Irregular Events Research Articles

Seasonal refuge patterns of phytoplankton trigger irregular bloom events in a contaminated environment

Several experimental evidences and field data documented that zooplankton may alter its behavioral response in the presence of toxic phytoplankton, reducing its consumption to the point of starvation. This paper is devoted to the mathematical study of such interactions of toxic phytoplankton with grazer zooplankton. The non-toxic phytoplankton is assumed to adopt a density-dependent refuge strategy to avoid over-predation by zooplankton. Both groups of phytoplankton are assumed to suffer direct harm from anthropogenic toxicants, while zooplankton is affected indirectly by ingesting contaminated phytoplankton. We calibrate the proposed model with the field data from Talsari and Digha Mohana, India, and estimate some crucial model parameters consistent with the behavior of the observed data. Our results demonstrate that zooplankton grazing on toxic phytoplankton plays a key role in the emergence or mitigation of plankton blooms. We also highlight the system’s potential to exhibit multiple stable configurations under the same ecological conditions. The plankton system experiences significant regime shifts, which are explored through various bifurcation scenarios, such as transcritical and saddle-node bifurcations. These shifts are influenced by changes in refuge capacity, species growth rates, and environmental carrying capacity. Furthermore, we incorporate environmental variations due to seasonal periodic or almost periodic changes, allowing the refuge parameter to be time-dependent. We observe that the forced system exhibits double periodic solutions. Moreover, stronger seasonal variations in the refuge pattern lead to irregular chaotic blooms. In conclusion, the results offer valuable insights into the sustainability of biodiversity, potentially shedding light on the origin of diverse plankton bloom phenomena.

Predictive Gaze Analytics: A Comparative Case Study of the Foretelling Signs of User Performance during Interaction with Visualizations of Ontology Class Hierarchies

The current research landscape in ontology visualization has largely focused on tool development, yielding an extensive array of visualization tools. Although many existing solutions provide multiple ontology visualization layouts, there is limited research in adapting to an individual user’s performance, despite successful applications of adaptive technologies in related fields, including information visualization. In an effort to innovate beyond traditional one-size-fits-all visualizations, this paper contributes one step towards realizing user adaptive visualization by recognizing timely moments when users may potentially need intervention, as real-time adaptation can only occur if it is possible to correctly predict user success and failure during an interaction in the first place. In addition, an open-source, reusable, and extensible software: Beach Environment for the Analytics of Human Gaze (BEACH-Gaze) is made available to the broader scientific community interested in descriptive and predictive gaze analytics. Building on a wealth of research in eye tracking, this paper compares four approaches to predictive gaze analytics through a series of experiments that utilize scheduled gaze digests, irregular gaze events, the last known gaze status, as well as all gaze captured for a user at a given moment in time. The results from a set of experimental trials suggest that irregular gaze events are most informative of early predictions of user performance, whereas cognitive workload appears to be most indicative of overall user performance in the task scenario presented in this paper. These empirical findings highlight the importance of an analytical approach to gaze on user predictions and indicate careful consideration when applying.

AONet: Attention network with optional activation for unsupervised video anomaly detection

AbstractAnomaly detection in video surveillance is crucial but challenging due to the rarity of irregular events and ambiguity of defining anomalies. We propose a method called AONet that utilizes a spatiotemporal module to extract spatiotemporal features efficiently, as well as a residual autoencoder equipped with an attention network for effective future frame prediction in video anomaly detection. AONet utilizes a novel activation function called OptAF that combines the strengths of the ReLU, leaky ReLU, and sigmoid functions. Furthermore, the proposed method employs a combination of robust loss functions to address various aspects of prediction errors and enhance training effectiveness. The performance of the proposed method is evaluated on three widely used benchmark datasets. The results indicate that the proposed method outperforms existing state‐of‐the‐art methods and demonstrates comparable performance, achieving area under the curve values of 97.0%, 86.9%, and 73.8% on the UCSD Ped2, CUHK Avenue, and ShanghaiTech Campus datasets, respectively. Additionally, the high speed of the proposed method enables its application to real‐time tasks.

Self-control enhances vigilance performance in temporally irregular tasks: an fNIRS frontoparietal investigation.

The present study investigated whether trait self-control impacted operators' behavior and associated neural resource strategies during a temporally irregular vigilance task. Functional near-infrared spectroscopy (fNIRS) readings of oxygenated hemoglobin (HbO2) and deoxygenated hemoglobin (HbR) from 29 participants were recorded fromthe prefrontal and parietal cortices. Self-control was associated with better perceptual sensitivity (A') in the task with the irregular event schedule. A left-lateralized effect of HbO2 was found for temporal irregularity within the dorsomedial prefrontal cortex, in accordance with functional transcranial doppler (fTCD) studies. Self-control increased HbR (decreasing activation) at right superior parietal lobule (rSPL; supporting vigilance utilization) and right inferior parietal lobule (rIPL; supporting resource reallocation). However, only rSPL was associated with the vigilance decrement-where decreases in activation led to better perceptual sensitivity in the temporally irregular task. Additionally, short stress-state measures suggest decreases in task engagement in individuals with higher self-control in the irregular task. The authors suggest a trait-state-brain-behavior relationship for self-control during difficult vigilance tasks. Implications for the study include steps toward rectifying the resource utilization vs. allocation debate in vigilance-as well as validating HbO2 and HbR as effective constructs for predicting operators' mental resources through fNIRS.

On the Gravity Wave‐Seeded Ionospheric Irregularities in the Martian Ionosphere

AbstractFor the past few decades, it has been demonstrated that gravity waves (GWs) and neutral winds can drive ionospheric irregularities on Earth. Still, as far as we know, the formation of ionospheric irregularities on Mars due to GWs has not been well studied. In this study, we use data from the NASA's Mars Atmosphere and Volatile Evolution (MAVEN) mission to show evidence of an irregularity event in the Martian ionosphere, potentially seeded by the GWs break (GWB). Statistical findings indicate that the observed ratio of GWB‐related irregularity events varies from ∼0.25 to ∼0.47 each year, and the average ratio in 2015–2020 is ∼0.37. We perform a numerical simulation to provide further insight into the processes behind irregularity formation, which employs neutral wind shear as a source of perturbation in the context of the GWB. The simulations yield results fundamentally aligned with the observed characteristics of ionospheric irregularities in the 2018 event by considering the wind shear as the disturbance source. This study provides supplementary insights into the perturbation sources involved in shaping irregularities within the Martian ionosphere and presents valuable information about the coupling between the Martian ionosphere and the lower atmosphere.

Performance assessment of a newly developed non-invasive 2D beam profile monitor for high-intensity accelerators

In high-intensity accelerators, minimizing beam loss is paramount to avoid damages and activation of accelerator components. To achieve this, a reliable beam profile monitor is essential for assessing the beam center and spread. Additionally, the beam profile can be used to steer the beam during regular operation, thus reducing beam loss. In cases of irregular events, the monitor can initiate beam profile recording to identify and address any issues promptly. In this manuscript, we present a detailed description of a non-invasive 2D beam profile monitor, focusing on its components, operation, and most importantly, its reliability and failure modes. From operation experience, failure modes of the system and its effects were identified. Fault tree analysis was carried out. Failure rate of sheet generator was estimated using response surface method. Failure rates of components were used to estimate the failure rate of the system. From the target reliability, the required maximum repair time of the system was calculated.

Climate Displacement in Pakistan: (under) reported Frame in Media Discourse on Climate Change in Pakistan

Climate disruption has brought irreversible damage to the world. Since global communities are being widely affected by these changes, masses of the populations are facing climate induced displacement. Such displacements involve internal as well as cross border migration. Climate change is marginalized issue in the hand of media in Pakistan, making climate induced displacement doubly underreported. This study focuses on the media coverage of climate change displacement in Pakistani media discourse. The key research objectives include; to find frequency of climate related news during flood coverage in Pakistan, to assess the nature of themes covered while reporting flood related news during defined period of time and to find climate change induced displacement in media coverage of floods in Pakistan. This study uses content analysis as a research method. Time frame focused in the current study involves 15th June 2022 to 15th September 2022, when flood hit major part of Pakistan. Findings of the study reveal that during defined period of time climate change induced displacement remained under reported in Pakistani newspapers (Dawn, The Nation and The Express Tribune). Moreover, while covering irregular weather events pertaining to climate change, main focus remained on damage, government criticism and aid related process.

Irregular Event Classification in Surveillance Videos Using an Auto-Encoder Deep Learning Framework

Anomaly detection is a major deep-learning problem that has a vast area to work upon. We have used a Convolutional Long Short-Term Memory (LSTM) Auto-encoder for the detection of irregular events based on regular events. Anomaly detection can be approached as a supervised problem, but the problem arises when we dig into varieties of anomalies which has many options and can be difficult to supervise, so the use of an unsupervised method is taken, and the results are calculated based on the regularity score of the sequences. The higher the score of regularity, the higher the chances of regularity in the sequence of video frames. The anomaly is detected on the frame level i.e. which frame has the irregularity, and which has regularity in it. The proposed model outperforms in terms of precision (0.97), recall (0.91), and f-measure (0.94) than the existing techniques.

Deep learning based anomaly detection in real-time video

AbstractMany security cameras have been put up in places like airports, roads, and banks for the safety of these public places. These cameras make a lot of video data, and most security camera recordings are only ever seen when something strange happens. This means that monitoring has to be done by people, which is time-consuming and often wrong, so automatic ways of monitoring have to be used. In this paper, we propose a system that automatically detects irregular events in videos based on the integration of Inflated 3D Convolution Network (I3D-ResNet50) and deep Multiple Instance Learning (MIL). This system considers both regular and unusual videos as negative and positive packets, respectively. Each video snippet is a case of that packet. An anomaly score is generated for each video snippet using a fully connected Neural Network (NN). After processing videos, we used an I3D-ResNet50 to extract features after applying 10-crop augmentations to the UCF-101 dataset that contains 130 GB of videos with 13 abnormal events such as fighting, stealing, abuse, etc., as well as normal events. Our experimental results show that the AUC is 82.85% with only 10,000 iterations compared with other approaches. This means that our model is better at spotting anomalies in real-time videos.

ANOMALY DETECTION SYSTEM

In an era marked by dynamic security challenges, real-time CCTV anomaly detection systems have emerged as a cornerstone in contemporary security frameworks. These systems, leveraging advanced algorithms rooted in machine learning, continuously scrutinize live video streams to establish a baseline of normal activities. The fundamental aim is to promptly identify deviations and anomalies, ushering in a new era of proactive and responsive security monitoring. This technology's real-time capabilities represent a transformative leap forward, enabling immediate responses to potential threats or irregular events within monitored environments. The effectiveness of real-time anomaly detection lies not only in its ability to distinguish between normal and abnormal patterns but also in its contribution to the broader landscape of safety and protection. This abstract delves into the multifaceted significance of real-time CCTV anomaly detection, exploring its role in elevating overall security measures. Beyond the immediate identification of anomalies, these systems promise to shape the future of security by offering a proactive approach to surveillance. As technological advancements persist, the integration of such systems underscores a commitment to anticipatory security strategies, ensuring adaptability in the face of evolving security challenges. Keywords: Anomaly Detection, Intrusion Detection, Machine Learning, Statistical Methods, Network Security, Cybersecurity, Pattern Recognition, Alarm Systems, Real-time Detection.

Time traveling through the floodscape: assessing the spatial and temporal probability of floods and susceptibility zones in the Lower Damodar Basin.

The flood of Damodar river is a well-known fact which is used to the whole riverine society of the basin as well as to the eastern India. The study aims to estimate the spatio-temporal probability of floods and identify susceptible zones in the Lower Damodar Basin (LDB). A flood frequency analysis around 90years hydrological series is performed using the Log-Pearson Type III model. The frequency ratio model has also been applied to determine the spatial context of flood. This reveals the extent to which the LDB could be inundated in response to peak discharge conditions, especially during the monsoon season. The findings indicate that 36.64% of the LDB falls under high to very high flood susceptibility categories, revealing an increasing downstream flood vulnerability trend. Hydro-geomorphic factors substantially contribute to the susceptibility of the LDB to high magnitude floods. A significant shift in flood recurrence intervals, from biennial occurrences in the pre-dam period to decadal or vicennial occurrences in the post-dam period, is observed. Despite a reduction in high-magnitude flood incidents due to dam and barrage construction, irregular flood events persist. The effect of flood in the LDB region is considered to be either positive as well as negative in terms of wholistic sense and impact. The analytical results of this research could serve to identify flood-prone zones and guide the development of flood resilience policies, thereby promoting sustainability within the LDB floodplain.

Arid erosion mapping: comparing LiDAR and structure from motion

Rapid development and uptake in uncrewed aerial vehicles (UAVs) for environmental monitoring, specifically using three-dimensional data from LiDAR and structure from motion (SfM), has enabled improved condition assessment, including fine-scale erosion monitoring. Comparing the precision of LiDAR and SfM for measuring erosion is essential in enabling appropriate method selection. Additionally, knowledge regarding optimal flight heights allows for consideration of the trade-off among survey areas, flight times and precision. We assessed UAV-based LiDAR and SfM for providing high-precision digital surface models (DSM) of substantial gully erosion on a conservation reserve in the southern Australian arid rangelands. The gullies exist in low-slope chenopod shrublands with calcareous soils, and are of significant management concern, with erosion occurring rapidly over short periods following irregular and intense rainfall events. Root mean squared error (RMSE) values for SfM-derived DSMs with resolutions of 2, 4 and 6 cm were lower than comparable LiDAR datasets (SfM = 0.72–1.39 cm; LiDAR = 2.08–3.15 cm). Additionally, 2 cm SfM-derived datasets exhibit notably lower RMSE values than 4 and 6 cm datasets (2 cm = 0.72 cm; 4–6 cm = 2.08–3.15 cm). Change detection over the 1-year study period highlighted erosion in locations of management concern. We propose that, although both methods are of value, SfM is preferred over LiDAR because of its simplicity, reduced cost, and the additional monitoring capabilities of visible-colour imagery, with no notable sacrifice in precision. Visible-colour survey areas and times can be optimised by increasing flight height without dramatic losses in precision. The use of either method will be of great benefit for the monitoring of arid gully erosion and assessing the effectiveness of management interventions, allowing adaptive management and leading to improved condition of arid rangelands into the future.

Validation Methods for the Ammonia Removal of an Air Scrubber on a Poultry House Using the Acid Use and the Process Water Nitrogen Balance

Highlights Acid use in an acid air scrubber predicts the ammonia removal of an air scrubber. Nitrogen balance of process and discharge water in an air scrubber predicts ammonia removal of an air scrubber. Long-term monitoring of acid use and/or the nitrogen balance can validate the ammonia reduction of an air scrubber. The two validation methods can support local authorities in granting environmental permits and enforcement. Abstract. Ensured ammonia reduction by novel technologies and guaranteed low ammonia emission from livestock houses is essential for the granting and monitoring of legal permits. This study focuses on methods to underpin the long-term effectiveness of an air scrubber and was done in a commercial poultry house. The measured ammonia removal by an air scrubber with ammonia sensors (method 1) was compared to the acid use for ammonia binding (method 2) and the nitrogen balance over the process water (method 3). Also, the effect of the length of the time period used for the comparison was evaluated, as was the effect of the spatial variation of the ammonia concentration in the house. The overall weekly data showed a clear linear relation between method 1 on the one hand and methods 2 and 3 on the other hand, with regression coefficients close to 1 and a variation of +/- 20% on a 4-weekly basis. The 4-weekly data showed a clearly reduced variation compared to weekly data, due to leveling out of the impact of irregular time events like acid dosage and water discharge. The barn emission assessed by method 1 was significantly (12%) influenced by the spatial aerial concentration differences of ammonia in the house. Taking this into account, method 2 overestimated the emission reduction of method 1 with 16.8% and method 3 was in good agreement with method 1. For method 2, a revised value for acid use per kg of ammonia binding needs to be substantiated in further research. Possible measurement errors influenced calculated ammonia removal with a maximum of +/-2%, but the relative effect on remaining emissions was larger with +/- 15% for method 3. This study shows that monitoring acid use and/or the nitrogen balance can validate the ammonia reduction of air scrubbers and the remaining ammonia emission and support local authorities in granting environmental permits and their enforcement. Keywords: Acid, Air scrubber, Ammonia, Nitrogen balance, Poultry.

Urban Streetscape Changes in Portland, Oregon: A Longitudinal Virtual Audit

Streetscape imagery has considerable potential for observing urban change. The literature lacks sufficient longitudinal studies, however, on urban change considering human perception and activities. We conducted a longitudinal virtual audit to observe the change in urban liveliness, human activities, and built environment by examining streetscape imagery taken in the late 2000s and the late 2010s in Portland, Oregon. Eleven untrained crowd workers were recruited to provide liveliness ratings of 24,242 streetscape images for both periods. Tabulation, mapping, and multilevel regression analyses were conducted to observe the distribution, changes in liveliness, and the factors affecting these changes. The results confirmed that the city had become livelier during the ten-year study period, which was spatially associated with the increase in pedestrians and cyclists and particular elements of the built environment, such as mid- and high-rise buildings and sidewalk signs. Although these results were somewhat expected, this study’s value lies in confirming the potential of virtual audits conducted using Google Street View Time Machine for retrospectively examining subjective and objective urban change. Caution should be exercised, though, while interpreting urban change as temporal conditions (e.g., season, weather, and irregular events) can potentially bias the results in longitudinal studies.

A semi-empirical model for magnetic storm dynamics

The near-Earth electromagnetic environment represents a far-from-equilibrium system characterized by sudden irregular energy relaxation events. For a broad class of complex systems, time series can be interpreted in terms of a superposition of stochastic and deterministic components occurring at different time scales. In this work we use the generalization of the SYM-H index provided by the SuperMAG collaboration (SMR), which is meant for monitoring the global variation of the horizontal component of the Earth’s magnetic field in the near-equatorial regions. The aim of this work is to model the SMR dynamics via stochastic differential equations thus providing a semi-empirical model whose parameters are retained from data. As a first step we test the Markov condition on the SMR data sample, which represents the basic condition for our stochastic modeling, and we show that such a requirement is accurately satisfied by SMR time series. This allows us to infer the model parameters for the SMR index through the Kramers–Moyal analysis. Finally, we give evidence that a purely diffusive process is not representative of the observed dynamics and then a model based on jump-diffusion processes must be considered to correctly reproduce the dynamical features of the SMR index.

BCD spectrophotometry for massive stars in transition phases

Context. Stars in transition phases, such as those showing the B[e] phenomenon and luminous blue variables (LBVs), undergo strong, often irregular mass-ejection events. The prediction of these phases in stellar evolution models is therefore extremely difficult, if not impossible. As a result, their effective temperatures, their luminosities, and even their true nature are not fully known. Aims. A suitable procedure to derive the stellar parameters of these types of objects is to use the BCD spectrophotometric classification system, which is based on the analysis of the Balmer discontinuity (BD). The BCD parameters (λ1, D) have the advantage that they are independent of interstellar extinction and circumstellar contributions. Methods. We obtained low-resolution spectra for a sample of 14 stars with the B[e] phenomenon and LBVs. Using the BCD classification system, we derived the stellar and physical parameters. The study was complemented with the information provided by the JHK colour-colour diagram. Results. For each star under investigation, the BCD system gives a complete set of fundamental parameters and related quantities such as luminosity and distance. Among the 14 studied stars, we confirmed the classification of HK Ori, HD 323771, and HD 52721 as pre-main sequence HAeB[e] stars, AS 202 and HD 85567 as FS CMa-type stars, and HD 62623 as sgB[e]. We also classified Hen 3- 847, CD-245721, and HD 53367 as young B[e] stars or FS CMa-type candidates, and HD58647 as a slightly evolved B[e] star. In addition, Hen 3–1398 is an sgB[e] and MWC 877, CPD–59 2854, and LHA 120-S 65 are LBV candidates. The stellar parameters of the latter two LBVs are determined for the first time. We also used the size-luminosity relation to estimate the inner radius of the dust disc around the pre-main sequence and main sequence B[e] stars. Conclusions. Our results emphasise that the BCD system is an important and highly valuable tool with which to derive the stellar parameters and physical properties of B-type stars in transition phases. This method can be combined with near-infrared (NIR) colour-colour diagrams to determine or confirm the evolutionary stage of emission-line stars with dust discs.

Preliminary assessment of the suspended sediment dynamics in the Sikkim–Darjeeling Himalayan river

The Sikkim–Darjeeling Himalaya region receives the highest amount of rainfall along the whole southern Himalayan margin and is known for the occurrence of extreme hydrometeorological and geomorphological events. The massive amounts of water and sediment transported each year through the mountain part of the Teesta River drainage system (∼8,150 km2)––the largest river in the region––have been severely impacted by dam construction in recent decades. The aim of the current study was to determine, for the first time in this part of the Himalaya region, the dynamics of suspended sediment transfer at a number of points distributed through the mountainous part of the Teesta River catchment prior to dam construction and preliminarily assess the impact of dam operations on the suspended sediment. Sediment sources were identified using a database of landslide inventories from 1965 to 2019, combined with visual interpretation of satellite imagery from the U.S. Corona programme and Google Earth. Hydrological and sediment data up to the second half of the 1990s were used to reconstruct the discharge and suspended sediment dynamics before direct human intervention in the river channels. The beginning and end of the construction of the reservoirs was determined by analyzing satellite images. The impact of dam operations on the suspended sediment was compiled from the available literature. The results of the current study indicate that the primary sources of sediment are landslides caused by the interaction of rainfall and road undercutting of slopes as well as channel erosion. During extreme rainfall events, the influence of deforested areas in the mobilization and delivery of sediment to the river network increases. The current analysis reveals that reconstruction of the suspended sediment dynamics should take into account the course of extreme events responsible for supplying material to the river network, as well as the long-term remobilization of already deposited sediment in the river channel. It was found that the mean suspended sediment load (SSL) following extreme rainfall, flooding, and landslides in the Teesta River catchment can be up to four times higher than its average values for the same catchment unaffected by such an event, and the effects can be observed for more than a decade afterwards. Under these conditions, the mean suspended sediment yield can reach 12,000 and up to 20,000 t/(km2·y) in individual years, which is among the highest in the Himalaya region and, indeed, the world. The construction of 13 dams in the last 30 years has disrupted the hydrological regime and sediment transport in the Teesta River catchment along 70% of its main course and largest tributaries, and this has resulted in the selective retention of coarser material in the reservoirs and a reduction in the SSL in the Himalayan piedmont. The high density of the dams suggests that further transport of suspended sediment will depend on the efficiency of the water and sediment management at the reservoirs, which may be affected by irregular natural extreme events.

New view of law of supply and demand on examples of medical-economic cases

When a person wants something, he is ready to pay more and more, but many other factors of international, state, public and medical-vital expediency act on prices, which greatly deform the direct relationship between supply and price (naturally, as well, the inverse relationship between demand and price) into almost completely irregular individual random events. Only in some cases can a direct and inverse relationships be maintained.

Context-based irregular activity detection in event logs for forensic investigations: An itemset mining approach

Event logs are a powerful source of digital evidence as they contain detailed information about activities performed on a computer. Forensic investigation of the event logs is a challenging and time-consuming task due to their large volume and continuous generation. A significant amount of time, effort, and knowledge is required to interpret their contents, discovering irregular events that are potentially pertinent to the investigation. As the number of digital investigations increases, so too must resources available to investigators. This requires new techniques to make the process easier and faster, reducing the burden on human investigators as well as being resource efficient. In this paper, a novel solution is presented to examine event logs and automatically identify irregular activities during forensic analysis. The proposed solution utilises a rare itemset mining approach to establish relationships among event entries, based on their contents. Following on, identified event relationships are ordered based on their temporal order to represent the timeline or sequence of activity. The solution is also capable of prioritising identified activities by calculating their degree of irregularity. The empirical analysis is performed on 15 live machines, and the results are discussed in terms of accuracy and performance metrics.

P-145 Direct-ICSI results in good embryological outcomes. A time-lapse study

Abstract Study question Is there a correlation between the method of sperm injection and morphokinetic and morphologic characteristics? Summary answer Results were comparable between the groups whereas the rate of utilizable embryos was significantly higher using Direct-ICSI. This suggests safety and efficacy using this technique. What is known already Maintaining high fertilization- and embryo development rates are key objectives of the IVF-laboratory. Little effort has been put into studying the effects of different manipulation techniques when performing manual microinjections. Specifically, we wanted to compare two methods for achieving cell-membrane puncture: Traditional cytoplasm aspiration technique versus membrane stretching and injection without aspiration –the so-called Direct ICSI method. This method has been proposed to give higher fertilization rates and is being implemented in IVF-laboratories to try to increase ICSI-results. As far as we are aware, no detailed comparison between the two methods on embryo development using time-lapse documentation has been published. Study design, size, duration The study included 44 ICSI-treatments from April 2020 to October 2021 with 119 oocytes injected with Direct-ICSI and 349 sibling oocytes using the conventional aspiration-ICSI technique. In this way, each patient contributed oocytes for both test- and control groups. However, as this was a pilot study, typically only a minority of the oocytes for each patient was injected using the Direct-ICSI method. All fertilized oocytes were included in the assessments up to the blastocyst stage. Participants/materials, setting, methods The center is a public funded University clinic performing > 500 ICSI cycles annually. Inclusion criteria were treatment cycles using fresh own oocytes with ejaculated sperm and at least 5 injectable oocytes after denudation. Time lapse culture was performed using the Embryoscope+ with GTL culture media, both supplied by Vitrolife. Clinical and laboratory procedures were performed according to standard practice. Fisheŕs exact test (categorical variables) and Mann-Whitney U test (continuous variables) were used for statistical analysis. Main results and the role of chance In total, 314 oocytes (67,1%) were fertilized and included in the morphology and morphokinetic assessments up to the blastocyst stage (day 5 or day 6 post-fertilization). Time-lapse parameters such as timing of cell division events and time to morula, time to blastocyst and similar were not significantly different between the groups. Rates of categorical classification of embryological anomalies such as degree of fragmentation, rate of multinucleated cell events, uneven cell size and irregular cell division events also did not differ significantly between the groups. Interestingly however, although fertilization rates did not differ between the two groups (68,1% in the test group vs 67,6% in the control group), the rate of utilizable embryos per injected oocyte was significantly higher in the Direct-ICSI group (40,3% vs 29,5%, p < 0.03), whereas the pregnancy rates did not differ between the groups. Limitations, reasons for caution The present study is a small pilot study with a limited number of cycles, however with 468 oocytes included. The study utilized internal (sibling) controls although oocytes were not truly randomized between the groups. To fully test the efficiency of Direct-ICSI a larger randomized study should be performed. Wider implications of the findings Our results indicate that Direct-ICSI is a safe method with no visible indication of irregularities in preimplantation cell division events using time-lapse monitoring. Aspirating an excess amount of cytoplasm during ICSI might impact embryo development, possibly explaining the increase of utilizable embryos in the Direct-ICSI group, where aspiration is avoided. Trial registration number Not applicable