University of Nicosia

Machine Learning (ML) methods have been proposed in the academic literature as alternatives to statistical ones for time series forecasting. Yet, scant evidence is available about their relative performance in terms of accuracy and computational requirements. The purpose of this paper is to evaluate such performance across multiple forecasting horizons using a large subset of 1045 monthly time series used in the M3 Competition. After comparing the post-sample accuracy of popular ML methods with that of eight traditional statistical ones, we found that the former are dominated across both accuracy measures used and for all forecasting horizons examined. Moreover, we observed that their computational requirements are considerably greater than those of statistical methods. The paper discusses the results, explains why the accuracy of ML models is below that of statistical ones and proposes some possible ways forward. The empirical results found in our research stress the need for objective and unbiased ways to test the performance of forecasting methods that can be achieved through sizable and open competitions allowing meaningful comparisons and definite conclusions.

This article is on representation of basis and the basis selection of techniques. The representation of this two is performed either by the method of probability random sampling or by the method of non-probability random sampling. The selection of random type is done by probability random sampling while the non-selection type is by non-probability probability random sampling. This selection of techniques is talking about either without control (unrestricted) or with control (restricted) when individually the element of each sample is selected from a given totality, the drawn of sample element goes with unrestricted while all the other types of the sampling is to be considered as a restricted sampling.

Abstract Over the past few years, the popularity of social media influencers (SMIs) has been growing exponentially, making influencer marketing (IM) prevalent in firm strategies. Despite the mounting interest of researchers and practitioners, the resulting scholarly work remains divergent, partial and fragmented. In light of the pivotal role of SMIs on the consumer decision journey and as this research domain is still developing, a comprehensive and critical overview of extant research on this topic is sorely needed. In response, this paper is the first to consolidate the present state of research on IM within social media settings. More specifically, a systematic review of relevant studies published in peer‐reviewed academic journals across diverse fields was conducted in order to identify key themes and dominant concepts. The analysis of 68 articles from 29 Chartered Association of Business Schools‐ranked journals forges a robust understanding of this phenomenon, shedding light on the mechanisms underlying the appeal of SMIs and their influential power in shaping consumer attitudes and behaviour. Based on the analysis, an integrative multidimensional framework is presented that considers antecedents, mediators and moderators of potential outcomes, as well as contextual factors that translate into consumer behaviour. In so doing, various research gaps are identified and avenues for future research are proposed that reflect important emerging areas and unexplored realms with reference to theory, context and methodology. Conclusively, implications of this study for theory and practice are discussed.

AIMS: To determine whether the Joint European Societies guidelines on cardiovascular prevention are being followed in everyday clinical practice of secondary prevention and to describe the lifestyle, risk factor and therapeutic management of coronary patients across Europe. METHODS AND RESULTS: EUROASPIRE IV was a cross-sectional study undertaken at 78 centres from 24 European countries. Patients <80 years with coronary disease who had coronary artery bypass graft, percutaneous coronary intervention or an acute coronary syndrome were identified from hospital records and interviewed and examined ≥ 6 months later. A total of 16,426 medical records were reviewed and 7998 patients (24.4% females) interviewed. At interview, 16.0% of patients smoked cigarettes, and 48.6% of those smoking at the time of the event were persistent smokers. Little or no physical activity was reported by 59.9%; 37.6% were obese (BMI ≥ 30 kg/m(2)) and 58.2% centrally obese (waist circumference ≥ 102 cm in men or ≥88 cm in women); 42.7% had blood pressure ≥ 140/90 mmHg (≥140/80 in people with diabetes); 80.5% had low-density lipoprotein cholesterol ≥ 1.8 mmol/l and 26.8% reported having diabetes. Cardioprotective medication was: anti-platelets 93.8%; beta-blockers 82.6%; angiotensin-converting enzyme inhibitors/angiotensin receptor blockers 75.1%; and statins 85.7%. Of the patients 50.7% were advised to participate in a cardiac rehabilitation programme and 81.3% of those advised attended at least one-half of the sessions. CONCLUSION: A large majority of coronary patients do not achieve the guideline standards for secondary prevention with high prevalences of persistent smoking, unhealthy diets, physical inactivity and consequently most patients are overweight or obese with a high prevalence of diabetes. Risk factor control is inadequate despite high reported use of medications and there are large variations in secondary prevention practice between centres. Less than one-half of the coronary patients access cardiac prevention and rehabilitation programmes. All coronary and vascular patients require a modern preventive cardiology programme, appropriately adapted to medical and cultural settings in each country, to achieve healthier lifestyles, better risk factor control and adherence with cardioprotective medications.

Although academic production in intelligent automation (e.g. artificial intelligence, robotics) has grown rapidly, we still lack a comprehensive understanding of the impacts of the utilization of these technologies in human resource management (HRM) at an organizational (firms) and individual (employees) level. This study therefore aims to systematize the academic inputs on intelligent automation so far and to clarify what are its main contributions to and challenges for HRM. In a systematic search of 13,136 potentially relevant studies published in the top HRM, international business (IB), general management (GM) and information management (IM) journals, we found 45 articles studying artificial intelligence, robotics and other advanced technologies within HRM settings. Results show that intelligent automation technologies constitute a new approach to managing employees and enhancing firm performance, thus offering several opportunities for HRM but also considerable challenges at a technological and ethical level. The impact of these technologies has been identified to concentrate on HRM strategies, namely, job replacement, human-robot/AI collaboration, decision-making and learning opportunities, and HRM activities, namely, recruiting, training and job performance. This study discusses these shifts in detail, along with the main contributions to theory and practice and directions for future research.

The M4 Competition follows on from the three previous M competitions, the purpose of which was to learn from empirical evidence both how to improve the forecasting accuracy and how such learning could be used to advance the theory and practice of forecasting. The aim of M4 was to replicate and extend the three previous competitions by: (a) significantly increasing the number of series, (b) expanding the number of forecasting methods, and (c) including prediction intervals in the evaluation process as well as point forecasts. This paper covers all aspects of M4 in detail, including its organization and running, the presentation of its results, the top-performing methods overall and by categories, its major findings and their implications, and the computational requirements of the various methods. Finally, it summarizes its main conclusions and states the expectation that its series will become a testing ground for the evaluation of new methods and the improvement of the practice of forecasting, while also suggesting some ways forward for the field.

OBJECTIVE: To report the global, regional, and national burden of chronic obstructive pulmonary disease (COPD) and its attributable risk factors between 1990 and 2019, by age, sex, and sociodemographic index. DESIGN: Systematic analysis. DATA SOURCE: Global Burden of Disease Study 2019. MAIN OUTCOME MEASURES: Data on the prevalence, deaths, and disability adjusted life years (DALYs) of COPD, and its attributable risk factors, were retrieved from the Global Burden of Disease 2019 project for 204 countries and territories, between 1990 and 2019. The counts and rates per 100 000 population, along with 95% uncertainty intervals, were presented for each estimate. RESULTS: In 2019, 212.3 million prevalent cases of COPD were reported globally, with COPD accounting for 3.3 million deaths and 74.4 million DALYs. The global age standardised point prevalence, death, and DALY rates for COPD were 2638.2 (95% uncertainty intervals 2492.2 to 2796.1), 42.5 (37.6 to 46.3), and 926.1 (848.8 to 997.7) per 100 000 population, which were 8.7%, 41.7%, and 39.8% lower than in 1990, respectively. In 2019, Denmark (4299.5), Myanmar (3963.7), and Belgium (3927.7) had the highest age standardised point prevalence of COPD. Egypt (62.0%), Georgia (54.9%), and Nicaragua (51.6%) showed the largest increases in age standardised point prevalence across the study period. In 2019, Nepal (182.5) and Japan (7.4) had the highest and lowest age standardised death rates per 100 000, respectively, and Nepal (3318.4) and Barbados (177.7) had the highest and lowest age standardised DALY rates per 100 000, respectively. In men, the global DALY rate of COPD increased up to age 85-89 years and then decreased with advancing age, whereas for women the rate increased up to the oldest age group (≥95 years). Regionally, an overall reversed V shaped association was found between sociodemographic index and the age standardised DALY rate of COPD. Factors contributing most to the DALYs rates for COPD were smoking (46.0%), pollution from ambient particulate matter (20.7%), and occupational exposure to particulate matter, gases, and fumes (15.6%). CONCLUSIONS: Despite the decreasing burden of COPD, this disease remains a major public health problem, especially in countries with a low sociodemographic index. Preventive programmes should focus on smoking cessation, improving air quality, and reducing occupational exposures to further reduce the burden of COPD.

Natriuretic peptide [NP; B-type NP (BNP), N-terminal proBNP (NT-proBNP), and midregional proANP (MR-proANP)] concentrations are quantitative plasma biomarkers for the presence and severity of haemodynamic cardiac stress and heart failure (HF). End-diastolic wall stress, intracardiac filling pressures, and intracardiac volumes seem to be the dominant triggers. This paper details the most important indications for NPs and highlights 11 key principles underlying their clinical use shown below. NPs should always be used in conjunction with all other clinical information. NPs are reasonable surrogates for intracardiac volumes and filling pressures. NPs should be measured in all patients presenting with symptoms suggestive of HF such as dyspnoea and/or fatigue, as their use facilitates the early diagnosis and risk stratification of HF. NPs have very high diagnostic accuracy in discriminating HF from other causes of dyspnoea: the higher the NP, the higher the likelihood that dyspnoea is caused by HF. Optimal NP cut-off concentrations for the diagnosis of acute HF (very high filling pressures) in patients presenting to the emergency department with acute dyspnoea are higher compared with those used in the diagnosis of chronic HF in patients with dyspnoea on exertion (mild increase in filling pressures at rest). Obese patients have lower NP concentrations, mandating the use of lower cut-off concentrations (about 50% lower). In stable HF patients, but also in patients with other cardiac disorders such as myocardial infarction, valvular heart disease, atrial fibrillation or pulmonary embolism, NP concentrations have high prognostic accuracy for death and HF hospitalization. Screening with NPs for the early detection of relevant cardiac disease including left ventricular systolic dysfunction in patients with cardiovascular risk factors may help to identify patients at increased risk, therefore allowing targeted preventive measures to prevent HF. BNP, NT-proBNP and MR-proANP have comparable diagnostic and prognostic accuracy. In patients with shock, NPs cannot be used to identify cause (e.g. cardiogenic vs. septic shock), but remain prognostic. NPs cannot identify the underlying cause of HF and, therefore, if elevated, must always be used in conjunction with cardiac imaging.

This position statement from the Heart Failure Association of the European Society of Cardiology Cardio-Oncology Study Group in collaboration with the International Cardio-Oncology Society presents practical, easy-to-use and evidence-based risk stratification tools for oncologists, haemato-oncologists and cardiologists to use in their clinical practice to risk stratify oncology patients prior to receiving cancer therapies known to cause heart failure or other serious cardiovascular toxicities. Baseline risk stratification proformas are presented for oncology patients prior to receiving the following cancer therapies: anthracycline chemotherapy, HER2-targeted therapies such as trastuzumab, vascular endothelial growth factor inhibitors, second and third generation multi-targeted kinase inhibitors for chronic myeloid leukaemia targeting BCR-ABL, multiple myeloma therapies (proteasome inhibitors and immunomodulatory drugs), RAF and MEK inhibitors or androgen deprivation therapies. Applying these risk stratification proformas will allow clinicians to stratify cancer patients into low, medium, high and very high risk of cardiovascular complications prior to starting treatment, with the aim of improving personalised approaches to minimise the risk of cardiovascular toxicity from cancer therapies.

What will be the global impact of the novel coronavirus (COVID-19)? Answering this question requires accurate forecasting the spread of confirmed cases as well as analysis of the number of deaths and recoveries. Forecasting, however, requires ample historical data. At the same time, no prediction is certain as the future rarely repeats itself in the same way as the past. Moreover, forecasts are influenced by the reliability of the data, vested interests, and what variables are being predicted. Also, psychological factors play a significant role in how people perceive and react to the danger from the disease and the fear that it may affect them personally. This paper introduces an objective approach to predicting the continuation of the COVID-19 using a simple, but powerful method to do so. Assuming that the data used is reliable and that the future will continue to follow the past pattern of the disease, our forecasts suggest a continuing increase in the confirmed COVID-19 cases with sizable associated uncertainty. The risks are far from symmetric as underestimating its spread like a pandemic and not doing enough to contain it is much more severe than overspending and being over careful when it will not be needed. This paper describes the timeline of a live forecasting exercise with massive potential implications for planning and decision making and provides objective forecasts for the confirmed cases of COVID-19.

Our understanding of the mechanisms of airborne transmission of viruses is incomplete. This paper employs computational multiphase fluid dynamics and heat transfer to investigate transport, dispersion, and evaporation of saliva particles arising from a human cough. An ejection process of saliva droplets in air was applied to mimic the real event of a human cough. We employ an advanced three-dimensional model based on fully coupled Eulerian-Lagrangian techniques that take into account the relative humidity, turbulent dispersion forces, droplet phase-change, evaporation, and breakup in addition to the droplet-droplet and droplet-air interactions. We computationally investigate the effect of wind speed on social distancing. For a mild human cough in air at 20 °C and 50% relative humidity, we found that human saliva-disease-carrier droplets may travel up to unexpected considerable distances depending on the wind speed. When the wind speed was approximately zero, the saliva droplets did not travel 2 m, which is within the social distancing recommendations. However, at wind speeds varying from 4 km/h to 15 km/h, we found that the saliva droplets can travel up to 6 m with a decrease in the concentration and liquid droplet size in the wind direction. Our findings imply that considering the environmental conditions, the 2 m social distance may not be sufficient. Further research is required to quantify the influence of parameters such as the environment's relative humidity and temperature among others.

BACKGROUND: Neck pain is one of the most common musculoskeletal disorders, having an age-standardised prevalence rate of 27.0 per 1000 population in 2019. This literature review describes the global epidemiology and trends associated with neck pain, before exploring the psychological and biological risk factors associated with the initiation and progression of neck pain. METHODS: The PubMed database and Google Scholar search engine were searched up to May 21, 2021. Studies were included that used human subjects and evaluated the effects of biological or psychological factors on the occurrence or progression of neck pain, or reported its epidemiology. RESULTS: Psychological risk factors, such as long-term stress, lack of social support, anxiety, and depression are important risk factors for neck pain. In terms of the biological risks, neck pain might occur as a consequence of certain diseases, such as neuromusculoskeletal disorders or autoimmune diseases. There is also evidence that demographic characteristics, such as age and sex, can influence the prevalence and development of neck pain, although further research is needed. CONCLUSIONS: The findings of the present study provide a comprehensive and informative overview that should be useful for the prevention, diagnosis, and management of neck pain.

BACKGROUND: The COVID-19 pandemic triggered vast governmental lockdowns. The impact of these lockdowns on mental health is inadequately understood. On the one hand such drastic changes in daily routines could be detrimental to mental health. On the other hand, it might not be experienced negatively, especially because the entire population was affected. METHODS: The aim of this study was to determine mental health outcomes during pandemic induced lockdowns and to examine known predictors of mental health outcomes. We therefore surveyed n = 9,565 people from 78 countries and 18 languages. Outcomes assessed were stress, depression, affect, and wellbeing. Predictors included country, sociodemographic factors, lockdown characteristics, social factors, and psychological factors. RESULTS: Results indicated that on average about 10% of the sample was languishing from low levels of mental health and about 50% had only moderate mental health. Importantly, three consistent predictors of mental health emerged: social support, education level, and psychologically flexible (vs. rigid) responding. Poorer outcomes were most strongly predicted by a worsening of finances and not having access to basic supplies. CONCLUSIONS: These results suggest that on whole, respondents were moderately mentally healthy at the time of a population-wide lockdown. The highest level of mental health difficulties were found in approximately 10% of the population. Findings suggest that public health initiatives should target people without social support and those whose finances worsen as a result of the lockdown. Interventions that promote psychological flexibility may mitigate the impact of the pandemic.

BACKGROUND: Anemia is a common disease which affects around 40% of children and 30% of reproductive age women and can have major health consequences. The present study reports the global, regional and national burden of anemia and its underlying causes between 1990 and 2019, by age, sex and socio-demographic index (SDI). METHODS: Publicly available data on the point prevalence and years lived with disability (YLDs) were retrieved from the global burden of disease (GBD) 2019 study for 204 countries and territories between 1990 and 2019. The point prevalence, YLD counts and rates per 100,000 population were presented, along with their corresponding 95% uncertainty intervals. RESULTS: In 2019, the global age-standardized point prevalence and YLD rates for anemia were 23,176.2 (22,943.5-23,418.6) and 672.4 (447.2-981.5) per 100,000 population, respectively. Moreover, the global age-standardized point prevalence and YLD rate decreased by 13.4% (12.1-14.5%) and 18.8% (16.9-20.8%), respectively, over the period 1990-2019. The highest national point prevalences of anemia were found in Zambia [49327.1 (95% UI: 46,838.5-51,700.1)], Mali [46890.1 (95% UI: 44,301.1-49,389.8)], and Burkina Faso [46117.2 (95% UI: 43,640.7-48,319.2)]. In 2019, the global point prevalence of anemia was highest in the 15-19 and 95+ age groups in females and males, respectively. Also, the burden of anemia was lower in regions with higher socio-economic development. Globally, most of the prevalent cases were attributable to dietary iron deficiency, as well as hemoglobinopathies and hemolytic anemias. CONCLUSIONS: Anemia remains a major health problem, especially among females in less developed countries. The implementation of preventive programs with a focus on improving access to iron supplements, early diagnosis and the treatment of hemoglobinopathies should be taken into consideration.

Cardiogenic shock (CS) is a complex multifactorial clinical syndrome with extremely high mortality, developing as a continuum, and progressing from the initial insult (underlying cause) to the subsequent occurrence of organ failure and death. There is a large spectrum of CS presentations resulting from the interaction between an acute cardiac insult and a patient's underlying cardiac and overall medical condition. Phenotyping patients with CS may have clinical impact on management because classification would support initiation of appropriate therapies. CS management should consider appropriate organization of the health care services, and therapies must be given to the appropriately selected patients, in a timely manner, whilst avoiding iatrogenic harm. Although several consensus-driven algorithms have been proposed, CS management remains challenging and substantial investments in research and development have not yielded proof of efficacy and safety for most of the therapies tested, and outcome in this condition remains poor. Future studies should consider the identification of the new pathophysiological targets, and high-quality translational research should facilitate incorporation of more targeted interventions in clinical research protocols, aimed to improve individual patient outcomes. Designing outcome clinical trials in CS remains particularly challenging in this critical and very costly scenario in cardiology, but information from these trials is imperiously needed to better inform the guidelines and clinical practice. The goal of this review is to summarize the current knowledge concerning the definition, epidemiology, underlying causes, pathophysiology and management of CS based on important lessons from clinical trials and registries, with a focus on improving in-hospital management.

Abstract This study examines the nature of interaction in an online course from both teacher and student perspectives. Major components of a conceptual framework to identify interaction were identified. Data analysis suggested that the structure of the course, class size, feedback, and prior experience with computer‐mediated communication all influenced interaction. Results of the study reconceptualize interaction as a theoretical construct and emphasize the importance of socially constructed meanings from the participants’ perspectives.

Data on comprehensive population-based surveillance of antimicrobial resistance is lacking. In low- and middle-income countries, the challenges are high due to weak laboratory capacity, poor health systems governance, lack of health information systems, and limited resources. Developing countries struggle with political and social dilemma, and bear a high health and economic burden of communicable diseases. Available data are fragmented and lack representativeness which limits their use to advice health policy makers and orientate the efficient allocation of funding and financial resources on programs to mitigate resistance. Low-quality data means soaring rates of antimicrobial resistance and the inability to track and map the spread of resistance, detect early outbreaks, and set national health policy to tackle resistance. Here, we review the barriers and limitations of conducting effective antimicrobial resistance surveillance, and we highlight multiple incremental approaches that may offer opportunities to strengthen population-based surveillance if tailored to the context of each country.

In this study, we present the results of the M5 “Accuracy” competition, which was the first of two parallel challenges in the latest M competition with the aim of advancing the theory and practice of forecasting. The main objective in the M5 “Accuracy” competition was to accurately predict 42,840 time series representing the hierarchical unit sales for the largest retail company in the world by revenue, Walmart. The competition required the submission of 30,490 point forecasts for the lowest cross-sectional aggregation level of the data, which could then be summed up accordingly to estimate forecasts for the remaining upward levels. We provide details of the implementation of the M5 “Accuracy” challenge, as well as the results and best performing methods, and summarize the major findings and conclusions. Finally, we discuss the implications of these findings and suggest directions for future research.

BACKGROUND: There is a high prevalence of children and young people (CYP) experiencing mental health (MH) problems. Owing to accessibility, affordability, and scalability, an increasing number of digital health interventions (DHIs) have been developed and incorporated into MH treatment. Studies have shown the potential of DHIs to improve MH outcomes. However, the modes of delivery used to engage CYP in digital MH interventions may differ, with implications for the extent to which findings pertain to the level of engagement with the DHI. Knowledge of the various modalities could aid in the development of interventions that are acceptable and feasible. OBJECTIVE: This review aimed to (1) identify modes of delivery used in CYP digital MH interventions, (2) explore influencing factors to usage and implementation, and (3) investigate ways in which the interventions have been evaluated and whether CYP engage in DHIs. METHODS: A literature search was performed in the Cochrane Library, Excerpta Medica dataBASE (EMBASE), Medical Literature Analysis and Retrieval System Online (MEDLINE), and PsycINFO databases using 3 key concepts "child and adolescent mental health," "digital intervention," and "engagement." Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed using rigorous inclusion criteria and screening by at least two reviewers. The selected articles were assessed for quality using the mixed methods appraisal tool, and data were extracted to address the review aims. Data aggregation and synthesis were conducted and presented as descriptive numerical summaries and a narrative synthesis, respectively. RESULTS: This study identified 6 modes of delivery from 83 articles and 71 interventions for engaging CYP: (1) websites, (2) games and computer-assisted programs, (3) apps, (4) robots and digital devices, (5) virtual reality, and (6) mobile text messaging. Overall, 2 themes emerged highlighting intervention-specific and person-specific barriers and facilitators to CYP's engagement. These themes encompassed factors such as suitability, usability, and acceptability of the DHIs and motivation, capability, and opportunity for the CYP using DHIs. The literature highlighted that CYP prefer DHIs with features such as videos, limited text, ability to personalize, ability to connect with others, and options to receive text message reminders. The findings of this review suggest a high average retention rate of 79% in studies involving various DHIs. CONCLUSIONS: The development of DHIs is increasing and may be of interest to CYP, particularly in the area of MH treatment. With continuous technological advancements, it is important to know which modalities may increase engagement and help CYP who are facing MH problems. This review identified the existing modalities and highlighted the influencing factors from the perspective of CYP. This knowledge provides information that can be used to design and evaluate new interventions and offers important theoretical insights into how and why CYP engage in DHIs.

Pain is a subjective experience that is influenced by genetics, gender, social, cultural and personal parameters. Opposed to chronic pain, which by definition has to last for at least 3 months, acute pain is mostly because of trauma, acute medical conditions or treatment. The link between mood disorders and acute pain has proven to be increasingly significant since the link is bi-directional, and both act as risk factors for each other. Depression and anxiety are associated with increased perception of pain severity, whereas prolonged duration of acute pain leads to increased mood dysregulation. Although both depression and anxiety have a proven association with acute pain, the link between depression and acute pain is more thoroughly studied. Pain can be the presenting or sole complaint in depressed patients who present to primary care practices and is often overlooked by clinicians. However, reports on the perception of experimentally-induced pain in depressed patients are mixed, showing both an increased and decreased pain threshold and pain tolerance across various studies. Although less data is published about anxiety and pain, the relationship is consistent across studies as increased anxiety leads to increased severity of pain perceived and decreased pain tolerance. Anxiety as well as fear, stress, and catastrophizing are also shown to be mediators in the causal pathway between pain and disability.