Miracle-dz/UniFAR-FTUs huggingface dataset:
A genomic assessment of the marine-speciation paradox within the toothed whale 1 superfamily Delphinoidea

The importance of post-divergence gene flow in speciation has been documented 14 across a range of taxa in recent years, and may have been especially widespread in highly 15 mobile, wide-ranging marine species, such as cetaceans. Here, we studied individual 16 genomes from nine species across the three families of the toothed whale superfamily Delphinoidea (Delphinidae, Phocoenidae, Monodontidae). To investigate the role of post- 18 divergence gene flow in the speciation process, we used a multifaceted approach, including: 19 (i) phylogenomics, (ii) the distribution of shared derived alleles, and (iii) demographic 20 inference. We found the divergence of lineages within Delphinoidea did not follow a process 21 of pure bifurcation, but was much more complex. Sliding-window phylogenomics reveal a 22 high prevalence of discordant topologies within the superfamily, with further analyses 23 indicating these discordances arose due to both incomplete lineage sorting and gene flow. D- statistics, D-foil, and f -branch analyses supported gene flow between members of 25 Delphinoidea, with the vast majority of gene flow occurring as ancient interfamilial events. Demographic analyses provided evidence that introgressive gene flow has likely ceased between all species pairs tested, despite reports of contemporary interspecific hybrids. Our 28 study provides the first steps towards resolving the large complexity of speciation
Fault-tolerant Control of Overactuated Multirotor UAV Platform under Propeller Failure

—Propeller failure is one major reason for the falling and crashing of multirotor Unmanned Aerial Vehicles (UAVs). While conventional multirotors can barely handle this issue due to underactuation, over-actuated platforms can still pursue the flight with proper fault-tolerant control (FTC). This paper investigates such a controller for one such over-actuated multirotor aerial platform composing quadcopters mounted on passive joints with input redundancy in both the high-level vehicle control and the low-level quadcopter control of vectored thrusts. To fully utilize the input redundancies of the whole platform under propeller failure, our proposed FTC controller has a hierarchical control architecture with three main components: (i) a low-level adjustment strategy to avoid propeller-level thrust saturation; (ii) a compensation loop to attenuate introduced disturbance; (iii) a nullspace-based control allocation framework to avoid quadcopter-level thrust saturation. Through reallocating actuator inputs in both the low-level and high-level control loops, the low-level quadcopter control can be maintained with at most two failed propellers and the whole platform can be stabilized without crashing. The proposed controller is extensively studied in both simulation and real-world experiments to demonstrate its superior performance.
Evidence of Decoupling in Bitcoin-Stock Market Price Relationship

: C ryptocurrency has gained widespread acceptance among speculators and investors alike owing to its volatility and its promised utility. With a burgeoning crypto market cap, dominated by Bitcoin, it is of paramount importance to identify and establish the relationship between an evolving Bitcoin and the backbone of traditional economic system - Stock market. This paper focuses on (a) Establishing instability and finding structural breaks (b) Identifying causal relationships between Bitcoin and S&P 500 (c)Using time series analysis to hypothesize decoupling of Bitcoin and stock market. The time series uses Daily prices, dating back to 2014. For the purposes of identifying structural breaks - CUSUM and Bai-Perron tests were used. Empirical relationship between Bitcoin and S&P 500 were identified using Granger full sample causality and Johannsen’s Cointegration test. Impulse response tests were performed. Finally, DCC-GARCH setup was used for measuring spill overs in volatility. The paper finds break dates at 2017:10 and 2020:9. Through establishing the linkages,
Theoretical investigation of the mechanism, stereoselectivity and regioselectivity of the epoxidation reaction of γ-himachalene: MEDT screening

Plants represent an immense source of complex chemical molecules exploited in the perfume, agro-food, cosmetic and pharmaceutical industries. Most plants contain essential oils; they are then entitled “aromatic plants". These essential oils are found in many parts of the plant: wood, leaves, fruits, bark, seeds and roots. These are complex mixtures consisting of several tens, or even more than one hundred compounds, mainly terpenes and aromatic compounds. Essential oils have many biological activities; they are utilized for their antiseptic properties against bacterial diseases, for example against the endocranial bacteria [1] or at the level of the vaginal microflora [2,3]. However, they also have cytotoxic properties [4] that bring them closer to antiseptics and disinfectants as broad spectrum antimicrobial agents [5]. The essential oils have antibacterial properties, antioxidant activity [6] and potential applications in foods [7], essential oils or their active compounds could also be used as protection agents against phytopathogenic fungi and microorganisms invading foodstuffs [8,9]. The essential oils of cedar of the Atlas which constituted by three elements such as α-himachalene, β-himachalene and γ-himachalene (Scheme 1 and Figure 1).
Analyzing ransomware negotiations with CONTI: An in-depth analysis

CONTI is a ransomware group that uses a double extortion attack to force its victims into paying. The group has more than $14m confirmed payments in bitcoin and has several high-profile victims in its portfolio. The latter is verified by the publication of the exfiltrated data of the victims who did not pay the requested ransom. Given the modus operandi of the group, we managed to intercept many of their negotiations, which provided us with intelligence into how they operate. The studied interactions correspond to more than a third of their earnings and are therefore quite indicative of how they work as a group.
Game Theory Solutions in Sensor-Based Human Activity Recognition: A Review

The Human Activity Recognition (HAR) tasks automatically identify human activities using the sensor data, which has numerous applications in healthcare, sports, security, and human-computer interaction. Despite significant advances in HAR, critical challenges still exist. Game theory has emerged as a promising solution to address these challenges in machine learning problems including HAR. However, there is a lack of research work on applying game theory solutions to the HAR problems. This review paper explores the potential of game theory as a solution for HAR tasks, and bridges the gap between game theory and HAR research work by suggesting novel game-theoretic approaches for HAR problems. The contributions of this work include exploring how game theory can improve the accuracy and robustness of HAR models, investigating how game-theoretic concepts can optimize recognition algorithms, and discussing the game-theoretic approaches against the existing HAR methods. The objective is to provide insights into the potential of game theory as a solution for sensor-based HAR, and contribute to develop a more accurate and efficient recognition system in the future research directions.
Characterization of the lumbricid fauna in alluvial soils in the Danube River floodplain area east of

Introduction The „Stopfenreuther Au", situated along the Danube River east of Vienna, is among the largest coherent natural floodplain areas in Central Europe. Ecological processes in the river-adjacent woodland are heavily influenced by submersion dynamics and the fluctuating groundwater level. Inundations not only affect erosion and sedimentation of soil material, but also provide a high amount of nutritive substances. On one hand, the plants and soil fauna inhabiting floodplains are therefore favoured by an abundant food supply, while on the other hand they must withstand disturbances caused by continuing changes of sedimentation and soil formation. Depending on the distance to the Danube and on the formation of soil strata, a great variety of biocenoses have developed. Like the vegetation, which shows a typical zonation from pioneer communities over the softwood forest near the river to the hardwood forest, soil animal communities are composed of differing portions of aquatic, inundation-tolerant and terrestrial species (DÜNGER 1983). ZULKA (1989, 1991) studied the distribution of soil arthropods in flooded and non-flooded areas at the Morava River (March) in Lower Austria for several years and found conspicuous differences of the species composition. The macrofauna (Isopoda, Diplopoda, Lithobiomorpha) showed a higher density and diversity in the non-flooded terraces. Floodplains house earthworms in comparatively great individual and species numbers (EMMERLING 1995). The occurrence of particular lumbricid species depends both on physicochemical factors such as humidity, temperature, acidity, carbon dioxide concentration, oxygen pressure etc. and on the supply of food (EDWARDS & LOFTY 1972; LEE 1985). HÖSER (1990) pointed to the importance of the nutrient usability, i.e. the quality (stage of decomposition) and dispersion (concentration) of food items in the soil. This usability is affected chiefly by the nature and composition of leaf litter and by sedimentation and stratification processes. In the "Stopfenreuther Au", lumbricid community structure, abundance, biomass and life-form © Biologiezentrum Linz/Austria; download unter www.biologiezentrum. at
International Migration and Citizenship Today

Section 1: Introduction 1. Introduction Section 2: Immigrants 2. Accepting Immigrants 3. Dealing with the Unwanted 4. Impact of Immigrants Section 3: Refugees 5. Modern Efforts to Protect Refugees 6. Problems of Protection Section 4: Citizenship 7. Rise of Nationalism and Citizenship 8. Naturalization Section 5: Conclusion 9. Beyond Conventional Approaches to Migration and Citizenship
Robust Communication-Optimal Distributed Clustering Algorithms

In this work, we study the $k$-median and $k$-means clustering problems when the data is distributed across many servers and can contain outliers. While there has been a lot of work on these problems for worst-case instances, we focus on gaining a finer understanding through the lens of beyond worst-case analysis. Our main motivation is the following: for many applications such as clustering proteins by function or clustering communities in a social network, there is some unknown target clustering, and the hope is that running a $k$-median or $k$-means algorithm will produce clusterings which are close to matching the target clustering. Worst-case results can guarantee constant factor approximations to the optimal $k$-median or $k$-means objective value, but not closeness to the target clustering. Our first result is a distributed algorithm which returns a near-optimal clustering assuming a natural notion of stability, namely, approximation stability [Balcan et. al 2013], even when a constant fraction of the data are outliers. The communication complexity is $\tilde O(sk+z)$ where $s$ is the number of machines, $k$ is the number of clusters, and $z$ is the number of outliers. Next, we show this amount of communication cannot be improved even in the setting when the input satisfies various non-worst-case assumptions. We give a matching $\Omega(sk+z)$ lower bound on the communication required both for approximating the optimal $k$-means or $k$-median cost up to any constant, and for returning a clustering that is close to the target clustering in Hamming distance. These lower bounds hold even when the data satisfies approximation stability or other common notions of stability, and the cluster sizes are balanced. Therefore, $\Omega(sk+z)$ is a communication bottleneck, even for real-world instances.
Current Research in Ecological and Social Psychology

Climate change attributable to human activities has created a global threat to humanity and the natural world. However, there is a tendency for people to view climate change as a threat primarily aﬀecting those in far-away places and there is reluctance to engage in pro-environmental action, which is often costly. It is therefore crucial to understand the factors that shape willingness to engage in pro-environmental behavior. Existing research suggests that personal experience with the consequences of climate change may increase pro-environmental action, however it is unknown whether personal experiences in other non-environmental domains may have similar ef-fects. The circumstances of the Covid-19 pandemic allowed us to conduct a quasi-natural experiment to examine the eﬀects of personal experience with a diﬀerent global threat, namely Covid-19, on environmental responses. Across two studies conducted among UK and US participants, we found that personal experience of Covid-19 was associated with pro-environmental behavioral intentions, and that this relationship was mediated by increased environmental concern. We found that personal experience with Covid-19 was associated with stronger self- transcendence values of universalism and benevolence, which played a further mediating role between personal experience with the virus and environmental concern. These ﬁndings suggest that personal experience with at least some global threats, even when not directly related to climate change, may increase concern for distant others and also sensitize people to environmental issues and motivate pro-environmental action.
Current Research in Ecological and Social Psychology

Anthropomorphism of nature is known to be related to pro-environmental outcomes; however, little is known about these variables in the context of the coronavirus pandemic. The economic impact of the prolonged lockdowns may disrupt the historical relationship between these variables, as ﬁnancial insecurity may compete with environmental concerns for consideration. This study examined the relationship between anthropomorphism of nature the context of COVID-19, and pro-environmental support, and the potential moderating role of ﬁnancial insecurity in this relationship. It was hypothesised that anthropomorphism of nature in the context of COVID-19 would have a lesser eﬀect on pro-environmental support for individuals who experienced ﬁnancial insecurity during the pandemic. Participants ( N = 615 ; M age = 48.71, SD age = 17.50; 70% female) completed self-report measures of anthropomorphism of nature, anthropomorphism of nature in the context of COVID-19, ﬁnancial insecu- rity, and a measure of support for pro-environmental policies in the economic recovery from COVID-19. Results demonstrated that, after controlling for general anthropomorphism of nature, anthropomorphism of nature in the context of COVID-19 predicted pro-environmental support ( R 2 = .05, F (4, 610) = 8.36, p < . 001). However, con-trary to expectation, pro-environmental support was higher in those experiencing ﬁnancial insecurity compared to those who were ﬁnancially secure ( B = -2.65, BootSE = .93, p = .004, 95% BootCI [-4.47, -.83]). Financial insecurity also did not moderate the relationship between anthropomorphism of nature in the COVID-19 con- text and pro-environmental support. Furthermore, the general tendency to anthropomorphise nature was not a signiﬁcant predictor of support for pro-environmental policies. These ﬁndings have important implications for understandings of anthropomorphism, ﬁnancial insecurity, and environmental protection as well as for public policy on economic recovery in response to the coronavirus pandemic.
Current Research in Ecological and Social Psychology

In the early days of the coronavirus outbreak, we observed mask use in public among 1,330 people across China. People in regions with a history of farming rice wore masks more often than people in wheat regions. Cultural diﬀerences persisted after taking into account objective risk factors such as local COVID cases. The diﬀerences ﬁt with the emerging theory that rice farming’s labor and irrigation demands made societies more interdependent, with tighter social norms. Cultural diﬀerences were strongest in the ambiguous, early days of the pandemic, then shrank as masks became nearly universal (94%). Separate survey and internet search data replicated this pattern. Although strong cultural diﬀerences lasted only a few days, research suggests that acting just a few days earlier can reduce deaths substantially.
Hypoxia-inducible factor 1 signaling drives placental aging and can provoke preterm labor

Most cases of preterm labor have unknown cause, and the burden of preterm birth is immense. Placental aging has been proposed to promote labor onset, but specific mechanisms remain elusive. We report findings stemming from unbiased transcriptomic analysis of mouse placenta, which revealed that hypoxia-inducible factor 1 (HIF-1) stabilization is a hallmark of advanced gestational timepoints, accompanied by mitochondrial dysregulation and cellular senescence; we detected similar effects in aging human placenta. In parallel in primary mouse trophoblasts and human choriocarcinoma cells, we modeled HIF-1 induction and demonstrated resultant mitochondrial dysfunction and cellular senescence. Transcriptomic analysis revealed that HIF-1 stabilization recapitulated gene signatures observed in aged placenta. Further, conditioned media from trophoblasts following HIF-1 induction promoted contractility in immortalized uterine myocytes, suggesting a mechanism by which the aging placenta may drive the transition from uterine quiescence to contractility at the onset of labor. Finally, pharmacological induction of HIF-1 via intraperitoneal administration of dimethyloxalyl glycine (DMOG) to pregnant mice caused preterm labor. These results provide clear evidence for placental aging in normal pregnancy, and demonstrate how HIF-1 signaling in late gestation may be a causal determinant of the mitochondrial dysfunction and senescence observed within the trophoblast as well as a trigger for uterine contraction.
Mapping European Research Networks

This paper proposes a framework for measuring the performance and mapping the geography of the European Research Area (ERA) based on the analysis of existing research and knowledge networks. The objective is to provide insights into the spatial structure of the European space from the perspective of the distribution of excellence in research. Starting from the debate on European spatial development, key issues such as polycentricity, the territorial dimension and impact of European policies, the role of research investments as an engine of urban and regional development, the paper explores the potential use of integrating social network analysis and GIS in the evaluation of the spatialrelational structure of the European Research Area. The research uses data on the participation of academic and business research actors into research projects funded by the European Commission under the Sixth Framework Programme.
Uncovering Spatiotemporal Dynamics of the Corticothalamic Network during Seizures

Objective: Although the clinical efficacy of deep brain stimulation targeting the anterior nucleus (AN) and centromedian nucleus (CM) of the thalamus has been actively investigated for the treatment of medication-resistant epilepsy, few studies have investigated dynamic ictal changes in corticothalamic connectivity in human EEG recording. This study aims to establish the complex spatiotemporal dynamics of the ictal corticothalamic network associated with various seizure foci. Methods: We analyzed ten patients (aged 2.7-28.1) with medication-resistant focal epilepsy who underwent stereotactic EEG evaluation with thalamic coverage. We examined both undirected and directed connectivity, incorporating coherence and spectral Granger causality analysis (GCA) between the diverse seizure foci and thalamic nuclei (AN and CM). Results: In our analysis of 36 seizures, coherence between seizure onset and thalamic nuclei increased across all frequencies, especially in slower bands (delta, theta, alpha). GCA showed increased information flow from seizure onset to the thalamus across all frequency bands, but outflows from the thalamus were mainly in slower frequencies, particularly delta. In the subgroup analysis based on various seizure foci, the delta coherence showed a more pronounced increase at CM than at AN during frontal lobe seizures. Conversely, in limbic seizures, the delta coherence increase was greater at AN compared to CM. Interpretation: It appears that the delta frequency plays a pivotal role in modulating the corticothalamic network during seizures. Our results underscore the significance of comprehending the spatiotemporal dynamics of the corticothalamic network during seizures, and this knowledge could guide personalized neuromodulation treatment strategies.
Distributed Containment Maneuvering of Uncertain Multiagent Systems in MIMO Strict-Feedback Form

This paper investigates the distributed containment maneuvering problem for uncertain nonlinear multiagent systems in multiple-input multiple-output (MIMO) strict-feedback form. The follower agents are driven to achieve a collective motion guided by multiple parameterized paths, and a dynamic behavior can be independently prescribed for the group during maneuvering. A containment maneuvering controller is developed by utilizing a modular design method enabling decoupled estimation and control. Specifically, an estimator module is constructed by utilizing an echo state network to identify the unknown nonlinearities. Next, a controller module is constructed by employing a modified dynamic surface control method where a second-order nonlinear tracking differentiator is introduced to extract the derivative information of the virtual control law. Subsequently, a path update law is derived such that the virtual leaders are synchronized, and the desired speed profile for the group can be specified independently. By using a small-gain theorem and cascade stability theory, the entire closed-loop system is proved to be input-to-state stable, and the containment maneuvering errors are uniformly ultimately bounded. An application for the formation control of marine surface vehicles is provided to show the efficacy of the proposed controller for containment maneuvering of uncertain nonlinear MIMO strict-feedback systems.
Bayesian inference in ring attractor networks

Significance Data from human subjects as well as animals show that working memories are associated with a sense of uncertainty. Indeed, a sense of uncertainty is what allows an observer to properly weigh new evidence against their current memory. However, we do not understand how the brain tracks uncertainty. Here, we describe a simple and biologically plausible network model that can track the uncertainty associated with working memory. The representation of uncertainty in this model improves the accuracy of its working memory, as compared to conventional models, because it assigns proper weight to new conflicting evidence. Our model provides an interpretation of observed fluctuations in brain activity, and it makes testable predictions.