bluuebunny/crossref_metadata_2025 huggingface dataset:
Stray urbanism: stray donkeys and place-identity in Makhanda, South Africa
Authors: Irvine Philippa Margaret , Memela Sinenhlanhla , Kondile Lisa
Published: June 2024

The presence of free-roaming livestock in cities is often seen as something that should be regulated, and zoning practices across the world generally attempt to restrict their presence or ensure their absence in urban areas. Apart from the health and safety reasoning behind such regulations, there is also a juxtaposition inherent within the presence of livestock in urban areas. This juxtaposition relates to the rural–urban dichotomy which presupposes that the presence of livestock is a rural characteristic and not an urban one. The present research challenges this dichotomy with the case study of Makhanda, South Africa. It utilises southern Urbanism and the contribution of donkeys to the place-identity of the city to frame this discussion. This paper used an online survey with residents of the city as well as key informant interviews to understand the layers of meaning that exist within local opinions on stray donkeys. It found that donkeys were seen by many as integral to the character or place-identity of the city. They were seen as both positive and negative symbols of the city – illustrating the juxtapositions within urban settlements and urbanism in southern cities. In this way, the case study reiterates the call from southern scholars to contextualise, reconceptualise and reframe urban theory so that is responsive to southern environments and experiences.
Injecting the score of the first-stage retriever as text improves BERT-based re-rankers
Authors: Askari Arian , Abolghasemi Amin , Pasi Gabriella , Kraaij Wessel , Verberne Suzan
Published: June 2024

In this paper we propose a novel approach for combining first-stage lexical retrieval models and Transformer-based re-rankers: we inject the relevance score of the lexical model as a token into the input of the cross-encoder re-ranker. It was shown in prior work that interpolation between the relevance score of lexical and Bidirectional Encoder Representations from Transformers (BERT) based re-rankers may not consistently result in higher effectiveness. Our idea is motivated by the finding that BERT models can capture numeric information. We compare several representations of the Best Match 25 (BM25) and Dense Passage Retrieval (DPR) scores and inject them as text in the input of four different cross-encoders. Since knowledge distillation, i.e., teacher-student training, proved to be highly effective for cross-encoder re-rankers, we additionally analyze the effect of injecting the relevance score into the student model while training the model by three larger teacher models. Evaluation on the MSMARCO Passage collection and the TREC DL collections shows that the proposed method significantly improves over all cross-encoder re-rankers as well as the common interpolation methods. We show that the improvement is consistent for all query types. We also find an improvement in exact matching capabilities over both the first-stage rankers and the cross-encoders. Our findings indicate that cross-encoder re-rankers can efficiently be improved without additional computational burden or extra steps in the pipeline by adding the output of the first-stage ranker to the model input. This effect is robust for different models and query types.
Verifying a Sequent Calculus Prover for First-Order Logic with Functions in Isabelle/HOL
Authors: From Asta Halkjær , Jacobsen Frederik Krogsdal
Published: June 2024

We describe the design, implementation and verification of an automated theorem prover for first-order logic with functions. The proof search procedure is based on sequent calculus and we formally verify its soundness and completeness in Isabelle/HOL using an existing abstract framework for coinductive proof trees. Our analytic completeness proof covers both open and closed formulas. Since our deterministic prover considers only the subset of terms relevant to proving a given sequent, we do the same when building a countermodel from a failed proof. Finally, we formally connect our prover with the proof system and semantics of the existing SeCaV system. In particular, the prover can generate human-readable SeCaV proofs which are also machine-verifiable proof certificates. The abstract framework we rely on requires us to fix a stream of proof rules in advance, independently of the formula we are trying to prove. We discuss the efficiency implications of this and the difficulties in mitigating them.
Do Virtual Reality Relaxation Experiences Alleviate Stress in Parents of Children with Autism? A Pilot Study
Authors: Lovell Brian , Wetherell Mark A.
Published: June 2024

Psychotherapeutic interventions such as cognitive training and psychoeducation tend to be effective for alleviating stress in caregivers of children with autism. However, these interventions are often time consuming and take place outside the home, posing challenges for accessibility. Technology, especially virtual reality (VR) technology, can be used to support a range of digital interventions at home. VR headsets, when used to simulate relaxing experiences, have already been linked with stress relieving effects for some caregiving groups. This study builds on this, exploring whether VR simulated relaxing environments engender positive psychological changes for caregivers of children with autism. A total of 18 caregivers were exposed to VR simulated natural environments (e.g., beach, forest) for 15 min in a single session. State mood, captured with POMS, was measured at baseline and immediately post intervention. Perceived stress (PSS) was captured at baseline and, to explore intervention effectiveness, at three- and seven-days post intervention. POMS scores for tension, anger, depression, fatigue and confusion were lower, and scores for vigour higher, immediately post intervention. PSS scores at three-and seven-days post intervention, while comparable with one another, were lower compared with baseline. Interacting with simulated natural environments in VR seems effective for improving caregivers’ state mood and reducing their perceived stress for up to seven days. Future research should aim to consolidate and expand on these findings with larger samples and longer follow up periods.
Hydrodynamics for Asymmetric Simple Exclusion on a Finite Segment with Glauber-Type Source
Authors: Xu Lu , Zhao Linjie
Published: June 2024

We consider an open interacting particle system on a finite lattice. The particles perform asymmetric simple exclusion and are randomly created or destroyed at all sites, with rates that grow rapidly near the boundaries. We study the hydrodynamic limit for the particle density at the hyperbolic space-time scale and obtain the entropy solution to a boundary-driven quasilinear conservation law with a source term. Different from the usual boundary conditions introduced in Bardos et al (Commun Partial Differ Equ 4(9):1017–1034, https://doi.org/10.1080/03605307908820117, 1979) and Otto (C R Acad Sci Paris 322(1):729–734, 1996), discontinuity (boundary layer) does not formulate at the boundaries due to the strong relaxation scheme.
Innovation for sustainable development goals: a comparative study of the obstacles and tactics in public organizations
Authors: Suchitwarasan Chutima , Cinar Emre , Simms Chris , Demircioglu Mehmet Akif
Published: June 2024

This study examines obstacles and tactics in Sustainable Development Goals (SDGs)-oriented public sector innovation (PSI). We analyzed 137 SDGs-oriented PSIs in Thailand and Korea. First, our results indicate that the configuration of obstacles is influenced by politico-administrative context and innovation type. Organizational level obstacles are more frequent in Thailand, whereas interaction level obstacles are more common in Korea. Second, we reveal the tactics used to overcome various kinds of obstacles and develop a classification that identifies a new tactics type, forming & coordinating for tackling obstacles originating from the governance of collaboration in the innovation process. This empirical study provides public managers with insights to comprehend PSI obstacles and choose effective tactics for overcoming them.
High-performance transparent AZO UV photodetectors
Authors: Ozel K. , Yildiz A.
Published: June 2024

In this work, the fabrication of undoped ZnO (ZO) and 3 at.% aluminum (Al) doped ZnO (AZO) thin films (TFs) based transparent photodetectors (PDs) was reported. Both films were spin-coated on fluorine-doped tin oxide (FTO) substrates to investigate the influence of Al doping on the ultraviolet (UV) detection performance of the devices. The systematic characterizations reveal that Al doping positively affects the characteristics of ZO-TFs. The Al doping leads to slight shift in crystalline peaks and induces an enhancement in grain size. In addition, the surface roughness of ZO-TFs gets lower on Al doping. Further, the Al doping improved the transparency and widening of band gap of TFs. The PDs having metal–semiconductor-metal (MSM) configuration were achieved by screen-printing of Ag paste onto ZO and AZO-TFs. The current–voltage (I-V) profiles of the fabricated PDs were measured in the dark and under UV excitation of 365 nm. The AZO-TFs based MSM PD exhibits a spectral responsivity of 326.82 mA/W and an external quantum efficiency of 111.03%. The reproducibility of the fabricated PDs was tested by performing time-dependent photo-response measurements.
Effect of Apolipoprotein E isoforms on the Abundance and Function of P-glycoprotein in Human Brain Microvascular Endothelial Cells
Authors: Kreutzer Ethan , Short Jennifer L. , Nicolazzo Joseph A.
Published: June 2024

Background

Individuals with Alzheimer’s disease (AD) often require many medications; however, these medications are dosed using regimens recommended for individuals without AD. This is despite reduced abundance and function of P-glycoprotein (P-gp) at the blood-brain barrier (BBB) in AD, which can impact brain exposure of drugs. The fundamental mechanisms leading to reduced P-gp abundance in sporadic AD remain unknown; however, it is known that the apolipoprotein E (apoE) gene has the strongest genetic link to sporadic AD development, and apoE isoforms can differentially alter BBB function. The aim of this study was to assess if apoE affects P-gp abundance and function in an isoform-dependent manner using a human cerebral microvascular endothelial cell (hCMEC/D3) model.

Methods

This study assessed the impact of apoE isoforms on P-gp abundance (by western blot) and function (by rhodamine 123 (R123) uptake) in hCMEC/D3 cells. Cells were exposed to recombinant apoE3 and apoE4 at 2 – 10 µg/mL over 24 – 72 hours. hCMEC/D3 cells were also exposed for 72 hours to astrocyte-conditioned media (ACM) from astrocytes expressing humanised apoE isoforms.

Results

P-gp abundance in hCMEC/D3 cells was not altered by recombinant apoE4 relative to recombinant apoE3, nor did ACM containing human apoE isoforms alter P-gp abundance. R123 accumulation in hCMEC/D3 cells was also unchanged with recombinant apoE isoform treatments, suggesting no change to P-gp function, despite both abundance and function being altered by positive controls SR12813 (5 µM) and PSC 833 (5 µM), respectively.

Conclusions

Different apoE isoforms have no direct influence on P-gp abundance or function within this model, and further in vivo studies would be required to address whether P-gp abundance or function are reduced in sporadic AD in an apoE isoform-specific manner.
Exploiting OFDM method for quantum communication
Authors: Sabaawi Abdulbasit M. A. , Almasaoodi Mohammed R. , Imre Sándor
Published: June 2024

Orthogonal frequency-division multiplexing (OFDM) is a crucial modulation method used in contemporary digital communication systems for its significant spectral efficiency, low latency, and robustness in challenging environments. This work examines the novel use of OFDM in quantum communication, an area that offers exceptional security and efficiency in information transfer using quantum mechanics principles. In the rapidly evolving field of quantum computing, understanding, and mitigating quantum bit errors is paramount. This paper presents a rigorous analysis of bit error rates (BER) in quantum circuits, focusing on the impact of the quantum Fourier transform and its inverse, contrasted against quantum circuits employing dynamic gate sequences. Our research methodology encompasses simulations over a diverse set of parameters, including varying qubit counts ranging from 2 to 8 and theta angles (15, 30, 45, and 60°), as well as random theta values, utilizing the advanced capabilities of the Qiskit framework. Our findings indicate that quantum OFDM substantially improves quantum communication, lowering errors and boosting security. The quantum model outperforms the reference model in BER, with further enhancements as qubits increase.
The representation, quantification, and nature of genetic information
Authors: Thorvaldsen Steinar , Øhrstrøm Peter , Hössjer Ola
Published: June 2024

Current genetics studies often refer to notions from information science. The purpose of this paper is to summarize and structure the different notions of information used in biology, as a step towards developing a taxonomy of information. Within this framework we propose an extension of Floridi’s conceptual model of information. We also make use of the concept of specified information and show that functional information and many other notions of information are either special cases of, or are closely related to, specified information. Since functionality of the proteins that genes code serves as an external and independent specification, this makes it possible to define genetic information in a way that includes semantic aspects. In particular, we discuss how to understand the qualitative aspects of genetic information, how to measure its quantitative aspects, and how variants of Shannon’s information measure can be applied to molecular sequence data of protein families. While a mathematical framework may not be able to incorporate all that is included within biological information, some aspects of it allow for statistical modelling. This is especially true if we restrict our focus on the discipline of genetics. The concept of genetic information is still disputed because it attributes semantic traits to what seems to be regular biochemical entities. Some researchers maintain that the use of information in biology is just metaphorical and may even be misleading. We argue that the foundation of the metaphorical view is relatively weak given the current findings in bioinformatics and show that the present understanding of genetics fits well into the context of the modern philosophy of information. The paper concludes that informational concepts have robust scientific applications at the level of genes.
Toward a third-generation rational choice theory: the multiple player approach to collective action problems
Authors: Brandt Urs Steiner , Poulsen Anders , Svendsen Gert Tinggaard
Published: June 2024

This paper aims to contribute to the development of a “third-generation” rational choice theory by introducing a Multiple Player Approach for analysing collective action problems. Drawing on the foundational first and second generation works of Olson (The logic of collective action, Cambridge University Press, Cambridge, 1965) and Ostrom (Scand Polit Stud 23(1):3–16), we introduce five player types that we believe capture essential empirical features of many real world collective action problems: Blind Riders, Tough Riders, Hard Riders, Easy Riders, and Low Riders. We consider the complex interaction and dynamics that unfold among them. The main novelty of the analysis is to draw attention to the need for active societal support to effectively empower and reward hard riders for resolving collective action problems, particularly when facing external shocks such as the Covid-19 pandemic, Brexit, and financial crises.
Analysis of Clinical Criteria for Discharge Among Patients Hospitalized for COVID-19: Development and Validation of a Risk Prediction Model
Authors: Schnipper Jeffrey L. , Oreper Sandra , Hubbard Colin C. , Kurbegov Dax , Egloff Shanna A. Arnold , Najafi Nader , Valdes Gilmer , Siddiqui Zishan , O.’Leary Kevin J. , Horwitz Leora I. , Lee Tiffany , Auerbach Andrew D.
Published: June 2024

Background

Patients hospitalized with COVID-19 can clinically deteriorate after a period of initial stability, making optimal timing of discharge a clinical and operational challenge.

Objective

To determine risks for post-discharge readmission and death among patients hospitalized with COVID-19.

Design

Multicenter retrospective observational cohort study, 2020–2021, with 30-day follow-up.

Participants

Adults admitted for care of COVID-19 respiratory disease between March 2, 2020, and February 11, 2021, to one of 180 US hospitals affiliated with the HCA Healthcare system.

Main Measures

Readmission to or death at an HCA hospital within 30 days of discharge was assessed. The area under the receiver operating characteristic curve (AUC) was calculated using an internal validation set (33% of the HCA cohort), and external validation was performed using similar data from six academic centers associated with a hospital medicine research network (HOMERuN).

Key Results

The final HCA cohort included 62,195 patients (mean age 61.9 years, 51.9% male), of whom 4704 (7.6%) were readmitted or died within 30 days of discharge. Independent risk factors for death or readmission included fever within 72 h of discharge; tachypnea, tachycardia, or lack of improvement in oxygen requirement in the last 24 h; lymphopenia or thrombocytopenia at the time of discharge; being ≤ 7 days since first positive test for SARS-CoV-2; HOSPITAL readmission risk score ≥ 5; and several comorbidities. Inpatient treatment with remdesivir or anticoagulation were associated with lower odds. The model’s AUC for the internal validation set was 0.73 (95% CI 0.71–0.74) and 0.66 (95% CI 0.64 to 0.67) for the external validation set.

Conclusions

This large retrospective study identified several factors associated with post-discharge readmission or death in models which performed with good discrimination. Patients 7 or fewer days since test positivity and who demonstrate potentially reversible risk factors may benefit from delaying discharge until those risk factors resolve.
Sociodemographic and psychological factors affecting motor vehicle crashes (MVCs): a classification analysis based on the contextual-mediated model of traffic-accident involvement
Authors: Tinella Luigi , Bosco Andrea , Koppel Sjaan , Lopez Antonella , Spano Giuseppina , Ricciardi Elisabetta , Traficante Sergio , Napoletano Rosa , Grattagliano Ignazio , Caffò Alessandro Oronzo
Published: June 2024

The study aimed to determine the sociodemographic and psychological profiles of drivers with a history of motor vehicle crashes (MVCs), following the contextual-mediated model of crash involvement, and trying to define similarities and differences with drivers without MVCs. Although road trauma prevention has become a central public health issue, the study of psychological determinants of MVCs does not have consistent results due to methodological and theoretical weaknesses. Three-hundred and forty-five active drivers (20% females) completed an extensive office-based fitness-to-drive evaluation including measures of cognition, personality, self-reported driving-related behaviors, attitudes, as well as computerized measures of driving performance. The Classification and Regression Tree method (CART) was used to identify discriminant predictors. The classification identified several relevant predictors; the personality trait of Discostraint (as a distal context variable; cut-point: 50 T points) and motor speed (as a proximal context variable; cut-point: 64 percentile ranks). The global classification model increased approximately 3 times the probability of identifying people with a history of MVC involvement, starting from an estimated prevalence of being involved in an MVC in a period of five years in the population of active drivers. Consistent with the ‘contextual-mediated model of traffic accident involvement’, the results of the present study suggest that road trauma analysis should focus on both distal and proximal driver-related factors by paying attention to their association in determining MVCs. These results represent a valuable source of knowledge for researchers and practitioners for preventing road trauma.
On the linkage of momentum and reversal – evidence from the G7 stock markets
Authors: Hofmann Daniel , Keiber Karl Ludwig , Luczak Adalbert
Published: June 2024

This paper studies the linkage of momentum and reversal in the G7 stock markets. We confirm Conrad and Yavuz’s (Rev Financ 21(2):555–581, 2017) finding that momentum is not linked to subsequent return reversal in the US stock market. In the stock markets of the remaining G7 countries, our results object the decoupling of momentum and return reversal. In these stock markets, the two return anomalies are linked to each other. In particular, momentum is followed by return reversal in the stock markets of Germany, the UK, Japan, Canada, France, and Italy. These observations obtain for momentum portfolios which are made up of different risk profiles with respect to size and book-to-market ratio. Our results hold true both in raw returns and in risk-adjusted returns.
Network Design and Control: Shape and Topology Optimization for the Turnpike Property for the Wave Equation
Authors: Gugat Martin , Qian Meizhi , Sokolowski Jan
Published: June 2024

The optimal control problems for the wave equation are considered on networks. The turnpike property is shown for the state equation, the adjoint state equation as well as the optimal cost. The shape and topology optimization is performed for the network with the shape functional given by the optimality system of the control problem. The set of admissible shapes for the network is compact in finite dimensions, thus the use of turnpike property is straightforward. The topology optimization is analysed for an example of nucleation of a small cycle at the internal node of network. The topological derivative of the cost is introduced and evaluated in the framework of domain decomposition technique. Numerical examples are provided.
Blick ins Innere: Analyse von 3D-Kulturen mittels Mikrokavitätenarrays
Authors: Zitzmann Franziska D. , Schmidt Sabine , Jahnke Heinz-Georg
Published: June 2024

Three-dimensional cultures are a big step towards a more accurate mimicry of the in vivo environment. Given the limited availability of non-invasive analysis methods, especially beyond 2D cultures, we have developed a platform for multimodal bioelectronic monitoring in combination with our microcavity array technology for label-free real-time analysis of 3D cultures. This allows a wide range of cell-specific processes and drug responses to be studied with enhanced spatial resolution and in an automated setting.
Stressresistenz durch Adaption der mitochondrialen Form
Authors: Anton Vincent , Escobar-Henriques Mafalda
Published: June 2024

Mitochondria are dynamic cellular compartments that can remodel their own shape and activity. They sense and convert cellular signals into informative triggers, allowing the cell to adapt to its ever-changing needs. We discovered that under stress this adaptation is performed by the E4 enzyme Ufd2/UBE4B, which tags mitochondrial fusion factors called mitofusins, thus signalling their degradation. Our findings highlight therapeutic intervention cues for mitofusin-associated diseases.
Transformation privaträumlicher Lebenswelten
Authors: Retkowski Alexandra , Glunde Bettina , Hilbig Melanie
Published: June 2024

Der Beitrag greift mit der Wohnraumberatung ein bislang in Deutschland öffentlich kaum wahrgenommenes und wissenschaftlich gering untersuchtes Tätigkeitsfeld von Fachleuten auf, die über eine Zusatzqualifikation verfügen und unterschiedlichen Grundberufen wie z. B. Sozialarbeiter*innen, Mitarbeiter*innen des Gesundheitsdienstes oder der Wohnungswirtschaft nachgehen oder aber ehrenamtlich tätig sind. Das Handlungsfeld ist mit Blick auf sozialökologische Transformationsprozesse von immenser Bedeutung, da es an der Schnittstelle von privater Lebenswelt, gesundheitsbezogener Daseinsvorsorge und auf Nachhaltigkeit ausgerichteten sozialräumlichen Entwicklungen liegt. Vor diesem Hintergrund entwirft der Beitrag mit dem Konzept der sozialräumlichen Resilienz einen Orientierungsrahmen für Professionalisierungsoptionen des Beratungsangebots zur Wohnraumanpassung älterer Menschen. Am Beispiel des Brandenburger Teils der Lausitz werden Fragen der präventiven Gesundheitsvorsorge mit den regional und besonders im ländlichen Raum gegebenen Krisenphänomenen des demografischen Wandels, des Fachkräftemangels im Sozial- und Gesundheitssektor sowie den ökologischen Dimensionen im Wohn- und Bausektor in Verbindung gebracht. Diese Perspektive auf Beratungsprozesse steht vor der besonderen Herausforderung, die Bedarfe und Bedürfnisse älterer Menschen nach Versorgung, Barrierefreiheit und Selbstständigkeit ins Verhältnis zu setzen zur Notwendigkeit, die ältere Bevölkerung gleichsam auch als Akteur*innen des sozialökologischen Strukturwandels zu adressieren. In diesem Zusammenhang kann Wohnraumberatung als Medium gesellschaftlicher, transdisziplinärer Aushandlungsprozesse verstanden werden, welche individuelle, sozialräumliche und ökologische Aspekte in der Daseinsvorsorge berücksichtigt.
The Implicit Equation of a Holditch Curve
Authors: Monterde Juan , Rochera David
Published: June 2024

Holditch’s theorem is a classical geometrical result on the areas of a given closed curve and another one, its Holditch curve, which is constructed as the locus of a fixed point dividing a chord of constant length that moves with its endpoints over the given curve and that returns back to its original position after some full revolution. Holditch curves have already been studied from the parametric point of view, although numerical methods and approximations are often necessary for their computation. In this paper, implicit equations of Holditch curves of algebraic curves are studied. The implicit equations can be simply found from the computation of a resultant of two polynomials. With the same techniques, Holditch curves of two initial algebraic curves are also considered. Moreover, the use of implicit equations allows to find new and explicit parameterizations of non-trivial Holditch curves, such as in the case of having an ellipse as an initial curve.
Operational efficiency and sustainability in smart ports: a comprehensive review
Authors: Alzate Paola , Isaza Gustavo A. , Toro Eliana M. , Jaramillo-Garzón Jorge A. , Hernandez Sara , Jurado Isabella , Hernandez Diana
Published: June 2024

The challenges of optimizing logistics operations in all links of the supply chain have led to the development of new dynamics around the revolution 4.0 and the response of operational efficiency linked to environmental sustainability. Smart ports are born as a strategy to meet customer needs from a technological evolution that generates quality logistical and operational responses. The objective of this review is to identify and to analyze the research perspectives related to smart ports. The implemented methodology considered a scientific mapping to determine the most relevant publications in terms of authors, journals, and countries with the greatest scientific participation in the subject and a network analysis based on the implementation of the tree metaphor of the graph theory. The R-studio software and the Bibliometrix plugin were used to process the information. The review considered 204 documents from the Scopus and Web of Science databases, identifying a growing trend in the number of enhanced publications as of 2019, with China being the country with the largest number of papers. In relation to research trends, the adaptation of ports to industry 4.0, maritime ports and technological security, and green and smart ports are the perspectives on the subject of study. Finally, an agenda for future research is presented.
Towards Responsible Urban Geospatial AI: Insights From the White and Grey Literatures
Authors: Marasinghe Raveena , Yigitcanlar Tan , Mayere Severine , Washington Tracy , Limb Mark
Published: June 2024

Artificial intelligence (AI) has increasingly been integrated into various domains, significantly impacting geospatial applications. Machine learning (ML) and computer vision (CV) are critical in urban decision-making. However, urban AI implementation faces unique challenges. Academic literature on responsible AI largely focuses on general principles, with limited emphasis on the geospatial domain. This important gap in scholarly work could hinder effective AI integration in urban geospatial applications. Our study employs a multi-method approach, including a systematic academic literature review, word frequency analysis and insights from grey literature, to examine potential challenges and propose strategies for effective geospatial AI (GeoAI) integration. We identify a range of responsible practices relevant to the complexities of using AI in urban geospatial planning and its effective implementation. The review provides a comprehensive and actionable framework for responsible AI adoption in the geospatial domain, offering a roadmap for urban researchers and practitioners. It highlights ways to optimise AI benefits while minimising potential negative consequences, contributing to urban sustainability and equity.
Integrated Dataset-Preparation System for ML-Based Medical Image Diagnosis with High Clinical Applicability in Various Modalities and Diagnoses
Authors: Nguyen My N. , Harada Kotori , Yoshimoto Takahiro , Duong Nam Phong , Sowa Yoshihiro , Sakai Koji , Fukuzawa Masayuki
Published: June 2024

This study proposed an integrated dataset-preparation system for ML-based medical image diagnosis, offering high clinical applicability in various modalities and diagnostic purposes. With the proliferation of ML-based computer-aided diagnosis using medical images, massive datasets should be prepared. Lacking of a standard procedure, dataset-preparation may become ineffective. Besides, on-demand procedures are locked to a single image-modality and purpose. For these reasons, we introduced a dataset-preparation system applicable for a variety of modalities and purposes. The system consisted of a common part including incremental anonymization and cross annotation for preparing anonymized unprocessed data, followed by modality/subject-dependent parts for subsequent processes. The incremental anonymization was carried out in batch after the image acquisition. Cross annotation enabled collaborative medical specialists to co-generate annotation objects. For quick observation of dataset, thumbnail images were created. With anonymized images, preprocessing was accomplished by complementing manual operations with automatic operations. Finally, feature extraction was automatically performed to obtain data representation. Experimental results on two demonstrative systems dedicated to esthetic outcome evaluation of breast reconstruction surgery from 3D breast images and tumor detection from breast MRI images were provided. The proposed system successfully prepared the 3D breast-mesh closures and their geometric features from 3D breast images, as well as radiomics and likelihood features from breast MRI images. The system also enabled effective voxel-by-voxel prediction of tumor region from breast MRI images using random-forest and k-nearest-neighbors algorithms. The results confirmed the efficiency of the system in preparing dataset with high clinical applicability regardless of the image modality and diagnostic purpose.
Shear strengthening of damaged reinforced concrete beams with iron-based shape memory alloy (Fe-SMA) strips: numerical and parametric analysis
Authors: Tabrizikahou Alireza , Białasik Jan , Borysiak Sławomir , Fabisiak Mateusz , Łasecka-Plura Magdalena , Jesionowski Teofil , Kuczma Mieczysław
Published: June 2024

Shape memory alloys (SMAs) are metallic materials that are characterized by their ability to restore their original shape after large deformation when activated by heating. This unique property renders SMAs appealing for various civil engineering applications. Iron-based SMAs (Fe-SMAs), including alloys like Fe–Mn–Si, stand out due to their cost-effectiveness and high strength. The primary focus of this research lies in the computational modeling of Fe-SMA strips utilized to reinforce damaged concrete structures. To achieve this, details from an experimental test are leveraged for the computational simulation of real-scale reinforced concrete beams that were first loaded to some level of damage, then released and strengthened, and subsequently retested. The strengthening approach involves the application of external Fe-SMA strips wrapping around the beams. This paper presents an original computational modeling setup that incorporates a switch option for the Fe-SMA material. This feature enables one to use a single simulation platform for the whole process. The significance of this method originates from its capacity to ensure a robust analysis that includes all simulation steps-testing unstrengthened beams, installing and heating Fe-SMA strips, and testing both damaged and strengthened beams—in a single, multi-step analysis. The computational simulation results were compared with the outcomes of the experimental test, revealing an acceptable level of agreement. The findings indicate a substantial increase in both shear strength and ductility as a result of the application of Fe-SMA strips. Additionally, parametric and mesh sensitivity studies were conducted. These aimed to investigate the mesh dependency of the model and to identify the optimal mesh size. Furthermore, variations in the details of the Fe-SMA strips, including thickness, width, quantity, and effect of applied temperature were explored to compare the outcomes of different applications of these strips.
Acridinedione-phthalimide conjugates: Intramolecular electron transfer and singlet oxygen generation studies for optical and photodynamic therapy applications
Authors: El-Khouly Mohamed E. , Khatab Hassan A. , Abdel-Shafi Ayamn A. , Hammad Sherif F.
Published: June 2024

We reported herein the synthesis, characterization of hybrid conjugates composed of phthalimide (Phth) and acridine-1,8-diones (Acr) for optical and medical applications. For the synthetic procedure, a three-step synthetic strategy has been utilized. The optical properties of the examined 1,8-acridinedione–phthalimide connected molecules (AcrPhth 1–5) have been examined utilizing various spectroscopic techniques, e.g., steady-state absorption and fluorescence, and time-correlated single photon counting. The steady-state absorption studies showed that AcrPhth 1–5 absorbs the light in the UV and visible region. The fluorescence studies of AcrPhth 1–5 exhibited significant fluorescence quenching compared to the acridinedione control compounds (Acr 1–5) suggesting the occurrence of electron-transfer reactions from the electron donating acridinedione moiety (Acr) to the electron accepting phthalimide moiety (Phth). The rate and efficiency of the electron-transfer reactions were determined from the fluorescence lifetime measurements indicating the fast electron-transfer processes of the covalently connected AcrPhth 1–5 conjugates. Computational studies supported the intramolecular electron-transfer reaction of AcrPhth conjugates using ab initio B3LYP/6-311G methods. In the optimized structures, the HOMO was found to be entirely located on the Acr entity, while the LUMO was found to be entirely on the Phth entity. Further, the synthesized compounds were tested as photosensitizers for generating the singlet oxygen species, which is a key factor in the photodynamic therapy (PDT) applications. The nanosecond laser flash measurements enable us to detect the triplet-excited states of examined Acr and AcrPhth conjugates, determining the triplet quantum yields, and direct detecting the singlet oxygen in an accurate way. From this observation, the singlet quantum yields were found to be in the range of 0.12–0.27 (for Acr 1–5) and 0.07–0.19 (for AcrPhth 1–5 conjugates). The molecular docking studies revealed that compound AcrPhth 2 exhibited high binding affinity with for key genes (p53, TOP2B, p38, and EGFR) suggesting its potential as a targeted anticancer therapy.

Graphical abstract
Monte Carlo simulations of light transport in sunscreen formulations
Authors: Herzog Bernd , Bressel Lena , Pulbere Sorin , Reich Oliver
Published: June 2024

Sunscreens are used for the protection of human skin against the harmful effects of solar UV radiation. Due to the low thickness of sunscreen films typically applied to the skin, it can be challenging to achieve the strong absorbance needed for good UV-protection, and most efficient sunscreen compositions are desirable. The presence of scattering particles can increase the efficacy of dissolved UV-absorbers in the oil or water phases of the formulation. As many sunscreens contain UV-absorbing particles, it is of interest how much the scattering effect of such materials contribute to the protection of the respective sunscreen. The currently available software programs for simulating sunscreen performance are based on a Beer–Lambert law approach and do not take into account such scattering effects of particles. However, Monte Carlo simulations of the UV-light transport through sunscreen films are capable to take scattering from particles into consideration. Using Monte Carlo simulations, this work shows that the efficacy of absorbance is indeed increased in the presence of scattering particles. However, this is of limited significance when the particles are UV-absorbers themselves.

Graphical abstract
The role of targeting CDK4/6 in cancer immunotherapy
Authors: Sun Mengyu , Dong Lin , Wang Yu , Liu Chao , Du Jiang , Wang Bo , Xing Bofan , Yao Xiaofeng , Ren Yu , Zhou Xuan
Published: June 2024

Cyclin-dependent kinase 4/6 (CDK4/6) acts as a crucial point of regulation in the G1-to-S transition in the cell division cycle, its aberrant activation was found in various human cancers, leading to abnormal cell proliferation. Recent clinical trials have reported that combined with other small-molecule targeted therapies, CDK4/6 inhibitors increase overall survival and objective response rates in breast cancer (BC), non-small cell lung cancer (NSCLC), and head and neck squamous cell carcinoma (HNSCC). Notably, targeting CDK4/6 triggers an antitumor immune response, providing a potential combined application method for immunotherapy. In this review, we summarize underlying mechanism of targeting CDK4/6 in regulating antigen presentation, immune cell activation, and tumor immune microenvironment (TIME) remodeling and in producing synergistic effects with immune checkpoint blockade (ICB) in cancer clinical treatment.
Multivariate investigation of physicochemical, nutritional and sensory attributes of traditional Lebanese grape molasses
Authors: Salameh Christelle , Abi Khalil Aimée , Kassouf Amine
Published: June 2024

Grape molasses is a natural sweetener widely consumed in Lebanon and Eastern Mediterranean countries. However, the lack of national standards that control its production often leads to inconsistent products and complicates international exports. Thirty grape molasses samples were collected from different Lebanese regions, and their physicochemical, microbiological, and sensory properties were investigated using a multivariate approach. Significant disparities were detected among samples obtained using different processes and from different geographical origins. The samples from the Bekaa region, manufactured with semi-industrial heat exchangers, were the most appreciated by the panelists due to their high dry matter content (80.41%), Brix degree (75°Brix), low water activity (0.55) and low titratable acidity (0.30%). Microbial contamination with osmophilic microorganisms was detected in several samples, highlighting poor hygiene practices and factory sanitation, in addition to post-contamination during the packaging and whipping steps. In summary, the key parameters that affect grape molasses quality are geographical origin, grape variety and ripening stage, soil and climatic factors, and manufacturing process, particularly juice concentration technique/time. These factors should be considered for future optimization and standardization of production processes and for monitoring and homogenizing the quality of this product.
Real-Time Classroom Behavior Analysis for Enhanced Engineering Education: An AI-Assisted Approach
Authors: Hu Jia , Huang Zhenxi , Li Jing , Xu Lingfeng , Zou Yuntao
Published: June 2024

Modern teaching has made significant progress, with many advanced equipment and technologies being introduced into the teaching process. Experimental teaching of engineering design courses is important. Due to limited teaching resources, engineering students need effective guidance during limited laboratory time. We will introduce artificial intelligence solutions to engineering education. We will use artificial intelligence technology for classroom behavior analysis to improve engineering design practice courses' teaching effectiveness. In an instructional milieu, image acquisition tools such as cameras are capable of real-time data capture, facilitating the identification and enumeration of students' emotional states. Concurrently, analytical software gauges the students' interaction patterns and performs comprehensive cluster analysis. Such multifaceted information provides valuable insights into the students' educational engagement, allowing educators to tailor their approach, thereby fostering enhanced pedagogical outcomes. The emotion recognition model we have developed, namely ERAM, demonstrates a rapid response rate coupled with dependable accuracy, making it a robust tool for classroom implementation. In contrast to the conventional post-lesson evaluations, our proposed technique furnishes immediate feedback throughout the instructional process. This real-time approach heralds a significant shift in instructional methodology, promoting timely intervention and adaptive teaching strategies. The control group experiment showed that intelligent systems improved teaching effectiveness by 8.44%. Intelligent systems can help teachers understand students' learning status and improve laboratory teaching quality in engineering design courses.
A Combined Marine Predators and Particle Swarm Optimization for Task Offloading in Vehicular Edge Computing Network
Authors: Abuthahir S. Syed , Peter J. Selvin Paul
Published: June 2024

With the rapid advancement in technology, numerous advanced vehicular applications have emerged that generate large volumes of data that need to be processed on the fly. The vehicles' computing resources are limited and constrained in processing the huge amount of data generated by these applications. Cloud data centers, which are large and capable of processing the generated data, tend to be far away from the vehicles. The long distance between the cloud and the vehicles results in large transmission delays, making the cloud less suitable for executing such data. To address the long-standing issue of huge transmission delays in the cloud, edge computing, which deploys computing servers at the edge of the network, was introduced. The edge computing network shortens the communication distance between the vehicles and the processing resources and also provides more powerful computation compared to the vehicles' computing resources. The advantages offered by the vehicular edge network can only be fully realized with robust and efficient resource allocation. Poor allocation of these resources can lead to a worse situation than the cloud. In this paper, a hybrid Marine Predatory and Particle Swarm Optimization Algorithm (MPA–PSO) is proposed for optimal resource allocation. The MPA–PSO algorithm takes advantage of the effectiveness and reliability of the global and local search abilities of the Particle Swarm Optimization Algorithm (PSO) to improve the suboptimal global search ability of the MPA. This enhances the other steps in the MPA to ensure an optimal solution. The proposed MPA–PSO algorithm was implemented using MATLAB alongside the conventional PSO and MPA, and the proposed MPA–PSO recorded a significant improvement over the PSO and MPA.
Divisive language
Authors: Dillon Moira R.
Published: June 2024

What language devises, it might divide. By exploring the relations among the core geometries of the physical world, the abstract geometry of Euclid, and language, I give new insight into both the persistence of core knowledge into adulthood and our access to it through language. My extension of Spelke's language argument has implications for pedagogy, philosophy, and artificial intelligence.
Investigating infant knowledge with representational similarity analysis
Authors: Ellis Cameron T.
Published: June 2024

Decades of research have pushed us closer to understanding what babies know. However, a powerful approach – representational similarity analysis (RSA) – is underused in developmental research. I discuss the strengths of this approach and what it can tell us about infant conceptual knowledge. As a case study, I focus on numerosity as a domain where RSA can make unique progress.
Envisioning U.S. Climate Predictions and Projections to Meet New Challenges
Authors: Mariotti Annarita , Bader David C. , Bauer Susanne E. , Danabasoglu Gokhan , Dunne John , Gross Brian , Leung L. Ruby , Pawson Steven , Putman William R. , Ramaswamy Venkatachalam , Schmidt Gavin A. , Tallapragada Vijay
Published: June 2024

In the face of a changing climate, the understanding, predictions, and projections of natural and human systems are increasingly crucial to prepare and cope with extremes and cascading hazards, determine unexpected feedbacks and potential tipping points, inform long‐term adaptation strategies, and guide mitigation approaches. Increasingly complex socio‐economic systems require enhanced predictive information to support advanced practices. Such new predictive challenges drive the need to fully capitalize on ambitious scientific and technological opportunities. These include the unrealized potential for very high‐resolution modeling of global‐to‐local Earth system processes across timescales, reduction of model biases, enhanced integration of human systems and the Earth Systems, better quantification of predictability and uncertainties; expedited science‐to‐service pathways, and co‐production of actionable information with stakeholders. Enabling technological opportunities include exascale computing, advanced data storage, novel observations and powerful data analytics, including artificial intelligence and machine learning. Looking to generate community discussions on how to accelerate progress on U.S. climate predictions and projections, representatives of Federally‐funded U.S. modeling groups outline here perspectives on a six‐pillar national approach grounded in climate science that builds on the strengths of the U.S. modeling community and agency goals. This calls for an unprecedented level of coordination to capitalize on transformative opportunities, augmenting and complementing current modeling center capabilities and plans to support agency missions. Tangible outcomes include projections with horizontal spatial resolutions finer than 10 km, representing extremes and associated risks in greater detail, reduced model errors, better predictability estimates, and more customized projections to support next generation climate services.