Power generation systems based on renewable energy sources are finding ever-widening applications and many researchers work on this problem. Many papers address the problem of transformerless structures, but few of them are aimed at conducting research on structures with multilevel converter topologies. In this paper a grid-tied transformerless PV-generation system based on a multilevel converter is discussed. There are common-mode leakage currents which act as a parasitic factor. It is also known that common-mode voltage is the main cause of the common-mode leakage current in grid-tied PV-generation systems. This paper considers the space vector pulse-width modulation (PWM) technique which is used to suppress or reduce common-mode leakage current. The proposed engineering solutions for a generation system based on the multilevel converter controlled with a pulse-width modulation technique are verified by experiment.

Viral co-infections, where a host is infected by multiple viruses simultaneously, are common in the human population. Human viral co-infections can lead to complex interactions between viruses and the host immune system, affecting the clinical outcome and posing challenges for treatment. Understanding the types, mechanisms, impacts, and identification methods of human viral co-infections is crucial for the prevention and control of viral diseases. In this review, we first introduce the significance of studying human viral co-infections and summarize the current research progress and gaps in this field. We then classify human viral co-infections into four types based on the pathogenic properties and species of the viruses involved. Next, we discuss the molecular mechanisms of viral co-infections, focusing on virus-virus interactions, host immune responses, and clinical manifestations. We also summarize the experimental and computational methods for identifying viral co-infections, emphasizing the latest advances in high-throughput sequencing and bioinformatics approaches. Finally, we highlight the challenges and future directions in human viral co-infection research, aiming to provide new insights and strategies for the prevention, control, diagnosis, and treatment of viral diseases. This review provides a comprehensive overview of the current knowledge and future perspectives on human viral co-infections, and underscores the need for interdisciplinary collaborations to address this complex and important topic.

In this work, we introduce the design a 16-channel in-pixel neural analog front-end which employs a current-based summing approach to establish a common-mode feedback loop. The primary aim of this novel structure is to enhance both the system common-mode rejection ratio (SCMRR) and the common-mode interference (CMI) range. Compared to more conventional designs, the hereby proposed front-end utilizes DC-coupled inverter-based main amplifiers, which significantly reduce the occupied on-chip area. Additionally, the current-based implementation of the CMFB loop obviates the need for voltage buffers, replacing them with simple common-gate transistors and in turn decreasing both area occupancy and power consumption. The proposed architecture is further examined from an analytical standpoint, providing a comprehensive evaluation through design equations of its performance in terms of gain, common-mode rejection and noise power. A 50μm×65μm compact layout of the pixel amplifiers that make up the recording channels of the front-end was designd in a 180 nm CMOS process. Simulations conducted in Cadence Virtuoso reveal an SCMRR of 80.5 dB and a PSRR of 72.58 dB, with a differential gain of 44 dB and a bandwidth that fully encompasses the frequency range of the bio-signals that can be theoretically captured by the neural probe. The noise integrated in the range between 1 Hz and 7.5 kHz results in an IRN of 4.04 μVrms. Power consumption is also tested, with a measured value of 3.77 μW per channel, corresponding to an overall consumpution of about 60 μW. To test its robustness with respect to PVT and mismatch variations, the front-end is evaluated by means of extensive parametric simulations and Monte Carlo simulations, revealing favorable results.

Air pollution, climate change and global warming show direct linkage. Introduction - Background: Research in the field has proposed and demonstrated their link to increased allergenicity in plants, leading to increased allergic diseases. Allergen patterns are changing in response to climate change. Across Europe, up to 12% of the population suffers from allergic diseases (bronchial asthma and allergic rhinitis) caused by the pollen grains. The medical costs of these types of allergies are enormous and are increasing with the spread of common ragweed - Ambrosia artemisiifolia* in Europe. In practice, more and more patients are turning to allergists. Methods: Based on these data, the research aims to identify safety measures and specific legislation to control and eradicate common ragweed in the countries most affected by the spread of this plant in Europe, increase in population exposure in countries affected by the presence of common ragweed and the socio-economic impact of allergic rhinitis and bronchial asthma at European level.[1][2] Our database search did not reveal any other research that has addressed this topic to date. Results: This research identifies specific legislation to the countries most affected by the spread of this plant pollen grains at European level, changes in allergen patterns and monitoring/safety eradication measures decided by local authorities, and data on the spread of common ragweed over the last two decades, costs per treatment, increased allergic rhinitis and bronchial asthma morbidity in the most affected areas. Conclusions: At European level, there are no universally valid models for eradicating this weed. Various methods can be used to limit the spread of common ragweed and its pollen production (e.g. mowing once or twice a year of overgrown land, ploughing, chemical control, public information, etc.). Local and regional cooperation should be considered essential to promote phytosanitary & safety measures and exchange of information on methods to identify and manage the spread of common ragweed. Unified legislation at European level would help all affected countries; reduce morbidity from respiratory allergic diseases and the costs of treating these diseases.

The chiral optical Tamm state (COTS) is a special localized state at the interface of a handedness-preserving mirror and a structurally chiral medium such as a cholesteric liquid crystal or a chiral sculptured thin film. The spectral behavior of COTS, observed as reflection resonances, is described by the temporal coupled-mode theory. Mode coupling is different for two circular light polarizations because COTS has a helix structure replicating that of the cholesteric. The mode coupling for co-handed circularly polarized light exponentially attenuates with the cholesteric layer thickness since the COTS frequency falls into the stop band. Cross-handed circularly polarized light freely goes through the cholesteric layer and can excite COTS when reflected from the handedness-preserving mirror. The coupling in this case is proportional to anisotropy of the cholesteric and theoretically it is only anisotropy of magnetic permittivity that can ultimately cancel this coupling. These two couplings being equal results in a polarization crossover (the Kopp--Genack effect) for which a linear polarization is optimal to excite COTS. The corresponding cholesteric thickness and scattering matrix for COTS are generally described by simple expressions.

An efficient design method is proposed for a compact common-mode rejection (CMR) filter utilizing dumbbell-shaped defected ground (DS-DG) structures and gap-coupled stub (GCS) resonators. A CMR filter for differential lines helps to improve the signal integrity of high-speed digital signals on printed circuit boards. The proposed CMR filter design is based on the equivalent circuit models, while the previous designs depended heavily on the DS-DG structure optimization using the EM simulations. The proposed CMR filter effectively reject the common-mode components with minimally affecting the differential signals. To prove the simplified design approach, a 5th-order Chebyshev band-stop filter has been designed with three DS-DG structures and two GCS resonators. From the simulated and measured results, it is found that the proposed CMR filter provides ~90% fractional frequency bandwidth with more than 20 dB of common-mode rejection ratio and less than 0.6 dB of insertion loss of the differential signal.

This paper addresses the input coupling problem for the shape memory alloy (SMA) actuated parallel platform with completely unknown nonlinear dynamics. The problem means that in a parallel platform with multiple SMA actuators acting together, the displacement of one of the actuators will simultaneously affect the remaining actuators to change. Due to the coupling problem and nonlinear characteristics of the SMA actuators, it is not easy to control the platform to achieve bi-directional swing with completely unknown nonlinear dynamics. Therefore, a model-free adaptive sliding mode control method is proposed to improve the control accuracy of the complex motion of the platform, avoiding the complex modeling process of the SMA actuated parallel platform. Based on the model-free adaptive control (MFAC) theory, a multiple input and multiple output (MIMO) dynamic linearized mathematical model of the parallel platform is established using the online input and output data of the system. Then, a sliding mode controller is designed based on the dynamic model. A rigorous theoretical analysis proves that the proposed model-free adaptive sliding mode controller is able to stably control the SMA actuated parallel platform, and its tracking error is uniformly ultimately bounded (UUB). Finally, experiments are conducted on the established SMA actuated parallel platform. The results show that the proposed model-free controller is feasible and effective, and can control the system well to achieve the complex motion of bi-directional swing.

Structural health monitoring has been studied by a number of researchers as well as various industries to keep up with the increasing demand for preventive maintenance routines. This work presents a novel method for reconstruct prompt, informed strain/stress responses at the hot spots of the structures based on strain measurements at remote locations. The structural responses measured from usage monitoring system at available locations are decomposed into modal responses using empirical mode decomposition. Transformation equations based on finite element modeling are derived to extrapolate the modal responses from the measured locations to critical locations where direct sensor measurements are not available. Then, two numerical examples (a two-span beam and a 19956-degree of freedom simplified airfoil) are used to demonstrate the overall reconstruction method. Finally, the present work investigates the effectiveness and accuracy of the method through a set of experiments conducted on an aluminium alloy cantilever beam commonly used in air vehicle and spacecraft. The experiments collect the vibration strain signals of the beam via optical fiber sensors. Reconstruction results are compared with theoretical solutions and a detailed error analysis is also provided.

The popular motor drive systems with a single two-level voltage source inverter (VSI) have one main problem that is the occurrence of the common-mode voltage (CMV), which is an effect of the electromagnetic interference, shaft voltage, bearing currents, leakage current. These cause the high stress, increasung temperature and early mechanical failure in machine. To overcome this problem, the technology of the dual two-level VSI fed open-end three-phase ac loads is now available to eliminate the CMV at the ac/induction motor load with the 120-degree modulation technique for controlling each inverter. In this paper, the discontinuous space vector modulation (DSVM) schemes are proposed and applied for the dual two-level VSI fed open-end load. It is based on the 120-degree modulation technique by using only 12 active voltage vectors and the 10 zero voltage vectors from the total 64 voltage vectors along with the different five-segment swicthing sequence designs with centralizing pulse width modulation technqiue in order to not only cancel the CMV in the ac load, but also reduce the switching number/switching loss of the conversion system. Among the various DSVM schemes, their performances are compared in this paper, such as the number of the switching, the step and peak value of the CMV in each inverter, and the quality of the output waveform, etc. The details of the verfication and comparison are carried out by simulation using Matlab/Simulink software.

Under the development mode of deep blending of emerging technologies, major projects are important for enhancing China's comprehensive national strength and independent innovation capability. Based on the social benefits of major projects, and considering the influence of reputation factors, an evolutionary game model composed of a general contractor and subcontractor of major projects is established. This paper studies the influence of various factors including the income distribution coefficient of collaborative innovation, and MATLAB simulation software is analyzed the influence of factors on an evolutionary path. The results show that a reasonable income distribution coefficient can promote the game behavior of both parties to the direction of active collaborative innovation; The reduction of innovation cost and the improvement of spillover technology absorption capacity can make innovation subjects tend to choose active collaborative innovation strategies. In addition, reputation loss above a specific threshold can effectively inhibit free-riding behavior and encourage innovation subjects to choose active collaborative innovation strategies. The research results provide reference for promoting major projects' technology innovation.

Over the past couple of decades, Global positioning system (GPS) technology has been utilized to collect large-scale data from travel surveys. As the precise spatiotemporal characteristics of travel could be provided by GPS devices, the issues of traditional travel survey, such as misreporting and non-response, could be addressed. Considering the defects of dedicated GPS devices (e.g., need much money to buy devices, forget to take devices to collect data, limit the simple size because of the number of devices, etc.), and the phenomenon that the smartphone is becoming one of necessities of life, there is a great chance for the smartphone to replace dedicated GPS devices. Although, several general reviews have been done about smartphone-based GPS travel survey in the literature review section in some articles, a systematic review from smartphone-based GPS data collection to travel mode detection has none. The included studies were searched from six databases. The purpose of this review is to critically assess the current literature on the existing methodologies of travel mode detection based on GPS raw data collected by smartphones. Meanwhile, according to the systematic comparison among different methods from data-preprocessing to travel mode detection, this paper could carefully provide the Strengths and Weaknesses of existing methods. Furthermore, it is the crucial step to develop the methodologies and applications of GPS raw data collected by smartphones.

Short-range Internet of Things (IoT) sensor nodes operating at 2.4 GHz need to provide ubiquitous wireless sensor networks (WSNs) with energy-efficient, wide-range output power (POUT) and fully integrated on a single chip for wireless body area networks (WBANs) and wireless personal area networks (WPANs) using low-power Bluetooth (BLE) and Zigbee standards. The proposed fully integrated transmitter (TX) utilizes a digitally controllable current-mode class-D (CMCD) power amplifier (PA) with a second harmonic distortion (HD2) suppression to reduce VCO pulling in an integrated system while meeting harmonic limit regulations. The CMCD PA is divided into 7-bit slices that can be reconfigured between differential and single-ended topologies. Duty cycle distortion compensation is performed for HD2 suppression, and an HD2 rejection filter and a modified C-L-C low-pass filter (LPF) reduce HD2 further. Implemented in a 28 nm CMOS process, the TX achieves a wide POUT range of from 12.1 to -31 dBm and provides a maximum efficiency of 39.8% while consuming 41.1 mW at 12.1 dBm POUT. The calibrated HD2 level is -82.2 dBc at 9.93 dBm POUT, resulting in a transmitter figure of merit (TX_FoM) of -97.52 dB. Higher order harmonic levels remain below -41.2 dBm even at 12.1 dBm POUT, meeting regulatory requirements.

In order to solve the problem of feature extraction of underwater acoustic signals in complex ocean environment, a new method for feature extraction from ship radiated noise is presented based on empirical mode decomposition theory and permutation entropy. It analyzes the separability for permutation entropies of the intrinsic mode functions of three types of ship radiated noise signals, and discusses the permutation entropy of the intrinsic mode function with the highest energy. In this study, ship radiated noise signals measured from three types of ships are decomposed into a set of intrinsic mode functions with empirical mode decomposition method. Then, the permutation entropies of all intrinsic mode functions are calculated with appropriate parameters. The permutation entropies are obviously different in the intrinsic mode functions with the highest energy, thus, the permutation entropy of the intrinsic mode function with the highest energy is regarded as a new characteristic parameter to extract the feature of ship radiated noise. After that, the characteristic parameters, namely, the energy difference between high and low frequency, permutation entropy, and multi-scale permutation entropy, are compared with the permutation entropy of the intrinsic mode function with the highest energy. It is discovered that the four characteristic parameters are at the same level for similar ships, however, there are differences in the parameters for different types of ships. The results demonstrate that the permutation entropy of the intrinsic mode function with the highest energy is better in separability as the characteristic parameter than the other three parameters by comparing their fluctuation ranges and the average values of the four characteristic parameters. Hence, the feature of ship radiated noise can be extracted efficiently with the method.

Gaze tracking of high-speed moving targets is a novel application mode for low Earth orbit microsatellites. In this mode, small satellites are equipped with high-resolution narrow-field-of-view video cameras for stable gaze-tracking imaging of high-speed moving targets. This paper proposes a high-precision attitude adaptive integral sliding mode control method with a feedforward compensation disturbance observer to enhance the capability of a microsatellite attitude control system for gaze tracking of high-speed moving targets. Specifically, first, we present the attitude control system model for microsatellites and the calculation method for the desired attitude of target tracking based on image feedback. Then, an adaptive integral sliding mode attitude control algorithm with a feedforward compensation disturbance observer, which meets the requirements of high-precision tracking control, is designed. The developed algorithm utilizes the disturbance observer to observe the friction torque of the flywheel and compensates for it through feedforward control. It also employs the adaptive integral sliding mode control algorithm to reduce the impact of uncertain disturbances, decrease the steady-state error of the system, and enhance the attitude control precision. Simulation experiments demonstrated that the designed disturbance observer can successfully observe the frictional disturbance torque of the flywheel. The attitude Euler angle control precision for high-speed moving target tracking reached 0.009°, and the angular velocity control precision reached 0.005°/s, validating the effectiveness of the proposed approach.

The protein C is a small viral protein encoded in an overlapping frame of the P gene in the sub-family Orthoparamyxovirinae. This protein, expressed by alternative translation initiation, is a virulence factor that regulates viral transcription, replication and production of defective interfering RNA, interferes with the host-cell innate immunity systems and supports assembly of viral particles and budding. We expressed and purified full-length and an N-terminally truncated C protein from Tupaia paramyxovirus (TupV) C protein (genus Narmovirus). We solved the crystal structure of the C-terminal part of TupV C protein at a resolution of 2.4 Å and found that it is structurally similar to Sendai virus C protein, suggesting that despite undetectable sequence conservation, these proteins are homologous. We characterized both truncated and full-length proteins by SEC-MALLS and SEC-SAXS and described their solution structures by ensemble models. We established a minireplicon assay for the related Nipah virus (NiV) and showed that TupV C inhibited the expression of NiV minigenome in a concentration-dependent manner as efficiently as NiV C protein. A previous study found that the Orthoparamyxovirinae C proteins former two clusters without detectable sequence similarity, raising the question of whether they were homologous or instead had originated independently. Since TupV C and SeV C are representative of these two clusters, our discovery that they have a similar structure indi-cates that all Orthoparamyxovirine C proteins are homologous. Our results also imply that, strik-ingly, a STAT1-binding site is encoded by exactly the same RNA region of the P/C gene across Paramyxovirinae, but in different reading frames (P or C) depending on which cluster they belong to.

ω-Transaminases have been immobilized on macrocellular silica monoliths and used as heterogeneous biocatalysts in a continuous flow mode enantioselective transamination reaction. The support was prepared by a sol-gel method based on emulsion templating. The enzyme was immobilized on the structured silica monoliths both by adsorption, and by covalent grafting using amino-functionalized silica monoliths and glutaraldehyde as a coupling agent. A simple reactor set-up based on the use of a heat-shrinkable Teflon tube is presented and successfully used for the continuous flow kinetic resolution of a chiral amine, 4-bromo-α-methylbenzylamine. The porous structure of the supports ensures effective mass transfer and the reactor works in the plug flow regime without preferential flow paths. When immobilized in the monolith and used in the flow reactor, transaminases retain their activity and their enantioselectivity. The solid biocatalyst is also shown to be stable both on stream and during storage. These essential features pave the way to the successful development of an environmentally friendly process for chiral amines production.

The analysis and simulation of water quality in distribution networks is a complex issue of great concern today. The analysis of the evolution of water age, as a simple indicator of water quality in the network, is of great interest in both design and operation phases. Understanding the factors that have the strongest influence on water quality is key to developing adequate strategies aimed at preserving it. This paper firstly analyses the factors with biggest influence in the tanks water age, to support the selection of the most appropriate configuration from the point of view of water quality during design phases. Then, the main considerations when modelling tanks following the different mixing models considered in Epanet have been presented. Also, a real tank behaviour has been characterised through field measurements and Epanet simulations in order to determine the best fitted mixing model.

Migraine and neuropathic pain (NP) are evocative of painful, disabling, chronic conditions which exhibit resembling symptoms and thus considered to share a common etiology. Calcitonin gene-related peptide (CGRP) has gained credit as a target for migraine management; nevertheless, the efficacy and the applicability of CGRP modifiers warrant search for more effective therapeutic targets for pain management. This scoping review overviews human studies of common pathogenic factors in migraine and NP to explore potential novel therapeutic targets. CGRP causes inflammation in the meninges; monoclonal antibodies and inhibitors target CGRP. Gluta-mate-induced hyperexcitability and subsequent sensitization are closely linked to an alteration of the tryptophan (Trp)-kynurenine (KYN) metabolic system; the Trp-KYN system may serve as a potential target. Microglial overaction is observed in migraine and NP; modifying the microglial activity may be a possible approach. Cytokine-induced inflammation is a leading hypothesis of the pathogenesis of the conditions; alleviating neuroinflammation may complement a pain-relieving armamentarium. Transient receptor potential (TRP) ion channels evoke the release of several substances; TRP ion channels may potentially emerge as new targets. The endocannabinoid system plays a major role in the pain trafficking pathway; modification of the system may open a new path toward discovery of new analgesics. Here we highlight the mechanism of those common pathogenic factors to explore therapeutic targets for innovative pain management in migraine and NP.

Powdery mildew is a severe disease causing substantial yield losses in wheat production worldwide. The Chinese wheat landrace Changanhongmai (CAHM) exhibits high resistance to the physiological race E09 of powdery mildew. This study aims to characterize the powdery mildew resistance gene in CAHM, and develop molecular markers for marker-assisted selection of wheat. To investigate the genetic characteristics of this resistant gene, we developed F1 plants, F2 generation population, and F2:3 families from a cross between CAHM and SY225. Genetic analysis demonstrated that all F1 plants were resistant to the disease, while the ratio of resistant to susceptible plants was 3: 1 in both the F2 population and F2:3 families, indicating that CAHM is inherited in a manner of single dominant powdery mildew resistance gene, which was tentatively designated as PmCAHM. By using bulk segregation analysis, we constructed a genetic map encompassing Xgwm273, Xwmc626, Xgwm11, Xgwm18, Xgdm28, Xgpw7812, Xgpw5195, Xwmc694 and PmCAHM. Among these markers, Xgpw7812 and Xgpw5195 were flanking markers tightly linked to PmCAHM at a genetic distance of 2.5 cM and 8.4 cM, respectively. Furthermore, nullisomic-tetrasomic analysis revealed that PmCAHM is located on chromosome 1B. These results indicate that PmCAHM differs from the internationally recognized powdery mildew resistance genes in both location and source. In addition, a new germplasm/line NW1748 with large seeds and powdery mildew resistance was developed from the cross and back cross populations of Fengyou 1718 (FY1718)/CAHM//FY 1718. Therefore, PmCAHM can serve as a novel powdery mildew resistance source for breeding of wheat by using NW1748 as the donor in the future.

Nearly half a century has passed since the discovery of cytoplasmic inheritance of human chloramphenicol resistance. The inheritance was then revealed to take place maternally by mitochondrial DNA (mtDNA). Later, a number of mutations in mtDNA were identified as a cause of severe inheritable metabolic diseases with neurological manifestation, and the impairment of mitochondrial functions has been probed in the pathogenesis of a wide range of illnesses including neurodegenerative diseases. Recently growing number of preclinical studies has revealed that animal behaviors are influenced by the impairment of mitochondrial functions and possibly by the loss of mitochondrial stress resilience. Indeed, as high as 54% of patients with one of the most common primary mitochondrial diseases, mitochondrial encephalomyopathy with lactic acidosis and stroke-like episodes (MELAS) syndrome, present psychiatric symptoms including cognitive impairment, mood disorder, anxiety, and psychosis. Mitochondria are multifunctional organelles which produce cellular energy and play a major role in other cellular functions including homeostasis, cellular signaling, and gene expression, among other. Mitochondrial functions are observed to be compromised and to become less resilient under continuous stress. Meanwhile, stress and inflammation have been linked to the activation of the tryptophan (Trp)-kynurenine (KYN) metabolic system, which observably contributes to development of pathological conditions including neurological and psychiatric disorders. This narrative review discusses the functions of mitochondria and the Trp-KYN system, the interaction of the Trp-KYN system with mitochondria, and the current understanding of the involvement of mitochondria and the Trp-KYN system in preclinical and clinical studies of major neurological and psychiatric diseases.

This paper discusses some of the most common misconceptions about large language models (LLMs), including the belief that they are sentient or conscious, that they are always accurate, and that they can replace human creativity. The paper also proposes a strategy for overcoming these misbeliefs, which involves educating the public about the capabilities and limitations of LLMs, developing guidelines for the responsible use of LLMs, and conducting more research to understand the potential impact of LLMs on society.

In this study, a novel flexible ethanol gas sensor was created by the deposition of CoFe2O4 (CFO) thin film was on a thin mica substrate using pulsed laser deposition. Transition electron microscopy (TEM) investigations clearly demonstrated the successful growth of CFO on the mica, where a well-defined interface was observed. Ethanol gas-sensing studies showed optimal performance at 200 °C, with the highest response, 19.2, to 100 ppm ethanol. Operating the sensor in self-heating mode under 7 V applied voltage, which was corresponds to a temperature of approximately 200 °C, produced a maximal response to ethanol of 19.2. This aligned with the highest responses observed during testing at 200 °C, confirming the sensor’s accuracy and sensitivity to ethanol under self-heating conditions. In addition, the sensor exhibited good selectivity to ethanol and excellent flexibility; maintaining its high performance after bending and tilting up to 5000 times. As this is the first report on flexible self-heated CFO gas sensors, we believe that this research holds great promise for the future development of high-quality sensors based on this approach.

The purpose of this paper is to study the sliding mode control as a Ricci flow process in the context of a three-story building structure subjected to seismic waves. The stability conditions result from two Lyapunov- functions, the first associated with slipping in a finite period of time, and the second with convergence of trajectories to the desired state. Simulation results show that the Ricci flow control leads to the minimization of the displacements of the floors. 3D Ricci solitons projection via a semi-conformal mapping to a surface is also studied.

This review is focused on synephrine, the principal phytochemical found in bitter orange and other medicinal plants, and widely used as a dietary supplement for weight loss/body fat reduction. We examine different aspects of synephrine biology, delving into its established and potential molecular targets, as well as its mechanisms of action. We present an overview of the origin, chemical composition, receptors, and pharmacological properties of synephrine, including its anti-inflammatory and anti-cancer activity in various in vitro and animal models. Additionally, we conduct a comparative analysis of the molecular targets and effects of synephrine with those of its metabolite, selective glucocorticoid receptor agonist (SEGRA) Compound A (CpdA), which shares a similar chemical structure with synephrine. SEGRA, including CpdA, have been extensively studied as glucocorticoid receptor activators that have a better benefit/risk profile than glucocorticoids due to the reduced adverse effects. We discuss the potential of synephrine usage as a template for the synthesis of new generation of non-steroidal SEGRA. The review also provides insights into the safe pharmacological profile of synephrine.

Deep learning (DL) algorithms used for DOTATATE PET lesion detection typically require large, well-annotated training datasets. These are difficult to obtain due to low incidence of gastroenteopancreatic neuroendocrine tumors (GEP-NETs), and the high cost of manual annotation. Furthermore, networks trained and tested with data acquired from site specific PET/CT instrumentation, acquisition and processing protocols have reduced performance when tested with offsite data. This lack of generalizability requires even larger, more diverse training datasets. The objective of this study is to investigate the feasibility of improving DL algorithm performance by better matching the background noise in training datasets to higher noise, out-of-domain testing datasets. 68Ga-DOTATATE PET/CT datasets were obtained from two scanners: Scanner1, a state-of-the-art digital PET/CT (GE DMI PET/CT; n=83 subjects), and Scanner2, an older-generation analog PET/CT (GE STE; n=123 subjects). Set1, the data set from Scanner1 was reconstructed with standard clinical parameters (5 minutes; Q.Clear) and list-mode reconstructions (VPFXS 2, 3, 4, and 5-minutes). Set2, data from Scanner2, representing out-of-domain clinical scans, used standard iterative reconstruction (5 minutes; OSEM). Reconstructed datasets were divided into training, validation, and testing datasets in a 60%, 20%, 20% proportion, and a deep neural network was trained with each: Network1 for Scanner1 and Network2 for Scanner2. DL performance (Network1) was tested with out-of-domain test data (Set2). To evaluate the effect of training sample size, we tested DL model performance using a fraction (25%, 50%, and 75%) of Set1 for training. Scanner1, list-mode 2-minute reconstructed data demonstrated the most similar noise level compared that of Set2, resulting in the best performance (F1=0.713). This was not significantly different compared to the highest performance, upper-bound limit using in-domain training for Network2 (F1=0.755; p-value=0.103). Regarding sample size, the F1 score significantly increased from 25% training data (F1=0.478) to 100% training data (F1=0.713; p<0.001). List-mode data from modern PET scanners can be reconstructed to better match the noise properties of older scanners. Using existing data and their associated annotations dramatically reduces the cost and effort in generating these datasets, and significantly improves the performance of existing DL algorithms. List-mode reconstructions can provide an efficient, low-cost method to improve DL algorithm generalizability.

This paper explores the application of fisheries management theories to broader environmental issues, including climate change and biodiversity conservation. It underscores the inherent trade-off in fisheries between yield and resource conservation, identifying harvesting as a significant environmental burden. Early recognition of the sustainability concept aimed to address challenges like economic discounts and the tragedy of the commons, contributing to the issue of overfishing. These insights extend beyond fisries to other environmental concerns, particularly climate change. The development of adaptive management, initially tailored to address uncertainties and non-stationarity in fisheries, has found application in diverse environmental issues. Recognizing humans as integral parts of ecosystems highlights the impossibility of achieving zero environmental impact when utilizing natural resources. The paper advocates for passive restoration to prevent overfishing, leveraging nature's resilience. While goals like complete biodiversity restoration are inherent in fisheries, their relevance may not be immediately apparent to other environmentalists. Despite ongoing discussions on the sustainability of ecosystem services, legislation often tends to favor the long-term maximization of fisheries yield. The paper calls for mutual understanding of theories and experiences across various environmental fields, including fisheries, to enhance collaborative efforts in each field.

The existence of a common ancestor to all living organisms in Earth is a necessary corollary of Darwin idea of common ancestry. The Last Universal Common Ancestor (LUCA) has been normally considered as the ancestor of cellular organisms that originated the three domains of life: Bacteria, Archaea and Eukarya. Recent studies about the nature of LUCA indicate that this first organism should present hundreds of genes and a complex metabolism. Trying to bring another of Darwin ideas into the origins of life discussion, we went back into the prebiotic chemistry trying to understand how LUCA could be originated under gradualist assumptions. Along this line of reasoning, it became clear to us that the definition of another ancestral should be of particular relevance to the understanding about the emergence of biological systems. Together with the view of biology as a language for chemical translation, on which proteins are encoded into nucleic acids polymers, we glimpse a point in the deep past on which this Translation mechanism could have taken place. Thus, we propose the emergence of this process shared by all biological systems as a point of interest and propose the existence of this pre-cellular entity named FUCA, as the First Universal Common Ancestor. FUCA was born in the very instant on which RNA-world replicators started to be capable to catalyze the bonding of amino acids into oligopeptides. FUCA has been considered mature when the translation system apparatus has been assembled together with the establishment of a primeval, possibly error-prone genetic code. This is FUCA, the earliest ancestor of LUCA’s lineage.

Mode locked pulse generation has been reported using both active and passive mode locking schemes. Active mode locking technique has been proven to be an effective way to generate high-repetition-rate pulses by incorporating a modulator inside the laser cavity. Compared to actively mode locked lasers, passively mode locked lasers can generate pulse train at ultrashort pulse width but with relatively lower repetition rate. Thus, it is a brilliant idea to build a hybrid mode locked system combining both active and passive mode lockers. In this review, several hybrid mode locked fiber ring laser systems are discussed and summarized. Hybrid mode locking is a promising method to generate high speed ultrashort optical pulses for fiber-optic telecommunication system.

In this paper, a multi-mode waveguide-based optical resonator is proposed for an integrated optical refractive index sensor. Conventional optical resonators have been studied for single-mode waveguide-based resonators to enhance the performance, but mass production is limited owing to the high fabrication costs of nano-scale structures. To overcome this problem, we designed an S-bend resonator based on a micro-scale multi-mode waveguide. In general, multi-mode waveguides cannot be utilized as optical resonators, because of a performance degradation resulting from modal dispersion and an output transmission with multi-peaks. Therefore, we exploited the mode discrimination phenomenon using the bending loss, and the resulting S-bend resonator yielded an output transmission without multi-peaks. This phenomenon is utilized to remove higher-order modes efficiently using the difference in the effective refractive index between the higher-order and fundamental modes. As a result, the resonator achieved a Q-factor and sensitivity of 2.3x10³ and 52 nm/RIU, respectively, using the variational finite-difference time-domain method. These results show that the multi-mode waveguide-based S-bend resonator with a wide line width can be utilized as a refractive index sensor.

The main function of dUTPases is to regulate the cellular levels of dUTP and dTTP, thereby playing a crucial role in the DNA repair mechanisms. Despite the fact that mutant organisms with the obliterated dUTPase enzymatic activity remain viable, it is not possible to knockout the dut gene completely due to the lethal consequences of such mutation for the organism. As a result, it is considered that this class of enzymes perform an additional function that is essential for the organism's survival. In this study, we provide the evidence that the dUTPase of bacteriophage T5 possesses supplemental function in addition to its canonical role. We determined the crystal structure of bacteriophage T5 dUTPase with a resolution of 2.0 Å, and discovered a distinct short loop, consisting of 6 amino acid residues which represents unique structural feature specific to the T5-like phages dUTPases. The removal of this element did not affect the overall structure of the homotrimer, but had significant effects on the development of the phage. Furthermore, it has been shown that the enzymatic function and the novel function of bacteriophage T5 dUTPase are unrelated and independent from each other.

Abstract: Background: COVID-19 is a respiratory disease that eventually became pandemic with 300 million people infected around the world. Alongside the improvement in COVID-19 management and vaccine development, identifying biomarkers for COVID-19 has recently reported to help in early prediction and managing severe cases which might improve outcome. The Aim of our study was to find out if there is any correlation between clinical severity and elevated hematological and biochemical markers in Covid-19 patients and its effect on the outcome Methods: We have collected data retrospectively of socio-demographic, medical history, biomarkers, and diseases outcome from five hospitals and health institutions in the Kingdom of Saudi Arabia. Results: Pneumonia was the most common presentation of COVID 19 in our cohort. All biomarkers (D-Dimer, CRP, troponin, LDH and ferritin) except for the mean lowest white blood cells were found to have significant correlation (p<0.05) with worse COVID-19 disease outcomes. There was a sig-nificant association between the inflammatory biomarkers and the disease severity of COVID 19 patients (p<0.001). Patients with evidence of severe respiratory disease particularly who required mechanical ventilation (MV) had higher biomarkers, when compared to those with stable respiratory condition (p<0.001). Conclusion: Identifying biomarkers predicts outcome for COVID-19 patients and may significantly help in the management.

This paper describes the load capacity of short fiber-reinforced polymer lugs with Ti-6Al-4V selective laser-melted bushings with the original embedded element surface roughness and after sandblasting and vibratory finishing. Lugs are an important part of pin-joints. Adhesion between PA6 and SLM produced titanium is not fully studied. The cohesive zone material Mode II model parameters were calibrated experimentally by extruding a cylindrical bushing along the lug axis. The values of the maximum equivalent tangential contact stress were fitted for cases with investigated embed element roughness. The critical fracture energy for tangential slip was also estimated. Validation of the constructed CZM Mode II models with the results of strength experiments was performed. In both the experiment and the calculation, greater bushing roughness provides greater lug load-bearing capacity. The presented models can be used for the preliminary evaluation of SFRP PA6 parts with titanium embedded elements bearing capacity.

Spatio-Temporal Dynamic Mode Decomposition (STDMD) is an extension of Dynamic Mode Decomposition (DMD) designed to handle spatio-temporal datasets. It extends the framework so that it can analyze data that has both spatial and temporal variations, allowing for the extraction of spatial structures and their temporal evolution. The STDMD method extracts temporal and spatial development information simultaneously, including wavenumber, frequencies and growth rates, which is essential in complex dynamic systems. We provide a comprehensive mathematical framework for sequential and parallel STDMD approaches. We also introduce delay coordinates generalization to the presented algorithms to extend the scope of their application. The extension, labeled delay embedding STDMD allows the use of delayed data, which can be both time-delayed and space-delayed. An explicit expression of the presented algorithms in matrix form is also provided, which facilitates theoretical analysis and provides a solid foundation for further research and development. The novel approach is demonstrated using some illustrative model dynamics.

As a fast and nondestructive spectroscopic analysis technique, Raman spectroscopy has been widely applied in chemistry. However, noise is usually unavoidable in Raman spectra. Hence, denoising is an important step before Raman spectral analysis. A novel spectral denoising method based on variational mode decomposition (VMD) was introduced to solve the above problem. The spectrum is decomposed into a series of modes (uk) by VMD. Then, the high frequency noise modes are removed and the remaining modes are reconstructed to obtain the denoised spectrum. The proposed method was verified by two artificial noised signals and two actual Raman spectra. As comparison, empirical mode decomposition (EMD), Savitzky-Golay (SG) smoothing and discrete wavelet transformation (DWT) are also investigated. At the same time, signal-to-noise ratio (SNR) was introduced as evaluation indicators to verify the performance of the proposed method. The results show that compared with EMD, VMD can significantly improve mode mixing and endpoint effect. Some information of the small sharp peak is lost after VMD denoising. However, VMD lost fewer information than that of EMD, SG smoothing and DWT. Moreover, the Raman spectrum by VMD denoising is more excellent than that of EMD, SG smoothing and DWT in terms of visualization and SNR. Therefore, VMD provides superior denoising capabilities for Raman spectra.

Hypertrophic Cardiomyopathy (HCM) is a common inherited disorder characterized by unexplained left ventricular hypertrophy, with or without left ventricular outflow tract (LVOT) obstruction. Single nuclei RNA-sequencing (snRNA-seq) of both obstructive and nonobstructive HCM patient samples have revealed alterations in communication between various cell types but a direct and integrated comparison between the two HCM phenotypes has not been reported. We performed a bioinformatic analysis of HCM snRNA-seq datasets from obstructive and nonobstructive patient samples to identify differentially expressed genes and distinctive patterns of intercellular communication. Differential gene expression analysis revealed 37 differentially expressed genes, predominantly in cardiomyocytes but also in other cell types, relevant to aging, muscle contraction, cell motility and the extracellular matrix. Intercellular communication was generally reduced in HCM, affecting the extracellular matrix, growth factor binding, integrin binding, PDGF binding and SMAD binding, but with increases in adenylate cyclase binding, calcium channel inhibitor activity, and serine-threonine kinase activity in nonobstructive HCM. Increases in neuron to leukocyte and dendritic cell communication, in fibroblast to leukocyte and dendritic cell communication and in endothelial cell communication to other cell types, largely through changes in expression of integrin-b1 and its cognate ligands, were also noted. These findings indicate both common and distinct physiological mechanisms affecting the pathogenesis of obstructive and nonobstructive HCM and provide opportunities for personalized management of different HCM phenotypes.

Traumatic brain injury (TBI) is an important global clinical issue, requiring not only prevention but also effective treatment. Following TBI, diverse parallel and intertwined pathological mechanisms affecting biochemical, neurochemical, and inflammatory pathways can have severe impact on the patient’s quality of life. The current review summarizes evidence for utility of amantadine in TBI in connection to its mechanism of action. Amantadine combining multiple mechanisms of action may offer both neuroprotective and neuroactivating effects in TBI patients. Indeed, use of amantadine in TBI has been encouraged by several clinical practice guidelines/recommendations. Amantadine is also available as infusion which may be of particular benefit in unconscious patients with TBI, due to immediate delivery to the central nervous system and the possibility of precise dosing. In other situations, orally administered amantadine may be used. There are several questions that remain to be addressed: Can amantadine be effective in disorders of consciousness requiring long-term treatment and in combination with drugs approved for treatment of TBI? Do the observed beneficial effects of amantadine extend to disorders of consciousness due to factors other than TBI? Well controlled clinical studies are warranted to ultimately confirm its utility in the TBI and provide answers these questions.

In the development of the safety-critical systems, it is important to perform Failure Modes and Effects Analysis (FMEA) process to identify potential failures. However, traditional FMEA activities tend to be considered difficult and time-consuming tasks. To compensate for the difficulty of the FMEA task, various types of tools are used to increase the quality and the effectiveness of the FMEA reports. This paper explains an Automatic FMEA tool which integrates the Model-based Design (MBD), FMEA, and Simulated Fault Injection techniques in a single environment. The Automatic FMEA tool has the following advantages compared to the existing FMEA analysis tool. First, the Automatic FMEA tool automatically generates FMEA reports compared to the traditional spreadsheet-based FMEA tools. Second, the Automatic FMEA tool analyzes the causality between the failure modes and the failure effects by performing model-based fault injection simulation. In order to demonstrate the applicability of the Automatic FMEA, we used the electronic fuel injection system (EFI) Simulink model. The results of the Automatic FMEA were compared to that of the legacy FMEA.

Recent years have seen a massive increase in research on mindfulness as both a therapeutic practice as well as a protective health factor. While many associations have been made between mindfulness and clinical outcomes, understanding of the underlying mechanistic processes is still in its infancy. In this review, associations between mindfulness and other established frameworks in cognitive control are explored—in particular the dual modes of control framework in cognitive control theory. Studies in mindfulness providing evidence towards a dual-mode mindfulness model are reviewed and compared with the proactive and reactive modes of cognitive control to identify common underlying principles. Studies involving cognitive testing, advanced neuroimaging, and neurotransmitter levels and their associations with proactive and reactive control are reviewed in the context of the dual modes of mindfulness. While evidence supporting relationships between proactive and reactive modes of mindfulness and cognitive control are preliminary, existing literature on mindfulness already supports the notion of two components of mindfulness and is in line with the hypothesis that cognitive control and mindfulness are closely related. Since preliminary evidence suggests that proactive forms of mindfulness are more associated with improvement in clinical outcomes, mindfulness programs could be modified to target proactive mindfulness practices to maximize outcomes. The implications of proactive and reactive mindfulness on therapy, limitations of the framework, and necessity of studies providing direct evidence are further discussed.

Network Embedding (NE) is an important method to learn the representations of network via a low-dimensional space. Conventional NE models focus on capturing the structure information and semantic information of vertices while neglecting such information for edges. In this work, we propose a novel NE model named BimoNet to capture both the structure and semantic information of edges. BimoNet is composed of two parts, i.e., the bi-mode embedding part and the deep neural network part. For bi-mode embedding part, the first mode named add-mode is used to express the entity-shared features of edges and the second mode named subtract-mode is employed to represent the entity-specific features of edges. These features actually reflect the semantic information. For deep neural network part, we firstly regard the edges in a network as nodes, and the vertices as links, which will not change the overall structure of the whole network. Then we take the nodes' adjacent matrix as the input of the deep neural network as it can obtain similar representations for nodes with similar structure. Afterwards, by jointly optimizing the objective function of these two parts, BimoNet could preserve both the semantic and structure information of edges. In experiments, we evaluate BimoNet on three real-world datasets and task of relation extraction, and BimoNet is demonstrated to outperform state-of-the-art baseline models consistently and significantly.

Exosomes, natural nanovesicles that contain a cargo of biologically active molecules such as lipids, proteins, and nucleic acids, are released from cells to the extracellular environment. They then act as autocrine, paracrine, or endocrine mediators of communication between cells by delivering their cargo into recipient cells and causing downstream effects. Exosomes are greatly enriched in miRNAs, which are small non-coding RNAs that act as cytoplasmic posttranscriptional repression agents, modulating the translation of mRNAs into proteins, as well as nuclear transcriptional gene activators. Neuronal exosomal miRNAs have important physiologic functions in the Central Nervous System (CNS), including cell-to-cell communication, synaptic plasticity, and neurogenesis, as well as modulating stress and inflammatory responses. Stress-induced changes of exosomal functions include effects on neurogenesis and neuroinflammation, which can lead to the appearance of various neuropsychiatric disorders, such as schizophrenia, major depression, bipolar disorder, and Alzheimer's and Huntington’s's diseases. The current knowledge regarding the roles of exosomes in the pathophysiology of common mental disorders is discussed in this review.

Steroid and hopanoid biomarkers can be found in ancient rocks and may give a glimpse of what life was present at that time. Sterols and hopanoids are produced by two related enzymes, though the evolutionary history of this protein family is complicated by losses and horizontal gene transfers, and appears to be widely misinterpreted. Here, I have added sequences from additional species, and re-analysis of the phylogeny of SHC and OSC indicates a single origin of both enzymes among eukaryotes. This pattern is best explained by endosymbiotic acquisition of both enzymes from a bacterial ancestor, followed by widespread loss of SHC, and two subsequent HGT events to ferns and ascomycetes. Thus, the last common ancestor of eukaryotes would have been bifunctional for both sterol and hopanoid production. Later enzymatic innovations allowed diversification of sterols in eukaryotes. Contrary to previous interpretations, the last eukaryotic common ancestor (LECA) potentially would have been able to produce hopanoids as a substitute for sterols in anaerobic conditions. Without invoking any other metabolic demand, the LECA could have been a facultative aerobe, living in unstable conditions with respect to oxygen level.

In this paper, we prove some common fi xed point theorems on complex partial metric space. The presented results gener- alize and expand some of the literature well-known results. We also explore some of the application of our key results.

The formation of new blood vessels is a critical process for tumor growth and may be achieved through different mechanisms. Angiogenesis represents the first described and most studied mode of vessel formation, but tumors may also use alternative ways to secure blood supply and eventually acquire resistance to anti-angiogenic treatments. These non-angiogenic mechanisms have been described more recently and include intussusceptive microvascular growth (IMG), vascular co-option, and vasculogenic mimicry. Like solid tumors, also in lymphomas angiogenic and non-angiogenic pathways play a fundamental role in tumor growth and progression. In view of the relevant prognostic and therapeutic implications, a comprehensive understanding of these mechanisms is of paramount importance for improving the efficacy of treatment in patients with lymphoma. In this review, we summarize the current knowledge on angiogenic and non-angiogenic mechanisms involved in the formation of new blood vessels in Hodgkin’s and non-Hodgkin’s lymphomas.

A data-driven analysis method known as dynamic mode decomposition (DMD) approximates the linear Koopman operator on projected space. In the spirit of Johnson-Lindenstrauss Lemma, we will use random projection to estimate the DMD modes in reduced dimensional space. In practical applications, snapshots are in high dimensional observable space and the DMD operator matrix is massive. Hence, computing DMD with the full spectrum is infeasible, so our main computational goal is estimating the eigenvalue and eigenvectors of the DMD operator in a projected domain. We will generalize the current algorithm to estimate a projected DMD operator. We focus on a powerful and simple random projection algorithm that will reduce the computational and storage cost. While clearly, a random projection simplifies the algorithmic complexity of a detailed optimal projection, as we will show, generally the results can be excellent nonetheless, and quality understood through a well-developed theory of random projections. We will demonstrate that modes can be calculated for a low cost by the projected data with sufficient dimension.

Type 2 Diabetes Mellitus and Alzheimer's disease are two diseases with a high incidence today that share similar pathophysiological mechanisms suggesting a potential causal relationship between them. In fact, Alzheimer-associated Mellitus Diabetes is also known as Type 3 Diabetes Mellitus and constitutes a diabetes intricately linked to Alzheimer's disease. Central to this association is insulin resistance, a key factor leading to decreased insulin sensitivity, hyperglycemia, and impaired glucose uptake. Because of this, the brain is altered resulting in energy deficits and neuronal damage associated with neurodegenerative disorder characteristic of Alzheimer's disease. Both diseases exhibit common biochemical and physiological characteristics such as inflammation, mitochondrial dysfunction, oxidative stress, and the formation of advanced glycation end products. Understanding the complex pathophysiology of Type 3 Mellitus Diabetes and identifying common features shared with Diabetes and Alzheimer's disease are essential steps towards potential therapeutic interventions targeting the insulin resistance pathway. The authors of this review on the relationships between type 2 diabetes and Alzheimer's disease have developed two works. In the first (Relationships between Type 2 Diabetes Mellitus and Alzheimer's Disease. I. Common pathogenic mechanisms), authors explore the shared (physiological, genetics and molecular) pathological changes occurring in Type 2 Mellitus Diabetes and Alzheimer's disease as well as pathways such as AMPK, PPARγ, cAMP, and PI3K/Akt as potential targets for managing Type 3 Diabetes Mellitus. By exploring these intricate mechanisms, the goal is to uncover their interdependencies and facilitate the discovery of innovative pharmacological and nutritional (epigenetics) strategies. In the second paper (Relationships between Type 2 Diabetes Mellitus and Alzheimer's Disease. II Potential therapies) we describe possible nutritional intervention, particularly dietary patterns and phytochemicals that can enhance the effects of pharmaceutical drugs designed against pathological mechanisms involved in the complex dual disease Type 2 Diabetes Mellitus and Alzheimer's disease (or in Type 3 Diabetes Mellitus as other authors consider).

With the continuous improvement and observable benefits of electric vehicles (EVs), major logistic companies are introducing more EVs into their conventional fleets. This gives rise to a new type of vehicle routing problem with mixed vehicles, where heterogeneous internal combustion vehicles (ICVs) and electric vehicles are considered in route planning. In addition, certain deliveries that are not efficient on any type of vehicles, are outsourced to third-party common carriers. In this paper, we define this problem as a mixed vehicle routing problem with common carriers (MVRPC). The objective of such problems is to minimize the transportation costs by considering routes with ICVs and EVs, the possibility of visiting recharging stations, outsourcing options, and drivers’ layover regulations. This variant of the vehicle routing problems has many practical applications, particularly in the design of long-haul transportation and last-mile delivery services. Effective MVRPC solutions play a key role in promoting the going Green image and optimally allocating resources. The problem has received limited attention in the literature likely because addressing all the needed aspects is especially challenging. To solve the large-scale problem, we develop a branch-and-cut pricing framework that relies on strong cuts and customized labeling algorithms. Numerical experiments highlight the effectiveness of our algorithm. This success can be attributed to tailored critical resources, dynamically bounded bidirectional labeling procedures, strong dominance criteria, and implementation strategies.

Data on helminth parasites and epizoites is presented for the long-beaked and short-beaked common dolphins from the Southeast Pacific. Sampling in 1985-2000 was conducted mainly at six fishing ports in Peru and Ecuador where cetaceans were landed. From a total of 473 common dolphins sampled, we identified helminths including three species of Trematoda: Nasitrema globicephalae, Pholeter gastrophilus and Braunina cordiformis; three species of Nematoda, which includes Anisakis spp., Crassicauda sp. and Halocercus sp.; and two cestodes Tetrabothrius forsteri and Clistobothrium delphini (formerly Phyllobothrium delphini). No acanthocephalans were observed. No statistically significant sexual and ontogenetic variation in helminth prevalence was detected after which samples were pooled. The highest prevalence in the long-beaked common dolphin (n=440) was observed for N. globicephalae (96.3%) in cranial sinuses, Crassicauda sp. (83.3%) in mammary glands, Crassicauda sp. (78.8%) infesting the cranial sinuses, followed by Cl. delphini (28.6%) in the blubber and P. gastrophilus and B. cordiformis (20.4%) in the digestive tract. Although comparative testing was unfeasible due to minimal samples of short-beaked common dolphin (n=33), several of the same helminth species were found, but not N. globicephalae nor B. cordiformis. No cyamids were encountered while pseudo-stalked barnacles Xenobalanus globicipitis were common. No new (global) helminth host records are revealed for common dolphins, but this study presents a first checklist of parasites separately for the Southeast Pacific long-beaked and short-beaked common dolphins. Future work should include exhaustive laboratory-based necropsies, enhanced sampling of the short-beaked form, focus on intermediate hosts and parasitic pathology, including potential human health impact from consumption of small cetaceans.

Despite the popularity of theraphosids, detailed reports on bite symptoms are still limited to few geographic regions and subfamilies. We therefore examined 363 published bite reports and noticed muscles cramps caused by theraphosids from nearly all continents and subfamilies. Symptoms are mostly locally restricted and mild, but 12.7% of victims experience pronounced cramps with highest incidence rates by Poecilotheriinae, Harpactirinae and Stromatopelminae subfamilies. We discuss how variations in venom quantity correlate with muscle cramp prevalence.

Introduction: Cholelithiasis and consumption of alcohol are the most frequent causes of acute pancreatitis (AP), accounting for about 30 to 40% of the cases, respectively. The frequency of acute biliary pancreatitis is high in a certain population in Brazil. Objective: To estimate the global frequencies of acute biliary pancreatitis (ABP), acute alcoholic pancreatitis (AAP) and the cases considered as acute idiopathic pancreatitis (AIP) in studies published from October 2006 to December 31, 2018. Methods: A systematic review of observational studies was performed from October 2006 to December 31, 2018. A meta-analysis by the random effects model was used to calculate the frequencies of global ABP, AIP and AAP and subgroups. Results: Forty-six studies representing 2,341,007 AP cases were included in 36 countries. The overall estimate for acute biliary pancreatitis (ABP) was 41.6% (95% CI 39.2-44.1), followed by acute alcoholic pancreatitis (AAP) with 20.5% (95% CI) 16.6- 24.6) and acute idiopathic pancreatitis (AIP) in 18.3% (95% CI 15.1-27.7). Conclusion: ABP is the most prevalent etiology of AP, being two times more frequent than second-placed pancreatitis. Latin America has a frequency for ABP much higher than the rest of the world. The importance of the etiologic diagnosis is the treatment of the cause for prevention of recurrence.

A well known result for the interference of two single-mode fields is that the degree of coherence and the degree of indistinguishablity are same when we consider the detection of a single photon. In this article we present the relation between degree of coherence, path indistinguishability and the fringe visibility considering interference of multiple number of single-mode fields while being interested in the detection of a single photon only . We will also mention how Born’s rule of interference for multiple sources is reflected in these results.

Autism spectrum disorder (ASD) is a neuropsychiatric condition characterized by impaired social interactions and repetitive stereotyped behaviors. Growing evidence highlights an important role of the gut-brain-microbiome axis in the pathogenesis of ASD. Research indicates an abnormal composition of the gut microbiome and the potential involvement of bacterial molecules in neuroinflammation and brain development disruptions. Concurrently, attention is directed towards the role of short-chain fatty acids (SCFAs) and impaired intestinal tightness. This comprehensive review emphasizes the potential impact of maternal gut microbiota changes on the development of autism in children, especially considering maternal immune activation (MIA). The following paper evaluates the impact of the birth route on the colonization of the child with bacteria in the first weeks of life. Furthermore, it explores the role of pro-inflammatory cytokines, such as IL-6 and IL-17a and mother’s obesity as potentially environmental factors of ASD. The purpose of the present analysis is to advance our understanding of ASD pathogenesis, while also searching for the positive implications of the latest therapies, such as probiotics, prebiotics or fecal microbiota transplantation, targeting the gut microbiota and reducing inflammation. This review aims to provide valuable insights that could instruct future studies and treatments for individuals affected by ASD.

A Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debilitating chronic disease of unknown aetiology under growing interest now in view of the increasingly recognized post-COVID syndrome as a new entity with similar clinical presentation. We performed the first cross-sectional study of ME/CFS in community population in Russia and then described and compared some clinical and pathophysiological characteristics of ME/CFS and post-COVID syndrome as neuroimmune disorders. Of the cohort of 76 individuals who suggested themselves suffering from ME/CFS 56 subsequently were confirmed as having CFS/ME according to ≥1 of the 4 most commonly used case definition. Of the cohort of 14 individuals with post-COVID-19 syndrome 14 met diagnostic criteria for ME/CFS. The prevalence of clinically expressed and subclinical anxiety and depression in ME / CFS and post-COVID ME/CFS did not differ significantly from that in healthy individuals. Severity of anxiety / depressive symptoms did not correlate with the severity of fatigue neigther in ME / CFS nor in post-COVID ME/CFS, but the positive correlation was found between the severity of fatigue and 20 other symptoms of ME / CFS related to the domains of “post-exertional exhaustion”, “immune dysfunction”, “sleep disturbances”, "dysfunction of the autonomic nervous system", "neurological sensory / motor disorders" and "pain syndromes". Immunological abnormalities were identified in 12/12 patients with ME / CFS according to the results of laboratory testing. The prevalence of postural orthostatic tachycardia assessed by the active standing test was 37.5% in ME / CFS and 75.0% in post-COVID ME/CFS (the latter was higher than in healthy controls, p = 0.02) There was a more pronounced increase in heart rate starting from the 6th minute of the test in post-COVID ME/CFS compared with the control group. Assessment of the functional characteristics of microcirculation by laser doppler flowmetry revealed obvious and very similar changes in ME/CFS and post-COVID ME/CFS compared to the healthy controls. The identified pattern corresponded to the hyperemic form of microcirculation disorders, usually observed in acute inflammatory processes or in deficiency of systemic vasoconstriction influences.

The nutraceutical value of pomegranate in the treatment of many neoplastic, cardiovascular, viral, inflammatory, metabolic, microbial, intestinal, reproductive and skin diseases is well-documented and is linked to its richness in phenolic compounds. This study aims to evaluate nutraceutical and genetic diversity of novel pomegranate genotypes (G1-G5) in comparison to leading commercial pomegranate varieties i.e. ‘Wonderful’, ‘Primosole’, ‘Dente di Cavallo’ and ‘Valenciana’. Morphometric measurements were carried out on fruits, accompanied by chemical characterization and the development of four new polymorphic SSR markers involved in the flavonoid pathway. The cultivars displayed a marked variability in the weight and shape of fruits, as well as in the weight of arils and juice yield. The highest level of total phenolic content and antioxidant activity was found in ‘Wonderful’ and G4, while the lowest was in ‘Dente di Cavallo’. Furthermore, the results showed that the pomegranate juice, is an excellent source of minerals, especially potassium, which plays a key role in organ functioning. The new flavonoid-related markers effectively differentiated the cultivars with the same diversity pattern as morpho-chemical characterization, so the SSRs developed in the present study can be used as a rapid tool for the identification of pomegranate cultivars with relevant nutraceutical traits.

The structures of recently discovered primarolides A and B suggest their non-enzymatic formation from a common 2-formylbenzophenone precursor. This hypothesis is based on the experimentally proven facile conversion of pestalone (also a 2-formyl-benzophenone) either into the isomeric lactone pestalalactone or the structurally related isoindolinone pestalachloride A. In a related fashion, the racemic isoindolinone natural product mariline A is supposed to biosynthetically originate from the corresponding keto-aldehyde and an aniline, as experimentally supported by model studies. Due to the close structural relationship with known systems, it appears highly probable that primarolides A and B were generated under the fermentation conditions from a massarinin-related 2-formylbenzophenone (proprimarolide) by reaction either with aniline or a nucleophilic catalyst, respectively. Suberoylanilide hydroxamic acid (SAHA), used as an additive during the fermentation, is supposed to act both as a source of aniline and as a nucleophilic catalyst.

Usage of antimicrobials in veterinary practices has always been under scrutiny due to the perceived risk of resulting in antimicrobial-resistant pathogens. This creates the necessity for understanding the role of the prescriber group. Hence, we conducted a cross-sectional survey among veterinary practitioners from August to November 2019 in the Chattogram district of Bangladesh, aiming to assess the practitioner’s perceptions regarding antimicrobial prescribing and antimicrobial resistance (AMR) issue. We collected responses from 100 veterinarians engaged in the treatment of the large animal, poultry, and pet animal through a self-administrated questionnaire. Proportions were calculated for categorical variables and the results are presented using visual aids. Our study revealed two key barriers - scarcity of enough information on antimicrobial used, and the lack of training in the proper prescription of antimicrobials. Participants recognized that prescribing too many varieties of antimicrobials and the use of an incomplete course of drugs as two very important causes for the development of antimicrobial resistance. In addition, prescription of inappropriate doses and incentives from pharmaceutical companies were dubbed as important causes. We also found that along with clinical features and types of organisms, the availability of drugs in the local market and the economic conditions of farmers have potential impacts on the antimicrobials prescribing decision of the veterinarians. However, all participants recognized the emerging threats of AMR. Results suggested that capacity building of veterinarians and the maintenance of strong coordination are crucial in ensuring the proper engagement of veterinarians as the front-line fighters for tackling the AMR issue.

The design of a mixed-mode proportional-integral-derivative (PID) controller circuit using current-feedback operational amplifiers (CFOAs) as active components is proposed. With the same circuit topology, the proposed configuration of three CFOAs, four resistors, and two capacitors is capable of performing the PID controller in all four operation modes: namely voltage mode, trans-admittance mode, current mode, and trans-impedance mode. Numerous mathematical analyses are conducted to determine the controller performance under ideal and non-ideal conditions. Additionally, the mixed-mode second-order lowpass filter is suggested, and also used to examine the workability of the proposed mixed-mode PID controller in a feedback control structure. The proposed PID controller is implemented with the commercially available IC-type CFOA AD844, and the simulation results are presented to illustrate the functionality of the controller and its closed-loop control system.

The microgrid is a small-scale, autonomous decentralized power plant with its own distributed generation, storage capacity and multiple loads, with the capacity to function in grid interconnected and an island mode. The decentralized control of microgrids with parallel operated voltage source converters (VSCs) is proposed in this paper to improve power quality using a machine learning approach. The DNN based MPPT controller is proposed and its best performance is presented. The SRF-PLL is utilized for AC side synchronization in VSC control. The proposed microgrid involves two PV arrays fed to two voltage source converters along with their independent controls, connected in parallel through LC filters and line coupling transformers and serves the loads at PCC. The proposed model is simulated using MATLAB/Simulink. The dq-framed inner loop control is employed to individually regulate the real and reactive power at the point of common coupling. Furthermore, the proposed model is analyzed and compared by employing a mathematical model of AC system dynamics, inner loop control, output voltage quality, AC harmonic spectrum analysis, and total harmonic distortion (THD) in both grid interconnected and island mode. In island mode, AC harmonic spectrum and THD are accomplished within the permissible range.

As a critical transmitter, the compact 532 nm lasers operating on high repetition and narrow pulse widths have been used widely for airborne or space-borne laser active remote sensing. We developed a free space pumped TEM₀₀ mode sub-nanosecond 532 nm laser that occupied a volume of less than 125 mm × 50 mm × 40 mm (0.25 liters). The fundamental 1064 nm laser consists of a passively Q-switched composite crystal microchip laser and an off-axis, two-pass power amplifier. The pump sources were two single-emitter semiconductor laser diodes (LD) of 808 nm with a maximum continuous wave (CW) power of 10 W each. The average power of fundamental 1064 nm laser was 1.26 W with the laser operating at 16 kHz repetition rates, and 857ps pulse widths. Since the beam distortion would be severe in microchip lasers in terms of the increase in heat load, for obtaining a high beam quality of 532 nm, the beam distortion was compensated by adjusting the distribution of pumping beam in our experiment of fundamental amplification. Furthermore, better than 0.6 W average power, 770 ps, beam quality of M² ＜1.2, and 16 kHz pulse output at 532 nm was obtained by a Type I LiB₃O₅ (LBO) crystal in the critical phase matching (CPM) regime for second harmonic generation (SHG).

Two-dimensional mass spectrometry (2D MS) is a method for tandem mass spectrometry that relies on manipulating ion motions to correlate precursor and fragment ion signals. 2D mass spectra are obtained by performing a Fourier transform in both the precursor ion mass-to-charge ratio (m/z) dimension and the fragment ion m/z dimension. The phase of the ion signals evolves linearly in the precursor m/z dimension and quadratically in the fragment m/z dimension. This study demonstrates that phase-corrected absorption mode 2D mass spectrometry improves signal-to-noise ratios by a factor of 2 and resolving power by a factor of 2 in each dimension compared to magnitude mode. Furthermore, phase correction leads to an easier differentiation between ion signals and artefacts, and therefore easier data interpretation.

(1) Background: There is not much research about obesity in nursing homes although knowledge will help us to develop customized treatment plans and prevention strategies, which may help to decrease the burden for all persons involved. The objective of conducting this study was to describe the prevalence of obesity and the association between obesity and care problems in nursing home patients. (2) Methods: This study is a secondary data analysis of data collected in an annually performed cross-sectional study called “Nursing Quality Measurement 2.0”. A standardized and tested questionnaire was used to collect data. (3) Results: 1236 nursing home patients took part and 16.7% of them were obese. The multivariate logistic regression analysis results show that urinary incontinence is significantly associated with the presence of obesity (OR 2.111). The other care problems of pressure injuries, fecal and double incontinence, physical restraints, falls and pain were not associated with obesity. (4) Conclusion: The results indicate that, in the nursing home setting, health care staff should pay special attention to the patients’ nutritional and continence status and help patients maintain a normal, healthy weight. Conducting more studies with larger sample sizes is recommended, as this will allow differentiation among different obesity classes.

The following system of equations {x_1 \cdot x_1=x_2, x_2 \cdot x_2=x_3, 2^{2^{x_1}}=x_3, x_4 \cdot x_5=x_2, x_6 \cdot x_7=x_2} has exactly one solution in ({\mathbb N}\{0,1})^7, namely (2,4,16,2,2,2,2). Hypothesis 1 states that if a system of equations S \subseteq {x_i \cdot x_j=x_k: i,j,k \in {1,...,7}} \cup {2^{2^{x_j}}=x_k: j,k \in {1,...,7}} has at most five equations and at most finitely many solutions in ({\mathbb N}\{0,1})^7, then each such solution (x_1,...,x_7) satisfies x_1,...,x_7 \leq 16. Hypothesis 1 implies that there are infinitely many composite numbers of the form 2^{2^{n}}+1. Hypotheses 2 and 3 are of similar kind. Hypothesis 2 implies that if the equation x!+1=y^2 has at most finitely many solutions in positive integers x and y, then each such solution (x,y) belongs to the set {(4,5),(5,11),(7,71)}. Hypothesis 3 implies that if the equation x(x+1)=y! has at most finitely many solutions in positive integers x and y, then each such solution (x,y) belongs to the set {(1,2),(2,3)}. We describe semi-algorithms sem_j (j=1,2,3) that never terminate. For every j \in {1,2,3}, if Hypothesis j is true, then sem_j endlessly prints consecutive positive integers starting from 1. For every j \in {1,2,3}, if Hypothesis j is false, then sem_j prints a finite number (including zero) of consecutive positive integers starting from 1.

(1) Background: The study presents an assessment of the psychometric properties of the Polish version the Short Schema Mode Inventory (SMI) adaptation. (2) Methods: First, the original version of the scale was translated. Subsequently, a validity and reliability study was conducted on a sample of 240 patients and 400 non-patients. In particular: the factor structure of the inventory was checked, internal reliability and intercorrelations between subscales were tested, differences between the clinical and non-clinical groups in terms of the severity of each factor were examined, and construct validity was assessed by comparing the association of results with external variables. (3) Results: The results did not conclusively confirm the 14-factor structure postulated in the original scale. Nevertheless, relatively the best fit indices were obtained for such a model. Internal reliability for the 14 subscales was in the acceptable to excellent range. Correlations between subscales took moderate to high values. The existence of differences between the clinical and non-clinical groups and the construct validity were confirmed. (4) Conclusions: The psychometric evaluation performed is mostly similar to the results obtained for other adaptations, and the results entitle the inventory to be used for research and clinical purposes with the knowledge of its limitations.

The goal of this study was to determine the relative susceptibility of four common equine wound pathogens to ten different types of antimicrobial agents based on minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC). Additionally, to describe the comparison of bactericidal activity of medical grade Manuka honey, local honey, and commercial, food-grade honey to other commonly used wound dressings. The objective is to provide veterinary practitioners with comparative data on the use of a variety of antimicrobial dressings for inhibiting growth of common wound bacteria. MIC and MBC for Manuka, store, and local honeys were comparable to those of sterile gauze, sugar, and hypertonic saline. Across bacterial species, local honey proved to have more bactericidal activity when compared to Manuka and commercial, food-grade honey. The MIC and MBC for PHMB gauze and foam was consistently at a higher dilution compared to the other antimicrobials. The majority of antimicrobials exhibited stronger inhibitory and bactericidal activity against a Streptococcus zooepidemicus isolate obtained from a wound compared to other bacteria that were ATCC lab acclimated. Additional research for in-vivo applications needs to be done to see whether differences exist in effective wound management.

(1) Background: Respiratory infections are a major public health problem worldwide, with potentially serious consequences. Indeed, these infections remain one of the main causes of morbidity and mortality in children under 5 years old in developing countries. Etiological information on respiratory infections is crucial for prevention and case management strategies. This systematic review aims to describe the etiology of respiratory infections reported in studies carried out in sub-Saharan African countries; (2) Methods: Using PubMed, HINARI and Google scholar search engines, a systematic search was carried out to identify published articles on the etiology of viral and/or bacterial respiratory infections in sub-Saharan Africa in patients of all ages. We have only considered data from sub-Saharan Africa. Papers published from 2010 to 2021, in English or French have been included in this review; (3) Results: After reviewing 115 articles reporting studies carried out in the African continent, only 32 articles were selected of which, studies were conducted in 15 sub-Saharan African countries, including 6/32 (18.75%) in Cameroon. Twenty (62.5%) were cross-sectional studies, and twenty-four (75%) were hospital-based investigations. In these studies, RT-PCR and culture methods were respectively used for viruses and bacteria investigations. Respiratory syncytial virus was the most frequently identified, with prevalence ranging from 0.6% to 59%, followed by rhinovirus (9.3% -73%), influenza virus (flu) A/B (0.9%-69.1%), and human adenovirus (0.9% - 30.8%). Streptococcus pneumoniae (14.2% - 96%), followed by Haemophilus influenzae type b (2.5% - 54%), and Klebsiella pneumoniae (1.4% - 49.9%) were the most frequently detected bacteria; (4) Conclusions: This review has reported that many pathogens, mainly viruses, are associated with acute respiratory infections in sub-Saharan Africa in both children and adults. Unfortunately, the limited geographical distribution of data across sub-Saharan Africa does not allow most of countries to develop an effective strategy for the prevention and treatment of respiratory infections.

The giant anteater (Myrmecophaga tridactyla) is a vulnerable specie from Central and South America and is considered extinct in Belize, Guatemala, El Salvador, and Uruguay. Therefore, studies describing the reproductive characteristics of this species are pivotal for its conservation. Thus, this study aimed to provide a morphological description of their female reproductive tissues. We collected tissue samples from six female giant anteaters, and performed gross, morphological, and histochemical analyses. Five adult and one young subjects were enrolled in the study. In the ovary, classifications were made according to the follicle and oocyte sizes: primordial, primary, secondary, early antral, or antral. Typical follicles with a single oocyte surrounded by a simple or stratified layer of cubic epithelium, atretic follicles, corpora lutea, corpora albicans, and ovarian cysts were also observed. No ovarian lesions were observed. By contrast, endometritis, metritis, mucometra, and endometrial cysts were identified in the uterus. Uterine alterations in these subjects were frequent and could affect reproduction.

In the event of an abrupt sunlight reduction scenario there is a time window that occurs between when food stores would likely run out for many countries (~6 months or less) and ~1 year when resilient foods are scaled up. A promising temporary resilient food is leaf protein concentrate (LPC). Although it is possible to extract LPC from tree biomass (e.g. leaves and needles), neither the yields nor the toxicity of the protein concentrates for humans from the most common tree species has been widely investigated. To help fill this knowledge gap, this study uses high-resolution mass spectrometry and an open source toolchain for non-targeted screening of toxins on five common North American coniferous species: Western Cedar, Douglas Fir, Ponderosa Pine, Western Hemlock, and Lodgepole Pine. The yields for LPC extraction from the conifers ranged from 1% to 7.5%. The toxicity screenings confirm that these trees may contain toxins that can be consumed in small amounts and additional studies including measuring the quantity of each toxin are needed. The results indicate that LPC is a promising candidate to be used as resilient food, but future work is needed before LPCs from conifers can be used as a wide-scale human food.

Marnaviridae viruses are abundant algal viruses that regulate the dynamics of algal blooms in aquatic environments. They employ a narrow host range because they merely lyse their own algal host species. This host-specific lysis is thought to correspond to the unique transmission mechanism of the Marnaviridae viruses. Here, we present the atomic structures of the full and empty capsids of Chaetoceros socialis forma radians RNA virus 1 built in 3.0 Å and 3.1 Å cryo-electron microscopy maps. The empty capsid structure and the structural variability provide insights on its assembly and uncoating intermediates. In conjunction with the previously reported atomic model of the Chaetoceros tenuissimus RNA virus type II capsid, we have identified the common and diverse structural features of the VP1 surface between the Marnaviridae viruses. We have also tested the potential usage of AlphaFold2 for structural prediction of the VP1s and a subsequent structural phylogeny for classifying Marnaviridae viruses by their hosts. These findings will be crucial for inferring the host-specific transmission mechanism in Marnaviridae viruses, which is decisive for monitoring and possibly regulating the occurrence and disappearance of algae blooms.

Phosphate (Pi) deficiency reduces nodule formation and development in different legume species including common bean. Despite the significant progress in the understanding of the genetic responses underlying the adaptation of nodules to Pi deficiency, it is still unclear whether this nutritional deficiency interferes with the molecular dialog between legumes and rhizobia, if so, what part of the molecular dialog is impaired? In this study, we provide evidence demonstrating that Pi deficiency negatively affects critical early molecular and physiological responses required for a successful symbiosis between common bean and rhizobia. We demonstrated that the infection thread formation and the expression of PvNSP2, PvNIN, and PvFLOT2, genes controlling the nodulation process, were significantly reduced in Pi-deficient common bean seedlings. Further transcriptional analysis revealed that the expression of hormones-related genes is compromised in Pi-deficient seedlings inoculated with rhizobia. Additionally, we showed that regardless of the presence or absence of rhizobia, the expression of PvRIC1 and PvRIC2, two genes participating in the autoregulation of nodule number, was higher in Pi-deficient seedlings than in control seedlings. The data presented in this study shed light on the understanding of how Pi deficiency impacts the early steps of the symbiosis between common bean and rhizobia.

The negative impact of drought on plant growth may be modified by different availability of mineral nutrients and by their adaptation to different local habitat conditions. In this study, we examine the impact of drought, fertilization with phosphorus and provenance, as well as their interactions, on the growth and allometric growth relationships between belowground and aboveground organs of common beech (Fagus sylvatica) and sessile oak (Quercus petraea). The research was conducted on saplings originating from two mature mixed stands (dry and wet provenances) dominated by these species. In the common garden experiment, saplings were exposed to regular watering and drought in interaction with moderate and high phosphorus concentrations in the growing substrate (achieved by phosphorus fertilization). Obtained results indicate negative impact of drought and phosphorus fertilization on the growth of both species. In common beech, phosphorus fertilization had a negative impact on its adaptive capacity to drought, because of the unfavourable ratios between fine root mass and mass of other organs. The sessile oak provenances under the impact of drought showed a different root collar diameter/stem height increment ratio, which indicates its different phenotypic plasticity as a consequence of adaptation to different frequencies of dry periods in their natural habitats.

The dynamic effects observed in collisions represent a specific area of high-energy interaction located at the boundary of mechanics, hydrodynamics, shock wave physics, and alternating high-pressure regions. The paper shows that in the volume of a solid metal body, as a result of dynamic alloying by a high-speed stream of powder particles in the super-deep penetration mode (SDP), fibre structures of altering material arise, forming the framework of the composite material. The stream of powder particles in the metal obstacle following the path of least resistance and the impact of shock waves on particles results in a volumetric framework from the products of interaction between the injected and matrix materials. When using SDP, defective structural elements (channelled) - germs of reinforcing fibres arise. At the subsequent heat treatment, there is an intensive diffusion. The growth process of reinforcing fibres shifts to higher temperatures (as compared to the standard mode), leading to an increase in the bending strength of the fibre material up to 13 times for high-speed tool W6Mo5Cr4V2 steel. As a result of the completion of the growth of reinforcing fibres in the volume of the W6Mo5Cr4V2 steel, the material's bending strength in 1.2 times is realised. Simultaneously, it provides an increase of wear resistance 1.7-1.8 times.

This article presents a decentralized phase-shedding technique for multiphase converters. The usual central digital controller is replaced by identical local controllers forming a daisy-chain structure. Phase-shedding decisions are taken locally based on a local inductor current monitoring and threshold crossing management. This control strategy allows to implement as many phases as desired in a modular manner. In order to handle specific events such as load current inrush or a start-up sequence and to guarantee optimal transient responses, additional functions are included into each local controllers. The inter-cell communication protocol is described, along with necessary design considerations of threshold and timing values. Finally, functional simulations are carried out on a 5-leg 12V/1.2V 60W multiphase converter, which validate the proposed decentralized phase-shedding strategy for a microcontroller power supply implementation.

The work safety standardization of enterprises based on the traditional work safety theory has played a significant role in reducing the number of accidents and improving work safety to some extent in China. However, some problems are coming with the work safety standardization of enterprises developing constantly in China. On the one hand, it is not combined with the actual situation of the enterprise, lacking pertinence and specificity, these defects resulted that it is not integrated with original safety production management system of enterprise and make it difficult to carry out. On the other hand, there is a lack of systematic management methods for the work safety management system of enterprise, most of enterprises only pay attention to the inspection result rather than the process control. This means after the check of the government, many enterprises will relax to carry out the system. This paper puts forward a new method for optimizing the standardization management mode of work safety based on the Viable System Model(VSM), which can solve the defects of work safety standardization of enterprises management system. An optimization model of work safety standardization based on VSM was construct for explaining the process optimization and control of work safety standardization management. It can improve the connectivity between the enterprise and the government. The conclusion of this paper can provide reference for achieving the development and optimization of work safety standardization of enterprises in China.

The new barrier mode in Apache Spark allows embedding distributed deep learning training as a Spark stage to simplify the distributed training workflow. In Spark, a task in a stage doesn’t depend on any other tasks in the same stage, and hence it can be scheduled independently. However, several algorithms require more sophisticated inter-task communications, similar to the MPI paradigm. By combining distributed message passing (using asynchronous network IO), OpenJDK’s new auto-vectorization and Spark’s barrier execution mode, we can add non-map/reduce based algorithms, such as Cannon’s distributed matrix multiplication to Spark. We document an efficient distributed matrix multiplication using Cannon’s algorithm, which improves significantly on the performance of the existing MLlib implementation. Used within a barrier task, the algorithm described herein results in an up to 24% performance increase on a 10,000x10,000 square matrix with a significantly lower memory footprint. Applications of efficient matrix multiplication include, among others, accelerating the training and implementation of deep convolutional neural network based workloads, and thus such efficient algorithms can play a ground-breaking role in faster, more efficient execution of even the most complicated machine learning tasks

We show that an experimentally plausible system consisting of a modulated wire medium hosted in a metal cavity can preserve the longitudinal field profile shaping predicted by Boyd et al. (2018) on the basis of a perfectly periodic wire-only structure. These new frequency domain numerical results are a significant step towards justifying the construction of an experimental apparatus to test the field profile shaping in practise.

This study investigates the metabolic parallels between stimulated pancreatic beta cells and cancer cells, emphasizing glucose and glutamine metabolism. Addressing the significant public health challenges of Type 2 Diabetes Mellitus (T2DM) and cancer, we aim to deepen understanding of the mechanisms driving insulin secretion and cellular proliferation. Our analysis of anaplerotic cycles and NADPH's role in biosynthesis elucidates their vital functions in both processes. Additionally, we find that both cell types share an antioxidative response mediated by the Nrf2 signaling pathway, glutathione synthesis, and UCP2 upregulation. Notably, UCP2 facilitates the transfer of C4 metabolites, enhancing reductive TCA cycle metabolism. We also uncover that hypoxic responses are transient in beta cells post-stimulation but persistent in cancer cells. By synthesizing these insights, our research suggests novel therapeutic targets for T2DM, highlighting the shared metabolic strategies of stimulated beta cells and cancer cells. This comparative analysis not only illuminates the metabolic complexity of these conditions but also emphasizes the crucial role of metabolic pathways in cell function and survival, offering fresh perspectives for tackling T2DM and cancer challenges.

Most fungal species are commensals, not pathogenic for plants, humans, or animals. However, several species from genera Alternaria, Aspergillus, Trichophyton and Microsporum are common causes of disease, even for immunocompetent individuals, contributing to skin barrier impairment. A total of 68 allergic dogs were selected from a veterinary dermatology and allergy outpatient consultation, for conditions related to Malassezia overgrowth or other fungal complications. Allergy diagnosis was made through anamnestic and clinical criteria and allergy-implicated species were identified by intradermal testing (IDT) and serum determination of specific immunoglobulin E (sIgE). Dermatophagoides farinae, Dactylis glomerata and Malassezia pachydermatis showed as the higher sensitization species from each group. Significant correlations at p<0.05 were found between Dactylis glomerata and Phleum pratense grass pollens, Dermatophagoides farinae and Dermatophagoides pteronyssinus, Acarus siro, Tyrophagus putrescentiae and Lepidoglyphus destructor dust/storage mites, and between fungi like Aspergillus mix and Penicillium or Alternaria alternata. A significant correlation was also found between sensitization to Aspergillus mix and D. farinae, D. pteronyssinus or A. siro. Rather severe dermatitis was observed where positive IDT to Malassezia pachydermatis was found, regardless of the presence of circulating sIgE, allowing us to perceive the usefulness of both sIgE and IDT for allergy diagnosis to fungi.

The importance of statistics in biological research is inevitable. The appliance of statistics is the most powerful tool to support the scientific hypothesis and to give credibility to biological research methodology, to interpret convoluted explanations and conclusions based on the research findings. The evidences from literatures point the persistent statistical errors, selection of non-proper statistical test with the consequence of misinterpretation of the scientific results which are published in international journals. One of the most extensively used statistical tests in the field of biology (preclinical and clinical) is analysis of variance (ANOVA). ANOVA test is in place of multiple T-tests to compare the means of more than two groups at a time; and there are some important points which biologists should be aware of them to avoid possible misinterpretation of results with the consequence of wrong conclusion. Accordingly, the aim of the current review is to help biologists to understand the basic concepts of ANOVA test and reach to a more valid interpretation of achieved results.

Analysis of non-stationary and nonlinear sound signals obtained from dynamical processes is one of the greatest challenges in signal processing. Turning machine operation is a highly dynamic process persuaded by many events such as dynamical responses, chip formations and operational conditions of machining. Traditional and widely used fast Fourier transformation and spectrogram is not suitable for processing sound signals acquired from dynamical systems as its result have significant deficiencies because of stationary assumptions and having priori basis. The relatively new technique, Discrete Wavelet Transform, which uses Wavelet decomposition and the recently developed technique, Hilbert Huang Transform (HHT) which uses Empirical Mode Decomposition have notably better properties in the analysis of nonlinear and non-stationary sound signals. This paper presents a comparative study on the decomposition of multicomponent sound signals using Empirical Mode Decomposition and Wavelet Decomposition to highlight the suitability found in HHT to analyze tool-emitted sound signals received from turning processes. Apart from the short mathematical and theoretical foundations of the transformations, this paper demonstrates their decomposition strength using an experimental case study of tool flank wear monitoring in turning. It also concludes HHT is more suitable than DWT to analyze tool-emitted sound signals received from turning processes.

In this paper, we introduced a comprehensive study, based on both numerical and experimental analyses, of side polished (SP) single mode fibers (SMF) to investigate their evanescent field interaction with air and liquid analytes. In particular, the finite element method (FEM) and the beam propagation method (BPM) are employed to predict the optical properties of the SP-SMF. An ad-hoc experimental setup has been designed and built to characterize the side polished single mode fiber when air, water, and isopropanol are set in the side polished region. The sensitivity of the analytes is obtained as 1.207 V/RIU. The performance in terms of effective refractive index and transmittance are reported to show how these SP-SMF can be efficiently used for calculating the liquid refractive index. The simulation and experimental results display the significant performance of the SP-SMF as a sensing element.

In this paper, the fixed-time stabilization problem for a class of uncertain chained system is addressed by using a novel nonsingular recursive terminal sliding mode control approach. A fixed-time controller and an adaptive law are designed to guarantee the uncertain chained form system both Lyapunov stable and fixed-time convergent within the settling time. The advantage of the controller based on the sliding mode is that the settling time does not depend on the system initial state. Furthermore, we use RBF neural network to estimate the uncertainty of the system. Finally, the simulation results demonstrate the performance of the control laws.

We present the generation and nonlinear frequency conversion of nanosecond cylindrical vector beams (CVBs) in two-mode fiber (TMF). Based on the polarized dependence vector mode coupling characteristic and the precise wavelength tunability of an acoustically-induced fiber grating (AIFG), the nanosecond cylindrical vector beams (CVBs, 1064 nm, 10 ns) is directly generated in a TMF with convenient switching characteristics between the radial and azimuthal vector beams. Furthermore, the stimulated Raman scattering (SRS) is produced based on the transmission of the nanosecond CVBs in the 100-meters long TMF, and the spatial intensity and polarization distributions characteristics the 1st-order Stokes shifted component is consistent with the nanosecond CVBs pump pulse. This work provides a method for achieving wavelength conversion of the CVBs in optical fiber.

Common rust (CR), caused by Puccina sorghi, is one of the major foliar diseases in maize, leading to quality deterioration and yield losses. To dissect the genetic architecture of CR resistance in maize, this study utilized the susceptible temperate inbred line Ye107 as the male parent crossed with three resistant tropical maize inbred lines (CML312, D39, and Y32) to generate 627 F7 recombinant inbred lines (RILs), aiming to identify maize disease-resistant loci and candidate genes for common rust. Phenotypic data exhibited good segregation between resistance and susceptibility, with varying degrees of resistance observed across different subpopulations. Significant genotype effects and genotype × environment interactions were noted with heritability ranging from 85.7% to 92.2%. Linkage analysis and genome-wide association analysis across three environments identified 20 QTLs and 62 significant SNPs. Among them, seven major QTLs explained 66% of the phenotypic variance. Comparison with six SNPs repeatedly identified across different environments revealed overlap between qRUST3-3 and Snp-203,116,453, and Snp-204,202,469. Haplotype analysis indicated two significantly different haplotypes for CR resistance for both of these SNPs. Based on LD decay plots, three co-located candidate genes, namely Zm00001d043536, Zm00001d043566, and Zm00001d043569, were identified within 20 kb up-stream and downstream of these two SNPs. Zm00001d043536 regulates hormone regulation, Zm00001d043566 controls stomatal opening and closure, related to trichome, and Zm00001d043569 is associated with plant disease immune responses. Additionally, we performed candidate gene screening for five additional SNPs repeatedly detected across different environments, resulting in the identification of five candidate genes. These findings contribute to the development of genetic resources for common rust resistance in maize breeding programs.

Anthracnose, caused by the fungus Colletotrichum lindemuthianum, poses a significant and widespread threat to the common bean crop. The use of plant genetic resistance has proven to be the most effective strategy for managing anthracnose disease. The Amendoim Cavalo (AC) Andean cultivar has resistance against multiple races of C. lindemuthianum, which is conferred by the Co-AC gene. Fine mapping of this resistance gene to common bean chromosome Pv01 enabled the identification of Phvul.001G244300, Phvul.001G244400, and Phvul.001G244500 candidate genes for further validation. In this study, we assessed the relative expression of Co-AC candidate genes, as well as other putative genes in vicinity of this locus and known resistance genes, in the AC cultivar following inoculation with the race 73 of C. lindemuthianum. Gene expression analysis revealed significantly higher expression levels of Phvul.001G244500. Notably, Phvul.001G244500 encodes a putative Basic Helix-Loop-Helix transcription factor, suggesting its involvement in the regulation of defense responses. Furthermore, we observed a significant modulation of the expression of defense related genes PR1a, PR1b, and PR2, in a time-course experiment. These findings contribute to the development of improved strategies for breeding anthracnose-resistant common bean cultivars, thereby mitigating the impact of this pathogen on crop yields and ensuring sustainable bean production.

Electronic structure calculations have been carried out to examine the effect of protonation and water molecules on the heme group of peroxidases in different redox (ferric, ferrous, compounds I and II) and spin states. Shared geometries, spectroscopic properties at Soret region, and thermodynamics of peroxidases are discussed. B3LYP and M06-2X density functionals with different basis sets were employed on a common molecular model of the active site (Fe-centred porphine and proximal imidazole). Computed Gibbs free energies indicate that the corresponding aquo complexes are not thermodynamically stable, supporting the five-coordinate Fe(III) centre in native ferric peroxidases, with a water molecule located at a non-bonding distance. Protonation of the ferryl oxygen of compound II is discussed in terms of thermodynamics, Fe–O bond distances, and redox properties. It is demonstrated that this protonation is necessary to account for the experimental data and computed Gibbs free energies that reveal pKa values of compound II about 8.5 – 9.0. Computation suggests that the origin of the general oxidative properties of peroxidase species, as well as their reactivity towards water and protons and Soret spectral properties, mostly resides on the iron porphyrin and its proximal ligand histidine.

Pompeii was connected to the great Serino aqueduct under the principate of Augustus. From that moment on, water became not only a precious resource for the inhabitants but also their true social indicator. It is no coincidence, in fact, that the concentration of sumptuous dwellings is in Regio VI, the district closest to the aqueduct reservoir (castellum aquae in Latin) and the one most equipped with piezometric towers, the first of the network, the ones that would never leave the decorative fountains of the peristyles dry. From this observation follows the original possibility of considering the water network a factor that contributed to designating the morphology of urban neighbourhoods and blocks.

Nucleosome positioning plays an important role in crucial biological processes like replication, transcription, and gene regulation. It has been widely used to predict the genome’s function and chromatin organisation. So far, the studies of patterns in nucleosome positioning have been limited to transcription start sites, CTCFs binding sites, and some promoter and loci regions. The genome-wide organisational pattern remains unknown. We have developed a theoretical model to coarse-grain nucleosome positioning data in order to obtain patterns in their distribution. Using hierarchical clustering on the auto-correlation function of this coarse-grained nucleosome positioning data, a genome-wide clustering is obtained for Candida albicans. The clustering shows the existence beyond hetero- and eu-chromatin inside the chromosomes.

Over the course of the pandemic due to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), multiple new clinical manifestations, as the consequence of the tropism of the virus, have been recognized. That includes now the neurological manifestations and conditions, such as headache, encephalitis, as well as olfactory and taste disorders. We present a series of ten cases of RT-PCR confirmed SARS-CoV-2 infected patients diagnosed with viral-associated olfactory and taste loss from four different countries.

In the international scenario of agriculture, Brazil stands out as the main producer and consumer of common bean (Phaseolus vulgaris L.) The increase in the productive potential of the crop is mainly due to breeding programs. The objective of this study was to estimate genetic parameters, predict genotypic values with REML/BLUP (Restricted Maximum Likelihood/Best Linear Unbiased Prediction) and, based on these values, study the variability in common bean cultivars with carioca and black grain. Twenty three agromorphological descriptors were evaluated, among them grain yield. Deviance analysis detected significant differences between the cultivars in both groups. Selective accuracy (Ac) was considered high for most of the traits. Broad-sense heritability (h_g² ) ranged from 0.05 to 0.72, but it was low for the trait yield (YLD). In the carioca grain group, the h_g² values for the traits related to plant morphology were higher than in the black group. Nevertheless, the h_g² values in the black group were higher in relation to the pod and seed traits. The correlations for YLD were moderate but different in the two commercial groups studied. In the black group, variables related to the seed morphology were correlated with grain yield, and in the carioca group, traits related to seed quantity. Based on the groupings, variability among the cultivars was observed. Three distinct clusters were formed for the carioca group and four for the black group. Based on the predicted genetic values, genetic variability and the most adapted and stable cultivars were detected among the cultivars in the studied environments.

Objectives: Isolated mild neutropenia is a common clinical problem. The current study aims to validate our previous findings regarding the high prevalence of isolated neutropenia in Southern and Southwestern Saudi Arabia and explore the effect of altitude or regional differences. Methods: In this retrospective cross-sectional study, laboratory results of a commercial laboratory were screened over a period of 5 years (2016–2020) in seven different cities in South and southwestern Saudi Arabia. Participants’ laboratory investigations were reviewed and excluded for any ab-normal complete blood count, renal profile, liver profile, lipid profile, thyroid function test, fasting blood glucose, or HbA1c findings. Descriptive analysis and 95th percentile range were calculated using standard statistical methods. Results: A total of 91,880 complete blood count results were included in the final analysis. isolated neutropenia is common laboratory finding, with a prevalence ranging from 11-23%. The 2.5th percentile of the neutrophil count was lower than 1.5×109/L in all seven cities. Conclusions: Mild to moderate neutropenia is common in Southern and Southwestern Saudi Arabia. Benign ethnic neutropenia (BEN) may explain this high prevalence. Since BEN has no clinical significance, the reference range for normal neutrophil counts needs to be adjusted to reflect the effect of BEN.

Current prenatal genetic evaluation showed a significantly increase in non-invasive screening and the reduction of invasive diagnostic procedures. To evaluate the diagnostic efficacy on detecting common aneuploidies, structural chromosomal rearrangements and pathogenic copy number variants (pCNV), we performed a retrospective analysis on a case series initially analyzed by aneuvysion fluorescence in situ hybridization (FISH) and karyotyping then followed by array comparative genomic hybridization (aCGH). Of the 386 cases retrieved from the past decade, common aneuploidies were detected in 137 cases (35.5%), other chromosomal structural rearrangements were detected in four cases (1%), and pCNV were detected in five cases (1.3%). The relative frequencies for common aneuploidies suggested a under detection of sex chromosome aneuploidies. Approximately 9.5% of cases with common aneuploidies showed a mosaic pattern. Inconsistent results between FISH and karyotyping were noted in cases with pseudo-mosaicism introduced by culture artifact or variable cellular proliferation from cells with mosaic karyotypic complements under in vitro cell culture. Based on findings from this case series, cell-based FISH and karyotyping should be performed to detect common aneuploidies, structural chromosomal abnormalities, and mosaic pattern. DNA-based aCGH and reflex FISH should be performed to detect and confirm genomic imbalances and pCNV. Practice points to ensure the diagnostic accuracy and efficacy were summarized.

Since decades, oxybutynin hydrochloride is prescribed to improve bladder control in cases of incontinence and excessive urination frequency. This review summarizes synthetic methods enabling preparation of the racemic drug and, in a detailed manner, preparation of (S)-2-cyclohexyl-2-hydroxy-2-phenylacetic acid, a key intermediate in the synthesis of (S)-oxybutynin. Mode of action and metabolism are briefly commented in order to explain the main adverse effects associated with its use and to justify the evolution observed in the diverse commercial formulations. Repositioning opportunities are discussed in terms of clinical trials for the management of hyperhidrosis, hot flashes, and obstructive sleep apnea.

The robust control of high precision electromechanical systems, such as micropositioners, is challenging in terms of the inherent high nonlinearity, the sensitivity to external interference, and the complexity of accurate identification of the model parameters. To cope with these problems, this work investigates a disturbance observer-based deep reinforcement learning control strategy to realize high robustness and precise tracking performance. Reinforcement learning has shown great potential as optimal control scheme, however, its application in micropositioning systems is still rare. Therefore, embedded with the integral differential compensator (ID), deep deterministic policy gradient (DDPG) is utilized in this work with the ability to not only decrease the state error but also improves the transient response speed. In addition, an adaptive sliding mode disturbance observer (ASMDO) is proposed to further eliminate the collective effect caused by the lumped disturbances. The sterling performance is revealed with intensive tracking simulation experiments and demonstrates the improvement in the accuracy and response time of the controller.

This paper presents three types of sliding mode controllers for a magnetic levitation system. First, a proportional-integral sliding mode controller (PI-SMC) is designed using a new switching surface and a proportional plus power rate reaching law. The PI-SMC is more robust than a feedback linearization controller in the presence of mismatched uncertainties and outperforms the SMC schemes reported recently in the literature in terms of the convergence rate and settling time. Next, to reduce the chattering phenomenon in the PI-SMC, a state feedback-based discrete-time SMC algorithm is developed. However, the disturbance rejection ability is compromised to some extent. Furthermore, to improve the robustness without compromising the chattering reduction benefits of the discrete-time SMC, mismatched uncertainties like sensor noise and track input disturbance are incorporated in a robust discrete-time SMC design using multirate output feedback (MROF). With this technique, it is possible to realize the effect of a full-state feedback controller without incurring the complexity of a dynamic controller or an additional discrete-time observer. Also, the MROF-based discrete-time SMC strategy can stabilize the magnetic levitation system with excellent dynamic and steady-state performance with superior robustness in the presence of mismatched uncertainties. The stability of the closed-loop system under the proposed controllers is proved by using the Lyapunov stability theory. The simulation results and analytical comparisons demonstrate the effectiveness and robustness of the proposed control schemes.

This paper proposed a damping method for enhancing oscillatory stability performance of power systems with high penetration of renewable energy by a resilient wide-area multi-mode controller. The resilient wide-area multi-mode controller is used as an additional controller in a renewable energy system with a battery energy storage to enhance the damping of the critically weak modes. The weak modes are likely to be triggered in the event of line outages or any other disturbances, and the system may become unstable in the absence of proper corrective and preventive control. A firefly algorithm has been employed to design such a controller. Eigenvalue analysis and time-domain simulation are used to analyze the performance of the proposed controller in a realistic representative power system. From the simulation results, it is evident that the oscillatory stability performance of the renewable rich power system can be enhanced with the proposed control to keep the damping on critical modes to the industrial standards. Furthermore, renewable energy penetration can be increased significantly in the realistic representative system by introducing the proposed controller without disturbing the oscillatory stability margin.

Diesel engines, as power equipment, are widely used in the fields of automobile industry, ship and power equipment. Due to wear or faulty adjustment, the valve train clearance abnormal fault is a typical failure of diesel engines, which may result in the performance degradation, even valve fracture and cylinder hit fault. However, the failure mechanism features mainly in time domain and angular domain, on which the current diagnosis methods based, are easily affected by working conditions or hard to extract accurate enough, as the diesel engine keeps running in transient and non-stationary process. This work arms at diagnosing this fault mainly based on frequency band features which would change when the valve clearance fault occurs. For the purpose of extracting a series of frequency band features adaptively，a decomposition technique based on improved variational mode decomposition is investigated in this work. As the connection between the features and the fault is fuzzy, the random forest algorithm is used to analyze the correspondence between features and faults. In addition, the feature dimension is reduced to improve the operation efficiency according to importance score. The experimental results under variable speed condition show that the method based on variational mode decomposition and random forest is capable to detect valve clearance fault effectively.

The objective of this paper is to research the impact of electrical and physical parameters that characterize the complementary MOSFET transistors (NMOS and PMOS transistors) in the CMOS inverter for static mode of operation. In addition to this, the paper also aims at exploring the directives that are to be followed during the design phase of the CMOS inverters that enable designers to design the CMOS inverters with the best possible performance, depending on operation conditions. The CMOS inverter designed with the best possible features also enables the designing of the CMOS logic circuits with the best possible performance, according to the operation conditions and designers’ requirements.

Abstract：The brain often switches freely between focused attention and divergent thinking, and the default mode network (DMN) is activated during brain rest. The discovery, function and characteristics of default mode network all indicate that learning does not stop when the brain "rests". Mental disease can lead to dysfunctional default mode networks, which affects learning adversely. Therefore, default mode network plays an important role in learning. Neural activities such as β-wave rhythm regulation, "subconscious" divergence mode initiation, hippocampal function and neural replay occur during default mode, which also explain that "rest" promotes learning. This paper reveals the role and neural mechanism of default mode network in learning from the neural level, discusses the essential role default mode network plays in learning, and default mode network enables rest to promote learning.

Magnetorheological (MR) fluids have been known to react to magnetic fields of sufficient magnitudes. While in the presence of the field the material develops a yield stress. The tunable property has made it attractive in e.g. semi-active damper applications in vibration control domain in particular. Within the context of a given application the fluids can be exploited in at least one of the fundamental operating modes of which the so-called gradient pinch mode has been least explored. Contrary to the other operating modes, the MR fluid volume in the flow channel is exposed to a non-uniform magnetic field in such a way that the Venturi-like contraction is developed in a flow channel solely by means of a solidified material in the regions near the walls rather than mechanically driven changes of the channel’s geometry. The pinch mode rheology of the material has made it a potential candidate in developing on a new category of MR valves. By convention, a pinch mode valve features a single flow channel with poles over which non-uniform magnetic field is induced. In this study the authors examine ways of extending the dynamic range of pinch mode valves by employing a number of such arrangements (stages) in series. To accomplish this, the authors developed a prototype of a multi-stage (three-stage) valve, and then compared its performance against that of a single-stage valve across a wide range of hydraulic and magnetic stimuli. To summarize, improvements in the pinch mode valve dynamic range are evident, however, at the same time it is hampered by the presence of serial air gaps in the flow channel.

In this paper, we exhibit new dynamical properties of the two-mode Caudrey-Dodd-Gibbon (TMCDG) equation. This model describes the motion of dual-waves in dispersive and nonlinear media, which mainly depends on the nonlinearity and dispersion parameters. The overlapping of such two-mode waves is affected by the phase-velocity parameter. The study takes a full advantages of the Kudryashov method and of the exponential-expansion method. For the first time, dual-wave solutions are obtained for arbitrary values of the nonlinearity and dispersive factors. The graphs of the novel solutions are also provided in order to depict the waves propagation, as well as to show the influence of the parameters.

This paper discusses approaches to the numerical integration of the coupled nonlinear Schrödinger equations system in case of few-mode wave propagation. The wave propagation assumes the propagation of up to nine modes of light in an optical fiber. In this case, the light propagation is described by the non-linear coupled Schrödinger equation system, where propagation of each mode is described by own Schrödinger equation with other modes interactions. In this case, the non-linear coupled Schrödinger equation system solving becomes increasingly complex, because each mode affects the propagation of other modes. The suggested solution is based on the direct numerical integration approach, which is based on a finite-difference integration scheme. The well-known explicit finite-difference integration scheme approach fails, due to the non-stability of the computing scheme. Due to this fact, the combined explicit/implicit finite-difference integration scheme, based on the implicit Crank–Nicolson finite-difference scheme, is used. It allows ensuring the stability of the computing scheme. Moreover, this approach allows separating the whole equation system on the independent equation system for each wave mode at each integration step. Additionally, the algorithm of numerical solution refining at each step and the integration method with automatic integration step selection are used. The suggested approach has performance gains (or resolutions) up to three or more orders of magnitude in comparison with the split-step Fourier method due to the fact that there is no need to produce direct and inverse Fourier transforms at each integration step. The main advantage of the proposed method is the ability to calculate the propagation of an arbitrary number of modes in the fiber.