Miracle-dz/UniFAR-FTUs huggingface dataset:
(Ir)rationality and Cognitive Biases in Large Language Models

Do large language models (LLMs) display rational reasoning? LLMs have been shown to contain human biases due to the data they have been trained on; whether this is reflected in rational reasoning remains less clear. In this paper, we answer this question by evaluating seven language models using tasks from the cognitive psychology literature. We find that, like humans, LLMs display irrationality in these tasks. However, the way this irrationality is displayed does not reflect that shown by humans. When incorrect answers are given by LLMs to these tasks, they are often incorrect in ways that differ from human-like biases. On top of this, the LLMs reveal an additional layer of irrationality in the significant inconsistency of the responses. Aside from the experimental results, this paper seeks to make a methodological contribution by showing how we can assess and compare different capabilities of these types of models, in this case with respect to rational reasoning.
Developing a Framework for Auditing Large Language Models Using Human-in-the-Loop

As LLMs become more pervasive across various users and scenarios, identifying potential issues when using these models becomes essential. Examples include bias, inconsistencies, and hallucination. Although auditing the LLM for these problems is desirable, it is far from being easy or solved. An effective method is to probe the LLM using different versions of the same question. This could expose inconsistencies in its knowledge or operation, indicating potential for bias or hallucination. However, to operationalize this auditing method at scale, we need an approach to create those probes reliably and automatically. In this paper we propose an automatic and scalable solution, where one uses a different LLM along with human-in-the-loop. This approach offers verifiability and transparency, while avoiding circular reliance on the same LLMs, and increasing scientific rigor and generalizability. Specifically, we present a novel methodology with two phases of verification using humans: standardized evaluation criteria to verify responses, and a structured prompt template to generate desired probes. Experiments on a set of questions from TruthfulQA dataset show that we can generate a reliable set of probes from one LLM that can be used to audit inconsistencies in a different LLM. The criteria for generating and applying auditing probes is generalizable to various LLMs regardless of the underlying structure or training mechanism.
Report of the Working Group on Interactions between Humans and Tursiops truncatus in the Southwest Atlantic Ocean

In this work we compiled the available information about humans and bottlenose dolphin interactions in the Southwest Atlantic Ocean (SWAO), including issues as historical direct takes, incidental captures in fisheries, positive interactions with fisheries, interactions of dolphins with tourism and boat traffic, habitat modification or degradation, and environmental pollution. The data compiled in this review demonstrated that coastal bottlenose dolphins are under anthropogenic pressure in the SWAO. Direct take of bottlenose dolphins in the wild does not appear to be an issue of conservation concern in the SWAO. Although the species is exposed to bioaccumulation of micropollutants, it is suggested that contamination level is lower when compared to bottlenose dolphins from other continents. Coastal works can impact bottlenose dolphin behavior and habitat use in a short-term, but those seem to be reversible when works stop. Bycatch occurs throughout the species distribution and seems to be occasional in Uruguayan and Argentinean waters, where there is evidence of a historic decline in dolphin sightings. In Brazil, bycatch is apparently low in the northeast and southeast coasts, but is frequent in certain areas of southern Brazil. Studies on the subject are scarce or preliminary and a great effort is still required to understand the real impact of human activities on bottlenose dolphins in the SWAO.
Transformers Can Achieve Length Generalization But Not Robustly

Length generalization, defined as the ability to extrapolate from shorter training sequences to longer test ones, is a significant challenge for language models. This issue persists even with large-scale Transformers handling relatively straightforward tasks. In this paper, we test the Transformer's ability of length generalization using the task of addition of two integers. We show that the success of length generalization is intricately linked to the data format and the type of position encoding. Using the right combination of data format and position encodings, we show for the first time that standard Transformers can extrapolate to a sequence length that is 2.5x the input length. Nevertheless, unlike in-distribution generalization, length generalization remains fragile, significantly influenced by factors like random weight initialization and training data order, leading to large variances across different random seeds.
Nearly Optimal Regret for Decentralized Online Convex Optimization

We investigate decentralized online convex optimization (D-OCO), in which a set of local learners are required to minimize a sequence of global loss functions using only local computations and communications. Previous studies have established $O(n^{5/4}\rho^{-1/2}\sqrt{T})$ and ${O}(n^{3/2}\rho^{-1}\log T)$ regret bounds for convex and strongly convex functions respectively, where $n$ is the number of local learners, $\rho<1$ is the spectral gap of the communication matrix, and $T$ is the time horizon. However, there exist large gaps from the existing lower bounds, i.e., $\Omega(n\sqrt{T})$ for convex functions and $\Omega(n)$ for strongly convex functions. To fill these gaps, in this paper, we first develop novel D-OCO algorithms that can respectively reduce the regret bounds for convex and strongly convex functions to $\tilde{O}(n\rho^{-1/4}\sqrt{T})$ and $\tilde{O}(n\rho^{-1/2}\log T)$. The primary technique is to design an online accelerated gossip strategy that enjoys a faster average consensus among local learners. Furthermore, by carefully exploiting the spectral properties of a specific network topology, we enhance the lower bounds for convex and strongly convex functions to $\Omega(n\rho^{-1/4}\sqrt{T})$ and $\Omega(n\rho^{-1/2})$, respectively. These lower bounds suggest that our algorithms are nearly optimal in terms of $T$, $n$, and $\rho$.
Max-Min Fair Energy-Efficient Beam Design for Quantized ISAC LEO Satellite Systems: A Rate-Splitting Approach

Low earth orbit (LEO) satellite systems with sensing functionality is envisioned to facilitate global-coverage service and emerging applications in 6G. Currently, two fundamental challenges, namely, inter-beam interference among users and power limitation at the LEO satellites, limit the full potential of the joint design of sensing and communication. To effectively control the interference, rate-splitting multiple access (RSMA) scheme is employed as the interference management strategy in the system design. On the other hand, to address the limited power supply at the LEO satellites, we consider low-resolution quantization digital-to-analog converters (DACs) at the transmitter to reduce power consumption, which grows exponentially with the number of quantization bits. Additionally, optimizing the total energy efficiency (EE) of the system is a common practice to save the power. However, this metric lacks fairness among users. To ensure this fairness and further enhance EE, we investigate the max-min fairness EE of the RSMA-assisted integrated sensing and communications (ISAC)-LEO satellite system. In this system, the satellite transmits a quantized dual-functional signal serving downlink users while detecting a target. Specifically, we optimize the precoders for maximizing the minimal EE among all users, considering the power consumption of each radio frequency (RF) chain under communication and sensing constraints. To tackle this optimization problem, we proposed an iterative algorithm based on successive convex approximation (SCA) and Dinkelbach's method. Numerical results illustrate that the proposed design outperforms the strategies that aim to maximize the total EE of the system and conventional space-division multiple access (SDMA) in terms of max-min fairness EE and the communication-sensing trade-off.
Improving image quality of sparse-view lung tumor CT images with U-Net

Background: We aimed at improving image quality (IQ) of sparse-view computed tomography (CT) images using a U-Net for lung metastasis detection and determining the best tradeoff between number of views, IQ, and diagnostic confidence. Methods: CT images from 41 subjects aged 62.8 $\pm$ 10.6 years (mean $\pm$ standard deviation), 23 men, 34 with lung metastasis, 7 healthy, were retrospectively selected (2016-2018) and forward projected onto 2,048-view sinograms. Six corresponding sparse-view CT data subsets at varying levels of undersampling were reconstructed from sinograms using filtered backprojection with 16, 32, 64, 128, 256, and 512 views. A dual-frame U-Net was trained and evaluated for each subsampling level on 8,658 images from 22 diseased subjects. A representative image per scan was selected from 19 subjects (12 diseased, 7 healthy) for a single-blinded multireader study. These slices, for all levels of subsampling, with and without U-Net postprocessing, were presented to three readers. IQ and diagnostic confidence were ranked using predefined scales. Subjective nodule segmentation was evaluated using sensitivity and Dice similarity coefficient (DSC); clustered Wilcoxon signed-rank test was used. Results: The 64-projection sparse-view images resulted in 0.89 sensitivity and 0.81 DSC, while their counterparts, postprocessed with the U-Net, had improved metrics (0.94 sensitivity and 0.85 DSC) (p = 0.400). Fewer views led to insufficient IQ for diagnosis. For increased views, no substantial discrepancies were noted between sparse-view and postprocessed images. Conclusions: Projection views can be reduced from 2,048 to 64 while maintaining IQ and the confidence of the radiologists on a satisfactory level.
Engineered T cells secreting anti-BCMA T cell engagers control multiple myeloma and promote immune memory in vivo

Multiple myeloma is the second most common hematological malignancy in adults and remains an incurable disease. B cell maturation antigen (BCMA)–directed immunotherapy, including T cells bearing chimeric antigen receptors (CARs) and systemically injected bispecific T cell engagers (TCEs), has shown remarkable clinical activity, and several products have received market approval. However, despite promising results, most patients eventually become refractory and relapse, highlighting the need for alternative strategies. Engineered T cells secreting TCE antibodies (STAb) represent a promising strategy that combines the advantages of adoptive cell therapies and bispecific antibodies. Here, we undertook a comprehensive preclinical study comparing the therapeutic potential of T cells either expressing second-generation anti-BCMA CARs (CAR-T) or secreting BCMAxCD3 TCEs (STAb-T) in a T cell–limiting experimental setting mimicking the conditions found in patients with relapsed/refractory multiple myeloma. STAb-T cells recruited T cell activity at extremely low effector-to-target ratios and were resistant to inhibition mediated by soluble BCMA released from the cell surface, resulting in enhanced cytotoxic responses and prevention of immune escape of multiple myeloma cells in vitro. These advantages led to robust expansion and persistence of STAb-T cells in vivo, generating long-lived memory BCMA-specific responses that could control multiple myeloma progression in xenograft models, outperforming traditional CAR-T cells. These promising preclinical results encourage clinical testing of the BCMA-STAb-T cell approach in relapsed/refractory multiple myeloma. Anti-BCMA STAb-T cells prevent myeloma relapse and exhibit superiority compared with CAR-T cells. Editor’s summary Taking a STAb at cellular therapy. Multiple myeloma is a hematological cancer with limited treatment options, particularly after relapse. Chimeric antigen receptor (CAR) T cells are being explored for multiple myeloma, much like for other hematological malignancies, but patients still relapse. Here, Díez-Alonso et al. developed STAb-T cells, which, rather than express a CAR, secrete T cell–engaging antibodies targeting B cell maturation antigen (BCMA) and CD3. The authors compared STAb-T cells with traditional CAR-T cells in vitro and in vivo, showing that the STAb-T cells more effectively killed target cells at low frequencies and were resistant to inhibition mediated by soluble BCMA released from myeloma cells, preventing immune escape. This translated to improved in vivo efficacy in a murine multiple myeloma model, supporting further development of BCMA-specific STAb-T cells as a therapeutic for this and other hematological malignancies. —Courtney Malo
The genome of Pasteuria ramosa reveals a high turnover rate of collagen-like genes

Collagen-like proteins (CLP) are commonly found in many pathogenic bacteria where they serve as adhesins to attach to host tissue. The repetition of the amino-acid pattern (Gly-Xaa-Yaa)n is the major feature of collagen and is essential to the formation of its stable triple helical structure. In the Daphnia magna–Pasteuria ramosa system, a model system for studying antagonistic coevolution, a specific CLP in the virulent parasite P. ramosa plays a pivotal role in host attachment, regulated by matching allele model. Recognizing the crucial role of CLPs in the infection process, we aimed to enhance our understanding of P. ramosa-CLPs by sequencing high-quality genomes of two isolates, using long-read technology. An analysis of a CLP gene tree of representative Bacillota species revealed a clear radiation of these genes in P. ramosa, which was not found in the closely related Pasteuria penetrans. A comparison of the isolates reveals a high synteny, with the exception of a few duplications and inversions, mainly involving CLPs or transposases. Across isolates, we observed a recent burst of transposases as well as duplications of CLP genes. On average, CLP genes are well conserved between isolates, but the presence/absence of individual CLP genes is not fully shared, with 39 and 43 genes in the two isolates. Our findings suggest a rapid radiation of CLP genes combined with a birth and death process of the large P. ramosa-CLP gene family, possibly driven by transposition and coevolution. Importance Although the host–pathogen Daphnia magna–Pasteuria ramosa system has served as a model for coevolution, we have, to date, lacked high-quality genomic resources for the parasite, as is the case for many such systems. By presenting a complete assembly of two distinct P. ramosa isolates, our study addresses this lack and provides deeper insights into the P. ramosa Collagen Like Protein (CLP) family, essential proteins involved in attachment to the host. We discover that the rapid radiation of CLP genes in P. ramosa appears to be driven by transposition and coevolution, enabling the parasite to adapt to host resistance mechanisms. These insights improve our understanding of host–parasite interactions and pave the way for comparative genomic analyses to better understand the evolution of these genes. They also have broader implications for disease control and therapeutic development targeting pathogenic bacteria adhesion mechanisms.
Supramodal neural information supports stimulus-driven attention across cortical levels

Sensory systems utilise stimulus-driven attention to survey the environment for significant features. The question arises: are the cortical networks that influence stimulus-driven attention supramodal or specific to each sensory modality? Here we employed a hierarchical target detection task (n=30), examining cortical responses linked to the detection of salient targets in the somatosensory and auditory modality. In a temporal decoding analysis, we reveal a transient early supramodal process activated by target detection. We also demonstrate that both common and unique modulations of salience-related cortical responses to somatosensory and auditory targets involve modality-specific and frontal regions using Parametric Empirical Bayes. Specifically, we found that the inferior frontal gyri share information across both sensory modalities, while recurrent information transfer between ipsilateral inferior frontal gyri and associative regions was modality-specific. Finally, we showed both supramodal and modality-specific attentional modulations of effective connectivity linking regions across hierarchical levels in the cortex. Our results provide evidence for an attention network which integrates information across inferior frontal cortices to detect salient targets irrespective of their specific sensory modality. Beyond the notion of a supramodal attention system, our findings support the role of modality-specific cortices in processing inputs from other sensory modalities, highlighting that attention can bias these processes at multiple stages of the cortical hierarchy. Author summary A key task of the brain is to deploy attention to detect important sensory events in its environment. How does the brain coordinate information from different senses when a sensory event pops out from the environment? Here we designed a nested oddball paradigm in which expectations about somatosensory and auditory stimuli are violated while high-density EEG is recorded. We also varied the extent to which the odd stimulus pops out from its sensory environment. Using temporal decoding, we reveal a supramodal short-lived cortical process when salient targets are detected. In an effective connectivity analysis, we also show that the detection of salient targets relies on a common interhemispheric inhibition between inferior frontal gyri. Beyond that, there are supramodal and modality-specific changes in effective connectivity linking associative and modality-specific regions in the cortex. Our results support a rapid and short-lived supramodal process in a distributed saliency detection system extending across the cortical hierarchy.
Developmental pathways underlying sexual differentiation in a U/V sex chromosome system

In many multicellular organisms, male and female developmental fates are not determined by the classic XX/XY or ZW/ZZ systems but rather by a third type of sex chromosomes, the U/V sex chromosomes. In U/V systems, sex is expressed in the haploid phase, with U chromosomes confined to females and V chromosomes to males. Here, we explore several male, female and partially sex- reversed male lines of a giant kelp with a U/V system, to decipher the role of U/V sex chromosomes and autosomes in the initiation of male versus female developmental programs. Using comparative transcriptomics and experimental approaches, we identify a small set of genes located on the V- and U sex chromosomes that play a role in triggering the male versus female developmental programs, and we uncover a subset of autosomal effector genes. We describe the transcriptomic pathways underlying sexual differentiation and show that male, but not female, developmental fate involves large-scale transcriptome reorganization with pervasive enrichment in regulatory genes affecting the expression of more than half of the giant kelp genome. Furthermore, male-biased genes are more species-specific and exhibit faster evolutionary rates than unbiased genes, whereas genes underlying female developmental fate are more evolutionary conserved. Our observations imply that a female- like phenotype is the “ground state” of the giant kelp morphology, which is complemented by the presence of a U-chromosome, but overridden by a dominant male developmental program in the presence of a V-chromosome.
The contribution of movement to social network structure and spreading dynamics under simple and complex transmission

The structure of social networks fundamentally influences spreading dynamics. In general, the more contact between individuals, the more opportunity there is for the transmission of information or disease to take place. Yet, contact between individuals, and any resulting transmission events, are determined by a combination of spatial (where individuals choose to move) and social rules (who they choose to interact with or learn from). Here we examine the effect of the social-spatial interface on spreading dynamics using a simulation model. We quantify the relative effects of different movement rules (localized, semi-localized, nomadic, and resource-based movement) and social transmission rules (simple transmission, anti-conformity, proportional, conformity, and threshold rules) to both the structure of social networks and spread of a novel behaviour. Localized movement created weakly connected sparse networks, nomadic movement created weakly connected dense networks, and resource-based movement generated strongly connected modular networks. The resulting rate of spreading varied with different combinations of movement and transmission rules, but— importantly—the relative rankings of transmission rules changed when running simulations on static versus dynamic representations of networks. Our results emphasize that individual-level social and spatial behaviours influence emergent network structure, and are of particular consequence for the spread of information under complex transmission rules.
Identification and distribution of two Mastomys spp. in Lesotho and part of South Africa : discussion

Mastomys specimens from the National Museum, Bloemfontein (n = 596), and the McGregor Museum, Kimberley (n = 194), have been re-identified according to skull characters as either Mastomys coucha or M. natalensis, using the method of Dippenaar, Swanepoel & Gordon (1993). Distribution was recorded and various data collected from specimen labels. This study documents a wider distribution of M. coucha than was previously recorded and renders it unlikely that M. natalensis occurs in large parts of Lesotho and the Northern Cape, North-West, Free State, and north-eastern parts of the Eastern Cape provinces.
Pushing the limits: expanding the temperature tolerance of a coral photosymbiont through differing selection regimes

Coral thermal bleaching resilience can be improved by enhancing photosymbiont thermal tolerance via experimental evolution. While successful for some strains, selection under stable temperatures was ineffective at increasing the thermal threshold of an already thermo-tolerant photosymbiont (Durusdinium trenchii). Corals from environments with fluctuating temperatures tend to have comparatively high heat tolerance. Therefore, we investigated whether exposure to temperature oscillations can raise the upper thermal limit of D. trenchii. We exposed a D. trenchii strain to stable and fluctuating temperatures profiles, which varied in oscillation frequency. After 2.1 years (54-73 generations), we characterised the adaptive responses under the various experimental evolution treatments by constructing thermal performance curves of growth from 21 to 31°C for the heat-evolved and wild-types lineages. Additionally, oxidative stress, photophysiology, photosynthesis and respiration rates were assessed under increasing temperatures. Of the fluctuating temperature profiles investigated, selection under the most frequent oscillations (diurnal) induced the greatest widening of D. trenchii’s thermal niche. Continuous selection under elevated temperatures induced the only increase in thermal optimum and a degree of generalism. Our findings demonstrate how differing levels of thermal homogeneity during selection drive unique adaptative responses to heat in a coral photosymbiont.