Time Budget Research Articles

Budget-aware Query Tuning: An AutoML Perspective

Modern database systems rely on cost-based query optimizers to come up with good execution plans for input queries. Such query optimizers rely on cost models to estimate the costs of candidate query execution plans. A cost model represents a function from a set of cost units to query execution cost, where each cost unit specifies the unit cost of executing a certain type of query processing operation (such as table scan or join). These cost units are traditionally viewed as constants, whose values only depend on the platform configuration where the database system runs on top of but are invariant for queries processed by the database system. In this paper, we challenge this classic view by thinking of these cost units as variables instead. We show that, by varying the cost-unit values one can obtain query plans that significantly outperform the default query plans returned by the query optimizer when viewing the cost units as constants. We term this cost-unit tuning process 'query tuning' (QT) and show that it is similar to the well-known hyper-parameter optimization (HPO) problem in AutoML. As a result, any state-of-the-art HPO technologies can be applied to QT. We study the QT problem in the context of anytime tuning, which is desirable in practice by constraining the total time spent on QT within a given budget-we call this problem budgetaware query tuning. We further extend our study from tuning a single query to tuning a workload with multiple queries, and we call this generalized problem budgetaware workload tuning (WT), which aims for minimizing the execution time of the entire workload. WT is more challenging as one needs to further prioritize individual query tuning within the given time budget. We propose solutions to both QT and WT and experimental evaluation using both benchmark and real workloads demonstrates the efficacy of our proposed solutions.

Time allocation among different sorts of activities: An overview of mathematical models

The history of time use research dates back more than 100 years. Russian scientists were among the first to conduct large-scale surveys in this field. Nowadays, this sphere has become interesting among scientists again. Rosstat has rebegun to conduct surveys on the daily time use, large-scale independent surveys have appeared, and media have increased their interest. The amount of empirical microdata that has emerged has made it possible to examine a complex concept as the household time use in ever more numbers. The purpose of this methodological overview is to describe the most significant mathematical models that have been used and are being used to study the time budgets of the population. This article overviews the first models in which time was considered as one of the means of production along with other goods, and households tried to maximize the utility function solely based on financial considerations. Then, modern models, where time is no less an important factor of well-being than material status, are represented. The article demonstrates how the new model classes that have recently emerged adapt to the data that is accessible in certain circumstances, modify themselves to accomplish fresh tasks, and become less costly when looking at analytical estimations. In order to categorize the population’s time budget structure under different research activities, the paper examines and systemsatizes a number of mathematical models

The behavior patterns of giraffes (Giraffa camelopardalis) housed across 18 US zoos.

Interpreting animal behavior in the context of welfare can be inherently challenging given the limited behavior data available for many species housed in zoos. Describing common behavior patterns may help animal managers by providing additional background when assessing the individuals in their care. Although valuable, these efforts require a large, collaborative approach and have, consequently, been rare. Here, we share the behavior patterns of zoo-housed giraffes, an iconic and commonly housed megafauna in zoos. Behavior data were evaluated for 66 giraffes living across 18 AZA-accredited zoos using the ZooMonitor Community platform. Data were recorded during 10-minute observation sessions. Observations were conducted during daytime hours over the course of approximately one year at each zoo (mean total observed time per individual = 23.2 hr). The most common behaviors observed were feeding/ foraging behaviors, which accounted for 38.6% of the mean visible time budget across giraffes. Time spent in these behaviors varied by individual and ranged from 14.3% to 69.3% of visible time. Stereotypic behaviors occurred in all study individuals, with oral stereotypic behaviors being most common. Although prevalent, stereotypic behaviors varied considerably across giraffes, with some individuals exhibiting these behaviors only on a few occasions to an individual that exhibited these behaviors once every few minutes. This study provides a robust evaluation of giraffe behavior across zoos to present a picture of their common behavior patterns in managed care. We hope these multi-institutional behavior patterns can provide perspective to aid animal managers in evaluating giraffes in their care.

Diurnal Activity Budgets and Feeding Habits of Grivet Monkey (Chlorocebus aethiops aethiops) in Fragmented Moist Afromontane Forest

ABSTRACTGrivet monkeys (Chlorocebus aethiops aethiops) are opportunistic omnivores and extremely adaptable in both rural and urban environments. A study was conducted out in human‐dominated fragmented moist Afromontane forest of wondo genet to investigate the diurnal activity budgets and feeding habits of grivet monkey. Data collection was carried out from February to September 2022 covering both wet and dry seasons. During each scan, individuals were recorded as performing one of the following activities: feeding, moving (searching for food), resting, grooming, playing and others such as drinking, vocalisation and defecation, or aggression and sexual activity. Dietary composition and preferences were assessed using scan sampling method. Proximate analysis was conducted to examine the nutritional makeup of feeding food items. The greatest proportion of the activity time budget of the grivet monkey was devoted to feeding, resting and moving, with relatively higher time devoted to feeding and moving and less time devoted to resting when compared with grivet monkeys inhabiting natural habitats. Grivet monkey utilised 42 food items grouped into 41 plant species and 1 insect. Psidium guava and Desmodium intortum, relatively with higher crude protein and less fibre, were the most preferred plants consumed. The study has pointed out that grivet monkeys in the human‐dominated landscape of Wondo Genet remnant moist afromontane forest tend to prefer to consume on fruit tress such as Persea americana, Mangifera indica and Psidium guava, which contain high nutritional content that are planted and managed around homesteads. It is recommended to plant and sustainably manage grivet monkeys' natural foods in human‐dominated landscape of Wondo Genet remnant moist afromontane forest to sustainably conserve the species and avoid/reduce human‐grivet monkey conflict.

Partial migration pays off in black-faced cormorants: insights from post-breeding GPS tracking

Seasonal variation in food availability or adverse weather patterns can create challenging conditions for year-round survival. Birds experiencing such fluctuations may migrate to locations with better food availability in the non-breeding period. While some species are obligate migrants, others are facultative migrants where various post-breeding strategies exist within populations. Several cormorant and shag species are facultative migrants with a range of post-breeding movement strategies within populations. Currently, most of the information available on cormorant post-breeding strategies originates from banding studies and little is known about their movements, time budget or habitat use during the non-breeding period. In the present study, Australian endemic black-faced cormorants (Phalacrocorax fuscescens), breeding on Notch Island, Victoria, were tracked with GPS data loggers during the non-breeding period. Different post-breeding strategies were observed. Individuals were either resident (N = 36, 69%), remaining within a short distance of the colony (16.7 ± 2.2 km) or migratory (N = 16, 31%), travelling greater distances (250.7 ± 24.4 km) to establish a new central place foraging location. Data from individuals which covered the entire non-breeding period indicated that, across strategies, individual birds had one area of residency during the non-breeding period. Migratory individuals were found to have lower daily activity levels, spending less time flying and foraging, than resident individuals during the early non-breeding period, possibly indicating that they had access to greater prey resources. Regardless of the post-breeding strategy, individuals utilised foraging locations that were of similar seabed depths year-round suggesting individual specialisation in prey resources or foraging habitats.

QCLUE: a quantum clustering algorithm for multi-dimensional datasets

Clustering algorithms are at the basis of several technological applications, and are fueling the development of rapidly evolving fields such as machine learning. In the recent past, however, it has become apparent that they face challenges stemming from datasets that span more spatial dimensions. In fact, the best-performing clustering algorithms scale linearly in the number of points, but quadratically with respect to the local density of points. In this work, we introduce qCLUE, a quantum clustering algorithm that scales linearly in both the number of points and their density. qCLUE is inspired by CLUE, an algorithm developed to address the challenging time and memory budgets of Event Reconstruction (ER) in future High-Energy Physics experiments. As such, qCLUE marries decades of development with the quadratic speedup provided by quantum computers. We numerically test qCLUE in several scenarios, demonstrating its effectiveness and proving it to be a promising route to handle complex data analysis tasks – especially in high-dimensional datasets with high densities of points.

Effect of temporal water restrictions on drinking behavior and time budget in lactating dairy cows according to their position in the social hierarchy within the herd

On dairy farms, milking practices can temporarily restrict cows from accessing drinking water. This study examined how different types of temporary water restriction, similar to those commonly encountered on farms, may affect the individual behavior and physiological dehydration status of cows and whether these effects could differ according to the cow's position in the social hierarchy of the group. Four treatments were applied (CTRL = free access to the drinker and feed fence, HL = 2 h of headlock at the feed fence after morning and evening milking, D2H = free access to the feed fence and no access to water for 2 h after milking and D4H = free access to the feed fence and no access to water for 4 h after milking) to 4 groups of 10 lactating dairy cows using a 4 × 4 Latin square design. Each treatment period lasted 1 week. The cows were housed within a free-stall barn, and each group was in a pen equipped with 1 electronic drinker, 10 individual feeders, and 2 cameras. Cow social dominance hierarchies were characterized using normalized David's scores, which were calculated from video-detected replacements at each pen's drinker. During the last 4 d of each treatment period, drinking behavior was measured using interconnected drinkers, and eating, idle, and lying times were measured using accelerometers. On d 6 of each treatment period, during the morning and evening milkings, blood and then milk samples were collected to analyze bioindicators of dehydration and milk composition, respectively. The daily water intake of cows was unaffected by either social dominance or treatment type. Drinking rate and drinking bout frequency were higher during the HL, D2H, and D4H treatments than during the CTRL treatment, and drinking time was lower during the D4H treatment than during the CTRL treatment. Hourly lying time decreased at the end of the water restriction periods, i.e., at 1000 h in HL, at 1100 h in D2H, and at 1200 and 1300 h in D4H, which was not observed in CTRL, which could be interpreted as a sign of cow discomfort. For blood collected before the morning milking, hematocrit levels were lower in the D4H treatment than in the HL treatment. For blood collected before the evening milking, creatinine concentrations were lower in the D4H treatment than in the D2H treatment, with a greater difference seen for dominant cows than for subordinate cows. For both milkings, milk freezing point was higher in the HL, D2H, and D4H treatments than in the CTRL treatment, indicating dilution. In contrast to the other social categories, subordinate cows made more daily visits to the drinker during the D4H treatment than during the CTRL treatment but displayed no differences in drinking bout duration or the duration of drinking interruptions within bouts in the D2H treatment compared with the CTRL treatment. Overall, cows were able to maintain their water intake despite the temporary water restrictions when they had access to the number of drinkers recommended by animal welfare guidelines. That said, their idle and lying time appeared to be disturbed.

The Influence of Internal Control and Client Importance on Audit Quality with Time Budget Pressure as a Moderating Variable

This study aims to empirically examine the influence of internal control and client importance on audit quality, with time budget pressure as a moderating variable. The data used in this study was sourced from a questionnaire survey distributed to respondents in March via Google Forms. Respondents were selected using purposive sampling, with criteria including junior auditors, senior auditors, and Managing Partners (leaders) from audit firms (KAP) in Bogor, Jakarta, Bali, and East Java. The final sample used in this study was 50 observations. The results of this study show that client importance has a negative effect on audit quality. Internal control has a positive effect on audit quality. Time budget pressure moderates the relationship between client importance and audit quality in a positive direction. Time budget pressure moderates the relationship between internal control and audit quality in a negative direction. Time budget pressure itself has a positive effect on audit quality. Keywords: Internal Control, Client Importance, Kualitas Audit dan Time Budget Pressure

Urban family with minor children: resources, moral guidelines and social adaptation of working parents. Part one

The first part of the article presents the results of studying the daily activities of working parents in the field of caring for minor children and their upbringing. Data from monitoring studies of the daily activities and time budget of urban residents carried out during 1986-2020 were used. The composition of families with children is considered and the resource characteristics of parents are analyzed, which turned out to be very similar for fathers and mothers. The relationship of parents' time spent on caring for children and their upbringing with parents' belonging to fathers and mothers, with their age, level of education, religious identity and income level in parents' families, as well as with some value orientations of fathers and mothers, is investigated. The analysis showed that the objective picture of working parents using time resources for activities with children does not agree with their subjective opinion that “activities with their childre n, their upbringing is the most important thing in the life of both spouses”. At the same time, most working fathers and mothers are satisfied with the time spent both on caring for children and on their upbringing as time resources. The characteristics of the provision of fathers and mothers with other resources do not affect their satisfaction with time spent. There is a direct relationship between satisfaction with the time spent on raising children and parents' satisfaction with life in general. An analysis of the moral guidelines of parents, which are the moral basis for the process of socialization of minor children in the family, has shown that more than half of the moral qualities related to virtues are the norm for the vast majority of fathers and to a somewhat lesser extent for mothers. At the same time, there is a tendency to blur parents' ideas about qualities-virtues and anti-virtues as a norm and deviation from it. In addition, a trend is emerging in which, judging by estimates, a considerable part of parents do not see a positive life prospect for their children, in terms of their social adaptation, if children in life are guided by the same virtues as the parents themselves. The first part in the article analyzes the composition and resource potential and the use of time resources of parents for child care and upbringing. The second part will be about the moral guidelines and the results of social adaptation of working parents. The numbering of tables and figures is continuous in both parts.

The impact of restricted grazing systems on the behaviour and welfare of ponies.

Equine obesity is a growing concern. Much of the current management advice centres on dietary restrictions, including the removal or limitation of grazing. Little is known about the impact of these approaches on the welfare of the horse. This study investigates the effect of two commonly used grazing systems advocated for the control of weight-the 'strip-grazing' and the 'track' systems-on the behaviour and welfare of outdoor-living ponies. A within-subject cross-over experimental design with four groups of pasture-kept ponies experiencing each system for 4 weeks in a random order. Time budgets and behavioural indicators of welfare were measured using 24-h electronic surveillance, morphometric parameters including weight, body condition score and cresty neck score were measured weekly and activity levels were tracked. The effect of grazing system on movement and behaviour was tested using a general linear model. Ponies moved more [median (IQR) % time spent moving, track: 3.23% (2.08%), strip: 2.02% (0.90%); p = 0.001] and travelled a greater distance [median (IQR) metres/24 h, track: 7013.47 m (1761.49 m), strip: 5331.91 m (494.16 m); p < 0.001] and engaged in less overt agonistic behaviour on the track system compared with the strip system [median (IQR) prevalence per hour; track: 0.14 (0.30), strip: 0.21 (0.37) p = 0.02]. A relatively short time period of exposure to each grazing system. Ponies on strip systems moved less and exhibited increased agonistic interactions compared with the track system, maybe as a result of a perceived reduction in space or concentration of resources, although the accessible areas were matched. These results suggest that there may be physical as well as psychological health benefits to the track system.

PSII-8 The effects of diet and finishing phase on the behavioral time budgets of feedlot cattle

Abstract Feedlot cattle undergo many transitions in diet, social group structure, and environment during the finishing period. Little is known about how their behavior may be altered by these transitions. The objective of our pilot project was to compare the behavior of younger feedlot cattle fed a low-concentrate diet to that of finishing cattle, and to create 24-h time budgets for activity and oral behaviors in these groups. Cattle [n = 20; body weight (BW) = 305 ± 21 kg, mean ± SD] were fed a low-concentrate feedlot diet (60:40, concentrate:forage; ST) and cattle (n = 20; BW = 522 ± 45 kg) received a finishing diet (90:10, concentrate:forage; FI) twice daily. Animals were separated by diet and housed in groups of 10. Trained observers recorded behaviors of each group by live instantaneous recording every 5 min for a continuous 48 h, resulting in 192 h of data collected. We predicted that ST cattle would spend more time eating and ruminating due to the higher forage diet. We also expected that FI animals would rest more and spend less time standing and walking as a result of being more familiar with the environment and their social group structure. We also quantified a wide range of oral behaviors including rumination, grooming and manipulation of non-feed items in the pen. Behaviors were summarized by 24-h period, animal, group, and diet, then averaged by animal, and then averaged again by group (n = 2/diet). Missing values accounted for 3% of the activity data and 11% of the oral behaviors. T-tests revealed that ST cattle ruminated more than FI (352 ± 3 vs. 304 ± 1 min/d, mean ± SE, P = 0.02), but differences between treatments were not detected for time spent eating (196 ± 15 vs. 131 ± 3 min/d), standing (584 ± 13 vs. 588 ± 29 min/d), walking (46 ± 10 vs. 35 ± 5 min/d), or lying (768 ± 16 vs. 772 ± 7 min/d; P ≥ 0.13). When fed the ST diet, cattle spent 5 ± 2 min/d grooming group mates, while FI cattle groomed others for 11 ± 1 min/d, although this was not analyzed statistically because it was rare. Similarly, there were numerical differences in the amount of time spent orally manipulating non-food items (8 ± 3 and 18 ± 1 min/d for ST and FI animals, respectively) that have not been previously described. These results suggest that behavioral differences might be more apparent with larger sample sizes, but with the present experimental design, the predictions were not supported. Nonetheless, these are the first behavioral observations of feedlot cattle and provide a comprehensive time budget of their activity, including a range of oral behaviors over a 48-h period.

393 The role of on-animal sensors in understanding feed intake, behavior, and performance of grazing livestock

Abstract Intake by grazing animals is difficult to reliably measure in the field, particularly in more diverse grazing systems where pastures vary greatly across time and space in resource availability, which in turn leads to greater variation in animal time budgets and intake patterns. Advances in remote livestock monitoring (e.g., on-animal sensors, walk -over-weighing), and advanced analytics such as machine learning algorithms can contribute to the development of robust, adaptable tools for better understanding of animal performance and behavior in grazing systems. Many existing tools for predicting livestock production require estimates of feed intake, and while estimates based on forage sward characteristics have been developed and used for temperate, relatively homogenous pastures, they are less well defined for more diverse rangelands. These diverse pastures are more difficult to characterize due to their greater variation in quantity and quality; consequently, animal selectivity is greater in more variable pastures. However, such feedback loops between pasture diversity and animal behavior may not yet be adequately represented in biophysical models. On-animal sensors such as accelerometers and GPS devices can be used to develop new ways of assessing relative intake by providing accurate estimates of animal location and behavior profiles, such as the use of machine learning algorithms to detect how much time is spent grazing, walking, ruminating, or resting. Measurements of animal behavior could then be combined with other animal-based methods such as walk-over-weighing and fecal NIR to improve estimates of intake and production for a wide range of extensive grazing environments. Sensor-derived measurements of animal movement could also be used to improve estimates of the energetic costs of grazing, thereby improving estimates of energy available for growth. As an example, data on recent activity and paddock use from on-animal sensors could be entered into a model to estimate current feeding requirements, then combined with weather and pasture quality forecasts. The ensuing baseline could then be used to explore the potential variability of these projections and generate a range for possible expected performance over the next month or season. This approach could be repeated over time, and animal performance and behavior measures used to update model estimates and improve forward projections. These methods could also be used in conjunction with estimates of animal energy requirements to provide real-time prediction of relative feed intake, which would provide a step-change in modelling livestock production in extensive grazing systems. For these approaches to be successful, additional calibration data are needed across a wide variety of environments and species, and the tools must be cost-effective to implement. In summary, on-animal measurements provide an adaptable, data-driven approach that could be integrated with existing tools to improve our understanding of feed intake, behavior, and performance of grazing animals.

Optimizing encoding strategies for 4D Flow MRI of mean and turbulent flow

For 4D Flow MRI of mean and turbulent flow a compromise between spatiotemporal undersampling and velocity encodings needs to be found. Assuming a fixed scan time budget, the impact of trading off spatiotemporal undersampling versus velocity encodings on quantification of velocity and turbulence for aortic 4D Flow MRI was investigated. For this purpose, patient-specific mean and turbulent aortic flow data were generated using computational fluid dynamics which were embedded into the patient-specific background image data to generate synthetic MRI data with corresponding ground truth flow. Cardiac and respiratory motion were included. Using the synthetic MRI data as input, 4D Flow MRI was subsequently simulated with undersampling along pseudo-spiral Golden angle Cartesian trajectories for various velocity encoding schemes. Data were reconstructed using a locally low rank approach to obtain mean and turbulent flow fields to be compared to ground truth. Results show that, for a 15-min scan, velocity magnitudes can be reconstructed with good accuracy relatively independent of the velocity encoding scheme (SSIMU=0.938±0.003)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$SSI{M}_{U}=0.938\\pm 0.003)$$\\end{document}, good accuracy (SSIMU≥0.933\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$SSI{M}_{U}\\ge 0.933$$\\end{document}) and with peak velocity errors limited to 10%. Turbulence maps on the other hand suffer from both lower reconstruction quality (SSIMTKE≥0.323\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$SSI{M}_{TKE}\\ge 0.323$$\\end{document}) and larger sensitivity to undersampling, motion and velocity encoding strengths (SSIMTKE=0.570±0.110)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$SSI{M}_{TKE}=0.570\\pm 0.110)$$\\end{document} when compared to velocity maps. The best compromise to measure unwrapped velocity maps and turbulent kinetic energy given a fixed 15-min scan budget was found to be a 7-point multi-Venc\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${V}_{enc}$$\\end{document} acquisition with a low Venc\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${V}_{enc}$$\\end{document} tuned for best sensitivity to the range of expected intra-voxel standard deviations and a high Venc\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${V}_{enc}$$\\end{document} larger than the expected peak velocity.

Enclosure design and welfare of plains zebras: Impact of enclosure design on behavior and space use of plains zebras under human care

ABSTRACT Plains zebras are commonly hosted in zoos, but few welfare-related studies are available in the literature. This research aimed to assess the effect of enclosure design on two groups of captive zebras housed at the Giardino Zoologico di Pistoia – GZP (Italy) and Parco Faunistico Valcorba – PFV (Italy) through the analysis of behavior and enclosure use. The groups consisted of an adult pair and a male juvenile at GZP and six adult females at PFV. We collected data in 2019 over 19 sampling days using the continuous focal animal sampling technique. We performed 12 observation sessions per day, with each session lasting 30 min. We analyzed the subjects’ behavioral time budget and enclosure use using Generalized Linear Mixed Models and the Electivity Index. The results showed that the time allocated to feeding behavior varied from 8–16% in the enclosure with gravel substrate (GZP) to 72–85% in the exhibit enriched with a pasture (PFV), with this last percentage resembling data reported for wild zebras. Results showed that institution was a significant predictor of feeding behavior, suggesting that the presence of a pasture can stimulate food-related behavioral patterns. Regarding enclosure use, the presence of hay and water troughs influenced the animals’ space use. Our findings also suggest that evaluating both behavior and enclosure use can provide a more comprehensive overview of the welfare state of the animals. However, future studies are needed to better investigate the influence of social factors on the behavior and enclosure usage of captive Plains zebras.

Convergent least-squares optimization methods for variational data assimilation

Data assimilation combines prior (or background) information with observations to estimate the initial state of a dynamical system over a given time-window. A common application is in numerical weather prediction where a previous forecast and atmospheric observations are used to obtain the initial conditions for a numerical weather forecast. In four-dimensional variational data assimilation (4D-Var), the problem is formulated as a nonlinear least-squares problem, usually solved using a variant of the classical Gauss-Newton (GN) method. However, we show that GN may not converge if poorly initialized. In particular, we show that this may occur when there is greater uncertainty in the background information compared to the observations, or when a long time-window is used in 4D-Var allowing more observations. The difficulties GN encounters may lead to inaccurate initial state conditions for subsequent forecasts. To overcome this, we apply two convergent GN variants (line search and regularization) to the long time-window 4D-Var problem and investigate the cases where they locate a more accurate estimate compared to GN within a given budget of computational time and cost. We show that these methods are able to improve the estimate of the initial state, which may lead to a more accurate forecast. Highlights Poor initialization of Gauss-Newton method may result in failure to converge. Safeguarded Gauss-Newton improves initial state estimate within limited time/cost. Results using twin experiments with long time-window and chaotic Lorenz models. Apply state of the art least-squares convergence theory to data assimilation. Improvements to initial state estimate may lead to a more accurate forecast.

Red Flags, Competence, Time Budget Pressure and Audit Risk: Effect on Auditor’s Ability to Detect Fraud

Red Flags, Competence, Time Budget Pressure and Audit Risk: Effect on Auditor’s Ability to Detect Fraud

Time budgets and weight shifting as indicators of pain in hospitalized horses.

Pain assessment in horses presents a significant challenge due to their nonverbal nature and their tendency to conceal signs of discomfort in the presence of potential threats, including humans. Therefore, this study aimed to identify pain-associated behaviors amenable to automated AI-based detection in video recordings. Additionally, it sought to determine correlations between pain intensity and behavioral and postural parameters by analyzing factors such as time budgets, weight shifting, and unstable resting. The ultimate goal is to facilitate the development of AI-based quantitative tools for pain assessment in horses. A cohort of 20 horses (mean age 15 ± 8) admitted to a university equine hospital underwent 24-h video recording. Behaviors were manually scored and retrospectively analyzed using Loopy® software. Three pain groups were established based on the Pain Score Vetmeduni Vienna : pain-free (P0), mild to moderate pain (P1), and severe pain (P2). Weight shifting emerged as a reliable indicator for discriminating between painful and pain-free horses, with significant differences observed between pain groups (p < 0.001) and before and after administration of analgesia. Additionally, severely painful horses (P2 group) exhibited lower frequencies of feeding and resting standing per hour compared to pain-free horses, while displaying a higher frequency of unstable resting per hour. The significant differences observed in these parameters between pain groups offer promising prospects for AI-based analysis and automated pain assessment in equine medicine. Further investigation is imperative to establish precise thresholds. Leveraging such technology has the potential to enable more effective pain detection and management in horses, ultimately enhancing welfare and informing clinical decision-making in equine medicine.

The Impact of Competence, Accountability, Professional Skills, and Professional Skepticism on Audit Quality with Time Budget Pressure as a Moderating Variable

The Impact of Competence, Accountability, Professional Skills, and Professional Skepticism on Audit Quality with Time Budget Pressure as a Moderating Variable

Per-Instance Algorithm Configuration in Homogeneous Instance Spaces: A Use Case in Reconfigurable Assembly Systems

The physical capabilities of a reconfigurable assembly system (RAS) increase the agility and responsiveness of the system in highly volatile market conditions. However, achieving optimal RAS utilization entails solving complex optimization problems effectively and efficiently. These optimizations often define homogenous sets of problem instances. While algorithm configuration in such homogeneous contexts traditionally adopts a “one-size-fits-all” approach, recent studies have shown the potential of per-instance algorithm configuration (PIAC) methods in these settings. In this work, we evaluate and compare the performance of different PIAC methods in this context, namely Hydra—a state-of-the-art PIAC method—and a simpler case-based reasoning (CBR) approach. We evaluate the impact of the tuning time budget and/or the number of unique problem instances used for training on each of the method’s performance and robustness. Our experiments show that whilst Hydra fails to improve upon the default algorithm configuration, the CBR method can lead to 16% performance increase using as few as 100 training instances. Following these findings, we evaluate Hydra’s methodology when applied to homogenous instance spaces. This analysis shows the limitations of Hydra’s inference mechanisms in these settings and showcases the advantages of distance-based approaches used in CBR.

The k-th order mean-deviation model for route choice under uncertainty

This study introduces the k-th order mean-deviation model for optimizing route choice within large, stochastic, and time-variant networks. This model addresses the limitations of the traditional mean-standard deviation approach by better handling extreme outcomes in travel times. It features an objective function called the “travel time budget”, which combines the average path travel time with a safety margin. This margin is defined by a trade-off coefficient and a selected deviation measure (total or semi) of the travel time. The model is divided into three variations: 1) The mean-total deviation (MTD) model for symmetric travel time distributions, 2) The mean-upper-semi-deviation (MUSD) model for asymmetric distributions prioritizing upper semi-deviations, suitable for risk-averse travelers, and 3) The mean-lower-semi-deviation (MLSD) model for asymmetric distributions focusing on lower semi-deviations, preferred by risk-prone individuals. We explore these models’ alignment with the stochastic dominance (SD) rule and develop a solution methodology based on SD principles. Numerical experiments in two real-world transportation networks demonstrate the models’ effectiveness and show how the choice of deviation affects route selection decisions.