bluuebunny/crossref_metadata_2025 huggingface dataset:
Characterization of Retinal VIP-Amacrine Cell Development During the Critical Period
Authors: Zhang Xuhong , Wang Xiaoyu , Li Yanqing , Zhang Yingying , Zhu Hong , Xie Chen , Zhou Yudong , Shen Ye , Tong Jianping
Published: February 2024

Retinal vasoactive intestinal peptide amacrine cells (VIP-ACs) play an important role in various retinal light-mediated pathological processes related to different developmental ocular diseases and even mental disorders. It is important to characterize the developmental changes in VIP-ACs to further elucidate their mechanisms of circuit function. We bred VIP-Cre mice with Ai14 and Ai32 to specifically label retinal VIP-ACs. The VIP-AC soma and spine density generally increased, from postnatal day (P)0 to P35, reaching adult levels at P14 and P28, respectively. The VIP-AC soma density curve was different with the VIP-AC spine density curve. The total retinal VIP content reached a high level plateau at P14 but was decreased in adults. From P14 to P16, the resting membrane potential (RMP) became more negative, and the input resistance decreased. Cell membrane capacitance (MC) showed three peaks at P7, P12 and P16. The RMP and MC reached a stable level similar to the adult level at P18, whereas input resistance reached a stable level at P21. The percentage of sustained voltage-dependent potassium currents peaked at P16 and remained stable thereafter. The spontaneous excitatory postsynaptic current and spontaneous inhibitory postsynaptic current frequencies and amplitudes, as well as charge transfer, peaked at P12 to P16; however, there were also secondary peaks at different time points. In conclusion, we found that the second, third and fourth weeks after birth were important periods of VIP-AC development. Many developmental changes occurred around eye opening. The development of soma, dendrite and electrophysiological properties showed uneven dynamics of progression. Cell differentiation may contribute to soma development whereas the changes of different ion channels may play important role for spine development.

Graphical Abstract

The second, third and fourth weeks after birth were important periods of VIP-AC development. VIP::Ai14 and VIP::Ai32 mice were used for soma and spine analysis, respectively. The developmental curves for VIP-AC soma have a distinct and longer platform, whereas the developmental curves for spine have a longer and smoother slopes. When the number of VIP-AC some is increasing, cell differentiation may play an important role. During the development of spine, the development of different ion channels is the most vital events. Kv-Ka represents the ion channels that conduct Ka, Kv-Kdr represents the ion channels that conduct Kdr, GABAR represents the inhibitory transmission and NMDAR represents the excitatory transmission. The events occur chronologically from left to right.
Semantic search as extractive paraphrase span detection
Authors: Kanerva Jenna , Kitti Hanna , Chang Li-Hsin , Vahtola Teemu , Creutz Mathias , Ginter Filip
Published: February 2024

In this paper, we approach the problem of semantic search by introducing a task of paraphrase span detection, i.e. given a segment of text as a query phrase, the task is to identify its paraphrase in a given document, the same modelling setup as typically used in extractive question answering. While current work in paraphrasing has almost uniquely focused on sentence-level approaches, the novel span detection approach gives a possibility to retrieve a segment of arbitrary length. On the Turku Paraphrase Corpus of 100,000 manually extracted Finnish paraphrase pairs including their original document context, we find that by achieving an exact match of 88.73 our paraphrase span detection approach outperforms widely adopted sentence-level retrieval baselines (lexical similarity as well as BERT and SBERT sentence embeddings) by more than 20pp in terms of exact match, and 11pp in terms of token-level F-score. This demonstrates a strong advantage of modelling the paraphrase retrieval in terms of span extraction rather than commonly used sentence similarity, the sentence-level approaches being clearly suboptimal for applications where the retrieval targets are not guaranteed to be full sentences. Even when limiting the evaluation to sentence-level retrieval targets only, the span detection model still outperforms the sentence-level baselines by more than 4 pp in terms of exact match, and almost 6pp F-score. Additionally, we introduce a method for creating artificial paraphrase data through back-translation, suitable for languages where manually annotated paraphrase resources for training the span detection model are not available.
Switched max-plus linear-dual inequalities: cycle time analysis and applications
Authors: Zorzenon Davide , Komenda Jan , Raisch Jörg
Published: February 2024

P-time event graphs are discrete event systems suitable for modeling processes in which tasks must be executed in predefined time windows. Their dynamics can be represented by max-plus linear-dual inequalities (LDIs), i.e., systems of linear dynamical inequalities in the primal and dual operations of the max-plus algebra. We define a new class of models called switched LDIs (SLDIs), which allow to switch between different modes of operation, each corresponding to a set of LDIs, according to a sequence of modes called schedule. In this paper, we focus on the analysis of SLDIs when the considered schedule is fixed and either periodic or intermittently periodic. We show that SLDIs can model a wide range of applications including single-robot multi-product processing networks, in which every product has different processing requirements and corresponds to a specific mode of operation. Based on the analysis of SLDIs, we propose algorithms to compute: i. minimum and maximum cycle times for these processes, improving the time complexity of other existing approaches; ii. a complete trajectory of the robot including start-up and shut-down transients.
Comments on Integration, Theory Conflicts, and Practical Implementations: Some Contrarian Ideas for Consideration
Authors: Ryan Richard M.
Published: February 2024

The ideal of theoretical integration in motivational approaches to education is worthy, but in this commentary, I raise some (semi)contrarian concerns about both the meaning of theoretical integration and how that occurs. Integration is more than an aggregation or combination of measures but rather involves synthesis into a framework with theoretic and meta-theoretic integrity. Across disciplines and fields of inquiry, the development of science largely happens within theories and at their boundaries. Integration in practice (e.g., interventions) raises different issues, mainly concerning the coordination of elements that may address different classroom issues, and therefore can stem from multiple models and theories. I also describe the common direction and progress of motivational psychology over the past several decades, albeit with some “jingle –jangle” trends muddying our conceptual waters. Yet contrary to the view that it is our multiple perspectives that confuse teachers, I argue that confusion more centrally lies in the wide gap between our generally student-centered theories and public policies and institutional norms that hinder their implementation and their integration into practice.
Spatiotemporal modelling of $$\hbox {PM}_{2.5}$$ concentrations in Lombardy (Italy): a comparative study
Authors: Otto Philipp , Fusta Moro Alessandro , Rodeschini Jacopo , Shaboviq Qendrim , Ignaccolo Rosaria , Golini Natalia , Cameletti Michela , Maranzano Paolo , Finazzi Francesco , Fassò Alessandro
Published: February 2024

This study presents a comparative analysis of three predictive models with an increasing degree of flexibility: hidden dynamic geostatistical models (HDGM), generalised additive mixed models (GAMM), and the random forest spatiotemporal kriging models (RFSTK). These models are evaluated for their effectiveness in predicting $$\text {PM}_{2.5}$$

PM

2.5

concentrations in Lombardy (North Italy) from 2016 to 2020. Despite differing methodologies, all models demonstrate proficient capture of spatiotemporal patterns within air pollution data with similar out-of-sample performance. Furthermore, the study delves into station-specific analyses, revealing variable model performance contingent on localised conditions. Model interpretation, facilitated by parametric coefficient analysis and partial dependence plots, unveils consistent associations between predictor variables and $$\text {PM}_{2.5}$$

PM

2.5

concentrations. Despite nuanced variations in modelling spatiotemporal correlations, all models effectively accounted for the underlying dependence. In summary, this study underscores the efficacy of conventional techniques in modelling correlated spatiotemporal data, concurrently highlighting the complementary potential of Machine Learning and classical statistical approaches.
What is a High-Quality Moral Case Deliberation?-Facilitators’ Perspectives in the Euro-MCD Project
Authors: Jakobsen Lena M. , Molewijk Bert , de Snoo-Trimp Janine , Svantesson Mia , Ursin Gøril
Published: February 2024

The evaluation of the European Moral Case Deliberation Outcomes project (Euro-MCD) has resulted in a revised evaluation instrument, knowledge about the content of MCD (moral case deliberation), and the perspectives of those involved. In this paper, we report on a perspective that has been overlooked, the facilitators’. We aim to describe facilitators’ perceptions of high-quality moral case deliberation and their Euro-MCD sessions. The research took place in Norway, Sweden, and the Netherlands using a survey combined with interviews with 41 facilitators. Facilitators’ perceived that attaining a high-quality MCD implies fostering a safe and respectful atmosphere, creating a wondering mode, being an attentive authority, developing moral reflective skills, reaching a common understanding, and ensuring organisational prerequisites for the MCD sessions. Our central conclusion is that efforts at three levels are required to attain a high-quality MCD: trained and virtuous facilitator; committed, respectful participants; and organizational space. Furthermore, managers have a responsibility to prepare MCD participants for what it means to take part in MCD.
Solid–Liquid Phase Equilibrium: Alkane Systems for Low-Temperature Energy Storage
Authors: Sequeira Maria C. M. , Nogueira Bernardo A. , Caetano Fernando J. P. , Diogo Hermínio P. , Fareleira João M. N. A. , Fausto Rui
Published: February 2024

The thermal characterization of two binary systems of n-alkanes that can be used as Phase Change Materials (PCMs) for thermal energy storage at low temperatures is reported in this work. The construction of the solid–liquid binary phase diagrams was achieved using differential scanning calorimetry (DSC) and Raman spectroscopy. The solidus and liquidus equilibrium temperatures were determined using DSC for thirty-nine different samples, three for the pure n-alkanes and the remaining for binary mixtures at selected molar compositions and used to acquire the corresponding solid–liquid phase diagrams. The two binary systems of n-octane/n-decane (C8/C10) and n-decane/n-dodecane (C10/C12) are characterized by a eutectic behavior at low temperatures. The eutectic temperature for the system C8/C10 was found at 211.95 K and the eutectic composition appeared at the molar fraction xoctane = 0.87. For the system C10/C12, the eutectic temperature was found at 237.85 K, and the eutectic composition appeared for the molar fraction xdecane = 0.78. This work aims to fulfill the lack of available data in the existing literature, considering the potential application of these systems for low-temperature thermal energy storage. Raman spectroscopy was used to complement the DSC data for the construction of the solid–liquid phase equilibrium diagrams, enabling the identification of the solid and liquid phases of the system. Additionally, the liquidus curve of the phase diagram was successfully described using a modified freezing point depression curve as fitting equation, the absolute root mean square deviation for the data correlation of the C8/C10 and C10/C12 systems being 2.56 K and 1.22 K, respectively. Ultimately, the fitting procedure also enabled a good prediction of the eutectic point for both studied systems.
Fast Multi-Wavelength Pyrometer for Dynamic Temperature Measurements
Authors: Belikov R. , Merges D. , Varentsov D. , Major Zs. , Neumayer P. , Hesselbach Ph. , Schanz M. , Winkler B.
Published: February 2024

Multi-wavelength pyrometry is an efficient tool for measuring high temperatures in dynamic experiments. A fast 5-channel pyrometer was built and successfully employed in ion-beam heating experiments at the GSI Centre for Heavy Ion Research (Darmstadt, Germany). Temperatures of metallic samples heated by an intense focused heavy ion beam up to their melting points and beyond were measured with nanosecond time resolution and a spatial resolution of about 200 μm. The modular instrument has demonstrated its high versatility also for temperature measurements of exothermic reactions with millisecond temporal resolution.
Mining Data Wrangling Workflows for Design Patterns Discovery and Specification
Authors: AlMasaud Abdullah , Sampaio Sandra , Sampaio Pedro
Published: February 2024

In this paper, we investigate Data Wrangling (DW) pipelines in the form of workflows devised by data analysts with varying levels of experience to find commonalities or patterns. We propose an approach for pattern discovery based on workflow mining techniques, addressing key challenges associated with finding patterns in data preparation solutions. The findings provide insights into the most commonly used DW operations, solution patterns, redundancies, and reuse opportunities in data preparation. The findings were used to create design pattern specifications curated into a catalog in the form of a DW Design Patterns Handbook. The evaluation of the proposed handbook is performed by surveying professionals with results confirming the usefulness of discovered patterns to the construction of DW solutions and assisting data analysts/scientists via the reuse of patterns and best practices in DW.
Barile–Macchia resolutions
Authors: Chau Trung , Kara Selvi
Published: February 2024

We construct cellular resolutions for monomial ideals via discrete Morse theory. In particular, we develop an algorithm to create homogeneous acyclic matchings and we call the cellular resolutions induced from these matchings Barile–Macchia resolutions. These resolutions are minimal for edge ideals of weighted oriented forests and (most) cycles. As a result, we provide recursive formulas for graded Betti numbers and projective dimension. Furthermore, we compare Barile–Macchia resolutions to those created by Batzies and Welker and some well-known simplicial resolutions. Under certain assumptions, whenever the above resolutions are minimal, so are Barile–Macchia resolutions.
Living with a Rare Disease: Psychosocial Impacts for Parents and Family Members – a Systematic Review
Authors: Atkins Jenny C. , Padgett Christine R.
Published: February 2024

As rare diseases often have an onset of symptoms in childhood, the burden of the disease and associated challenges commonly fall to the individual’s family members. Managing this burden, and navigating these challenges, has been found to affect the health and lifestyle of family members and lead to them experiencing negative psychosocial impacts and lower quality of life. The aim of the current study was to consolidate and summarise the published quantitative evidence on the psychosocial impacts experienced by individuals who have a family member with a rare disease. We performed a systematic literature search including quantitative studies on psychosocial impacts experienced by family members of individuals with a rare disease across three databases (PubMed, PsychINFO, and CINAHL) from inception to November 2021. Of the 2024 titles identified, 30 studies met the inclusion criteria and were included in the review. A narrative analysis revealed that family members of individuals with rare disease experience a wide range of psychosocial impacts, some of which appear to be unique to, or amplified by, the rarity of the disease. Whilst there are occasional positive outcomes of having a family member with a rare disease, overall family members have been found to experience increased psychological distress, lower quality of life, higher caregiver burden and changes to their social support. Clinical and practical implications of these findings are discussed, as well as implications and directions for future research.
Ant diversity along elevational gradients in the European Alps: insights for conservation under a changing climate
Authors: Schifani Enrico , Grasso Donato A. , Gobbi Mauro , Spotti Fiorenza A. , Pedrotti Luca , Vettorazzo Enrico , Mori Alessandra , Castracani Cristina
Published: February 2024

Due to particular vulnerabilities and environmental constraints, Alpine faunas are exposed to significant threats from climate change. However, baseline diversity and distribution data to monitor the trends of key arthropod groups are often scarce. Ants are highly diversified and key ecological actors across terrestrial ecosystems, including mountain ranges. We investigated ant diversity and distribution in the Southern European Alps to provide detailed data over wide elevational gradients and make a first assessment of potential vulnerabilities in the face of global warming. We detected 40 species from 700 to over 2600 m asl, with progressively less diversity corresponding to higher elevations and lower temperatures. Maximum temperature was weakly related to ant diversity as compared to mean and minimum temperature. In shaping ant diversity, the highest elevation species had wide elevation ranges, consistent with Rapoport’s rule. We documented a fauna characterized by cold-adapted genera, species with wide geographic distributions and presumably high dispersal capabilities, no dietary specializations, and a high frequency of social parasitism. Concerning Bergmann’s rule, average ant species size was not larger in the coldest environments. Red wood ants, characterized by much more populous colonies as compared to the other ant species, had the highest number of ant individuals to be found at intermediate elevations and in woodland habitats. On the other hand, grasslands and shrublands proved to be the most species-rich habitats. Our data lay the groundwork for further investigation on elevational shifts and provide context for the discussion of key aspects of the management and conservation of European alpine ants.

Implications for insect conservation

The cold climate of the European Alps has so far protected its ant fauna from the incursion of alien competitors as compared to what is observed in the Mediterranean region. The scarcity of species with restricted distribution ranges or high-elevation specialists, as well as diet specialists, may grant ants of the European Alps more resilience to climate change as compared to other Alpine arthropod groups. On the other hand, many species are highly interconnected by social parasitism relationships that may be vulnerable to ecological cascade effects. While forest habitats host red wood ants, which are often protected for their important ecological role, the importance of grassland must not be overlooked as they support the highest ant species richness.
Gambling in Victoria: Changes in Participation, Problem Gambling and Gambling Environment Between 2008 and 2018
Authors: Stone Christine Anne , Yeung Kristal , Shaw Lindsay , Billi Rosa
Published: February 2024

Gambling and its impacts are an important public health issue. The relationship between gambling, problem gambling and gambling harm is complex and dynamic. Replicate prevalence studies are useful for surveillance and monitoring gambling impacts within jurisdictions. The purpose of this study was to compare changes in gambling and problem gambling in the Victorian adult population between 2008 and 2018 by investigating individual gambling activities and exploring their relationship with the Victorian gambling ecosystem. Gambling participation has decreased; problem gambling prevalence has not. Investigation beyond these summary measures reveals important details: (a) Electronic Gaming Machines (EGMs), casino table games, race and sports betting (‘high-risk activities’), informal private betting, and Keno, and their associations with problem gambling endure. Further, the strength of this association is unaffected by changes in product technology, delivery, or the Victorian environment in which they reside, (b) participation in high-risk activities, excluding EGMs, increased while for other activities they decreased, (c) EGMs continue to pose the greatest risk for Victorians, (d) males and young adults continue having a higher problem gambling prevalence rate and preferring both online gambling and high-risk activities (excluding racing favoured by an ageing, older cohort, and Keno, by all ages), and (e) gambling access and exposure proliferated enabling single site multiple gambling opportunities on high-risk activities. Young adults represented a new vulnerable group as they reach the legal gambling age. The most effective interventions (based on major falls in real expenditure (losses) on EGMs, the highest risk activity) were the smoking bans, removal of ATMs from venues and decreases in bet size. There is great potential for prevention, intervention, and minimising harm in the gambling environment.
One (Financial Well-Being) Model Fits All? Testing the Multidimensional Subjective Financial Well-Being Scale Across Nine Countries
Authors: Sorgente Angela , Atay Bünyamin , Aubrey Marc , Bhatia Shikha , Crespo Carla , Fonseca Gabriela , Güneri Oya Yerin , Lep Žan , Lessard David , Negru-Subtirica Oana , Portugal Alda , Ranta Mette , Relvas Ana Paula , Singh Nidhi , Sirsch Ulrike , Zupančič Maja , Lanz Margherita
Published: February 2024

A multidimensional model of emerging adults’ subjective financial well-being was proposed (Sorgente and Lanz, Int Journal of Behavioral Development, 43(5), 466–478 2019). The authors also developed a 5-factor scale (the Multidimensional Subjective Financial Well-being Scale, MSFWBS) intending to measure this construct in the European context. To date, data using this instrument have been collected in nine countries: Austria, Canada, Finland, India, Italy, Portugal, Romania, Slovenia, and Turkey. In the current study, data from these countries were analysed to test the validity of this model internationally. In particular, using an international sample of 4,475 emerging adults, we collected the following kinds of validity evidence for the MSFWBS: score structure, reliability, generalizability, convergent, and criterion-related evidence. Findings suggest that the MSFWBS (1) yields valid and reliable scores, and (2) works well in individualistic and economically developed countries, producing comparable scores. Implications for researchers and practitioners are discussed.
The Helmholtz Equation with Uncertainties in the Wavenumber
Authors: Pulch Roland , Sète Olivier
Published: February 2024

We investigate the Helmholtz equation with suitable boundary conditions and uncertainties in the wavenumber. Thus the wavenumber is modeled as a random variable or a random field. We discretize the Helmholtz equation using finite differences in space, which leads to a linear system of algebraic equations including random variables. A stochastic Galerkin method yields a deterministic linear system of algebraic equations. This linear system is high-dimensional, sparse and complex symmetric but, in general, not hermitian. We therefore solve this system iteratively with GMRES and propose two preconditioners: a complex shifted Laplace preconditioner and a mean value preconditioner. Both preconditioners reduce the number of iteration steps as well as the computation time in our numerical experiments.
Novel Fluoroboric Acid Additive for Blend Membrane to be Used in PEM Fuel Cell, Characterization Studies, and Performance Test
Authors: Yagizatli Yavuz , Ar Irfan
Published: February 2024

This study focuses on developing an alternative membrane for PEMFC due to the disadvantages of using Nafion. Fluoroboric acid (FBA) was used as an additive material to SPEEK-PVA blend membranes at different weight ratios (1%, 5%, 7.5%, 10%, and 12.5%), and a synthesis procedure was carried out with the solution-casting. Thermal crosslinking was performed with all membranes. Utilizing FBA, with its highly electronegative fluorine groups, is a novel approach expected to enhance proton conductivity. The structural, morphological, and thermal properties of the synthesized membranes were determined by FTIR, XRD, SEM, TGA-DTG, and DSC. Water uptake capacity (WUC), swelling property, area change, dynamic mechanical analysis, ion exchange capacity (IEC), AC impedance analysis, hydrolytic stability, and oxidative stability analyses were performed for fuel cell applications. Although FBA does not have a crystal structure, the synergy it created with the SPEEK-PVA membrane increased the crystallinity of the membrane and, accordingly, glass transition temperature. SEM images of membranes at a ratio above 7.5% show that agglomerations occur in the structure and this is supported by other analyses. It was determined that the membrane composition with the highest WUC (16.44%), IEC (1.55 meq/g), and proton conductivity (0.57 S/cm) values contained 7.5% FBA from the characterization studies, and a single-cell performance test was actualized with this. 418 mA/cm2 current density and 250.8 mW/cm2 power density were obtained at 0.6 V cell potential, with the membrane containing 7.5% FBA. This study shows that the synthesized membrane, especially the FBA, is a promising option for PEMFC application.

Graphical Abstract
Grazing distribution of wild guanacos and livestock in Patagonian rangelands: an ecological approach to assess mixed carrying capacity and overgrazing risk in extensive pastoral systems
Authors: Rodríguez Victoria , Marino Andrea , Schroeder Natalia
Published: February 2024

Context

Along with forage availability, rangeland’s carrying capacity (CC) is determined by other landscape features limiting the spatial distribution of the animals, such as water sources or topography. However, livestock management is often based on the stock adjustment to an estimated CC, assuming that the animals use the entire paddocks and wild herbivores are absent.

Objectives

Our objectives were to address how the CC estimation deviates from the classic outcome when the effective space use by livestock is considered, and when the forage consumption by co-occurring wild herbivore is accounted for. Finally, we evaluated large herbivores densities regarding this mixed CC.

Methods

Based on herbivore counts and geo-referenced explanatory variables within a ranch of Chubut, Argentina, we predicted sheep and guanaco distribution at a scale of 0.25 km2 cells. Addressing the relationship between the predicted sheep stock and the CC in each cell, we then re-calculated the CC adjusted by spatial use. We also estimated a mixed CC by computing the forage consumption by sheep and guanacos.

Results

Sheep distribution was shaped mainly by drinking water location, promoting over and under-grazed areas. Guanaco distribution pattern opposed livestock density. Accounting for the restrictions in sheep spatial use resulted in a reduction of the estimated CC compared to the classic approach, whereas the mixed approach resulted in higher CC estimates.

Conclusions

Accounting for herbivore presence and distribution modifies the CC estimation and therefore the diagnosis of overstock situations. The proposed adjustments to CC assessment methods can contribute to the sustainable management of livestock and wildlife in rangelands.
Goal-conditioned offline reinforcement learning through state space partitioning
Authors: Wang Mianchu , Jin Yue , Montana Giovanni
Published: February 2024

Offline reinforcement learning (RL) aims to create policies for sequential decision-making using exclusively offline datasets. This presents a significant challenge, especially when attempting to accomplish multiple distinct goals or outcomes within a given scenario while receiving sparse rewards. Prior methods using advantage weighting for offline goal-conditioned learning improve policies monotonically. However, they still face challenges from distribution shift and multi-modality that arise due to conflicting ways to reach a goal. This issue is especially challenging in long-horizon tasks, where the presence of multiple, often conflicting, solutions makes it hard to identify a single optimal policy for transitioning from a state to a desired goal. To address these challenges, we introduce a complementary advantage-based weighting scheme that incorporates an additional source of inductive bias. Given a value-based partitioning of the state space, the contribution of actions expected to lead to target regions that are easier to reach, compared to the final goal, is further increased. Our proposed approach, Dual-Advantage Weighted Offline Goal-conditioned RL, outperforms several competing offline algorithms in widely used benchmarks. Furthermore, we provide a theoretical guarantee that the learned policy will not be inferior to the underlying behavior policy.
Goal exploration augmentation via pre-trained skills for sparse-reward long-horizon goal-conditioned reinforcement learning
Authors: Wu Lisheng , Chen Ke
Published: February 2024

Reinforcement learning often struggles to accomplish a sparse-reward long-horizon task in a complex environment. Goal-conditioned reinforcement learning (GCRL) has been employed to tackle this difficult problem via a curriculum of easy-to-reach sub-goals. In GCRL, exploring novel sub-goals is essential for the agent to ultimately find the pathway to the desired goal. How to explore novel sub-goals efficiently is one of the most challenging issues in GCRL. Several goal exploration methods have been proposed to address this issue but still struggle to find the desired goals efficiently. In this paper, we propose a novel learning objective by optimizing the entropy of both achieved and new goals to be explored for more efficient goal exploration in sub-goal selection based GCRL. To optimize this objective, we first explore and exploit the frequently occurring goal-transition patterns mined in the environments similar to the current task to compose skills via skill learning. Then, the pre-trained skills are applied in goal exploration with theoretical justification. Evaluation on a variety of spare-reward long-horizon benchmark tasks suggests that incorporating our method into several state-of-the-art GCRL baselines significantly boosts their exploration efficiency while improving or maintaining their performance.
Solutions to graded reflection equation of GL-type
Authors: Algethami D. , Mudrov A. , Stukopin V.
Published: February 2024

We list solutions of the graded reflection equation associated with the fundamental vector representation of a quantum supergroup of GL-type.
Review: Human stem cell-based 3D in vitro angiogenesis models for preclinical drug screening applications
Authors: Esparza Aibhlin , Jimenez Nicole , Borrego Edgar A. , Browne Shane , Natividad-Diaz Sylvia L.
Published: February 2024

Vascular diseases are the underlying pathology in many life-threatening illnesses. Human cellular and molecular mechanisms involved in angiogenesis are complex and difficult to study in current 2D in vitro and in vivo animal models. Engineered 3D in vitro models that incorporate human pluripotent stem cell (hPSC) derived endothelial cells (ECs) and supportive biomaterials within a dynamic microfluidic platform provide a less expensive, more controlled, and reproducible platform to better study angiogenic processes in response to external chemical or physical stimulus. Current studies to develop 3D in vitro angiogenesis models aim to establish single-source systems by incorporating hPSC-ECs into biomimetic extracellular matrices (ECM) and microfluidic devices to create a patient-specific, physiologically relevant platform that facilitates preclinical study of endothelial cell-ECM interactions, vascular disease pathology, and drug treatment pharmacokinetics. This review provides a detailed description of the current methods used for the directed differentiation of human stem cells to endothelial cells and their use in engineered 3D in vitro angiogenesis models that have been developed within the last 10 years.
SR-MACL: Session-Based Recommendation with Multi-layer Aggregation Augmentation in Contrastive Learning
Authors: Gao Shiwei , Zeng Yufeng , Dang Xiaochao , Dong Xiaohui
Published: February 2024

Session-based recommendation (SBR) aims to predict the next item of interest in chronological order based on a given sequence of short-term behaviour of anonymous users. Due to the limited data available for short-term user interactions, its performance is more susceptible to data sparsity problems than traditional recommendation methods. Contrastive learning is often used to solve the data sparsity problem due to its ability to extract general features from the raw data. Existing session-based recommendation methods based on graph contrastive learning typically build graph contrastive learning by using information from other sessions to generate augmented views. While this avoids the problem that the use of dropout in traditional contrast learning methods can cause damage to the session context, it inevitably introduces irrelevant item information, which interferes with accurately modelling user interests and leads to sub-optimal model performance. To address these issues, we propose a new session recommendation method based on multi-layer aggregation augmentation contrastive learning, namely SR-MACL. In SR-MACL we construct a contrastive view by adding noise to the embedding representation and forming a contrastive embedding representation by multi-layer aggregation, which not only effectively solves the problem that traditional graph enhancement methods can destroy the context of the whole session, but also avoids the interference of irrelevant items. Experimental results on three real datasets have shown that SR-MACL can improve the accuracy of recommendation results and predict the user's next interaction more effectively.
Designing policies that could work: understanding the interaction between policy design spaces and organizational responses in public sector
Authors: Capano Giliberto , Lepori Benedetto
Published: February 2024

The goal of this paper is to contribute toward bridging the gap between policy design and implementation by focusing on domains, such as education, healthcare and community services, where policy implementation is largely left to the autonomous decision of public service providers, which are strategic actors themselves. More specifically, we suggest that two characteristics of policy design spaces in which policies are designed, i.e., the level of ideational coherence and the prevailing function of the adopted policy instruments, generate systematic patterns of responses in terms of the extent of compliance with policy goals, the presence of strategic gaming and possible defiance. We illustrate our model through a contrastive case study of the introduction of performance-based funding in the higher education sector in four European countries (France, Italy, Norway, and the United Kingdom). Our analysis displays that policy designs chosen by governments to steer public systems have different trade-offs in terms of responses of the public organizations involved that are essential to effectively implement governmental policies. The model we are proposing provides therefore a framework to understand how these interactions unfold in specific contexts, what are their effects on the achievement of policy goals and how policymakers could exploit their degrees of freedom in policy design to reduce unwanted effects.
DFT and QSAR study of Catechol-O-methyltransferase (COMT) as inhibitors for Parkinson’s disease treatment
Authors: Sherif Salma , Sameh Ahmed , Salah Sohaila Mohammed , Omar Amina , Elhaes Hanan , Ibrahim Asmaa , Refaat Ahmed , Ibrahim Medhat A.
Published: February 2024

Parkinson’s disease is characterized by a lack of the neurotransmitter or cell-signaling molecule dopamine. Levodopa is a well-known drug for Parkinson’s disease since it induces dopamine. Catechol-O-methyltransferase (COMT) are enzymes that break down levodopa, limiting the amount delivered to the brain. COMT inhibitors act by extending the duration of action of levodopa, thus improving the amount of time benefit from levodopa. There are several FDA-approved COMT inhibitors used, such as Entacapone and Tolcapone. Tolcapone can penetrate blood-brain barrier (BBB), but most of the drug stays in the plasma because its high protein bound, and it has severe side effects, while Entacapone cannot penetrate BBB, which reduces drug efficiency. This study aims to design higher-efficiency drug inhibitors by investigating the physical properties in terms of total energy, total dipole moment and HOMO/LUMO band gap at DFT: B3LYP level using the LAN2DZ basis set, in addition to quantitative structure activity relationship (QSAR) calculations to test the biological activity of these drug inhibitors for the treatment of Parkinson’s disease.
The Oxidation Behaviors of NiCoCrAlY Coatings After Pre-Oxidation Treatment During High-Temperature Oxidation at 800 ℃ and 900 ℃
Authors: Negami Masahiro , Yamabe-Mitarai Yoko
Published: February 2024

Thermal barrier coatings (TBCs) are essential for protecting the high-temperature components in gas turbines. However, the durability of TBCs is limited, and new technologies to improve their lifetime are necessary. This study focuses on the pre-oxidation treatment of the NiCoCrAlY bond coat in TBCs to reduce the growth rate of the thermally grown oxide (TGO) and improve the TBC lifetime. The mechanism of the TGO growth rate reduction by the pre-oxidation treatment of NiCoCrAlY was investigated. Oxidation behaviors of the surface of NiCoCrAlY coating samples with or without pre-oxidation treatment were evaluated in air at 800 °C and 900 °C. In-situ X-ray diffraction (XRD) measurements and isothermal oxidation tests were performed. The obtained results revealed that the growth rate of TGO is significantly suppressed by α-Al2O3 layer formed by the pre-oxidation treatment. The generation of γ-Al2O3 and θ-Al2O3, which are typically formed below 900 °C, was significantly reduced by pre-oxidation. It is suggested that this reduction suppresses of the TGO growth.
Pharmacists working in residential aged care: a survey of pharmacist interest and perceived preparedness
Authors: Cross Amanda J. , Hawthorne Deborah , Kouladjian O’Donnell Lisa , Lee Kenneth , Page Amy Theresa
Published: February 2024

Background

Pharmacists involvement in residential aged care facilities has traditionally been limited to that of an external contractor providing medication reviews, or medication supply.

Aim

To explore Australian pharmacists’ interest and perceived preparedness to work as on-site pharmacists in residential aged care.

Method

National cross-sectional anonymous online survey open for two weeks (September 17th to October 1st 2022) consisting of Likert-type, multiple choice and multiple selection questions. Australian pharmacists were recruited using a broad advertising strategy which included social and traditional media platforms, and snowball sampling. Data were collected on pharmacist self-reported interest and perceived preparedness to work as on-site aged care pharmacists in residential aged care. Data were analysed using descriptive statistics.

Results

Responses were received from 720 participants, 643 were eligible. Most participants were female (n = 466, 73%) and mean (SD) age was 43.5 (SD 12.5) years. Over half the participants were interested or extremely interested in working as an on-site aged care pharmacist (56%, n = 360), and agreed or strongly agreed (n = 475, 76%) that they felt prepared to work as an on-site aged care pharmacist. Most pharmacists felt prepared to engage in a variety of roles within the facilities (> 73% for each role), including resident and system level roles, and the majority agreed they felt prepared to engage with stakeholders, including general practitioners (93%) and medical specialists (86%).

Conclusion

Pharmacists reported they are interested and feel prepared to work as on-site aged care pharmacists. These findings will inform the roll-out of this new model of care to enhance multidisciplinary collaboration in residential aged care.

Graphical Abstract
Effects of inpatient creatinine testing frequency on acute kidney injury identification and staging: a historical cohort study
Authors: Oliveira Catarina Luz , Duarte-Ramos Filipa , Alves da Costa Filipa , Fernandez-Llimos Fernando
Published: February 2024

Background

Acute kidney injury (AKI) is a multifactorial condition often induced by drugs commonly used in hospitals. Identifying and staging AKI necessitates frequent monitoring of renal function.

Aim

To assess the impact of real-world hospital practices regarding serum creatinine (SCr) testing on the identification and staging of AKI, and its implications for adjusting drug doses.

Method

A historical cohort study utilizing hospital records from all adult patients admitted between 01/06/2018 and 31/12/2020 was conducted. Patients with no SCr assessment during their stay or those with an SCr at admission ≥ 2 mg/dL were excluded. AKI was determined using two criteria, namely AKIN and KDIGO, considering the time intervals between two SCr tests as outlined in the criteria. Additionally, patients with SCr increases exceeding AKI limits, regardless the time interval, were also identified. The estimated glomerular filtration rate (eGFR) and kinetic eGFR (KeGFR) were calculated.

Results

During the study period, 17,269 hospitalizations and 62,255 SCr tests were recorded. Among the 17,032 hospitalizations with a length of stay > 48 h, 46.8% experienced periods with no SCr tests performed for more than 48 h. Any stage of AKI was identified in 7.0% of patients and in 9.1% using AKI and KDIGO criteria, respectively. Ignoring time limits in both criteria revealed potential AKI in 1942 patients (11.2%), indicating a potential underdiagnosis of AKI by 37.5% or 19.1%, depending on the criteria used. A total of 76 drugs requiring dose adjustment in patients with eGFR ≤ 50 ml/min were prescribed in 78.5% admissions. These drugs were prescribed in 87.9% of patients potentially underdiagnosed with AKIN and in 88.9% with KDIGO.

Conclusion

There is a need for changes in the established hospital procedures to ensure more frequent testing of SCr levels. Implementing an advanced scope of practice for clinical pharmacists could support these changes.
Model-averaging as an accurate approach for ex-post economic optimum nitrogen rate estimation
Authors: Matavel Custódio Efraim , Meyer-Aurich Andreas , Piepho Hans-Peter
Published: February 2024

Finding economic optimum fertilizer rate with good accuracy is essential for optimal crop yield, efficient resource utilization, and environmental well-being. However, the prevailing incomplete understanding of input-output relationships leads to imprecise crop yield response functions, such as those for winter wheat, and potentially biased fertilizer choices. From a statistical point of view, there is uncertainity with regards to which model is most suitable to estimate the economic optimum fertilizer rate. This complexity is amplified when considering site-specific nitrogen fertilization, which factors into elements like soil attributes, topography, and crop variations within a field, as opposed to uniform application. This study undertakes a comparative analysis to evaluate biases, variance, mean squared errors and confidence intervals in Economic Optimum Nitrogen Rate (EONR) estimations across different functional forms. The goal is to uncover performance discrepancies among these forms and explore potential advantages of adopting model averaging for optimizing nitrogen use in crop cultivation. The results of simulations reveal noteworthy biases when comparing diverse yield functions with the averaged model, particularly evident in the Linear-Plateau and Mitscherlich models. Moreover, analysis of empirical data indicates that confidence intervals for the averaged model overlap with the projected ranges of all functions. This implies that the averaged model could be suitable for determining EONR and effectively address the problem of model specification without focusing on one specific functional form. The effectiveness of model averaging hinges on incorporating models that well approximate the true model. However, even if the true model is not known, the average model can provide reasonable information for determining the EONR, provided that similar model specifications are considered. This has implications for modelling of yield response for various applications and can contribute to unbiased estimations of yield response.
Strong Gravitational Lensing and Microlensing of Supernovae
Authors: Suyu Sherry H. , Goobar Ariel , Collett Thomas , More Anupreeta , Vernardos Giorgos
Published: February 2024

Strong gravitational lensing and microlensing of supernovae (SNe) are emerging as a new probe of cosmology and astrophysics in recent years. We provide an overview of this nascent research field, starting with a summary of the first discoveries of strongly lensed SNe. We describe the use of the time delays between multiple SN images as a way to measure cosmological distances and thus constrain cosmological parameters, particularly the Hubble constant, whose value is currently under heated debates. New methods for measuring the time delays in lensed SNe have been developed, and the sample of lensed SNe from the upcoming Rubin Observatory Legacy Survey of Space and Time (LSST) is expected to provide competitive cosmological constraints. Lensed SNe are also powerful astrophysical probes. We review the usage of lensed SNe to constrain SN progenitors, acquire high-z SN spectra through lensing magnifications, infer SN sizes via microlensing, and measure properties of dust in galaxies. The current challenge in the field is the rarity and difficulty in finding lensed SNe. We describe various methods and ongoing efforts to find these spectacular explosions, forecast the properties of the expected sample of lensed SNe from upcoming surveys particularly the LSST, and summarize the observational follow-up requirements to enable the various scientific studies. We anticipate the upcoming years to be exciting with a boom in lensed SN discoveries.
Large-scale unsupervised spatio-temporal semantic analysis of vast regions from satellite images sequences
Authors: Echegoyen Carlos , Pérez Aritz , Santafé Guzmán , Pérez-Goya Unai , Ugarte María Dolores
Published: February 2024

Temporal sequences of satellite images constitute a highly valuable and abundant resource for analyzing regions of interest. However, the automatic acquisition of knowledge on a large scale is a challenging task due to different factors such as the lack of precise labeled data, the definition and variability of the terrain entities, or the inherent complexity of the images and their fusion. In this context, we present a fully unsupervised and general methodology to conduct spatio-temporal taxonomies of large regions from sequences of satellite images. Our approach relies on a combination of deep embeddings and time series clustering to capture the semantic properties of the ground and its evolution over time, providing a comprehensive understanding of the region of interest. The proposed method is enhanced by a novel procedure specifically devised to refine the embedding and exploit the underlying spatio-temporal patterns. We use this methodology to conduct an in-depth analysis of a 220 km$$^2$$2region in northern Spain in different settings. The results provide a broad and intuitive perspective of the land where large areas are connected in a compact and well-structured manner, mainly based on climatic, phytological, and hydrological factors.