urban agglomerations: Influencing mechanisms and multi‐scenario simulations

AbstractIn the context of climate change and rapid urbanization, there have been unparalleled changes in land use and land cover (LULC), resulting in substantial impacts on the surrounding habitat quality (HQ), particularly in ecologically vulnerable arid regions. However, previous studies on the influencing mechanisms of HQ in arid urban agglomerations and future multi‐scenario simulations remain limited. To fill this knowledge gap, this study aimed to reveal the influencing mechanisms in HQ changes and to develop a multi‐scenario HQ assessment framework within arid urban agglomerations. We assessed the spatiotemporal variations in HQ using the InVEST model and three periods of LULC data for the urban agglomeration on the northern slope of the Tianshan Mountains (UANSTM), and the partial least squares structural equation model was introduced to explore the interactions between natural and non‐natural factors and their impacts on HQ. Additionally, we coupled multi‐objective programming and PLUS models to predict the LULC under different optimization scenarios (natural development scenario (NDS), ecological protection scenario (EPS), ecological–economic coordinated scenario, and economic development scenario) for the UANSTM in 2030, and to assess HQ. Results show that (1) the HQ index of the UANSTM was 0.507, 0.520, and 0.495 in 2000, 2010, and 2020 respectively, with a spatial distribution pattern of high values in the west, low values in the east, and high in the central and low in the north and south; (2) geomorphic, climatic, and LULC factors have direct positive effects on HQ, while socio‐economic factors have a direct negative effect on HQ. In addition, geomorphic, socio‐economic, and climatic factors also influence HQ through potential indirect paths. Climatic and LULC factors enhance the positive effect of geomorphic on HQ while counteracting the direct negative effect of socio‐economic factors on HQ. Climatic factors have the largest negative effect on HQ through their influence on LULC; (3) according to the four scenarios in 2030, the highest HQ index (increased by 0.13%) was found under the EPS, which also aligns more closely with SDGs. Conversely, NDS showed the lowest HQ index (declined by 2.59%). The research results could provide a scientific basis for promoting sustainable land management and ecological conservation for the UANSTM.

Dynamics of inflammation-associated plasma proteins following faecal microbiota transplantation in patients with psoriatic arthritis and healthy controls: exploratory findings from the FLORA trial

ObjectivesThe gut microbiota can mediate both pro and anti-inflammatory responses. In patients with psoriatic arthritis (PsA), we investigated the impact of faecal microbiota transplantation (FMT), relative to sham transplantation, on...

Forecasting Economic Growth: Evidence from housing, banking, and credit conditions

Previous studies on economic growth have separately examined the role of housing, banking, and credit market conditions, despite their interrelatedness. Therefore, this paper comprehensively investigates the relative importance of four indicators [house prices, residential investment, corporate credit spreads, and aggregate bank liquidity creation (LC)] to forecast U.S. real GDP growth. We do so after accounting for a comprehensive set of other predictors and aim to identify indicators that better forecast economic growth. Our in-and out-of-sample results show that house prices and corporate credit spreads predict real GDP growth better than residential investment and LC. Moreover, shocks to house prices and corporate credit spreads have a greater impact on real GDP growth and other macroeconomic indicators than shocks to LC and residential investment. Furthermore, house prices have the largest positive impact on inflation and the largest negative effect on unemployment. These results may have potential monetary policy implications.

The impact of health expenditure and economic growth on CO2 in China: a quantile regression model approach.

Based on the environmental Kuznets curve (EKC) hypothesis and using Chinese provincial panel data from 2002 to 2019, this study examines how different types of healthcare expenditure and levels of economic development and energy consumption contribute to carbon emissions regionally. Considering the wide regional differences in the development levels of China, this paper uses quantile regressions and draws the following robust conclusions: (1) The EKC hypothesis was validated by all methods in eastern China. (2) The carbon emission reduction of government, private, and social health expenditure is confirmed. Furthermore, the impact of health expenditure on carbon reduction decreases from East to West. (3) Government, private, and social health expenditure all cause reductions in CO2 emissions, with private health expenditure having the largest negative effect on CO2 emissions, followed by government health expenditure and finally social health expenditure. Overall, the limited empirical work available on the impact of different kinds of health expenditure on carbon emission in the existing literature, this study greatly assists policy makers and researchers to understand the importance of health expenditure in improving environmental performance.

How does digital financial inclusion affect green economic development? A perspective from regional competitions

Digital financial inclusion aims to bring financial services to a wider range of people and businesses at a much lower cost, using big data and cloud computing to capture and share information. At the same time, the Chinese government aims to build a green and sustainable economy. Therefore, this study analyzes the impact of digital financial inclusion on green economic efficiency and identifies the moderating role of regional competition based on the empirical analysis of data from 265 prefecture-level cities in China from 2010 to 2017. Our results indicate that (1) digital financial inclusion promotes the green economy, which has a significant positive spillover effect, (2) regional competition is beneficial for green economy development, but the interaction of digital financial inclusion and regional competition is detrimental, and (3) digital financial services make the largest positive contribution to the green economy, and digital payment services have the largest negative effect.

Impact of adverse events on health-related quality of life after left ventricular assist device implantation: An STS INTERMACS analysis

We sought to quantify the impact of pre- and postoperative variables on health-related quality of life (HRQOL) after left ventricular assist device (LVAD) implantation. Primary durable LVAD implants between 2012 and 2019 in the Interagency Registry for Mechanically Assisted Circulatory Support were identified. Multivariable modeling using general linear models assessed the impact of baseline characteristics and postimplant adverse events (AEs) on HRQOL as assessed by the EQ-5D visual analog scale (VAS) and the Kansas City Cardiomyopathy Questionnaire-12 (KCCQ) at 6 months and 3 years. Of 22,230 patients, 9,888 had VAS and 10,552 had KCCQ reported at 6 months, and 2,170 patients had VAS and 2,355 had KCCQ reported at 3 years postimplant. VAS improved from a mean of 38.2 ± 28.3 to 70.7 ± 22.9 at 6 months and from 40.1 ± 27.8 to 70.3 ± 23.1 at 3 years. KCCQ improved from 28.2 ± 23.9 to 64.3 ± 23.2 at 6 months and from 29.8 ± 23.7 to 63.0 ± 23.7 at 3 years. Preimplant variables, including baseline VAS, had small effect sizes on HRQOL while postimplant AEs had large negative effect sizes. Recent stroke, respiratory failure, and renal dysfunction had the largest negative effect on HRQOL at 6 months, while recent renal dysfunction, respiratory failure, and infection had the largest negative effect at 3 years. AEs following LVAD implantation have large negative effects on HRQOL in early and late follow-up. Understanding the impact of AEs on HRQOL may assist shared decision-making regarding LVAD eligibility. Continued efforts to reduce post-LVAD AEs are warranted to improve HRQOL in addition to survival.

A robust bridge rivet identification method using deep learning and computer vision

Timely and effective inspection ensures safe operation and optimum resource use for infrastructure maintenance and renewal. Robot advances allow rapid collection of inspection image data. However, distinguishing bridge elements from large amounts of image data is challenging. Rivets are critical elements, joining different profiles into components. However, automatic rivet identification has received little attention. This study proposes a rivet identification method based on computer vision and deep learning. A sustainable training framework is presented to build a robust detector. A novel rivet dataset was collected and annotated from a full-size bridge. YOLOv5 is used to extract features and predicate classifications. The model achieved an 88.9% precision, 90.5% recall, and 90.1% F1 score. The accuracy and robustness were evaluated on another riveted bridge under various operational conditions. The rivet detector generally performs well, achieving 85% or even 95% accuracy in most situations. Out-of-focus and object occlusion have the largest negative effect.

Multiple pressures and vegetation conditions shape the spatiotemporal variations of ecosystem services in the Qinghai-Tibet Plateau.

Human activities and environmental change can impact the supply of ecosystem services (ESs) as pressures. Understanding the mechanisms of these impacts is crucial to support ecological conservation and restoration policy and applications. In this study, we highlighted the contribution of vegetation to mitigating these impacts on ESs in the Qinghai-Tibet Plateau (QTP) of China. First, we identified hot and cold spots of pressures from human activities and environmental factors and mapped the cumulative provision of five ESs (i.e., water yield, soil retention, carbon sequestration, habitat quality, and landscape aesthetics). Then, we clustered these ESs into five bundles based on their supply level. Furthermore, structural equation modeling was used to quantify the pathways of multiple pressures on ESs. The results indicated that 1) for 2000, 2010 and 2019, the percentages of hot spots with high pressure were 28.88%, 27.59% and 45.66% respectively, with significant spatial heterogeneity from northwest to southeast; 2) both regions with high and low cumulative ES values experienced increased volatility; and 3) the joint effects of multiple pressures shaped ESs through pressure-ES (direct) and pressure-vegetation-ES (indirect) pathways. Specifically, precipitation had the largest positive effect on regulating services (rα ≥ 0.76), and landscape fragmentation had the largest negative effect on cultural services (-0.10 ≤ rα ≤ -0.07). Vegetation played an important role in modulating multiple pressures on ESs. This study contributes to ecosystem management by effectively coping with anthropogenic and environmental pressures and sustaining the supply of ESs, particularly in alpine and plateau regions.

Interactions between Ecosystem Services and Social Economies in the Yangtze River Economic Belt

AbstractAn in‐depth understanding of the relationships between ecosystem services (ESs) and socioeconomic (SE) development is an important prerequisite for the coordination and sustainable development of regional human–environmental management strategies. In this study, the coupling coordination model is employed to explore the synergistic and trade‐off relationships between ESs and SE factors.The results show that the ESs in the Yangtze River Economic Belt are currently in a trade‐off stage. At the urban scale, the synergy between water production and other ecosystem functions is more than 20% higher than that of other systems. The proportion of trade‐offs between sediment retention and other ecosystem functions is also high, more than 40% higher than that of other systems. ESs are greatly affected by SE development; the expansion of cultivated land area has the largest negative effect on ESs, and rainfall has the largest negative effect on SE factors. The population has the largest positive effect on ESs, and carbon storage has the largest positive effect on SE factors. This study provides a research method by exploring the patterns of development, interaction, and impact in the Yangtze River Economic Belt, which can provide a basis for the SE development and ESs management of watershed economic zones.

Understanding the factors associated with one-way and round-trip carsharing usage based on a hybrid operation carsharing system: A case study in Beijing

As carsharing is promoted in many cities, studying the factors related to station-level demand under multi-mode operating carsharing systems will help better develop carsharing programs. In this paper, the number of transactions is calculated to represent the carsharing demand based on the data from a one-way and round-trip hybrid operation carsharing system in Beijing. The generalized additive model is then conducted with carsharing demand as the dependent variable and five groups of independent variables: station attributes, public transit, built environment, weather, and consumption features. The main results are: (1) the one-way station has a substitution effect on the round-trip station; (2) the one-way and round-trip stations not only have considerable demand in places well served by transit but also can play different and complementary roles in areas underserved by transit; (3) the percentage of residential POIs, the POI-mixed entropy, and the number of cars per household are the most statistically significant factors; (4) weather conditions such as precipitation, high temperatures, and poor air quality play a positive role in carsharing usage; (5) personalized incentives help attract more usage, while the positive effect is minor; (6) both population density and average consumption are highly nonlinear to carsharing usage. Population densities of around 10,000 people/km2 have the largest positive effect on one-way station usage and around 6,500 people/km2 have the largest negative effect on round-trip station usage. When the average consumption exceeds 100 RMB, the usage of one-way stations decreases more rapidly compared to round-trip stations. This study can help the operators understand and refine their business strategies, and can provide insights into determining the location and mode of carsharing stations.

Global Crisis and Economic Fundamentals: Its Impact on Foreign Direct Investment in ASEAN Countries

Foreign direct investment has an important role in the running of a country's economy. This study aims to analyze the role of macroeconomic fundamentals consisting of Gross Domestic Product (GDP), interest rates, exchange rates, and exports in influencing Foreign Direct Investment (FDI) in the ASEAN 6 region (Indonesia, Malaysia, Singapore, Thailand, the Philippines, and Vietnamese). The data used are from 1990-2019 sourced from the World Bank and UNCTAD. The method used is panel data regression and time series with the best model selection, namely the Random Effect Model. The results of panel data analysis show that GDP, interest rates, exchange rates, and exports are the determinants of FDI in ASEAN 6 with a significant probability value. The positive direction coefficient is indicated by the GDP and exchange rate variables, while interest rates and exports indicate a negative direction coefficient. The results of the time-series data confirm that each country has similar results in the panel data analysis, but interest rates in Malaysia have the largest negative effect on FDI in Malaysia. Meanwhile, the exchange rate and exports contributed positively with the largest coefficient for Indonesia. The 1998 and 2008 economic crises were also found to have a negative impact on FDI but not significantly in some countries.

Global Crisis and Economic Fundamentals: Its Impact on Foreign Direct Investment in ASEAN Countries

Foreign direct investment has an important role in the running of a country's economy. This study aims to analyze the role of macroeconomic fundamentals consisting of Gross Domestic Product (GDP), interest rates, exchange rates, and exports in influencing Foreign Direct Investment (FDI) in the ASEAN 6 region (Indonesia, Malaysia, Singapore, Thailand, the Philippines, and Vietnamese). The data used are from 1990-2019 sourced from the World Bank and UNCTAD. The method used is panel data regression and time series with the best model selection, namely the Random Effect Model. The results of panel data analysis show that GDP, interest rates, exchange rates, and exports are the determinants of FDI in ASEAN 6 with a significant probability value. The positive direction coefficient is indicated by the GDP and exchange rate variables, while interest rates and exports indicate a negative direction coefficient. The results of the time-series data confirm that each country has similar results in the panel data analysis, but interest rates in Malaysia have the largest negative effect on FDI in Malaysia. Meanwhile, the exchange rate and exports contributed positively with the largest coefficient for Indonesia. The 1998 and 2008 economic crises were also found to have a negative impact on FDI but not significantly in some countries.

Effect of additives on properties of cross‐linked carboxymethyl starch/polyvinyl alcohol composite films

AbstractIn order to improve the comprehensive performance of cross‐linked carboxymethyl starch (CCMS)/polyvinyl alcohol (PVA) composite films, expand its application in the field of daily packaging. The CCMS/PVA blend films were prepared by solution casting method. The effect of environmentally friendly non‐toxic additives citric acid, urea, CaCl2, and nano‐SiO2 on the microscopic surface morphology, crystallization properties, thermal properties, mechanical properties, water resistance and optical properties of the CCMS/PVA composite films were investigated. The biocomposite films were characterized by SEM, FT‐IR, XRD, TGA, tensile testing, water absorption test, water vapor transmission test, and UV–visible spectrophotometer. The result indicates that the compound addition of citric acid and urea greatly increase the elongation at break of the composite films from 9.2% to 225.7%. With the composite addition of citric acid and nano‐SiO2, the composite film has the best water resistance and water vapor barrier properties. The composite films added with citric acid, urea and nano‐SiO2 can obtain the best thermal stability. Among these four additives, CaCl2 has the largest negative effect on the elongation at break and urea has the largest negative effect on water resistance properties of the CCMS/PVA composites. The CCMS/PVA composite films prepared by adding 30% citric acid and 6% nano‐SiO2 has the best comprehensive performance. The tensile strength, elongation at break, solubility, thermal decomposition temperature, water vapor permeability and light transmittance of the CCMS/PVA/CA/S composite films are 3.3 MPa, 168%, 34.6%, 293.2°C, 1.54 × 10−11 g s−1 m−1 Pa−1 and 22.47%, respectively. The biocomposite film has the potential to be applied in the field of packaging, and provides a reference for further research.

Having Difficulties Reading the Facial Expression of Older Individuals? Blame It on the Facial Muscles, Not the Wrinkles.

Previous studies have found it is more difficult identifying an emotional expression displayed by an older than a younger face. It is unknown whether this is caused by age-related changes such as wrinkles and folds interfering with perception, or by the aging of facial muscles, potentially reducing the ability of older individuals to display an interpretable expression. To discriminate between these two possibilities, participants attempted to identify facial expressions under different conditions. To control for the variables (wrinkles/folds vs facial muscles), we used Generative Adversarial Networks to make faces look older or younger. Based upon behavior data collected from 28 individuals, our model predicts that the odds of correctly identifying the expressed emotion of a face reduced 16.2% when younger faces (condition 1) are artificially aged (condition 3). Replacing the younger faces with natural old-looking faces (Condition 2), however, results in an even stronger effect (odds of correct identification decreased by 50.9%). Counterintuitively, making old faces (Condition 2) look young (Condition 4) results in the largest negative effect (odds of correct identification decreased by 74.8% compared with natural young faces). Taken together, these results suggest that both age-related decline in the facial muscles’ ability to express facial emotions and age-related physical changes in the face, explain why it is difficult to recognize facial expressions from older faces; the effect of the former, however, is much stronger than that of the latter. Facial muscle exercises, therefore, might improve the capacity to convey facial emotional expressions in the elderly.

N08 Construction of an explanatory model for quality of life in outpatients with ulcerative colitis

Abstract Background Previous studies have reported explanatory models of health-related quality of life (HRQoL) in patients with Crohn disease or inflammatory bowel disease. However, no model for HRQoL has been developed that is specialised for patients with ulcerative colitis (UC). In this study, we aimed to develop and evaluate a predictive explanatory model for HRQoL among outpatients with UC in Japan. Methods We conducted a cross-sectional survey between December 2019 and July 2020 at a clinic in Japan. HRQoL was evaluated using the 32-item Inflammatory Bowel Disease Questionnaire (IBDQ-32). We extracted explanatory variables of HRQoL, including disease activity, psychological symptoms, and social support, from previous studies and created an explanatory model based on the conceptual model of Wilson & Cleary (1995). The relationship between explanatory variables and the IBDQ-32 total score was examined using the Spearman’s rank correlation coefficient, Mann–Whitney test, or Kruskal–Wallis test. We conducted multiple regression analysis and path analysis to examine the effect of explanatory variables on IBDQ-32 total score. Results We included a total of 203 patients with UC. Variables that were significantly associated with the IBDQ-32 total score were partial Mayo Score, presence or absence of treatment side effects, Hospital Anxiety and Depression Scale (HADS) score, and having/not having an adviser when patients were severely ill-conditioned. HADS had the largest negative effect on IBDQ-32 total score (β = −0.474), followed by partial Mayo Score (β = −0.408), presence/absence of treatment side effects (β = −0.116), having/not having an adviser when patients were ill-conditioned (β = 0.081). Having an adviser or not when ill-conditioned had an indirect effect on patients’ IBDQ-32 total score via HADS (β = −0.111). We verified the final model, which included IBDQ-32 total score and the above four explanatory variables (adjusted R² = 0.501, GFI = 0.996, AGFI = 0.970, CFI = 1.000, RMSEA = 0.010, AIC = 28.043). Conclusion Psychological symptoms had the most direct effect on HRQoL in patients with UC and acted as a mediator in the relationship between social support and HRQoL. Nursing interventions to improve HRQoL in patients with UC should consider the effect of psychological symptoms and support when patients are severely ill-conditioned.

Beneficiation of recycled process water at DRDGOLD's ERGO plant, and its effect on gold recovery

To conserve fresh water resources and comply with environmental regulations, DRDGOLD, a South African gold producer re-treating surface tailings, has transitioned to a fully closed water circulation system. Consequently, the accumulation of contaminants, as well as addition of reagents, has led to changes in water composition that have compromised leach performance and overall gold recovery. A two-sample t-test confirmed a significant difference in gold recoveries between the use of Rand Water, which was used as a benchmark, and untreated process water. Atomic absorption analysis of ERGO's process water, confirmed the presence of iron, nickel, zinc, and manganese. A study of the effect of the identified contaminants on gold recovery showed that iron, nickel, and zinc have the largest negative effect on gold recovery, with iron and nickel being more detrimental than zinc. Sulphates were shown to have a possible passivation effect, which also influenced gold recoveries, although to a lesser extent than the heavy metals. Calcium, when present in excess, had a positive influence on gold recovery indicating the possible formation of a calcium aurocyanide complex. Lime softening successfully reduced the heavy metal and sulphate concentrations, and the gold recoveries obtained with the treated process water were similar to those as achieved with Rand Water.

The mathematical model for forecasting the accumulation of heavy metals in pig production

The results of research represent the impact of extensive doses of heavy metals such as lead and cadmium in store pigs bodies. Heavy metals were fed jointly and individually in the doses exceeding the maximum allowable concentrations in the fodder by 10 and 20 times. Therefore, the process of intoxication of the biological object (a swine) by heavy metals is modeled in a way similar to that, which might occur as the result of environmental pollution. The study was performed in order to determine the targets and the extent of the impact of heavy metals exerted upon the body weight, weight of inner parts of the animal body, and the incorporation rate of heavy metals in the swine breeding products. Statistical processing of the obtained data allowed developing mathematical models and determining the correlational relationships between the aspects under investigation. It is determined that heavy metals exert an essential negative impact upon the rate of animal growth and the power of influence increases with the dose. It is also confirmed by a high value of correlational relationship between these parameters (the correlation coefficient (r) is 0.854). Thus, the body weight of swine during the latter of I-II stagesdecreased by 5.5 to 14.8% as it was compared to the control under the influence of hemotoxic substances. The extent of the impact was also dependent upon the toxin itself. Thus, the largest negative effect was observed both under the impact of cadmium only and of cadmium and lead taken together. The highest accumulation of heavy metals was observed in the liver and kidneys, whereas the lowest – in the muscles. The built regression equations showed that increasing of the dose of the relevant element in the fodder exerted the main impact on concentration of cadmium and lead in the body and meat. The content of cadmium in the fodder exerted an impact upon concentration of lead in the meat – with the increase of cadmium concentration the content of lead in the meat decreased. The results of the studies provide an overview of the targets and the extent of the impact exerted by heavy metals upon biological objects. The mathematical models may be used for prediction of the impact and the incorporation rate value of the hemotoxic substances in the swine breeding products. Key words: lead, cadmium, swine breeding products, ecocide environmental impact, migration of xenobiotic, mathematical model.