Search Results (43)

This study investigated the effects of caffeine supplementation, carbohydrate mouth rinsing, and combined caffeine supplementation with carbohydrate mouth rinsing on the pulling performance and ratings of perceived exertion in indoor tug-of-war athletes. Eighteen tug-of-war athletes were recruited as participants. They underwent four supplementation protocols in a double-blind, single-factor, repeated-measures design: caffeine supplementation (CAF), carbohydrate solution mouth rinsing (CHO), combined caffeine supplementation with carbohydrate mouth rinsing (CAF-CHO), and a placebo (PLA). Each participant performed a maximal pulling test at 80% of their maximum pulling force, and the duration was recorded. Ratings of perceived exertion were also assessed. Data were analyzed using SPSS version 25.0 for Windows, and effect sizes (ES) were calculated. The main findings were as follows: (1) The CAF-CHO group showed a significantly longer pulling duration than the PLA and CHO groups (165.0 ± 69.2 s vs. 137.4 ± 48.9 s vs. 135.6 ± 66.6 s). (2) The CAF group also demonstrated a significantly longer pulling duration than the CHO group (162.0 ± 14.1 s vs. 135.6 ± 66.6 s). (3) Both the CAF-CHO and CAF groups exhibited large effect sizes (ω² > 0.14) compared to the PLA and CHO groups. Both caffeine supplementation combined with carbohydrate mouth rinsing and caffeine supplementation alone can significantly enhance the duration of 80% maximal pulling performance in indoor tug-of-war athletes, with the primary effect attributed to caffeine. These results provide practical strategies for coaches and athletes to suppress fatigue and improve pulling performance during competitions or training sessions for indoor tug-of-war. Full article

This study examines the predictability of the last 30 min of intraday stock price movements within the US financial market. The analysis encompasses several potential explanatory variables, including returns from each 30 min intraday trading session, overnight returns, the federal reserve fund rate decision days and the subsequent three days, the US dollar index, month effects, weekday effects, and market volatilities. Market-adaptive trading strategies are developed and backtested on the basis of the study’s insights. Unlike the commonly employed multiple linear regression methods with Gaussian errors, this research utilizes a Bayesian linear regression model with Student-t error terms to more accurately capture the heavy tails characteristic of financial returns. A comparative analysis of these two approaches is conducted and the limitations inherent in the traditionally used method are discussed. Our main findings are based on data from 2007 to 2018. We observed that well-studied factors such as overnight effects and intraday momentum have diminished over time. Some other new factors were significant, such as lunchtime returns during boring days and the tug-of-war effect over the days after a federal fund rate change decision. Ultimately, we incorporate findings derived from data spanning 2022 to 2024 to provide a contemporary perspective on the examined components, followed by a discussion of the study’s limitations. Full article

Miniature steerable instruments have the potential to reduce the invasiveness of therapeutic interventions and enable new treatment options. Traditional ways of driving such instruments rely on extrinsic systems due to the challenge of miniaturizing and embedding intrinsic actuators that are powerful enough near the instrument tip or within the instrument shaft. This work introduces a method to amplify the output force of fluidic actuators by connecting their outputs in parallel but distributing them serially in currently underutilized space along the device’s long axis. It is shown that this new approach makes it possible to realize a significant force amplification within the same instrument diameter, producing a $380\%$ higher static force and a further driving motion of the steerable bending segment 55.6° than an actuator representing the current state of the art, all while occupying a similar footprint. Full article

Background: Tug-of-War (TOW) games involve repetitive hand movements and vigorous force, raising the risk of peripheral neuropathy in the upper extremities. The prevalence of carpal tunnel syndrome (CTS) in TOW athletes remains unclear. We hypothesize that elite female TOW athletes have a higher prevalence of CTS than the general population. Methods: Twenty-nine female TOW athletes were recruited from a national team and participated in the study. CTS was clinically diagnosed by history taking and physical examination. Nerve conduction studies (NCS) were additionally performed to confirm CTS. Results: Twelve athletes were clinically diagnosed with CTS; however, only nine were confirmed by NCS. Ten athletes were diagnosed with subclinical CTS by NCS, while seven were classified as truly-non-CTS by both clinical assessment and NCS. The prevalence of CTS and subclinical CTS among the athletes was found to be 33.3% and 37.0%, respectively, significantly higher than 2.7% in the general population by electrodiagnosis. The body weight (p = 0.025) of the athletes with CTS and subclinical CTS was significantly different from those of the athletes without CTS. Conclusions: Our observations revealed a higher prevalence of CTS among elite female TOW athletes, with body weight being a risk factor. The forceful grasping and pulling of the rope may contribute to the development of CTS. Full article

The creation of frameworks for lowering natural hazards is a sustainable development goal specified by the United Nations. This study aims to predict drought occurrence in Tamil Nadu, India, using 26 years of data, with only 3 drought years. Since the drought-occurrence years are minimal, it is an imbalanced dataset, which gives a suboptimal classification performance. The accuracy metric has a tendency to produce misleadingly high results by focusing on the accuracy of forecasting the majority class while ignoring the minority class; hence, this work considers the metrics’ precision and recall. A novel strategy uses attribute (or instance) weighting, which allots weights to attributes (or instances) based on their importance, to improve precision and recall. These weights are found using a bio-inspired optimization algorithm, by designing its fitness function to improve precision and recall of the minority (drought) class. Since increasing precision and recall is a tug-of-war, multi-objective optimization helps to identify optimal attribute (or instance) weight balancing precision and recall while maximizing both. The newly introduced Synergistic Optimization Algorithm (SOA) is utilized for multi-objective optimization in order to ascertain weights for attributes (or instances). In SOA, to solve multi-objective optimization, each objective’s population was generated using three distinct algorithms, namely, the Genetic, Firefly, and Particle Swarm Optimization (PSO) algorithms. The experimental results demonstrated that the prediction performance for the minority drought class was superior when utilizing instance (or attribute) weighting compared to the approach not employing attribute/instance weighting. The Gradient Boosting classifier with an attribute-weighted dataset achieved precision and recall values of 0.92 and 0.79, whereas, with instance weighting, the values were 0.9 and 0.76 for the drought class. The attribute weighting shows that in addition to the default drought indices SPI and SPEI, pollution factors and mean sea level rise are valuable indicators in drought prediction. From instance weighting, it is inferred that the instances of the months of March, April, July, and August contribute most to drought prediction. Full article

The relationship between modernization and religion is contested, with the literature differing in how and in what ways religion helps or hinders countries’ social, economic, and political development. This paper draws upon the history of Christianity in South Korea to critically explore the links between religion and modernization. It makes two arguments. First, discussions of the link between religion and modernization frequently employ static definitions of religion, but Christianity is characterized by oscillations between worldly (institutionalizing) and unworldly (countercultural) impulses that theoretically make very different contributions to social, economic, and political development. Second, in the case of South Korea, it is shown that both impulses have made vital contributions to the country’s modernization at different times. This suggests that the dynamic tug-of-war between the institutional and countercultural facets of Korean Christianity, although problematic for individual believers and religious leaders, helped it become an important contributor to the country’s success story. However, this paper concludes on a cautionary note by warning that extreme instances of these impulses have caused cleavages between Christianity and the Korean state and society and could undermine its future contributions. This suggests that diversity and toleration—a hallmark of Korean Christianity—will continue to be the best pathway forward. Full article

The ABO blood groups, Lewis antigens, and secretor systems are important components of transfusion medicine. These interconnected systems have been also shown to be associated with differing susceptibility to bacterial and viral infections, likely as the result of selection over the course of evolution and the constant tug of war between humans and infectious microbes. This comprehensive narrative review aimed to explore the literature and to present the current state of knowledge on reported associations of the ABO, Lewis, and secretor blood groups with SARS-CoV-2 infection and COVID-19 severity. Our main finding was that the A blood group may be associated with increased susceptibility to SARS-CoV-2 infection, and possibly also with increased disease severity and overall mortality. The proposed pathophysiological pathways explaining this potential association include antibody-mediated mechanisms and increased thrombotic risk amongst blood group A individuals, in addition to altered inflammatory cytokine expression profiles. Preliminary evidence does not support the association between ABO blood groups and COVID-19 vaccine response, or the risk of developing long COVID. Even though the emergency state of the pandemic is over, further research is needed especially in this area since tens of millions of people worldwide suffer from lingering COVID-19 symptoms. Full article

Human T cell leukemia virus type 1 (HTLV-1) is a retrovirus associated with a lymphoproliferative disease known as adult T cell leukemia/lymphoma (ATLL). HTLV-1 infection efficiently transforms human T cells in vivo and in vitro. The virus does not transduce a proto-oncogene, nor does it integrate into tumor-promoting genomic sites. Instead, HTLV-1 uses a random mutagenesis model, resulting in cellular transformation. Expression of the viral protein Tax is critical for the immortalization of infected cells by targeting specific cellular signaling pathways. However, Tax is highly immunogenic and represents the main target for the elimination of virally infected cells by host cytotoxic T cells (CTLs). In addition, Tax expression in naïve cells induces pro-apoptotic signals and has been associated with the induction of non-replicative cellular senescence. This review will explore these conundrums and discuss the mechanisms used by the Tax viral oncoprotein to influence life-and-death cellular decisions and affect HTLV-1 pathogenesis. Full article

Viruses rely on host cells to replicate their genomes and assemble new viral particles. Thus, they have evolved intricate mechanisms to exploit host factors. Host cells, in turn, have developed strategies to inhibit viruses, resulting in a nuanced interplay of co-evolution between virus and host. This dynamic often involves competition for resources crucial for both host cell survival and virus replication. Iron and iron-containing cofactors, including iron–sulfur clusters, are known to be a heavily fought for resource during bacterial infections, where control over iron can tug the war in favor of the pathogen or the host. It is logical to assume that viruses also engage in this competition. Surprisingly, our knowledge about how viruses utilize iron (Fe) and iron–sulfur (FeS) clusters remains limited. The handful of reviews on this topic primarily emphasize the significance of iron in supporting the host immune response against viral infections. The aim of this review, however, is to organize our current understanding of how viral proteins utilize FeS clusters, to give perspectives on what questions to ask next and to propose important avenues for future investigations. Full article

Neurofeedback (NF) shows promise in enhancing memory, but its application to the medial temporal lobe (MTL) still needs to be studied. Therefore, we aimed to develop an NF system for the memory function of the MTL and examine neural activity changes and memory task score changes through NF training. We created a memory NF system using intracranial electrodes to acquire and visualise the neural activity of the MTL during memory encoding. Twenty trials of a tug-of-war game per session were employed for NF and designed to control neural activity bidirectionally (Up/Down condition). NF training was conducted with three patients with drug-resistant epilepsy, and we observed an increasing difference in NF signal between conditions (Up–Down) as NF training progressed. Similarities and negative correlation tendencies between the transition of neural activity and the transition of memory function were also observed. Our findings demonstrate NF’s potential to modulate MTL activity and memory encoding. Future research needs further improvements to the NF system to validate its effects on memory functions. Nonetheless, this study represents a crucial step in understanding NF’s application to memory and provides valuable insights into developing more efficient memory enhancement strategies. Full article

Long-Range (LoRa) devices have been deployed in many Internet of Things (IoT) applications due to their ability to communicate over long distances with low power consumption. The scalability and communication performance of the LoRa systems are highly dependent on the spreading factor (SF) and channel allocations. In particular, it is important to set the SF appropriately according to the distance between the LoRa device and the gateway since the signal reception sensitivity and bit rate depend on the used SF, which are in a trade-off relationship. In addition, considering the surge in the number of LoRa devices recently, the scalability of LoRa systems is also greatly affected by the channels that the LoRa devices use for communications. It was demonstrated that the lightweight decentralized learning-based joint channel and SF-selection methods can make appropriate decisions with low computational complexity and power consumption in our previous study. However, the effect of the location situation of the LoRa devices on the communication performance in a practical larger-scale LoRa system has not been studied. Hence, to clarify the effect of the location situation of the LoRa devices on the communication performance in LoRa systems, in this paper, we implemented and evaluated the learning-based joint channel and SF-selection methods in a practical LoRa system. In the learning-based methods, the channel and SF are decided only based on the ACKnowledge information. The learning methods evaluated in this paper were the Tug of War dynamics, Upper Confidence Bound 1, and $ϵ$-greedy algorithms. Moreover, to consider the relevance of the channel and SF, we propose a combinational multi-armed bandit-based joint channel and SF-selection method. Compared with the independent methods, the combinations of the channel and SF are set as arms. Conversely, the SF and channel are set as independent arms in the independent methods that are evaluated in our previous work. From the experimental results, we can see the following points. First, the combinatorial methods can achieve a higher frame success rate and fairness than the independent methods. In addition, the FSR can be improved by joint channel and SF selection compared to SF selection only. Moreover, the channel and SF selection dependents on the location situation to a great extent. Full article

The intrinsic relation between water and energy has made the water–energy nexus a burgeoning issue in the discussion of sustainable development. Recently, research has begun to pay attention to stakeholders in the nexus. They, however, identified stakeholders as a given without employing methodically scientific processes with rigorous parameters. Filling in the gap, this study presents a heuristic approach to identifying critical stakeholders of multi-actor systems in the water–energy nexus. It involves three sources of influence (social roles, specific concerns, and key problems) along with four other boundary issues (motivation, control, knowledge, legitimacy), forming a matrix of the boundary categories of Critical Systems Heuristics (CSH). This study applied the heuristic analysis to the project of floating photovoltaics installed in a pond in Hyogo, Japan, as the case study. It is a unique case of the water–energy nexus since the location of the floatovoltaic installation is a privately owned pond that is also part of the public landscape and an irrigation source for the surrounding agricultural areas. The results identified two macrogroups of stakeholders (residents and project developers) driven by general interests in the project. They were derivable as overlapping micro-actors interested in more specific issues related to different facets of the project. Overall, conflicting interests in the multi-actor systems indicated deadlocked interactions due to a multidirectional tug-of-war between the microgroups of actors. Conceptually, this study significantly contributes to the literature on the water–energy nexus and stakeholder management. Practically, the approach used offers scientific processes to understand the multi-actor systems and conflicting interests involved in/affected by the nexus, paving the way for more comprehensive resolution processes of water–energy conflicts. Full article

Drought directly affects environmental sustainability. Predicting the drought at the earliest opportunity will help to execute drought mitigation plans. Several drought indices are used to predict the severity of drought across different geographical regions. The two main drought indices used in India for meteorological drought are the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI). This work is a study to find the ability of above mentioned indices to predict meteorological drought for the state of Tamil Nadu using 62 years of data. The prediction results are evaluated using the performance metrics of precision, recall, f1 score, Matthews correlation coefficient, and accuracy. The dataset is severely imbalanced due to the low number of drought incidence years. Hence there exists a tug of war between precision and recall, so for improving it without affecting one another, a multi-objective optimization process is applied. The prediction performance is improved by using the filter-global-supervised feature weighting and wrapper-global-supervised feature weighting techniques. In the filter-based feature weighting approach, the information gain measure and Pearson correlation coefficient are used as feature weights. For the wrapper-based feature weighting approach, two-stage particle swarm optimization (PSO) is designed to calculate the weights of the features, and the random forest is used as the classifier. This two-stage PSO constructs the best population set for individual objectives and then searches around it to find the best particle so that the multiple contradicting objectives will converge into the best solution easier. When compared to classification without feature weighting, two-stage PSO feature weighting achieves a 45% improvement in precision. However, only a moderate improvement in recall is obtained. According to the findings, SPI3 and SPEI12 should be given more weightage in metrological drought prediction. Full article

It has been 70 years since the concept of varied centromere strengths was introduced based on the behavior of dicentric chromosomes. One of the key conclusions from those early experiments was that some centromeres could pull with sufficient force to break a dicentric chromosome bridge, while others could not. In the ensuing decades there have been numerous studies to characterize strengths of the various components involved, such as the spindle, the kinetochore, and the chromosome itself. We review these various measurements to determine if the conclusions about centromere strength are supported by current evidence, with special attention to characterization of Drosophila melanogaster kinetochores upon which the original conclusions were based. Full article

The sustenance of marginal and small farm households is a pertinent question given that their number is on the rise in South-Asia. The study aims to assess their present socio-economic profile and the challenges faced in order to draw a roadmap of development for these underprivileged households. The study pertains to Indian Punjab and data from the Situation Assessment Survey of the 70th Round of NSSO are used. The concepts of economic surplus, occupational diversity, farm productivity and vertical and horizontal inequalities are used to achieve the objectives. This study reveals that marginal farm households faced food insecurity as they failed to meet consumption expenditure from the income earned. In fact, small farm households are left with an annual economic surplus of Rs 8890 per capita only, after meeting consumption needs. Income is unevenly distributed among farm households with a Gini coefficient of 0.48. The majority of the marginal and small farm households fall in lower-income quintiles and are occupationally more diversified than their larger counterparts. Horizontal inequalities are lower between the farm-size categories (0.14) than within farm-size categories (0.27). The Gini coefficient within each farm-size category is the highest among marginal farm households (0.50), followed by small farm households (0.45), highlighting their economic stress and tug-of-war survival. Further, the farm households belonging to socially lower castes falls only in the marginal farm-size category and represent the lowest income. Development must be sustainable and inclusive, hence, policies to develop marginal farmers’ centric farming systems and high value crops such as potato, cotton, sugarcane and oilseeds, providing high yielding livestock breeds, value addition through farmer-producer organizations, non-farm employment through MGNREGA, provision of institutional credit at subsidised rate of interest and quality health and education facilities in the public sector are recommended to uplift the affected households. Full article