Potential Opportunities Research Articles

Structured Pruning for Deep Convolutional Neural Networks: A Survey.

The remarkable performance of deep Convolutional neural networks (CNNs) is generally attributed to their deeper and wider architectures, which can come with significant computational costs. Pruning neural networks has thus gained interest since it effectively lowers storage and computational costs. In contrast to weight pruning, which results in unstructured models, structured pruning provides the benefit of realistic acceleration by producing models that are friendly to hardware implementation. The special requirements of structured pruning have led to the discovery of numerous new challenges and the development of innovative solutions. This article surveys the recent progress towards structured pruning of deep CNNs. We summarize and compare the state-of-the-art structured pruning techniques with respect to filter ranking methods, regularization methods, dynamic execution, neural architecture search, the lottery ticket hypothesis, and the applications of pruning. While discussing structured pruning algorithms, we briefly introduce the unstructured pruning counterpart to emphasize their differences. Furthermore, we provide insights into potential research opportunities in the field of structured pruning. A curated list of neural network pruning papers can be found at: https://github.com/he-y/Awesome-Pruning. A dedicated website offering a more interactive comparison of structured pruning methods can be found at: https://huggingface.co/spaces/he-yang/Structured-Pruning-Survey.

Predicting clinical progression and cognitive decline in patients with relapsing-remitting multiple sclerosis: a 6-year follow-up study.

Cognitive impairment occurs from the earliest stages of multiple sclerosis (MS) and progresses over time. The introduction of disease modifying therapies (DMTs) has changed the prognosis for MS patients, offering a potential opportunity for improvement in the cognitive arena as well. 41 patients with relapsing-remitting multiple sclerosis (MS) were recruited to the study. Thirty patients were available for final follow-up and were included in the analysis. Baseline (BL) brain MRI including volumetry and neuropsychological tests were performed. Blood samples were collected at BL and follow-up (FU) and were tested for: vascular endothelial growth factor (VEGF), soluble vascular cell adhesion molecule-1 (sVCAM1), soluble platelet-endothelial CAM-1 (sPECAM1), and soluble intercellular CAM-1 (sICAM-1). Patients were invited for a final neuropsychological follow-up after a median of 6 years. Disease activity (relapses, EDSS increase, new/active brain lesions on MRI) was analysed between BL and FU. The study group deteriorated in the Rey-Osterrieth Complex Figure (ROCF) test (p = 0.001), but improved significantly in three other tests, i.e. semantic fluency test (p = 0.013), California Verbal Learning Test (CVLT, p = 0.016), and Word Comprehension Test (WCT, p < 0.001). EDSS increase correlated negatively with semantic fluency and WCT scores (r = -0.579, p = 0.001 and r = -0.391, p = 0.033, respectively). Improvements in semantic fluency test and WCT correlated positively with baseline deep grey matter, grey matter, and cortical volumes (p < 0.05, r > 0). Higher EDSS on FU correlated significantly negatively with baseline left and right pallidum, right caudate, right putamen, right accumbens, and cortical volume (p < 0.05, r < 0). No significant relationship was found between the number of relapses and EDSS on FU or neuropsychological deteriorations. Improvements in WCT and CVLT correlated positively with baseline sPECAM1 and sVCAM1 results, respectively (r > 0, p < 0.05). Deterioration in ROCF test correlated significantly with higher levels of baseline VEGF and sVCAM1 (p < 0.05). Brain volume is an important predictor of future EDSS and cognitive functions outcome. MS patients have a potential for improving in neuropsychological tests over time. It remains to be established whether this is related to successful disease modification with immunotherapy. Baseline volumetric measures are stronger predictors of cognitive performance than relapse activity, which yet again highlights the importance of atrophy in MS prognosis.

Inequalities in urban green space distribution across priority population groups: Evidence from Tāmaki Makaurau Auckland, Aotearoa New Zealand

Growing evidence has shown that urban green space (UGS) in neighbourhoods can substantially enhance residents' well-being. This study focuses on the possible inequitable UGS distribution among priority population groups of city-dwellers in the region of Tāmaki Makaurau, Aotearoa New Zealand. UGS availability was calculated using coverage ratio of service area and Overlap/cumulative opportunity. UGS accessibility was measured using Gaussian-based two-step floating catchment area. Bivariate analysis, spatial regression, ordinary least squares estimation, and Moran's I were employed to explore the potential inequality between UGS distribution and priority population groups. The results revealed that most deprived neighbourhoods tended to have more UGS availability but less accessibility. Children, adolescents and elderly were likely to have less potential opportunity to choose different UGS to visit. Areas with a higher proportion of Māori had less UGS availability and Pacific populations had less accessibility. Neighbourhoods with a higher proportion of Asian people had more UGS availability but less accessibility. This study adds new evidence to UGS inequality in priority population groups by contributing a regional investigation in a developed country. The results can inform policy makers and planners on where and how to implement UGS and on which groups to focus on to prevent further disparities.

Development and experiences of an internet-based acceptance and commitment training (I-ACT) intervention in ice hockey players: a qualitative feasibility study.

Internet-based psychological interventions have increased the accessibility of evidence-based treatments in clinical psychology but are still an unexplored delivery format in sport psychology research. This study describes the development and evaluates the experiences of an internet-based acceptance and commitment therapy/training (I-ACT) intervention in ice hockey players focusing on performance enhancement and a sustainable sport participation. I-ACT consisted of seven weekly modules and the feasibility of the intervention was investigated using a qualitative research design. Four national level ice hockey players took part of I-ACT and were interviewed about their experiences using a semi-structured protocol. Interview transcripts were analyzed using qualitative content analysis. Findings suggest that the content of I-ACT was comprehensible, relevant, and that it was possible to put the psychological skills into practice. I-ACT was described as helpful to the ice hockey players either in their sport performance or in their life outside of sport. The internet-format was generally perceived as positive, flexible, and a feasible option for delivering psychological interventions in an elite sport context. Some concerns were raised regarding the timing of the intervention at the end of the season, and some players also wished for more time to complete I-ACT. It was also expressed that some of the exercises could have been better adapted for goaltenders. Further trials are needed to evaluate the effects of I-ACT on performance and mental health outcomes in various sport populations using robust quantitative research methodology. Internet-based psychological interventions are a potential future opportunity to make evidence-based practices more accessible for athletes.

Model‐free learning‐based distributed cooperative tracking control of human‐in‐the‐loop multi‐agent systems

AbstractThis article studies the model‐free learning‐based distributed cooperative tracking control of human‐in‐the‐loop multi‐agent systems in the presence of an active leader. The core role of human‐in‐the‐loop is to use the ground station to send control commands to the non‐zero control input of the leader, and then directly or indirectly control a group of agents to complete complex tasks. Meanwhile, three essential demands including the completely unknown system model, the control objective obtained optimally, as well as no initial admissible control strategy requirement, are satisfied simultaneously. It is worth emphasizing that the relevant results only satisfy one or two demands at most, which are essentially not applicable to this problem. In this article, a model‐based human‐in‐the‐loop learning algorithm is first presented to achieve the optimal tracking control, as well as the convergence of the proposed learning algorithm is proved. Then, a bias‐based data‐driven learning algorithm is proposed, which provides the potential opportunities to overcome the difficulties caused by the above‐mentioned three demands. Finally, the validity of theoretical results is testified by a numerical example.

The Current Understanding of Mechanistic Pathways in Zeolite Crystallization.

Zeolite catalysts and adsorbents have been an integral part of many commercial processes and are projected to play a significant role in emerging technologies to address the changing energy and environmental landscapes. The ability to rationally design zeolites with tailored properties relies on a fundamental understanding of crystallization pathways to strategically manipulate processes of nucleation and growth. The complexity of zeolite growth media engenders a diversity of crystallization mechanisms that can manifest at different synthesis stages. In this review, we discuss the current understanding of classical and nonclassical pathways associated with the formation of (alumino)silicate zeolites. We begin with a brief overview of zeolite history and seminal advancements, followed by a comprehensive discussion of different classes of zeolite precursors with respect to their methods of assembly and physicochemical properties. The following two sections provide detailed discussions of nucleation and growth pathways wherein we emphasize general trends and highlight specific observations for select zeolite framework types. We then close with conclusions and future outlook to summarize key hypotheses, current knowledge gaps, and potential opportunities to guide zeolite synthesis toward a more exact science.

The New Cyberlinktech, Inc. Resilience to Creating Growth Model

The New Cyberlinktech, Inc. (TNCI) operates in a highly dynamic and evolving market, requiring the need for a strategic business plan to sustain growth and adaptability. The New Cyberlinktech, Inc. (TNCI) is one of the leading information technology providers for Private Emission Testing Centers (PETCs) under the Department of Transportation and the Land Transportation Office in the Philippines. TNCI faces significant challenges in the current market landscape, including increasing regulatory pressure against PETCs, the emergence of the Motor Vehicle Inspection System (MVIS) as an alternative mode of vehicle testing, and the frequent leadership changes and abrupt policy shifts at the Land Transportation Office (LTO) and the Department of Transportation (DOTr). To ensure sustainability and adaptability, this dissertation aims to develop a comprehensive business plan for The New Cyberlinktech, Inc. (TNCI) that addresses the challenges posed by the rapidly changing market landscape including a 5-year roadmap. The research design employs a mixed methods approach. The qualitative phase involves conducting interviews with key stakeholders within TNCI, including senior management, employees, and selected industry experts. Through these qualitative interactions, the study aims to identify the specific challenges faced by TNCI in the evolving market and explore potential strategic approaches to address them. In the quantitative phase, the focus is on using surveys among the current clients of the company to determine the preferred IT projects that they want the company to implement in the future. The quantitative analysis provides a comprehensive assessment of TNCI’s current performance, identifies potential risks and opportunities, and informs the development of strategic recommendations. The integrated analysis phase synthesizes the findings from the qualitative and quantitative data. By comparing and contrasting the insights gained from both approaches, a holistic understanding of the challenges and opportunities facing TNCI is achieved. The strategic business plan is formulated based on the integrated analysis, considering the specific needs and goals of TNCI. The plan encompasses strategies to address regulatory challenges, navigate the MVIS landscape, manage leadership changes, adapt to policy shifts, and recommend potential IT projects that the company can adapt and implement. Potential findings may include insights into the specific regulatory pressures faced by PETCs, the implications of the MVIS on TNCI’s business model, and strategies to mitigate the effects of leadership and policy changes. The implications of the research findings can inform TNCI’s decision-making process and help guide the company in sustaining growth and adaptability in the rapidly evolving market. This dissertation contributes to the body of knowledge by providing a comprehensive strategic business plan tailored to TNCI’s context. The findings and recommendations have practical implications for TNCI and other IT companies operating in similar environments. Future research opportunities may involve evaluating the implementation and effectiveness of the proposed business plan and exploring additional strategies to enhance TNCI’s competitive advantage in the PETC industry. Keywords: Strategic continuity, Business plan, Sustainability, Adaptability, Private Emission Testing Centers, Motor Vehicle Inspection System, Regulatory pressure, Leadership change, Policy shifts, mixed methods researc

V-MXenes for energy storage/conversion applications: Trends and Prospects.

MXenes, a two-dimensional (2D) material, exhibit excellent optical, electrical, chemical, mechanical, and electrochemical properties. Titanium-based MXene (Ti-MXene) has been extensively studied and serves as the foundation for 2D MXenes. However, other transition metals possess the potential to offer excellent properties in various applications. This comprehensive review aims to provide an overview of the properties, challenges, key findings, and applications of less-explored vanadium-based MXenes (V-MXenes) and their composites. The current trends in V-MXene and their composites for energy storage and conversion applications have been thoroughly summarized. Overall, this review offers valuable insights, identifies potential opportunities, and provides key suggestions for future advancements in the MXenes and energy storage/conversion applications.

Problems and Prospects of Urbanization in Kathmandu Valley

The capital of Nepal, Kathmandu, is undergoing rapid urbanization with issues like overcrowding, infrastructure strain, and environmental challenges. Informal settlements highlight resource disparities. The study explores urbanization's impact on cultural identity and social dynamics. Effective governance is crucial for managing urbanization and promoting social inclusion, but Nepal faces challenges like slow law implementation and corruption. Governance is pivotal for development, addressing issues like corruption and law enforcement. Despite challenges, urbanization presents opportunities for new industries and social services. The study aims to identify prospects for sustainable urbanization in Kathmandu, emphasizing green infrastructure, sustainable transportation, and community-based initiatives. A sociological perspective aids in understanding social dynamics and potential opportunities arising from urban growth.

Liquid Metal as Energy Conversion Sensitizers: Materials and Applications.

Energy can exist in nature in a wide range of forms. Energy conversion refers to the process in which energy is converted from one form to another, and this process will be greatly enhanced by energy conversion sensitizers. Recently, an emerging class of new materials, namely liquid metals (LMs), shows excellent prospects as highly versatile materials. Notably, in terms of energy delivery and conversion, LMs functional materials are chemical responsive, heat-responsive, photo-responsive, magnetic-responsive, microwave-responsive, and medical imaging responsive. All these intrinsic virtues enabled promising applications in energy conversion, which means LMs can act as energy sensitizers for enhancing energy conversion and transport. Herein, first the unique properties of the light, heat, magnetic and microwave converting capacity of gallium-based LMs materials are summarized. Then platforms and applications of LM-based energy conversion sensitizers are highlighted. Finally, some of the potential applications and opportunities of LMs are prospected as energy conversion sensitizers in the future, as well as unresolved challenges. Collectively, it is believed that this review provides a clear perspective for LMs mediated energy conversion, and this topic will help deepen knowledge of the physical chemistry properties of LMs functional materials.

Neuromorphic Nanoionics for Human-Machine Interaction: From Materials to Applications.

Human-machine interaction (HMI) technology has undergone significant advancements in recent years, enabling seamless communication between humans and machines. Its expansion has extended into various emerging domains, including human healthcare, machine perception, and biointerfaces, thereby magnifying the demand for advanced intelligent technologies. Neuromorphic computing, a paradigm rooted in nanoionic devices that emulate the operations and architecture of the human brain, has emerged as a powerful tool for highly efficient information processing. This paper delivers a comprehensive review of recent developments in nanoionic device-based neuromorphic computing technologies and their pivotal role in shaping the next-generation of HMI. Through a detailed examination of fundamental mechanisms and behaviors, the paper explores the ability of nanoionic memristors and ion-gated transistors to emulate the intricate functions of neurons and synapses. Crucial performance metrics, such as reliability, energy efficiency, flexibility, and biocompatibility, are rigorously evaluated. Potential applications, challenges, and opportunities of using the neuromorphic computing technologies in emerging HMI technologies, are discussed and outlooked, shedding light on the fusion of humans with machines.

Targeting STAT3 and NF-κB Signaling Pathways in Cancer Prevention and Treatment: The Role of Chalcones.

Chalcones are a type of natural flavonoid compound that have been found to possess promising anticancer properties. Studies have shown that chalcones can inhibit the growth and proliferation of cancer cells, induce apoptosis, and suppress tumor angiogenesis. In addition to their potential therapeutic applications, chalcones have also been studied for their chemopreventive effects, which involve reducing the risk of cancer development in healthy individuals. Overall, the anticancer properties of chalcones make them a promising area of research for developing new cancer treatments and preventative strategies. This review aims to provide a thorough overview of the central studies reported in the literature concerning cancer prevention and the treatment of chalcones. Although chalcones target many different mechanisms, the STAT and NF-κB signaling pathways are the ones this review will focus on, highlighting the existing crosstalk between these two pathways and considering the potential therapeutic opportunities for chalcone combinations.

Exploring dynamic urban mobility patterns from traffic flow data using community detection

ABSTRACT The rise of data from smart city services and the emergence of advanced algorithms have emphasized the need for a deeper understanding of the underlying patterns of urban mobility and the potential opportunities for more efficient urban planning and policymaking. By identifying communities with similar mobility patterns, researchers can gain better insights into how people move within and between different regions. Traditional community detection methodologies mainly focused on identifying geographic communities defined by shared locations. However, this perspective overlooks the broader definition of communities. Communities can also emerge from shared social interests, collective actions, and activity patterns. This implies that geographically disparate areas might exhibit similar patterns, which is particularly relevant in the study of mobility pattern similarity. Rather than focusing on regions with strong spatial interactions, this study aims to identify regions that show more similarity to each other than to other areas. Such similarities may indicate parallel urban functionalities, which are essential for effective urban planning and policymaking. To bridge this gap, our study introduces a customized community detection algorithm that employs Dynamic Time Warping (DTW) to quantitatively assess the similarity in mobility patterns between different communities. This advanced approach not only improves the identification of comparable mobility patterns but also demonstrates remarkable flexibility, broadening its application to various other social phenomena. The results demonstrate the effectiveness of the proposed model in capturing complex mobility patterns across different locations and days of the week.

Visual interpretation of clinical images among dental students using eye-tracking technology.

Tele-consultations are increasingly used for screening and diagnosis. Only a few studies have assessed dental students' visual attention to clinical images. To (i) determine dental students' gaze behavior, visual fixations, and diagnostic competence while viewing clinical images, and (ii) explore potential opportunities to strengthen the teaching-learning approaches. Tobii Pro Nano-device captured the eye-tracking data for 65 dental undergraduate students in this cross-sectional study. The predetermined areas of interest (AOI) for all five clinical photographs were uploaded onto Tobii software. All participants used a think-aloud protocol with no restrictions to view time. A total of 325 clinical pictures were analyzed, and the average view time was 189.25±76.90 s. Most participants started at the center of the image (three frontal photos), spent a significant share of their view time on prominent findings, did not follow a systematic pattern, and exhibited diagnostic incompetence. Also, most participants followed a "Z" viewing pattern (oscillating movement from left to right) for the remaining two pictures. Subjects frequently fixated on the prominent AOI, however, failed to make the correct diagnosis. Their view patterns revealed no sequential viewing. Therefore, emphasizing knowledge about common dental abnormalities and focusing on full coverage of clinical pictures can improve dental students' diagnostic competence and view patterns.

Advances in Additive Manufacturing of Polymer-Fused Deposition Modeling on Textiles: From 3D Printing to Innovative 4D Printing-A Review.

Technological advances and the development of new and advanced materials allow the transition from three-dimensional (3D) printing to the innovation of four-dimensional (4D) printing. 3D printing is the process of precisely creating objects with complex shapes by depositing superimposed layers of material. Current 3D printing technology allows two or more filaments of different polymeric materials to be placed, which, together with the development of intelligent materials that change shape over time or under the action of an external stimulus, allow us to innovate and move toward an emerging area of research, innovative 4D printing technology. 4D printing makes it possible to manufacture actuators and sensors for various technological applications. Its most significant development is currently in the manufacture of intelligent textiles. The potential of 4D printing lies in modular manufacturing, where fabric-printed material interaction enables the creation of bio-inspired and biomimetic devices. The central part of this review summarizes the effect of the primary external stimuli on 4D textile materials, followed by the leading applications. Shape memory polymers attract current and potential opportunities in the textile industry to develop smart clothing for protection against extreme environments, auxiliary prostheses, smart splints or orthoses to assist the muscles in their medical recovery, and comfort devices. In the future, intelligent textiles will perform much more demanding roles, thus envisioning the application fields of 4D printing in the next decade.

Abstract B109: Uncovering novel vulnerabilities in ovarian cancer by studying cell death in neoplastic transformation

Abstract B109: Uncovering novel vulnerabilities in ovarian cancer by studying cell death in neoplastic transformation

Between Sea and Sky: Understanding Liability for Private and Commercial Space Operations

The legal framework for commercial space activities has been an emerging issue in recent decades. Understanding and addressing liability in space activities is crucial for the sustainable and responsible development of the commercial space industry, analogous to laying the foundation for a sturdy structure that can withstand the challenges of the ever-evolving space frontier. This article explores the concept of liability for private and commercial space launches and its importance in ensuring the safe and responsible operation of activities in space. Examining liability in lex maritima and commercial space law involves drawing parallels between the regulations governing both domains and uncovering potential opportunities for learning from existing legal frameworks. The analysis considers liability in various maritime zones, such as the territorial sea, high sea, and deep-sea bed, and draws comparisons to liability in the territory, space, and celestial body. It discusses the challenges and implications of addressing liability in space activities, including the allocation of liability, the protection of public safety, and the preservation of space as a shared resource.

Insights From Commodity Markets Reaction to the Russia–Ukraine War

The article aims to investigate how the Russia–Ukraine war has affected India’s base metal, energy, and bullion markets using short-term event technique. The official website of Multi Commodity Exchange of India Limited (MCX) has provided the daily prices for nine specific commodities and selected commodity indexes. The study discovered that the two countries’ conflict had no discernible effect on the Cumulative Abnormal Returns (CARs) of a few selected indices. However, more in-depth examination of specific commodities showed that the CAR of just the base metal index was considerably impacted. The study also observed that the war had an impact on returns of investors who experienced positive returns only in case of nickel whereas negative returns in case of copper, lead and zinc. However, analysis of the cumulative average abnormal return (CAAR) of the selected indices has revealed a consistent and significant negative impact which could be due to other external factors influencing prices of the commodity index and individual indices. The present study is quite useful to investors, traders, analysts, policy makers and risk managers as it assists them to make informed investment decisions, manage risk, identify potential opportunities in the market and develop trading strategies.

Analyzing and modeling massive transfusion strategies and the role of fibrinogen-How much is the patient actually receiving?

Hemorrhage is a leading cause of preventable death in trauma, cardiac surgery, liver transplant, and childbirth. While emphasis on protocolization and ratio of blood product transfusion improves ability to treat hemorrhage rapidly, tools to facilitate understanding of the overall content of a specific transfusion strategy are lacking. Medical modeling can provide insights into where deficits in treatment could arise and key areas for clinical study. By using a transfusion model to gain insight into the aggregate content of massive transfusion protocols (MTPs), clinicians can optimize protocols and create opportunities for future studies of precision transfusion medicine in hemorrhage treatment. The transfusion model describes the individual round and aggregate content provided by four rounds of MTP, illustrating that the total content of blood elements and coagulation factor changes over time, independent of the patient's condition. The configurable model calculates the aggregate hematocrit, platelet concentration, percent volume plasma, total grams and concentration of citrate, percent volume anticoagulant and additive solution, and concentration of clotting factors: fibrinogen, factor XIII, factor VIII, and von Willebrand factor, provided by the MTP strategy. Transfusion strategies based on a 1:1:1 or whole blood foundation provide between 13.7 and 17.2 L of blood products over four rounds. Content of strategies varies widely across all measurements based on base strategy and addition of concentrated sources of fibrinogen and other key clotting factors. Differences observed between modeled transfusion strategies provide key insights into potential opportunities to provide patients with precision transfusion strategy.

Phenomenology of the inclusive potential of the family as a factor in the socialization of children with disabilities

Introduction. Lack of tools for studying the potential resources and capabilities of the family, as well as search for optimal strategies and mechanisms for the real inclusion of people with disabilities in all spheres of public life is on the current agenda of national and international initiatives. For a comprehensive analysis of inclusive potential of families raising children with disabilities, aspects of the rehabilitation potential of the individual and the environment, of educational potential, functionality and effectiveness of the family, and of competence, including inclusive competence, are considered. The emphasis is shifted to understanding the potential of the family as a factor in the socialization of children with disabilities. The article aims to systematize and scientifically analyze ideas about the potential opportunities and resources for the socialization of children with disabilities and their families, and to justify the criteria base and mechanism for assessing the inclusive potential of families. Materials and methods. Within the framework of interdisciplinary scientific discourse, a model of the criteria base and mechanism for analyzing and assessing the inclusive potential of a family raising a child with disabilities is proposed. The basis for constructing the model is the decomposition of groups of competencies through indicators of parental effectiveness based on formalization. Results and discussion. Based on the analysis of the terminological field related to the assessment and development of family potential in matters of socialization and development of a child with disabilities, the author’s positions on inclusive family potential are presented. Some socio-psychological phenomena are considered that reflect the capabilities and resources of both the children themselves and their social environment. Particular attention is paid to indicating the functional effectiveness of parents of children with disabilities. Conclusion. The discussed model for assessing the inclusive potential of families raising children with disabilities has a universal design, formed as a result of initial testing and expert assessment of the professional community. This approach allows analyzing individual indicators and assessing influence of certain factors on the effectiveness of accompanying children of different categories of disabilities. A systematic analysis of individual groups of parents’ inclusive competencies allows optimizing their inclusion in the comprehensive support of children with disabilities.