Future Events Research Articles

Analysis of the relationship between the profitability of market portfolios and the profitability of shares of companies in the oil sector

Purpose: This article aims to elucidate whether the particularity of the high level of explanation of the relationship between the return on the market and the return on shares of companies in the oil sector in Brazil occurs similarly in other markets.
 Methodology: The oil companies considered were listed as the main ones by Forbes, Fortune and Exame magazines. Their shares and market movement were obtained from their respective host countries stock exchanges, and other information on institutional websites (e.g: OPEC - Organization of the Petroleum Exporting Countries). As theoretical support, CAPM and APT metrics were applied between from January 2, 2015, to March 31, 2021.
 Results: Considering the privileged position of the fuel sector for the movement of the level of economic activity of the countries, the result of this research confirmed that the particularity of the Brazilian scenario is observed in other countries with regard to the high level of explanation of the return of the superior market portfolio at 50%. The research observed that the Explanation Coefficient tends to capture in a more significant way the effects of crises that come from local economic contexts and impacts on the world economy, such as a possible reduction in the level of gross domestic product of countries such as the United States or China. As for the unexpected event, such as Covid-19, the model, in principle, did not present the same result, which could be observed in the quarterly analyses.
 Contributions of the Study: Research can help managers and investors, as by demonstrating similarities one can predict future events or assist in decision-making.

A Stratified Fuzzy Decision-Making Approach for Sustainable Circular Supplier Selection

Circular economy has attracted great attention as it meets environmental and social requirements. Selecting appropriate suppliers considering circular, and sustainability aspects for all industries is of great significance. However, addressing sustainable circular supplier selection (SCSS) problems is a difficult task due to the uncertainty in real-life cases in terms of possible future events and experts’ judgments. This article aims to address the SCSS problem considering the impacts of possible future events via a multiple-criteria decision-making framework. For this purpose, stratification theory is utilized to develop and practice a novel framework called stratified fuzzy full consistency method to identify the optimal weight coefficients of criteria considering the possible impacts of future events. Later, a novel extension of mixed aggregation by comprehensive normalization technique under fuzzy environment is developed to prioritize suppliers with respect to sustainability and circular economy criteria. To prove the practicability of the developed methodology, outcomes of a real case study related to a textile company in Turkey are presented. Furthermore, sensitivity analyses and a comparative analysis are conducted to illustrate the proposed model's performance under different conditions. According to the results, information disclosure, interests and rights of employees, and child labor are identified as top three criteria with values of 0.1112, 0.1102, and 0.1110, respectively.

Who Should I Engage With at What Time? A Missing Event-Aware Temporal Graph Neural Network.

Temporal graph neural network (GNN) has recently received significant attention due to its wide application scenarios, such as bioinformatics, knowledge graphs, and social networks. There are some temporal GNNs that achieve remarkable results. However, these works focus on future event prediction and are performed under the assumption that all historical events are observable. In real-world applications, events are not always observable, and estimating event time is as important as predicting future events. In this article, we propose, a missing event-aware temporal GNN, which uniformly models evolving graph structure and timing of events to support predicting what will happen in the future and when it will happen. models the dynamic of both observed and missing events as two coupled temporal point processes (TPPs), thereby incorporating the effects of missing events into the network. Experimental results on several real-world temporal graphs demonstrate that significantly outperforms the existing methods with up to 89% and 112% more accurate time and link prediction. Code can be found on https://github.com/HIT-ICES/TNNLS-MTGN.

The Tsunami Generated by the Gorringe Bank Fault: Analyzing Wave Heights and Travel Time in the Atlantic Coast of Morocco

Two hundred sixty-eight years (about three centuries) since the 1755 Lisbon tsunami, which provoked large-scale damage in Portugal, Spain and Morocco. Scientists in several countries have mobilized to develop investigative methods to study this extraordinary tsunami, with the aim of reducing the impact of waves in future events and protecting and warning populations at risk. However, the most important question remains whether the entire damaged community has sufficient information about the impact to prepare for tsunami risks. The aim of this paper is to determine the maximum wave heights in selected cities located within high-risk tsunami zones in Morocco, as well as the tsunami arrival time for each site. We used the Non-linear Shallow Water model With Nested Grids (NSWING) code to model tsunami propagation. Six cities were determined as observation points as being the subject of tsunami studies in previous work, namely Tangier, Asilah, Rabat, Casablanca, El-Jadida and Safi. The maximum wave height calculated within the Atlantic coast of Morocco exceeds 5 m in some locations and the first waves reach the Moroccan coast in 60 minutes. The authorities might utilize these results to develop evacuation plans.

Rheumatic heart disease presenting with paracentral acute middle maculopathy (PAMM): A case report from rural India

A 38-year-old gentleman presented to us with disturbance in his superior field of view for 3 days. His visual acuity in both eyes was 6/6, N6. The macula of the left eye had a hypopigmented band. OCT demonstrated hyperreflectivity of the inner plexiform, inner nuclear, and outer plexiform layers of the retina, and perimetry showed a corresponding visual field defect. The patient revealed a history of heart surgery 26 years ago, and an echocardiogram revealed mitral valve abnormalities. The history and findings led to a diagnosis of paracentral acute middle maculopathy (PAMM) secondary to rheumatic heart disease. The patient was referred to a cardiologist and started on anti-platelet medications. Thus, we report an unusual case of PAMM due to chronic rheumatic heart disease in a young male from remote rural India. In our case, we made sure to start the patient on anti-platelet medications to prevent future adverse events.

Identifying Factor Associations Emerging from an Academic Metaverse Event for Scholars in a Postpandemic World: Social Presence and Technology Self-Efficacy in Gather.Town.

COVID-19 has prompted conferences to transition to online formats, inadvertently diminishing their emphasis on the social element. In online events, a sense of presence leading to a sense of companionship is limited in conventional conferencing platforms. Although the extant body of research on virtual conferences is growing, academic events in the Metaverse get little attention. Such events and their relevance to social presence within the Metaverse and associations among observable factors are seldom discussed. This study examined the perspectives of scholars in an online seminar during COVID-19 hosted in Gather.Town, a Metaverse-like conferencing environment. A hypothetical model was built to determine whether social presence and technology self-efficacy impact scholars' satisfaction and facilitate academic interactions. Ninety-three scholars in an academic seminar for research projects in information and computer education were polled to obtain data, which was then evaluated using partial least squares structural equation modeling (PLS-SEM). The proposed model explained 57.1 percent of the variables, and the findings showed that social presence and technology self-efficacy had a positive and significant impact on academic interactions and exchanges, as well as technology self-efficacy playing an essential role in determining overall satisfaction. However, social presence does not appear to have a direct impact on satisfaction, implying that a positive academic experience may still be achieved with or without the feature of being with others supported by the Metaverse. Although digital communication will only become more diverse and intense, it is important to understand how to maintain the basic character of human interactions virtually, even amid a pandemic. This research attempts to shed light on some critical factors in creating a conducive environment for future Metaverse-like academic events.

Changes to Middle East and Southwest Asia Compound Drought and Heat since 1999

Abstract We diagnose physical factors related to frequent compound drought and heat extremes over a Middle East and Southwest Asia (MESA; 30°–40°N, 35°–65°E) region in a recent (1999–2022) compared to a prior (1951–98) period. The recent compound extremes were related to conflict, disease transmission, and water shortages in this already semiarid region. Observed estimates and four transient climate model ensembles are used to identify the effect of El Niño–Southern Oscillation (ENSO) and atmospheric forcing by greenhouse gases and aerosols on these compound extremes in autumn (September–November), winter (December–February), spring (March–May), and summer (June–August) that may lead to practical forecast skill for future compound events. Observations and climate models indicate that MESA compound drought and heat in the autumn, winter, and spring wet seasons for the recent period were related to the La Niña phase of ENSO and an attendant northward shift of the storm track that hinders precipitation-bearing storms from moving through MESA. A comparison of different conditions in the model simulations is used to isolate the effects of La Niña and the atmospheric forcing by greenhouse gases and aerosols on compound MESA drought and heat. A comparison of recent and prior periods in the climate models, which isolates the effects of the atmospheric forcing, indicates that greenhouse gases and aerosols are related to the increases in MESA heat frequency in all seasons. A comparison of La Niña to ENSO neutral and El Niño in the recent period of the climate models indicates that La Niña is related to increases in MESA drought frequency in the wet seasons. Significance Statement Compound drought and heat pose serious threats to the Middle East and Southwest Asia (MESA) where political and socioeconomic challenges leave its people vulnerable to climate extremes. In this region, frequent seasonal compound drought and heat in a recent (1999–2022) compared to a prior (1951–98) period were related to conflict and water shortages. Physical factors related to these compound extremes in the recent period over MESA were identified, potentially rendering future occurrences predictable. La Niña and atmospheric forcing by greenhouse gases and aerosols contributed to the compound extremes, with the former related to anomalously low precipitation in the September–November, December–February, and March–May wet seasons and the latter related to anomalous high temperatures in all seasons, including June–August.

Prevalence of Hyperuricemia and Its Risk Factors Among Residents of a Rural Field Practice Area in Belagavi, India

Background: Serum Uric Acid (SUA) is often overlooked in primary healthcare, primarily associated with Gouty Arthritis. However, the literature indicates its links to dyslipidaemia, cardiovascular diseases, hypertension, and metabolic syndrome. This study aimed to determine the prevalence of hyperuricemia and its associated risk factors among rural residents. Methodology: A cross-sectional study was conducted from January to May 2023, involving 300 individuals aged ≥30 during routine NCD screening. Data on socio-demographics, meat consumption habits, thiazide diuretic usage, and anthropometric measurements were collected. Blood samples were obtained for SUA analysis after informed consent. Results: Participants had a median age of 45 years, BMI of 25.41 kg/m², and SUA level of 5 mg/dl. The study revealed an overall hyperuricemia prevalence of 32.7%. While no significant associations were found between hyperuricemia and the variables analysed, a statistically significant positive linear correlation emerged between SUA levels and waist or hip circumference. Binary logistic regression showed a significant association between hyperuricemia and the frequency of meat consumption. Conclusion: This study suggests that SUA can serve as a valuable tool in primary healthcare. Identifying and treating individuals with hyperuricemia, and educating those at risk, can help prevent future vascular events.

Vascular Risk Factors and Their Influence on Migraine Phenotype in Older Adults

This comprehensive review examines the impact of vascular risk factors on the phenotypic expression of migraine in the elderly population. Migraine, particularly migraine with aura, has been established as a risk factor for ischemic lesions of the brain, stroke, and other cardiovascular diseases. The association between migraine and specific vascular events, such as stroke, myocardial infarction, and angina pectoris, underscores the need for a comprehensive understanding of the interplay between migraine and cardiovascular diseases. The challenges in differentiating migraine from vascular insults, especially in the elderly population, highlight the need for improved diagnostic and treatment strategies to address the complexities of managing migraine in this demographic. Patient education and treatment of modifiable risk factors may decrease future vascular events, emphasizing the importance of addressing vascular risk factors in migraine management. The potential impact of prevention and treatment of unfavorable arterial hemodynamics on neurocognitive outcomes underscores the broader implications of addressing vascular risk factors in migraine management. The clinical and public health relevance of understanding the modifiability of vascular risk factors in elderly migraine patients extends to addressing challenges in cancer survivorship, radiological emergency response, and rational person behavior, emphasizing the diverse applications of addressing vascular risk factors in healthcare and public health. Ultimately, the clinical and public health relevance of understanding the impact of vascular risk factors on the phenotypic expression of elderly migraine underscores the need for continued research and clinical vigilance in addressing the complex interplay between migraine and vascular risk factors in the elderly population.

Disruption of the Covid-19 pandemic on the agri-food sector: A systematic review of its implications in post-pandemic and future of food security

<abstract> <p>The unprecedented challenges posed by the global COVID-19 pandemic have significantly impacted various sectors, with the agri-food system proving especially vulnerable to disruptions. Ensuring food security and bolstering the resilience of agri-food systems in the aftermath of the pandemic has emerged as a crucial concern. Utilizing the PRISMA protocol, this systematic literature review systematically searched relevant databases and repositories using specific keywords related to agri-food security in the pre and post-pandemic context. The final review incorporated 37 articles. The results revealed that the pandemic profoundly impacted all facets of the agri-food sector, particularly agri-food systems. Despite this, we identified several measures that were implemented or recommended to mitigate disruptions caused by the pandemic and ensure the resilience of the agri-food sector for future similar events. Robust policy measures, promotion of urban agriculture, support for small-scale farmers, enhancement of the international market, technological innovations, collaborations, research and development, and the promotion of novel foods were all highlighted as crucial resilience measures. Policymakers, researchers, and stakeholders are urged to adopt a comprehensive approach encompassing these measures to build a resilient and secure food future in the post-pandemic era.</p> </abstract>

PreGLAM: A Predictive, Gameplay-based Layered Affect Model

We present the Predictive Gameplay-based Layered Affect Model (PreGLAM), an affective game spectator model that flexibly integrates into a game design process. PreGLAM combines elements of real-time Player Experience Models, and Affective Non-Player-Character models to output real-time estimated values for a spectator's valence, arousal, and tension during gameplay. Because tension is related to prospective events, PreGLAM attempts to predict future gameplay events. We implement and evaluate PreGLAM in a custom game <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Galactic Defense</i> , which we also describe. PreGLAM significantly outperforms a random walk time series in how accurately it matches ground-truth annotations, and has comparable accuracy to state of the art affect models.

Heat-related illness in Singapore: Descriptive analysis of a tertiary care center from 2008 to 2020

Background This study aimed to describe the clinical characteristics and epidemiology of heat-related illnesses presented at a tertiary hospital in Singapore. Method This retrospective observational study utilized electronic health records from the emergency department (ED) of Singapore General Hospital. Patients primarily diagnosed with heat-related illnesses from 2008 to 2020, were analyzed. The annual number of cases and the temporal trend of heat-related illnesses were described, along with the characteristics of patients. Results Among the 1,833,908 patients registered at the ED, 426 patients had diagnoses of heat-related illnesses. The median age (interquartile range [IQR]) was 32 (22, 43) years, with 303 (71%) being male and 201 (47%) not being Singapore citizens. The annual number of cases ranged from a minimum of 21 in 2019 to a maximum of 49 cases in 2015, except for four cases in 2020. Heat-related illnesses occurred most commonly on Sundays (233, 55%) and in December (97, 23%). A significant number of cases in December coincided with the day of an annually organized marathon (91, 21%). Approximately half of the total cases required hospitalization, with 183 (43%) admitted to the general ward and 31 (7%) admitted to the intensive care unit. The 30-day mortality was 2 (0.5%). Conclusion This descriptive study indicated the unique characteristics of heat-related illness in a tertiary care hospital in Singapore. These local contexts may be valuable to consider preventative measures for heat-related illness, in preparation for future extreme weather events related to climate change.

Resilience of transportation infrastructure networks to road failures.

Anthropogenic climate change drives extreme weather events, leading to significant consequences for both society and the environment. This includes damage to road infrastructure, causing disruptions in transportation, obstructing access to emergency services, and hindering humanitarian organizations after natural disasters. In this study, we develop a novel method for analyzing the impacts of natural hazards on transportation networks rooted in the gravity model of travel, offering a fresh perspective to assess the repercussions of natural hazards on transportation network stability. Applying this approach to the Ahr valley flood of 2021, we discovered that the destruction of bridges and roads caused major bottlenecks, affecting areas considerably distant from the flood's epicenter. Furthermore, the flood-induced damage to the infrastructure also increased the response time of emergency vehicles, severely impeding the accessibility of emergency services. Our findings highlight the need for targeted road repair and reinforcement, with a focus on maintaining traffic flow for emergency responses. This research provides a new perspective that can aid in prioritizing transportation network resilience measures to reduce the economic and social costs of future extreme weather events.

Detecting Abrupt Changes in High-Dimensional Self-Exciting Poisson Processes

High-dimensional self-exciting point processes have been widely used in many application areas to model discrete event data in which past and current events affect the likelihood of future events. In this paper, we are concerned with detecting abrupt changes of the coefficient matrices in discrete-time high-dimensional self-exciting Poisson processes, which have yet to be studied in the existing literature due to both theoretical and computational challenges rooted in the non-stationary and high-dimensional nature of the underlying process. We propose a penalized dynamic programming approach which is supported by a theoretical rate analysis and numerical evidence.

Tracking seismicity in an underfunded institution: The case of La Soufrière St Vincent volcanic eruption 2020–2021

An unusual volcanic transition was recorded at La Soufrière Volcano in the Lesser Antilles during the 2020–2021 eruptive episode. Initial activity was an effusive phase that lasted three months and turned explosive on 9 April 2021. Although the transition was recognised when it occurred and people were timely evacuated thanks to the detection of subtle geophysical patterns, this work attempts to extract more detailed information from the seismic dataset to improve the monitoring of future events. Due to network limitations and the low amplitudes of the recorded signals, the elaboration of a conceptual model from earthquake locations turned out to be challenging. Accordingly, new analysis methods were developed, including: seismic interferometry using cross-correlation functions to locate the sources of tremor and explosions and a fluid-filled crack model to quantify the bulk modulus of magma stored in the system and translate it to gas content. Both are now applied in quasi-real time for the interpretation of future unrest. The VT locations feature a NNW-SSE alignment across the eruption site with focal depths shallower than 4 km. The banded tremor located at shallow levels (∼1 km depth) and the explosions featured two distinct behaviours, deepening of sources as the eruption progressed, as well as the activation of near-surface sources associated with the eruptive jet. A fluid-filled crack model points to an injection of gas into the system on 9 April, which amounts to approximately 76% gas-volume fraction. We propose a volatile injection equivalent to a 7% gas-volume fraction entering the system on 12 March; however, it was not energetic enough to produce changes in the extrusion rate. Seismological analyses support the conceptual model proposed by Joseph et al. (2022), where a dome sealed the system with a minimal amount of gas exsolved (0.7% gas-volume fraction). For the onset of the explosive phase, the system accumulated enough gases to produce the dome collapse and cleared the vent, decreased the internal pressure and triggered fragmentation.

Characteristics and functions of predictive and directive memories and forecasts

AbstractEarlier research focused on three functions of recollecting the past self, social, and directive functions, but few studies examined the characteristics of events serving these functions. Moreover, research has neglected the function of prediction, which refers to predicting the future by recollecting the past. The current study distinguished the predictive function from the directive function and aimed to characterize memories and future events serving different functions by employing function prompts as cues. In addition, the frequency of using function‐cued memories for the other functions was measured. Results showed that predictive and directive function ratings of the predictive function cued events were significantly different. However, directive events served the predictive function as frequently as the directive function, indicating that the predictive function is a prerequisite for future planning conceptualized under the directive function. The results are indicative of a distinct predictive function and considerable overlap between functions of memories.

Association of mean pericoronary adipose tissue attenuation with different demographic factors in a subgroup of patients without coronary artery disease stratified by sex, body mass index, and age.

In patients without coronary artery disease (CAD), few studies have evaluated the association between mean pericoronary adipose tissue attenuation (PCATMA) and patient-based demographic factors, for example, age or sex. Therefore, the purpose of this study is to investigate the association between PCATMA and various demographic factors in patients without CAD. In this case-control study, the 806 patients who underwent coronary computed tomography angiography and were not diagnosed with CAD between July 2020 and July 2022 were retrospectively enrolled. Their PCATMA values of the proximal right coronary artery were measured automatically. Patients without CAD were stratified according to sex, body mass index (BMI), and age, and the relationship between PCATMA and different clinical characteristics was explored using Fisher's exact test or Chi-squared test and independent t-tests or Wilcoxon Mann-Whitney U tests. Compared to non-smoking women [-88.00 (-95.00, -81.00) HU], women who smoked [-84.00 (-94.00, -78.00) HU, P=0.037] had higher PCATMA values and a positive correlation with PCATMA (rs=0.101, P=0.036). Compared to non-hypertensive patients with BMI ≥24.91 kg/m2 [-87.00 (-95.00, -81.00) HU], hypertensive patients with BMI ≥24.91 kg/m2 [-84.00 (-92.00, -78.00) HU, P=0.004] had higher PCATMA values, and a positive correlation with PCATMA (rs=0.144, P=0.004). In a subgroup of patients without CAD stratified by sex, BMI, and age, PCATMA values were all higher in patients with dyslipidemia (women, men, BMI ≥24.91 kg/m2, BMI <24.91 kg/m2, age ≥55 years, and age <55 years: -82.00, -82.00, -81.50, -82.00, -81.00 and -83.50 HU, respectively) than in those without dyslipidemia (-89.00, -89.00, -89.00, -90.00, -90.00 and -88.00 HU, respectively; all P<0.001) and showed a positive relationship (rs=0.328, 0.339, 0.342, 0.326, 0.367, and 0.298, respectively; all P<0.001). Higher PCATMA attenuation values were observed in patients with dyslipidemia, smoking women, and hypertensive patients with BMI ≥24.91 kg/m2, suggesting that PCATMA values can be used to detect patients at high risk for future events with CAD even if they do not currently have atherosclerosis.

A Real-Time Redispatch Method to Evaluate the Contribution of Storage to Capacity Adequacy

This paper proposes a novel real-time redispatch method for energy storage systems (ESSs) in resource adequacy studies. In case of real-time contingencies, a realistic operating profile is generated for ESSs to enhance system reliability by mitigating loss of load events, while maintaining their market schedule to the extent possible. Contrary to the standard approaches in the literature, the proposed method neither adopts a perfect foresight for future events, such as generator failures, nor does it resort to “greedy” adequacy-oriented management strategies which are detached from normal operation. Instead, storages follow a market-driven schedule, being suitably redispatched during real-time operation when necessary for adequacy reasons, subject to their energy and power capacity constraints. The redispatch method is deterministically formulated through a sequence of logical conditions and is integrated into a stochastic adequacy assessment model built upon Monte Carlo technique. Multiple battery energy storage configurations have been examined, with the Greek power system serving as a realistic case study, to evaluate the method against others available in the literature and calculate the capacity value of battery ESS.

Mental IQ Detection Using Machine Learning: A Review Paper

Abstract: A Mental IQ Detection using the ML technology is software based application which is designed to detect the mental IQ with their age.[1]Machine Learning is that develops algorithms by learning the hidden patterns of the datasets used it to make predictions on new similar type data. We are using Machine learning for the mental IQ detection because we can improve accuracy of the software application, it has large amount of data Making predictions about future event ML has wide range of libraries and algorithm that are available.[2]We will be using KNN Algorithm, Logistic Algorithm, Linear Algorithm, etc. IQ test continue to be one of most reliable tools to measure intelligence skills of the human. The Intelligence Quotient (IQ) tests and the corresponding psychometric explanations dominate both the scientific and popular views about human intelligence. It starts with getting information from registration form using java on android studio, where each user will have to give test series provided by the developer.[3] After user gives test series, that’s where ML comes in where we need to process the date using different libraries and algorithms to detect the Mental IQ of the user with their age, ensuring transparency and security of each user

A Systematic Review On Green Banking Disclosure

This paper presents a systematic review of the topic of Green Banking Disclosure (GBD). GBD has been a growing concept since 2008, with its development bringing about changes, both in terms of the natural and social environments. As such, it is crucial to give it due attention. The study reviewed 50 papers, including 65 empirical ones, and yielded four main findings. Firstly, in terms of theory, legitimacy theory, stakeholder theory, and the concept of Spider profit growth, which serves as an indicator of a company's fund utilization efficiency, were prevalent in the literature. These theories provide a basis for evaluating company management performance, motivating management, and controlling economic resource allocation, ultimately aiding in forecasting future profits and economic events. Secondly, the Green Coin Rating (GCR) concept, comprising six points, played a significant role in the discourse on green banking. Thirdly, the majority of GBD studies were conducted in Muslim-majority countries. The research population included all financial reports of Islamic Commercial Banks during the period 2016-2019. The sample consisted of nine Islamic Commercial Banks that published annual reports up to 2019 and met the criteria for implementing the Green Banking concept. The study suggests that future research endeavors should consider integrating both primary and secondary data to assess the implementation of Green Banking and green financing in banking institutions. This approach would lead to a more comprehensive understanding of the subject and provide a more communicative perspective for customers.