Browse Articles

Distributed generation and shunt capacitor allocation in radial distribution power networks using a hybrid optimization approach

Abstract This article proposes a new hybrid approach for determining the optimal locations and sizes of distributed generation (DG) and shunt capacitor (SC) units in a radial distribution power network (RPDN). The hybrid framework is introduced, integrating the global search competency of the Whale Optimizer Algorithm (WOA) with the local search proficiency of the Osprey Optimizer Algorithm (OOA) to achieve a better quality solution for the simultaneous DG/SC allocation problem. The hybrid technique assesses its efficacy for different combinations of DG and SC unit allocations on the different-sized RDPNs, including 33-bus, 69-bus, and 118-bus benchmark systems. The optimization problem is solved for single- and multi-objective functions addressing active power loss (APL) reduction, bus voltage (BV) improvement, and operating cost reduction. For a single unit of DG and SC placement, the APL of the 33-bus RDPN is minimized by 77.29%. In contrast, the second combination involving two units of DG/SC placement achieves a PL reduction of 89.61%. Likewise, the first and second combinations of simultaneous DG/SC integration in the 69-bus RDPN yield 52.67% and 74.97% of APL reduction, respectively. Further, the application of the hybrid algorithm is investigated on the 118-bus RPDN for evaluating its effectiveness and scalability to large power networks. Additionally, for multi-objective problems, the optimized single-unit DG/SC allocation inside the 69-bus RDPN reduces the power losses (PL) by 55.70% and enhances minimum BV to 0.9686 per unit for the operational cost of $15266.78. Moreover, the proposed Hybrid Whale- Osprey Algorithm (HWOA) effectively addressed the load uncertainty in the 69-bus RDPN, minimizing the PL and enhancing the BV above the critical value. The quantitative simulation findings showcase the better PL reduction compared to similar works addressed in the literature, demonstrating the benefits of integrating the exploration and exploitation behaviors of WOA and OOA.

Social movements are transformative agents for biodiversity conservation

Civil society has long been a catalyst for social change by reshaping structures, influencing values, and challenging power dynamics; however, its role in driving transformative change for biodiversity remains underexplored. To address this gap, we analyze 2,801 socio-environmental mobilizations documented in the Environmental Justice Atlas (EJAtlas). These mobilizations produce diverse outcomes that reveal distinct spatial, temporal, and sectoral patterns and proactively and reactively respond to environmental impacts across the globe. Notably, about 40% of these mobilizations occur within the top 30% of global priority lands for species conservation and their actions contribute to the achievement of key Kunming-Montreal Global Biodiversity Framework targets focused on ecosystem protection, restoration, sustainable use, and inclusive spatial planning. Yet, one-third of mobilizations face repression, criminalization, or violence—pressures that are even more common in high-priority conservation areas. Moreover, mobilizations facing repressive outcomes contest environmental threats relevant for the KMGBF targets more extensively than those with progressive outcomes, underscoring the risks faced by movements driving biodiversity protection in critical regions. To amplify the transformative potential of socio-environmental mobilizations, we emphasize the importance of recognizing, strengthening, and protecting them through coordinated action among diverse social actors. By fostering collaboration and targeted resource allocation, these efforts can empower socio-environmental mobilizations to catalyze meaningful and lasting change for biodiversity conservation.

Detection of balance in the elderly under the influence of stress (DEPIE): A cross-sectional study protocol

Age-related changes increase frailty and vulnerability to stress in older adults, and stress has been linked to poorer balance and fall risk. However, the mechanisms by which emotional stress may contribute to falls remain unclear. This study explores whether: 1) emotional stressors lead to neuromuscular changes that affect postural control in older adults; and 2) technology can assist in fall prevention by detecting increased risk. A cross-sectional, laboratory-based observational study is being conducted in a single session comparing 30 young adults (18–39 years) and 30 older adults (≥65 years), in which participants are exposed to emotional stressors (high-arousal images) and their immediate neuromuscular and balance responses are recorded. The first participant was enrolled on November 27, 2024. All participants complete a sequence of physical tasks under two conditions: viewing low-arousal and high-arousal images from the International Affective Picture System. The physical tasks involve standing up from a chair, walking to a table, transferring water between bottles, returning to the chair, and sitting down. Emotional responses are assessed using heart rate variability, respiratory rate and subjective feelings of unease. Electromyographic signals are analysed using wearable sensors, ground pressure is recorded via pressure sensors and bottle manipulation is tracked with inertial measurement units. Furthermore, balance is evaluated using the Timed Up and Go Test and the Functional Reach Test, administered before the low-arousal condition and after the high-arousal condition. Comprehensive data analysis will provide new insights to aid professionals in designing interventions for detecting and preventing fall risk in older adults. The study was approved by the corresponding ethics committee and registered at ClinicalTrials.gov (NCT06682754) on November 21, 2024. It is being conducted at the University of Alcalá, Spain, and is funded by the European Union and the ‘Junta de Castilla-La Mancha’. Principal investigators are Dr. Bernardo Alarcos and Dr. Susana Nunez-Nagy ( susana.nunez@uah.es ). The collected data will be anonymized and shared in an open-access repository, in line with ethical and open science principles.

Combinatorial chemistry identifies additional compounds that selectively inhibit DLK-dependent retrograde signaling while minimally affecting other axonal roles of DLK

Pore size dynamics control complex volume swelling in pyroptosis

Pyroptosis, an inflammatory form of cell death, is characterized by massive cell swelling and plasma membrane rupture. Although swelling was recently shown to occur in two steps, the molecular and biophysical mechanisms driving this process remained unclear. Using fast quantitative microscopy, we reveal that between the two swelling phases, cell volume transiently stabilizes despite sustained plasma membrane permeability to ions and small molecules. From a biophysical perspective, the existence of such a plateau is puzzling, as ion pumps should not be able to regulate cell volume under these conditions. To address this, we developed a physical model based on an ion pump and leak framework that incorporates the dynamics of nonselective pore formation. Experimentally, we demonstrate that the plateau phase is controlled by the dynamics of the gasdermin D (GSDMD) pore enlargement, which is modulated by ninjurin-1 (Ninj1) activation, possibly through intracellular calcium. Ninj1-mediated lesions are also required for the second swelling phase. We further show that fully opened GSDMD pores display an effective hydrodynamic radius slightly above 1.9 nm, providing an in situ upper bound for pore size. Together, our findings demonstrate that pyroptotic volume dysregulation emerges from the successive and interdependent actions of GSDMD and Ninj1, each imparting distinct permeability regimes associated with increased water filtration and decreased ion selectivity due to pore opening. These insights bridge molecular and biophysical perspectives on lytic cell death and may inform the broader understanding of membrane rupture in inflammatory and pathological contexts.

The efficacy of freehand, pilot drilled and fully guided implant surgery in partially edentulous patients: A randomized control trial

Background Partial edentulism poses challenges to oral function, aesthetics, and quality of life. Implant placement techniques—freehand, pilot-drilled, and fully guided—differ in accuracy, surgical time, and outcomes. In this study, only one predefined index implant per patient was analyzed to avoid confounding from multi-implant cases, and template fabrication for the pilot-drilled group was performed using diagnostic wax-up and thermoplastic material. This study evaluated these techniques in partially edentulous patients. Methods Ninety patients were randomly assigned to three groups: freehand (n = 30), pilot- drilled (n = 30), and fully guided (n = 30). Surgery duration, implant placement accuracy, post- operative complications, early implant failure rates, and patient satisfaction were measured. Accuracy was assessed using standardized CBCT imaging at 12 months, and satisfaction was evaluated via a validated questionnaire six months after prosthetic loading. Results The fully guided technique demonstrated superior accuracy (p < 0.001), shorter surgical times (45 minutes vs. 60 and 75 minutes, p < 0.01), fewer complications (5% vs. 15% and 20%, p < 0.05), and higher satisfaction (9.2/10, p < 0.01). Early implant failure, defined at the implant level, occurred in 4/30 implants (13.3%) in the freehand group, 0/30 in the pilot-drilled group, and 2/30 in the fully guided group (p < 0.05). Conclusion Fully guided implant surgery outperformed other techniques in accuracy, efficiency, and patient satisfaction. These findings support fully guided, prosthetically driven workflows as a preferred option for partially edentulous patients, particularly in cases requiring high precision.

A cross-sectional study exploring academic motivation among rehabilitation science students under different teaching approaches in China

A data-driven chromatin model reveals spatial and dynamic features of genome organization

Compacting chromatin within the cellular nucleus presents a significant challenge for biology. Chromosomes must be both condensed and spatially organized to enable essential processes such as transcription and replication. Chromosome conformation capture experiments (e.g., Hi-C) provide valuable information about the spatial organization and, therefore, the connectivity between different genomic regions. These experiments inspired polymer models that describe the physical mechanism of the chromosomal energy landscape. The Full-Inversion Chromatin model (FI-Chrom), a data-driven approach for modeling genome organization, uses Hi-C contact maps to infer pairwise interaction potentials between all chromosomal loci. It combines Graphics Processing Unit (GPU)-accelerated simulations with efficient training of tens of millions of parameters derived from the maximum-entropy principle to determine 3D structures of chromosomes that accurately reproduce Hi-C-like data. FI-Chrom does not make any a priori assumptions regarding chromosome architecture, making it applicable to any chromosome conformation capture experiment. Its derived structural ensembles capture all essential features from the short- and long-range interactions of typical chromosome organization, such as segregated compartments, chromosome territories, and fully or partially formed loops. Although Hi-C contains only structural information, FI-Chrom extends these data by revealing an emergent dynamical mechanism encoded in the inferred energy landscape. For example, simulations show that chromatin loops are not static architectural features but rather transient structural elements. Statistical analyses further indicate that loops confined within a single compartment occur more frequently than those spanning multiple compartments, highlighting the dynamic and compartment-dependent nature of chromatin organization.

Financial constraints and corporate bankruptcy risks in China: The buffer role of cash holdings

Corporate bankruptcy risk in China is increasingly driven by structural credit discrimination and a systemic financial mismatch. This study investigates the impact of cash holdings and financial constraints on corporate bankruptcy risk in China. We employ the Two-step system Generalized Method of Moments (GMM) to analyze an unbalanced panel of 32,081 annual observations from listed firms in China, spanning the period from 2010 to 2023. Our findings indicate that higher financial constraints increase bankruptcy risk, as a one-point rise in the SA index reduces the Z-score by 4.26 points, supporting Market Timing Theory. Conversely, cash holdings serve as a powerful protective buffer; a 1% increase in cash holdings raises the Z-score by 0.37 points, supporting the Precautionary Savings and Trade-off theories. Furthermore, our results highlight the buffer role of cash holdings for financially constrained firms, where higher cash reserves mitigate the adverse effects of financial constraints on bankruptcy risk. Our main findings remain robust after employing alternative bankruptcy risk proxies, firm size-based, and exchange subsamples. These findings provide valuable insights for financial managers and policymakers, highlighting the importance of effective liquidity management and credit accessibility in mitigating corporate distress in emerging markets.

Deep atrous context convolution generative adversarial network with corner key point extracted feature for nuts classification

Abstract Deep learning-based nut classification has emerged as a viable way to automate the detection and categorization of different nut varieties in the food processing and agriculture sectors. Conventional techniques for classifying nuts mostly rely on manually created characteristics like texture, color, shape, or edges. These characteristics frequently fall short of capturing the image’s complete complexity, particularly when nuts show tiny visual variances. This research proposes Deep Atrous Context Convolution Generative Adversarial Network (DAC-GAN) model that categorize the 8 classes of nuts like brazil nuts, cashew, peanut, pecan nut, pistachio, chest nut, macadamia and Walnut. This research uses Common Nut KAGGLE dataset with 4,000 nuts images of 8 nuts classes. The DAC-GAN approach overcomes the difficulties of having limited labelled data for nut classification tasks by employing DCGANs’ ability to produce high-quality, synthetic nut images to supplement the dataset. The DCGAN comprises of a discriminator and a generator block. The discriminator block develops the ability to differentiate between synthetic and real images, while the generator block generates realistic nut images from random noise. The real images along with the DCGAN generated images are processed with feature filtering methods to extract the Corner Key Points Featured (CKPF) nuts images. To further enhance the feature selection, the CKPF edges are extracted from the image that provides unique, geometrically distinctive critical corners to further process for representative learning. To proceed with the effective feature extraction and model learning, the CKPF nuts images are processed with atrous convolution that capture the intricate details by expanding the receptive field without losing resolution. The novelty of this work exists by appending the filtration and atrous convolution that acquire the spatial data features from the nut’s images at various resolutions. Atrous convolution was refined by appending the pre-context and post-context block that add the image level information to the features. The effectiveness of the DAC-GAN model was validated with the traditional augmented dataset with all existing filtering images and CNN models. Implementation outcome shows that DAC-GAN found to exhibit high accuracy of 99.83% towards the nuts type classification. The superiority of the DAC-GAN method over traditional approaches is demonstrated by extensive experiments on augmented and DCGAN generated datasets, which achieve higher classification accuracy and generalization across a variety of nut type categorization. The outcome demonstrates that the DCGAN together with atrous convolution have the potential to be an effective tool for automating nut sorting in food industry.

RecBCD-dependent post-UV replication restart in <i> <i>Escherichia coli</i> </i> triggers fork triplication

Ultraviolet (UV) irradiation induces pyrimidine dimers in DNA, which block replication, but are efficiently removed by excision, allowing replication restart. Interestingly, soon after restart, the cells become capable of inducible stable DNA replication (iSDR) without new origin-initiations—suggesting unusual replication topology. The original idea was that the preexisting forks remain dormant even after UV-lesion removal, and when the new origin-initiated forks arrive, they rear-end the dormant forks, creating potential for iSDR. While there is origin-overinitiation after UV, the current idea is that preexisting forks are restarted—making the iSDR potential unclear. We used replication profiling of post-UV cells to investigate reactivation of UV-blocked forks. To compare profile time-sequences, we developed indexation procedure generating nested profile sets. Wild type nested set shows: 1) no replication during the first 30 min post-UV; 2) overinitiation from the origin combined with restart of preexisting forks during the next 30 min post-UV. The restart required RecBCD enzyme to repair double-strand breaks, confirming that the UV-stalled forks disintegrate and need recombinational repair to restart. Preexisting fork restart is separate from new origin-initiations by DnaA, as the dnaA (Ts) mutant at 42 °C restarts preexisting forks normally. Remarkably, the absence of powerful replication wave from origin-initiations in the dnaA mutant reveals a restart-initiated replication wave toward the origin, indicating that the restart mechanism causes fork triplication—potentially explaining the SDR phenomenon. There is no post-UV replication in the dnaA recBC double mutant, consistent with only two pathways of replication resumption in post-UV cells: restart or new origin-initiation.

Relationship between postural and kinesthetic awareness, static balance, and weight-bearing asymmetry in individuals with chronic stroke: A cross-sectional study

Postural and kinesthetic awareness are essential sensory-perceptual components contributing to balance control and symmetrical weight distribution. In individuals with chronic stroke, deficits in body awareness can impair postural stability and increase asymmetry, yet their precise relationships with balance parameters remain insufficiently explored. This cross-sectional study investigated the associations between postural and kinesthetic awareness and both static balance performance and weight-bearing asymmetry in individuals with chronic stroke. Forty-eight participants who were at least six months post-stroke were assessed using the Postural Awareness Scale (PAS), and joint position sense error was measured via a digital inclinometer. Static balance parameters, including center of pressure (COP), sway area, path length, and sway velocity, were evaluated using a stabilometric force platform. Weight-bearing asymmetry (WBA) was calculated using the two-scale method. Pearson’s correlations and multiple linear regression analyses were conducted. Postural awareness was significantly negatively correlated with sway area (r = –0.53, p = 0.001) and sway velocity (r = –0.51, p = 0.002), while joint position sense error was positively correlated with these metrics (r = 0.47–0.49, p &lt; 0.01). Both awareness measures were significantly associated with WBA (PAS: r = –0.49; joint position error: r = 0.48, p &lt; 0.01). Regression analyses identified PAS as a significant predictor of sway area (β = –0.38, p = 0.002) and WBA (β = –0.36, p = 0.003), while joint position sense error significantly predicted sway velocity (β = 0.41, p = 0.001). These findings highlight the independent associations of postural and kinesthetic awareness with postural control and symmetry in individuals with chronic stroke, suggesting their potential relevance for rehabilitation strategies aimed at improving balance and functional stability.

An LSTM architecture for real-time multi-domain stability boundary prediction beyond post-fault dependency in power systems

Intermediate evolutionary state of motile sperm and pollen tubes in the extant gymnosperm <i>Cycas revoluta</i>

Evolutionary transitions in land plant fertilization from zooidogamy to siphonogamy were characterized by transformations of male reproductive cells. Basal land plants such as bryophytes and pteridophytes have motile sperm, whereas most seed plants have nonmotile sperm, delivered by a pollen tube. Despite being seed plants, gymnosperm cycads and ginkgo uniquely form highly multiflagellated and large motile sperm within pollen tubes. However, the evolutionary state of these male reproductive cells remains unknown. We clarified the gene expression profiles of Cycas revoluta pollen tubes and motile sperm swimming toward female reproductive cells. Male cycad cells expressed fewer genes associated with transcription, translation, and related processes, which is consistent across land plants. We compared the distinctive orthologous groups (OGs) of the genes specifically expressed in sperm and pollen tubes with those in other plants. Cycad pollen tubes shared several OGs with angiosperms but possessed significantly fewer gene copies and lacked cell wall remodeling and plasma membrane-localized receptor genes that contribute to rapid and guided growth. The growth mechanism of cycad pollen tubes might be largely different from angiosperm pollen tubes. In contrast, despite their morphological uniqueness, cycad sperm shared representative OGs with angiosperm sperm cells to the same extent as egg cells. In addition, a sperm-specific histone variant may contribute to transcriptional regulation via chromatin condensation like other male gametes. As an extant gymnosperm that retains zooidogamy with pollen tubes, the cycad represents a molecular intermediate state in the transition from zooidogamy to siphonogamy, providing insight into the evolution of land plant fertilization.

Metabolic and bariatric surgery among patients with social anxiety disorder, a matched cohort study

Social anxiety disorder is common among patients considered for metabolic and bariatric surgery (MBS). The combination of social anxiety with obesity may, however, be associated with a higher risk for adverse outcomes after surgery. In this nationwide, registry-based, matched cohort study, all patients who underwent primary MBS in Sweden from 2007 until 2019 and who had a diagnosis of moderate to severe social anxiety disorder (n = 586) were matched using a Propensity score to controls who underwent the same treatment but who did not have social anxiety disorder (n = 5791) with a mean follow-up time of 6.9 years. Patients with social anxiety disorder experienced an increased risk for non-serious postoperative complications (OR 1.59; 95%CI 1.21–2.09), self-harm (HR 2.44 CI 95% 1.84–3.25 p &lt; 0.001) and alcohol or substance abuse (HR 2.41, 95%CI 1.96–2.96, p &lt; 0.001), and reported lower psychosocial health-related quality of life before and after surgery. However, patients with social anxiety disorder significantly improved in health-related quality of life compared to baseline, and experienced similar effects on weight reduction at 2 years after surgery (total weight loss: 32.8 ± 10.3% compared to 32.6 ± 9.7%) and risks for cardiovascular events compared to the matched control group. MBS appears to be a safe and effective treatment for severe obesity in patients with social anxiety disorder, but an individualized and increased peri- and postoperative support should be considered for patients with moderate to severe social anxiety disorder and severe obesity.

Behavioral and innovation drivers of farmers’ support for forest policy at the forest agriculture interface

Observation of emergent scaling of spin–charge correlations at the onset of the pseudogap

In strongly correlated materials, interacting electrons are entangled and form collective quantum states, resulting in rich low-temperature phase diagrams. Notable examples include cuprate superconductors, in which superconductivity emerges at low doping out of an unusual “pseudogap” metallic state above the critical temperature. The Fermi–Hubbard model, describing a wide range of phenomena associated with strong electron correlations, still offers major computational challenges despite its simple formulation. In this context, ultracold atoms quantum simulators have provided invaluable insights into the microscopic nature of correlated quantum states. Here, we use a quantum gas microscope Fermi–Hubbard simulator to explore a wide range of dopings and temperatures in a regime where a pseudogap is known to develop. By measuring multipoint correlation functions up to fifth order, we uncover a universal scaling behavior in magnetic and higher-order spin–charge correlations characterized by a doping-dependent temperature scale. Accurate comparisons with determinant Quantum Monte Carlo and Minimally Entangled Typical Thermal States simulations confirm that this temperature scale is comparable to the pseudogap temperature T ∗ . Our quantitative findings reveal a qualitative behavior of magnetic properties and spin–charge correlations in an emergent pseudogap and pave the way toward the exploration of charge pairing and collective phenomena expected at lower temperatures.

Cardiosphere-derived cells in the primary prevention of sepsis-induced acute lung injury in pigs

Acute respiratory distress syndrome (ARDS) prevention in patients coincide with significant risk factors, including severe sepsis. Cardiosphere-derived cells (CDCs) are cardiac stromal/progenitor cells with anti-inflammatory and immunomodulatory effects, which may impact favorably on sepsis-induced acute lung injury (ALI). We used a pig model of sepsis (lipopolysaccharide, LPS) to test whether CDCs, given IV in a preventive paradigm, can ameliorate ALI, relative to placebo. Yorkshire/Landrace hybrid domestic pigs (n = 34) were divided into 3 groups: 1) healthy controls; 2) LPS (60ug/kg) + saline (placebo) group; and 3) LPS + CDC group, with CDCs given in 3 different doses (25, 50 and 100 million cells) after LPS. All pigs were briefly intubated on mechanical ventilation on room air to obtain baseline and 1-hour data and again at the final endpoint of 48hours. Chest mechanics, gas exchange, hemodynamics, blood, bronchoalveolar lavage assays and lung histology were assessed. LPS + CDCs compared with LPS + saline improved: gas exchange (increased hypoxemia ratio [p = 0.03],chest mechanics (respiratory compliance [p = 0.002]; peak and plateau pressures [p = 0.01/0.049]), pulmonary hemodynamics (decreased pulmonary artery pressures [p = .0008]), reduced BAL neutrophils [p = 0.04]), and systemic cytokines, e.g., IL-1, IL-6, IL-18 and IFNγ [p &lt; 0.05]) and serum creatinine (p = 0.02), while alveolar lavage cytokines, e.g., IL-1, IL-6,IL-8,and IL-18 were changed. Histopathology was improved (decreased atelectasis, hemorrhage and arteriolar thickness). In summary, CDCs given in a preventive fashion, attenuated manifestations of LPS-induced ALI. As CDCs have an extensive safety record in hundreds of patients, our findings motivate clinical testing of CDCs for the primary prevention of sepsis-induced ARDS.

YTHDC1 modulates the malignant phenotype of retinoblastoma via SQSTM1-mediated autophagy

Broad beta-CoV immunity and transmission blockade by a single-dose live-attenuated vaccine with atypical codon usage

Current COVID-19 vaccines have saved countless lives but primarily aim to induce immunity to the spike or its RBD protein and often fail to confer broad or durable protection against rapidly evolving variants and prevent transmission. Here, we invented a live-attenuated broad-spectrum coronavirus vaccine (cb1) by changing the codon usage bias of SARS-CoV-2 genome, which maintained amino acid conservation but reduced virulence. A single intranasal dose of cb1 vaccine elicits remarkably broad and potent immunity that overcomes existing parenteral vaccine’s limitations. cb1 induced robust neutralizing antibody and T cell responses that translated into complete protection in animal models, including prevention of viral transmission to unvaccinated contacts. Notably, cb1 provided cross-protection not only against diverse SARS-CoV-2 variants of concern but also against more divergent SARS-CoV-1 and hCoV-OC43, a breadth of immunity unparalleled by current vaccines. These findings highlight the potential of cb1 to address urgent needs for next-generation COVID-19 vaccines that elicit mucosal immunity with broad, long-lasting efficacy, eliminating the necessity for frequent updates.