bluuebunny/crossref_metadata_2025 huggingface dataset:
A bibliographic outlook: machine learning on biofilm
Authors: Ding Yuanzhao , Chen Shan
Published: December 2024

A biofilm refers to an intricate community of microorganisms firmly attached to surfaces and enveloped within a self-generated extracellular matrix. Machine learning (ML) methodologies have been harnessed across diverse facets of biofilm research, encompassing predictions of biofilm formation, identification of pivotal genes and the formulation of novel therapeutic approaches. This investigation undertook a bibliographic analysis focused on ML applications in biofilm research, aiming to present a comprehensive overview of the field’s current status. Our exploration involved searching the Web of Science database for articles incorporating the term “machine learning biofilm,” leading to the identification and analysis of 126 pertinent articles. Our findings indicate a substantial upswing in the publication count concerning ML in biofilm over the last decade, underscoring an escalating interest in deploying ML techniques for biofilm investigations. The analysis further disclosed prevalent research themes, predominantly revolving around biofilm formation, prediction and control. Notably, artificial neural networks and support vector machines emerged as the most frequently employed ML techniques in biofilm research. Overall, our study furnishes valuable insights into prevailing trends and future trajectories within the realm of ML applied to biofilm research. It underscores the significance of collaborative efforts between biofilm researchers and ML experts, advocating for interdisciplinary synergy to propel innovation in this domain.
Data-driven supervision to optimize the effectiveness of proactive case detection for mental health care among children: a proof-of-concept study
Authors: van den Broek Myrthe , Greene M. Claire , Guevara Anthony F. , Agondeze Sandra , Kyanjo Erimiah , Irakoze Olivier , Kasujja Rosco , Kohrt Brandon A. , Jordans Mark J. D.
Published: December 2024

This proof-of-concept study evaluated an optimization strategy for the Community Case Detection Tool (CCDT) aimed at improving community-level mental health detection and help-seeking among children aged 6–18 years. The optimization strategy, CCDT+, combined data-driven supervision with motivational interviewing techniques and behavioural nudges for community gatekeepers using the CCDT. This mixed-methods study was conducted from January to May 2023 in Palorinya refugee settlement in Uganda. We evaluated (1) the added value of the CCDT+ in improving the accuracy of detection and mental health service utilization compared to standard CCDT, and (2) implementation outcomes of the CCDT+. Of the 1026 children detected, 801 (78%) sought help, with 656 needing mental health care (PPV = 0.82; 95% CI: 0.79, 0.84). The CCDT+ significantly increased detection accuracy, with 2.34 times higher odds compared to standard CCDT (95% CI: 1.41, 3.83). Additionally, areas using the CCDT+ had a 2.05-fold increase in mental health service utilization (95% CI: 1.09, 3.83). The CCDT+ shows promise as an embedded quality-optimization process for the detection of mental health problems among children and enhance help-seeking, potentially leading to more efficient use of mental health care resources.
Responses of Ventenata dubia and other species seven years after herbicide applications to an improved pasture in Montana
Authors: Mangold Jane M. , Sencenbaugh Lilly , Harvey Audrey J. , Rebis Matthew E. , Rew Lisa J.
Published: December 2024

We evaluated herbicides for controlling the annual grass ventenata [Ventenata dubia (Leers) Coss.], with particular interest in indaziflam, a preemergence cellulose biosynthesis inhibitor. In 2016, indaziflam was applied postemergence alone and in mixture with glyphosate, imazapic, propoxycarbazone-sodium, or rimsulfuron to an improved pasture in southwestern Montana. A non-sprayed control was included for comparison purposes. Canopy cover of each species was assessed annually for 7 yr; cover was grouped by life-form and longevity, and species richness was calculated. Five years (2021) after treatment, the seedbank was assessed. Our results indicated that treatments including indaziflam reduced V. dubia cover 1 to 3 yr and even up to 6 yr after application, with V. dubia cover being zero or close to zero. However, at 7 yr (2023) after treatment, V. dubia was low across all treatments, including the non-sprayed control. Perennial grasses and forbs and annual forbs were generally unaffected by any treatment and did not increase in cover over the 7 yr, even though V. dubia decreased. Two years after treatment, species richness was lowest in treatments that included indaziflam, but at 7 yr, species richness was similar across all treatments. Indaziflam depleted the monocot and dicot seedbank, with fewer than 5 seedlings of any species emerging from treatments that included indaziflam, while other treatments resulted in 60 to 165 seedlings per sample (40 cm3 of soil). In summary, at our study site, a single application of indaziflam controlled V. dubia for 6 yr, appeared to deplete the seedbank at 5 yr, and cover of perennial and annual vegetation and species richness was unaffected. By the end of the study, though, V. dubia cover appeared to be influenced by factors other than herbicide treatments, possibly variable precipitation over time, an exclusion of grazing, and competitive perennial grasses dominating the site.
Invasive knotweed (Polygonum spp.) movement in a northern New Hampshire (USA) stream system
Authors: Charpentier Jessica E. , Gunn John S. , Cheng Matthew L.H. , Licht Sofia , McCoy Jon H. , Truscott Jonathan C. , Furey Nathan B.
Published: December 2024

Non-native plants negatively impact ecosystems via a variety of mechanisms, including in forested riparian areas. Japanese knotweed [Polygonum cuspidatum Siebold & Zucc.] and its hybrids (referred to as Polygonum spp. hereafter) are widely spread throughout North America and can impact flora and fauna of riparian habitats. Thus, information improving our ability to understand and predict the potential spread and colonization of Polygonum spp. is valuable. One dispersal mechanism is hydrochory (i.e., dispersal by water), including the downstream dispersal of viable stems that can facilitate rapid invasion within a watershed. We used passive integrated transponder (PIT) telemetry in experimental releases of Polygonum spp. stems to track the downstream transport of Polygonum spp. in a small (second-order) stream in northern New Hampshire, USA, in the summers of 2021 and 2022. A total of 180 (90 each year) Polygonum spp. stems were released at three sites within the stream reach, with 185 (∼98%) being recaptured at least once, with a total of 686 recaptures. Individual relocated stems moved a maximum distance of 30 to 875 m downstream in 2021 and 13 to 1,233 m in 2022 during regular flows; however, a high-streamflow event in July 2021 flushed out all remaining stems downstream of the study area. Generalized additive mixed models (GAMMs) identified site-specific differences in stem movement rates and a general reduction in movement rates with increased duration of time elapsed since post-release. In general, Polygonum spp. stems moved farther downstream in sites with lower channel sinuosity, although other fine-scale habitat factors (e.g., water depth, habitat type, and presence of wood and debris jams) likely contribute to the ability for Polygonum spp. to further disperse or otherwise be retained within the channel. Thus, stream morphology and stream flow are likely to affect where Polygonum spp. stems will be retained and potentially reestablish. Predictive tools identifying areas of higher probability of hydrochory-based dispersal could help to focus removal efforts when employed or to identify riparian habitats at highest risk for spread.
Ages and Stages Questionnaires in the assessment of young children after cardiac surgery
Authors: Sabarigirivasan Vaishnavi , Read Julie S. , Ridout Deborah , Hoskote Aparna , Sheehan Karen , Wellman Paul , Jones Alison , Wray Jo , Brown Katherine L.
Published: December 2024

Aims:

This study explored the prospective use of the Ages and Stages Questionnaires-3 in follow-up after cardiac surgery.

Materials and Method:

For children undergoing cardiac surgery at 5 United Kingdom centres, the Ages and Stages Questionnaires-3 were administered 6 months and 2 years later, with an outcome based on pre-defined cut-points: Red = 1 or more domain scores >2 standard deviations below the normative mean, Amber = 1 or more domain scores 1–2 standard deviations below the normal range based on the manual, Green = scores within the normal range based on the manual.

Results:

From a cohort of 554 children <60 months old at surgery, 306 participated in the postoperative assessment: 117 (38.3%) were scored as Green, 57 (18.6%) as Amber, and 132 (43.1%) as Red. Children aged 6 months at first assessment (neonatal surgery) were likely to score Red (113/124, 85.6%) compared to older age groups (n = 32/182, 17.6%). Considering risk factors of congenital heart complexity, univentricular status, congenital comorbidity, and child age in a logistic regression model for the outcome of Ages and Stages score Red, only younger age was significant (p < 0.001). 87 children had surgery in infancy and were reassessed as toddlers. Of these, 43 (49.2%) improved, 30 (34.5%) stayed the same, and 13 (16.1%) worsened. Improved scores were predominantly in those who had a first assessment at 6 months old.

Discussion:

The Ages and Stages Questionnaires results are most challenging to interpret in young babies of 6 months old who are affected by complex CHD.
Time series analysis of GSS bonds Part 2 – further univariate analysis of S&P Green Bond Index
Authors: Dey Debashish
Published: December 2024

The popularity of green, social and sustainability-linked bonds (GSS bonds) continues to rise, with circa US$939 billion of such bonds issued globally in 2023. Given the rising popularity of ESG-related investment solutions, their relatively recent emergence, and limited research in this field, continued investigation is essential. Extending non-traditional techniques such as neural networks to these fields creates a good blend of innovation and potential. This paper follows on from our initial publication, where we aim to replicate the S&P Green Bond Index (i.e. this is a time series problem) over a period using non-traditional techniques (neural networks) predicting 1 day ahead. We take a novel approach of applying an N-BEATS model architecture. N-BEATS is a complex feedforward neural network architecture, consisting of basic building blocks and stacks, introducing the novel doubly residual stacking of backcasts and forecasts. In this paper, we also revisit the neural network architectures from our initial publication, which include DNNs, CNNs, GRUs and LSTMs. We continue the univariate time series problem, increasing the data input window from 1 day to 2 and 5 days respectively, whilst still aiming to predict 1 day ahead.
Deciphering the concurrent phenomenon of childhood malnutrition by using the extended composite index of anthropometric failure (ECIAF): facts from the BESLEN project
Authors: Dumlu Bilgin Gözde , Kaya Cebioğlu İrem , Kavsara Hasan Kaan , Sarioğlu Aybüke , Keküllüoğlu Tan Melis , Aydin Sema , Usta Pınar , Okan Bakir Binnur
Published: December 2024

Objective:

To investigate the co-existence of single and multiple anthropometric failures among children using an extended composite index of anthropometric failure (ECIAF). This study aims to elucidate the complex interplay between child-specific and maternal factors, highlighting the multifaceted nature of childhood malnutrition.

Design:

A multicentre cross-sectional study as part of the BESLEN project

Setting:

Mother-Child Education Centre in the Pendik district of Istanbul, Türkiye

Participants:

1283 children (preschool children, n 822, school-aged children, n 462) and 1044 mothers

Results:

Almost 1/3 of the children included in the study had an anthropometric failure as determined by ECIAF. Weight excess was the leading cause of the total anthropometric failures, most of which were observed to be slightly higher in boys, except for stunting only and co-occurrence of stunting and underweight. Among the mother-related factors, including higher BMI and waist circumference, low maternal age at delivery, low number of children in the household and being a single parent may be considered predisposing factors to any phenomenon of childhood malnutrition. Among child-related factors, birth weight being ≥ 3500 g had a higher risk for ECIAF failure, and children aged ≥ 60 months were more likely to experience stunting and underweight, while those < 60 months had a higher prevalence of weight excess.

Conclusions:

The co-existence of stunting and overweight, the occurrence of weight excess in one in three stunted children and the high risk of central obesity are public health concerns. Also, ECIAF can better assess all aspects of childhood malnutrition than conventional measures.
Ex-situ evaluation of curry leaf (Murraya koenigii (L.) Spreng) germplasm to unravel the genetic diversity of leaf essential oils
Authors: Raghu Borehalli Rangaswamy , Shivashankara Kodthalu Seetharamaiah , Mahadappa Priyanka , Lokesha Ankanahalli Narayanashetty , Nandini Kebbahalli Shivashankarappa , Rao Vala Keshava , Prasanna H.C. , Dutta Sudip Kumar
Published: December 2024

The present study was conducted with the objective of studying the genetic diversity of essential oils (EOs) in curry leaf (CL) ex-situ. Chemometric methods and pattern analysis were employed to assess the genetic diversity of EOs and to characterise diverse sets of CL germplasm into different chemotypes. The study revealed a huge genetic diversity for EO yield and its composition among the tested genotypes. Cultivated types had significantly higher EO yields and showed a greater degree of genetic divergence compared to wild types. In total, 80 different compounds were identified in the EOs of CL and classified into major (6) and minor (74) compounds. The major compounds α-pinene, γ-terpinene, and α-selinene and 14 minor compounds were highly variable among the tested genotypes. They may play an important role in the formation of different chemotypes. Other important compounds, such as trans-caryophyllene and α-humulene, were more widely distributed among the tested genotypes and indicated their predominant occurrence in the EOs of CL. Some major compounds, such as valencene and γ-terpinene, showed a significant regional correlation, indicating the role of geographic factors in the evolution of different chemotypes. Furthermore, some compounds such as α-pinene, bornyl acetate, and camphene had significantly higher concentrations in wild types compared to cultivated types, indicating the influence of domestication through human selection on the composition of EOs in CL. A total of 4 major chemotypes were characterised, of which three new chemotypes are being reported for the first time in CL.
Effect of fall-planted cover crops on weed suppression, grain sorghum yield, and profitability in the semi-arid Central Great Plains
Authors: Dhanda Sachin , Kumar Vipan , Dille J. Anita , Obour Augustine , Yeager Elizabeth A. , Holman Johnathan
Published: December 2024

Integrating cover crops (CC) in dryland crop rotations could help in controlling herbicide-resistant weeds. Field experiments were conducted at Kansas State University Agricultural Research Center near Hays, KS from 2020-2023 to determine the effect of fall-planted CC on weed suppression in grain sorghum, crop yield, and net returns in no-till dryland winter wheat (Triticum aestivum L.)-grain sorghum [Sorghum bicolor (L.) Moench]-fallow (W-S-F) rotation. The field site had a natural seedbank of glyphosate-resistant (GR) kochia [Bassia scoparia (L.) A. J. Scott] and Palmer amaranth (Amaranthus palmeri S. Watson). A CC mixture (triticale/winter peas/radish/rapeseed) was planted after wheat harvest and terminated at triticale heading stage before sorghum planting. Treatments included nontreated control, chemical fallow, CC terminated with glyphosate (GLY), and CC terminated with GLY+ acetochlor/atrazine (ACR/ATZ). Across three years, CC terminated with GLY+ACR/ATZ reduced total weed density by 34-81% and total weed biomass by 45-73% compared to chemical fallow during the sorghum growing season. Average grain sorghum yield was 786 to 1432 kg ha-1 and did not differ between chemical fallow and CC terminated with GLY+ACR/ATZ. However, net returns were lower with both CC treatments (USD -$275 to $66) in all three years compared to chemical fallow (USD -$111 to $120). These results suggest that fallow replacement with fall-planted CC in the W-S-F rotation can help suppress GR B. scoparia and A. palmeri in the subsequent grain sorghum. However, the cost of integrating CC exceeded the benefits of improved weed control and lower net returns were recorded in all three years compared to chemical fallow.
Adopting Older Children
Authors: Bejenaru Anca
Published: December 2024

Abstract: Introduction: In the last 7 years, against the backdrop of policy changes in the field of child adoption, an increasing number of Romanians have adopted children over 5 years old. Aim: The present study explores how women transition to motherhood when adopting older children. I focus on their experiences, the demands they face, their coping strategies, and the resources available to them. Methods: We interviewed 19 adoptive mothers using a narrative interview and analyzed the data thematically, resulting in three main themes and eight subthemes. Results: Many demands arose from the older children’s behaviors and attitudes and their challenges in forming new bonds and adjusting to the adoptive family system. These demands were felt by mothers as overwhelming, leading to fatigue, uncertainty, and sometimes anxiety. Most mothers relied on informal support, as formal resources in the private system proved costly, with few free options from the state. Conclusion: The study presents recommendations for policymakers and practitioners to adequately prepare parents for the adoption process and the development of support services for the postadoption period.
Retrieval of Cloud Macro‐Physical Properties Using theFY‐4A Advanced Geostationary Radiation Imager (AGRI) and the Geostationary Interferometric Infrared Sounder (GIIRS)
Authors: Guo Bin , Zhang Feng , Zhao Zhijun , Guo Jinyu , Li Wenwen
Published: December 2024

This study presents a novel approach for conducting all‐day retrieval of cloud macro‐physical properties (single‐layer cloud phase, cloud top height, and cloud base height for optical thickness less than 10) using the Advanced Geostationary Radiation Imager (AGRI) and the Geostationary Interferometric Infrared Sounder (GIIRS) onboard the geostationary meteorological satellite Fengyun‐4A based on machine learning methods. Model accuracy was compared after integrating ECMWF Reanalysis v5 (ERA‐5) data, atmospheric temperature and moisture profiles, and GIIRS clear‐column radiance. Results demonstrate that integrating GIIRS clear‐column radiances can enhance the precision of cloud phase classification and the retrieval of cloud macro‐physical properties. This effectively replaces the role of atmospheric temperature and humidity profiles, which are typically required for thermal infrared remote sensing retrieval. Moreover, the issue of delayed acquisition of ERA‐5 atmospheric temperature and humidity profiles is mitigated, enabling near real‐time and all‐day retrieval of cloud macro‐physical properties.
Seismoelectric Conversion at Poroelastic/Elastic Interfaces and the Role of Dielectric Permittivity: Experimental and Numerical Analysis
Authors: Bernardo Natael , Martins‐Gomes Victor , Bordes Clarisse , Brito Daniel
Published: December 2024

Seismoelectric phenomena, caused by electrokinetic coupling between seismic and electromagnetic fields, have attracted significant interest in geological reservoir characterization for their sensitivity to pore‐fluid contrasts. Consequently, most studies have focused on seismic‐to‐electromagnetic conversions at fluid/poroelastic and poroelastic/poroelastic interfaces. However, when investigating permeable zones in unfractured media, often associated with geothermal reservoirs, poroelastic/elastic interfaces must be considered. To address this, we conducted laboratory and numerical experiments using a container filled with quartz sand saturated with a NaCl solution, with one of five thin layers made of different materials (four elastic and one poroelastic) embedded within the sand. Our numerical simulations assume an elastic medium as poroelastic using limiting values for certain physical parameters. The results confirm that seismoelectric conversion occurs at poroelastic/elastic transitions, showing a strong agreement between experiments and simulations. Furthermore, we inferred that the amplitudes of electromagnetic waves generated at poroelastic/elastic interfaces are mainly controlled by contrasts of dielectric permittivity.
AqUavplant Dataset: A High-Resolution Aquatic Plant Classification and Segmentation Image Dataset Using UAV
Authors: Istiak Md. Abrar , Khan Razib Hayat , Rony Jahid Hasan , Syeed M. M. Mahbubul , Ashrafuzzaman M. , Karim Md. Rajaul , Hossain Md Shakhawat , Uddin Mohammad Faisal
Published: December 2024

Aquatic vegetation species are declining gradually, posing a threat to the stability of aquatic ecosystems. The decline can be controlled with proper monitoring and mapping of the species for effective conservation and management. The Unmanned Ariel Vehicle (UAV) aka Drone can be deployed to comprehensively capture large area of water bodies for effective mapping and monitoring. This study developed the AqUavplant dataset consisting of 197 high resolution (3840px  × 2160px, 4K) images of 31 aquatic plant species collected from nine different sites in Bangladesh. The DJI Mavic 3 Pro triple-camera professional drone is used with a ground sampling distance (GSD) value of 0.04-0.05 cm/px for optimal image collection without losing detail. The dataset is complemented with binary and multiclass semantic segmentation mask to facilitate ML based model development for automatic plant mapping. The dataset can be used to detect the diversity of indigenous and invasive species, monitor plant growth and diseases, measure the growth ratio to preserve biodiversity, and prevent extinction.
Feasibility test of per-flight contrail avoidance in commercial aviation
Authors: Sonabend-W Aaron , Elkin Carl , Dean Thomas , Dudley John , Ali Noman , Blickstein Jill , Brand Erica , Broshears Brian , Chen Sixing , Engberg Zebediah , Galyen Mark , Geraedts Scott , Goyal Nita , Grenham Rebecca , Hager Ulrike , Hecker Deborah , Jany Marco , McCloskey Kevin , Ng Joe , Norris Brian , Opel Frank , Rothenberg Juliet , Sankar Tharun , Sanekommu Dinesh , Sarna Aaron , Schütt Ole , Shapiro Marc , Soh Rachel , Van Arsdale Christopher , Platt John C.
Published: December 2024

Contrails, formed by aircraft engines, are a major component of aviation’s impact on anthropogenic climate change. Contrail avoidance is a potential option to mitigate this warming effect, however, uncertainties surrounding operational constraints and accurate formation prediction make it unclear whether it is feasible. Here we address this gap with a feasibility test through a randomized controlled trial of contrail avoidance in commercial aviation at the per-flight level. Predictions for regions prone to contrail formation came from a physics-based simulation model and a machine learning model. Participating pilots made altitude adjustments based on contrail formation predictions for flights assigned to the treatment group. Using satellite-based imagery we observed 64% fewer contrails in these flights relative to the control group flights, a statistically significant reduction (p = 0.0331). Our targeted per-flight intervention allowed the airline to track their expected vs actual fuel usage, we found that there is a 2% increase in fuel per adjusted flight. This study demonstrates that per-flight detectable contrail avoidance is feasible in commercial aviation.
Atomistic modeling of large biological systems and the need for (un-)realistic approaches
Authors: Götze Jan P.
Published: December 2024

In this chapter, the benefits of hybrid quantum mechanics/molecular mechanics (QM/MM) approaches are critically compared to QM-only cluster models. Hybrid models can include the immediate bonded situation near the QM/MM boundary, as well as the vast number of long-range interactions of the real system. They thus promise to be more realistic than cluster models. However, most contemporary QM/MM models include a classical molecular dynamics (MD) protocol beforehand, providing a structural ensemble. This results in several arguments for and against the use of either approach, although not directly arising from “QM/MM vs. cluster”. It is found that, counter-intuitively, QM/MM models include setup-related advantages that make them easier to build, making them more convenient for a modeler compared to clusters. Concerning the scientific necessity of including the full system, QM/MM studies often omit the (actually trivial) option to check for the relevance of the environment. Such tests would however provide (a) an overview for which problems cluster approaches may suffice and (b) possibly more insights than available from the QM/MM calculations alone. It is proposed here that the easiest and most cost-effective improvement of a QM/MM protocol is the a posteriori deactivation of the coulombic environment (i.e., the point charge field) and comparing the results from the two sets of simulations. This would give a direct measure for experimentalists on the potential for, e.g., influencing a reaction via changes of individual amino acids. The results would be more meaningful and, by means of error cancellation, more justified, although at the cost of including “unrealistic” gas phase models in the study.
Quantitative Microscopy of Active Colloids
Authors: Cerbino Roberto , Giavazzi Fabio
Published: December 2024

This chapter presents an introduction to microscopy techniques and methodologies that are applicable for the study of active colloidal systems. It begins with a primer of optical imaging, to further describe quantitative and statistical analysis methods, providing insights into the individual and collective dynamics of active colloids. A modern dual perspective, examining both direct and reciprocal space analyses, is offered.
Introduction to Active Colloids
Authors: Sapre Aditya , Sen Ayusman , Ghosh Ambarish
Published: December 2024

This chapter provides an overview of the entire research field of active colloids ranging from molecules to microparticles, spanning their types, propulsion mechanisms, collective behavior, applications, and key research frontiers. The goal is to give readers a general understanding of this research field and its important concepts.
Self-propelling Droplets
Authors: Maass C. C. , Michelin S. , Zarzar L. D.
Published: December 2024

Self-propelled droplets provide a very simple and accessible realization of active colloids. To achieve spontaneous and self-sustained propulsion, they only require a generic chemical reaction or molecular transport at an emulsion interface that is susceptible to a chemohydrodynamic instability based on the advection of chemical species by self-induced interfacial flows. In contrast to most solid phoretic colloids, they do not require a pre-engineered front-back asymmetry to function. In this chapter we cover the foundational chemical and engineering aspects on how to produce simple and complex active emulsions, discuss the theoretical foundations of their modeling and the current experimental and numerical evidence of their complex dynamics, as well as their motility under a number of experimental parameters and boundary conditions.
Active Colloids in Complex Environments
Authors: Ketzetzi Stefania , Simmchen Juliane , Isa Lucio
Published: December 2024

This chapter provides an overview of the effects of complex environments on active colloids. We start with solid boundaries and confining structures, highlight interactions with colloids and other “softer” passive objects, and show parallels with behaviours observed when particles move close to – or directly at – interfaces. In the second half, we address complex environments with unbound domains, in particular, velocity-modulating environments and the effect of local gradients.
Applications of Active Colloids
Authors: Katuri J. , Sanchez S.
Published: December 2024

Alongside the rapid progress made in the development and understanding of new active colloidal systems over the last two decades, several applications have also been developed for these particles in a range of different areas. The unique properties of active colloids – self-propulsion, ability to respond to environmental cues, collective behaviour, and the ease of functionalizing particle surfaces – have led to applications in self-assembly, materials design, sensing, therapeutics, and environmental remediation. In this chapter we will build on the previous discussions on propulsion, control, and interactions of active colloidal systems and offer insight into what general strategies and approaches are best suited for different application areas. While we do not attempt to provide a comprehensive review of the thousands of applications that have been developed for active colloidal systems, we will provide illustrative examples that aim to highlight the state of the art in application development with active colloids.
Active Matter and Artificial Intelligence
Authors: Volpe Giorgio , Cichos Frank , Volpe Giovanni
Published: December 2024

In this chapter, we explore the intersection of active matter and artificial intelligence (AI), providing a brief overview of machine learning principles and their application in understanding and manipulating active matter. We discuss both opportunities and challenges that AI methodologies present in the data acquisition and analysis as well as in the data-driven modelling of active colloids. We then highlight the role of AI in enhancing navigation and search strategies of active colloids, and in understanding their collective dynamics, offering insights into the algorithms that guide these processes. We conclude by addressing the ethical implications and safety guidelines necessary for the responsible use of AI in this field. With this chapter, we aim to equip readers with a thorough understanding of the current state and potential advancements in employing AI to unravel the complexities of active colloids, making it a valuable resource for researchers and enthusiasts alike.
Harnessing Both Light and Dark Conditions for Photocatalytic Hydrogen Production: Pathway for Ultimate Green Hydrogen
Authors: Mann Rohit , Khushalani Deepa
Published: December 2024

Hydrogen production methods span from carbon-intensive grey variants to cleaner blue and turquoise, with green variants being the most environmentally friendly. However, green hydrogen faces challenges due to the intermittent nature of solar energy and low efficiency. Photocatalysis, particularly using semiconductors, provides a promising paradigm shift for hydrogen production, by splitting water into hydrogen and oxygen when exposed to light, and offering a genuinely green and sustainable approach. Ionic carbon nitride, a semiconductor catalyst, demonstrates remarkable efficiency in hydrogen production, and in this chapter we present not only its ability to efficiently split seawater, but also showcase its unique ability for dark photocatalysis, generating hydrogen even without light. Understanding the structure–property relationships of carbon nitride can further enhance its potential for sustainable hydrogen production and revolutionize the energy landscape.
Advances in Metal–Organic Frameworks for Electrocatalytic Hydrogen Generation
Authors: Nagappan Sreenivasan , Kundu Subrata
Published: December 2024

Hydrogen is regarded as a vital resource for the advancement of renewable energy technologies. Electrocatalytic water splitting has emerged as a viable technique for producing ultra-pure hydrogen. The electrocatalyst, which can catalyze the electrochemical process to decrease the overpotential by increasing the current density, is critical to the effectiveness of this approach. Metal–organic frameworks (MOFs) have become recognized as possible electrocatalysts in recent years due to their exposed surface active sites, evenly distributed interconnected pore structure, and adjustable shape. Thus, the significance of homogeneous and heterogeneous MOFs and their derivatives for the electrocatalytic hydrogen evolution process (HER) is summarized in this chapter. The chapter begins with an overview of the fundamentals of the electrocatalytic HER, after which the importance of various transition metal-based pristine MOFs and their derivatives towards the HER is examined. However, there is still plenty of room for improvement given their sub-par intrinsic activity and weak conductivity. Various MOF-derived composites, as well as new methodologies and procedures, are given to solve intrinsic activity and conductivity issues, emphasizing progress in MOF-based materials for a more effective HER electrocatalyst in large-scale hydrogen production.
Introduction to Photoelectrocatalytic Hydrogen Production
Authors: Sharma Surbhi , Atul  , Sharma Kartik
Published: December 2024

The current energy issues that have arisen due to climate change require us to focus our efforts on fresh alternatives to fossil fuels. In this context, it is vital to take into consideration efficient catalytic methods to produce hydrogen from renewable sources, as a clean fuel. Photoelectrochemical H2 production is one of the most promising technologies, which could potentially provide a clean, cost-effective, and domestically produced energy carrier, by taking advantage of the maximum radiation that continually strikes the Earth’s surface. The use of longer wavelength photons for H2 production, raising reaction efficiency at any given wavelength, and extending the lifetime of semiconductor materials are just a few of the issues that need to be resolved in order to increase energy conversion efficiency for H2 production. Despite these obstacles, there are viable options for reaching the crucial objective of producing photoelectrochemical H2 effectively and economically. Although the same types of semiconductor are used, typical factors affecting the performance in photoelectrochemical systems are also encountered. For rational design of high-performing photoactive materials—which may also act as a general guideline for the creation of good photocatalysts or photoelectrodes towards the production of sustainable solar fuel—it is essential to understand the underlying mechanisms in relation to their photoactivities. This chapter sheds some light on photoelectrochemical H2 production, the function of semiconductors, cocatalysts, and the band gap, and discusses some of its applications.
Microplastic Detection and Quantification with Biosensing Techniques
Authors: Islam Santa , Abu Nayem S. M. , Awal Abdul , Aziz Md. Abdul , Saleh Ahammad A. J.
Published: December 2024

Microplastics (MPs), particles ranging from 1 μm to 5 mm, have risen to prominence as significant pollutants on a global scale, driven by the widespread use of plastics in our daily lives. Their ability to transition from the micro- to the nanoscale (less than 1 μm) allows them to permeate every corner of the natural world, leading to ecological imbalances and global crises. Despite their pervasive presence, the absence of a standardized method for effectively separating and analyzing microplastics in real food or environmental samples remains a critical challenge. Consequently, there is a pressing need to devise a simple, rapid, cost-effective, and accurate method, capable of precisely gauging the degree of MP contamination. Conventional detection methods have several limitations in the detection of microplastics, as they are not always efficient in terms of cost, speed, on-site capabilities, or real-time analysis. In this particular context, biosensors have demonstrated remarkable efficacy in enabling accurate, on-site, and real-time detection of MPs. This chapter covers basic topics with an emphasis on the detection and measurement of MPs utilizing biosensing technology.
Electroanalysis of Vitamins Using Carbon Sensors
Authors: Beitollahi Hadi , Dourandish Zahra , Zaimbashi Reza , Tajik Somayeh
Published: December 2024

Vitamins are a group of organic compounds that play a crucial role in the proper functioning of living organisms. While some vitamins are synthesized within living organisms, others must be acquired through the diet to fulfill the needs of the organism, hence classifying them as essential compounds. Insufficient levels or deficiencies of vitamins in the human body can lead to the onset of metabolic disorders. Therefore, it is essential to ensure adequate daily intake of vitamins through diet or supplements and to regularly monitor their levels. It is widely recognized that nearly all vitamins exhibit electrochemical activity. By leveraging the electrochemical reduction or oxidation of vitamins in an electrolyte, electrochemical sensors can determine the concentration of vitamins through current measurement at the working electrode. An emerging trend in the development of electrochemical sensors is the integration of carbon-based nanomaterials, such as graphene and its derivatives, carbon nanotubes (CNTs), and graphitic carbon nitride (GCN or g-C3N4), with working electrodes. Carbon nanomaterials exhibit significant potential in electrochemical sensing technology owing to their distinctive electrical, thermal, optical, chemical, and mechanical characteristics. This chapter reviews research advancements from the past decade in carbon nanomaterial-based electrochemical sensors for detecting both water- and fat-soluble vitamins. Additionally, the chapter addresses the challenges and future prospects associated with carbon nanomaterial-based electrochemical sensors in this field.
Detection of Toxins in Food by Biosensors
Authors: Sadak Selenay , Silah Hülya , Uslu Bengi
Published: December 2024

Foods are the only source of energy and nutrients for humans. Toxin-producing microorganisms can exist in foods, and partially or entirely destroy the nutritional quality of foods. Food toxins are universally a major health topic, causing foodborne diseases that severely impact humans. So, utilizing scientific technologies to determine toxins in food is important to prevent food safety problems and protect human health. Sensor systems present high selectivity, sensitivity, and ability to analyze complicated samples, making them ideal analytical methods for the qualification and quantification of food toxins. Recent nanotechnological improvements have greatly increased sensitivity, making possible the monitoring of food toxins at ultralow levels. In this chapter, various electrochemical sensor systems described in the literature for the determination of several food toxins are summarized, highlighting their advantages, restrictions, and applications in terms of sensitivity, simplicity, detection limit, and linearity range.
Detection of Psychotomimetic Drugs in Beverages and Food
Authors: Gopavaram Sumanth , Chandrashekharappa Sandeep
Published: December 2024

The food and beverage industry requires efficient and cost-effective techniques to ensure product quality and process control, as the application of analytical methods, such as high-performance liquid chromatography (HPLC) or enzymatic procedures, can be expensive or time-consuming. The presence of drug residues in beverages and foods has become a growing concern due to adverse health risks and regulatory implications. There is a strong need for the rapid and sensitive detection of psychotomimetic drugs in foods and beverages with high specificity. Various approaches have been developed, such as electrophoresis, biosensors, and immunoassay methods. The use of biosensor technology in the domain of beverages and foods shows significant potential. The key application of biosensors has attained significant importance in the fields of drug innovation, drug identification, bioremediation, food protection principles, security, protection, and ecological examination. In this chapter, we discuss the biosensor applications in psychotomimetic drug detection in beverages and foods.
Combining digital imaging and quantum dots for analytical purposes
Authors: de Almeida João Paulo B. , dos Santos Thomas Fernando Ferreira Tributino , Sabino Júnior José Roberto , do Amaral Elias Vinicius Ferreira , Oliveira Claudinéia R. S. , Maia Matheus V. , T. Suarez Willian , Ayres Lucas B. , Garcia Carlos D. , dos Santos Vagner B.
Published: December 2024

This review provides a critical assessment of the most recent advances in digital imaging (DI) methods, applied for the development of analytical methodologies combining quantum dots (QDs).
Luminescent terbium(iii) probes containing an aromatic amino acid-based antenna for discrimination between adenine and guanine nucleotides
Authors: Pradhan Sunanda , Shukla Nitin , Panigrahi Goutam , Patra Ashis K.
Published: December 2024

Luminescent Tb(iii)-probes for sensitive sensing and discrimination of purine nucleotides using the PeT mechanism via π–π stacking interactions under physiological conditions.
Solvents and their hydrogen bonding properties as general considerations in carbon dioxide reduction by molecular catalysts
Authors: Li Xiaohan , Warren Jeffrey J.
Published: December 2024

Solvent hydrogen bonding properties exert a strong influence on electrocatalytic carbon dioxide reduction by molecular electrocatalysts.
Quinoa is more effective than other whole grains in the management of impaired glucose tolerance: a randomized controlled trial
Authors: Huang Lu , Li Xiaoli , Zou Mingxi , Zeng Hongli , Wu Shixin , Liang Yuchan , Wang Dongjiang , Yang Yan , Qiu Zhenyang , Zhou Quan
Published: December 2024

Quinoa supplementation in individuals with impaired glucose tolerance improves glycemic control, boosts metabolic health, lowers T2DM risk, and aids glycemic normalization, highlighting its potential as a dietary approach for diabetes prevention.
Morphology controlled Cu3BiS3 nanostructures: superior electrocatalytic sensing of organic nitro compounds
Authors: Pandit Manzoor Ahmad , Hemanth Kumar Dasari Sai , Varkolu Mohan , Muralidharan Krishnamurthi
Published: December 2024

Addressing the pressing need to develop affordable and efficient catalysts is essential.
Zn-crosslinking of copolymer-bearing imidazole pendants to form polymeric nanoparticles for pH-sensitive drug delivery
Authors: Yang Wenjing , Zhang Mengna , Zhao Xubo
Published: December 2024

Polymers can be assembled into nanomaterials with different structures.
Macrocycle- and metal-centered reduction of cobalt trithiadodecaazahexaphyrin (Hhp). Metal-to-ligand charge transfer in {(CoI2CoIIO)(Hhp˙4−)}2−
Authors: Nazarov Dmitry I. , Kuzmin Alexey V. , Islyaikin Mikhail K. , Ivanov Evgenii N. , Shestakov Alexander F. , Faraonov Maxim A. , Khasanov Salavat S. , Otsuka Akihiro , Yamochi Hideki , Kitagawa Hiroshi , Konarev Dmitri V.
Published: December 2024

Crystals of {Cryptand(K+)}2{(CoI2CoIIO)2+(Hhp˙4−)}2−·2C6H4Cl2 (1) were obtained from H3Hhp and CoII(acac)2 under reduction. Salt 1 demonstrates a metal-to-macrocycle charge transfer and low-energy d–π optical transition.
Degradation of organic pollutants on NiFe2O4/PANI/rGO nanocomposites by peroxymonosulfate activation technology
Authors: Cheng Yuanyuan , Zhang Ziyang , Hong Yimiao , Li Xinyang , Song Hangyuan , Zhang Yuxi
Published: December 2024

With the increasing environmental pollution, especially water pollution, it is urgent to develop environmentally friendly, low-consumption, and efficient water treatment technology.
Recent breakthroughs in non-conjugated polymers for thermally activated delayed fluorescent OLEDs: emitters, hosts, and hole-transport materials
Authors: Bommireddy Purusottam Reddy , Mameda Naresh , Musalikunta Chandra Sekhar , Lee Young-Woong , Suh Youngsuk , Godumala Mallesham , Park Si-Hyun
Published: December 2024

Non-conjugated linkers interrupt direct conjugation in the polymer backbone, providing enhanced solubility, blue TADF emitters, and high triplet energy host and hole transport materials.
A persistent concealed non-Kekulé nanographene: synthesis and in situ characterization
Authors: Imran Muhammad , Yang Lin , Zhang Jin-Jiang , Qiu Zhen-Lin , Fu Yubin , Israel Noel , Dmitrieva Evgenia , Lucotti Andrea , Serra Gianluca , Tommasini Matteo , Ma Ji , Feng Xinliang
Published: December 2024

A persistent concealed non-Kekulé nanographene featuring two phenalene units fused in a cis configuration to a perylene core was successfully synthesized in solution and characterized.
Towards flexible large-scale, environmentally sustainable methanol and ammonia co-production using industrial symbiosis
Authors: Magson Joshua , Lee Chan Thérèse G. , Mohammed Akeem , Ward Keeran
Published: December 2024

Uncovering pathways to sustainable co-production schemes using industrial symbiosis.
Calix[4]arene@MIL-101 as host@MOF for cage-in-cage pore space partitioning for enhanced CO2 separation and catalysis
Authors: Navid Saied Shafiei , Hosseinzadeh Rahman , Oestreich Robert , Abdpour Soheil , Beglau Thi Hai Yen , Janiak Christoph
Published: December 2024

para-Sulfonated calix[4]arene, a bowl-shaped macrocycle possessing intrinsic porosity, was incorporated into the voids of the MIL-101(Cr) metal–organic framework by adsorptive loading from a solution.
Tuning of the ionic conductivity of Ba7Nb4MoO20 by pressure: a neutron diffraction and atomistic modelling study
Authors: Watson V. , Zhou Y. , Tawse D. N. , Ballantyne O. J. , Ridley C. J. , Dawson J. A. , Mclaughlin A. C.
Published: December 2024

Pressure is used to tune the crystal structure and the ionic conductivity of the dual ion conductor Ba7Nb4MoO20. Increasing pressure results in a reduction in the fraction of MO4 tetrahedra within the P–L layer and a decrease in oxide-ion transport.
Bottom-up reconstitution design of a biomimetic atelocollagen microfibril for enhancing hemostatic, antibacterial, and biodegradable benefits
Authors: Zhang Xiaoxia , Cai Lin , Li Guoying
Published: December 2024

A biomimetic atelocollagen microfibril integrates straightforward preparation, efficient hemostasis, infection prevention, fast biodegradability, and a low immune response, demonstrating significant potential for clinical translation and application.
Exploring the triplet-to-singlet conversion mechanism in persistent luminescence: insights from a host–guest system
Authors: Bueno Fernando Teixeira , de Sousa Araújo Cassiano Tiago , de Silva Piotr , de Oliveira Neto Pedro Henrique , de Sousa Leonardo Evaristo
Published: December 2024

Triplet-to-singlet energy transfer from NPB to DCJTB enables fluorescence-derived luminescence on a tenths-of-a-second timescale, driven by NPB's efficient dual emission and low non-radiative triplet decay rate.