Search Results (49)

The study relies on an extensive dataset (≈1.86 million news headlines) to investigate the heterogeneity and predictive power of explicit sentiment signals (TextBlob, VADER, and FinBERT) and implied sentiment (VIX) for stock market trends. We find that news content predominantly consists of objective or neutral information, with only a small portion carrying subjective or emotive weight. There is a structural market bias toward upswings (bullish market states). Market behavior appears anticipatory rather than reactive: forward-looking implied sentiment captures a substantial share (≈45–50%) of the variation in stock returns. By contrast, sentiment scores, even when disaggregated into firm- and non-firm-specific subscores, lack robust predictive power. However, weekend and holiday sentiment contains modest yet valuable market signals. Algorithm-wise, Gradient Boosting Machine (GBM) stands out in both classification (bullish vs. bearish) and regression tasks. Neither FinBERT news sentiment, historical returns, nor implied volatility offer a consistently exploitable edge over market efficiency. Thus, our findings lend empirical support to both the weak-form and semi-strong forms of the Efficient Market Hypothesis. In the realm of exploitable trading strategies, markets remain an enigma against systematic alpha. Full article

Environmentally modified housing [EMH; windowless, insulated sidewalls and ceiling, thermostatically controlled ventilation fans) versus conventional housing [CVH; cross-ventilated, insulated ceiling, ceiling fans) improved broiler performance in the summer. The objective of this investigation was to determine whether social behaviors differed between two population densities (0.06 m²/chick [HD] or 0.07 m²/chick [LD]) in these houses. We used a randomized block statistical design, involving houses, population densities, observation times, and bird age. Behaviors were observed weekly, during the morning and the afternoon. Individual observers focused on the group of broilers in one of three defined 26.76 m² areas in each of the four pens in each house. Aggressive encounters, tail and back pecking, feather eating, thermoregulatory, preening, and flock mobility were recorded. Feather pecking, eating and aggressive encounters were expressed at greater rates in HD birds in CVH. A salt-deficient diet caused increased feather pecking and aggressive encounters, which decreased after correction of the mistake. Increased heat indices (HIs), HD, and greater light intensity in CVH influenced behaviors and mortality more severely than in EMH. In CVH and EMH, burrowing/thermoregulatory/resting activity increased with increasing HIs. Afternoon preening was elevated significantly in EMH. It was concluded that broilers reared in EMH were more comfortable and experienced improved welfare compared to those reared in CVH. Full article

To collect the energy generated by rotational motion in the natural environment, a piezoelectric electromagnetic hybrid energy harvester (HEH) based on a planetary gear system is proposed. The harvester combines piezoelectric and electromagnetic effects and is mainly used for collecting low-frequency rotational energy. The HEH has a compact structure and contains four sets of piezoelectric energy harvesters (PEHs) and electromagnetic energy harvesters (EMHs) inside. The working principle of the energy harvester is analyzed, its theoretical model is established, and a simulation analysis is conducted. To verify the effectiveness of the design, an experimental device is constructed. The results indicate that the HEH can generate an average output power of 250 mW under eight magnets and an external excitation frequency of 7 Hz. In actual power supply testing, the HEH can light up 60 LEDs and provide stable power supply for the temperature–humidity meter. Full article

This paper introduces advanced computational methods for stock price prediction, integrating Fast Recurrent Neural Networks (FastRNN) with meta-heuristic algorithms such as the Horse Herd Optimization Algorithm (HOA) and the Spotted Hyena Optimizer (SHO). By challenging the Efficient Market Hypothesis (EMH) and Random Walk Hypothesis, our research demonstrates the effectiveness of these hybrid models in semi-strong or weak-form efficient markets. The study leverages data from five listed Iranian companies (2011–2021) and 25 factors encompassing technical, fundamental, and economic considerations. Our findings highlight the superior accuracy of the FastRNN optimised by HOA, SHO, and a Generative Adversarial Network (GAN) in forecasting stock prices compared to conventional FastRNN models. This research contributes to the multidisciplinary field of computational economics, emphasising advanced computing capabilities to address complex economic problems through innovative econometrics, optimisation, and machine learning approaches. Full article

In this paper, pathohistological images of extramedullary hematopoiesis (EMH) in stomach mucosa in a 68-year-old female patient with treated osteomyelofibrosis are presented. The digestive system is a potential but uncommon site of EMH, with the gastric mucosa being particularly rare. According to the available literature, only 12 cases have been described. Full article

This study investigates the key factors which influence design learners’ behavioral intention to collaborate with AI in the educational metaverse (EMH-AIc). Engaging design learners in EMH-AIc enhances learning efficiency, personalizes learning experiences, and supports equitable and sustainable design education. However, limited research has focused on these influencing factors, leading to a lack of theoretical grounding for user behavior in this context. Drawing on social cognitive theory (SCT), this study constructs a three-dimensional theoretical model comprising the external environment, individual cognition, and behavior, validated within an EMH-AIc setting. By using Spatial.io’s Apache Art Studio as the experimental platform and analyzing data from 533 design learners with SPSS 27.0, SmartPLS 4.0, and partial least squares structural equation modeling (PLS-SEM), this study identifies those rewards, teacher support, and facilitating conditions in the external environment, with self-efficacy, outcome expectation, and trust in cognition also significantly influencing behavioral intention. Additionally, individual cognition mediates the relationship between the external environment and behavioral intention. This study not only extends SCT application within the educational metaverse but also provides actionable insights for optimizing design learning experiences, contributing to the sustainable development of design education. Full article

This study explores market efficiency and behavior by integrating key theories such as the Efficient Market Hypothesis (EMH), Adaptive Market Hypothesis (AMH), Informational Efficiency and Random Walk theory. Using LSTM enhanced by optimizers like Stochastic Gradient Descent (SGD), Adam, AdaGrad, and RMSprop, we analyze market inefficiencies in the Standard and Poor’s (SPX) index over a 22-year period. Our results reveal “pockets in time” that challenge EMH predictions, particularly with the AdaGrad optimizer at a size of the hidden layer (HS) of 64. Beyond forecasting, we apply the Dominguez–Lobato (DL) and General Spectral (GS) tests as part of the Martingale Difference Hypothesis to assess statistical inefficiencies and deviations from the Random Walk model. By emphasizing “informational efficiency”, we examine how quickly new information is reflected in stock prices. We argue that market inefficiencies are transient phenomena influenced by structural shifts and information flow, challenging the notion that forecasting alone can refute EMH. Additionally, we compare LSTM with ARIMA with Exponential Smoothing, and LightGBM to highlight the strengths and limitations of these models in financial forecasting. The LSTM model excels at capturing temporal dependencies, while LightGBM demonstrates its effectiveness in detecting non-linear relationships. Our comprehensive approach offers a nuanced understanding of market dynamics and inefficiencies. Full article

Since the early 1970s, the study of Black–Scholes (BS) partial differential equations (PDEs) under the Efficient Market Hypothesis (EMH) has been a subject of active research in financial engineering. It has now become obvious, even to casual observers, that the classical BS models derived under the EMH framework fail to account for a number of realistic price evolutions in real-time market data. An alternative approach to the EMH framework is the Fractal Market Hypothesis (FMH), which proposes better and clearer explanations of market behaviours during unfavourable market conditions. The FMH involves non-local derivatives and integral operators, as well as fractional stochastic processes, which provide better tools for explaining the dynamics of evolving market anomalies, something that classical BS models may fail to explain. In this work, using the FMH, we derive a time-fractional Black–Scholes partial differential equation (tfBS-PDE) and then transform it into a heat equation, which allows for ease of implementing a high-order numerical scheme for solving it. Furthermore, the stability and convergence properties of the numerical scheme are discussed, and overall techniques are applied to pricing European put option problems. Full article

Extramedullary hematopoiesis (EMH) serves as a compensatory mechanism in chronic hemolytic anemias, such as thalassemia, and can result in spinal cord compression. This case report highlights a 36-year-old woman with transfusion-dependent β-thalassemia (TDT) who presented with lower extremity motor deficiency, pelvic paresthesia, and bladder dysfunction. The patient had a history of lower back pain, bilateral lower limb weakness, and demonstrated poor compliance with iron chelation therapy. MRI findings indicated spinal cord compression attributable to extramedullary hematopoiesis. Due to the infeasibility of surgical intervention, the patient underwent hypertransfusion and iron chelation therapy. While neurological symptoms improved, urinary retention persisted. The patient continues to receive iron chelation treatment and undergo transfusions. Managing extramedullary hematopoiesis in thalassemia necessitates an individualized treatment approach. Full article

Apoptotic cells possess immunomodulatory effects that can be utilized to treat imbalanced immune conditions. Information on the preclinical safety of such treatment is sparse. In this study, the safety of apoptotic cells (Allocetra-OTS) was assessed in a GLP toxicological study on Sprague Dawley rats. Three doses of Allocetra-OTS or vehicle were administered intravenously (IV) for 3 consecutive days. Animals in the main study were sacrificed on day 4, while animals from the recovery groups were kept for 14 or 28 days. Allocetra-OTS was well tolerated, and no adverse effects were observed in terms of body weight, clinical signs, food consumption, or ophthalmologic observation. Thus, the No Observed Adverse Effect Level (NOAEL) dose was determined as the highest dose administered. An observed elevation in immune cells was suspected to be due to Allocetra-OTS, similarly to other clinical chemistry parameters; however, it was resolved in the recovery phases. Splenomegaly and dose-related extramedullary hematopoiesis (EMH) in the red pulp were observed, with no adverse events, and were considered to be a normal and expected reaction following the IV administration of cell-based therapies. In conclusion, under the conditions of this study, Allocetra-OTS was concluded to be safe, further supporting its potential candidacy for clinical studies. Full article

‘Falstaff^PBR’ is a pear variety released by CREA and New Plant in 2012. This study focused on the effects of various clonal rootstocks on the main productive and qualitative traits of ‘Falstaff^PBR’ scion. The rootstocks used were ‘EMC’, ‘EMH’, and ‘BA29’ for quince (Cydonia oblonga) and pear ‘Farold 40’ (Pyrus communis). Plants were planted in 2009 with a layout that, depending on the used rootstock, varied between 60 and 120 cm on the row, according to the rootstock standard planting system, and 350 cm between rows. The average yield calculated in the trail field in the 4 years of production (2014–2017) was over 22.7 tons ha⁻¹ on ‘BA29’, 22.8 tons ha⁻¹ on ‘EMH’, 16.3 tons ha⁻¹ on ‘Farold 40’, and 18.4 on ‘EMC’. Fruits of the plants grafted on ‘Farold 40’ always had a medium-to-high size, while fruits produced by the plants grafted onto ‘BA29’ have been larger in size since the first years of production. The plants grafted onto ‘EMH’ produced fruits with the highest percentage of red overcolor. The ‘EMH’ rootstock is optimal for ‘Falstaff^PBR’ as it gives the plant an intermediate vigor between ‘BA29’ and ‘EMC’, and a good yield per hectare from the first planting years; the average fruit size is excellent. Full article

The efficient capital markets hypothesis (EMH) posits that security prices incorporate all available information in capital markets. Nevertheless, real stock markets often exhibit speculative behavior due to information asymmetry and the limited rationality of investors. This paper employs statistical analysis, a multiple regression approach, and robustness tests to investigate the impact of investor attention and accounting information comparability on stock returns. We collected monthly data from all Chinese A-share stocks listed on the main board of the Shanghai Stock Exchange for the period 2017–2021. Our findings reveal a significant positive correlation between current investor attention and current monthly stock returns and a significant negative correlation between lagged investor attention and current monthly stock returns. Moreover, accounting information comparability serves as a substantial moderator, amplifying the positive effect of current investor attention on current stock returns and mitigating the negative impact of lagged investor attention. We investigate the indicator of accounting information comparability from the perspective of investor attention. Significantly, we use accounting information comparability as a moderating variable for the first time to assess its influence on stock returns. Our results demonstrate that accounting information comparability significantly contributes to mitigating excessive share price declines and stimulating share price increases. This discovery also acts as an internal driver for listed companies to proactively improve accounting information comparability. Full article

Modelling and analysis of spatiotemporal characteristics of plant invasion can help in mapping and predicting the spread of invasive plants. The aim of our research was to investigate the spatiotemporal variability of five common invasive plant species (Ailanthus altissima, Asclepias syriaca, Elaeagnus angustifolia, Robinia pseudoacacia, and Solidago spp.) within different land cover (ecosystem)-type categories. The basis of the study was the National Geospatial Database of Invasive Plants (NGDIP) of Hungary, and the ecosystem types of the Ecosystem Map of Hungary (EMH). The GIS-based analysis of the detailed occurrence database of the invasive species (NGDIP) and the thematic land-cover (ecosystem)-type maps (EMH) examined allow us to answer the question of in which habitat types the occurrence and distribution of the given invasive plant has stagnated, decreased, or increased between 2006 and 2018. We developed a methodology with relevant data sources and demonstrated invasion variation, which can be used for future management planning and invasive biology research. Our results show that Asclepias syriaca and Robinia pseudoacacia are increasingly threatening grasslands and are also spreading more intensively in complex cultivated areas. The occurrences of Ailanthus altissima and Asclepias syriaca are declining in built-up areas due to the increasingly extreme environmental conditions of cities or modified urban planning. The spread of Solidago spp. is increasingly common in wetlands, threatening the biodiversity of floodplain (riparian) vegetation. Full article

Under the efficient market hypothesis (EMH), part of the literature ignores the characteristics of carbon markets. Based on the fractal market hypothesis (FMH), using the MF-DCCA method, this empirical study complements related research. We studied the non-linear multifractal correlation between carbon price fluctuations and China’s economic policy uncertainty (CNEPU) in Shenzhen, Beijing, Tianjin, and the national carbon market. The results show the following: (1) There is no linear correlation between price volatility and CNEPU in all carbon markets. (2) In the national carbon market, the correlation linkage between price fluctuation and CNEPU has not yet formed. (3) In the three regional carbon markets of Shenzhen, Beijing, and Tianjin, the long-range correlations exist with anti-persistence multifractal characteristics, which means that an increase in CNEPU will reduce price fluctuations. (4) After dividing the time scale into long-term and short-term, we found that it does not change the multifractal characteristics but it does change the fractal intensity. Finally, some suggestions are given to policymakers and carbon finance investors. Full article