Temporal Shifts Research Articles

Peripheral Modernisms and Parody of the Bildungsroman: A Comparative Case Study on Italo Svevo and A. H. Tanpınar

ABSTRACT This article offers a comparative reading of Italo Svevo and Ahmet Hamdi Tanpınar’s mock-development novels in light of the history of economic development in Italy and Turkey and their trajectories of integration into global capitalism. These authors from the semi-peripheries of Euromodernity employ strikingly similar modernist techniques in order to unsettle the bildungsroman and its humanist ideals. This article argues that the farcical use of psychoanalysis as a thematic attack on the unity of the subject, chronopathology in both form and content, and parody in style, situation, and plot represent peripheral narrative strategies developed as a response to being always already late vis-a-vis the hegemonic core culture. The classical bildungsroman is comically distorted and creatively adapted to the peripheral condition, becoming a key vehicle for reflecting on disintegrated subject positions, temporal shifts, untimely interruptions, and discordances. The form is simultaneously subverted and creatively adapted to the peripheral condition, reflecting the inevitable encounter with the hegemonic culture and the nation-state.

Fostering Creative Support for Change: Insights from Temporal Shifts in Employee Benefit Appraisals

Fostering Creative Support for Change: Insights from Temporal Shifts in Employee Benefit Appraisals

Effects of temporal hydrologic shifts on the population biology of an endangered freshwater fish in a dryland river ecosystem

AbstractSpecies occupying dryland river ecosystems often experience “boom‐and‐bust” demographic cycles that coincide with shifts in habitat availability. Knowing whether declines are within natural thresholds versus those caused by acute human disturbance is critical for managing protected species. We investigated temporal shifts in abundance and habitat use of an endangered population of the threespine stickleback Gasterosteus aculeatus in southern California, where a Mediterranean climate leads to ephemeral habitat in one of the regions' least hydrologically modified rivers, the Santa Clara River. We conducted population surveys over a period of below‐average rainfall in the upper watershed in Soledad Canyon, with predefined reaches surveyed multiple times per year to capture different hydrologic conditions. Abundances were stable across years but varied significantly depending on location, with some reaches remaining dry and others drying seasonally to varying degrees. Occupancy models showed that the presence of stable perennial reaches, drying regime, and other site‐specific factors were important predictors of habitat use, and that certain reaches may be key to ensuring source‐sink dynamics as flow dissipates over the dry season. Low occupancy in two sections was driven by different predominant mechanisms, one by diel cycles of evapotranspiration and the other by cattails (Typha spp.), with both having greater effects during the hotter, drier parts of the year. As dryland river ecosystems are vulnerable to the effects of anthropogenic‐induced climate change, this study demonstrates how temporal monitoring can delimit dry‐state benchmarks for improving management interventions (i.e., translocation and habitat restoration) for protected species under conditions that are predicted to worsen in the coming years.

Investigation on phytoplankton dynamics and its environmental correlates in the Xiangjiaba channel-type reservoir

Mega reservoirs, such as the Three Gorges Reservoir on the Yangtze River, have garnered significant attention due to their environmental impacts. However, the ecological ramifications of upstream cascade reservoirs remain understudied, despite their potential influence on the Yangtze River ecosystem. The Xiangjiaba Reservoir (XJB), presents a unique case for understanding the ecological impacts of large channel-type reservoirs marked with considerable water depth and extensive runoff, which lies between the characteristics of rivers and lakes. This study delves into the phytoplankton community dynamics and associated environmental factors within the XJB. Through field surveys and laboratory analysis, we explore the drivers of phytoplankton distribution and their temporal shifts. Our findings revel significant changes in phytoplankton dominance among various phyla. Bacillariophyta and Chlorophyta dominated throughout the year, while Cryptophyta prevailed in spring and Xanthophyta peaked in autumn, indicating a unique ecological feature of XJB. The reservoir’s water quality was found to be moderate. The average chlorophyll-a exhibited significant spatial–temporal variations, peaking at 26 μg/L at the mainstream-tributary confluence. Our investigation reveals a tenfold increase in algal abundance since the reservoir’s inception, accompanied by a significant transition from a Bacillariophyta-dominated community to a diverse, multi-phylum system. This shift has been significantly influenced by hydrodynamic conditions, with water stratification favoring flagellated algae like Chlorophyta and Cryptophyta. Notably, differences in phytoplankton composition between XJB and the Three Gorges Reservoir were linked to the latter’s pronounced vertical mixing. The slower ecological responses of the phytoplankton community to hydrodynamic changes underscore the importance of long-term, continuous monitoring to maintain the reservoir’s ecological balance. Our research offers insights into the ecological impacts of reservoir construction, highlighting the role of hydrodynamics in reservoir ecosystems and aiding in understanding reservoir functioning, water quality management, and biodiversity conservation.

Spatial and temporal variation in respiratory syncytial virus (RSV) subtype RNA in wastewater and relation to clinical specimens.

Respiratory syncytial virus (RSV) causes a large burden of respiratory illness globally. It has two subtypes, RSV A and RSV B, but little is known regarding the predominance of these subtypes during different seasons and their impact on morbidity and mortality. Using molecular methods, we quantified RSV A and RSV B RNA in wastewater solids across multiple seasons and metropolitan areas to gain insight into the predominance of RSV subtypes. We determined the predominant subtype for each group using the proportion of RSV A to total RSV (RSV A + RSV B) in each wastewater sample (PA,WW) and conducted a comparative analysis temporally, spatially, and against clinical specimens. A median PA,WW of 0.00 in the first season and 0.58 in the second season indicated a temporal shift in the predominant subtype. Spatially, while we observed dominance of the same subtype, PA,WW was higher in some areas (PA,WW = 0.58-0.88). The same subtype predominated in wastewater and clinical samples, but clinical samples showed higher levels of RSV A (RSV A positivity in clinical samples = 0.79, median PA,WW = 0.58). These results suggest that wastewater, alongside clinical data, holds promise for enhanced subtype surveillance.IMPORTANCERespiratory syncytial virus (RSV) causes a large burden of respiratory illness globally. It has two subtypes, RSV A and RSV B, but little is known regarding the predominance of these subtypes during different seasons and their impact on morbidity and mortality. The study illustrates that information on subtype predominance can be gleaned from wastewater. As a biological composite sample from the entire contributing population, wastewater monitoring of RSV A and B can complement clinical surveillance of RSV.

Selective Enrichment of Methylococcaceae versus Methylocystaceae Methanotrophs via Control of Methane Feeding Schemes.

Methanotrophs are crucial in keeping environmental CH4 emissions in check. However, the contributions of different groups of methanotrophs at terrestrial CH4-oxidation hotspots, such as the oxic-anoxic interface of rice paddies, have shown considerable inconsistency across observations. To address the knowledge gap regarding this inconsistency, methanotrophic microbiomes were enriched from paddy soils in well-mixed CH4-fed batch reactors under six different incubation conditions, prepared as combinations of two CH4 mixing ratios (0.5 and 10%) and three supplemented Cu2+ concentrations (0, 2, and 10 μM). Monitoring of temporal community shifts in these cultures revealed a dominance of Methylocystis spp. in all 0.5%-CH4 cultures, while methanotrophs affiliated to Gammaproteobacteria dominated the 10%-CH4 cultures that were less consistent both temporally and across conditions. The shotgun metagenome analyses of the 0.5%-CH4 cultures corroborated the Methylocystis dominance and, interestingly, showed that copper deficiency did not select for mmoXYZ-possessing methanotrophs. Instead, a mbn cluster, accounting for approximately 5% of the Methylocystis population, was identified, suggesting the ecological significance of methanobactin in Cu-deficient methanotrophy. These findings underscore the important role of Methylocystis spp. in mitigating emissions from terrestrial CH4 hotspots and suggest the feasibility of directed enrichment and/or isolation of Methylocystis spp. for utilization in, for example, methanobactin and polyhydroxybutyrate production.

Temporal temperature shifts govern the population succession of picoeukaryotes and picocyanobacteria in a coastal ecosystem

Picophytoplankton are vital components of the marine microbial food web. Being the smallest in the phytoplankton group, their short life cycles make them excellent bioindicators of environmental conditions. Given this, an investigation was conducted at the Kandla Port ecosystem (Latitude 23º 01' N; Longitude 70º 13' E) in the state of Gujarat, India to assess the response of picophytoplankton community structure to temporal and spatial environmental conditions. The sampling was conducted in July 2015, October-November 2015, and February 2016 at twenty-six stations. The results revealed a wide annual temperature range due to the study site's proximity to the Tropic of Cancer. The salinity ranged up to 40 while the turbulence caused by the macrotides resulted in highly turbid waters, especially during July due to precipitation. The picophytoplankton community was represented by picocyanobacteria (three sub-groups of Synechococcus) and picoeukaryotes (three sub-groups including Cryptophytes). The picocyanobacteria were abundant during the less turbid, warmer October-November period and lower during the cooler February period. The dominant Synechoccocus groups are associated positively with NH4+ and negatively with PO43-. The Cryptophytes were present during the warm and cool periods indicating tolerance to a wide range of temperature, salinity, and light. Their positive correlation with PO43- and NH4+ concentrations during February and October-November, respectively suggests a causal relationship. The picoeukaryotic group dominated the picophytoplankton community during the cooler period (February). The relative importance of the two picophytoplankton groups changed throughout the year exhibiting temporal niche segregation and hence establishing their role as bioindicators of temperature.

Area ReSTIR: Resampling for Real-Time Defocus and Antialiasing

Recent advancements in spatiotemporal reservoir resampling (ReSTIR) leverage sample reuse from neighbors to efficiently evaluate the path integral. Like rasterization, ReSTIR methods implicitly assume a pinhole camera and evaluate the light arriving at a pixel through a single predetermined subpixel location at a time (e.g., the pixel center). This prevents efficient path reuse in and near pixels with high-frequency details. We introduce Area ReSTIR , extending ReSTIR reservoirs to also integrate each pixel's 4D ray space, including 2D areas on the film and lens. We design novel subpixel-tracking temporal reuse and shift mappings that maximize resampling quality in such regions. This robustifies ReSTIR against high-frequency content, letting us importance sample subpixel and lens coordinates and efficiently render antialiasing and depth of field.

To stay or not to stay? Temporal shifts in dung beetle occupancy in a cloud forest landscape

To stay or not to stay? Temporal shifts in dung beetle occupancy in a cloud forest landscape

Dual carbon goal and agriculture in China: Exploring key factors influencing farmers’ behavior in adopting low carbon technologies

Identifying the factors influencing farmers’ adoption of low-carbon technologies (FA) and understanding their impacts are essential for shaping effective agricultural policies amied at emission reduction and carbon sequestration in China. This study employs a meta-analysis of 122 empirical studies, delves into 23 driving factors affecting FA and addresses the inconsistencies present in the existing literature. We systematically examine the effect size, source of heterogeneity, and time-accumulation effect of the driving factors on FA. We find that significant heterogeneity in the factors influencing FA, except for farming experience, sources of heterogeneity from the survey zone, methodology model, technological attributes, report source, financial support, and the sampling year. Additionally, age, farming experience, and adoption cost negatively correlate with FA. In contrast, educational level, health status, technical training, economic and welfare cognition, land contract, soil quality, terrain, information accessibility, demonstration, government promotion, government regulation, government support, agricultural cooperatives member, peer effect, and agricultural income ratio demonstrate a positive correlation. Especially, demonstration and age show a particularly strong correlation. Finally, the effect of demonstration, age, economic and welfare cognition, farming experience, land contract, soil quality, information accessibility, government promotion, and support, as well as agricultural cooperative membership and peer effects on FA, are generally stable but exhibit varying degrees of attenuation over time. The effect of village cadre, family income, farm scale, gender, health status, technical training, and off-farm work on FA show notable temporal shifts and maintain a weak correlation with FA. This study contributes to shaping China's current low-carbon agriculture policies across various regions. It encourages policymakers to comprehensively consider the stability of key factors, other potential factors, technological attributes, rural socio-economic context, and their interrelations.

Streamflow in the United States: Characteristics, trends, regime shifts, and extremes

Long-term streamflow observations contain essential information for understanding hydrological changes and managing water resources. A continental-scale dataset or analysis of temporal streamflow change is still lacking across hydrologic gauges in the Conterminous United States (CONUS). Here, we compiled 70 years of streamflow records from 1951 to 2021 at ~ 8000 hydrologic stations across the CONUS and characterized temporal trends, regime shifts, and extreme events using a Bayesian time series analysis algorithm. We found that the occurrences of sudden streamflow changes (e.g., regime shifts and extreme events) have been increasing with time across the CONUS. In addition, we derived 181 streamflow indicators that are valuable for hydrological and biological applications, such as the duration and frequency of high or low streamflow events. The Mississippi River Basin, especially the middle and lower parts, was a hot spot of high-frequency high-flow events. Overall, we anticipate the dataset generated here offers valuable information for understanding and quantifying changes in water resources across the CONUS.

Quantitative Stock Selection Model Using Graph Learning and a Spatial–Temporal Encoder

In the rapidly evolving domain of finance, quantitative stock selection strategies have gained prominence, driven by the pursuit of maximizing returns while mitigating risks through sophisticated data analysis and algorithmic models. Yet, prevailing models frequently neglect the fluid dynamics of asset relationships and market shifts, a gap that undermines their predictive and risk management efficacy. This oversight renders them vulnerable to market volatility, adversely affecting investment decision quality and return consistency. Addressing this critical gap, our study proposes the Graph Learning Spatial–Temporal Encoder Network (GL-STN), a pioneering model that seamlessly integrates graph theory and spatial–temporal encoding to navigate the intricacies and variabilities of financial markets. By harnessing the inherent structural knowledge of stock markets, the GL-STN model adeptly captures the nonlinear interactions and temporal shifts among assets. Our innovative approach amalgamates graph convolutional layers, attention mechanisms, and long short-term memory (LSTM) networks, offering a comprehensive analysis of spatial–temporal data features. This integration not only deciphers complex stock market interdependencies but also accentuates crucial market insights, enabling the model to forecast market trends with heightened precision. Rigorous evaluations across diverse market boards—Main Board, SME Board, STAR Market, and ChiNext—underscore the GL-STN model’s exceptional ability to withstand market turbulence and enhance profitability, affirming its substantial utility in quantitative stock selection.

Age-specific composition of milk microbiota in Tibetan sheep and goats

This study investigates the dynamic changes in milk nutritional composition and microbial communities in Tibetan sheep and goats during the first 56 days of lactation. Milk samples were systematically collected at five time points (D0, D7, D14, D28, D56) post-delivery. In Tibetan sheep, milk fat, protein, and casein contents were highest on D0, gradually decreased, and stabilized after D14, while lactose and galactose levels showed the opposite trend. Goat milk exhibited similar initial peaks, with significant changes particularly between D0, D7, D14, and D56. 16S rRNA gene sequencing revealed increasing microbial diversity in both species over the lactation period. Principal coordinates analysis identified distinct microbial clusters corresponding to early (D0–D7), transitional (D14–D28), and mature (D56) stages. Core phyla, including Proteobacteria, Firmicutes, Bacteroidetes, and Actinobacteria, dominated the milk microbiota, with significant temporal shifts. Core microbes like Lactobacillus, Leuconostoc, and Streptococcus were common in both species, with species-specific taxa observed (e.g., Pediococcus in sheep, Shewanella in goats). Furthermore, we observed a highly shared core microbiota in sheep and goat milk, including Lactobacillus, Leuconostoc, and Streptococcus. Spearman correlation analysis highlighted significant relationships between specific microbial genera and milk nutrients. For instance, Lactobacillus positively correlated with total solids, non-fat milk solids, protein, and casein, while Mannheimia negatively correlated with protein content. This study underscores the complex interplay between milk composition and microbial dynamics in Tibetan sheep and goats, informing strategies for livestock management and nutritional enhancement.Key points• The milk can be classified into three types based on the microbiota composition• The changes of milk microbiota are closely related to the variations in nutrition• Filter out microbiota with species specificity and age specificity in the milk

Evidence for seasonal shift in the reproduction of Aldabra giant tortoises (Aldabrachelys gigantea) in managed care in the Northern hemisphere compared to the natural habitat in the Southern hemisphere.

Ex situ breeding constitutes an important tool for species conservation; however, many reptile species are not managed sustainably under human care due to poor fecundity in ex situ settings. In this study, we tested whether the translocation of a seasonally reproducing species to a different environment results in decoupling of extrinsic signals and intrinsic conditions. The endocrinological patterns of plasma steroid sex hormones, follicular development, and mating behaviour of two female and two male sexually mature Aldabra tortoises (Aldabrachelys gigantea) in a zoological institution in the Northern hemisphere was aligned with enclosure climate data (mean monthly daylight duration, temperature, and precipitation) and compared with respective hormone patterns of wild individuals and climate conditions in the native habitat on the Aldabra Atoll in the Southern hemisphere. Whereas occurrence of mating behaviour was not considered a limiting factor, lack of ovulation and subsequent follicular atresia was the main reason for the lack of reproductive output. While it was impossible to elucidate the triggering factors of ovulation and the multifactorial complexity of reproduction was not fully addressed, this study indicates suboptimal temperature conditions and relative temporal shifts of interacting external triggers (temperature and photoperiod) in the zoo setting.

Temporal shifts in the phytoplankton network in a large eutrophic shallow freshwater lake subjected to major environmental changes due to human interventions

Phytoplankton communities are crucial components of aquatic ecosystems, and since they are highly interactive, they always form complex networks. Yet, our understanding of how interactive phytoplankton networks vary through time under changing environmental conditions is limited. Using a 29-year (339 months) long-term dataset on Lake Taihu, China, we constructed a temporal network comprising monthly sub-networks using “extended Local Similarity Analysis” and assessed how eutrophication, climate change, and restoration efforts influenced the temporal dynamics of network complexity and stability. The network architecture of phytoplankton showed strong dynamic changes with varying environments. Our results revealed cascading effects of eutrophication and climate change on phytoplankton network stability via changes in network complexity. The network stability of phytoplankton increased with average degree, modularity, and nestedness and decreased with connectance. Eutrophication (increasing nitrogen) stabilized the phytoplankton network, mainly by increasing its average degree, while climate change, i.e., warming and decreasing wind speed enhanced its stability by increasing the cohesion of phytoplankton communities directly and by decreasing the connectance of network indirectly. A remarkable shift and a major decrease in the temporal dynamics of phytoplankton network complexity (average degree, nestedness) and stability (robustness, persistence) were detected after 2007 when numerous eutrophication mitigation efforts (not all successful) were implemented, leading to simplified phytoplankton networks and reduced stability. Our findings provide new insights into the organization of phytoplankton networks under eutrophication (or re-oligotrophication) and climate change in subtropical shallow lakes.

FTAN: Frame-to-frame temporal alignment network with contrastive learning for few-shot action recognition

Most current few-shot action recognition approaches follow the metric learning paradigm, measuring the distance of any sub-sequences (frames, any frame combinations or clips) between different actions for classification. However, this disordered distance metric between action sub-sequences ignores the long-term temporal relations of actions, which may result in significant metric deviations. What's more, the distance metric suffers from the distinctive temporal distribution of different actions, including intra-class temporal offsets and inter-class local similarity. In this paper, a novel few-shot action recognition framework, Frame-to-frame Temporal Alignment Network (FTAN), is proposed to address the above challenges. Specifically, an attention-based temporal alignment (ATA) module is devised to calculate the distance between corresponding frames of different actions along the temporal dimension to achieve frame-to-frame temporal alignment. Meanwhile, the Temporal Context module (TCM) is proposed to increase inter-class diversity by enriching the frame-level feature representation, and the Frames Cyclic Shift Module (FCSM) performs frame-level temporal cyclic shift to reduce intra-class inconsistency. In addition, we present temporal and global contrastive objectives to assist in learning discriminative and class-agnostic visual features. Experimental results show that the proposed architecture achieves state-of-the-art on HMDB51, UCF101, Something-Something V2 and Kinetics-100 datasets.

Reduced actual vapor pressure exerts a significant influence on maize yield through vapor pressure deficit amid climate warming.

Understanding the impact of climate warming on crop yield and its associated mechanisms is paramount for ensuring food security. Here, we conduct a thorough analysis of the impact of vapor pressure deficit (VPD) on maize yield, leveraging a rich dataset comprising temporal and spatial observations spanning 40 years across 31 maize-growing locations in Northeast and North China. Our investigation extends to the influencing meteorological factors that drive changes in VPD during the maize growing phase. Regression analysis reveals a linear negative relationship between VPD and maize yield, demonstrating diverse spatiotemporal characteristics. Spatially, maize yield exhibits higher sensitivity to VPD in Northeast China (NEC), despite the higher VPD levels in North China Plain (NCP). The opposite patterns reveal that high VPD not invariably lead to detrimental yield impacts. Temporal analysis sheds light on an upward trend in VPD, with values of 0.05 and 0.02 kPa/10yr, accompanied by significant abrupt changes around 1996 in NEC and 2006 in NCP, respectively. These temporal shifts contribute to the heightened sensitivity of maize yield in both regions. Importantly, we emphasize the need to pay closer attention to the substantial the impact of actual vapor pressure on abrupt VPD changes during the maize growing phase, particularly in the context of ongoing climate warming.

Spatial and Temporal Shifts of Endophytic Bacteria in Conifer Seedlings of Abies religiosa (Kunth) Schltdl. & Cham.

Endophytes play an important role in plant development, survival, and establishment, but their temporal dynamics in young conifer plants are still largely unknown. In this study, the bacterial community was determined by metabarcoding of the 16S rRNA gene in the rhizoplane, roots, and aerial parts of 1- and 5-month-old seedlings of natural populations of Abies religiosa (Kunth) Schltdl. & Cham. In 1-month-old seedlings, Pseudomonas dominated aerial parts (relative abundance 71.6%) and roots (37.9%). However, the roots exhibited significantly higher bacterial species richness than the aerial parts, with the dissimilarity between these plant sections mostly explained by the loss of bacterial amplification sequence variants. After 5 months, Mucilaginibacter dominated in the rhizoplane (9.0%), Streptomyces in the roots (12.2%), and Pseudomonas in the aerial parts (18.1%). The bacterial richness and community structure differed significantly between the plant sections, and these variations were explained mostly by 1-for-1 substitution. The relative abundance of putative metabolic pathways significantly differed between the plant sections at both 1 and 5 months. All the dominant bacterial genera (e.g., Pseudomonas and Burkholderia-Caballeronia-Paraburkholderia) have been reported to have plant growth-promoting capacities and/or antagonism against pathogens, but what defines their role for plant development has still to be determined. This investigation improves our understanding of the early plant-bacteria interactions essential for natural regeneration of A. religiosa forest.

Weakened connection between spring leaf-out and autumn senescence in the Northern Hemisphere.

Vegetation autumn phenology is critical in regulating the ecosystem carbon cycle and regional climate. However, the dominant drivers of autumn senescence and their temporal shifts under climate change remain poorly understood. Here, we conducted a multi-factor analysis considering both direct climatic controls and biological carryover effects from start-of-season (SOS) and seasonal peak vegetation activities on the end-of-season (EOS) to fill these knowledge gaps. Combining satellite and ground observations across the northern hemisphere, we found that carryover effects from early-to-peak vegetation activities exerted greater influence on EOS than the direct climatic controls on nearly half of the vegetated land. Unexpectedly, the carryover effects from SOS on EOS have significantly weakened over recent decades, accompanied by strengthened climatic controls. Such results indicate the weakened constraint of leaf longevity on senescence due to prolonged growing season in response to climate change. These findings underscore the important role of biological carryover effects in regulating vegetation autumn senescence under climate change, which should be incorporated into the formulation and enhancement of phenology modules utilized in land surface models.

Time is of the essence: A general framework for uncovering temporal structures of communities.

Ecological communities are inherently dynamic: species constantly turn over within years, months, weeks or even days. These temporal shifts in community composition determine essential aspects of species interactions and how energy, nutrients, information, diseases and perturbations 'flow' through systems. Yet, our understanding of community structure has relied heavily on static analyses not designed to capture critical features of this dynamic temporal dimension of communities. Here, we propose a conceptual and methodological framework for quantifying and analysing this temporal dimension. Conceptually, we split the temporal structure into two definitive features, sequence and duration, and review how they are linked to key concepts in ecology. We then outline how we can capture these definitive features using perspectives and tools from temporal graph theory. We demonstrate how we can easily integrate ongoing research on phenology into this framework and highlight what new opportunities arise from this approach to answer fundamental questions in community ecology. As climate change reshuffles ecological communities worldwide, quantifying the temporal organization of communities is imperative to resolve the fundamental processes that shape natural ecosystems and predict how these systems may change in the future.