bluuebunny/crossref_metadata_2025 huggingface dataset:
A systematic review of techniques and clinical evidence to adopt virtual reality in post-stroke upper limb rehabilitation
Authors: Mani Bharathi V. , Manimegalai P. , George S. Thomas , Pamela D. , Mohammed Mazin Abed , Abdulkareem Karrar Hameed , Jaber Mustafa Musa , Damaševičius Robertas
Published: November 2024

Recognizing the limitations of traditional therapy can be tedious and demotivating, we explore VR’s dynamic and immersive environment to potentially improve patient engagement and motivation. This approach promises accelerated recovery by integrating real-time feedback and progress monitoring. This study aims to compare various VR training techniques employed for upper limb rehabilitation in stroke survivors. We have followed the PRISMA guidelines for systematic reviews. Articles were filtered with title words such as “virtual reality rehabilitation”, “rehabilitation”, “upper limb”, “lower limb”, “interactive gaming system”, and “VR based games” were searched in databases (LILACS, PUBMED, IEEE, WoS, and Scopus). Articles published between 2005 and 2021 were analyzed. There were 820 articles found, but only the most relevant 96 papers were analyzed. Most of the studies were randomised controlled trials (RCTs) that were submitted in 2014 or beyond. The sample size ranged from 5 to 96 persons with chronic stroke, or adults and seniors. There were no samples analyzed for those under the age of 18. Nintendo Wii® and Microsoft’s Kinect were the most popular video gaming systems. In most of the publications, the intervention took place 2–3 sessions per week, for about 2–12 weeks, with each session lasting 30 to 60 min. The most assessed outcomes were body steadiness, upper extremity motor capabilities, daily tasks, and quality of life. The Fugl–Meyer Assessment was one the commonly used tool for measuring outcomes. After VR therapy, the research found that quality of life, dynamic steadiness, and upper extremity movement function improved. To achieve dynamic equilibrium, VR proved more beneficial than traditional treatments. The most important outcomes, the researchers focused, were day-to-day activity and physical movements of the patients. Some studies investigated the early consequences of VR on daily activities and social involvement.
A Kernel approach for extending nonparametric multivariate analysis of variance in high-dimensional settings
Authors: Gallego Vicente , Oller Ramon
Published: November 2024

The nonparametric multivariate analysis of variance (NPMANOVA) testing procedure has been proven to be a valuable tool for comparing groups. In the present paper, we propose a kernel extension of this technique in order to effectively confront high-dimensionality, a recurrent problem in many fields of science. The new method is called kernel multivariate analysis of variance (KMANOVA). The basic idea is to take advantage of the kernel framework: we propose to project the data from the original data space to a Hilbert space generated by a given kernel function and then perform the NPMANOVA method in the reproducing kernel Hilbert space (RKHS). Dispersion of the embedded points can be measured by the distance induced by the inner product in the RKHS but also by many other distances best suited in high-dimensional settings. For this purpose, we study two promising distances: a Manhattan-type distance and a distance based on an orthogonal projection of the embedded points in the direction of the group centroids. We show that the NPMANOVA method and the KMANOVA method with the induced distance are essentially equivalent. We also show that the KMANOVA method with the other two distances performs considerably better than the NPMANOVA method. We illustrate the advantages of our approach in the context of genetic association studies and demonstrate its usefulness on Alzheimer’s disease data. We also provide a software implementation of the method that is available on GitHub https://github.com/8699vicente/Kmanova.
Genomic insights into climate change-induced forest dieback in Abies alba hotspots of decline
Authors: García-García Isabel , Méndez-Cea Belén , Gallego Francisco Javier , Linares Juan Carlos , Horreo Jose Luis
Published: November 2024

Understanding adaptive genetic responses to climate change is an issue of utmost importance to improve conservation policies and adaptive management. This study deeps on it, focusing on rear-edge silver fir (Abies alba) forests, where decline has been reported and linked to climatic stressors, such as warming and recurrent drought events. Hotspots and coldspots of forest decline and mortality were defined. Different sets of single nucleotide polymorphisms (SNPs), namely genome-wide and adaptive, were used to study their genetic characteristics, aiming to identify differences in genetic diversity between vigor classes (declining and non-declining trees) and age cohorts (adult trees and saplings). Global DNA methylation levels were assessed to investigate a possible role of epigenetic processes in adaptation to stressful environments. Parentage and relatedness analysis were conducted to track the genetic lineage of trees from each site. Our findings indicate that, even though adaptive SNPs seem to provide more insightful information than the genome-wide set, the optimal approach for evolutionary studies is a combination of both. Changes in adaptive genomic diversity and DNA methylation were observed between vigor classes, revealing the existence of a molecular basis behind the ongoing decline events in silver forests. Besides, trees’ relatives display a higher mixture of origins in coldspots, which could provide a temporary refuge for the species’ genetic diversity and adaptive potential. All in all, both genetic and epigenetic characteristics should be considered in order to comprehend how forest trees respond to climate stress to achieve adaptation to climate change.
Helmholtz FEM solutions are locally quasi-optimal modulo low frequencies
Authors: Averseng M. , Galkowski J. , Spence E. A.
Published: November 2024

For h-FEM discretisations of the Helmholtz equation with wavenumber k, we obtain k-explicit analogues of the classic local FEM error bounds of Nitsche and Schatz (Math. Comput. 28(128), 937–958 1974), Wahlbin (1991, §9), Demlow et al.(Math. Comput. 80(273), 1–9 2011), showing that these bounds hold with constants independent of k, provided one works in Sobolev norms weighted with k in the natural way. We prove two main results: (i) a bound on the local $$H^1$$

H
1

error by the best approximation error plus the $$L^2$$

L
2

error, both on a slightly larger set, and (ii) the bound in (i) but now with the $$L^2$$

L
2

error replaced by the error in a negative Sobolev norm. The result (i) is valid for shape-regular triangulations, and is the k-explicit analogue of the main result of Demlow et al. (Math. Comput. 80(273), 1–9 2011). The result (ii) is valid when the mesh is locally quasi-uniform on the scale of the wavelength (i.e., on the scale of $$k^{-1}$$

k

-
1

) and is the k-explicit analogue of the results of Nitsche and Schatz (Math. Comput. 28(128), 937–958 1974), Wahlbin (1991, §9). Since our Sobolev spaces are weighted with k in the natural way, the result (ii) indicates that the Helmholtz FEM solution is locally quasi-optimal modulo low frequencies (i.e., frequencies $$\lesssim k$$

≲
k

). Numerical experiments confirm this property, and also highlight interesting propagation phenomena in the Helmholtz FEM error.
Amelioration of hypoxia and cold stress in Nile tilapia: comparative effect of Chlorella vulgaris and its nanoparticle dietary supplementation on performance, antioxidant, hepatic functions, and meat quality
Authors: Youssuf Hadeer , Soror Eman I. , Shehab Ahmed , El-daim Amira M. , Abo-Gamil Zienab H. , Ahmed-Farid Omar , Hamad Ahmed , Edris Shimaa , Matter Aya F.
Published: November 2024

Nile tilapia, a widely cultivated freshwater fish, faces significant stressors, such as hypoxia and cold temperatures, which can negatively impact its quality and growth. The current study explored the impact of Chlorella vulgaris (CV) powder and its nanoparticles (CVNPs) on the growth performance, antioxidant capacity, liver protection, and meat quality of Nile tilapia to alleviate hypoxia and cold stress. A total of 450 healthy 28-day-old Nile tilapia fingerlings (average weight 5.32 ± 1.1 g, length 3.1 ± 0.5 cm) were divided into five groups: T1 (2.5 g/kg CV), T2 (5 g/kg CV), T3 (2.5 g/kg CVNP), T4 (5 g/kg CVNP), and the control group received a basal diet without additives, each with three subgroups in tri-replicate (10 fish/replicate). After six weeks of feeding, growth metrics and meat quality parameters were assessed, and each group was subjected to hypoxia, cold stress, or optimal conditions. The results revealed that T4 exhibited the highest weight gain (WG) and lowest feed conversion ratio (FCR), whereas T1 showed the highest specific growth rate (SGR) and length gain. Hypoxia and cold stress significantly (p < 0.05) increased cortisol, oxidative markers (MDA, NO, and GSSG), and liver enzymes (ALT and AST) while reducing (p < 0.05) antioxidant markers (SOD and GSH) and total cholesterol (TC). ATP levels significantly (p < 0.05) decreased in hypoxic fish, indicating muscle energy depletion. T1 significantly (p < 0.05) lowered cortisol levels, whereas T2 and T3 significantly (p < 0.05) increased superoxide dismutase (SOD) levels. T2 also significantly (p < 0.05) increased the TC level. ALT levels significantly (p < 0.05) decreased at T1, T2, and T4, with AST levels reduced at T4 only. CV and CVNP supplementation significantly (p < 0.05) reduced the muscle MDA levels under optimal and stressful conditions, notably at T1 and T4. Additionally, meat lightness, yellowness, and chroma significantly (p < 0.05) increased in stressed tilapia, whereas meat redness was improved under optimal conditions. Fatty acid profiles varied with CV and CVNP levels across different conditions. In conclusion, CV, particularly in the nanoparticle form, enhanced the growth, antioxidant activity, and meat quality of tilapia under physical stress.
Approximate bregman proximal gradient algorithm for relatively smooth nonconvex optimization
Authors: Takahashi Shota , Takeda Akiko
Published: November 2024

In this paper, we propose the approximate Bregman proximal gradient algorithm (ABPG) for solving composite nonconvex optimization problems. ABPG employs a new distance that approximates the Bregman distance, making the subproblem of ABPG simpler to solve compared to existing Bregman-type algorithms. The subproblem of ABPG is often expressed in a closed form. Similarly to existing Bregman-type algorithms, ABPG does not require the global Lipschitz continuity for the gradient of the smooth part. Instead, assuming the smooth adaptable property, we establish the global subsequential convergence under standard assumptions. Additionally, assuming that the Kurdyka–Łojasiewicz property holds, we prove the global convergence for a special case. Our numerical experiments on the

$$\ell _p$$

ℓ
p

regularized least squares problem, the

$$\ell _p$$

ℓ
p

loss problem, and the nonnegative linear system show that ABPG outperforms existing algorithms especially when the gradient of the smooth part is not globally Lipschitz or even locally Lipschitz continuous.
Fast convergence of the primal-dual dynamical system and corresponding algorithms for a nonsmooth bilinearly coupled saddle point problem
Authors: Ding Ke-wei , Fliege Jörg , Vuong Phan Tu
Published: November 2024

This paper studies the convergence rate of a second-order dynamical system associated with a nonsmooth bilinearly coupled convex-concave saddle point problem, as well as the convergence rate of its corresponding discretizations. We derive the convergence rate of the primal-dual gap for the second-order dynamical system with asymptotically vanishing damping term. Based on an implicit discretization scheme, we propose a primal-dual algorithm and provide a non-ergodic convergence rate under a general setting for the inertial parameters when one objective function is continuously differentiable and convex and the other is a proper, convex and lower semicontinuous function. For this algorithm we derive a

$$O\left( 1/k^2 \right) $$

O

1
/

k
2

convergence rate under three classical rules proposed by Nesterov, Chambolle-Dossal and Attouch-Cabot without assuming strong convexity, which is compatible with the results of the continuous-time dynamic system. For the case when both objective functions are continuously differentiable and convex, we further present a primal-dual algorithm based on an explicit discretization. We provide a corresponding non-ergodic convergence rate for this algorithm and show that the sequence of iterates generated weakly converges to a primal-dual optimal solution. Finally, we present numerical experiments that indicate the superior numerical performance of both algorithms.
More than just fun: Investigating students’ perceptions towards the potential of leveraging esports for promoting the acquisition of 21st century skills
Authors: Zhong Yuchun , Guo Kai , Fryer Luke Kutszik , Chu Samuel Kai Wah , Deng Hao
Published: November 2024

Esports (electronic sports) or competitive video gaming has taken its place as a leading form of entertainment for young people worldwide. However, esports were generally studied as a popular form of entertainment, and rarely have studies examined esports from an educational perspective. This study aimed to investigate the perceived impact of various types of esports on the acquisition of the 4Cs skills (critical thinking, creativity, collaboration, and communication) through the lenses of higher education students. A sequential mixed methods research design was adopted, with a questionnaire survey involving 628 participants followed by semi-structured interviews with 46 participants. The quantitative findings showed that the players generally perceived that esports can cultivate the 4Cs skills and their perception was significantly related to gaming experience, gaming frequency, and time spent on each gameplay. The higher level of engagement in games was associated with higher 4Cs skills. No significant difference was found in scores of the 4Cs skills across nine esports genres. Apart from statistical inferences, natural language process (NLP) techniques combined with thematic analysis were used to identify various mechanisms and elements of different games associated with the 4Cs skills development. The quantitative and qualitative findings collectively shed light on the potential of integrating esports elements into innovative pedagogies for promoting learning and developing the 4Cs skills for both life and career.
Editorial on special issues: “regional nutrient management in the circular economy” & “nitrogen and carbon recycling: benefits from the stakeholders’ perspective”
Authors: Wichern Florian , García-González María Cruz , Moral Raúl , Papangelou Anastasia , Spiller Marc
Published: November 2024

The intensification and specialization of global agriculture has led to a nutrient surplus resulting in regional environmental issues such as eutrophication and loss of biodiversity due to nutrient accumulation. Addressing these challenges requires a shift towards regional nutrient circularity, inspired by the principles of a circular economy, to create a more resource-efficient agricultural system. Circular agriculture, particularly in Europe, provides a model for sustainable nutrient management at various scales—local, regional, national and international. Existing technologies enable the production of fertilizers from secondary or waste streams and can improve nutrient use efficiency. The development of a market with transparency of supply and demand dynamics, standardized products, and reliable traceability is essential for the effective implementation of nutrient circularity. However, practical nutrient management takes place on a local level, with significant variability in environmental, economic, and social conditions at the farm and field levels due to differences in nutrient demand by crops or farm management, e.g. organic farming with often lower total nutrient intensity. Therefore, the successful development of a regional circular nutrient economy necessitates a stronger stakeholder perspective, emphasizing the importance of participatory research approaches. In addition to circularity, the efficiency of nutrient use from secondary fertilizers must be enhanced, and the broader food system must evolve towards more nutrient-efficient practices. This transformation will likely require adopting a planetary health diet that promotes both sufficiency and sustainability in nutrient use. Therefore, policy measures need to provide a clear regulatory framework at supranational (e.g. European Union) or national level, targeting environmental and societal goals, while at the same time supporting locally adaptable interventions through economic incentives and innovation support.
A brief review on Ce and Zr-based phase-separated metallic glasses
Authors: Singh Devinder , Singh Dharmendra , Tiwari Radhey Shyam , Ramasamy Parthiban , Eckert Jürgen
Published: November 2024

Phase-separated metallic glasses (MGs) have attracted a lot of interest recently because they offer a unique opportunity to design composites or alloys with hierarchical microstructure at various length scales. Phase-separated MGs differ from other MGs in terms of their structure and physical properties. Though a lot of theoretical work has been done, there is still a lack of understanding regarding the mechanism underlying phase separation in MGs. In general, phase separation in many MG systems is explained on the basis of nucleation and growth or spinodal decomposition mechanisms. On the other hand, the phase separation in Ce-based MGs is examined based on changes in the electronic structure of Ce atoms. This opens up a new direction of research for delineating issues pertaining to phase separation in amorphous systems. The present brief review aims to provide a comprehensive overview of the phase separation phenomenon in Ce- and Zr-based MG systems. It is broadly divided into two sections: the first section gives a brief introduction into the phase separation in MG systems, mechanisms of phase separation, micro-structural and thermal characteristics, and advantages of phase separation. The second section discusses some of the recent work on Ce- and Zr-based phase-separated MGs with respect to their design and properties.

Graphical Abstract
Experience with Mandatory Reporting of Intimate Partner Violence: An Explorative Qualitative Study of Service Providers and Help-Seeking IPV Victims and IPV Perpetrators
Authors: Kristiansen Susanne Tilke Thon , Leer-Salvesen Kjartan , Dahl Silje Louise , Linge Anita Dyb , Vatnar Solveig Karin Bø
Published: November 2024

Purpose

This study explored service providers’ and help-seeking intimate partner violence (IPV) victims’ and IPV perpetrators’ experiences with mandatory reporting of intimate partner violence (MR-IPV) in Norway. We examined the following research questions: How do service providers experience work within the context of MR-IPV? How do help-seeking IPV victims and IPV perpetrators experience MR-IPV?

Methods

This qualitative study used reflexive thematic analysis to identify, analyze and report themes and patterns uncovered in semi-structured interviews with 42 service providers and 6 help-seeking IPV victims and IPV perpetrators, following Braun and Clark’s Qualitative Research in Psychology six phases of reflexive thematic analysis.

Results

The service providers in this study aimed to establish collaboration with help-seeking IPV victims and IPV perpetrators to avert IPV rather than immediately reporting IPV to the police, thus working within the discretionary space allowed in the Norwegian legislation. Stories concerning breaches of trust related to MR-IPV were prominent in the interviews with both groups of help-seekers. The IPV perpetrators expressed having experienced a breach of trust when the IPV was reported to the police, while most of the IPV victims expressed a breach of trust due to a lack of MR-IPV.

Conclusions

IPV victims expressed ambivalence linked to a desire for interventions and a fear of not receiving adequate help. These findings highlight the challenges of certain requirements placed on service providers when working within the MR-IPV context; distinguishing between situations in which collaboration is appropriate and situations in which immediate reporting to the police is required.
Solution existence for a class of nonsmooth robust optimization problems
Authors: Hung Nguyen Canh , Chuong Thai Doan , Le Hoang Anh Nguyen
Published: November 2024

The main purpose of this paper is to investigate the existence of global optimal solutions for nonsmooth and nonconvex robust optimization problems. To do this, we first introduce a concept called extended tangency variety and show how a robust optimization problem can be transformed into a minimizing problem of the corresponding tangency variety. We utilize this concept together with a constraint qualification condition and the boundedness of the objective function to provide relationships among the concepts of robust properness, robust M-tamesness and robust Palais-Smale condition related to the considered problem. The obtained results are also employed to derive necessary and sufficient conditions for the existence of global optimal solutions to the underlying robust optimization problem.
A High-Order Eulerian–Lagrangian Runge–Kutta Finite Volume (EL–RK–FV) Method for Scalar Nonlinear Conservation Laws
Authors: Chen Jiajie , Nakao Joseph , Qiu Jing-Mei , Yang Yang
Published: November 2024

We present a class of high-order Eulerian–Lagrangian Runge–Kutta finite volume methods that can numerically solve Burgers’ equation with shock formations, which could be extended to general scalar conservation laws. Eulerian–Lagrangian (EL) and semi-Lagrangian (SL) methods have recently seen increased development and have become a staple for allowing large time-stepping sizes. Yet, maintaining relatively large time-stepping sizes post shock formation remains quite challenging. Our proposed scheme integrates the partial differential equation on a space-time region partitioned by linear approximations to the characteristics determined by the Rankine–Hugoniot jump condition. We trace the characteristics forward in time and present a merging procedure for the mesh cells to handle intersecting characteristics due to shocks. Following this partitioning, we write the equation in a time-differential form and evolve with Runge–Kutta methods in a method-of-lines fashion. High-resolution methods such as ENO and WENO-AO schemes are used for spatial reconstruction. Extension to higher dimensions is done via dimensional splitting. Numerical experiments demonstrate our scheme’s high-order accuracy and ability to sharply capture post-shock solutions with large time-stepping sizes.
Parametric Machine Learning-Based Adaptive Sampling Algorithm for Efficient IoT Data Collection in Environmental Monitoring
Authors: Algabroun Hatem , Håkansson Lars
Published: November 2024

With the IoT trend, wireless sensors are gaining growing interest. This is due to the possibility of installing them in locations inaccessible to wired sensors. Although great success has already been achieved in this area, energy limitation remains a major obstacle for further advances. As such, it is important to optimize sampling to a sufficient rate to catch important information without excessive energy consumption. One way to achieve sufficient sampling is by using an algorithm for adaptive sampling named dynamic sampling rate algorithm (DSRA); however, this algorithm requires an expert to set and tune its parameters, which might not always be readily available. This study aims to further develop this algorithm to be machine learning based to tune these parameters. To achieve this goal, the algorithm was modified and an optimization strategy that considers a predetermined error threshold was developed. Then the algorithm was implemented using simulated and real data with a set of predetermined errors thresholds to observe its performance. The results showed that the developed algorithm exhibited adaptive sampling behavior, and it could collect data efficiently depending on the predetermined error threshold. Based on the results, it is possible to conclude that the developed algorithm endows sensors with adaptive sampling capabilities based on the signal rate of change.
Are They Ready to Teach? Generative AI as a Means to Uncover Pre-Service Science Teachers’ PCK and Enhance Their Preparation Program
Authors: Blonder Ron , Feldman-Maggor Yael , Rap Shelley
Published: November 2024

Integrating generative artificial intelligence (GenAI) in pre-service teachers’ education programs offers a transformative opportunity to enhance the pedagogical development of future science educators. This conceptual paper suggests applying the GenAI tool to evaluate pedagogical content knowledge (PCK) among pre-service science teachers. By holding interactive dialogues with GenAI, pre-service teachers engage in lesson planning in a way that reveals their understanding of content, pedagogy, and PCK while facilitating the practical application of theoretical knowledge. Interpretation of these interactions provides insights into teachers-to-be knowledge and skills, enabling personalized learning experiences and targeted program adjustments. The paper underscores the need to equip pre-service teachers with the necessary competencies to utilize GenAI effectively in their future teaching practices. It contributes to the ongoing discourse on technology’s role in teacher preparation programs, highlighting the potential of addressing existing challenges in evaluating and developing teacher knowledge via GenAI. The suggested future research directions aim to further investigate the GenAI usage implications in educational contexts.
Lateritic Ni–Co Prospectivity Modeling in Eastern Australia Using an Enhanced Generative Adversarial Network and Positive-Unlabeled Bagging
Authors: Wake Nathan , Farahbakhsh Ehsan , Müller R. Dietmar
Published: November 2024

The surging demand for Ni and Co, driven by the acceleration of clean energy transitions, has sparked interest in the Lachlan Orogen of New South Wales for its potential lateritic Ni–Co resources. Despite recent discoveries, a substantial knowledge gap exists in understanding the full scope of these critical metals in this geological province. This study employed a machine learning-based framework, integrating multidimensional datasets to create prospectivity maps for lateritic Ni–Co deposits within a specific Lachlan Orogen segment. The framework generated a variety of data-driven models incorporating geological (rock units, metamorphic facies), structural, and geophysical (magnetics, gravity, radiometrics, and remote sensing spectroscopy) data layers. These models ranged from comprehensive models that use all available data layers to fine-tuned models restricted to high-ranking features. Additionally, two hybrid (knowledge-data-driven) models distinguished between hypogene and supergene components of the lateritic Ni–Co mineral systems. The study implemented data augmentation methods and tackled imbalances in training samples using the SMOTE–GAN method, addressing common machine learning challenges with sparse training data. The study overcame difficulties in defining negative training samples by translating geological and geophysical data into training proxy layers and employing a positive and unlabeled bagging technique. The prospectivity maps revealed a robust spatial correlation between high probabilities and known mineral occurrences, projecting extensions from these sites and identifying potential greenfield areas for future exploration in the Lachlan Orogen. The high-accuracy models developed in this study utilizing the Random Forest classifier enhanced the understanding of mineralization processes and exploration potential in this promising region.
Withhold by default: a difference between epistemic and practical rationality
Authors: Tucker Chris
Published: November 2024

In practical rationality, if two reasons for alternative actions are tied, then either action is *permissible*. In epistemic rationality, we get the Epistemic Ties Datum: if the reasons for belief and disbelief are tied, then withholding judgment is *required*. I argue that this difference is explained by a difference in default biases. Practical rationality is biased toward permissibility. An action is permissible unless the specific features of the situation (e.g., the costs and benefits that apply) make it prohibited. In contrast, epistemic rationality is biased toward withholding judgment. Withholding judgment is required unless the specific features of the situation (e.g., the evidence) makes belief or disbelief permissible. This difference explains the Epistemic Ties Datum. When the reasons for belief and disbelief are equally weighty, they cancel each other out. But then the only remaining reason is the default reason, or default bias, to withhold judgment. Since it is the only remaining reason, it requires us to withhold judgment.
The spontaneous provision of criminal law
Authors: Benzecry Gabriel F. , Thompson Henry A.
Published: November 2024

For decades, non-state actors have supplied criminal law in Brazil’s favelas. This paper offers a humanomics account of the private provision of an impure public good. Our analysis reaches three conclusions. First, criminal law can be provided without either public intervention or reliance on the price system. Informal norms may be sufficient, indicating that Adam Smith’s invisible hand logic extends beyond legal markets grounded in private property rights and governed by well-defined prices. Second, a common sense of propriety, a key aspect of the humanomics approach, may not always be context-free. One’s environment may shape the precise objects of propriety. Third, spontaneous legal orders can be robust to agent type.
COVID-19 in California Community Colleges: College Responses, College Resources, and Student Outcomes
Authors: Hart Cassandra M.D. , Xu Di , Alonso Emily , Hill Michael
Published: November 2024

In Spring 2020, colleges across the nation swiftly transitioned their operations—including both classes and student support services—to remote delivery on an emergency basis in response to the crisis posed by the COVID-19 pandemic. While prior research has documented that the transition was associated with decrements in student outcomes, there remains limited understanding of the organizational factors that might have mitigated these negative associations during the pandemic. Drawing on administrative data from the California Community College system, along with a novel survey conducted among distance education leaders, our study reveals that the degree of declines in course completion and course passing rates varied based on pre-COVID online education resources (such as the ratio of distance education personnel to students and the availability of pre-COVID professional development programs in online learning): Colleges with greater pre-COVID online resources experienced more modest declines in student performance. To a lesser extent, we also found that declines in student performance during the onset of the pandemic varied depending on the responses implemented in reaction to the pandemic, such as the extent of technology delivery to students. The implications of our findings extend to the realm of planning for the continuity of operations in potential future crises.
Institutional Complexity and Social Innovation: The Case of Chinese Social Enterprises
Authors: Fu Jiawei Sophia , Yan Shipeng
Published: November 2024

Social enterprises (SEs) have emerged throughout the world to address societal challenges through market-based activities and innovation. Research has focused on how SEs manage the tensions arising from the combination of social-welfare and market logics, neglecting the institutional complexity that arises in authoritarian regimes where the state plays a dominant role. Based on the institutional logics perspective and interview data of 42 SE leaders in China, we find that key tensions arise from the state and social-welfare logics and that state logic (re)configures the social–market relationships to be compatible. Chinese SEs employed depoliticization and localization to adapt to this unique form of institutional complexity in their social innovation efforts. This study advances research on SEs, institutional complexity, and hybrid organizing.
Using GeoMx DSP Spatial Proteomics to Investigate Immune Infiltration of NOD Mouse Islet and Exocrine Compartments
Authors: Tekin Hasim , Lindhardt Claes , Antvorskov Julie Christine , Bager Nicolai Schou , Michaelsen Signe Regner , Areškevičiūtė Aušrinė , Vind Jonas Pordel , Kristensen Bjarne Winther , Josefsen Knud
Published: November 2024

Purpose

Type 1 Diabetes (T1D) pathogenesis involves immune cells infiltrating pancreatic Islets of Langerhans, leading to T cell activation, beta cell destruction, and impaired insulin production. However, infiltration has a heterogenic nature that isn’t described in detail, as not all islets are infiltrated. The aim of this study was to investigate if the observed heterogeneity is coupled to differences in immune and/or dysfunctional status of islets or exocrine cells, and if specific markers could elucidate mechanistic details of T1D pathogenesis.

Procedures

The GeoMx platform was used to spatially quantify protein levels in pancreatic islets and exocrine tissue in Non-Obese Diabetic (NOD) mice. The protein panel included 17 immune activity markers and nine dysfunction markers. Immunohistochemical (IHC) staining and digital image analysis was used to analyze select marker proteins.

Results

Use of the GeoMx platform to investigate T1D was shown to be possible, as Granzyme B protein levels were found to be lower in distal islet areas when compared to proximal areas. Smooth Muscle Actin protein levels were higher in exocrine areas proximal to immune-infiltrated islets, when compared to distally located exocrine areas. Findings from GeoMx were however not observed in IHC-stained sections.

Conclusions

This study demonstrates that investigating T1D is possible with spatial proteomics, as the assays revealed presence of heterogenic islet areas in NOD mice, which may play a role in T1D progression and escape from immune recognition. This study highlights the potential of spatial technologies for elucidating T1D pathogenesis and future treatment strategies.
A two-step dynamic FEM-FELA approach for seismic slope stability assessment
Authors: Schmüdderich Christoph , Herz Charlotte , Albared Alischa , Machaček Jan , Prada-Sarmiento Luis Felipe , Staubach Patrick , Wichtmann Torsten
Published: November 2024

The determination of the factor of safety (FoS) of slopes during seismic excitation can be complex if the relevant effects of pore water pressure accumulation, nonlinear material response and variable shear strength are duly accounted for. A rational two-step approach to tackle this task based on a hydro-mechanically coupled dynamic simulation and finite element limit analyses is henceforth introduced. To ensure accurate transfer of the hydro-mechanical soil state, a mapping concept is presented, accounting for spatial distributions of stresses, excess pore water pressures, inertial forces and shear strength. The proposed approach is compared to limit equilibrium method (LEM) for the case of a large-scale water-saturated open cast mine slope subjected to seismic loading. In comparison with LEM, the new approach to assess seismic slope stability proves to be simpler in its implementation and straightforward, which could be an important asset for practitioners.
Immigrant Generation, Ethnicity, and Early-life Education Outcomes: Evidence from the Born in Bradford Family Cohort Study
Authors: Hou Bo , Nazroo James , Wright John , Mon-Williams Mark , Pickett Kate E.
Published: November 2024

This paper examines the relationship between ethnicity and immigrant generation in relationship to early educational outcomes and their potential determinants. Using Born in Bradford, a large longitudinal birth cohort, and its linked education and health records, we investigated the associations between ethnicity, immigration generations and education measures (Early Years Foundation Stage Profile and National Curriculum Key Stage One). We looked at the children of both first- and second-generation immigrants and compared them with White British non-immigrant children. Logistic regressions were used to examine the explanatory factors of the differences. On the Early Years Foundation Stage Profile, children of first-generation Pakistani immigrants did less well than White British non-immigrant children. This was largely related to language barriers. There were no significant differences between the children of second-generation Pakistani families and children of White British non-immigrant families. In Key Stage One results, there were no differences in reading and maths between children of first-generation Pakistani immigrants and the White British children, however, children of first-generation Pakistani immigrants had better scores in Key Stage One writing. Children of second-generation Pakistani immigrants had better odds of achieving expected standards in most models for reading and writing (but not maths) than the White British children. This might be attributed to better socioeconomic circumstances. Immigrant generation is an independent predictor for early educational outcomes. There are different patterns associated with different immigrant generations. Early life policy interventions to help children of first-generation immigrant with their English language before school could improve these children’s school readiness.
Standardization of radiation therapy quality control system through mutual quality control based on failure mode and effects analysis
Authors: Tanimoto Yuki , Oita Masataka , Koshi Kazunobu , Ishiwaki Kiyoshi , Hiramatsu Futoshi , Sasaki Toshihisa , Ise Hiroki , Miyagawa Takashi , Maeda Takeshi , Okahira Shinsuke , Hamaguchi Takashi , Kawaguchi Tatsuya , Funada Norihiro , Yamamoto Shuhei , Hiroshige Akira , Mukai Yuki , Yoshida Shohei , Fujita Yoshiki , Nakahira Atsuki , Honda Hirofumi
Published: November 2024

The advancement of irradiation technology has increased the demand for quality control of radiation therapy equipment. Consequently, the number of quality control items and required personnel have also increased. However, differences in the proportion of qualified personnel to irradiation techniques have caused bias in quality control systems among institutions. To standardize the quality across institutions, researchers should conduct mutual quality control by analyzing the quality control data of one institution at another institution and comparing the results with those of their own institutions. This study uses failure mode and effects analysis (FMEA) to identify potential risks in 12 radiation therapy institutions, compares the results before and after implementation of mutual quality control, and examines the utility of mutual quality control in risk reduction. Furthermore, a cost-effectiveness factor is introduced into FMEA to evaluate the utility of mutual quality control.
Calliandra hispidulocarpa (Fabaceae), a new species from Jalisco, Mexico, with an amended description of C. longipedicellata
Authors: Hernández Héctor M. , Gómez-Hinostrosa Carlos
Published: November 2024

We describe
Calliandra hispidulocarpa
(Fabaceae), a new species from the Sierra de Manantlán, southwestern Jalisco, Mexico. Specimens of the new species had been confused with the allopatric C. longipedicellata, a hypothetically closely related species restricted to a contiguous mountain range. The morphological differences between the two species are discussed and their geographical distribution is mapped.
Progress in the Identification and Design of Novel Antimicrobial Peptides Against Pathogenic Microorganisms
Authors: Sun Shengwei
Published: November 2024

The occurrence and spread of antimicrobial resistance (AMR) pose a looming threat to human health around the world. Novel antibiotics are urgently needed to address the AMR crisis. In recent years, antimicrobial peptides (AMPs) have gained increasing attention as potential alternatives to conventional antibiotics due to their abundant sources, structural diversity, broad-spectrum antimicrobial activity, and ease of production. Given its significance, there has been a tremendous advancement in the research and development of AMPs. Numerous AMPs have been identified from various natural sources (e.g., plant, animal, human, microorganism) based on either well-established isolation or bioinformatic pipelines. Moreover, computer-assisted strategies (e.g., machine learning (ML) and deep learning (DL)) have emerged as a powerful and promising technology for the accurate prediction and design of new AMPs. It may overcome some of the shortcomings of traditional antibiotic discovery and contribute to the rapid development and translation of AMPs. In these cases, this review aims to appraise the latest advances in identifying and designing AMPs and their significant antimicrobial activities against a wide range of bacterial pathogens. The review also highlights the critical challenges in discovering and applying AMPs.
Importance of LINC00852/miR-145-5p in breast cancer: a bioinformatics and experimental study
Authors: Shakoori Abbas , Hosseinzadeh Asghar , Nafisi Nahid , Omranipour Ramesh , Sahebi Leyla , Nazanin Hosseinkhan  , Ahmadi Mohsen , Ghafouri-Fard Soudeh , Abtin Maryam
Published: November 2024

Purpose

We aimed to examine the importance of an lncRNA, namely LINC00852, in the pathogenesis of breast cancer.

Materials and methods

In the current study, we used several online tools to examine the importance of LINC00852 in breast cancer. Then, we examined these findings in 50 pairs of breast cancer tissues and adjacent non-cancerous ones. We also re-evaluated the data of miR-145-5p signature from our recent study.

Results

While in silico tools revealed down-regulation of LINC00852 in breast cancer samples, expression assays showed significant up-regulation of this lncRNAs in breast cancer samples compared with matching control samples from Iranian patients. miR-145-5p was under-expressed in breast cancer samples compared with non-cancerous samples. LINC00852 could separate breast cancer tissues from adjacent non-malignant tissues with an AUC value of 0.7218 (P value < 0.001).

Conclusion

The current study potentiates LINC00852/miR-145-5p axis as a possible contributor to the pathogenesis of breast cancer.
Catecholamine-Induced Inflammasome Activation in the Heart Following Photothrombotic Stroke
Authors: Scott Xavier O. , Kerr Nadine A. , Sanchez-Molano Juliana , de Rivero Vaccari Juan Pablo , Hadad Roey , De La Cruz Alicia , Larsson H. Peter , Dietrich W. Dalton , Keane Robert W.
Published: November 2024

Cerebrovascular stroke patients exhibit an increased incidence of cardiac arrhythmias. The pathomechanisms underlying post-traumatic cardiac dysfunction include a surge of catecholamines and an increased systemic inflammatory response, but whether inflammasome activation contributes to cardiac dysfunction remains unexplored. Here, we used a mouse model of photothrombotic stroke (PTS) to investigate the role of inflammasome activation in post-stroke cardiac dysfunction by catecholamines and to evaluate the effectiveness of the inflammasome inhibitor IC100 on inflammasome activation. To evaluate functional electrophysiological changes in the heart by catecholamine treatment, we recorded action potential duration in excised zebrafish hearts with and without IC100 treatment. We show that PTS induced AIM2 inflammasome activation in atria and ventricles that was significantly reduced by administration of IC100. Injection of epinephrine into naïve mice induced a significant increase in AIM2, IL-1b and caspase-8 in atria. Treatment of excised zebrafish hearts with epinephrine shortened the action potential duration and this shortening that was reduced by IC100. These findings indicate that stroke initiates a catecholamine surge that induces inflammasome activation and pyroptosis in the heart that is blocked by IC100, thus providing a framework for the development of therapeutics for stroke-related cardiovascular injury.
Microcrystalline cellulose acetate incorporating cyanoacetyl moiety
Authors: Othman Hoda Sabry , Elsayed Alaa E. , Nawwar G. A. M.
Published: November 2024

This work is part of our research to develop facile green methods for synthesizing bioactive molecules from biomass. The current study deals with the preparation and investigation of the newly synthesized cyanoacetyl-acetylated microcrystalline cellulose (CAA-MCC). The novelty of this derivative lies not only in its ability to act as a green dry-film biocide/UV blocker for eco-friendly waterborne paints but also in being biomass-derived via solar pulping of rice straw, which is a mild process that produces cellulosic pulp and non-toxic black liquor. Solar acid dissociation of the bleached pulp produces microcrystalline cellulose (MCC), which was utilized to synthesize its acetate derivative incorporating the cyanoacetyl moiety (CAA-MCC). The presence of acetyl and cyano acetyl groups in CAA-MCC was confirmed using elemental and spectral analyses, including FT-IR and NMR. Two sets of paint formulations were prepared, one with CAA-MCC and the other with the commercial dry-film biocide Rocima 363. Scanning electron microscope (SEM) and energy-dispersive X-ray (EDAX) analyses were performed for MCC, CAA-MCC, and the prepared dry films. CAA-MCC demonstrated moderate antibacterial activity, encouraging its evaluation as a dry-film biocide and UV blocker. CAA-MCC paint films showed resistance to microbial growth on their surfaces without inhibition zones. Moreover, films were exposed to ultraviolet (UV) radiation while monitoring their color change over time. The results revealed that films containing CAA-MCC were more resistant to deterioration than those containing Rocima 363. Viscosity, X-cut adhesion, hardness, and water resistance were also evaluated, and they all improved with the CAA-MCC addition. CAA-MCC could act as a new, cost-effective alternative to petrochemical-derived biocides and UV blockers that can improve paint performance.

Graphical Abstract
Authority and responsibilities of an alliance manager: sustainability alliance case studies between corporate and heterogeneous sectors
Authors: Ishida Mitsue
Published: November 2024

In a world undergoing rapid change, the effective use of strategic alliances is important for a company to gain a competitive advantage. While previous research has mentioned the importance of understanding the authority and responsibilities of a successful alliance manager, few studies have investigated this topic using systematically gathered real-world data. This study aims to determine the kind of authority and responsibilities an alliance manager has in successful sustainability alliance projects. These generally require cooperation with players in heterogeneous sectors. An analytical framework was developed to examine sustainability alliance cases. Findings reveal that alliance managers at companies with excellent sustainability performance operate in an environment in which psychological safety is ensured. This enables them to autonomously develop emergent activities inside and outside the organization and have greater influence over alliance projects than the authority granted to them. This study suggests that it is essential for an organization to have a management philosophy based on sustainability as a standard for making value judgments. The communication of this philosophy contributes to the psychological safety of staff and thus their initiative taking in boundary spanning.