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We establish several results on the word problem for just infinite groups. First, for finitely generated just infinite groups we show that the word problem is uniformly decidable for presentations with recursively enumerable sets of relations. Our proof does not use the Wilson--Grigorchuk theorem on the classification of just infinite groups and proceeds directly from the definition, using ideas from classical results on decidability of the word problem: Kuznetsov's theorem and McKinsey--Maltsev theorem. For countably generated presentations of just infinite groups with a recursively enumerable set of relations we show that the word problem is decidable in all cases except locally finite groups without a computable lower bound on subgroup sizes. Finally, we construct presentations of countably generated locally finite groups with recursively enumerable set of relations, for which the word problem is undecidable. Yet, there exist other presentations of these groups, for which the word problem is decidable.
A profinite group G is just infinite if every non-trivial closed normal subgroup of G is of finite index, and hereditarily just infinite if every open subgroup is just infinite. Hereditarily just infinite profinite groups need not be virtually pro-p, as shown in a recent paper of Wilson. The same paper gives a criterion on an inverse system of finite groups that is sufficient to ensure the limit is either virtually abelian or hereditarily just infinite. We give criteria of a similar nature that characterise the just infinite and hereditarily just infinite properties under the assumption that G is not virtually pro-p.
We study just infinite algebras which remain so upon extension of scalars by arbitrary field extensions. Such rings are called stably just infinite. We show that just infinite rings over algebraically closed fields are stably just infinite provided that the ring is either right noetherian or countably generated over a large field. We give examples to show that, over countable fields, a just infinite algebra which is either affine or non-noetherian need not remain just infinite under extension of scalars. We also give a concrete classification of PI stably just infinite rings and give two characterizations of non-PI stably just infinite rings in terms of Martindale's extended center.
A residually finite (profinite) group $G$ is just infinite if every non-trivial (closed) normal subgroup of $G$ is of finite index. This paper considers the problem of determining whether a (closed) subgroup $H$ of a just infinite group is itself just infinite. If $G$ is not virtually abelian, we give a description of the just infinite property for normal subgroups in terms of maximal subgroups. In particular, we show that such a group $G$ is hereditarily just infinite if and only if all maximal subgroups of finite index are just infinite. We also obtain results for certain families of virtually abelian groups, including all virtually abelian pro-$p$ groups and their discrete analogues.
By seamlessly integrating everyday objects and by changing the way we interact with our surroundings, Internet of Things (IoT) is drastically improving the life quality of households and enhancing the productivity of businesses. Given the unique IoT characteristics, IoT applications have emerged distinctively from the mainstream application types. Inspired by the outlook of a programmable world, we further foresee an IoT-native trend in designing, developing, deploying, and maintaining software systems. However, although the challenges of IoT software projects are frequently discussed, addressing those challenges are still in the "crossing the chasm" period. By participating in a few various IoT projects, we gradually distilled three fundamental principles for engineering IoT-native software systems, such as just enough, just in time, and just for "me". These principles target the challenges that are associated with the most typical features of IoT environments, ranging from resource limits to technology heterogeneity of IoT devices. We expect this research to trigger dedicated efforts, techniques and theories for the topic IoT-native software engineering.
This paper puts forth a networking paradigm, referred to as just-in-time (JIT) communication, to support client-server applications with stringent request-response latency requirement. Of interest is not just the round-trip delay of the network, but the actual request-response latency experienced by the application. The JIT framework contains two salient features. At the client side, the communication layer will 'pull' a request from the client just when there is an upcoming transmission opportunity from the network. This ensures that the request contains information that is as fresh as possible (e.g., a sensor reading obtained just before the transmission opportunity). At the server side, the network ascertains that the server, after receiving and processing the request to generate a response (e.g., a control command to be sent to the client), will have a transmission opportunity at just this time. We realize the JIT system, including the protocol stack, over a Time-Division-Multiple-Access (TDMA) network implemented on a System-on-Chip (SoC) platform. We prove that a TDMA network with a power-of-2 time slots per superframe is optimal for realizing the server-side JIT function. Ou
A profinite group $G$ is just infinite if every closed normal subgroup of $G$ is of finite index. We prove that an infinite profinite group is just infinite if and only if, for every open subgroup $H$ of $G$, there are only finitely many open normal subgroups of $G$ not contained in $H$. This extends a result recently established by Barnea, Gavioli, Jaikin-Zapirain, Monti and Scoppola, who proved the same characterisation in the case of pro-$p$ groups. We also use this result to establish a number of features of the general structure of profinite groups with regard to the just infinite property.
We present a fully automated learning-based approach for segmenting knee cartilage in the presence of osteoarthritis (OA). The algorithm employs a hierarchical set of two random forest classifiers. The first is a neighborhood approximation forest, the output probability map of which is utilized as a feature set for the second random forest (RF) classifier. The output probabilities of the hierarchical approach are used as cost functions in a Layered Optimal Graph Segmentation of Multiple Objects and Surfaces (LOGISMOS). In this work, we highlight a novel post-processing interaction called just-enough interaction (JEI) which enables quick and accurate generation of a large set of training examples. Disjoint sets of 15 and 13 subjects were used for training and tested on another disjoint set of 53 knee datasets. All images were acquired using a double echo steady state (DESS) MRI sequence and are from the osteoarthritis initiative (OAI) database. Segmentation performance using the learning-based cost function showed significant reduction in segmentation errors ($p< 0.05$) in comparison with conventional gradient-based cost functions.
The neutrino long wavelength (just-so) oscillation is reconsidered as a solution to the solar neutrino problem. In the light of the presently updated results of the four solar neutrino experiments, the data fit in the just-so scenario substantially improves and becomes almost as good as in the MSW scenario. Surprising result of our analysis is that best fit is achieved when the oscillation occurs only between two neutrino states: switching on the oscillation into third neutrino increases the $χ^2$ value. Namely, we consider the vacuum oscillation scenario in the three-neutrino system (4 parameters) and find out that the $χ^2$ minimum is always achieved in the {\it two} parameter subspace in which actually only {\it two} neutrino states oscillate. This holds in the framework of any solar model with relaxed prediction of the various neutrino fluxes. The possible theoretical implications of this observation are also discussed.
Physicists have taken a major step toward using AI not just to analyze data, but to uncover entirely new laws of nature。 By combining a specially designed neural network with precise 3D tracking of particles in a dusty plasma—a strange “fourth state of matter” found from space to wildfires—the team revealed hidden patterns in how particles interact
At WIRED Health, pioneering Alzheimer's researcher John Hardy outlined the stakes—and next steps—of where treatment is headed next
A 150-year-old rule in geometry has been proven wrong。 Mathematicians found two different doughnut-shaped surfaces that look identical when measured locally but are actually different overall。 For decades, researchers suspected this might be possible but couldn’t prove it—until now
Scientists have uncovered the true boundary of the Milky Way’s star-forming region using stellar “age mapping。” They found a telltale U-shaped pattern showing that star formation drops sharply around 35,000–40,000 light-years from the center。 Beyond that, stars are mostly migrants, slowly drifting outward rather than forming in place
New experiments suggest that freezing and thawing on early Earth may have helped primitive cell-like structures grow and evolve。 Tiny lipid bubbles behaved very differently depending on their membrane makeup—some fused into larger compartments and captured DNA more efficiently。 These fusion events could have mixed key molecules, setting the stage f
In a breakthrough experiment, scientists directly imaged how particles pair up in a system that mimics superconductors。 Instead of behaving independently, the pairs moved in a synchronized, dance-like pattern—something never predicted before。 This suggests a major gap in the classic theory of superconductivity
Access Now, the group that organizes RightsCon, says Zambian officials asked it to exclude Taiwanese participants if it wanted the event to proceed as planned
The Jiao Tong University Spectroscopic Telescope (JUST) is a 4.4-meter f/6.0 segmentedmirror telescope dedicated to spectroscopic observations. The JUST primary mirror is composed of 18 hexagonal segments, each with a diameter of 1.1 m. JUST provides two Nasmyth platforms for placing science instruments. One Nasmyth focus fits a field of view of 10 arcmin and the other has an extended field of view of 1.2 deg with correction optics. A tertiary mirror is used to switch between the two Nasmyth foci. JUST will be installed at a site at Lenghu in Qinghai Province, China, and will conduct spectroscopic observations with three types of instruments to explore the dark universe, trace the dynamic universe, and search for exoplanets: (1) a multi-fiber (2000 fibers) medium-resolution spectrometer (R=4000-5000) to spectroscopically map galaxies and large-scale structure; (2) an integral field unit (IFU) array of 500 optical fibers and/or a long-slit spectrograph dedicated to fast follow-ups of transient sources for multimessenger astronomy; (3) a high-resolution spectrometer (R~100000) designed to identify Jupiter analogs and Earth-like planets, with the capability to characterize the atmosph
Background: Programming is a fundamental skill in computer science and software engineering specifically. Mastering it is a challenge for novices, which is evidenced by numerous errors that students make during programming assignments. Objective: In our study, we want to identify common programming errors in CS2 courses and understand how students evolve over time. Method: To this end, we conducted a longitudinal study of errors that students of a CS2 course made in subsequent programming assignments. Specifically, we manually categorized 710 errors based on a modified version of an established error framework. Result: We could observe a learning curve of students, such that they start out with only few syntactical errors, but with a high number of semantic errors. During the course, the syntax and semantic errors almost completely vanish, but logical errors remain consistently present. Conclusion: Thus, students have only little trouble with learning the programming language, but need more time to understand and express concepts in a programming language.
Neutron-rich outflows in neutron-star mergers (NSMs) or other explosive events can be subject to substantial heating through the release of rest-mass energy in the course of the rapid neutron-capture (r-) process. This r-process heating can potentially have a significant impact on the dynamics determining the velocity distribution of the ejecta, but due to the complexity of detailed nuclear networks required to describe the r-process self-consistently, hydrodynamic models of NSMs often neglect r-process heating or include it using crude parametrizations. In this work, we present a conceptually new method, RHINE, for emulating the r-process and concomitant energy release in hydrodynamic simulations via machine-learning algorithms. The method requires the evolution of only a few additional quantities characterizing the composition, of which the nuclear rates of change are obtained at each location and time step from neural networks trained by a large set of trajectories from full nuclear-network calculations. The scheme is tested by comparing spherically symmetric wind simulations and long-term simulations of NSMs using RHINE with post-processing results from nucleosynthesis calculat