Most existing cancer therapies negatively affect normal tissue as well as cancerous tissue. A potentially effective strategy for treating cancer that precludes off-target damage and could be an option for most patients would involve targeting one or more mutations that are ubiquitous in the given patient’s tumor(s). To effect this strategy, one would employ multi-region sequencing of a patient’s primary tumor and metastases to seek out mutations that are shared between all or at least most regions. Once the target or targets are known, one would ideally rapidly generate a molecular switch for at least one of said ubiquitous mutations that can distinguish the mutated DNA, RNA, or protein from the wild-type version and subsequently trigger a therapeutic response. I propose that the therapeutic response involve the replication of an oncolytic virus or intracellular bacterium, as any mutation can theoretically be detected by a vector that enters the cell - and automatic propagation could be very helpful. Moreover, the mutation “signal” can be easily enhanced through transcriptional and translational (if the target is an intracellular protein) enhancement. Importantly, RNA may make the best target for the molecular switches in terms of amplification of the signal and ease of targeting.

Abstract Successful treatment against infectious agents depends on rapid and accurate detection of the causative organisms. Misdiagnosis can hamper such success while leading to improper advising of antibiotics. In Bangladesh, the majority of the diagnostic centers detect and identify pathogens through culture and biochemical test-based methods and suggest antibiotics based solely on the results of disk-diffusion methods. This pilot study tried to validate the identity of the isolates characterized by diagnostic facilities near Dhaka. One hundred and twenty pre-characterized clinical isolates were analyzed biochemically and genotypically. Random Amplification of Polymorphic DNA-PCR, rcsA, and phoA genes-based PCR, and Loop-Mediated Isothermal Amplification (LAMP)-based identification of Klebsiella pneumoniae and Escherichia coli, respectively, followed by 16S rRNA sequencing confirmed misidentification of some clinical pathogens of other genera as Klebsiella spp. and E. coli. According to the antibiotic susceptibility testing guidelines, antibiotic choice, sensitivity pattern, and breakpoint measurement are different for each group of organisms. The lack of adherence to proper standards results in misdiagnosis and may facilitate the development of antibiotic resistance. The pilot study observers misidentification of clinical pathogens identified by the diagnostic centers. Well-characterized rapid molecular techniques like LAMP are suggested in clinical diagnosis to avoid misdiagnosis and subsequently circumvent antibiotic resistance development.

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.

Background: The gut microbiome plays a major role in chronic diseases, of which several are characterized by an altered composition and diversity of bacterial communities. Large-scale sequencing projects allowed characterizing the perturbations of these communities. However, translating these discoveries into clinical applications remains a challenges. To facilitate routine implementation of microbiome profiling in clinical settings, portable, real-time, and low-cost sequencing technologies are needed. Results: Here, we propose a computational and experimental protocol for whole genome quantitative metagenomics studies of human gut microbiome with Oxford Nanopore sequencing technology (ONT) that could be applied to other microbial ecosystems. We developed a bioinformatic protocol to analyse ONT sequences taxonomically and functionally and optimized pre-analytic protocols including stool collection and DNA extraction methods to maximize read length. This is a critical parameter for the sequence alignment and classification. Our protocol was evaluated using simulations of metagenomic communities which reflect naturally occuring compositional variations. Next, we validated both protocols using stool samples from a bariatric surgery cohort, sequenced with ONT, Illumina and SOLiD technologies. Results revealed similar diversity and microbial composition profiles. Conclusion: This protocol can be implemented in the clinical or research setting, bringing rapid personalized whole genome profiling of target microbiome species.

The holistic approach of One Health, which sees human, animal, plant, and environmental health as a unit, rather than discrete parts, requires not only interdisciplinary cooperation, but standardized methods for communicating and archiving data, enabling participants to easily share what they have learned and allow others to build upon their findings.Ongoing work by NCBI and the GenomeTrakr project illustrates how open data platforms can help meet the needs of federal and state regulators, public health laboratories, departments of agriculture, and universities. Here we describe how microbial pathogen surveillance can be transformed by having an open access database along with Best Practices for contributors to follow. First, we describe the open pathogen surveillance framework, hosted on the NCBI platform. We cover the current community standards for WGS quality, provide an SOP for assessing your own sequence quality and recommend QC thresholds for all submitters to follow. We then provide an overview of NCBI data submission along with step by step details. And finally, we provide curation guidance and an SOP for keeping your public data current within the database. These Best Practices can be models for other open data projects, thereby advancing the One Health goals of Findable, Accessible, Interoperable and Re-usable (FAIR) data.

The transition to reproduction is a crucial step in the life cycle of any organism. In Arabidopsis thaliana the establishment of reproductive growth can be divided into two phases: Firstly, cauline leaves with axillary meristems are formed and internode elongation begins. Secondly, lateral meristems develop into flowers with defined organs. Floral shoots are usually determinate and suppress the development of lateral shoots. Here, we describe a transposon insertion mutant in the Nossen accession with defects in floral development and growth. Most strikingly is the outgrowth of stems from the axillary bracts of the primary flower carrying secondary flowers. Therefore, we named this mutant flower-in-flower (fif). However, the transposon insertion in the annotated gene is not the cause for the fif phenotype. By means of classical and genome sequencing-based mapping, the mutation responsible for the fif phenotype was found to be in the LEAFY gene. The mutation, a G-to-A exchange in the second exon of LEAFY, creates a novel lfy allele and results in a cysteine-to-tyrosine exchange in the α1-helix of LEAFY´s DNA-binding domain. This exchange abolishes target DNA-binding, whereas subcellular localization and homomerization are not affected. To explain the strong fif phenotype against this molecular findings, several hypotheses are discussed.

This study investigates job satisfaction, burnout, and well-being among first-generation migrant physicians in anesthesia and intensive care medicine in Germany, comparing them to their native German counterparts. Utilizing a cross-sectional survey design, the study collected data from 513 physicians, 110 of whom identified as having a migration background. Job satisfaction was measured using the German version of the Warr-Cook-Wall (WCW) Job Satisfaction Scale, burnout was assessed with the Copenhagen Burnout Inventory (CBI), and well-being was evaluated using the WHO-5 Well-Being Index. The job satisfaction ratings revealed no significant differences between migrant and German physicians in most dimensions, including physical workload, freedom to choose work methods, satisfaction with colleagues, responsibility, income, skill utilization, and variety in work tasks. However, migrant physicians reported significantly higher satisfaction with recognition received for their work and lower dissatisfaction with working hours. Burnout assessments showed that migrant physicians experienced higher psychological strain, perceiving every work hour as more exhausting and having significantly less energy for family and friends. Notably, migrant physicians reported higher difficulty and frustration in working with patients. Well-being ratings indicated that migrant physicians felt less energetic and active but found their daily life more filled with interesting activities. The findings underscore the unique challenges faced by migrant physicians, particularly in terms of recognition and patient-related burnout. These results highlight the need for targeted interventions to support migrant physicians, including cultural competence training and flexible working hours to enhance their job satisfaction and overall well-being. Addressing these issues is crucial for maintaining the quality of patient care and the occupational health of migrant physicians in Germany.

This paper addresses the mixed convective flow and heat transfer in combustible third grade fluid through a slant channel that is filled with a permeable materials. The fluid layer in contact with the lower plate is exposed to convective heating with the ambient while at the upper plate, a constant heat flux is experienced. We employ the spectral quasilinearisation method (SQLM) to the coupled nonlinear flow governing equations. Fluid velocity and temperature profiles, local entropy generation and irreversibility ratio are computed and analysed quantitatively and qualitatively. A residual error analysis demonstrated high accuracy and convergence of the numerical method. The results on flow and thermal effects, entropy generation rate and Bejan number revealed fascinating manifestations that have profound implications in design of thermo-mechanical systems. In particular, the results of the thermal analysis are pertinent to optimal designs of systems that achieve efficient energy utilization.

This paper designed a new type of generator, transgenerator, that integrates the wind turbine and flywheel into one system, aiming to make the flywheel distributed energy storage (FDES) more modular and scalable than the conventional FDES. The transgenerator is a three-member dual-mechanical-port (DMP) machine with two rotating members (inner and outer rotors) and one stationary member (stator). The transgenerator-flywheel system is introduced with the system configuration, transgenerator overview, flywheel operation principle and power management strategies, and control system. Simulations are performed in MATLAB/ Simulink to verify the system viability, including control system verification and the flywheel storage performance evaluation. Results show that the inner and outer rotors can be controlled independently with accurate and fast control response, and the grid-side control works properly. The flywheel performs well with considerable charging power and storage capacity.

Many advanced technologies have been employed in the high performance active matrix displays including liquid crystal displays, organic light emitting diode displays, and micro light emitting diode displays. On the other side, there have existed the strong demand on the cost reduction and it is one of low cost schemes to integrate the driver circuit in a panel based on thin film transistor technologies. This paper reviews overall concept, operation principles, and various circuit approaches in shift registers for the scanning pulse generation. In addition, it deals with the implementation of additional functionalities in gate drivers to support pixel compensation, multi-line driving, in-cell capacitive touch screen, pixel sensing, and adaptive scanning region control.

Background: Study to assess glucose levels of people with type 1 diabetes (T1D) overnight based on insulin type and timing. Methods: Real-world, retrospective study in T1D using multiple daily insulin injections. Contin-uous glucose monitoring and insulin injections data were collected for ten hours after dinner us-ing the Insulclock® connected cap. Meal events were identified using ROC detection methodology. The timing of rapid insulin, second injections, and the type of insulin analogs used were evaluat-ed. Results: Nocturnal profiles (n=775, 49 subjects) were analyzed. Higher glucose AUC over 180mg/dL was observed in delayed injections (number; %; mg/dL x h): -45-15min (n=136; 17.5%, 175.9 ±271.0); -15-0min (n= 231; 29.8%, 164.0 ±237.1); 0+45min (n= 408; 52.6%, 203.6 ±260.9), (p 0.049). The use of ultrarapid (FiAsp®) (URI) vs rapid insulin analogs (RI) was associated with less hypoglycemia events (7.1 vs 13.6%; p 0.005) and TBR70 (1.7 +6.9 vs 4.6 +13.9%; p 0.003). Us-ers of glargine U300 vs degludec had higher TIR (70.7 vs 58.5 %) (Adjusted R-squared: 0.22, p < 0.001). The use of a correction injection (n= 144, 18.6%) was associated with higher hypoglycemia events (18.1 vs 9.5%; p 0.003), TBR70 (5.5 +14.2 vs 3.0 +11.1%; p 0.003), glucose AUC over 180 mg/dL (226.1 +257.8 vs 178.0 +255.3 mg/dL x h; p 0.001), and lower TIR (56.0 +27.4 vs 62.7 +29.6 mg/dL x h; p 0.004). Conclusions: Dinner rapid insulin timing, insulin types and correction injections affect nocturnal glucose profile in T1D.

Cancer cells show altered antioxidant defense systems, dysregulated redox signaling, and increased generation of reactive oxygen species (ROS). Targeting cancer cells through ROS-mediated mechanisms has emerged as a significant therapeutic strategy due to its implications in cancer progression, survival, and resistance. Extensive research has focused on selective generation of H2O2 in cancer cells for selective cancer cell killing by employing various strategies such as metal-based prodrugs, photodynamic therapy, enzyme-based systems, nano-particle mediated approaches, chemical modulators, and combination therapies. Many of these H2O2-amplifying approaches have demonstrated promising anticancer effects and selectivity in preclinical investigations. They selectively induce cytotoxicity in cancer cells while sparing normal cells, sensitize resistant cells, and modulate the tumor microenvironment. However, challenges remain in achieving selectivity, addressing tumor heterogeneity, ensuring efficient delivery, and managing safety and toxicity. To address those issues, H2O2-generating agents have been combined with other treatments leading to optimized combination therapies. This review focuses on various chemical agents/approaches that kill cancer cells via H2O2-mediated mechanisms. Different categories of compounds that selectively generate H2O2 in cancer cells are summarized, their underlying mechanisms and function are elucidated, preclinical and clinical studies as well as recent advancements are discussed, and their prospects as targeted therapeutic agents and their therapeutic utility in combination with other treatments are explored. By understanding the potential of these compounds, researchers can pave the way for the development of effective and personalized cancer treatments.

This research explores the behaviors of Generation Z consumers in China, particularly focusing on their interaction with companies through social media for the joint creation of value. Adopting a qualitative methodology, the research initially constructs a scale for assessing co-creation of value on social media platforms. Subsequently, it delves into the motivational aspects of users' engagement in these co-creative activities. The study unveils a range of utilitarian and hedonic motivations that drive Generation Z's value co-creation actions on social media. Insights derived from the findings offer both theoretical and practical implications for the field.

Since the creation of the first parallel electrical power systems around the world, the rotor angle stability of synchronously operating generators has been one of the most crucial and challenging problems. In modern electricity networks, involving Kazakhstani, where the renewable energy technologies are rapidly penetrating, and the issue of stability takes on even greater importance due to the technical shortcomings of inverter-based generation. In this framework, an analysis of rotor angle transient stability was carried out when replacing existing synchronous generators with doubly fed induction generators under a certain pre-emergency mode. A critical proportion of active power generation by DFIG units was identified at which transient stability can still be maintained due to the sufficient stored kinetic energy of the synchronous machines remaining in operation. In addition, 2 simple solutions were investigated to improve transient stability, such as an increased time of the automatic reclosure operation and the use of special load shedding automation. For the analysis, a real power system of Mangystau region in Kazakhstan was considered, and the PowerWorld software was used.

Swarf of aluminum alloy with high corrosion resistance and ductility was successfully converted into fine hydroreactive powders via its ball milling with silver powder and either lithium chloride or gallium. The later substances significantly intensified particle size reduction, while silver formed ‘cathodic’ sites (Ag, Ag2Al) promoting Al corrosion in aqueous saline solutions with hydrogen generation. The diffraction patterns, microphotographs, and elemental analysis results demonstrated partial aluminum oxidation in the samples and their contamination with tungsten carbide from milling balls. Those effects were responsible for obtaining hydrogen yields lower than expected. For AlCl3 solution at 60 °C, Al–LiCl–Ag, Al–LiCl, Al–Ga–Ag, and Al–Ga composites delivered (84.6±0.2), (86.8±1.4), (80.2±0.5), and (76.7±0.7)% of the expected hydrogen respectively. Modification with Ag promoted Al oxidation thus providing higher hydrogen evolution rates. The samples with Ag were tested in CaCl2 solution as well, for which the reaction proceeded much slower. At a higher temperature (80 °C) after 3 h of experiment, the hydrogen yields for Al–LiCl–Ag and Al–Ga–Ag powders were (46.7±2.1) and (31.8±1.9)%. The tested Ag-modified composite powders were considered promising for hydrogen generation and had a potential for further improvement to provide higher performance.

This comprehensive review explores the principles, applications, and future directions of human-powered energy generation technologies. It begins by providing a detailed examination of viable human energy sources, elucidating the physical principles behind various energy harvesting devices. The review then compiles and assesses existing products in the field of human power generation, while also outlining the opportunities and challenges it presents. Finally, an innovative concept of an eco-village system is introduced to demonstrate a future potential application scenario for human-generated electricity. It outlines two developmental stages for this system and underscores its significance in the construction of the harmonious and sustainable communities. This forward-thinking approach could pave the way for broader discussions on sustainable living and eco-friendly energy generation in a world increasingly focused on environmental concerns and social stability.

To realize fast and effective synthetic aperture radar (SAR) deception jamming, a high-quality SAR deception jamming template library can be generated by performing sample augmentation on SAR deception jamming templates. However, current sample augmentation schemes of SAR deception jamming templates face certain problems. First, the authenticity of templates is low due to the lack of speckle noise. Second, the generated templates have low similarity to the target and shadow areas of the input templates. To solve these problems, this study proposes a sample augmentation scheme based on generative adversarial networks, which can generate a high-quality library of SAR deception jamming templates with shadows. The proposed scheme solves the two aforementioned problems from the following aspects. First, the influence of the speckle noise is considered in the network to avoid the problem of reduced authenticity in generated images. Second, a channel attention mechanism module is used to improve the network's learning ability of shadow features, which improves the similarity between the generated template and the shadow area in the input template. Finally, the proposed scheme and the SinGAN scheme are compared regarding the equivalent numbers of looks and the structural similarity between the target and shadow in the sample augmentation results. The comparison results demonstrate that, compared to the templates generated by the SinGAN scheme, those generated by the proposed scheme have targets and shadow features similar to those of the original image, and can incorporate speckle noise characteristics, resulting in higher authenticity, which helps to achieve fast and effective SAR deception jamming.

Here we report a new synthetic protocol based on Microwave- Assisted Synthesis (MAS) for the preparation in higher yields of zinc and copper MOFs based on different bis(pyrazolyl)-tagged ligands ([M(BPZ)]n where M = Zn(II), Cu(II), H2BPZ = 4,4′-bipyrazole, [M(BPZ-NH2)]n where M = Zn(II), Cu(II); H2BPZ-NH2 = 3-amino-4,4’-bipyrazole, and [Mx(Me4BPZPh)] where M = Zn(II), x = 1; Cu(II), x = 2; H2Me4BPZPh = bis-4′-(3′,5′-dimethyl)- pyrazolylbenzene) and a detailed study of their antibacterial activity, tested against Gram-negative (E. coli) and Gram-positive (S. aureus) bacteria, as representative agents of infections. The results show that all MOFs exert a broad-spectrum activity and strong efficiency in bacterial growth inhibition, with a mechanism of action based on surface contact of MOFs particles with bacterial cells through the so-called “chelation effect” and reactive oxygen species (ROS) generation, without a significant release of Zn(II) and Cu(II) ions. In addition, morphological changes were elucidated by using scanning electron microscope (SEM) and bacterial cell damage was further confirmed by confocal laser scanning microscopy (CLSM) test.

The objective of this study is to clarify the effect of restoring the lowered masticatory muscle functional pressure and correcting the imbalance of bilateral masticatory muscle functional pressure on jawbone growth during growth and development with quantitative evaluation of the changes in micro/nanostructural characteristics of entheses. Male Wistar rats aged 4 weeks were divided into an experimental group injected with a botulinum toxin serotype A (BoNT/A) formulation to reduce muscle function (BTX group) and a control group (CTRL group). They were euthanized after 6, 8, 10, 12, and 16 weeks after measuring the difference between the midline of the upper and lower incisors. The mandibles were harvested for histological examination, second harmonic generation imaging, and quantitative evaluation of biological apatite (BAp) crystal alignment. The midline difference decreased with age in weeks. In rats from 6 weeks after BoNT/A administration to 12 weeks after administration, collagen fibre bundle diameter was significantly smaller in the BTX group; the difference between the two groups decreased with increasing age. BAp crystal alignment was significantly different on the X-axis and the Y-axis on the BTX group from 6 weeks after BoNT/A administration to 10 weeks after administration. Asymmetry of mandibular bone formation caused by load imbalance during growth could be corrected by adjustment of the function of the masseter muscle on either side.

Activated platelets are involved in blood coagulation by exposing phosphatidylserine (PS), which serves as a substrate for assembling coagulation complexes. Platelets accelerate fibrin formation and thrombin generation, two final reactions of the coagulation cascade. We investigated the effects of antiplatelet drugs on platelet impact in these reactions and platelet ability to expose PS. Washed human platelets were incubated with acetylsalicylic acid (ASA), ticagrelor, ASA in combination with ticagrelor, ruciromab (glycoprotein IIb-IIIa antagonist) or prostaglandin E1 (PGE1). Platelets were not activated or activated by collagen, sedimented in multiwell plates and plasma was added after supernatant removal. Fibrin formation (clotting) was monitored in a recalcification assay by light absorbance and thrombin generation in a fluorogenic test. PS exposure was assessed by annexin V staining using flow cytometry. Ticagrelor (alone and in combination with ASA), ruciromab and PGE1, but not ASA prolonged the lag phase and decreased the maximum rate of plasma clotting, and decreased the peak and maximum rate of thrombin generation. Inhibition was observed when platelets were not treated with exogenous agonists (activation by endogenous thrombin) and pretreated with collagen. Ticagrelor (alone and in combination with ASA), ruciromab and PGE1, but not ASA decreased PS exposure on washed platelets activated by thrombin and by thrombin + collagen. PS exposure on activated platelets in whole blood was lower in patients with acute coronary syndrome receiving ticagrelor + ASA in comparison with donors free of medications. These results indicate that antiplatelet drugs are able to suppress platelet coagulation activity not only in vitro but also after administration to patients.

Novel TFN membranes were examined for the removal of heavy metals (Cu and Pb) from synthetic wastewater in forward osmosis (FO) experiments using MgCl2 as a draw solute. The TFN membranes were fabricated on top of a commercial PS35 ultrafiltration membrane by in-situ interfacial polymerization of piperazine (PIP) and 1,3,5-benzenetricarbonyl trichloride (TMC) containing different amounts of dispersed functionalized halloysite nanotubes (HNTs) nanoparticles. The HNTs nanoparticles were functionalized with the first generation of poly(amidoamine) (PAMAM) dendrimers. The TFN and the control TFC membranes showed rejections of Cu2+ and Pb2+, ranging from 94.5% to 98.1%. The presence of heavy metal in the feed solution enhanced the FO performance of all membranes. In particular, the reverse flux of MgCl2 decreased at least 2.5 times compared to the experiments with pure water as a feed. Simultaneously, the water flux also increased. The improved FO performance of the membranes in the presence of heavy metal ions is attributed to their adsorption by the membranes. The adsorption of heavy metals was confirmed by a decrease in the negativity of zeta potential and the results from inductively coupled plasma mass spectrometry (ICP-MS) of the membranes after the FO experiments.

The proliferation of devices for the Internet of Things (IoT) and their implication in many activities of our lives have led to a considerable increase in concern about the security of these devices, posing a double challenge for designers and developers of products. On the one hand, the design of new security primitives, suitable for resource-limited devices, that can facilitate the inclusion of mechanisms and protocols to ensure the integrity and privacy of the data exchanged over the Internet. On the other hand, the development of techniques and tools to evaluate the quality of the proposed solutions as a step prior to their deployment, as well as to monitor their behavior once in operation against possible changes in operating conditions arising naturally or as a consequence of a stress situation forced by an attacker. To address these challenges, this paper first describes the design of a security primitive that plays an important role as a component of a hardware-based root of trust, as it can act as a source of entropy for true random number generation (TRNG) or as a physical unclonable function (PUF) to facilitate the generation of identifiers linked to the device on which it is implemented. The work also illustrates different software components that allow carrying out a self-assessment strategy to characterize and validate the performance of this primitive in its dual functionality, as well as to monitor possible changes in security levels that may occur during operation as a result of device aging and variations in power supply or operating temperature. The designed PUF/TRNG is provided as a configurable IP module, which takes advantage of the internal architecture of the Xilinx Series-7 and Zynq-7000 programmable devices and incorporates an AXI4-based standard interface to facilitate its interaction with soft- and hard-core processing systems. Several test systems that contain different instances of the IP have been implemented and subjected to an exhaustive set of on-line tests to obtain the metrics that determine its quality in terms of uniqueness, reliability, and entropy characteristics. The results obtained prove that the proposed module is a suitable candidate for various security applications. As an example, an implementation that uses less than 5% of the resources of a low-cost programmable device is capable of obfuscating and recovering 512-bit cryptographic keys with virtually zero error rate.

Machine Learning (ML) methods have become important to enhance the performance of decision-support predictive models. However, class imbalance is one of the main challenges for developing ML models, because it limits the generalization of these models, and biases the learning algorithms. In this paper, we consider oversampling methods for generating synthetic categorical clinical data aiming to improve the predictive performance in ML models, and the identification of risk factors for cardiovascular diseases (CVDs). We performed a comparative study of several categorical synthetic data generation methods, including Generative Adversarial Networks (GANs). Then, we assessed the impact of combining oversampling strategies and linear and nonlinear supervised ML methods. Lastly, we conducted a post-hoc model interpretability based on the importance of the risk factors. Experimental results show the potential of GAN-based models for generating high-quality categorical synthetic data, yielding probability mass functions that are highly close to real data, maintaining relevant insights, and contributing to increase the predictive performance. The GAN-based model and a linear classifier outperforms other oversampling techniques, improving 2\% the area under the curve. These results demonstrate the capability of synthetic data to help both in determining risk factors and building models for CVD prediction.

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.

The age of information (AoI) metric was proposed to measure the freshness of messages obtained at the terminal node of a status updating system. In this paper, the AoI of discrete time status updating system with probabilistic packet preemption is investigated by analyzing the steady state of a three-dimensional discrete stochastic process. Assuming the queue used in system is Ber/Geo/1/2*/η, which represents that the system size is 2 and the packet in buffer can be preempted by fresher packet with probability η. Instead of considering system’s AoI separately, we use a three-dimensional state vector (n,m,l) to simultaneously track the real time changes of the AoI, the age of packet in server, and the age of packet waiting in buffer. We give the explicit expression of system’s average AoI, and show that the average AoI of system without packet preemption is obtained by letting η=0. When η is set to 1, the mean of AoI of system having Ber/Geo/1/2* queue is obtained as well. Combining the results we have obtained and comparing them with corresponding average continuous AoIs, we propose a possible relationship between average discrete AoI with Ber/Geo/1/c queue and the average continuous AoI with M/M/1/c queue. For each of two extreme cases where η=0 and η=1, we also determine the stationary distribution of AoI using the probability generation function (PGF) method. The relations between average AoI and the packet preemption probability η, as well as AoI’s distribution curves in two extreme cases are illustrated by numerical simulations. Notice that the probabilistic packet preemption may occur, for example, in an energy harvest (EH) node of wireless sensor network, where the packet in buffer can be replaced only when the node collects enough energy. In particular, to exhibit the usefulness of our idea and methods and highlight the merits of considering discrete time systems, in this paper we give much more explanations showing that how the results about continuous AoI is derived by analyzing the corresponding discrete time system, and how the discrete age analysis is generalized to the system with multiple sources. In terms of packet service process, we also propose our idea to analyze system’s AoI when the service time distribution is relaxed to be arbitrary.

Voltage Stability & Control, is very crucial compared to other Power System (PS) Quality and Stability issues. Long-Vertical-Power-Flows in Conventional Grids, causes voltage drops which in turn causes huge power losses, especially in the Medium Voltage (MV) and Low Voltage (LV) Distribution Networks. Such technical losses in abysmally-planned weak distribution networks, lead to substantial loss of revenues to the utility grid. Apart from classic Voltage Regulation (VR) techniques, with the rise of Distributed Generation (DG) based on Renewable Energy Sources (RES), Horizontal-Power-Flows can be introduced in the network, through various Smart Grid techniques. Coupling such sources, near load centers shall mitigate long flows from expensive conventional sources at times of huge demands, improving feeders’ Voltage Profile. This Ancillary Service of Voltage Support from DG RESs shall thereby alleviate revenue losses caused by long-power-flows in weak distribution grids. For a developing country like Pakistan, loss of revenue from an already expensive utility gives huge blow to the economy. So, a similar technique for voltage support is proposed for an 11-kV feeder, which faces similar problem, and the results are remarkable. The technique is implemented using OpenDSS Tool by modelling 3MWp PV Penetration along with some future storage.

Photovoltaic (PV) generation is potentially uncertain. Probabilistic PV generation forecasting methods have been proposed with prediction intervals (PIs). However, several studies have dealt with geographically distributed PVs in a certain area. In this study, a two-step probabilistic forecast scheme is proposed for geographically distributed PV generation forecasting. Each step of the proposed scheme adopts ensemble forecasting based on three different machine-learning methods. In this case study, the proposed scheme was compared with conventional non-multistep forecasting. The proposed scheme improved the reliability of the PIs and deterministic PV forecasting results through 30 days of continuous operation with real data in Japan.

This research will examine the computational methods to calculate the nonlinear optical process of second harmonic generation (SHG) that will be hypothesized to be present during lithium ion insertion into silicon nanowires. First it will be determined whether the medium in which SHG is conveyed is non-centrosymmetric or whether the medium is inversion symmetric where SHG as a part of the second-order nonlinear optical phenomenon does not exist. It will be demonstrated that the main interaction that determines SHG is multiphoton absorption on lithium ions. The quantum harmonic oscillator (QHO) is used as the background that generates coherent states for electrons and photons that transverse the length of the silicon nanowire. The matrix elements of the Hamiltonian which represents the energy of the system will be used to calculate the probability density of second-order nonlinear optical interactions which includes collectively SHG, sum-frequency generation (SFG) and difference-frequency generation (DFG). As a result it will be seen that at varies concentrations of lithium ions (Li+) within the crystallized silicon (c-Si) matrix the second-order nonlinear optical process has probabilities substantial enough to create second harmonic generation that could possibly be used for such applications as second harmonic imaging microscopy.

Hopfield Neural Networks (HNNs) are recurrent neural networks used to implement associative memory. Their main feature is their ability to pattern recognition, optimization, or image segmentation. However, sometimes it is not easy to provide the users with good explanations about the results obtained with them due to mainly the large number of changes in the state of neurons (and their weights) produced during a problem of machine learning. There are currently limited techniques to visualize, verbalize, or abstract HNNs. This paper outlines how we can construct automatic video generation systems to explain their execution. This work constitutes a novel approach to get explainable artificial intelligence systems in general and HNNs in particular building on the theory of data-to-text systems and software visualization approaches. We present a complete methodology to build these kinds of systems. Software architecture is also designed, implemented, and tested. Technical details about the implementation are also detailed and explained. Finally, we apply our approach for creating a complete explainer video about the execution of HNNs on a small recognition problem.

We introduce firm solar forecasts as a strategy to operate optimally overbuilt solar power plants in conjunction with optimally sized storage systems so as to make up for any power prediction errors, hence entirely remove load balancing uncertainty emanating from grid-connected solar fleets. A central part of this strategy is plant overbuilding that we term implicit storage. We show that strategy, while economically justifiable on its own account, is an effective entry step to least-cost ultra-high solar penetration where firm power generation will be a prerequisite. We demonstrate that in absence of an implicit storage strategy, ultra-high solar penetration would be vastly more expensive. Using the New York Independent System Operator (NYISO) as a case study, we determine current and future cost of firm forecasts for a comprehensive set of scenarios in each ISO electrical region, comparing centralized vs. decentralized production and assessing load flexibility’s impact. We simulate the growth of the strategy from firm forecast to firm power generation. We conclude that ultra-high solar penetration enabled by the present strategy, whereby solar would firmly supply the entire NYISO load, could be achieved locally at electricity production costs comparable to current NYISO wholesale market prices.

Induction machines drive many industrial processes, and their unexpected failure can cause heavy production losses. The analysis of the current spectrum can identify online the characteristic fault signatures at an early stage, avoiding unexpected breakdowns. Nevertheless, frequency domain analysis requires stable working conditions, which is not the case for wind generators, motors driving varying loads, etc. In these cases an analysis in the time-frequency domain -such as a spectrogram- is required for detecting faults signatures. The spectrogram is built using the short frequency Fourier transform, but its resolution depends critically on the time window used to generate it: short windows provide good time resolution, but poor frequency resolution, just the opposite than long windows. Therefore, the window must be adapted at each time to the shape of the expected fault harmonics, by highly skilled maintenance personnel. In this paper, this problem is solved with the design of a new multi-band window, which generates simultaneously many different narrow-band current spectrograms, and combines them into a single, high resolution one, without the need of manual adjustments. The proposed method is validated with the diagnosis of bar breakages during the start-up of a commercial induction motor.

This paper presents an optimized energy management strategy for Li-ion power batteries used on electric vehicles (EVs) at low temperatures. Under low-temperature environments, EVs suffer a sharp driving range loss resulted from the energy and power capability reduction of the battery. Simultaneously, because of Li plating, battery degradation becomes an increasing concern as temperature drops. All these factors could greatly increase the total vehicle operation cost. Prior to battery charging and vehicle operating, preheating battery to a battery-friendly temperature is an approach to promote energy utilization and reduce total cost. Based on the proposed LiFePO4 battery model, the total vehicle operation cost under certain driving cycles is quantified in the present paper. Then given a certain ambient temperature, a target temperature of preheating is optimized under the principle of minimizing total cost. As for the preheating method, a liquid heating system is also implemented on an electric bus. Simulation results show that the preheating process becomes increasingly necessary with a decreasing ambient temperature; however, the preheating demand declines as driving range grows. Vehicle tests verify that the preheating management strategy proposed in this paper is able to save total vehicle operation cost.

This study explores the critical role of DNA methylation in shaping phenotypic diversity and driving evolutionary adaptation in chickpea (Cicer arietinum). By employing whole-genome bisulfite sequencing and advanced genomic techniques, we analyzed DNA methylation patterns across various chickpea cultivars, focusing on key adaptive traits such as drought tolerance, disease resistance, seed size, and flowering time. Our results revealed significant methylation changes associated with these traits, providing novel insights into the epigenetic regulation of gene expression and its impact on phenotypic variation. Additionally, we investigated the dynamic responses of DNA methylation under different environmental stresses, highlighting the plasticity of the chickpea epigenome. This research not only enhances our understanding of the epigenetic mechanisms underlying plant evolution but also opens up new avenues for developing epigenetic-based strategies for crop improvement.

This study investigates the impact of DNA methylation on phenotypic diversity in chickpeas (Cicer arietinum). By analyzing DNA methylation landscapes across various chickpea cultivars, we aim to decipher the evolutionary processes underlying phenotypic variation. Using bisulfite sequencing and advanced genomic techniques, we identified significant methylation patterns associated with key adaptive traits. Our findings provide novel insights into the role of epigenetic modifications in plant evolution and offer potential applications in crop improvement.

This study investigates the impact of DNA methylation on phenotypic diversity in chickpeas (Cicer arietinum). By analyzing DNA methylation landscapes across various chickpea cultivars, we aim to decipher the evolutionary processes underlying phenotypic variation. Using bisulfite sequencing and advanced genomic techniques, we identified significant methylation patterns associated with key adaptive traits. Our findings provide novel insights into the role of epigenetic modifications in plant evolution and offer potential applications in crop improvement.

Recent advancements in molecular diagnostics have highlighted the potential of circulating cell-free DNA (ccfDNA) as a biomarker in various diseases. This study aims to explore the role of ccfDNA in the early diagnosis, prognosis, and therapeutic monitoring of diseases, with a focus on oncology. We conducted a comprehensive review and analysis of current literature, combined with experimental approaches involving advanced genomic sequencing and bioinformatics techniques. Our research systematically characterizes the molecular composition of ccfDNA, including its origins, size distribution, and methylation patterns, across different disease states. Furthermore, we investigate the dynamics of ccfDNA release and clearance in the bloodstream, elucidating mechanisms that could influence its diagnostic accuracy. In the context of cancer, we analyze the correlation between tumor-derived ccfDNA and disease progression, response to therapy, and overall survival. Our findings indicate that ccfDNA holds promise as a non-invasive biomarker for early disease detection, real-time monitoring of treatment efficacy, and potentially, predicting relapse. This study contributes to the growing field of liquid biopsies and opens new avenues for personalized medicine, emphasizing the need for standardized protocols in ccfDNA analysis to maximize its clinical utility. The implications of our findings extend beyond oncology, suggesting potential applications of ccfDNA in other pathological conditions.

Infant mortality remains a major global concern. Sudden unexpected death in infancy (SUDI) is reported globally and in the Western Cape of South Africa it accounted for 40% of all infant deaths between 2012 and 2016. Research highlighting molecular typing of respiratory viruses in SUDI cases is lacking. A total of 116 PCR-positive human rhinovirus (HRV) and respiratory syncytial virus (RSV) swab samples collected from the lungs and trachea of SUDI cases admitted to Tygerberg Medico-legal Mortuary in Cape Town between 2015 and 2019 were included and underwent sequencing and phylogenetic analysis. Three distinct HRV species were identified; HRV-A (n=28), HRV-C (n=11), and HRV-B (n=4), including eight HRV-A, seven HRV-C and one HRV-B genotypes. For RSV, both RSV-A (n=5) and -B (n=5) were detected, but no RSV-A. After amino acid alignment indicating 20 amino acid duplication and nine substitutions, two BA9 genotypes were confirmed. This study describes the first molecular and phylogenetic characterisation of respiratory viruses in SUDI cases in South Africa. The rapid decline in viral viability in post-mortem samples and the retrospective study design employed for the current study did not allow for any correlations between viral genotypes and cause of death and future prospective studies should investigate temporality and specific viral strains associated with clinical disease severity.

Background: SARS-CoV-2 Omicron JN.1 has the highest number of amino acid mutations in its receptor binding domain (RBD) and has acquired a hallmark L455S mutation. The immune evasion capability of JN.1 is a subject of scientific investigation. The US CDC used RT-qPCR SGTF as the proxy indicator of JN.1 infections for evaluation of the effectiveness of updated monovalent XBB.1.5 COVID-19 vaccines against JN.1 and recommended that all persons aged ≥6 months should receive an updated COVID-19 vaccine dose. Objective: Recommend Sanger sequencing for diagnosis of JN.1 infections to generate the data based on which guidelines are made to direct vaccination policies. Methods: The RNA in nasopharyngeal swab specimens from patients with clinical respiratory infection was subjected to nested RT-PCR, targeting a 398-base segment of the N-gene and a 445-base segment of the RBD of SARS-CoV-2 for amplification. The DNA sequences were analyzed for amino acid mutations. Results: The N-gene sequence showed Q229K, usually associated with Omicron BA.2.86 (+JN.1). The RBD sequence showed 24 amino acid mutations, including the hallmark L455S mutation for JN.1 and the V483del for BA.2.86 lineage. Conclusions: The CDC should consider Sanger sequencing of the RBD to diagnose JN.1 infections for statistical analysis in making vaccination policies.

This review article offers an in-depth look at DNA, its discovery, structure, functions, and the significant role it plays in modern biomedical research. It begins by revisiting the landmark discovery of the DNA double helix by scientists Watson and Crick, a structure resembling a twisted ladder that forms the blueprint of life. The review explains the basic processes of DNA replication (copying DNA), transcription (converting DNA to RNA), and translation (turning RNA into proteins), which are fundamental to understanding how genetic information is passed on and used by living organisms. The article then explores gene regulation and epigenetics, which involve how genes are turned on or off and how environmental factors can affect gene expression without changing the DNA sequence itself. It examines how DNA interacts with various proteins and modifiers, which play crucial roles in these processes. A major focus is on the advancements in DNA sequencing technologies. From the initial Sanger sequencing method, which was labor-intensive and time-consuming, to the highly efficient next-generation sequencing (NGS) and the latest single-molecule sequencing techniques, the review covers how these technologies have revolutionized genomics and personalized medicine. It also highlights the importance of computational genomics and bioinformatics, fields that deal with analyzing and interpreting the vast amounts of data generated by DNA sequencing. The review discusses DNA's crucial role in understanding human diseases. It covers DNA-based research in cancer, rare genetic disorders, infectious diseases, and pharmacogenomics (how genes affect a person's response to drugs). It emphasizes studies that have led to new ways of diagnosing and treating diseases. The article looks at the future of DNA research. It talks about emerging technologies like CRISPR-Cas9, a revolutionary gene-editing tool that allows scientists to modify DNA with high precision. Synthetic biology, an interdisciplinary field that combines biology and engineering for designing and constructing new biological parts and systems, is also discussed. Furthermore, DNA nanotechnology, which involves designing DNA molecules for technological uses, is explored. Finally, the review addresses ethical issues in DNA research, such as privacy concerns and debates over genome editing.

Listerias of the phylogenetic lineage II (PLII) are common in the European environment, and are hypovirulent. Despite this, they caused more than a third of sporadic cases of listeriosis, and multi-country foodborne outbreaks. L. monocytogenes ST37 is one of them. During the COVID-19 pandemic ST37 appeared in the clinical cases and ranked second in occurrence among food isolates in the Moscow region. The aim of this study was to describe the genomic features of ST37 isolates from different sources. All clinical cases of ST37 were in the cohort of male patients (age, 48-81 years) with meningitis-septicemia manifestation, and COVID-19 or Influenza in the anamnesis. The core genomes of the fish isolates were closely related. The clinical and meat isolates revealed a large diversity. Prophages (2-4/genome) were the source of the unique genes. Two clinical isolates displayed the pseudolysogeny, and excided prophages were A006-like. Absence of the plasmids, the assortment of virulence factors and resistance determinants in chromosome corresponded to the hypovirulent characteristics. However, all clinical isolates caused severe disease with deaths in four cases. Thus, these studies allow us to speculate that a previous viral infection increases a human susceptibility to listeriosis.

Mallard (Anas platyrhynchos) are currently one of the most popular species in rare bird breeding in several southern provinces of China, but there are very few studies on the gut microbial communities of domestic and wild mallards. In this study, 16S rRNA gene high-throughput sequencing technology was used to compare the composition and diversity of gut microbial communities in domestic and wild mallards. Alpha diversity analysis revealed significant differences in the gut microbial communities of domestic and wild mallards. Beta diversity analysis showed that the two groups of stool samples were mostly separated on the principal coordinate analysis (PCOA) plot. In domestic mallards, Firmicutes (67.97%) was the most abundant bacterial phylum, followed by Proteobacteria (24.48%), Bacteroidetes (3.13%), Fusobacteria (2.21%), and Actinobacteria (1.10%). The dominant bacterial phyla in wild mallards were Firmicutes (79.02%), Proteobacteria (12.85%), Fusobacteria (3.37%), and Bacteroidetes (2.79%). At the genus level, a total of 10 dominant genera (Streptococcus, Enterococcus, Clostridium, Lactobacillus, Soilbacillus, Bacillus, Acinetobacter, Comamonas, Shigella, and Cetobacterium) with an average relative abundance greater than 1% were detected in the fecal samples of both groups. The average relative abundance of five potential pathogens (Streptococcus, Enterococcus, Acinetobacter, Comamonas, and Shigella) was higher in domestic mallards than in wild mallards. The enrichment of pathogenic bacteria in the intestinal tract of domestic mallards should be of sufficient concern.

Mallard (Anas platyrhynchos) are currently one of the most popular species in rare bird breeding in several southern provinces of China, but there are very few studies on the gut microbial communities of domestic and wild mallards. In this study, 16S rRNA gene high-throughput sequencing technology was used to compare the composition and diversity of gut microbial communities in domestic and wild mallards. Alpha diversity analysis revealed significant differences in the gut microbial communities of domestic and wild mallards. Beta diversity analysis showed that the two groups of stool samples were mostly separated on the principal coordinate analysis (PCOA) plot. In domestic mallards, Firmicutes (67.97%) was the most abundant bacterial phylum, followed by Proteobacteria (24.48%), Bacteroidetes (3.13%), Fusobacteria (2.21%), and Actinobacteria (1.10%). The dominant bacterial phyla in wild mallards were Firmicutes (79.02%), Proteobacteria (12.85%), Fusobacteria (3.37%), and Bacteroidetes (2.79%). At the genus level, a total of 10 dominant genera (Streptococcus, Enterococcus, Clostridium, Lactobacillus, Soilbacillus, Bacillus, Acinetobacter, Comamonas, Shigella, and Cetobacterium) with an average relative abundance greater than 1% were detected in the fecal samples of both groups. The average relative abundance of five potential pathogens (Streptococcus, Enterococcus, Acinetobacter, Comamonas, and Shigella) was higher in domestic mallards than in wild mallards. The enrichment of pathogenic bacteria in the intestinal tract of domestic mallards should be of sufficient concern.

Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection, with septic cardiomyopathy being a common and severe complication. Despite its significant clinical impact, the molecular mechanisms underlying sepsis-induced cardiomyopathy (SICM) remain incompletely understood. In this study, we performed a comparative analysis of whole transcriptome profiles in two widely used mouse models of septic cardiomyopathy, the cecal ligation and puncture (CLP) model and the lipopolysaccharide (LPS) model. Our aim was to identify key genes and pathways involved in the development of septic cardiomyopathy and to evaluate the similarities and differences between the two models. Our findings suggested that 1) both methods can induce septic heart dysfunction within 24 hours; 2) distinct whole transcriptome expression profiles are revealed; 3) potentially different pathways are involved in causing heart failure in sepsis. The comprehensive comparison provides valuable insights into the molecular basis of septic cardiomyopathy and contributes to the ongoing search for effective treatment strategies, triggered by different factors for SICM.

Next generation sequencing and metabolomics have become very cost and work efficient and are integrated into an ever growing number of life science research projects. Typically, well established software pipelines provide quantitative data informing about gene expression or concentrations of metabolites from the raw data. This data needs to be visualized and further analyzed in order to support scientific hypothesis building and identification of underlying biological patterns. Some tools exist, but require installation or manual programming. We developed “Gene Expression Plotter” (GXP), an RNA-Seq and Metabolomics data visualization and analysis tool entirely running in the user’s web browsers, thus not needing any custom installation, manual programming or upload of confidential data to third party servers. GXP enables the user to generate interactive plots, visually summarize genetic or metabolic responses in scientific sketches (Mapman), carry out cluster and principal component analysis, and conduct overrepresentation analyses. GXP can be used to publish research data along with interactive plots and results of analyses carried out with it. GXP is freely available on GitHub: https://github.com/usadellab/GeneExpressionPlots

The genus Pseudomonas hosts an extensive genetic diversity and is one of the largest genera among Gram-negative bacteria. Type strains of Pseudomonas are well-known to represent only a small fraction of this diversity and the number of available Pseudomonas genome sequences is increasing rapidly. Consequently, new Pseudomonas species are regularly reported and the number of species within the genus is in constant evolution. In this study, whole genome se-quencing enabled us to define 43 new Pseudomonas species and to provide an update of the Pseu-domonas evolutionary and taxonomic relationships. Phylogenies based on the rpoD gene and whole genome sequences, including 316 and 313 type strains of Pseudomonas, respectively, re-vealed sixteen groups of Pseudomonas and justified the partitioning of the P. putida group into fifteen subgroups. Pairwise average nucleotide identities were calculated between type strains and a selection of 60 genomes of non-type strains of Pseudomonas. Forty-one strains were incor-rectly assigned at the species level and among those, 19 strains were shown to represent an addi-tional 13 new Pseudomonas species that remain to be formally classified. This work pinpoints the importance of correct taxonomic assignment and phylogenetic classification in order to perform integrative studies linking genetic diversity, lifestyle and metabolic potential of Pseudomonas spp.

Aegilops columnaris Zhuk. is tetraploid grass species (2n=4x=28, UcUcXcXc) closely related to Ae. neglecta and growing in Western Asia and a western part of the Fertile Crescent. Genetic diversity of Ae. columnaris was assessed using C-banding, FISH, nuclear and chloroplast (cp)DNA analyses, and gliadin electrophoresis. Cytogenetically Ae. columnaris was subdivided into two groups, C-I and C-II, showing different karyotype structure, C-banding and FISH patterns. Group C-I was more similar to Ae. neglecta. All types of markers revealed significant heterogeneity of the C-II group, although group C-I was also polymorphic. Two chromosomal groups were consistent with plastogroups identified in a current study based on sequencing of three chloroplast intergenic spacer regions. The similarity of group C-I of Ae. columnaris with Ae. neglecta and their distinctness from C-II indicate that divergence of the C-I group was associated with minor genome modifications. Group C-II could emerge from C-I relatively recently, probably due to introgression from another Aegilops species followed by a reorganization of the parental genomes. Most C-II accessions were collected from the very narrow geographic region, and they might originate from a common ancestor. We suggest that the C-II group is at the initial stage of species divergence and undergoing an extensive speciation process.

In the post antimicrobial era, increasing attention is paid towards using bacteriophage (phage in short) therapy to control antibiotic-resistant bacteria. The first step in phage therapy applications is isolating highly efficient lytic phages or phage cocktails from various sources. When a double-layer- agar with around 0.7% agar in top agar is employed, it results in a low number of phage isolation with a poor resolution, and in many cases, you miss the phage. To address this problem, a low concentration of agar in top agar is examined for better phage isolation. Here, our results proved the efficiency of isolating phage upon formulating a double-layer agar with 0.3% agar in top agar. A sewage sample was collected then phages were isolated, purified, and spotted on a top layer agar with 0.3% agar. The results showed the possibility of isolating a higher number of phages on 0.3% top agar than 0.7%. The finding advocates using 0.3% top agar for the double-layer agar, as it will provide fast, better, and easy phage screening and isolation.

Directed evolution methods are becoming increasingly popular, as they are extremely powerful toward developing new biomolecules with altered/novel activities, e.g., proteins with new catalytic functions or substrate specificities, and nucleic acids that recognize an intended target. Especially useful are systems that have incorporated continuous evolution, where the protein to be evolved undergoes continuous mutagenesis to evolve a desired trait with little to no input from the researcher once the system is started. However, continuous evolution methods can be challenging to implement in the lab and daunting for researchers to invest time and resources. Our intent is to provide basic information and helpful suggestions that we have gained from our experience with bacterial phage-assisted continuous evolution (PACE). Specifically, we review factors to consider before adopting PACE for a given evolution scheme, different types of selection circuits that can be utilized with particular focus on the PACE-B1H selection system, what optimization of a PACE selection circuit may look like using directed evolution of ME47 as a case study, and additional techniques that may be incorporated into a PACE experiment. With this information, researchers will be better equipped to determine if PACE is a valid strategy to use to evolve their proteins and how to set up a valid selection circuit.

In this research work the study of Buongiorno Model Darcy Forchheimer flow of Hybrid nanofluid flow on isothermal permeable stretch/shrink sheet with homogeneous and heterogeneous reaction is investigated. The effects of MHD, thermal radiation, viscous dissipation, Joule heating, and heat generation/absorption are taken into account. Hybrid nanofluids can act as a medium for heterogeneous-homogeneous reactions. The nanoparticles dispersed in the fluid can influence reaction kinetics and species transport, potentially, altering reaction rates and pathways. The applications of HNF in reactions, both homogeneous and heterogeneous, lie in leveraging their enhanced thermal properties, catalytic potential, and improved mixing capabilities to optimize reaction efficiency and control reaction conditions. Similarity transformation is used to convert a set of PDEs into a set of ODEs. HAM is used for the solution of the obtained ODEs system. In a heterogeneous reaction, the concentration gradient is amplified; in a homogeneous reaction, the impact is opposite. Moreover, at higher compositions of HNPs, the concentration and velocity rise while the temperature falls. Furthermore, as the values of homogeneous and heterogeneous reactions increase, the concentration falls. It is reliable with the idea that a greater reaction rate lowers the diffusion rate. Nevertheless, these parameters do not affect temperature or velocity.

Exergy analysis evaluates the efficiency of system components by quantifying the rate of entropy generation. In general, the exergy destruction rate or irreversibility rate was directly obtained through the exergy-balance equation. However, this method cannot determine the origin of the component's entropy generation rate, which is a very important factor in system design and improvement. In this study, a thorough energy, exergy thermoeconomic analysis of a proton exchange membrane fuel cell (PEMFC) was performed, providing the heat transfer rate, entropy generation rate and cost loss rate of each component. The irreversibility rate of each component is obtained by the Gouy-Stodolar theorem. Detailed and extensive exergy and thermoeconomic analyses of PEMFC system have determined that water cooling units experience the greatest heat transfer among the components in the studied PEMFC system, resulting in the greatest irreversibility and thus the greatest monetary flow loss.

Building energy demand impacts a myriad of interconnected economic, societal, and environmental aspects. As a result, Buildings Energy Models (BEM) play an important role in the process of urban design and planning. While previous studies have investigated the effects of building interventions on energy efficiency, their applicability may be limited due to the BEM’s high computational complexity. This limits their ability to systematically study important aspects of energy demand on a large scale. The development of Machine Learning Models (MLM) allows to design the required detailed analysis and solutions, while reducing the computational burden, making MLM attractive for urban designers. The capability of MLM to generalize well for multiple contexts (in our case, multiple buildings) is a crucial contributor to their applicability. However, the validation process in a wider context is often overlooked, therefore its generalization capabilities are not quantified. In this paper, we present a framework to train and validate a surrogate model derived from a physics-based BEM. Our method employs a Multiple Linear Regression model to predict Energy Use Intensity (EUI) for office buildings in Singapore using 36 input parameters (covariates), based on a training dataset of 23,000 samples. Model validation is performed by comparing the results of the Surrogate Model (SM) to a widely used BEM for a sample of 120 buildings. Our results indicate that the SM has an accuracy of NRMSE of 13%, NMBE of −3.56%, and R2 of 0.92, which suggests it can effectively and accurately predict building EUI. We also conduct a sensitivity analysis, which indicates that the parameters associated with internal loads and internal space usage are the most influential. Additionally, we present a reduced order model trained with only the 11 most influential parameters, which exhibits negligible loss in accuracy compared to the full SM while providing reduced complexity. Finally, we demonstrate an application of our SM to evaluate energy efficiency under uncertainty scenarios. The analytically derived results indicate a potential reduction of EUI of offices in Singapore from 227kWh/m2 to 99kWh/m2 by altering the building parameters that were identified as most influential.

Generative models have recently gained popularity in Remote Sensing, offering substantial benefits for interpreting and utilizing satellite imagery across diverse applications such as climate monitoring, urban planning, and wildfire detection. These models are particularly adept at addressing the challenges posed by satellite images, which often exhibit domain variability due to seasonal changes, sensor characteristics, and especially variations in spectral bands. Such variability can significantly impact model performance across various tasks. In response to these challenges, our work introduces a novel approach that harnesses the capabilities of Generative Adversarial Networks (GANs), augmented with Contrastive Learning, to generate target domain images that account for multi-spectral band variations effectively. By maximizing mutual information between corresponding patches and leveraging the power of GANs, our model aims to generate realistic-looking images across different multi-spectral domains. We present a comparative analysis of our model against other well-established generative models, demonstrating its efficacy in generating high-quality satellite images while effectively managing domain variations inherent to multi-spectral diversity.

Ultralight power generation equipment has high requirements for the power density, continuous operation, and transient stability of the whole machine, and there is a direct conflict between high power density design and substantial stability control in the power unit design. In order to meet the power density requirements of ultra-light power stations, three main problems need to be solved, namely engine speed oscillation and flameout in the process of load power mutation, matching of the generator and engine torque, and stabilizing the voltage waveform of the AC output end. In this paper, we proposed an exquisite control strategy for ultralight power generation systems in engines, generators, and inverters. The effectiveness and practicability of the proposed strategy are verified by both simulation and experiment. The results show that the proposed control strategy can effectively solve the instability problem of the ultralights generator set and improve the stability of the system, where the response recovery can be achieved within 0.9 seconds under the condition of total load increase or decrease, and the mismatching degree of the generator following the engine is reduced by 90%. The strategy could also guarantee long-term stable operation with high-quality electrical energy output.

This paper presents a design and performance analysis of a 10-element 5G massive MIMO antenna array for sub-6GHz mobile handsets, specifically for LTE bands 42 (3400-3600 MHz), 43 (3600-3800 MHz), 48/49 (3550-3700 MHz) applications. The proposed antenna array consists of 10 closely spaced linearly polarized inverted-F antennas with a compact size of 20 × 9 mm2 of a single element. The proposed antenna array provides high gain, high efficiency, and low correlation between the antenna elements, which results in improved channel capacity, increased data rate, and enhanced signal quality. The performance of the antenna array is evaluated in terms of the radiation pattern, gain, efficiency, and correlation coefficient. The simulation and measured results show that the proposed antenna array achieves an approximate peak gain of 3.1 dBi at the resonance frequency, a total efficiency of 65 %, and a low correlation coefficient of 0.06 between the antenna elements. Therefore, the proposed 5G massive MIMO antenna array is a promising candidate for sub-6 GHz mobile handsets, particularly for LTE bands 42/43/48/49 applications.

Energy demand and consumption in recent times have witnessed a rapid proliferation influenced by technological developments, increased population and economic growth. This has fuelled research trends in the domain of energy management employing tri-generation systems such as the combined cooling, heating and power (CCHP) systems. Furthermore, the incorporation of renewable energy, especially solar energy, to complement the thermal input by fossil fuels has facilitated the effectiveness and sustainability of CCHP systems. This study proposes a new approach to improve the overall efficiency of CCHP systems and compute the optimal design parameters in order to assist decision makers to identify the best geometrical configuration. A multi-objective optimization formulation of a solar-assisted CCHP system was adopted to maximize the net power, the exergy efficiency and minimize the CO2 emission using the greywolf optimization technique. In addition, the effects of the decision variables on the objective functions were analysed. The proposed optimization approach yielded 100 set of Pareto optimal solutions which would serve as options to the decision maker to make a selection in order to improve the performance of a solar-assisted CCHP system. This study demonstrates that the proposed approach is potentially suitable for the optimization of a solar-assisted CCHP system.

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

Keeping the bus voltage within acceptable limits depends on dispatching reactive power. Power quality improves as a result of creating an effective power flow system, which also helps to reduce power loss. Therefore, Optimal Reactive Power Dispatch (ORPD) studies aim at designing appropriate system configurations to enable a reliable operation of power systems. Establishment of such a configuration is handled through control variables in power systems. On the other hand, installing Distributed Generation Unit (DGU) into a power system can have an important effect on power quality and power loss minimization. In this paper, Grey Wolf Optimization (GWO method is applied to ORPD problem for the first time, to find optimal placement of newly installed DGUs at the power system. Active power loss and voltage minimization have been minimized by optimizing the control variables while keeping them within their upper and lower bounds, and by finding the optimal placement of a newly installed DGU in power system. On the basis of IEEE 30 bus and IEEE 118 bus systems, performance of the suggested approach is investigated. A comparison is also performed among the proposed method and some other methods. Test results demonstrate that the resulting configuration contributes to growing the rate of renewable integration to a power system. The results also indicate that the suggested optimization approach applied to ORPD problem has improved power system performance in terms of both on power loss and voltage deviation. The promising results highlight the potential of the GWO algorithm to facilitate the integration of renewable power sources, and its role in promoting sustainable energy solutions.

In the era of electrification and artificial intelligence, direct current motors are widely utilized with numerous innovative adaptive and learning methods. Traditional methods utilize model-based algebraic techniques with system identification, such as recursive least squares, extended least squares, and autoregressive moving averages. The new method known as deterministic artificial intelligence asserts physical-based process dynamics to achieve target trajectory tracking. There are two common autonomous trajectory generation algorithms: sinusoidal function and Pontryagin's based generation algorithm. This thesis aims to simulate model-following and deterministic artificial intelligence methods using sinusoidal and Pontryagin's methods and compare their performance difference when following challenging step function slew maneuver.

The operational measure (OM) of the Second-Generation Intact Stability Criteria (SGISC) is the initial step toward the design of a performance-based dynamic stability assessment of the ship by considering both the vessel’s operation, loading condition and weather parameters. The SGISC recommends the standard wave scatter table (WST) for the environmental data, an indefinite requirement for a simplified assessment pathway, which provides the probability of wave occurrence. The existing standard WST was developed based on the North Atlantic Ocean. This study aims to identify the discrepancy in the probability of wave occurrence in the IMO-recommended WST when compared with developed hindcast WST for smaller regions of the North Atlantic Ocean for the application of SGISC. The significant difference in the existing standard WST is identified when compared with hindcast data, especially across different seasons. A case study of OM on the C11 class post-Panamax container ship for excessive acceleration is provided to better represent the study. The identified limitation limits the use of standard WST in ship stability assessment. The study recommends using hindcast-based WST for SGISC applications that are region and season based. This recommendation is beneficial in improving the safety assessment by OM, given the data is reliable and available for the season and region-specific, and hence the accuracy of the ship stability can be improved while using for the SGISC OM assessment. Further, it makes the WST adhere to the actual framework of the SGISC, i.e., using existing environmental data for design assessment and improving the simplified stability analysis.

Developing detailed Finite Element Models related to aerospace, automobile, civil, material science etc could be a very challenging task, especially generating a mesh that could produce accurate results. This review article provides an overview of different types of structural mechanics problems which are of interest to researchers and recent developments in meshing methodology related to each type of problems. The article also describes an automatic 2D mesh generation framework leverag- ing the capabilities of commercial FEA software MSC.PATRAN

Sources are classified into two depending upon the factor of reviving. These sources, which cannot be revived into their original shape once they are consumed, are considered as nonrenewable energy resources, i.e., (coal, fuel) Moreover, those energy resources which are revivable to the original condition even after being consumed are known as renewable energy resources, i.e., (wind, solar, hydel) Renewable energy is a cost-effective way to generate clean and green electrical energy Now a day’s majority of the countries are paying heed to energy generation from RES Pakistan is mostly relying on conventional energy resources which are mostly nonrenewable in nature coal, fuel is one of the major resources, and with the advent of time their prices are increasing on the other hand RES have great potential in the country with the deployment of RES greater reliability and an effective power system can be obtained In this thesis, a similar concept is being used and a hybrid power system is proposed which is composed of intermixing of renewable and nonrenewable sources The Source side is composed of solar, wind, fuel cells which will be used in an optimal manner to serve load The goal is to provide an economical, reliable, uninterruptable power supply. This is achieved by optimal controller (PI, PD, PID, FOPID) Optimization techniques are applied to the controllers to achieve the desired results. Advanced algorithms (Particle swarm optimization, Flower Pollination Algorithm) will be used to extract the desired output from the controller Detailed comparison in the form of tables and results will be provided, which will highlight the efficiency of the proposed system.

In the current era of ‘big data’, scientists are able to quickly amass enormous amount of data in a limited number of experiments. The investigators then try to hypothesize about the root cause based on the observed trends for the predictors and the response variable. This involves identifying the discriminatory predictors that are most responsible for explaining variation in the response variable. In the current work, we investigated three related multivariate techniques: Principal Component Regression (PCR), Partial Least Squares or Projections to Latent Structures (PLS), and Orthogonal Partial Least Squares (OPLS). To perform a comparative analysis, we used a publicly available dataset for Parkinson’ disease patien ts. We first performed the analysis using a cross-validated number of principal components for the aforementioned techniques. Our results demonstrated that PLS and OPLS were better suited than PCR for identifying the discriminatory predictors. Since the X data did not exhibit a strong correlation, we also performed Multiple Linear Regression (MLR) on the dataset. A comparison of the top five discriminatory predictors identified by the four techniques showed a substantial overlap between the results obtained by PLS, OPLS, and MLR, and the three techniques exhibited a significant divergence from the variables identified by PCR. A further investigation of the data revealed that PCR could be used to identify the discriminatory variables successfully if the number of principal components in the regression model were increased. In summary, we recommend using PLS or OPLS for hypothesis generation and systemizing the selection process for principal components when using PCR.rewordexplain later why MLR can be used on a dataset with no correlation

Cardiac myosin-binding protein C (MyBPC) is a thick-filament associated regulatory protein in the sarcomere. It regulates the sensitive contractile system of the myocardium by acting as a mechanical tether, sensitizing the thin filament or modulating myosin motor activity. Mutations in the MYBPC3 gene are a frequent cause for the development of hypertrophic cardiomyopathy, the most frequent cardiac disorder. Recently, the monoallelic double mutation MYBPC3Δ25bp/D389V has been discovered as a subset of the common MYBPC3Δ25bp variant in South Asia. MYBPC3Δ25bp/D389V carriers exhibit hyperdynamic features, which are considered an early finding for the development of hypertrophic cardiomyopathy. Using correlation-guided molecular dynamics simulations sampling, we show that the D389V mutation shifts the conformational distribution of the C2 domain of MyBPC. We further applied biochemical approaches to probe the effects of the D389V mutation on structure, thermostability and protein-protein interactions of MyBPC C2. The melting temperature (Tm) of MyBPC C2 D389V is decreased by 4 to 7 °C compared to wild type while the interaction of the C0-C2 domains with myosin and actin remains unchanged. Additionally, we utilized steered molecular dynamics (SMD) simulations to investigate the altered unfolding pathway of MyBPC C2 D389V. Based on our data, we propose a pathomechanism for the development of HCM in MYBPC3Δ25bp and MYBPC3Δ25bp/D389V carriers.

An in-depth study of the failure of granular materials, which is known as a mechanism to generate defects, can reveal the facts about the origin of the imperfections such as cracks in the carbon anodes. The initiation and propagation of the cracks in the carbon anode, especially the horizontal cracks below the stub-holes, reduce the anode efficiency during the electrolysis process. In order to avoid the formation of cracks in the carbon anodes, the failure analysis of coke aggregates can be employed to determine the appropriate recipe and operating conditions. In this paper, it will be shown that a particular failure mode can be responsible for the crack generation in the carbon anodes. The second-order work criterion is employed to analyze the failure of the coke aggregate specimens and the relationships between the second-order work, the kinetic energy, and the instability of the granular material are investigated. In addition, the coke aggregates are modeled by exploiting the discrete element method (DEM) to reveal the micro-mechanical behavior of the dry coke aggregates during the compaction process. The optimal number of particles required for the failure analysis in the DEM simulations is determined. The effects of the confining pressure and the strain rate as two important compaction process parameters on the failure are studied. The results reveal that increasing the confining pressure enhances the probability of the diffusing mode of the failure in the specimen. On the other hand, the increase of strain rate augments the chance of the strain localization mode of the failure in the specimen.

The aim of this articles is to investigate the entropy optimization in unsteady MHD flow Darcy-Forchheimer nanofluids towards a stretchable sheet. The surface we tend to think about is porous and stretchy under acceleration. Flow occurs due to the stretching of the surface. Four distinct types of aqueous nanostructures are taken in this examination where copper oxide ( ), copper ( ), titanium dioxide ( ) and aluminum oxide ( ) are the nanoparticles. Irreversibility analysis are discussed through second law of thermodynamics. The expression of energy is mathematically designed and discussed according to heat generation / absorption, dissipation, thermal radiation, and joule heating. The nonlinear PDE (partial differential conditions) is first changed to ODE (normal differential conditions) through appropriate similarity variables. Here we used the numerically embedded solution technique to develop a numerical result for the obtained nonlinear flow expression. Influence of various flow parameter velocity temperature distribution and entropy generation are discussed. Reduction occurs in velocity profile for larger porosity and magnetic parameters. An enhancement in entropy generation and temperature distribution is seen for Brinkman number. An opposite effect is noticed in velocity and temperature through solid volume friction.

This paper contains a concise overview of the deployment of scattered solar power plants in Poland, mainly from the perspective of their communication networks, and how the recent development of the Polish 4G networks has a very positive impact for the performance of the whole monitoring system (production control and video-surveillance), with a special emphasis on video-analytics, due to its higher bandwidth demand. All the information will be shown from the point of view of the solar photovoltaics developer I+D Energías, and therefore it constitutes a real user’s experience.

In the present work, we provide an electronic structure based method for the “on-the-fly” deter- mination of vibrational sum frequency generation (v-SFG) spectra. The predictive power of this scheme is demonstrated at the air-water interface. While the instantaneous fluctuations in dipole moment are obtained using the maximally localized Wannier functions, the fluctuations in polar- izability are approximated to be proportional to the second moment of Wannier functions. The spectrum henceforth obtained captures the signatures of hydrogen bond stretching, bending, as well as low-frequency librational modes.

Zinc-oxide (ZnO) nanostructures including nanorods are currently considered as a pioneer research of interest world-wide due to their excellent application potentials in various applied fields especially for the improvement of energy harvesting photovoltaic solar cells (PSC). We report on the growth and morphological properties of zinc-oxide (ZnO) nanorods grown on the surface of plain zinc (non-etched and chemically etched) plates by using a simple, economical, and environment-friendly technique. We apply hot water treatment (HWT) technique to grow the ZnO nanorods and varies the process parameters, such as temperature and the process time duration. The morphological, and elemental analysis confirm the agglomeration of multiple ZnO nanorods with its proper stoichiometry. The obtained nanostructures for different temperatures with different time duration showed the variation in uniformity, density, thickness and nanonorods size. The ZnO nanorods produced on the etched zinc surface were found thicker and uniform as compared to those grown on the non-etched zinc surface. This chemically etched Zinc plates preparation can be an easy solution to grow ZnO nanorods with high density and uniformity suitable for PSC applications such as to enhance the energy conversion efficiency of the photovoltaic (PV) solar cells towards the future sustainable green earth.

In order to reach the theoretical efficiency limits of lead-based metal halide perovskite solar cells, the voltage should be enhanced because it suffers from nonradiative recombination. Perovskite materials contain intrinsic defects that can act as Shockley-Read-Hall recombination centers. Several experimental and computational studies have characterized such defect states within the band gap. We give a systematic overview of compositional engineering by distinguishing the different defect reducing mechanisms. Doping effects are divided into influences on: (1) Crystallization; (2) Lattice properties. Incorporation of dopant influences the lattice properties by: (a) Lattice strain relaxation; (b) Chemical bonding enhancement; (c) Band gap tuning. The intrinsic lattice strain in undoped perovskite was shown to induce vacancy formation. The incorporation of smaller ions, such as Cl, F and Cd, increases the energy for vacancy formation. Zn doping is reported to induce strain relaxation but also to enhance the chemical bonding. The combination of computational studies using (DFT) calculations quantifying and qualifying the defect reducing propensities of different dopants with experimental studies is essential for deeper understanding and unraveling insights, such as the dynamics of iodine vacancies and the photochemistry of the iodine interstitials, and can eventually lead to a more rational approach in the search for optimal photovoltaic materials.

We present a review of the current state of the field for a rapidly evolving group of technologies related to solar energy harvesting in built environments. In particular, we focus on recent achievements in enabling the widespread distributed generation of electric energy assisted by energy capture in semi-transparent or even optically clear glazing systems and building wall areas. Whilst concentrating on the cutting-edge recent results achieved in the integration of traditional photovoltaic device types into novel concentrator-type windows and glazings, we compare the main performance characteristics reported with these achievable using more conventional (opaque or semi-transparent) solar cell technologies. A critical overview of the current status and future application potential of multiple existing and emergent energy harvesting technologies for building integration is provided.

Time recordings of impulse-type oscillation responses are short and highly transient. These characteristics may complicate the usage of classical spectral signal processing techniques for a) describing the dynamics and b) deriving discriminative features from the data. However, common model identification and validation techniques mostly rely on steady-state recordings, characteristic spectral properties and non-transient behavior. In this work, a recent method, which allows reconstructing differential equations from time series data, is extended for higher degrees of automation. With special focus on short and strongly damped oscillations, an optimization procedure is proposed that fine-tunes the reconstructed dynamical models with respect to model simplicity and error reduction. This framework is analyzed with particular focus on the amount of information available to the reconstruction, noise contamination and non-linearities contained in the time series input. Using the example of a mechanical oscillator, we illustrate how the optimized reconstruction method can be used to identify a suitable model and to extract features from uni-variate and multivariate time series recordings in an engineering-compliant environment. Moreover, the determined minimal models allow for identifying the qualitative nature of the underlying dynamical systems as well as testing for the degree and strength of non-linearity. The reconstructed differential equations would then be potentially available for classical numerical studies, such as bifurcation analysis. These results represent a physically interpretable enhancement of data-driven modeling approaches in structural dynamics.

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

The crack geometry and associated strain field around Berkovich and Vickers indents on silicon have been studied by X-ray diffraction imaging and micro-Raman spectroscopy scanning. The techniques are complementary, the Raman data coming from within a few micrometers of the indentation, whereas the X-ray image probes the strain field at a distance of typically tens of micrometers. For example, Raman data provides an explanation for the central contrast feature in the X-ray images of an indent. Strain relaxation from breakout and high temperature annealing are examined and it is demonstrated that millimeter length cracks, similar to those produced by mechanical damage from misaligned handling tools, can be generated in a controlled fashion by indentation within 75 micrometers of the bevel edge of 200mm diameter wafers.

Smith-Magenis syndrome is a complex neurobehavioral genetic disorder. The spectrum of SMS phenotype is broad but commonly includes craniofacial, neurobehavioral, and otolaryngologic features. While the etiology of SMS is commonly attributed to one copy interstitial deletion in the 17p11.2 region (90-95% of cases), variants identified by sequence analysis in RAI1 have also been reported in 5-10% of cases. The phenotypic spectrum of patients with RAI1 sequence alterations is not clear. In this study, we report a 9-year-old male with global cognitive and psychomotor developmental delay, musculoskeletal and cardiovascular abnormalities, and dysmorphic craniofacial features. Whole genome quad analysis of the proband, unaffected parent, and unaffected brother identified a novel de novo RAI1:c.2736delC variant. This is the first report of this variant in the literature. This report also highlights the details of the genome analysis and this patient's phenotypic spectrum.

The study of biologically active substances from natural sources shows the prospect of obtaining a new type of antimicrobial agents, highly effective against pathogenic microorganisms and non-toxic to humans. Our study reveals for the first time that Cornu aspersum mucus has the potential to act as a source of antibacterial agents against bacterial pathogens such as Bacillus cereus 1085, Propionibacterium acnes 1897, Salmonella enterica 8691, Enterococcus faecalis 3915, and Enterococcus faecium 8754. Both mucus fractions with MW<20 kDa and MW>20 kDa showed antimicrobial activity and antioxidant properties that’s why they can be turned into an alternative agent to expensive synthetic antibacterial compounds. Using de novo sequencing 16 novel peptides with potential antibacterial activity were identified by in a fraction with MW<20 kDa. The results of electrophoretic and proteomic analysis of mucus fraction with MW >20 kDa presented proteins with potential antibacterial activity highly homologous to hemocyanins, mucus protein Aspernin, lectins, L-amino acid oxidase-like protein, and mucins (mucin-5AC, mucin-5B, mucin-2 and mucin-17). Thanks to the synergistic action of the bioactive components, the mucus fraction with MW > 20 kDa in low concentrations per 8–2 µg/mL showed promising antimicrobial activity against the tested bacteria, comparable to Vancomycin and without unwanted cytotoxic effects against non-target cells. Additionally, C. aspersum mucus fractions were found to have a positive effect on eukaryotic organisms by reducing the levels of intracellular oxidative damage and increasing the antioxidant capacity of the cell. These findings could serve as a basis for the development of a potent non-cytotoxic antibacterial agent to replace conventional antibiotics and avoid the development of antibiotic resistance.

Background: Non-alcoholic fatty liver disease (NAFLD) is manifested by hepatic steatosis, insulin resistance, hepatocyte death, and systemic inflammation. Obesity induces steatosis and chronic inflammation in the liver. However, the precise mechanism underlying hepatic steatosis in the setting of obesity remains unclear. Here we report studies that address this question. Methods: 14 weeks on high-fat diet (HFD) with high sucrose, C57BL/6 mice revealed a phenotype of liver steatosis. Transcriptional profiling analysis of the liver tissues was performed using RNA sequencing (RNA-seq). Results: Our RNA-seq data revealed 692 differentially expressed genes involved in processes of lipid metabolism, oxidative stress, immune responses, and cell proliferation. Notably, the gene encoding neutral sphingomyelinase SMPD3, was predominantly upregulated in the liver tissues of the mice displaying a phenotype of steatosis. Moreover, nSMase2 activity was elevated in these tissues of the liver. Pharmacological and genetic inhibition of nSMase2 prevented intracellular lipid accumulation and TNFα-induced inflammation in in-vitro HepG2-steatosis cellular model. Furthermore, nSMase2 inhibition ameliorates oxidative damage by rescuing PPARα and prevent cell death associated with high glucose/oleic acid-induced fat accumulation in HepG2 cells. Conclusions: Collectively, our findings highlight the prominent role of nSMase2 in hepatic steatosis which could serve as a potential therapeutic target for NAFLD and other hepatic steatosis-linked disorders.

Conjugative transposons in Gram-negative bacteria have a significant role in the dissemination of antibiotic-resistance-conferring genes between bacteria. This study aims to genomically characterize plasmids and conjugative transposons carrying integrons in clinical isolates of Klebsiella pneumoniae. Genetic composition of conjugative transposons and phenotypic assessment of 50 multidrug-resistant K. pneumoniae isolates from Tertiary-care Hospital (SQUH), Muscat, Oman was investigated. Horizontal transferability was investigated by filter- mating conjugation experiments. Whole genome sequencing (WGS) was performed to determine the sequence type (ST), acquired resistome and plasmidome of integron-carrying strains. Class 1 integron was detected in 96% of isolates and among integron-positive isolates, 18 stains contained variable regions. Horizontal transferability by conjugation confirmed the successful transfer of integrons between cells and WGS confirmed their presence in conjugative plasmids. Dihydrofolate reductase (dfrA14) was the most prevalent (34.8%) gene cassettes in class 1 integrons. MLST analysis detected predominantly ST-231 and ST-395. BlaOXA-232 and blaCTX-M-15 were the most frequently detected carbapenems and beta-lactamases in sequenced isolates. This study highlighted the high transmissibility of MDR-conferring conjugative plasmids in clinical isolates of K. pneumoniae. Therefore, the wise use of antibiotics and the adherence to effective infection control measures are necessary to limit further dissemination of multidrug-resistant organisms.

The majority of Candida species are known as non-pathogenic yeasts and rarely involved in human diseases. However, recently case reports of human infections caused by non-albicans Candida species have increased, mostly in immunocompromised hosts. Our study aimed to describe and caracterise as thoroughly as possible, a new species of the Candida genus, named here Candida massiliensis (PMML0037), isolated from a clinical sample of human sputum. We compared genetic data based on the sequences of four genetic regions: "Internal Transcribed Spacers" of rRNA, D1/D2 domains (28S large subunit rRNA) and part of the genes encoding Translation Elongation Factor 1-α and β-tubulin2, to morphological characters, from scanning electron microscopy (TM 4000 Plus, SU5000), physiological, including the results of oxidation and assimilation tests of different carbon sources by the Biolog system, and chemical mapping by Energy-Dispersive X-ray Spectroscopy. Lastly, the in vitro antifungal susceptibility profile was performed using the E-testTM exponential gradient method. The multilocus analysis supported the genetic position of Candida massiliensis (PMML0037) as a new species of the genus Candida, and the phenotypic analysis highlighted its unique morphological and chemical profile when compared to other Candida species included in the study.

Heteromorphic sex chromosomes are rarely found in plants. They were observed only in 47 species from phylogenetically distant families, suggesting that the evolution of sex chromosomes was independent in these species. It was shown that DNA repeat sequences are one of the major factors driving sex chromosomes evolution, and an accumulation or elimination of the repetitive DNA elements are closely linked with the formation of differences in the sex chromosomes. The goal of this study was to characterize the transposon composition in male and female plants of Cannabis sativa L., Humulus lupulus L. and Humulus japonicus Siebold &amp; Zucc. For the first time, the male and female genomes of H. japonicus as well as male genomes of H. lupulus and C. sativa have been sequenced (there were no open data about them). The analysis of genome-wide sequencing data with using Repeatexplorer2 and author’s scripts was carried out. It was shown that accumulation of Ty3-gypsy may be associated with speciation in Cannabaceae family which is the opposite of the theory of speciation throw whole-genome duplication. Moreover, the sex-specific DNA repeat clusters in C. sativa and H. japonicus were found. The analysis also revealed that the concentration of Tekay, Retand and Ikeros repeats in the Y chromosome of C. sativa is lower than in the X chromosome and the Angela concentration is higher in the Y chromosome.

Polymyxin resistance, determined by mcr genes located on plasmid DNA, currently pose a high epidemiological threat. Non-typhoid Salmonella (NTS) are one of the key pathogens causing diarrheal diseases. Here, we report the isolation and whole genome sequencing of multidrug colistin-resistant/susceptible isolates of non-typhoid Salmonella enterica serovars carries mcr genes. Non-typhoid strains of Salmonella enterica subsp. enterica were isolated during microbiological monitoring of the environment, food, and diarrheal disease patients between 2018 and 2020 in Russia (n=586). mcr-1 genes were detected using a previously developed qPCR assay and whole genome sequencing of mcr positive isolates was performed by both short-read (Illumina) and long-read (Oxford Nanopore) approaches. Three colistin-resistant isolates including two isolates of S. Enteritidis and one isolate of S. Bovismorbificans carried the mcr-1.1 gene located on IncX4 and IncI2 conjugative plasmids, respectively. The phenotypically colistin-susceptible isolate of S. Typhimurium carried a mcr-9 gene on plasmid IncHI2. In conclusion, we present the first three cases of mcr gene carrying NTS isolates detected in Russia with both outbreak and sporadic epidemiological background.

Presence of mutated genes strongly correlates with incidence of cancer. Decades of research, however, has not yielded any specific causative gene or set of genes for the vast majority of cancers. The Cancer Genome Atlas program was supposed to provide clarity but it only gave much more data without any accompanying insight into how the disease begins and progresses. It may be time to notice that epidemiological studies consistently show that the environment, not genes, has the principal role in causing cancer. Since carcinogenic chemicals in our food, drink, air and water are the primary culprit, we need to look at the biochemistry of cancer, with focus on enzymes which carry out any and all transformations in a cell. In particular, attention should be paid to the rate-limiting enzyme in DNA synthesis, ribonucleotide reductase (RnR) which is tightly linked to tumor growth. Beside the circumstantial evidence that cancer is induced at its vulnerable active-site by various carcinogens, there exists experimental proof of its role in initiating retinoblastoma and HPV-related cervical cancers. Blocking the activity of RnR is a certain way to arrest cancer.

A growing number of emerging SARS-CoV-2 variants is being identified worldwide, potentially impacting the effectiveness of current vaccines. We report the data obtained in several Italian regions involved in the SARS-CoV-2 variant monitoring from the beginning of the epidemic and spanning the period from October 2020 to March 2021.

Issues presented by the application of monoclonal antibodies in diagnostic assays and as curative agents can make the use of such molecules cost-prohibitive and sometimes even unsafe. This has warranted the development of short single-stranded oligonucleotides known as Aptamers. The structural malleability of these short DNA or RNA nucleotide segments allows them to exist in distinct conformations. SELEX (Systematic Evolution of Ligands by Exponential Enrichment) is a multi-step process for synthesis of aptamers. Each step of this procedure is governed by a diverse set of factors that influence production efficiency, binding affinity, and specificity of the oligonucleotides. Headway in aptamer research has been made in recent years by the introduction of newer iterations of the SELEX process. A greater number of studies are now being carried out to incorporate aptamers into existing disease detection tools and therapies. An overview has been given first on the key aptamer properties and the process of their production (with its newer iterations), contrasting each of them with that of monoclonal antibodies. Possible manifold applications afforded due to unique aptamer characteristics are also discussed. A keen review is further provided on the design, development and use of fluorescent aptamers in bioimaging, sequencing or profiling, and treatment of pathogenic bacteria and tumor cells.

The identification and molecular characterization of cellular hierarchies in complex tissues is key to understanding both normal cellular homeostasis and tumorigenesis. The mammary epithelium is a heterogeneous tissue consisting of two main cellular compartments, an outer basal layer containing myoepithelial cells and an inner luminal layer consisting of estrogen receptor-negative (ER⁻) ductal cells and secretory alveolar cells (in the fully functional differentiated tissue) and hormone-responsive estrogen receptor-positive (ER⁺) cells. Recent publications have used single-cell RNA-sequencing (scRNA-seq) analysis to decipher epithelial cell differentiation hierarchies in human and murine mammary glands, and reported the identification of new cell types and states based on the expression of the luminal progenitor cell marker KIT (c-Kit). These studies allow for comprehensive and unbiased analysis of the different cell types that constitute a heterogeneous tissue. Here we discuss scRNA-seq studies in the context of previous research in which mammary epithelial cell populations were molecularly and functionally characterized, and identified c-Kit⁺ progenitors and cell states analogous to those reported in the recent scRNA-seq studies.

Virus diseases of strawberry present several complex problems. More than 25 viruses have been described in the genus Fragaria thus far. Here, we describe a novel rhabdovirus, tentatively named strawberry virus 1 (StrV-1), that infects F. ananassa and F. vesca plants. Genomic sequences of three distinct StrV-1 genotypes co-infecting a single F. ananassa host were obtained using combined Illumina and Ion Proton high-throughput sequencing. StrV-1 was transmitted to herbaceous plants via Aphis fabae and A. ruborum, further mechanically transmitted to Nicotiana occidentalis 37B and sub-transferred to N. benthamiana, N. benthamiana DCL2/4i, N. occidentalis 37B and Physalis floridana plants. Irregular chlorotic sectors on leaf blades and the multiplication of calyx leaves seem to be the diagnostic symptoms for StrV-1 on indexed F. vesca clones. StrV-1 was detected in asymptomatic grafted plants and in 49 out of 159 field strawberry samples via RT-PCR followed by Sanger sequencing. The bacilliform shape of the virions, which have a cytoplasm-limited distribution, their size, and phylogenetic relationships support the assignment of StrV-1 to a distinct species of the genus Cytorhabdovirus. Acyrthosiphon malvae, A. fabae and A. ruborum were shown to transmit StrV-1 under experimental conditions.

Combined awareness about the power and limitations of bioinformatics and molecular biology enables advanced research based on high-throughput data. Despite an increasing demand for scientists with a combined background in both fields, the education in dry lab and wet lab is often separated. This work describes an example of integrated education with focus on genomics and transcriptomics. Participants learn computational and molecular biology methods in the same practical course. Peer-review is applied as a teaching method to foster cooperative learning of students with heterogeneous backgrounds. Evaluation results indicate acceptance and appreciation of this approach.

This study investigated whether biogas reactor performance, including microbial community development, in response to a change in substrate composition is influenced by initial inoculum source. Test reactors were first started with two different inocula and operated with the same grass-manure mixture for more than 120 days. These reactors initially showed great differences depending on inoculum source, but eventually showed similar performance and overall microbial community structure. At the start of the present experiment, the substrate was complemented with milled feed wheat, added all at once or divided into two portions. The starting hypothesis was that process performance depends on initial inoculum source and microbial diversity, and thus that reactor performance is influenced by the feeding regime. In response to the substrate change, all reactors showed increases and decreases in volumetric and specific methane production, respectively. However, specific methane yield and development of the microbial community showed differences related to initial inoculum source, confirming the hypothesis. The different feeding strategies had however only minor effects on process performance and overall community structure, but still induced differences in the cellulose-degrading community and in cellulose degradation.

The sustainable development of an area is highly dependable on reliable electrical energy supply. Microgrids are important in integrating distributed energy resources (DERs) using power electronic converters. However, microgrid control becomes challenging with the increasing number of distributed generators and loads. With the conventional droop control method, power contributions from DER converters cannot be accurately shared due to a mismatch of line impedances. In this paper, an augmented hierarchical control mechanism is proposed to solve the issues mentioned above. This hierarchical control mechanism consists of primary and secondary controllers. The primary stage utilized the droop controller to improve optimal power flow, mainly for the resistive network. The secondary stage is based on an improved methodology to compensate for the voltage and frequency variations during small and large signal disturbances. Moreover, the modelling and analysis for PMSG-based wind energy conversion systems are also presented. The response of the primary controller for the active and reactive power sharing is investigated. The analysis emphasizes the demonstration of optimal power-sharing under normal and abnormal conditions for the considered load. Finally, the suggested robust controller's performance is evaluated in MATLAB environment and simulation results show the proposed scheme's superiority under different operating conditions.

With the targets of petroleum exploration transferred to the deep and ancient strata, abundant oil and gas resources have been found in the Lower Paleozoic and older strata in central and western China. Due to complex evolutionary processes including multiple episodes of hydrocarbon accumulation and ubiquitously accompanied by secondary alterations, significant uncertainties were remained for the generation time and accumulation processes of these revealed petroleum. In this paper, relative pure Re and Os elements existing in the asphaltene fractions of Lower Cambrian solid bitumen collected from the Guangyuan area, western Sichuan Basin, SW China and another Middle–Lower Ordovician heavy oils in the Aiding area of the Tahe oilfield in the Tarim Basin, NW China were successfully obtained by the sample pre-treatments, and Re–Os isotopic analysis was subsequently carried out for the dating of these two petroleum. The Re–Os isotopic composition indicates a generation time of Guangyuan bitumen to locate between 572 Ma and 559 Ma, corresponding to the late Sinian period of Neoproterozoic era. By the means of Re–Os isochron ages, initial 187Os/188Os ratios, and carbon isotopic compositions, the Lower Cambrian bitumen is supposed to be originated from source rocks of the Doushantuo Formation in the Sinian strata and subsequently migrated into the reservoirs of Dengying Formation. These previously reserved petroleum had been transformed to present bitumen by the destruction of reservoirs caused by tectonic uplift. The Re–Os dating results of Middle–Lower Ordovician heavy oil of Tarim Basin supposed that it was formed between 450 Ma to 436 Ma, corresponding to the Late Ordovician–Early Silurian system, and the generated petroleum is likely to migrate into the Middle–Lower Ordovician karst reservoirs to form early oil reservoirs. With tectonic uplift, these oil reservoirs were degraded and reformed to be present heavy oil reservoirs.

High-penetration of Distributed Energy Resources (DER) in low voltage distribution grids, mainly photovoltaics (PV), might lead to overvoltage in the point of common coupling. Volt-VAr is one of the common control functions for DER power converters used to enhance the stability and the reliability of the voltage in the distribution system and, thus, fulfilling the network operator requirements. In this study, a centralized algorithm will provide local Volt-VAr control parameters to each PV inverter, based on the electrical grid characteristics where each equipment is installed. Since accurate information of grid characteristics is typically not available, the parametrization of the electrical grid is done using power meter data in DER location and a voltage sensitivity matrix. The algorithm has different optimization modes to both minimize voltage deviation and line current. In order to validate the effectiveness of the algorithm and its deployment in real infrastructure, it has been tested in an experimental setup with PV emulators in a set of 5-day tests. Volt-VAr control algorithm successfully adapted its parameters based on grid topology and PV inverter characteristics, achieving a voltage reduction up to 25% of the allowed voltage deviation.

The study investigates the determinants of mobile Internet banking adoption among Gen-Y in Malaysia. Align the issue of the study and research objectives, and the study underpinned Technology Acceptance Model (TAM) as the main guideline or a blueprint to analyze the research model. The study applied survey research design and analyzed using Structural Equation Modelling (SEM) under the PLS-SEM technique with SmartPLS 2.0. A total of 358 mobile internet banking users in Malaysia were random proportional selected as respondents and analyzed. Results from the partial least square structural equation modeling (PLS-SEM) revealed that perceived ease of use, perceived usefulness, facilitating condition, and personal innovativeness in IT have significantly influenced the attitude of mobile internet banking adoption in Malaysia. Additionally, perceived ease of use and facilitating conditions found to have a significant influence on the perceived usefulness of Mobile Internet Banking. Lastly, facilitating conditions and personal innovativeness in IT are significantly influence the perceived ease of use of mobile internet banking among Gen-Y in Malaysia

Risk-based redispatch optimization is proposed as a methodology to support the Transmission System Operator (TSO) with preventive remedial actions obtained by extending the security constrained unit commitment/economic dispatch with constraints resulting from the risk assessed for the power system. Although being heuristic, the methodology is based on comprehensive dynamic security assessment as time-domain simulations are used, allowing to express the degree of all types of instabilities, e.g., caused by contingencies, in monetary terms. Therefore, the risk is assessed as the expected value of the cost incurred by the TSO. Such approach forms a new pathway to including risk in planning procedures already used by TSOs. Results obtained for the IEEE39 dynamic power system, with costs assigned to load shedding and generator tripping due to single transmission lines short-circuits, are shown as a reference case.

Although different assessments and evaluations of Dual-Miller cycle performed, specified output power and thermal performance associated with engine determined. Besides, multi objective optimization of thermal efficiency, Ecological Coefficient of performance ( ) and Ecological function ( ) by the mean of NSGA-II technique and thermodynamic analysis performed. The Pareto optimal frontier obtaining the best optimum solution is chosen by fuzzy Bellman-Zadeh, LINMAP, and TOPSIS decision-making techniques. Based on the results, performances of dual-Miller cycles and their optimization are improved.

The heat and matter transfer during glucose catabolism in living systems and their relation with entropy production are a challenging subject of the classical thermodynamics applied to biology. In this respect, an analogy between mechanics and thermodynamics has been performed via the definition of the entropy density acceleration expressed by the time derivative of the rate of entropy density and related to heat and matter transfer in minimum living systems. Cells are regarded as open thermodynamic systems that exchange heat and matter resulting from irreversible processes with the intercellular environment. Prigogine’s minimum energy dissipation principle is reformulated using the notion of entropy density acceleration applied to glucose catabolism. It is shown that, for out-of-equilibrium states, the calculated entropy density acceleration is finite and negative and approaches as a function of time a zero value at global thermodynamic equilibrium for heat and matter transfer independently of the cell type and the metabolic pathway. These results could be important for a deeper understanding of entropy generation and its correlation with heat transfer in cell biology with special regard to glucose catabolism representing the prototype of irreversible reactions and a crucial metabolic pathway in stem cells and cancer stem cells.

Transposable elements (TEs) are repetitive elements which make up around 45% of the human genome. A class of TEs known as SINE-VNTR-Alu (SVA) demonstrate the capacity to mobilise throughout the genome, resulting in SVA polymorphisms for presence or absence within the population. Although studies have previously highlighted the involvement of TEs within neurodegenerative diseases, such as Parkinson’s disease and amyotrophic lateral sclerosis (ALS), however the exact mechanism has yet to be identified. In this study we used whole genome sequencing and RNA sequencing data of ALS patients and healthy controls from the New York Genome Center ALS Consortium, to elucidate the influence of reference SVA elements on gene expression genome-wide within central nervous system (CNS) tissues. To investigate this, we applied matrix expression quantitative trait loci analysis and demonstrated that reference SVA insertion polymorphisms can significantly modulate the expression of numerous genes, preferentially in the trans position, and in a tissue-specific manner. We also highlight that SVAs significantly regulate mitochondrial genes as well as genes within the HLA and MAPT loci, previously associated within neurodegenerative disease. In conclusion, this study continues to bring to light the effects of polymorphic SVAs on gene regulation and further highlights the importance of TEs within disease pathology.

Zinc is an important nutrient for plant growth and development. Its availability is influenced by zinc solubilizing microbes (ZSM). Effects of commonly promoted agronomic practices on the abundance of ZSM are so far not well understood. In this study, we assessed the effects of farmyard manure (FYM) application, either sole, or in combination with residue and/or inorganic fertilizer inputs on ZSM community structure using 11 treatments in a long-term (17 years) integrated soil fertility management experiment located in western Kenya, The study was conducted in 2019. Bacterial and fungal community composition (at 0-15 cm depth) was evaluated by amplicon sequencing on an Illumina Miseq platform following the manufacturer’s guidelines. Microbial diversity indices (Shannon, Simpson and Chao1) and statistical analyses were computed using R project packages. Putative ZSM (i.e., the ZSM generally considered to possess the zinc solubilizing capabilities) were clustered in two major clades based on either application or no application of FYM. Sole application of FYM significantly (P<0.05) increased the abundance of several ZSM under maize-tephrosia rotation. In addition, systems with combined application of FYM with other inputs generally showed significantly increasing trends for some ZSM under maize-tephrosia rotation. Moreover, combined application of FYM and P rather than P only significantly increased abundance of some ZSM under maize-monocropping systems. Furthermore, besides affecting ZSM abundance, soil chemical variables involving soil organic carbon (SOC), total N and Olsen P significantly increased with FYM application. This study indicated that management practices like application of FYM that increase SOC, and other soil chemical parameters, also/concomitantly increase ZSM abundance; implying enhanced capacities for microbial-linked zinc availability.

Whole-genome sequencing (WGS) was used for genomic characterization of 110 strains of Listeria innocua isolated from 23 cattle farms, 8 beef abattoirs, and 48 retail outlets in Gauteng province, South Africa. In silico multilocus sequence typing (MLST) was used to identify the isolates' sequence types (STs). BLAST-based analyses were used to identify antimicrobial and virulence genes. The study also linked the detection of the genes to the origin (sources and types of samples) of the L. innocua isolates. The study detected 12 STs, 13 resistance genes, and 23 virulence genes. Of the 12 STs de-tected, ST637 (26.4%), ST448 (20%), 537 (13.6%), and 1085 (12.7%) were predominant, and the frequency varied significantly (P<0.05). All 110 isolates of L. innocua were car-riers of one or more antimicrobial resistance genes, with resistance genes lin (100%), fosX (100%), and tet(M) (30%) being the most frequently detected (P<0.05). Of the 23 virulence genes recognized, 13 (clpC, clpE, clpP, hbp1.svpA, hbp2, iap/cwhA, lap, lpeA, lplA1, lspA, oatA, pdgA, and prsA2) were found in all 110 isolates of L. innocua. Overall, diversity and significant differences were detected in the frequencies of STs, resistance, and virulence genes according to the origins (source and sample type) of the L. innocua isolates. This, being the first genomic characterization of L. innocua recovered from the three levels (farm, abattoir, and retail outlets) of the beef production system in South Africa, provides data on the organism's distribution and potential food safety implications..

Cyclic vomiting syndrome (CVS) is a frequently disabling condition defined by severe, discrete, stereotypical episodes of nausea and vomiting. In our previous report [1], a candidate gene list was evaluated in a group of 80 unrelated participants with CVS with extensive genetic sequencing (whole exome/genome). Twenty-two good candidate genes for CVS association were identified, from which a cellular model of aberrant cation transport and energy metabolism was proposed. Herein, we present additional clinical information on those 80 participants, including eight case reports to highlight general principles and clinical practices. Our participants demonstrate substantial phenotypic and genotypic heterogeneity in CVS, including a propensity for specific co-morbidities in the participants and relatives, evolution towards episodes in which vomiting is less apparent, labeling with “non-organic” diagnoses, multiple genes, polygenic inheritance, and association with variants not designated as Pathogenic. Our case reports illustrate how genetic information can guide clinical management and argue to the high clinical utility of appropriate genetic testing and analysis in CVS. Expression profiling of our 22 candidate genes suggests an anatomical model in a unit defined by vagal afferents and adjacent cells. Our models are consistent with multiple current hypotheses of CVS and the efficacy of commonly-recommended treatments.

Until the 1950s, developmental dyslexia was defined as a hereditary visual disability, selectively affecting reading without compromising oral or non-verbal reasoning skills. This changed radically after the development of the phonological theory of dyslexia; this not only ruled out any role for visual processing in its aetiology, but also cast doubt on the use of discrepancy between reading and reasoning skills as a criterion for diagnosing it. Here I argue that this theory is set at too high a cognitive level to be explanatory; we need to understand the pathophysiological visual and auditory mechanisms that cause children’s phonological problems. I discuss how the ‘magnocellular theory’ attempts to do this in terms of slowed and error prone temporal processing which leads to dyslexics’ defective visual and auditory sequencing when attempting to read. I attempt to deal with the criticisms of this theory and show how it leads to a number of successful ways of helping dyslexic children to overcome their reading difficulties.

This research paper examines the transformative impact of Artificial Intelligence (AI) on the global journalism industry. The integration of AI technologies, such as machine learning and natural language processing, has drastically changed journalistic practices and media operations. The study aims to understand how AI affects news production, distribution, and ethical considerations within journalism. By providing historical context and reviewing existing literature, this paper situates its analysis within the broader academic discourse. A mixed-methods approach is used for data collection and analysis, ensuring comprehensive and reliable findings. Results indicate that AI tools enhance journalistic efficiency and capabilities but also introduce challenges related to accuracy, authenticity, and editorial judgment. The implications for employment in journalism are significant, necessitating new skills and roles. The discussion interprets these findings in the context of media evolution and ethical standards. This study concludes by advocating for a balanced approach to AI adoption in journalism, emphasizing the importance of ethical guidelines, continuous journalist training, and ongoing research to navigate this evolving landscape.