Fitness Landscape Research Articles

Ecology and demography of early Homo sapiens: a synthesis of archaeological and climatic data from eastern Africa

ABSTRACT Eastern Africa maintains a key position in debates surrounding the emergence of Homo sapiens across Africa. Extensive research in the region has revealed a rich fossil record in association with a ‘generic’ but variable Middle Stone Age (MSA) material culture, providing an important laboratory for testing hypotheses about the behavioural evolution of our species. For example, multiple archaeological studies of the eastern African MSA note a link between the distribution and density of sites, archaeological diversity and environmental conditions, with ecology and demography often cited as key drivers of cultural evolution. This article formulates new hypotheses using theoretical models of complex fitness landscapes of evolution and reviews the archaeological and climatic records of Middle-late Pleistocene eastern Africa in the light of these ideas. It proposes that evidence from eastern Africa implicates much of the region as a refugial zone within Pleistocene Africa, providing consistently suitable conditions for survival that were characterised by high and changing biodiversity, facilitating population growth and interconnectivity as well as material culture diversification. Interactions between different evolutionary processes likely resulted in the complex cultural mosaic observed across Africa, including the appearance of ‘specific’ innovations against a backdrop of more ‘generic’ MSA elements.

A trade-off in evolution: the adaptive landscape of spiders without venom glands.

Venom glands play a key role in the predation and defense strategies of almost all spider groups. However, the spider family Uloboridae lacks venom glands and has evolved an adaptive strategy: they excessively wrap their prey directly with spider silk instead of paralyzing it first with toxins. This shift in survival strategy is very fascinating, but the genetic underpinnings behind it are poorly understood. Spanning multiple spider groups, we conducted multiomics analyses on Octonoba sinensis and described the adaptive evolution of the Uloboridae family at the genome level. We observed the coding genes of myosin and twitchin in muscles are under positive selection, energy metabolism functions are enhanced, and gene families related to tracheal development and tissue mechanical strength are expanded or emerged, all of which are related to the unique anatomical structure and predatory behavior of spiders in the family Uloboridae. In addition, we also scanned the elements that are absent or under relaxed purifying selection, as well as toxin gene homologs in the genomes of 2 species in this family. The results show that the absence of regions and regions under relaxed selection in these spiders' genomes are concentrated in areas related to development and neurosystem. The search for toxin homologs reveals possible gene function shift between toxins and nontoxins and confirms that there are no reliable toxin genes in the genome of this group. This study demonstrates the trade-off between different predation strategies in spiders, using either chemical or physical strategy, and provides insights into the possible mechanism underlying this trade-off. Venomless spiders need to mobilize multiple developmental and metabolic pathways related to motor function and limb mechanical strength to cover the decline in adaptability caused by the absence of venom glands.

On synergy between ultrahigh throughput screening and machine learning in biocatalyst engineering.

Protein design and directed evolution have separately contributed enormously to protein engineering. Without being mutually exclusive, the former relies on computation from first principles, while the latter is a combinatorial approach based on chance. Advances in ultrahigh throughput (uHT) screening, next generation sequencing and machine learning may create alternative routes to engineered proteins, where functional information linked to specific sequences is interpreted and extrapolated in silico. In particular, the miniaturisation of functional tests in water-in-oil emulsion droplets with picoliter volumes and their rapid generation and analysis (>1 kHz) allows screening of >107-membered libraries in a day. Subsequently, decoding the selected clones by short or long-read sequencing methods leads to large sequence-function datasets that may allow extrapolation from experimental directed evolution to further improved mutants beyond the observed hits. In this work, we explore experimental strategies for how to draw up 'fitness landscapes' in sequence space with uHT droplet microfluidics, review the current state of AI/ML in enzyme engineering and discuss how uHT datasets may be combined with AI/ML to make meaningful predictions and accelerate biocatalyst engineering.

Variable success in linking micro- and macroevolution

Abstract Attempts to predict macroevolution from microevolution, and microevolution from macroevolution, when natural selection is the main cause have met with varying success. Explanations for failure are numerous, but the reasons are uncertain even when a link is found. Here, I discuss possible explanations for outcomes of three efforts and ways to test them. First, quantitative genetic variation within populations often predicts directions of species divergence with surprising accuracy. Natural selection probably contributes to this pattern, but the evidence suggests that even long-term phenotypic evolution is influenced by enduring genetic biases. Second, the rate of evolution of reproductive isolation repeatedly fails to predict species diversification rates for unknown reasons. Suspicion falls on the influence of ecological and population demographic processes that might play a dominant role in the net rate of accumulation of species, an idea as yet little tested. Third, macroevolutionary patterns in the distribution of phenotypes of species in clades can in principle predict selection coefficients in diverging populations. I use the concept of adaptive landscape to suggest why the macroevolutionary signal of divergent selection is strongest at the time of splitting and why little information about selection coefficients from phylogenetic methods remains in the long run. Estimating adaptive landscapes from first principles would facilitate further efforts to link microevolution and macroevolution.

Strategic evaluation of e-learning: A case study of the university of Jordan during crisis

Crises possess a remarkable propensity to serve as catalysts for change, particularly within the sphere of education. They catalyze change in several key dimensions, including Accelerated Adoption of Technology, Highlighting Inequalities, Global Collaboration, Adaptation of Assessment Methods, Engagement with Online Resources, and Reimagining Education. In essence, crises compelling educational institutions to reevaluate long-standing norms and embrace innovative solutions. They shine a spotlight on challenges that may have remained overlooked and stimulate the formulation of strategies aimed at cultivating a more robust, adaptable, and inclusive educational landscape. This study provides a comprehensive strengths, weaknesses, opportunities, and threats (SWOT) analysis of E-learning at The University of Jordan amid the COVID-19 pandemic, offering valuable insights for strategic planning during crises. Based on data collected from 379 undergraduate students in the year 2022, it reveals strengths in terms of convenience and flexibility but highlights weaknesses such as low bandwidth and unstable internet connections. Additionally, it recognizes the opportunity for E-learning effectiveness during lockdowns while identifying threats like unreliable power supply and inconsistent internet access. This analysis enriches our understanding of the educational landscape and equips decision-makers with essential insights to enhance E-learning resilience and effectiveness during challenging times.

Graph Distance and Adaptive K-Nearest Neighbors Selection-Based Density Peak Clustering

Graph Distance and Adaptive K-Nearest Neighbors Selection-Based Density Peak Clustering

Nearest-Better Network for Fitness Landscape Analysis of Continuous Optimization Problems

Nearest-Better Network for Fitness Landscape Analysis of Continuous Optimization Problems

Navigating the landscape of enzyme design: from molecular simulations to machine learning.

Global environmental issues and sustainable development call for new technologies for fine chemical synthesis and waste valorization. Biocatalysis has attracted great attention as the alternative to the traditional organic synthesis. However, it is challenging to navigate the vast sequence space to identify those proteins with admirable biocatalytic functions. The recent development of deep-learning based structure prediction methods such as AlphaFold2 reinforced by different computational simulations or multiscale calculations has largely expanded the 3D structure databases and enabled structure-based design. While structure-based approaches shed light on site-specific enzyme engineering, they are not suitable for large-scale screening of potential biocatalysts. Effective utilization of big data using machine learning techniques opens up a new era for accelerated predictions. Here, we review the approaches and applications of structure-based and machine-learning guided enzyme design. We also provide our view on the challenges and perspectives on effectively employing enzyme design approaches integrating traditional molecular simulations and machine learning, and the importance of database construction and algorithm development in attaining predictive ML models to explore the sequence fitness landscape for the design of admirable biocatalysts.

The Three Worlds of Task Complexity

Aim/Purpose: To provide a systematic approach to defining task complexity using a three worlds model previously introduced in informing science research. Background: The task complexity construct presents researchers with a quandary. While it appears useful on the surface, repeated attempts to define it rigorously have failed to gain traction in the broader research community. The level of inconsistency between definitions is shown to have changed little in the past 20 years. Methodology: Using a common framework that treats task complexity as a latent construct residing between sources and outcomes, moderated by both task familiarity and task discretion, separate models for each of the three worlds are developed. Contribution: Our paper proposes a potential path forward by showing how many issues in past task complexity research can be reconciled by framing the construct according to the three worlds model: the world we experience, the world of human artifacts, and the “real world.” Findings: The framework defines experienced complexity as occurring in the mind of the task performer while performing a single task instance, intrinsic complexity as a function of the internal characteristics of the problem space used to perform a bounded set of task instances, and extrinsic complexity as the ruggedness of the fitness landscape in which the task is performed. Recommendation for Researchers: It offers a path to convergence for definitions of task complexity. Future Research: The three worlds of task complexity can potentially be applied to many practical problems.

Self-driving laboratories to autonomously navigate the protein fitness landscape

Protein engineering has nearly limitless applications across chemistry, energy and medicine, but creating new proteins with improved or novel functions remains slow, labor-intensive and inefficient. Here we present the Self-driving Autonomous Machines for Protein Landscape Exploration (SAMPLE) platform for fully autonomous protein engineering. SAMPLE is driven by an intelligent agent that learns protein sequence–function relationships, designs new proteins and sends designs to a fully automated robotic system that experimentally tests the designed proteins and provides feedback to improve the agent’s understanding of the system. We deploy four SAMPLE agents with the goal of engineering glycoside hydrolase enzymes with enhanced thermal tolerance. Despite showing individual differences in their search behavior, all four agents quickly converge on thermostable enzymes. Self-driving laboratories automate and accelerate the scientific discovery process and hold great potential for the fields of protein engineering and synthetic biology.

Smart fitness trainer using an advanced interdisciplinary approach

The Smart Fitness Trainer represents a pioneering endeavor at the intersection of diverse disciplines, amalgamating computer vision and Internet of Things (IoT) technologies. Its primary objective is to redefine the fitness landscape by introducing real-time exercise form analysis and assistance. Through the fusion of biomechanics, human-computer interaction, and data analytics, this innovative system provides instantaneous visual feedback via a mirror interface, thereby augmenting safety and efficacy during workout sessions. Embracing sophisticated interdisciplinary methodologies, the Smart Fitness Mirror fosters healthier lifestyles and delivers tailored training experiences, heralding a transformative era in fitness technology. This initiative underscores the transformative potential of collaborative multidisciplinary efforts in reshaping the domain of fitness and well-being.

Path-dependent speciation in dynamic fitness landscapes

Path-dependent speciation in dynamic fitness landscapes

Dynamics of Soil Fertility Indicators in Protective Forest Plantations

The purpose of the work is to analyze the dynamics of soil fertility indicators under forest belts in comparison with the inter-belt space in the agricultural landscape due to soil transformation under the influence of adaptive landscape farming systems. A comparative analysis of the variability of soil fertility indicators in forest belts and agrocenoses revealed similar trends in its direction and intensity, which indicates the uniform nature of the soil-forming process. However, some features have been identified. The humus content in the soils of forest belts is on average slightly higher than in the space between the belts. This is caused by higher (2 times) rates of humus accumulation in them in the first period after the development of landscape farming systems. It is during this period that the weedy and rhizomatous stages of restorative succession of the herbaceous flora of forest belts are confined, characterized by a powerful vegetative mass of vegetation and, consequently, an equally significant supply of fresh organic matter, rich in nutrients, into the soil.

Application of geoinformation systems in the agricultural complex

Precision farming, encompassing coordinated farming, adaptive landscape farming, and precision farming, represents a scientific paradigm in agricultural production that capitalizes on the inherent variability in soil fertility within localized areas. By tailoring practices to specific soil characteristics, precision farming optimizes profitability through the targeted application of fertilizers and plant protection products. Serving as the epitome of flexible landscape farming, precision farming integrates advanced agricultural technologies to achieve heightened productivity levels. Data collected through precision farming practices informs critical aspects of agricultural management, including strategic planting, precise calculation of input quantities, improved crop forecasting, and enhanced financial planning. Successful implementation of precision farming hinges on a thorough consideration of local soil attributes and climatic conditions, underscoring the importance of site-specific adaptation in modern agricultural strategies.

Intensity and Direction of Dynamics of Soil Fertility Indicators in Landscape Farming

The purpose of the work is to study the dynamics of soil fertility indicators after the development of adaptive landscape farming systems in the most eroded region of the Belgorod region since 1981. Based on 40 years of research at the model object “Turnip Log”, it is shown that the direction and intensity of the soil-forming process is changing. Four stages are distinguished: at the first until 1993 the decrease in humus content and alkalization of the soil environment, characteristic of washed away carbonate soils, continues; at the second stage, the rate of humus loss drops 10 times; the third ten-year period is characterized by a significant increase in organic matter and its stabilization subsequently, which accompanied by a transition in pHsol. to the area of neutral values. The dynamics of mobile forms of macroelements and agronomically valuable cations Ca2+ and Mg2+ indicate the cultivation of soils in general. At the same time, it is emphasized that there are no universal elements in the agricultural system; Along with the creation of an ecological framework of protective plantings, it is necessary to comply with the principles of adaptive placement of agricultural crops and a deficit-free balance of humus and nutrients in crop rotations.

ВЛИЯНИЕ КУЛЬТУР ТРАВОПОЛЬНОГО СЕВООБОРОТА НА ПЛОДОРОДИЕ ПОЧВЫ

The development of effective, highly productive crop rotations in modern agricultural production is an urgent task. The purpose of the research is to study the influence of grass–field crop rotation crops on agrophysical, biological indicators of soil fertility and crop yields. The research was carried out at the experimental site of the Department of Adaptive Landscape Agriculture of the National Research Institute of Agriculture of the VNC RAS in 2021-2022. The soil of the experimental site is represented by leached chernozems on pebbles. The experiments, phenological observations, and statistical processing of the obtained data were carried out according to generally accepted methods. Under various crops, the lumpy structure (at the beginning of the growing season) accounted for from 13.46 to 49.56%, the macrostructure – from 48.53 to 81.88%, aggregates less than 0.25 mm – from 1.88 to 8.01%. By the end of the growing season, the proportion of the dusty fraction under winter wheat decreased from 8.01% to 1.09%. The structural coefficient varied between 2.48 (corn) and 2.79 (oats + clover). The highest indicators of total porosity at the beginning of the growing season were noted under crops: oats + clover (57.5%), clover (57.6%) and potatoes (58.8%), and at the end of the growing season under clover (57.1%) and potatoes (59.6%). The highest yield of feed units was noted for the following variants: oats + clover – 9.83 t/ha, clover – 9.49 t/ha, corn – 9.49 t/ha. More digestible protein was contained in the clover crop, the rest of the crops were at about the same level. The best indicators of energy value were obtained for corn for grain – 101.0 GJ/ha, for perennial grasses of 1 and 2 years of use – 57.3-65.0 GJ/ha, winter wheat – 81.4 GJ/ha and potatoes – 69.9 GJ/ha.

The Influence of Landscape Farming Systems on the Fertility of Eroded Residual Carbonate Chernozem

The purpose of the work is to study the influence of adaptive landscape farming systems on the fertility indicators of eroded residual carbonate chernozem. The study of carbonate soils is of particular scientific and practical interest, since they are susceptible to easy destruction, accelerated degradation and increased difficulty in restoring fertility; they suffer more from water erosion and deflation. With the integrated use of all elements of adaptive landscape farming systems, primarily including anti-erosion organization of the territory that forms the soil-protective configuration of fields, a system of protective forest plantings, adaptive placement of agricultural crops, a fertilizer system aimed at a deficit-free balance of humus and nutrients, even in extremely difficult soil conditions. -relief conditions of the Krasnogvardeisky test site managed to stop soil erosion losses, which contributed to an increase in their fertility.

Adaptive Peak Extracting Transform and Its Application in Sedimentary Cycle Division

Adaptive Peak Extracting Transform and Its Application in Sedimentary Cycle Division

Analysis of Global Health System Readiness in Facing the Global Health Crisis: Lessons from the COVID-19 Pandemic and Strategies to Increase Resilience

The international fitness landscape has been substantially impacted with the useful resource of the emergence of exceptional challenges, with the COVID-19 pandemic serving as a paradigmatic crisis. This research seeks to behavior a whole evaluation of the readiness of the global fitness device in responding to such worldwide health crises. Drawing insights from the training observed out sooner or later of the COVID-19 pandemic, the have a study targets to come to be privy to strengths, weaknesses, and gaps inside the current international fitness infrastructure. Furthermore, the research will find out and advise strategies to decorate the resilience of the global fitness device, making sure a more effective and coordinated reaction to destiny fitness emergencies. By inspecting the intricacies of preparedness, response mechanisms, and collaborative efforts at the global degree, this observe contributes precious insights to the continuing discourse on strengthening worldwide health governance and resilience inside the face of evolving fitness annoying conditions.

SYSTEM OF AGROTECHNICAL ANTI-EROSION MEASURES IN THE CONDITIONS OF THE MOUNTAIN AREA OF THE UKRAINIAN CARPATHIANS

The results of research on the development of elements of ecologically safe directions for the creation of a model of soil protection systems of agriculture, based on the specific naturalclimatic and economic-economic conditions of the mountain zone of the Ukrainian Carpathians, which would provide an opportunity to ensure the necessary level of soil protection from water erosion, are presented. justified use of land resources, the expected level of their productivity and ecological balance in the region. namely, the technology of anti-erosion protection of sloping agricultural landscapes in the system of phytoremedial measures of the Carpathian mountain zone, which will ensure the preservation and reproduction of soil fertility, the structure of natural resources, their protection from erosive degradation in the context of climate change, risks of increased water erosion. Key words: reproduction of soil fertility, fertilizers, soil bacteria, ecologically safe land use, adaptive landscape farming system, land resources, rural areas, water erosion