bluuebunny/crossref_metadata_2025 huggingface dataset:
Mineralization of clofibric acid by persulfate-promoted catalytic subcritical water oxidation process using CoFe2O4@SiO2 catalyst
Authors: Görmez Özkan
Published: June 2024

The design and use of innovative treatment processes are very important in preventing the possible toxic effects of organic pollutants in aquatic environments. One of these methods is the subcritical water oxidation method, which has been used recently. In the current study, the mineralization of clofibric acid (CFA) was carried out under more effective and mild conditions using persulfate (PS) as an oxidant and CoFe2O4@SiO2 catalyst by the subcritical water oxidation (sub-CWO) process. Characterization of the synthesized catalyst was performed through XRD, FTIR, TEM and SEM–EDS analyses. In the CFA oxidation with persulfate-promoted catalytic Sub-CWO process, optimum working conditions was determined as 15 mM PS, 40 min, 383 K, and 0.3 g L−1 catalyst dosage using the response surface method and Box–Behnken design. The catalyst's efficiency remained relatively stable after three cycles under optimal conditions, resulting in a 97% total organic carbon (TOC) removal. Decomposition products were determined and a degradation mechanism was proposed.
Determinants of housing prices: Serbian Cities’ perspective
Authors: Marinković Srđan , Džunić Marija , Marjanović Ivana
Published: June 2024

This study investigates the spatial and temporal dynamics of housing prices in Serbia, addressing the critical need to understand the drivers of real estate prices and their implications for economic and social welfare. Employing a panel data analysis approach on a unique dataset covering 24 distinct urban areas in Serbia from 2011 to 2021, we examine the relevance of diverse economic, demographic, and infrastructural indicators, providing novel insights within a developing country context. Our findings reveal that the housing market stock-flow model effectively predicts housing price appreciation trends, explaining over 60 percent of variation in property prices. Notably, disparities in labour income, captured by average wages and registered employment rates, emerge as significant determinants of real estate prices, underlining socio-economic disparities within Serbian cities. Housing prices exhibit a positive response to the population/housing stock ratio, suggesting higher prices in cities experiencing faster population growth relative to housing supply. Intensified construction is associated with elevated housing prices. Additionally, we find positive association between the inflation variable and housing prices, underlining real estate’s potential as an inflation hedge. Public service provision and infrastructural amenities also emerge as contributors to higher housing prices in urban areas, emphasizing the importance of comprehensive urban planning strategies. Our study contributes to the literature by providing specific quantitative evidence, advancing the understanding of urban housing market dynamics in developing countries. By offering nuanced insights into determinants of housing prices, our research informs policymakers and urban planners seeking to foster equitable and sustainable urban development strategies.
Customized Green Energetic Tetra(Imidazole)Copper(II) Nitrate (Cu-Im) Complex/Ammonium Nitrate Co-crystal: A Novel Reactive Halogen-Free Oxidizer with Superior Stability and Decomposition Kinetics
Authors: Attwa Mohamed , Tantawy Hesham , Elbasuney Sherif
Published: June 2024

Ammonium nitrate (AN) is the most promising affordable green oxidizer for solid propellants; however, its endothermic phase transitions and endothermic decomposition restrict its applications. This work shaded the light on multifunctional energetic complex tetra(imidazole)copper (II) nitrate (Cu-Im) with combustion enthalpy of 15.57 KJ/g as a high energy dense material, phase stabilizer, and catalyst for AN-based propellant. The Cu-Im complex was synthesized via a green simple solvent-free melt-assisting technique. As-synthesized Cu-Im complex demonstrated a highly pure crystalline structure with thermal stability up to 200 °C. Cu-Im complex was integrated into AN via an evaporative crystallization technique. The phase transitions and the thermal behavior of the developed Cu-Im complex/AN cocrystal were investigated via DSC and TGA. The Cu-Im complex stabilized the phase transition of AN up to 88.48 °C via an evolved strong hydrogen bonding system within the Cu-Im complex/AN cocrystal. Moreover, the energetic Cu-Im complex offered a significant decrease in the endothermic phase transition peaks associated with IV↔II, and II↔I by 38.81%, and 25.28% respectively. Additionally, AN strong endothermic melting was decreased by 45.32%. The Cu-Im complex converts the AN endothermic thermal decomposition peak with + 1400 J/g into an intensive exothermic peak with the release of -2241 J/g. The Cu-Im complex exhibited a superior catalytic effect via the decrease in AN decomposition temperature by 48.85 °C. Cu-Im complex offered a remarkable reduction in apparent activation energy of AN decomposition by 56.24% and 48.12% via Kissinger’s model and integral iso-conversional nonlinear Vyazovkin method (VYA) respectively. The superior catalytic performance of the Cu-Im complex was attributed to the evolution of CuO nanoparticles during its decomposition. The electron-deficient Lewis acid copper ions have a large affinity to electron lone pair of nitrogen; this effect could support the conversion of NH3 to N2 and H2. This catalytic action could boost the decomposition enthalpy of AN. Consequently, the developed Cu-Im/AN cocrystal could be considered a potential green substitute for perchlorate-based oxidizers.
Cationic Iridium(III) Complexes Bearing Different Bulky N,N′-Chelating Ligands
Authors: Wong Wai-Yeung , Chau Nga-Yuen , Wang Qiwei , Jiang Lu , Li Junlong , Sun Zelin
Published: June 2024

Six cationic iridium(III) complexes bearing different bulky N,N′-chelating ligands were successfully synthesized and characterized by spectroscopic, electrochemical, thermal and photophysical methods. Because the molecular quenching and self-aggregation within molecules would deteriorate the device efficiency, the bulky molecules can suppress these problems and improve the device performance. The best doped organic light-emitting diodes based on these charged Ir(III) complex E1 exhibited Lmax of 26,800 cd/m2, ηL, max of 35.0 cd/A and ηP, max of 18.5 lm/W, which also showed a small efficiency roll-off in the range of 100 to 1000 cd/m2.

Graphical Abstract
Hop, walk or bound? Limb proportions in kangaroos and the probable locomotion of the extinct genus Protemnodon
Authors: Jones Billie , Janis Christine M.
Published: June 2024

Kangaroos (Macropodoidea) display a diversity of locomotor modes, from bounding quadrupedally to hopping bipedally; but hopping has a body mass limit, which was exceeded by a number of extinct taxa. In the Pleistocene, a variety of “giant” kangaroos existed, both within the extinct subfamily Sthenurinae and the extant subfamily Macropodinae (both within the family Macropodidae). Sthenurines have been previously considered to have a type of locomotion (bipedal striding) different from extant kangaroos, but the primary locomotor mode of the large species of the extinct “giant” macropodine genus Protemnodon, closely related to extant large kangaroos, has undergone little question and has been assumed to be hopping. Here, the association between limb proportions and locomotor mode across Macropodoidea is assessed by examination of functional limb indices. We show that large (> 100 kg) Protemnodon species are unlike any other known macropodoids; their position in this functional morphospace, along with previously published evidence on humeral morphology, supports a prior hypothesis of a primarily quadrupedal mode of locomotion, likely some sort of bounding.
Process Evaluation of Individual Placement and Support and Participatory Workplace Intervention to Increase the Sustainable Work Participation of People with Work Disabilities
Authors: Oude Geerdink E. , Huysmans M. A. , van Kempen H. , Maarleveld J. M. , van Weeghel J. , Anema J. R.
Published: June 2024

Purpose

This study is a process evaluation of the use of Individual Placement and Support (IPS) and Participatory Workplace Intervention (PWI) to increase the work participation of people with work disabilities. We ran the evaluation alongside a randomized controlled trial (RCT), to investigate whether and to what extent IPS and PWI were executed according to protocol.

Methods

The study population consisted of clients with work disabilities, and their job coaches who were employed by the municipality of a large city in the Netherlands. Data were collected between September 2019 and November 2022 using registration forms, accompanied by researchers’ notes and logbooks.

Results

For IPS the dose delivered was reasonable and the IPS fidelity measurement score was fair. The job search focused on paid work for almost all clients and was based on their wishes as indicated in the protocol, but integration of employment services with (health) care was often lacking. A minority of the clients who were assigned to PWI received the intervention, often because the client did not start work within the follow-up period and a workplace was a requirement to apply the intervention.

Conclusion

The results of this study show that IPS was executed reasonably and with a fair fidelity, which indicated implementation was sufficient to find an effect on work participation in the RCT. PWI was barely realized in practice and no conclusions regarding the fidelity could be drawn. We therefore conclude that we cannot expect PWI to have any effect on work participation in the RCT.
Discrete-time graph neural networks for transaction prediction in Web3 social platforms
Authors: Dileo Manuel , Zignani Matteo
Published: June 2024

In Web3 social platforms, i.e. social web applications that rely on blockchain technology to support their functionalities, interactions among users are usually multimodal, from common social interactions such as following, liking, or posting, to specific relations given by crypto-token transfers facilitated by the blockchain. In this dynamic and intertwined networked context, modeled as a financial network, our main goals are (i) to predict whether a pair of users will be involved in a financial transaction, i.e. the transaction prediction task, even using textual information produced by users, and (ii) to verify whether performances may be enhanced by textual content. To address the above issues, we compared current snapshot-based temporal graph learning methods and developed T3GNN, a solution based on state-of-the-art temporal graph neural networks’ design, which integrates fine-tuned sentence embeddings and a simple yet effective graph-augmentation strategy for representing content, and historical negative sampling. We evaluated models in a Web3 context by leveraging a novel high-resolution temporal dataset, collected from one of the most used Web3 social platforms, which spans more than one year of financial interactions as well as published textual content. The experimental evaluation has shown that T3GNN consistently achieved the best performance over time and for most of the snapshots. Furthermore, through an extensive analysis of the performance of our model, we show that, despite the graph structure being crucial for making predictions, textual content contains useful information for forecasting transactions, highlighting an interplay between users’ interests and economic relationships in Web3 platforms. Finally, the evaluation has also highlighted the importance of adopting sampling methods alternative to random negative sampling when dealing with prediction tasks on temporal networks.
Flowable resin-based composites modified with chlorhexidine-loaded mesoporous silica nanoparticles induce superior antibiofilm properties
Authors: Shrestha Barsha , Aati Sultan , Maria Rajan Sheetal , Fawzy Amr
Published: June 2024

Clinical failure of dental resin-composite restorations is mainly due to bacterial-mediated secondary caries formation. Therefore, the development of a flowable resin-composite material having inherent antibacterial properties is crucial to enhance the durability of dental restorations. Herein, dental flowable resin-composite material was modified with chlorhexidine-loaded mesoporous silica nanoparticles (CHX-MSN) to induce in situ antibacterial properties against S. mutans. Mesoporous silica nanoparticles loaded with chlorhexidine (CHX-MSN) were formulated and characterized for drug-loading/encapsulation efficiency, morphology by electron microscopy, and infrared spectral analysis. CHX-MSN were incorporated into the flowable composite material at different concentrations of 1, 5, and 10% (w/w) and examined at two time points (baseline and 3 months in artificial saliva). The CHX-MSN modified composites exhibited an initial CHX release burst followed by a steady release up to 30 days. The antimicrobial efficacy of the modified composites was evaluated by crystal violet assay, MTT assay, and confocal laser scanning microscopy. In addition to measuring the degree of conversion and cytotoxicity, the mechanical properties were characterized by surface microhardness and flexural strength. The modified composites demonstrated a significant increase in antimicrobial properties compared to the unmodified control (p < 0.05) which is dependent on the concentration of the CHX-MSN nanoparticles. In addition, the modified composites possessed acceptable biocompatibility without adversely affecting mechanical properties and degree of conversion up to 5% addition of CHX-MSN nanoparticles. This study introduced a protocol to develop resin-based flowable dental composite material having superior antibacterial property against cariogenic biofilms aiming for enhancing clinical longevity of dental restorations.

Graphical Abstract
Defining the role of surgery for patients with multiple brain metastases
Authors: Ersoy Tunc Faik , Brainman Daniel , Coras Roland , Berger Björn , Weissinger Florian , Grote Alexander , Simon Matthias
Published: June 2024

Purpose

To better define the role of surgery, we investigated survival and functional outcomes in patients with multiple brain metastases.

Methods

Pertinent clinical and radiological data of 131 consecutive patients (156 surgeries) were analyzed retrospectively.

Results

Surgical indications included mass effect (84.6%) and need for tissue acquisition (44.9%, for molecularly informed treatment: 10 patients). Major (i.e. CTCAE grade 3–5) neurological, surgical and medical complication were observed in 6 (3.8%), 12 (7.7%), and 12 (7.7%) surgical cases. Median preoperative and discharge KPS were 80% (IQF: 60–90%). Median overall survival (mOS) was 7.4 months. However, estimated 1 and 2 year overall survival rates were 35.6% and 25.1%, respectively. Survival was dismal (i.e. mOS ≤ 2.5 months) in patients who had no postoperative radio- and systemic therapy, or who incurred major complications. Multivariate analysis with all parameters significantly correlated with survival as univariate parameters revealed female sex, oligometastases, no major new/worsened neurological deficits, and postoperative radio- and systemic therapy as independent positive prognostic parameters. Univariate positive prognostic parameters also included histology (best survival in breast cancer patients) and less than median (0.28 cm3) residual tumor load.

Conclusions

Surgery is a reasonable therapeutic option in many patients with multiple brain metastases. Operations should primarily aim at reducing mass effect thereby preserving the patients’ functional health status which will allow for further local (radiation) and systemic therapy. Surgery for the acquisition of metastatic tissue (more recently for molecularly informed treatment) is another important surgical indication. Cytoreductive surgery may also carry a survival benefit by itself.
Explicit frictional stick–slip dynamics of elastic contact problem incorporating the LuGre model
Authors: Hu Han , Zhu Xiaosong , Batou Anas , Ouyang Huajiang
Published: June 2024

Dynamical contact problem with friction is of continuous concern and have been investigated over the years. The effective and accurate description of the development of the friction force is the key to this problem. However, the stick–slip phenomenon, as typical dynamical behaviour, has rarely been considered when developing contact algorithms for frictional contact problems of elastic bodies. The conventionally used Coulomb’s model, with differentiating the static and kinetic coefficient of friction, can lead to inaccurate results due to errors generated when switch between the stick or slip states. In this work, a three-dimensional mortar-based frictional contact algorithm is proposed in an explicit scheme. The proposed algorithm incorporates the LuGre model to account for dynamical frictional behaviours such as stick–slip. The effectiveness and accuracy of the proposed algorithm are validated through several simplified two-dimensional cases. The sticking time ratio and the evolution of the global coefficient of friction with time of a three-dimensional contact problem with a randomly rough contact interface are investigated as an application.
A Combination of Machine Learning and PBPK Modeling Approach for Pharmacokinetics Prediction of Small Molecules in Humans
Authors: Li Yuelin , Wang Zonghu , Li Yuru , Du Jiewen , Gao Xiangrui , Li Yuanpeng , Lai Lipeng
Published: June 2024

Purpose:

Recently, there has been rapid development in model-informed drug development, which has the potential to reduce animal experiments and accelerate drug discovery. Physiologically based pharmacokinetic (PBPK) and machine learning (ML) models are commonly used in early drug discovery to predict drug properties. However, basic PBPK models require a large number of molecule-specific inputs from in vitro experiments, which hinders the efficiency and accuracy of these models. To address this issue, this paper introduces a new computational platform that combines ML and PBPK models. The platform predicts molecule PK profiles with high accuracy and without the need for experimental data.

Methods:

This study developed a whole-body PBPK model and ML models of plasma protein fraction unbound ($$f_{up}$$

f

up

), Caco-2 cell permeability, and total plasma clearance to predict the PK of small molecules after intravenous administration. Pharmacokinetic profiles were simulated using a “bottom-up” PBPK modeling approach with ML inputs. Additionally, 40 compounds were used to evaluate the platform’s accuracy.

Results:

Results showed that the ML-PBPK model predicted the area under the concentration-time curve (AUC) with 65.0$$\%$$
%
accuracy within a 2-fold range, which was higher than using in vitro inputs with 47.5$$\%$$
%
accuracy.

Conclusion:

The ML-PBPK model platform provides high accuracy in prediction and reduces the number of experiments and time required compared to traditional PBPK approaches. The platform successfully predicts human PK parameters without in vitro and in vivo experiments and can potentially guide early drug discovery and development.
Dual process theory and the challenges of functional individuation
Authors: Grayot James D. , Beck Lukas , Heijmeskamp Thijs
Published: June 2024

Despite on-going debates in philosophy and cognitive science, dual process theory (DPT) remains a popular framework for theorizing about human cognition. Its central hypothesis is that cognitive processing can be subsumed under two generic types. In this paper, we argue that the putative success and popularity of this framework remains overstated and gives rise to certain misunderstandings. If DPT has predictive and/or explanatory power, it is through offering descriptions of cognitive phenomena via functional analysis. But functional descriptions require an individuation strategy. To date, there has been no systematic exploration of how Type 1 and Type 2 are functionally individuated. Following recent debates in philosophy of cognitive science, we consider three individuation strategies (i.e., abstraction, reification, fictionalization) and assess the legitimacy of each in relation to DPT. This leads us to the verdict that the most viable route for justifying DPT is to construe Type 1 and Type 2 processes as reifications. We conclude that, construed as reifications, the common rationales offered by proponents of DPT for demarcating Type 1 and Type 2 processes do not escape criticism and require further theoretical justification.
Parental Loss and Mental Health in Post-Khmer-Rouge Cambodia
Authors: Heuveline Patrick , Clague Angela K.
Published: June 2024

Adverse childhood events (ACE) may have lasting consequences throughout the life course. We focus on one particular type of ACE, parental loss in Cambodia—a country that lost nearly 25% of its population during the 1975-79 Khmer-Rouge regime—and on mental health disorders, one of the potential mechanisms through which ACE may have long-term consequences. Self-reports of symptoms that map on to the Diagnostic and Statistical Manual of Mental Health Disorders (DSM) criteria for anxiety, depression, and post-traumatic stress disorder (PTSD) were collected from 4,405 adults aged 20 and over. We first assess exposure to traumatic events and the prevalence of anxiety, depression, and PTSD using the DSM and alternative criteria. Based on the DSM criteria and previously validated Likert-scale thresholds, we find a high prevalence of anxiety (56.0%), depression (42.8%), and PTSD (2.3%), and even higher levels even among KRR survivors. We then use logit models to analyze the effect of parental loss before age 20 on the likelihood of having experienced traumatic events and experiencing mental health disorders. We find the loss of one parent increases the likelihood of full-PTSD symptoms, but the loss of both parents does not. These findings may result from positive selection into better-off households for orphans whose parents have both died but may also reflect the grief-related difficulties faced by the surviving parent of paternal or maternal orphans. While alternative thresholds for PTSD produced higher prevalence estimates, these measures did not perform better for assessing the effect of parental loss on mental health.
The Role of Salience and Memory in Fertility Decisions: Experimental Evidence
Authors: Galasso Vincenzo
Published: June 2024

Public policies use communication campaigns to affect individual behavior. We analyze how providing women with information on the beneficial effects of using formal childcare may affect their realized fertility. We argue that cues in the messages are particularly salient for mothers and women with fertility intensions, since they activate these women’s past memories. Hence, cues induce these women to create mental representations of future actions, such as realized fertility. We exploit a randomized survey experiment run in 2011, which provides information on the positive effects that attending daycare may have on the children’ future cognitive development. Using a follow-up survey run six-year later we show that the treatment increases realized fertility among mothers and women with declared fertility intentions, for whom the communication was more salient. Yet, the treatment did not affect the individual knowledge nor recall of the information provided in the message. Our results carry important policy implications: persuading individuals is difficult, but communication can be effective if salient.
Conditional independence in a binary choice experiment
Authors: Wilcox Nathaniel T.
Published: June 2024

Experimental and behavioral economists, as well as psychologists, commonly assume conditional independence of choices when constructing likelihood functions for structural estimation of choice functions. I test this assumption using data from a new experiment designed for this purpose. Within the limits of the experiment’s identifying restriction and designed power to detect deviations from conditional independence, conditional independence is not rejected. In naturally occurring data, concerns about violations of conditional independence are certainly proper and well-taken (for well-known reasons). However, when an experimenter employs the particular experimental mechanisms and designs used here, the findings suggest that conditional independence is an acceptable assumption for analyzing data so generated.
Predicting citation impact of academic papers across research areas using multiple models and early citations
Authors: Zhang Fang , Wu Shengli
Published: June 2024

As the volume of scientific literature expands rapidly, accurately gauging and predicting the citation impact of academic papers has become increasingly imperative. Citation counts serve as a widely adopted metric for this purpose. While numerous researchers have explored techniques for projecting papers’ citation counts, a prevalent constraint lies in the utilization of a singular model across all papers within a dataset. This universal approach, suitable for small, homogeneous collections, proves less effective for large, heterogeneous collections spanning various research domains, thereby curtailing the practical utility of these methodologies. In this study, we propose a pioneering methodology that deploys multiple models tailored to distinct research domains and integrates early citation data. Our approach encompasses instance-based learning techniques to categorize papers into different research domains and distinct prediction models trained on early citation counts for papers within each domain. We assessed our methodology using two extensive datasets sourced from DBLP and arXiv. Our experimental findings affirm that the proposed classification methodology is both precise and efficient in classifying papers into research domains. Furthermore, the proposed prediction methodology, harnessing multiple domain-specific models and early citations, surpasses four state-of-the-art baseline methods in most instances, substantially enhancing the accuracy of citation impact predictions for diverse collections of academic papers.
Optimization of containerized application deployment in virtualized environments: a novel mathematical framework for resource-efficient and energy-aware server infrastructure
Authors: Rabieyan Reza , Yahyapour Ramin , Jahnke Patrick
Published: June 2024

This study addresses the critical need for effective resource management through software container migration in cloud data centers. It emphasizes its role in avoiding resource shortages and reducing energy consumption in cloud environments. This study introduces a novel multi-objective integer linear programming (ILP) approach for software container replacements, complemented by a specialized algorithm designed to migrate software containers between over- and underutilized hosts to enhance efficiency compared to traditional optimization methods. The simulation results demonstrate the algorithm's effectiveness, validating its potential for optimizing energy usage and resource allocation in cloud environments. Statistical analyses confirm the proposed model's and algorithm's superiority over benchmark approaches, highlighting their potential for enhancing resource management in cloud computing systems.
Understanding Japan's Land-use Dynamics between 1987 and 2050 using Land Accounting and Scenario Analysis
Authors: Huang Wanhui , Hashimoto Shizuka , Yoshida Takehito , Saito Osamu , Meraj Gowhar
Published: June 2024

Amidst global concerns about land use change and its far-reaching impact on biodiversity and human well-being, there is a growing need to understand how land use stock and flow changes over time through land use accounting. While existing studies on land accounting have focused on historical land changes, little attention has been paid to future transitions. This study assessed historical patterns and projected future shifts in land use dynamics from 1987 to 2050 across Japan by combining high-resolution land use and land cover datasets, land change simulations, and land accounting. In the analyses, particular attention was paid to the historical and future trends of farmland abandonment by leveraging data at 100-m resolution built on national vegetation surveys. High-resolution analysis of farmland abandonment issue with national scale in Japan is a novelty. From 1987 to 1998, the land stock analysis results showed a pronounced marked increase in residential land (10.4%) and grassland (16.9%); the flow analysis results showed that urban residential sprawl expansion was mainly formed by secondary (32.6%) and plantation (21.1%) forest areas, coinciding with increasing population and economic growth. Projections from 2010 to 2050 indicate a marked increase in abandoned farmland (67.2% per decade), a trend influenced by rapid population decline and presumably agricultural policies, especially significant in regions such as Hokkaido and Kyushu. The findings of this study are crucial for shaping policy and decision-making, underlining the need for sustainable land management strategies that effectively balance urban growth, agricultural productivity, and environmental preservation in Japan.
Hip fracture rate and osteoporosis treatment in Ontario: A population-based retrospective cohort study
Authors: AbuAlrob Hajar , Ioannidis George , Jaglal Susan , Costa Andrew , Grifith Lauren E. , Thabane Lehana , Adachi Jonathan D. , Cameron Cathy , Hillier Loretta , Lau Arthur , Papaioannou Alexandra
Published: June 2024

Summary

This population-based study analyzes hip fracture and osteoporosis treatment rates among older adults, stratified by place of residence prior to fracture. Hip fracture rates were higher among older adults living in the community and discharged to long-term care (LTC) after fracture, compared to LTC residents and older adults living in the community. Only 23% of LTC residents at high fracture risk received osteoporosis treatment.

Purpose

This population-based study examines hip fracture rate and osteoporosis management among long-term care (LTC) residents > 65 years of age compared to community-dwelling older adults at the time of fracture and admitted to LTC after fracture, in Ontario, Canada.

Methods

Healthcare utilization and administrative databases were linked using unique, encoded identifiers from the ICES Data Repository to estimate hip fractures (identified using the Public Health Agency of Canada algorithm and International Classification of Diseases (ICD)-10 codes) and osteoporosis management (pharmacotherapy) among adults > 66 years from April 1, 2014 to March 31, 2018. Sex-specific and age-standardized rates were compared by pre-fracture residency and discharge location (i.e., LTC to LTC, community to LTC, or community to community). Fracture risk was determined using the Fracture Risk Scale (FRS).

Results

At baseline (2014/15), the overall age-standardized hip fracture rate among LTC residents was 223 per 10,000 person-years (173 per 10,000 females and 157 per 10,000 males), 509 per 10,000 person-years (468 per 10,000 females and 320 per 10,000 males) among the community to LTC cohort, and 31.5 per 10,000 person-years (43.1 per 10,000 females and 25.6 per 10,000 males). During the 5-year observation period, the overall annual average percent change (APC) for hip fracture increased significantly in LTC (AAPC =  + 8.6 (95% CI 5.0 to 12.3; p = 0.004) compared to the community to LTC group (AAPC =  + 2.5 (95% CI − 3.0 to 8.2; p = 0.248)) and the community-to-community cohort (AAPC − 3.8 (95% CI − 6.7 to − 0.7; p = 030)). However, hip fracture rate remained higher in the community to LTC group over the study period. There were 33,594 LTC residents identified as high risk of fracture (FRS score 4 +), of which 7777 were on treatment (23.3%).

Conclusion

Overall, hip fracture rates have increased in LTC and among community-dwelling adults admitted to LTC after fracture. However, hip fracture rates among community-dwelling adults have decreased over time. A non-significant increase in osteoporosis treatment rates was observed among LTC residents at high risk of fracture (FRS4 +). Residents in LTC are at very high risk for fracture and require individualized based on goals of care and life expectancy.
Expression and Relations of Unique miRNAs Investigated in Metabolic Bariatric Surgery: A Systematic Review
Authors: Hany Mohamed , Demerdash Hala M , Abouelnasr Anwar Ashraf , Torensma Bart
Published: June 2024

Several studies have indicated that miRNAs play crucial roles in adipogenesis, insulin resistance, and inflammatory pathways associated with obesity and change after metabolic bariatric surgery (MBS). This systematic review explores and maps the existing literature on how miRNAs are expressed and investigates the unique miRNAs with the effects after MBS. The Cochrane Central Register of Controlled Trials (CENTRAL), PubMed, and EMBASE were searched from 2019 until February 2024. This SR found 825 miRNAs from 25 studies, identifying 507 unique ones not used twice in the same study. A total of 21 studies (84%) measured RNA before and after surgery. The miRNA used per study ranged from 1 to 146 miRNA types, with a median study sample size of just 27 patients per study, raising concerns about some conclusions’ robustness. From the 507 unique miRNAs, only 16 were consistently analyzed in 4 to 7 studies, which gave 77 different outcomes in relation to miRNA after MBS. MiRNA 122 and 122-5p were analyzed the most. Others were 106b-5p, 140-5p, 183-5p, 199b-5p, 20b-5p, 424-5p, 486-5p, 7-5p, 92a, 93-5p, 194-5p, 21-5p, 221, 320a, and 223-3p. A gap was observed in many studies, whereby the results were not the same, or there was no explanation for the effects after MBS was given within the same miRNA. Fifteen miRNAs were reported to have the same upward and downward trend, although not within the same study, and only 26.1% employed some form of statistical modeling to account for bias or confounding factors. Directions and effects in miRNA are visible, but still, inconsistent outcomes linked to the same miRNA after MBS, underscoring the need for clarity in miRNA-outcome relationships. Collaborative efforts, consensus-driven miRNA dictionaries, and larger, more rigorous studies are necessary to improve methodology designs and improve outcomes.
Dirichlet Problem for Nonlinear Higher-Order Equations in Upper Half Plane
Authors: Gökgöz Pelin Ayşe
Published: June 2024

In this article, we consider the Dirichlet problem for nonlinear higher-order equations in upper half plane. Firstly we introduce the solutions of inhomogeneous polyanalytic equation in upper half plane. Then we investigate the properties of relevant integral operators. Lastly we transform the Dirichlet problem for nonlinear higher-order equations in upper half plane into the system of integro-differential equations and we obtain the existence of unique solution using Banach fixed point theorem.
Review of Small Modular Reactors: Challenges in Safety and Economy to Success
Authors: Lee Jeong Ik
Published: June 2024

This paper explores the paradigm shift in nuclear energy generation from large, centralized nuclear power plants towards small modular reactors (SMRs), in response to the evolving economic, safety, and environmental challenges faced by the nuclear industry. For over 70 years, nuclear power has been a cornerstone of electricity generation, offering a low-carbon, reliable, and cost-effective solution. However, the traditional model of large-scale nuclear reactors has encountered significant barriers, including high financial risks, stringent safety concerns, and a lack of adaptability to smaller electrical grids, and changing energy markets. With over 70 types of SMRs currently under development globally, this study reviews several prominent models to assess their general characteristics and potential advantages. Through simple physical and economic models, the paper evaluates the impact of reducing reactor size on efficiency, safety, and cost, highlighting the shared traits and innovations across different SMR designs. The findings indicate that SMRs could address many of the limitations of conventional nuclear power, offering more flexible, scalable, and economically viable options for electricity generation. This paper finally tries to identify key technologies and strategic considerations essential for their successful deployment in a rapidly transforming global energy landscape.
Playing for peace: scoping review of sports programs as agents of peace
Authors: Rodríguez Sebastián , León-Prieto Catalina , Rodríguez-Jaime María Fernanda , Lugo Lady Stephania
Published: June 2024

The quest for peace and stability in contemporary society, particularly in conflict-affected regions, is of vital importance. In the 21st century, sport has evolved beyond its traditional role of entertainment and competition to become a powerful force for change. Its ability to bring people together, overcome cultural barriers and promote universal values makes it an effective vehicle for promoting peace and coexistence. Despite the undeniable potential of sport as a social bridge between divided communities, previous studies have not specifically addressed the concept of peace. In addition, researchers may need information on existing programs for study, replication or improvement. This study aims to provide an overview of programs that use sport to promote peace. Following the guidelines of the Joanna Briggs Institute and PRISMA, databases such as Scopus, PubMed, SciELO and EBSCO were searched. Two reviewers independently performed a thorough selection, including 17 manuscripts. The predominant methodology in these studies was qualitative. Within this context, most of the experiences recovered took place in Colombia, with soccer being the most used sport modality in such programs. These programs are presented as a tool to promote peace in diverse contexts of conflict, violence and community division, and their capacity to be instrumentalized for peaceful purposes is remarkable, even surpassing the capacity of States to regulate and resolve conflicts.
miR-200a-3p promotes the malignancy of endometrial carcinoma through negative regulation of epithelial-mesenchymal transition
Authors: Ma Ying , Wang Yiru , Wang Can , Wang Yan , Hu Jingshu , Zhang Zexue , Dong Tuo , Chen Xiuwei
Published: June 2024

Background

miR-200a-3p is involved in the progression of malignant behavior in various tumors, and its mechanism of action in endometrial cancer is speculated to be related to epithelial-mesenchymal transition (EMT). Therefore, this study explored the metastatic mechanism of miR-200a-3p and EMT in endometrial cancer, with the aim of identifying potential therapeutic targets.

Methods

qRT-PCR was used to analyze miR-200a-3p expression in HEC-1B and Ishikawa cell lines. The cell proliferation assay, transwell assay, and cell scratch test were used to assess changes in the malignant phenotypes of cells after regulating miR-200a-3p expression. Changes in EMT-related protein zinc finger E-box binding homeobox 1 (ZEB1) were detected after regulating miR-200a-3p expression. An endometrial carcinoma transplantation mouse tumor model was constructed, and multiple EMT-related proteins were examined.

Results

The expression of miR-200a-3p and ZEB1 in the endometrial cancer cell lines was higher than in normal endometrial epithelial cell lines (P < 0.05). After silencing miR-200a-3p, the expression of EMT-related protein ZEB1 increased, indicating a negative correlation. Simultaneously, the proliferation, invasion, and metastasis of endometrial cancer cells were significantly enhanced. After miR-200a-3p overexpression, the corresponding malignant phenotype was reversed (P < 0.05). In in vivo experiments, the degree of tumor malignancy and the expression level of EMT-related proteins were significantly reduced in the miR-200a-3p mimic group (P < 0.05).

Conclusion

This study found that miR-200a-3p is a promising target, regulating the EMT process and promoting endometrial cancer progression.
One-way ticket to the moon? An NLP-based insight on the phenomenon of small-scale neo-broker trading
Authors: Kant Gillian , Zhelyazkov Ivan , Thielmann Anton , Weisser Christoph , Schlee Michael , Ehrling Christoph , Säfken Benjamin , Kneib Thomas
Published: June 2024

We present an Natural Language Processing based analysis on the phenomenon of “Meme Stocks”, which has emerged as a result of the proliferation of neo-brokers like Robinhood and the massive increase in the number of small-scale stock investors. Such investors often use specific Social Media channels to share short-term investment decisions and strategies, resulting in partial collusion and planning of investment decisions. The impact of online communities on the stock prices of affected companies has been considerable in the short term. This paper has two objectives. Firstly, we chronologically model the discourse on the most prominent platforms. Secondly, we examine the potential for using collaboratively made investment decisions as a means to assist in the selection of potential investments.. To understand the investment decision-making processes of small-scale investors, we analyze data from Social Media platforms like Reddit, Stocktwits and Seeking Alpha. Our methodology combines Sentiment Analysis and Topic Modelling. Sentiment Analysis is conducted using VADER and a fine-tuned BERT model. For Topic Modelling, we utilize LDA, NMF and the state-of-the-art BERTopic. We identify the topics and shapes of discussions over time and evaluate the potential for leveraging information of the decision-making process of investors for trading choices. We utilize Random Forest and Neural Network Models to show that latent information in discussions can be exploited for trend prediction of stocks affected by Social Network driven herd behavior. Our findings provide valuable insights into content and sentiment of discussions and are a vehicle to improve efficient trading decisions for stocks affected from short-term herd behavior.
Assessing and Monitoring Nutrition Security in the United States: A Narrative Review of Current Measures and Instruments
Authors: Kenney Emma , Adebiyi Victoria O. , Seligman Hilary K. , Ehmke Mariah D. , Guthrie Joanne F. , Coleman-Jensen Alisha , Frongillo Edward A.
Published: June 2024

Purpose of Review

Because nutrition plays a crucial role in the development of chronic diseases, ensuring nutrition security is important for promoting population health. Nutrition security is defined as having consistent and equitable access to healthy, safe, affordable foods essential to optimal health and well-being. Distinguished from food security, nutrition security consists of two constructs: healthy diets and nutritional status. The study aimed to identify population measures that reflect the important constructs of nutrition security (i.e., healthy diets and nutritional status) to inform U.S. nutrition security assessment and monitoring.

Recent Findings

Through a narrative review conducted across multiple databases, associations between subconstructs of healthy diets and nutritional status were identified. Of the six subconstructs that constitute healthy diets, nutrient adequacy and moderation were most often used to assess and monitor healthfulness of U.S. population diets and were associated with health outcomes. There is little evidence of an association between health outcomes and macronutrient balance or diversity in the U.S. Thirteen instruments were identified as potentially suitable for measuring at least one subconstruct of healthy diet in the population.

This review highlights the importance of nutrition security in addressing population health challenges. It emphasizes the potential use of multiple instruments and measures to comprehensively monitor population nutrition security and inform intervention strategies. Identifying feasible and practical measures for assessing and monitoring nutrition security is imperative for advancing population health and mitigating the burden of chronic diseases.
Measuring Circularity in Life Cycle Management: A Literature Review
Authors: Basile Vincenzo , Petacca Nunzia , Vona Roberto
Published: June 2024

Circularity has emerged as a pivotal concept in the realm of sustainable resource management and business operations. Resource exhaustion and environmental degradation propelled by globalization and the culture of consumerism have intensified the focus on the concept of the circular economy around the world. Nevertheless, the evaluation and quantification of circularity achievements remain uncommon in corporate practices. This article employs a systematic literature review to delve into circularity measurements in the managerial life cycle. Key approaches emerging from the academic literature are examined, including life cycle costing, life cycle assessment, life cycle cost–benefit, life cycle benefit analysis, and life cycle sustainability assessment. The review seeks to offer a comprehensive overview of the methodologies employed to assess circularity in corporate processes, highlighting current challenges and opportunities for effective implementation. We adopt a conceptual model of sustainable and circular life cycle management based on specific performance indicators that allow the environmental, social, and economic impact of processes to be assessed throughout the life cycle of products or services. The implementation of Sustainable and Circular Life Cycle Management from a managerial perspective could support firms to eradicate and quantify waste, preserve the inherent value of products and materials, encourage the adoption of renewable energies, and eliminate harmful chemicals.
Polymer transfer film formation from cryogenic to elevated temperatures
Authors: Bashandeh Kian , Tsigkis Vasilis , Amiri Ahmad , Lan Pixiang , Polycarpou Andreas A.
Published: June 2024

This study reports on the tribological performance of aromatic thermosetting co-polyester (ATSP) and polyether ether ketone (PEEK)-based polymer composite coatings mixed with PTFE filler. The coatings were tested across a wide temperature range from −180 to 110 °C to simulate the environmental temperatures on Titan, Moon, and Mars, which are of particular interest for NASA’s future exploratory missions. An experimental setup was developed to conduct the pin-on-disk experiments under dry sliding conditions and extreme temperature and contact pressure. Transfer film formation and its characteristics were found to play significant roles in the tribological performance, and the characteristics of the film were temperature-dependent. The XPS and SEM analysis indicated the increase of the PTFE content in the transfer film as the temperature decreased to cryogenic conditions. The coefficient of friction did not follow a linear trend with temperature and was minimum at 110 °C and maximum at −180 °C. ATSP coating showed superior performance with lower friction and unmeasurable wear at all temperatures, whereas PEEK coating exhibited maximum wear at 25 °C followed by −180, and 110 °C.