Exponential Increase Research Articles

Paying reviewers and regulating the number of papers may help fix the peer-review process

The exponential increase in the number of submissions, further accelerated by generative AI, and the decline in the availability of experts are burdening the peer review process. This has led to high unethical desk rejection rates, a growing appeal for the publication of unreviewed preprints, and a worrying proliferation of predatory journals. The idea of monetarily compensating peer reviewers has been around for many years; maybe, it is time to take it seriously as one way to save the peer review process. Here, I argue that paying reviewers, when done in a fair and transparent way, is a viable solution. Like the case of professional language editors, part-time or full-time professional reviewers, managed by universities or for-profit companies, can be an integral part of modern peer review. Being a professional reviewer could be financially attractive to retired senior researchers and to researchers who enjoy evaluating papers but are not motivated to do so for free. Moreover, not all produced research needs to go through peer review, and thus persuading researchers to limit submissions to their most novel and useful research could also help bring submission volumes to manageable levels. Overall, this paper reckons that the problem is not the peer review process per se but rather its function within an academic ecosystem dominated by an unhealthy culture of ‘publish or perish’. Instead of reforming the peer review process, academia has to look for better science dissemination schemes that promote collaboration over competition, engagement over judgement, and research quality and sustainability over quantity.

Study of Effect of Radiation Hazards in Human Life

In this paper, we have investigated the effect of radiations on human life by expressing the exponential decay law curve, dose curve, shielding effectiveness curve and radiation exposure simulation curve. Also this research investigates the impact of radiation hazards on human health, focusing on both quantitative data and qualitative case studies. Utilizing a comprehensive analysis of radiation exposure levels and their associated health outcomes, we plotted various graphs to illustrate the correlation between radiation dose and adverse health effects. Our research combines empirical data with in-depth case studies to assess how different levels and types of radiation influence human life. The findings reveal a significant relationship between radiation exposure and increased risks of several health conditions, including cancer and radiation sickness. By analyzing the plotted data and case studies, this paper provides a detailed understanding of the short-term and long-term effects of radiation hazards. The results underscore the importance of effective radiation safety measures and informed public health policies to mitigate these risks.

Dear-PSM: A deep learning-based peptide search engine enables full database search for proteomics.

Peptide spectrum matching is the process of linking mass spectrometry data with peptide sequences. An experimental spectrum can match thousands of candidate peptides with variable modifications leading to an exponential increase in candidates. Completing the search within a limited time is a key challenge. Traditional searches expedite the process by restricting peptide mass errors and variable modifications, but this limits interpretive capability. To address this challenge, we propose Dear-PSM, a peptide search engine that supports full database searching. Dear-PSM does not restrict peptide mass errors, matching each spectrum to all peptides in the database and increasing the number of variable modifications per peptide from the conventional 3-20. Leveraging inverted index technology, Dear-PSM creates a high-performance index table of experimental spectra and utilizes deep learning algorithms for peptide validation. Through these techniques, Dear-PSM achieves a speed breakthrough 7 times faster than mainstream search engines on a regular desktop computer, with a remarkable 240-fold reduction in memory consumption. Benchmark test results demonstrate that Dear-PSM, in full database search mode, can reproduce over 90% of the results obtained by mainstream search engines when handling complex mass spectrometry data collected from different species using various instruments. Furthermore, it uncovers a substantial number of new peptides and proteins. Dear-PSM has been publicly released on the GitHub repository https://github.com/jianweishuai/Dear-PSM.

Deep learning‐based spectrum sharing in next generation multi‐operator cellular networks

SummaryOwing to the exponential increase in wireless network services and bandwidth requirements, sharing the radio spectrum among multiple network operators seems inevitable. In wireless networks, enabling efficient spectrum sharing for resource allocation is quite challenging due to several random factors, especially in multi‐operator spectrum sharing. While spectrum sensing can be useful in spectrum‐sharing networks, the chance of collision exists due to the inherent unreliability of wireless networks, making operators reluctant to use sensing‐based mechanisms for spectrum sharing. To circumvent these issues, we utilize an alternative approach, whereby we propose an efficient spectrum‐sharing mechanism leveraging a spectrum coordinator (SC) in a multi‐operator spectrum‐sharing scenario assisted by deep learning (DL). In our proposed scheme, before the beginning of each timeslot, the base station of each operator transmits the number of required resources based on the number of packets in the base station's queue to SC. In addition, base stations also transmit the list of available channels to SC. After gathering information from all base stations, SC distributes this collected information to all the base stations. Each base station then utilizes the DL‐based spectrum‐sharing algorithm and computes the number of resources it can use based on the number of packets in its queue and the number of packets in the queues of other operators. Furthermore, by leveraging DL, each operator also computes the cost it must pay to other operators for using their resources. We evaluate the performance of the proposed network through extensive simulations. It is shown that the proposed DL‐based spectrum‐sharing mechanism outperforms the conventional spectrum allocation scheme, thus paving the way for more dynamic and efficient multi‐operator spectrum sharing.

Bibliometric analysis of the trends and evolution in β-lactam allergy research

BackgroundBeta-lactams remain the most reported drug allergy globally, with the volume and diversity of related drug allergy research continuing to accumulate. Recognizing evolving research trends can help inform future directions and encourage synergistic collaborations. ObjectiveWe conducted a comprehensive bibliometric analysis of all publications relevant to beta-lactam allergy, with a focus on longitudinal publication rates, international collaborations and keyword/ trend analysis. MethodsMeta-data from all original articles, letters and reviews relevant to beta-lactam allergy on the Web of Science Core Collection up till 31-Dec-2023 were analysed. ResultsFrom 1966-2023, there were 4451 records (3536 articles, 631 reviews, 284 letters) from 78 countries. There was an exponential increase in publications, especially during the last decade, with half of all publications on beta-lactam allergy published during this time (50.6%, 2252/4452). Overall, 18.1% (805/4452) involved international co-authorships, with significant increase since the last decade (12.7% vs. 23.3%, p<0.001). The most frequent keywords, in the first published half of articles were “skin testing” (84/1919), “IgE” (57/1919) and “anaphylaxis” (49/1919); in contrast to “skin testing” (137/3351), “drug provocation test” (121/3351), “antimicrobial resistance” (120/3351) and “antimicrobial stewardship” (118/3351) in the latter. ConclusionThere has been a surge in publications, international collaboration and shifting paradigms in beta-lactam allergy research. The field has evolved beyond focusing on “in vitro tests” or “desensitization”, toward “antimicrobial stewardship”. However, there is still seems to relatively fewer collaborations with non-Western countries. Further international collaborations to harmonize delabelling strategies against the threat of mislabelled beta-lactam allergy should be encouraged.

Inelastic relaxation in tin oxide thin films with an amorphous structure

Inelastic relaxation in amorphous tin oxide thin films obtained by ion-beam sputtering in an argon atmosphere were studied. The films retain an amorphous structure after annealing at temperatures below 623 K for 30 min and crystallization begins after annealing at 673 K with the formation of two phases, where the SnO2 phase predominates over the SnO phase. Annealing at 723 K for 30 min leads to a partial transition of the SnO crystalline phase to the SnO2 phase.The temperature dependence of internal friction revealed maxima at 585 K and 603 K, identified as β - relaxation maxima, as well as at 690 K, identified as α - relaxation maximum. It is assumed that the β - relaxation maxima at 585 K and 603 K are associated with local hopps of oxygen atoms within the defect structure of SnO2 and with local hopps of tin atoms within the defect structure of SnO, respectively. The exponential increase in internal friction up to a temperature of 690 K in the α - relaxation region is associated with the diffusion of nonequilibrium vacancy-like defects of the amorphous structure below the glass transition temperature and equilibrium ones above the glass transition temperature. Estimates of the migration energy and formation energy of vacancy-like defects in amorphous tin oxide were made.

Giant Tunneling Electro‐Resistance in Ultrathin Ferroelectric Tunnel Junctions: The Interface Barrier Gain Mechanism

AbstractUltrathin ferroelectric tunnel junctions (FTJs) hold considerable promise for next‐generation, high‐speed, low‐power, and high‐density nonvolatile memory applications. Achieving a substantial tunneling electro‐resistance (TER) remains a challenge as the ferroelectric layer is thinned to nanoscale dimensions, often resulting in a diminished or lost polarization. An innovative interface barrier gain mechanism is introduced, employing interface electronic state modulation to precisely control the size of an additional interface barrier. This strategy lessens the dependency of the tunneling barrier on ferroelectric polarization strength, facilitating a remarkable TER even at ferroelectric thicknesses as minimal as ≈1 nm. The focus is on composite FTJs using In2Se3/MTe2 (M = Mo, W), where the inclusion of an MTe2 monolayer disrupts the asymmetric electrode configuration. The weak ferroelectric polarization reversal of the In2Se3 monolayer effectively modulates the electronic state coupling at the In2Se3/MTe2 interface. This modulation leads to variations in the width and height of the Schottky barrier at the heterojunction‐electrode interface corresponding with the ferroelectric polarization reversal, establishing a beneficial Ohmic contact in the “on” state and resulting in an exponential TER increase up to 5.4 × 106%. This work introduces a universal mechanism to overcome the thickness limitations traditionally associated with enhancing TER, marking a significant advancement in the development of ultrathin ferroelectric nonvolatile devices.

Mathematical modeling of meningioma volume change after radiation treatment

ObjectiveMeningiomas are the most common primary central nervous tumor and are often treated with radiation therapy. This study examines the long-term volumetric changes of intracranial meningiomas in response to radiation therapy. The objective is to analyze and model the volumetric changes following treatment. MethodsData from a retrospective single-institution database (2005–2015) were used, with inclusion criteria being patients with a diagnosis of meningiomas, along with additional inclusion criteria consisting of treatment with radiation, having at least three magnetic resonance imaging (MRI) scans with one or more before and after radiation treatment, and the patients following up for at least eighteen months. Exclusion criteria consisted of patients less than 18 years old, patients receiving surgery and/or adjuvant chemotherapy following radiation, and patients without any available details regarding radiation treatment parameters. Tumor volumes were measured via T1-weighted post-contrast MRI and calculated using the ABC/2 ellipsoidal approximation, a method allowing for the measurement of non-linear growth volume reduction. ResultsOf 48 meningioma patients considered, 10 % experienced post-radiation growth, while 75 % witnessed a ≥50 % decrease in volume over a follow-up period of 0.3–14.9 years. Median decay rate was 0.81, and within 1.17 years, 90 % achieved the predicted volume reduction. Predicted vs. actual volumes showed a mean difference of 0.009 ± 0.347 cc. Initial tumor volumes strongly correlated (Pearson’s R=0.98, R-squared=0.96) with final asymptotic volumes, which had a median of 1.50 cc, with interquartile range (IQR) = [0.39, 3.67]. Conclusion90 % of patients achieved tumor-volume reduction at 1.17 years post-treatment, reaching a non-zero asymptote strongly correlated with initial tumor volume, and 75 % experienced at least a 50 % volume decrease. Individual volume changes for responsive meningiomas can be modeled and predicted using exponential decay curves.

Potential of membrane distillation for water recovery and reuse in water stress scenarios: Perspective from a bibliometric analysis

Climate change and related issues such as water scarcity and the urgent need for a transition to sustainable energy sources have motivated the development of novel processes and techniques that can be applied for water treatment, recovery and reuse. Among these emerging processes, membrane distillation in its different configurations has been extensively studied and reported in the literature. A bibliometric analysis was performed to investigate the research documents published in the scientific database Scopus until 2024, related to use of membrane distillation for water recovery and reuse. The main quantitative attributes of the research during this period were identified. The results of this analysis showed a very low scientific production until 2005, followed by a rapid exponential increase since then. The combined contribution of the two most productive countries (China and USA respectively) accounted for more than 41 % of the total number of publications, followed by Australia and Saudi Arabia, which occupied the third and fourth positions in the ranking. Chemical engineering was the most important subject category (57.4 % contribution), closely followed by environmental sciences. The review of the most cited documents and keywords showed that membrane wetting is one of the main drawbacks that can reduce the performance of membrane distillation and the use of innovative superhydrophobic, omniphobic or Janus membranes resulted an adequate solution to avoid this problem. Moreover, the desalination of seawater, brines and other highly saline solutions can be considered as the most studied application of membrane distillation. The consideration of the energetic aspects of membrane distillation and its coupling with other technologies were identified as relevant topics during the bibliometric network analysis. Special attention was given to the potential of membrane distillation for water recovery and reuse in the Chilean context of water stress for the production of drinking water and the treatment of domestic greywater and wastewater from mining and other industrial activities.

Sentiment Analysis of PeduliLindungi User Using Naïve Bayes Classifier Algorithm and Support Vector Machine

The Indonesian government is attempting to track the spread of the virus by creating an application named “PeduliLindungi” to deal with the coronavirus's exponential increase in cases across the country. Because it has a feature to disclose the user's location immediately, it is envisaged that this program can reduce the transmission of viruses in monitoring. Indonesians have used the PeduliLindungi, and there are user reviews of both positive and negative experiences. Therefore, to enhance these services, an assessment is required. The text mining method can extract information from users' reviews to collect this data. This method's application additionally uses the Naive Bayes Classifier and Support Vector Machine algorithms, which analyze word associations and do a classification evaluation of the data's accuracy. Based on the two methods' calculations, the NBC algorithm's average classification accuracy was 83.81%, and the SVM algorithm was 93.84%. Following that, discoveries on words that frequently exist or are used by people are obtained through word associations in the sentiment analysis of positive or negative reviews.

The Multicollinearity Effect on the Performance of Machine Learning Algorithms: Case Examples in Healthcare Modelling

Background: The data extracted from various fields inherently consists of extremely correlated measurements in parallel with the exponential increase in the size of the data that need to be interpreted owing to the technological advances. This problem, called the multicollinearity, influences the performance of both statistical and machine learning algorithms. Statistical models proposed as a potential remedy to this problem have not been sufficiently evaluated in the literature. Therefore, a comprehensive comparison of statistical and machine learning models is required for addressing the multicollinearity problem. Methods: Statistical models (including Ridge, Liu, Lasso and Elastic Net regression) and the eight most important machine learning algorithms (including Cart, Knn, Mlp, MARS, Cubist, Svm, Bagging and XGBoost) are comprehensively compared by using two different healthcare datasets (including Body Fat and Cancer) having multicollinearity problem. The performance of the models is assessed through cross validation methods via root mean square error, mean absolute error and r-squared criteria. Results: The results of the study revealed that statistical models outperformed machine learning models in terms of root mean square error, mean absolute error and r-squared criteria in both training and testing performance. Particularly the Liu regression often achieved better relative performance (up to 7.60% to 46.08% for Body Fat data set and up to 1.55% to 21.53% for Cancer data set on training performance and up to 1.56% to 38.08% for Body Fat data set and up to 3.50% to 23.29% for Cancer data set on testing performance) among regression methods as well as compared to machine algorithms. Conclusions: Liu regression is mostly disregarded in the machine learning literature, but since it outperforms the most powerful and widely used machine learning algorithms, it appears to be a promising tool in almost all fields, especially for regression-based studies including data with multicollinearity problem.

Achieving Non-Interfacial Blocking Zinc Ion Transport Based on MOF Derived Manganese Oxides and Amorphous Carbon Hybrid Materials.

How to coordinate electron and ion transport behavior across scales and interfaces within ion battery electrodes? The exponential increase in surface area observed in nanoscale electrode materials results in an incomprehensibly vast spatial interval. Herein, to address the problems of volume expansion, dissolution of cathode material, and the charge accumulation problem existing in manganiferous materials for zinc ion batteries, metal organic framework is utilized to form the architecture of non-interfacial blocking ~10 nm Mn2O3 nanoparticles and amorphous carbon hybrid electrode materials, demonstrating a high specific capacity of 361 mAh g-1 (0.1 A g-1), and excellent cycle stability of 105 mAh g-1 after 2000 cycles under 1 A g-1. The uniform and non-separated disposition of Mn and C atoms constitutes an interconnected network with high electronic and ionic conductivity, minimizing issues like structural collapse and volume expansion of the electrode material during cycling. The cooperative insert mechanism of H+ and Zn2+ are analyzed via ex-situ XRD and in-situ Raman tests. The model battery is assembled to present practical possibilities. The results indicate that MOF-derived carbonization provides an effective strategy for exploring Mn-based electrode materials with high ion and electron transport capacity.

Experimental research on shear strength characteristics of cement-stabilized dredged silty clay reinforced with alginate fiber

In order to avoid uneven dispersion or agglomeration of traditional fibers after mechanical mixing, alginate fibers as natural fibers were selected in this study to reinforce the cement-stabilized dredged silty clay, forming alginate fiber-reinforced cement-stabilized dredged silty clay. The shear strength of cement-stabilized dredged silty clay reinforced with alginate fibers with the same cement content (9 % by wet weight) and cured for 7 and 28 days was investigated. Consolidated undrained (CU) triaxial compression tests were carried out on reinforced soil samples with varying fiber lengths (3 mm, 6 mm, and 9 mm) and fiber contents (0 %, 0.3 %, 0.6 %, and 0.9 % by weight of wet soil) to assess the shear strength characteristics. The results showed that, on average, the shear strength increased by 18.30 % and 18.56 % with the increasing content and length of alginate fibers, respectively. The variation in deviator stress and axial strain exhibited a shift from strain-softening to strain-hardening with increased confining pressure, alginate fiber content, and length. Hence, a double exponential curve model with different fiber content and length in three confined pressures was proposed, and the correlation coefficient of the fitting results was above 0.90. The secant modulus E50 increased and subsequently decreased with the length of fibers, with the largest secant modulus E50 observed for 6 mm fiber length. The strength parameters (cohesion c and internal friction angle φ) exhibited contrasting responses to variations in alginate fiber length and content. The cohesion of the fiber-reinforced soil specimens increased by 29.0 % and 13.1 %, respectively, for increased fiber content and length. Nevertheless, the angle of internal friction remained relatively unchanged. The findings of this study can serve as a reference guide for related engineering projects.

The linear Paul Trap's Confined Stability Area for 40Ca+ Ions

تقدم تكنولوجيا الكم طرقًا حسابية واتصالات ومحاكاة وقياسًا جديدة. تحتاج أجهزة الكمبيوتر التقليدية إلى المساعدة في حل المشكلات المهمة مثل التحليل بسبب الزيادات الهائلة في وقت الحساب. ومع ذلك، تستخدم أجهزة الكمبيوتر الكمومية ميكانيكا الكم لحجم المشكلة الأسي الفرعي ويمكنها محاكاة الطبيعة على المستوى الكمي. يهتم العلماء بشكل متزايد بتطوير أجهزة الكمبيوتر الكمومية باستخدام ذرات متأينة مفردة في مصائد باولي. تمثل الحالة الأساسية لكل أيون أقل قيمة ممكنة للبت الكمي. تم استخدام الأيونات المحتجزة 40Ca+ في إحدى الدراسات كمثال على الكيوبت الكمومي. تم استخدام برنامج MATLAB على العوامل النموذجية التي تؤثر على الحالة المقيدة وتأثيراتها. يجب أن تكون الحلول مستقرة في كلا الاتجاهين، مما يتطلب حصرًا ثلاثي الأبعاد لمعادلة ماثيو. تؤثر المتغيرات على المسافة من مركز المصيدة لنهاية القطب، وجهد UDC، وكتلة الأيون، والترددات الراديوية. تم استخدام جهد متغير للتحكم وإظهار تأثيره على سلسلة محددة من الأيونات المحاصرة. يهدف هذا البحث إلى فهم أفضل للظروف المثلى للحجز وحركة الأيونات من الحالة (4S1/2) إلى الحالة (4P1/2) بالرنين. تخضع الحالة الكمومية للتعديل والتغيير، مما يجعلها أداة واعدة لحل المشكلات المعقدة.

Boosting conversion of waste activated sludge to methane during anaerobic digestion via facilitating direct interspecies electron transfer with glycerol

Possibility of boosting conversion of waste activated sludge to methane via facilitating direct interspecies electron transfer with glycerol was explored. Methane yields with 5 %/8 % glycerol were 1.18/1.31 folds higher than that without glycerol. After removing methane yields from glycerol, methane yields with 5 %/8 % glycerol was still 17 %/19 % higher than that without glycerol. Electron transfer coefficients for charge/discharge in sludge with 8 % glycerol were 1.12/1.39 folds higher than that without glycerol. Analysis of conductivity-temperature responses found that conductivity of sludge with 8 % glycerol exhibited an exponential increase when temperature was declined, similar to that with 8 % ethanol. However, conductivity of sludge with 8 % glycerol was one order of magnitude higher than that with 8 % ethanol. Electrochemical Fourier transform infrared spectra showed that reversible changes of bands associated with c-type cytochrome in sludge with 8 % glycerol were more intense than that with 8 % ethanol. Analysis of microbial communities showed that glycerol feeding increased the abundance of Methanospirillum hungatei JF-1, and specially enriched Tangfeifania diversioriginum, Syntrophomonas zehnderi OL-4 and Trichococcus pasteurii. These results indicated that glycerol feeding facilitated the better direct interspecies electron transfer than ethanol feeding that had been previously documented during anaerobic digestion of waste activated sludge.

Accelerated aging behavior of degradable and non-degradable microplastics via advanced oxidation and their adsorption characteristics towards tetracycline

The increasing global utilization of biodegradable plastics due to stringent regulations on traditional plastics has caused a significant rise in microplastic (MPs) pollution in aquatic ecosystems from biodegradable products. However, the environmental behavior of biodegradable MPs remains inadequately elucidated. This study explored the aging processes of polylactic acid (PLA) and polystyrene (PS) under a heat-activated potassium persulfate (K2S2O8) system, as well as their adsorption characteristics towards tetracycline (TCs). In comparison to PS, the surface structure of PLA experienced more pronounced changes over aging, exhibiting evident pits, cracks, and fragmentation. The carbonyl index (CI) and oxygen/carbon ratio (O/C) of PS displayed exponential growth over time, whereas the values for PLA showed linear and exponential increases, respectively. The adsorption capacity of TCs by PS and PLA aged for 6 days increased from 0.312 mg‧g−1 and 0.457 mg‧g−1for original PS and PLA, respectively, to 0.372 mg‧g−1 and 0.649 mg‧g−1. Meanwhile, the adsorption rate (k2 values) for TCs decreased by 42.03 % for PS and 79.64 % for PLA compared to their initial values. The findings indicated that biodegradable PLA-MPs may exhibit higher tetracycline carrying capacities than PS, potentially increasing environmental and organismal risks, particularly in view of aging effects.

Generation and deployment of honeytokens in relational databases for cyber deception

Despite considerable investments in database security, global statistics indicate an exponential increase in data breaches. Organizations are often unaware of data breaches for weeks, months, or even years. Sufficient for adversaries to compromise and ex-filtrate business or mission-critical data. Recent research suggests using honeytokens for early detection of data breaches in organizations. Existing honeytoken generation methods rely on regular expressions, rule mining, constraint satisfaction, or representation learning, which are complex and limited to a few attributes. We created a framework for generating and deploying honeytokens in relational databases that actively monitor sensitive records and quickly detect data breaches and their misuse. To generate the honeytoken we have used the hierarchical machine learning algorithm which uses a recursive technique to model the parent–child relationships of multi-table databases. The proposed method enables the organization to take remedial action to reduce the impact of data breaches and complement existing database security solutions.

A universal optoelectronic imaging platform with wafer-scale integration of two-dimensional semiconductors

Photodetectors (PDs) are crucial in modern society, as they enable the detection of a diverse range of light-based signals. With the exponential increase in their development, materials are being used to create a wide range of PDs that play critical roles in enabling various applications and technologies. Image sensor technology has been hindered due to the lack of a universal system that can integrate all types of PDs with silicon-based readout integrated circuits (ROICs). To address this issue, we conducted experiments using two-dimensional materials as an example. We fabricated high-performance MoS2/MoTe2-based photodetectors and identified the most suitable ROICs to pair with them. This established a solid foundation for further research in the field of image sensors. We developed and implemented a versatile testing system that uses a printed circuit board to connect the PD and ROIC. After the ROIC generates the sampled signal, it is collected and processed by algorithms, which overcome device uniformity limitations and produce a high-quality image that is visible to the naked eye. This universal system can be used with a wide range of PD and ROIC types made from different materials, making it highly convenient for diverse testing applications and the development of diverse image sensor types. This robust new platform is expected to spur further innovation and advancements in this rapidly developing field.

Epidemiological and environmental investigation of the 'big four' Vibrio species, 1994 to 2021: a Baltic Sea retrospective study.

BackgroundThe Vibrio genus comprises several bacterial species present in the Baltic Sea region (BSR), which are known to cause human infections.AimTo provide a comprehensive retrospective analysis of Vibrio-induced infections in the BSR from 1994 to 2021, focusing on the 'big four' Vibrio species - V. alginolyticus, V. cholerae non-O1/O139, V. parahaemolyticus and V. vulnificus - in eight European countries (Denmark, Estonia, Finland, Germany, Latvia, Lithuania, Poland and Sweden) bordering the Baltic Sea.MethodsOur analysis includes data on infections, Vibrio species distribution in coastal waters and environmental data received from national health agencies or extracted from scientific literature and online databases. A redundancy analysis was performed to determine the potential impact of several independent variables, such as sea surface temperature, salinity, the number of designated coastal beaches and year, on the Vibrio infection rate.ResultsFor BSR countries conducting surveillance, we observed an exponential increase in total Vibrio infections (n = 1,553) across the region over time. In Sweden and Germany, total numbers of Vibrio spp. and infections caused by V. alginolyticus and V. parahaemolyticus positively correlate with increasing sea surface temperature. Salinity emerged as a critical driver of Vibrio spp. distribution and abundance. Furthermore, our proposed statistical model reveals 12 to 20 unreported cases in Lithuania and Poland, respectively, countries with no surveillance.ConclusionsThere are discrepancies in Vibrio surveillance and monitoring among countries, emphasising the need for comprehensive monitoring programmes of these pathogens to protect human health, particularly in the context of climate change.

Automating execution of surveillance procedures for NPP main control rooms

ABSTRACT For the past 30 years, progress in the automation of control processes in the nuclear industry has been much slower compared to other industries. In the same timeframe, other complex industrial and/or high-risk processes (e.g., aviation) have been revolutionized by the exponential increase of technology capability in computing and information systems. The reason for the relatively slow trickling of technology advancements in the nuclear field is multi-faceted: i) resistance to change from a traditionally proven solution (partially due to very specific regulation requirements); ii) the cost to adopt Computerized Procedure Systems for existing NPPs, without having a quantified and proven safety benefit; iii) relatively low number of new NPPs being built following the Chernobyl and Fukushima disasters; iv) possible negative impact on the human factors aspect. After a short introduction to automation in another high-risk industry (aviation), this paper focuses on the practical approach required for automating Surveillance Procedures, and at the same time taking into consideration the human factors impact of this approach.