bluuebunny/crossref_metadata_2025 huggingface dataset:
Input misallocation and productivity dynamics
Authors: Lai Hung-pin , Kumbhakar Subal C.
Published: February 2025

This paper builds on Hsieh and Klenow’s (2009) model to offer a refined analysis of how input misallocations impact aggregate total factor productivity (TFP). We enhance the original model by relaxing the assumption of uniform input prices and adopting an econometric approach to estimate parameters using firm-level data. Estimation of model parameters and allocation efficiency is based on the system of input demand and the production function. We use an indirect inference approach to estimate the system to avoid maximum likelihood estimation, which often faces convergence issues, when there are numerous constraints. We demonstrate our model using the US firm-level manufacturing panel data from 1975 to 2010. Our final sample contains 55,518 observations. We divide the manufacturing industry into seven major categories. Our findings indicate that between 1975 and 2010, the average productivity growth rate was 2.8% but could have reached 3.2% without misallocation, highlighting the substantial gains possible through better resource allocation.
Linguistic convergence in U.S.-raised Spanish–English bilinguals’ nominal demonstrative use
Authors: Lease Sarah , Shin Naomi
Published: February 2025

This study investigates linguistic convergence in Spanish–English bilinguals’ demonstrative use in English (this/that) and Spanish (este/ese). Participants completed a task that tested the influence of speaker-referent distance on demonstrative use. Study 1 includes Spanish-speaking monolinguals in Mexico, English-speaking monolinguals in the USA, and Spanish–English bilinguals who were born in the USA or arrived at a young age. Results show that speaker-referent distance constrained all groups’ demonstrative use; however, this effect was weaker in the bilinguals’ Spanish as compared to the Spanish-speaking monolinguals. Study 2 focuses on the bilinguals’ demonstratives. Group-level and individual analyses present evidence for linguistic convergence: the bilinguals’ usage patterns were similar across their languages. Additionally, language dominance predicted usage patterns: the more English-dominant the participant, the greater the likelihood of producing proximal demonstratives for near and far referents alike. This pattern mirrors common diachronic changes, supporting the view that bilinguals may propel language change.
The Conditionality of Trusting Caseworkers in the Social Services Sector – Insights from Germany and Denmark
Authors: Zschache Ulrike , Schneider Stephanie , Brus Anne , Trenz Hans-Jörg
Published: February 2025

Citizen trust is a prerequisite for the success of service provision. However, working relations are typically shaped by power asymmetries and one-sided dependencies, contributing to cautiousness towards or distrust of caseworkers (Dumbrill, 2006; de Boer and Coady, 2007). This article sheds light on the conditions and mechanisms that lead (some) citizens nevertheless to trust their caseworker. Based on thematic coding of semi-structured interviews with twenty-five German and sixteen Danish welfare users, our findings elucidate how shared problem perceptions and positive experiences in direct working relationships with committed, citizens-oriented caseworkers mitigate structural asymmetries and allow trust-building. In particular, they underscore the importance of personal bonding and positive emotions, including feelings of sympathy, or even friendship, and of being seen, understood and respected. Our article strengthens the interpersonal, micro-level perspective on trust-building in welfare service provision and provides new empirical insights into the role of personal relations in trust-adverse institutionalised contexts.
Between Moscow and Geneva: The Soviet Red Cross and the International Red Cross Movement
Authors: Hearne Siobhán
Published: February 2025

In the decades after the death of Iosif Stalin in 1953, Soviet foreign policy shifted away from isolationism to knowledge transfer and competition with the West, as well as robust engagement with the decolonising and non-aligned world. A core component of this reorientation was the reversal of the USSR’s temporary withdrawal from international organisations. This article explores the Soviet Red Cross’s involvement in the League of Red Cross Societies and argues that the two organisations engaged in a mutually beneficial partnership that was built upon shared visions of humanitarianism and development. In this period, the Soviet Red Cross co-hosted major international seminars and conferences with the League, helped to channel humanitarian relief to conflict zones, and supported the League’s development initiatives in the Global South. In return, the League offered the Soviets opportunities to forge links with newly independent countries of the decolonising world and advance narratives about Soviet superiority to international and domestic audiences.
Introducing a psychological formulation model of maladaptive daydreaming
Authors: Lucas Amy , Bone Alexandra
Published: February 2025

Maladaptive daydreaming (MD) is an increasingly recognised mental health difficulty, which refers to a compulsive cycle of dissociative absorption in vivid mental fantasy that results in clinical distress and functional impairment. Fantasies are usually complex in plot and characters, and are highly pleasurable and absorbing. MD provides temporary escape, soothing, or attempted processing of difficult internal and external experiences, but results in longer-term negative consequences that both create and exacerbate real-life suffering. The literature thus far has expanded beyond defining and understanding MD and has turned its attention towards assessment and pilot interventions. This paper presents the first formulation framework and associated diagrammatic model of MD, drawing upon the existing evidence base and cognitive behavioural theory to capture its development, maintenance, and processes. The model was reviewed by two leading experts in the field and trialled by three contributors with lived experience of MD. Feedback was positive, suggesting it accurately captured and organised the complexity and depth of the MD experience, facilitated the development of personal insight, and fostered a sense of hope with regard to creating change. The model is intended for use within clinical practice to aid mental health professionals and people with MD to guide assessment, collaborative discovery and formulation, and intervention. It is imperative that the model be tested further within research and clinical practice to further ensure its efficacy, validity, and applicability for people with MD.

Key learning aims

(1)

To consider the development and maintenance factors, and processes involved in MD from a cognitive behavioural perspective.

(2)

To introduce a new formulation model for MD and understand how the model can be used in clinical practice.

(3)

To highlight how psychological formulation has the power to better understand and organise the complex and often overwhelming MD phenomenon and provide hope for meaningful change.
Building Trust with AI: How Essential is Validating AI Models in the Therapeutic Triad of Therapist, Patient, and Artificial Third? Comment on What is the Current and Future Status of Digital Mental Health Interventions?
Authors: Garcia-Rudolph Alejandro , Sánchez-Pinsach David , Gilabert Anna , Saurí Joan , Soler Maria Dolors , Opisso Eloy
Published: February 2025

Since the publication of “What is the Current and Future Status of Digital Mental Health Interventions?” the exponential growth and widespread adoption of ChatGPT have underscored the importance of reassessing its utility in digital mental health interventions. This review critically examined the potential of ChatGPT, particularly focusing on its application within clinical psychology settings as the technology has continued evolving through 2023 and 2024. Alongside this, our literature review spanned US Medical Licensing Examination (USMLE) validations, assessments of the capacity to interpret human emotions, analyses concerning the identification of depression and its determinants at treatment initiation, and reported our findings. Our review evaluated the capabilities of GPT-3.5 and GPT-4.0 separately in clinical psychology settings, highlighting the potential of conversational AI to overcome traditional barriers such as stigma and accessibility in mental health treatment. Each model displayed different levels of proficiency, indicating a promising yet cautious pathway for integrating AI into mental health practices.
Soft back exosuit controlled by neuro-mechanical modeling provides adaptive assistance while lifting unknown loads and reduces lumbosacral compression forces
Authors: Moya-Esteban Alejandro , Refai Mohamed Irfan , Sridar Saivimal , van der Kooij Herman , Sartori Massimo
Published: February 2025

State-of-the-art controllers for active back exosuits rely on body kinematics and state machines. These controllers do not continuously target the lumbosacral compression forces or adapt to unknown external loads. The use of additional contact or load detection could make such controllers more adaptive; however, it can be impractical for daily use. Here, we developed a novel neuro-mechanical model-based controller (NMBC) that uses a personalized electromyography (EMG)-driven musculoskeletal (MSK) model to estimate lumbosacral joint loading. NMBC provided adaptive, subject- and load-specific assistive forces proportional to estimates of the active part of biological joint moments through a soft back support exosuit. Without a priori information, the maximum assistive forces of the cable were modulated across weights. Simultaneously, we applied a non-adaptive, kinematic-dependent, trunk inclination-based controller (TIBC). Both NMBC and TIBC reduced the mean and peak biomechanical metrics, although not all reductions were significant. TIBC did not modulate assistance across weights. NMBC showed larger reductions of mean than peak values, significant reductions during the erect stance and the cumulative compressive loads by 21% over multiple cycles in a cohort of 10 participants. Overall, NMBC targeted mean lumbosacral compressive forces during lifting without a priori information of the load being carried. This may facilitate the adoption of non-hindering wearable robotics in real-life scenarios. As NMBC is informed by an EMG-driven MSK model, it is possible to tune the timing of NMBC-generated torque commands to the exosuit (delaying or anticipating commands with respect to biological torques) to target further reduction of peak or mean compressive forces and muscle fatigue.
Ab wann sind Mädchen die Lesestarken?
Authors: Scheerer-Neumann Gerheid , Schnitzler Carola
Published: February 2025

Zusammenfassung: Hintergrund: Die großen Schulstudien wie IGLU (4. Schuljahr) und PISA (15-Jährige) zeigen seit Jahren eine höhere Lesekompetenz von Mädchen im Vergleich zu Jungen. Es stellt sich die Frage, ob geschlechtsbezogene Disparitäten auch schon bei jüngeren Schulkindern bestehen. Methode: In einer vertiefenden Analyse der Daten aus der Normierung des Potsdamer Lesetests (PLT) mit N = 1007 Schülern und N = 1044 Schülerinnen der Klassenstufen 1–4 werden geschlechtsspezifische Unterschiede beim stillen Wortlesen (Untertest Worterkennen) und beim lesenden Verstehen von Texten (Untertest Leseverstehen) untersucht. Ergebnisse: Beim Leseverstehen erreichen die Mädchen ab dem 3. Schuljahr signifikant höhere Leistungen, im 4. Schuljahr auch beim Worterkennen. Bei der Bearbeitung der Leseaufgaben weisen Mädchen eine höhere Geschwindigkeit und Genauigkeit auf. In beiden Untertests gehen die signifikanten Mittelwertsunterschiede mit einem deutlich höheren Anteil der Jungen in der untersten Leistungsgruppe (T < 40) einher. Die Effekte des Geschlechts bleiben auch bei gleichzeitiger Kontrolle sprachlicher Fähigkeiten bestehen. Diskussion: Am Ende der Grundschulzeit besteht ein Vorsprung der Mädchen sowohl beim Worterkennen als auch beim Leseverstehen, d.h. bei hierarchieniedrigen wie auch bei hierarchiehöheren Leseprozessen. Schulische Fördermaßnahmen sollten beide Teilprozesse des Lesens umfassen und verstärkt die Jungen im Blick haben.
Initial Thermal States of Super‐Earth Exoplanets and Implications for Early Dynamos
Authors: White Nathaniel I. , Li Jie
Published: February 2025

The accretion of Earth and the formation of a metallic core released a large amount of primordial heat and may have enabled its evolution into a habitable world. Metal‐silicate segregation likely occurs in super‐Earth exoplanets as well, but its influence on their initial thermal states has not been fully examined. Here we calculated the energy released during core‐mantle differentiation of super‐Earths for a range of planet radii and core mass fractions. We found that the energy of differentiation increases with planet mass for rocky planets with Earth‐like composition, and it peaks at 55% core by mass in Earth‐sized rocky planets. Using the latest mineral physics constraints on the equations‐of‐state and melting curve of relevant phases, we modeled the initial thermal profiles and assessed the extent of melting in initial iron cores for plausible heat retention efficiencies. Our results suggest that following accretion and metal‐silicate differentiation, the cores of most super‐Earths are expected to be at least partially molten, a necessary condition for the generation of a magnetic field. Based on the largely molten state of Earth's core at the present day, we place a lower bound of 7% retention of accretional energy as primordial heat in rocky planets.
Childhood trauma cortisol and immune cell glucocorticoid transcript levels are associated with increased risk for suicidality in adolescence
Authors: Goltser-Dubner Tanya , Benarroch Fortu , Lavon Michal , Amer Reaan , Canetti Laura , Giesser Ruth , Kianski Ella , Martin Josef , Pevzner Dalya , Blum Weinberg Pnina , Ben-Ari Amichai , Bar-Nitsan Moriah , Alon Shaked , Yshai Shai , Lotan Amit , Galili-Weisstub Esti , Segman Ronen , Shalev Amit
Published: February 2025

Rising adolescent suicide rates present a growing unmet need. Childhood trauma (CT) has been associated with altered cortisol dynamics and immune cell glucocorticoid reactivity, yet their additive longer-term contributions to later suicide outcomes are less clear. The current study compared CT scores, resting salivary free cortisol and mononuclear cell gene expression levels of the nuclear receptor, subfamily 3, member 1 (NR3C1) coding the glucocorticoid receptor, and its co-chaperons FKBP prolyl isomerase 5 (FKBP5) and KIT Ligand (KITLG), between a cohort of adolescents presenting with a suicidal crisis requiring hospital treatment, and matched healthy controls. Childhood trauma scores and glucocorticoid measures were significantly altered among suicidal adolescents, and CT scores correlated with mononuclear cell glucocorticoid transcripts. Both CT scores and glucocorticoid measures explained substantial additive portions of the variance in adolescent suicidality. Long-term perturbations in cortisol dynamics and immune cell glucocorticoid response elements denote dysregulated immune stress reactivity, and may possess value in prediction and point to modifiable-risk factors in prevention of clinically significant suicidality during the brittle period of adolescence, years after childhood trauma exposure.
Targeting AKT as a promising strategy for SOX2-positive, chemoresistant osteosarcoma
Authors: Liu Yujie , Kang Li , Luo Jing , Yang Minglei , Wang Da , Ye Juelan , Yang Xinghai , Wan Wei , Wong Jiemin , Xiao Jianru
Published: February 2025

Osteosarcoma (OS) is the most prevalent type of primary malignant bone cancer and currently lacks effective targeted treatments. Increasing evidence indicates that SOX2 overexpression is a primary driver of OS. By screening a small-molecule kinase inhibitor library, we identified AKT as a kinase essential for robust SOX2 expression in OS cells. AKT was found to be frequently overexpressed in OS and positively correlated with SOX2 protein levels. We demonstrated that AKT has no effect on SOX2 transcription but promotes SOX2 protein stability. Mechanistically, AKT binds to and phosphorylates SOX2 at T116, preventing SOX2 ubiquitination and proteasome-dependent degradation by ubiquitin E3 ligases UBR5 and STUB1. Moreover, we found that AKT-SOX2 axis is a significant modulator of cancer stemness and chemoresistance and that the combination of AKT inhibitor MK2206 and cisplatin resulted in a synergistic and potent inhibition of OS tumor growth in the PDX model. In conclusion, we identified a critical role for AKT in promoting SOX2 overexpression, tumor stemness, and chemoresistance in OS, and provided evidence that targeting AKT combined with chemotherapy may hold promise for treating refractory OS.
CCN2 mediates fibroblast-macrophage interaction in knee arthrofibrosis based on single-cell RNA-seq analysis
Authors: Li Ziyun , Jiang Jia , Cai Kangwen , Qiao Yi , Zhang Xuancheng , Wang Liren , Kang Yuhao , Wu Xiulin , Zhao Benpeng , Wang Xiuli , Zhang Tianyi , Lin Zhiqi , Wu Jinlong , Lu Simin , Gao Haihan , Jin Haocheng , Xu Caiqi , Huangfu Xiaoqiao , James Zhengzhi , Chen Qiuhua , Zheng Xiaoqi , Liu Ning-Ning , Zhao Jinzhong
Published: February 2025

Knee arthrofibrosis, characterized by excessive matrix protein production and deposition, substantially impairs basic daily functions, causing considerable distress and financial burden. However, the underlying pathomechanisms remain unclear. Here, we characterized the heterogeneous cell populations and cellular pathways by combination of flow cytometry and single-cell RNA-seq analysis of synovial tissues from six patients with or without knee arthrofibrosis. Increased macrophages and fibroblasts were observed with decreased numbers of fibroblast-like synoviocytes, endothelial cells, vascular smooth muscle cells, and T cells in the arthrofibrosis group compared with negative controls. Notably, fibroblasts were discovered to interact with macrophages, and lead to fibrosis through TGF-β pathway induced CCN2 expression in fibroblasts. CCN2 was demonstrated to be required for fibroblast pro-fibrotic functions (activation, proliferation, and migration) through TGFBR/SMAD pathway. The expression of CCN2 was positively correlated with the collagen volume and TGF-β expression and negatively associated with patient-reported outcome measures in another cohort of patients with knee arthrofibrosis. Our study reveals the role of CCN2 in the fibroblast-macrophage interaction through TGF-β pathway which might help to shed light on CCN2 as a potential biomarker.
Additively-manufactured monocrystalline YBCO superconductor
Authors: Zhang Dingchang , Boffo Cristian , Dunand David C.
Published: February 2025

Single-crystal microstructures enable high-performance YBa2Cu3O7-x superconductors which are however limited to simple shapes due to their brittleness. Additive manufacturing can fabricate YBa2Cu3O7-x superconductor with complex shapes, albeit with a polycrystalline microstructure. Here, we demonstrate a route to grow single-crystals from 3D-ink-printed, polycrystalline, sintered superconducting YBa2Cu3O7-x (YBCO or Y123) + Y2BaCuO5 (Y211), manufacturing objects with complex architectures displaying both high critical current density (Jc=2.1 × 104 A.cm–2, 77 K) and high critical temperature (Tc= 88-89.5 K). An ink containing precursor powders (Y2O3, BaCO3, and CuO) is 3D-extruded into complex geometries and then reaction-sintered to obtain polycrystalline Y123 + Y211. A seed is then utilized to transform these 3D-printed parts from polycrystal to monocrystal via the melt growth method. The geometric details of 3D-printed parts survive the process without slumping, sagging or collapse, despite the long-term presence of liquid above the peritectic temperature. Origami structures can be created by sheet folding after 3D-printing. This additive approach enables the facile fabrication of superconducting devices with complex shapes and architectures, such as advanced undulator magnets to generate synchrotron radiation and microwave cavities for dark-matter axion search. This work highlights the potential of additive manufacturing for producing monocrystalline cuprate superconductors and opens the door to additive manufacturing of other monocrystalline functional ceramic or semiconductor materials.
Relationship between hearing thresholds and cognitive function in hearing aid non-users and long-term users post-midlife
Authors: Nishiyama Takanori , Kimizuka Tomomi , Kataoka Chinatsu , Tazoe Mami , Sato Yasunori , Hosoya Makoto , Shimanuki Marie N. , Wakabayashi Takeshi , Ueno Masafumi , Ozawa Hiroyuki , Oishi Naoki
Published: February 2025

The extent of hearing loss requiring hearing aid (HA) to prevent cognitive decline is unclear; we assessed this post-midlife along with the relationship between hearing thresholds and cognitive function in those who had never used HA (non-users) or used HAs for >3 years (long-term users). This study comprised 117 individuals ≥55 years with an average hearing threshold of ≥25 dB HL in their better ear and 55 of the non-users and 62 of the long-term users. The Mini-Mental State Examination, the Symbol Digit Modalities Test (SDMT), and pure-tone and sound-field audiometry were assessed. Mean ± SD hearing levels of the non-user and long-term user group were 40.83 ± 8.16 and 51.13 ± 14.80 dB HL. Non-users showed a significant association (P = 0.01) between the hearing thresholds and SDMT scores, with a cutoff value of above 38.75 dB HL identified as affecting cognitive function. There were no significant associations for long-term users.
Caveolin 1 and 2 enhance the proliferative capacity of BCAM-positive corneal progenitors
Authors: Sasamoto Yuzuru , Kiritoshi Shoko , Lee Catherine A. A. , Fukuda Yoshiko , Martin Gabrielle , Ksander Bruce R. , Frank Markus H. , Frank Natasha Y.
Published: February 2025

Caveolin (CAV) 1 and 2 are integral membrane proteins that constitute major components of small membrane pouches termed caveolae. While several functions have been described in other tissues, the roles of CAV1 and CAV2 in the ocular surface have remained unknown. In the current study, we investigated the expression and function of CAV1 and CAV2 in the human cornea. We found CAV1 and CAV2 to be preferentially expressed by proliferative Basal Cell Adhesion Molecule (BCAM)-positive progenitor cells along the entire limbal and corneal basal epithelial layer. Functional gene knockdown studies reveal that BCAM, BCAM co-expressed Laminin α5 (LAMA5) and Laminin α3 (LAMA3) regulate expression of CAV2. Mechanistically, we demonstrate that CAV1 and CAV2 contribute to enhanced BCAM-positive cell proliferation through regulation of Fibroblast Growth Factor Receptor 2 (FGFR2) cell surface expression. In aggregate, our study identifies specific expression of CAV1 and CAV2 in BCAM-positive corneal basal epithelial cells and uncovers a novel CAV1/CAV2-dependent mechanism of corneal progenitor cell proliferation, with potential implications for therapeutic enhancement of corneal regeneration.
Evaluating site selection for optimal photovoltaic installations and CO₂ emission reduction in selected districts of khyber pakhtunkhwa
Authors: Farnaz  , Nuthammachot Narissara , Shabbir Rabia
Published: February 2025

As the global market for renewable energy solutions expands, geospatial analysis is becoming crucial for optimizing solar potential. The current study assesses the suitability of installing PV solar system in the Mardan, Peshawar, and Nowshera districts in Pakistan using a multi-criteria decision-making (MCDM) approach. Analysis of different parameters, such as topography, land use and land cover (LULC), solar radiation and land surface temperature (LST), were performed to find the appropriate locations for solar in their respective regions. The study employed binary classification and weighted overlay methods to detect patterns of spatial suitability. Peshawar showed maximum ability with 859.8 km² categorized as favorable with a projected annual power output capacity of 67.77 trillion kWh and a decrease in CO₂ emission of 2.78 billion metric tons. Mardan closely followed the suitable area with 828.4 km² with energy generation of 39.74 trillion kWh/year and reduction of CO₂ emissions by 1.63 billion metric tons. Nowshera has an appropriate area of 503.0 km², for energy output of 670.06 billion kWh, and CO₂ reduction of 27.46 million metric tons. These results underline the importance of combining geospatial and meteorological data for accurate planning of solar energy systems. By highlighting location-specific features, including topography and solar irradiance illustrates the importance of tailoring energy outputs and environmental impacts to local contexts. These insights help guide policymakers in driving renewable energy projects, and support Pakistan’s sustainable development and climate targets.
Characterization of the electronic structure and fate of doubly ionized carbon diselenide
Authors: Parriani Marco , Olsson Emelie , Daver Ideböhn Veronica , Wallner Måns , Squibb Richard J. , Nyman Gunnar , Falcinelli Stefano , Eland John H. D. , Hochlaf Majdi , Feifel Raimund
Published: February 2025

Single photon double ionization of carbon diselenide (
$${\hbox {CSe}}_{2}$$
) has been investigated by means of multi-particle coincidence techniques. The interpretation of the experimental spectra is helped by post-Hartree-Fock computations at the Coupled Clusters and Multi-Reference Configuration-Interaction levels to determine the energetics and electronic state potentials of
$$\hbox {CSe}_2^{2+}$$
and its fragments. The lowest experimental double ionization energy of
$${\hbox {CSe}}_{2}$$
has been found to be 24.68 ± 0.20 eV, reflecting the
$$\hbox { X} ^3\Sigma ^-_g$$
ground state, and is in agreement with the theoretical vertical double ionization energy of 24.41 eV. Several fragmentation channels are reported including experimental appearance energies and kinetic energy releases in comparison to theoretical results on their characteristics. In particular, we identify several purely repulsive, Coulomb explosion fragmentation channels.
Algorithm for pixel-level concrete pavement crack segmentation based on an improved U-Net model
Authors: Zhang Zixuan , He Yike , Hu Di , Jin Qiang , Zhou Manxu , Liu Zongwei , Chen Hongli , Wang He , Xiang Xinchen
Published: February 2025

Cracks that occur in concrete surfaces are numerous and diverse, and different cracks will affect road safety in different degrees. Accurately identifying pavement cracks is crucial for assessing road conditions and formulating maintenance strategies. This study improves the original U-shaped convolutional network (U-Net) model through the introduction of two innovations, thereby modifying its structure, reducing the number of parameters, enhancing its ability to distinguish between background and cracks, and improving its speed and accuracy in crack detection tasks. Additionally, datasets with different exposure levels and noise conditions are used to train the network, broadening its predictive ability. A custom dataset of 960 road crack images was added to the public dataset to train and evaluate the model. The test results demonstrate that the proposed U-Net-FML model achieves high accuracy and detection speed in complex environments, with MIoU, F1 score, precision, and recall values of 76.4%, 74.2%, 84.2%, and 66.4%, respectively, significantly surpassing those of the other models. Among the seven comparison models, U-Net-FML has the strongest overall performance, highlighting its engineering value for precise detection and efficient analysis of cracks.
Global warming may turn ice-free areas of Maritime and Peninsular Antarctica into potential soil organic carbon sinks
Authors: de Mello Danilo C. , Francelino Márcio R. , Moquedace Cássio M. , Baldi Clara G. O. , Silva Lucas V. , Siqueira Rafael G. , Veloso Gustavo V. , Fernandes-Filho Elpídio I. , Thomazini André , Demattê José A. M. , Ferreira Tiago O. , Gomes Lucas Carvalho , Senra Eduardo O. , Schaefer Carlos E. G. R.
Published: February 2025

The impact of intensified climate change driven by global warming on the stocks and dynamics of soil organic carbon in Antarctica is currently uncertain. Our objective with this was evaluate the potential repercussions of global warming on soil organic carbon under three Shared Socioeconomic Pathways. Employing a methodology that integrates soil field data, machine learning, and projections of future climate change scenarios for the Maritime and Peninsular Antarctic ice-free areas, we focus on predicting the soil organic carbon within the 0–30 cm soil layer. To achieve this, we utilized one of the largest soil databases of Antarctica, which contains data from 2800 observation sites. In our predictive modeling of SOC stocks, we used relief data and, bioclimatic variables (from Chelsa database) as predictor variables, primarily focusing on temperature, precipitation, and net primary production. The prediction performance of the soil organic carbon stocks model, as measured by concordance correlation coefficient, was 0.52 for the 0-5 cm soil depth, 0.56 for the 5-15 cm depth, and 0.46 for the 15-30 cm depth. Our model reveal that the effects of climate change, primarily changes in temperature and precipitation, are going to increase in soil organic carbon stock (359 ± 146 Mg to 686 ± 197 Mg), indicating that ice-free regions of Maritime and Peninsular Antarctica will tend to function as a carbon sink. However, the magnitude of the soil carbon sink is contingent upon the existing soil organic carbon content and soil depth. The estimated soil organic carbon stocks are controlled mainly by temperature and precipitation, which are interconnected with net primary productivity.
Evaluating the effectiveness of whole blood plasma versus protein precipitates in ovarian cancer detection through infrared spectroscopy
Authors: Neves Ana C. O. , Paraskevaidi Maria , Martin-Hirsch Pierre , G. de Lima Kássio M.
Published: February 2025

ATR-FTIR spectroscopy to analyse blood plasma samples from benign and ovarian cancer cases. Accuracy values of 96% and 92% were achieved for the protein precipitates and whole plasma datasets, respectively.
Unnatural foldamers as inhibitors of Aβ aggregation via stabilizing Aβ helix
Authors: Liu Heng , Zhao Xue , Chen Jianyu , Win Yu Yu , Cai Jianfeng
Published: February 2025

Protein aggregation is a critical factor in the development and progression of several human diseases, including Alzheimer's disease (AD), Huntington's disease, Parkinson's disease, and type 2 diabetes. Among these conditions,...
Tetrasubstituted imidazole-based multifunctional fluorophores: trace water detection and lipid droplets (LDs) imaging studies
Authors: Zafar Mohammad Masood , Yadav Rashmi , Singh Alok , Tyagi Nidhi , Samanta Animesh , Mishra Rakesh K.
Published: February 2025

The tetrasubstituted imidazoles, TSIm-1 & TSIm-2 with flexible and rigid core respectively, displayed the remarkable photophysical properties as well as aggregation-induced emission. TSIm-1 exhibited the trace water detection in THF...
Auto-generating Question-Answering Datasets with Domain-Specific Knowledge for Language Models in Scientific Tasks
Authors: Li Zongqian , Cole Jacqueline
Published: February 2025

Global software giants are relying on a ‘knowledge is power’ style of competitive advantage to back their leading foundational language models. However, many seek to democratize artificial intelligence (AI) as...
Impact of varying the core–shell structural sequence on the efficiency of cascade reagent-free Fenton-like oxidation: the case of magnetically recycling resorcinol–formaldehyde resins/magnetite composite microspheres
Authors: Yang Liang , Wang Yanlong , Chen Tingyu , Liu Lifang , Cai Yun , Fang Jun , Yang Yang
Published: February 2025

Iron-based inorganic–organic hybrid Fenton catalysts, which recently emerged, are recognized as one of the novel materials for the deep mineralization of inert pollutants for environmental remediation in photo-assisted Fenton-like reactions,...
Dietary phytosterol supplementation mitigates renal fibrosis via activating mitophagy and modulating the gut microbiota
Authors: Yang Fan , Gao Yingjie , Xie Siyi , Yang Wenjing , Wang Qiyan , Ye Wenqian , Sun Lu , Zhou Jiangtao , Feng XiuE
Published: February 2025

Chronic kidney disease (CKD) poses a significant global health challenge, primarily driven by renal fibrosis, with limited treatment options.
Dynamic Broadband Plasmonic Absorber enabled by Electrochemical Lithium Metal Batteries
Authors: Huiling Yu
Published: February 2025

As plasmonic absorbers attract considerable attention in the fields of solar energy harvesting, sensors, and cloaking technology, achieving dynamic tuning holds promise for multifunctional applications. However, existent designs face challenges...
Effect of peptide secondary structure on calcium phosphate mineralization for bone regeneration
Authors: Liu Liting , Yin Dongyue , Liu Kexin , Ren Jian , Han Wanru , Deng Chunlin
Published: February 2025

With its helical structure, the P11-4 peptide changed the structure and crystallization of calcium phosphate, enhancing its role in promoting osteogenic differentiation.
Interface-oriented bridges toward efficient carbon-based perovskite solar cells
Authors: Chen Yan , Tong Zhensang , Ding Feifei , Zhou Huanyi , Yang Ye , Huang JinYan , Wei Jianwu , Su Qionghua , Liu Zhihui , Cheng HanChi , Zhou Liya , Chen Peican
Published: February 2025

Interface-oriented chemical bridges.
Structural rigidity, thermochromism and piezochromism of layered hybrid perovskites containing an interdigitated organic bilayer
Authors: Maufort Arthur , Van Landeghem Melissa , Deutsch Maxime , Banks Peter , La Magne Paola , Van Hecke Kristof , Cerdá Jesús , Lutsen Laurence , Vanderzande Dirk , Quarti Claudio , Beljonne David , Pillet Sebastien , Vandewal Koen , Van Gompel Wouter T.M.
Published: February 2025

Layered hybrid perovskites are intensively researched today as highly tunable materials for efficient light harvesting and emitting devices. In classical layered hybrid perovskites, the structural rigidity mainly stems from the...
Dual-Functional Composite Coating with Flame-retardant and Antibacterial Properties for Flexible Polyurethane Foams
Authors: Zeng Ying , Li Zheng , Feng Yeqin , Chi Manzhou , Lv Hongjin , Yang Guo-Yu
Published: February 2025

Dual functionalization of polyurethane (PU) foam to achieve both flame-retardant and antibacterial properties is crucial for meeting stringent fire safety and hygiene standards. Herein, an efficient dual-functional coating, PDA@CS-POM, is...
Investigation of MgO additives on microstructure and properties of thin LLZO electrolytes for all-solid-state batteries
Authors: Go Wooseok , Doeff Marca M. , Tucker Michael C.
Published: February 2025

To realize high-energy density lithium lanthanum zirconate (LLZO)-based solid-state batteries (SSB), LLZO electrolytes should be fabricated with low thickness and high mechanical strength.
Isomer-Driven Pyrazole Frameworks: Structural and Zwitterionic Insights for Advanced Energetics
Authors: Thaltiri Vikranth , Staples Richard J. , Burch Jessica E. , Bera Anshuman , Vennapusa Sivaranjana Reddy , Shreeve Jean'ne M.
Published: February 2025

High-energy density materials (HEDMs) demand innovative molecular strategies for achieving optimized detonation performance, stability, and insensitivity. Now we present an isomer-driven design of two advanced energetic frameworks: high-energy compound 5,...
Sustained acid release from stimuli responsive organic crystals facilitates shape modulation in metal nanoparticle synthesis
Authors: Naim Khalid , Samadder Prodipta , Rahman Atikur , Sahoo Subash Chandra , Neelakandan Prakash P.
Published: February 2025

Stimuli responsive fluorescent materials play an essential role in smart material engineering. We designed molecules that exhibited stimuli responsive luminescence and gradual proton release for the synthesis and passivation of metal nanoparticles.
Can We Trust Our Ears? How Accurate and Reliable Are Speech-Language Pathologists' Estimates of Children's Speech Intelligibility?
Authors: Allison Kristen M. , Millington Marnie , Grimm Alanna
Published: February 2025

Purpose:

This study aimed to investigate the accuracy and reliability of subjective intelligibility estimates of young children's speech made by speech-language pathologists (SLPs) compared to naive listeners, and to examine how the severity of the child's speech impairment influences SLPs' intelligibility estimates.

Method:

Eighteen certified SLPs and 18 naive listeners provided intelligibility ratings of single-word speech samples produced by six preschoolers with speech disorders. All listeners rated intelligibility using two different methods: orthographic transcription and subjective estimation of the percentage of words understood. Absolute differences between estimated and transcription intelligibility scores were used to examine accuracy of intelligibility estimates in both listener groups, and intraclass correlations were used to evaluate interrater reliability.

Results:

Subjective intelligibility estimates differed from orthographic transcription-based intelligibility scores by 12.4% in the SLP listener group and 18.9% in the naive listener group. Interrater reliability of estimated intelligibility was substantially lower than transcription intelligibility in both listener groups.

Conclusion:

Results of this preliminary study suggest that subjective intelligibility estimates by SLPs are not adequately accurate or reliable for measurement of children's speech intelligibility.
Unveiling stellar spin: Determining inclination angles in Be stars
Authors: Turis-Gallo D. , Cur'e M. , Levenhagen R.S. , Arcos C. , Araya I. , Christen A.
Published: February 2025

The physical properties of stellar atmospheres in rapidly rotating massive stars, such as Be stars, are critical to understanding their evolution and their role as progenitors of supernovae. These stars, which often have near-critical rotation, exhibit equatorial stretching and gravity darkening, which significantly complicates the determination of parameters such as the inclination angle. Be stars, characterized by their extreme rotational velocities, serve as excellent candidates for exploring these phenomena. However, fundamental quantities such as polar and equatorial radii and inclination angles are typically derived from interferometry, which applies only to a limited number of stars. This study aims to enhance the determination of inclination angles for Be stars using the ZPEKTR spectral synthesis code. By incorporating advanced models of gravity darkening and stellar deformation, we evaluated the effectiveness of this method with a sample of ten Be stars from the BeSOS database, comparing results with established interferometric data. We used the ZPEKTR code to model the effects of stellar oblateness and gravity darkening on spectral lines, focusing on the HeI 4471 Å line. We applied a χ^2-test minimization approach to identify the best-fitting models, and we evaluated the inclination angles derived against interferometric measurements. Our analysis reveals a robust linear correlation (slope: $0.952 ± 0.033$; R^2 = 0.989) between the inclination angles derived from ZPEKTR and using interferometric techniques, which demonstrates an excellent agreement. The ZPEKTR code effectively models high rotational velocity effects, providing precise stellar parameter determinations. The ZPEKTR code is a powerful tool for estimating inclination angles in Be stars. The results underscore the potential of advanced spectroscopic techniques to yield inclination measurements comparable to interferometry, which offers a pathway to studying distant massive stars for which interferometric observations are not feasible.
ANN-Based Design of a Hybrid Renewable Energy System for Hybrid Electric Vehicle Applications
Authors: Babu Jarapala Ramesh , Murty M.V.D.S. Krishna , Rajashekar Deva , Susheela N.
Published: February 2025

This article examines energy management strategies for hybrid power systems, leveraging an Artificial Neural Network (ANN) to optimize power flow based on real-time needs. The ANN controller ensures maximum power point tracking (MPPT) from renewable sources like photovoltaics (PV), wind turbines (WTs), and fuel cells (FCs), utilizing DC-DC converters. By regulating power flow and dampening fluctuations, the ANN-based method is tested on hybrid setups with PV panels, WTs, and FCs. Simulations in MATLAB/Simulink show that ANN outperforms Fuzzy Logic in MPPT efficiency, particularly for standalone and grid applications at variable loads, enhancing renewable energy reliability.
Design and Implementation of a High-Efficiency 15-Level Asymmetrical Multilevel Inverter for Renewable Energy Applications
Authors: Veeranjaneyulu I Venkata , Kumar Tripathi Abhishek , Pavan Jonnalagadda , Chaitanya Somu , Prasad Ch. V.S.R.
Published: February 2025

The growing use of photovoltaic (PV) plants for energy generation highlights the need for efficient conversion of DC to AC for powering loads or grid integration. Multilevel inverters (MLIs) are an effective solution as their stepped output voltage approximates a sinusoidal waveform, reducing harmonic distortion. However, increasing the number of voltage levels typically requires additional switches and DC sources, complicating the design and control. This paper proposes a novel 15-level asymmetrical MLI that utilizes only 7 switches and 3 asymmetrical DC voltage sources, significantly simplifying the circuit while achieving high performance. The reduced switch count minimizes switching losses, resulting in improved efficiency. The inverter’s design employs a fundamental switching scheme that reduces complexity and enhances overall system efficiency. With a 97.4% switching efficiency, the proposed topology outperforms conventional multilevel inverters in terms of power conversion efficiency. The nearest level control modulation technique is used to generate pulses at the fundamental frequency, ensuring precise control and further reducing total harmonic distortion (THD). MATLAB/Simulink simulations are used to evaluate THD, with results showing a 25% reduction compared to conventional designs, ensuring compliance with IEEE 519 standards. The proposed inverter topology demonstrates significant advantages for renewable energy systems (RES) applications, offering a cost-effective, high-efficiency solution suitable for grid integration and PV applications. The findings suggest further potential for optimization through intelligent control algorithms and closed-loop systems.
Artificial Super Intelligence-Optimized Electric Spring for Hybrid Renewable Energy Systems
Authors: Srujana A. , Rao P. Nageswara , Haritha K. , Babu Viswaprakash
Published: February 2025

This article introduces the design of an advanced smart grid model that optimizes power management through the integration of renewable energy sources. A key innovation lies in the use of a Renewable-Powered Smart Grid System driven by an Artificial Super Intelligence Network (ASIN) to ensure stable voltage profiles and balanced reactive power. The system harnesses solar and wind energy, employing ASIN techniques alongside Electric Spring technology for efficient reactive power control. The seamless integration of renewable sources allows the system to meet grid power demands while managing reactive power effectively. A Feed Forward Neural Network (FFNN) is utilized to optimize power calculations, determining voltage profiles, and minimizing power losses based on varying load conditions. The Electric Spring acts as an optimal VAR compensating device, keeping reactive power within permissible limits, thereby improving voltage stability, reducing losses, and maintaining reactive power balance across the grid. The proposed system is implemented and tested in a MATLAB/Simulink environment under three distinct scenarios. Results indicate that the hybrid energy-powered smart grid meets its performance objectives efficiently. Notably, the integration of renewable sources with ASIN enhances the voltage profile by approximately 97.70% increasing it from 1.074 to 1.083 p. u. Additionally, real power losses are reduced from 3.531 MW to 3.45 MW, demonstrating the system’s improved efficiency.
Design and Economic Optimization of Microgrid
Authors: Syed Mahaboob Shareef , Prasanth B. Venkata , Kumaraswamy I , Raju B. Sreenivasa , Ramya P. Sai , Rao Y. Ranga
Published: February 2025

In modern electrical systems, microgrids plays vital role in enhancing performance of the power system. The analysis uses HOMER tool for the simulation. Microgrids are small in ratings compared to the conventional energy sources and are independent power producers that can be more reliable and eco-friendly. HOMER helps to determine the proper combination of energy sources. The study considers the real time location of GUNTUR which is present in Andhra Pradesh state of INDIA. In the considered location to incorporate renewable energy sources in to the microgrid, the potential of wind and solar availability was estimated first. The simulation findings show that using HOMER microgrids use less non-renewable energy, work efficiently and with less operating cost to run. This gives an optimized solution for the sustained and smart power utilization.
Fuzzy Controlled MPPT to Grid Connected PV Systems
Authors: Sukumar G. Durga , Prasad R. Ramanjan , Vardhan R. Harsha , Pakkiraiah B. , Krishna Ch. Leela
Published: February 2025

Solar photovoltaic (PV) energy stands as a predominant source of renewable power. The efficiency of energy conversion from sunlight via photovoltaic panels is subject to fluctuation due to varying solar intensity and radiation levels. To optimize the power output, the Maximum Power Point Tracking (MPPT) technique is pivotal. Among the various methods available, high- performance soft computing techniques serve as robust MPPT strategies. This paper introduces a Fuzzy Logic Controller (FLC)-based MPPT system for grid-connected PV systems operating under both steady and variable climatic conditions. The FLC-based MPPT system adeptly adjusts the PV system’s voltage, current, and power settings to harness the maximum feasible power output from the photovoltaic panels. Simulation outcomes demonstrate that the FLC- based MPPT system outperforms the conventional Perturb and Observe (P&O) MPPT method. The employment of a fuzzy logic-controlled grid connection for PV systems heralds significant enhancements in the efficiency, stability, and reliability of integrating renewable energy into the electrical grid. Leveraging fuzzy logic algorithms, this technique allows for dynamic power management, precise voltage regulation, and enhanced frequency stability, effectively mitigating the issues inherent to intermittent solar power. A notable strength of this approach is its inherent flexibility, adapting in real-time to fluctuating environmental and grid conditions, thereby optimizing system performance across diverse scenarios. Furthermore, the implementation of a fuzzy logic- controlled grid connection ensures smooth integration of PV systems into the grid, reducing risks associated with grid disturbances, voltage fluctuations, and frequency anomalies. This strategy not only bolsters the reliability of renewable energy sources but also enhances grid resilience against variable demand and generation dynamics. In summary, the integration of fuzzy logic-controlled connections presents a forward-thinking solution that significantly advances PV system integration into the grid, yielding marked improvements in efficiency, reliability, and overall grid stability. Fuzzy logic-based MPPT offers a robust and adaptable approach to tracking the maximum power point in grid-connected PV systems, overcoming some of the limitations of traditional methods like P&O.