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A revision on articles concerning thermal analysis of tetracyclines is presented, regarding drug-excipient compatibility, characterization of drug releasing systems, physicochemical behavior of drug-supported systems and degradation of some pharmaceuticals itself. Initially, an overview of information regarding this class of drugs is presented. A bibliographic survey revealed relatively few works on this subject despite the worldwide use and relevance of this class of antibiotics. Here, 37 papers published during the time frame 2000–2022 were classified as above and discussed once they presented thermoanalytical data straightly related to the tetracyclines. From the thermal studies of the drugs, a general decomposition behavior could be identified and it is presented. [ABSTRACT FROM AUTHOR]

Socially aware robot navigation is gaining popularity with the increase in delivery and assistive robots. The research is further fueled by a need for socially aware navigation skills in autonomous vehicles to move safely and appropriately in spaces shared with humans. Although most of these are ground robots, drones are also entering the field. In this paper, we present a literature survey of the works on socially aware robot navigation in the past 10 years. We propose four different faceted taxonomies to navigate the literature and examine the field from four different perspectives. Through the taxonomic review, we discuss the current research directions and the extending scope of applications in various domains. Further, we put forward a list of current research opportunities and present a discussion on possible future challenges that are likely to emerge in the field. [ABSTRACT FROM AUTHOR]

Technology management (TM) aims to enhance technical competitiveness, providing organizations with a market advantage. The increasing interest in artificial intelligence (AI) within TM has sparked debate: supporters praise AI's decision-making capabilities, while critics stress the importance of human expertise. This study advocates for integrating AI into TM as a supportive tool for human decision-making rather than replacing domain experts. To achieve this, a comprehensive literature review examines the integration of AI in TM, exploring potential benefits and challenges. The research analyzes text mining works, existing data, and the suitability of AI models for various TM tasks. Additionally, it reviews AI applications in TM, identifying opportunities and challenges. [ABSTRACT FROM AUTHOR]

Human parsing aims to partition humans in image or video into multiple pixel-level semantic parts. In the last decade, it has gained significantly increased interest in the computer vision community and has been utilized in a broad range of practical applications, from security monitoring, to social media, to visual special effects, just to name a few. Although deep learning-based human parsing solutions have made remarkable achievements, many important concepts, existing challenges, and potential research directions are still confusing. In this survey, we comprehensively review three core sub-tasks: single human parsing, multiple human parsing, and video human parsing, by introducing their respective task settings, background concepts, relevant problems and applications, representative literature, and datasets. We also present quantitative performance comparisons of the reviewed methods on benchmark datasets. Additionally, to promote sustainable development of the community, we put forward a transformer-based human parsing framework, providing a high-performance baseline for follow-up research through universal, concise, and extensible solutions. Finally, we point out a set of under-investigated open issues in this field and suggest new directions for future study. We also provide a regularly updated project page, to continuously track recent developments in this fast-advancing field: https://github.com/soeaver/awesome-human-parsing. [ABSTRACT FROM AUTHOR]

Survival analysis is an integral part of medical statistics that is extensively utilized to establish prognostic indices for mortality or disease recurrence, assess treatment efficacy, and tailor effective treatment plans. The identification of prognostic biomarkers capable of predicting patient survival is a primary objective in the field of cancer research. With the recent integration of digital histology images into routine clinical practice, a plethora of Artificial Intelligence (AI)-based methods for digital pathology has emerged in scholarly literature, facilitating patient survival prediction. These methods have demonstrated remarkable proficiency in analyzing and interpreting whole slide images, yielding results comparable to those of expert pathologists. The complexity of AI-driven techniques is magnified by the distinctive characteristics of digital histology images, including their gigapixel size and diverse tissue appearances. Consequently, advanced patch-based methods are employed to effectively extract features that correlate with patient survival. These computational methods significantly enhance survival prediction accuracy and augment prognostic capabilities in cancer patients. The review discusses the methodologies employed in the literature, their performance metrics, ongoing challenges, and potential solutions for future advancements. This paper explains survival analysis and feature extraction methods for analyzing cancer patients. It also compiles essential acronyms related to cancer precision medicine. Furthermore, it is noteworthy that this is the inaugural review paper in the field. The target audience for this interdisciplinary review comprises AI practitioners, medical statisticians, and progressive oncologists who are enthusiastic about translating AI-driven solutions into clinical practice. We expect this comprehensive review article to guide future research directions in the field of cancer research. [ABSTRACT FROM AUTHOR]

• Historical review: the revival of ancient colour before digital technologies. • Digital approaches: data management, 3D scanning, 2D documentation, and AI in polychrome reconstruction. • Visualization technologies: VR/AR applications and real-time visualization of ancient colour. The digital technologies employed in archaeology since the 1990s have progressively and experimentally been utilized over the last two decades to document and re-present the ancient polychromy of Greek and Roman marble artworks. Given that this remains a developing field of investigation and application, this study offers, for the first time, a systematic review of the endeavours undertaken thus far in implementing information technology for the documentation, analysis, reconstruction, visualization, and presentation of ancient polychromy. This overview is supported by a literature review and existing implementations, organized into methods and techniques employed for 3D colour preservation, analysis, and reconstruction, as well as those used for the visualization and dissemination of findings. The goal is to identify gaps and provide intriguing insights for future research concerning the use of digital technologies as an essential tool in the stages of documenting and disseminating ancient polychromy in architecture and archaeological artefacts. This, in turn, aims to encourage data sharing, contribute to the dissemination of science-based knowledge and resolve substantial barriers associated with the long-term retention of digital data. [ABSTRACT FROM AUTHOR]

Abstract Person re-identification (ReID) aims to find the person of interest across multiple non-overlapping cameras. It is considered an essential step for person tracking applications which is vital for surveillance. Person ReID could be investigated either using image-based or video-based. Video-based person ReID is considered more discriminating and realistic than image-based ReID due to the massive information extracted for each person. Different deep-learning techniques have been used for video-based ReID. In this survey, recently published articles are reviewed according to video-based ReID system pipeline: deep features learning, deep metric learning, and deep learning approaches. The deep feature learning approaches are categorized into spatial and temporal approaches, while deep metric learning is divided into metric and metric learning approaches. The deep learning approaches are differentiated into: supervised, unsupervised, weakly-supervised, and one-shot learning. A detailed analysis is held for the architectures of the state-of-the-art deep learning approaches. And their performance on four benchmark datasets is compared.

Person re-identification (ReID) aims to find the person of interest across multiple non-overlapping cameras. It is considered an essential step for person tracking applications which is vital for surveillance. Person ReID could be investigated either using image-based or video-based. Video-based person ReID is considered more discriminating and realistic than image-based ReID due to the massive information extracted for each person. Different deep-learning techniques have been used for video-based ReID. In this survey, recently published articles are reviewed according to video-based ReID system pipeline: deep features learning, deep metric learning, and deep learning approaches. The deep feature learning approaches are categorized into spatial and temporal approaches, while deep metric learning is divided into metric and metric learning approaches. The deep learning approaches are differentiated into: supervised, unsupervised, weakly-supervised, and one-shot learning. A detailed analysis is held for the architectures of the state-of-the-art deep learning approaches. And their performance on four benchmark datasets is compared. [ABSTRACT FROM AUTHOR]

Currently, a significant gap exists between academic and industrial research in automated driving development. Despite this, there is common sense that cooperative control approaches in automated vehicles will surpass the previously favored takeover paradigm in most driving situations due to enhanced driving performance and user experience. Yet, the application of these concepts in real driving situations remains unclear, and a holistic approach to driving cooperation is missing. Existing research has primarily focused on testing specific interaction scenarios and implementations. To address this gap and offer a contemporary perspective on designing human–vehicle cooperation in automated driving, we have developed a three-part taxonomy with the help of an extensive literature review. The taxonomy broadens the notion of driving cooperation towards a holistic and application-oriented view by encompassing (1) the "Cooperation Use Case", (2) the "Cooperation Frame", and (3) the "Human–Machine Interface". We validate the taxonomy by categorizing related literature and providing a detailed analysis of an exemplar paper. The proposed taxonomy offers designers and researchers a concise overview of the current state of driver cooperation and insights for future work. Further, the taxonomy can guide automotive HMI designers in ideation, communication, comparison, and reflection of cooperative driving interfaces. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Social Sciences Research / Sosyal Bilimler Arastirmalari Dergisi is the property of ODU Journal of Social Sciences Research and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The article discusses working-time preferences and outcomes in English-speaking countries, the Netherlands, and Germany, and it focuses on gender, care responsibilities, and current working hours. It reports that while there is a desire to change working-time arrangements, preferences often align with the "normal working day" standard, indicating the influence of cultural and socio-economic factors on preference formation and the potential implications for average working hours.

Occluded person re-identification (Re-ID) focuses on addressing the occlusion problem when retrieving the person of interest across non-overlapping cameras. With the increasing demand for intelligent video surveillance and the application of person Re-ID technology, the real-world occlusion problem draws considerable interest from researchers. Although a large number of occluded person Re-ID methods have been proposed, there are few surveys that focus on occlusion. To fill this gap and help boost future research, this article provides a systematic survey of occluded person Re-ID. In this work, we review recent deep learning based occluded person Re-ID research. First, we summarize the main issues caused by occlusion as four groups: position misalignment, scale misalignment, noisy information, and missing information. Second, we categorize existing methods into six solution groups: matching, image transformation, multi-scale features, attention mechanism, auxiliary information, and contextual recovery. We also discuss the characteristics of each approach, as well as the issues they address. Furthermore, we present the performance comparison of recent occluded person Re-ID methods on four public datasets: Partial-ReID, Partial-iLIDS, Occluded-ReID, and Occluded-DukeMTMC. We conclude the study with thoughts on promising future research directions. [ABSTRACT FROM AUTHOR]

The vehicle sideslip angle or lateral velocity is a measure both for driving stability and for occupant’s subjective perception of safety. With the introduction of vehicle dynamics control systems and automated driving functions, knowledge of this vehicle motion state is required for many control strategies. This article gives an overview on the state of the art on sideslip angle estimation. In contrast to other literature studies on this topic, it focuses on vehicle dynamics based algorithms. The following types of observers are discussed: Kalman Filter-type, recursive least squares (RLS), sliding mode observers (SMO) or nonlinear observers (NLO). Eventually, cascaded observers are used that first estimate some states, which then act as input to the sideslip angle estimator. Since the choice of an observer strategy always depends on the application, this article provides a brief insight into the work of selected research groups that have studied the topic. These examples will help to clarify the presence of many different approaches in the literature. A detailed discussion on vehicle and tire models is not included but referenced to other sources. Finally, this article provides recommendations for two main target groups: First, researchers and engineers that plan to design an algorithm for sideslip angle estimation using deterministic vehicle dynamics based approaches. Second, researchers and engineers planning to include an existing algorithm in an automated driving function that want to learn about advantages and limitations of these types of algorithms.

Most nanomedicines require efficient in vivo delivery to elicit meaningful diagnostic and therapeutic effects. However, en route to their intended tissues, systemically administered nanoparticles often encounter delivery barriers. To describe these barriers, the term "nanoparticle blood removal pathways" (NBRP) is proposed, which summarizes the interactions between nanoparticles and the body's various cell‐dependent and cell‐independent blood clearance mechanisms. Nanoparticle design and biological modulation strategies are reviewed to mitigate nanoparticle‐NBRP interactions. As these interactions affect nanoparticle delivery, the preclinical literature from 2011–2021 is studied, and the nanoparticle blood circulation and organ biodistribution data are analyzed. The findings reveal that nanoparticle surface chemistry affects the in vivo behavior more than other nanoparticle design parameters. Combinatory biological‐PEG surface modification improves the blood area under the curve by ≈418%, with a decrease in liver accumulation of up to 47%. A greater understanding of nanoparticle‐NBRP interactions and associated delivery trends will provide new nanoparticle design and biological modulation strategies for safer, more effective, and more efficient nanomedicines. [ABSTRACT FROM AUTHOR]

Graph neural networks (GNNs) are models that capture the dependencies between graph data by passing messages between graph nodes and they have been widely used to process graph data that contains relational information. Example application areas include social networks, recommendation systems, and life sciences. However, like all neural networks, there are underpinning security and privacy concerns associated with GNN deployments in practice. For example, attackers can perturb a graph’s data to undermine a model’s effectiveness, or they can steal the model’s data and/or parameters, thus threatening the privacy of the model. In this survey, we provide a comprehensive review of recent research efforts on security and/or privacy in GNNs. We also systematically describe the distinctions and relationships between security and privacy, as well as providing an outlook on future directions of research in this area. [ABSTRACT FROM AUTHOR]

Mixed palletizing constitutes one of the problems in the logistics domain aroused from the need for fast product movement to satisfy the continuously increasing number of customers with the demand for highly personalized goods. In a demanding environment, such as warehouses, where break bulk and the consolidation of loads take up most of the working time, the automation of mixed palletizing can lead to increased efficiency and speed while keeping errors to a minimum. Space utilization of pallets enables savings in storage and transportation costs, boosting the overall sustainable role of the Supply Chain sector. This paper presents the proposed approaches to mixed palletizing stemming from different fields, with a focus on recent developments in the application of Industry 4.0 technologies. Our research highlights quite a few areas that require attention from researchers. [ABSTRACT FROM AUTHOR]

Existing land registration systems have several issues like dual ownership, fraudulent or incomplete registries. The existing system also includes a lot of middle men which makes it prone to malicious acts and results in a vulnerable system. Keeping track of who owns which part of land is a big challenge. To overcome this problem blockchain technology is used. Use of blockchain will remove middle men, increase trust, efficiency of the system and reduce corruption. This paper highlights the issues related to the current system such as authenticity, centralization, reliability, transparency, etc and proposes a better method using ethereum blockchain and smart contracts to overcome this problem. Blockchain method provides identification of true ownership of land, authenticity and transparency in the system. [ABSTRACT FROM AUTHOR]

Generative artificial intelligence (GenAI) has fired the world's imagination. The higher education sector is not immune from the GenAI hype, panic, and mania. The emergence of artificial intelligence, in its newest form, into curriculum, student life, and learning has created an entanglement of technology, people, and learning. Yet, there is still a lack of cohesive accounts of the emergent literature used to inform practical learning and teaching decisions. Our manuscript responds with the deployment of a previously published systematic literature review to create the first version of the Artificial Intelligence in Higher Education Database (AIHE V1). Published in conjunction with this article, we pioneer an open-access resource to support learning and teaching scholars to gain timely access to pre-examined literature on AI and higher education. This first version documents 160 manuscripts published between 30 November 2022 and 31 December 2023. Using a rigorous systematic review method, engaging in the PRISMA approach, we offer a first glance at the metadata of articles published on AI and higher education during the first year of ChatGPT. [ABSTRACT FROM AUTHOR]

Micro‐/nanorobots (mn‐robots), inspired by the versatile mechanisms found in natural microorganisms, show great potential in enabling innovative bio‐applications. The 3D‐printed magnetic mn‐robots are substantially advanced to swim in vivo and to carry and release therapeutic agents in a controlled manner. To understand the state of the art of such robots and identify their development trend, this article presents a comprehensive and systematic review of the recent works on development of magnetic robots and their applications in biomedical engineering, with a particular focus on targeted therapeutic delivery. The developments in materials, fabrications, actuations, and applications with design for magnetic mn‐robots are reviewed, and it is aimed to discover the limitations of the existing works and to identify the knowledge gap, thereby deriving future research directions on developing magnetic mn‐robots, especially for their applications in targeted therapeutic delivery. [ABSTRACT FROM AUTHOR]

Aiming at obtaining structural information and 3D motion of dynamic scenes, scene flow estimation has been an interest of research in computer vision and computer graphics for a long time. It is also a fundamental task for various applications such as autonomous driving. Compared to previous methods that utilize image representations, many recent researches build upon the power of deep analysis and focus on point clouds representation to conduct 3D flow estimation. This paper comprehensively reviews the pioneering literature in scene flow estimation based on point clouds. Meanwhile, it delves into detail in learning paradigms and presents insightful comparisons between the state‐of‐the‐art methods using deep learning for scene flow estimation. Furthermore, this paper investigates various higher‐level scene understanding tasks, including object tracking, motion segmentation, etc. and concludes with an overview of foreseeable research trends for scene flow estimation. [ABSTRACT FROM AUTHOR]

Micro‐/nanorobots (mn‐robots), inspired by the versatile mechanisms found in natural microorganisms, show great potential in enabling innovative bio‐applications. The 3D‐printed magnetic mn‐robots are substantially advanced to swim in vivo and to carry and release therapeutic agents in a controlled manner. To understand the state of the art of such robots and identify their development trend, this article presents a comprehensive and systematic review of the recent works on development of magnetic robots and their applications in biomedical engineering, with a particular focus on targeted therapeutic delivery. The developments in materials, fabrications, actuations, and applications with design for magnetic mn‐robots are reviewed, and it is aimed to discover the limitations of the existing works and to identify the knowledge gap, thereby deriving future research directions on developing magnetic mn‐robots, especially for their applications in targeted therapeutic delivery.

In recent years, spatial dependence in production frontier models has attracted considerable research attention. This is explained, among other things, by the observation that in many economic sectors, decisions on taxes, expenditure, research and development, etc., are likely to be interconnected across production units. Consequently, the assumption that (benchmarked) production units operate in isolation from their peers may no longer be valid. In this article, we review and summarize this literature. First, we identify a set of analyses in the production frontier field that take into account spatial dependence based on a systematic search in the Web of Science and Scopus databases from 1975 to 2022, and provide global insights into this subfield. We find that this literature is relatively young: we trace the first contribution back to 2004 and, until 2011, the number of analyses per year remained relatively low (one per year at most). Second, we analyze identified articles in depth, classify them, and briefly outline avenues for future research. We hope that this will enable researchers to navigate this subfield and develop it further. We observe that the majority of these articles use parametric methods (e.g., stochastic frontier analysis) over nonparametric ones (e.g., data envelopment analysis). We also note that while in the nonparametric framework, the objective of the vast majority of contributions is to distinguish the intrinsic performance of productive units by the contribution of their territories, contributions in the parametric framework are more diverse. Highlights: We identify analyses in the frontier field that consider spatial dependence. We observe that this literature is relatively young but fast-growing. Most of these analyses use parametric methods over nonparametric ones. We classify the analyses and outline avenues for future research. This literature could benefit from putting identification issues at its center. [ABSTRACT FROM AUTHOR]

Marine container terminals play a significant role for international trade networks and global market. To cope with the rapid and steady growth of the seaborne trade market, marine container terminal operators must address the operational challenges with appropriate analytical methods to meet the needs of the market. The berth allocation and scheduling problem is one of the important decisions faced by operators during operations planning. The optimization of a berth schedule is strongly associated with the allocation of spatial and temporal resources. An optimal and robust berth schedule remarkably improves the productivity and competitiveness of a seaport. A significant number of berth allocation and scheduling studies have been conducted over the last years. Thus, there is an existing need for a comprehensive and critical literature survey to analyze the state-of-the-art research progress, developing tendencies, current shortcomings, and potential future research directions. Therefore, this study thoroughly selected scientific manuscripts dedicated to the berth allocation and scheduling problem. The identified studies were categorized based on spatial attributes, including discrete, continuous, and hybrid berth allocation and scheduling problems. A detailed review was performed for the identified study categories. A representative mathematical formulation for each category was presented along with a detailed summary of various considerations and characteristics of every study. A specific emphasis was given to the solution methods adopted. The current research shortcomings and important research needs were outlined based on the review of the state-of-the-art. This study was conducted with the expectation of assisting the scientific community and relevant stakeholders with berth allocation and scheduling. [ABSTRACT FROM AUTHOR]

The purpose of this survey paper is to paint the landscape of research on the efficiency profiles of Islamic banks with a focus on Data Envelopment Analysis (DEA) studies. This paper uses a comprehensive systematic literature review to survey 80 relevant papers published between 2004 and 2021. Such landscape is organised around classifications of types of measures of efficiency and their analyses, types of DEA analyses, types of DEA modelling frameworks and models, evaluation approaches and choice of variables for the specification of DEA models, and drivers of efficiency. To the best of our knowledge, no survey on the drivers of efficiency has ever been conducted. In this paper, we overcome this gap in the context of Islamic banking and back up previous findings with relevant theories. In addition, we unify the literature terminologywise. Finally, a critical analysis of the literature is provided along with methodological gaps, inconsistencies, and future research directions. [ABSTRACT FROM AUTHOR]

In Japan, high-level radioactive waste and specific low-level radioactive waste which includes long-lived radionuclides are planned to be disposed of in the geological formations at depths greater than 300 m. The disposal site will be selected through a stepwise site investigation process that consists of a Literature Survey, Preliminary Investigation, and Detailed Investigation phases. In October 2020 a Literature Survey was launched in Japan at two municipalities in Hokkaido for the first time since NUMO initiated a nationwide call for volunteer municipalities in 2002, and the outcomes are currently being compiled. To enhance the public's understanding of how to implement safe geological disposal in Japan based on the latest scientific knowledge and technology, NUMO, as the implementing organisation, developed and published a safety case for geological disposal at the pre-siting stage. This safety case provides multiple lines of arguments and evidence to demonstrate the feasibility of the geological disposal and a basic structure for a safety case that will be applicable to any potential sites in Japan. The safety case also presented some R&D challenges to enhance the technical confidence of the project, including the R&D topics related to rock mechanics. This report presents the current status of the geological disposal programme in Japan, together with the status of the Literature Survey phase and an overview of the NUMO safety case. [ABSTRACT FROM AUTHOR]

The challenge experienced by users in navigating complex interior facilities is addressed by the Virtual Tour and Indoor Navigation System using QR Scanner in this research paper. Traditional navigation methods, such as maps and signals, can be difficult to comprehend and frequently give insufficient information about the surroundings. The Virtual Tour and Indoor Navigation System of College Premises named as Destiny is a cutting-edge system developed to give students, faculty, and visitors an immersive and interactive exploration of the college campus. To create an extensive and entertaining virtual tour experience, the system makes use of modern technologies such as virtual reality, augmented reality, and QR code scanning. Users can access a detailed map of the campus and navigate through different buildings and amenities, such as lecture rooms, libraries, labs, and sports facilities, using this system. Users can access extra information about each facility, including schedules, resources, and other pertinent data, by scanning QR codes posted at important areas. The system is user-friendly and accessible, allowing users to effortlessly navigate the college grounds and locate the amenities they require. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Turkish Operations Management (JTOM) is the property of Ankara Yildirim Beyazit University Journal of Turkish Operations Management (JTOM) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Modern Code Review (MCR) is a lightweight alternative to traditional code inspections. While secondary studies on MCR exist, it is uanknown whether the research community has targeted themes that practitioners consider important. Objectives: The objectives are to provide an overview of MCR research, analyze the practitioners’ opinions on the importance of MCR research, investigate the alignment between research and practice, and propose future MCR research avenues. Method: We conducted a systematic mapping study to survey state of the art until and including 2021, employed the Q-Methodology to analyze the practitioners’ perception of the relevance of MCR research, and analyzed the primary studies’ research impact. Results: We analyzed 244 primary studies, resulting in five themes. As a result of the 1,300 survey data points, we found that the respondents are positive about research investigating the impact of MCR on product quality and MCR process properties. In contrast, they are negative about human factor– and support systems–related research. Conclusion: These results indicate a misalignment between the state of the art and the themes deemed important by most survey respondents. Researchers should focus on solutions that can improve the state of MCR practice. We provide an MCR research agenda that can potentially increase the impact of MCR research. [ABSTRACT FROM AUTHOR]

Recent reviews have highlighted the dominance of vertebrates and plants in macroecological and biogeographical publications while invertebrates are underrepresented despite their global ecological relevance and vast diversity. We argue that although the study of invertebrate biogeography and macroecology has data limitations and thus lags behind in global research coverage, it has left a strong mark on the development of the discipline and has continuing potential to significantly shape its future. First, we detail how historical collecting and identification impediments caused decelerated progress at the macro-scale. Second, we show the quantitative impact of early invertebrate studies in contrast to lowered current representation. Third, we discuss ways in which authors, editors, and reviewers may foster invertebrate studies in macroecology. These include an honest appreciation of the value of study replication, of understudied but diverse taxa, and of the ecological traits that make invertebrates unique in comparison to vertebrates (e.g., wider array of life cycles, symbioses, and ecological niches), as well as the expanded potential for experimentation and manipulation.

Abstract This article intends to review the theoretical aspects and current research on agency theory. It aims to explore the main ideas, problems, and issues related to agency theory through a survey of the current literature. Agency theory is caused by agency relationships and information asymmetry which causes agency problems and agency costs. This article not only categorizes agency problems into six categories representing various concepts and problems but also solutions offered related to agency theory research over the last five years. This literature survey will enlighten practitioners and researchers in understanding, analyzing, mitigating agency problems, and guiding future research on agency theory. Abstrak Artikel ini bermaksud untuk meninjau aspek teoretis dan riset terkini tentang teori keagenan. Hal ini bertujuan untuk mengeksplorasi ide-ide utama, masalah, dan isu-isu yang terkait dengan teori keagenan melalui survei literatur saat ini. Teori keagenan disebabkan oleh hubungan keagenan dan asimetri informasi yang menyebabkan masalah keagenan dan biaya keagenan. Artikel ini tidak hanya mengkategorikan masalah keagenan ke dalam enam kategori yang mewakili berbagai konsep dan masalah tetapi juga menawarkan solusi terkait dengan riset teori keagenan selama lima tahun terakhir. Survei literatur ini akan mencerahkan praktisi dan peneliti dalam memahami, menganalisis, mengurangi masalah keagenan, dan membantu memandu riset selanjutnya tentang teori keagenan.

Iran, possessing unique topographic and diverse climatic conditions, is the home of 8167 vascular plant species. Iran has a historical tradition in using plants for medicinal purposes. Approximately 2075 species over the whole are popularly characterized as medicinal or aromatic. Medicinal trees and shrubs compose a significant percentage of Iranian medicinal flora. Nonetheless, there are no integrated databases on their applications and most of the publications and documents have been scattered to date. Therefore, the present investigation aims to integrate the published literature considering its ethnobotanical aspects that would serve as promising precursors for developing potent medicines of plant origin. In the study, we compile information about ethnobotany of trees and shrubs of Iran. Our survey found 174 taxa belonging to 109 genera and 56 families. The majority of species were classified in Rosaceae, Fabaceae, Rutaceae, Salicaceae, and Lamiaceae families. Rosaceae was the most dominant, representing 21.8% of the total plant species recorded, among them, the genus with the highest number of species was Prunus (16 species). Berberis vulgaris, Citrus limon, and Betula pendula have the highest number of medicinal uses (24 number of uses) in Iran. Leaves (22.7%) represented the most dominant usage of the plant parts, while the most commonly used preparation method was infusion (33.5%). Most of the plant species have been consumed for digestive system treatment (21%), followed by immune system treatment (20%). The present review highlights that different trees and shrubs taxa have great traditional applications in various healing throughout the Iranian territory. The represented data can potentially be a precious reference containing useful information for directing further phytochemical, biological, and pharmacological investigations. Several endemic species of trees and shrubs, particularly Ribes khorasanicum, are frequently used in Iranian traditional medicine. Because of overharvesting, these species are calling a wake-up alarm for conservation.

Intermediate public transport (IPT) or paratransit is an indispensable part of the transportation system in low and middle-income countries. This paper presents the state-of-the-art research advances in the domain of paratransit service quality evaluation through the use of systematic bibliographic analysis. The annual production rate of publication in this sector is 17.88%, which indicates the growing intensity of research activity in this subject and thus justifies the need to perform a thorough review of available literature. This holistic approach is aimed at providing comprehensive information on paratransit research areas, the citation networks, along with the contribution of different countries. All pertinent research studies published in Scopus until 2021 are analyzed to acquire research status in this domain. For the extraction of valuable knowledge from the archives of large-scale literature, the co-occurrence and the co-citation networks of concurrence are constructed. Visualizing the bibliographic network gives a clear understanding of the extent of the literature available, areas of expertise, and research trends. The comprehensive analysis of the shortlisted documents led to the identification of various sub-sectors of the research field, types of paratransit vehicles, and research methodologies adopted by different scholars to evaluate service quality. The research gap thus identified is that despite acknowledging the importance of IPT and its vital role in many developing countries, very few research studies have been conducted to evaluate its service quality. The significant findings through an in-depth review provide ways for the scope of future work.

Iran, possessing unique topographic and diverse climatic conditions, is the home of 8167 vascular plant species. Iran has a historical tradition in using plants for medicinal purposes. Approximately 2075 species over the whole are popularly characterized as medicinal or aromatic. Medicinal trees and shrubs compose a significant percentage of Iranian medicinal flora. Nonetheless, there are no integrated databases on their applications and most of the publications and documents have been scattered to date. Therefore, the present investigation aims to integrate the published literature considering its ethnobotanical aspects that would serve as promising precursors for developing potent medicines of plant origin. In the study, we compile information about ethnobotany of trees and shrubs of Iran. Our survey found 174 taxa belonging to 109 genera and 56 families. The majority of species were classified in Rosaceae, Fabaceae, Rutaceae, Salicaceae, and Lamiaceae families. Rosaceae was the most dominant, representing 21.8% of the total plant species recorded, among them, the genus with the highest number of species was Prunus (16 species). Berberis vulgaris, Citrus limon, and Betula pendula have the highest number of medicinal uses (24 number of uses) in Iran. Leaves (22.7%) represented the most dominant usage of the plant parts, while the most commonly used preparation method was infusion (33.5%). Most of the plant species have been consumed for digestive system treatment (21%), followed by immune system treatment (20%). The present review highlights that different trees and shrubs taxa have great traditional applications in various healing throughout the Iranian territory. The represented data can potentially be a precious reference containing useful information for directing further phytochemical, biological, and pharmacological investigations. Several endemic species of trees and shrubs, particularly Ribes khorasanicum, are frequently used in Iranian traditional medicine. Because of overharvesting, these species are calling a wake-up alarm for conservation. [ABSTRACT FROM AUTHOR]

Visible-infrared cross-modality person re-identification (VI-ReID) is currently a prevalent but challenging research topic in computer vision, since it can remedy the poor performance of existing single-modality ReID models under insufficient illumination, thus enabling the 24/7 surveillance systems. Although extensive research efforts have been dedicated to VI-ReID, a systematic and comprehensive literature review is still missing. Considering that, in this paper, a comprehensive review of VI-ReID approaches is provided. First, we clarify the importance, definition and challenges of VI-ReID. Secondly and most importantly, we elaborately analyze the motivations and the methodologies of existing VI-ReID methods. Accordingly, we will provide a comprehensive taxonomy, including 4 categories with 8 sub-items, for those state-of-the-art (SOTA) VI-ReID models. After that, we elaborate on some widely used datasets and evaluation metrics. Next, comprehensive comparisons of SOTA methods are made on the benchmark datasets. Based on the results, we point out the limitations of current methods. At last, we outline the challenges in this field and future research trends. [Display omitted] • Providing a comprehensive and detailed review for cross-modality person re-identification. • Categorizing existing VI-ReID approaches according to their motivations and methodologies. • Evaluating and comparing the performance of different VI-ReID methods. [ABSTRACT FROM AUTHOR]