Representation Of Time Research Articles

The patient representation struggle during the COVID-19 pandemic: Missed opportunities for resilient healthcare systems.

The role of patient participation and representation during crises, such as the COVID-19 pandemic, has been under-researched. Existing studies paint a pessimistic picture of patient representation during the pandemic. However, there are indications that patient representatives have adapted to the new situation and can contribute to the resilience of healthcare systems. This paper aims to further explore the potential contribution of patient representatives for healthcare system resilience during the COVID-19 pandemic. The study used a qualitative approach. We conducted a thematic analysis on the following data: interviews with client council members (n = 32) and representatives from patient organizations (n = 6) and focus groups (n = 2) to investigate patient representation on both the national policy level and organizational level in the Netherlands. We identified the crisis discourse, the dependent position, the diversity of patient perspectives and the layered decision-making structure as themes that help to understand what made patient representation in pandemic times a struggle for national and local patient representatives. The analysis of the subjects these representatives put forward during decision-making shows that their input can play an important role in broadening discussions, challenging decisions, and suggesting alternatives during a crisis. We identified several strategies (e.g., collaborating with other actors, proactively putting subjects on the policy agenda, finding new ways of contacting their 'constituency') used by the patient representatives studied to exert influence despite the difficulties encountered. The struggle for patient representation during pandemic decision-making is a missed opportunity for resilient healthcare systems as these representatives can play a role in opening up discussions and putting different perspectives to the fore. Moreover, the adaptive strategies used by representatives to influence decision-making offer lessons for future representation activities. However, adaptations to the crisis decision-making structure are also needed to enable patient representatives to play their role. We conducted interviews with patient representatives and discussed our preliminary findings with patient representatives during the focus groups. Zorgbelang, a patient organization supporting client councils and enabling and organizing patient participation for organizations and municipalities, was partner in this research and contributed to the interview guide, conducting interviews and focus groups. Additionally, the analysis made by the first author was discussed and refined multiple times with the partners of Zorgbelang and one of them co-authored this paper.

Frequency analysis of passive sonar signals using multiple-measurement physics-informed neural network

We propose a deep learning based frequency analysis for passive sonar signals by considering a linear system based on a relation between time and frequency domain signal representations. An adaptive learned iterative shrinkage thresholding algorithm (Ada-LISTA) is utilized as the deep learning architecture to solve the linear system effectively and to ensure generalization performance. To obtain more reliable solutions, we involve the linear system in loss function during training. Futhermore, in order to reduce noise effectively, we employ multiple measurements from time and space domains, which have common frequency components of passive sonar signals. Thus, the loss function is modified for solutions from the multiple measurements to have shared frequency components. We conduct experiments using synthetic and underwater in-situ data to examine performance of frequency analysis considering the linear system in designing the architecture and finding the optimal weights. The frequency analysis demonstrates superior performance in detecting frequency components and reducing noise, compared to fast Fourier transform and sparse Bayesian learning with low computational burden during its application to the test measurements.

Indoor Environmental Quality and Comfort in Offices: A Review

People spend about 90% of their time in closed spaces such as residential and office environments, and indoor environmental quality (IEQ) has effects on their health, well-being, overall comfort and work productivity. The IEQ domains (i.e., thermal, acoustic, visual and indoor air quality) are able to influence office users’ work day and even cause the onset of diseases. This review aims at investigating IEQ in offices and the multidomain combined effects on occupants’ overall comfort. Studies published between 2016 and 2022 were summarized, focusing on four research questions formulated to deepen the knowledge on (i) IEQ perception and evaluation, (ii) IEQ indexes and parameters, (iii) factors that influence comfort perception and (iv) IEQ and comfort representation in space and time. For these research questions, a total of 29, 19, 10 and 9 studies, found on the Scopus database through a keywords search, were considered, respectively. The studies were included only if they appraised a multidomain approach. The results obtained for each research question reveal that: (i) Post-Occupancy Evaluation (POE) surveys are often applied to understand how occupants perceive IEQ, and in-field monitoring based on low-cost sensors is implemented more and more to acquire IEQ data, (ii) a set of indexes and parameters for IEQ assessment is not standardized yet, although some parameters are commonly used, (iii) personal factors like age and gender, and contextual factors like workstation location and office type, influence occupants’ comfort perception and (iv) dashboards are used to allow office end-users to visualize the indoor conditions of the environment.

A Study on General State Model of Differential Drive Wheeled Mobile Robots

This study introduces a novel approach by representing a multi-input-multi-output (MIMO) differential drive wheel mobile robot (DDWMR) using the standard state space representation for the first time. This representation facilitates the application of analysis and control system design techniques to MIMO systems. Specifically, the investigation delves into stability, controllability, observability, input-output interaction, and the relative gain array of the DDWMR model. To demonstrate the concept, the established methodology employs the conventional pole placement controller design technique to formulate a state feedback control law for trajectory tracking in the DDWMR system, utilizing both a nominal and a generalized model. The generalized model incorporates distinct parameters for the left and right motor-wheel systems, unlike the nominal model where they are assumed to be identical. Simulation results highlight that accounting for the asymmetric characteristics through the controller derived from the generalized model yields superior performance compared to the nominal model-based controller. Furthermore, the proposed model can be served as an illustrative platform for evaluating innovative MIMO control methodologies in prospective studies.

Investigating the invisible threat: An exploration of air exchange rates and ultrafine particle dynamics in hospital operating rooms

The air exchange rate (AER), defined as the number of times the air is fully replaced per hour in an indoor space, is an important parameter affecting indoor air quality (IAQ). Hospital operation rooms (ORs), one of the indoor environments with relatively high health risks, should maintain high AERs to quickly remove surgical smoke during surgery. This study aimed to investigate the characteristics and transmission of pollutants in ORs through on-site measurements and numerical simulations. To determine actual AER (AERactual), both exponential decay and concentration variations, resulting in a more precise representation of indoor air pollutant residence time, were considered. Our results revealed that gaseous pollutants exhibited lower AERactual values compared to particulate pollutants due to their higher diffusibility. Notably, the AERactual of total volatile organic compounds (TVOC) was found to be greater than that of carbon dioxide (CO2) due to the higher reactivity of TVOC. Furthermore, this study also investigated the characteristics of surgical smoke particles and observed variations in emission factors (EF) depending on the surgical procedure, ranging from approximately 1010 to 1011 particles per minute. Moreover, coarse particles (>2.5 μm) were primarily influenced by drag forces, resulting in lower AERactual values. Additionally, the AERactual of ultrafine particles (UFPs) was examined, revealing that smaller particles exhibited lower AERactual values, potentially due to stronger Brownian motion. By combining measurement and simulation analysis, the spatial distribution of lung deposited surface area (LDSA) concentrations could be evaluated, providing accurate exposure concentrations for health risk assessments.

Comics Anthropocenes: visualizing multiple space-times in Anglophone speculative comics

ABSTRACT Comics and graphic novels have not typically been foregrounded in accounts of Anthropocene fictions. This article argues that speculative comics are particularly suited to visualizing the Anthropocene through their verbal-visual strategies for representing multiple scales of space and time. Defined as the era in which human-driven processes have become detectable in the Earth’s geological record, the concept of the Anthropocene has also been challenged by postcolonial and Indigenous theorists for presuming an undifferentiated humanity responsible for ecological crises. Speculative comics offer strategies for representing multiple scales of space and time that call into question the ‘human’ as a geological force. While autobiographical and documentary comics represent the scale of individual human experience, speculative comics feature nonhuman spaces and times on multiple, asynchronous scales. This article first contextualizes the representation of space and time in speculative Anglophone comics from early superhero comics to the contemporary period, then focusing on three case studies drawn from contemporary Anglophone comics: Grant Morrison and Chris Burnham’s Nameless (2015), Warren Ellis and Jason Howard’s Trees (2014–2016, 2020), and Ram V and Filipe Andrade’s The Many Deaths of Laila Starr (2021).

Electrical Power Edge-End Interaction Modeling with Time Series Label Noise Learning

In the context of electrical power systems, modeling the edge-end interaction involves understanding the dynamic relationship between different components and endpoints of the system. However, the time series of electrical power obtained by user terminals often suffer from low-quality issues such as missing values, numerical anomalies, and noisy labels. These issues can easily reduce the robustness of data mining results for edge-end interaction models. Therefore, this paper proposes a time–frequency noisy label classification (TF-NLC) model, which improves the robustness of edge-end interaction models in dealing with low-quality issues. Specifically, we employ two deep neural networks that are trained concurrently, utilizing both the time and frequency domains. The two networks mutually guide each other’s classification training by selecting clean labels from batches within small loss data. To further improve the robustness of the classification of time and frequency domain feature representations, we introduce a time–frequency domain consistency contrastive learning module. By classifying the selection of clean labels based on time–frequency representations for mutually guided training, TF-NLC can effectively mitigate the negative impact of noisy labels on model training. Extensive experiments on eight electrical power and ten other different realistic scenario time series datasets show that our proposed TF-NLC achieves advanced classification performance under different noisy label scenarios. Also, the ablation and visualization experiments further demonstrate the robustness of our proposed method.

An Ontology-Based Knowledge Representation Method for Typhoon Events from Chinese News Reports

Typhoons are destructive weather events. News media reports contain large amounts of typhoon information. Transforming this information into useful knowledge to provide a basis for mining typhoon knowledge and supporting disaster prevention and relief is urgently required to solve this problem. Knowledge representation can be used to address this problem, although it presents several challenges. These challenges lie in expressing the static and dynamic characteristics of typhoons and formalizing the knowledge representation method and making it suitable for machine processing. Moreover, the general Chinese time and space representation method is overly cumbersome for use in ontologies. The present study proposes an ontology-based typhoon event representation method that solves the representation problems of the typhoon static concept and dynamic features. Furthermore, it summarizes the fixed patterns of time and space in Chinese news and designs a time and space model suitable for typhoon event ontologies. From the ontology population, typhoon event ontology instances are created, and the typhoon event ontology model is applied to the analysis of typhoon processes, verifying the effectiveness of the typhoon event ontology model.

On local times of Martin-Löf random Brownian motion

In this paper we study the local times of Brownian motion from the point of view of algorithmic randomness. We introduce the notion of effective local time and show that any path which is Martin-Löf random with respect to the Wiener measure has continuous effective local times at every computable point. Finally we obtain a new simple representation of classical Brownian local times, computationally expressed.

Classification of EEG Signal using Independent Component Analysis and Discrete Wavelet Transform based on Linear Discriminant Analysis

Autism Spectrum Disorder (ASD) is a neurodevelopment syndrome decreasing sufferers' social interaction, communication skills, and emotional expression. Autism syndrome can be detected using an electroencephalogram (EEG). This study utilized the EEG of autistic people to support the classification study of machine learning schemes to produce the best accuracy. One of the best approaches to classify the EEG signal is The Linear Discriminant Analysis (LDA), a machine learning technique to classify autism and normal EEG signals. LDA was chosen because it can maximize the distance between classes and minimize the number of scatters by utilizing between and within-class functions. This method was combined with other methods: Independent Components Analysis (ICA) and Discrete Wavelet Transform (DWT), to improve the accuracy system. ICA removes artifacts or signals other than brain signals that can cause noise in the EEG signal, so the analyzed signal was a complete EEG signal without other factors. DWT can help increase noise suppression in the EEG signal and provide signal information through frequency and time representation. The EEG dataset was collated from 16 children (eight autistic and eight normal). The signals from the dataset were filtered by artifacts using ICA, decomposed by three levels through DWT, and classified using the Linear Discriminant Analysis (LDA) technique. Using the Confusion Matrix, the results reveal the best accuracy of 99%.

The Nostalgic Home in E. M. Forster's Novels

Edward Morgan Forster wrote 6 novels, all of which revolve around the concept of home in relation to the representation of time and its impact on human soul and spirit. Homes of Forster are created by people and their emotions; hence they are very effective in their lives. In his Aspects of the Novel, Forster confirms that the art of fiction depends on facets like characters, plots, patterns, time, and places. This paper handles the representation of homes and the impact of time on these homes in E.M. Forester's Where Angels Fear to Tread, A Room With A View and Howard's End. In these novels Forster uses a recurrent theme; that is the impact of time on places and people. As Angels Fear to Tread echoes Alexander Pope's line in his An Essay on Criticism: "for fools rush in where angels fear to tread", the novel deals with concepts like national character, connection across social differences, the passage of time and its impact on places and houses. In A Room with A View, Forster contrasts Florence, Italy and Windy Corner, England, showing their influence on the development of Lucy, the heroine. Lucy is torn between two different lives. She misses the feeling of home, warmth and domesticity. She struggles throughout the whole novel to embrace love, security, and belonging. Home as a concept is an evasive axis in Forster's Howard's End. The novel is set in the Victorian era where all houses were rebuilt, reconstructed and replaced. There was a demanding rebuilding initiative across Britain, especially in London. That's why houses and places were obviously an entity for people's emotional values. In Howard's End, the Schlegels are evicted from Wickham place, and this leads to their dichotomy. The concepts of places, dwelling, passing of time, and nostalgia, give an opportunity for readers to observe the importance of home in modern life. In Forster's novels, homes are experienced on many levels: homes as places people have already visited and lived in; homes as places people imagined through pictures or dreams; and homes that are never visited or even imagined by dwellers. As John Edward Hardy states: "buildings, and the design of them, the architectural character of civilization, would seem to be in Forster's mind fundamentally related to its character of manners and morals", it would be significant to have a deeper look into the concept of home, time and nostalgia in relation to modern man. Keywords: houses, homes, Forster's novels, passage of time, nostalgia and modernity

The combination of the horizontal and vertical dimensions in mental time representation: the existence of a spatial mental map of time.

Horizontal and vertical representations of time (past-left or down and future-right or top) have been demonstrated. However, only a few studies have investigated the existence of a spatial map of time, considering it as the interaction of different spatial dimensions in space. The aim of this study was to investigate the existence of a mental time representation along the diagonal axes, intended as the combination of the horizontal and the vertical dimensions. Seventy-nine Italian participants (85% females; mean age = 25.11 ± 4.86 years; 77 right-handed) performed an online temporal judgment task using 20 Italian temporal expressions presented either always in the center (Experiment 1) or in the four corners of the screen (Experiment 2) and two pairs of response keys ("C" and "U" for the positive diagonal; "R" and "N" for the negative diagonal). Results showed spatial-temporal associations in positive (i.e., time was represented from left-bottom to right-top) and negative (i.e., time was represented from left-top to right-bottom) diagonals, although in Experiment 2 these associations were weak for the negative diagonal. These spatial-temporal associations along both diagonals were confirmed even when participants were free to place different temporal stimuli along a diagonally drawn line, in a Time-to-Position task, indicating that the temporal expressions could be ordered linearly along the diagonal spaces. Finally, these data indicated that the horizontal information was mainly used for determining the spatial-temporal associations along both diagonals, whereas the vertical information was flexible with a bottom-to-top (for positive diagonal) and top-to-bottom (for negative diagonal) temporal representation.

The faceless and vulnerable other – the visual portrayal of older people on German online news sites within the context of the COVID-19 pandemic

Abstract Recent studies provide evidence that the coverage of older people's issues in the mass media during the COVID-19 pandemic was accompanied by a (re-)emergence of negative stereotypes surrounding the question of age. However, these studies primarily relied on written materials. As visual imagery has the power to attract greater attention than words, this study set out to investigate the visual portrayal of older adults in the mass media. Via web crawling, we identified a total of 3,560 articles with keywords such as ‘older adults’ and ‘COVID-19 pandemic’ in the four most popular online news sites in Germany during the first phase of the pandemic. We applied visual content analysis to assess the frequency of a diverse set of characteristics of older adults in the cover photos of the articles in question (N = 604). Older individuals were most often depicted as physically weak, alone, professionally taken care of, passive, living at home or in a nursing home, and cognitively inactive. The images – mostly of female passing persons – were characterised by a stereotypical presentation that evokes distance to the subject by cropping out any faces. Our results reflect findings on the negative media representation of older adults as homogenously vulnerable in verbal materials during the COVID-19 pandemic in contrast to increasingly diverse representations in pre-pandemic times. This stereotypical misrepresentation of older adults can be interpreted as visual ageism, which is amplified by their visual othering. Our findings demonstrate the need for the media to reflect upon these practices as negative age stereotypes have an impact on mental health for people of all ages.

Visual Representations to Stimulate New Musicking Strategies in Live Coding

In live coding, the code can be considered as an archetypal form of score that notates formal processes. We aimed at investigating the possibility of using graphic visuals as a complementary form of descriptive score by visualising sound events using different time representations. To this end, we devised two visualisation systems (Time_X and Time_Z). Time_X represents time along thex-axis, while in Time_Z the objects overlap along an imaginaryz-axis. Based on our previous personal experience with the system, such forms of visual scores can help to develop new musicking strategies while live coding. In this article, we wanted to broaden such reflections, and we used them as probes in a study with three live coders. After tailoring the two systems to the usual practice of the three participants, we asked them to use the systems for three weeks and keep a diary. At the end, we interviewed them. Based on their comments, we present some reflections on the use of graphic forms of visualisation in live coding, on how they can support musicking process, and to what extent such visuals can be considered scores.

Encoding, working memory, or decision: how feedback modulates time perception.

The hypothesis that individuals can accurately represent temporal information within approximately 3 s is the premise of several theoretical models and empirical studies in the field of temporal processing. The significance of accurately representing time within 3 s and the universality of the overestimation contrast dramatically. To clarify whether this overestimation arises from an inability to accurately represent time or a response bias, we systematically examined whether feedback reduces overestimation at the 3 temporal processing stages of timing (encoding), working memory, and decisions proposed by the scalar timing model. Participants reproduced the time interval between 2 circles with or without feedback, while the electroencephalogram (EEG) was synchronously recorded. Behavioral results showed that feedback shortened reproduced times and significantly minimized overestimation. EEG results showed that feedback significantly decreased the amplitude of contingent negative variation (CNV) in the decision stage but did not modulate the CNV amplitude in the encoding stage or the P2-P3b amplitudes in the working memory stage. These results suggest that overestimation arises from response bias when individuals convert an accurate representation of time into behavior. Our study provides electrophysiological evidence to support the conception that short intervals under approximately 3 s can be accurately represented as "temporal gestalt."

How time gets spatial: factors determining the stability and instability of the mental time line

Left-to-right readers classify faster past events with motor responses on the left side of space and future events with responses on the right side. This suggests a left-to-right spatial organization in the mental representation of time. Here, we show that the significance and reliability of this representation are linked to the joint use of temporal and spatial codes in the task at hand. In a first unimanual Go/No-Go Implicit Association Test (IAT), attending selectively to “past” or to “future” words did not activate corresponding “left” or “right” spatial concepts and vice versa. In a second IAT, attending to both temporal (i.e., “past” and “future”) words and spatial targets (i.e., “left” and “right”) pointing arrows produced faster responses for congruent rather than incongruent combinations of temporal and spatial concepts in task instructions (e.g., congruent = “Go with past words and left-pointing arrows”; incongruent = “Go with past words and right-pointing arrows”). This effect increased markedly in a STEARC task where spatial codes defined the selection between “left-side” and “right-side” button presses that were associated with “past” and “future” words. Two control experiments showed only partial or unreliable space–time congruency effects when (a) participants attended to superordinate semantic codes that included both spatial “left”/”right” or temporal “past/future” subordinate codes; (b) a primary speeded response was assigned to one dimension (e.g., “past vs. future”) and a nonspeeded one to the other dimension (e.g., “left” vs. “right”). These results help to define the conditions that trigger a stable and reliable spatial representation of time-related concepts.

Protocols for in vitro reconstitution of the cyanobacterial circadian clock.

Circadian clocks are intracellular systems that orchestrate metabolic processes in anticipation of sunrise and sunset by providing an internal representation of local time. Because the ~24-h metabolic rhythms they produce are important to health across diverse life forms there is growing interest in their mechanisms. However, mechanistic studies are challenging in vivo due to the complex, that is, poorly defined, milieu of live cells. Recently, we reconstituted the intact circadian clock of cyanobacteria in vitro. It oscillates autonomously and remains phase coherent for many days with a fluorescence-based readout that enables real-time observation of individual clock proteins and promoter DNA simultaneously under defined conditions without user intervention. We found that reproducibility of the reactions required strict adherence to the quality of each recombinant clock protein purified from Escherichia coli. Here, we provide protocols for preparing in vitro clock samples so that other labs can ask questions about how changing environments, like temperature, metabolites, and protein levels are reflected in the core oscillator and propagated to regulation of transcription, providing deeper mechanistic insights into clock biology.

A time-bucket MILP formulation for optimal lot-sizing and scheduling of real-world chemical batch plants

We propose a new time-bucket MILP model for lot-sizing and scheduling problems arising in chemical batch plants. The main idea behind time-bucket models is to partition time into fixed-length macroperiods and flexible length microperiods, that lie within the macroperiods. We show that the time-bucket model benefits from advantages of both continuous and discrete time representations. It allows to include important real-world constraints, can be solved with moderate computational effort, and thus promotes MILP for large-scale, industrial problems. We investigate the scalability of the model and apply it to a formulation and filling process from an industrial agrochemical production with 7 formulation lines, intermediate buffer tanks, and 7 filling lines. We optimize a one month period with 50 intermediates, and 83 finished products. A comparison of the MILP solution to a discrete event simulation solution shows that 17% of production capacity can be freed up and significant improvement in on-time delivery.

A taster for time: Monday is sweeter than Friday


 Space-time metaphors in English and Chinese connote two metaphorical representations of time in space: the ego-moving representation and the time-moving representation. Extant research thereon has evinced that the choice of either is subject to both spatial and non-spatial factors (e.g., emotion). Conjoining two separate lines of inquiry, one into the relationship between emotion and time and the other into the metaphorical associations between taste and emotion, the current research examined the bidirectional relationship between taste and time. In Study 1, participants tasted sweet-, sour-, bitter-, and spicy-dominated snacks before responding to the temporally ambiguous “Next Wednesday’s meeting” question (Li, 2019) and the results showed that those who tasted sweet snack reported more time-moving perspectives than ego-moving perspectives whereas the opposite tendency was registered in those who tasted the other three snacks. The taste-aroused approach motivation rather than the taste-induced emotion was a reliable predictor of the temporal perspective preference. By priming participants with either the time-moving or the ego-moving frame of reference, Study 2 investigated the reverse influence of temporal perspective on taste preference and the results indicated that compared to the ego-moving prime, the time-moving prime prompted a distinctively stronger liking for the sweet-tasting snack as a result of relatively low happiness and approach motivation. Taken together, the results suggest that how people metaphorically conceptualize time can be modulated by taste, providing corroborative evidence for the embodied cognition that the understanding of abstract concepts are grounded in sensory, motor, and affective experiences.

Decoupling in the vertical shape of HCHO during a sea breeze event: The effect on trace gas satellite retrievals and column-to-surface translation

The effect of sea breeze circulation on stratification of the vertical formaldehyde (HCHO) concentration vertical profiles is explored using a regional atmospheric chemical transport model (CTM) for three synoptically stagnant days focused on the east coast of the U.S in June 2018. During this event, a significant thermal contrast between the Atlantic Ocean and the terrestrial regions (12–17 °C), observed by moderate resolution imaging spectroradiometer (MODIS) and well-captured by the WRF-CMAQ model (15–18 °C), is conducive to monsoon-like flow, perpendicular to the shorelines, carrying clean marine air masses over the land within a few hundreds of meters above the surface. In contrast, the westerly continental polluted air masses prevail in higher altitudes. These two conflicting flows result in atypical vertical shapes of HCHO concentrations increasing with altitude. This decoupling pattern is so pronounced that we observe total column HCHO negatively correlate with surface concentrations. Comparisons of an accredited global model, GEOS-CF, to surface wind measurements and MODIS skin temperature indicate its poor representation of the sea breeze timing and strength, resulting in GEOS-CF HCHO vertical shapes being drastically different from the WRF-CMAQ. Based on radiative transfer calculations, the differences in the vertical distribution of HCHO between the WRF-CMAQ and that of GEOS-CF in the first 3 km are sufficient to induce a 20–30% error in air mass factors (thus total vertical HCHO column abundances). Through an experiment involving converting HCHO total columns to surface mixing ratios, we demonstrate that GEOS-CF allocates noticeably more HCHO molecules (40–150%) to the surface layer due to the misrepresentation of the vertical shape of HCHO during the sea breeze event. It is known that a significant fraction of the human population lives in coastal areas prone to detrimental effects caused by air pollution, and elevated pollutant concentrations usually occur in synoptically stagnant atmospheric conditions when local circulation patterns come into play; accordingly, our experiments emphasize the importance of the effect a priori profiles can have on satellite-derived applications under such conditions. To ensure that the quantitative representation of satellite-based trace gas retrievals on a daily basis is trustworthy and useable for air quality applications, atmospheric models providing a priori profiles for satellite retrievals should be well-tuned to reproduce complex local circulation such as sea-land breezes.