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PurposeThis study aims to assess and decompose the sustainable development using the 17 sustainable development goals (SDGs) in Iran in 2018, for proposing agenda-setting of public policy.Design/methodology/approachIt ranks the SDGs not only in Iran but also in the region and the world to reveal the synergetic effects.FindingsBased on the results, subaltern-populace generally suffers from the hegemonic domination of ruling elite-bourgeois, lack of strong institutions, heterogeneous policy networks and lack of advocacy role of non-governmental organizations, due to no transparency, issues in law or no rule of law, no stringent regulation, rent, suppression and Mafia, all leading to corruption and injustice.Practical implicationsTo stop the loop of corruption-injustice, Iran should homogenize the structure of the policy network. Furthermore, the failed SDGs of the three-geographic analysis are the same in a character; all of them propose SDG 3, good health and well-being as a serious failed goal.Social implicationsIn this regard, strong evidence is the pandemic Coronavirus, COVID 19 since 2019, due to its highly-disastrous consequences in early 2020 where the public policymakers could not adopt policies promptly in the glob, particularly in Iran.Originality/valueIn Iran, in addition to this, the malfunction of health is rooted in “subjective well-being” and “traffic deaths,” respectively. Concerning the transportations system in Iran, it is underscored that it is damaging the sustainable development from all the three pillars of sustainable development including, economic, social and environmental.

Issuance of green bonds (GBs) is valuable for developing countries because it provides a market deepening mechanism, which enables greater liquidity for investments in Renewable Energy (RE) sector. This paper is premised on the outlook for the first GB in Ghana. The study investigates the features of GBs, which investors prioritise as preferential for RE financing (REF). Employing the literature, twelve beneficial features of GBs were identified and formed the based for a questionnaire, which was handed to experts in financial institutions to complete. Data were analysed and ranked with the relative importance index and other statistical tests. The findings illustrated that low-interest rates, similar payback period, economic convenience and transparency issuance are among the top preferential features for feasible green bond rollouts in Ghana. Findings implied that akin to other worldwide cases for renewable energy financing, GBs represent a degree of flexibility, which stems from the homogeneity in their respective features. The study illustrates the specific priorities, which must be considered by potential investors. Resultantly, enabling GBs issuers to develop GB packages that suit the needs of the investment community and ultimately contribute to RE targets' achievement.

Supply-chains (SC) present performance bottlenecks that contribute to a high level of costs, infiltration of product quality, and impact productivity. Examples of such inhibitors include the bullwhip effect, new product lines, high inventory, and restrictive data flows. These bottlenecks can force manufacturers to source more raw materials and increase production significantly. Also, restrictive data flow in a complex global SC network generally slows down the movement of goods and services. The use of Distributed Ledger Technologies (DLT) in supply chain management (SCM) demonstrates the potentials to to reduce these bottlenecks through transparency, decentralization, and optimizations in data management. These technologies promise to enhance the trustworthiness of entities within the supply chain, ensure the accuracy of data-driven operations, and enable existing SCM processes to migrate from a linear to a fully circular economy. This paper presents a comprehensive review of 111 articles published in the public domain in the use and efficacy of DLT in SC. It acts as a roadmap for current and future researchers who focus on SC Security Management to better understand the integration of digital technologies such as DLT. We clustered these articles using standard descriptors linked to trustworthiness, namely, immutability, transparency, traceability, and integrity.

Blockchain for supply chain use cases is quickly becoming a prevalent topic of discussion among distribution giants and smaller players. The actual and perceived benefits of blockchain have driven these discussions, as supply chain partners are well aware of the data protection, increased transparency, and end-to-end authentication of goods that blockchain technology can provide. Track and trace mandates from regulatory bodies are also driving the discussions. However, missing from the dialogue is how partners in this ecosystem manage and resolve disputes using smart contracts inherent in blockchain instead of existing dispute resolution mechanisms and processes. This gap is critical; trust will be eroded if supply chain partners do not have adequate dispute resolution mechanisms within the blockchain ecosystem. This paper highlights the areas of friction and potential disputes for supply chains arising from emerging technology such as Artificial Intelligence (AI), asset management using Internet of Things (IoT), and particularly blockchain, a type of Distributed Ledger Technology (DLT). We discuss the importance of regulation in how the use of DLT in supply chains is managed and suggest principles of resolving inevitable disputes with disparate information. We emphasize the need for portable and enforceable contractual terms and argue that standardizing how disputes are resolved may go a long way to technology adoption.

Worker selection in crowdsensing plays an important role in the quality control of sensing services. The majority of existing studies on worker selection {\color{red}were} largely dependent on a trusted centralized server, which might suffer from single point of failure, the lack of transparency and so on. Some works recently proposed blockchain-based crowdsensing, which {\color{red}utilized} reputation values stored on blockchains to select trusted workers. However, the transparency of blockchains enables attackers to effectively infer private information about workers by the disclosure of their reputation values. In this paper, we {\color{red}proposed} the TrustWorker, a trustworthy and privacy-preserving worker selection scheme for blockchain-based crowdsensing. By taking the advantages of blockchains such as decentralization, transparency and immutability, our TrustWorker {\color{red}could} make the worker selection process trustworthy. To protect workers' reputation privacy in our TrustWorker, we {\color{red}adopted} a deterministic encryption algorithm to encrypt reputation values and then {\color{red}selected} the top N workers in the light of secret minimum heapsort scheme. Finally, we theoretically {\color{red}analyzed} the effectiveness and efficiency of our TrustWorker, and then {\color{red}conducted} a series of experiments. The theoretical analysis and experiment results demonstrate that our TrustWorker can achieve trustworthy worker selection, while ensuring the workers' privacy and the high quality of sensing services.

Despite the critical roles of knowledge filters and knowledge spillovers in the knowledge spillover theory of entrepreneurship (KSTE), the impact of knowledge filters on knowledge spillovers at the firm level remains underexplored. This article thus extends the KSTE to the firm level by directly investigating the effects of knowledge filters on knowledge spillovers (employee venturing behaviors) in incumbent firms. Moreover, based on the KSTE and institutional theory, we examine how regulatory institution (government support) and the enforceability of it (government transparency) moderate the effect of knowledge filters in incumbent firms on their employee venturing behaviors. We collect survey data from the Chinese pharmaceutical industry as it is knowledge intensive and entrepreneurially active by using a multi-informant method, that is, two senior managers from every responding company were interviewed on site by using structured questionnaires. To further minimize bias, we combine the survey data with provincial secondary data to test research hypotheses. Our findings reveal that the positive link between incumbent firms’ knowledge filters and employee venturing behaviors is enhanced by government policy support and government tax support. Furthermore, government transparency strengthens the moderating effect of government policy support whereas it weakens the moderating role of government tax support on the link between knowledge filters and employee venturing behaviors. Overall, this article explores the key proposition of the KSTE framework at the firm level, thus constructing the microfoundation of the KSTE, and substantiates the importance of integrating regulatory institutions into the firm-level KSTE.

Blockchain is a chain of blocks where each block contains a set of transactions that are digitally signed by its verifier and stored across the distributed network so that all the legitimate stakeholders can access/verify them. Due to the attributes of Blockchain such as decentralization, immutability, auditability, transparency, and cryptographic security, it offers various benefits to different domains such as cryptocurrency, financial sectors, private/public segments, insurance, healthcare, supply chain management, Internet of Things, etc. However, the technology is in its early stage and still, there is a range of concerns that are yet to be addressed before its wide adoption. Through this paper, we intend to cover extensive study on the Blockchain that includes taxonomy, application/use-cases, consensus mechanisms, prospective research, future directions, and related technologies. This paper also aims to discuss the opportunities, benefits, and challenges of Blockchain technology and to assist the research community in understanding the same.

The automotive industry has witnessed an increasing level of development in the past decades; from manufacturing manually operated vehicles to manufacturing vehicles with a high level of automation. With the recent developments in Artificial Intelligence (AI), automotive companies now employ blackbox AI models to enable vehicles to perceive their environments and make driving decisions with little or no input from a human. With the hope to deploy autonomous vehicles (AV) on a commercial scale, the acceptance of AV by society becomes paramount and may largely depend on their degree of transparency, trustworthiness, and compliance with regulations. The assessment of the compliance of AVs to these acceptance requirements can be facilitated through the provision of explanations for AVs' behaviour. Explainability is therefore seen as an important requirement for AVs. AVs should be able to explain what they have 'seen', done, and might do in environments in which they operate. In this paper, we provide a comprehensive survey of the existing body of work around explainable autonomous driving. First, we open with a motivation for explanations by highlighting and emphasising the importance of transparency, accountability, and trust in AVs; and examining existing regulations and standards related to AVs. Second, we identify and categorise the different stakeholders involved in the development, use, and regulation of AVs and elicit their explanation requirements for AV. Third, we provide a rigorous review of previous work on explanations for the different AV operations (i.e., perception, localisation, planning, control, and system management). Finally, we identify pertinent challenges and provide recommendations, such as a conceptual framework for AV explainability. This survey aims to provide the fundamental knowledge required of researchers who are interested in explainability in AVs., Comment: Accepted for publication in IEEE Transactions on Intelligent Transportation Systems

With calls for increasing transparency, governments are releasing greater amounts of data in multiple domains including finance, education, and healthcare. We focus on healthcare due to its economic importance worldwide. The efficient exploratory analysis of healthcare data constitutes a significant challenge. Key concerns in public health include the quick identification and analysis of trends and the detection of outliers. This allows policies to be rapidly adapted to changing circumstances. We present an efficient outlier detection technique, termed PIKS (Pruned iterative-k means searchlight), which combines an iterative k-means algorithm with a pruned searchlight based scan. We apply this technique to identify outliers in two publicly available healthcare datasets from the New York Statewide Planning and Research Cooperative System, and California’s Office of Statewide Health Planning and Development. We provide a comparison of our technique with three other existing outlier detection techniques, consisting of auto-encoders, isolation forests, and feature bagging. We identified outliers in conditions including suicide rates, immunity disorders, social admissions, cardiomyopathies, and pregnancy in the third trimester. We demonstrate that the PIKS technique produces results consistent with other techniques such as the auto-encoder. However, the auto-encoder needs to be trained, which requires several parameters to be tuned. In comparison, the PIKS technique has far fewer parameters to tune. This makes it advantageous for fast, “out-of-the-box” data exploration. The PIKS technique is scalable and can readily ingest new datasets. Hence, it can provide valuable, up-to-date insights to citizens, patients, and policy-makers. We have made our code open source, and with the availability of open data, other researchers can easily reproduce and extend our work. This will help promote a deeper understanding of healthcare policies and public health issues.

Leading by example is one of the most powerful methods to encourage individuals to work toward a common objective. Despite the importance of leadership, little is known about how the effectiveness of leading by example depends on institutional features, such as the transparency and design of leaders' compensation contracts. We conduct two experiments to study this interplay between leadership and contracting in organizations with social missions (i.e., socially driven organizations). We find that under non-transparent contracts, leader contributions to the social objective positively influence follower contributions, reflecting effective leading by example. More importantly, under transparent contracts, the positive effect of leader contributions on follower contributions is diminished by an increase in the intensity of variable compensation and/or the amount of fixed compensation in the leader's contract. Our study informs the debate on pay transparency and demonstrates that organizations need to carefully consider the effects of contract design on leadership effectiveness. Data Availability: Contact the authors. JEL Classifications: C90; D63; D83; M40; M52.

Earthquake models can produce aftershock forecasts, which have recently been released to lay audiences following large earthquakes. While visualization literature suggests that displaying forecast uncertainty can improve how forecast maps are used, research on uncertainty visualization is missing from earthquake science. We designed a pre-registered online experiment to test the effectiveness of three visualization techniques for displaying aftershock forecast maps and their uncertainty. These maps showed the forecasted number of aftershocks at each location for a week following a hypothetical mainshock, along with the uncertainty around each location’s forecast. Three different uncertainty visualizations were produced: (1) forecast and uncertainty maps adjacent to one another; (2) the forecast map depicted in a color scheme, with the uncertainty shown by the transparency of the color; and (3) two maps that showed the lower and upper bounds of the forecast distribution at each location. Unlike previous experiments, we compared the three uncertainty visualizations using tasks that are systematically designed to address broadly applicable and user-generated communication goals. We compared task responses between participants using uncertainty visualizations and using the forecast map shown without its uncertainty (the current practice). Participants completed two map-reading tasks that targeted several dimensions of the readability of uncertainty visualizations. Participants then performed a comparative judgment task, which demonstrated whether a visualization was successful in reaching two key communication goals: indicating where many aftershocks and no aftershocks are likely (sure bets) and where the forecast is low but the uncertainty is high enough to imply potential risk (surprises). All visualizations performed equally well in the goal of communicating sure bet situations. But the visualization with lower and upper bounds was substantially better than the other designs at communicating surprises. These results have implications for the communication of forecast uncertainty both within and beyond earthquake science.

This article reflects on current trends and proposes new considerations for the future of mobile technologies for health (mHealth). Our focus is predominantly on the value of and concerns with regard to the application of digital health within low- and middle-income countries (LMICs). It is in LMICs and marginalized communities that mHealth (within the wider scope of digital health) could be most useful and valuable. Peer-reviewed literature on mHealth in LMICs provides reassurance of this potential, often reflecting on the ubiquity of mobile phones and ever-increasing connectivity globally, reaching remote or otherwise disengaged populations. Efforts to adapt successful programs for LMIC contexts and populations are only just starting to reap rewards. Private-sector investment in mHealth offers value through enhanced capacity and advances in technology as well as the ability to meet increasing consumer demand for real-time, accessible, convenient, and choice-driven health care options. We examine some of the potential considerations associated with a private-sector investment, questioning whether a core of transparency, local ownership, equity, and safety are likely to be upheld in the current environment of health entrepreneurship. Expected final online publication date for the Annual Review of Public Health, Volume 43 is April 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

This paper considers the digitalisation of food infrastructure as a wider context within which smart farming and big data applications in agriculture are being introduced. It examines the use of digital devices aimed providing traceability and transparency across different sites of food supply chains, from farm to fork. The infrastructural perspective problematises ideas of digitalisation as a technological fix to the uncertainness of food supply chains, and highlights the relational nature of food. Digital devices aimed at ensuring food integrity and the control of supply chains are shown to reconstitute infrastructures of qualification by which the qualities of foodstuffs are established as they move through the processes of the supply chain, from production to consumption. The paper identifies question of power around the ongoing process of infrastructuring that generate a requirement for more labour by some actors; the possibility of new politics and relationships built around increased circulation of quality information; and questions of who controls access to information that are obscured by different understandings of transparency.

INTRODUCTIONSARS-CoV-2 testing is one of the options to combat COVID-19 in Kenya. In the first COVID-19 year there was limited tapping of the private sectors potential to scale up testing in Kenya. In April 2020, we initiated a unique public-private partnership (PPP) project in Kisumu County connecting the private sector to centralized testing supported by the ministry of health (MoH), COVID-Dx, to accelerate the local response to COVID-19. Within COVID-Dx, we aimed to demonstrate this PPPs performance as a replicable model for effective public-private collaboration in responding to the COVID-19 pandemic in similar settings. METHODSKEMRI, Department of Health Kisumu County, PharmAccess Foundation, and local faith-based and private healthcare facilities collaborated in COVID-Dx. COVID-Dx was implemented from June 01, 2020, to March 31, 2021, in Kisumu County, Kenya. Trained laboratory technologists in participating healthcare facilities collected nasopharyngeal and oropharyngeal samples from patients meeting the MoH COVID-19 case definition. Samples were tested at the central laboratory in KEMRI via SARS-CoV-2 RT-PCR. Healthcare workers in participating facilities collected data using the digitized MoH COVID-19 Case Identification Form. We shared aggregated results from these data via (semi-) live dashboard to all relevant stakeholders. We did descriptive statistical analyses using Stata 16 to inform project processes. RESULTSNine facilities participated in the project. A total of 4,324 PCR tests for SARS-CoV-2 were done, with 425 positives. We noted differences in positivity rates between the facilities. Healthcare workers were the largest group tested in the project, 1009, representing 43% of the Kisumu healthcare workforce. CONCLUSIONCOVID-Dx can serve as a model for PPPs scale-up testing, especially LMICs, and digitizing the MoH case report form improved reporting efficiency, demonstrating that digital is the way forward. The COVID-Dx PPP has led to another collaboration with Kisumu County aimed towards extending the COVID-Dx model to other counties. SUMMARY BOX O_TEXTBOXWhat is already known?O_LIIn sub-Saharan Africa, COVID-19 responses are mainly rolled out through the public healthcare sector, even though the private sector plays a significant role in health service delivery C_LIO_LIThe challenge is to combine private and public efforts in healthcare delivery in a mutually supportive and collaborative manner, especially during large outbreaks such as COVID-19. C_LI What are the new findings?O_LIThe development of a public-private partnership (COVID-Dx) at the start of a global pandemic - COVID-19 - is challenging, but PPPs are essential for epidemic preparedness. C_LIO_LIThe development of a digital app with a corresponding dashboard, ensures transparency and efficiency. It has shown to enable data-driven decision-making and provides insight into how to prioritize funding streams. C_LI What do the new findings imply?O_LIThis PPP model is replicable and can serve as an example of PPPs for epidemic preparedness in similar settings in LMICs. C_LIO_LIDigital is the way going forward when combatting large outbreaks in the future, especially in LMICs C_LI C_TEXTBOX

This article aims to review and systematize prior works that investigate how the presence of women in top echelon positions of firms affects sustainability and to create an agenda to guide future research in this promising area. In contrast to previous reviews, ours examines how women in top echelon positions affect sustainability by distinguishing both the position women held in the firm (i.e. Board of Directors—BoD, top management team, CEO and relevant committees) and the specific elements of sustainability (i.e. activity, performance, and disclosure). Our structured systematic review resulted in 187 publications retrieved from Web of Science and Scopus and revealed that the presence of women in top echelon positions is associated with greater engagement in social and environmental projects. Their presence also positively influences the environmental and social performance and increases the level, quality, and transparency of sustainability disclosure. Furthermore, the presence of women in top echelon positions and the implementation of sustainable activities improve both the firm financial performance and value. However, conflicting results have also emerged. On the basis of these findings, research gaps and future research agenda are identified and presented.

Due to rapidly rising healthcare costs worldwide, there is significant interest in controlling them. An important aspect concerns price transparency, as preliminary efforts have demonstrated that patients will shop for lower costs, driving efficiency. This requires the data to be made available, and models that can predict healthcare costs for a wide range of patient demographics and conditions. We present an approach to this problem by developing a predictive model using machine-learning techniques. We analyzed de-identified patient data from New York State SPARCS (statewide planning and research cooperative system), consisting of 2.3 million records in 2016. We built models to predict costs from patient diagnoses and demographics. We investigated two model classes consisting of sparse regression and decision trees. We obtained the best performance by using a decision tree with depth 10. We obtained an R-square value of 0.76 which is better than the values reported in the literature for similar problems., Comment: 2020 IEEE International Conference on Healthcare Informatics (ICHI)

Increasingly, marketing and consumer researchers rely on online data collection services. While actively-managed data collection services directly assist with the sampling process, minimally-managed data collection services, such as Amazon’s Mechanical Turk (MTurk), leave researchers solely responsible for recruiting, screening, cleaning, and evaluating responses. The research reported here proposes a 2 x 2 framework based on sampling goal and methodology for screening and evaluating the quality of online samples. By sampling goals, screeners can be categorized as selection, which involves matching the sample with the targeted population; or as accuracy, which involves ensuring that participants are appropriately attentive. By methodology, screeners can be categorized as direct, which screens individual responses; and as statistical, which provides quantitative signals of low quality. Multiple screeners for each of the four categories are compared across three MTurk samples, two actively-managed data collection samples (Qualtrics and Dynata), and a student sample. The results suggest the need for screening in every online sample, particularly for the MTurk samples, with the fewest supplier-provided filters. Recommendations are provided for researchers and journal reviewers that provide greater transparency with respect to sample practices.

The role that private actors play in accelerating or preventing progressive climate policy and true decarbonization is a core research interest of global environmental politics. Yet scholars have struggled to measure the political behavior of multinational firms due to lack of transparency about their activities and inconsistency in reporting requirements across jurisdictions. In this research note, we present a new data source—firms’ earnings calls—that scholars might use to better understand the political behavior of major multinational polluters. To illustrate the value of earnings calls as a data source, we construct an original data set of all earnings calls made between 2005 and 2019 by major oil and gas firms. We then code these transcripts, demonstrating that although firms can be classified as more or less pro-climate, there is little evidence of the industry’s public acceptance of decarbonization. These unique data could permit researchers to explore important questions about climate politics, the evolution of private governance, and the relationship between policy and firms’ political behavior. Moreover, we suggest extensions of our approach, including other multinational industries that are amenable to this type of analysis.

Permissionless blockchains have been described as a novel institutional building block for voluntary economic exchange, with unique protocol features such as automated contract execution, high levels of network and process transparency, and uniquely distributed governance. We argue that conventional institutional economics analysis of blockchain networks is incomplete absent a more robust application of descriptive polycentric analysis. Though the distributed governance that permissionless blockchain protocols provide is novel, these networks nonetheless require ongoing coordination between stakeholders and are subject to competitive pressures much like other private organizations pursuing similar goals for a set of users who can choose among providers. We characterize change on blockchain networks as resulting from internal sources and external sources. These internal sources include constitutional (protocol) design and the related need for collective choice processes to update protocols. In addition to law and regulation, competitive pressure is itself a critical external source of governance. Predominantly through analysis of two leading cryptocurrency networks, Bitcoin and Ethereum, we illustrate how conceptualizing of blockchain as a polycentric enterprise enhances our predictive and descriptive understanding of these networks.

The concept of Industry 4.0 was conceived to make manufacturing and industrial processes more modern and sustainable. It is achieved through the use of emerging technologies such as IoT, additive manufacturing, and robotics. One such technology is Blockchain, which provides many benefits like security, decentralization, and transparency. Blockchain was first proposed in the year 2008 as the technology behind the now-famous cryptocurrency Bitcoin. Since then, blockchain technology has seen a lot of improvements and changes. Blockchain has also branched out from its digital currencies to other industries such as healthcare, governance, supply chain, and entertainment. This article focuses on how and why blockchain technology can be used in conjunction with additive manufacturing and other new technologies to keep up with the current manufacturing demands of consumers. This article zeros in on the existing problems in the manufacturing industry and how blockchain and additive manufacturing can be used to mitigate them and provides rough guidelines for future researchers or organizations looking to integrate Blockchain into their supply chain.

Some criticize the data-driven study of driverless car ethics for relying on deterministic crash scenarios where the focus should be on minimizing the occurrence of accidents instead. Indeed, decisions in road traffic are taken in the domain of risk. A relevant ethical question is, however, whether autonomous vehicles should actually minimize an accident’s probability or rather balance the accident’s probability and severity. While ethicists’ introspections might lead them to different conclusions, a participatory paradigm in ethics demands to include laypeople’s intuitions into the societal debate. In three online studies, we found that the mere minimization of accident probability in ethical dilemmas does not correspond to the views of our sample. Our participants favor a balanced consideration of accident probability and severity. This remains true even if the underlying dilemma is based on a more realistic scenario of allocating minor risks among road users. Our findings furthermore illustrate that trolley problems may be informative for autonomous vehicles and emphasize the importance of transparency if manufacturers and the public do not agree on guiding principles in road traffic.

Why is Digital Transformation Important? Digital transformation is changing the way an organization operates. Systems, processes, workflow, and culture are all evaluated. This transformation affects each level of an organization and brings together data across areas to work together more effectively. • It is worth noting that we point with much pride to the recent trends of the Egyptian state to enhance and support the development in the provision of smart and mechanized government services... in order to raise the productive efficiency of the employee in various work sites and achieve a technological breakthrough in all sectors... as well as facilitation for citizens in Get the desired service • We recall in this context the achievements of Egypt in this field A budget of one billion pounds was allocated in the 2019-2020 budget To update the information infrastructure and digital content... In this context, and within the efforts of the Egyptian Ministry of Planning represented in the Information and Decision Support Center, the electronic enterprise management system (institutional memory) was launched: It is one of the leading and specialized programs in the Middle East in the field of managing electronic institutions through the methods it provides for following up and developing the administrative performance.. The use of this program has led to control and governance and enhance the transparency of the financial performance of the state.. as well as tightening control over government expenditures and raising the efficiency of spending

Modern agri-food supply chains have transitioned from autonomous and independent local actors to globally interlinked system of multiactors connected by complex relationships, affecting ways in which food is produced, processed, transported, and delivered to end consumers. Frequent incidences of fraudulent practices expose lack of transparency in agri-food supply chains, causing concerns related to economic losses, eroding consumer trust and enterprise brand value. Traditionally associated with cryptocurrencies, banking and finance, blockchains are now being applied in the agri-food sector to address supply chain-related challenges. This article examines the question: How blockchain technology facilitates transparency in agri-food supply chains? Primary attributes of blockchain, namely traceability, immutability, auditability, and provenance, promote transparency in supply chains. Using thematic analysis, the following three areas were identified for implementing blockchain in agri-food supply chains: first, agri-food distribution; second, agri-food origin and sourcing; third, agri-food safety and quality. By cross-mapping thematic areas with primary attributes, our analysis resulted in classification of 25 uses cases. Preliminary findings of this study highlight blockchain-enabled transparency via contemporary uses cases in conceptual, proof-of-concept and commercial stages. It is imperative to sift through the hype and scrutinize limitations of the technology which could interfere with its adoption, deployment, and scalability in agri-food supply chains.

Conspicuous interdisciplinary effort has been spent on addressing the consequences of climate change in a forward-looking way. The concept of solution space is a recent contribution to help decision-makers identify feasible and effective adaptation solutions and to provide guidance on when they should be implemented and by whom. Although the current conceptualization of solution space already considers multiple disciplines, it remains dominated by biophysical ones and has not yet fully integrated legal and governance dimensions. This article first reflects on the current solution space framework through the lenses of law and governance and then proposes approaches to enrich legal and governance dimensions in the solution space concept. We argue that the legal and governance dimensions of the current concept of solution space can be improved by taking into account four aspects: 1) understanding the institutional and legal systems in a context-specific way; 2) embracing the dynamics and reflexivity of law and governance in the episteme of path dependency; 3) applying more diverse analytical methods (qualitative, qualitative/ quantitative, value-oriented) and/or assessments on a case-by-case basis; and 4) adding a normative perspective that includes the principles of legitimacy, transparency, accountability, equity, and distributive justice to measure the appropriateness of a certain adaptation strategy. The article concludes with suggestions for future research on how to implement the enriched solution space concept.

The research aims to use the blockchain technology to ensure the distribution of XBRL content to a decentralized peer- to-peer network while maintaining the authority of the government toward the whole data. The topic of combination XBRL and blockchain is scarcely discussed in academic journal due to the very early stage of technology development. This paper explains how to build a distributed ledger platform prototype that designed to improve financial reports transparency and integrity by using blockchain technology in line with XBRL to form XBRL chain. XBRL chain helps in developing smart contracts that more business rules encoded in software, why are as good as the person or team devising the rules and the developer turning those rules into code. These smart contracts with newest encoded accounting rules could effectively control the recording of accounting activities. Therefore, these contracts would provide automatic assurance on processes, such as posting, classification and cutoff. The proposed framework of XBRL chain makes the quality of information in the financial reporting more interoperability and comparability. This framework should subject to six situational conditions are: multi party, trusted authority, decentralization, smart contract, data confusability, and type of blockchain. A case study is implemented on Egyptian company (EDITA ) Food Company that publishes its financial statements under IFRS. The case explained how the integration between XBRL and blockchain can be built to implement XBRL mapping for consolidated balance sheet and profit or loss statement the mapping process is implemented under using black chain software. Also, the percentage of fit between IFRS taxonomy 2020 and Egyptian financial practices are measured. The findings of the case study revealed that, for EDITA Food Company, 89 percent of the elements in the two basic financial statements exist in the taxonomy. The high degree of misfit is found in the balance sheet statement 14 percent and in income statement is 6 percent limitations and future research directions are, this paper contributes to the literature by expending upon emerging concerns and providing opportunities for future research.

The wealth of user data acts as a fuel for network intelligence toward the sixth generation wireless networks (6G). Due to data heterogeneity and dynamics, decentralized data management (DM) is desirable for achieving transparent data operations across network domains, and blockchain can be a promising solution. However, the increasing data volume and stringent data privacy-preservation requirements in 6G bring significantly technical challenge to balance transparency, efficiency, and privacy requirements in decentralized blockchain-based DM. In this paper, we propose blockchain solutions to address the challenge. First, we explore the consensus protocols and scalability mechanisms in blockchains and discuss the roles of DM stakeholders in blockchain architectures. Second, we investigate the authentication and authorization requirements for DM stakeholders. Third, we categorize DM privacy requirements and study blockchain-based mechanisms for collaborative data processing. Subsequently, we present research issues and potential solutions for blockchain-based DM toward 6G from these three perspectives. Finally, we conclude this paper and discuss future research directions.

With the rapid development of digital devices, how to transmit information among different devices with multimedia carrier has drawn much attention from the research community. This paper focuses on the important user scenario ‘`screen-to-camera information transmission’'. Along this direction, image coding based techniques have been shown to be the most popular and effective way in the past decades. However after careful study, we find none of existing methods can satisfy the four important properties simultaneously, i.e., high transparency, high embedding efficiency, strong transmission robustness and high adaptability to device types. It is mainly because these properties are contradictory with each other. So in this paper, we propose an screen-to-camera image code dubbed ‘`TERA’' with Transparency, Efficiency, Robustness and Adaptability, which makes it possible to circumvent the contradiction among the above four properties for the first time. Generally, it adopts the color decomposition principle to ensure the visual quality and the superposition-based scheme to ensure embedding efficiency. And BCH-coding-based information arrangement and a powerful attention-guided information decoding network are further designed to guarantee the robustness and adaptability. Through extensive experiments, the superiority and broad applications of our method are demonstrated.

Explainable Artificial Intelligence (XAI) is an emerging research topic of machine learning aimed at unboxing how AI systems' black-box choices are made. This research field inspects the measures and models involved in decision-making and seeks solutions to explain them explicitly. Many of the machine learning algorithms can not manifest how and why a decision has been cast. This is particularly true of the most popular deep neural network approaches currently in use. Consequently, our confidence in AI systems can be hindered by the lack of explainability in these black-box models. The XAI becomes more and more crucial for deep learning powered applications, especially for medical and healthcare studies, although in general these deep neural networks can return an arresting dividend in performance. The insufficient explainability and transparency in most existing AI systems can be one of the major reasons that successful implementation and integration of AI tools into routine clinical practice are uncommon. In this study, we first surveyed the current progress of XAI and in particular its advances in healthcare applications. We then introduced our solutions for XAI leveraging multi-modal and multi-centre data fusion, and subsequently validated in two showcases following real clinical scenarios. Comprehensive quantitative and qualitative analyses can prove the efficacy of our proposed XAI solutions, from which we can envisage successful applications in a broader range of clinical questions., 68 pages, 19 figures, submitted to the Information Fusion journal

This article developed an integrated framework for idea screening in the front end of innovation. A hierarchical decision model was used to develop the integrated framework. The proposed framework is deployed via a questionnaire of 15 experts from 7 well-known high technology organizations across multiple countries, using Delphi method to identify and validate criteria in front end new product idea screening process. The findings from integrating three perspectives (intuition, rationality, and reflections) show that idea screening can be improved in the context of creativity, quality, transparency, and effectiveness in decision making. This integration helped to reveal additional screening criteria to existing studies. The conversion of implicit to explicit knowledge that can be documented is beneficial to continuous improvement in decision making. Combining the three perspectives within the deployed framework contributes to a more in-depth understanding of idea screening that is complementary and represents a robust approach in comparison to existing studies that use either one or two perspectives, particularly since the findings complement the limitations of a human mind; given that much of idea screening occurs in the minds of experts. Future work involves applying the proposed framework in practice, for selecting the best idea to fund in a specific organization.

There are many ways in which education 4.0 can continue to develop rapidly and coexist with the development of increasingly advanced technology to be able to bond with each other to be balanced, one of which is using blockchain technology which is integrated in the education sector for various purposes. The main direction in the process of developing global integration in the field of education which includes the creation of a single educational space and optimization of interaction between education and stakeholder relationships. The blockchain method that is incorporated in education 4.0 in Indonesia cannot be said to be widely used because initially blockchain was only known for the financial sector. In fact blockchain is very broad and very appropriate to be applied in this era, as if blockchain offers technology, trust and transparency by replacing the previous system with a new system. A special problem in the need for innovative research to be able to offer new insights into blockchain transformation inf education and application opportunities that can be accepted and used optimally. Researchers used the vast mind method and literature study. The goal is to be able to inform the added value of blockchain that is applied in education as needed, the renewal of research and opportunities for implementing blockchain in education 4.0. Blockchain technology that can be used in education, for example, is archiving, learning, certification and other.

Purpose This study aims to blockchain facilitate information sharing among different players in the food industry, such as farmers, food suppliers and investors, enabling an effective decision-making process where the information about goods is traceable without any inherent risk. Although blockchain technology is emerging, its use in the food industry needs to be explored from different angles, such as organizations’ policy, adoption strategies and potential technology innovations which could positively impact business processes. Design/methodology/approach For this purpose, the authors survey 84 organizations in the food industry. Further, the authors conducted in-depth- interviews with three organizations that applied blockchain technology in the production phase to address the pros and cons of this adaption and discuss how the technology could be improved based on the challenges they faced. Moreover, an overview of current and potential digital transformation uses cases of blockchain technology in the food industry has been provided. Findings The results suggested that perceived efficiency, transparency, standardization and platform development and traceability factors positively influenced intention to use (ITU). Practical implications The adoption of the blockchain cloud solution is neither time-consuming nor expensive; organizations may attempt to predict how regulations or standards will be developed to create a blockchain solution compatible with them. Originality/value This study is among the primary studies investigating the role of blockchain technology in the food sector from the organizations’ viewpoint, highlighting the factors influencing the ITU.

The volume of the biomedical literature continues to expand at a substantial rate. The research literature surrounding pharmaceutical services is no different. Due in part to events in the recent past, researchers, consumers, funders, and policymakers have raised concerns about the credibility, transparency, and potential waste in the global research enterprise. Meta-research, or research on research, provides a way to examine the efficiency, quality, and potential bias in the overall research ecosystem. The field of meta-research is a relatively new but rapidly growing field that has seen many applications in biomedical research. Applications in pharmacy research, however, are still developing. The goals of this commentary are to introduce pharmacy researchers to the concept of meta-research, discuss several examples of meta-research in pharmacy, and motivate the importance of sustained meta-research efforts in pharmacy.

In this paper, we explore and describe what is needed to allow connected and automated vehicles (CAVs) to break traffic rules in order to minimise road safety risk and to operate with appropriate transparency (according to recommendation 4 in Bonnefon et al., European Commission, 2020). Reviewing current traffic rules with particular reference to two driving situations (speeding and mounting the pavement), we illustrate why current traffic rules are not suitable for CAVs and why making new traffic rules specifically for CAVs would be inappropriate. In defining an alternative approach to achieving safe CAV driving behaviours, we describe the use of ethical goal functions as part of hybrid AI systems, suggesting that functions should be defined by governmental bodies with input from citizens and stakeholders. Ethical goal functions for CAVs would enable developers to optimise driving behaviours for safety under conditions of uncertainty whilst allowing for differentiation of products according to brand values. Such functions can differ between regions according to preferences for safety behaviours within that region and can be updated over time, responding to continual socio-technological feedback loops. We conclude that defining ethical goal functions is an urgent and necessary step from governmental bodies to enable the safe and transparent operation of CAVs and accelerate the reduction in road casualties they promise to achieve.

Orbital congestion, contestation and competition are on the rise, and space activities are expected to align with treaties, arrangements, and guidelines elaborated at a time when the space ecosystem was simpler - and it is becoming more complex. To cope efficiently with this changing situation, at a time when space systems have become an indispensable enabler for an ever-increasing range of socio-economic activities, new rules of the road are necessary. Indeed, these should ensure the sustained stability and security of the space environment, providing norms and standards beyond transparency and confidence building measures, laying the ground for the founding elements of a space traffic coordination (management?). Hence, for us to be dependent on a reliable space-enabled information flow will require a significant decrease of their vulnerability; protection as well as “fail safe” are becoming the chief concerns. This paper will first review the current legal and regulatory provisions under which space activities take place, pointing out some limitations of the international dialogue, which is quite complex, anarchic, and with no clear global leadership, complicated by the dual use (civil and military) of space. Moreover, enforcement appears to be ineffective. It will then consider new public, as well as private, initiatives that are underway, evaluating the robustness of their foundations. Possible avenues are proposed in support of the most recent prominent initiatives, including the possibility for an international agreement on standards and behaviours, or an international civil space organisation inspired by the International Civil Aviation Organisation - ICAO. Emphasis will be placed on the urgency of bringing together these initiatives and processes under a common umbrella, or at least to achieve the convergence of a set of rules noting that international hard law provisions are far reaching. A step-by-step approach is suggested, addressing immediate, mid-term, and long-term actions to provide a stable space environment favourable to LEO large constellations, in-orbit refuelling/repairing, active debris removal, human commercial space-flight, cis-lunar/interplanetary traffic, space resources exploitation, and security/defence operations.

Background As operating room (OR) expenditures increase, faculty and surgical trainees will play a key role in curbing future costs. However, supply cost utilization varies widely among providers and, despite requirements for cost education during surgical training, little is known about trainees' comfort discussing these topics. To improve OR cost transparency, our institution began delivering real-time supply “receipts” to faculty and trainees after each surgical case. This study compares faculty and surgical trainees' perceptions about supply receipts and their effect on individual practice and cultural change. Study Design Faculty and surgical trainees (residents and fellows) from all adult surgical specialties at a large academic center were emailed separate surveys. Results A total of 120 faculty (30.0% response rate) and 119 trainees (35.7% response rate) completed the survey. Compared with trainees, faculty are more confident discussing OR costs (p Conclusions Supply receipts have been well received and have led to meaningful cultural changes. However, trainees are less confident discussing these issues and desire a greater emphasis on OR cost in their curriculum.

Objectives To assess the quality of diabetic eye disease clinical practice guidelines. Study design and setting A systematic search of diabetic eye disease guidelines was conducted on six online databases and guideline repositories. Four reviewers independently rated quality using the Appraisal of Guidelines, Research, and Evaluation (AGREE II) instrument. Aggregate scores (%) for six domains and overall quality assessment were calculated. A “good quality” guideline was one with ≥60% score for “rigor of development” and in at least two other domains. Results Eighteen guidelines met the inclusion criteria, of which 13 were evidence-based guidelines (involved systematic search and grading of evidence). The median scores (interquartile range (IQR)) for “scope and purpose,” “stakeholder involvement,” “rigor of development,” “clarity of presentation,” “applicability” and “editorial independence” were 73.6% (54.2%–80.6%), 48.6% (29.2%–71.5%), 60.2% (30.9%–78.1%), 86.6% (76.7%–94.4%), 28.6% (18.0%–37.8%) and 60.2% (30.9%–78.1%), respectively. The median overall score (out of 7) of all guidelines was 5.1 (IQR: 3.7–5.8). Evidence-based guidelines scored significantly higher compared to expert-consensus guidelines. Half (n = 9) of the guidelines (all evidence-based) were of “good quality.” Conclusion A wide variation in methodological quality exists among diabetic eyecare guidelines, with nine demonstrating “good quality.” Future iterations of guidelines could improve by appropriately engaging stakeholders, following a rigorous development process, including support for application in clinical practice and ensuring editorial transparency.

When COVID-19 hit, many people began working, going to school, and living much of their lives from home. The Internet was a gateway to the world. This article uses data from Internet speed tests, consumer complaints, search engine optimization tools, and logs of Internet use from public libraries to understand the effects of the pandemic on Internet use and performance. Despite reports that the Internet handled the surge in traffic well, we find that complaints about Internet speed nearly tripled, and performance was degraded. Downstream data rates changed little, but median upstream data rates at midday dropped by about a third. When discussing Internet performance, people typically focus on downstream. This focus should shift. Internet service providers and policymakers should reduce the asymmetry by changing how infrastructure is designed, how Internet services are advertised, how regulators write transparency rules, and how government defines “broadband” in subsidy programs intended to reduce the digital divide. We also find significant increases in the use of many important categories of online content, including those used for work communications, education, grocery shopping, social media, news, and job searches. This shows the importance of the Internet during the crisis. Many people without Internet at home turned to public Wi-Fi hotspots during the pandemic. We find that this occurred disproportionately in neighborhoods with more students. Future distance learning initiatives should consider the challenges some students face in obtaining Internet access.

Limiting the spread of contagious diseases can involve both government-managed and voluntary efforts. Governments have a number of policy options beyond direct intervention that can shape individuals’ responses to a pandemic and its associated costs. During its first wave of COVID-19 cases, Singapore was among a few countries that attempted to adjust behavior through the announcement of detailed case information. Singapore’s Ministry of Health maintained and shared precise, daily information detailing local travel behavior and residences of COVID-19 cases. We use this policy along with device-level cellphone data to quantify how local and national COVID-19 case announcements trigger differential behavioral changes. We find evidence that individuals are three times more responsive to outbreaks in granularly defined locales. Conditional on keeping infection rates at a manageable level, the results suggest economic value in this type of transparency by mitigating the scope of precautionary activity reductions.

Paguyuban Selter L PKL Alun-alun Klaten merupakan kelompok pedagang yang berjualan di alun-alun Klaten. anggota paguyuban sebanyak 25 yang terdiri dari pedagang dengan beberapa jenis dagangan yang dijual, namun sebagian besar berdagang makanan. Pedagang berjualan dari pagi sampai malam dan tidak ada batasan waktu karena pedagang Selter L ini mempunyai lapak yang permanen sehingga sudah mempunyai ijin untuk berdagang di lapak tersebut. Paguyuban Selter L melakukan pertemuan setiap sebulan sekali yaitu di Minggu Pertama dan dilakukan pada malam hari. tujuan dari melakukan kegiatan Simpan Pinjam adalah agar anggota Paguyuban tidak meminjam uang atau terjerat oleh rentenir tapi akan meminjam dari tabungan para anggotanya. Namun kegiatan paguyuban ini belum terdokumentasi dengan baik khususnya dalam hal administrasi keuangannya, pencatatan hasil rapat, pengelolaan kas masih belum tertib sehingga perlu adanya pendampingan dan penyuluhan. Dengan permasalahan yang ada tujuan pengabdian yaitu mendampingi, memberikan penyuluhan dan masukan mengenai cara pencatatan, pelaporan dan transparasi dalam menyampaikan laporan keuangan paguyuban. Metode yang digunakan dalam pengabdian ini dengan penyuluhan, pendampingan dan monitoring. Hasil dari pengabdian ini adalah pencatatan dan pendokumentasian laporan keuangan menjadi lebih tertata, tertip dan mudah dipahami serta yang terpenting adanya transparansi laporan kepada semua anggota Paguyubab Selter L PKL Alun-alun Klaten dan simpanan anggota semakin banyak dan berkembang.

Purpose Program evaluation stands as an evidence-based process that would allow institutions to document and improve the quality of graduate programs and determine how to respond to growing calls for aligning training models to economic realities. This paper aims to present the current state of evaluation in research-based doctoral programs in STEM fields. Design/methodology/approach To highlight the recent evaluative processes, the authors restricted the initial literature search to papers published in English between 2008 and 2019. As the authors were motivated by the shift at NIH, this review focuses on STEM programs, though papers on broader evaluation efforts were included as long as STEM-specific results could be identified. In total, 137 papers were included in the final review. Findings Only nine papers presented an evaluation of a full program. Instead, papers focused on evaluating individual components of a graduate program, testing small interventions or examining existing national data sets. The review did not find any documents that focused on the continual monitoring of training quality. Originality/value This review can serve as a resource, encourage transparency and provide motivation for faculty and administrators to gather and use assessment data to improve training models. By understanding how existing evaluations are conducted and implemented, administrators can apply evidence-based methodologies to ensure the highest quality training to best prepare students.

PurposeIn this viewpoint article, the authors consider the challenges in implementing restrictive policies, with a particular focus on how these policies are experienced, in practice, from alternative standpoints.Design/methodology/approachThe authors draw on social science studies of decommissioning work to highlight how patient and official versions of value often vary, creating difficulties and distrust as restrictive policies are implemented. Patients and the public are well aware that financial calculations are somehow embedded in concepts of “evidence” and “value” but are usually unfamiliar with the social infrastructures that produce and utilise such concepts. The authors discuss with reference to a contemporary restrictive programme in England.FindingsWhile policymakers and researchers frequently present restrictive policies as “win-win” scenarios (achieving both cost-savings for healthcare services and improved patient care), social science analyses highlight the potential for tensions and controversies between stakeholders. The authors recognise that cost containment is a necessary component of policymaking work but argue that policymakers and researchers should seek to map (and make visible) the socially organised reasoning, systems and processes that are involved in enacting restrictive policies. Although transparency may pose challenges, it is important for informed democratic engagement, allowing legitimate scrutiny of whose voices are being heard and interests served (the “winners” and “losers”).Originality/valueThe authors argue for social science analyses that explore overuse, value and restrictive practices from alternative (e.g. patient) standpoints. These can provide important insights to help identify priorities for intervention and support better communication.

It is often maintained that there is no one consistent mass media policy in Lithuania. There are, indeed, many mechanisms of state financial aid and support, and the allocation of funds itself is rather inconsistent and accidental. There is no data or information available as to how the strengths and weaknesses of the particular mechanisms created and aid/funding opportunities available are perceived by the target audience of such efforts – the staff of the editorial boards of the news outlets and the particular business owners. Having conducted a questionaire-based study and a series of in-depth structured interviews with selected typical representatives from the industry, here we delineate the perception: the editorial staff maintain that the most impactful mechanism of allocating state support for the press are direct payments, especially those distributed by the Lithuanian Media Support Foundation, though the principles regulating its decision-making should be amended so as to allow for more transparency. One should also ensure that whatever is being funded has a case for continuity, sustainability and long-term future in regard to its activities. Additionally, especially inasmuch as any allocation of funds is related to an attempt to ensure the long-term success of democratic governance, the funding is to be targeted at local news rather than national or international news. These findings are shown to be comparable to tendencies observed abroad.

Purpose Smart manufacturing is the prime gripper for the transformation and upgrading of the manufacturing industry. Smart manufacturing systems (SMSs) largely determine how smart manufacturing evolves in technical and organizational dimensions and how it realizes values in products, production or services. SMSs are growing rapidly and receiving tons of attention from academic research and industrial practice. However, the development of SMSs is still in its fancy, and many issues wait to be identified and solved, such as single point failures, low transparency and ineffective resource sharing. Blockchain, an emerging technology deriving from Bitcoin, is competent to aid SMSs to conquer troubles due to its decentralization, traceability, trackability, disintermediation, auditability and etc. The purpose of this paper is to investigate the blockchain applications in SMSs, seek out the challenges faced by blockchain-enabled SMSs (BSMSs) and provide referable research directions and ideas. Design/methodology/approach A comprehensive literature review as a survey is conducted in this paper. The survey starts by introducing blockchain concepts, followed by the descriptions of a literature review method and the blockchain applications throughout the product life cycle in SMSs. Then, the key issues and challenges confronting BSMSs are discussed and some possible research directions are also proposed. It finally presents qualitative and quantitative descriptions of BSMSs, along with some conclusions and implications. Findings The findings of this paper present a deep understanding about the current status and challenges of blockchain adoption in SMSs. Furthermore, this paper provides a brand new thinking for future research. Originality/value This paper minutely analyzes the impacts that blockchain exerts on SMSs in view of the product life cycle, and proposes using the complexity science thinking to deal with BSMSs qualitatively and quantitatively, including tackling the current major problems BSMSs face. This research can serve as a foundation for future theoretical studies and enterprise practice.

Smart Farming with technologies such as IoT, computer vision, and AI can improve agricultural efficiency, transparency, profitability, and equity for farmers in low-and middle-income countries.

Internet connects people to people, people to machine, and machine to machine for a life of serendipity through a Cloud. Internet of Things networks objects or people and integrates them with software to collect and exchange data. The Internet of things (IoT) influences our lives based on how we ruminate, respond, and anticipate. IoT 2021 heralds from the fringes to the data ecosystem and panaches a comfort zone. IoT is overwhelmingly embraced by businessmen and consumers due to increased productivity and convenience. Internet of Things facilitates intelligent device control with cloud vendors like Amazon and Google using artificial intelligence for data analytics, and with digital assistants like Alexa and Siri providing a voice user interface. Smart IoT is all about duplex connecting, processing, and implementing. Centralized IoT architecture is vulnerable to cyber-attacks. With Block Chain, it is possible to maintain transparency and security of the transaction's data. Robotic Process Automation (RPA) using bots has automated laborious tasks in 2019. Embedded Internet using Facial Recognition could reduce the coronavirus pandemic crisis by making a paradigm shift from fingerprint sensors to facial recognition. Security concerns are addressed with micro-segmentation approaches. IoT, an incredible vision of the future makes systems adaptive with customized features, responsive with increased efficiency, and procurable with optimized cost. This research delivers a comprehensive insight into the technical perspectives of IoT, focusing on interoperability, flexibility, scalability, mobility, security, transparency, standardization, and low energy. A smart classroom is implemented based on the concepts of IoT.

Thanks to the exponential growth in computing power and vast amounts of data, artificial intelligence (AI) has witnessed remarkable developments in recent years, enabling it to be ubiquitously adopted in our daily lives. Even though AI-powered systems have brought competitive advantages, the black-box nature makes them lack transparency and prevents them from explaining their decisions. This issue has motivated the introduction of explainable artificial intelligence (XAI), which promotes AI algorithms that can show their internal process and explain how they made decisions. The number of XAI research has increased significantly in recent years, but there lacks a unified and comprehensive review of the latest XAI progress. This review aims to bridge the gap by discovering the critical perspectives of the rapidly growing body of research associated with XAI. After offering the readers a solid XAI background, we analyze and review various XAI methods, which are grouped into (i) pre-modeling explainability, (ii) interpretable model, and (iii) post-modeling explainability. We also pay attention to the current methods that dedicate to interpret and analyze deep learning methods. In addition, we systematically discuss various XAI challenges, such as the trade-off between the performance and the explainability, evaluation methods, security, and policy. Finally, we show the standard approaches that are leveraged to deal with the mentioned challenges.

Lobbying is regulated at European level by permissive legal provisions but, at the same time, disparate or lacking in legislative and application coherence. The state of the European decision-making process reveals the need to bring about changes that require more rigorous, applied and, why not, severe regulation of lobbying and interest representation.

The digital village is a community empowerment program through the use of digital technology and the internet in developing village potential, marketing and accelerating access and information services. The Sundutan Tigo Village Office is a government agency, having its address at Sundutan Tigo Village, Natal District, Mandailing Natal Regency. The Village Office has the receipt and disbursement of funds. Based on the results of the pre-survey at the research location, there are still many people who do not know how much the village fund budget is realized by their village government per year. In fact, in this case the main purpose of rolling out village funds is other than for rural development, the most important thing is how the village government empowers village communities, so that they can support national development through work carried out in villages both from an economic and other perspective. etc. For this reason, a computerized information system is needed, which is able to overcome the obstacles and problems that exist in the transparency of the village fund management.

It has been widely acknowledged that female workers account for 80% of the Ready Made Garments (RMG) industry’s workforce in Bangladesh but a number of studies estimated different male to female workers’ ratios ranging from 35: 65 to 55:45. To contribute to such debate, this paper leverage the data of the ‘Mapped in Bangladesh’ (MiB) project. While the objective of the MiB project is to enable transparency and accountability in the RMG sector by providing the industry stakeholders accurate, updated and authentic factory data collected through the factory census method and published in a digital map; this paper aims to shed light on the male to female ratio of workers employed in the RMG factories of Bangladesh is not 20:80, but it is 42:58 according to the findings from MiB data. Presenting such data, the study seeks to discuss how factory issues can influence the gender composition of RMG Workers. These issues such as factory locations, factory type, factory size and production sections are important to understand the challenges of future research addressing the gender composition of RMG workers in Bangladesh.

The exploration of new nonlinear optical (NLO) materials which can realize the balance between deep-ultraviolet (UV) transparency and large NLO response is still urgently needed owing to their abil...