bluuebunny/crossref_metadata_2025 huggingface dataset:
The DMA’s Consent Moment and its Relationship with the GDPR
Authors: D’Amico Alessia S.
Published: June 2024

The Digital Markets Act (DMA) is designed to ensure fair and contestable digital markets. With one of the key sources of market power of big tech being data, it is not surprising that it is the subject matter of a number of DMA provisions. Article 5(2) prohibits gatekeepers from engaging in forms of accumulation and cross-use of personal data, unless they receive users’ consent, defined by reference to the General Data Protection Regulation (GDPR).

Consent as defined by the GDPR suffers from a number of shortcomings, among other things, relating to whether consent can be truly freely given. The DMA tries to address some of the shortcomings by formulating a version of consent that seemingly goes beyond the GDPR. While a new version of consent may ensure greater effectiveness, it raises questions concerning the interaction and compatibility with the GDPR.

To shed light on this issue, the paper discusses the role and meaning of consent in the DMA vis-à-vis the GDPR and explores how to interpret consent under both the DMA and GDPR in a manner that is consistent with each other and that accounts for the characteristics of digital markets.
Society for Healthcare Epidemiology of America position statement on pandemic preparedness for policymakers: mitigating supply shortages
Authors: Weber David Jay , Malani Anurag N. , Shenoy Erica S. , Banach David B. , Batshon Lynne Jones , Branch-Elliman Westyn , Dumyati Ghinwa , Haessler Sarah , Hsu Vincent P. , Jump Robin L.P. , Mathew Trini A. , Murthy Rekha K. , Pergam Steven A.
Published: June 2024

The COVID-19 has had major direct (e.g., deaths) and indirect (e.g., social inequities) effects in the United States. While the public health response to the epidemic featured some important successes (e.g., universal masking ,and rapid development and approval of vaccines and therapeutics), there were systemic failures (e.g., inadequate public health infrastructure) that overshadowed these successes. Key deficiency in the U.S. response were shortages of personal protective equipment (PPE) and supply chain deficiencies. Recommendations are provided for mitigating supply shortages and supply chain failures in healthcare settings in future pandemics. Some key recommendations for preventing shortages of essential components of infection control and prevention include increasing the stockpile of PPE in the U.S. National Strategic Stockpile, increased transparency of the Stockpile, invoking the Defense Production Act at an early stage, and rapid review and authorization by FDA/EPA/OSHA of non-U.S. approved products. Recommendations are also provided for mitigating shortages of diagnostic testing, medications and medical equipment.
Vulnerability of firn to hydrofracture: poromechanics modeling
Authors: Meng Yue , Culberg Riley , Lai Ching-Yao
Published: June 2024

On the Greenland Ice Sheet, hydrofracture connects the supraglacial and subglacial hydrologic systems, coupling surface runoff dynamics and ice velocity. In recent decades, the growth of low-permeability ice slabs in the wet snow zone has expanded Greenland's runoff zone, but observations suggest that surface-to-bed connections are rare, because meltwater drains through crevasses into the porous firn beneath ice slabs. However, there is little quantitative evidence confirming the absence of surface-to-bed fracture propagation. Here, we use poromechanics to investigate whether water-filled crevasses in ice slabs can propagate vertically through an underlying porous firn layer. Based on numerical simulations, we develop an analytical estimate of the water injection-induced effective stress in the firn given the water level in the crevasse, ice slab thickness, and firn properties. We find that the firn layer substantially reduces the system's vulnerability to hydrofracture because much of the hydrostatic stress is accommodated by a change in pore pressure, rather than being transmitted to the solid skeleton. This result suggests that surface-to-bed hydrofracture will not occur in ice slab regions until all pore space proximal to the initial flaw has been filled with solid ice.
Are Firms Gerrymandered?
Authors: ARTÉS JOAQUÍN , KAUFMAN AARON R. , RICHTER BRIAN K. , TIMMONS JEFFREY F.
Published: June 2024

We provide the first evidence that firms, not just voters, are gerrymandered. We compare allocations of firms in enacted redistricting plans to counterfactual distributions constructed using simulation methods. We find that firms are over-allocated to districts held by the mapmakers’ party when partisans control the redistricting process; maps drawn by courts and independent commissions allocate firms more proportionately. Our results hold when we account for the gerrymandering of seats: fixing the number of seats the mapmakers’ party wins, they obtain more firms than expected in their districts. Our research reveals that partisan mapmakers target more than just voters, shedding new light on the link between corporate and political power in the United States and opening new pathways for studying how mapmakers actually draw district boundaries.
Non-agreeing degree constructions
Authors: Mendia Jon Ander , Espinal M.Teresa
Published: June 2024

This paper deals with a construction, which we dub Non-Agreeing Degree (NAD) constructions, with the distinguishing property that the agreement pattern between subjects and degree predicates is optionally disrupted, even in languages (like Spanish) where verbs commonly agree with their subjects. We show that the agreeing versus non-agreeing alternation comes with important semantic differences for the interpretation of the degree construction. We provide a first systematic description of this type of constructions and postulate a formal syntactic and semantic analysis. We argue that NAD constructions are characterized by degree predicates that introduce a non-conventional nominal scale and by subjects that are interpreted as equally non-conventional units of measurement. We postulate an intensionalization process on the subject of NAD constructions, which we capture via a general nominalization function that allows a default as well as an ordinary agreement pattern between subject and copula.
Methodological issues in Rma etymology
Authors: Sims Nathaniel
Published: June 2024

This paper examines the state-of-the-art for the historical study of the Rma (Qiang) language (< Trans-Himalayan/Sino-Tibetan) and points out some methodological issues in earlier work. The paper discusses how vowel correspondences have been obfuscated by loanwords, onomatopoeic forms, and analogical levelling. It also discusses the analysis of compound forms and points out how certain compound forms have been incorrectly etymologized. It deals with broader, more fundamental issues in prior work such as top-down rather than bottom-up reconstructions, and problematic conceptualizations of what constitutes reconstructions. The article offers potential solutions to the issues discussed and points out where future work would be most profitable.
The hospital as a laboratory: Population studies at Tel-Hashomer hospital in Israel (1950s-1960s)
Authors: Barell Ari , Kirsh Nurit
Published: June 2024

Argument

In this article we examine how a leading Israeli hospital gradually became a large biomedical research facility, resembling a huge laboratory. For Chaim Sheba (1908-1971), the founder and first director of Tel-Hashomer Hospital, the massive immigration to Israel in the 1950s was a unique opportunity for research of diverse human populations, especially Jews who had arrived to Israel from Asia and Africa. The paper focuses on the way research and medical practices were integrated and their boundaries blurred, and studies the conditions under which an entire hospital became a research field. Using the case of one of Israel’s prominent medical institutes, we explore and expand upon the idea of “the hospital as a laboratory,” arguing that, for Sheba, it was not only the hospital but the entire country that functioned as a great research site—a vast laboratory that “had no walls.”
The Ancients and the Moderns: Chasles on Euclid’s lost Porisms and the pursuit of geometry
Authors: Michel Nicolas , Smadja Ivahn
Published: June 2024

Of Euclid’s lost manuscripts, few have elicited as much scholarly attention as the Porisms, of which a couple of brief summaries by late-Antiquity commentators are extant. Despite the lack of textual sources, attempts at restoring the content of this absent volume became numerous in early-modern Europe, following the diffusion of ancient mathematical manuscripts preserved in the Arabic world. Later, one similar attempt was that of French geometer Michel Chasles (1793–1880). This paper investigates the historiographical tenets and practices involved in Chasles’ restoration of the porisms, as well as the philosophical and mathematical claims tentatively buttressed therewith. Echoes of the Quarrel of the Ancients and the Moderns, and of a long-standing debate on the authority and usefulness of the past, are shown to have decisively shaped Chasles’ enterprise—and, with it, his integration of mathematical and historical research.
Agreement between retrospective and prospective assessments of childhood abuse revisited
Authors: Nivison Marissa D. , Filetti Clarissa R. , Carlson Elizabeth A. , Jacobvitz Deborah B. , Roisman Glenn I.
Published: June 2024

A recent meta-analytic review demonstrated that retrospective assessments of childhood abuse acquired during adulthood – typically via self-report – demonstrate weak agreement with assessments of maltreatment gathered prospectively. The current report builds on prior findings by investigating the agreement of prospectively documented abuse from birth to age 17.5 years in the Minnesota Longitudinal Study of Risk and Adaptation with retrospective, Adult Attachment Interview-based assessments of childhood abuse administered at ages 19 and 26 years. In this sample, an agreement between prospective and retrospective assessments of childhood abuse was considerably stronger (κ = .56) than was observed meta-analytically. Retrospective assessments identified prospectively documented sexual abuse somewhat better than physical abuse, and the retrospective approach taken here was more sensitive to identifying abuse perpetrated by primary caregivers compared to non-caregivers based on prospective records.
Monitoring bird migration using nocturnal flight calls on the East Asian–Australasian Flyway: a case from Beijing
Authors: Liu Shuangqi , Townshend Terry , Farnsworth Andrew , Alexander Danny , Tian Hua , Hua Fangyuan
Published: June 2024

Migratory birds are experiencing widespread population declines, underscoring the urgency of effective conservation actions. Long-term monitoring of migratory birds, especially during migration, is crucial for such actions yet remains technically challenging. Bioacoustic monitoring of nocturnal flight calls (NFCs) constitutes a promising technique to monitor migratory birds during migration. Such monitoring has increased in North America and Europe, but its application on the East Asian–Australasian Flyway (EAAF) remains limited. Here, we present findings from an NFC monitoring project conducted at a recording station in central Beijing, China over four migration seasons. From around 3,350 hours of recording effort, we manually extracted and identified 84,135 NFCs, involving at least 111 species or species groups that are associated with a wide range of habitat types. We also found that NFCs provided additional information on species’ migration phenology in comparison with citizen science observation data. To our knowledge, this study is the first formal investigation of bird migration using NFC monitoring on the EAAF, serving as a proof-of-concept case for wider, long-term monitoring efforts in this traditionally understudied region. Our findings also highlight the significance of incorporating migratory bird conservation into urban planning and land management practices.
Experiments on Landquakes Generated by Free‐Falling Granular Masses: Implications for Rockfall Impact Dynamics
Authors: Li Tianhua , Wang Yufeng , Cheng Qiangong , Lin Qiwen , Shi Anwen , Ming Jie , Luo Xiao
Published: June 2024

The properties of rockfalls, such as the volume and geometry of the detached rock mass as well as the number and diameter of rock fragments, greatly affect their propagated behavior, and different strategies are required to mitigate rockfall hazards. Landquakes generated by rockfalls are regarded as good proxies for those properties. To explore the free‐fall impact dynamics of rockfalls, a series of free‐fall experiments on granular masses were designed and conducted with the characteristics of the generated landquakes versus initial variables being analyzed. The results show that the particle diameter is a dominant factor affecting landquakes, with the most significant effect on the mean frequency. The impact area is another key factor, with which both the maximum seismic amplitude and radiated seismic energy have strong positive correlations, while the mean frequency of landquakes shows a weak negative correlation. The maximum seismic amplitude appears to have a poor correlation with the numbers of layers of the free‐falling granular masses, and it was proven that the maximum seismic amplitude is determined by only the lower part of the granular masses. Quantitative relationships between the number of particles and seismic signal characteristics indicate that disintegration needs to be accounted for when landquakes are used to investigate the characteristics of a rockfall. Moreover, the frequency of landquakes decreases with a decrease in the vertical velocity and increase in the horizontal velocity during granular mass collapse.
Feasibility of Formulating Ecosystem Biogeochemical Models From Established Physical Rules
Authors: Tang Jinyun , Riley William J. , Manzoni Stefano , Maggi Federico
Published: June 2024

To improve the predictive capability of ecosystem biogeochemical models (EBMs), we discuss the feasibility of formulating biogeochemical processes using physical rules that have underpinned the many successes in computational physics and chemistry. We argue that the currently popular empirically based approaches, such as multiplicative empirical response functions and the law of the minimum, will not lead to EBM formulations that can be continuously refined to incorporate improved mechanistic understanding and empirical observations of biogeochemical processes. Instead, we propose that EBM parameterizations, as a lossy data compression problem, can be better formulated using established physical rules widely used in computational physics and chemistry, and different biogeochemical processes can be more robustly integrated within a reactive‐transport framework. Through several examples, we demonstrate how mathematical representations derived from physical rules can improve understanding of relevant biogeochemical processes and enable more effective communication between modelers, observationalists, and experimentalists regarding essential questions, such as what measurements are needed to meaningfully inform models and how can models generate new process‐level hypotheses to test in empirical studies. Finally, while empirical models with more parameters are often less robust, physical rules‐based models can be more robust and show lower predictive equifinality, stemming from their enhanced consistency in representations of processes, interactions and spatial scaling.
Magnetic Barriers Might Explain Mysterious Hot Jupiters
Authors: O’Callaghan Jonathan
Published: June 2024

Hot Jupiters might end up very close to stars because a magnetic field halts their progress—and future observations could confirm the idea.
Kinetic Signatures, Dawn‐Dusk Asymmetries, and Flux Transfer Events Associated With Mercury's Dayside Magnetopause Reconnection From 3D MHD‐AEPIC Simulations
Authors: Li Changkun , Jia Xianzhe , Chen Yuxi , Toth Gabor , Zhou Hongyang , Slavin James A. , Sun Weijie , Poh Gangkai
Published: June 2024

Mercury possesses a miniature yet dynamic magnetosphere driven primarily by magnetic reconnection occurring regularly at the magnetopause and in the magnetotail. Using the newly developed Magnetohydrodynamics with Adaptively Embedded Particle‐in‐Cell (MHD‐AEPIC) model coupled with planetary interior, we have performed a series of global simulations with a range of upstream conditions to study in detail the kinetic signatures, asymmetries, and flux transfer events (FTEs) associated with Mercury's dayside magnetopause reconnection. By treating both ions and electrons kinetically, the embedded PIC model reveals crescent‐shaped phase‐space distributions near reconnection sites, counter‐streaming ion populations in the cusp region, and temperature anisotropies within FTEs. A novel metric and algorithm are developed to automatically identify reconnection X‐lines in our 3D simulations. The spatial distribution of reconnection sites as modeled by the PIC code exhibits notable dawn‐dusk asymmetries, likely due to such kinetic effects as X‐line spreading and Hall effects. Across all simulations, simulated FTEs occur quasi‐periodically every 4–9 s. The properties of simulated FTEs show clear dependencies on the upstream solar wind Alfvénic Mach number (MA) and the interplanetary magnetic field orientation, consistent with MESSENGER observations and previous Hall‐MHD simulations. FTEs formed in our MHD‐AEPIC model tend to carry a large amount of open flux, contributing ∼3%–36% of the total open flux generated at the dayside. Taken together, our MHD‐AEPIC simulations provide new insights into the kinetic processes associated with Mercury's magnetopause reconnection that should prove useful for interpreting spacecraft observations, such as those from MESSENGER and BepiColombo.
Associations between media parenting practices and early adolescent screen use
Authors: Nagata Jason M. , Paul Angel , Yen Felicia , Smith-Russack Zacariah , Shao Iris Yuefan , Al-shoaibi Abubakr A. A. , Ganson Kyle T. , Testa Alexander , Kiss Orsolya , He Jinbo , Baker Fiona C.
Published: June 2024

Background

To assess the prevalence of various media parenting practices and identify their associations with early adolescent screen time and problematic social media, video game, and mobile phone use.

Methods

Cross-sectional data from Year 3 of the Adolescent Brain Cognitive Development (ABCD) Study (2019–2022) that included 10,048 adolescents (12–13 years, 48.3% female, 45.6% racial/ethnic minorities) in the US were analyzed using multiple linear regression analyses adjusting for potential confounders.

Results

Parent screen use, family mealtime screen use, and bedroom screen use were associated with greater adolescent screen time and problematic social media, video game, and mobile phone use. Parental use of screens to control behavior (e.g., as a reward or punishment) was associated with higher screen time and greater problematic video game use. Parental monitoring of screens was associated with lower screen time and less problematic social media and mobile phone use. Parental limit setting of screens was associated with lower screen time and less problematic social media, video game, and mobile phone use.

Discussion

Parent screen use, mealtime screen use, and bedroom screen use were associated with higher adolescent problematic screen use and could be limited in a family media use plan. Parental monitoring and limiting of screen time are associated with less problematic screen use.

Impact statement

Although the American Academy of Pediatrics provides guidance for screen use for children 5–18 years, there is a paucity of evidence-based guidance for media parenting practices, specifically for early adolescents.

In a diverse sample of 10,048 early adolescents across the US, we found cross-sectional associations between parent, mealtime, and bedroom screen use and higher adolescent problematic screen use.

Parental monitoring and limiting of adolescent screen time were cross-sectionally associated with less problematic screen use in our analytic sample and may be incorporated into a family media use plan.
Identification of cross reactive T cell responses in adenovirus based COVID 19 vaccines
Authors: Gardner Joshua , Abrams Simon Timothy , Toh Cheng-Hock , Parker Alan L. , Lovatt Charlotte , Nicolson Phillip L. R. , Watson Steve P. , Grice Sophie , Hering Luisa , Pirmohamed Munir , Naisbitt Dean J.
Published: June 2024

Vaccination has proven to be a valuable tool to combat SARS-CoV-2. However, reports of rare adverse reactions such as thrombosis/thrombocytopenia syndrome after ChAdOx1 nCoV-19 vaccination have caused scientific, public and media concern. ChAdOx1 was vectorised from the Y25 chimpanzee adenovirus, which was selected due to low human seroprevalence to circumvent pre-existing immunity. In this study, we aimed to explore patterns of T-cell activation after SARS-CoV-2 COVID-19 vaccine exposure in vitro using PBMCs collected from pre-pandemic ChAdOx1 nCoV-19 naïve healthy donors (HDs), and ChAdOx1 nCoV-19 and Pfizer vaccinated controls. PBMCs were assessed for T-cell proliferation using the lymphocyte transformation test (LTT) following exposure to SARS-CoV-2 COVID-19 vaccines. Cytokine analysis was performed via intracellular cytokine staining, ELISpot assay and LEGENDplex immunoassays. T-cell assays performed in pre-pandemic vaccine naïve HDs, revealed widespread lymphocyte stimulation after exposure to ChAdOx1 nCoV-19 (95%), ChAdOx-spike (90%) and the Ad26.COV2. S vaccine, but not on exposure to the BNT162b2 vaccine. ICS analysis demonstrated that CD4+ CD45RO+ memory T-cells are activated by ChAdOx1 nCoV-19 in vaccine naïve HDs. Cytometric immunoassays showed ChAdOx1 nCoV-19 exposure was associated with the release of proinflammatory and cytotoxic molecules, such as IFN-γ, IL-6, perforin, granzyme B and FasL. These studies demonstrate a ubiquitous T-cell response to ChAdOx1 nCoV-19 and Ad26.COV2. S in HDs recruited prior to the SARS-CoV-2 pandemic, with T-cell stimulation also identified in vaccinated controls. This may be due to underlying T-cell cross-reactivity with prevalent human adenoviruses and further study will be needed to identify T-cell epitopes involved.
Companies inadvertently fund online misinformation despite consumer backlash
Authors: Ahmad Wajeeha , Sen Ananya , Eesley Charles , Brynjolfsson Erik
Published: June 2024

The financial motivation to earn advertising revenue has been widely conjectured to be pivotal for the production of online misinformation1–4. Research aimed at mitigating misinformation has so far focused on interventions at the user level5–8, with little emphasis on how the supply of misinformation can itself be countered. Here we show how online misinformation is largely financed by advertising, examine how financing misinformation affects the companies involved, and outline interventions for reducing the financing of misinformation. First, we find that advertising on websites that publish misinformation is pervasive for companies across several industries and is amplified by digital advertising platforms that algorithmically distribute advertising across the web. Using an information-provision experiment9, we find that companies that advertise on websites that publish misinformation can face substantial backlash from their consumers. To examine why misinformation continues to be monetized despite the potential backlash for the advertisers involved, we survey decision-makers at companies. We find that most decision-makers are unaware that their companies’ advertising appears on misinformation websites but have a strong preference to avoid doing so. Moreover, those who are unaware and uncertain about their company’s role in financing misinformation increase their demand for a platform-based solution to reduce monetizing misinformation when informed about how platforms amplify advertising placement on misinformation websites. We identify low-cost, scalable information-based interventions to reduce the financial incentive to misinform and counter the supply of misinformation online.
Observation of 2D-magnesium-intercalated gallium nitride superlattices
Authors: Wang Jia , Cai Wentao , Lu Weifang , Lu Shun , Kano Emi , Agulto Verdad C. , Sarkar Biplab , Watanabe Hirotaka , Ikarashi Nobuyuki , Iwamoto Toshiyuki , Nakajima Makoto , Honda Yoshio , Amano Hiroshi
Published: June 2024

Since the demonstration of p-type gallium nitride (GaN) through doping with substitutional magnesium (Mg) atoms1,2, rapid and comprehensive developments, such as blue light-emitting diodes, have considerably shaped our modern lives and contributed to a more carbon-neutral society3–5. However, the details of the interplay between GaN and Mg have remained largely unknown6–11. Here we observe that Mg-intercalated GaN superlattices can form spontaneously by annealing a metallic Mg film on GaN at atmospheric pressure. To our knowledge, this marks the first instance of a two-dimensional metal intercalated into a bulk semiconductor, with each Mg monolayer being intricately inserted between several monolayers of hexagonal GaN. Characterized as an interstitial intercalation, this process induces substantial uniaxial compressive strain perpendicular to the interstitial layers. Consequently, the GaN layers in the Mg-intercalated GaN superlattices exhibit an exceptional elastic strain exceeding −10% (equivalent to a stress of more than 20 GPa), among the highest recorded for thin-film materials12. The strain alters the electronic band structure and greatly enhances hole transport along the compression direction. Furthermore, the Mg sheets induce a unique periodic transition in GaN polarity, generating polarization-field-induced net charges. These characteristics offer fresh insights into semiconductor doping and conductivity enhancement, as well as into elastic strain engineering of nanomaterials and metal–semiconductor superlattices13.
Migraine incidence and coffee consumption among child-bearing age women: the Korea Nurses’ Health Study
Authors: Cha Chiyoung , Kim Oksoo , Pang Yanghee , Jeong Hyunseon , Lee Jung Eun , Lee Heayoung , Dan Hyunju
Published: June 2024

This longitudinal study aimed to identify factors that influence migraines in Korean women nurses using data from the Korea Nurses’ Health Study. Among those who participated in Survey 1 (2013–2014) and the follow-up survey (2015–2019), we selected 2605 participants for Cox proportional hazard regression analysis, 521 participants who were newly diagnosed with migraine and 2084 controls using a 1:4 incidence density sampling approach. Consuming coffee (≥ 3 cups: RR = 1.666; 95% CI = 1.175–2.362, < 3 cups: RR = 1.439; 95% CI = 1.053–1.966), being obese (BMI ≥ 25: RR = 1.341, 95% CI = 1.003–1.793), and engaging in vigorous physical activity (RR = 1.010; 95% CI = 1.000–1.019) increased the risk of developing a migraine. Nurses with an annual salary greater than $3500 were less likely to develop migraines (RR = 0.786, 95% CI = 0.631–0.979). The results imply that lifestyle factors, such as the amount of coffee consumption, BMI level, and degree of physical activity could be considered when formulating treatment plans for women who have newly developed migraines.
Facile synthesis of iron nanoparticles from Camellia Sinensis leaves catalysed for biodiesel synthesis from Azolla filiculoides
Authors: Sundararaman Sathish , Karthikeyan M. , Aravind kumar J. , Deivasigamani Prabu , Soosai Michael Rahul , Ramaraja A. , Sahana S. , Thamer Badr M. , El-Newehy Mohamed H. , Rajasimman M. , T R Praveenkumar
Published: June 2024

Recent years have seen an increase in research on biodiesel, an environmentally benign and renewable fuel alternative for traditional fossil fuels. Biodiesel might become more cost-effective and competitive with diesel if a solid heterogeneous catalyst is used in its production. One way to make biodiesel more affordable and competitive with diesel is to employ a solid heterogeneous catalyst in its manufacturing. Based on X-ray diffraction (XRD) and Fourier Transform infrared spectroscopy (FTIR), the researchers in this study proved their hypothesis that iron oxide core–shell nanoparticles were generated during the green synthesis of iron-based nanoparticles (FeNPs) from Camellia Sinensis leaves. The fabrication of spherical iron nanoparticles was successfully confirmed using scanning electron microscopy (SEM). As a heterogeneous catalyst, the synthesised catalyst has shown potential in facilitating the conversion of algae oil into biodiesel. With the optimal parameters (0.5 weight percent catalytic load, 1:6 oil—methanol ratio, 60 °C reaction temperature, and 1 h and 30 min reaction duration), a 93.33% yield was attained. This may be due to its acid–base property, chemical stability, stronger metal support interaction. Furthermore, the catalyst was employed for transesterification reactions five times after regeneration with n-hexane washing followed by calcination at 650 °C for 3 h.
The enhanced photocatalytic performance of CPAA doping with different concentrations of Titanium oxide nanocomposite against MB dyes under simulated sunlight irradiations
Authors: Sayed Marwa M. , Aboraia Abdelaziz M. , Kasem Yara A. , Elewa Nancy N. , Ismail Yasser A. M. , Aly Kamal I.
Published: June 2024

The pure conjugated polyarylene azomethine (CPAA) and its nanocomposites (CPAA-TiO2) with different concentrations of TiO2 nanoparticles were successfully prepared by in-situ technique and analyzed by different advanced techniques. XRD has confirmed the structural properties and crystallinity of (CPAA) and nanocomposites. The SEM clearly shows that the (CPAA) is uniform and homogeneous, with tightly connected aggregate layers in shape. However, the amount of TiO2 in the nanocomposites greatly affects their morphology, revealing structural differences and indicating a reaction between (CPAA) and TiO2, especially at a higher concentration of 5% TiO2. A new composite of (CPAA) was introduced and the photocatalytic effect for MB was studied. The removal efficiency of (pure-CPAA) over MB dye under simulated sunlight was 62%. However, (CPAA-TiO2 1%) destroyed 90% of MB dyes. It was discovered that the low band gap of (CPAA-TiO2 1% (2.84 eV)) accelerates high electron–hole recombination, increasing photocatalytic activity.
Urinary beta-2 microglobulin increases whereas TIMP-2 and IGFBP7 decline after unilateral nephrectomy in healthy kidney donors
Authors: de Rooij Esther N. M. , Hoogeveen Ellen K. , Romijn Fred P. H. T. M. , van der Kooy Sandra W. , Veighey Kristin V. , Dekker Friedo W. , van Kooten Cees , Cobbaert Christa M. , de Fijter Johan W.
Published: June 2024

Early kidney injury may be detected by urinary markers, such as beta-2 microglobulin (B2M), tissue inhibitor of metalloproteinases-2 (TIMP-2), insulin-like growth factor-binding protein 7 (IGFBP7), kidney injury molecule-1 (KIM-1) and/or neutrophil gelatinase-associated lipocalin (NGAL). Of these biomarkers information on pathophysiology and reference ranges in both healthy and diseased populations are scarce. Differences in urinary levels of B2M, TIMP-2, IGFBP7, KIM-1 and NGAL were compared 24 h before and after nephrectomy in 38 living kidney donors from the REnal Protection Against Ischaemia–Reperfusion in transplantation study. Linear regression was used to assess the relation between baseline biomarker concentration and kidney function 1 year after nephrectomy. Median levels of urinary creatinine and creatinine standardized B2M, TIMP-2, IGFBP7, KIM-1, NGAL, and albumin 24 h before nephrectomy in donors were 9.4 mmol/L, 14 μg/mmol, 16 pmol/mmol, 99 pmol/mmol, 63 ng/mmol, 1390 ng/mmol and 0.7 mg/mmol, with median differences 24 h after nephrectomy of − 0.9, + 1906, − 7.1, − 38.3, − 6.9, + 2378 and + 1.2, respectively. The change of donor eGFR after 12 months per SD increment at baseline of B2M, TIMP-2, IGFBP7, KIM-1 and NGAL was: − 1.1, − 2.3, − 0.7, − 1.6 and − 2.8, respectively. Urinary TIMP-2 and IGFBP7 excretion halved after nephrectomy, similar to urinary creatinine, suggesting these markers predominantly reflect glomerular filtration. B2M and NGAL excretion increased significantly, similar to albumin, indicating decreased proximal tubular reabsorption following nephrectomy. KIM-1 did not change considerably after nephrectomy. Even though none of these biomarkers showed a strong relation with long-term donor eGFR, these results provide valuable insight into the pathophysiology of these urinary biomarkers.
A novel model for relation prediction in knowledge graphs exploiting semantic and structural feature integration
Authors: Yang Jianliang , Lu Guoxuan , He Siyuan , Cao Qiuer , Liu Yuenan
Published: June 2024

Relation prediction is a critical task in knowledge graph completion and associated downstream tasks that rely on knowledge representation. Previous studies indicate that both structural features and semantic information are meaningful for predicting missing relations in knowledge graphs. This has led to the development of two types of methods: structure-based methods and semantics-based methods. Since these two approaches represent two distinct learning paradigms, it is difficult to fully utilize both sets of features within a single learning model, especially deep features. As a result, existing studies usually focus on only one type of feature. This leads to an insufficient representation of knowledge in current methods and makes them prone to overlooking certain patterns when predicting missing relations. In this study, we introduce a novel model, RP-ISS, which combines deep semantic and structural features for relation prediction. The RP-ISS model utilizes a two-part architecture, with the first component being a RoBERTa module that is responsible for extracting semantic features from entity nodes. The second part of the system employs an edge-based relational message-passing network designed to capture and interpret structural information within the data. To alleviate the computational burden of the message-passing network on the RoBERTa module during the sampling process, RP-ISS introduces a node embedding memory bank, which updates asynchronously to circumvent excessive computation. The model was assessed on three publicly accessible datasets (WN18RR, WN18, and FB15k-237), and the results revealed that RP-ISS surpasses all baseline methods across all evaluation metrics. Moreover, RP-ISS showcases robust performance in graph inductive learning.
Ecological restoration at pilot-scale employing site-specific rationales for small-patch degraded mangroves in Indian Sundarbans
Authors: Ray Krishna , Basak Sandip Kumar , Giri Chayan Kumar , Kotal Hemendra Nath , Mandal Anup , Chatterjee Kiranmoy , Saha Subhajit , Biswas Biswajit , Mondal Sumana , Das Ipsita , Ghosh Anwesha , Bhadury Punyasloke , Joshi Rahul
Published: June 2024

To date, degraded mangrove ecosystem restoration accomplished worldwide primarily aligns towards rehabilitation with monotypic plantations, while ecological restoration principles are rarely followed in these interventions. However, researchers admit that most of these initiatives' success rate is not appreciable often. An integrative framework of ecological restoration for degraded mangroves where site-specific observations could be scientifically rationalized, with co-located reference pristine mangroves as the target ecosystem to achieve is currently distinctively lacking. Through this experimental scale study, we studied the suitability of site-specific strategies to ecologically restore degraded mangrove patches vis-à-vis the conventional mono-species plantations in a highly vulnerable mangrove ecosystem in Indian Sundarbans. This comprehensive restoration framework was trialed in small discrete degraded mangrove patches spanning ~ 65 ha. Site-specific key restoration components applied are statistically validated through RDA analyses and Bayesian t-tests. 25 quantifiable metrics evaluate the restoration success of a ~ 3 ha degraded mangrove patch with Ridgeline distribution, Kolmogorov–Smirnov (K-S) tests, and Mahalanobis Distance (D2) measure to prove the site’s near-equivalence to pristine reference in multiple ecosystem attributes. This restoration intervention irrevocably establishes the greater potential of this framework in the recovery of ecosystem functions and self-sustenance compared to that of predominant monoculture practices for vulnerable mangroves.
Model test study on the mechanical response of the deep buried tunnel lining
Authors: Duan Longyan , Feng Jimeng , Song Jiadai , Yao Shiyu
Published: June 2024

Deep-buried tunnels with weak surrounding rock are frequently encountered issues in traffic engineering. It plays an important role in the excavation process and the project operation. This paper applies the theoretical analysis and laboratory test related to four different conditions in terms of their thickness to determine the mechanical response of deep-buried tunnel lining. Then, the energy dissipative structure theory is employed to explain the experimental results. This paper has made the following achievements: firstly, it is found that the toughness of the secondary lining was found to be often the most important indicator of tunnel safety, with better-toughness linings having higher tensile strength and crack resistance. Secondly, it suggests that the inclusion of steel reinforcement in the concrete lining can effectively improve the secondary lining toughness. Finally, it proves that the more ductile liner had more energy, higher load-carrying capacity, and was better able to maintain the overall stability of the structure.
Suspended sediment load prediction using sparrow search algorithm-based support vector machine model
Authors: Samantaray Sandeep , Sahoo Abinash , Satapathy Deba Prakash , Oudah Atheer Y. , Yaseen Zaher Mundher
Published: June 2024

Prediction of suspended sediment load (SSL) in streams is significant in hydrological modeling and water resources engineering. Development of a consistent and accurate sediment prediction model is highly necessary due to its difficulty and complexity in practice because sediment transportation is vastly non-linear and is governed by several variables like rainfall, strength of flow, and sediment supply. Artificial intelligence (AI) approaches have become prevalent in water resource engineering to solve multifaceted problems like sediment load modelling. The present work proposes a robust model incorporating support vector machine with a novel sparrow search algorithm (SVM-SSA) to compute SSL in Tilga, Jenapur, Jaraikela and Gomlai stations in Brahmani river basin, Odisha State, India. Five different scenarios are considered for model development. Performance assessment of developed model is analyzed on basis of mean absolute error (MAE), root mean squared error (RMSE), determination coefficient (R2), and Nash–Sutcliffe efficiency (ENS). The outcomes of SVM-SSA model are compared with three hybrid models, namely SVM-BOA (Butterfly optimization algorithm), SVM-GOA (Grasshopper optimization algorithm), SVM-BA (Bat algorithm), and benchmark SVM model. The findings revealed that SVM-SSA model successfully estimates SSL with high accuracy for scenario V with sediment (3-month lag) and discharge (current time-step and 3-month lag) as input than other alternatives with RMSE = 15.5287, MAE = 15.3926, and ENS = 0.96481. The conventional SVM model performed the worst in SSL prediction. Findings of this investigation tend to claim suitability of employed approach to model SSL in rivers precisely and reliably. The prediction model guarantees the precision of the forecasted outcomes while significantly decreasing the computing time expenditure, and the precision satisfies the demands of realistic engineering applications.
RhizoNet segments plant roots to assess biomass and growth for enabling self-driving labs
Authors: Sordo Zineb , Andeer Peter , Sethian James , Northen Trent , Ushizima Daniela
Published: June 2024

Flatbed scanners are commonly used for root analysis, but typical manual segmentation methods are time-consuming and prone to errors, especially in large-scale, multi-plant studies. Furthermore, the complex nature of root structures combined with noisy backgrounds in images complicates automated analysis. Addressing these challenges, this article introduces RhizoNet, a deep learning-based workflow to semantically segment plant root scans. Utilizing a sophisticated Residual U-Net architecture, RhizoNet enhances prediction accuracy and employs a convex hull operation for delineation of the primary root component. Its main objective is to accurately segment root biomass and monitor its growth over time. RhizoNet processes color scans of plants grown in a hydroponic system known as EcoFAB, subjected to specific nutritional treatments. The root detection model using RhizoNet demonstrates strong generalization in the validation tests of all experiments despite variable treatments. The main contributions are the standardization of root segmentation and phenotyping, systematic and accelerated analysis of thousands of images, significantly aiding in the precise assessment of root growth dynamics under varying plant conditions, and offering a path toward self-driving labs.
Influence of air intake from existing shafts on the safety of operating trains
Authors: Huang Changfu , Li Shaohua , Zhang Zhenbo , Yao Tiejun , Shi Xianming , Tian Jingwei , Hu Zhinan , Wang Yuhai
Published: June 2024

Given the influence of air intake from inclined shafts in existing tunnel ventilation systems on train comfort and aerodynamic safety, a numerical analysis method is used to study the comfort and aerodynamic safety of operating trains under three conditions—inclined shaft closed and inclined shaft open without and with air intake—and to explore the variation law of transient pressure and aerodynamic force (lift coefficient, transverse force coefficient, and overturning moment coefficient). Combined with practical engineering and requirements, the influence of inclined shaft air intake on train operation comfort and aerodynamic safety is analyzed. Through this research, the influence of using air intake from the inclined shaft of an existing tunnel, a ventilation scheme of the new Wushaoling Tunnel, on the comfort and aerodynamic force of trains is revealed, and the comfort and aerodynamic safety of trains in an actual project are evaluated, verifying the rationality of the ventilation scheme of the Wushaoling Tunnel.
Optimal weighting factor design based on entropy technique in finite control set model predictive torque control for electric drive applications
Authors: Shahid Muhammad Bilal , Jin Weidong , Abbasi Muhammad Abbas , Li Lian , Rasool Akhtar , Bhatti Abdul Rauf , Hussen Abdulkerim Sherefa
Published: June 2024

In the conventional finite control set model predictive torque control, the cost function consists of different control objectives with varying units of measurements. Due to presence of diverse variables in cost function, weighting factors are used to set the relative importance of these objectives. However, selection of these weighting factors in predictive control of electric drives and power converters still remains an open research challenge. Improper selection of weighting factors can lead to deterioration of the controller performance. This work proposes a novel weighting factor tuning method based on the Multi-Criteria-Decision-Making (MCDM) technique called the Entropy method. This technique has several advantages for multi-objective problem optimization. It provides a quantitive approach and incorporates uncertainties and adaptability to assess the relative importance of different criteria or objectives. This technique performs the online tuning of the weighting factor by forming a data set of the control objectives, i.e., electromagnetic torque and stator flux magnitude. After obtaining the error set of control variables, the objective matrix is normalized, and the entropy technique is applied to design the corresponding weights. An experimental setup based on the dSpace dS1104 controller is used to validate the effectiveness of the proposed method for a two-level, three-phase voltage source inverter (2L-3P) fed induction motor drive. The dynamic response of the proposed technique is compared with the previously proposed MCDM-based weighting factor tuning technique and conventional MPTC. The results reveal that the proposed method provides an improved dynamic response of the drive under changing operating conditions with a reduction of 28% in computational burden and 38% in total harmonic distortion, respectively.
Blocking Oncostatin M receptor abrogates STAT3 mediated integrin signaling and overcomes chemoresistance in ovarian cancer
Authors: Geethadevi Anjali , Ku Zhiqiang , Tsaih Shirng-Wern , Parashar Deepak , Kadamberi Ishaque P. , Xiong Wei , Deng Hui , George Jasmine , Kumar Sudhir , Mittal Sonam , Zhang Ningyan , Pradeep Sunila , An Zhiqiang , Chaluvally-Raghavan Pradeep
Published: June 2024

Chemotherapy such as cisplatin is widely used to treat ovarian cancer either before or after surgical debulking. However, cancer relapse due to chemotherapy resistance is a major challenge in the treatment of ovarian cancer. The underlying mechanisms related to chemotherapy resistance remain largely unclear. Therefore, identification of effective therapeutic strategies is urgently needed to overcome therapy resistance. Transcriptome-based analysis, in vitro studies and functional assays identified that cisplatin-resistant ovarian cancer cells express high levels of OSMR compared to cisplatin sensitive cells. Furthermore, OSMR expression associated with a module of integrin family genes and predominantly linked with integrin αV (ITGAV) and integrin β3 (ITGB3) for cisplatin resistance. Using ectopic expression and knockdown approaches, we proved that OSMR directly regulates ITGAV and ITGB3 gene expression through STAT3 activation. Notably, targeting OSMR using anti-OSMR human antibody inhibited the growth and metastasis of ovarian cancer cells and sensitized cisplatin treatment. Taken together, our results underscore the pivotal role of OSMR as a requirement for cisplatin resistance in ovarian cancer. Notably, OSMR fostered the expression of a distinct set of integrin genes, which in turn resulted into a crosstalk between OSMR and integrins for signaling activation that is critical for cisplatin resistance. Therefore, targeting OSMR emerges as a promising and viable strategy to reverse cisplatin-resistance in ovarian cancer.
Proteomic profiling reveals diagnostic signatures and pathogenic insights in multisystem inflammatory syndrome in children
Authors: Nygaard Ulrikka , Nielsen Annelaura Bach , Dungu Kia Hee Schultz , Drici Lylia , Holm Mette , Ottenheijm Maud Eline , Nielsen Allan Bybeck , Glenthøj Jonathan Peter , Schmidt Lisbeth Samsø , Cortes Dina , Jørgensen Inger Merete , Mogensen Trine Hyrup , Schmiegelow Kjeld , Mann Matthias , Vissing Nadja Hawwa , Wewer Albrechtsen Nicolai J.
Published: June 2024

Multisystem inflammatory syndrome in children (MIS-C) is a severe disease that emerged during the COVID-19 pandemic. Although recognized as an immune-mediated condition, the pathogenesis remains unresolved. Furthermore, the absence of a diagnostic test can lead to delayed immunotherapy. Using state-of-the-art mass-spectrometry proteomics, assisted by artificial intelligence (AI), we aimed to identify a diagnostic signature for MIS-C and to gain insights into disease mechanisms. We identified a highly specific 4-protein diagnostic signature in children with MIS-C. Furthermore, we identified seven clusters that differed between MIS-C and controls, indicating an interplay between apolipoproteins, immune response proteins, coagulation factors, platelet function, and the complement cascade. These intricate protein patterns indicated MIS-C as an immunometabolic condition with global hypercoagulability. Our findings emphasize the potential of AI-assisted proteomics as a powerful and unbiased tool for assessing disease pathogenesis and suggesting avenues for future interventions and impact on pediatric disease trajectories through early diagnosis.