bluuebunny/crossref_metadata_2025 huggingface dataset:
Radiative cooling performance of a modified paint formulation with an integrated UV and convection shielding layer
Authors: Lio Giuseppe Emanuele , Levorin Sara , Erdogan Atakan , Werlé Jeremy , Corso Alain J. , Schenato Luca , Wiersma Diederik S. , Santagiustina Marco , Pattelli Lorenzo , Pelizzo Maria Guglielmina
Published: August 2024

Passive radiative cooling (PRC) technology promises to reduce a significant fraction of our energy needs and carbon footprint associated with cooling. Among different approaches, paint-like systems present several advantages in cost-effectiveness, scalability, and application ease. We report on a PRC system consisting of a paint mixture modified with 50 %wt glass bubbles and a top polypropylene-polyethylene-polypropylene (PP-PE-PP) film typically used as a battery separator. The resulting material exhibits a solar reflectance of 94 % and an absorption (evaluated by Attenuated Total Reflectance spectroscopy) with a peak at 10 µm of 60 %. The addition of the glass bubbles and the top film increases the paint reflectance over the solar spectrum and the UV, thanks to the nanoporous PP-PE-PP film (NPF), while allowing most thermal radiation through, shielding from convection, and making the coating more easily washable. The material has been tested under realistic outdoor conditions, checking the different performance obtained when sticking the PP-PE-PP film directly onto the wet paint layer or by using it as a separate windshield enclosing the sample test chamber. Despite its high solar reflectance, no radiative cooling is observed with respect to ambient temperature during the peak hours (solar irradiation >500 W m −2). Below this threshold, a temperature drop of −3 °C and a cooling power exceeding 100 W m−2 is observed. Notably, even using a visibly opaque convection shield, the configuration where the PP-PE-PP film seals the sample results in a substantial overheating of the air pocket surrounding the sample , which is detrimental to obtaining a temperature drop with respect to the true ambient temperature.
Research on the properties of creep compaction of crushed gangue in a deep long-wall goaf
Authors: wen peng , Guo Wenbing , Tan Yi , Bai Erhu , Yang WeiQiang
Published: August 2024

One of the typical deep mining areas in China is the West Yu mining area. The majority of the deep mining and hollowing areas in this area face serious challenges in controlling surface subsidence and protecting structures due to the conflict between surface subsidence and tense land use for ground engineering and construction. The long-term performance of the shattered gangue body in the mining hollow area needs to be examined as part of the stability analysis. The creep characteristics and crushing features of the same gradation of sandstone, mudstone, and sandy mudstone of three different kinds of single lithology, as well as sandstone-sandy mudstone and mudstone-sandy mudstone combined lithology of crushed gangue under the side-limit compression conditions, were studied. These findings were based on the engineering geological conditions of the mining airspace area in the certain mining area of a mine in west Henan Province. By using a graded loading test, the creep and compression properties of crushed gangue samples with various single and combined lithologies in the caved zone were evaluated. Additionally, the effects of varying stress levels and intensities on the properties of creep compaction of crushed gangue samples in the caved zone were described. Created a creep-time prediction model for crushed gangue in a deep longwall mining area's caved zone. The study's findings offer theoretical direction for the movement of the mining zone's surface and the underlying gangue layer, as well as for the safe administration of the mining zone.
RETRACTED: Fabrication of cinnamaldehyde-loaded polycaprolactone (PCL) electrospun nanofibers as a potential antibiofilm preventative approach against Escherichia coli
Authors: Alshammari Maryam K , Aodah Alhassan H , Alshehri Abdullah A , Aldossary Ahmad M , Alsudir Samar A , Alkhulaifi Manal M , Farraj Dunia A Al , Khalaf Suhail , Alyamani Essam J , Tawfik Essam A
Published: August 2024

The authors have requested that this preprint be removed from Research Square.
Transgenic T cell therapy targeting the glioblastoma stem cell antigen PTPRZ1 with a vaccine-induced, patient-derived T cell receptor
Authors: Bunse Lukas , Chih Yu-Chan , Dietsch Amelie Christina , Koopmann Philipp , Ma Xiujian , Agardy Dennis Alexander , Zhao Binghao , De Roia Alice , Kourtesakis Alexandros , Kilian Michael , Krämer Christopher , Suwala Abigail K. , Stenzinger Miriam , Bonig Halvard , Blum Agnieszka , Pieńkowski Victor , Aman Kuralay , Becker Jonas P , Feldmann Henrike , Bunse Theresa , Harbottle Richard , Riemer Angelika B. , LIU Hai-Kun , Etminan Nima , Sahm Felix , Ratliff Miriam , Wick Wolfgang , Platten Michael , Green Edward Wilhelm
Published: August 2024

Response to CAR-T cell therapy in glioblastoma (GB) patients is limited, particularly because of the paucity of cell surface immunotherapeutic targets or low antigen sensitivity. Moreover, tonic CAR signaling leads to T cell dysfunction eventually resulting in non-durable responses. T cell receptor-engineered T (TCR-T) cell therapy circumvents the latter limitation by allowing safe and ubiquitous targeting of the GB-derived peptidome. Protein tyrosine phosphatase receptor type Z1 (PTPRZ1), a GB antigen associated with GB cell stemness, was previously targeted in multipeptide vaccination trials. Here, we identify a therapeutic HLA-A*02-restricted PTPRZ1-reactive TCR retrieved from a vaccinated GB patient. Single-cell sequencing of primary brain tumor samples showed PTPRZ1 overexpression exclusively in malignant cells and most pronounced in GB stem cells and astrocyte (AC)- or oligodendrocyte-progenitor (OPC)-like cells. The validated vaccine-induced TCR recognized the endogenously processed antigen without cross-reactivity to in silico predicted low-risk off-targets. PTPRZ1-specific TCR-engineered human primary T cells (PTPRZ1-TCR-T) killed target cells antigen-specifically. Intravenous adoptive cell transfer against experimental brain tumors alone was not efficacious, but the addition of intracerebroventricular administration of PTPRZ1-TCR-T resulted in potent tumor rejection. PTPRZ1-TCR-T maintained stem cell memory phenotype in vitro and in vivo. PTPRZ1-TCR-T lysed all examined HLA-A*02+ primary GB cell lines with a preference for slow-cycling GB stem cells (GSCs) and AC-like cells. To further develop PTPRZ1-TCR-T as off-the-shelf therapy for HLA-A*02 GB patients, a phase I first-in-human clinical trial INVENT4GB is in preparation.
Climate change may lead to the inability of millions of people to afford a healthy diet
Authors: Li Bengang , Jiang Yongye , Fu Bo , Ciais Philippe , Suo Xinhao , Chen Guolong , Lai Yuqin , Shen Guofeng
Published: August 2024

The Food and Agriculture Organization (FAO) of the United Nations has called for the food system worldwide to shift from 'feeding people' to 'nourishing people', with the aim of improving the affordability of a diverse diet to better meet health needs. Achieving this goal requires reducing poverty and advancing agricultural development. However, climate change negatively impacts agricultural yields and food prices, diminishing these efforts. The extent to which climate change affects the affordability of healthy diets and their regional variations remains unclear. In this study, the impact of climate change on the affordability of healthy diets under different scenarios was assessed by coupling a climate-crop yield model with integrated assessment model GCAM7. We found that under the high-emission scenario (SSP5-unconstrained), the impacts of climate change, including global crop yield reductions and consequent increases in food prices, lead to an additional 70 million people globally will be unable to afford healthy diets by the end of the century, despite significant economic growth. Under the low-emission scenario SSP1-2.6, the impact on the food system is less than one-tenth that under SSP5-unconstrained. In all scenarios, developing regions are significantly more affected than wealthier regions, despite contributing less to climate change. In addressing climate change, we must acknowledge the varying vulnerabilities in affordability across different regions and populations. Effective mitigation measures are essential to ensure that everyone, regardless of their location, can access a healthy diet.
CIDER: Counterfactual-Invariant Diffusion-based GNN Explainer for Causal Subgraph Inference
Authors: zhang qibin , LYU Chengshang , Chen Lingxi , Jin Qiqi , Luonan Chen
Published: August 2024

Inferring causal links or subgraphs corresponding to a specific phenotype or label based solely on measured data is an important yet challenging task, which is also different from inferring causal nodes. While Graph Neural Network (GNN) Explainers have shown potential in subgraph identification, existing methods with GNN often offer associative rather than causal insights. This lack of transparency and explainability hinders our understanding of their results and also underlying mechanisms. To address this issue, we propose a novel method of causal link/subgraph inference, called CIDER: Counterfactual-Invariant Diffusion-based GNN ExplaineR, by implementing both counterfactual and diffusion implementations. In other words, it is a model-agnostic and task-agnostic framework for generating causal explanations based on a counterfactual-invariant and diffusion process, which provides not only causal subgraphs due to counterfactual implementation but reliable causal links due to the diffusion process. Specifically, CIDER is first formulated as an inference task that generatively provides the two distributions of one causal subgraph and another spurious subgraph. Then, to enhance the reliability, we further model the CIDER framework as a diffusion process. Thus, using the causal subgraph distribution, we can explicitly quantify the contribution of each subgraph to a phenotype/label in a counterfactual manner, representing each subgraph’s causal strength. From a causality perspective, CIDER is an interventional causal method, different from traditional association studies or observational causal approaches, and can also reduce the effects of unobserved confounders. We evaluate CIDER on both synthetic and real-world datasets, which all demonstrate the superiority of CIDER over state-of-the-art methods.
The transcription factor Bcl11a is essential for functional B-1a cell maintenance during aging
Authors: Yu Yong , Xu Shasha , Huang Liangfeng , Zhang Lin , Wang Jing , Hu Yi , Yang Yi , Shi Xiao , Liu Chaohong , Wang Rong , Miao Zhichao
Published: August 2024

B-1a cells, key natural IgM producers, are established during fetal and neonatal stages and maintained through self-renewal in adulthood. Essential for initial immune responses, these cells experience a functional decline and clonal expansion as they age, a process not yet fully understood. Our study identifies the transcription factor Bcl11a as crucial for maintaining B-1a cell numbers, showing variable expression between aged male and female mice. Enhanced Bcl11a expression in females correlates with increased B-1a cell counts, whereas its reduction in males leads to fewer cells. Deleting Bcl11a markedly reduces B-1a cell numbers across both sexes and all ages, highlighting its essential role in cell maintenance. Bcl11a's loss upregulates FcγRIV (Fcgr4), facilitating NK cell-mediated antibody-dependent cellular cytotoxicity (ADCC). By repressing Fcgr4 directly and indirectly through Fcer1g, Bcl11a protects B-1a cells from ADCC, thus preserving their viability. This discovery emphasizes the potential of modulating Bcl11a expression to boost immune function in the elderly, underscoring its importance in immune surveillance and cellular integrity.
Five Thousand Years of Inequality in the Carpathian Basin
Authors: Duffy Paul R. , Wilkes Fynn , Skorna Henry , Furholt Martin , Dickie Cait , Furholt Kata , Bilotti Giacomo , Müller Johannes , Feinman Gary M.
Published: August 2024

The emergence of sedentary farming economies, especially in contexts intensified by plow agriculture, has been argued to underpin marked increases in economic inequality and its intergenerational transmission across Eurasia. To assess this presumed causal relationship, we examine relational (burials) and material (house sizes) inequalities in the Carpathian Basin, a large region in central Europe, from the time the first farmers arrived in southeastern Europe through the next five millennia to the Bronze Age. We find that although farming did increase the potentials for both relational and material inequalities that potential was rarely reached, and then only for short durations. A series of leveling mechanisms, which shifted over time, are identified including the removal of material wealth from circulation, community fission, and investments of surplus labor in infrastructural investments. In the Carpathian Basin, only after at least five thousand years were the intergenerational potentials of material wealth transmissions more broadly realized.
Best Practices and Training Needs Related to Interactions With Family Members During Neonatal Resuscitation Procedures: A Scoping Review Protocol
Authors: HERVIEUX Coralie , MOUSSA Ahmed , LOYE Nathalie , BOURQUE Claude Julie
Published: August 2024

Background: Family presence during a resuscitation (FPDR) in neonatology is unevenly accepted by healthcare professionals (HCPs). To develop innovative educational materials for resuscitation teams in the neonatal intensive care units (NICUs), evidence-based information is needed on constructive interactions with family members during the procedures. This protocol is for a scoping review that aims to identify the best practices regarding support and interactions of HCPs with family members during neonatal resuscitation in the NICU and to propose recommendations for developing a targeted in-situ simulation training. The review willfocus on HCPs’ perception of FPDR in terms of interpersonal skills, reluctance and need for interactional training.
Methods and analysis: In 2021, Dainty and collaborators published a systematic review on FPDR (pediatric and neonatal) that focused on the impact on the patients as well as family-centered and HCP centred outcomes. From their literature strategic search, we will extrapolate and narrow down the search to “neonatology” and add relevant recent studies. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Review (PRISMA-ScR) model will guide the literature search on four electronic databases (ScienceDirect, PubMed, MEDLINE Ovid and CINAHL) for studies published from January 2012 to December 2022. Data collection process will be documented through a PRISMA-P flowchart, including the application of inclusion/exclusion criteria. After data extraction, we will conduct a descriptive thematic analysis to synthesise content and identify emerging themes on family support and interactions, and on behaviors and actions recommended for HCP during neonatal resuscitation.
Ethics and dissemination: Formal ethic approval is not required, as primary data will not be collected in this study. The findings of this study will be disseminated through scientific conferences, publications, and knowledge transfer activities in simulation training in neonatology.
Satellite images reveal reduced lake chlorophyll concentration and eutrophication in China
Authors: Song Kaishan , Li Sijia , Xiao Xiangming , Liu Ge , Wen Zhidan , Fang Chong , Shang Yingxing , Tao Hui , Li Yong , Zhang Lele , Wang Qiang , Zhou Haoyun
Published: August 2024

Lake trophic state is the sentinel of water quality. Improvement of lake trophic state is at the core of various aquatic sustainable development goals for China. Although trophic state regime shifts have been well documented in some lakes, a national-scale assessment on spatiotemporal variation of trophic state has not been done. Here, we analyze Chl-a maps derived from Landsat images during 1990-2020 and assess the changes of trophic states over >1138 large lakes (surface areas larger than 1 km2), which account for 60.1% of total lake areas in China. On the average, these lakes in China had the most pronounced decreases of Chl-a levels since 2010. 180 light-eutrophic lakes (10<1.6, μg L-1) showed increases. At province-scale, the climate variations such as precipitation, temperature and wind speed could positively drive Chl-a’s increases, the increased GDP (3.16%) dominated their reduces. Further, the national protected policies promulgated and implemented significantly decrease lake Chl-a levels and alleviate trophic state since 2010. The patent policies implemented have a greater role in promoting water qualities, particular in relatively rich provinces/municipality as Beijing, Zhengjiang and Shanghai, following by central and east regions. Increased conservation and restoration efforts offset the success of climate change to increase eutrophication.
A Comparative Analysis of Wax and Solid Residues From Plastic Wastes Pyrolysis by FTIR Spectroscopy
Authors: Gurbanov Muslum Ahmed , Guliyeva Ulviye Aydin , Mirzazada Elshan Valeh
Published: August 2024

Following the division of the PET-1 plastic samples (Azerbaijan-made, SIRAB brand noncarbonated beverage) used for the study into 1 cm² pieces, they were fired in quartz ampoules at temperatures of 350°C, 450°C, and 550°C for one hour. The FTIR spectroscopy method was applied in accordance with the objectives of the study. Since PET is thermally stable, separation of the volatiles occurs above 420°C. At 450°C, peaks characteristic of wax are observed in the wavenumber range of 2500–3062 cm− 1, which may be due to the dispersion of the ether group in the PET macromolecule (these peaks are absent in the original sample). In our study, we observed a peak at approximately 1679 cm− 1, which we believe may be characteristic of the ether (C = O) group. During the thermal destruction of the PET-1 samples at temperatures of 450 and 550°C, strong peaks appear in the regions of 1260, 1085, and 1020 cm-1 in the FT-IR spectra, which could be indicative of the presence of carboxylic acids.
Correlation between vegetation indices obtained by rpa and grain yield
Authors: Rosa Helton Aparecido , Johann Jerry Adriani , Becker Willyan Ronaldo , Silveira João Felipe Cesar , Blanco Idelvan Bonadiman
Published: August 2024

The objective of this study was to evaluate the correlations between vegetation indices (VI), obtained by RGB camera on flights of Remotely piloted aircraft System (RPA), with yield maps of agricultural crops. Monitoring was carried out during 4 harvest seasons: soybean 2018/19, maize (2019), soybean 2019/20 and wheat (2020), in two areas of a rural property located in Toledo, Paraná. During the harvests, periodic flights were performed using DJI-branded RPA Phantom 3 Advanced. For the generation of orthomosaic, Agisoft PhotoScan software (Free trial) was used. After the RGB bands normalization, the vegetation indices MPRI, VARI, GLI and ExG were calculated for 3 flight dates in each harvest in the study areas. At the end of the crop cycle, samples were collected to create the yield maps. With the yield data, descriptive statistics analyzes were performed and, later, the correlation between the VIs and the yields of each harvest was performed using Spearman's correlation coefficient (rs). According to the research, it would be suggested that the farmer carry out surveys with RPA with RGB camera in soybean crop, mainly in R7 stage, in maize at VT (bolting) stage and in wheat at tillering stage, since these phenological stages showed higher correlations and between the VIs and the yield of each crop. The pairs of VIs MPRI and VARI, GLI and ExG were similar as vegetative indicators, so only two of them would already have the capacity to represent the variations existing in the areas of the study between the dates.
O Esporte como estratégia de permanência e êxito na educação profissional e tecnológica: uma revisão de escopo
Authors: Rojas Martines Ricardo , Rezende dos Reis Caroline , F. Coelho-Ravagnani Christianne , Cordeiro Barbosa Filho Valter , De Paula Ravagnani Fabricio Cesar
Published: August 2024

Devido aos benefícios sociais, cognitivos, físicos e psíquicos, o esporte-educação pode ser uma estratégia para melhorar os índices de permanência e êxito escolares. Embora seja parte importante da Rede Federal de Educação Profissional, Científica e Tecnológica (RFEPCT), evidências sobre a implementação do esporte-educação são pouco exploradas. Assim, o objetivo desta revisão de escopo é identificar quais estratégias relacionadas ao esporte-educação têm sido implementadas na RFEPCT para estimular a permanência e o êxito dos estudantes. Para tanto, baseou-se na análise dos Planos Estratégicos Institucionais de Permanência e Êxito do Estudante (Peipee) da RFEPCT, publicados on-line desde 2015. Este método seguiu a lista de checagem Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (Tricco et al., 2018). A busca documental foi realizada em 66 sites institucionais, resultando na identificação de 20 Peipee, sendo que 15 apontavam o esporte em ações de permanência e êxito, sendo selecionados para análise. Houve tentativas institucionais de adotar o esporte como ferramenta para melhorar a permanência e o êxito dos estudantes, sobretudo com base nas ações voltadas ao aprimoramento da infraestrutura esportiva, ao desenvolvimento de projetos extensionistas esportivos e/ou aos auxílios estudantis. Ademais, constatou-se a ausência de Peipee em 70% dos sites institucionais. Faz-se necessário, maior engajamento e transparência institucional na formulação e na disponibilização dos Peipee, mais investimentos em esporte, de maneira a mantê-lo ativo nesses documentos. Dessa forma, os Institutos Federais podem transformar os ambientes escolares em locais favoráveis para combater a evasão e promover a retenção dos estudantes.
Quantum work capacitances: Ultimate limits for energy extraction on noisy quantum batteries
Authors: Tirone Salvatore , Salvia Raffaele , Chessa Stefano , Giovannetti Vittorio
Published: August 2024

We present a theoretical analysis of the energy recovery efficiency for quantum batteries composed of many identical quantum cells undergoing noise. While the possibility of using quantum effects to speed up the charging processes of batteries have been vastly investigated, In order to traslate these ideas into working devices it is crucial to assess the stability of the storage phase in the quantum battery elements when they are in contact with environmental noise. In this work we formalize this problem introducing a series of operationally well defined figures of merit (the work capacitances and the Maximal Asymptotic Work/Energy Ratios) which gauge the highest efficiency one can attain in recovering useful energy from quantum battery models that are formed by large collections of identical and independent elements (quantum cells or q-cells). Explicit evaluations of such quantities are presented for the case where the energy storing system undergoes through dephasing and depolarizing noise.
Open string stub as an auxiliary string field
Authors: Erbin Harold , Firat Atakan Hilmi
Published: August 2024

Witten’s open string field theory with a generalized version of stubs is reformulated as a cubic string field theory using an auxiliary string field. The gauge symmetries and equations of motion as well as the associative algebra of the resulting theory are investigated. Integrating out either the original or auxiliary field is shown to recover the conventional cubic theory. Our analysis demonstrates that deformations due to the stubs can be described as a homotopy transfer purely in the context of strong deformation retract. We also discuss to what extent the vertex regions resulting from stubs provide a model for the elementary interactions of closed string field theory.
Does Sustainability Assurance enhance the connection between Corporate Governance and Firm Performance in India?
Authors: C. Bhat Deepa , S. Shenoy Sandeep , K. Shetty Dasharathraj , Abhilash Abhilash
Published: August 2024

Scholarly attention to the association between corporate governance and firm performance, considering sustainability assurance as a moderator is scarce. This study aims to examine the moderating role of sustainability assurance in the nexus between corporate governance and firm performance in India. The data relating to 35 environmentally sensitive companies among the top 100 National Stock Exchange (NSE) listed entities were gathered from the ProwessIQ Database and annual reports of companies during 2016–2022. The fixed effect regression model was employed. The results show an insignificant effect of board effectiveness on firm performance as measured by return on assets (ROA), return on equity (ROE), and Tobin’s Q. Similar findings were documented on the audit committee effectiveness and firm performance nexus, except for Tobin’s Q (β = 0.316). In addition, the study did not support the moderating role of sustainability assurance on the board effectiveness and firm performance nexus, indicating the presence of ineffective corporate governance mechanisms. However, the results show that sustainability assurance significantly and negatively moderates the relationship between audit committee effectiveness and ROA (β = –0.021), ROE (β = –0.074), and Tobin’s Q (β = –0.996). This implies that the practice of external assurance of sustainability reports by firms with audit committee effectiveness is an additional burden due to the extra cost involved. Further, the result indicates the learning curve effect among Indian companies. Thus, the findings suggest the need for regulatory focus on encouraging sustainable business practices in terms of effective corporate governance and sustainability assurance.
AcknowledgmentThe authors are grateful to Manipal Academy of Higher Education (MAHE), Manipal, for providing financial assistance in the form of a “JRF Contingency Grant” for this research article.
A rolling bearing fault diagnosis method based on Compressive sensing and Local characteristic-scale decomposition
Authors: Jo Myong-Jin , Kim Su-Jong , Choe Tong-Chol
Published: August 2024

Rolling bearings are an important part of the system with rotating parts. In the past, the rolling bearing fault diagnosis was based on the envelope of the bearing vibration waveform and FFT analysis to identify the fault and classify the fault type by the feature frequency. In addition, they proposed a method to perform signal processing by decomposing the envelope EMD to improve the diagnostic accuracy. However, this method is computationally intensive due to the iterative computation based on the reduced averaging method, and the convergence rate is different depending on the signal characteristics, which makes it difficult to perform real-time functions and consume a lot of memory space for data communication. In this paper, a method for diagnosing faults in rolling bearings based on compressive sensing (CS) and local characteristic-scale decomposition (LCD) is proposed and the effectiveness of bearing fault diagnosis method is verified by numerical experiments. In this paper, we propose a method to improve the diagnostic accuracy and shorten the computational time by identifying characteristic frequencies of the bearing fault from the Hilbert envelope spectrum of the components decomposed by the LCD after preprocessing and signal filtering of vibration signals based on CS.
The use of innovative technologies to improve treated wastewater irrigation of olive trees in the Souss-Massa region, Morocco
Authors: Mansir Imane , Naji Yassine , Scardigno Alessandra , Dragonetti G. , El Otmani Mohamed , Bouchaou Lhoussaine , Choukr-Allah Redouane
Published: August 2024

Treated wastewater (TWW) use represents a strategic prospect for sustainable agricultural development in water-scarce countries. The objective of this study was to evaluate the feasibility of adopting an innovative nozzle and irrigation management support (SIM) to promote the cultivation of olive trees under TWW in Morocco. The study involved 4-year-old olive trees irrigated according to the water requirement estimated by both the SIM model and the FAO56 method. The results showed that neither agronomic and physiological parameters nor leaves were affected by irrigation with TWW. However, the soil reacted differently as its alkalinity but witnessed a decrease in the fresh water (FW) treatments. The soil solution electrical conductivity was generally higher for TWW than FW. The savings on water and fertilizer costs generated by the TWW and TWW + SIM treatments are 570€ and 585€/ha, respectively, and the adoption of the two innovations generates additional net benefits equal to 45,000€, while to the nozzle with TWW alone, additional net benefits were observed that is 42,000€. A minimum increase in return of only 0.6% is needed to cover investment costs over the 30-year life of the project and the investment could be profitable even with a decrease in return of 48%.
Hydrotalcite and Hydrotalcite-Based Materials
Authors: Kadiyala K Ganesh , Jagadeesh Kadali
Published: August 2024

This chapter deals with the history of hydrotalcite and hydrotalcite-based
materials. A rare mineral known as hydrotalcite was found in Sweden sometimes in the
1840s. Magnesium aluminum hydroxycarbonate, Mg6Al2
(OH)16CO34H2O, is its
chemical name, and Taylor and Allmann independently determined its layered
structure. For a long time, hydrotalcite and other isomorphous minerals (such as
piroaurite, sjogrenite, and takovite) were the focus of most mineralogical studies.
However, beginning in the 1970s, it was discovered that these rare minerals, also
known as anionic clays, could be prepared quickly and affordably in a laboratory and
have a variety of intriguing chemical properties. The different arrangements of the
stacking of the layers, the ordering of the metal cations, as well as the arrangement of
anions and water molecules in the interlayer galleries, result in a variety of
stoichiometry in hydrotalcite, which are layered double hydroxides. Due to their unique
characteristics, including their enormous surface area, ion exchangeability, insolubility
in water, and most organic sorbents, among others, the compounds of the hydrotalcite
group demonstrate a wide variety of potential uses.
Synthesis and Characterization of HydrotalciteBased materials
Authors: Dhanda Nishu , Kumari Chetna , Bareth Diksha , Kumar Sudesh
Published: August 2024

Hydrotalcite (HT) has the chemical formula Mg6Al2
(OH)16CO3
•4H2O, with a
stacked crystal structure comprising layers of positively charged hydroxides that are
interlayer anion neutralization as carbonate and contain H2O particles. These double
hydroxides in layers (LDH) are a class of highly fascinating materials for the industry
due to the simplicity of their production and the ability to add additional layer cations
and interlayer anions. Hydrotalcite-based materials such as magnesium aluminide
(MgAl) hydrotalcite with a range of magnesium to aluminium (Mg/Al) molar ratios are
used to prepare catalysts for effective changes of organic molecules. X-ray diffraction
and scanning electron microscopy (SEM) characterization measure the catalyst's
crystallinity, surface area, and shape. The HT has been employed as a scaffold for
immobilizing numerous metals, enabling highly selective organic reactions, i.e., the
dehydrogenation of alcohols and the deoxygenation of epoxides. It may also work with
other metal catalysts to speed up subsequent responses in a single pot. It offers a vital
method for the environmentally responsible synthesis of valuable compounds. This
chapter overviews the hydrotalcite synthesis, classification, and application research.
Corporate bankruptcy prediction model
Authors: Insani Fitriyah , Pontoh Grace T , Said Darwis
Published: August 2024

This study is a systematic literature review aimed at providing a comprehensive understanding of the use of various models such as Altman Z-Score, Springate, Zmijewski, Grover, Beneish, and Ohlson in the analysis of bankruptcy prediction for companies. The study details many research articles published in various academic journals and other reliable sources. Literature analysis involves identifying trends, common findings, as well as recent developments in the use of these models as bankruptcy prediction tools. This literature review indicates that despite significant advancements in the development of bankruptcy prediction models, challenges persist in applying these models universally across different contexts, particularly given contextual variations between industries and countries. The insights from this literature study are valuable for researchers, financial practitioners, and decision-makers in applying any models for bankruptcy prediction analysis. Furthermore, this literature review encourages further research in developing more sophisticated and timely bankruptcy prediction models.
Differences in Fear and Negativity Levels Between Formal and Informal Health-Related Websites: Analysis of Sentiments and Emotions
Authors: Paradise Vit Abigail , Magid Avi
Published: August 2024

Background

Searching for web-based health-related information is frequently performed by the public and may affect public behavior regarding health decision-making. Particularly, it may result in anxiety, erroneous, and harmful self-diagnosis. Most searched health-related topics are cancer, cardiovascular diseases, and infectious diseases. A health-related web-based search may result in either formal or informal medical website, both of which may evoke feelings of fear and negativity.

Objective

Our study aimed to assess whether there is a difference in fear and negativity levels between information appearing on formal and informal health-related websites.

Methods

A web search was performed to retrieve the contents of websites containing symptoms of selected diseases, using selected common symptoms. Retrieved websites were classified into formal and informal websites. Fear and negativity of each content were evaluated using 3 transformer models. A fourth transformer model was fine-tuned using an existing emotion data set obtained from a web-based health community. For formal and informal websites, fear and negativity levels were aggregated. t tests were conducted to evaluate the differences in fear and negativity levels between formal and informal websites.

Results

In this study, unique websites (N=1448) were collected, of which 534 were considered formal and 914 were considered informal. There were 1820 result pages from formal websites and 1494 result pages from informal websites. According to our findings, fear levels were statistically higher (t2753=3.331; P<.001) on formal websites (mean 0.388, SD 0.177) than on informal websites (mean 0.366, SD 0.168). The results also show that the level of negativity was statistically higher (t2753=2.726; P=.006) on formal websites (mean 0.657, SD 0.211) than on informal websites (mean 0.636, SD 0.201).

Conclusions

Positive texts may increase the credibility of formal health websites and increase their usage by the general public and the public’s compliance to the recommendations. Increasing the usage of natural language processing tools before publishing health-related information to achieve a more positive and less stressful text to be disseminated to the public is recommended.
Online Delivery of Interprofessional Adverse Childhood Experiences Training to Rural Providers: Usability Study
Authors: Kapp Julie M , Dicke Rachel , Quinn Kathleen
Published: August 2024

Background

The population health burden of adverse childhood experiences (ACEs) reflects a critical need for evidence-based provider training. Rural children are also more likely than urban children to have any ACEs. A large proportion of providers are unaware of the detrimental effects of ACEs. There is a significant documented need for training providers about ACEs and trauma-informed care, in addition to a demand for that training.

Objective

The objective was to develop, implement, and evaluate an online ACEs training curriculum tailored to Missouri providers, particularly those in rural areas given the higher prevalence of ACEs.

Methods

From July 2021 to June 2022, we conducted literature reviews and environmental scans of training videos, partner organizations, clinical practice guidelines, and community-based resources to curate appropriate and tailored content for the course. We developed the ACEs training course in the Canvas learning platform (Instructure) with the assistance of an instructional designer and media designer. The course was certified for continuing medical education, as well as continuing education for licensed professional counselors, psychologists, and social workers. Recruitment occurred via key stakeholder email invitations and snowball recruitment.

Results

Overall, 135 providers across Missouri requested enrollment, with 72.6% (n=98) enrolling and accessing the training. Of the latter, 49% (n=48) completed course requirements, with 100% of respondents agreeing that the content was relevant to their work, life, or practice; they intend to apply the content to their work, life, or practice; they feel confident to do so; and they would recommend the course to others. Qualitative responses supported active intent to translate knowledge into practice.

Conclusions

This study demonstrated the feasibility, acceptability, and effectiveness of interprofessional workforce ACEs training. Robust interest statewide reflects recognition of the topic’s importance and intention to translate knowledge into practice.
Twenty-Five Years of Progress—Lessons Learned From JMIR Publications to Address Gender Parity in Digital Health Authorships: Bibliometric Analysis (Preprint)
Authors: Meyer Annika , Streichert Thomas
Published: August 2024

BACKGROUND

Digital health research plays a vital role in advancing equitable health care. The diversity of research teams is thereby instrumental in capturing societal challenges, increasing productivity, and reducing bias in algorithms. Despite its importance, the gender distribution within digital health authorship remains largely unexplored.

OBJECTIVE

This study aimed to investigate the gender distribution among first and last authors in digital health research, thereby identifying predicting factors of female authorship.

METHODS

This bibliometric analysis examined the gender distribution across 59,980 publications from 1999 to 2023, spanning 42 digital health journals indexed in the Web of Science. To identify strategies ensuring equality in research, a detailed comparison of gender representation in JMIR journals was conducted within the field, as well as against a matched sample. Two-tailed Welch 2-sample t tests, Wilcoxon rank sum tests, and chi-square tests were used to assess differences. In addition, odds ratios were calculated to identify predictors of female authorship.

RESULTS

The analysis revealed that 37% of first authors and 30% of last authors in digital health were female. JMIR journals demonstrated a higher representation, with 49% of first authors and 38% of last authors being female, yielding odds ratios of 1.96 (95% CI 1.90-2.03; P<.001) and 1.78 (95% CI 1.71-1.84; P<.001), respectively. Since 2008, JMIR journals have consistently featured a greater proportion of female first authors than male counterparts. Other factors that predicted female authorship included having female authors in other relevant positions and gender discordance, given the higher rate of male last authors in the field.

CONCLUSIONS

There was an evident shift toward gender parity across publications in digital health, particularly from the publisher JMIR Publications. The specialized focus of its sister journals, equitable editorial policies, and transparency in the review process might contribute to these achievements. Further research is imperative to establish causality, enabling the replication of these successful strategies across other scientific fields to bridge the gender gap in digital health effectively.
Analysis of Retinal Thickness in Patients with Chronic Diseases Using Standardized Optical Coherence Tomography Databases Based on the Radiology Common Data Model (R-CDM) (Preprint)
Authors: Park ChulHyoung , Lee So Hee , Park Rae Woong , Park Sang Jun , Choi Seo Yoon , You Seng Chan , Jeon Ja Young , Lee Da Yeon
Published: August 2024

BACKGROUND

The Observational Medical Outcome Partners - Common Data Model (OMOP-CDM) is an international standard for harmonizing electronic medical record (EMR) data. However, since it does not standardize unstructured data such as medical imaging, utilizing this data in multi-institutional collaborative research becomes challenging. To overcome this limitation, extensions such as the Radiology Common Data Model (R-CDM) have emerged to include and standardize these data types.

OBJECTIVE

This work aims to demonstrate that by standardizing Optical Coherence Tomography (OCT) data into an R-CDM format, multi-institutional collaborative studies analyzing changes in retinal thickness in patients with long-standing chronic diseases can be performed very efficiently.

METHODS

We standardized OCT images collected from two tertiary hospitals for research purposes using the R-CDM. As a proof of concept, we conducted a comparative analysis of retinal thickness between patients who have long suffered from chronic diseases and those who have not. Patients diagnosed or treated for retinal and choroidal diseases, which could affect retinal thickness, were excluded from the analysis. Using the existing OMOP-CDM at each institution, we extracted cohorts of chronic disease patients and control groups, performing large-scale 1:2 propensity score matching (PSM). Subsequently, we linked OMOP-CDM and R-CDM to extract the OCT image data of these cohorts and analyzed central macular thickness (CMT) and retinal nerve fiber layer (RNFL) thickness using a linear mixed model.

RESULTS

OCT data of 261,874 images from Ajou University Medical Center (AUMC) and 475,626 images from Seoul National University Bundang Hospital (SNUBH) were standardized in the form of R-CDM. The R-CDM databases established at each institution were linked with the OMOP-CDM database. Following 1:2 PSM, the type 2 diabetes mellitus (T2DM) cohort included 957 patients, and the control cohort had 1,603 patients. During the follow-up period, significant reductions in CMT were observed in the T2DM cohorts at both institutions (P = 0.04 and P < 0.01, respectively), without significant changes in RNFL thickness (P = 0.56 and P = 0.39, respectively). Notably, a significant reduction in CMT during the follow-up was observed only at AUMC in the hypertension (HTN) cohort, compared to the control group; no other significant differences in retinal thickness changes were found in the remaining analyses.

CONCLUSIONS

The significance of our study lies in demonstrating the efficiency of multi-institutional collaborative research that simultaneously utilizes clinical data and medical imaging data by leveraging the OMOP-CDM for standardizing EMR data, and the R-CDM for standardizing medical imaging data.
A Hybrid Deep Learning-Based Feature Selection Approach for Supporting Early Detection of Long-Term Behavioral Outcomes in Cancer Survivors (Preprint)
Authors: Huang Tracy , Ngan Chun-Kit , Cheung Yin Ting , Marcotte Madelyn , Cabrera Benjamin
Published: August 2024

BACKGROUND

The number of cancer survivors is growing, and cancer survivors often suffer from long-term behavioral outcomes due to cancer treatments. There is a need for better computational methods to handle and predict cancer behavioral outcomes so physicians and healthcare providers can implement preventative treatments for cancer survivors.

OBJECTIVE

The aim of this study is to create a new feature selection algorithm to improve the performance of machine learning classifiers to predict long-term behavioral outcomes in cancer survivors.

METHODS

We devise a hybrid deep learning-based feature selection approach to support early detection of long-term behavioral outcomes in cancer survivors. Within a data-driven, clinical-domain guided framework to select the best set of features among cancer treatments, chronic health conditions, socio-environmental factors, we develop a two-stage feature selection algorithm, i.e., a multi-metric, majority-voting filter and a deep drop-out neural network, to dynamically and automatically select the best set of features for each behavioral outcome. We also conduct an experimental case study on existing study data with 102 survivors of acute lymphoblastic leukemia (ALL) (aged 15 to 39 years old at evaluation and > 5 years post-cancer diagnosis) who were treated in a public hospital of Hong Kong. Finally, we design and implement radial charts to illustrate the significance of the selected features on each behavioral outcome to support clinical professionals’ future treatment and diagnoses.

RESULTS

In this pilot study, we demonstrate that our approach outperforms the traditional statistical and computation methods, including linear and non-linear feature selectors, for the addressed top-priority behavioral outcomes. Our approach holistically has higher F1, precision, and recall scores compared to existing feature selection methods. The models select several significant clinical and socioenvironmental variables as risk factors associated with the development of behavioral problems in young survivors of ALL.

CONCLUSIONS

Our novel feature selection algorithm has potential to improve machine learning classifiers’ capability to predict long-term behavioral outcomes in cancer survivors.