Magnetoelastic switching in multiferroic nanomagnets with a small voltage is a promising substitute for current charge-based CMOS devices. Here, we study strain-mediated multiferroic majority logic gate by solving Landau-Lifshitz-Gilbert equation and establish an energy- efficient CMOS compatible equivalent circuit analogy to capacitor's I- V characteristics. We can easily simulate nanomagnet logic units using this tool. After that, the circuit is verified by SPICE simulations. Results show that the output voltage polarity is determined by the majority of input voltage polarity with ultralow energy consumption, working similarly to majority logic function. The SPICE circuit model shows ultralow energy consumption because of the conserved dynamic current, which can serve as a promising logic unit, consequently, integrated into large-scale nanomagnetic logic circuits and even a nanomagnetic chip.

Previous studies have established the association of sex with gene and protein expression. This study investigated the association of sex with the abundance of endogenous urinary peptides, using capillary electrophoresis-coupled to mass spectrometry datasets from 2008 healthy individuals and patients with type II diabetes, divided in one discovery and two validation cohorts. Statistical analysis using the Mann-Whitney test, adjusted for multiple testing, revealed 143 sex-associated peptides in the discovery cohort. Of these, 90 peptides were associated with sex in at least one of the validation cohorts and showed agreement in their regulation trends across all cohorts. The 90 sex-associated peptides were fragments of 29 parental proteins. Comparison with previously published transcriptomics data demonstrated that the genes encoding 16 of these parental proteins had sex-biased expression. The 143 sex-associated peptides were combined into a support vector machine-based classifier that could discriminate males from females in two independent sets of healthy individuals and patients with type II diabetes, with an AUC of 89% and 81%, respectively. Collectively, the urinary peptidome contains multiple sex-associated differences, which may enable a better understanding of sex-biased molecular mechanisms and the development of more accurate diagnostic, prognostic or predictive classifiers for each individual sex.

Variation in fitness components can be linked in some cases to variation of key traits. Metric traits that lie at the intersection of development, defense, and ecological interactions may be expected to experience strong environmental selection, informing our understanding of evolutionary and ecological processes. Here, we use quantitative genetic and population genomic methods to investigate disease dynamics in hybrid and non-hybrid populations. We focus our investigation on morphological and ecophysiological traits which inform our understanding of physiology, growth, and defense against a pathogen. In particular, we investigate stomata, microscopic pores on the surface of a leaf which regulate gas exhange during photosynthesis and are sites of entry for various plant pathogens. Stomatal patterning traits were highly predictive of disease risk. Admixture mapping identified a polygenic basis of disease resistance. Candidate genes for stomatal and disease resistance map to the same genomic regions, and are experienceing positive selection. Genes with functions for guard cell homeostasis, the plant immune system, components of constitutive defenses, and growth related transcription factors were identified. Our results indicate positive selection is filtering genetic variance from one of the parental species maladpated to a novel pathogen, and changing suites of stomatal traits which contribute to disease variation in natural populations.

INTRODUCTIONCharles Bonnet Syndrome(CBS) was first described in 1760 by Naturalist and philosopher Charles Bonnet, who first observed lifelike complex visual hallucinations in his grandfather Charles Lullis after bilateral cataract surgery(1); it was a neurologist George de Morsier who coined the term in 1938 after Charles Bonnet himself developed the condition(2). CBS, also known as ”phantom image”, is characterized by recurrent or persistent complex visual hallucinations in people with a disease of the visual system with intact insight, intellectual function and normal cognitive functioning without primary psychiatric disorders(3,4). With limited knowledge of CBS among physicians, the prevalence of CBS is underreported(4) even though 41-59% of the visually impaired experience elementary visual phenomena, and 11-15% exhibit complex hallucinations, due to a medical condition or artificially produced, such as in preparation for cataract surgery(5,6). The presence of varying inclusion criteria, inconsistent depth of questioning and limited patient disclosure for fear of being ridiculed may all contribute to underreporting(3,5). Visual hallucinations could be a sign of psychiatric disorders, neurological diseases, metabolic abnormalities, and the use or abuse of specific drugs(7). Both elementary forms(3) and complex visual hallucinations are reported in CBS(8); while glaucoma,cataract and age-related macular degeneration are the most common associated disorders, any ophthalmological conditions can lead to CBS(7), especially in significant visual impairment(9). A pituitary adenoma is rarely associated with CBS (10); however, reduced visual acuity or a visual field deficit can occur from the benign tumour’s compressing optic chiasm affecting one or both eyes(11).There are three main theories associated with the pathogenesis of CBS, and these are; the sensory deprivation or deafferentiation theory related to spontaneous excitation due to a loss of visual input to the brain(12), the release theory associated with excessive excitation and the consequent release of visual hallucinations(13,14), and the ”irritative theory” due to distal provocative injuries transmit abnormal input to the visual cortex leading to abnormal excitatory activity to the temporal and occipital lobes(15,16).Charles Bonnet syndrome is treated multifacetedly with pharmacotherapy, psychosocial therapy, maintaining appropriate eye care, and sensory stimulation. Generally, CBS is treated with antipsychotics and antidepressants(5), and in some cases, antiepileptic medications have also been used with variable benefits (17).An 81-year-old blind male presented with a three-year history of visual hallucinations after a recurrence of pituitary macroadenoma. His past psychiatric history is uneventful, and he has intact insight with no cognitive impairment. He improved on a low haloperidol dosage, with a few relapses, when he stops the medications.

The global interest in fatty acids is steadily rising due to their wealth of industrial potential ranging from cosmetics to biofuels. Unfortunately, certain fatty acids, such as monounsaturated C12, cannot be produced cost and energy-efficiently using conventional methods. Biosynthesis of fatty acids using microorganisms can overcome this drawback. However, rewiring a microbe’s metabolome for increased production remains challenging. To overcome this, sophisticated genome-wide metabolic network models have become available. These models predict the effect of genetic perturbations on the metabolism, thereby serving as a guide for metabolic pathways optimization. In this work, we used constraint-based modeling in combination with the algorithm Optknock to identify gene deletions in Escherichia coli that improve the C12 fatty acid production. Nine gene targets were identified that, when deleted, were predicted to increase C12 titers. Targets play a role in anaplerotic reactions, amino acid synthesis, carbon metabolism and cofactor-balancing. Subsequently, we constructed the corresponding (combinatorial) deletion mutants to validate the in silico predictions in vivo. Our highest producer (Δ maeB Δ ndk Δ pykA) reaches a titer of 6.7 mg/L, corresponding to a 7.5-fold increase in C12 fatty acid production. This study demonstrates that model-guided metabolic engineering is a useful tool to improve C12 fatty acid production.

Fermentation monitoring is a powerful tool for bioprocess development and optimisation. On-line metabolomics is a technology that is starting to gain attention as a bioprocess monitoring tool, allowing the direct measurement of many compounds in the fermentation broth at a very high time resolution. In this work, targeted on-line metabolomics was used to monitor 40 metabolites of interest during three Escherichia coli succinate production fermentation experiments every 5 minutes with a triple quadrupole mass spectrometer. This allowed capturing high time resolution biological data that can provide critical information for process optimisation. For 9 of these metabolites, simple univariate regression models were used to model compound concentration from their on-line mass spectrometry peak area. These on-line metabolomics univariate models performed comparably to vibrational spectroscopy multivariate PLS regressions models reported in the literature, which typically are much more complex and time consuming to build. In conclusion, this work shows how on-line metabolomics can be used to directly monitor many bioprocess compounds of interest and obtain rich biological and bioprocess data.

Changes in land use and climate change have been reported to reduce biodiversity of the environment and human microbiota. This may lead to inadequate and unbalanced stimulation of immunoregulatory circuits and ultimately, to clinical diseases, such as asthma and allergies. We summarised available empirical evidence on the role of inner and outer layers of biodiversity in the development of asthma, asthma-like symptoms, and allergic sensitization. We conducted a systematic search in SciVerse Scopus, PubMed MEDLINE, and Web of Science up to 5 December 2022 to identify relevant studies assessing the relations between inner and outer layers of biodiversity and the risk of asthma, wheezing and/or allergic sensitization. We applied random-effects models to calculate summary effect estimates. The protocol was registered in PROSPERO (CRD42022381725). Of 75 studies, 20 provided effect estimates for the meta-analysis showing an association between high outer layer biodiversity and a low risk of asthma development (Shannon diversity index: OR (95% CI) = 0.77 (0.55; 1.06); bacterial richness: OR (95% CI) = 0.74 (0.57; 0.96)). Although the evidence on the effect of inner layer biodiversity suggested that bacterial diversity was slightly higher among individuals with asthma, there was no clear evidence of a significant association between inner layer biodiversity and the risk of asthma, wheezing or allergic sensitization. The weight of evidence suggests that environmental exposure to high biodiversity may protect from the development of asthma, whereas there was no consistent evidence on any association between inner layer biodiversity and asthma, wheezing or allergic sensitization.

Background: Modelling atopic dermatitis (AD) in vitro is paramount to understand the disease pathophysiology and identify novel treatments. Previous studies have shown that the Th2 cytokines IL-4 and IL-13 induce AD-like features in keratinocytes in vitro. However, it has not been systematically researched whether the addition of Th2 cells, their supernatants or a 3D structure are superior to model AD compared to simple 2D cell culture with cytokines. Methods: For the first time, we investigated what in vitro option most closely resembles the disease in vivo based on single-cell RNA sequencing data (scRNA-seq) obtained from skin biopsies in a clinical study and published datasets of healthy and AD donors. In vitro models were generated with primary fibroblasts and keratinocytes, subjected to cytokine treatment or Th2 cell cocultures in 2D/3D. Gene expression changes were assessed using qPCR and Multiplex Immunoassays. Results: Of all cytokines tested, incubation of keratinocytes and fibroblasts with IL-4 and IL-13 induced the closest in vivo-like AD phenotype which was observed in the scRNA-seq data. Addition of Th2 cells to fibroblasts failed to model AD due to the downregulation of ECM-associated genes such as POSTN. While keratinocytes cultured in 3D showed better stratification than in 2D, changes induced with AD triggers did not better resemble AD keratinocyte subtypes observed in vivo. Conclusions: Taken together, our comprehensive study shows that the simple model using IL-4 or IL-13 in 2D most accurately models AD in fibroblasts and keratinocytes in vitro, which may aid the discovery of novel treatment options.

Self-efficacy (SE) is recognized as a main determinant of successful performance and may mediate the relationship between psychological performance enhancement techniques and sports performance. Identifying the cognitive–motor processes of superior performance can provide crucial information not only for accelerating the motor learning process but also for enhancing motor performance. The frontal midline theta power (Fmθ) reflects the level of top–down attention allocated to achieve a desired cognitive–motor behavior. Thus, this study investigated the effect of SE on the performance and Fmθ of golf players and explored the association between the objective measures of cortical dynamics and SE. Thirty-four skilled golfers were recruited (within-subject design) to perform 60 putts, and their electroencephalographic activity was recorded during the task. The SE score was measured using a visual analog scale ranging from 0 to 10 before each putt. Paired t test results revealed that trials with higher SE scores were associated with a higher putting success rate than trials with lower SE scores (53.3% vs 46.7%). Moreover, trials with higher SE scores were preceded by lower Fmθ than trials with lower SE scores (4.49 vs. 5.18). These findings suggested that higher SE was followed by less top–down attentional control, a characteristic of automatic processing, leading to better putting performance. Our findings support Bandura’s SE theory and elucidate the intermediate processes of SE by investigating the effect of the anticipation of outcomes on sports performance and attentional control before putting.

Background Recombinant factor IX Fc fusion protein (rFIX-Fc) is an extended half-life (EHL) factor concentrate administered to haemophilia B patients. So far, a population pharmacokinetic (PK) model has only been published for patients ≥12 years of age. Aim Assess the predictive performance of the published rFIX-Fc population PK model for patients of all ages and develop a model that describes rFIX-Fc PK using real world data. Methods We collected prospective and retrospective data from patients with haemophilia B (FIX activity level ≤5 IU/dL) treated with rFIX-Fc and included in the OPTI-CLOT TARGET study (NTR7523) or United Kingdom (UK)-EHL Outcome Registry (NCT02938156). Predictive performance was assessed by comparing predicted with observed FIX activity levels. A novel population PK model was constructed using nonlinear mixed-effects modelling. Results Real world data was obtained from 37 patients (median age: 16 years, range 2-71) of whom 14 were <12 years of age. Observed FIX activity levels were significantly higher than levels predicted using the published model, with a median prediction error (PE) of -48.8%. The novel model showed a lower median PE (3.4%) and better described rFIX-Fc PK, especially for children <12 years of age. In the novel model, an increase in age was correlated with a decrease in clearance (p<0.01). Conclusion The published population PK model significantly underpredicted FIX activity levels. The novel model better describes rFIX-Fc PK, especially for children <12 years of age. This study underlines the necessity to strive for representative population PK models, thereby avoiding extrapolation outside the studied population.

This study applies the generative adversarial network-based optimization approach to site selection and capacity determination of energy storage device in a power grid. Through the combination of modified long short-term memory and generative adversarial networks, the proposed method enhances the learning capability for the decision support of energy storage allocation. This method excels at the utilization of modified long short-term memory to ensure a better data-generation and data-discrimination in a generative adversarial network, enabling the achievement of effective data learning and deduction. To validate the feasibility of the proposed approach, a practical system as well as an example system are both examined under different scenarios, where the placement cost, peak load, and voltage deviation are all concerned. Test results gained from this study are beneficial for energy storage industry applications. In this study, a novel approach is proposed for site selection and capacity determination of energy storage devices in power grids by applying a generative adversarial network-based optimization method. The proposed approach combines modified long short-term memory and generative adversarial networks to enhance the learning capability for decision support of energy storage allocation. Specifically, the modified long short-term memory improves the data-generation and data-discrimination in the generative adversarial network, leading to effective data learning and deduction. To demonstrate the feasibility of our proposed approach, a practical system as well as an example system are tested under different scenarios, where the placement cost, peak load, and voltage deviation are all taken into considerations. Test results indicate the feasibility of the method, providing valuable insights for the energy storage industry.

In January of 2017, the Department of Health and Human Services began allowing states to enforce work requirements for Medicaid recipients. In the past, these types of requirements have had negative effects on access to safety net programs. We reviewed the literature for articles that looked at the effects on the health of Medicaid recipients who were impacted by work requirements. We identified nine texts, but the methods and evidence varied in quality. The research we found on this subject is done by academic universities and paid for by some private, but mostly public funds. The included texts describe effects on different groups of people, mostly those who are vulnerable or suffering from acute and chronic disease. With so little evidence at this time, we cannot clearly say if work requirements have positive or negative impacts on health. However, we found that there is an opportunity for researchers to anticipate the impact on health, so they can design and carry out studies that measure any likely changes.

Background Cancer is the leading cause of death among Asian Americans, who face barriers to cancer care. Cancer supportive care needs among Asian Americans remain understudied. Methods We recruited 47 Asian American adults with colorectal, liver, or lung cancer who spoke Chinese, English, or Vietnamese, and were starting or undergoing cancer treatment. We assessed cancer supportive care needs in four domains: cancer information, daily living, behavioral health, and language assistance. Hierarchical cluster analysis was used to identify clusters of participants based on their need profiles to further examine the association between need profiles and quality of life (QoL) assessed by the Functional Assessment of Cancer Therapy (FACT-G). Results Participants (mean age=57.6) included 72% males and 62% spoke English less than very well. Older participants (age >65) and those with annual income <$50K reported higher daily living needs. Men and younger participants (age <50) reported higher behavioral health needs. We found 3 clusters displaying distinct cancer supportive need profiles: Cluster 1 (28% of the sample) displayed high needs across all domains; Cluster 2 (51%) had low overall needs; and Cluster 3 (21%) had high needs for cancer information and daily living. Cluster 1 participants reported lowest QoL. Conclusions Cancer supportive care needs among Asian American patients with colorectal, liver and lung cancer were associated with patient characteristics and QoL. Understanding cancer supportive care needs will inform future interventions to improve care and QoL for Asian American cancer patients.

Spacecraft magnetic field measurements are frequently degraded by stray magnetic fields originating from onboard electrical systems. These interference signals can mask the natural ambient magnetic field, reducing the quality of scientific data collected. Traditional approaches involve positioning magnetometers on mechanical booms to minimize the influence of the spacecraft's stray magnetic fields. However, this method is impractical for resource-constrained platforms, such as CubeSats, which necessitate compact and cost-effective designs. In this work, we introduce an interference removal technique called Wavelet-Adaptive Interference Cancellation for Underdetermined Platforms (WAIC-UP). This method effectively eliminates stray magnetic field signals using multiple magnetometers, without requiring prior knowledge of the spectral content, location, or magnitude of the interference signals. WAIC-UP capitalizes on the distinct spectral properties of various interference signals and employs an analytical method to separate them from ambient magnetic field in the wavelet domain. We validate the efficacy of WAIC-UP through a statistical simulation of randomized 1U CubeSat interference configurations, as well as with real-world magnetic field signals generated by copper coils. Our findings demonstrate that WAIC-UP consistently retrieves the ambient magnetic field under various interference conditions and does so with orders of magnitude less computational time compared to other modern noise removal algorithms. By facilitating high-quality magnetic field measurements on boomless platforms, WAIC-UP presents new opportunities for small-satellite-based space science missions.

The Effects of Physical Parameters of Buildings on Energy Consumption Fatemeh Bateni**Department of Architecture and Urbanism Engineering, Qazvin Islamic Azad University, Qazvin, IranEmail: fatemeh.bateni87@gmail.comAbstractNowadays, over 40% of energy consumption in the world occurs in the building sector. Given such a significant impact, designing buildings with long-term energy efficiency is of substantial importance. The purpose of the present study is to assess the thermal performance of a vast spectrum of parameters, including building orientation, window-to-wall ratio, transparency, and geographical direction in a cold and temperate climate. To this end, a case study is conducted on eight samples of prevalent building plans in Ilam city, located in the west of Iran. The results of the data analysis were written as mathematical functions, and ultimately, the proposed pattern function related to the four selected criteria of the optimal pattern was presented by comparing the functions of thermal comfort and natural lighting. In conclusion, square-shaped plans are the most optimal, and higher length-to-width ratios lead to higher energy consumption.Keywords : Physical Parameters; Residential Buildings; Energy Consumption; Square-shaped Plans; Building DesigningIntroductionIn every country, the building sector is responsible for more than one third of the total energy consumption (1). As a result, the amount and methods of energy consumption in buildings have always been a concern in construction projects. However, such a concern can be considerably mitigated by using modern technologies and adhering to the existing construction standards. In many countries, the shape and form of buildings are chosen based on climate conditions, which in turn affect how energy is consumed; in other words, the forms of buildings are selected through strategies that are suitable to the climate (1). Accordingly, the most important related indices include the type of materials, building orientation, thickness of walls, openings, and type of ceiling (2, 3). Attention has been paid to these indices, and today, architects also take them into account when reviewing the rules and changes to optimize energy consumption and lessen the consequences of unregulated consumption.The direct or indirect consumption of fossil fuels in buildings emits a large amount of CO2 into the atmosphere. Contemplating and recognizing the means to reduce CO2 production and consume energy in an optimal manner are instrumental to confronting the incorrect use of energy (4-6). This amount of emission amounts to nearly 40% of the entire CO2 (i.e., 842 million tonnes per year) (7), which entails 36% of the global energy consumption (8-10). Today, energy saving refers to the implementation of solutions specified under various regulatory frameworks (11, 12). Global guidelines on the energy performance of buildings require the adoption of tools for calculating energy consumption performance, applying the minimum performance standards during the design process, operating the construction, licensing the building, and ensuring control over heating and cooling systems (13-15). In fact, interior thermal comfort is considered the main driver of energy consumption in buildings (11, 16, 17), which can be of importance in two areas, including the type of consumed and the physical factors involved in energy consumption and suitable efficiency.Due to the inevitable degradation in their physical performance, many of the existing buildings are unlikely to be regarded as “green” buildings in terms of energy consumption. The physical performance of buildings should be specified in detail prior to any construction or system maintenance operations (18-20). There are numerous studies conducted on areas such as consumer behaviour, construction operation and system repair and maintenance, envelope function, lighting, hot water and heating systems, building materials, and HVAC (heating, ventilation, and air conditioning); these studies have offered a variety of models on energy reinforcement strategies and economic assessment of different types of existing structures in residential and non-residential buildings (21, 22).In Europe, the AR ranking, which assesses the physical performance of buildings, is used to enhance the energy performance of degraded buildings. This method provides reliable information regarding how energy is consumed or wasted in these types of buildings, with the ultimate purpose of reducing energy consumption and specifying the effect of each physical dimension on the amount of energy consumption. Nonetheless, collecting consistent data on the existing buildings is difficult, and the energy performance assessment of these buildings is commonly done using simplified data obtained from refined data and tables from different sources (23, 24). The same approach is adopted in this study.Numerous studies conducted in this area have examined optimal building designs; therefore, many more passive solutions have been proposed regarding energy reduction and efficiency in the building sector. Studies have shown that the energy performance of buildings depends on five factors, including weather, building design, urban geometry, system efficiency, and residents’ behaviour (25). According to evidence, the architectural design helps to reduce energy consumption (26, 27). In design and construction principles, inactive design strategies and bioclimatic designs are the main solutions to minimize energy demand (28). Studies have classified building designs into six parameters, which include the shape of the building, transparent surfaces, orientation of the building, thermal-physical features, building materials, and distances between buildings (29, 30).Clearly, energy source provision is one of the future concerns of mankind. The essential actions to mitigate these concerns may include controlling energy consumption, using clean energies, and employing modern knowledge for constructions with minimum energy consumption (31).In the present study, the design and construction of buildings in cold, temperate, and Mediterranean climates are highlighted. The empirical designing and constructing of buildings via different materials has, in many cases, offered substantially suitable potentials to create buildings that consistently involve optimal energy consumption. These indices have been mostly related to available materials, consistency between the climate and buildings, and the method of using renewable energies through building architecture, acquired through experiment over time. Given changes in lifestyle, fuel diversity, economic costs, family behaviour, available materials, and climate change, it appears that previous methods cannot meet the requirements of optimal energy consumption. Given such a fact, it is necessary to employ the technology of today’s world to optimize these indices and make use of new energy consumption methods in buildings. All in all, reducing energy consumption in buildings requires accurate, practical answers to the issue. As a result, the present study seeks to examine the effect of buildings’ physical features on the extent of energy consumption; further, different types of buildings and prevalent architectures in this study were compared to calculate energy consumption in various forms and provide suitable strategies for optimizing energy consumption in these buildings.Materials and MethodsThe present research is an applied, design-based study conducted using the analytical approach. The purpose of the study was to evaluate the physical parameters of residential buildings with the prevalent edge ratios in Ilam City – located in Iran – in order to provide an optimal pattern relative to the assessed parameters. Accordingly, eight prevalent residential building plans with the same total area (156 m2) were taken into account (Samples A, B, C, D, E, F, G, and H).Generally, the A/C and lighting systems in a residential building account for 40% and 11% of the total energy consumption, respectively. The eight samples in this study were examined in terms of thermal performance and lighting of the entire building. The physical characteristics of buildings, such as materials and the type of openings, were considered the same across all eight samples in the data analysis. Materials used in this study are as follows:

The representation of an explicit solution to the Prabhakar fractional differential delayed system is studied employing the far-famed Laplace transform technique. Second, the existence uniqueness of the solution is debated together with the Ulam-Hyers stability of a semilinear Prabhakar fractional differential delayed system. Thirdly, the necessary and sufficient circumstances for the controllability of linear Prabhakar fractional differential delayed system are determined by describing the Gramian matrix. A sufficient circumstance for the relative controllability of a semilinear Prabhakar fractional differential delayed system is studied via the Krasnoselskii's fixed point theorem. Numerical examples are offered to verify the theoretical findings.

Numerous biodiversity–ecosystem functioning (BEF) experiments have shown that plant community productivity typically increases with species diversity. In these studies, diversity is generally quantified using metrics of taxonomic, phylogenetic, or functional differences among community members. Research has also shown that the relationships between species diversity and functioning depends on the spatial scale considered, primarily because larger areas may contain different ecosystem types and span gradients in environmental conditions, which result in a turnover of the species set present locally. A fact that has received little attention, however, is that ecological systems are hierarchically structured, from genes to individuals to communities to entire landscapes, and that additional biological variation occurs at levels of organization above and below those typically considered in BEF research. Here, we present cases of diversity effects at different hierarchical levels of organization and compare these to the species-diversity effects traditionally studied. We argue that when this evidence is combined across levels, a general framework emerges that allows the transfer of insights and concepts between traditionally disparate disciplines. Such a framework presents an important step towards a better understanding of the functional importance of diversity in complex, real-world systems.

As a source of information on species’ geographic distributions, macroecologists and biogeographers have had to rely on expert-derived range maps to study biodiversity patterns at large scales. In addition to being biased towards well-studied taxa and subjective by nature, such maps suffer from a lack of consistency in how species’ absences are treated within the wider distribution. Using the finer resolution of the Interim Biogeographic Regionalization for Australia (subregions) and example sets of Australian species as study system, we developed a reproducible, data-driven approach to map the extent of occurrence (EOO) of hundreds—or even thousands—of species by combining presence-only data and subregions (i.e., non-equal-sized operational units that represent homogenous areas of unique environmental features) within a unifying quantitative framework. From data-driven and expert-derived range maps for 533 birds, species richness’ estimates differ at three biogeographical scales—whit bias (mean error) at coarser resolution (ecoregion) being half that at subregional scale—and the spatial association between pairs of these birds’ presence-absence maps vary from nearly zero to almost one (representing such pattern almost either differently or identically, respectively). Holes within the wider distribution of the EOO maps for pairs of amphibians, mammals, reptiles, and plants seem to respond to the demarcation of different subpopulations over Australia rather than causing an underestimation of a species’ empirical distribution. These results demonstrate that this approach can reliably map EOO of species whose distributions aligns with three broad types of geographic patterns (wide-range, habitat-specialists, and range-restricted species). This alternative to expert-derived range maps can serve as a basis for more robust, data-driven studies of biogeographic biodiversity patterns, thus improving our understanding and conservation efforts of global biodiversity.

This study aimed to determine the effects of adverse childhood experiences and childhood experiences on adolescents’ psychological resilience and Cognitive Emotional Behavioral regulation. Four hundred thirty-three(n:433) students (18-21 years old) attending a Vocational School of a University in Turkey completed online questionnaires using the Childhood Experiences Scale, the Cognitive Emotion Regulation Scale, the Adult Resilience Scale, and the Negative Childhood Experiences Scale-Turkish version. In the study, it is seen that the psychological resilience of adolescents differs according to age. No significant difference was found between men and women in the study. When cognitive-emotional regulation strategies are examined, it is seen that 18-year-old adolescents are more likely to blame- others than 19- and 20-year-old adolescents. Although there were no differences in psychological resilience in the study, differences were obtained between women and adolescents regarding cognitive and emotional regulation. It was found that female adolescents used the strategies of “self-blame, blame-others, rumination, catastrophizing, and positive refocusing,” which are among the Cognitive Emotional Regulation Strategies more than male adolescents. It has been determined that male adolescents use ” Putting into perspective ” more. As a result of regression analysis, differences in childhood experiences and psychological resistance were obtained according to age. The psychological resistance of 20 -year -old adolescents with a high score of submissiveness, threat, and unvalued was found to be high. In our study, a positive relationship was observed between rumination and adolescents who had an experience of being unvalued and submissive from their childhood experiences. In contrast, those who had less adverse childhood experiences used rumination more.

By multiplying with the continuous factor (CF), the conventional Class- F / F - 1 , Class-J power amplifier (PA) can be expanded to their corresponding continuous modes, resulting in a great degree of freedom for broadband design. However, this method can hardly apply to other types of PAs. In view of this problem, the continuous mode is deeply analyzed from the perspective of equation solving for the first time, and a general theory for high-efficiency broadband continuous PA design is proposed. In this theory, the continuous impedance space does not rely on a mapping relationship achieved by multiplying with the CF, but on a direct solution of the high-efficiency equations to obtain the broadband design space. This approach is simpler and has the potential to provide greater design space. As a validation, this theory is used for the analysis of Class-E PAs and a new continuous Class-E (NC-E) PA is presented. With knee-point voltage and finite harmonics taken into account, this type of PA greatly expands the broadband design space of Class-E PAs, and also has the advantage of harmonic matching. The NC-E PA is designed and manufactured using GaN HEMT CGH40010F, which achieves 40.6∼41.6dBm output power and 66.2%∼74.2% drain efficiency (DE) in the frequency band of 2.5-3.8GHz.

Recently hydraulic and mechanical-based aircraft systems are replaced by electrical-based ’on board aircraft systems’ because of their various advantages like less volume and weight, and reliability. So electrical power system architecture needs to be modified. In spacecraft, a major volume is utilised for the electrical subsystem. The main requirements of the electrical power system of spacecraft are better reliability, less volume and weight, and improved power efficiency. Separate power-generating sources are used for propulsion and various auxiliary systems. Solar-based generation, nuclear-based generation, and fuel cells are some electrical energy sources used in aircraft. More reliable power generation techniques are required for long-duration space missions. The multiphase alternator is a better choice for reliable power generation. Another constraining factor for space power systems is volume and weight because of less space availability in the aircraft. Considering these constraining factors very high power density alternators are suitable for space power systems. Hence, High-Speed Homo Polar Inductor Alternator (HSHIA) is the most suitable candidate. High-speed operation up to 1 lakh RPM is possible with this machine due to its better power density and the special structure of the rotor. This machine already finds application in pulse charging as well as for energy storage by NASA and certain defense organizations. For studying its suitability for auxiliary power generation, a performance analysis is to be carried out. In HSHIA the performance is classified into three levels such as magnetic, electrical, and thermal. This paper presents the electrical performance analysis of HSHIA with different load conditions using the 3 -D Finite Element Method.

Variable supply voltage-clustered voltage scaling (VS-CVS) is an effective way to decrease power consumption without compromising performance. One of the major challenges in VS-CVS design is that level converting flip-flops(LCFFs) not only need to have low power consumption but also high performance. In this paper, we propose two new structures of LCFF: the data branch sharing LCFF based on conditional charging (DBS-LCFFCC) and the data branch sharing LCFF based on precharging (DBS-LCFFP).The new structures adopt a data branch sharing scheme to improve the speed of the circuit as well as to reduce the number of transistors. Based on simulation results using HSPICE with PTM 32nm CMOS technology, the proposed LCFFs show an improvement of 19.2% to 67.2% and 41.6% to 76.3% in power-delay-product (PDP) at 50% data switching activity, respectively, compared to other advanced LCFFs.

In this paper, for standalone and grid-connected PV systems, a three-phase simplified split-source inverter (SSI) is proposed and controlled using a model-predictive control (MPC). The maximum power point tracking (MPPT) approach used is an incremental conductance method based on a PI controller for both systems. The standalone system is composed of PV modules, a three-phase SSI, and a bidirectional power DC-DC converter that connects a battery bank and a DC-side capacitor. The output AC voltages of SSI are controlled using model-predictive control. The bidirectional power DC/DC converter regulates the DC-link voltage (DCLV). The grid-connected system consists of PV modules, a three-phase SSI, and an AC-side L-filter. The DC-link PI controller generates reference currents for the MPC algorithm. The MPC uses these reference currents to adjust and deliver the PV power to the grid while regulating the DCLV. The PI controllers’ parameters are selected for both systems using the Harris Hawks optimization method. Both PV systems simulation results show that under various operating conditions, they have succeeded in fixing a DCLV and producing a high-quality AC output voltage and current at low THD. Experimental results for the three-phase standalone PV system used to verify the system’s performance.

Psychopathy, as a phenomenon, has been mostly studied forensic concept of the current century. Various studies have linked psychopathy to other concepts such as crimes, aggression, violence, personality. There is another debate around that describe psychopathy as productive for certain profession such as CEOs and Surgeons. Current study aimed to assess the relationship of psychopathy among medical students in Pakistan with reference to demographic characteristics (age, gender). Urdu Psychopathy Scale (Dil & Kazmi, 2016) was used to assess the psychopathy. male and female medical students were approached using convenient sampling. Results revealed that age is not related to psychopathy. Significant gender differences exist with respect to psychopathy, and 4.68% of medical students score 262 or higher. The study provided a way to look into the phenomenon of psychopathy among medical students.