This paper reports a new control strategy to improve sharing of unbalanced currents in islanded LV microgrids. This technique provides fast and effective sharing of positive-, negative- and zero-sequence currents, and is the first example of zero-sequence current sharing in the literature. The controllers are designed in the stationary frame. The control structure consists of four loops; 1)~the current controller; 2)~the voltage controller; 3)~the droop controller and the 4)~negative and zero sequence current controllers. The output current is considered unknown for the controller and is added to the control system as a disturbance. The proposed controller features a high gain in fundamental and harmonic frequencies, hence a good voltage quality is obtained in the presence of unbalanced and nonlinear loads. To this aim, a proportional-resonant (PR) controller is adopted as the current controller. By using a multi-resonant controller as current controller, a unified control structure is obtained which is suitable for both grid-connected and islanded modes. The voltage controller is designed using a resonant controller so that the voltage can have low VUF and THD in the presence of unbalanced and nonlinear loads. Furthermore, in this paper droop method is applied to the control structure to share real and reactive powers. Simulation studies show that the conventional droop method cannot share the oscillatory part of the output power that is due to the presence of unbalanced loads in the microgrid. This paper relies on using zero and negative sequence virtual impedance controller to share the oscillatory part of output power. By using zero-sequence virtual impedance controller (ZSVIC) and negative-sequence virtual impedance controller (NSVIC), the zero and negative sequence currents in the microgrid are controlled and shared effectively. By compensating zero- and negative-sequence currents locally, the flow of these currents in the microgrid is minimized, and the overall power quality of the islanded LV microgrid is improved.

Pancreatic neuroendocrine neoplasms (pNENs) are rare tumors accounting for only 1-2% of all pancreatic tumors. pNENs are pathologically heterogeneous and are categorized into three groups (neuroendocrine tumor: NET G1, NET G2 and neuroendocrine carcinoma: NEC) on the basis of Ki-67 proliferation index and mitotic count according to the 2010 WHO classification of gastroenteropancreatic NENs. NEC in this classification includes both histologically well-differentiated and poorly differentiated subtypes, and modification of the WHO 2010 classification is under discussion based on genetic and clinical data. Genomic analysis has revealed NETs G1/G2 have genetic alterations in chromatin remodeling genes such as MEN1, DAXX and ATRX, whereas NECs have an inactivation of TP53 and RB1, and these data suggest that different treatment approaches would be required for NET G1/G2 and NEC. While there are promising molecular targeted drugs, such as everolimus or sunitinib, for advanced NET G1/G2, treatment stratification based on appropriate predictive and prognostic biomarkers is becoming an important issue. The clinical outcome of NEC is still dismal, and a more detailed understanding of the genetic backround together with preclinical studies to develop new agents, including those already under investigation for SCLC, will be needed to improve the prognosis.

One-dimensional chain of core-shell pairs connected by ideal springs enables design of the metamaterial demonstrating the negative effective density and negative specific thermal capacity. We assume that the molar thermal capacity of the reported metamaterial is governed by the Dulong-Petit law in its high temperature limit. The specific thermal capacity depends of the density of the metamaterial; thus, it is expected to be negative, when the effective density of the chain is negative. The range of the frequencies enabling the effect of the negative thermal capacity is established. Dependence of the effective thermal capacity on the exciting frequency for various core/shell mass ratios is elucidated. The effective thermal capacity becomes negative in the vicinity of the local resonance frequency ω0 in the situation when the frequency ω approaches ω0 from above. The effect of the negative effective thermal capacity is expected in metals in the vicinity of the plasma frequency.

With the rise of novel immunotherapies able to stimulate the antitumor immune response, increasing literature data concerning the immunogenicity of breast cancer have been published in recent years. Numerous clinical studies have been conducted in order to identify novel biomarkers that could reflect the immunogenicity of BC and predict response to immunotherapy. In this regard, TILs have emerged as an important immunological biomarker related to the antitumor immune re-sponse in BC. TILs are more frequently observed in triple-negative breast cancer and HER2+ sub-types where increased TIL levels have been linked to better response to neoadjuvant chemotherapy and with improved survival. PD-L1 is a type 1 transmembrane protein ligand expressed on T lymphocytes, B lymphocytes and antigen-presenting cells and is considered a key inhibitory checkpoint involved in cancer immune regulation. PD-L1 immunohistochemical expression in breast cancer is observed in about 10–30% of cases and is extremely variable based on tumor stage and molecular subtypes . In detail, TNBC shows the highest percentages of PD-L1 positivity, followed by HER2+ tumors. On the other hand, PD-L1 is rarely expressed (0-10% of cases) in hormone-receptor positive BC. The prognostic role of PD-L1 expression in BC is still controversial since different immunohistochemistry (IHC) clones, cut-off points and scoring systems have been utilized across published studies. In the present paper an extensive review on the current knowledge of immune landscape of BC is provided. In detail TILS and PD-L1 expression across different BC subtypes is discussed also providing a guide for their pathological assessment and reporting.

The system of non-interacting electrically charged core-massless spring-shell mechanical units, demonstrating negative effective mass, is considered, seen as a Drude-Lorentz gas. When such an ideal gas is exposed to the external harmonic field, it demonstrates as the certain conditions the negative frequency-dependent electrical conductivity. The negative value of the electrical conductivity implies that the electrical current will flow against the direction of the electric field and correspondingly the direction of the electrical force. Low- and high-frequency asymptotic behavior of the electrical conductivity is addressed. The same system demonstrates at low frequencies the negative asymptotic refraction. Experimental realization of the introduced model system, based on the exploitation of plasma oscillations of the free electron gas is suggested.

Let $S=\left(s_1, \ldots, s_n\right)$ be a finite sequence of integers. Then $S$ is a Gilbreath sequence of length $n$, $S\in\mathbb{G}_n$, iff $s_1$ is even or odd and $s_2, \ldots, s_n$ are respectively odd or even and $\min\mathbb{K}_{\left(s_1, \ldots, s_m\right)}\leq s_{m+1}\leq\max\mathbb{K}_{\left(s_1, \ldots, s_m\right)}\forall m\in\left[\left.1, n\right)\right.$. This, applied to the order sequence of prime number $P$, defines Gilbreath polynomials and two integer sequences A347924 \cite{oeisA347924} and A347925 \cite{oeisA347925} which are used to prove that Gilbreath conjecture $GC$ is implied by $p_n-2^{n-1}\leqslant\mathcal{P}_{n-1}\left(1\right)$ where $\mathcal{P}_{n-1}\left(1\right)$ is the $n-1$-th Gilbreath polynomial at 1.

In this paper, we define Tetranacci and Tetranacci-Lucas matrix sequences and investigate their properties.

In general, a superconductor has zero resistance, although it requires significant refrigeration or high pressures with high manufacturing costs, which prevents it into practical applications. In other words, solving these issues implies main superconducting researches. To solve these problems, this paper describes a new type of superconductivity, which is independent for temperatures and which operates without pressures. The principles of the presented system are as follows:First a voltage source, a current source and a load are connected in series. Then, the voltage of the voltage source is adjusted to balance the voltage of the load. Under this condition, the balance of the two voltages provides a zero voltage between the taps of the current source and the generated current from the voltage source becomes zero because of the internal infinite resistance of the current source. As a result, the electric powers generated by the two sources are zero, and therefore, the load cannot generate Joule heating because of energy conservation. However, the current from the current source (not the voltage source) is not zero; therefore, we can predict that the resistance of the load must be zero. As a theory, we derived a new electric field and transient attractive force, which result in a very short coherence of an electron pair because there is not the Coulomb repulsive force due to the existence of the above transient attractive force. Note that both the forces are derived by the Poisson equation, which implies that they cannot be compatible. Therefore, the pair combination energy from spins becomes extremely strong, which is not destroyed by the normal heat energy. Moreover, every center-of-mass motion of electron pair results in the Bose-Einstein condensation and the macroscopic wave function, which produces the London equation (i.e., the Meissner effect). Moreover, by introducing the equivalent circuit, this paper conducted numerical calculations. As a result, we could derive numerically zero resistance and responses for additional static magnetic fields as a discharged current, which implies the Meissner effect. Note that this paper has prepared Appendix section, which provides a guide to reproduce actual experiments and preliminary experimental results. These results in the Appendix indicate the zero resistances and Meissner effects.

While the language model using the stop sign as an independent token has been widely used to decide when the model should stop, it may lead to the growth of vocabulary dimensions and further problems. Similarly, present research on game algorithms usually estimate stopping point related problems based on the evaluation of the winning rate. However, information redundancy may also exist in such models, thus increasing the training difficulty. Above two types of tasks (and similar autoregressive tasks) show a common problem of stopping point prediction. In this paper, we describe a design of separated model, trying to separate the complexity of stopping point prediction from the main task model, so that the information used for estimating stopping point can be reduced. On this basis, in order to verify the rationality of using separated model, we propose a model-free test method. It judges the separability of transformed data based on point difference and sequence difference metrics. In this way, it can predict the credibility of the separated model inference.

This paper describes the successful application of the Transformer model used in the natural language processing and vision tasks as a means of processing the time series of signals from gyroscope and accelerometer sensors for the classification of human activities. The Transformer model is based on deep neural networks with many layers which can generalize well on signals. All measured signals come from a smartphone placed in a waist bag. Activity prediction is sequence-to-sequence, each time step of the signal is assigned a designation of the performed activity. Emphasis is placed on attention mechanisms, which express individual dependencies between signal values within a time series. In comparison with another recent result, the recognition precision was improved from 89.67 percent to 99.2 percent. The transformer model should in the future be included among the top options in machine learning methods for human activity recognition.

The origin of SARS-CoV-2 is debated, even after 18 months into the COVID-19 pandemic and a special investigation conducted by the World Health Organization. The RaTG13 sequence has been a highlight of discussions surrounding the origin of SARS-CoV-2. Here we express our opinion about the need for better reporting standards for information about sequencing data, especially for pathogens, citing our findings with the reported RaTG13 genome.

Paraphrase generation is an important yet challenging task in NLP. Neural network-based approaches have achieved remarkable success in sequence-to-sequence(seq2seq) learning. Previous paraphrase generation work generally ignores syntactic information regardless of its availability, with the assumption that neural nets could learn such linguistic knowledge implicitly. In this work we make an endeavor to probe into the efficacy of explicit syntactic information for the task of paraphrase generation. Syntactic information can appear in the form of dependency trees which could be easily acquired from off-the-shelf syntactic parsers. Such tree structures could be conveniently encoded via graph convolutional networks(GCNs) to obtain more meaningful sentence representations, which could improve generated paraphrases. Through extensive experiments on four paraphrase datasets with different sizes and genres, we demonstrate the utility of syntactic information in neural paraphrase generation under the framework of seq2seq modeling. Specifically, our GCN-enhanced models consistently outperform their syntax-agnostic counterparts in multiple evaluation metrics.

As a kind of converse of the celebrated Erd˝os-Szekeres theorem, we present a necessary and sufficient condition for a sequence of length n to contain a longest increasing subsequence and a longest decreasing subsequence of given lengths x and y, respectively.

Complex modeling has received significant attention in recent years and is increasingly used to explain the statistical phenomenon with increasing and decreasing fluctuations such as the similarity or difference of spike protein charge patterns of coronaviruses. Different from the existing covariance or correlation coefficient methods in traditional integer dimension construction, this study proposes a simplified novel fractional dimension derivation with the exact Excel tool algorithm. It involves the fractional center moment extension to covariance, which ends up a complex covariance coefficient that is better than the Pearson correlation coefficient, in the sense that the nonlinearity relationship can be further depicted. The spike protein sequences of coronaviruses were obtained from the GenBank and GISAID database, including the coronaviruses from pangolin, bat, canine, swine (three variants), feline, tiger, SARS-CoV-1, MERS, and SARS-CoV-2 (including the strains of Wuhan, Beijing, New York, German, and UK variant B.1.1.7) were used as the representative examples in this study. By examining the values above and below the average/mean based on the positive and negative charge patterns of the amino acid residues of the spike proteins from coronaviruses, the proposed algorithm provides deep insights into the nonlinear evolving trends of spike proteins for understanding the viral evolution and identifying the protein characteristics associated with viral fatality. The calculation results demonstrate that the complex covariance coefficient analyzed by this algorithm is capable of distinguishing the subtle nonlinear differences in the spike protein charge patterns with reference to Wuhan strain SARS-CoV-2 for which the Pearson correlation coefficient may overlook. Our analysis reveals the unique convergent (positive correlative) to divergent (negative correlative) domain center positions of each virus. The convergent or conserved region may be critical to the viral stability or viability; while the divergent region is highly variable between coronaviruses suggesting high frequency of mutations in this region. The analyses show that the conserved center region of SARS-CoV-1 spike protein is located at amino acid residues 900, but shifted to the amino acid residues 700 in MERS spike protein, and then to amino acid residues 600 in SARS-COV-2 spike protein, indicating the evolvement of the coronaviruses. Interestingly, the conserved center region of the spike protein in SARS-COV-2 variant B.1.1.7 shifted back to amino acid residues 700, suggesting this variant is more virulent than the original SARS-COV-2 strain. Another important characteristic our study reveals is that the distance between the divergent mean and the maximal divergent point in each of the viruses (MERS>SARS-CoV-1>SARS-CoV-2) is proportional to viral fatality rate. This algorithm may help to understand and analyze the evolving trends and critical characteristics of SARS-COV-2 variants, other coronaviral proteins and viruses.

Commercial buildings situated in hot and humid tropical climates rely significantly on cooling systems to maintain optimal occupant comfort. A well-accurate day-ahead load profile prediction plays a pivotal role in planning the energy requirements of cooling systems. Despite the pressing need for effective day-ahead cooling load predictions, current methodologies have not fully harnessed the potential of advanced deep-learning techniques. This research paper aims to address this gap by investigating the application of innovative deep learning models in day-ahead hourly cooling load prediction for commercial buildings situated in tropical climates. A range of deep learning techniques, including Deep Neural Network, Convolutional Neural Networks, Recurrent Neural Networks, and Long Short-Term Memory networks are employed to enhance prediction accuracy. Furthermore, these individual deep learning techniques are synergistically integrated to create hybrid models, such as CNN-LSTM and Sequence-to-Sequence models. An extensive comparative analysis is conducted to identify the most effective hybrid model. Sequence-to-sequence model provided better performance compared to the other single and hybrid models. Experiments are conducted to choose the time horizons from the past that can serve as input to the models. Further, the influence of various categories of input parameters on prediction performance has been assessed. Historical cooling load, calendar features and outdoor weather parameters are found in decreasing order of influence on prediction accuracy. This research focuses on buildings located in Singapore and presents a comprehensive case study to validate the proposed models and methodologies.

Ajuga arabica is an essential medicinal plant found naturally in Saudi Arabia, recognized for its therapeutic characteristics. Nevertheless, research on the genetic diversity and population arrangement of this species in Saudi Arabia is deficient. In this study, we conducted a comparative examination of DNA and gene sequences to evaluate the genetic diversity and population configuration of Ajuga arabica in Saudi Arabia. Our findings demonstrate that there are high levels of genetic diversity within populations, but low levels of genetic differentiation among populations. Moreover, we discovered proof of gene flow among populations, suggesting that there are no significant genetic barriers to gene flow. Our results offer valuable insights into the genetic diversity and population structure of Ajuga arabica in Saudi Arabia, which can support conservation efforts and promote the sustainable use of this valuable medicinal plant.

Given any sequence a = (an)n1 of positive real numbers and any set E of complex sequences, we write Ea for the set of all sequences y = (yn)n1 such that y=a = (yn=an)n1 2 E. In this paper, we use the spaces w1, w0 and w of strongly bounded, summable to zero and summable sequences, that are the sets of all sequences y such that ? n?1Pn k=1 jykj
n is bounded, tends to zero and such that y ? le 2 w0, for some scalar l, respectively, (cf. [24, 22]). These sets where used in the statistical convergence, (cf. [17, Chapter 4]). Then we deal with the solvability of each of the (SSIE) F
 E + F0x where E is a linear space of sequences, F = c0, c, `1, w0, w, or w1 and F0 = c0, c, or `1. For instance, the solvability of the (SSIE) w
 w0+s(c) x consists in determining the set of all sequences x = (xn)n1 2 U+ that satisfy the following statement. For every sequence y that satisfy the condition limn!1 n?1Pn k=1 jyk ? yk?1 ? lj = 0, there are two sequences u and v, with y = u+v such that limn!1 n?1Pn k=1 jukj = 0 and limn!1 (vn=xn) = L for some scalars l and L. These results extend those stated in [11, 12, 10].

Because imbalanced power will cause the loss of the propulsion motor of the railway vehicle, and the increase in temperature will shorten the service life of the electric vehicle. Not only this, but also increase the cost of electricity and maintenance. In the past, the industry only focused on methods to improve power quality such as load capacity, relay setting, and harmonic resolution. Now, the consider of three-phase unbalance rate (TPUR) must be applied. I propose special transformers wiring (STW) to improve the three unbalance rates and provide different transformer wiring methods. According to the IEEE Committee, in the future, power companies will need to install balanced relay stations to improve three-phase unbalance rate. the internal regulations of Taipower must be less than 4.5% (voltage unbalance rate (NPSUR)of 2.5% and motor temperature rise of 12.5%). the derivation of the transformer "three-phase unbalance rate" model is the focus of the railway system. This research is based on the model derivation of different wiring methods to improve the hot problem caused by the three-phase imbalance and improve the service life of the train. And pointed out that Scott, Le-Blanc, Modified-Woodbridge three wiring methods can be applied to future railway system routes to improve the three-phase unbalance rate, in line with the IEEE standard of less than 2%.

The gravitational charge should be the energy instead of mass. This modification will lead to some different results and the experiments to test are also presented. Especially, we propose a scheme to achieve the negative energy and gravitational repulsive force in the lab.

The nucleosome is a major modulator of DNA accessibility to other cellular factors. Nucleosome positioning has a critical importance in regulating cell processes such as transcription, replication, recombination or DNA repair. The DNA sequence is a major factor influencing the position of nucleosomes on genomes. Different sequence motifs can promote or inhibit the nucleosome formation, thus influencing the accessibility to the DNA. Sequence-encoded nucleosome positioning having functional consequences on cell processes can then be selected or counter-selected during evolution. We review the interplay between sequence evolution and nucleosome positioning evolution. We first focus on the different ways to encode nucleosome positions in the DNA sequence, and to which extent these mechanisms are responsible of genome-wide nucleosome positioning in vivo. Then, we discuss the findings about selection of sequences for their nucleosomal properties. Finally, we illustrate how the nucleosome can directly influence sequence evolution through its interactions with DNA damage and repair mechanisms. This review aims to provide an overview of the mutual influence of sequence evolution and nucleosome positioning evolution, possibly leading to complex evolutionary dynamics.

Escherichia coli phage Eco_BIFF was isolated from several laboratory stocks of E. coli K-12 MG1655 derivatives. The source of the contamination is unknown. Eco_BIFF is a lytic phage that shows effective growth inhibition of E. coli K-12. Here, we announce the complete genome sequence of Eco_BIFF, and major findings from its genome annotation.

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

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

To realize structural vibration control,a two parameters H2 optimization design was proposed to optimize the tuning ratio and damping ratio for electromagnetic tuned mass damper (EMTMD). The control effect of this two parameters optimization design is better than that of classical tuned mass damper (TMD).For this two parameters optimization,the most important thing is that the inductance of the coil can be set very small and the external load resistance can be positive ,which can avoid the use of complex negative impedance circuit. If Ref.[6] were designed according to the H2 optimization of two parameters, the EMTMD can be used for multi-modal vibration control of structures without connecting negative inductance and negative resistance spontaneously.

We evaluate the nested sum $\sum_{a_{n - 1} = c}^{a_n } {\sum_{a_{n - 2} = c}^{a_{n - 1} } { \cdots \sum_{a_0 = c}^{a_1 } {x^{a_0 } } } }$ where $a_n$ and $c$ are any integers and $x$ is a real or complex variable. Consequently, we evaluate multiple sums involving the terms of a general second order sequence, the Horadam sequence (W_j (a, b; p, q)), defined for all non-negative integers j by the recurrence relation W₀ = a, W₁ = b; W_j = pW_j−1 − qW_j−2 (j≥2); where a, b, p and q are arbitrary complex numbers, with p ≠ 0, q ≠ 0.

Sarcosine (N-methylglycine), a glutamatergic modulator, reduces the primary negative symp-toms of schizophrenia. These beneficial changes might be mediated by trophic factors such as ep-idermal growth factor (EGF). We assessed associations between initial serum EGF levels or changes in serum EGF levels and symptom severity during the addition of sarcosine to stable an-tipsychotic treatment and thereby evaluate the associations between glutamatergic modulation, clinical changes and peripheral EGF concentrations. 58 subjects with a diagnosis of chronic schizophrenia with dominant negative symptoms, stably treated with antipsychotics completed a prospective 6-month, randomized, double-blind, placebo-controlled study. Subjects received orally 2 grams of sarcosine (n=28) or placebo (n=30) daily. Serum EGF levels and symptom se-verity (using Positive and Negative Syndrome Scale - PANSS and Calgary Depression Scale for Schizophrenia - CDSS) were assessed at baseline, 6 weeks, and 6 months follow-up. Augmenta-tion antipsychotic treatment with sarcosine had no effect on EGF serum levels at any time-points. Only the sarcosine group showed a significant improvement in negative symptoms, general psy-chopathology subscales, and the overall PANSS score. We found reduction of serum EGF levels in the placebo group, but levels in the sarcosine remained stable during the study. Our data indicate that improvement in negative symptoms due to sarcosine augmentation is not mediated by EGF, but effective treatment may induce the production or block the decrease in EGF concentrations, which indicates the neuroprotective effect of treatment and confirms the relationship between neuroprotection and EGF levels.

Prime period sequences can serve as the fundamental tool to construct arbitrary composite period sequences. This is a review study of prime period perfect Gaussian integer sequence (PGIS). When cyclic group {1,2,…,N−1} can be partitioned into k cosets, where N=kf+1 is an odd prime number, the construction of a degree-(k+1) PGIS can be derived from either matching the flat magnitude spectrum criterion or making the sequence with ideal periodic autocorrelation function (PACF). This is a systematic approach of prime period N=kf+1 PGIS construction, and is applied to construct PGISs with degrees 1, 2, 3 and 5. However, for degrees larger than 3, matching either the flat magnitude spectrum or achieving the ideal PACF encounters a great challenge of solving a system of nonlinear constraint equations. To deal with this problem, the correlation and convolution operations can be applied upon PGIS of lower degrees to generate new PGIS with degree-4 and other higher degrees, e.g., 6, 7, 10, 11, 12, 14, 20 and 21 in this paper. In this convolution based scheme, both degree and pattern of a PGIS vary and can be indeterminant, which is rather nonsystematic compared with the systematic approach. The combination of systematic and nonsystematic schemes contributes the great efficiency for constructing abundant PGISs with various degrees and patterns for the associated applications.

Introduction: The presence of multiple comorbidities increases the risk of all-cause mortality, but the effects of the comorbidity sequence before the baseline date on mortality remained unexplored. This study investigated the relationship between coronary heart disease (CHD), atrial fibrillation (AF) and heart failure (HF) sequence on all-cause mortality risk in type 2 diabetes mellitus. Methods: This study included patients with type 2 diabetes mellitus prescribed antidiabetic/cardiovascular medications in public hospitals of Hong Kong between January 1st, 2009 and December 31st, 2009 with follow-up until death or December 31st, 2019. Cox regression was used to identify comorbidity sequences predicting all-cause mortality in patients with different medication subgroups. Results: A total of 249291 patients (age: 66.0±12.4 years, 47.4% male) were included. At baseline, 7564, 10900 and 25589 patients had AF, HF and CHD, respectively. Over follow-up (3524±1218 days), 85870 patients died (mortality rate: 35.7 per 1000 person-years). Sulphonylurea users with CHD developed later, but insulin users with CHD developing earlier, in the disease course had lower mortality risks. Amongst insulin users with two of the three comorbidities, CHD with preceding AF (hazard ratio [HR]: 3.06, 95% CI: [2.60-3.61], p<0.001) or HF (HR: 3.84 [3.47- 4.24], p<0.001) had a higher mortality. In users of lipid-lowering agents with all three comorbidities, those with preceding AF had higher risk of mortality (AF-CHD-HF: HR: 3.22, [2.24-4.61], p<0.001; AF-HF-CHD: HR: 3.71, [2.66-5.16], p<0.001). Conclusion: The sequence of comorbidity development affects the risk of all-cause mortality to varying degrees in diabetic patients on different antidiabetic/cardiovascular medications.

Optinalysis, as a method of symmetry detection, is a new algorithm that intrametrically (within elements or variables) or intermetrically (between elements or variables) computes and compares two or more univariate or multi-clustered or multivariate sequences as a mirror-like reflection of each other (optics-like manner), hence the name is driven. Optinalysis is based by the principles of reflection and moment about a symmetrical line which detects symmetry that reflects a similarity measurement. This proposed methodology was validated in comparison with Pearson method of skewness detection, and also with some algorithms for pairewise alignment and comparison of genomic sequences (Needle, Stretcher, Water, Matcher) on EMBL-EBI website. A results comparison shows that optinalysis is more advance, more sensitive, more inferential and simple alternative approach of skewness detection and pairewise sequence comparison.

In this paper, we generalize the concept of I-statistical convergence, which is a recently introduced summability method, with an infinite matrix of complex numbers and a modulus function. Lacunary sequences will also be included in our definitions. The name of our new method will be A^{I}-lacunary statistical convergence with respect to a sequence of modulus functions. We also define strongly A^{I}-lacunary convergence and we give some inclusion relations between these methods.

The purpose of the present study is to explore the linkage between Hazardous Road Locations-based crash counts and a variety of geometric characteristics, roadway characteristics, traffic flow characteristics and spatial features in the region of Sousse, Tunisia. For this purpose, collision data was collected from at 52 hazardous road sections including 1397 crash records for a 11-year monitoring period from January 1, 2004 to December 31, 2014 obtained from National Observatory for Information, Training, Documentation and Studies on Road Safety in Tunisia (NOITDRS). The matrix of Pearson correlation was used in order to avoid inclusion of both variables, which were highly correlated. Both the Random Effects Negative Binomial model and the Negative Binomial model were estimated. To evaluate the models, the Random Effect Negative Binomial model improves the goodness-of-fit compared to the Negative Binomial model. Average Daily Traffic volume, Curved alignment, Presence of public lighting, Visibility, Number of lane, Presence of vertical/horizontal sign, Presence of rural segment, Presence of drainage system, Roadway surface condition, Presence of paved shoulder and presence of major road were found as significant variables influencing accident occurrences. Overall, the current research contributes to the literature from empirical, modeling methodological standpoints since it was the first study conducted in Tunisia to use crash prediction models for hazardous road locations, and that portrays Tunisian reality. The research findings present advantageous insights on hazardous road locations in the region of Sousse, Tunisia and present useful planning tools for public authorities in Tunisia.

The implementation of green logistics can reduce the increasingly serious environmental damage and improve the operating efficiency of logistics enterprises. In this paper, through quantitative calculation of logistics negative external costs, including traffic accidents, atmospheric pollution, noise pollution, and pollution caused by packaging, we build accounting standards to calculate the negative external cost of logistics enterprises that mainly generate pollution from transportation and packaging. Then, assuming the impetus provided by government implementing incentive mechanisms in a free market economy, we establish a ‘Logistics Negative External Cost Internalizing’ model, which quantitatively analyzes the relationships among freight rate, freight volume, investment of enterprise for implementing green logistics, and the subsidy given by government, under the comparison of the two modes ‘enterprise operates first’ and ‘government subsidizes first’. The results show that the introduction of ‘government subsidizes first’ incentive mechanism and increasing freight rate are helpful in promoting the process of logistics market greening.

We present a differential-calculus-based method which allows one to derive more identities from {\it any} given Fibonacci-Lucas identity containing a finite number of terms and having at least one free index. The strength of our method is that no additional information is required about the given original identity. The method readily extends to a generalized Fibonacci sequence.

The study examines n-balls, regular n-simplices, and n-orthoplices in real dimensions using novel recurrence relations that removed indefiniteness present in known formulas. They show that in the negative, integer dimensions volumes of n-balls are zero if n is even, positive if n = -4k - 1, and negative if n = -4k - 3, for natural k. Volumes and surfaces of n-cubes inscribed in n-balls in negative dimensions are complex, wherein for negative, integer dimensions they are associated with integral powers of the imaginary unit. The relations are continuous for n Î ℝ and show that the constant of π is absent for 0 ≤ n < 2. For n < -1 self-dual n-simplices are undefined in the negative, integer dimensions, and their volumes and surfaces are imaginary in the negative, fractional ones, and divergent with decreasing n. In negative, integer dimensions n-orthoplices reduce to the empty set, and their real volumes and imaginary surfaces are divergent in negative, fractional ones with decreasing n. Out of three regular, convex polytopes present in all natural dimensions, only n-orthoplices, n-cubes (and n-balls) are defined in the negative, integer dimensions.

Here, we report a simple and effective method for separation of gram-negative bacteria using aptamer-modified microbeads and acoustophoresis. As acoustophoresis allows for simultaneous washing and size-dependent separation in continuous flow mode, we efficiently obtained gram-negative bacteria that showed high affinity without any additional washing steps. The proposed device has a simple and efficient channel design, utilizing a long, square-shaped microchannel that shows excellent separation performance in terms of the purity, recovery, and concentration factor. Microbeads (10 µm) coated with the GN6 aptamer can specifically bind gram-negative bacteria. Using acoustophoresis, gram-negative bacteria-bound microbeads and other unbound/contaminants can be separated by size with high purity and recovery. The device demonstrated excellent separation performance, with high recovery (up to 98%), high purity (up to 99%), and a high volume rate (500 µL/min), and a concentration factor of up to 20×. The acoustophoresis microfluidic device also showed binding affinity to multiple strains of gram-negative bacteria, but not to gram-positive bacteria. This study presents a new paradigm for early diagnosis of bacterial infectious diseases. In addition to detecting living bacteria or bacteria-derived biomarkers, this protocol can be extended to monitoring the contamination of water resources, and may aid quick responses to bioterrorism and pathogenic bacterial infections.

The Botryosphaeriales order are best known for the diseases they cause in woody plants, as primary pathogens or latent pathogens residing in the woody tissue of asymptomatic hosts. In the first instance, Botryosphaeriales species have been identified in Venezuela using morphological de-scriptions in the 80's and 90's, and later, the mid-2000s using molecular techniques. The mor-phological descriptions of the asexual morphs were initially used for the identification of Botry-osphaeriales genera and species. Lasiodiplodia spp., (as L. theobromae) was the most isolated fungus in Venezuela within the Botryosphaeriales and has been found in more than 50% of the hosts in native and non-native plants, followed by Diplodia, Dothiorella, Fusicoccum, Lasiodiplodia, Micro-diplodia, Macrophomina, Neofusicoccum, Sphaeropsis, and Botryosphaeria, considered all of them cosmopolitan group. With molecular studies, that included DNA sequence data from multiple genes, such as the internal transcribed spacer of rDNA (ITS), translation elongation factor-1α (tef1), and β-tubulin (btub) used on the fungi isolated from woody plants, mainly trees or forest species, resulted in the presence of two families within the Botryosphaeriales order for Venezuela. Botryosphaeriaceae family with the genera: Botryosphaeria, Cophinforma, Diplodia, Lasiodiplodia and Neofusicoccum, and the Pseudofusicoccumaceae family that includes the genus Pseudofusicoccum. In Botryosphaeriaceae family was again the Lasiodiplodia genus the most predominant in most hosts, and the specie L. theobromae the most isolated in native and non-native plants; Botryosphaeria dothidea, Cophinforma atrovirens, Diplodia scrobiculata (syn. Diplodia guayanensis), Lasiodiplodia brasi-liensis, L. crassispora, L. pseudotheobromae, Neofusicoccum arbuti (syn. N. andinum), N. parvum, and N. ribis are cosmopolitan species, and they were isolated from native and non-native plants; while Pseudofusicoccum stromaticum was found in plantations non-native of Acacia mangium, E. urophylla x E. grandis, Eucalyptus urophylla, and reported exclusively in South America; Lasiodiplodia venezue-lensis has only been reported in Venezuela, from native and non-native plants. The presence, distribution, diversity, and symptoms of these fungi, mainly of the new genus, new species, and reports found in Venezuela and other parts of the world, were also reviewed.

Plesiomonas shigelloides is the only species in the genus and has zoonotic importance due to its serious implications resulting from the consumption of contaminated seafood. This is the first report on the genomic features of the whole-genome sequence (WGS) of P. shigelloides strain V-78 recovered from diseased rainbow trout, Oncorhynchus mykiss. The genome of P. shigelloides V-78 consists of 4,478,098 base pairs (bp), which encode 3730 proteins and has a G+C content of 51.1%. The bioinformatics analysis of WGS of V-78 confirmed the presence of 121 tRNA genes and 42 rRNA genes (15 genes for 5S rRNA, 13 genes for 16S rRNA and 14 genes for 23S rRNA). Comprehensive genome analyses revealed that the strain encodes for secondary metabolites, antimicrobial resistance, and virulence genes. The strain V-78 has 31 known antibiotic resistance models, which encode many antimicrobial resistances. Also, strain V-78 has 42 different virulence genes such as adhesion, secretion system, and motility. The digital DNA-DNA hybridization value against P. shigelloides NCTC 10360 was 74.2%, while the average nucleotide identity value was 97.1%. Based on the scrutinized analysis of genomic data, strain V-78 should be considered a novel subspecies of P. shigelloides, for which Plesiomonas shigelloides subsp. oncorhynchi is proposed.

Antimicrobial peptides (AMPs) are considered as promising alternatives to conventional antibiotics in order to overcome the growing problems of antibiotic resistance. Computational prediction approaches receive an increasing interest to identify and design the best candidate AMPs prior to the in-vitro tests. In this study, we focused on the linear cationic peptides with non-hemolytic activity, which are downloaded from the Database of Antimicrobial Activity and Structure of Peptides (DBAASP). Referring to the MIC (Minimum inhibition concentration) values, we have assigned a positive label to a peptide if it shows antimicrobial activity; otherwise the peptide is labeled as negative. Here, we focused on the peptides showing antimicrobial activity against Gram-negative and against Gram-positive bacteria separately, and we created two datasets accordingly. Ten different physico-chemical properties of the peptides are calculated and used as features in our study. Following data exploration and data preprocessing steps, a variety of classification algorithms are used with 100-fold Monte Carlo Cross Validation to build models and to predict the antimicrobial activity of the peptides. Among the generated models, Random Forest has resulted in the best performance metrics for both Gram-negative dataset (Accuracy: 0.98, Recall: 0.99, Specificity: 0.97, Precision: 0.97, AUC: 0.99, F1: 0.98) and Gram-positive dataset (Accuracy: 0.95, Recall: 0.95, Specificity: 0.95, Precision: 0.90, AUC: 0.97, F1: 0.92) after outlier elimination is applied. This prediction approach might be useful to evaluate the antibacterial potential of a candidate peptide sequence before moving to the experimental studies.

Our understanding of phylogenetic relationships among Gadiformes fish is obtained through the analysis of a small number of genes, but uncertainty remains around critical nodes. A series of phylogenetic controversial exists at the suborder, family, subfamily, and species levels. A total of 1105 orthologous exon sequences and translated amino acid sequences from 36 genomes and 12 transcriptomes covering 33 species were applied to investigate the phylogenetic relationships within Gadiformes and address these problems. Phylogenetic trees reconstructed with the amino acid data set using different tree-building methods (RAxML and MrBayes) showed consistent topology. The monophyly of Gadifromes was confirmed in our study. However, the three suborders Muraenolepidoidei, Macrouroidei, and Gadoidei were not well recovered by our phy-logenomic study, rejecting the validity of suborder Muraenolepidoidei. Four major lineages were revealed in this study. The family Bregmacerotidae forming clade I was the basal lineage of Gadiformes. The family Merluciidae formed clade II. Clade III contained families Melanonidae, Muraenolepididae, Macrouridae (with subfamilies Trachyrincinae, Macrourinae, and Bathygadinae), and Moridae. Clade IV contained at least three families of suborder Gadoidei, i.e., Gadidae, Phycidae, and Ranicipitidae. The subspecies of Lota lota from Amur River were confirmed, indicating that exon markers were a valid high-resolution method for delimiting subspecies or distinct lineages within species level. The PSMC analysis of different populations of L. lota suggests a continuous decline since 2 Myr.

To explore the impact of parenting styles on the perception of campus non-physical bullying, 492 students in upper elementary school grades were surveyed by using the Delaware Bullying Victimization Scale, the Negative Coping Style Scale, the Negative Affect Scale, and the Egna Minnen Beträffende Uppfostran Questionnaire. The questionnaire survey was conducted in the fifth and sixth grades of eight primary schools in Zhejiang province. The results showed that cyberbullying was not significantly related to an anxious parenting style, but negative affect experiences, negative coping styles, negative family parenting styles, and the perception of campus non-physical bullying were all positively correlated with each other (p < 0.05). The refusal parenting style was shown to be an important factor that affected students’ perception of campus non-physical bullying; it was observed to directly affect students’ perception of campus non-physical bullying and indirectly affect students’ perception of campus non-physical bullying by influencing negative affect experiences and negative coping styles. In conclusion, negative affect experiences and negative coping styles had a chain-like mediating effect between the refusal parenting style and students’ perception of campus verbal bullying. Moreover, negative affect experiences had a partial mediating effect between the refusal parenting style and students’ perceptions of campus cyberbullying, relationship bullying, and non-physical bullying total scores. Implications and suggestions based on these results are also discussed.

Macromolecules with well-defined structures in terms of molar mass and monomer sequence became interesting building blocks for modern materials. The precision of the macromolecular structure makes fine-tuning of the properties of resulting materials possible. Conjugated macromolecules exhibit excellent optoelectronic properties that make them exceptional candidates for sensors construction. The importance of chain length and monomer sequence is particularly important in conjugated systems. The sequence lengths, monomer sequence and structural modification often influence the energy bang gap between HOMO and LUMO orbitals of the molecules that reflect in their properties. Moreover, the supramolecular aggregation that is often observed in oligo-conjugated systems is usually strongly affected by even minor structural changes that are used for sensor designs. This review summarizes the examples of well-defined conjugated macromolecules based on oligo(arylene ethynylene)s skeleton used for sensor applications. The sensing mechanisms and importance of uniformity of structure are discussed.

Bioinformatics is a rapidly developing field enabling scientific experiments through computer models and simulations. Considering the vast databases of biological data available, it is ex-tremely important to develop efficient methods and algorithms for their processing. Sequence comparison is the best method for studying the evolutionary interaction between genes. It is based on alignment – the process of arranging two or more sequences to achieve the maximum level of identity and degree of similarity. The paper presents a new version of the algorithm for pairwise DNA sequences alignment, based on a new method called CAT, where a dependency with a previous match and the closes neighbor are taken in consideration to increase uniqueness of the CAT profile and to reduce possible collisions, i.e. two or more sequence having same CAT profiles. This makes proposed algorithm suitable for finding exact match of a concrete DNA se-quence in a big set of DNA data faster. The generation of CAT profiles is made once before data has been uploaded to the database, allowing the profiles to be used as metadata for the sequenc-es. It consists of an algorithm to calculate a CAT profile against the selected reference sequences and an algorithm to compare two sequences based on the calculated CAT profiles. Improve-ments in generation of the CAT profiles, are detailed described in the paper. Block scheme, pseudo code tables and figures were updated according to the proposed new version and ex-perimental results. Experiments have been carried out with the new version of the method and different datasets to align DNA sequences based on the CAT method. New experimental results in terms of collisions, speed, and efficiency of the proposed solutions are presented. Experiments related to the performance comparison with Needleman-Wunsch were re-executed with the new version of the algorithm to confirm that we have the same performance. An analysis of the per-formance of the proposed CAT based algorithm against Knuth–Morris–Pratt algorithm, which has a complexity of O(n) and is one of the most widely used for searching biological data, was performed. The impact of prior matching dependencies on uniqueness for generated CAT pro-files is investigated. The analysis of the experimental results obtained by sequence alignment shows a small deviation of the proposed algorithm based on the CAT method, which can be ig-nored if this deviation is acceptable at the expense of performance. The time efficiency of the CAT algorithm remains constant, regardless of the length of the sequences. Therefore, the ad-vantage of the proposed method is its fast processing in the alignment of large sequences, for which the execution of the exact algorithms takes a long time. The example code realization of the CAT Method, under the protection of the GNU General Public License v3.0, can be accessed on GitHub at: https://github.com/HristoS/CATSequenceAnalysis.

An addition sequence is an important operation in many applications of computer science, such as multi-modular exponentiation and outsourcing protocols. Finding an addition sequence for a set of positive integers with the shortest length is challenging due to the high computational time required to find the solution. In this paper, a new metaheuristic algorithm is designed based on the simulated annealing strategy to generate a short addition sequence. The efficiency of the proposed algorithm was proved experimentally by comparing it with the previous exact and heuristic algorithms in terms of running time and the length of the addition sequence.

Attack investigation is an important research field in forensics analysis. Many existing supervised attack investigation methods rely on well-labeled data for effective training. While the unsupervised approach based on BERT can mitigate the issues, the high degree of similarity between certain real-world attack and normal behaviors makes it challenging to accurately identify disguised attacks. This paper proposes ConLBS, an attack investigation approach that combines the contrastive learning framework and multi-layer Transformer network to realize the classification of behavior sequences. Specifically, ConLBS constructs behavior sequences describing behavior patterns from audit logs, and a novel lemmatization strategy is proposed to map the semantics to the attack pattern layer. Four different augmentation strategies are explored to enhance the differentiation between attack and normal behavior sequences. Moreover, ConLBS can perform unsupervised representation learning on unlabeled sequences, and can be trained either supervised or unsupervised depending on the availability of labeled data. The performance of ConLBS is evaluated in two public datasets. The results show that ConLBS can effectively identify at-tack behavior sequences in the cases of unlabeled data or less labeled data to realize attack investigation, and achieve the superior effectiveness compared to existing methods and models.

Plant diseases are among the major factors affecting plant productivity. Biological control of plant diseases is preferred over chemical control as it is environment-friendly, cost-effective, and sustainable. Among many microbes capable of providing biological control of plant diseases, probiotic Bacillus species are most promising as they can survive in adverse conditions, provide plants with a wide range of benefits including protection from phytopathogens. Wheat blast caused by Magnaporthe oryzae Triticum pathotype (MoT) has emerged as a potential threat to global wheat production. Due to unreliability of fungicides and limited cultivar resistance, we aimed to screen and identify potential antagonist bacteria collected from internal tissues of rice and wheat seeds to determine their in vitro and in vivo inhibitory effects against MoT. Dual culture and seedling assays were performed to evaluate the efficacy of probiotic bacteria. Out of 170 bacterial isolates, three bacteria (BTS-3, BTS-4, and BTLK6A) were screened as potential antagonists against MoT in vitro. Artificial inoculation at the seedling stage showed that the isolates BTS-4, BTS–3, and BTLK6A reduced 89, 88, and 85% of wheat blast disease severity, respectively, compared to mock-inoculated control. The bacterial isolates were identified as Bacillus subtilis (BTS-3) and B. velezensis (BTS-4 and BTLK6A) through genome phylogeny. The whole genome sequence of these three bacterial strains decoded a number of orthologs to intrinsic genes of antimicrobial peptides, antioxidant defense enzymes, cell wall degrading enzymes, compounds involved in the induction of systemic resistance (ISR) in host plants, and volatile compounds to make them promising biologicals to control MoT in wheat. Combined data of in vitro and in vivo along with genome analysis suggest that Bacillus spp. suppress the destructive wheat blast disease likely through antibiosis and ISR in the host plants. Further field evaluation and characterization of antimicrobial compounds are needed for a better understanding of the mode of action and practical recommendation of these bacteria for wheat blast control in the farmers’ fields.

The world is facing a major health crisis, the global pandemic of COVID-19 caused by the SARS-CoV-2 coronavirus, for which no approved antiviral agents or vaccines are currently available. Here we describe a collection of codon-optimized coding sequences for SARS-CoV-2 cloned into Gateway-compatible entry vectors, which enable rapid transfer into a variety of expression and tagging vectors. The collection is freely available via Addgene. We hope that widespread availability of this SARS-CoV-2 resource will enable many subsequent molecular studies to better understand the viral life cycle and how to block it.

Road segment can be estimated from GPS trajectories by averaging. However, most existing averaging strategies suffer from high complexity or poor accuracy. For example, finding the optimal mean for a set of sequences is known to be NP-hard, while using Medoid compromises the quality. In this paper, we introduce three extremely fast and practical methods for solving the problem. The methods first analyze three descriptors and then use either a simple linear model or a more complex curvy model depending on an angle criterion. The results outperform Medoid and provide equal or better accuracy than the best existing methods while being very fast, and therefore suitable for real-time processing.

The exceptional increase in molecular DNA sequence data in open repositories is mirrored by an ever-growing interest among evolutionary biologists to harvest and use those data for phylogenetic inference. Many quality issues, however, are known and the sheer amount and complexity of data available can pose considerable barriers to their usefulness. A key issue in this domain is the high frequency of sequence mislabelling encountered when searching for suitable sequences for phylogenetic analysis. These issues include the incorrect identification of sequenced species, non-standardised and ambiguous sequence annotation, and the inadvertent addition of paralogous sequences by users, among others. Taken together, these issues likely add considerable noise, error or bias to phylogenetic inference, a risk that is likely to increase with the size of phylogenies or the molecular datasets used to generate them. Here we present a software package, phylotaR, that bypasses the above issues by using instead an alignment search tool to identify orthologous sequences. Our package builds on the framework of its predecessor, PhyLoTa, by providing a modular pipeline for identifying overlapping sequence clusters using up-to-date GenBank data and providing new features, improvements and tools. We demonstrate our pipeline’s effectiveness by presenting trees generated from phylotaR clusters for two large taxonomic clades: palms and primates. Given the versatility of this package, we hope that it will become a standard tool for any research aiming to use GenBank data for phylogenetic analysis.

According to statistics from the Food and Agriculture Organization, the world population will increase to about 91 million (Asia 51 million, Africa 19 million). A rise in the world’s population means an increased need for food. However, climate change has caused desertification and unpredictable weather, creating problems in the supply and demand of food. Sweet potato (Ipomoea batatas) is an alternative to solving the food problem, as it is one of the world’s most important food crops, especially in developing countries. The tuberous roots of sweet potato are usually used as staple food, animal feed, industrial material, or raw material for alcohol production. In the future, more variations of sweet potato will be needed for breeding this crop. Recently, molecular markers developed for sweet potato have demonstrated good potential for use in genetic selection. In this study, a cDNA library was constructed from the total RNA of sweet potato leaves. A total of 789 copies of the cDNA were cloned in Escherichia coli by employing the pGEM-T Easy vector. Sequencing was carried out by Solgent Co. (Korea). As many as 579 expressed sequence tag–simple sequence repeat (EST-SSR) markers were designed (73.38%) from the known cDNA nucleotide base sequences. The lengths of the developed EST-SSR markers ranged from 100 to 499 bp (average length 238 bp). Their motif sequence types were varied, with most being dinucleotides and pentanucleotides, and the most commonly found motifs were CAGAAT (29.0%) and TCT (2.8%). Based on these SSR-containing sequences, 619 pairs of high-quality SSR primers were designed using WebSat and Primer3web. The total number of primers designed was 144. Polymorphism was evident in 82 EST-SSR markers among 20 Korean sweet potato cultivars tested and in 90 EST-SSR markers in the two parents of a mapping population, Yeseumi and Annobeny. In this study, the hexaploid sweet potato (2n = 6x = 90) EST-SSR markers were developed in the absence of full-sequence data. Moreover, by acting as a molecular tag for particular traits, the EST-SSR marker can also simultaneously identify information about the corresponding gene. These EST-SSR markers will allow the molecular analysis of sweet potato to be done more efficiently. Thus, we can develop high-quality sweet potato while overcoming the challenges from climate change and other unfavorable conditions.

Breast cancer represents the most common neoplasm worldwide. Viral infections are involved with carcinogenesis, especially those caused by oncogenic Human Papillomavirus (HPV) genotypes. The relationship between HPV and various types of cancer, such as breast and lung, still requires further studies. After infection with HPV, there is a remodeling of the tumor microenvironment, providing a post-infection alteration with immunosuppressive characteristics. This study evaluated the role of HPV in breast adenocarcinoma cell lineage (MDA-MB-231), transfected with the HPV16 E5, E6, and E7 oncogenes and co-cultured with PBMCs. Immunophenotyping was performed. There was an increase in CD4+ T cells number when compared with non-transfected and transfected MDA-MB-231, especially the Treg profile. Moreover, proinflammatory intracellular cytokines, such as IFN-γ, TNF-α, and IL-17 were impaired by transfected cells and a decrease in the cytolytic ac-tivity of the CD8+ and CD56+ lymphocytes was also observed in the presence of HPV oncogenes, mainly with E6 and E7 in NK and TCD8+ cells. In conclusion, MDA-MB-231 breast cell lineage transfected with HPV oncogenes can downregulate the number and function of lymphocytes and monocytes.

Bromodomain-containing protein 4 (BRD4) is an intracellular protein that regulates expression of various cellular functions. This study investigated whether BRD4 inhibition can alter the immunomodulatory and antitumor effects of radiation therapy (RT). A murine breast cancer cell line was implanted into BALB/c mice. The dual-tumor model was used to evaluate the abscopal effects of RT. A total of 24 Gy was delivered and BRD4 inhibitor was injected intravenously. Tumor size was measured and in vivo imaging was performed to evaluate tumor growth. Flow cytometry and immunohistochemistry were performed to examine immunologic changes upon treatment. The combination of BRD4 inhibitor and RT significantly suppressed tumor growth compared to RT alone. BRD4 inhibitor reduced the size of the unirradiated tumor indicating that it may induce systemic immune responses. Expression of HIF-1α and PD-L1 in tumor was significantly downregulated by the BRD4 inhibitor. Proportion of M1 tumor-associated macrophages (TAMs) increased, and proportion of M2 TAMs decreased upon BRD4 inhibition. BRD4 inhibitor expanded CD4+ and CD8+ T cell populations and reduced the population of monocytic myeloid-derived suppressor cells (M-MDSCs). RT-induced splenic M-MDSCs decreased upon addition of BRD4 inhibitor. Therefore, addition of BRD4 inhibition significantly enhanced the systemic antitumor responses of local RT.

The article deals with auxetic structures made on the basis of suitably connected rigid rotating squares (from Grima and Evans), with axes of rotation on the squares’ surface. The geometric model and the resulting relationships that allow for the determination of Poisson’s ratio are considered in detail. It is demonstrated that changing the rotation axis position does not affect the negative Poisson’s ratio, equal to -1. The models built confirm the initial considerations and can offer new application possibilities.

Background: Triple negative breast cancer (TNBC) is the most aggressive form of breast cancer with poor outcomes. The molecular basis of TNBC remains poorly understood. The objective of this study was to explore the relationship between obesity and TNBC in premenopausal and postmenopausal Caucasian women using whole genome transcription profiling. Methods: We compared gene expression levels of tumor samples drawn from normal weight, overweight and obese in pre and postmenopausal women diagnosed with TNBC. We performed hierarchical clustering to assess similarity in patterns of gene expression profiles, and conducted network and pathway analysis to identify molecular networks and biological pathways. Results: We discovered gene signatures distinguishing normal weight from obese, normal weight from overweight and overweight from obese individuals in both premenopausal and postmenopausal women. The analysis revealed molecular networks and biological pathways dysregulated in response to obesity. Among the discovered pathways included the unfolded protein response, endoplasmatic reticulum stress, B cell receptor and the autophagy signaling pathways in obese premenopausal women and the integrin, axonal guidance, ERK/MAPK and Glutathione biosynthesis signaling pathways obese postmenopausal women. Conclusions: The results suggest that both overweight and obesity are associated with TNBC, highlighting the need for conformation of these results in independent studies.

Build a special identical equation, use its calculation characters to prove and search for solution of any odd converging to 1 equation through (*3+1)/2^k operation, change the operation to (*3+2^m-1)/2^k, and get a solution for this equation, give a specific example to verify. Thus prove the Collatz Conjecture is true. Furthermore, analysis the sequences produced by iteration calculation during the procedure of searching for solution, build a weight function model, prove it decrease progressively to 0, build a complement weight function model, prove it increase to its convergence state. Build a (*3+2^m-1)/2^k odd tree, prove if odd in (*3+2^m-1)/2^k long huge odd sequence can not converge, the sequence must outstep the boundary of the tree after infinite steps of (*3+2^m-1)/2^k operation.

Up to now, Schrödinger equation, Klein-Gordon equation (KGE) and Dirac equation are believed the fundamental equations of quantum mechanics. Schrödinger equation has a defect that there is no NKE solutions. Dirac equation has positive kinetic energy (PKE) and negative kinetic energy (NKE) branches. Both branches should have low momentum, or nonrelativistic, approximations: one is Schrödinger equation and the other is NKE Schrödinger equation. KGE has two problems: it is an equation of second time derivative, and calculated density is not definitely positive. To overcome the problems, it should be revised as PKE and NKE decoupled KGEs. The fundamental equations of quantum mechanics after the modification have at least two merits. They are of unitary in that everyone contains the first time derivative and are symmetric with respect to PKE and NKE. This reflects the symmetry of the PKE and NKE matters, as well as matter and dark matter, of our universe. The problems of one-dimensional step potentials are resolved by means of the modified fundamental equations for a nonrelativistic particle.

The present article aims at investigating the role of social support in the emotional well-being of young offenders. We hypothesized that perceived social support would be positively related to the emotional well-being of juvenile offenders. The methods were worked out to study perceived and received social support, psychological well-being and emotional state of the juvenile offenders. The entire sample consisted of 56 males aged from 15 to 18 years old (M = 16.5; SD = 0.8). 32 subjects (57%) were in pretrial detention and 24 participants (43%) were in a correctional camp located in the central region of Russia. The study detected that the level of psychological well-being of the respondents from the camp was correlated neither with perceived social support nor with the frequency of seeking assistance from the different sources of support. For the respondents in the pretrial detention, the level of psychological well-being was directly connected to the degree of the perceived support from the friends. The obtained differences might be associated with the influence of social environment in the pretrial detention and in the camps.

Phospholipases are among the important elements involved in lipid-dependent cell signaling that lead to the induction of downstream pathways. In the current study, phospholipases D (PLDs) gene family was characterized and compared in two important oilseeds crops, Brassica napus and Camelina sativa. The results revealed that PLD has 33 members in Camelina sativa (CsPLD) and 41 members in Brassica napus (BnPLD). All studied PLDs showed a negative GRAVY value, indicating that PLDs are probably hydrophilic proteins. Phylogenetic analysis separated PLDs into five subfamilies; gamma, delta, beta, alpha, and zeta. According to evolution analysis, a different evolution process was observed between CsPLD and BnPLD. In addition, the results disclosed that the most of the PLD genes have been segmentally duplicated under purifying selection. Cis-regulatory elements related to ABA and auxin responsiveness were more found in upstream region of CsPLDs, while elements linked with MeJA responsiveness were more dis-tributed in promoter region of BnPLDs. Analysis of the expression data showed that PLD alpha genes have a wide expression and are expressed in most tissues. Quantitative expression analysis (qPCR) of CsPLD genes under salt stress, 200 mM of NaCl, was done in different time series. The results revealed that the CsPLD genes are involved in the response to salinity stress and their expression levels enhance with the increase of salinity stress time. The outcomes of this research will be useful for future molecular work related to lipid signaling in oilseed plants.

Legionella is an opportunistic pathogen with a biphasic life cycle and humans are occasional hosts of Legionella. The aim of the study was to assess the distribution of virulence genes and genetic diversity among L. pneumophila isolated from water-supply systems of residential buildings in Latvia. In total, 492 water samples from 200 residential buildings were collected. Identification of Legionella spp. was performed according to ISO 11731 and 58 isolates were subjected to whole genome sequencing. At least one Legionella positive sample was found in 112 out of 200 apartment buildings (56.0%). The study revealed extensive sequence type diversity where 58 L. pneumophila isolates fell into 36 different sequence types. A total of 420 virulence genes were identified of which 260 genes were found in all sequenced L. pneumophila isolates. Virulence genes enhC, htpB, omp28, and mip were detected in all isolates, suggesting that adhesion, at-tachment, and entry into host cells are enabled for all isolates. The relative frequency of viru-lence genes among L. pneumophila isolates was high. High prevalence, extensive genetic diver-sity, and the wide range of virulence genes indicated that the virulence potential of environ-mental Legionella is high and proper risk management is of key importance to public health.

Most non-infectious diseases are associated with dysfunction of proteins or protein complexes. Аssociation between sequence and structure is analyzed since a long time, and analysis of sequence organization in domains and motifs is actual research area. A mathematical method is proposed here to identify the hierarchical organization of protein sequences. The method is based on pentapeptide as a unit of protein sequences. This method was applied on a non-homologous dataset of protein sequences. The analysis revealed 11 hierarchical levels of protein sequence organization, showing the relationship of these multiple fragments of sequences. Using different examples, we illustrated how the fragments of the spatial structure of protein correspond to the elements of the hierarchical structure of the protein sequence. A hierarchical structure is observed in the protein sequence. This methodology is an interesting basis for mathematically based classification of elements of spatial organization of proteins. Elements of the hierarchical structure of different levels of the hierarchy can be used for biotechnological and medical problems.

We report on the isolation of the previously uncultured Neocallimastigomycota SK4 lineage by two independent research groups from a wild aoudad sheep rumen sample (Texas, USA) and an alpaca fecal sample (Baden-Württemberg, Germany). Isolates from both locations showed near identical morphological and microscopic features, forming medium-sized white filamentous colonies with a white center of sporangia on agar roll tubes and a heavy biofilm in liquid media. Microscopic analysis revealed monocentric thalli, and spherical polyflagellated zoospores with 7–20 flagella. Zoospore release occurred through an apical pore as well as by sporangial wall rupturing, a duality that is unique amongst described AGF strains. Isolates were capable of growing on a wide range of mono-, oligo-, and polysaccharides substrates. Phylogenetic assessment based on the D1-D2 large rRNA subunit (D1-D2 LSU) and internal transcribed spacer-1 (ITS-1) regions demonstrated high sequence identity (minimum identity of 99.07% and 96.96%, respectively) between all isolates; but low sequence identity (92.4% and 86.7%, respectively) to their closest cultured relatives. D1-D2 LSU phylogenetic trees grouped the isolates as a new monophyletic clade within the Orpinomyces-Neocallimastix-Pecoramyces-Feramyces-Ghazallamyces supragenus group. D1-D2 LSU and ITS-1 sequences from the obtained isolates were either identical, or displayed extremely high sequence similarity to sequences recovered from the same Aoudad sheep sample on which isolation was conducted, as well as several sequences recovered from domestic sheep and few other herbivores. Interestingly, members of the SK4 clade seem to be encountered in animals grazing on summer pasture. We hence propose accommodating these novel isolates in a new genus, Aestipascuomyces (derived from the Latin word for “summer pasture”), and a new species, A. dupliciliberatus. The type strain is Aestipascuomyces dupliciliberatus strain R4.

Emerging and reemerging pathogens is a global challenge for public health. Recently, a novel coronavirus disease emerged in Wuhan, Hubei province of China, in December 2019. It is named COVID-19 by World Health Organization (WHO). It is known to be caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) that affects the lower respiratory tract and manifests as pneumonia in humans. Coronaviruses (CoVs) are structurally more complicated as compared to other RNA viruses. This viral epidemic has led to the deaths of many, including the elderly or those with chronic disease or compromised immunity. Viruses cause infection and diseases in humans of varying degrees, upper respiratory tract infections (URTIs) cause common cold while lower respiratory tract infections induce pneumonia, bronchitis, and even severe acute respiratory syndrome (SARS). The costs of COVID-19 are not limited. It equally affects all the medical, sociological, psychological, and economic aspects globally. This is regarded as the third deadly outbreak in the last two decades after Severe Acute Respiratory Syndrome SARS (2002–2003) and Middle East Respiratory Syndrome MERS (2012). Based on the sequence homology of SARS-CoV-2, different animal sources including bats, snakes, and pangolins have been reported as potential carriers of this viral strain. Real-time RT-PCR represents the primary method for the diagnosis of new emerging viral strain SARS-CoV-2. The transmission dynamics suggest that SARS-CoV-2 is transmitted from person-to-person through direct contact or coughing, sneezing, and by respiratory droplets. Several anti-viral treatments including lopinavir/ritonavir, remdesivir, chloroquine phosphate, and abidor are also suggested with different recommendations and prescriptions. Protective and preventive strategies as suggested by various health organization i.e. WHO and US Center for Disease Control and Prevention (CDC) must be adopted by everyone. This review covers the important aspects of novel COVID-19 including characteristics, virology, symptoms, diagnostics, clinical aspects, transmission dynamics, and protective measures of COVID-19.

The simple sequence repeats (SSRs) are small 1-6bp tandem repeat elements present across diverse genomes and involved in gene regulation and evolution. Presently we analyzed SSRs in genomes of 98 species of family Polyomaviridae across four genera. The genome size ranged from 3962bp (BM87) to 7369bp (BM85) but maximum genomes were in the range of 5 to 5.5 kb. The GC% had an average of 42% and ranged between 34.69 (BM95) to 52.35 (BM81). A total of 3036 SSRs and 223 cSSRs were extracted using IMEx with incident frequency from 18 to 56 and 0 to 7 respectively. The most prevalent mono-nucleotide repeat motif was “T” (48.95%) followed by “A” (33.48%). “AT/TA” was the most prevalent dinucleotide motif closely followed by “CT/TC”. The distribution was expectedly more in coding region with 77.6% SSRs of which nearly half were in Large T Antigen (LTA) gene. Notably, most viruses with humans, apes and related species as host exhibited exclusivity of mono-nucleotide repeats in AT region, a proposed predictive marker for determination of humans as host in virus in course of its evolution. Each genome has a unique SSR signature which is pivotal for viral evolution particularly in terms of host divergence.

Buildings have started to play a critical role in the stability and resilience of modern smart grids, leading to a refocusing of large scale energy management strategies from the supply side to the consumer side. When the buildings integrate local renewable energy generation in the form of renewable energy resources they become prosumers and this reflects into additional complexity into the operation of the interconnected complex energy systems. A class of methods of modelling the energy consumption patterns of the building have recently emerged as black-box input-output approaches with the ability to capture underlying consumption trends. These make use and require large quantities of quality data produces by non-deterministic processes underlying the energy consumption. We present an application of a class of neural networks, namely deep learning techniques for time series sequence modelling with the goal of accurate and reliable building energy load forecasting. The Recurrent Neural Network implementation uses Long Short-Term Memory layers in increasing density of nodes to quantify prediction accuracy. The case study is illustrated on four university buildings from temperate climates over one year of operation using a reference benchmarking dataset that allows replicable results. The obtained results are discussed in terms of accuracy metrics and computational and network architecture aspects and are considered suitable for further used in future in situ energy management at the building and neighbourhood levels.

One of creators of quantum mechanics P. Jordan in his work on quantum biology claimed that life's missing laws were the rules of chance and probability of the quantum world. The article presents author’s results of studying frequencies (or probabilities) of nucleotides on so-called epi-chains of long DNA sequences of various eukaryotic and prokaryotic genomes. DNA epi-chains are algorithmically constructed subsequencies of DNA nucleotide sequences. According to the algorithm of construction of any epi-chain of the order n, the epi-chain is such nucleotide subsequence, in which the numerations of adjacent nucleotides differ by natural number n (n = 1, 2, 3, 4,…). Correspondingly each epi-chain of order n ≥ 2 contains n times less nucleotides than the original DNA sequence. The presented results unexpectedly discover that in long single-stranded and double-stranded DNA of any tested genome its DNA epi-chains of different orders n (values n are not too large) have practically identical frequencies (or probabilities) of each kind of nucleotides. These data allow considering DNA as a regular rich set of epi-chains, which can play a certain role in genetic and epigenetic phenomena as the author belives. Appropriate rules of nucleotide frequencies on epi-chains of long DNA sequences are formulated for further their tests on a wider set of genomes. These results testify on existence of long-range coherence in long DNA and remind the Fröhlich's theory of long-range coherence in biological systems. The phenomenological data are discussed from different standpoints: the DNA double helices and helical antennas with circular polarizations of electromagnetic waves; relations with the Fröhlich's theory; numerical analysis of DNA epi-chains under binary representations of nucleotides. Results are useful for developing quantum and algebraic biology.

Selenium is a trace metal essential to human health, and its deficiency has been related to, for instance, cardiovascular and myodegenerative diseases, infertility and osteochondropathy Kashin-Beck disease. It is incorporated as selenocysteine to selenoproteins, which protect against reactive oxygen and nitrogen species. They also participate in the activation of thyroid hormone, and play a role in immune system functioning. The synthesis and incorporation of selenocysteine occurs via a special mechanism, which differs from the one used for standard amino acids. The codon for selenocysteine is the regular in-frame stop codon, which can be passed by specific complex machinery participating in translation elongation and termination. This includes the presence of selenocysteine insertion sequence (SECIS) in the 3’-untranslated part of the selenoprotein mRNAs. Selenium deficiency is known to control both selenoprotein and non-selenoprotein transcriptomes. Nonsense-mediated decay is involved in the regulation of selenoprotein mRNA levels, both other mechanisms are also possible.

This study investigates the effects of ambient illumination and negatively polarized text color on visual fatigue, exploring the issue of visual fatigue when using visual display terminals in low-illumination environments. The research methodology utilized an experimental design to collect data on changes in pupil accommodation and blink rate through an eye tracker. Partici-pants completed a reading task while exposed to various text colors and ambient light conditions to evaluate visual fatigue and cognitive performance. The study's findings suggest that text color significantly affects visual fatigue, with red text causing the highest level of visual fatigue and yellow text causing the lowest level of visual fatigue. Improvements in ambient lighting reduce visual fatigue, but the degree of improvement varies depending on the text color. Additionally, cognitive performance is better when using yellow and white text but worse when using red text. Yellow text is the most effective choice for reducing visual fatigue under negative polarity. In-creasing ambient lighting can also improve visual fatigue in low-illumination conditions. These findings will offer valuable guidance for designing visual terminal device interfaces, especially for low-illumination or night environments, to minimize visual fatigue and improve the user ex-perience.

This article systematically disproves the notion that entropy is a measure of disorder and disproves Schrödinger's notion of negative entropy (negentropy) using multiple novel and compelling arguments. To mathematically describe the second law of thermodynamics, the concept of entropy was created and defined in the 1860s as heat energy divided by thermodynamic temperature, and the entropy of an object increases when it absorbs heat. This is the uncontroversial and fundamental nature of entropy, which is pivotal to current thermodynamics and from which multiple facts are deduced. These facts consistently disprove the above two widely accepted notions. Multiple biological facts (e.g., life orderliness is encoded and provided by inherited genes rather than entropy decline) can also disprove Schrödinger's negentropy notion. This article further elucidates the reasoning errors of the two notions. Moreover, the second law of thermodynamics and the notion that many natural or social systems tend to become more disordered over time result from distinct statistical probabilities and are hence independent of each other.

This study aims to spatially analyze the distribution characteristics of vacant homes in Asan-si, Chungcheongnam-do, and understand the differences in factors causing vacant homes by type. We use a variety of statistical methods to examine these factors and identify key influencing factors such as the number of vacant stores, changes in overall population, land use complexity, and physical characteristics of land and buildings. The findings reveal that the factors contributing to the occurrence of vacant homes vary significantly by region and property type, highlighting the need for region-specific policies. For instance, in old town areas, small lot ratios and land use complexity are significant, while in rural village, the average number of floors and land use complexity play a major role. This study underscores the diversity of factors influencing vacant homes, suggesting that policies should be tailored to the unique characteristics of different regions to effectively address this issue.

ABSTRACT Background: To date, the COVID-19 pandemic has been the foremost health concern for humankind in the new millennia. This paper aims to describe the related hospitalizations in Italy during the first two years of the health emergency. Design and methods: This is a retrospective, population-based study of Italian hospitalizations for patients diagnosed with COVID-19 during the 2020-2021 period, extracted from the National Hospital Discharge Registry. The outcome variables considered include hospital admissions, costs, and length of stay, among other hospitalization-level variables. Costs were estimated through the charges associated with the Diagnosis-Related Group and Major Diagnostic Categories coding system, plus an additional cost attributed to COVID-19 admissions. To these charges was added an extra cost defined by the ministry of health. Results: In Italy, there were 357,354 hospitalizations for COVID-19 attributed to 298,856 patients in 2020 and 399,043 hospitalizations for COVID-19 attributed to 333,447 patients in 2021. COVID-19 patients faced a transfer rate thrice that of other patients. Hospitalizations were concentrated predominantly in the northern regions, particularly in the first year. Hospitalization rates varied by age in a sine wave pattern, peaking in the youngest and oldest age groups, with mortality rates escalating with age— tending to remain below 3% for those under 44 but surging to 40% in individuals over 75. The financial impact of COVID-19 hospitalizations was substantial, with total costs reaching €3.97 billion in 2020 and €4.99 billion in 2021. Costs per admission and per day also rose, from €11,112 and €807 in 2020 to €12,503 and €844 in 2021, respectively. Excluding the added financial burden of COVID-19, costs would have been notably lower. Hospitalizations involving continuous invasive mechanical ventilation were particularly costly (about 24.000 euros x admission), reflecting the significant resources required for these treatments. Conclusion: Implementing a protective pad around the entire health system that leverages networks of family doctors and nurses, connected in real time to the entire health system, can be crucial. Such a network, tasked with monitoring the local epidemiological situation, protecting vulnerable individuals also through telehealth visits, and establishing a triage system for infections in the initial phase, may effectively help in managing virus spread and protecting hospitals from unpredictable waves of admission demand. Strengthening primary health care could be a decisive factor for the future and enhance the system's resilience in facing new challenges.

We have successfully synthesized a series of Bi doped BaFe2As2 high quality single crystals for the first time. The x-ray diffraction (XRD) patterns show an expansion of lattice parameter c with Bi doping, indicating a negative pressure effect. By investigating the resistivity, a Fermi liquid (FL) to non-Fermi liquid (NFL) crossover is observed from normal state to antiferromagnetic order state, accompanied by three superconducting transitions labeled as SC I, SC II and SC III which are supposed to be induced from three superconducting realms with various Bi concentration. Thus, the NFL behavior is proposed to be closely related with the presence of superconductivity. The magnetic susceptibility measurements further speculates that the SC I and SC III phases should be filamentary superconductivity while the SC II be a possible bulk superconductivity with TC 7 K.

Buckground: Although ceftazidime/avibactam (CAZ/AVI) has become important option for treating adults and children, no recommendations exist for neonates. We report a neonatal sepsis case due to CAZ/AVI-resistant KPC-2 producing-Klebsiella pneumoniae carrying blaVEB-25 and the use of a customized active surveillance program in conjunction to infection control measures. Methods: The index case was an extremely premature neonate hospitalized for 110 days that had been previously treated with multiple antibiotics. Customized molecular surveillance was implemented at hospital level and enhanced infection control measures were taken for early recognition and prevention of outbreak. Detection and identification of blaVEB-25 was performed by next-generation sequencing. Results: That was the first case of a bloodstream infection caused by KPC producing K. pneumoniae that was resistant to CAZ/AVI without the presence of a metalo-β-lactamase in the multiplex PCR platform in a neonate. All 36 additional patients tested (12 in the same NICU and 24 from other hospital departments) carried wild-type blaVEB-1 but they did not harbor blaVEB-25. Conclusion: The emergence of VEB-25 is signal for horizontal transfer of plasmids at hospital facilities and it is of greatest concern for maintaining a sharp vigilance for surveillance of novel resistance mechanisms. Molecular diagnostics can guide appropriate antimicrobial therapy and early implementation of infection control measures against antimicrobial resistance.

Triple negative breast cancer (TNBC) has a negative expression of estrogen receptors (ER), progesterone receptors (PR), or human epidermal growth factor receptors (HER2). The survival rate for TNBC is generally worse than other breast cancer subtypes. TNBC treatment has made significant advances, but certain limitations remain. Treatment for TNBC can be challenging since the disease has various subtypes. Individualized therapy is recommended rather than generalized therapy, given the genetic variations among these TNBC subtypes. A precise and effective treatment for TNBC requires identifying prognostic markers. Depending on the type and stage of TNBC, patients are treated with various therapeutic interventions. A variety of treatment options are available, such as chemotherapy, immunotherapy, radiotherapy, and surgery. Chemotherapy is the most common of these options. TNBC is generally treated with systemic chemotherapy using drugs such as anthracyclines and taxanes in the neoadjuvant or adjuvant settings. Developing resistance to anticancer drugs and off target toxicity are the primary hindrances to chemotherapeutic solutions for cancer. It is imperative that researchers, clinicians, and pharmaceutical companies work together to develop effective treatment options for TNBC. Several studies have suggested nanotechnology as a potential solution to the problem of suboptimal TNBC treatment.

Sphingomonas paucimobilis is an opportunist pathogen bacillus gram-negative aerobic with a rare occurrence. We present a case in an immunocompetent man successfully treated by surgical debridement, purulent drainage and with an associated course of antibiotics. A large necrotic infection, approximately 5 cm x 3 cm, in a 74-year-old man was identified. Empirical antibiotic therapy with ciprofloxacin 400mg EV 12/12 hours, associated with clindamycin 600mg EV 6/6 hours and pain control was done through dipyrone 1gr, tramadol 400 mg. Deep venous thrombosis was prevented through the prescription of enoxaparin 40mg subcutaneous once a day during hospitalization. The case was well illustrated with pictures throughout treatment. Complete healing was achieved after 90 days. Herein, we present a case of cutaneous contamination. The presented case is the third cutaneous contamination case reported in the literature and the first reported case in the Amazonia region in Brazil.

Evolution remains an incessant process in viruses, allowing them to elude host immune response and induce severe diseases, impacting the diagnostic and vaccine effectiveness. Predicting emerging viral genomes is crucial, particularly in diseases like dengue, where viruses disrupt host cells, leading to fatal outcomes. Deep learning has been applied to predict dengue fever cases; there has been relatively less emphasis on its significance in forecasting emerging Dengue Virus (DENV) serotype. While Recurrent Neural Networks (RNN) were originally designed for modeling temporal sequences, our proposed DL-DVE generative and classification model, trained on complete genome data of DENV, transcends traditional approaches by learning semantic relationships between nucleotides in a continuous vector space instead of representing contextual meaning of nucleotide characters. Leveraging 2000 publicly available DENV complete genome sequences, our Long Short-Term Memory (LSTM) based generative and Feedforward Neural Network (FNN) based classification DL-DVE model showcases proficiency in learning intricate patterns and generating sequences for emerging serotype of DENV. The generative model showed accuracy of 93% and the classification model provided insight into the specific serotype label, corroborated by BLAST search verification. Evaluation metrics such as ROC-AUC value 0.818, accuracy, precision, recall and F1 score all to be around 99.00%, demonstrated the classification model’s reliability.  Our model classified the generated sequences as DENV-4, exhibiting 65.99% similarity to DENV-4 and around 63-65% similarity with other serotypes, indicating notable distinction from other serotypes. Moreover, the intra-serotype divergence of sequences with a minimum 90% similarity underscored their uniqueness. We analyzed the conserved motifs in the genome through MEME Suite (version 5.5.5). Our research strives to contribute to the ongoing fight against the Dengue virus by offering predictive insights into its genomic evolution. Looking ahead, proactive predictive modeling before mutations occur holds potential for guiding vaccine design and diagnostic kit development.

This review provides an overview of advancements in plant genomics, emphasizing key stages in genomics projects and addressing associated challenges. Long read sequencing enables the cost-effective sequencing of plant DNA and assembly of highly continuous genome sequences - often even separating haplophases. Incorporating external hints, such as cDNA sequences from RNA-seq or full length cDNA sequencing, enhances the identification of gene models. While these steps enable high-throughput exploration of numerous plant genomes, a significant bottleneck lies in elucidating gene functions. The classical approach based on wet lab methods is impractical when dealing with thousands of genes in a new genome sequence. To overcome this challenge, computational tools harnessing existing information for cross species knowledge transfer are essential for expediting the functional annotation process. In support of researchers entering the field of plant genomics, a collection of recommended tools has been curated and is accessible at https://github.com/bpucker/ToolOverview.

In some applications of microgrid and distributed generation, it is required to feed islanded or stand-alone loads with high-quality voltage to provide low total harmonic distortion (THD). To fulfil these demands, an LC filter is connected to the output terminals of power electronics converters. A cascaded voltage and current control loop with pulse-width modulation schemes are used to regulate the voltage and current in these systems. However, these strategies have some drawbacks, particularly when multiple-input multiple-output plants (MIMO) are controlled using single-input single-output (SISO) design methods. This methodology usually produces a sluggish transient response and cross-coupling between different control loops. In this paper, a model predictive control (MPC) strategy based on the concept of optimal switching sequences (OSS) is designed to control voltage and current in an LC filter connected to a three-level neutral-point clamped converter. The strategy solves two well-formulated optimisation problems to achieve control of the LC filter variables and the voltages of the DC-link capacitors. Hardware-in-the-Loop (HIL) results are obtained to validate the feasibility of the proposed strategy, using a PLECS-RT HIL platform and a DSP Microlab Box controller. In addition to the good dynamic performance of the proposed OSS-MPC, it is demonstrated by the HIL results that the control algorithm is capable of obtaining low total harmonic distortion (THD) in the output voltage for different conditions.

The two main strategies used in this study are the binary representation and the decomposition of a natural number into many compound functions of odd function and even function. The Collatz conjecture regarding odd even numbers in number theory can be examined and discussed using them in this way: The sequence created by the finite iterations of the Collatz function becomes the ultimately periodic sequence if any natural number is the beginning value, proving the conjecture that has been held for 85 years.

Alfalfa is an important forage crop around the world. LncRNAs are considered to be a class of functional biomacromolecules, while little is known about lncRNAs in alfalfa. In this study, RNAs from different tissues of alfalfa were sequenced and anlyzed with full-length transcriptome sequencing technology, yielding the full-length transcripts dataset of alfalfa. Based on sequencing and public RNA-seq data, lncRNAs of alfalfa were predicted genome-wide by CPC2 and PLEK. The results showed most lncRNAs shared low sequence conservation with those in other plant species, part of which seems originate from plastid genome. We also identified 88563 lncRNAs, approximately 99.8% of total lncRNAs, with possibility of coding small ORFs using two prediction tools. Our research generated the biggest sequence set of alfalfa lncRNAs, and revealed some plastid originated lncRNAs with high sequence conservation.

Cymbidium goeringii, locally known as the spring orchid in Korea, is one of the most important and popular horticultural species in the family Orchidaceae. C. goeringii cultivars were originated from plants with rare phenotypes in wild mountains where pine trees commonly grow. This study aimed to determine the cultivar-specific combined genotypes (CGs) of short sequence repeats (SSRs) by analyzing multiple samples per cultivar of C. goeringii. In this study, we collected more than 4,000 samples from 67 cultivars and determined the genotypes of 12 SSRs. Based on the most frequent combined genotypes (CG1s), the average observed allele number and combined matching probability were 11.8 per marker and 3.118×10-11, respectively. Frequencies of the CG1 in 50 cultivars (n ≥ 10) ranged from 40.9% to 100.0%, with an average of 70.1%. Assuming that individuals with the CG1 are genuine in the corresponding cultivars, approximately 30% of C. goeringii on the farms and markets may be not genuine. The dendrogram of the phylogenetic tree and principal coordinate analysis largely divided the cultivars into three groups according to their countries of origin; however, the genetic distances were not distant among the cultivars. In conclusion, this dataset of C. goeringii cultivar-specific SSR profiles could be used for ecogenetic studies and forensic authentication. This study suggests that genetic authentication should be introduced for the sale of expensive C. goeringii cultivars. We believe that this study will help establish a genetic method for the forensic authentication of C. goeringii cultivars.

The suitability of an animal model to study human diseases heavily relies on the similarity between the two species at the genetic, epigenetic, gene expression and metabolic levels. However, consistent data from different animal models at each level to evaluate this suitability is lacking. With the availability of genome sequences for many mammalian species it is now possible to compare animal models based on the genomic similarities. Here, we compare the coding sequences (CDS) of five mammalian models that include rhesus macaque, marmoset, pig, mouse and rat with those from human. We identified 10,316 conserved CDS across the five organisms and human based on the sequence similarity. Mapping the human disease-associated single nucleotide polymorphisms (SNPs) from these conserved CDS in each species has identified species-specific association with various human diseases. While associations for a disease such as colon cancer were prevalent in multiple model species, pig showed the highest number (117 diseases) of model-specific human disease associations. Based on the percentage of disease-associated SNP-containing genes, marmoset models are well suited to study many human ailments including behavioral and gastrointestinal diseases. Comparison of gene expression levels of the conserved CDS from colon, heart, kidney, lung, skeletal muscle, and spleen tissues in these models showed correlations with human expression levels in a tissue-specific manner. In the gastrointestinal tissues (colon, spleen), the pig showed the highest correlation while mouse displayed a better correlation in the heart and kidney. This study demonstrated genomic as well as tissue-specific expression-based similarity evaluation of five animal models against human that could help investigators select a suitable animal model to study their targeted disease.

Leishmaniasis is a disease caused by parasites of Leishmania genus and transmitted by sand fly vectors. Tegumentary leishmaniasis is the most prevalent clinical outcome in Latin America afflicting people from 18 countries. In Panama, leishmaniasis has annual incidence rates as high as 3000 cases, representing therefore one of the major public health problems. In endemic regions, L. panamensis is responsible for almost eighty percent of the human cases that present different clinical outcomes. This differences in disease outcomes could be result of the local interplay between L. panamensis variants and human hosts with different genetic backgrounds. The genetic diversity of L. panamensis in Panama has only been partially explored, and the variability reported for this species is based on few studies restricted to small populations and/or with poor resolutive markers at low taxonomic levels. Accordingly, in this study we explored the genetic diversity of sixty-nine L. panamensis isolates from different endemic regions of Panama using a MLST approach based on four housekeeping genes (Aconitase, ALAT, GPI and HSP70). Two to seven haplotypes per locus were identified, and regional differences in L. panamensis genetic diversity were observed. Genotype analysis evidenced the circulation of thirteen L. panamensis genotypes, a fact that might have important implications for the local control of the disease.

Foot and Mouth Disease (FMD) is a viral disease, widespread and highly contagious affecting mainly cloven-hoofed domestic and wild animals. FMD can lead to high economic losses due to reduction in animals’ production such as drop of milk production, loss of body weight and high mortality rate in young ruminants. Sixteen nasal swabs and epithelial tissues were collected from animals showing typical clinical signs of FMD during the last FMD outbreak in Libya in 2018-2019. Blood samples, swabs and epithelial tissues impressions on Flinders Technology Associates (FTA) cards were shipped to the FMD Reference laboratory in Brescia, Italy, and tested for the detection of FMD viruses. Nucleic acids were extracted from the FTA cards and molecular testing of the examined FTA cards confirmed that the FMD virus circulating in Libya was serotype O. Sequencing analysis of the FMD virus VP1 gene confirmed that FMD virus strain was serotype O/East Africa 3 (O/EA-3) topotype. The phylogenetic of the VP-1 gene of the FMD virus showed very high nucleotide identity (99.8%) between the virus circulating in Libya and the Algerian FMD virus strains isolated in Algeria on 2018 and 2019.

Magnesium transporters (MGTs) play a prominent role in the absorption, transport and storage of magnesium in plant cells. In the present study, MGT gene family members were identified and characterized in two species of cucurbitaceae, including C. sativus and C. lanatus. 20, 19, and 20 MGT genes were recognized in C. lanatus, C. sativus, and C. melo, respectively. According to physicochemical properties, the members of each sub-class of MGTs in the species of cucurbitaceae showed the close relationship. Proteins from NIPA were identified as hydrophilic proteins with high stability. Based on phylogenetic analysis, MGT family members were classified into three groups, and NIPAs showed more diversity. Besides, duplication events were not identified between the MGT members in C. lanatus, and C. sativus. According to pocket analysis, residues such as L, V, S, I, and A were frequently observed in the binding sites of MGT proteins in both species. The prediction of post-translation modifications revealed that MSR2 proteins have high phosphorylation potential than other sub-classes in both studied plants. The expression profile of MGTs showed that MGTs are more expressed in root tissues. In addition, MGTs showed differential expression in response to abiotic/biotic stresses as well as hormone application and NIPAs were more induced in response to stimuli in watermelon. The results of this study, as the primary work of MGT gene family, can be used in programs related to cucurbitaceae breeding.

In this paper we establish a topological framework of τ-structures to quantify the evolutionary transitions between two RNA sequence-structure pairs. τ-structures developed here consist of a pair of RNA secondary structures together with a non-crossing partial matching between the two backbones. The loop complex of a τ-structure captures the intersections of loops in both secondary structures. We compute the loop homology of τ-structures. We show that only the zeroth, first and second homology groups are free. In particular, we prove that the rank of the second homology group equals the number γ of certain arc-components in a τ-structure, and the rank of the first homology is given by γ−χ+1, where χ is the Euler characteristic of the loop complex.

This article presents description of social structures such as, for example, states, in the context of their consideration as systems. Moreover, it seeks to develop K. Marx’s model in terms of systematic approach, as well as to justify the application of the Fibonacci sequence to systems in general and, in particular, to social systems. The description covers a wide range of issues, ranging from the assertion of the basic principle of living systems as patterns in resources flows to description of functions of various aspects of states and their economics in terms of objective needs of such structures. In addition, this article justifies synergetic effect based on proposed model, and the way this effect is applied to state systems. Moreover, it includes the description of main changes of socio-economic formations throughout the history as a natural development of social systems, including possible modern stages. The fundamental tool of this description is description of essence of the mechanism of property rights and its formation options. The differences of two extreme directions of such development are also described on the basis of the objective factor of resource provision. Special attention is given to the concept of surplus value as a feature of social production systems.

The aim of this paper is to discuss the relations between various notions of sequential completeness and the corresponding notions of completeness by nets or by filters in the setting of quasi-metric spaces. We propose a new definition of right $K$-Cauchy net in a quasi-metric space for which the corresponding completeness is equivalent to the sequential completeness. In this way we complete some results of R.~A. Stoltenberg, Proc. London Math. Soc. \textbf{17} (1967), 226--240, and V.~Gregori and J.~Ferrer, Proc. Lond. Math. Soc., III Ser., \textbf{49} (1984), 36. A discussion on nets defined over ordered or pre-ordered directed sets is also included.

Background: SARS-CoV-2 infection has spread to over 200 countries since it was first reported in December of 2019. Significant country-specific variations in infection and mortality rate have been noted. Although country-specific differences in public health response have had a large impact on infection rate control, it is currently unclear as to whether evolution of the virus itself has also contributed to variations in infection and mortality rate. Previous studies on SARS-CoV-2 mutations were based on the analysis of ~ 160 SARS-CoV-2 sequences available until mid-February 2020.^{2, 3, 4, 5} By mid-April, > 550 SARS-CoV-2 sequences had been deposited in GenBank, and over 8,200 in the GISAID database. Methods: We performed a sequence analysis on 474 SARS-CoV-2 genomes submitted to GenBank up to April 11, 2020 by multiple alignment using Map to a Reference Assembly and Variants/SNP identification. The results were verified on a larger scale, 8,126 hCoV-19 (SARS-CoV-2) sequences from GISAID database. Results: We identified 5 recently emerged mutations in many isolates (up to 40%). Our analysis highlights 5 frequent new mutations that have emerged since late February 2020. These mutations are: one each missense (non-synonymous) mutation in orf1ab (C1059T), orf3 (G25563T) and orf8 (C27964T), one in 5’UTR (C241T), one in a non-coding region (G29553A). The final mutation (G29553A) was found to be almost exclusive to the US isolates. The first 3 mutations are non-synonymous, leading to amino acid substitutions in the viral protein sequence. Except for C241T, all the novel mutations identified are absent in the isolates from Italy and Spain in the SARS-CoV-2 genomes deposited in GenBank and GISAID by April 13, 2020. Conclusion: The results of current study indicate that new mutations are emerging as COVID-19 pandemic are spreading to different countries and that geography specific mutants may exist. The findings of current study lay the foundation for further investigation into the impact of SARS-CoV-2 mutations on disease incidence, severity, and host immune response. In addition, it may also provide insights into vaccine development and serological response detection for the virus.

We obtain two generalizations of a known theorem of A. Alam and M. Imdad (Fixed Point Theory Appl. 17 (2015) 693–702) showing that some standard proofs can be obtained involving only Cauchy sequences of the successive approximations instead of the usual successive approximations sequences. Suitable examples prove the effective generalization of our results in metric spaces not necessarily complete.

Background: Metastatic triple-negative breast cancer (TNBC) is aggressive with a poor median overall survival (OS), ranging from 8 to 13 months. There exists considerable heterogeneity in the survival at the individual patient level. To better understand the survival heterogeneity and improve risk stratification, our study aims to identify the factors influencing survival utilizing a large patient sample in the National Cancer Database (NCDB). Methods: Women diagnosed with metastatic TNBC from 2010 to 2020 in the NCDB were included. Demographic, clinic-pathological, treatment data, and overall survival (OS) outcomes were collected. Kaplan-Meier curves were used to estimate OS. The log-rank test was used to identify OS differences between groups for each variable in the univariate analysis. For the multivariate analysis, the Cox proportional hazard model with backward elimination was used to identify factors affecting OS. Adjusted hazard ratios and 95% confidence intervals are presented. Results: 2,273 women had a median overall survival of 13.6 months. Factors associated with statistically significantly worse OS included older age, higher comorbidity scores, specific histologies, higher number of metastatic sites, presence of liver or other site metastases in those with only one metastatic site (excluding brain metastases), presence of cranial and extra-cranial metastases, lack of chemotherapy, lack of immunotherapy, lack of surgery to distant sites, lack of radiation to distant sites, and receipt of palliative treatment to alleviate symptoms. In the multivariate analysis, comorbidity score, histology, number of metastatic sites, immunotherapy, and chemotherapy had a statistically significant effect on the OS. Conclusions: Through NCDB analysis, we have identified prognostic factors for metastatic TNBC. These findings will help improve prognostication at diagnosis, optimize treatment strategies, and facilitate patient stratification in future clinical trials.

When asked to estimate the carbon footprint of a bundle of relatively low carbon footprint items and relatively high carbon footprint items, people typically report a lower value compared to estimating the high carbon footprint items alone. This finding is called the negative footprint illusion and suggests people report the average rather than sum of the combined items’ carbon footprint. In a recent paper by Gorissen et al. (2024), the authors claimed that people are immune to this illusion if the question is framed differently. Specifically, they found that estimates of the environmental friendliness of a set comprising a burger (high carbon footprint) and an organic apple (low carbon footprint) was higher than for a set comprising the burger alone, whereas no difference was found between the two sets when participants were asked to estimate how environmentally damaging they were. Using larger item categories wherein the degree of the items’ environmental impact is clearly communicated, here we show it does not matter whether participants are required to estimate how friendly or damaging the items are. The roles of attribute substitution, dependent variables, and independent variables (stimulus characteristics) in modulating the negative footprint illusion is discussed.

Background: As the most invasive breast cancer (BrCa), triple-negative BrCa (TNBC) has the worst survival. The use of dexmedetomidine potentially affected BrCa surgery and dexmedetomidine was reported to have direct effects on TNBC cells. The objective of this study is to explore the mechanisms underlying the effect of dexmedetomidine on TNBC. Methods: Dexmedetomidine targets were predicted using The Cancer Genome Atlas data SwissTargetPrediction. Cell lines MDA-MB-231, MCF7, and MCF10A were used to validate the targets in TNBC with both clinical samples and cell lines. Cancer cell lines and normal breast cell lines were grouped in cancer and normal groups respectively. Both groups were exposed to dexmedetomidine treatment. Cell Counting Kit-8 was used to determine the effect of dexmedetomidine on cells with target silencing. The binding model of the candidate targets was docked and critical amino acids were mutated to validate the binding model. Results: Dexmedetomidine selectively inhibits cancer cells. Catalytic subunit of the DNA-dependent protein kinase (PRKDC), indoleamine 2,3-dioxygenase 1 (IDO1), opioid receptor kappa 1 (OPRK1), glutaminyl-peptide cyclotransferase (QPCT), macrophage migration inhibitory factor (MIF), potassium voltage-gated channel, subfamily H (Eag-related), member 2 (KCNH2), cholinergic receptor, muscarinic 3 (CHRM3), and potassium intermediate/small conductance calcium-activated channel, subfamily N, member 4 (KCNN4) were identified as dexmedetomidine targets in TNBC. The expression levels of PRKDC, IDO1, MIF, KCNH2, CHRM3, and KCNN4 were found to be upregulated in TNBC tissues compared to non-TNBC tissues(p<0.05). Silencing of these genes was found to reduce the sensitivity of TNBC cells to dexmedetomidine(p<0.05). This effect was counteracted when the silenced genes were overexpressed, resulting in an increase in the sensitivity of cells to dexmedetomidine (p<0.05). Furthermore, a direct interaction between dexmedetomidine and IDO1 and CHRM3 was observed, which regulated the sensitivity of cells to dexmedetomidine(p<0.05).Conclusion: IDO1 and CHRM3 are direct targets of dexmedetomidine in TNBC.

The negative binomial regression model (NBRM) is a generalized linear model which relaxes the restrictive assumption by the Poisson regression model when the variance is equal to the mean. The estimation of the parameters of the NBRM is obtained using the maximum likelihood (ML) method. Maximum likelihood estimator becomes unstable when the explanatory variables are linearly dependent, a situation known as multicollinearity. Based on this, we developed a new estimator called modified jackknifed Negative Binomial Kibria-Lukman (MJNBKL) estimator for the radiation of multicollinearity in NBRM using four different biasing (shrinkage) parameters. We establish superiority condition for MJNBKL estimator over the ones. The performance MJNBKL estimator was ascertained by comparing it with the existing ones through a Monte Carlo simulation study and two real life application datasets. The results of the simulation and real life application show that MJNBKL estimator outperformed the other estimators compared with by having the smallest MSE across all sample sizes and for different levels of correlation for the four biasing parameters used and the third biasing parameter is the optimal shrinkage parameter with the lowest MSE.

Abstract Background. There is an inherent limit in the accuracy of our measurements, set by nature itself and predicted by Heisenberg's uncertainty principle, which defines the properties of nature in the microcosmos. There is a fundamental limit to the accuracy with which complementary phys-ical quantities of a particle can be predicted from their initial conditions. As classical physics is essentially considered at borderline of quantum mechanics, so the power of uncertainty princi-ple is limited in describing everyday life perceived or managed phenomena. Method. In this study, we apply Heisenberg's uncertainty principle to children under diagnostic uncertainty re-garding appendicitis. We analyze this phenomenon in clinical practice. Results. Medical practice is full of uncertainty. False negative decisions correlate with delays in treatment and adverse outcomes in children with atypical appendicitis. On the other hand, false-positive surgery deci-sions result in negative appendectomies. With improvement of technology, the incidence of complicated appendicitis or negative appendectomies due to diagnostic uncertainty has de-creased but cannot be ignored or eliminated. Conclusion. According to the principle, there is a fundamental limit to the accuracy with which the complementary variables of negative appen-dectomy and complicated appendicitis can be observed or measured simultaneously. What does all this mean for the physician?

Prosthetics have come a long way since their inception, and recent advancements in materials science have enabled the development of prosthetic devices with improved functionality and comfort. One promising area of research is the use of auxetic metamaterials in prosthetics. Auxetic materials have a negative Poisson's ratio, which means that they expand laterally when stretched, unlike conventional materials, which contract laterally. This unique property allows for the creation of prosthetic devices that can better conform to the contours of the human body and provide a more natural feel. In this review article, we provide an overview of the current state of the art in the development of prosthetics using auxetic metamaterials. We discuss the mechanical properties of these materials, including their negative Poisson's ratio and other properties that make them suitable for use in prosthetic devices. We also explore the limitations that currently exist in implementing these materials in prosthetic devices, including challenges in manufacturing and cost. Despite these challenges, the future prospects for the development of prosthetic devices using auxetic metamaterials are promising. Continued research and development in this field could lead to the creation of more comfortable, functional, and natural-feeling prosthetic devices. Overall, the use of auxetic metamaterials in prosthetics represents a promising area of research with the potential to improve the lives of millions of people around the world who rely on prosthetic devices.

It is proven that the Clapeyron-Mendeleev equation, originally discovered for gases with large entropy, describes the state of dark matter and energy due to enormous self-gravitation. It is shown that the dark matter exists as compact cold neutrino stars at positive temperature with size twice the Schwarzschild radius. In contrast, the dark energy is dark matter at temperature below the absolute zero, which is locked entirely in black holes, where the pressure is negative as required for the Universe intrinsic expansion. The derived dark phase diagram predicts negative critical temperatures for the Big Bang and the Big Rip of black holes.

Triple-negative breast cancer (TNBC) is a subtype of breast cancer that disproportionally accounts for the majority of breast cancer-related deaths due to the lack of specific targets for effective treatments. In this review, we highlight the complexity of the transforming growth factor-beta family (TGF-β) pathway and discuss how the dysregulation of the TGF-β pathway promotes oncogenic attributes in TNBC which negatively affects patient prognosis. Moreover, we discuss recent findings highlighting TGF-β inhibition as a potent method to target mesenchymal (CD44⁺/CD24^-) and epithelial (ALDH^high) cancer stem cell (CSC) populations. CSCs are associated with tumorigenesis, metastasis, relapse, resistance, and diminished patient prognosis; however, due to differential signal pathway enrichment and plasticity, these populations remain difficult to target and persist as a major barrier barring successful therapy. This review highlights the importance of TGF-β as a driver of chemoresistance, radioresistance and reduced patient prognosis in breast cancer and highlights novel treatment strategies which modulate TGF-β, impede cancer progression and reduce the rate of resistance generation via targeting the CSC populations in TNBC and thus reducing tumorigenicity. Potential TGF-β inhibitors targeting based on clinical trials are summarized for further investigation which may lead to the development of novel therapies to improve TNBC patient prognosis.

Today, air quality is one of the global concerns that governments are facing. One of the main air pollutants is the particulate matter (PM) that affects human health. This article presents the modeling of a purification system by means of negative air ions (NAIs) for air pollutant removal, using computational intelligence methods. The system uses a high voltage booster output to ionize air molecules from stainless steel electrodes; its particle-capturing efficiency reaches up to 97%. With two devices (5 x 2 x 2.5 cm), 2 trillion negative ions are produced per second, and the particulate matter (PM 2.5) can be reduced from 999 to 0 mg / m3 in a period of approximately 5 to 7 minutes (in a 40 x 40 x 40 cm acrylic chamber). This negative ion generator is a viable and sustainable alternative to reduce polluting emissions, with beneficial effects on human health.

The development of smart negative electrode materials with high capacitance for use in supercapacitors remains challenging. Although there have been several types of electrode materials with high capacitance used in energy storage, carbon-based materials are the most reliable electrodes due to their high conductivity, high power density and excellent stability. The most common complaint about general carbon materials is that these as-formed electrode materials can hardly ever be used as free-standing electrodes. Free-standing carbon-based electrodes are in high demand and are a passionate topic of energy storage research. Electrospun nanofibers are a potential candidate to fill this gap. However, the as-spun carbon nanofibers (ECNFs) have low capacitance and energy density on their own. To this end, several attempts have been made to improve these characteristics. In this review, we introduce negative electrode materials that have been developed. Moreover, this review places special attention to the advances of electrospun nanofiber-based negative electrode materials and their limitations. Based on the above information, we put forth a future perspective on how these limitations can be overcome to meet the demands of next-generation smart devices.

Background: We attempted to find if there were gender differences in different types of Negative life events and Suicidal ideation among Chinese adolescents, then analyze the relationship between different types of Negative life events and Suicidal ideation among these young students. Methods: Based on the data from 6 middle-schools and 3 universities in 3 cities of Western China, the gender difference in different types of Negative life events and Suicidal ideation and their related factors were investigated and analyzed in the study. Results: Gender differences were found during different types of Negative life events and Suicidal ideation; Negative life events could predict the intensity of Suicidal ideation by gender, to some specific types. Conclusions: Negative life events were proved to be risk factors of adolescents’ Suicidal ideation regardless of different gender stereotypes, but the specific classification of negative life events which had significant impact on adolescents’ Suicidal ideation also indicated significant gender divisions. For males, negative life events of punishment and adaptation had a significant and boosting impact on their Suicidal ideation, the higher the scores of punishment and adaptation negative life events had, the greater intensity of male adolescents were to have Suicidal ideation. Thus, the above two types of negative life events may be the main stressors predicting male adolescents' Suicidal ideation; For females, in addition to punishment, other types of negative life events all had significant impacts on their Suicidal ideation, which can be treated as the main stressors to trigger female adolescents' Suicidal ideation; Additionally, parents’ marital status of remarriage and divorce were proved to be significant indicators to adolescents’ Suicidal ideation, the age variable was proved to be strongly correlated with Suicidal ideation among female adolescents.

Metabolite transport across cellular membranes is a key feature of living organisms. Specialized proteins or protein complexes mediate such transport processes and are accessible to genetic engineering approaches. This special issue will reflect on the different transport between cellular compartments. It will provide an overview about different transporter classes and metabolic engineering approaches in different organisms ranging from Bacteria to Eukarya. The transport mechanisms energetics of these compounds were thought little of, and most consideration was given to the designing of metabolic pathways. Gram-negative microbes discharge a wide scope of proteins whose capacities incorporate biogenesis of organelles, for example, pilli and flagella, supplement securing, destructiveness, and efflux of medications and different poisons. Six particular emission frameworks have been appeared to intervene protein send out through the inward and external layers of Gram-negative microbes. These pathways are exceptionally monitored all through the Gram-negative bacterial species. In Gram-positive microscopic organisms, discharged proteins are usually moved across the single layer by the Sec pathway or the two-arginine (Tat) pathway. Recently efforts focused on transporter and metabolite engineering, visualize the improvement and enhancement of microbial cell to pass such metabolites these metabolite carrier proteins are inserted into the inner membrane of mitochondria across the inner membrane, specialized carrier proteins are necessary that mediate the transport into and out of the mitochondrial matrix. Two main strategies for metabolic engineering in plants: the introduction of genes encoding new enzymes and the use of TFs controlling specialized metabolic pathways