bluuebunny/crossref_metadata_2025_split huggingface dataset:
Towards environmentally sustainable water management in Africa: a comprehensive review of life cycle assessment studies in water and wastewater treatment
Authors: Ogbu Charles Amarachi , Alexiou Ivanova Tatiana , Ewemoje Temitayo Abayomi , Alabi Habeeb Adedotun , Roubík Hynek 
Published: February 2025

Abstract

Purpose
Life cycle assessment (LCA) provides a comprehensive methodology to evaluate the environmental impacts of products, processes, and services based on the net flow of energy, materials, and emissions throughout their life cycle. This review focuses on the state of LCA in water and wastewater treatment in Africa, aiming to ascertain the extent of its implementation while synthesising the existing challenges and opportunities.

Methods
The articles were selected using the systematic review checklist of the standardised technique for assessing and reporting reviews of LCA. Strings of keywords were used to search for articles on the Web of Science, Scopus, and Google Scholar databases. Only original articles that assessed at least the water or wastewater treatment process using the ISO 14040/14044 LCA methodology were included. Case studies included were carried out in Africa.

Results and discussion
A total of 41 studies containing 131 scenarios were found. Over 68% of the studies originated from South Africa and Egypt, with a notable absence of representation from Nigeria and Tunisia. Urban wastewater treatment was assessed in 41% of the studies, 37% covered industrial, and 7% focused on domestic. In total, 15% was dedicated to water treatment. Only 32% of all studies considered the entire life cycle. The ReCiPe and CML were the most popular impact assessment methods. Biosolids and nutrient recovery were covered in 23% and 9% of the studies, respectively. Global warming potential was the most influential impact category, and electricity generation from fossil fuels was the major contributor to adverse environmental impacts.

Conclusions
The review emphasises the need for increased data acquisition and storage, renewable energy use, and material recovery to offset environmental impacts in the water and wastewater sectors. It highlights the importance of integrating LCA into engineering design, engaging stakeholders in LCA, and establishing performance standards for green innovations. Future research and policy development to promote sustainable treatment practices are advocated.
Isolation and single-molecule magnetism of neutral rare-earth(III) sandwich complexes supported by compact aromatic rings
Authors: Liu Ming , Chen Yan-Cong , Zheng Jieyu , Peng Xiao-Han , Tong Ming-Liang , Mansikkamäki Akseli , Guo Fu-Sheng 
Published: February 2025

Abstract
Over the past few decades, various types of metal-sandwich structures have been synthesized and reported, which significantly advanced organometallic chemistry and contributed to numerous applications. However, charge-neutral rare-earth(III) sandwich structures based on compact aromatic ligands still remained unexplored due to the challenges in their synthesis. Nevertheless, the immense potential of this type of structure in building high-performance single-molecule magnets (SMMs) has compelled us to overcome these synthetic obstacles. Herein, we aimed to isolate such complexes in a general formula of [(Ring1)REIII(Ring2)]. [(C4B)Et4Me2NREIII(Cp
iPr5)] (3-RE, RE = Y, Dy; (C4B)Et4Me2N = 1-(N,N-dimethylamino)-2,3,4,5-tetraethylborolyl; Cp
iPr5 = pentaisopropylcyclopentadienyl) were successfully obtained via the salt-metathesis reaction of the precursor [REIII(Cp
iPr5)(BH4)2-(THF)] (1-RE, RE = Y, Dy; THF = tetrahydrofuran) and the new aminoborolide ligand [Na2(C4B)Et4Me2N(THF)2]2 (2), which represent the first neutral rare-earth(III)-sandwich complexes ligated by compact aromatic ligands. Both complexes 3-RE were characterized by single-crystal X-ray diffraction, elemental analysis, UV-Vis-NIR and FTIR. Diamagnetic 3-Y was studied by NMR spectroscopy. Static and dynamic magnetic properties of 3-Dy were investigated by SQUID magnetometry, showing a high anisotropy barrier of 785(12) cm−1 and open hysteresis loops up to 12 K. The bonding of nitrogen to dysprosium(III) near the equatorial plane lowers the anisotropy, and a bulkier ligand in the future should be able to avoid this. This work not only demonstrates that such type of neutral rare-earth(III)-sandwich complexes is totally synthetically feasible, but also paves the way for the development of high-performance SMMs.
Mathematical Model of CAR T-Cell Therapy for a B-Cell Lymphoma Lymph Node
Authors: Sabir Soukaina , León-Triana Odelaisy , Serrano Sergio , Barrio Roberto , Pérez-García Victor M. 
Published: February 2025

Abstract
CAR T-cell therapies have demonstrated significant success in treating B-cell leukemia in children and young adults. However, their effectiveness in treating B-cell lymphomas has been limited in comparison to leukemia. In this paper we present a mathematical model that elucidates the dynamics of diffuse large B-cell lymphoma and CAR T-cells in a lymph node. The mathematical model aids in understanding the complex interplay between the cell populations involved and proposes ways to identify potential underlying dynamical causes of treatment failure. We also study the phenomenon of immunosuppression induced by tumor cells and theoretically demonstrate its impact on cell dynamics. Through the examination of various response scenarios, we underscore the significance of product characteristics in treatment outcomes.
In Silico Discovery of Antigenic-Secreted Proteins to Diagnostic Human Toxocariasis
Authors: Henao María A. , Cortes Isabella , Isaza Juan P. 
Published: February 2025

Abstract

Background
Human toxocariasis is a helminthic zoonosis caused by infection of Toxocara canis or T. cati. Humans can be infected by through ingestion of embryonated eggs from contaminated water, food or soil. Diagnosis is challenging, immunodiagnosis tests are commonly implemented with major pitfalls in the cross-reactivity with other pathogens, particularly in endemic areas.

Methods
With the aim of identify species-specific genes encoding for highly expressed antigenic proteins, a list of parasites that may infect humans and that might present similar clinical symptoms to T. canis infections was built. Only organisms whose genomes were completely sequenced and the proteome predicted were included. First, orthologous proteins were detected and the subcellular localization of T. canis proteins was predicted. In order to identify differentially expressed genes encoding proteins in larvae L3, pair-wise comparisons among transcriptomes from body parts and genders were performed. Finally, all secreted proteins classified as species-specific of T. canis, whose genes were upregulated in larvae L3 were included in an antigenic prediction.

Results
Twenty-eight parasites were included in the analyses, proteins of T. canis were clustered in 11,399 groups, however, 279 were species-specific groups which represent 816 proteins. Three hundred and twenty-two proteins were predicted to be secreted and upregulated in larvae L3, however, after filtering these proteins by their orthology inference, only three proteins met all the features included in this study (species-specific, upregulated, secreted, and antigenic potential). To conclude, our strategy in the study is a rational approach for discovering antigenic proteins to be used in diagnosis.
Development of a 3D-knee brace joint using MRI data and a genetic algorithm
Authors: Schmid Quirin T. , Ruschke Stefan , Karampinos Dimitrios C. , Senner Veit 
Published: February 2025

Abstract
Approximately 40% of sports-related injuries affect the knee joint, with the anterior cruciate ligament particularly susceptible to injury. The use of knee orthoses for the prevention of knee injuries has become a common practice in sports such as ice hockey, American football, and alpine skiing. However, orthoses cannot accurately reproduce the complex kinematics of the knee. This might be associated with a decrease in performance and comfort. This study aims to improve the congruence between orthotic joints and a measured knee motion. Knee kinematics of four male participants were recorded using a combination of video motion capture and MRI. Finite helical axes were computed to design the new orthotic joint. The new joint consists of two four-bar linkages optimized by a genetic algorithm to approximate the finite helical axis positions. A multi-body simulation was used to determine the change of constraining forces in the knee using the new orthosis compared to a conventional one. The mean squared error between knee and orthosis motions for the medial joint parts was 0.07 to 2.04 mm and 1.1 to 10.65 mm for the lateral joints. The total MSE was 3.46 mm. The simulation results showed substantially reduced constraining forces for the new joint, indicating a better match with natural knee kinematics. This improvement could increases orthosis effectiveness and comfort, thereby accelerating the healing process. In conclusion, the introduced approach allows a more accurate replication of the knee’s natural movement, thereby minimizing constraining forces in the knee and possibly improving comfort.
Reconfiguring International Security – The Strategic Evolution of Modern Warfare
Authors: Schäfer Philip Jan 
Published: February 2025

Abstract
This paper delves into the evolving nature of international security, focusing on the strategic transformations within military thought and practice that are increasingly shaping global power dynamics. Moving beyond the traditional emphasis on high-level political decisions, it is argued that the day-to-day practices of military institutions, especially their adaptations to modern warfare, play a crucial role in defining a state’s international stance. This is shown by analyzing the development of new conceptual frameworks within NATO and the PLA.
How instructors use learning analytics: the pivotal role of pedagogy
Authors: Li Qiujie , Jung Yeonji , Wise Alyssa Friend 
Published: February 2025

Abstract
This study fills a gap in knowledge regarding experienced instructors’ use of learning analytics, focusing on differences in their approach, the knowledge and skills they activate, and the development of these knowledge and skills. Through a qualitative analysis of think-aloud interviews with 13 analytics-experienced instructors, two distinct profiles of analytics use emerged. Instructors in the first profile prioritized monitoring student engagement and performance to foster desirable behaviors, using analytics to align students with course expectations. Instructors in the second profile focused on understanding student perceptions of learning, aligning the course design with diverse learning behaviors and needs. To arrive at such use, instructors went beyond mere acquisition of technical knowledge to also integrate pedagogical knowledge into their analytics practices. Lastly, the study uncovered specific learning analytics supports, such as ongoing individual consultations, invaluable for developing the needed technical and pedagogical knowledge. Together, the results of this study reveal the pivotal role of pedagogy in analytics use, calling for refinement of conceptual models and tailoring of practical support for instructors.
Mindfulness-Based Intervention to Reduce Sensitivity to Anxiety in a Spanish Primary Education Setting
Authors: García-Lorenzo Rut , Carbonero-Martín Miguel Ángel , Valdivieso-León Lorena , Izar-de-la-Fuente Iker 
Published: February 2025

Abstract

Objectives
Mindfulness involves the ability to pay full and conscious attention to what is happening in the present moment. Scientific evidence supports its benefits in the educational field, contributing to the development of strategies that help students cope academically, socially and emotionally. Meta-analyses on mindfulness in the Spanish educational context reported significant improvements along the same lines. The aim of this study was to determine whether a mindfulness-based intervention for primary school students improved their sensitivity to anxiety.

Method
A total of 352 students (170 boys, 182 girls) aged 6 to 12 years participated in Spain. A quasi-experimental pre-test-post-test design was used, with experimental group (266 students) and control group (86 students). Anxiety sensitivity was measured with the Anxiety Sensitivity Index for Children. The intervention followed a sequential learning order based on the Mindfulness-Based Stress Reduction (MBSR) programme.

Results
A significant decrease in anxiety sensitivity was observed in the post-intervention measure. Additionally, comparisons of pre-test and posttest scores in the control group revealed significant differences. In terms of effect size, the difference between pre- and post-intervention scores was close to medium (Cohen's d = 0.43).

Conclusions
The efficacy of the programme was confirmed, and it was shown that the mindfulness intervention was beneficial; in the experimental group, anxiety sensitivity decreased significantly compared to that in the control group after participation in the programme.
Learning-based pattern-data-driven forecast approach for predicting future well responses
Authors: Kim Yeongju , Min Baehyun , Sun Alexander , Ren Bo , Jeong Hoonyoung 
Published: February 2025

Abstract
Forecasting well responses, such as flow rates and pressures, is crucial for effective reservoir management and investment decision-making in the development of subsurface reservoir resources. Recently, data-driven forecast methods, such as data-space inversion (DSI) and a learning-based data-driven forecast approach (LDFA), have been introduced to mitigate the computational cost and geological constraint issues of history-matching methods. However, DSI and LDFA have extrapolation, conditioning, and prediction variance issues. In this study, we propose two simpler alternatives, a learning-based pattern-data-driven forecast approach (LPFA) and an ensemble conditioning step (ECS), to resolve the issues associated with DSI and LDFA. LPFA mitigates the extrapolation issue by scaling well responses for each instance using the mean and variance of an observation period. ECS addresses the conditioning and prediction variance issues of LDFA and LPFA by combining predictions of multiple learning models and screening out predictions that do not sufficiently honor observed data. The prediction performances of DSI, LDFA, LPFA, and ECS were compared using two benchmark models: Brugge and Olympus models. Among these methods, LPFA provided the most accurate predictions for future well responses and reasonable uncertainty intervals, achieving an error of 2.3%. Even when predicting well responses outside the range of prior data, LPFA maintained a prediction error of 4.8%, unlike the other methods whose performance significantly declined. ECS improved the prediction accuracy by 1–2% and reduced the uncertainty in the predictions of future well responses by approximately 50%. Our approaches are generic and can be integrated with other data-driven forecast methods to enhance prediction performance.
Exploring the therapeutic potential of oleanolic acid and its derivatives in cancer treatment: a comprehensive review
Authors: D’Mello Rachel Savio , Mendon Vividh , Pai Padmini , Das Ipshita , Sundara Babitha Kampa 
Published: February 2025

Abstract
Oleanolic acid (OA) is a triterpenoid that occurs naturally and may be isolated from various plants. Analogs of oleanolic acid can be produced artificially or naturally. The current treatments have limited selectivity and may also impact normal cells. OA and its derivatives provide a promising cancer treatment platform with greater selectivity and less toxic effects. As a result of their enhanced sensitivity, selectivity, and low toxicity, they are great options for focusing on particular biological pathways and reducing the growth of tumor cells. The effects of OA and derivatives of OA on various cancer types have been investigated. However, breast and hepatocellular malignancies are the most studied cancers. In breast cancer, derivatives such as saikosaponin A (SSa), saikosaponin B (SSb), and SZC014 influence key pathways such as the Janus kinase/signal transducer and activator of transcription (JAK/STAT), protein kinase-B (Akt), and nuclear factor-kappa B (NF-κB) pathways, inhibiting metastasis, angiogenesis, and cell migration, respectively. When a para-aminobenzoic acid (PABA)/nitric oxide (NO) derivative of OA is administered to HepG2 cells, the reactive oxygen species (ROS)/mitogen-activated protein kinase (MAPK)-mediated mitochondrial pathway causes apoptosis. Nanoformulations incorporating OA, such as OA-paclitaxel (PTX), show potential for suppressing tumor progression by inhibiting drug efflux mechanisms. Thus, exploring the interactions of OA and a few of its derivatives with various cellular pathways offers a promising approach to combating different types of cancer. This review delves into the potential of oleanolic acid and its derivatives in retarding cancer progression through their interactions with diverse cellular pathways.
Evaluation of systemic inflammatory response following transcatheter aortic valve replacement: a pathway to rational antibiotic use
Authors: Guthoff Henning , Lohner Valerie , Mons Ute , Götz Julia , Wienemann Hendrik , Wrobel Jan , Nienaber Stephan , Macherey-Meyer Sascha , von Stein Philipp , Baldus Stephan , Adam Matti , Körber Maria Isabel , Jung Norma , Mauri Victor 
Published: February 2025

Abstract

Purpose
Elevations in inflammatory markers after transcatheter aortic valve replacement (TAVR) often lead to preemptive antibiotic therapy (ABT). Distinguishing between physiological inflammatory reaction and true infection is crucial for rational ABT use.

Methods
This retrospective study included 1275 consecutive TAVR patients from January 2020 to July 2022. Infectious foci, ABT administration, and inflammatory markers over seven days post-procedure were evaluated. Using multivariable logistic regression, predictors for infection were identified and integrated into the Risk of Infection After TAVR (RIAT) score.

Results
An infectious focus was retrospectively identified in 2.6% of patients, while 11.4% received ABT. Distinct trends in body temperature (BT), white blood cells (WBC), and C-reactive protein (CRP) were noted, with BT and WBC peaking on day 1 and CRP on day 3. Significant predictors of infection included a rise in BT of ≥ 0.2 °C between day 1 and 3 (odds ratio [OR] 3.08, 95% confidence interval [CI] 1.38–6.88, p = 0.006), elevated WBC counts ≥ 12 × 109/L (OR 3.77, 95% CI 1.67–8.48, p = 0.001), and CRP levels ≥ 80 mg/L (OR 5.72, 95% CI 2.59–12.64, p < 0.001) within three days after TAVR. Integrating these into the RIAT score revealed an infection probability of 1.5% for scores 0–3 points, 9.2% for scores 4–6 points, and 54.5% for scores 7–8 points.

Conclusion
Our findings indicate significant ABT overuse among TAVR recipients, likely due to misinterpretation of postoperative physiological reactions. Incorporating specific changes and thresholds of BT, WBC, and CRP post-TAVR into the RIAT score improved risk prediction for infection, underscoring its utility in enhancing antibiotic stewardship in this growing patient population.
A Team Approach: How the LEND Program Can Provide Interdisciplinary Training for Behavior Analysts
Authors: Vincent Lori B. , Scott Meagan , Weber Stephanie , Srivorakiat Laura , Stepanek Mary , Smith Jennifer 
Published: February 2025

Abstract
Supporting people with neurodevelopmental disabilities often requires interdisciplinary collaboration and effective partnerships with clients and their families. Behavior analysts receive intensive training and supervision in a variety of domains; however, expanding interdisciplinary training for behavior analysts is needed. Interdisciplinary training programs, such as the Leadership Education in Neurodevelopmental and Related Disabilities (LEND) programs, offer trainees the opportunity to hone their skills as advocates for people with neurodevelopmental disabilities and collaborators as part of an interdisciplinary team. Historically, many LEND programs have not offered training positions specifically to behavior analysis students or professionals, although some behavior analysts have participated as trainees in other disciplines such as psychology or special education. The benefits, barriers, and possible future directions of interdisciplinary training for behavior analysts within a LEND program are discussed through the experience of the University of Cincinnati LEND Program which added an Applied Behavior Analysis (ABA) training track in 2020.
Vehicle-to-Everything Communication in Intelligent Connected Vehicles: A Survey and Taxonomy
Authors: Zhang Xinyu , Li Junxian , Zhou Jingyi , Zhang Shiyan , Wang Jingyuan , Yuan Yi , Liu Jiale , Li Jun 
Published: February 2025

Abstract
This paper conducts a thorough exploration of vehicle-to-everything (V2X) communication in the realm of intelligent connected vehicles (ICVs). It initiates by tackling challenges across three pivotal phases of cooperative communication: pre-communication, during-communication, and post-communication. The discourse delves into a spectrum of concepts and strategies to surmount these challenges. Furthermore, it meticulously scrutinizes diverse communication scenarios and associated techniques, evaluating their significance and feasibility. Moreover, an in-depth analysis of various datasets is undertaken, considering their distinctive attributes and suitability for diverse communication tasks. The paper critically examines and debates the platforms and frameworks used in the experiments, providing valuable insights into their performance. Following a comprehensive review of existing methods and datasets, the paper identifies potential research directions and challenges that warrant further exploration in the realm of V2X communication for intelligent connected vehicles. This comprehensive examination contributes to a deeper understanding of the subject, paving the way for future advancements in this dynamic field.
State-of-art of in situ observations of inclusion agglomeration at steel/Ar and steel/slag interfaces: a review of recent development on experimental and theoretical studies
Authors: Wang Yi , Fu Jian-xun , Kumar Deepoo , Wang Qiang , Yang Hong-liang , Mu Wang-zhong 
Published: February 2025

Abstract
Cleanliness control of advanced steels is of vital importance for quality control of the products. In order to understand and control the inclusion removal during refining process in molten steel, its motion behaviors at the multiple steel/gas/slag interfaces have attracted the attention much of metallurgical community. The recent development of the agglomeration of non-metallic inclusions at the steel/Ar and steel/slag interfaces has been summarized, and both the experimental as well as theoretical works have been surveyed. In terms of in situ observation of high-temperature interfacial phenomena in the molten steel, researchers utilized high-temperature confocal laser scanning microscopy to observe the movement of more types of inclusions at the interface, i.e., the investigated inclusion is no longer limited to Al2O3-based inclusions but moves forward to rare earth oxides, MgO-based oxides, etc. In terms of theoretical models, especially the model of inclusions at the steel/slag interface, the recent development has overcome the limitations of the assumptions of Kralchevsky–Paunov model and verified the possible errors caused by the model assumptions by combining the water model and the physical model. Last but not least, the future work in this topic has been suggested, which could be in combination of thermal physical properties of steels and slag, as well as utilize the artificial intelligence-based methodology to implement a comprehensive inclusion motion behaviors during a comprehensive metallurgical process.