Temporal Window Research Articles

Abstract 4119428: Monosialoganglioside-containing nanoliposomes protect against acute and chronic ischemic stroke injury

Background: Stroke remains a leading cause of mortality and disability. The narrow temporal window and limited availability of, and eligibility for thrombolytic therapy or endovascular thrombectomy are major therapeutic limitations in treating stroke. Neuroprotective therapies that could be given early to replace or augment these existing therapies are needed to improve stroke outcomes. We showed that monosialoganglioside (GM1) containing nanoliposomes composed of phosphatidylcholine, cholesterol and GM1 (70/25/5% molar ratios, NLGM1) protect against hypoxic injury likely through Nrf2-dependent upregulation of antoxidant enzymes. Aims: To test if post-occlusion NLGM1 treatment could reduce 1) acute stroke injury following middle cerebral artery occlusion (MCAO) and 2) chronic injury following photothrombotic (PT) stroke injury. Methods: 20 week old C57BL/6 mice underwent MCAO for 60 minutes and then injected with saline or NLGM1 (1 or 2 mg IV) prior to reperfusion. Neurologic deficit score and brain infarct % area were measured the next day. Separately, mice underwent PT injury followed by injection of saline or NLGM1 (1 or 2 mg immediately and 2 hours post-injury) and cognitive/behavior tests done 1-90 days post injury. Results: Following MCAO, there was reduced neurologic impairment, infarct volume and brain edema with NLGM1 versus saline control (Fig. 1). Following PT injury, there was reduced neurologic, cognitive and motor impairment from Day 2-90 post-injury with NLGM1 versus saline control (Fig. 2). In both stroke models, there was no difference in efficacy between 1 and 2 mg NLGM1 doses. Conclusions: Treatment of mice with NLGM1 following MCAO or PT stroke injury resulted in improved structural (infarct size, edema) and functional (cognitive, behavior, motor) outcomes in the acute (MCAO) and chronic (PT) timeframes. NLGM1 is a potential novel therapeutic agent for stroke.

Rainfall is associated with divorce in the socially monogamous Seychelles warbler.

Divorce-terminating a pair bond whilst both members are alive-is a mating strategy observed in many socially monogamous species often linked to poor reproductive success. As environmental factors directly affect individual condition and reproductive performance, they can indirectly influence divorce. Given current climate change, understanding how environmental fluctuations affect partnership stability has important implications, including for conservation. Yet, the relationship between the environment and divorce remains largely unstudied. We examined the influence of temporal environmental variability on the prevalence of within- and between-season divorce and the possible underlying mechanisms in a socially monogamous passerine. Analysing 16 years of data from a longitudinal dataset, we investigated the relationship between rainfall and divorce in the Seychelles warbler (Acrocephalus sechellensis). First, we performed climate window analyses to identify the temporal windows of rainfall that best predict reproductive success and divorce. Then, we tested the effects of these temporal windows of rainfall on reproductive success and divorce and the influence of reproductive success on divorce whilst controlling for covariates. Annual divorce rates varied from 1% to 16%. The probability of divorce was significantly associated with the quadratic effect of 7 months of total rainfall before and during the breeding season, with divorce increasing in years with low and high rainfall. This quadratic relationship was driven by a heavy rainfall event in 1997, as excluding 1997 from our analyses left a significant negative linear relationship between rainfall and divorce. Although the same temporal window of rainfall predicting divorce significantly influenced reproductive success, we found no significant correlation between reproductive success and divorce. Our findings suggest that rainfall impacts divorce. Given that this effect is likely not directly mediated by reproductive success, we discuss other possible drivers. Although the 1997 super El Niño event shows how heavy rainfall may affect socially monogamous partnerships, more data are required to estimate the robustness of this effect. By adding to the growing body of literature showing that environmental conditions influence the stability of socially monogamous partnerships, we provide novel insights that may also be important for conservation efforts in times of climate change.

Unveiling the origin of XMM-Newton soft proton flares

Context. Low-energy (< 300 keV) protons entering the field of view of the XMM-Newton telescope scatter with the X-ray mirror surface and might reach the X-ray detectors on the focal plane. They manifest in the form of a sudden increase in the rates, usually referred to as soft proton flares. By knowing the conversion factor between the soft proton energy and the deposited charge on the detector, it is possible to derive the incoming flux and to study the environment of the Earth magnetosphere at different distances, given the wide and elliptical XMM-Newton orbit. Thanks to detailed Geant4 simulations, we were able to build specific soft proton response matrices for MOS and PN. Aims. In this second paper, we present the results of testing these matrices with real data for the first time, while also exploring the seasonal and solar activity effect on the proton environment. The selected spectra are relative to 55 simultaneous MOS and PN observations with flares raised in four different temporal windows: December-January and July-August of 2001-2002 (solar maximum) and 2019-2020 (solar minimum). Methods. We selected and extracted the flare mean spectra and count rates in the 2–11.5 keV energy range for the four epochs. After investigating the rate variations among the MOS1, MOS2, and PN instruments, we fit the X-ray spectra using XSPEC and the proton response matrices. The best-fitting parameters derived for the three instruments were compared in order to obtain the systematic errors. Results. There is no seasonal or solar activity effect on the soft proton mean count rates, but we find large discrepancies in the instrument cross-correlations across the 20 years of satellite operations. In 2001-2002, after a few years of operation, the MOS1 and MOS2 rates are similar, and about 20% with regard to the PN ones. After 20 years, PN does not present any variation in its response, while MOS1 suffers a reduction of ∼30%, in addition to the 30% loss due to the damage of two CCDs, and MOS2 is affected by an even worse degradation (70%). The main result of the spectral analysis is that the physical model representative of the proton spectra at the input of the telescope is a power law. However, a second and phenomenological component is necessary to take into account imprecision in the generation of the matrices at softer (< 5 keV) energies. This component contributes for 21% for the MOS and 5% for the PN to the total flux in the 2–5 keV energy range. Conclusions. This study, which is the first application of the soft proton response matrices to real data, shows coherent results between detectors and allows us to estimate systematic uncertainties in the measured spectra of 3% between the two MOS detectors and of 24% between MOS and PN, together with a systematic in the input flux of about a factor of two. They are all likely due to uncertainties in the proton transmission models, with the presence of additional passive material in front of the front-illuminated MOS, and element deposition on its electrode structure across the mission life. Dedicated studies and laboratory measurements are required for improving the accuracy of the proton response files.

Counter-Activism Against Ideological Opponents: Evidence Based on the Competitive Dynamics of Corporate Engagement in Advocacy Giving

A growing body of literature has sought to understand the strategic drivers of corporate activism, emphasizing the ideological composition of a firm’s workforce as its salient internal driver. Despite these advancements, however, the heterogeneity in its effect remains underexplored, leaving it unclear when employee ideology is more likely to translate into activism. We address this gap by considering competitors’ actions—another important driver uncovered in the scholarship—as a key source of heterogeneity. We examine how these actions can shape the external context in which a firm’s employees evaluate the value of its activism, thereby influencing the firm’s incentives to act on employees' preferences. Our central conjecture is that activism by so-called ideological opponents of a firm’s employee base will be a particularly strong driver of its own activism. This is because actions taken by competitors who hold stances opposite to those valued by a firm’s employees can create a temporal window during which the firm can gain enough employee appreciation for its activism—particularly counter-activism opposing the stance of the competitor. Leveraging the donation records of corporate foundations to advocacy nonprofits as a novel channel for studying corporate activism, we find support for this conjecture. Consistent with our theory, we further find that this effect is driven by firms whose employees hold homogeneous ideological preferences and arises primarily around issues with strong ideological contention.

Enhancing Daily Crash Count Prediction using Deep Learning with Window Size Selection and Seasonality Predictor Integration

The escalating need for proactive safety measures, coupled with advancements in data collection and analytical techniques, has significantly refined the accuracy of crash count predictions, shifting from annual scales to finer daily or hourly estimates. This research places emphasis on recurrent neural networks (RNNs), specifically the long short-term memory (LSTM) model, acknowledged for effectively managing sequential data in time series predictions. Paramount considerations encompass the treatment of input data, including the decision to incorporate temporal features alongside endogenous historical target values, and the establishment of an optimal window size for data input. Despite the critical nature of these facets, exhaustive studies concurrently investigating both under controlled conditions are scarce. This research addresses this gap, assessing diverse scenarios featuring distinct temporal treatments and window sizes, and employing an LSTM model with uniform fine-tuned parameters to ensure a fair comparison. Findings indicate a significant variation in performance among models employing different window sizes and month predictor integration, under identical RNN structures and LSTM configurations. The best model outperformed the least effective by roughly 30% concerning root mean square error (RMSE) and ranking correlation between predicted and actual target crash counts in the test datasets. Unlike seasonality predictor treatment, diverse window size selections did not lead to statistically significant differences in model performance. Generally, a window size of 3 performed worst under most conditions, followed by a size of 14. Sizes of 7 and 28 performed best in nearly an equal numbers of cases.

Segmentation window of speech information processing in the human auditory cortex

Humans perceive continuous speech signals as discrete sequences. To clarify the temporal segmentation window of speech information processing in the human auditory cortex, the relationship between speech perception and cortical responses was investigated using auditory evoked magnetic fields (AEFs). AEFs were measured while participants heard synthetic Japanese words /atataka/. There were eight types of /atataka/ with different speech rates. The durations of the words ranged from 75 to 600 ms. The results revealed a clear correlation between the AEFs and syllables. Specifically, when the durations of the words were between 375 and 600 ms, the evoked responses exhibited four clear responses from the superior temporal area, M100, that corresponded not only to the onset of speech but also to each group of consonant/vowel syllable units. The number of evoked M100 responses was correlated to the duration of the stimulus as well as the number of perceived syllables. The approximate range of the temporal segmentation window limit of speech perception was considered to be between 75 and 94 ms. This finding may contribute to optimizing the temporal performance of high-speed synthesized speech generation systems.

The fate of weakly bound light nuclei in central collider experiments: A challenge in favor of a late continuous decoupling mechanism

Arguments are presented that the reaction products of central high energy nuclear collisions up to collider energies can rigorously be interpreted in terms of a continuous decoupling mechanism based on continuous equations of motion. The various aspects of the collision dynamics are investigated in terms of the individual decoupling processes. Thereby each observed particle decouples during its own temporal decoupling window. This includes a “very late” decoupling of the faintly bound Hypertritons observed in recent ALICE experiments. The success of the strategy is based upon 200 years old wisdom and leads to a revised interpretation of the entire decoupling process.

Development of an Electromyography Signal Acquisition Prototype and Statistical Validation Against a Commercial Device.

Electromyography (EMG) stands out as an accessible and inexpensive method for identifying muscle contractions on the surface and within deeper muscle tissues. Using specialized electronic circuits for amplification and filtering can help develop simple but effective systems for detecting and analyzing these signals. However, EMG devices developed by research teams frequently lack rigorous methodologies for validating the quality of the signals they record compared to those obtained by commercial systems that have undergone extensive testing and regulatory approval for market release. This underscores the critical need for standardized validation techniques to reliably assess the performance of experimental devices relative to established commercial equipment. Hence, this study introduces a methodology for the development and statistical validation of a laboratory EMG circuit compared with a professional device available on the market. The experiment simultaneously recorded the muscle electrical activity of 18 volunteers using two biosignal acquisition devices-a prototype EMG and a commercial system-both applied in parallel at the same recording site. Volunteers performed a series of finger and wrist extension movements to elicit myoelectric activity in these forearm muscles. To achieve this, it was necessary to develop not only the EMG signal conditioning board, but also two additional interface boards: one for enabling parallel recording on both devices and another for synchronizing the devices with the task programmatically controlled in Python that the volunteers were required to perform. The EMG signals generated during these tasks were recorded simultaneously by both devices. Subsequently, 22 feature indices commonly used for classifying muscular activity patterns were calculated from two-second temporal windows of the recordings to extract detailed temporal and spatial characteristics. Finally, the Mean Absolute Percentage Error (MAPE) was computed to compare the indices from the prototype with those from the commercial device, using this method as a validation system to assess the quality of the signals recorded by the prototype relative to the commercial equipment. A concordance of 87.6% was observed between the feature indices calculated from the recordings of both devices, suggesting high effectiveness and reliability of the EMG signals recorded by the prototype compared to the commercial device. These results validate the efficacy of our EMG prototype device and provide a solid foundation for the future evaluation of similar devices, ensuring their reliability, accuracy, and suitability for research or clinical applications.

Increasing temperature threatens post‐fire auto‐successional dynamics of a Mediterranean obligate seeder

Abstract Reproductive traits influence plant auto‐successional dynamics in post‐fire regeneration. Obligate seeding species rely on their seedbank and on the climatic conditions following the fire to ensure a successful recovery, defining the window of opportunity for seedling emergence. In the Mediterranean basin, emergence opportunities generally begin with autumnal rains. However, climate change‐induced increases in temperature and drought could jeopardise the regeneration capacity of seeding species by causing temporal shifts in emergence opportunities or by modifying wildfire seasonality. This study aimed to explore the impact of experimentally induced climate change on regeneration dynamics of Aleppo pine (Pinus halepensis), a serotinous Mediterranean obligate seeder. In March 2021, we set up an 18‐month climate change simulation experiment with 15 open‐top chambers (OTC), each paired with a control subplot (CON) on top of Aleppo pines that were naturally regenerating after a stand‐replacing wildfire in SW Catalonia (June 2019). We tagged 178 young Aleppo pine recruits in OTC and CON subplots (98 and 81 respectively), classified according to their initial size, to periodically measure height growth and survival throughout the experiment duration. Furthermore, Aleppo pine seeds were seasonally sown (7900 total seeds) in 10 subplot pairs between May 2021 and April 2022, to monthly monitor temporal patterns of seedling emergence and survival. We found that OTCs reduced overall emergence rates and caused the loss of the autumnal window of opportunity for the emergence of Aleppo pine seedlings. Furthermore, seedlings which emerged within OTCs faced higher mortality rates in all seasons, with only 1% of seedlings surviving compared with 21.1% of seedlings in control plots. The OTC‐induced conditions were also detrimental to the survival of recruited seedlings, especially those with a smaller initial size, although no significant effects of temperature increase were found on growth. Synthesis. Climate change is likely to interfere with the post‐fire regeneration dynamics of obligate seeders by shortening the temporal window of opportunities for emergence and by enhancing the bottleneck effects throughout the recruitment process in the early phases of pine demographic recovery. Altogether, it could threaten post‐fire regeneration by increasing the hazard of a demographic collapse of Aleppo pine.

Remote ischemic post-conditioning for neonatal encephalopathy: a safety and feasibility trial.

Despite implementation of therapeutic hypothermia (TH) for infants with neonatal encephalopathy (NE), a significant proportion of infants suffer neurodevelopmental impairment (NDI). Remote ischemic conditioning (RIC) is a proposed neuroprotective maneuver that has been studied in adults with brain injury, but it has not been previously investigated in infants with NE. We performed a prospective, randomized, safety and dose escalation study in 32 neonates with NE. Four cohorts of consecutive patients were randomized to RIC therapy, including four cycles of limb ischemia and reperfusion on progressive days of TH, or sham. Clinical, biochemical, and safety outcomes were monitored in both groups. All patients received the designated RIC therapy without interruption or delay. RIC was not associated with increased pain, vascular, cutaneous, muscular, or neural safety events. There was no difference in the incidence of seizures, brain injury, or mortality between the two groups with the escalation of RIC dose and frequency. We found that RIC is a safe and feasible adjunctive therapy for neonates with NE undergoing TH. This pilot study establishes critical safety and feasibility data that are necessary for the design of future studies to investigate the potential efficacy of RIC to reduce NDI. Remote ischemic conditioning (RIC) is a possible neuroprotective intervention in infants with hypoxic-ischemic encephalopathy (HIE). RIC can be administered concurrently with therapeutic hypothermia without any notable adverse events. Future studies will need to address potential efficacy of RIC to improve neurodevelopmental outcomes, as well as consider the ideal temporal window and dose for RIC in this patient population.

Positioning comfort measures in antenatal counselling for periviable infants.

Caring for the extremely premature infant born in the grey zone of viability is the most difficult area of neonatal medicine. Little research has been done on antenatal communication between neonatologists and parents anticipating the birth of a periviable infant. This article analyses 25 antenatal consultations between neonatologists and parents in one Midwestern hospital in the United States of America. It explores how neonatologists position comfort care as one of two predominant care trajectories for extremely premature infants born into the grey zone of viability. We found comfort care featured minimally in and was often marginalised by neonatologists' language. The two dominant discourses contributing to this were acute medicine's life-saving capacity and a limited temporal window marked by gestational age where comfort measures were deemed appropriate. Antenatal consultations framed by shared decision-making could be approached as a form of care characterised by a relational openness and responsiveness to parents' views on care. This asks neonatologists to enter antenatal consultations for periviability without knowing ahead of time which care trajectory will necessarily call one's attention or the particular response one should take, thus highlighting the skills of reflexivity in addition to an attentiveness and openness towards those receiving care.

Effect of noisy environment on secure quantum teleportation of unimodal Gaussian states

Quantum networks rely on quantum teleportation, a process where an unknown quantum state is transmitted between sender and receiver via entangled states and classical communication. In our study, we utilize a continuous variable two-mode squeezed vacuum state as the primary resource for quantum teleportation, shared by Alice and Bob, while exposed to a squeezed thermal environment. Secure quantum teleportation necessitates a teleportation fidelity exceeding 2/3 and the establishment of two-way steering of the resource state. We investigate the temporal evolution of steering and teleportation fidelity to determine critical parameter values for secure quantum teleportation of a coherent Gaussian state. Our findings reveal constraints imposed by temperature, dissipation rate, and squeezing parameters of the squeezed thermal reservoir on the duration of secure quantum teleportation. Intriguingly, we demonstrate that increasing the squeezing parameter of the initial state effectively extends the temporal window for a successful secure quantum teleportation.

An SCA-based classifier for motor imagery EEG classification

Efficient and accurate multi-class classification of electroencephalogram (EEG) signals poses a significant challenge in the development of motor imagery-based brain–computer interface (MI-BCI). Drawing inspiration from the sine cosine algorithm (SCA), a widely employed swarm intelligence algorithm for optimization problems, we proposed a novel population-based classification algorithm for EEG signals in this article. To fully leverage the characteristics contained in EEG signals, multi-scale sub-signals were constructed in terms of temporal windows and spectral bands simultaneously, and the common spatial pattern (CSP) features were extracted from each sub-signal. Subsequently, we integrated the multi-center optimal vectors mechanism into the classical SCA, resulting in the development of a multi-center SCA (MCSCA) classifier. During the classification stage, the label was assigned to the test trials by evaluating the Euclidean distance between their feature vectors and each optimal vector in MCSCA. Additionally, the weights of feature vectors were exploited to select the sub-signal of specific temporal windows and spectral bands for feature reduction, thereby declining computational effort and eliminating data redundancy. To validate the performance of the MCSCA classifier, we conducted four-class classification experiments using the BCI Competition IV dataset 2a, achieving an average classification accuracy of 71.89%. The experimental results show that the proposed algorithm offers a novel and effective approach for EEG classification.

Visualizing Thermally Activated Conical Intersections Governing Non-Radiative Triplet Decay in a Ni(II) Porphyrin-Nanographene Conjugate with Variable Temperature Transient Absorption Spectroscopy.

Metalloporphyrins based on open-shell transition metals, such as Ni(II), exhibit typically fast excited-state relaxation. In this work, we shed light into the nonradiative relaxation mechanism in a nanographene-Ni(II) porphyrin conjugate. Variable temperature transient absorption and global fit analysis are combined to produce a picture of the relaxation pathways. At room temperature, photoexcitation of the lowest π-π* transition is followed by vibrational cooling in 1.6 ps, setting a short 20 ps temporal window wherein a small fraction of relaxed singlets radiatively decay to the ground state before intersystem crossing proceeds. Following intersystem crossing, triplets relax rapidly to the ground state (S0) in a few tens of picoseconds. By performing measurements at low temperature, we provide evidence for a competition between two terminal relaxation pathways from the lowest (metal-centered) triplet to the ground state: a slow ground state relaxation process proceeding in time scales beyond 1.6 ns and a faster pathway dictated by a sloped conical intersection, which is thermally accessible at room temperature from the triplet state. The overall triplet decay at a given temperature is dictated by the interplay of these two contributions. This observation bears significance in understanding the underlying fast relaxation processes in Ni-based molecules and related transition metal complexes, opening avenues for potential applications for energy harvesting and optoelectronics.

BundleMoCap++: Efficient, robust and smooth motion capture from sparse multiview videos

Producing smooth and accurate motions from sparse videos without requiring specialized equipment and markers is a long-standing problem in the research community. Most approaches typically involve complex processes such as temporal constraints, multiple stages combining data-driven regression and optimization techniques, and bundle solving over temporal windows. These increase the computational burden and introduce the challenge of hyperparameter tuning for the different objective terms. In contrast, BundleMoCap++ offers a simple yet effective approach to this problem. It solves the motion in a single stage, eliminating the need for temporal smoothness objectives while still delivering smooth motions without compromising accuracy. BundleMoCap++ outperforms the state-of-the-art without increasing complexity. Our approach is based on manifold interpolation between latent keyframes. By relying on a local manifold smoothness assumption and appropriate interpolation schemes, we efficiently solve a bundle of frames using two or more latent codes. Additionally, the method is implemented as a sliding window optimization and requires only the first frame to be properly initialized, reducing the overall computational burden. BundleMoCap++’s strength lies in achieving high-quality motion capture results with fewer computational resources. To do this efficiently, we propose a novel human pose prior that focuses on the geometric aspect of the latent space, modeling it as a hypersphere, allowing for the introduction of sophisticated interpolation techniques. We also propose an algorithm for optimizing the latent variables directly on the learned manifold, improving convergence and performance. Finally, we introduce high-order interpolation techniques adapted for the hypersphere, allowing us to increase the solving temporal window, enhancing performance and efficiency.

Enhanced Blue Band Vegetation Index (The Re-Modified Anthocyanin Reflectance Index (RMARI)) for Accurate Farmland Shelterbelt Extraction

Farmland shelterbelts are aimed at farmland protection and productivity improvement, environmental protection and ecological balance, as well as land use planning and management. Farmland shelterbelts play a vital role in determining the structural integrity and overall effectiveness of farmland, and assessing the dynamic changes within these protective forests accurately and swiftly is essential to maintaining their protective functions as well as for policy formulation and effectiveness evaluation in relevant departments. Traditional methods for extracting farmland shelterbelt information have faced significant challenges due to the large workload required and the inconsistencies in the accuracy of existing methods. For example, the existing vegetation index extraction methods often have significant errors, which remain unresolved. Therefore, developing a more efficient extraction method with greater accuracy is imperative. This study focused on Youyi Farm in Heilongjiang Province, China, utilizing satellite data with spatial resolutions ranging from 0.8 m (GF-7) to 30 m (Landsat). By taking into account the growth cycles of farmland shelterbelts and variations in crop types, the optimal temporal window for extraction is identified based on phenological analysis. The study introduced a new index—the Re-Modified Anthocyanin Reflectance Index (RMARI)—which is an improvement on existing vegetation indexes, such as the NDVI and the improved original ARI. Both the accuracy and extraction results showed significant improvements, and the feasibility of the RMARI was confirmed. The study proposed four extraction schemes for farmland shelterbelts: (1) spectral feature extraction, (2) extraction using vegetation indexes, (3) random forest extraction, and (4) RF combined with characteristic index bands. The extraction process was implemented on the GEE platform, and results from different spatial resolutions were compared. Results showed that (1) the bare soil period in May is the optimal time period for extracting farmland shelterbelts; (2) the RF method combined with characteristic index bands produces the best extraction results, effectively distinguishing shelterbelts from other land features; (3) the RMARI reduces background noise more effectively than the NDVI and ARI, resulting in more comprehensive extraction outcomes; and (4) among the satellite images analyzed—GF-7, Planet, Sentinel-2, and Landsat OLI 8—GF-7 achieves the highest extraction accuracy (with a Kappa coefficient of 0.95 and an OA of 0.97), providing the most detailed textural information. However, comprehensive analysis suggests that Sentinel-2 is more suitable for large-scale farmland shelterbelt information extraction. This study provides new approaches and technical support for periodic dynamic forestry surveys, providing valuable reference points for agricultural ecological research.

Recommendations on bioacoustical metrics relevant for regulating exposure to anthropogenic underwater sounda).

Metrics to be used in noise impact assessment must integrate the physical acoustic characteristics of the sound field with relevant biology of animals. Several metrics have been established to determine and regulate underwater noise exposure to aquatic fauna. However, recent advances in understanding cause-effect relationships indicate that additional metrics are needed to fully describe and quantify the impact of sound fields on aquatic fauna. Existing regulations have primarily focused on marine mammals and are based on the dichotomy of sound types as being either impulsive or non-impulsive. This classification of sound types, however, is overly simplistic and insufficient for adequate impact assessments of sound on animals. It is recommended that the definition of impulsiveness be refined by incorporating kurtosis as an additional parameter and applying an appropriate conversion factor. Auditory frequency weighting functions, which scale the importance of particular sound frequencies to account for an animal's sensitivity to those frequencies, should be applied. Minimum phase filters are recommended for calculating weighted sound pressure. Temporal observation windows should be reported as signal duration influences its detectability by animals. Acknowledging that auditory integration time differs across species and is frequency dependent, standardized temporal integration windows are proposed for various signal types.

Circadian regulation of dengue virus transmission and replication: insights into vector activity and viral dynamics.

Dengue fever, caused by dengue virus, poses a significant global health challenge, particularly in tropical regions where Aedes aegypti serves as the primary vector. The circadian clock in Aedes aegypti governs key behavioral and physiological processes, including activity patterns, feeding behaviors, and susceptibility to dengue virus infection. This article explores the influence of circadian rhythms on the mosquito's ability to transmit dengue virus, emphasizing how the circadian regulation of gene expression, immune responses, and lipid metabolism in the mosquito vector creates temporal windows that affect viral replication efficiency.

Music literacy shapes the specialization of a right hemispheric word reading area

This study aimed to examine differences in the brain activity of professional musicians and non-musicians, particularly in relation to neuroplastic changes that may be associated with musical training. Specifically, we investigated whether the ability to read complex musical notation might be linked to neurofunctional adaptations that could influence word reading mechanisms. The study involved 80 participants (half of which were musicians). High-density EEG recordings and swLORETA inverse solutions were employed to analyze brain activity related to word processing and orthographic analysis. The electromagnetic signals were analyzed in the temporal window corresponding to the latency of N170 component (150–190 ms). Musicians and musically naïve people (controls) were matched based on native language, sociocultural and educational status, age, and laterality preference. Behavioural data and reading proficiency tests demonstrated higher reading skills (for words, non-words and text), and faster RTs to target letters embedded in words, in musicians. Source reconstruction showed fundamental differences in word reading mechanisms between musicians and non-musicians, including a larger involvement of the right occipitotemporal cortex, in the former than the latter. In particular, musicians showed a bilateral activation of the middle occipital gyrus (BA19, Visual Word Form Area), which was strongly lateralized to the left hemisphere in controls, during word orthographic analysis. A relationship is proposed between music literacy, enhanced reading skills and the development of a right-sided reading area for notation recognition in musicians, which could serve as a potential protective factor for ‘surface’ dyslexia.

Epidural Spinal Cord Recordings (ESRs): sources of neural-appearing artifact in stimulation evoked compound action potentials.

Evoked compound action potentials (ECAPs) measured during epidural spinal cord stimulation (SCS) can help elucidate fundamental mechanisms for the treatment of pain and inform closed-loop control of SCS. Previous studies have used ECAPs to characterize neural responses to various neuromodulation therapies and have demonstrated that ECAPs are highly prone to multiple sources of artifact, including post-stimulus pulse capacitive artifact, electromyography (EMG) bleed-through, and motion artifact. However, a thorough characterization has yet to be performed for how these sources of artifact may contaminate recordings within the temporal window commonly used to determine activation of A-beta fibers in a large animal model.
We characterized sources of artifacts that can contaminate the recording of ECAPs in an epidural SCS swine model using the Abbott Octrode™ lead. Spinal ECAP recordings can be contaminated by capacitive artifact, short latency EMG from nearby muscles of the back, and motion artifact. The capacitive artifact can appear nearly identical in duration and waveshape to evoked A-beta responses. EMG bleed-through can have phase shifts across the electrode array, similar to the phase shift anticipated by propagation of an evoked A-beta fiber response. The short latency EMG is often evident at currents similar to those needed to activate A-beta fibers associated with the treatment of pain. Changes in CSF between the cord and dura, and motion induced during breathing created a cyclic oscillation in all evoked components of recorded ECAPs. 
Controls must be implemented to separate neural signal from sources of artifact in SCS ECAPs. We suggest experimental procedures and reporting requirements necessary to disambiguate underlying neural response from these confounds. These data are important to better understand the framework for recorded ESRs, with components such as ECAPs, EMG, and artifacts, and have important implications for closed-loop control algorithms to account for transient motion such as postural changes and cough.