Miracle-dz/UniFAR-FTUs huggingface dataset:
Clustering Without an Eigengap

We study graph clustering in the Stochastic Block Model (SBM) in the presence of both large clusters and small, unrecoverable clusters. Previous approaches achieving exact recovery do not allow any small clusters of size $o(\sqrt{n})$, or require a size gap between the smallest recovered cluster and the largest non-recovered cluster. We provide an algorithm based on semidefinite programming (SDP) which removes these requirements and provably recovers large clusters regardless of the remaining cluster sizes. Mid-sized clusters pose unique challenges to the analysis, since their proximity to the recovery threshold makes them highly sensitive to small noise perturbations and precludes a closed-form candidate solution. We develop novel techniques, including a leave-one-out-style argument which controls the correlation between SDP solutions and noise vectors even when the removal of one row of noise can drastically change the SDP solution. We also develop improved eigenvalue perturbation bounds of potential independent interest. Using our gap-free clustering procedure, we obtain efficient algorithms for the problem of clustering with a faulty oracle with superior query complexities, notably achieving $o(n^2)$ sample complexity even in the presence of a large number of small clusters. Our gap-free clustering procedure also leads to improved algorithms for recursive clustering. Our results extend to certain heterogeneous probability settings that are challenging for alternative algorithms.
Discovery of Spherules of Likely Extrasolar Composition in the Pacific Ocean Site of the CNEOS 2014-01-08 (IM1) Bolide

We have conducted an extensive towed-magnetic-sled survey during the period 14-28 June, 2023, over the seafloor centered around the calculated path of the bolide CNEOS 2014-01-08 (IM1) about 85 km north of Manus Island, Papua New Guinea. We found about 700 spherules of diameter 0.05-1.3 millimeters in our samples, of which 57 were analyzed so far. The spherules were significantly concentrated along the expected meteor path. Mass spectrometry of 47 spherules near the high-yield regions along IM1's path reveals a distinct extra-solar abundance pattern for 5 of them, while background spherules have abundances consistent with a solar system origin. The unique spherules show an excess of Be, La and U, by up to three orders of magnitude relative to the solar system standard of CI chondrites. These"BeLaU"-type spherules, never seen before, also have very low refractory siderophile elements such as Re. Volatile elements, such as Mn, Zn, Pb, are depleted as expected from evaporation losses during a meteor's airburst. In addition, the mass-dependent variations in $^{57}$Fe/$^{54}$Fe and $^{56}$Fe/$^{54}$Fe are also consistent with evaporative loss of the light isotopes during the spherules' travel in the atmosphere. The"BeLaU"abundance pattern is not found in control regions outside of IM1's path and does not match commonly manufactured alloys or natural meteorites in the solar system. This evidence points towards an association of"BeLaU"-type spherules with IM1, supporting its interstellar origin independently of the high velocity and unusual material strength implied from the CNEOS data. We suggest that the"BeLaU"abundance pattern could have originated from a highly differentiated magma ocean of a planet with an iron core outside the solar system or from more exotic sources.
Development of a Multilocus Sequence Typing Scheme for Characterization of Clinical Isolates of Acinetobacter baumannii

ABSTRACT In this study a multilocus sequence typing (MLST) scheme for Acinetobacter baumannii was developed and evaluated by using 40 clinical A. baumannii isolates recovered from outbreaks in Spanish and German hospitals during the years 1990 to 2001, as well as isolates from other European hospitals and two DSMZ reference strains of A. baumannii. For comparison, two isolates of Acinetobacter species 13 (sensu Tjernberg and Ursing), two clinical isolates, and three DSMZ strains of A. calcoaceticus (both belonging to the A. calcoaceticus-A. baumannii complex) were also investigated. Primers were designed for conserved regions of housekeeping genes, and 305- to 513-bp internal fragments of seven such genes—gltA, gyrB, gdhB, recA, cpn60, gpi, and rpoD—were sequenced for all strains. The number of alleles at individual loci ranged from 6 to 12, and a total of 20 allelic profiles or sequence types were distinguished among the investigated A. baumannii strains. The MLST data were in high concordance with the epidemiologic typing results generated by pulsed-field gel electrophoresis and amplified fragment length polymorphism fingerprinting. The MLST scheme provides a high level of resolution and an excellent tool for studying the population structure and long-term epidemiology of A. baumannii.
Information Bounds on phase transitions in disordered systems

Information theory, rooted in computer science, and many-body physics, have traditionally been studied as (almost) independent fields. Only recently has this paradigm started to shift, with many-body physics being studied and characterized using tools developed in information theory. In our work, we introduce a new perspective on this connection, and study phase transitions in models with randomness, such as localization in disordered systems, or random quantum circuits with measurements. Utilizing information-based arguments regarding probability distribution differentiation, we bound critical exponents in such phase transitions (specifically, those controlling the correlation or localization lengths). We benchmark our method and rederive the well-known Harris criterion, bounding critical exponents in the Anderson localization transition for noninteracting particles, as well as classical disordered spin systems. We then move on to apply our method to many-body localization. While in real space our critical exponent bound agrees with recent consensus, we find that, somewhat surprisingly, numerical results on Fock-space localization for limited-sized systems do not obey our bounds, indicating that the simulation results might not hold asymptotically (similarly to what is now believed to have occurred in the real-space problem). We also apply our approach to random quantum circuits with random measurements, for which we can derive bounds transcending recent mappings to percolation problems.
Jais and Jais-chat: Arabic-Centric Foundation and Instruction-Tuned Open Generative Large Language Models

We introduce Jais and Jais-chat, new state-of-the-art Arabic-centric foundation and instruction-tuned open generative large language models (LLMs). The models are based on the GPT-3 decoder-only architecture and are pretrained on a mixture of Arabic and English texts, including source code in various programming languages. With 13 billion parameters, they demonstrate better knowledge and reasoning capabilities in Arabic than any existing open Arabic and multilingual models by a sizable margin, based on extensive evaluation. Moreover, the models are competitive in English compared to English-centric open models of similar size, despite being trained on much less English data. We provide a detailed description of the training, the tuning, the safety alignment, and the evaluation of the models. We release two open versions of the model -- the foundation Jais model, and an instruction-tuned Jais-chat variant -- with the aim of promoting research on Arabic LLMs. Available at https://huggingface.co/inception-mbzuai/jais-13b-chat
Hidden-Role Games: Equilibrium Concepts and Computation

In this paper, we study the class of games known as hidden-role games in which players are assigned privately to teams and are faced with the challenge of recognizing and cooperating with teammates. This model includes both popular recreational games such as the Mafia/Werewolf family and The Resistance (Avalon) and many real-world settings, such as distributed systems where nodes need to work together to accomplish a goal in the face of possible corruptions. There has been little to no formal mathematical grounding of such settings in the literature, and it was previously not even clear what the right solution concepts (notions of equilibria) should be. A suitable notion of equilibrium should take into account the communication channels available to the players (e.g., can they communicate? Can they communicate in private? ). Defining such suitable notions turns out to be a nontrivial task with several surprising consequences. In this paper, we provide the first rigorous definition of equilibrium for hidden-role games, which overcomes serious limitations of other solution concepts not designed for hidden-role games. We then show that in certain cases, including the above recreational games, optimal equilibria can be computed efficiently. In most other cases, we show that computing an optimal equilibrium is at least NP-hard or coNP-hard. Lastly, we experimentally validate our approach by computing exact equilibria for complete 5- and 6-player Avalon instances whose size in terms of number of information sets is larger than $10^{56}$.
Carnot: A highly Scalable and Responsive BFT Consensus protocol

We present Carnot, a leader-based Byzantine Fault Tolerant (BFT) consensus protocol that is responsive and operates under the partially synchronous model. Responsive BFT consensus protocols exhibit wire-speed operation and deliver instantaneous finality, thereby addressing a fundamental need in distributed systems. A key challenge in scaling these protocols has been the computational complexity associated with authenticator verification. We demonstrate that Carnot effectively addresses this bottleneck by adeptly streamlining the verification and aggregation of $O(log(N))$ authenticators per node. This notable advancement marks a substantial improvement over the prevailing $O(N)$ state-of-the-art approaches. Leveraging this inherent property, Carnot demonstrates its capacity to seamlessly scale to networks comprising tens to hundreds of thousands of nodes. We envision Carnot as a critical stride towards bridging the gap between classical BFT consensus mechanisms and blockchain technology.
WeatherBench 2: A benchmark for the next generation of data-driven global weather models

WeatherBench 2 is an update to the global, medium-range (1-14 day) weather forecasting benchmark proposed by Rasp et al. (2020), designed with the aim to accelerate progress in data-driven weather modeling. WeatherBench 2 consists of an open-source evaluation framework, publicly available training, ground truth and baseline data as well as a continuously updated website with the latest metrics and state-of-the-art models: https://sites.research. google/weatherbench. This paper describes the design principles of the evaluation framework and presents results for current state-of-the-art physical and data-driven weather models. The metrics are based on established practices for evaluating weather forecasts at leading operational weather centers. We define a set of headline scores to provide an overview of model performance. In addition, we also discuss caveats in the current evaluation setup and challenges for the future of data-driven weather forecasting.
Learning Sequential Information in Task-based fMRI for Synthetic Data Augmentation

Insufficiency of training data is a persistent issue in medical image analysis, especially for task-based functional magnetic resonance images (fMRI) with spatio-temporal imaging data acquired using specific cognitive tasks. In this paper, we propose an approach for generating synthetic fMRI sequences that can then be used to create augmented training datasets in downstream learning tasks. To synthesize high-resolution task-specific fMRI, we adapt the $\alpha$-GAN structure, leveraging advantages of both GAN and variational autoencoder models, and propose different alternatives in aggregating temporal information. The synthetic images are evaluated from multiple perspectives including visualizations and an autism spectrum disorder (ASD) classification task. The results show that the synthetic task-based fMRI can provide effective data augmentation in learning the ASD classification task.
Dark sector and Axion-like particle search at BESIII

Dark matter (DM) refers to a new type of matter that may explain observed rotation curves of galaxies and the composite structure of the Universe. It may couple to the Standard Model particles via portals, which include the possibility of axion-like particle, light Higgs boson, dark photon and spin-1/2 fermions. The axion-like particle and light Higgs boson can be accessible via radiative decays of $J/\psi$ while the dark photon via initial-state radiation process using the data of high-intensity $e^+e^-$ collider experiments, such as the BESIII experiment. DM may be depicted as baryonic matter in an invisible final state. The presence of a massless dark photon, predicted by the spontaneous broken of Abelian group $U(1)_D$, may enhance the branching fractions of rare flavor changing neutral current decay processes. BESIII experiment has recently explored the possibility of these DM scenarios using the data samples collected at several energy points, including $J/\psi$ and $\psi(3686)$ resonances. This report summarizes the recent results of the BESIII experiment related to the dark-sector and Axion-like particles.
Abstract Fractional Cauchy Problem: Existence of Propagators and Inhomogeneous Solution Representation

We consider a Cauchy problem for the inhomogeneous differential equation given in terms of an unbounded linear operator A and the Caputo fractional derivative of order α∈(0,2) in time. The previously known representation of the mild solution to such a problem does not have a conventional variation-of-constants like form, with the propagator derived from the associated homogeneous problem. Instead, it relies on the existence of two propagators with different analytical properties. This fact limits theoretical and especially numerical applicability of the existing solution representation. Here, we propose an alternative representation of the mild solution to the given problem that consolidates the solution formulas for sub-parabolic, parabolic and sub-hyperbolic equations with a positive sectorial operator A and non-zero initial data. The new representation is solely based on the propagator of the homogeneous problem and, therefore, can be considered as a more natural fractional extension of the solution to the classical parabolic Cauchy problem. By exploiting a trade-off between the regularity assumptions on the initial data in terms of the fractional powers of A and the regularity assumptions on the right-hand side in time, we show that the proposed solution formula is strongly convergent for t≥0 under considerably weaker assumptions compared to the standard results from the literature. Crucially, the achieved relaxation of space regularity assumptions ensures that the new solution representation is practically feasible for any α∈(0,2) and is amenable to the numerical evaluation using uniformly accurate quadrature-based algorithms.
Late time modification of structure growth and the 
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 tension

The $S_8$ tension between low-redshift galaxy surveys and the primary CMB signals a possible breakdown of the $\Lambda$CDM model. Recently differing results have been obtained using low-redshift galaxy surveys and the higher redshifts probed by CMB lensing, motivating a possible time-dependent modification to the growth of structure. We investigate a simple phenomenological model in which the growth of structure deviates from the $\Lambda$CDM prediction at late times, in particular as a simple function of the dark energy density. Fitting to galaxy lensing, CMB lensing, BAO, and Supernovae datasets, we find significant evidence - 2.5 - 3$\sigma$, depending on analysis choices - for a non-zero value of the parameter quantifying a deviation from $\Lambda$CDM. The preferred model, which has a slower growth of structure below $z\sim 1$, improves the joint fit to the data over $\Lambda$CDM. While the overall fit is improved, there is weak evidence for galaxy and CMB lensing favoring different changes in the growth of structure.
Intranasal neuropeptide Y1 receptor antagonism improves motor deficits in symptomatic SOD1 ALS mice

Neuropeptide Y (NPY) is a 36 amino acid peptide widely considered to provide neuroprotection in a range of neurodegenerative diseases. In the fatal motor neuron disease amyotrophic lateral sclerosis (ALS), recent evidence supports a link between NPY and ALS disease processes. The goal of this study was to determine the therapeutic potential and role of NPY in ALS, harnessing the brain‐targeted intranasal delivery of the peptide, previously utilised to correct motor and cognitive phenotypes in other neurological conditions.
hyperhomocysteinemia is an independent predictor of long-term clinical outcomes in Chinese octogenarians with acute coronary syndrome

Objective: To evaluate the prognostic value of homocysteine (Hcy) in Chinese acute coronary syndrome (ACS) octogenarians. Methods: The study cohort comprised 660 consecutive ACS octogenarians who underwent coronary angiography. We classified the patients into three groups according to Hcy tertiles. Kaplan–Meier method was performed for survival and major adverse cardiac events (MACE) rates. Multivariate Cox regression was performed to identify mortality predictors. Receiver operating characteristic curve analysis was performed to predict the cutoff value of Hcy for all-cause mortality. Results: The follow-up period was 28 (inter-quartile range: 16–38) months. Diastolic blood pressure, ratios of male, renal failure and old myocardial infarction in high plasma level Hcy (H-Hcy) group were higher than those in low (L-Hcy) and middle (M-Hcy) plasma level of Hcy groups ( P , 0.05). The Hcy level was positively correlated with uric acid level ( r = 0.211, P = 0.001) and Cystatin C (Cys C) level ( r = 0.212, P = 0.001) and negatively correlated with estimated glomerular filtration rate ( r =- 0.148, P = 0.018). For the long-term outcomes, the cumulative survival rate of H-Hcy group was significantly lower than that of L-Hcy and M-Hcy groups ( P = 0.006). All-cause mortality and MACE of H-Hcy group were higher than those of L-Hcy and M-Hcy group ( P = 0.0001, P = 0.0008). Hcy is an independent predictor for long-term all-cause mortality (odds ratio = 2.26, 95% CI = 1.23–4.16, P = 0.023) and MACE (odds ratio = 1.91, 95% CI = 1.03–3.51, P = 0.039). Receiver operating characteristic curve analysis indicated the predictive cutoff value of Hcy for all-cause mortality was 17.67 µ mol/L (0.667, 0.681). Conclusion: In ACS octogenarians, hyperhomocysteinemia is an important predictor for long-term all-cause mortality and MACE.
Wind Energy Comes of Age

WHERE THE TECHNOLOGY STANDS TODAY. Overview. The Vikings Are Coming. The Research and Development Dilemma. Death Knell for the Giants. Historical Background. The Giant Killers. Wind Energy's Declining Costs. ENVIRONMENTAL COSTS AND BENEFITS: THERE'S NO FREE LUNCH. Machines in the Garden: Aesthetics, Opinion, Design, and Acceptance. Impact on Flora and Fauna. Impacts on People. Impact on Land. Benefits. The Emerald City. WHERE WIND ENERGY IS HEADED. Wind's Future. Appendices. Index.
Use patterns of over-the-counter (OTC) medications and perspectives on OTC medications among Korean adult patients with chronic diseases: gender and age differences

Background A number of symptomatic patients tend to use over-the-counter (OTC) medications and prescription medications. OTC medications can be easily obtained in pharmacies for self-treatment, but using OTC medications is not always safe and beneficial for patients. The aims of this study were to examine the use patterns of OTC medications and assess patients’ perspectives regarding the use of OTC medications in Korean patients with chronic diseases. Patients and methods A descriptive, cross-sectional survey was carried out with Korean patients who visited the community pharmacy, located at the southern region of South Korea, during September 2015. Results A total of 345 patients participated in this survey. Approximately 64% of Korean survey respondents reported that they had used OTC drugs. The most commonly used OTC medications were antipyretics, analgesics and anti-inflammatory drugs. The perception level of Korean consumers on adverse drug reactions and drug–drug interactions from OTC medications was relatively low. Although OTC package leaflets are a main source of information about OTC medications, Korean consumers’ level of reading OTC package leaflets was relatively low. Conclusion Based on these results, this study can serve as a meaningful starting point for interventions of health care professionals regarding OTC medications in South Korea. In particular, pharmacists should inform their consumers of drug-related problems from OTC drugs during consultation with the consumers; however, information about OTC drugs should be tailored to consumer information needs with the consideration of his or her circumstance. It is somewhat difficult to generalize the results from this study to other regions of South Korea since most of the respondents were probably residents of a small rural city located in the southern region of South Korea.
Establishment and validation of an AJCC stage-and histologic grade-based nomogram for pancreatic neuroendocrine tumors after surgical resection

Background: Development of an accurate model to predict prognosis for patients with pancreatic neuroendocrine tumors (P-NETs) after surgical resection is urgently needed. Methods: In the present study, we conducted Cox proportional hazards regression to identify critical prognostic factors for P-NETs by analyzing data from 2174 patients in the Surveillance, Epidemiology, and End Results (SEER) database. Based on the results of multivariate analysis, a novel nomogram was established. Finally, the novel nomogram for P-NETs was validated in a cohort of 81 patients from a Chinese institute. Results: In the multivariate analysis, age, tumor location, American Joint Committee on Cancer (AJCC) stage, histologic grade, lymph node ratio (LNR) and tumor size were independent risk factors for overall survival (OS) in P-NET patients who underwent radical resection. A nomogram consisting of age, sex, AJCC stage and histologic grade was found to have a concordance index (C-index) of 0.79 for OS in the SEER database, which was signi ﬁ cantly higher than the C-index based on the AJCC stage, European Neuroendocrine Tumor Society (ENETS) stage or histologic grade alone. In the validation cohort, the C-index based on the nomogram reached 0.78 for OS. We also de ﬁ ned high-risk (total points >13.5 based on the nomogram) and low-risk populations (total points <13.5 based on the nomogram) in the validation cohort. We found that the actual 5-year recurrence rate in the high-risk group was signi ﬁ cantly higher than that in the low-risk group (80.8% vs 23.4%, P <0.001). Kaplan-Meier analysis showed that the 5-year recurrence-free survival (RFS) in the low-risk group was signi ﬁ cantly higher than that in the high-risk group ( P <0.001). Conclusion: An AJCC stage- and histologic grade-based model was found to be extremely ef ﬁ cient in predicting survival for patients with P-NETs after surgical resection and deserves further evaluation for future clinical applications.