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This paper presents a machine learning-based approach to grade engine health and generate a respective score ranging from 0 to 100 for tuned high-performance vehicles. It integrates the technical intricacies of automotive engineering with machine learning practices in a clear and sequential process. Data are collected from sensors monitoring revolutions per minute, boost, rail pressure, timing, and temperature. The data are processed for supervised learning and analyzed using visualizations such as a heatmap and t-SNE plots. Models are trained, innovatively tuned through hyperparameter optimization, and tested for their ability to grade new data logs. The results highlight K-Neighbors, Extra Trees, and Extreme Gradient Boosting as exceptional regressors for this task. The automated grading of engine health and performance enhances objectivity and efficiency in the tuning process and potentially serves as a basis for a digital twin. The developed methodology is discussed in the context of health evaluation for any sensor-based system, with practical applications extending across various domains and industries. [ABSTRACT FROM AUTHOR]

This study addressed multi-product optimization in Cedrelinga cateniformis plantations in the Peruvian Amazon, aiming to maximize volumetric yields of logs and sawn lumber. Data from seven plantations of different ages and types, established on degraded land, were analyzed by using ten stem profile models to predict taper and optimize wood use. In addition, the structure of each plantation was evaluated using diameter distributions and height–diameter ratios; log and sawn timber production was optimized using SigmaE 2.0 software. The Garay model proved most effective, providing high predictive accuracy (adjusted R2 values up to 0.963) and biological realism. Marked differences in volumetric yield were observed between plantations: older and more widely spaced plantations produced higher timber volumes. Logs of optimal length (1.83–3.05 m) and larger dimension wood (e.g., 25.40 × 5.08 cm) were identified as key contributors to maximizing volumetric yields. The highest yields were observed in mature plantations, in which the total log volume reached 508.1 m3ha−1 and the sawn lumber volume 333.6 m3ha−1. The findings demonstrate the power of data-driven decision-making in the timber industry. By combining precise modeling and optimization techniques, we developed a framework that enables sawmill operators to maximize log and lumber yields. The insights gained from this research can be used to improve operational efficiency and reduce waste, ultimately leading to increased profitability. These practices promote support for smallholders and the forestry industry while contributing to the long-term development of the Peruvian Amazon. [ABSTRACT FROM AUTHOR]

Cybercrime is one of the fastest-growing crimes worldwide. It is observed that every seven seconds, cyber attackers penetrate cyber systems. While detecting an anomaly or attack, the log system is one of the crucial components of any system storing and managing all the events. It has always been challenging to detect an anomaly in logs. This is because of continuous and ever-changing log events and their mutability property. In this paper, we develop a machine learning-based artificial intelligence approach to address this issue of log analysis by proposing two modules. The first one is anomaly detection using different machine learning models. The second one is a distributed immutable storage system for securely storing the logs. In addition, we present a descriptive and user-friendly web application by integrating all modules using HTML, CSS, and Flask Framework on the Heroku cloud environment. The results demonstrate that the proposed hybrid machine learning models are capable of achieving 99.7% accuracy in detecting network anomalies. [ABSTRACT FROM AUTHOR]

Petrographic and petrophysical characterizations of the pre-salt Chela formation of the Nsiamfumu and Liawenda fields in the onshore Coastal Basin of the D.R. Congo it was performed. These characterizations, as part of the static modelling of the reservoirs, involved reading log measurements, thin-slice observations of rock samples taken from this formation, calculations and interpretation of logs, CPI (Computer Processed Interpretation) and DST (Drill Stem Testing) from well tests. The following observations were obtained: • Wells Lw-1: the formation is characterized by dolomitic limestone and micaceous black shale with a thickness of 34 m having heavy oil indices and an average porosity of 17% and a salinity greater than 300 gr/L; • Well Lw-2: the formation is characterized by islands of sand, coarse sandstone and a few quartz pebbles with a thickness of 10m showing evidence of light oil, gas and an average porosity of 24%; • Shaft Lw-3: the formation is dominated by micaceous shale and dolomite interbeds with a thickness of 14m showing little evidence of hydrocarbons, only salt water and residual oils; • Puits Ns-1: the formation is characterized by beige to grey dolomite, grey shale and white sand with a thickness of 6m showing evidence of light oil and an average porosity of 20%.

Petrographic and petrophysical characterizations of the pre-salt Chela formation of the Nsiamfumu and Liawenda fields in the onshore Coastal Basin of the D.R. Congo it was performed. These characterizations, as part of the static modelling of the reservoirs, involved reading log measurements, thin-slice observations of rock samples taken from this formation, calculations and interpretation of logs, CPI (Computer Processed Interpretation) and DST (Drill Stem Testing) from well tests. The following observations were obtained: • Wells Lw-1: the formation is characterized by dolomitic limestone and micaceous black shale with a thickness of 34 m having heavy oil indices and an average porosity of 17% and a salinity greater than 300 gr/L; • Well Lw-2: the formation is characterized by islands of sand, coarse sandstone and a few quartz pebbles with a thickness of 10m showing evidence of light oil, gas and an average porosity of 24%; • Shaft Lw-3: the formation is dominated by micaceous shale and dolomite interbeds with a thickness of 14m showing little evidence of hydrocarbons, only salt water and residual oils; • Puits Ns-1: the formation is characterized by beige to grey dolomite, grey shale and white sand with a thickness of 6m showing evidence of light oil and an average porosity of 20%. [ABSTRACT FROM AUTHOR]

Recent exploration has revealed that the Middle Triassic Leikoupo Formation 32 Submember (T2/32) in the Sichuan Basin contains unconventional marl reservoirs with significant natural gas potential. Due to limited cores, old wells, and conventional logs, however, the lithological understanding of T2/32 is incomplete and relies solely on inaccurate mud logs. This lack of lithological foundation challenges geology and petroleum research. To identify complex lithology, this paper presents a double-hierarchical workflow to identify seven types of lithology using logs. The first order distinguishes salt, anhydrite, and marl, while the second order further subdivides marl into anhydrite marl, argillaceous limestone, shaly limestone, and limy shale. Different rocks' logging response characteristics are summarized based on quantity-limited cores and micro-resistivity imaging logs. Lithological identification of 2D and 3D plots is established using sensitive GR, DEN, and RT. Corresponding identification standards are built in two hierarchies. According to these standards, the lithology of T2/32 is identified in a total of 119 wells. Finally, the lithological characteristics of vertical, horizontal, and plane are discussed in the research area. The research results may aid in comprehending the entire lithological characteristics of the complex marl reservoir in T2/32 of the Sichuan Basin. It would help the exploration potential of petroleum systems in turn. [ABSTRACT FROM AUTHOR]

The Oligocene of the eastern area of the Arabian Plate is worthwhile studying due to it being both poorly exposed and understood. This first bed-by-bed lithostratigraphic/microfacies study of the Oligocene coral-bearing Ma'ahm Beds elucidates their depositional environments by analyzing their standard microfacies (SMF). The Ma'ahm Beds are >112 m thick. The basal Unit 1 is ≧22 m thick, dominated by thick-bedded foraminferal wackestones, packstones, and grainstones. Unit 1 evolves from restricted lagoonal conditions (SMF 16) to a transition toward open marine lagoonal conditions. Coarsening-up and thickening-up trends in Unit 1 last into Unit 2, which is 65 m thick, mainly characterized by very thick-bedded floatstones and float- to rudstones. This unit is more coarsely grained and thicker bedded than Unit 1, with prevailing corals and red algae. Unit 2 represents open marine lagoonal conditions (SMF 8). Unit 3 is 25 m thick and defined by alternating of boundstones (SMF 7) and floatstones (SMF 8), the dominant bioclasts being corals. Unit 3 represents an open marine lagoon, and its top contains a coral patch reef complex. The limestones are typically pure as the influx of siliciclastic material was negligible. The corals indicate clean water, lacking high amounts of suspended fines, which is compatible with (1) the slow regional doming of the southerly located Jabal Akhdar and Saih Hatat domes after 30 Ma (low/moderate relief), (2) the absence of the South Asian Monsoon (limited fluvial discharge of fines) and (3) the long-term rise of the eustatic sea level during much of the Oligocene shifting the depocenter landward. The lagoon was likely protected by coral barrier reefs, separated by reef gaps, allowing for an efficient water exchange with the open ocean. The coral patch reefs formed within the lagoon. Based on the scattered outcrop pattern of the Ma'ahm Beds, we suggest that future facies maps of the easternmost part of the Arabian Plate should consider marly deposits as the most widespread Oligocene sediment, while pure limestones (patch reefs and their debris) should represent only small speckles on such maps. [ABSTRACT FROM AUTHOR]

This study demonstrates the effectiveness of integrating both velocity trend and effective stress in overpressure and sediment compaction prediction. Incorporating both strategies into overpressure forecasting is shown to be helpful in this study. The gamma ray, density, neutron, acoustic, and deep resistivity records from the X-Field deep offshore Niger Delta were used. These wells were X-001, 002, 003, and 004. The sediment compaction mechanism, attributed to differential sedimentation rates and grain size component, was predicted using a cross plot of compressional sonic velocity versus depth color coded with gamma ray log. Compaction disequilibrium is the dominant overpressure mechanism, as evidenced by the cross plot of sonic velocity against density, color coded with depth for wells X-001 and X-004. The wells' effective stress was plotted using density logs to create an overburden trend, and gamma ray logs were utilized to create shale volume logs. Overpressure prediction focused on the deformation behavior of shale formations since they are more sensitive to overpressure phenomena than sands, being denser and characterized by less resistant minerals. Therefore, shale bodies within the same depth range are more likely to experience loss of porosity and rise in density with depth, as demonstrated in the wells. Well X-001's computed normal compaction trend (NCT) indicates normal compaction from the surface to a depth of 2500 m; however, the NCT line deflects to the left at this depth, signaling the onset of overpressure; at this point, the well pressure is expected to exceed hydrostatic pressure. Beyond this depth, an increase in porosity in the overpressured shale was detected, leading to a decrease in sonic velocity below the usual compaction trend line. In well X-001, the TOV is located at this depth. Overpressure zones were also first detected in wells X-002 and X-004 at depths of 2400 and 2500 meters, respectively. Based on these results, it is likely that sediment compaction trends normalize at depths below 2500 m in the research area. The innovation in predicting sediment compaction and overpressure for deep-water operations in the Gulf of Guinea involves advanced geophysical and geological modeling techniques. [ABSTRACT FROM AUTHOR]

In the last century, old-growth forests in boreal and sub-boreal zone have decreased, along with their contribution to biological diversity. In order to carry on management strategies aimed at maintaining deadwood diversity in old-growth forests, it is fundamental to identify simply and readily measurable indicators. This study investigated the deadwood diversity in four old-growth forests in southern Finland. Five indicators of deadwood diversity (deadwood amount and diversity by species, component, decay class, water reservoir in logs) were estimated and analysed. The results showed an average deadwood volume of approximately 85±28 m3·ha−1 diversified by decay class and component. Besides, the results showed average Shannon index values four the four old-growth forests equal to 0.488 for deadwood species diversity, 0.932 for component diversity, and 1.286 for decay class diversity. The set of deadwood diversity indicators used in this study successfully supported the analysis of deadwood diversity in boreal and sub-boreal old-growth forests.

Recent exploration has revealed that the Middle Triassic Leikoupo Formation 32 Submember (T2l32) in the Sichuan Basin contains unconventional marl reservoirs with significant natural gas potential. Due to limited cores, old wells, and conventional logs, however, the lithological understanding of T2l32 is incomplete and relies solely on inaccurate mud logs. This lack of lithological foundation challenges geology and petroleum research. To identify complex lithology, this paper presents a double-hierarchical workflow to identify seven types of lithology using logs. The first order distinguishes salt, anhydrite, and marl, while the second order further subdivides marl into anhydrite marl, argillaceous limestone, shaly limestone, and limy shale. Different rocks’ logging response characteristics are summarized based on quantity-limited cores and micro-resistivity imaging logs. Lithological identification of 2D and 3D plots is established using sensitive GR, DEN, and RT. Corresponding identification standards are built in two hierarchies. According to these standards, the lithology of T2l32 is identified in a total of 119 wells. Finally, the lithological characteristics of vertical, horizontal, and plane are discussed in the research area. The research results may aid in comprehending the entire lithological characteristics of the complex marl reservoir in T2l32 of the Sichuan Basin. It would help the exploration potential of petroleum systems in turn.

Biodiversity loss due to intensive timber production is a ubiquitous conservation issue across temperate and boreal forest ecosystems. Retention forestry, the retention of deadwood and old-growth features within production forest, is one management strategy that has been implemented in various countries around the world to conserve a wide range of taxa within managed forests. The success and ecological implications of retention forestry are currently subject to intensive investigation and while some taxa like birds and insects have already been studied frequently, larger mammals have received less attention. Pine martens are one of the few larger mammals in central Europe preferring older forest and potentially profiting directly from deadwood retention as a consequence of implemented retention forestry. The goal of our study was to assess the response of European marten species to deadwood retention in montane mixed forests. Using marten detection rates from camera traps on 135 research plots we assessed the response of martens to deadwood at three different spatial scales using generalized linear mixed models. We found no effect of lying deadwood on marten detections at the plot scale (1 ha) or in a 10 m radius around the camera traps. However, we found a significant increase of marten detections if logs (> 10 cm in diameter) were directly in front and in view of the camera trap. Our results show that deadwood retention as a measure of retention forestry does affect microhabitat use of martens, but not stand selection during the growing season. Logs directly in view of the camera trap increase marten detection rates as martens choose to move and forage along fallen trees when they are available. When using camera trapping to collect data on martens, trap positioning in front of logs can heavily bias trapping results when unaccounted for. [ABSTRACT FROM AUTHOR]

Background: The relationship between educational outcomes and the use of web-based clinical knowledge support systems in teaching hospitals remains unknown in Japan. A previous study on this topic could have been affected by recall bias because of the use of a self-reported questionnaire. Objective: We aimed to explore the relationship between the use of the Wolters Kluwer UpToDate clinical knowledge support system in teaching hospitals and residents' General Medicine In-Training Examination (GM-ITE) scores. In this study, we objectively evaluated the relationship between the total number of UpToDate hospital use logs and the GM-ITE scores. Methods: This nationwide cross-sectional study included postgraduate year–1 and –2 residents who had taken the examination in the 2020 academic year. Hospital-level information was obtained from published web pages, and UpToDate hospital use logs were provided by Wolters Kluwer. We evaluated the relationship between the total number of UpToDate hospital use logs and residents' GM-ITE scores. We analyzed 215 teaching hospitals with at least 5 GM-ITE examinees and hospital use logs from 2017 to 2019. Results: The study population consisted of 3013 residents from 215 teaching hospitals with at least 5 GM-ITE examinees and web-based resource use log data from 2017 to 2019. High-use hospital residents had significantly higher GM-ITE scores than low-use hospital residents (mean 26.9, SD 2.0 vs mean 26.2, SD 2.3; P =.009; Cohen d =0.35, 95% CI 0.08-0.62). The GM-ITE scores were significantly correlated with the total number of hospital use logs (Pearson r =0.28; P <.001). The multilevel analysis revealed a positive association between the total number of logs divided by the number of hospital physicians and the GM-ITE scores (estimated coefficient=0.36, 95% CI 0.14-0.59; P =.001). Conclusions: The findings suggest that the development of residents' clinical reasoning abilities through UpToDate is associated with high GM-ITE scores. Thus, higher use of UpToDate may lead physicians and residents in high-use hospitals to increase the implementation of evidence-based medicine, leading to high educational outcomes. [ABSTRACT FROM AUTHOR]

Teachers' self-regulated learning (SRL) plays a crucial role in developing technological pedagogical content knowledge (TPACK), a complex professional skill. It is crucial to identify teachers' SRL activities that may lead to favorable TPACK. Previous studies have focused on the analysis of individual data sources from self-reported surveys or log files, which are insufficient to capture all SRL activities in the TPACK context. While multimodal learning analytics (MMLA) has the potential to improve SRL measurement, it remains unknown how multimodal data collected from different sources can be combined to identify salient features of SRL activities and examine how TPACK outcomes can be predicted by SRL activities identified from multimodal data. This study combined multimodal data from computer logs and think-aloud data to analyze teachers' SRL activities in designing a technology-integrated lesson. We identified the salient features of SRL from the combined data and explored how identified SRL activities might predict TPACK outcomes reflected in teacher-generated lesson plans. The results of random forest regression analysis show that three SRL activities from the logs and two from the think-aloud data formed the best combination that explained a significant proportion of variances in TPACK performance. The impact of MMLA in SRL measurement and the implication of this study are discussed. [ABSTRACT FROM AUTHOR]

The most promising alternative to the methyl bromide fumigation of exported logs is steam-heating the log in a vacuum. Research has confirmed that steam heating to 56 °C for 30 minutes kills all viable propagules of oak wilt pathogen (Bretziella fagacearum) in the sapwood of oak logs. The purpose of this study was to determine whether this heat-treatment method has any effect on the quality or value of white oak veneer logs shipped between the US and EU. Seventeen steam- and vacuum-treated and seventeen untreated control logs were shipped from Baltimore, Maryland to the Czech Republic, for processing into veneer, between December 2021 and February 2022. The treated and untreated logs were sawn into flitches, soaked in hot water vats, sliced, dried, and the veneer from each log was graded for quality. Each log was assigned a value based on the veneer quality and yield. The average value of treated log was 1,547 €/m³, and the average value of the untreated logs was 1,539 €/m³. The null hypothesis was statistically confirmed. Therefore, it is concluded that the 56 °C/30 min, sapwood heat treatment using vacuum and saturated steam had no adverse impact on the value of the white oak veneer logs.

The present study is developed in the areas of the Los Palacios Agroindustrial Base Business Unit, with the objective of increasing the yield of Eucalyptus pellita F Muell, and Eucalyptus saligna Smith sawn wood from the use of a combination of treatments to reduce the effect of growth stresses and sawing schemes. 200 logs of 4 m were used and through the two-factor ANOVA analysis, it was found that there are no significant differences between the species on the Cracking Index; considering also that the best results are obtained in logs stored with irrigation for Eucalyptus saligna and standing ringed trees for both species. From the application of the elimination method in the linear regression analysis, the conicity variable is excluded for the construction of the prediction model using the diameter of the logs as the only independent variable in the two equations obtained, which are characterized by presenting high coefficients of correlation, determination and low standard errors of estimation. Taking into consideration the sawing methods, it is defined that the best yields of sawn wood are obtained from alternative tangential sawing combined with the treatment of standing ringed trees. [ABSTRACT FROM AUTHOR]

Copyright of Revista Chapingo Serie Ciencias Forestales is the property of Universidad Autonoma Chapingo and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Acoustics is a field with significant application in wood science and technology for the classification and grading, through non-destructive tests, of a large variety of products from standing trees to building structural elements and musical instruments. In this review article the following aspects are treated: (1) The theoretical background related to acoustical characterization of wood as an orthotropic material. We refer to the wave propagation in anisotropic media, to the wood anatomic structure and propagation phenomena, to the velocity of ultrasonic waves and the elastic constants of an orthotropic solid. The acoustic methods for the determination of the elastic constants of wood range from the low frequency domain to the ultrasonic domain using direct contact techniques or ultrasonic spectroscopy. (2) The acoustic and ultrasonic methods for quality assessment of trees, logs, lumber and structural timber products. Scattering-based techniques and ultrasonic tomography are used for quality assessment of standing trees and green logs. The methods are based on scanning stress waves using dry-point-contact ultrasound or air-coupled ultrasound and are discussed for quality assessment of structural composite timber products and for delamination detection in wood-based composite boards. (3) The high-power ultrasound as a field with important potential for industrial applications such as wood drying and other applications. (4) The methods for the characterization of acoustical properties of the wood species used for musical instrument manufacturing, wood anisotropy, the quality of wood for musical instruments and the factors of influence related to the environmental conditions, the natural aging of wood and the effects of long-term loading by static or dynamic regimes on wood properties. Today, the acoustics of wood is a branch of wood science with huge applications in industry. [ABSTRACT FROM AUTHOR]

If a problem occurs on the network, IT professionals need to be sure that they will be notified and receive the necessary information to resolve it and prevent similar situations in the future. Notifications are an important element of network monitoring. When an abnormal behavior occurs on the network, the system must immediately notify IT professionals so that they can respond quickly. This is when this process becomes most effective. Network monitoring must include automatic notifications of failures and events that may affect performance. In the event of an error, such notifications should be sent via email, SMS, or other convenient channel. Dynamic networks require systems that can identify vulnerabilities in real time. Therefore, some network monitoring systems provide capabilities for collecting security data, such as network logs, application logs, and security messages. This data is collected and analyzed to detect anomalies, and in the event of threats, alerts can be sent to the appropriate IT professional. Thus, a network monitoring system allows you to: ensure a continuous workflow, monitor the status of the network and respond to possible problems in a timely manner, improve network efficiency, and increase network reliability and security. Given this, we can conclude that it is crucial to monitor networks and respond to problems in a timely manner for their successful operation. This requires the use of specialized monitoring systems that can quickly analyze the state of the network, identify problem areas, and notify the appropriate specialists. This work is focused on analyzing existing network monitoring systems, highlighting their pros and cons. The technologies and methodologies used to create such solutions were studied. A new monitoring system aimed at optimizing the process of tracking the status of network security was developed. The functionality of the system is enriched by sending notifications and implementing rules for tracking abnormal behavior in the network, which will help to better identify malicious actions and warn specialists in a timely manner. [ABSTRACT FROM AUTHOR]

Copyright of Coal Geology & Exploration is the property of Xian Research Institute of China Coal Research Institute and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Revista Chapingo Serie Ciencias Forestales is the property of Universidad Autonoma Chapingo and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The multifaceted role of deadwood in forest ecosystems has been widely recognized while it is regarded as an indicator of sustainable forest management. Nevertheless, there are hardly any data on deadwood volume and structure in managed forests in Greece. The study took place in beech forests of the Western and Central part of the Rodopi Mountain Range. The objective was to determine the amount, variability and quality of deadwood and to compare it with data from managed as well as natural forests. Data were collected on 30 randomly distributed circular plots of 0.1 ha. The results showed that the average deadwood amount (13.46 m3 ha−1) was much lower compared to that recorded in other European forests and they highlighted the absence of large dead standing trees due to the management regime. The deadwood quality showed great variation in stages of decay.

Advances in personalization of digital services are driven by low-cost data collection and processing, in addition to the wide variety of third-party frameworks for authentication, storage, and marketing. New privacy regulations,such asthe General Data Protection Regulation (GDPR) and the California Consumer Privacy Act, increasingly require organizations to explicitly state their data practices in privacy policies. When data practices change, a new version of the policy is released. This can occur a few times a year, when data collection or processing requirements are rapidly changing. Consent evolution raises specific challenges to ensuring GDPR compliance. We propose a formal consent framework to support organizations, data users, and data subjects in their understanding of policy evolution under a consent regime that supports both the retroactive and non-retroactive granting and withdrawal of consent. The contributions include (i) a formal framework to reason about data collection and access under multiple consent granting and revocation scenarios, (ii) a scripting language that implements the consent framework for encoding and executing different scenarios, (iii) five consent evolution use cases that illustrate how organizations would evolve their policies using this framework, and (iv) a scalability evaluation of the reasoning framework. The framework models are used to verify when user consent prevents or detects unauthorized data collection and access. The framework can be integrated into a runtime architecture to monitor policy violations as data practices evolve in real time. The framework was evaluated using the five use cases and a simulation to measure the framework scalability. The simulation results show that the approach is computationally scalable for use in runtime consent monitoring under a standard model of data collection and access and practice and policy evolution. [ABSTRACT FROM AUTHOR]

Dead wood, including coarse woody debris, CWD, and fine woody debris, FWD, plays a substantial role in forest ecosystem functioning. However, the amount and dynamics of dead wood in the forests of Northern Eurasia are poorly understood. The aim of this study was to develop a spatially distributed modelling system (limited to the territories of the former Soviet Union) to assess the amount and structure of dead wood by its components (including snags, logs, stumps, and the dry branches of living trees) based on the most comprehensive database of field measurements to date. The system is intended to be used to assess the dead wood volume and the amount of dead wood in carbon units as part of the carbon budget calculation of forests at different scales. It is presented using multi-dimensional regression equations of dead wood expansion factors (DWEF)—the ratio of the dead wood component volume to the growing stock volume of the stands. The system can be also used for the accounting of dead wood stock and its dynamics in national greenhouse gas inventories and UNFCCC reporting. The system's accuracy is satisfactory for the average level of disturbance regimes but it may require corrections for regions with accelerated disturbance regimes. [ABSTRACT FROM AUTHOR]

In tropical forests, especially in the Southeast Asia, there are only fragmentary estimates of coarse woody debris (CWD) pools and dynamics. Our study examines the volume and structural diversity of CWD in forests not affected by commercial felling in the territories of the Bidoup Núi Bà and Bù Gia M p National Parks of the Republic of Vietnam. In the lowland Dipterocarp forests of Bù Gia M p National Park, the average volume of CWD was almost two times lower than the average CWD stock in the mixed montane forests of Bidoup Núi Bà national park: 44 m3 ha–1 versus 78 m3 ha–1. The mass of CWD depended linearly on its volume and averaged 24 t ha–1. The projective cover of CWD averaged 269 m2 ha–1. Snags prevailed among the substrate categories (position types), accounting for 42 and 31% in the Bidoup Núi Bà and Bù Gia M p forests, respectively. The proportion of large branches in the montane forests of Bidoup Núi Bà National Park was 8%, while in the lowland forests of Bù Gia M p it reached 33% of the CWD volume. Very high termite activity was noted in the Bù Gia M p National Park—in 73% of the studied CWD pieces. The percentage of thermite tunnels partially filled with soil was, on average, 32% of the CWD volume. The high projective cover of CWD with various types of mass loss: consumption by invertebrates, white- and brown-rot decay suggests a significant role of CWD in the soil-forming processes. The similarities were revealed in the volume and size of CWD in the studied monsoon tropical forests of South Vietnam and in the primeval European boreal Norway spruce forests with fine-scale gap dynamics. The predominance of snags among the CWD categories and the nearly bell-shaped distribution of the CWD volume by decay classes complement the similarity of the CWD pool in tropical lowland and montane mixed forests with that in uneven-aged spruce boreal forests. However, a high proportion of branches in the structure of CWD, especially in lowland deciduous mixed forests distinguishes the CWD in tropical forests from the CWD in boreal and temperate forests. [ABSTRACT FROM AUTHOR]

Companies, institutions or governments process large amounts of data for the development of their activities. This knowledge usually comes from devices that collect data from various sources. Processing them in real time is essential to ensure the flow of information about the current state of infrastructure, as this knowledge is the basis for management and decision making in the event of an attack or anomalous situations. Therefore, this article exposes three unsupervised machine learning models based on clustering techniques and threshold definitions to detect anomalies from heterogeneous streaming cybersecurity data sources. After evaluation, this paper presents a case of heterogeneous cybersecurity devices, comparing WSSSE, Silhouette and training time metrics for all models, where K-Means was defined as the optimal algorithm for anomaly detection in streaming data processing. The anomaly detection's accuracy achieved is also significantly high. A comparison with other research studies is also performed, against which the proposed method proved its strong points. [ABSTRACT FROM AUTHOR]

Background: Cloud-native software systems often have a much more decentralized structure and many independently deployable and (horizontally) scalable components, making it more complicated to create a shared and consolidated picture of the overall decentralized system state. Today, observability is often understood as a triad of collecting and processing metrics, distributed tracing data, and logging. The result is often a complex observability system composed of three stovepipes whose data are difficult to correlate. Objective: This study analyzes whether these three historically emerged observability stovepipes of logs, metrics and distributed traces could be handled in a more integrated way and with a more straightforward instrumentation approach. Method: This study applied an action research methodology used mainly in industry–academia collaboration and common in software engineering. The research design utilized iterative action research cycles, including one long-term use case. Results: This study presents a unified logging library for Python and a unified logging architecture that uses the structured logging approach. The evaluation shows that several thousand events per minute are easily processable. Conclusions: The results indicate that a unification of the current observability triad is possible without the necessity to develop utterly new toolchains. [ABSTRACT FROM AUTHOR]

This paper describes an approach for computing the specific heat capacities of logs stored for long in an open warehouse. It includes the heat capacities of the wood of non-frozen and frozen zones in the logs and of both the frozen free and bound water in these zones, also the capacities formed by the release of the latent heat of both the free and bound water during their crystallization, as well as the effective specific heat capacities of logs stored in an open warehouse at periodically changing air temperature. The approach is based on the solutions of 2D models of the temperature distribution in logs during their alternating heating and cooling. Results from a simulative study of 2D unsteady temperature distribution and all types of the specific heat capacities of beech logs with a diameter of 0.4 m, length of 0.8 m, moisture content of 60%, and initial temperature of 0°C and 20°C during their 5 days and nights continous alternating heating, cooling, freezing and defrosting in an open warehouse at sinusoidal change of the ambient air temperature with various initial and different amplitudes in the range from –25°C to 40°C are graphically presented and analyzed. [ABSTRACT FROM AUTHOR]

Abstract This paper was developed within the scope of a PhD thesis that intends to characterize the use of mobile applications by the students of the University of Aveiro during class time. The main purpose of this paper is to present the results of an initial pilot study that aimed to fine-tune data collection methods in order to gather data that reflected the practices of the use of mobile applications by students in a higher education institution during classes. In this paper we present the context of the pilot, its technological settings, the analysed cases and the discussion and conclusions carried out to gather mobile applications usage data logs from students of an undergraduate degree on Communication Technologies. Our study gathered data from 77 participants, taking theoretical classes in the Department of Communication and Arts at the University of Aveiro. The research was based on the Grounded Theory method approach aiming to analyse the logs from the access points of the University. With the collected data, a profile of the use of mobile devices during classes was drawn. The preliminary findings suggest that the use of apps during the theoretical classes of the Department of Communication and Art is quite high and that the most used apps are Social networks like Facebook and Instagram. During this pilot the accesses during theoretical classes corresponded to approximately 11,177 accesses per student. We also concluded that the students agree that accessing applications can distract them during these classes and that they have a misperception about their use of online applications during classes, as the usage time is, in fact, more intensive than what participants reported.

Assessing intrinsic wood qualities such as modulus of elasticity and internal decay in trees and logs can be challenging. However, acoustic technologies have been investigated for a possible solution. This paper reviews available literature on non-destructive acoustic methods for assessing wood quality, both in tree and log form. The paper further reviews the effects of silvicultural practices (such as thinning and pruning) on wood quality assessed by nondestructive acoustic methods. We documented some of the benefits of application of nondestructive acoustic methods on wood quality of trees and logs. The acoustic velocity of a tree (VT) or log (VL) of the propagated waves and wood density can be used to determine the Dynamic Modulus of Elasticity (MOEd). Thinning was reported to affect VT/VL and MOEd negatively. Acoustic tomography methods were equally found to have good accuracy in detecting the location and extent of wood decay in standing trees and logs. [ABSTRACT FROM AUTHOR]

The issue of poor aqueous solubility is often a great hitch in the development of liquid dosage forms for those drugs that the Biopharmaceutics Classification System (BCS) includes in classes II and IV. Among the possible technological solutions, inclusion of the drug molecule within polymeric micelles, and particularly nanomicelles, has been proposed in the last years as a valid strategy. Our attention has been recently attracted by Soluplus®, an amphiphilic polyvinyl caprolactam-polyvinyl acetate-polyethylene glycol graft copolymer able to form small and stable nanomicelles. The aim of this study was to characterize Soluplus® nanomicelles to enhance the apparent solubility of three model APIs, categorized in BCS class II: ibuprofen (IBU), idebenone (IDE), and miconazole (MIC). Drug-loaded Soluplus® micelles with a mean size around 60–70 nm were prepared by two methods (direct dissolution or film hydration method). The prepared nanosystems were characterized in terms of mean particle size and Zeta potential, physical stability, drug solubility, and in vitro drug release. The solubility of the tested APIs was shown to increase linearly with the concentration of graft copolymer. Soluplus® can be easily submitted to membrane filtration (0.2 µm PES or PTFE membranes), showing the potential to be sterilized by this method. Freeze-drying enabled to obtain powder materials that, upon reconstitution with water, maintained the initial micelle size. Finally, viscosity studies indicated that these nanomicelles have potential applications where a bioadhesive material is advantageous, such as in topical ocular administration. [ABSTRACT FROM AUTHOR]