Open Research Questions Research Articles

Intestinal alterations and mild glucose homeostasis impairments in the offspring born to overweight rats

The gut plays a crucial role in metabolism by regulating the passage of nutrients, water and microbial-derived substances to the portal circulation. Additionally, it produces incretins, such as glucose-insulinotropic releasing peptide (GIP) and glucagon-like derived peptide 1 (GLP1, encoded by gcg gene) in response to nutrient uptake. We aimed to investigate whether offspring from overweight rats develop anomalies in the barrier function and incretin transcription. We observed pro-inflammatory related changes along with a reduction in Claudin-3 levels resulting in increased gut-permeability in fetuses and offspring from overweight rats. Importantly, we found decreased gip mRNA levels in both fetuses and offspring from overweight rats. Differently, gcg mRNA levels were upregulated in fetuses, downregulated in female offspring and unchanged in male offspring from overweight rats. When cultured with high glucose, intestinal explants showed an increase in gip and gcg mRNA levels in control offspring. In contrast, offspring from overweight rats did not exhibit any response in gip mRNA levels. Additionally, while females showed no response, male offspring from overweight rats did exhibit an upregulation in gcg mRNA levels. Furthermore, female and male offspring from overweight rats showed sex-dependent anomalies when orally challenged with a glucose overload, returning to baseline glucose levels after 120 min.These results open new research questions about the role of the adverse maternal metabolic condition in the programming of impairments in glucose homeostasis, enteroendocrine function and gut barrier function in the offspring from overweight mothers and highlight the importance of a perinatal maternal healthy metabolism.

Capturing the College Experience: A Four-Year Mobile Sensing Study of Mental Health, Resilience and Behavior of College Students during the Pandemic.

Understanding the dynamics of mental health among undergraduate students across the college years is of critical importance, particularly during a global pandemic. In our study, we track two cohorts of first-year students at Dartmouth College for four years, both on and off campus, creating the longest longitudinal mobile sensing study to date. Using passive sensor data, surveys, and interviews, we capture changing behaviors before, during, and after the COVID-19 pandemic subsides. Our findings reveal the pandemic's impact on students' mental health, gender based behavioral differences, impact of changing living conditions and evidence of persistent behavioral patterns as the pandemic subsides. We observe that while some behaviors return to normal, others remain elevated. Tracking over 200 undergraduate students from high school to graduation, our study provides invaluable insights into changing behaviors, resilience and mental health in college life. Conducting a long-term study with frequent phone OS updates poses significant challenges for mobile sensing apps, data completeness and compliance. Our results offer new insights for Human-Computer Interaction researchers, educators and administrators regarding college life pressures. We also detail the public release of the de-identified College Experience Study dataset used in this paper and discuss a number of open research questions that could be studied using the public dataset.

Gender and generational cohort impact on entrepreneurs’ emotional intelligence and transformational leadership

Emotional intelligence (EI) and leadership style are topics that have attracted a growing interest in the literature. In this study, we posit that entrepreneurs’ EI is an antecedent of transformational leadership (TL) while examining the moderating role of gender and generational cohort. Data were collected from 2,084 international entrepreneurs and analysed using multivariate analysis and hierarchical linear regression. The results confirm EI as an antecedent of TL and show that others’ emotion appraisal (OEA) and regulation of emotions (ROE) are the most contributing subdimensions of EI to TL. Moreover, the study also reveals significant gender and generational cohort differences for EI and TL. In one of the relevant findings, our research shows that only female Gen Z entrepreneurs have lower scores than their male counterparts. Although men’s EI scores are similar across generations, women’s scores are significantly higher in each older generation leaving ¡open questions for further research in the area.

Opinion: Stratospheric ozone – depletion, recovery and new challenges

Abstract. We summarise current important and well-established open issues related to the depletion of stratospheric ozone and discuss some newly emerging challenges. The ozone layer is recovering from the effects of halogenated source gases due to the continued success of the Montreal Protocol despite recent renewed production of controlled substances and the impact of uncontrolled very short-lived substances. The increasing atmospheric concentrations of greenhouse gases, such as carbon dioxide, methane (CH4) and nitrous oxide (N2O), have large potential to perturb stratospheric ozone in different ways, but their future evolutions, and hence impacts, are uncertain. Ozone depletion through injection of smoke particles has been observed following recent Australian wildfires. Further perturbations to the ozone layer are currently occurring through the unexpected injection of massive amounts of water vapour from the Hunga Tonga–Hunga Ha'apai volcano in 2022. Open research questions emphasise the critical need to maintain, if not expand, the observational network and to address the impending “satellite data gap” in global, height-resolved observations of stratospheric trace gases and aerosols. We will, in effect, be largely blind to the stratospheric effects of similar wildfire and volcanic events in the near future. Complex Earth system models (ESMs) being developed for climate projections have the stratosphere as an important component. However, the huge computational requirement of these models must not result in an oversimplification of the many processes affecting the ozone layer. Regardless, a hierarchy of simpler process models will continue to be important for testing our evolving understanding of the ozone layer and for providing policy-relevant information.

Comparing Metaheuristic Search Techniques in Addressing the Effectiveness of Clustering-Based DDoS Attack Detection Methods

Distributed Denial of Service (DDoS) attacks have increased in frequency and sophistication over the last ten years. Part of the challenge of defending against such attacks requires the analysis of very large volumes of data. Metaheuristic algorithms can assist in selecting relevant features from the network traffic data for use in DDoS detection models. By efficiently exploring different combinations of features, these methods can identify subsets that are informative for distinguishing between normal and attack traffic. However, identifying an optimized solution in this area is an open research question. Tuning the parameters of metaheuristic search techniques in the optimization process is critical. In this study, a switching approximation is used in a variety of metaheuristic search techniques. This approximation is used to find the best solution for the analysis of the network traffic features in either lower or upper values between 0 and 1. We compare the fine-tuning of this parameter against standard approaches and find that it is not substantially better than the BestFirst algorithm (a standard default approach for feature selection). This study contributes to the literature by testing and eliminating various fine-tuning strategies for the metaheuristic approach.

Hydrotropism mechanisms and their interplay with gravitropism.

Plants partly optimize their water recruitment from the growth medium by directing root growth toward a moisture source, a phenomenon termed hydrotropism. The default mechanism of downward growth, termed gravitropism, often functions to counteract hydrotropism when the water-potential gradient deviates from the gravity vector. This review addresses the identity of the root sites in which hydrotropism-regulating factors function to attenuate gravitropism and the interplay between these various factors. In this context, the function of hormones, including auxin, abscisic acid, and cytokinins, as well as secondary messengers, calcium ions, and reactive oxygen species in the conflict between these two opposing tropisms is discussed. We have assembled the available data on the effects of various chemicals and genetic backgrounds on both gravitropism and hydrotropism, to provide an up-to-date perspective on the interactions that dictate the orientation of root tip growth. We specify the relevant open questions for future research. Broadening our understanding of root mechanisms of water recruitment holds great potential for providing advanced approaches and technologies that can improve crop plant performance under less-than-optimal conditions, in light of predicted frequent and prolonged drought periods due to global climate change.

Transposed Poisson Structures

To present a survey on known results from the theory of transposed Poisson algebras, as well as to establish new results on this subject, are the main aims of the present paper. Furthermore, a list of open questions for future research is given.

Reinforcement Learning for Generative AI: State of the Art, Opportunities and Open Research Challenges

Generative Artificial Intelligence (AI) is one of the most exciting developments in Computer Science of the last decade. At the same time, Reinforcement Learning (RL) has emerged as a very successful paradigm for a variety of machine learning tasks. In this survey, we discuss the state of the art, opportunities and open research questions in applying RL to generative AI. In particular, we will discuss three types of applications, namely, RL as an alternative way for generation without specified objectives; as a way for generating outputs while concurrently maximizing an objective function; and, finally, as a way of embedding desired characteristics, which cannot be easily captured by means of an objective function, into the generative process. We conclude the survey with an in-depth discussion of the opportunities and challenges in this fascinating emerging area.

From everyday exposure to pragmatic mastery

Abstract In this paper, we review recent findings on the development of communicative behaviour of monolingual and bilingual toddlers and preschoolers. We describe how the unique experience of growing up with two (or more) languages affects children’s everyday experiences and the pragmatics of their communicative behaviour. Deriving from this literature, we introduce a novel perspective on children’s development of communicative behaviour (COMmmunicative-Experience, COME), discussing potential mechanisms behind this pragmatic behaviour. It assumes that children experience communicative situations of varying efficiency and that these experiences shape their communicative behaviour: The more experiences children have with non-effective communicative situations, the larger their communicative repertoire becomes and the more flexibly this repertoire can be applied in a given situation. Notably, the COME perspective is not limited to bilingual communicative development but can be applied to a variety of other pragmatic contexts. Therefore, we broaden the discussion by identifying open questions for future research.

A survey on blockchain deployment for biometric systems

AbstractBlockchain technology has become an emerging area in recent years due to its capacity to improve the security, dependability, and resilience of distributed systems. Research based on this technique has impacted several firms, including banking, healthcare, data processing, remote sensing, and many others. The key characteristics of blockchain technology that make it appealing are data immutability, transparency, privacy, decentralization, and distributed ledgers. However, there is a chance of a privacy breach with sensitive biometric data. The purpose of this investigation is to examine blockchain‐based biometric applications research. It begins by determining the myriad ways that biometrics and blockchain may work together, including the storage and protection of biometric templates, identity management, and biometric authentication systems. Different biometric applications with respect to blockchain technology are also identified, along with the types of biometric data taken into account, features and capabilities of blockchain technology exploited, and blockchain technology frameworks employed. Finally, the authors seek to investigate blockchain concepts in the biometric domain by evaluating their pros and cons and summarizing the methods developed on blockchain for diverse biometric applications. Additionally, the applications of blockchain‐based biometric systems are highlighted before moving on to open research questions and potential future research areas.

Neurochemical differences in core regions of the autistic brain: a multivoxel 1H-MRS study in children

Autism spectrum disorder (ASD) is a neurodevelopmental condition which compromises various cognitive and behavioural domains. The understanding of the pathophysiology and molecular neurobiology of ASD is still an open critical research question. Here, we aimed to address ASD neurochemistry in the same time point at key regions that have been associated with its pathophysiology: the insula, hippocampus, putamen and thalamus. We conducted a multivoxel proton magnetic resonance spectroscopy (1H-MRS) study to non-invasively estimate the concentrations of total choline (GPC + PCh, tCho), total N-acetyl-aspartate (NAA + NAAG, tNAA) and Glx (Glu + Gln), presenting the results as ratios to total creatine while investigating replication for ratios to total choline as a secondary analysis. Twenty-two male children aged between 10 and 18 years diagnosed with ASD (none with intellectual disability, in spite of the expected lower IQ) and 22 age- and gender-matched typically developing (TD) controls were included. Aspartate ratios were significantly lower in the insula (tNAA/tCr: p = 0.010; tNAA/tCho: p = 0.012) and putamen (tNAA/tCr: p = 0.015) of ASD individuals in comparison with TD controls. The Glx ratios were significantly higher in the hippocampus of the ASD group (Glx/tCr: p = 0.027; Glx/tCho: p = 0.011). Differences in tNAA and Glx indices suggest that these metabolites might be neurochemical markers of region-specific atypical metabolism in ASD children, with a potential contribution for future advances in clinical monitoring and treatment.

Cognition in Social Engineering Empirical Research: A Systematic Literature Review

The interdisciplinarity of the Social Engineering (SE) domain creates crucial challenges for the development and advancement of empirical SE research, making it particularly difficult to identify the space of open research questions that can be addressed empirically. This space encompasses questions on attack conditions, employed experimental methods, and interactions with underlying cognitive aspects. As a consequence, much potential in the breadth of existing empirical SE research and in its mapping to the actual cognitive processes it aims to measure is left untapped. In this work, we carry out a systematic review of 169 articles investigating overall 735 hypotheses in the field of empirical SE research, focusing on experimental characteristics and core cognitive features from both attacker and target perspectives. Our study reveals that experiments only partially reproduce real attacks and that the exploitable SE attack surface appears much larger than the coverage provided by the current body of research. Factors such as targets’ context and cognitive processes are often ignored or not explicitly considered in experimental designs. Similarly, the effects of different pretexts and varied targetization levels are overall marginally investigated. Our findings on current SE research dynamics provide insights into methodological shortcomings and help identify supplementary techniques that can open promising future research directions.

Towards a genomic resolution of the Phengaris alcon species complex

AbstractTaxonomic entities below the species level often pose difficulties for conservation practice, especially when they are ecologically distinct from the nominal species. Genomic tools provide the opportunity to study and potentially resolve such cryptic diversity. The Alcon blue butterfly Phengaris alcon species complex is such a cryptic example, comprising different ecotypes or even subspecies, one of them is the high elevation taxon P. rebeli from the European Alps. We sequenced a first reference genome for Phengaris alcon. Furthermore, we generated whole genome resequence data for individuals of three Swiss ecotypes, i.e., the low elevation P. alcon, the mid elevation and high elevation alpine P. rebeli and integrated genomic data from across Europe to study the relationship among these ecotypes. At a European scale, our results suggest that for the P. alcon complex, biogeography and the evolutionary context of diversification is more multifaceted than previously suggested, falling in the range of more recent ecological speciation. In Switzerland, the three ecotypes were genetically isolated with only limited current gene flow between them. Past gene flow, however, could have given rise to the mid elevation ecotype. Our findings emphasise that high elevation P. rebeli in the Alps should be treated as a distinct species. Our study highlights how the availability of reference genome assemblies allows to address so far open taxonomic questions in conservation research and that broadscale studies are needed to understand the biogeographic history of apparent diversification.

The fifth edition of the WHO classification of mature B-cell neoplasms: open questions for research.

The fifth edition of the World Health Organization Classification of Haematolymphoid Tumours (WHO-HAEM5) is the product of an evidence-based evolution of the revised fourth edition with wide multidisciplinary consultation. Nonetheless, while every classification incorporates scientific advances and aims to improve upon the prior version, medical knowledge remains incomplete and individual neoplasms may not be easily subclassified in a given scheme. Thus, optimal classification requires ongoing study, and there are certain aspects of some entities and subtypes that require further refinements. In this review, we highlight a selection of these challenging areas to prompt more research investigations. These include (1) a 'placeholder term' of splenic B-cell lymphoma/leukaemia with prominent nucleoli (SBLPN) to accommodate many of the splenic lymphomas previously classified as hairy cell leukaemia variant and B-prolymphocytic leukaemia, a clear new start to define their pathobiology; (2) how best to classify BCL2 rearrangement negative follicular lymphoma including those with BCL6 rearrangement, integrating the emerging new knowledge on various germinal centre B-cell subsets; (3) what is the spectrum of non-IG gene partners of MYC translocation in diffuse large B-cell lymphoma/high-grade B-cell lymphoma and how they impact MYC expression and clinical outcome; how best to investigate this in a routine clinical setting; and (4) how best to define high-grade B-cell lymphoma not otherwise specified and high-grade B-cell lymphoma with 11q aberrations to distinguish them from their mimics and characterise their molecular pathogenetic mechanism. Addressing these questions would provide more robust evidence to better define these entities/subtypes, improve their diagnosis and/or prognostic stratification, leading to better patient care. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Cellulite and the Aesthetic Management of the Buttocks and Thighs: 6 Cases Illustrating Targeted Verifiable Subcision as Part of a Multimodal Approach to Lower Body Rejuvenation

Abstract Background In the buttocks and thighs, skin quality, focal adiposity, volume deficiency, skin laxity, and/or textural issues each contribute to overall appearance. For patients undergoing rejuvenation/beautification procedures, global improvement is desired, making multimodal treatment the standard of care to address these mechanistically distinct concerns. Resolution of cellulite depressions is central to patient satisfaction and aesthetic outcomes: without management, the overall aesthetic suffers, and patients are left partially unsatisfied with treatment results. With minimally invasive Targeted Verifiable Subcision (TVS; Avéli [Revelle Aesthetics, Inc., Mountain View, CA]), septa with a confirmed role in dimple formation can be released through mechanically verified subcision, permitting consistent outcomes. Objectives Discuss the application of TVS as part of a multimodal approach to buttock and thigh rejuvenation and share best practices for obtaining optimal improvement. Methods A group of 6 experts in aesthetic plastic surgery and dermatology convened for a 2 h roundtable discussion of select case studies, best practices, and their approaches for obtaining optimal outcomes in clinical practice. Results Clinical cases from 6 patients who presented for buttock and/or thigh rejuvenation/beautification are presented where TVS was applied as part of a multimodal approach. Before and after images, details of patient cases, and a discussion of best practices for patient education and evaluation, treatment planning, technique, safety, postprocedure care, and open research questions are included. Conclusions TVS is emerging as a valuable tool for the treatment of cellulite in the buttocks and thighs that may potentially be used alongside surgical and nonsurgical approaches, often on the same day. Level of Evidence: 4

Governance Models for Non-Profit Organizations: a literature review

Good corporate governance, which influences organizational performance, is the foundation of effective internal control. Adopting a governance paradigm, however, presents difficulties. By identifying and mapping processes and data, Enterprise Architecture (EA) may help with changes. Key Performance Indicators (KPI) provide important indicators for organizational activities. By employing a structured Balanced Scorecard (BSC), management may obtain a comprehensive overview of performance and make informed decisions to improve outcomes. In this article, we will present relevant concepts related to Governance Models, obtained through a comprehensive literature review. The advantages of implementing a suitable governance model and the essential tools for its development are also discussed. We will close with a summary and open research questions.

Performance Analysis of Different Reward Functions in Reinforcement Learning for the Scheduling of Modular Automotive Production Systems

Conventional, linear production lines struggle with the new flexibility requirements of the automotive market. Modular production has the potential to radically improve the production flexibility. However, scheduling modular production systems is still an open research question. Reinforcement learning (RL) is a form of artificial intelligence that shows great potential in scheduling complex modular production systems. Nonetheless, the performance of RL agents heavily depends on their reward function. Designing an optimal reward function is highly complex. This paper addresses this research gap and systematically compares six different reward functions for a variety of different modular production scenarios. In addition, a new learning method using resets is proposed and its performance is compared with the standard learning approach. The results suggest that dense reward functions perform better than a sparse one. However, there are major case-to-case discrepancies. The proposed learning method outperforms the standard learning method by 7 % on average. Nonetheless, the performance difference between different scenarios is larger than with the standard approach.

Adversarial Robustness of Deep Neural Networks: A Survey from a Formal Verification Perspective

Neural networks have been widely applied in security applications such as spam and phishing detection, intrusion prevention, and malware detection. This black-box method, however, often has uncertainty and poor explainability in applications. Furthermore, neural networks themselves are often vulnerable to adversarial attacks. For those reasons, there is a high demand for trustworthy and rigorous methods to verify the robustness of neural network models. Adversarial robustness, which concerns the reliability of a neural network when dealing with maliciously manipulated inputs, is one of the hottest topics in security and machine learning. In this work, we survey existing literature in adversarial robustness verification for neural networks and collect 39 diversified research works across machine learning, security, and software engineering domains. We systematically analyze their approaches, including how robustness is formulated, what verification techniques are used, and the strengths and limitations of each technique. We provide a taxonomy from a formal verification perspective for a comprehensive understanding of this topic. We classify the existing techniques based on property specification, problem reduction, and reasoning strategies. We also demonstrate representative techniques that have been applied in existing studies with a sample model. Finally, we discuss open questions for future research.

A PID Control Architecture Based on IEC 61499

This work presents an approach for PID control and optimization in a distributed system, using the IEC 61499 control standard. This standard enables communication among different PLCs, which are used to develop a three-layered event-driven control of a SISO loop. The lowest layer is in charge of cyclical data acquisition. The second layer carries out an event-based PID control. The highest layer runs a control optimization algorithm, specifically a simple tuning approach based on Ziegler-Nichols that is used to determine the PID parameters for different operating points. The proposed approach is assessed in a tank level SISO control problem, whose behavior can be modeled as a first-order plus dead time system in each operating point. For that purpose, it has been implemented using two PLCs and a software PLC running on an industrial computer. The experimental results on the SISO level control loop show the feasibility of the proposed approach for event-driven control in a distributed system and open interesting research questions in the intersection of controller design and distributed automation.

Cognitive Assistance Systems in Intralogistics: A User Study on the Effects of Varying Levels of Customization

This study investigates the impact of varying levels of customization in digital assistance systems on human-centered evaluation measures and logistical performance within intralogistics. In this regard, the provision of an adequate extent of such customization pose an open research question. Thus, in this research we focus on a user study centered on picking and packaging processes. The participants were supported by cognitive assistance systems of different levels of system customization. While performing tasks their logistical performance was measured and the usability, user experience and technology acceptance were assessed using standard questionnaires. The results show that customization influences both the performance and the human-centered evaluation of the cognitive assistance systems. The research suggests, that a certain level of customization should be considered in the design of digital assistance systems, which is not necessarily the maximum level.