Background Self-harm typically is without lethal intent. Death can occur rarely, with suicide taking on an atypical form that raises the suspicion of hetero-aggression. Our study aimed to identify the link between self-harm and suicide intent and also to outline the positive diagnosis of an atypical suicide case which has raised the suspicion of hetero-aggression. For this purpose, the psychological autopsy method should be used regularly in suicide investigation because it not only allows a positive diagnosis of suicide but can also provide a detailed picture of mental degradation and associated suicide risk factors. Case presentation The case of a 26-year-old man from a rural area, found dead in the basement, at home, naked, barricaded inside, is described. Methods The on-site investigation and a complete forensic autopsy were performed. In addition, we apply the psychological autopsy method which gathered enough information to outline the positive diagnosis of suicide. We also made a brief literature review on the suicide risk factors and the behavioral changes that occurred during the COVID-19 pandemic in schizophrenic patients. Results The forensic autopsy revealed that he presented a complex craniofacial trauma as the cause of death (with scalp lacerations, frontal fracture, subarachnoid hemorrhage, and frontal cerebral contusions) associated with torso trauma (with self-inflicted stabbed wounds) with bruises and abrasions on the limbs. The injuries that caused death were self-inflicted and ensued repeatedly hitting his head against blunt objects. Using the psychological autopsy method, we found out that he presented multiple psychiatric hospitalizations for schizophrenia for almost 10 years, recently with reduced compliance to treatment. We also documented two previous suicide attempts and a gradual deterioration of his mental health. Conclusions We highlighted the role of the psychological autopsy (in addition to the judicial investigation and the forensic autopsy) for the diagnosis of committed suicide, for making a rigorous differential diagnosis between accident, hetero-aggression, and suicide, and also in pin-pointing the suicide risk factors.
As a result of a greater worldwide aspiration for wealth and economic progress, increased use of natural resources for diverse industries resulted in increased pollution emissions, mainly carbon dioxide. Energy security, economic stability, job security, biodiversity loss, climate change, and global warming all require reconciliation and resolution now, more than ever before. This paper explores the causal relationship between CO2 emissions, economic growth, available energy, and employment for a panel of eight South-Eastern European countries from 1995 to 2019. We investigate the relationship using panel unit root tests, panel cointegration methods, and panel causality tests. The results show a short-run bidirectional panel causality between CO2 emissions and employment and between available energy and employment. The results further indicate a unidirectional causality from available energy and employment to GDP. The long-run causal relationship results show that the estimated coefficients of the lagged ECT in the CO2 emissions, GDP, and employment equations are statistically significant, implying these variables could play a significant role in the system’s adjustment process as it departs from long-run equilibrium. We also conducted a variance decomposition analysis, which allowed us to compare the extent of the individual factors’ contributions to each other over the next five years.
The authors have focused on organizational capabilities to achieve sustainable development goals (SDG) in the current study. In this regard, green knowledge management (GKM) and green innovation (specifically green technological and management innovation) are investigated. Moreover, it is also studied whether organizational green culture (OGC) strengthens organizational capabilities to innovate green and achieve sustainability goals via GKM. The researcher collected data from managers of different levels from manufacturing and service enterprises of all sizes and analyzed it through structural equation modeling. GKM strengthens organizational capabilities to achieve green innovation and SDG as per the findings. Moreover, green innovation has also been found to be a significant positive predictor of corporate sustainable development (CSD). It is also found that OGC strengthens the relationship between GKM and green innovation for achieving SDG. Furthermore, for all sizes of manufacturing and service organizations, GKM is found to be equally important.
In this study, we examine the contribution of nuclear, fossil (coal, oil, and gas), and renewable (hydro, solar, wind, biofuel) electricity sources to pollution in the globalization era, as measured by total greenhouse gases (GHG) produced by electricity per capita. We conduct an empirical investigation in a global panel of 163 countries which assesses both the concurrent and individual effects of alternative energy sources. Additionally, we implement a second model to assess the roles of various electricity sources on the carbon intensity of electricity generation. Robust GMM estimators show that fossil electricity is a major polluter and a driver of carbon intensity. Furthermore, nuclear and renewable energy reduce pollution on a global scale, with wind emerging as the most efficient energy source in the global fight against pollution and climate change. Moreover, globalization as measured by trade openness tends to reduce the carbon intensity of electricity production (CI), whereas biofuels have an increasing impact on CI. The findings have important policy implications, indicating that shifting to nuclear and renewable energy sources could help countries achieve their sustainable development goals more efficiently.
Background: Chronic pancreatitis (CP) has been described as a multifactorial, ongoing inflammatory condition of the pancreas of varying intensity that produces persistent pain, leading to exocrine and endocrine insufficiency and a decreased lifespan. Currently, there are three primary forms of chronic pancreatitis: chronic autoimmune pancreatitis (steroid-sensitive pancreatitis), chronic obstructive pancreatitis, and chronic calcific pancreatitis, the latter being closely related to excessive alcohol consumption for one or even two decades before the onset of symptoms. Case report: We present the case of a 29 year old man who required medical attention for a significant unintentional weight loss and a history of upper abdominal pain. Blood tests revealed substantial abnormalities, and the patient was admitted for further investigation. CT and MRI confirmed the presence of a pancreatic pseudocyst and extensive pancreatic parenchymal calcifications and revealed multiple hepatosplenic microabscesses of fungal etiology. Conclusions: Chronic calcifying pancreatitis is a complex clinical entity that can lead to secondary diabetes due to progressive destruction of the pancreatic parenchyma. Protein malnutrition, caused by malabsorption syndrome, immune cell dysfunction, and a high glucose environment caused by diabetes mellitus, may create a state of immunodeficiency, predisposing the patient to opportunistic infections.
The unprecedented scale of disinformation on the Internet for more than a decade represents a serious challenge for democratic societies. When this process is focused on a well-established subject such as climate change, it can subvert measures and policies that various governmental bodies have taken to mitigate the phenomenon. It is therefore essential to effectively identify and counteract fake news on climate change. To do this, our main contribution represents a novel dataset with more than 2300 articles written in French, gathered using web scraping from all types of media dealing with climate change. Manual labeling was performed by two annotators with three classes: “fake”, “biased”, and “true”. Machine Learning models ranging from bag-of-words representations used by an SVM to Transformer-based architectures built on top of CamemBERT were built to automatically classify the articles. Our results, with an F1-score of 84.75% using the BERT-based model at the article level coupled with hand-crafted features specifically tailored for this task, represent a strong baseline. At the same time, we highlight perceptual properties as text sequences (i.e., fake, biased, and irrelevant text fragments) at the sentence level, with a macro F1 of 45.01% and a micro F1 of 78.11%. Based on these results, our proposed method facilitates the identification of fake news, and thus contributes to better education of the public.
Water is a risk factor for epidemics of waterborne diseases with effects on human health. In 2019, new viral pneumonia cases occurred in China and spread worldwide. The aim of this study was to assess the feasibility and accuracy of a wastewater-based epidemiological (WBE) monitoring tool in a SARS-CoV-2 hot spot (Sibiu City metropolitan area), namely to highlight the correlation between the number of infections on the days of sampling and the amount of viral RNA detected in wastewater. Wastewater samples were collected once a week, and viral RNA was extracted and quantified. In parallel, the daily number of SARS-CoV-2 infections was obtained from the local council. The correlation between the number of infections and viruses detected in sewage was measured by Pearson correlation coefficients. The results show the amount of viral RNA in the wastewater is directly correlated with the number of infections reported in the week up to the sampling day and also the number of infections reported for the sampling day. Moreover, correlation coefficients show the amount of viral RNA in wastewater increases in advance of the increase in reported infection cases. Therefore, WBE can be used as a tool for monitoring virus spread trends in human communities and can help anticipate the trend of this type of viral infection.
The aim of the present paper is that of conducting a study on the basis of which the optimal parameters for the manufacturing of polymer parts by means of the single point incremental forming process can be chosen in such a way that the process forces have minimum values. Two poly-meric materials with a 3 mm thickness, polyamide and polyethylene, were chosen for the analysis. The other input parameters that were considered were: the punch diameter, the step on vertical direction and the wall angle. The Taguchi method was chosen for the design of experiments. Each of the input parameters, except for the material, were varied on three levels-for the punch diameter: 6 mm, 8 mm and 10 mm; for the step on vertical direction: 0.5 mm, 0.75 mm and 1 mm; and for the wall angle: 50°, 55° and 60°. Forces were measured in the three directions of the coordinate axes and the results were analyzed based on the signal-to-noise ratio and an analysis of variance with the aim of minimizing the values of the forces. Considering the input parameters analyzed, it was concluded that the forces are most influenced by the material, followed by the punch diameter, the step on vertical direction and the wall angle.
In view of the current agenda in the field of climate and environmental conservation, the requirements for environmental project appraisal are being tightened: the evaluation of environmental indicators of project implementation should be carried out on a par with indicators of its economic performance. Current approaches to the assessment of environmental and economic efficiency do not completely cover the negative environmental impacts of a project's implementation, and this reduces the effectiveness of the evaluation. Therefore, it is necessary to develop a system of environmental indicators that will address the specifics of the industry. This is made possible on the basis of determining a list of key factors that should be included in the evaluation system. The purpose of this study is to determine the most significant factors for establishing a simple yet thorough assessment framework to evaluate the efficiency of energy investment projects. Research methodology includes an a priori ranking method and analysis of interrelations between factors. Based on the results obtained, the authors have formed a list of key factors that could become the basis of a future system of environmental indicators for the efficiency assessment of energy projects.
Purpose Return to work is a complex and challenging process which takes various forms in different contexts. The aim of this study is to explore and compare cross-country differences in stakeholders’ experiences and views on actors, policies and practices relevant for return to work after long-term sickness absence. The comparative exploration is done in six countries with various legislative backgrounds, welfare and social dialogue systems. Methods Using a purposive sample, six multidisciplinary stakeholders group discussions were conducted in six countries: Belgium, Estonia, Ireland, Italy, Romania and Slovakia. A total of 51 individuals comprised of social partners, policymakers or representatives of public bodies and patient associations participated. An interpretative phenomenological analysis was employed to derive the most important themes in the discussions. Results Five major themes emerged from the group discussions. A graphic model is proposed to emphasize the variety of frameworks and processes across countries. Conclusions The core part of the return to work process is the dynamic relation between legislation, stakeholders and practices, which is influenced by broader national and societal factors. The cross-country variation in legislations, stakeholders and practices can be understood as a continuum, from low to high structuring, development and comprehensiveness. Although social dialogue appears to have a role in return to work process with variation across countries, it is not always on top of the agenda of social partners.
In this study, we introduce the expression dλ(x,y):=λ∥x∥+(1−λ)∥y∥−∥λx+(1−λ)y∥ on the real normed space X(X,∥·∥), where x,y∈X and λ∈R. We characterize this expression and find various estimates of it. We also obtain a generalization and some refinements of Maligranda’s inequality. Finally, we give some relations between dλ(x,y) and several types of angular distances between two nonzero vectors in a real normed space.
The COVID-19 pandemic context asserted the digitalization process in the European Union member countries five years forward (at least). The digital divide, a frequent debated issue was brought to the fore, and, under these circumstances, the proposed aim of the paper is to analyze the digitalization process, considering the data provided by Digital Economy and Society Index (DESI) and, additionally, the Stringency Index, that measure the governmental restrictions during the pandemic for 2020. From a methodological perspective, the empirical study focused on performing the Data Envelopment Analysis (DEA) non-parametric test. Measuring the digitalization efficiency or inefficiency of the European member states was conducted by using an output-oriented model, focused on output maximization for a given level of input, assuming Constant Returns to Scale (CRS). The results highlighted major discrepancies between the European countries. Solely eight countries out of 27 can be considered efficient in the digitalization processes during the COVID-19 pandemic. Based on the model, the most efficient EU countries could be considered peers/benchmarks for the inefficient ones, which should examine the best practices in order to improve their current situation.
To analyse the capacity of a soil to sequester organic carbon and the impact that deforestation and reforestation can have on its physical and chemical properties, specific laboratory analyses are necessary. According to a standard methodology, a number of 16 samples were taken from two different depths (0–10 cm, 10–20 cm) and from two different areas (degraded area and forest area) to identify if the type of land use and sampling depth are the key factors in changing the obtained values and also to prove the hypothesis according to which forest lands may have a higher carbon sequestration capacity. The highest value of soil organic carbon was identified in the forest area at a depth of 0–10 cm. The organic carbon values relative to the surface indicated a higher average in the forest area with a value of 36.19 t/ha, compared to the degraded area, with a value of 32.07 t/ha which indicated a greater capacity of carbon sequestration in forest lands. The forest lands also indicated the highest water holding capacity, with values of up to 100% at a depth of 0–10 cm. The higher values of organic carbon, its sequestration capacity and water holding capacity values in the forest lands compared to the values obtained on the degraded lands and at the surface of 0–10 cm compared to the depth of 10–20 showed that the type of land use and sampling depth influences the physico-chemical properties of the soil and leads to a visibly greater capacity to sequester carbon. These results match the expected ones and support our hypothesis
Our article conducts a critical reassessment of one of the most influential cultural myths in Eastern Europe throughout the nineteenth and twentieth centuries: the nationalist definition of peasantry as embodying the quintessence of the nation. In order to evaluate the imagological scope and ideological implications engendered by this so-called ‘people-nation myth’, we focus on the Romanian culture, whom we consider fully representative for the Eastern European context. More exactly, our study employs a distant reading of the Romanian rural novel from the first half of the twentieth century, precisely the literary subgenre supposed to reflect the coalescence between the peasantry and the nation. By analysing the co-occurrences in these novels between words belonging to the vocabularies of nation and rurality, we aim at showing that – contrary to traditional historiographic consensus – nation building has less to do with language or ethnicity, and much more to do with social emancipation.
This study investigates the impact of remote workplace factors on employees’ social and technical self-assessed performance during the COVID-19 pandemic. The impact of the variables belonging to the employee’s profile, organizational environment, and work-life balance categories on social and technical performance were analyzed, based on a survey of 801 Romanian employees, using ordinary least squares and quantile regression techniques. While the first method provided summary point estimates that calculated the average effect of the explanatory variables for the “average employee”, the second approach allowed us to focus on the effects explanatory variables have on the entire conditional distribution of the response variables, taking into account that this effect can be different for employees with different levels of performance. Job autonomy, engagement, communication skills, trust in co-workers, occupational self-efficacy, and family-work conflict, significantly influence both social and technical performance. PhD education and trust in management significantly influence social performance, while motivation, stress, the share of time spent in remote work, organizational commitment, children in the household, and household size, influence only technical performance.
Background: Numerous tools, including inflammatory biomarkers and lung injury severity scores, have been evaluated as predictors of disease progression and the requirement for intensive therapy in COVID-19 patients. This study aims to verify the predictive role of inflammatory biomarkers [monocyte to lymphocyte ratio (MLR), neutrophil to lymphocyte ratio (NLR), systemic inflammatory index (SII), Systemic Inflammation Response Index (SIRI), Aggregate Index of Systemic Inflammation (AISI), and interleukin-6 (IL-6)] and the total system score (TSS) in the need for invasive mechanical ventilation (IMV) and mortality in COVID-19 patients. Methods: The present study was designed as an observational, analytical, retrospective cohort study and included all patients over 18 years of age with a diagnosis of COVID-19 pneumonia, confirmed through real time-polymerase chain reaction (RT-PCR) and radiological chest CT findings admitted to County Emergency Clinical Hospital of Targu-Mureș, Romania, and Modular Intensive Care Unit of UMFST "George Emil Palade" of Targu Mures, Romania between January 2021 and December 2021. Results: Non-Survivors patients were associated with higher age (p = 0.01), higher incidence of cardiac disease [atrial fibrillation (AF) p = 0.0008; chronic heart failure (CHF) p = 0.01], chronic kidney disease (CKD; p = 0.02), unvaccinated status (p = 0.001), and higher pulmonary parenchyma involvement (p < 0.0001). Multivariate analysis showed a high baseline value for MLR, NLR, SII, SIRI, AISI, IL-6, and TSS independent predictor of adverse outcomes for all recruited patients. Moreover, the presence of AF, CHF, CKD, and dyslipidemia were independent predictors of mortality. Furthermore, AF and dyslipidemia were independent predictors of IMV need. Conclusions: According to our findings, higher MLR, NLR, SII, SIRI, AISI, IL-6, and TSS values at admission strongly predict IMV requirement and mortality. Moreover, patients above 70 with AF, dyslipidemia, and unvaccinated status highly predicted IMV need and fatality. Likewise, CHF and CKD were independent predictors of increased mortality.
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