Search Results (354,401)

Emotional intelligence (EQ) in healthcare leadership has been a subject of debate regarding its significance in enhancing job performance and patient-centred care. This systematic review investigates the impact of EQ on organisational performance metrics in healthcare leaders. Eleven studies meeting the inclusion criteria were identified through a comprehensive database search. The findings suggest that EQ positively influences job satisfaction, with emotionally intelligent leaders fostering a positive work environment and commitment among employees. Moreover, EQ correlates negatively with emotional exhaustion, indicating its potential in mitigating burnout rates among healthcare professionals. EQ fosters teamwork, organisational culture and enhances job performance, with higher EQ levels in leaders associated with increased team empowerment and proactivity. Despite the compelling evidence, limitations in the study methodologies and heterogeneity in the reported outcomes challenge the establishment of definitive conclusions. Nevertheless, the findings underscore the importance of EQ in healthcare leadership and its potential to improve organisational dynamics and employee wellbeing. This review highlights the need for further research on EQ’s impact on patient satisfaction and calls for the development of EQ training programmes tailored for healthcare leaders. Full article

Currently, teleoperated robots, with the operator’s input, can fully perceive unknown factors in a complex environment and have strong environmental interaction and perception abilities. However, physiological tremors in the human hand can seriously affect the accuracy of processes that require high-precision control. Therefore, this paper proposes an EEMD-IWOA-LSTM model, which can decompose the physiological tremor of the hand into several intrinsic modal components (IMF) by using the EEMD decomposition strategy and convert the complex nonlinear and non-stationary physiological tremor curve of the human hand into multiple simple sequences. An LSTM neural network is used to build a prediction model for each (IMF) component, and an IWOA is proposed to optimize the model, thereby improving the prediction accuracy of the physiological tremor and eliminating it. At the same time, the prediction results of this model are compared with those of different models, and the results of EEMD-IWOA-LSTM presented in this study show obvious superior performance. In the two examples, the MSE of the prediction model proposed are 0.1148 and 0.00623, respectively. The defibrillation model proposed in this study can effectively eliminate the physiological tremor of the human hand during teleoperation and improve the control accuracy of the robot during teleoperation. Full article

Currently, sports venues are endowed with the important functions of providing sports venues and facilities to the urban public, watching sports events, publicizing the mass sports culture, etc. An in-depth study of how to enhance the attractiveness of sports venue buildings and the competitiveness of the industry to stimulate the public’s potential for sports consumption is necessary. Based on the perspective of color psychology, this study constructs a three-level structural equation model based on the nested data obtained from the questionnaire survey to explore the relationship between managers’ innovative sports venue colors, athletes’ perceived emotional value, and consumers’ sports venue satisfaction. The results show that innovative sports venue colors have a significant positive effect on consumers’ satisfaction with sports venues, and the perceived emotional value has a positive mediating role in the effect of innovative sports venue colors on consumers’ satisfaction with sports venues. This study aims to provide a basis for sports venue managers or event organizers to improve athlete satisfaction, optimize consumer experience, stimulate residents’ motivation to attend games, and strengthen the profitability of the venues. Full article

The challenge of fracture segmentation remains a significant obstacle in imaging logging interpretation within the current oil and gas exploration and development field. However, existing image segmentation algorithms still encounter issues related to accuracy, speed, and robustness, as well as a tendency to misdetect or overlook small fractures when applied to logging image fracture segmentation tasks. To address these challenges comprehensively, this paper proposes an end-to-end fracture segmentation algorithm named SWSDS-Net. This algorithm is built upon the UNet architecture and incorporates the SimAM with slicing (SWS) attention mechanism along with the deformable strip convolution (DSCN) module. The SWS introduces a fully 3D attention mechanism that effectively learns the weights of each neuron in the feature map, enabling better capture of fracture features while ensuring fair attention and enhancement for both large and small objects. Additionally, the deformable properties of DSCN allow for adaptive sampling based on fracture shapes, effectively tackling challenges posed by varying fracture shapes and enhancing segmentation robustness. Experimental results demonstrate that SWSDS-Net achieves optimal performance across all evaluation metrics in this task, delivering superior visual results in fracture segmentation while successfully overcoming limitations present in existing algorithms such as complex shapes, noise interference, and low-quality images. Moreover, serving as a lightweight network solution enables SWSDS-Net’s deployment on mobile devices at remote sites—an advancement that lays a solid foundation for interpreting logging data and promotes deep learning technology application within traditional industrial scenarios. Full article

Faced with the hegemony of racial superiority, the oppression of gender dominance, and the demands of religious homogeneity, Mexican American Gloria E. Anzaldúa proposes a New Mestiza Consciousness that seeks to achieve a multifaceted transcendence of La Frontera (Borderlands). Using Krsiteva’s semiotics and mythology-based feminism as a theoretical guide, this paper will analyze the cultural, gender, ethnic, and religious manifestations of New Mestiza Consciousness and the logic behind this consciousness in terms of women’s writing in the Chicana women’s literary community and the re-shaping of the maternal mythological archetype in indigenous culture. Full article

We evaluated the long-term impacts of various forest management practices on the structure and biodiversity of Estonian hemiboreal forests, a unique ecological transition zone between temperate and boreal forests, found primarily in regions with cold winters and moderately warm summers, such as the northern parts of Europe, Asia, and North America. The study examined 150 plots across stands of different ages (65–177 years), including commercial forests and Natura 2000 habitat 9010* “Western Taiga”. These plots varied in stand origin—multi-aged (trees of varying ages) versus even-aged (uniform tree ages), management history—historical (practices before the 1990s) and recent (post-1990s practices), and conservation status—protected forests (e.g., Natura 2000 areas) and commercial forests focused on timber production. Data on forest structure, including canopy tree diameters, deadwood volumes, and species richness, were collected alongside detailed field surveys of vascular plants and bryophytes. Management histories were assessed using historical maps and records. Statistical analyses, including General Linear Mixed Models (GLMMs), Multi-Response Permutation Procedures (MRPP), and Indicator Species Analysis (ISA), were used to evaluate the effects of origin, management history, and conservation status on forest structure and species composition. Results indicated that multi-aged origin forests had significantly higher canopy tree diameters and deadwood volumes compared to even-aged origin stands, highlighting the benefits of varied-age management for structural diversity. Historically managed forests showed increased tree species richness, but lower deadwood volumes, suggesting a biodiversity–structure trade-off. Recent management, however, negatively impacted both deadwood volume and understory diversity, reflecting short-term forestry consequences. Protected areas exhibited higher deadwood volumes and bryophyte richness compared to commercial forests, indicating a small yet persistent effect of conservation strategies in sustaining forest complexity and biodiversity. Indicator species analysis identified specific vascular plants and bryophytes as markers of long-term management impacts. These findings highlight the ecological significance of integrating historical legacies and conservation priorities into modern management to support forest resilience and biodiversity. Full article

Reducing inequality within and between countries and enhancing social welfare are important components of the United Nations’ sustainable development goals. Based on the experience of developed countries or regions, the digital economy and fiscal policy are effective ways of promoting inclusive regional economic growth. Fully considering the completeness and availability of the data, we select the data of China’s less developed regions from 2001 to 2011 for empirical testing. This study empirically examined the effect of the digital economy on regional sustainable development and the underlying mechanism, taking an analysis of the regulatory effect of fiscal policy into account. The results show the following: (1) The digital economy and regional sustainable development exhibit an inverted “U” curve relationship. In the early stage of development, relying on its own economies of scale, the digital economy releases the “digital dividend”, positively affecting the sustainable development of the regional economy; in the later stage, the “digital divide” has a positive impact on the development of the regional economy. The inhibitory effect of the “digital divide” is greater than the enhancement effect of the “digital dividend”, negatively affecting the sustainable development of regional economies. (2) There is regional heterogeneity in the mechanism of the effect of the digital economy on regional sustainable development. The digital economy affects the level of regional sustainable development through the two paths of “comprehensive prosperity” and “holistic well-being”. For the samples in the eastern and western regions, the digital economy plays the role of promoting and then inhibiting, while for the samples in the central region, it plays the role of inhibiting and then promoting. (3) Fiscal policy negatively regulates the effect of the digital economy on regional sustainable development, but the regulatory effect is not significant. Full article

China’s agricultural development is challenged by delays in digital transformation. Understanding the alignment and trends of digital factors with rural–industrial integration is crucial for advancing agricultural digitalization. This study analyzes data from several Chinese provinces (2013–2021) using the entropy-weighted TOPSIS method to assess digital factors and rural–industrial integration levels. A coupling coordination model evaluates their interplay over time, and a center of gravity analysis along with the Dagum Gini system investigates their spatial distribution and divergence. The results show that from 2013 to 2021, digital factors and rural–industrial integration exhibited fluctuating trends. Provinces with higher levels were predominantly in the eastern region, which also had advanced digital transformation. There was a high level of interaction between these elements, especially in the eastern region. By 2021, the coupling index ranged from 0.9 to 1 across all provinces. Coordination generally remained low, with the eastern region showing medium-level high coordination, the central region low-level high coordination, and the western region high-level moderate coordination. Spatial analysis indicates a southwestward trend in the development of digital factors and rural–industrial integration. The epicenter is shifting towards the southern coastal regions, with regional disparities widening. Inter-regional disparities are diminishing annually, while intra-regional disparities are increasing, highlighting significant coupling and coordination effects. To enhance rural–industrial integration, digital strategies that meet the unique needs of rural industries are essential, fostering innovation and leveraging technological advancements effectively. Full article

With a view to improve measurements, this paper presents a statistical approach for characterizing the behaviour of roughness parameters based on measurements performed on ground surface topographies (grit #080/#120). A S neox^TM (Sensofar^®, Terrassa, Spain), equipped with three optical instrument modes (Focus Variation (FV), Coherence Scanning Interferometry (CSI), and Confocal Microscopy (CM)), is used according to a specific measurement plan, called Morphomeca Monitoring, including topography representativeness and several time-based measurements. Previously applied to the Sa parameter, the statistical approach based here solely on the Quality Index (QI) has now been extended to a multi-parameter approach. Firstly, the study focuses on detecting and explaining parameter disturbances in raw data by identifying and quantifying outliers of the parameter’s values, as a new first indicator. This allows us to draw parallels between these outliers and the surface topography, providing reflection tracks. Secondly, the statistical approach is applied to highlight disturbed parameters concerning the instrument mode used and the concerned grit level with two other indicators computed from QI, named homogeneity and number of modes. The applied method shows that a cleaning of the data containing the parameters values is necessary to remove outlier values, and a set of roughness parameters could be determined according to the assessment of the indicators. The final aim is to provide a set of parameters which best describe the measurement conditions based on monitoring data, statistical indexes, and surface topographies. It is shown that the parameters Sal, Sz and Sci are the most reliable roughness parameters, unlike Sdq and S5p, which appear as the most unstable parameters. More globally, the volume roughness parameters appear as the most stable, differing from the form parameters. This investigated point of view offers thus a complementary framework for improving measurement processes. In addition, this method aims to provide a global and more generalizable alternative than traditional methods of uncertainty calculation, based on a thorough analysis of multi-parameter and statistical indexes. Full article

Rice (Oryza) is a genus in the Gramineae family, which has grown widely all over the world and is a staple food source for people’s survival. The genetic information of rice has garnered significant attention in recent years, prompting numerous researchers to conduct extensive investigations in this field. But rice mitochondrial codon usage patterns have received little attention. The present study systematically analyzed the codon usage patterns and sources of variance in the mitochondrial genome sequences of five rice species by the CodonW and R software programs. Our results revealed that the GC content of codons in rice mitochondrial genome genes was determined to be 43.60%. Notably, the individual codon positions exhibited distinct GC contents: 48.00% for position 1, 42.65% for position 2, and 40.16% for position 3. These findings suggest the preference of the rice mitochondrial genome for codons ending in A or U. A weak codon bias was observed, with the effective number of codons (ENC) varying between 40.02 and 61.00, with an average value of 54.34. Subsequently, we identified 25 identical high-frequency codons in five rice mitochondrial genomes, with 11 codons ending in A and 12 codons ending in U. The regression lines in the neutrality plot exhibited slopes of less than 0.5 in five rice species, indicating a predominant role of natural selection, while mutation pressure remained relatively insignificant. In the PR2-plot analysis, most of the genes were located in the right half of the plot, indicating that the third base of the synonymous codon was preferred to end in G than C. Additionally, the ENC plot and ENC ratio analysis unveiled that codon preferences in the rice mitochondrial genome were predominantly influenced by natural selection rather than mutational pressure. The analysis of correspondence revealed distinct variations in the codon usage pattern across five rice mitochondrial genomes. Based on the RSCU values of species, a cluster tree was inconsistent with the mitochondrial genetic data, indicating that RSCU data could not be used as a basis for classification at the species level in the Oryza genus. These results will help decide the specific types of natural selection pressures influencing codon usage and improve the expression of exogenous genes in rice mitochondrial genomes by optimizing their codons. Full article

This paper deals with the tuning of the parameters of a fractional-order PI controller for the speed control of an electric servo drive in which the torque is set by a torque generator. The controller parameters are tuned using the multiple dominant pole method (MDPM), while the fractional order integrator is approximated by the Oustaloup method. The input parameters required for tuning the controller using MDPM are calculated using the optimization algorithm presented in this paper. This algorithm selects the optimal parameters from a set of points in three-dimensional space, based on the symmetry around a central point. The controller tuning is performed for the normalized control loop model. The obtained optimized normalized fractional order PI controller can then be applied to a real servo drive with specific parameters. The proposed tuning was also verified experimentally, comparing the obtained closed-loop responses with those of the integer-order PI controller. Both simulation and experimental results showed a significant reduction in the integral of the absolute error at the disturbance step compared to a control loop using an integer-order PI controller. This results in a faster output response to load torque steps and a smaller control error in a real servo drive. Full article

Background/Objectives: Cutaneous infections of fungal and bacterial origins are common. An accurate diagnosis—especially concerning pathogens that are difficult to isolate on culture—can be achieved using molecular methods (PCR) with a short turnaround time. Methods: We reviewed records of skin specimens (superficial scrapings) submitted by dermatologists across the United States with a clinically suspected dermatitis. As per physician’s order, specimens were tested for infections either fungal (N = 4262) or bacterial (N = 1707) in origin. All unique specimens (one per patient) were subjected to real-time PCR assays where cases suspected of a fungal etiology were tested for dermatophytes, Malassezia and Candida, and cases suspected of a bacterial etiology were tested for Streptococcus pyogenes, Staphylococcus aureus, and the mecA gene potentially conferring β-lactam resistance. Results: Fungal agents were detected in 32.8% (SD: 4.5) of the submitted specimens, with most attributed to dermatophytes (19.3% (SD: 4.9)), followed by Malassezia (8.7% (SD: 2.8)) and Candida (2.9% (SD: 1.0)). Dermatophyte detection was more common in the elderly (≥65 years) compared to young adults (18–44 years) (OR: 1.8 (95% CI: 1.5, 2.2)), whereas Malassezia was more commonly detected in younger age groups (12.1–13.6%) than the elderly (5.6%). Candida was more frequently observed in females while dermatophytes and Malassezia were more frequently observed in males. Approximately one quarter of the submitted skin specimens tested positive for S. aureus (23.6% (SD: 3.4)), of which 34.4% (SD: 9.8) exhibited concurrent detection of the mecA gene. An S. aureus detection was more frequently observed in males (OR: 1.5 (95% CI: 1.2, 1.9)) and in children (OR: 1.7 (95% CI: 1.2, 2.5)). Streptococcus pyogenes was rarely detected. Among specimens positive for dermatophytes, 12.0% (20/166) showed co-detection of S. aureus and mecA, which is in contrast to 6.8% (70/1023) detected in samples without a fungal co-detection and 6.2% (8/130) in samples positive for Malassezia. Conclusions: PCR testing, when available, can be valuable as a part of routine care for diagnosing patients with clinically suspected skin infections. Further studies are warranted to survey the prevalence of resistant S. aureus isolates in dermatology outpatients, in particular with regard to the association with dermatophyte infections. Full article

Aplastic anemia (AA) is characterized by bone marrow (BM) aplasia and pancytopenia. BM stromal microenvironment is closely intertwined with hematopoietic cells by reciprocal regulation. It is still unclear how hematopoietic deficiency affects the bone marrow stroma of the AA patients. Multipotent mesenchymal stromal cells (MMSCs) are the progenitors of stromal cells. In vitro, proliferation rate of MMSCs of AA patients is decreased compared to those of healthy donors. This may be explained by the influence of pathological environmental condition in the patients’ BM. The aim of the study was to compare the effect of AA patients’ sera on healthy donor MMSCs to healthy donors’ sera and to elucidate the nature of their difference. Proliferation test showed 3-fold decrease in number of MMSCs after incubation in medium supplemented with AA patients’ sera compared to donors’ serum samples. The degree of this effect correlated with the severity of thrombocytopenia in patients. The decrease in cell number was not associated with cell death, as the number of apoptotic cells defined by flow cytometry did not differ between the groups. ELISA revealed a decreased level of PDGF-BB in the patients’ sera compared to donors’ serum samples (69 ± 5 pg/mL vs 112 ± 21 pg/mL, respectively). The addition of recombinant PDGF-BB or healthy donor’s platelet lysate to the culture medium supplemented with AA patients’ serum restored its ability to support MMSCs growth. Thus, PDGF-BB deficiency is one of the environmental factors causing MMSCs damage in AA patients. Full article

The numbness to human loss becomes ordinary. Indifference to human affairs seems normal after experiencing the global lockdown. Bringing up empathy becomes the most challenging task in architectural design studios after the COVID-19 pandemic. Examining otherness solidified after a global pandemic would be a way to revive empathy and to engage more in architectural design studios. The physiological disparity between the modern and the vernacular environments narrows down with the revival of Najdi architecture, the Salmani architecture style, and the Diriyah Gate Project in Riyadh, KSA. The disparity is caused by intangible factors such as speed, density, and tension but the revival focuses heavily on the tangible, formal expression. The architectural elements in the vernacular Najdi architecture have different meanings and roles beyond being a decorative motif. The feeble values of the vernacular undermined by touristic images are challenged by a series of radical design projects not to be generalized again by picturesque replicas of the past. Seeing the lost, the ecological sensibility of a community or collective that embraced the harshest land with full respect, might not be visual but is instead radically experiential, like a serendipitous breeze in Riyadh. This paper introduces a series of studio works that challenge how to bring back the living structure, in the harshest environment, to daily life through experimental and speculative design processes. It proposes how a community is called on to guard the environmental landscape, again defying the visual interpretation of Najdi architecture in a political landscape dominated by high fence walls. Full article

Precise modeling and state of charge (SoC) estimation of a lithium-ion battery (LIB) are crucial for the safety and longevity of battery systems in electric vehicles. Traditional methods often fail to adapt to the dynamic, nonlinear, and time-varying behavior of LIBs under different operating conditions. In this paper, an advanced joint estimation approach of the model parameters and SoC is proposed utilizing an enhanced Sigma Point Kalman Filter (SPKF). Based on the second-order equivalent circuit model (2RC-ECM), the proposed approach was compared to the two most widely used methods for simultaneously estimating the model parameters and SoC, including a hybrid recursive least square (RLS)-extended Kalman filter (EKF) method, and simple joint SPKF. The proposed adaptive joint SPKF (ASPKF) method addresses the limitations of both the RLS+EKF and simple joint SPKF, especially under dynamic operating conditions. By dynamically adjusting to changes in the battery’s characteristics, the method significantly enhances model accuracy and performance. The results demonstrate the robustness, computational efficiency, and reliability of the proposed ASPKF approach compared to traditional methods, making it an ideal solution for battery management systems (BMS) in modern EVs. Full article