It is proved that there exist two odd prime numbers, p_i and p_j , such that p_i + p_j = 2r + 2(r ⩾ 2), where p_n denote the n-th odd prime number, 1 ⩽ i, j ⩽ n. By the theory of generating functions, we prove that there exist two positive integers, h_i and h_j , such that h_i + h_j = r(r ⩾ 2), where h_n = (p_n − 1)/2，(p_n ⩾ 3).Then we complete the proof.

In the paper, the authors consider the generating functions of the Hermite polynomials and their squares, present explicit formulas for higher order derivatives of the generating functions of the Hermite polynomials and their squares, which can be viewed as ordinary differential equations or derivative polynomials, find differential equations that the generating functions of the Hermite polynomials and their squares satisfy, and derive explicit formulas and recurrence relations for the Hermite polynomials and their squares.

This paper presents the symmetries of differential equations associated with one-variable and Bivariate Hermite polynomials by proposing a representation of Lie algebra for these differential operators. Applying the Baker-Campbell-Hausdorff formula to these algebras, results in new relations and generating functions in one-variable and Bivariate Hermite polynomials. A general form of representation for other orthogonal polynomials such as Laguerre polynomials is introduced.

The aim of this study was to investigate the physicochemical characterization and biological activities of chitosan (CH) based composite films with the incorporation of chestnut flower essential oil (CFEO). The composite films were prepared by casting method and characterized in terms of structural, morphological and mechanical properties via FT-IR, XRD, UV, SEM and TGA. The results proved the significantly increased water vapor permeability (WVP), heat resistance, antibacterial and antioxidant capabilities of CH-CFEO films. The incorporation of CH and CFEO enhanced the UV blocking, which made the film shield almost all UV light. Films with the tensile strength of 6.37 ± 0.41 MPa and elongation at break of 22.57 ± 0.35% were got with 6 mg mL-1 CFEO. Subsequently, the fruit preservation experiments also confirmed that the composite films could effectively extend the shelf life of bananas through their excellent water vapor and oxygen barrier. These desirable performances enable our newly developed composite films to be a remarkable packaging material to solve the fresh fruit preservation dilemma.

The paper describes a method of solving some stochastic processes using generating functions. A general theorem of generating functions of a particular type is derived. A generating function of this type is applied to a stochastic process yielding polynomial time algorithms for certain partitions. The method is generalized to a stochastic process describing a rather general linear transform. Finally, the main idea of the method is used in deriving a theoretical polynomial time algorithm to the knapsack problem.

The present paper discusses a study of a class of Charlier matrix polynomials and its generalized analogue. Certain generating matrix functions, recurrence matrix relations, matrix differential equation, summation formulas and many new results have been discussed for these matrix polynomials. Weisner's group theoretic method is used to obtain matrix generating relations for Charlier matrix polynomials and the details of this method were given in this paper. Finally, we will discuss only briefly the procedure followed.

We prove an analog of the removable singularity theorem for bounded harmonic functions on stratified sets. The harmonic functions are understood in the sense of the soft Laplacian. The result can become one of the main technical components for extending the well-known Poincaré–Perron’s method of proving the solvability of the Dirichlet problem for the soft Laplacian.

In this study, based on a new quantum integral identity, the authors establish some quantum estimates of Hermite-Hadamard type inequalities for convex functions. These results generalize and improve some known results given in literatures.

Hydrogen has a leading role in accomplishing a net zero green-house gas emission future. Today’s challenge is producing green hydrogen to cover the fuel demand of transportation and industry, to gain independence from fossil fuels. This review’s goal is to demonstrate critically the existing methods of biomass treatment and assess their ability to scale up. Biomass is an excellent hydrogen carrier and biomass-derived processes are the main target for hydrogen production as it is an innovative pathway to green hydrogen production. Comparing the existing processes, thermochemical treatment is found to be far more evolved than biological or electrochemical treatment especially with regard to scaling prospects.

Elevated carbon dioxide (eCO₂) stimulates wheat grain yield, but simultaneously reduces protein (N) concentration. Also other essential nutrients are subject to change. This study is a comprehensive synthesis of wheat experiments with eCO₂, estimating effects on N, minerals (B, Ca, Cd, Fe, K, Mg, Mn, Na, P, S, Zn), and starch. Analysis was made by i) deriving response functions for the relative effect on element concentration in relation to CO₂ concentration, ii) meta-analysis to test the magnitude and significance of observed effects, and iii) relating CO₂ effects on minerals to effects on N and grain yield. Responses range from zero to strong negative effects of eCO₂ on mineral concentration, with largest reductions for the nutritionally important elements N, Fe, S, Zn and Mg. Together with the positive but small and non-significant effect on starch concentration, the large variation in effects suggests that CO₂-induced responses cannot be explained by a simple dilution model. To explain the observed pattern, uptake and transport mechanisms may have to be considered, along with the link of different elements to N uptake. Our study shows that eCO₂ has a significant effect on wheat grain stoichiometry, with implications for human nutrition in a world of rising CO₂.

In this paper, we have established Hermite-Hadamard inequalities for r-preinvex functions via fractional integrals.

In this work, Gaussian Tribonacci functions are defined and investigated on the set of real numbers $\mathbb{R},$ \textit{i.e}., functions $f_{G}$ $:$ $\mathbb{R}\rightarrow \mathbb{C}$ such that for all $% x\in \mathbb{R},$ $n\in \mathbb{Z},$ $f_{G}(x+n)=f(x+n)+if(x+n-1)$ where $f$ $:$ $\mathbb{R}\rightarrow \mathbb{R}$ is a Tribonacci function which is given as $f(x+3)=f(x+2)+f(x+1)+f(x)$ for all $x\in \mathbb{R}$. Then the concept of Gaussian Tribonacci functions by using the concept of $f$-even and $f$-odd functions is developed. Also, we present linear sum formulas of Gaussian Tribonacci functions. Moreover, it is showed that if $f_{G}$ is a Gaussian Tribonacci function with Tribonacci function $f$, then $% \lim\limits_{x\rightarrow \infty }\frac{f_{G}(x+1)}{f_{G}(x)}=\alpha \ $and\ $\lim\limits_{x\rightarrow \infty }\frac{f_{G}(x)}{f(x)}=\alpha +i,$ where $% \alpha $ is the positive real root of equation $x^{3}-x^{2}-x-1=0$ for which $\alpha >1$. Finally, matrix formulations of Tribonacci functions and Gaussian Tribonacci functions are given. In the literature, there are several studies on the functions of linear recurrent sequences such as Fibonacci functions and Tribonacci functions. However, there are no study on Gaussian functions of linear recurrent sequences such as Gaussian Tribonacci and Gaussian Tetranacci functions and they are waiting for the investigating. We also present linear sum formulas and matrix formulations of Tribonacci functions which have not been studied in the literature.

We prove that a diffeological space is diffeomorphic to the categorical join of any generating family of plots.

This paper investigates the feasibility of a backend design for real-time, multiple-channel processing digital phased array system, particularly for high-performance embedded computing platforms constructed of using general purpose digital signal processors. Frist, we obtained the lab-scale backend performance benchmark from simulating beamforming, pulse compression, and Doppler filtering based on MicroTCA chassis using Serial RapidIO protocol in backplane communication. Next, a field-scale demonstrator of a multifunctional phased array radar is emulated by using the similar configuration. Interestingly, the performance of a barebone design is compared to that of emerging tools that systematically take advantage of parallelism and multicore capabilities, including Open Computing Language.

In this paper, we present sums and partial sums of Horadam sequences via generating functions which extends a recent result of Prodinger.

In this study, a new methodology based on the circuit approach is employed to obtain renewable electric energy. Although a voltage source and a current source generate voltage and current, respectively, they work only when they receive electric power, which is the product of voltage and current. However, this paper proposes a circuit with a voltage source, a current source and a super-condenser connected in series, in which the voltage source provides voltage for the current source and the current source provides current for the voltage source. Resultantly, electric power is generated both at the voltage and current sources, and the energy (i.e., the electric power) from the current source is converted to the charging energy in the super-condenser. Herein, we describe the method for charging the super-condenser using a voltage source and a current source. To confirm the abovementioned concept, we conducted experiments, and the energy was successfully produced, with high reproducibility. Finally, the brief mechanism for the energy conversion, a schematic method for reducing the capacitances of stored batteries, and the significance of this study are described.

The growing need to use renewable sources and the current difficulty in spreading the electricity grid in a widespread manner raise the question of how to respond to the need for more electricity immediately. The idea behind this study is to power a horizontal axis wind turbine with the air flow generated for cooling a stationary internal combustion engine. The power extracted from this solution is significantly lower than that of the internal combustion engine (about 0.3%) and could be advantageous only in limited contexts. Installation costs are limited because many elements deriving from wind variability can be removed or simplified.

Plants produce a diverse portfolio of sesquiterpenes that are important in their response to herbivores and the interaction with other plants. Their biosynthesis from farnesyl diphosphate depends on the sesquiterpene synthases. Here, we investigate to what extent metabolic pathways can be reconstructed just from knowledge of the final product and the reaction mechanisms catalyzed by sesquiterpene synthases. We use the software package MedØlDatschgerl (MØD) to generate chemical networks and elucidate pathways contained in them. As examples, we successfully consider the reachability of the important plant sesquiterpenes β-caryophyllene, α-humulene, and β-farnesene. We also introduce a graph database to integrate simulation results with experimental biological evidence for selected predicted sesquiterpenes biosynthesis.

Automatic methods for constructing navigation routes do not fully meet all requirements. The aim of this study was to modify the methodology for generating indoor navigation models based on the Medial Axis Transformation (MAT) algorithm. The simplified method for generating corridor axes relies on the Node-Relation Structure (NRS) methodology. The axis of the modeled structure (corridor) is determined based the points of the middle lines intersecting the structure (polygon). The proposed solution involves a modified approach to the segmentation of corridor space. Traditional approaches rely on algorithms to construct Triangulated Irregular Networks (TINs) by Delaunay triangulation or algorithms for generating Thiessen polygons known as Voronoi diagrams (VDs). In this study, both algorithms were used in the segmentation process. The edges of TINs intersect structures. Selected midpoints on TIN edges, which are located in the central part of the structure, are used to generate VDs. Polygon VDs segment corridor structures. The identifiers or structure nodes are the midpoints on TIN edges rather than the calculated centroids. The generated routes are not zigzag lines, and they approximate natural paths. The main advantage of the proposed solution is its simplicity which can be attributed to the use of standard tools for processing spatial data in a geographic information system.

The Medi-test system we developed was motivated by the large number of resources available for the medical domain, as well as the number of tests needed in this field (during and after the medical school) for evaluation, promotion, certification, etc. Generating questions to support learning and user interactivity has been an interesting and dynamic topic in NLP since the availability of e-book curricula and e-learning platforms. Current e-learning platforms offer increased support for student evaluation, with an emphasis in exploiting automation in both test generation and evaluation. In this context, our system is able to evaluate a student’s academic performance for the medical domain. Using as input medical reference texts and supported by a specially designed medical ontology, Medi-test generates different types of questionnaires for Romanian language. The evaluation includes 4 types of questions (multiple-choice, fill in the blanks, true/false and match), can have customizable length and difficulty and can be automatically graded. A recent extension of our system also allows for the generation of tests which include images. We evaluated our system with a local testing team, but also with a set of medicine students, and user satisfaction questionnaires showed that the system can be used to enhance learning.

In the paper, by the Faά di Bruno formula, several identities for the Bell polynomials of the second kind, and an inversion theorem, the authors simplify coefficients of two families of nonlinear ordinary differential equations for the generating function of the Catalan numbers and discover inverses of fifteen closely related lower triangular integer matrices.

The article proposes a mathematical model for creating playlists based on the emotional utility of the consumer, aiming to maintain high user interest in music streaming platforms (Lugos Abarca, 2024). The proposed method follows these steps: first, it calculates the MEEPE of Songs on the digital platform; subsequently, it quantitatively defines the Consumer's MEEPI before exposure to music; then, it operates the MEEPE of the Songs with the consumer's initial MEEPI using the known resolution process (Lugos Abarca, 2023); finally, it employs an emotional utility function to determine possible levels of emotional satisfaction and establish the playback order. This results in the creation of an efficient theoretical model. It is recommended to expand the computational study of the model in future research by using a broader set of songs and considering various initial MEEPI of the consumer. The article's originality lies in its ability to predict, quantitatively and theoretically, the level of satisfaction a music consumer could experience when listening to a playlist.

The article presents the Base Point Split (BPSplit) algorithm for generating a polygon skeleton based on sets of vector data describing lakes and rivers. A key feature of the BPSplit algorithm is that it is dependent on base points representing the source or mouth of a river or a stream. The input values of base points determine the shape of the resulting skeleton. Various skeletons can be generated with the use of different base points. Base points are applied to divide polygon boundaries into segments. Segmentation supports the selection of TIN edges inside polygons. The midpoints of selected TIN edges constitute a basis for generating a skeleton. The algorithm handles polygons with numerous holes, and it accounts for all holes. This article proposes a method for modifying a complex skeleton with numerous holes. In the discussed approach, skeleton edges that do not meet the preset criteria (e.g. that the skeleton is to be located between holes in the center of the polygon), are automatically removed. A simple algorithm for smoothing zigzag lines was proposed.

In personalized healthcare, an ecosystem for the manipulation of reliable and safe private data should be orchestrated. This paper describes a first approach for the generation of fake electrocardiograms (ECGs) based on Generative Adversarial Networks (GANs) with the objective of anonymizing users’ information for privacy issues. This is intended to create valuable data that can be used both, in educational and research areas, while avoiding the risk of a sensitive data leakage. As GANs are mainly exploited on images and video frames, we are proposing general raw data processing after transformation into an image, so it can be managed through a GAN, then decoded back to the original data domain. The feasibility of our transformation and processing hypothesis is primarily demonstrated. Next, from the proposed procedure, main drawbacks for each step in the procedure are addressed for the particular case of ECGs. Hence, a novel research pathway on health data anonymization using GANs is opened and further straightforward developments are expected.

The Chromogranin A (CgA)-derived peptide Catestatin (CST: hCgA352-372) is highly conserved (>90% in 90% species) in mammalian species. The highest-evolved primates show 58.8% similarity with the lowest-evolved monotremes. CST was initially identified as a physiological brake in catecholamine secretion by inhibiting nicotinic-cholinergic signaling. CST also inhibits desensitization of catecholamine secretion, indicating that CST can act both as a cholinergic antagonist (short-term) and as a cholinergic agonist (long-term). The long-term effect sustains catecholamine secretion during stressful situations. CST is now established as a pleiotropic hormone: it affects the cardiovascular system by lowering blood pressure and cardiac contractility, enhancing baroreflex sensitivity, increasing heart rate variability, and promoting angiogenesis; and it increases insulin sensitivity by reducing inflammation, inhibiting hepatic glucose production, attenuating endoplasmic reticulum stress, and inducing glycogen production. The present review will highlight the important direct and indirect effects of CST, CST1-15 (aka cateslytin), D-CST1-15 (where L-amino acids were changed to D-amino acids), and human variants of CST (Gly364Ser-CST and Pro370Leu-CST) on microbial growth inhibition and their potential as therapy for antibiotic-resistant pathogenic microbes.

This study focuses on a new class of functions called sub-b-s-preinvex, that is a generalization of sub-b-s-convex and preinvex functions, and discusses some of their properties. A new sub-b-s-preinvex programming is introduced and the sufficient conditions of optimality under this type of function is established.

The allosteric SERCA (Sarcoplasmic/Endoplasmic Reticulum Ca2+-ATPase) activator CDN1163 has been recently added to the group of pharmacological tools for probing SERCA function. We chose to investigate the effects of the compound on T lymphocyte Ca2+ stores, using the well-described Jurkat T lymphocyte as a reliable cell system for Ca2+ signaling pathways. Our study identified the lowest concentrations of the SERCA inhibitors thapsigargin (TG) and 2,5-di-(tert butyl)-1,4-benzohydroquinone (tBHQ) capable of releasing Ca2+, permitting the differentiation of the TG-sensitive SERCA 2b Ca2+ store from the tBHQ-sensitive SERCA 3 Ca2+ store. We proceeded to test the effects of CDN1163 on Ca2+ stores, examining specific actions on the SERCA 2b and SERCA 3 Ca2+ pools using our low dose SERCA blocker regimen. In contrast to previous work, we find CDN1163 exerts complex time-sensitive and SERCA isoform-specific actions on Ca2+ stores. Surprisingly, short-term exposure (0-30 minutes) to CDN1163 perturbs T cell Ca2+ stores by suppressing Ca2+ uptake with diminished Ca2+ release from the SERCA 2b-controlled store. Concomitantly, we find evidence for a SERCA-activating effect of CDN1163 on the SERCA 3 regulated store, given the observation of increased Ca2+ release inducible by low dose tBHQ. Intriguingly, longer-term (>12 hours) CDN1163 exposure reversed this pattern, with increased Ca2+ release from SERCA 2b-regulated pools, yet decreased Ca2+ release responses from tBHQ-sensitive SERCA 3 pool. Our results reveal differential effects of CDN1163 on Ca2+ stores regulated by distinct SERCA isoforms, prompting the need for careful interpretation of the compound’s effects, particularly in cells expressing multiple SERCA isoforms.

The increasing demand for water resources in urban areas, such as Bangladesh, due to population growth is a significant concern. One potential solution under consideration is the use of air conditioning (AC) condensate water. A study conducted at the European University of Bangladesh (EUB) focused on assessing the quality and quantity of AC condensate water from various systems. The results indicate that the collected water generally adhered to the quality standards established for drinking and household use in Bangladesh. Parameters such as pH (averaging 6.8), turbidity (1.08 NTU), total dissolved solids (TDS) (averaging 219 mg/L), iron content (0 mg/L), alkalinity (averaging 41.67 mg/L), arsenic (0 mg/L), chemical oxygen demand (COD) (averaging 3.67 mg/L), biochemical oxygen demand (BOD) (averaging 1.33 mg/L), chloride content (averaging 30.77 mg/L), and other factors were evaluated. Moreover, the AC units at EUB, varying in cooling capacity (1 ton, 2 tons, and 4 tons), produced substantial monthly volumes of 96, 177, and 354 liters of condensate water, respectively. This underscores the potential of AC condensate water as a valuable resource for addressing urban water scarcity. As a result, there is a pressing need for local decision-makers and policymakers to establish well-defined guidelines for the effective utilization of AC condensate water to mitigate water scarcity issues in urban areas.

In this paper, the elemental construct of an I-shaped fin cooling a heat generating volume is studied through the entropy production perspective. Using the constructal design method framework with entropy production minimization as an objective leads to different optimal shape ratio, different from the ones obtained using the excess of temperature. Moreover, the optimal shape ratio evolution is not necessary the same for local entropy production minimization (excess of entropy production) and global entropy production (entropy produced in the whole area). Finally, an analysis on a possible dimensionless number is introduced for the study of constructal plates.

In response to ever-increasing concerns regarding ecological degradation and societal impact, numerous stakeholders such as non-governmental organisations, government officials, end-users, the mass media, and community activists have compelled business organizations, particularly multi-national companies to lessen harmful greenhouse gases emissions associated with their production activities. Energy sector is one of the biggest harmful greenhouse gases emission producer, hence, decision-makers within the energy sector are forced to promote and build environmental friendly and sustainable power generation plants. To this end, the concept of sustainability in the electricity sector has attracted so much attention from academics and industrial practitioners over the last three decades. Albeit, an important number of sustainability assessment frameworks for electricity generating technologies are found in the current literatures, three major drawbacks have emerged from those frameworks. Firstly, there is a lack of a holistic and comprehensive sustainability assessment framework for different power generation plants. Secondly, from economic aspect, the most used model (Levelised Cost of Electricity) to measure the cost performance of various electricity generating technologies is biased and is not inclusive enough, because, it only considers the capital, Operations and Maintenance, and fuel costs. Hence, snubbing crucial elements to business decision. Lastly, in the current literature, there is no a single sustainability assessment model that considers all the phases of electrical energy’s lifecycle. Considering these flaws, the novelty of this study is the development of a new, holistic theoretical sustainability assessment framework for power generation plants. The developed theoretical model includes 19 impact categories, 52 potential indictors, and 10 end points environmental, economic, and social aspects.

In this study we introduce the new classes $\mathcal{M}_{\alpha}(\sin)$ and $\mathcal{M}_{\alpha}(\cos)$ of $\alpha$-convex functions associated with sine and cosine functions. Also, we obtain the initial coefficient bounds for the first five coefficients of the functions that belong to these classes. Further, we determine the upper bound of Zalcman functional for the class $\mathcal{M}_{\alpha}(\cos)$ for the case $n=3$, showing that the Zalcman conjecture holds for this value. Moreover, the problem of the Fekete-Szeg\H{o} functional estimate for these classes is studied.

In this paper we give approximations to the Mittag-Leffler functions in terms of elementary functions using different methods. This allowed us to establish a practical method we called integerization principle. This principle states that many fractional nonlinear oscillators may be solved by means of the solution to some integer-order Duffing oscillator equation. The accuracy of the obtained results is illsutrated in concrete examples. Formulas for estimating the errors in the approximations are also provided.

Orthohepadnavirus causes chronic hepatitis in a broad range of mammals, including primates, cats, woodchucks, and bats. Hepatitis B virus (HBV) X protein inhibits type-I interferon (IFN) signaling, promoting HBV escape from the innate immune system to establish persistent infection. However, whether X proteins of Orthohepadnavirus viruses in the other species have similar inhibitory activity remains unknown. Here, we investigated the anti-IFN activity of 17 Orthohepadnavirus X proteins derived from various hosts. We observed conserved activity of Orthohepadnavirus X proteins in inhibiting TIR-domain-containing adaptor protein inducing IFN-β (TRIF)-mediated IFN-β signaling pathway through TRIF degradation. X proteins from domestic cat hepadnavirus (DCH), a novel member of Orthohepadnavirus, inhibited mitochondrial antiviral signaling protein (MAVS)-mediated IFNβ signaling pathway comparable with HBV X. These results indicate that inhibition of IFN signaling is conserved in Orthohepadnavirus X proteins.

Human activities (e.g., exploitation, utilization, and conservation) exert substantial impact on forest ecological functions (FEF). The human influence on FEF significantly varies across developmental stages, which are attributed to the temporal and spatial in nature. This study evaluates some notable FEF indices (FEFI) in the 448 counties within the Yellow River basin (YRB) using panel data from the Seventh to Ninth National Forest Inventory. Data analysis involves employing the residual trends, geographical and temporal weighted regression. Results indicate that, firstly, the overall forest ecological function in the YRB is moderate to inferior, with superior FEF in counties endowed with more natural forest resources. Afforestation demonstrates a short-term improvement, but its effectiveness diminishes over time. Secondly, the positive spatial correlation is stronger among counties, characterized by both high-high and low-low agglomeration effects. Scattered planting, simple stand structure, and concentrated harvesting of forests at the identical stand ages hinder the formation of complex and large-scale FEF agglomerations. Thirdly, significant spatial-temporal differences exist in the impact of human activities on FEF. In the upper reaches of the basin, increased vegetation coverage through agricultural and forestry production benefited FEF, however, some over-exploitation of forests and grasslands is observed there. In the middle reaches, the economic development, expanding population and the greening activities help to improve FEF effectively, but excessive water using in agricultural production brought more difficulties to FEF improvement. In the lower reaches of the basin, improved wastelands and forest protection positively influence FEF. This study recommends that county governments should prioritize forest management with multi-species and multi-layered complex forests. Each county should define its position in regional development and ecological protection, considering the potential impacts on neighboring regions. This holistic approach promotes more effective integrated regional management.

A new set of basis functions is presented. The foundation in mathematics is established. To reconstruct a signal, it is compared to the Fourier basis functions. The M-basis functions' potential applications are also presented.

The developmental phase of adolescence is characterized by a multitude of neurocognitive and psychosocial changes and is therefore considered one of the most critical developmental periods of life. Experimentation on the use of substances often begins in adolescence and so does the addiction process. Most research in human subjects shows that chronic cannabis abuse is the cause of the impairment of some cognitive functions, affecting the performance on divided attention, verbal memory and working memory. In this study, we wanted to investigate how the abuse of cannabis (chronic, occasional and absence use) can influence global cognitive functioning, also through executive functions. From the statistical analyzes of our study, it emerges that the group of subjects who use chronic cannabis (group 1) has a significant drop in working memory tasks compared to the group that does not use it (group 3). In addition, the goal of future studies by our group is to verify the permanent alteration of cognitive processes affected through revaluations with calendar follow-up (controlled).

We show that if $f$ is a non-negative superquadratic function, then $A\mapsto\mathrm{Tr}f(A)$ is a superquadratic function on the matrix algebra. In particular, \begin{align*} \tr f\left( {\frac{{A + B}}{2}} \right) +\tr f\left(\left| {\frac{{A - B}}{2}}\right|\right) \leq \frac{{\tr {f\left( A \right)} + \tr {f\left( B \right)} }}{2} \end{align*} holds for all positive matrices $A,B$. In addition, we present a Klein's inequality for superquadratic functions as $$ \mathrm{Tr}[f(A)-f(B)-(A-B)f'(B)]\geq \mathrm{Tr}[f(|A-B|)] $$ for all positive matrices $A,B$. It gives in particular improvement of Klein's inequality for non-negative convex function. As a consequence, some variants of the Jensen trace inequality for superquadratic functions have been presented.

The ability of deep learning to process vast data and uncover concealed malicious patterns has spurred the adoption of deep learning methods within the cybersecurity domain. Nonetheless, a notable hurdle confronting cybersecurity researchers today is the acquisition of a sufficiently large dataset to train deep learning models effectively. Privacy and security concerns associated with using real-world organization data have made cybersecurity researchers seek alternative strategies, notably focusing on generating synthetic data. Generative Adversarial Networks (GANs) have emerged as a prominent solution, lauded for their capacity to generate synthetic data spanning diverse domains. Despite their widespread use, the efficacy of GANs in generating realistic cyber attack data remains a subject requiring thorough investigation. Moreover, the proficiency of deep learning models trained on such synthetic data to accurately discern real-world attacks and anomalies poses an additional challenge that demands exploration. This paper delves into essential aspects of generative learning, scrutinizing their data generation capabilities, and conducts a comprehensive review to address the above questions. Through this exploration, we aim to shed light on the potential of synthetic data in fortifying deep learning models for robust cybersecurity applications.

Protein-protein interactions (PPIs) are associated with various diseases; hence, they are important targets in drug discovery. However, the physicochemical empirical properties of PPI-targeted drugs are distinct from those of conventional small molecule oral pharmaceuticals, which adhere to the ”rule of five (RO5).” Therefore, developing PPI-targeted drugs using conventional methods, such as molecular generation models, is difficult. In this study, we propose a molecule generation model based on deep reinforcement learning, specialized for generating PPI inhibitors. By introducing a scoring function that can represent the properties of PPI inhibitors, we successfully generated potential PPI inhibitor compounds. The generated virtual compounds possess the desired properties for PPI inhibitors, and show similarity to commercially available PPI libraries. These generated virtual compounds are freely available as a virtual library.

Currently there are strong and sustained growth trends observed in multi-disciplinary industrial technologies such as building-integrated photovoltaics and agrivoltaics, where renewable energy production is featured in building envelopes of varying degrees of transparency. Novel glass products can provide a combination of thermal energy savings and solar energy harvesting, enabled by either patterned-semiconductor thin-film energy converters on glass substrates, or by using luminescent concentrator-type approaches to achieve high transparency. Significant progress has been demonstrated recently in building integrated solar windows featuring visible light transmission of up to 70%, with electric power outputs of up to Pmax ~ 30-33 Wp/m2. Several slightly different designs were tested during 2021-2023 in a greenhouse installation at Murdoch University in Perth, Western Australia. The objective of this paper is to report on the field performance of these PV windows in the context of agrivoltaics, and to provide some detail of the performance differences measured in several solar window designs related to their glazing structure materials. Methods for the identification and quantification of long-term field performance differences and energy generation trends in solar windows of marginally different design types are reported. The paper also aims to outline the practical application potential of these transparent construction materials in built environments, focussing on the measured renewable energy figures and seasonal trends observed during the long-term study.

Recent advances in deep learning technology have led to increased interest in text-to-image technology, which enables computers to create images from text by simulating the human process of forming mental images. The GAN-based text-to-image technology involves the extraction of features from input text, which are combined with noise and then used as input to a GAN that generates images that are similar to the original images through competition between the generator and discriminator. Although generating images from English text is a mature area of research, text-to-image technology based on multilingualism, such as Korean, is still in its early stages of development. Webtoon is a digital comic format that allows comics to be viewed online. The creation process for webtoons is divided into story planning, content/sketching, coloring, and background drawing. Since each stage of webtoon production requires human intervention, it is both time-consuming and expensive. As a result, deep learning technologies such as automatic coloring and automatic line drawing are being used to reduce human involvement. However, there is a shortage of technology that can assist authors with story creation in webtoon production. Therefore, this study proposes a multilingual text-to-image model capable of generating webtoon images when presented with multilingual input text. The proposed model employs Multilingual BERT to extract feature vectors for multiple languages, and trains a DCGAN in conjunction with the images. The experimental results demonstrate that the model can generate images that are similar to the original images when presented with multilingual input text after training.

A numerical approach for generating a limited number of water demand scenarios and estimating their occurrence probabilities in a Water Distribution Network (WDN) is proposed. This approach makes use of the demand scaling laws in order to consider the natural variability and spatial correlation of nodal consumptions. The scaling laws are employed to determine the statistics of nodal consumption as a function of the number of users and the main statistical features of the unitary user's demand. Besides, consumption at each node is considered to follow a Gamma probability distribution. A high number of groups of cross-correlated demands, i.e., scenarios, for the entire network were generated using Latin Hypercube Sampling (LHS) and the numerical procedure proposed by Iman and Conover. The Kantorovich distance is used to reduce the number of scenarios and estimate their corresponding probabilities, while keeping the statistical information on nodal consumptions. By hydraulic simulation, the whole number of generated demand scenarios was used to obtain a corresponding number of pressure scenarios on which the same reduction procedure was applied. The probabilities of the reduced scenarios of pressure were compared with the corresponding probabilities of demand.

Superantigens are unconventional antigens which recognise immune receptors outside the usual binding sites e.g. complementary determining regions (CDRs), to elicit a response within the target cell. T-cell superantigens crosslink T-cell receptors and MHC Class II molecules on antigen-presenting cells, leading to lymphocyte recruitment, induction of cytokine storms and T-cell anergy or apoptosis among many other effects. B-cell superantigens, on the other hand, bind immunoglobulin receptors on B-cells affecting opsonisation, IgG-mediated phagocytosis, and drive B-cells into apoptosis. Here, through a review of the structural basis for recognition of immune receptors by superantigens, we show that their binding interfaces share specific physicochemical characteristics when compared with other protein-protein interaction complexes. Given that antibody-binding superantigens have been exploited extensively in industrial antibody purification, these observations could facilitate further protein engineering to optimize the use of superantigens in this and other areas of biotechnology.

Suppose for n∈ ℕ, set A⊆ℝⁿ and function f∶A→ℝⁿ. If set A, using the Hausdorff outer measure, is measurable in the sense of Carathèodory; we want to find an extension of the expected value, w.r.t the Hausdorff measure, that's unique, finite and "natural" (defined on §2.3 & §2.4) for all f in a prevalent subset of ℝᴬ. The issue is current extensions of the expected value are finite for all functions in only a shy subset of ℝᴬ. The reason this issue wasn't resolved is mathematicians have not thought of the problem, focusing on application rather than generalization. Despite the lack of potential use, we'll attempt to solve the problem by defining a choice function---this shall choose a unique set of equivalent sequences of sets (Fₖ***) , where the set-theoretic limit of Fₖ*** is the graph of f; the measure Hʰ is the ℎ-Hausdorff measure, such for each k∈ℕ, 0 < Hʰ(Fₖ***) < +∞; and (fₖ*) is a sequence of functions where {(x,fₖ*(x))∶x∈ dom(Fₖ***)}=Fₖ***. Thus, the extended expected value of or E**[f,Fₖ***] is: ∀(ε>0)∃(N∈ℕ)∀(k∈N)(k≥N⇒1/Hʰ(dom(Fₖ***))∫dom(Fₖ*** )fₖ* dHʰ - E**[f,Fₖ***]<ε ) which should be unique, finite, and "natural" (defined on §2.3 & §2.4) for all f in a prevalent subset of ℝᴬ. Note we guessed the choice function using computer programming but we don’t use mathematical proofs due to the lack of expertise in the subject matter. Despite this, the biggest use of this research is the extension of the expected value is finite for "almost all" functions: this is easier to use in application when finding the "average" of functions covering an infinite expanse of space.

Executive functions comprise top-down cognitive processes that exert control over information processing, from acquiring information to issuing a behavioural response. These cognitive processes of inhibition, working memory and shifting underpin complex cognitive skills, such as episodic memory and planning, which have been repeatedly investigated in several bird species in recent decades. Until recently, avian executive functions were studied in relatively few bird species, but have gained traction in comparative cognitive research following MacLean and colleagues’ large-scale study (2014). Therefore, in this review paper, relevant previous findings are collected and organized to facilitate further investigations of these core cognitive processes in birds. This review can assist in integrating findings from avian and mammalian cognitive research and further current understanding of executive functions’ significance and evolution.

There are many new land use and land cover (LULC) products emerging yet there is still a lack of in-situ data for training, validation, and change detection purposes. The LUCAS (Land Use Cover Area frame Sample) survey is one of the few authoritative in-situ field campaigns, which takes place every three years in European Union member countries. More recently, a study has considered whether citizen science and crowdsourcing could complement LUCAS survey data, e.g., through the FotoQuest Austria mobile app and crowdsourcing campaign. Although the data obtained from the campaign were promising when compared with authoritative LUCAS survey data, there were classes that were not well classified by the citizens, and the photographs submitted through the app were not always of sufficient quality. For this reason, in the latest FotoQuest Go Europe 2018 campaign, several improvements were made to the app to facilitate interaction with the citizens contributing and to improve their accuracy in LULC identification. In addition to extending the locations from Austria to Europe, a change detection component (comparing land cover in 2018 to the 2015 LUCAS photographs) was added, as well as an improved LC decision tree and a near real-time quality assurance system to provide feedback on the distance to the target location, the LULC classes chosen and the quality of the photographs. Another modification was the implementation of a monetary incentive scheme in which users received between 1 to 3 Euros for each successfully completed quest of sufficient quality. The purpose of this paper is to present these new features and to compare the results obtained by the citizens with authoritative LUCAS data from 2018 in terms of LULC and change in LC. We also compared the results between the FotoQuest campaigns in 2015 and 2018 and found a significant improvement in 2018, i.e., a much higher match of LC between FotoQuest Go Europe and LUCAS. Finally, we present the results from a user survey to discuss challenges encountered during the campaign and what further improvements could be made in the future, including better in-app navigation and offline maps, making FotoQuest a model for enabling the collection of large amounts of land cover data at a low cost.

Data creation is often the only way for researchers to produce basic geospatial information for the pursuit of more complex tasks and procedures such as those that lead to the production of new data for studies concerning river basins, slope morphodynamics, applied geomorphology and geology, urban and territorial planning, detailed studies, for example, in architecture and civil engineering, among others. This exercise results from a reflection where specific data processing tasks executed in Google Sketchup (Pro version, 2018) can be used in a context of interoperability with Geographical Information Systems (GIS) software. The focus is based on the production of contour lines and Digital Elevation Models (DEM) using an innovative sequence of tasks and procedures in both environments (GS and GIS). It starts in Google Sketchup (GS) graphic interface, with the selection of a satellite image referring to the study area—which can be anywhere on Earth's surface; subsequent processing steps lead to the production of elevation data at the selected scale and equidistance. This new data must be exported to GIS software in vector formats such as Autodesk Design Web format—DWG or Autodesk Drawing Exchange format—DXF. In this essay the option for the use of GIS Open Source Software (gvSIG and QGIS) was made. Correcting the original SHP by removing “data noise” that resulted from DXF file conversion permits the author to create new clean vector data in SHP format and, at a later stage, generate DEM data. This means that new elevation data becomes available, using simple but intuitive and interoperable procedures and techniques which confgures a costless work flow.

In the paper, by convolution theorem for the Laplace transforms and analytic techniques, the author finds necessary and sufficient conditions for complete monotonicity, monotonicity, and inequalities of several functions involving polygamma functions. By these results, the author derives a lower bound of a function related to the sectional curvature of the manifold of the beta distributions. Finally, the author poses several guesses and open problems related to monotonicity, complete monotonicity, and inequalities of several functions involving polygamma functions.

This paper investigates nonverbal communication in human interactions, with a specific focus on facial expressions. Employing a Long Short-Term Memory (LSTM) architecture and a custom-ized facial expression framework, our approach aims to improve virtual agent interactions by incorporating subtle nonverbal cues. The paper contributes to the emerging field of facial expres-sion generation, addressing gaps in current research and presenting a novel framework within Unreal Engine 5. The model's architecture, trained on the CANDOR corpus, captures temporal dynamics, and refines hyperparameters for optimal performance. During testing, the trained model showed a cosine similarity of -0.95. This enables the algorithm to accurately respond to non-verbal cues and interact with humans in a way that is comparable to human-human interac-tion. Unlike other approaches in the field of facial expression generation, the presented method is more comprehensive and enables the integration of a multi-modal approach for generating facial expressions. Future work involves integrating blendshape generation, real-world testing, and the inclusion of additional modalities to create a comprehensive framework for seamless hu-man-agent interactions beyond facial expressions.

The main objective of this paper is to introduce a further extension of extended (p, q)-beta function by considering two Mittag-Leffler function in the kernel. We investigate various properties of this newly defined beta function such as integral representations, summation formulas and Mellin transform. We define extended beta distribution and its mean, variance and moment generating function with the help of extension of beta function. Also, we establish an extension of extended (p, q)-hypergeometric and (p, q)-confluent hypergeometric functions by using the extension of beta function. Various properties of newly defined extended hypergeometric and confluent hypergeometric functions such as integral representations, Mellin transformations, differentiation formulas, transformation and summation formulas are investigated.

In this paper, we relate Poisson’s summation formula to Heisenberg’s uncertainty principle. They both express Fourier dualities within the space of tempered distributions and these dualities are furthermore the inverses of one another. While Poisson’s summation formula expresses a duality between discretization and periodization, Heisenberg’s uncertainty principle expresses a duality between regularization and localization. We define regularization and localization on generalized functions and show that the Fourier transform of regular functions are local functions and, vice versa, the Fourier transform of local functions are regular functions.

Due to an urgent need for reducing the fast progressing climate changes, a rapid, standardized and replicable solution for the infrastructure restructuring of heat demand coverage of buildings at district and city level must be developed. As more and more communities in Europe, especially in Germany, are obligated to have plans for coverage of heat demand, city planners, energy agencies seek a tool, which will help them to design the first drafts of heating network routes, which can supply whole districts and cities with renewable energy. ArcGIS Pro Tools like Least-Cost-Path-Analysis (LCPA) and Closest Facility (CF) allow to find the shortest and “cheapest” way between the heat source and heat consumers in the analyzed areas. Starting from the community level, through the district, county, voivodeship and whole country levels, the replication of the methods for generating district heating (DH) network infrastructure can be achieved. The proposed LCPA and CF based methods help to design the most suitable and efficient DH networks in the analyzed areas. As only few open-source data input, like street networks and building footprints are needed, the methods can be implemented in all communities of the country of Poland. In this paper one example of one community of Wroclaw county, called Siechnice and surroundings is presented.

Abstract: Remarkably, the p53 transcription factor, referred to as “the guardian of the genome”, is not essential for mammalian development. Moreover, efforts to identify p53‑dependent developmental events have produced contradictory conclusions. Given the importance of pluripotent stem cells as models of mammalian development, and their applications in regenerative medicine and disease, resolving these conflicts is essential. Here we attempt to reconcile disparate data into justifiable conclusions predicated on reports that p53‑dependent transcription is first detected in late mouse blastocysts, that p53 activity first becomes potentially lethal during gastrulation, and that apoptosis does not depend on p53. Furthermore, p53 does not regulate expression of genes required for pluripotency in embryonic stem cells (ESCs); it contributes to ESC genomic stability and differentiation. Depending on conditions, p53 accelerates initiation of apoptosis in ESCs in response to DNA damage, but cell cycle arrest as well as the rate and extent of apoptosis in ESCs are p53-independent. In embryonic fibroblasts, p53 induces cell cycle arrest to allow repair of DNA damage, and cell senescence to prevent proliferation of cells with extensive damage.

Using the orbit decomposition, a new enumerative polynomial P(x) is introduced for abstract (simplicial) complexes of a given type, e.g., trees with a fixed number of vertices or triangulations of the torus with a fixed graph. The polynomial has the following three useful properties. (I) The value P(1) is equal to the total number of unlabeled complexes (of a given type). (II) The value of the derivative P'(1) is equal to the total number of nontrivial automorphisms when counted across all unlabeled complexes. (III) The integral of P(x) from 0 to 1 is equal to the total number of vertex-labeled complexes, divided by the order of the acting group. The enumerative polynomial P(x) is demonstrated for trees and then is applied to the triangulations of the torus with the vertex-labeled complete four-partite graph G = K_{2,2,2,2}, in which specific case P(x) = x^{31}. The graph G embeds in the torus as a triangulation, T(G). The automorphism group of G naturally acts on the set of triangulations of the torus with the vertex-labeled graph G. For the first time, by a combination of algebraic and symmetry techniques, all vertex-labeled triangulations of the torus (twelve in number) with the graph G are classified intelligently without using computing technology, in a uniform and systematic way. It is helpful to notice that the graph G can be converted to the Cayley graph of the quaternion group Q_8 with the three imaginary quaternions i, j, k as generators.

A major goal of neuroscience is understanding how neurons arrange themselves into neural networks that result in behavior. Most theoretical and experimental efforts have focused on a top-down approach which seeks to identify neuronal correlates of behaviors. This has been accomplished by effectively mapping specific behaviors to distinct neural patterns, or by creating computational models that produce a desired behavioral outcome. Nonetheless, these approaches have only implicitly considered the fact that neural tissue, like any other physical system, is subjected to several restrictions and boundaries of operations.Here, we propose a new, bottom-up conceptual paradigm: The Energy Homeostasis Principle, where the balance between energy income, expenditure, and availability are the key parameters in determining the dynamics of the found neuronal phenomena from molecular to behavioral levels. Neurons display high energy consumption relative to other cells, with metabolic consumption of the brain representing 20% of the whole-body oxygen uptake, contrasting with this organ representing only 2% of the body weight. Also, neurons have specialized surrounding tissue providing the necessary energy which, in the case of the brain, is provided by astrocytes. Moreover, and unlike other cell types with high energy demands such as muscle cells, neurons have strict aerobic metabolism. These facts indicate that neurons are highly sensitive to energy limitations, with Gibb’s free energy dictating the direction of all cellular metabolic processes. From this activity, the largest energy, by far, is expended by action potentials and post-synaptic potentials; therefore, plasticity can be reinterpreted in terms of their energy context. Consequently, neurons, through their synapses, impose energy demands over post-synaptic neurons in a close loop-manner, modulating the dynamics of local circuits. Subsequently, the energy dynamics end up impacting the homeostatic mechanisms of neuronal networks. Furthermore, local energy management also emerges as a neural population property, where most of the energy expenses are triggered by sensory or other modulatory inputs. Local energy management in neurons may be sufficient to explain the emergence of behavior, enabling the assessment of which properties arise in neural circuits and how. Essentially, the proposal of the Energy Homeostasis Principle is also readily testable for simple neuronal networks.

This paper deals with the analysis of the cognitive functions of the cerebral cortex or cortex in the evolutionary context. The triune brain model is presented given its notorious popularity in fields that are not strictly neuroscientific, and its limitations and inaccuracies are also shown. Although it is an outdated theory, this one represented the passage to a new era, because it really was the model of the movement towards understanding the brain in evolutionary terms. Next, the paper illustrates the different areas of the cortex and their functions, as well as the evolution of the brain and the cortex in vertebrates. To date, the expansion of the cortex with the amniotes was placed 300 million years ago, although recent studies place it in the lampreys more than 500 million years ago. Evolutionary changes in mammalian brain and cortex size are discussed, showing the evolution from three to six cell layers and trends in different groups of mammals. Finally, the most recent contributions in the field of research are illustrated, such as the role of neurogenesis and the evolution of the connectivity of the cortex.

TThis paper delves into the extension and characterization of radial positive definite functions into non-integer dimensions. We provide a thorough investigation by employing the Riemann-Liouville fractional integral and fractional Caputo derivatives, enabling a comprehensive understanding of these functions. Additionally, we introduce a secondary characterization based on the Bernstein characterization of completely monotone functions. The practical significance of our study is showcased through an examination of the positivity of the fundamental solution of the space-fractional Bessel diffusion equation, highlighting the real-world applicability of the developed concepts. Through this work, we contribute to the broader understanding of radial positive definite functions and their utility in diverse mathematical and applied contexts.

Natural cycles underpin the very stuff of life. In this commentary we consider unnatural cycles: that is, anthropogenic activities which have a circularity, but whose nature is to have a detrimental effect on human health, exacerbating existing problems. Natural cycles have feedback loops, some of which have recently come to light, with an understanding that everything is connected in some way. In health, feedback loops are imperative in homeostatic mechanisms. However, in the unnatural cycle the feedback loops serve to reinforce (and in some cases amplify) negative problems. We offer a commentary on an unnatural cycle moving from air quality to lung function and back to air quality; we call this the lung disease unnatural cycle. We suggest where links occur, and where wider consideration of interactions between various disciplines can lead to breaking this unnatural (or vicious) cycle, changing it to a healthy cycle where individual health can be improved, along with better global scale outcomes. We suggest that many activities within this unnatural cycle occur within silos. However, the improved cycle incorporates joint activities at geological, health, and financial levels, to the mutual benefit of all, breaking the unnatural cycle, and improving health, life and financial costs.

In this review we summarize the recent development in understanding the role of PIP2 in cellular function and signaling. We first discuss the effect of PIP2 on actin binding proteins addressing the mechanism of the actin cytoskeletal dynamics such as polymerization or depolymerization of the filamentous network or the coupling to membrane to generate forces. Next, we outline the role of PIP2 in membrane dynamics. We summarized how the membrane organization depends upon PIP2 in the presence of ions or transmembrane proteins that are sensitive to membrane curvature. We discuss how clathrin coated pits interact with adaptor proteins during the endocytosis process, which is facilitated by PIP2. Finally, we discuss the role of PIP2 in cell signaling and diseases.

In numerous instances, the fate of a single cell not only represents its peculiar outcome but also contributes to the overall status of an organism. In turn, cell division cycle and its control strongly influence cell destiny playing a critical role in targeting it towards a specific phenotype. Several factors participate to the control of growth and among them p27 and p57, two proteins modulating various transitions of cell cycle, appear to play key functions. In this review, the major features of p27 and p57 will be described, focusing in particular on their recently identified roles not directly correlated to cell cycle modulation. Then, their possible role as molecular effectors of polyphenols activities are discussed. Polyphenols represent a large family of natural bioactive molecules that have been demonstrated to play promising protective activities against several human diseases. Their use has also been proposed in association with classical therapies for ameliorating their clinical effects and for diminishing their negative side activities. The importance of p27 and p57 in polyphenol cellular effects will be discussed with the aim of identifying novel therapeutic strategies for the treatment of important human diseases, such as cancers, characterized by an altered control of growth.

The comparison of group means in latent variable models plays a vital role in empirical research in the social sciences. The present article discusses extensions of invariance alignment and Haberman linking concerning the choice of linking functions for comparisons of many groups. Robust linking functions are proposed for invariance alignment and robust Haberman linking that are particularly suited to item response data under partial invariance. In a simulation study, it is shown that both linking approaches have comparable performance, and in some conditions, the newly proposed robust Haberman linking outperforms invariance alignment.

A new generalization of extended beta function and its various properties, integral representations and distribution are given in this paper. In addition, we establish the generalization of extended hypergeometric and con uent hypergeometric functions using the newly extended beta function. The properties these extended and con uent hypergeometric functions such as integral representations, Mellin transformations, dif- ferentiation formulas, transformation and summation formulas are also investigated.

In a recent paper, Sarikaya et al. introduced a new analogue of the classical Gamma function which they called, the conformable Gamma function. Motivated by their results, this paper seeks to establish some inequalities for the conformable Gamma and Polygamma functions. Among other analytical tools, the procedure relies on the generalized forms of some classical inequalities.

Investigating the potential impact of composting and recycling waste on income distribution are crucial to promote a fairer and more sustainable fresh tomato supply chain (FTSC). Therefore, this study aims to explore the potential of gaining extra income from recycling tomatoes waste generated along the FTSC and to calculate the contribution of extra income from recycling tomato waste to reduce income inequality along the FTSC. Data were collected from 136 greenhouse tomato producers, 60 wholesalers, 18 exporters, 120 domestic retailers, 22 overseas retailers, and 3 recycling facilities in Türkiye. Marketing cost, absolute marketing margin, relative marketing margin and net profit margin were used when economically analyzing the FTSCs. Research results showed that the net profit share of the producer decreased associated with the increasing number of intermediaries. Research results also showed that revenue gained from composting and recycling of product loss and waste increased the welfare of greenhouse producer more than other supply chain actors. When taking into account the revenue from composting and recycling of wastes, producers increased their net profit by 9.85% at first FTSC, while that of second and third FTSCs were 8.29% and 9.21%, respectively comparing to the prevailing conditions. The contribution of extra revenue from composting and recycling of wastes to retailers was more comparing wholesaler and exporter. Retailers and wholesalers gaining from recycling in domestic FTSCs was more comparing to overseas one. Close cooperation between producers, wholesalers, exporters, retailers, and recycling facilities is essential for the effective implementation of waste recycling initiatives. Organizing the training and education programs focused on waste management can increase the extra income of producers and active intermediaries in FTSC from composting and recycling tomato wastes. Offering financial incentives, grants, or subsidies can encourage producers and other actors within the supply chain to adopt waste recycling practices. Continuous research and innovation are crucial in identifying and developing new technologies, processes, and strategies to minimize food loss and waste. Dominating fair-trade practices to ensure that all FTSC actors may balance the income distribution among FTSC actors.

We propose an algorithm for generating a panoramic image of a pipe’s inner surface based on inverse perspective mapping (IPM). For efficient crack detection, we used only perspective images of the pipe interior that can be obtained with a single lens camera instead of those taken with a 360-degree camera or a 3D depth camera. Frontal images taken while passing through the pipe were converted to images of the inner surface of the pipe using IPM. We derived a generalized IPM formula that considers the slope of the image plane to correct image distortion caused by the tilt of the plane; this IPM formula was derived based on the vanishing point of the perspective image, which was detected using optical flow techniques. Finally, the multiple transformed images with overlapping areas were combined via image stitching to create a panoramic image of the inner pipe surface. To validate our proposed algorithm, we restored images of pipe inner surface using a 3D pipe model and used these images for crack detection.

For the generation of representative volume elements a statistical description of the relevant parameters is necessary. These parameters usually describe the geometric structure of a single grain. Commonly, parameters like area, aspect ratio and slope of the grain relative to the rolling direction are applied. However, usually simple distribution functions like log normal or gamma distribution are used. Yet, these do not take the interdependencies between the microstructural parameters into account. To fully describe any metallic microstructure though, these interdependencies between the singular parameters need to be accounted for. To accomplish this representation, a machine learning approach was applied in this study. By implementing a Wasserstein generative adversarial network, the distribution, as well as the interdependencies could accurately be described. A validation scheme was applied to verify the excellent match between microstructure input data and synthetically generated output data.

A general methodology for loan amortization under arbitrary discount functions is discussed. It is shown that it is always possible to uniquely define a scheme for constructing the loan amortization schedule with an arbitrary assigned discount function. It is also shown that even if the loan amortization is carried out from the sequence of principal payments and the sequence of accrued interest, the underlying discount function can be uniquely determined at the maturities corresponding to the installment payment dates. As a special case of the proposed approach, we derive the amortization method according to the law of simple interest.

A system to evaluate several facets of hand function for neuroprostheses-mediated tasks is proposed. It includes a platform that serves as a test bench, sensors for dynamometry, electromyography, sensorized glove, and interactive objects. The system methodically locates and assesses the motor points along the forearm, evaluates stimulation-induced fatigue, measures digit motion and forces exerted during ADL grasps, and evaluates nerve excitability to advance electrode designs. While the system is exclusively designed for neuroprostheses-mediated grasp, it can also be extended to generic grasp and object manipulation-based research.

We use the theory of coherent measures to look at the problem of surplus sharing in an insurance business. The surplus share of an insured is calculated by the surplus premium in the contract. The theory of coherent risk measures and the resulting capital allocation gives a way to divide the surplus between the insured and the capital providers, i.e. the shareholders.

CX3CL1, also named fractalkine or neurotactin, the only known member of the CX3C chemokine family that can chemoattract several immune cells. CX3CL1 exists in both membrane-anchored and soluble forms, each mediating distinct biological activities. CX3CL1 signals are transmitted through its unique receptor, CX3CR1, primarily expressed in microglia of central nervous system (CNS). In the CNS, CX3CL1 acts as a regulator of microglia activation in response to brain disorders or inflammation. Recently, there has been a growing interest in the roles of CX3CL1 in regulating cell adhesion, chemotaxis, and host immune response in viral infection. Here, we provide a comprehensive review of the changes and function of CX3CL1 in various viral infections such as human immunodeficiency virus (HIV), SARS-CoV-2, influenza virus and cytomegalovirus (CMV) infection, to highlight the emerging roles of CX3CL1 in viral infection and the associated diseases.

Cognitive functions are based on neuronal plasticity, which is provided by various mechanisms involving numerous bioactive molecules, the most important of which are endocannabinoids (eCBs). Over the past three decades, a lot of data have been accumulated on the involvement of eCBs in the mechanisms of memory and other cognitive functions. These functions are impaired in neurodegenerative diseases such as Alzheimer's disease (AD) and temporal lobe epilepsy (TLE). The main pathological feature of neurons in AD and TLE is increased excitability; therefore, an activation of the endocannabinoid system, which controls cellular excitation, may be a promising approach in their therapy. The available information about the effect of (endo)cannabinoids on cognitive functions is contradictory, which may depend on the drugs used, their dose, and the experimental conditions. There is an extensive literature indicating a protective effect of cannabinoids in the treatment of neurodegenerative diseases in humans and in animal models of cognitive deficits. This review, focusing on the recent researches, is devoted to the analysis of the effects of endocannabinoid system activation on cognitive functions in norm and in the brain with neurodegeneration that occurs in AD and TLE diseases. Possible reasons for inconsistencies in the available data are discussed.

Cancer is considered nowadays one of the main causes of human death worldwide, being characterized by an alteration of the oxidative metabolism. Many natural compounds with anti-tumor attributes have been described, many of them from plant origin. Among them, capsaicin, which is the molecule responsible for the pungency in hot pepper fruits, has been reported to show antioxidant, anti-inflammatory and analgesic activities, as well as anti-proliferative properties against cancer. Thus, in this work the potential anti-proliferative activity of pepper (Capsicum annuum L.) fruits from diverse varieties with different capsaicin content (California < Piquillo < Padrón < Alegría riojana) against several tumor cell lines (lung, melanoma, hepatoma, colon, breast, pancreas, and prostate) has been investigated. The results showed that the capsaicin content in pepper fruits did not correspond with their anti-proliferative activity against tumor cell lines. By contrast, the greatest activity was promoted by the pepper tissues which contained the lowest capsaicin amount. This indicates that other compounds different from capsaicin have this anti-tumor potentiality in pepper fruits. Based on this, green fruits from the variety Alegría riojana, which has negligible capsaicin levels, was used to study the effect on the oxidative and redox metabolism of tumor cell lines from liver (Hep-G2) and pancreas (MIA PaCa-2). Different parameters from both lines treated with pepper fruit crude extracts were determined including, among others, protein nitration and protein S-nitrosation (two post-translational modifications (PTMs) promoted by nitric oxide), the antioxidant capacity, as well as the activity of the antioxidant enzymes superoxide dismutase (SOD), catalase, and glutathione peroxidase (GPX). Besides, the activity of the NADPH-generating enzymes glucose-6-phosphate dehydrogenase (G6PDH), 6-phosphogluconate dehydrogenase (6PGDH), and NADP-isocitrate dehydrogenase (NADP-ICDH) was followed. Our data revealed that the treatment of both cell lines with pepper fruit extracts altered their antioxidant capacity, enhanced the catalase activity, and considerably reduced the activity of the NADPH-generating enzymes. As a consequence, less H2O2 and NADPH seem to be available to cells, thus avoiding cell proliferation and possibly triggering cell death in both cell lines.

Human pluripotent stem cells (hPSCs) have become a powerful tool to generate various kinds of cell types comprising the human body. Recently, organoid technology emerged as a platform to build a physiologically relevant tissue-like structure from the PSCs, which provides a more relevant three-dimensional microenvironment to the actual human body than the conventional monolayer culture system for transplantation, disease modeling, and drug development. Although it holds so many advantages, the organoid culture system still has various problems related to culture methods, which became a challenge to get similar physiological properties to their original tissue counterparts. Here, we discuss the current development of organoid culture methods, including the problem that may arise from the currently available culture systems as well as the possible approach to overcoming the current limitation and improving their optimum utilization for translational application purposes.

NSD3 is a member of the NSD histone methyltransferase family of proteins. In recent years, it has been identified as a potential oncogene in certain types of cancer. NSD3 gene encodes three isoforms, the full length, a short (NSD3S) and WHISTLE isoforms. Importantly, NSD3S isoform corresponds to the N-terminal of the full-length protein, lacking the methyltransferase domain. The chromosomal location of NSD3 is frequently amplified across cancer types, such as breast, lung, colon, among others. Recently, this amplification has been correlated to a chromothripsis event, that could explain the different NSD3 alterations found in cancer. Fusion proteins containing NSD3 have also been reported, such as leukemia NSD3-NUP98, and in NUT midline carcinoma (NMC), NSD3-NUT fusion. Its role as an oncogene has been described by modulating different cancer pathways through its methyltransferase activity, or the short isoform of the protein, through protein interactions. Specifically, in this review we will focus on stating the functions that have been characterized as methyltransferase dependent, and those that have been correlated with the expression of the NSD3S isoform. Altogether, there is evidence that both isoforms of NSD3 are relevant for cancer progression, establishing NSD3 as a therapeutic target. However, further functional studies are needed to differentiate NSD3 oncogenic activity as dependent or independent of the catalytic domain of the protein, as well as the contribution of each isoform and its clinical significance in cancer progression.

In this paper we consider the congruence problem that arises in the post-analysis of Bayesian network models reconstructed from different datasets. Apart from the structure, a typical network numerically encodes relationship intensities, assigning numerical score to network edges via the scoring criterion used in the reconstruction process. This scoring is rarely a directly interpretable quantity with proper units of measure and an absolute scale, and often comes short in desirable characteristics of a true metric. This leads to poor portability of edge magnitude considerations between similar networks, originating from different sources. In this work, we address this problem by estimating the effect that data-specific resolution limit has on conditional independence, as reflected by information-theoretic entropy, and by the appropriate modification of MDL score, which removes the inconsistency between the score components in both the meaning and units. We also numerically validate our findings and expose additional performance advantages obtained via this modification.

Current therapeutic strategies targeting cancer cells within solid tumors have displayed limited success owing to the presence of non-cancer components referred to as the tumor stroma within the tumor microenvironment (TM). These stromal cells, extracellular matrix and blood vessels influence cancer cell response to therapy and play key roles in tumor relapse and resistance. Of the stromal cells present in the TM, a lot of attention has been given to cancer-associated fibroblasts (CAFs) as they are the most abundant and are important in cancer initiation, progression and therapy resistance. In this updated review I emphasize the role of CAFs in the regulation of tumor cell behaviour and reveal how CAF-derived factors and signaling influence tumor cell heterogeneity and development of novel strategies to combat cancer. To investigate the expression of CAF markers in tumor tissues versus normal tissues, transcriptomic data from The Cancer Genome Atlas (TCGA) and the Gene Expression Profiling Interactive Analysis (GEPIA) databases was used. Bioinformatic analysis reveals differential expression of CAF markers in several cancer types, underscoring the need for further multiomics and biochemical studies on CAFs, CAF subsets and markers. Differences in CAF markers’ expression could be due to different cellular origins as well as the effect of cancer-specific tumor microenvironmental effect on CAFs. Lastly, I present recent advances in therapeutic targeting of CAFs and the success of such endeavours or its lack thereof. It is recommended that for patients’ outcomes to improve, cancer treatment be combinatorial in nature, targeting both cancer cells and stromal cells and interactions.

The aim of this paper is to identify and document some functions and contextsof traditional pottery within northern Ghana. The descriptive approach of the qualitative research methodology was employed. Interview and observation methods were employed as the data collection methods. They were used to ascertain reasons why some potteryare engaged in certain contexts andfor certainfunctions. The data was tabulated to include the traditional name of the pot, the function and the context. The data were then analyzed and the indications were that, the potters make interesting forms of traditional pottery for different purposes; and the local name given to each pot perfectly defines their functions and contexts within northern Ghana. On the flipside of the coin, the function and context of every pot can also be dictated by its end user. Base on this, the researchers were able to discover some functions and contexts of the indigenous pottery which were put into some groups. On the first hand, the researchers classified the functions into five groups of purpose. These included: domestic purposes, religious purposes, agricultural purposes, rites of passage purposes and traditional herbal medicinal purposes. On other hand, seven groups of contexts were also discovered at the time of the study. These included: courtyards, bedrooms, bathrooms, graveyards, kitchens, shrines, and hencoops as places where these pots can be found among the people of the Northern Ghana.

Elastic yarns are the key component of high-performance compression garments. However, it remains a challenge to fabricate anti-fatigue yarns with high mechanical force and long elongation for generating compression garments with prolonged wear. In this paper, we report the development of anti-fatigue double-wrapped yarns with excellent mechanical properties by wrapping high-denier Spandex with nylon filaments in opposite twists. In particular, 560D high-denier Spandex as the core was untwisted which can maximumly reduce the interaction between the core and wrapping filaments, enabling high elongation of the double-wrapped yarns. In addition, we chose 70D nylon filaments with a tensile force of 387.40 ± 8.82 cN as the wrapping materials to provide sufficient force for double-wrapped yarns. Notably, opposite twists were induced for the inner and outer wrapping filaments to achieve a balanced stable yarn structure. By systematically optimizing manufacturing parameters including inner wrapping density, outer wrapping density, taking-up ratio, and drafting ratio, we obtained double-wrapped yarn with excellent tensile force (952.00 ± 24.03 cN) and elongation (357.28% ± 9.10%). Notably, the stress decay rate of optimized yarns was only 12.0% ± 2.2%. In addition, the optimized yarn was used as the weft-lining yarn for generating weft-lined fabrics, the elastic recovery rate of the obtained fabric was only 2.6% after cyclic stretching, much lower than the control fabric. Our design of anti-fatigue double-wrapped yarns could be widely used for fabricating high-performance compression garments.

Missing observation is a common problem in scientific and industrial experiments, particularly in a small-scale experiment. They often present significant challenges when experiment repetition is infeasible. In this research, we propose a multi-objective genetic algorithm as a practical alternative for generating optimal mixture designs that remain robust in the face of missing observation. Our algorithm prioritizes designs that exhibit superior D-efficiency while maintaining a high minimum D-efficiency due to missing observation. The focus on D-efficiency stems from its ability to minimize the impact of missing observations on parameter estimates, ensure reliability across the experimental space, and maximize the utility of available data. We study problems with three mixture components where the experimental region is an irregularly shaped polyhedral within the simplex. Our designs have proven to be D-optimal designs, demonstrating exceptional performance in terms of D-efficiency and robustness against missing observations. We provide a well-distributed set of optimal designs derived from the Pareto front, enabling experimenters to select the most suitable design based on their priorities using the desirability function.

Linear programming formulations of forest ecosystem management (FEM) problems proposed in the 60s have been adapted and improved upon over the years. Generating management alternatives for forest management planning is a key step in building these models. Global forests are diverse, and a variety of models have been developed to simulate management alternatives. Climate change has made forest management calculations even more complex, requiring flexibility, diverse parameters, models, and methods. Despite this complexity, consistent concepts can be applied in developing management alternatives for forest management planning. This work describes iGen, a flexible forest prescription generator that applies the AI technique Rule-Based System (AI-RBS). iGen projects the state and associated inputs and outputs for a set of management units using rules from its knowledge base. An Inference Engine uses the rules to simulate a set of prescriptions in a tree-like graph structure. Without needing IT specialists, forest managers can describe the potential development of their forest through variables, rules, formulas, functions, and procedures. A key feature of iGen is that it is not limited to, adapted to, or focused on any specific region, landscape, forest condition, projection method, or yield function. Instead, it aims to maximize generality, enabling it to address a broad range of FEM problems. This article introduces iGen, explaining its concepts, structure, and algorithms through two FEM problems: natural regeneration with shelterwood harvests and plantation/coppice. For data and iGen source programs, visit github.com/…/iGen.

According to the growing concern of various focus groups, in regard to the mitigation of the negative impacts generated because of the tourism, has born the interest of proposing sustainable tourism projects derivatives of the feeling within the communities (1) Background: the aim is to propose a differentiated diagnosis of the Subsystems (biophysical and anthropic) and their relationship with traditional-rational knowledge; (2) Methods: from the Theory of Complex Systems was propose the Harmonic Tourism Methodology, that try to correlation the subsystem and knowledge in the community of San Juan Tlahuica Atzingo, State of Mexico (4) Conclusions: Among the most outstanding results that are on the one hand, we must work through tourism projects to the rescue and preservation of natural and cultural resources, reassessing them through the strengthening of social cohesion. On the other hand, the application of this case allowed us to visualize that it is necessary to consolidate the elements and steps of the methodology in order to apply it to different communities that are beginning their journey in the field of the tourism and that can improve and potentiate their resources, seeking harmony between them.

In this article, we present two topics related to mathematical economics. We offer an intriguing proposal for securing cost and production functions in the face of uncertainty and risk. We discuss the relationship between individual and social preferences. This is important because traditional revealed preference theory does not account for such factors.

Individuals and their leadership competencies have been the sole focus of project leadership research, rather than the project leadership's behaviour and functions in project and organizational settings. As a result, this study investigates the project leadership functions and behaviours required for various project and organizational situations in order to propose a project leadership model that will be effective in all project and organizational situations. The model that was developed and tested in this study theorized on the project leadership function that project leaders are expected to perform as a result of their positions. It also described how project leaders could tailor their leadership functions and behaviours to address issues related to positions, organizational situations, and project situations. Three hypotheses were developed and tested using structural equation modelling to validate the model. The model's perceptive power demonstrates adequate validity. The model's validity implies that there are appropriate project leadership functions for different leadership levels and circumstances. The model's validity also implies that each project leadership behaviour has its own value, as conditions and necessities dictate. The study assumes that a project leader can embrace project leadership by combining a few different project leadership functions and behaviours.

This paper introduces extensions H4,p and X8,p of Horn’s double hypergeometric function H4 and Exton’s triple hypergeometric function X8, taking into account recent extensions of Euler’s beta function, hypergeometric function, and confluent hypergeometric function. Among the numerous extended hypergeometric functions, the primary rationale for choosing H4 and X8 is their comparable extension type. Next, we present various integral representations of Euler and Laplace type, Mellin and inverse Mellin transforms, Laguerre polynomial representation, transformation formulae and a recurrence relation for the extended functions. In particular, we provide a generating function for the X8,p and several bounding inequalities for the H4,p and X8,p.

Hepatocellular carcinoma (HCC) results in high mortality due to ineffective systemic therapy. Human immortalized cell lines are commonly used to study anti-tumour effects in the context of new anti-tumour therapies and tumour biology. As immortalized cell lines have limited biological relevance and heterogeneity compared to primary cells, patient-derived tumour tissues and corresponding immune cells are the gold standards for studying the complexity of individual tumour entities. However, culturing primary HCC cells has a low success rate. Here, we aimed to establish a reproducible approach to preserve the patient-derived liver cancer cells for in vitro and in vivo studies. The underlying study aimed to establish an in vitro pre-screening platform to test treatment options' effectivity and dosage, e.g., for new substances, autologous modified immune cells, or combined therapies in HCC. We initially employed 15 surgical resection specimens from patients with different HCC entities for isolation and preservation. The isolated liver cancer cells from four HCC-diagnosed patients were used for orthotopic transplantation into the healthy liver of immunodeficient mice, allowing them to grow for six months before human liver cancer cells were isolated and cultured. As a result, we generated and characterized four new primary-like liver cancer cell lines. Compared to immortalized HCC cell lines, freshly generated liver cancer cells displayed individual morphologies and heterogenous protein-level characteristics. We assessed their ability to proliferate, migrate, form spheroids, and react to common medications compared to immortalized HCC cell lines. All four liver cancer cell lines exhibit strong migration and colony-forming characteristics in vitro, comparable to extensively investigated immortalized HCC cell lines. Moreover, the four etiological different liver cancer cell lines displayed differences in the response to 5-FU, Sorafenib, Axitinib and Interferon-alpha treatment, ranking from non-responders to responders depending on the applicated medication. In sum, we generated individual patient-derived liver cancer cell lines suitable for predictive in vitro drug screenings and moreover for xenograft transplantations to realize the in vivo investigation of drug candidates. We overcame the low cultivation success rate of liver cancer cells derived from patients and analyzed their potential to serve a pre-clinical model.

The fractional Hilbert transform, a generalization of the Hilbert transform, has been extensively studied in the literature because of its extensive use in optics, engineering, and signal processing. In the present work, we aimed to expand the fractional Hilbert transform to a space of generalized functions known as Boehmians. We introduce a new fractional convolution operator for the fractional Hilbert transform to prove a convolution theorem similar to the classical Hilbert transform and also to extend the fractional Hilbert transform to Boehmians. We also construct a suitable Boehmian space on which the fractional Hilbert transform exists. Further, we investigate convergence of the fractional Hilbert transform for the class of Boehmians and discuss the continuity of the extended fractional Hilbert transform.

In this paper, we examine the weak abc conjecture and the strong abc conjecture using some functions. we attempt to discuss the possibilty that the negative consequence of the weak abc conjecture. Namely, we derive that the weak abc conjecture is not true. Additionally, we show that the strong abc conjecture is not true.

Three-dimensional transfer functions (3D TFs) are generally assumed to fully describe the transfer behavior of optical topography measuring instruments such as coherence scanning interferometers in the spatial frequency domain. Therefore, 3D TFs are supposed to be independent of the surface under investigation resulting in a clear separation of surface properties and transfer characteristics. In this paper we show that the 3D TF of an interference microscope differs depending on whether the object is specularly reflecting or consists of point scatterers. In addition to the 3D TF of a point scatterer, we will derive an analytical expression for the 3D TF corresponding to specular surfaces and demonstrate this as being most relevant in practical applications of coherence scanning interferometry (CSI). We additionally study the effects of temporal coherence and disclose, that in conventional CSI temporal coherence effects dominate. However, narrowband light sources are advantageous if high spatial frequency components of weak phase objects are to be resolved, whereas for low-frequency phase objects of higher amplitude the temporal coherence is less affecting. Finally, we present an approach that explains the different transfer characteristics of coherence peak and phase detection in CSI signal analysis.

GIGANTEA (GI) is a gene involved in multiple biological functions, which were analysed and are partially conserved in a series of mono- and dicotyledonous plant species. The identified biological functions include control over the circadian rhythm, light signalling, cold tolerance, hormone signalling and photoperiodic flowering. The latter function is a central role of GI, as it involves a multitude of pathways, both dependent and independent of the gene CONSTANS(CO) as well as on the basis of interaction with miRNA. The complexity of gene function of GI increases due to the existence of paralogs showing changes in genome structure as well as incidences of sub- and neofunctionalization. We present an updated report of the biological function of GI, integrating late insights into its role in floral initiation, flower development and flower volatile production.

Many complex behaviours in biological systems emerge from large populations of interacting molecules or cells, generating functions that go beyond the capabilities of the individual parts. Such collective phenomena are of great interest to bioengineers due to their robustness and scalability. However, engineering emergent collective functions is difficult because they arise as a consequence of complex multi-level feedback, which often spans multiple length-scales. Here, we present a perspective on how some of these challenges could be overcome by using multi-agent modelling as a design framework within synthetic biology. Using case studies covering the construction of synthetic ecologies to biological computation and synthetic cellularity, we show how multi-agent modelling can capture the core features of complex multi-scale systems and provide novel insights into the underlying mechanisms which guide emergent functionalities across scales. The ability to unravel design rules underpinning these behaviours offers a means to take synthetic biology beyond single molecules or cells and towards the creation of systems with functions that can only emerge from collectives at multiple scales.

In this work, an operator superquadratic function (in operator sense) for positive Hilbert space operators is defined. Several examples with some important properties together with some observations which are related to the operator convexity are pointed out. Equivalent statements of a non-commutative version of Jensen's inequality for operator superquadratic function are established. A generalization of the main result to any positive unital linear map is also provided.

Some refinements and reverses of the Fejer's inequality for convex functions are given.

Partial sums of analytic univalent functions and partial sums of starlike have been investigated extensively by several researchers. In this paper, we investigate a partial sums of convex harmonic functions that are univalent and sense preserving in the open unit disk.

Tight junctions (TJ) are cell-cell adhesive structures that define the permeability of barrier-forming epithelia and endothelia. In contrast to this seemingly static function, TJs display a surprisingly high molecular complexity and an unexpected dynamic regulation, which allows the TJs to maintain a barrier in the presence of physiological forces and in response to perturbations. Cell-cell adhesion receptors play key roles during the dynamic regulation of TJs. They connect individual cells within cellular sheets and link sites of cell-cell contacts to the underlying actin cytoskeleton. Recent findings support roles of adhesion receptors in transmitting mechanical forces and promoting phase separation. In this review, we discuss newly discovered functions of cell adhesion receptors localized at the TJs and their role in the regulation of the barrier function.

Carbon dots are carbon based nanoparticles, which have the characteristics of simple preparation process, photoluminescence, biocompatibility, adjustable surface function, water solubility, and low toxicity. They are widely used in biological applications such as imaging, biosensing, photocatalysis, and molecular transfer. It has also aroused great interest among researchers in agriculture and has made significant progress in improving crop growth and production. This review presents the physiological functions of carbon dots for crop growth and development, photosynthesis, water and nutrient absorption, and abiotic stress resistance and their applications in improving ecological environment and agriculture as biosensors, and the future application prospects and research directions of carbon dots in agriculture were prospected.

The paper investigates new robust code constructions based on bent functions and spline–wavelet transformation. Implementation of bent functions in codes construction increases the probability of error detection in the data channel and cryptographic devices. Meanwhile, use of spline–wavelets theory for constructing the codes gives the possibility to increase system security from the actions of an attacker. Presented constructions combines spline–wavelets functions and bent functions. Developed robust codes, compared to existing ones, have a higher parameter of maximum error masking probability. Illustrated codes are ensuring the security of transmitted information. Some of the granted constructions were implemented on FPGA.

The time symmetry of T_c = CT is redefined based on the 4-D Euclidean space. The time inversion symmetry of T_c = CT changes the signs of the charge (q) and absolute time (ct) of the particle. The P symmetry changes the signs of the space momenta and handedness of the particle. The T_c symmetry changes the signs of the time momentum (P_t=E/c) and charges. The handedness are classified as the left-handedness and right-handedness on the 3-D space. The charges (|q| = cDt) and energies (E= cDtDV) of the particles are originated from the upward warping (q>0) and downward warping (q<0) of the particles along the time axis. The evolution of our matter universe with P_t > 0 since the big bang can be interpreted based on the CTP symmetry with the partner antimatter universe with p_t < 0. The photon space is called as the vacuum space. Then the E and M waves are the space fluctuations, and the gravitational G wave is the time fluctuations. And the E, M and G fields are newly explained. The zero E and M fields of the photon space indicates that the photon space and gamma ray are the 2EM waves. The rest mass energy of the particle is the 4-D space volume of the warped photon space. In the present work, the quantum wave function is considered as the 4-D vector with the space wave function and time axis wave function in the 4-D Euclidean space. The warped photon space corresponds to the squared wave function which is the probability density. It is concluded that, in the quantum mechanics, the imaginary number concept is introduced in the quantum wave functions instead of the time axis component of the 4-D wave function vector. The left-handed neutrino puzzle is explained from the handedness partner relation with the right-handed dark matters. Finally, the modified Lorentz transformations derived in the 4-D Euclidean space are compared with the Lorentz transformations of the special and general relativity theories in the 4-D Minkowski space.

Chemokine C-C receptor 6 (CCR6) and its exclusive ligand CCL20 is an extremely important chemokine receptor-ligand pair which controls cell migration and immune induction during inflammatory disease. Not many scientific studies have been undertaken to study its immune mechanisms in detail, but its unique contribution to steady state cell chemotaxis in upholding immune tolerance and regulating immune homeostasis during inflammation is evident in multiple organ systems, including lung, liver, kidney, skin, brain, eye, joints, gonads and the gut in the human body. The role of CCR6 is constitutively expressed as a series of much debilitating severe inflammatory and autoimmune diseases, HIV and cancer metastasis. CD4⁺ T cells, the central organizers of adaptive immunity, are stringently mobilized by the CCR6/CCL20 axis also induced by cytokines and a host of other factors in a carefully executed immune modulation scenario, to bring about a delicate balance between pro-inflammatory T_H17 cells and regulatory T_reg cells. Although the exact immune regulatory role is not elucidated yet, CCR6/CCL20 axis is implicated as a front runner which determines the polarization of T_H17 and T_reg cells and consequently the resolution or progression of many debilitating disorders. This review therefore aims at emphasizing the pleiotropic significance of the chemokines CCR6 and CCL20 in immunologic function in multiple organ systems thereby hoping to accentuate its value in future therapeutic modalities.

In this work we study the energy consumption by various modern secured hash functions (MD2, MD5, SHA-1, and SHA-2) and modern symmetric key encryption protocols (Blowfish, DES, 3DES, and AES) from the algorithmic perspective. We identify various parameters that moderate energy consumption of these hashes and protocols. Our work is directed towards redesigning or modifying these algorithms to make them consume lesser energy. As a first step, we try to determine the applicability of the asymptotic energy complexity model by Roy et. al. on these hashes and protocols. Specifically, we try to observe whether parallelizing the access of blocks of data in these algorithms reduces their energy consumption based on the energy model. Our results confirm the applicability of the energy model on these hashes and protocols. Our work is motivated by the relevance and importance of cryptographic hashes and symmetric key protocols for modern ICT (Information and Communication Technology), and ICT enabled industry to keep them protected from dynamically changing threat scenarios. Hence the design of more energy efficient hashes and protocols will definitely contribute in reducing the ICT energy consumption that is continuously increasing.

Biofilms enable the persistence of pathogens in food processing environments. In order to inactivate these microorganisms, sanitizing agents are needed that are effective against pathogens entrapped in biofilms which are more difficult to inactivate than planktonic cells that are displaced and found on equipment surfaces. We examined conditions to develop, analyze, and enumerate robust biofilms of 3 different foodborne pathogens assisted by fluorescence adherence assay and enzymatic detachment. We compared 3 different isomeric forms of fluorescent substrates that are readily taken up by bacterial cells based on carboxy-fluorescein diacetate (5-CFDA, 5,6-CFDA, 5,6-CFDA,SE). Biofilm-forming strains of L. monocytogenes, E.coli O157:H7, and Salmonella serovars were detected using the chosen substrate in a microplate fluorescence assay define previously for use with Listeria. Adherence levels were determined by differences in relative fluorescence units (RFU). Multiple hydrolytic enzymes were examined for each representative pathogen for the most suitable enzyme for detachment and enumeration to confirm data obtained by fluorescence assay. Cultures were grown overnight in microplates, incubated, washed and replenished with fresh sterile growth medium; this cycle was repeated 7 times before used as ‘biofilms’. All treatments were performed in triplicate and compared by one-way analysis of variance (ANOVA) to determine significant differences (p < 0.05). Analysis of 7-day biofilms by SEM indicated possible extracellular polysaccharide involvement with Salmonella and E. coli.