bluuebunny/crossref_metadata_2025 huggingface dataset:
Sub-Nyquist Harmonic Current Component Extraction using Band Pass Filters for NILM
Authors: Jung Guyeop , Kim Geun Young , Ahn Sung-Hoon
Published: February 2025

As environmental issues emerge, interest in monitoring power consumption is increasing, and Non-Intrusive Load Monitoring (NILM) has gained attention as a method for this. Recent advancements in artificial intelligence (AI) have improved the performance of NILM systems in terms of accuracy and inference time. However, due to insufficient research on data acquisition methods, the practicality of implementing these systems remains limited. This study focuses on the development of an IoT-based edge device acquiring current harmonic component with sub-Nyquist sampling using a Band Pass Filter (BPF) approach. The primary objective is to extract high-frequency harmonic components from AC power signals at sampling rates lower than traditionally required rate, addressed by the Nyquist-Shannon sampling theorem. To validate the effectiveness of the collected current harmonic components, an SVM algorithm was embedded into the device to perform a simple classification task. The device achieved 100% accuracy with an inference time of 584 ms. This innovative approach enables simultaneous multi-channel monitoring using a single low-performance NILM device. This contributes to reducing the costs associated with energy monitoring while enhancing the scalability of energy management points.
Soil Characteristics Rather Than Microbial Inoculation Determines The Effects Of Alternative Phosphorus-Fertilizers On Ryegrass Yield And The Soil Microbial Community
Authors: García-Díaz Celia , Siles José A. , Bastida Felipe , Moreno José Luis
Published: February 2025

With global phosphate rock resources declining for conventional fertilizers, there is growing interest in exploring alternative, more sustainable materials to enhance soil fertility and crop yield production. Additionally, leveraging microorganisms to improve phosphorus (P) availability in soils is an appealing approach for sustainable agriculture. This study evaluates the effects of different P-rich materials, including struvite (STRU), meat and bone meal (MBM), and phosphate rock (PR), combined with a microbial consortium with P-solubilizing and plant growth-promoting capabilities, on P availability and plant growth in two soils with contrasting physicochemical properties. To achieve these goals, a pot experiment was conducted to assess P content in soil, ryegrass, and microbial biomass, along with microbial enzyme activity and community composition using microbial fatty acid analysis. The experiment involved two soils with contrasting characteristics, amended with conventional monoammonium phosphate (CHEM), STRU, MBM, and PR, with or without microbial inoculation. Soil characteristics and the type of P fertilizer significantly influenced P availability, ryegrass uptake, and plant yield. Microbial inoculation did not increase soil P or ryegrass yield. Fatty acid analysis showed microbial community changes with soil characteristics and fertilizer. Struvite performed similarly to CHEM, while MBM was less effective than struvite but better than PR as a P fertilizer. Our study found that soil characteristics and the type of phosphate fertilizer affected soil P dynamics in the soil–plant system. Recycled P-based fertilizers offer sustainable alternatives to synthetic ones, potentially alleviating agricultural challenges.
Comparison of the Perlite, Leonardite, Vermicompost and Peat Moss and Their Combinations with Cocopeat as Tomato Growing Media
Authors: Erdal İbrahim , Aktaş Hakan
Published: February 2025

Study was aimed to compare the effects of individual usage of substrates perlite, leonardite, vermicompost, and peat moos alone and their mixtures with cocopeat on the growth, yield and mineral nutrition of tomato. Each substrate was used as a control in itself, and they mixed with cocopeat at the rate of 1:1, 1:2, 1:4 (V/V) and thus 17 growing media (GM) were obtained. The seedlings of tomato were planted in 7 l GM containing pots then watered during the first week, then drip-irrigated with nutrient solution. The research was arranged as a four-replication greenhouse experiment. The amount of the applied nutrient solution was adjusted manually until 10–30% leaching ratio. The highest biomass was recorded from the plants grown in solely peat moss and 1/2 cocopeat/peat moss medium, on the other hand plants grown in solely leonardite had the lowest vegetative biomass. The highest fruit yields were obtained from plants grown in solely peat, the lowest yield was recorded from the plant grown in vermicompost. In general, vermicompost and cocopeat + vermicompost mixtures were the most effective media on the leaf and fruit nutrient concentrations of tomatoes, but it was observed that this affected vegetative growth rather than fruit yield. In conclusion, it can be said that the most effective individual substrate on the growth and fruit yield was peat moss. On the other hand, it was seen that substrates such as vermicompost and leonardite, which do not give successful results when used alone, become more usable media when mixed with cocopoeat.
Leveraging augmented reality in education involving new pedagogies with emerging societal relevance
Authors: Mirza Tabasum , Dutta Rubina , Tuli Neha , Mantri Archana
Published: February 2025

Recent innovations and development in educational technologies have revolutionized the methods and tools used for teaching and learning. Among these innovative technologies augmented reality is emerging as a promising educational technology that can be used by teachers in classrooms. Augmented Reality (AR) has gained popularity in education because of its positive impact on learner motivation, situational interest and memory retention. AR provides authentic learning opportunities to students by allowing three-dimensional interaction with the digital elements overlaid in their natural environment. This study aims at identifying different challenges and issues in existing AR applications from the pedagogical point of view with the help of literature review and teacher survey. In the present study two research questions have been designed as: to analyze various challenges and issues in integration of augmented reality technology for education. To identify pedagogical issues in use of augmented reality technology. The main goal of this study was to examine this relationship using two core operational issues: identifying pedagogical concerns in the usage of augmented reality and examining the advantages and difficulties of integrating augmented reality technology for education. About 24.3% of teachers use mobile applications based on augmented reality to teach. The percentage of teachers that use mobile applications for teaching is only 27.2%, while 72.8% do not use them. The findings can help researchers and developers in understanding the pedagogical issues that should be considered for design and development of AR applications in order to achieve learning outcomes effectively.

Clinical trial number: Not applicable.
Design for operator contestability: control over autonomous systems by introducing defeaters
Authors: Veluwenkamp Herman , Buijsman Stefan
Published: February 2025

This paper introduces the concept of Operator Contestability in AI systems: the principle that those overseeing AI systems (operators) must have the necessary control to be accountable for the decisions made by these algorithms. We argue that designers have a duty to ensure operator contestability. We demonstrate how this duty can be fulfilled by applying the'Design for Defeaters' framework, which provides strategies to embed tools within AI systems that enable operators to challenge decisions. Defeaters are designed to contest either the justification for the AI’s data inputs (undercutting defeaters) or the validity of the conclusions drawn from that data (rebutting defeaters). To illustrate the necessity and application of this framework, we examine case studies such as AI-driven recruitment processes, where operators need tools and authority to uncover and address potential biases, and autonomous driving systems, where real-time decision-making is crucial. The paper argues that operator contestability requires ensuring that operators have (1) epistemic access to the relevant normative reasons and (2) the authority and cognitive capacity to act on these defeaters. By addressing these challenges, the paper emphasizes the importance of designing AI systems in a way that enables operators to effectively contest AI decisions, thereby ensuring that the appropriate individuals can take responsibility for the outcomes of human-AI interactions.
Hydrochemical assessment of borehole water in Effurun, Delta state Niger Delta, Nigeria: implications for public health and safety
Authors: Ojo Odunayo Tope , Ike Chiaka Joy , Aladeboyeje Adegoke Ige , Olaseeni Olayiwola Grace , Adewumi Olumuyiwa Femi
Published: February 2025

Borehole water plays a critical role in providing drinking water in Effurun, Delta State, Nigeria. However, concerns about potential contamination from both natural and anthropogenic sources necessitate regular groundwater quality assessments. This study evaluates the hydrochemical properties of borehole water to ensure public health safety and to understand the groundwater's suitability for consumption. The aim of this study is to assess the quality of borehole water in Effurun by analyzing major ions, trace metals, and other hydrochemical parameters, and to compare the findings with WHO and NSDWQ drinking water standards. Ten borehole water samples were collected from various locations across Effurun. Hydrochemical analyses were conducted to measure cations (calcium, magnesium, sodium, potassium), anions (chloride, bicarbonate, sulfate, nitrate), and trace metals (lead, copper, zinc, manganese). Statistical analysis and spatial mapping were employed to evaluate the distribution of ion concentrations and identify areas of concern. Calcium levels in the boreholes ranged from 29.95 mg/L to 64.50 mg/L, while magnesium levels were more consistent, ranging between 9.50 mg/L and 14.20 mg/L. Sodium and potassium showed moderate correlations with calcium. Chloride levels varied widely, indicating potential contamination from seawater intrusion or industrial discharge. Elevated sulfate and nitrate concentrations pointed to agricultural runoff. Trace metals, particularly lead, exceeded safety limits, with lead concentrations ranging from 0.092 mg/L to 0.127 mg/L, posing significant health risks. Spatial analysis revealed varying ion concentrations across Effurun, with higher calcium and magnesium levels near water bodies, suggesting local geology's influence. The central area exhibited moderate ion concentrations, while the southeastern region had the highest calcium levels, possibly due to geological formations rich in calcium or human activities. The study highlights diverse hydrochemical characteristics of Effurun's borehole water, with some areas showing contamination beyond acceptable limits. Regular monitoring is essential to ensure safe drinking water and address potential health risks. The findings stress the need for improved water resource management and contamination control. This study provides a comprehensive spatial analysis of groundwater quality in Effurun, identifying specific areas at risk of contamination and offering data-driven recommendations for public health and sustainable water management.
Prismatic Dieudonné Theory – ERRATUM
Authors: Anschütz Johannes , Le Bras Arthur-César
Published: February 2025

A proof of a proposition in the published paper was erroneous. We clarify the effects in this erratum.
A characterisation of higher torsion classes
Authors: August Jenny , Haugland Johanne , Jacobsen Karin M. , Kvamme Sondre , Palu Yann , Treffinger Hipolito
Published: February 2025

Let
$\mathcal {A}$
be an abelian length category containing a d-cluster tilting subcategory
$\mathcal {M}$
. We prove that a subcategory of
$\mathcal {M}$
is a d-torsion class if and only if it is closed under d-extensions and d-quotients. This generalises an important result for classical torsion classes. As an application, we prove that the d-torsion classes in
$\mathcal {M}$
form a complete lattice. Moreover, we use the characterisation to classify the d-torsion classes associated to higher Auslander algebras of type
$\mathbb {A}$
, and give an algorithm to compute them explicitly. The classification is furthermore extended to the setup of higher Nakayama algebras.
Legacy Effects and Arbuscular Mycorrhizal Fungi of Linaria vulgaris Invasion in Colorado and Illinois, USA
Authors: Novak Logan , Mueller Gregory M. , Egerton-Warburton Louise M.
Published: February 2025

Invasive plants’ ability to extend their range depends upon their local environment and both positive and negative interactions with native species. Interactions between invasive and native plants may be indirectly linked to the soil fungal community, which may enhance or suppress invasion through mutualism or parasitism. Many invasive plants preferentially select fungal communities or change soil chemistry to gain a competitive advantage, and such changes can remain even after the invader is removed, known as legacy effects. Linaria vulgaris is an invasive forb that is aggressive in the Western U.S. but is non-aggressive in the Midwestern U.S. We evaluated the relationship between soil abiotic properties, nitrogen (N) enrichment, arbuscular mycorrhizal fungal (AMF) community composition and L. vulgaris invasion in aggressive (CO) and non-aggressive (IL) populations. We collected soil from uninvaded and invaded sites in Gothic, CO, and near Chicago, IL, and sequenced AMF community composition in each site. Using the same soil, we grew L. vulgaris and native species for 120 days, with half of pots receiving N-fertilization, and harvested biomass. We also injected a 15N-labelled tracer in pots and analyzed plant tissue for 15N enrichment and N uptake rates (NUR). In CO soil, L. vulgaris rhizomes sprouted more in invaded soil, whereas in IL soil, L. vulgaris only sprouted in uninvaded soil. N-fertilization had no impact on biomass and NUR did not differ significantly between any treatment. AMF communities differed between the two sites but were not significantly influenced by invasion history. Our results suggest that L. vulgaris leaves legacy effects, but that these effects are different between aggressive and non-aggressive populations. Legacy effects may facilitate reinvasion in CO, but we did not find conclusive evidence of legacy effects in IL, and differences between the sites could be shaped by endemic AMF communities.
Evaluation of elevated band height for basal bark triclopyr applications to Schinus terebinthifolia
Authors: Oberweger Conrad A. , Enloe Stephen F. , Wilson Christopher P. , Prince Candice M. , Sperry Benjamin P.
Published: February 2025

Basal bark application involves applying an oil-soluble herbicide in an oil carrier to the lower 0 to 45-cm of woody stems. For triclopyr, basal bark application typically requires the butoxyethyl ester formulation; however, this cannot be applied when standing water is present, which is common in seasonally flooded wetlands. Recently, the intermediate oil and water-soluble triclopyr acid formulation was registered for use in aquatic sites, allowing for basal bark applications in wetlands where standing water is present. Recent studies indicated that flooding after basal bark treatment can result in triclopyr release to surface waters and subsequent non-target injury. Elevated band application height (i.e., treating a higher band on each stem) may reduce non-target injury potential; however, this modified application technique has not been well tested on woody invasive species. To evaluate this approach, a field study on Schinus terebinthifolia was conducted near Melbourne and Wimauma, FL on well-established and juvenile rootstocks. Treatments included triclopyr acid at 17, 34, and 69 g L-1 applied in an oil carrier and treatment band heights of 0 to 45-cm and 61 to 107-cm from the ground line. At Melbourne, both band heights treated with 34 or 69 g L-1 resulted in 75 to 100% mortality of mature rootstocks. However, triclopyr applied at 17 g L-1 to the low and elevated band heights resulted in 70 and 11% mortality, respectively. All treatments resulted in 90 to 100% mortality at Wimauma, where the rootstocks were juvenile and much smaller. These findings indicate elevated band heights may be a useful approach for woody plant control and may support an effective management strategy in inundated wetlands that provides better prevention of non-target injury.
Economic abuse, the bank, and the devil in the detail: One Savings Bank plc v Catherine Waller-Edwards [2024] EWCA Civ 302
Authors: Rowan Eleanor
Published: February 2025

In One Savings Bank plc v Catherine Waller-Edwards,1 the Court of Appeal considered – for the first time – whether banks are put on constructive notice to potential undue influence in joint benefit remortgage/suretyship hybrid transactions. At a time where there is an increasing awareness of economic abuse as a form of domestic abuse,2 this appeal offered an important opportunity to reassess banks’ responsibilities in assisting potential victim-survivors. Unfortunately, that opportunity was not seized. In this case comment, I set out the negative impacts the Court of Appeal judgment could have on victim-survivors of economic abuse going forward, and how these concerns could – since this case has now been given leave to appeal – be addressed by the Supreme Court.
Tailoring Narratives on War in Ukraine: Cross-national Study of Sputnik News
Authors: Burda Robin , Bundzíková Veronika
Published: February 2025

The article analyses how Russian state-controlled media adapt narratives across their language versions to speak to specific national audiences. These media support the Kremlin by echoing its strategic narratives in the international arena. Our article stems from the assumption that the media tailor the narratives and do not deliver homogenous news. Texts published since the initial days of the Russian invasion of Ukraine were analyzed from Sputnik Czech Republic, Germany, and Sputnik World, known to spread the Russian regime’s propaganda. The central question was how the Russian regime depicted and explained the invasion of Ukraine in 2022 in the chosen languages. Qualitative coding based on a predefined codebook, modified with codes inductively acquired during the analysis, was used to deeply understand strategic narratives and identify key differences among the Russian regime’s influence campaigns in various national contexts. Some narratives were found to differ based on the national contexts, strengthening the initial assumption. However, analyzed texts also consistently depict Russia as a victim and the West as a threat across the language versions.
Effects of probiotic supplementation on intestinal flora, brain–gut peptides and clinical outcomes in children with anorexia nervosa
Authors: Lu Xiaoyan , Liu Yali , Hao Longxia , Li Junqiong , Hua Linjuan
Published: February 2025

This study aims to assess the therapeutic effects of probiotic oral therapy in paediatric patients with anorexia nervosa (AN) and to investigate its impact on intestinal flora composition, brain–gut peptide levels and overall clinical outcomes. A retrospective study was conducted involving 100 children diagnosed with AN at Xingtang County People’s Hospital between January 2023 and June 2024. Patients were divided into two groups: a control group (n 50) receiving zinc gluconate oral solution alone and an observation group (n 50) receiving zinc gluconate plus probiotics. Outcome measures included intestinal flora analysis, brain–gut peptide levels (somatostatin (SS) and nitric oxide (NO)), clinical efficacy, serum trace element levels (Ca, Zn and Fe) and prognosis, including recurrence rates 6 months post-treatment. Baseline characteristics were similar between the two groups (P > 0·05). After treatment, the observation group showed significantly higher levels of Bifidobacterium and Lactobacillus and lower levels of Enterobacter compared with the control group (P < 0·05). Additionally, the observation group had lower levels of SS and NO (P < 0·05), indicating improved brain–gut communication. Clinical efficacy was significantly higher in the observation group (P < 0·05), with improved serum trace element levels (P < 0·05 for Ca, Zn and Fe). Furthermore, the recurrence rate 6 months post-treatment was significantly lower in the observation group compared with the control group (P < 0·05). Probiotic supplementation in children with AN effectively modulates intestinal flora, improves brain–gut peptide levels and enhances clinical outcomes.
Biomarkers of food intake: current status and future opportunities
Authors: Brennan Lorraine
Published: February 2025

The current review will examine the field of food intake biomarkers and the potential use of such biomarkers. Biomarkers of food intake have the potential to be objective measures of intake thus addressing some of the limitations associated with self-reported dietary assessment methods. They are typically food-derived biomarkers present in biological samples and distinct from endogenous metabolites. To date, metabolomic profiling has been successful in identifying several putative food intake biomarkers. With respect to food intake biomarkers, there has been a proliferation of publications in this field. However, caution is needed when interpreting these as food intake biomarkers. Many have not been validated thus hampering their use. While much of the focus to date is on discovery of food intake biomarkers there are excellent examples of how to utilise these biomarkers in nutrition research. Applications include but are not limited to: (1) measurement of adherence to diets in intervention studies (2) objectively predicting intake with no reliance on self-reported data and (3) calibrating self-reported data in large epidemiological studies. Examples of these applications will be covered in this review. While significant progress is achieved to date in the food intake biomarkers field there are a number of key challenges that remain. Examples include lack of databases focused on food-derived metabolites thus hindering the discovery of new biomarkers and the need for new statistical approaches to deal with multiple biomarkers for single foods. Addressing these and other key challenges will be key to development of future opportunities.
‘More Prussian than the Prussian’? Battlefield Prisoner Killing by British and Canadian Forces on the Western Front, 1914–1918
Authors: Kay Alex J.
Published: February 2025

Many historians continue to regard the killing of prisoners and potential prisoners on the battlefield as having been an absolute exception during the Great War, something that was ‘episodic’ and happened only ‘in isolated cases’. One reason for this assessment might be the fact that the subject has rarely been examined empirically. This article is the first study directly to compare the actions of the British and the Canadians, the Empire’s two largest armies on the western front. Drawing on a wide range of primary source material, including, for the first time, unit war diaries and after-action reports, this article reveals that documentary evidence exists for scores of separate instances of prisoner killing by British and Canadian troops deployed against German forces between August 1914 and November 1918, with the number of dead ranging from individual enemy soldiers to several hundred victims at once. Examples are recorded of prisoner killing by enlisted men, NCOs and officers, acting either in groups or alone, and furthermore of officers at platoon, battalion, regimental and even corps level either encouraging prisoner killing or issuing explicit ‘take no prisoners’ orders. The level of acceptance that commanders showed for these practices, the openness with which soldiers discussed them in their letters home to mothers, sisters and wives, and the almost complete absence of any disciplinary action against the perpetrators indicate that – on some level – they were regarded as legitimate.
Analyzing lexical-semantic networks in Alzheimer’s disease patients: eye-tracking study
Authors: Arias-Trejo Natalia , Angulo-Chavira Armando Quetzalcóatl , González-González Martha M. , Minto-García Aline
Published: February 2025

Adults have an interconnected lexicon in which two words are related because their referents belong to the same semantic category, because they occur in the same context, or both. This interconnection has been explored by means of the priming effect, in which people respond more rapidly to related than to unrelated words and benefit from the lexical boost when the two types of interconnections are combined. Although substantial research has reported on the memory problems of people diagnosed with Alzheimer’s disease (AD), it remains unknown whether they experience problems with related words at these levels of comprehension. This study analyzed the lexical networks of older adults with AD and typically aging (TA) adults to understand their semantic memory related to word associations. We tested combined taxonomic-thematic, purely taxonomic, and purely thematic relationships using an eye tracker to analyze fixations to a named target picture preceded by a related or unrelated prime word. Participants with TA showed a priming effect in all three types of relationships, but those with AD showed this effect only with purely thematic pairs. Words that share more than one level of relationship seem to create competition, revealing a deficit in the lexical networks of people with AD.
Choreographing Deportation in David Herrera's TOUCH
Authors: Aldape Muñoz Juan Manuel
Published: February 2025

Deportations and the threat of removal are choreographic strategies of the nation-state's ever-growing monopoly of movement through border securitization and immigration enforcement, which persists into the twenty-first century. While literature and the visual arts have received critical and popular attention by considering forced family separations, dance remains overlooked. Analyzing dance performances that relate directly to deportation teaches us not only about the painful impact of forced removal: it instructs us to decode, move and maintain relationships as aliens and citizens amid the increasing control of motion in the United States and the cruel joke offered by a nation of immigrants.
Design of robust fractional order fuzzy PID sliding mode controller based on hybrid swarm intelligence algorithm for a 6-DOF robotic manipulator
Authors: Karahan Oguzhan , Karci Hasan
Published: February 2025

In this paper, fractional-order (FO), intelligent, and robust sliding mode control (SMC) and stabilization of inherently nonlinear, multi-input, multi-output 6-DOF robot manipulators are investigated. To ensure robust control and better performance of the robot system, significant studies on various control transactions have been explored. First, a sliding proportional-integral-derivative (PID) surface is conceived and then its FO constitute is developed. It is an important fact that in SMC, the reaching phase is fast and the chattering is abated in the sliding phase. In particular, the discontinuity in the SMC is prevented in view of the boundary layer obtained by recommending the sigmoid function together with fuzzy logic to eliminate the chattering phenomenon. A hybrid tuning method consisting of gray wolf optimization and particle swarm optimization (GWO-PSO) algorithms is applied to tune the parameters of PID sliding mode control (PIDSMC), FO PIDSMC (FOPIDSMC), fuzzy PIDSMC (FPIDSMC), and FO fuzzy PIDSMC (FOFPIDSMC) controllers. In simulation results, the tuned FOFPIDSMC controller consistently outperforms PIDSMC, FOPIDSMC, and FPIDSMC controllers tuned by the GWO-PSO in dynamic performance, trajectory tracking, disturbance rejection, and mass uncertainty scenarios. It has been seen through a thorough performance analysis that 91.93% and 44.13% improvement are, respectively, obtained for mean absolute error (MAE) and torques root mean square (RMS) values of the joints when using from the PIDSMC to the FOFPIDSMC. Finally, the simulation outcomes reveal the superior aspects of the designed FOFPIDSMC and also demonstrate that the FOFPIDSMC controller enhances the dynamic performances of the 6-revolute universal robots 5 (6R UR5) robot manipulator under a variety of operating conditions.
CHRONOLOGICALLY TRIMMED LS FOR NONLINEAR PREDICTIVE REGRESSIONS WITH PERSISTENCE OF UNKNOWN FORM
Authors: Hu Zhishui , Kasparis Ioannis , Wang Qiying
Published: February 2025

Relatively, recent work by Jeganathan (2008, Cowles Foundation Discussion Paper 1649) and Wang (2014, Econometric Theory, 30(3), 509–535) on generalized martingale central limit theorems (MCLTs) implicitly introduces a new class of instrument arrays that yield (mixed) Gaussian limit theory irrespective of the persistence level in the data. Motivated by these developments, we propose a new semiparametric method for estimation and inference in nonlinear predictive regressions with persistent predictors. The proposed method that we term chronologically trimmed least squares (CTLS) is comparable to the IVX method of Phillips and Magdalinos (2009, Econometric inference in the vicinity of unity. Mimeo, Singapore Management University) and yields conventional inference in regressions where the nature and extent of persistence in the data are uncertain. In terms of model generality, our contribution to the existing literature is twofold. First, our covariate model space allows for both nearly integrated (NI) and fractional processes (stationary and nonstationary) as a special case, while the vast majority of articles in this area only consider NI arrays. Second, we allow for nonlinear regression functions. The CTLS estimator is obtained by applying certain chronological trimming to the OLS instruments using appropriate kernel functions of time trend variables. In particular, the instruments under consideration are a generalized (averaged) version of those widely used for time-varying parameter (TVP) models. For the purposes of our analysis, we develop a novel asymptotic theory for sample averages of various processes weighted by such kernel functionals which is of independent interest and highly relevant to the TVP literature. Leveraging our nonlinear framework, we also provide an investigation on the effects of misbalancing on the predictability hypothesis. A new methodology is proposed to mitigate misbalancing effects. These methods are used for exploring the predictability of SP500 returns.
America the Failure? Critical Narratives of the United States in Chinese State Media
Authors: Carothers Christopher , Freedman Joshua B.
Published: February 2025

As relations between the United States and China have grown tenser, how has the Chinese Communist Party's (CCP) portrayal of the United States changed? And what might portrayals of the United States tell us about domestic messaging in China? This study systematically investigates CCP messaging about the United States in the contemporary era. To do this, we hand code, categorize and analyse 1,761 editorials about the United States published between 2003 and 2022 in People's Daily, the Party's flagship newspaper. In addition to showing a sustained rise in critical portrayals since 2018, we identify and elaborate three distinct critical narratives about the United States: it is a dangerous hegemon abroad, it has poor values at home, and it is increasingly weak and in decline. These narratives appear both independently and in combination and are often framed to contrast with portrayals of China. We argue that these narratives are not just negative propaganda to discredit the United States but can also be a strategy to promote a positive vision of the CCP's virtues and governance at home. This study contributes empirically and theoretically to research on propaganda and legitimation in China.
Dientamoeba fragilis cases identified by molecular detection, Utah, United States, 2014–2024
Authors: Jones Anna , Couturier Marc Roger , Pavia Andrew T. , Leung Daniel T.
Published: February 2025

Dientamoeba fragilis (D. fragilis) is an intestinal protozoan parasite with uncertain pathogenic potential. In the United States, data on D. fragilis in the era of molecular detection are limited. The aim of this retrospective chart review was to evaluate the epidemiology and clinical characteristics of D. fragilis cases identified using polymerase chain reaction assays between 2016 and 2024 at our academic medical centre located in Utah. We identified 28 unique cases with varying gastrointestinal symptomatology including diarrhoea, abdominal pain, nausea, vomiting, and bloating. Approximately half (52%) of patients with follow-up data demonstrated improvement in symptoms following initial treatment for D. fragilis. The overall prevalence of D. fragilis was low among those tested (0.6% positivity). Additional research, including case-control studies, is needed to better describe the etiologic role of D. fragilis.
Face enumeration for split matroid polytopes
Authors: Ferroni Luis , Schröter Benjamin
Published: February 2025

This paper initiates the explicit study of face numbers of matroid polytopes and their computation. We prove that, for the large class of split matroid polytopes, their face numbers depend solely on the number of cyclic flats of each rank and size, together with information on the modular pairs of cyclic flats. We provide a formula which allows us to calculate

$f$

-vectors without the need of taking convex hulls or computing face lattices. We discuss the particular cases of sparse paving matroids and rank two matroids, which are of independent interest due to their appearances in other combinatorial and geometric settings.
Human rights at sea: Analyzing states’ responses to cruise ships during the COVID-19 pandemic
Authors: CHEN Lixin
Published: February 2025

In the early stages of the COVID-19 pandemic, the treatment of cruise ships by coastal states was inconsistent, with some ships being allowed to dock while others were not. To that end, this Note focuses on the obligations that a coastal state owes to the individuals onboard the cruise ships in the context of the COVID-19 pandemic, including the rights to life and health. It further considers whether and how such rights are to be balanced with other countervailing considerations of such states, such as the risk of transmission to the local communities. This author concludes with the view that individuals onboard the cruise ships can, and should, consider turning to international human rights law for guidance and recourse. After all, the human rights regime is most suited for and accustomed to governing the relationship between individuals and a state, as compared to between states.
Mechanisms Behind the Long‐Distance Diurnal Offshore Precipitation Propagation in Northwestern South America
Authors: Hu Jingyi , Chen Xingchao
Published: February 2025

Northwestern South America (NWSA) is the rainiest region on Earth, with diurnal precipitation exhibiting extensive westward offshore propagation of up to about 1,200 km in boreal spring (March‐May). The diurnal offshore precipitation propagation begins slowly (3–10 m s−1) near the coast of NWSA (<200 km) but accelerates significantly (∼20 m s−1) and shows an afternoon enhancement far from the coast (>400 km). However, the driving mechanisms behind this long‐distance precipitation propagation remain unclear. Using a new cloud tracking and classification data set, we found that mesoscale convective systems (MCSs) are the dominant precipitation contributors in the offshore region of NWSA. Cloud tracking shows that the long‐distance propagation and the afternoon enhancement of diurnal precipitation primarily originate from MCSs initiated in the early morning, either over open oceans or from the coast of Central America. Composite tendency analysis shows that MCSs initiated near the coast of Central America have significant upward cooling and moistening signals starting from the surface before initiation. Further analysis of surface diurnal perturbation fields indicates that the land breeze is the primary driving mechanism for MCS initiation. Conversely, for MCSs initiated over open oceans, a significant downward cooling signal from 400 hPa is observed ∼7 hr before initiation, corresponding to the passage of diurnal gravity waves emitted from the Andes. Additionally, our findings highlight the critical role of lower and mid‐level moisture conditions in MCS initiation, alongside the influence of gravity waves.
Substorm Identification With the WINDMI Magnetosphere ‐ Ionosphere Nonlinear Physics Model
Authors: Adhya P. , Spencer E. , Kayode‐Adeoye M.
Published: February 2025

We investigate the applicability and performance of the plasma physics based WINDMI model to the analysis and identification of substorm onsets. There are several substorm onset criteria that have been developed into event lists, either from auroral observations or from auroral electrojet features. Five of these substorm onset lists are available at the SuperMAG website. We analyze these lists, aggregate them and use the WINDMI model to assess the identified events, emphasizing the loading/unloading mechanism in substorm dynamics. The WINDMI model employs eight differential equations utilizing solar wind data measured at L1 by the ACE satellite as input to generate outputs such as the magnetotail current, the ring current and the field‐aligned currents (FACs). In particular, the WINDMI model current output represents the westward auroral electrojet, which is related to the substorm SML index. We analyze a decade of solar wind and substorm onset data from 1998 to 2007, encompassing 39,863 onsets. Our findings reveal a significant correlation, with WINDMI‐derived enhancements in FAC coinciding with the identified substorm events approximately 32% of the time. This suggests that a substantial proportion of substorms may be attributed to solar wind driving that results in the loading and unloading of energy in the magnetotail.
RA‐ConvLSTM: Recurrent‐Architecture Attentional ConvLSTM Networks for Prediction of Global Total Electron Content
Authors: Xue Kaiyu , Shi Chuang , Wang Cheng
Published: February 2025

The ionosphere poses a significant source of error in satellite‐based navigation systems for aviation and radio communication applications. Accurate estimation of the total electron content (TEC) can effectively mitigate the impact of such errors. However, constrained by observational techniques, the acquisition of global ionospheric TEC in practical applications relies heavily on high‐precision forecasting products. In this study, we construct a global ionospheric forecasting model based on the global ionospheric TEC products disseminated by the International GNSS Service (IGS) and deep learning. We incorporate an attention module to extract global spatiotemporal features from historical ionospheric data and employ these features to predict the TEC values over the next 24 hr. Additionally, we select a long short‐term memory (LSTM) model and a ConvLSTM model as baseline models for comparison, conducting experiments under varying solar activity conditions. The experimental results demonstrate that RA‐ConvLSTM model outperforms the other two models in quantifying the performance of the models. During high solar activity years, the bias and Root Mean Square Error (RMSE) of RA‐ConvLSTM model are −0.0298 TECU and 3.8980 TECU, respectively, while during low solar activity years, these values are 0.0905 TECU and 1.5059 TECU, marking a notable improvement over the comparative models. Furthermore, by contrasting the precision of the three forecasting models during geomagnetic storms, the RA‐ConvLSTM model exhibits the least fluctuations in accuracy, indicative of a higher degree of stability in its forecasting outcomes.
Single-shot super-resolved fringe projection profilometry (SSSR-FPP): 100,000 frames-per-second 3D imaging with deep learning
Authors: Wang Bowen , Chen Wenwu , Qian Jiaming , Feng Shijie , Chen Qian , Zuo Chao
Published: February 2025

To reveal the fundamental aspects hidden behind a variety of transient events in mechanics, physics, and biology, the highly desired ability to acquire three-dimensional (3D) images with ultrafast temporal resolution has been long sought. As one of the most commonly employed 3D sensing techniques, fringe projection profilometry (FPP) reconstructs the depth of a scene from stereo images taken with sequentially structured illuminations. However, the imaging speed of current FPP methods is generally capped at several kHz, which is limited by the projector-camera hardware and the number of fringe patterns required for phase retrieval and unwrapping. Here we report a novel learning-based ultrafast 3D imaging technique, termed single-shot super-resolved FPP (SSSR-FPP), which enables ultrafast 3D imaging at 100,000 Hz. SSSR-FPP uses only one pair of low signal-to-noise ratio (SNR), low-resolution, and pixelated fringe patterns as input, while the high-resolution unwrapped phase and fringe orders can be deciphered with a specific trained deep neural network. Our approach exploits the significant speed gain achieved by reducing the imaging window of conventional high-speed cameras, while “regenerating” the lost spatial resolution through deep learning. To demonstrate the high spatio-temporal resolution of SSSR-FPP, we present 3D videography of several transient scenes, including rotating turbofan blades, exploding building blocks, and the reciprocating motion of a steam engine, etc., which were previously challenging or even impossible to capture with conventional methods. Experimental results establish SSSR-FPP as a significant step forward in the field of 3D optical sensing, offering new insights into a broad spectrum of dynamic processes across various scientific disciplines.
REDD1 expression in podocytes facilitates renal inflammation and pyroptosis in streptozotocin-induced diabetic nephropathy
Authors: Sunilkumar Siddharth , Subrahmanian Sandeep M. , Yerlikaya Esma I. , Toro Allyson L. , Harhaj Edward W. , Kimball Scot R. , Dennis Michael D.
Published: February 2025

Sterile inflammation resulting in an altered immune response is a key determinant of renal injury in diabetic nephropathy (DN). In this investigation, we evaluated the hypothesis that hyperglycemic conditions augment the pro-inflammatory immune response in the kidney by promoting podocyte-specific expression of the stress response protein regulated in development and DNA damage response 1 (REDD1). In support of the hypothesis, streptozotocin (STZ)-induced diabetes increased REDD1 protein abundance in the kidney concomitant with renal immune cell infiltration. In diabetic mice, administration of the SGLT2 inhibitor dapagliflozin was followed by reductions in blood glucose concentration, renal REDD1 protein abundance, and immune cell infiltration. In contrast with diabetic REDD1+/+ mice, diabetic REDD1−/− mice did not exhibit albuminuria, increased pro-inflammatory factors, or renal macrophage infiltration. In cultured human podocytes, exposure to hyperglycemic conditions promoted REDD1-dependent activation of NF-κB signaling. REDD1 deletion in podocytes attenuated both the increase in chemokine expression and macrophage chemotaxis under hyperglycemic conditions. Notably, podocyte-specific REDD1 deletion prevented the pro-inflammatory immune cell infiltration in the kidneys of diabetic mice. Furthermore, exposure of podocytes to hyperglycemic conditions promoted REDD1-dependent pyroptotic cell death, evidenced by an NLRP3-mediated increase in caspase-1 activity and LDH release. REDD1 expression in podocytes was also required for an increase in pyroptosis markers in the glomeruli of diabetic mice. The data support that podocyte-specific REDD1 is necessary for chronic NF-κB activation in the context of diabetes and raises the prospect that therapies targeting podocyte-specific REDD1 may be helpful in DN.
Degradable hypercrosslinked porous polymer generated from aromatic polyketone
Authors: Zheng Handou , Tu Guangshui , Du Cheng , Gao Heng , Pei Lixia , Gao Haiyang
Published: February 2025

Although hypercrosslinked porous polymers as highly efficient adsorbents can remove pollutants, hypercrosslinked polymers (HCPs) themselves are also a source of white plastic pollution. Development of degradable HCPs is highly desirable based on the full environmental protection concept. In this paper, we reported the direct synthesis of hypercrosslinked polyketones (HCPK-X, X = H, OtBu) generated from degradable aromatic polyketones via external crosslinking technique. The hypercrosslinked structure of HCPK-X was fully characterized, and HCPK-OtBu had a mesopores structure (1.27–68.5 nm) and large surface area (S
BET = 321 m2/g). HCPK-OtBu exhibits a good adsorption capability for aniline removal from aqueous solution, and its enhanced adsorption capability is ascribed to the interactions between aniline and the carbonyl and tert-butoxy groups. The photodegradation of hypercrosslinked polyketones was evaluated and emphasized. The prepared hypercrosslinked polyketones can rapidly and efficiently decompose under UV light irradiation, which represents the first sample of degradable hypercrosslinked polymers.
BenthicNet: A global compilation of seafloor images for deep learning applications
Authors: Lowe Scott C. , Misiuk Benjamin , Xu Isaac , Abdulazizov Shakhboz , Baroi Amit R. , Bastos Alex C. , Best Merlin , Ferrini Vicki , Friedman Ariell , Hart Deborah , Hoegh-Guldberg Ove , Ierodiaconou Daniel , Mackin-McLaughlin Julia , Markey Kathryn , Menandro Pedro S. , Monk Jacquomo , Nemani Shreya , O’Brien John , Oh Elizabeth , Reshitnyk Luba Y. , Robert Katleen , Roelfsema Chris M. , Sameoto Jessica A. , Schimel Alexandre C. G. , Thomson Jordan A. , Wilson Brittany R. , Wong Melisa C. , Brown Craig J. , Trappenberg Thomas
Published: February 2025

Advances in underwater imaging enable collection of extensive seafloor image datasets necessary for monitoring important benthic ecosystems. The ability to collect seafloor imagery has outpaced our capacity to analyze it, hindering mobilization of this crucial environmental information. Machine learning approaches provide opportunities to increase the efficiency with which seafloor imagery is analyzed, yet large and consistent datasets to support development of such approaches are scarce. Here we present BenthicNet: a global compilation of seafloor imagery designed to support the training and evaluation of large-scale image recognition models. An initial set of over 11.4 million images was collected and curated to represent a diversity of seafloor environments using a representative subset of 1.3 million images. These are accompanied by 3.1 million annotations translated to the CATAMI scheme, which span 190,000 of the images. A large deep learning model was trained on this compilation and preliminary results suggest it has utility for automating large and small-scale image analysis tasks. The compilation and model are made openly available for reuse.