Global Cost Research Articles

Scientific sinkhole: estimating the cost of peer review based on survey data with snowball sampling

BackgroundThere are a variety of costs associated with publication of scientific findings. The purpose of this work was to estimate the cost of peer review in scientific publishing per reviewer, per year and for the entire scientific community.MethodsInternet-based self-report, cross-sectional survey, live between June 28, 2021 and August 2, 2021 was used. Participants were recruited via snowball sampling. No restrictions were placed on geographic location or field of study. Respondents who were asked to act as a peer-reviewer for at least one manuscript submitted to a scientific journal in 2020 were eligible. The primary outcome measure was the cost of peer review per person, per year (calculated as wage-cost x number of initial reviews and number of re-reviews per year). The secondary outcome was the cost of peer review globally (calculated as the number of peer-reviewed papers in Scopus x median wage-cost of initial review and re-review).ResultsA total of 354 participants completed at least one question of the survey, and information necessary to calculate the cost of peer-review was available for 308 participants from 33 countries (44% from Canada). The cost of peer review was estimated at $US1,272 per person, per year ($US1,015 for initial review and $US256 for re-review), or US$1.1–1.7 billion for the scientific community per year. The global cost of peer-review was estimated at US$6 billion in 2020 when relying on the Dimensions database and taking into account reviewed-but-rejected manuscripts.ConclusionsPeer review represents an important financial piece of scientific publishing. Our results may not represent all countries or fields of study, but are consistent with previous estimates and provide additional context from peer reviewers themselves. Researchers and scientists have long provided peer review as a contribution to the scientific community. Recognizing the importance of peer-review, institutions should acknowledge these costs in job descriptions, performance measurement, promotion packages, and funding applications. Journals should develop methods to compensate reviewers for their time and improve transparency while maintaining the integrity of the peer-review process.

A Dynamic Grid Index for CkNN Queries on Large-Scale Road Networks with Moving Objects

As the Internet of Things devices are deployed on a large scale, location-based services are being increasingly utilized. Among these services, kNN (k-nearest neighbor) queries based on road network constraints have gained importance. This study focuses on the CkNN (continuous k-nearest neighbor) queries for non-uniformly distributed moving objects with large-scale dynamic road network constraints, where CkNN objects are continuously and periodically queried based on their motion evolution. The present CkNN high-concurrency query under the constraints of a super-large road network faces problems, such as high computational cost and low query efficiency. The aim of this study is to ensure high concurrency nearest neighbor query requests while shortening the query response time and reducing global computation costs. To address this issue, we propose the DVTG-Index (Dynamic V-Tree Double-Layer Grid Index), which intelligently adjusts the index granularity by continuously merging and splitting subgraphs as the objects move, thereby filtering unnecessary vertices. Based on DVTG-Index, we further propose the DVTG-CkNN algorithm to calculate the initial kNN query and utilize the existing results to speed up the CkNN query. Finally, extensive experiments on real road networks confirm the superior performance of our proposed method, which has significant practical applications in large-scale dynamic road network constraints with non-uniformly distributed moving objects.

The Development of a Low-Cost Hydrophone for Passive Acoustic Monitoring of Dolphin’s Vocalizations

Passive acoustics are widely used to monitor the presence of dolphins in the marine environment. This study aims to introduce a low-cost and homemade approach for assembling a complete underwater microphone (i.e., the hydrophone), employing cheap and easy to obtain components. The hydrophone was assembled with two piezo disks connected in a balanced configuration and encased in a plastic container filled with plastic foam. The hydrophone’s performance was validated by direct comparison with the commercially available AS-1 hydrophone (Aquarian Hydrophones, Anacortes, U.S.) on different underwater acoustic signals: artificial acoustic signals (ramp and multitone signals) and various dolphin vocalizations (whistle, echolocation clicks, and burst pulse signals). The sensitivity of the device’s performance to changes in the emission source position was also tested. The results of the validation procedure on both artificial signals and real dolphin vocalizations showed that the significant cost savings associated with cheap technology had a minimal effect on the recording device’s performance within the frequency range of 0–35 kHz. At this stage of experimentation, the global cost of the hydrophone could be estimated at a few euros, making it extremely price competitive when compared to more expensive commercially available models. In the future, this effective and low-cost technology would allow for continuous monitoring of the presence of free-ranging dolphins, significantly lowering the total cost of autonomous monitoring systems. This would permit broadening the monitored areas and creating a network of recorders, thus improving the acquisition of data.

Efecto de la inactivación de las órdenes múltiples para solicitud de estudios complementarios en una central de emergencias

Introducción. La plantilla de órdenes múltiples es una herramienta informática que podría producir consecuencias inadvertidas pese a sus innumerables beneficios. Nos propusimos explorar el efecto de su inactivación sobre las solicitudes de estudios complementarios y los costos asociados. Métodos. Corte transversal en la Central de Emergencias de Adultos del Hospital Italiano de Buenos Aires, que incluyó muestra consecutiva de consultas pre-intervención (Enero-Febrero 2020) y post-intervención (2021). Mediante el uso de bases secundarias, las variables incluidas fueron los débitos administrativos y sus respectivos precios de facturación. Resultados. Hubo 27.671 consultas en 2020 con una mediana de valor total de 474$, y 20.819 con 1.639$ en 2021. Tras el análisis restringido al área de consultorios de moderada complejidad (excluyendo consultas por COVID-19), se encontró: una disminución en la mediana del número de prácticas por consulta (mediana de 11 vs 10, p=0,001), una disminución en la solicitud de al menos una práctica de laboratorio (45% versus 39%, p=0,001), sin encontrar cambios significativos en costos globales (mediana 1.419$ vs 1.081$; p=0,122) ni en costos específicos de laboratorio (mediana 1.071$ vs 1.089$, p=0,710). Conclusión. Pese a la inflación interanual, se logró una reducción significativa en el número de prácticas y se mantuvieron los costos globales por consulta. Estos hallazgos demuestran la efectividad de la intervención, pero serán necesarias medidas educativas que apunten al recordatorio de los potenciales daños en la sobreutilización, y los costos sanitarios de los estudios innecesarios.

Broadening the circle: creativity, regeneration and redistribution in value loops

PurposeIncreasing industrial agriculture and economic crisis has generated creative responses in pursuit of responsible solutions to the human and environmental cost of globalization by applying these models to promote social responsibility, help sustain livelihoods and foster biodiversity. A key issue concerns how responsible and circular businesses might provide appropriate responses to large-scale “wicked” problems. This paper aims to ask what such creativity looks like in the context of a circular economy that attempts to build closed value loops, by examining a case from the organic cotton textile industry: Appachi Eco-Logic.Design/methodology/approachThis study uses an ethnographic extended-case approach to identify two phases of creative growth at Appachi Eco-Logic, examining how closing the value loop and creating circularity involved broadening the circle to include more and more actors.FindingsThis study identifies two major challenges to achieving and maintaining full circularity before concluding with a broad provocation for the study of circular economies.Originality/valueThe case offers insight into fundamental features of circularity, regeneration and redistribution, which can be used by managers to build responsible and sustainable closed value loops.

The carbon border adjustment mechanism is inefficient in addressing carbon leakage and results in unfair welfare losses

The European Commission has proposed a Carbon Border Adjustment Mechanism (CBAM) to reduce carbon leakage and create a level playing field for its domestic products and imported goods. Nevertheless, the effectiveness of the proposal remains unclear, especially when it triggers threats of retaliation from trading partners of the European Union. We apply a Computable General Equilibrium model - Global Trade Analysis Project - to assess the economic and environmental impacts of different CBAM schemes. Here we show that the effectiveness of the CBAM to address carbon leakage risks is rather limited, and the CBAM raises concerns over global welfare costs, Correct to Gross Domestic Product (GDP) losses, and violation of equality principles. Trade retaliation leads to multiplied welfare losses, which would mostly be borne by poor countries. Our results question the carbon leakage reduction effect of a unilateral trade policy and suggest that climate change mitigation still needs to be performed within the framework of international cooperation.

Evaluation of a Soft Sensor Concept for Indirect Flow Rate Estimation in Solenoid-Operated Spool Valves

Concepts, such as power and condition monitoring or smart systems, are becoming increasingly important but require extensive insight into the process or machine, which is mostly gained by additional sensors. However, this development is contrasted by growing global competition and cost pressure. The measurement concept of a soft flow rate sensor presented here, addresses this discrepancy by means of a cost-effective software-based sensor, utilizing the dependence between flow rate and flow force in hydraulic spool valves. In the presented work, the feasibility of the introduced approach and the anticipated challenges, such as the modeling of disturbances in the mechanical, fluidic and electromagnetic subdomain, are assessed. For this purpose, important phenomena influencing measurement accuracy are identified on the basis of previous work. With the help of these findings, a greatly simplified version of the soft sensor is built and evaluated with a commercial valve to perform an initial test of the concept. Regardless of future implementations, the soft sensor concept presented here may have limitations in terms of dynamics and accuracy. However, the aim is not to replace a classic flow rate sensor, such as a gear sensor, but rather to create a cost-effective way to determine the flow rate without any additional integration effort.

Food Proteins: Potential Resources

According to the FAO and WHO, half of the world’s population (nearly eight billion people) is protein deficient. Protein deficiency is the most important nutritional problem in the world. Proteins can be animal- (meat and offal, fish, milk, eggs) or plant- (cereals, legumes, oilseeds) based, microbiologically synthesized (from yeast and a variety of bacteria), and synthetic or artificial (produced after amino acid synthesis). Animal proteins are the most expensive. The systematic incorporation of alternative proteins in the human diet is becoming increasingly urgent as global meat costs rise. Legumes, cereals, seeds, and nuts can all provide protein to the human body. Microalgae are considered to be an excellent source of functional and biologically active nutrients for human nutritional needs. Arthrospira platensis and Chlorella vulgaris are the most popular microalgae on the global market today, both of which are marketed as standalone functional foods containing proteins, vitamins, and minerals. Insects, as a source of dietary protein, differ in protein content from 20 to 75%. Investments in plant-based meat companies exceeded $350 million in 2020. The FAO predicts that the market for edible insects will reach $1.2 billion by 2023. All of these alternative protein sources are becoming more popular in the modern food industry for the production of high-protein foods and dietary supplements. This review aims to be a state-of-the-art study of new and potential sources of dietary proteins.

Economic costs of invasive rodents worldwide: the tip of the iceberg.

Rodents are among the most notorious invasive alien species worldwide. These invaders have substantially impacted native ecosystems, food production and storage, local infrastructures, human health and well-being. However, the lack of standardized and understandable estimation of their impacts is a serious barrier to raising societal awareness, and hampers effective management interventions at relevant scales. Here, we assessed the economic costs of invasive alien rodents globally in order to help overcome these obstacles. For this purpose, we combined and analysed economic cost data from the InvaCost database-the most up-to-date and comprehensive synthesis of reported invasion costs-and specific complementary searches within and beyond the published literature. Our conservative analysis showed that reported costs of rodent invasions reached a conservative total of US$ 3.6 billion between 1930 and 2022 (annually US$ 87.5 million between 1980 and 2022), and were significantly increasing through time. The highest cost reported was for muskrat Ondatra zibethicus (US$ 377.5 million), then unspecified Rattus spp. (US$ 327.8 million), followed by Rattus norvegicus specifically (US$ 156.6 million) and Castor canadensis (US$ 150.4 million). Of the total costs, 87% were damage-related, principally impacting agriculture and predominantly reported in Asia (60%), Europe (19%) and North America (9%). Our study evidenced obvious cost underreporting with only 99 documents gathered globally, clear taxonomic gaps, reliability issues for cost assessment, and skewed breakdowns of costs among regions, sectors and contexts. As a consequence, these reported costs represent only a very small fraction of the expected true cost of rodent invasions (e.g., using a less conservative analytic approach would have led to a global amount more than 80-times higher than estimated here). These findings strongly suggest that available information represents a substantial underestimation of the global costs incurred. We offer recommendations for improving estimates of costs to fill these knowledge gaps including: systematic distinction between native and invasive rodents' impacts; monetizing indirect impacts on human health; and greater integrative and concerted research effort between scientists and stakeholders. Finally, we discuss why and how this approach will stimulate and provide support for proactive and sustainable management strategies in the context of alien rodent invasions, for which biosecurity measures should be amplified globally.

Impact of pneumocystosis on the Spanish health care system, 1997–2020: Profile of HIV and non-HIV immunocompromised patients

BackgroundPneumocystis jirovecii is an opportunistic fungus recognized for causing P. jirovecii pneumonia. The global prevalence is thought to be higher than 400,000 annual cases, although detailed information about epidemiological patterns is scarce. MethodologyA retrospective longitudinal descriptive study was performed among patients with diagnosis of pneumocystosis according to Classification of Diseases 9th edition, Clinical Modification (code 136.3 for the cases from 1997 to 2015; and 10th edition code B59.0 for cases from 2016 to 2020 in Spanish public hospitals from 1 January 1997–31 December 2020. ResultsA total of 25289 cases were diagnosed. The period incidence rate was 2.36 (95 % CI, 2.33–2.39) cases per 100,000 person-years. Infection was more frequent among men (72.2 %) than among women (27.8 %). Comorbidity was the main characteristic of this cohort. Up to 72.3 % of pneumocystis-infected patients (18293) had HIV coinfection. During the study period, there was a progressive decrease in the number of HIV coinfected cases as the group of patients without HIV infection increased, with the largest group in 2017. The lethality rate in the cohort was 16.7 %. The global cost was €229,234,805 and the average ( ± SD) cost per patient was €9065 ( ± 9315). ConclusionsThe epidemiology of pneumocystosis in Spain has changed in the last two decades. We noted in our study the possibility of a reemergence among non-HIV immunocompromised patients as patients with hematological and nonhematological neoplasia and other risk groups. The lethality of pneumocystosis continues to be high, and the underlying diseases are the main variable associated with lethality.

The electoral consequences of compensation for globalization

As opposition to globalization grows, many governments seek policy responses. One response – the European Globalisation Adjustment Fund – provides support to workers in European Union member states who are made redundant as a result of globalization. Proponents argue that by offsetting some of the costs of globalization, the programme may bolster public support for international economic integration and the political parties that support it. I investigate the impact of the European Globalisation Adjustment Fund on voters’ support for protectionist political parties using a difference-in-differences research design and official election results at the district and commune level. I also examine individual-level voting data. I find that in regions exposed to rising imports, assistance from the European Globalisation Adjustment Fund generates a small decrease in the vote share of one of Europe’s most prominent anti-globalization parties, which ranges in magnitude from 0 to 1.5 percentage points. While consistent with the logic of embedded liberalism, the finding suggests that the theorized connection between compensation and support for globalization may be conditional rather than categorical.

Recent Trends in Biosensing and Diagnostic Methods for Novel Cancer Biomarkers.

Cancer is one of the major public health issues in the world. It has become the second leading cause of death, with approximately 75% of cancer deaths transpiring in low- or middle-income countries. It causes a heavy global economic cost estimated at more than a trillion dollars per year. The most common cancers are breast, colon, rectum, prostate, and lung cancers. Many of these cancers can be treated effectively and cured if detected at the primary stage. Nowadays, around 50% of cancers are detected at late stages, leading to serious health complications and death. Early diagnosis of cancer diseases substantially increases the efficient treatment and high chances of survival. Biosensors are one of the potential screening methodologies useful in the early screening of cancer biomarkers. This review summarizes the recent findings about novel cancer biomarkers and their advantages over traditional biomarkers, and novel biosensing and diagnostic methods for them; thus, this review may be helpful in the early recognition and monitoring of treatment response of various human cancers.

Carbon border adjustment mechanism: a systematic literature review of the latest developments

ABSTRACT Carbon border adjustment mechanism aims to level the playing field and reduce carbon leakage through import taxes and/or export subsidies based on the carbon content for products from countries with different levels of carbon policy stringency. The introduction of an EU carbon border adjustment mechanism (CBAM) has triggered a lively debate on its potential impacts, especially among developing countries. In fact, introducing CBAM is not a new idea; researchers in fields of economics and law have investigated this policy over the last decade. Against this backdrop, this study conducts a literature review of the most recent economic studies of CBAM and provides an exhaustive synthesis of this literature. We employ the so-called ‘Preferred Reporting Items for Systematic Reviews and Meta-Analysis’ approach (PRISMA), which includes an exhaustive screening of studies. Specifically, we identified 97 relevant studies on CBAM from 2004 to 31 August 2021, and conducted descriptive and content analysis of these. Our content analysis highlights the potential impacts of CBAM in terms of its effectiveness across 3 policy objectives: protecting fair competition; reducing carbon leakage; and limiting global welfare costs. We synthesize findings on how policy design and characteristics of an economy lead to different levels and types of effectiveness of a CBAM, and we contrast alternative policy designs across various objectives. Armed with this systematic review of the literature, we spell out insights and challenges in formulating effective CBAM polices. This review thus offers evidenced-based guidance for the policy design of a CBAM and a foundation for further research. Key policy insights There is no one-size-fits-all approach to design and implement CBAM to tackle competitiveness and carbon leakage; policy design and characteristics of the economy matter. According to the effectiveness of CBAM across the 3 policy objectives, alternative policy designs should account for the coverage of trade, of sector(s), and also the means to determine carbon content of traded commodities, the use of revenues collected through CBAM, and the adjustment price. In formulating sound CBAM policies, competitiveness, carbon leakage and welfare evaluation are central economic concerns; however, consistency with the latest international climate policy architecture and fairness issues should also be addressed.

A local cost simulation-based algorithm to solve distributed constraint optimization problems.

As an important incomplete algorithm for solving Distributed Constraint Optimization Problems (DCOPs), local search algorithms exhibit the advantages of flexibility, high efficiency and high fault tolerance. However, the significant historical values of agents that affect the local cost and global cost are never taken into in existing incomplete algorithms. In this article, a novel Local Cost Simulation-based Algorithm named LCS is presented to exploit the potential of historical values of agents to further enhance the exploration ability of the local search algorithm. In LCS, the Exponential Weighted Moving Average (EWMA) is introduced to simulate the local cost to generate the selection probability of each value. Moreover, populations are constructed for each agent to increase the times of being selected inferior solutions by population optimization and information exchange between populations. We theoretically analyze the feasibility of EWMA and the availability of solution quality improvement. In addition, based on our extensive empirical evaluations, we experimentally demonstrate that LCS outperforms state-of-the-art DCOP incomplete algorithms.

Centralised KYC - Secure Platform

The KYC chain in the financial industry is crucial and necessitates stringent compliance as well as expensive manual labor. According to estimates, the global cost of KYC procedures has increased to $1.5 billion. Evaluating data and keeping tight tabs on them takes very little time and effort takes very little time and effort to evaluate data and keep tight tabs on them. Each financial service provider develops their own set of requirements for KYC documents under the present centralized approach. Users must comply with KYC standards with each institution and service provider they utilize as a result. Even if user information needs to be changed down the road, all financial institutions and service providers must be informed separately. Create a central KYC database that would be available to everyone. Keywords— CNN (Convolutional Neural Network), SVM (Support Vector Machine), BERT, LSTM (long short-term memory networks), RNN (Recurrent Neural Network), ANN (Artificial Neural Network), DCNN (Deep Convolution Neural Network, MAML (Model- Agnostic Meta- Learning), GRU (Gated Recurrent Unit), BILSTM (Bidirectional Long Short-Term Memory)

Multicriteria Decision Analysis of Steel and Mass Timber Prototype Buildings in the Pacific Northwest

This study used multicriteria decision analysis to quantitatively compare two prototype buildings, both designed using equivalent mass timber and steel structural systems across four decision criteria of seismic resiliency, global warming potential, superstructure cost, and durability. The 5-story and 12-story prototype buildings were both located at an arbitrary site in Seattle, WA. The first three decision criteria were quantitatively measured for each prototype building and durability was assumed to be equivalent between the alternatives. Seismic resiliency was measured using the median expected annual loss calculated using as a percentage of predicted building replacement cost using a procedure in line with FEMA P-58. The global warming potential was measured over the production, construction, and end-of-life stages using the life-cycle analysis program Athena Impact Estimator for Buildings (IE4B). The superstructure cost was calculated as the average cost per square meter using 10 estimating variations that attempt to account for uncertainty in market rates of material, labor, and mass timber design efficiency. Five decision-maker scenarios were analyzed that span the practical range of decision-maker priorities, as informed by discussions with architects and engineers active in the Pacific Northwest. Results from this study showed that for decision-maker cases where the global warming priority was low, steel buildings were the preferred choice. For cases with moderate to high global warming priority and low priority on cost, mass timber buildings were the preferred choice. However, for decision-maker scenarios with moderate priority on both global warming potential and cost, the steel and mass timber buildings were approximately equivalent. Finally, a hybrid steel–timber alternative was presented as a possible sweet-spot solution that merged the benefits of each building material and minimized their drawbacks, making it the most-preferred solution for the case of moderate priority on both cost and global warming potential. The hybrid case was also close second in ranked choice for all other scenarios examined.

Ailing neurosurgical services in rural Africa

Ailing neurosurgical services in rural Africa

The Effect of Stem Cells on Meniscus Tear Injuries

The Meniscus injuries are associated with pain, swelling, impairment in function and activity levels as well as early osteoarthritis of the knee joint. The prevalence of meniscal tear injuries is close to 12% to 14%, with an occurrence of 60-70 cases per 100,000 individuals. There are about 850,000 cases per year and the global annual cost is estimated at $4 billion. Professional and amateur athletes demonstrate meniscus tear rates between 1.58-2.98 injuries per 10,000 athletic exposures. Sports with the highest rates of athletes affected by meniscus tear injuries include: football, soccer, basketball, wrestling, and rugby. Meniscus tear surgeries may lead to potential side effects or medical complications. The effectiveness of stem cells for meniscus injuries in animal and human subjects is something that researchers have investigated. Often preferred mesenchymal stem cells are the source for procedures seen in orthopedics as they change into many types of tissues including: cartilage, bone, muscle, bone, and fat. The use of stem cells in transplantation has shown an improved rate of healing, enhanced tissue quality, sustained functional gains, and improved outcomes in clinic. Researchers think the use of stem cells may offer other options for people with an orthopedic injury including meniscus tears decreasing recovery time, improving function, and decreasing degenerative osteoarthritis.

Sublinear and Linear Convergence of Modified ADMM for Distributed Nonconvex Optimization

In this article, we consider distributed nonconvex optimization over an undirected connected network. Each agent can only access to its own local nonconvex cost function and all agents collaborate to minimize the sum of these functions by using local information exchange. We first propose a modified alternating direction method of multipliers (ADMM) algorithm. We show that the proposed algorithm converges to a stationary point with the sublinear rate <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathcal {O}(1/T)$</tex-math></inline-formula> if each local cost function is smooth and the algorithm parameters are chosen appropriately. We also show that the proposed algorithm linearly converges to a global optimum under an additional condition that the global cost function satisfies the Polyak–Łojasiewicz condition, which is weaker than the commonly used conditions for showing linear convergence rates including strong convexity. We then propose a distributed linearized ADMM (L-ADMM) algorithm, derived from the modified ADMM algorithm, by linearizing the local cost function at each iteration. We show that the L-ADMM algorithm has the same convergence properties as the modified ADMM algorithm under the same conditions. Numerical simulations are included to verify the correctness and efficiency of the proposed algorithms.

Normalization and possibility of classification analysis using the optimal warping paths of dynamic time warping in gait analysis.

The purpose of this study was to verify classification performance and the difference analysis between gender using optimal warping paths of dynamic time warping (DTW) and to examine the usefulness of root mean square error (RMSE) represented by the perpendicular distance from the optimal warping path to the diagonal. A 3-dimensional motion analysis experiment was performed with 24 healthy adults (male=12, female=12) in their 20s of age without gait-related diseases or injuries for the past 6 months to collect gait data. This study performed a DTW 132 times in total (male=62, female=62) for the flexion angle of the right leg's hip, knee, and ankle joints. Then, the global cost and the RMSE of the optimal warping paths were calculated and normalized. The difference analysis was performed by independent t-test. Machine learning was performed to test the classification performance using the neural network, support vector machine, and logistic regression model among the supervised models. Results analyzed using global cost and RMSE for hip, knee, and ankle joints showed a statistically significant difference between genders in global cost and RMSE for hip and knee joints but not for ankle joints using RMSE. Considering both area under the receiver operating characteristic curve and F1-score, the logistic regression model has been evaluated as the most suitable for gender classification using the global cost or RMSE. This study demonstrated that optimal warping paths could be used for statistical difference analysis and classification analysis.