Limited availability of expensive alloying elements elevates low-alloyed steels to a unique position in the field of lightweight construction and mass production. Quenching and partitioning (Q&P) heat treatments of low-alloyed steels with exceptional property combinations are particularly promising. In this study, we characterize for the first time a new low-alloyed steel to be processed by Q&P heat treatments. In combined experimental and numerical studies, we design a novel approach that effectively combines the short cycle times of press hardening with the excellent property profiles of Q&P-treated steels. We identify appropriate transformation parameters for Q&P heat treatments by dilatometric studies and we adjust a number of reference conditions with different isothermal holding times. By means of SEM analysis and XRD measurements, we show that different fractions of retained austenite result in different mechanical properties. Initial numerical designs of the process can identify varying temperature profiles and cooling rates depending on the position in the die. The results show that the geometry of the part plays a minor role, but the die temperature is the dominant factor for successful partitioning directly in the press hardening process.

In this study, we introduce a new class of bi-univalent functions using q-Janowski Function. We derive the Fekete-Szegö functional problems for functions in this new subclass, as well as estimates for the Taylor-Maclaurin coefficients |α2| and |α3|. Furthermore, a collection of fresh outcomes are3 presented by customizing the parameters employed in our initial discoveries.

We construct a novel family of summation-integral type hybrid operators in terms of shape parameter $\alpha\in \lbrack 0,1]$ in this paper. Basic estimates, rate of convergence, and order of approximation are also studied using the Korovkin theorem and the modulus of smoothness. We investigate the local approximation findings for these sequences of positive linear operators utilising Peetre's K-functional, Lipschitz class, and second-order modulus of smoothness.

Distributed Energy Resources might have a severe influence on Power Line Communications, as they can generate interfering signals and high frequency emissions or supraharmonics that may cause loss of metering and control data. In this paper, the influence of various energy resources on Narrowband Power Line Communications is described and analyzed through several test measurements performed in a real microgrid. Accordingly, the paper describes the effects on smart metering communications through MAC layer analysis. Results show that the commutation frequency of inverters and the presence of battery chargers are remarkable sources of disturbance in low voltage distribution networks. In this sense, the results presented can contribute to efforts towards standardization and normative of emissions at higher frequencies higher, such as CENELEC EN 50160 and IEC/TS 62749.

The scattering pattern from a narrow absorbing/amplifying grating is investigated. A simple model of a narrow amplifying grating is solved exactly numerically and approximately analytically for the regime where the beam’s wavelength is much shorter than the grating’s wavelength. The main results are: The incident angle divides the scattering pattern into two regimes: below and above the incident angles. The former regime has a weak dependence on the incident angle but has a strong dependence on the scattering one. In this regime, a new grating formula is derived. The opposite occurs in the latter regime, which is very sensitive to the incident angle, but has only weak dependence on the scattering angle. Consequently, at certain incident angles, all the scattering is concentrated in the first regime, i.e., all scattering angles are lower than the incident angle.

Transit-oriented development (TOD), such as metro depot and over-track building complexes, has expanded rapidly in China. Over-track building construction has the advantage of comprehensive utilization of land resources, ease of commuting to work, and provide funds for subway construction. However, there still has a pending problem, disturbance of railway vibration, for TOD. Excessive noise and vibration seriously affect people’s life. To address this challenge, field measurements are used to obtain the vibration source characteristics and vibration propagation of the ground and the superstructure in this study. And the typical metro depot with over-track building in Wuhan was selected. The effects of vibration on the surrounding ground and adjacent buildings caused by the operation of trains have been measured, and the propagation law of train-induced ground vibration acceleration in the time and frequency domains has been analyzed. The distribution and propagation laws of vibration noise, structural noise and secondary structure noise in sensitive areas such as the throat area, depot area, test section and access section of the over-track buildings and their impact laws on the over-track buildings are obtained. And the effectiveness of the vibration and noise reduction methods used were evaluated. Results show that within 43 m from the train running track, the train running induced vertical vibration acceleration level in the high-rise building peak size of 58.8 dB, the average value of 55.62 dB; vibration frequency components are mainly 40-60 Hz. The findings might provide useful insight for designing vibration mitigation systems in new metro depots with over-track buildings.

Epithelial-mesenchymal transition (EMT) plays an important role in the acquisition of cancer stem cell (CSC) feature and drug resistance, which are the main hallmarks of cancer malignancy. Although previous findings have shown that several signaling pathways are activated in cancer progression, the precise mechanism of signaling pathways in EMT and CSCs are not fully understood. In this study, we focused on the intestinal and diffuse-type gastric cancer (GC), and analyzed the gene expression of public RNAseq data to understand the molecular pathway regulation in different subtypes of gastric cancer. Network pathway analysis was performed by Ingenuity Pathway Analysis (IPA). Total 2815 probe set IDs were significantly different between intestinal- and diffuse-type GC data in cBioPortal Cancer Genomics. The 10 genes including male-specific lethal 3 homolog (Drosophila) pseudogene 1 (MSL3P1), CDC28 protein kinase regulatory subunit 1B (CKS1B), DEAD-box helicase 27 (DDX27), golgi to ER traffic protein 4 (GET4), chromosome segregation 1 like (CSE1L), translocase of outer mitochondrial membrane 34 (TOMM34), YTH N6-methyladenosine RNA binding protein 1 (YTHDF1), ribonucleic acid export 1 (RAE1), par-6 family cell polarity regulator beta (PARD6B), and MRG domain binding protein (MRGBP) were found to have difference in gene expression in intestinal- and diffuse-type GC. Total 463 direct relationships with 3 molecules (MYC, NTRK1, UBE2M) were found in the biomarker-filtered network generated by network pathway analysis. The networks and features in intestinal- and diffuse-type GC have been investigated and profiled in bioinformatics. Our results revealed the signaling pathways networks in intestinal- and diffuse-type GC, bringing new light for the elucidation of drug resistance mechanisms in CSCs.

Tourism gentrification presents issues of privatization of public space, the transformation of public services to cater to tourists, the erosion of community social bonds, and the commodification of regional consumption, which has far-reaching impacts on the well-being of local residents and a desire to relocate. Thus, tourism gentrification in traditional industrial areas is defined as a process driven by the reconfiguration of spatial functions and the transformation of service provisions, resulting in displacement. This study employs Q methodology aims to understand the residents’ perceptions of tourism gentrification with a specific focus on the 798 Industrial Art Zone in Beijing, China. The results reveal four dimensions that form residents’ stress: neighboring environment, community attachment, economic interest, and cultural identity. Based on the stress threshold theory, this study further proposes a framework to explain the decision-making processes of residents in relation to their intent to relocate due to stress from interactions with migrants and visitors and changes in the place functions of industrial areas and communities. The findings offer valuable theoretical knowledge surrounding tourism gentrification from residents’ perspectives and suggest practical guidance for policymakers and destination managers in reducing residents’ stress and promoting sustainable development of industrial tourism.

: This paper proposes a reem-shape phononic crystal for the performance enhancement of TPoS resonators. The proposed phononic crystal offers an ultra-wide acoustic band gap that prevents energy leakage through the supporting substrate on its placement at the anchoring boundary, resulting in significant improvements in the resonator quality factor. Simulated results show reem-shape Phononic crystals generate a band gap up to 175MHz with BG of 90% and enhance the anchor quality factor from 180,000 to 6,000,000 and unloaded quality factor from 133,000 to 160,000 representing 33.3-fold and 1.2-fold improvements respectively.

Increased data acquisition by uncalibrated, heterogeneous digital sensor systems such as smartphones present new challenges. Binary metrics are proposed for the quantification of cyber-physical signal characteristics and features, and a standardized constant-Q variation of the Gabor atom is developed for use with wavelet transforms. Two different continuous wavelet transform (CWT) reconstruction formulas are presented and tested under different signal to noise ratio (SNR) conditions. A sparse superposition of Nth order Gabor atoms worked well against a synthetic blast transient using the wavelet entropy and an entropy-like parametrization of the SNR as the CWT coefficient-weighting functions. The proposed methods should be well suited for sparse feature extraction and dictionary-based machine learning across multiple sensor modalities.

In the present paper, the (p,q)-Hermite based Apostol type Frobenius-Euler polynomials and numbers are firstly considered and then diverse basic identities and properties for the mentioned polynomials and numbers, including addition theorems, difference equations, integral representations, derivative properties, recurrence relations. Moreover, we provide summation formulas and relations associated with the Stirling numbers of the second kind.

The evolving multiphase induction generators (MPIG) with more than three phases are receiving prominence in high power generation systems. This paper aims at the development of a comprehensive model of the wind turbine driven seven-phase induction generator (7PIG) along with necessary the power electronic converters and controller for grid interface. The dynamic model of the system is developed in Maltlab/Simulink. Synchronous reference frame phase-locked loop (SRFPLL) system is incorporated for grid synchronization. The modeling aspects are detailed and the system response is observed for various wind velocities. The effectiveness of seven phase induction generator is demonstrated with the fault tolerant capability and high output power with reduced phase current when compared to conventional 3-phase wind generation scheme. The response of the PLL is analyzed and the results are presented.

Machine learning methods have been a standard approach to select features that are associated with an outcome and build a prediction model when the number of candidate features is large. LASSO has been one of the most popular approaches to this end. LASSO approach selects features with large regression estimates, rather than based on statistical significance, associating the outcome, by imposing L1-norm penalty to overcome the high dimensionality of the candidate features. As a result, LASSO may select insignificant features while possibly missing significant ones. Furthermore, from our experience, LASSO has been found to select too many features. By selecting features that are not associated with the outcome, we may have to spend more cost to collect and manage them in the future use of a fitted prediction model. Using the combination of L1- and L2-norm penalties, elastic net (EN) tends to select more features than LASSO. The overly selected features that are not associated with the outcome act like white noise, so that the fitted prediction model loses the prediction accuracy. In this paper, we propose to use the standard regression methods (without any penalizing approach) with stepwise variable selection procedure to overcome these issues. Unlike LASSO and EN, this method selects features based on statistical significance. Through extensive simulations, we show that this maximum likelihood estimation based method selects very small number of features while maintaining a high prediction power, while LASSO and EN make a large number of false selections to result in loss of prediction accuracy. Contrary to LASSO and EN, the regression methods combined with a stepwise variable selection method is a standard statistical method, so that any biostatistician can use it to analyze high dimensional data even without advanced bioinformatics knowledge.

L-asparaginase (ASNase) is an aminohydrolase currently used in the pharmaceutical and food industries. Enzyme immobilization is an exciting option for both applications, allowing a more straightforward recovery and increased stability. High surface area and customizable porosity make carbon xerogels (CXs) promising materials for ASNase immobilization. This work describes the influence of contact time, pH, and ASNase concentration on the immobilization yield (IY) and relative recovered activity (RRA) using Central Composite Design methodology. The most promising results were obtained using CX with an average pore size of 4 nm (CX-4), reaching IY and RRA of 100%. At the optimal conditions, the ASNase-CXs biocomposite was characterized and evaluated in terms of kinetic properties and operational, thermal and pH stabilities. The immobilized ASNase onto CX-4 retained 71% of its original activity after six continuous reaction cycles, showed a good thermal stability at 37 °C (RRA of 91% after 90 min) and was able to adapt to both acidic and alkaline environments. Finally, the results indicated a 3.9-fold increase in the immobilized ASNase affinity for the substrate, confirming the potential of CXs as a support for ASNase and as a cost-effective tool for subsequent use in the therapeutic and food sectors.

In this work, we propose an approach for the autonomous navigation of mobile robots using fusion of sensor data by a Double Deep Q-Network with collision avoidance by detecting moving people via computer vision techniques. We evaluate two data fusion methods for the proposed autonomous navigation approach: Interactive and Late fusion strategy. Both are used to integrate mobile robot sensors through the following sensors: GPS, IMU and, an RGB-D camera. The proposed collision avoidance module is implemented along with the sensor fusion architecture in order to prevent the autonomous mobile robot from colliding with moving people. The simulation results indicate a significant impact on the success of completing the proposed mission by the mobile robot with the fusion of sensors, indicating a performance increase (success rate) of 27% in relation to navigation without sensor fusion. With the addition of moving people in the environment, deploying the people detection and collision avoidance security module has improved about 14% the success rate when compared to that of the autonomous navigation approach without the security module. Video was developed with robot navigation using the DDQN-Late Fusion https://www.loom.com/share/684afa6a5b0148afadc9a200ab9f3483.

. Manufacturers are increasingly adopting mixed-flow manufacturing models to meet the growing customized, diverse, and dynamic customer demand. In such an environment, material distribution scheduling optimization is vital for smooth operations and is integral to production management. However, manufacturers frequently encounter problems like disordered and delayed material distribution. Traditional scheduling methods suffer from problems like inadequate transparency, delayed decision directives, and suboptimal results, impacting performance. To this end, this study proposes a dynamic material distribution scheduling optimization model and strategy based on digital twin (DT) to address these problems. Firstly, we introduce workstation satisfaction and establish a material distribution path optimization model minimizing total distribution cost while maximizing workstation satisfaction. Subsequently, we present a cloud-edge computing-based decision framework and explain the DT-based material distribution system's components and operation. Furthermore, a dynamic material distribution scheduling optimization mechanism based on DT is designed. By incorporating a savings method and incentive, penalty strategies, improvements are made to the path node selection probabilities and the information pheromone update rules of the traditional ant colony optimization (ACO) algorithm. Finally, a numerical case study, using real data from collaborating enterprises, validates the proposed algorithm and strategy. This research offers valuable insights into logistics management and algorithm design in smart manufacturing environments.

Excess consumption of a high-fat diet has been identified as one of the contributing factors for obesity. Women are at higher risk for adult obesity than men, predisposing them to a different set of detrimental disease conditions. Furthermore, aging studies show that physiological decline also has a serious impact on changes in the endocrine properties of white adipose tissue. Howev-er, there is still relatively little known about the factors associated with obesity and aging and their compounding impact on women’s health. To investigate adipocytokine secretion profile changes, female C3H/HeJ mice were induced to obesity through long-term consumption of a high-fat diet. Weight gain measurements and Echo MRI analysis of fat composition showed in-creases were a due solely to the high fat content in the diet. Adipocytokine secretions were ana-lyzed in media conditioned from harvested visceral fat tissue that was organ cultured ex-vivo. Adipocytokine analysis across diets and age showed significant increases in Adiponectin and Leptin secretion in high-fat diets, accelerated increases in Resistin secretion with high-fat diets. Aging induced increased secretion of Lipcalin-2, Pentraxin-3 and Serpin E1, MCP-1 and ICAM-1, regardless of diet. Furthermore, comparisons of organoid cultured protein secretions and flash-frozen tissue samples differed greatly, suggesting the WAT organoid cultures may yield information more reflective of in situ conditions. Taken together, our results show that diet and aging significantly impact secretions from adipose tissue, that may contribute to women’s health issues.

The present analysis deals with the study of the $f(Q, T )$ theory of gravity which was recently considered by many cosmologists. In this theory of gravity, the action is taken as an arbitrary function $f(Q, T )$ where $Q$ is non-metricity and $T$ is the trace of energy-momentum tensor for matter fluid. In this study, we have taken three different forms of the function $f(Q, T )$ as $f(Q,T)=a_1Q+a_2 T$ and $f(Q,T)=a_3 Q^2+a_4 T$ and discussed some physical properties of the same. Also, we have obtained the various cosmological parameters towards Friedmann-Lemaitre-Robertson-walker (FLRW) Universe by defining the transit form of scale factor which yields the Hubble parameter in redshift form as $H(z)=\frac{H_{0}}{(\lambda+1)} \left(\lambda+ (1+z)^{\delta}\right)$. %We have obtained the approx best-fit values of model parameters using the least square method for observational constraints on available datasets like Hubble dataset $H(z)$, Supernova dataset SNe-Ia, etc., by applying the Root Mean Squared Error formula (RMSE). By applying the Root Mean Squared Error formula (RMSE), we were able to determine the approximate best-fit values of model parameters using the least square approach for observational constraints on the datasets Hubble dataset $H(z)$, Supernova dataset SNe-Ia, etc. We have observed that the deceleration parameter $q(z)$ exhibits a signature-flipping (transition) point within the range $0.623 \le z_{0} \le 1.668$ through which it changes its phase from the decelerated to the accelerated expanding universe with $\omega = -1$ at $z=-1$ for the approximate best-fit values of the model parameters. %For obtained approx best-fit values of model parameters we have observed that the deceleration parameter $q(z)$ shows a signature-flipping (transition) point within the range $0.623 \le z_{0} \le 1.668$ through which it changes its phase from decelerated to the accelerated expanding universe with $\omega = -1$ at $z=-1$.

Beyond the usual ferromagnetic and paramagnetic phases present in spin systems, the usual q-state clock model, presents an intermediate vortex state when the number of possible orientations q for the system is equal to 5 or larger. Such vortex states give rise to the Berezinskii-Kosterlitz-Thouless (BKT) phase present up to the XY model in the limit q→∞. Based on information theory, we present here an analysis of the classical order parameters plus new short-range parameters defined here. Thus, we show that even using the first nearest neighbors spin-spin correlations only, it is possible to distinguish the two transitions presented by this system for q greater than or equal to 5. Moreover, the appearance at relatively low temperature and disappearance of the BKT phase at a rather fix higher temperature is univocally determined by the short-range interactions recognized by the information content of classical and new parameters.

Machine learning is an established and frequently used technique in industry and academia but a standard process model to improve success and efficiency of machine learning applications is still missing. Project organizations and machine learning practitioners have a need for guidance throughout the life cycle of a machine learning application to meet business expectations. We therefore propose a process model for the development of machine learning applications, that covers six phases from defining the scope to maintaining the deployed machine learning application. The first phase combines business and data understanding as data availability oftentimes affects the feasibility of the project. The sixth phase covers state-of-the-art approaches for monitoring and maintenance of a machine learning applications, as the risk of model degradation in a changing environment is eminent. With each task of the process, we propose quality assurance methodology that is suitable to address challenges in machine learning development that we identify in form of risks. The methodology is drawn from practical experience and scientific literature and has proven to be general and stable. The process model expands on CRISP-DM, a data mining process model that enjoys strong industry support but lacks to address machine learning specific tasks. Our work proposes an industry and application neutral process model tailored for machine learning applications with focus on technical tasks for quality assurance.

In this paper, inspired by Jleli and Samet [journal of inequalities and applications 38 (2014) 2 1–8] we introduce two new classes of auxiliary functions and utilize the same to define (q, y)R-weak 3 contractions. Utilizing (q, y)R-weak contractions, we prove some fixed point theorems in the setting 4 of relational metric spaces. We employ some examples to substantiate the utility of our newly proved 5 results. Finally, we apply one of our newly proved results to ensure the existence and uniqueness of 6 solution of a Volterra-type integral equation.

The statistics of grain displacements probability distribution function (pdf) during the shear of a granular medium displays an unusual dependence with the shear increment upscaling as recently evinced [Phys. Rev. Lett. 115 238301 2015]. Basically, the pdf of grain displacements has clear nonextensive ($q$-Gaussian) features at small scales but approaches to Gaussian characteristics at large shear window scales -- the granulence effect. Here, we extend this analysis studying a larger system (more grains considered in the experimental setup) which exhibits a severe shear band fault during the macroscopic straining. We calculate the pdf of grain displacements and the dependency of the $q$-statistics with the shear increment. This analysis have shown a singular behavior of $q$ at large scales, displaying a non-monotonic dependence with the shear increment. By means of an independent image analysis, we demonstrate that this singular non-monotonicity could be associated with the emergence of a shear band within the confined system. We show that the exact point where the $q$-value inverts its tendency coincides with the emergence of a giant percolation cluster along the system, caused by the shear band. We believe that this original approach using Statistical Mechanics tools to identify shear bands can be a very useful piece to solve the complex puzzle of the rheology of dense granular systems.

In this paper we introduce the hypo-q-norms on a Cartesian product of inner product spaces. A representation of these norms in terms of inner products, the equivalence with the q-norms on a Cartesian product and some reverse inequalities obtained via the scalar Shisha-Mond, Birnacki et al., Grüss type inequalities, Boas-Bellman and Bombieri type inequalities are also given.

The world has changed. New technologies, new trends, new protocols, new efficient algorithms, and systems have been used widely by civilized countries to have better and more convenient living. In this research, there have been introduced many new terms, technologies, and mechanisms. Moreover, threats, attacks, and vulnerabilities have been studied and a novel scenario has been proposed in order to overcome all these violations that have been presented in this paper. The scenario is based on a security model that has been proposed for critical sectors, such as hospitals, industries, etc., which need efficient solutions to go one step further and improve the secure and efficient living and treatment of people. The aim of this research has been to understand through research the IoT security issues and propose the appropriate solutions based on the most suitable security algorithms. The results, which have been based on the complexity, the throughput, the power consumption, the strength, and the memory usage of the algorithms studied, have been hopeful and helpful for future research and experimentation.

Consciousness results from comprehending the living creature from its existence in time and space. Thought and consciousness are distinguishing factors between humans and machines having artificial intelligence. No algorithm has been offered for artificial self-awareness based on Thinking. Previous studies have not studied the relationship between consciousness, thinking and time. In this study, the relationship between consciousness, thinking, memories and speech over time has been studied. A deep logical connection exists between consciousness, thinking, and time. An algorithm can be designed for artificial consciousness based on this research findings.

The anomaly detection task is very important in computer science. And there are a lot of anomaly detection methods. Different from some thresholding methods, some unsupervised methods could make us get more accurate and faster result, which is the object of the project. In this paper, I tried to use EWMA and some other methods in two datasets: Webank time consuming indicators dataset and AIOps Challenge dataset. The paper consists nine parts: background of the project, related work, description of algorithms, implementation details, experimental setup and data sets used, experimental results and discussion, future directions, reference and meeting notes.

Rainfall variability has resulted in extreme events like devastating floods and droughts which is the main cause of human vulnerability to precipitation in West Africa. Attempts have been made by previous studies to understand rainfall variability over Ghana but these have mostly focused on the major rainy season of April-July, leaving a gap in our understanding of the variability in the September-November season which is a very important aspect of the Ghanaian climate system. The current study seeks to close this knowledge gap by employing statistical tools to quantify variabilities in rainfall amounts, rain days, and extreme precipitation indices in the minor rainfall season over Ghana. We find extremely high variability in rainfall with a Coefficient of variation (CV) between 25.3% and 70.8%, and moderate to high variability in rain days (CV=14.0% - 48.8%). Rainfall amount was found to be higher over the middle sector (262.7 mm – 400.2 mm) but lowest over the east coast (125.2 mm – 181.8 mm). Analysis of the second rainfall season using the Mankandell Test presents a non-significant trend of rainfall amount and extreme indices (R10, R20, R99p, and R99p) for many places in southern Ghana. Rainfall Anomaly Indices show that the middle sector recorded above normal precipitation which is the opposite for areas in the transition zone. The result of this work provides a good understanding of rainfall in the minor rainfall season and may be used for planning purposes.

Reinforcement learning (RL) is an extensively applied control method for the purpose of designing intelligent control systems to achieve high accuracy as well as better performance. In the present article, the PID controller is considered as the main control strategy for brushless DC (BLDC) motor speed control. For better performance, the fuzzy Q-learning (FQL) method as a reinforcement learning approach is proposed to adjust the PID coefficients. A comparison with the adaptive PID (APID) controller is also performed for the superiority of the proposed method, and the findings demonstrate the reduction of the error of the proposed method and elimination of the overshoot for controlling the motor speed. MATLAB/SIMULINK has been used for modeling, simulation, and control design of the BLDC motor.

The proliferation of mobile and IoT devices, coupled with the advances in the wireless communication capabilities of these devices, have urged the need for novel communication paradigms for such heterogeneous hybrid networks. Researchers have proposed opportunistic routing as a means to leverage the potentials offered by such heterogeneous networks. While several proposals for multiple opportunistic routing protocols exist, only a few have explored fuzzy logic to evaluate wireless links status in the network to construct stable and faster paths towards the destinations. We propose FQ-AGO, a novel Fuzzy Logic Q-learning Based Asymmetric Link Aware and Geographic Opportunistic Routing scheme that leverages the presence of long-range transmission links to assign forwarding candidates towards a given destination. The proposed routing scheme utilizes fuzzy logic to evaluate whether a wireless link is useful or not by capturing multiple network metrics, the available bandwidth, link quality, node transmission power, and distance progress. Based on the fuzzy logic evaluation, the proposed routing scheme employs a Q-learning algorithm to select the best candidate set toward the destination. We implement FQ-AGO on the NS-3 simulator and compare the performance of the proposed routing scheme with three other relevant protocols: AODV, DSDV, and GOR. For precise analysis, we consider various network metrics to compare the performance of the routing protocols. Our simulation result validates our analysis and demonstrates remarkable performance improvements in terms of total network throughput, packet delivery ration, and end-to-end delay.

A new discrete distribution for count data called extended biparametric Waring (EBW) distribution is developed. Its name is related to the fact that, in a specific configuration of its parameters, it can be seen as a biparametric version of the univariate generalized Waring (UGW) distribution, a well-known model for the variance decomposition into three components: randomness, liability and proneness. Unlike the UGW distribution, the EBW can model both overdispersed and underdispersed data sets. In fact, the EBW distribution is a particular case of a UWG distribution when its first parameter is positive; otherwise, it is a particular case of a Complex Triparametric Pearson (CTP) distribution. Hence, this new model inherits most of their properties and, moreover, it helps to solve the identification problem in the variance components of the UGW model. We compare the EBW with the UGW by a simulation study, but also with other over and underdispersed distributions through the Kullback-Leibler divergence. Additionally, we have carried out a simulation study in order to analyse the properties of the maximum likelihood parameter estimates. Finally, some application examples are included which show that the proposed model provides similar or even better results than other models, but with fewer parameters.

The protection of electronics against environmental influences and mechanical loads is important for integration of conventional electronics in textile conductive tapes. For this purpose, the sensors on the tapes are molded with plastic locally. This process step is recognized in the injection molding process. The molding compound is then later selected depending on: The field of application, the parameters of the manufacturing process and the textile tape properties. We have designed a mould for liquid silicone (LSR) as well as for the textile and electronic insertions. The cavities are sealed by a local compression of the textile and the two inserts are positioned with position pins representing the main aspect of the mould design. The sampling tool and the process parameter optimization are mainly based on the material properties of the silicone and the mechanical sensitivity of the inserts. To reduce the deformation of the circuit boards by the melt front and ensuring the functionality of the electronics a low-pressure process is used.

This study examines the performance of the Indian Monsoon Data Assimilation and Analy-sis (IMDAA) in predicting five extremely severe cyclonic storms (ESCS) over the Bay of Bengal. The Advanced Research version of the WRF (ARW) model is utilized for this analysis over the last two decades. The initial and lateral boundary conditions are derived from the IMDAA datasets with a horizontal resolution of 0.12° × 0.12°. Five ESCSs from the past two decades are considered: Sidr 2007, Phailin 2013, Hudhud 2014, Fani 2019, and Amphan 2020. The model is integrated up to 96 hours using double nested domains of 12 km and 4 km. Model performance is evaluated using the 4 km results, compared with available observational datasets, including the best-fit data from the India Meteorological Department (IMD), The Tropical Rainfall Measuring Mission (TRMM) satellite, and Doppler Weather Radar (DWR). The results indicate that IMDAA provides accurate forecasts for ESCSs Fani, Hudhud, and Sidr in terms of track, intensity, and mean sea level pressure, aligning well with IMD observational datasets. However, Sidr's track deviates more from the observations. The calculated mean absolute maximum sustained wind speed errors range from 8.4 m/s to 10.6 m/s from day-1 to day-4, while mean track errors range from 114 km to 496 km during the same period. Statistical analysis, including bias, mean error, and standard deviation, underscores the significance of ESCS prediction. The discussion also covers rainfall prediction, maximum reflectivity, and the associated structure of the storms.

To reveal the relationship between metallodrugs and cancer malignancy, molecular networks of anti-cancer drugs were analyzed. Molecular networks in several types of cancers were analyzed in Ingenuity Pathway Analysis (IPA). Analysis of carboplatin revealed the causal network in diffuse large B-cell lymphoma. Analysis of 12 analyses of cisplatin treatment identified causal networks including camptothecin and NUPR1. The causal network of camptothecin, which includes PTEN, FAS, and IRF1, was inactivated in diffuse-type GC and activated in intestinal-type GC. Upstream regulator analysis of cisplatin revealed an increase in FAS, BTG2, SESN1 and CDKN1A, and the involvement of the tumor microenvironment pathway. Upstream regulators of cisplatin-treated lung adenocarcinoma included a histone deacetylase inhibitor, trichostatin A (TSA). Causal network of arsenic was inactivated in diffuse-type GC and activated in intestinal-type GC, and included ERK, EGFR, SRC, IKK and TP53. Prediction of RNA-RNA interactions with the causal network of arsenic identified 10 microRNAs including mir-101, mir-103, and mir-22. The results revealed the involvement of EMT in arsenic treatment. Analysis of oxaliplatin, a platinum drug, revealed that the SPINK1 pancreatic cancer pathway is inactivated in ischemic cardiomyopathy. The study showed the importance of the relationship between platinum drugs or arsenic trioxide and the tumor microenvironment in the treatment of resistant cancer in humans.

The research explores the impact of financial indicators on the credit ratings of companies listed on the S&P 500, employing a Sys-GMM Model to address endogeneity concerns. The study investigated three independent variables categorized as market and survival factors alongside with seven control variables sourced from leverage, liquidity, interest coverage, profitability, market, survival, and macroeconomic domains. The sample comprised 2398 observations from Capital IQ Pro, spanning nine years (2013 to 2021) and encompassing 240 public companies. The findings suggest that neither Tobin's Q (TQ) and Total Shareholder Return (TSR) lack significant correlations with credit ratings, implying that stock market performance and total shareholder return do not directly impact credit ratings. In contrast, the Altman Z-score (AZS) emerged as a significant predictor, indicating its importance in assessing credit risk. These insights enhance understanding of financial indicators' impact on credit ratings, aiding financial institutions and companies in prudent lending and financing decisions.

One third of a person’s life is spent on sleep, therefore the quality and habit of sleep affects health. A single case study indicated that perspiration could serve as a prognostic marker. Diagnosing nocturnal perspiration is common clinical practice, since this serves as a major symptom in many pathologies. Till this day no specific evidence-based approach for diagnosing nocturnal perspiration exists. By introducing the Q-strip, a device which quantitatively measures nocturnal perspiration, this could be acquired. The Q-strip could serve a purpose in diagnosing nocturnal perspiration more efficient without being intrusive. In addition to its health sensing potentials, the Q-strip makes it possible to visualise perspiration patterns. This introduces the possibility to examine the quality of sleep. Future research is recommended to investigate this.

Coenzyme Q (CoQ) is a lipidic compound widely distributed in nature with crucial functions in metabolism, protection against oxidative damage and ferroptosis, and other processes. CoQ biosynthesis is a conserved and complex pathway involving several proteins. COQ2 is a member of the UbiA family of transmembrane prenyltransferases that catalyzes the condensation of the head and tail precursors of CoQ, a key step in the process because its product is the first intermediate that will be modified in the head by the next component of the synthesis process. Mutations in this protein have been linked to primary CoQ deficiency in humans, a rare disease predominantly affecting organs with a high energy demand. The reaction catalyzed by COQ2 and its mechanism are still unknown. Here we aimed at clarifying COQ2 reaction by exploring possible substrate binding sites using a strategy based on homology, comprising the identification of ligand-bound homologs with solved structures available in the Protein Data Bank (PDB) and their subsequent structural superposition to the AlphaFold predicted model for COQ2. The results highlight some residues located on the central cavity or the matrix loops that may be involved in substrate interaction, some of them mutated in primary CoQ deficiency patients. Furthermore, we analyze the structural modifications introduced by the pathogenic mutations found in humans. These findings shed new light on the understanding of COQ2 function and, thus, CoQ biosynthesis and pathogenicity of primary CoQ deficiency.

Towards smart batteries for electric vehicles (EVs) smart algorithms to control battery packs, mainly reconfigurable batteries, have to be developed. This work proposes a reinforcement learning (RL) algorithm to balance the State of Charge (SoC) of reconfigurable batteries based on the topologies half-bridge and battery modular multilevel management (BM3). As RL algorithm, Amortized Q-learning (AQL) is implemented, which allows enourmous numbers of possible configurations of the reconfigurable battery to be controlled, as well as the combination of classical controlling approach and machine learning methods. This enables safety mechanisms in control. As a neural network of the AQL a Feedforward Neuronal Network (FNN) is implemented consisting of three hidden layers. The experimental evaluation using a 12-cell hybrid cascaded multilevel converter illustrates the applicability of the method to balance the SoC and maintain the balanced state during discharge. The evaluation shows a 20.3% slower balancing compared to the classical. Nevertheless, AQL shows great potential to be applied for multiobjective optimizations as an applicable RL algorithm for control in power electronics.

Given the AdS/CFT relationship, the study of higher-dimensional AdS black holes is extremely important. Furthermore, since the restriction derived from $f(Q)$'s field equations which prevents it from deriving spherically symmetric black hole solutions, the result is either $Q'=0$ or $f_{QQ}=0$. We derive static anti-de-Sitter black holes in $D$-dimensions using the cylindrical coordinate in the framework of the cubic form of $f(Q)$ gravity, where the coincident gauge condition is imposed \cite{Heisenberg:2023lru,Maurya:2023muz}. Within this study we are going to use the power-law ansatz which is the most viable according to observations where $f(Q)=Q+\frac{1}2\gamma Q^2+\frac{1}3\gamma Q^3-2\Lambda$, and the condition $D \geq 4$ is satisfied. Since these solutions lack a general relativity limit, they belong to a brand-new solution class, the characteristics of which are derived only from the non-metricity $Q$ modification. We investigate the singularities of the solutions by computing the values of different curvature and non-metricity invariants. We discover that the solutions indeed have a central singularity, but because of the f(Q) impact, it is softer than in the typical general relativity case. In conclusion, we compute thermodynamic parameters such as Gibbs free energy, Hawking temperature, and entropy. These thermodynamic calculations confirm that our model is stable.

β-Ga2O3 crystal have attracted great attentions in the fields of photonics and photoelectronics because of its ultra wide-band gap and high thermal conductivity. Here, pure β-Ga2O3 crystal was successfully grown by optical floating zone (OFZ) method, and used as saturable absorbers to realize a passively Q-switched all-solid-state 1μm laser for the first time. By placing the as-grown β-Ga2O3 crystal into the resonator of Nd:GYAP solid-state laser, a Q-switched pulses at the center wavelength of 1080.4 nm are generated under a output coupling of 10%. The maximum output power is 191.5 mW while the shortest pulse width is 606.54 ns, and the maximum repetition frequency is 344.06 kHz. The maximum pulse energy and peak power are 0.567 μJ and 0.93 W, respectively. Our experimental results show that β-Ga2O3 crystal has great potential in the development of all-solid-state 1μm pulsed laser.

In this paper, we investigate several relations for p-adic gamma function by means of their Mahler expansion and fermionic p-adic q-integral on ℤ_{p}. We also derive two fermionic p-adic q-integrals of p-adic gamma function in terms of q-Boole polynomials and numbers. Moreover, we discover fermionic p-adic q-integral of the derivative of p-adic gamma function. We acquire a representation for the p-adic Euler constant by means of the q-Boole polynomials. We finally develop a novel, explicit and interesting representation for the p-adic Euler constant including Stirling numbers of the first kind.

In this paper we introduce the hypo-q-operator norm and hypo-q-numerical radius on a Cartesian product of algebras of bounded linear operators on Banach spaces. A representation of these norms in terms of semi-inner products, the equivalence with the q-norms on a Cartesian product and some reverse inequalities obtained via the scalar reverses of Cauchy-Buniakowski-Schwarz inequality are also given.

We give three new authentication schemes without secrecy. The first two on finite fields and Galois rings, using Gray map for this link. The third construction is given on Galois rings. The main achievement in this work is to obtain optimal impersonation and substitution probabilities in the schemes. Additionally, in the first and second scheme, we simplify the source space and bring a better relationship between the size of the message space and the key space than the given in [8]. Finally, we provide a third scheme on Galois rings, which generalizes the scheme over finite fields constructed in [9].

Substantial resources are invested in conservation of marine biodiversity globally. Fishing is the primary threat to many marine species and is one we can manage. However, threatened marine species are legally caught in industrial fisheries. To determine the magnitude and extent of this problem, we analysed global fisheries catch and import data and found reported catch records of 91 globally threatened species, thirteen of which are traded internationally. Seventy-three species targeted in industrial fisheries account for 99% of threatened species catch volume and value. Our results are a conservative estimate of threatened species catch and trade because we only consider species-level data, excluding group records; for example, we omit ‘sharks and rays,’ which represents over 200 threatened species. Although most fishing countries are involved in catch or trade of threatened species, it is driven largely by European nations. On land and for charismatic marine animals (e.g., whales), industrial-scale harvest of species at risk of extinction is controversial and usually highly regulated. In contrast, fishing for endangered fish and invertebrates is widespread but poorly documented. Given the development of new fisheries monitoring technologies and the current push for stronger international mechanisms for biodiversity management, industrial fishing of threatened fish and invertebrates should no longer be neglected in conservation and sustainability commitments.

This work examines drought and wet events based on Standardized Precipitation-Evapotranspiration Index (SPEI) over Kenya from 1981 to 2016. Spatiotemporal analysis of dry and wet events is conducted for 3 and 12-month SPEI. The drought incidences were observed during the period 1984, 1987, 2000, 2006, 2009, 2015, and 2016 for SPEI-3 whilst the SPEI-12 demonstrated the manifestation of drought during the year 2000 and 2006. SPEI clearly shows that the wettest period, 1997 and 1998 that coincide with the El Nino event in both time steps. SPEI -3 shows a reduction in moderate drought events while severe and extreme cases were on increase towards the end of the twentieth century. Conversely, SPEI-12 depicts an overall increase in severe drought occurrence over the study location with observed intensity of -1.54 and cumulative frequency of 64 months during the study period. The trend of wet events is upwards in the western and central highlands while the rest of the regions show increase in dry events during the study period. Moreover, moderate dry/wet events predominate whilst extreme events occur least frequent across all grid cells. It is apparent that the study area experiences mild extreme dry events in both categories although moderately severe dry events dominate most parts of the study area. High intensity and frequency of drought is noted in SPEI-3 while least occurrences of extreme events are recorded in SPEI-12. Although drought event prevails across the study area, there is evidence of extreme flood conditions over the recent decades. These findings form a good basis for next step of research that will look at projection of droughts over the study area based on regional climate models.

The present study evaluates the psychometric properties of the Conflicts in Romantic Relationships Over Facebook Use Scale with a sample of Puerto Rican adults. A total of 577 Puerto Ricans participated on this confirmatory and psychometric study. The results confirmed that the scale has a multidimensional structure. These dimensions are: Partner Facebook intrusion, Conflict over Facebook use, and Jealousy over Facebook use. A total of 18 items complied with the criteria of discrimination and presented appropriate factorial loads (6 items per dimension). The Cronbach’s Alpha indexes of the dimensions ranged between .87 and .95 and the omega coefficients ranged between .88 and .95. In summary, the instrument has the appropriate psychometric properties to continue with validation studies, as well as to be implemented in various work areas, both theoretical and applied.

Given a polynomial $P(x_{1}, x_{2}, \ldots, x_{n})$ which is the sum of terms, where each term is a product of two distinct variables, then the problem $APSS$ consists in calculating the total sum value of $\sum_{\forall U_{i}} P(u_{1}, u_{2}, \ldots, u_{n})$, for all the possible assignments $U_{i} = \{u_{1}, u_{2}, ... u_{n}\}$ to the variables such that $u_{j} \in \{0, 1\}$. $APSS$ is the abbreviation for the problem name Algebraic Polynomial Sum Solver Over $\{0, 1\}$. We show that $APSS$ is in $\#L$ and therefore, it is in $FP$ as well. The functional polynomial time solution was implemented with Scala in \url{https://github.com/frankvegadelgado/sat} using the DIMACS format for the formulas in $\textit{MONOTONE-2SAT}$.

This study examined the efficacy of essential oil (EO) obtained from the Australian native plants, lemon myrtle (Backhousia citriodora) (LM) to inhibit Penicillium digitatum by in vitro agar diffusion and vapor assay, and in inoculated oranges. Gas chromatograph/mass spectrometry analysis revealed the main constituent of LM EO as citral. Pure citral was also included in the experiment for com-parison. LM EO at 1, 2, 3, 4 and 5 µL disc-1 in the in vitro tests significantly inhibited fungal growth compared to the non-treated control. Moreover, LM EO at 4 and 5 µL disc-1 in both the assays completely inhibited fungal growth similar to its main component of citral. Inoculated oranges dipped in 1000 μL L-1 LM EO solutions for 5, 10, 15 and 30 sec showed significantly lower fungal wounds compared to control. While higher dipping times generated slight rind injury, a 5 and 10 sec dip did not cause any injury to the fruit rind. The quality assessments and sensory evaluations also revealed that the addition of LM EO did not adversely affect the quality and taste of the oranges. These findings suggest LM EO as an alternative to synthetic fungicides to inhibit wastage in citrus during storage.

Pekalongan is one of several cities that lies in the northern coast of Java island which is often flooded due to sea level rise. This condition impacted its urban development characteristic and increase in the future. In this research both Geographical Information System based and Spatial Metric approach are used. The spatial pattern is analyzed by using spatial metric based on the exploration of land use change that occurred. In this research, the spatial pattern is focused on aggregation pattern and diversity in coastal area. The result shows that the land use of coastal area are dominated with swamp, then followed by settlement and fishpond. It is also shown that the greatest land use change occurred on paddy field and swamp areas. Based on the spatial metric calculation, the aggregation level of land use decrease periodically and has a small growth level. It is indicated from its metric value aggregation and diversity from two periods: 2003-2009 and 2009-2016. Overall the land use of Pekalongan experienced large dynamics, especially in its coastal area. The spatial pattern trend in those area tend to be more sprawl as defined by the decrease of aggregation pattern and low level of land use growth pattern.

We investigate a singularly perturbed q-difference differential Cauchy problem with polynomial coefficients in complex time and space with quadratic nonlinearity. We construct local holomorphic solutions on sectors in the complex plane with respect to the perturbation parameter with values in some Banach space of formal power series in space with analytic coefficients on shrinking domains in time. Two aspects of these solutions are addressed. One feature concerns asymptotic expansions in the parameter for which a Gevrey type structure is unveiled. The other fact deals with confluence properties as q tends to 1. In particular the built up Banach valued solutions are shown to merge in norm to a fully bounded holomorphic map in all its arguments that solves a nonlinear partial differential Cauchy problem.

This paper directly addresses a long-standing issue that affects the development of many complex distributed software systems: how to establish quickly, cheaply, and reliably whether they can deliver their intended performance before expending significant time, effort and money on detailed design and implementation. We describe ∆QSD, a novel metrics-based and quality-centric paradigm that uses formalised outcome diagrams to explore the performance consequences of design decisions, as a performance blueprint of the system. The distinctive feature of outcome diagrams is that they capture the essential observational properties of the system, independent of the details of system structure and behaviour. The ∆QSD paradigm derives bounds on performance expressed as probability distributions encompassing all possible executions of the system. The ∆QSD paradigm is both effective and generic: it allows values from various sources to be combined in a rigorous way, so that approximate results can be obtained quickly and subsequently refined. ∆QSD has been successfully used by Predictable Network Solutions for consultancy on large-scale applications in a number of industries, including telecommunications, avionics, and space and defence, resulting in cumulative savings worth billions of US dollars. The paper outlines the ∆QSD paradigm, describes its formal underpinnings, and illustrates its use via a topical real-world example taken from the blockchain/cryptocurrency domain. ∆QSD has enabled challenging throughput targets to be met for a globally distributed blockchain operating on the public internet.

Given the landscape of intricate and constantly evolving cyber threats, organizations demand refined strategies to deploy a Security Information and Event Management to support the management of a Cyber Security Operations Center. The dynamic nature of cyber threats complicates the efficient allocation of the location of network intrusion detection sensors, a critical component of a robust cybersecurity framework. Our research introduces an approach that integrates the precision of biomimetic optimization algorithms with the adaptability of Deep Q–Learning. By employing different biomimetic algorithms enhanced with deep learning, we aim to refine the deployment of sensors in network infrastructures, balancing the network security imperative against deployment costs. The results of computational tests demonstrate that the improved iterations leveraging Deep Q–Learning have outperformed their native counterparts. These findings underscore the importance of reinforcement learning, specifically through Deep Q–Learning, as a powerful tool to enhance the effectiveness of metaheuristics in addressing optimization challenges.

The high-speed railway operation environment monitoring network system has a wide variety of sensors and inconsistent business requirements, which have certain requirements for data transmission delay and network life. Most of the previous research focuses only on prolonging network lifetime or reducing data transmission delays when designing or optimizing routing protocols, without co-designing the two. In addition, due to the harsh operating environment of high-speed railways, when the network changes dynamically, the traditional routing algorithm will generate unnecessary redesigns and lead to high overhead. Based on the actual needs of high-speed railway operation environment monitoring, this paper proposes a novel Double Q-values adaptive model combined with the existing reinforcement learning method, which considers the energy balance of the network and real-time data transmission, and constructs energy saving and delay. The two-dimensional reward avoids the extra overhead of maintaining a global routing table while capturing network dynamics. In addition, the adaptive weight coefficient is used to ensure the adaptability of the model to each business of the high-speed railway operation environment monitoring system. Finally, simulations and performance evaluations are carried out and compared with previous studies.Finally, simulations and performance evaluations are carried out and compared with previous studies. The results show that the proposed routing algorithm successfully extends the network’s life cycle and gets good real-time data performance. It also saves energy and has fewer delays than the other three routing protocols in different situations.

Increasing the quality factor (Q) of an optical resonator device has been a research focus to be utilized in various applications. Higher Q-factor means light is confined in a longer time which will produce a shaper peak and higher transmission. In this paper, we introduce a novel technique to increase further the Q-factor of a one-dimensional photonic crystal (1D PhC) cavity device by using an end loop-mirror (ELM). The technique utilizes and recycles the light transmission from the conventional 1D PhC cavity design. The design has been proved to work by using the 2.5D FDTD simulation with Lumerical FDTD and MODE softwares. By using the ELM technique, the Q- factor of a 1D PhC design has been shown to have increased up to 79.53 % from the initial Q value without the ELM. This novel design technique can be combined with any high Q-factor and very high Q-factor designs to increase more the Q-factor value of a photonic crystal cavity devices or any other suitable optical resonator devices. The experimental result shows that the device is measurable by adding a Y-branch component to the one-port structure and able to get the high-Q result.

In this paper we introduce the hypo-q-norms on a Cartesian product of algebras of bounded linear operators on Hilbert spaces. A representation of these norms in terms of inner products, the equivalence with the q-norms on a Cartesian product and some reverse inequalities obtained via the scalar reverses of Cauchy-Buniakowski-Schwarz inequality are also given. Several bounds for the norms δ_p, ϑ_p and the real norms η_r,p and θ_r,p are provided as well.

The formation of solid solution series Cs_1-xM_xGaQ₂-mC64 (M = K, Rb; Q = S, Se; x = 0–1) was studied by X-ray diffraction and spectroscopic methods, revealing a complete miscibility of CsGaQ₂-mC64 with RbGaQ₂ and KGaSe₂, and a large miscibility gap with KGaS₂. All solid solution members exhibit similar Raman spectra, indicating the covalent Ga-Q bonding character. The similar optical band gaps likewise further contribute to this conclusion. Up to a degree of substitution, these solid solutions undergo a phase transition similar to CsGaQ₂-mC64. The influence of the substitution parameter x on phase transition process was investigated in situ using high-temperature X-ray powder diffraction experiments. Phase-pure solid solutions of the high-temperature polymorphs Cs_1-xM_xGaQ₂-mC16 were obtained up to x_max(K) = 0.1 and x_max(Rb) = 0.3. The crystal structures of these new CsGaQ₂-mC16 analogous high-temperature phases were refined from synchrotron diffraction data by Rietveld-refinement.

The objective of this study is to investigate whether the sequence length of HIV-1 increases over time. A longitudinal analysis of full-length coding region sequences (FLs) in an outbreak of HIV-1 infection among patients with hemophilia and local controls identified as infected with the Korean subclade B of HIV-1 (KSB). Genes amplified by overlapping RT-PCR or nested PCR were subjected to direct sequencing. In total, 141 FLs were sequentially determined over 30 years in 62 KSB-infected patients. Non-KSB sequences were retrieved from the Los Alamos National Laboratory HIV Database. Phylogenetic analysis indicated that within KSB, 2 FLs from plasma donors O and P comprised two clusters together with 8 and 12 patients with hemophilia, respectively. Signature pattern analysis for the KSB of HIV-1 revealed signature nucleotide residues at 1.05%, compared with local controls. Additionally, in-depth FLs sequence analysis over 30 years in KSB indicates that the KSB FL significantly increases over time before combined antiretroviral therapy (cART) and decreases on cART. Furthermore, the increase in FLs over time significantly occurred in the subtypes B, C and G, but, there was no increase in the subtypes D, A, and F1. Consequently, subtypes F1 and D had the shortest sequence length. Our analysis was extended to compare HIV-1 with HIV-2 and SIVs. Essentially, the longer the sequence length (SIVsm > HIV-2 > SIVcpz > HIV-1), the longer the survival period. The increase in the length of the HIV-1 sequence over time suggests that it might be an evolutionary direction toward attenuated pathogenicity.

The paper presents the first retrievals of clean snow properties using spaceborne hyperspectral The Environmental Mapping and Analysis Program (EnMAP) observations. The location close to the Dome C in Antarctica has been selected. At this location the atmospheric effects except molecular light scattering and absorption are weak and the simplified atmospheric correction scheme can be applied. The ice grain size, snow specific surface area and snow spectral and broadband albedos have been retrieved using single view EnMAP measurements. In addition, we propose the technique to retrieve trace gas concentrations (e.g., water vapor, ozone) from EnMAP observations over the snow surfaces. Close correspondence of satellite and ground measured parameters has been found.

A 3-month (June-August) regime of the year 2002 summer rainfall (JJA2002) was simulated with 30 physics combinations using the Weather Research and Forecasting (WRF) model at 12-km horizontal grid resolution. The objective is to examine summer rainfall sensitivity to parameterization of microphysical, convective, and boundary layer processes and identify the best possible combination of parameterization options that perform relatively better in simulating the spatial and temporal distribution of summer rains over Ethiopia. The WRF simulated rainfall was evaluated against station data and satellite rainfall products (CHIRPS and ENACTS) using mean absolute error, Pearson and Pattern correlation coefficients (PCC), pattern correlation, and error in a number of rainy days as evaluation metrics. Summer rainfall is found to be most sensitive to the choice of cumulus parameterization and least sensitive to cloud microphysics. All simulations captured the spatial distribution of mean seasonal precipitation with PCC ranging from 0.89-0.94. However, all simulations overestimated precipitation amount and number of rainy days. Out of the 30, the simulations that use a combination of Grell-3D cumulus scheme, ACM2 boundary layer, Lin Microphysics, Dudhai shortwave radiation, and RRTM longwave radiation scheme ranked the top and provided the most realistic simulation in terms of amount and spatio-temporal distribution of summer rainfall.

Soil temperature reflects the impact of local factors，such as vegetation，soil and the atmosphere of a region. Therefore, it is important to understand the regional variation of soil temperature. However, lack of observations with adequate spatial and/or temporal coverage, it would be difficult to use the observation data to study the regional variation. Based on the observation data from Nanchang and Ganzhou stations and ERA-Interim/Land reanalysis data, this study analyzed the temporal-spatial distribution characteristics of soil temperature over Poyang Lake Basin. The results showed close correlations between observation data and reanalysis data at different depths. Reanalysis data could mainly reproduce the temporal-spatial distributions of soil temperature over the Poyang Lake Basin, but generally underestimate their magnitudes. Temporally, there is an obvious warming trend in the basin. Seasonally, the temperature raised fastest in spring and slowest in summer, except for the ST4, which rising fastest in spring and slowest in winter. In terms of depths, the temperature of ST1 rises fastest. For the other layers, the warming trend is almost similar. An abrupt change of annual soil temperature at all depths occurred in 1997, and annual soil temperatures at all depths were abnormally low in 1984. Spatially, annual soil temperature decreased with latitude, except for the summer ST1. Because of the high temperature and precipitation in summer, the ST1 are higher around the lake and the river. The climatic trend of soil temperature presents the general increase trend from south to north, opposite to the distribution of soil temperature. The findings provide a basis for understanding and assessing the variation of the soil temperature over the Poyang Lake Basin.

Two new systematic authentication codes based on the Gray map over a Galois ring are introduced. The first introduced code attains optimal impersonation and substitution probabilities. The second code improves space sizes but it does not attain optimal probabilities. Besides it is conditioned to the existence of a special class of bent maps on Galois rings.

Selecting drought-tolerant and more water-efficient wheat genotypes is a research priority, spe-cifically in regions with irregular rainfall or areas where climate change is expected to result in reduced water availability. The objective of this work was to use high-throughput measurements with morphophysiological traits to characterize wheat genotypes in relation to water stress. Field experiments were conducted from May to September 2018 and 2019, using a sprinkler bar irriga-tion system to control water availability to eighteen wheat genotypes: BRS 254; BRS 264; CPAC 01019; CPAC 01047; CPAC 07258; CPAC 08318; CPAC 9110; BRS 394 (irrigated biotypes) and Aliança; BR 18_Terena; BRS 404; MGS Brilhante; PF 020037; PF 020062; PF 120337; PF 100368; PF 080492; TBIO Sintonia (rainfed biotypes). The water regimes varied from 22 to 100% of the crop evapotranspiration replacement. Water stress negatively affected gas exchange, vegetation indices and grain yield. High throughput variables TCARI, NDVI, OSAVI, SAVI, PRI, NDRE and GNDVI had higher correlation with yield and morphophysiological measurements. The drought re-sistance index indicated that genotypes Aliança BRS 254, BRS 404, CPAC 01019, PF 020062, and PF 080492 were more drought tolerant.

Background: Long COVID, characterized by a persistent symptom spectrum following SARS-CoV-2 infection, poses significant health, social, and economic challenges. This review aims to consolidate knowledge on its epidemiology, clinical features, and underlying mechanisms to guide global responses; Methods: We conducted a systematic literature review, analyzing peer-reviewed articles and reports to gather comprehensive data on long COVID’s epidemiology, symptomatology, and management approaches; Results: Our analysis revealed a wide array of long COVID symptoms and risk factors, with notable demographic variability. The current understanding of its pathophysiology suggests a multifactorial origin yet remains partially understood. Emerging diagnostic criteria and potential therapeutic strategies were identified, highlighting advancements in long COVID management.; Conclusion: This review highlights the multifaceted nature of long COVID, revealing a broad spectrum of symptoms, diverse risk factors, and the complex interplay of physiological mechanisms underpinning the condition. Long COVID symptoms and disorders will continue to weigh on healthcare systems in years to come. Ad-dressing long COVID requires a holistic management strategy that integrates clinical care, social support, and policy initiatives. The findings underscore the need for increased international cooperation in research and health planning to address the complex challenges of long COVID. There is a call for continued refinement of diagnostic and treatment modalities, emphasizing a multidisciplinary approach to manage the ongoing and evolving impacts of the condition.

Searching over a sorted list is a classical problem in computer science. Binary Search takes at most log2n+1 tries to find an item in a sorted list of size n. Interpolation Search achieves an average time complexity of Ο(loglogn) for uniformly distributed data. Hybrids of Binary Search and Interpolation Search are also available to handle data with unknown distributions. This paper analyzes the computation cost of these methods and shows that interpolation can significantly affect their performance — accordingly, a new method, Interpolation Once Binary Search (IOBS), is proposed. The experimental results show that IOBS outperforms the hybrids of Binary Search and Interpolation Search for nonuniformly distributed data.

The 3GPP release 16 integrates TSN functionality into 5G and standardizes various options for TSN time synchronization over 5G such as transparent mode and bridge mode. The time domains for the TSN network and the 5G network are kept separate with an option to synchronize either of the networks to the other. The TSN time synchronization over 5G is possible either by using the IEEE 1588 generalized Precision Time Protocol (gPTP) based on UDP/IP multicast or via IEEE 802.1AS based on Ethernet PDUs. The INET and Simu5G simulation frameworks, which are both based on the OMNeT++ discrete event simulator, are widely used for simulating TSN and 5G networks. The INET framework comprises the 802.1AS based time synchronization mechanism and Simu5G provides the 5G user plane carrying IP PDUs. We modified the 802.1AS based synchronization model of INET so that it works over UDP/IP. With that it is possible to synchronize TSN slaves (connected to 5G UEs), across a 5G network, with a TSN master clock, present within a TSN network, that is connected to the 5G core network. Our simulation results show that 500 microseconds synchronization accuracy can be achieved with the corrected asymmetric propagation delay of uplink and downlink between the gNodeB (gNB) and the User Equipment (UE). Futhermore, the synchronization accuracy can be improved if the delay difference between uplink and downlink is known.

The volume of vehicular traffic in large cities has increased in recent years, the devices that collect vehicular GPS data such as cameras, GPS receivers and others generate millions of records at every instant of time generating problems in processing and storage of these data which becomes important for researchers. Intelligent Transportation Systems perform vehicle monitoring and control by collecting GPS trajectories, this large volume of information is necessary to have an optimal storage process. Its processing by means of compression techniques and simplification algorithms allow to reduce the necessary storage space. This paper presents a GPS trajectory simplification algorithm that considers noise reduction, point simplification and analysis of road network information. The results obtained on two data sets from the cities of California and Beijing are satisfactory, achieving a higher compression ratio without affecting data quality

We have shown that according to the predictions of the standard quantum theory, signaling is possible using a postponed compensation Hong-Ou-Mandel interferometer, although it violates Lorentz invariance. We argue that new physics is required to deal with such a paradox. Either quantum principles or relativity needs reassessment. We propose an experiment that can decide whether relativity rules over quantum or vice versa.

Coronaviruses are a large family of RNA viruses which cause respiratory infections ranging from the common cold to more severe diseases such as Middle East Respiratory Syndrome (MERS), Severe Acute Respiratory Syndrome (SARS) and COVID-19. This article highlights some key findings based on a thorough scanning of genes of 475 SARS-CoV2 genomes, including the co-presence of ORF7a and ORF8 over the 256 SARS-CoV2 genomes and the absence of the gene ORF7b over the 219 SARS-CoV2 genomes collected from various countries including India. The presence of the gene ORF7b is found in the SARS-CoV2 genomes containing the L-type strain which is reported to having much higher virulence as compared to the S-type strain.

Sixty years ago in the lab adjacent to Fred Sanger (1958 Nobel Prize for protein chemistry), I discovered the cell surface hydroxyproline-rich glycoproteins. Nature keeps some of her secrets longer than others. It has taken many years to dissect the molecular function and biological role of extensins and arabinogalactan proteins (AGPs). Extensins template the formation of new cell walls. AGPs remained baffling and enigmatic until a Eureka moment when computer prediction of AGP calcium binding depicted paired glucuronic acid residues and thus the likely role of a cell surface AGP-Ca²⁺capacitor: In conjunction with the auxin-activated proton pump that releases bound Ca²⁺ it led us to formulate the Hechtian Growth Oscillator as A Global Paradigm with a pivotal role in Ca²⁺ homeostasis. The ramifications are profound. They cannot be shrugged off with sceptical disdain but demand critical reappraisal of current dogma. Phyllotaxis is an ancient problem; it involves an essential role for auxin and the auxin efflux “PIN” proteins together with mechanotransduction of stress-strain as phyllotactic determinants. However, a general explanation remains elusive despite much effort, particularly by mathematicians. Here we propose a novel biochemical algorithm: Hechtian oscillator transduction of cell wall stress generates phyllotactic patterns quite independent of a mathematical approach. Plants simply use different rules and follow a different route.

Mixing layer height (MLH) is a crucial parameter for air quality modelling that is still not routinely measured. Common methods for MLH determination use atmospheric profiles recorded by radiosonde but they suffer from course temporal resolution since balloon launching is only twice a day. Recently cheap ceilometers are gaining popularity in the retrieval of MLH diurnal evolution based on aerosol profiles. This study presents a comparison of a proprietary (Jenoptik) and a free available (STRAT) algorithms to retrieve MLH diurnal cycle. The comparison is accomplished in summer season over urban area and radiosonde data is used to estimate MLHs according to parcel, lapse rate, and Richardson methods (the last algorithm is used as a reference in the study) in addition. It was found that STRAT and Jenoptik give lower MLH than radiosonde with an underestimation of about 150m and 650m respectively. Additionally, STRAT showed reasonable performance in tracking of MLH diurnal evolution. Daily MLH maximum of about 2000m was found in the late afternoon (18-19 LT). In contrast, Jenoptik algorithm showed more weaknesses, mainly attributed to its real-time operation and independent processing of a single profile. At night and during morning transition period, both lidar-based methods showed difficulties as MLH was often in the ceilometer’s incomplete overlapping zone so residual or advected aerosol layers aloft were misleadingly reported as mixing layer (ML).

Long-range radio transmissions open new sensor application fields, in particular for environment monitoring. As an example, the {\sl LoRa} radio protocol enables to connect remote sensors at distance as long as ten kilometers in line-of-sight. However, the large area covered also bring several difficulties, such as the placement of sensing devices in regard to geography topology, or the variability of communication latency. Sensing the environment also carries constraints related to the interest of sensing points in relation with a physical phenomenon. Criteria for designs are thus evolving a lot from the existing methods, especially in complex terrains. This article describes simulation techniques based on geography analysis to compute long-range radio coverages and radio characteristics in these situations. As radio propagation is just a particular case of physical phenomena, it is shown how a unified approach also allows to characterize the behavior of potential physical risks. The case of heavy rainfall and flooding is investigated. Geography analysis is achieved using segmentation tools to produce cellular systems which are in turn translated into code for high-performance computations. The paper provides results from practical complex terrain experiments using LoRa, that confirm the accuracy of the simulation, scheduling characteristics for sample networks, and performance tables for simulations on middle range Graphics Processing Units (GPUs).

We aimed to investigate whether the sequence length of HIV-1 increases over time. A longitudinal analysis of full-length coding region sequences (FLs) during an HIV-1 outbreak among pa-tients with hemophilia and local controls infected with the Korean subclade B of HIV-1 (KSB) was performed. Genes were amplified by overlapping RT-PCR or nested PCR and subjected to direct sequencing. Overall, 141 FLs were sequentially determined over 30 years in 62 KSB-infected patients. Phylogenetic analysis indicated that within KSB, two FLs from plasma donors O and P comprised two clusters together with 8 and 12 patients with hemophilia, respectively. Signature pattern analysis for the KSB of HIV-1 revealed 91 signature nucleotide residues (1.05%). In total, 48 and 43 signature nucleotides originated from clusters O and P, respectively. Only six positions contained 100% specific nucleotide(s) in clusters O and P. Additionally, in-depth FL analysis over 30 years indicates that the KSB FL significantly increased over time before combined antiretroviral therapy (cART) and decreased with cART. The increase occurred due to a significant increase in env and nef genes, originating in the variable regions of both genes. The increase in the sequence length of HIV-1 over time suggests that it has an evolutionary direction.

Price markups and firm Tobin’s Q ratios are widely believed to have been increasing in the past several decades. Various models for the calculation of price markups have been developed, but each have methodological drawbacks and some results are poorly reflective of the near past wider macroeconomic experience. This paper defines an approach for the definition and measurement of markup pricing using the measure of Economic Rent and The Capital Asset Pricing Model. The results show limited markup pricing for The UK’s FTSE 100 companies (2018-2023), but that that certain Real Estate, Technology/Media and Financial Services/Equity Investment firms have enjoyed higher price markup levels. An analysis of the business models of these firms is used to qualitatively propose explanations for such markups. Finally, this work offers a formal proof that that expected price markup is equal to Tobin’s Q and finds that the empiric market level of markup is near equivalent to the market Tobin’s Q; differences between the markup and Tobin’s Q at the level of the firm are equally assessed.

Lightning is responsible for most annually burned area by wildfires in the extratropical region of the Northern Hemisphere. Hence, predicting the occurrence of wildfires requires reliable forecasting of the chance of cloud-to-ground lightning strikes during storms. Here, we describe the development and verification of a probabilistic lightning-strike algorithm designed to run on a uniform 20-km grid over the Continental USA and Alaska. The algorithm consists of a large set of logistic equations parameterized via logistic regression using long-term data records of observed lightning strikes and meteorological reanalysis fields from NOAA. Principal Component Analysis was employed to extract 13 Principal Components (strong predictors) from a list of 611 potential predictors. Our statistical analysis revealed that the occurrence of cloud-to-ground lightning strikes primarily depends on three factors: horizontal temperature distribution by pressure levels, amount of low-level atmospheric moisture, and wind vectors. These physical variables impact the vertical separation of electric charges in the lower troposphere during storms causing the voltage potential between ground and the cloud deck to increase to a level that triggers electrical discharges. Results from a forecast verification using independent data showed excellent model skill, thus making this algorithm suitable for inclusion into software systems forecasting the chance of wildfire ignitions.

Background: Informal caregivers' own quality of life, health status, and determinants are poorly understood despite their concerns for the health of the individuals they assist. Objectives: To compare the quality of life and the health determinants of older informal caregivers with those of older adults without caregiving responsibilities. Methods: An online survey was designed to investigate the quality of life and the health determinants of people aged 65 years and over, with a focus on informal caregivers. In addition to socio-demographic data, the number of informal caregiver and the Zarit scale of caregiver burden were collected. Quality of life (SF-12) and health determinants (access to technology and level of physical activity (IPAQ)) were assessed and compared between informal caregivers and the others. Results: A total of 111 participants (70 ± 3.83 years, 71.2% of women). The majority of respondents (91.8%) were Belgian. One third of the respondents identified themselves as informal caregiver and declared to have severe burden (61.9±15.2/88). Socio-demographic characteristics and access to technology were similar between informal caregivers and non-caregivers (p>0.05). However, informal caregivers have a lower SF-12 score in the mental score domain (44.3±10.2 vs; 50.7±7.0; p=0.004) and a lower level of physical activity (434±312 METS/min/week vs.1126±815 METS/min/week; p=0.01) than their peers. Conclusions: Informal caregivers reported lower quality of life and lower level of physical activity than their peers. Given the recognized importance of physical activity for overall health, this survey highlights the need to promote physical activity among older informal caregivers.

Stratocumulus (Sc) is the most common cloud type in China. Sc clouds may or may not be accompanied by various types of precipitation that are representative of different macro- and microphysical characteristics. The finely resolved CloudSat data products are used in this study to quantitatively investigate the macro- and microphysical characteristics of precipitating and non-precipitating Sc (PS and NPS, respectively) clouds over Eastern China (EC). Based on statistical information extracted from the CloudSat data, Sc clouds are highly likely to occur alone, in association with liquid precipitation, or in association with drizzle over 25.65% of EC. The cloud bases of NPS clouds are higher than those of PS clouds, although the latter display higher cloud top heights and thicker cloud thicknesses. The spatial distributions of microphysical characteristics differ between PS and NPS clouds. The magnitudes of microphysical characteristics in NPS clouds are relatively small and decrease with height, whereas the magnitudes of microphysical characteristics in PS clouds are relatively large and peak in response to certain circulation patterns and over certain terrain. The variations in microphysical characteristics in Sc clouds with height and contoured frequency by altitude diagrams (CFADs) of radar reflectivity may indicate that different microphysical processes operate in PS and NPS clouds. In NPS clouds, hydrometeor particles accumulate by coalescence as they rise; once the particles are too large to be supported by updrafts, the cloud droplets form raindrops. In PS clouds, raindrops increase continuously in size via collision-coalescence processes as they fall. The levels between 2.5 and 3.0 km represent the space where particles grow most rapidly. Particles are affected by updrafts and accumulate at levels between 2.5 and 1.0 km as height decreases.

Albedo is a key variable in the response of glaciers to climate. In Iceland, large albedo variations in the ice caps may be caused by the deposition of volcanic ash (tephra). Sparse in situ field measurements are insufficient to characterize the spatial variation of albedo over the ice caps. Here we evaluate the latest MCD43 MODIS albedo product (collection 6) to monitor albedo over the Icelandic ice caps using albedo from ten automatic weather stations in Vatnajökull and Langjökull as ground truth. We examine the influence of the albedo variability within MODIS pixels by comparing the results with a collection of Landsat scenes. The results indicate a good ability of the MODIS product to characterize the seasonal and interannual albedo changes with correlation coefficients ranging from 0.47 to 0.90 (median 0.84) and a small bias ranging from -0.07 to 0.09. The root-mean square errors (RMSE) ranging from 0.08 and 0.21, is larger than that from previous studies, but we did not discard the retrievals flagged as bad quality to maximize the amount of observations given the frequent cloud obstruction in Iceland. We find a positive but non-significant relationship between the RMSE and the subpixel variability as indicated by the standard deviation of the Landsat albedo within the MODIS pixel (R=0.48). The summer albedo maps and time series computed from the MODIS product show that the albedo decreased significantly after the Eyjafjallajökull and Grímsvötn eruptions in 2010 and 2011 in all the main ice caps (except the northernmost Drangajökull), with albedo reduction up to 0.6 over large regions of the accumulation areas. Following this validation, these data will be assimilated in an energy and mass balance model of to better understand the relative influence of the volcanic and climate forcing to the ongoing mass losses of Icelandic ice caps.

In this paper, the stabilization and high efficiency of an unstable Second Harmonic Generation (SHG) of a Nd : YVO4 laser with a KTP intracavity is carried out by using a passive Q-switching crystal and a parametric modulation method (harmonic modulation) is shown. The harmonic modulation was defined as um(t) = Amsin(2π fmt), with modulation amplitude as Am(Vpp), and modulation frequency as fm(Hz), applied to the pumping of the Nd : YVO4 -KTP laser to control the amplitude and frequency of the emission, thus stabilizing the dynamic states of this laser. The promising application of this green light source is materialized when such light is necessary for high-density optics, such as in the treatment materials industry or in some aesthetic applications.

Tuning fork gyroscopes (TFGs) are promising for potential high-precision applications. This work proposes and experimentally demonstrates a novel high-Q dual mass tuning fork microelectro-mechanical system (MEMS) gyroscope utilizing three-dimensional (3D) packaging techniques. Except for two symmetrically-decoupled proof masses (PM) with synchronization structures, a symmetrically-decoupled lever structure is designed to force the antiparallel, antiphase drive-mode motion and basically eliminate the low-frequency spurious modes. The thermoelastic damping (TED) and anchor loss are greatly reduced by the linearly-coupled, momentum- and torque-balanced antiphase sense mode. Besides, a novel 3D packaging technique is used to realize high Q-factors. A composite substrate encapsulation cap, fabricated by through-silicon-via (TSV) and glass-in-silicon (GIS) reflow processes, is anodically bonded to the sensing structures at wafer scales. A self-developed control circuit is adopted to realize loop control and characterize gyro-scope performances. It is shown that a high-reliability electrical connection together with a high-air-impermeability package can be fulfilled with this 3D packaging technique. Furthermore, the Q-factors of the drive and sense modes reach up to 51947 and 49249, respectively. This TFG realizes a wide measurement range of ±1800° /s and a high resolution of 0.1° /s with a scale-factor nonlinearity 720 ppm after automatic mode-matching. Besides, the long-term zero-rate output (ZRO) drift can be effectively suppressed by temperature compensation, inducing a small angle random walk (ARW) of 0.923°/√h and a low bias instability (BI) of 9.270°/h.

In this paper we present experimental results concerning Acoustic Emission (AE) recorded during cyclic compression tests on two different kinds of brittle building materials, namely concrete and basalt. The AE inter-event times were investigated through a non-extensive statistical mechanics analysis which shows that their decumulative probability distributions follow q-exponential laws. The entropic index q and the relaxation parameter q  1=Tq, obtained by fitting the experimental data, exhibit systematic changes during the various stages of the failure process, namely (q; Tq) linearly align. The Tq = 0 point corresponds to the macroscopic breakdown of the material. The slope, including its sign, of the linear alignment appears to depend on the chemical and mechanical properties of the sample. These results provide an insight on the warning signs of the incipient failure of building materials and could therefore be used in monitoring the health of existing structures such as buildings and bridges.

This study focuses on the ability of the global land data assimilation system LDAS-Monde to improve the representation of land surface variables (LSVs) over Burkina Faso through the joint assimilation of satellite derived Surface Soil Moisture (SSM) and Leaf Area Index (LAI) from January 2001 to June 2018. The LDAS-Monde offline system is forced by the latest European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis ERA5, leading to a 0.25° x 0.25° spatial resolution reanalysis of the LSVs. Within LDAS-Monde, SSM and LAI observations from the Copernicus Global Land Service (CGLS) are assimilated using the CO2-responsive version of the ISBA (Interactions between Soil, Biosphere and Atmosphere) land surface model (LSM). First, it is shown that ERA5 better represents precipitation and incoming solar radiation than ERA-Interim former reanalysis from ECMWF. Results of two experiments are compared: open-loop simulation (i.e. no assimilation) and analysis (i.e. joint assimilation of SSM and LAI). After jointly assimilating SSM and LAI, it is noticed that the assimilation is able to impact soil moisture in the first top soil layers (the first 20 cm), and also in deeper soil layers (from 20 cm to 60 cm and below). The assimilation is able to improve the simulation of both SSM and LAI. For LAI in particular, the southern region of the domain (dominated by a Sudan-Guinean climate) highlights a strong impact of the assimilation compared to the other two sub-regions of Burkina Faso (dominated by Sahelian and Sudan-Sahelian climates). In the southern part of the domain, differences between the model and the observations are the largest, prior to any assimilation. These differences are linked to the model failing to represent the behavior of some specific vegetation species, which are known to put on leaves before the first rains of the season. The LDAS-Monde analysis is very efficient at compensating for this model weakness. Evapotranspiration estimates from the Global Land Evaporation Amsterdam Model (GLEAM) project as well as upscaled carbon uptake from the FLUXCOM project are used in the evaluation process, again demonstrating improvements in the representation of evapotranspiration and gross primary production after assimilation.

Iapetus, a Saturn moon, shows the most differentiated albedo dichotomy of the Solar System. The dark leading side has a lower albedo than the bright trailing side. Spectral data on the visible light reveal the existence of two types of materials on the surface. The darkening in the leading side is thought to be originated by the presence of organic material and carbonaceous compounds on surface, while the trailing side is covered by water ice due to migration processes from the dark side. On airless bodies like Iapetus, the surface escape speed is greater than the speed of water molecules, resulting in the retention of a H2O atmosphere that allows some species to get diffused through it. Here, there were performed simulations of the evolution of the surface temperature for each of the two hemispheres of Iapetus. The results showed a slow yet steady increment of temperatures for both sides, with a steeper slope for the dark hemisphere. It was also simulated how much energy budget can be accumulated in both sides and its consequences. Finally, we calculated the diffusion coefficients for ammonia, methane, and water ice. The results let us infer how these compounds could evolve over time.

Background: Primary cardiac sarcomas (PCS) are extremely rare malignant tumors involving the heart. Only isolated case reports have been described. There is a paucity of data on the epidemiological characteristics of PCS. This study has the objective of investigating the epidemiologic characteristics, survival outcomes, and independent prognostic factors of PCS. Methods: We enrolled a total of 362 patients with PCS, between 2000 and 2017, by retrieving the Surveillance, Epidemiology, and End Results (SEER) database. We analyzed demographics, clinical characteristics, and overall mortality (OM) as well as cancer-specific mortality (CSM) of PCS. Variables with a p-value < 0.1 in the univariate Cox regression were incorporated into the multivariate Cox model to determine the independent prognostic factors, with a hazard ratio (HR) of greater than 1 representing adverse prognostic factors. Results: Crude analysis revealed a high OM in age 80+ (HR=5.958, 95% CI 3.357-10.575, p=0), followed by age 60-79 (HR=1.429, 95% CI 1.028-1.986, p=0.033); and PCS with distant metastases (HR=1.888, 95% CI 1.389-2.566, p=0). Patients that underwent surgical resection of the primary tumor and patients with malignant fibrous histiocytomas (HR=0.657, 95% CI 0.455-0.95, p=0.025) had a better OM (HR=0.606, 95% CI 0.465-0.791, p=0). The highest cancer-specific mortality was observed in age 80+ (HR=5.037, 95% CI 2.606-9.736, p=0) and patients with distant metastases (HR=1.953, 95% CI 1.396-2.733, p=0). Patients with malignant fibrous histiocytomas (HR=0.572, 95% CI 0.378-0.865, p=0.008) and those who underwent surgery (HR=0.581, 95% CI 0.436-0.774, p=0) had a lower CSM. Multivariate Cox proportional hazard regression analyses revealed higher OM in the age group 80+ (HR=13.261, 95% CI 5.839-30.119, p=0) and advanced disease with distant metastases (HR=2.013, 95% CI 1.355-2.99, p=0.001). Lower OM was found in patients with rhabdomyosarcoma (HR=0.364, 95% CI 0.154-0.86, p=0.021) and widowed patients (HR=0.506, 95% CI 0.263-0.977, p=0.042). Multivariate Cox proportional hazard regression analyses of CSM also revealed higher mortality in the same groups, and lower mortality in patients with Rhabdomyosarcoma. Conclusion: In this United States population-based retrospective cohort study using the SEER database, we found that cardiac rhabdomyosarcoma was associated with the lowest CSM and OM. Furthermore, as expected, age and advanced disease at diagnosis were independent factors predicting poor prognosis. Surgical resection of the primary tumor showed lower CSM and OM in the crude analysis but when adjusted for covariates in the multivariate analysis, it did not significantly impact the overall mortality or the cancer-specific mortality. These findings allow for treating clinicians to recognize patients that should be referred to palliative/hospice care at the time of diagnosis and avoid any surgical interventions as they did not show any differences in mortality. Surgical resection in patients with poor prognoses should be reserved as a palliative measure rather than an attempt to cure the disease.

This study evaluates the historical mean surface temperature (hereafter T2m) and examines how T2m changes over East Africa (EA) in the 21^st century using CMIP6 models. An evaluation was conducted based on mean state, trends, and statistical metrics (Bias, Correlation Coefficient, Root Mean Square Difference, and Taylor skill score). For future projections over EA, five best performing CMIP6 models (based on their performance ranking in historical mean temperature simulations) under the shared socioeconomic pathways SSP2-4.5 and SSP5-8.5 scenarios were employed. The historical simulations reveal an overestimation of the mean annual T2m cycle over the study region with fewer models depicting underestimations. Further, CMIP6 models reproduce the spatial and temporal trends within the observed range proximity. Overall, the best performing models are as follows: FGOALS-g3, HadGEM-GC31-LL, MPI-ESM2-LR, CNRM-CM6-1, and IPSL-CM6A-LR. During the three-time slice under consideration, the Multi Model Ensemble (MME) project many changes during the late period (2080 – 2100) with expected mean changes at 2.4 °C for SSP2-4.5 and 4.4 °C for the SSP5-8.5 scenario. The magnitude of change based on Sen’s slope estimator and Mann-Kendall test reveal significant increasing tendencies with projections of 0.24°C decade-1 (0.65°C decade-1) under SSP2-4.5 (SSP5-8.5) scenarios. The findings from this study illustrate higher warming in the latest model outputs of CMIP6 relative to its predecessor, despite identical instantaneous radiative forcing.

Accurate inundation maps for flooded wetlands and rivers are a critical resource for their management and conservation. In this paper we automate a method (thresholding of the short-wave infrared band) for classifying inundation, using Landsat imagery and Google Earth Engine. We demonstrate the method in the Okavango Delta, northern Botswana, a complex case study due to the spectral overlap between inundated areas covered with aquatic vegetation and dryland vegetation classes on satellite imagery. Inundation classifications in the Okavango Delta have predominately been implemented on broad spatial resolution images. We present the longest time series to date (1990-2019) of inundation maps at high spatial resolution (30m) for the Okavango Delta. We validated the maps using image-based and in situ data accuracy assessments, with accuracy ranging from 91.5 - 98.1%. Use of Landsat imagery resulted in consistently lower estimates of inundation extent than previous studies, likely due to the increased number of mixed pixels that occur when using broad spatial resolution imagery, which can lead to overestimations of the size of inundated areas. We provide the inundation maps and Google Earth Engine code for public use.

The impacts of climate change on precipitation and drought characteristics over Bangladesh were examined by using the daily precipitation outputs from 29 bias-corrected general circulation models (GCMs) under the representative concentration pathway (RCP) 4.5 and 8.5 scenarios. A precipitation-based drought estimator, namely, the Effective Drought Index (EDI), was applied to quantify the characteristics of drought events in terms of the severity and duration. The changes in drought characteristics were assessed for the beginning (2010–2039), middle (2040–2069), and end of this century (2070–2099) relative to the 1976–2005 baseline. The GCMs were limited in regard to forecasting the occurrence of future extreme droughts. Overall, the findings showed that the annual precipitation will increase in the 21st century over Bangladesh; the increasing rate was comparatively higher under the RCP8.5 scenario. The highest increase of rainfall is expected to happen over the drought-prone northern region. The general trends of drought frequency, duration, and intensity are likely to decrease in the 21st century over Bangladesh under both RCP scenarios, except for the maximum drought intensity during the beginning of the century, which is projected to increase over the country. The extreme and medium-term drought events did not show any significant changes in the future under both scenarios except for the medium-term droughts, which decreased by 55% compared to the base period during the 2070s under RCP8.5. However, extreme drought days will likely increase in most of the cropping seasons for the different future periods under both scenarios. The spatial distribution of changes in drought characteristics indicates that the drought-vulnerable areas are expected to shift from the northwestern region to the central and the southern region in the future under both scenarios due to the effects of climate change.

Sleep disorders (SD) have a complex aetiology, and socioeconomic status (SES) as determined by social class, household income, ethnicity and education plays an important role in their development. As SD are associated with cognitive impairment and mood disorders, they in turn impact SES. Socioeconomic status also influences allostatic load caused by chronic accumulation of stress throughout life. Environmental and psychological stressors have a direct effect on SD, and they are modulated by SES, in combination with comorbidities like obesity and cardiovascular disease. This review explores the recent theories about the influence of SES on the development of SD in the general population, whether or not occurring with comorbidities, and also focusses on the interplay between socioeconomic status, circadian rhythms, aging and clinical outcomes like metabolic diseases and cancer.

The human oral microbiome refers to an ecological community of symbiotic and pathogenic microorganisms found in the oral cavity. The oral cavity is a suitable environment that provides various kinds of biological niches such as teeth, tongue, and oral mucosa. The oral cavity is the gateway between the external environment and the human body, maintaining oral homeostasis, protecting the mouth, and preventing disease. On the flip side, the oral microbiome plays an important role in triggering, development, and progression of oral and systemic diseases. Currently, disease diagnosis through the analysis of the human oral microbiome has been realized with the recent development of innovative detection technology, and is overwhelmingly promising compared to the previous era. It has been found that patients with oral diseases and systemic diseases have variations in the oral microbiome compared to normal subjects. This narrative review provides insight into the pathophysiological role that oral microbiome plays in influencing oral and systemic diseases, and updates the knowledge related to the oral microbiome over the past 30 years. A wide range of updates was provided with the latest knowledge of the oral microbiome to help researchers and clinicians in both academic and clinical aspects. The microbial community information can be utilized in non-invasive diagnosis and help develop a new paradigm in precision medicine, which will benefit human health in the era of post-metagenomics.

The Hubble parameter H(z), as a function of redshift, is modified by the presence of a new term originated from the extrinsic curvature in an embedded space-time. Assuming an asymptotic expansion factor $a\sim 0$ or, equivalently $z\rightarrow \infty$, it is obtained a nearly resemblance of the present model ($\beta$-model) with quintessence $w$CDM model with $H(z)\sim H_{wCDM}(z)$ at background level. In conjunction with $\Lambda$CDM, we test the models using a pack of recent datasets like that of the ``Gold 2018'' growth data, the best-fit Planck2018/$\Lambda$CDM parameters on the Cosmic Microwave Background (CMB), the Baryon Acoustic Oscillations (BAO) measurements, the Pantheon Supernovae type Ia and the Hubble parameter data with redshift ranging from $0.01 < z < 2.3$. Performing the Akaike Information Criterion (AIC) to ascertain the statistical viability of the model from Jeffreys' scale, we apply a joint likelihood analysis to the data with the Markov Chain Monte Carlo (MCMC) method. We find that the present model is in very good agreement with observations with a close statistical equivalence with the $\Lambda$CDM and $w$CDM cosmologies at 1-$\sigma$ level. We also show that a mild alleviation of the $\sigma$ tension between the growth amplitude factor and the matter content $(\sigma_8$-$\Omega_m)$ of the observations from CMB and Large Scale Structure (LSS) probes. A comparison of the aforementioned full pack of data in MCMC chains is made with the resulting MCMC from Pantheon SNIa+$H(z)$ in order to analyse the sensitivity of the models and how they respond to a cosmography analysis on the evolution of $H(z)$ and the deceleration parameter $q(z)$. In this sense, we find that only the $\beta$-model can be unaffected to the variations of the previous datasets due to its several minima in the likelihood (degeneracies) of the related parameters with an overall percentage relative difference only up to 4$\%$.

Necrotic enteritis (NE) is an intestinal disease that results in poor performance, inefficient nu-trient absorption, and has a devastating economic impact on poultry production. This study evaluated the effects of a saponin-based product (Clarity Q [CQ]) during a NE challenge. A to-tal of 1,200 male chicks were randomly assigned to four dietary treatments (10 pens/treatment; 30 birds/pen): treatment 1 (NC): a non-medicated corn-soybean basal diet; treatment 2 (PC) NC + 50 g/metric ton (MT) of Bacitracin methylene disalicylate (BMD); treatments 3 (CQ15) and 4 (CQ30) NC + 15 and 30 g/MT, respectively. On day (d) of placement, birds were challenged by a coccidia vaccine to induce NE. On d 8, 14, 28, and 42, performance parameters were measured. On d 8, three birds/pen were necropsied for NE lesions. On d 8 and d 14, jejunum samples from one bird/pen were collected for mRNA abundance of tight junction proteins and nutrient trans-porter genes. Data were analyzed in JMP (JMP Pro, 16) and significance (P ≤ 0.05) between treatments identified by Fisher’s least significant difference (LSD) test. Compared to PC and NC, CQ15 had higher average daily gain (ADG), while CQ30 had lower average daily feed in-take (ADFI) and feed conversion ratio (FCR). NE lesions in the duodenum were lower in CQ15 compared to all other treatments. On d 8, mRNA abundance of CLDN1, CLDN5, AMPK, PepT2, GLUT2, and EAAT3 were significantly greater in CQ30 (P < 0.05) compared to both PC and NC. On d 14, mRNA abundance of ZO2 and PepT2 was significantly lower in PC when compared to all treatments, while that of ANXA1, JAM3, and GLUT5 was comparable to CQ15. In summary, adding Clarity Q to broiler diets has the potential to alleviate adverse effects caused by this enteric disease by improving performance, reducing intestinal lesions, and positively modulating the mRNA abundance of various tight junction proteins and key nutrient transporters during peak NE infection.

Onion is one of the most economically and nutritionally important vegetable crops in West Africa. However, high-yielding varieties that are accessible to farmers remain scarce. Onion lines from the World Vegetable Center’s Allium program were evaluated during the cool and dry season from September to March for three years to identify adapted onion lines suitable for sustainable intensi-fication of production systems in Northern Ghana and Southern Mali. Trials were implemented in the Upper East and Northern Regions of Ghana and in two districts in the Sudan savanna zones of Mali (Bougouni and Koutiala). Nine onion lines, including a check variety were assessed for yield stability using a randomized complete block design. The trials were carried out in “technology parks” under the joint management of farmers and researchers. Onion bulb weight was recorded for each plot after harvest. Separate analyses of variances were performed for each location and season. Analysis of variance of combined locations, seasons and lines was made to determine the most stable varieties using the line-superiority measure and ecovalence stability coefficients. Results indicated that lines AVON1310 and AVON1325 were most stable for yield performance over lo-cations and seasons. From the genotype main effects and genotype-by-environment interaction (GGE) biplot, the best performing lines were AVON1310 (33.32 t.h-1), AVON1308 (28.81 t.h-1) and AVON1325 (31.68 t.h-1). These lines are potential candidates for sustainable intensification of onion production in Ghana and Mali.

This study examines the improvement in coupled intercomparison project phase six (CMIP6) models against the predecessor CMIP5 in simulating mean and extreme precipitation over the East Africa region. The study compares the climatology of the precipitation indices simulated by the CMIP models with the CHIRPS dataset using robust statistical techniques for 1981 – 2005. The results display the varying performance of the general circulation models (GCMs) in the simulation of annual and seasonal precipitation climatology over the study domain. CMIP6-MME shows improved performance in the local annual mean cycle simulation with a better representation of two peaks, especially the MAM rainfall relative to its predecessor. Moreover, simulation of extreme indices is well captured in CMIP6 models relative to its predecessor. The CMIP6-MME performed better than the CMIP5-MME with lesser biases in simulating SDII, CDD, and R20mm over East Africa. Remarkably, most CMIP6 models are unable to simulate extremely wet days (R95p). A few CMIP6 models (e.g., NorESM2-MM and CNRM-CM6-1) depicts robust performance in reproducing the observed indices across all analyses. Conversely, OND season shows the overestimation of some indices (i.e., R95p, PRCPTOT), except for SDII, CDD, and R20mm. Consistent with other studies, the mean ensemble performance for both CMIP5/6 shows better performance due to the cancellation of some systematic errors in the individual models. Generally, the CMIP6 depicts improved performance in the simulation of MAM season akin CMIP5 models. However, the new model generation is still marred with uncertainty, thereby depicting substandard performance over the East Africa domain. This calls for further investigation of attribution studies into the sources of persistent systematic biases and a prerequisite for identifying individual models with robust features that can accurately simulate observed patterns for future usage.

Steganography is the branch of cryptology that deals with concealing information inside another information. it’s prefer over cryptography as it hides a message inside another innocent looking message, while cryptography shows scrambled message that might arouse attention of an attacker, however the challenges in steganography is the modification of carrier that causes some abnormalities which is detectable and often the methods are not optimize. This paper presents a novel approach in cryptography and steganography, which utilizes mathematical concept of bits combination to optimize time of transmission using sets of multiple transmitter, and receiver’s addresses where each abstractly represents a bits combination without itself modified. In addition, the paper introduces a concept of dynamical clockwise and anti-clockwise rotation of bits combination over addresses after every transmission to reinforce resistivity against steganalysis.

In California, water is a perennial concern. As competition for water resources increases due to growth in population, California’s tree nut farmers are committed to improving the efficiency of water used for food production. There is an imminent need to have reliable methods that provide information about the temporal and spatial variability of crop water requirements, which allow farmers to make irrigation decisions at field scale. This study focuses on estimating the actual evapotranspiration and crop coefficients of an almond and pistachio orchard located in Central Valley (California) during an entire growing season by combining a simple crop evapotranspiration model with remote sensing data. A dataset of the vegetation index NDVI derived from Landsat-8 was used to facilitate the estimation of the basal crop coefficient (Kcb), or potential crop water use. The soil water evaporation coefficient (Ke) was measured from microlysimeters. The water stress coefficient (Ks) was derived from airborne remotely sensed canopy thermal-based methods, using seasonal regressions between the crop water stress index (CWSI) and stem water potential (Ystem). These regressions were statistically-significant for both crops, indicating clear seasonal differences in pistachios, but not in almonds. In almonds, the estimated maximum Kcb values ranged between 1.05 to 0.90, while for pistachios, it ranged between 0.89 to 0.80. The model indicated a difference of 97 mm in transpiration over the season between both crops. Soil evaporation accounted for an average of 16% and 13% of the total actual evapotranspiration for almonds and pistachios, respectively. Verification of the model-based daily crop evapotranspiration estimates was done using eddy-covariance and surface renewal data collected in the same orchards, yielding an r² >= 0.7 and average root mean square errors (RMSE) of 0.74 and 0.91 mm day^-1 for almond and pistachio, respectively. It is concluded that the combination of crop evapotranspiration models with remotely-sensed data is helpful for upscaling irrigation information from plant to field scale and thus may be used by farmers for making day-to-day irrigation management decisions.

Let R be a commutative ring and m, n be positive integers. We define a proper submodule N of an R-module M to be (m,n)-closed if for r∈R and b∈M, r^{m}b∈N implies rⁿ∈(N:_{R}M) or b∈N. This class of submodules lies properly between the classes of prime and primary submodules. Many characterizations, properties and supporting examples concerning this class of submodules are provided. The notion of (m,n)-modules is introduced and characterized. Furhermore, the (m,n)-closed avoidance theorem is proved. Finally, the (m,n)-closed submodules in amalgamated modules are studied.

In thermodynamic theory, free energy (i.e., available energy) is the concept facilitating the combined applications of the theory’s two fundamental laws, the first and the second laws of thermodynamics. The critical step was taken by Kelvin, then by Helmholtz and Gibbs— that in natural processes, free energy dissipates spontaneously. With the formulation of the second law of entropy growth, this may be referred to as the dissymmetry proposition manifested in the spontaneous increase of system/environment-entropy towards equilibrium. Because of Kelvin’s pre-entropy-law formulation of free energy, our concept of free energy is still defined, energy-centrally, as body’s internal energy or enthalpy, subtracted by energy that is not available within a framework on the premise of primacy of energy, in which free energy dissipates spontaneously and universally. This primacy of energy is called into question because the driving force to cause a system’s change is the purview of the second law. This paper makes a case for an engineering thermodynamics framework, instead, to be based on the premise of the primacy of dissymmetry over free energy. With Gibbsian thermodynamics undergirded with dissymmetry proposition and engineering thermodynamics with the dissymmetry premise, the two branches of thermodynamics are unified to become classical thermodynamics.

A defining feature of a productive infection is the co-opting of host cell resources for viral replication. Despite their repertoire of molecular functions, viruses subvert host defenses to take control of cellular factors such as RNA binding proteins (RBPs). RBPs are involved in virtually all steps of mRNA life forming ribonucleoprotein complexes (mRNPs) in a highly ordered and regulated process to control RNA fate and stability in the cell. Thus, the hallmark of this viral takeover is to reshape RNA fate in the cell to modulate host gene expression and evade immune responses. Here we provide an extensive review of work in this area, particularly how the host-viral interplay influences RBP functions to modulate the host cell. Overall, in this review, we highlight the myriad of ways RBPs can regulate RNA stability in either a pro-viral or antiviral manner by gathering novel insights gained from research studies in this field.

This study analyses the detection efficiency of the Worldwide Lightning Location Network (WWLLN) of sensors over Spain, a comparison is made with the Meteorological Spanish Agency (AEMET) Lightning Detection Network. The WWLLN operates a planetary distributed network of Very Low Frequency (VLF) antennas which detect lightning VLF signals around the Earth. Very high currents from lightning strokes radiate strong VLF signals in the band 6-22 kHz, which are detected up to 10,000 km, therefore WWLLN receiving sensors can be sparsely spaced. However the detection capability of VLF signals depends on the environment, and clean areas with a good ground and no metal parts around must be selected for proper reception. For the area of Spain and Portugal we had two WWLLN sensors in 2012, and three sensors later on for the data of 2020, 2021 and 2022. The sensors in Iberian Peninsula are at a distance of around 760 km; that is very close in comparison with other WWLLN sensors in the Earth which are around 5.000-15.000 km. The WWLLN sensors send the timing of the detection to the central sensor where the location of the lightning is determined with an improved algorithm when a mini-mum of 5 sensors detect the VLF signal. We show that detection efficiency was excellent and consistent with previous studies. Lightning location data from 1st January 2012 to 30st April 2012 from AEMET was used to analyze time and space shared events with the WWLLN network with 0.5s time difference and 20 km distance. The results improved in 2020, 2021 and 2022. More than 40,000 lightning strikes were analyzed in the present work, and we found a detection efficiency > 38%.

The climate change impacts on some regions of the planet faster and stronger. These areas are known as the hot spots for climate change and Cyprus (Nicosia) in the Mediterranean is one of these spots. This paper aims to analyze the significant changes of atmospheric aerosol characteristics in 2019 and during the extreme event of 25 April 2019. We study the aerosol optical thickness (AOT), Ångström exponent, single scattering albedo, refractive index (imaginary and real parts), size, and vertical distribution of aerosol particles during the event of a high atmospheric aerosol contamination over Nicosia in details. For this purpose, we used the ground-based lidar, observations of the sun-photometer AERONET Nicosia station, satellite products from the Moderate Resolution Imaging Spectroradiometer (MODIS), and back trajectories of air movements calculated using the Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT). On 23–25 April, according to lidar and sun-photometer observations, strong aerosol pollution over Nicosia was detected. On April 25, 2019, the AOT value exceeds 1.0 at λ = 440 nm. Analysis of the optical and microphysical characteristics supported that the pollution consists of mainly Saharan dust and partly urban aerosols. This assumption was confirmed by HYSPLIT backward trajectories and MODIS images where air masses containing dust particles came from North Africa and from the Eastern part of Europe.

Telomeres are crucial structures that preserve genome stability. Their progressive erosion over rounds of DNA duplication determines senescence of cells and organisms. Telomere length homeostasis is critical for cancer development then telomere maintenance mechanisms are established targets in cancer treatment. Besides telomere elongation, telomere’s dysfunction impinges on intracellular signalling pathways, in particular DNA damage signalling and repair affecting cancer cell survival and proliferation. This review summarizes and discusses about the recent findings in anti-cancer drug development targeting different “telosome” components.

The present study analyzed seasonal (i.e., Dec-Jan [DJF] and June – August [JJA]) temperature change for the near (2025-2054) and far future (2070-2099) under SSP245, SSP370, and SSP585 scenarios over Pakistan. The anomalies, Mann-Kendall trend tests, Sequential Mann-Kendall trend test (SQMK), and probability density frequency (PDF) analysis were used to investigate future mean temperature variations. The DJF season projected higher increase in temperature in the northern (3.8 ^oC, 5.1 ^oC and 6.5 ^oC), followed by central regions (3.8 ^oC, 4.9 ^oC and 6.4 ^oC) under SSP245, SSP370 and SSP585 scenarios, respectively. The central region is likely to record significant increase in JJA (3.0 ^oC, 4.4 ^oC and 5.4 ^oC) mean temperature in far future under the given SSP scenarios. Compared to historical (PDF), the far future DJF temperature changes revealed significant higher warming over northern, central and then over southern regions under most of SSP scenarios. The southern regions are projected to possible rise in far future JJA temperatures by 2.7 ^oC, 3.3 ^oC and 4.3 ^oC, under SSP245, SSP370 and SSP585, respectively. The PDFs for JJA further verify the highest positive abrupt shift in temperature across the central region and then southern region. The future diverse seasonal temperature changes supports further examination of the associated mechanisms and factors responsible for temperature changes to address climate change.