Perception and motor interaction with physical surroundings can be analyzed by the changes in probability laws governing two possible outcomes of neuronal activity, namely the presence or absence of spikes (binary states). Perception and motor interaction with physical environment are accounted partly by the reduction in entropy within the probability distributions of binary states of neurons in distributed neural circuits, given the knowledge about the characteristics of stimuli in physical surroundings. This reduction in the total entropy of multiple pairs of circuits in networks, by an amount equal to the increase of mutual information among them, occurs as sensory information is processed successively from lower to higher cortical areas or between different areas at the same hierarchical level but belonging to different networks. The increase in mutual information is partly accounted by temporal coupling as well as synaptic connections as proposed by Bahmer and Gupta [1]. We propose that robust increases in mutual information, measuring the association between the characteristics of sensory inputs and neural circuits connectivity patterns, are partly responsible for perception and successful motor interactions with physical surroundings. It is also argued that perception from a sensory input is the result of networking of many circuits to a common circuit that primarily processes the given sensory input.

This study introduces a cascade nonlinear proportional integral retarded (CNPIR) controller for the first time in the literature, aiming to achieve real-time precise control of a double-tank liquid level system. It begins by outlining the characteristics of de-lay-based systems and detailing the dynamic behavior of the liquid-level system. The study evaluates the system's performance by developing and analyzing the mathe-matical models of both the feedforward proportional-integral (FF-PI) controller and the CNPIR controller. Two different control techniques were employed, with real-time tests conducted to assess the system's axis movement performance. The FF-PI controller was used as the initial control technique, while the CNPIR controller was introduced to enhance system performance during trajectory tracking. Experimental results demon-strated that the CNPIR method significantly improved trajectory tracking response, reduced overshoot, and achieved better steady-state error under external disturbances compared to the FF-PI controller. Thus, the experimental study, highlights the effec-tiveness of the proposed control design and its superiority over some existing classical methods.

We present a novel method for interpolating univariate time series data. The proposed method combines multi-point fractional Brownian bridges, a genetic algorithm, and Takens’ theorem for reconstructing a phase space from univariate time series data. The basic idea is to first generate a population of different stochastically interpolated time series data, and secondly, to use a genetic algorithm to find the pieces in the population which generate the smoothest reconstructed phase space trajectory. A smooth trajectory curve is hereby found to have a low variance of second derivatives along the curve. For simplicity, we refer to the developed method as PhaSpaSto-interpolation, which is an abbreviation for phase-space-trajectory-smoothing stochastic interpolation. The proposed approach is tested and validated with a univariate time series of the Lorenz system, five non-model data sets and tested against a cubic spline interpolation and a linear linear interpolation. We find that the criterion for smoothness guarantees low errors on known model and non-model data. Finally, we interpolate the discussed non-model data sets, and show the corresponding improved phase space portraits. The proposed method is useful for interpolating low-sampled time series data sets for, e.g., machine learning, regression analysis, or time series prediction approaches.

The P versus NP problem is a fundamental question in computer science. It asks whether problems whose solutions can be quickly verified can also be quickly solved. Here, "quickly" refers to computational time that grows proportionally to the size of the input (polynomial time). While the problem's roots trace back to a 1955 letter from John Nash, its formalization is attributed to Stephen Cook and Leonid Levin. Despite extensive research, a definitive answer remains elusive. Closely tied to this is the concept of NP-completeness. If a single NP-complete problem could be solved efficiently, it would imply that all problems in NP can be solved efficiently, proving that P equals NP. This work posits that MONOTONE ONE-IN-THREE 3SAT, a notoriously difficult NP-complete problem, can be solved efficiently, thereby establishing the equivalence of P and NP.

We propose a novel tensor-based formalism for inferring causal structures from time series. An information theoretical analysis of transfer entropy (TE), shows that TE results from transmission of information over a set of communication channels. Tensors are the mathematical equivalents of these multi-channel causal channels. A multi-channel causal channel is a generalization of a discrete memoryless channel (DMC). We consider a DMC as a single-channel causal channel. Investigation of a system comprising three variables shows that in our formalism, bivariate analysis suffices to differentiate between direct and indirect relations. For this to be true, we have to combine the output of multi-channel causal channels with the output of single-channel causal channels. We can understand this result when we consider the role of noise. Subsequent transmission of information over noisy channels can never result in less noisy transmission overall. This implies that a Data Processing Inequality (DPI) exists for transfer entropy.

In a recent paper, we have shown how gravity and information can be related. The relation is based on the thermodynamic extension of the gravitational system under consideration using the holographic principle. Using this idea, we were able to derive the Gullstrand-Painlevé (GP) metric. In this short paper, we re-derive the GP metric using information. However, we now extend the spacetime to 5D with the fifth dimension being time, that is, the (3+1)D spacetime is now promoted to (3+1+1)D spacetime. We also comment on the possible Braneworld interpretation of this model.

This paper gives solutions to puzzles of double Wheeler’s delayed choice experiments, a photon’s passing two paths simultaneously and wave collapse velocity measure, and shows new quantum control, new quantum oscillation and new controlling photon oscillator (that can be arranged in quantum computer and quantum network as their classical correspondences) in experiments. Furthermore, this paper obtains the measured attractive state and the new useful key technology of altering state’s evolving paths for quantum systems. We discover the reason and the technological way for the present changes the past, further show their feasible experiments of new quantum control, new quantum oscillation and new quantum oscillator. Finally, this paper achieves the collapse response time t of wave, further concretely deduces the measured collapse velocity of quantum system. In the past, the collapse velocity cannot be objectively deduced and experimentally measured.

Sharding shows great potential for extending the blockchain. The current challenge facing sharded blockchain technology lies in addressing the extended transaction confirmation times caused by isolated states between shards and unbalanced transaction allocation strategies. These factors contribute to an increase in cross-shard transactions and disproportionate shard workload, ultimately resulting in indefinite confirmation delays for cross-shard transactions. A critical priority for sharded blockchain systems is to conduct a comprehensive qualitative analysis to better understand and mitigate the prolonged transaction confirmation times. We introduce a Product-Form Queue Network (PFQN) model to address the transaction confirmation time problem in sharded blockchains and incorporate a new confirmation queue to more accurately simulate the actual transaction confirmation process in the blockchain. In addition, we provide a detailed quantitative analysis of the relationship between network load, consensus efficiency, and security in sharded blockchains, laying a theoretical foundation for achieving robustness and efficiency in sharded blockchains. This research not only contributes to addressing the scalability issues in sharded blockchains but also offers a new perspective for future research directions.

The open data market is growing, driven by laws requiring governments to make data publicly available. However, the true value of this market lies in the products and services derived from open data. In Slovenia, the open data market has been growing since 2015, especially in the field of mobility. Platforms such as Avtolog.si facilitate the retrieval of vehicle data via vehicle identification numbers, while tocen.si, ojpp.si, and brezavta.si aggregate mobility data, focusing on sustainable and micromobile public transportation services. These platforms use open government data and private sector open data, and are freely accessible. This study examines the use of open data in the Slovenian mobility applications and similar solutions developed in other countries. By mapping these applications, we gain valuable insights into potential advances in the field, and provide a useful resource for future developers worldwide. By focusing on the socio-economic impact of these innovations, the study identifies methods for evaluating such applications. This approach highlights how transforming open data into user-friendly products and services can deepen our understanding of their broader societal and economic benefits. While open data is valuable in its own right, its full transformative potential is realized through innovative products that support sustainable lifestyles and promote environmentally conscious behavior.

In this paper, we study a one-dimensional Bresse-Cattaneo system with infinite memories and time-dependent delay term (the coefficient of which is not necessarily positive) in the internal feedbacks. First, it is proved that the system is well-posed by means of the Hille-Yosida theorem under suitable assumptions on the relaxation functions. Then, without any restriction on the speeds of wave propagations, we establish the exponential or general decay result by introducing suitable energy and Lyapunov functionals.

Speech emotion recognition (SER) is a technology that can be applied in distance education to analyze speech patterns and evaluate speakers’ emotional states in real-time. It provides valuable insights and can be used to enhance the learning experience by enabling the assessment of instructors’ emotional stability, a factor that significantly impacts information delivery effectiveness. Students demonstrate different engagement levels during learning activities, and assessing this engagement is an important aspect of controlling the learning process and improving e-learning systems. An important aspect that may influence student engagement is the emotional states of their instructors. Accordingly, this research uses deep learning techniques to create an automated system for recognizing instructors’ emotions in their speech when delivering distance learning. This methodology entails integrating Transformer, convolutional neural network, and long short-term memory architectures into an ensemble to enhance SER. Feature extraction from audio data used Mel-frequency cepstral coefficients, chroma, Mel spectrogram, zero crossing rate, spectral contrast, centroid, bandwidth, roll-off, and root-mean square, with subsequent optimization processes adding noise to, conducting time stretching, and shifting the audio data. Notably, several Transformer blocks were incorporated, and a multi-head self-attention mechanism was employed to identify the relationships between the input sequence segments. The pre-processing and data augmentation methodologies significantly enhanced the precision of the results in that the model achieved accuracy rates of 96.3%, 99.86%, 96.5%, and 85.3% on the Ryerson Audio-Visual Database of Emotional Speech and Song, Berlin Database of Emotional Speech, Surrey Audio-Visual Expressed Emotion, and Interactive Emotional Dyadic Motion Capture datasets. Furthermore, it achieved 83% accuracy on another dataset created for this research—the Saudi Higher Education Instructor Emotions dataset. The results demonstrate this model’s considerable accuracy in detecting emotions in speech data across different languages and datasets.

Health care operations in many hospitals are experiencing increasing demand which is however hindered by the limited resources available. The imbalance between the demand and service provision capacity within the hospitals have resulted in long waiting times for service delivery due to overcrowding, high costs of treatment as well as low levels of patient’s satisfaction. The above problems are attributed to the development of hospital management information system. This dissertation is focused on investigating some of the causes of the increased cost and time consumption as well as low levels of patient’s satisfaction in the application of hospital management information system. The study used comparative design to make a comparison of the respondents from two different hospital facilities where 400 health workers were drawn for research. The questionnaire was used as a survey tool for the study that involved both qualitative and quantitative analysis. The results of the study indicate various playing factors that arise due to the development of the hospital management information system. These factors include the large functionality of the system, the need for training of the end users, the increasing ageing population, and delays. The identified factors play a significant role in the way the information system impacts the time taken, the cost involved, and patient satisfaction. Keywords: health, hospital, doctors, technology, information system, time, and cost.

In this paper, the time-resolved model of photoacoustic signal for samples with a complex inner structure is derived including local non-equilibrium of structural elements with multiple degrees of freedom, i.e. structural entropy of the system. The local non-equilibrium is taken into account through the fractional operator. By analyzing the model for two types of time-dependent excitation, a very short pulse and a very long pulse, it is shown that the rates of non-equilibrium relaxations in complex samples can be measured by applying the derived model and time-domain measurements. Limitations of the model and further directions of its development are discussed.

Today massive amounts of sequenced metagenomic and -transcriptomic data from different ecological niches and environmental locations are available. Scientific progress depends critically on methods that allow extracting useful information from the various types of sequence data. Here, we will first discuss types of information contained in the various flavours of biological sequence data, and how this information can be interpreted to increase our scientific knowledge and understanding. We argue that a mechanistic understanding is required to consistently interpret experimental observations, and that this understanding is greatly facilitated by the generation and analysis of dynamic mathematical models. We conclude that, in order to construct mathematical models and to test mechanistic hypotheses, time-series data is of critical importance. We review diverse techniques to analyse time-series data and discuss various approaches by which time-series of biological sequence data was successfully used to derive and test mechanistic hypotheses. Analysing the bottlenecks of current strategies in the extraction of knowledge and understanding from data, we conclude that combined experimental and theoretical efforts should be implemented as early as possible during the planning phase of individual experiments and scientific research projects.

There is a long standing ‘two times problem’ in that a satisfactory reconciliation between the time of physics and that of psychology has not been realized. A partial solution to the past/present/future phenomenon has been successfully given by the Hartle information gathering and processing system (IGUS) view. That model IGUS robot is enhanced here for the entire ‘two times problem’ to deal with not only the temporal experiences of the flow of time but also those of manifest time. A dualistic robot is proposed which has a veridical system of temporal experiences that are compatible with various spacetime cosmologies. It also has an illusory system of corresponding temporal experiences. This dualistic IGUS robot was made possible by discovering temporal experience within the brain that correspond to those of physics. The dualistic theory suggests that the veridical system, as a result of evolution, begets the illusory system to enhance behavioral adaptation. Thus, there is just one fundamental physical time which the brain does, indeed, possess and then enhances with illusory counterparts. Therefore, there should no longer be a need to reify illusory temporal experiences as modern spacetime cosmologies tend to do. Physical time already resides within human time.

Protection suit is vital for fireman’ safety. Traditional protection suit just physically protects fireman from empyrosis, but can not locate the body injury position from the impact debris. Herein, we present a wearable impact debris positioning system for fireman protection suit alarming based on accelerometer array. The wearable piezoelectric accelerometers with distribute regularly on the suit to detect the vibration on different body parts, which is conducive to positioning injured body parts. In addition, the injured parts can be displayed on the dummy body model on the upper computer with a higher localization accuracy of 4 cm. The positioning alarm system has a rapid response time of 0.11ms attributing to smart signal processing method. This work provides a reliable and smart method for locating and assessing the body injury position from the impact debris, which is significant for fire disaster commander to rescue injured fireman in time.

Addressing non-unions involves stabilizing the affected area through osteosynthesis and improving bone biology using bone grafts. However, there is no consensus on the optimal treatment method. This study aims to compare outcomes of non-union revision using conventional treatment methods (metal hardware ± graft) versus osteosynthesis with the human, allogeneic cortical bone screw (Shark Screw®). Thirty-four patients underwent conventional treatment, while 28 cases received Shark Screws®. Patient demographics, bone healing, time to bone healing, and complications were assessed. Results revealed a healing rate of 96.4% for the Shark Screw® group, compared to 82.3% for the conventionally treated group. The Shark Screw® group exhibited a tendency for faster bone healing (9.4±3.2 vs. 12.9±8.5 weeks, p=0.05061). Hardware irritations led to six metal removals in the conventional group versus two in the Shark Screw® group. The Shark Screw® emerges as a promising option for personalized non-union treatment in the foot, ankle, and select lower leg cases, facilitating effective osteosynthesis and grafting within a single construct, promoting high union rates, low complications, and a rapid healing process.

Real-time object detection remains a pivotal topic in the realm of computer vision. Balancing the accuracy and speed of object detectors poses a formidable challenge for both academic researchers and industry practitioners. While recent transformer-based models have showncase the prowess of the attention mechanism, delivering remarkable performance improvements over CNNs, their computational demands can hinder their effectiveness in real-time detection tasks. In this paper, we elect to use YOLOX as our robust starting point and introduce a series of effective enhancements, culminating in a new high-performance detector named YOLOAX. To further exploit the power of the attention mechanism, we devise multi-dimensional attention-based modules that activate CNNs, emphasizing the most pertinent regions and bolstering the capacity to learn the most informative image representations from feature maps. Moreover, we introduce a novel leading label assignment strategy called STA, along with a groundbreaking loss function named GEIOU Loss, to further refine our detector's performance. We provide extensive ablation studies on the COCO and PASCAL VOC 2012 detection datasets to validate our proposed methods. Remarkably, our YOLOAX is trained solely on the MS-COCO dataset from scratch, without leveraging any prior knowledge, which achieves an impressive 54.2% AP on the COCO 2017 test set while maintaining a real-time speed of 72.3 fps, surpassing YOLOX by a significant margin of 3.0% AP. Our source code and pre-trained models are openly accessible at https://github.com/KejianXu/yoloax.

In recent years, the individualized demand of customers brings small batches and diversification of orders towards enterprises. The application of enabling technologies in factory, such as the Industrial Internet of Things (IIoT) and Cloud Manufacturing (CMfg), enhances the ability of customer requirement automatic elicitation and the manufacturing process control. The job shop scheduling problem with random job arrival time dramatically increases the difficulty in process management. Thus, how to collaboratively schedule the production and logistics resources in the shop floor is very challenging, and it has a fundamental and practical significance of achieving the competitiveness for an enterprise. To address this issue, the real-time model of production and logistics resources is built firstly. Then, the task entropy model is built based on the task information. Finally, the real-time self-adaption collaboration of production and logistics resources is realized. The proposed algorithm is carried out based on a practical case to evaluate its effectiveness. Experimental results show that our proposed algorithm outperforms three existing algorithms.

An information-theoretic data mining method is employed to analyze categorical spatiotemporal Geographic Information System land use data. Reconstructability Analysis (RA) is a maximum-entropy-based data modeling methodology that works exclusively with discrete data such as those in the National Land Cover Database (NLCD). The NLCD are organized into a spatial (raster) grid, and are available in consistent format for every five years from 2001 to 2021. An NLCD tool reports how much change occurred for each category of land use; for the study area examined the most dynamic class is Evergreen Forest (EFO), so the presence or absence of EFO in 2021 was chosen as the dependent variable that our data modeling attempts to predict. RA predicts the outcome with approximately 80% accuracy using a sparse set of cells from a spacetime data cube consisting of neighboring lagged-time cells. When the predicting cells are all Shrubs & Grasses there is a high probability for a 2021 state of EFO, while when the predicting cells are all EFO, there is a high probability that the 2021 state will be not-EFO. These findings are interpreted as detecting forest clear-cut cycles that show up in the data, and explain why this class is so dynamic. This study introduces a new approach to analyzing GIS categorical data and expands the range of applications that this entropy-based methodology can successfully model.

This paper aims to address the exponential stability and stabilization problems for a class of delayed nonlinear Markov jump systems under randomly occurring Denial-of-Service (DoS) attack and packet loss. Firstly, the stochastic characteristics of DoS attack and packet loss are depicted by the attack success rate and packet loss rate. Secondly, a Period Observation Window (POW) method and a hybrid-input strategy are proposed to compensate for the impact of DoS attack and packet loss on the system. Thirdly, A Dynamic Event-triggered Mechanism (DETM) is introduced to save more network resources and ensure the security and reliability of systems. Then, by constructing a general common Lyapunov functional and combining with the DETM and other inequality analysis techniques, the less conservative stability and stabilization criteria for the underlying systems are derived. In the end, the effectiveness of our result is verified through a numerical example.

This paper explores an event-based version of quantum mechanics which differs from the commonly accepted one, even though the usual elements of quantum formalism, e.g., the Hilbert space, are maintained. This version introduces as primary element the occurrence of micro-events induced by usual physical (mechanical, electromagnetic and so on) interactions. These micro-events correspond to state reductions and are identified with quantum jumps, already introduced by Bohr in his atomic model and experimentally well established today. Macroscopic bodies are defined as clusters of jumps; the emergence of classicality thus becomes understandable and time honoured paradoxes can be solved. In particular, we discuss the cat paradox in this context. Quantum jumps are described as temporal localizations of physical quantities; if the information associated with these localizations has to be finite, two time scales spontaneously appear: an upper cosmological scale and a lower scale of elementary "particles''. This allows the interpretation of the Bekenstein limit like a particular informational constraint on the manifestation of a micro-event in the cosmos it belongs. The topic appears relevant in relation to recent discussions on possible spatiotemporal constraints on quantum computing.

The high penetration of distributed energy resources poses significant challenges to the dispatch and operation of power systems. Improving the accuracy of short-term load forecasting (STLF) can optimize grid management, leading to increased economic and social benefits. Currently, some simple AI and hybrid models has issues to deal with and struggle with multivariate dependencies, long-term dependencies, and non-linear relationships. This paper proposes a novel hybrid model for short-term load forecasting (STLF) that integrates multiple AI models with Lasso regression using the stacking technique. The base learners include ANN, XgBoost, LSTM, Stacked LSTM, and Bi-LSTM, while Lasso regression serves as the meta-learner. By considering factors such as temperature, rainfall, and daily electricity prices, the model aims to more accurately reflect real-world conditions and enhance predictive accuracy. Empirical analyses on real-world datasets from Australia and Spain show significant improvements in forecasting accuracy, with a substantial reduction in Mean Absolute Percentage Error (MAPE) compared to existing hybrid models and individual AI models. This research highlights the efficiency of the stacking technique in improving STLF accuracy, suggesting potential operational efficiency benefits for the power industry.

We review our theory of interdependence applied to autonomous human-machine teams, with which we have made several generalizations based on theory that have led to new discoveries, compared to social science which is struggling to break free of its validation crisis, but also has no generalizations to new discoveries with human teams, let alone to human-machine teams. In this invited article, based around the stability of a team, of our discoveries, we review the uncertainty between a team's structure and its performance, our first finding. We generalize that finding to deception, vulnerability, innovation and fittedness. From there, our next generalization is to the quantum likeness of interdependence and quantum mechanics; we move on to Shannon holes, knowledge, and conclude with the value of debate and the need for boundaries to contain debate, to reduce interference, and to protect states of interdependence. After the introduction, we extend our model in Section 2 to energy and time, and we close with a brief review of innovation and future plans.

This paper studies the duration patterns of unemployment spells for immigrants and the determinants of unemployment’s completion into one of a number of studied labour market states in Finland. We estimate a duration model for unemployment with competing risks of its terminating into employment, labour market training or economic inactivity. Taking into account the wide period of observation and opportunities to analyse processes of labour market integration during various periods of economic development in Finland, in combination with the individualistic character of the labour careers of immigrants, this research is beneficial owing to the many various findings concerning labour market integration of immigrants. The approach undertaken in this research has a dualistic “descriptive-dynamic” character under which integration is understood as a never-ending process, which is conditioned by a time period of long-term existence and a context of solitary action. We find that transitions out of unemployment spells have a cyclical character; after every new “cycle” in unemployment, the probability of terminating unemployment decreases further. We also find that ascriptive factors make sense in the process of job-placement of immigrants from unemployment. Therefore, the gender, education and age of immigrants, as well as the effect of the period in which first unemployment occurred, potentially predict transitions out of unemployment and further labour market integration of immigrants.

In children, the global burden of vaccines-preventable diseases (VPDs) and deaths can be averted by adopting timely immunization practices. Administering immunization to a child within 28 or 30 days of the designated immunization date is referred to as timely immunization. Delaying or missing vaccinations puts children, especially those in urban slums, at a higher risk of getting sick or dying from different diseases. This study was designed to examine the immunization practices and to measure the determinants of immunization non-compliance in children living in urban slums of Karachi, Pakistan. A community-based retrospective cohort was carried out from October-2018- to August-2019 in six different urban slums of Karachi. Immunization status of children aged less than 2 years was assessed by reviewing their vaccination card. Children from each slum were approached via 30x7 multistage stratified cluster sampling technique. Data of each child was analysed descriptively and inferentially using a statistical software, i.e., Jamovi version 1.2.25. The practice of timely immunization was observed in approximately half of children, i.e., 49.8%(n=457). The immunization rate at birth (first-visit) was 100%, of which 95.7% were timely immunized. Following the second immunization visit, a sharp decline in the immunization rate, including timely immunization rate was observed. Lack of knowledge, childhood illnesses, lack of interest, and vaccines unavailability were the main reasons of immunization non-compliance. However, an increase in paternal education was significantly associated to decrease the odds of immunization non-compliance. A decrease in the practice of timely immunization is replaced by either invalid and/or delayed and/or missed immunization practices. Thus, timely immunization is crucial for preventing the infectious diseases and promoting the health of a child.

The most commonly used real-time augmentation services in China are International GNSS Service (IGS) real-time service, PPP-B2b service, and BeiDou Satellite-Based Augmentation System (BDSBAS) dual-frequency augmentation service. However, the research on the performance evaluation, comparison and application scope of these three products is still unknown and unrevealed. This article introduces methods for obtaining real-time augmentation information and real-time orbit and clock offset recovery. Based on real-time orbit and clock offset accuracy, positioning accuracy, and positioning availability, it systematically evaluates the performance of CNES, PPP-B2b, and BDSBAS augmentation information. The results indicate that the radial accuracy of CNES and PPP-B2b real-time orbit products is consistent, and the Root Mean Square (RMS) is better than 5 cm. CNES can achieve centimeter-level accuracy in both along-track and cross-track components, surpassing the decimeter-level accuracy of PPP-B2b. Both services demonstrate consistent accuracy in real-time clock offset, with PPP-B2b showing similar standard deviations (STD) of 0.16 ns for different satellites. However, for CNES, the STD of real-time clock offset varies for GPS, BDS-3 MEO, and BDS-3 IGSO satellites, with values of 0.10 ns, 0.19 ns, and 0.60 ns, respectively. The accuracy and availability of the two PPP services exhibit the same levels, with centimeter-level accuracy achieved after convergence and positioning availability exceeding 99%. Therefore, the difference between the two services in application areas depends on the acquisition of augmentation information. However, BDSBAS, which concentrates on code observations, demonstrates lower accuracy in real-time orbit and clock offset, positioning accuracy, and positioning availability compared to the other two services. Its primary application is in the aviation and maritime domains, where there is a greater need for service integrity, continuity, and reliability.

Metaverse represents a multifaceted digital universe integrating diverse technologies to create immersive, interconnected virtual environments. Key components foundational to its structure include the infrastructure layer for hardware and network support, the human interface layer utilizing virtual reality (VR) and augmented reality (AR) devices, and a decentralized layer leveraging blockchain for secure digital asset management. Further components encompass spatial computing for realistic 3D environments, the creator economy for content generation and monetization, and discovery mechanisms for navigation within Metaverse. VR, AR, blockchain, AI, the fifth-generation (5G) networks, and the Internet of Things (IoT) are central to Metaverse functionality, enabling real-time interactions and data integration. Real-Time Metaverse aims to replicate instantaneous real-world interactions, requiring advanced technological infrastructure for seamless data exchange. Critical challenges include ensuring low latency, high bandwidth, scalability, and robust security measures. Metaverse’s potential spans various domains, promising to revolutionize social interactions, entertainment, workplaces, and education through dynamic, immersive experiences. Ongoing advancements in high-performance computing, cloud services, and AI-driven technologies are essential for addressing existing barriers and achieving a cohesive, secure, and inclusive Metaverse ecosystem. Future research must focus on enhancing user experience, accessibility, and standardized interoperability to fully realize the transformative capabilities of a Metaverse.

Traffic anomaly detection is crucial for urban management, yet current research is often confined to small-scale endeavors. This study collected nine months of real-time Wuhan traffic monitoring data from Amap. We proposed Traffic-ConvLSTM, a multi-scale spatial-temporal technique based on long and short-term memory networks (LSTM) and convolutional neural networks (CNN) to effectively achieve long-term anomaly detection at the city level. First, we convert the traffic flow data into image representation, which enables the capture of the spatial correlation between traffic flow and roads and the correlation between traffic flow and roads, as well as the surrounding environment. Second, The model utilizes convolution kernels of different sizes to extract spatial features at road-level, regional-level, and city-level scales, while incorporating temporal features of different time steps to capture hourly, daily, and weekly dynamics. Additionally, varying weights are assigned to the convolution kernels and temporal features of varying spatio-temporal scales to capture the heterogeneous strengths of spatio-temporal correlations within patterns of traffic anomalies. The proposed Traffic-ConvLSTM model exhibits improved performance over existing techniques in the task of identifying long-term and large-scale traffic anomaly occurrences. Furthermore, the analysis reveals significant traffic anomalies during holidays and urban sporting events. The diverse travel patterns observed in response to various activities offer insights for large-scale urban traffic anomaly management, providing recommendations for city-level traffic control strategies.

Informational (Shannon) measures of symmetry are introduced and analyzed for the patterns built of 1D and 2D shapes. The informational measure of symmetry Hsym (G) characterizes the an averaged uncertainty in the presence of symmetry elements from the group G in a given pattern; whereas the Shannon-like measure of symmetry Ωsym (G) quantifies averaged uncertainty of appearance of shapes possessing in total n elements of symmetry belonging to group G in a given pattern. Hsym(G1)=Ωsym(G1)=0 for the patterns built of irregular, non-symmetric shapes. Both of informational measures of symmetry are intensive parameters of the pattern and do not depend on the number of shapes, their size and area of the pattern. They are also insensitive to the long-range order inherent for the pattern. Informational measures of symmetry of fractal patterns are addressed. The mixed patterns including curves and shapes are considered. Time evolution of the Shannon measures of symmetry is treated. The close-packed and dispersed 2D patterns are analyzed.

Climacteric fruits undergo a characteristic ripening process regulated by ethylene, a key plant hormone. Extending the shelf life of these fruits while preserving their postharvest quality poses a significant challenge for the food industry. This review provides a comprehensive overview of physiological and molecular strategies to delay ethylene-mediated ripening in climacteric fruits and their impact on shelf life, postharvest quality, sensory attributes, and volatile compounds. Additionally, it examines the role of ethylene in fruit ripening analysing various ethylene managing strategies including ethylene inhibitors, ethylene adsorbents and ethylene scavengers by catalytic oxidation The review concludes with future research directions including integrated strategies, environmental considerations and commercial applications for improving postharvest handling and fruit quality.

Many children have suspected delayed language development and need extensive support from parents and the health care team. This study aimed to investigate suspected delayed language development and factors associated with suspected delayed language development among early childhood in Southern Thailand. Children aged 24 to 60 months were recruited as study samples using stratified random sampling conducted in 23 districts and simple randomized seven sections (425 children). Instruments comprised demographic data of the children and families, The preschool temperament questionnaire, and the Language Development Screening questionnaire using developmental surveillance and promotion manual. I was collecting data from July 2020 to January 2021. Data analysis used descriptive statistics and logistic regression. The results showed that 40.9 percent suspected delayed development. Daily screen time exceeding 2 hours per day (A.O.R. = 17.30, 95% CI: 7.35-40.72), and regarding a child's temperament, moderate-to-difficult temperament (A.O.R. = 9.56, 95% CI: 5.12-17.85) were significantly associated with a suspected delay of language development. The study suggested two-way communication and appropriate responses will help develop children's language.

Air sampling using vortex air samplers combined with species specific amplification of pathogen DNA, was carried out over two years in four or five locations in the Salinas Valley of California. The resulting time series data for the abundance of pathogen DNA trapped per day displayed complex dynamics with features of both deterministic (chaotic) and stochastic dynamics. Methods of nonlinear time series analysis developed for the reconstruction of low dimensional attractors provided new insights into the complexity of the pathogen abundance data, but also indicated that practicality may limit the capacity for definitively classifying the dynamics of air borne plant pathogen inoculum. Over the two years of the study five location/year combinations were classified as having stochastic linear dynamics and four were not. Calculation of entropy values for either the number of pathogen DNA copies or for a binary string indicating the pathogen abundance data were increasing or not, revealed (1) some robust differences in the dynamics between seasons that were not obvious in the time series data themselves, and also (2) that the series were almost all at their theoretical maximum entropy value when considered from the simple perspective of whether instantaneous change along the sequence is positive or not.

This study presents a novel approach to enhance Large Language Models (LLMs) like Alpaca by dynamically integrating real-time information. This method addresses the issue of content hallucination and data relevancy by automatically collecting and integrating current data from credible sources into model prompts. Experiments show a significant improvement in accuracy and a decrease in content hallucination, with a manageable increase in response time. The research underscores the potential of real-time data integration in making LLMs more accurate and contextually relevant, setting a foundation for future advancements in dynamic data processing in AI.

Amidst the backdrop of continually declining total fertility rates and a population structure trending towards super-aging in China, can simple adjustments to birth policies effectively address the challenges of low fertility and aging? This study constructs a three-phase overlapping-generation model that incorporates fertility rates and delayed retirement. It investigates the economic impact of adjustments in birth policies and delayed retirement, and utilizes simulations and analyses based on real-world data from China. The research yields several key findings:1.Although theoretically, the impact of population aging on economic growth rates is uncertain, empirical data simulations indicate that the current level of population aging in China has already exerted a certain adverse impact on economic growth.2.Given the current population structure, delayed retirement can, to some extent, promote economic growth. However, due to potential vulnerabilities of older individuals who choose delayed retirement, such as reduced labor efficiency and learning abilities, the implementation of delayed retirement policies should be flexible and context-specific.3.Increasing fertility rates can mitigate the economic impact of the current demographic challenges. Thus, relaxing birth policies remains a crucial strategy that China must implement. A coordinated adjustment of delayed retirement and fertility rates is more likely to enhance economic growth.

With the aging of China's population, the problem of pension security has become more and more prominent, and whether delayed retirement can effectively alleviate the pension fund gap and ensure the sustainability of the pension fund has become the focus of social concern. This study predicts the income and expenditure of urban workers' basic pension insurance fund from 2021 to 2050 by constructing an actuarial model of pension insurance fund income and expenditure, and simulates the effect of delayed retirement policy. The prediction results show that under the existing system, the basic pension insurance fund for urban workers will have a shortfall for the first time in 2027, and the shortfall will expand year by year. Compared with the non-implementation of delayed retirement policy, the simulation of the implementation of delayed retirementt program delayed the emergence of the fund gap until 2029, and the forecast period of the pension fund gap significantly narrowed, indicating that delayed retirement policy has a certain positive impact on alleviating the pressure of pension payments, but delayed retirementt can not completely eliminate the pension fund gap. In view of this, this paper suggests that a progressive and flexible delayed retirement policy should be introduced as soon as possible to better adapt to the needs of different groups. At the same time, differentiated policies should be formulated for different groups of people and a pension incentive mechanism for delayed retirement should be set up to improve public acceptance of delayed retirement policy. In addition, delayed retirement policy should be combined with other measures, such as lowering the corporate contribution rate and enhancing the value-added capacity of the pension fund, so as to ensure the sustainability of the pension fund.

The conventional explanation of delayed-choice experiments seems to violate our causal intuition. This apparent violation is caused by a misinterpretation of the conventional formulation of quantum mechanics. I reanalyze these experiments using advanced and time-symmetric formulations of quantum mechanics. All three formulations give the same experimental predictions, but the advanced and time-symmetric formulations violate our causal intuition that effects only happen after causes. I explore reasons why our causal intuition may be wrong at the quantum level. I also suggest how conventional causation might be recovered in the classical limit, and speculate on cosmological boundary conditions.

This paper explores the application of machine learning in financial time series analysis, focusing on predicting trends in financial enterprise stocks and economic data. It begins by distinguishing stocks from stocks and elucidates risk management strategies in the stock market. Traditional statistical methods such as ARIMA and exponential smoothing are discussed in terms of their advantages and limitations in economic forecasting. Subsequently, the effectiveness of machine learning techniques, particularly LSTM and CNN-BiLSTM hybrid models, in financial market prediction is detailed, highlighting their capability to capture nonlinear patterns in dynamic markets. The study demonstrates the advancements in predictive accuracy and robustness achieved by deep learning methods through empirical analysis and model validation. The findings contribute significantly to academic discourse and offer practical insights for investors, financial analysts, and policymakers navigating market volatility and optimizing investment strategies. Finally, the paper outlines prospects for machine learning in financial forecasting, laying a theoretical foundation and methodological framework for achieving more precise and reliable economic predictions.

In this paper, we derive Jeffreys divergence, generalized Fisher divergence and corresponding De Bruijn identities on space-time random field. First, we determine the relation between Fisher information on the space-time random field in one of the space-time points and the ratio of Jeffreys divergence on a space-time random field at distinct space-time positions to the square of coordinate difference. In addition, we also find identities between the partial derivative of the Jeffreys divergence and the generalized Fisher divergence with respect to space-time variables, i.e. the De Bruijn identities, between two space-time random fields obtained by different parameters under the same Fokker-Planck equations. At the end of this paper, we present three examples of the Fokker-Planck equations on space-time random fields, identify their density functions, and derive the Jeffreys divergence, generalized Fisher information, generalized Fisher divergence, and accompanying De Bruijn identities.

In economics, especially econometrics, fixed-effects are widely recognized as powerful tools for heterogeneity analysis of longitudinal data sets. However, the existing research pays more attention to such as the variable selection, parameter estimation and dimension reduction on linear relationships with too many assumptions while nonlinear relationships are ubiquitous. In this paper, an extension fixed-effects model is proposed on the curve_fit nonlinear least squares. First, with the help of expert knowledge, the series regressions between independent variables including time and dependent variable is estimated on each series data, and the parameters are estimated by curve_fit. Similarly, the coeffection between independent variables including time and dependent variable is also initially estimated on the whole panel data. Second, the distance between regressions is defined, and then the coeffect function between the series regressions is obtained on the initial co-effect with curve_fit. Third, the time-effects and individual fixed-effects for each series data in the panel data are estimated on the differences of series regressions and co-effect function. Additionally, the effectiveness of the proposed method is varified on the synthetic data.

One of the main causes of the dismal prognosis in patients who survive the initial bleeding after aneurysmal subarachnoidal hemorrhage is the delayed cerebral ischaemia caused by vasospasm. Studies suggest that cerebral magnesium and pH may potentially play a role in the pathophysiology of this adverse event. Using phosphorous magnetic resonance spectrocopy (31P-MRS) we calculated the cerebral magnesium (Mg) and pH level in 13 patients who suffered aSAH. The values between the group that developed clinically significant vasospasm (n=7) and the group that did not (n=6) were compared. The results of this study showed significantly lower cerebral Mg levels (p=0.019) and higher pH (p<0.001) in cumulative group (all brain voxels together) in patients who developed clinically significant vasospasm. Further clinical studies on a larger group of carefully selected patients are needed in order to predict clinically significant vasospasm.

The diagnosis of celiac disease (CD) may be delayed due to non-specific clinical symptoms. The aim of the study was to evaluate the clinical manifestation and diagnostic process of CD in Polish children and adults. Methods: The members of the Polish Coeliac Society (n=2 500) were asked to complete a questionnaire on socio-demographic factors, clinical and diagnostic aspects of CD. The analysis was based on 796 responses from patients with confirmed CD diagnosis, and included 224 (28.1%) children and 572 (71.9%) adults. Results: The mean duration of symptoms prior to CD diagnosis in children was significantly shorter than in adults (p < 0.001), and amounted to 3.1 and 9 years respectively. The most frequent symptoms before CD diagnosis were abdominal pain and bloating in children (70.4%), and chronic fatigue in adults (74.5%). Although almost all CD patients claimed to strictly avoid gluten after CD diagnosis, symptoms were still present in the majority of these respondents. No comorbid diseases were reported by 29.8% of children and by 11.7% of adults (p < 0.001). Conclusions: The results indicate that CD diagnosis is delayed in Poland, espe-cially in adults, and clinicians should be aware of the diversity in CD presentation.

Wireless Powered Communication Networks (WPCN), which has attracted much attention of researchers, also been recently recommended in 5^th generation (5G) wireless networks. With the help of the WPCN, the reliability and battery life of wireless low-power devices can be improved. In this paper, we investigate throughput and ergodic capacity in WPCN-assisted amplify-and-forward (AF) relaying system, considering two transmission modes including delay-tolerant and delay-limited. As important achievement, we propose symmetric energy harvesting protocol, namely time power switching relaying (TPSR) in order to find maximal throughput. In particular, both time switching and power switching coefficients in this schemes are considered. Unlike most of the previous works, we further focus on impact of outdated channel state information (CSI) in this WPCN. In order to evaluate information processing efficiency, the performance can be substantially improved by optimally harvesting time and power coefficients of the received signal at relay node for energy and information extraction, and by deploying several scenarios. By deploying Monte Carlo simulation, it is confirmed that the system performance is more sensitive to CSI estimation error, noise variance, signal-to-noise ratio (SNR) and resulting in other reasonable computations of TPSR need be deployed to obtain QoS requirement.

Satellite Crop Detection technologies are focused on detection of different types of crops on the field in the early stage before harvesting. Crop detection is usually done on a time series of satellite data by classification of the desired fields. Currently, data obtained from Remote Sensing (RS) are used to solve tasks related to the identification of the type of agricultural crops, also modern technologies using AI methods are desired in the postprocessing part. In this challenge Sentinel-1 and Sentinel-2 time series data were used due to their periodic availability. Our focus was to develop methodology for classification of time series of Sentinel 2 and Sentinel 1 data and compare how accuracy of classification can be increased, but also how to guarantee availability of data. We analyse phenology of single crops and on the basis of this analysis we started to provide crop classification. Original crop classifications were made from Enhanced Vegetation Index (EVI) layers made from Sentinel-2 time-series data and then we added also . To increase accuracy we also integrate into the process parcel borders and provide classification of fields..

Responsible, efficient, and environmentally conscious energy consumption practices are increasingly essential for ensuring the reliability of the modern electricity grid. This study focuses on leveraging time series analysis to improve forecasting accuracy, crucial for various application domains where real-world time series data often exhibit complex, non-linear patterns. Our approach advocates for utilizing Long Short Term Memory (LSTM) and Bidirectional LSTM (BiLSTM) models for precise time series forecasting. To ensure a fair evaluation, we compare the performance of our proposed approach with traditional neural networks, time-series forecasting methods, and conventional decline curves. Additionally, individual models based on LSTM, Bi-LSTM, and other machine learning methods are implemented for a comprehensive assessment. Experimental results consistently demonstrate that our proposed model outperforms all benchmarking methods in terms of mean absolute error (MAE) across most datasets. Addressing the imbalance between activations by consumer and prosumer groups, our predictions show superior performance compared to several traditional forecasting methods, such as the Autoregressive Integrated Moving Average model (ARIMA) and Seasonal Autoregressive Integrated Moving Average model (SARIMA). Specifically, the root mean square error (RMSE) of Bi-LSTM is 5.35%, 46.08%, and 50.6% lower than LSTM, ARIMA, and SARIMA, respectively, on the May test data.

Background: This study aimed to investigate the impact of the COVID-19 pandemic on breast reconstruction trends in the United States, focusing on implant-based and autologous techniques, as well as the timing of reconstruction (immediate vs. delayed). Methods: A retrospective analysis of data from the American Society of Plastic Surgeons' National Plastic Surgery Statistics from 2015 to 2022 was conducted. Annual trends in breast reconstruction procedures were analyzed, comparing the pre-pandemic (2015-2019) and pandemic (2020-2022) periods. Results: The total number of breast reconstructions increased from 106,338 in 2015 to 151,641 in 2022. The proportion of implant-based reconstructions decreased from 81.41% pre-pandemic to 76.51% during the pandemic (p < 0.001), with a notable rise in direct-to-implant procedures from 10.37% to 19.12% (p < 0.001). Autologous reconstructions increased from 18.59% to 23.49% (p < 0.001). Among autologous techniques, DIEP flaps remained the most popular. Immediate reconstruction rates increased from 72.61% pre-pandemic to 75.57% during the pandemic, while delayed recon-struction rates decreased from 27.39% to 24.43% (p < 0.001). Conclusions: The COVID-19 pandemic has significantly influenced breast reconstruction trends in the United States, with a shift towards autologous techniques, particularly DIEP flaps, and an in-crease in immediate reconstructions. These changes may reflect adaptations in surgical practice and decision-making processes in response to the unique challenges posed by the pandemic. Further research is needed to assess the long-term outcomes and patient satisfaction associated with these trends.

Background: Along with sarcopenia, delayed blood pressure (BP) recovery after standing and orthostatic hypotension (OH) are among key clinical challenges associated with ageing. Previous studies have reported an association between sarcopenia and delayed orthostatic BP recovery and OH. However, the haemodynamic mechanisms underlying this association remain unclear. Methods: 107 attendees to a falls and syncope clinic aged 50+ years underwent an active stand test with non-invasive beat-to-beat haemodynamic measurement. Hand grip strength and 5-chair stands time were measured. Muscle mass was estimated using bioelectrical impedance analysis, and participants were classified as non-sarcopenic and sarcopenic. Mixed effects models with linear splines were used to model the effect of sarcopenia status on Modelflow®-derived mean arterial pressure (MAP), cardiac output (CO), total peripheral resistance (TPR), stroke volume (SV) and heart rate (HR) after standing, while controlling for potential confounders. Results: Sarcopenia was associated with: attenuated recovery of MAP in the 10-20s period after standing (β -0.67, P<0.001); attenuated rise to peak (0-10s) and recovery from peak (10-20s) of CO (β -0.05, P<0.001; β 0.06, P<0.001); attenuated recovery (10-20s) of TPR from nadir (β -0.02, P<0.001) and attenuated recovery from peak (10-20s) of SV (β 0.54, P<0.001). HR was not significantly associated with sarcopenia status at any time interval after standing. Conclusion: The attenuated BP recovery after standing seen in sarcopenia appears to be driven by initial diminished peak of CO followed by attenuated recovery of CO from peak and TPR from nadir. The CO finding appears to be driven by SV rather than HR. Potential mechanisms for these findings include: cardio-sarcopenia, the effects of sarcopenia on the autonomic nervous system and/or the skeletal muscle pump.

In the first wave of COVID-19, up to 20% of patients had skin lesions with variable characteristics. There is no clear evidence of the involvement of the SARS-CoV-2 virus in all the cases; some of these lesions may be secondary to drug hypersensitivity. To analyze the possible cause of the skin lesions, we performed a complete allergology study on 11 patients. One year after recovery from COVID-19, we performed a lymphocyte transformation test (LTT) and Th1/Th2 cytokine secretion assays of PBMC. We included 5 nonallergic patients treated with the same drugs without lesions. Except for one patient who had an immediate reaction to azithromycin, all patients had a positive LTT to at least one of the drugs tested (azithromycin, clavulanic acid, hydroxychloroquine, lopinavir, and ritonavir). None of the nonallergic patients had a positive LTT. We found mixed Th1/Th2 cytokine secretion (IL-4, IL-5, IL-13, and IFN-γ) in patients with skin lesions corresponding to mixed drug hypersensitivity type IVa and IVb. In all cases, we identified a candidate drug as the culprit for skin lesions during SARS-CoV-2 infection, although only three patients had a positive drug challenge. Therefore, it would be reasonable to recommend avoiding the drug in question in all cases.

Previous studies have quantified repolarization variability using time-domain, frequency-domain and non-linear analysis in mouse hearts. Here, we investigated the relationship between these parameters and ventricular arrhythmogenicity in a hypokalaemia model of acquired long QT syndrome. Methods: Left ventricular monophasic action potentials (MAPs) were recorded during right ventricular regular 8 Hz pacing during normokalaemia (5.2 mM [K+]), hypokalaemia modelling LQTS (3 mM [K+]) or hypokalaemia with 0.1 mM heptanol in Langendorff-perfused mouse hearts. Results: During normokalaemia, mean APD was 33.5±3.7 ms. Standard deviation (SD) of APDs was 0.63±0.33 ms, coefficient of variation was 1.9±1.0% and the root mean square (RMS) of successive differences in APDs was 0.3±0.1 ms. Low- and high-frequency peaks were 0.6±0.5 and 2.3±0.7 Hz, respectively, with percentage powers of 38±22 and 61±23%. Poincaré plots of APDn+1 against APDn revealed ellipsoid morphologies with SD along the line-of-identity (SD2) to SD perpendicular to the line-of-identity (SD1) ratio of 4.6±1.1. Approximate and sample entropy were 0.49±0.12 and 0.64±0.29, respectively. Detrended fluctuation analysis revealed short- and long-term fluctuation slopes of 1.62±0.27 and 0.60±0.18, respectively. Hypokalaemia provoked ventricular tachycardia in six of seven hearts, prolonged APDs (51.2±7.9 ms), decreased SD2/SD1 ratio (3.1±1.0), increased approximate and sample entropy (0.68±0.08 and 1.02±0.33) and decreased short-term fluctuation slope (1.23 ± 0.20) (ANOVA, P<0.05). Heptanol prevented VT in all hearts studied without further altering the above repolarization parameters observed during hypokalaemia. Conclusion: Reduced SD2/SD1, increased entropy and decreased short-term fluctuation slope are associated with ventricular arrhythmogenesis in hypokalaemia. Heptanol exerts anti-arrhythmic effects without affecting repolarization variability.

In real financial market, the delayed market feedback and the delayed effect of government macro-control are inevitable. And both the delay of market feedback and the delay of macro-control effect bring about the mathematical difficulties in studying stabilization and synchronization of the hyper-chaotic financial system. However, employing Lyapunov function method, differential mean value theorem, suitable bounded hypotheses and pulse control technology results in the globally asymptotical stabilization and synchronization criteria. It is the first paper to drive the stabilization and synchronization criteria under the assumptions of the double delays. Finally, numerical examples illuminate the effectiveness of the proposed methods.

Much remains to be understood for delayed ultraweak photon emission (UPE) from organism in association with oxidative burst following external perturbation, a phenomenon that has been experimented for over three decades. Delayed UPE often decays hyperbolically; yet, it is not uncommon to have delayed UPE that reveals first-order kinetic patterns characterized by single-exponential, double exponential, or multi-exponential changes. Some delayed UPEs also presented transient patterns that are characteristic of second-order responses. A soliton-based photon-storage model has addressed the hyperbolic decaying pattern of delayed UPE; however, there are questions outstanding regarding modeling other non-hyperbolic kinetics as well as the large range of temporal scales of delayed UPE that can vary from 8.5 microseconds to many hours. This work proposes an alternative, phenomenological model-framework for interpreting the various kinetic patterns of delayed UPE following stress. The delayed UPE is considered to be governed by two sequential phases: a stress-transfer phase that transforms the external stress to photo-genesis for emitting photons, and a photon-diffusion phase that transmits the photons emitted by the photo-genesis to the surface of organism for being detected as delayed UPE. Time-resolved photon diffusion analysis reveals that any delayed UPE in organism with a delay time >100ns cannot be addressed by the inherent temporal spread that realistic tissue scattering will cause. A slow stress-transfer phase is thus required to explain the delay time-scales of delayed UPE at a minimum of 8.5 µs as reported experimentally. The stress-transfer phase is hypothesized to carry the following types of responses: single or multiple 1st-order low-pass, single 2nd-order low-pass with various damping factors, and single 2nd-order band-pass with various damping factors. A single 1st–order low-pass response with a time-varying kinetic rate is also analyzed. The responses of these modeled pathways to bolus and step inputs demonstrate that a kinetic pattern other than the exact single-exponential one may have multiple causes.

Recent studies have indicated that terahertz time-domain spectroscopy (THz-TDS) can stably and efficiently acquire output spectra using an affordable and compact multimode laser diode (MMLD) with delayed optical feedback as the light source. This research focused on a numerical analysis of the optimal conditions for employing an MMLD with delayed optical feedback (chaotic oscillating laser diode) in THz-TDS, utilizing multimode rate equations. The findings revealed that the intermittent chaotic output generated by the MMLD, characterized by concurrent picosecond pulse oscillations lasting several tens of picoseconds, proves to be highly effective for THz-TDS. By appropriately setting the amounts of injection current and optical feedback, and the delay time of optical feedback, intermittent chaotic oscillation can be attained within a considerably broad parameter range. Moreover, both the MMLD output spectrum and the THz-TDS output spectrum exhibit a consistently stable shape at the microsecond scale, demonstrating the attractor properties inherent in an MMLD with delayed optical feedback.

This qualitative research explores the profound implications of integrating real-time supply chain information on marketing decisions within service industries. Through semi-structured interviews with professionals from logistics, retail, hospitality, healthcare, and telecommunications sectors, the study examines how real-time data enhances demand forecasting, inventory management, personalized marketing approaches, agility in marketing responses, and supplier relationship management. Findings reveal that real-time supply chain information significantly improves accuracy in predicting customer demand and optimizing inventory levels, thereby reducing costs and enhancing service delivery efficiency. Moreover, real-time data enables more targeted marketing strategies through granular customer segmentation and dynamic pricing adjustments based on real-time market dynamics. The agility afforded by real-time information allows companies to swiftly adapt marketing strategies to emerging trends and consumer behaviors, maintaining competitiveness in dynamic service markets. Enhanced supplier collaboration and risk management further underscore the strategic value of real-time supply chain integration, fostering stronger partnerships and supply chain resilience. This study contributes to a deeper understanding of how real-time supply chain information transforms marketing practices in service industries, highlighting its role in improving operational efficiency, customer satisfaction, and overall competitiveness. Future research could explore implementation challenges and long-term impacts across diverse service sectors, providing insights into optimizing the strategic use of real-time data for sustained business success.

The accurate forecasting of solar power output is essential for ensuring the stable and efficient operation of grid-connected photovoltaic (PV) systems, especially when faced with variable weather patterns. This research focuses on the integration of Machine Learning (ML) methodologies and climatic parameters to predict solar panel energy generation, with a specific emphasis on addressing consumption-production imbalances. Leveraging a dataset sourced from the Kaggle platform, the study is conducted in the context of Estonia, aiming to optimize solar energy utilization in this geographic region. The dataset, obtained from Kaggle, encompasses comprehensive information on climatic variables, including sunlight intensity, temperature, and humidity, alongside corresponding solar panel energy output. Leveraging machine learning algorithms, including XGBoost regression and neural networks, our model aims to identify complex patterns and relationships within the datasets. By tailoring the model to Estonia's climatic nuances, we seek to enhance the accuracy of energy production forecasts and, consequently, better manage the challenges associated with consumption-production imbalances. Furthermore, the research investigates the adaptability of the proposed model to diverse climatic conditions, ensuring its applicability for similar endeavors in other geographical locations. The performance of the forecasting model will be evaluated using error metrics like mean absolute error (MAE) and root mean squared error (RMSE). This study leverages a comprehensive dataset from Kaggle and utilizes advanced machine learning techniques to generate valuable insights. These insights can inform the development of sustainable energy policies and practices, ultimately leading to a more efficient and reliable renewable energy infrastructure.

Information can be considered as the most fundamental, philosophical, physical and mathematical concept originating from the totality by means of physical and mathematical transcendentalism (the counterpart of philosophical transcendentalism). Classical and quantum information, particularly by their units, bit and qubit, correspond and unify the finite and infinite. As classical information is relevant to finite series and sets, as quantum information, to infinite ones. A fundamental joint relativity of the finite and infinite, of the external and internal is to be investigated. The corresponding invariance is able to define physical action and its quantity only on the basis of information and especially: on the relativity of classical and quantum information. The concept of transcendental time, an epoché in relation to the direction of time arrow can be defined. Its correlate is that information invariant to the finite and infinite, therefore unifying both classical and quantum information.

Delayed Gastric Conduit Emptying (DGCE) occurs in 15-39% of patients who underwent esophagectomy. Intra-Pyloric Injection of Botulinum Toxin (IPBT), Pneumatic Balloon Dilation (PBD), and the same session combination (BTPD), represent the main endoscopic procedures, but comparative data are currently unavailable. We retrospectively analyzed prospectively collected data on all consecutive patients with DGCE treated endoscopically with IPBT, PBD, or BTPD. ISDE Diagnostic Criteria were used for DGCE diagnosis and classification. Gastric Outlet Obstruction Score was used for clinical staging. All patients undergoing IPBT received 100 UI of toxin, while those undergoing PBD were dilated up to 20mm. Clinical success (CS) was defined as the resolution of symptoms/resumption of feeding at discharge or expanding dietary intake at any rate. Recurrence was defined as symptom relapse after more than 15 days of well-being requiring endoscopic/surgical intervention. 64 patients (81.2% male, 90.6% Ivor-Lewis esophagectomy, 77.4% adenocarcinoma), median age 62 years (IQR 55-70), were enrolled: 18 (28.1%) in the IPBT group, 24 (37.5%) in the PBD group and 22 (34.4%) in the BTPD group. No statistically significant differences were found in the baseline characteristics, surgical techniques, and median follow-up among the three groups. BTPD showed a higher CS rate (100%) compared to the PD and BTPD groups (p=0.02) and Kaplan-Meier analysis with log-rank test revealed that the BTPD group was associated both with a significatively shorter mean time to refeed of 1.16 days (95% CI 0.8-1.5; p=0.001) and a shorter median time to discharge of 1 day (95% CI 1-3; p=0.0001). Endoscopic management of DGCE remains challenging. Waiting for further strong evidence, BTPD can offer patients a higher clinical efficacy rate and a shorter time to refeed and be discharged.

Treating clubfoot in walking age children is debated, despite studies showing that using Ponseti casting principles can correct the mid-foot effectively. We aimed to explore techniques and approaches for management of older children with clubfoot and identify areas of management consensus. A mixed-methods cross-sectional electronic survey on delayed presenting clubfoot (DPC) was sent to 88 clubfoot practitioners (response rate 56.8%). We collected data on decision-making, casting, imaging, orthotics, surgery, re-currence, rehabilitation, multidisciplinary care and contextual factors. The quantitative data were analysed using descriptive statistics and the qualitative data were analysed using conventional content analysis. Many respondents used the Pirani score and some used the PAVER score to aid deformity severity assessment and correctability [1,2]. Ponseti casting principles were consistently applied with a stepwise approach. Con-textual factors influenced the timing of the treatment, the decision to treat a bilateral deformity simultaneously, and casting intervals. Differences were seen around orthotic usage and use of tibialis anterior tendon transfer following full correction. The survey identified consensus areas in overall principles of management for delayed presenting clubfoot and implementation of Ponseti principles, indicating these principles are well recognized as a multidisciplinary approach for older children with clubfoot. Some dif-ferences in approach may reflect different economic or social contexts. The principles can be adapted well for different geographical and healthcare contexts.

The phenomenon of quantum erasure exposed a remarkable ambiguity in the interpretation of quantum entanglement. On the one hand, the data is compatible with the possibility of arrow-of-time violations. On the other hand, it is also possible that temporal non-locality is an artifact of post-selection. Twenty years later, this problem can be solved with a quantum monogamy experiment, in which four entangled quanta are measured at the same time. If Bell violations can be recovered from a “monogamous” quantum system, then the arrow of time is obeyed at the quantum level.

The next-generation communication systems demand integration of sensing, communication, and power transfer (PT) capabilities, requiring high spectral efficiency, energy efficiency, and low cost, while also necessitating robustness in high-speed scenarios. Integrated sensing and communication systems (ISACS) exhibit the ability to simultaneously perform communication and sensing tasks using a single RF signal, while simultaneous wireless information and power transfer (SWIPT) systems can handle simultaneous information and energy transmission, and orthogonal time frequency space (OTFS) signals are adept at handling high Doppler scenarios. Combining the advantages of these three technologies, a novel cyclic prefix (CP) OTFS based integrated simultaneous wireless sensing, communication, and power transfer system (ISWSCPTS) framework is proposed in this work. Within the ISWSCPTS, the CP-OTFS matched filter (MF) based target detection and parameters estimation (MF-TDaPE) algorithm is proposed to endow the system with sensing capabilities. To enhance the system’s sensing capability, a waveform design algorithm based on CP-OTFS ambiguity function shaping (AFS) is proposed, which is solved by iteratively method. Furthermore, to maximize the system’s sensing performance under communication and PT Quality of Service (QoS) constraints, a semidefinite relaxation (SDR) beamforming design (SDR-BD) algorithm is proposed, solved using through SDR technique. Simulation results demonstrate that the ISWSCPTS exhibits stronger parameter estimation performance in high-speed scenarios compared to orthogonal frequency division multiplexing (OFDM), waveform designed by CP-OTFS AFS demonstrates superior interference resilience, and beamforming designed by SDR-BD strikes a balance in the overall performance of the ISWSCPTS.

Delayed discharge for non-clinical reasons is defined as a period of stay that continues after a patient has been deemed medically fit to leave the hospital but is unable to do so for non-medical reasons. This circumstance overburdens the healthcare system and constitutes a major problem for healthcare systems and the patients themselves in this situation.The aim of this study was to evaluate the delay in effective discharge for non-medical reasons in patients admitted to acute care hospitals in Spain. A scoping review was conducted in order to revise and obtain an up-to-date review. The initial search strategy identified a total of 123 references, which were successively screened to a final selection of 13 studies. To conclude, delayed discharge from hospital for non-clinical reasons is a multifactorial problem. It may be due to factors internal or external to the hospital, as well as personal factors. The main causes of the delay are similar among the studies found, as are the clinical characteristics of the patients, most of whom are elderly, frail, and more dependent due to declining functional capacities. Further studies addressing the socio-familial characteristics of the patients and the perspective of the patient and families would be necessary.

Injured peripheral nerves regenerate their axons in contrast to those in the central nervous system. However, functional recovery after surgical repair is often disappointing. The basis for the poor recovery is the progressive deterioration with time and distance, of the growth capacity of the neurons that lose their contact with targets (chronic axotomy) and the growth support of the chronically denervated Schwann cells (SC) in the distal nerve stumps. This is despite the retained capacity of chronically denervated and atrophic muscle to accept reinnervation. Progressive decline in regeneration associated genes in both axotomized neurons and denervated SCs accounts for the decline in regenerative success in association with silencing of neural activity in sensory neurons due to their disconnection from their sense organs and, in motoneurons due to loss of their synaptic contacts in the spinal cord. Whilst exogenous neurotrophic factors promote nerve regeneration, the profuse axonal outgrowth and difficulties in delivery are avoided by promoting their endogenous expression with brief (1 hour) low frequency (20Hz) electrical stimulation (ES) proximal to the injury site. ES accelerates axon outgrowth and in turn, target reinnervation in both animals and human subjects. Applying ES to intact nerve days prior to nerve injury, conditional ES (CES) increases axonal outgrowth and regeneration rate with the potential for application in nerve transfer surgeries and end-to-side neurorrhaphies. However, the additional surgery for applying CES electrodes may be a hurdle. ES is applicable in all surgeries with excellent outcomes.

The present study examined mechanisms underlying memory deficits in patients with Parkinson disease (PD)and their associations with structural metrics. Nineteen PD and 22 matched controls underwent two memory experiments. In experiment 1 (delayed memory task), subjects were asked to remember an array of colored rectangles with varying memory set sizes [Low-Load (2 items), Low-Load with Distractor, &amp; High-Load (5 items)]. After a 7s delay period, they reported whether the orientation of any relevant figures had changed (test period). In experiment 2 (working memory task), memory arrays were presented in varying set sizes (2 to 6 items) with no distractors that were followed by a 2s delay period and subsequent test period. Brain MRI data were acquired to assess structural differences (volumes and cortical thickness) in brain areas related to attention, working memory storage, and episodic memory. Compared to controls, PD patients had lower memory capacity scores in all memory load conditions for experiment 1 (p &lt;0.021) whereas there were no group differences in any memory load conditions for experiment 2 (p&gt;0.06). In addition, PD patients had lower thickness in the left superior temporal gyrus (p=0.02). Lower thickness values in the left superior temporal gyrus were significant predictors of lower delayed memory performance in Low-Load and Low-Load with Distractor conditions (ps’&lt;0.044) and working memory performance of memory load conditions of 4 and 5 items (p’s&lt;0.012). The present findings suggest that PD patients may have intact working memory storage capacity but impaired attentional filtering and memory consolidation that may lead to lower delayed memory scores. Lower delayed memory in PD may partly be associated with lower cortical thickness in the left superior temporal gyrus.

In a recent paper [1], I argued against backward in time effects used by several authors to explain delayed choice experiments. I gave an explanation showing that there is no physical influence propagating from the present to the past and modifying the state of the system at a time previous to the measurement. However, though the solution is straightforward in the case of delayed choice experiments involving only one particle, it is subtler in the case of experiments involving two entangled particles because they give rise to EPR-like situations. Considering that a measurement is not an actual change of the physical state of a system and is relative to the observer allows to understand that there is neither backward in time effects nor instantaneous collapse of the second system when the first one is measured, as is often postulated. This allows also to get rid of any non-locality [2]. In this paper, I want to go further into the consequences of this way of considering the measurement, that I have called Convivial Solipsism, and show that even if, in the usual sense, there is no physical effect of the present or of the future on the past, we must nevertheless consider that the observer’s past is sometimes not entirely determined and that it becomes determined only when certain measurements are done latter. This apparent contradiction disappears if one understand that each observer builds, through her own measurements, her own world (that I call the phenomenal world in Convivial Solipsism) which is different from what we are used to consider as the common world shared by everybody.

Splenic rupture and hematoma are significant complications that can arise in patients with non-Hodgkin lymphoma (NHL). Understanding these associations is essential for optimal patient management and patients' enhancing outcomes. Histopathological and immunohistochemistry analyses are crucial in diagnosing NHL and assessing splenic involvement. A judicial autopsy was requested by the Prosecutor's Office for a malpractice claim due to a fall in the hospital. In the Emergency Department, a 72-year-old man fell from the gurney, reporting a wound to his forehead. No other symptoms were reported. A face and brain CT scan showed no abnormalities. Nine days after discharge, the patient presented with abdominal pain. Abdominal CT revealed splenic rupture and hemoperitoneum. The patient underwent open splenectomy, but the patient showed signs of hemodynamic shock and subsequently died. The evidence emerging from the autopsy allowed us to diagnose a Mantle Cell non-Hodgkin lymphoma with spleen involvement, previously unknown. Histopathological and immunohistochemical analyses were performed to assess splenic rupture's diagnosis and time estimation. The findings strongly suggest that the splenic rupture was associated with the patient's fall and the pre-existing malignancy. This case highlights the importance of considering underlying hematological malignancies when investigating delayed splenic rupture. Immunohistochemical study of spleen samples allowed the assessment of the timing of splenic hematoma and rupture, leading to establishing a causal relationship with trauma.

Gold-centered carbene-metal-amides (CMAs) containing cyclic (alkyl)(amino)carbenes (CAACs) are promising emitters for thermally activated delayed fluorescence (TADF). Aiming at design and optimization of new TADF emitters, we report a density functional theory study of over 60 CMAs with various CAAC ligands, systematically evaluating computed parameters in relation to photoluminescence properties. We demonstrate that the efficiency of TADF of CMAs, arising from a compromise of exchange energy and oscillator strength, is governed by the overlap of HOMO and LUMO orbitals, where HOMO is localized on amide and LUMO on Au-carbene. The S0 ground states and excited T1 states of the CMAs adopt approximately coplanar geometries of carbenes and amides, but rotate perpendicular in the excited S1 states, resulting in degeneracy or near-degeneracy of S1 and T1, accompanied with lowering of the S1-S0 oscillator strength from its maximum at coplanar geometries to near zero at rotated geometries. Based on computations, promising new TADF emitters are proposed and synthesized. Bright CMA complex (Et2CAAC)Au(carbazolide) is obtained and fully characterized to demonstrate that high radiative rates up to 106 s-1 can be obtained for the gold-CMA complexes with small CAAC-carbene ligands.

The time series of daily new cases of Covid-19 infection in different zones of Italy, several European countries and New York City were analyzed in order to characterize the large fluctuations contained in them. The comparison shows that the time series share a similar evolution, although with delays of one or two weeks, with Italy that precedes the other countries. Correlation analysis indicates a strict resemblance between the time series of the first differences, which emphasize accelerations and slowdowns of the epidemic (e.g., correlation coefficient r=0.70 for Italian vs. worldwide data). According to Fourier analysis the signals have a dominant oscillatory component at a period of seven days, with minima located near the weekends. Some of the possible causes of this time modulation are discussed. In particular, it is hypothesized a delayed or missed recognition of a significant fraction of the new cases during the weekend, with possible consequences for the evolution of the epidemic.

This article is a tribute to Lewis Wolpert on the occasion of the recent 50th anniversary of the publication of his article ‘Positional Information and the Spatial Pattern of Differentiation’. This tribute relates to another of his ideas: his early ‘Progress Zone’ timing model for limb development. Recent evidence is reviewed that a mechanism sharing features with this model patterns the main body axis in early vertebrate development. This tribute celebrates the golden era of Developmental Biology.

Whether the universe is a computer simulation, or whether we wish to efficiently model our universe in a computer simulation, there would be benefits to modeling it in a fashion analogous to computer spreadsheet, each lattice cell can be conceived as containing all the mathematical formula necessary to continuously compute its state relative to changes in all its neighboring cells, and by progression, in relation to all the cells of entire space-time lattice. Alternatively, the “real” universe may itself be built on a space cell lattice, an irregular foam of space cells, in which each cell may be conceived as a multidimensional cell of distortable space, the shape of which fully describes (a) the four basic forces (gravity, electromagnetic, strong, weak) observed at that cell of space, and (b) the probability (or weight distribution) of any quantum states overlapping the cell and its neighbors. At an appropriate scale, it would appear that this conceptual model would resolve apparent conflicts between general relativity and quantum physics. It would also provide a new interpretation of Planck’s constant as description of the number of space cell events associated with any set of observable events. If formulae operating at a lattice cell level can be improve our ability to understand and model larger scale phenomena, this would be strong evidence in favor of the theory that mathematics is not just a human invention but rather an inherent feature of space-time itself.

Addressing the significant challenge in high-speed cotton dibbling operations in Xinjiang—specifically, the duck bill’s ("Duck bill" is a type of duck-billed bunch planting mechanism or component). shortened opening duration leading to seed throwing and floating—a new crawler-type delayed hole-forming mechanism has been designed. This mechanism extends the duck bill horizontally, thereby prolonging its opening time, enabling cotton sowing speeds of up to 6 km/h. Following agronomic principles for cotton planting, the overall layout of the crawler-type hole-forming mechanism, the structural parameters of the key components and the trajectory of the hole-forming are determined. We use the Discrete Element Method (DEM) and multi-body dynamics coupling method to simulate and analyze the motion process of the device. The fixed the tilt angle of the duck bill α(A), the depth of the duck bill hole-forming into the soil h(B), and the angle of rotation of the moving duck bill β(C) were taken as the experimental factors, with the longitudinal length of cotton seed hole (Y1) and the hole-forming depth of cotton seed hole (Y2) as the response values. The parameter range of each factor and the preliminary influence on the response value were determined through pre-experiments and single-factor simulation test. Based on RecurDyn-EDEM coupling, a quadratic regression orthogonal rotation combination simulation test was carried out. The results show that the order of the primary and secondary factors affecting the Y1 of the time-lapse hole-forming device was: A > C > B. The order of primary and secondary factors affecting the Y2 of the delayed hole forming device was: B > C > A. When the A was 2.4 °, the B was 42.4 mm, and the C was 30.5 °, the performance of the hole-forming was the best, and the Y1 was 26.4 mm, and the Y2 was 25.0 mm. The bench verification test results show that under the optimized combination of operating parameters, the average Y1 was 29.1 mm, and the average Y2 was 23.2 mm. Compared with the results of the previous coupled simulation model, the average relative errors of the two are 7.23 % and 4.36 %, respectively, indicating the accuracy and effectiveness of the established DEM simulation model and virtual test analysis. The hole-forming area and the opening time of the duck bill after the stable operation of the machine were recorded and measured. The calculated hole dislocation rate Hc was 4.33 %, which did not exceed the national standard requirement of 6 %. The qualified rate of hole distance Hx was 94.33 %, which was much higher than the national standard requirement of 80 %. The average opening time of the duck bill at a speed of 6 km/h is 0.45 s, which is much longer than the time required for cotton seeds to fall from the duck bill 0.11 s. It meets the requirements of high-speed cotton planting in China and facilitating advancements in future high-speed planter technology.

Particles and photons appear to be total opposites; the former has rest mass which requires space to exist; the latter has kinetic energy which requires time to occur (oscillate). But they do share certain properties (e.g., quantization) that remain invariant when one is transformed (swapped) for the other. This gauge invariance is developed in some detail.The symmetry between particle and photon turns out to be one of inversion. It is the equalities of special relativity that support this inversion and the accompanying invariances: mass transformed to energy; space transformed to time. The great advantage of these symmetries (inversions) is that they provide guidance for an object little understood (the photon) based upon an object well understood (the particle). On this basis, progress can be made in the understanding of some long-standing issues: wave-particle duality, time’s arrow, the constant speed of light and nonlocality.

This study proposed to use wearable EEG to study the impact of vipassana mindfulness practice on beginner's physiological and neurological responses. Mindfulness meditation has been shown to have numerous benefits, including stress reduction, improved attention and cognitive function, and enhanced emotional regulation. The roots of mindfulness meditation in Buddhism emphasize cultivating present-moment awareness and insight. However, the neural mechanisms together with physiological mechanism and their interaction underlying these benefits remain poorly understood. Method: One middle age man (50 years old) participated in this longitudinal study using wearable EEG to investigate the neurophysiological change during a one-month consecutive vipassana mindfulness practice. Both EEG and heart rate responses were recorded each time, before (5 minutes), during (20 minutes), and after (5 minutes) meditation sessions. The EEG and HR data were analyzed by Matlab and EEGlab to examine changes in brainwave activity and heart rate. Results: alpha peak frequency (APF) is significantly lower after mindfulness meditation, as shown by comparison of APF before mindfulness (pre-5) and during mindfulness practice (med-20), and comparison between APF of pre-5 and after mindfulness practice (post-5). The same is with the beta peak power. While for theta peak frequency, it is significant lower during mindfulness meditation (med-20), when comparing to either pre-5 or post-5. See figure 1a. However, peak power index is not so sensitive, and it is more obvious in theta wave band. That is, the theta power peak is significantly lower after meditation, as can be observed in comparison between pre-5 and med-20, also between pre-5 and med-20. See figure 1b. STATE Heart-mean (bpm) Heart-std(bmp) pre-5 69.88 3.88 med-20 68.36 2.81 post-5 69.55 4.13 t-value test (pre-med) 0.0694 0.0003 t-value test (pre-post) 0.7934 0.3656 t-value test (post-med) 0.3193 0.0001 Table 1. The difference of Heart rate (mean and SD) in before (pre-5), during (med-20) and after (post-5)mindfulness meditation. We find significant change in standard deviation (SD) of heart rate between meditation and non-meditation mental states, as shown in table 1. The study provides insights into the underlying neurophysiological mechanisms of mindfulness meditation using wearable EEG devices. It demonstrates that in term of EEG measurement, spectrum frequency can be more sensitive than spectrum power; also heart rate variability as measured by SD is more sensitive to mean of HR. The proposed study contributes to the literature by using wearable EEG devices to collect data in a more accessible and convenient manner.

In our recent works we reported that physical and chemical characteristics of serum can vary in relation to the psychic activity of an individual depending on whether it is oriented to stress or relaxation. We wandered if these observations could be accompanied by an appreciable modification of the Ph, electric conductivity and Delayed Luminescence of the same serum samples. Our preliminary data may suggest that the serum pH could significantly increase during a Relaxation Response intervention while electric conductivity seems to decrease. Moreover, Delayed Luminescense could vary in the same subject according to the Relaxation Response practice. According to our proof of concept study, we postulate the appearance of a coherent system within the blood samples analyzed after the Relaxation Response. Further researches and some technical development are needed to support our preliminary findings.

Einstein’s publication of the Special Theory of Relativity in 1905 gave birth to the space-time model as a fundamental arena of the universe. Time has become 4th dimension of space and theoretically one could move backward and forward in time. Hypothetical time travel has been a hot topic of scientific discussion since Kurt Gödel published his article about closed time-like curves (CTC) in 1949. He was aware that his CTC model confirms that there is no physical time. Physicists understood his model as a theoretical frame for time travel. Recent research confirmed that universal space is time-invariant. Motion happens only in space and time is the duration of motion. Nobody can travel in time because time has no physical existence. Time as duration is an emergent physical quantity entering existence in the process of measurement of the duration of material change with clocks. The universal space is utterly timeless. There is no physical time in the universe.

Primary care pediatricians encounter a wide range of complex conditions in their daily clinical practice. It is not uncommon for their patients to get exposed to medical errors. Diagnostic errors, defined as missed, delayed, or wrong diagnosis, are of great importance as they may cause significant harm to the pediatric patient with severe disease. These errors often occur when the symptoms and signs of a disease are atypical or missing. Data on the most frequent misdiagnosed situations in pediatrics is scarce. One of these groups of conditions is that regarding cardiac diseases. The pediatric cardiology field has met rapid development over the past few decades. Primary care providers play a key role in diagnosis, management, and referral of children with heart disease, both congenital and acquired, because many common cardiac complaints are first addressed in the primary care setting. The scope of this review is to investigate the cardiac entities that are often missed by the general pediatricians. In particular, it aims to spot the most common of them, to describe their clinical presentation, their diagnostic options, red flags, and tips, and to provide the ways to avoid erroneous, delayed, or missed diagnosis.

The ubiquitous connectivity for the space-air-ground integrated network (SAGIN) of the beyond fifth generation of communication and sixth generation of communication (B5G/6G) is envisaged to meet the needs for the demanded quality of service (QoS), green communication, and "dual carbon" target. However, the offloading and computation of massive latency-sensitive tasks dramatically increases the energy consumption of the network. Furthermore, the traditional power supply technology of the network base stations (BSs) enhances the carbon emission. To address these issues, we first propose a SAGIN architecture with energy harvesting devices, where the BS is powered by both renewable energy (RE) and the conventional grid. The BS explores wireless power transfer (WPT) technology to power the unmanned aerial vehicle (UAV) for stable network operation. RE sharing between neighbouring BSs is designed to fully utilize RE for reduce carbon emission. Secondly, on the basis of task offloading decision, UAV trajectory, and RE sharing ratio, we construct cost functions with joint latency-oriented, energy consumption, and carbon emission. Then, we develop a twin delayed deep deterministic policy gradient (TD3PG) algorithm based on deep reinforcement learning to minimize the cost function. Finally, simulation results demonstrate that the proposed algorithm outperforms the benchmark algorithm in terms of reducing latency, energy saving, and lower carbon emission.

.In his groundbreaking 1905 paper on special relativity, Einstein distinguished between local and global time in inertial systems, introducing his famous definition of distant simultaneity to give physical content to the notion of global time. Over the following decade, Einstein attempted to generalize this analysis of relativistic time to include accelerated frames of reference, which, according to the principle of equivalence, should also account for time in the presence of gravity. Characteristically, Einstein's methodology during this period focused on simple, intuitively accessible physical situations, exhibiting a high degree of symmetry. However, in the final general theory of relativity, the a priori existence of such global symmetries cannot be assumed. Despite this, Einstein repeated some of his early reasoning patterns even in his 1916 review paper on general relativity and in later writings. Modern commentators have criticized these arguments as confused, invalid, and inconsistent. Here, we defend Einstein in the specific context of his use of global time and his derivations of the gravitational redshift formula. We argue that a detailed examination of Einstein's early work clarifies his later reasoning and demonstrates its consistency and validity.

Research has shown that emotional states may influence the subjective experience of time. The present study involved 111 healthy adult participants and examined the impact of emotional stimuli on time perception, using a time estimation task with four conditions: in one of the conditions, participants estimated the exposure time of a black screen, wherein the duration could vary be-tween 2 to 7 s (condition without emotional interference); in the other conditions, participants es-timated the exposure time (also ranging from 2 to 7 s) of images that would induce pleasant, un-pleasant, or neutral emotions, to which participants were instructed to focus their attention (pleasant, unpleasant, or neutral emotions). The results showed that participants estimated “shorter” time intervals (underestimation) for pleasant and unpleasant images compared to the condition without interference, but no significant differences were found between the neutral condition and the condition without interference. It is suggested that increased attention to an ex-ternal stimuli, regardless of its emotional valence, produces an underestimated perception of time.

We consider the problem of scheduling $n$ jobs with identical processing times and given release as well as delivery times on $m$ uniform machines. The goal is to minimize the makespan, i.e., the maximum full completion time of any job. This problem is well-known to have an open complexity status even if the number of jobs is fixed. We present a polynomial-time algorithm for the problem which is based on the earlier introduced algorithmic framework blesscmore (``branch less and cut more''). We extend the analysis of the so-called behavior alternatives developed earlier for the version of the problem with identical parallel machines and show how the earlier used technique for identical machines can be extended to the uniform machine environment if a special condition on the job parameters is imposed. The time complexity of the proposed algorithm is $O(\gamma m^2 n\log n)$, where $\gamma$ can be either $n$ or the maximum job delivery time $q_{\max}$. This complexity can even be reduced further by using a smaller number $\kappa<n$ in the estimation describing the number of jobs of particular types. However, this number $\kappa$ becomes only known when the algorithm has terminated.

This paper is aimed at studying the temporal evolution of the surface displacements occurred over the past few years in the ocean-reclaimed platforms of the Shanghai megacity (China), which are mainly ascribable to consolidation processes of large dredger fills and alluvial deposits. With respect to previous analyses carried out over the same area, this work provides a joint multi-platform differential interferometry synthetic aperture radar (DInSAR) analysis, based on the application of the advanced Small BAseline Subset (SBAS) algorithm. This led us to retrieve long-term deformation time-series that are helpful for a better understanding of the on-going deformation phenomena. To this aim, we have exploited two sequences of SAR data collected by the ASAR/ENVISAT and by the COSMO-SkyMed (CSK) sensors, respectively, spanning the whole time period from 2007 to 2016. Unfortunately, the large time gap (of about three years) existing between the available ASAR/ENVISAT and CSK datasets gave rise to additional difficulties for their combination. Nevertheless, this problem has been faced by benefiting from the knowledge of a time-dependent model describing the temporal evolution of the expected deformations affecting the Shanghai ocean-reclaimed platforms.

In Einstein’s Special Relativity(SR), time is treated as one of the four dimensions within spacetime and is relative in nature. Typically, a photon clock serves as the illustrative device in the time dilation thought experiment, featuring a single photon bouncing between two mirrors. However, the present paper identifies a fundamental flaw in this thought experiment, hence challenging its validity. Contrary to SR, this paper asserts that time is a consequence of motion. Space and time should be treated differently as proposed by classical mechanics. Importantly, this stance does not challenge the concept of curved space in General Relativity (GR), but rather questions the idea of relative time, as employed in both SR and GR. The absence of time dilation also dispels the twin paradox, prompting a necessary reassessment of the second postulate of relativity to ensure a more precise depiction of relativistic effects.

The effects of simulated acid rain (SAR) on the photosynthetic performance of subtropical coniferous species have not been thoroughly investigated. In this study, we treated two coniferous species, Pinus massoniana (PM) and Cunninghamia lanceolata (CL), with SAR and then analyzed photosynthetic activities via the simultaneous measurement of prompt fluorescence(PF), delayed fluorescence(DF), and modulated reflection at 820 nm(MR820). Following the low-pH SAR treatment, the I–P phase of the OJIP curves of PM and CL decreased significantly and then the K-band and L-band were detectable. The delayed fluorescence for both PM and CL decreased as the pH of the SAR solution decreased, with a more significant decrease in the I1 peak than in the I2 peak. According to the MR820 curve, the exposure to SAR stress inhibited the rapid decrease and slow increase in the MR820 transients of PM and CL. The gradients of the decreasing and increasing phases were lower for CL than for PM at pH 2.5. In addition, SAR decreased the light energy captured per unit area (ABS/CSm) and the quantum yield of electron transfer per unit area (ETO/CSm), but it increased the accumulation of QA−, thereby decreasing primary photochemical efficiency (TRO/CSm, φPO). These changes in photosystem II (PSII) resulted in a decrease in the maximum quantum yield of PSII (Fv/Fm) and the performance index (PIABS). Moreover, PSII was protected from thylakoid membrane photodamages through the increase in heat dissipation per unit area (DIO/CSm) in response to SAR. The increase in δRO as the pH of the SAR solution decreased was observed for PM, but not for CL. Considered together, the study findings suggest that SAR treatments can decrease chlorophyll contents and damage the OEC in PM and CL, which obstructs the transfer of electrons on the donor and acceptor sides of PSII. However, PM is better able to withstand SAR stress than CL, likely because of the activation of a protective mechanism (reflected by the change in δRO). Therefore, in coniferous forest areas severely affected by acid rain, CL may need to be protected more than PM.

In this paper, we obtain the existence and uniqueness theorem for solutions of Caputo type fractional stochastic delay differential systems (FSDDSs) with Poisson jumps by utilizing delayed perturbation of Mittag-Leffler function. Moreover, by using Burkholder-Davis-Gundy's inequality, Doob's martingale inequality and Holder inequality, we prove that the solution of the averaged FSDDSs converges to that of the standard FSDDSs in the sense of Lp. Some known results in the literature are extended.

This service improvement project was carried out at LEKMA Hospital, Ghana. Ghana has high levels of antimicrobial resistance (AMR). There is an urgent need to introduce models of care that optimize antibiotic prescribing. Methods Delayed / back-up prescribing is a strategy that could reduce antibiotic use in suspected upper respiratory tract infections. Four different models of delayed / back-up prescribing [no prescription; post-dated prescription (given to patient); post-dated prescription (forwarded to pharmacy); and follow-up appointment for reassessment after 3 days] were implemented in discussion between clinician and patient. Patients were contacted 10 days after their appointment to record compliance, check on their wellbeing, and rate their experience. Results Over a 3-month period (12/2019-02/2020), 142 patients were eligible for delayed / back-up prescribing. The most common clinical diagnoses were sore throat (102/140, 73%), common cold (22/140, 16%) and sinusitis (10/140, 7%). In total, 12 (9%) patients remained symptomatic at day 10, and only one individual in the entire cohort took antibiotics. Most patients (95%) rated their experience as good or very good. Conclusions Delayed / back-up prescribing models can lead to substantial reduction in antibiotic consumption amongst outpatient department patients with suspected upper respiratory tract infections. Delayed / back-up prescribing can be implemented safely in low and middle-income countries.

Time, traditionally viewed as a linear, non-dynamic parameter, is re-envisioned in this study as a Hyperdimensional concept. This paper conducts a cross-disciplinary examination, critically analysing the conceptualization of time in classical mechanics, quantum mechanics, and cosmology to propose a ground breaking reconceptualisation that extends beyond conventional frameworks. In classical mechanics, time is perceived as an absolute, continuously progressing backdrop, largely independent of events. Quantum mechanics treats time as a static parameter that does not influence quantum states but provides a framework for their evolution. In cosmology, time is considered a dimension that emerges from the Big Bang and serves as a measure for the universe's expansion, yet it does not interact with the structural dynamics of the cosmos. Challenging the transformative insights of Einstein’s relativity, which merges time with spatial dimensions under extreme conditions, we advocate for a perspective that views time as a Hyperdimensional and universal constant. This perspective posits that time, despite its unique and intrinsic properties, does not dynamically interact with or alter physical phenomena. Instead, it underpins our understanding of phenomena across different scales—from the minutiae of quantum states to the macroscopic dynamics of cosmology—without direct causation or change. A critical examination of time dilation and relativistic assumptions reveals significant discrepancies in traditional interpretations, particularly in how they are applied across different physical contexts. Our findings challenge the uniform applicability of time dilation, suggesting that observed phenomena often attributed to relativistic effects might better be explained through non-relativistic mechanisms such as phase shifts or changes in wavelength rather than temporal dilation. By synthesizing insights from various scientific domains, we advocate for a unified theory that recognizes time as a fundamental, universal dimension that is conceptual and non-interactive. Our goal is to bridge existing gaps between diverse scientific interpretations and promote a more integrated, profound understanding of time's autonomous and intrinsic nature.

The present investigation focuses on the impact of jet nozzle orientation on mixing time in a cylindrical tank. The aim is to identify nozzle positions that improve mixing performance and to elucidate the governing parameters that influence it. A water tank was employed for the experiment. The vertical inclination angle (α) and the horizontal inclination angle (β) of the jet nozzle determined the nozzle positions. Mixing time was determined using an inert tracer and spectrophotometry measurements. The findings show that the mixing time is significantly influenced by the position of the jet nozzle position. The accuracy of existing jet turbulence and the circulation models for the prediction of mixing time was evaluated for the different nozzle positions. Our results indicate that both models provide accurate predictions for the conventional centrally aligned (β = 0°), upward-pointing jet nozzle positions only (α > 0). For the other nozzle positions where β > 0° and at varying α, the data follow the same trends as the jet turbulence and circulation models, however, the proportionality constants vary. Shorter mixing times can be attributed principally to longer jet path lengths and therefore higher fluid entrainment and circulation, as well as higher dissipation rates per jet length squared. However, it is suspected that the 3-dimensional nature of the flow pattern generated in the tank also plays a non-negligible role since mixing is hindered when the nozzle points more towards the tank wall.

Physicists have employed various approaches to solve the “paradox” and offered a consistent conclusion that the traveller twin is younger than the homebody twin. However, some authors attribute the cause of differential aging to acceleration, while others believe that acceleration should not be regarded as the source of differential aging, but frame switch is. So far there is no agreement on this issue. Actually, acceleration and frame switch should not be regarded as the source of differential aging. The author will introduce a thought experiment in which two very long spacecraft are moving in opposite directions at a speed close to the speed of light to discuss the real cause of differential aging. The author found that the real cause of differential aging in the twin “paradox” is because of the asymmetry of destination choice. People always choose their destinations in the universe rather than in spacecraft. The destinations are always stationary relative to the homebody twin and moving relative to the traveller twin. Once we choose a destination in a reference frame, the distance is the proper length in this reference frame, but the distance will contract in another moving reference frame, thus the recording time will be shorter.

This addendum contains clarifications and a sharpening of some of the results on the VIT transform framework developed in [1]. The focus is on the right-coefficient and left- coefficient forms of the transform, the extraction of a first-order term from a left polynomial fraction, and the application to linear time-varying systems.

We have introduced a sign operator of energy, analogous to the operator helicity, but in the direction of what we call energy vector. However, this energy vector needs a time vector. To give physical senses to the components of such a time vector, we try to explain the time dilation in special relativity and try to relate the components of the time vector to the tunneling times when an electron crosses a potential barrier.

Climate change such as sea level rise, change in temperature, precipitation, and storminess are expected to impact significantly coastal lagoons. The nature and magnitude of these impacts are uncertain. The objective of the research is to determine the climate change impacts on mixing and circulation at Songkhla lagoon, Thailand. Songkhla lagoon is the largest lagoonal water resource in Thailand and Southeast Asia. The lagoon is a combined freshwater and estuarine complex of high productivity which represents an extraordinary combination of environmental resources believed to be unique in the region. This work is part of a Climate Change impact assessment framework. It is the validation phase (step 5) of the framework applying a case study. Delft 3D was used to simulate CC scenarios in the climate downscaling models, part of the previous framework steps. These results were compared to the current conditions to determine the main changes in mixing and circulation in the coastal lagoon. Three indicators were applied to quantify the impacts: flushing time, salinity intrusion and stratification. The results suggest an increase in water velocities at the inlet in future scenarios and a decrease of flushing time. Salinity and stratification showed more complex changes in futures scenarios.

A number of experimental tests of time orientability are described as well as clear experimental signatures from non time orientability (time reversal). Some tests are well known, while others are based on more recent theoretical work. Surprisingly, the results all suggest that time is not orientable at a microscopic level; even definitive tests are positive. At a microscopic level the direction of time can reverse and a consistent forward time direction cannot be defined. That is the conclusion supported by a range of well-known experiments. The conflict between quantum theory and local realism; electrodynamics with electric charges; and spin half transformation properties of fermions; can all be interpreted as evidence of time reversal. While particle-antiparticle annihilation provides a definitive test. It offers both a new view of space-time and an novel interpretation of quantum theory with the potential to unify classical and quantum theories.

Heat stress due to climate warming can significantly affect the synthesis of sex hormones in male adolescents, which can impair the ability of the hypothalamus to secrete gonadotropin-releasing hormone on the hypothalamic-pituitary-gonadal axis, which leads to a decrease in luteinizing hormone and follicle-stimulating hormone, which ultimately negatively affects spermatogenesis and testosterone synthesis. For optimal spermatogenesis, the testicular temperature should be 2–6°C lower than body temperature. Heat stress directly affects the testes, damaging them and re-ducing testosterone synthesis. Additionally, chronic heat stress abnormally increases the level of aromatase in Leydig cells, which increases estradiol synthesis while decreasing testosterone, lead-ing to an imbalance of sex hormones and spermatogenesis failure. Low levels of testosterone in male adolescents lead to delayed puberty and incomplete sexual maturation, negatively affect height growth and bone mineral density, and can lead to a decrease in lean body mass and an in-crease in fat mass. In order for male adolescents to acquire healthy reproductive capacity, it is recommended to provide sufficient nutrition and energy, avoid exposure to heat stress, and pro-vide foods and supplements to prevent or repair testosterone reduction, germ cell damage, and sperm count reduction caused by heat stress so that they can enter a healthy adulthood.

Therapeutic measures aimed at optimising organ function prior to transplantation - whether by conditioning the donor after determination of brain death or by improving organ preservation after kidney removal - have the potential to enhance outcomes after transplantation. The particular advantage is that, unlike any optimised immunosuppressive therapy, a positive effect can be achieved without side effects for the organ recipient. In recent years, several such measures have been tested in controlled clinical trials on large patient cohorts following kidney transplantation. Hypothermic pulsatile machine perfusion in particular has become the focus of interest, but interventions in the donor prior to organ removal, such as the administration of low-dose dopamine until the start of cold perfusion as an example of conditioning antioxidant therapy, and therapeutic donor hypothermia in the intensive care unit after brain death confirmation have also significantly reduced the frequency of dialysis after transplantation with far less effort and cost. With regard to a favourable effect on graft survival in the long-term, the database for all procedures is less clear and controversial. The aim of this review article is to re-evaluate the available clinical evidence on the basis of the large multicentre controlled trials, which have also significantly influenced later meta-analyses, and to assess the significance for use in routine clinical practice.

Can physical objects be in time-symmetry? Physical objects can only exist in a medium that has physical attributes, which means this medium is a type of energy. Is time energy? This article will show that time is not energy and there is no possibility that physical objects could be in time-symmetry. Physical objects only can be in symmetry in the time-invariant space in which they exist. In this perspective time measured with clocks is the result of the observer’s measurement in the time-invariant space. The time-symmetry model is flawed.

This study investigates lost foam shell casting coatings, focusing on the effects of mixing time and standing time on the viscosity and rheological properties of the coatings. The results show that the viscosity of the coating decreases with increasing mixing time and eventually stabilizes. Conversely, the viscosity initially increases and then decreases with prolonged standing time. To ensure optimal coating performance, this study determined that the mixing time should be no less than 50 minutes, and the standing time should not exceed 40 hours.

Capacity Expansion Models (CEMs) are optimization models used for long-term energy planning on national to continental scale. They are typically computationally demanding, thus in need of simplification, where one such simplification is to reduce the temporal representation. This paper investigates how using representative periods to reduce the temporal representation in CEMs distorts results compared to a benchmark model of a full chronological year. The test model is a generic CEM applied to Europe, equipped with a novel formulation for storage in model versions with reduced temporal representation. We test the performance of reduced models at penetration levels of wind and solar of 90%. Three measures for accuracy are used: (i) system cost, (ii) total capacity mix and (iii) regional capacity. We find that: (i) the system cost is well represented (~5% deviation from benchmark) with as few as ten representative days, (ii) the capacity mix is in general fairly well (~20% deviation) represented with 50 or more representative days, and (iii) the regional capacity mix displays large deviations (>50%) from benchmark for as many as 250 representative days. We conclude that modelers should be aware of the error margins when presenting results on these three aspects.

Today, due to recent developments in technology, children devote plenty of time for screen viewing. However, its harmful effects are not yet clear. The purpose of present study was to examine the associations among screen viewing and sleep duration, and body mass index (BMI) in under-five years old children. This cross-sectional study was conducted with 322 under-five healthy children that were selected using multistage stratified cluster sampling method in 2017. The data that were gathered by time-use diary method were analyzed using Kolmogorov-Smirnov test, Spearman correlation tests, multiple linear regression analysis, one-way ANCOVA, two-way ANCOVA. There was a negative correlation between screen time and sleep duration (rs = -0.42, p = 0.00), positive correlation between screen time and BMI (rs = 0.38, p = 0.00) and sleep duration negatively correlated with BMI (rs = -0.22, p = 0.00). screen viewing was a predictive factor for both sleep duration (β = -0.26, p = 0.00) and BMI (β = -0.26, p = 0.00). screen viewing had a significant impact on sleep duration (4, 314) = 5.02, P = 0.001) and BMI (F (4, 314) = 1.16, P=0.298). Results of this study indicated that screen viewing is related to sleep duration and BMI in under-five children. furthermore, screen time has an impact on sleep duration and BMI scores of children. findings of our study suggest that sleep duration negatively is associated with BMI in under-five-year-old children.

Time estimation was investigated in 24 healthy adults, 12 women and 12 men, before and after an exhaustive exercise. We compared the capability of estimating time intervals in the range from 1 to 5 s using tasks requiring mental count and tasks that did not allow the mental count. Time estimation and blood lactate levels were evaluated before and at the end of the exercise. We found that the perception of time intervals between 1 and 5 s was affected at the end of the exercise. The observed effects, associated with a significant increase in blood lactate levels, were different in the two types of time estimation used in the present study. In experimental conditions in which participants had to evaluate duration of the time interval by mental counting, at the end of exercise a significant reduction in the overestimation of time made at rest was observed. On the other hand, when participants had to assess the difference in duration between two events without the possibility to mentally count, at the end of the exercise a significant deterioration in performance was observed. In both cases, no gender differences were seen.

The current work reveals the fine tuning between stability zones and randomness of Pointwise Stationary Fluid Flow Approximation (PSFFA) model of the non-stationary queueing D/M/1 system. More specifically, this clearly provides more insights into developing a contemporary PSFFA theory that unifies non-stationary queueing theory with chaos theory and fields in both theoretical physics and chaotic systems. This opens new grounds for stability analysis of non-stationary queueing systems.

In this paper, the concept of absolute airspace is further elaborated, and the time transform effect, the frequency transform relation of clock timing, and the principle of Doppler effect of special relativistic light are analyzed and demonstrated. Based on the concept of absolute airspace, a new and accurate Doppler effect relation of light (electromagnetic wave) is proposed. It is proved that there is a synchronous relationship between the time shift effect and the frequency change of the timing inside the clock. When the light (electromagnetic wave) source is in motion, the Doppler effect includes two physical mechanisms: the frequency change caused by time transformation effect and the frequency change caused by relative motion. When the light source is in motion, the Doppler effect of the light there are some differences in different directions due to the rotation of the earth. The relation of Doppler effect of special relativistic light is only a highly approximate relation, and its theoretical basis, special relativity, is flawed in principle.

Effects and interactions of incubation time and chick preplacement holding time on mortality at placement, utilization of yolk sac, crop filling rate, early feeding–drinking behavior and broiler live performance were investigated. Ross 308 broiler hatching eggs from a 39-week-old flock were set in two identical setters in a commercial hatchery,with setting time 12 hours earlier in one machine. At the end of incubation, chicks were removed from the hatchers at the same time. Thus, incubation times were either 504 h (normal incubation time (NIT) treatment) or 516 h (longer incubation time (LIT) treatment). After pull time, chicks from each incubation time group were subjected to either 6, 24, 48, 60 or 72 h preplacement holding times. At placement, chicks were given access to feed and water. In total, 19,200 chicks were randomly assigned to a total of 10 subtreatment groups (2 incubation times × 5 preplacement holding times). Therefore, a total of 1,920 chicks were used in each subtreatment group for the grow-out period in a commercial broiler house. An interaction was found between incubation time and preplacement holding time for residual yolk sac (RYS) weight (g, %) (p &lt; 0.001). RYS weight was greater at pull time and at 6 and 24 h of preplacement holding time in the NIT treatment compared to the LIT treatment, while differences were no longer evident at 48–72 h. The lowest percentage of chicks with full crops and eating activity was observed in the shortest preplacement holding time (6 h) group at 3 h after placement. As expected, the initial BW at placement clearly decreased with increasing duration after the pull time (p &lt; 0.05) with the highest and lowest weights were found in the 6 and 72 h holding time treatments respectively. This BW difference was still evident at 35 d after placement and chicks held for the longest period after the pull time (72 h) showed the lowest BW (p &lt; 0.001). However, there was no significant difference between the 6 and 60 h preplacement holding times. Mortality during the first 7 d after placement increased only when the preplacement holding time was extended to 72 h (p = 0.031). Similar to the 7 d results, chicks held for 72 h exhibited higher 0-35 day mortality compared to those held for 6 or 24 h (p = 0.028). Neither BW nor mortality was affected by incubation time treatment at 35 d after placement (p &gt; 0.05). It can be concluded that there were no significant differences in average BW and mortality, up to and including a 60-h holding time under thermal comfort conditions, but a 72-h preplacement holding time resulted in final BW and mortality being negatively affected. In addition, LIT tended to have a beneficial effect on BW and mortality compared to NIT when the preplacement holding time was shorter (6–24 h) but had a negative effect for extended holding times (48–72 h).