Operator Actions Research Articles

A Qualitative Study Evaluating the Challenges of Orthopedists and Internists in the Earthquake Zone

Abstract Background The earthquake centered in Kahramanmaras province, Turkey, on February 6, 2023, with a magnitude of 7.7, resulted in the loss of 53,537 lives and the injury of 107,213 people. This study was conducted to evaluate the challenges and experiences of physicians who provided post-disaster medical care. Methods We conducted a qualitative study with orthopedists and internists who had worked in the earthquake zone using in-depth interviews. Participants were selected through snowball sampling. Interviews explored challenges in the disaster zone, obstacles related to healthcare services, and disaster management. Thematic analysis was used. Results A total of 13 physicians participated in the study. Data revealed four main themes: disaster management, organizational deficiencies, challenges faced, and logistical issues. Participants indicated that the Ministry of Health didn’t have a priori operational emergency action plan, which led to problems in healthcare service delivery. Some physicians complained that they had to serve just as emergency consultants and were not able to carry out tasks compatible with their expertise. Some indicated that they organized the services rather than providing medical care. Almost all encountered a variety of interesting cases and evaluated their experience as significant. Logistical needs were met mostly with the support of non-governmental organizations. Conclusions We need to have a priori operational emergency action plan to ensure the effective delivery of healthcare services in the aftermath of a disaster. The Ministry of Health needs to allocate and coordinate healthcare personnel in line with their areas of expertise and prevent service disruptions. Key messages • There is a need to make an operational emergency action plan beforehand to deliver healthcare services effectively following a disaster. • Physicians should be allocated in line with their specialty of expertise to efficiently address the healthcare needs.

Revolutionizing Ocean Cleanup: A Portuguese Case Study with Unmanned Vehicles Fighting Spills

It is of the utmost importance for every country to monitor and control maritime pollution within its exclusive economic zone (EEZ). The European Maritime Safety Agency (EMSA) has developed and implemented the CleanSeaNet (CSN) satellite monitoring system to aid in the surveillance and control of hydrocarbon and hazardous substance spills in the ocean. This system’s primary objective is to alert European Union (EU) coastal states to potential spills within their EEZs, enabling them to take the necessary legal and operational actions. To reduce operational costs and increase response capability, the feasibility of implementing a national network (NN) of unmanned vehicles (UVs), both surface and aerial, was explored using a Portuguese case study. The following approach and analysis can be easily generalized to other case studies, bringing essential knowledge to the field. Analyzing oil spill alert events in the Portuguese EEZ between 2017 and 2021 and performing a strengths, weaknesses, opportunities, and threats (SWOT) analysis, essential information has been proposed for the optimal location of an NN of UVs. The study results demonstrate that integrating spill alerts at sea with UVs may significantly improve response time, costs, and personnel involvement, making maritime pollution combat actions more effective.

Generalized boson and fermion operators with a maximal total occupation property

Abstract We propose a new generalization of the standard (anti-)commutation relations for creation and annihilation operators of bosons and fermions. These relations preserve the usual symmetry properties of bosons and fermions. Only the standard (anti-)commutator relation involving one creation and one annihilation operator is deformed by introducing fractional coefficients, containing a positive integer parameter p. The Fock space is determined by the classical definition. The new relations are chosen in such a way that the total occupation number in the system has the maximum value p. From the actions of creation and annihilation operators in the Fock space, a group theoretical framework is determined, and from here the correspondence with known particle statistics is established.

Quantification of delamination resistance data of FRP composites and its limits

Quantitative delamination resistance data of fibre-reinforced polymer-matrix (FRP) composites for quasi-static or cyclic fatigue loads are determined under different loading modes and load rates, respectively. Such data find use, e.g., in FRP materials’ development, materials’ selection, assessment of durability, or structural design. Round robins during test development yielded repeatability and reproducibility (coefficients of variation) of roughly 10 to 25%. This scatter has several different sources. Intrinsic material variability amounts to a few percent at best, at least for advanced manufacturing processes. This intrinsic scatter is essential for material comparisons and structural design. Measurement resolution specified in standardised test procedures yields a maximum of 4–5% variability. Most of the remaining scatter comes from other, extrinsic sources. Test operator actions, e.g., choice of test set-up, manual data acquisition or data analysis can yield extrinsic scatter. Damage mechanisms during delamination initiation and propagation act on the micro- and meso-scale, typically a few micrometer to a few hundred micrometer in size, with corresponding time-scales estimated to between a few tens of nanoseconds and a few microseconds. Defect size-scales are hence several orders of magnitudes lower than test specimen and structural scales, respectively. Predictive capability of models using such test data for structures are, therefore, limited. Major issues are up-scaling from straight beam-like specimens to larger shell-like structures, possibly with complex shape and varying thickness as well as from unidirectional fibre orientation to multidirectional lay-ups.

Cyclic mining of alarm and operator action events for enhanced process operation

This paper addresses the challenge of fault propagation in industrial facilities, where a fault in one process variable can lead to cascading faults in other variables. As a result, the propagation of alarms corresponding to these faulty variables occurs, leading operators to potentially receive an excessive number of alarm notifications that could significantly impact their decision-making capabilities. To address this issue, a systematic method is proposed to investigate potential fault propagation paths to provide decision support in response to alarm notifications, in order to minimize industrial process failures. The contributions of this paper are twofold. Firstly, it involves enhanced dependency analysis that captures dependent alarms and identifies both weak and strong dependencies among alarm variables using historical alarm and event (A&E) logs that are generated by industrial control systems. Secondly, it offers comprehensive visualization of fault propagation in response to single and multiple alarms, including extracting crucial timing information, identifying the shortest, longest, and critical paths, and determining effective operator actions. The proposed method is designed to enhance process operation and provide essential decision support for industrial operators. The effectiveness of the proposed approach is validated through a case study using real industrial data.

Active Control for Construction Stability of Suspension Arch Rib Segments Based on ARID System

In response to the issues of vibrations affecting the construction safety, speed, and accuracy of suspended structures due to dynamic disturbances during lifting, environmental disturbances, and improper operator actions, this paper investigates the application of the Active Rotary Inertia Driver (ARID) system for double-rope suspended structures, namely analyzes, and applies control to the vibration response of double-rope suspended structures under external excitations. Taking the double-rope suspended structure as an example, a dynamic analytical model of the double-rope suspended structure is established based on D’Alembert’s principle. Through shake table tests, the dynamic response characteristics and vibration control effects of the double-rope suspended structure under various external excitations are studied, and the influence of the twisting radius of the suspended structure on the control effect is analyzed. The experimental results show that the ARID control system achieves significant control effects on the swing and torsional vibrations of the suspended structure, which validates the accuracy of the theoretical model for the ARID control system and demonstrates its feasibility for practical applications.

Dynamic risk assessment of Uncertain Random System considering operator's simple emergency-stop action in short time window

Human-machine systems can be considered as typical Uncertain Random Systems (URS). In human-machine systems, operator's simple emergency-stop actions act as a vital soft barrier. Conventional Human Reliability Analyses face challenges in evaluating operator's simple emergency-stop action due to their static characteristics, incompatibility with short time windows, and problems posed by small samples. This paper provides a novel solution to risk assessment of human-machine systems involving operator's simple emergency-stop mechanism. Specifically, an evaluation method of operator's simple emergency-stop action is established, where human cognition is decomposed according to its temporal and logical dimensions, key indicators of human sub-cognition are evaluated, and uncertainty theory is used to integrate these indicators. The output of proposed method is uncertainty of operator's behavior (UOB), which can offer more information than traditional Human Error Probability (HEP) and can be readily converted into uncertainty of human error. Further, a precise simulation method for dynamic risk assessment of Uncertain Random Systems is developed, in which the integration of the UOB is achieved. A case study demonstrates the effectiveness of the proposed methods, and its results show that the proposed methods can clearly reflect the differences in system risk under short time window conditions that have minor distinctions.

Dynamic Seismic Probabilistic Risk Assessment of Nuclear Power Plants Using Advanced Structural Methodologies

The conditional core damage probability (CCDP) of a representative nuclear power plant is estimated for a beyond design basis earthquake (BDBE) using state-of-the-art structural models within a dynamic probabilistic risk assessment (DPRA) framework. Randomness of seismic excitation and uncertainty of structural parameters are considered using a simulation-based approach. Finite element models are developed for the structure and a liquid container (hydro-accumulator), and fluid–structure interaction is considered with the arbitrary Lagrangian-Eulerian method. The CCDP is evaluated through a time-dependent event tree. Also, correlation among multiple hydro-accumulators is investigated. The results show that operator action and implementation time of mobile safety equipment are critical under BDBE in case of loss of offsite power following an earthquake. It was also found necessary to adopt a DPRA approach to determine the available time for action and core damage timing probabilistically.

Linear and nonlinear time-series methodologies for bridge condition assessment: A literature review

Railway bridges are essential components of any transportation system and are typically subjected to several environmental and operational actions that can cause damage. Furthermore, they are not easily replaced, and their failure can have catastrophic consequences. Considering the expected lifespan of bridges, it is essential to guarantee their adequate serviceability and safety. In this scenario, emerges the Structural Health Monitoring (SHM), which allows the early identification of damage before it becomes critical. Damage identification is usually performed by the comparison between the damaged and undamaged responses obtained from monitoring data. Among the several features extracted from the responses, the time-series models exhibit a better performance, capability of early damage detection, and may also be applied within online damage detection strategies using unsupervised machine learning frameworks. In this paper, a review of advanced time-series methodologies for damage detection is presented. Initially, several time-series models often used in SHM are described, such as Autoregressive Models (AR), Recurrent Neural Networks (RNN), Gated Recurrent Unit (GRU), and Long Short-Term Memory (LSTM). Later, the framework where these models are usually applied is also detailed, including the latest upgrades and most relevant results. Finally, the conclusions summarize and elucidate the current perspectives and research gaps on the time-series models.

A Study on the Governance Model of Village Credit Bank in Rural Governance — Taking Youxiqiao Village as an Example

Rural governance is an important component of the modernization of the national governance system and governance capacity, and is a key link in achieving the strategy of rural revitalization. The paper takes Youxiqiao Village as an example and adopts a case analysis method to study the operational mechanism and action logic of the "Villager Credit Bank" governance model in rural governance. Research has shown that the governance model of "Village Credit Bank" has three major characteristics: standardized content, procedural process, and reward and punishment methods. It can play an important role in rural governance, including (1) stimulating the enthusiasm of villagers, (2) strengthening the role of grassroots organizations, (3) promoting the orderly implementation of village projects, and (4) enriching grassroots governance methods, which can provide reference for the governance of other villages.

ARTIFICIAL CRISES IN FINANCIAL MARKETS: PROBLEMS OF DIAGNOSIS AND PREVENTION

Purpose: The aim of this study is to diagnose and prevent crises in the country's financial markets by managing the connectedness of the attacked market with other. Theoretical Framework: Non-statistical changes in the largest connected markets and the parameters of the attacked market's connection with them. There is a need to consider ways to counter crises by managing the connection of the attacked market with other financial markets in the country. Design/Methodology/Approach: Methods for diagnosing crises are proposed to identify signs of a man-made crisis and strategies for its prevention. The proposed approach will prevent the actions of unscrupulous private financial market operators who want to receive unscrupulous income, stimulating volatility. Findings: Among the most important results, it was determined that there are serious shortcomings in the organization and structure of financial markets that require active government intervention. The state can not only legislative and administrative, but also financial methods prevent the actions of dishonest operators or minimize the consequences of the crises caused by them. Research, Practical & Social implications: This study makes it possible to identify signs of an artificial crisis and strategies for its prevention. Using the data of this study, the state operator in the financial markets can distribute its financial, administrative and informational resources in turn against its opponents and thus have a significant advantage over each of them. Originality/Value: The value of the study lies in the fact that various methods for diagnosing financial crises are offered by studying non-statistical changes in the largest connected markets and the parameters of the attacked market's connection with them. Using this information, the state can minimize the consequences of artificial financial crises.

Effectiveness of the Role of the Rokan Hulu Regency Transportation Service in Monitoring Illegal Travel in Pasir Pengaraian City

This research aims to find out how effective the role of the Rokan Hulu district transportation service is in monitoring illegal travel in the city of Pasir Pengaraian. This study used descriptive qualitative method. The indicators in this research are input, process, output and outcome. This research was conducted at the Rokan Hulu Regency transportation service. Collecting data obtained through interviews, observation, documentation. The author's technique for determining informants uses the snowball sampling method. The snowball sampling method is a technique for taking data sources, initially the number is small and then becomes larger, this is because the few data sources are not able to provide satisfactory data, so look for other informants to use as data sources. Based on the research results, it can be concluded that the effectiveness of the role of the Rokan Hulu Regency Transportation Service in monitoring illegal travel in Pasir Pengaraian City is still not effective and optimal because what happens in the field in the monitoring process is only monitoring actions in routine operations and raids, but these activities are still rare. done. The inhibiting factors or obstacles for the Rokan Hulu district transportation service are that they are still careless in terms of supervision, lack of certainty and schedule in carrying out supervision, limited budget, lack of level of public awareness, and still difficulty for transport drivers in processing permits..

Demonstration for cold atmospheric pressure plasma jet operation and antibacterial action in microgravity

Cold atmospheric pressure plasma (ionized gas) is an innovative medical tool for the treatment of infected wounds thanks to its potential to inactivate drug-resistant microorganisms and promote tissue regeneration and vascularization. The low power consumption, compactness, and versatility of Cold Atmospheric Pressure Plasma (CAPP) devices make them an ideal tool for risk mitigation associated with human spaceflights. This work presents results in microgravity on the operability of CAPP and its antimicrobial effect. The experiments carried out in parabolic flights make it possible to optimize the treatment conditions (i.e., the distance, the gas mixture) and to obtain the rapid inactivation (<15 s) of Escherichia coli samples. Interestingly, the inactivation efficiency of CAPP was higher during parabolic flights than under terrestrial conditions. Overall, these results encourage the further development of CAPP medical devices for its implementation during human spaceflights.

Reinforcement Learning-Based Control Sequence Optimization for Advanced Reactors

The last decade has seen the development and application of data-driven methods taking off in nuclear engineering research, aiming to improve the safety and reliability of nuclear power. This work focuses on developing a reinforcement learning-based control sequence optimization framework for advanced nuclear systems, which not only aims to enhance flexible operations, promoting the economics of advanced nuclear technology, but also prioritizing safety during normal operation. At its core, the framework allows the sequence of operational actions to be learned and optimized by an agent to facilitate smooth transitions between the modes of operations (i.e., load-following), while ensuring that all safety significant system parameters remain within their respective limits. To generate dynamic system responses, facilitate control strategy development, and demonstrate the effectiveness of the framework, a simulation environment of a pebble-bed high-temperature gas-cooled reactor was utilized. The soft actor-critic algorithm was adopted to train a reinforcement learning agent, which can generate control sequences to maneuver plant power output in the range between 100% and 50% of the nameplate power through sufficient training. It was shown in the performance validation that the agent successfully generated control actions that maintained electrical output within a tight tolerance of 0.5% from the demand while satisfying all safety constraints. During the mode transition, the agent can maintain the reactor outlet temperature within ±1.5 °C and steam pressure within 0.1 MPa of their setpoints, respectively, by dynamically adjusting control rod positions, control valve openings, and pump speeds. The results demonstrate the effectiveness of the optimization framework and the feasibility of reinforcement learning in designing control strategies for advanced reactor systems.

Trust in automation and the accuracy of human–algorithm teams performing one-to-one face matching tasks

The human face is commonly used for identity verification. While this task was once exclusively performed by humans, technological advancements have seen automated facial recognition systems (AFRS) integrated into many identification scenarios. Although many state-of-the-art AFRS are exceptionally accurate, they often require human oversight or involvement, such that a human operator actions the final decision. Previously, we have shown that on average, humans assisted by a simulated AFRS (sAFRS) failed to reach the level of accuracy achieved by the same sAFRS alone, due to overturning the system’s correct decisions and/or failing to correct sAFRS errors. The aim of the current study was to investigate whether participants’ trust in automation was related to their performance on a one-to-one face matching task when assisted by a sAFRS. Participants (n = 160) completed a standard face matching task in two phases: an unassisted baseline phase, and an assisted phase where they were shown the identification decision (95% accurate) made by a sAFRS prior to submitting their own decision. While most participants improved with sAFRS assistance, those with greater relative trust in automation achieved larger gains in performance. However, the average aided performance of participants still failed to reach that of the sAFRS alone, regardless of trust status. Nonetheless, further analysis revealed a small sample of participants who achieved 100% accuracy when aided by the sAFRS. Our results speak to the importance of considering individual differences when selecting employees for roles requiring human–algorithm interaction, including identity verification tasks that incorporate facial recognition technologies.

Concepts of Unification and Cooperation between the Autonomous Region of Krajina and the Serbian Autonomous District of Krajina in 1991 and 1992

The authors of this paper analyze the relationship between the two regions from their unilateral declarations until the second half of 1992. The Serbian Autonomous Region of Krajina (later the Republic of Serbian Krajina) in Croatia and the Autonomous Region of Krajina (ARK) in the northwestern part of Bosnia and Herzegovina were the first, as formal-legal successors of municipal communities, to be unilaterally formed autonomous regions based on ethnic principles in the process of the dissolution of Yugoslavia. Both were proclaimed by unilateral decisions of the republican organizations of the Serbian Democratic Party (SDS) both in Croatia and in Bosnia and Herzegovina before Slovenia and Croatia declared independence. Immediately after these declarations, politicians from both Krajinas analyzed and publicly presented their views on the future status of the newly formed regions. One of the options was the unification of these two regions into one administrative unit or state, with the most prominent advocates being the leading politicians from both regions. In order to justify the formation of such an administrative unit, reports were published on the necessity of its formation as a separate entity within the “fragmented Yugoslavia” or Greater Serbian state. However, the question arose of how much such unification would diminish the influence of SDS political leaders from Bosnia and Herzegovina and who would actually be the new national leader among the Serbs west of the Drina River? This question, as it turned out, burdened the entire relationship between the political and military leadership in both the Republic of Srpska (RS) and the Republic of Serbian Krajina (RSK) in various phases of the dissolution of Yugoslavia. Despite disagreements and different positions on the unification of the two Krajinas and the question of their status, political and military cooperation was unquestionable in the first two years of aggression against the Republic of Croatia and the Republic of Bosnia and Herzegovina. Cooperation was particularly intense in the second half of 1992 when the 1st and 2nd Krajina Corps of the Army of the Serbian Republic of Bosnia and Herzegovina/Army of the Republic of Srpska, in cooperation with the police structures of the RSK and the Serbian Army of Krajina (SAK), were jointly tasked with implementing the Six Strategic Goals of the Serbian Republic of Bosnia and Herzegovina/Republic of Srpska. This cooperation was particularly evident in the “battle for establishing the corridor” between Krajina and Semberija as the Second Strategic Goal, or joint action in Operation “Corridor '92”. In this paper, we will analyze the period from the end of 1990 and the first half of 1991 when the unilateral declarations of the Serbian Autonomous Region of Krajina and the Community of Municipalities of Bosnian Krajina (ZOBK), later ARK, occurred, until September 1992 when the decision was made to cease the existence of autonomous regions in the RS. This is the period when mass atrocities were committed against Bosniak and Croatian civilian populations in the RSK and RS. In the second half of 1991, the Bosnian Krajina was a direct war zone from which units of the Yugoslav People's Army (JNA) carried out aggressive operations against Croatia, and in 1992, it became a symbol of crimes against civilians in Bosnia and Herzegovina. Areas under Serbian control became “ethnically cleansed”, and Bihać, as a city under continuous military action from the RS and RSK military forces, became one of the symbols of the siege. The question arises as to whether the strategic goals of the RS could have been realized if the two Krajinas had not closely cooperated? This is precisely one of the questions we will answer. In order to answer such and similar questions, an analysis of the role of military and police structures of both regions is necessary, both in crimes and in military operations in the Bihać region.

Конфискация имущества как мера противодействия незаконному обороту наркотических средств, психотропных веществ или их аналогов

Financial University under the Government of the Russian Federation, LL.D., Professor, Honored Lawyer of the Russian Federation Purpose: to consider the institution of confiscation of property as another measure of a criminal law nature, and to show the practice of using this criminal law institution in cases of illegal trafficking of narcotic drugs, psychotropic substances or their analogues. Research methods: comparative legal, dogmatic, analysis of judicial practice. Conclusions: based on the analysis of the provisions of Chapter 15.1 of the Criminal Code of the Russian Federation and Article 81 of the Criminal Procedure Code of the Russian Federation, it is shown that the legal basis for confiscation of property in cases of illicit trafficking in narcotic, psychotropic substances or their analogues is interdisciplinary in nature. It is noted that if the property has the properties specified in paragraphs “a”-“d” of Article 104.1 of the Criminal Code of the Russian Federation, the court is obliged to make a decision on the confiscation of such property. When planning opera-tional search activities and investigative actions, it is necessary to pay special attention to providing evidence of the connection of the property subject to confiscation with a specific crime. Scientific and practical significance: the legal nature of confiscation of property as another measure of a criminal nature is revealed, its place in the system of similar institutions is indicated, the specifics of the implementation of the provisions of Chapter 15.1 of the Criminal Code are indicated by the example of court decisions on specific cases. Disputes about the ownership of confiscated property to persons not involved in crimes may be resolved at the stage of execution of a court verdict, including in court.

Econometric Analysis of the Influence of Factors on the Share of Energy From Renewable Sources in the EU

The use of renewable energy is at the core of EU energy policy, reducing dependence on fossil fuels imported from non-EU countries, reducing greenhouse gas emissions and decoupling energy costs from oil prices. Currently, 22.5% of energy consumed in the EU comes from renewable sources. This increase over 2021 is due to strong growth in solar energy. This share is also increasing due to the consumption of non-renewable energy sources in 2022. According to expert forecasts, the share of renewable energy sources in Europe will continue to grow. Achieving the 42.5% target by 2030 will require a deep transformation of the European energy system. The very strong climate and energy policies pursued in the EU for about a dozen years and aimed at limiting emissions of harmful substances into the environment have led to a gradual abandonment of traditional energy sources. Increasing demand for energy while reducing its supply from traditional sources means that in order not to make the economy too dependent on energy imports, the dynamic development of renewable energy is necessary. The EU is therefore taking very extensive operational and strategic actions to use other sources for production, such as wind, solar energy, mechanical water energy, biomass and geothermal energy, as well as tidal waves, ocean heat, wave energy and sea currents. In this study, we assess the impact of energy, economic and environmental factors on the share of renewable energy in the EU. The aim of these studies was to identify the energy, economic and environmental indicators that have the greatest impact on the share of energy from renewable sources in the European Union. The study was conducted using the Statgraphics Centurion software package. The source data for the study was data from the official Eurostat website for the period from 2012 to 2022. The results of this study show that changes in gross domestic product in market prices per capita have a positive impact, as do changes in greenhouse gas emissions per capita negatively affect the share of energy from renewable sources in the EU in the period 2012-2022. This may most likely be due to the fact that EU countries are more likely to invest in renewable energy as they can afford to invest in the development of expensive renewable energy technologies and support subsidies for the promotion and regulation of renewable energy. The negative impact of per capita greenhouse gas emissions on renewable energy development is due to the high share of coal in the EU energy mix, meaning that coal not only has negative environmental impacts, but also negative environmental impacts. development of renewable energy.

Fast hardware-aware matrix-free algorithms for higher-order finite-element discretized matrix multivector products on distributed systems

Recent hardware-aware matrix-free algorithms for higher-order finite-element (FE) discretized matrix-vector multiplications reduce floating point operations and data access costs compared to traditional sparse matrix approaches. In this work, we address a critical gap in existing matrix-free implementations which are not well suited for the action of FE discretized matrices on very large number of vectors. In particular, we propose efficient matrix-free algorithms for evaluating FE discretized matrix-multivector products on both multi-node CPU and GPU architectures. To this end, we employ batched evaluation strategies, with the batchsize tailored to underlying hardware architectures, leading to better data locality and enabling further parallelization. On CPUs, we utilize even-odd decomposition, SIMD vectorization, and overlapping computation and communication strategies. On GPUs, we develop strategies to overlap compute with data movement for achieving efficient pipelining and reduced data accesses through the use of GPU-shared memory, constant memory and kernel fusion. Our implementation outperforms the baselines for Helmholtz operator action on 1024 vectors, achieving up to 1.4x improvement on one CPU node and up to 2.8x on one GPU node, while reaching up to 4.4x and 1.5x improvement on multiple nodes for CPUs (3072 cores) and GPUs (24 GPUs), respectively. We further benchmark the performance of the proposed implementation for solving a model eigenvalue problem for 1024 smallest eigenvalue-eigenvector pairs by employing the Chebyshev Filtered Subspace Iteration method, achieving up to 1.5x improvement on one CPU node and up to 2.2x on one GPU node while reaching up to 3.0x and 1.4x improvement on multi-node CPUs (3072 cores) and GPUs (24 GPUs), respectively.

A review of natural resource extraction industries and their influence on the occurrence of poverty

PurposeThis research paper takes a narrow approach to examining the apparent link between poverty and the resource extraction industries. However, it acknowledges that much more is to be explored about this relationship. Many complexities influence the occurrence and degree of poverty in a particular country, region, or community.Design/methodology/approachThe literature review identified proposed and operational poverty reduction actions and processes categorized under the broad concept of community development projects. The surveyed cases describe how various corporate strategies, work processes, labor requirements and efficient management and governance solutions are purported to improve poverty-reduction efforts potentially.FindingsNo causal linkages between poverty and hypothetically valuable and successful community development projects were found. No poverty monitoring evaluations and learning data (MEL) for these projects were proposed and published in most of the literature. However, associations were observed between some business practices implemented in these resource extraction community development projects and observations of indicators of lower poverty levels.Practical implicationsThe research improves our understanding of the requirements and opportunities for successful community development projects by highlighting processes, company strategy, human resource programs and enlightened governance that can contribute to reducing poverty.Originality/valueThe paper identifies the characteristics of community development projects that appear to span natural resource extraction industries and countries. Effective management strategies and representative and formally designated organisational governance boards are essential for these projects.