bluuebunny/crossref_metadata_2025 huggingface dataset:
Silica/klucel nanocomposite as promising durable adsorbent for lead removal from industrial effluents
Authors: El-Shafey Shaymaa E. , Obada Mohammed K. , El-Shamy A. M. , Mohamed Wael S.
Published: October 2024

The removal of heavy metals, such as lead, from industrial wastewater is imperative due to their detrimental effects on both human health and the environment. This study delves into investigating the feasibility of employing a novel adsorbent, specifically a silica/klucel nanocomposite, for effectively extract lead from industrial effluents. The synthesis of this nanocomposite involved a simple and cost-effective method, combining silica nanoparticles with klucel. XRD, FTIR, E-SEM, Raman, and N2 gas adsorption at − 196 °C tools were employed to prospect the formation of silica/klucel nanocomposite. Outstandingly, treating 50 ml of 50 mg/l of lead with 10 mg of adsorbent exhibited rapid removal, which reached a maximum (95%) at 60 min contact time. The resulting composite demonstrated remarkable adsorption capabilities, primarily attributed to two factors: the expansive surface area of silica nanoparticles 139.1 m2/g and the porous structure provided by klucel. Through batch adsorption experiments, the nanocomposite’s proficiency in removing lead ions from aqueous solutions became evident. The kinetics of the adsorption process were found to adhere closely to a pseudo-second-order model, hinting at chemical adsorption as the rate-determining step. Langmuir isotherm model revealed that lead ions tend to form a monolayer on the surface of the nanocomposite and the maximum adsorption capacity (qm) was 63.938 mg/g. Additionally, the nanocomposite, exhibited notable stability and could be reused multiple times, where 65% removal efficiency was announced until the 7th cycle without significant degradation in performance. In summary, the silica/klucel nanocomposite emerges as a promising and eco-friendly adsorbent for removing lead from industrial effluents. Its efficient performance and sustainability offer a compelling solution to combat heavy metal contamination, thereby contributing to environmental preservation and human well-being.
Assessment of disability and disease burden in neuromyelitis optica spectrum disorders in the CIRCLES Cohort
Authors: Gholizadeh Shervin , Exuzides Alex , Sinnott Jennifer , Palmer Chella , Waltz Michael , Rose John W. , Jolley Anna Marie , Behne Jacinta M. , Behne Megan K. , Blaschke Terrence F. , Smith Terry J. , Lewis Katelyn E. , Cook Lawrence J. , Yeaman Michael R. ,   on behalf of The Guthy-Jackson Charitable Foundation CIRCLES Study Group
Published: October 2024

Neuromyelitis optica spectrum disorders (NMOSD) comprise autoimmune diseases imposing substantial disability. We compared an NMOSD-targeted disability assessment of mobility, vision, and self-care domains (individually and composite) with the multiple sclerosis-targeted Expanded Disability Status Scale (EDSS) to assess NMOSD disease burden. An overall cohort (n = 505) and a subset of these patients with an enriched dataset (n = 198) were analyzed from the CIRCLES longitudinal, observational database of patients with AQP4-IgG–seropositive or –seronegative NMOSD in North America. Multinomial modeling was used to identify temporal correlates of disability improvement, stability, and worsening. Prior on-study relapse correlated with worsening mobility (OR, 3.08; 95% CI: 1.61–5.90), vision (OR, 3.99; 95% CI: 2.03–7.86), self-care disability (OR, 1.90; 95% CI: 1.07–3.38), and mean composite index disability (OR, 4.20; 95% CI: 1.71–10.34). Higher vision disability was associated with Black race, shorter time on-study, and AQP4-IgG–seropositive status in patients ≥ 18 years (p < 0.05). Disease onset phenotype and sex correlated with pain interference (p < 0.05). These correlates of NMOSD disability were undetected by EDSS. The CIRCLES real-world experience supports the need for NMOSD-specific disability assessment to improve recognition of disease burden, facilitate proactive clinical management, offer insights into resilience, and inform clinical trial design.
A novel genetic strategy to enable rapid detection of rare non-native alleles
Authors: Cooper Robert D. , Luckau Tara K. , Toffelmier Erin , Cook Dave G. , Martinelli Stacy , Fawcett Michael H. , Shaffer H. Bradley
Published: October 2024

Established invasive species represent one of the most harmful and challenging threats to native biodiversity, necessitating methods for Early Detection and Rapid Response. Cryptic invasions are particularly challenging and often require expensive and time-consuming molecular surveys which limits their usefulness for management. We present a novel application of the Fluidigm SNP-Type Assay to identify rare non-native alleles that significantly reduces the cost and time to generate diagnostic results. We demonstrate the efficacy of this method using experimental Fluidigm pools (99% accuracy) and sequence data (96% accuracy). We apply our novel methodology to an endangered population of California tiger salamanders in Sonoma County where two individual non-native tiger salamander hybrids have previously been detected since 2008. We screened 5805 larvae in 387 sample-pools containing 15 larvae each. We did not detect any non-native hybrids in the population, a result that was verified with sequence data, though we strongly recommend additional years of sampling to confirm hybrid absence. Our success with a challenging, large-genome amphibian suggests this method may be applied to any system, and would be particularly useful when it is necessary for conservation practitioners to rapidly identify rare taxa or genes of interest.
Menstrual cycle does not impact the hypoxic ventilatory response and acute mountain sickness prediction
Authors: Citherlet Tom , Raberin Antoine , Manferdelli Giorgio , Pialoux Vincent , Millet Grégoire P.
Published: October 2024

The relationship between the variations in ovarian hormones (i.e., estrogens and progesterone) and the hypoxic ventilatory response (HVR) remains unclear. HVR is a key adaptive mechanism to high altitude and has been proposed as a predictor for acute mountain sickness (AMS). This study aimed to explore the effects of hormonal changes across the menstrual cycle on HVR. Additionally, it assessed the predictive capacity of HVR for AMS and examined whether a particular menstrual phase could enhance its predictive accuracy. Thirteen eumenorrheic women performed a pure nitrogen breathing test near sea level, measuring HVR and cerebral oxygenation in early follicular, late follicular, and mid-luteal phases. Oxidative stress and ovarian hormone levels were also measured. AMS symptoms were evaluated after spending 14 h, including one overnight, at an altitude of 3,375 m. No differences in HVR, ventilation, peripheral oxygen saturation, or cerebral oxygenation were observed between the three menstrual cycle phases. Moreover, these parameters and the oxidative stress markers did not differ between the women with or without AMS (31% vs 69%), regardless of the menstrual cycle phase. In conclusion, ventilatory responses and cerebral oxygenation in normobaric hypoxia were consistent across the menstrual cycle. Furthermore, these parameters did not differentiate women with or without AMS.
Alternative climatic steady states near the Permian–Triassic Boundary
Authors: Ragon C. , Vérard C. , Kasparian J. , Brunetti M.
Published: October 2024

Due to spatial scarcity and uncertainties in sediment data, initial and boundary conditions in deep-time climate simulations are not well constrained. On the other hand, depending on these conditions, feedback mechanisms in the climate system compete and balance differently. This opens up the possibility to obtain multiple steady states in numerical experiments. Here, we use the MIT general circulation model to explore the existence of such alternative steady states around the Permian–Triassic Boundary (PTB). We construct the corresponding bifurcation diagram, taking into account processes on a timescale of thousands of years, in order to identify the stability range of the steady states and tipping points as the atmospheric CO2 content is varied. We find three alternative steady states with a difference in global mean surface air temperature of about 10 °C. We also examine how these climatic steady states are modified when feedbacks operating on comparable or longer time scales are included, namely vegetation dynamics and air-sea carbon exchanges. Our findings on multistability provide a useful framework for explaining the climatic variations observed in the Early Triassic geological record, as well as some discrepancies between numerical simulations in the literature and geological data at PTB and its aftermath.
Gliflozins, sucrose and flavonoids are allosteric activators of lecithin-cholesterol acyltransferase
Authors: Niemelä Akseli , Giorgi Laura , Nouri Sirine , Yurttaş Betül , Rauniyar Khushbu , Jeltsch Michael , Koivuniemi Artturi
Published: October 2024

Lecithin-cholesterol acyltransferase (LCAT) serves as a pivotal enzyme in preserving cholesterol homeostasis via reverse cholesterol transport, a process closely associated with the onset of atherosclerosis. Impaired LCAT function can lead to severe LCAT deficiency disorders for which no pharmacological treatment exists. LCAT-based therapies, such as small molecule positive allosteric modulators (PAMs), against LCAT deficiencies and atherosclerosis hold promise, although their efficacy against atherosclerosis remains challenging. Herein we utilized a quantitative in silico metric to predict the activity of novel PAMs and tested their potencies with in vitro enzymatic assays. As predicted, sodium-glucose cotransporter 2 (SGLT2) inhibitors (gliflozins), sucrose and flavonoids activate LCAT. This has intriguing implications for the mechanism of action of gliflozins, which are commonly used in the treatment of type 2 diabetes, and for the endogenous activation of LCAT. Our results underscore the potential of molecular dynamics simulations in rational drug design.
Effect of electrostatic confinement on the dome-shaped superconducting phase diagram at the LaAlO3/SrTiO3 interface
Authors: Wójcik Paweł , Szafran Bartłomiej , Czarnecki Julian , Citro Roberta , Zegrodnik Michał
Published: October 2024

The two-dimensional electron gas (2DEG) at the LaAlO$$_3$$/SrTiO$$_3$$ (LAO/STO) interface exhibits gate-tunable superconductivity with a dome-like shape of critical temperature as a function of electron concentration. This behavior has not been unambiguously explained yet. Here, we develop a microscopic model based on the Schrödinger–Poisson approach to determine the electronic structure of the LAO/STO 2DEG, which we then apply to study the principal characteristics of the superconducting phase within the real-space pairing mean-field approach. For the electron concentrations reported in the experiment, we successfully reproduce the dome-like shape of the superconducting gap. According to our analysis such behavior results from the interplay between the Fermi surface topology and the gap symmetry, with the dominant extended s-wave contribution. Similarly as in the experimental report, we observe a bifurcation effect in the superconducting gap dependence on the electron density when the 2DEG is electrostatically doped either with the top gate or the bottom gate. Our findings explains the dome-shaped phase diagram of the considered heterostucture with good agreement with the experimental data which, in turn, strongly suggest the appearance of the extended s-wave symmetry of the gap in 2DEG at the LAO/STO interface.
N–N atropisomer synthesis via electrolyte- and base-free electrochemical cobalt-catalysed C–H annulation
Authors: Cai Jiating , Li Linzai , Wang Chuitian , Qin Shi , Li Yuanyuan , Liao Si-Yan , Wang Shengdong , Gao Hui , Zhou Zhi , Huang Yugang , Yi Wei , Zeng Zhongyi
Published: October 2024

An exogenous electrolyte- and base-free electrochemical cobalt-catalysed atroposelective C–H annulation has been established to construct N–N axially chiral isoquinolinones in excellent enantioselectivities and good yields.
Measuring green chemistry: methods, models, and metrics
Authors: Bardow André , Pérez-Ramírez Javier , Sala Serenella , Vaccaro Luigi
Published: October 2024

This themed collection includes selected examples aiming to quantify the benefits and trade-offs of green chemistry by providing assessment methods, models, indicators, and metrics.
A simple method for elemental analysis of liquids in sprayed microdroplets by laser-induced breakdown spectroscopy
Authors: Feng Jun , Yan Yihui , Liu Yuzhu , Lengyel Jozef
Published: October 2024

The study shows that paper spray and laser-induced breakdown spectroscopy (PS-LIBS) analyze trace elements in aqueous solutions, addressing challenges in bulk analysis. Its efficiency highlights its potential for in situ liquid sample analysis.
β-Methoxyphenyl substituted porphyrins: synthesis, characterization and comprehensive spectral, structural, electrochemical and theoretical analysis
Authors: Arif Waseem , Kumar Vipin , Chetti Prabhakar , Kumar Ravi
Published: October 2024

Regioselective β-methoxyphenylporphyrins (MTPP(R)2; R = p-CH3O-Ph, m-CH3O-Ph, and m,p-CH3O-Ph; M = 2H, Co(ii), Ni(ii), Cu(ii), & Zn(ii)) with tunable spectral, electrochemical properties along with structural & theoretical analysis are reported.
Efficient adsorption performance of uranium in wastewater by novel MXene material TiVCTx and its aerogel composites
Authors: Luo Xiaoxia , Ren Xianliang , Wang Hongwei
Published: October 2024

This work focuses on the application potential of novel MXene materials in the field of uranium-containing wastewater adsorption, particularly addressing gaps in existing research.
Advancing urban mobility in developing countries: A mobile RSU approach for sustainable transportation
Authors: Ngossaha Justin Moskolaï , Pidy Léonce Thérèse Pidy , Karunathilake Thenuka , Förster Anna , Bowong Samuel
Published: October 2024

The rapid and uncontrolled urbanization of cities in developing countries has engendered a plethora of urban mobility issues, including traffic congestion, accidents, and air pollution. To address these challenges, contemporary urban mobility trends are incorporating innovative technologies and sustainable governance practices. This article investigates how urban managers can leverage the opportunities presented by cost‐effective technologies and the management of urban data to enhance urban mobility in developing countries. Within this discourse, an RSU‐based approach is proposed that employs motorbike taxis for inter‐vehicular communication, given their status as the most widely used form of public transportation. This approach substantially diminishes investment costs and reinforces the sustainability of urban mobility. Through the implementation of this solution, a noteworthy reduction is anticipated in the emission of gases such as CO2, and NOx, known contributors to climate change and various respiratory diseases. To validate the efficacy of the proposed solution, four distinct scenarios are scrutinized in a case study centered on the city of Douala in Cameroon, utilizing tools such as OMNET++, SUMO, Veins, and INET. The proposed framework offers significant benefits in terms of environmental sustainability and operational efficiency. It enables a 10% reduction in CO2 emissions, a 15% reduction in NOx emissions, an 11% drop in fuel consumption, and a 15% reduction in waiting time in traffic jams. The envisaged solution aims to aid urban managers in their decision‐making processes, specifically in advancing sustainable urban mobility. Through the adoption of this approach, cities in developing countries can mitigate challenges associated with urban mobility and enhance the overall well‐being of their residents.
LSTM‐based real‐time stress detection using PPG signals on raspberry Pi
Authors: Rostami Amin , Motaman Koorosh , Tarvirdizadeh Bahram , Alipour Khalil , Ghamari Mohammad
Published: October 2024

Stress, widely recognised for its profound adverse effects on both physical and mental health, necessitates the development of innovative real‐time detection methods. In this context, the escalating prevalence of wearable embedded systems, integrated with artificial intelligence (AI) for the continuous monitoring of critical physiological indicators like heart rate and blood pressure, accentuates their growing relevance in the efficient detection of stress. This article presents an innovative methodology employing deep learning algorithms on the Raspberry Pi 3, a platform distinguished by its cost‐effectiveness and limited resources. The authors have developed an advanced AI algorithm that achieves high accuracy in real‐time stress detection using photoplethysmography (PPG) sensors while significantly reducing computational demands. The authors’ method utilises an artificial neural network with long short‐term memory (LSTM) layers, proving highly effective in time‐series data analysis. In this study, the authors implement key TensorFlow toolkit optimisation techniques including quantisation aware training (QAT), Pruning and prune‐preserving quantisation aware training. These techniques are applied to refine the authors’ model, decreasing size and latency without sacrificing accuracy. The results highlight the LSTM‐based model's proficiency in accurately detecting stress using raw PPG sensor data on the Raspberry Pi 3, a comparatively affordable platform. The model attains an accuracy of 89.32% and an F1 score of 89.55% on the diverse wearable stress and affect detection stress‐level dataset. Additionally, the authors’ optimised model exhibits substantial reductions in both size and latency while maintaining high accuracy. This approach shows great potential for various applications, such as stress monitoring in healthcare, sports, and workplace settings. The use of the Raspberry Pi 3 makes the system portable, cost‐effective, and energy‐efficient, enhancing its potential impact and accessibility.
La difficile équation économique de la chaleur nucléaire
Authors: Hanine Ilyas
Published: October 2024

Les modèles économiques dans le secteur de l’énergie jouent un rôle crucial dans la sécurisation des flux de revenus attendus par les financeurs. Or ces modèles évoluent et nécessitent une adaptation constante de tous les acteurs.
Investigating the Photoactivity of Low-Valent Zirconium Catalyst in Ether Activation
Authors: Zhao Jie
Published: October 2024

The cross-coupling of two distinct C(sp3
)–O bonds provides a highly valuable pathway for the construction of C(sp3
)–C(sp3
) bonds, but it remains underdeveloped. Recently, we reported an innovative photoinduced Zr-catalyzed carbomagnesiation for the reductive coupling of ethers with high cross-selectivity. Mechanistic investigation reveals that photoexcitation of low-valent zirconocene facilitates the activation of C(sp3
)–O bonds of benzylic ethers. This leads to the formation of functionalized benzylic Grignard reagents for downstream coupling with aliphatic ethers through an SN2-like pathway.

1 Introduction

2 Concept of Our Design on this Work

3 Photoinduced Zr-Catalyzed Cross-Coupling of Ethers

4 Photoinduced Zr-Catalyzed Cross-Coupling of Benzylic Magnesium Alkoxide with Ethers

5 Our Methods for Mechanism Investigation

6 Conclusion
BMIDA-Directed Catalytic Asymmetric Transfer Hydrogenation for Enantioselective Access to α-Boryl Alcohols
Authors: Fang Xinqiang , Yang Shuang
Published: October 2024

The quest for general and highly efficient and enantioselective catalytic route to chiral alcohols remains a formidable challenge in asymmetric synthesis. Here, we highlight our recent work of asymmetric transfer hydrogenation (ATH) of N-methyliminodiacetyl (MIDA) acylboronates, showcasing a versatile platform for the efficient synthesis of enantiomerically enriched secondary alcohols. Acyl-MIDA-boronates harboring diverse (het)aryl, alkyl, alkynyl, alkenyl, and carbonyl substituents can be hydrogenated, yielding various α-borylated alcohols with high ee values. Crucially, the boron moiety can be easily transformed into other groups, allowing access to previously unattainable carbinols adorned with two structurally similar substituents. The enantioselectivity-directing role of BMIDA is elucidated by computational analyses, which stems from the CH–O electrostatic attraction between the η6-arene-CH of the catalyst and the σ-bonded oxygen atoms within BMIDA. This work represents the first asymmetric transformation on acylboronates and expands the domain of asymmetric transfer hydrogenation.
Nickel-Catalyzed Enantioselective Reductive Spirocyclization of 1,6-Enynes with o-Bromobenzaldehydes
Authors: Guo Haoyun , Chen Yate , Kong Wangqing
Published: October 2024

We developed a Ni-catalyzed asymmetric reductive spirocyclization of 1,6-enynes with o-haloaryl aldehydes. This approach provides an efficient method for the construction of chiral spiroindanone pyrrolidine derivatives in good yields with excellent enantio- and diastereoselectivity (up to 99% ee, >20:1 dr). This reaction does not require pre-prepared organometallic reagents and exhibits excellent substrate compatibility.
Metal-Free Selective Air-Oxidation of Sulfides to Sulfoxides Using 2,2′-Azobis-(2,4-dimethyl-4-methoxyvaleronitrile) (V-70) and Isobutyraldehyde
Authors: Matsugi Masato , Kato Yamato , Kanoh Miho , Shioiri Takayuki
Published: October 2024

Selective oxidation of sulfides to sulfoxides using ‘air’ was achieved using a combination of 2,2′-azobis-(2,4-dimethyl-4-methoxyvaleronitrile) (a radical initiator) and isobutyraldehyde (a co-oxidant). Various sulfides were successfully converted into their corresponding sulfoxides using this method. This approach promotes a sustainable oxidation process by excluding harmful oxidants, such as peroxides and metal reagents.
Recent Advances in Transition-Metal-Catalyzed Enantioconvergent Transformations of Epoxides
Authors: Li Jianye , Li Sijia , Zhang Guozhu , Guo Rui , Liu Shuting , Cui Guohao
Published: October 2024

In recent years, asymmetric ring-opening reactions of epoxides have emerged as a compelling strategy for constructing chiral building blocks in organic synthesis. Among these, transition-metal-catalyzed stereoselective transformations of epoxides have garnered particular attention for their high efficiency and cost-effectiveness. The increasing interest and advancements in this area have spurred exploration into diverse transition-metal catalysts and chiral ligands, highlighting their potential to facilitate a wide range of transformations with enhanced efficiency and flexibility. This short review showcases significant achievements in transition-metal-catalyzed enantioconvergent transformations of epoxides, emphasizing their scope of application and reaction mechanisms.

1 Introduction

2 Palladium-Catalyzed Enantioconvergent Cross-Coupling of Epoxides

3 Nickel-Catalyzed Enantioconvergent Cross-Coupling of Epoxides

4 Titanium-Catalyzed Enantioconvergent Cross-Coupling of Epoxides

5 Iridium-Catalyzed Enantioconvergent Cross-Coupling of Epoxides

6 Cobalt-Catalyzed Enantioconvergent Cross-Coupling of Epoxides

7 Copper-Catalyzed Enantioconvergent Cross-Coupling of Epoxides

8 Conclusions and Outlook
Synergistic Pd/Cu-Catalyzed Asymmetric Csp3–Csp3 Coupling of 1,3-Dienes with 2-Acylimidazoles
Authors: Zi Weiwei , Wang Mingze
Published: October 2024

The catalytic asymmetric coupling of 1,3-dienes with carbon nucleophiles is an important process for forming Csp3–Csp3 bonds. Here, we describe a synergistic Pd/Cu-catalyzed coupling of 1,3-dienes with 2-acylimidazoles. This reaction produces 2-acylimidazole derivatives that have α,β-adjacent stereocenters in moderate yields with good to excellent stereoselectivity.
Immunohistochemical Subclassification of Peripheral T Cell Lymphomas-Not Otherwise Specified
Authors: Chandran Keerthana , Nair Indu R. , Keechilat Pavithran
Published: October 2024

Objective Peripheral T cell lymphomas-not otherwise specified (PTCL-NOS) are a heterogeneous group of mature T cell lymphomas that do not belong to any specified subtype. Gene expression profiling has revealed two biological variants of PTCL-NOS, PTCLGATA3 and PTCLTBX21. This study aims to subclassify PTCL-NOS using immunohistochemistry (IHC) and to establish its implication in prognosis.

Methods A descriptive study was done using 39 morphologically and immunohistochemically diagnosed cases of PTCL diagnosed over a 10-year period, 2013 to 2022. The additional IHC markers used were GATA3 and CCR4 for PTCLGATA3 and TBX21 and CXCR3 for PTCLTBX21. All cases had a minimum follow-up of 6 months.

Results After subclassification of PTCL-NOS (n = 39), 44% were PTCLGATA3 subtype. This subtype showed monomorphic morphology and a high ki67 index, and was found to a have worse outcome. In comparison, PTCLTBX21 showed heterogeneous morphology and a low ki67 index.

Conclusion Subcategorization of PTCL-NOS based on the IHC markers helps in the stratification of this disease. This will also identify cases with more aggressive behavior at the time of diagnosis.
Laser beams offer simplified calculations for quantum computing
Authors: Lim Alane
Published: October 2024

Well-established optical computing methods can be used to execute vector-matrix algebra for quantum computing.
Thoughtful data analysis
Authors: Bradley Elizabeth , White James W. C. , Garland Joshua
Published: October 2024

The acceleration in the field of data science is well known [see, e.g., D. Donoho, J. Comput. Graph. Stat. 26(4), 745–766 (2017) and references therein]. Improvements in technology for acquisition, storage, and processing have made unheard of amounts of data available to scientists; in parallel with that, the pace of methodological advance has also been rapid; with new techniques and packages becoming available, it seems, every day. With these affordances come many challenges, notably the volume and variety of the data [Fan et al., Natl. Sci. Rev. 1(2), 293–314 (2014)]. In this Perspective piece, we examine a different challenge—how to choose and use the right analysis method—and make an argument for the sharing of raw data.
Using k-means to sort spectra: Electronic order mapping from scanning tunneling spectroscopy measurements
Authors: King V. , Choi Seokhwan , Chen Dong , Stuart Brandon , Kim Jisun , Oudah Mohamed , Kim Jimin , Kim B. J. , Bonn D. A. , Burke S. A.
Published: October 2024

Hyperspectral imaging techniques have a unique ability to probe the inhomogeneity of material properties whether driven by compositional variation or other forms of phase segregation. In the doped cuprates, iridates, and related materials, scanning tunneling microscopy/spectroscopy (STM/STS) measurements have found the emergence of pseudogap “puddles” from the macroscopically Mott insulating phase with increased doping. However, categorizing this hyperspectral data by electronic order is not trivial and has often been done with ad hoc methods. In this paper, we demonstrate the utility of k-means, a simple and easy-to-use unsupervised clustering method, as a tool for classifying heterogeneous scanning tunneling spectroscopy data by electronic order for Rh-doped Sr2IrO4, a cuprate-like material. Applied to STM data acquired within the Mott phase, k-means was able to identify areas of Mott order and of pseudogap order. The unsupervised nature of k-means limits avenues for bias and provides clustered spectral shapes without a priori knowledge of the physics. Additionally, we demonstrate the use of k-means as a preprocessing tool to constrain phenomenological function fitting. Clustering the data allows us to reduce the fitting parameter space, limiting over-fitting. We suggest k-means as a fast, simple model for processing hyperspectral data on materials of mixed electronic order.
Preparation and property of (NaZn)3+-substituted Sc2Mo3O12 ceramics with negative thermal expansion
Authors: Liu Hongfei , Shao Zhanlu , Zhu Jun , Zhang Zhiping
Published: October 2024

To modulate the negative thermal expansion (NTE) performances of Sc2Mo3O12 ceramics, (NaZn)3+-substituted Sc2Mo3O12 ceramics were prepared via solid-state reactions. The crystal phase, morphology, and NTE properties of the NaxZnxSc2−x(MoO4)3 (0 ≤ x ≤ 1) samples were investigated. XRD results reveal that NaxZnxSc2−x(MoO4)3 samples undergo a change in crystal structure from orthorhombic to hexagonal phase due to (NaZn)3+ doping. (NaZn)3+ introduction also promotes grain growth and increases the density of the NaxZnxSc2−x(MoO4)3 ceramics. With the increase in (NaZn)3+ substitution, NaxZnxSc2−x(MoO4)3 ceramics exhibit stronger NTE, and the thermal expansion coefficients (CTEs) improve from −4.74 × 10−6 to −8.77 × 10−6 °C−1 in 30–650 °C. High-temperature XRD results reveal that the hexagonal NaxZnxSc2−x(MoO4)3 samples exhibit anisotropic NTE. With the increase in (NaZn)3+ substitution, the linear CTEs of the a and b axes decreased from −13.17 × 10−6 to −15.93 × 10−6 °C−1, while one of the c axes decreased from 18.38 × 10−6 to 12.27 × 10−6 °C−1. Consequently, hexagonal NaxZnxSc2−x(MoO4)3 samples present stronger NTE as the content x rises.
Our World Full of Wonder
Authors: Nilson Jevita , Racklyeft Jess
Published: October 2024

Our world is full of amazing natural wonders. From sparkling seas and towering trees, to valleys, lakes and waterfalls, there are extraordinary places that seem too magical to be true but can be found right here on planet Earth.

There are ghostly green lights of the aurora borealis near the North Pole, and exquisite rainbow mountains in China. There is a lake in Australia so pink it looks like fairy floss, and giant crystal caves hidden below Mexico.

These are just some of the incredible places you will discover in Our World Full of Wonder.

Shall we go explore?

Reading level varies from child to child, but we recommend this book for ages 5 to 9.
Systematics of Apatelodidae Neumoegen & Dyar, 1894 (Lepidoptera: Bombycoidea) based on molecular and morphological data
Authors: Orlandin Elton , Piovesan Mônica , Carneiro Eduardo
Published: October 2024

Apatelodidae is a family of New World bombycoids distributed mainly in the Neotropical region, with 14 genera, 222 valid species and 8 subspecies. These moths are medium-sized with a wingspan ranging from 2 to 8 cm, generally greyish, straw-yellow or reddish-brown, with darker spots and lines on the dorsal side of the wings. We combine adult morphology and molecular data to test, under a probabilistic framework, the monophyly of apatelodid genera and the placement of Tamphana (Bombycidae). We sampled the type species of 12 of the 14 valid genera of Apatelodidae, including the type species of synonymised genera. We sampled ~75% of the species from all valid genera in the family and outgroups from Bombycidae, Brahmaeidae, Eupterotidae and Phiditiidae, totalling 195 terminals. Examination of the specimens resulted in a matrix of 138 morphological characters (116 from male; 22 from female) from the head (7 from male; 1 from female), thorax (37 from male; 4 from female), abdomen (5 from male) and genitalia (66 from male; 17 from female). For the molecular analyses, we used four genes: DDC (647 bp) for 14% of terminals; CAD (2486 bp) for 23% of terminals, Wgl (409 bp) for 38% of terminals and COI (658 bp) for 75% of terminals. Species of Tamphana were recovered in Apatelodidae as two independent clades. The genera Arotros, Crastolliana, Drepatelodes, Pantelodes, and Prothysana were recovered as monophyletic. The remaining apatelodid genera were polyphyletic. We propose a new genus-level classification: Tamphana is transferred to Apatelodidae; 16 new genera are proposed: Aymara gen. nov., Campesina gen. nov., Caribas gen. nov., Cecile gen. nov., Kaweskar gen. nov., Lempira gen. nov., Misak gen. nov., Mocambo gen. nov., Nhanderu gen. nov., Peabiru gen. nov., Raoni gen. nov., Tapuia gen. nov., Tibira gen. nov., Tupac gen. nov., Tuyvae gen. nov. and Zapata gen. nov. Two new species are described: Mocambo lauracensis sp. nov., and Nhanderu takua sp. nov. We revalidate the genus Hygrochroa stat. rev. and three species: Carnotena perlineata stat. rev., Tupac bombycina stat. rev., comb. nov. and Zanola vivax stat. rev. Overall, we propose 82 new generic combinations, synonymise 16 species, and restore the status of 3 species: Apatelodes floramia stat. rest., Carnotena rectilinea comb. nov., stat. rest. and Ephoria nubilosa stat. rest. Additionally, we summarise data on the natural history and distribution of each Apatelodidae species. ZooBank: urn:lsid:zoobank.org:pub:254AA924-30B3-48A8-AB15-CCF2745C3B8E
Measurement of α-synuclein as protein cargo in plasma extracellular vesicles
Authors: Gilboa Tal , Ter-Ovanesyan Dmitry , Wang Shih-Chin , Whiteman Sara , Kannarkat George T. , Church George M. , Chen-Plotkin Alice S. , Walt David R.
Published: October 2024

Extracellular vesicles (EVs) are released by all cells and hold great promise as a class of biomarkers. This promise has led to increased interest in measuring EV proteins from both total EVs as well as brain-derived EVs in plasma. However, measuring cargo proteins in EVs has been challenging because EVs are present at low levels, and EV isolation methods are imperfect at separating EVs from free proteins. Thus, knowing whether a protein measured after EV isolation is truly inside EVs is difficult. In this study, we developed methods to measure whether a protein is inside EVs and quantify the ratio of a protein in EVs relative to total plasma. To achieve this, we combined a high-yield size-exclusion chromatography protocol with an optimized protease protection assay and Single Molecule Array (Simoa) digital enzyme-linked immunoassays (ELISAs) for ultrasensitive measurement of proteins inside EVs. We applied these methods to analyze α-synuclein and confirmed that a small fraction of the total plasma α-synuclein is inside EVs. Additionally, we developed a highly sensitive Simoa assay for phosphorylated α-synuclein (phosphorylated at the Ser129 residue). We found enrichment in the phosphorylated α-synuclein to total α-synuclein ratio inside EVs relative to outside EVs. Finally, we applied the methods we developed to measure total and phosphorylated α-synuclein inside EVs from Parkinson’s disease and Lewy body dementia patient samples. This work provides a framework for determining the levels of proteins in EVs and represents an important step in the development of EV diagnostics for diseases of the brain, as well as other organs.
Metabolic engineering of
Corynebacterium glutamicum
for the production of pyrone and pyridine dicarboxylic acids
Authors: Cho Jae Sung , Luo Zi Wei , Moon Cheon Woo , Prabowo Cindy Pricilia Surya , Lee Sang Yup
Published: October 2024

Environmental concerns from plastic waste are driving interest in alternative monomers from bio-based sources. Pseudoaromatic dicarboxylic acids are promising alternatives with chemical structures similar to widely used petroleum-based aromatic dicarboxylic acids. However, their use in polyester synthesis has been limited due to production challenges. Here, we report the fermentative production of five pseudoaromatic dicarboxylic acids, including 2-pyrone-4,6-dicarboxylic acid (PDC) and pyridine dicarboxylic acids (PDCAs: 2,3-, 2,4-, 2,5-, and 2,6-PDCA), from glucose using five engineered
Corynebacterium glutamicum
strains. A platform
C. glutamicum
chassis strain was constructed by modulating the expression of nine genes involved in the synthesis and degradation pathways of precursor protocatechuate (PCA) and the glucose-uptake system. Comparative transcriptome analysis of the engineered strain against wild-type
C. glutamicum
identified
iolE
(
NCgl0160
) as a target for PDC production. Optimized fed-batch fermentation conditions enabled the final engineered strain to produce 76.17 ± 1.24 g/L of PDC. Using this platform strain, we constructed 2,3-, 2,4-, and 2,5-PDCA-producing strains by modulating the expression of key enzymes. Additionally, we demonstrated a previously uncharacterized pathway for 2,3-PDCA biosynthesis. The engineered strains produced 2.79 ± 0.005 g/L of 2,3-PDCA, 494.26 ± 2.61 mg/L of 2,4-PDCA, and 1.42 ± 0.02 g/L of 2,5-PDCA through fed-batch fermentation. To complete the portfolio, we introduced the 2,6-PDCA biosynthetic pathway to an L-aspartate pathway–enhanced
C. glutamicum
strain, producing 15.01 ± 0.03 g/L of 2,6-PDCA in fed-batch fermentation. The metabolic engineering strategies developed here will be useful for the production of pseudoaromatic chemicals.
Higgs inflation via a metastable standard model potential, generalised renormalisation frame prescriptions and predictions for primordial gravitational waves
Authors: McDonald J.
Published: October 2024

Higgs Inflation via a metastable Standard Model Higgs Potential is possible if the effective Planck mass in the Jordan frame increases after inflation ends. Here we consider the predictions of this model independently of the dynamics responsible for the Planck mass transition. The classical predictions are the same as for conventional Higgs Inflation. The quantum corrections are dependent upon the conformal frame in which the effective potential is calculated. We generalise beyond the usual Prescription I and II renormalisation frame choices to include intermediate frames characterised by a parameter α. We find that the model predicts a well-defined correlation between the values of the scalar spectral index ns
and tensor-to-scalar ratio r. For values of ns
varying between the 2-σ Planck observational limits, we find that r varies between 0.002 and 0.005 as ns
increases, compared to the classical prediction of 0.003. Therefore significantly larger or smaller values of r are possible, which are correlated with larger or smaller values of ns
. In addition, the model can be compatible with the larger values of ns
predicted by Early Dark Energy solutions to the Hubble tension, with correspondingly larger values of r. The model can be tested via the detection of primordial gravitational waves by the next generation of CMB polarisation experiments.
Superradiant phase transitions in ultrastrong coupling regime
Authors: Alodjants A P , Zacharenko P V , Tsarev D V
Published: October 2024

One of the long-standing problems in quantum optics and laser physics is the observation of both equilibrium and non-equilibrium (Dicke) superradiant states in two-level (qubit) systems interacting with the quantized electromagnetic (EM) field. We demonstrate that the superradiant phase transition (PT) at thermal equilibrium in such a system is close to ultrastrong light–matter coupling (USC) condition, which is currently available for superconducting devices. We examine the USC regime for EM fields interacting with two-level systems located in highly connected graph nodes of photonic networks beyond the rotating wave approximation. We find that a critical matter–field coupling parameter reduces

⟨
k
⟩

times due to network peculiarities providing suitable conditions for equilibrium PT observation;

⟨
k
⟩

is a network average node degree. We study the non-equilibrium (Dicke) superradiance for the same network system and show that superradiance appears as a non-equilibrium PT to the superradiant laser operating within a bad cavity limit. We show that population inversion in this case plays the same role as the reciprocal temperature inherent to the equilibrium superradiant PT. Our results open new perspectives for experimental observation of superradiance in cavity-free systems in the gigahertz photonic regime and beyond.
Classifying extended, localized and critical states in quasiperiodic lattices via unsupervised learning
Authors: Zheng 郑 Bohan 博涵 , Zhu 朱 Siyu 思宇 , Zhou 周 Xingping 兴平 , Liu 刘 Tong 通
Published: October 2024

Classification of quantum phases is one of the most important areas of research in condensed matter physics. In this work, we obtain the phase diagram of one-dimensional quasiperiodic models via unsupervised learning. Firstly, we choose two advanced unsupervised learning algorithms, namely, density-based spatial clustering of applications with noise (DBSCAN) and ordering points to identify the clustering structure (OPTICS), to explore the distinct phases of the Aubry–André–Harper model and the quasiperiodic p-wave model. The unsupervised learning results match well with those obtained through traditional numerical diagonalization. Finally, we assess similarity across different algorithms and find that the highest degree of similarity between the results of unsupervised learning algorithms and those of traditional algorithms exceeds 98%. Our work sheds light on applications of unsupervised learning for phase classification.
Introduction to latent variable energy-based models: a path toward autonomous machine intelligence
Authors: Dawid Anna , LeCun Yann
Published: October 2024

Current automated systems have crucial limitations that need to be addressed before artificial intelligence can reach human-like levels and bring new technological revolutions. Among others, our societies still lack level-5 self-driving cars, domestic robots, and virtual assistants that learn reliable world models, reason, and plan complex action sequences. In these notes, we summarize the main ideas behind the architecture of autonomous intelligence of the future proposed by Yann LeCun. In particular, we introduce energy-based and latent variable models and combine their advantages in the building block of LeCun’s proposal, that is, in the hierarchical joint-embedding predictive architecture.
Learning to sample better
Authors: S Albergo Michael , Vanden-Eijnden Eric
Published: October 2024

These lecture notes provide an introduction to recent advances in generative modeling methods based on the dynamical transportation of measures, by means of which samples from a simple base measure are mapped to samples from a target measure of interest. Special emphasis is put on the applications of these methods to Monte–Carlo (MC) sampling techniques, such as importance sampling and Markov Chain Monte–Carlo schemes. In this context, it is shown how the maps can be learned variationally using data generated by MC sampling, and how they can in turn be used to improve such sampling in a positive feedback loop.
Research on Cooperative Tracking of Multiple Agents on Heterogeneous Ground
Authors: Zheng Siying , Wu Jie , Wang Zhaolong , Qu Liping , He Yikai
Published: October 2024

Pursuit-evasion scenarios are typical and significant area of study multi-agent behaviours. While previous research has primarily focused on training pursuit strategies on idealized flat, this paper explores pursuit strategies on heterogeneous ground that rely on ground features from the effects of friction and viscous forces. Since agent interacts with heterogeneous ground and changes its acceleration, we perform multi-agent modelling. Aiming at the multi-agent deep deterministic policy gradient (MADDPG) algorithm’s low training efficiency and slow convergence speed in pursuit learning, we use the prioritized experience selection mechanism of MADDPG algorithm (PES-MADDPG) which improve the experience extraction mechanism based on the policy evaluation function error and the experience extraction training frequency. With this approach, the design of rewards results in faster convergence of reward values. The experimental findings confirm that the suggested method delivers better performance and effectiveness for pursuers and evaders on heterogeneous ground, and both can acquire the relevant movement strategies through training.
Design and Operation of IoT System and Power Communication with Digital Twin Technology
Authors: Lou Jia , Wang Chaoer , Xu Mengjie , He Le , Zhang Pengjie
Published: October 2024

This paper explores how to integrate digital twin technology into IoT system design to achieve more efficient monitoring and maintenance of power communication networks. By introducing digital twin technology, the real-time performance and accuracy of embedded systems in power communication are enhanced, providing strong data support and simulation environments for predictive maintenance and fault diagnosis. This paper combines theoretical research with practical applications to propose an embedded IoT system design based on the ARM9 platform and verifies its effectiveness in power communication networks. In the testing phase, the ARM9-based IoT system demonstrated a processing speed 15% faster than previous designs, with a latency reduction of 18% in communication processes. These enhancements contribute to the overall efficiency and reliability of power communication networks.
Research on Amplification Algorithm of Small Sample Soil Composite Data Based on Probability Distribution
Authors: Zhang Shuyue , Liang Xiangyang , Song Yang
Published: October 2024

Analyzing and studying the data of soil compounds from 10 cities, two important features were found in this project. First, the data for all compounds in soil follow a normal distribution with different parameters. Therefore, this paper argues that small-sample soil compound amplification data should also have these two characteristics. Based on this, this paper proposes a new algorithm called PDWCC (probability distribution with correlation coefficient) for amplification of small-sample soil compound data. The algorithm combines a probability distribution with a Pearson correlation coefficient. In addition, an optimized genetic algorithm incorporating a mutation operator was introduced to improve the efficiency of data amplification. Finally, experimental comparisons were made with conventional Bootstrap and SMOTE amplification algorithms using SVM classifiers. The results show that the PDWCC amplification algorithm outperforms the other algorithms in terms of classification accuracy, recall and F1 value with mean values of 81.77%, 79.34% and 78.65%, respectively.
A Holt Trend-Enabled Attention-ConV-GRU Method for Long-Term Degradation Prediction of Fuel Cells
Authors: Xie Teng , Wang Chu , Wang Peng , Wang Xueren , Di Ruohai
Published: October 2024

Proton Exchange Membrane Fuel Cell (PEMFC) has attracted widespread attention as a promising energy conversion device. However, the lack of durability is one of the major reasons limiting the further development of PEMFC. Accurately predicting the Remaining Usable Life (RUL) of a PEMFC is a key prerequisite for durability enhancement. This paper is dedicated to addressing the limitations of the training data interval for RUL prediction performance. Based on the above ideas, we propose a Holt trend-enabled Attention-Convolution-Gated Recurrent Unit method for extracting trend information and making multi-step predictions. The experimental results show that this strategy improves the multi-step prediction and maintains the inherent degradation trend over a longer range of time steps. The Root Mean Square Error and Mean Absolute Error both fell by more than 45%. The prediction accuracy reach 93.76%.