bluuebunny/crossref_metadata_2025 huggingface dataset:
Genetic diversity modulates the physical and transcriptomic response of skeletal muscle to simulated microgravity in male mice
Authors: Zeineddine Yasmina , Friedman Michael A. , Buettmann Evan G. , Abraham Lovell B. , Hoppock Gabriel A. , Donahue Henry J.
Published: December 2023

Developments in long-term space exploration necessitate advancements in countermeasures against microgravity-induced skeletal muscle loss. Astronaut data shows considerable variation in muscle loss in response to microgravity. Previous experiments suggest that genetic background influences the skeletal muscle response to unloading, but no in-depth analysis of genetic expression has been performed. Here, we placed eight, male, inbred founder strains of the diversity outbred mice (129S1/SvImJ, A/J, C57BL/6J, CAST/EiJ, NOD/ShiLtJ, NZO/HILtJ, PWK/PhJ, and WSB/EiJ) in simulated microgravity (SM) via hindlimb unloading for three weeks. Body weight, muscle morphology, muscle strength, protein synthesis marker expression, and RNA expression were collected. A/J and CAST/EiJ mice were most susceptible to SM-induced muscle loss, whereas NOD/ShiLtJ mice were the most protected. In response to SM, A/J and CAST/EiJ mice experienced reductions in body weight, muscle mass, muscle volume, and muscle cross-sectional area. A/J mice had the highest number of differentially expressed genes (68) and associated gene ontologies (328). Downregulation of immunological gene ontologies and genes encoding anabolic immune factors suggest that immune dysregulation contributes to the response of A/J mice to SM. Several muscle properties showed significant interactions between SM and mouse strain and a high degree of heritability. These data imply that genetic background plays a role in the degree of muscle loss in SM and that more individualized programs should be developed for astronauts to protect their skeletal muscles against microgravity on long-term missions.
Cluster-assembled superatomic crystals for chirality-dependent charge-to-spin conversion
Authors: Zhao Yanyan , Zhao Jijun , Guo Yu , Zhou Si
Published: December 2023

In chiral materials, spins and chirality are coupled via spin-orbit interaction, provoking a fast-growing field of chiral spintronics. Compared with the widely explored chiral molecules, exploration of chirality-dependent spin effects in crystals and supramolecules remain limited. Here we assemble chiral superatomic crystals MXTe4 (M = transition metal; X = Ga or Ge) using telluride tetrahedra clusters as building blocks. Distinct from atomic crystals, these assembled monolayers have tunable symmetries and electronic characteristics by tilting the tetrahedral units through the variation of inter-cluster interaction. Dresselhaus-type spin textures and anisotropic spin Hall effect with inversed sign of spin current under opposite geometrical handedness are demonstrated in these chiral monolayers by symmetry analysis and verified by ab initio calculations. These results provide an innovative paradigm for assembling superatomic crystals with designated symmetry and hierarchical structures to access the chirality-driven quantum effects.
Global and local drivers of Echinococcus multilocularis infection in the western Balkan region
Authors: Moloi Sibusiso , Tari Tamás , Halász Tibor , Gallai Bence , Nagy Gábor , Csivincsik Ágnes
Published: December 2023

The cestode, Echinococcus multilocularis, is one of the most threatening parasitic challenges in the European Union. Despite the warming climate, the parasite intensively spread in Europe's colder and warmer regions. Little is known about the expansion of E. multilocularis in the Balkan region. Ordinary least squares, geographically weighted and multi-scale geographically weighted regressions were used to detect global and local drivers that influenced the prevalence in red foxes and golden jackals in the southwestern part of Hungary. Based on the study of 391 animals, the overall prevalence exceeded 18% (in fox 15.2%, in jackal 21.1%). The regression models revealed that the wetland had a global effect (β = 0.391, p = 0.006). In contrast, on the local scale, the mean annual precipitation (β = 0.285, p = 0.008) and the precipitation seasonality (β = − 0.211, p = 0.014) had statistically significant effects on the infection level. The geospatial models suggested that microclimatic effects might compensate for the disadvantages of a warmer Mediterranean climate. This study calls attention to fine-scale analysis and locally acting environmental factors, which can delay the expected epidemic fade-out. The findings of our study are suggested to consider in surveillance strategies.
A survey on performance evaluation of artificial intelligence algorithms for improving IoT security systems
Authors: Meziane Hind , Ouerdi Noura
Published: December 2023

Security is an important field in the Internet of Things (IoT) systems. The IoT and security are topical domains. Because it was obtained 35,077 document results from the Scopus database. Hence, the AI (Artificial Intelligence) has proven its efficiency in several domains including security, digital marketing, healthcare, big data, industry, education, robotic, and entertainment. Thus, the contribution of AI to the security of IoT systems has become a huge breakthrough. This contribution adopts the artificial intelligence (AI) as a base solution for the IoT security systems. Two different subsets of AI algorithms were considered: Machine Learning (ML) and Deep Learning (DL) methods. Nevertheless, it is difficult to determine which AI method and IoT dataset are best (more suitable) for classifying and/or detecting intrusions and attacks in the IoT domain. The large number of existing publications on this phenomenon explains the need for the current state of research that covers publications on IoT security using AI methods. Thus, this study compares the results regarding AI algorithms that have been mentioned in the related works. The goal of this paper is to compare the performance assessment of the existing AI algorithms in order to choose the best algorithm as well as whether the chosen algorithm can be used for classifying or/and detecting intrusions and attacks in order to improve security in the IoT domain. This study compares these methods in term of accuracy rate. Evaluating the current state of IoT security, AI and IoT datasets is the main aim for considering our future work. After that, this paper proposes, as result, a new and general taxonomy of AI techniques for IoT security (classification and detection techniques). Finally, the obtained results from this assessment survey that was dedicated to research conducted between 2018 and 2023 were satisfactory. This paper provides a good reference for researchers and readers in the IoT domain.
The bodily self from psychosis to psychedelics
Authors: Harduf Amir , Panishev Gabriella , Harel Eiran V. , Stern Yonatan , Salomon Roy
Published: December 2023

The sense of self is a foundational element of neurotypical human consciousness. We normally experience the world as embodied agents, with the unified sensation of our selfhood being nested in our body. Critically, the sense of self can be altered in psychiatric conditions such as psychosis and altered states of consciousness induced by psychedelic compounds. The similarity of phenomenological effects across psychosis and psychedelic experiences has given rise to the “psychotomimetic” theory suggesting that psychedelics simulate psychosis-like states. Moreover, psychedelic-induced changes in the sense of self have been related to reported improvements in mental health. Here we investigated the bodily self in psychedelic, psychiatric, and control populations. Using the Moving Rubber Hand Illusion, we tested (N = 75) patients with psychosis, participants with a history of substantial psychedelic experiences, and control participants to see how psychedelic and psychiatric experience impacts the bodily self. Results revealed that psychosis patients had reduced Body Ownership and Sense of Agency during volitional action. The psychedelic group reported subjective long-lasting changes to the sense of self, but no differences between control and psychedelic participants were found. Our results suggest that while psychedelics induce both acute and enduring subjective changes in the sense of self, these are not manifested at the level of the bodily self. Furthermore, our data show that bodily self-processing, related to volitional action, is disrupted in psychosis patients. We discuss these findings in relation to anomalous self-processing across psychedelic and psychotic experiences.
A Gestalt account of human behavior is supported by evidence from switching between single and dual actions
Authors: Huestegge Lynn , Pieczykolan Aleks , Koch Iring
Published: December 2023

The question of how behavior is represented in the mind lies at the core of psychology as the science of mind and behavior. While a long-standing research tradition has established two opposing fundamental views of perceptual representation, Structuralism and Gestalt psychology, we test both accounts with respect to action representation: Are multiple actions (characterizing human behavior in general) represented as the sum of their component actions (Structuralist view) or holistically (Gestalt view)? Using a single-/dual-response switch paradigm, we analyzed switches between dual ([A + B]) and single ([A], [B]) responses across different effector systems and revealed comparable performance in partial repetitions and full switches of behavioral requirements (e.g., in [A + B] → [A] vs. [B] → [A], or [A] → [A + B] vs. [B] → [A + B]), but only when the presence of dimensional overlap between responses allows for Gestalt formation. This evidence for a Gestalt view of behavior in our paradigm challenges some fundamental assumptions in current (tacitly Structuralist) action control theories (in particular the idea that all actions are represented compositionally with reference to their components), provides a novel explanatory angle for understanding complex, highly synchronized human behavior (e.g., dance), and delimitates the degree to which complex behavior can be analyzed in terms of its basic components.
Data-driven distillation and precision prognosis in traumatic brain injury with interpretable machine learning
Authors: Tritt Andrew , Yue John K. , Ferguson Adam R. , Torres Espin Abel , Nelson Lindsay D. , Yuh Esther L. , Markowitz Amy J. , Manley Geoffrey T. , Bouchard Kristofer E. ,   the TRACK-TBI Investigators, Keene C. Dirk , Madden Christopher , McCrea Michael , Merchant Randall , Mukherjee Pratik , Ngwenya Laura B. , Robertson Claudia , Schnyer David , Taylor Sabrina R. , Zafonte Ross
Published: December 2023

Traumatic brain injury (TBI) affects how the brain functions in the short and long term. Resulting patient outcomes across physical, cognitive, and psychological domains are complex and often difficult to predict. Major challenges to developing personalized treatment for TBI include distilling large quantities of complex data and increasing the precision with which patient outcome prediction (prognoses) can be rendered. We developed and applied interpretable machine learning methods to TBI patient data. We show that complex data describing TBI patients' intake characteristics and outcome phenotypes can be distilled to smaller sets of clinically interpretable latent factors. We demonstrate that 19 clusters of TBI outcomes can be predicted from intake data, a ~ 6× improvement in precision over clinical standards. Finally, we show that 36% of the outcome variance across patients can be predicted. These results demonstrate the importance of interpretable machine learning applied to deeply characterized patients for data-driven distillation and precision prognosis.
Assessing population structure and migration patterns of wild boar (Sus scrofa) in Japan
Authors: Sawai Kotaro , Arakawa Aisaku , Taniguchi Masaaki , Xiao Bo , Sawai Miwa , Osaki Makoto , Yamaguchi Emi , Hayama Yoko , Murato Yoshinori , Shimizu Yumiko , Kondo Sonoko , Yamamoto Takehisa
Published: December 2023

Geographical wildlife patterns reflect historical range expansion and connectivity and provide insights into wildlife population management. In our large-scale phylogeographic population analysis of wild boars (Sus scrofa leucomystax) in Japan, we identified 15 clusters using 29 microsatellite markers, each structured within a range of approximately 200 km. This suggests that evolution was essentially driven by isolation by distance, and that the range of gene flow was limited. One cluster contained subpopulations located approximately 900 km apart, indicating the occurrence of past anthropogenic introductions. Moreover, we estimated effective migration to visualize the geographic genetic population diversity. This analysis identified six potential barriers, one of which involved large plains and mountainous areas in the Kanto region of eastern Japan. This barrier likely persisted in the two eastern clusters for an extended period, restricting migration to the neighboring areas. Overall, our study sheds light on the demographic history of wild boar in Japan, provides evidence of past anthropogenic introductions from distant areas, and highlights the importance of geographic barriers in shaping genetic diversity and population dynamics. This knowledge will be beneficial for forming informed wildlife management strategies toward the conservation of genetic integrity and ecological balance of wild boar populations in Japan.
A novel hybrid feature selection and ensemble-based machine learning approach for botnet detection
Authors: Hossain Md. Alamgir , Islam Md. Saiful
Published: December 2023

In the age of sophisticated cyber threats, botnet detection remains a crucial yet complex security challenge. Existing detection systems are continually outmaneuvered by the relentless advancement of botnet strategies, necessitating a more dynamic and proactive approach. Our research introduces a ground-breaking solution to the persistent botnet problem through a strategic amalgamation of Hybrid Feature Selection methods—Categorical Analysis, Mutual Information, and Principal Component Analysis—and a robust ensemble of machine learning techniques. We uniquely combine these feature selection tools to refine the input space, enhancing the detection capabilities of the ensemble learners. Extra Trees, as the ensemble technique of choice, exhibits exemplary performance, culminating in a near-perfect 99.99% accuracy rate in botnet classification across varied datasets. Our model not only surpasses previous benchmarks but also demonstrates exceptional adaptability to new botnet phenomena, ensuring persistent accuracy in a landscape of evolving threats. Detailed comparative analyses manifest our model's superiority, consistently achieving over 99% True Positive Rates and an unprecedented False Positive Rate close to 0.00%, thereby setting a new precedent for reliability in botnet detection. This research signifies a transformative step in cybersecurity, offering unprecedented precision and resilience against botnet infiltrations, and providing an indispensable blueprint for the development of next-generation security frameworks.
Structure-based discovery of novel P-glycoprotein inhibitors targeting the nucleotide binding domains
Authors: Moesgaard Laust , Pedersen Maria L. , Uhd Nielsen Carsten , Kongsted Jacob
Published: December 2023

P-glycoprotein (P-gp), a membrane transport protein overexpressed in certain drug-resistant cancer cells, has been the target of numerous drug discovery projects aimed at overcoming drug resistance in cancer. Most characterized P-gp inhibitors bind at the large hydrophobic drug binding domain (DBD), but none have yet attained regulatory approval. In this study, we explored the potential of designing inhibitors that target the nucleotide binding domains (NBDs), by computationally screening a large library of 2.6 billion synthesizable molecules, using a combination of machine learning-guided molecular docking and molecular dynamics (MD). 14 of the computationally best-scoring molecules were subsequently tested for their ability to inhibit P-gp mediated calcein-AM efflux. In total, five diverse compounds exhibited inhibitory effects in the calcein-AM assay without displaying toxicity. The activity of these compounds was confirmed by their ability to decrease the verapamil-stimulated ATPase activity of P-gp in a subsequent assay. The discovery of these five novel P-gp inhibitors demonstrates the potential of in-silico screening in drug discovery and provides a new stepping point towards future potent P-gp inhibitors.
A retrospective cohort study on the clinical outcomes of patients admitted to intensive care units with dysnatremia
Authors: Ng Pauline Yeung , Cheung Regina Yui Ting , Ip April , Chan Wai Ming , Sin Wai Ching , Yap Desmond Yat-Hin
Published: December 2023

With evolving patient characteristics and patterns of ICU utilization, the impact of dysnatremias on patient outcomes and healthcare costs in the present era have not been well studied. Patients ≥ 18 years admitted to the ICUs in public hospitals in Hong Kong between January 2010 and June 2022 and had at least one serum sodium measurement obtained within 24 h prior to or following ICU admission were stratified into normonatremic (135-145 mmol/L), hyponatremic (< 135 mmol/L) and hypernatremic (> 145 mmol/L) groups. A total of 162,026 patients were included—9098 (5.6%), 40,533 (25.0%) and 112,395 (69.4%) patients were hypernatremic, hyponatremic and normonatremic at the time of ICU admission, respectively. The odds of patients with hypernatremia and hyponatremia dying in the ICU were 27% and 14% higher (aOR 1.27, 95% CI 1.19–1.36 and aOR 1.14, 95% CI 1.08–1.19, respectively; P < 0.001 for both), and 52% and 21% higher for dying in the hospital (aOR 1.52, 95% CI 1.43–1.62 and aOR 1.21, 95% CI 1.17–1.26, respectively; P < 0.001 for both] compared with those with normonatremia. Patients with dysnatremia also had longer ICU length of stay (LOS), hospital LOS, and higher healthcare costs than the normonatremic group. Dysnatremias at ICU admission were associated with increased ICU and in-hospital mortality and overall healthcare burden.
CNN-based flow field prediction for bus aerodynamics analysis
Authors: Garcia-Fernandez Roberto , Portal-Porras Koldo , Irigaray Oscar , Ansa Zugatz , Fernandez-Gamiz Unai
Published: December 2023

The aim of this article is to evaluate the ability of a convolutional neural network (CNN) to predict velocity and pressure aerodynamic fields in heavy vehicles. For training and testing the developed CNN, various CFD simulations of three different vehicle geometries have been conducted, considering the RANS-based k-ω SST turbulent model. Two geometries correspond to the SC7 and SC5 coach models of the bus manufacturer SUNSUNDEGUI and the third one corresponds to Ahmed body. By generating different variants of these three geometries, a large number of representations of the velocity and pressure fields are obtained that will be used to train, verify, and evaluate the convolutional neural network. To improve the accuracy of the CNN, the field representations obtained are discretized as a function of the expected velocity gradient, so that in the areas where there is a greater variation in velocity, the corresponding neuron is smaller. The results show good agreement between numerical results and CNN predictions, being the CNN able to accurately represent the velocity and pressure fields with very low errors. Additionally, a substantial improvement in the computational time needed for each simulation is appreciated, reducing it by four orders of magnitude.
Digitally-enhanced dog behavioral testing
Authors: Farhat Nareed , Lazebnik Teddy , Monteny Joke , Moons Christel Palmyre Henri , Wydooghe Eline , van der Linden Dirk , Zamansky Anna
Published: December 2023

Behavioral traits in dogs are assessed for a wide range of purposes such as determining selection for breeding, chance of being adopted or prediction of working aptitude. Most methods for assessing behavioral traits are questionnaire or observation-based, requiring significant amounts of time, effort and expertise. In addition, these methods might be also susceptible to subjectivity and bias, negatively impacting their reliability. In this study, we proposed an automated computational approach that may provide a more objective, robust and resource-efficient alternative to current solutions. Using part of a ‘Stranger Test’ protocol, we tested n = 53 dogs for their response to the presence and neutral actions of a stranger. Dog coping styles were scored by three dog behavior experts. Moreover, data were collected from their owners/trainers using the Canine Behavioral Assessment and Research Questionnaire (C-BARQ). An unsupervised clustering of the dogs’ trajectories revealed two main clusters showing a significant difference in the stranger-directed fear C-BARQ category, as well as a good separation between (sufficiently) relaxed dogs and dogs with excessive behaviors towards strangers based on expert scoring. Based on the clustering, we obtained a machine learning classifier for expert scoring of coping styles towards strangers, which reached an accuracy of 78%. We also obtained a regression model predicting C-BARQ scores with varying performance, the best being Owner-Directed Aggression (with a mean average error of 0.108) and Excitability (with a mean square error of 0.032). This case study demonstrates a novel paradigm of ‘machine-based’ dog behavioral assessment, highlighting the value and great promise of AI in this context.
Comparative effectiveness of first-line antihypertensive drug classes on the maintenance of estimated glomerular filtration rate (eGFR) in real world primary care
Authors: Gao Qiao , Tan Ngiap Chuan , Lee Mong Li , Hsu Wynne , Choo Jason
Published: December 2023

Renin-angiotensin system inhibitors (RASi), particularly angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin II receptor blockers (ARBs), are commonly used in the treatment of hypertension and are recommended for kidney protection. Uncertainty remains about the effectiveness of RASi being used as first-line antihypertensive therapy on eGFR maintenance compared to its alternatives, especially for those with no or early-stage chronic kidney disease (CKD). We conducted a retrospective cohort study of 19,499 individuals (mean age 64.1, 43.5% males) from primary care in Singapore with 4.5 median follow-up years. The study cohort included newly diagnosed individuals with hypertension (whose eGFR was mainly in CKD stages G1-G2) and initiated on ACEIs, ARBs, beta-blockers (BBs), calcium channel blockers (CCBs) or diuretics (Ds) as first-line antihypertensive monotherapy. We compared the estimated glomerular filtration rate (eGFR) curve before/after the drug initiation over time of patients under different drug classes and analyzed the time to declining to a more advanced stage CKD. Inverse probability of treatment weighting (IPTW) was used to adjust for baseline confounding factors. Two key findings were observed. First, after initiating antihypertensive drugs, the eGFR almost maintained the same as the baseline in the first follow-up year, compared with dropping 3 mL/min/1.73 m2 per year before drug initiation. Second, ARBs were observed to be slightly inferior to ACEIs (HR = 1.14, 95% CI = (1.04, 1.23)) and other antihypertensive agents (HR = 1.10, 95% CI = (1.01, 1.20)) in delaying eGFR decline to a more advanced CKD stage in the study population. Our results showed that initiating antihypertensive agents can significantly maintain eGFR for those newly diagnosed patients with hypertension. However, RASi may not be superior to other antihypertensive agents in maintaining eGFR levels for non-CKD or early stages CKD patients.
Predictors of unfavourable outcome in adults with suspected central nervous system infections: a prospective cohort study
Authors: ter Horst Liora , van Zeggeren Ingeborg E. , Olie Sabine E. ,   I-PACE Study Group, Brenner J. , Citroen J. , van Geel B.M. , Heckenberg S.G.B. , Jellema K. , Kester M.I. , Killestein J. , Mook B.B. , Resok Y.C. , Titulaer M.J. , van Veen K.E.B. , Verschuur C.V.M. , van de Beek Diederik , Brouwer Matthijs C.
Published: December 2023

Suspected central nervous system (CNS) infections may pose a diagnostic challenge, and often concern severely ill patients. We aim to identify predictors of unfavourable outcome to prioritize diagnostics and treatment improvements. Unfavourable outcome was assessed on the Glasgow Outcome Scale at hospital discharge, defined by a score of 1 to 4. Of the 1152 episodes with suspected CNS infection, from two Dutch prospective cohorts, the median age was 54 (IQR 37–67), and 563 episodes (49%) occurred in women. The final diagnoses were categorized as CNS infection (N = 358 episodes, 31%), CNS inflammatory disease (N = 113, 10%), non-infectious non-inflammatory neurological disorder (N = 388, 34%), non-neurological infection (N = 252, 22%), and other systemic disorder (N = 41, 4%). Unfavourable outcome occurred in 412 of 1152 (36%), and 99 died (9%). Predictors for unfavourable outcomes included advanced age, absence of headache, tachycardia, altered mental state, focal cerebral deficits, cranial nerve palsies, low thrombocytes, high CSF protein, and the final diagnosis of CNS inflammatory disease (odds ratio 4.5 [95% confidence interval 1.5–12.6]). Episodes suspected of having a CNS infection face high risk of experiencing unfavourable outcome, stressing the urgent need for rapid and accurate diagnostics. Amongst the suspected CNS infection group, those diagnosed with CNS inflammatory disease have the highest risk.
2 × 4.5 kW bidirectional output near-single-mode quasi-continuous wave monolithic fiber laser
Authors: Ding Xinyi , Zeng Lingfa , Wang Li , Wu Hanshuo , Wang Peng , Zhang Hanwei , Wang Xiaolin , Ning Yu , Xi Fengjie , Xu Xiaojun
Published: December 2023

Quasi-continuous wave (QCW) laser has a very broad application in the industrial field, especially in additive manufacturing, surface treatment, laser cutting, laser cleaning, and laser drilling. Compared with the unidirectional fiber laser, the bidirectional output can be achieved two ports high power output with only one resonator, which can greatly reduce the industrial cost. However, there are few researches on QCW fiber lasers with bidirectional output. Here, we optimized and demonstrated a bidirectional output QCW laser with output power of 2 × 4.5 kW based on a double-clad ytterbium-doped fiber with a core/cladding diameter of 25/400 μm. The peak power at both ends reached 4515 W and 4694 W, respectively. The Raman suppression ratio at both ends of A and B is about 12 dB, and the beam quality factor M2 is about 1.37 and 1.42, respectively. The corresponding optical-to-optical efficiency is 79%. To the best of our knowledge, this is the highest peak power of QCW laser with near-single-mode beam quality in a bidirectional structure laser.
Heat generation/absorption effect on natural convective heat transfer in a wavy triangular cavity filled with nanofluid
Authors: Islam Tarikul , Alam Md. Nur , Niazai Shafiullah , Khan Ilyas , Fayz-Al-Asad Md. , Alqahtani Sultan
Published: December 2023

This study is numerically executed to investigate the influence of heat generation or absorption on free convective flow and temperature transport within a wavy triangular enclosure filled by the nanofluid taking the Brownian effect of nanoparticles. The water (H2O) is employed as base fluid and copper (Cu) as nanoparticles for making effective Cu–H2O nanofluids. The perpendicular sinusoidally wavy wall is cooled at low temperature while the horizontal bottom sidewall is heated non-uniformly (sinusoidal). The inclined wall of the enclosure is insulated. The governing dimensionless non-linear PDEs are executed numerically with the help of the Galerkin weighted residual type finite element technique. The numerically simulated results are displayed through average Nusselt number, isothermal contours, and streamlines for the various model parameters such as Hartmann number, Rayleigh number, heat generation or absorption parameter, nanoparticles volume fraction, and undulation parameter. The outcomes illustrate that the temperature transport rate augments significantly for the enhancement of Rayleigh number as well as nanoparticles volume fraction whereas reduces for the increment of Hartman number. The heat transfer is significantly influenced by the size, shape, and Brownian motion of the nanoparticles. The rate of heat transport increases by 20.43% considering the Brownian effect for 1% nanoparticle volume. The thermal performance increases by 8.66% for the blade shape instead of the spherical shape of nanoparticles. In addition, heat transfer is impacted by the small size of nanoparticles. The thermal transport rate increases by 35.87% when the size of the nanoparticles reduces from 100 to 10 nm. Moreover, the rate of heat transmission increases efficiently as the undulation parameter rises. It is also seen that a crucial factor in the flow of nanofluids and heat transmission is the heat generation/absorption parameter that influences temperature distribution, heat transfer rates, and overall thermal performance.
Examining district-level disparity and determinants of timeliness of emergency medical services in Maharashtra, India
Authors: Jana Arnab , Sarkar Ahana , Parmar Vipul , Saunik Sujata
Published: December 2023

The quality of emergency medical services remains a major public health issue in developing countries in terms of access, availability, or timely delivery, owing to high socio-economic and ethnic disparities. Particularly, the timeliness of EMS remains a drawback, leading to higher mortality and morbidity. The aim of the study is to assess the district-level differences and factors that influence ambulance travel time, as there was no study done in the Indian scenario. Sequential Explanatory Design was applied here, which involved a descriptive study and spatial analysis of the call volume and distribution to understand the operational challenges of MEMS, followed by in-depth interviews among medical officers and officials to explore the reasons for the challenges. The data, shared by the Department of Health, Government of Maharashtra, consisted of 38,823 records (emergency: 16,197 and hospital-to-hospital transfer: 22,626), including emergency and hospital-to-hospital transfer calls across 36 districts of Maharashtra for November 2022. Spatial analyses were performed to identify the districts with challenges of timeliness. The average ambulance response time (T) across the districts was reported at 134.5 min for emergency cases and 222.80 min for hospital-to-hospital transfer cases. The total ambulance response time, was classified as preparation time (t1:3.53 min for emergency, 3.69 min for hospital-to-hospital transfer), travel time from base to scene (t2: 23.15 min for emergency, 17.18 min for hospital-to-hospital transfer), time required at scene (t3: 12.12 min for emergency, 14.72 min for hospital-to-hospital transfer), travel time from scene to hospital (t4:39.41 min for emergency, 74.34 min for hospital-to-hospital transfer), patient handover time (t5: 10.85 min for emergency, 13.84 min for hospital-to-hospital transfer), and return from base to hospital (t6: 41.89 min for emergency, 94.72 min for hospital-to-hospital transfer). Multivariate linear regression was conducted to investigate the factors that influence ambulance travel time. The finding identifies that the ambulance travel time increased for the districts with lesser population density, lower road density, fewer hospitals, a higher district area served per ambulance, and a higher population served per ambulance. Additionally, socio-cultural reasons affecting health-seeking behaviour, early closing of healthcare centres, undercapacity and resource-deficit healthcare centres, and overloading of specialised tertiary hospitals were identified as determinants of delay in patient assessment and handover time in qualitative findings. A decisive and multi-sectoral approach is required to address the timeliness of EMS in the Indian context.
Temporal coherence in particulate matter in East Asian outflow regions: fingerprints of ENSO and Asian dust
Authors: Kueh Mien-Tze , Lin Chuan-Yao , Chien Yi-Yun
Published: December 2023

Understanding temporal coherence in particulate matter (PM) pollution across East Asian outflow regions is crucial for collaborative efforts in addressing air pollution challenges. In this study, we analyze daily PM exceedance patterns using ground-based measurements over the past two decades, focusing on the influence of El Niño-Southern Oscillation (ENSO) and Asian dust activity. ENSO-related coherent PM exceedance shows lower occurrence during El Niño compared to La Niña in spring, due to weakened continental outflows and increased precipitation. Temporal distribution of dust-related coherent PM exceedance closely mirrors springtime dust activity in source regions, indicating significant dust emission impact on outflow regions. Our findings have implications for climate variability and the assessment of multi-decade model simulations.
Drivers of soil microbial and detritivore activity across global grasslands
Authors: Siebert Julia , Sünnemann Marie , Hautier Yann , Risch Anita C. , Bakker Jonathan D. , Biederman Lori , Blumenthal Dana M. , Borer Elizabeth T. , Bugalho Miguel N. , Broadbent Arthur A. D. , Caldeira Maria C. , Cleland Elsa , Davies Kendi F. , Eskelinen Anu , Hagenah Nicole , Knops Johannes M. H. , MacDougall Andrew S. , McCulley Rebecca L. , Moore Joslin L. , Power Sally A. , Price Jodi N. , Seabloom Eric W. , Standish Rachel , Stevens Carly J. , Zimmermann Stephan , Eisenhauer Nico
Published: December 2023

Covering approximately 40% of land surfaces, grasslands provide critical ecosystem services that rely on soil organisms. However, the global determinants of soil biodiversity and functioning remain underexplored. In this study, we investigate the drivers of soil microbial and detritivore activity in grasslands across a wide range of climatic conditions on five continents. We apply standardized treatments of nutrient addition and herbivore reduction, allowing us to disentangle the regional and local drivers of soil organism activity. We use structural equation modeling to assess the direct and indirect effects of local and regional drivers on soil biological activities. Microbial and detritivore activities are positively correlated across global grasslands. These correlations are shaped more by global climatic factors than by local treatments, with annual precipitation and soil water content explaining the majority of the variation. Nutrient addition tends to reduce microbial activity by enhancing plant growth, while herbivore reduction typically increases microbial and detritivore activity through increased soil moisture. Our findings emphasize soil moisture as a key driver of soil biological activity, highlighting the potential impacts of climate change, altered grazing pressure, and eutrophication on nutrient cycling and decomposition within grassland ecosystems.
Polarization and multiscale structural balance in signed networks
Authors: Talaga Szymon , Stella Massimo , Swanson Trevor James , Teixeira Andreia Sofia
Published: December 2023

Polarization, or a division into mutually hostile groups, is a common feature of social systems. It is studied in Structural Balance Theory in terms of semicycles in signed networks. However, enumerating semicycles is computationally expensive, so approximations are often needed. Here we introduce the Multiscale Semiwalk Balance approach for measuring the degree of balance (DoB) in (un)directed, (un)weighted signed networks by approximating semicycles with closed semiwalks. It allows selecting the resolution of analysis appropriate for assessing DoB motivated by the Locality Principle, which posits that patterns in shorter cycles are more important than in longer ones. Our approach overcomes several limitations affecting walk-based approximations and provides methods for assessing DoB at various scales, from graphs to individual nodes, and for clustering signed networks. We demonstrate its effectiveness by applying it to real-world social systems, which leads to explainable results for networks with expected patterns (polarization in the US Congress) and a more nuanced perspective for other systems. Our work may facilitate studying polarization and structural balance in a variety of contexts and at multiple scales.
Repair-driven DNA tetrahedral nanomachine combined with DNAzyme for 8-oxo guanine DNA glycosylase activity assay, drug screening and intracellular imaging
Authors: Qiu Yun , Liu Bin , Zhou Wenchao , Tao Xueqing , Liu Yang , Mao Linxi , Wang Huizhen , Yuan Hanwen , Yang Yupei , Li Bin , Wang Wei , Qiu Yixing
Published: December 2023

A DNA tetrahedral nanomachine and DNAzyme-based fluorescent approach for 8-oxo guanine DNA glycosylase activity detection, natural compound screening, and intracellular imaging.
Quantitative analysis of drug tablet aging by fast hyper-spectral stimulated Raman scattering microscopy
Authors: Wei Yuxiao , Pence Isaac J. , Wiatrowski Anna , Slade Julia B. , Evans Conor L.
Published: December 2023

Pharmaceutical development of drug tablets requires ensuring chemical uniformity and stability. S4RS imaging of drug tablets can quantify chemical degradation and distribution at a faster speed and higher resolution compared to existing technologies.
UPLC-MS/MS method for quantitative determination of the advanced glycation endproducts Nε-(carboxymethyl)lysine and Nε-(carboxyethyl)lysine
Authors: Skrajewski-Schuler Lauren A. , Soule Logan D. , Geiger Morgan , Spence Dana
Published: December 2023

Within hyperglycemic blood storage, proteins on the red blood cell (RBC) membrane undergo glycation to form advanced glycated end products (AGEs).
Ammonia synthesis by the reductive N–N bond cleavage of hydrazine using an air-stable, phosphine-free ruthenium catalyst
Authors: Mohanty Aisa , Rout Smruti Rekha , Dandela Rambabu , Daw Prosenjit
Published: December 2023

An air-stable, phosphine-free ruthenium-based molecular catalyst is developed for the efficient reduction of hydrazine to ammonia using suitable reductant and proton pairs.
Chronological development of functional fluorophores for bio-imaging
Authors: Munan Subrata , Chang Young-Tae , Samanta Animesh
Published: December 2023

This review explores the historical to contemporary evolution of fluorophores, emphasizing applications in cellular imaging. It covers the chronological development of advanced fluorophores (2007–2022) and speculates on future biomedical challenges.
Fractional Marcus–Hush–Chidsey–Yakopcic current–voltage model for redox-based resistive memory devices
Authors: Paradezhenko G. V. , Prodan D. V. , Pervishko A. A. , Yudin D. , Allagui A.
Published: December 2023

We propose a circuit-level model supplemented with memory trace for describing electrical behavior of redox-based resistive memory devices.
A performance degradation model of nitrile butadiene rubber (NBR) O-rings for hydrogen permeation effects under high-pressure
Authors: Wu Di , Li Yantang , Hua Yang , Xu Jingxiang , Zhang Xiaolu , Miao Yang
Published: December 2023

The integration of molecular chain changes on a microscopic scale to achieve macroscopic performance is crucial in degradation processes concerning O-ring seals.
Analysing the stability of He-filled hydrates: how many He atoms fit in the sII crystal?
Authors: Yanes-Rodríguez Raquel , Prosmiti Rita
Published: December 2023

Multioccupancy and stability of He@sII clathrate hydrates from first-principles computations.
The design and optimization of heterogeneous catalysts using computational methods
Authors: Shambhawi  , Mohan Ojus , Choksi Tej S. , Lapkin Alexei A.
Published: December 2023

Computational design of catalytic materials is a high dimensional structure optimization problem that is limited by the bottleneck of expensive quantum computation tools. An illustration of interaction of different factors involved in the design and optimization of a catalyst.
Atomic Sn sites supported on N-doped porous carbon for accelerating the oxygen reduction reaction
Authors: Jiang Rong , Zhi Qianjun , Jin Yucheng , Liu Wenping , Chen Baotong , Yang Baochan , Li Wenjun , Qi Dongdong , Wang Kang , Sun Tingting , Jiang Jianzhuang
Published: December 2023

A catalyst with discrete atomic Sn sites decorated into N-doped porous carbon has been prepared, which displays superior ORR activity in both acid and alkaline solutions.
Light cycling as a key to understanding the outdoor behaviour of perovskite solar cells
Authors: Khenkin Mark , Köbler Hans , Remec Marko , Roy Rajarshi , Erdil Ulas , Li Jinzhao , Phung Nga , Adwan Ghefar , Paramasivam Gopinath , Emery Quiterie , Unger Eva , Schlatmann Rutger , Ulbrich Carolin , Abate Antonio
Published: December 2023

The long-term outdoor performance and stability of Perovskite Solar Cells showed several features that stem from the device's meta-stability. To rationalize this behavior we need indoor ageing experiments with cycled light.
Nutritional quality analysis of high-moisture extrudates containing mixed proteins from soy and surimi
Authors: Hu Anna , Zhang Yujie , Zhang Jinchuang , Li Tongqing , Wang Zhaojun , Wang Qiang
Published: December 2023

High-moisture extrusion of mixed proteins from soy and surimi improves the nutritional qualities of alternative protein products.
The promotion of fatty acid β-oxidation by hesperidin via activating SIRT1/PGC1α to improve NAFLD induced by a high-fat diet
Authors: Nie Tong , Wang Xin , Li Aqun , Shan Anshan , Ma Jun
Published: December 2023

Reducing fat deposits in hepatocytes is a direct treatment for nonalcoholic fatty liver disease (NAFLD) and the fatty acid metabolic processes mediated by fatty acid β-oxidation are important for the prevention of NAFLD.
High-throughput single-cell assay for precise measurement of the intrinsic mechanical properties and shape characteristics of red blood cells
Authors: Wei Qiaodong , Xiong Ying , Ma Yuhang , Liu Deyun , Lu Yunshu , Zhang Shenghong , Wang Xiaolong , Huang Huaxiong , Liu Yingbin , Dao Ming , Gong Xiaobo
Published: December 2023

A unique high-throughput single-cell microfluidic method for measuring the inherent physical/mechanical properties of RBCs.
Pore-interface engineering improves doxorubicin loading to triazine-based covalent organic framework
Authors: Rathi Preeti , Chowdhury Sumanta , Das Partha Pratim , Keshri Anand Kumar , Chaudhary Anubha , Siril Prem Felix
Published: December 2023

Pore-surface engineering improves anticancer drug loading over surface area enhancement in COFs.
Enhancing the perovskite solar cell performance by the interface modification of Zn–Sn–O compound heterostructures
Authors: Poobalan Ranjith Kumar , Ramanathan Ramarajan , R. Chellakumar , Ravichandran K. , Zinigrad Michel
Published: December 2023

Interface modification of Zn–Sn–O compound heterostructure for an enhanced perovskite solar cell performance.
One pot oxygen mediated syntheses of stable radicals
Authors: Kulshrestha Mohit , Ramachandran C. N. , Gonnade Rajesh G. , Sadhu Kalyan K.
Published: December 2023

Aerial oxygen and base mediated synthesis is performed for three unprecedented neutral carbon centered radicals in solid state, whose emissions and stabilities depend on C(sp3)-, C(sp2)- or H-substitution at the radical center.
A mechanistic study on coupling of CO2 and epoxide mediated by guanidine/TBAI catalysts
Authors: Fu Yihua , Zhang Yan , Hu Changwei , Su Zhishan
Published: December 2023

Guanidine acted as H-bond donor to activate styrene oxide by (N)H⋯O interaction, facilitating epoxide ring-opening.
Self-decorating cells via surface-initiated enzymatic controlled radical polymerization
Authors: Belluati Andrea , Happel Dominic , Erbe Malte , Kirchner Nicole , Szelwicka Anna , Bloch Adrian , Berner Valeria , Christmann Andreas , Hertel Brigitte , Pardehkhorram Raheleh , Reyhani Amin , Kolmar Harald , Bruns Nico
Published: December 2023

Through the use of surface-displayed horseradish peroxidase, this work explores the enzymatic catalysis of both bioRAFT and bioATRP to prompt polymer synthesis on the surface of S. cerevisiae cells, with bioATRP outperforming bioRAFT polymerization.
Recent development of manganese dioxide-based materials as zinc-ion battery cathode
Authors: Jia Shaofeng , Li Le , Shi Yue , Wang Conghui , Cao Minghui , Ji Yongqiang , Zhang Dan
Published: December 2023

This review of the recent research progress of manganese dioxide-based zinc ion batteries (ZIBs), and the reaction mechanism, electrochemical performance, and challenges.
Pyrolysis-free synthesis of a high-loading single-atom Cu catalyst for efficient electrocatalytic CO2-to-CH4 conversion
Authors: Li Jiawei , Jiang Yawen , Li Jiayi , Wang Xinyu , Liu Hengjie , Zhang Ning , Long Ran , Xiong Yujie
Published: December 2023

A pyrolysis-free method is developed to prepare a single-atom Cu catalyst with controllable loading and dispersion that achieves efficient electrocatalytic CO2-to-CH4 conversion with a high activity and selectivity.
Copper-mediated [3 + 2] oxidative cyclization of oxime acetate and its utility in the formal synthesis of fentiazac
Authors: Jadhao Nitin L , Musale Harish B. , Gajbhiye Jayant M. , Humne Vivek T.
Published: December 2023

The direct synthesis of 2-aminothiazole has been developed from oxime acetate using a copper catalyst. The applicability of the present method is used in the formal synthesis of fentiazac.
Interlayer coupling controlled electronic and magnetic properties of two-dimensional VOCl2/PtTe2 van der Waals heterostructure
Authors: Qian Zhonghua , Ji Jie , Qian Liyan , Mao Yuxuan , Yao Suchen , Xu Jingyi , Wang Licheng
Published: December 2023

Two dimensional VOCl2/PtTe2 heterostructure with ferromagnetic metal and large magnetic anisotropy energy were investigated.
Monitoring the synthesis of neutral lipids in lipid droplets of living human cancer cells using two-color infrared photothermal microscopy
Authors: Park Chanjong , Lim Jong Min , Hong Seok-Cheol , Cho Minhaeng
Published: December 2023

Two-color infrared photothermal microscopy (2C-IPM) can be used to study lipid metabolism in lipid droplets (LDs). Using deuterated fatty acids, it distinguishes endogenous and newly synthesized lipids, allowing quantitative analysis and monitoring of neutral lipid synthesis in living cell LDs.
Conductive polymer nanocomposites: recent advances in the construction of electrochemical biosensors
Authors: Zeng Hui , Xie Ying , Liu Tao , Chu Zhenyu , Dempsey Eithne , Jin Wanqin
Published: December 2023

This review focuses on the design, preparation and application of nanostructured CPNs in the construction of advanced electrochemical biosensors in medical diagnostics.
Ruthenium catalyzed transformation of levulinic acid to γ-valerolactone in water
Authors: Priya Bhanu , Sahu Vinod K. , Singh Sanjay K.
Published: December 2023

Efficient transformation of biomass derived LA to GVL is achieved over a Ru-pyridylamine based molecular catalyst in water at 80 °C using HCOOH, where the role of the ligand was found to be crucial in achieving high catalytic activity (yield 95%).
A zinc porphyrin-based halogen-bonded organic framework with the heavy atom effect as a highly efficient photocatalyst for oxidative coupling of amines
Authors: Sun Penghao , Dong Hongqiang , Lv Siheng , Yin Yongfei , Gong Guanfei , Wang Lu , Wang Jike , Chen Shigui
Published: December 2023

A novel zinc porphyrin-based [N⋯I+⋯N] halogen-bonded organic framework has high photocatalytic 1O2 yields, which results from the heavy atom effect of the I+, and acts as a highly efficient photocatalyst for organic synthesis.
Facile one-pot synthesis of flower-like ellagic acid microparticles incorporating anti-microbial peptides for enhanced wound healing
Authors: Zhang Guo , Wang Yu , Qiu Hua , Lu Lei
Published: December 2023

Flower-like microparticles, AMPs@EAMPs, effectively combine antimicrobial peptides with ellagic acid, offering long-term antibacterial activity, biocompatibility, and potential for tissue repair and immune barrier reconstruction.